Solid body model: industrial steel pipe transporting clean water.
\\n\\n
Released this past November, the list is based on data collected from the Web of Science and highlights some of the world’s most influential scientific minds by naming the researchers whose publications over the previous decade have included a high number of Highly Cited Papers placing them among the top 1% most-cited.
\\n\\nWe wish to congratulate all of the researchers named and especially our authors on this amazing accomplishment! We are happy and proud to share in their success!
Note: Edited in March 2021
\\n"}]',published:!0,mainMedia:{caption:"Highly Cited",originalUrl:"/media/original/117"}},components:[{type:"htmlEditorComponent",content:'IntechOpen is proud to announce that 191 of our authors have made the Clarivate™ Highly Cited Researchers List for 2020, ranking them among the top 1% most-cited.
\n\nThroughout the years, the list has named a total of 261 IntechOpen authors as Highly Cited. Of those researchers, 69 have been featured on the list multiple times.
\n\n\n\nReleased this past November, the list is based on data collected from the Web of Science and highlights some of the world’s most influential scientific minds by naming the researchers whose publications over the previous decade have included a high number of Highly Cited Papers placing them among the top 1% most-cited.
\n\nWe wish to congratulate all of the researchers named and especially our authors on this amazing accomplishment! We are happy and proud to share in their success!
Note: Edited in March 2021
\n'}],latestNews:[{slug:"webinar-introduction-to-open-science-wednesday-18-may-1-pm-cest-20220518",title:"Webinar: Introduction to Open Science | Wednesday 18 May, 1 PM CEST"},{slug:"step-in-the-right-direction-intechopen-launches-a-portfolio-of-open-science-journals-20220414",title:"Step in the Right Direction: IntechOpen Launches a Portfolio of Open Science Journals"},{slug:"let-s-meet-at-london-book-fair-5-7-april-2022-olympia-london-20220321",title:"Let’s meet at London Book Fair, 5-7 April 2022, Olympia London"},{slug:"50-books-published-as-part-of-intechopen-and-knowledge-unlatched-ku-collaboration-20220316",title:"50 Books published as part of IntechOpen and Knowledge Unlatched (KU) Collaboration"},{slug:"intechopen-joins-the-united-nations-sustainable-development-goals-publishers-compact-20221702",title:"IntechOpen joins the United Nations Sustainable Development Goals Publishers Compact"},{slug:"intechopen-signs-exclusive-representation-agreement-with-lsr-libros-servicios-y-representaciones-s-a-de-c-v-20211123",title:"IntechOpen Signs Exclusive Representation Agreement with LSR Libros Servicios y Representaciones S.A. de C.V"},{slug:"intechopen-expands-partnership-with-research4life-20211110",title:"IntechOpen Expands Partnership with Research4Life"},{slug:"introducing-intechopen-book-series-a-new-publishing-format-for-oa-books-20210915",title:"Introducing IntechOpen Book Series - A New Publishing Format for OA Books"}]},book:{item:{type:"book",id:"72",leadTitle:null,fullTitle:"Ionic Liquids: Theory, Properties, New Approaches",title:"Ionic Liquids",subtitle:"Theory, Properties, New Approaches",reviewType:"peer-reviewed",abstract:"Ionic Liquids (ILs) are one of the most interesting and rapidly developing areas of modern physical chemistry, technologies and engineering. This book, consisting of 29 chapters gathered in 4 sections, reviews in detail and compiles information about some important physical-chemical properties of ILs and new practical approaches. This is the first book of a series of forthcoming publications on this field by this publisher. The first volume covers some aspects of synthesis, isolation, production, modification, the analysis methods and modeling to reveal the structures and properties of some room temperature ILs, as well as their new possible applications. The book will be of help to chemists, physicists, biologists, technologists and other experts in a variety of disciplines, both academic and industrial, as well as to students and PhD students. It may help to promote the progress in ILs development also.",isbn:null,printIsbn:"978-953-307-349-1",pdfIsbn:"978-953-51-4517-2",doi:"10.5772/603",price:159,priceEur:175,priceUsd:205,slug:"ionic-liquids-theory-properties-new-approaches",numberOfPages:750,isOpenForSubmission:!1,isInWos:1,isInBkci:!0,hash:"d94ffa3cfa10505e3b1d676d46fcd3f5",bookSignature:"Alexander Kokorin",publishedDate:"February 28th 2011",coverURL:"https://cdn.intechopen.com/books/images_new/72.jpg",numberOfDownloads:157046,numberOfWosCitations:488,numberOfCrossrefCitations:109,numberOfCrossrefCitationsByBook:56,numberOfDimensionsCitations:324,numberOfDimensionsCitationsByBook:91,hasAltmetrics:1,numberOfTotalCitations:921,isAvailableForWebshopOrdering:!0,dateEndFirstStepPublish:"May 12th 2010",dateEndSecondStepPublish:"June 9th 2010",dateEndThirdStepPublish:"September 14th 2010",dateEndFourthStepPublish:"November 13th 2010",dateEndFifthStepPublish:"January 27th 2011",currentStepOfPublishingProcess:5,indexedIn:"1,2,3,4,5,6,7,8",editedByType:"Edited by",kuFlag:!1,featuredMarkup:null,editors:[{id:"19816",title:"Prof.",name:"Alexander",middleName:null,surname:"Kokorin",slug:"alexander-kokorin",fullName:"Alexander Kokorin",profilePictureURL:"https://mts.intechopen.com/storage/users/19816/images/1607_n.jpg",biography:"Alexander I. Kokorin: born: 1947, Moscow; DSc., PhD; Principal Research Fellow (Research Professor) of Department of Kinetics and Catalysis, N. Semenov Institute of Chemical Physics, Russian Academy of Sciences, Moscow.\r\nArea of research interests: physical chemistry of complex-organized molecular and nanosized systems, including polymer-metal complexes; the surface of doped oxide semiconductors. He is an expert in structural, absorptive, catalytic and photocatalytic properties, in structural organization and dynamic features of ionic liquids, in magnetic interactions between paramagnetic centers. The author or co-author of 3 books, over 200 articles and reviews in scientific journals and books. He is an actual member of the International EPR/ESR Society, European Society on Quantum Solar Energy Conversion, Moscow House of Scientists, of the Board of Moscow Physical Society.",institutionString:null,position:null,outsideEditionCount:0,totalCites:0,totalAuthoredChapters:"2",totalChapterViews:"0",totalEditedBooks:"3",institution:{name:"Semenov Institute of Chemical Physics",institutionURL:null,country:{name:"Russia"}}}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,coeditorOne:null,coeditorTwo:null,coeditorThree:null,coeditorFour:null,coeditorFive:null,topics:[{id:"935",title:"Fluid Dynamics",slug:"materials-science-fluid-mechanics-fluid-dynamics"}],chapters:[{id:"13911",title:"Thermodynamic Properties of Ionic Liquids - Measurements and Predictions -",doi:"10.5772/15222",slug:"thermodynamic-properties-of-ionic-liquids-measurements-and-predictions-",totalDownloads:8035,totalCrossrefCites:4,totalDimensionsCites:7,hasAltmetrics:0,abstract:null,signatures:"Zhi-Cheng Tan, Urs Welz-Biermann, Pei-Fang Yan, Qing-Shan Liu and Da-Wei Fang",downloadPdfUrl:"/chapter/pdf-download/13911",previewPdfUrl:"/chapter/pdf-preview/13911",authors:[{id:"20011",title:"Prof.",name:"Zhi-Cheng",surname:"Tan",slug:"zhi-cheng-tan",fullName:"Zhi-Cheng Tan"},{id:"20825",title:"Prof.",name:"Urs",surname:"Welz-Biermann",slug:"urs-welz-biermann",fullName:"Urs Welz-Biermann"},{id:"20826",title:"Prof.",name:"Pei-Fang",surname:"Yan",slug:"pei-fang-yan",fullName:"Pei-Fang Yan"},{id:"20827",title:"Dr.",name:"Qing-Shan",surname:"Liu",slug:"qing-shan-liu",fullName:"Qing-Shan Liu"},{id:"20828",title:"Prof.",name:"Da-Wei",surname:"Fang",slug:"da-wei-fang",fullName:"Da-Wei Fang"}],corrections:null},{id:"13912",title:"Thermal Properties of Ionic Liquids and Ionanofluids",doi:"10.5772/13920",slug:"thermal-properties-of-ionic-liquids-and-ionanofluids",totalDownloads:8833,totalCrossrefCites:10,totalDimensionsCites:23,hasAltmetrics:0,abstract:null,signatures:"A.P.C. 