Comparison of microcystin synthetase genes.
\r\n\t
",isbn:"978-1-80356-966-6",printIsbn:"978-1-80356-965-9",pdfIsbn:"978-1-80356-967-3",doi:null,price:0,priceEur:0,priceUsd:0,slug:null,numberOfPages:0,isOpenForSubmission:!1,isSalesforceBook:!1,isNomenclature:!1,hash:"f86a9f720cc3ac0f1c385d0367ea89b9",bookSignature:"Dr. Fiaz Ahmad and Prof. Muhammad Sultan",publishedDate:null,coverURL:"https://cdn.intechopen.com/books/images_new/11624.jpg",keywords:"Agricultural Waste, Reuse, Reduction, Soil Health, Recycling, Agriculture and Environment, Modelling and Simulation, Agro-Industrial Waste, Bioresource Processing, Processing and Management, Crop Residue, Forest Waste",numberOfDownloads:null,numberOfWosCitations:0,numberOfCrossrefCitations:null,numberOfDimensionsCitations:null,numberOfTotalCitations:null,isAvailableForWebshopOrdering:!0,dateEndFirstStepPublish:"April 8th 2022",dateEndSecondStepPublish:"June 16th 2022",dateEndThirdStepPublish:"August 15th 2022",dateEndFourthStepPublish:"November 3rd 2022",dateEndFifthStepPublish:"January 2nd 2023",dateConfirmationOfParticipation:null,remainingDaysToSecondStep:"2 months",secondStepPassed:!0,areRegistrationsClosed:!0,currentStepOfPublishingProcess:4,editedByType:null,kuFlag:!1,biosketch:"Dr. Fiaz Ahmad is a researcher in the field of Agricultural Engineering with fifteen years of field and academic experience, currently in charge of the Agricultural Machinery Design Laboratory at Bahauddin Zakariya University. He applied for two patents at the national level.",coeditorOneBiosketch:"A renowned researcher in the field of Agricultural Engineering with 14 years of academic experience at Bahauddin Zakariya University. Winner of various prestigious fellowships, awards, and research grants. Published 250+ articles along with several books and chapters. Guest editor of seven ISI-SCI journals for publishers like SAGE, MDPI, and Frontiers.",coeditorTwoBiosketch:null,coeditorThreeBiosketch:null,coeditorFourBiosketch:null,coeditorFiveBiosketch:null,editors:[{id:"338219",title:"Dr.",name:"Fiaz",middleName:null,surname:"Ahmad",slug:"fiaz-ahmad",fullName:"Fiaz Ahmad",profilePictureURL:"https://mts.intechopen.com/storage/users/338219/images/system/338219.png",biography:"Dr. Fiaz Ahmad is an assistant professor and lecturer at the Department of Agricultural Engineering, Bahauddin Zakariya University, Multan, Pakistan. He obtained his Ph.D. in Agricultural Bioenvironmental and Energy Engineering from Nanjing Agriculture University, China, in 2015, and completed his postdoctorate in Agricultural Engineering from Jiangsu University, Zhenjiang, China, in 2020. He was awarded a fellowship from the Higher Education Commission of Pakistan for Ph.D. studies and from the Chinese Government for post-doctoral studies. He earned a BSc and MSc (Hons) in Agricultural Engineering from the University of Agriculture, Faisalabad, Pakistan, in 2004 and 2007, respectively. He is the author of more than fifty journal and conference articles. He has supervised six master’s students to date, and is currently supervising six master and two doctoral students. Dr. Ahmad has completed three research projects with his research interest focusing on the design of agricultural machinery, agricultural waste management, artificial intelligence (AI), and agricultural bioenvironment.",institutionString:"Bahauddin Zakariya University",position:null,outsideEditionCount:0,totalCites:0,totalAuthoredChapters:"2",totalChapterViews:"0",totalEditedBooks:"1",institution:{name:"Bahauddin Zakariya University",institutionURL:null,country:{name:"Pakistan"}}}],coeditorOne:{id:"199381",title:"Prof.",name:"Muhammad",middleName:null,surname:"Sultan",slug:"muhammad-sultan",fullName:"Muhammad Sultan",profilePictureURL:"https://mts.intechopen.com/storage/users/199381/images/system/199381.png",biography:"Muhammad Sultan is an Assistant Professor at the Department of Agricultural\r\nEngineering, Bahauddin Zakariya University, Multan (Pakistan). He completed his Ph.D.\r\nand Postdoc from Kyushu University (Japan) in the field of Energy & Environmental\r\nEngineering. He was an awardee of MEXT and JASSO fellowships (from the Japanese\r\nGovernment) during Ph.D. and Postdoc studies, respectively. He also did a Postdoc as\r\na Canadian Queen Elizabeth Advance Scholar at Simon Fraser University (Canada) in\r\nthe field of Mechatronic Systems Engineering. He worked for Kyushu University\r\nInternational Institute for Carbon-Neutral Energy Research (WPI-I2CNER) for two years.\r\nCurrently, he is working on 4 research projects funded by the Higher Education\r\nCommission (HEC) of Pakistan. He has completed six projects in past in the field of\r\nagricultural engineering. He has supervised 10+ M.Eng. and Ph.D. thesis and 10+\r\nstudents are currently working under his supervision. He has published 120+ journal\r\narticles, 100+ conference articles, 13 book chapters, and 6 books. He is serving as guest\r\neditor for the journals like Sustainability (MDPI), Agriculture (MDPI), Energies (MDPI),\r\nAdvances in Mechanical Engineering (SAGE), Frontiers in Mechanical Engineering, and\r\nEvergreen Journal of Kyushu University. His research is focused on developing energy-\r\nefficient temperature and humidity control systems for agricultural storage, greenhouse,\r\nlivestock, and poultry applications. His research keywords include desiccant air-\r\nconditioning, evaporative cooling, adsorption heat pump, Maisotsenko cycle (M-cycle),\r\nenergy recovery ventilators; adsorption desalination; wastewater treatment.",institutionString:"Bahauddin Zakariya University",position:null,outsideEditionCount:0,totalCites:0,totalAuthoredChapters:"5",totalChapterViews:"0",totalEditedBooks:"0",institution:{name:"Bahauddin Zakariya University",institutionURL:null,country:{name:"Pakistan"}}},coeditorTwo:null,coeditorThree:null,coeditorFour:null,coeditorFive:null,topics:[{id:"5",title:"Agricultural and Biological Sciences",slug:"agricultural-and-biological-sciences"}],chapters:null,productType:{id:"1",title:"Edited Volume",chapterContentType:"chapter",authoredCaption:"Edited by"},personalPublishingAssistant:{id:"440212",firstName:"Elena",lastName:"Vracaric",middleName:null,title:"Ms.",imageUrl:"https://mts.intechopen.com/storage/users/440212/images/20007_n.jpg",email:"elena@intechopen.com",biography:"As an Author Service Manager, my responsibilities include monitoring and facilitating all publishing activities for authors and editors. From chapter submission and review to approval and revision, copyediting and design, until final publication, I work closely with authors and editors to ensure a simple and easy publishing process. I maintain constant and effective communication with authors, editors and reviewers, which allows for a level of personal support that enables contributors to fully commit and concentrate on the chapters they are writing, editing, or reviewing. I assist authors in the preparation of their full chapter submissions and track important deadlines and ensure they are met. I help to coordinate internal processes such as linguistic review, and monitor the technical aspects of the process. As an ASM I am also involved in the acquisition of editors. Whether that be identifying an exceptional author and proposing an editorship collaboration, or contacting researchers who would like the opportunity to work with IntechOpen, I establish and help manage author and editor acquisition and contact."}},relatedBooks:[{type:"book",id:"10454",title:"Technology in Agriculture",subtitle:null,isOpenForSubmission:!1,hash:"dcfc52d92f694b0848977a3c11c13d00",slug:"technology-in-agriculture",bookSignature:"Fiaz Ahmad and Muhammad Sultan",coverURL:"https://cdn.intechopen.com/books/images_new/10454.jpg",editedByType:"Edited by",editors:[{id:"338219",title:"Dr.",name:"Fiaz",surname:"Ahmad",slug:"fiaz-ahmad",fullName:"Fiaz Ahmad"}],productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"6418",title:"Hyperspectral Imaging in Agriculture, Food and Environment",subtitle:null,isOpenForSubmission:!1,hash:"9005c36534a5dc065577a011aea13d4d",slug:"hyperspectral-imaging-in-agriculture-food-and-environment",bookSignature:"Alejandro Isabel Luna Maldonado, Humberto Rodríguez Fuentes and Juan Antonio Vidales Contreras",coverURL:"https://cdn.intechopen.com/books/images_new/6418.jpg",editedByType:"Edited by",editors:[{id:"105774",title:"Prof.",name:"Alejandro Isabel",surname:"Luna Maldonado",slug:"alejandro-isabel-luna-maldonado",fullName:"Alejandro Isabel Luna Maldonado"}],productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"10359",title:"Landraces",subtitle:"Traditional Variety and Natural Breed",isOpenForSubmission:!1,hash:"0600836fb2c422f7b624363d1e854f68",slug:"landraces-traditional-variety-and-natural-breed",bookSignature:"Amr Elkelish",coverURL:"https://cdn.intechopen.com/books/images_new/10359.jpg",editedByType:"Edited by",editors:[{id:"231337",title:"Dr.",name:"Amr",surname:"Elkelish",slug:"amr-elkelish",fullName:"Amr Elkelish"}],productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"1591",title:"Infrared Spectroscopy",subtitle:"Materials Science, Engineering and Technology",isOpenForSubmission:!1,hash:"99b4b7b71a8caeb693ed762b40b017f4",slug:"infrared-spectroscopy-materials-science-engineering-and-technology",bookSignature:"Theophile Theophanides",coverURL:"https://cdn.intechopen.com/books/images_new/1591.jpg",editedByType:"Edited by",editors:[{id:"37194",title:"Dr.",name:"Theophile",surname:"Theophanides",slug:"theophile-theophanides",fullName:"Theophile Theophanides"}],productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"3161",title:"Frontiers in Guided Wave Optics and Optoelectronics",subtitle:null,isOpenForSubmission:!1,hash:"deb44e9c99f82bbce1083abea743146c",slug:"frontiers-in-guided-wave-optics-and-optoelectronics",bookSignature:"Bishnu Pal",coverURL:"https://cdn.intechopen.com/books/images_new/3161.jpg",editedByType:"Edited by",editors:[{id:"4782",title:"Prof.",name:"Bishnu",surname:"Pal",slug:"bishnu-pal",fullName:"Bishnu Pal"}],productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"371",title:"Abiotic Stress in Plants",subtitle:"Mechanisms and Adaptations",isOpenForSubmission:!1,hash:"588466f487e307619849d72389178a74",slug:"abiotic-stress-in-plants-mechanisms-and-adaptations",bookSignature:"Arun Shanker and B. 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Simultaneously, some freshwater cyanobacteria can produce various toxins, named cyanotoxins, some of which are potently poisonous to humans and animals. A well-known cyanotoxicosis in humans was reported from Brazil in association with medical malpractice in 1996. In this incident, 126 patients in a hemodialysis unit were affected, and 60 of them died due to using microcystin-contaminated water from a local reservoir. A cyanobacterial bloom was found in that reservoir concurrently [1]. Besides, there have been reports concerning human cyanotoxin poisoning by drinking water or via injury after contacting recreational water [2]. Apart from humans, numerous animal poisoning cases have also taken place because they can reach the unprocessed natural water directly so that the risk of being poisoned becomes higher. These cases involve livestock, pets, and wildlife [3, 4, 5, 6, 7, 8, 9, 10].
Cyanobacterial blooms occurred more frequently in recent years, which may have been attributed to the aggravating eutrophication in freshwater and global warming. As such, cyanotoxin poisoning incidents have also been increasingly reported. Nowadays, freshwater cyanobacterial blooms have broader geographical and temporal impacts on local water bodies that act as vital municipal or agricultural water supplies. With the possibility of cyanotoxin contamination, humans and animals residing in surrounding areas continue to be threatened. Therefore, testing for toxic cyanobacteria or cyanotoxins is imperative for detection and preventive measures.
Although cyanobacteria can be observed under a microscope, their toxigenicity cannot be determined by microscopy because the toxigenic cyanobacteria do not have unique morphological characteristics. Some laboratories have adopted a testing strategy that combines microscopic observation and cyanotoxin detection to indicate the existence of toxigenic cyanobacteria in samples. Although this strategy may seem reasonable and pragmatic, it needs collaboration between chemical analysts and microalgal biologists to reach an agreement on the conclusion. Furthermore, it neglects the complex phenomena of the same toxin production by different species or genera, leading to an incorrect judgment of the truly culpable toxin producers.
