The results of molecular docking simulation.
\r\n\tWithin this scenario, special attention needs to be devoted to financial implications, due to their pervasiveness. Nobody would question the key role that finance plays to complement the real sphere of the economy and that has increasingly attracted both academics and practitioners. As a result, traditional pillars – such as financial markets, products, and institutions – have evolved significantly, with financial innovation fueling further progress over time. The global side of the coin features – among others – financially connected markets, international financial exchanges, and financial conglomerates that provide valuable opportunities in terms of international corporate finance. On the other side, recent advances have involved a wider recourse to ESG factors, allowed forward steps towards a more inclusive financial system, and have made digital finance a must, rather than an option, even though much remains to be accomplished, for instance, to facilitate access to formal financial channels in many underdeveloped regions.
\r\n\r\n\t
\r\n\tThis book aims to examine emerging trends, new perspectives, and empirical applications that deal with globalization and sustainability. The goal is to provide a comprehensive overview of these important concepts as valuable support to successfully meet the challenges and take on the opportunities ahead. At the same time, drawing upon empirical evidence can contribute to bridging the gap between theory and practice, which also fits within the scope of this book.
Ebola, previously known as Ebola virus disease, is an acute viral infection causing hemorrhagic fever marked by high mortality rate in human and nonhuman primates [1]. It is a zoonotic disease transmitted by direct contact with mucosal tissue or bodily fluids (blood, feces, and other secreted fluids) of the infected living or dead human and animal [2, 3, 4]. The animal reservoir for this disease is still unknown. Fruit bat (
Ebola is an enveloped, nonsegmented, negative-sense, single-stranded RNA virus which belongs to
The Ebola virus genomic RNA is consisted of around 19,000 nucleotides [14]. It encodes seven structural protein, namely, nucleoprotein (NP), glycoprotein (GP), RNA-dependent RNA polymerase (L), matrix protein (VP40), and three nucleocapsid proteins (VP24, VP30, and VP35) [15, 16]. It also encodes one nonstructural protein, the secretory glycoprotein (sGP) [17]. The genome is linearly arranged as follows: 3′-leader-NP-VP35-VP40-GP/sGP-VP30-VP24-L-trailer-5′ [14, 17, 18].
The seven structural proteins and one nonstructural protein have an imperative role in Ebola virus life cycle [16]. NP: viral replication and scaffold for additional viral proteins. GP: binds to receptors on the cell surface and membrane fusion, pathogenicity. sGP: inhibits neutrophil function and adsorbs neutralizing antibodies. L: synthesis of positive-sense RNA. VP40: viral assembly and budding, structural integrity of viral particles, and maturation of the virion. VP24: nucleocapsid formation, encapsulates and shields viral genome from nucleases, viral replication. VP30: viral transcription activator. VP35: multi-virulence functionality, innate immune antagonist, and an RNAi silencing suppressor [16, 17].
The patient who suffers from Ebola shows no symptoms during the initial infection. After the incubation for about 4–10 days, the general symptoms such as fever, myalgia, and malaise and sometimes accompanied by chills appear. These symptoms often confused with dengue or malaria in tropical climates [3, 19]. As the infection progresses, the patient shows flu-like symptoms accompanied by gastrointestinal symptoms. In severe cases, Ebola developed into a conjunctival hemorrhage, epistaxis, melena, hematemesis, coagulation abnormalities, and a range of hematological irregularities. The neurological symptoms such as encephalopathy, convulsions, and delirium may also occur during the late stage of the infection [19, 20]. The patient dies around 6–9 weeks after the symptoms appear [21]. With the nonspecific symptoms, severe morbidity, and high mortality rate, the World Health Organization (WHO) has acknowledged Ebola as one of the most malignant diseases in the world [22].
The first recorded Ebola outbreak emerged in Sudan between June and November 1976. It mainly affected Nzara, Maridi, Tembura, and Juba where 150 of 284 victims died (the mortality rate of 53%) [2, 23]. After the first outbreak, 19 other outbreaks have occurred in Africa with the mean fatality rate of 65.4% [11].
The last and the most extensive Ebola outbreak was announced by the WHO on March 23, 2014. This outbreak appears to have emerged in the Guéckédou district of the southeast region of Republic of Guinea [24, 25, 26]. The WHO announced the epidemic to be a Public Health Emergency of International Concern (PHEIC) on August 8, 2014, due to the severe consequences if Ebola ever spread around the globe. PHEIC was disclosed because of the weak health services of Guinea, Liberia, Sierra Leone, and other neighboring countries at risk in combating Ebola and the continuing transmission with a high fatality rate of Ebola in West Africa [26]. When the outbreak ends in March 2016, Ebola has claimed 1310 lives out of 28,616 reported cases [27, 28]. Even though the damage caused by the last outbreak of Ebola is calamitous, there is still no FDA-approved antiviral drug to treat this disease.
Ebola is considered as one of the neglected tropical diseases because the outbreaks take place in the poor populations with limited resources, mostly in West Africa [29]. The research and drug development for Ebola have been neglected for decades because the drug developers regard it as a commercially unattractive project to invest their resource. The negligence occurs to all tropical diseases by only 13 out of 1393 new approved drugs between 1975 and 1999 that were indicated for tropical disease [30]. However, the frequent outbreaks in the last decade and the massive outbreak which was occurred in 2014 have drawn much attention to drug development for Ebola [16]. Without available treatment or vaccine, paramedic only relied on palliative care for the infected patients and barrier methods to prevent the transmission [31]. Hence, the researchers investigating ways for helping people just infected with Ebola (treatment) and preventing people to get infected when exposed to Ebola (vaccine) [32].
The conventional medical treatment for Ebola is a supportive care with intravenous fluids or oral rehydration with electrolyte solutions. The reason being that the virus interferes with blood clotting and disrupts electrolyte balance. Thus, such intervention can help to keep up the condition of the patient. However, such intervention is not enough for severely ill patients to sustain and recover [21, 32].
Zmapp, a combined humanized monoclonal antibody, was tested as a passive immunotherapy against Ebola. The preclinical test was conducted by Mapp Biopharmaceutical. This monoclonal antibody shows 100% efficacy in preventing lethal disease on cynomolgus macaques when treatment is initiated up to 5 days postinfection of EBOV [31].
Other experimental therapies developed a novel synthetic adenosine analog, BCX4430. This compound shows in vitro and in vivo activity by inhibiting viral RNA polymerase function, acting as a non-obligate RNA chain terminator. BCX4430 protects both mice and guinea pig models from a severe infection of Ebola virus and Marburg virus. In addition, this compound completely protects cynomolgus macaques from Marburg virus infection if administered as late as 48 h after infection [33].
Not only does the research focus on the development of a novel drug, but the research is also conducted to identify potential repurposed therapeutic agents for the treatment of Ebola [34, 35]. Toremifene and clomiphene, the selective estrogen reuptake modulators, are currently known as the drug to treat breast cancer and infertility, respectively. Both drugs inhibit Ebola virus entry into the cell by preventing the late stage membrane fusion. These drugs show an inhibition activity by more than 90% in vitro. Higher dose than the standard clinical range is needed to achieve the therapeutic effect on Ebola. However, a higher dose would increase the risk of serious side effect of toremifene and clomiphene, which are electrolyte derangements and ocular adverse effect, respectively [36].
Other experiments screen amiodarone, a multichannel ion blocker; sertraline, selective serotonin reuptake inhibitor; and bepridil, a calcium channel blocker as a repurposed therapeutic agent targeting Ebola. Amiodarone works by the induction of Niemann-Pick C-like phenotype that inhibits late endosomal entry of Ebola virus [37]. Sertraline and bepridil work in a similar fashion to amiodarone. Both drugs show inhibition activity in an in vitro test by more than 90% [35].
Several vaccines have also been developed to prevent the Ebola. ChAd3-ZEBOV, which has developed by GlaxoSmithKline in collaboration with the US National Institute of Allergy and Infectious Diseases, is a chimpanzee-derived adenovirus vector with an Ebola virus gene inserted. This vaccine induced uniform protection against acute lethal Ebola virus in cynomolgus macaques. However, the protection of this vaccine declines over several months [38].
The other vaccine, which is developed by the Public Health Agency of Canada in Winnipeg, is rVSV-ZEBOV. It uses an attenuated vesicular stomatitis virus which has been genetically modified to express glycoprotein of Ebola virus. The rVSV-ZEBOV has undergone a ring vaccination phase 3 efficacy trial which assesses the protective activity of rVSV-ZEBOV against Ebola virus in human beings. The result shows that rVSV-ZEBOV offers substantial protection against Ebola virus infection. Both randomized and a non-randomized clusters of vaccinated individuals show no disease development from the challenge performed 10 days postvaccination [39].
The Center for Disease Control and Prevention considered Ebola virus as a tier 1 select agent because it possesses a considerable risk of intentional misuse with a severe threat to public health and safety [40]. Researchers need to fill the APHIS/CDC Form 1 in order to register for possession, use, and transfer of Ebola virus. All requirements including the availability of Biosafety Level (BSL) 4 laboratory and certified personnel are needed to get access to Ebola virus sample [41]. Thus, to get a suitable sample, researchers tend to move their experiments on the genetically modified virus that can express part of known Ebola virus genome because it is not subjected to select agent [42].
Genomic and proteomic data of Ebola virus has been collected each time the outbreak occurred and stored in the open source database. Also, the Ebola virus protein interaction with the corresponding drug lead through in vitro test has also been increased in the past decades. To date, the protein three-dimensional (3D) structure of Ebola virus NP, VP35, VP40, GP, VP30, and VP24 has been available in Protein Databank (PDB). In addition, the active site residues of each protein have also been identified, except for NP. L is the only Ebola virus protein with unavailable 3D structure and unidentified active site [16]. Thus, researchers use a bioinformatics approach to utilize the readily available genomic and proteomic data to research drug design and discovery.
