Comparison of some MO/C-based nanostructure gas sensors sensitivity (S%) toward NO2, NH3, and CO gases.
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More than half of the publishers listed alongside IntechOpen (18 out of 30) are Social Science and Humanities publishers. IntechOpen is an exception to this as a leader in not only Open Access content but Open Access content across all scientific disciplines, including Physical Sciences, Engineering and Technology, Health Sciences, Life Science, and Social Sciences and Humanities.
\\n\\nOur breakdown of titles published demonstrates this with 47% PET, 31% HS, 18% LS, and 4% SSH books published.
\\n\\n“Even though ItechOpen has shown the potential of sci-tech books using an OA approach,” other publishers “have shown little interest in OA books.”
\\n\\nAdditionally, each book published by IntechOpen contains original content and research findings.
\\n\\nWe are honored to be among such prestigious publishers and we hope to continue to spearhead that growth in our quest to promote Open Access as a true pioneer in OA book publishing.
\\n\\n\\n\\n
\\n"}]',published:!0,mainMedia:{caption:"IntechOpen Maintains",originalUrl:"/media/original/113"}},components:[{type:"htmlEditorComponent",content:'
Simba Information has released its Open Access Book Publishing 2020 - 2024 report and has again identified IntechOpen as the world’s largest Open Access book publisher by title count.
\n\nSimba Information is a leading provider for market intelligence and forecasts in the media and publishing industry. The report, published every year, provides an overview and financial outlook for the global professional e-book publishing market.
\n\nIntechOpen, De Gruyter, and Frontiers are the largest OA book publishers by title count, with IntechOpen coming in at first place with 5,101 OA books published, a good 1,782 titles ahead of the nearest competitor.
\n\nSince the first Open Access Book Publishing report published in 2016, IntechOpen has held the top stop each year.
\n\n\n\nMore than half of the publishers listed alongside IntechOpen (18 out of 30) are Social Science and Humanities publishers. IntechOpen is an exception to this as a leader in not only Open Access content but Open Access content across all scientific disciplines, including Physical Sciences, Engineering and Technology, Health Sciences, Life Science, and Social Sciences and Humanities.
\n\nOur breakdown of titles published demonstrates this with 47% PET, 31% HS, 18% LS, and 4% SSH books published.
\n\n“Even though ItechOpen has shown the potential of sci-tech books using an OA approach,” other publishers “have shown little interest in OA books.”
\n\nAdditionally, each book published by IntechOpen contains original content and research findings.
\n\nWe are honored to be among such prestigious publishers and we hope to continue to spearhead that growth in our quest to promote Open Access as a true pioneer in OA book publishing.
\n\n\n\n
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Patil and Prakash Rao",coverURL:"https://cdn.intechopen.com/books/images_new/3547.jpg",licenceType:"CC BY 3.0",editedByType:"Edited by",editors:[{id:"164249",title:"Dr.",name:"Yogesh",middleName:"Bhagwan",surname:"Patil",slug:"yogesh-patil",fullName:"Yogesh Patil"}],productType:{id:"1",title:"Edited Volume",chapterContentType:"chapter",authoredCaption:"Edited by"}}},ofsBook:{item:{type:"book",id:"11792",leadTitle:null,title:"Insects as Food - New Dietary Sources, Production, and Quality of Products",subtitle:null,reviewType:"peer-reviewed",abstract:"
\r\n\tRecent scientific data describe insects as a great source of micro and macro nutrients with great digestibility and bio-availability. This book entitled "Insect as food" is an attempt to provide the latest and up-to-date information on various aspects of insect-based food products. The readers will definitely appreciate the capacity of insects as food for humans and feed for animals and livestock. The readers will enjoy topics related to the production and farming of insects. This book is a complete guide to producing insects at a large scale for livestock and food industries. This book will further discuss technological progress and emerging innovation incorporated into the insect product development sectors making this book a useful resource for those interested in large-scale production of alternate meat and protein analogs. Furthermore, insect-based bio-products as anti-aging constituents will also presented in this book. Finally, comprehensive studies on market development and sensory acceptability of insect foods from Asia and the rest of the world will also be welcomed in this book.
",isbn:"978-1-83768-272-0",printIsbn:"978-1-83768-271-3",pdfIsbn:"978-1-83768-273-7",doi:null,price:0,priceEur:0,priceUsd:0,slug:null,numberOfPages:0,isOpenForSubmission:!0,isSalesforceBook:!1,isNomenclature:!1,hash:"3ca360f1592f80cbe79280ce265c0f12",bookSignature:"Dr. Umar Bacha",publishedDate:null,coverURL:"https://cdn.intechopen.com/books/images_new/11792.jpg",keywords:"Edible Insects, Reproductive Cycle, Nutritional Requirements, Consumer Perception, Antioxidant Compounds, Cricket Powder, Bioactive Compounds, Nutrition Profile, Extruded Insect Products, Insect Protein Production, Emerging Technology, Insect Proteins",numberOfDownloads:null,numberOfWosCitations:0,numberOfCrossrefCitations:null,numberOfDimensionsCitations:null,numberOfTotalCitations:null,isAvailableForWebshopOrdering:!0,dateEndFirstStepPublish:"June 1st 2022",dateEndSecondStepPublish:"June 29th 2022",dateEndThirdStepPublish:"August 28th 2022",dateEndFourthStepPublish:"November 16th 2022",dateEndFifthStepPublish:"January 15th 2023",dateConfirmationOfParticipation:null,remainingDaysToSecondStep:"2 months",secondStepPassed:!0,areRegistrationsClosed:!1,currentStepOfPublishingProcess:3,editedByType:null,kuFlag:!1,biosketch:"Umar Bacha is an Associate Professor at the School of Health Sciences interested to delineate the cross-talks between metabolic cues and metabolic chronic diseases. 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High rate of gas emissions has both a negative impact on human/animal health and it can also have bad consequences on the environment and natural resources from day by day.
\nWith the start of the Industrial Revolution, the acceleration of coal and mine quarries caused a significant increase in deaths due to toxic gas. First, canaries were used in gas detectors in mines. The cost and difficulty of using different methods for determination of toxic gases have revealed the gas sensors. In 1815, British scientist H. Davy developed a gas meter called ‘Davy’s lamp’ against methane gas [1]. In 1926, Johnson produced the first commercial catalytic, combustion gas sensor, and in 1929, the company they founded with Williams became the first company in Silicon Valley in electronics [2].
\nGas sensors are used to detect combustible, explosive and toxic gases, when the measured gas concentration exceeds the threshold value they can give an alarm (sound, signal, etc.) that can be used as portable or fixed devices. The most important part of this device production is the sensor which determines 4S parameters (sensitivity, selectivity, stability, speed). Apart from them, recovery time, response time and power consumption are also other parameters. The sensor part records changes in the physical conditions or chemical components as signals (permeability, resistance, temperature, acoustic wave, capacitance, etc.) as a result of interaction between target gas and surface atoms (O−, O2−, H+ and OH−) by absorption/desorption of gas on the material surface at a specific operating temperature. Signal can correlate concentration of target gas [3].
\nThe recent change in the OSHA Time Weighted Average (TWA) Permissible Exposure Limit (PEL) is 25, 35 and 1 ppm for NH3, CO and NO2 gases, respectively [4].
\nCO is a toxic colorless gas, environmental pollutant and kills by causing hypoxia with damaged hemoglobin cells in the blood. In general, the measurement of CO gas is realized by detection of percentage of carboxyhemoglobin in the blood. Another important issue is creation of residential and automotive environment so it is so necessary fast and sensitive detection. Difficulty in detecting very low levels and continuous CO formation in the air poses problems [5].
\nOdorless and toxic ammonia (NH3) combustion, which is used in a large area as a fertilizer, refrigerant material and household cleaning product, is a major hazard. Using or producing ammonia besides any uncontrolled leaks by the infrastructures or its explosion causes health hazards. In addition, it is a chemical pollutant in the production of silicon type devices in clean room [6].
\nNitrogen dioxide (NO2) is a volatile and toxic gas. It has hazardous effects in environment as a secondary pollutant and its detection is so important. NO2 gas generates fuel burning at high temperature and in nitrogen cycle, including acid rains. Under even very low concentrations (<10 ppm) it causes serious damages for human health such as throat discomfort, transient coughs, eye irritation, fatigue and nausea [7].
\nWith nano-sized designed gas sensors, surface to volume ratio is increased for absorbed target gas as well as higher efficiency is obtained than traditional bulk-scale designed devices, because different atomic coordination and translational symmetry at the surface ensure electrical properties changing in semiconductors [8]. In particular, a dramatic increase using the nano-sized designed gas sensors have been observed in industrial areas such as pharmaceuticals, medical, automotive, building automation, space tools, wearable devices. The first study of the semiconductor material group was given by Brattain and Bardeen on germanium (Ge) in 1953 [9]. In the next study, in 1954, Heiland had a research report on the gas sensitivities of metal oxides, and also in 1962 Seiyama showed that ZnO structures were sensitive to reactive gases in the air [10]. In 1968, Taguchi-type sensors were introduced to market and metal oxide (SnO2) gas sensors were moved to industrial level [11].
\nNano-scale designed gas sensors are usually classified depending on measurement data as follows; (i) chemiresistors, (ii) thermal conductivity gas sensors, (iii) acoustic wave gas sensors, (iv) calorimetric gas sensors, (v) optical gas sensors (vi) electrochemical gas sensors and (vii) infrared absorption gas sensors [13, 14].
\nChemiresistive gas sensor working principle can be explained simply as adsorption of electron with target gas on the surface can cause charge transfer (a change in charge carrier concentration) between target gas/material surface region (receptor function) so electrical properties can be (resistance or conductivity) increase or decrease. Easy measurement with two electrodes is a factor in their preference and supplying safety.
\nToday, using chemiresistive metal oxide (MO) semiconductors, real-time gas sensor has gained great importance both in the science/industrial world due to their high sensitivity to chemical environments, low price, simple implantation, safety and durable to high temperature/high pressure, indicating that compelling conditions. Companies such as FIS, Mics, UST, CityTech, Appliedensors and Newcosmos produce millions of MO gas sensor per year, especially the Figaro company which produces Taguchi type sensors [15].
\nGas selectivity is a critical problem for metal oxide gas sensors. To increase the selectivity of metal oxide sensors, it is proposed to use a heating mode of a gas-sensing floor with rapid temperature modulation in the last studies.
\nMetal oxide semiconductor gas sensors are focused on different and new materials at room temperature with the increasing need for faster, more precise and easy gas sensing, as showed in \nFigure 1\n. Thus, the most important parameter mechanism is gas sensitivity, which still does not reveal the exact reasons (strongly related to surface reactions), can be detailed. Production techniques (spray pyrolysis, pulsed laser deposition, magnetron sputtering, spin coating, and chemical bath deposition) are undeniable facts because structure parameters, grain boundaries, point defects, surface morphology, porosity, etc. must be affected. Additionally, reducing (H2, H2S, etc.)/oxidizing (NH3, NO2, etc.) gas types and p- or n-type is also effective on the chemiresistive MO performance, as showed in \nFigure 2\n. Oxidizing or reducing gas is associated with electron affinity, which is compared to the work function of most metal oxide so in the case of oxidizing gas, the adsorbed gas molecules on the surface of the MO are anions.
\nAdvantages and disadvantages of semiconductor metal oxides (reprinted from study of [
Sensitivity measurement of material type and target gas type (reprinted from study of [
The change in electrical resistance of semiconductors can be explained as follows; formation of the space-charge depletion zone on the surface and around the particle and the energy band bending. Surface energy barriers with variable heights and widths depend on the relationship between charging the surface states of the adsorbed species for conduction electrons. In gas sensors using n-type semiconductor oxide, it has been observed that the resistance of the oxide increases with the interaction of gases such as O3 or NO2, while the resistance decrease of the oxide occurs with interaction of gases such as CH4 and CO, as showed in \nFigure 2\n.
\nIt is discussed that resistive-type metal oxide semiconductors produced by nanostructures (especially thin films) in detail toward NH3, NO2 and CO gases. Additionally, effect of doping and nanocomposite forming with C-based material (especially carbon nanotubes) were studied.
\nSince 1962, the addition of the oxygen contained in the metal oxides to the reaction so increase of reactions and their stable chemical transduction properties which can reversibly convert chemical reactions on a surface make the metal oxides attractive for detect various harmful, toxic, and explosive gases. Development of gas sensors, which are almost 21% of the metal oxides used in the field, is rapidly increasing [17]. Because they have unique properties such as low cost, long lifetime, fast response time and relatively high sensitivity. However, some restrictions are detected in these structures such as background gas effect, poor selectivity and power consumption in high temperature conditions which could not be proper for especially wireless applications.
\nBasically, the main challenge is they operate only at elevated temperatures and consume more power with high operating temperatures. Physisorption and chemisorption are surface adsorption forms of oxygen. Physisorption to chemisorption needs activation energy with realized by increasing operating temperature. In addition, forming of oxygen species depends on the operating temperature substantially. Sun et al. reported that molecular species are more than atomic species below 150°C, this cause a decrease in gas sensitivity [18].
\nAnother goal of gas sensitivity works is to ensure that electrical change in the gas environment occurs not only at grain boundaries but on the entire material surface. Since grain boundaries are smaller than MO particles, surface chemistry is more effective and the effect of grain boundaries on electrical change is not considered.
\nTo achieve high performance from MO gas sensors, detailed knowledge of the gas sensing mechanism is essential. In general, it can be explained as follows; oxygen adsorption on the surface of sensing material, adsorbed oxygen species (extrinsic surface acceptor states) molecular (\n
Among metal oxide gas sensors single (ZnO, NiO, TiO2, SnO2, WO3, etc.), binary and ternary samples have unique properties such as chemical stability, relatively low harmful for environment, abundant in nature and low cost. Wang et al. showed that metal oxides selected for real gas sensors can be separated according to their electronic structure [20];
d0 transition metal oxides: In this group (WO3, V2O5, TiO2 and etc.), d0 electronic configurations are preferred with their wide band gap energy and surface forms so it can measure easily.
pre-transition metal oxides: In this group (Al2O3, MgO and etc) are not preferred due to neither electrons nor holes forming so occurs very band gap energy, structural instability and difficulty of measure electrical conductivity.
post-transition metal oxides: They have d10 electronic configuration. ZnO, SnO2 Ga2O3 and In2O3 are preferred in MO gas sensor applications. Because they are so proper for electron accumulation and chemisorption of donor-like species occurrence.
In semiconductor gas sensor applications, advantages of thin film using are low resource waste, high surface/volume ratio, low power consumption, easy compliance with integrated circuits and easy alteration of electrical properties with changing film production parameters. Thin film technology allows the film properties to be changed by keeping the thickness parameter under considerable control. In this way, thin films are easily integrated into the device during the material production process. They can also be used as electronic circuit elements by acting as new materials when they are produced in multilayer.
\nThin film metal oxides are used by the detection a lot of gas types such as Carbon-based (CO, CO2, CH4, C2H5OH, C3H8), nitrogen-based (NH3, NO, NO2), H2, H2S, ethanol, acetone, LPG and moisture.