Cyanotoxin testing has been in place. Yet, available tests have shortcomings. For example, commercial enzyme-linked immunosorbent assays (ELISAs) have been widely employed in water testing for cyanotoxins. However, it still has issues, such as low sensitivity [11] or inaccuracy. Erroneous detection is due to the cross-reactivity of isomorphic substances with targets. False-positive results can occur in a worst-case scenario [12]. The high performance liquid chromatography (HPLC) and liquid chromatography-mass spectrometry (LC–MS) are the most accurate analytical methods and have been often employed in cyanotoxin testing [11, 13, 14, 15, 16]. But they require exquisite instruments and complicated operations, making them not as affordable as ELISA-based testing. Aside from these limitations, chemical testing can only tell the presence and/or quantity of cyanotoxins without identifying the toxin producer(s). However, it is crucial to recognize the existence of toxigenic cyanobacteria in water bodies for monitoring and early warning of cyanotoxin poisoning incidents.
It is known that cyanotoxin synthesis is catalyzed by a string of relevant enzymes encoded by toxin synthetase genes [17, 18, 19, 20, 21, 22, 23]. Lack of essential genes for forming a toxin backbone or disruption of the enzymatic cascade toward toxin production results in the failure of toxin synthesis. Therefore, the detection of toxin synthetase genes in samples by a molecular test can disclose the presence or absence of toxigenic cyanobacteria. In this chapter, we review the application of molecular techniques, particularly PCR-based assays, for detecting toxigenic cyanobacteria in freshwater.
Like other bacteria, cyanobacteria often have one circular chromosome and a few plasmids that consist of the whole genome. The cyanobacterial chromosome is a few megabases in size and contains most of the genes, while plasmids play a role in transferring DNA elements. Compared to the eukaryotic microalgae, the cyanobacterial genome is highly compressed but still contains all genes essential for aquatic and photosynthetic life. Some species even have genes that can facilitate competitive superiority in the environment. For example, gas vesicle genes in
Cyanotoxin synthetase genes often cluster together in the genome and constitute one or more operons that are transcribed in identical or opposite directions [19, 21, 22, 23, 26]. The reason for such an arrangement is likely that the transcription can be well regulated so that all pertaining genes are transcribed simultaneously. This process may ensure that all necessary enzymes/proteins are present for subsequent toxin synthesis. The whole-genome sequencing of toxic cyanobacteria to date has demonstrated only a single copy of the toxin gene cluster in the cyanobacterial genome [27, 28, 29]. The toxin synthetase genes have conserved sequences encoding conserved domains/motifs in the corresponding proteins with specific functions during toxin syntheses, such as polyketide synthesis, adenylation, and methylation. The genes are always clustered closely with whose proteins conduct successive functions in a cascade reaction. It should be reiterated that the synthetase genes are indispensable for toxin production, making them the ideal targets for molecular detection.
Cyanotoxins are traditionally named after the first identified toxin-producing genus, as in the case of microcystin (
Microcystin is the most common cyanotoxin implicated in human and animal poisoning incidents [36, 37, 38]. It is a hepatotoxin and thus can cause severe impairment in the liver when ingested by the casualties. The toxin is known to be produced by several genera of cyanobacteria, such as
Microcystin is a cyclic heptapeptide that inhibits the eukaryotic protein phosphatase type 1 and 2A in humans and animals by forming an irreversible covalent bond to a cysteine in the catalytic domain of these enzymes. It consists of the following amino acids: D-alanine, X, D-MeAsp (D-erythro-ß-methyl-aspartic acid), Z, Adda ((2S,3S,8S,9S)-3-amino-9-methoxy-2,6,8-trimethyl-10-phenyldeca-4,6-dienoic acid), D-glutamic acid, and Mdha (N-methyldehydroalanine). X and Z represent variable L amino acids. It has reportedly over 80 variants, mostly differing in amino acids at the positions X and Z [39].
Microcystin is a non-ribosomal oligopeptide, which means unlike most of the peptides and proteins, it is not synthesized by cellular ribosomes. The enzymes responsible for its synthesis contain the non-ribosomal peptide synthetases (NRPS) and polyketide synthases (PKS) modules as well as tailoring functional domains. All the enzymes are the protein products encoded by the microcystin synthetase genes (
Gene | Size (bp)1 | Encoded domain or function2 | Existence in different genera | ||
---|---|---|---|---|---|
8838 | NRPS, C, NMT, E | yes | yes | yes | |
6318 | NRPS, A, T, C | yes | yes | yes | |
3876 | NRPS, C, A, TE | yes | yes | yes | |
11721 | PKS, KS, AT, KR, DH, ACP, CM | yes | yes | yes | |
10464 | PKS, NRPS, KS, AT, ACP, CM, AMT | yes | yes | yes | |
756 | Racemase | yes | yes | no | |
7896 | NRPS, PKS, KS, AT, CM, DH, KR, ACP | yes | yes | yes | |
1617 | Transporter | yes | yes | yes | |
1014 | Dehydrogenase | yes | yes | no | |
837 | OM | yes | yes | yes | |
< 1000 | TE | no | no | yes |
Comparison of microcystin synthetase genes.
Values are from
NRPS, non-ribosomal peptide synthetase; C, condensation; NMT,
The microcystin synthetase gene (
Per annotation of
The cyanobacterial alkaloid anatoxin-a has been found in different genera, such as
Although anatoxin-a doesn’t look structurally complicated, its synthesis still requires a cascade of many enzymes whose genes known as anatoxin-a synthetase genes (
Gene | Size (bp)1 | Encoded domain or function2 | Existence in different genera | ||
---|---|---|---|---|---|
750 | TE | yes | yes | yes | |
1143 | Proline-ACP oxidase | yes | yes | yes | |
1596 | Proline adenylation | yes | yes | yes | |
273 | Acyl carrier | yes | yes | yes | |
6438 | PKS, KS, AT, DH, ER, KR, ACP | yes | yes | yes | |
5619 | PKS, KS, AT, DH, KR, ACP | yes | yes | yes | |
4896 | PKS, KS, AT, CM, ACP | yes | yes | yes | |
< 1000 | Transposase | no | yes | yes | |
< 2000 | Transporter | yes | yes | yes | |
723 | Cyclase | yes | yes | yes | |
<1000 | Reductase | no | no | yes |
Comparison of anatoxin-a synthetase genes.
Values are from
TE, thioesterase; ACP, acyl carrier protein; PKS, polyketide synthase; KS, β-ketoacyl synthase; AT, acyltransferase; DH, dehydratase; ER, enoylreductase; KR, ketoreductase; CM,
The anatoxin-a synthetase gene (
To start the anatoxin-a synthesis, AnaC activates and tethers the precursor proline to AnaD, which covalently combines with the proline. Then AnaB dehydrogenates the heterocyclic ring of proline to form a “C=N” double bond. AnaE introduces a carbonyl group into its connection with the heterocycle passed from AnaD. Then AnaJ catalyzes a cyclization step to form the characteristic bicyclic ring structure of anatoxin-a by connecting the heterocyclic ring with the backbone. At the same time, the growing chain is bound to the acyl carrier protein domain of AnaF. Finally, the bicyclic thioester is transferred to AnaG for chain extension by adding an acyl group, followed by the enzymatic reaction of AnaA to break the single “SCO-C” covalent bond connecting the enzyme (AnaG) and final product for the completion and releasing of anatoxin-a. Similar to its counterpart McyH in microcystin-producing cyanobacteria, AnaI transports the toxin through the cytomembrane. The rest of the Ana proteins are not commonly shared across different genera and have their own functions. AnaH is a transposase only found in
Cylindrospermopsin can be produced by various cyanobacterial genera, such as
Cylindrospermopsin is synthesized via a string of NRPS/PKS reactions conducted by up to over a dozen Cyr proteins (Table 3, Figure 3). The cylindrospermopsin synthetase genes (
Gene | Size (bp)1 | Encoded domain or function2 | Existence in different genera | ||
---|---|---|---|---|---|
1176 | AMT | yes | yes | yes | |
8754 | NRPS, PKS, PCP, KS, AT, DH, MT, KR, ACP | yes | yes | yes | |
5005 | PKS, KS, AT, KR, ACP | yes | yes | yes | |
5631 | PKS, KS, AT, DH, KR, ACP | yes | yes | yes | |
5667 | PKS, KS, AT, DH, KR, ACP | yes | yes | yes | |
4074 | PKS, KS, AT, ACP | yes | yes | yes | |
1437 | Uracil ring formation | yes | yes | yes | |
1431 | Uracil ring formation | yes | yes | yes | |
831 | Hydroxylation | yes | yes | yes | |
780 | Sulfotransferase | yes | yes | yes | |
1398 | Exporter | yes | yes | yes | |
750 | Transposase | yes | no | no | |
318 | Transposase | yes | no | no | |
600 | Adenylylsulfate kinase | yes | no | yes | |
1548 | Regulator | yes | no | yes | |
152 | ATP-grasp protein | no | no | yes | |
404 | Transposase | no | no | yes | |
299 | Transposase | no | no | yes |
Comparison of cylindrospermopsin synthetase genes.
Values are from
AMT, aminotransferase; NRPS, non-ribosomal peptide synthetase; PKS, polyketide synthase; PCP, peptidyl carrier protein; AT, acyltransferase; DH, dehydratase; MT, methyl transferase; KR, ketoreductase; ACP, acyl carrier protein; KS, β-ketoacyl synthase.
The cylindrospermopsin synthetase gene (
As
Nodularin is a cyclic pentapeptide and has the identical chemical structure as microcystin except the lack of D-alanine and the amino acid at position X. The mechanism of its toxicity is the same as microcystin’s, i.e., inhibiting the eukaryotic protein phosphatase catalytic subunit type 1 and 2A and leading to severe liver damage. Different from the three aforementioned cyanotoxins, nodularin is solely found in
Gene | Size (bp)1 | Encoded domain or function2 |
---|---|---|
2607 | NRPS, A, NM, PCP, C | |
1299 | C, A, PCP, TE | |
2640 | NRPS, PKS, A, PCP, KS, AT, CM, KR, ACP | |
3872 | PKS, KS, AT, CM, DH, KR, ACP | |
927 | OM | |
3475 | PKS, NRPS, KS, AT, CM, ACP, AMT, C, A, PCP | |
235 | Racemase | |
341 | D-3-phosphoglycerate dehydrogenase | |
601 | ABC transporter |
Comparison of nodularin synthetase genes.
Values are from
NRPS, non-ribosomal peptide synthetase; A, adenylation; NM,
The nodularin synthetase gene (
Nodularin synthesis is conducted putatively according to the annotated functions of each Nda protein. NdaC activates the starter unit as phenylalanine or phenylacetate, and then NdaE catalyzes the transfer of a methyl group to the growing chain. NdaD is involved in two further polyketide extension steps, and NdaF facilitates the final round of polyketide extension and the biosynthesis of Adda. Next, epimerization of L-glutamic acid is catalyzed by NdaG, followed by the peptide condensation carried out by NdaA and NdaB. During the condensation, NdaH participates in the conversion of N-methyl-L-threonine (MeThr) to N-methyldehydrobutyrine (MeDhb) with a cofactor nicotinamide adenine dinucleotide (NADH). Finally, the mature peptide chain is cyclized by NdaB and released from the enzyme-substrate complex. As an ABC-transporter, NdaI is responsible for the transmembrane transportation of nodularin for extracellular excretion.
PCR-based assays have been most commonly utilized in molecular identification studies because the assays are able to recognize targets accurately. The assays incorporate oligonucleotide primers explicitly designed for complementary sequences of the target gene(s). Two types of PCR methods have been used: conventional gel-based PCR and real-time PCR. In general, the real-time PCR has higher sensitivity (i.e., detect a low amount of the target) than the conventional PCR. The real-time PCR also offers better specificity than the conventional PCR since it uses an additional oligonucleotide known as a probe, which is complementary to sequences between primer-binding sequences.
Furthermore, the real-time PCR allows estimating the number of the intended target in samples when performed with standards with a known copy number of the target sequences. This procedure is referred to as quantitative real-time PCR (qPCR). In addition, reverse transcription (RT)-PCR or RT-qPCR platforms have been utilized for specifically detecting transcripts (i.e., mRNAs) from the target genes of cyanobacteria. Typically, PCR can be completed within one or two hours, much shorter than the traditional analytical methods and microscopy mentioned above.