Computer-aided drug discovery and development (CADDD) is employed to accelerate hit identification, hit-to-lead selection, enhance absorption, distribution, metabolism, excretion, and toxicity (ADMET) profile and avoid another safety issue [43]. This approach is currently growing and adapted quickly by pharmaceutical industry and academia because it reduces the time and cost of drug research [44, 45]. Currently, 16 compounds (Aliskiren, Boceprevir, Captopril, Dorzolamide, Indinavir, LY-517717, Nolatrexed, NVP-AUY922, Oseltamivir, Raltegravir, Ritonavir, Rupintrivir, Saquinavir, TMI-005, Tirofiban, and Zanamivir) are in clinical trial or have been approved for therapeutic use. These compounds are the examples of successful application of CADDD [46, 47]. Through CADDD, the hit rate of the novel and repurposed drug for Ebola therapy could be improved.
A consistently effective treatment for Ebola is currently not yet available. Present therapeutic options are directed at palliative and supportive care to maintain and prolong the patient life. The majority of treatment, novel or repurposed drug, have been developed, but none of them are entirely satisfactory. In attempts to find a drug in the treatment of Ebola, inhibitors targeting EBOV VP35 have received little attention even though it has a critical function in host immune evasion and viral RNA synthesis. Our objective is to find the optimal in silico Ebola therapeutic agents which later will be implemented in the wet laboratory.
In this chapter, we will discuss the result of our in silico approach against EBOV VP35, one of the viral protein of EBOV which is responsible for the viral RNA synthesis and as the RNAi silencing suppressor agents [48, 49]. Moreover, this protein was also being studied by Brown et al. in 2014, which discovered the actual pose of their selected inhibitors against the EBOV VP35 in their perspective binding site and also deposited their work in RCSB Protein Databank (PDB) through several PDB IDs [50]. Thus, their proteins can be used as the template for pharmacophore mapping model for our docking simulation approach. Moreover, we also deployed the Indonesian natural product compounds for virtual screening purpose to find the suitable lead compounds for combating Ebola. The reason for choosing the Indonesian natural product compounds because of Indonesia, as one of the largest megadiversity countries, has no less than 38,000 flowering plants that grow around the nation, with 55% of them are endemic plants [51, 52].
First, we prepared the Indonesian natural product compounds by searching the molecular structures through several journals and databases [53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69], after which we were drawing them using ChemBioDraw 14.0 software. From this step, we obtained about 3429 compounds in the process. All of these ligands were then protonated, washed, and minimized by using MOE 2014.09 software [70]. These ligands were saved for the docking simulation purpose. For the EBOV VP35 protein, we selected the PDB ID: 4IBC as our protein, and we determined the pharmacophore site through standard protein-ligand interaction fingerprints (PLIF) protocol of MOE 2014.09 software. This step generated the pharmacophore model around the binding site of EBOV VP35 after we performed the protonating process of EBOV VP35 through “LigX” feature of MOE 2014.09 software. Later on, we conducted molecular docking simulation using the modification of our current approach [71, 72]. Instead of using “Triangle Matcher” and “London dG,” we used “Pharmacophore” and “Affinity dG” for “Placement” and “Rescoring 1” parameters to accommodate the pharmacophore model that created in an earlier phase, while the rest of parameters were set according to the default setup. First, the STD1 ligand (IUPAC name: 2-(4-(4-(2-chlorobenzoyl)-5-(2-chlorophenyl)-2,3-dioxo-2,3-dihydro-1H-pyrrol-1-yl)phenyl)acetic acid) and 100 decoy ligands were docked into the binding site to validate the pharmacophore model. “Rigid Receptor” and “Induced-Fit” protocols were performed against the Indonesian natural product compounds and STD1 ligand later on.
In an attempt of searching the proper pharmacophore site in the binding site of EBOV VP35, we utilized the PLIF protocol from MOE 2014.09 software by using STD1 ligand as the template. From this approach, we figured out that the binding site of EBOV VP35 protein consists of three pharmacophore sites, as it displayed in Figure 1. One hydrophobic spot is affiliated with Lys248 residues through arene-hydrogen interaction, while two H-bond acceptors, lone-pair sites, are connected with Gln241 and Lys251. These sites were responsible for the binding attachment of the STD01 ligand when bound to EBOV VP35 protein. Thus, it can be predicted that any ligands that bind to these residues may exhibit the same antiviral activities like STD01 ligand.
The pharmacophore model of the STD01 ligand in the binding site of EBOV VP35 protein. According to the PLIF feature of MOE 2014.09 software, the STD01 ligand comprises three pharmacophore sites: one hydrophobic point and two acceptor/lone-pair points (left). In the docking simulations, we deployed the “exclude points” to indicate the residues that exist in the VP35 binding site and prevent the larger ligands to interact with the binding site.
The pharmacophore sites were later validated by having the STD01 ligand and 100 decoys to be screened through molecular docking simulation. In this phase, we deployed “virtual screening” approach as our docking protocol, with pharmacophore model that was included in the simulation. After the screening was conducted, we discovered that all of the decoys did not pass the test, indicating this method was validated and did not create the “false-positive” ligand that may result during docking simulation. Furthermore, the STD01 ligand passed this test with a ∆Gbinding score of −5.2778 kcal/mol and RMSD value of 1.5487 Å. This result was shown that the parameters that were set earlier were decent enough to be reproduced in the next simulation. The comparison of the initial and screened poses of STD01 ligand is shown in Figure 2.
The binding interaction of the STD01 ligand and EBOV VP35 binding site. The 2D interaction after docking simulation is displayed in the left figure, while the right figure presents the difference between the initial pose (shown in yellow) and after the docking simulation was conducted (shown in pink).
The pharmacophore-based docking simulation of EBOV VP35 protein was later performed against the 3429 Indonesian natural product ligands that were already prepared. From the simulations, we acquired 20 ligands that matched with the pharmacophore model of EBOV VP35, which means that other 3409 ligands did not possess the properties that needed to pass the initial pharmacophore screening. In the first docking simulation (Rigid Docking protocol), we found four Indonesian natural product ligands, namely, multifloroside, myricetin 3-robinobioside, kaempferol 3-(6G-malonylneohesperidoside), and theasaponin, which have the ∆Gbinding score lower than the STD01 ligand. The molecular structures of these ligands can be seen in Figure 3.
The molecular structure of multifloroside (top left), myricetin 3-robinobioside (top middle), kaempferol 3-(6G-malonylneohesperidoside) (top right), theasaponin (bottom left), and 2-(4-(4-(2-chlorobenzoyl)-5-(2-chlorophenyl)-2,3-dioxo-2,3-dihydro-1H-pyrrol-1-yl)phenyl)acetic acid (bottom right).
After the first docking simulation had been performed, the second docking simulation (Induced-Fit protocol) was utilized against these four proteins to revalidate the docking pose that was produced in the previous simulations. If the RMSD difference was lower than 2.0 Å, it means that the docking pose is good enough and may be reproduced in the actual simulation [73]. In this simulation, we found that multifloroside ligand has the lowest ∆Gbinding score of −10.8405 kcal/mol, followed by myricetin 3-robinobioside (−10.0897 kcal/mol), kaempferol 3-(6G-malonylneohesperidoside) (−9.8721 kcal/mol), and theasaponin (−9.0175 kcal/mol). These results were significantly lower than the STD01 ligand, which sits in −9.0175 kcal/mol. However, we must take into account that the RMSD value of multifloroside ligand was 3.2691 Å, higher than 2.0 Å; it means that the docking pose that was generated during the docking simulation was not acceptable. Meanwhile, the other three ligands possessed the tolerable RMSD value (1.2275, 1.0311, and 0.4352 Å for myricetin 3-robinobioside, kaempferol 3-(6G-malonylneohesperidoside), and theasaponin, respectively). Furthermore, we also observed the interactions between the ligands and the binding site of EBOV VP35. From the docking simulation, we figured out that all three remaining ligands made interactions with Gln241 and Lys251, which are important in suppressing the EBOV VP35 activity. The full results of molecular docking simulations can be seen in Table 1 and Figure 4.
Molecule name | ∆Gbinding (RMSD) | H-bond interaction residues |
---|---|---|
Multifloroside | −10.8405 kcal/mol (3.2691) | Arg225, Tyr229, Lys 248, and Lys251 |
Myricetin 3-robinobioside | −10.0897 kcal/mol (1.2275) | Lys222, Arg225, Gln241, and Lys251 |
Kaempferol 3-(6G-malonylneohesperidoside) | −9.8721 kcal/mol (1.0311) | Gln241, Gln244, Lys251, and His296 |
Theasaponin | −9.0175 kcal/mol (0.4352) | Arg225, Gln241, and Lys251 |
STD01 ligand ( | −8.4579 kcal/mol (0.7747) | Gln241, Lys248, and Lys251 |
The results of molecular docking simulation.
The interacting residues of EBOV VP35 protein with myricetin 3-robinobioside (left), kaempferol 3-(6G-malonylneohesperidoside) (middle), and theasaponin (right).
Without no doubt, the drug developments of Ebola are desperately needed due to high pathogenicity and mortality rate that emitted by this disease. Through this chapter, we present that bioinformatics and CADDD, especially the pharmacophore-based drug design, may be the solution to significantly increase the viability of the newly discovered lead compounds that can be introduced as the drug candidate of Ebola virus, which can be supported later through in vitro study to validate the results that we found in previous research. The dry lab experiments should play a significant role in the development of drugs, not only Ebola but also for all diseases due to low cost and not a time-consuming process. Therefore, the improvements and developments of bioinformatics and CADDD should also speed up the time that we needed to obtain the drug candidates for our health problems.
This book chapter is financially supported by Penelitian Unggulan Perguruan Tinggi (PUPT) 2017, granted by Ministry of Research, Technology, and Higher Education, the Republic of Indonesia through Directorate of Research and Community Engagements, Universitas Indonesia, with no: 2716/UN2.R3.1/HKP.05.00/2017.
None are declared.