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His research interests include thermophysical properties of hydrocarbons at high-pressure, high-temperature conditions, and technical challenges associated with oil recovery from ultra-deep petroleum reservoirs.",institutionString:"University of Pittsburgh",position:null,outsideEditionCount:0,totalCites:0,totalAuthoredChapters:"0",totalChapterViews:"0",totalEditedBooks:"0",institution:{name:"University of Pittsburgh",institutionURL:null,country:{name:"United States of America"}}}],coeditorOne:{id:"313507",title:"Dr.",name:"Adel",middleName:null,surname:"Alenzi",slug:"adel-alenzi",fullName:"Adel Alenzi",profilePictureURL:"https://mts.intechopen.com/storage/users/313507/images/system/313507.jpg",biography:"Dr. Adel F. Alenzi is an Assistant Professor at the Department of Chemical Engineering Technology at the College of Technological Studies, Kuwait. He was previously the Department Chairman at the College of Technological Studies. Dr. Alenzi received his PhD degree in Chemical Engineering from the University of Pittsburgh, USA, 2012. He finished his undergraduate studies from University of Missouri - Columbia, USA, 1996. Dr. Alenzi research work focuses on multi-scale, multi-phase study of the transport phenomena (the flow of momentum, heat transfer, and mass transfer) applied to process engineering. 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Spanner, a much respected naval architect, invented a helical lobate tube which increased the efficiency of heating of water in the boilers of ships [1, 2]. Importantly, his design could be manufactured economically by drawing cylindrical tube through special dies (see Figure 1).
Three-lobe boiler tube after Spanner, 1939, 1945. Reproduced courtesy of Transport and Sedimentation Conference, Wroclaw University of Environmental and Life Sciences, Poland.
For particle-bearing liquids, swirl puts particles into suspension at lower axial velocities than would be the case for a cylindrical duct. Once in suspension, particles (or debris for downstream collection) remain in full or partial suspension long after the swirl has decayed to negligible proportions.
Lower axial velocity implies much lower pumping power: a strong economic reason to swirl the flow in the first place. The efficacy of swirl generation in pumping particulate liquids, particularly river slurries, has been recognized for many years. The Gordon patent for a duct with internal vanes to encourage swirl was published in 1899 [3].
Economic benefits are not the only reasons for studying swirl. In some instances, enhanced swirl is required irrespective of increased pressure losses and pumping power requirement.
The data in this chapter originate from several sources. Much of it comes from validated computational fluid dynamics (CFD) code using RANS (Reynolds-averaged Navier Stokes equations). The basis of these equations is ‘Reynolds decomposition’, whereby an instantaneous quantity is decomposed into time-averaged quantities and fluctuating quantities. In cylindrical polar co-ordinates (
RANS turbulence modelling techniques are often classed by the number of equations used to model the flow field. Early results were obtained using two-equation
Firstly, I should explain what I mean by ‘swirl’ and then define precise ways to assess it. In turbulent pipe flow, there are many eddies and circulations cascading from the large to the small. Kolmorogov [6] showed that most of the kinetic energy in the flow is contained in large-scale structures. Energy ‘cascades’ to smaller scales by an inviscid mechanism until it is small enough for viscous dissipation to take place. I define swirl as large-scale, one-way circulation surrounding the geometric centre of the duct.
With a definition of swirl in place, I now need to explain the mathematical measures of this behaviour. Is it useful, strong or weak, efficient or profligate in its expenditure of pipeline pressure? The first and most obvious measure is the circumferential velocity, sometimes referred to as tangential velocity,
Circumferential velocity as a measure of swirl takes no account of the axial velocity required to generate or maintain it. In contrast, the
1.4% by volume coarse sand in water, axial velocity 1.7 m/s showing
The
where
Measurement transducers can be corrupted by swirling flow, and International Standard ISO 5167 specifies a maximum swirl-angle limit of 2° at or near transducer stations.
The swirl angle does not take account of the angular momentum given to the flowing liquid. The ratio of angular momentum flux to the product of pipe radius and axial momentum flux is known as the
where
Swirl number gives a simple way to classify swirl for computational calculation methods. If
Swirl intensity and swirl angle are closely related measures and in many cases an almost linear relation exists between them.
Pressure loss is an inevitable consequence of swirl generation and it is important to use that pressure effectively. Ganeshalingam [8] developed a dimensionless group,
where
This measure has proved invaluable in optimizing Spanner-type duct designs.
Another pressure-related metric for use when a Spanner-type duct generates swirl is the pressure loss for an equivalent length of smooth circular tube. The well-known Darcy-Weisbach equation can be used to calculate this:
where
In many cases of developed swirling flow, the swirl angle,
Circumferential velocity,
Damping friction (directly proportional to tangential velocity) clearly has little effect in the central 84% of Figure 3. The peripheral 16% of the velocity profile indicates gathering damping friction as the radius increases. At the outer radial extremity, the circumferential velocity falls to zero in accordance with the
where
In turbulent pipe flow, close to the wall, is a
The simplified system dynamics of the analogy of a solid-liquid cylinder are described by three elements: the
where
In the model, the coefficient of damping,
Fully developed swirling flow in a cylindrical duct.
In order to quantify the damping coefficient,
Newton’s law of viscosity gives
Torque is applied at the outer radius as wall friction or reaction from the pipe profile, so
Comparing (10) with (8), we obtain the coefficient of damping per unit length.
where
The next major challenge to the solid body model is the transmission of torque. In a solid shaft, the torque is transmitted by its stiffness, but stiffness has been discounted as a factor in liquids. In the case of a profiled swirl tube, the torque comes from the interaction of the axial flow with the walls of the tube, an interaction the author describes as the
Dividing throughout by
Note that the group of variables at the left-hand side of Eq. (3)
where the time constant
The
The solution to Eq. (14) has another (steady-state) part, the
There are a series of driving functions of interest and I shall start with the simplest: the decay of swirl angle downstream of swirling flow from, for example, a pump output or double elbow. The driving function
When
Halsey [10] studied the swirl in clean water following a double elbow. His work was aimed at measurement devices for which swirling flow is disruptive. ISO 5167 specifies a 2° swirl-angle limit for measurement purposes and Halsey came up with an empirical law for its decay as follows
where
Differentiating (19) gives
when
Equating exponents in Eqs. (18) and (21), we have a first estimate of the time constant
The solid body model gives us
From this, and the time constant
It is not possible to specify the total extinction of swirl. For some purposes, the point of 95% reduction in swirl angle (
m/s | — | — | s | m | Nms/m | m | — |
---|---|---|---|---|---|---|---|
1 | 50,000 | 0.024 | 1.37 | 0.95 | 0.00045 | 0.0065 | 82.3 |
1.5 | 75,000 | 0.023 | 0.97 | 1.00 | 0.00064 | 0.0050 | 76.8 |
2 | 100,000 | 0.022 | 0.75 | 1.04 | 0.00082 | 0.0040 | 71.8 |
2.5 | 125,000 | 0.022 | 0.61 | 1.06 | 0.00101 | 0.0034 | 67.5 |
3 | 150,000 | 0.022 | 0.52 | 1.07 | 0.00119 | 0.0029 | 63.9 |
3.5 | 175,000 | 0.021 | 0.45 | 1.08 | 0.00137 | 0.0026 | 60.8 |
4 | 200,000 | 0.021 | 0.39 | 1.09 | 0.00156 | 0.0023 | 58.0 |
Solid body model: industrial steel pipe transporting clean water.
