",isbn:"978-1-80355-607-9",printIsbn:"978-1-80355-606-2",pdfIsbn:"978-1-80355-608-6",doi:null,price:0,priceEur:0,priceUsd:0,slug:null,numberOfPages:0,isOpenForSubmission:!0,isSalesforceBook:!1,isNomenclature:!1,hash:"6cf0b844f6881c758c61cca10dc8b134",bookSignature:"Associate Prof. Gülşen Akın Evingür and Dr. Önder Pekcan",publishedDate:null,coverURL:"https://cdn.intechopen.com/books/images_new/11830.jpg",keywords:"Elasticity, Toughness, Modulus, Compression, Extension, Optical Properties, Swelling, Drying, Diffusion, Release, Transmission Loss, Sound Absorption Coefficient",numberOfDownloads:null,numberOfWosCitations:0,numberOfCrossrefCitations:null,numberOfDimensionsCitations:null,numberOfTotalCitations:null,isAvailableForWebshopOrdering:!0,dateEndFirstStepPublish:"April 5th 2022",dateEndSecondStepPublish:"June 15th 2022",dateEndThirdStepPublish:"August 14th 2022",dateEndFourthStepPublish:"November 2nd 2022",dateEndFifthStepPublish:"January 1st 2023",dateConfirmationOfParticipation:null,remainingDaysToSecondStep:"20 days",secondStepPassed:!0,areRegistrationsClosed:!1,currentStepOfPublishingProcess:3,editedByType:null,kuFlag:!1,biosketch:"Dr. Evingür is a researcher in polymer composites and a lecturer at a maritime university. She has edited 2 books and has had 5 chapters published in international books, and 3 international and 5 national projects, respectively.",coeditorOneBiosketch:"Prof. Pekcan received their Ph.D. from the University of Wyoming, United States of America, in 1974. He has more than 362 SCI articles, 26 chapters, and 10 projects and is a member Science Academy in Turkey.",coeditorTwoBiosketch:null,coeditorThreeBiosketch:null,coeditorFourBiosketch:null,coeditorFiveBiosketch:null,editors:[{id:"180256",title:"Associate Prof.",name:"Gülşen",middleName:null,surname:"Akın Evingür",slug:"gulsen-akin-evingur",fullName:"Gülşen Akın Evingür",profilePictureURL:"https://mts.intechopen.com/storage/users/180256/images/system/180256.jpeg",biography:"Gülşen Akın Evingür graduated from Physics Department at the Yıldız Technical University (YTU, İstanbul, Turkey) in 1996. She completed her Master of Science degree in 2002 at the same department. The titled of her thesis was 'Electrical Properties of Polystyrene”. She received her PhD from Physics Engineering at İstanbul Technical University in 2011. The title of the thesis was 'Phase Transitions in Composite Gels”. She worked as an Assistant Professor between 2011 and 2018, and she is currently working as an Assosciate Professor at Pîrî Reis University, Istanbul, Turkey. She has been engaged in various academic studies in the fields of composites and their mechanical, optical, electrical, and acoustic properties. She has authored more than 60 SCI articles, 92 proceedings in national and international journals, respectively. 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He became Associate Professor at Hacettepe University in 1979. \nHe visited ICTP Trieste, Italy as Visiting Scientist between June and August 1980. Between 1980 and 1981 he was a Visiting Scientist at the Technical University of Gdansk, Poland. \nHe worked as Visiting Professor at the Department of Chemistry, University of Toronto, Canada between 1981 and 1988. \nHe was appointed as full Professor at the Department of Physics, Istanbul Technical University, Turkey and worked there between 1988 and 2005. \nHe became an Elected Member of the Turkish Academy of Sciences (TÜBA) in January 1995. \nHe became the Dean of School of Arts and Sciences at the Istanbul Technical University in 1997. \nHe received the Science Award from the Scientific and Technological Research Council of Turkey (TÜBİTAK) in 1998. Prof. Pekcan was elected as Member of the Council of TÜBA in 2001 and Scientific Board of TÜBİTAK in 2003, respectively. \nHe was Head of the Department of Physics, and then became Dean of School of Arts and Sciences at the Işık University between 2005 and 2008.\nHe worked as Dean at the School of Art and Sciences, Kadir Has University (2008—2012). \nNow he is Professor at the Department of Bioinformatics and Genetics, Kadir Has University. Since 2012 he is a member of Science Academy. In the last few years Prof. Pekcan’s work covers mostly the area of biopolymers and nanocomposites.",institutionString:"Kadir Has University",position:null,outsideEditionCount:0,totalCites:0,totalAuthoredChapters:"2",totalChapterViews:"0",totalEditedBooks:"0",institution:{name:"Kadir Has University",institutionURL:null,country:{name:"Turkey"}}},coeditorTwo:null,coeditorThree:null,coeditorFour:null,coeditorFive:null,topics:[{id:"14",title:"Materials Science",slug:"materials-science"}],chapters:null,productType:{id:"1",title:"Edited Volume",chapterContentType:"chapter",authoredCaption:"Edited by"},personalPublishingAssistant:{id:"185543",firstName:"Maja",lastName:"Bozicevic",middleName:null,title:"Mrs.",imageUrl:"https://mts.intechopen.com/storage/users/185543/images/4748_n.jpeg",email:"maja.b@intechopen.com",biography:"As an Author Service Manager my responsibilities include monitoring and facilitating all publishing activities for authors and editors. 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1. Introduction
Novel findings on the immune-regulatory processes and metabolic mechanisms may open new avenues in the complex diseases as well as obesity; research on basic and clinical advances in immunometabolism has evolved rapidly during the past years, and the emergence of new tools for the detection and characterization of regulation of inflammation in systemic inflammatory diseases with metabolic comorbidity may play an imperative role.
Interplay in regulation of inflammation and metabolic risk factors are a complex cluster. The inflammatory condition associated with adipose tissue represents a triggering factor in the etiology of the obesity pathological-mechanism and mainly contributes to the related disease outcomes.
The purpose of this chapter is to address recent findings in metabolic, molecular biology, function, and pathology of the immune response to inflammation on the role of the immunometabolism in obesity. That containing significant new findings in the field, presenting the state of the art findings, will offer the new insights into interplay in the regulation of inflammation, especially in the tools of the comorbidity, in order to know their mechanisms by metabolic and immune response that cause disease.
2. Healthy adipose tissue
2.1 Morphology and cellular biology
Adipose tissue (AT) is a type of specialized connective tissue, and as such, it consists of two main components: a cellular population and a specialized extracellular matrix (ECM) [1].
The cellular population is integrated not only by adipocytes (the main cell type, by which receives its name) but also by preadipocytes, mesenchymal stem cells (MSCs), fibroblasts, endothelial and smooth muscle cells of blood vessels and any immune system cell, and adipose tissue macrophages (ATMs) with relevance [2, 3].
Its ECM, as any other, is composed of a wide type of collagens (fibrillar (I and III) and nonfibrillar (IV, VI, and VIII)), laminins, fibronectin, and proteoglycans; especially the external membrane contains a large complex of collagen IV and VIII as well as heparan sulfate proteoglycans and laminins [4]. AT ECM possesses the highest collagen VI concentration compared to any other body tissue [5, 6]. Altogether, the ECM and the non-adipocyte cellular population receive the name of stromal-vascular fraction (SVF) [7].
2.1.1 Classification
Histologically, AT is classified according to adipocyte microscopic characteristics as white (WAT), brown (BAT), and beige. White adipocytes are big oval cells with a single lipid droplet that fills the whole cytoplasm, displacing the nucleus and other organelles through periphery; its main function is the storage of energy in the form of triglycerides (TG) and lipolysis. Brown adipocytes are oval cells with multilocular lipid droplets uniformly distributed over the cytoplasm and have a high number of mitochondria, each one with several cristae expressing uncoupling protein 1 (UCP-1), characteristics that reflect an important thermogenic property. Beige adipocytes are cells with brown phenotype within WAT, that is why they are also called brite (brown-in-white) adipocytes; under basal conditions they express low quantity of UCP-1 but can overexpress it upon β-adrenergic simulation and thus acquire thermogenic function [8, 9, 10].
Moreover, adipose tissue has an important endocrine function, as it is capable to secrete own specific hormones called adipokines [11].
2.1.2 Fat depots
In humans WAT constitutes close to 5–10% of total human body weight and is located in two main compartments: intra-abdominal, named visceral AT (VAT), and subcutaneous AT (SCAT), also called hypodermis. VAT coats internal organs and protects them from mechanical friction and damage and can be divided into omental, mesenteric, retroperitoneal, gonadal and pericardial; SCAT is designated according to its superficial or deep situation regarding to the fascia superficialis as lamellar or areolar [12]. Moreover, abdominal and gluteofemoral regions are more relevant regarding of functional properties [13, 14].
It is remarkable to note that gender-related differences in distribution and quantity exist. While women have more SCAT (especially in gluteofemoral and peripheral regions), men have more VAT because SCAT has higher levels of estrogen and progesterone receptors, while VAT has more androgen receptors [15, 16].
In rodents, the main SCAT pads are anterior, from the neck to the axillae running through the interscapular area, and posterior, from the dorsolumbar to the gluteal region running through the inguinal region. Also, the striated muscle called panniculus carnosus clearly separates two layers of WAT depots: one directly underlying the reticular dermis and SCAT as such [17]; the former compartment is designated as dermal WAT (DWAT), composed primarily by intradermal adipocytes. These two terms were proposed as a redefinition of the nomenclature of skin-associated adipocytes, as it more accurately reflects their immediate developmental origin and anatomical location; humans, although not having a panniculus carnosus, possess functional and morphological distinctions between DWAT and SCAT [18, 19].
Differentiation, lipolytic and endocrine activity, and leucocyte population differ between VAT and SCAT, conferring them distinct metabolic properties and, in case of VAT, attribution of metabolic disturbances like dyslipidemia, glucose intolerance, and insulin resistance (IR) [20].
2.2 Immunometabolism
As an interdisciplinary field, immunometabolism emerged from discoveries of interdependent functions and mechanisms between the immune system and parenchymal cells of metabolic organs, which confer adaptive processes in homeostasis or disease at cellular, tissue, and systemic level [21, 22]. AT is the most studied in this field.
2.2.1 Immune response
Immune system has an important role on the control of AT homeostatic state, where its main functions are keeping an anti-inflammatory environment and remodeling of the extracellular matrix [8].
Under physiologic state, AT leucocyte population is integrated by eosinophils, mast cells, group 2 innate lymphoid cells (ILC2), invariant natural killer T cells (iNKT), regulatory T lymphocytes (Treg), and, of particular interest, adipose tissue macrophages (ATMs). It is proposed that these immune cells contribute to the maintenance of AT integrity through secretion of cytokines such as IL-4, IL-5, IL-13, and IL-10 (a Th2-type immune response) and that under hypercaloric state, macrophage accumulation may be a protective mechanism of the body to cope metabolic disturbances [23].
IL-33 produced by endothelial stromal cells has a key role in homeostatic maintenance and function of ECM. It is ligand of ST2 receptor, which is expressed in mast cells, Treg, eosinophils, ILC2s, and iNKT cells, practically the whole resident leucocyte population [24, 25].
In vitro and in vivo studies have demonstrated important effects of IL-33: production of IL-5 and IL-13 by Th2 lymphocytes and macrophages, eosinophil IL-4 production and survival, as well as ILC2s survival and expansion, the latter similar for Tregs [26]. iNKT cells express the transcriptional factor E4BP4; in adipose tissue produce anti-inflammatory cytokines, such as IL-2, IL-4, and IL-10; and participate in control of the homeostasis of Treg cells and macrophages in this tissue [27].
IL-25 promotes lipid metabolism and energy production, improves mitochondrial respiratory capacity, and alleviates lipid accumulation in the liver and AT via M2 macrophages and its interaction with adipocytes.
As we can observe, AT leucocytes produce the Th2-type cytokines, profile that favors the maintenance of ATMs in an anti-inflammatory M2 phenotype, known for the expression of arginase-1 (Arg-1, which inhibits iNOS activity) and production of IL-10 and IL-1Ra. ATMs also play an important lipid “buffering” activity, as they engulf free fatty acids (FFA) coming from adipocytes that have surpassed their lipid storage capacity and unchain lipolysis. Moreover, ATMs engulf death adipocytes that have reached a critical death size (CDS) [28] by a process named efferocytosis [29].
Thus, ATM is the fundamental leucocyte for correct AT functionality, as it engulfs apoptotic cell debris, and, FFA released whether by lipolysis or adipocyte death, promotes ECM reconstruction [30] and provides ECM components as scaffolds for its remodeling in the same way as under wound healing process; all these mechanisms promote adipogenesis and hyperplastic AT expansion. It is worth noting that these beneficial functions take place only under an anti-inflammatory M2 phenotype (Figure 1).
The ECM of any specialized connective tissue is essential not only for mechanic and structural sustain but also for providing a network that permits inter- and extracellular communication that enables proper growth and differentiation [1]. AT ECM is no exception, and its remodeling is regulated by resident leucocytes and own adipocytes.
WAT can undergo remodeling in response to changes in energy balance, like ECM degradation by members of the matrix metalloproteinase (MMP) family during adipocyte enlargement (hypertrophy) and allowing expansion by adipogenesis, under a positive energy balance [31, 32]; on the other hand, MMP activity counterregulation is mediated by their tissue inhibitors (TIMPs). The balance between MMPs and TIMPs is critical for ECM integrity and function, and alterations in this proteolysis balance may contribute to many pathological states [33].
Secreted protein, acidic, and rich in cysteine complex (SPARC)/osteonectin and its C and N isoforms contribute to AT ECM remodeling; they modulate cell-ECM contact, cell-cell interaction, ECM deposition, and adipose stem cells (ASCs) migration and posterior incorporation into expanding neovasculature accompanying WAT growth [34]. A study showed that serum concentrations of SPARC and MMP-2 after bariatric surgery decreased, SMAC correlated with HOMA-IR, and MMP-9 inversely correlated with serum adiponectin levels [35].
Regarding vasculature, AT ECM remodeling is influenced by a variety of angiogenic molecules, and it is triggered by transient hypoxia as a result of enlarged adipocytes under a positive energy balance. Hypoxia stimulates the production of angiogenic factors to compensate low perfusion rate; vascular endothelial growth factor (VEGF) is known as a master regulator of angiogenesis and plays crucial roles in the neovascular development of AT with obesity [36]. Hypoxia-inducible factor-1α (HIF-1α) binds to the proximal hypoxia response element in the VEGF gene promoter [37]; nevertheless, it also has a role in regulation of ECM remodeling, as overexpression of a constitutively active form of HIF-1α in adipose tissue forced the expression of pro-fibrotic genes, including Col I and III, elastin, lysyl oxidase, and Timp1 [38].
This shows that detrimental ECM component deposition occurs under chronic hypoxic conditions. Transforming growth factor beta (TGFβ) and tumor necrosis factor-α (TNF-α) are released under acute hypoxia state and act as proangiogenic factors [39, 40], and the latter activates expression of preadipocyte genes in 3T3-L1 adipocytes [41]. This is in contrast to the belief that AT inflammation exerts a fundamentally negative impact on metabolism, postulating the concept “healthy inflammation” under overnutrition, requiring an acute local inflammation in order to prevent lipotoxicity and ectopic lipid accumulation; in this regard, a report showed the analysis of three animal models with constitutive or inducible expression of anti-inflammatory factors and revealed their inability to expand AT, leading to ectopic lipid deposition and deteriorated metabolic profile [42].
Platelet-derived growing factor B (PDGF-B), usually produced by endothelial cells, activates an intracellular signaling cascade binding to its receptor (PDGFRβ) and promotes pericyte detachment and migration around new-forming vessels for maturation, playing key roles in vascular development and wound healing in adults via angiogenic actions [43]. Surprisingly, Onogi Y. and colleagues found that M1 macrophages were a major type of cells expressing PDGF-B in obese adipose tissue and correlated with elevated pericyte detachment in a dose-dependent manner; in contrast, inducible knockout pdgfrb mice presented reduced M1 macrophages and CLS formation but increased M2 macrophages. Additionally, they were protected from body weight gain, accumulation of SCAT, VAT, and ectopic fat in muscle and liver and showed improved whole-body glucose metabolism under high-fat diet (HFD) condition. The expression of hypoxic and proinflammatory factors (Hif1a, Emr1, Itgax, Mrc1, Tnfa, and Ccl2) was significantly increased by HFD feeding mice, whereas the increasing effects were attenuated in HFD-fed PDGFRB-KO mice [44]. Also, increased adipogenic capacity of PDGFRβ+ precursors through PPARG overexpression in pericytes resulted in healthy VAT expansion in obesity and adiponectin-dependent improvements in glucose homeostasis, in contrast with knockout PPARG counterparts; moreover, the ability of the thiazolidinedione (TZD) class of antidiabetic drugs to promote healthy visceral WAT remodeling is dependent on mural cell PPARG [45].
An experimental in vivo study consisting of brown adipogenesis by β3-adrenergic receptor (ADRB3) activation caused crown-like structures (CLSs) formation: white adipocyte death recruited M2-polarized macrophages with high expression of osteopontin (OPN), which in turn attracted a subpopulation of PDGFRα+ CD44+ (OPN receptor) progenitors that underwent adipogenesis, in contrast with knockout OPN [46]. It is important to highlight that recruited M2 macrophages also showed upregulation of Arg1 and Il10 without significant changes in proinflammatory markers, indicating that ADRB3-mediated adipogenesis involves recruitment of macrophages that mediate non-inflammatory tissue repair [47]. Another study combining experiments in mouse models and human conditions reported that PDGFRα + CD9high cells originate pro-fibrotic cells, while their CD9low counterparts harbored pro-adipogenic potential; frequency of PDGFRα + CD9high in omental WAT (oWAT) correlated not only to oWAT fibrosis level but also to the severity of insulin resistance and T2D [48].
Adipokines can also help regulate angiogenesis, a sustained and progressive increase in leptin resulting from hypoxic conditions could induce VEGF and receptor (VEGFR2) expression, activate sirtuin 1 (SIRT1), and subsequent HIF-2α stabilization promoting its activity [49].
2.2.3 Glucose and lipid metabolism
A steady and continuous energy supply is necessary for all cells’ survival; the production of the principal high-energy molecule, the adenosine triphosphate (ATP), is primarily obtained by the metabolism of such molecules as glucose and fatty acids. In the case of carbohydrates, these are the main source of energy in almost every living organism, from archaea to humans. It is not only the supply of these molecules, but also the intricate mechanism of regulation of pathways that control the consumption and storage of these biomolecules.
For example, after a meal, or what is called a post absorptive state, there is an increment of plasmatic glucose concentration which results in the secretion of hormones such as insulin by the pancreas; this contributes to the regulation of glucose metabolism as well, and the physiological response varies on every tissue, as can been seen in muscle and liver, where insulin favors glycolysis and glycogenesis. Nevertheless, this hormone not only alters the carbohydrates metabolism, but also promotes cholesterol synthesis and lipogenesis (or TG synthesis) in hepatic and adipose tissues [50].
In the case of glycolysis, it represents the central path for glucose metabolism and provides multiple intermediate products. On aerobic conditions, it starts in the cytoplasm of the cell, with glucose as a substrate, which is partially oxidized by 10 enzymatic reactions, obtaining two pyruvate molecules, reducing equivalents such as NADH (nicotinamide adenine dinucleotide in reduced form) and a net production of 2 ATPs for each glucose [51].
Afterward, the pyruvate molecules will be transformed into acetyl-CoA and transported into the mitochondria to continue their oxidation in the tricarboxylate cycle to produce two CO2 molecules, three NADH and one FADH (flavin adenine dinucleotide in reduced form). The latter will transfer their electrons to the mitochondrial complexes of the electron respiratory chain; a series of redox transformation and the aid of molecular oxygen will finally converge in the synthesis of ATP by the ATP synthase complex.
Both ATP, NADH, and acetyl-CoA are metabolites that are shown to be thermodynamically favorable and are indicated as the protagonists in cellular energy metabolism [52].
After glycogen, the body stores energy in the form of TG in adipose tissue; nevertheless, diverse types of lipids are required for the maintenance of cellular functions, not only for energetic ones, but also structural (such as phospholipids) or for the formation of specialized products like steroid hormones. These are obtained from diet, absorbed and subsequently transported by lipoproteins such as the very high-density lipoprotein (VLDL), low-density lipoprotein (LDL) and high-density lipoprotein (HDL), all of these ensembled by the liver. FFAs are a major source of acetyl-CoA molecules by β-oxidation, these molecules continue their oxidation in the tricarboxylate cycle and the electron respiratory chain, providing a significant amount of energy at the cellular level.
Due to the importance of these biomolecules, there is a narrow regulation that includes transcription factors such as sterol regulatory element-binding proteins (SREBPs) and hormonal control for an adequate function [53].
Although these regulatory mechanisms are recognized, the possible regulatory activity that miRNAs may have in lipid and cholesterol homeostasis has recently been suggested, particularly for miR-122 and miR-33 [54].
3. Adipose tissue and disease
3.1 Insulin resistance
3.1.1 Obesity as a trigger
Obesity is a disease of multifactorial origin with a worldwide increasing prevalence; it entails an injurious health status for individuals, which represents a serious public health issue. This condition is associated to diverse diseases and has a complex treatment, being the reason why it must be assessed in a multidisciplinary context by healthcare professionals.
