Landslide classifications based on material and types of movements [13].
\\n\\n
These books synthesize perspectives of renowned scientists from the world’s most prestigious institutions - from Fukushima Renewable Energy Institute in Japan to Stanford University in the United States, including Columbia University (US), University of Sidney (AU), University of Miami (USA), Cardiff University (UK), and many others.
\\n\\nThis collaboration embodied the true essence of Open Access by simplifying the approach to OA publishing for Academic editors and authors who contributed their research and allowed the new research to be made available free and open to anyone anywhere in the world.
\\n\\nTo celebrate the 50 books published, we have gathered them at one location - just one click away, so that you can easily browse the subjects of your interest, download the content directly, share it or read online.
\\n\\n\\n\\n\\n"}]',published:!0,mainMedia:null},components:[{type:"htmlEditorComponent",content:'
IntechOpen and Knowledge Unlatched formed a partnership to support researchers working in engineering sciences by enabling an easier approach to publishing Open Access content. Using the Knowledge Unlatched crowdfunding model to raise the publishing costs through libraries around the world, Open Access Publishing Fee (OAPF) was not required from the authors.
\n\nInitially, the partnership supported engineering research, but it soon grew to include physical and life sciences, attracting more researchers to the advantages of Open Access publishing.
\n\n\n\nThese books synthesize perspectives of renowned scientists from the world’s most prestigious institutions - from Fukushima Renewable Energy Institute in Japan to Stanford University in the United States, including Columbia University (US), University of Sidney (AU), University of Miami (USA), Cardiff University (UK), and many others.
\n\nThis collaboration embodied the true essence of Open Access by simplifying the approach to OA publishing for Academic editors and authors who contributed their research and allowed the new research to be made available free and open to anyone anywhere in the world.
\n\nTo celebrate the 50 books published, we have gathered them at one location - just one click away, so that you can easily browse the subjects of your interest, download the content directly, share it or read online.
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It includes seven chapters in two sections: “Calculations and Simulations in Semiconductors” and “Semiconductor Materials.” The world will emerge different after the social and economic reorganizations caused by the COVID-19 pandemic and will be even more dependent on semiconductors than ever before. New Advances in Semiconductors is a book that brings together the contributions of important researchers around the world and is able to give an idea about the different characteristics of semiconductor materials and their applications. There is a section dedicated to theory, calculations and logic and another dedicated to the development and characterization of semiconductor materials of great future interest. I really hope that this book will help to spread knowledge about this research field to other researchers and students working in this area or even to those interested in starting their more advanced studies.",isbn:"978-1-80355-682-6",printIsbn:"978-1-80355-681-9",pdfIsbn:"978-1-80355-683-3",doi:null,price:119,priceEur:129,priceUsd:155,slug:"new-advances-in-semiconductors",numberOfPages:128,isOpenForSubmission:!1,isInWos:null,isInBkci:!1,hash:"238b808626f765e883b9bff8b62eae18",bookSignature:"Alberto Adriano Cavalheiro",publishedDate:"June 15th 2022",coverURL:"https://cdn.intechopen.com/books/images_new/11158.jpg",numberOfDownloads:262,numberOfWosCitations:0,numberOfCrossrefCitations:0,numberOfCrossrefCitationsByBook:null,numberOfDimensionsCitations:0,numberOfDimensionsCitationsByBook:null,hasAltmetrics:0,numberOfTotalCitations:0,isAvailableForWebshopOrdering:!0,dateEndFirstStepPublish:"October 5th 2021",dateEndSecondStepPublish:"November 2nd 2021",dateEndThirdStepPublish:"January 1st 2022",dateEndFourthStepPublish:"March 22nd 2022",dateEndFifthStepPublish:"May 21st 2022",currentStepOfPublishingProcess:5,indexedIn:"1,2,3,4,5,6,7",editedByType:"Edited by",kuFlag:!1,featuredMarkup:null,editors:[{id:"201848",title:"Dr.",name:"Alberto Adriano",middleName:null,surname:"Cavalheiro",slug:"alberto-adriano-cavalheiro",fullName:"Alberto Adriano Cavalheiro",profilePictureURL:"https://mts.intechopen.com/storage/users/201848/images/system/201848.jpg",biography:"Alberto Adriano Cavalheiro is an associate professor at the State University of Mato Grosso do Sul (UEMS), Brazil, where he works as a permanent lecturer in the Graduate Program in Natural Resources and coordinates the LIMAN materials laboratory. He holds a bachelor\\'s, master’s, and a doctorate in Chemistry and a Licentiate of Science. He completed two postdocs with research in semiconductors and catalysts. He works in teaching, research, and extension, with a focus on chemistry and material and environmental sciences. He also coordinates the chemistry area of the Teaching Initiation Program at UEMS. He has numerous funded projects, articles in peer-reviewed journals, and book chapters to his credit. Dr. Cavalheiro has mentored several undergraduate and graduate students.",institutionString:"Mato Grosso do Sul State University",position:null,outsideEditionCount:0,totalCites:0,totalAuthoredChapters:"1",totalChapterViews:"0",totalEditedBooks:"2",institution:{name:"Mato Grosso do Sul State