Clean water: pipe diameter,
It is generally accepted that a
The half-life distances
Starting from an analysis by Kitoh [4], the tangential momentum equation for axi-symmetric flow gives an equation for circumferential shear stress at the wall in the decay of swirl in a circular pipe.
Now
where
Leibnitz’s rule for the differentiation of integrals allows the change of order of integration and differentiation in Eq. (25):
For a constant Reynolds number, the axial velocity
This allows the simplification of swirl intensity to
and substituting for
i.e.
Note that since
Returning to the analogy of a solid body for the flow, one might reasonably expect a linear relationship between circumferential stress and circumferential strain (swirl intensity or swirl angle) for a given Reynolds number. This can be tested with a straightforward simulation experiment.
The simulation experiment (below) gives
The imposition of pipe roughness considerably increases the friction factor,
SIMULATION EXPERIMENT: swirl decay in a cylindrical tube
Figure 5 shows the results of a simple RANS simulation for the flow of clean water through a 50-mm diameter smooth circular tube using the Reynolds stress model (
Reynolds number
Friction factor (Blasius equation):
Time constant (Eq. (22))
Effective range downstream:
For the solid body model this is
Measured mean friction factor over range: 0.0197
In this range, the regression law applied to the CFD data is very precise (
where
Dimensionless wall shear stress plotted against swirl intensity.
Note the significant difference in time constant for smooth pipe when compared to commercial industrial steel pipe because of the increased value of the multiplier
Since the swirl angle is linearly related to swirl intensity in most cases, it follows that Halsey’s correlation [10] also fits the data.
Previously, we have seen that a solid body model can be applied to the simple case of swirl decaying downstream. In these cases, the driving function is simply a step to zero:
The contours of duct walls should impart torque to the flow while minimizing pressure loss. By designing using this criterion, pressure costs are used in an effective way. Here, Ganeshalingham’s dimensionless group,
The boiler tube patented by Spanner and illustrated in Figure 1 has only three lobes. Raylor [11] idealized the lobe profiles to form semicircular shapes for his CFD modelling to test the design for the transportation of particle-bearing liquids. The computer modelling was underpinned by experimental work on an extant boiler tube. Later work by Ganeshalingam showed that a four-lobe duct (or a 2-lobe duct) was more efficient when compared on the basis of swirl effectiveness.
In Figure 6, after Ariyaratne [13], it can be seen that the contours of tangential velocity adopt a more circular pattern in the four-lobe variant and that an efficient circulating core flow is produced in consequence.
Contours of tangential velocity in three-lobe and four-lobe swirl pipes. Pure water with an axial velocity 2 m/s. Source: Jones and Ariyaratne [
Simply equating the area of the four-lobe duct to
I first consider a four-lobe swirl duct with constant pitch:diameter ratio of 8:1 simply connected in line after a cylindrical duct. The driving function for this is a positive step or Heaviside function in swirl gradient
The constant
Figure 7 illustrates the response of a system comprising a four-lobe Spanner-type duct with cross-sectional area equal to a cylindrical upstream main of diameter 50 mm carrying clean water at an axial velocity of 2 m/s. The ordinates are tangential velocities at a radius of 0.7
Response of tangential velocity in a Spanner-type swirl-inducing duct of diameter 50 mm carrying clean water at 2 m/s. Radial position is 0.7
The length of the wake (the point at which swirl has decayed by 95%) is 3
Note the apparent anomaly between the calculated constant
The example of a fixed-pitch duct is useful in that it gives a standard length for swirl pipe designs. However, a lobate swirl duct cannot be added directly to a cylindrical pipe without incurring wasteful pressure losses. A better solution is to allow the shape to develop in a sigmoidal fashion. A family of sigmoidal coefficients is given by
and illustrated in Figure 8.
Coefficients for the development of cross-section shape.
For a Spanner-type lobate duct, the sigmoidal function can be used to schedule the growth of lobe area, the expansion of the duct or, usually, the development of the radius of the lobe to its final value. In this case, the factors are
The exponent
Originally, a
Raylor [11] showed that advantages accrued from the gradual angular acceleration of twist in a profiled tube. In recent work, this has been combined with the asymmetric beta function to create a duct with developing cross-sections and acceleration of twist throughout the tube. Inserting the driving function for this case we obtain
where
Eq. (16) gives the complementary function as in the previous cases
The
Comparing coefficients we have the solution for the PI
Hence, the complete solution (PI + CF) is given by
Applying the boundary condition
So
Eq. (44) specifies the response of the solid body model to the ramped driving function in Eq. (39). A two-lobe design is illustrated in Table 2. The design is a modestly twisting tube but pressure losses are considerably larger than those expected in a smooth straight duct for the same duty (using the Darcy-Weisbach equation for this prediction). Increasing the amount of twist and increasing the number of lobes to four can improve the performance of the tube at the expense of increased pressure loss.
Design data sheet for a two-lobe swirl inducing duct (lobe radius
The purpose of this chapter has been to examine the technical aspects of swirling flows and to facilitate the design of ducts for specific purposes. Swirling flow is a complex, while stunningly beautiful, phenomenon and my work has been guided by the need to reduce its complexity for the designer. The emphasis has been on Spanner-type profiled tubes, but this is by no means the only way to generate swirl. The fascinating medical prospect that small amplitude helically coiled pipes might be used as bypass grafts to prevent occlusion by thrombosis has been the subject of scholarly study [14, 15].
The efficacy of the first-order solid body model was demonstrated by the simulation of flow through a 10.0-m cylindrical tube. The prediction that the downstream data taken after a distance of 3
As always, I am indebted to my research students Benjamin Raylor, Jeyakumar Ganeshalingam, Chanchala Ariyaratne and Ruth Tonkin for their tireless experimental and computational work in the early days. I am particularly indebted to Benjamin Raylor for his continued efforts to the present day, his enthusiasm for swirl ducts, his hard work and unfailing support.
The global population is predicted to reach 8.6 billion in 2030, 9.8 billion in 2050, and 11.2 billion in 2100 [1]. This expanding population and their subsequent consumption will lead to an increase in the global food demand, and it will be great challenge for food security under climate change and land-use scenarios. Exclusively, abiotic and biotic stresses caused by the global climate change progressively affected the cropping systems which will pose serious intimidations for global food production [2]. Most developed countries have had to embrace modern-day agricultural technologies to achieve food security for increasing populations, as well as to support agri-business and income generation. Currently, scientists have been propagating to explore crop diversification as an alternative strategy for developing countries. The ecological consequences of technologically focused agricultural systems that have been adopted and appreciated for many decades without the consideration of the environment, and the impact on the ecosystem is now coming into focus and scrutiny with the vivid and negative environmental impact of modern-day agriculture, and how it has greatly contributed to climate change. The current agricultural practices are not sustainable due to their misuse of valuable resources and environmental degradation. Hence, the philosophy of basic plant science research, and the direction of demand-based plant breeding should be changed to allow the plants for growing well in normal and limited resources in a sustainable way. In these reflections, it is suggested to grow soybean due to its higher adaptation and mitigation approaches in changing climates and multiplicity effects.