It is defined as an abnormal or excessive fat accumulation that can be detrimental for health [55]. It originates from the interrelation of inadequate food intake and/or overfeeding, sedentary lifestyle, and psychological, genetic, and ambiental factors. The excessive adiposity status hinders the disease reversion because of the difficulty to perform physical activity and the metabolic and satiety dysregulation [56].
Obesity develops a diversity of somatic complications such as respiratory, mechanic, cardiovascular, and metabolic, as well as psychological and social, which make its assessment, prognosis, and intervention even more complicated. Diagnosis is preceded by an anthropometric evaluation, which correlates adiposity with a total body weight of individuals [57].
Progressive AT expansion in the organism, given by a positive energy balance from excessive macronutrients and calorie intake, entails an elevated number of circulating FFA that triggers a deregulation in the organism, from changes in body structure to changes at local and systemic levels [58]. This excessive AT induces a chronic inflammatory state, also named lipoinflammation, causing hypoxia of adipocytes [59]. AT hypoxia and inflammation correlate with the risk of developing insulin resistance (IR), type 2 diabetes (T2D), and cardiovascular disease (CVD).
When the organism is under positive energy balance, energy excess accumulates in AT, giving place to SCAT hyperplasia until a physiologic allowed limit as energy reservoir is reached. When energy excess prevails, it is now stored at VAT; unfortunately this depot does not possess a great capacity as SCAT, resulting in adipocyte hypertrophy and subsequent android, central, or visceral adiposity [60, 61].
Central obesity is highly associated with T2D and CVD. AT is the pathogenic site where obesity-induced local IR originates before being systemic; its secretory genetic expression profile of endocrine and paracrine bioactive substances reflects a generalized inflammatory local state, the reason why adipocyte is referred to as key to the onset and development of obesity-induced inflammation and to macrophages as amplifiers of this process [62].
As aforementioned, AT initially plays a role in energy reservoir but also has a significant function in metabolism and immune system. Resident ATMs are key in IR onset, as they produce proinflammatory molecules which can explain more than 50% of secretion of TNF-α, by the action of insulin on adipocytes and on peripheric organs of the body [63].
Other implicated adipokines are resistin and IL-6, which stimulate hormone-sensitive lipase (HSL) activity resulting in triglycerides cleavage and subsequent glycerol and FFA release; these high circulating FFA levels are the cause and consequence of IR and T2D [64].
We can broadly elucidate that adipocytes and ATMs synthesize proinflammatory molecules and that weight increase at the expense of AT will contribute in turn to the perpetuation of chronic inflammation by increasing the levels of circulating cytokines. Required actions to help reverse the IR process should be focused on establishing a healthy diet accompanied by exercise; these will help to reduce the proinflammatory state, while downregulation of TNF-α and IL-6 expression of adipocytes occur. Meanwhile, exercise by its own will enhance mitochondrial FFA metabolism, avoiding their storage [65].
Other factors involved in IR and inflammation are implicated by diet and related to gut microbiota, which in turn demonstrates how an excessive saturated fat consumption can drive an important bacterial lipopolysaccharide (LPS) production, which impacts on systemic inflammation [58].
Initial steps that launch the inflammatory response are less well elucidated. On experimental studies with HFD-induced obesity murine models, HIF-1α levels are observed before the onset of a significant adiposity status; under this situation, adipocyte hypoxia and HIF-1α act as early triggers of inflammation and IR [59].
3.1.2 Inflammatory pathway
Adipose tissue complex and diverse functions have implications in the whole body, and cytokines are involved in his physiologic response. In obesity condition the major cytokines expressed by AT are leptin, resistin, TNFα, chemerin, MCP-1 and IL-6 [66, 67]. On the other hand, the adipose cells are both hyperplastic and hypertrophic, and in this state induce the inflammatory process. Dysregulation of adipose tissue promotes incorrect remodeling and subsequent inflammation, according to recruitment of macrophages and expression of chemotactic cytokines like MCP-1, TNFα and chemerin, to mention some of them. The phenotype involved is the M1 pro-inflammatory and evidence shows that this situation is not only local, but also systemic and this promotes further inflammation explaining how obesity can be the etiologic cause of other diseases [68, 69].
In addition, it is well known that this mechanism promotes insulin resistance, which is the previous phase before the development of T2D. However, the adipocyte is in a very close communication with the macrophage making the inflammatory process redundant and more complex. Nevertheless, in lean adipose tissue, it is typically the opposite, meaning that macrophages differentiate into a M2 anti-inflammatory phenotype, releasing IL-10, TGFβ, IL-4, and other regulatory cytokines [70]. Otherwise other mechanisms that can promote the anti-inflammatory pathway, like the consumption of Omega 3 fatty acids, exist [71].
Taking it all together, obesity results from genetic, epigenetic, physiological, behavioral, molecular and environmental factors that lead the proinflammatory phenotype [72, 73].
3.1.3 Molecular mechanism
It is described that adipose cells derive from a stem cell that can differentiate into adipocytes, chondrocytes, osteoblasts, and myocytes [74].
In a first phase, adipoblasts can be addressed to the adipogenic lineage and become preadipocytes. If the stimuli in the tissue continue, these cells maturate to become mature adipose cells with lipid storage capacity [75].
There are two main transcription factors that are involved in the differentiation of the adipocyte, CCAAT/enhancer-binding protein α (C/EBP-α), and peroxisome proliferator-activated receptor γ (PPAR-γ). PPAR-γ is the most described transcriptional factor, and its expression is regulated by the co-factor PGC1α and the production of adiponectin [76, 77].
Transcription factors that belong to the C/EBP family also have a crucial play in the differentiation, and there are reports that this factor can be activating more early than PPAR-γ (Figure 2) [78].
Figure 2.
Adipose tissue differentiation and hyperplasia and hypertrophy consequences.
The dysfunction in the capacity of generating healthy adipose tissue has several metabolic consequences, like dyslipidemia, hypertension, and insulin resistance among others [79].
Many molecular mechanisms are involved since the adipocytes have different gene expression patterns, leading to the expression of different types of adipokines depending the phenotype induced in the tissue. Healthy expansion of adipocytes depends on the plasticity of the extracellular matrix, but in obesity there is a limiting in the oxygen diffusion, and it becomes hypoxic [80].
3.1.4 Role of adipokines and myokines
Skeletal muscle compounds 40% of total body weight in healthy individuals. The muscle is the major site for the insulin-stimulated glucose uptake and lipid metabolism, so it is an important part of metabolism maintenance [81].
Adipose tissue possesses more than 600 potentially secretory proteins, which means that more adipokines and myokines are still in line for discovery and characterization [82].
Additionally in adipokines there is a cross talk between these and myokines, which are synthetized by the muscle. Nevertheless, both tissues can express the same cytokines creating a regulation process with a strong communication. The most characterized cytokines are chemerin, TNFa, MCP-1 and IL-6. It is demonstrated that WAT deposits exist in skeletal muscle and facilitate communication, also, these tissues usually are in close anatomical proximity.
The knowledge of the most important characterized myokines is as follows:
IL-6: this increases in favor of the exercises, but it is recognized that it has a controversial role in the inflammatory or anti-inflammatory pathway.
Il-15: it mediates a beneficial effect on physical activity.
Irisin: it stimulates the development of brown adipose tissue activating MPK and ERK molecular ways, and it is regulated by the age and gender. This molecule has also a controversial role, because it has been reported to increase obesity.
Myonectin: it has a homology worth the sequence of adiponectin and promotes fatty acid uptaking in mice [82, 84, 85, 86].
Principally, the major role of the adipomyokines is contributing to metabolism, angiogenesis, blood vessel regulation, adipogenesis, myogenesis, and immune response [82]. On the other hand, it is important to remark the impact that macrophages have in metabolism, since they induce a response in both tissues. For example, when circulating monocytes respond to chemoattractant molecules, they migrate into adipose and muscle tissue, and then develop a phenotype depending on environmental necessities (Table 1) [94].
Finally, there is another terminology newly adopted by the scientist called organokines, because it has been suggested that all proteins secreted in various tissues or organs (liver, adipose tissue, muscle, and bone) have an intimate relationship in the context of the communication and regulation for the maintaining of homeostasis and that they are involved in a network of paracrine and endocrine cross talk [84].
3.1.5 Emerging role of microRNAs in obesity
In the context of complex diseases, obesity is the prototype of immuno-metabolic disease; it is considered a major factor that triggers metabolic risk and the development of secondary chronic illness2, insulin resistance (IR), and metabolic syndrome (MS). The susceptibility of a subject to develop obesity will depend on different factors such as the repertoire of individual variations in an ensemble of relevant genes, their history of exposure to environmental risk factors, and the interaction between the lifestyle and metabolism, which is also modulated by the gene regulators [95, 96, 97].
Meanwhile, obesity presents many subclinical manifestations, characterized by alterations in lipids and carbohydrate metabolism at different levels; most of these changes is due to a low-grade systemic chronic inflammation [98, 99] that favors the development of IR. Adipose tissue is the primary anatomical site where IR disease takes place; in early stage this tissue became inflamed.
Novel findings on the immune-regulatory processes and metabolic mechanisms may open new avenues in the treatment of the common complex diseases as well as inflammatory component; research on basic and clinical advances in immunometabolism has evolved rapidly during the past years, and the beginning of new tools for the detection and characterization of regulation of inflammation in metabolic diseases with comorbidity may play an imperative role; nevertheless, the precise mechanisms mediating this relationship remains poorly understood.
Interplay in the regulation of inflammation and metabolic risk factors are a complex cluster. The inflammatory condition associated with adipose tissue represents a triggering factor in the etiology of the obesity pathological mechanisms and mainly contributes to the related disease outcomes.
In the early stages of obesity, in white adipose tissue, primed immune cells are recruited as adiposity increases, and these cells became resident cells (mainly macrophages) and secrete proinflammatory adipokines that promote further recruitment of circulating monocytes [100, 101, 102, 103]. Later, they polarize toward M1 macrophages, favoring a subclinical chronic inflammatory state [102, 104, 105, 106] secondary to irregular increase and distribution of fat depots [107]. In IR, the expression of genes implicated in glucose and lipid absorption and metabolism in liver and adipose tissue is dysregulated, at the same time, insulin signaling pathway in peripheral tissues is also disturbed [108]; this IR scenario precedes the development of T2D and other related diseases.
The identification of diverse molecular mechanisms related to energy metabolism has allowed the definition of strategies for searching genes implied in obesity and IR.
In the decade that precedes us, experimental reports show the existence of small noncoding RNAs, which are identified as microRNAs, (miRs) with the function of regulating cellular processes through modulating the expression of genes that code for functional proteins.
The insulin signaling pathways may be regulated by microRNAs (miRNA) that modulate the stability and translation of messenger RNAs (mRNA) by a particular mechanism of binding seeding sequences located in target genes, resulting in protein decay [109, 110].
Once synthesized, some miRNA can be released into circulation via exosomes, vesicular bodies, lipoproteins, simple extrusion, or apoptotic bodies. Most researches in the field have assessed the presence of circulating miRNA in many body fluids, being related to their impaired expression in tissues under physiological and pathological conditions. Several studies have shown a correlation of particular circulating miRNA with the development of different pathologies, positioning them as valuable biomarkers in silent diseases such as obesity, IR, and MS [111, 112].
Although rapid progress is being made in research on miRs, there is little availability of experimental tools with scientific value and mechanisms that lead from the discoveries of miRs to the therapeutic application in diseases. Therefore, the current demand is to explore the expression and biological function of miRs in the development of diseases in vivo.
The main considerations that are known are that the process of its biogenesis is governed by regulatory checkpoints, based on the fact that the sequence of the primary transcript does not correspond linearly to mature miR. The abundance or scarcity of a miR indicates its level of regulation.
Under physiological conditions, it has been shown that miRs modulate gene expression; however pathological stress increases or decreases its function. Therefore, its function will be defined by the effect on the expression of the genes to which it is directed. Predictions indicate that 60% of target mRNA genes have similar binding sequences in the 3′UTR region for single or multiple miRs. These miRs exert their silencing function through two different mechanisms: translation inhibition (initiation or elongation) and target mRNA degradation. In the target genes for miRs, it is observed that 3′UTR regions have binding sites for multiple miRs; this suggests cooperation and redundancy of the effect on gene expression between the different miRs.
Currently, there are 1917 human miRNAs listed in the miRNA database miRBase (http://www.mirbase.org), representing 1% of all genes in the human genome. These miRNAs are predicted to target aprox. 30% of the human gene pool.
From the extraction of plasma and blood serum miRs from human and mammalian animal samples, they have been proposed as diagnostic biomarkers in the diseases. The attributes that stand out are that the miRs extracted from the serum have stability, and the results in the quantification are reproducible and consistent among individuals of the same species.
The logical sequence in the integral investigation of miRs is firstly to identify the presence in a given sample. The experimental tools used to measure the expression profile of miRs have been by microarray analysis or deep sequencing, while the determination of the level of expression of individual miRs has been performed by RT-PCR, in situ hybridization or northern blot.
However, the investigations carried out can be categorized from two conceptual points, the determination of the level of expression in which the most used methodological tool is real-time PCR analysis and global expression assays. The former stand out for their specificity while confirming the latter, while the latter provide a broad view of the presence and regulation of miRs.
Properly identifying the functionality and level of expression of a specific miR is limited due to the high degree of sequence homology between some miRs and the size of the molecule; the parallel application of different molecular tools strengthens the identification or quantification process of the level of expression. However, an unfavorable factor is the combined regulation of multiple genes or small changes in gene regulation that are lost in biological noise.
Enhancing the work of performing research surrounding these novel gene regulators will advance our understanding of miRNAs and their specific functions and will augment the opportunities to safely follow them as therapeutic targets [113].
3.2 IR in muscle and liver
Conventionally, insulin acts directly on the WAT under the cascade of the IRS1 axis, PI3K, and AKT, for glucose absorption, with a possible positive feedback of the phosphorylation of Ser388 from IRS2, by cyclin-dependent kinase 4 (CDK4) [114], culminating with lipolysis regulation. However, as described in previous sections of the chapter, inflammatory processes and alternative activation of macrophages favor the pathogenic adiposity in which the action of insulin is not carried out correctly and therefore does not slow the lipolysis process.
Although the mechanism of signaling pathways that links pathogenic adiposity to insulin resistance in skeletal muscle and liver has not been well defined due to the difficulty of modeling in vitro systems that allow cell coordination as in a complex organism, the process of understanding molecular bases has lagged behind the direct action of insulin in an organ or cell. The best way to associate it is the chronic surplus of energy that favors the accumulation of ectopic lipids in the liver and skeletal muscle that trigger the activation of pathways that impair insulin signaling, causing the decrease in glucose absorption in muscle cells and of glycogenesis in liver [115].
3.2.1 Liver
In a physiological stage with food withdrawal, the main source of glucose in the bloodstream is the liver. On the other hand, after absorption of nutrients by the intestine, the production of hepatic glucose should be interrupted in coordination with hyperinsulinemia.
The most assertive explanations of how insulin acts to promote glucose homeostasis by inhibiting both glycogenolysis and hepatic gluconeogenesis have focused on the canonical pathway of insulin interacting directly in the liver by activating the insulin receptor (InsR) and the substrate of insulin receptor (IRS) and the phosphoinositol 3-kinase signaling cascade (PI3K/Akt/mTOR pathway) by inhibiting transcription of the forkhead box class O-1FOXO1 factor and thus gene transcription and activation of gluconeogenic enzymes such as phosphoenolpyruvate carboxykinase (PCK1) and glucose 6 phosphatase (G6PC) [116, 117].
However, it has been observed that suppression of hepatic glucose production is not totally dependent on the Akt activation pathway, for which remote insulin actions that interact indirectly with the physiological process of hepatic glucose have been studied. On one hand, the reduction of PCK1 and glucose 6-phosphatase (G6Pase) through cerebral insulin action activates the ATP-sensitive potassium channels (KATP) of hypothalamus and stimulate the vagal transmission and STAT3 activation [118, 119], blocking the de novo glucose formation by the liver and therefore regulating serum hyperglycemia.
On the other hand, insulin action in WAT suppresses lipolysis and reduces the fatty acids flow into the liver, therefore, reduction of both acetyl-CoA concentration and pyruvate-to-glucose conversion occur, corresponding with the cessation of glycerol supply, observing a decrease in pyruvate carboxylase (PC) enzyme activity [120].
However, when WAT is in an inflammatory process and insulin resistance, it constantly increases the supply of gluconeogenic substrates, such as non-esterified fatty acids (NEFAS), and glycerol favors hepatic glucose production [121]. In stages with normal insulin levels, fatty acids in the bloodstream compete with glucose to internalize cells independent of hyperglycemia; however when insulin concentration or activity is deficient, fatty acids contribute directly to the production of glucose [122]. The ectopic accumulation of fatty acids in liver increases the content of acetyl-CoA allosterically activating PC and increasing gluconeogenesis; this increase in glucose and the presence of pro-inflammatory cytokines lead to inadequate insulin signaling in liver and subsequently, IR [123].
According to current knowledge of the importance of indirect insulin pathways in the liver to maintain the homeostatic glucose process, research groups will follow some therapeutic targets associated with the signaling pathways of G-protein-coupled receptors (GPCRs) [124] as well as inhibitors of the enzyme acetyl-CoA carboxylase [125, 126] for the treatment of metabolic diseases. Similarly there is evidence that proves that the diet with low calorie concentrations can reverse hyperglycemia [127].
3.2.2 Muscle
The skeletal muscle is responsible for 70% of the elimination of total body glucose, associated with its capacity and energy need. Therefore, insulin sensitivity of skeletal muscle is critically important in maintaining homeostasis of blood glucose [128].
Many studies propose molecules related to the deterioration in insulin signaling; however, they agree that these molecules accumulate when the energy supply exceeds the demand in the body. Therefore, it suggests that the IR in the muscle not only has intrinsic problems as a reference. One of the main mechanisms proposed to elucidate the pathogenic process of IR in skeletal muscle is mitochondrial compromise due to the bioenergetic imbalance present mainly in pathological adiposity. However, the molecular pathways to describe this event are not entirely elucidated.
In the physiological process of insulin/IR interaction in skeletal muscle, you can activate two signaling pathways with the phosphorylation of IRS1 and, on the one hand, the PI3K/AKT pathway that induces glycogen synthesis and glucose uptake by recruiting the transporter protein of glucose (GLUT-4) to the plasma membrane, while the activation of the MAPK pathway favors the growth and differentiation of skeletal muscle [129].
The presence of pathological adiposity provides high concentrations of fatty acids and cytokines that activate signaling pathways linked to obesity that converge with insulin signaling. As plasma FFA increase, they accumulate in muscle. Intramuscular diacylglycerol (DAG) and ceramides levels rise, compounds that might act as second messengers in alternative signaling pathways that interfere with IRS-1 adequate phosphorylation [108, 130].
The presence of TAG and DG in muscle activates Ser307 phosphorylation in IRS-1, resulting in the activation of PKC-θ. These changes in turn result in a decrease in the tyrosine phosphorylation of IRS-1 and a lower activation of the PI3K associated with IRS-1, resulting in a decrease in insulin-stimulated glucose transport activity. Intramolecular lipids (IMCL) have been observed to be elevated when lipid oxidation is poor and lipid supply to the muscle is exceeded [120, 131, 132].
The bioenergetic imbalance favors mitochondrial beta oxidation, although incompletely which can increase the concentration of reactive oxygen species (ROS) mainly H2O2, this reactive species is responsible for the inhibition of PP2A causing the activation of JNK and ERK, and these inhibit serine phosphorylation in IRS1. When the energy demand is exceeded, skeletal muscle mitochondria stimulate lipid biosynthesis that redundantly increases the concentration of ROS and myocellular lipids [133, 134, 135].
Although the process by which ROS and fatty acids trigger insulin resistance is not yet elucidated, it can be deduced that energy imbalance is the fundamental key.
4. A new terminology: pathologic adiposity
Total adipose mass, fat depot location, and particular AT type function are the predominant factors that explain high metabolic risk in individuals with obesity, since number, distribution, and leucocyte population differ between SCAT and VAT from lean and obese individuals; VAT has higher a macrophage number, and adipocyte size is smaller and has less lipid storage capacity. These differences suggest VAT can undergo subclinical inflammation and metabolic disease [136]; actually, central obesity associates with higher CVD, metabolic disorders, and early death, in contrast with gynecoid obesity at the expense of SCAT accumulation in the gluteofemoral region [13].
With the aforementioned, we can state that not every obese individual is affected by the common metabolic abnormalities associated with obesity. Approximately 10–25% of obese and a smaller fraction of morbidly obese persons are “metabolically healthy” (metabolically healthy obese, MHO), as they are insulin sensitive and normotensive and possess a favorable lipid profile; furthermore, they present less VAT and hepatic lipids and possess normal glucose metabolism. On the other hand, a subgroup of normal weight individuals suffers obesity characteristic metabolic abnormalities, whereby they are denominated as “metabolically healthy but with normal weight” (MONW). It is suggested that MHO individuals own a less detrimental metabolic profile and better prognosis compared to normal weight individuals with metabolic syndrome [137, 138, 139].
As stated before in this chapter, under acute caloric excess, enlarged adipocytes suffer hypoperfusion and mechanic stress owing to its surrounding ECM, which causes transient hypoxia and triggers angiogenesis and release of stress signals so that AT could undergo healthy remodeling and maintenance [140].