\nThe large number of grain boundaries in thin film polycrystalline MO’s limits mobility, thus reducing carrier concentration and decreasing gas sensitivity. The presence of depletion layers in these grain boundaries is the most important factor that reduces mobility. Grain boundaries affect mobility due to their positioning to potential barriers with high intensity defect levels.
\nThere have been a lot of ZnO thin film study to detect NO2 gas sensing that have been reported with different morphologies nanowires, nanorods [21], nanoprisms [22] and nanospheres [23] in order to enhance surface area. In 2019, Duoc et al. synthesized ZnO nanowires and nanorods with using on-chip grown via hydrothermal method at room temperature NO2 gas sensing [24]. The diameter of these structures severely affected gas sensing, indicating nanowires were more sensitive than nanorods. ZnO nanobarded fibers were synthesized by electrospinning and chemical bath deposition. These structures showed improved NO2 detection performance for gas concentrations up to 30 ppb [25].
\nIn our previous study, nanoflower shaped n-type ZnO films synthesized by chemical bath deposition and their 0.5 ppm NO2 gas sensing was detected, showing in \nFigures 3\n and \n4\n [26]. Operating temperature was chosen at 200°C due to statical recovery kinetics were worse under this temperature. Oxygen vacancies (oxygen-deficient ZnO) acted as adsorption sites, electron donor sites and nucleation centers for small metal clusters. Reaction on the ZnO film surface was given by two equations between exposing oxidizing type NO2 molecules and oxygen species in the ZnO grain boundaries;
\nSEM images of (a) ZnO and annealed ZnO films at (b) 450°C, (c) 500°C and (d) 550°C (reprinted from [
0.5 ppm NO2 gas sensitivity of ZnO thin films at 200°C (reprinted from [
With increasing annealing temperature and thereby decreased grain sizes caused an increase surface/volume ratio and NO2 gas sensing, as expected for n-type ZnO. It was interesting that very high annealing temperature (>500°C) could lead to deterioration on the substrate/deposited layer interface, as showed in \nFigure 3d\n.
\nTo arrangement structural, morphological and gas sensing properties of MO nanomaterials, doping is an effective method with metallic ions (Al, Fe, Co, Cu, Ag and etc.). Defect sites and location of a host or doping ions determines grain size and electronic band of nanomaterials thereby sensing layer resistance. The substituted atoms can act as reactive sites for gas adsorption [27]. On the other word, surface impurities and defects with generating doping ions and thereby adsorption sites can cause extrinsic electronic states [28]. The reduction of the grain size to nanometers or to a scale comparable to the thickness of the charge depletion layer leads to a dramatic improvement in the gas sensitivity. It has been also found that the crystal structure of the grains affects the absorption of gases. Metal atom doping can also increase gas selectivity as reported by Govardhan and Grace [29].
\nIonic radius difference plays a very important role between metal dopant and host metal (Zn, Sn, Fe, etc.) in gas sensing. Interstitial sites and oxygen vacancies are so critical in physisorption and chemisorption processes. To determine electronic traps in the doped structure deep level transient spectroscopy is an effective method.
\nHowever, heavily doped metal oxides (>10%) showed poor gas performance with high concentration defect regions, which is attributed to limitation on the Fermi level shift during interaction with the target gas [30].
\nThe highest surface roughness values are 5% Al doping, and samples with this dopant have the highest NH3 response times, explained by Aydın et al. [31]. Other Al:ZnO film studies were received by Dimitrov et al. [32] and Patil and Sondkar [33] toward CO gas.
\nIn our previous study, Al-source effect was investigated on the NH3 gas sensing and response time parameters as showed in \nFigures 5\n\n
SEM images of (a) pure ZnO and (b, c, and d) different Al:ZnO films depending on Al-source reprinted from [
NH3 sensing response of Al:ZnO films as a function of time (reprinted from [
(a) NH3 gas response and (b) NH3 gas recovery times of Al:ZnO films (reprinted from [
As showed in \nFigures 5\n and \n6\n, nanorod formations (\nFigure 5b\n) had highest response times and gas sensing at low temperatures in powder Al-source used samples. Al-sources have high impact on gas sensing character due to changing film growth process and surface morphologies.
\nThe exceptional and unique properties of carbon-based materials (carbon nanotubes, graphene, graphite, and plumbane) offer a great advantage for the production of improved composites, while their applications as a matrix element depends primarily on the relationship between the matrix and the other material. Gas sensor sensitivity of some MO-C-based nanostructures (MO: ZnO, SnO2, TiO2) is showed in \nTable 1\n and SWCNT-MO structure studies are so rare until now, interestingly. Because SWCNTs are much more expensive than MWCNTs and titanium oxide film production is usually expensive by physical methods. Defects forms such as atom vacancies, functional groups and stone wall defects on nanotubes can enhance the sensitivity toward different gases with metal oxide compositions. Additionally, as a matrix material supplies high quality of crystal lattice leading to a quite low electronic noise and they act as the Schottky barrier. These defect sites lower the activation energy barrier thus enabling chemisorptions of analytes on the surface of CNTs and make room temperature measurements possible [35].
\n\n | NO2 gas sensing | \nNH3 gas sensing | \nCO gas sensing | \nReferences | \n
---|---|---|---|---|
Graphene-ZnO | \n17.4 (100 ppm) | \n1.25 (10 ppm) | \n23.5 (1 ppm) | \n[36, 37, 38] | \n
Graphene-SnO2\n | \n2.45 (20 ppm) | \n1.9 (500 ppm) | \n9 (400 ppm) | \n[39, 40, 41] | \n
Graphene-TiO2\n | \n— | \n1.7 (10 ppm) | \n6.5 (100 ppm) | \n[42, 43] | \n
MWCNT-ZnO | \n1.025 (10 ppm) | \n41 (10 ppm) | \n— | \n[44, 45] | \n
MWCNT-SnO2\n | \n2 (10 ppm) | \n1.06 (60 ppm) | \n0 (100 ppm) | \n[39, 46, 47] | \n
MWCNT-TiO2\n | \n— | \n2 (100 ppm) | \n7 (50 ppm) | \n[48, 49] | \n
SWCNT-ZnO | \n6 (250 ppm) | \n— | \n0 (50 ppm) | \n[50, 51] | \n
SWCNT-SnO2\n | \n11.1 (10 ppm) | \n50 (100 ppm) | \n1.29 (50 ppm) | \n[52, 53, 54] | \n
SWCNT-TiO2\n | \n— | \n— | \n— | \n— | \n
Comparison of some MO/C-based nanostructure gas sensors sensitivity (S%) toward NO2, NH3, and CO gases.
In general, incorporation of C-based material into MO structure, n-type to p-type convert or p-n junction are observed so active sites available for gas adsorption and formation desired depletion layer [36].
\nAnother improvement mechanism approach at room temperature proposed by Tai et al., indicating that supporting role of MO nanoparticles layer (first depletion layer from adsorption of ionized oxygen) as well as formed accumulation heterojunction at interface between MO and C-based material (second depletion layer) [37].
\nIn a recent study, Lee et al. explained that improvement mechanism that was attributed the removal of oxygen-containing functional groups, the supply of electrons from the oxygen vacancies of ZnO material, and the formation of C-O-Zn bonds in ZnO-rGO membrane and operation under 100 ppm NO2 at room temperature [55].
\nAmong C-based materials, two types of carbon nanotubes (CNTs) (both single-walled [SWCNT] and multi-walled [MWCNT] carbon nanotubes) are so attractive in gas sensor support material studies due to their room temperature gas sensing, fast response and good reversibility properties. Hollow cores and inner/outside walls of CNTs supply large gas adsorption regions so they allow donating/withdrawing charge carrier mobilization [56]. Therefore, it causes a change in charge carrier concentration.
\nMulti-walled carbon nanotubes (MWCNTs) are nanoscale materials that comprise of several concentric single walled carbon nanotubes (SWCNTs) and exhibit diameters in the range of 5 and 30 nm [57]. Purification of MWCNTs (acid treatment, oxidation by heating, filtration, centrifugation, size-exclusive chromatography, etc.) is a preferred method to observation of no signal between target gas/CNT surface [58].
\nSputter of nanoclusters of proper type atoms on surface provides catalysis process, enhancing gas sensing with functionalization of CNTs [59].
\nAs reported to our previous study, MWCNT coating and MWCNT etching with HCl acid treatment effect was investigated on nanoflower ZnO seed layer against CO gas, showed in \nFigures 8\n and \n9\n [60]. The gas-sensing results had been shown that the response had been dramatically enhanced with the decoration of MWCNTs and rMWCNTs/ZnO sensor had exhibited the highest response to CO gas at 70°C. Consequently, it had been determined that gas sensing performance of the MWCNTs-decorated ZnO sensors had improved surface reactions with ZnO lattice. This may be attributed to the diffusion of the target gas through MWCNTs nanochannels.
\nSEM images of (a) ZnO/MWCNT and (b) ZnO/etched MWCNT films (reprinted from [
Gas sensing parameters of ZnO/MWCNT film (reprinted from [
In global, gas sensor market demands high performance on all 4S parameters (most common from ppb to ppm), miniaturization of weight, compatibility with other device components/wireless, flexibility for especially wearable devices and fabrication cost. It is expected to reach nearly 3 billion dollars in 2027. Recently, chemiresistive metal oxide semiconductor gas sensors are so interesting due to low cost, relatively high sensitivity and easy integration with CMOS compatible devices. The fact that the metal oxide gas sensor studies are very wide and there are quite a lot of publications in the literature about this topic. Hence some limitations are obligatory in this chapter.
\nUnlike other gas sensors in chemiresistive gas sensors, target gas concentration variation can be done in a quantitative way by direct measurement of electrical resistance. A change in the barrier height occurs between the particles due to the reducing or oxidizing of target gas. This detection largely depends on the grain size, depletion layer width and conduction characteristics of the nanostructures. Debye length must be compatible to the depletion layer.
\nLong-life sensitivity is still a key challenge. Today, the first and most common approach can be given as rapid decrease of material dimension (3D to 1D) and thus it has rapid expansion on the sensitive region but other factors (background gas, grain boundaries, granular forms, humidity and etc.) can be disregarded. Additionally, minimum particle size and enhanced/tunable surface reactivity at room temperature are main goals in a lot of studies. However, particle stability thereby gas sensing performance is not stable especially with particle size changing. Gas transfer via micro-, meso-, and nano-porous sensing films with their assembled hierarchical, hollow, and yolk-shell forms has an enormous effect on interaction of target gas-oxygen species-nanoparticles.
\nIn this study, metal oxide gas sensors by nanostructures were investigated comprehensively. ZnO nanoflower, Al:ZnO depending on Al-solution type and ZnO/MWCNT films were investigated toward different gases from our previous studies. Gas sensitivity was preferred main gas sensor parameter.
\nThe results show that there is an interaction between the gas molecules and the sample surface based on the exchange of charges. While there is no gas in the environment, O2 molecules adsorbed on the sample surface form an electron depletion zone. When the sample interacts with gas molecules, O2 molecules also interact with the gas, and O2 molecules begin to be dislocated from the surface. By separating O2 molecules from the surface, electrons are released according to the property of the gas (reducing or oxidizing), or an electron is ionized from the sample. Thus, the change in electrical conductivity is observed. The detection rates and return mechanisms of the samples have also been fairly quick. Return times indicate that the main mechanism between the gases and the sample surface is physical adsorption. In physical adsorption, gas molecules are held in structurally formed cavities on the surfaces of the container in which they are located, interacting with the surface atoms Van der Waals. This phenomenon is reversible.
\nIn MO and metal doping MO studies, film growth process must be under control to avoid agglomerative formations and un-expected ion positions in crystal structure, this causes gas adsorption process decreasing. Similar effect also occurs in C-based material/MO nanocomposites however having bonds of C-based materials and p- to n-type conversion/p-n junction have improvement effect on the gas sensitivity with expanded depletion region, indicating room temperature sensing.
\nOn the other hand, in improvement studies of gas sensors, metal oxide gas sensors based on micro-hotplates fabricated with micro-electro-mechanical system (MEMS) technology that needs to be developed due to being restrictions on material and design. Uniform mesoporous structures are also desirable because they allow more sensing regions for gas diffusion. Additionally, metal organic frameworks (MOFs) with ultrahigh porosity have been also so attractive especially last years.
\nConsidering the circumstances mentioned above, engineering control over the metal oxide structure and sensor design is so critical in order to obtain high stability as well as high gas sensitivity. Development of new metal oxide material compositions and their high stability/crystallinity will bring high performance gas sensors. New nanofabrication techniques and surface improved studies have contributed to development metal oxide gas sensors.
\nI would like to thank Emin Yakar and Sani Demiri for academic support. Also, I would like to thank Irmak Karaduman Er and Selim Acar for their help in the gas sensor performance measurements section.
\nThank you to the Science and Technology Application and Research Center (ÇOBILTUM/ÇOMU) for supporting instrumental analysis.
\nMentorship is the bidirectional partnership between a mentor, who acts as a guide or teacher, and a mentee, who acts as a learner. In graduate medical education (GME), mentorship serves to enhance mastery of curriculum content and is important in conveying various non-clinical aspects of training like professionalism, networking, values, clinical judgment, and other soft-skills that are not easily taught in a structured curriculum format [1, 2, 3]. This is an often overlooked aspect of personal and professional trainee growth process, as this chapter will outline in granular detail.
Mentorship is important for a variety of reasons, including the ability of participating parties to develop opportunities in education, personal growth, and professional support [4]. Because it is not a strictly defined process, mentorship may appear somewhat ambiguous to participants. As such, mentorship is not to be confused with advising, coaching or sponsorship [5]. Advising is a system in which one party offers advice and guidance to another party. This is often an administrative task to help ensure the ‘advisee’ is on track; thus it tends to be a unidirectional exchange [6, 7]. Sponsorship typically involves a well-connected individual advocating for the career advancement of a less established individual. Similar to advising, it is a primarily unidirectional relationship [8]. While mentors may also engage in sponsorship, the two concepts are definitionally distinct while having the potential for synergistic interaction [9, 10].
Mentorship, which is based largely on the difference in experiences between individuals at various stages of their careers, creates a space to “flatten” the vertical hierarchy that governs medical education and offers an opportunity for a more horizontal exchange of information and perspectives. While mentorship is not a new concept or practice in medicine, the analysis of effective mentorship and its role in addressing modern challenges in postgraduate medical education is relatively new, and an area that clearly warrants more investigation [11]. The goal of this chapter is to outline different approaches toward mentorship and provide the reader with basic concepts relevant to effective and competent practice of mentorship.
Mentorship can be used as a tool to improve outcomes, professional transitions, research productivity, recovery from burnout, and can even teach resilience. The role of mentorship in easing the transition from being a medical student to becoming a practicing clinician has been demonstrated in several studies [12, 13, 14, 15]. Similar to medical students entering into residency training, nurse practitioners experience a similar transition and ‘reality shock’ when they move to a full-time hospital position [16, 17]. Of importance, a negative experience during this transition can have significant impact on preventing individuals from reaching their potential and may cause some to even leave the profession. The dichotomy between expectations and reality, along with increased responsibility, can take a toll as individuals navigate their new roles. When mentorship is utilized to ease such transitions, confidence and competence of mentees may increase [18, 19]. It may also be reasonably expected that mentorship-based interventions may produce a number of beneficial effects, including decreased burnout and turnover [18, 20, 21, 22].
