\nThe book is divided into three parts:
\nPart I: Ecological interpretation of land-use act - in this part, ecosystem and land use turn out to be a significant factor in the process of creating an ecological landscape.
\nPart II: Landscape district in applied ecological analysis - this part attempts to illustrate the best possible model of analysis integrated with landscape in practical case studies.
\nPart III: The anthropogenic impacts on landscape creation - this part discusses the human impact on landscape creation.",isbn:"978-953-51-2514-3",printIsbn:"978-953-51-2513-6",pdfIsbn:"978-953-51-5442-6",doi:"10.5772/61905",price:119,priceEur:129,priceUsd:155,slug:"landscape-ecology-the-influences-of-land-use-and-anthropogenic-impacts-of-landscape-creation",numberOfPages:140,isOpenForSubmission:!1,isInWos:null,isInBkci:!1,hash:"354db0cb765007d8e48728a1356f2b75",bookSignature:"Amjad Almusaed",publishedDate:"July 27th 2016",coverURL:"https://cdn.intechopen.com/books/images_new/5289.jpg",numberOfDownloads:14417,numberOfWosCitations:10,numberOfCrossrefCitations:39,numberOfCrossrefCitationsByBook:0,numberOfDimensionsCitations:77,numberOfDimensionsCitationsByBook:0,hasAltmetrics:1,numberOfTotalCitations:126,isAvailableForWebshopOrdering:!0,dateEndFirstStepPublish:"November 12th 2015",dateEndSecondStepPublish:"December 3rd 2015",dateEndThirdStepPublish:"March 22nd 2016",dateEndFourthStepPublish:"June 20th 2016",dateEndFifthStepPublish:"July 20th 2016",currentStepOfPublishingProcess:5,indexedIn:"1,2,3,4,5,6",editedByType:"Edited by",kuFlag:!1,featuredMarkup:null,editors:[{id:"110471",title:"Prof.",name:"Amjad",middleName:"Zaki",surname:"Almusaed",slug:"amjad-almusaed",fullName:"Amjad Almusaed",profilePictureURL:"https://mts.intechopen.com/storage/users/110471/images/system/110471.png",biography:"Prof. Amjad Almusaed has a Ph.D. in Architecture (Environmental Design) from Ion Mincu University, Bucharest, Romania. He completed postdoctoral research in 2004 on sustainable and bioclimatic houses at the School of Architecture, Aarhus, Denmark. His research expertise is sustainability in architecture and urban planning and design. He has carried out a great deal of research and technical survey work and has performed several studies in these areas. He has edited many international books and is an active member of many worldwide architectural associations. He has published more than 170 international academic works (papers, research, books, and book chapters) in different languages.",institutionString:"Jönköping University",position:null,outsideEditionCount:0,totalCites:0,totalAuthoredChapters:"10",totalChapterViews:"0",totalEditedBooks:"10",institution:{name:"Jönköping University",institutionURL:null,country:{name:"Sweden"}}}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,coeditorOne:null,coeditorTwo:null,coeditorThree:null,coeditorFour:null,coeditorFive:null,topics:[{id:"849",title:"Landscape Ecology",slug:"landscape-ecology"}],chapters:[{id:"51201",title:"Agriculture and Its Impact on Land‐Use, Environment, and Ecosystem Services",doi:"10.5772/63719",slug:"agriculture-and-its-impact-on-land-use-environment-and-ecosystem-services",totalDownloads:8430,totalCrossrefCites:34,totalDimensionsCites:70,hasAltmetrics:1,abstract:"Human expansion throughout the world caused that agriculture is a dominant form of land management globally. Human influence on the land is accelerating because of rapid population growth and increasing food requirements. To stress the interactions between society and the environment, the driving forces (D), pressures (P), states (S), impacts (I), and response (R) (DPSIR) framework approach was used for analyzing and assessing the influence of agriculture on land use, environment, and ecosystem services. The DPSIR model was used to identify a series of core indicators and to establish the nature of interactions between different driving forces, pressures, states, impacts, and responses. We assessed selected indicators at global, national, and local levels. Driving force indicators describe growing population trend and linking land‐use patterns. The driving forces exert pressure on the environment assessed by indicators describing development in fertilizer and pesticides consumption, by number of livestock, and by intensification joined growing release of ammonia and greenhouse gas (GHG) emissions from agriculture, and water abstraction. The pressure reflects in the state of environment, mainly expressed by soil and water quality indicators. Negative changes in the state then have negative impacts on landscape, e.g., traditional landscape disappearance, biodiversity, climate, and ecosystem services. As a response, technological, economic, policy, or legislation measures are adopted.",signatures:"Radoslava Kanianska",downloadPdfUrl:"/chapter/pdf-download/51201",previewPdfUrl:"/chapter/pdf-preview/51201",authors:[{id:"184781",title:"Ph.D.",name:"Radoslava",surname:"Kanianska",slug:"radoslava-kanianska",fullName:"Radoslava Kanianska"}],corrections:null},{id:"50964",title:"Modelling the Contribution of Land Use to Nitrate Yield from a Rural Catchment",doi:"10.5772/63718",slug:"modelling-the-contribution-of-land-use-to-nitrate-yield-from-a-rural-catchment",totalDownloads:1428,totalCrossrefCites:2,totalDimensionsCites:2,hasAltmetrics:1,abstract:"The nutrient flow dynamics in rural landscapes are among the basic characteristics of landscape functioning. In this study, the ecohydrological model SWAT (Soil and Water Assessment Tool) was applied in a small rural catchment in northwest (NW) Spain to evaluate the contribution of land use on nitrate losses and to assess the relative importance of different pathways by which nitrate is delivered to the drainage network. The model was first calibrated and validated at a monthly time step. The SWAT model performance was satisfactory (R2 > 0.5; Nash-Sutcliffe efficiency (NSE) > 0.5 and percent bias (PBIAS) < 10%) during both the calibration and validation periods, indicating that SWAT predicted the nitrate discharge accurately. Using the calibrated SWAT model, this study showed that agricultural lands, even though they represent only 30% of the catchment, were main contributor to the nitrate losses accounting for about 77% of the total nitrate yield. The model results also indicated that, irrespective of the land use, groundwater flow is the main pathway for nitrate losses (63%); therefore, appropriate management practices aimed at decreasing nitrate leaching will be key factors in reducing nitrate yield in the study catchment.",signatures:"Maria-Luz Rodríguez-Blanco, Ricardo Arias, Maria-Mercedes\nTaboada-Castro, Joao Pedro Nunes, Jan Jacob Keizer and Maria-\nTeresa Taboada-Castro",downloadPdfUrl:"/chapter/pdf-download/50964",previewPdfUrl:"/chapter/pdf-preview/50964",authors:[{id:"183458",title:"Dr.",name:"María-Luz",surname:"Rodríguez-Blanco",slug:"maria-luz-rodriguez-blanco",fullName:"María-Luz Rodríguez-Blanco"}],corrections:null},{id:"51225",title:"Multitemporal Analysis in Mediterranean Forestland with Remote Sensing",doi:"10.5772/63721",slug:"multitemporal-analysis-in-mediterranean-forestland-with-remote-sensing",totalDownloads:1210,totalCrossrefCites:0,totalDimensionsCites:1,hasAltmetrics:0,abstract:"The study employs a Fourier transform analysis approach to assess the land-cover changes in a mountainous Mediterranean protected area using multi-temporal satellite images. Harmonic analysis was applied to a time series of Landsat satellite images acquired from 1984 to 2008 to extract information about land cover status with a vegetation spectral index, the Normalized Difference Vegetation Index (NDVI). Ancillary cartographic information depicting land cover classes and the enlargement of the protected area over time (i.e., maps showing the original delineation in 1995 and subsequent enlargement in 2007) were employed as additional factors to understand vegetation-cover changes. Significant differences in the NDVI and harmonic components values were observed with respect to both factors. The application of the Fourier transform was particularly successful to extract subtle information. The harmonic analysis of the NDVI time series revealed valuable information about the evolution of the landscape. The initially protected area (northern sector) seems more affected by human activities than the southern sector (enlarged area in 2007) as revealed by the analysis of the first harmonic component that was closely related with vegetation coverage. Rural abandonment is a major driver of land-cover changes in the study area.",signatures:"Ignacio Melendez-Pastor, Encarni I. Hernández, Jose Navarro-\nPedreño, Ignacio Gómez and Magaly Koch",downloadPdfUrl:"/chapter/pdf-download/51225",previewPdfUrl:"/chapter/pdf-preview/51225",authors:[{id:"109913",title:"Dr.",name:"Ignacio",surname:"Melendez-Pastor",slug:"ignacio-melendez-pastor",fullName:"Ignacio Melendez-Pastor"},{id:"137038",title:"Dr.",name:"Encarni I.",surname:"Hernández",slug:"encarni-i.