Nonetheless, obesity is a chronic caloric excess state, which means adipocyte enlargement surpasses angiogenesis, whereby hypoxia and stress signals perpetuate and cause fibrosis and cell death with eventual necrosis; this scenario causes local lipotoxicity, as ATM lipid buffering function is surpassed by the increased FFAs levels caused by overfeeding or adipocyte lipolysis and death [141, 142]. Thus, ATMs undergo metabolic activation, as lipids like palmitate are TLR-2/4 ligands, therefore initiating a proinflammatory response and polarization towards a M1 phenotype, losing all pro-homeostatic functions that we have previously discussed [143, 144, 145]. Furthermore, the other resident leucocytes will change in number and function as ATMs did, towards a Th1-type immune response.
The activation of NF-kB pathway with cytokine/chemokine release and the contribution of harmful metabolites (i.e., ceramide and sphingosine 1-phosphate, S1P) interfere with proper insulin signaling, therefore establishing a local AT IR [146, 147, 148].
After the AT IR is established, non-suppressive lipolysis now perpetuates and triggers high circulating FFA levels giving place to peripheral/systemic lipotoxicity: ectopic fat accumulation in liver and muscle; additionally, the proinflammatory cytokine, adipokine, and chemokine profile will circulate through the bloodstream, establishing metainflammation. Eventually, the high ectopic lipid concentration in this tissues will unleash similar detrimental effects that took place at AT, establishing now peripheral/systemic IR and dyslipidemia [132, 149].
The ensemble of this AT dysfunction and its harmful metabolic clinical repercussions is what we call pathologic adiposity: the adiposity status that determinates metabolic systemic dysfunction (IR and dyslipidemia), whether in an obese or normal weight individual, “metabolically unhealthy obese” (MUO), or “metabolically obese normal weight” (MONW) person, respectively (Figure 3).
Figure 3.
A series of unfortunate events that leads to a pathologic adiposity status.
5. Conclusions
Metainflammation can be defined as the systemic metabolic inflammation derived from obese adipose tissue in which innate and adaptive immune system cells have changed in number and function, from a lean and homeostatic to a proinflammatory state, and whose cytokine and adipokine proinflammatory profiles cause metabolic syndrome. Some authors consider metainflammation as the result of dysfunctional adipose tissue that consists of unhealthy expansion (hypertrophy) and angiogenesis, hypoxia, and detrimental ECM remodeling, which in turn limit adipocyte lipid storage capacity; altogether, these deleterious scenarios cause lipolysis and ectopic fat accumulation in the liver and muscle.
The knowledge developed in recent years in relation to the homeostatic interaction between immune system and the energetic metabolism along with the role of miRs allows that in a state in imbalance such as obesity, new biomarkers that show clinical information about the state are sought health of individuals and the early detection of the risk of developing metabolic complications is derived from the state of pathological adiposity.
Conflict of interest
The authors declare no conflict of interest.
Acronyms and abbreviations
ADRB3
β3-adrenergic receptor
AKT
protein kinase B
ASCs
adipose stem cells
AT
adipose tissue
ATMs
adipose tissue macrophages
ATP
adenosine triphosphate
BAT
brown adipose tissue
C/EBP-α
CCAAT/enhancer-binding protein α
CDK4
cyclin-dependent kinase 4
CDS
critical death size
CVD
cardiovascular disease
DWAT
dermal WAT
ECM
extracellular matrix
ERK
extracellular signal-regulated kinase-1
FADH
flavin adenine dinucleotide in reduced form
FFA
free fatty acids
FGF21
fibroblast growth factor 21
FOXO1
forkhead box class O-1
Fstl 1
follistatin-related protein 1
G6PaseC
glucose 6 phosphatase
GLUT
transporter protein of glucose
HDL
high-density lipoproteins
HFD
high-fat diet
HIF-1α
hypoxia-inducible factor-1α
HSL
hormone sensitive lipase
IL
interleukin
ILC2
group 2 innate lymphoid cells
IMCL
intramolecular lipids
iNKT
invariant natural killer T cells
IR
insulin resistance
IRS1
substrate of insulin receptor 1
IRS2
substrate of insulin receptor 2
KATP
ATP-sensitive potassium channels
LDL
low-density lipoprotein
LPS
lipopolysaccharide
MCP-1
monocyte chemoattractant protein-1
miRs
microRNAs
MPK
mitogen-activated protein kinase
mRNA
messenger RNAs
MS
metabolic syndrome
MSCs
mesenchymal stem cells
NADH
nicotinamide adenine dinucleotide in reduced form
NEFAS
non-esterified fatty acids
OPN
osteopontin
PAI-1
plasminogen activator inhibitor-1
PCK1
phosphoenolpyruvate carboxy kinase
PC
pyruvate carboxylase
PDGF
platelet-derived growth factor
PDGFR
platelet-derived growth factor receptor
PEDF
pigment epithelium-derived factor
PI3K
phosphoinositide 3-kinases
PPAR-γ
peroxisome proliferator-activated receptor γ
RT-PCR
real-time polymerase chain reaction
SCAT
subcutaneous adipose tissue
SIRT 1
sirtuin 1
SPARC
secreted protein, acidic, and rich in cysteine complex
SREBPs
sterol regulatory element-binding proteins
STAT3
signal transducer and activator of transcription 3
SVF
stromal-vascular fraction
S1P
sphingosine-1-phosphate
TZD
thiazolidinediones
TIMP
tissue inhibitor of matrix metalloproteinases
T2D
type 2 diabetes
TG
triglycerides
TGFβ
transforming growth factor beta
TNFα
tumor necrosis factor alpha
Treg
regulatory T lymphocytes
UCP-1
uncoupling protein 1
VAT
visceral adipose tissue
VLDL
very-low-density lipoprotein
WAT
white adipose tissue
\n',keywords:"obesity, adipose tissue, adipose tissue macrophages-M1 phenotype, exosomes, microRNAs, insulin resistance, pathologic adiposity",chapterPDFUrl:"https://cdn.intechopen.com/pdfs/70627.pdf",chapterXML:"https://mts.intechopen.com/source/xml/70627.xml",downloadPdfUrl:"/chapter/pdf-download/70627",previewPdfUrl:"/chapter/pdf-preview/70627",totalDownloads:1058,totalViews:0,totalCrossrefCites:3,totalDimensionsCites:3,totalAltmetricsMentions:0,impactScore:2,impactScorePercentile:81,impactScoreQuartile:4,hasAltmetrics:0,dateSubmitted:"September 4th 2019",dateReviewed:"November 19th 2019",datePrePublished:"January 9th 2020",datePublished:"February 19th 2020",dateFinished:"December 24th 2019",readingETA:"0",abstract:"Obesity, being an epidemy these days, is the trigger of metabolic disturbances such as cardiovascular disease, type 2 diabetes, and insulin resistance. Defined as an increase in fat storage, adipose tissue has been put under the spotlight as the culprit of these conditions, as it is composed not only by adipocytes but of any immune system cell and a singular extracellular matrix. Its behavior under acute and chronic hypercaloric states is quite different; persistent hypertrophy in the latter creates hypoxia, resulting in the release of reactive oxygen species and proinflammatory cytokines that impact on the immune response type of the resident leucocytes, mainly macrophages. Hypertrophy over hyperplasia, adipose tissue macrophages-M1 phenotype polarization, and the adipokines/myokines profile are thought to be regulated by foreign microRNAs, delivered from surrounding or distant cells by exosomes through the bloodstream. In this chapter, we focus on adipose tissue immunometabolism and how obesity causes the chronic inflammatory state, and, subsequently, this stablishes a pathologic adiposity, characterized by dyslipidemia and insulin resistance (IR).",reviewType:"peer-reviewed",bibtexUrl:"/chapter/bibtex/70627",risUrl:"/chapter/ris/70627",book:{id:"7017",slug:"obesity"},signatures:"Fernanda-Isadora Corona-Meraz, Jesus-Aureliano Robles-De Anda, Perla-Monserrat Madrigal-Ruiz, Gustavo-Ignacio Díaz-Rubio, Jorge Castro-Albarrán and Rosa-Elena Navarro-Hernández",authors:[{id:"191565",title:"Dr.",name:"Rosa Elena",middleName:null,surname:"Navarro Hernandez",fullName:"Rosa Elena Navarro Hernandez",slug:"rosa-elena-navarro-hernandez",email:"rosa_elena_n@hotmail.com",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",institution:null},{id:"195067",title:"MSc.",name:"Fernanda Isadora",middleName:null,surname:"Corona Meraz",fullName:"Fernanda Isadora Corona Meraz",slug:"fernanda-isadora-corona-meraz",email:"fernandacoronameraz@live.com.mx",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",institution:null},{id:"311468",title:"BSc.",name:"J. Aureliano",middleName:null,surname:"Robles-De Anda",fullName:"J. Aureliano Robles-De Anda",slug:"j.-aureliano-robles-de-anda",email:"aureliano.robles7@gmail.com",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",institution:null},{id:"311477",title:"Dr.",name:"Perla-Monserrat",middleName:null,surname:"Madrigal-Ruiz",fullName:"Perla-Monserrat Madrigal-Ruiz",slug:"perla-monserrat-madrigal-ruiz",email:"perlamadrigal@hotmail.com",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",institution:{name:"University of Guadalajara",institutionURL:null,country:{name:"Mexico"}}},{id:"311478",title:"Dr.",name:"Jorge",middleName:null,surname:"Castro-Albarran",fullName:"Jorge Castro-Albarran",slug:"jorge-castro-albarran",email:"nutjca@gmail.com",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",institution:{name:"University of Guadalajara",institutionURL:null,country:{name:"Mexico"}}},{id:"311479",title:"MSc.",name:"Gustavo Ignacio",middleName:null,surname:"Diaz-Rubio",fullName:"Gustavo Ignacio Diaz-Rubio",slug:"gustavo-ignacio-diaz-rubio",email:"gusqfb@hotmail.com",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",institution:{name:"University of Guadalajara",institutionURL:null,country:{name:"Mexico"}}}],sections:[{id:"sec_1",title:"1. Introduction",level:"1"},{id:"sec_2",title:"2. Healthy adipose tissue",level:"1"},{id:"sec_2_2",title:"2.1 Morphology and cellular biology",level:"2"},{id:"sec_2_3",title:"2.1.1 Classification",level:"3"},{id:"sec_3_3",title:"2.1.2 Fat depots",level:"3"},{id:"sec_5_2",title:"2.2 Immunometabolism",level:"2"},{id:"sec_5_3",title:"Table 1.",level:"3"},{id:"sec_6_3",title:"2.2.2 ECM remodeling",level:"3"},{id:"sec_7_3",title:"2.2.3 Glucose and lipid metabolism",level:"3"},{id:"sec_10",title:"3. Adipose tissue and disease",level:"1"},{id:"sec_10_2",title:"3.1 Insulin resistance",level:"2"},{id:"sec_10_3",title:"3.1.1 Obesity as a trigger",level:"3"},{id:"sec_11_3",title:"3.1.2 Inflammatory pathway",level:"3"},{id:"sec_12_3",title:"3.1.3 Molecular mechanism",level:"3"},{id:"sec_13_3",title:"3.1.4 Role of adipokines and myokines",level:"3"},{id:"sec_14_3",title:"3.1.5 Emerging role of microRNAs in obesity",level:"3"},{id:"sec_16_2",title:"3.2 IR in muscle and liver",level:"2"},{id:"sec_16_3",title:"3.2.1 Liver",level:"3"},{id:"sec_17_3",title:"3.2.2 Muscle",level:"3"},{id:"sec_20",title:"4. A new terminology: pathologic adiposity",level:"1"},{id:"sec_21",title:"5. Conclusions",level:"1"},{id:"sec_25",title:"Conflict of interest",level:"1"},{id:"sec_24",title:"Acronyms and abbreviations",level:"1"}],chapterReferences:[{id:"B1",body:'Ross M, Wojciech P. Connective tissue. In: Histology: A Text and Atlas with Correlated Cell and Molecular Biology. 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UDG-CA-701, Research Group on Immunometabolism and Complex Diseases, Department of Molecular Biology and Genomics, Health Sciences School, University of Guadalajara, Mexico
Department of Biomedical Sciences, Health Sciences Division, CUTonalá, University of Guadalajara, Mexico
UDG-CA-701, Research Group on Immunometabolism and Complex Diseases, Department of Molecular Biology and Genomics, Health Sciences School, University of Guadalajara, Mexico
Doctoral Program in Molecular Sciences in Medicine, Department of Molecular Biology and Genomics, Health Sciences School, University of Guadalajara, Mexico
UDG-CA-701, Research Group on Immunometabolism and Complex Diseases, Department of Molecular Biology and Genomics, Health Sciences School, University of Guadalajara, Mexico
Doctoral Program in Molecular Sciences in Medicine, Department of Molecular Biology and Genomics, Health Sciences School, University of Guadalajara, Mexico
UDG-CA-701, Research Group on Immunometabolism and Complex Diseases, Department of Molecular Biology and Genomics, Health Sciences School, University of Guadalajara, Mexico
Department of Health Sciences and Human Ecology, Regional Development Division, CUCSur, University of Guadalajara, Mexico
UDG-CA-701, Research Group on Immunometabolism and Complex Diseases, Department of Molecular Biology and Genomics, Health Sciences School, University of Guadalajara, Mexico
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1. Introduction
If you reached this point, you are probably familiar with the concept of binaural rendering. You likely also know that it is used for producing spatial sound over headphones in most of today’s personal mixed reality experiences. While conceptually sound, binaural rendering is subject to several limitations in practice, some of them leading users to perceive distorted versions of the encoded 3D scene. Those distortions range from slight localisation blur to critical scenarios where auditory events are perceived on the opposite hemisphere from their actual position. Researchers have been working on techniques to address this problem of binaural localisation accuracy for some time now. To establish the benefit of these techniques, they predominantly, and quite naturally, rely on localisation performance evaluations.
The problem that concerns us here is that there is no standard for said evaluation. As a consequence, fully appreciating the value of a technique often requires careful reading and interpretation of both protocols and associated results. This becomes truly problematic when comparing the results of several studies, where differences in protocol and evaluation metrics make for complicated analysis at best, simply impossible in some cases. Without inter-study comparison, it becomes hard to reach any conclusion on the overall and added value of an HRTF selection, synthesis, or learning method. The objective of this chapter is to lay the foundations of such a standard.
1.1 Context
One of the most frequent causes of auditory space distortion in binaural rendering is related to the use of non-individual Head Related Transfer Functions (HRTF)2. An HRTF is a collection of filter pairs that, applied to a mono signal, modify it so that it has the same characteristics as if it had physically been travelling from a specific point in space to our ears. The term HRTF refers to the set of filter pairs, each corresponding to a different source position, typically forming a sphere of fixed radius around the listener. When sound travels to our ears, the acoustic wave interactions with our morphology causes deformations in the perceived signal. From childhood, our brain learned to interpret these acoustic cues as different source positions. Since there exist many variations of ear, head, and torso shapes that each deform the sound differently, so too are there variations in HRTFs. While we are quite adept at sound localisation with our own ears and our own HRTF, the problem arises when we start using someone else’s.
In practice, most users will end up experiencing binaural rendering using an HRTF that is not their own, as in the case of a non-individual HRTF, generally taken from an existing database. Presently, measuring an individual’s HRTF most often requires specific equipment and access to an anechoic room. Methods exist to simulate an HRTF from geometrical head scans or morphological data, but they suffer the same drawbacks: the techniques are either too costly or burdensome to implement in practical scenarios, or they produce HRTFs that do not exactly match the individual users. As mentioned, using a non-individual HRTF, which the brain has not trained with, often results in distortions of the perceived auditory space. Researchers have been working on this issue, proposing new simulation methods, HRTF selection processes, and even HRTF training programs focused on the reduction of these distortions.
Naturally, all these lines of research end up using a localisation evaluation task to assess the benefit of new techniques. As mentioned above, there exists no standard method for this evaluation, hindering results appraisal and inter-study comparisons.
1.2 Chapter scope and organisation
The objective of this chapter is to outline a set of metrics and propose a methodology to assess localisation performance in the context of HRTF selection and training programs. While the tools proposed can be applied to other contexts, they were designed with HRTF training in mind as not only do they assess instantaneous performance but also performance evolution, adding another dimension to the analysis workflow.
Section 2 presents a state of the art of evaluation metrics used to assess localisation accuracy in previous studies. Section 3 introduces the proposed methodology and the set of metrics on which it is built. Section 4 is a case-study, using the methodology to re-analyse and compare the results of five contemporary experiments on HRTF learning. Section 4 concludes this chapter.
2. State of the art
This section presents and discusses a variety of metrics and methods of analysis introduced in previous studies for the evaluation of auditory localisation performance, in the context of HRTF selection and learning. Further, it discusses what aspect of the data or human behaviour is highlighted by each metric.
2.1 Analysis based on angular distances
The majority of the metrics used in the literature to assess localisation performance are derived from the angular distance from the source position to the participant’s response. This section discusses the most common of these metrics, their interpretation, and limitations. It builds upon the work presented in Letowski and Letowski [1].
2.1.1 Egocentric coordinate systems
Many auditory localisation tasks have participants indicating perceived target locations around them. As such, egocentric coordinate systems are a logical choice for the assessment of pointing errors. The spherical coordinate system, illustrated in Figure 1a, uses axes of azimuth and elevation angles. As most researchers are familiar with this coordinate system, it provides an intuitive framework to view and present results.
Figure 1.
(a) Spherical, and (b) interaural coordinate systems used in the methodology, for a source positioned at angles (55°, 46°) as defined in each coordinate system. Spherical azimuth angle θ is defined in [−180°:180°], elevation angle φ in [−90°:90°]. Interaural lateral angle α is defined in [−90°:90°], polar angle β in [−180°:180°]. The lateral angle used here is shifted by 90° compared to that originally defined by Morimoto and Aokata [2]. In both systems, listeners are facing X with their left ear pointing towards Y.
Alternatively, the interaural coordinate system has been proposed to evaluate localisation results as a more natural representation of how sound is perceived. The lateral angle, referred to as the “binaural disparity cue” by Morimoto and Aokata [2], defines cones-of-confusion along which the binaural cues of Interaural Level Difference (ILD) and Interaural Time Difference (ITD) are approximately constant. A cone-of-confusion is a set of positions presenting binaural cue/localisation ambiguities, that listeners may not be able to differentiate unless provided with further spectral cues or head movement information [3]. While not truly ‘cones’, these constant ILD or ITD surfaces generally define a circle when the radius is fixed (see [4] for more discussion on the variation with radius of these constant-value surfaces). To maintain accepted terminology in the field, each of these circles is termed a “cone-of-confusion”. The polar angle, or “spectral cue”, is primarily linked with the monaural spectral cues in the HRTF. This independence of binaural and monaural cues makes the interaural coordinate system a compelling choice when assessing localisation performance, particularly when monaural cues are of special interest as in HRTF selection and learning tasks.
Other conventions have been proposed, such as the double-pole [5] or three-pole [6] coordinate systems. These systems have been designed to circumvent compression issues impacting single-pole (spherical and interaural) coordinate systems, further discussed in Section 2.1.3. They can prove very helpful for some types of data presentation [5], yet can confuse the analysis as more than one coordinate vector can be assigned to any given point in space.
2.1.2 Azimuth, elevation, lateral, and polar errors
Regardless of the coordinate system used, angular errors can be calculated using either the signed or absolute difference between target and response coordinates. The signed error will give an indication on the “localisation bias” [5] where the absolute error, more often used in the literature [7, 8, 9, 10], provides a measure of how close a response is to the target, regardless of error direction. Computing summary statistics from these values can be a first and straightforward step to characterise both the central tendency and dispersion, or “localisation blur” [11], of participant responses [1].
Care must be taken in calculating signed and absolute errors because of the discontinuities in the azimuth and polar angles of the spherical and interaural coordinate systems. If a source is close to the discontinuity and the response crosses it (e.g. 179° to −179°), the calculated error will be artificially large. Likewise, summary statistics such as mean or standard deviation should also be computed away from those discontinuities. Another problem that results from working with egocentric systems is that data distributions will be warped by the sphere curvature, requiring in theory to use circular statistics when comparing statistical distributions. As discussed in [1], linear statistics can however be used in practice if the directional judgements are relatively well concentrated around a central direction.
2.1.3 Compensating for spatial compression
Both the spherical and interaural coordinate systems introduce spatial compression at their poles. In the interaural coordinate system for example, the circumference of the cone-of-confusion at 80° lateral angle is much smaller than that of a cone at 0° lateral angle. Therefore, polar angle errors at the poles (near ±90° lateral angle) are more exaggerated than near the median plane. The same problem impacts azimuth errors near the poles (near ±90° elevation angle) for the spherical coordinate system.
Previous studies have sought to avoid the spatial compression problem altogether by limiting the analysis to targets away from the poles [12]. The downside of this method is that it limits the scope of the study’s conclusions because a large region of space cannot be studied. Still others have proposed compensation schemes, using for example the lateral angle to weight the response contribution to the average polar error [13, 14, 15]. Carlile et al. [13] for example weighted polar response errors using the cosine of the target lateral angle, decreasing response contributions as targets moved towards the interaural axis. This method more accurately reflects the arc length between the target and response locations on the circle, keeping in mind that this weighting does not take the lateral angle of the response into account.