The molecular identification of microcystin-producing cyanobacteria has been conducted using nearly all
Although most publications have been concerned about toxic/toxigenic
The rest of the
With increased bioinformatic data related to
There are a few unidentified open reading frames (ORFs) flanking the
The
Like
Molecular detection of cylindrospermopsin-producing cyanobacteria has been mostly reported for
Multi-generic detection of cylindrospermopsin-producing cyanobacteria was reported as well. Campo et al. found that
There are also a few ORFs flanking the
Since
Apart from the four most commonly reported cyanotoxins mentioned above, there are a few other cyanotoxins, such as saxitoxin, lyngbyatoxin, guanitoxin, β-N-methylamino-L-alanin (BMAA), aplysiatoxin, and lipopolysaccharide [18, 77, 78]. Hitherto, only the gene clusters for the biosynthesis of saxitoxin and lyngbyatoxin have been characterized.
Saxitoxin belongs to the group of carbamate alkaloid toxins composed of a tetrahydropurine group and two guanidinium moieties [79] and can also be produced by marine phytoplankton [80]. It can cause paralytic shellfish poisoning syndrome and afflict human health via bioaccumulation. At least 30 clustered saxitoxin synthesis genes (
The
Lyngbyatoxin is characterized as a potent skin irritant produced by
No literature regarding molecular detection of cyanobacteria producing the rest of the toxins mentioned above could be searched. It is most likely because there are few reports as to the molecular mechanisms of their biosynthesis. Nevertheless, it is worthwhile to briefly introduce guanitoxin, previously known as anatoxin-a(S), to emphasize its difference from anatoxin-a. Guanitoxin was recently renamed due to its structural and toxicological disparities from anatoxin-a [77]. It is a guanidino organophosphate neurotoxin that irreversibly inhibits acetylcholinesterase’s active site, leading to excess acetylcholine, which causes severe salvation and chromodacryorrhea, so-called “bloody tears” before respiratory arrest [84]. Up to now, it was only found in planktonic
As various cyanobacterial genera can produce the same cyanotoxin, the development of toxigenic cyanobacteria identification needs to be multi-generic detection. Furthermore, as many genes for different toxins have sequences for the same conserved domains, designing PCR methods for all the cyanobacteria producing multiple toxins would be ideal.
Although most publications have focused on the selected cyanotoxins and their producers, more attention should be paid to other cyanotoxins and producers due to their potential of posing a significant threat to animal and human health. However, many cyanotoxin-producing cyanobacteria still lack bioinformation for the synthesis-related genes (e.g., guanitoxin), and it is thereby urgent to make further exploration to enrich the gene pools and their sequences so that a much more comprehensive understanding of the molecular mechanisms and the development of nucleic acid-based identification methods can be facilitated.
With the technical advance in PCR, researchers have been able to develop multiplex PCR methods in which many cyanotoxin biosynthesis genes can be detected simultaneously. For example, Ouahid et al. devised a multiplex PCR assay to detect six
Cyanobacteria with cyanotoxin synthetase genes in their genome are clearly equipped with the ability of toxin production. However, transcription of toxin biosynthesis genes is triggered by various environmental factors [88, 89, 90]; hence, toxin production is not consistently ongoing. It means the presence of genes itself may not always translate into the appearance of toxins unless they are inter- or extra-cellularly accumulated and detectable. Furthermore, the significant positive correlation between gene copies and toxin levels is still controversial, as described in this chapter and another review [91]. Instead, the presence of mRNA transcripts from cyanotoxin synthase genes may be more closely associated with toxin production. Consequently, cDNA detection is justifiable to indicate an ongoing toxin synthesis, which is more critical and useful for monitoring the toxin-producing cyanobacteria. For this purpose, genes located at the end of operons should be good candidates for two reasons. One, primers designed from those genes can be directly used in cDNA testing like other genes because cyanobacteria lack introns. Two, the appearance of those genes in cDNA form signifies the successful cascade transcription of the clustered genes, gearing up all pertinent proteins for toxin synthesis. For example,
Although qPCR is preferred due to its many advantages, conventional PCR should also be considered for assessing the presence or absence of toxigenic cyanobacteria in water samples, as previously reported [49, 56]. In addition, the simplicity and cheaper operation may make conventional PCRs a more cost-effective tool for molecular detection of toxigenic cyanobacteria in comparison to qPCRs.
Besides PCR-based assays, there are other molecular technologies applicable to the identification and/or characterization of toxigenic cyanobacteria. A noteworthy method is the next-generation sequencing (NGS) technology. The technology has been widely used to identify previously unrecognized agents, non-culturable microorganisms, and/or variants because of its advanced and hypothesis-free sequencing ability [92] and has been applied to cyanobacteria research. Although most NGS studies have been investigations of taxonomic diversities using representative cyanobacterial genetic markers such as 16S rDNA [93, 94], the potential toxigenicity of cyanobacteria can be disclosed by sequencing the pooled libraries of toxin biosynthesis associated genes. Casero et al. revealed the existence of multiple toxigenic taxa in a summer bloom in a Spanish reservoir using
Nowadays, freshwater cyanobacterial blooms are seen more frequently than ever before because of increased eutrophication of their habitats and climate changes (e.g., global warming), which are utterly favorable to the overgrowth of cyanobacteria. Even though toxic cyanobacterial species are not always the mere culprit for these ecological disasters, they are often the dominant organisms and cause more destructive consequences because they can produce potent cyanotoxins into the water. There is no doubt that the toxic freshwater cyanobacteria pose a grave threat to human and animal health, agricultural production, tourism, to name a few. Hence, advancing techniques and technologies for rapid and reliable identification and monitoring of toxic cyanobacteria is an inevitable mission for healthcare, economy, and environmental conservation. To date, molecular assays, especially PCR-based tests, have been employed in toxic cyanobacterial identification, but their utilization should be further expanded into large-scale and long-term detection tasks and routine monitoring programs for not only the acute poisoning incidents but also the chronic impacts and preventative measures.
The authors disclosed receipt of the following financial support for the publication of this chapter: the manuscript compilation was supported in part by funding from the Innovative Swine Industry Enhancement Grant Program by the Iowa Attorney General’s Office, Iowa State University (ISU) Health Research Initiative, and ISU Veterinary Diagnostic Laboratory Research Support Fund.
The authors declare no conflict of interest.
The authors are sincerely grateful to the people who have made their contributions to the pertaining studies that are helpful for writing the chapter, including, but not limited to, Dr. Steve Ensley, Dr. Hyun-Joong Kim, Dr. Christopher Filstrup, Dr. Baoqing Guo, Dr. Paula Imerman, Dr. Grace Wilkinson, Dwayne Schrunk, and Amy Curtis.
There are a large number of rotating machineries being intensively employed in the modern industry, such as hydro-turbines, pumps, steam turbines, compressors, and generators. They are widely employed in the power generation, heating, refrigeration, and chemical industries. The rotating machineries often involve extreme conditions such as extremely low load, high temperature, high pressure, high speed, and overload. Hence, the malfunctions may occur after the long-term operation with possibly catastrophic consequences. Therefore, it is very important to understand and monitor the operational states of rotating machineries.
With the developments of data analysis technology, signal analysis methods become gradually mature and have been widely applied in the field of condition monitoring and fault diagnosis of various kinds of rotating machineries. The signal analysis could extract useful information from the original signal, and judge the operational states of the equipment based on the obtained information. Signal analysis is of great significance to the rotating machineries both for condition monitoring and fault diagnosis.
A reversible pump turbine is the core part of the pumped hydro energy storage power station. It can switch between the pumping and the generating mode according to the actual demand. When the reversible pump turbine deviates from the design working condition, it is easy to produce serious pressure pulsation and vibration due to the influence of rotor-stator interaction in the vaneless space and the vortex rope in the draft tube, which will affect the normal operation of the pump turbine and the safety of the whole power station [1, 2, 3]. Therefore, to monitor the operational states of reversible pump turbine and ensure its safety and efficient operation, it is very necessary to employ the signal analysis methods extensively.
This chapter will review several typical signal analysis methods and introduce their applications in the field of the reversible pump turbine in detail through specific cases. This chapter will be divided into the following four parts. The first part will introduce the time-domain analysis methods of the signals. The second part will introduce the time-frequency analysis methods of the signals. The third part will introduce the signal decomposition and the signal de-noising. The fourth part will demonstrate the applications of the introduced signal analysis methods in the field of the reversible pump turbines with the aid of on-site measured signals.
Signals can convey information by expressing the relationship between time and other physical quantities. The time-domain analysis methods of signals refer to a series of processing such as amplification, filtering, statistical feature calculation and correlation analysis in the time domain. Through time-domain analysis methods, the characteristic parameters reflecting the operational state of the mechanical equipment can be extracted from the signal, which could be further employed for the purpose of the evaluation of the operational state and fault diagnosis of the equipment. Time-domain analysis methods could also analyze the auto-correlation (AC) and cross-correlation characteristics of the signal together with the degree of chaos. This section will be divided into three parts including the time domain statistical parameters, the correlation analysis and the chaos evaluation.
The classical time-domain statistical parameters include the peak value, peak-to-peak value, mean value, mean square value, root mean square, variance and standard deviation. The meanings of these statistical parameters are explained in detail below. Here, the
Peak value refers to the maximum amplitude of a signal.
Peak-to-peak value refers to the difference between the maximum value and the minimum value of a signal within a given period. In the practical application, to eliminate the influences of distortion and noise in the signal, the peak-to-peak value is usually calculated by the confidence interval method with employing the confidence coefficient (e.g., 97 or 95%). Then, the peak-to-peak value could be calculated by using the upper and the lower limits of the obtained signal.
The mean value is the averaged value of the whole signal.
Mean square value refers to the mean of the square of the signal, indicating the strength and average power of the signal.
Root mean square refers to the arithmetic square root of the mean square value.
Variance is the average square value of the difference between the amplitude of the original signal and the mean value. It describes the fluctuation range of the signal and represents the strength of the fluctuating component in the signal.
Standard deviation is the arithmetic square root of variance.
When there are multiple signals, sometimes it is necessary to study the relationship between them. Correlation analysis (including auto-correlation function and cross-correlation analysis) could show the similarity or dependence between signals.
The auto-correlation (AC) function describes the correlation of a signal between its values at a certain time and after a certain time delay
The cross-correlation function describes the degree of similarity of the time-domain waveforms of two signals
The higher the
In the practical application of signal correlation analysis, to compare the magnitude of the correlation, we often use the normalized form of the correlation function. The normalized form of the auto-correlation function is defined as follows:
The normalized form of the cross-correlation function is defined as follows:
where
Chaos is an inherent characteristic of a nonlinear dynamic system. When a signal is generated by a nonlinear system, it may show the characteristic of chaos. At this time, the signal waveform is very irregular and is very similar to the characteristic of random noise. Entropy can be adopted to measure the chaos of a nonlinear dynamic system. The more chaotic the system, the higher its entropy. Therefore, we can use entropy to evaluate the degree of chaos in a signal. As a typical method, the permutation entropy for evaluating the degree of chaos in a signal is introduced below [4].
Permutation entropy is an index to measure the complexity of the time series [4]. The more regular the time series is, the smaller the permutation entropy is. The corresponding calculation process is given as follows [4].
Considering a time series
Here, the “
Now, each
Here, the “
There are up to “
When
The variation range of the normalized permutation entropy is between 0 and 1. In the practical application of calculating the permutation entropy of a signal, the whole data points within the signal can be intercepted by a window with a certain length. And the permutation entropy of the data points in each window is calculated by moving the window one data at a time. In the present chapter, the average permutation entropy of all the windows will be taken as the permutation entropy of the whole signal.
In this section, the pressure pulsation signal (the pressure pulsation signal 1) in the vaneless space of a prototype pump turbine under the dimensionless load condition (the ratio of the actual operational load to the rated load)
The time-domain diagram of the dimensionless pressure pulsation signal 1.
The statistical parameters of the dimensionless pressure pulsation signal 1 in the time domain are shown in the Table 1 as follows:
Statistical parameter | Value |
---|---|
Peak value | 0.9492 |
Peak-to-peak value (confidence coefficient 97%) | 0.0911 |
Peak-to-peak value (confidence coefficient 95%) | 0.0883 |
Mean | 0.9081 |
Mean square value | 0.8252 |
Root mean square | 0.9084 |
Variance | 0.0006 |
Standard deviation | 0.0244 |
The time-domain statistical parameters of the dimensionless pressure pulsation signal 1.
Figures 2 and 3 show the normalized AC functions of the dimensionless pressure pulsation signal 1 and a random noise signal. When
The normalized AC function of the dimensionless pressure pulsation signal 1.
The normalized AC function of the random noise.
In the experiment, another dimensionless pressure pulsation signal (the dimensionless pressure pulsation signal 2) was measured in the vaneless space at the same operational condition (
The time-domain diagram of the dimensionless pressure pulsation signal 2.
