Characteristics of the Earthquakes occurred in Mexico during 2009–2010. Their magnitudes are presented in bold (Catalogue of National Seismological Service, Mexico)
\\n\\n
Released this past November, the list is based on data collected from the Web of Science and highlights some of the world’s most influential scientific minds by naming the researchers whose publications over the previous decade have included a high number of Highly Cited Papers placing them among the top 1% most-cited.
\\n\\nWe wish to congratulate all of the researchers named and especially our authors on this amazing accomplishment! We are happy and proud to share in their success!
Note: Edited in March 2021
\\n"}]',published:!0,mainMedia:{caption:"Highly Cited",originalUrl:"/media/original/117"}},components:[{type:"htmlEditorComponent",content:'IntechOpen is proud to announce that 191 of our authors have made the Clarivate™ Highly Cited Researchers List for 2020, ranking them among the top 1% most-cited.
\n\nThroughout the years, the list has named a total of 261 IntechOpen authors as Highly Cited. Of those researchers, 69 have been featured on the list multiple times.
\n\n\n\nReleased this past November, the list is based on data collected from the Web of Science and highlights some of the world’s most influential scientific minds by naming the researchers whose publications over the previous decade have included a high number of Highly Cited Papers placing them among the top 1% most-cited.
\n\nWe wish to congratulate all of the researchers named and especially our authors on this amazing accomplishment! We are happy and proud to share in their success!
Note: Edited in March 2021
\n'}],latestNews:[{slug:"webinar-introduction-to-open-science-wednesday-18-may-1-pm-cest-20220518",title:"Webinar: Introduction to Open Science | Wednesday 18 May, 1 PM CEST"},{slug:"step-in-the-right-direction-intechopen-launches-a-portfolio-of-open-science-journals-20220414",title:"Step in the Right Direction: IntechOpen Launches a Portfolio of Open Science Journals"},{slug:"let-s-meet-at-london-book-fair-5-7-april-2022-olympia-london-20220321",title:"Let’s meet at London Book Fair, 5-7 April 2022, Olympia London"},{slug:"50-books-published-as-part-of-intechopen-and-knowledge-unlatched-ku-collaboration-20220316",title:"50 Books published as part of IntechOpen and Knowledge Unlatched (KU) Collaboration"},{slug:"intechopen-joins-the-united-nations-sustainable-development-goals-publishers-compact-20221702",title:"IntechOpen joins the United Nations Sustainable Development Goals Publishers Compact"},{slug:"intechopen-signs-exclusive-representation-agreement-with-lsr-libros-servicios-y-representaciones-s-a-de-c-v-20211123",title:"IntechOpen Signs Exclusive Representation Agreement with LSR Libros Servicios y Representaciones S.A. de C.V"},{slug:"intechopen-expands-partnership-with-research4life-20211110",title:"IntechOpen Expands Partnership with Research4Life"},{slug:"introducing-intechopen-book-series-a-new-publishing-format-for-oa-books-20210915",title:"Introducing IntechOpen Book Series - A New Publishing Format for OA Books"}]},book:{item:{type:"book",id:"10321",leadTitle:null,fullTitle:"Advances in Precision Medicine Oncology",title:"Advances in Precision Medicine Oncology",subtitle:null,reviewType:"peer-reviewed",abstract:"Recent advances in precision medicine and immuno-oncology have led to highly specific and efficacious cancer therapies such as monoclonal antibodies and immune checkpoint inhibitors (ICIs). This book provides an up-to-date overview of advances in the field of immuno-oncology. Chapters cover such topics as ICIs and how they mount a robust immune response against cancer cells as well as the response of ICIs to treatment predictive biomarkers and their potential immune-related adverse events (irAEs). Additionally, the book includes a comprehensive review of the powerful FDA-approved therapeutic agent doxorubicin, highlighting the molecular mechanisms behind doxorubicin’s drug resistance and critical side effects.",isbn:"978-1-83968-868-3",printIsbn:"978-1-83968-867-6",pdfIsbn:"978-1-83968-869-0",doi:"10.5772/intechopen.91507",price:119,priceEur:129,priceUsd:155,slug:"advances-in-precision-medicine-oncology",numberOfPages:260,isOpenForSubmission:!1,isInWos:null,isInBkci:!1,hash:"043ad1c1a6bbdcd5604917ccbff003d8",bookSignature:"Hilal Arnouk and Bassam Abdul Rasool Hassan",publishedDate:"July 21st 2021",coverURL:"https://cdn.intechopen.com/books/images_new/10321.jpg",numberOfDownloads:4202,numberOfWosCitations:0,numberOfCrossrefCitations:2,numberOfCrossrefCitationsByBook:0,numberOfDimensionsCitations:4,numberOfDimensionsCitationsByBook:0,hasAltmetrics:0,numberOfTotalCitations:6,isAvailableForWebshopOrdering:!0,dateEndFirstStepPublish:"September 24th 2020",dateEndSecondStepPublish:"October 22nd 2020",dateEndThirdStepPublish:"December 21st 2020",dateEndFourthStepPublish:"March 11th 2021",dateEndFifthStepPublish:"May 10th 2021",currentStepOfPublishingProcess:5,indexedIn:"1,2,3,4,5,6",editedByType:"Edited by",kuFlag:!1,featuredMarkup:null,editors:[{id:"76431",title:"Dr.",name:"Hilal",middleName:null,surname:"Arnouk",slug:"hilal-arnouk",fullName:"Hilal Arnouk",profilePictureURL:"https://mts.intechopen.com/storage/users/76431/images/system/76431.jpg",biography:"Hilal Arnouk, MD, Ph.D., is an Associate Professor at the Department of Pathology, Midwestern University, Downers Grove, Illinois. Dr. Arnouk received his education and post-doctorate training at Roswell Park Cancer Institute, the State University of New York at Buffalo, the Medical College of Georgia, and the University of Alabama at Birmingham. He has directed research studies in academia and biotech industry settings. His major areas of expertise include cancer immunotherapy, biomarker discovery, and precision medicine. Additionally, Dr. Arnouk tremendously enjoys being an educator and a mentor for professional students in the medical and biomedical sciences.",institutionString:null,position:null,outsideEditionCount:null,totalCites:0,totalAuthoredChapters:"1",totalChapterViews:"0",totalEditedBooks:"3",institution:{name:"Midwestern University",institutionURL:null,country:{name:"United States of America"}}}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,coeditorOne:{id:"155124",title:"Dr.",name:"Bassam",middleName:"Abdul Rasool",surname:"Hassan",slug:"bassam-hassan",fullName:"Bassam Hassan",profilePictureURL:"https://mts.intechopen.com/storage/users/155124/images/system/155124.png",biography:"Bassam Abdul Rasool Hassan obtained a Ph.D. in Clinical Pharmacy from the School of Pharmacy, Universiti Sains Malaysia (USM). He worked as a senior lecturer at the Department of Pharmacy, Faculty of Medicine, Universiti Malaya (UM), in 2014–2017, and at the Department of Pharmacy Practice, Faculty of Pharmacy, Universiti Teknologi MARA (UiTM), Shah Alam, Malaysia, in 2017–2019. Dr. Hassan currently works as a senior lecturer at the Department of Pharmacy, Al-Rafidain University College, Baghdad, Iraq.",institutionString:"Al-Rafidain University College",position:null,outsideEditionCount:0,totalCites:0,totalAuthoredChapters:"3",totalChapterViews:"0",totalEditedBooks:"1",institution:null},coeditorTwo:null,coeditorThree:null,coeditorFour:null,coeditorFive:null,topics:[{id:"1083",title:"Medical Oncology",slug:"medical-oncology"}],chapters:[{id:"76212",title:"Immune and Cell Cycle Checkpoint Inhibitors for Cancer Immunotherapy",doi:"10.5772/intechopen.96664",slug:"immune-and-cell-cycle-checkpoint-inhibitors-for-cancer-immunotherapy",totalDownloads:300,totalCrossrefCites:0,totalDimensionsCites:0,hasAltmetrics:0,abstract:"The rational design of immunotherapeutic agents has advanced with a fundamental understanding that both innate and adaptive immunity play important roles in cancer surveillance and tumor destruction; given that oncogenesis occurs and cancer progresses through the growth of tumor cells with low immunogenicity in an increasingly immunosuppressive tumor microenvironment. Checkpoint inhibitors in the form of monoclonal antibodies that block cancer’s ability to deactivate and evade the immune system have been widely indicated for a variety of tumor types. Through targeting the biological mechanisms and pathways that cancer cells use to interact with and suppress the immune system, immunotherapeutic agents have achieved success in inhibiting tumor growth while eliciting lesser toxicities, compared to treatments with standard chemotherapy. Development of “precise” bio-active tumor-targeted gene vectors, biotechnologies, and reagents has also advanced. This chapter presents ongoing clinical research involving immune checkpoint inhibitors, while addressing the clinical potential for tumor-targeted gene blockade in combination with tumor-targeted cytokine delivery, in patients with advanced metastatic disease, providing strategic clinical approaches to precision cancer immunotherapy.",signatures:"Erlinda M. Gordon, Nicole L. Angel, Ted T. Kim, Don A. Brigham, Sant P. Chawla and Frederick L. Hall",downloadPdfUrl:"/chapter/pdf-download/76212",previewPdfUrl:"/chapter/pdf-preview/76212",authors:[{id:"333221",title:"Dr.",name:"Erlinda M.",surname:"Gordon",slug:"erlinda-m.