Filters play a vital role in numerous microwave applications. A microwave bandpass filter (BPF), in general, is a class of filter that is utilized to operate on the frequency response within the range of frequencies lying between 300 MHz and 300 GHz and allowing the best signal transmission at desired frequencies (passband), while eliminating signals at redundant frequencies (stopband) [1]. Among various techniques to design a bandpass filter, substrate integrated waveguides (SIWs) [2] are becoming more popular recently. SIW is a planar structure that is fabricated by using two periodic rows of conducting cylindrical vias implanted in a dielectric substrate, as shown in Figure 1. Hence, it acts as a bridge between planar and nonplanar technology.
Conventional substrate integrated waveguide.
To design efficient and well-performing wireless systems, there is a great need to design compact, lightweight microwave components. Over the past few years, various SIW miniaturization techniques have been proposed by researchers. Recently, [3] has reviewed the recent trends and various miniaturization techniques of SIW. Recently, folded SIW (FSIW) technique (C & T type FSIW) has been proposed by [4, 5]. Miniaturization was achieved using half mode SIW and Hilbert fractal for 5G applications [6]. Further, [7] proposed a ridge SIW to achieve miniaturization and suppress the harmonics.
From the design Equations [8] for a substrate integrated waveguide (SIW), d as the diameter of the vias and p as distance between the vias known as pitch, the equivalent width of dielectric-filled rectangular waveguide,
Width of SIW,
Also, for choosing the value of
A metamaterial is a word derived from the Greek word—it is a combination of the words “meta” and “material,” in which “meta” means something beyond normal, altered, changed, or something advanced. It is an artificial material designed to obtain the physical properties that do not exist in natural materials. A metamaterial [9] is an artificially engineered material with desirable properties not found in nature. A metamaterial affects electromagnetic waves by having structural features smaller than the wavelength of the medium of electromagnetic interaction. Metamaterials rely mainly on their physical structure to manipulate the electromagnetic waves to exhibit superior characteristics.
In 1999, John Pendry was the first to identify a practical way to make a left-handed metamaterial. Pendry’s theoretical idea was that metallic wires aligned along the direction of a wave could provide negative permittivity (ε < 0), and a split ring with its axis placed along the direction of wave propagation could do so could provide negative permeability. In 2000, Smith et al. reported the experimental demonstration of functioning electromagnetic metamaterials by stacking, periodically, split-ring resonators and thin wire structures as shown in Figure 2.
The array of split-ring resonators plus wire assemblies.
Metamaterials with negative RI have numerous interesting properties. Several physical phenomena are reversed in LH media and at the intersection between LH and RH media due to the opposite sign of phase and group velocities. Some of the effects are:
Reversal of Snell’s law
Reversal of Doppler effect
Reversal of Vavilov-Cherenkov radiation
Lensing effect (convex lenses produce diverging rays, which is opposite to RH lenses)
The time-averaged Poynting vector (S) is antiparallel to phase velocity
Russian scientist Veselago first proposed the metamaterial classification by considering the permittivity, ε, and the permeability, μ of a homogeneous material. The relationship between the refractive index and the constituent parameters ε and μ is given by the formula:
where εr and μr are the relative permittivity and permeability of the material. From Eq. (4), sign ± of n can get 1 in the four cases, which depends on the pairs of the sign of εr and μr. The electromagnetic metamaterials are classified based on each case of the pair sign ε and μ; they are shown in Figure 3.
Metamaterial classification.
In quadrant I, both parameters ε and μ are positive and are called double positive (DPS) or right-handed medium (RHM). In quadrant II, the parameters are ε < 0—negative, and μ > 0—positive, and such material is called epsilon negative (ENG) medium and is represented by plasma. In quadrant III, parameters ε < 0—negative, and μ < 0—negative, this region is called double-negative (DNG) or left-handed medium (LHM), and such material could not be found in nature. The quadrant IV ε > 0—positive, and μ < 0—negative, such material is called μ—negative (MNG), represented by ferrite materials.
A split-ring resonator (SRR) is a type of metamaterial, which is artificially created. SRR cell is made up of a pair of enclosed loops of nonmagnetic metals that split at opposite ends, as shown in Figure 4. When these materials are exposed to the magnetic field of electromagnetic waves, they give strong magnetic coupling unavailable in conventional materials. When SRRs are arranged periodically (array), they provides negative permeability.
Split-ring resonator with its equivalent circuit.
The above structure of SRR is known as edge-coupled split-ring resonator (EC-SRR) structure, which comprises concentric metal split rings printed on the same side of the dielectric substrate. EC SRR benefits of strong magnetic polarizability near resonance and easy fabrication. However, it has certain drawbacks: (i) Its electric size cannot be reduced below one-tenth of wavelength; (ii) it suffers from cross-polarizability/bianisotropic effect. Another type of SRR overcomes these limitations, called broadside-coupled SRR (BC-SRR) [10]. In the BC-SRR configuration, the rings are etched on both faces of the substrate, as shown in Figure 5a. Similar to EC-SRR, charges formed in the lower half of the BC-SRR are the replica of charges formed in the upper half, as shown in Figure 5b. Though this formation of charge does not create an electric dipole, BC SRR is non-bianisotropic. Since both rings are of identical dimension and keep inverse symmetry, for this reason, cross-polarizability tensor vanishes.
Charge distributions in (a) EC-SRR (b) BC-SRR. rext is the outer radius of ring and ro is the inner radius of the ring.
The application of the Babinet principle leads to the origin of its counterpart known as a complementary split-ring resonator (CSRR) in which the rings are engraved on the conductive surface, and its magnetic and electric characteristics are changed when compared with SRR.
A SIW bandpass filter based on edge-coupled CSRRs was proposed for the first time in 2007 by [11]. The SIW filter consisted of the tapered transition line with the CSRR. As SIW possesses high-pass characteristic, whereas a CSSR manifests band-stop characteristic, therefore by integrating CSRR with SIW, a bandpass SIW filter is designed. Figure 6 depicts the structure of SIW with CSSR etched in the top side of the substrate.
(a) Top and (b) bottom view of basic unit cell [
Figure 7 depicts the equivalent lumped equivalent circuit for Figure 6. CSRRs etched in the center are excited by the electric field induced by the SIW. Therefore, this coupling can be labeled by connecting the SIW capacitance to the CSRR. In these models, L is the inductance of SIW vias, and C is the coupling capacitance between the CSRR and SIW. The resonator is represented by a parallel LC tank, where Lc and Cc represent the reactive elements, and R accounts for losses.
The equivalent circuit model.
Figure 8a shows the dimensional geometry of the proposed SIW-CSSRs bandpass filter [11], and Figure 8b shows the photograph of the fabricated design. The substrate used in the filter is RT/Duroid 5880, with a permittivity of 2.2 and a height of 0.254 mm.
(a) Dimensional layout of BPF and (b) fabricated BPF [
Figure 9 compares the simulated and measured results of the filter. The measured insertion and return losses are about 2.16 dB and 11.6 dB, respectively. The filter shows a wide bandwidth ranging from 6.2 to 8.6 GHz (FBW of 32.4%).
Comparison of simulated and measured results [
The effect of changing the orientations of the CSRR ring was exhaustively studied by [12], which was verified by simulations and experiments that modify CSRR’s orientations, different passband characteristics can be obtained. The orientation was specified with respect to the direction of the outer ring’s split, as shown in Figure 10. Hence, they are aligned face to face, back to back, and side by side. The side-by-side type has also been divided into two cases with the CSRRs reversely or equally oriented.
Configurations of various SIW-CSRR unit cells in which the CSRRs are: (a) face to face, (b) back to back, (c) side-by-side reversely oriented, and (d) side-by-side equally oriented.
After simulation of various orientations, it was found that by altering the configuration of the CSRRs in a particular position (face-to-face orientation), the propagation of TE10 mode can be suppressed, resulting in enhanced selectivity and stopband rejection of the filter. The waveguide width was chosen as w = 12.3 mm to keep the cutoff frequency of the initial SIW at about 8.7 GHz. The Rogers substrate RT/Duroid 5880 with a thickness of 0.508 mm and a relative permittivity of 2.2 is used in the design. The metalized vias have a diameter of 0.8 mm and a center-to-center spacing of 1.48 mm.
After the simulation of various configurations, it was found that the unit cells with face-to-face and back-to-back oriented CSRR exhibit a similar kind of passband with one transmission zero and one pole located above the passband. Nonetheless, for the second case, the transmission zero is close to the pole leading to a steep upper side transition but with large insertion loss due to the weak coupling. For the third case, two rings are arranged side by side in opposite directions, and two transmission poles with two transmission zeros in the upper band are achieved. The propagation is quite weak for the fourth case due to weak magnetic coupling.
Eventually, a two-stage filter using the unit cell aligned face to face is simulated and fabricated using Rogers RT/Duroid 5880. A distance of 8.8 mm separates the two cells. The proposed bandpass filter achieves one transmission zeros at 6.4 GHz in the upper band, resulting in high selectivity and a wide upper stopband. The two-pole filter has a measured center frequency of 5.0 GHz and a 3-dB bandwidth of 0.33 GHz (3.2% FBW).
Recently, a novel bandpass filter using diamond-shaped edge-coupled CSRR was proposed [13]. This section discusses the design methodology of single-stage and two-stage bandpass filters with diamond-shaped EC-CSRR structures.
The physical construction of CSRR is shown in Figure 11, where the upper orange part is conducting layer, and the light gray part is the substrate. The CSRR structure consists of two diamond-shaped split resonant rings with their openings opposite (face to face) to each other for tight coupling between them. As CSRRs are integrated with SIW, a passband with an evanescent resonant mode lower than the SIW’s cutoff frequency is created, miniaturizing the size of the conventional SIW [13]. Figure 11 shows the dimensional view of a single-stage SIW filter loaded with diamond-shaped CSRR. The optimized dimensions of filter are: length of single-stage SIW LSIW = 10 mm, width of SIW WSIW = 8.5 mm, the inner radius of ring R1 = 1.0 mm, the outer radius of ring R2 = 1.6 mm, the thickness of ring T = 0.25 mm, the gap between open ends of outer ring G = 0.40 mm, the perpendicular distance between outer rings S = 1.25 mm. Figure 12 shows the frequency response of single-stage CSRR incorporating SIW filter. The figure shows that in a single-stage SIW filter, one passband is formed with a center frequency of 8.75 GHz, below the waveguide cutoff frequency causing miniaturization by approximately 33%. The passband has 3-dB bandwidth of 0.42 GHz with an in-band insertion loss of 0.62 dB. The maximum value of return loss is −24.4 dB. Also, the stopband created has a high rejection level at the upper stopband.