When the delay time
In the present chapter, the embedded dimension, delay time and window length required in the analysis procedure of the permutation entropy are 6, 3 and 128, respectively. The analysis results of the permutation entropy of the dimensionless pressure pulsation signal 1, the dimensionless pressure pulsation signal 2 and the random noise signal are as follows:
It can be seen from the Table 2 that the analysis results of the permutation entropy of the dimensionless pressure pulsation signals 1 and 2 are smaller than that of the random noise, because the dimensionless pressure pulsation signals contain certain characteristic frequencies with regularity. The permutation entropy of the random noise is large, which indicates its high degree of chaos.
Signal | Permutation entropy |
---|---|
Dimensionless pressure pulsation signal 1 | 0.4254 |
Dimensionless pressure pulsation signal 2 | 0.4271 |
Random noise | 0.5666 |
Analysis results of permutation entropy of different types of signals.
The aim of the time-frequency analysis is to study the time-varying signals, which can reflect the relationship of the variations of the frequency and amplitude with time within the signal. Generally speaking, the typical time-frequency analysis methods include the short-time Fourier transform [5], the Hilbert-Huang transform [6] and the VMD-Hilbert transform with a detailed introduction in this section.
Before introducing the time-frequency analysis methods, the traditional Fourier transform is:
where
The formula of the short-time Fourier Transform (STFT) is presented above [5]. Compared with the traditional Fourier transform, the window function is added to the formula. STFT needs to select a window function, which can be moved continuously to identify the frequencies at different times. The window function will affect the resolution of the spectrum. The smaller the window size, the higher the time resolution of the spectrum. Normally, the low frequency band requires high frequency resolution and low time resolution. And, the high frequency band requires low frequency resolution and high time resolution. However, after the window function is selected, the resolution of the entire spectrum is fixed and cannot be adjusted. Therefore, STFT is suitable for analyzing the segmented stationary signals or approximately stationary signals.
Hilbert-Huang transform (HHT) consists of two parts including the empirical mode decomposition (EMD) and the Hilbert spectrum analysis (HSA). These two parts will be introduced in detail below.
The EMD method can decompose the original signal into several intrinsic mode functions (IMFs) and the residual component
Firstly, calculating all the extreme points of the signal
Secondly, calculating the mean curve
Thirdly, the screening stop condition is given as [6]:
Here, the “
Fourthly, repeating the above steps to obtain all the remaining IMF until the residual component
Although, the EMD can realize signal decomposition, it has the problems of endpoint effect and mode mixing. Endpoint effect means that analysis results at the signal endpoints will produce errors, which will affect the internal data. Mode mixing means that the EMD method cannot effectively separate different mode components based on the time characteristic scales. These problems can lead to serious performance degradation of EMD methods.
HSA performs a Hilbert transform on each IMF obtained by EMD. The specific steps are given as follows:
Firstly, performing the Hilbert transform on each IMF
Here,
Secondly, using the above formula to construct the analytical signal
Here [6],
Thirdly, the instantaneous frequency of each IMF can be obtained from the following formula [6]:
After expressing the results on the time-frequency plane, the Hilbert amplitude spectrum of each IMF
Fourthly, by presenting the amplitude spectrum of all IMFs in a spectrum, the Hilbert spectrum of the original signal can be obtained as follows [6]:
The advantage of HHT is that it is not restricted by the linear and stationary characteristics of the signal and can analyze non-linear and non-stationary signals. At the same time, the HHT is self-adaptive through using the EMD to eliminate the choice of basis function. In addition, HHT is not restricted by Heisenberg’s uncertainty principle.
The principle of VMD-Hilbert transform is similar to HHT. It also uses the signal decomposition method to obtain the IMF component of the signal, and then obtains the Hilbert spectrum of the signal through HAS. The difference between these two is that the variational mode decomposition (VMD) [7] is adopted as the signal decomposition method.
The core idea of the VMD method is to construct and solve the variational optimization problem in the frequency domain. The specific steps include the following ones.
Firstly, decomposing the original signal into
Here,
Secondly, the constraints are added to ensure that the sum of the estimated bandwidths of each IMF is minimum and the sum of
Here,
Thirdly, the Lagrange multiplication operator is introduced to transform the constrained variational problem into an unconstrained variational problem. And an augmented Lagrange expression is obtained as follows [7]:
Here,
Fourthly, the alternating direction multiplier method is used to iteratively solve IMF
Here, “^” refers to the Fourier transform operation. The “
When the calculation result meets the given solution accuracy
Fifthly, the
Compared with the EMD, the VMD overcomes the problem of mode mixing and has a more solid mathematical theoretical foundation.
In the present chapter, the “
This section uses the vibration signal at the top cover of a prototype reversible pump turbine during the start-up transient process of generating mode as the analysis object to demonstrate the applications of the time-frequency analysis methods introduced in Sections 3.1 and 3.2. The length of the signal is 2 s and the sampling frequency is 1000 Hz. Figure 5 shows the time-domain diagram of the vibration signal at the top cover.
The time-domain diagram of the vibration signal at the top cover.
Figure 6 shows the result of the fast Fourier transform (FFT) of the vibration signal. It can be seen from the Figure 6 that the most obvious frequency component in the vibration signal is 40 Hz with an amplitude of about 0.46 mm. In addition, there is also a relatively obvious peak near 80 Hz with an amplitude of about 0.17 mm. However, Figure 6 cannot provide information about the amplitude variation of different frequency components with time, which is a shortcoming of the traditional Fourier transform.
The FFT spectrum of the vibration signal.
Figures 7 and 8 are the STFT results of the vibration signal with the window length of 64 and 256 respectively. From these two figures, not only the amplitudes of different frequency components in the vibration signals but also the variations of the amplitude of each frequency varying with the time can be seen. However, the STFT results are significantly affected by the window size. By comparing Figures 7 and 8, it can be concluded that there exist obvious amplitudes at and around 40 Hz in the Figure 7, while it almost has obvious amplitudes only at 40 Hz in the Figure 8, which is caused by the difference in the window size between them. In the actual application of the STFT, it is difficult to choose the appropriate window size, which is the main problem of this method.
The STFT result of the vibration signal with the window length of 64 and the window function of Blackman.
The STFT result of the vibration signal with the window length of 256 and the window function of Blackman.
Different with the fixed basis functions of traditional Fourier transform and STFT, HHT and VMD-Hilbert transform can obtain basis functions through adaptive mode decomposition. In addition, HHT and VMD-Hilbert transform do not need to select the window functions and they can achieve high resolutions both in time and frequency domains. Figures 9 and 10 are the results of the HHT and VMD-Hilbert transform of the signal, respectively. It can be found that the analysis result in the Figure 9 is unclear because the dominant frequencies of the signal cannot be clearly observed, while the analysis result in the Figure 10 is very clear. This can be attributed to that the VMD overcomes the mode mixing problem in the EMD adopted in the HHT.
The analysis result of HHT of the vibration signal.
The analysis result of VMD-Hilbert transform of the vibration signal.
Mode refers to the natural vibration characteristics of the mechanical structure, which is composed of natural frequency, damping ratio and mode shape. In practical engineering, the vibration of rotating machinery is often composed of different complex modes. The process of decomposing the vibration signal into sub-signals with different frequency bands on the basis of different modes is called the mode decomposition of the signal. Through the mode decomposition, the modes containing noise can be found and will be further deleted through the signal de-noising. In our previous research [8], similar methods with those shown in this section have been adopted to analyze the vibration signal from the rotating machinery of nuclear power. However, the specific frequency components between the signals between the rotating machinery of nuclear power and the reversible pump turbine are a little different.
Typical signal analysis methods, such as EMD and VMD, have been fully described in Section 3.2. In this section, a simulated swing signal at the turbine guide bearing of a prototype pump turbine will be used to demonstrate the signal de-noising effects based on these two methods. The simulated rotational speed of the unit is 500 rpm. The characteristic frequencies contained in the simulated signal are 1 time, 2 times and 3 times, the rotational frequency of the impeller with the corresponding amplitudes of 10, 2 and 1 μm, respectively. The signal is dimensionless by dividing the corresponding amplitude of the rotational frequency of the impeller (10 μm). The length of the signal is 2 s and the sampling frequency is 1000 Hz. The white noise with the signal-noise ratio (
The time-domain diagrams of simulated swing signals. (a) The simulated swing signal without noise. (b) The added noise with the
The EMD analysis results of the simulated swing signal.
The VMD analysis results of the simulated swing signal.
Through mode decomposition, several IMFs are obtained to further constitute the given signal with low noise. The IMFs contain different frequency bands. By removing the IMFs dominated by the random noises and retaining the IMFs dominated by the useful signals, the signal de-noising will be proceeded. Generally speaking, the cross-correlation coefficient between the noise-dominated IMF and the original signal is small, while the cross-correlation coefficient between the IMF component dominated by the useful signal and the original signal is relatively large. Based on this principle, the noise-dominated IMFs can be identified according to the cross-correlation coefficients.
Table 3 shows the cross-correlation coefficients of the IMFs obtained by EMD and VMD and the simulated swing signal. Here, the threshold of the cross-correlation coefficient is set to 0.12 [8]. And the IMFs with the cross-correlation coefficients larger than this threshold are retained.
Mode component | EMD | VMD |
---|---|---|
IMF1 | 0.0757 | 0.9732 |
IMF2 | 0.0537 | 0.2378 |
IMF3 | 0.7777 | 0.0453 |
IMF4 | 0.3762 | 0.0430 |
IMF5 | 0.0067 | 0.0407 |
IMF6 | 0.0242 | 0.0412 |
IMF7 | 0.0349 | 0.0400 |
residual | 0.0103 | — |
Cross-correlation coefficients of IMFs based on EMD and VMD and the simulated swing signal.
Based on the analysis results in Table 3, the IMF3 and IMF4 in the EMD analysis results and the IMF1 and IMF2 in the VMD analysis results are selected to reconstruct the de-noised swing signals, respectively. Figure 14 shows the de-noising results of the simulated swing signal based on EMD and VMD, respectively.
The de-noising results of the simulated swing signal based on EMD and VMD. (a) The simulated swing signal without noise. (b) The de-noised signal is based on EMD. (c) The de-noised signal is based on VMD.
Figure 14 shows that both the de-noised signals based on EMD and VMD are relatively smooth oscillation curves. Compared with the simulated swing signal without noise, the de-noised signal based on EMD has some abnormal spikes or irregularities as indicated by the red circles in the Figure 14b, while the time-domain waveform of the de-noised signal based on VMD is much closer to the simulated swing signal without noise, which indicates that the signal de-noising based on VMD has a better effect than that based on EMD.
The evaluation indexes of signal de-noising can help us quantitatively analyze the de-noising effects. Some evaluation indexes will be introduced below. Here
The larger the SNR, the better the de-noising effect.
The larger the
The smaller the RMSE, the better the de-noising effect.
The evaluation indexes of signal de-noising effects based on EMD and VMD are calculated respectively and the results are shown in Table 4.
Evaluation index | EMD | VMD |
---|---|---|
12.1328 | 29.5778 | |
0.969 | 0.9995 | |
0.1856 | 0.024 |
The evaluation indexes of de-noising for the simulated swing signal based on EMD and VMD.
It can be seen from Table 4 that compared with the results of signal de-noising based on EMD, the results of signal de-noising based on VMD have a larger
In Sections 4.1–4.3, the simulated swing signal is adopted to demonstrate the signal decomposition and the signal de-noising processes. In this section, the analysis results of mode decomposition and de-noising of measured swing signal of a prototype pump turbine are presented. The swing signal at the turbine guide bearing of a pump turbine was measured at
The time-domain diagram of the measured swing signal.
The EMD and VMD analysis results of the measured swing signal are shown in Figures 16 and 17.
The EMD analysis results of the measured swing signal.
The VMD analysis results of the measured swing signal.
The cross-correlation coefficients of the IMFs obtained by EMD and VMD and the measured swing signal are shown in Table 5.
Mode component | EMD | VMD |
---|---|---|
IMF1 | 0.0635 | 0.9471 |
IMF2 | 0.0797 | 0.4739 |
IMF3 | 0.7677 | 0.1096 |
IMF4 | 0.2904 | 0.0323 |
IMF5 | 0.0500 | 0.0321 |
IMF6 | 0.0715 | 0.0200 |
IMF7 | 0.1455 | 0.0154 |
residual | 0.0444 | — |
The cross-correlation coefficients of the IMFs based on EMD and VMD and the measured swing signal.
