Deep learning approaches: Key-points and description.
\\n\\n
IntechOpen was founded by scientists, for scientists, in order to make book publishing accessible around the globe. Over the last two decades, this has driven Open Access (OA) book publishing whilst levelling the playing field for global academics. Through our innovative publishing model and the support of the research community, we have now published over 5,700 Open Access books and are visited online by over three million academics every month. These researchers are increasingly working in broad technology-based subjects, driving multidisciplinary academic endeavours into human health, environment, and technology.
\\n\\nBy listening to our community, and in order to serve these rapidly growing areas which lie at the core of IntechOpen's expertise, we are launching a portfolio of Open Science journals:
\\n\\nAll three journals will publish under an Open Access model and embrace Open Science policies to help support the changing needs of academics in these fast-moving research areas. There will be direct links to preprint servers and data repositories, allowing full reproducibility and rapid dissemination of published papers to help accelerate the pace of research. Each journal has renowned Editors in Chief who will work alongside a global Editorial Board, delivering robust single-blind peer review. Supported by our internal editorial teams, this will ensure our authors will receive a quick, user-friendly, and personalised publishing experience.
\\n\\n"By launching our journals portfolio we are introducing new, dedicated homes for interdisciplinary technology-focused researchers to publish their work, whilst embracing Open Science and creating a unique global home for academics to disseminate their work. We are taking a leap toward Open Science continuing and expanding our fundamental commitment to openly sharing scientific research across the world, making it available for the benefit of all." Dr. Sara Uhac, IntechOpen CEO
\\n\\n"Our aim is to promote and create better science for a better world by increasing access to information and the latest scientific developments to all scientists, innovators, entrepreneurs and students and give them the opportunity to learn, observe and contribute to knowledge creation. Open Science promotes a swifter path from research to innovation to produce new products and services." Alex Lazinica, IntechOpen founder
\\n\\nIn conclusion, Natalia Reinic Babic, Head of Journal Publishing and Open Science at IntechOpen adds:
\\n\\n“On behalf of the journal team I’d like to thank all our Editors in Chief, Editorial Boards, internal supporting teams, and our scientific community for their continuous support in making this portfolio a reality - we couldn’t have done it without you! With your support in place, we are confident these journals will become as impactful and successful as our book publishing program and bring us closer to a more open (science) future.”
\\n\\nWe invite you to visit the journals homepage and learn more about the journal’s Editorial Boards, scope and vision as all three journals are now open for submissions.
\\n\\nFeel free to share this news on social media and help us mark this memorable moment!
\\n\\n\\n"}]',published:!0,mainMedia:{caption:"",originalUrl:"/media/original/237"}},components:[{type:"htmlEditorComponent",content:'
After years of being acknowledged as the world's leading publisher of Open Access books, today, we are proud to announce we’ve successfully launched a portfolio of Open Science journals covering rapidly expanding areas of interdisciplinary research.
\n\n\n\nIntechOpen was founded by scientists, for scientists, in order to make book publishing accessible around the globe. Over the last two decades, this has driven Open Access (OA) book publishing whilst levelling the playing field for global academics. Through our innovative publishing model and the support of the research community, we have now published over 5,700 Open Access books and are visited online by over three million academics every month. These researchers are increasingly working in broad technology-based subjects, driving multidisciplinary academic endeavours into human health, environment, and technology.
\n\nBy listening to our community, and in order to serve these rapidly growing areas which lie at the core of IntechOpen's expertise, we are launching a portfolio of Open Science journals:
\n\nAll three journals will publish under an Open Access model and embrace Open Science policies to help support the changing needs of academics in these fast-moving research areas. There will be direct links to preprint servers and data repositories, allowing full reproducibility and rapid dissemination of published papers to help accelerate the pace of research. Each journal has renowned Editors in Chief who will work alongside a global Editorial Board, delivering robust single-blind peer review. Supported by our internal editorial teams, this will ensure our authors will receive a quick, user-friendly, and personalised publishing experience.
\n\n"By launching our journals portfolio we are introducing new, dedicated homes for interdisciplinary technology-focused researchers to publish their work, whilst embracing Open Science and creating a unique global home for academics to disseminate their work. We are taking a leap toward Open Science continuing and expanding our fundamental commitment to openly sharing scientific research across the world, making it available for the benefit of all." Dr. Sara Uhac, IntechOpen CEO
\n\n"Our aim is to promote and create better science for a better world by increasing access to information and the latest scientific developments to all scientists, innovators, entrepreneurs and students and give them the opportunity to learn, observe and contribute to knowledge creation. Open Science promotes a swifter path from research to innovation to produce new products and services." Alex Lazinica, IntechOpen founder
\n\nIn conclusion, Natalia Reinic Babic, Head of Journal Publishing and Open Science at IntechOpen adds:
\n\n“On behalf of the journal team I’d like to thank all our Editors in Chief, Editorial Boards, internal supporting teams, and our scientific community for their continuous support in making this portfolio a reality - we couldn’t have done it without you! With your support in place, we are confident these journals will become as impactful and successful as our book publishing program and bring us closer to a more open (science) future.”
\n\nWe invite you to visit the journals homepage and learn more about the journal’s Editorial Boards, scope and vision as all three journals are now open for submissions.
\n\nFeel free to share this news on social media and help us mark this memorable moment!
\n\n\n'}],latestNews:[{slug:"intechopen-supports-asapbio-s-new-initiative-publish-your-reviews-20220729",title:"IntechOpen Supports ASAPbio’s New Initiative Publish Your Reviews"},{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"}]},book:{item:{type:"book",id:"10739",leadTitle:null,fullTitle:"Global Decline of Insects",title:"Global Decline of Insects",subtitle:null,reviewType:"peer-reviewed",abstract:"Insects are a group of animals that contribute significantly to the proper functioning of different ecosystems on the planet. They provide services such as pollinating crops, recycling nutrients and controlling pests. Many scientific publications and reports have studied the current global decline of insects. This decline can severely affect other groups of animals including birds, reptiles, amphibians, fish, and small mammals that utilize insects as a source of food. This will have a great impact on the trophic cascade and an eventual adverse effect on the overall ecosystem. This book provides insights into the possible reasons behind the decline of insects as well as potential measures that might mitigate this decline. It contains eleven chapters written by different experts. The book is useful for a wide range of readers including entomologists, ecologists, botanists, environmentalists, and amateurs who love collecting and preserving insects.",isbn:"978-1-83969-588-9",printIsbn:"978-1-83969-587-2",pdfIsbn:"978-1-83969-589-6",doi:"10.5772/intechopen.94711",price:119,priceEur:129,priceUsd:155,slug:"global-decline-of-insects",numberOfPages:198,isOpenForSubmission:!1,isInWos:null,isInBkci:!1,hash:"543783652b9092962a8fa4bed38eeb17",bookSignature:"Hamadttu Abdel Farag El-Shafie",publishedDate:"July 20th 2022",coverURL:"https://cdn.intechopen.com/books/images_new/10739.jpg",numberOfDownloads:1607,numberOfWosCitations:0,numberOfCrossrefCitations:11,numberOfCrossrefCitationsByBook:0,numberOfDimensionsCitations:20,numberOfDimensionsCitationsByBook:0,hasAltmetrics:1,numberOfTotalCitations:31,isAvailableForWebshopOrdering:!0,dateEndFirstStepPublish:"February 25th 2021",dateEndSecondStepPublish:"March 25th 2021",dateEndThirdStepPublish:"May 24th 2021",dateEndFourthStepPublish:"August 12th 2021",dateEndFifthStepPublish:"October 11th 2021",currentStepOfPublishingProcess:5,indexedIn:"1,2,3,4,5,6",editedByType:"Edited by",kuFlag:!1,featuredMarkup:null,editors:[{id:"192142",title:"Dr.",name:"Hamadttu",middleName:null,surname:"Abdel Farag El-Shafie",slug:"hamadttu-abdel-farag-el-shafie",fullName:"Hamadttu Abdel Farag El-Shafie",profilePictureURL:"https://mts.intechopen.com/storage/users/192142/images/system/192142.jpg",biography:"Hamadttu Abdel Farag El-Shafie is an Associate Professor of Entomology and a senior research entomologist at the Date Palm Research Center of Excellence, King Faisal University, Saudi Arabia. He is the head of the sustainable pest management research program at Date Palm. He obtained his BSc and MSc from the University of Khartoum, Sudan, in 1988 and 1993, respectively. He received his Ph.D. from the University of Giessen, Institute of Phytopathology and Applied Entomology, Germany, in 2001. In 2008, Dr. El-Shafie was appointed head of the Crop Protection Department, and then deputy dean for academic affairs at the Faculty of Agriculture, University of Khartoum, Sudan. He supervised twenty-five MSc students and five Ph.D. students at the University of Khartoum. His research interest focuses on the sustainable management of field crop pests using biopesticides and semiochemical-based technologies. He has more than twelve years of experience in the management of the invasive red palm weevil and other date palm pests of major significance. He has published seventy research papers in international peer-reviewed journals and seventeen book chapters with international publishers. He has also edited two books. Dr. El-Shafie has participated in more than thirty international conferences in the field of entomology. During the last decade, he has been reviewing manuscripts for thirty-five renowned international journals.",institutionString:"King Faisal University",position:null,outsideEditionCount:0,totalCites:0,totalAuthoredChapters:"7",totalChapterViews:"0",totalEditedBooks:"2",institution:{name:"King Faisal University",institutionURL:null,country:{name:"Saudi Arabia"}}}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,coeditorOne:null,coeditorTwo:null,coeditorThree:null,coeditorFour:null,coeditorFive:null,topics:[{id:"35",title:"Entomology",slug:"entomology"}],chapters:[{id:"77656",title:"Causes and Reasons of Insect Decline and the Way Forward",doi:"10.5772/intechopen.98786",slug:"causes-and-reasons-of-insect-decline-and-the-way-forward",totalDownloads:341,totalCrossrefCites:0,totalDimensionsCites:0,hasAltmetrics:1,abstract:"There are lot of reasons and causes of insect decline. The main causes of insect decline is attributed to habitat destruction, land use changes, deforestation, intensive agriculture, urbanization, pollution, climate change, introduction of invasive insect species, application of pesticides, mass trapping of insects using pheromones and light traps, pathological problems on various insects, and introduction of exotic honey bees in new areas that compete with the native bees for resource portioning and other management techniques for pest management, and even not leaving any pest residue for predators and parasitoids for their survival. The use of chemical insecticides against target or non-target organisms is major cause for insect decline. The diseases and decline of the important pollinators is still a mistry for colony collapse disorder. To overcome the cause of insect decline, various conservation techniques to be adopted and augmentation of artificial nesting and feeding structures, use of green pesticides, maintaining the proper pest defender ratio (P:D), policies and reaching to political audience at global level and other factors already discussed in the chapter may be helpful for mitigating the insect decline and especially for the pollinators, a key insect for life.",signatures:"Showket A. Dar, Mohmmad Javed Ansari, Yahya Al Naggar, Shafia Hassan, Syed Nighat, Syed Burjes Zehra, Rizwan Rashid, Mudasir Hassan and Barkat Hussain",downloadPdfUrl:"/chapter/pdf-download/77656",previewPdfUrl:"/chapter/pdf-preview/77656",authors:[{id:"319667",title:"Dr.",name:"Barkat",surname:"Hussain",slug:"barkat-hussain",fullName:"Barkat Hussain"},{id:"424959",title:"Dr.",name:"Showket A.",surname:"Dar",slug:"showket-a.