Equivalent circuit and corrosion parameters for AZ91D alloy in various concentrations of ethylene glycol solution after 2 h immersion
\\n\\n
Released this past November, the list is based on data collected from the Web of Science and highlights some of the world’s most influential scientific minds by naming the researchers whose publications over the previous decade have included a high number of Highly Cited Papers placing them among the top 1% most-cited.
\\n\\nWe wish to congratulate all of the researchers named and especially our authors on this amazing accomplishment! We are happy and proud to share in their success!
Note: Edited in March 2021
\\n"}]',published:!0,mainMedia:{caption:"Highly Cited",originalUrl:"/media/original/117"}},components:[{type:"htmlEditorComponent",content:'IntechOpen is proud to announce that 191 of our authors have made the Clarivate™ Highly Cited Researchers List for 2020, ranking them among the top 1% most-cited.
\n\nThroughout the years, the list has named a total of 261 IntechOpen authors as Highly Cited. Of those researchers, 69 have been featured on the list multiple times.
\n\n\n\nReleased this past November, the list is based on data collected from the Web of Science and highlights some of the world’s most influential scientific minds by naming the researchers whose publications over the previous decade have included a high number of Highly Cited Papers placing them among the top 1% most-cited.
\n\nWe wish to congratulate all of the researchers named and especially our authors on this amazing accomplishment! We are happy and proud to share in their success!
Note: Edited in March 2021
\n'}],latestNews:[{slug:"webinar-introduction-to-open-science-wednesday-18-may-1-pm-cest-20220518",title:"Webinar: Introduction to Open Science | Wednesday 18 May, 1 PM CEST"},{slug:"step-in-the-right-direction-intechopen-launches-a-portfolio-of-open-science-journals-20220414",title:"Step in the Right Direction: IntechOpen Launches a Portfolio of Open Science Journals"},{slug:"let-s-meet-at-london-book-fair-5-7-april-2022-olympia-london-20220321",title:"Let’s meet at London Book Fair, 5-7 April 2022, Olympia London"},{slug:"50-books-published-as-part-of-intechopen-and-knowledge-unlatched-ku-collaboration-20220316",title:"50 Books published as part of IntechOpen and Knowledge Unlatched (KU) Collaboration"},{slug:"intechopen-joins-the-united-nations-sustainable-development-goals-publishers-compact-20221702",title:"IntechOpen joins the United Nations Sustainable Development Goals Publishers Compact"},{slug:"intechopen-signs-exclusive-representation-agreement-with-lsr-libros-servicios-y-representaciones-s-a-de-c-v-20211123",title:"IntechOpen Signs Exclusive Representation Agreement with LSR Libros Servicios y Representaciones S.A. de C.V"},{slug:"intechopen-expands-partnership-with-research4life-20211110",title:"IntechOpen Expands Partnership with Research4Life"},{slug:"introducing-intechopen-book-series-a-new-publishing-format-for-oa-books-20210915",title:"Introducing IntechOpen Book Series - A New Publishing Format for OA Books"}]},book:{item:{type:"book",id:"10423",leadTitle:null,fullTitle:"The Wonders of Diptera - Characteristics, Diversity, and Significance for the World's Ecosystems",title:"The Wonders of Diptera",subtitle:"Characteristics, Diversity, and Significance for the World's Ecosystems",reviewType:"peer-reviewed",abstract:"This book provides comprehensive and concise knowledge about Diptera, an order of insects that has both useful and harmful aspects for humans, animals, plants, and the environment. Insects of this order act as agricultural pests as well as vectors of diseases and carriers of microorganisms. Chapters cover such topics as characteristics of different types of Dipteran insects including fruit flies, mosquitos, and midges, and strategies to control insect populations to combat the spread of human and animal diseases such as dengue, trypanosomosis, and others.",isbn:"978-1-83968-883-6",printIsbn:"978-1-83968-882-9",pdfIsbn:"978-1-83968-884-3",doi:"10.5772/intechopen.91609",price:119,priceEur:129,priceUsd:155,slug:"the-wonders-of-diptera-characteristics-diversity-and-significance-for-the-world-s-ecosystems",numberOfPages:188,isOpenForSubmission:!1,isInWos:null,isInBkci:!1,hash:"2746b4288e78c8688d1be1bd9d99a127",bookSignature:"Farzana Khan Perveen",publishedDate:"September 8th 2021",coverURL:"https://cdn.intechopen.com/books/images_new/10423.jpg",numberOfDownloads:2505,numberOfWosCitations:0,numberOfCrossrefCitations:0,numberOfCrossrefCitationsByBook:0,numberOfDimensionsCitations:0,numberOfDimensionsCitationsByBook:0,hasAltmetrics:0,numberOfTotalCitations:0,isAvailableForWebshopOrdering:!0,dateEndFirstStepPublish:"September 18th 2020",dateEndSecondStepPublish:"October 16th 2020",dateEndThirdStepPublish:"December 15th 2020",dateEndFourthStepPublish:"March 5th 2021",dateEndFifthStepPublish:"May 4th 2021",currentStepOfPublishingProcess:5,indexedIn:"1,2,3,4,5,6",editedByType:"Edited by",kuFlag:!1,featuredMarkup:null,editors:[{id:"75563",title:"Dr.",name:"Farzana Khan",middleName:null,surname:"Perveen",slug:"farzana-khan-perveen",fullName:"Farzana Khan Perveen",profilePictureURL:"https://mts.intechopen.com/storage/users/75563/images/system/75563.jpg",biography:"Dr. Farzana Khan Perveen (FLS; Gold Medalist) obtained her BSc (Hons) and MSc in Entomology from the University of Karachi, Pakistan, and MAS (Monbusho Scholarship) in Agronomy from Nagoya University, Japan, and a Ph.D. in Toxicology from the University of Karachi. She is the founder of the Department of Zoology and former controller of examinations at Shaheed Benazir Bhutto University, Hazara University, and Kohat University of Science and Technology. She is the author of 150 high-impact research papers, 135 abstracts, 40 authored books, 9 chapters, and 9 edited books. She is also a student supervisor. Her fields of interest are entomology, toxicology, forensic entomology.",institutionString:"Classes et Events in Sciences (C.E.S.)",position:null,outsideEditionCount:0,totalCites:0,totalAuthoredChapters:"6",totalChapterViews:"0",totalEditedBooks:"7",institution:null}],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:"78012",title:"Introductory Chapter: Diptera",doi:"10.5772/intechopen.99440",slug:"introductory-chapter-diptera",totalDownloads:179,totalCrossrefCites:0,totalDimensionsCites:0,hasAltmetrics:0,abstract:null,signatures:"Farzana Perveen and Anzela Khan",downloadPdfUrl:"/chapter/pdf-download/78012",previewPdfUrl:"/chapter/pdf-preview/78012",authors:[{id:"75563",title:"Dr.",name:"Farzana Khan",surname:"Perveen",slug:"farzana-khan-perveen",fullName:"Farzana Khan Perveen"},{id:"383356",title:"Dr.",name:"Anzela",surname:"Khan",slug:"anzela-khan",fullName:"Anzela Khan"}],corrections:null},{id:"75438",title:"Characteristics of Dipteran Insects",doi:"10.5772/intechopen.96448",slug:"characteristics-of-dipteran-insects",totalDownloads:486,totalCrossrefCites:0,totalDimensionsCites:0,hasAltmetrics:0,abstract:"Diptera means two wings (Di: two, pteron: wing). They have complete metamorphosis and they are holometabolous insects which means there are 4 stages (egg, larvae, pupae and adult). The name of larval stage is “maggot”. Some of the dipteran insects cause damage in agricultural production. Some are harmful for humans. Dipteran insects have two wings. Hind wings are reduced and they are called “halteres”. Function of halteres is balancing when the insects fly. Except mosquitoes, dipteran insects have sponging-sucking mouthparts. Important examples for dipteran insects are Olive fruit fly and Medfly which cause damages in agricultural production. OFF is the most destructive pest in olive growing areas and Mediterranean fruit fly cause damages in fruit production.",signatures:"Murat Helvacı",downloadPdfUrl:"/chapter/pdf-download/75438",previewPdfUrl:"/chapter/pdf-preview/75438",authors:[{id:"301984",title:"Ph.D.",name:"Murat",surname:"Helvaci",slug:"murat-helvaci",fullName:"Murat Helvaci"}],corrections:null},{id:"75974",title:"Fruit Flies (Drosophila spp.) Collection, Handling, and Maintenance: Field to Laboratory",doi:"10.5772/intechopen.97014",slug:"fruit-flies-em-drosophila-spp-em-collection-handling-and-maintenance-field-to-laboratory",totalDownloads:373,totalCrossrefCites:0,totalDimensionsCites:0,hasAltmetrics:0,abstract:"As drosophilids are versatile, low maintenance and non-harming model organisms, they can be easily used in all fields of life sciences like Genetics, Biotechnology, Cancer biology, Genomics, Reproductive biology, Developmental biology, Micro chemical studies, ecology and much more. For using such a model organism, we need to learn capturing, rearing and culturing their progeny along with basic identification and differentiation between males and females. This chapter is being emphasized on techniques of capturing these flies with different and effective techniques. Along with it, most species-specific baits are discussed to catch more yield. Culture food media, a set measurement of different ingredients is used to rear the collected sample. The reasons for using each ingredient are also discussed in this chapter. At last, this chapter highlights the basic clues to identify different species in the field and lab along with learning distinguishing characteristics of males and females easily and effectively.",signatures:"Pragya Topal, Divita Garg and Rajendra S. Fartyal",downloadPdfUrl:"/chapter/pdf-download/75974",previewPdfUrl:"/chapter/pdf-preview/75974",authors:[{id:"336156",title:"Assistant Prof.",name:"Rajendra S.",surname:"Fartyal",slug:"rajendra-s.-fartyal",fullName:"Rajendra S. Fartyal"},{id:"336657",title:"Ms.",name:"Pragya",surname:"Topal",slug:"pragya-topal",fullName:"Pragya Topal"},{id:"344407",title:"Ms.",name:"Divita",surname:"Garg",slug:"divita-garg",fullName:"Divita Garg"}],corrections:null},{id:"75382",title:"Diversity of Tephritidae and Agromyzidae (Diptera: Brachycera) in Flower Heads of Asteraceae in the Chaco",doi:"10.5772/intechopen.96352",slug:"diversity-of-tephritidae-and-agromyzidae-diptera-brachycera-in-flower-heads-of-asteraceae-in-the-cha",totalDownloads:125,totalCrossrefCites:0,totalDimensionsCites:0,hasAltmetrics:1,abstract:"The Chaco is an international biome, connecting four countries: Paraguay (230,000 km2), Bolivia (90,000 km2), Argentina (520,000 km2), and Brazil (Mato Grosso do Sul state (MS), with around 9,000 km2 and in the middle of South America. Brazilian Chaco is restricted to Porto Murtinho region, MS. The daisies (Asteraceae) with near 24,000 species worldwide is characterized by herbs and shrubs that coevolved with several taxa of endophagous insects: dipterans Agromyzidae, Ceciidomyidae and Tephritidae; Coleoptera (Apionidae), Hemiptera (Miridae), Lepidoptera (Blastobasidae, Gelechiidae, Pterophoridae, Pyralidae, and Tortricidae) and the parasitoids of this endophagous insects, which found in the daisies’s flower heads ideal conditions for food, breeding site and shelter. The Neotropical florivorous flies are the Agromyzinae (Agromyzidae), and Tephritinae (Tephritidae), which in their larval stage feed on Asteraceae inflorescences. To report the species of florivore flies, their host plants and parasitoids in flower heads of Asteraceae from the Brazilian Chaco, we sampled inflorescences of 25 species (± 500 flower heads/species) that were kept in containers to the emergence of the florivorous flies or their parasitoids sampled in the three phytophysiognomies. The adult insects after 48 hours of their emergence were fixed in 80% ethanol for later identification. A total 25 species of Asteraceae were evaluated in the Brazilian Chaco, being collected 17,000 flower heads. Nine tribes of two Asteraceae subfamilies were sampled, from which 15 species of florivorous flies were recovered. We found 5 genera with 9 of Tephritinae (Tephritidae), 6 species of Melanagromyza (Agromyzinae, Agromyzidae), and 104 parasitoids (Hymenoptera) of the florivorous flies.",signatures:"Manoel A. Uchoa, Anderson S. Fernandes and Jimi N. Nakajima",downloadPdfUrl:"/chapter/pdf-download/75382",previewPdfUrl:"/chapter/pdf-preview/75382",authors:[{id:"87919",title:"Dr.",name:"Manoel",surname:"Uchoa",slug:"manoel-uchoa",fullName:"Manoel Uchoa"},{id:"346550",title:"Dr.",name:"Jimi N.",surname:"Nakajima",slug:"jimi-n.-nakajima",fullName:"Jimi N. Nakajima"},{id:"346551",title:"Dr.",name:"Anderson S.",surname:"Fernandes",slug:"anderson-s.-fernandes",fullName:"Anderson S. Fernandes"}],corrections:null},{id:"75428",title:"Feeding by Florivorous Flies (Tephritidae and Agromyzidae) in Flower Heads of Neotropical Asteraceae (Asterales) from Central Brazil",doi:"10.5772/intechopen.96412",slug:"feeding-by-florivorous-flies-tephritidae-and-agromyzidae-in-flower-heads-of-neotropical-asteraceae-a",totalDownloads:179,totalCrossrefCites:0,totalDimensionsCites:0,hasAltmetrics:0,abstract:"The four following Diptera families are peculiar because they are predominantly phytophagous: Cecidomyiidae, Agromyzidae, Lonchaeidae and Tephritidae; which is uncommon for dipterans. Tephritine’s larvae, depending on the species, consumes leaves, stems, flowers or roots of their host plants. Some tephritines feeds on flower heads of weed Asteraceae and can act in population suppression of invasive species in cultivated areas. In Mid-West of Brazil, we investigate Tephritinae and Agromyzinae flies in flower heads of Asteraceae species in three different phytophisiognomies in Dourados region, state of Mato Grosso do Sul. Here, 12 florivore fly species (9 Tephritinae, and 3 Melanagromyza spp., Agromizinae, Agromyzidae) are reported for the first time in Mid-West Brazil. We stablish the species of Asteraceae host for Tephritinae (Tephritidae) and for some species of Melanagromyza (Agromyzinae) in environments of Cerrado, Semideciduous Forest, and agroecosystem at Dourados-MS region. The inflorescences of Asteraceae species (± 500 capitula/species) were kept in containers to the emergence of the florivorous flies or their parasitoids. The adult insects after 48 hours were fixed in 80% ethanol for later identification. A total 36 species of Asteraceae were evaluated in the three regions of Dourados-MS, Brazil. Were obtained 120,031 flower heads of Astereceae, emerging 2,698 adults of insects: 833 Tephritinae (Tephritidae), belonging to 7 genera and 9 species; 1,089 Melanagromyza spp. (Agromyzidae) and 776 parasitoids (Hymenoptera) from the tephritines and agromyzines. We found that some florivore fly species needs to be better studied to employ in suppression programs of invasive Asteraceae population in the Neotropical Region.",signatures:"Manoel A. Uchoa, Morgana F. Wachter-Serapião and Nádia Roque",downloadPdfUrl:"/chapter/pdf-download/75428",previewPdfUrl:"/chapter/pdf-preview/75428",authors:[{id:"87919",title:"Dr.",name:"Manoel",surname:"Uchoa",slug:"manoel-uchoa",fullName:"Manoel Uchoa"},{id:"346548",title:"Dr.",name:"Nádia",surname:"Roque",slug:"nadia-roque",fullName:"Nádia Roque"},{id:"346549",title:"Dr.",name:"Morgana F.",surname:"Wachter-Serapião",slug:"morgana-f.-wachter-serapiao",fullName:"Morgana F. Wachter-Serapião"}],corrections:null},{id:"74836",title:"Chironomidae: Biology, Ecology and Systematics",doi:"10.5772/intechopen.95577",slug:"chironomidae-biology-ecology-and-systematics",totalDownloads:430,totalCrossrefCites:0,totalDimensionsCites:0,hasAltmetrics:0,abstract:"The family of Chironomidae is a group of Diptera insects belonging to the suborder of Nematocera, commonly called “non-biting midges” in the adult stage and “bloodworms” in the larval stage. The Chironomidae are often the most abundant group of macroinvertebrates, in number of species and individuals, encountered in all aquatic environments of freshwater, brackish, terrestrial and even the sea. Likewise, Chironomidae occur in all the continents. The Chironomidae family is divided into 11 sub-families that have diffrent ecological statues. Despite the wealth of data on Chironomidae in the Holarctic region, other parts of the world are poorly studied and few guides to identifying Chironomidae have been produced. This chapter includes a theoretical synthesis on the Chironomidae, it deals with the Biology (life cycle and description of different stages), description of all subfamilies and the ecology of this important family of Diptera.",signatures:"Zerguine Karima",downloadPdfUrl:"/chapter/pdf-download/74836",previewPdfUrl:"/chapter/pdf-preview/74836",authors:[{id:"334825",title:"Dr.",name:"Karima",surname:"Zerguine",slug:"karima-zerguine",fullName:"Karima Zerguine"}],corrections:null},{id:"74320",title:"Ecological Aspects of Tabanids (Diptera: Tabanidae) in a Gabonese Cattle Ranch",doi:"10.5772/intechopen.95062",slug:"ecological-aspects-of-tabanids-diptera-tabanidae-in-a-gabonese-cattle-ranch",totalDownloads:146,totalCrossrefCites:0,totalDimensionsCites:0,hasAltmetrics:0,abstract:"To embark on an anti-vectorial fight against mechanical vectors of animal trypanosomosis, investigations were undertaken in order to determine the abundance, species diversity and daily activity of tabanids in a cattle ranch in Gabon. The nzi and vavoua traps were used to catch tabanids in three divisions of this ranch. In this study, 616 tabanids were captured: 349 (56.66%) in Division 1, 226 (36.69%) in Division 2 and 41 (6.66%) in Division 3. In the first Division, T. taeniola was the most abundant species with an Apparent Density (ADT) of 2.2, followed by H. pluvialis (ADT = 1.05). In the second Division, H. pluvialis was most abundant with ADT of 1.6, followed by T. taeniola (ADT = 0.38). In the last Division, the most abundant species was H. pluvialis (ADT = 0.15). Comparing the relative abundance of catches with sites (Divisions), we realized that there was no statistically significant difference in catches with trapping sites. It was noticed that Division 3 recorded the highest diversity index values. We realized that the nzi trap recorded higher tabanid catches than the vavoua trap. The diurnal activity rhythm of the most