The threshold of the cross-correlation coefficient is also set to 0.12 [8]. Based on the analysis results in Table 5, the IMF3, IMF4, and IMF7 in the EMD analysis results and the IMF1 and IMF2 in the VMD analysis result are selected to reconstruct the de-noised swing signals, respectively. Figure 18 shows the de-noising results of the measured swing signal based on EMD and VMD, respectively. As shown in Figure 18, the VMD shows a better de-noising effect by comparing the smoothness of the curves.
The de-noising results of the measured swing signal is based on EMD and VMD. (a) The original measured swing signal. (b) The de-noised signal is based on the EMD. (c) The de-noised signal based on VMD.
In summary, signal analysis and processing can help us better understand the operational states of the reversible pump turbines. Through the time-domain analysis, the time-domain characteristic parameters such as peak value, peak-to-peak value and average value can be obtained. Through the time-frequency analysis, the time-frequency variation characteristics of signals can be grasped. Through the mode decomposition of the signal, various components within the signal can be distinguished and the signal de-noising can be further performed. Therefore, signal analysis plays a very important role for the condition monitoring and fault diagnosis of the reversible pump turbines.
This work was financially supported by the National Natural Science Foundation of China (Project Nos.: U1965106, 51976056 and 52076215).
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Achilias"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"10681",title:"Biodegradation Technology of Organic and Inorganic Pollutants",subtitle:null,isOpenForSubmission:!1,hash:"9a6e10e02788092872fd249436898e97",slug:"biodegradation-technology-of-organic-and-inorganic-pollutants",bookSignature:"Kassio Ferreira Mendes, Rodrigo Nogueira de Sousa and Kamila Cabral Mielke",coverURL:"https://cdn.intechopen.com/books/images_new/10681.jpg",editedByType:"Edited by",editors:[{id:"197720",title:"Ph.D.",name:"Kassio",middleName:null,surname:"Ferreira Mendes",slug:"kassio-ferreira-mendes",fullName:"Kassio Ferreira Mendes"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"10843",title:"Persistent Organic Pollutants (POPs)",subtitle:"Monitoring, Impact and Treatment",isOpenForSubmission:!1,hash:"f5b1589f0a990b6114fef2dadc735dd9",slug:"persistent-organic-pollutants-pops-monitoring-impact-and-treatment",bookSignature:"Mohamed Nageeb Rashed",coverURL:"https://cdn.intechopen.com/books/images_new/10843.jpg",editedByType:"Edited by",editors:[{id:"63465",title:"Prof.",name:"Mohamed Nageeb",middleName:null,surname:"Rashed",slug:"mohamed-nageeb-rashed",fullName:"Mohamed Nageeb Rashed"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}}],booksByTopicTotal:218,seriesByTopicCollection:[],seriesByTopicTotal:0,mostCitedChapters:[{id:"29369",doi:"10.5772/32373",title:"Textile Organic Dyes – Characteristics, Polluting Effects and Separation/Elimination Procedures from Industrial Effluents – A Critical Overview",slug:"textile-organic-dyes-characteristics-polluting-effects-and-separation-elimination-procedures-from-in",totalDownloads:29487,totalCrossrefCites:128,totalDimensionsCites:321,abstract:null,book:{id:"872",slug:"organic-pollutants-ten-years-after-the-stockholm-convention-environmental-and-analytical-update",title:"Organic Pollutants Ten Years After the Stockholm Convention",fullTitle:"Organic Pollutants Ten Years After the Stockholm Convention - Environmental and Analytical Update"},signatures:"Zaharia Carmen and Suteu Daniela",authors:[{id:"91196",title:"Prof.",name:"Carmen",middleName:null,surname:"Zaharia",slug:"carmen-zaharia",fullName:"Carmen Zaharia"},{id:"92084",title:"Dr.",name:"Daniela",middleName:null,surname:"Suteu",slug:"daniela-suteu",fullName:"Daniela Suteu"}]},{id:"42059",doi:"10.5772/54048",title:"Adsorption Technique for the Removal of Organic Pollutants from Water and Wastewater",slug:"adsorption-technique-for-the-removal-of-organic-pollutants-from-water-and-wastewater",totalDownloads:30043,totalCrossrefCites:51,totalDimensionsCites:221,abstract:null,book:{id:"3426",slug:"organic-pollutants-monitoring-risk-and-treatment",title:"Organic Pollutants",fullTitle:"Organic Pollutants - Monitoring, Risk and Treatment"},signatures:"Mohamed Nageeb Rashed",authors:[{id:"63465",title:"Prof.",name:"Mohamed Nageeb",middleName:null,surname:"Rashed",slug:"mohamed-nageeb-rashed",fullName:"Mohamed Nageeb Rashed"}]},{id:"27305",doi:"10.5772/39363",title:"Water Stress in Plants: Causes, Effects and Responses",slug:"water-stress-in-plants-causes-effects-and-responses",totalDownloads:28496,totalCrossrefCites:72,totalDimensionsCites:172,abstract:null,book:{id:"911",slug:"water-stress",title:"Water Stress",fullTitle:"Water Stress"},signatures:"Seyed Y. S. Lisar, Rouhollah Motafakkerazad, Mosharraf M. Hossain and Ismail M. M. Rahman",authors:[{id:"110740",title:"Dr.",name:"Ismail M.M.",middleName:null,surname:"Rahman",slug:"ismail-m.m.-rahman",fullName:"Ismail M.M. Rahman"}]},{id:"62247",doi:"10.5772/intechopen.77315",title:"Application of Biosorption for Removal of Heavy Metals from Wastewater",slug:"application-of-biosorption-for-removal-of-heavy-metals-from-wastewater",totalDownloads:7645,totalCrossrefCites:75,totalDimensionsCites:152,abstract:"Fresh water accounts for 3% of water resources on the Earth. Human and industrial activities produce and discharge wastes containing heavy metals into the water resources making them unavailable and threatening human health and the ecosystem. Conventional methods for the removal of metal ions such as chemical precipitation and membrane filtration are extremely expensive when treating large amounts of water, inefficient at low concentrations of metal (incomplete metal removal) and generate large quantities of sludge and other toxic products that require careful disposal. Biosorption and bioaccumulation are ecofriendly alternatives. These alternative methods have advantages over conventional methods. Abundant natural materials like microbial biomass, agro-wastes, and industrial byproducts have been suggested as potential biosorbents for heavy metal removal due to the presence of metal-binding functional groups. Biosorption is influenced by various process parameters such as pH, temperature, initial concentration of the metal ions, biosorbent dose, and speed of agitation. Also, the biomass can be modified by physical and chemical treatment before use. The process can be made economical by regenerating and reusing the biosorbent after removing the heavy metals. Various bioreactors can be used in biosorption for the removal of metal ions from large volumes of water or effluents. The recent developments and the future scope for biosorption as a wastewater treatment option are discussed.",book:{id:"6137",slug:"biosorption",title:"Biosorption",fullTitle:"Biosorption"},signatures:"Sri Lakshmi Ramya Krishna Kanamarlapudi, Vinay Kumar\nChintalpudi and Sudhamani Muddada",authors:[{id:"238433",title:"Associate Prof.",name:"Sudhamani",middleName:null,surname:"Muddada",slug:"sudhamani-muddada",fullName:"Sudhamani Muddada"},{id:"244937",title:"Mrs.",name:"S L Ramyakrishna",middleName:null,surname:"Kanamarlapudi",slug:"s-l-ramyakrishna-kanamarlapudi",fullName:"S L Ramyakrishna Kanamarlapudi"},{id:"244938",title:"Mr.",name:"Vinay Kumar",middleName:null,surname:"Chintalpudi",slug:"vinay-kumar-chintalpudi",fullName:"Vinay Kumar Chintalpudi"}]},{id:"53211",doi:"10.5772/66416",title:"Biofloc Technology (BFT): A Tool for Water Quality Management in Aquaculture",slug:"biofloc-technology-bft-a-tool-for-water-quality-management-in-aquaculture",totalDownloads:16966,totalCrossrefCites:65,totalDimensionsCites:148,abstract:"Biofloc technology (BFT) is considered the new “blue revolution” in aquaculture. Such technique is based on in situ microorganism production which plays three major roles: (i) maintenance of water quality, by the uptake of nitrogen compounds generating in situ microbial protein; (ii) nutrition, increasing culture feasibility by reducing feed conversion ratio (FCR) and a decrease of feed costs; and (iii) competition with pathogens. The aggregates (bioflocs) are a rich protein-lipid natural source of food available in situ 24 hours per day due to a complex interaction between organic matter, physical substrate, and large range of microorganisms. This natural productivity plays an important role recycling nutrients and maintaining the water quality. The present chapter will discuss some insights of the role of microorganisms in BFT, main water quality parameters, the importance of the correct carbon-to-nitrogen ratio in the culture media, its calculations, and different types, as well as metagenomics of microorganisms and future perspectives.",book:{id:"5355",slug:"water-quality",title:"Water Quality",fullTitle:"Water Quality"},signatures:"Maurício Gustavo Coelho Emerenciano, Luis Rafael Martínez-\nCórdova, Marcel Martínez-Porchas and Anselmo Miranda-Baeza",authors:[{id:"146126",title:"Dr.",name:"Maurício Gustavo Coelho",middleName:null,surname:"Emerenciano",slug:"mauricio-gustavo-coelho-emerenciano",fullName:"Maurício Gustavo Coelho Emerenciano"},{id:"186970",title:"Prof.",name:"Marcel",middleName:null,surname:"Martínez-Porchas",slug:"marcel-martinez-porchas",fullName:"Marcel Martínez-Porchas"},{id:"186971",title:"Prof.",name:"Anselmo",middleName:null,surname:"Miranda-Baeza",slug:"anselmo-miranda-baeza",fullName:"Anselmo Miranda-Baeza"},{id:"195101",title:"Dr.",name:"Luis Rafael",middleName:null,surname:"Martínez-Córdoba",slug:"luis-rafael-martinez-cordoba",fullName:"Luis Rafael Martínez-Córdoba"}]}],mostDownloadedChaptersLast30Days:[{id:"69568",title:"Water Quality Parameters",slug:"water-quality-parameters",totalDownloads:10201,totalCrossrefCites:14,totalDimensionsCites:37,abstract:"Since the industrial revolution in the late eighteenth century, the world has discovered new sources of pollution nearly every day. So, air and water can potentially become polluted everywhere. Little is known about changes in pollution rates. The increase in water-related diseases provides a real assessment of the degree of pollution in the environment. This chapter summarizes water quality parameters from an ecological perspective not only for humans but also for other living things. According to its quality, water can be classified into four types. Those four water quality types are discussed through an extensive review of their important common attributes including physical, chemical, and biological parameters. These water quality parameters are reviewed in terms of definition, sources, impacts, effects, and measuring methods.",book:{id:"7718",slug:"water-quality-science-assessments-and-policy",title:"Water Quality",fullTitle:"Water Quality - Science, Assessments and Policy"},signatures:"Nayla Hassan Omer",authors:null},{id:"58138",title:"Water Pollution: Effects, Prevention, and Climatic Impact",slug:"water-pollution-effects-prevention-and-climatic-impact",totalDownloads:21566,totalCrossrefCites:18,totalDimensionsCites:38,abstract:"The stress on our water environment as a result of increased industrialization, which aids urbanization, is becoming very high thus reducing the availability of clean water. Polluted water is of great concern to the aquatic organism, plants, humans, and climate and indeed alters the ecosystem. The preservation of our water environment, which is embedded in sustainable development, must be well driven by all sectors. While effective wastewater treatment has the tendency of salvaging the water environment, integration of environmental policies into the actor firms core objectives coupled with continuous periodical enlightenment on the present and future consequences of environmental/water pollution will greatly assist in conserving the water environment.",book:{id:"6157",slug:"water-challenges-of-an-urbanizing-world",title:"Water Challenges of an Urbanizing World",fullTitle:"Water Challenges of an Urbanizing World"},signatures:"Inyinbor Adejumoke A., Adebesin Babatunde O., Oluyori Abimbola\nP., Adelani-Akande Tabitha A., Dada Adewumi O. and Oreofe Toyin\nA.",authors:[{id:"101570",title:"MSc.",name:"Babatunde Olufemi",middleName:null,surname:"Adebesin",slug:"babatunde-olufemi-adebesin",fullName:"Babatunde Olufemi Adebesin"},{id:"187738",title:"Dr.",name:"Adejumoke",middleName:"Abosede",surname:"Inyinbor",slug:"adejumoke-inyinbor",fullName:"Adejumoke Inyinbor"},{id:"188818",title:"Dr.",name:"Abimbola",middleName:null,surname:"Oluyori",slug:"abimbola-oluyori",fullName:"Abimbola Oluyori"},{id:"188819",title:"Mrs.",name:"Tabitha",middleName:null,surname:"Adelani-Akande",slug:"tabitha-adelani-akande",fullName:"Tabitha Adelani-Akande"},{id:"208501",title:"Dr.",name:"Adewumi",middleName:null,surname:"Dada",slug:"adewumi-dada",fullName:"Adewumi Dada"},{id:"208502",title:"Ms.",name:"Toyin",middleName:null,surname:"Oreofe",slug:"toyin-oreofe",fullName:"Toyin Oreofe"}]},{id:"45422",title:"Urban Waterfront Regenerations",slug:"urban-waterfront-regenerations",totalDownloads:14246,totalCrossrefCites:4,totalDimensionsCites:12,abstract:null,book:{id:"3560",slug:"advances-in-landscape-architecture",title:"Advances in Landscape Architecture",fullTitle:"Advances in Landscape Architecture"},signatures:"Umut Pekin Timur",authors:[{id:"165480",title:"Dr.",name:"Umut",middleName:null,surname:"Pekin Timur",slug:"umut-pekin-timur",fullName:"Umut