2.1.4 Using directional statistics to analyse sound localisation accuracy
Due to the discontinuities and spatial compression in the angular metrics of the typical coordinate systems, some work has simply examined the distance between the participant responses and the true target positions to assess the extent of localisation error. The most basic method, the great-circle error used in several studies [9, 15, 16], is measured as the distance along the unit sphere between the response and target locations. The great-circle error is independent of the selected coordinate system, not affected by the issues related to discontinuity in the axes or spatial compression.
Great-circle error on its own does not provide information about the direction of the response. Paired with the angular direction, it becomes a vector that fully describes the difference between the response and target positions [1]. Similar to bearing used to navigate on the globe, angular direction is the angle between the vector of the target towards the positive pole and that of the target towards the response. This vector can be used to compute the mean position of the responses, or centroid, and perform directional or spherical statistics. Alternatively, the centroid of the response locations may be calculated by separately summing the x, y, and z coordinates of the responses and dividing by the resultant length [17, 18], though this method may experience some undesirable results for edge cases with widely-scattered locations on the sphere.
To perform statistical analyses of the localisation accuracy, the variance in the response locations must be quantified [19, 20] . Given the two-dimensionality of the data, previous work has used Kent distributions on a sphere [17, 21] to determine ellipses that portray the variance of the data along major and minor axes of the spread of the responses. With Kent distributions, circular statistical tests may be conducted to evaluate the significance of the distance between the centroid of the responses and the target location (such as the Rayleigh z test) or the differences between mean response locations for different conditions (such as the Watson two-sample U2 test) [22]. Alternatively, Wightman and Kistler [18] suggest the use of the “concentration parameter” κ to characterise the variance, or “dispersion”, of the response locations on the sphere.
2.1.5 Further high level metrics based on angular distances
The spherical correlation coefficient has been used to provide an overall measure of the correlation between target and response positions [13, 17, 18]. As with standard correlation, the spherical correlation coefficient ranges from −1 to 1, where a value of 1 is obtained for two identical data sets, and a value of −1 is obtained for two sets that are reflections of one another. By construction, the spherical correlation coefficient is invariant for global rotations between the two sets.
Rather than looking at single or mean error values to assess localisation accuracy, Hofman et al. [23] and Trapeau et al. [24] studied the linear regression between targets and responses elevation angles. Termed “elevation gain”, the slope of this regression provides a higher level metric that can be used to detect compression or dilation effects in participant responses. Van Wanrooij and Van Opstal [25] extended this technique, applying the regression on target versus response azimuth as well as elevation angles. To account for azimuthal dependence of the elevation gain, they also introduced the notion of “local elevation gain”, averaging elevation gain values based on a sliding azimuthal window. This metric allows the assessment of how elevation compression and dilation effects impact different regions of the sphere.
2.2 Analysis based on confusions classification
2.2.1 Confusions classification
An analysis based on angular distances alone would fail to distinguish local accuracy misinterpretations from critical space confusions, where responses are often on the opposite hemisphere from target positions. These kinds of errors are very common in studies using non-individualised HRTFs [8, 10, 26, 27], though they also occur when listening with one’s own ears or HRTF [5].
One of the simplest techniques is that used by Honda et al. [28], which defines a hit-miss criterion based on a threshold great-circle error value. Though intuitive, the method does not provide much information on the nature or potential origin of the confusions.
A slightly more elaborate form of confusion classification was used by Middlebrooks [12], which flags responses as confusions when they are in a different hemisphere than that of the target. To avoid reporting small local accuracy errors as confusions for targets near the hemispheres limits, only those responses with polar angle errors greater than 90° were considered when searching for confusions. The classification thus resulted in three types of “quadrant confusions”: front-back, up-down, and left-right. Majdak et al. [14] further improved the definition, introducing a weighting factor to compensate for polar angle compression near the interaural axis. A comparable strategy was adopted by Carlile et al. [13], excluding from confusion checks those targets too close to the interaural axis.
A parallel classification was proposed by Martin et al. [29], determining confusion types based on cone-of-confusion angle values rather than sphere quadrants. The classification was further refined by Yamagishi and Ozawa [30], Parseihian and Katz [8] and Zagala et al. [16], adding “precision” and “combined” confusions to the already existing confusion types. This classification is discussed in more detail in Section 3.1.4.
2.2.2 Separating angular and confusions errors contributions
Given the relatively high incidence of front-back confusions in non-individual HRTF localisation tasks, results often exhibit a bi-modal distribution [10]. Analyses applied to data that contain a large portion of front-back confusions will have large variance and potentially inaccurate averages. The other confusion types also have a similar, if somewhat less characteristic, impact on the data, artificially inflating localisation errors. As such, it is common practice to split the data to analyse confusions separately from local performance [1, 12, 14, 31]. A potential problem with this approach is that excluding data from an analysis may result in an unbalanced data set, which limits the use of classical repeated-measures statistics.
Another approach that preserves the sample size of the data consists of ‘folding’ the responses into the same subspace as that of the target prior to the analysis. This technique has only ever been applied to mirror front-back confusions [18], as it may only apply to very specific circumstances and tends to inflate the power of the resulting conclusions [1].
2.3 Additional analysis methods
2.3.1 Decomposing the analysis across sphere regions
Several studies have shown variations in localisation accuracy as a function of region on the sphere due to, amongst other things, cue interpretation [3] or reporting method [32]. In these cases, decomposition schemes were used to better characterise those variations and understand their origins. As mentioned in Section 2.1.5, Van Wanrooij and Van Opstal [25] for example decomposed the analysis of elevation gain across azimuthal regions. Later, Majdak et al. [14] proposed an analysis split into hemi-fields to detect higher accuracy variations for targets in the rear region. Middlebrooks [12] applied a similar spatial decomposition to detect high variability for responses in the upper-rear quadrant, temporarily excluding them from the analysis to better assess variations in remaining regions. The principal drawback of decomposition is that it reduces the statistical power of the analysis, and can result in unbalanced data sets if responses are not evenly spread across the regions under consideration.
2.3.2 Performance evolution modelling and analysis
For the evaluation of HRTF learning, it is essential to assess the progression of participant performance over multiple sessions. On the assumption that any adaptation to an HRTF is a process with diminishing returns with repeated training sessions, localisation performances may be modelled as an exponential decay y=y0exp−t/τ+c [15, 31]. Here y0 is the initial performance, t is the time (training day, session, etc.), τ is the improvement time constant, and c is the long term performance. This model of performance over time allows for comparisons between studies, such as determining if different protocols lead to faster learning rates or if better long term performance can be achieved. If the training duration proves insufficient to reach a performance plateau/asymptote, like that seen in Stitt et al., [10], the improvement data may be better modelled using the linear form ax+b [9, 31]. In addition to performance modelling, the correlation between training duration and performance metrics has been used to determine if factors other than training duration, like participant attention, should be considered to explain performance evolution [33].
Analysis of performance evolution can be performed per condition (grouping participants) [8, 10] or per participant [23]. Participant performance evaluation makes it harder to draw general conclusions, but potentially provides deeper insight into performance as not all participants exhibit the same ability to adapt to a new HRTF [24]. This adaptation capacity appears to be a function of initial HRTF affinity or “perceptual quality” [10]. For inter-study comparisons, some form of performance scaling or normalisation may first be required to compensate for such affinities, highlighting performance improvement rather than absolute value [10].
3. Methodology for assessing localisation performance
From the literature review in the previous section, a methodology is derived for assessing binaural localisation accuracy. Though it was designed with a focus on HRTF training programs, it should be applicable to any HRTF-related study interested in localisation performance assessment. Section 3.1 introduces the conventions and metrics used in the methodology, itself detailed in Section 3.2. The metrics proposed along with the notions they examine are summarised in Table 1 at the end of this section. A MATLAB toolbox for the evaluation of all the metrics discussed here is available online3.
Name
Notion examined
Space coverage statistic
Density and homogeneity of the evaluation grid
Confusion rates
Percentage of errors resulting from cone-of-confusion or quadrant ambiguities
Localisation accuracy in the horizontal plane, excluding confusions
Local polar error
Localisation accuracy in the vertical plane, excluding confusions
Local azimuth error
Localisation accuracy in the horizontal plane, excluding confusions
Local elevation error
Localisation accuracy in the vertical plane, excluding confusions
Local lateral compression
Whether localisation errors are distorted systematically towards the median plane ZX, excluding confusions
Local elevation compression
Whether localisation errors are distorted systematically towards the horizontal plane XY, excluding confusions
Local lateral bias
Whether there is a systematic rotational offset on responses around the Z axis, excluding confusions
Local elevation bias
Whether there is a systematic upward offset on responses, towards positive Z, excluding confusions
Per-region metrics
Decomposition of the analysis across target regions
Local responses distribution
Whether two sets of responses, excluding confusions, belong to different spherical distributions (using Kent distribution and circular statistics)
Table 1.
Summary of the evaluation metrics used in the methodology, grouped by concept similarity.
3.1 Conventions and evaluation metrics
3.1.1 Coordinate systems
The methodology makes use of both spherical and interaural coordinate systems, illustrated in Figure 1. While the spherical coordinate system provides an intuitive perspective on the results, the interaural system has been especially designed to separate the analysis of binaural and monaural cues, as discussed in Section 2.1.1, making it a natural choice for the analysis of HRTF-related localisation performance.
3.1.2 Protocol space coverage
Space coverage is a set of metrics, scangle and scshape, designed to provide insight on the density of points tested during the localisation task, as well as on the homogeneity of their distribution on the sphere. scangle represents the density of the evaluated positions for a given test protocol. It is is computed based on the spherical Voronoi diagram built from the evaluated positions, as the average over the solid angles of its cells [34], accompanied, ±, by its standard deviation. As illustrated in Figure 2, denser grids result in smaller scangle, with standard deviation decreasing for increasingly homogeneous distributions.
Figure 2.
Various test grids and associated space coverage statistics. (a) Homogeneous grid with large number of points, (b) homogeneous grid with small number of points, (c) non-homogeneous grid with small number of points, and (d) horizontal grid with small number of points.
scshape is computed as the average over the shape indices of the cells of the Voronoi diagram, defined as:
shape_index=4πcell_areacell_perimeter2E1
where the perimeter is computed as the sum of the great-circle values between the cell vertices, expressed in radians. The squared value of the perimeter, as well as a 4π normalisation factor, are used so that the final shape index value is defined in 01. Cells shaped as circles will have an index close to 1, whereas the index will decrease towards 0 as the cell grows into an elongated polygon. As illustrated in Figure 2, scshape is used in addition to scangle standard deviation to detect uneven evaluation grid distributions. Note that grid density has a negative impact on scshape: dropping from 0.91 to 0.84 for uniform grids of 20 and 80 points respectively [35].
3.1.3 Great circle error and angular direction
The great-circle error is defined as the minimum arc between the response and the true target position. This metric provides an intuitive way to assess the local localisation accuracy as the spherical distance between the responses and the target. Given xyztarget and xyzresponse as the vectors in Cartesian coordinates of the target and response positions respectively, the great-circle error is defined in [0°:180°] as:
where smaller values correspond to better localisation performances.
The angular direction is coupled to the great circle to enable vector summation of target to response arcs on the sphere. The direction towards the right ear constitutes the positive pole in the interaural coordinate system. The angular direction may then be calculated from the interaural coordinates as:
where α is the lateral angle and β is the polar angle.
3.1.4 Confusion classification
As discussed in Section 2.2, confusion classification schemes are primarily designed to separate small localisation errors from larger errors caused by erroneous localisation behaviours typically observed in binaural localisation tasks. The scheme used in the methodology is designed around notions borrowed from both cone-of-confusion [8, 10, 16, 29] and sphere quadrant [12, 14] classifications. It separates responses into 4 categories: those near the target (precision errors), those opposite the target compared to the YZ plane (front-back errors), those within the target cone-of-confusion (in-cone errors), and the remainder (off-cone errors).
The classification is illustrated in Figure 3a. Responses within a 45° radius cone around the target are defined as precision errors. Responses within a 45° cone around the symmetrical of the target position regarding the YZ plane, not already classified as precision errors, are defined as front-back errors. Responses with a lateral angle within 45° of that of the target, not already classified as either precision or front-back confusions, are defined as in-cone errors. Remaining responses are defined as off-cone errors. Figure 3b and c schematically show several alternate approaches, evaluated before choosing the current method (discussed in more detail below).
Figure 3.
Confusion type as a function of response position on the sphere, for a target at spherical coordinates (35°, 10°) and a listener facing X with his left ear pointing towards Y. (a) Proposed classification scheme, (b) classification used in Stitt et al. [10] based on polar angle only, and (c) attempt at solving pole compression issues of (b).
The proposed 45° threshold value is somewhat arbitrary, based on a segmentation of localisation error distributions of responses from previous studies [8, 9, 10]. This value can be adapted depending on the context of the study and the nominal localisation accuracy expected. To improve understanding, the evolution of confusion zones for a 20° threshold and various target position is illustrated in Figure 4. The sum of the four confusion category rates always sums to 100%.
Figure 4.
Confusion type as a function of response position on the sphere for the proposed classification scheme with an angle threshold of 20 and a listener facing X with his left ear pointing towards Y. Target at spherical coordinates (a) (35°, 10°), (b) (70°, 40°), and (c) (80°, 10°).
The distinction between in- and off-cone confusions is inspired from the duplex theory [36, 37], separating responses based on whether they are caused by misinterpreting monaural cues (in-cone confusions) or binaural cues (off-cone confusions). The commonly cited front-back confusion category has been maintained, despite not having a clearly identified origin in signal symmetry, as it represents a behaviour frequently observed in localisation studies [38]. Other confusion categories have been considered for this scheme, such as up-down or combined up-down-front-back confusions. They have been discarded however, as their representative patterns were not prevalent in the ≈10000 participant responses analysed in Section 4 or the meta analysis on ≈80000 responses in free field by Best et al. [38].
Compared to traditional cone-of-confusion classifications defined using only polar angle [8, 10, 16, 29], the main drawback of the proposed scheme is that it is susceptible to ITD mismatch. By only looking at the difference in polar angle between target and response, these classifications are not impacted by participants misinterpreting the ITD of the target, focusing on monaural cues interpretation characterisation. As illustrated in Figure 3b, the problem of these classifications is that they have high rate of false error detection at the poles of the interaural coordinate system, were a small shift in response can be interpreted as e.g. a front-back confusion instead of a precision error.
An attempt was made to propose a new scheme, inspired by the one used in Stitt et al. [10], alleviating the pole issue by increasing the (polar) spread of the precision zone as targets near the poles, constraining said spread to always span 45 of great-circle angle when projected on the sphere. As illustrated in Figure 3c, this constraint results in a undesirable warping of the precision error zone for targets within a certain lateral distance from the poles.
The solution proposed for studies needing a classification based on monaural cues interpretation alone is to extend the proposed scheme, artificially adjusting the lateral position of targets prior to the classification to discard errors related to ITD mismatch. This adjustment can be made on a per-participant/target basis, replacing the lateral angle of targets by the mean lateral angle of their associated responses prior to the classification. It can also be performed on a per-response basis by simply assuming that targets and responses always have the same lateral position. The case study of Section 4 uses the second, simple, non-adaptive form of the classification scheme.
3.1.5 Azimuth, elevation, lateral, and polar errors and biases
Lateral and polar errors are defined as the absolute difference between target and response positions in interaural coordinates. They are used to project localisation errors onto spatial dimensions associated with separate cues in the HRTF, allowing for an analysis of their independent contribution to the overall performance. Both are defined in [0°:180°], where smaller values correspond to better localisation performances. In the methodology, lateral and polar errors will be evaluated only on responses classified as precision confusions, hence referred to as local lateral and polar errors. This limitation allows to avoid the discontinuities discussed in Section 2.1.2 as well as the hazardous interpretation of values compounding local errors and spatial confusions.
As mentioned in Section 2.1.3, compression at the poles will lead to artificially inflated polar errors for targets near the interaural axis. A weight, proportional to the target lateral position, can be applied to the polar error to compensate for the compression, defining the polar error weighted as:
polar_error_weighted=polar_error∗cosαtargetE4
This weight is designed so that, for a target and a response that share the same lateral angle, the polar error weighted is equal to the arc length (great-circle) that separates them, regardless of said lateral angle. Note that while lateral error is not impacted by pole compression, it ‘folds’ near the interaural axis: random responses will overall have a lower local lateral error for targets in this region. This is a valuable feature of the interaural system when assessing the symmetric contribution of binaural cues (ITD/ILD) to localisation error. It can nonetheless lead to artificially deflated lateral errors when used in a different context.
Azimuth and elevation errors are defined as the absolute difference between target and response positions in spherical coordinates. They correspond to a more traditional projection of spherical coordinates, more intuitive yet no longer guided by auditory cue separation. Like interaural errors, azimuth and elevation errors are defined [0°:180°] and will be used only for local precision evaluation. As for polar error, azimuth error compression near the poles can be compensated for, defining the azimuth error weighted as:
azimuth_error_weighted=azimuth_error∗cosφtargetE5
In addition to absolute errors, signed lateral and elevation errors are used in the methodology. Mean signed errors, referred to as biases, are typically used to examine systematic rotational biases, induced for example by an offset between the tracking system used for measuring the HRTF and that used during the evaluation task, or reporting bias. As for absolute errors, usage of both metrics will be restricted to responses classified as precision confusions.
Finally, lateral and elevation compression errors are used to highlight space compression and dilation effects. Lateral compression, is defined as ‖αtarget‖−‖αresponse‖, so that a positive error corresponds to a compression towards the median plane ZX. Respectively, a negative error corresponds to a dilation away from the median plane. Similarly, the elevation compression is defined as ‖φtarget‖−‖φresponse‖, so that a positive error corresponds to a compression towards the horizontal plane XY. Respectively, a negative error corresponds to a dilation away from the horizontal plane. Compression errors are for example used to characterise a pointing bias caused by the reporting interface, or to detect lateral compressions resulting from an ITD mismatch between the presented HRTF and that of the participants.
3.1.6 Sphere regions
The decomposition of the analysis in sphere regions depends on the context. As such, there exists no one ideal decomposition scheme. To support the case study presented in the next section, the sphere will be split into 6 regions: front-up (x>0 and z>0), front-down (x>0 and z<0), back-up (x<0 and z>0), back-down (x<0 and z<0), left (y>0), and right (y<0). This scheme has been chosen to best highlight region specific behaviours while remaining manageable, based on a preliminary analysis of the experiments studied in Section 4. The redundant left and right regions have been added for systematic checks on lateralisation discrepancies in participant responses.
3.2 Methodology
The methodology is proposed as a set of analysis steps, each building on the previous one to provide a comprehensive assessment of participants localisation performance.
3.2.1 Evaluation task characterisation
The first step of the analysis is to assess how much of the space, i.e. sphere, has been tested during the localisation task. In addition to depicting the grid of tested positions, this step reports its space coverage statistics as defined in Section 3.1.2. This provides readers with a simple set of metrics that reflect the spatial thoroughness of the evaluation, a value they can use to qualify the study’s conclusions as well as for inter-study comparisons.
Atypical evaluation grids and their potential impact on participant results should also be discussed here. An evaluation on frontal field positions alone is likely to result in better overall performance compared to one encompassing the whole sphere, due to known variations of perceptual accuracy across sphere regions [5]. When using such grids, reporting metrics chance rates, i.e. their values for responses randomly distributed on the sphere, as proposed by Majdak et al. [14] can greatly help readers appreciate the presented results. Another problematic example is the use of evaluation grids sparse enough for participants to identify and recall the tested positions, likely impacting participants performance and associated conclusions.
Finally, the stimulus characteristics (type, duration, etc.) as well as the reporting method should be described and discussed here, so that any systematic bias they may have on participant responses can be detected during the analysis.
3.2.2 Assess global extent of localisation error
The objective here is to get a rough overview of participant performance during the localisation task, simply answering the question “how far were responses from the true target position?”. The assessment is based on the great-circle error as defined in Section 3.1.3.
3.2.3 Assess critical localisation confusions
The next step consists in separating small precision errors from critical confusions. The nature and types of confusions is characterised early on as they can have a critical impact on localisation performance, often far more detrimental than local localisation accuracy issues. This characterisation is performed using one of the classification methods defined in Section 3.1.3.
3.2.4 Assess local extent of localisation error
This next step takes a closer look at responses classified as precision errors, i.e. the non-confused responses, to examine the local localisation performance. The mean great-circle error and angular direction of responses classified as precision confusions is computed to analyse the extent of local errors. Note that this metric does not depend on the confusion classification method used, as precision errors are defined using the same criterion in both methods. Conclusions drawn from this local analysis should naturally be leveraged by the percentage of responses it encompasses.
3.2.5 Horizontal and vertical decomposition of the localisation error
Whether or not this step should be included in the analysis, and which metrics it should make use of, depends on the context of the study. An experiment focusing on perceptual ITD adjustment for example would likely make use of both local lateral error as well as lateral compression. A training program attempting to fine tune participant interpretation of monaural cues would on the other hand base its evaluation on the local polar error. For some studies, this decomposition will not make sense and should be avoided to limit Type I error inflation.
3.2.6 Decompose the analysis across sphere regions
This final step consists in repeating all of the above, decomposing the analysis based on target positions to assess how participants fared in specific regions of the sphere. Given the loss of statistical power and the additional clutter that this analysis represents, it only needs to apply to those studies interested in characterising spatial imbalances in performance. The decomposition can then be performed using either a sphere splitting scheme as the one described in Section 3.1.6, or on a per-target position basis. For example, this approach can be used to support the design of HRTF learning programs that would focus dynamically on those regions/confusions that are the most problematic [9].