frequent species encountered slightly differed with prospection sites.",signatures:"Ovono Mélodie Audrey Prisca, Mounioko Franck, Zinga Koumba Christophe Roland, Koumba Aubin Armel, Sevidzem Silas Lendzele, Maroundou Audrey Pamela, Acapovi-Yao Géneviève Lydie, Tamesse Joseph Lebel, Simo Gustave, M’batchi Bertrand and Mavoungou Jacques François",downloadPdfUrl:"/chapter/pdf-download/74320",previewPdfUrl:"/chapter/pdf-preview/74320",authors:[{id:"243979",title:"Ph.D. Student",name:"Sevidzem",surname:"Lendzele",slug:"sevidzem-lendzele",fullName:"Sevidzem Lendzele"},{id:"340184",title:"Dr.",name:"Ovono Mélodie",surname:"Audrey Prisca",slug:"ovono-melodie-audrey-prisca",fullName:"Ovono Mélodie Audrey Prisca"},{id:"340185",title:"Dr.",name:"Mounioko",surname:"Franck",slug:"mounioko-franck",fullName:"Mounioko Franck"},{id:"340186",title:"Dr.",name:"Zinga Koumba Christophe",surname:"Roland",slug:"zinga-koumba-christophe-roland",fullName:"Zinga Koumba Christophe Roland"},{id:"340187",title:"Dr.",name:"Maroundou Audrey",surname:"Pamela",slug:"maroundou-audrey-pamela",fullName:"Maroundou Audrey Pamela"},{id:"340188",title:"Dr.",name:"Acapovi-Yao Géneviève",surname:"Lydie",slug:"acapovi-yao-genevieve-lydie",fullName:"Acapovi-Yao Géneviève Lydie"},{id:"340190",title:"Dr.",name:"Tamesse Joseph",surname:"Lebel",slug:"tamesse-joseph-lebel",fullName:"Tamesse Joseph Lebel"},{id:"340191",title:"Dr.",name:"Simo",surname:"Gustave",slug:"simo-gustave",fullName:"Simo Gustave"},{id:"340192",title:"Dr.",name:"M’batchi",surname:"Bertrand",slug:"m'batchi-bertrand",fullName:"M’batchi Bertrand"},{id:"340193",title:"Dr.",name:"Mavoungou Jacques",surname:"François",slug:"mavoungou-jacques-francois",fullName:"Mavoungou Jacques François"}],corrections:null},{id:"75790",title:"Morphological Keys for the Identification of Tunisian Culicoides Biting Midges (Diptera: Ceratopogonidae)",doi:"10.5772/intechopen.96656",slug:"morphological-keys-for-the-identification-of-tunisian-em-culicoides-em-biting-midges-diptera-ceratop",totalDownloads:134,totalCrossrefCites:0,totalDimensionsCites:0,hasAltmetrics:0,abstract:"Culicoides biting midges are tiny blood-feeding insects of several diseases with veterinary and public health significance, including Bluetongue in ruminants, African horse sickness in equids and filarial diseases like Onchocercosis and Mansonellosis affecting various species such as humans. Their identification depends basically on the microscope examination of key morphological characters. Consequently, identification keys are important to any non experiment working with these biting midges. The Tunisian fauna of Culicoides biting midges consists of 35 species, whose morphological delineation may be troublesome for non-taxonomists. In response to this situation, and for the first time a key to the adult Culicoides species in Tunisia was prepared.",signatures:"Darine Slama, Emna Chaker and Hamouda Babba",downloadPdfUrl:"/chapter/pdf-download/75790",previewPdfUrl:"/chapter/pdf-preview/75790",authors:[{id:"192246",title:"Ph.D.",name:"Darine",surname:"Slama",slug:"darine-slama",fullName:"Darine Slama"},{id:"195408",title:"Prof.",name:"Hamouda",surname:"Babba",slug:"hamouda-babba",fullName:"Hamouda Babba"},{id:"195409",title:"Prof.",name:"Emna",surname:"Chaker",slug:"emna-chaker",fullName:"Emna Chaker"}],corrections:null},{id:"75244",title:"Control Strategy for Aedes aegypti (Linnaeus, 1762) Population",doi:"10.5772/intechopen.96088",slug:"control-strategy-for-em-aedes-aegypti-em-linnaeus-1762-population",totalDownloads:213,totalCrossrefCites:0,totalDimensionsCites:0,hasAltmetrics:0,abstract:"The mosquito Aedes aegypti (Diptera: Culicidae), is adapted to different environments, mainly urban ones. They have a high degree of vectorial competence for viral diseases, especially Dengue, the arbovirus with the highest number of cases in the world. The adaptive ability of this insect and the abundance of breeding sites have undermined attempts at population’s control, resulting in a high degree of infestation in many regions of the world, resulting in a Dengue endemic. It is important to understand the different nuances of the insect in order to understand the adaptive capacity of this vector, through the knowledge of his behavior, to propose new strategies and engagement of population in proactive actions that allow the population control of this vector, especially in periods of greater proliferation. This chapter discusses population control strategies, in different scenarios and carried out by different researchers, mainly in Brazil.",signatures:"Taiana Gabriela Barbosa de Souza, Eduardo José de Arruda, Raphael Antônio Borges Gomes, Alex Martins Machado and Antônio Pancrácio de Souza",downloadPdfUrl:"/chapter/pdf-download/75244",previewPdfUrl:"/chapter/pdf-preview/75244",authors:[{id:"301356",title:"Dr.",name:"Eduardo",surname:"Arruda",slug:"eduardo-arruda",fullName:"Eduardo Arruda"},{id:"308803",title:"Dr.",name:"António",surname:"Souza",slug:"antonio-souza",fullName:"António Souza"},{id:"343503",title:"Dr.",name:"Alex",surname:"Martins Machado",slug:"alex-martins-machado",fullName:"Alex Martins Machado"},{id:"343509",title:"BSc.",name:"Taiana",surname:"Gabriela Barbosa De Souza",slug:"taiana-gabriela-barbosa-de-souza",fullName:"Taiana Gabriela Barbosa De Souza"},{id:"346904",title:"Dr.",name:"Raphael Antônio",surname:"Borges Gomes",slug:"raphael-antonio-borges-gomes",fullName:"Raphael Antônio Borges Gomes"}],corrections:null},{id:"76977",title:"Environmental Manipulation: A Potential Tool for Mosquito Vector Control",doi:"10.5772/intechopen.95924",slug:"environmental-manipulation-a-potential-tool-for-mosquito-vector-control",totalDownloads:240,totalCrossrefCites:0,totalDimensionsCites:0,hasAltmetrics:0,abstract:"Mosquito borne diseases have continued to ravage man and his animals despite efforts to curb its spread. The use of chemicals has been the main thrust for control of all life stages of mosquitoes. Increased resistance to commonly used insecticides has called for renewed effort for vector control. Environmental management for vector control is one of the new strategies developed to tackle the menace of vectors. Manipulation of abiotic factors has widely gained acceptance due to laboratory and semi-field trials and findings. In this chapter, we reviewed literatures on some critical abiotic factors and their effects on bionomics and biological fitness of immature and adult life stages of mosquito species. We also looked at prospects for developing protocols based on these findings.",signatures:"Ukubuiwe Azubuike Christian, Olayemi Israel Kayode, Ukubuiwe Catherine Chinenye and Ugbede Bright Sule",downloadPdfUrl:"/chapter/pdf-download/76977",previewPdfUrl:"/chapter/pdf-preview/76977",authors:[{id:"335962",title:"Dr.",name:"Azubuike",surname:"Ukubuiwe",slug:"azubuike-ukubuiwe",fullName:"Azubuike Ukubuiwe"},{id:"344891",title:"Prof.",name:"Israel Kayode",surname:"Olayemi",slug:"israel-kayode-olayemi",fullName:"Israel Kayode Olayemi"},{id:"344892",title:"Mrs.",name:"Chinenye Catherine",surname:"Ukubuiwe",slug:"chinenye-catherine-ukubuiwe",fullName:"Chinenye Catherine Ukubuiwe"},{id:"345712",title:"Mr.",name:"Bright Ugbede",surname:"Sule",slug:"bright-ugbede-sule",fullName:"Bright Ugbede Sule"}],corrections:null}],productType:{id:"1",title:"Edited Volume",chapterContentType:"chapter",authoredCaption:"Edited 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This work reviews the corrosion protection of magnesium based alloys in industrial solutions. Corrosion behavior had been studied using electrochemical impedance spectroscopy (EIS), Potentiondynamic polarization and scanning electron microscope (SEM) techniques. Magnesium is the lightest of all metals in practical use with density of 1.74 g cm-3. Pure magnesium metal has useful properties such as shielding against electromagnetic waves, vibration damping, dent resistance and machinability, in addition to its recyclability as it has a lower specific heat and a lower melting point than other metals. On the other hand, magnesium has shortcomings such as insufficient strength, elongation and heat resistance as well as being subject to corrosion. It is necessary to deal with its shortcomings and improve its performance through alloying with various elements. Alloying magnesium improves its strength, heat resistance and creep resistance [1].
Magnesium alloys are the most versatile and attractive metallic materials. They are used for a broad range in commercial, industrial and aerospace applications due to their many advantages, such as light density, good mechanical properties and excellent castability [2-4]. The most common magnesium alloys are those containing aluminum, Zinc, manganese, zirconium, thorium and rare earth metals. The latter alloys are used when resistance to creep and high temperature strength are required. One of the major problems that limit magnesium alloys application is their high susceptibility to corrosion in different media [5] which depends widely on film formation and surface electrolyte interaction. A serious limitation for the wide-spread use of several magnesium alloys is their susceptibility to general and localized (pitting) corrosion. The AZ-based Mg system has been the basis of the most widely used magnesium alloys [6]. One of the most successful magnesium-aluminium alloy is AZ91D, which has a two-phase microstructure typically consisting of α-Mg matrix with the β-phase (the intermetallic Mg17Al12) distributed along the α grain boundaries. The α-phase consists of α-Mg-Al-Zn solid solution with the same structure as pure magnesium [5]. Also AZ31E alloy have excellent mechanical properties. Extruded Mg alloys as AZ31E is getting more and more widely used because of their considerably high plasticity in comparison with the die-cast Mg alloys [7].
Corrosion is a major problem in the cooling system of an engine block. Currently, the main composition of a conventional coolant is 30–70 vol% ethylene glycol [7]. This can be used for studying the corrosion behavior of AZ91D alloy. Most existing commercial coolants fail to provide adequate corrosion protection to magnesium alloys [8]. Some companies have also realized the difficulty of using the conventional coolants for magnesium alloys, and are developing coolants with new inhibitors [9]. Song et al. [7] observed that the corrosion rate of magnesium in aqueous ethylene glycol depends on the concentration of the solution. A diluted ethylene glycol solution is more corrosive than a concentrated one at room temperature. Ethylene glycol solution contaminated by individual contaminants NaCl, NaHCO3 or Na2SO4 is more corrosive to magnesium. NaCl is the most detrimental contaminant. In this work, a study for the corrosion behavior of AZ91D alloy in this coolant has been done, due to this issue is important industrially. The aim is to characterize the corrosion properties of AZ91D alloy in aqueous ethylene glycol-water solutions of different percentages. The influence of adding chloride or flouride ion in ethylene glycol solution on the corrosion behavior was studied. Also the effect of paractamol ((N-acetyl-para-aminophenol=APAP) as inhibitor in ethylene glycol for AZ91D alloy is investigated [6].
Electrochemical characterization and corrosion behavior of AZ31E alloy was done in aqueous Oxalic acid as industrial solution [10]. Oxalic acid is a relatively strong organic acid used as purifying agent in pharmaceutical industry. Oxalic acid\'s main applications include cleaning or bleaching, especially for the removal of rust [11]. The work aims to attain more information concerning the corrosion behavior of AZ31E alloy in oxalic acid solution containing Cl-, F-or PO
One of the major problems that limit magnesium alloys application is their high susceptibility to corrosion in different media. This makes studying the corrosion and corrosion control of Mg alloys an interesting point of research which can enable extending the potential use of these important materials in a broad range of many technical and innovative applications.
The aim is to study the corrosion resistance of Mg alloys which depends essentially on two main factors: (i) alloy microstructure and (ii) properties of the developed surface film.
Generally, it is aimed to find the best magnesium alloy with low cost and low corrosion rate and to find a possible way to improve corrosion resistance of either AZ91D or AZ31E alloy in different industrial solutions.
Samples of die cast magnesium aluminum alloy (AZ91D or AZ31E) in the form of plates (200 x 100 x 5 mm) were donated from Department of mining, Metallurgy and Materials Engineering, Laval University, Canada. The chemical composition (wt%) of the two alloys are as follows: 9.0 Al, 0.67 Zn, 0.33 Mn, 0.03 Cu, 0.01 Si, 0.005 Fe, 0.002 Ni, 0.0008 Be and balance Mg for AZ91D alloy; and 2.8 Al, 0.96 Zn, 0.28 Mn, 0.0017 Cu, 0.0111 Fe, 0.0007 Ni, 0.0001 Be and balance Mg for AZ31E. They were used for preparing the working electrodes. The sample was divided into small coupons. Each coupon was welded to an electrical wire and fixed with Araldite epoxy resin in a glass tube leaving cross-sectional area of the specimen 0.2 cm2 for AZ91D alloy and 0.196 cm2 for both AZ31E alloy.
The solutions used were prepared using Analar grade reagents for each work are (ethylene glycol, sodium fluoride, sodium chloride and paracetamol [6]) and (oxalic acid, sodium fluoride, sodium chloride and sodium phosphate [12]). All solutions were prepared using triply distilled water.
The surface of the test electrode was mechanically polished by emery papers with 400 up to 1000 grit to ensure the same surface roughness, degreasing in acetone, rinsing with ethanol and drying in air.
The cell used was a typical three-electrode one fitted with a large platinum sheet of size 15×20×2mm as a counter electrode (CE), saturated calomel (SCE) as a reference electrode (RE) and the alloy as the working electrode (WE).
The impedance diagrams were recorded at the free immersion potential (OCP) by applying a 10 mV sinusoidal potential through a frequency domain from 100 kHz down to 100 mHz. The EIS was recorded after reading a steady state open-circuit potential. The polarization scans were carried out at a rate of 1 mV/s over the potential range from-2.5 to 0 mV vs. saturated calomel electrode (SCE). Prior to the potential sweep, the electrode was left under open-circuit in the respective solution until a steady free corrosion potential was recorded. Corrosion current, icorr, which is equivalent to the corrosion rate is given by the intersection of the Tafel lines extrapolation. In the weight loss measurements, the treated samples were weighed before and after the immersion in Hank\'s solution in absence and in presence of different concentrations of glucosamine sulphate. The instrument used is the electrochemical workstation IM6e Zahner-elektrik, GmbH, (Kronach, Germany).The electrochemical and weight loss experiments were always carried inside an air thermostat which was kept at 25oC, unless otherwise stated. The SEM micrographs were collected using a JEOL JXA-840A electron probe microanalyzer.
The EIS scans of AZ91D alloy as a function of concentration for ethylene glycol were recorded (Figure 1) after leaving the working electrode for 2 h in the test solution until reaching a steady state potential value (Est). As shown in Figure 1, an increase in ethylene glycol concentration leads to a decrease in the |Z| value, indicating that pure ethylene glycol is almost inert to magnesium alloy and the corrosion of magnesium alloy in ethylene glycol solution is closely related to the water content of the solution [7].
EIS data of AZ91D alloy exposed after 2 h immersion in various concentrations of ethylene glycol solution: (1) 30%, (2) 50%, (3) 70% and (4) 90%.
By studying the effect of adding either fluoride or chloride to the highest corrosive concentration(30% ethylene glycol-70% water), it was found that the impedance value decreases (Figure 2a) with increasing chloride ion concentration due to its aggressiveness [10]. However, for fluoride containing ethylene glycol solution impedance value increases with increasing F-ion concentrations shown in Figure 2b.
EIS data of AZ91D alloy exposed after 2 h immersion in 30% ethylene glycol solution with (a) chloride and (b) fluoride ions of various concentrations: (1) 0.01 M, (2) 0.05 M, (3) 0.1 M, (4) 0.3 M and (5) 0.6 M.
On adding paracetamol as inhibitor in the concentration range (0.01-1.0 mM) for corrosion of the blank (30% ethylene glycol-70% water), it was found that both |Z| value and phase angle maximum (
EIS data (a) Bode plots and (b) Nyquist plots of AZ91D alloy exposed after 2 h immersion in 30% ethylene glycol solution with paracetamol of various concentrations: (1) 0.01 mM, (2) 0.05 mM, (3) 0.1 mM, (4) 0.5 mM and (5) 1.0 mM.
The results in general reveal two clear trends concerning the number of peaks observed in the patterns of the phase shift. The first one is for the behavior of AZ91D alloy in chloride, flouride and paracetamol containing ethylene glycol, where the Bode plots display only one maximum phase lag at all tested concentrations, however, for paracetamol, the phase angle maximum is nearly 45o, corresponding to a diffusion control in the passive layer. The second trend is for the alloy behavior in ethylene glycol medium with different concentrations where another peak of phase lag appears at the low frequency region and also the phase angle maximum is nearly 45o due to diffusion phenomenon. The impedance data were thus simulated to the appropriate equivalent circuit for the cases with one time constant (Figure 4a,b) and the others exhibiting two time constants (Figure 4c), respectively. This simulation gave a reasonable fit. The estimated data for ethylene glycol is given in Table 1, for chloride and fluoride ions in Table 2 and for paracetamol ethylene glycol containing solution in Table 3.
The equivalent circuit model representing (a,b) one and (c) two time constants.