-gordon",fullName:"Erlinda M. Gordon"},{id:"337003",title:"Dr.",name:"Sant",surname:"Chawla",slug:"sant-chawla",fullName:"Sant Chawla"},{id:"337004",title:"Dr.",name:"Frederick",surname:"Hall",slug:"frederick-hall",fullName:"Frederick Hall"},{id:"346195",title:"Ms.",name:"Nicole",surname:"Angel",slug:"nicole-angel",fullName:"Nicole Angel"},{id:"346196",title:"Mr.",name:"Ted",surname:"Kim",slug:"ted-kim",fullName:"Ted Kim"},{id:"346197",title:"Dr.",name:"Don",surname:"Brigham",slug:"don-brigham",fullName:"Don Brigham"}],corrections:null},{id:"75496",title:"Evolving Dynamic Biomarkers for Prediction of Immune Responses to Checkpoint Inhibitors in Cancer",doi:"10.5772/intechopen.96494",slug:"evolving-dynamic-biomarkers-for-prediction-of-immune-responses-to-checkpoint-inhibitors-in-cancer",totalDownloads:284,totalCrossrefCites:0,totalDimensionsCites:0,hasAltmetrics:0,abstract:"Immune checkpoint inhibitors (ICIs) have been approved as first or second line therapy in a large group of cancers. However, the observation of potentially long-lasting responses was restricted to limited subset of patients. Efforts have been made to identify predictive factors of response to ICIs in order to select eligible patients and to avoid exposing non-responding patients to treatment side effects. Although several biomarkers have been identified, their predictive potential remains unsatisfactory. One promising emerging approach is to focus on dynamic biomarkers to directly characterize the response and, more importantly, to identify those patients presenting an immune response failure. Several studies have shown a strong correlation between specific circulating immune cell subsets and tumor immune infiltrates. Moreover, liquid biomarkers including soluble immune checkpoint molecules have potential in predicting the modulation of the immune response under immune checkpoint blockade. In this chapter, we will discuss current advances in the study of circulatory and intra-tumoral dynamic biomarkers as predictors of responses to ICIs therapy in cancer.",signatures:"Afsheen Raza, Maysaloun Merhi, Allan Relecom, Queenie Fernandes, Varghese Inchakalody, Abdul Rahman Zar Gul, Shahab Uddin, Mohammed Ussama Al Homsi and Said Dermime",downloadPdfUrl:"/chapter/pdf-download/75496",previewPdfUrl:"/chapter/pdf-preview/75496",authors:[{id:"336904",title:"Dr.",name:"Said",surname:"Dermime",slug:"said-dermime",fullName:"Said Dermime"},{id:"339275",title:"Dr.",name:"Maysaloun",surname:"Merhi",slug:"maysaloun-merhi",fullName:"Maysaloun Merhi"},{id:"339295",title:"MSc.",name:"Queenie",surname:"Fernandes",slug:"queenie-fernandes",fullName:"Queenie Fernandes"},{id:"339296",title:"Dr.",name:"Afsheen",surname:"Raza",slug:"afsheen-raza",fullName:"Afsheen Raza"},{id:"339297",title:"Dr.",name:"Varghese",surname:"Inchakalody",slug:"varghese-inchakalody",fullName:"Varghese Inchakalody"},{id:"339298",title:"Dr.",name:"Shahab",surname:"Uddin",slug:"shahab-uddin",fullName:"Shahab Uddin"},{id:"344921",title:"Dr.",name:"Allan",surname:"Relecom",slug:"allan-relecom",fullName:"Allan Relecom"},{id:"344923",title:"Dr.",name:"Abdul Rahman",surname:"Gul",slug:"abdul-rahman-gul",fullName:"Abdul Rahman Gul"},{id:"344924",title:"Dr.",name:"Mohammed",surname:"Al Homsi",slug:"mohammed-al-homsi",fullName:"Mohammed Al Homsi"}],corrections:null},{id:"75485",title:"The Endocrinological Side Effects of Immunotherapies",doi:"10.5772/intechopen.96491",slug:"the-endocrinological-side-effects-of-immunotherapies",totalDownloads:205,totalCrossrefCites:0,totalDimensionsCites:0,hasAltmetrics:0,abstract:"The use of immunotherapies is gaining importance in the treatment of advanced malignancies. There are many checkpoints in the immune system which prevents T-cells from attacking one’s own body cells. The cancer cells can camouflage from the T-cells and the immune system is unable to mount an effective anti-tumor response. The immunotherapies, mainly monoclonal antibodies anti-cytotoxic T-lymphocyte antigen 4 (CTLA-4), anti-programmed cell death protein-1 (PD-1) and anti-PD-1 ligand molecules (PD-L1 and L2) reactivate the immune system to act against cancerous cells but they can also cause T-cells to attack healthy cells causing various autoimmune diseases, which are known as immune related adverse events (irAEs). Current clinical data shows increased incidence of pituitary disorders with CTLA4 inhibitors and thyroid dysfunction in patients with PD-1/PD L-1 1 blockade. There have also been association of type 1 diabetes mellitus and primary adrenal insufficiency in patients with immune check point inhibitors. In this chapter we will discuss the incidence, characteristic findings, diagnosis and management of various endocrinological side effects due to targeted immunotherapies used in various malignancies.",signatures:"Anush Patel, Haisam Abid and Amrat Kumar",downloadPdfUrl:"/chapter/pdf-download/75485",previewPdfUrl:"/chapter/pdf-preview/75485",authors:[{id:"58496",title:"Dr.",name:"Anush",surname:"Patel",slug:"anush-patel",fullName:"Anush Patel"},{id:"336269",title:"Dr.",name:"Haisam",surname:"Abid",slug:"haisam-abid",fullName:"Haisam Abid"},{id:"336271",title:"Dr.",name:"Amrat",surname:"Kumar",slug:"amrat-kumar",fullName:"Amrat Kumar"}],corrections:null},{id:"75020",title:"Immunotherapy in Malignant Pleural Mesothelioma",doi:"10.5772/intechopen.95823",slug:"immunotherapy-in-malignant-pleural-mesothelioma",totalDownloads:285,totalCrossrefCites:0,totalDimensionsCites:0,hasAltmetrics:0,abstract:"Malignant pleural mesothelioma (MPM) is an extremely aggressive plural malignancy mainly caused by asbestos exposure. Basic research about the immune suppressive tumor microenvironment in MPM has suggested that MPM might be a good candidate for immune therapy. Immunocheckpoint inhibitors have shown some promising results. A phase Ib trial with pembrolizumab, an antibody specific for the programmed cell death 1 protein (anti-PD-1), showed efficacy in patients with programmed death-ligand 1 (PD-L1)-positive MPM. Among 25 patients tested, 5 patients (20%) achieved a partial response. A Japanese group evaluated the efficacy and safety of nivolumab, an anti-PD-L1 antibody, for patients with advanced MPM in a phase II study. Ten (29%) patients showed an objective response. Based on those results, nivolumab was approved in Japan for unresectable recurrent MPM. A phase III randomized study was conducted to compare nivolumab plus ipilimumab to platinum doublet chemotherapy as a first-line therapy in unresectable MPM. The primary endpoint, overall survival (OS), was significantly improved in the nivolumab plus ipilimumab group. Cellular therapies and cancer vaccines are limited by many challenges; therefore, improvements to overcome these difficulties are urgently warranted. Further research is needed, including large-scale clinical trials, to clarify the utility and safety of immunotherapy in MPM.",signatures:"Asako Matsuda and Nobukazu Fujimoto",downloadPdfUrl:"/chapter/pdf-download/75020",previewPdfUrl:"/chapter/pdf-preview/75020",authors:[{id:"307730",title:"Dr.",name:"Nobukazu",surname:"Fujimoto",slug:"nobukazu-fujimoto",fullName:"Nobukazu Fujimoto"},{id:"337549",title:"Dr.",name:"Asako",surname:"Matsuda",slug:"asako-matsuda",fullName:"Asako Matsuda"}],corrections:null},{id:"75475",title:"Targeted Cancer Therapy Using Nanoparticles and Antibody Fragments",doi:"10.5772/intechopen.96550",slug:"targeted-cancer-therapy-using-nanoparticles-and-antibody-fragments",totalDownloads:372,totalCrossrefCites:0,totalDimensionsCites:0,hasAltmetrics:0,abstract:"Cancer is caused by an uncontrolled cell division, forming a tumor capable of metastasis. Cancer is the second leading cause of death worldwide. Conventional treatments kill healthy cells, causing side effects. Recently, nanomaterials are explored due to properties such as as- nano-size, high loading, and ligands’ attachment for a selective delivery. Apart from normal body cells, cancer cells express many receptors in excess, which serve as ‘targets’ for attacking the cells. Various ligands like proteins, peptides, polysaccharides can be attached to nanoparticles to allow proper and specific reach to the tumor. Such nanoparticles go to their desired site and stick onto the receptors, taken inside the cells by various methods. Antibodies are natural proteins that bind to foreign substances and remove them. IgG being the most explored antibody, suffers from many disadvantages such as non-specificity for required antigen, limited binding sites, low tumor penetration. Hence many researchers experimented by removing and adjusting the binding sites, using only the binding sites, enhancing the valency of naturally available IgG. It gave many benefits such as enhanced penetration, reduced immunogenicity, better delivery of drugs with fewer side effects. Continuing advancements in the field of protein engineering will help scientists to come up with better solutions. The properties allow easy surface interaction and entry, achieve better biodistribution, and reduce the amount of drug required. Targeting is based on Paul Ehrlich’s ‘magic bullet, ‘where the therapeutic moiety has two parts-one to identify the target and the second to eliminate it. This concept is revised to incorporate a third component, a carrier. Many nanocarriers can be used to target cancer cells containing ligands to identify malignant cells. Approaches to targeting are passive, active and physical targeting. Many such nanoparticles are in clinical trials and can be a better solution to cancer therapy.",signatures:"Sankha Bhattacharya and Kapil Gore",downloadPdfUrl:"/chapter/pdf-download/75475",previewPdfUrl:"/chapter/pdf-preview/75475",authors:[{id:"250076",title:"Dr.",name:"Sankha",surname:"Bhattacharya",slug:"sankha-bhattacharya",fullName:"Sankha Bhattacharya"},{id:"344172",title:"Mr.",name:"Kapil",surname:"Gore",slug:"kapil-gore",fullName:"Kapil Gore"}],corrections:null},{id:"75838",title:"Antibody Therapy Targeting Cancer-Specific Cell Surface Antigen AGR2",doi:"10.5772/intechopen.96492",slug:"antibody-therapy-targeting-cancer-specific-cell-surface-antigen-agr2",totalDownloads:293,totalCrossrefCites:0,totalDimensionsCites:0,hasAltmetrics:0,abstract:"For anterior gradient 2 (AGR2), normal cells express the intracellular form iAGR2 localized to the endoplasmic reticulum while cancer cells express the extracellular form eAGR2 localized on the cell surface and secreted. Antibodies targeting eAGR2+ cancer cells for eradication will spare normal cells. Two AGR2 monoclonal antibodies, P1G4 and P3A5, were shown to recognize specifically eAGR2+ pancreatic tumors implanted in mice. In addition, P1G4 showed enhancement in drug inhibition of tumor growth. Human:mouse chimeric antibodies of IgG1, IgG2, IgG4 were generated for both antibodies. These human IgG were shown to lyse eAGR2+ prostate cancer cells in vitro with human serum. AGR2 has an important function in distal spread of cancer cells, and is highly expressed in prostate, pancreatic, bladder metastases. Therefore, immunotherapy based on AGR2 antibody-mediated ADCC and CDC is highly promising. Cancer specificity of eAGR2 predicts possibly minimal collateral damage to healthy tissues and organs. Moreover, AGR2 therapy, once fully developed and approved, can be used to treat other solid tumors since AGR2 is an adenocarcinoma antigen found in many common malignancies.",signatures:"Alvin Y. Liu, Tatjana Crnogorac-Jurcevic, James J. Lai and Hung-Ming Lam",downloadPdfUrl:"/chapter/pdf-download/75838",previewPdfUrl:"/chapter/pdf-preview/75838",authors:[{id:"337480",title:"Associate Prof.",name:"Alvin Y.",surname:"Liu",slug:"alvin-y.-liu",fullName:"Alvin Y. Liu"},{id:"345022",title:"Dr.",name:"Tatjana",surname:"Crnogorac-Jurcevic",slug:"tatjana-crnogorac-jurcevic",fullName:"Tatjana Crnogorac-Jurcevic"},{id:"345023",title:"Dr.",name:"James J.",surname:"Lai",slug:"james-j.