To further characterise local localisation behaviours, the analysis can be completed by evaluating average response positions and spherical response distributions. The former, computed by summing local great-circle error vectors, as discussed in Section 3.1.3, will help characterise variations of localisation accuracy across sphere regions [21]. The latter, characterised using Kent distributions (see Section 3.1.3), will provide the statistical framework to assess the significance of those variations.
4. Case study
The methodology defined in the previous section is applied here to build a comparative analysis on a selection of studies, focusing on the use of, and adaptation to, binaural cues for auditory localisation. The objective of this case study collection is not so much to present a thorough comparison of these studies as to illustrate how the methodology can be applied to a practical use case, and how its constituting metrics react to concrete scenarios. To further focus the case-study on these points, significance assessment is based on the overlapping of estimated distributions Confidence Intervals (CIs) rather than on null-hypothesis tests [39].
4.1 Study selection overview
Several studies of the impact of HRTF training on localisation accuracy have been selected from existing literature, for which authors graciously provided raw participant data used in the comparative analysis. A short description of each study is provided in the next section, reporting only those elements that concern the present analysis.
Common to most of the presented studies is the notion of HRTF perceptual quality. This term refers to the perceptual matching, localisation wise, between a participant and an HRTF. A low quality HRTF is one that results in bad localisation accuracy. Inversely, the higher the quality, the better the localisation accuracy, the highest quality match corresponding in theory to one’s own HRTF. Replicating the potential outcomes of selecting an HRTF from an existing database, three degrees of perceptual matching are considered in these studies in addition to individual HRTF: worst-match, random-match, and best-match HRTF. Best and worst-match HRTFs represent respectively a best and worst case outcome, typically obtained by asking participants to perform a localisation task with, or a perceptual ranking of, an existing set of HRTFs.
4.1.1 Study description: exp-majdak
Majdak et al. [14], a 2010 study on the impact of various reporting methods during training with their individual HRTF. 10 participants trained on auditory localisation: 5 reporting perceived localisation positions with their hand, 5 with their head. Each participant completed 600–2200 localisation trials over a span of 2–32 d. Training and evaluation were performed within each trial: a session was composed of 50 trials, completed in 20–30 min. Each trial consisted of a localisation task with feedback, testing participants on 1380 positions overall, distributed on a sphere, using a 500 ms burst of white noise as stimulus. As the reporting method proved to have only a small impact on training efficiency, the 10 participants have hereafter been aggregated in a single group (grp-majdak-indiv), focusing the analysis on the impact of HRTF quality on performance evolution.
4.1.2 Study description: exp-parseihian
Parseihian and Katz [8], a 2012 study on accommodation to non-individual HRTF. 12 participants trained on auditory localisation, each completing 3 sessions of 12 min each on 3 consecutive days. Each session consisted of an interactive audio localisation game followed by a localisation task evaluation testing participants on 25 positions distributed on a sphere, using a 180 ms sequence of white noise bursts as stimulus. Before training, each participant ranked a set of 7 perceptually orthogonal HRTFs [40, 41] from the LISTEN database [42] based on localisation accuracy as perceived during predefined audio trajectories. The best and worst-match HRTF for each participant was extracted from this ranking. Participants were then divided into 3 groups: 2 that trained with their individual HRTF (grp-parse-indiv), 5 with the best-match HRTF (grp-parse-best), and 5 with the worst-match HRTF (grp-parse-worst). An additional 2 groups that performed only 1 training session are not considered in the current analysis. The ITDs of all HRTFs were adjusted based on individual participant head circumference, using a model derived from a regression between measured ITDs and morphological parameters. This technique is used as a practical method, easily carried out by end-users, to maximise initial localisation performance accuracy.
4.1.3 Study description: exp-stitt
Stitt et al. [10], a 2019 study on accommodation to non-individual HRTF. 16 participants trained on auditory localisation, each completing 10 sessions of 12 min each over a span of 10–20 weeks. The worst-match HRTF selection, training game, stimulus, and tested audio source positions during the localisation task evaluation at the end of each training session were the same as those of exp-parseihian. Participants were divided into 2 groups: 4 training with individual HRTFs (grp-stitt-indiv) and 8 with worst-match HRTFs (grp-stitt-worst). An additional 8 participants trained for only 4 sessions with their worst-match HRTFs are not considered in the current analysis.
4.1.4 Study description: exp-steadman
Steadman et al. [15], a 2019 study on accommodation to non-individual HRTF. 27 participants trained on auditory localisation, each completing 9 sessions of 12 min each over a span of 3 d. A localisation task evaluation was conducted at the beginning and end of each day as well as between each training session the first day, testing participants on 12 positions distributed on a sphere using a 1.6 s stimulus merging bursts of white noise and speech signal. All participants trained with the same randomly-matched HRTF selected from the 7 LISTEN database of exp-parseihian. Participants were distributed in 3 groups, training on various gamified and interactive versions of an audio localisation game, aggregated as one group in the current analysis (grp-steadman-random). An additional 9 participants, acting as a control group not undertaking training, are also not considered in the current analysis, as well as the results of a parallel evaluation task performed on another HRTF than that used during training.
4.1.5 Study description: exp-poirier
Poirier-Quinot and Katz [9], a 2021 study on accommodation to non-individual HRTF. 12 participants trained on auditory localisation (grp-poirier-best), each completing 3 sessions of 12 min each over a span of 3–5 d. Participants trained using a best-match HRTF selected from the 7 LISTEN database of exp-parseihian, though the simplified subjective selection method was only concerned with identifying the best-match HRTF. An additional 12 participants trained with their best-match HRTF in a reverberant condition are not considered in the current analysis. Each session consisted of an interactive audio localisation game followed by a localisation task evaluation testing 20 positions distributed on a sphere using the same stimulus as in exp-parseihian.
4.2 Application of the methodology
4.2.1 Time alignment of evaluation sessions
In all these experiments, the training sessions lasted for 12 min, except for exp-majdak where both training and evaluation were performed in a single block of 20–30 min. According to exp-majdak, the evaluation itself took half that time, leaving a per-session training duration equivalent to that of the other studies. A time realignment across experiments was executed such that the evaluation sessions compared are separated by equivalent training durations. Thus, the sessions have been renumbered to account for changes in protocol.
In the analysis, evaluation sessions are numbered from 1 to 11, each separated by a 12 min training. Exp-poirier and exp-parseihian only performed 3 training sessions, hence the missing data-points in subsequent figures. Likewise, exp-stitt and exp-majdak did not report pre-training performances, missing session 1 data-points. Finally, the number of evaluations in exp-steadman spreads out from session 4 onward, switching from an evaluation session after each training to an evaluation at the beginning and end of each 3-sessions training day.
4.2.2 Evaluation task characterisation
The space coverage of target positions evaluated during the localisation task of each study are reported in Figure 5. The high density of the grid of exp-majdak results in a very low average scangle compared to those of the other experiments. Its comparatively high standard deviation is due to the absence of test positions in the bottom part of the sphere (polar gap). For comparison, a homogeneous grid with the same number of points would have yielded scangle=0.5°±0.003. Distribution homogeneity is also responsible for the lower scangle standard deviation value observed in exp-poirier compared to that of exp-parseihian and exp-stitt. Finally, exp-steadman, with fewer test points and a polar gap in the bottom hemisphere, has the highest scangle value and standard deviation.
Figure 5.
Space coverage statistics of the evaluation task in the selected studies (a) majdak, (b) parseihian/stitt, (c) poirier and (d) steadman.
As could be expected, all the grids present high scshape values, being overall evenly distributed on the sphere. Grid density around polar gaps impacts the metric, explaining why exp-poirier value is higher than that of exp-majdak while both grids are evenly distributed: removing polar gap contributions in these grids would yield scshape values of 0.91 and 0.84 respectively.
Two different reporting methods were used in the five studies: head pointing (exp-majdak and exp-steadman) and hand pointing (exp-majdak, exp-parseihian, exp-steadman, exp-poirier). This should have little to no impact on the comparative analysis however, as both methods lead to similar reporting biases [32]. exp-parseihian, exp-stitt, and exp-poirier used the same stimulus: a 180 sequence of three white noise bursts. Exp-majdak used a slightly longer, unique burst of 500 ms, and exp-steadman used a 1.6 s stimulus composed of both white noise bursts and speech signal. All these stimuli are likely to present the transient energy and the broad frequency content necessary for auditory space discrimination [43, 44]. The difference in stimulus duration may have repercussions in the analysis, as the participants can initiate more head movements to facilitate auditory localisation during the presentation of longer stimuli [45]. While adaptive rendering (i.e. dynamic cues) was disabled during stimulus presentation in exp-parseihian, exp-stitt, and exp-poirier, this is not explicitly stated in exp-majdak and exp-steadman.
4.2.3 Assessing the global extent of localisation error
The evolution of great-circle angle error across studies and training sessions is reported in Figure 6. Besides the clear benefit of training observed in all studies, the metric also highlights the overall positive impact of HRTF quality on initial performance. Interestingly, while the results from exp-parseihian suggest a similar intra-HRTF quality/performance relationship, it reports larger great-circle angle errors compared to those of the other experiments. This point already illustrates how differences in evaluation protocols or inter-participant variations may complicate the comparison of results across studies, as discussed in Section 4.3.
Figure 6.
Great-circle error mean and CI evolution across sessions and experiments. The great-circle error value for random responses is of ≈90° for all experiments.
4.2.4 Assessing the critical localisation confusions
Much like the great-circle error, precision confusion rates can be used to assess performance evolution during training, as illustrated in Figure 7. Trends observed on initial precision rates and their evolution reflect the observation made on the great-circle error analysis. Precision rates and great-circle angle values are indeed highly correlated across training sessions, with correlation coefficients in [−1.0:−0.9] for all studies. As each confusion rate aggregates all the responses of a participant during an evaluation session however, their CI is by construction often wide enough to confuse the analysis compared to that based on great-circle errors.
Figure 7.
Precision confusion rates mean and CI evolution across sessions and experiments. Grp-parse-indiv was removed from the figure, composed of only 2 participants, resulting in a CI so large it confused the whole plot.
This widening of the CIs is particularly apparent in the comparison of the other confusion rates, reported in Figure 8 for the evaluation that took place after the first training session. While a trend indeed suggests that the amount of confusions increases with decreasing HRTF quality, overlapping CIs often prevent any definite conclusion. Observing these rates can still help inform the analysis, as the poor performance of grp-parse-indiv on great-circle error observed in the previous section can be partly attributed to their high in-cone confusion rates, while their off-cone confusion rate is on par with that of grp-stitt-indiv and grp-majdak-indiv.
Figure 8.
Confusion rates after the first training session across experiments.
Maybe the most interesting use of confusion rates is to decompose the overall performance evolution. As illustrated by its confusion rate evolution in Figure 9, grp-stitt-worst performance evolution observed in Figure 6 should, confusion wise, mainly be attributed to improvements in front-back confusions during training.
Figure 9.
Confusion rates mean and CI evolution across sessions for grp-stitt-worst.
4.2.5 Assessing the local extent of localisation error
Results of the confusion classification indicate that roughly 50% of responses were within the vicinity of the target (precision errors) after the first training session across experiments. The analysis here focuses on these responses, assessing local accuracy issues to complete that on localisation confusions.
Figure 10 reports local great-circle errors across training sessions and experiments. Looking once more at grp-stitt-worst, their local accuracy did not improve during training, oscillating around 25°. The improvement seen on overall great-circle error for that group can therefore be solely attributed to the reduction in front-back confusions reported in the previous section. Likewise, the 10° improvement on overall great-circle error observed for grp-parse-worst between sessions 2 and 3 can be attributed to a reduction in confusion rates, as it does not appear on local great-circle error. Separating the contribution of confusions from that of local accuracy also reveals a significant difference between grp-stitt-indiv and grp-majdak-indiv improvement of local great-circle error between sessions 2 and 6, not visible on global great-circle error.
Figure 10.
Local great-circle error mean and CI evolution across sessions and experiments.
4.2.6 Horizontal and vertical decomposition of the localisation error
Local lateral error evolution across sessions for all experiments is reported in Figure 11a. As expected, initial performances indicate that participants using individual HRTF were quite apt at lateral localisation, accustomed as they were to the presented ITD and ILD cues. Exp-poirier, exp-stitt, and exp-parseihian used a similar ITD adjustment scheme, slightly improved in its last iteration for exp-poirier compared to that of exp-stitt, itself an incrementation on that of exp-parseihian. As such, the progression of initial lateral errors between grp-parse-worst, grp-stitt-worst, and grp-poirier-best can be expected. The performance of grp-steadman-random, on par with that of participants using ITD-adjusted or individual HRTFs, could be either attributed to the small number of evaluation positions (similar to that used during training), or to the 1.6 s burst and voice stimulus used as compared to the 180 ms to 500 ms burst trains used in the other experiments.
Figure 11.
(a) local lateral error, and (b) local lateral compression evolution across sessions and experiments.
Participants trained with individual HRTF did not improve much on local lateral error overall, starting at ≈11° after the first training session and only improving to at ≈9° after the last. Comparison of performance evolution between groups training with a worst-match HRTF (grp-parse-worst and grp-stitt-worst) against that of groups training with a best-match HRTF (grp-parse-best and grp-poirier-best) suggests a positive impact of HRTF quality on potential local lateral error improvement. It would also seem that the ITD adjustment applied in exp-parseihian and exp-stitt was not sufficient to compensate for poor HRTF quality regarding lateral localisation accuracy.
Focusing on local lateral compression evolution, Figure 11b reveals a systematic over-estimation of the lateral angle across experiments, i.e. participants overall reported targets closer to the inter-aural axis poles than they truly were. Analysis of session 2, after the first training session, indicates that 62% of the 73 participants presented an overall lateral compression of less than −5°, against only 4% presenting one above 5°.
Local polar error evolution across sessions for all experiments is reported in Figure 12a. Overall performance was still a function of HRTF quality, but for grp-parse-indiv poor performance prior to training and grp-steadman-random, on par with exp-stitt and exp-majdak control groups using individual HRTFs. The impact of training is hardly more pronounced than that observed on local lateral error. Training still helped lower local polar error overall, with even participants using individual HRTFs slightly improving during training: grp-stitt-indiv and grp-majdak-indiv gained ≈3° in local polar accuracy over the course of training, roughly identical to the improvement observed on local lateral accuracy. Note here that an analysis based on the overall polar error, i.e. taking into account confusions, would have suggested ≈12° improvement after training for these two groups. Finally, most of the improvement on local polar error occurred during the early stage of the training, decreasing of ≈7° between sessions 1 and 2 in average over all experiments, not considering exp-stitt and exp-majdak as participants were not tested prior to training, and of only ≈7° between sessions 2 and 4.
Figure 12.
Participants (a) local polar error, and (b) local elevation compression across training sessions and experiments.
The analysis of local elevation compression also reveals a stronger tendency to under-estimate target elevation, i.e. responses closer to the horizontal plane than the true target, than that observed on local lateral compression. Across experiments, 38% of the 73 participants presented a local elevation compression of more than 5° after the first training session, compared to 14% for elevation dilation. A trend suggests that local elevation compression is quickly corrected during the first training session and remains at a relatively constant value regardless of the method or number of training sessions. The surprisingly high plateau reached by grp-majdak-indiv compared to grp-stitt-indiv, also training on individual HRTFs, could be attributed to the the difference in tested grid positions: exp-majdak presented far more targets near the 90° elevation pole than exp-stitt.
4.2.7 Decompose the analysis across sphere regions
This section illustrates how splitting results analysis across sphere regions might highlight spatial imbalances in performance. To avoid further cluttering the chapter, only two example decompositions will be presented: confusion rates based on sphere regions, and local great-circle error based on individual target locations.
Decomposition of confusion rates based on the regions defined in Section 3.1.6 is illustrated Figure 13. Results displayed are aggregated over all five studies, to focus the analysis on general binaural localisation behaviours. The first noticeable result is that targets in the front-down region were the most susceptible to front-back and in-cone confusions initially, resulting in a very low precision rate (30% vs. 47% and more for the other regions) prior to the first training session. Interestingly, confusion rates in the front-down region were systematically higher than those in the front-up region, for all but off-cone confusions. The initial rate of front-back confusions of targets in front of participants, more than twice that of targets behind them, is likely due to the absence of visual feedback during the localisation task, increasing likelihood of perceiving a sound as behind if they cannot see its source, regardless of HRTF cues.
Figure 13.
Evolution of confusion rates across sessions, decomposed based on sphere regions, aggregated over all experiments.
A second interesting result is the negligible evolution of front-back confusions for targets in the back regions throughout training (i.e. back-to-front). While the precision rate of all regions increased, and front-back confusions dropped for front regions, training seemed to have no impact on front-back rates in the back region. Analysis of per-region accuracy however revealed that the local great-circle error decreased evenly across regions, from ≈25° in session 1 to ≈21° in session 11.
These observations suggest that future training programs could be improved by focusing slightly more on reducing front-back and in-cone confusions in the front-down region. Stagnating rates, such as that of front-back confusions in the back-up region, around 15% across sessions, would also suggest that there is room for improvement in the design of didactic training programs that would aid participants towards reaching 0% confusion rates.
Further refining the analysis, Figure 14 focuses on the assessment of mean response locations for each target presented in exp-poirier. Mean response locations were obtained by summing local great-circle error vectors as discussed in Section 3.2.6. Their positions relative to targets, and the evolution of these positions during training, provides a thorough characterisation of participant’s local accuracy evolution on the sphere. Additionally, the lateral and elevation compression effects observed in Section 4.2.6 are clearly visible, where mean responses are generally biased towards the interaural axes and/or the horizontal plane.
Figure 14.
Evolution of mean response locations across targets and sessions in exp-poirier. Hollow circles represent target positions. Filled circles represent mean response locations, surrounded by standard error ellipses computed using Kent distributions.
4.2.8 Handling initial performance offsets
This additional step in the analysis can be seen as an extension of the evaluation task characterisation proposed in Section 4.2.2 specific to the assessment of localisation performance evolution. It presents some of the techniques that exist to compare said evolution despite unbalanced initial conditions across studies or groups of participants.
Techniques have been proposed to conduct training efficiency analysis on unbalanced initial conditions. Stitt et al. [10] for example applied per-participant arithmetic normalisation, based on group baseline performances. Realigning initial conditions, this technique allows to focus the analysis on relative improvement, as illustrated in Figure 15.
Figure 15.
Great-circle error evolution across sessions and experiments. Data normalised (subtraction) with group mean results of session 2 as reference.
Another technique for relative improvement comparison, used for example by Majdak et al. [31] and Poirier-Quinot and Katz [9], is to compare the coefficients of a regression applied on performance evolution. As mentioned in Section 2.3.2, two main regression models have been adopted to fit said evolution depending on the training stages represented in the data. Figure 16 illustrates how both can be fitted to local great-circle error evolution across experiments. Groups performance evolution was first fitted to the exponential form in Figure 16a, resorting to the linear form in (b) when the evolution did not follow an exponential form, resulting in regression parameters CIs so wide as to prevent any meaningful interpretation. The use of a regression is particularly attractive, as it reduces the performance evolution analysis to a simple high level coefficient comparison, coefficients that can usually be interpreted in simple terms such as initial performance or improvement rate.
Figure 16.
Regressions on local great-circle error evolution across training and experiments, (a) exponential regression “y0×exp−sessionID/τ+c”, and (b) linear regression “a×sessionID+b”. y0 represents the initial performance, τ the improvement time constant, and c the long term performance. b represents the initial performance, a the improvement rate.
As mentioned, these techniques are generally applied to compensate for unbalanced initial performance. Although they are perfectly valid to assess the impact of HRTF quality or training efficiency on relative improvement, the scope of any conclusion made using them is greatly limited as the potential improvement margin naturally depends on initial performance.
4.3 Discussion
As illustrated throughout Section 4.2, drawing clear cut conclusions from the comparison of results from several studies is difficult at best. Most of the time, it is simply impossible, generally because of uncontrolled variations across test conditions. These variations, limiting both intra- and inter-study analysis, are discussed in this section.
4.3.1 Evaluation task
Variations in the evaluation protocols and procedures between studies in the literature present a challenge for comparing the multiple experiments. Different experimental design choices, such as reporting method, spectral content and duration of the stimulus, and evaluation grid, have a direct impact on the baseline performance of participants [32]. For example, given the choice by exp-steadman to use a random-match HRTF, the notable results of grp-steadman-random compared to those of the other groups could be attributed to the training program. However, the 1.6 sec stimulus (that may have enabled the use of head movements during the evaluation) may also have contributed to the improved performance of grp-steadman-random compared to the other studies that used 180 or 500 ms bursts [46].
The use of a unique grid for localisation tasks across studies would assuredly simplify results comparisons. Said grid could, for example, be designed to be homogeneously distributed on the sphere [35]. For more flexible test conditions, a series of test grids of increasing point densities could be defined, where test positions of any given grid would be present on its higher density neighbours, easing down-sampling for comparison. Regarding the stimulus used or the reporting method, a simple solution would be to settle on those that respectively optimise localisation accuracy [47] and minimise reporting bias [32]. Pending the adoption of common practices, the bias induced by those design choices could technically be assessed from the results of a control group using individual HRTFs.
Another issue when comparing performance evolution across studies is the alignment of the evaluation sessions for fair comparison. As proposed in Section 4.2.1, a simple solution is to align them based on training duration. Time alignment would seem a better option than its alternative, based on the number of positions presented during the training. Time is of direct interest for end-users, and an alignment based on presented positions would bias the analysis in favour of slower exploratory training paradigms.