Based on the above observations, it follows that mentorship is an emerging tool in combating burnout. In fact, residency training is the stage where physicians are most vulnerable to burnout [23, 24, 25, 26]. The annual cost of burnout-related medical errors and workforce turnover is estimated to be $4.6 billion excluding the emotional cost of these errors to patients, families, and physicians [23, 27, 28]. Burnout is largely due to work demands, personal relationship strain, lack of rest/sleep, and high levels of responsibility [29, 30, 31]. Residents who have experienced burnout identified mentorship from colleagues and attendings as an important part of recovering from this insidious condition [23, 32]. Additionally many of the factors related to burnout are ubiquitous to residency and by implementing peer mentorship from more advanced residents, programs have been able to normalize the intern experience and minimize difficulties, while promoting resilience and wellness in these vulnerable groups [33, 34].
It has been shown that mentees generate more peer-reviewed publications, receive more grant funding, report greater career satisfaction, and are more likely to be mentors themselves [8, 35, 36]. Mentees are also likely to achieve faster academic promotion and have greater faculty retention [37, 38]. Despite these benefits, the number of physicians engaged in academics and research is decreasing, the proportion of NIH-funded principal investigators over age 60 is increasing, and it is becoming more difficult for early-physician scientists to find mentors [37]. Furthermore, the expectations of physicians at the conclusion of their training are extensive, and include proficiency in clinical, teaching, scholarly, and administrative duties [39, 40, 41]. Mentorship is a means for mentees to develop soft skills such as written and verbal communication, team building, leadership, professionalism, and various other nontechnical skills – items that are often not included in our standard curricula or overlooked during training [39]. In addition, mentees benefit from professional coaching, emotional support, and networking opportunities provided by mentors [42], and mentorship meetings that include discussions of wellness, mindfulness, and coping skills add further benefit to participants [22, 43, 44, 45].
The many benefits of mentorship outlined above are not just limited to mentees. Of importance, mentors are also more likely to report higher career satisfaction, greater academic productivity and publications, personal gratification, and renewed passion for medicine [46, 47]. It is not uncommon for attending physicians to experience “monotony” of their everyday routines – a factor that undoubtedly contributes to burnout [48, 49]. Within this broader context, the opportunity to interact with enthusiastic trainees and seeing medicine from a fresh perspective can be both refreshing and rejuvenating [50, 51]. Furthermore, mentorship is a way to extend one’s legacy by supporting the professional longevity and acumen of the next generation of physicians [37]. It is in the best interest of society to train compassionate and competent physicians, and among the most important aspects of long-term sustainable development is the fostering of mentorship as an avenue of transmitting experience-based skills, knowledge, and the very important ability to self-reflect and embrace self-improvement [52]. The field of medicine is evolving rapidly, and physicians further removed from training may benefit greatly from knowledge of new approaches, schools of thought, technologies, and other trends shared by their mentees.
Mentorship is important in guidance regarding setting and managing expectations for daily practice and career trajectory. As such, it is a very effective method for achieving better professional outcomes and retention. This type of intervention is especially needed to address women leaving medicine, a trend that is increasingly costly and dangerous for the medical system and patients. Of concern, nearly 40% of women physicians decide to pursue part-time work or leave medicine altogether within six years of completing residency [53]. Among reasons for this phenomenon are discrimination, salary inequity, and harassment, but the main challenge to women in medicine continues to be the difficulty of balancing work with family demands [54, 55, 56]. While systemic changes, such as expanded parental leave policies, need to be made to ease this tension for female physicians, mentorship is one of many tools that can help. Mentorship provides an avenue for women (and men) to come together and discuss the real challenges that women face in medicine, help younger trainees manage their expectations, and may ultimately yield increased research projects to create useful solutions [57, 58, 59].
There are important additional gender-specific considerations. For example, research shows that it may be more challenging for women to find mentors [42]. One proposed reason for this is the lack of availability of mentors with similar backgrounds and/or experiences. For example, there are fewer women mentors available to mentor surgery residents [60]. This is not only due to the relatively fewer women in the field, but also due to the additional unique time pressures in personal life faced by women surgeons [61]. Similar considerations apply to other male-dominated disciplines where there is already a lack of female mentors, and women in those fields often do not have the time to commit to mentorship due to competing priorities and external demands [62, 63]. Women may also feel somewhat uncomfortable reaching out to male mentors due to gender dynamics [64]. It naturally follows that the paucity of female mentors in certain areas is deleterious to diversity in the medical profession, since it has been noted that specialty fellows-in-training consistently indicate that they chose their subspecialty largely due to having had a mentor in the field [42].
As a consequence, without sufficient representation of female mentors in subspecialties, fewer women have the support and the opportunity to enter those fields, which ultimately perpetuates the cycle of exclusion. Institutional support such as dedicated time for mentorship could be a helpful factor in increasing numbers of female mentors. It is also harder for individuals from underrepresented groups to find mentors [65, 66], and despite the best intentions the experiences of microaggressions or outright bias continue to occur [67, 68]. Peer mentorship has been especially helpful in bridging this gap for underrepresented minority trainees, since successive classes of trainees have been increasingly diverse [69, 70]. Due to the uneven opportunity for organic mentorship, formal mentorship programs have also been important to ensure fair and equitable access to mentors. In summary, there continues to be an unmet need for mentors, with large numbers of residents and other medical trainees reporting that they wish they had mentors or that they had difficulty initiating a mentorship [42, 71]. This crisis is negatively affecting the medical profession and requires urgent and durable resolution.
The senior mentorship model is the traditional mentorship model in which the mentor is a well-established faculty member who can provide guidance informed by personal experience and professional connections [72]. Senior mentors are well positioned to serve as sponsors and can provide mentees with more opportunities for professional advancement. A major barrier to the success of this type of relationship is the presence of an institutional hierarchy – and thus power gradient(s) - that insidiously influences all interactions between mentor and mentee [73, 74, 75]. The power dynamic results in mentees feeling uncomfortable showing vulnerabilities, speaking honestly, and challenging the mentor when appropriate [75, 76]. It also can lead mentees to overextend themselves in a pursuit to meet their mentors’ expectations, which ultimately may degrade the relationship [77]. Finally, there is much less diversity among senior attendings, thus limiting the diversity among available mentors.
Peer mentorship is a very successful approach that facilitates access to mentorship experience for individuals early on in their careers, thus increasing the likelihood that they will continue to serve as mentors throughout their career [67]. It also eliminates a certain level of formality and hierarchical barriers that exist in traditional mentorship relationships, thus providing a more flexible and relaxed environment. For example, it is not as daunting to reschedule a meeting with a peer as it may be to do the same with a senior leader. In various studies, residents have noted that it is easier to go to a peer resident mentor than to a faculty member [78]. This is potentially due to increased approachability and lessened fear of being criticized or judged.
Peer mentorship has been especially successful for underrepresented minority students who may experience cultural challenges in medicine, especially when there is a lack of representative attendings or faculty mentors [79, 80]. Connecting residents at different levels of training addresses some of the barriers to diversity in mentorship. Beyond technical skills, there are certain ‘unspoken rules’ that residents must pick up in the hospital and postgraduate environment. Having a peer mentor can help assuage this discomfort and facilitate learning these unspoken rules and expectations, especially related to being a minority in medicine [67]. The peer mentorship model helps both parties gain confidence, connect with colleagues, broaden professional networks, and can be a powerful tool for experience-based knowledge sharing between senior and junior residents [67]. Such peer mentorship programs have been implemented successfully for residents and staff from underrepresented minority groups [67, 81, 82].
The peer mentoring model is also an effective way to build a growing cadre of female mentors – a factor important in addressing some of the gender-based issues associated with male predominance across certain medical disciplines [83, 84]. The increased flexibility of a peer-based mentoring approach makes it more attractive for female residents to mentor each other and can make mentees feel more at ease by eliminating the hierarchy.
Also known as one-on-one mentorship, this is a more traditional approach in which there is one mentor and one mentee, usually working together in a long-term professional relationship. The primary advantage of this model is the opportunity to invest deeply in a single, more dedicated relationship [85]. However, because time constraint is a concern for many mentors, it is important to note that weekly and monthly meetings were both shown to have equal success rates, which may make it easier for individual mentors to commit to more mentees [86]. A significant drawback of this method is the lack of diversity offered from a single mentor.
Group, ‘team-based,’ or ‘multiple-mentor’ model is an approach where a mentee has several mentors, each facilitating growth in different, often complementary areas [87, 88]. This method allows for more diversity in both content and perspectives; however, it is possible that mentors and mentees are more likely to develop a more superficial bond through this practice. This model also puts a higher burden on mentees as they must coordinate logistics and time-manage multiple mentors, all while requiring less time from individual mentors. Furthermore, as discussed pre previous sections, it can be difficult to find one mentor, let alone multiple, so supply of mentors remains a major limiting factor. A version of multiple mentoring is a ‘team-based’ approach in which the various mentors communicate among themselves in order to facilitate more efficient mentoring of an individual mentee [78]. A summary of commonly employed mentorship models is provided in Table 1.
Pros | Cons | ||
---|---|---|---|
Mentor Identity | Senior Model | Greater potential for sponsorship Mentor conveys more collective experience, insight, and wisdom Generally better for professional guidance | Lack of diversity amongst available attendings Barriers to open discussion due to hierarchy |
Peer Model | Fewer barriers to open discussion due to diminished sense of hierarchy Less formal, More flexible Fresh memory of institution specific advice Can be cathartic for mentor Generally better for emotional guidance | Potentially less sponsorship and fewer networking opportunities for vertical career progress | |
Structure | One-to-One Mentorship | Potentially more rewarding for mentors Mentee tends to model mentor’s path and behavior making it easier to attribute success Fewer people for mentees to meet with | More time consuming Less diversity in presented perspectives and more limited areas of focus |
Group/Multiple Mentorship | Less time strain on mentors More collaborative and diverse network reinforces the team based care model Mentee gets guidance in more areas | Limited discussion breadth with each mentor Potentially less feeling of investment in mentorship Increased time strain on mentees |
Mentorships include either a peer or senior mentor and either a one-to-one or multiple mentorship structure.
Senior mentors provide more experience and connections but have limited availability and less candid conversations. Peer mentors provide less formality and more candid discussion but offer fewer career progress opportunities. One-to-one mentorships provide the opportunity to develop deep relationships but can be more time consuming for mentors and provide less diverse perspectives to the mentee. Multiple mentorship reduces the strain on mentors, and offers more diverse perspectives, but increases the logistical work for mentees. All combinations of mentorships organization outlined in the table can be adapted to a virtual environment which can potentially lead to larger and more global mentorship programs.
Micromentorship is a model proposed by Waljee, et al., in which the mentorship relationship changes based on goals, and focuses on frequent, brief, informal communication and feedback, targeting improvement in very specific areas [89]. This is better suited to younger generations who have grown up in the technology era, as it has been shown that they are more purpose-driven, show preference toward collaboration and horizontal/flat social structures, are more focused on end product deliverables, and above all are accustomed to instant access to information [89]. It also provides benefits to the mentor – primarily because time constraint is a major concern – by decreasing the amount of time set aside for mentorship meetings. Under this paradigm, a simple intervention such as a quick text message, email, or phone call may be sufficient to meet a particular mentee’s needs and expectations. The micromentorship model can be adapted and scaled to include the increasingly virtual social interaction landscape, with informal meetings, which typically involve less planning, and the ability to more readily connect people across the globe.
Micromentorship is highly compatible with the group mentorship model in which a mentee has many mentors, all focused on providing guidance in diverse areas. This also prepares the mentees for more effective participation in modern team-based medicine approaches, addresses some issues of isolation among residents, and strengthens the feeling of community [39]. This model also empowers mentees by reducing the effects of the hierarchical structure of the traditional mentorship model and by eliminating a level of formality which, within the medical system, can be very beneficial to sharing knowledge, experience, and bidirectional feedback. By providing trainees with a greater stake in their community and collective decision-making, institutions will likely reduce attrition and improve retention of talent at the same time.
Maslow’s Hierarchy of Needs is a general principle stating that foundational needs must be met before higher level developmental processes like self-actualization can be met. Hale, et al., adapted this hierarchy to help tackle the issue of burnout among medical residents and to address critical wellness issues [90]. In their model, mentorship is placed at the highest tier as a method of accomplishing self-actualization. However, this model could be reasonably expanded to view mentorship as a tool to address various levels of needs rather than just self-actualization (Figure 1).
Remapping Maslow’s Hierarchy of Needs to represent general focus areas of mentorship. Mentorship practices can focus on fostering a sense of belonging, esteem, self-actualization, safety, and improving physiologic conditions.
For example, when initially setting general goals for the mentor-mentee relationship, there should be a discussion of where to focus efforts so that the needs can be optimally met. If the mentor and mentee agree to emphasize wellness, then implementing reflection and wellness check-ins during regularly scheduled meetings could address the corresponding domain components [91, 92]. Implementation of reflective practices may help emphasize wellness, with benefits in both mental and physical health domains [92, 93, 94, 95]. Mentorship can target self-actualization through discussions about professional identity or career mapping. Building of one’s esteem can be accomplished by treating each other with respect and fairness and working on various projects (including research) together to reinforce the value that each member of the team adds to the final outcome [96, 97]. The general domain of “safety” can be addressed by exchanging advice on practical life matters, including financial topics, as well as having candid conversations about personal boundaries [97, 98, 99]. While this framework is not universally applicable across all mentorship relationships, it may help in setting goals and creating actionable items for the pair to work on. This model also works very well with the ‘multiple mentor’ model, where different mentors could be responsible for addressing different aspects of the mentee’s growth. This method could also be helpful in addressing the need for diversity within a mentorship team; for example, matching a female mentor with a female mentee to discuss work-life balance or wellness [77].
Prior to engaging in mentorship, mentors should reflect on their own education and experiences at various levels of training [100]. They should identify what skills, behaviors, or thought patterns they found helpful and formative. They should reflect on good advice given to them by their own mentors or colleagues. Do they remember how they felt as a student, so they can understand what (and how) the mentee is experiencing? What were elements of successful mentorships and professional interactions that they have had? What do they wish they had been taught? What characteristics do they hope their own doctors possess? What do they hope for the future of medicine? What do they want to pass on to the next generation? Mentors should use this thought exercise to inform their mentorship technique and goals. They should revisit their answers regularly to ensure they are staying on track and mentoring with intention [34, 101].
Among key benefits of a fruitful mentor-mentee relationship is the generally higher intrinsic motivation among mentees [102]. This is important because intrinsic motivation is positively associated with ongoing focus on self-improvement and life-long learning. Thus, measures to increase intrinsic motivation amongst medical trainees could have positive implications for one’s entire career. Opportunities that support autonomous learning were shown to cultivate intrinsic motivation, which could be implemented in mentorship. For example, the mentor could invite his or her mentee to conduct research and present information on any topic of their choosing. This, in turn, provides the mentee with valuable skills related to self-directed, independent work.