University",institutionURL:null,country:{name:"Brazil"}}}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,coeditorOne:null,coeditorTwo:null,coeditorThree:null,coeditorFour:null,coeditorFive:null,topics:[{id:"740",title:"Electronic Devices and Materials",slug:"electronic-devices-and-materials"}],chapters:[{id:"81253",title:"Many-Electron Problem in an Atomic Lattice Reduced Exactly to Two-Particle Pseudo-Electron Excitations: Key to Alternative First-Principles Methods",doi:"10.5772/intechopen.103045",slug:"many-electron-problem-in-an-atomic-lattice-reduced-exactly-to-two-particle-em-pseudo-electron-em-exc",totalDownloads:21,totalCrossrefCites:0,totalDimensionsCites:0,hasAltmetrics:0,abstract:"Prediction of properties of solids (semiconductors) is based almost entirely on the first-principles methods. The first principles theories are far from being perfect and new schemes are developing. In this study, we do not follow the traditional one-particle-in-effective-field concept. Instead, all Coulomb interactions between particles are treated in their original form, i.e., particle-particle discrete interactions. Two-particles Coulomb excitations theory in a crystal lattice is proposed, along with a method for calculations of physical measurables. Most important, the relevant particles are not electrons but pseudo-electrons with both the Coulomb interaction mode and the effective mass different from those of electrons. The unitary transformation represents the many-body system as an ensemble of two-pseudo-electron excitations without neglection of the terms in a Hamiltonian. The many-particle wave function, being derived in a non-trivial two-particle form, ensures a full description of exchange-correlation and screening effects, for both ground and excited states. As an example, the energy of a many-electron system and the quasiparticle energies are expressed in an elegant integral closed-form and compared with the Density Functional Theory. The proposed scheme possibly opens a new route toward the numerical evaluation of properties of many-particle systems.",signatures:"Adil-Gerai Kussow",downloadPdfUrl:"/chapter/pdf-download/81253",previewPdfUrl:"/chapter/pdf-preview/81253",authors:[{id:"443117",title:"Dr.",name:"Adil-Gerai",surname:"Kussow",slug:"adil-gerai-kussow",fullName:"Adil-Gerai Kussow"}],corrections:null},{id:"81158",title:"SOA Model and Design Guidelines in Lossless Photonic Subsystem",doi:"10.5772/intechopen.103048",slug:"soa-model-and-design-guidelines-in-lossless-photonic-subsystem",totalDownloads:47,totalCrossrefCites:0,totalDimensionsCites:0,hasAltmetrics:0,abstract:"We propose a new practical analytical model to calculate the performance of amplitude-modulated systems, including semiconductor optical amplifiers (SOA). Lower and upper-performance bounds are given in terms of signal quality factor (Q) concerning the input signal pattern. The target is to provide a design tool for gain elements included in photonic integrated circuits (PIC) to compensate for their insertion loss. This subject is a critical issue, for example, in the arrays of optical transmitters with silicon photonics modulators used for interconnection applications. Due to implementation limitations, the design of an SOA embedded in a PIC is considerably different with respect to the use of SOAs as line amplifiers in optical networks. SOA amplified spontaneous emission (ASE) and gain saturation effects have been included in the model, together with the input signal extinction ratio and the receiver electrical filter. Each degradation effect provides its own contribution to the signal integrity in terms of signal-to-noise ratio (SNR) or inter-symbol interference (ISI). The model shows that the SOA operation at low extinction ratios, typical in optical interconnect applications, is substantially different from the operation at higher extinction ratios used in transport networks. The model is validated through numerical simulations and experiments. Finally, two examples are provided for dimensioning a PIC system and optimizing the SOA parameters.",signatures:"Pantea Nadimi Goki, Antonio Tufano, Fabio Cavaliere and Luca Potì",downloadPdfUrl:"/chapter/pdf-download/81158",previewPdfUrl:"/chapter/pdf-preview/81158",authors:[{id:"2707",title:"Dr.",name:"Luca",surname:"Poti",slug:"luca-poti",fullName:"Luca Poti"},{id:"443676",title:"Dr.",name:"Pantea",surname:"Nadimi Goki",slug:"pantea-nadimi-goki",fullName:"Pantea Nadimi Goki"},{id:"447731",title:"Dr.",name:"Antonio",surname:"Tufano",slug:"antonio-tufano",fullName:"Antonio Tufano"},{id:"447733",title:"Dr.",name:"Fabio",surname:"Cavaliere",slug:"fabio-cavaliere",fullName:"Fabio Cavaliere"}],corrections:null},{id:"81346",title:"Power Reduction Using Efficient Way of Tri-State Buffer Connection",doi:"10.5772/intechopen.102643",slug:"power-reduction-using-efficient-way-of-tri-state-buffer-connection",totalDownloads:22,totalCrossrefCites:0,totalDimensionsCites:0,hasAltmetrics:0,abstract:"Clock gating is a very important technique for decreasing wasted power in digital design. One of the approaches to obtain dissipated power is an intention by the way of masking the clock pulse that is going to the unused part of the design. In this research, a comparative evaluation of current clock gating techniques on synchronous digital design changed into provided. In the new suggested design, the gated clock technology circuit is a use of tri-state buffer and gated clock. The new submodule was created by the connection of two tri-state logic used as switched to control to the design. The new suggested technique was saving more power and area. The