Pekin Timur"}]},{id:"24941",title:"Tsunami in Makran Region and Its Effect on the Persian Gulf",slug:"tsunami-in-makran-region-and-its-effect-on-the-persian-gulf",totalDownloads:7604,totalCrossrefCites:4,totalDimensionsCites:7,abstract:null,book:{id:"406",slug:"tsunami-a-growing-disaster",title:"Tsunami",fullTitle:"Tsunami - A Growing Disaster"},signatures:"Mohammad Mokhtari",authors:[{id:"52451",title:"Dr.",name:"Mohammad",middleName:null,surname:"Mokhtari",slug:"mohammad-mokhtari",fullName:"Mohammad Mokhtari"}]},{id:"66307",title:"Bio-hydrogen and Methane Production from Lignocellulosic Materials",slug:"bio-hydrogen-and-methane-production-from-lignocellulosic-materials",totalDownloads:2957,totalCrossrefCites:6,totalDimensionsCites:8,abstract:"This chapter covers the information on bio-hydrogen and methane production from lignocellulosic materials. Pretreatment methods of lignocellulosic materials and the factors affecting bio-hydrogen production, both dark- and photo-fermentation, and methane production are addressed. Last but not least, the processes for bio-hydrogen and methane production from lignocellulosic materials are discussed.",book:{id:"7608",slug:"biomass-for-bioenergy-recent-trends-and-future-challenges",title:"Biomass for Bioenergy",fullTitle:"Biomass for Bioenergy - Recent Trends and Future Challenges"},signatures:"Apilak Salakkam, Pensri Plangklang, Sureewan Sittijunda, Mallika Boonmee Kongkeitkajorn, Siriporn Lunprom and Alissara Reungsang",authors:null}],onlineFirstChaptersFilter:{topicId:"12",limit:6,offset:0},onlineFirstChaptersCollection:[{id:"82624",title:"Protective Forests for Ecosystem-based Disaster Risk Reduction (Eco-DRR) in the Alpine Space",slug:"protective-forests-for-ecosystem-based-disaster-risk-reduction-eco-drr-in-the-alpine-space",totalDownloads:3,totalDimensionsCites:0,doi:"10.5772/intechopen.99505",abstract:"Mountain forests are an efficient Forest-based Solution (FbS) for Ecosystem-based Disaster Risk Reduction (Eco-DRR) by lowering the frequency, magnitude, and/or intensity of natural hazards. Technical protection measures are often poor solutions as stand-alone measures to reduce disaster risk limited by material wear and fatigue or financial resources and aesthetical values. Protective forests should therefore be considered as key elements in integrated risk management strategies. However, the definition of protective forests and the understanding and assessment of their protective functions and effects differ greatly among Alpine Space countries. In this chapter, we present a short introduction to the concept of Eco-DRR and companion terms and propose a definition of FbS as a specific case of Nature-based Solutions for an ecosystem-based and integrated risk management of natural hazards. That is, we guide the reader through the maze of existing definitions and concepts and try to disentangle their meanings. Furthermore, we present an introduction to forest regulations in the Alpine Space and European protective forest management guidelines. Our considerations and recommendations can help strengthen the role of protective forests as FbS in Eco-DRR and the acknowledgment of the key protective function they have and the crucial protective effects they provide in mountain areas.",book:{id:"10812",title:"Protective forests as Ecosystem-based solution for Disaster Risk Reduction (ECO-DRR)",coverURL:"//cdnintech.com/web/frontend/www/assets/cover.jpg"},signatures:"Michaela Teich, Cristian Accastello, Frank Perzl and Frédéric Berger"},{id:"82465",title:"Agroforestry: An Approach for Sustainability and Climate Mitigation",slug:"agroforestry-an-approach-for-sustainability-and-climate-mitigation",totalDownloads:10,totalDimensionsCites:0,doi:"10.5772/intechopen.105406",abstract:"Agroforestry Systems (AFS), or the association of trees with crops (or animals), is a strategy for land management and use that allows production within the sustainable development: (a) environmentally (production environmentally harmonic); (b) technically (integrating existing resources on the farm); (c) economically (increase in production), and (d) socially (equality of duties and opportunities, quality of life of the family group). As an intentional integration of trees or shrubs with crop and animal production, this practice makes environmental, economic, and social benefits to farmers. Given that there is a set of definitions, rather than a single definition of Agroforestry (AF) and AFS, it is justified to explore the historical evolution and the minimum coincidences of criteria to define them and apply them in the recovery of degraded areas. Knowing how to classify AFS allows us to indicate which type or group of AFS is suitable for a particular area with its characteristics. The greatest benefit that AFS can bring to degraded or sloping areas lies in their ability to combine soil conservation with productive functions. In other words, AF is arborizing agriculture and animal production to obtain more benefits including climate change adaptation and mitigation by ecosystem services.",book:{id:"11663",title:"Vegetation Dynamics, Changing Ecosystems and Human Responsibility",coverURL:"https://cdn.intechopen.com/books/images_new/11663.jpg"},signatures:"Ricardo O. Russo"},{id:"82754",title:"Impact of Revegetation on Ecological Restoration of a Constructed Soil in a Coal Mining in Southern Brazil",slug:"impact-of-revegetation-on-ecological-restoration-of-a-constructed-soil-in-a-coal-mining-in-southern-",totalDownloads:6,totalDimensionsCites:0,doi:"10.5772/intechopen.105895",abstract:"The main problems in the constructed soils are the generation of acid mine drainage promoted by the presence of coal debris in the overburden layer and the compaction of the topsoil promoted by the machine traffic when the material used in the overburden cover is more clayey. This book chapter aimed to show an overview of the impact of more than a decade of revegetation with different perennial grasses on the chemical, physical, and biological quality of constructed soil after coal mining. The study was carried out in a coal mining area, located in southern Brazil. The soil was constructed in early 2003 and the perennial grasses, Hemarthria altissima; Paspalum notatum cv. Pensacola; Cynodon dactylon cv Tifton; and Urochloa brizantha; were implanted in November/December 2003. In 11.5, 17.6 and 18 years of revegetation soil samples were collected and the chemical, physical, and biological attributes were determined. Our results show that liming is an important practice in the restoration of these strongly anthropized soils because this positively impacts the plants’ development, facilitating the roots system expansion. Biological attributes such as soil fauna and the microorganism’s population are the attributes that possibly takes longer to establish itself in these areas.",book:{id:"11663",title:"Vegetation Dynamics, Changing Ecosystems and Human Responsibility",coverURL:"https://cdn.intechopen.com/books/images_new/11663.jpg"},signatures:"Lizete Stumpf, Maria Bertaso De Garcia Fernandez, Pablo Miguel, Luiz Fernando Spinelli Pinto, Ryan Noremberg Schubert, Luís Carlos Iuñes de Oliveira Filho, Tania Hipolito Montiel, Lucas Da Silva Barbosa, Jeferson Diego Leidemer and Thábata Barbosa Duarte"},{id:"82936",title:"Soil Degradation Processes Linked to Long-Term Forest-Type Damage",slug:"soil-degradation-processes-linked-to-long-term-forest-type-damage",totalDownloads:5,totalDimensionsCites:0,doi:"10.5772/intechopen.106390",abstract:"Forest degradation impairs ability of the whole landscape adaptation to environmental change. The impacts of forest degradation on landscape are caused by a self-organization decline. At the present time, the self-organization decline was largely due to nitrogen deposition and deforestation which exacerbated impacts of climate change. Nevertheless, forest degradation processes are either reversible or irreversible. Irreversible forest degradation begins with soil damage. In this paper, we present processes of forest soil degradation in relation to vulnerability of regulation adaptability on global environmental change. The regulatory forest capabilities were indicated through soil organic matter sequestration dynamics. We devided the degradation processes into quantitative and qualitative damages of physical or chemical soil properties. Quantitative soil degradation includes irreversible loss of an earth’s body after claim, erosion or desertification, while qualitative degradation consists of predominantly reversible consequences after soil disintegration, leaching, acidification, salinization and intoxication. As a result of deforestation, the forest soil vulnerability is spreading through quantitative degradation replacing hitherto predominantly qualitative changes under continuous vegetation cover. Increasing needs to natural resources using and accompanying waste pollution destroy soil self-organization through biodiversity loss, simplification in functional links among living forms and substance losses from ecosystem. We concluded that subsequent irreversible changes in ecosystem self-organization cause a change of biome potential natural vegetation and the land usability decrease.",book:{id:"11457",title:"Forest Degradation Under Global Change",coverURL:"https://cdn.intechopen.com/books/images_new/11457.jpg"},signatures:"Pavel Samec, Aleš Kučera and Gabriela Tomášová"},{id:"82828",title:"Vegetation and Avifauna Distribution in the Serengeti National Park",slug:"vegetation-and-avifauna-distribution-in-the-serengeti-national-park",totalDownloads:6,totalDimensionsCites:0,doi:"10.5772/intechopen.106165",abstract:"In order to examine the bird species changes within different vegetation structures, the variations were compared between Commiphora-dominated vegetations with those of Vachellia tortilis and Vachellia robusta-dominated vegetations, and also compared the birds of grassland with those of Vachellia drepanolobium and Vachellia seyal-dominated vegetations. This study was conducted between February 2010 and April 2012. A total of 40 plots of 100 m × 100 m were established. Nonparametric Mann-Whitney U-test was used to examine differences in bird species between vegetations. Species richness estimates were obtained using the Species Diversity and Richness. A total of 171 bird species representing 103 genera, 12 orders, and 54 families were recorded. We found differences in bird species distribution whereby V. tortilis has higher bird species richness (102 species), abundance, and diversity when compared with Commiphora with 66 species and V. robusta with 59 species. These results suggest that variations in bird species abundance, diversity, and distribution could be attributed to differences in the structural diversity of vegetation. Therefore it is important to maintain different types of vegetation by keeping the frequency of fire to a minimum and prescribed fire should be employed and encouraged to control wildfire and so maintain a diversity of vegetation and birds community.",book:{id:"11663",title:"Vegetation Dynamics, Changing Ecosystems and Human Responsibility",coverURL:"https://cdn.intechopen.com/books/images_new/11663.jpg"},signatures:"Ally K. Nkwabi and Pius Y. Kavana"},{id:"82808",title:"Climate Change and Anthropogenic Impacts on the Ecosystem of the Transgressive Mud Coastal Region of Bight of Benin, Nigeria",slug:"climate-change-and-anthropogenic-impacts-on-the-ecosystem-of-the-transgressive-mud-coastal-region-of",totalDownloads:8,totalDimensionsCites:0,doi:"10.5772/intechopen.105760",abstract:"The transgressive mud coastal area of Bight of Benin is a muddy coastal complex that lies east of the Barrier/lagoon coast and stretches to the Benin River in the northwestern flank of the Niger Delta Nigeria. It constitutes a fragile buffer zone between the tranquil waters of the swamps and the menacing waves of the Atlantic Ocean. Extensive breaching of this narrow coastal plain results in massive incursion of the sea into the inland swamps with serious implications for national security and the economy. Climate change impacts from the results of meteorological information of the regions shows a gradual degradation in the past 30 years. 