Schematics of single-stage SIW BPF.
Frequency response of single-stage SIW BPF.
The two-stage filter is proposed to improve the passband and stopband performance of the filter, as shown in Figure 13. The length of the two-stage SIW filter is taken as LSIW
Schematics of two-stage SIW BPF.
(a) Current distribution in the passband. (b) Current distribution in the stopband.
Figure 15 shows the simulated frequency response of two-stage SIW BPF. The response clearly shows that one passband is formed with two poles and transmission zero. The passband has a center frequency of 8.86 GHz with 3-dB bandwidth of 0.74 GHz and an in-band insertion loss of 0.48 dB. The maximum return loss is −29.4 dB. Further, the stopband rejection is more than 60 dB, which is relatively better than a single-stage filter. In the second stage of transmission, zero is in proximity to poles leading to a high roll-off rate of 72.5 dB/GHz and 40.5 dB/GHz at the upper and lower edge, respectively.
Frequency response of two-stage SIW BPF.
A novel SIW BPF using broadside-coupled complementary split-ring resonator (BC-CSRR) pairs was implemented for the first time by [14]. Figure 16 (left) shows the structure of the BC-SRR (broadside-coupled split-ring resonator. It can be derived from EC-SRR by substituting one of the rings with another ring situated precisely at the opposite side of the substrate. From the duality principle, the negative image of the BC-SRR is termed as the broadside-coupled complementary split-ring resonator (BC-CSRR), as shown in Figure 16 (right).
Broadside-coupled SRR (BC-SRR), left and broadside-coupled CSRR (BC-CSRR), right.
Figure 17 depicts the layout of the proposed SIW BC-CSRR. It is evident that two BC-CSRRs are aligned side by side with opposite orientations to each other. A microstrip feed line is used to excite the SIW cavity. For the selected dielectric substrate with ɛr = 2.65 and waveguide cutoff frequency of 8.15 GHz, the width of the SIW (w) is calculated to be 12.5 mm. Figure 18 shows the simulated transmission response for the SIW integrated with the unit cell. It is evident from the response that it creates a passband with a center frequency of 5.6 GHz, which is below waveguide cutoff frequency.
Structure of the proposed SIW BC-CSRR unit cell [
Simulated frequency response of the original SIW and SIW BC-CSRR pair [
Figure 19 depicts the proposed two-stage BC-CSRR BPF with separation between rings (
Structure of the proposed SIW BC-CSRR unit cell [
Figure 20 shows the photograph of the fabricated filter using a substrate with ɛr = 2.65 and a thickness of 1 mm. Figure 21 compares the simulated and measured frequency response of the BPF. The measured center frequency and 3-dB bandwidths are 5.75 GHz and 0.32 GHz, respectively. The measured in-band return loss is below 12 dB. The dimension of the filter is 20 mm x 13 mm (0.38 x 0.25 λo2).
Snapshot of the SIW BPF with BC-CSRR pairs [
Comparison of simulated and measured result [
This work [15] proposes the design of a substrate integrated waveguide (SIW) bandpass filter (BPF) incorporated with a novel broadside-coupled complementary split-ring resonator (BC-CSRR). The complementary double S shape as metamaterial is carved on the top and broad bottom walls of SIW with orientation 180o to each other. The proposed filter is designed for X band using substrate alumina with a relative permittivity of 9.8 and height of 0.508 mm. Further, the width of the SIW, WSIW is set to 5.4 mm to keep the nominal cutoff frequency of the waveguide to 10 GHz using SIW design equations.
For designing the proposed S-shaped metamaterial, a double S-shaped structure was placed one above the another in an antisymmetrical manner over a dielectric layer forming a shape of 8 [16]. S on both sides of the dielectric forms metamaterial that simultaneously provides negative permeability and permittivity. The side length of the S shape is kept equal to λg/4 (A = 2.25 mm), and thickness T is kept equal to 0.35 mm, as shown in Figure 22.
Geometry of S structure.
Figure 23 depicts the setup to get S parameters of complementary S-shaped metamaterial using HFSS. For this, two-layered dielectric substrates (alumina) having relative permittivity 9.8 of thickness 0.508 mm are stacked over each other. The S-shaped structure is placed on the opposite side of the top dielectric substrate one above the other (in a complementary manner) to form Figure 8. A 50 Ω microstrip line is provided at the bottom of the lower substrate.
Geometry of double “S”-shaped structure with microstrip line at the bottom.
In HFSS, first, simulate the metamaterial structure by providing the solution frequency. Then get S-parameters (S11, S21) in tabular form as follows:
Result- > Create Modal Simulation Data Report - > Data Table.
Create a data table for S(1,1) containing magnitude and angle in rad (phase).
Similarly, create a data table for S (2,1). These files have extension .csv (comma-separated values).
Export these .csv files to the same folder where MATLAB code is kept. Now, call these files S(1,1).csv and S(2,1).csv in parameter extraction MATLAB code [17] in function referred as DATA_READ specifying the path locations of files.
Successful execution of MATLAB code [17] for the parameter extraction results led to permittivity and permeability, as shown in Figure 24. The graph indicates that the permeability and permittivity are negative simultaneously for the frequency range between 7.25 GHz and 9.15 GHz. It illustrates that the structure has metamaterial characteristics for the frequency range between 7.25 GHz and 9.15 GHz.
Graph of real values of μ and ε.
Figure 25 shows single-stage BC-CSRR BPF, which has a pair of identical “S”-shaped etched on the SIW top and broad bottom walls but at 180° to each other. A tapered microstrip feed line has been used for exciting the SIW. The design parameters are taken as: WSIW = 5.4 mm, LSIW = 4.2 mm, P = 1.6 mm, D = 0.8 mm, LT = 4 mm, WT = 2 mm, LM = 2 mm, WM = 0.50 mm, A = 2.25 mm, and T = 0.35 mm.
Schematics of single-stage SIW BC-CSRR BPF.
Figure 26 shows the equivalent circuit of the single-stage BC-CSRR BPF. The equivalent circuit of the S-shaped SRR structure is given by [18], in which S-SRR is modeled by a series L-C circuit in each half ring of the eight-shaped structure through a common capacitor. Since CSRR is complementary to the SRR structure, the equivalent circuit of single unit BC-CSRR will be dual of S-SRR. The metallic vias of the SIW are modeled as Lv.
Equivalent circuit of BC-CSRR BPF.
Figure 27 shows the simulated result of the equivalent lumped circuit using ADS.
Frequency response (S11) of an equivalent lumped circuit of single-stage BC-CSRR SIW filter.
Figure 28 shows the frequency response of single-stage BC-CSRR incorporated SIW filter. The figure shows that by etching the S structure in SIW, a passband is obtained with a center frequency of 8.2 GHz and 3-dB bandwidth of 0.15 GHz. The maximum return loss is 21.55 dB, and insertion loss is 0.32 dB at the center frequency. It can be seen that the resonant frequency of the SIW BC-CSRR element is well below the cutoff frequency of the original SIW, causing its miniaturization.
Frequency response of single-stage BC-CSRR SIW filter.
In order to improve roll-off factor and order of filter, cascaded connection [19] of two identical BC-CSRR structures is used to form two-stage BPF. Figure 29 shows the structure of two-stage BC-CSRR BPF with design parameters taken as: WSIW = 5.4 mm, LSIW = 4.2 mm P = 1.6 mm, diameter of via D = 0.8 mm, LT = 4 mm, WT = 2 mm, LM = 2 mm, WM = 0.50 mm, A = 2.25 mm, T = 0.35 mm, and L = 4.25 mm.
Schematics of two-stage SIW BC-CSRR BPF.
The distance (L) between two BC-CSRRs has a vital influence on the performance of the proposed two-stage filter. Figure 30 shows the parametric analysis of return loss with varying values of L (for L = 3.25, 3.75, 4.25, 4.75, 5.25 mm). It is clear from Figure 30 that the filter shows optimum performance for L = 4.25 mm. For other small or big values of L, its response becomes undesirable.
Parametric analysis of return loss for varying side length “a.”
Figure 31a and b depicts the current distribution in passband and stopband, respectively. As seen from the current distribution, it is clear that when the filter is passing the signal, the center resonator is resonant and has a large current that couples the signal through to the output.
Current distribution in (a) passband and (b) stopband.
Figure 32 shows the frequency response of two-stage BS-CSRR. From the response, it can be observed that a passband with 3-dB bandwidth of 0.385 GHz is obtained. The simulated insertion loss is 0.32 dB, and the simulated roll-off rate at the lower and upper edge of the passband is calculated to be 78.26 dB/GHz and 65.5 dB/GHz, respectively. The maximum return loss value is 24.85 dB at the center frequency of 8.4 GHz with a 3-dB bandwidth of 0.38 GHz.
Frequency response of single-stage BC-CSRR SIW filter.
The proposed filter is fabricated using substrate material alumina with a relative dielectric constant of 9.8, tan δ = 0.001, and thickness of 0.508 mm to validate the result. Figure 33a and b shows the photograph of the top and bottom layer of the assembled filter with overall dimensions as 10 mm (length excluding transition) × 8.5 mm (width).
(a) Top and (b) bottom view of the fabricated bandpass filter.