-lai",fullName:"James J. Lai"},{id:"345024",title:"Dr.",name:"Hung-Ming",surname:"Lam",slug:"hung-ming-lam",fullName:"Hung-Ming Lam"}],corrections:null},{id:"74972",title:"Advances in Adoptive Cellular Therapy (ACT)",doi:"10.5772/intechopen.95854",slug:"advances-in-adoptive-cellular-therapy-act-",totalDownloads:207,totalCrossrefCites:0,totalDimensionsCites:0,hasAltmetrics:0,abstract:"Adoptive T cell therapy (ACT) is getting acknowledged as the Advanced Therapy Medicinal Products (ATMPs) in many countries and it has evolved as one of the newest regimens to treat cancer. Developed gradually by the basic understanding of cells, involved in innate and adaptive immunity, ACT has emerged as one of the successful immunotherapies in recent times. It broadly includes various cell types such as stem cells, T cells, dendritic cells and Natural Killer cells. By the applications of genetic engineering and advanced cell culture techniques, these cells from patients’ blood, can be manipulated to train them for better efficacy against specific tumor cells. However, only some cells’ subsets have shown promising regression for certain cancer cells types. To understand the reason behind this, technical knowledge about the tumor antigens presentation, tumor microenvironment (TME), hosts’ immune responses and possible issues in the manufacturing of adoptive cellular material for infusion in patients are being explored further. This chapter brings together development of immune cells from basic research to clinical use, newer approaches which have been taken to address the resistance of ACT and future promises of this therapy.",signatures:"Rajesh Kumar Yadav, Bandana Kumari, Pritanjali Singh, Asgar Ali, Sadhana Sharma and Krishnan Hajela",downloadPdfUrl:"/chapter/pdf-download/74972",previewPdfUrl:"/chapter/pdf-preview/74972",authors:[{id:"335174",title:"Prof.",name:"Sadhana",surname:"Sharma",slug:"sadhana-sharma",fullName:"Sadhana Sharma"},{id:"335348",title:"Dr.",name:"Rajesh Kumar",surname:"Yadav",slug:"rajesh-kumar-yadav",fullName:"Rajesh Kumar Yadav"},{id:"344952",title:"Dr.",name:"Bandana",surname:"Kumari",slug:"bandana-kumari",fullName:"Bandana Kumari"},{id:"344953",title:"Dr.",name:"Asgar",surname:"Ali",slug:"asgar-ali",fullName:"Asgar Ali"},{id:"344954",title:"Dr.",name:"Pritanjali",surname:"Singh",slug:"pritanjali-singh",fullName:"Pritanjali Singh"},{id:"420204",title:"Dr.",name:"Krishnan",surname:"Hajela",slug:"krishnan-hajela",fullName:"Krishnan Hajela"}],corrections:null},{id:"76116",title:"Mathematical Modeling and Dynamics of Oncolytic Virotherapy",doi:"10.5772/intechopen.96963",slug:"mathematical-modeling-and-dynamics-of-oncolytic-virotherapy",totalDownloads:208,totalCrossrefCites:0,totalDimensionsCites:0,hasAltmetrics:0,abstract:"Oncolytic virotherapy is a cancer treatment that uses competent replicating viruses to destroy cancer cells. This field progressed from earlier observations of accidental viral infections causing remission in many malignancies to virus drugs targeting and killing cancer cells. In this chapter, we study some basic models of the oncolytic virotherapy and their dynamics. We show how the dynamical system’s theory can capture the behavior of the solutions of those models and provide different approaches to studying the models. We study the thresholds that enable us to classify asymptotic dynamics of the solutions. Fractional-derivative approach tells us about the memory of the derivative and related solutions of the models. We also study the affect of introducing control parameters on the cost of the therapy.",signatures:"Abdullah Abu-Rqayiq",downloadPdfUrl:"/chapter/pdf-download/76116",previewPdfUrl:"/chapter/pdf-preview/76116",authors:[{id:"315106",title:"Dr.",name:"Abdullah",surname:"Abu-Rqayiq",slug:"abdullah-abu-rqayiq",fullName:"Abdullah Abu-Rqayiq"}],corrections:null},{id:"73668",title:"Molecular-Level Understanding of the Anticancer Action Mechanism of Anthracyclines",doi:"10.5772/intechopen.94180",slug:"molecular-level-understanding-of-the-anticancer-action-mechanism-of-anthracyclines",totalDownloads:551,totalCrossrefCites:0,totalDimensionsCites:0,hasAltmetrics:0,abstract:"Anthracyclines drugs are used as a treatment regime to combat cancer owing to their great chemotherapeutic potential. They are characterized by the presence of a wide range of derivatives, the most famous are doxorubicin and daunorubicin. The proposed action mechanism of anthracyclines and their derivatives to exert cytotoxic effect involves the intercalation of the drug molecule into nucleic acid and inhibition of the activity of topoisomerases. These events consequences in halting DNA replication and transcription mechanisms of the cell. Understanding of the structural and conformational changes associated with nucleic acid after binding with drugs provides significant knowledge for the development of more effective drugs. A comprehensive elucidation of the molecular mechanism(s) of action of anthracyclines drugs plays a significant role in the rational drug designing to obtain an effective, selective, and safe anti-cancer drugs.",signatures:"Manish Shandilya, Shrutika Sharma, Prabhu Prasad Das and Sonika Charak",downloadPdfUrl:"/chapter/pdf-download/73668",previewPdfUrl:"/chapter/pdf-preview/73668",authors:[{id:"325803",title:"Dr.",name:"Sonika",surname:"Charak",slug:"sonika-charak",fullName:"Sonika Charak"},{id:"326284",title:"Dr.",name:"Manish",surname:"Shandilya",slug:"manish-shandilya",fullName:"Manish Shandilya"},{id:"326287",title:"Ms.",name:"Shrutika",surname:"Sharma",slug:"shrutika-sharma",fullName:"Shrutika Sharma"},{id:"330638",title:"Dr.",name:"Prabhu Prasad",surname:"Das",slug:"prabhu-prasad-das",fullName:"Prabhu Prasad Das"}],corrections:null},{id:"74276",title:"Overview on the Side Effects of Doxorubicin",doi:"10.5772/intechopen.94896",slug:"overview-on-the-side-effects-of-doxorubicin",totalDownloads:537,totalCrossrefCites:1,totalDimensionsCites:2,hasAltmetrics:0,abstract:"Doxorubicin is an anthracycline antibiotic extracted from the bacterium Streptomyces peucetius. Its cytotoxic effect produced by intercalating with DNA causing breakdown of DNA strand which causes cancer cell apoptosis. Despite being an effective anticancer agent it causes several crucial side effects like carditoxicity, neuropathy, hepatotoxicity, nephrotoxicity, alopecia, typhlitis, myelosuppression, neutropenia, anaemia, thrombocytopenia, nausea, and diarrhoea were caused mainly due to the inability to distinguish between cancer cells and normal cells. This chapter mainly focuses on doxorubicin’s side effects, current understanding of the molecular mechanisms, and management and preventive strategies of doxorubicin’s cardiotoxicity during the treatment of various type of cancer.",signatures:"Chittipolu Ajaykumar",downloadPdfUrl:"/chapter/pdf-download/74276",previewPdfUrl:"/chapter/pdf-preview/74276",authors:[{id:"327203",title:"Assistant Prof.",name:"Chittipolu",surname:"Ajaykumar",slug:"chittipolu-ajaykumar",fullName:"Chittipolu Ajaykumar"}],corrections:null},{id:"74811",title:"Overcoming P-Glycoprotein-Mediated Doxorubicin Resistance",doi:"10.5772/intechopen.95553",slug:"overcoming-p-glycoprotein-mediated-doxorubicin-resistance",totalDownloads:484,totalCrossrefCites:0,totalDimensionsCites:1,hasAltmetrics:0,abstract:"Intracellular concentration of doxorubicin in target cancer cells is a major determinant of therapeutic success of doxorubicin-based regimens. As known, doxorubicin is a substrate of P-glycoprotein (P-gp), the drug efflux transporter in the ABC superfamily. High expression level of P-gp in cancer cells can prevent intracellular accumulation of doxorubicin up to its effective level, leading to doxorubicin resistance and treatment failure. Moreover, these P-gp-overexpressed cells display multi-drug resistance (MDR) phenotype. Regarding this, application of P-gp modulators (suppressor of P-gp activity and expression) is likely to reverse MDR and restore cell sensitivity to doxorubicin treatment. In searching for potential chemo-sensitizer against resistant cancer, a number of phytochemicals or dietary compounds have been studied extensively for their P-gp modulating effects. Furthermore, combination between doxorubicin and P-gp modulators (e.g., plant-derived compounds, siRNA) given through specific target delivery platforms have been an effective strategic approach for MDR reversal and restore doxorubicin effectiveness for cancer treatment.",signatures:"Suree Jianmongkol",downloadPdfUrl:"/chapter/pdf-download/74811",previewPdfUrl:"/chapter/pdf-preview/74811",authors:[{id:"317928",title:"Associate Prof.",name:"Suree",surname:"Jianmongkol",slug:"suree-jianmongkol",fullName:"Suree Jianmongkol"}],corrections:null},{id:"76820",title:"Improving the Antitumor Effect of Doxorubicin in the Treatment of Eyeball and Orbital Tumors",doi:"10.5772/intechopen.95080",slug:"improving-the-antitumor-effect-of-doxorubicin-in-the-treatment-of-eyeball-and-orbital-tumors",totalDownloads:253,totalCrossrefCites:0,totalDimensionsCites:0,hasAltmetrics:0,abstract:"Malignant tumors of the orbit are the main cause for 41–45.9% of orbital tumor, and they will threaten both the organ of vision and the life of the patient. In our opinion, improving the effectiveness of treatment of malignant tumors can be implemented in the following areas: a) immobilization of doxorubicin in synthetic polymeric materials, which will fill the tissue structures that were resected and reduce the percentage of tumor recurrence. b) the use of nanomaterials for the delivery of doxorubicin to tumor cells. To develop a hydrogel implant and nanoparticles, to study the diffusion kinetics of doxorubicin in a hydrogel implant and the ability of nanoparticles to transport doxorubicin. The developed gels based on acrylic acid (AAc) were obtained by radical polymerization of an aqueous solution of monomers (AAc and N, N-methylenebisacrylamide (MBA)) at a temperature of 70°C. Matrices based on polyvinyl formal (PVF) were obtained by treatment of polyvinyl alcohol (PVA) with formaldehyde in the presence of a strong acid. Experimental studies were performed on rabbits of the Chinchilla breed, weighing 2–3 kg, aged 5–6 months, which during the study were in the same conditions. We implanted the hybrid gel in the scleral sac; orbital tissue and in the ear tissue of rabbits: Evaluation of the response of soft tissues and bone structures to implant materials was carried out on the basis of analysis of changes in clinical and pathomorphological parameters was