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Since from August 2013 working as a Associate Professor, and in 2016 promoted to Profeesor in the School of Basic Sciences: Department of Chemistry and having 20 years of teaching and research experiences.",institutionString:null,institution:{name:"Rani Channamma University, Belagavi",country:{name:"India"}}},{id:"158492",title:"Prof.",name:"Yusuf",middleName:null,surname:"Tutar",slug:"yusuf-tutar",fullName:"Yusuf Tutar",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/158492/images/system/158492.jpeg",biography:"Prof. Dr. Yusuf Tutar conducts his research at the Hamidiye Faculty of Pharmacy, Department of Basic Pharmaceutical Sciences, Division of Biochemistry, University of Health Sciences, Turkey. He is also a faculty member in the Molecular Oncology Program. He obtained his MSc and Ph.D. at Oregon State University and Texas Tech University, respectively. He pursued his postdoctoral studies at Rutgers University Medical School and the National Institutes of Health (NIH/NIDDK), USA. His research focuses on biochemistry, biophysics, genetics, molecular biology, and molecular medicine with specialization in the fields of drug design, protein structure-function, protein folding, prions, microRNA, pseudogenes, molecular cancer, epigenetics, metabolites, proteomics, genomics, protein expression, and characterization by spectroscopic and calorimetric methods.",institutionString:"University of Health Sciences",institution:null},{id:"180528",title:"Dr.",name:"Hiroyuki",middleName:null,surname:"Kagechika",slug:"hiroyuki-kagechika",fullName:"Hiroyuki Kagechika",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/180528/images/system/180528.jpg",biography:"Hiroyuki Kagechika received his bachelor’s degree and Ph.D. in Pharmaceutical Sciences from the University of Tokyo, Japan, where he served as an associate professor until 2004. He is currently a professor at the Institute of Biomaterials and Bioengineering (IBB), Tokyo Medical and Dental University (TMDU). From 2010 to 2012, he was the dean of the Graduate School of Biomedical Science. Since 2012, he has served as the vice dean of the Graduate School of Medical and Dental Sciences. He has been the director of the IBB since 2020. Dr. Kagechika’s major research interests are the medicinal chemistry of retinoids, vitamins D/K, and nuclear receptors. He has developed various compounds including a drug for acute promyelocytic leukemia.",institutionString:"Tokyo Medical and Dental University",institution:{name:"Tokyo Medical and Dental University",country:{name:"Japan"}}},{id:"94311",title:"Prof.",name:"Martins",middleName:"Ochubiojo",surname:"Ochubiojo Emeje",slug:"martins-ochubiojo-emeje",fullName:"Martins Ochubiojo Emeje",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/94311/images/system/94311.jpeg",biography:"Martins Emeje obtained a BPharm with distinction from Ahmadu Bello University, Nigeria, and an MPharm and Ph.D. from the University of Nigeria (UNN), where he received the best Ph.D. award and was enlisted as UNN’s “Face of Research.” He established the first nanomedicine center in Nigeria and was the pioneer head of the intellectual property and technology transfer as well as the technology innovation and support center. 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He received his post-doctoral training in oncology and cancer proteomics for two years at the Cancer Research Institute of Human Medical University in China. In 2001, he went to the University of Tennessee Health Science Center (UTHSC) in USA, where he was a post-doctoral researcher and focused on mass spectrometry and cancer proteomics. Then, he was appointed as an Assistant Professor of Neurology, UTHSC in 2005. He moved to the Cleveland Clinic in USA as a Project Scientist/Staff in 2006 where he focused on the studies of eye disease proteomics and biomarkers. He returned to UTHSC as an Assistant Professor of Neurology in the end of 2007, engaging in proteomics and biomarker studies of lung diseases and brain tumors, and initiating the studies of predictive, preventive, and personalized medicine (PPPM) in cancer. In 2010, he was promoted to Associate Professor of Neurology, UTHSC. Currently, he is a Professor at Xiangya Hospital of Central South University in China, Fellow of Royal Society of Medicine (FRSM), the European EPMA National Representative in China, Regular Member of American Association for the Advancement of Science (AAAS), European Cooperation of Science and Technology (e-COST) grant evaluator, Associate Editors of BMC Genomics, BMC Medical Genomics, EPMA Journal, and Frontiers in Endocrinology, Executive Editor-in-Chief of Med One. He has\npublished 116 peer-reviewed research articles, 16 book chapters, 2 books, and 2 US patents. 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He has published several articles in peer-reviewed journals, chapters, and edited books. His area of specialization is free radical biochemistry and autoimmune diseases.",institutionString:"Imam Abdulrahman Bin Faisal University",institution:{name:"Imam Abdulrahman Bin Faisal University",country:{name:"Saudi Arabia"}}},{id:"41865",title:"Prof.",name:"Farid A.",middleName:null,surname:"Badria",slug:"farid-a.-badria",fullName:"Farid A. Badria",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/41865/images/system/41865.jpg",biography:"Farid A. Badria, Ph.D., is the recipient of several awards, including The World Academy of Sciences (TWAS) Prize for Public Understanding of Science; the World Intellectual Property Organization (WIPO) Gold Medal for best invention; Outstanding Arab Scholar, Kuwait; and the Khwarizmi International Award, Iran. He has 250 publications, 12 books, 20 patents, and several marketed pharmaceutical products to his credit. He continues to lead research projects on developing new therapies for liver, skin disorders, and cancer. Dr. Badria was listed among the world’s top 2% of scientists in medicinal and biomolecular chemistry in 2019 and 2020. He is a member of the Arab Development Fund, Kuwait; International Cell Research Organization–United Nations Educational, Scientific and Cultural Organization (ICRO–UNESCO), Chile; and UNESCO Biotechnology France",institutionString:"Mansoura University",institution:{name:"Mansoura University",country:{name:"Egypt"}}},{id:"329385",title:"Dr.",name:"Rajesh K.",middleName:"Kumar",surname:"Singh",slug:"rajesh-k.-singh",fullName:"Rajesh K. Singh",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/329385/images/system/329385.png",biography:"Dr. Singh received a BPharm (2003) and MPharm (2005) from Panjab University, Chandigarh, India, and a Ph.D. (2013) from Punjab Technical University (PTU), Jalandhar, India. He has more than sixteen years of teaching experience and has supervised numerous postgraduate and Ph.D. students. He has to his credit more than seventy papers in SCI- and SCOPUS-indexed journals, fifty-five conference proceedings, four books, six Best Paper Awards, and five projects from different government agencies. He is currently an editorial board member of eight international journals and a reviewer for more than fifty scientific journals. He received Top Reviewer and Excellent Peer Reviewer Awards from Publons in 2016 and 2017, respectively. He is also on the panel of The International Reviewer for reviewing research proposals for grants from the Royal Society. He also serves as a Publons Academy mentor and Bentham brand ambassador.",institutionString:"Punjab Technical University",institution:{name:"Punjab Technical University",country:{name:"India"}}},{id:"142388",title:"Dr.",name:"Thiago",middleName:"Gomes",surname:"Gomes Heck",slug:"thiago-gomes-heck",fullName:"Thiago Gomes Heck",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/142388/images/7259_n.jpg",biography:null,institutionString:null,institution:{name:"Universidade Regional do Noroeste do Estado do Rio Grande do Sul",country:{name:"Brazil"}}},{id:"336273",title:"Assistant Prof.",name:"Janja",middleName:null,surname:"Zupan",slug:"janja-zupan",fullName:"Janja Zupan",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/336273/images/14853_n.jpeg",biography:"Janja Zupan graduated in 2005 at the Department of Clinical Biochemistry (superviser prof. dr. Janja Marc) in the field of genetics of osteoporosis. Since November 2009 she is working as a Teaching Assistant at the Faculty of Pharmacy, Department of Clinical Biochemistry. In 2011 she completed part of her research and PhD work at Institute of Genetics and Molecular Medicine, University of Edinburgh. She finished her PhD entitled The influence of the proinflammatory cytokines on the RANK/RANKL/OPG in bone tissue of osteoporotic and osteoarthritic patients in 2012. From 2014-2016 she worked at the Institute of Biomedical Sciences, University of Aberdeen as a postdoctoral research fellow on UK Arthritis research project where she gained knowledge in mesenchymal stem cells and regenerative medicine. She returned back to University of Ljubljana, Faculty of Pharmacy in 2016. She is currently leading project entitled Mesenchymal stem cells-the keepers of tissue endogenous regenerative capacity facing up to aging of the musculoskeletal system funded by Slovenian Research Agency.",institutionString:null,institution:{name:"University of Ljubljana",country:{name:"Slovenia"}}},{id:"357453",title:"Dr.",name:"Radheshyam",middleName:null,surname:"Maurya",slug:"radheshyam-maurya",fullName:"Radheshyam Maurya",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/357453/images/16535_n.jpg",biography:null,institutionString:null,institution:{name:"University of Hyderabad",country:{name:"India"}}},{id:"418340",title:"Dr.",name:"Jyotirmoi",middleName:null,surname:"Aich",slug:"jyotirmoi-aich",fullName:"Jyotirmoi Aich",position:null,profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0033Y000038Ugi5QAC/Profile_Picture_2022-04-15T07:48:28.png",biography:"Biotechnologist with 15 years of research including 6 years of teaching experience. Demonstrated record of scientific achievements through consistent publication record (H index = 13, with 874 citations) in high impact journals such as Nature Communications, Oncotarget, Annals of Oncology, PNAS, and AJRCCM, etc. Strong research professional with a post-doctorate from ACTREC where I gained experimental oncology experience in clinical settings and a doctorate from IGIB where I gained expertise in asthma pathophysiology. A well-trained biotechnologist with diverse experience on the bench across different research themes ranging from asthma to cancer and other infectious diseases. An individual with a strong commitment and innovative mindset. Have the ability to work on diverse projects such as regenerative and molecular medicine with an overall mindset of improving healthcare.",institutionString:"DY Patil Deemed to Be University",institution:null},{id:"349288",title:"Prof.",name:"Soumya",middleName:null,surname:"Basu",slug:"soumya-basu",fullName:"Soumya Basu",position:null,profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0033Y000035QxIDQA0/Profile_Picture_2022-04-15T07:47:01.jpg",biography:"Soumya Basu, Ph.D., is currently working as an Associate Professor at Dr. D. Y. Patil Biotechnology and Bioinformatics Institute, Dr. D. Y. Patil Vidyapeeth, Pune, Maharashtra, India. With 16+ years of trans-disciplinary research experience in Drug Design, development, and pre-clinical validation; 20+ research article publications in journals of repute, 9+ years of teaching experience, trained with cross-disciplinary education, Dr. Basu is a life-long learner and always thrives for new challenges.\r\nHer research area is the design and synthesis of small molecule partial agonists of PPAR-γ in lung cancer. She is also using artificial intelligence and deep learning methods to understand the exosomal miRNA’s role in cancer metastasis. Dr. Basu is the recipient of many awards including the Early Career Research Award from the Department of Science and Technology, Govt. of India. She is a reviewer of many journals like Molecular Biology Reports, Frontiers in Oncology, RSC Advances, PLOS ONE, Journal of Biomolecular Structure & Dynamics, Journal of Molecular Graphics and Modelling, etc. She has edited and authored/co-authored 21 journal papers, 3 book chapters, and 15 abstracts. She is a Board of Studies member at her university. She is a life member of 'The Cytometry Society”-in India and 'All India Cell Biology Society”- in India.",institutionString:"Dr. D.Y. Patil Vidyapeeth, Pune",institution:{name:"Dr. D.Y. Patil Vidyapeeth, Pune",country:{name:"India"}}},{id:"354817",title:"Dr.",name:"Anubhab",middleName:null,surname:"Mukherjee",slug:"anubhab-mukherjee",fullName:"Anubhab Mukherjee",position:null,profilePictureURL:"https://intech-files.s3.amazonaws.com/0033Y0000365PbRQAU/ProfilePicture%202022-04-15%2005%3A11%3A18.480",biography:"A former member of Laboratory of Nanomedicine, Brigham and Women’s Hospital, Harvard University, Boston, USA, Dr. Anubhab Mukherjee is an ardent votary of science who strives to make an impact in the lives of those afflicted with cancer and other chronic/acute ailments. He completed his Ph.D. from CSIR-Indian Institute of Chemical Technology, Hyderabad, India, having been skilled with RNAi, liposomal drug delivery, preclinical cell and animal studies. He pursued post-doctoral research at College of Pharmacy, Health Science Center, Texas A & M University and was involved in another postdoctoral research at Department of Translational Neurosciences and Neurotherapeutics, John Wayne Cancer Institute, Santa Monica, California. In 2015, he worked in Harvard-MIT Health Sciences & Technology as a visiting scientist. He has substantial experience in nanotechnology-based formulation development and successfully served various Indian organizations to develop pharmaceuticals and nutraceutical products. He is an inventor in many US patents and an author in many peer-reviewed articles, book chapters and books published in various media of international repute. Dr. Mukherjee is currently serving as Principal Scientist, R&D at Esperer Onco Nutrition (EON) Pvt. Ltd. and heads the Hyderabad R&D center of the organization.",institutionString:"Esperer Onco Nutrition Pvt Ltd.",institution:null},{id:"319365",title:"Assistant Prof.",name:"Manash K.",middleName:null,surname:"Paul",slug:"manash-k.