\n\t\t\t\t | \n\t\t\t\n\t\t\t\t | \n\t\t\t\n\t\t\t\t | \n\t\t\t\n\t\t\t\t | \n\t\t\t\n\t\t\t\t | \n\t\t\t\n\t\t\t\t | \n\t\t\t\n\t\t\t\t | \n\t\t\t\n\t\t\t\t | \n\t\t\t\n\t\t\t\t | \n\t\t\t\n\t\t\t\t | \n\t\t\t\n\t\t\t\t | \n\t\t
30 | \n\t\t\t11.4 | \n\t\t\t0.5 | \n\t\t\t88.9 | \n\t\t\t4.4 | \n\t\t\t4.5 | \n\t\t\t1.64 | \n\t\t\t5.0 | \n\t\t\t11.5 | \n\t\t\t0.50 | \n\t\t\t-1.45 | \n\t\t
50 | \n\t\t\t21.9 | \n\t\t\t0.7 | \n\t\t\t77.9 | \n\t\t\t6.2 | \n\t\t\t4.3 | \n\t\t\t1.52 | \n\t\t\t6.9 | \n\t\t\t13.1 | \n\t\t\t0.41 | \n\t\t\t-1.34 | \n\t\t
70 | \n\t\t\t26.8 | \n\t\t\t1.2 | \n\t\t\t71.0 | \n\t\t\t10.5 | \n\t\t\t4.2 | \n\t\t\t1.47 | \n\t\t\t11.7 | \n\t\t\t14.3 | \n\t\t\t0.25 | \n\t\t\t-1.26 | \n\t\t
90 | \n\t\t\t30.0 | \n\t\t\t1.4 | \n\t\t\t66.4 | \n\t\t\t15.4 | \n\t\t\t4.0 | \n\t\t\t1.33 | \n\t\t\t16.8 | \n\t\t\t15.3 | \n\t\t\t0.1 | \n\t\t\t-1.18 | \n\t\t
Equivalent circuit and corrosion parameters for AZ91D alloy in various concentrations of ethylene glycol solution after 2 h immersion
\n\t\t\t\t | \n\t\t\t\n\t\t\t\t | \n\t\t\t\n\t\t\t\t | \n\t\t\t\n\t\t\t\t | \n\t\t\t\n\t\t\t\t | \n\t\t\t\n\t\t\t\t | \n\t\t\t\n\t\t\t\t | \n\t\t
\n\t\t\t\t | \n\t\t\t\n\t\t\t\t | \n\t\t\t\n\t\t\t\t | \n\t\t\t\n\t\t\t\t | \n\t\t\t\n\t\t\t\t | \n\t\t\t\n\t\t\t\t | \n\t\t|
NaCl | \n\t\t\t0.01 | \n\t\t\t7.7 | \n\t\t\t2.67 | \n\t\t\t154.8 | \n\t\t\t0.47 | \n\t\t\t-1.36 | \n\t\t
0.05 | \n\t\t\t5.8 | \n\t\t\t4.36 | \n\t\t\t50.2 | \n\t\t\t0.49 | \n\t\t\t-1.43 | \n\t\t|
0.10 | \n\t\t\t3.1 | \n\t\t\t7.44 | \n\t\t\t9.0 | \n\t\t\t0.64 | \n\t\t\t-1.52 | \n\t\t|
0.30 | \n\t\t\t1.1 | \n\t\t\t8.50 | \n\t\t\t4.2 | \n\t\t\t3.40 | \n\t\t\t-1.53 | \n\t\t|
0.60 | \n\t\t\t0.6 | \n\t\t\t9.58 | \n\t\t\t2.5 | \n\t\t\t30.4 | \n\t\t\t-1.63 | \n\t\t|
NaF | \n\t\t\t0.01 | \n\t\t\t4.1 | \n\t\t\t3.54 | \n\t\t\t22.1 | \n\t\t\t0.19 | \n\t\t\t-1.41 | \n\t\t
0.05 | \n\t\t\t5.5 | \n\t\t\t3.46 | \n\t\t\t21.8 | \n\t\t\t0.11 | \n\t\t\t-1.43 | \n\t\t|
0.10 | \n\t\t\t7.0 | \n\t\t\t2.46 | \n\t\t\t15.8 | \n\t\t\t0.09 | \n\t\t\t-1.45 | \n\t\t|
0.30 | \n\t\t\t8.4 | \n\t\t\t1.23 | \n\t\t\t7.3 | \n\t\t\t0.03 | \n\t\t\t-1.51 | \n\t\t
Equivalent circuit and corrosion parameters for AZ91D alloy after 2 h immersion in 30% ethylene glycol solution with different concentrations of Cl- or F- ions
\n\t\t\t\t | \n\t\t\t\n\t\t\t\t | \n\t\t\t\n\t\t\t\t | \n\t\t\t\n\t\t\t\t | \n\t\t\t\n\t\t\t\t | \n\t\t\t\n\t\t\t\t | \n\t\t\t\n\t\t\t\t | \n\t\t\t\n\t\t\t\t | \n\t\t
\n\t\t\t\t | \n\t\t\t\n\t\t\t\t | \n\t\t\t\n\t\t\t\t | \n\t\t\t\n\t\t\t\t | \n\t\t\t\n\t\t\t\t | \n\t\t\t\n\t\t\t\t | \n\t\t\t\n\t\t\t\t | \n\t\t\t\n\t\t\t\t | \n\t\t
0.01 | \n\t\t\t0.33 | \n\t\t\t6.1 | \n\t\t\t2.7 | \n\t\t\t2.90 | \n\t\t\t0.100 | \n\t\t\t-1.37 | \n\t\t\t80.0 | \n\t\t
0.05 | \n\t\t\t0.37 | \n\t\t\t10.0 | \n\t\t\t2.2 | \n\t\t\t1.84 | \n\t\t\t0.020 | \n\t\t\t-1.26 | \n\t\t\t96.0 | \n\t\t
0.1 | \n\t\t\t0.47 | \n\t\t\t8.5 | \n\t\t\t2.4 | \n\t\t\t1.39 | \n\t\t\t0.040 | \n\t\t\t-1.41 | \n\t\t\t92.1 | \n\t\t
0.5 | \n\t\t\t0.64 | \n\t\t\t5.6 | \n\t\t\t2.8 | \n\t\t\t2.52 | \n\t\t\t0.045 | \n\t\t\t-1.44 | \n\t\t\t91.0 | \n\t\t
1.0 | \n\t\t\t0.92 | \n\t\t\t5.1 | \n\t\t\t3.6 | \n\t\t\t1.46 | \n\t\t\t0.051 | \n\t\t\t-1.46 | \n\t\t\t89.8 | \n\t\t
Equivalent circuit and corrosion parameters for AZ91D alloy after 2 h immersion in 30% ethylene glycol solution with different concentrations of paracetamol
Generally, the impedance response is well simulated by the classic parallel resistor capacitor (RC) combination in series with the solution resistance (Rs). In this model [10] a charge transfer resistance (R) is in parallel with the double layer capacitance (C), as shown in Figure 4a. Figure 4b is one time constant model containing Warburg impedance (Zw) in series to R [13], which is related to ion diffusion through passive film and indicates that the corrosion mechanism is controlled not only by a charge-transfer process but also by a diffusion process. The appropriate equivalent model for the impedance diagrams with two time constants, consists of two series circuits, R1ZwC1 and R2C2 parallel combination and both are in series with Rs. C1 is the capacitance of the outer layer, C2 pertains to the inner layer, while R1 and R2 are the respective resistances of the outer and inner layers constituting the surface film, respectively [14]. A linear region at the lower frequencies in the Nyquist plot in Figure 3b would be related to diffusion phenomena [15, 16] thereby an equivalent circuit with Warburg component Zw is more appropriate. Analysis of the experimental spectra were made by best fitting to the corresponding equivalent circuit using Thales software provided with the workstation where the dispersion formula suitable to each model was used [14]. In this complex formula an empirical exponent (α), varying between 0 and 1, is introduced to account for the deviation from the ideal capacitive behavior due to surface inhomogeneties, roughness factors and adsorption effects [10]. An ideal capacitor corresponds to
The total resistance (RT) and relative thickness (1/CT) for AZ91D alloy at various concentrations of ethylene glycol solution, measured after 2 h immersion.
The effect of concentration for ethylene glycol or additive ions or inhibitor on the relative thickness(1/CT) [18] of AZ91D. Figure 5 reveals features generally concurrent to the behavior of the film resistance. It shows that the resistance (RT) and the relative thickness (1/CT) of the surface film on AZ91D sample increase with increasing the concentration of ethylene glycol. Thus, 30% ethylene glycol (blank) is an aggressive solution as shown in SEM image in Fig. 6a, where corrosion products appear on the surface. Pure ethylene glycol has very poor electrical conductivity and is almost an insulator [7]. However, dilution by water facilitates the hydrolysis of the hydroxyl groups in ethylene glycol increasing its electrical conductivity. Ethylene glycol molecule is larger than water, so the adsorption of the former at the surface of AZ91D alloy can result in a lower capacitance value [7]. When the concentration of ethylene glycol increases, more ethylene glycol will be adsorbed on the surface, leading to a lower CT. This explains the decreasing corrosion rate of AZ91D alloy with increasing concentration of ethylene glycol and also the decrease in the Warburg impedance diffusion.
(a-d). SEM micrograph of the (a) blank (30% ethylene glycol solution), (b) 0.3 M F-(c) 0.05 mM paracetamol and (d) 1.0 mM paracetamol, ethylene glycol containing solution.
As given in Table 2, in ethylene glycol solution contaminated with chloride ions, the resistance decreases sharply at first then reaches a quasi state value with increasing concentration of contaminant [6]. The addition of chloride does not significantly increase the capacitance value until the amount of the added Cl-ions is above a certain level (> 0.05 M). At concentrations > 0.05 M, they are more corrosive than the blank, indicating film dissolution, which can be attributed to the more aggressive nature of the chloride anion. The increase in capacitance should be due to the replacement of ethylene glycol on the alloy surface by the chloride ions as contaminant.
Fluoride is also an important substance that could exist in normal water and can easily be introduced into vehicle coolant systems [19]. As given in Table 2, in fluoride medium at concentrations > 0.05 M, R and 1/C of the surface film increase steeply than the blank due to the formation of less soluble and more stable magnesium fluoride (MgF2) film [17]. This is confirmed by SEM micrograph of 0.3 M fluoride in ethylene glycol concentration (Figure 6b), the grain particles of the salt film grow laterally during the prolonged exposure (2 h) covering nearly the whole surface of the alloy indicating more stability as compared to the blank shown in Figure 6a. In fact, F-has recently been used as an inhibitor in coolants for magnesium alloys [7]. However, the inhibition mechanism has not been systematically studied. Gulbrandsen et. al. [20] reported that crystalline KMgF3 was identified on magnesium at higher F-concentration in the more alkaline solutions. At 0.01 M fluoride concentration ethylene glycol may help in the formation of this compound, so that the resistance decreases than the blank. Table 2 shows that the addition of F-into ethylene glycol strikingly enhanced R but decreased Rs and C. The significantly reduced C and dramatically improved R suggest that [7] a three-dimensional film was formed on the magnesium surface which is much thicker than the adsorbed film and thus can effectively separate the magnesium alloy from the solution, making the corrosion reaction at the interface very slow. As to the solution resistance Rs, its decrease after the addition of F-can be simply attributed to the increased total concentration of ions by adding F-into the solution.
Finally, the effect of adding paracetamol as inhibitor was studied; it was found that all concentrations give good inhibition as compared to the blank which may be due to the adsorption of the inhibitor through the adsorption. The rate of adsorption is usually rapid and hence, the reactive metal surface is shielded from the aggressive environment [21]. However, it was found that there is a critical concentration for the inhibitor at 0.05 mM which has the highest resistance as shown in Table 3, and the resistance decreases with increasing the inhibitor concentration > 0.05 mM. This behavior is confirmed by SEM micrographs shown in Figure 6(c,d), where Figure 6c is for 0.05 mM and Figure 6b for 1.0 mM paracetamol containing ethylene glycol solution. Figure 6c shows a denser and smoother film adsorbed on the alloy surface than that formed on 1.0 mM concentration Figure 6d, Also the two are much better than the blank shown in Figure 6a.
The anodic and cathodic (E-log i) plots of AZ91D alloy in the ethylene glycol solution of different concentrations were also studied using potentiodynamic polarization measurements at a scan rate of 1.0 mV s-1. The curves were swept from-2.5 V to-1.0 V vs. SCE. Prior to the potential scan the electrode was left for 2 h until a steady free corrosion potential (Est) value was recorded. The electrochemical parameters shown in Tables 1 and 2 were obtained by analyzing the I/E data as described elsewhere [10]. The corrosion potential (Ecorr) and current density (icorr) were calculated by Tafel extrapolation method for the cathodic branches of the polarization curves. Furthermore, to illustrate the relative stability of the surface film on AZ91D alloy in the investigated solutions, icorr values are found to decrease and Ecorr values shifts positively with increasing ethylene glycol percentage. Since increasing water percentage in ethylene glycol is responsible for the corrosivity of the solution to the alloy. However, in chloride containing solution icorr values increases and Ecorr values shifts to more negative values with increasing Cl-concentration. This behavior reflects the harmful influence of Cl-ions on the corrosion performance of AZ91D in aqueous liquids [7]. In Flouride containing solutions, a strange behavior occurs, where icorr decreases and Ecorr values tend to more negative values with increasing F-concentration. Particularly, the role of the β-phase in corrosion is extensively addressed for AZ91D, and it is generally accepted that the β-phase is a corrosion barrier and its presence in an AZ91D alloy is beneficial to the corrosion resistance of the alloy. The reason is fluoride refined AZ91D magnesium alloy by blocking the growth of primary fir-tree crystals in the crystal boundary [22]. Thus, the dimension of β phase is decreased. In the cathodic reaction process, the overpotential of the hydrogen generation increased due to the dispersion of β phase, which resulted in the corrosion potential of the AZ91D.
Fig. 7 shows polarization scans for paracetamol, from which icorr values is calculated and drawn against inhibitor concentration (Fig. 8). As can be seen, icorr value is the lowest at 0.05 mM paracetamol concentration, which is a critical concentration and shows the highest inhibition efficiency (IE) of 96% which calculated from the following equation:
Generally, impedance and polarization measurements confirm each other and all are confirmed by SEM images.
Cathodic and anodic scans of AZ91D alloy exposed after 2 h immersion in 30% ethylene glycol solution with paracetamol of various concentrations: (1) 0.01 mM, (2) 0.05 mM, (3) 0.1 mM, (4) 0.5 mM and (5) 1.0 mM.
Variation of icorr and IE% for AZ91D alloy exposed after 2 h immersion in 30% ethylene glycol solution with various concentrations of paracetamol.
The impedance measurements recorded after 2 hours of immersion for AZ31E electrode in oxalic acid solution with different concentrations are presented in Figure 9. Bode plots show an intermediate frequency phase peak shifts to lower frequency and higher phase angle maximum with decreasing oxalic acid concentration. Also, impedance values increase with decreasing the concentration of oxalic acid. The appropriate equivalent model used (Figure 4c) consists of two circuits in series from R1C1ZW and R2C2 parallel combination and both are in series with Rs as discussed above. In all cases, good conformity between theoretical and experimental results was obtained with an average error of 4%. The evaluated experimental values are given in Table 4.
Bode plots of AZ31E electrode in naturally aerated oxalic acid solution of different concentrations, at 298 K.
\n\t\t\t\t | \n\t\t\t\n\t\t\t\t | \n\t\t\t\n\t\t\t\t | \n\t\t\t\n\t\t\t\t | \n\t\t\t\n\t\t\t\t | \n\t\t\t\n\t\t\t\t | \n\t\t\t\n\t\t\t\t | \n\t\t\t\n\t\t\t\t | \n\t\t\t\n\t\t\t\t | \n\t\t
\n\t\t\t\t | \n\t\t\t\n\t\t\t\t | \n\t\t\t\n\t\t\t\t | \n\t\t\t\n\t\t\t\t | \n\t\t\t\n\t\t\t\t | \n\t\t\t\n\t\t\t\t | \n\t\t\t\n\t\t\t\t | \n\t\t||
0.01 | \n\t\t\t2.1 | \n\t\t\t4.7 | \n\t\t\t0.94 | \n\t\t\t58.3 | \n\t\t\t10.2 | \n\t\t\t19.2 | \n\t\t\t0.58 | \n\t\t\t243 | \n\t\t
0.25 | \n\t\t\t1.3 | \n\t\t\t5.4 | \n\t\t\t0.93 | \n\t\t\t35.6 | \n\t\t\t9.7 | \n\t\t\t20.1 | \n\t\t\t0.56 | \n\t\t\t200 | \n\t\t
0.50 | \n\t\t\t0.8 | \n\t\t\t6.6 | \n\t\t\t0.91 | \n\t\t\t22.3 | \n\t\t\t7.5 | \n\t\t\t21.3 | \n\t\t\t0.55 | \n\t\t\t100 | \n\t\t
1.00 | \n\t\t\t0.7 | \n\t\t\t8.3 | \n\t\t\t0.90 | \n\t\t\t14.4 | \n\t\t\t5.2 | \n\t\t\t22.0 | \n\t\t\t0.52 | \n\t\t\t44 | \n\t\t
Impedance parameters of AZ31E electrode in naturally aerated oxalic acid of different concentrations, at 298 K.
It was found that, when AZ31E electrode was immersed in oxalic acid solution, two competitive processes occur. The first one is oxide formation which yields a compact magnesium oxide film with good corrosion resistance. The second one is the formation of magnesium oxalate complexes, which yields a thick porous film as in case of Aluminum alloys [23] with expected low corrosion resistance, where oxalate ions are bidentate ligands capable of forming strong surface complexes. With increasing of oxalic acid concentration the alternation of the compact oxide film by porous one will increase leading to an increase in the corrosion rate. This also is due to increasing of the acidity of the medium.
In Table 4, R1 represents the resistance of the passive film which decreases with increasing of oxalic acid concentration due to alternation of compact film by porous one. Consequently, the decrease in the relative thickness of the passive film (1/C1) supports this concept. As the most stable formula for magnesium oxalate is dehydrated one [24], so R2 can represent the resistance of the hydrated layer and the decreasing of relative thickness (1/C2) of this layer with increasing of oxalic acid concentration reflects the strong adsorption of the oxalate anion with increasing of its concentration and increasing of hydrogen evolution. Moreover, the presence of diffusion process at the interfacial layer of the electrode indicates again the formation of porous film and the decreasing of diffusion impedance indicating the increase of electrolyte diffusion through the pores, as a sequence of increasing of the porosity with the increase of oxalate concentration.
At the lowest concentration of oxalic acid (0.01 M) with highest corrosion resistance, the tested electrode was immersed in this solution containing either Cl-, F-or PO
Bode plots of AZ31E electrode as a function of concentration for Cl-anion in naturally aerated 0.01 M oxalic acid solution, at 298 K.