Finally, the merging of both evaluation and training sessions, as used in exp-majdak, is not ideal in the context of inter-study comparison. Although this practice allows for a more granular analysis of performance evolution, it systematically leads to confusing analysis compared to studies alternating between training and evaluation sessions. Additionally, it would seem that the alternating design imposes a lesser constraint on the training paradigm itself, allowing for implicit learning strategies not focused on target localisation [48].
4.3.2 Intra- and inter-participant variations
Variations between participants’ performance is an issue common to most psychophysical studies studies. Two aspects of these variations can become critical in the context of HRTF learning studies.
The first aspect concerns imbalances in initial participant performance across tested conditions. As discussed in Section 4.2.8, such imbalance is likely to weaken or void conclusions resulting from the analysis. For within experiment comparisons, a simple solution is to run a pre-training evaluation session, to then create groups of equivalent performance based on the metrics used in the analysis. The problem naturally worsens when dealing with inter-study analysis. The use of a control group using individual HRTF is again advised to serve as a baseline reference for the comparative analysis.
The second aspect concerns the difference in participants’ immediate sensitivity to HRTF quality, and their ability to adapt to a non-individual HRTF. Both have been discussed in previous studies, where some participants were more prone to instantly benefit from a best-match HRTF [49] or to adapt to a poorly matched HRTF [10]. To avoid missing out on interesting behaviours due to the variance introduced by some participants, it is recommended to conduct a second pass of the analysis on sub-groups, for example aggregated based on their improvement rate [10]. Although the conclusions from the sub-group analysis may be weaker compared to an overall analysis, the technique provides readers with a more thorough understanding of the training as well as the potential advantages and limitations of the tested conditions.
4.3.3 Procedural versus perceptual learning
In the present context, procedural learning refers to participants becoming familiar with the various aspects of the localisation task, resulting in a performance improvement that is not due to an accommodation to HRTF specific cues (perceptual learning). As of yet, there exists no model for a posteriori dissociating the contribution of both types of learning to performance evolution. Intra-study comparisons would most likely not be affected since one could generally assume that the procedural learning has a similar impact on all tested conditions. However, by not allowing the procedural learning to plateau before the first evaluation, the generalisation of a study conclusions become problematic when one needs to compare the results from various studies based on different protocols.
Results of control groups generally prove extremely valuable during inter-study comparison. Participants only taking part in the evaluation and not the training, as in exp-steadman, can provide a good insight on the impact of the evaluation task implementation on performance across experiments. Even better, the inclusion of a control group using their own HRTF, as in exp-stitt and exp-parseihian, provides a solid baseline to dissociate procedural from perceptual learning during both intra- and inter-study analysis.
Additionally, simple experimental design choices can be applied to avoid having to deal with certain forms of procedural training. The proprioceptive adjustment required for accurately reporting perceived positions [14] can for example be greatly accelerated by using a natural 3D reporting method coupled to a visual pointer [9], as well as providing a reference grid to help orientation in the sphere [31]. Thorough beta testing can further eliminate design flaws that participants can exploit to improve their performance, such as the use of too small a set of test positions, or unconstrained tracking allowing for small head movements during the stimulus presentation phase of the localisation task.
Other aspects of procedural training, such as having participants focus on the listening task, can only be removed by introducing a pre-experimental training session. Such a session was applied in exp-majdak, where participants trained for approximately 30 min on a localisation task coupling visual feedback and stereo panning. This pre-experimental training likely contributed to the smooth improvement in great-circle error by grp-majdak-indiv from session 2 onward compared to the disjointed improvement observed for grp-stitt-indiv between sessions 2 and 3 in Figure 6. Paradoxically, the only limitation of the pre-training proposed in exp-majdak, which did not use actual binaural signals, is that it does not familiarise participants with binaural rendering. Pending formal evidence, one may assume that there exists an adaptation process during which participants will grow consistent in their localisation estimation, even in the absence of feedback, much like the effect observed on HRTF quality ratings reported by Andreopoulou and Katz [50]. Regardless of whether this adaptation should be labelled as perceptual or procedural training, it will still interfere with the evaluation of training efficiency itself.
Overall, it is reasonable to assume that one could design a pre-training session that accommodates procedural learning in roughly 15 min, even taking into account this last point, and relaxing the time constraint imposed in exp-majdak. This session however still takes a non-negligible amount of time, which will contribute to participant fatigue and loss of focus. Because of this, it is likely that most experimental designs will continue to include aspects of procedural learning as a shared effect, equally impacting all tested conditions. An alternative solution would be to conduct a set of studies to measure and model the various aspects of procedural learning in the present context, so that its contribution to performance evolution could be dissociated from that of perceptual improvement even in the absence of a pre-training session.
5. Conclusion
This chapter presented a methodology for the assessment of auditory localisation accuracy in the context of HRTF selection and learning tasks. Based on existing metrics and decomposition schemes, the methodology consists of a series of steps guiding analysis towards the creation of comprehensive and repeatable performance assessments. A collected case-study was then proposed that compared the results of five contemporary experiments on HRTF learning and illustrates how the methodology can be applied to better understand participant performances and their evolution.
The initial intent of this chapter was to propose a set of metrics and an analysis workflow that would be adopted and adapted by the community to standardise the evaluation of localisation performance. In time, the standardisation would help simplify the comparison of results from different studies, allowing to assess hypotheses and draw conclusions beyond the scope of the constituting studies. While the proposed case-study provides a glimpse at the benefits of such standardisation, it is limited by one of, if not the most, major issue of inter-study comparison: the lack of a reference between tested conditions. Without this reference, conclusions drawn from the analysis can hardly be generalised, much like those that would result from a comparison between language learning techniques without a priori knowledge of participants learning abilities, or how different is the language learnt compared to their mother tongue.
As of now, the only applicable solution to provide such reference across studies is to systematically add a control group composed of participants using their own HRTF to the experiment. A large enough group composed of experts and novices alike would indeed provide a stable reference that can be used to assert a certain equivalence in e.g. the evaluation task before proceeding to inter-study performance comparison. However, this solution is rarely practical due to the complexity of the HRTF measurement process, which is the main incentive for HRTF learning in the first place. A somewhat less constraining, yet highly unlikely, scenario would be the creation and adoption of a unique evaluation platform, shared across all studies to formalise future HRTF selection methods and training program comparisons.
With luck, the issue will solve itself as the next generation of HRTF individualisation techniques render selection and training obsolete. In the meantime, methodologies such as the one proposed here should help improve the rigour of studies and consequently the understanding of the fundamental issues regarding auditory localisation and spatial hearing accommodation to non-individual HRTFs and their applications.
Acknowledgments
This work was funded in part through a fundamental research collaboration partnership between Sorbonne Université, CNRS, Institut ∂’ Alembert and Facebook Reality Labs. This work was funded in part by the RASPUTIN project (ANR-18-CE38-0004, https://rasputin.lam.jussieu.frrasputin.lam.jussieu.fr) and an associated “Innov’up Faisabilité” grant from the Région Île de France. Portions of this work have been carried out in the context of the Sonicom project, that has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No. 101017743.
\n',keywords:"spatial hearing, binaural, localisation accuracy, evaluation, HRTF selection, HRTF training",chapterPDFUrl:"https://cdn.intechopen.com/pdfs/81900.pdf",chapterXML:"https://mts.intechopen.com/source/xml/81900.xml",downloadPdfUrl:"/chapter/pdf-download/81900",previewPdfUrl:"/chapter/pdf-preview/81900",totalDownloads:58,totalViews:0,totalCrossrefCites:0,dateSubmitted:null,dateReviewed:"April 14th 2022",datePrePublished:"May 22nd 2022",datePublished:null,dateFinished:"May 22nd 2022",readingETA:"0",abstract:"Through a review of the current literature, this chapter defines a methodology for the analysis of HRTF localisation performance, as applied to assess the quality of an HRTF selection or learning program. A case study is subsequently proposed, applying this methodology to a cross-comparison on the results of five contemporary experiments on HRTF learning. 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State of the art",level:"1"},{id:"sec_4_2",title:"2.1 Analysis based on angular distances",level:"2"},{id:"sec_4_3",title:"2.1.1 Egocentric coordinate systems",level:"3"},{id:"sec_5_3",title:"2.1.2 Azimuth, elevation, lateral, and polar errors",level:"3"},{id:"sec_6_3",title:"2.1.3 Compensating for spatial compression",level:"3"},{id:"sec_7_3",title:"2.1.4 Using directional statistics to analyse sound localisation accuracy",level:"3"},{id:"sec_8_3",title:"2.1.5 Further high level metrics based on angular distances",level:"3"},{id:"sec_10_2",title:"2.2 Analysis based on confusions classification",level:"2"},{id:"sec_10_3",title:"2.2.1 Confusions classification",level:"3"},{id:"sec_11_3",title:"2.2.2 Separating angular and confusions errors contributions",level:"3"},{id:"sec_13_2",title:"2.3 Additional analysis methods",level:"2"},{id:"sec_13_3",title:"2.3.1 Decomposing the analysis across sphere regions",level:"3"},{id:"sec_14_3",title:"2.3.2 Performance evolution modelling and analysis",level:"3"},{id:"sec_17",title:"3. 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Case study",level:"1"},{id:"sec_32_2",title:"4.1 Study selection overview",level:"2"},{id:"sec_32_3",title:"4.1.1 Study description: exp-majdak",level:"3"},{id:"sec_33_3",title:"4.1.2 Study description: exp-parseihian",level:"3"},{id:"sec_34_3",title:"4.1.3 Study description: exp-stitt",level:"3"},{id:"sec_35_3",title:"4.1.4 Study description: exp-steadman",level:"3"},{id:"sec_36_3",title:"4.1.5 Study description: exp-poirier",level:"3"},{id:"sec_38_2",title:"4.2 Application of the methodology",level:"2"},{id:"sec_38_3",title:"4.2.1 Time alignment of evaluation sessions",level:"3"},{id:"sec_39_3",title:"4.2.2 Evaluation task characterisation",level:"3"},{id:"sec_40_3",title:"4.2.3 Assessing the global extent of localisation error",level:"3"},{id:"sec_41_3",title:"4.2.4 Assessing the critical localisation confusions",level:"3"},{id:"sec_42_3",title:"4.2.5 Assessing the local extent of localisation error",level:"3"},{id:"sec_43_3",title:"4.2.6 Horizontal and vertical decomposition of the localisation error",level:"3"},{id:"sec_44_3",title:"4.2.7 Decompose the analysis across sphere regions",level:"3"},{id:"sec_45_3",title:"4.2.8 Handling initial performance offsets",level:"3"},{id:"sec_47_2",title:"4.3 Discussion",level:"2"},{id:"sec_47_3",title:"4.3.1 Evaluation task",level:"3"},{id:"sec_48_3",title:"4.3.2 Intra- and inter-participant variations",level:"3"},{id:"sec_49_3",title:"4.3.3 Procedural versus perceptual learning",level:"3"},{id:"sec_52",title:"5. 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DOI: 10.1016/j.apacoust.2006.08.007'},{id:"B29",body:'Martin RL, McAnally KI, Senova MA. Free-field equivalent localization of virtual audio. Journal of the Audio Engineering Society. 2001;49(1/2):14-22'},{id:"B30",body:'Yamagishi D, Ozawa K. Effects of timbre on learning to remediate sound localization in the horizontal plane. In: Principles and Applications of Spatial Hearing. Singapore: World Scientific; 2011. pp. 61-70'},{id:"B31",body:'Majdak P, Walder T, Laback B. Effect of long-term training on sound localization performance with spectrally warped and band-limited head-related transfer functions. The Journal of the Acoustical Society of America. 2013;134(3):2148-2159. DOI: 10.1121/1.4816543'},{id:"B32",body:'Bahu H, Carpentier T, Noisternig M, Warusfel O. Comparison of different egocentric pointing methods for 3D sound localization experiments. Acta Acustica. 2016;102(1):107-118. DOI: 10.3813/AAA.918928'},{id:"B33",body:'Klein F, Werner S. Auditory adaptation to non-individual HRTF cues in binaural audio reproduction. Journal of the Audio Engineering Society. 2016;64(1/2):45-54'},{id:"B34",body:'Van Oosterom A, Strackee J. The solid angle of a plane triangle. IEEE Transactions on Biomedical Engineering. 1983;2:125-126. DOI: 10.1109/TBME.1983.325207'},{id:"B35",body:'Saff EB, Kuijlaars AB. Distributing many points on a sphere. The Mathematical Intelligencer. 1997;19(1):5-11'},{id:"B36",body:'Middlebrooks JC, Green DM. Sound localization by human listeners. Annual Review of Psychology. 1991;42(1):135-159'},{id:"B37",body:'Rayleigh L. XII. On our perception of sound direction. The London, Edinburgh, and Dublin Philosophical Magazine and Journal of Science. 1907;13(74):214-232. DOI: 10.1080/14786440709463595'},{id:"B38",body:'Best V, Brungart D, Carlile S, Jin C, Macpherson E, Martin R, et al. A meta-analysis of localization errors made in the anechoic free field. In: Principles and Applications of Spatial Hearing. Singapore: World Scientific; 2011. pp. 14-23'},{id:"B39",body:'Cumming G. The new statistics: Why and how. Psychological Science. 2014;25(1):7-29. DOI: 10.1177/0956797613504966'},{id:"B40",body:'Andreopoulou A, Katz BFG. Subjective HRTF evaluations for obtaining global similarity metrics of assessors and assessees. Journal of Multimodal User Interfaces. 2016b;10(3):259-271. DOI: 10.1007/s12193-016-0214-y'},{id:"B41",body:'Katz BFG, Parseihian G. Perceptually based head-related transfer function database optimization. The Journal of the Acoustical Society of America. 2012;131(2):99-105. DOI: 10.1121/1.3672641'},{id:"B42",body:'Warusfel O. IRCAM Listen HRTF Database. 2003. Available from: http://recherche.ircam.fr/equipes/salles/listen [Accessed: Sepember 29, 2018]'},{id:"B43",body:'Dramas F, Katz BFG, Jouffrais C. Auditory-guided reaching movements in the peripersonal frontal space. The Journal of the Acoustical Society of America. 2008;123(5):3723-3723. DOI: 10.1121/1.2935195'},{id:"B44",body:'Kumpik DP, Kacelnik O, King AJ. Adaptive reweighting of auditory localization cues in response to chronic unilateral earplugging in humans. The Journal of Neuroscience. 2010;30(14):4883-4894. DOI: 10.1523/JNEUROSCI.5488-09.2010'},{id:"B45",body:'Woodworth RS, Schlosberg H. Experimental Psychology. Rev. ed. Oxford, England: Holt; 1954'},{id:"B46",body:'Wallach H. The role of head movements and vestibular and visual cues in sound localization. Journal of Experimental Psychology. 1940;27(4):339-368'},{id:"B47",body:'Begault DR, Wenzel EM, Anderson MR. Direct comparison of the impact of head tracking, reverberation, and individualized head-related transfer functions on the spatial perception of a virtual speech source. Journal of the Audio Engineering Society. 2001;49(10):904-916'},{id:"B48",body:'Mendonça C. A review on auditory space adaptations to altered head-related cues. Frontiers in Neuroscience. 2014;8(219):1-14. DOI: 10.3389/fnins.2014.00219'},{id:"B49",body:'Poirier-Quinot D, Katz BFG. Assessing the impact of head-related transfer function individualization on performance: Case of a virtual reality shooter game. The Journal of the Audio Engineering Society. 2020;68(4):248-260. DOI: 10.17743/jaes.2020.0004'},{id:"B50",body:'Andreopoulou A, Katz B. Investigation on subjective HRTF rating repeatability. In: Audio Engineering Society Convention. Vol. 140. New York, United States: Audio Engineering Society; 2016. pp. 9597:1-9597:959710'}],footnotes:[{id:"fn1",explanation:"We use the term individual to identify the HRTF of the user, individualised or personalised to indicated an HRTF modified or selected to best accommodate the user, and non-individual or non-individualised to indicate an HRTF that has not been tailored to the user. A so-called generic or dummy-head HRTF are specific instances of non-individual HRTFs."},{id:"fn2",explanation:"MATLAB auditory localisation evaluation toolbox: https://hal.archives-ouvertes.fr/hal-03265190."}],contributors:[{corresp:null,contributorFullName:"David Poirier-Quinot",address:null,affiliation:'
Sciences et Technologies de la Musique et du Son (STMS)—IRCAM, CNRS, Sorbonne Université, France
'},{corresp:null,contributorFullName:"Martin S. Lawless",address:null,affiliation:'
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The proportion of sp2 (graphetically) and sp3 (diamond-like) determines the properties of the DLC. This coating can be applied to automobile engine component in an attempt to provide energy efficiency by reducing friction and wear. However, DLC coatings are faced with issues of thermal instability caused by increasing temperature in the combustion engine of a vehicle. Therefore, it became necessary to seek ways of improving this coating to meetup with all tribological requirements that will be able to resist transformational change of the coating as the temperature increases. This chapter discusses the need for diamond-like carbon coatings for automobile engine applications, due to their ultra-low friction coefficient (<0.1) and excellent wear resistance (wear rate ~ 7 x 10−17 m3/N.m). The importance of DLC coatings deposited using PECVD technique, their mechanical and tribological properties at conditions similar to automobile engines would also be discussed. Non-metallic (hydrogen, boron, nitrogen, phosphorus, fluorine and sulfur) or metals (copper, nickel, tungsten, titanium, molybdenum, silicon, chromium and niobium) has been used to improve the thermal stability of DLC coatings. Recently, incorporation of Ag nanoparticles, TiO2 nanoparticles, WO3 nanoparticles and MoO3 nanoparticles into DLC has been used. The novel fabrication of diamond-like carbon coatings incorporated nanoparticles (WO3/MoO3) using PECVD for automobile applications has shown an improvement in the adhesion properties of the DLC coatings. DLC coatings had a critical load of 25 N, while after incorporating with WO3/MoO3 nanoparticles had critical load at 32 N and 39 N respectively.",signatures:"Funsho Olaitan Kolawole, Shola Kolade Kolawole, Luis Bernardo Varela, Adebayo Felix Owa, Marco Antonio Ramirez and André Paulo Tschiptschin",authors:[{id:"253841",title:"Dr.",name:"Shola",surname:"Kolawole",fullName:"Shola Kolawole",slug:"shola-kolawole",email:"sholak190e@yahoo.com"},{id:"330793",title:"Dr.",name:"Funsho",surname:"Kolawole",fullName:"Funsho Kolawole",slug:"funsho-kolawole",email:"fkopresido@yahoo.com"},{id:"330804",title:"Dr.",name:"Luis Bernardo",surname:"Varela",fullName:"Luis Bernardo Varela",slug:"luis-bernardo-varela",email:"luisbv@yahoo.com"},{id:"330841",title:"Prof.",name:"Marco Antonio",surname:"Ramirez",fullName:"Marco Antonio Ramirez",slug:"marco-antonio-ramirez",email:"maarmie@yahoo.com"},{id:"330842",title:"Dr.",name:"Adebayo",surname:"Owa",fullName:"Adebayo Owa",slug:"adebayo-owa",email:"adebayo.owa@fuoye.edu.ng"},{id:"330843",title:"Prof.",name:"André Paulo",surname:"Tschiptschin",fullName:"André Paulo Tschiptschin",slug:"andre-paulo-tschiptschin",email:"adnryp@yahoo.com"}],book:{id:"10257",title:"Engineering Applications of Diamond",slug:"engineering-applications-of-diamond",productType:{id:"1",title:"Edited Volume"}}}],collaborators:[{id:"251217",title:"Prof.",name:"Tatsuhiko",surname:"Aizawa",slug:"tatsuhiko-aizawa",fullName:"Tatsuhiko Aizawa",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:null},{id:"253841",title:"Dr.",name:"Shola",surname:"Kolawole",slug:"shola-kolawole",fullName:"Shola Kolawole",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:null},{id:"289331",title:"Mr.",name:"Tadahiko",surname:"Inohara",slug:"tadahiko-inohara",fullName:"Tadahiko Inohara",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:null},{id:"330804",title:"Dr.",name:"Luis Bernardo",surname:"Varela",slug:"luis-bernardo-varela",fullName:"Luis Bernardo Varela",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:null},{id:"330841",title:"Prof.",name:"Marco Antonio",surname:"Ramirez",slug:"marco-antonio-ramirez",fullName:"Marco Antonio Ramirez",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:null},{id:"330842",title:"Dr.",name:"Adebayo",surname:"Owa",slug:"adebayo-owa",fullName:"Adebayo Owa",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Federal University Oye Ekiti",institutionURL:null,country:{name:"Nigeria"}}},{id:"330843",title:"Prof.",name:"André Paulo",surname:"Tschiptschin",slug:"andre-paulo-tschiptschin",fullName:"André Paulo Tschiptschin",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:null},{id:"335289",title:"Dr.",name:"Huijie",surname:"Zheng",slug:"huijie-zheng",fullName:"Huijie Zheng",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:null},{id:"339213",title:"Dr.",name:"Arne",surname:"Wickenbrock",slug:"arne-wickenbrock",fullName:"Arne Wickenbrock",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:null},{id:"339231",title:"Prof.",name:"Dmitry",surname:"Budker",slug:"dmitry-budker",fullName:"Dmitry Budker",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:null}]},generic:{page:{slug:"prior-publication-policy",title:"Prior Publication Policy",intro:"
The Internet has irrevocably changed the dynamics of scholarly communication and publishing. Consequently, we find it necessary to indicate, unambiguously, our definition of what we consider to be a published scientific work.