In history, soybean (
Soybean is one of the most valuable crops in the world due to its multiple uses as a least expensive source of protein, healthy unsaturated fats and carbohydrate for the human diet, livestock and aquaculture feed, and biofuel. It is predominantly grown worldwide for high-quality, inexpensive proteins, and oil. It is highly nutritious food commodity as a source of vegetable protein and low cholesterol at an affordable price and is considered as a good substitute for animal protein due to containing essential amino acids required for human nutrition. The approximate composition of soybean is 36% protein, 19% oil, 35% carbohydrate including 17% dietary fiber, 5% minerals, and several other components including vitamins [10]. Soybean oil contains 16% saturated fatty acids, 23% monounsaturated fatty acids, and 58% polyunsaturated fatty acids [11]. In addition to edible oil, soybean is used as many processed foodstuffs such as soybean sprouts, toasted soy protein flours, soy milk, tofu, tempeh, miso, natto, soybean paste, and soy sauce [12], and also, bean curd, oncom, tauco, soybean cake, ice cream, soy flour, etc. [13]. Soybeans are also an important food commodity after rice and maize. Soybean is by far the cheapest source of protein for the poor smallholders as compared to other quality foods that are rich in proteins such as animal meat, fish, eggs, and milk. Based on the protein quality (protein digestibility corrected amino acid score), the value of soybean protein is equivalent (whole soybeans 96, soybean milk 91) to eggs (97) [14]. Several bioactive compounds like isoflavones, peptides, flavonoids, phytic acid, soy lipids, soy phytoalexins, soyasaponins, lectins, hemagglutinin, soy toxins, and vitamins are isolated from soybean and soy food products [15]. It has been reported earlier in many studies that consumption of soybean in different forms provides bioactive compounds as well which significantly lowered the risks for several cancers including breast [16], prostate [17], lung [18], colon [19], liver [20], and bladder [21], hypercholesterolemia and cardiovascular diseases [22], osteoporosis [23], hypertension [24], and blood pressure [25]. The consumption of protein from soybean sources by human beings is currently low worldwide, although there is increasing public and commercial interest since the crop could be a major source of dietary protein for the future. Malnutrition is a major global health problem, especially for developing countries, and food insecurity is the prime factor for malnutrition [26]. However, soybean-based foods are cheaper and readily available which can solve the problems.
Soybean is not only a good source of high-quality edible oil and proteins for human beings but also a high-quality forage protein in animal feed worldwide. Feed is a key pillar in the journey of improving the productivity of livestock. Quality feed is the fundamental factor to increase the productivity of livestock. Soybean is also widely used as high quality and protein-rich animal feed [13] due to its auspicious attributes such as relatively high protein content, suitable amino acid profile except for methionine, and minimal variation in nutrient content. Soybean byproducts (raw materials and soybean meal) are used as a source of protein feedstuff for domestic animals including pig, chicken, cattle, horse, sheep, and fish feed and many prepackaged meals [10]. Soybean meal (SBM) contributes about 30% to poultry feeds [27]. It represents two-thirds of the total world output of protein feedstuffs [28]. Its feeding value is unparalleled by any other plant protein source [29]. SBM usually contains 47–49% crude protein (CP) and 3% crude fiber (CF) [30]. SBM is considered superior to other vegetable protein sources in terms of CP content and exceeds them in both total and digestible amino acid content [31]. The protein digestibility of SBM in poultry is approximately 85% [32]. Among the vegetable protein sources, SBM is used to meet the feed requirement of animals for limiting amino acids in cereal-based diets due to being the most cost-effective source of amino acids [33]. Therefore, the production of soybean, which is used extensively as animal feed, must be increased beyond the current production level due to meet the animal protein demand of overgrowing population in the world.
Nitrogen is a critical limiting element for growth and development by increasing chlorophyll as well as photosynthesis in crop plants. It is also the most abundant element in the atmosphere and exists in the diatomic form (N2) but the plant cannot uptake and use N2 directly. Only a group of plants known as legumes under the family of Fabaceae are well-known for being able to harvest N2 from the atmosphere and incorporated it into the soil which is termed biological nitrogen fixation (BNF). BNF is firstly discovered by Beijerinck in 1901 [34]. The conversion of atmospheric dinitrogen (N2) to ammonia (NH3) under the combined action of biological and chemical activities is known as BNF [35]. It is a chemical process by which molecular N2, with a strong triple covalent bond, in the air is converted into ammonia (NH3) or related nitrogenous compounds, typically in soil or aquatic systems [36]. It is an important microbially mediated process that converts N2 gas to NH3 using the nitrogenase protein complex [37]. Some bacteria contain enzymes that can reduce N2 and turn it into ammonia. Consequently, the NH3 is used to produce essential elements, and it is a process known as BNF [38, 39]. The BNF can be symbiotic (mutualistic associations between plant species and fixing microorganisms, mainly rhizobia), or asymbiotic (when transmitted by free-living fixing microorganisms, like the species of the genera Azotobacter and Beijerinckia) [40].
Soybean also improves soil fertility, another benefit of soybean cultivation, by fixing atmospheric nitrogen through BNF [41, 42]. Soybean plants can freely assimilate NH3 to produce nitrogenous biomolecules. These prokaryotes include aquatic organisms (cyanobacteria), free-living soil bacteria (
The fixation of atmospheric nitrogen is a complex process that requires a large input of energy to carry on [43]. For fixing nitrogen microorganisms require 16 moles of adenosine triphosphate (ATP) to reduce each mole of nitrogen [50]. Microorganisms obtain this energy by oxidizing organic molecules, such as non-photosynthetic free-living microorganisms obtain from other organisms, photosynthetic microorganisms (Cyanobacteria) obtain from sugars (photosynthetic product), and associative and symbiotic nitrogen-fixing microorganisms obtain from their host plants’ rhizospheres [50, 51]. The BNF process is affected by several factors [52] like abiotic stresses water deficit or excess water, salinity, temperature, heavy metals, and biocides [53], mineral elements such as high soil nitrate concentration [54], phosphorous [55] and sulfur [56, 57], acidity [58] and alkalinity [59], and biotic factors like ineffective rhizobia [60], plant diseases [61], and weeds [62]. At pH 7.0, we observed that there was low nitrogenase activity.
Crop rotation is an important agronomic management practice that is followed to sustain soil fertility and reduce pests and diseases. It also enhances to form some beneficial soil microbes with the following crops when the rotational crops are legumes specially soybean, which pointedly increased the growth and productivity of the crops. It has been well established that cultivation of soybean in 2- and 3-year rotations with corn and wheat in agriculture is highly profitable and advantageous for soil [63]. It has also been reported that soybean as a rotational crop is significantly cost-effective and beneficial to soil health [64, 65]. It has been established earlier that crop rotation recovers soil health and resilience by increasing soil organic carbon (SOC) [66, 67, 68], improving soil structure [69], enhancing nutrient availability [70], decreasing pests and pathogens in crops, increasing the population disease-defeating soil microbes [71, 72], and consequently increases yield of crops [73]. It is well documented that crop rotation as corn-soybean-wheat increased soybean yield in 1-year out of 3-year rotations as compared to growing every other year in corn-soybean rotations [74]. The high frequency of soybean in a crop rotation has decreased the SOC storage, and reduced macro aggregation owing to low residue inputs of soybean [75, 76, 77]. Soybean provided N through BNF as well as exploiting soil N from chemical sources [78, 79]. The soybean yield is meaningfully increased under rotations of corn-soybean in 2 years as compared to growing continuously [80, 81, 82]. Soybean in a 2-year rotations with corn increased grain yield by 9.2 and 12% over continuous soybean growing under no-tillage and conventional tillage conditions, respectively [80]. Rotation of soybean with traditional crops such as maize increases soil fertility by fixing nitrogen in the soil consequently increasing yield by 10–20% [83].