Bode plots of AZ31E electrode as a function of concentration for PO
The theoretical simulated parameters for the tested alloy at each concentration from the added anions (Cl-, F-or PO
\n\t\t\t\t | \n\t\t\t\n\t\t\t\t | \n\t\t\t\n\t\t\t\t | \n\t\t\t\n\t\t\t\t | \n\t\t\t\n\t\t\t\t | \n\t\t\t\n\t\t\t\t | \n\t\t\t\n\t\t\t\t | \n\t\t\t\n\t\t\t\t | \n\t\t\t\n\t\t\t\t | \n\t\t\t\n\t\t\t\t | \n\t\t\t\n\t\t\t\t | \n\t\t
\n\t\t\t\t | \n\t\t\t\n\t\t\t\t | \n\t\t\t\n\t\t\t\t | \n\t\t\t\n\t\t\t\t | \n\t\t\t\n\t\t\t\t | \n\t\t\t\n\t\t\t\t | \n\t\t\t\n\t\t\t\t | \n\t\t\t\n\t\t\t\t | \n\t\t|||
Cl-\n\t\t\t | \n\t\t\tblank | \n\t\t\t2.10 | \n\t\t\t4.7 | \n\t\t\t0.84 | \n\t\t\t58.3 | \n\t\t\t10.2 | \n\t\t\t19.2 | \n\t\t\t0.58 | \n\t\t\t243 | \n\t\t\t31.7 | \n\t\t
0.01 | \n\t\t\t20.0 | \n\t\t\t2.5 | \n\t\t\t0.83 | \n\t\t\t94.1 | \n\t\t\t5.30 | \n\t\t\t7.60 | \n\t\t\t0.57 | \n\t\t\t501 | \n\t\t\t13.4 | \n\t\t|
0.25 | \n\t\t\t14.3 | \n\t\t\t2.9 | \n\t\t\t0.83 | \n\t\t\t87.4 | \n\t\t\t4.30 | \n\t\t\t11.9 | \n\t\t\t0.56 | \n\t\t\t80 | \n\t\t\t16.7 | \n\t\t|
0.50 | \n\t\t\t10.5 | \n\t\t\t3.9 | \n\t\t\t0.81 | \n\t\t\t82.1 | \n\t\t\t3.10 | \n\t\t\t14.9 | \n\t\t\t0.54 | \n\t\t\t100 | \n\t\t\t20.6 | \n\t\t|
1.00 | \n\t\t\t6.70 | \n\t\t\t4.1 | \n\t\t\t0.84 | \n\t\t\t63.7 | \n\t\t\t1.50 | \n\t\t\t18.6 | \n\t\t\t0.53 | \n\t\t\t589 | \n\t\t\t25.1 | \n\t\t|
F-\n\t\t\t | \n\t\t\tblank | \n\t\t\t2.10 | \n\t\t\t4.7 | \n\t\t\t0.84 | \n\t\t\t58.3 | \n\t\t\t10.2 | \n\t\t\t19.2 | \n\t\t\t0.58 | \n\t\t\t243 | \n\t\t\t31.7 | \n\t\t
0.01 | \n\t\t\t23.8 | \n\t\t\t2.1 | \n\t\t\t0.81 | \n\t\t\t110 | \n\t\t\t9.30 | \n\t\t\t5.30 | \n\t\t\t0.59 | \n\t\t\t208 | \n\t\t\t10.8 | \n\t\t|
0.25 | \n\t\t\t21.3 | \n\t\t\t2.5 | \n\t\t\t0.87 | \n\t\t\t106 | \n\t\t\t8.60 | \n\t\t\t6.40 | \n\t\t\t0.67 | \n\t\t\t80 | \n\t\t\t11.2 | \n\t\t|
0.50 | \n\t\t\t18.6 | \n\t\t\t2.6 | \n\t\t\t0.87 | \n\t\t\t91.6 | \n\t\t\t7.50 | \n\t\t\t9.60 | \n\t\t\t0.62 | \n\t\t\t100 | \n\t\t\t12.1 | \n\t\t|
1.00 | \n\t\t\t15.8 | \n\t\t\t2.8 | \n\t\t\t0.81 | \n\t\t\t69.2 | \n\t\t\t6.70 | \n\t\t\t10.1 | \n\t\t\t0.59 | \n\t\t\t589 | \n\t\t\t14.0 | \n\t\t|
PO4\n\t\t\t\t3-\n\t\t\t | \n\t\t\tBlank | \n\t\t\t2.10 | \n\t\t\t4.7 | \n\t\t\t0.84 | \n\t\t\t58.3 | \n\t\t\t10.2 | \n\t\t\t19.2 | \n\t\t\t0.58 | \n\t\t\t243 | \n\t\t\t31.7 | \n\t\t
0.01 | \n\t\t\t17.0 | \n\t\t\t2.4 | \n\t\t\t0.87 | \n\t\t\t121 | \n\t\t\t4.20 | \n\t\t\t7.40 | \n\t\t\t0.57 | \n\t\t\t1075 | \n\t\t\t30.0 | \n\t\t|
0.25 | \n\t\t\t20.1 | \n\t\t\t2.1 | \n\t\t\t0.88 | \n\t\t\t143 | \n\t\t\t5.40 | \n\t\t\t6.10 | \n\t\t\t0.52 | \n\t\t\t199 | \n\t\t\t15.8 | \n\t\t|
0.50 | \n\t\t\t24.2 | \n\t\t\t1.2 | \n\t\t\t0.85 | \n\t\t\t165 | \n\t\t\t6.20 | \n\t\t\t5.60 | \n\t\t\t0.56 | \n\t\t\t2290 | \n\t\t\t3.50 | \n\t\t|
1.00 | \n\t\t\t28.9 | \n\t\t\t0.6 | \n\t\t\t0.82 | \n\t\t\t198 | \n\t\t\t8.10 | \n\t\t\t4.70 | \n\t\t\t0.65 | \n\t\t\t3388 | \n\t\t\t2.41 | \n\t\t
Impedance and corrosion parameters of AZ31E electrode as a function of concentration for Cl-, F-and PO
In chloride or fluoride additive solutions, the total resistance (Figure 12), Warburg resistance and 1/C decreases with increasing its concentrations. As stated previously, this is due to the deleterious effect of chloride ions [10]. For F-ions, an oxidation reaction occurred in the formation of MgF2 as follows:
Since Mg(OH)2 was not stable in acidic solution [25], reactions should occur as follows:
The overall reaction occurred as follows:
The pores in the film should be generated by the hydrogen evolution. These pores might be decreased or filled by the precipitation of MgF2 particles [25], thus the presence of fluoride ions decreases the corrosion of the tested alloy than the blank (0.01 M oxalic acid). However, depassivation process occurs by increasing fluoride concentration due to breakdown of the formed grained layer of MgF2 that leads to drastic increase in the surface roughness. Furthermore, in presence of F-ions, aluminum which becomes enriched in the surface can form the soluble complex (AlF6)3-, thereby, participates at higher F-ions concentrations in decreasing the stability of the passive surface film on AZ31E alloy [14]. However, Cl-ion is more strongly adsorbed on the alloy surface than F-ions, so, its resistivity is lower than fluoride ion.
For phosphate anion as additive, increasing the total resistance (RT) (Figure 12), W and 1/C1 with increasing of phosphate concentration indicates that interaction between oxalic acid and phosphate forms phosphate complexes that increase with increasing phosphate concentration and leads to passivation of AZ31E surface. Also, by measuring the pH of the medium, it increases slightly from acidic ~ 6.8 to basic medium reaching to 11.1 at 1.0 M phosphate concentration, leading to passivation. At pH 11.1, HPO
Variation of RT of AZ31E electrode as a function of concentration for oxalic acid and Cl-, F-or PO
Impedance results are in good agreement with polarization data.
The Potentiodynamic polarization behavior of the AZ31E electrode was studied in relation to concentration of oxalic acid electrolyte. Figure 13 shows the scans for the tested electrode in 0.01 M oxalic acid solution with different concentrations (0.01-1.0 M) of PO
Potentiodynamic polarization scans of AZ31E electrode as a function of concentration for PO
On increasing the concentration of oxalic acid, an increase in the corrosion current density was observed (Figure 14). This may reflects the changing of the nature of the film formed on the surface (may represents the replacement of MgO by Mg2C2O4).
Variation of logarithm of corrosion current density (icorr) for AZ31E electrode as a function of concentration for oxalic acid and Cl-, F-or PO
The effect of added Cl-or F-or PO
Generally, for comparing corrosion rate obtained from Tafel and EIS measurements, it is well known that the polarization resistance
\n\t\t\t\t | \n\t\t\t\n\t\t\t\t | \n\t\t\t\n\t\t\t\t | \n\t\t\t\n\t\t\t\t | \n\t\t\t\n\t\t\t\t | \n\t\t\t\n\t\t\t\t | \n\t\t\t\n\t\t\t\t | \n\t\t\t\n\t\t\t\t | \n\t\t
\n\t\t\t\t | \n\t\t\t\n\t\t\t\t | \n\t\t\t\n\t\t\t\t | \n\t\t\t\n\t\t\t\t | \n\t\t\t\n\t\t\t\t | \n\t\t\t\n\t\t\t\t | \n\t\t\t\n\t\t\t\t | \n\t\t|
Cl-\n\t\t\t | \n\t\t\tblank | \n\t\t\t2.10 | \n\t\t\t109.4 | \n\t\t\t2.50 | \n\t\t\t31.7 | \n\t\t\t7.24 | \n\t\t\t0.72 | \n\t\t
0.01 | \n\t\t\t20.0 | \n\t\t\t14.28 | \n\t\t\t0.33 | \n\t\t\t13.4 | \n\t\t\t21.3 | \n\t\t\t0.31 | \n\t\t|
0.25 | \n\t\t\t14.3 | \n\t\t\t19.41 | \n\t\t\t0.45 | \n\t\t\t16.7 | \n\t\t\t16.7 | \n\t\t\t0.38 | \n\t\t|
0.50 | \n\t\t\t10.5 | \n\t\t\t26.16 | \n\t\t\t0.59 | \n\t\t\t20.6 | \n\t\t\t13.4 | \n\t\t\t0.47 | \n\t\t|
1.00 | \n\t\t\t6.70 | \n\t\t\t41.1 | \n\t\t\t0.93 | \n\t\t\t25.1 | \n\t\t\t10.9 | \n\t\t\t0.57 | \n\t\t|
F-\n\t\t\t | \n\t\t\tblank | \n\t\t\t2.10 | \n\t\t\t109.43 | \n\t\t\t2.50 | \n\t\t\t31.7 | \n\t\t\t7.24 | \n\t\t\t0.72 | \n\t\t
0.01 | \n\t\t\t23.8 | \n\t\t\t18.93 | \n\t\t\t0.43 | \n\t\t\t10.8 | \n\t\t\t41.5 | \n\t\t\t0.25 | \n\t\t|
0.25 | \n\t\t\t21.3 | \n\t\t\t21.44 | \n\t\t\t0.49 | \n\t\t\t11.2 | \n\t\t\t40.8 | \n\t\t\t0.26 | \n\t\t|
0.50 | \n\t\t\t18.6 | \n\t\t\t25.57 | \n\t\t\t0.58 | \n\t\t\t12.1 | \n\t\t\t39.5 | \n\t\t\t0.28 | \n\t\t|
1.00 | \n\t\t\t15.8 | \n\t\t\t27.07 | \n\t\t\t0.62 | \n\t\t\t14.0 | \n\t\t\t30.6 | \n\t\t\t0.32 | \n\t\t|
PO4\n\t\t\t\t3-\n\t\t\t | \n\t\t\tblank | \n\t\t\t2.10 | \n\t\t\t109.43 | \n\t\t\t2.50 | \n\t\t\t31.7 | \n\t\t\t7.24 | \n\t\t\t0.72 | \n\t\t
0.01 | \n\t\t\t17.0 | \n\t\t\t41.98 | \n\t\t\t0.96 | \n\t\t\t30.0 | \n\t\t\t23.8 | \n\t\t\t0.69 | \n\t\t|
0.25 | \n\t\t\t20.1 | \n\t\t\t32.36 | \n\t\t\t0.74 | \n\t\t\t15.8 | \n\t\t\t41.2 | \n\t\t\t0.36 | \n\t\t|
0.50 | \n\t\t\t24.2 | \n\t\t\t8.391 | \n\t\t\t0.19 | \n\t\t\t3.50 | \n\t\t\t58.1 | \n\t\t\t0.08 | \n\t\t|
1.00 | \n\t\t\t28.9 | \n\t\t\t5.883 | \n\t\t\t0.13 | \n\t\t\t2.41 | \n\t\t\t70.8 | \n\t\t\t0.06 | \n\t\t
Corrosion rate (Pi) calculated from EIS and Tafel methods of AZ31E electrode as a function of concentration for Cl-, F-and PO
As given in Table 6, it can be seen that evaluated Rp values obtained from Tafel measurements have the same trend as RT obtained from EIS measurements. By calculating icorr from EIS measurements using cathodic, anodic slopes and RT, it was found that they also have the same trend as that obtained from Tafel measurements. By calculation of corrosion rate, where icorr (mA cm-2) is related to the average corrosion rate in mm/y (Pi) using [4]:
It was found that corrosion rate obtained from EIS method is comparable with that obtained from Tafel extrapolation method. Thus there is a good agreement between corrosion rates determined by both techniques.
The corrosion rate of magnesium alloy in aqueous ethylene glycol depends on the concentration of the solution. A diluted ethylene glycol solution is more corrosive than a concentrated one at room temperature. Ethylene glycol solution containing Cl-> 0.05 M or F-< 0.05 M are more corrosive than the blank (30% ethylene glycol-70% water). However, at concentrations < 0.05 for chloride or > 0.05 M flouride ions, some inhibition effect has been observed. The corrosion of AZ91D alloy in the blank can be effectively inhibited by addition of 0.05 mM paracetamol that reacts with AZ91D alloy and forms a protective film on the surface at this concentration.
The corrosion rate of AZ31E magnesium alloy in oxalic acid solution depends on the concentration of the solution and the additive. A concentrated oxalic acid solution with lowest pH and highest hydrogen evolution is the more corrosive one. Oxalic acid solution of 0.01 M concentration containing Cl-or F-are more corrosive with increasing the concentration from 0.01 to 1.0 M for the anions as observed from impedance or polarization techniques. For PO
The granting of industrial property (IP) assets should be based on two central and interrelated principles: quality and efficiency. An efficient system to ensure protection of IP rights is basically bound to the time taken to execute the granting procedures, but also to the clarity and organization of the analysis performed during the technical examination. On its turn, quality is usually bound to the standardization and improvement of administrative proceedings, providing reliability and legal certainty in decisions.
As to the granting procedures and time for granting industrial property rights, the Brazilian National Institute of Industrial Property – INPI-BR has been using its efforts to significantly reduce and adjust the granting time taken by the Institute to the average of major international offices. Among its actions, we note the implementation of the so-called “backlog combat plan” announced still in 2019, which is already in effect and expected to be in place until 2021 [1]. It is also worth highlighting the results and efforts regarding the time taken by the Institute to register trademarks, leading to the inclusion of INPI-BR among the signatories of the Madrid Protocol [2].
Over the last decades, INPI-BR has been incorporating to its Strategic Plan several initiatives related to the quality of its applications/registrations. The Strategic Plan 2018-2021 [3] provided for partnerships, cooperation agreements with international offices, improvement of prioritized examination programs, implementation and review of patent examination guidelines, among other activities. As to the technical cooperation initiatives, we note a recent strategic partnership between INPI-BR and the European Patent Office – EPO that includes training, discussion of best practices, sharing of tools, and exchange of patent databases [4].
It is important to highlight that there are studies [5, 6, 7] showing that changes in the workload of examiners can affect the quality of the examination process and its results, suggesting that a factor with high potential of causing instability in the applications/registrations and discrepancies in the decisions of a patent office is the unbalanced workload of patent examiners, i.e., an uneven distribution of patent applications among them. Additionally, it is also relevant to highlight that a specific study [8] using automatically data related to INPI-BR applications showed that the volume of patent applications can be used as a measure of examiner’s workload, and suggests that claim’s pages is probably a key workload indicator. Such facts become even more relevant since INPI-BR currently does not apply a well defined application distribution method, and the decision/responsibility for distribution is on behalf of the team leaders, who are somewhat free to apply their own criteria.
Thus, due to the importance of the subject for INPI-BR itself, specifically for the Patent Directorate of the Brazilian National Institute of Industrial Property – DIRPA, and to the scarcity of studies on methods for analyzing and distributing patent applications to the examiners, aiming at balancing the workload in an optimized manner, the development of a method in this regard would be a great contribution to the efficiency and quality of patent examination, being an important element to fulfill the mission of international Intellectual Property offices in general.
The Brazilian Industrial Property Law (LPI) [9], in its chapter III – article 19, defines that a patent application shall include: application; description; claims; figures, if any; abstract; and proof of payment of the application fee. Therefore, disregarding the abstract, which is usually limited to a single page, a patent application is basically composed of three major parts: description, patent claims, and figures (whenever necessary). We note that these three main parts have specific shape and content characteristics that should be evaluated in more details.
Regarding the description, article 24 of the LPI provides that: “The description shall describe the object clearly and sufficiently, as to enable reproduction by an expert, and indicate, when applicable, the best mode of execution.”.
Thus, the description includes the details of the applicant/inventor’s invention, clearly explaining its practical implementation to third parties and a person skilled in the art. Consequently, it is one of the most relevant parts of the patent application and is expected to have more pages. Therefore, the number of pages of description of a patent application is a variable relevant to its evaluation.
Regarding claims, article 25 of the LPI provides that: “The claims shall be based on the description, describe the particularities of the application, and provide a clear and accurate definition of the subject matter of the protection”.
We note that, within a same patent claim’s section, the claims may be classified as independent or dependent. Independent claims seek to protect essential and specific technical characteristics of the invention as a whole, while dependent claims are those that, while keeping the unity of invention, include all features of other previous claim(s) and define details of these characteristics and/or additional characteristics not deemed essential to the invention [10].
Therefore, according to the comprehensive content in the description, the claims specify, on a more accurate basis, the object of protection, i.e., define the scope of protection. In a recent study [11], the role of the characterizing term (the expression “characterized by”) in the patent documentation for delimitation of industrial property rights is discussed in more details considering the history of the Brazilian and international legal framework.
In this context, we note that both the extent of the claims (number of patent claim pages) and the number of claims (total number of independent and dependent claims) are highly relevant to the examination of a patent application.
As provided for in article 19 of the LPI, the submission of drawings/figures in the patent application is optional. While the figures are not mandatory, we note that the majority of applicants and inventors include them in the documentation submitted for examination. Such fact points that figures are an important part of the patent application, and one of the main reasons therefor is that they facilitate reading and understanding of the subject matter under examination. Hence, the number of figures pages can also be relevant when examining a patent application.
Information included in patent documentation (including bibliographic data in the cover sheet) is an important tool for technological research and development [12]. It is important to note that information included in the cover sheet of a patent document is identified by numeric codes, as the Internationally Agreed Numbers for the Identification of Data (INID), and its specific standards are defined by the World Intellectual Property Organization – WIPO.
Among the bibliographic data included in the cover sheet, we highlight: application number (21), number of the priority document, if any (31); filing date (22); priority date, if any (32); date of publication (43); name of the inventor (72); name of the holder of the rights on the patent (73); International Patent Classification (51); title of the invention (54); and abstract (57). A detailed description of these codes can be found in Appendix 1 of Standard ST.9 of the WIPO Handbook on Industrial Property Information and Documentation [13].
In this context, it is important to highlight that, as we intend to obtain variables relevant for evaluating and distributing patent applications for examination, among these bibliographic data, we are only interested in those already available from the filing until publication of the application, i.e., those that can be obtained before the patent examination process. Thus, in a first analysis, we focus on the identification numbers of the applications, filing date/year, inventors, priorities, and international patent classification (IPC), provided that the latter will be addressed in further details below.
The IPC [14] allowed for standardization of documents from different countries with different languages and technical expressions. Pursuant to WIPO, it has an important role as it serves as: (i) an instrument for the orderly arrangement of patent documents aiming to facilitate access to the technological and legal information contained therein; (ii) a basis for selective dissemination of information to all users of patent information as a reference and/or knowledge; (iii) a basis for investigating the state of the art in given fields of technology; (iv) a basis for the preparation of industrial property statistics which in turn allows the assessment of technological development in various areas [15].