The scattering parameters of the fabricated filter are measured by a vector network analyzer Anritsu S 820E. A two-port SOLT (short- open- load and thru) calibration has been done to consider cable losses between the VNA and the DUT. The measured and HFSS simulated results are compared and depicted in Figure 34a. It can be seen that the measured passband of the filter is from 8.20 GHz to 8.74 GHz with 3-dB bandwidth of 0.54 GHz. The maximum return loss value is 17.2 dB with an insertion loss of 0.92 dB in almost the entire passband. It achieves good attenuation (>20 dB) in the upper stopband. The measured roll-off rate is 58.5 dB/GHz and 60.2 dB/GHz at the lower and upper edge of the passband, respectively. Figure 34b depicts the simulated and measured VSWR plot for the entire range.
Comparison of (a) the simulated and measured result S parameters and (b) VSWR.
The metamaterials can be applied to enhance bandwidth, create a compact structure or multifrequency bands, etc. In this chapter, various compact and selective CSRR integrated SIW bandpass filters have been analyzed, demonstrating their performance. To apply metamaterials, the first step is to design their unit cells, creating special metamaterial properties at the desired frequency. The size of the unit cells is calculated, simulated, and optimized using the HFSS software. First, three edge-coupled CSRR (EC-CSRR) BPFs have been analyzed for the design and performance. Then two broadside-coupled CSRR (BC-CSRR) BPFs have been analyzed elaborately and evaluated for performance.
This work was carried out during the tenure of ‘The European Research Consortium for Informatics and Mathematics (ERCIM) Alain Bensoussan’ Fellowship’ programme.
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In this work, a methodology is proposed for the evaluation of the abrasive wear of the plates of the centrifugal pump impellers, used in the gross water infrastructure station (GWIS) of sedimentary rivers, due to the sediment load variation and the river fluviometric dimension. In order to determine the wear mode and the relationship of the material-specific wear coefficient (K), due to the sediment concentration, a rotating ball abrasometer test was performed on SAE 8620, gray cast iron (GCI), and nodular cast iron (NCI), used in the manufacture of impellers. As an abrasive suspension, the concentrations of 1, 2, 3, 5, and 10 g L−1 of sediment were used in distilled water. The wear volume as a function of the relative velocity of the mixture in relation to the impeller blades was estimated mathematically. The results show that: i) The abrasive capacity of the sediments in different concentrations; ii) SAE 8620 steel was more resistant to abrasive wear; and iii) the rotational control of the pump as a function of sediment concentration and river level showed the possibility of reducing wear by 30%.",book:{id:"7766",slug:"rotating-machinery",title:"Rotating Machinery",fullTitle:"Rotating Machinery"},signatures:"Rodrigo O.P. Serrano, José G. do V. Moreira, Ana L.P. de Castro, Maria A. Pinto, Edna M. de F. Viana and Carlos B. Martinez",authors:[{id:"275910",title:"Ph.D.",name:"Rodrigo",middleName:null,surname:"Serrano",slug:"rodrigo-serrano",fullName:"Rodrigo Serrano"},{id:"281555",title:"Dr.",name:"José",middleName:null,surname:"Moreira",slug:"jose-moreira",fullName:"José Moreira"},{id:"281557",title:"Dr.",name:"Ana",middleName:"Letícia Pilz",surname:"Castro",slug:"ana-castro",fullName:"Ana Castro"},{id:"281558",title:"Dr.",name:"Edna",middleName:null,surname:"Viana",slug:"edna-viana",fullName:"Edna Viana"},{id:"281559",title:"Dr.",name:"Maria",middleName:null,surname:"Pinto",slug:"maria-pinto",fullName:"Maria Pinto"},{id:"281560",title:"Dr.",name:"Calos",middleName:null,surname:"Martinez",slug:"calos-martinez",fullName:"Calos Martinez"}]},{id:"69828",doi:"10.5772/intechopen.83828",title:"Uncertainty Analysis Techniques Applied to Rotating Machines",slug:"uncertainty-analysis-techniques-applied-to-rotating-machines",totalDownloads:746,totalCrossrefCites:1,totalDimensionsCites:1,abstract:"This chapter presents the modeling procedure, numerical application, and experimental validation of uncertain quantification techniques applied to flexible rotor systems. The uncertainty modeling is based both on the stochastic and fuzzy approaches. The stochastic approach creates a representative model for the flexible rotor system by using the stochastic finite element method. In this case, the uncertain parameters of the rotating machine are characterized by homogeneous Gaussian random fields expressed in a spectral form by using the Karhunen-Loève (KL) expansion. The fuzzy approach uses the fuzzy finite element method, which is based on the α-level optimization. A comparative study regarding the numerical and experimental results obtained from a flexible rotor test rig is analyzed for the stochastic and fuzzy approaches.",book:{id:"7766",slug:"rotating-machinery",title:"Rotating Machinery",fullTitle:"Rotating Machinery"},signatures:"Fabian Andres Lara-Molina, Arinan De Piemonte Dourado, Aldemir Ap. Cavalini and Valder Steffen",authors:[{id:"274498",title:"Prof.",name:"Valder",middleName:null,surname:"Steffen Jr",slug:"valder-steffen-jr",fullName:"Valder Steffen Jr"},{id:"274503",title:"Dr.",name:"Aldemir Ap.",middleName:null,surname:"Cavalini Jr",slug:"aldemir-ap.-cavalini-jr",fullName:"Aldemir Ap. Cavalini Jr"}]},{id:"66712",doi:"10.5772/intechopen.85877",title:"Development and Control of Generator-Converter Topology for Direct-Drive Wind Turbines",slug:"development-and-control-of-generator-converter-topology-for-direct-drive-wind-turbines",totalDownloads:812,totalCrossrefCites:0,totalDimensionsCites:0,abstract:"In this chapter, a new topology for Direct-Drive Wind Turbines (DDWTs) with a low-voltage generator design is presented in order to eliminate the required dc-bus capacitors or dc-link inductors. In the presented topology, the grid-side converter is replaced by a boost Current Source Inverter (CSI) therefore removing the need for the dc-bus electrolytic capacitors which results in increasing the system lifetime. In the developed topology, the synchronous inductance of the generator is utilized. This facilitates the elimination of the intrinsically required dc-link inductor in the CSI which further contributes to a reduction in the overall system weight and size. The boost CSI is capable of converting a low dc voltage to a higher line-to-line voltage. This results in the implementation of a low-voltage generator for DDWTs. The feasibility of the presented low-voltage generator is investigated through Finite Element (FE) computations. In this chapter, a modified 1.5 MW low-voltage generator for the proposed topology is compared with an existing 1.5 MW Permanent Magnet (PM) synchronous generator for DDWTs. The feasibility of the presented topology of generator-converter for DDWTs is verified through simulations and laboratory tests. Furthermore, the controls developed for the developed wind turbine topology is also presented in this chapter.",book:{id:"7766",slug:"rotating-machinery",title:"Rotating Machinery",fullTitle:"Rotating Machinery"},signatures:"Akanksha Singh",authors:[{id:"276799",title:"Dr.",name:"Akanksha",middleName:null,surname:"Singh",slug:"akanksha-singh",fullName:"Akanksha Singh"}]},{id:"66758",doi:"10.5772/intechopen.85910",title:"Advance Measurement Techniques in Turbomachines",slug:"advance-measurement-techniques-in-turbomachines",totalDownloads:686,totalCrossrefCites:0,totalDimensionsCites:0,abstract:"This chapter focuses on advanced measurement techniques that have been used in applications of turbomachines including temperature measurements, pressure measurements, velocity measurements, and strain/stress measurements. Though the measurement techniques are fundamentally the same as those used in other applications, the unique features associated with turbomachines place challenges in implementing these techniques. This chapter covers the fundamental working principles of individual measurement technique as well as the highlights of its application in turbomachines.",book:{id:"7766",slug:"rotating-machinery",title:"Rotating Machinery",fullTitle:"Rotating Machinery"},signatures:"Fangyuan Lou",authors:[{id:"275580",title:"Dr.",name:"Fangyuan",middleName:null,surname:"Lou",slug:"fangyuan-lou",fullName:"Fangyuan Lou"}]}],mostDownloadedChaptersLast30Days:[{id:"65843",title:"Straight-Bladed Vertical Axis Wind Turbines: History, Performance, and Applications",slug:"straight-bladed-vertical-axis-wind-turbines-history-performance-and-applications",totalDownloads:2743,totalCrossrefCites:4,totalDimensionsCites:6,abstract:"Wind turbine is a kind of rotating machinery. Although the horizontal axis wind turbine (HAWT) is the most popular wind turbine, the vertical axis wind turbine (VAWT) with the main advantages of smart design, novel structure, and wind direction independence receives more and more attention in small-scale wind power market. The straight-bladed VAWT (SB-VAWT) is one of the most researched and studied VAWTs. In this chapter, the historical development of the SB-VAWT will be briefly reviewed firstly. Then the aerodynamic models for the turbine design and performance analysis will be introduced. Finally, the types of traditional and new SB-VAWT and their characteristics and main utilizations will be introduced.",book:{id:"7766",slug:"rotating-machinery",title:"Rotating Machinery",fullTitle:"Rotating Machinery"},signatures:"Yan Li",authors:[{id:"277795",title:"Prof.",name:"Yan",middleName:null,surname:"Li",slug:"yan-li",fullName:"Yan Li"}]},{id:"67029",title:"Methodology for Abrasive Wear Evaluation in Elevator Stage Centrifugal Pump Impellers",slug:"methodology-for-abrasive-wear-evaluation-in-elevator-stage-centrifugal-pump-impellers",totalDownloads:752,totalCrossrefCites:0,totalDimensionsCites:1,abstract:"The abrasion resistance of the impellers depends on the characteristics of the materials used in their manufacture. In this work, a methodology is proposed for the evaluation of the abrasive wear of the plates of the centrifugal pump impellers, used in the gross water infrastructure station (GWIS) of sedimentary rivers, due to the sediment load variation and the river fluviometric dimension. In order to determine the wear mode and the relationship of the material-specific wear coefficient (K), due to the sediment