suggested sub-module was achieved by using ASIC design methodologies. In order to implement Huffman modules, the architecture of the proposed module has been generated using Verilog HDL language. In addition, it is proved using Modalism-Altera 10.3c (Quartus II 14.1) tools. By using the tri-state technique, dynamic power and total power are decreased. The suggested technique will decrease the hardware complexity.",signatures:"Maan Hameed",downloadPdfUrl:"/chapter/pdf-download/81346",previewPdfUrl:"/chapter/pdf-preview/81346",authors:[{id:"225901",title:"Dr.",name:"Maan",surname:"Hameed",slug:"maan-hameed",fullName:"Maan Hameed"}],corrections:null},{id:"80827",title:"Theory of Charge Transport in the Illuminated Semiconductor/Liquid Junctions",doi:"10.5772/intechopen.103049",slug:"theory-of-charge-transport-in-the-illuminated-semiconductor-liquid-junctions",totalDownloads:98,totalCrossrefCites:0,totalDimensionsCites:0,hasAltmetrics:0,abstract:"The field of photoelectrochemical (PEC) cells for solar water splitting or CO2 reduction has attracted intense attention of many research groups in last 15 years. Nevertheless, a cost-effective and efficient PEC cell for hydrogen production in the large scale was not yet discovered. The core functionality of the PEC cell is provided by the semiconductor/liquid junction, creating the electrostatic field to separate the photogenerated charges. This work aims to be a starting point for a newcomer in the field providing a compact knowledge about the charge transport and electrochemistry fundamentals in semiconductor/liquid junctions in the steady state. We describe charge transport within the semiconductor and electron transfer between the semiconductor and electrolyte, followed by the effect of illumination and charge recombination on charge transport. Finally, we discuss the effects due to surface trap states and the relation of the theoretical expressions and experimental results.",signatures:"Peter Cendula",downloadPdfUrl:"/chapter/pdf-download/80827",previewPdfUrl:"/chapter/pdf-preview/80827",authors:[{id:"440070",title:"Dr.",name:"Peter",surname:"Cendula",slug:"peter-cendula",fullName:"Peter Cendula"}],corrections:null},{id:"80904",title:"Temperature Dependence of Electrical Resistivity of (III, Mn)V Diluted Magnetic Semiconductors",doi:"10.5772/intechopen.103046",slug:"temperature-dependence-of-electrical-resistivity-of-em-iii-mn-em-em-v-em-diluted-magnetic-semiconduc",totalDownloads:34,totalCrossrefCites:0,totalDimensionsCites:0,hasAltmetrics:0,abstract:"In this work, a theory of temperature dependence of electrical resistivity is developed, with a particular emphasis on dilute magnetic semiconductors (DMSs). The approach is based on the equation of motion of the Ruderman-Kittel-Kasuya-Yosida (RKKY) exchange interaction and considers both spin and charge disorder. The formalism is applied to the specific case of Ga1−xMnxAs.Using the RKKY exchange interaction, the relaxation time τand the exchange interaction J are calculated. Then using spin-dependent relaxation time, electrical resistivity of the material is calculated. The electrical resistivity of Mn-doped III—V DMS is decreased with increasing temperature and magnetic impurity concentration.",signatures:"Edosa Tasisa Jira",downloadPdfUrl:"/chapter/pdf-download/80904",previewPdfUrl:"/chapter/pdf-preview/80904",authors:[{id:"443240",title:"M.Sc.",name:"Edosa",surname:"Tasisa Jira",slug:"edosa-tasisa-jira",fullName:"Edosa Tasisa Jira"}],corrections:null},{id:"81339",title:"Radiation Response of Group-IV and III-V Semiconductors Subjected to D–D and D–T Fusion Neutrons",doi:"10.5772/intechopen.103047",slug:"radiation-response-of-group-iv-and-iii-v-semiconductors-subjected-to-d-d-and-d-t-fusion-neutrons",totalDownloads:40,totalCrossrefCites:0,totalDimensionsCites:0,hasAltmetrics:0,abstract:"This work focuses on the radiation response of Group IV (Si, Ge, SiC, diamond) and III-V (GaAs, GaN, GaP, GaSb, InAs, InP, InSb, AlAs) semiconductors subjected to D–D (2.45 MeV) and D–T (14 MeV) neutrons. The response of each material has been systematically investigated through a direct calculation using nuclear cross-section libraries, MCNP6, and Geant4 numerical simulations. For the semiconductor materials considered, we have investigated in detail the reaction rates per type of reaction (elastic, inelastic, and nonelastic) and proposed an exhaustive classification and counting of all the neutron-induced events and secondary products as a function of their nature and energy. 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As a result, a geologist’s participation in landslide inventory, susceptibility, hazard, and risk mapping is critical. In landslide susceptibility, hazard, and risk mapping, mapping and analysis of previous and active landslide incidence are demanding tasks that can be used for landslide prevention and mitigation. Landslide disaster prevention and mitigation will not be effective unless the landslide-prone area is correctly mapped [1]. Landslides can bury animals and persons; demolish houses, farms, and infrastructures in a short amount of time [2] and Wubalem [3]. Hong et al. [2], Wubalem [4] are stated that within a short period, landslides can bury animals and humans, destroy houses, farms, and infrastructures. Landslide is one of the foremost destructive and dangerous natural hazards that cause numerous fatalities and economic losses worldwide [2, 5, 6, 7]. Therefore, landslide inventory, susceptibility, hazard, and risk mapping and assessment are vital to disaster loss reduction and function as a suggestion for sustainable land use planning.