-dar",fullName:"Showket A. Dar"},{id:"424960",title:"Dr.",name:"Mohmmad Javed",surname:"Ansari",slug:"mohmmad-javed-ansari",fullName:"Mohmmad Javed Ansari"},{id:"424961",title:"Dr.",name:"Yahya Al",surname:"Naggar",slug:"yahya-al-naggar",fullName:"Yahya Al Naggar"},{id:"424962",title:"Dr.",name:"Syed",surname:"Nighat",slug:"syed-nighat",fullName:"Syed Nighat"},{id:"424963",title:"Dr.",name:"Syed Burjes",surname:"Zehra",slug:"syed-burjes-zehra",fullName:"Syed Burjes Zehra"},{id:"424964",title:"Dr.",name:"Rizwan",surname:"Rashid",slug:"rizwan-rashid",fullName:"Rizwan Rashid"},{id:"424965",title:"Dr.",name:"Mudasir",surname:"Hassan",slug:"mudasir-hassan",fullName:"Mudasir Hassan"}],corrections:null},{id:"78578",title:"Potential Reasons for Insect Decline",doi:"10.5772/intechopen.100065",slug:"potential-reasons-for-insect-decline",totalDownloads:179,totalCrossrefCites:0,totalDimensionsCites:0,hasAltmetrics:0,abstract:"Insects are the key component of world’s ecosystem and act as vital force to maintain life’s framework. But in present scenario, Insects are under multi-continental crisis apparent as reduction in abundance, diversity and biomass. The impact of decline is severe in areas which are highly impacted by human activities such as industrialized and agricultural landscapes. Habitat loss and degradation; intensive use of pesticides; pollution; introduction of invasive species and climate change are the most influential factors for their alarming decline and each factor is multifaceted. The accelerated decline in insect population can cause unpredictable negative consequences for the biosphere and is a matter of global concern that requires immediate and effective international collaborations. An urgent need is to identify the species at greatest threat; factors threatening their survival and finally the consequences of their loss. In order to maintain the integrity of managed and natural ecosystems, the protection of Insect diversity is critically important.",signatures:"Gagan Preet Kour Bali and Amritpal Singh Kaleka",downloadPdfUrl:"/chapter/pdf-download/78578",previewPdfUrl:"/chapter/pdf-preview/78578",authors:[{id:"277963",title:"Dr.",name:"Amritpal Singh",surname:"Kaleka",slug:"amritpal-singh-kaleka",fullName:"Amritpal Singh Kaleka"},{id:"277966",title:"Dr.",name:"Gagan",surname:"Preet Kour Bali",slug:"gagan-preet-kour-bali",fullName:"Gagan Preet Kour Bali"}],corrections:null},{id:"80971",title:"Agricultural Intensification Causes Decline in Insect Biodiversity",doi:"10.5772/intechopen.101360",slug:"agricultural-intensification-causes-decline-in-insect-biodiversity",totalDownloads:58,totalCrossrefCites:0,totalDimensionsCites:0,hasAltmetrics:0,abstract:"The world’s population exceeded 7 billion in late 2011 and it is expected to reach 9.3 billion by 2050. Meanwhile, demand for food is predicted to increase between 50 and 100% by 2050. To meet the food demands of the increasing population, agricultural intensification practices including growing monocultures of high-yielding crop varieties and increased applications of fertilizers and pesticides have been used to increase productivity. These practices, however, impact negatively on biodiversity of existing flora and fauna, particularly causing huge declines in insect biodiversity. This chapter reviews present state of knowledge about agricultural intensification practices and global decline of insect biodiversity (i.e., pest and beneficial insect species) in intensive agricultural system and point out the likely drivers of these declines. It concludes the review by examining sustainable agricultural intensification practices that could be used to mitigate these biodiversity declines while maintaining productivity in intensive agricultural systems.",signatures:"Mumuni Abudulai, Jerry Asalma Nboyine, Peter Quandahor, Ahmed Seidu and Fousséni Traore",downloadPdfUrl:"/chapter/pdf-download/80971",previewPdfUrl:"/chapter/pdf-preview/80971",authors:[{id:"216049",title:"Ph.D.",name:"Mumuni",surname:"Abudulai",slug:"mumuni-abudulai",fullName:"Mumuni Abudulai"},{id:"356219",title:"Dr.",name:"Jerry",surname:"Asalma Nboyine",slug:"jerry-asalma-nboyine",fullName:"Jerry Asalma Nboyine"},{id:"425036",title:"Mr.",name:"Ahmed",surname:"Seidu",slug:"ahmed-seidu",fullName:"Ahmed Seidu"},{id:"425038",title:"Mr.",name:"Peter",surname:"Quandahor",slug:"peter-quandahor",fullName:"Peter Quandahor"},{id:"485112",title:"Dr.",name:"Fousséni",surname:"Traore",slug:"fousseni-traore",fullName:"Fousséni Traore"}],corrections:null},{id:"77657",title:"Pesticide Impact on Honeybees Declines and Emerging Food Security Crisis",doi:"10.5772/intechopen.98871",slug:"pesticide-impact-on-honeybees-declines-and-emerging-food-security-crisis",totalDownloads:170,totalCrossrefCites:1,totalDimensionsCites:1,hasAltmetrics:0,abstract:"Bee crisis is threatening worldwide food security. Pesticides are extensively used in the agricultural zone. Unfortunately, these pesticides cause severe toxicity toward pollinators than the target pests such as honeybees. This review summarizes the different studies related to pesticide hazards of bees. This paper reported risks of pesticides neurological and physiological poisoning toward honeybees. Pesticides act as poison and ruin vital functions involved in leaning and cognition, behavior and, the body physiological mechanisms. Many laboratory and field research data evaluated the lethal and sub-lethal poisoning on bee foraging dance, learning, and memory abilities of honeybees. Insecticide residues are detected in bee bodies and LD50 and LC50 values evaluated. It is also studied that in honeybees systemic insecticide residues and, its metabolite adulterated in their body during foraging activities. Similarly, pesticide-contaminated food stored in a hive consumed continuously by honeybees may cause sub-lethal toxicity effects. Which causes anomalous bee social behavior and ultimately leads to colony collapse disorder. If population of pollinator decline it will disturb the food chain and leads to food crisis. This review emphasized causes of bee decline with the emergence of pesticides in agricultural domains.",signatures:"Farkhanda Manzoor and Mahnoor Pervez",downloadPdfUrl:"/chapter/pdf-download/77657",previewPdfUrl:"/chapter/pdf-preview/77657",authors:[{id:"354312",title:"Prof.",name:"Dr Farkhanda",surname:"Manzoor",slug:"dr-farkhanda-manzoor",fullName:"Dr Farkhanda Manzoor"},{id:"354313",title:"Dr.",name:"Mahnoor",surname:"Pervez",slug:"mahnoor-pervez",fullName:"Mahnoor Pervez"}],corrections:null},{id:"78872",title:"Diversity, Importance and Decline of Pollinating Insects in Present Era",doi:"10.5772/intechopen.100316",slug:"diversity-importance-and-decline-of-pollinating-insects-in-present-era",totalDownloads:104,totalCrossrefCites:0,totalDimensionsCites:0,hasAltmetrics:0,abstract:"Pollination is a multi-million-year-old co-evolutionary process involving flowering plants and pollinators. It is one of the most important mechanisms in preservation and promotion of biodiversity as well as life on Earth. Pollinator diversity is essential for maintaining overall biological diversity in many habitats including agro-ecosystems. Pollinators are responsible for assisting reproduction in over 80% of the world’s flowering plants. In their absence, humans and wildlife would go hungry. Insects are the most efficient pollinators as they play a crucial part in pollination ecology. Pollinators and their habitats have ecological, economic, cultural and social benefits. Pollination efficiency is highly dependent on certain attributes and characteristics of pollinators such as vision, anatomy, food preferences, olfaction, behaviour and learning ability. With the rapid growth of human population, our demand for food has also risen. Our agricultural systems will need to produce more food in a sustainable manner in the future to cope with this. Pollinators play an important role in these ecosystems and will continue to do so in the future. Because pollinators are so important to agriculture, we need to learn more about which crops require specific pollinators and how to best maintain and promote both wild and controlled species. Their diversity needs protection because there are specific relationships between certain crops and pollinators. Pollinator communities are suffering as a result of man-made habitat disruptions, including severe biodiversity loss. This diversity must be protected by combining conservation measures with sustainable farming practices which could increase crop yields while protecting insect pollinator species.",signatures:"Navkiran Kaur and Amritpal Singh Kaleka",downloadPdfUrl:"/chapter/pdf-download/78872",previewPdfUrl:"/chapter/pdf-preview/78872",authors:[{id:"277963",title:"Dr.",name:"Amritpal Singh",surname:"Kaleka",slug:"amritpal-singh-kaleka",fullName:"Amritpal Singh Kaleka"},{id:"277967",title:"Ms.",name:"Navkiran",surname:"Kaur",slug:"navkiran-kaur",fullName:"Navkiran Kaur"}],corrections:null},{id:"79121",title:"Botanical Insecticides Are a Non-Toxic Alternative to Conventional Pesticides in the Control of Insects and Pests",doi:"10.5772/intechopen.100416",slug:"botanical-insecticides-are-a-non-toxic-alternative-to-conventional-pesticides-in-the-control-of-inse",totalDownloads:276,totalCrossrefCites:6,totalDimensionsCites:11,hasAltmetrics:0,abstract:"Insect control for crops is one of the most critical global concerns. Pest management is an economic and ecological problem worldwide due to the human and environmental risks raised by most synthetic pesticide products. Botanical insecticides have resurfaced in popularity due to their low cost and low environmental impact, rather than their negative effects on human health. Botanical insecticides destroy only the insects they are meant to kill, leaving no residue on food or in the environment. Botanicals have long been used to combat pests. The compounds have many environmental advantages. However, as opposed to other bio-control pests and pathogens, their use was minimal during the twentieth century. In developing countries, botanical insecticides are well adapted for use in organic food production. Nonetheless, they may play a far bigger role in developed countries’ food production and post-harvest food protection. Consequently, the current chapter briefly addresses botanicals with active ingredients with insecticidal, antifeedant, or repellent properties.",signatures:"Nazeer Ahmed, Mukhtar Alam, Muhammad Saeed, Hidayat Ullah, Toheed Iqbal, Khalid Awadh Al-Mutairi, Kiran Shahjeer, Rafi Ullah, Saeed Ahmed, Nibal Abd Aleem Hassan Ahmed, Hanem Fathy Khater and Muhammad Salman",downloadPdfUrl:"/chapter/pdf-download/79121",previewPdfUrl:"/chapter/pdf-preview/79121",authors:[{id:"97300",title:"Prof.",name:"Khalid Awadh",surname:"Al-Mutairi",slug:"khalid-awadh-al-mutairi",fullName:"Khalid Awadh Al-Mutairi"},{id:"191884",title:"Dr.",name:"Toheed",surname:"Iqbal",slug:"toheed-iqbal",fullName:"Toheed Iqbal"},{id:"263876",title:"Dr.",name:"Hidayat",surname:"Ullah",slug:"hidayat-ullah",fullName:"Hidayat Ullah"},{id:"263877",title:"Dr.",name:"Mukhtar",surname:"Alam",slug:"mukhtar-alam",fullName:"Mukhtar Alam"},{id:"355528",title:"Dr.",name:"Nazeer",surname:"Ahmed",slug:"nazeer-ahmed",fullName:"Nazeer Ahmed"},{id:"420069",title:"Mrs.",name:"Kiran",surname:"Shahjeer",slug:"kiran-shahjeer",fullName:"Kiran Shahjeer"},{id:"420070",title:"Mr.",name:"Saeed",surname:"Ahmed",slug:"saeed-ahmed",fullName:"Saeed Ahmed"},{id:"420221",title:"Dr.",name:"Muhammad",surname:"Saeed",slug:"muhammad-saeed",fullName:"Muhammad Saeed"},{id:"420222",title:"Dr.",name:"Rafi",surname:"Ullah",slug:"rafi-ullah",fullName:"Rafi Ullah"},{id:"436507",title:"Dr.",name:"Nibal Abd Aleem",surname:"Hassan Ahmed",slug:"nibal-abd-aleem-hassan-ahmed",fullName:"Nibal Abd Aleem Hassan Ahmed"},{id:"436596",title:"Prof.",name:"Hanem Fathy",surname:"Khater",slug:"hanem-fathy-khater",fullName:"Hanem Fathy Khater"},{id:"485113",title:"Dr.",name:"Muhammad",surname:"Salman",slug:"muhammad-salman",fullName:"Muhammad Salman"}],corrections:null},{id:"78945",title:"Botanical Insecticides and Their Potential as Anti-Insect/Pests: Are They Successful against Insects and Pests?",doi:"10.5772/intechopen.100418",slug:"botanical-insecticides-and-their-potential-as-anti-insect-pests-are-they-successful-against-insects-",totalDownloads:234,totalCrossrefCites:4,totalDimensionsCites:8,hasAltmetrics:0,abstract:"In low-income countries, subsistence and transitional farms frequently use botanical insecticides. The shortage or high cost of industrial pesticides also prompts their use. Botanical insecticides are also prescribed by agricultural and development programs and certain development organizations. However, since insecticidal proof of their effectiveness and protection might not be sufficient or usable, this may be called into question. While insecticidal botanicals have been extensively studied, there has yet to be a fusion that focuses especially on the domestic synthesis of biopesticides that work infield and storage effectively. In this chapter, we look at the effectiveness of botanicals (neem, garlic, and essential oil) that are used as insecticides. In addition, this chapter also focuses on research carried out on the use of these essential oils as insecticides. Processes that use variable amounts of ingredients and concentrations and ratios of active ingredients can have varying impacts on the efficacy of plant-based biological insecticides. Finally, using home-made insecticides would reduce the losses that occur during food production and enable us to use environment-friendly pest management methods.",signatures:"Toheed Iqbal, Nazeer Ahmed, Kiran Shahjeer, Saeed Ahmed, Khalid Awadh Al-Mutairi, Hanem Fathy Khater and Reham Fathey Ali",downloadPdfUrl:"/chapter/pdf-download/78945",previewPdfUrl:"/chapter/pdf-preview/78945",authors:[{id:"97300",title:"Prof.",name:"Khalid Awadh",surname:"Al-Mutairi",slug:"khalid-awadh-al-mutairi",fullName:"Khalid Awadh Al-Mutairi"},{id:"191884",title:"Dr.",name:"Toheed",surname:"Iqbal",slug:"toheed-iqbal",fullName:"Toheed Iqbal"},{id:"355528",title:"Dr.",name:"Nazeer",surname:"Ahmed",slug:"nazeer-ahmed",fullName:"Nazeer Ahmed"},{id:"420069",title:"Mrs.",name:"Kiran",surname:"Shahjeer",slug:"kiran-shahjeer",fullName:"Kiran Shahjeer"},{id:"420070",title:"Mr.",name:"Saeed",surname:"Ahmed",slug:"saeed-ahmed",fullName:"Saeed Ahmed"},{id:"71812",title:"Prof.",name:"Hanem Fathy",surname:"Khater",slug:"hanem-fathy-khater",fullName:"Hanem Fathy Khater"},{id:"436610",title:"Dr.",name:"Reham Fathey",surname:"Ali",slug:"reham-fathey-ali",fullName:"Reham Fathey Ali"}],corrections:null},{id:"81925",title:"Fenitothion Degradation by Aspergillus parasiticus",doi:"10.5772/intechopen.100028",slug:"fenitothion-degradation-by-em-aspergillus-parasiticus-em-",totalDownloads:3,totalCrossrefCites:0,totalDimensionsCites:0,hasAltmetrics:0,abstract:"India is a predominantly agriculture-based country with a population of 1.27 billion, according to FAO the population has reached to 1.66 billion in between 2007 and 2050. Tense because of overgrowing population the yield of crops were increased by applying various insecticides for controlling (insects, pests). Globally, an appraise 1 to 2.5 million tons of effective insecticide additives go on applied each year, especially in agriculture. Fenitrothion is an organophosphate insecticide employed to destroy pests, insects particularly in Paddy fields and it is an acetylcholinesterase inhibitor, neurotoxicant and the toxic