Mentees must enter into a mentorship knowing that the onus of cultivating the relationship rests primarily on them [77]. First, they must identify a potential mentor with consideration of personality fit, field of expertise, career and life experience, and professional network. In the absence of an organized mentorship structure, the mentee should initiate contact and set up a meeting to discuss the viability of a potential mentorship relationship. If both parties agree to move forward, a series of meetings should outline the general goals of the mentorship, specific goals and topics of interest, frequency and type of communication, as well as various work and learning styles [77]. Both parties should consider outlining expectations for the relationship and for each other – something discussed in more detail in a subsequent section on mentorship malpractice. After that, general and specific goals can be set, optimally in an orderly, well-outlined fashion.
The mentee must come to subsequent meetings prepared with discussion points, including challenges that they seek guidance on, as well as the status of any projects they are working on with their mentor. Optimally, they should leave the meeting with a list of ‘action items’ to complete by the next meeting, as well as a mutually agreed date for the next meeting. Mentees should seek feedback at regular intervals, frequently enough to ensure continuity of experience. Feedback should encompass mentee-specific goals and objectives. Some guiding questions to help evaluate the relationship include [103]:
To what extent has the mentor helped build confidence and satisfaction within profession and career?
Do I feel that my mentor is focused on my performance, career development, and personal well-being to the extent that I expect?
Are our meetings productive and driven by outlined goals?
Do I feel that our conversations are kept confidential?
Am I comfortable disagreeing with my mentor and expressing my opinions?
Am I encouraged to give feedback to my mentor?
Are we considerate of each other’s time?
Does my mentor motivate me to excel?
Is my mentor open to hearing new ideas and perspectives?
Do I appreciate and show gratitude towards my mentor?
Do I follow through on commitments made?
Do we meet on a regular basis?
Do I feel valued as an individual and feel like I am encouraged to give feedback to my mentor?
Evaluation of these answers could be on a graded scale from 0 to 5 as suggested by Wadhwa, et al. [103]. In terms of attitude, mentees should be generally appreciative and show gratitude for their mentor’s time. They should be honest about their limitations, take initiative, follow through with tasks, take risks and be willing to leave their comfort zone [77]. They should be eager to learn from their mentors and show respect in all interactions.
In order to ensure high quality of mentors and excellent mentee experience, involvement in a mentorship program must be voluntary, otherwise an advising-type relationship tends to emerge [86]. While there could be incentives such as dedicated time for mentorship in more academically-oriented institutions, mentors have to be willing to engage for personal reasons. Likewise, mentorship pairs must not be imposed but rather mutually chosen [78]. Most mentees choose mentors based on personality/style rather than academic achievements.
Before mentoring commences, individuals should reflect as outlined in the intentional mentoring section above. Mentors should also be aware that the best indicator of a successful mentorship relationship is when mentees feel that their mentors are invested in their day-to-day progress [104]. Among the most common reasons for mentorship failure is ‘mentor neglect,’ thus mentors must be effective communicators to minimize this threat [104, 105]. For example, one way to avoid neglect is to communicate effectively if meetings need to be cancelled and even give a clear message that mentorship might not be possible under a specific set of circumstances or conditions; leaving mentees in suspense is the primary mode of neglect and is largely avoidable. Another common threat to the success of mentorships is the power dynamic and negative impacts of hierarchy (e.g., ‘the power gradient’) within the relationship [106, 107]. To mitigate the above issues, mentors need to clearly indicate that mentees should avoid engaging in activities or projects that do not align well with their interests, skill set, or capacity to complete. This may be challenging for mentees because of the above-mentioned ‘power gradient’ and potentially mentee concerns of appearing ungrateful or unappreciative for opportunities offered to them.
To help optimize mentor-mentee interactions, mentors should make efforts to make routine information exchange less formal and to reduce either the presence or the appearance of hierarchical barriers. For example, mentors could preface the mentorship with statements of support and encouragement, while emphasizing that the ultimate signs of strength, maturity, and leadership include the ability to self-assess, know when to seek advice or help, and estimating one’s ability to take on more work. A mentor should also inquire early on about the mentee’s preferred work and motivational styles [77]. There should be mutual awareness of reasonable expectations, comfort levels, resources and generally speaking support (e.g., both in terms of resources and encouragement). At the same time, a balance should be struck between the amount and relative proportions of encouragement, support, and praise. Imbalance among those three factors may lead to mismatched expectations (e.g., praising poor effort will likely be counter-productive).
Throughout the entire mentorship process, mentors should embrace opportunities for mentees to engage in reciprocal teaching. This both enhances the mentee’s teaching (and leadership) skills and provides the mentor a fresh perspective on mutually relevant topics. This input can be solicited, for example, by asking a mentee a question about technology or changes to medical education. Mentors should embrace their commitment to life-long learning and regularly and frequently seek feedback about their performance as a mentor and the effectiveness of the mentorship on the whole. Other factors in creating a successful mentorship include implementing micro-motivational behaviors as well as awareness and avoidance of exposing mentees to unintentional microaggressions [108, 109]. In terms of their general approach, mentors should keep an open mind and be eager to learn from their mentees [77]. They should treat mentees with respect and view them as valuable colleagues. Mentors should be honest with mentees while at the same time exhibiting patience and generosity (Figure 2).
Mentees bear the majority of work in mentorship and have the responsibility for cultivating the relationship; however, actionable items for both mentor and mentee can help facilitate a successful relationships. Having clearly defined tasks and responsibilities increases likelihood of success [
Mentorship malpractice is an important topic within the overall context of this chapter. It is critical that both mentors and mentees understand the scope of their mentorship relationship, and that education regarding manifestations of “bad mentorship” is provided to all stakeholders. For example, Chopra, et al., grouped mentorship malpractice into active and passive types [110]. The authors further categorize active mentorship malpractice into three subtypes – the hijacker who takes hostage a mentee’s idea, project, or grant, often for self-gain; the exploiter who torpedoes a mentee’s success by saddling them with low-yield activities; and the possessor who dominates the mentee across various areas of collaboration [110]. Passive mentorship malpractice can be divided into the following three subtypes – the ‘bottleneck’ mentor who is preoccupied with own competing priorities and does not have the bandwidth or the desire to attend to mentees; the ‘country clubber’ mentor who focuses on conflict evasion and avoids difficult but necessary conversations; and the ‘world traveler’ mentor who spends little to no time or effort on mentoring while often exploiting the mentee for self-promotion [110]. In addition to educational efforts, more formal ‘mentor-mentee agreements’ may help enforce accountability within the overall relationship [111]. Finally, active prevention of mentorship malpractice requires mentees to be proactive, including the establishment of a ‘mentorship team,’ setting boundaries, communicating needs, knowing when to walk away, and not being complicit by facilitating negative mentor traits [110].
It is generally accepted that physicians at all levels of training carry tremendous amounts of responsibility and face significant time constraints due to multiple competing clinical and non-clinical priorities [112, 113, 114]. A major concern among potential mentors is the time commitment required for a successful mentorship. This is a valid concern, and while new approaches to mentorship like ‘micro-mentorship’ and group mentorship provide avenues to lessen the time demand, mentorship is still an added responsibility. Consequently, it is up to the individual to evaluate if the benefits of mentorship are worth the time commitment [2, 115, 116].
While mentorships and mentor-mentee relationships may have been less structured in the past, they have always been crucial to most training and education. There may be specific factors in today’s clinical practice which impede one’s ability to mentor effectively. We have already mentioned time constraints as one barrier, and in order to preserve and improve mentorship in post graduate medical education there is a need to identify in what ways time constraints, particularly in the modern day, may be more of a barrier than before. The dawn of the electronic health record has certainly made many aspects of clinical life easier and more efficient. Still physicians may spend more time in front of computers, in cubicles and offices than out on the wards where the traditional “paper charts” would be, and hence render themselves less accessible to potential mentees. Notes used to be briefer in the past when they were hand written and more time may have been spent with students and trainees to nurture potential mentorships. Electronic health records also bring with them more “tick boxes”, asynchronous tasks and time spent on “filing” [117, 118, 119] which further could tighten existing time constraints. Additionally, the shift in employment of physicians by hospitals rather than being self-employed, along with the increasing administrative burden [120], highlights the need for “protected time” for teaching physicians to help promote and facilitate mentorship [121]. Non-physician managers may be less likely to understand the value of mentorship in medical training and may be more likely to be focused on optimization of clinical and financial efficiency. Another factor to consider could be the growing number of non-physician practitioners providing care and services in hospitals in the U.S. Where a medical or surgical team decades ago would most likely only have consisted of physicians at different levels of training, seniority and status, along with medical students, modern medical teams are much more diverse. Today a medical or surgical team is more likely to consist of a mix of physicians and non-physician practitioners. Given that the attending physician and the advanced practitioner are working together permanently over years and the trainee is only “rotating” through, he or she may feel more as an outsider, potential mentors may appear less available, and the landscape in which the mentee is navigating, may, in some ways appear more complex and intimidating. Physicians may actually be spending more time and resources mentoring non-physician practitioners and entrusting them with projects simply because of continuity. There is however little research into the effect that the growing number of non-physicians employed by hospitals have on training and mentorship, and more research into this topic may be beneficial. If the necessity of the mentor-mentee relationship in medical training could be elucidated, and robust data presented regarding positive outcomes with regard to diversity, retention of female physicians in the work place, and prevention of burnout, both for mentees and mentors, non-physician managers may see the benefits of more protected time to facilitate such relationships. Hence, it could be argued, that time set aside where faculty members are protected from clinical and administrative duties, in order to mentor physicians in training, may be an emerging and growing need in today’s healthcare system.
The coronavirus disease 2019 (COVID-19) pandemic has certainly also posed its own challenges to medical education as a whole [122]. Over the last year students over several fields, not just medicine, have been kept out of class rooms and auditoriums and have been unable to congregate in student lounges, libraries, cafeterias and other places where healthy academic discussions may occur [122]. This is equally true for residents and fellows as well as medical students. Potential mentors are simply less visible and may be less accessible and overall harder to approach in the era of the pandemic. Research mentorships have also identified barriers specifically related to COVID-19, such as transitioning research forums and groups to virtual platforms, adapting the mentorship relationship to video conferencing platforms if needed and providing virtual research opportunities [123, 124]. It may also prove particularly valuable to consider promoting more mentor-mentee meetings in a time where social distancing and avoiding larger gatherings are mandated, given that this involves a two-person team only in most cases. Additionally the pandemic has opened the door for virtual gatherings through video conferencing platforms, which can include many of the advantages of a “face to face” meeting, while allowing for relationships to transcend geographical boundaries [125], a benefit which may outlast the pandemic itself. Mentorship may also be redefined given the already high burnout rate among physicians and trainees, even before the pandemic [126], to include not only academic support, but also emotional support and support of broadly defined ‘wellness measures’ through mutual compassion during a stressful time [123].
Modern day challenges to traditional mentorship in postgraduate medical education could be overcome by either addressing the challenges themselves or “challenging” the traditional model of mentorship. With more and more of the work that clinicians perform requiring information-technology (IT) skills and constantly being “up to date” with regard to the new features of medical software and EMRs, our physicians-in-training may find themselves at a unique advantage. New graduates from medical school would naturally be comfortable with IT skills and may also be more likely to evolve and pick up ‘new tricks’ pertaining to EMR use, enabling them to teach their mentors. This introduces the concept of “reverse mentorship”, where the less experienced physician could help the more experienced physician gain confidence and knowledge ultimately benefitting both the mentee and the mentor and “leveling the playing field” [127, 128]. Reverse mentorship may help those physicians with limited EMR knowledge or skills, lack of familiarity with modern electronic research tools, and even virtual and video meeting and teaching sessions. In addition, reverse mentorship may also be beneficial to some of the gender specific and ethnic barriers to mentorship mentioned earlier in this chapter. Female and minority physicians-in-training could mentor their faculty members in modern challenges which may be specific to females or minorities, ultimately increasing the understanding of these important topics among predominantly white, male mentor pool. Reverse mentorship may also be particularly relevant to postgraduate medical education during the current pandemic. Traditionally senior physicians have more knowledge and confidence in medicine because of decades of academic research and clinical experience. However, this advantage may be somewhat lost in the midst of a pandemic. The rapidity with which COVID-19 infiltrated and shook the very foundation of outpatient and inpatient medicine over the last year, made it important for physicians to constantly stay current on the newest guidelines for management and newest evidence pertaining to COVID-19. Many experienced physicians were humbled and may have found themselves receiving updates and tips from younger less experienced colleges. A “group mentorship” model which potentially could include physicians, advanced practitioners and nurse managers as well as hospital administrators as mentors, may improve the overall training of a physician-in-training mentee, and render them more equipped to practice in a rapidly evolving healthcare system.
Having discussed mentorship in graduate medical education, it is important to emphasize that mentorship should not suddenly start during one’s residency training. Optimally, long-term mentorship relationships may begin during undergraduate years, especially once a future physician decides to commit to medicine as a career. One of the challenges of being an undergraduate medical student is receiving proper advice and mentorship, especially regarding various expectations and realities of modern healthcare. In this context, mentorship can be crucial in helping set up a premedical student for future success. Deciding to apply to medical school and gaining entrance into medical school can be difficult and anxiety-provoking [129]. Mentors can help reduce that anxiety and provide insight into the realities of a career in medicine. A mentor-mentee relationship can provide meaningful information, experience and confidence to a premedical student.
Many premedical students lack knowledge about the medical field or about entrance into medical school. Also, many of these students have no connections to individuals in the medical field [130]. A well-organized premedical advising program would serve students well by providing opportunities for direct mentorship by those in the medical field. Such programs could take the form of longitudinal mentorship, one-on-one physician mentoring programs, or periodic educational sessions with physicians.
A mentorship program could allow premedical students gain assistance in selecting undergraduate classes, completing medical school applications, crafting personal statements, preparing for medical school interviews, preparing for the medical college admission testing (MCAT), choosing extracurricular activities, understanding professionalism, developing leadership, or finding opportunities for research, volunteering or clinical experience. Mentorship programs can provide essential support for those who come from disadvantaged backgrounds or from groups underrepresented in medicine.
Having physician mentors can augment the advice of undergraduate premedical advisors and provide essential networking opportunities, as well as clinical experiences. Students can learn what a physician’s life is actually like and better understand the skills needed beyond excellent grades and test scores. They can witness real-life patient-physician interactions and communication [130], ask questions and may even gain exposure to different fields of medicine.
In conclusion, having a mentorship program could be beneficial in multiple ways to undergraduate premedical students. It would be a welcome resource if all undergraduate institutions had a well-developed program and mechanism(s) for assisting with the development and maintenance of mentor-mentee relationships.
Studies have shown that rates of burnout and low motivation in residency can be linked to specific factors, including lack of adequate mentorship [23]. Thus, it is essential to conduct necessary research and strategize how to best implement key initiatives like mentorship programs so they are optimally effective and helpful in preventing burnout, disengagement, and loss of talent [23]. Within this broader context, the intention, initiation and execution of mentorship all warrant additional research. Mentorship has proven to be very beneficial, but because it is implemented in a variety of ways and for a variety of purposes, its effects can be difficult to measure. There is a great need for increased research on various benefits of mentorship, as increased evidence will likely incentivize institutions to create mentorship-friendly policies like protected time, which in turn would encourage more faculty to serve as mentors. Examples of measurable outcomes include grants, publications, mentorship evaluations and awards, quality improvement measures, academic advancement, career satisfaction and faculty retention [37]. However, intangibles such as stronger collegial relationships, enhanced learning opportunities, and greater interprofessional engagement and awareness also need to be examined in a more rigorous fashion [37]. These less tangible markers may lead to greater fulfillment within the profession, less burnout and even better patient outcomes. Formal, long term evaluation of the success of mentorship programs is needed in order to measure the true costs, benefits, and institutional outcomes. With a shift to pro-mentorship cultures, institutions and individuals could greatly improve their outcomes and satisfaction within medicine.