The extenuation actions of landslide incidence within the planet are required determination of the causal factors, identification of prevailing landslides, and generation of landslide susceptibility, hazard, and risk map [8]. Landslide inventory mapping is extremely important to work out landslide type, failure mechanism, spatial distribution, and size in a given region. Landslide inventory is also important for landslide susceptibility, hazard, and risk mapping. Chen and Wang [9] explained that susceptibility, hazard, and risk maps of landslides are the results of the statistical relationship in between landslide governing factors and preexisting landslides. Susceptibility, hazard, and risk map of landslides are imperative for scientific support of the government’s response to land use practice and landslide hazards management [9, 10]. The landslide susceptibility or hazard mapping is not only to determine the factors that are most influential to the landslides that occurred within the region but also to appraisal the comparative influence of every landslide governing factors [9]. As stated by Chen and Wang [9], landslide susceptibility or hazard mapping is also significant to inaugurate an association between the factors and landslides to foresee the landslide hazard in the future. As a result, extensive and accurate landslide inventory mapping, as well as the creation of landslide susceptibility, hazard, and risk maps, is critical. Although the reason for landslide incidence and its mechanisms are so complex, human interventions, earthquakes, and heavy rainfall can trigger it. As Kifle [11]; Wubalem and Meten [4] stated that landslide incidence can also occur when the resistance force exceeds by driving force thanks to the destabilization of natural soil or rock slopes. This chapter is provided a summary of the sort of landslide type, factor, landslide inventory, landslide susceptibility, hazard, risk mapping, and validation approaches.
Landslide is that the movement of the mass of rock, debris, and earth downslope [12, 13, 14, 15]. Landslides are also defined as an outsized range of geotechnical phenomena under the influence of gravity. On another hand, a landslide is that the type of mass wasting activity that denotes any outward or downslope movement of soil and rock under the direct influence of gravity when the drive exceeds the resistance force of a slope [13, 14, 16]. These masses may range in size from card to entire mountainsides. Their movements may vary in velocities. Landslide as a geological hazard is caused by earthquake or eruption, rainfall, and act. This is often initiated when an area of a hill slope or sloping section of the seabed is rendered weak to support its weight. It is one of the foremost destructive natural hazards triggered by natural and man-made factors like an earthquake, rainfall [17], and act like an improper/poor quarry, and road construction/inadequate maintenance in mountainous terrain [18].
In geohazard mapping, susceptibility/vulnerability, hazard, and risk mapping are the foremost important activities to understand, mapping, and evaluating the spatiotemporal condition and level of risk because of geo-hazards. These terms have different meanings but some researchers use the terms interchangeably. Susceptibility refers to the probability of occurrence of an event within a selected type during a given location whereas hazard refers to the probability of occurrence of an event within a selected type and magnitude during a given location within a reference period. This means, susceptibility is usually used to predict the spatial occurrence of events, but the hazard is usually used to predict the spatiotemporal occurrence of events during a given terrain. The term risk refers to the expected losses or damage by events during a given region, which are the products of susceptibility, hazard, and elements in peril. Vulnerability means the degree of loss to a given element of the set of elements in peril resulting from the occurrence of natural phenomena of a given magnitude. It is expressed on a scale from 0 (no damage) to 1 (total damage). Elements at risk is potentially vulnerable of properties, population, and economic activities including public services in peril during a given area.
Landslides are usually classified based on the materials involved (rocks, debris, and soils) and on their mechanism and failure (Table 1). Other factors include groundwater content and the rate and dimension of the movement. Classifying and studying this phenomenon is important to manage damages because of the landslide. Classification of the landslide is the primary step to investigate landslides. According to Varnes [13, 19], landslides are classified based on the types of material, mode of movement, landslide activity, the rate of movement, depth, the magnitude of slide and moisture content.