metabolites in the environment is remain for longer periods, so it is necessary to degrade the fenitrothion by biodegradation. The fungi Aspergillus parasiticus were screened from paddy fields and Molecular characterized it by 26S rDNA gene sequencing, the fungi breaks the insecticide within 24 h of incubation in PDB. The course of the degradation process was studied using FTIR and HPLC.",signatures:"Thenepalli Sudha Rani and Potireddy Suvarna Latha Devi",downloadPdfUrl:"/chapter/pdf-download/81925",previewPdfUrl:"/chapter/pdf-preview/81925",authors:[{id:"355512",title:"Ph.D. Student",name:"Thenepalli",surname:"Sudha Rani",slug:"thenepalli-sudha-rani",fullName:"Thenepalli Sudha Rani"},{id:"356086",title:"Prof.",name:"Potireddy Suvarna",surname:"Latha Devi",slug:"potireddy-suvarna-latha-devi",fullName:"Potireddy Suvarna Latha Devi"}],corrections:null},{id:"78491",title:"Insect Conservation and Management: A Need of the Hour",doi:"10.5772/intechopen.100023",slug:"insect-conservation-and-management-a-need-of-the-hour",totalDownloads:38,totalCrossrefCites:0,totalDimensionsCites:0,hasAltmetrics:0,abstract:"Insects play a very vital role in divergent ecosystems and have gained great economic and medical importance as pollinators, pests, predators, parasitoids, decomposers and vectors. With the large-scale practice of synthetic pesticides, the diminishing rate of beneficial and pollinator insects is increasing rapidly. Environmental pollution, climate change, global warming, urbanization, industrialization and some natural calamities like wildfires add more fuel to the acceleration of insect decline all over the world. Alternative steps should be employed to replace the toxic pesticides and implementation of integrated pest management (IPM) should be put forward to reduce the overuse of synthetic pesticides and fertilizers, which have a great impact on beneficial insects as well as birds, aquatic organisms, and also on human health. The present study aims to create awareness among the researchers and general public by providing a brief review of insect importance, decline and conservation strategies.",signatures:"Muzafar Riyaz, Rauf Ahmad Shah and Soosaimanickam Maria Packiam",downloadPdfUrl:"/chapter/pdf-download/78491",previewPdfUrl:"/chapter/pdf-preview/78491",authors:[{id:"354257",title:"Dr.",name:"Muzafar",surname:"Riyaz",slug:"muzafar-riyaz",fullName:"Muzafar Riyaz"},{id:"416857",title:"MSc.",name:"Rauf Ahmad",surname:"Shah",slug:"rauf-ahmad-shah",fullName:"Rauf Ahmad Shah"},{id:"429272",title:"Dr.",name:"Soosaimanickam",surname:"Maria Packiam",slug:"soosaimanickam-maria-packiam",fullName:"Soosaimanickam Maria Packiam"}],corrections:null},{id:"79060",title:"Description of a New Species of the Genus Anagrus (Hymenoptera: Chalcidoidea: Mymaridae): A Biocontrol Agent as an Alternative to Insecticide Use",doi:"10.5772/intechopen.99957",slug:"description-of-a-new-species-of-the-genus-em-anagrus-em-hymenoptera-chalcidoidea-mymaridae-a-biocont",totalDownloads:83,totalCrossrefCites:0,totalDimensionsCites:0,hasAltmetrics:0,abstract:"Although insects are economically important as they produce honey, silk, act as pollinators and also play an important role in functioning of an ecosystem, yet insect population is declining very fast. One of the possible causes of insects decline is excessive use of pesticides. Control of pest with synthetic chemicals or pesticides result in several issues and complications. These chemical pesticides or insecticides can also cause toxic effects on beneficial organisms like honeybees and butterflies which are important pollinators. So, biocontrol agents can be used as best alternative to control pest without harming beneficial organism and non-target insects or other organism as majority of biocontrol agents are host specific. Biological control agents including predators and parasotoids are natural enemies of insect pests. Present chapter deals with the description and illustration of one new species Anagrus (Anagrus) sololinearis sp.nov from India. This new species belongs to genus Anagrus (Hymenoptera: Chalcidoidea: Mymaridae). Genus Anagrus is considered as one of the important and most promising biocontrol agents in insects as it is an egg parasitoid.",signatures:"Shireen Saleem and Shoeba Binte Anis",downloadPdfUrl:"/chapter/pdf-download/79060",previewPdfUrl:"/chapter/pdf-preview/79060",authors:[{id:"355546",title:"Dr.",name:"Shireen",surname:"Saleem",slug:"shireen-saleem",fullName:"Shireen Saleem"},{id:"355548",title:"Dr.",name:"Shoeba",surname:"Binte Anis",slug:"shoeba-binte-anis",fullName:"Shoeba Binte Anis"}],corrections:null},{id:"80012",title:"Impacts of Organic Farming on Insects Abundance and Diversity",doi:"10.5772/intechopen.102035",slug:"impacts-of-organic-farming-on-insects-abundance-and-diversity",totalDownloads:123,totalCrossrefCites:0,totalDimensionsCites:0,hasAltmetrics:0,abstract:"Organic farming encourages maximum utilization of the natural biological processes to manage the farm in terms of soil fertilization and pest control, which implies using none or less synthetic fertilizers, pesticides, and plant and animal growth-promoting substances. All these practices increase arthropod diversity, particularly soil-dwelling insects. Intercropping, cover crops, and hedges, which are common practices in organic fields, provide alternative habitats for arthropod communities. The refugia also provide a good source of food for pollinators in terms of pollen grains and nectar. The interactions among the different plant and animal taxa (weeds, birds, mammals) that are found in the organic farming ecosystem have a great impact on insects’ abundance and diversity. This chapter summarizes the impacts of the organic farming system on the abundance and diversity of insects. The role of organic farming in mitigating the impact of agriculture intensification, urbanization, deforestation, and climate change on global insects’ decline and diversity loss is discussed.",signatures:"Hamadttu Abdel Farag El-Shafie",downloadPdfUrl:"/chapter/pdf-download/80012",previewPdfUrl:"/chapter/pdf-preview/80012",authors:[{id:"192142",title:"Dr.",name:"Hamadttu",surname:"Abdel Farag El-Shafie",slug:"hamadttu-abdel-farag-el-shafie",fullName:"Hamadttu Abdel Farag El-Shafie"}],corrections:null}],productType:{id:"1",title:"Edited Volume",chapterContentType:"chapter",authoredCaption:"Edited by"},subseries:null,tags:null},relatedBooks:[{type:"book",id:"9698",title:"Invasive Species",subtitle:"Introduction Pathways, Economic Impact, and Possible Management Options",isOpenForSubmission:!1,hash:"132b23bdec7eff6ba300d67cc44d2d91",slug:"invasive-species-introduction-pathways-economic-impact-and-possible-management-options",bookSignature:"Hamadttu El-Shafie",coverURL:"https://cdn.intechopen.com/books/images_new/9698.jpg",editedByType:"Edited by",editors:[{id:"192142",title:"Dr.",name:"Hamadttu",surname:"Abdel Farag El-Shafie",slug:"hamadttu-abdel-farag-el-shafie",fullName:"Hamadttu Abdel Farag El-Shafie"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"6619",title:"Insect Science",subtitle:"Diversity, Conservation and Nutrition",isOpenForSubmission:!1,hash:"08241b041b2072a88452041f8fdebe7e",slug:"insect-science-diversity-conservation-and-nutrition",bookSignature:"Mohammad Manjur Shah and Umar Sharif",coverURL:"https://cdn.intechopen.com/books/images_new/6619.jpg",editedByType:"Edited by",editors:[{id:"94128",title:"Dr.",name:"Mohammad Manjur",surname:"Shah",slug:"mohammad-manjur-shah",fullName:"Mohammad Manjur Shah"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"10423",title:"The Wonders of Diptera",subtitle:"Characteristics, Diversity, and Significance for the World's Ecosystems",isOpenForSubmission:!1,hash:"2746b4288e78c8688d1be1bd9d99a127",slug:"the-wonders-of-diptera-characteristics-diversity-and-significance-for-the-world-s-ecosystems",bookSignature:"Farzana Khan Perveen",coverURL:"https://cdn.intechopen.com/books/images_new/10423.jpg",editedByType:"Edited by",editors:[{id:"75563",title:"Dr.",name:"Farzana Khan",surname:"Perveen",slug:"farzana-khan-perveen",fullName:"Farzana Khan Perveen"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"1591",title:"Infrared Spectroscopy",subtitle:"Materials Science, Engineering and Technology",isOpenForSubmission:!1,hash:"99b4b7b71a8caeb693ed762b40b017f4",slug:"infrared-spectroscopy-materials-science-engineering-and-technology",bookSignature:"Theophile Theophanides",coverURL:"https://cdn.intechopen.com/books/images_new/1591.jpg",editedByType:"Edited by",editors:[{id:"37194",title:"Dr.",name:"Theophile",surname:"Theophanides",slug:"theophile-theophanides",fullName:"Theophile Theophanides"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"3161",title:"Frontiers in Guided Wave Optics and Optoelectronics",subtitle:null,isOpenForSubmission:!1,hash:"deb44e9c99f82bbce1083abea743146c",slug:"frontiers-in-guided-wave-optics-and-optoelectronics",bookSignature:"Bishnu Pal",coverURL:"https://cdn.intechopen.com/books/images_new/3161.jpg",editedByType:"Edited by",editors:[{id:"4782",title:"Prof.",name:"Bishnu",surname:"Pal",slug:"bishnu-pal",fullName:"Bishnu Pal"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"371",title:"Abiotic Stress in Plants",subtitle:"Mechanisms and Adaptations",isOpenForSubmission:!1,hash:"588466f487e307619849d72389178a74",slug:"abiotic-stress-in-plants-mechanisms-and-adaptations",bookSignature:"Arun Shanker and B. 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The image data processing is a relevant support for clinical diagnosis and sharing of health information, for instance, the correct interpretation of images may be crucial for early diseases detection. The use of sophisticated devices has greatly improved the acquisition of data at a very high resolution and faster rate, although the image interpretation process based on machine learning techniques is only recently taking hold. Bioinformatics tools allow to retrieve information able to support a scientist during a diagnosis in order to detect efficiently abnormalities and to monitor their changes over time. In the last years, medical and biological images are quickly growing in terms of size and information content. The term “bioimage” concerns all images related to biological samples acquired using medical technologies such as the Computed Tomography (CT) or the Magnetic Resonance Imaging (MRI); briefly, CT is a technique based on ionizing radiation, for instance, X-rays are used to acquire the images; instead, MRI (or Nuclear-MRI) uses magnetic fields and Radio Frequencies (RF) to produce detailed pictures. An MRI Scanner measures the RF emitted by hydrogen atoms, the RF are directly related to the amount of energy previously provided to the atom and to its necessity to return at an equilibrium state after an excitation. These different approaches make that a CT scanner is better suited to detect cancer or cerebral hemorrhage, while brain tumor is more clearly visible using an MRI scanner. Bioinformatics techniques allow the developing of solutions which provide a support for images acquisition and analysis as well as the integration of biological datasets (e.g., gene data and ontologies) for patterns discovering and disorders detection. For instance, in neuroimaging an interesting branch of study concerns the correlation between brain regions and cognitive functions using several techniques such as the Functional-MRI (fMRI); the latter is based on the Blood Oxygenation Level Dependent (BOLD) signal which represents the increment of blood oxygenation in order to identify the brain region affected during activities (e.g., hands motion) and to reflect the local neuronal signaling [1]. This approach uses the BOLD signal in fMRI to study the activity of the hydrogen atoms that compose the water molecules contained in the brain [2].
BOLD signal in fMRI uses the hydrogen atoms that compose the water molecules contained in the brain to study its activity. An MRI Scanner measures the radio frequency emitted by hydrogen atoms after a first step during which this absorbs energy to the same radio frequency; this effect is related to the necessity of an atom to return to an equilibrium state after an excitation.
When a magnetic field is applied, the atoms absorb energy at a determinate radio frequency; for a clinical-standard fMRI technology at 1.5 Tesla this is approximately 64 MHz. BOLD techniques measure the changes in blood oxygenation resulting from the inhomogeneity of the magnetic field within each small volume of tissue that contains hydrogen atoms. Furthermore, the BOLD signal depends on several magnetic properties, such as Deoxy- and Oxy-hemoglobin. The first introduces an inhomogeneity into the magnetic field due to its paramagnetic properties, the latter is weakly diamagnetic. The variations in the concentrations of Deoxy- and Oxy-hemoglobin produce a decrement and an increment, respectively, in image intensity [3]. Many diseases may be studied using neuroimaging to analyze modifications and alterations in brain regions. Nevertheless, to perform detailed analysis, bioinformatics techniques and algorithms have to be developed. Recent studies focus their attention on the improvement of prediction performance in evaluation of diseases, for instance, in [4] authors recruited 120 schizophrenia patients and 120 healthy controls to compare four methods: Linear Discriminant Analysis (LDA), k-Nearest Neighbors (KNN), Gaussian process classifier (GPC) and Support Vector Machines (SVM). The results illustrate that using brain imaging is possible to study the brain areas as well as a set of specific cognitive functions and their related mental activities. Assuming that a physician needs to develop a model for phenotype–genotype association in Alzheimer’s disease (AD), an association study of longitudinal phenotypic markers to AD relevant SNPs could be conducted in order to perform a task-correlated longitudinal sparse regression between MRI and Micro Array technologies, respectively, for the images and the genomic information [5]. The study of bioimaging has met a large quantitative data from heterogeneous sources and the correlation among the data is a decisive step for knowledge extraction; thus, the latter allows a scientist to study novel solutions, and bioinformatics algorithms play a primary role to match heterogeneous sources, based on different models, in order to extract the information of interest.