performed after 10, 30 and 60 days. Diffusion of doxorubicin was examined by using UV spectroscopy [spectrophotometer-fluorimeter DS-11 FX + (DeNovix, USA)], analyzing samples at regular intervals during the day at a temperature of 25° C. The concentration of active substances was determined by the normalized peak absorption of doxorubicin at 480 nm. The release kinetics of the antitumor drug doxorubicin were investigated by using a UV spectrometer “Specord M 40” (maximum absorption 480 nm). The developed hydrogel implant has good biocompatibility and germination of surrounding tissues in the structure of the implant, as well as the formation of a massive fibrous capsule around it. An important advantage of the implant is also the lack of its tendency to resorption. Moreover, the results showed that the diffusion kinetics of doxorubicin from a liquid-crosslinked hydrogel reaches a minimum therapeutic level within a few minutes, while in the case of a tightly crosslinked - after a few hours. It was also found that the liquid-crosslinked hydrogel adsorbs twice as much as the cytostatic - doxorubicin. The analysis of the research results approved that the size of the nanoparticles is the main factor for improving drug delevary and penetration. Thus, nanoparticles with a diameter of less than 200 nm can penetrate into cells and are not removed from the circulatory system by macrophages, thereby prolonging their circulation in the body. About 10 nm. The developed hybrid hydrogel compositions have high mechanical strength, porosity, which provides 100% penetration of doxorubicin into experimental animal tissues. It was found that the kinetics of diffusion of drugs from liquid-crosslinked hydrogel reaches a minimum therapeutic level within a few minutes, whereas in the case of densely crosslinked hydrogel diffusion begins with a delay of several hours and the amount of drug released at equilibrium reaches much lower values (20–25%). The obtained preliminary experimental results allow us to conclude that our developed pathways for the delivery of drugs, in particular, doxorubicin to tumor cells will increase the effectiveness of antitumor therapy.",signatures:"Anatoliy Parfentievich Maletskyy, Yuriy Markovich Samchenko and Natalia Mikhailivna Bigun",downloadPdfUrl:"/chapter/pdf-download/76820",previewPdfUrl:"/chapter/pdf-preview/76820",authors:[{id:"325981",title:"Prof.",name:"Anatoliy Parfentievich",surname:"Maletskyy",slug:"anatoliy-parfentievich-maletskyy",fullName:"Anatoliy Parfentievich Maletskyy"},{id:"326712",title:"Dr.",name:"Yuriy Markovich",surname:"Samchenko",slug:"yuriy-markovich-samchenko",fullName:"Yuriy Markovich Samchenko"},{id:"333970",title:"Dr.",name:"Natalia Mikhailivna",surname:"Bigun",slug:"natalia-mikhailivna-bigun",fullName:"Natalia Mikhailivna Bigun"}],corrections:null},{id:"76515",title:"The Paradigm of Targeting an Oncogenic Tyrosine Kinase: Lesson from BCR-ABL",doi:"10.5772/intechopen.97528",slug:"the-paradigm-of-targeting-an-oncogenic-tyrosine-kinase-lesson-from-bcr-abl",totalDownloads:223,totalCrossrefCites:1,totalDimensionsCites:1,hasAltmetrics:0,abstract:"The aberrant tyrosine phosphorylation, either due to constitutive tyrosine kinases (TKs) or to inactivation of protein tyrosine phosphatases (PTPs), is a widespread feature of many cancerous cells. The BCR-ABL fusion protein, which arises from the Philadelphia chromosome, is a molecular distinct and peculiar trait of some kind of leukemia, namely Chronic Myeloid and Acute Lymphoblastic Leukemia, and displays constitutive tyrosine kinase activity. In the chapter, we will highlight the milestones that had led to the identification of the BCR-ABL fusion gene and its role as the only molecular pathogenic event sufficient to elicit and sustain chronic myeloid leukemia. We will also discuss the effort made to unveil the molecular mechanisms of action of the chimeric tyrosine kinase that eventually lead to aberrant cell proliferation and impaired cell-death. Furthermore, we will also review the lesson learned from the selective inhibition of BCR-ABL which currently represent a breakthrough in the treatment of several tumors characterized by defective tyrosine kinase activity.",signatures:"Enrico Bracco, M. Shahzad Ali, Stefano Magnati and Giuseppe Saglio",downloadPdfUrl:"/chapter/pdf-download/76515",previewPdfUrl:"/chapter/pdf-preview/76515",authors:[{id:"58476",title:"Prof.",name:"Giuseppe",surname:"Saglio",slug:"giuseppe-saglio",fullName:"Giuseppe Saglio"},{id:"343243",title:"Assistant Prof.",name:"Enrico",surname:"Bracco",slug:"enrico-bracco",fullName:"Enrico Bracco"},{id:"352739",title:"Dr.",name:"Muhammad S.",surname:"Ali",slug:"muhammad-s.-ali",fullName:"Muhammad S. Ali"},{id:"352740",title:"BSc.",name:"Stefano",surname:"Magnati",slug:"stefano-magnati",fullName:"Stefano Magnati"}],corrections:null}],productType:{id:"1",title:"Edited Volume",chapterContentType:"chapter",authoredCaption:"Edited by"},subseries:null,tags:null},relatedBooks:[{type:"book",id:"8025",title:"Cancer Immunotherapy and Biological Cancer Treatments",subtitle:null,isOpenForSubmission:!1,hash:"e9953ff7bc3b22ae75810e286dd86b73",slug:"cancer-immunotherapy-and-biological-cancer-treatments",bookSignature:"Hilal Arnouk",coverURL:"https://cdn.intechopen.com/books/images_new/8025.jpg",editedByType:"Edited by",editors:[{id:"76431",title:"Dr.",name:"Hilal",surname:"Arnouk",slug:"hilal-arnouk",fullName:"Hilal Arnouk"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"946",title:"Advancements in Tumor Immunotherapy and Cancer Vaccines",subtitle:null,isOpenForSubmission:!1,hash:"aa9eb0c98931a6c6e516ecf1962f99a4",slug:"advancements-in-tumor-immunotherapy-and-cancer-vaccines",bookSignature:"Hilal Arnouk",coverURL:"https://cdn.intechopen.com/books/images_new/946.jpg",editedByType:"Edited by",editors:[{id:"76431",title:"Dr.",name:"Hilal",surname:"Arnouk",slug:"hilal-arnouk",fullName:"Hilal Arnouk"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"374",title:"Current Cancer Treatment",subtitle:"Novel Beyond Conventional Approaches",isOpenForSubmission:!1,hash:"d752cf5b05d575243ec2c2144073f579",slug:"current-cancer-treatment-novel-beyond-conventional-approaches",bookSignature:"Öner Özdemir",coverURL:"https://cdn.intechopen.com/books/images_new/374.jpg",editedByType:"Edited by",editors:[{id:"52298",title:"Prof.",name:"Oner",surname:"Ozdemir",slug:"oner-ozdemir",fullName:"Oner Ozdemir"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"3273",title:"Cancer Treatment",subtitle:"Conventional and Innovative Approaches",isOpenForSubmission:!1,hash:"cdd9872a05001212b3583bff95bae979",slug:"cancer-treatment-conventional-and-innovative-approaches",bookSignature:"Letícia Rangel",coverURL:"https://cdn.intechopen.com/books/images_new/3273.jpg",editedByType:"Edited by",editors:[{id:"60359",title:"Dr.",name:"Letícia",surname:"Rangel",slug:"leticia-rangel",fullName:"Letícia Rangel"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"1311",title:"Advances in Cancer Therapy",subtitle:null,isOpenForSubmission:!1,hash:"24db071212f134f4a7dc3dc0cc786fec",slug:"advances-in-cancer-therapy",bookSignature:"Hala Gali-Muhtasib",coverURL:"https://cdn.intechopen.com/books/images_new/1311.jpg",editedByType:"Edited by",editors:[{id:"57145",title:"Prof.",name:"Hala",surname:"Gali-Muhtasib",slug:"hala-gali-muhtasib",fullName:"Hala Gali-Muhtasib"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"3002",title:"Oncogenomics and Cancer Proteomics",subtitle:"Novel Approaches in Biomarkers Discovery and Therapeutic Targets in Cancer",isOpenForSubmission:!1,hash:"bc8990331803d9e6084b367163dcf218",slug:"oncogenomics-and-cancer-proteomics-novel-approaches-in-biomarkers-discovery-and-therapeutic-targets-in-cancer",bookSignature:"César López-Camarillo and Elena Aréchaga-Ocampo",coverURL:"https://cdn.intechopen.com/books/images_new/3002.jpg",editedByType:"Edited by",editors:[{id:"40928",title:"Dr.",name:"Cesar",surname:"Lopez-Camarillo",slug:"cesar-lopez-camarillo",fullName:"Cesar Lopez-Camarillo"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"1001",title:"Tumor Microenvironment and Myelomonocytic Cells",subtitle:null,isOpenForSubmission:!1,hash:"a2392066cd104cd48f3b296bf72b97a6",slug:"tumor-microenvironment-and-myelomonocytic-cells",bookSignature:"Subhra K. 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The contents of the book will be written by multiple authors and edited by experts in the field.",isbn:null,printIsbn:null,pdfIsbn:null,doi:null,price:0,priceEur:0,priceUsd:0,slug:null,numberOfPages:0,isOpenForSubmission:!1,isSalesforceBook:!1,isNomenclature:!1,hash:"824d83663c080630d0a9a830b4292f1c",bookSignature:"",publishedDate:null,coverURL:"https://cdn.intechopen.com/books/images_new/8615.jpg",keywords:null,numberOfDownloads:null,numberOfWosCitations:0,numberOfCrossrefCitations:0,numberOfDimensionsCitations:null,numberOfTotalCitations:null,isAvailableForWebshopOrdering:!0,dateEndFirstStepPublish:"August 8th 2018",dateEndSecondStepPublish:"August 29th 2018",dateEndThirdStepPublish:"October 28th 2018",dateEndFourthStepPublish:"January 16th 2019",dateEndFifthStepPublish:"March 17th 2019",dateConfirmationOfParticipation:null,remainingDaysToSecondStep:"4 years",secondStepPassed:!0,areRegistrationsClosed:!0,currentStepOfPublishingProcess:1,editedByType:null,kuFlag:!1,biosketch:null,coeditorOneBiosketch:null,coeditorTwoBiosketch:null,coeditorThreeBiosketch:null,coeditorFourBiosketch:null,coeditorFiveBiosketch:null,editors:null,coeditorOne:null,coeditorTwo:null,coeditorThree:null,coeditorFour:null,coeditorFive:null,topics:[{id:"16",title:"Medicine",slug:"medicine"}],chapters:null,productType:{id:"1",title:"Edited Volume",chapterContentType:"chapter",authoredCaption:"Edited by"},personalPublishingAssistant:null},relatedBooks:[{type:"book",id:"6550",title:"Cohort Studies in Health Sciences",subtitle:null,isOpenForSubmission:!1,hash:"01df5aba4fff1a84b37a2fdafa809660",slug:"cohort-studies-in-health-sciences",bookSignature:"R. 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They have been focused on finding pre-seismic precursors for prediction and forecasting tasks [2-6]. In this regard, different electromagnetic phenomena (EP) encompassing a large frequency range, being the ultra-low-frequency (ULF) range one of the most promising, have been associated with EQs because they typically occur during, but sometimes prior to seismic activity [7-14] Although many detection methods have been proposed, the relevance and severity of EQs damages demand still more efficient and reliable diagnosis methods.