Movement type | Slope material type | Source | |||
---|---|---|---|---|---|
Bedrock | Soil mass in failed slope | [13] | |||
Principal coarse | Principal fine | [13] | |||
Topples | Rock topple | Debris topple | Earth topple | [13] | |
Fall | Rock fall | Debris fall | Earth fall | [13] | |
Lateral spread | Rock spread | Debris spread | Earth spread | [13] | |
Slide | Translational slide | Rockslide | Debris slide | Earth slide | [13] |
Rotational slide | |||||
Flows | Rock flow (Deep creep) | Debris flow | Earth flow | [13] | |
Composite or complex Two or more principal types of movement in combination | [13] |
Landslide classifications based on material and types of movements [13].
Rotational landslides are more common in cohesive, homogeneous soils. The failure, which can be superficial or deep-rooted, occurs along curved surfaces concave upwards, having a shape of a spoon. Successive landslides occur mainly in stiff fissured clays with gradients similar to their angle of equilibrium and in soft very sensitive clays, where the initial landslide causes an accumulation of remolded clay, which as it flows, leaves the material higher up without support, so promoting successive failures. These failures are shallow but can have considerable lateral continuity [20]. Weak rock masses or those with a high degree of fracturing or weathering, where the structural discontinuities do not form preferred surfaces for failure may also suffer this type of successive landslides.
In translational slides, failure takes place along pre-existing planar surfaces or discontinuities (bedding planes, contact between different types of materials, structural surfaces, etc.) and sometimes the failure plane is a fine layer of clay material between more competent strata [20].
The sliding mass can be sometimes rectangular blocks that have been detached from the mass at discontinuities or tension cracks (block landslides). Translational slides generally move faster than rotational ones, because of their simple geometry of failure mechanism.
As defined by Vallejo and Ferrer [20], flows are mass movements of soil (mud or earth flows), debris (debris flows), or rock blocks (rock fragment flows) often with high water content, where the material behaves as a fluid undergoing continuous deformation but without having well-defined failure surfaces. Water is the main triggering factor because water decreases the strength of materials having low cohesion [20]. Flows mainly affect sensitive clay soils which show considerable loss of strength when mobilized; these movements are not very deep in their extent and develop on slopes <10°.
Mud or Earth flows occur in predominantly fine and homogeneous materials and may move at a speed of the many meters per second; the loss of strength is typically caused by water saturation. They are classified consistent with the sort of fabric, its strength, and its water content. Mudflows are generally small-scale and slow but sometimes especially in-saturated conditions, they are extensive and fast, with catastrophic consequences once they reach populated areas. Fine volcanic materials are particularly vulnerable to this sort of process.
Debris flows are complex movements, which include rock fragments, blocks, cobbles, and gravel in a fine-grained matrix of sands, silts, and clays. They occur on slopes covered with loose or non-consolidated material, especially where there is no vegetation cover.
Creep may be a very slow, almost imperceptible superficial movement (a few decimeters deep), which affects soils and weathered materials, causing continuous deformations that becomes progressively noticeable on slopes over time. This causes fences, walls, or posts to lean or offset and trees to be bent. Creep may be a time-dependent deformation and defines the deformational behavior of the fabric instead of the sort of movement.
Solifluction affects the saturated surface layer of slopes. This is often a slow movement produced by the freeze–thaw process because the daily or seasonal temperature variations change the water phase and water content of fine-grained soils in cold regions.
Rock falls are very quick free falls of rocks, which are dislodged from pre-existing discontinuity planes (tectonic, bedding surfaces, and tension cracks). The movement could also be by a vertical fall, by a series of bounces, or by rolling down the slope surface. They are common on steep slopes in mountainous areas, on cliffs, and generally, on rock walls and therefore the blocks are bounded by different sets of discontinuities often forming wedge-shaped blocks. The factors that cause rock falls include erosion and loss of support for previously loosened blocks in steep slopes, water pressures in discontinuities, and tension cracks and seismic shakes. Although the fallen blocks could also be relatively small in terms of volume, rock falls are sudden processes that pose a big risk to communication routes and buildings in mountainous zones and at the foot of steep slopes. Masses of soil can also fall from vertical natural and excavated slopes, thanks to the existence of tension cracks generated by tensional stresses or shrinkage cracks within the ground that has dried.
The toppling of strata or blocks of rock may be included in rock falls. Toppling occurs when the strata dip in the opposite direction to the slope and form naturally inclined blocks, which are free to rotate because of failure at the foot of the slope. Toppling tends to occur mainly on rocky slope faces, which intersect steeply dipping strata [20].