-paul",fullName:"Manash K. Paul",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/319365/images/system/319365.png",biography:"Manash K. Paul is a scientist and Principal Investigator at the University of California Los Angeles. He has contributed significantly to the fields of stem cell biology, regenerative medicine, and lung cancer. His research focuses on various signaling processes involved in maintaining stem cell homeostasis during the injury-repair process, deciphering the lung stem cell niche, pulmonary disease modeling, immuno-oncology, and drug discovery. He is currently investigating the role of extracellular vesicles in premalignant lung cell migration and detecting the metastatic phenotype of lung cancer via artificial intelligence-based analyses of exosomal Raman signatures. Dr. Paul also works on spatial multiplex immunofluorescence-based tissue mapping to understand the immune repertoire in lung cancer. Dr. Paul has published in more than sixty-five peer-reviewed international journals and is highly cited. He is the recipient of many awards, including the UCLA Vice Chancellor’s award and the 2022 AAISCR-R Vijayalaxmi Award for Innovative Cancer Research. He is a senior member of the Institute of Electrical and Electronics Engineers (IEEE) and an editorial board member for several international journals.",institutionString:"University of California Los Angeles",institution:{name:"University of California Los Angeles",country:{name:"United States of America"}}},{id:"311457",title:"Dr.",name:"Júlia",middleName:null,surname:"Scherer Santos",slug:"julia-scherer-santos",fullName:"Júlia Scherer Santos",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/311457/images/system/311457.jpg",biography:"Dr. Júlia Scherer Santos works in the areas of cosmetology, nanotechnology, pharmaceutical technology, beauty, and aesthetics. Dr. Santos also has experience as a professor of graduate courses. Graduated in Pharmacy, specialization in Cosmetology and Cosmeceuticals applied to aesthetics, specialization in Aesthetic and Cosmetic Health, and a doctorate in Pharmaceutical Nanotechnology. Teaching experience in Pharmacy and Aesthetics and Cosmetics courses. She works mainly on the following subjects: nanotechnology, cosmetology, pharmaceutical technology, aesthetics.",institutionString:"Universidade Federal de Juiz de Fora",institution:{name:"Universidade Federal de Juiz de Fora",country:{name:"Brazil"}}},{id:"219081",title:"Dr.",name:"Abdulsamed",middleName:null,surname:"Kükürt",slug:"abdulsamed-kukurt",fullName:"Abdulsamed Kükürt",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/219081/images/system/219081.png",biography:"Dr. Kükürt graduated from Uludağ University in Turkey. He started his academic career as a Research Assistant in the Department of Biochemistry at Kafkas University. In 2019, he completed his Ph.D. program in the Department of Biochemistry at the Institute of Health Sciences. He is currently working at the Department of Biochemistry, Kafkas University. He has 27 published research articles in academic journals, 11 book chapters, and 37 papers. He took part in 10 academic projects. He served as a reviewer for many articles. He still serves as a member of the review board in many academic journals. He is currently working on the protective activity of phenolic compounds in disorders associated with oxidative stress and inflammation.",institutionString:null,institution:{name:"Kafkas University",country:{name:"Turkey"}}},{id:"178366",title:"Dr.",name:"Volkan",middleName:null,surname:"Gelen",slug:"volkan-gelen",fullName:"Volkan Gelen",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/178366/images/system/178366.jpg",biography:"Volkan Gelen is a Physiology specialist who received his veterinary degree from Kafkas University in 2011. Between 2011-2015, he worked as an assistant at Atatürk University, Faculty of Veterinary Medicine, Department of Physiology. In 2016, he joined Kafkas University, Faculty of Veterinary Medicine, Department of Physiology as an assistant professor. Dr. Gelen has been engaged in various academic activities at Kafkas University since 2016. There he completed 5 projects and has 3 ongoing projects. He has 60 articles published in scientific journals and 20 poster presentations in scientific congresses. His research interests include physiology, endocrine system, cancer, diabetes, cardiovascular system diseases, and isolated organ bath system studies.",institutionString:"Kafkas University",institution:{name:"Kafkas University",country:{name:"Turkey"}}},{id:"418963",title:"Dr.",name:"Augustine Ododo",middleName:"Augustine",surname:"Osagie",slug:"augustine-ododo-osagie",fullName:"Augustine Ododo Osagie",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/418963/images/16900_n.jpg",biography:"Born into the family of Osagie, a prince of the Benin Kingdom. I am currently an academic in the Department of Medical Biochemistry, University of Benin. Part of the duties are to teach undergraduate students and conduct academic research.",institutionString:null,institution:{name:"University of Benin",country:{name:"Nigeria"}}},{id:"192992",title:"Prof.",name:"Shagufta",middleName:null,surname:"Perveen",slug:"shagufta-perveen",fullName:"Shagufta Perveen",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/192992/images/system/192992.png",biography:"Prof. Shagufta Perveen is a Distinguish Professor in the Department of Pharmacognosy, College of Pharmacy, King Saud University, Riyadh, Saudi Arabia. Dr. Perveen has acted as the principal investigator of major research projects funded by the research unit of King Saud University. She has more than ninety original research papers in peer-reviewed journals of international repute to her credit. She is a fellow member of the Royal Society of Chemistry UK and the American Chemical Society of the United States.",institutionString:"King Saud University",institution:{name:"King Saud University",country:{name:"Saudi Arabia"}}},{id:"49848",title:"Dr.",name:"Wen-Long",middleName:null,surname:"Hu",slug:"wen-long-hu",fullName:"Wen-Long Hu",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/49848/images/system/49848.jpg",biography:"Wen-Long Hu is Chief of the Division of Acupuncture, Department of Chinese Medicine at Kaohsiung Chang Gung Memorial Hospital, as well as an adjunct associate professor at Fooyin University and Kaohsiung Medical University. Wen-Long is President of Taiwan Traditional Chinese Medicine Medical Association. He has 28 years of experience in clinical practice in laser acupuncture therapy and 34 years in acupuncture. He is an invited speaker for lectures and workshops in laser acupuncture at many symposiums held by medical associations. He owns the patent for herbal preparation and producing, and for the supercritical fluid-treated needle. Dr. Hu has published three books, 12 book chapters, and more than 30 papers in reputed journals, besides serving as an editorial board member of repute.",institutionString:"Kaohsiung Chang Gung Memorial Hospital",institution:{name:"Kaohsiung Chang Gung Memorial Hospital",country:{name:"Taiwan"}}},{id:"298472",title:"Prof.",name:"Andrey V.",middleName:null,surname:"Grechko",slug:"andrey-v.-grechko",fullName:"Andrey V. Grechko",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/298472/images/system/298472.png",biography:"Andrey Vyacheslavovich Grechko, Ph.D., Professor, is a Corresponding Member of the Russian Academy of Sciences. He graduated from the Semashko Moscow Medical Institute (Semashko National Research Institute of Public Health) with a degree in Medicine (1998), the Clinical Department of Dermatovenerology (2000), and received a second higher education in Psychology (2009). Professor A.V. Grechko held the position of Сhief Physician of the Central Clinical Hospital in Moscow. He worked as a professor at the faculty and was engaged in scientific research at the Medical University. Starting in 2013, he has been the initiator of the creation of the Federal Scientific and Clinical Center for Intensive Care and Rehabilitology, Moscow, Russian Federation, where he also serves as Director since 2015. He has many years of experience in research and teaching in various fields of medicine, is an author/co-author of more than 200 scientific publications, 13 patents, 15 medical books/chapters, including Chapter in Book «Metabolomics», IntechOpen, 2020 «Metabolomic Discovery of Microbiota Dysfunction as the Cause of Pathology».",institutionString:"Federal Research and Clinical Center of Intensive Care Medicine and Rehabilitology",institution:null},{id:"199461",title:"Prof.",name:"Natalia V.",middleName:null,surname:"Beloborodova",slug:"natalia-v.-beloborodova",fullName:"Natalia V. Beloborodova",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/199461/images/system/199461.jpg",biography:'Natalia Vladimirovna Beloborodova was educated at the Pirogov Russian National Research Medical University, with a degree in pediatrics in 1980, a Ph.D. in 1987, and a specialization in Clinical Microbiology from First Moscow State Medical University in 2004. She has been a Professor since 1996. Currently, she is the Head of the Laboratory of Metabolism, a division of the Federal Research and Clinical Center of Intensive Care Medicine and Rehabilitology, Moscow, Russian Federation. N.V. Beloborodova has many years of clinical experience in the field of intensive care and surgery. She studies infectious complications and sepsis. She initiated a series of interdisciplinary clinical and experimental studies based on the concept of integrating human metabolism and its microbiota. Her scientific achievements are widely known: she is the recipient of the Marie E. Coates Award \\"Best lecturer-scientist\\" Gustafsson Fund, Karolinska Institutes, Stockholm, Sweden, and the International Sepsis Forum Award, Pasteur Institute, Paris, France (2014), etc. Professor N.V. Beloborodova wrote 210 papers, five books, 10 chapters and has edited four books.',institutionString:"Federal Research and Clinical Center of Intensive Care Medicine and Rehabilitology",institution:null},{id:"354260",title:"Ph.D.",name:"Tércio Elyan",middleName:"Azevedo",surname:"Azevedo Martins",slug:"tercio-elyan-azevedo-martins",fullName:"Tércio Elyan Azevedo Martins",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/354260/images/16241_n.jpg",biography:"Graduated in Pharmacy from the Federal University of Ceará with the modality in Industrial Pharmacy, Specialist in Production and Control of Medicines from the University of São Paulo (USP), Master in Pharmaceuticals and Medicines from the University of São Paulo (USP) and Doctor of Science in the program of Pharmaceuticals and Medicines by the University of São Paulo. Professor at Universidade Paulista (UNIP) in the areas of chemistry, cosmetology and trichology. Assistant Coordinator of the Higher Course in Aesthetic and Cosmetic Technology at Universidade Paulista Campus Chácara Santo Antônio. Experience in the Pharmacy area, with emphasis on Pharmacotechnics, Pharmaceutical Technology, Research and Development of Cosmetics, acting mainly on topics such as cosmetology, antioxidant activity, aesthetics, photoprotection, cyclodextrin and thermal analysis.",institutionString:null,institution:{name:"University of Sao Paulo",country:{name:"Brazil"}}},{id:"334285",title:"Ph.D. Student",name:"Sameer",middleName:"Kumar",surname:"Jagirdar",slug:"sameer-jagirdar",fullName:"Sameer Jagirdar",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/334285/images/14691_n.jpg",biography:"I\\'m a graduate student at the center for biosystems science and engineering at the Indian Institute of Science, Bangalore, India. I am interested in studying host-pathogen interactions at the biomaterial interface.",institutionString:null,institution:{name:"Indian Institute of Science Bangalore",country:{name:"India"}}},{id:"329248",title:"Dr.",name:"Md. Faheem",middleName:null,surname:"Haider",slug:"md.-faheem-haider",fullName:"Md. Faheem Haider",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/329248/images/system/329248.jpg",biography:"Dr. Md. Faheem Haider completed his BPharm in 2012 at Integral University, Lucknow, India. In 2014, he completed his MPharm with specialization in Pharmaceutics at Babasaheb Bhimrao Ambedkar University, Lucknow, India. He received his Ph.D. degree from Jamia Hamdard University, New Delhi, India, in 2018. He was selected for the GPAT six times and his best All India Rank was 34. Currently, he is an assistant professor at Integral University. Previously he was an assistant professor at IIMT University, Meerut, India. He has experience teaching DPharm, Pharm.D, BPharm, and MPharm students. He has more than five publications in reputed journals to his credit. Dr. Faheem’s research area is the development and characterization of nanoformulation for the delivery of drugs to various organs.",institutionString:"Integral University",institution:{name:"Integral University",country:{name:"India"}}},{id:"329795",title:"Dr.",name:"Mohd Aftab",middleName:"Aftab",surname:"Siddiqui",slug:"mohd-aftab-siddiqui",fullName:"Mohd Aftab Siddiqui",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/329795/images/system/329795.png",biography:"Dr. Mohd Aftab Siddiqui is an assistant professor in the Faculty of Pharmacy, Integral University, Lucknow, India, where he obtained a Ph.D. in Pharmacology in 2020. He also obtained a BPharm and MPharm from the same university in 2013 and 2015, respectively. His area of research is the pharmacological screening of herbal drugs/natural products in liver cancer and cardiac diseases. He is a member of many professional bodies and has guided many MPharm and PharmD research projects. 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