Techniques and methods such as polarization or spectral density ratio analysis [15-16], transfer function analysis [17], fractal analysis [18-22], singular value decomposition [23], principal component analysis [16, 21], and the discrete wavelet transform (DWT) [2, 24], among others have been proposed to analyse the ULF geomagnetic signals associated to EQs. Yet, despite showing promising results, the inherent characteristics of the ULF geomagnetic signals such as high noise levels, weak amplitude, and interferences from other sources due to the distance between the epicenter and sensor, among others may compromise the performance and reliability of the analysis. From this point of view, the development and application of new detection methods to make a more efficient and reliable diagnosis in terms of processing and performance are still interesting research fields.
In this chapter, the application of the empirical wavelet transform (EWT) to ULF signals for detecting seismic precursor anomalies is presented. Besides, a comparison with the DWT is carried out in order to show the EWT advantages. Moreover, a fuzzy logic (FL) system for automatic diagnosis using the variance of the EWT results is proposed. For this, three ULF signals associated to seismic activities and random calm periods are analysed. The obtained results show the usefulness and effectiveness of the proposed methodology, making it a suitable and reliable tool to detect ULF anomalies.
In order to investigate the relationships between ULF geomagnetic signals and pre-seismic anomalies, ULF geomagnetic data from Juriquilla seismic station, located in Queretaro, Mexico, with geographic coordinates: longitude -100.45° N and latitude 20.70° E, are used. The ULF geomagnetic signals are monitored by means of a fluxgate magnetometer. It allows monitoring three mutually orthogonal components of the magnetic field, two horizontal (Mx: North-South and My: East-West) components and a vertical component (Mz). The three geomagnetic components are measured using a sampling frequency of 1 Hz to obtain 65,000 samples during a time window of 18 hrs, which comprise 9 hours before the main shock and 9 hrs after it. In this research, three recent seismic events with magnitude greater than 6.0 are analysed. Further, for comparison purposes, random analyses during periods of seismic calm are used. Table 1 summarize the characteristics of the studied EQs.
To discriminate the geomagnetic activity of the magnetosphere because of the solar activity and cultural noise, the analysed EQs data are compared with the geomagnetic activity expressed by Dst index (http://wdc.kugi.kyoto-u.ac.jp/dstdir/), where those indices apparently had no correlation with EQs variation.
\n\t\t\t\t | \n\t\t\t\n\t\t\t\t | \n\t\t\t\n\t\t\t\t | \n\t\t\t\n\t\t\t\t | \n\t\t\t\n\t\t\t\t | \n\t\t\t\n\t\t\t\t | \n\t\t\t\n\t\t\t\t | \n\t\t\t\n\t\t\t\t | \n\t\t\t\n\t\t\t\t | \n\t\t\t\n\t\t\t\t | \n\t\t\t\n\t\t\t\t | \n\t\t\t\n\t\t\t\t | \n\t\t\t\n\t\t\t\t | \n\t\t
1 | \n\t\t\t2009 | \n\t\t\t8 | \n\t\t\t3 | \n\t\t\t13 | \n\t\t\t0 | \n\t\t\t-112.24 | \n\t\t\t28.48 | \n\t\t\t6.9 | \n\t\t\t10 | \n\t\t\t1473 | \n\t\t\t2292 | \n\t\t\t0.64 | \n\t\t
2 | \n\t\t\t2009 | \n\t\t\t9 | \n\t\t\t24 | \n\t\t\t2 | \n\t\t\t16 | \n\t\t\t-107.43 | \n\t\t\t17.72 | \n\t\t\t6.2 | \n\t\t\t21 | \n\t\t\t8052 | \n\t\t\t1109 | \n\t\t\t0.73 | \n\t\t
3 | \n\t\t\t2010 | \n\t\t\t6 | \n\t\t\t30 | \n\t\t\t2 | \n\t\t\t22 | \n\t\t\t-98.03 | \n\t\t\t16.22 | \n\t\t\t6.0 | \n\t\t\t8 | \n\t\t\t563 | \n\t\t\t684 | \n\t\t\t0.82 | \n\t\t
Characteristics of the Earthquakes occurred in Mexico during 2009–2010. Their magnitudes are presented in bold (Catalogue of National Seismological Service, Mexico)
Note: The Year / month / day / hour / minute are the exact time of the EQ (Local Time); Latitude and Longitude are the geographic coordinates of the epicenter, Magnitude and Depth are the EQ measures, Distance is the distance between the epicenter and Juriquilla station, and p is the radius of the EQ preparation.
This section presents the theoretical background of the Discrete Wavelet transform and the Empirical Wavelet Transform used for the analysis of ULF signals.
Discrete Wavelet Transform (DWT) is a useful method for analysis of non-stationary, no linear and transient signals because it decomposes the time series signal into multiple time-frequency levels retaining the characteristics of the analysed signal [2]. DWT is defined by Eq. (1), where
The DWT is calculated using a set of low- and high-pass filters bank called approximations (ACL) and details (DCL) into desired levels
DWT basis construction.
According to the Mallat algorithm, the frequency band for the approximations
Different types of wavelet mother function have been proposed to analyse ULF signals in order to find anomalies related with EQs such as Daubechies, Haar, Morlet, Symlets, Coiflets, and Meyer (Figure 2). However, it has been demonstrated that the most effective to analyse ULF signals is the Daubechies mother function [2, 24, 26]. For this reason, Daubechies as mother wavelet is used in this work.
Wavelets used in ULF signals.
EWT is a new adaptive wavelet transform capable of decomposing a time series signal
EWT basis construction.
Following the idea used in deriving the Meyer’s wavelet, [27] defines the empirical scaling function to estimate the low-pass wavelet filter coefficients according to following Equation:
\n\t\t\t\tAnd an empirical wavelet function to build the
where
After having built the wavelet filters, the signal
where the details
This section presents the proposed methodology. It consists of the ULF geomagnetic signals analysis through the EWT, then a statistical parameter based on the variance is applied and, finally, an automatic diagnosis by means of a FL system is computed as shown in Figure. 4.
Proposed methodology.
Generally, the pre-seismic anomalies are too much weak to be detected by the Fourier transform (Chavez et al., 2010); hence, the frequency bands are selected manually using the EWT. Several experimental using both algorithms are carried out to estimate the best frequency band of the ULF geomagnetic signal to detect anomalies associated to the EQs. After the experimental runs, it is found that for the EWT algorithm the frequency band from 0.0470 to 0.0781 Hz and for the DWT algorithm the frequency band or third decomposition from 0.0625 to 0.125 Hz with a Daubechies wavelet of order 5 generate the best results, enhancing correlation with associated seismic anomalies events. Figure. 5 presents the obtained results for the EWT and the DWT, where both the seismic calm signal (left-side plots) and the seismic activity signal (right-side plots), which corresponds to event 1 (Table 1), can be observed. Figure.5(a) shows that in both analysis, the seismic calm period do not present significant spikes over time, indicating the absence of seismic activity. On the other hand, observing the results shown in Figure. 5(b), both time-frequency analysis can detect the occurrence of peaks prior to seismic (Pre-seismic event zone) and another peaks after the main shock (Post-seismic event zone). These magnetic perturbations occur about 8hrs before the main shock and about 2 hrs after it. Open circles remark perturbations in the signal.. But, it is noticeable that, using the EWT method, it is better noticeable of the pre-seismic and post-seismic anomalies.
Comparison between the EWT time-frequency analysis and DWT time-frequency analysis; for (a) seismic calm, and (b) with seismic activity.
In order to evaluate the significance of these results, a complementary statistical analysis based on the variance of the EWT and DWT results is computed to measure the fluctuations between seismic activity and seismic calm period as follows:
\n\t\t\t\twhere
Variance (V) of the seismic activity and seismic calm period using: (a) EWT and (b) DWT.
After showing in the previous section that EWT improves the correlation between the seismic event and the ULF electromagnetic signal, the proposed EWT time-frequency analysis is applied to seismic calm and three seismic events with different geographical location. Figure. 7 shows the EWT time-frequency analysis for seismic calm period and the 3 seismic events. The three components of the magnetic field, Mx, My, and Mz, are analysed as shown in Figure. 7. The main shock position is indicated by an arrow and two circles. It shows the pre-seismic and post-seismic anomalies associated with the EQs. The EWT results for seismic calm period do not present significant spikes over time, indicating the absence of seismic activity, as shown in Figure. 7(a-c); unlike the signals with seismic activity where several spikes appear before and after the main shock. All the analysed signals comprise 9 hrs before and 9 hrs after each seismic event, considering the time zero as the specific time of the occurrence of the EQ.
EWT analysis of the three geomagnetic components: Mx, My and Mz, for a seismic calm (a-c), and with seismic activity: (d) to (f)
Similar to previous section, to evaluate the significance of the results, a complementary statistical analysis based on the variance of the EWT results is computed to measure the fluctuations between seismic activity and seismic calm period. Figure. 8 shows the variance V results obtained for three analysed seismic events as well as for their three components (Mx, My, and Mz). The results correspond to running data windows each 1000 samples. According to the obtained results in Figure.8(a-c), there are important variations of V for the three components that could be associated with occurrence of the EQs. As observed, V increases before, during and, after the seismic event on the three components: Mx (a), My (b), and Mz (c). Observing Figure. 8, the Mx geomagnetic component presents an important variance in three different ranges: from 8 to 5 hrs before seismic event, between 2hr before and 2hr after the main shock, and from 3 to 7 hrs after the main EQs (post-seismic zone). The My component shows variance in different ranges, from 8 to 6 hrs before seismic event, between 2 hrs before and 2 hrs after main shock, and from 3 to 8 hrs after the main EQs. Finally, the Mz geomagnetic component also presents variance in three different ranges: from 8 to 6 hrs before seismic event, 2 hrs before and 2 hrs after main shock, and from 4 to 8 hrs after seismic event. In summary, these results show that the EWT is adequate to find electro-magnetic seismic precursors related to the variance magnitude.
Variance of the EWT for the three geomagnetic components: (a) Mx, (b) My, and (c) Mz.
Once the variance of the EWT signals is computed, a FL-based system is used for automatically diagnosing the severity of the ULF geomagnetic variations associated to seismic events. A FL system represents a group of rules for reasoning under uncertainty in an imprecise or fuzzy manner. It is usually used when a mathematical model of a process does not exist or does exist but is too difficult to encode and too complex to be evaluated fast enough for real time operation. Besides, it can use several sources of information in order to take a decision according to a particular objective.