A significant number of working papers, early drafts, and similar work in progress are openly shared online between members of the scientific community. It has become common to announce one’s own research on a personal website or a blog to gather comments and suggestions from other researchers. Such works and online postings are, indeed, published in the sense that they are made publicly available. However, this does not mean that if submitted for publication by IntechOpen they are not original works. We differentiate between reviewed and non-reviewed works when determining whether a work is original and has been published in a scholarly sense or not.
\\n\\n
The significance of Peer Review cannot be overstated when it comes to defining, in our terms, what constitutes a published scientific work. Peer Review is widely considered to be the cornerstone of modern publishing processes and the key value-adding contribution to a scholarly manuscript that a publisher can make.
\\n\\n
Other than the issue of originality, research misconduct is another major issue that all publishers have to address. IntechOpen’s Retraction & Correction Policy and various publication ethics guidelines identify both redundant publication and (self)plagiarism to fall within the definition of research misconduct, thus constituting grounds for rejection or the issue of a Retraction if the work has already been published.
\\n\\n
In order to facilitate the tracking of a manuscript’s publishing history and its development from its earliest draft to the manuscript submitted, we encourage Authors to disclose any instances of a manuscript’s prior publication, whether it be through a conference presentation, a newspaper article, a working paper publicly available in a repository or a blog post.
\\n\\n
A note to the Academic Editor containing detailed information about a submitted manuscript’s previous public availability is the preferred means of reporting prior publication. This helps us determine if there are any earlier versions of a manuscript that should be disclosed to our readers or if any of those earlier versions should be cited and listed in a manuscript’s references.
\\n\\n
Some basic information about the editorial treatment of different varieties of prior publication is laid out below:
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1. CONFERENCE PAPERS & PRESENTATIONS
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Given that conference papers and presentations generally pass through some sort of peer or editorial review, we consider them to be published in the accepted scholarly sense, particularly if they are published as a part of conference proceedings.
\\n\\n
All submitted manuscripts originating from a previously published conference paper must contain at least 50% of new original content to be accepted for review and considered for publication.
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Authors are required to report any links their manuscript might have with their earlier conference papers and presentations in a note to the Academic Editor, as well as in the manuscript itself. Additionally, Authors should obtain any necessary permissions from the publisher of their conference paper if copyright transfer occurred during the publishing process. Failure to do so may prevent Us from publishing an otherwise worthy work.
\\n\\n
2. NEWSPAPER & MAGAZINE ARTICLES
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Newspaper and magazine articles usually do not pass through any extensive peer or editorial review and we do not consider them to be published in the scholarly sense. Articles appearing in newspapers and magazines rarely possess the depth and structure characteristic of scholarly articles.
\\n\\n
Submitted manuscripts stemming from a previous newspaper or magazine article will be accepted for review and considered for publication. However, Authors are strongly advised to report any such publication in an accompanying note to the External Editor.
\\n\\n
As with the conference papers and presentations, Authors should obtain any necessary permissions from the newspaper or magazine that published the work, and indicate that they have done so in a note to the External Editor.
\\n\\n
3. GREY LITERATURE
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White papers, working papers, technical reports and all other forms of papers which fall within the scope of the ‘Luxembourg definition’ of grey literature do not pass through any extensive peer or editorial review and we do not consider them to be published in the scholarly sense.
\\n\\n
Although such papers are regularly made publicly available via personal websites and institutional repositories, their general purpose is to gather comments and feedback from Authors’ colleagues in order to further improve a manuscript intended for future publication.
\\n\\n
When submitting their work, Authors are required to disclose the existence of any publicly available earlier drafts in a note to the Academic Editor. In cases where earlier drafts of the submitted version of the manuscript are publicly available, any overlap between the versions will generally not be considered an instance of self-plagiarism.
\\n\\n
4. SOCIAL MEDIA, BLOG & MESSAGE BOARD POSTINGS
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We feel that social media, blogs and message boards are generally used with the same intention as grey literature, to formulate ideas for a manuscript and gather early feedback from like-minded researchers in order to improve a particular piece of work before submitting it for publication. Therefore, we do not consider such internet postings to be publication in the scholarly sense.
\\n\\n
Nevertheless, Authors are encouraged to disclose the existence of any internet postings in which they outline and describe their research or posted passages of their manuscripts in a note to the Academic Editor. Please note that we will not strictly enforce this request in the same way that we would instructions we consider to be part of our conditions of acceptance for publication. We understand that it may be difficult to keep track of all one’s internet postings in which the researcher´s current work might be mentioned.
\\n\\n
In cases where there is any overlap between the Author´s submitted manuscript and related internet postings, we will generally not consider it to be an instance of self-plagiarism. This also holds true for any co-Author as well.
A significant number of working papers, early drafts, and similar work in progress are openly shared online between members of the scientific community. It has become common to announce one’s own research on a personal website or a blog to gather comments and suggestions from other researchers. Such works and online postings are, indeed, published in the sense that they are made publicly available. However, this does not mean that if submitted for publication by IntechOpen they are not original works. We differentiate between reviewed and non-reviewed works when determining whether a work is original and has been published in a scholarly sense or not.
\n\n
The significance of Peer Review cannot be overstated when it comes to defining, in our terms, what constitutes a published scientific work. Peer Review is widely considered to be the cornerstone of modern publishing processes and the key value-adding contribution to a scholarly manuscript that a publisher can make.
\n\n
Other than the issue of originality, research misconduct is another major issue that all publishers have to address. IntechOpen’s Retraction & Correction Policy and various publication ethics guidelines identify both redundant publication and (self)plagiarism to fall within the definition of research misconduct, thus constituting grounds for rejection or the issue of a Retraction if the work has already been published.
\n\n
In order to facilitate the tracking of a manuscript’s publishing history and its development from its earliest draft to the manuscript submitted, we encourage Authors to disclose any instances of a manuscript’s prior publication, whether it be through a conference presentation, a newspaper article, a working paper publicly available in a repository or a blog post.
\n\n
A note to the Academic Editor containing detailed information about a submitted manuscript’s previous public availability is the preferred means of reporting prior publication. This helps us determine if there are any earlier versions of a manuscript that should be disclosed to our readers or if any of those earlier versions should be cited and listed in a manuscript’s references.
\n\n
Some basic information about the editorial treatment of different varieties of prior publication is laid out below:
\n\n
1. CONFERENCE PAPERS & PRESENTATIONS
\n\n
Given that conference papers and presentations generally pass through some sort of peer or editorial review, we consider them to be published in the accepted scholarly sense, particularly if they are published as a part of conference proceedings.
\n\n
All submitted manuscripts originating from a previously published conference paper must contain at least 50% of new original content to be accepted for review and considered for publication.
\n\n
Authors are required to report any links their manuscript might have with their earlier conference papers and presentations in a note to the Academic Editor, as well as in the manuscript itself. Additionally, Authors should obtain any necessary permissions from the publisher of their conference paper if copyright transfer occurred during the publishing process. Failure to do so may prevent Us from publishing an otherwise worthy work.
\n\n
2. NEWSPAPER & MAGAZINE ARTICLES
\n\n
Newspaper and magazine articles usually do not pass through any extensive peer or editorial review and we do not consider them to be published in the scholarly sense. Articles appearing in newspapers and magazines rarely possess the depth and structure characteristic of scholarly articles.
\n\n
Submitted manuscripts stemming from a previous newspaper or magazine article will be accepted for review and considered for publication. However, Authors are strongly advised to report any such publication in an accompanying note to the External Editor.
\n\n
As with the conference papers and presentations, Authors should obtain any necessary permissions from the newspaper or magazine that published the work, and indicate that they have done so in a note to the External Editor.
\n\n
3. GREY LITERATURE
\n\n
White papers, working papers, technical reports and all other forms of papers which fall within the scope of the ‘Luxembourg definition’ of grey literature do not pass through any extensive peer or editorial review and we do not consider them to be published in the scholarly sense.
\n\n
Although such papers are regularly made publicly available via personal websites and institutional repositories, their general purpose is to gather comments and feedback from Authors’ colleagues in order to further improve a manuscript intended for future publication.
\n\n
When submitting their work, Authors are required to disclose the existence of any publicly available earlier drafts in a note to the Academic Editor. In cases where earlier drafts of the submitted version of the manuscript are publicly available, any overlap between the versions will generally not be considered an instance of self-plagiarism.
\n\n
4. SOCIAL MEDIA, BLOG & MESSAGE BOARD POSTINGS
\n\n
We feel that social media, blogs and message boards are generally used with the same intention as grey literature, to formulate ideas for a manuscript and gather early feedback from like-minded researchers in order to improve a particular piece of work before submitting it for publication. Therefore, we do not consider such internet postings to be publication in the scholarly sense.
\n\n
Nevertheless, Authors are encouraged to disclose the existence of any internet postings in which they outline and describe their research or posted passages of their manuscripts in a note to the Academic Editor. Please note that we will not strictly enforce this request in the same way that we would instructions we consider to be part of our conditions of acceptance for publication. We understand that it may be difficult to keep track of all one’s internet postings in which the researcher´s current work might be mentioned.
\n\n
In cases where there is any overlap between the Author´s submitted manuscript and related internet postings, we will generally not consider it to be an instance of self-plagiarism. This also holds true for any co-Author as well.
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Pal is Professor of Physics at Mahindra École\nCentrale Hyderabad India since July 1st 2014 after retirement\nas Professor of Physics from IIT Delhi; Ph.D.’1975 from IIT\nDelhi; Fellow of OSA and SPIE; Senior Member IEEE;\nHonorary Foreign Member Royal Norwegian Society for\nScience and Arts; Member OSA Board of Directors (2009-\n11); Distinguished Lecturer IEEE Photonics Society (2005-\n07).",institutionString:null,institution:{name:"Indian Institute of Technology Delhi",country:{name:"India"}}},{id:"69653",title:"Dr.",name:"Chusak",middleName:null,surname:"Limsakul",slug:"chusak-limsakul",fullName:"Chusak Limsakul",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Prince of Songkla University",country:{name:"Thailand"}}},{id:"23804",title:"Dr.",name:"Hamzah",middleName:null,surname:"Arof",slug:"hamzah-arof",fullName:"Hamzah Arof",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/23804/images/5492_n.jpg",biography:"Hamzah Arof received his BSc from Michigan State University, and PhD from the University of Wales. 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Currently he is affiliated with the Department of Electrical Engineering, University of Malaya, Malaysia.",institutionString:null,institution:{name:"University of Malaya",country:{name:"Malaysia"}}},{id:"41989",title:"Prof.",name:"He",middleName:null,surname:"Tian",slug:"he-tian",fullName:"He Tian",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"East China University of Science and Technology",country:{name:"China"}}},{id:"33351",title:null,name:"Hendra",middleName:null,surname:"Hermawan",slug:"hendra-hermawan",fullName:"Hendra Hermawan",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/33351/images/168_n.jpg",biography:null,institutionString:null,institution:{name:"Institut Teknologi Bandung",country:{name:"Indonesia"}}},{id:"11981",title:"Prof.",name:"Hiroshi",middleName:null,surname:"Ishiguro",slug:"hiroshi-ishiguro",fullName:"Hiroshi Ishiguro",position:null,profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRglaQAC/Profile_Picture_1626411846553",biography:"Hiroshi Ishiguro is an award-winning roboticist and innovator. 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Very young children are regular users of smartphones and tablet, so their early digital engagement poses new challenges to parent-child relationships and parental role. First, the chapter introduces the “digital parenting” construct, moving through the literature from “traditional” parenting styles to more recent studies on “parental mediation,” that is, the different behaviors parents adopt to regulate children’s engagement with the Internet and digital media. Second, the chapter reviews empirical researches on different parental mediation practices (active or restrictive behaviors) and how they are adjusted according to the child’s characteristics (age, digital competences, etc.) or parent’s media competence and beliefs. Finally, from a bidirectional perspective of parent-child relationships, the chapter discusses the role of youths’ social involvement, communication, self-disclosure, and digital skills on parent’s beliefs and practices. 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Very young children are regular users of smartphones and tablet, so their early digital engagement poses new challenges to parent-child relationships and parental role. First, the chapter introduces the “digital parenting” construct, moving through the literature from “traditional” parenting styles to more recent studies on “parental mediation,” that is, the different behaviors parents adopt to regulate children’s engagement with the Internet and digital media. Second, the chapter reviews empirical researches on different parental mediation practices (active or restrictive behaviors) and how they are adjusted according to the child’s characteristics (age, digital competences, etc.) or parent’s media competence and beliefs. Finally, from a bidirectional perspective of parent-child relationships, the chapter discusses the role of youths’ social involvement, communication, self-disclosure, and digital skills on parent’s beliefs and practices. 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A particular parenting style influences all phases of development and life style of adolescent. Helicopter parents overly protect their children from the difficulties by setting some set of instructions without consideration of the uniqueness of their children. Recent literature has got huge attention on this parenting style and debating the pros and cons on the development of child. Higher life satisfaction and better psychological wellbeing have been found in the children of highly intrusive parents. When there are positive effects of helicopter parenting, there are negative outcome and impacts that have also been studied. The difficulties in emotional regulation, academic productivity, and social skills among children raised by helicopter parenting have been reported in the literature. Low self-efficacy, lack of trust on peers, and alienation from peers have also been associated with helicopter parenting. The chapter highlights the associated aspects of childhood and adolescence, raised by helicopter parenting. As parents have their own concern about raising their children in certain manner, it is important to understand the underlying mechanism of parenting style. Therefore, this chapter also describes the theoretical framework. The associated mental health issues and supportive psychological intervention to be also discussed.",book:{id:"9043",slug:"parenting-studies-by-an-ecocultural-and-transactional-perspective",title:"Parenting",fullTitle:"Parenting - Studies by an Ecocultural and Transactional Perspective"},signatures:"Deepika Srivastav and M.N. 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Building solid healthy relationships at this stage of their lives is of utmost importance to help them cope with the changes and challenges they are experiencing. The purpose of this chapter is to explore the parent-adolescent relationship in the substance dependency field. The focus is on the relationship between parents and their adolescents who have a substance use disorder. Parenting adolescents poses its own set of challenges, making it difficult to build and maintain healthy parent-adolescent relationships. We argue that although adolescent substance use disorder has been extensively researched, the relationship between parents and adolescents with substance use disorder has surprisingly not received the same attention. It is this gap that this chapter seeks to address. With this in mind, the ecological systems theory was employed here to shed light on the importance and significance of developing healthy parent-adolescent relationships. 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\r\n\tTransforming our World: the 2030 Agenda for Sustainable Development endorsed by United Nations and 193 Member States, came into effect on Jan 1, 2016, to guide decision making and actions to the year 2030 and beyond. Central to this Agenda are 17 Goals, 169 associated targets and over 230 indicators that are reviewed annually. The vision envisaged in the implementation of the SDGs is centered on the five Ps: People, Planet, Prosperity, Peace and Partnership. This call for renewed focused efforts ensure we have a safe and healthy planet for current and future generations.
\r\n
\r\n\t
\r\n
\r\n\tThis Series focuses on covering research and applied research involving the five Ps through the following topics:
\r\n
\r\n\t
\r\n
\r\n\t1. Sustainable Economy and Fair Society that relates to SDG 1 on No Poverty, SDG 2 on Zero Hunger, SDG 8 on Decent Work and Economic Growth, SDG 10 on Reduced Inequalities, SDG 12 on Responsible Consumption and Production, and SDG 17 Partnership for the Goals
\r\n
\r\n\t
\r\n
\r\n\t2. Health and Wellbeing focusing on SDG 3 on Good Health and Wellbeing and SDG 6 on Clean Water and Sanitation
\r\n
\r\n\t
\r\n
\r\n\t3. Inclusivity and Social Equality involving SDG 4 on Quality Education, SDG 5 on Gender Equality, and SDG 16 on Peace, Justice and Strong Institutions
\r\n
\r\n\t
\r\n
\r\n\t4. Climate Change and Environmental Sustainability comprising SDG 13 on Climate Action, SDG 14 on Life Below Water, and SDG 15 on Life on Land
\r\n
\r\n\t
\r\n
\r\n\t5. Urban Planning and Environmental Management embracing SDG 7 on Affordable Clean Energy, SDG 9 on Industry, Innovation and Infrastructure, and SDG 11 on Sustainable Cities and Communities.
\r\n
\r\n\t
\r\n
\r\n\tThe series also seeks to support the use of cross cutting SDGs, as many of the goals listed above, targets and indicators are all interconnected to impact our lives and the decisions we make on a daily basis, making them impossible to tie to a single topic.