As compared to cereal crops, the residues of soybean contain a low C to N ratio, which promotes the decomposition of residues rapidly [76, 84]. However, accumulation and sequestration of C in a stable soil aggregate from soybean residues is lower over the corn and cereal residues, indicating a lower C to N ratio, and lower phenolic acid content of soybean residues [85, 86].
Corn-soybean rotation including winter wheat increased soybean yield over mono-cropping soybean due to higher infestation of pest predation and/or soil-borne plant pathogens as well as reduced SOC levels owing to lower aboveground and belowground biomass from continuous soybean cropping [64, 87]. The soybean yield is significantly increased with rotation as compared to continuous soybean due to increasing soil organic matter plus improving soil properties [88, 89], increasing the resource available for heterotrophic soil microbial communities, and increasing C and N cycling [89, 90]. Moreover, the strong rotational benefits were observed by Giller
Soil is a nonrenewable resource that may be degraded due to inappropriate management practices. Intercropping systems allow to enhance resource-use efficiency and crop productivity which promote multiple ecosystem services [93]. Integration of legume crops is fundamental in many intercropping systems [94], and legume-based cropping systems improve soil fertility in many ways, such as increasing SOC and humus content, N and P availability, etc. [95]. It has been documented earlier that grain legumes are weak suppressors of weeds, but the mixing of crop species in the same cropping system improves the ability of the crop to suppress weeds [96, 97]. Soybean is characterized as a major economic crop in smallholder farming systems due to sustaining soil fertility [42], providing feed for livestock, and improving rural household nutrition and income. Inoculation of
There are a number of the impact that grain legumes have on the environment and the soil in regards to quality. Meanwhile, the role of legumes like soybean to alleviate the negative effects caused by climate change has been rarely addressed. The emission of greenhouse gases (GHG) such as carbon dioxide (CO2) and nitrous oxide (N2O), methane (CH4), etc. are the causes of global warming. Legumes reduce the emission of GHG in agricultural systems by reducing mineral N fertilization, sequestration of carbon in soils, and the overall fossil energy inputs in the system [99].
N2O is much more active than CO2 which represents nearly 5–6% of the total atmospheric gases [100]. Around 60% N2O emission is occurred by agricultural practices which exemplify as the main source of emission [101], and the production of crops and animals are the main source of emission [102]. In crop production, the application of nitrogenous fertilizers is the birthplace of the majority of these emissions [101]. It has been estimated that about 1.0 kg of N is emitted as N2O from every 100 kg of N fertilizer [95]. The amount of N2O emission largely depends on several factors including N application rate, soil organic C content, soil pH, and texture [103, 104]. In most of cropping and pasture systems, de-nitrification is the leading source of N2O emission [104, 105, 106]. Several studies in recent years have been signified the role of legumes in the reduction of GHG emissions. For example, it has been reported that legumes discharge around 5–7 times less GHG per unit area compared with other crops [107]. Generally, the losses N2O from soils under legume crops are undoubtedly lower than those from both N2O fertilized in grasslands and non-legume crops [95]. Among legumes, soybean most efficiently produced and provided the maximum protein (g) per GHG emission out of 22 plant and animal protein sources [108]. Adoption of sustainable agricultural systems mitigate the emission of GHG such as conservation agriculture systems, which is suitable for the cultivation of both grain, and green-manure legumes lessen the emission of GHG.
Food and water security will be a major global issue focus in the coming decades due to climate change and population pressure. Malnutrition, predominantly protein deficiency, is prevalent in many parts of the world. Therefore, appropriate technology should be addressed by lawmakers and scientists for food security, and the cultivation of legumes majorly soybean is a first step to address the food security issues worldwide. Soybeans produce the highest amount of protein per hectare [109] and are well positioned to meet the need of future global protein. Conventional protein sources are highly expensive as well as a vulnerable population is unable to purchase from these sources. Hence, soybean-based protein foods are an important strategy to relieve malnutrition and hunger problems. Since it has been evidenced that smallholder farmers have limited capability to overcome crop production challenges due to changing climate [110]. They produce soybean for gaining higher yields, family demand, and net profits with minimum N fertilizer input which eventually improved their living standards as well as food security [111].
A sustainable agricultural system is the only way to sustainably intensify food crop production without causing damage to human and environmental health. Soybean and other nitrogen-fixing legumes should be a viable crop included in all forms of cropping systems as they can efficiently utilize atmospheric nitrogen through the process of BNF. The most important thing is the integration of soybean and another legume across different cropping systems which would effectively reduce the usage of chemical nitrogenous fertilizers, and conserve soil fertility. It is important to focus on the cultivation of crops that provides higher yield, economic return by maintaining soil health as well as environmental balances. Some priority areas seem to emerge, and these areas require deeper investigation to fully understand how the BNF dynamics, and how to utilize BNF in best way for sustainable agriculture. Thus, soybean crops should be grown to reduce hunger, malnutrition, and poverty as well as to bring food security by sustaining agriculture in light of climate and population challenges.
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Integrity - We are consistent and dependable, always striving for precision and accuracy in the true spirit of science.
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\n\nIntechOpen is a dynamic, vibrant company, where exceptional people are achieving great things. We offer a creative, dedicated, committed, and passionate environment but never lose sight of the fact that science and discovery is exciting and rewarding. We constantly strive to ensure that members of our community can work, travel, meet world-renowned researchers and grow their own career and develop their own experiences.