The IPC is divided into eight sections (A, B, C, D, E, F, G, and H). The sections are the highest levels of hierarchy of the classification. Each section is subdivided into classes, representing the second hierarchical level of the classification. Each class comprises one or more subclasses, indicating the third hierarchical level of the classification. Each subclass is broken down into subdivisions, referred to as “groups”, which are either main groups (fourth hierarchical level of the classification) or subgroups (lower hierarchical levels dependent upon the main group level of the classification). We present below an example classification of the electricity area by using all hierarchical levels, from section to subgroup.
Example: H02M 7/48.
Where:
H Section (A, B, […], H): Electricity;
H02 Class (two digits): Energy Production, Conversion, or Distribution;
H02M Subclass (one letter): Apparatus for Conversion Between DC and AC;
H02M7 Main Group (one or more numeric digits): Conversion of AC power input into DC power output;
H02M7/48 Subgroup – (at least two numeric digits): using discharge tubes with control electrode or semiconductor devices with control electrode.
We highlight that the IPC is revised periodically based on meetings with experts from WIPO member countries, and such revision is published and may be accessed through INPI and WIPO websites. We further highlight that a patent document may fall under more than one IPC symbol. This is due to the fact that it can have claims in more than one category (device and method, for example), be related to one or more areas of application, or even to specific functions.
The study of Harloff and Wagner [16], based on EPO data for modeling the examination time, defined that, among other factors that impact the complexity of a patent application, the total number of claims and the number of IPC subclasses are major direct variables of the application. Therefore, the number of IPC subclasses is also a variable to be considered when evaluating a patent application to be distributed.
As seen previously, a patent application is basically composed of three main parts: description, claims and figures (if any). For description and figures, for example, the number of pages is a relevant variable. As for patent claims, the number of pages, number of claims, whether independent or not, etc. Additionally, bibliographic data present information that also become potentially relevant variables, such as IPC classification, inventors, filing dates and years, etc. In this context, there are some papers that use specific variables of patent documentation to determine specifications like: economic value, time effort applied to the technical evaluation, scope of patent protection, among others.
An economic value approach to European patents using their claims, references, among others as variables, is described in [17].
Other papers [18, 19] are related to methods for analyzing and assessing the scope of protection of a patent based on variables related to the patent claim scope. The first uses the number of pages of the first independent patent claim as a relevant variable. The second uses two variables: the number of words in the shortest independent patent claim and the total number of independent claims.
However, none of the papers mentioned address the use of the parameters of the patent application or data in the examination process to create a method for distributing the applications to examiners. In [20, 21], studies were carried out with evidence that, at the United States Patent and Trademark Office –USPTO, after the application was directed to a large technological area (for example, electricity or chemistry), its subsequent designation to a specific examiner was nearly random. On the other hand, [22] found evidence that, at USPTO, applications of the same applicant, as well as applications with similar abstracts and titles, tend to be distributed to the same examiner. The authors suggest that, although such methods seek to follow the principle of efficiency, a balance with the principle of justice should be pursued as well. On the other hand, they emphasize that a random distribution favors the principle of justice, but fails to follow the principle of efficiency, which counts on the expertise of the examiners in certain examination subclasses.
In view of the foregoing, one has to take into account not only factors contributing to efficiency, such as distribution of application by subclasses pursuant to the examiners’ education/interest, but also factors contributing to better balance, i.e., variables including the amount of data and the complexity of the patent applications to be examined. Consequently, justice should not be confused with randomness.
As already seen, the workload in each patent office is one of the indicators affecting the quality not only of patent examination, but of patent systems as a whole. It is also worth mentioning that the increased workload of examiners, and the consequent decrease in time for examining a patent application, may adversely affect the quality of patents granted, i.e., it tends to increase the granting of improper patents. Thus, it is important to seek better workload distribution and balancing to the examiners, as to reconcile working conditions and results.
Papers [23, 24] show that the volume of patent applications at EPO has been increasing throughout the years, and they relate the volume of patent application to an essentially two-dimensional problem, with two predominant variables: total number of pages of the patent application and number of claims. In this context, the total number of pages would be related to the level of description of the invention at stake and the total number of claims to protection scope. The authors also emphasize that these variables would be correlated, in different proportions, to the number of priorities, inventors, and IPC classifications. As limitations to the study, they mention that it would be better to evaluate the amount of independent and dependent claims, although this information is not easily accessible in data sources available.
To assess the hypothesis of technological complexity of a patent application, another study [25] uses a mathematical model considering the number of inventors, the number of IPC classes, and the number of references to previous patents. The authors emphasize that the increased volume of data may be related to both the technical complexity of the invention/application and a strategy matter, i.e., the desire to maintain certain know-how rather than actually protect it. It is important to highlight that, with the results of the model applied, the authors suggest that an increased number of inventors tend to create more complex inventions, requiring a greater number of pages and claims so that such inventions are described in details.
When the examiner receives a new patent application for examination, it is clear that the first step, which may takes a longer time, is reading the application. In principle, as the examiner needs to carefully read the entire application and see the figures, further confirming if the claims are based in the description and if the matter is sufficiently described so that a third person skilled in the art can execute it, the relevant variable to be considered in this step is the application’s total number of pages.
Upon the Initial Technical Analysis, the examiner should carry a prior art search aiming at determining the state-of-the-art closer to the matter claimed. For the searches, the examiner should basically consider the patent claim scope, more specifically its independent claims. Additionally, if the claims include several specifications and are quite extensive, an even greater effort shall be employed. Finally, the greater the number of classifications in the application, the greater the tendency to address more than one technological area or borderline regions, which can also cause the search to be even more complex. Thus, the number of independent claims, the number of pages of the patent claims, and the number of subclasses of the application may also be variables to be considered in this step.
Upon searches and determination of the useful prior art for examination, the third major step is the comparison between the matter claimed and the knowledge presented in the state-of-the-art, i.e., analysis of the patentability. This third step is hereinafter referred to as Specific Technical Analysis. Upon analysis of patentability, a detailed examination of the independent claims in the application is mandatory. Thus, the first relevant variable in this step will be the number of independent claims. As in the searches, if the claims are quite extensive and have several technical specifications, the effort applied will be greater. So the number of claim pages is also a relevant variable in this step. As in some cases, dependent claims are also analyzed in details, the possibility of using the number of dependent claims is considered, and, in this case, the total number of claims could be used as a variable of interest.
Twelve possible variables were initially identified to be used in this paper: number of pages of description (Variable 1); number of claim pages (Variable 2); number of pages of figures (Variable 3); number of third parties observation pages (Variable 4); number of independent claims (Variable 5); number of dependent claims (Variable 6); number of IPC subclasses (Variable 7); year of filing (Variable 8); number of inventors (Variable 9); number of priorities (Variable 10); number of references to the state-of-the-art in the patent document under examination (Variable 11); number of references to the patent document under examination in other patent documents (Variable 12).
Upon identification of the possible variables of interest, the following additional criteria were established for selecting study variables:
moment of availability of the variable - as the main objective is to evaluate the document for later distribution for examination, only variables accessible from filing until publication of the patent application will be selected;
reliability and efficiency - variables failing to provide full reliability in data obtained, which may require the use of more than one platform/database and/or which require a very long time to be obtained, which could greatly increase the complexity of the model or even render its practical application unfeasible, will not be selected.
It should be noted that most of patent applications filed in INPI only include references to the state-of-the-art after a first examination, i.e., after the application has already been distributed, and references to other documents would still require access to more than one database. In this context, these variables are not deemed to fully meet the criteria of “moment of availability” and “reliability and efficiency”. Thus, at first, the variables related to references will be disregarded, hence ten variables will be used to obtain data samples, which are: number of pages of description (Variable 1); number of claim pages (Variable 2); number of pages of figures (Variable 3); number of third parties observation pages (Variable 4); number of independent claims (Variable 5); number of dependent claims (Variable 6); number of IPC subclasses (Variable 7); year of filing (Variable 8); number of inventors (Variable 9); and number of priorities (Variable 10).
Based on the studies carried out with EPO data on voluminosity (volume of data) of a patent application, it appears that the volume of data that the examiner needs to deal with during the examination of a patent application is one of the main constraints on examination effort/time. Additionally, such studies indicate that voluminosity is a problem related to two patent application variables: total number of pages and total number of claims. Thus, a first assumption will consider that the volume of data of a patent application can be represented by the variables with the greatest positive correlation with the total number of pages of the application and/or with the total number of claims. Initial hypothesis 1 is that there are five variables directly bound to the volume of data: number of pages of description, claim pages, and pages of figures, in addition to the number of dependent and independent claims.
On the other hand, although most of the examination effort is bound to the direct volume of data that the examiner deals with, it is possible to note that there is still the hypothesis of existence of complementary variables, bound to an indirect and more subjective complexity, specifically related to the patent application itself, the applicants’ strategy, or even particularities of the examination process. In this context, there are some variables suggested in the studies carried out; however, there is no consensus by the authors or in the studies carried out revealing the exact influence of each of them, if any. Initial hypothesis 2 is that there is, even if reduced, indirect influence of the other abovementioned variables.
The proposed methodology aims at creating a model capable of evaluating the complexity and volume of patent applications, in addition to a new fair and efficient manner of distributing patent applications to patent examiners. For this, it is necessary to obtain the application data with its variables of interest, evaluate patent applications according to the selected variables, create a specific logic for this distribution, and, finally, evaluate the new proposed logic compared to the original distribution. Thus, the proposed method can be divided into four main parts, which complement each other and will be detailed below.
We obtained data from applications that already went through the first examination step during two years, in the area of electricity, more precisely from May 2015 to May 2017, month in which the research was initiated. By identifying and selecting the variables, the proposal was to tabulate data from all patent applications analyzed, including all relevant variables selected, and identify the patent examiner who received the application for analysis. These data were defined as the Initial Test Sample and, based on it, the IPC for the sample patent applications and, consequently, the specific area of expertise (ZAE) of each examiner were then identified.
As this is a problem with multiple variables of interest, we attempted to find a multivariate analysis method to solve it. The bibliographic review was made to choose a method that meets the following criteria:
did not limit the number of variables used;
was based on a pair correlation analysis of each variable in order to enable a specific analysis of their relations;
in case of a high number of variables, allowed for reduction of the size of the problem, i.e., to reduce the number of variables (n) to other components or variables (x), with x < n, without significant loss of data or of information about the problem to be resolved; and
was mathematically and statistically robust and scientifically tested in many different fields of knowledge.
Given the established criteria, the method of principal component analysis (PCA) was selected as the basic tool for evaluation of patent applications. Such method allows for determination of such principal components of the specific problem according to the share of general variance explained by each of the components. Following identification of these new components, a General Complexity Ratio (IGC) is proposed for the patent applications, which is the ratio of the weighted sum of the most significant components plus their eigenvalues to the sum of the eigenvalues themselves, which were obtained from the correlation matrix of the original variables of the problem. Based on these ratios for each of the applications, these were classified into up to five classes (Very Light, Light, Moderate, Heavy, and Very Heavy) according to the average and the standard deviation of the general ratios obtained. It is important to highlight that the eigenvalues and eigenvectors were determined both manually and with the assistance of the software Matlab and of the Matrix Calculator (Available at https://matrixcalc.org/pt/vectors.html), and the other steps were executed using Excel electronic spreadsheets (Microsoft Office 2010).
After choosing the method, determining the ratios and the classification of the applications into classes, the next step is a sensitivity analysis/validation of the ratios and classification of the patent applications. For this step, an experimental/empirical research is proposed, aiming to establish a correlation between the ratios and classifications found and the time/effort to exam the patent applications. First, the substantive process of patent examination by INPI and the standard examination report were analyzed in order to identify the main examination steps and directly or indirectly related variables. Based on these main examination steps, a form was prepared to survey the time for examination, to be filled up by the examiners, in which information about the time to execute each step is inserted. Thus, a list of applications is determined, hereinafter referred to as Standard Sample, with tabulation of data, including all the variables of interest in addition to the time for examination. The PCA method will then be applied to this new sample, and the IGC ratios for each patent application will be calculated, in addition to their classification into classes. In this context, the correlation between the ratios obtained and the time for examination will be verified, and the PCA method will be applied, including several simulations with variations in the sample size and in the number of variables. This procedure aims at showing the variables with direct impact on the time for examination and the representativeness of the IGC regarding these variables, evaluating the minimum necessary sample size, and also testing the applicability of the PCA method.
In this 3rd part of the proposed method, a specific logic for distribution of applications was built based on the previously obtained classification into the five classes, and also on the classification of the application according to the IPC. Data obtained from the patent applications were separated by main IPC subclasses, and so, the main subclasses examined by each examiner were identified, as well as their ZAE was determined. This area was obtained considering the subclasses of patent applications with occurrences above 5% of the total examinations by each examiner evaluated based on the largest sample obtained, the Initial Test Sample. Thus, a new logic of distribution of patent applications is proposed according to the classification of the general ratios and to the ZAE, considering the following criteria:
Very heavy and heavy applications shall be equally distributed among the examiners;
Very heavy and heavy applications shall be compensated, respectively, with distribution of very light and light applications;
The remaining moderate applications shall be distributed;
In all previous steps, patent applications shall be distributed considering the ZAE determined for each examiner.
In the fourth and last part of the proposed method, first a new sample of more recent patent applications was obtained, hereinafter referred to as the Final Redistribution Sample. Patent application data were obtained from the same examiners in the field of electricity that made up the Initial Test Sample, however, with the first examinations carried out between May and July 2020. It is important to note that, after the backlog combat plan was implemented by INPI, the examination process has somewhat changed for most of the patent applications in the area of electricity. Hence, obtaining this redistribution sample was necessary to harmonize the examination process carried out by the examiners evaluated therein with the process implemented by the examiner, from which the Standard Sample with time was obtained. This harmonization was made using standard samples with time and redistribution samples containing the same type of patent applications, in other words, patent applications that may be examined using data from previous searches by international offices. It is important to note that this type of application covers an average of 88% of the total stock of patent applications filed until 2016 in the field of electricity.
Based on this new sample, we apply the proposed model and logic for distribution, and then calculate a Distribution Balancing Ratio (IBD) both for the original distribution and for the new distribution, a ratio that ranges from zero to one, and considers the differences between the medians of the variables of each examiner’s samples and the general medians of the division’s variables. Within this context, it should be noted that the closer the medians of the variables of the examiners’ individual samples are to the general medians of the division’s variables, the larger the amount of the IDB is and, consequently, the better balanced the distribution is. The breakdown of the IBD, including explanations and analyses about its formula, maximum and minimum limits, will be presented in item 4 – Development.
The principal component analysis is a multivariate statistics technique focused on explaining the variance–covariance structure of a set of data, and its main objectives are the reduction of the dimensionality of the problem and the better interpretation of data [26, 27, 28]. Still according to [27], the PCA usually reveals relations that would not have been previously identified only with an analysis of the original set of data and variables, enabling a more comprehensive interpretation of the study phenomenon.
To examine a patent application, several measured variables of each patent application of the study population should be considered. The proposal of the principal component analysis method is to apply a transformation to such variables, so that the new components obtained enable a better breakdown and analysis of the elements of such population. In [29], it is shown that this new look has great value when it comes to creating a typology for the population, classifying the elements according to certain criteria, etc. According to Vicini [30] “In practice, the algorithm is based on the variance-covariance matrix, or on the correlation matrix, from which the eigenvalues and eigenvectors are extracted” and “finally, writing the linear combinations, which will be the new variables, referred to as principal components”.
It is important to note that the PCA is widely employed, evidencing its efficiency and robustness in applications in several fields of knowledge, such as agronomy, zootechnics, medicine, among others [31, 32, 33, 34]. Examples of practical applications of the PCA for evaluation of public services in Brazilian states, assessment of the regional development of cities in the Brazilian state of Santa Catarina, as well as analysis of crime statistics in U.S. states can be found, respectively, in the papers [35, 36, 37].
The following steps are necessary for determining the principal components:
create an original data matrix Xij of size n x p in which the columns (j = 1, 2, …, p) are the original variables of the problem and the rows (i = 1, 2, …, n) are individuals in the population (in our case, each patent application);
standardize the original variables so all of them have mean equal to zero and standard deviation equal to one, avoiding the influence of different orders of magnitude and obtaining a new data matrix Zij;
calculate the variance–covariance matrix (S) and the correlation matrix (R) which, in case of standardized variables, will be equal;
find the eigenvalues of the matrices and their corresponding eigenvectors;
select the components calculating linear combinations of original variables with the eigenvectors of the correlation matrix.
Eqs. (1) and (2) below show, respectively, the calculation for standardization of the variables and matrix Z of standardized variables.
Where: Xij is the element of the original data matrix; μp is the average of variable p, being p = j; and δp is the standard deviation of variable p, being p = j.
Eqs. (3)-(5) below show, respectively, the calculation of the variances, covariances, and matrix S.
Where: VAR [Zj] is the variance of the standardized variable Zj; COV[Zj; Zj’] is the covariance of the standardized variables Zj and Zj’; n is the number of individuals; μj and μj’ are, respectively, the average of the standardized variables Zj and Zj’; and Zjk are the data matrix elements.
Eqs. (6) and (7) below allow for determination of the eigenvalues and eigenvectors of matrix S and, so, matrix V of eigenvectors of S is determined according to Eq. (8).
Where: S is the Variance–Covariance matrix of pxp dimension of standardized data;
Upon acquisition of the eigenvectors associated with eigenvalues in a descending order, the principal components (Y1, Y2, …, Yp) for each of the n individuals under analysis is determined through a linear combination between the standardized variables and the eigenvalues calculated. Therefore, we can then write the components of individual n in the form of the following equation:
Where: i ranges from 1 to p; Yi (n) is component i of individual n; Zip are the elements of matrix Z of standardized variables; and vpi are the elements of the eigenvectors calculated.
It is important to highlight that in the PCA, the contribution of each principal component (Y1, Y2, …, Yp) is measured in terms of its variance. Thus, it is possible to calculate that contribution considering the relation between the variance of the component under analysis and the sum of the variances of all components, resulting in the proportion (or percentage) of total explained variance to each of the components. Eq. (10) below shows how to calculate each contribution Ci (C1, C2, …, Cp).
Where: Ci is the contribution or total % variance explained by component Yi; VAR(Yi) is the variance of principal component Yi;
It should be noted that further details about the PCA formal mathematical statements and its properties, as well as about all linear algebra used, may be consulted throughout the already mentioned works [26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37].
Kaiser’s [38] is the most used criterion to date. According to such criterion, only components associated with eigenvalues with ranges wider than the unit are considered principal components, i.e.:
A second option is to perform a graphic analysis and verify greater differences among the consecutive eigenvalues. The Cattel [39] criterion, for example, suggests a graphic representation of the range of eigenvalues based on the number of eigenvalues, arranged in an ascending order. The number of components would be selected based on the breaking point of the graph. This breaking point occurs when there is a slump in the range of eigenvalues [40].
A third possible criterion, also quite disseminated, is to use a reference value for the proportion of variance explained by the principal components. Following this logic, the principal components whose cumulative percentage of explained variance exceeds such reference value shall be selected. It is important to highlight that there is no consensus among researchers about which percentage should be used, and there are several practical examples. A great part of the applications uses the limit of 70%. In [40], the problem was ranked in levels of acceptance, and amounts between 62 and 80% were considered reasonable or “partially good”.