A file format is a solution able to organize a data inside a file using a specific model to allow the storing and the handling of its information content; building a standard for these processes is necessary to extend the compatibility to the highest number of devices and tools. The increasing adoption in the clinical practice of the 3D solutions, due also to the evolution of technologies in medical imaging such as the Computed Tomography (CT) and the Magnetic Resonance Imaging (MRI), produced the affirmation of the Digital Imaging and Communication in Medicine (DICOM) standard. It is supported from almost all independent manufacturers of imaging equipment that need to guarantee an easy and fast solution for data storage and exchange; furthermore, DICOM is adaptable and extensible to accommodate the requirements for an imaging technology. Briefly, this standard is able to handle the storage, viewing, and transmission of medical images, as well as data sharing in clinical research. In the DICOM format each image is stored in a separate instance (comparable to an ‘object’ in computer language) which includes metadata and images data. The first contains several information concerning the patient, the manufacturer and technology used to acquire the medical images (modality included), the physician, imaging parameters (e.g., slice thickness and spacing, image orientation and frames features); its size is small as all attributes are represented using raw text in tags-based format. Instead, an image (or slice) concerns the numerical matrices containing a gray-scale value for each related pixel; thus, the volume rendering consisting of the union of all slices in the properly order. In the DICOM standard a redundancy of information is created due to the fact that metadata are repeated in a header generated for all images; this is due to the need to guarantee the independence of each slice from the others both during viewing and transmission. The flexibility of tags information contained in the header produces different information among the scanner manufacturers based on DICOM; this causes incompatibilities and critical failures in the tools that use it.
These disadvantages have led to the implementation of novel standards such as: Neuroimaging Informatics Technology Initiative (NIfTI) standard, Analyze or Minc.
The first version of NIfTI was developed as a set of extensions starting from the Analyze (release 7.5) format in order to extend the support to multidimensional data (e.g., for volumes representation) and to allow the handling of MRI data. Analyze consists of a header (a .hdr file) that contains information (e.g., dimensions and identification), and in voxel raw data (a .img file) for image representation. On the other hand, it does not support the unambiguously establish of the image orientation, as well as the unsigned 16 bits data so its adoption is not widespread [6]. NIfTI is a minimalist format adopted in neuroimaging research consisting, as in Analyze, of a header and an uncompressed image data stored, respectively in a ‘.hdr’ and ‘.img’ file; furthermore, it is able to unify both elements in a single ‘.nii’ file that have the first 348 bytes reserved for the header. In a NIfTI file, an image may be represented using up to seven dimensions of which three are for the space, one for the time and three for the diffusion gradient direction [7]; this feature allowed its growing adoption in neuroscience.
A conversion from DICOM to NIfTI is generally possible using dedicated solutions like ‘dcm2nii’ (http://www.nitrc.org/projects/dcm2nii/). In [8] a test-scenario based on a cloud implementation of dcm2nii is proposed; it provides the analysis of 812 volumes, stored in 991,000 DICOM files and related to 41 subjects undergoing clinical CT scanners for a neurological study. Experimental results illustrate that the conversion process is extremely time-consuming; in details, authors report that it may need of a computing grid which uses up to 156 cores to process about 52 volumes/minute.
Ultimately, Minc format was developed in 1992 by the Montreal Neurological Institute (MNI); the last release (Minc2) is based on Hierarchical Data Format version 5 (HDF5) and supports large data file as well as a set of tools for DICOM/NIfTI conversion. Each MINC file concerns a multidimensional dataset with all related metadata. It is generally used only in projects developed directly by the MNI Brain Imaging Center for the releasing of library and tools [9].
To date the most widespread formats among the mentioned remain the DICOM and the NIfTI standards which are also supported by most medical device manufacturers.
Techniques and methods for image analysis are generally based on Machine Learning (ML) and Artificial Intelligence (AI); these allow to efficiently derive relevant information from heterogeneous data such as phenotypes, morphologic features, as well as patterns. In bioinformatics, a pattern may be related to diseases or alterations and it is generally used to associate an image domain with a specific alteration. Briefly, it consists of a sequence of items modeled through a mathematical function able to represent a specific structure, for instance, the patterns can be used to represent a part of an image, or to better say a part of the matrix that contains the value of each pixel/voxel. Assuming that we want to use this approach in neurosciences, a pattern could be used to discover the alterations that affect the normal functions of the brain; the issue could be solved using an algorithm for pattern recognition which is able to integrate information across several sources. In this context, the techniques based on Machine Learning (ML) and Data-Mining approaches are the most used for the developing of bioinformatics tools. Generally, an ML algorithm may be able to identify morphologies by basing its analysis on a training-set of known patterns (supervised learning); alternatively, it could be able to analyze directly an input dataset in order to identify novel pattern using predictions not related to training-sets previously imported but acquired during the analysis (unsupervised learning). Furthermore, a pipeline based on patterns recognition is considered a valid approach for diagnosis and prognosis, as well as to perform studies using several medical imaging from heterogeneous sources. Assuming to conduct a study for the analysis of alterations in a specific brain’s region, a pattern recognition solution may be implemented; its pipeline could consist of three main steps: the first able to acquire raw data in a structured model, the second to select the features of interest and the third to perform an algorithm that allow the analysis. The final result will be represented by a set of data with a reduced dimensionality for the space (e.g., represented using the voxel) [10] that will therefore allow to discriminate quickly the patients from the healthy controls using a classifier based, for example, on a cross-validation approach.
In medical image processing, useful approaches are based on the Neural Network (NN). An NN is conceptually inspired by the human brain system and consists of: (i) an input layer, (ii) an output layer and (iii) one or more hidden layers; the number of layers is related to the level of abstraction, as well as to the reliability of the prediction (e.g., a deep neural network hierarchically extends to over 1000 layers). For instance, the NN can be used to extract ROIs [11] using data acquired from mammograms [12]. A powerful set of techniques for learning in NN is the Deep Learning (DL); it is a growing trend for data analysis and medical imaging, becoming one of the breakthrough technologies [13]. A Deep Neural Network performs all possible mappings, importing a dataset built in a previous training step, in order to formulate predictions for the unknown cases in input. Several algorithms based on machine learning are based on DL approaches [14], such as: Convolutional Neural Network (CNN), Deep Neural Network (DNN), Deep Belief Network (DBN), Deep Botlzmann Machine (DBM) and Recurrent Neural Network (RNN); the description and key points are shown in Table 1.
Type | Description |
---|---|
Convolutional Neural Network (CNN) | It is based on a neurobiological model that imports 2D inputs in order to produce a 3D output volume for the neuronal activity. Generally, it requires large dataset, as well as many layers. |
Deep Neural Network (DPN) | DPN is used in non-linear computations using hidden layers (≥2) for classification and regression. It is a solution typically used for many areas; its general-purpose approach is very slow not being optimized for a specific context. |
Deep Belief Network (DBN) | It uses undirected connections for top two layers in order to allow supervised and unsupervised training for the network. For the network initialization perform a layer-by-layer greedy learning; this approach is computationally expensive. |
Deep Botlzmann Machine (DBM) | It is based on undirected links among the layers using a stochastic maximum likelihood algorithm. Top-Down feedback are supported in order to perform a bust inference. |
Recurrent Neural Network (RNN) | It is a Neural Network used for stream data analysis when the output is related to previous computation; during the recursions all weight are shared for all layers. The key points are reported below:
|
Deep learning approaches: Key-points and description.
Assuming that we want to develop an algorithm to discriminate a specific area (e.g., representing a cancer) from an entire biomedical acquisition, an algorithm for handling of 3D volume and segmentation must be implemented. For instance, UNet [15], VNet and DeepMedic [16], and its improved version DMRes [17], are able to perform a fast and precise segmentation using a CNN architecture for fast and precise segmentation.
In addition, the study of medical sciences (e.g., neurosciences) has met a large quantitative of data and the bioinformatics tools and algorithms play a primary role in reference to knowledge extractions, these allow to perform data-integration techniques obtaining an interdisciplinary view matching heterogeneous sources with different models in order to extract information of interest. In [18] the authors develop BioMediator System to provide a data integration across several biomedical domains and data types in order to allow a biologist to retrieve molecular and genomic information using a browser engine based on head constraints and global path constraints. Assuming that we want to base an application on a mediation approach for a data integration in neurosciences, a first step is related to information retrieving, for instance, the Human Database (HID, http://nbirn.net/research/function/hid.shtm) and the eXtensible Neuroimaging Archive Toolkit (XNAT, http://www.xnat.org) can be used. Subsequently, a query engine for virtual data-integration can be developed. It could implement a OGSA-DAI/DQP architecture, respectively: Open Grid Services Architecture (OGSA) Distributed Access and Integration (DAI) and OGSA Distributed Query Processing (DQP); this solution offers a streaming dataflow workflow evaluation engine, and on a distributed query evaluation engine [19].
Bioinformatics allows a scientist to extract knowledge from a large set of information consisting of heterogeneous resources, as well as to handle the information of interest and more generally the methods for data storage and retrieval.
For instance, to acquire information of interest from a biomedical image often requires the development of a set of instructions in accordance to the research project; in this regard, a custom algorithm is able to extract knowledge from an input exactly as required by the scientist, and generally more efficiently than a generic commercial or free solution being designed on specific requirements identified in the case study.
Assuming that a researcher wants to implement a solution able to predict structure in accordance with a set of known patterns defined in a “training” phase, a machine-learning approach is perhaps the best choice.
Briefly, the possibilities are mainly two: (i) the implementation of an algorithm “from scratch” or (ii) the importing of existing toolkits (e.g., framework and libraries) within its own algorithm. A development “from scratch” is particularly expensive and time consuming compared to the use of libraries/framework “ready to use”. Therefore, it is important to evaluate the availability of existing toolkits before starting the development, as well as the efficiency of those chosen in accordance with the intended aim.
Supposing to use Python as programming-language, Scikit-Learn (http://scikit-learn.org/stable/
Alternatively, a useful solution to implement algorithms that use machine-learning techniques for data analysis could be Tensorflow (http://www.tensorflow.org). It is a popular library developed by Google Inc. to implement and execute large-scale artificial neural networks based on typed and multi-dimensional array (named Tensor); a Tensor is a generalization of arrays and matrices with higher size. Its approach is based on nodes defined during a training task, in each training iteration new links are established.
Furthermore, Tensorflow’s API allows the implementation of tools able to train and to test neural networks using computational graphs built in Python or C++. Assuming that a scientist wants to develop a machine-learning interface than the TensorFlow’s API is a good starting point, for instance, the DICOM support may be extended in order to implement a classifier for medical imaging that uses bioimage datasets as input for tensors [22]. Therefore, this solution could therefore represent a potential tool useful for diagnostic in the clinical practice. Assuming that we want to improve the accuracy of a disease diagnosis, a deep learning solution may be implemented. For instance, the input for the model could be represented by Alzheimer’s Disease Neuroimaging Initiative (ADNI) data acquired with Magnetic Resonance Imaging (MRI) or Positron Emission Tomography (PET) techniques. To evaluate the model a pre-processing step is performed in order to (i) correct the intensity inhomogeneity, (ii) normalize data into a template space, (iii) define maps for the gray matter tissue and (iv) improve the signal-to-noise ratio (e.g., using a Gaussian kernel). An interesting requirement could be represented by the possibility of capturing the highly nonlinear relationships between Input and Output; the Convolutional Neural Networks (CNNs) are a candidate solution for this aim (as previously defined:
More toolkits are available from several program languages and platforms in bioinformatics, and generally, these are based on Machine Learning (ML) solutions (or similar approaches). A standard which is able to produce a comparison among toolkits in ML is not defined, as each tool is often designed for determinate needs related to different problems, and its approach is therefore to be considered context-specific [24].
A list of useful toolkits is shown below and summarized in Table 2; only objective criteria (e.g., programming-language and features) are reported so that everyone may correlate a toolkit in reference to their needs.
ODTbrain is a Python library that implements a back-propagation algorithm for dense diffraction tomography in 3D [25]. The three-dimensional (3D) refractive index distribution of a unique cell allows to describe its inner structure in a marker-free manner. The term dense, full-view tomographic data set denotes a set of images of a cell acquired for multiple rotational positions, densely distributed from 0 to 360 degrees. The projection tomography, based on the inversion of the Radon transform, is generally used to perform the reconstruction and its quality is greatly improved when first order scattering is taken into account. This advanced reconstruction technique is called diffraction tomography. The first implementation of diffraction tomography has been proposed in ODTbrain. The algorithm is an extension to optical projection tomography that takes into account diffraction of light due to the refractive index of the sample. In ODTbrain the reconstruction process is divided into three main steps: filtering, reconstruction and object data construction. ODTbrain is able to reconstruct 3D refractive index maps from projections of biological or artificial phase objects; the algorithm is validated performing the analysis on a simulated dataset and subsequently authors have compared results with the reconstruction qualities of Optical Diffraction Tomography (ODT) and Optical Projection Tomography (OPT).