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Among these heavy metals, a few have direct or indirect impact on the human body. Some of these heavy metals such as copper, cobalt, iron, nickel, magnesium, molybdenum, chromium, selenium, manganese and zinc have functional roles which are essential for various diverse physiological and biochemical activities in the body. However, some of these heavy metals in high doses can be harmful to the body while others such as cadmium, mercury, lead, chromium, silver, and arsenic in minute quantities have delirious effects in the body causing acute and chronic toxicities in humans. The focus of this chapter is to describe the various mechanism of intoxication of some selected heavy metals in humans along with their health effects. Therefore it aims to highlight on biochemical mechanisms of heavy metal intoxication which involves binding to proteins and enzymes, altering their activity and causing damage. More so, the mechanism by which heavy metals cause neurotoxicity, generate free radical which promotes oxidative stress damaging lipids, proteins and DNA molecules and how these free radicals propagate carcinogenesis are discussed. Alongside these mechanisms, the noxious health effects of these heavy metals are discussed.",book:{id:"7111",slug:"poisoning-in-the-modern-world-new-tricks-for-an-old-dog-",title:"Poisoning in the Modern World",fullTitle:"Poisoning in the Modern World - New Tricks for an Old Dog?"},signatures:"Godwill Azeh Engwa, Paschaline Udoka Ferdinand, Friday Nweke Nwalo and Marian N. 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The traditional healer provides health care services based on culture, religious background, knowledge, attitudes, and beliefs that are prevalent in his community. Illness is regarded as having both natural and supernatural causes and thus must be treated by both physical and spiritual means, using divination, incantations, animal sacrifice, exorcism, and herbs. Herbal medicine is the cornerstone of traditional medicine but may include minerals and animal parts. The adjustment is ok, but may be replaced with –‘ Herbal medicine was once termed primitive by western medicine but through scientific investigations there is a better understanding of its therapeutic activities such that many pharmaceuticals have been modeled on phytochemicals derived from it. Major obstacles to the use of African medicinal plants are their poor quality control and safety. Traditional medical practices are still shrouded with much secrecy, with few reports or documentations of adverse reactions. However, the future of African traditional medicine is bright if viewed in the context of service provision, increase of health care coverage, economic potential, and poverty reduction. 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The main global health organizations have incorporated patient safety in their review of work practices. The data provided by the medical laboratories have a direct impact on patient safety and a fault in any of processes such as strategic, operational and support, could affect it. To provide appreciate and reliable data to the physicians, it is important to emphasize the need to design risk management plan in the laboratory. Failure Mode and Effect Analysis (FMEA) is an efficient technique for error detection and reduction. Technical Committee of the International Organization for Standardization (ISO) licensed a technical specification for medical laboratories suggesting FMEA as a method for prospective risk analysis of high-risk processes. FMEA model helps to identify quality failures, their effects and risks with their reduction/elimination, which depends on severity, probability and detection. 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Among these heavy metals, a few have direct or indirect impact on the human body. Some of these heavy metals such as copper, cobalt, iron, nickel, magnesium, molybdenum, chromium, selenium, manganese and zinc have functional roles which are essential for various diverse physiological and biochemical activities in the body. However, some of these heavy metals in high doses can be harmful to the body while others such as cadmium, mercury, lead, chromium, silver, and arsenic in minute quantities have delirious effects in the body causing acute and chronic toxicities in humans. The focus of this chapter is to describe the various mechanism of intoxication of some selected heavy metals in humans along with their health effects. Therefore it aims to highlight on biochemical mechanisms of heavy metal intoxication which involves binding to proteins and enzymes, altering their activity and causing damage. 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Liposuction is a procedure to improve the body contour and not a surgery to reduce weight, although recently people who have failed in their plans to lose weight look at liposuction as a means to contour their body figure. Tumescent liposuction of large volumes requires a meticulous selection of each patient; their preoperative evaluation and perioperative management are essential to obtain the expected results. The various techniques of general anesthesia are the most recommended and should be monitored in the usual way, as well as monitoring the total doses of infiltrated local anesthetics to avoid systemic toxicity. The management of intravenous fluids is controversial, but the current trend is the restricted use of hydrosaline solutions. The most feared complications are deep vein thrombosis, pulmonary thromboembolism, fat embolism, lung edema, hypothermia, infections and even death. The adherence to the management guidelines and prophylaxis of venous thrombosis/thromboembolism is mandatory.",book:{id:"6221",slug:"anesthesia-topics-for-plastic-and-reconstructive-surgery",title:"Anesthesia Topics for Plastic and Reconstructive Surgery",fullTitle:"Anesthesia Topics for Plastic and Reconstructive Surgery"},signatures:"Sergio Granados-Tinajero, Carlos Buenrostro-Vásquez, Cecilia\nCárdenas-Maytorena and Marcela Contreras-López",authors:[{id:"273532",title:"Dr.",name:"Sergio Octavio",middleName:null,surname:"Granados Tinajero",slug:"sergio-octavio-granados-tinajero",fullName:"Sergio Octavio Granados Tinajero"}]},{id:"30178",title:"Chest Mobilization Techniques for Improving Ventilation and Gas Exchange in Chronic Lung Disease",slug:"chest-mobilization-techniques-for-improving-ventilation-and-gas-exchange-in-chronic-lung-disease",totalDownloads:31230,totalCrossrefCites:1,totalDimensionsCites:6,abstract:null,book:{id:"648",slug:"chronic-obstructive-pulmonary-disease-current-concepts-and-practice",title:"Chronic Obstructive Pulmonary Disease",fullTitle:"Chronic Obstructive Pulmonary Disease - Current Concepts and Practice"},signatures:"Donrawee Leelarungrayub",authors:[{id:"73709",title:"Associate Prof.",name:"Jirakrit",middleName:null,surname:"Leelarungrayub",slug:"jirakrit-leelarungrayub",fullName:"Jirakrit Leelarungrayub"}]}],onlineFirstChaptersFilter:{topicId:"3",limit:6,offset:0},onlineFirstChaptersCollection:[{id:"83174",title:"Role of Biomarkers in Hepatocellular Carcinoma and Their Disease Progression",slug:"role-of-biomarkers-in-hepatocellular-carcinoma-and-their-disease-progression",totalDownloads:2,totalDimensionsCites:null,doi:"10.5772/intechopen.105856",abstract:"Hepatocellular carcinoma (HCC) is one of the third leading and common lethal cancers worldwide. Early detection of tumorigenesis of hepatocellular carcinoma is through ultrasonography, computerized tomography (CT) scans, and magnetic resonance imaging (MRI) scans; however, these methods are not up to the mark, so a search for an efficient biomarker for early diagnosis and treatment of hepatocarcinogenesis is important. Proteomic and genomic approaches aid to develop new promising biomarkers for the diagnosis of HCC at the early stages. These biomarkers not only help in prognosis but also provide better therapeutic intervention against HCC. Among the different biomarker candidates, liquid biopsy [including circulating tumor cells (CTCs) and circulating tumor DNA (ctDNA)] has recently emerged as a noninvasive detection technique for the characterization of circulating cells, providing a strong basis and early diagnosis for the individualized treatment of patients. This review provides the current understanding of HCC biomarkers that predict the risk of HCC recurrence.",book:{id:"11596",title:"Liver Cancer - Genesis, Progression and Metastasis",coverURL:"https://cdn.intechopen.com/books/images_new/11596.jpg"},signatures:"S.S. Haque, Ravi Bhushan Raman and Mehboobus Salam"},{id:"83033",title:"Mental Health Issues of Japanese Elementary School Teachers: The Effects of the Japanese Classroom Management Style",slug:"mental-health-issues-of-japanese-elementary-school-teachers-the-effects-of-the-japanese-classroom-ma",totalDownloads:1,totalDimensionsCites:null,doi:"10.5772/intechopen.104530",abstract:"Teachers in Japan face work-related mental health issues, such as depression and adjustment disorders. The number of elementary school teachers taking leave of absence due to mental illness has been increasing every year and is high according to international standards. One of the reasons for this was the workload on a single teacher, resulting in long working hours. The authors believe that the reason for long working hours may be the Japanese classroom management style. This chapter compares the Japanese classroom management style of elementary school teachers with the classroom management styles of other countries, such as India, and discusses the reasons for the long working hours under the Japanese classroom management style.",book:{id:"11684",title:"Mental Health - Preventive Strategies",coverURL:"https://cdn.intechopen.com/books/images_new/11684.jpg"},signatures:"Miyuki Matsumoto, Michiko Ishikawa and Sadananda Reddy"},{id:"83158",title:"Cannabis and the Brain: Friend or Foe?",slug:"cannabis-and-the-brain-friend-or-foe",totalDownloads:0,totalDimensionsCites:0,doi:"10.5772/intechopen.106669",abstract:"Legalization of cannabis in the US and other countries highlight the need to understand the health consequences of this substance use. Research indicates that some cannabis ingredients may play beneficial role in treating various medical conditions while other ingredients may pose health risks. This review is focused on the brain and mental health effects of cannabis use. The rationale for examining cannabis use in behavioral and neural conditions is that these conditions are highly widespread in the US and account for high level of medical healthcare and associated cost. The purpose of this review is to provide an overview of the known medicinal benefits of selected cannabis cannabinoids in conditions like pediatric epilepsy, attention deficit hyperactivity disorder, autism spectrum disorder, and the known side effects or contraindications in conditions such as addiction, cognition, and psychosis. Several recommendations are made as to studies that will help further understanding the increasing role of cannabis in neuropsychiatric health and disease.",book:{id:"11714",title:"Cannabinoids - Recent Perspectives and Applications in Human Health",coverURL:"https://cdn.intechopen.com/books/images_new/11714.jpg"},signatures:"Ali E. Dabiri and Ghassan S. Kassab"},{id:"83161",title:"Repurposing BCG and MMR Vaccines for Combating Covid-19: A Review and Opinion Based on Clinical Evidence",slug:"repurposing-bcg-and-mmr-vaccines-for-combating-covid-19-a-review-and-opinion-based-on-clinical-evide",totalDownloads:0,totalDimensionsCites:0,doi:"10.5772/intechopen.106788",abstract:"Our review comprehends past and recent developments encircling the two vaccines, BCG and MMR, which have efficacy lasting 10 years and are known to trigger the production of Interferon and various cytokines. BCG has depicted long-lasting effects, reduction in mortality, and hospitalizations associated with various diseases in different age groups as per studies across Sweden, West Africa, Spain, and Indonesia. Clinical trials are in progress in Holland, Australia, and Germany to study its effects on COVID-19. Most Asian countries with childhood BCG vaccination programs have shown lower COVID-19-related per capita death rates. The MMR vaccination has shown a reduction in hospitalizations and COVID-19-related deaths in about 11 countries, and a randomized clinical trial has been proposed in New Orleans. Reasons such as inhibition of pulmonary inflammation and structural similarity have been cited for such consequences. BCG and MMR may serve to shorten the duration of infection, minimize harmful pathology, reduce hospitalization rates, and curb the spread of the disease, but more research is required to assess the associated risks, especially for the elderly and people with comorbidities who are prone to severe complications of COVID-19.",book:{id:"11724",title:"COVID-19 Vaccines - Current State and Perspectives",coverURL:"https://cdn.intechopen.com/books/images_new/11724.jpg"},signatures:"Kasturi Mahesh Tawde, Aditya Manivannan Iyer and Harshal Ashok Pawar"},{id:"83173",title:"Pain Management in the Emergency Department- Newer Modalities and Current Perspective",slug:"pain-management-in-the-emergency-department-newer-modalities-and-current-perspective",totalDownloads:1,totalDimensionsCites:null,doi:"10.5772/intechopen.105952",abstract:"Pain is one of the most common complaints and yet one of the most neglected aspects of management in the emergency department. Optimal pain management is a nuanced skill which focusses on reduction of pain to an acceptable level to allow for safe discharge and return to normal activities, in addition to improving patient satisfaction and comfort during their stay in hospital. Adequate analgesia also improves physiological parameters such as heart rate and blood pressure. The aim is improving rather than eradication of pain altogether while maintaining an acceptable level of adverse effects. This chapter will discuss assessment of pain in the emergency department along with various modalities of pain management with specific focus on newer modalities including ultrasound guided regional nerve blocks. Ultrasound guided nerve blocks are associated with better analgesia and have fewer chances of drug related adverse events, especially in older patients and those with comorbidities where large doses of systemic medications are associated with a significant risk of adverse effects.",book:{id:"10883",title:"Pain Management - From Pain Mechanisms to Patient Care",coverURL:"https://cdn.intechopen.com/books/images_new/10883.jpg"},signatures:"Sakshi Yadav, Anuj Ajayababu, Tej Prakash Sinha and Sanjeev Bhoi"},{id:"83136",title:"Vector Control: Insights Arising from the Post-Genomics Findings on Insects’ Reproductive Biology",slug:"vector-control-insights-arising-from-the-post-genomics-findings-on-insects-reproductive-biology",totalDownloads:1,totalDimensionsCites:0,doi:"10.5772/intechopen.106273",abstract:"The high prevalence of neglected vector-borne diseases, such as Chagas disease and dengue fever, imposes enormous health and financial burdens in developing countries. Historically, and still, to this day, the main effective methods to manage those diseases rely on vector population control. Although early efforts in understanding vector-specific biology resulted in important advancements in the development of strategies for the management of vector-borne diseases, studies regarding the complex physiology of local vector species were weakened by the expanding use of insecticide-based tools, which were, at the time, proven simpler and effective. The rising threat of insecticide resistance and climate change (which can expand endemic areas) has reemphasized the need to rely on thorough species-specific vector biology. One approach to controlling vector populations is to disrupt molecular processes or antagonize the metabolic targets required to produce viable eggs. Here, we discuss new findings arising from post-genomics molecular studies on vector reproductive biology and discuss their potential for the elaboration of new effective vector control interventions.",book:{id:"11227",title:"New Advances in Neglected Tropical Diseases",coverURL:"https://cdn.intechopen.com/books/images_new/11227.jpg"},signatures:"Isabela Ramos and Fabio