Although each criterion has advantages and disadvantages, in this paper a combination of the three above-described criteria was adopted. As a reference value for the third criterion, we believe a percentage of explained variance starting at 60% is a suitable amount for selecting the most representative principal components.
Hongyu et al. [31] also states that “In order to establish a ratio that enables us to order a set of n objects, according to a criterion defined by a set of m suitable variables, it is necessary to choose the weights of the variables so that they translate information contained in them,” provided that, to create a ratio as a linear combination of variables, “it is desirable that this ratio includes the maximum possible information of the set of variables selected for study”. According to Sandanielo [41] (
In this context, this paper intends to, in a first evaluation, use a ratio in one dimension based on the most significant principal components (carefully selected using the selection criteria addressed in item 4.2), weighted by their corresponding eigenvalues. Hence, a General Complexity Ratio (IGC) is defined for the patent applications to be evaluated, according to the following equation:
Where: Yi are the principal components calculated,
To group data according to the IGC ratio calculated, the first step was to standardize the original values using Eq. (1) and, therefore, the standard deviation of the IGC sample will always be equal to one. Based on IGC data for all patent applications under examination, classification ranges were then defined as shown in Figure 1.
Classification of the patent applications into classes.
After calculating the IGC ratio and classifying the applications, the complete model for evaluating patent applications is created. A diagram of the model is presented in Figure 2.
Diagram of the model.
Thus, the next step is to enable its evaluation through a sensitivity analysis and through the correlations with time for examination/analysis of the application. This evaluation will happen through preparation of a form regarding the time for examination in order to obtain a new Standard Sample of patent applications with time, in addition to several simulations considering different numbers of variables and sample sizes. Figure 3 shows the template form developed.
Time for examination form.
After classifying all applications to be distributed during the selected period, an iterative sequence of steps for their distribution is then proposed, seeking to prioritize the choice of applications based, whenever possible, on the IGC classification of each application being distributed, in addition to the ZAE of each examiner.
Verify the Main IPC Subclass in which the Current Application falls:
i. If the Current Application pertains to the Current Examiner’s ZAE, then select the Current Application and proceed to Step 2;
ii. If there is no application pertaining to the Current Examiner’s ZAE, look for the next application in line that does not pertain to any other Examiner’s ZAE and, only after that, proceed to Step 2.
Check the Current Application Classification (Very Light, Light, Moderate, Heavy, or Very Heavy):
i. If an Application with the same Classification has not yet been distributed to the Current Examiner, then distribute the Current Application and proceed to Step 3;
ii. Otherwise, search for the next available Application and return to Step 1.
Repeat Steps 1 and 2 until an Application with each Classification is distributed to the Current Examiner.
Go to the next Examiner on the list and perform Steps 1 to 3.
Repeat Steps 1 to 4 until there are enough Applications in each of the Classifications:
i. If there are no more applications with any of the Classifications, repeat Steps 1 through 5 for the remaining Classifications until there are no more Applications available for distribution.
In order to evaluate the distribution of the patent applications, a new data sample was obtained, referred to as Final Redistribution Sample. As the Standard Sample (with time) used to validate the model was obtained using examination data that, on their turn, were also based on international searches, this new redistribution sample was necessary to harmonize the examination process carried out by the examiners evaluated therein with the process implemented by the examiner, from which the Standard Sample with time was obtained. Based on this new sample, the proposed model and distribution logic are applied, and a Distribution Balancing Ratio (IBD) is then calculated, both for the original distribution and the new one, according to Eq. (12):
Where:
In a first analysis of the IBD equation, it can be verified that the ratio seeks to capture and measure the influence of the differences between the medians of the variables of each examiner’s samples and the general medians of the division’s variables (complete sample). It is important to note that all medians of the variables composing the IBD are normalized (divided) by the general values of the respective medians of the complete sample. With that, we seek to avoid further distortions caused by different orders of magnitude of certain variables.
Additionally, as the several medians calculated can be higher or lower than the respective median of the division, the differences in these values can be positive or negative. Hence, as we wish to obtain an accumulated measurement of all differences in medians with no loss of information and without having a negative deviation in a certain variable compensating a positive deviation in another, we choose to square the differences and then add and extract the square root.
More specifically, when the numerator and the denominator of the IBD equation are analyzed, it can be noticed that both have the same first term, which is the sum of the squares of the normalized medians of all variables of interest from the examiners’ samples. However, the denominator has a second additional term presenting the sum of the squares of the normalized differences between the medians of each examiner’s individual samples and the medians of the corresponding variables from the complete sample.
It is important to highlight that, in an ideal distribution, the medians of the variables from all examiners’ samples would be equal to the medians of the general variables of the division, i.e., the sum of the squares of the differences of the medians (second term of the IBD denominator) would be zero and, consequently, the IBD would be equal 1. On the other hand, a random distribution in which the examiners’ samples have great differences in median values, when compared to the general division medians, would lead to very high denominator values, thus greatly reducing the IBD and, ultimately, making it tend to zero. Thereafter, we have that, the closer the medians of the variables from the examiners’ individual samples are to the general medians of the division’s variables, the greater and closer to 1 the IBD value will be and, consequently, better balanced the distribution will be.
Data were obtained from a total of eleven (11) Examiners from the Electricity Division, to be fully analyzed. For each patent application of such examiners with at least one examination already carried out, all variables of interest were obtained, totaling eight hundred and fourteen (814) patent applications to be evaluated and making up the initial test sample. Data from the Initial Test Sample were standardized according to Eq. (1). Figure 4 shows the structure of data from the initial test sample with standardized data.
Structure of the initial test sample with standardized data.
In the initial test sample, a total number of 95 main subclasses was found over all 814 patent applications analyzed. However, when considering only the examiners’ ZAE (subclasses including 5% or more applications for each examiner), 25 main subclasses were responsible for 636 applications, i.e., about 80% of the total evaluated. It is important to highlight that, given that 3 of such 25 subclasses had very low occurrences, 22 subclasses were used in the set of interest for evaluation, equivalent to 619 applications (76% of total). Figure 5 shows each one of the 11 examiners’ areas of expertise by IPC subclasses. Note that the gray area corresponds to the examiners’ Specific Areas of Expertise (ZAE), while the white area corresponds to subclasses that, despite not being part of the examiner’s ZAE, are part of the ZAE of some of the other examiners evaluated.
Examiners’ areas of expertise by IPC subclass.
Figures 6 and 7 show the results obtained in the PCA.
Eigenvalues and variances.
Weighting coefficients.
By analyzing Figure 6, when using only the criterion considering eigenvalues higher than one, only the first four (4) components would be selected. However, these would be responsible for about 65% of total variance. It can also be verified that the range sharply drops when we get to the eigenvalue of component 6 (0.73). Additionally, the first five components explain a total variance of 75.05%. Hence, these first five components were selected for the next steps.
In Figure 7, the significant factors to each variable (very close to or above 0.4) were hatched in gray. In a first analysis, it can be noticed that component Y1 is quite detached from the others. In addition to explaining virtually 30% of all variance, the component is associated with variables directly related to the volume of data (pages of description, of claims, and of figures, in addition to the number of independent and dependent claims). Such fact is consistent with the initial hypothesis 1, related to the volume variables. As for components Y2 and Y3, although they may be slightly related to the volume of data, they basically represent the influences of variables, year of filing, number of inventors, and priorities. These components appear to be associated with development strategies, management of the applicants, and maturity of the technology involved. On the other hand, components Y4 and Y5 complement the others by being associated with the variables, number of subclasses, and pages of third party observations. Such components appear to represent specific influences of the technological area of the patent applications. This result is consistent with the initial hypothesis 2, related to the variables with complementary or indirect influences.
By applying the proposed redistribution logic, a new configuration of samples by examiner was obtained. Figure 8 shows a comparison between the percentage of applications distributed to each examiner within their ZAE.
Percentage of applications within the ZAE before and after the new distribution.
By analyzing Figure 8, it is possible to note that, for ten out of the eleven examiners, there was a significant increase in the number of applications distributed to them and pertaining to their own ZAE. Only examiner 9 had a small decrease (that could even be corrected with a fine adjustment), due to the fact that his data sample was significantly larger than that of the others. Thus, this new configuration seems to contribute to examiners to work within their specific fields of expertise and knowledge.
Finally, the IBD ratios of the original sample distribution and its redistribution were calculated. Through Eq. (12), an IBD equal to 0.86 for the original case and an IBD equal to 0.88 for the redistribution were obtained, i.e., there was an increase in the IBD with the new distribution, evidencing that the medians of the examiners’ applications after redistribution are closer to the general division’s median. Such fact corroborates the fact that with the new distribution, we have a tendency towards greater balance regarding volume of data/complexity of applications distributed to the examiners.
Similarly to the procedure carried out for the initial test sample, data of patent applications of the technological area regarding electrical engineering were obtained. However, as, in this case, we intend to obtain a standard sample with time to serve as a reference, all data were obtained from the time for examination form filled by a single examiner. For each patent application of such examiner, all variables of interest were obtained, for a total amount of fifty (50) patent applications, with all first actions already published. Data were collected between January and July 2020, with all sample applications using data from previous searches by international offices.
We note that from the ten possible variables to be analyzed, the only one that was not considered in this case was the number of pages of third parties observations, given that there is no application with such document available in the sample.
For the sensitivity analysis of the model, dozens of simulations were performed considering all cases: from the most complete one, with nine variables, to the simplest ones, with three variables. For all cases, simulations for each ten sample applications were performed, i.e., for each set of cases with three to nine variables, tests were performed considering 10, 20, 30, 40, and 50 patent applications of the standard sample. A minimum of ten test applications was chosen, as it is recommended that the sample should have a population at least larger than the number of variables in order to apply the PCA method, provided that the larger the sample, in theory, the best for the model.
When executing the simulations, the correlations of all variables and of the IGC ratios with time were verified, and the IGC was calculated both using the criterion of 70% of the variance, being referred to as IGC70%, and using the criterion of eigenvalues higher than one, being referred to as IGCλ>1. It is important to note that, when IGC70% and IGCλ>1 are equal, we will refer to it simply as IGC. Finally, an IGC related only to the principal component (Y1) of the cases, the most significant component in terms of variance, being referred to as IGCY1, was also calculated.
After executing all the simulations, and having a gamut of results for dozens of cases, the cases of more relevance and interest in terms of analyzed variables and their correlations with time were selected. Namely:
Case 1– Case 9 Var, complete with the nine variables;
Case 2 – Case 5 Var, including only the five variables of direct volume;
Case 3 – Case 4 Var, similar to case 2, but excluding the variable “number of pages of figures” (given that this variable presented lower scores in the PCA and the lowest individual correlation with time among the five of volume);
Case 4 – Case 3 Var, similar to case 3, but aggregating the amount of dependent and independent claims in only one variable (i.e., considering pages of description, claim pages, and total claims); and
Case 5 – Case 3 Var (2), similar to case 4, but replacing the pages of description with the total of pages. Hence, the following variables were considered: total number of pages, claim pages and total claims.
Figures 9 and 10 show the results of eigenvalues and cumulative variances for all the five described Cases.
Eigenvalues of cases 1 to 5.
Cumulative variances of cases 1 to 5.
By analyzing Figures 9 and 10, it is possible to note that:
Case 9 Var: simulations using 10 and 20 applications deviate from the others, and the cases using 30 to 50 applications are almost coincident, i.e., the eigenvalues of the components only tend to be stable starting in the sample with 30 applications. The same phenomenon can be observed by analyzing the cumulative variances of the samples. These results evidence that, for cases with nine variables that are intended to be executed, a sample of at least 30 patent applications, preferably 50 applications, is recommended to obtain better performance of the PCA method;
Case 5 Var: only the simulation using a sample of 10 applications quite deviates from the others; the case using 20 applications shows a slight deviation; and cases using 30 to 50 applications are almost coincident, i.e., the eigenvalues of the components already tend to be stable starting in the sample with 20 applications. The same phenomenon can be observed by analyzing the cumulative variances of the samples. These results evidence that, for cases with five variables that are intended to be executed, a sample of at least 20 patent applications, preferably 30 applications, is recommended to obtain better performance of the PCA method;
Case 4 Var: simulations using 10 and 20 applications slightly deviate from the others, and the cases using 30 to 50 applications are coincident, i.e., the eigenvalues of the components already tend to be quite stable starting in the sample with 10 applications, and very stable starting in 30 applications. The same phenomenon can be observed by analyzing the cumulative variances of the samples. These results evidence that, for cases with four variables that are intended to be executed, a sample of at least 10 patent applications, preferably 20 applications, is recommended to obtain better performance of the PCA method.
Case 3 Var and Case 3 Var(2): all simulations, from samples of 10 to 50 applications, are virtually coincident, i.e., the eigenvalues of the components have excellent stability. The same phenomenon can be observed by analyzing the cumulative variances of the samples. These results evidence that, for cases with three variables that are intended to be executed, a sample of at least 10 patent applications, preferably 20 applications, is recommended to obtain better performance of the PCA method.
Figures 11 and 12 show the results of correlations of the IGC with time.
Correlation of the IGC with the time for examination – cases 1 to 5.
Correlation of the IGC with the time for examination – cases 1 to 5 – By samples.
The analysis of Figures 11 and 12 indicates that:
Case 9 Var: based on a sample with a total of 30 patent applications, there is a slight advantage of correlation with time for IGCY1, and both are very close to the value of 0.8;
Case 5 Var: except for the sample with 20 applications, the larger the sample, the greater the correlation of the IGC with time. On the other hand, upon analysis of the IGCY1, that is, considering only the most significant principal component, basically related to the main direct volume variables, the correlation with time increases significantly, reaching even larger values (0.86). It is also worth to highlight that the correlation of the IGCY1 with time increases a lot when the sample have 20 applications instead of 10; from then on, it seems to stabilize, oscillating around 0.85. This result proves to be consistent with the profile of the eigenvalues and cumulative variances analyzed, reinforcing the need for a sample with a least 20 applications. Finally, a very similar profile is noted in the three curves. Once again, the IGCY1 has better results upon analysis of the correlation with time;
Case 4 Var: the profile of the three curves is quite similar, and, based on the sample with 30 applications, the correlation with time of all ratios gets close to 0.80 and oscillates around that. It is also worth to highlight that both IGC curves show a good correlation with time even based on a sample with only 10 applications, a result that proves to be consistent with the profile of the eigenvalues and cumulative variances analyzed. Finally, it can be noticed that, although the correlation values of the three curves are close to each other, once again, the IGCY1 (in this case also equal to the IGCλ>1) has an advantage over the others;
Case 3 Var: the profile of both curves is quite similar, and, based on the sample with 20 applications, the correlation with time of all ratios gets close to 0.80 and oscillates around that. It is also worth to highlight that both curves already show a reasonable correlation with time even based on a sample with only 10 applications, a result that proves to be consistent with the profile of the eigenvalues and cumulative variances analyzed. Finally, it can be noticed that, although the correlation values of both curves are close to each other, once again, the IGC (in this case IGC = IGC70% = IGCλ>1 = IGCY1) has an advantage.
Case 3 Var (2): based on the sample with 20 applications, the correlation of the IGC with time is always above 0.84. It is also worth to highlight that both curves already show a reasonable correlation with time even based on a sample with only 10 applications, a result that proves to be consistent with the profile of the eigenvalues and cumulative variances. Finally, it can be noticed that this is the case in which the IGC (once again, IGC = IGC70% = IGCλ>1 = IGCY1) has the higher values of correlation with time, so it has an advantage regarding all variables individually. In addition to having a high correlation with time, this is the most indicated case for practical application, because, besides having only three variables and principal components with great stability, it does not require a division of the claims into independent and dependent, which greatly facilitates the data collection.
The analysis of Figures 11 and 12 also indicates that the profile of the curves is quite similar, with an increasing trend for the correlation of the IGC with time in the beginning of all of them, i.e., when the number of variables decreases from nine to five, and, from five to three variables, the curves stabilize. These results reflect the previous analyses that showed that, when only the direct volume variables are selected (with their combinations varying), the trend was for obtaining higher and more stable correlations with time. Thus, although all nine variables of the study may contribute to the complexity of the patent application, in practice, the direct volume variables already represent well the examination effort/time.
It should also be noted that the correlations of the IGCY1 with time remained high and almost constant for any of the cases analyzed with samples with twenty applications or more, showing a quite stable behavior regardless of the sample size. Consequently, for the problem in particular, the results converge showing that the IGCY1 ratio seems more suitable to represent the examination effort/time. The results obtained suggest that Case 3 Var (2) is the one with the best cost–benefit relation for the performance of even more specific practical tests, whether because it captures the influences of the main variables of direct volume data, because it is simpler regarding obtaining and collecting data (as it does not require a division of the claims into independent and dependent), or because it has higher correlations of the IGC with time.
Figure 13 shows the classifications of the Sample applications by time and by the IGCY1. Table 1 shows the applications in which there was divergence in the classification.
Classification of applications of the standard sample (with time).
Comparison of Classifications according to Time and IGCY1 | |||||
---|---|---|---|---|---|
Application | Claim Pages | Total Pages | Total Claims | Classification according to the Time | Classification according to IGCY1 |
3 | 2 | 34 | 5 | Light | Moderate |
8 | 5 | 50 | 15 | Moderate | Heavy |
10 | 2 | 13 | 3 | Moderate | Light |
11 | 6 | 37 | 19 | Moderate | Heavy |
20 | 5 | 34 | 16 | Moderate | Heavy |
26 | 4 | 36 | 15 | Moderate | Heavy |
30 | 4 | 56 | 8 | Heavy | Moderate |
Applications with divergent classifications.
By analyzing Figure 13, it can be verified that, when classified by time for examination, none of the applications from the sample was considered to be neither very light nor very heavy. Most applications were classified as moderate (36 or 72%), then light (8 or 16%), followed by heavy (6 or 12%). This result proves to be consistent with data obtained, as the standard sample is fairly homogeneous, shows applications of the same type of examination (using data from previous searches), and the time variable presented a moderate coefficient of variation (16.58%). Similarly to the classification by time, when classified by the IGCY1, none of the patent applications from the sample was considered to be neither very light nor very heavy. Most applications were classified as moderate (33 or 66%), then heavy (9 or 18%), followed by light (8 or 16%).
By analyzing Table 1, it can be verified that there was a total of seven patent applications with conflicting classifications by time and IGCY1. Therefore, this result shows that the classification of 43 of the 50 applications (86% of the total) converged, in other words, it shows great similarity. It is important to note that the correlation of the IGCY1 with time for the case under analysis was 0.85, i.e., the classification criterion proved to be efficient, managing to keep up with the capture tendency of this relation of the ratio with the time. More specifically to the differences found, there were four new classifications according to the IGCY1 as heavy (applications 8, 11, 20, and 26). Such applications have higher than average number of claim pages, total number of pages, and total number of claims, showing a profile similar to the other five heavy applications with similar classifications and, so, its classification as heavy according to the IGCY1 is warranted. On the other hand, it can be noticed that applications 20 and 26 showed IGC values close to one, i.e., to the classification limit between the moderate and heavy ranges. Consequently, there are two factors that may possibly explain this phenomenon: i) errors inherent in the mathematical model, which, although in small amounts, tend to occur depending on the variables, samples, and criteria adopted; and ii) measurement errors or deviations in time, which could move a classification close to the limit of the ranges.