Rock avalanches are rapidly falling masses of rock and debris that detach themselves from steep slopes, sometimes amid ice or snow. The rock masses disintegrate during their fall and form deposits of very different block sizes and form deposits of very different block sizes, with no rounding from abrasion and chaotic distribution [20]. Rock avalanche deposits are unstructured and have great porosity [20]. Avalanches are generally the results of large-scale landslides or rock falls during which due to the steep gradient and therefore the lack of both structure and cohesion in their materials, travel down over steep slopes at great speed (up to 100 Km/h).
Debris avalanches are formed from rock material containing an excellent sort of sizes and should include large blocks and abundant fines [20]. Loose deposits and loose materials resulting from volcanic eruptions are susceptible to this process. The most difference with debris flows, aside from water content (which is not necessary for debris avalanches), is that the rate and speed of movement of the avalanche in areas of a steep gradient.
This sort of movement (also called lateral spreading) refers to the movement of rock blocks or coherent, cemented soil masses that rest on soft & deformable slopes. These movements are thanks to the loss of strength of the underlying material, which either flows or deformed under the load of the rigid blocks. Lateral spreading can also cause by liquefaction of the underlying material or by lateral extrusion of sentimental, wet clays under the load of the masses above them [20]. These movements occur on gentle slopes and should be very extensive.
Determining the states and distribution of landslides is extremely important to repair the consequences of landslides on infrastructures, lives, farmlands, and environments. The landslide are going to be found within the following different states of condition. Active landslide is currently moving. A suspended landslide has moved within the last twelve months but is not active at the present. A reactivated landslide is a lively landslide that has been inactive. An inactive landslide is a landslide, which did not moved at most for year.
Inactive landslides are often subdivided into these states:
A dormant landslide is an inactive landslide, which will be reactivated by its original causes or other causes.
An abandoned landslide is an inactive landslide that is not suffering from its original causes.
A stabilized landslide is an inactive landslide that has been shielded from its original causes by artificial remedial measures.
A relict landslide is an inactive landslide that developed under geomorphological or climate considerably different from those at the present.
Potential and existed landslides can be identified or recognized using different techniques considering various features that existed on the earth’s surface. Different features indicate landslide signs like
Depression at top (water ponding)
Bulging at toe Tension cracks
Water seepage (generally at toe)
Tilted and crooked trees
Change in vegetation
Change in topography
Change in drainage pattern
In hazard minimization, the evaluation of landslide conditioning and triggering factors is a very important task. Geodynamic processes affecting the earth’s surface cause mass movements of different types, sizes, and speeds [20]. Landslide movement is that the most frequent and widespread sort of mass movement generated by the gravitational downslope displacement of soil and rock masses [20]. The force of gravity and therefore the progressive weakening of geological materials, mainly thanks to weathering, alongside the action of other natural and environmental phenomena, make mass movements relatively common on the earth’s surface [20]. These processes create potential geological risks, as they will cause economic loss and social damage if they affect human activities, buildings, and infrastructure [20]. How to avoid these adverse effects is the subject of research including mass movements, their characteristics, instability mechanisms, controlling factors, and causes. To carry out this research, it is necessary to understand the characteristics and therefore the geological, geotechnical, and hydrogeological properties of the soil and rock materials involved and their mechanical behavior also because the factors that condition and trigger such movements [20]. Studies during this field should specialize in the investigation of [20]
Particular processes for the design of stabilizing measures to either mitigate or reduce damage.
Analysis of the factors, which control and trigger processes at particular locations, to stop possible movements.
Mapping either unstable or potentially unstable zones, in order that the hazardous areas are often delimited and preventive measures are often applied.
As usual, landslides might transpire when shear stress exceeds the shear strength of slope material. The factors that cause landslide have been classified as factors that contribute to an increase of the shear stress and factors that contribute to the decrease of shear strength; however, water is another factor contributing to both increasing and decreasing shear stress and shear strength of slope material respectively. Factors these increase shear stresses are included removal of lateral support; surcharge/ overloading, transitory earth stress, regional tilting, removal of underline support, and increase in lateral pressure. The factors that contribute to the decrease of shear strength of slope material include factors like initial state or inherent characteristics of materials and the changing or variable factors that tend to lower the shear strength of a material. On other hand, factors that control landslides are classified into two such as intrinsic/inherent/static and external/dynamic landslide factors [21, 22, 23].
According to Anbalangan [21], and Raghuvashi et al. [24], intrinsic parameters are the inherent controlling factors that outline the favorable or unfavorable condition within the slope. These include slope material, slope geometry, structural discontinuity, land use/cover, and groundwater. These factors have an excellent influence to decrease the strength of the slope material. Hence, mapping and perception of their impression are crucial for slope stability analysis.
The kind of fabric during a slope is closely associated with the sort of instability. Different lithology are going to be showed different degrees of susceptibility to potential slippage or failure. The stress–strain behavior of materials is governed by their strength properties, which also depend upon the presence of water. Sorts of failure and therefore the location of failure surfaces depend upon factors like alternating materials of various lithology, the extent of weathering, and therefore the presence of layers of sentimental material or hard strata. Soils, which are considered homogeneous materials, compared to rock masses, instability could also be generated by differences within the degree of compaction, cementation, and grain size, which can make sure areas more vulnerable to weakness and water flow. In rock masses, characterization and analysis of slope behavior are further complicated by the presence of layers of strata with differing strengths and properties [20].