Gomes"}],onlineFirstChaptersTotal:784},preDownload:{success:null,errors:{}},subscriptionForm:{success:null,errors:{}},aboutIntechopen:{},privacyPolicy:{},peerReviewing:{},howOpenAccessPublishingWithIntechopenWorks:{},sponsorshipBooks:{sponsorshipBooks:[],offset:8,limit:8,total:0},allSeries:{pteSeriesList:[{id:"14",title:"Artificial Intelligence",numberOfPublishedBooks:11,numberOfPublishedChapters:91,numberOfOpenTopics:6,numberOfUpcomingTopics:0,issn:"2633-1403",doi:"10.5772/intechopen.79920",isOpenForSubmission:!0},{id:"7",title:"Biomedical Engineering",numberOfPublishedBooks:12,numberOfPublishedChapters:108,numberOfOpenTopics:3,numberOfUpcomingTopics:0,issn:"2631-5343",doi:"10.5772/intechopen.71985",isOpenForSubmission:!0}],lsSeriesList:[{id:"11",title:"Biochemistry",numberOfPublishedBooks:33,numberOfPublishedChapters:333,numberOfOpenTopics:4,numberOfUpcomingTopics:0,issn:"2632-0983",doi:"10.5772/intechopen.72877",isOpenForSubmission:!0},{id:"25",title:"Environmental Sciences",numberOfPublishedBooks:1,numberOfPublishedChapters:19,numberOfOpenTopics:4,numberOfUpcomingTopics:0,issn:"2754-6713",doi:"10.5772/intechopen.100362",isOpenForSubmission:!0},{id:"10",title:"Physiology",numberOfPublishedBooks:14,numberOfPublishedChapters:145,numberOfOpenTopics:4,numberOfUpcomingTopics:0,issn:"2631-8261",doi:"10.5772/intechopen.72796",isOpenForSubmission:!0}],hsSeriesList:[{id:"3",title:"Dentistry",numberOfPublishedBooks:11,numberOfPublishedChapters:144,numberOfOpenTopics:2,numberOfUpcomingTopics:0,issn:"2631-6218",doi:"10.5772/intechopen.71199",isOpenForSubmission:!0},{id:"6",title:"Infectious Diseases",numberOfPublishedBooks:13,numberOfPublishedChapters:126,numberOfOpenTopics:4,numberOfUpcomingTopics:0,issn:"2631-6188",doi:"10.5772/intechopen.71852",isOpenForSubmission:!0},{id:"13",title:"Veterinary Medicine and Science",numberOfPublishedBooks:11,numberOfPublishedChapters:113,numberOfOpenTopics:3,numberOfUpcomingTopics:0,issn:"2632-0517",doi:"10.5772/intechopen.73681",isOpenForSubmission:!0}],sshSeriesList:[{id:"22",title:"Business, Management and Economics",numberOfPublishedBooks:1,numberOfPublishedChapters:23,numberOfOpenTopics:3,numberOfUpcomingTopics:0,issn:"2753-894X",doi:"10.5772/intechopen.100359",isOpenForSubmission:!0},{id:"23",title:"Education and Human Development",numberOfPublishedBooks:0,numberOfPublishedChapters:13,numberOfOpenTopics:1,numberOfUpcomingTopics:1,issn:null,doi:"10.5772/intechopen.100360",isOpenForSubmission:!0},{id:"24",title:"Sustainable Development",numberOfPublishedBooks:1,numberOfPublishedChapters:19,numberOfOpenTopics:5,numberOfUpcomingTopics:0,issn:"2753-6580",doi:"10.5772/intechopen.100361",isOpenForSubmission:!0}],testimonialsList:[{id:"13",text:"The collaboration with and support of the technical staff of IntechOpen is fantastic. The whole process of submitting an article and editing of the submitted article goes extremely smooth and fast, the number of reads and downloads of chapters is high, and the contributions are also frequently cited.",author:{id:"55578",name:"Antonio",surname:"Jurado-Navas",institutionString:null,profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRisIQAS/Profile_Picture_1626166543950",slug:"antonio-jurado-navas",institution:{id:"720",name:"University of Malaga",country:{id:null,name:"Spain"}}}},{id:"6",text:"It is great to work with the IntechOpen to produce a worthwhile collection of research that also becomes a great educational resource and guide for future research endeavors.",author:{id:"259298",name:"Edward",surname:"Narayan",institutionString:null,profilePictureURL:"https://mts.intechopen.com/storage/users/259298/images/system/259298.jpeg",slug:"edward-narayan",institution:{id:"3",name:"University of Queensland",country:{id:null,name:"Australia"}}}}]},series:{item:{id:"14",title:"Artificial Intelligence",doi:"10.5772/intechopen.79920",issn:"2633-1403",scope:"Artificial Intelligence (AI) is a rapidly developing multidisciplinary research area that aims to solve increasingly complex problems. In today's highly integrated world, AI promises to become a robust and powerful means for obtaining solutions to previously unsolvable problems. This Series is intended for researchers and students alike interested in this fascinating field and its many applications.",coverUrl:"https://cdn.intechopen.com/series/covers/14.jpg",latestPublicationDate:"August 17th, 2022",hasOnlineFirst:!0,numberOfPublishedBooks:11,editor:{id:"218714",title:"Prof.",name:"Andries",middleName:null,surname:"Engelbrecht",slug:"andries-engelbrecht",fullName:"Andries Engelbrecht",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRNR8QAO/Profile_Picture_1622640468300",biography:"Andries Engelbrecht received the Masters and PhD degrees in Computer Science from the University of Stellenbosch, South Africa, in 1994 and 1999 respectively. He is currently appointed as the Voigt Chair in Data Science in the Department of Industrial Engineering, with a joint appointment as Professor in the Computer Science Division, Stellenbosch University. Prior to his appointment at Stellenbosch University, he has been at the University of Pretoria, Department of Computer Science (1998-2018), where he was appointed as South Africa Research Chair in Artifical Intelligence (2007-2018), the head of the Department of Computer Science (2008-2017), and Director of the Institute for Big Data and Data Science (2017-2018). In addition to a number of research articles, he has written two books, Computational Intelligence: An Introduction and Fundamentals of Computational Swarm Intelligence.",institutionString:null,institution:{name:"Stellenbosch University",institutionURL:null,country:{name:"South Africa"}}},editorTwo:null,editorThree:null},subseries:{paginationCount:6,paginationItems:[{id:"22",title:"Applied Intelligence",coverUrl:"https://cdn.intechopen.com/series_topics/covers/22.jpg",isOpenForSubmission:!0,editor:{id:"27170",title:"Prof.",name:"Carlos",middleName:"M.",surname:"Travieso-Gonzalez",slug:"carlos-travieso-gonzalez",fullName:"Carlos Travieso-Gonzalez",profilePictureURL:"https://mts.intechopen.com/storage/users/27170/images/system/27170.jpeg",biography:"Carlos M. Travieso-González received his MSc degree in Telecommunication Engineering at Polytechnic University of Catalonia (UPC), Spain in 1997, and his Ph.D. degree in 2002 at the University of Las Palmas de Gran Canaria (ULPGC-Spain). He is a full professor of signal processing and pattern recognition and is head of the Signals and Communications Department at ULPGC, teaching from 2001 on subjects on signal processing and learning theory. His research lines are biometrics, biomedical signals and images, data mining, classification system, signal and image processing, machine learning, and environmental intelligence. He has researched in 52 international and Spanish research projects, some of them as head researcher. He is co-author of 4 books, co-editor of 27 proceedings books, guest editor for 8 JCR-ISI international journals, and up to 24 book chapters. He has over 450 papers published in international journals and conferences (81 of them indexed on JCR – ISI - Web of Science). He has published seven patents in the Spanish Patent and Trademark Office. He has been a supervisor on 8 Ph.D. theses (11 more are under supervision), and 130 master theses. He is the founder of The IEEE IWOBI conference series and the president of its Steering Committee, as well as the founder of both the InnoEducaTIC and APPIS conference series. He is an evaluator of project proposals for the European Union (H2020), Medical Research Council (MRC, UK), Spanish Government (ANECA, Spain), Research National Agency (ANR, France), DAAD (Germany), Argentinian Government, and the Colombian Institutions. He has been a reviewer in different indexed international journals (<70) and conferences (<250) since 2001. He has been a member of the IASTED Technical Committee on Image Processing from 2007 and a member of the IASTED Technical Committee on Artificial Intelligence and Expert Systems from 2011. \n\nHe has held the general chair position for the following: ACM-APPIS (2020, 2021), IEEE-IWOBI (2019, 2020 and 2020), A PPIS (2018, 2019), IEEE-IWOBI (2014, 2015, 2017, 2018), InnoEducaTIC (2014, 2017), IEEE-INES (2013), NoLISP (2011), JRBP (2012), and IEEE-ICCST (2005)\n\nHe is an associate editor of the Computational Intelligence and Neuroscience Journal (Hindawi – Q2 JCR-ISI). He was vice dean from 2004 to 2010 in the Higher Technical School of Telecommunication Engineers at ULPGC and the vice dean of Graduate and Postgraduate Studies from March 2013 to November 2017. He won the “Catedra Telefonica” Awards in Modality of Knowledge Transfer, 2017, 2018, and 2019 editions, and awards in Modality of COVID Research in 2020.\n\nPublic References:\nResearcher ID http://www.researcherid.com/rid/N-5967-2014\nORCID https://orcid.org/0000-0002-4621-2768 \nScopus Author ID https://www.scopus.com/authid/detail.uri?authorId=6602376272\nScholar Google https://scholar.google.es/citations?user=G1ks9nIAAAAJ&hl=en \nResearchGate https://www.researchgate.net/profile/Carlos_Travieso",institutionString:null,institution:{name:"University of Las Palmas de Gran Canaria",institutionURL:null,country:{name:"Spain"}}},editorTwo:null,editorThree:null},{id:"23",title:"Computational Neuroscience",coverUrl:"https://cdn.intechopen.com/series_topics/covers/23.jpg",isOpenForSubmission:!0,editor:{id:"14004",title:"Dr.",name:"Magnus",middleName:null,surname:"Johnsson",slug:"magnus-johnsson",fullName:"Magnus Johnsson",profilePictureURL:"https://mts.intechopen.com/storage/users/14004/images/system/14004.png",biography:"Dr Magnus Johnsson is a cross-disciplinary scientist, lecturer, scientific editor and AI/machine learning consultant from Sweden. \n\nHe is currently at Malmö University in Sweden, but also held positions at Lund University in Sweden and at Moscow Engineering Physics Institute. \nHe holds editorial positions at several international scientific journals and has served as a scientific editor for books and special journal issues. \nHis research interests are wide and include, but are not limited to, autonomous systems, computer modeling, artificial neural networks, artificial intelligence, cognitive neuroscience, cognitive robotics, cognitive architectures, cognitive aids and the philosophy of mind. \n\nDr. Johnsson has experience from working in the industry and he has a keen interest in the application of neural networks and artificial intelligence to fields like industry, finance, and medicine. \n\nWeb page: www.magnusjohnsson.se",institutionString:null,institution:{name:"Malmö University",institutionURL:null,country:{name:"Sweden"}}},editorTwo:null,editorThree:null},{id:"24",title:"Computer Vision",coverUrl:"https://cdn.intechopen.com/series_topics/covers/24.jpg",isOpenForSubmission:!0,editor:{id:"294154",title:"Prof.",name:"George",middleName:null,surname:"Papakostas",slug:"george-papakostas",fullName:"George Papakostas",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002hYaGbQAK/Profile_Picture_1624519712088",biography:"George A. Papakostas has received a diploma in Electrical and Computer Engineering in 1999 and the M.Sc. and Ph.D. degrees in Electrical and Computer Engineering in 2002 and 2007, respectively, from the Democritus University of Thrace (DUTH), Greece. Dr. Papakostas serves as a Tenured Full Professor at the Department of Computer Science, International Hellenic University, Greece. Dr. Papakostas has 10 years of experience in large-scale systems design as a senior software engineer and technical manager, and 20 years of research experience in the field of Artificial Intelligence. Currently, he is the Head of the “Visual Computing” division of HUman-MAchines INteraction Laboratory (HUMAIN-Lab) and the Director of the MPhil program “Advanced Technologies in Informatics and Computers” hosted by the Department of Computer Science, International Hellenic University. He has (co)authored more than 150 publications in indexed journals, international conferences and book chapters, 1 book (in Greek), 3 edited books, and 5 journal special issues. His publications have more than 2100 citations with h-index 27 (GoogleScholar). His research interests include computer/machine vision, machine learning, pattern recognition, computational intelligence. \nDr. Papakostas served as a reviewer in numerous journals, as a program\ncommittee member in international conferences and he is a member of the IAENG, MIR Labs, EUCogIII, INSTICC and the Technical Chamber of Greece (TEE).",institutionString:null,institution:{name:"International Hellenic University",institutionURL:null,country:{name:"Greece"}}},editorTwo:null,editorThree:null},{id:"25",title:"Evolutionary Computation",coverUrl:"https://cdn.intechopen.com/series_topics/covers/25.jpg",isOpenForSubmission:!0,editor:{id:"136112",title:"Dr.",name:"Sebastian",middleName:null,surname:"Ventura Soto",slug:"sebastian-ventura-soto",fullName:"Sebastian Ventura Soto",profilePictureURL:"https://mts.intechopen.com/storage/users/136112/images/system/136112.png",biography:"Sebastian Ventura is a Spanish researcher, a full professor with the Department of Computer Science and Numerical Analysis, University of Córdoba. Dr Ventura also holds the positions of Affiliated Professor at Virginia Commonwealth University (Richmond, USA) and Distinguished Adjunct Professor at King Abdulaziz University (Jeddah, Saudi Arabia). Additionally, he is deputy director of the Andalusian Research Institute in Data Science and Computational Intelligence (DaSCI) and heads the Knowledge Discovery and Intelligent Systems Research Laboratory. He has published more than ten books and over 300 articles in journals and scientific conferences. Currently, his work has received over 18,000 citations according to Google Scholar, including more than 2200 citations in 2020. In the last five years, he has published more than 60 papers in international journals indexed in the JCR (around 70% of them belonging to first quartile journals) and he has edited some Springer books “Supervised Descriptive Pattern Mining” (2018), “Multiple Instance Learning - Foundations and Algorithms” (2016), and “Pattern Mining with Evolutionary Algorithms” (2016). He has also been involved in more than 20 research projects supported by the Spanish and Andalusian governments and the European Union. He currently belongs to the editorial board of PeerJ Computer Science, Information Fusion and Engineering Applications of Artificial Intelligence journals, being also associate editor of Applied Computational Intelligence and Soft Computing and IEEE Transactions on Cybernetics. Finally, he is editor-in-chief of Progress in Artificial Intelligence. He is a Senior Member of the IEEE Computer, the IEEE Computational Intelligence, and the IEEE Systems, Man, and Cybernetics Societies, and the Association of Computing Machinery (ACM). Finally, his main research interests include data science, computational intelligence, and their applications.",institutionString:null,institution:{name:"University of Córdoba",institutionURL:null,country:{name:"Spain"}}},editorTwo:null,editorThree:null},{id:"26",title:"Machine Learning and Data Mining",coverUrl:"https://cdn.intechopen.com/series_topics/covers/26.jpg",isOpenForSubmission:!0,editor:{id:"24555",title:"Dr.",name:"Marco Antonio",middleName:null,surname:"Aceves Fernandez",slug:"marco-antonio-aceves-fernandez",fullName:"Marco Antonio Aceves Fernandez",profilePictureURL:"https://mts.intechopen.com/storage/users/24555/images/system/24555.jpg",biography:"Dr. Marco Antonio Aceves Fernandez obtained his B.Sc. (Eng.) in Telematics from the Universidad de Colima, Mexico. He obtained both his M.Sc. and Ph.D. from the University of Liverpool, England, in the field of Intelligent Systems. He is a full professor at the Universidad Autonoma de Queretaro, Mexico, and a member of the National System of Researchers (SNI) since 2009. Dr. Aceves Fernandez has published more than 80 research papers as well as a number of book chapters and congress papers. He has contributed in more than 20 funded research projects, both academic and industrial, in the area of artificial intelligence, ranging from environmental, biomedical, automotive, aviation, consumer, and robotics to other applications. He is also a honorary president at the National Association of Embedded Systems (AMESE), a senior member of the IEEE, and a board member of many institutions. His research interests include intelligent and embedded systems.",institutionString:"Universidad