concentration, a rotating ball abrasometer test was performed on SAE 8620, gray cast iron (GCI), and nodular cast iron (NCI), used in the manufacture of impellers. As an abrasive suspension, the concentrations of 1, 2, 3, 5, and 10 g L−1 of sediment were used in distilled water. The wear volume as a function of the relative velocity of the mixture in relation to the impeller blades was estimated mathematically. The results show that: i) The abrasive capacity of the sediments in different concentrations; ii) SAE 8620 steel was more resistant to abrasive wear; and iii) the rotational control of the pump as a function of sediment concentration and river level showed the possibility of reducing wear by 30%.",book:{id:"7766",slug:"rotating-machinery",title:"Rotating Machinery",fullTitle:"Rotating Machinery"},signatures:"Rodrigo O.P. Serrano, José G. do V. Moreira, Ana L.P. de Castro, Maria A. Pinto, Edna M. de F. Viana and Carlos B. Martinez",authors:[{id:"275910",title:"Ph.D.",name:"Rodrigo",middleName:null,surname:"Serrano",slug:"rodrigo-serrano",fullName:"Rodrigo Serrano"},{id:"281555",title:"Dr.",name:"José",middleName:null,surname:"Moreira",slug:"jose-moreira",fullName:"José Moreira"},{id:"281557",title:"Dr.",name:"Ana",middleName:"Letícia Pilz",surname:"Castro",slug:"ana-castro",fullName:"Ana Castro"},{id:"281558",title:"Dr.",name:"Edna",middleName:null,surname:"Viana",slug:"edna-viana",fullName:"Edna Viana"},{id:"281559",title:"Dr.",name:"Maria",middleName:null,surname:"Pinto",slug:"maria-pinto",fullName:"Maria Pinto"},{id:"281560",title:"Dr.",name:"Calos",middleName:null,surname:"Martinez",slug:"calos-martinez",fullName:"Calos Martinez"}]},{id:"69167",title:"Introductory Chapter: Rotating Machinery",slug:"introductory-chapter-rotating-machinery",totalDownloads:776,totalCrossrefCites:0,totalDimensionsCites:0,abstract:null,book:{id:"7766",slug:"rotating-machinery",title:"Rotating Machinery",fullTitle:"Rotating Machinery"},signatures:"Getu Hailu",authors:[{id:"250634",title:"Ph.D.",name:"Getu",middleName:null,surname:"Hailu",slug:"getu-hailu",fullName:"Getu Hailu"}]},{id:"66712",title:"Development and Control of Generator-Converter Topology for Direct-Drive Wind Turbines",slug:"development-and-control-of-generator-converter-topology-for-direct-drive-wind-turbines",totalDownloads:812,totalCrossrefCites:0,totalDimensionsCites:0,abstract:"In this chapter, a new topology for Direct-Drive Wind Turbines (DDWTs) with a low-voltage generator design is presented in order to eliminate the required dc-bus capacitors or dc-link inductors. In the presented topology, the grid-side converter is replaced by a boost Current Source Inverter (CSI) therefore removing the need for the dc-bus electrolytic capacitors which results in increasing the system lifetime. In the developed topology, the synchronous inductance of the generator is utilized. This facilitates the elimination of the intrinsically required dc-link inductor in the CSI which further contributes to a reduction in the overall system weight and size. The boost CSI is capable of converting a low dc voltage to a higher line-to-line voltage. This results in the implementation of a low-voltage generator for DDWTs. The feasibility of the presented low-voltage generator is investigated through Finite Element (FE) computations. In this chapter, a modified 1.5 MW low-voltage generator for the proposed topology is compared with an existing 1.5 MW Permanent Magnet (PM) synchronous generator for DDWTs. The feasibility of the presented topology of generator-converter for DDWTs is verified through simulations and laboratory tests. Furthermore, the controls developed for the developed wind turbine topology is also presented in this chapter.",book:{id:"7766",slug:"rotating-machinery",title:"Rotating Machinery",fullTitle:"Rotating Machinery"},signatures:"Akanksha Singh",authors:[{id:"276799",title:"Dr.",name:"Akanksha",middleName:null,surname:"Singh",slug:"akanksha-singh",fullName:"Akanksha Singh"}]},{id:"66758",title:"Advance Measurement Techniques in Turbomachines",slug:"advance-measurement-techniques-in-turbomachines",totalDownloads:686,totalCrossrefCites:0,totalDimensionsCites:0,abstract:"This chapter focuses on advanced measurement techniques that have been used in applications of turbomachines including temperature measurements, pressure measurements, velocity measurements, and strain/stress measurements. Though the measurement techniques are fundamentally the same as those used in other applications, the unique features associated with turbomachines place challenges in implementing these techniques. This chapter covers the fundamental working principles of individual measurement technique as well as the highlights of its application in turbomachines.",book:{id:"7766",slug:"rotating-machinery",title:"Rotating Machinery",fullTitle:"Rotating Machinery"},signatures:"Fangyuan Lou",authors:[{id:"275580",title:"Dr.",name:"Fangyuan",middleName:null,surname:"Lou",slug:"fangyuan-lou",fullName:"Fangyuan Lou"}]}],onlineFirstChaptersFilter:{topicId:"821",limit:6,offset:0},onlineFirstChaptersCollection:[],onlineFirstChaptersTotal:0},preDownload:{success:null,errors:{}},subscriptionForm:{success:null,errors:{}},aboutIntechopen:{},privacyPolicy:{},peerReviewing:{},howOpenAccessPublishingWithIntechopenWorks:{},sponsorshipBooks:{sponsorshipBooks:[],offset:0,limit:8,total:null},allSeries:{pteSeriesList:[],lsSeriesList:[],hsSeriesList:[],sshSeriesList:[],testimonialsList:[]},series:{item:{id:"11",title:"Biochemistry",doi:"10.5772/intechopen.72877",issn:"2632-0983",scope:"Biochemistry, the study of chemical transformations occurring within living organisms, impacts all areas of life sciences, from molecular crystallography and genetics to ecology, medicine, and population biology. Biochemistry examines macromolecules - proteins, nucleic acids, carbohydrates, and lipids – and their building blocks, structures, functions, and interactions. Much of biochemistry is devoted to enzymes, proteins that catalyze chemical reactions, enzyme structures, mechanisms of action and their roles within cells. Biochemistry also studies small signaling molecules, coenzymes, inhibitors, vitamins, and hormones, which play roles in life processes. Biochemical experimentation, besides coopting classical chemistry methods, e.g., chromatography, adopted new techniques, e.g., X-ray diffraction, electron microscopy, NMR, radioisotopes, and developed sophisticated microbial genetic tools, e.g., auxotroph mutants and their revertants, fermentation, etc. More recently, biochemistry embraced the ‘big data’ omics systems. Initial biochemical studies have been exclusively analytic: dissecting, purifying, and examining individual components of a biological system; in the apt words of Efraim Racker (1913 –1991), “Don’t waste clean thinking on dirty enzymes.” Today, however, biochemistry is becoming more agglomerative and comprehensive, setting out to integrate and describe entirely particular biological systems. The ‘big data’ metabolomics can define the complement of small molecules, e.g., in a soil or biofilm sample; proteomics can distinguish all the comprising proteins, e.g., serum; metagenomics can identify all the genes in a complex environment, e.g., the bovine rumen. This Biochemistry Series will address the current research on biomolecules and the emerging trends with great promise.",coverUrl:"https://cdn.intechopen.com/series/covers/11.jpg",latestPublicationDate:"May 26th, 2022",hasOnlineFirst:!0,numberOfPublishedBooks:27,editor:{id:"31610",title:"Dr.",name:"Miroslav",middleName:null,surname:"Blumenberg",slug:"miroslav-blumenberg",fullName:"Miroslav Blumenberg",profilePictureURL:"https://mts.intechopen.com/storage/users/31610/images/system/31610.jpg",biography:"Miroslav Blumenberg, Ph.D., was born in Subotica and received his BSc in Belgrade, Yugoslavia. He completed his Ph.D. at MIT in Organic Chemistry; he followed up his Ph.D. with two postdoctoral study periods at Stanford University. Since 1983, he has been a faculty member of the RO Perelman Department of Dermatology, NYU School of Medicine, where he is codirector of a training grant in cutaneous biology. Dr. Blumenberg’s research is focused on the epidermis, expression of keratin genes, transcription profiling, keratinocyte differentiation, inflammatory diseases and cancers, and most recently the effects of the microbiome on the skin. He has published more than 100 peer-reviewed research articles and graduated numerous Ph.D. and postdoctoral students.",institutionString:null,institution:{name:"New York University Langone Medical Center",institutionURL:null,country:{name:"United States of America"}}},editorTwo:null,editorThree:null},subseries:{paginationCount:10,paginationItems:[{id:"14",title:"Cell and Molecular Biology",coverUrl:"https://cdn.intechopen.com/series_topics/covers/14.jpg",editor:{id:"165627",title:"Dr.",name:"Rosa María",middleName:null,surname:"Martínez-Espinosa",slug:"rosa-maria-martinez-espinosa",fullName:"Rosa María Martínez-Espinosa",profilePictureURL:"https://mts.intechopen.com/storage/users/165627/images/system/165627.jpeg",biography:"Dr. Rosa María Martínez-Espinosa has been a Spanish Full Professor since 2020 (Biochemistry and Molecular Biology) and is currently Vice-President of International Relations and Cooperation development and leader of the research group 'Applied Biochemistry” (University of Alicante, Spain). Other positions she has held at the university include Vice-Dean of Master Programs, Vice-Dean of the Degree in Biology and Vice-Dean for Mobility and Enterprise and Engagement at the Faculty of Science (University of Alicante). She received her Bachelor in Biology in 1998 (University of Alicante) and her PhD in 2003 (Biochemistry, University of Alicante). She undertook post-doctoral research at the University of East Anglia (Norwich, U.K. 2004-2005; 2007-2008).\nHer multidisciplinary research focuses on investigating archaea and their potential applications in biotechnology. She has an H-index of 21. She has authored one patent and has published more than 70 indexed papers and around 60 book chapters.\nShe has contributed to more than 150 national and international meetings during the last 15 years. Her research interests include archaea metabolism, enzymes purification and characterization, gene regulation, carotenoids and bioplastics production, antioxidant\ncompounds, waste water treatments, and brines bioremediation.