Geological structures or discontinuities play a definitive role in conditioning the slope stability in rock masses. A mixture of structural elements and geometric slope parameters, like height, gradient, and orientation, defines problems, which will occur. The spatial distribution of discontinuities is that the structure of the rock mass [20]. The presence of those surfaces of weakness (bedding surfaces, joints, and faults) dipping towards the slope face implies the existence of potential failure planes on which sliding can readily occur.
The orientation and spatial distribution of discontinuities will condition the sort and mechanism of the instability. A specific system of fracturing will condition both the direction of movement and therefore the size of blocks susceptible to slide or the presence of a fault dipping towards a slope face will limit the unstable area. Structural changes and singularities within the rock mass, like Tectonized or shear areas, or abrupt changes within the dip of the strata, indicate heterogeneities from which failure might originate. Slope stability could also be suffering from changes to the initial conditions during excavation; for instance, the existence of tectonic in place stress related to compressive or extensional structures like folds and faults.
Most failures are caused by the effects of water in the ground, including pore pressures and erosion of the slope materials. Water is considered the worst enemy of slope stability, together with human actions where excavations are carried out without adequate geotechnical care. The presence of water in a slope reduces stability by decreasing ground strength and increasing forces, which favor instability. The main effects of water are a reduction in the shear strength of failure surfaces as effective normal stress, σ’n, decreases.
The following aspects should be known to understand the effects of water in a slope [20]: 1) Hydrogeological behavior of the materials 2) Presence of water table and piezo metric heads 3) Water flow in the slope 4) Relevant hydrogeological parameters: permeability coefficient or hydraulic conductivity, hydraulic gradient, transmissivity, and storage coefficient. One way of obtaining an approximate assessment of the entire force exerted by water on discontinuity surfaces or tension cracks is to assume the triangular distribution of hydrostatic pressure on these surfaces.
The possible failure of a slope along a surface depends on the strength, which depends on cohesion and therefore the interior angle of friction. The influence of geological history (e.g. consolidation, erosion, diagenetic processes, in situ stresses, and weathering) on the mechanical (shear strength) properties of soils must be determined considering the geological characteristics. In rock masses, mechanical behavior is decided by the strength properties of the discontinuities and therefore the intact rock counting on its degree of fracturing and the nature of the materials and discontinuities within it. The behavior of a tough rock mass generally depends on the characteristics of its discontinuities, although the lithology and its geological evolution can also play a crucial role. The shear strength of surfaces of weakness depends on their nature and origin, persistence, spacing, roughness, type and thickness of infill, and thus the presence of water.
Slope stability is highly control by in situ stresses [20]. The strain relief from decompression when the slope is excavated may transform its material properties [20]. In rock slopes, the weakest areas are often degraded and begin to behave like soft rock or granular soil. This effect is common in mudstone or mud-shale slopes subjected to high in place stresses; the rock formation is weakened into a granular material with cement-sized fragments several meters thick inside the slope, resulting in disintegration and collapse of the slope.
Slope morphometry refers to the steepness of the slope, which controls not only the strain distribution inside the slope mass but also affects weathering layer depth and surface runoff [25]. As reported by Lai [25], the degree and height of the slope influence the quantity of runoff and thus the extent of erosion. The steeper the slope, the upper velocity of water flowing down a slope and have higher erosive power. Thus, the slope material that supports the slope are getting to be removed and heighten the slope instability problem.
Aspect is that the orientation of the slope. Different slope direction has different weather, land cover, and radiation intensity that affects the exposure of the slope to radiation, wind impact, and rainfall [26, 27].
Curvature is that the measure of the roughness of a given terrain. The curvature may ask the concaveness, concaveness, and flatness of a slope. According to Pradhan [28, 29]; Alkhasawneh et al. [30], as cited in Meten et al. [26] the negative value refers to the valley, the positive value refers to Capitol Hill slope, and zero/ approaches zero value refers to flat acreage. The curvature condition controls the hydraulic condition and thus the consequences of gravity for slope stability.
External triggering factors are dynamic factors, which may trigger slope movement by increasing driving force. These triggering factors include rainfall, seismic and act. Static and dynamic loads exerted on slopes modify the force distribution and may produce instability. Static loads include the load of structures or buildings on a slope or loads derived from fills, waste dumps, or heavy vehicles, and when these loads are exerted on the slope head, they create a further weight, which will contribute to the destabilizing forces. Dynamic loads are mainly thanks to natural or induced seismicity and vibrations caused by nearby blasting. These mainly affect jointed rock masses by opening up pre-existing discontinuities, reducing their shear strength, and displacing rock blocks, which can then fall. Dynamic forces produced by an action earthquake can be given as a function of the maximum horizontal acceleration. Precipitation and climate regime influence slope stability by modifying groundwater content. The strength of the soil mass becomes loss due to changes in soil structure by alternating periods of rainfall and drought.