Regarding application 10, classified as light according to the IGCY1 and as moderate according to time, it is possible to note it is indeed a quite short application that, at first, would actually tend to be classified as light. Specifically in this case, the standardized time was very near to minus one (standardized time = − 0.91), i.e., quite near to the limit between moderate and light classes. Unlike the conflicting heavy cases (in which deviations probably occurred for reasons inherent in the model), in this case the tendency is that time measurement deviations may have caused the discrepancy.
In the case of application 3, classified as moderate according to the IGCY1 and as light according to time, we notice that it is an application with few claims and few claim pages, but with a quite high count of total pages. Depending on the specific examination procedure and the need to better understand the description and the figures, time may lead to a moderate or light classification. Hence, it is a type of application difficult to classify
Finally, application number thirty, classified as moderate according to the IGCY1 and heavy according to time, showed a IGCY1 virtually equal to one (IGCY1 = 0.995), reaching the exact limit between the moderate and heavy classification ranges. It ends up being a case similar to the discrepancies of the heavy applications, due to issues inherent in the mathematical model.
In short, it can be verified that the model manages to represent quite satisfactorily the examination time/effort, and for cases in the threshold of the criteria adopted, few discrepancies occur, and, in these cases, the discrepancies occur only in the adjacent ranges. In other words, any discrepancies that occur are occasional, not rough, and reasonable given the limitations inherent in this kind of model and research.
Ten patent applications of ten examiners under analysis were selected to compose the final redistribution sample, amounting to one hundred (100) patent applications to be examined. The steps of the proposed methodology were strictly followed, but, due to the fact that the purpose of this case was to obtain a sample to apply the model validated with the standard sample with time (our reference), all variables of interest were obtained of first examinations already published, collected between May and July 2020, and all sample applications are also using data from previous searches by international offices (in the context of the “backlog combat plan”, i.e., without executing specific prior art search). The case chosen for the redistribution simulation was Case 5 – Case 3 Var (2), given that this case obtained the best results in the validation tests with the standard sample with time. Figure 14 shows the classifications of the redistribution sample applications.
classifications of the Redistribution sample applications.
None of the sample patent applications were classified as very light. Most applications were classified as moderate (71%), followed by light (16%), heavy (11%), and, finally, very heavy, which were only two (2%). It should be noted that the data on the IGCY1 showed normal statistical distribution, similarly to the time and the IGCY1 of the standard sample.
Figure 15 indicates that with the redistribution there was a better balance in the concentration of applications within the ZAE of each examiner. We note that in the case of six out of the ten examiners, there was an increased number of applications distributed to them and pertaining to their own ZAE, with an emphasis on examiners 5, 6, 9 and 10, with significant increases. Only examiner 8 remained with a poor concentration (10%) of applications within his ZAE, which may be explained by the fact that this examiner is a more “versatile” examiner of the division, and does not have such a well defined ZAE. Thus, the results suggest that this new configuration contributes for the examiners to work within their specific fields of expertise and knowledge.
Percentage of applications within the ZAE before and after the new distribution.
To complement the cycle of the methodology and make a last comparison between the distributions, the IBD ratios of the original sample distribution and of its redistribution were calculated. Eq. (12) resulted in an IBD equal to 0.83 for the original case and an IBD equal to 0.9 for the redistribution, i.e., there was an increased IBD with the new distribution, showing that the medians of the applications of the examiners after redistribution get closer to the general median of the division. This corroborates the fact that the new distribution results in a trend for better balance regarding the volume of data and time/effort of the applications distributed to the examiners.
In this study, ten possible variables were identified, relevant to the evaluation and distribution of the patent applications to the examiners. Among these variables, the ones directly related to the voluminosity of a patent document, i.e., the volume of data that the examiner has to deal with when examining patents, were identified, namely: the number of pages of description, the number of claim pages, the number of pages of figures, the number of independent claims and the number of dependent claims.
With the application of the PCA in a first data sample, referred to as Initial Test Sample, it was verified that the components were consistent with the initial hypotheses. Based on this initial sample, containing a large number of applications examined over two years, the examiners’ Specific Areas of Expertise (ZAE) were determined, that is, the IPC subclasses (technological areas) they examine the most according to their knowledge and work experience. These ZAE are highly relevant, as these subclasses are one of the criteria used to distribute patent applications to the examiners, and their comparison before and after any redistribution is important.
The patent applications were also classified in up to five classes: very light, light, moderate, heavy, and very heavy, and the classification had as a reference the IGC values, considering ranges equivalent to the average ratio plus one, three or more standard deviations. Then the applications were redistributed with emphasis on the examiners’ ZAE and on the classifications. The results show that the medians of the examiners’ applications approached the general medians of the division, suggesting that the new distribution is more balanced in volume of data than the original one. Moreover, with the new distribution, the examiners had the majority of their applications allocated within their respective ZAE, i.e., they would examine more applications in their specific areas of knowledge and preference, also suggesting that the new distribution contributes to better efficiency, quality, and motivation.
Additionally, the results obtained suggest that, although the five variables directly related to volume of data tend to be the ones that mostly impact the examination process, all ten variables selected, to some extent, influence the analysis of complexity of patent applications.
On the other hand, as complexity is something relative, to investigate if this complexity indeed captures the examination time/effort, a sensitivity analysis of the model developed was performed in order to verify the correlations of variables and IGC with time. In order to do so, it was then necessary to obtain a new sample of patent applications, referred to as Standard Sample, now with the additional collection of the examination time variable. In this context, simulations considering different variables and standard sample sizes were performed, with application of the PCA method and the model developed, including calculation of the IGC with different criteria and their correlations with time. The results obtained suggest that, for our specific problem, the IGC with greater efficiency and stability was IGCY1, i.e., using only the first principal component, the one which is most representative as to total data variance.
It is also worth noting that the case including only three variables (number of claim pages, total number of pages, and total number of claims) is the one recommended to perform even more specific practical tests, whether because it captures the influences of the main variables of direct volume of data, given the simplicity for data acquisition and collection (as it does not require separation of independent claims from the dependent ones), or because it has consistently higher correlations of the IGCY1 with time, always close to 0.85.
Based on this new sample with the collection of the time for examination, the patent applications were once again classified into the five classes defined (very light, light, moderate, heavy and very heavy). Such classifications were carried out twice, the first time using the time for examination variable as a reference, i.e., the standard reference classification, and the second time using the IGCY1 ratio, i.e., the classification suggested by the model. Upon comparison between these classifications according to time and the classifications of the model, the results showed a strong similarity, as the model correctly classified 43 out of the 50 patent applications analyzed, a total of 86%.
After testing the mathematical model and the criteria for classification with the correlations with time, the following step was to perform a first practical complete redistribution test. In order to do so, it was necessary to collect a third and final sample, referred to as Final Redistribution Sample, with 100 patent applications, being 10 applications of 10 different examiners, all using data from previous searches by international offices, so that the profile of this new sample was similar to the profile of the standard sample, as our reference had already been tested. Based on this new sample, we determined the main central tendency statistics of the samples by examiner and calculated the Distribution Balancing Ratios (IBD) both for the original distribution and for the sample redistributed according to the IGCY1.
The results obtained with the new redistribution showed that there was a better balance in the examination concentration within the ZAE of each examiner, and in the samples of six out of the ten examiners analyzed, there was an increased number of applications distributed to them and pertaining to their own ZAE. Thus, there is evidence that this new configuration contributes for the examiners to work within their specific fields of expertise and knowledge and, consequently, to their efficiency and motivation. It should also be noted that the new redistribution produced a positive effect on the medians of the examiners’ samples, which was mathematically quantified by calculating the IBD, which, in the original distribution, had a value of 0.83 and, after redistribution, increased to 0.90.
In short, our results suggest that the mathematical model is able to represent quite satisfactorily the examination time/effort for patent applications. Also, the logic proposed managed to achieve the goal of better balancing the examiners’ workload distribution.
Supporting women in scientific research and encouraging more women to pursue careers in STEM fields has been an issue on the global agenda for many years. But there is still much to be done. And IntechOpen wants to help.
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The importance of these compounds in wine is due to their large effect on the organoleptic attributes of wine. Phenolic compounds play a crucial role in the colour as well as mouthfeel properties of wines. UV-visible spectroscopy appears as a suitable technique for the evaluation of phenolic compounds’ properties and content. The ability of the phenolic ring to absorb UV light and the fact that some of the phenolic substances are coloured compounds, i.e. show absorption features in the visible region, make UV-visible spectroscopy a suitable technique to investigate and quantify grape and wine phenolic compounds. A number of analytical techniques are currently used for phenolic quantification. These include both simpler approaches (spectrophotometric determinations) as well as more complex methodologies such liquid chromatography analysis. Moreover, a number of spectroscopy applications have also been recently reported and are becoming popular within the wine industry. This chapter reviews information on the UV-visible spectral properties of phenolic compounds, changes occurring during wine ageing and also discusses the current UV-visible based analytical techniques used for the quantification of phenolic compounds in grapes and wine.",book:{id:"6878",slug:"frontiers-and-new-trends-in-the-science-of-fermented-food-and-beverages",title:"Frontiers and New Trends in the Science of Fermented Food and Beverages",fullTitle:"Frontiers and New Trends in the Science of Fermented Food and Beverages"},signatures:"Jose Luis Aleixandre-Tudo and Wessel du Toit",authors:[{id:"250919",title:"Dr.",name:"Jose Luis",middleName:null,surname:"Aleixandre-Tudo",slug:"jose-luis-aleixandre-tudo",fullName:"Jose Luis Aleixandre-Tudo"},{id:"261223",title:"Prof.",name:"Wessel",middleName:null,surname:"Du Toit",slug:"wessel-du-toit",fullName:"Wessel Du Toit"}]},{id:"38354",doi:"10.5772/48453",title:"Oxygen Scavengers: An Approach on Food Preservation",slug:"oxygen-scavengers-an-approach-on-food-preservation",totalDownloads:16150,totalCrossrefCites:8,totalDimensionsCites:46,abstract:null,book:{id:"1128",slug:"structure-and-function-of-food-engineering",title:"Structure and Function of Food Engineering",fullTitle:"Structure and Function of Food Engineering"},signatures:"Renato Souza Cruz, Geany Peruch Camilloto and Ana Clarissa dos Santos Pires",authors:[{id:"144206",title:"Dr.",name:"Renato",middleName:null,surname:"Cruz",slug:"renato-cruz",fullName:"Renato Cruz"},{id:"144215",title:"Dr.",name:"Ana Clarissa",middleName:null,surname:"Pires",slug:"ana-clarissa-pires",fullName:"Ana Clarissa Pires"},{id:"144219",title:"MSc.",name:"Geany",middleName:null,surname:"Camilloto",slug:"geany-camilloto",fullName:"Geany Camilloto"}]}],mostDownloadedChaptersLast30Days:[{id:"38363",title:"Pulsed Electric Fields for Food Processing Technology",slug:"pulsed-electric-fields-for-food-processing-technology",totalDownloads:29444,totalCrossrefCites:15,totalDimensionsCites:72,abstract:null,book:{id:"1128",slug:"structure-and-function-of-food-engineering",title:"Structure and Function of Food Engineering",fullTitle:"Structure and Function of Food Engineering"},signatures:"Maged E.A. Mohamed and Ayman H. Amer Eissa",authors:[{id:"147638",title:"Dr.",name:"Maged",middleName:"E. A.",surname:"Mohammed",slug:"maged-mohammed",fullName:"Maged Mohammed"}]},{id:"66671",title:"Extraction and Purification of Pectin from Agro-Industrial Wastes",slug:"extraction-and-purification-of-pectin-from-agro-industrial-wastes",totalDownloads:2721,totalCrossrefCites:1,totalDimensionsCites:9,abstract:"With the advent of science and technology, agro-industrial wastes are converted into various value-added products to meet the demands of increasing population. In recent years, natural polymers have evoked tremendous interest due to easy conversion into value-added products. Apart from various natural polymers, pectin occupied a prominent place due to diverse pharmaceutical and therapeutic applications. Excess utilisation of pectin, the gap between production and demand is widening. To fulfil this gap various techniques are adopted for obtaining high yield pectin from various agro-industrial wastes. This chapter will be focusing on extraction and purification of pectin from various agro-industrial wastes, considered as main environmental pollutants.",book:{id:"8504",slug:"pectins-extraction-purification-characterization-and-applications",title:"Pectins",fullTitle:"Pectins - Extraction, Purification, Characterization and Applications"},signatures:"Erumalla Venkatanagaraju, N. Bharathi, Rachiraju Hema Sindhuja, Rajshree Roy Chowdhury and Yarram Sreelekha",authors:null},{id:"69396",title:"Soybean Amino Acids in Health, Genetics, and Evaluation",slug:"soybean-amino-acids-in-health-genetics-and-evaluation",totalDownloads:1383,totalCrossrefCites:0,totalDimensionsCites:6,abstract:"Soybean is an important source of protein and amino acids for humans and livestock because of its well-balanced amino acid profile. This chapter outlines the strengths and weaknesses of soybean as a complete amino acid source as well as the relative importance of individual amino acids. Special attention is paid to the sulfur-containing amino acids, methionine and cysteine. Breeding and genetic engineering efforts are summarized to highlight previous accomplishments in amino acid improvement and potential avenues for future research. Agronomic properties and processing methods that affect amino acid levels in soybean food and feed are also explained. A brief introduction into current amino acid evaluation techniques is provided. By understanding the complexities of amino acids in soybean, protein quality for humans and livestock can be maximized.",book:{id:"6972",slug:"soybean-for-human-consumption-and-animal-feed",title:"Soybean for Human Consumption and Animal Feed",fullTitle:"Soybean for Human Consumption and Animal Feed"},signatures:"William Monte Singer, Bo Zhang, M.A. Rouf Mian and Haibo Huang",authors:[{id:"308970",title:"Mr.",name:"William",middleName:null,surname:"Singer",slug:"william-singer",fullName:"William Singer"},{id:"309005",title:"Dr.",name:"Bo",middleName:null,surname:"Zhang",slug:"bo-zhang",fullName:"Bo Zhang"},{id:"310776",title:"Dr.",name:"M.A. Rouf",middleName:null,surname:"Mian",slug:"m.a.-rouf-mian",fullName:"M.A. Rouf Mian"},{id:"310777",title:"Dr.",name:"Haibo",middleName:null,surname:"Huang",slug:"haibo-huang",fullName:"Haibo Huang"}]},{id:"56975",title:"Metabolic Processes During Seed Germination",slug:"metabolic-processes-during-seed-germination",totalDownloads:6166,totalCrossrefCites:29,totalDimensionsCites:63,abstract:"Seed germination is crucial stage in plant development and can be considered as a determinant for plant productivity. Physiological and biochemical changes followed by morphological changes during germination are strongly related to seedling survival rate and vegetative growth which consequently affect yield and quality. This study is aimed to focus on proceeding of the most vital metabolic processes namely reserve mobilization, phytohormonal regulation, glyoxylate cycle and respiration process under either stressful or non-stressful conditions that may be led to suggest and conduct the more successful experimental improvements. Seed imbibition triggered the activation of various metabolic processes such as synthesis of hydrolytic enzymes which resulted in hydrolysis of reserve food into simple available form for embryo uptake. Abiotic stresses potentially affect seed germination and seedling establishment through various factors, such as a reduction in water availability, changes in the mobilization of stored reserves, hormonal balance alteration and affecting the structural organization of proteins. Recent strategies for improving seed quality involved classical genetic, molecular biology and invigoration treatments known as priming treatments. H2O2 accumulation and associated oxidative damages together with a decline in antioxidant mechanisms can be regarded as a source of stress that may suppress germination. Seed priming was aimed primarily to control seed hydration by lowering external water potential, or shortening the hydration period.",book:{id:"6096",slug:"advances-in-seed-biology",title:"Seed Biology",fullTitle:"Advances in Seed Biology"},signatures:"Awatif S. Ali and Alaaeldin A. Elozeiri",authors:[{id:"207241",title:"Dr.",name:"Awatif",middleName:null,surname:"Ali",slug:"awatif-ali",fullName:"Awatif Ali"}]},{id:"51587",title:"Casein Proteins: Structural and Functional Aspects",slug:"casein-proteins-structural-and-functional-aspects",totalDownloads:4815,totalCrossrefCites:17,totalDimensionsCites:40,abstract:"Mammalian milk is a complex fluid mixture of various proteins, minerals, and lipids, which play an important role in providing nutrition and immunity to the newborn. Casein proteins, which form about 80% of the bovine milk proteins, form large colloidal particles with calcium phosphate to form casein micelles, which for many years have been an important subject of interest. Casein micelles are composed of four main types of proteins: αS1‐casein, αS2‐casein, β‐casein, and k‐casein. These constituent casein proteins lack well‐defined secondary and tertiary structure due to large amount of propyl residues. These micelles are being extensively studied because of their importance in functional behavior of milk and various milk products. However, the exact structure and nature of these casein micelles are still under debate. These different casein proteins possess different functional properties due to their primary amino acid sequence.",book:{id:"5060",slug:"milk-proteins-from-structure-to-biological-properties-and-health-aspects",title:"Milk Proteins",fullTitle:"Milk Proteins - From Structure to Biological Properties and Health Aspects"},signatures:"Mohd Younus Bhat, Tanveer Ali Dar and Laishram Rajendrakumar\nSingh",authors:[{id:"178323",title:"Dr.",name:"Laishram R",middleName:null,surname:"Singh",slug:"laishram-r-singh",fullName:"Laishram R Singh"},{id:"183444",title:"Mr.",name:"Md. Younus",middleName:null,surname:"Bhat",slug:"md.