-hernandez",fullName:"Encarni I. Hernández"},{id:"137040",title:"Prof.",name:"Jose",surname:"Navarro-Pedreño",slug:"jose-navarro-pedreno",fullName:"Jose Navarro-Pedreño"},{id:"137041",title:"Prof.",name:"Ignacio",surname:"Gómez Lucas",slug:"ignacio-gomez-lucas",fullName:"Ignacio Gómez Lucas"},{id:"183525",title:"Dr.",name:"Magaly",surname:"Koch",slug:"magaly-koch",fullName:"Magaly Koch"}],corrections:null},{id:"50268",title:"Hydrological Trend Analysis Integrated with Landscape Analysis at the Watershed Scale (Case Study: Langat Basin, Malaysia)",doi:"10.5772/62463",slug:"hydrological-trend-analysis-integrated-with-landscape-analysis-at-the-watershed-scale-case-study-lan",totalDownloads:1002,totalCrossrefCites:1,totalDimensionsCites:2,hasAltmetrics:0,abstract:"In this study, the trends of water and sediment data collected from three hydrometer stations over the past 25 years of development in the state of Selangor, Peninsular Malaysia, were analyzed using the Mann–Kendall and Pettitt’s tests. Landscape metrics for establishing the relationship between land use changes and trends of hydrological time series were calculated. The hydrologic trends were also studied in terms of rainfall variations and man-made features. Results indicated upward trends in water discharge at the Hulu Langat sub-basin and sediment load at the Semenyih sub-basin. These increasing trends were mainly caused by rapid changes in land use. Upward trends of hydrological series at the Hulu Langat sub-basin matched its rainfall pattern. At the Lui sub-basin, however, trends of hydrological series and variations in rainfall and land use were not statistically significant.",signatures:"Hadi Memarian and Siva K. Balasundram",downloadPdfUrl:"/chapter/pdf-download/50268",previewPdfUrl:"/chapter/pdf-preview/50268",authors:[{id:"182821",title:"Dr.",name:"Hadi",surname:"Memarian",slug:"hadi-memarian",fullName:"Hadi Memarian"},{id:"184945",title:"Prof.",name:"Siva",surname:"Kumar Balasundram",slug:"siva-kumar-balasundram",fullName:"Siva Kumar Balasundram"}],corrections:null},{id:"51291",title:"The Anthropic Pressure on the Landscapes of the Subcarpathian and Piedmont Basin of Dâmboviţa River (Romania)",doi:"10.5772/63722",slug:"the-anthropic-pressure-on-the-landscapes-of-the-subcarpathian-and-piedmont-basin-of-d-mbovi-a-river-",totalDownloads:1076,totalCrossrefCites:1,totalDimensionsCites:1,hasAltmetrics:0,abstract:"The Subcarpathian and Piedmont Basin of Dâmboviţa cover an area of 412 km2 and largely overlap north-western part of Dâmboviţa County, namely the relief units: Gethian Subcarpathians (the Subcarpahians of Argeş), Subcarpathians of Curvature (the Subcarpathians of Ialomiţa) and Getian Plateau (Piedmont of Cândeşti).",signatures:"Mihaela Sencovici and Gica Pehoiu",downloadPdfUrl:"/chapter/pdf-download/51291",previewPdfUrl:"/chapter/pdf-preview/51291",authors:[{id:"94647",title:"Dr",name:"Gica",surname:"Pehoiu",slug:"gica-pehoiu",fullName:"Gica Pehoiu"},{id:"186700",title:"Dr.",name:"Mihaela",surname:"Sencovici",slug:"mihaela-sencovici",fullName:"Mihaela Sencovici"}],corrections:null},{id:"50472",title:"Tracking Anthropogenic Influences on the Condition of Plant Communities at Sites and Landscape Scales",doi:"10.5772/62874",slug:"tracking-anthropogenic-influences-on-the-condition-of-plant-communities-at-sites-and-landscape-scale",totalDownloads:1272,totalCrossrefCites:1,totalDimensionsCites:1,hasAltmetrics:0,abstract:"Deriving vegetation condition assessments from land use classifications and mapping only provides rudimentary and very coarse insights; ones that may be misleading for planning and priority setting by regional planners and policy makers. Standardized indicators of past ecological resilience for a particular landscape can assist land managers and ecologists track, evaluate and report the outcomes of land management decisions. Developing a timetable of the varying goals of land management practices and their past effects on vegetation condition including regenerative capacity is suited to on-ground managers.Access to information about how and why landscapes were transformed helps regional planners and policy makers identify and prioritise areas for investment relative to an ideal state. Tracking the responses of previous native plant communities to a range of land management practices helps decision makers gain an understanding of which outcomes can be realistically achieved in particular landscape contexts.",signatures:"Richard Thackway",downloadPdfUrl:"/chapter/pdf-download/50472",previewPdfUrl:"/chapter/pdf-preview/50472",authors:[{id:"171613",title:"Associate Prof.",name:"Richard",surname:"Thackway",slug:"richard-thackway",fullName:"Richard Thackway"}],corrections:null}],productType:{id:"1",title:"Edited Volume",chapterContentType:"chapter",authoredCaption:"Edited by"},subseries:null,tags:null},relatedBooks:[{type:"book",id:"6066",title:"Landscape Architecture",subtitle:"The Sense of Places, Models and Applications",isOpenForSubmission:!1,hash:"fd4ff3f5b34fb2ee8089dc8da74a843a",slug:"landscape-architecture-the-sense-of-places-models-and-applications",bookSignature:"Amjad Almusaed",coverURL:"https://cdn.intechopen.com/books/images_new/6066.jpg",editedByType:"Edited 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\r\n\tXylanases are hydrolases depolymerizing the plant cell component xylan, the second most abundant polysaccharide. Xylanases are produced by fungi, bacteria, yeast, marine algae, protozoans, snails, crustaceans, insects, seeds, etc., but the principal commercial source is filamentous fungi. Xylanase belonging to pentosanases, a class of enzyme that breaks down cell wall matrix of plants, breaks down xylan into xylose residues. This property of xylanase makes it a commercially important enzyme.
\r\n\r\n\tThe present book aims to give an insight into the structure, function and applications of xylanase in various industries along with the current trends in xylanase enzyme research.
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During several decades, it was admitted that macrophages are issued from circulating monocytes in homeostatic conditions or after their migration to the tissues following chemokine gradients. More recently, the use of new tools such as genetic fate mapping techniques has shown that most of resident macrophages are of embryonic origin and monocytes contribute to their renewal when homeostasis is impaired [2]. In addition to their role in regulation of tissue development and homeostasis, macrophages actively participate to innate immune defense through the recognition of viruses, bacteria, parasites or fungi [3].
In contrast to lymphoid cells, macrophages are neither antigen specific nor clonally restricted and express a large panel of membrane molecules. The activation ways of macrophages during infection rely on the interaction of pathogen-associated molecular pattern (PAMPs) with pathogen recognition receptors (PRRs) such as toll-like receptors (TLRs), scavenger receptors, C type lectin receptors, or complement receptors [4]. The interaction between PAMPs and PRRs leads to the activation of macrophages including production and secretion of cytokines, chemokines and lipid mediators, and promotes the uptake of microorganisms and their destruction [5]. Hence, macrophages are at the center of anti-infectious immune response, which includes pathogen recognition, macrophage activation and pathogen elimination [6, 7].