The designed and implemented FL system to perform the diagnosis process is a Mamdani-type fuzzy inference system with two inputs, one output, and 16 rules. The system uses Max–Min composition, and the centroid of area method for defuzzification. The inputs are the variance of EWT results for the signals Mx and My, the Mz signal is not considered since it presents a low difference between seismic activity and calm period. These inputs are partitioned into four trapezoidal membership function sets, as shown in Figures. 9(a) and 9(b). They are labelled as NV (normal variance), LV (low variance), MV (medium variance), and HV (high variance). The output is also divided into four trapezoidal membership functions as shown in Figure. 9(c), their labels are NF (normal fluctuations), LF (low fluctuations), MF (medium fluctuations), and HF (high fluctuations). The crisp output of the Mamdani FL system can assume values between 0.5 and 4.5, where normal variations = 1, low variations = 2, medium variations = 3, and high variations = 4. The parameters of membership functions are determined according to the interpretation of the variance results by the authors. The set of rules that classifies the inputs variance is show in Table 2; there, one rule can be read as follows if (variance Mx is NV and variance My is NV) (light gray) then the geomagnetic fluctuations magnitude is NF (dark gray), and so on.
\n\t\t\t\t | \n\t\t\t\n\t\t\t\t | \n\t\t||||
NV | \n\t\t\tLV | \n\t\t\tMV | \n\t\t\tHV | \n\t\t||
\n\t\t\t\t | \n\t\t\tNV | \n\t\t\tNF | \n\t\t\tNF | \n\t\t\tLF | \n\t\t\tMF | \n\t\t
LV | \n\t\t\tLF | \n\t\t\tLF | \n\t\t\tMF | \n\t\t\tHF | \n\t\t|
MV | \n\t\t\tLF | \n\t\t\tMF | \n\t\t\tHF | \n\t\t\tHF | \n\t\t|
HV | \n\t\t\tMF | \n\t\t\tHF | \n\t\t\tHF | \n\t\t\tHF | \n\t\t
Rules table for the proposed FL
Membership functions: (a) Input Mx variance, (b) Input My variance, and (c) Output diagnosis.
The FL output for a calm period signal is shown in Figure. 10(a), where most of the results are Normal and only a few data indicate Low ULF geomagnetic variations. On the other hand, the outputs for the three geomagnetic signals associated to EQs indicate many Medium and High variations as shown in Figure. 10(b-d); therefore, if these results are obtained in future data they could be associated to seismic activities.
FL-based diagnosis for the analysed cases: (a) calm period and (b-d) seismic activities associated to ULF geomagnetic variations.
In this chapter, a new time-frequency study based on the EWT for analysing ULF geomagnetic signals, at Juriquilla station in Queretaro Mexico, is presented. In order to prove the effectiveness of the EWT algorithm; three real data of EQs are analysed. The results demonstrate that the proposal has a greater detectability than DWT for detecting anomalies before, during, and after the main shock since EWT allows selecting narrow time-frequency sub-bands, unlike the DWT where the calculated time-frequency sub-bands depend on sampling frequency of the time signal. Further, the variance, a statistical complementary analysis, shows that a seismic event can be detected from 8 to 5 hrs before it occurs. It also indicates that relevant information can be obtained from 563 to 1473 km (epicenter distance) to the testing station. Therefore, the proposed time-frequency analysis can extract the abnormal signals in the ULF range of the EP related to different stages of the EQ preparation. Finally, the proposed FL system can automatically classify the magnitude variations of the EP into Normal, Low, Medium, and High variations using both Mx and My signals, where is found that Medium and High variations could be associated to seismic activities.
In a future work, the overall methodology will be implemented into a digital signal processor (DSP) for online and continuous monitoring of ULF geomagnetic variations and possibly used for obtain a implicit correlation between the seismic magnitude and the ULF geomagnetic signals.
From the viewpoint of mathematical systems, the time series observed in physics are usually regarded as coming from the Lagrangian systems, also called the conventional systems. The systems can be analyzed by the conventional Euclidean geometry [1]. However, the systems in practice are usually nonlinear and complex. Thus, a lot of interesting time series in nature are complex due to nonlinear phenomena derived from nonlinear dynamical systems [2]. The nonlinear dynamical systems have been described by Hamiltonian systems and dealt with by using symplectic geometry [3]. Symplectic geometry is an even dimensional geometry living on even dimensional spaces. Different from the conventional Euclidean geometry that measures 1-dimensional lengths and angles, the symplectic geometry studies the metric properties (such as area) and can preserve the system structure in the phase space [4]. Apart from applications on the classical dynamical systems to solve the equation problems, symplectic geometry has been also used on the studies of nonlinear time series [5, 6, 7, 8].
According to Takens’ embedding theorem, a time series can be reconstructed into an attractor in phase space [9]. The reconstructed attractor is a geometrical object that can reflect the underlying dynamical system. In order to better understand the nature of the underlying system, the attractor and its properties are characterized in the phase space by various mathematical methods, such as dimension, fractal geometry, Lyapunov exponent, entropy and symplectic geometry [1, 5, 10, 11]. For dimension, fractal geometry, Lyapunov exponent, entropy, there are a more extensive discussion with mathematical details in some research literatures [12, 13, 14, 15]. Here, we only introduce how to apply symplectic geometry theory to extract the information from the reconstructed attractor and its application on physics, engineering and biomedical engineering.
The reconstruction from a time series of observation is the first and most crucial step in nonlinear time series analysis. It is also the basis of applications of symplectic geometry on time series analysis. Takens’ embedding theorem allows us to reconstruct an equivalent attractor of the underlying dynamical system by embedding one time series. The theorem proves that the reconstructed attractor has the same dynamical characteristics as the attractor of the original system if the embedding dimension
where the number of dots in the attractor is
----------------------------------
function matrixSignal = signalMatrix(x, N)
% ------Construct data matrix------
%
% Synopsis:
% matrixSignal = signalMatrix(x, N)
%
% Description:
% It constructs a data matrix from a time series as a column vector, i.e., a
% reconstruction attractor.
%
% Input:
% x a time series with the length n.
% N [1x1] Output dimension; N > 1 (default N = dim);
%
% Ouputs:
% matrixSignal [N x M] a data matrix (M = n-N + 1).
%
if nargin <2, N = 2; end
n = length(x);
M = n-N + 1;
matrixSignal = zeros(N,M);
for i = 1:N
matrixSignal(i,:) = x(i:M + i-1);
end
-------------------------------------
In the symplectic spaces, Hamiltonian system is the analysis fundamental for the real physical processes [4, 5]. A real system should be first described by a suitable Hamiltonian system, i.e. an even dimensional matrix. For a time series, its Hamiltonian matrix
Here,
Here,
Symplectic geometry focuses on the study of area measure in symplectic space
Geometry space | Symplectic space | Euclidean space |
---|---|---|
Space dimension | 2 | |
Unit matrix | unit symplect matrix: | unit matrix: |
Determinant of unit matrix | | | | |
Product calculation | symplectic inner product < | Inner product ( |
Calculation measure | area | length |
Orthogonality | ||
Space basis | Adjoint symplectic orthonormal basis | Orthogonal basis |
Orthogonal matrix | Symplectic matrix | Orthogonal matrix |
Analysis matrix | Hamiltonian matrix | Symmetry matrix |
Matrix transformation | Hamiltonian transformation | Symmetry transformation |
Eigenvalues of the matrix | The eigenvalues of | The eigenvalues |
Eigenvectors of the matrix | The eigenvectors of | The eigenvectors of |
The comparison between symplectic geometry and Euclidean geometry.
In Euclidean space, the inner product is denoted as the measure of the length. The unit matrix is
The properties of the matrix
The normal symplectic inner product is also denoted briefly as the symplectic inner product in a real vector space
The symplectic inner product is a bilinear antisymmetric nonsingular cross product. In symplectic space, the length of any vectors is equal to 0. But there exists the concept of symplectic orthogonal cross-course.
then
where
The orthogonal of the Euclidean space is different from the symplectic orthogonal. If vectors
where
If a vector set {
where
where
Thus, the symplectic inner product operation is transformed to the matrix operation of ordinary vectors or matrices by applying a normal adjoint symplectic orthonormal basis.
then
Let
According to the above definition of symplectic matrix, there are:
Thus, the product of symplectic matrixes is also a symplectic matrix.
where
Then the matrix
Let
where
According to Definition 2.6, let the matrix
Therefore,
The eigenvalues of a Hamiltonian matrix have the specific characteristics of the Hamiltonian matrix. However, the eigenvalues may be complex or repeated eigenvalues. In order to obtain the real eigenvalues of a Hamiltonian matrix
1. Let a 2
2. Build a 2
Here
3. Use the symplectic
4. The eigenvalues of the Hamiltonian matrix
In symplectic space, the symplectic
Let a Householder matrix
where, ‘*’ means the conjugate transposition. Then, there is
Therefore, the Householder matrix
In symplectic space, the reconstructed attractor can keep its properties unchanged [5, 6]. Its symplectic geometry spectrums can be given by the symplectic geometry theory above. On the basis of Section 2.1 and 2.2, one can build a Hamiltonian matrix
Let
If the vector
then, there is:
where
Then, the elementary reflective matrix
So, there is
Continue to deal with
Then,
where
Then, the elementary reflective matrix
Thus, we can get
Repeat the same steps until
Thus, a symplectic Householder matrix
where
-------------------------------------
function [P, R] = householder (A)
% ------Solve Householder Transform Matrix------
%
% Synopsis:
% [P, R] = householder (A)
%
% Description:
% It solves a Householder matrix from a data matrix, i.e., a
% reconstruction attractor.
%
% Input:
% A [mRow x mCol] a data matrix.
%
% Ouputs:
% P [mRow x mRow] a Householder matrix
% R [mRow x mCol] an upper triangle matrix
[mRow, mCol] = size(A);
if mRow>mCol
A = A’;
[mRow, mCol] = size(A);
end
I_matrix = eye(mRow);
m = min([mRow, mCol]);
p = I_matrix;
for i = 1:m.
S = A(:,i);
if i > 1.
S(1:i-1) = 0;
end
alpha = sqrt(S’*S);
delta1 = S-alpha*I_matrix(:,i);
delta = sqrt(delta1\'*delta1);
if delta==0
delta = eps;
end
omega = delta1/delta;
p = I_matrix-2*omega*omega\';
A = p*A;
P = p*P;
end
R = A;
return
-------------------------------------
For the attractor matrix
where
To estimate the embedding dimension is usually the first step of nonlinear analysis [5]. For a time series, it is important to resolve a suitable embedding dimension of the observed system. Due to the measure-preserving charactistic of symplectic geometry, symplectic geometry spectrums can be used to estimate the embedding dimension of the system from a time series. With the increase of the dimension
Symplectic entropy(SymEn) is a kind of entropy measure for a dynamic system in symplectic space [16]. Based on the symplectic geometry spectrums, the SymEn measures the energy distribution in symplectic space of a dynamic system from a time series. The distribution of the energy of the system is described by the eigenvalues
where
Then,
The matlab program is as follows:
----------------------------------
function SymEn = SymplecticEntropy(A)
[Q, R] = householder(A);
delta = diag(R);
sum_delta = sum(delta);
p = delta./sum_delta;
SymEn = −sum(p.*log(p));
Return
-------------------------------------
The SymEn value represents the uncertainty of the entropy about the underlying probability distribution of a dynamic system in symplectic space, called Symplectic Entropy.