CP-CHARM [26] is a user-friendly image-based classification algorithm. It is inspired by WND-CHARM. The latter is a multi-purpose image classification algorithm that can be applied without optimization or modifying the starting data; features are computed on the whole image and no segmentation is required [27]. Using the CP-CHARM algorithm a user is able to extract several morphological features from an image without first being segmented; furthermore, in order to be suitable and accessible to all the biological research community, even with few expertise, CP-CHARM relies on CellProfiler an open source image analysis software for quantitative analysis of biological images [28]. The proposed method has been demonstrated to perform well on a wide range of bioimage classification problems. The proposed method has been validated firstly by showing that it could achieve performance similar to those of WND-CHARM. Then the algorithm has been used on several kinds of biological datasets, for example, data freely available from the Broad Bioimage Benchmark Collection (BBBC) [29] and tissue images from the Human Protein Atlas (HPA) [30]. CP-CHARM has been demonstrated to perform well on a wide range of bioimage classification problems.
SCIFIO is a flexible framework for SCientific Image Format Input and Output. In other words, it is a library for reading and writing N-dimensional image data. SCIFIO is an open source plugin for the SciJava framework that offers support for handling of scientific images. SCIFIO defines a common pattern for image format construction and can be easily extended—from custom formats to new metadata schema. It is developed by the ImageJ development team at the Laboratory for Optical and Computational Instrumentation (LOCI) at the University of Wisconsin-Madison. The Open Microscopy Environment’s Bio-Formats library provides the ability to convert many proprietary image formats to a common OME-TIFF format, using the OME-XML schema. This allows scientists to freely share image data without being restricted by proprietary format barriers. It is part of the SciJavasoftware stack and in use by several projects including ImageJ2, ImgLib2, and the Insight Toolkit (ITK). One of the main features of SCIFIO concerns the support of multiple domain-specific formats within a unified environment [31].
The Neuroscience Information Framework (NIF) is a framework that promotes the integrating access to Web-Based neuroscience resources [32]. It is supported from the Institutes and Centers forming the NIH Blueprint for Neuroscience Research. The framework is based on an Open Source design and offers dynamic and web-accessible resources focused on neuroscience that are described using an integrated terminology, also it is able to support concept-based queries as well as the integration of neuroscience information with complementary areas of biomedicine.
Web-based Hyperbolic Image Data Explorer (WHIDE) combines more features related to principles of machine learning and scientific-information in order to analyze the aspects (space and collocation) of Toponome Imaging System (TIS) images. WHIDE uses Hierarchical Hyperbolic SOM (H2SOM) clustering to resolve non-linear features and dynamic interactive manipulation of the colors, as well as to organize the clusters in a hierarchical structure. Authors tested the tool for TIS analysis but is not excluded that it is applicable to other MBI data [33].
Graph-based Active Learning of Agglomeration (GALA) is an algorithm, implemented in python language, for image segmentation. GALA belongs to a class of segmentation algorithms called agglomerative algorithms, in which segments are formed by merging smaller segments. It works by repeatedly consulting a gold standard segmentation (prepared by human annotators) as it agglomerates sub-segments according to its current best guess. More specifically, GALA accumulates a training dataset used to fit a classifier that guides the subsequent agglomeration decisions. GALA includes several scientific Python libraries: numpy, scipy and others, to perform segmentation analysis; also, it implements a solution based on machine-learning approach [34].
ACQ4 is a modular software for data acquisition and analysis in neurophysiology research. It is available for download at http://www.acq4.org. ACQ4 integrates the task of acquiring, managing and analyzing experimental data. It is developed as general-purpose tools with the main aim to combine traditional electrophysiology, photostimulation and imaging for experiments automation. The system is highly modular and therefore it is quite simple to add new functionalities.
Name | Language | Main methods |
---|---|---|
jicbioimage | Python | Microscopy data, view and explore data, generate reproducible analyses. |
Scikit-Learn | Python | Classification, regression, clustering, model selection, preprocessing. |
ODTbrain | Python | Back-propagation algorithm for dense diffraction tomography in 3D. |
CP-CHARM | Python | Image automated classification (optimization is not required). |
SCIFIO | Java | Handling of scientific images. |
NIF | (framework, web-based) | Queries support for NIF. |
WHIDE | (web-based) | H2SOM clustering, imaging analysis (space and collocation). |
GALA | Python | Data acquisition and analysis in neurophysiology. |
ACQ4 | Python | Experiments automation. |
Toolkits for medical imaging.
In [35] authors present several use-cases for ACQ4 to illustrate its functionalities reported as a set of experiments that are possible using this tool; below are briefly listed: (i) Multiphoton calcium imaging during whisker deflection; (ii) Laser scanning photostimulation; (iii) In vitro patch clamp with drug perfusion and (iv) In vivo recording during an operant conditioning task. ACQ4 uses free and open-source tools such as Python, NumPy/SciPy for numerical computation, PyQt for the user interface and PyQtGraph for scientific graphics. ACQ4.
jicbioimage is a tool implemented in python language for automated and reproducible bioimage analysis; jicbioimage has been used on over 15 internal projects at various stages of the publication pipeline [36]. Using jicbioimaget an user is able to (i) read bioimage data in several format, for this aim the features of Python-BioFormat are imported by authors; (ii) transform and segment images using methods based on numpy, scipy, and scikit-image and (iii) examine the versions for an experiment: briefly, the versions for an initial image are stored by jicbioimage during all transformations to help a scientist to understands the steps performed by the tool and its sub-processes.
eIMES 3D (standing for Evolution Imaging System 3D for Mobile) is a system that supports image reconstruction with dedicated features for the mobile environments [37, 38]. Using eIMES 3D, a cancer network data infrastructure can be defined and implemented in order to integrate information regarding rare and complex diseases. Furthermore, it provides a hardware infrastructure to connect multiple devices, as well as to create workstations (WorkSpaces) with independent and asynchronous features for information retrieving in order to acquire 3D images from a central database. Briefly, eIMES 3D allows:
full control and management of data and imaging by means of artificial intelligence algorithms;
advanced stereoscopic 3D visualization by using theWebGL innovative technology;
sharing of medical data;
distribution of 3D imaging on different output devices;
query the system through a search of the various case studies.
The AI algorithms allow to provide a new layer of information by applying set of rules fixed by international protocols, or by expert of the domain. These conceptually use known information and a set of production rules to derive new information or to change beliefs as a result of new knowledge. The logical formalization of AI algorithm is defined using a set of logical rules in order to extract new layers deriving knowledge (deductive process). Furthermore, the AI algorithms can apply an abductive process: using novel observation, that modifies the existing protocol, the information can be updated with the new specifications.
The fast growth of medical imaging may be seen monitoring the increase of available solutions and the interest in its research field, as well as in clinical practice. The increasing adoption in the clinical practice of the 3D solutions, due also to the evolution of technologies in medical imaging, such as the Computed Tomography and the Magnetic Resonance Imaging, produced a large amount of data. Knowledge extraction from medical images is still a complex task; this chapter recalls several images techniques and approaches used in bioinformatics, also describing some useful toolkits for the development of custom solutions.
Loose connective tissue disorders include lipedema, Dercum’s disease (DD), familial multiple lipomatosis (FML) and multiple symmetric lipomatosis (MSL). All these disorders share many similarities with lipedema including painful lipomas, obesity, fibrosis, a risk of developing lymphedema and difficulty in losing the abnormal fat through diet and exercise. There are clinical characteristics specific for lipedema, including the onset of the disease, fat location and associated health issues (\nTable 1\n) [1, 2].
\nCharacteristic | \nLipedema | \nDD | \nMSL | \nFML | \nMSL | \n
---|---|---|---|---|---|
Abnormal fat location | \nLegs, arms, abdomen | \nGlobal | \nUpper; can be global | \nArms, thighs, trunk, abdomen | \nUpper; can be global | \n
Diet-resistant fat | \nYes | \nYes | \nYes | \nYes | \nYes | \n
Lipomas | \nYes | \nCommon | \nCommon in men | \nCommon | \nCommon in men | \n
Time fat change | \nPuberty; 3rd decade | \nChild-adult | \nAdult; child rare | \nChild-adult | \nAdult; child rare | \n
Painful fat | \nYes | \nYes | \nNot usually | \nLipoma | \nNot usually | \n
Sex predominance | \nFemale | \nFemale | \nMale | \nMale = female | \nMale | \n
Lymphatic dysfunction | \nYes | \nYes | \nYes | \nYes | \nYes | \n
Prevalence | \nPossibly common | \nPossibly common | \nRare | \nRare | \nRare | \n
Associated conditions | \nLymphedema | \nAutoimmune; diabetes | \nNeuropathy | \nMoles; neuropathy | \nNeuropathy | \n
Inheritance pattern | \nAutosomal dominant; incomplete penetrance | \nAutosomal dominant; sex-specific influence | \nAutosomal dominant or recessive | \nAutosomal dominant | \nAutosomal dominant or recessive | \n
Lipedema is often misdiagnosed as lifestyle-induced obesity that affects ~10% of women of European descent as well as other populations [3, 4]. Although both disorders are considered inflammatory diseases due to the presence of increased macrophages and hypertrophic adipocytes, there are significant differences between the two disorders. Among these is the location of the fat, primarily abdominal or spread widely over the body in obesity compared to the symmetric distribution in the lower extremities in lipedema, the texture of the skin (thin and soft in lipedema and thicker in obesity), easy bruising and pain upon the introduction of pressure in lipedema [5, 6].
\nThe focus of this review will be on the disease of lipedema, different stages and types, diagnosis and treatment, pathogenesis and current research in the field.
\nLipedema also referred to as lipedema, is a painful loose connective tissue disorder first described in 1940 by Allen and Hines [7]. Lipedema is characterized by symmetric enlargement of the buttocks, hips and legs due to deposition of loose connective tissue that includes fascia, adipocytes, immune cells and other structures; arms are also affected in 80% of patients [3, 4]. Feet are typically spared, but ankle cuffs are often noted in advanced stages of lipedema where the risk of lymphedema is also high [8, 9]. Patients with lipedema experience mobility issues, psychosocial distress, anxiety, eating disorders, sleep apnea and depression [1, 10].
\nLipedema is considered a hormone-related disorder affecting almost exclusively women during puberty, childbirth or menopause. Case reports of men with lipedema have been described in literature. Men with lipedema have elevated estrogen level and low to absent testosterone levels resulting in cirrhosis, gynecomastia and hypogonadism [11, 12, 13]. While the exact etiopathogenesis of this disease is unknown [10, 14], many studies have demonstrated that inflammatory cells, hypertrophic adipocytes, abnormal blood vessels and lymphatic dysfunction are associated with tissue damage and development of a fibrotic disease [14, 15, 16, 17].
\nLipedema consists of three stages characterized by the texture of skin and tissue formation. Stage 1 involves smooth skin over pearl-sized nodules in a hypertrophic fat layer; Stage 2 has skin indentations over a hypertrophic fat structure of pearl-to-apple-size masses; and Stage 3 includes pearl-sized nodules and much larger fat masses causing lobules of skin and fat to form mainly on the hips, thighs, and around the knees. Lymphedema, causing fluid accumulation in the limbs, may develop during any stage of lipedema and is referred to as lipo-lymphedema [1, 3, 10, 18, 19].
\nHealthcare providers often misdiagnose women with lipedema as they do not take into account the disproportionate size of the legs compared to trunk especially in Stage 1 and 2 along with the inability to lose fat from areas affected by lipedema. It is possible to confuse women with Stage 3 lipedema as having lifestyle-induced obesity due to fat involving more areas of the body.
\nIn addition to stages of lipedema, lipedema is also characterized by types determined by the area of the body that is affected. There are five types of lipedema; types I, II, and III are the most common. In Type I, fat is deposited in the areas of the buttocks and hips resembling saddle bags. In Type II, fat extends to the knees from the buttocks area with the formation of folds of fat around the inside of the knee. In Type III, fat spreads all over the lower body from the hips to the ankles. In Type IV, upper arms are affected causing difficulty in lifting the arm and stress on the shoulder. In Type V, fat is restricted to the lower legs. It is worth noting that patients with lipedema can clinically present with a mixture of types [3, 10].
\nPain, tenderness, bruising easily, symmetrical swelling of the legs, heaviness of affected limbs, burning sensations in the skin and fat, soft skin, negative stemmer’s sign and hypermobile joints are among the common symptoms observed in lipedema patients [2, 3, 6, 13]. Hypermobility in women with has been reported to contribute to joint damage and increase the risk of cardiovascular disease as seen in Ehlers Danlos Syndrome-Hypermobility Type (EDS-HT) with Beighton score higher than 5 [2, 3, 20, 21]. Thus, hypermobility causes structural changes in lipedema tissue resulting in increased fibrosis, dysfunction of blood vessels and accumulation of interstitial fluid.
\nWomen with lipedema also experience emotional symptoms due to unexplained weight gain including embarrassment, anxiety and depression that impact their overall quality of life [22, 23]. Symptoms may progress in advanced stages of lipedema that might be associated with increased cardiovascular and renal diseases. A study conducted by Herbst el al. in 2015 provides a detailed list of symptoms experienced by lipedema patients [3].
\nDiagnosis of lipedema involves a comprehensive physical exam based on the criteria listed by Wold and colleagues in 1951, [4] medical and surgical history, list of medications that might affect weight or fluid retention and family history. A physical examination includes assessment of the enlarged lower extremities carefully noting the texture of the affected areas such as velvety soft skin that can be found in hypermobility, nodular fat, pain when applying pressure, tenderness upon palpation and accumulation of fluid such as pitting or non-pitting edema which may indicate lymphedema [18, 24]. Bruising caused by increased capillary fragility [6], spider veins and telangiectasia showing on the surface of the skin due to venous insufficiency are also observed in lipedema patients [4, 10].