The polarization state of macrophage is characterized by their activation by pathogen ligands and inflammatory molecules. As previously described for T cell subsets with Th1 and Th2 functional dichotomy, M1 and M2 polarization may correspond to downstream effects of T cell polarization [8]. Numerous approaches have been performed to investigate macrophage responses during infection. Among them, the concept of polarization profile has represented a powerful strategy to investigate macrophage activation states during infection [9]. Here, we investigate tools available to study macrophages in a critical point of view and we propose them to assess prognosis and therapeutic response in bacterial infectious diseases.
The term of “polarization” corresponds to functional states exhibiting a binary distribution. It was used for the first time in 1986 by Mosmann et al. to characterize two murine T helper lymphocyte sub-populations, i.e., Th1 and Th2 according to their respective stimuli, interferon (IFN)-γ and interleukin (IL)-4 [10]. The concept of macrophage polarization was deduced from the Th1 and Th2 polarization and accounted for the diversity of macrophage activation [8]. Hence, Stein et al. showed that IL-4 stimulated the expression by murine macrophages of the mannose type 1 receptor (MRC1, CD206) associated to enhanced particle uptake and decreased release of tumor necrosis factor (TNF), a potent inflammatory cytokine; these characteristics may be considered as a model of M2 signature [11]. Later, Mills et al. confirmed that Th1 or Th2 lymphocytes led to the polarization of macrophages into M1 (inflammatory) and M2 (immunoregulatory) profiles [8]. Another nomenclature coexisted with M1/M2 polarization: M1 macrophages were also called classically activated macrophages while M2 macrophages exhibited an alternative type of activation [12]. Few authors use now these two terms and the heterogeneity of M2 macrophages do not fit with the category of alternative activation, explaining why we will use only M1 and M2 terms.
As depicted in Figure 1, M1 and M2 profiles are induced by specific ligands. M1 profile is elicited by inflammatory cytokines (TNF or IFN-γ), bacterial components such as lipopolysaccharide (LPS) or growth factors including granulocyte-macrophage colony-stimulating factor (GM-CSF). In contrast, Th2 cytokines (IL-4, IL-10 and IL-13) lead to M2 polarization in the same way as IL-33, transforming growth factor (TGF)-β or macrophage colony-stimulating factor (M-CSF), the master growth factor of myeloid lineage. According the way of stimulation, macrophages express several different markers, secrete different mediators and exercise specific functions (Figure 1) [13, 14, 15, 16]. It is important to note that M2 macrophages are more heterogeneous than M1 macrophages and have been divided into three distinct profiles including M2a, M2b and M2c according their functions as “alternative and repairers” (M2a) or anti-inflammatory regulators (M2b and M2c) [17, 18]. M2a, M2b and M2c macrophages are activated by IL-14 and IL-13, immunes complexes associated with TLRs or glucocorticoids, IL-10 and TGF-β, respectively [13]. In contrast to a general point of view, using mass spectrometry we found that IFN-γ-stimulated macrophages exhibit a proteomic profile distinct from LPS-stimulated macrophages or LPS/IFN-γ-stimulated macrophages even if they are all included in M1 category [19]. The appearance of numerous discrepancies with the concept of M1/M2 dichotomy led scientists working on macrophage polarization to propose a reappraisal based on the type of agonist. Hence, the concept of polarization should include the source of macrophages, the type of activation and a collection of activation markers. We have proposed to adopt a nomenclature related to the agonist: M(IL-4), M(IFN-γ), M(IL-10), M(GC), M(Ig) and M(LPS) [20].
Polarization profile of placental macrophages. Summary of the molecules involved in polarization profiles inducing the expression of several proteins leading to several functions of placental macrophages.
The M1 profile is classically associated with control of bacterial infections but its definition is variable among publications. In some reports, only few inflammatory mediators (cytokines and inducible nitric oxide synthase (iNOS)) are considered whereas, in others, a combination of markers is used with large sets of genes or proteins [16, 21, 22]. In
On another hand, bacteria such as
The survival and the replication of pathogenic bacteria within macrophages may rely on strategies interfering with their polarization.
The evaluation of macrophage polarization depends on cell type (primary cells
In healthy humans and patients, primary macrophages derived from peripheral blood mononuclear cells (PBMCs) constitute the most practical model, especially to evaluate the polarization profile. Monocytes are isolated from PBMCs using CD14+ positive selection and differentiated into monocyte-derived macrophages (MDMs) that are not immortalized and do not proliferate. MDMs are produced in large quantities that allow the evaluation of several polarization markers [51]. Nevertheless, there is large donor variability, and cells from certain donors do not respond to polarizing agonists. This variability among individuals may point to
The evaluation of macrophage polarization needs a set of markers rather than a single molecule. This is exemplified by the use of a scavenger receptor, CD163, as a prototype of M2 marker. Indeed, CD163 is expressed by M1 cells and non-myeloid cells although at lower level [65]. The same comment can be done with iNOS, a M1 marker, also expressed by endothelial cells and arterial wall smooth muscle cells [66]. The development of high-throughput methods (omics technics) has offered the opportunity to provide convenient sets of polarization markers. The transcriptomics methods such as microarray had been a strategy to investigate macrophage polarization since they provide a large panel of transcripts associated with different modes of polarization (Figure 1). Martinez et al. reported transcriptomic analysis of activated macrophages: 5.2% and 0.3% of transcripts are associated with M1 and M2 polarization profiles, respectively [14]. Few years later, Xue et al. performed a transcriptomic analysis of human macrophages stimulated by various panels of agonists [67]. They identified nine specific distinct profiles according the agonist used, and a common transcriptomic signature, which was pertinent to isolate a polarized signature in inflammatory and infectious diseases outside of cancer [68]. Some alternative approaches to microarray such as nanostring method uses directly a panel of genes to measure their variation and may be convenient to investigate macrophage polarization [69]. Whatever the method, gene expression data must be controlled by quantitative RT-PCR, a very sensitive technic that needs low amounts of cells [70]. Discrepancies between microarray and quantitative RT-PCR have been often observed in macrophage polarization studies. The emergence of single cell RNA-sequencing (scRNA-seq) method might provide a powerful tool for analysis macrophage populations including their phenotype and therefore their polarization profile. Interestingly, the used of scRNA-seq permitted to show that M2 macrophages express varying levels of Arg1, challenging the dogma that macrophages with M2 profile all express Arg1 [71].
All these methods measure the expression of genes associated with macrophage polarization. This approach does not have the robustness of methods determining the expression of proteins. The enzyme-linked immunosorbent assay (ELISA) has the disadvantage to measure isolated secreted molecules associated with a given profile. The simultaneous measurement of up to 50 proteins using Luminex assays constitutes an interesting option but the cost and the specialized detection equipment represent a disadvantage. We previously investigated macrophage polarization by a proteomic approach using MALDI-TOF mass spectrometry technique combined with gel electrophoresis [19, 72]. This combined approach allows the determination of M1 signature of human macrophages stimulated with IFN-γ, LPS or bacteria. Moreover, different subtypes of M1 and M2 polarized macrophages have been identified using this approach [72].
The flow cytometry and CyTOF techniques offer a better investigation of macrophage phenotypes through the investigation of protein expression at a single cell resolution level. Hence, CyTOF panels have been proposed to measure polarization markers and, combined with high dimensional analysis, CyTOF enables the identification of novel functional macrophage subsets [73]. The emergence of cycling imaging that purposes to stain cells with different cocktail markers after bleaching allows the detection of more than 30 markers at once [74]. Finally, basic methods such as cell morphology could be used to evaluate functional phenotypes of polarized macrophages [75]. Indeed, polarized M2 murine macrophages are more elongated than M1 cells [76, 77].