Symplectic principal component analysis (SPCA) is a kind of principal component analysis (PCA) to map the dynamic system from a time series into the symplectic space [17]. Due to the preserving-measure nature of symplectic geometry, symplectic principal components elucidate the dominant features of a time series for an underlying system. The principal components corresponding to larger eigenvalues capture the key relationship between the variables in symplectic space. The components corresponding to smaller eigenvalues are regarded to relate primarily to the less important components or noise in the time series. The analysis of eigenvalues are also called as the symplectic geometry spectrums analysis (SGSA) [6, 18, 19]. The corresponding components are also regarded as symplectic geometry mode decomposition (SGMD) [7, 8, 20, 21]. According to the symplectic geometry spectrums above, if the number of the chosen symplectic principal components is
The corresponding
Then, the reestimated attractor matrix is equal to the sum of
The reestimated time series
Symplectic geometry theory has been applied to deal with a time series in fields of physics, engineering, biomedical engineering [6, 7, 8, 11, 16, 17, 18, 19, 20, 21, 22, 23, 24], since Lei et al.(2002) first proposed a symplectic geometry method to estimate the appropriate embedding dimension from a time series [5]. Here, we will introduce four research cases in terms of the above theorem and properties of symplectic geometry for the time series analysis.
Lorenz chaotic system was accidentally discovered by Edward Norton Lorenz [25], an American meteorologist, in 1963 when he was studying weather forecast, and was known as the first chaotic attractor. Since then, people began to study chaos, a random-like phenomenon. Lorenz chaotic time series
where
The attractor reconstructed from Lorenz chaotic time series
-------------------------------------
% Compute a Lorenz chaotic time series
% Example:
% state = [5 5 5];
% Ts = 0.005;
% N = 10000;
% y = calculate_lorenz(state, Ts, N);
% x = y(:,1);
function y = calculate_lorenz(state, Ts, N).
if nargin <1
state = [5 5 5];
Ts = 0.005;
N = 10000;
end
if nargin == 1
Ts = 0.005;
N = 10000;
end
if nargin == 2
N = 10000;
end
% set time span with specific times for the solution
T = 0:Ts:N*Ts;
% set a scalar relative error tolerance \'RelTol\' (1e-3 by default).
% and a vector of absolute error tolerances \'AbsTol\' (all components 1e-6% by default).
options = odeset(\'RelTol\',1e-4,\'AbsTol\',[1e-4 1e-4 1e-5]);
% solve Lorenz chaotic system
[t,y] = ode45(\'lorenzeq1\',T,state,options);
return
function ydot = lorenzeq(t,y)
% Lorenz equation
b = 8/3;
r = 28;
delta = 10;
A = [−delta delta 0;r − 1 -y(1);y(2) 0 -b];
ydot = A*y;
return
--------------------------------------
% Calculate the embedding dimension.
state = [5 5 5];
Ts = 0.005;
N = 10000;
y = calculate_lorenz(state, Ts, N);
x = y(:,1);
figure.
for N = 3:5:23
X = signalMatrix(x,N);
A = X*X’;
[Q, R] = householder(A);
delta = diag(R);
sum_delta = sum(delta);
d = log10(delta./sum_delta);
n = length(d);
plot(1:n, d, \'b*-\')
hold on
end
ylabel(\'log10(\\delta_{\\iti}/tr(\\delta_{\\iti}))\')
xlabel(\'{\\itd} = 3:5:23\')
axis([0 25–15 0])
-----------------------------------
Figure 1a shows the symplectic geometry spectrums
The embedding dimension estimation of Lorenz chaos series with no noise based on: (a) the symplectic geometry method; (b) the SVD method.
In the practical engineering research, a lot of time series data due to their complexity are considered to be nonlinear, such as the surface EMG signal in biomedical engineering. As a kind of non-invasive measure for the contracting skeletal muscles, the surface EMG signal reflects some information about the muscle, limb movements and loading of the bones and joints. It has been widely applied to assess biomechanical and motor control deficits and other functional disorders, as well as to diagnose neuromuscular problems. However, due to noise interference, the study of surface EMG signal is still a great challenge in biomedical engineering. Many researches indicate that the surface EMG signal is complex and nonlinear. The embedding dimension estimation of the surface EMG signal is usually critical to analyze its nonlinear features. As an example, we use the above symplectic geometry method to estimate the embedding dimension of the surface EMG signal during forearm supination. The length of the surface EMG signal is 1000 points. The data sampling frequency is 1 kHz. Figure 2a shows the raw surface EMG signal. Figure 2b gives the symplectic geometry spectrums
The embedding dimension analysis of the surface EMG signal based on the symplectic geometry spectrums: (a) Typical surface EMG signal during forearm supination; (b) The symplectic geometry spectrums of the surface EMG data in (a), where abscissa is the analysis dimension
In the rotating machinery systems, it is extremely important for rolling bearings to detect faults from vibration signals. The Case Western Reserve University (CWRU) Bearing Data Center provides a website database for the vibration signals of bearings (http://csegroups.case.edu/bearingdatacenter /pages/welcome-case-western-reserve-university-bearing-data-center-website). From the website, the acceleration vibration data sets for 6205-2RS JEM of SKF deep-groove ball bearings are obtained to detect their fault categories. The corresponding sampling frequency is 12 kHz, the shaft speed 1730 r/min. The analyzed data sets include No.100 for normal condition(NC), No.212 for inner race fault (IRF), No.225 for rolling element fault (REF), and No.261 for outer race fault (ORF) at 12 o’clock position. The data of each set consist of the vibration signals at the housing of the drive end (DE) bearing and that of the fan end (FE) bearing, which the faults are at the drive end. The corresponding fault depth and diameter are 0.21 inches and 0.53 mm, respectively.
Symplectic geometry preserves the nature of a dynamic system under symplectic similar transformations. As an entropy measure in symplectic geometry, the SymEn value of a time series measures the lack of information in a dynamic system to reflect its properties. For the complexity of a rolling bearing, the SymEn estimate is applied to test its nonlinear characteristics from the vibration signals. Figure 2 shows the SymEn values of the vibration signals at the drive end and their surrogate data sets based on the null hypothesis of a Gaussian linear stochastic process. Here, the length of each data is 6000 points. The embedding dimension
Meanwhile, the 39 sets of surrogate data are generated by the iterated amplitude adjusted Fourier transform (IAAFT) algorithm in the 95% confidence level [26]. From Figure 3, we can see that there are the significant differences between these SymEn values of the vibration signals of a rolling bearing and their surrogate data sets. The results indicate that the vibration data could contain nonlinear characteristics. The original vibration signals are not from a Gaussian linear stochastic process in the 95% confidence level but from a nonlinear dynamical system. It conforms that the rolling bearing system is a complex nonlinear dynamical system.
The nonlinear analysis of vibration signals based on the SymEn method: (a) for the normal condition (NC); (b) for the outer race fault (ORF); (c) for the rolling element fault (REF); (d) for the inner race fault (IRF). The abscissa is the SymEn values of vibration signals and their surrogate data.
Due to the complexity of rolling bearings, it is often thought that the high dimensional features can better identify the faults of rolling bearings [27, 28, 29]. However, the SymEn method can availably extract the low-dimensional features to identify the faults of rolling bearings from vibration signals quite precisely. Figure 4 shows the four working states of rolling bearings, i.e., NC, ORF, REF, and IRF, based on 2-dimensional features. The abscissa is the SymEn estimates of vibration signals at the drive end. The ordinate is those estimates of vibration signals at the fan end. We can see that the four states are obviously different. There are 100% accuracies by RBF classifier for the four states of the rolling bearings. Figure 5 plots the histogram of error values between output classes and target classes for the SymEn estimates as features of vibration signals.
The states analysis of rolling for bearings with the SymEn estimates.
The analysis of error values identification accuracies of four states.
In the practical engineering measurement, the vibration data of rolling bearings have often become contaminated with noise. The noise reduction is also beneficial to analyze the measured data. The SPCA method preserves the intrinsic nonlinear nature of the raw data. The symplectic principal components can better retrieve dominant patterns from the noisy data. For the vibration signals of rolling bearings, the first symplectic principal component is used two times continuously to reduce the noise in the data.
The specific analysis procedures are as follows:
Build a Hamiltonian matrix from the measured data in terms of Eq. (1), Definition 2.1, 2.2 and Theorem 2.3;
Use the Eq. (44)–(59) to compute a symplectic Householder transform matrix
Construct the first symplectic principal component eigenvector matrix
Calculate the first symplectic principal component coefficients
Get the first denoised data
Let the first denoised data
Figure 6 shows the effect of denoising for the vibration signals of rolling element fault (REF), No.225 data in the CWRU database [11]. For the rolling element fault at the drive end, the fault state can be seen clearly by the second reducing noise (see Figure 6a). For the vibration signals at the fan end without faults, the periodical characteristics in the normal state can be shown after the two reducing noise (see Figure 6b).
The two times denoising analysis for the vibration signals of rolling element fault (REF) in No.225 data from the CWRU database. (a) The abscissa is the number of data points; (b) the ordinate is the amplitude (v) of the data.
Moreover, the noise reduction method based on the symplectic geometry has been used to denoise several time series data of Lorenz chaotic system, duffing chaotic system, Chua’s chaotic system with noise, as well as the sunspot number [30]. The details can be found in literatures [17, 30].
Besides, the symplectic geometry method also further integrate other approaches to better investigate the fault extraction and identification for rotating systems, such as symplectic geometry mode decomposition [19] with power spectral entropy [7] as well as Lagrange multiplier [20], symplectic transformation based variational Bayesian learning [21].
This chapter introduces the symplectic geometry theory in the research field of the time series analysis in view of the complexity of a time series. Corresponding to Euclidean geometry, the basic concepts and basic elements of mathematics of the symplectic geometry are given, such as the symplectic space, symplectic transformation, Hamiltonian matrix, symplectic entropy (SymEn), symplectic principal component analysis (SPCA), and so on. Based on the symplectic geometry theory, the symplectic geometry spectrum analysis (SGSA), the symplectic entropy (SymEn) method and the symplectic geometry mode decomposition (SGMD) method are demonstrated to investigate the principal characteristics of a time series in the symplectic space. Meanwhile, the corresponding matlab programs are given. At last, in order to facilitate readers to learn, use and develop the symplectic geometry method, some applications of symplectic geometry on time series analysis are presented, such as the embedding dimension estimation, nonlinear testing, fault diagnosis, as well as noise reduction.
The embedding dimension estimation is often the first step in nonlinear time series analysis. Case 1 and 2 show the embedding dimension estimation of Lorenz chaotic time series and the surface EMG signal based on symplectic geometry spectrum. Moreover, the symplectic entropy method is applied to detect the nonlinearity of vibration signals on rolling bearings and identify the faults of vibration signals on rolling bearings (see Case 3). Considering the noise pollution in the practical engineering measurement, to dispose of the noise problem is very necessary for the measured time series analysis. Case 4 uses the SPCA method based on symplectic geometry to investigate the denoise of the vibration signals for rolling element fault (REF) from the CWRU database.