Autonoma de Queretaro",institution:{name:"Autonomous University of Queretaro",institutionURL:null,country:{name:"Mexico"}}},editorTwo:null,editorThree:null},{id:"27",title:"Multi-Agent Systems",coverUrl:"https://cdn.intechopen.com/series_topics/covers/27.jpg",isOpenForSubmission:!0,editor:{id:"148497",title:"Dr.",name:"Mehmet",middleName:"Emin",surname:"Aydin",slug:"mehmet-aydin",fullName:"Mehmet Aydin",profilePictureURL:"https://mts.intechopen.com/storage/users/148497/images/system/148497.jpg",biography:"Dr. Mehmet Emin Aydin is a Senior Lecturer with the Department of Computer Science and Creative Technology, the University of the West of England, Bristol, UK. His research interests include swarm intelligence, parallel and distributed metaheuristics, machine learning, intelligent agents and multi-agent systems, resource planning, scheduling and optimization, combinatorial optimization. Dr. Aydin is currently a Fellow of Higher Education Academy, UK, a member of EPSRC College, a senior member of IEEE and a senior member of ACM. In addition to being a member of advisory committees of many international conferences, he is an Editorial Board Member of various peer-reviewed international journals. He has served as guest editor for a number of special issues of peer-reviewed international journals.",institutionString:null,institution:{name:"University of the West of England",institutionURL:null,country:{name:"United Kingdom"}}},editorTwo:null,editorThree:null}]},overviewPageOFChapters:{paginationCount:6,paginationItems:[{id:"82526",title:"Deep Multiagent Reinforcement Learning Methods Addressing the Scalability Challenge",doi:"10.5772/intechopen.105627",signatures:"Theocharis Kravaris and George A. Vouros",slug:"deep-multiagent-reinforcement-learning-methods-addressing-the-scalability-challenge",totalDownloads:19,totalCrossrefCites:0,totalDimensionsCites:0,authors:null,book:{title:"Multi-Agent Technologies and Machine Learning",coverURL:"https://cdn.intechopen.com/books/images_new/11445.jpg",subseries:{id:"27",title:"Multi-Agent Systems"}}},{id:"82196",title:"Multi-Features Assisted Age Invariant Face Recognition and Retrieval Using CNN with Scale Invariant Heat Kernel Signature",doi:"10.5772/intechopen.104944",signatures:"Kamarajugadda Kishore Kumar and Movva Pavani",slug:"multi-features-assisted-age-invariant-face-recognition-and-retrieval-using-cnn-with-scale-invariant-",totalDownloads:14,totalCrossrefCites:0,totalDimensionsCites:0,authors:null,book:{title:"Pattern Recognition - New Insights",coverURL:"https://cdn.intechopen.com/books/images_new/11442.jpg",subseries:{id:"26",title:"Machine Learning and Data Mining"}}},{id:"82063",title:"Evaluating Similarities and Differences between Machine Learning and Traditional Statistical Modeling in Healthcare Analytics",doi:"10.5772/intechopen.105116",signatures:"Michele Bennett, Ewa J. 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He was elected a Yangtze River Scholars Distinguished Professor in 2013, a member of the International Statistical Institute (ISI) in 2016, a member of the board of the International Chinese Statistical Association (ICSA) in 2018, and a fellow of the Institute of Mathematical Statistics (IMS) in 2021. He received the ICSA Outstanding Service Award in 2018 and the National Science Foundation for Distinguished Young Scholars of China in 2012. He serves as a member of the editorial board of Statistics and Its Interface and Journal of Systems Science and Complexity. He is also a field editor for Communications in Mathematics and Statistics. His research interests include biostatistics, empirical likelihood, missing data analysis, variable selection, high-dimensional data analysis, Bayesian statistics, and data science. He has published more than 190 research papers and authored five books.",institutionString:"Yunnan University",institution:{name:"Yunnan University",country:{name:"China"}}},{id:"1177",title:"Prof.",name:"António",middleName:"J. R.",surname:"José Ribeiro Neves",slug:"antonio-jose-ribeiro-neves",fullName:"António José Ribeiro Neves",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/1177/images/system/1177.jpg",biography:"Prof. António J. R. Neves received a Ph.D. in Electrical Engineering from the University of Aveiro, Portugal, in 2007. Since 2002, he has been a researcher at the Institute of Electronics and Informatics Engineering of Aveiro. Since 2007, he has been an assistant professor in the Department of Electronics, Telecommunications, and Informatics, University of Aveiro. He is the director of the undergraduate course on Electrical and Computers Engineering and the vice-director of the master’s degree in Electronics and Telecommunications Engineering. He is an IEEE Senior Member and a member of several other research organizations worldwide. His main research interests are computer vision, intelligent systems, robotics, and image and video processing. He has participated in or coordinated several research projects and received more than thirty-five awards. He has 161 publications to his credit, including books, book chapters, journal articles, and conference papers. He has vast experience as a reviewer of several journals and conferences. As a professor, Dr. Neves has supervised several Ph.D. and master’s students and was involved in more than twenty-five different courses.",institutionString:null,institution:{name:"University of Aveiro",country:{name:"Portugal"}}},{id:"11317",title:"Dr.",name:"Francisco",middleName:null,surname:"Javier Gallegos-Funes",slug:"francisco-javier-gallegos-funes",fullName:"Francisco Javier Gallegos-Funes",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/11317/images/system/11317.png",biography:"Francisco J. Gallegos-Funes received his Ph.D. in Communications and Electronics from the Instituto Politécnico Nacional de México (National Polytechnic Institute of Mexico) in 2003. He is currently an associate professor in the Escuela Superior de Ingeniería Mecánica y Eléctrica (Mechanical and Electrical Engineering Higher School) at the same institute. His areas of scientific interest are signal and image processing, filtering, steganography, segmentation, pattern recognition, biomedical signal processing, sensors, and real-time applications.",institutionString:"Instituto Politécnico Nacional",institution:{name:"Instituto Politécnico Nacional",country:{name:"Mexico"}}},{id:"428449",title:"Dr.",name:"Ronaldo",middleName:null,surname:"Ferreira",slug:"ronaldo-ferreira",fullName:"Ronaldo Ferreira",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/428449/images/21449_n.png",biography:null,institutionString:null,institution:{name:"University of Aveiro",country:{name:"Portugal"}}},{id:"165328",title:"Dr.",name:"Vahid",middleName:null,surname:"Asadpour",slug:"vahid-asadpour",fullName:"Vahid Asadpour",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/165328/images/system/165328.jpg",biography:"Vahid Asadpour, MS, Ph.D., is currently with the Department of Research and Evaluation, Kaiser Permanente Southern California. He has both an MS and Ph.D. in Biomedical Engineering. He was previously a research scientist at the University of California Los Angeles (UCLA) and visiting professor and researcher at the University of North Dakota. He is currently working in artificial intelligence and its applications in medical signal processing. In addition, he is using digital signal processing in medical imaging and speech processing. Dr. Asadpour has developed brain-computer interfacing algorithms and has published books, book chapters, and several journal and conference papers in this field and other areas of intelligent signal processing. He has also designed medical devices, including a laser Doppler monitoring system.",institutionString:"Kaiser Permanente Southern California",institution:null},{id:"169608",title:"Prof.",name:"Marian",middleName:null,surname:"Găiceanu",slug:"marian-gaiceanu",fullName:"Marian Găiceanu",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/169608/images/system/169608.png",biography:"Prof. Dr. Marian Gaiceanu graduated from the Naval and Electrical Engineering Faculty, Dunarea de Jos University of Galati, Romania, in 1997. He received a Ph.D. (Magna Cum Laude) in Electrical Engineering in 2002. Since 2017, Dr. Gaiceanu has been a Ph.D. supervisor for students in Electrical Engineering. He has been employed at Dunarea de Jos University of Galati since 1996, where he is currently a professor. Dr. Gaiceanu is a member of the National Council for Attesting Titles, Diplomas and Certificates, an expert of the Executive Agency for Higher Education, Research Funding, and a member of the Senate of the Dunarea de Jos University of Galati. He has been the head of the Integrated Energy Conversion Systems and Advanced Control of Complex Processes Research Center, Romania, since 2016. He has conducted several projects in power converter systems for electrical drives, power quality, PEM and SOFC fuel cell power converters for utilities, electric vehicles, and marine applications with the Department of Regulation and Control, SIEI S.pA. (2002–2004) and the Polytechnic University of Turin, Italy (2002–2004, 2006–2007). He is a member of the Institute of Electrical and Electronics Engineers (IEEE) and cofounder-member of the IEEE Power Electronics Romanian Chapter. He is a guest editor at Energies and an academic book editor for IntechOpen. He is also a member of the editorial boards of the Journal of Electrical Engineering, Electronics, Control and Computer Science and Sustainability. Dr. Gaiceanu has been General Chairman of the IEEE International Symposium on Electrical and Electronics Engineering in the last six editions.",institutionString:'"Dunarea de Jos" University of Galati',institution:{name:'"Dunarea de Jos" University of Galati',country:{name:"Romania"}}},{id:"4519",title:"Prof.",name:"Jaydip",middleName:null,surname:"Sen",slug:"jaydip-sen",fullName:"Jaydip Sen",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/4519/images/system/4519.jpeg",biography:"Jaydip Sen is associated with Praxis Business School, Kolkata, India, as a professor in the Department of Data Science. His research areas include security and privacy issues in computing and communication, intrusion detection systems, machine learning, deep learning, and artificial intelligence in the financial domain. He has more than 200 publications in reputed international journals, refereed conference proceedings, and 20 book chapters in books published by internationally renowned publishing houses, such as Springer, CRC press, IGI Global, etc. Currently, he is serving on the editorial board of the prestigious journal Frontiers in Communications and Networks and in the technical program committees of a number of high-ranked international conferences organized by the IEEE, USA, and the ACM, USA. He has been listed among the top 2% of scientists in the world for the last three consecutive years, 2019 to 2021 as per studies conducted by the Stanford University, USA.",institutionString:"Praxis Business School",institution:null},{id:"320071",title:"Dr.",name:"Sidra",middleName:null,surname:"Mehtab",slug:"sidra-mehtab",fullName:"Sidra Mehtab",position:null,profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0033Y00002v6KHoQAM/Profile_Picture_1584512086360",biography:"Sidra Mehtab has completed her BS with honors in Physics from Calcutta University, India in 2018. She has done MS in Data Science and Analytics from Maulana Abul Kalam Azad University of Technology (MAKAUT), Kolkata, India in 2020. Her research areas include Econometrics, Time Series Analysis, Machine Learning, Deep Learning, Artificial Intelligence, and Computer and Network Security with a particular focus on Cyber Security Analytics. Ms. Mehtab has published seven papers in international conferences and one of her papers has been accepted for publication in a reputable international journal. She has won the best paper awards in two prestigious international conferences – BAICONF 2019, and ICADCML 2021, organized in the Indian Institute of Management, Bangalore, India in December 2019, and SOA University, Bhubaneswar, India in January 2021. Besides, Ms. Mehtab has also published two book chapters in two books. Seven of her book chapters will be published in a volume shortly in 2021 by Cambridge Scholars’ Press, UK. Currently, she is working as the joint editor of two edited volumes on Time Series Analysis and Forecasting to be published in the first half of 2021 by an international house. Currently, she is working as a Data Scientist with an MNC in Delhi, India.",institutionString:"NSHM College of Management and Technology",institution:{name:"Association for Computing Machinery",country:{name:"United States of America"}}},{id:"226240",title:"Dr.",name:"Andri Irfan",middleName:null,surname:"Rifai",slug:"andri-irfan-rifai",fullName:"Andri Irfan Rifai",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/226240/images/7412_n.jpg",biography:"Andri IRFAN is a Senior Lecturer of Civil Engineering and Planning. He completed the PhD at the Universitas Indonesia & Universidade do Minho with Sandwich Program Scholarship from the Directorate General of Higher Education and LPDP scholarship. He has been teaching for more than 19 years and much active to applied his knowledge in the project construction in Indonesia. His research interest ranges from pavement management system to advanced data mining techniques for transportation engineering. He has published more than 50 papers in journals and 2 books.",institutionString:null,institution:{name:"Universitas Internasional Batam",country:{name:"Indonesia"}}},{id:"314576",title:"Dr.",name:"Ibai",middleName:null,surname:"Laña",slug:"ibai-lana",fullName:"Ibai Laña",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/314576/images/system/314576.jpg",biography:"Dr. Ibai Laña works at TECNALIA as a data analyst. He received his Ph.D. in Artificial Intelligence from the University of the Basque Country (UPV/EHU), Spain, in 2018. He is currently a senior researcher at TECNALIA. His research interests fall within the intersection of intelligent transportation systems, machine learning, traffic data analysis, and data science. He has dealt with urban traffic forecasting problems, applying machine learning models and evolutionary algorithms. He has experience in origin-destination matrix estimation or point of interest and trajectory detection. Working with large volumes of data has given him a good command of big data processing tools and NoSQL databases. He has also been a visiting scholar at the Knowledge Engineering and Discovery Research Institute, Auckland University of Technology.",institutionString:"TECNALIA Research & Innovation",institution:{name:"Tecnalia",country:{name:"Spain"}}},{id:"314575",title:"Dr.",name:"Jesus",middleName:null,surname:"L. Lobo",slug:"jesus-l.-lobo",fullName:"Jesus L. Lobo",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/314575/images/system/314575.png",biography:"Dr. Jesús López is currently based in Bilbao (Spain) working at TECNALIA as Artificial Intelligence Research Scientist. In most cases, a project idea or a new research line needs to be investigated to see if it is good enough to take into production or to focus on it. That is exactly what he does, diving into Machine Learning algorithms and technologies to help TECNALIA to decide whether something is great in theory or will actually impact on the product or processes of its projects. So, he is expert at framing experiments, developing hypotheses, and proving whether they’re true or not, in order to investigate fundamental problems with a longer time horizon. He is also able to design and develop PoCs and system prototypes in simulation. He has participated in several national and internacional R&D projects.