A new and exciting field of exploring macrophage polarization, the study of metabolic changes, has recently emerged. LPS ligation of TLR-4 elicits a shift to glycolytic metabolism with impaired mitochondrial respiration. Associated with IFN- γ, LPS induces alterations in tricarboxylic acid cycle. In contrast, IL-4 responses are associated with a shift to oxidative metabolism. Hence, the M2 program associates changes in polyamine synthesis and fatty acid oxidation [78, 79].
This huge diversity of methods exploring macrophage activation including macrophage polarization needs to define the conditions of using these methods and the stratification of indications.
The interest of measuring macrophage polarization in patients is to assess activation status of macrophages to stratify them and to measure their response to treatment. The investigation of macrophage polarization in infected patients requires the choice of pertinent cell types and of the method of measurement. Studies with macrophages from healthy controls stimulated
The investigation of patients with bacterial infection is limited by accessibility of biological materials in contrast to cancer in whom tissue biopsies are required for the diagnosis. In practice, circulating monocytes, associated or not with lymphocytes, are the major source of myeloid cells. However, it is uncertain that the M1/M2 polarization of tissue macrophages is also found in circulating monocytes. We compared the polarization of monocytes and MDMs from healthy donors in response to canonical agonists of macrophage M1/M2 polarization, IFN-γ and IL-4. While the two cytokines elicit clear polarized profile in MDMs, a similar polarization is observed in early stimulated monocytes and is lost after 24 h of treatment [80]. This observation may account for numerous discrepancies found in several examples of infectious diseases. While
The biopsies are reserved to severe infections or rare infectious diseases in which they are necessary for the diagnosis as in Whipple’s disease. The advantage of such approach has been recently illustrated. In patients with tuberculosis who underwent surgical treatment, the investigation of pulmonary biopsies revealed that M2-like polarization was correlated with multidrug resistance [84]. We are suggesting adopting the guidelines used in oncology to characterize TAMs [66]. The polarization of tissue macrophages may be assessed in histological sections either by isolation of cells and
The concept of macrophage polarization has reached adulthood. If it is extremely efficient for pathophysiological studies, it needs to be adapted to the requirements of clinical investigations. This requires to follow the guidelines we defined several years ago according each type of agonist instead of too imprecise categories such as M1 or M2 cells. It also requires new technical solutions to directly investigate macrophages within tissues. Finally, we have to propose alternatives to biopsy sampling in infected patients who do not require such aggressive procedure.
Soraya Mezouar was supported by a “Fondation pour la Recherche Médicale” postdoctoral fellowship (reference: SPF20151234951). This work was supported by the French Government under the “Investissements d’avenir” (Investments for the future) program managed by the “Agence Nationale de la Recherche” (reference: 10-IAHU-03).
The authors declare no competing interests.
S.M. and J.L.M. conceived and wrote the manuscript.
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His main focus now is to unravel the mechanism of drought and heat stress response in plants to tackle climate change related threats in agriculture.",institutionString:null,institution:{name:"Indian Council of Agricultural Research",country:{name:"India"}}},{id:"4782",title:"Prof.",name:"Bishnu",middleName:"P",surname:"Pal",slug:"bishnu-pal",fullName:"Bishnu Pal",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/4782/images/system/4782.jpg",biography:"Bishnu P. 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The importance of these compounds in wine is due to their large effect on the organoleptic attributes of wine. Phenolic compounds play a crucial role in the colour as well as mouthfeel properties of wines. UV-visible spectroscopy appears as a suitable technique for the evaluation of phenolic compounds’ properties and content. The ability of the phenolic ring to absorb UV light and the fact that some of the phenolic substances are coloured compounds, i.e. show absorption features in the visible region, make UV-visible spectroscopy a suitable technique to investigate and quantify grape and wine phenolic compounds. A number of analytical techniques are currently used for phenolic quantification. These include both simpler approaches (spectrophotometric determinations) as well as more complex methodologies such liquid chromatography analysis. Moreover, a number of spectroscopy applications have also been recently reported and are becoming popular within the wine industry. This chapter reviews information on the UV-visible spectral properties of phenolic compounds, changes occurring during wine ageing and also discusses the current UV-visible based analytical techniques used for the quantification of phenolic compounds in grapes and wine.",book:{id:"6878",slug:"frontiers-and-new-trends-in-the-science-of-fermented-food-and-beverages",title:"Frontiers and New Trends in the Science of Fermented Food and Beverages",fullTitle:"Frontiers and New Trends in the Science of Fermented Food and Beverages"},signatures:"Jose Luis Aleixandre-Tudo and Wessel du Toit",authors:[{id:"250919",title:"Dr.",name:"Jose Luis",middleName:null,surname:"Aleixandre-Tudo",slug:"jose-luis-aleixandre-tudo",fullName:"Jose Luis Aleixandre-Tudo"},{id:"261223",title:"Prof.",name:"Wessel",middleName:null,surname:"Du Toit",slug:"wessel-du-toit",fullName:"Wessel Du Toit"}]},{id:"51587",doi:"10.5772/64187",title:"Casein Proteins: Structural and Functional Aspects",slug:"casein-proteins-structural-and-functional-aspects",totalDownloads:4780,totalCrossrefCites:16,totalDimensionsCites:38,abstract:"Mammalian milk is a complex fluid mixture of various proteins, minerals, and lipids, which play an important role in providing nutrition and immunity to the newborn. Casein proteins, which form about 80% of the bovine milk proteins, form large colloidal particles with calcium phosphate to form casein micelles, which for many years have been an important subject of interest. Casein micelles are composed of four main types of proteins: αS1‐casein, αS2‐casein, β‐casein, and k‐casein. These constituent casein proteins lack well‐defined secondary and tertiary structure due to large amount of propyl residues. These micelles are being extensively studied because of their importance in functional behavior of milk and various milk products. However, the exact structure and nature of these casein micelles are still under debate. These different casein proteins possess different functional properties due to their primary amino acid sequence.",book:{id:"5060",slug:"milk-proteins-from-structure-to-biological-properties-and-health-aspects",title:"Milk Proteins",fullTitle:"Milk Proteins - From Structure to Biological Properties and Health Aspects"},signatures:"Mohd Younus Bhat, Tanveer Ali Dar and Laishram Rajendrakumar\nSingh",authors:[{id:"178323",title:"Dr.",name:"Laishram R",middleName:null,surname:"Singh",slug:"laishram-r-singh",fullName:"Laishram R Singh"},{id:"183444",title:"Mr.",name:"Md. Younus",middleName:null,surname:"Bhat",slug:"md.-younus-bhat",fullName:"Md. 