-younus-bhat",fullName:"Md. Younus Bhat"}]}],onlineFirstChaptersFilter:{topicId:"36",limit:6,offset:0},onlineFirstChaptersCollection:[{id:"81975",title:"Self-Sustained Communities: Food Security in Times of Crisis",slug:"self-sustained-communities-food-security-in-times-of-crisis",totalDownloads:11,totalDimensionsCites:0,doi:"10.5772/intechopen.104425",abstract:"The COVID-19 pandemic has caused an increase in the number of poor people around the world and led to the risk of food insecurity on a global scale. Even in Thailand, a country where food production exceeds domestic demand, the COVID-19 pandemic affects food security. The increased unemployment and the consequent loss of income resulting from the pandemics undermine food accessibility and affordability for many people. This chapter addresses the problem of food insecurity in Thailand during and after the COVID-19 crisis. It provides an analysis of the current status of food insecurity and food system resilience in Thailand and suggests solutions. It also proposes the adoption of a “Food Self-Sustained Community (FSSC)” model, which refers to the concept of building food security in a community. By planning and designing in advance, a community can switch its normal form of production seamlessly to a self-sufficiency model that prepares it for future crises, so that the community can produce enough food for all members without relying on sources outside the community.",book:{id:"10897",title:"Food Systems Resilience",coverURL:"https://cdn.intechopen.com/books/images_new/10897.jpg"},signatures:"Kriengsak Chareonwongsak"},{id:"81297",title:"Legumes Cropping and Nitrogen Fixation under Mediterranean Climate: The Case of Montado/Dehesa System",slug:"legumes-cropping-and-nitrogen-fixation-under-mediterranean-climate-the-case-of-montado-dehesa-system",totalDownloads:24,totalDimensionsCites:0,doi:"10.5772/intechopen.104473",abstract:"Climate change contributes to the environmental pressures that the Montado/Dehesa systems are experiencing, leading to an impoverishment of the floristic composition of the understorey. The strongly acidic soils of these systems are associated with nutrient deficiencies, nutritional disorders and the toxicity of metals, especially Mn and Al; these problems are discussed with emphasis on the antagonism between Fe and Mn and the relationship between K concentration and Mg uptake and concentration. The potential for the use of the legume-rhizobia symbiosis to increase biological nitrogen fixation and avenues for research are discussed. The co-colonization of the roots of legumes with arbuscular mycorrhizal (AM) fungi and the effects on P and Mn uptake are discussed. A better understanding of the relationships between soil pH, organic matter content (SOM), microbial community, soil P content and the plant strategies to mobilize it, as well as plant effects on the soil solution concentrations of Mn, is important for the management of these systems. The increase of biological nitrogen fixation in these systems, through the breeding of tolerant cultivars to acidic soils and a stepwise legumes enrichment, alongside soil fertility management, may contribute to increasing biomass production, SOM content and overall ecological plasticity.",book:{id:"10897",title:"Food Systems Resilience",coverURL:"https://cdn.intechopen.com/books/images_new/10897.jpg"},signatures:"Fernando Teixeira"},{id:"81493",title:"Rust Disease Classification Using Deep Learning Based Algorithm: The Case of Wheat",slug:"rust-disease-classification-using-deep-learning-based-algorithm-the-case-of-wheat",totalDownloads:79,totalDimensionsCites:0,doi:"10.5772/intechopen.104426",abstract:"Rusts are plant diseases caused by obligate fungi parasites. They are usually host-specific and cause greater losses of yields in crops, trees, and ornamental plants. Wheat is a staple food crop bearing losses specifically due to three species of rust fungi namely leaf rust (Puccinia triticina), stem rust (Puccinia graminis), and yellow rust (Puccinia striiformis). These diseases are usually inspected manually by a human being but at a large scale, this process is labor-intensive, time-consuming, and prone to human errors. Therefore, there is a need for an effective and efficient system that helps in the identification and classification of these diseases at early stages. In the present study, a deep learning-based CNN (i.e., VGG16) transfer learning model has been utilized for wheat disease classification on the CGIAR image dataset, containing two classes of wheat rust disease (leaf rust and stem rust), and one class of healthy wheat images. The deep learning models produced the best results by tuning the various hyper-parameters such as batch size, number of epochs, and learning rate. The proposed model has reported the best classification accuracy rate of 99.54% on 80 epochs using an initial learning rate from 0.01 and decayed to 0.0001.",book:{id:"10897",title:"Food Systems Resilience",coverURL:"https://cdn.intechopen.com/books/images_new/10897.jpg"},signatures:"Shivani Sood, Harjeet Singh and Suruchi Jindal"},{id:"81235",title:"Global Food System Transformation for Resilience",slug:"global-food-system-transformation-for-resilience",totalDownloads:65,totalDimensionsCites:1,doi:"10.5772/intechopen.102749",abstract:"Our world is incredibly diverse and beautiful, everything we do has an impact on the environment, and our actions are intertwined. Recognizing how our actions affect the Earth on a global scale means, we need to change the way we do things. We must ensure that the value society derives from our actions comes at a low cost to the environment. A sustainable strategy to establish a resilient food system is to ensure that human demand for the Earth’s resources for food is kept within the supply of these resources. While more than 800 million people worldwide suffer from chronic malnutrition, our food systems emit roughly a third of all greenhouse emissions. Also, over 80% of our biodiversity gets lost. Hence, scaling up food system is simply not an option to feed nine to ten billion people by 2050 as we will need to produce more food in the next four decades than all of history’s farmers have harvested in the last eight thousand years. Therefore, rather than upscaling, the global food systems require transformation. Four critical aspects of this transformation include: “Boosting the small; Transforming the Big; Losing Less; and Eating Smarter.” Examining these four areas more deeply, it becomes evident that, while new technology will be critical to the transformation, government involvement, as well as better financial and behavioral change from residents and consumers, will be required. This chapter focuses on these four pillars that make up the global food system transformation for resilience.",book:{id:"10897",title:"Food Systems Resilience",coverURL:"https://cdn.intechopen.com/books/images_new/10897.jpg"},signatures:"Jasper Okoro Godwin Elechi, Ikechukwu U. Nwiyi and Cornelius Smah Adamu"},{id:"80749",title:"Analysis of the Nexus between Coping Strategies and Resilience to Food Insecurity Shocks: The Case of Rural Households in Boricha Woreda, Sidama National Regional State, Ethiopia",slug:"analysis-of-the-nexus-between-coping-strategies-and-resilience-to-food-insecurity-shocks-the-case-of",totalDownloads:67,totalDimensionsCites:1,doi:"10.5772/intechopen.102613",abstract:"This chapter reports on the coping strategies employed by households in the event of food insecurity shocks and the nexus between the types of coping strategies and resilience to food insecurity in one of the food-stressed woreda from Sidama National Regional State, Ethiopia. The households use various consumption-based coping strategies that run from compromising the quality of food-to-food rationing. Repeatedly occurring food shortage has also forced some households to employ resilience erosive coping mechanisms such as selling reproductive assets. Such coping strategies have an important implication on the household’s capacity to cope with the future food insecurity-related shocks, with a statistically significant relationship between the nature of coping strategies utilized in response to previous food insecurity-related shocks and the household’s resilience to upcoming shocks. Coordinating crises management based on humanitarian intervention with households’ livelihood assets protection and resilience strengthening is the major policy implication of this study.",book:{id:"10897",title:"Food Systems Resilience",coverURL:"https://cdn.intechopen.com/books/images_new/10897.jpg"},signatures:"Adane Atara Debessa, Degefa Tolossa and Berhanu Denu"},{id:"80753",title:"Toward Safe Food Systems: Analyses of Mycotoxin Contaminants in Food and Preventive Strategies Thereof for Their Formation and Toxicity",slug:"toward-safe-food-systems-analyses-of-mycotoxin-contaminants-in-food-and-preventive-strategies-thereo",totalDownloads:64,totalDimensionsCites:0,doi:"10.5772/intechopen.101461",abstract:"Mycotoxin contaminants in food pose a threat to human and animal health. These lead to food wastage and threaten food security that is already a serious problem in Africa. In addition, these affect trading and especially affect incomes of rural farmers. The broad impacts of these contaminants require integrated solutions and strategies. It is thus critical to not only develop strategies for analysis of these toxins but also develop removal and preventive strategies of these contaminants to ensure consumer safety and compliance with regulatory standards. Further within the aim of promoting food safety, there is need for operational policy framework and strategy on the management of these contaminants to promote their mitigation. This chapter discusses integrated strategies for monitoring and control of mycotoxin contamination in food matrices to promote their mitigation and build resilient food systems in Africa and thus reinforce efforts to reach sustainable food security.",book:{id:"10897",title:"Food Systems Resilience",coverURL:"https://cdn.intechopen.com/books/images_new/10897.jpg"},signatures:"Dikabo Mogopodi, Mesha Mbisana, Samuel Raditloko, Inonge Chibua and Banyaladzi Paphane"}],onlineFirstChaptersTotal:10},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:9,numberOfPublishedChapters:90,numberOfOpenTopics:6,numberOfUpcomingTopics:0,issn:"2633-1403",doi:"10.5772/intechopen.79920",isOpenForSubmission:!0},{id:"7",title:"Biomedical Engineering",numberOfPublishedBooks:12,numberOfPublishedChapters:104,numberOfOpenTopics:3,numberOfUpcomingTopics:0,issn:"2631-5343",doi:"10.5772/intechopen.71985",isOpenForSubmission:!0}],lsSeriesList:[{id:"11",title:"Biochemistry",numberOfPublishedBooks:32,numberOfPublishedChapters:319,numberOfOpenTopics:4,numberOfUpcomingTopics:0,issn:"2632-0983",doi:"10.5772/intechopen.72877",isOpenForSubmission:!0},{id:"25",title:"Environmental Sciences",numberOfPublishedBooks:1,numberOfPublishedChapters:12,numberOfOpenTopics:4,numberOfUpcomingTopics:0,issn:"2754-6713",doi:"10.5772/intechopen.100362",isOpenForSubmission:!0},{id:"10",title:"Physiology",numberOfPublishedBooks:11,numberOfPublishedChapters:141,numberOfOpenTopics:4,numberOfUpcomingTopics:0,issn:"2631-8261",doi:"10.5772/intechopen.72796",isOpenForSubmission:!0}],hsSeriesList:[{id:"3",title:"Dentistry",numberOfPublishedBooks:8,numberOfPublishedChapters:133,numberOfOpenTopics:2,numberOfUpcomingTopics:0,issn:"2631-6218",doi:"10.5772/intechopen.71199",isOpenForSubmission:!0},{id:"6",title:"Infectious Diseases",numberOfPublishedBooks:13,numberOfPublishedChapters:113,numberOfOpenTopics:3,numberOfUpcomingTopics:1,issn:"2631-6188",doi:"10.5772/intechopen.71852",isOpenForSubmission:!0},{id:"13",title:"Veterinary Medicine and Science",numberOfPublishedBooks:11,numberOfPublishedChapters:107,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:19,numberOfOpenTopics:3,numberOfUpcomingTopics:0,issn:"2753-894X",doi:"10.5772/intechopen.100359",isOpenForSubmission:!0},{id:"23",title:"Education and Human Development",numberOfPublishedBooks:0,numberOfPublishedChapters:5,numberOfOpenTopics:1,numberOfUpcomingTopics:1,issn:null,doi:"10.5772/intechopen.100360",isOpenForSubmission:!0},{id:"24",title:"Sustainable Development",numberOfPublishedBooks:0,numberOfPublishedChapters:16,numberOfOpenTopics:5,numberOfUpcomingTopics:0,issn:null,doi:"10.5772/intechopen.100361",isOpenForSubmission:!0}],testimonialsList:[{id:"6",text:"It is great to work with the IntechOpen to produce a worthwhile collection of research that also becomes a great educational resource and guide for future research endeavors.",author:{id:"259298",name:"Edward",surname:"Narayan",institutionString:null,profilePictureURL:"https://mts.intechopen.com/storage/users/259298/images/system/259298.jpeg",slug:"edward-narayan",institution:{id:"3",name:"University of Queensland",country:{id:null,name:"Australia"}}}},{id:"13",text:"The collaboration with and support of the technical staff of IntechOpen is fantastic. 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",coverUrl:"https://cdn.intechopen.com/series/covers/23.jpg",latestPublicationDate:"June 25th, 2022",hasOnlineFirst:!0,numberOfPublishedBooks:0,editor:{id:"280770",title:"Dr.",name:"Katherine K.M.",middleName:null,surname:"Stavropoulos",slug:"katherine-k.m.-stavropoulos",fullName:"Katherine K.M. Stavropoulos",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRdFuQAK/Profile_Picture_2022-05-24T09:03:48.jpg",biography:"Katherine Stavropoulos received her BA in Psychology from Trinity College, in Connecticut, USA. Dr. Stavropoulos received her Ph.D. in Experimental Psychology from the University of California, San Diego. She completed her postdoctoral work at the Yale Child Study Center with Dr. James McPartland. Dr. Stavropoulos’ doctoral dissertation explored neural correlates of reward anticipation to social versus nonsocial stimuli in children with and without autism spectrum disorders (ASD). She has been a faculty member at the University of California, Riverside in the School of Education since 2016. Her research focuses on translational studies to explore the reward system in ASD, as well as how anxiety contributes to social challenges in ASD. She also investigates how behavioral interventions affect neural activity, behavior, and school performance in children with ASD. She is also involved in the diagnosis of children with ASD and is a licensed clinical psychologist in California. She is the Assistant Director of the SEARCH Center at UCR and is a Faculty member in the Graduate Program in Neuroscience.",institutionString:null,institution:{name:"University of California, Riverside",institutionURL:null,country:{name:"United States of America"}}},editorTwo:null,editorThree:null},subseries:{paginationCount:2,paginationItems:[{id:"90",title:"Human Development",coverUrl:"https://cdn.intechopen.com/series_topics/covers/90.jpg",editor:{id:"191040",title:"Dr.",name:"Tal",middleName:null,surname:"Dotan Ben-Soussan",slug:"tal-dotan-ben-soussan",fullName:"Tal Dotan Ben-Soussan",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bSBf1QAG/Profile_Picture_2022-03-18T07:56:11.jpg",biography:"Tal Dotan Ben-Soussan, Ph.D., is the director of the Research Institute for Neuroscience, Education and Didactics (RINED) – Paoletti Foundation. Ben-Soussan leads international studies on training and neuroplasticity from neurophysiological and psychobiological perspectives. As a neuroscientist and bio-psychologist, she has published numerous articles on neuroplasticity, movement and meditation. She acts as an editor and reviewer in several renowned journals and coordinates international conferences integrating theoretical, methodological and practical approaches on various topics, such as silence, logics and neuro-education. 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Much of biochemistry is devoted to enzymes, proteins that catalyze chemical reactions, enzyme structures, mechanisms of action and their roles within cells. Biochemistry also studies small signaling molecules, coenzymes, inhibitors, vitamins, and hormones, which play roles in life processes. Biochemical experimentation, besides coopting classical chemistry methods, e.g., chromatography, adopted new techniques, e.g., X-ray diffraction, electron microscopy, NMR, radioisotopes, and developed sophisticated microbial genetic tools, e.g., auxotroph mutants and their revertants, fermentation, etc. More recently, biochemistry embraced the ‘big data’ omics systems. Initial biochemical studies have been exclusively analytic: dissecting, purifying, and examining individual components of a biological system; in the apt words of Efraim Racker (1913 –1991), “Don’t waste clean thinking on dirty enzymes.” Today, however, biochemistry is becoming more agglomerative and comprehensive, setting out to integrate and describe entirely particular biological systems. The ‘big data’ metabolomics can define the complement of small molecules, e.g., in a soil or biofilm sample; proteomics can distinguish all the comprising proteins, e.g., serum; metagenomics can identify all the genes in a complex environment, e.g., the bovine rumen. 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Dr. Blumenberg’s research is focused on the epidermis, expression of keratin genes, transcription profiling, keratinocyte differentiation, inflammatory diseases and cancers, and most recently the effects of the microbiome on the skin. 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In recent years, the application of chemistry to biological molecules has gained significant interest in medicinal and pharmacological studies. This topic will be devoted to understanding the interplay between biomolecules and chemical compounds, their structure and function, and their potential applications in related fields. Being a part of the biochemistry discipline, the ideas and concepts that have emerged from Chemical Biology have affected other related areas. 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Behind these definitions are hidden all the aspects of normal and pathological functioning of all processes that the topic ‘Metabolism’ will cover within the Biochemistry Series. 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Thus proteomics, an area of research that detects all protein forms expressed in an organism, including splice isoforms and post-translational modifications, is more suitable than genomics for a comprehensive understanding of the biochemical processes that govern life. The most common proteomics applications are currently in the clinical field for the identification, in a variety of biological matrices, of biomarkers for diagnosis and therapeutic intervention of disorders. From the comparison of proteomic profiles of control and disease or different physiological states, which may emerge, changes in protein expression can provide new insights into the roles played by some proteins in human pathologies. Understanding how proteins function and interact with each other is another goal of proteomics that makes this approach even more intriguing. Specialized technology and expertise are required to assess the proteome of any biological sample. Currently, proteomics relies mainly on mass spectrometry (MS) combined with electrophoretic (1 or 2-DE-MS) and/or chromatographic techniques (LC-MS/MS). MS is an excellent tool that has gained popularity in proteomics because of its ability to gather a complex body of information such as cataloging protein expression, identifying protein modification sites, and defining protein interactions. The Proteomics topic aims to attract contributions on all aspects of MS-based proteomics that, by pushing the boundaries of MS capabilities, may address biological problems that have not been resolved yet.",annualVolume:11414,isOpenForSubmission:!0,coverUrl:"https://cdn.intechopen.com/series_topics/covers/18.jpg",editor:{id:"200689",title:"Prof.",name:"Paolo",middleName:null,surname:"Iadarola",fullName:"Paolo Iadarola",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bSCl8QAG/Profile_Picture_1623568118342",institutionString:null,institution:{name:"University of Pavia",institutionURL:null,country:{name:"Italy"}}},editorTwo:{id:"201414",title:"Dr.",name:"Simona",middleName:null,surname:"Viglio",fullName:"Simona Viglio",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRKDHQA4/Profile_Picture_1630402531487",institutionString:null,institution:{name:"University of Pavia",institutionURL:null,country:{name:"Italy"}}},editorThree:null,editorialBoard:[{id:"72288",title:"Dr.",name:"Arli Aditya",middleName:null,surname:"Parikesit",fullName:"Arli Aditya Parikesit",profilePictureURL:"https://mts.intechopen.com/storage/users/72288/images/system/72288.jpg",institutionString:null,institution:{name:"Indonesia International Institute for Life Sciences",institutionURL:null,country:{name:"Indonesia"}}},{id:"40928",title:"Dr.",name:"Cesar",middleName:null,surname:"Lopez-Camarillo",fullName:"Cesar Lopez-Camarillo",profilePictureURL:"https://mts.intechopen.com/storage/users/40928/images/3884_n.png",institutionString:null,institution:{name:"Universidad Autónoma de la Ciudad de México",institutionURL:null,country:{name:"Mexico"}}},{id:"81926",title:"Dr.",name:"Shymaa",middleName:null,surname:"Enany",fullName:"Shymaa Enany",profilePictureURL:"https://mts.intechopen.com/storage/users/81926/images/system/81926.png",institutionString:"Suez Canal University",institution:{name:"Suez Canal University",institutionURL:null,country:{name:"Egypt"}}}]}]}},libraryRecommendation:{success:null,errors:{},institutions:[]},route:{name:"chapter.detail",path:"/chapters/47447",hash:"",query:{},params:{id:"47447"},fullPath:"/chapters/47447",meta:{},from:{name:null,path:"/",hash:"",query:{},params:{},fullPath:"/",meta:{}}}},function(){var e;(e=document.currentScript||document.scripts[document.scripts.length-1]).parentNode.removeChild(e)}()