\nAlthough, there is no cure for lipedema, treatments like liposuction (tumescent and water jet) [25], complete decongestive therapy that includes manual lymphatic drainage [26, 27], compression garments, a healthy diet, physical activity, medications and supplements (statins, selenium, diosmin, amphetamines and butcher’s broom) have been shown to reduce pain, improve lymphatic function, decrease leakage from blood vessels, lessen inflammation and fibrosis and maintain a healthy gut [24, 28, 29, 30, 31, 32, 33, 34].
\nLiposuction is by far the most effective treatment to decrease the fibrotic lipedema fat and thereby maintain mobility which is essential for the welfare of women living with lipedema [35, 36, 37]. Water jet-assisted liposuction has been proven to be as effective as tumescent liposuction. Damage to the lymph vessels has not been show as evidenced in a histological study conducted by Stutz et al. on lipoaspirates collected from lipedema patients [32]. Nevertheless, special care should be taken with lipo-lymphedema patients, where accumulated lymph and or fibrotic tissue should be removed first. Furthermore, follow-up and compression therapy are advised for successful and effective treatment.
\nDeep tissue massage has also been demonstrated to improve the quality of subcutaneous adipose tissue by decreasing pain, fibrosis and fat tissue in women with lipedema [29, 38].
\nAdditionally, a healthy non-inflammatory diet is highly recommended, even though it will not reduce the lipedema tissue, but it might slow the progression of the disease by reducing inflammation and pain, lessen the swelling and ultimately improve quality of life. No one plan works for everyone but a ketogenic diet with low processed carbohydrate and mild physical exercises like walking, swimming, Pilates, yoga and other home excise programs are suggested by lipedema specialists. These activates will help the function of lymphatic pump and maintain a normal metabolism.
\nFinally, it is very important to detect and treat lipedema at early stages thus preventing the complications that might occur due to the progression of disease. These complications comprise eating disorders, sleep apnea, diabetes mellitus, arthritis, hypertension, cellulitis, cardiac and renal disease.
\nThere are distinctive criteria for lipedema which are absent in lymphedema including a negative Stemmer’s sign, minimal pitting edema, thin skin, easy bruising, tenderness and pain [14, 39, 40]. Although lymphatic microaneurysms might develop in the later stages of lipedema leading to secondary lymphedema, imaging techniques like high-resolution cutaneous ultrasonography and magnetic resonance imaging showed no defects in the lymphatic system in early stages [24, 41, 42, 43]. Other methods have also been successfully used to differentiate lipedema from lymphedema which includes tissue dielectric constant and dual-energy X-ray absorptiometry techniques [44, 45, 46, 47, 48].
\nDysfunction of lymphatic vessels results in accumulation of interstitial fluid (edema) in adipose tissues triggering inflammation by the recruitment of macrophages resulting in fibrosis and difficulty with weight loss. As a consequence, adipose tissue loses its elasticity suggesting that lipedema might be a connective tissue disorder [15, 49]. Studies have also indicated that edema might induce growth of lipedema fat as well as hypoxia resulting in adipocyte cell death [50].
\nFurther, morphologic changes in lymphatic vessels and accumulation of interstitial fluid are present in some women with lipedema, with no change in transport of lymphatic fluid, which suggests these individuals might have a higher risk of progressing to lipo-lymphedema especially in advanced stages of lipedema [15, 51]. Accurate diagnosis of lipedema in association with lymphedema is essential for treating and following up of lipedema patients.
\nHormones, genetic factors, leaky blood vessels, dysfunctional lymphatics system, inflammation, hypertrophic adipocytes and interstitial thickening are among the factors that contribute to the pathogenesis of lipedema [10, 12, 15].
\nHormones play an essential role in the etiology of the lipedema, but how they affect the metabolism and function of adipocytes function is still unknown. Studies have shown that hormones, like estrogen and progesterone, have a direct effect on lipogenesis, insulin levels and adipose tissue distribution in the body. Dysregulation of hormonal levels lead to fat dysregulation, impairment of the lipogenesis-lipolysis mechanism, hypertension, insulin resistance and hyperinsulinemia [13, 52, 53]. Hormones might also have an impact on the nervous system which might explain the pain experienced by lipedema patients. Szél et al. hypothesized that alteration in estrogen (or estrogen receptors) maybe involved in the pathogenesis of lipedema by suggesting a link between accumulation of adipose tissue, imbalanced estrogen levels and inflammation of the peripheral and sympathetic nerves of the disease [13].
\nLipedema fat tissue is characterized by hypertrophic adipocytes, inflammatory immune cells, dilation of subdermal blood and lymphatic vessels. We and others have shown a high number of infiltrating macrophages in lipedema adipose tissue detected by the CD68 marker and observed as around blood vessels or as crown-like structures surrounding necrotic adipocytes. In addition to macrophages, mast cells and T-lymphocytes were detected in hyper-vascular areas mainly around blood vessels in lipedema fat tissue which might contribute to capillary permeability and accumulation of interstitial fluid [15, 16, 54].
\nAn article published in 2004 by Taylor et al. showed that accumulation of mast cells in lipedema tissue contributed to increased interstitial fluid, deterioration of adipocytes and potentially elastic fiber fragmentation due to the release of elastase [55], confirming that lipedema is a connective tissue disorder. Adding to that, direct cell-cell interaction between hypertrophic adipocyte and macrophages as well as secreted paracrine factors such as vascular endothelial growth factor (VEGF), a marker of angiogenesis, previously reported in the blood of women with lipedema [56] might be associated with increase in the number of blood vessels, dilation of capillaries, hypoxia, inflammation and tissue fibrosis found in lipedema patients [15, 18, 57].
\nAdipose tissue-derived stem cells are widely studied for their immunomodulatory, anti-inflammatory, anti-fibrotic, anti-apoptotic and pro-angiogenic effects [58, 59, 60], but how ASCs contribute to the development of lipedema has not been investigated yet. Due to their high therapeutic potential, ASCs are now considered an indispensable tool in regenerative medicine [61, 62, 63, 64]. Studies have shown the successful treatment with ASCs for many disease including graft-versus-host disease [65], wound healing [66], cardiovascular [67], inflammatory bowel disease [68], diabetes mellitus [69] and several injuries including kidney and spinal cord [70], bone and craniofacial reconstruction [71, 72], liver cirrhosis [73], multiple sclerosis [74]. In addition to their self-renewal ability, ASCs have the ability to differentiate into multiple lineages, including adipocytes, osteoblasts, chondrocytes, and endothelial cells [75, 76]. Thus, ASCs might play a role in lipedema adiposity by inducing the expansion and differentiation of progenitor adipose-derived stem/progenitor cells (pre-adipocytes) into mature adipocytes (hyperplasia). Suga el at. have shown an increase in proliferation of adipose-derived stem/progenitor cell proliferation using Ki67 and CD34 markers suggesting an increase in adipogenesis, hypoxia, and adipocyte necrosis, at least in one case [16].
\nAdding to that, inflammatory cytokines secreted by hypertrophic adipocytes and factors in the interstitial fluid could stimulate ASC differentiation into mature adipocytes. Alternatively, ASCs produce a plethora of pro- and anti-inflammatory cytokines that might contribute to angiogenesis and inflammation resulting in leaky and fragile blood vessels [77, 78]. Priglinger et al. have characterized lipedema ASCs isolated from liposuction samples and showed an increasing number of endothelial/pericytic cells using CD146 marker in lipedema patients compared to healthy individuals proposing that this increase might be a marker of repair of leaky blood and lymphatic vessels in lipedema tissues [54].
\nAlthough, ASCs might induce adipogenesis in lipedema an in-depth characterization of ASCs is required to confirm this theory. Otherwise, if ASCs prove to have anti-inflammatory, anti-fibrotic or pro-angiogenic effects, then they might be used to lessen tissue damage caused by leaky vessels; hence autologous treatment might be a promising tool for lipedema patients.
\nLipedema is a painful fat disease that should be differentiated from obesity and lymphedema. It is the responsibility of the healthcare provider to determine the accurate diagnosis of the disease for successful treatment and management. Liposuction, hands-on therapy, exercise, and a healthy eating plan are recommended for lipedema patients. Although the etiology of lipedema is complicated, hypertrophic adipocytes, inflammatory cytokines, and macrophages, hypoxia, leaky vessels and accumulation of interstitial fluid contribute to the pathogenesis of the disease and may also help guide treatment.
\nThis work was funded by a grant from the Lipedema Foundation.
\nThe authors declare no conflict of interest.
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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. 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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. 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Higher education institutions should expand the portfolio of their e-services, given that the demands of students are expected to increase in the future.",book:{id:"11914",title:"E-service Digital Innovation",coverURL:"https://cdn.intechopen.com/books/images_new/11914.jpg"},signatures:"Adam Malešević"},{id:"82995",title:"A Hybrid Genetic, Differential Evolution Optimization Algorithm",slug:"a-hybrid-genetic-differential-evolution-optimization-algorithm",totalDownloads:3,totalDimensionsCites:0,doi:"10.5772/intechopen.106204",abstract:"This chapter presents a heuristic evolutionary optimization algorithm that is loosely based on the principles of evolution and natural genetics. In particular, this chapter describes an evolutionary algorithm that is a hybrid of a genetic algorithm and a differential evolution algorithm. This algorithm uses an elitist, ranking, random selection method, several mutation methods and both two level and three level Taguchi crossover. 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Using Salsa20/12 stream cipher, the texture images can be encrypted using bit masking and permutation procedures and as part of a new scheme for encrypting 3D objects, which complements the existing methods for 3D object encryption. 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Our case study evaluates Activity Based Learning (ABL) by use of GBL as a tool to drive collaborative student learning. The activity described targets students’ ability to engage in hands-on practical collaborative learning, utilising existing skills in order to collectively share and reinforce knowledge. It relies on knowledge acquired from several subject topics thus consolidating applications through a studio-based activity in the form of a game bringing about its own benefits in teaching and learning. Widely used in a range of subjects, the application of GBL in Engineering and Technology and its effectiveness is less explored and reported as a learning tool in Engineering education. We present an approach to underpinning engineering education as part of a studio-based activity for Mechanical Engineering Design. We explore the options and potential for collaborative learning whilst offering students the opportunity to compete with peer teams for ranked positions on a leader board. We report on the level of student engagement and the extent to which learning outcomes were met through the introduction of such an activity.",book:{id:"11552",title:"Gamification - Analysis, Design and Development",coverURL:"https://cdn.intechopen.com/books/images_new/11552.jpg"},signatures:"Mike Mavromihales and Violeta Holmes"}],onlineFirstChaptersTotal:91},preDownload:{success:null,errors:{}},subscriptionForm:{success:null,errors:{}},aboutIntechopen:{},privacyPolicy:{},peerReviewing:{},howOpenAccessPublishingWithIntechopenWorks:{},sponsorshipBooks:{sponsorshipBooks:[],offset:8,limit:8,total:0},allSeries:{pteSeriesList:[{id:"14",title:"Artificial Intelligence",numberOfPublishedBooks:11,numberOfPublishedChapters:91,numberOfOpenTopics:6,numberOfUpcomingTopics:0,issn:"2633-1403",doi:"10.5772/intechopen.79920",isOpenForSubmission:!0},{id:"7",title:"Biomedical Engineering",numberOfPublishedBooks:12,numberOfPublishedChapters:108,numberOfOpenTopics:3,numberOfUpcomingTopics:0,issn:"2631-5343",doi:"10.5772/intechopen.71985",isOpenForSubmission:!0}],lsSeriesList:[{id:"11",title:"Biochemistry",numberOfPublishedBooks:33,numberOfPublishedChapters:333,numberOfOpenTopics:4,numberOfUpcomingTopics:0,issn:"2632-0983",doi:"10.5772/intechopen.72877",isOpenForSubmission:!0},{id:"25",title:"Environmental Sciences",numberOfPublishedBooks:1,numberOfPublishedChapters:19,numberOfOpenTopics:4,numberOfUpcomingTopics:0,issn:"2754-6713",doi:"10.5772/intechopen.100362",isOpenForSubmission:!0},{id:"10",title:"Physiology",numberOfPublishedBooks:14,numberOfPublishedChapters:145,numberOfOpenTopics:4,numberOfUpcomingTopics:0,issn:"2631-8261",doi:"10.5772/intechopen.72796",isOpenForSubmission:!0}],hsSeriesList:[{id:"3",title:"Dentistry",numberOfPublishedBooks:11,numberOfPublishedChapters:144,numberOfOpenTopics:2,numberOfUpcomingTopics:0,issn:"2631-6218",doi:"10.5772/intechopen.71199",isOpenForSubmission:!0},{id:"6",title:"Infectious Diseases",numberOfPublishedBooks:13,numberOfPublishedChapters:124,numberOfOpenTopics:4,numberOfUpcomingTopics:0,issn:"2631-6188",doi:"10.5772/intechopen.71852",isOpenForSubmission:!0},{id:"13",title:"Veterinary Medicine and Science",numberOfPublishedBooks:11,numberOfPublishedChapters:113,numberOfOpenTopics:3,numberOfUpcomingTopics:0,issn:"2632-0517",doi:"10.5772/intechopen.73681",isOpenForSubmission:!0}],sshSeriesList:[{id:"22",title:"Business, Management and Economics",numberOfPublishedBooks:1,numberOfPublishedChapters:23,numberOfOpenTopics:3,numberOfUpcomingTopics:0,issn:"2753-894X",doi:"10.5772/intechopen.100359",isOpenForSubmission:!0},{id:"23",title:"Education and Human Development",numberOfPublishedBooks:0,numberOfPublishedChapters:12,numberOfOpenTopics:1,numberOfUpcomingTopics:1,issn:null,doi:"10.5772/intechopen.100360",isOpenForSubmission:!0},{id:"24",title:"Sustainable Development",numberOfPublishedBooks:1,numberOfPublishedChapters:19,numberOfOpenTopics:5,numberOfUpcomingTopics:0,issn:"2753-6580",doi:"10.5772/intechopen.100361",isOpenForSubmission:!0}],testimonialsList:[{id:"13",text:"The collaboration with and support of the technical staff of IntechOpen is fantastic. 