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Subba Tata",coverURL:"https://cdn.intechopen.com/books/images_new/7999.jpg",editedByType:"Edited by",editors:[{id:"187859",title:"Prof.",name:"Kusal",middleName:"K.",surname:"Das",slug:"kusal-das",fullName:"Kusal Das"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"6986",title:"Telomerase and non-Telomerase Mechanisms of Telomere Maintenance",subtitle:null,isOpenForSubmission:!1,hash:"79b7d4e97e1e0722f4ce1309a2088be3",slug:"telomerase-and-non-telomerase-mechanisms-of-telomere-maintenance",bookSignature:"Tammy A. Morrish",coverURL:"https://cdn.intechopen.com/books/images_new/6986.jpg",editedByType:"Edited by",editors:[{id:"275021",title:"Dr.",name:"Tammy A.",middleName:null,surname:"Morrish",slug:"tammy-a.-morrish",fullName:"Tammy A. 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Buchholz and Erik J. Behringer",coverURL:"https://cdn.intechopen.com/books/images_new/7264.jpg",editedByType:"Edited by",editors:[{id:"89438",title:"Dr.",name:"John N.",middleName:null,surname:"Buchholz",slug:"john-n.-buchholz",fullName:"John N. Buchholz"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}}],booksByTopicTotal:15,seriesByTopicCollection:[],seriesByTopicTotal:0,mostCitedChapters:[{id:"64565",doi:"10.5772/intechopen.81552",title:"Two-Dimensional (2D) and Three-Dimensional (3D) Cell Culturing in Drug Discovery",slug:"two-dimensional-2d-and-three-dimensional-3d-cell-culturing-in-drug-discovery",totalDownloads:3324,totalCrossrefCites:11,totalDimensionsCites:40,abstract:"Cell culture is an indispensable in vitro tool used to improve our perception and understanding of cell biology, the development of tissue engineering, tissue morphology, mechanisms of diseases and drug action. Efficient cell culturing techniques both in vitro and in vivo allow researchers to design and develop new drugs in preclinical studies. Two-dimensional (2D) cell cultures have been used since 1900s and are still a dominant method in many biological studies. However, 2D cell cultures poorly imitate the conditions in vivo. Recently three-dimensional (3D) cell cultures have received remarkable attention in studies such as drug discovery and development. Optimization of cell culture conditions is very critical in ensuring powerful experimental reproducibility, which may help to find new therapies for cancer and other diseases. In this chapter, we discuss the 2D and 3D cell culture technologies and their role in drug discovery.",book:{id:"6964",slug:"cell-culture",title:"Cell Culture",fullTitle:"Cell Culture"},signatures:"Jitcy Saji Joseph, Sibusiso Tebogo Malindisa and Monde Ntwasa",authors:null},{id:"68141",doi:"10.5772/intechopen.87778",title:"Nonenzymatic Exogenous and Endogenous Antioxidants",slug:"nonenzymatic-exogenous-and-endogenous-antioxidants",totalDownloads:1920,totalCrossrefCites:17,totalDimensionsCites:30,abstract:"Nonenzymatic exogenous and endogenous antioxidants play an important role in human health and act as preservatives for cosmetics, pharmaceuticals, and food products. This chapter will discuss the chemical structure and mechanism of action of the most important nonenzymatic small exogenous and endogenous organic molecules that act as antioxidants. The chapter will focus on the structural features, functional groups, properties, biosynthetic origin, and mechanism of action of such antioxidants. It also covers damages that free radicals create and the mechanisms by which they are neutralized by the various antioxidants. The scope of this chapter will be limited to nonenzymatic exogenous and endogenous antioxidants since enzymatic antioxidants have been discussed extensively in several reviews.",book:{id:"7999",slug:"free-radical-medicine-and-biology",title:"Free Radical Medicine and Biology",fullTitle:"Free Radical Medicine and Biology"},signatures:"Ziad Moussa, Zaher M.A. Judeh and Saleh A. Ahmed",authors:[{id:"300774",title:"Dr.",name:"Ziad",middleName:null,surname:"Moussa",slug:"ziad-moussa",fullName:"Ziad Moussa"},{id:"306324",title:"Dr.",name:"Zaher",middleName:null,surname:"M. A. Judeh",slug:"zaher-m.-a.-judeh",fullName:"Zaher M. A. Judeh"},{id:"306325",title:"Prof.",name:"Saleh",middleName:null,surname:"A. Ahmed",slug:"saleh-a.-ahmed",fullName:"Saleh A. Ahmed"}]},{id:"62562",doi:"10.5772/intechopen.79502",title:"Keratin Waste: The Biodegradable Polymers",slug:"keratin-waste-the-biodegradable-polymers",totalDownloads:2288,totalCrossrefCites:9,totalDimensionsCites:16,abstract:"Keratins are everywhere, from being the major components of household dust to common contaminants of laboratory protein analysis. Keratin is the major structural fibrous protein belonging to the large family of structural proteins to form hair, wool, feathers, nails, and horns of many kinds of animals and has a high concentration of cysteine, 7–20% of the total amino acid residues, that form inter- and intramolecular disulfide bonds. Keratin wastes are considered as the environmental pollutants and produced mostly from the poultry farms, slaughterhouses, and leather industries. Keratin wastes are dumped, buried, used for landfilling, or incinerated and all these actions increase the threats of environmental hazards, pollution, negatively influence the public health, and increase greenhouse gases concentration. Nature has provided planet Earth with a variety of beneficial organisms. Soil is considered as a well-known source for the growth of keratinophilic microflora (fungi and bacteria), which have the capability to degrade the keratin waste. The keratin-degradation ability of keratinophilic microflora has been credited with the production of the microbial keratinase enzyme and biodegradation takes place (enzymatic degradation). So, the keratin wastes are the biodegradable polymers. Keratinase is the industrially significant enzyme that offers bioconversion of keratin waste, utilization as animal feed supplements, and dehairing agents in tannery industries and textile industries.",book:{id:"6820",slug:"keratin",title:"Keratin",fullTitle:"Keratin"},signatures:"Tarun Kumar Kumawat, Anima Sharma, Vishnu Sharma and\nSubhash Chandra",authors:[{id:"250905",title:"Dr.",name:"Anima",middleName:null,surname:"Sharma",slug:"anima-sharma",fullName:"Anima Sharma"},{id:"257932",title:"Dr.",name:"Tarun Kumar",middleName:null,surname:"Kumawat",slug:"tarun-kumar-kumawat",fullName:"Tarun Kumar Kumawat"},{id:"257942",title:"Dr.",name:"Vishnu",middleName:null,surname:"Sharma",slug:"vishnu-sharma",fullName:"Vishnu Sharma"},{id:"257944",title:"Prof.",name:"Subhash",middleName:null,surname:"Chandra",slug:"subhash-chandra",fullName:"Subhash Chandra"}]},{id:"62159",doi:"10.5772/intechopen.79050",title:"Keratins in Skin Epidermal Development and Diseases",slug:"keratins-in-skin-epidermal-development-and-diseases",totalDownloads:2435,totalCrossrefCites:5,totalDimensionsCites:13,abstract:"Epidermal keratinocyte (KC), the major cell type in the skin epidermis, plays critical roles in forming a permeability barrier to separate internal organs from external stimuli. Keratins, constituting about 30–80% of the total protein in KCs, form the major intermediate filament cytoskeleton of KC. Keratins consist of 54 unique genes in humans and they are expressed in cell-, differentiation- and development-dependent manner. While keratin pairs K5-K14 and K1-K10 are normally associated with KCs at different cell differentiation stages, other keratin pairs such as K6-K16/K17 and K8–K18 and are usually not expressed in normal skin interfollicular epidermis, but are elevated during wounding, inflammatory skin diseases such as psoriasis or malignant conversion of KC. The expression and function of keratins are tightly regulated at both transcriptional and post-transcriptional levels. Inherited or spontaneous mutations in keratins or abnormal keratin regulations or modifications can cause KC and cutaneous tissue fragility, skin hypertrophic and inflammatory conditions or malignant transformation of KC, therefore accounting for a large number of disorders in human skin. Here we review the recent literature on how keratins are normally expressed during skin development and how mutations or misregulations of these keratins are involved in the pathogenesis of skin diseases.",book:{id:"6820",slug:"keratin",title:"Keratin",fullTitle:"Keratin"},signatures:"Ling-juan Zhang",authors:[{id:"241614",title:"Dr.",name:"Lingjuan",middleName:null,surname:"Zhang",slug:"lingjuan-zhang",fullName:"Lingjuan Zhang"}]},{id:"63131",doi:"10.5772/intechopen.80051",title:"Keratinaceous Wastes and Their Valorization through Keratinolytic Microorganisms",slug:"keratinaceous-wastes-and-their-valorization-through-keratinolytic-microorganisms",totalDownloads:1455,totalCrossrefCites:4,totalDimensionsCites:10,abstract:"Keratin is a fibrous protein mainly found in higher vertebrates such as mammals, birds, and reptiles. It is also a major constituent