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In recent past, a new application envisaged for pectin polymers as edible films or coating. These films act as natural barrier for exchange of moisture, gases, lipids, and volatiles between food and environment, and protect fruits and vegetable from microbial contamination. The degree of esterification of pectin and other structural modifications defines the functional properties. Herein, various functional properties of pectin in relation to food processing and packaging are discussed.",book:{id:"8504",slug:"pectins-extraction-purification-characterization-and-applications",title:"Pectins",fullTitle:"Pectins - Extraction, Purification, Characterization and Applications"},signatures:"Thiraviam Vanitha and Mahejibin Khan",authors:null},{id:"63457",doi:"10.5772/intechopen.79447",title:"Nanoemulsions in Food Industry",slug:"nanoemulsions-in-food-industry",totalDownloads:2255,totalCrossrefCites:11,totalDimensionsCites:28,abstract:"A great attention has been received in the last few years for nanotechnology applications in food as well as pharmaceutical industries. People are looking for healthy and safe food worldwide. Therefore, researchers have been currently focusing on nanoemulsion technology that is particularly suited for the production of functional food. This chapter includes an overview about nanoemulsion terminology and formulation, various approaches for production of nanoemulsions which include high energy approaches such as high-pressure valve homogenization, microfluidizers and ultrasonic homogenization, and low energy methods such as spontaneous emulsification, phase inversion composition, phase inversion temperature and emulsion inversion point. In addition, the applications of nanoemulsions in food industry are discussed in detail.",book:{id:"7332",slug:"some-new-aspects-of-colloidal-systems-in-foods",title:"Some New Aspects of Colloidal Systems in Foods",fullTitle:"Some New Aspects of Colloidal Systems in Foods"},signatures:"Mohamed A. Salem and Shahira M. 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In recent years, natural polymers have evoked tremendous interest due to easy conversion into value-added products. Apart from various natural polymers, pectin occupied a prominent place due to diverse pharmaceutical and therapeutic applications. Excess utilisation of pectin, the gap between production and demand is widening. To fulfil this gap various techniques are adopted for obtaining high yield pectin from various agro-industrial wastes. This chapter will be focusing on extraction and purification of pectin from various agro-industrial wastes, considered as main environmental pollutants.",book:{id:"8504",slug:"pectins-extraction-purification-characterization-and-applications",title:"Pectins",fullTitle:"Pectins - Extraction, Purification, Characterization and Applications"},signatures:"Erumalla Venkatanagaraju, N. 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These micelles are being extensively studied because of their importance in functional behavior of milk and various milk products. However, the exact structure and nature of these casein micelles are still under debate. These different casein proteins possess different functional properties due to their primary amino acid sequence.",book:{id:"5060",slug:"milk-proteins-from-structure-to-biological-properties-and-health-aspects",title:"Milk Proteins",fullTitle:"Milk Proteins - From Structure to Biological Properties and Health Aspects"},signatures:"Mohd Younus Bhat, Tanveer Ali Dar and Laishram Rajendrakumar\nSingh",authors:[{id:"178323",title:"Dr.",name:"Laishram R",middleName:null,surname:"Singh",slug:"laishram-r-singh",fullName:"Laishram R Singh"},{id:"183444",title:"Mr.",name:"Md. Younus",middleName:null,surname:"Bhat",slug:"md.-younus-bhat",fullName:"Md. Younus Bhat"}]},{id:"62738",title:"The Role of UV-Visible Spectroscopy for Phenolic Compounds Quantification in Winemaking",slug:"the-role-of-uv-visible-spectroscopy-for-phenolic-compounds-quantification-in-winemaking",totalDownloads:2679,totalCrossrefCites:17,totalDimensionsCites:49,abstract:"Phenolic compounds are bioactive substances present in a large number of food products including wine. The importance of these compounds in wine is due to their large effect on the organoleptic attributes of wine. Phenolic compounds play a crucial role in the colour as well as mouthfeel properties of wines. UV-visible spectroscopy appears as a suitable technique for the evaluation of phenolic compounds’ properties and content. The ability of the phenolic ring to absorb UV light and the fact that some of the phenolic substances are coloured compounds, i.e. show absorption features in the visible region, make UV-visible spectroscopy a suitable technique to investigate and quantify grape and wine phenolic compounds. A number of analytical techniques are currently used for phenolic quantification. These include both simpler approaches (spectrophotometric determinations) as well as more complex methodologies such liquid chromatography analysis. Moreover, a number of spectroscopy applications have also been recently reported and are becoming popular within the wine industry. This chapter reviews information on the UV-visible spectral properties of phenolic compounds, changes occurring during wine ageing and also discusses the current UV-visible based analytical techniques used for the quantification of phenolic compounds in grapes and wine.",book:{id:"6878",slug:"frontiers-and-new-trends-in-the-science-of-fermented-food-and-beverages",title:"Frontiers and New Trends in the Science of Fermented Food and Beverages",fullTitle:"Frontiers and New Trends in the Science of Fermented Food and Beverages"},signatures:"Jose Luis Aleixandre-Tudo and Wessel du Toit",authors:[{id:"250919",title:"Dr.",name:"Jose Luis",middleName:null,surname:"Aleixandre-Tudo",slug:"jose-luis-aleixandre-tudo",fullName:"Jose Luis Aleixandre-Tudo"},{id:"261223",title:"Prof.",name:"Wessel",middleName:null,surname:"Du Toit",slug:"wessel-du-toit",fullName:"Wessel Du Toit"}]},{id:"65793",title:"Role of Pectin in Food Processing and Food Packaging",slug:"role-of-pectin-in-food-processing-and-food-packaging",totalDownloads:2945,totalCrossrefCites:14,totalDimensionsCites:36,abstract:"Pectin is a branched heteropolysaccharide consisting of long-chain galacturonan segments and other neutral sugars such as rhamnose, arabinose, galactose, and xylose. It forms a matrix with celluloses and hemicelluloses and contributes to the cell structure. Due to the presence of several sugar moieties and different levels of methyl esterification, pectin does not have defined molecular weight like other polysaccharides. Pectin has wide applications. It is used as emulsifier, gelling agent, thickener, stabilizer, and fat or sugar replacer in low-calorie foods. Pectin and pectin-derived oligosaccharides can also be used as an important ingredient in functional foods. In recent past, a new application envisaged for pectin polymers as edible films or coating. These films act as natural barrier for exchange of moisture, gases, lipids, and volatiles between food and environment, and protect fruits and vegetable from microbial contamination. The degree of esterification of pectin and other structural modifications defines the functional properties. Herein, various functional properties of pectin in relation to food processing and packaging are discussed.",book:{id:"8504",slug:"pectins-extraction-purification-characterization-and-applications",title:"Pectins",fullTitle:"Pectins - Extraction, Purification, Characterization and Applications"},signatures:"Thiraviam Vanitha and Mahejibin Khan",authors:null},{id:"66458",title:"Pectin - Extraction, Purification, Characterization and Applications",slug:"pectin-extraction-purification-characterization-and-applications",totalDownloads:1417,totalCrossrefCites:4,totalDimensionsCites:8,abstract:"Fruits, vegetables, and other plant-based foods are particularly important as they are source of dietary carbohydrates, and therefore much of the energy in the adult diet. Plant food also contains a wide range of dietary components rich in bioactive phytochemicals and is essential to the human body that may provide desirable health benefits beyond basic nutrition. Pectin is one of the nonstarch polysaccharides (NSPs), which constitutes the major fraction of the plant cell wall in association and/or substituted with other polysaccharides, and they cover a great variety of biological functions and chemical structures. Generally, pectin is isolated from by-products of agro-foods using extraction technologies with the emergence of novel and effective techniques that inclined toward a cleaner process. Pectin is widely used both in food sector (as gelling, thickening, and stabilizer agent) and in pharmaceutical industries (bioactive components) including biomedical application (drug delivery, tissue engineering, and wound healing) as innovative applications.",book:{id:"8504",slug:"pectins-extraction-purification-characterization-and-applications",title:"Pectins",fullTitle:"Pectins - Extraction, Purification, Characterization and Applications"},signatures:"Virginia Rodríguez Robledo* and Lucía Isabel Castro Vázquez",authors:null}],onlineFirstChaptersFilter:{topicId:"333",limit:6,offset:0},onlineFirstChaptersCollection:[],onlineFirstChaptersTotal:0},preDownload:{success:null,errors:{}},subscriptionForm:{success:null,errors:{}},aboutIntechopen:{},privacyPolicy:{},peerReviewing:{},howOpenAccessPublishingWithIntechopenWorks:{},sponsorshipBooks:{sponsorshipBooks:[],offset:0,limit:8,total:null},allSeries:{pteSeriesList:[{id:"14",title:"Artificial Intelligence",numberOfPublishedBooks:9,numberOfPublishedChapters:87,numberOfOpenTopics:6,numberOfUpcomingTopics:0,issn:"2633-1403",doi:"10.5772/intechopen.79920",isOpenForSubmission:!0},{id:"7",title:"Biomedical Engineering",numberOfPublishedBooks:12,numberOfPublishedChapters:99,numberOfOpenTopics:3,numberOfUpcomingTopics:0,issn:"2631-5343",doi:"10.5772/intechopen.71985",isOpenForSubmission:!0}],lsSeriesList:[{id:"11",title:"Biochemistry",numberOfPublishedBooks:27,numberOfPublishedChapters:290,numberOfOpenTopics:4,numberOfUpcomingTopics:0,issn:"2632-0983",doi:"10.5772/intechopen.72877",isOpenForSubmission:!0},{id:"25",title:"Environmental Sciences",numberOfPublishedBooks:1,numberOfPublishedChapters:9,numberOfOpenTopics:4,numberOfUpcomingTopics:0,issn:"2754-6713",doi:"10.5772/intechopen.100362",isOpenForSubmission:!0},{id:"10",title:"Physiology",numberOfPublishedBooks:11,numberOfPublishedChapters:139,numberOfOpenTopics:4,numberOfUpcomingTopics:0,issn:"2631-8261",doi:"10.5772/intechopen.72796",isOpenForSubmission:!0}],hsSeriesList:[{id:"3",title:"Dentistry",numberOfPublishedBooks:8,numberOfPublishedChapters:129,numberOfOpenTopics:0,numberOfUpcomingTopics:2,issn:"2631-6218",doi:"10.5772/intechopen.71199",isOpenForSubmission:!1},{id:"6",title:"Infectious Diseases",numberOfPublishedBooks:13,numberOfPublishedChapters:108,numberOfOpenTopics:3,numberOfUpcomingTopics:1,issn:"2631-6188",doi:"10.5772/intechopen.71852",isOpenForSubmission:!0},{id:"13",title:"Veterinary Medicine and Science",numberOfPublishedBooks:11,numberOfPublishedChapters:104,numberOfOpenTopics:3,numberOfUpcomingTopics:0,issn:"2632-0517",doi:"10.5772/intechopen.73681",isOpenForSubmission:!0}],sshSeriesList:[{id:"22",title:"Business, Management and Economics",numberOfPublishedBooks:1,numberOfPublishedChapters:12,numberOfOpenTopics:2,numberOfUpcomingTopics:1,issn:"2753-894X",doi:"10.5772/intechopen.100359",isOpenForSubmission:!0},{id:"23",title:"Education and Human Development",numberOfPublishedBooks:0,numberOfPublishedChapters:0,numberOfOpenTopics:2,numberOfUpcomingTopics:0,issn:null,doi:"10.5772/intechopen.100360",isOpenForSubmission:!1},{id:"24",title:"Sustainable Development",numberOfPublishedBooks:0,numberOfPublishedChapters:12,numberOfOpenTopics:5,numberOfUpcomingTopics:0,issn:null,doi:"10.5772/intechopen.100361",isOpenForSubmission:!0}],testimonialsList:[{id:"6",text:"It is great to work with the IntechOpen to produce a worthwhile collection of research that also becomes a great educational resource and guide for future research endeavors.",author:{id:"259298",name:"Edward",surname:"Narayan",institutionString:null,profilePictureURL:"https://mts.intechopen.com/storage/users/259298/images/system/259298.jpeg",slug:"edward-narayan",institution:{id:"3",name:"University of Queensland",country:{id:null,name:"Australia"}}}},{id:"13",text:"The collaboration with and support of the technical staff of IntechOpen is fantastic. The whole process of submitting an article and editing of the submitted article goes extremely smooth and fast, the number of reads and downloads of chapters is high, and the contributions are also frequently cited.",author:{id:"55578",name:"Antonio",surname:"Jurado-Navas",institutionString:null,profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRisIQAS/Profile_Picture_1626166543950",slug:"antonio-jurado-navas",institution:{id:"720",name:"University of Malaga",country:{id:null,name:"Spain"}}}}]},series:{item:{id:"14",title:"Artificial Intelligence",doi:"10.5772/intechopen.79920",issn:"2633-1403",scope:"Artificial Intelligence (AI) is a rapidly developing multidisciplinary research area that aims to solve increasingly complex problems. In today's highly integrated world, AI promises to become a robust and powerful means for obtaining solutions to previously unsolvable problems. This Series is intended for researchers and students alike interested in this fascinating field and its many applications.",coverUrl:"https://cdn.intechopen.com/series/covers/14.jpg",latestPublicationDate:"May 18th, 2022",hasOnlineFirst:!0,numberOfPublishedBooks:9,editor:{id:"218714",title:"Prof.",name:"Andries",middleName:null,surname:"Engelbrecht",slug:"andries-engelbrecht",fullName:"Andries Engelbrecht",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRNR8QAO/Profile_Picture_1622640468300",biography:"Andries Engelbrecht received the Masters and PhD degrees in Computer Science from the University of Stellenbosch, South Africa, in 1994 and 1999 respectively. He is currently appointed as the Voigt Chair in Data Science in the Department of Industrial Engineering, with a joint appointment as Professor in the Computer Science Division, Stellenbosch University. Prior to his appointment at Stellenbosch University, he has been at the University of Pretoria, Department of Computer Science (1998-2018), where he was appointed as South Africa Research Chair in Artifical Intelligence (2007-2018), the head of the Department of Computer Science (2008-2017), and Director of the Institute for Big Data and Data Science (2017-2018). In addition to a number of research articles, he has written two books, Computational Intelligence: An Introduction and Fundamentals of Computational Swarm Intelligence.",institutionString:null,institution:{name:"Stellenbosch University",institutionURL:null,country:{name:"South Africa"}}},editorTwo:null,editorThree:null},subseries:{paginationCount:6,paginationItems:[{id:"22",title:"Applied Intelligence",coverUrl:"https://cdn.intechopen.com/series_topics/covers/22.jpg",isOpenForSubmission:!0,editor:{id:"27170",title:"Prof.",name:"Carlos",middleName:"M.",surname:"Travieso-Gonzalez",slug:"carlos-travieso-gonzalez",fullName:"Carlos Travieso-Gonzalez",profilePictureURL:"https://mts.intechopen.com/storage/users/27170/images/system/27170.jpeg",biography:"Carlos M. Travieso-González received his MSc degree in Telecommunication Engineering at Polytechnic University of Catalonia (UPC), Spain in 1997, and his Ph.D. degree in 2002 at the University of Las Palmas de Gran Canaria (ULPGC-Spain). He is a full professor of signal processing and pattern recognition and is head of the Signals and Communications Department at ULPGC, teaching from 2001 on subjects on signal processing and learning theory. His research lines are biometrics, biomedical signals and images, data mining, classification system, signal and image processing, machine learning, and environmental intelligence. He has researched in 52 international and Spanish research projects, some of them as head researcher. He is co-author of 4 books, co-editor of 27 proceedings books, guest editor for 8 JCR-ISI international journals, and up to 24 book chapters. He has over 450 papers published in international journals and conferences (81 of them indexed on JCR – ISI - Web of Science). He has published seven patents in the Spanish Patent and Trademark Office. He has been a supervisor on 8 Ph.D. theses (11 more are under supervision), and 130 master theses. He is the founder of The IEEE IWOBI conference series and the president of its Steering Committee, as well as the founder of both the InnoEducaTIC and APPIS conference series. He is an evaluator of project proposals for the European Union (H2020), Medical Research Council (MRC, UK), Spanish Government (ANECA, Spain), Research National Agency (ANR, France), DAAD (Germany), Argentinian Government, and the Colombian Institutions. He has been a reviewer in different indexed international journals (<70) and conferences (<250) since 2001. He has been a member of the IASTED Technical Committee on Image Processing from 2007 and a member of the IASTED Technical Committee on Artificial Intelligence and Expert Systems from 2011. \n\nHe has held the general chair position for the following: ACM-APPIS (2020, 2021), IEEE-IWOBI (2019, 2020 and 2020), A PPIS (2018, 2019), IEEE-IWOBI (2014, 2015, 2017, 2018), InnoEducaTIC (2014, 2017), IEEE-INES (2013), NoLISP (2011), JRBP (2012), and IEEE-ICCST (2005)\n\nHe is an associate editor of the Computational Intelligence and Neuroscience Journal (Hindawi – Q2 JCR-ISI). He was vice dean from 2004 to 2010 in the Higher Technical School of Telecommunication Engineers at ULPGC and the vice dean of Graduate and Postgraduate Studies from March 2013 to November 2017. He won the “Catedra Telefonica” Awards in Modality of Knowledge Transfer, 2017, 2018, and 2019 editions, and awards in Modality of COVID Research in 2020.