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He completed a one-year Post-Doctoral Fellowship awarded by the DFAIT (Foreign Affairs and International Trade Canada) at the Institute of Biomedical Engineering of the University of New Brunswick (Canada) in 2010. Currently, he is Professor in the Faculty of Electrical Engineering (UFU). He has authored and co-authored more than 200 peer-reviewed publications in Biomedical Engineering. He has been a researcher of The National Council for Scientific and Technological Development (CNPq-Brazil) since 2009. He has served as an ad-hoc consultant for CNPq, CAPES (Coordination for the Improvement of Higher Education Personnel), FINEP (Brazilian Innovation Agency), and other funding bodies on several occasions. He was the Secretary of the Brazilian Society of Biomedical Engineering (SBEB) from 2015 to 2016, President of SBEB (2017-2018) and Vice-President of SBEB (2019-2020). 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His fields of interest are anterior segment disease, keratoconus, glaucoma, corneal dystrophies, and cataracts. His research topics include\nintraocular lens power calculation, eye modification induced by refractive surgery, glaucoma progression, and validation of new diagnostic devices in ophthalmology. \nHe has published more than 100 papers in international and Italian scientific journals, more than 60 in journals with impact factors, and chapters in international and Italian books. He has also edited two international books and authored more than 150 communications or posters for the most important international and Italian ophthalmology conferences.",institutionString:'University of Campania "Luigi Vanvitelli"',institution:{name:'University of Campania "Luigi Vanvitelli"',institutionURL:null,country:{name:"Italy"}}}]},{type:"book",id:"7560",title:"Non-Invasive Diagnostic Methods",subtitle:"Image Processing",coverURL:"https://cdn.intechopen.com/books/images_new/7560.jpg",slug:"non-invasive-diagnostic-methods-image-processing",publishedDate:"December 19th 2018",editedByType:"Edited by",bookSignature:"Mariusz Marzec and Robert Koprowski",hash:"d92fd8cf5a90a47f2b8a310837a5600e",volumeInSeries:3,fullTitle:"Non-Invasive Diagnostic Methods - Image Processing",editors:[{id:"253468",title:"Dr.",name:"Mariusz",middleName:null,surname:"Marzec",slug:"mariusz-marzec",fullName:"Mariusz Marzec",profilePictureURL:"https://mts.intechopen.com/storage/users/253468/images/system/253468.png",biography:"An assistant professor at Department of Biomedical Computer Systems, at Institute of Computer Science, Silesian University in Katowice. Scientific interests: computer analysis and processing of images, biomedical images, databases and programming languages. 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Dr. Mohammadi received his BSc. and MSc. degrees in Mechanical Engineering from Sharif University of Technology, Tehran, Iran, and his PhD. degree in Biomedical Engineering (biomaterials) from the University of Western Ontario. He was a postdoctoral trainee for almost four years at University of Calgary and Harvard Medical School. He is an industry innovator having created the technology to produce lifelike synthetic platforms that can be used for the simulation of almost all cardiovascular reconstructive surgeries. He’s been heavily involved in the design and development of cardiovascular devices and technology for the past 10 years. 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He was elected a Yangtze River Scholars Distinguished Professor in 2013, a member of the International Statistical Institute (ISI) in 2016, a member of the board of the International Chinese Statistical Association (ICSA) in 2018, and a fellow of the Institute of Mathematical Statistics (IMS) in 2021. He received the ICSA Outstanding Service Award in 2018 and the National Science Foundation for Distinguished Young Scholars of China in 2012. He serves as a member of the editorial board of Statistics and Its Interface and Journal of Systems Science and Complexity. He is also a field editor for Communications in Mathematics and Statistics. His research interests include biostatistics, empirical likelihood, missing data analysis, variable selection, high-dimensional data analysis, Bayesian statistics, and data science. He has published more than 190 research papers and authored five books.",institutionString:"Yunnan University",institution:{name:"Yunnan University",country:{name:"China"}}},{id:"1177",title:"Prof.",name:"António",middleName:"J. R.",surname:"José Ribeiro Neves",slug:"antonio-jose-ribeiro-neves",fullName:"António José Ribeiro Neves",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/1177/images/system/1177.jpg",biography:"Prof. António J. R. Neves received a Ph.D. in Electrical Engineering from the University of Aveiro, Portugal, in 2007. Since 2002, he has been a researcher at the Institute of Electronics and Informatics Engineering of Aveiro. Since 2007, he has been an assistant professor in the Department of Electronics, Telecommunications, and Informatics, University of Aveiro. He is the director of the undergraduate course on Electrical and Computers Engineering and the vice-director of the master’s degree in Electronics and Telecommunications Engineering. He is an IEEE Senior Member and a member of several other research organizations worldwide. His main research interests are computer vision, intelligent systems, robotics, and image and video processing. He has participated in or coordinated several research projects and received more than thirty-five awards. He has 161 publications to his credit, including books, book chapters, journal articles, and conference papers. He has vast experience as a reviewer of several journals and conferences. As a professor, Dr. Neves has supervised several Ph.D. and master’s students and was involved in more than twenty-five different courses.",institutionString:null,institution:{name:"University of Aveiro",country:{name:"Portugal"}}},{id:"11317",title:"Dr.",name:"Francisco",middleName:null,surname:"Javier Gallegos-Funes",slug:"francisco-javier-gallegos-funes",fullName:"Francisco Javier Gallegos-Funes",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/11317/images/system/11317.png",biography:"Francisco J. Gallegos-Funes received his Ph.D. in Communications and Electronics from the Instituto Politécnico Nacional de México (National Polytechnic Institute of Mexico) in 2003. He is currently an associate professor in the Escuela Superior de Ingeniería Mecánica y Eléctrica (Mechanical and Electrical Engineering Higher School) at the same institute. His areas of scientific interest are signal and image processing, filtering, steganography, segmentation, pattern recognition, biomedical signal processing, sensors, and real-time applications.",institutionString:"Instituto Politécnico Nacional",institution:{name:"Instituto Politécnico Nacional",country:{name:"Mexico"}}},{id:"428449",title:"Dr.",name:"Ronaldo",middleName:null,surname:"Ferreira",slug:"ronaldo-ferreira",fullName:"Ronaldo Ferreira",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/428449/images/21449_n.png",biography:null,institutionString:null,institution:{name:"University of Aveiro",country:{name:"Portugal"}}},{id:"165328",title:"Dr.",name:"Vahid",middleName:null,surname:"Asadpour",slug:"vahid-asadpour",fullName:"Vahid Asadpour",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/165328/images/system/165328.jpg",biography:"Vahid Asadpour, MS, Ph.D., is currently with the Department of Research and Evaluation, Kaiser Permanente Southern California. He has both an MS and Ph.D. in Biomedical Engineering. He was previously a research scientist at the University of California Los Angeles (UCLA) and visiting professor and researcher at the University of North Dakota. He is currently working in artificial intelligence and its applications in medical signal processing. In addition, he is using digital signal processing in medical imaging and speech processing. Dr. Asadpour has developed brain-computer interfacing algorithms and has published books, book chapters, and several journal and conference papers in this field and other areas of intelligent signal processing. He has also designed medical devices, including a laser Doppler monitoring system.",institutionString:"Kaiser Permanente Southern California",institution:null},{id:"169608",title:"Prof.",name:"Marian",middleName:null,surname:"Găiceanu",slug:"marian-gaiceanu",fullName:"Marian Găiceanu",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/169608/images/system/169608.png",biography:"Prof. Dr. Marian Gaiceanu graduated from the Naval and Electrical Engineering Faculty, Dunarea de Jos University of Galati, Romania, in 1997. He received a Ph.D. (Magna Cum Laude) in Electrical Engineering in 2002. Since 2017, Dr. Gaiceanu has been a Ph.D. supervisor for students in Electrical Engineering. He has been employed at Dunarea de Jos University of Galati since 1996, where he is currently a professor. Dr. Gaiceanu is a member of the National Council for Attesting Titles, Diplomas and Certificates, an expert of the Executive Agency for Higher Education, Research Funding, and a member of the Senate of the Dunarea de Jos University of Galati. He has been the head of the Integrated Energy Conversion Systems and Advanced Control of Complex Processes Research Center, Romania, since 2016. He has conducted several projects in power converter systems for electrical drives, power quality, PEM and SOFC fuel cell power converters for utilities, electric vehicles, and marine applications with the Department of Regulation and Control, SIEI S.pA. (2002–2004) and the Polytechnic University of Turin, Italy (2002–2004, 2006–2007). He is a member of the Institute of Electrical and Electronics Engineers (IEEE) and cofounder-member of the IEEE Power Electronics Romanian Chapter. He is a guest editor at Energies and an academic book editor for IntechOpen. He is also a member of the editorial boards of the Journal of Electrical Engineering, Electronics, Control and Computer Science and Sustainability. Dr. Gaiceanu has been General Chairman of the IEEE International Symposium on Electrical and Electronics Engineering in the last six editions.",institutionString:'"Dunarea de Jos" University of Galati',institution:{name:'"Dunarea de Jos" University of Galati',country:{name:"Romania"}}},{id:"4519",title:"Prof.",name:"Jaydip",middleName:null,surname:"Sen",slug:"jaydip-sen",fullName:"Jaydip Sen",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/4519/images/system/4519.jpeg",biography:"Jaydip Sen is associated with Praxis Business School, Kolkata, India, as a professor in the Department of Data Science. His research areas include security and privacy issues in computing and communication, intrusion detection systems, machine learning, deep learning, and artificial intelligence in the financial domain. He has more than 200 publications in reputed international journals, refereed conference proceedings, and 20 book chapters in books published by internationally renowned publishing houses, such as Springer, CRC press, IGI Global, etc. Currently, he is serving on the editorial board of the prestigious journal Frontiers in Communications and Networks and in the technical program committees of a number of high-ranked international conferences organized by the IEEE, USA, and the ACM, USA. He has been listed among the top 2% of scientists in the world for the last three consecutive years, 2019 to 2021 as per studies conducted by the Stanford University, USA.",institutionString:"Praxis Business School",institution:null},{id:"320071",title:"Dr.",name:"Sidra",middleName:null,surname:"Mehtab",slug:"sidra-mehtab",fullName:"Sidra Mehtab",position:null,profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0033Y00002v6KHoQAM/Profile_Picture_1584512086360",biography:"Sidra Mehtab has completed her BS with honors in Physics from Calcutta University, India in 2018. She has done MS in Data Science and Analytics from Maulana Abul Kalam Azad University of Technology (MAKAUT), Kolkata, India in 2020. Her research areas include Econometrics, Time Series Analysis, Machine Learning, Deep Learning, Artificial Intelligence, and Computer and Network Security with a particular focus on Cyber Security Analytics. Ms. Mehtab has published seven papers in international conferences and one of her papers has been accepted for publication in a reputable international journal. She has won the best paper awards in two prestigious international conferences – BAICONF 2019, and ICADCML 2021, organized in the Indian Institute of Management, Bangalore, India in December 2019, and SOA University, Bhubaneswar, India in January 2021. Besides, Ms. Mehtab has also published two book chapters in two books. Seven of her book chapters will be published in a volume shortly in 2021 by Cambridge Scholars’ Press, UK. Currently, she is working as the joint editor of two edited volumes on Time Series Analysis and Forecasting to be published in the first half of 2021 by an international house. Currently, she is working as a Data Scientist with an MNC in Delhi, India.",institutionString:"NSHM College of Management and Technology",institution:{name:"Association for Computing Machinery",country:{name:"United States of America"}}},{id:"226240",title:"Dr.",name:"Andri Irfan",middleName:null,surname:"Rifai",slug:"andri-irfan-rifai",fullName:"Andri Irfan Rifai",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/226240/images/7412_n.jpg",biography:"Andri IRFAN is a Senior Lecturer of Civil Engineering and Planning. He completed the PhD at the Universitas Indonesia & Universidade do Minho with Sandwich Program Scholarship from the Directorate General of Higher Education and LPDP scholarship. He has been teaching for more than 19 years and much active to applied his knowledge in the project construction in Indonesia. His research interest ranges from pavement management system to advanced data mining techniques for transportation engineering. He has published more than 50 papers in journals and 2 books.",institutionString:null,institution:{name:"Universitas Internasional Batam",country:{name:"Indonesia"}}},{id:"314576",title:"Dr.",name:"Ibai",middleName:null,surname:"Laña",slug:"ibai-lana",fullName:"Ibai Laña",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/314576/images/system/314576.jpg",biography:"Dr. Ibai Laña works at TECNALIA as a data analyst. He received his Ph.D. in Artificial Intelligence from the University of the Basque Country (UPV/EHU), Spain, in 2018. He is currently a senior researcher at TECNALIA. His research interests fall within the intersection of intelligent transportation systems, machine learning, traffic data analysis, and data science. He has dealt with urban traffic forecasting problems, applying machine learning models and evolutionary algorithms. He has experience in origin-destination matrix estimation or point of interest and trajectory detection. Working with large volumes of data has given him a good command of big data processing tools and NoSQL databases. He has also been a visiting scholar at the Knowledge Engineering and Discovery Research Institute, Auckland University of Technology.",institutionString:"TECNALIA Research & Innovation",institution:{name:"Tecnalia",country:{name:"Spain"}}},{id:"314575",title:"Dr.",name:"Jesus",middleName:null,surname:"L. Lobo",slug:"jesus-l.