of human epithelial tissues. Major keratinaceous wastes include skin, hair, wool, feather, horns, hooves, and nails. Large amounts of such wastes are generated from meat industry, poultry houses, and wool industry etc. Though keratinous wastes contain about 90% protein, keratin is usually recalcitrant to normal proteases. Such wastes have been traditionally digested using physico-chemical methods. But such techniques are energy-intensive and technologically demanding. Also, such approaches lead to degradation of certain amino acids such as lysine. In nature, keratinaceous wastes don’t accumulate indicating that keratinolytic microorganisms exist in nature. Keratinase producing strains are distributed among bacteria, fungi, and actinobacteria etc. Hence, potent keratinolytic microbes and their enzymes may be used for valorization of keratinous wastes. Efficient degradation of such wastes may generate value-added products such as feed additives, agricultural biofertilizers, and cosmetics. This chapter will give a comprehensive overview of types of keratinaceous wastes, kinds of keratinolytic microbes and keratinases, and valorization of such wastes using keratinase producing strains and/or keratinases.",book:{id:"6820",slug:"keratin",title:"Keratin",fullTitle:"Keratin"},signatures:"Debananda Singh Ningthoujam, Keishing Tamreihao, Saikat\nMukherjee, Rakhi Khunjamayum, Laishram Jaya Devi and Roshan\nSingh Asem",authors:[{id:"224389",title:"Dr.",name:"K",middleName:null,surname:"Tamreihao",slug:"k-tamreihao",fullName:"K Tamreihao"},{id:"242319",title:"Prof.",name:"Debananda",middleName:null,surname:"Ningthoujam",slug:"debananda-ningthoujam",fullName:"Debananda Ningthoujam"},{id:"262045",title:"Dr.",name:"Saikat",middleName:null,surname:"Mukherjee",slug:"saikat-mukherjee",fullName:"Saikat Mukherjee"},{id:"262046",title:"Ms.",name:"Rakhi",middleName:null,surname:"Khunjamayum",slug:"rakhi-khunjamayum",fullName:"Rakhi Khunjamayum"},{id:"262076",title:"Ms.",name:"Laishram",middleName:null,surname:"Jaya Devi",slug:"laishram-jaya-devi",fullName:"Laishram Jaya Devi"},{id:"262077",title:"Mr.",name:"Roshan Singh",middleName:null,surname:"Asem",slug:"roshan-singh-asem",fullName:"Roshan Singh Asem"}]}],mostDownloadedChaptersLast30Days:[{id:"67793",title:"Kinetic Studies on Cell Growth",slug:"kinetic-studies-on-cell-growth",totalDownloads:3810,totalCrossrefCites:3,totalDimensionsCites:8,abstract:"The kinetic model of cell growth is substantially capable to predict product formation. Mathematical models provide a strategy for solving problems encountered in fermentation process. A biochemical engineering approach to address this problem could be to develop a mathematical model which not only helps in the understanding of the system but also predicts various cultivation strategies to facilitate the optimization of a fermentation process, saving much of the time and cost for performing experiments. The presented overview indicates that many of the environmentally relevant aspects in growth kinetics are still waiting to be discovered, established, and exploited. A kinetic model that describes microbial growth, product formation and substrate consumption and the experimental data were fitted with modified logistic equation.",book:{id:"7121",slug:"cell-growth",title:"Cell Growth",fullTitle:"Cell Growth"},signatures:"Punniavan Sakthiselvan, Setti Sudharsan Meenambiga and Ramasamy Madhumathi",authors:[{id:"268626",title:"Dr.",name:"Punniavan",middleName:null,surname:"Sakthiselvan",slug:"punniavan-sakthiselvan",fullName:"Punniavan Sakthiselvan"},{id:"269591",title:"Dr.",name:"Madhumathi",middleName:null,surname:"Ramasamy",slug:"madhumathi-ramasamy",fullName:"Madhumathi Ramasamy"},{id:"279920",title:"Dr.",name:"S S",middleName:null,surname:"Meenambiga",slug:"s-s-meenambiga",fullName:"S S Meenambiga"}]},{id:"69690",title:"Ion Homeostasis Response to Nutrient-Deficiency Stress in Plants",slug:"ion-homeostasis-response-to-nutrient-deficiency-stress-in-plants",totalDownloads:2552,totalCrossrefCites:3,totalDimensionsCites:6,abstract:"A crucial feature of plant performance is its strong dependence on the availability of essential mineral nutrients, affecting multiple vital functions. Indeed, mineral-nutrient deficiency is one of the major stress factors affecting plant growth and development. Thereby, nitrogen and potassium represent the most abundant mineral contributors, critical for plant survival. While studying plant responses to nutrient deficiency, one should keep in mind that mineral nutrients, along with their specific metabolic roles, are directly involved in maintaining cell ion homeostasis, which relies on a finely tuned equilibrium between cytosolic and vacuolar ion pools. Therefore, in this chapter we briefly summarize the role of the ion homeostasis system in cell responses to environmental deficiency of nitrate and potassium ions. Special attention is paid to the implementation of plant responses via NO3− and K+ root transport and regulation of ion distribution in cell compartments. These responses are strongly dependent on plant species, as well as severity and duration of nutrient deficiency.",book:{id:"7121",slug:"cell-growth",title:"Cell Growth",fullTitle:"Cell Growth"},signatures:"Natalia Osmolovskaya, Julia Shumilina, Ksenia Bureiko, Veronika Chantseva, Tatiana Bilova, Ludmila Kuchaeva, Nikolai Laman, Ludger A. Wessjohann and Andrej Frolov",authors:[{id:"177609",title:"Dr.",name:"Natalia",middleName:null,surname:"Osmolovskaya",slug:"natalia-osmolovskaya",fullName:"Natalia Osmolovskaya"},{id:"309520",title:"Ms.",name:"Julia",middleName:null,surname:"Shumilina",slug:"julia-shumilina",fullName:"Julia Shumilina"},{id:"309521",title:"Ms.",name:"Ksenia",middleName:null,surname:"Bureiko",slug:"ksenia-bureiko",fullName:"Ksenia Bureiko"},{id:"309522",title:"Ms.",name:"Veronika",middleName:null,surname:"Chantseva",slug:"veronika-chantseva",fullName:"Veronika Chantseva"},{id:"309523",title:"Dr.",name:"Tatiana",middleName:null,surname:"Bilova",slug:"tatiana-bilova",fullName:"Tatiana Bilova"},{id:"309524",title:"Mrs.",name:"Ludmila",middleName:null,surname:"Kuchaeva",slug:"ludmila-kuchaeva",fullName:"Ludmila Kuchaeva"},{id:"309525",title:"Prof.",name:"Ludger A.",middleName:null,surname:"Wessjohann",slug:"ludger-a.-wessjohann",fullName:"Ludger A. Wessjohann"},{id:"309526",title:"Dr.",name:"Andrej",middleName:null,surname:"Frolov",slug:"andrej-frolov",fullName:"Andrej Frolov"}]},{id:"62159",title:"Keratins in Skin Epidermal Development and Diseases",slug:"keratins-in-skin-epidermal-development-and-diseases",totalDownloads:2435,totalCrossrefCites:5,totalDimensionsCites:13,abstract:"Epidermal keratinocyte (KC), the major cell type in the skin epidermis, plays critical roles in forming a permeability barrier to separate internal organs from external stimuli. Keratins, constituting about 30–80% of the total protein in KCs, form the major intermediate filament cytoskeleton of KC. Keratins consist of 54 unique genes in humans and they are expressed in cell-, differentiation- and development-dependent manner. While keratin pairs K5-K14 and K1-K10 are normally associated with KCs at different cell differentiation stages, other keratin pairs such as K6-K16/K17 and K8–K18 and are usually not expressed in normal skin interfollicular epidermis, but are elevated during wounding, inflammatory skin diseases such as psoriasis or malignant conversion of KC. The expression and function of keratins are tightly regulated at both transcriptional and post-transcriptional levels. Inherited or spontaneous mutations in keratins or abnormal keratin regulations or modifications can cause KC and cutaneous tissue fragility, skin hypertrophic and inflammatory conditions or malignant transformation of KC, therefore accounting for a large number of disorders in human skin. Here we review the recent literature on how keratins are normally