Symplectic geometry provides a new research idea for data analysis in practice. Although the symplectic geometry theory has been developed and applied on the nonlinear time series analysis, the related research based on symplectic geometry still needs to be further developed. Many future challenges in the research of symplectic geometry theory and various applications on a number of diverse aspects need to be developed furtherly. This chapter is only to provide a snapshot of some current trends and future challenges in the research of symplectic geometry theory on the time series analysis.
This work was supported by Shanghai “Science and technology innovation action plan” bio-medicine science and technology support project (Grant No. 19441907400).
The authors declare no conflict of interest.
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\n'}]},successStories:{items:[]},authorsAndEditors:{filterParams:{},profiles:[{id:"396",title:"Dr.",name:"Vedran",middleName:null,surname:"Kordic",slug:"vedran-kordic",fullName:"Vedran Kordic",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/396/images/7281_n.png",biography:"After obtaining his Master's degree in Mechanical Engineering he continued his education at the Vienna University of Technology where he obtained his PhD degree in 2004. He worked as a researcher at the Automation and Control Institute, Faculty of Electrical Engineering, Vienna University of Technology until 2008. His studies in robotics lead him not only to a PhD degree but also inspired him to co-found and build the International Journal of Advanced Robotic Systems - world's first Open Access journal in the field of robotics.",institutionString:null,institution:{name:"TU Wien",country:{name:"Austria"}}},{id:"441",title:"Ph.D.",name:"Jaekyu",middleName:null,surname:"Park",slug:"jaekyu-park",fullName:"Jaekyu Park",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/441/images/1881_n.jpg",biography:null,institutionString:null,institution:{name:"LG Corporation (South Korea)",country:{name:"Korea, South"}}},{id:"465",title:"Dr",name:"Christian",middleName:null,surname:"Martens",slug:"christian-martens",fullName:"Christian Martens",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:null},{id:"479",title:"Dr.",name:"Valentina",middleName:null,surname:"Colla",slug:"valentina-colla",fullName:"Valentina Colla",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/479/images/358_n.jpg",biography:null,institutionString:null,institution:{name:"Sant'Anna School of Advanced Studies",country:{name:"Italy"}}},{id:"494",title:"PhD",name:"Loris",middleName:null,surname:"Nanni",slug:"loris-nanni",fullName:"Loris Nanni",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/494/images/system/494.jpg",biography:"Loris Nanni received his Master Degree cum laude on June-2002 from the University of Bologna, and the April 26th 2006 he received his Ph.D. in Computer Engineering at DEIS, University of Bologna. On September, 29th 2006 he has won a post PhD fellowship from the university of Bologna (from October 2006 to October 2008), at the competitive examination he was ranked first in the industrial engineering area. He extensively served as referee for several international journals. He is author/coauthor of more than 100 research papers. He has been involved in some projects supported by MURST and European Community. His research interests include pattern recognition, bioinformatics, and biometric systems (fingerprint classification and recognition, signature verification, face recognition).",institutionString:null,institution:null},{id:"496",title:"Dr.",name:"Carlos",middleName:null,surname:"Leon",slug:"carlos-leon",fullName:"Carlos Leon",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"University of Seville",country:{name:"Spain"}}},{id:"512",title:"Dr.",name:"Dayang",middleName:null,surname:"Jawawi",slug:"dayang-jawawi",fullName:"Dayang Jawawi",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"University of Technology Malaysia",country:{name:"Malaysia"}}},{id:"528",title:"Dr.",name:"Kresimir",middleName:null,surname:"Delac",slug:"kresimir-delac",fullName:"Kresimir Delac",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/528/images/system/528.jpg",biography:"K. Delac received his B.Sc.E.E. degree in 2003 and is currentlypursuing a Ph.D. degree at the University of Zagreb, Faculty of Electrical Engineering andComputing. His current research interests are digital image analysis, pattern recognition andbiometrics.",institutionString:null,institution:{name:"University of Zagreb",country:{name:"Croatia"}}},{id:"557",title:"Dr.",name:"Andon",middleName:"Venelinov",surname:"Topalov",slug:"andon-topalov",fullName:"Andon Topalov",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/557/images/1927_n.jpg",biography:"Dr. Andon V. Topalov received the MSc degree in Control Engineering from the Faculty of Information Systems, Technologies, and Automation at Moscow State University of Civil Engineering (MGGU) in 1979. He then received his PhD degree in Control Engineering from the Department of Automation and Remote Control at Moscow State Mining University (MGSU), Moscow, in 1984. From 1985 to 1986, he was a Research Fellow in the Research Institute for Electronic Equipment, ZZU AD, Plovdiv, Bulgaria. In 1986, he joined the Department of Control Systems, Technical University of Sofia at the Plovdiv campus, where he is presently a Full Professor. He has held long-term visiting Professor/Scholar positions at various institutions in South Korea, Turkey, Mexico, Greece, Belgium, UK, and Germany. And he has coauthored one book and authored or coauthored more than 80 research papers in conference proceedings and journals. His current research interests are in the fields of intelligent control and robotics.",institutionString:null,institution:{name:"Technical University of Sofia",country:{name:"Bulgaria"}}},{id:"585",title:"Prof.",name:"Munir",middleName:null,surname:"Merdan",slug:"munir-merdan",fullName:"Munir Merdan",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/585/images/system/585.jpg",biography:"Munir Merdan received the M.Sc. degree in mechanical engineering from the Technical University of Sarajevo, Bosnia and Herzegovina, in 2001, and the Ph.D. degree in electrical engineering from the Vienna University of Technology, Vienna, Austria, in 2009.Since 2005, he has been at the Automation and Control Institute, Vienna University of Technology, where he is currently a Senior Researcher. 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Aalborg University has Two Satellite Campuses, one in Copenhagen (Aalborg University Copenhagen) and the other in Esbjerg (Aalborg University Esbjerg).\n· He is a member of prestigious IEEE (Institute of Electrical and Electronics Engineers), and IAENG (International Association of Engineers) organizations. \n· He is the chief Editor of the Journal of Software Engineering.\n· He is the member of the Editorial Board of International Journal of Computer Science and Software Technology (IJCSST) and International Journal of Computer Engineering and Information Technology. \n· He is also the Editor of Communication in Computer and Information Science CCIS-20 by Springer.\n· Reviewer For Many Conferences\nHe is the lead person in making collaboration agreements between Aalborg University and many universities of Pakistan, for which the MOU’s (Memorandum of Understanding) have been signed.\nProfessor Akbar is working in Academia since 1990, he started his career as a Lab demonstrator/TA at the University of Sussex. After finishing his P. hD degree in 1992, he served in the Industry as a Scientific Officer and continued his academic career as a visiting scholar for a number of educational institutions. In 1996 he joined National University of Science & Technology Pakistan (NUST) as an Associate Professor; NUST is one of the top few universities in Pakistan. In 1999 he joined an International Company Lineo Inc, Canada as Manager Compiler Group, where he headed the group for developing Compiler Tool Chain and Porting of Operating Systems for the BLACKfin processor. The processor development was a joint venture by Intel and Analog Devices. In 2002 Lineo Inc., was taken over by another company, so he joined Aalborg University Denmark as an Assistant Professor.\nProfessor Akbar has truly a multi-disciplined career and he continued his legacy and making progress in many areas of his interests both in teaching and research. He has contributed in stochastic estimation of control area especially, in the Multiple Target Tracking and Interactive Multiple Model (IMM) research, Ball & Beam Control Problem, Robotics, Levitation Control. He has contributed in developing Algorithms for Fingerprint Matching, Computer Vision and Face Recognition. He has been supervising Pattern Recognition, Formal Languages and Distributed Processing projects for several years. He has reviewed many books on Management, Computer Science. Currently, he is an active and permanent reviewer for many international conferences and symposia and the program committee member for many international conferences.\nIn teaching he has taught the core computer science subjects like, Digital Design, Real Time Embedded System Programming, Operating Systems, Software Engineering, Data Structures, Databases, Compiler Construction. 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It is more common during the neonatal period than at any other age with the estimated incidence of 0.25 per 1000 live births. The absence of specific clinical presentation makes diagnosis of meningitis more difficult in neonates than in older children. Culture of cerebrospinal fluid is the traditional gold standard for diagnosis of bacterial meningitis, so all newborn infants with proven or suspected sepsis should undergo lumbar puncture. However, deciding when to perform lumbar puncture and interpretation of the results are challenging. Although the pathophysiology of neonatal meningitis is complex and not fully understood, researches on diagnostic and prognostic tools are ongoing. 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This chapter will examine the multiple dimensions influencing maternal decision-making in regards to the feeding practices of infants including 1) individual maternal characteristics, 2) organizational factors, 3) hospital/provider recommendations, and 4) systematic/policy factors. The chapter will also examine the impact of infant feeding practices on early infant and childhood health outcomes. Research has demonstrated the benefits of breastfeeding on infants and early childhood which includes but is not limited to protection against common illnesses and infections, improved IQ , and even increased school attendance. Moreover, the World Health Assembly global nutrition objectives focus on encouraging breastfeeding support across all sectors in addition to implementing tailored community-based approaches, limiting the excessive marketing of infant formula, and enforcing supportive breastfeeding legislation. 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Initial biochemical studies have been exclusively analytic: dissecting, purifying, and examining individual components of a biological system; in the apt words of Efraim Racker (1913 –1991), “Don’t waste clean thinking on dirty enzymes.” Today, however, biochemistry is becoming more agglomerative and comprehensive, setting out to integrate and describe entirely particular biological systems. The ‘big data’ metabolomics can define the complement of small molecules, e.g., in a soil or biofilm sample; proteomics can distinguish all the comprising proteins, e.g., serum; metagenomics can identify all the genes in a complex environment, e.g., the bovine rumen. 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Dr. Blumenberg’s research is focused on the epidermis, expression of keratin genes, transcription profiling, keratinocyte differentiation, inflammatory diseases and cancers, and most recently the effects of the microbiome on the skin. 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Her research interests include archaea metabolism, enzymes purification and characterization, gene regulation, carotenoids and bioplastics production, antioxidant\ncompounds, waste water treatments, and brines bioremediation.\nRosa María’s other roles include editorial board member for several journals related\nto biochemistry, reviewer for more than 60 journals (biochemistry, molecular biology, biotechnology, chemistry and microbiology) and president of several organizing committees in international meetings related to the N-cycle or respiratory processes.",institutionString:null,institution:{name:"University of Alicante",institutionURL:null,country:{name:"Spain"}}},editorTwo:null,editorThree:null},{id:"15",title:"Chemical Biology",coverUrl:"https://cdn.intechopen.com/series_topics/covers/15.jpg",isOpenForSubmission:!0,annualVolume:11411,editor:{id:"441442",title:"Dr.",name:"Şükrü",middleName:null,surname:"Beydemir",slug:"sukru-beydemir",fullName:"Şükrü Beydemir",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0033Y00003GsUoIQAV/Profile_Picture_1634557147521",biography:"Dr. Şükrü Beydemir obtained a BSc in Chemistry in 1995 from Yüzüncü Yıl University, MSc in Biochemistry in 1998, and PhD in Biochemistry in 2002 from Atatürk University, Turkey. 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