\n\nPublic References:\nResearcher ID http://www.researcherid.com/rid/N-5967-2014\nORCID https://orcid.org/0000-0002-4621-2768 \nScopus Author ID https://www.scopus.com/authid/detail.uri?authorId=6602376272\nScholar Google https://scholar.google.es/citations?user=G1ks9nIAAAAJ&hl=en \nResearchGate https://www.researchgate.net/profile/Carlos_Travieso",institutionString:null,institution:{name:"University of Las Palmas de Gran Canaria",institutionURL:null,country:{name:"Spain"}}},editorTwo:null,editorThree:null},{id:"23",title:"Computational Neuroscience",coverUrl:"https://cdn.intechopen.com/series_topics/covers/23.jpg",isOpenForSubmission:!0,editor:{id:"14004",title:"Dr.",name:"Magnus",middleName:null,surname:"Johnsson",slug:"magnus-johnsson",fullName:"Magnus Johnsson",profilePictureURL:"https://mts.intechopen.com/storage/users/14004/images/system/14004.png",biography:"Dr Magnus Johnsson is a cross-disciplinary scientist, lecturer, scientific editor and AI/machine learning consultant from Sweden. \n\nHe is currently at Malmö University in Sweden, but also held positions at Lund University in Sweden and at Moscow Engineering Physics Institute. \nHe holds editorial positions at several international scientific journals and has served as a scientific editor for books and special journal issues. \nHis research interests are wide and include, but are not limited to, autonomous systems, computer modeling, artificial neural networks, artificial intelligence, cognitive neuroscience, cognitive robotics, cognitive architectures, cognitive aids and the philosophy of mind. \n\nDr. Johnsson has experience from working in the industry and he has a keen interest in the application of neural networks and artificial intelligence to fields like industry, finance, and medicine. \n\nWeb page: www.magnusjohnsson.se",institutionString:null,institution:{name:"Malmö University",institutionURL:null,country:{name:"Sweden"}}},editorTwo:null,editorThree:null},{id:"24",title:"Computer Vision",coverUrl:"https://cdn.intechopen.com/series_topics/covers/24.jpg",isOpenForSubmission:!0,editor:{id:"294154",title:"Prof.",name:"George",middleName:null,surname:"Papakostas",slug:"george-papakostas",fullName:"George Papakostas",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002hYaGbQAK/Profile_Picture_1624519712088",biography:"George A. Papakostas has received a diploma in Electrical and Computer Engineering in 1999 and the M.Sc. and Ph.D. degrees in Electrical and Computer Engineering in 2002 and 2007, respectively, from the Democritus University of Thrace (DUTH), Greece. Dr. Papakostas serves as a Tenured Full Professor at the Department of Computer Science, International Hellenic University, Greece. Dr. Papakostas has 10 years of experience in large-scale systems design as a senior software engineer and technical manager, and 20 years of research experience in the field of Artificial Intelligence. Currently, he is the Head of the “Visual Computing” division of HUman-MAchines INteraction Laboratory (HUMAIN-Lab) and the Director of the MPhil program “Advanced Technologies in Informatics and Computers” hosted by the Department of Computer Science, International Hellenic University. He has (co)authored more than 150 publications in indexed journals, international conferences and book chapters, 1 book (in Greek), 3 edited books, and 5 journal special issues. His publications have more than 2100 citations with h-index 27 (GoogleScholar). His research interests include computer/machine vision, machine learning, pattern recognition, computational intelligence. \nDr. Papakostas served as a reviewer in numerous journals, as a program\ncommittee member in international conferences and he is a member of the IAENG, MIR Labs, EUCogIII, INSTICC and the Technical Chamber of Greece (TEE).",institutionString:null,institution:{name:"International Hellenic University",institutionURL:null,country:{name:"Greece"}}},editorTwo:null,editorThree:null},{id:"25",title:"Evolutionary Computation",coverUrl:"https://cdn.intechopen.com/series_topics/covers/25.jpg",isOpenForSubmission:!0,editor:{id:"136112",title:"Dr.",name:"Sebastian",middleName:null,surname:"Ventura Soto",slug:"sebastian-ventura-soto",fullName:"Sebastian Ventura Soto",profilePictureURL:"https://mts.intechopen.com/storage/users/136112/images/system/136112.png",biography:"Sebastian Ventura is a Spanish researcher, a full professor with the Department of Computer Science and Numerical Analysis, University of Córdoba. Dr Ventura also holds the positions of Affiliated Professor at Virginia Commonwealth University (Richmond, USA) and Distinguished Adjunct Professor at King Abdulaziz University (Jeddah, Saudi Arabia). Additionally, he is deputy director of the Andalusian Research Institute in Data Science and Computational Intelligence (DaSCI) and heads the Knowledge Discovery and Intelligent Systems Research Laboratory. He has published more than ten books and over 300 articles in journals and scientific conferences. Currently, his work has received over 18,000 citations according to Google Scholar, including more than 2200 citations in 2020. In the last five years, he has published more than 60 papers in international journals indexed in the JCR (around 70% of them belonging to first quartile journals) and he has edited some Springer books “Supervised Descriptive Pattern Mining” (2018), “Multiple Instance Learning - Foundations and Algorithms” (2016), and “Pattern Mining with Evolutionary Algorithms” (2016). He has also been involved in more than 20 research projects supported by the Spanish and Andalusian governments and the European Union. He currently belongs to the editorial board of PeerJ Computer Science, Information Fusion and Engineering Applications of Artificial Intelligence journals, being also associate editor of Applied Computational Intelligence and Soft Computing and IEEE Transactions on Cybernetics. Finally, he is editor-in-chief of Progress in Artificial Intelligence. He is a Senior Member of the IEEE Computer, the IEEE Computational Intelligence, and the IEEE Systems, Man, and Cybernetics Societies, and the Association of Computing Machinery (ACM). Finally, his main research interests include data science, computational intelligence, and their applications.",institutionString:null,institution:{name:"University of Córdoba",institutionURL:null,country:{name:"Spain"}}},editorTwo:null,editorThree:null},{id:"26",title:"Machine Learning and Data Mining",coverUrl:"https://cdn.intechopen.com/series_topics/covers/26.jpg",isOpenForSubmission:!0,editor:{id:"24555",title:"Dr.",name:"Marco Antonio",middleName:null,surname:"Aceves Fernandez",slug:"marco-antonio-aceves-fernandez",fullName:"Marco Antonio Aceves Fernandez",profilePictureURL:"https://mts.intechopen.com/storage/users/24555/images/system/24555.jpg",biography:"Dr. Marco Antonio Aceves Fernandez obtained his B.Sc. (Eng.) in Telematics from the Universidad de Colima, Mexico. He obtained both his M.Sc. and Ph.D. from the University of Liverpool, England, in the field of Intelligent Systems. He is a full professor at the Universidad Autonoma de Queretaro, Mexico, and a member of the National System of Researchers (SNI) since 2009. Dr. Aceves Fernandez has published more than 80 research papers as well as a number of book chapters and congress papers. He has contributed in more than 20 funded research projects, both academic and industrial, in the area of artificial intelligence, ranging from environmental, biomedical, automotive, aviation, consumer, and robotics to other applications. He is also a honorary president at the National Association