\n\nAs another relevant part of his everyday research work, he usually publishes his findings in reputed scientific refereed journals and international conferences, occasionally acting as reviewer and Programme Commitee member. Concretely, since 2018 he has published 9 JCR (8 Q1) journal papers, 9 conference papers (e.g. ECML PKDD 2021), and he has co-edited a book. He is also active in popular science writing data science stories for reputed blogs (KDNuggets, TowardsDataScience, Naukas). Besides, he has recently embarked on mentoring programmes as mentor, and has also worked as data science trainer.",institutionString:"TECNALIA Research & Innovation",institution:{name:"Tecnalia",country:{name:"Spain"}}},{id:"103779",title:"Prof.",name:"Yalcin",middleName:null,surname:"Isler",slug:"yalcin-isler",fullName:"Yalcin Isler",position:null,profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRyQ8QAK/Profile_Picture_1628834958734",biography:"Yalcin Isler (1971 - Burdur / Turkey) received the B.Sc. degree in the Department of Electrical and Electronics Engineering from Anadolu University, Eskisehir, Turkey, in 1993, the M.Sc. degree from the Department of Electronics and Communication Engineering, Suleyman Demirel University, Isparta, Turkey, in 1996, the Ph.D. degree from the Department of Electrical and Electronics Engineering, Dokuz Eylul University, Izmir, Turkey, in 2009, and the Competence of Associate Professorship from the Turkish Interuniversity Council in 2019.\n\nHe was Lecturer at Burdur Vocational School in Suleyman Demirel University (1993-2000, Burdur / Turkey), Software Engineer (2000-2002, Izmir / Turkey), Research Assistant in Bulent Ecevit University (2002-2003, Zonguldak / Turkey), Research Assistant in Dokuz Eylul University (2003-2010, Izmir / Turkey), Assistant Professor at the Department of Electrical and Electronics Engineering in Bulent Ecevit University (2010-2012, Zonguldak / Turkey), Assistant Professor at the Department of Biomedical Engineering in Izmir Katip Celebi University (2012-2019, Izmir / Turkey). He is an Associate Professor at the Department of Biomedical Engineering at Izmir Katip Celebi University, Izmir / Turkey, since 2019. In addition to academics, he has also founded Islerya Medical and Information Technologies Company, Izmir / Turkey, since 2017.\n\nHis main research interests cover biomedical signal processing, pattern recognition, medical device design, programming, and embedded systems. He has many scientific papers and participated in several projects in these study fields. He was an IEEE Student Member (2009-2011) and IEEE Member (2011-2014) and has been IEEE Senior Member since 2014.",institutionString:null,institution:{name:"Izmir Kâtip Çelebi University",country:{name:"Turkey"}}},{id:"339677",title:"Dr.",name:"Mrinmoy",middleName:null,surname:"Roy",slug:"mrinmoy-roy",fullName:"Mrinmoy Roy",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/339677/images/16768_n.jpg",biography:"An accomplished Sales & Marketing professional with 12 years of cross-functional experience in well-known organisations such as CIPLA, LUPIN, GLENMARK, ASTRAZENECA across different segment of Sales & Marketing, International Business, Institutional Business, Product Management, Strategic Marketing of HIV, Oncology, Derma, Respiratory, Anti-Diabetic, Nutraceutical & Stomatological Product Portfolio and Generic as well as Chronic Critical Care Portfolio. A First Class MBA in International Business & Strategic Marketing, B.Pharm, D.Pharm, Google Certified Digital Marketing Professional. Qualified PhD Candidate in Operations and Management with special focus on Artificial Intelligence and Machine Learning adoption, analysis and use in Healthcare, Hospital & Pharma Domain. Seasoned with diverse therapy area of Pharmaceutical Sales & Marketing ranging from generating revenue through generating prescriptions, launching new products, and making them big brands with continuous strategy execution at the Physician and Patients level. Moved from Sales to Marketing and Business Development for 3.5 years in South East Asian Market operating from Manila, Philippines. Came back to India and handled and developed Brands such as Gluconorm, Lupisulin, Supracal, Absolut Woman, Hemozink, Fabiflu (For COVID 19), and many more. In my previous assignment I used to develop and execute strategies on Sales & Marketing, Commercialization & Business Development for Institution and Corporate Hospital Business portfolio of Oncology Therapy Area for AstraZeneca Pharma India Ltd. Being a Research Scholar and Student of ‘Operations Research & Management: Artificial Intelligence’ I published several pioneer research papers and book chapters on the same in Internationally reputed journals and Books indexed in Scopus, Springer and Ei Compendex, Google Scholar etc. Currently, I am launching PGDM Pharmaceutical Management Program in IIHMR Bangalore and spearheading the course curriculum and structure of the same. I am interested in Collaboration for Healthcare Innovation, Pharma AI Innovation, Future trend in Marketing and Management with incubation on Healthcare, Healthcare IT startups, AI-ML Modelling and Healthcare Algorithm based training module development. I am also an affiliated member of the Institute of Management Consultant of India, looking forward to Healthcare, Healthcare IT and Innovation, Pharma and Hospital Management Consulting works.",institutionString:null,institution:{name:"Lovely Professional University",country:{name:"India"}}},{id:"1063",title:"Prof.",name:"Constantin",middleName:null,surname:"Volosencu",slug:"constantin-volosencu",fullName:"Constantin Volosencu",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/1063/images/system/1063.png",biography:"Prof. Dr. Constantin Voloşencu graduated as an engineer from\nPolitehnica University of Timișoara, Romania, where he also\nobtained a doctorate degree. He is currently a full professor in\nthe Department of Automation and Applied Informatics at the\nsame university. Dr. Voloşencu is the author of ten books, seven\nbook chapters, and more than 160 papers published in journals\nand conference proceedings. He has also edited twelve books and\nhas twenty-seven patents to his name. He is a manager of research grants, editor in\nchief and member of international journal editorial boards, a former plenary speaker, a member of scientific committees, and chair at international conferences. His\nresearch is in the fields of control systems, control of electric drives, fuzzy control\nsystems, neural network applications, fault detection and diagnosis, sensor network\napplications, monitoring of distributed parameter systems, and power ultrasound\napplications. He has developed automation equipment for machine tools, spooling\nmachines, high-power ultrasound processes, and more.",institutionString:'"Politechnica" University Timişoara',institution:null},{id:"221364",title:"Dr.",name:"Eneko",middleName:null,surname:"Osaba",slug:"eneko-osaba",fullName:"Eneko Osaba",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/221364/images/system/221364.jpg",biography:"Dr. Eneko Osaba works at TECNALIA as a senior researcher. He obtained his Ph.D. in Artificial Intelligence in 2015. He has participated in more than twenty-five local and European research projects, and in the publication of more than 130 papers. He has performed several stays at universities in the United Kingdom, Italy, and Malta. Dr. Osaba has served as a program committee member in more than forty international conferences and participated in organizing activities in more than ten international conferences. He is a member of the editorial board of the International Journal of Artificial Intelligence, Data in Brief, and Journal of Advanced Transportation. He is also a guest editor for the Journal of Computational Science, Neurocomputing, Swarm, and Evolutionary Computation and IEEE ITS Magazine.",institutionString:"TECNALIA Research & Innovation",institution:{name:"Tecnalia",country:{name:"Spain"}}},{id:"275829",title:"Dr.",name:"Esther",middleName:null,surname:"Villar-Rodriguez",slug:"esther-villar-rodriguez",fullName:"Esther Villar-Rodriguez",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/275829/images/system/275829.jpg",biography:"Dr. Esther Villar obtained a Ph.D. in Information and Communication Technologies from the University of Alcalá, Spain, in 2015. She obtained a degree in Computer Science from the University of Deusto, Spain, in 2010, and an MSc in Computer Languages and Systems from the National University of Distance Education, Spain, in 2012. Her areas of interest and knowledge include natural language processing (NLP), detection of impersonation in social networks, semantic web, and machine learning. Dr. Esther Villar made several contributions at conferences and publishing in various journals in those fields. Currently, she is working within the OPTIMA (Optimization Modeling & Analytics) business of TECNALIA’s ICT Division as a data scientist in projects related to the prediction and optimization of management and industrial processes (resource planning, energy efficiency, etc).",institutionString:"TECNALIA Research & Innovation",institution:{name:"Tecnalia",country:{name:"Spain"}}},{id:"49813",title:"Dr.",name:"Javier",middleName:null,surname:"Del Ser",slug:"javier-del-ser",fullName:"Javier Del Ser",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/49813/images/system/49813.png",biography:"Prof. Dr. Javier Del Ser received his first PhD in Telecommunication Engineering (Cum Laude) from the University of Navarra, Spain, in 2006, and a second PhD in Computational Intelligence (Summa Cum Laude) from the University of Alcala, Spain, in 2013. He is currently a principal researcher in data analytics and optimisation at TECNALIA (Spain), a visiting fellow at the Basque Center for Applied Mathematics (BCAM) and a part-time lecturer at the University of the Basque Country (UPV/EHU). His research interests gravitate on the use of descriptive, prescriptive and predictive algorithms for data mining and optimization in a diverse range of application fields such as Energy, Transport, Telecommunications, Health and Industry, among others. In these fields he has published more than 240 articles, co-supervised 8 Ph.D. theses, edited 6 books, coauthored 7 patents and participated/led more than 40 research projects. He is a Senior Member of the IEEE, and a recipient of the Biscay Talent prize for his academic career.",institutionString:"Tecnalia Research & Innovation",institution:{name:"Tecnalia",country:{name:"Spain"}}},{id:"278948",title:"Dr.",name:"Carlos Pedro",middleName:null,surname:"Gonçalves",slug:"carlos-pedro-goncalves",fullName:"Carlos Pedro Gonçalves",position:null,profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRcmyQAC/Profile_Picture_1564224512145",biography:'Carlos Pedro Gonçalves (PhD) is an Associate Professor at Lusophone University of Humanities and Technologies and a researcher on Complexity Sciences, Quantum Technologies, Artificial Intelligence, Strategic Studies, Studies in Intelligence and Security, FinTech and Financial Risk Modeling. He is also a progammer with programming experience in:\n\nA) Quantum Computing using Qiskit Python module and IBM Quantum Experience Platform, with software developed on the simulation of Quantum Artificial Neural Networks and Quantum Cybersecurity;\n\nB) Artificial Intelligence and Machine learning programming in Python;\n\nC) Artificial Intelligence, Multiagent Systems Modeling and System Dynamics Modeling in Netlogo, with models developed in the areas of Chaos Theory, Econophysics, Artificial Intelligence, Classical and Quantum Complex Systems Science, with the Econophysics models having been cited worldwide and incorporated in PhD programs by different Universities.\n\nReceived an Arctic Code Vault Contributor status by GitHub, due to having developed open source software preserved in the \\"Arctic Code Vault\\" for future generations (https://archiveprogram.github.com/arctic-vault/), with the Strategy Analyzer A.I. module for decision making support (based on his PhD thesis, used in his Classes on Decision Making and in Strategic Intelligence Consulting Activities) and QNeural Python Quantum Neural Network simulator also preserved in the \\"Arctic Code Vault\\", for access to these software modules see: https://github.com/cpgoncalves. He is also a peer reviewer with outsanding review status from Elsevier journals, including Physica A, Neurocomputing and Engineering Applications of Artificial Intelligence. Science CV available at: https://www.cienciavitae.pt//pt/8E1C-A8B3-78C5 and ORCID: https://orcid.org/0000-0002-0298-3974',institutionString:"University of Lisbon",institution:{name:"Universidade Lusófona",country:{name:"Portugal"}}},{id:"310576",title:"Prof.",name:"Erick Giovani",middleName:null,surname:"Sperandio Nascimento",slug:"erick-giovani-sperandio-nascimento",fullName:"Erick Giovani Sperandio Nascimento",position:null,profilePictureURL:"https://intech-files.s3.amazonaws.com/0033Y00002pDKxDQAW/ProfilePicture%202022-06-20%2019%3A57%3A24.788",biography:"Prof. Erick Sperandio is the Lead Researcher and professor of Artificial Intelligence (AI) at SENAI CIMATEC, Bahia, Brazil, also working with Computational Modeling (CM) and HPC. He holds a PhD in Environmental Engineering in the area of Atmospheric Computational Modeling, a Master in Informatics in the field of Computational Intelligence and Graduated in Computer Science from UFES. He currently coordinates, leads and participates in R&D projects in the areas of AI, computational modeling and supercomputing applied to different areas such as Oil and Gas, Health, Advanced Manufacturing, Renewable Energies and Atmospheric Sciences, advising undergraduate, master's and doctoral students. He is the Lead Researcher at SENAI CIMATEC's Reference Center on Artificial Intelligence. In addition, he is a Certified Instructor and University Ambassador of the NVIDIA Deep Learning Institute (DLI) in the areas of Deep Learning, Computer Vision, Natural Language Processing and Recommender Systems, and Principal Investigator of the NVIDIA/CIMATEC AI Joint Lab, the first in Latin America within the NVIDIA AI Technology Center (NVAITC) worldwide program. He also works as a researcher at the Supercomputing Center for Industrial Innovation (CS2i) and at the SENAI Institute of Innovation for Automation (ISI Automação), both from SENAI CIMATEC. He is a member and vice-coordinator of the Basic Board of Scientific-Technological Advice and Evaluation, in the area of Innovation, of the Foundation for Research Support of the State of Bahia (FAPESB). He serves as Technology Transfer Coordinator and one of the Principal Investigators at the National Applied Research Center in Artificial Intelligence (CPA-IA) of SENAI CIMATEC, focusing on Industry, being one of the six CPA-IA in Brazil approved by MCTI / FAPESP / CGI.br. He also participates as one of the representatives of Brazil in the BRICS Innovation Collaboration Working Group on HPC, ICT and AI. He is the coordinator of the Work Group of the Axis 5 - Workforce and Training - of the Brazilian Strategy for Artificial Intelligence (EBIA), and member of the MCTI/EMBRAPII AI Innovation Network Training Committee. He is the coordinator, by SENAI CIMATEC, of the Artificial Intelligence Reference Network of the State of Bahia (REDE BAH.IA). He leads the working group of experts representing Brazil in the Global Partnership on Artificial Intelligence (GPAI), on the theme \"AI and the Pandemic Response\".",institutionString:null,institution:null},{id:"241400",title:"Prof.",name:"Mohammed",middleName:null,surname:"Bsiss",slug:"mohammed-bsiss",fullName:"Mohammed Bsiss",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/241400/images/8062_n.jpg",biography:null,institutionString:null,institution:null},{id:"276128",title:"Dr.",name:"Hira",middleName:null,surname:"Fatima",slug:"hira-fatima",fullName:"Hira Fatima",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/276128/images/14420_n.jpg",biography:"Dr. Hira Fatima\nAssistant Professor\nDepartment of Mathematics\nInstitute of Applied Science\nMangalayatan University, Aligarh\nMobile: no : 8532041179\nhirafatima2014@gmal.com\n\nDr. Hira Fatima has received his Ph.D. degree in pure Mathematics from Aligarh Muslim University, Aligarh India. Currently working as an Assistant Professor in the Department of Mathematics, Institute of Applied Science, Mangalayatan University, Aligarh. She taught so many courses of Mathematics of UG and PG level. Her research Area of Expertise is Functional Analysis & Sequence Spaces. She has been working on Ideal Convergence of double sequence. She has published 17 research papers in National and International Journals including Cogent Mathematics, Filomat, Journal of Intelligent and Fuzzy Systems, Advances in Difference Equations, Journal of Mathematical Analysis, Journal of Mathematical & Computer Science etc. She has also reviewed few research papers for the and international journals. 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