\nRosa María’s other roles include editorial board member for several journals related\nto biochemistry, reviewer for more than 60 journals (biochemistry, molecular biology, biotechnology, chemistry and microbiology) and president of several organizing committees in international meetings related to the N-cycle or respiratory processes.",institutionString:null,institution:{name:"University of Alicante",institutionURL:null,country:{name:"Spain"}}},editorTwo:null,editorThree:null,editorialBoard:[{id:"79367",title:"Dr.",name:"Ana Isabel",middleName:null,surname:"Flores",slug:"ana-isabel-flores",fullName:"Ana Isabel Flores",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRpIOQA0/Profile_Picture_1632418099564",institutionString:null,institution:{name:"Hospital Universitario 12 De Octubre",institutionURL:null,country:{name:"Spain"}}},{id:"328234",title:"Ph.D.",name:"Christian",middleName:null,surname:"Palavecino",slug:"christian-palavecino",fullName:"Christian Palavecino",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0033Y000030DhEhQAK/Profile_Picture_1628835318625",institutionString:null,institution:{name:"Central University of Chile",institutionURL:null,country:{name:"Chile"}}},{id:"186585",title:"Dr.",name:"Francisco Javier",middleName:null,surname:"Martin-Romero",slug:"francisco-javier-martin-romero",fullName:"Francisco Javier Martin-Romero",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bSB3HQAW/Profile_Picture_1631258137641",institutionString:null,institution:{name:"University of Extremadura",institutionURL:null,country:{name:"Spain"}}}]},{id:"15",title:"Chemical Biology",coverUrl:"https://cdn.intechopen.com/series_topics/covers/15.jpg",editor:{id:"441442",title:"Dr.",name:"Şükrü",middleName:null,surname:"Beydemir",slug:"sukru-beydemir",fullName:"Şükrü Beydemir",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0033Y00003GsUoIQAV/Profile_Picture_1634557147521",biography:"Dr. Şükrü Beydemir obtained a BSc in Chemistry in 1995 from Yüzüncü Yıl University, MSc in Biochemistry in 1998, and PhD in Biochemistry in 2002 from Atatürk University, Turkey. He performed post-doctoral studies at Max-Planck Institute, Germany, and University of Florence, Italy in addition to making several scientific visits abroad. He currently works as a Full Professor of Biochemistry in the Faculty of Pharmacy, Anadolu University, Turkey. Dr. Beydemir has published over a hundred scientific papers spanning protein biochemistry, enzymology and medicinal chemistry, reviews, book chapters and presented several conferences to scientists worldwide. He has received numerous publication awards from various international scientific councils. He serves in the Editorial Board of several international journals. Dr. Beydemir is also Rector of Bilecik Şeyh Edebali University, Turkey.",institutionString:null,institution:{name:"Anadolu University",institutionURL:null,country:{name:"Turkey"}}},editorTwo:{id:"13652",title:"Prof.",name:"Deniz",middleName:null,surname:"Ekinci",slug:"deniz-ekinci",fullName:"Deniz Ekinci",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002aYLT1QAO/Profile_Picture_1634557223079",biography:"Dr. Deniz Ekinci obtained a BSc in Chemistry in 2004, MSc in Biochemistry in 2006, and PhD in Biochemistry in 2009 from Atatürk University, Turkey. He studied at Stetson University, USA, in 2007-2008 and at the Max Planck Institute of Molecular Cell Biology and Genetics, Germany, in 2009-2010. Dr. Ekinci currently works as a Full Professor of Biochemistry in the Faculty of Agriculture and is the Head of the Enzyme and Microbial Biotechnology Division, Ondokuz Mayıs University, Turkey. He is a member of the Turkish Biochemical Society, American Chemical Society, and German Genetics society. Dr. Ekinci published around ninety scientific papers, reviews and book chapters, and presented several conferences to scientists. He has received numerous publication awards from several scientific councils. Dr. Ekinci serves as the Editor in Chief of four international books and is involved in the Editorial Board of several international journals.",institutionString:null,institution:{name:"Ondokuz Mayıs University",institutionURL:null,country:{name:"Turkey"}}},editorThree:null,editorialBoard:[{id:"241413",title:"Dr.",name:"Azhar",middleName:null,surname:"Rasul",slug:"azhar-rasul",fullName:"Azhar Rasul",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRT1oQAG/Profile_Picture_1635251978933",institutionString:null,institution:{name:"Government College University, Faisalabad",institutionURL:null,country:{name:"Pakistan"}}},{id:"178316",title:"Ph.D.",name:"Sergey",middleName:null,surname:"Sedykh",slug:"sergey-sedykh",fullName:"Sergey Sedykh",profilePictureURL:"https://mts.intechopen.com/storage/users/178316/images/system/178316.jfif",institutionString:null,institution:{name:"Novosibirsk State University",institutionURL:null,country:{name:"Russia"}}}]},{id:"17",title:"Metabolism",coverUrl:"https://cdn.intechopen.com/series_topics/covers/17.jpg",editor:{id:"138626",title:"Dr.",name:"Yannis",middleName:null,surname:"Karamanos",slug:"yannis-karamanos",fullName:"Yannis Karamanos",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002g6Jv2QAE/Profile_Picture_1629356660984",biography:"Yannis Karamanos, born in Greece in 1953, completed his pre-graduate studies at the Université Pierre et Marie Curie, Paris, then his Masters and Doctoral degree at the Université de Lille (1983). He was associate professor at the University of Limoges (1987) before becoming full professor of biochemistry at the Université d’Artois (1996). He worked on the structure-function relationships of glycoconjugates and his main project was the investigations on the biological roles of the de-N-glycosylation enzymes (Endo-N-acetyl-β-D-glucosaminidase and peptide-N4-(N-acetyl-β-glucosaminyl) asparagine amidase). From 2002 he contributes to the understanding of the Blood-brain barrier functioning using proteomics approaches. He has published more than 70 papers. His teaching areas are energy metabolism and regulation, integration and organ specialization and metabolic adaptation.",institutionString:null,institution:{name:"Artois University",institutionURL:null,country:{name:"France"}}},editorTwo:null,editorThree:null,editorialBoard:[{id:"243049",title:"Dr.",name:"Anca",middleName:null,surname:"Pantea Stoian",slug:"anca-pantea-stoian",fullName:"Anca Pantea Stoian",profilePictureURL:"https://mts.intechopen.com/storage/users/243049/images/system/243049.jpg",institutionString:null,institution:{name:"Carol Davila University of Medicine and Pharmacy",institutionURL:null,country:{name:"Romania"}}},{id:"203824",title:"Dr.",name:"Attilio",middleName:null,surname:"Rigotti",slug:"attilio-rigotti",fullName:"Attilio Rigotti",profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",institutionString:null,institution:{name:"Pontifical Catholic University of Chile",institutionURL:null,country:{name:"Chile"}}},{id:"300470",title:"Dr.",name:"Yanfei (Jacob)",middleName:null,surname:"Qi",slug:"yanfei-(jacob)-qi",fullName:"Yanfei (Jacob) Qi",profilePictureURL:"https://mts.intechopen.com/storage/users/300470/images/system/300470.jpg",institutionString:null,institution:{name:"Centenary Institute of Cancer Medicine and Cell Biology",institutionURL:null,country:{name:"Australia"}}}]},{id:"18",title:"Proteomics",coverUrl:"https://cdn.intechopen.com/series_topics/covers/18.jpg",editor:{id:"200689",title:"Prof.",name:"Paolo",middleName:null,surname:"Iadarola",slug:"paolo-iadarola",fullName:"Paolo Iadarola",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bSCl8QAG/Profile_Picture_1623568118342",biography:"Paolo Iadarola graduated with a degree in Chemistry from the University of Pavia (Italy) in July 1972. He then worked as an Assistant Professor at the Faculty of Science of the same University until 1984. In 1985, Prof. Iadarola became Associate Professor at the Department of Biology and Biotechnologies of the University of Pavia and retired in October 2017. Since then, he has been working as an Adjunct Professor in the same Department at the University of Pavia. His research activity during the first years was primarily focused on the purification and structural characterization of enzymes from animal and plant sources. During this period, Prof. Iadarola familiarized himself with the conventional techniques used in column chromatography, spectrophotometry, manual Edman degradation, and electrophoresis). Since 1995, he has been working on: i) the determination in biological fluids (serum, urine, bronchoalveolar lavage, sputum) of proteolytic activities involved in the degradation processes of connective tissue matrix, and ii) on the identification of biological markers of lung diseases. In this context, he has developed and validated new methodologies (e.g., Capillary Electrophoresis coupled to Laser-Induced Fluorescence, CE-LIF) whose application enabled him to determine both the amounts of biochemical markers (Desmosines) in urine/serum of patients affected by Chronic Obstructive Pulmonary Disease (COPD) and the activity of proteolytic enzymes (Human Neutrophil Elastase, Cathepsin G, Pseudomonas aeruginosa elastase) in sputa of these patients. More recently, Prof. Iadarola was involved in developing techniques such as two-dimensional electrophoresis coupled to liquid chromatography/mass spectrometry (2DE-LC/MS) for the proteomic analysis of biological fluids aimed at the identification of potential biomarkers of different lung diseases. He is the author of about 150 publications (According to Scopus: H-Index: 23; Total citations: 1568- According to WOS: H-Index: 20; Total Citations: 1296) of peer-reviewed international journals. He is a Consultant Reviewer for several journals, including the Journal of Chromatography A, Journal of Chromatography B, Plos ONE, Proteomes, International Journal of Molecular Science, Biotech, Electrophoresis, and others. 