expressed during skin development and how mutations or misregulations of these keratins are involved in the pathogenesis of skin diseases.",book:{id:"6820",slug:"keratin",title:"Keratin",fullTitle:"Keratin"},signatures:"Ling-juan Zhang",authors:[{id:"241614",title:"Dr.",name:"Lingjuan",middleName:null,surname:"Zhang",slug:"lingjuan-zhang",fullName:"Lingjuan Zhang"}]},{id:"62187",title:"Calcium and Cell Response to Heavy Metals: Can Yeast Provide an Answer?",slug:"calcium-and-cell-response-to-heavy-metals-can-yeast-provide-an-answer-",totalDownloads:1263,totalCrossrefCites:2,totalDimensionsCites:3,abstract:"Despite constant efforts to maintain a clean environment, heavy metal pollution continues to raise challenges to the industrialized world. Exposure to heavy metals is detrimental to living organisms, and it is of utmost importance that cells find rapid and efficient ways to respond to and eventually adapt to surplus metals for survival under severe stress. This chapter focuses on the attempts done so far to elucidate the calcium-mediated response to heavy metal stress using the model organism Saccharomyces cerevisiae. The possibilities to record the transient elevations of calcium within yeast cells concomitantly with the heavy metal exposure are presented, and the limitations imposed by interference between calcium and heavy metals are discussed.",book:{id:"7264",slug:"calcium-and-signal-transduction",title:"Calcium and Signal Transduction",fullTitle:"Calcium and Signal Transduction"},signatures:"Ileana Cornelia Farcasanu, Claudia Valentina Popa and Lavinia\nLiliana Ruta",authors:[{id:"203734",title:"Dr.",name:"Ileana",middleName:"Cornelia",surname:"Farcasanu",slug:"ileana-farcasanu",fullName:"Ileana Farcasanu"},{id:"203865",title:"Dr.",name:"Lavinia",middleName:null,surname:"Ruta",slug:"lavinia-ruta",fullName:"Lavinia Ruta"},{id:"255728",title:"Dr.",name:"Claudia Valentina",middleName:null,surname:"Popa",slug:"claudia-valentina-popa",fullName:"Claudia Valentina Popa"}]},{id:"61953",title:"L-Type Calcium Channels: Structure and Functions",slug:"l-type-calcium-channels-structure-and-functions",totalDownloads:2776,totalCrossrefCites:4,totalDimensionsCites:7,abstract:"Voltage-gated calcium channels (VGCCs) manage the electrical signaling of cells by allowing the selective-diffusion of calcium ions in response to the changes in the cellular membrane potential. Among the different VGCCs, the long-lasting or the L-type calcium channels (LTCCs) are prevalently expressed in a variety of cells, such as skeletal muscle, ventricular myocytes, smooth muscles and dendritic cells and forms the largest family of the VGCCs. Their wide expression pattern and significant role in diverse cellular events, including neurotransmission, cell cycle, muscular contraction, cardiac action potential and gene expression, has made these channels the major targets for drug development. In this book chapter, we aim to provide a comprehensive overview of the different VGCCs and focus on the sequence-structure–function properties of the LTCCs. Our chapter will summarize and review the various experimental and computational analyses performed on the structures of the LTCCs and their implications in drug discovery applications.",book:{id:"6683",slug:"ion-channels-in-health-and-sickness",title:"Ion Channels in Health and Sickness",fullTitle:"Ion Channels in Health and Sickness"},signatures:"Tianhua Feng, Subha Kalyaanamoorthy and Khaled Barakat",authors:[{id:"57391",title:"Dr.",name:"Khaled",middleName:"Hasaan",surname:"Barakat",slug:"khaled-barakat",fullName:"Khaled Barakat"},{id:"236912",title:"B.Sc.",name:"Tianhua",middleName:null,surname:"Feng",slug:"tianhua-feng",fullName:"Tianhua Feng"},{id:"236999",title:"Dr.",name:"Subha",middleName:null,surname:"Kalyaanamoorthy",slug:"subha-kalyaanamoorthy",fullName:"Subha Kalyaanamoorthy"}]}],onlineFirstChaptersFilter:{topicId:"47",limit:6,offset:0},onlineFirstChaptersCollection:[],onlineFirstChaptersTotal:0},preDownload:{success:null,errors:{}},subscriptionForm:{success:null,errors:{}},aboutIntechopen:{},privacyPolicy:{},peerReviewing:{},howOpenAccessPublishingWithIntechopenWorks:{},sponsorshipBooks:{sponsorshipBooks:[],offset:8,limit:8,total:0},allSeries:{pteSeriesList:[{id:"14",title:"Artificial Intelligence",numberOfPublishedBooks:9,numberOfPublishedChapters:89,numberOfOpenTopics:6,numberOfUpcomingTopics:0,issn:"2633-1403",doi:"10.5772/intechopen.79920",isOpenForSubmission:!0},{id:"7",title:"Biomedical Engineering",numberOfPublishedBooks:12,numberOfPublishedChapters:104,numberOfOpenTopics:3,numberOfUpcomingTopics:0,issn:"2631-5343",doi:"10.5772/intechopen.71985",isOpenForSubmission:!0}],lsSeriesList:[{id:"11",title:"Biochemistry",numberOfPublishedBooks:31,numberOfPublishedChapters:314,numberOfOpenTopics:4,numberOfUpcomingTopics:0,issn:"2632-0983",doi:"10.5772/intechopen.72877",isOpenForSubmission:!0},{id:"25",title:"Environmental Sciences",numberOfPublishedBooks:1,numberOfPublishedChapters:11,numberOfOpenTopics:4,numberOfUpcomingTopics:0,issn:"2754-6713",doi:"10.5772/intechopen.100362",isOpenForSubmission:!0},{id:"10",title:"Physiology",numberOfPublishedBooks:11,numberOfPublishedChapters:141,numberOfOpenTopics:4,numberOfUpcomingTopics:0,issn:"2631-8261",doi:"10.5772/intechopen.72796",isOpenForSubmission:!0}],hsSeriesList:[{id:"3",title:"Dentistry",numberOfPublishedBooks:8,numberOfPublishedChapters:129,numberOfOpenTopics:2,numberOfUpcomingTopics:0,issn:"2631-6218",doi:"10.5772/intechopen.71199",isOpenForSubmission:!0},{id:"6",title:"Infectious Diseases",numberOfPublishedBooks:13,numberOfPublishedChapters:113,numberOfOpenTopics:3,numberOfUpcomingTopics:1,issn:"2631-6188",doi:"10.5772/intechopen.71852",isOpenForSubmission:!0},{id:"13",title:"Veterinary Medicine and Science",numberOfPublishedBooks:11,numberOfPublishedChapters:105,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:18,numberOfOpenTopics:2,numberOfUpcomingTopics:1,issn:"2753-894X",doi:"10.5772/intechopen.100359",isOpenForSubmission:!0},{id:"23",title:"Education and Human Development",numberOfPublishedBooks:0,numberOfPublishedChapters:5,numberOfOpenTopics:1,numberOfUpcomingTopics:1,issn:null,doi:"10.5772/intechopen.100360",isOpenForSubmission:!0},{id:"24",title:"Sustainable Development",numberOfPublishedBooks:0,numberOfPublishedChapters:14,numberOfOpenTopics:5,numberOfUpcomingTopics:0,issn:null,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:"June 11th, 2022",hasOnlineFirst:!0,numberOfPublishedBooks:9,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:19,paginationItems:[{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:6,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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\r\n\tThe environment is subject to severe anthropic effects. Among them are those associated with pollution, resource extraction and overexploitation, loss of biodiversity, soil degradation, disorderly land occupation and planning, and many others. These anthropic effects could potentially be caused by any inadequate management of the environment. However, ecosystems have a resilience that makes them react to disturbances which mitigate the negative effects. It is critical to understand how ecosystems, natural and anthropized, including urban environments, respond to actions that have a negative influence and how they are managed. It is also important to establish when the limits marked by the resilience and the breaking point are achieved and when no return is possible. The main focus for the chapters is to cover the subjects such as understanding how the environment resilience works, the mechanisms involved, and how to manage them in order to improve our interactions with the environment and promote the use of adequate management practices such as those outlined in the United Nations’ Sustainable Development Goals.
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