of Embedded Systems (AMESE), a senior member of the IEEE, and a board member of many institutions. His research interests include intelligent and embedded systems.",institutionString:"Universidad Autonoma de Queretaro",institution:{name:"Autonomous University of Queretaro",institutionURL:null,country:{name:"Mexico"}}},editorTwo:null,editorThree:null},{id:"27",title:"Multi-Agent Systems",coverUrl:"https://cdn.intechopen.com/series_topics/covers/27.jpg",isOpenForSubmission:!0,editor:{id:"148497",title:"Dr.",name:"Mehmet",middleName:"Emin",surname:"Aydin",slug:"mehmet-aydin",fullName:"Mehmet Aydin",profilePictureURL:"https://mts.intechopen.com/storage/users/148497/images/system/148497.jpg",biography:"Dr. Mehmet Emin Aydin is a Senior Lecturer with the Department of Computer Science and Creative Technology, the University of the West of England, Bristol, UK. His research interests include swarm intelligence, parallel and distributed metaheuristics, machine learning, intelligent agents and multi-agent systems, resource planning, scheduling and optimization, combinatorial optimization. Dr. Aydin is currently a Fellow of Higher Education Academy, UK, a member of EPSRC College, a senior member of IEEE and a senior member of ACM. In addition to being a member of advisory committees of many international conferences, he is an Editorial Board Member of various peer-reviewed international journals. He has served as guest editor for a number of special issues of peer-reviewed international journals.",institutionString:null,institution:{name:"University of the West of England",institutionURL:null,country:{name:"United Kingdom"}}},editorTwo:null,editorThree:null}]},overviewPageOFChapters:{paginationCount:17,paginationItems:[{id:"81791",title:"Self-Supervised Contrastive Representation Learning in Computer Vision",doi:"10.5772/intechopen.104785",signatures:"Yalin Bastanlar and Semih Orhan",slug:"self-supervised-contrastive-representation-learning-in-computer-vision",totalDownloads:12,totalCrossrefCites:0,totalDimensionsCites:0,authors:null,book:{title:"Pattern Recognition - New Insights",coverURL:"https://cdn.intechopen.com/books/images_new/11442.jpg",subseries:{id:"26",title:"Machine Learning and Data Mining"}}},{id:"79345",title:"Application of Jump Diffusion Models in Insurance Claim Estimation",doi:"10.5772/intechopen.99853",signatures:"Leonard Mushunje, Chiedza Elvina Mashiri, Edina Chandiwana and Maxwell Mashasha",slug:"application-of-jump-diffusion-models-in-insurance-claim-estimation-1",totalDownloads:2,totalCrossrefCites:0,totalDimensionsCites:0,authors:null,book:{title:"Data Clustering",coverURL:"https://cdn.intechopen.com/books/images_new/10820.jpg",subseries:{id:"26",title:"Machine Learning and Data Mining"}}},{id:"81557",title:"Object Tracking Using Adapted Optical Flow",doi:"10.5772/intechopen.102863",signatures:"Ronaldo Ferreira, Joaquim José de Castro Ferreira and António José Ribeiro Neves",slug:"object-tracking-using-adapted-optical-flow",totalDownloads:11,totalCrossrefCites:0,totalDimensionsCites:0,authors:null,book:{title:"Information Extraction and Object Tracking in Digital Video",coverURL:"https://cdn.intechopen.com/books/images_new/10652.jpg",subseries:{id:"24",title:"Computer Vision"}}},{id:"81558",title:"Thresholding Image Techniques for Plant Segmentation",doi:"10.5772/intechopen.104587",signatures:"Miguel Ángel Castillo-Martínez, Francisco Javier Gallegos-Funes, Blanca E. Carvajal-Gámez, Guillermo Urriolagoitia-Sosa and Alberto J. Rosales-Silva",slug:"thresholding-image-techniques-for-plant-segmentation",totalDownloads:16,totalCrossrefCites:0,totalDimensionsCites:0,authors:null,book:{title:"Information Extraction and Object Tracking in Digital Video",coverURL:"https://cdn.intechopen.com/books/images_new/10652.jpg",subseries:{id:"24",title:"Computer Vision"}}}]},overviewPagePublishedBooks:{paginationCount:9,paginationItems:[{type:"book",id:"7723",title:"Artificial Intelligence",subtitle:"Applications in Medicine and Biology",coverURL:"https://cdn.intechopen.com/books/images_new/7723.jpg",slug:"artificial-intelligence-applications-in-medicine-and-biology",publishedDate:"July 31st 2019",editedByType:"Edited by",bookSignature:"Marco Antonio Aceves-Fernandez",hash:"a3852659e727f95c98c740ed98146011",volumeInSeries:1,fullTitle:"Artificial Intelligence - Applications in Medicine and Biology",editors:[{id:"24555",title:"Dr.",name:"Marco Antonio",middleName:null,surname:"Aceves Fernandez",slug:"marco-antonio-aceves-fernandez",fullName:"Marco Antonio Aceves Fernandez",profilePictureURL:"https://mts.intechopen.com/storage/users/24555/images/system/24555.jpg",biography:"Dr. Marco Antonio Aceves Fernandez obtained his B.Sc. (Eng.) in Telematics from the Universidad de Colima, Mexico. He obtained both his M.Sc. and Ph.D. from the University of Liverpool, England, in the field of Intelligent Systems. He is a full professor at the Universidad Autonoma de Queretaro, Mexico, and a member of the National System of Researchers (SNI) since 2009. Dr. Aceves Fernandez has published more than 80 research papers as well as a number of book chapters and congress papers. He has contributed in more than 20 funded research projects, both academic and industrial, in the area of artificial intelligence, ranging from environmental, biomedical, automotive, aviation, consumer, and robotics to other applications. He is also a honorary president at the National Association of Embedded Systems (AMESE), a senior member of the IEEE, and a board member of many institutions. His research interests include intelligent and embedded systems.",institutionString:"Universidad Autonoma de Queretaro",institution:{name:"Autonomous University of Queretaro",institutionURL:null,country:{name:"Mexico"}}}]},{type:"book",id:"7726",title:"Swarm Intelligence",subtitle:"Recent Advances, New Perspectives and Applications",coverURL:"https://cdn.intechopen.com/books/images_new/7726.jpg",slug:"swarm-intelligence-recent-advances-new-perspectives-and-applications",publishedDate:"December 4th 2019",editedByType:"Edited by",bookSignature:"Javier Del Ser, Esther Villar and Eneko Osaba",hash:"e7ea7e74ce7a7a8e5359629e07c68d31",volumeInSeries:2,fullTitle:"Swarm Intelligence - Recent Advances, New Perspectives and Applications",editors:[{id:"49813",title:"Dr.",name:"Javier",middleName:null,surname:"Del Ser",slug:"javier-del-ser",fullName:"Javier Del Ser",profilePictureURL:"https://mts.intechopen.com/storage/users/49813/images/system/49813.png",biography:"Prof. Dr. Javier Del Ser received his first PhD in Telecommunication Engineering (Cum Laude) from the University of Navarra, Spain, in 2006, and a second PhD in Computational Intelligence (Summa Cum Laude) from the University of Alcala, Spain, in 2013. He is currently a principal researcher in data analytics and optimisation at TECNALIA (Spain), a visiting fellow at the Basque Center for Applied Mathematics (BCAM) and a part-time lecturer at the University of the Basque Country (UPV/EHU). His research interests gravitate on the use of descriptive, prescriptive and predictive algorithms for data mining and optimization in a diverse range of application fields such as Energy, Transport, Telecommunications, Health and Industry, among others. In these fields he has published more than 240 articles, co-supervised 8 Ph.D. theses, edited 6 books, coauthored 7 patents and participated/led more than 40 research projects. 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He is currently a full professor in\nthe Department of Automation and Applied Informatics at the\nsame university. Dr. Voloşencu is the author of ten books, seven\nbook chapters, and more than 160 papers published in journals\nand conference proceedings. He has also edited twelve books and\nhas twenty-seven patents to his name. He is a manager of research grants, editor in\nchief and member of international journal editorial boards, a former plenary speaker, a member of scientific committees, and chair at international conferences. His\nresearch is in the fields of control systems, control of electric drives, fuzzy control\nsystems, neural network applications, fault detection and diagnosis, sensor network\napplications, monitoring of distributed parameter systems, and power ultrasound\napplications. 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