-lobo",fullName:"Jesus L. Lobo",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/314575/images/system/314575.png",biography:"Dr. Jesús López is currently based in Bilbao (Spain) working at TECNALIA as Artificial Intelligence Research Scientist. In most cases, a project idea or a new research line needs to be investigated to see if it is good enough to take into production or to focus on it. That is exactly what he does, diving into Machine Learning algorithms and technologies to help TECNALIA to decide whether something is great in theory or will actually impact on the product or processes of its projects. So, he is expert at framing experiments, developing hypotheses, and proving whether they’re true or not, in order to investigate fundamental problems with a longer time horizon. He is also able to design and develop PoCs and system prototypes in simulation. He has participated in several national and internacional R&D projects.\n\nAs another relevant part of his everyday research work, he usually publishes his findings in reputed scientific refereed journals and international conferences, occasionally acting as reviewer and Programme Commitee member. Concretely, since 2018 he has published 9 JCR (8 Q1) journal papers, 9 conference papers (e.g. ECML PKDD 2021), and he has co-edited a book. He is also active in popular science writing data science stories for reputed blogs (KDNuggets, TowardsDataScience, Naukas). Besides, he has recently embarked on mentoring programmes as mentor, and has also worked as data science trainer.",institutionString:"TECNALIA Research & Innovation",institution:{name:"Tecnalia",country:{name:"Spain"}}},{id:"103779",title:"Prof.",name:"Yalcin",middleName:null,surname:"Isler",slug:"yalcin-isler",fullName:"Yalcin Isler",position:null,profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRyQ8QAK/Profile_Picture_1628834958734",biography:"Yalcin Isler (1971 - Burdur / Turkey) received the B.Sc. degree in the Department of Electrical and Electronics Engineering from Anadolu University, Eskisehir, Turkey, in 1993, the M.Sc. degree from the Department of Electronics and Communication Engineering, Suleyman Demirel University, Isparta, Turkey, in 1996, the Ph.D. degree from the Department of Electrical and Electronics Engineering, Dokuz Eylul University, Izmir, Turkey, in 2009, and the Competence of Associate Professorship from the Turkish Interuniversity Council in 2019.\n\nHe was Lecturer at Burdur Vocational School in Suleyman Demirel University (1993-2000, Burdur / Turkey), Software Engineer (2000-2002, Izmir / Turkey), Research Assistant in Bulent Ecevit University (2002-2003, Zonguldak / Turkey), Research Assistant in Dokuz Eylul University (2003-2010, Izmir / Turkey), Assistant Professor at the Department of Electrical and Electronics Engineering in Bulent Ecevit University (2010-2012, Zonguldak / Turkey), Assistant Professor at the Department of Biomedical Engineering in Izmir Katip Celebi University (2012-2019, Izmir / Turkey). He is an Associate Professor at the Department of Biomedical Engineering at Izmir Katip Celebi University, Izmir / Turkey, since 2019. In addition to academics, he has also founded Islerya Medical and Information Technologies Company, Izmir / Turkey, since 2017.\n\nHis main research interests cover biomedical signal processing, pattern recognition, medical device design, programming, and embedded systems. He has many scientific papers and participated in several projects in these study fields. He was an IEEE Student Member (2009-2011) and IEEE Member (2011-2014) and has been IEEE Senior Member since 2014.",institutionString:null,institution:{name:"Izmir Kâtip Çelebi University",country:{name:"Turkey"}}},{id:"339677",title:"Dr.",name:"Mrinmoy",middleName:null,surname:"Roy",slug:"mrinmoy-roy",fullName:"Mrinmoy Roy",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/339677/images/16768_n.jpg",biography:"An accomplished Sales & Marketing professional with 12 years of cross-functional experience in well-known organisations such as CIPLA, LUPIN, GLENMARK, ASTRAZENECA across different segment of Sales & Marketing, International Business, Institutional Business, Product Management, Strategic Marketing of HIV, Oncology, Derma, Respiratory, Anti-Diabetic, Nutraceutical & Stomatological Product Portfolio and Generic as well as Chronic Critical Care Portfolio. A First Class MBA in International Business & Strategic Marketing, B.Pharm, D.Pharm, Google Certified Digital Marketing Professional. Qualified PhD Candidate in Operations and Management with special focus on Artificial Intelligence and Machine Learning adoption, analysis and use in Healthcare, Hospital & Pharma Domain. Seasoned with diverse therapy area of Pharmaceutical Sales & Marketing ranging from generating revenue through generating prescriptions, launching new products, and making them big brands with continuous strategy execution at the Physician and Patients level. Moved from Sales to Marketing and Business Development for 3.5 years in South East Asian Market operating from Manila, Philippines. Came back to India and handled and developed Brands such as Gluconorm, Lupisulin, Supracal, Absolut Woman, Hemozink, Fabiflu (For COVID 19), and many more. In my previous assignment I used to develop and execute strategies on Sales & Marketing, Commercialization & Business Development for Institution and Corporate Hospital Business portfolio of Oncology Therapy Area for AstraZeneca Pharma India Ltd. Being a Research Scholar and Student of ‘Operations Research & Management: Artificial Intelligence’ I published several pioneer research papers and book chapters on the same in Internationally reputed journals and Books indexed in Scopus, Springer and Ei Compendex, Google Scholar etc. Currently, I am launching PGDM Pharmaceutical Management Program in IIHMR Bangalore and spearheading the course curriculum and structure of the same. I am interested in Collaboration for Healthcare Innovation, Pharma AI Innovation, Future trend in Marketing and Management with incubation on Healthcare, Healthcare IT startups, AI-ML Modelling and Healthcare Algorithm based training module development. I am also an affiliated member of the Institute of Management Consultant of India, looking forward to Healthcare, Healthcare IT and Innovation, Pharma and Hospital Management Consulting works.",institutionString:null,institution:{name:"Lovely Professional University",country:{name:"India"}}},{id:"1063",title:"Prof.",name:"Constantin",middleName:null,surname:"Volosencu",slug:"constantin-volosencu",fullName:"Constantin Volosencu",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/1063/images/system/1063.png",biography:"Prof. Dr. Constantin Voloşencu graduated as an engineer from\nPolitehnica University of Timișoara, Romania, where he also\nobtained a doctorate degree. He is currently a full professor in\nthe Department of Automation and Applied Informatics at the\nsame university. Dr. Voloşencu is the author of ten books, seven\nbook chapters, and more than 160 papers published in journals\nand conference proceedings. He has also edited twelve books and\nhas twenty-seven patents to his name. He is a manager of research grants, editor in\nchief and member of international journal editorial boards, a former plenary speaker, a member of scientific committees, and chair at international conferences. His\nresearch is in the fields of control systems, control of electric drives, fuzzy control\nsystems, neural network applications, fault detection and diagnosis, sensor network\napplications, monitoring of distributed parameter systems, and power ultrasound\napplications. He has developed automation equipment for machine tools, spooling\nmachines, high-power ultrasound processes, and more.",institutionString:'"Politechnica" University Timişoara',institution:null},{id:"221364",title:"Dr.",name:"Eneko",middleName:null,surname:"Osaba",slug:"eneko-osaba",fullName:"Eneko Osaba",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/221364/images/system/221364.jpg",biography:"Dr. Eneko Osaba works at TECNALIA as a senior researcher. He obtained his Ph.D. in Artificial Intelligence in 2015. He has participated in more than twenty-five local and European research projects, and in the publication of more than 130 papers. He has performed several stays at universities in the United Kingdom, Italy, and Malta. Dr. Osaba has served as a program committee member in more than forty international conferences and participated in organizing activities in more than ten international conferences. He is a member of the editorial board of the International Journal of Artificial Intelligence, Data in Brief, and Journal of Advanced Transportation. He is also a guest editor for the Journal of Computational Science, Neurocomputing, Swarm, and Evolutionary Computation and IEEE ITS Magazine.",institutionString:"TECNALIA Research & Innovation",institution:{name:"Tecnalia",country:{name:"Spain"}}},{id:"275829",title:"Dr.",name:"Esther",middleName:null,surname:"Villar-Rodriguez",slug:"esther-villar-rodriguez",fullName:"Esther Villar-Rodriguez",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/275829/images/system/275829.jpg",biography:"Dr. Esther Villar obtained a Ph.D. in Information and Communication Technologies from the University of Alcalá, Spain, in 2015. She obtained a degree in Computer Science from the University of Deusto, Spain, in 2010, and an MSc in Computer Languages and Systems from the National University of Distance Education, Spain, in 2012. Her areas of interest and knowledge include natural language processing (NLP), detection of impersonation in social networks, semantic web, and machine learning. Dr. Esther Villar made several contributions at conferences and publishing in various journals in those fields. 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He is currently a principal researcher in data analytics and optimisation at TECNALIA (Spain), a visiting fellow at the Basque Center for Applied Mathematics (BCAM) and a part-time lecturer at the University of the Basque Country (UPV/EHU). His research interests gravitate on the use of descriptive, prescriptive and predictive algorithms for data mining and optimization in a diverse range of application fields such as Energy, Transport, Telecommunications, Health and Industry, among others. In these fields he has published more than 240 articles, co-supervised 8 Ph.D. theses, edited 6 books, coauthored 7 patents and participated/led more than 40 research projects. He is a Senior Member of the IEEE, and a recipient of the Biscay Talent prize for his academic career.",institutionString:"Tecnalia Research & Innovation",institution:{name:"Tecnalia",country:{name:"Spain"}}},{id:"278948",title:"Dr.",name:"Carlos Pedro",middleName:null,surname:"Gonçalves",slug:"carlos-pedro-goncalves",fullName:"Carlos Pedro Gonçalves",position:null,profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRcmyQAC/Profile_Picture_1564224512145",biography:'Carlos Pedro Gonçalves (PhD) is an Associate Professor at Lusophone University of Humanities and Technologies and a researcher on Complexity Sciences, Quantum Technologies, Artificial Intelligence, Strategic Studies, Studies in Intelligence and Security, FinTech and Financial Risk Modeling. 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Currently working as an Assistant Professor in the Department of Mathematics, Institute of Applied Science, Mangalayatan University, Aligarh. She taught so many courses of Mathematics of UG and PG level. Her research Area of Expertise is Functional Analysis & Sequence Spaces. She has been working on Ideal Convergence of double sequence. She has published 17 research papers in National and International Journals including Cogent Mathematics, Filomat, Journal of Intelligent and Fuzzy Systems, Advances in Difference Equations, Journal of Mathematical Analysis, Journal of Mathematical & Computer Science etc. She has also reviewed few research papers for the and international journals. 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Ongoing issues, recent advances, and future diagnostic approaches and therapeutic strategies will also be discussed. This book series will focus on various aspects and properties of infectious diseases whose deep understanding is essential for safeguarding the human race from losing resources and economies due to pathogens.",coverUrl:"https://cdn.intechopen.com/series/covers/6.jpg",latestPublicationDate:"August 16th, 2022",hasOnlineFirst:!0,numberOfOpenTopics:4,numberOfPublishedChapters:124,numberOfPublishedBooks:13,editor:{id:"131400",title:"Prof.",name:"Alfonso J.",middleName:null,surname:"Rodriguez-Morales",fullName:"Alfonso J. Rodriguez-Morales",profilePictureURL:"https://mts.intechopen.com/storage/users/131400/images/system/131400.png",biography:"Dr. Rodriguez-Morales is an expert in tropical and emerging diseases, particularly zoonotic and vector-borne diseases (especially arboviral diseases). He is the president of the Travel Medicine Committee of the Pan-American Infectious Diseases Association (API), as well as the president of the Colombian Association of Infectious Diseases (ACIN). He is a member of the Committee on Tropical Medicine, Zoonoses, and Travel Medicine of ACIN. He is a vice-president of the Latin American Society for Travel Medicine (SLAMVI) and a Member of the Council of the International Society for Infectious Diseases (ISID). Since 2014, he has been recognized as a Senior Researcher, at the Ministry of Science of Colombia. He is a professor at the Faculty of Medicine of the Fundacion Universitaria Autonoma de las Americas, in Pereira, Risaralda, Colombia. He is an External Professor, Master in Research on Tropical Medicine and International Health, Universitat de Barcelona, Spain. He is also a professor at the Master in Clinical Epidemiology and Biostatistics, Universidad Científica del Sur, Lima, Peru. In 2021 he has been awarded the “Raul Isturiz Award” Medal of the API. Also, in 2021, he was awarded with the “Jose Felix Patiño” Asclepius Staff Medal of the Colombian Medical College, due to his scientific contributions to COVID-19 during the pandemic. He is currently the Editor in Chief of the journal Travel Medicine and Infectious Diseases. His Scopus H index is 47 (Google Scholar H index, 68).",institutionString:"Institución Universitaria Visión de las Américas, Colombia",institution:null},subseries:[{id:"3",title:"Bacterial Infectious Diseases",keywords:"Antibiotics, Biofilm, Antibiotic Resistance, Host-microbiota Relationship, Treatment, Diagnostic Tools",scope:"