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This includes, but is not limited to: single-neuron modeling, sensory processing, motor control, memory, and synaptic plasticity, attention, identification, categorization, discrimination, learning, development, axonal patterning, guidance, neural architecture, behaviors, and dynamics of networks, cognition and the neuroscientific basis of consciousness. Particularly interesting are models of various types of more compound functions and abilities, various and more general fundamental principles (e.g., regarding architecture, organization, learning, development, etc.) found at various spatial and temporal levels.",coverUrl:"https://cdn.intechopen.com/series_topics/covers/23.jpg",keywords:"Single-Neuron Modeling, Sensory Processing, Motor Control, Memory and Synaptic Pasticity, Attention, Identification, Categorization, Discrimination, Learning, Development, Axonal Patterning and Guidance, Neural Architecture, Behaviours and Dynamics of Networks, Cognition and the Neuroscientific Basis of Consciousness"},{id:"24",title:"Computer Vision",scope:"The scope of this topic is to disseminate the recent advances in the rapidly growing field of computer vision from both the theoretical and practical points of view. Novel computational algorithms for image analysis, scene understanding, biometrics, deep learning and their software or hardware implementations for natural and medical images, robotics, VR/AR, applications are some research directions relevant to this topic.",coverUrl:"https://cdn.intechopen.com/series_topics/covers/24.jpg",keywords:"Image Analysis, Scene Understanding, Biometrics, Deep Learning, Software Implementation, Hardware Implementation, Natural Images, Medical Images, Robotics, VR/AR"},{id:"25",title:"Evolutionary Computation",scope:"Evolutionary computing is a paradigm that has grown dramatically in recent years. This group of bio-inspired metaheuristics solves multiple optimization problems by applying the metaphor of natural selection. It so far has solved problems such as resource allocation, routing, schedule planning, and engineering design. Moreover, in the field of machine learning, evolutionary computation has carved out a significant niche both in the generation of learning models and in the automatic design and optimization of hyperparameters in deep learning models. This collection aims to include quality volumes on various topics related to evolutionary algorithms and, alternatively, other metaheuristics of interest inspired by nature. For example, some of the issues of interest could be the following: Advances in evolutionary computation (Genetic algorithms, Genetic programming, Bio-inspired metaheuristics, Hybrid metaheuristics, Parallel ECs); Applications of evolutionary algorithms (Machine learning and Data Mining with EAs, Search-Based Software Engineering, Scheduling, and Planning Applications, Smart Transport Applications, Applications to Games, Image Analysis, Signal Processing and Pattern Recognition, Applications to Sustainability).",coverUrl:"https://cdn.intechopen.com/series_topics/covers/25.jpg",keywords:"Genetic Algorithms, Genetic Programming, Evolutionary Programming, Evolution Strategies, Hybrid Algorithms, Bioinspired Metaheuristics, Ant Colony Optimization, Evolutionary Learning, Hyperparameter Optimization"},{id:"26",title:"Machine Learning and Data Mining",scope:"The scope of machine learning and data mining is immense and is growing every day. It has become a massive part of our daily lives, making predictions based on experience, making this a fascinating area that solves problems that otherwise would not be possible or easy to solve. This topic aims to encompass algorithms that learn from experience (supervised and unsupervised), improve their performance over time and enable machines to make data-driven decisions. It is not limited to any particular applications, but contributions are encouraged from all disciplines.",coverUrl:"https://cdn.intechopen.com/series_topics/covers/26.jpg",keywords:"Intelligent Systems, Machine Learning, Data Science, Data Mining, Artificial Intelligence"},{id:"27",title:"Multi-Agent Systems",scope:"Multi-agent systems are recognised as a state of the art field in Artificial Intelligence studies, which is popular due to the usefulness in facilitation capabilities to handle real-world problem-solving in a distributed fashion. The area covers many techniques that offer solutions to emerging problems in robotics and enterprise-level software systems. Collaborative intelligence is highly and effectively achieved with multi-agent systems. Areas of application include swarms of robots, flocks of UAVs, collaborative software management. Given the level of technological enhancements, the popularity of machine learning in use has opened a new chapter in multi-agent studies alongside the practical challenges and long-lasting collaboration issues in the field. It has increased the urgency and the need for further studies in this field. We welcome chapters presenting research on the many applications of multi-agent studies including, but not limited to, the following key areas: machine learning for multi-agent systems; modeling swarms robots and flocks of UAVs with multi-agent systems; decision science and multi-agent systems; software engineering for and with multi-agent systems; tools and technologies of multi-agent systems.",coverUrl:"https://cdn.intechopen.com/series_topics/covers/27.jpg",keywords:"Collaborative Intelligence, Learning, Distributed Control System, Swarm Robotics, Decision Science, Software Engineering"}],annualVolumeBook:{},thematicCollection:[],selectedSeries:{title:"Artificial Intelligence",id:"14"},selectedSubseries:null},seriesLanding:{item:{id:"25",title:"Environmental Sciences",doi:"10.5772/intechopen.100362",issn:"2754-6713",scope:"\r\n\tScientists have long researched to understand the environment and man’s place in it. The search for this knowledge grows in importance as rapid increases in population and economic development intensify humans’ stresses on ecosystems. Fortunately, rapid increases in multiple scientific areas are advancing our understanding of environmental sciences. Breakthroughs in computing, molecular biology, ecology, and sustainability science are enhancing our ability to utilize environmental sciences to address real-world problems.
\r\n\tThe four topics of this book series - Pollution; Environmental Resilience and Management; Ecosystems and Biodiversity; and Water Science - will address important areas of advancement in the environmental sciences. They will represent an excellent initial grouping of published works on these critical topics.
\r\n\tPollution is caused by a wide variety of human activities and occurs in diverse forms, for example biological, chemical, et cetera. In recent years, significant efforts have been made to ensure that the environment is clean, that rigorous rules are implemented, and old laws are updated to reduce the risks towards humans and ecosystems. However, rapid industrialization and the need for more cultivable sources or habitable lands, for an increasing population, as well as fewer alternatives for waste disposal, make the pollution control tasks more challenging. Therefore, this topic will focus on assessing and managing environmental pollution. It will cover various subjects, including risk assessment due to the pollution of ecosystems, transport and fate of pollutants, restoration or remediation of polluted matrices, and efforts towards sustainable solutions to minimize environmental pollution.
",annualVolume:11966,isOpenForSubmission:!0,coverUrl:"https://cdn.intechopen.com/series_topics/covers/38.jpg",editor:{id:"110740",title:"Dr.",name:"Ismail M.M.",middleName:null,surname:"Rahman",fullName:"Ismail M.M. Rahman",profilePictureURL:"https://mts.intechopen.com/storage/users/110740/images/2319_n.jpg",institutionString:null,institution:{name:"Fukushima University",institutionURL:null,country:{name:"Japan"}}},editorTwo:{id:"201020",title:"Dr.",name:"Zinnat Ara",middleName:null,surname:"Begum",fullName:"Zinnat Ara Begum",profilePictureURL:"https://mts.intechopen.com/storage/users/201020/images/system/201020.jpeg",institutionString:null,institution:{name:"Fukushima University",institutionURL:null,country:{name:"Japan"}}},editorThree:null,editorialBoard:[{id:"252368",title:"Dr.",name:"Meng-Chuan",middleName:null,surname:"Ong",fullName:"Meng-Chuan Ong",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRVotQAG/Profile_Picture_2022-05-20T12:04:28.jpg",institutionString:null,institution:{name:"Universiti Malaysia Terengganu",institutionURL:null,country:{name:"Malaysia"}}},{id:"63465",title:"Prof.",name:"Mohamed Nageeb",middleName:null,surname:"Rashed",fullName:"Mohamed Nageeb Rashed",profilePictureURL:"https://mts.intechopen.com/storage/users/63465/images/system/63465.gif",institutionString:null,institution:{name:"Aswan University",institutionURL:null,country:{name:"Egypt"}}},{id:"187907",title:"Dr.",name:"Olga",middleName:null,surname:"Anne",fullName:"Olga Anne",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bSBE5QAO/Profile_Picture_2022-04-07T09:42:13.png",institutionString:null,institution:{name:"Klaipeda State University of Applied Sciences",institutionURL:null,country:{name:"Lithuania"}}}]},{id:"39",title:"Environmental Resilience and Management",keywords:"Anthropic effects, Overexploitation, Biodiversity loss, Degradation, Inadequate Management, SDGs adequate practices",scope:"\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.
",annualVolume:11967,isOpenForSubmission:!0,coverUrl:"https://cdn.intechopen.com/series_topics/covers/39.jpg",editor:{id:"137040",title:"Prof.",name:"Jose",middleName:null,surname:"Navarro-Pedreño",fullName:"Jose Navarro-Pedreño",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRAXrQAO/Profile_Picture_2022-03-09T15:50:19.jpg",institutionString:"Miguel Hernández University of Elche, Spain",institution:null},editorTwo:null,editorThree:null,editorialBoard:[{id:"177015",title:"Prof.",name:"Elke Jurandy",middleName:null,surname:"Bran Nogueira Cardoso",fullName:"Elke Jurandy Bran Nogueira Cardoso",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRGxzQAG/Profile_Picture_2022-03-25T08:32:33.jpg",institutionString:"Universidade de São Paulo, Brazil",institution:null},{id:"211260",title:"Dr.",name:"Sandra",middleName:null,surname:"Ricart",fullName:"Sandra Ricart",profilePictureURL:"https://mts.intechopen.com/storage/users/211260/images/system/211260.jpeg",institutionString:null,institution:{name:"University of Alicante",institutionURL:null,country:{name:"Spain"}}}]},{id:"40",title:"Ecosystems and Biodiversity",keywords:"Ecosystems, Biodiversity, Fauna, Taxonomy, Invasive species, Destruction of habitats, Overexploitation of natural resources, Pollution, Global warming, Conservation of natural spaces, Bioremediation",scope:"