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He worked as a post-doctoral fellow at the Public Health Research Institute (PHRI), Newark, NJ for four years before accepting a three-year faculty position at Brigham Young University-Hawaii. Dr. Engohang-Ndong is a tenured faculty member with the academic rank of Full Professor at Kent State University, Ohio, where he teaches a wide range of biological science courses and pursues his research in medical and environmental microbiology. 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He has an excellent track record in the herpesvirus field, and his group is engaged in clinical research in the field of Epstein-Barr virus diseases. He is the editor of the online Encyclopedia of Environment and he coordinates the Universal Health Coverage education program for the BioHealth Computing Schools of the European Institute of Science.",institutionString:null,institution:{name:"Grenoble Alpes University",country:{name:"France"}}},{id:"131400",title:"Prof.",name:"Alfonso J.",middleName:null,surname:"Rodriguez-Morales",slug:"alfonso-j.-rodriguez-morales",fullName:"Alfonso J. Rodriguez-Morales",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/131400/images/system/131400.png",biography:"Dr. Rodriguez-Morales is an expert in tropical and emerging diseases, particularly zoonotic and vector-borne diseases (especially arboviral diseases). He is the president of the Travel Medicine Committee of the Pan-American Infectious Diseases Association (API), as well as the president of the Colombian Association of Infectious Diseases (ACIN). He is a member of the Committee on Tropical Medicine, Zoonoses, and Travel Medicine of ACIN. He is a vice-president of the Latin American Society for Travel Medicine (SLAMVI) and a Member of the Council of the International Society for Infectious Diseases (ISID). Since 2014, he has been recognized as a Senior Researcher, at the Ministry of Science of Colombia. He is a professor at the Faculty of Medicine of the Fundacion Universitaria Autonoma de las Americas, in Pereira, Risaralda, Colombia. He is an External Professor, Master in Research on Tropical Medicine and International Health, Universitat de Barcelona, Spain. He is also a professor at the Master in Clinical Epidemiology and Biostatistics, Universidad Científica del Sur, Lima, Peru. In 2021 he has been awarded the “Raul Isturiz Award” Medal of the API. Also, in 2021, he was awarded with the “Jose Felix Patiño” Asclepius Staff Medal of the Colombian Medical College, due to his scientific contributions to COVID-19 during the pandemic. He is currently the Editor in Chief of the journal Travel Medicine and Infectious Diseases. His Scopus H index is 47 (Google Scholar H index, 68).",institutionString:"Institución Universitaria Visión de las Américas, Colombia",institution:null},{id:"332819",title:"Dr.",name:"Chukwudi Michael",middleName:"Michael",surname:"Egbuche",slug:"chukwudi-michael-egbuche",fullName:"Chukwudi Michael Egbuche",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/332819/images/14624_n.jpg",biography:"I an Dr. Chukwudi Michael Egbuche. I am a Senior Lecturer in the Department of Parasitology and Entomology, Nnamdi Azikiwe University, Awka.",institutionString:null,institution:{name:"Nnamdi Azikiwe University",country:{name:"Nigeria"}}},{id:"284232",title:"Mr.",name:"Nikunj",middleName:"U",surname:"Tandel",slug:"nikunj-tandel",fullName:"Nikunj Tandel",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/284232/images/8275_n.jpg",biography:'Mr. Nikunj Tandel has completed his Master\'s degree in Biotechnology from VIT University, India in the year of 2012. He is having 8 years of research experience especially in the field of malaria epidemiology, immunology, and nanoparticle-based drug delivery system against the infectious diseases, autoimmune disorders and cancer. He has worked for the NIH funded-International Center of Excellence in Malaria Research project "Center for the study of complex malaria in India (CSCMi)" in collaboration with New York University. The preliminary objectives of the study are to understand and develop the evidence-based tools and interventions for the control and prevention of malaria in different sites of the INDIA. Alongside, with the help of next-generation genomics study, the team has studied the antimalarial drug resistance in India. Further, he has extended his research in the development of Humanized mice for the study of liver-stage malaria and identification of molecular marker(s) for the Artemisinin resistance. At present, his research focuses on understanding the role of B cells in the activation of CD8+ T cells in malaria. Received the CSIR-SRF (Senior Research Fellow) award-2018, FIMSA (Federation of Immunological Societies of Asia-Oceania) Travel Bursary award to attend the IUIS-IIS-FIMSA Immunology course-2019',institutionString:"Nirma University",institution:{name:"Nirma University",country:{name:"India"}}},{id:"334383",title:"Ph.D.",name:"Simone",middleName:"Ulrich",surname:"Ulrich Picoli",slug:"simone-ulrich-picoli",fullName:"Simone Ulrich Picoli",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/334383/images/15919_n.jpg",biography:"Graduated in Pharmacy from Universidade Luterana do Brasil (1999), Master in Agricultural and Environmental Microbiology from Federal University of Rio Grande do Sul (2002), Specialization in Clinical Microbiology from Universidade de São Paulo, USP (2007) and PhD in Sciences in Gastroenterology and Hepatology (2012). She is currently an Adjunct Professor at Feevale University in Medicine and Biomedicine courses and a permanent professor of the Academic Master\\'s Degree in Virology. She has experience in the field of Microbiology, with an emphasis on Bacteriology, working mainly on the following topics: bacteriophages, bacterial resistance, clinical microbiology and food microbiology.",institutionString:null,institution:{name:"Universidade Feevale",country:{name:"Brazil"}}},{id:"229220",title:"Dr.",name:"Amjad",middleName:"Islam",surname:"Aqib",slug:"amjad-aqib",fullName:"Amjad Aqib",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/229220/images/system/229220.png",biography:"Dr. Amjad Islam Aqib obtained a DVM and MSc (Hons) from University of Agriculture Faisalabad (UAF), Pakistan, and a PhD from the University of Veterinary and Animal Sciences Lahore, Pakistan. Dr. Aqib joined the Department of Clinical Medicine and Surgery at UAF for one year as an assistant professor where he developed a research laboratory designated for pathogenic bacteria. Since 2018, he has been Assistant Professor/Officer in-charge, Department of Medicine, Manager Research Operations and Development-ORIC, and President One Health Club at Cholistan University of Veterinary and Animal Sciences, Bahawalpur, Pakistan. He has nearly 100 publications to his credit. His research interests include epidemiological patterns and molecular analysis of antimicrobial resistance and modulation and vaccine development against animal pathogens of public health concern.",institutionString:"Cholistan University of Veterinary and Animal Sciences",institution:null},{id:"62900",title:"Prof.",name:"Fethi",middleName:null,surname:"Derbel",slug:"fethi-derbel",fullName:"Fethi Derbel",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/62900/images/system/62900.jpeg",biography:"Professor Fethi Derbel was born in 1960 in Tunisia. He received his medical degree from the Sousse Faculty of Medicine at Sousse, University of Sousse, Tunisia. He completed his surgical residency in General Surgery at the University Hospital Farhat Hached of Sousse and was a member of the Unit of Liver Transplantation in the University of Rennes, France. He then worked in the Department of Surgery at the Sahloul University Hospital in Sousse. Professor Derbel is presently working at the Clinique les Oliviers, Sousse, Tunisia. His hospital activities are mostly concerned with laparoscopic, colorectal, pancreatic, hepatobiliary, and gastric surgery. He is also very interested in hernia surgery and performs ventral hernia repairs and inguinal hernia repairs. He has been a member of the GREPA and Tunisian Hernia Society (THS). During his residency, he managed patients suffering from diabetic foot, and he was very interested in this pathology. For this reason, he decided to coordinate a book project dealing with the diabetic foot. Professor Derbel has published many articles in journals and collaborates intensively with IntechOpen Access Publisher as an editor.",institutionString:"Clinique les Oliviers",institution:null},{id:"300144",title:"Dr.",name:"Meriem",middleName:null,surname:"Braiki",slug:"meriem-braiki",fullName:"Meriem Braiki",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/300144/images/system/300144.jpg",biography:"Dr. Meriem Braiki is a specialist in pediatric surgeon from Tunisia. She was born in 1985. She received her medical degree from the University of Medicine at Sousse, Tunisia. She achieved her surgical residency training periods in Pediatric Surgery departments at University Hospitals in Monastir, Tunis and France.\r\nShe is currently working at the Pediatric surgery department, Sidi Bouzid Hospital, Tunisia. Her hospital activities are mostly concerned with laparoscopic, parietal, urological and digestive surgery. She has published several articles in diffrent journals.",institutionString:"Sidi Bouzid Regional Hospital",institution:null},{id:"229481",title:"Dr.",name:"Erika M.",middleName:"Martins",surname:"de Carvalho",slug:"erika-m.-de-carvalho",fullName:"Erika M. de Carvalho",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/229481/images/6397_n.jpg",biography:null,institutionString:null,institution:{name:"Oswaldo Cruz Foundation",country:{name:"Brazil"}}},{id:"186537",title:"Prof.",name:"Tonay",middleName:null,surname:"Inceboz",slug:"tonay-inceboz",fullName:"Tonay Inceboz",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/186537/images/system/186537.jfif",biography:"I was graduated from Ege University of Medical Faculty (Turkey) in 1988 and completed his Med. PhD degree in Medical Parasitology at the same university. I became an Associate Professor in 2008 and Professor in 2014. I am currently working as a Professor at the Department of Medical Parasitology at Dokuz Eylul University, Izmir, Turkey.\n\nI have given many lectures, presentations in different academic meetings. I have more than 60 articles in peer-reviewed journals, 18 book chapters, 1 book editorship.\n\nMy research interests are Echinococcus granulosus, Echinococcus multilocularis (diagnosis, life cycle, in vitro and in vivo cultivation), and Trichomonas vaginalis (diagnosis, PCR, and in vitro cultivation).",institutionString:"Dokuz Eylül University",institution:{name:"Dokuz Eylül University",country:{name:"Turkey"}}},{id:"71812",title:"Prof.",name:"Hanem Fathy",middleName:"Fathy",surname:"Khater",slug:"hanem-fathy-khater",fullName:"Hanem Fathy Khater",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/71812/images/1167_n.jpg",biography:"Prof. Khater is a Professor of Parasitology at Benha University, Egypt. She studied for her doctoral degree, at the Department of Entomology, College of Agriculture, Food and Natural Resources, University of Missouri, Columbia, USA. She has completed her Ph.D. degrees in Parasitology in Egypt, from where she got the award for “the best scientific Ph.D. dissertation”. She worked at the School of Biological Sciences, Bristol, England, the UK in controlling insects of medical and veterinary importance as a grant from Newton Mosharafa, the British Council. Her research is focused on searching of pesticides against mosquitoes, house flies, lice, green bottle fly, camel nasal botfly, soft and hard ticks, mites, and the diamondback moth as well as control of several parasites using safe and natural materials to avoid drug resistances and environmental contamination.",institutionString:null,institution:{name:"Banha University",country:{name:"Egypt"}}},{id:"99780",title:"Prof.",name:"Omolade",middleName:"Olayinka",surname:"Okwa",slug:"omolade-okwa",fullName:"Omolade Okwa",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/99780/images/system/99780.jpg",biography:"Omolade Olayinka Okwa is presently a Professor of Parasitology at Lagos State University, Nigeria. She has a PhD in Parasitology (1997), an MSc in Cellular Parasitology (1992), and a BSc (Hons) Zoology (1990) all from the University of Ibadan, Nigeria. She teaches parasitology at the undergraduate and postgraduate levels. She was a recipient of a Commonwealth fellowship supported by British Council tenable at the Centre for Entomology and Parasitology (CAEP), Keele University, United Kingdom between 2004 and 2005. She was awarded an Honorary Visiting Research Fellow at the same university from 2005 to 2007. \nShe has been an external examiner to the Department of Veterinary Microbiology and Parasitology, University of Ibadan, MSc programme between 2010 and 2012. She is a member of the Nigerian Society of Experimental Biology (NISEB), Parasitology and Public Health Society of Nigeria (PPSN), Science Association of Nigeria (SAN), Zoological Society of Nigeria (ZSN), and is Vice Chairperson of the Organisation of Women in Science (OWSG), LASU chapter. She served as Head of Department of Zoology and Environmental Biology, Lagos State University from 2007 to 2010 and 2014 to 2016. She is a reviewer for several local and international journals such as Unilag Journal of Science, Libyan Journal of Medicine, Journal of Medicine and Medical Sciences, and Annual Research and Review in Science. \nShe has authored 45 scientific research publications in local and international journals, 8 scientific reviews, 4 books, and 3 book chapters, which includes the books “Malaria Parasites” and “Malaria” which are IntechOpen access publications.",institutionString:"Lagos State University",institution:{name:"Lagos State University",country:{name:"Nigeria"}}},{id:"273100",title:"Dr.",name:"Vijay",middleName:null,surname:"Gayam",slug:"vijay-gayam",fullName:"Vijay Gayam",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/273100/images/system/273100.jpeg",biography:"Dr. Vijay Bhaskar Reddy Gayam is currently practicing as an internist at Interfaith Medical Center in Brooklyn, New York, USA. He is also a Clinical Assistant Professor at the SUNY Downstate University Hospital and Adjunct Professor of Medicine at the American University of Antigua. He is a holder of an M.B.B.S. degree bestowed to him by Osmania Medical College and received his M.D. at Interfaith Medical Center. His career goals thus far have heavily focused on direct patient care, medical education, and clinical research. He currently serves in two leadership capacities; Assistant Program Director of Medicine at Interfaith Medical Center and as a Councilor for the American\r\nFederation for Medical Research. As a true academician and researcher, he has more than 50 papers indexed in international peer-reviewed journals. He has also presented numerous papers in multiple national and international scientific conferences. His areas of research interest include general internal medicine, gastroenterology and hepatology. He serves as an editor, editorial board member and reviewer for multiple international journals. His research on Hepatitis C has been very successful and has led to multiple research awards, including the 'Equity in Prevention and Treatment Award” from the New York Department of Health Viral Hepatitis Symposium (2018) and the 'Presidential Poster Award” awarded to him by the American College of Gastroenterology (2018). He was also awarded 'Outstanding Clinician in General Medicine” by Venus International Foundation for his extensive research expertise and services, perform over and above the standard expected in the advancement of healthcare, patient safety and quality of care.",institutionString:"Interfaith Medical Center",institution:{name:"Interfaith Medical Center",country:{name:"United States of America"}}},{id:"93517",title:"Dr.",name:"Clement",middleName:"Adebajo",surname:"Meseko",slug:"clement-meseko",fullName:"Clement Meseko",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/93517/images/system/93517.jpg",biography:"Dr. Clement Meseko obtained DVM and PhD degree in Veterinary Medicine and Virology respectively. He has worked for over 20 years in both private and public sectors including the academia, contributing to knowledge and control of infectious disease. Through the application of epidemiological skill, classical and molecular virological skills, he investigates viruses of economic and public health importance for the mitigation of the negative impact on people, animal and the environment in the context of Onehealth. \r\nDr. Meseko’s field experience on animal and zoonotic diseases and pathogen dynamics at the human-animal interface over the years shaped his carrier in research and scientific inquiries. He has been part of the investigation of Highly Pathogenic Avian Influenza incursions in sub Saharan Africa and monitors swine Influenza (Pandemic influenza Virus) agro-ecology and potential for interspecies transmission. He has authored and reviewed a number of journal articles and book chapters.",institutionString:"National Veterinary Research Institute",institution:{name:"National Veterinary Research Institute",country:{name:"Nigeria"}}},{id:"158026",title:"Prof.",name:"Shailendra K.",middleName:null,surname:"Saxena",slug:"shailendra-k.-saxena",fullName:"Shailendra K. Saxena",position:null,profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRET3QAO/Profile_Picture_2022-05-10T10:10:26.jpeg",biography:"Professor Dr. Shailendra K. Saxena is a vice dean and professor at King George's Medical University, Lucknow, India. His research interests involve understanding the molecular mechanisms of host defense during human viral infections and developing new predictive, preventive, and therapeutic strategies for them using Japanese encephalitis virus (JEV), HIV, and emerging viruses as a model via stem cell and cell culture technologies. His research work has been published in various high-impact factor journals (Science, PNAS, Nature Medicine) with a high number of citations. He has received many awards and honors in India and abroad including various Young Scientist Awards, BBSRC India Partnering Award, and Dr. JC Bose National Award of Department of Biotechnology, Min. of Science and Technology, Govt. of India. Dr. Saxena is a fellow of various international societies/academies including the Royal College of Pathologists, United Kingdom; Royal Society of Medicine, London; Royal Society of Biology, United Kingdom; Royal Society of Chemistry, London; and Academy of Translational Medicine Professionals, Austria. He was named a Global Leader in Science by The Scientist. He is also an international opinion leader/expert in vaccination for Japanese encephalitis by IPIC (UK).",institutionString:"King George's Medical University",institution:{name:"King George's Medical University",country:{name:"India"}}},{id:"94928",title:"Dr.",name:"Takuo",middleName:null,surname:"Mizukami",slug:"takuo-mizukami",fullName:"Takuo Mizukami",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/94928/images/6402_n.jpg",biography:null,institutionString:null,institution:{name:"National Institute of Infectious Diseases",country:{name:"Japan"}}},{id:"233433",title:"Dr.",name:"Yulia",middleName:null,surname:"Desheva",slug:"yulia-desheva",fullName:"Yulia Desheva",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/233433/images/system/233433.png",biography:"Dr. Yulia Desheva is a leading researcher at the Institute of Experimental Medicine, St. Petersburg, Russia. She is a professor in the Stomatology Faculty, St. Petersburg State University. She has expertise in the development and evaluation of a wide range of live mucosal vaccines against influenza and bacterial complications. Her research interests include immunity against influenza and COVID-19 and the development of immunization schemes for high-risk individuals.",institutionString:'Federal State Budgetary Scientific Institution "Institute of Experimental Medicine"',institution:null},{id:"238958",title:"Mr.",name:"Atamjit",middleName:null,surname:"Singh",slug:"atamjit-singh",fullName:"Atamjit Singh",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/238958/images/6575_n.jpg",biography:null,institutionString:null,institution:null},{id:"333753",title:"Dr.",name:"Rais",middleName:null,surname:"Ahmed",slug:"rais-ahmed",fullName:"Rais Ahmed",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/333753/images/20168_n.jpg",biography:null,institutionString:null,institution:null},{id:"252058",title:"M.Sc.",name:"Juan",middleName:null,surname:"Sulca",slug:"juan-sulca",fullName:"Juan Sulca",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/252058/images/12834_n.jpg",biography:null,institutionString:null,institution:null},{id:"191392",title:"Dr.",name:"Marimuthu",middleName:null,surname:"Govindarajan",slug:"marimuthu-govindarajan",fullName:"Marimuthu Govindarajan",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/191392/images/5828_n.jpg",biography:"Dr. M. Govindarajan completed his BSc degree in Zoology at Government Arts College (Autonomous), Kumbakonam, and MSc, MPhil, and PhD degrees at Annamalai University, Annamalai Nagar, Tamil Nadu, India. He is serving as an assistant professor at the Department of Zoology, Annamalai University. His research interests include isolation, identification, and characterization of biologically active molecules from plants and microbes. He has identified more than 20 pure compounds with high mosquitocidal activity and also conducted high-quality research on photochemistry and nanosynthesis. He has published more than 150 studies in journals with impact factor and 2 books in Lambert Academic Publishing, Germany. He serves as an editorial board member in various national and international scientific journals.",institutionString:null,institution:null},{id:"274660",title:"Dr.",name:"Damodar",middleName:null,surname:"Paudel",slug:"damodar-paudel",fullName:"Damodar Paudel",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/274660/images/8176_n.jpg",biography:"I am DrDamodar Paudel,currently working as consultant Physician in Nepal police Hospital.",institutionString:null,institution:null},{id:"241562",title:"Dr.",name:"Melvin",middleName:null,surname:"Sanicas",slug:"melvin-sanicas",fullName:"Melvin Sanicas",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/241562/images/6699_n.jpg",biography:null,institutionString:null,institution:null},{id:"337446",title:"Dr.",name:"Maria",middleName:null,surname:"Zavala-Colon",slug:"maria-zavala-colon",fullName:"Maria Zavala-Colon",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"University of Puerto Rico, Medical Sciences Campus",country:{name:"United States of America"}}},{id:"338856",title:"Mrs.",name:"Nur Alvira",middleName:null,surname:"Pascawati",slug:"nur-alvira-pascawati",fullName:"Nur Alvira Pascawati",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Universitas Respati Yogyakarta",country:{name:"Indonesia"}}},{id:"441116",title:"Dr.",name:"Jovanka M.",middleName:null,surname:"Voyich",slug:"jovanka-m.-voyich",fullName:"Jovanka M. Voyich",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Montana State University",country:{name:"United States of America"}}},{id:"330412",title:"Dr.",name:"Muhammad",middleName:null,surname:"Farhab",slug:"muhammad-farhab",fullName:"Muhammad Farhab",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"University of Agriculture Faisalabad",country:{name:"Pakistan"}}},{id:"349495",title:"Dr.",name:"Muhammad",middleName:null,surname:"Ijaz",slug:"muhammad-ijaz",fullName:"Muhammad Ijaz",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"University of Veterinary and Animal Sciences",country:{name:"Pakistan"}}}]}},subseries:{item:{id:"95",type:"subseries",title:"Urban Planning and Environmental Management",keywords:"Circular economy, Contingency planning and response to disasters, Ecosystem services, Integrated urban water management, Nature-based solutions, Sustainable urban development, Urban green spaces",scope:"
\r\n\tIf we aim to prosper as a society and as a species, there is no alternative to sustainability-oriented development and growth. Sustainable development is no longer a choice but a necessity for us all. Ecosystems and preserving ecosystem services and inclusive urban development present promising solutions to environmental problems. Contextually, the emphasis on studying these fields will enable us to identify and define the critical factors for territorial success in the upcoming decades to be considered by the main-actors, decision and policy makers, technicians, and public in general.
\r\n
\r\n\tHolistic urban planning and environmental management are therefore crucial spheres that will define sustainable trajectories for our urbanizing planet. This urban and environmental planning topic aims to attract contributions that address sustainable urban development challenges and solutions, including integrated urban water management, planning for the urban circular economy, monitoring of risks, contingency planning and response to disasters, among several other challenges and solutions.
",coverUrl:"https://cdn.intechopen.com/series_topics/covers/95.jpg",hasOnlineFirst:!1,hasPublishedBooks:!1,annualVolume:11979,editor:{id:"181079",title:"Dr.",name:"Christoph",middleName:null,surname:"Lüthi",slug:"christoph-luthi",fullName:"Christoph Lüthi",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRHSqQAO/Profile_Picture_2022-04-12T15:51:33.png",biography:"Dr. Christoph Lüthi is an urban infrastructure planner with over 25 years of experience in planning and design of urban infrastructure in middle and low-income countries. He holds a Master’s Degree in Urban Development Planning from the University College of London (UCL), and a Ph.D. in Urban Planning & Engineering from TU Berlin. He has conducted applied research on urban planning and infrastructure issues in over 20 countries in Africa and Asia. In 2005 he joined Eawag-Sandec as Leader of the Strategic Environmental Sanitation Planning Group. Since 2015 he heads the research department Sanitation, Water and Solid Waste for Development (Sandec) at the Swiss Federal Institute of Aquatic Research and Technology (Eawag).",institutionString:"Swiss Federal Institute of Aquatic Science and Technology, Switzerland",institution:null},editorTwo:{id:"290571",title:"Dr.",name:"Rui Alexandre",middleName:null,surname:"Castanho",slug:"rui-alexandre-castanho",fullName:"Rui Alexandre Castanho",profilePictureURL:"https://mts.intechopen.com/storage/users/290571/images/system/290571.jpg",biography:"Rui Alexandre Castanho has a master\\'s degree in Planning, Audit, and Control in Urban Green Spaces and an international Ph.D. in Sustainable Planning in Borderlands. Currently, he is a professor at WSB University, Poland, and a visiting professor at the University of Johannesburg, South Africa. Dr. Castanho is a post-doc researcher on the GREAT Project, University of Azores, Ponta Delgada, Portugal. He collaborates with the Environmental Resources Analysis Research Group (ARAM), University of Extremadura (UEx), Spain; VALORIZA - Research Center for the Enhancement of Endogenous Resources, Polytechnic Institute of Portalegre (IPP), Portugal; Centre for Tourism Research, Development and Innovation (CITUR), Madeira, Portugal; and AQUAGEO Research Group, University of Campinas (UNICAMP), Brazil.",institutionString:"University of Johannesburg, South Africa and WSB University, Poland",institution:{name:"University of Johannesburg",institutionURL:null,country:{name:"South Africa"}}},editorThree:null,series:{id:"24",title:"Sustainable Development",doi:"10.5772/intechopen.100361",issn:null},editorialBoard:[{id:"181486",title:"Dr.",name:"Claudia",middleName:null,surname:"Trillo",slug:"claudia-trillo",fullName:"Claudia Trillo",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bSAZHQA4/Profile_Picture_2022-03-14T08:26:43.jpg",institutionString:null,institution:{name:"University of Salford",institutionURL:null,country:{name:"United Kingdom"}}},{id:"308328",title:"Dr.",name:"Dávid",middleName:null,surname:"Földes",slug:"david-foldes",fullName:"Dávid Földes",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0033Y00002nXXGKQA4/Profile_Picture_2022-03-11T08:25:45.jpg",institutionString:null,institution:{name:"Budapest University of Technology and Economics",institutionURL:null,country:{name:"Hungary"}}},{id:"282172",title:"Dr.",name:"Ivan",middleName:null,surname:"Oropeza-Perez",slug:"ivan-oropeza-perez",fullName:"Ivan Oropeza-Perez",profilePictureURL:"https://mts.intechopen.com/storage/users/282172/images/system/282172.jpg",institutionString:"Universidad de las Américas Puebla",institution:{name:"Universidad de las Américas Puebla",institutionURL:null,country:{name:"Mexico"}}}]},onlineFirstChapters:{paginationCount:14,paginationItems:[{id:"82457",title:"Canine Hearing Management",doi:"10.5772/intechopen.105515",signatures:"Peter M. 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