Man Made Factors: Abebe et al. [31]; Kifle [11, 32] is explained that the demand for new land for infrastructure, settlement, and agriculture are primary means in which humans can contribute to slope instability condition through the excavation of slope toe or slope faces, loading of slope crest, drawdown (or reservoirs), irrigation, mining, artificial vibration, deforestation, and water leakage from utilities.
Landslide inventory is that the simplest sort of landslide map [33]. The landslide inventory map portrays the spatial distribution, frequency, activity, size, time, type, displace material, the intensity of injury, and density of landslide. It is often used because the base for future landslide susceptibility, hazard, and risk prediction by evaluating the connection between the prevailing landslide event and landslide driving factors [34]. Besides, landslide inventory is often used to evaluate the accuracy and performance of the landslide susceptibility, hazard, and risk maps. Landslide inventory map shows the past and current landslide incidences, which may be prepared using various techniques like the aerial photograph, Google Earth imagery, field investigation, and evaluation of archive data including GIS tools. Depend upon the aim, the size of the base map or aerial photograph, the extent of the study area, and therefore the availability of resources, a landslide inventory map are often prepared using different techniques as expressed above [35]. For instance, a small-scale landslide inventory map (1,25,000) landslide inventory maps are often prepared for a selected area using aerial photographs at the size of >1:20,000, Google Earth Imagery analysis, and extensive fieldwork [3, 4, 36, 37]. The Google Earth Imagery may be a free tool that helps not only to spot statistic landslide boundary but also wont to determine the area coverage, perimeter, and distance of slope material movement compared to other techniques, however, it needs field for verification purpose. As a result, currently, from the active and old landslide scarps, researchers intended to spot historical landslides using statistic Google Earth Imagery analysis instead of an aerial photograph. Depend upon the dimensions of the landslide and therefore the mapping scale, active and old landslide boundaries are often digitized into polygons employing a GIS tool with the assistance of Google Earth Imagery, and eventually, a landslide inventory map are often produced. The landslide inventory is going to be classified as training data sets and testing landslide data sets (Figure 1). Most of the researchers classified landslides into 70% for training data sets and 30% for testing landslide data sets [26, 38, 39, 40]. As shown in Figures 2–4, Google Earth Imagery analysis is so effective for landslide inventory mapping. Landslide investigation is an important task in landslide disaster reduction strategies. It can be conducted to determine and predict old, active, and future landslide incidence by examining land features. For example, field survey is used to evaluate slope gradient, geomorphology, geology, drainage, nature of soil, land use land cover, surface and subsurface water, geodynamic process, old and active landslide conditions. Generally, the methods or techniques that used to investigate landslides are summarized in Table 2.
Landslide inventory map of the study area [
Landslide in Chemoga catchment, northwestern Ethiopia.
Landslide in Woldia area, northwestern Ethiopia.
Landslide in Dessie town, Ethiopia.
Scop | Phase of study | Methods or thechniques | Objectives |
---|---|---|---|
Regional landslide study | Preliminary | Review of existing information and existing maps. Google Earth Imagery analysis, Interpretation of aerial photos and remote sensing. | Identify processes and type of movements. Identify conditioning factors. General evaluation of stability of the area. Indentify location and boundary of landslide. |
General study | Field observations. Processes mapping. Factors mapping. | ||
Conducted to investigate landslides or slope failure for specific area | Study of process and causal factors | Field surveys. Preliminary underground investigation: geophysical methods. | Describe and classify processes and materials. Susceptibility analysis based on the existing processes and concurrence of conditioning factors. Record landslide type, location, magnitude, frequency, dimention, damage, and element at risk. |
Detail investigation | Boreholes, geophysical methods, in situ tests, sampling, Laboratory tests. | Describe and classify movements. Collect morphological, geological, hydrogeological and geomechanical data. | |
Monitoring | Inclinometers, extensometers, tiltometers, piezometers. | Collect data on speed, direction, stability analysis using Limit equilibrium methods and Stress–strain numerical models. Determine situation of failure planes, water pressures. | |
Stability analysis | Limit equilibrium methods. Stress–strain numerical models. | Define failure models and failure mechanisms. Evaluate stability. Design corrective measures. |
Summary of landslide investigation techniques [20].
Landslide susceptibility may be a quantitative or qualitative evaluation of landslide occurrence of a specific type in a given location that is wont to predict spatial distribution, classification, and area of existed or potentially prone area [12, 37]. However, a landslide hazard map is employed to predict future spatial and temporal landslide occurrence with a specific type and magnitude. Although both landslide susceptibility and hazard map are different concepts, many researchers are used the terms as interchangeable. The researchers consider their susceptibility map as a hazard map during which magnitude and frequency did not consider in their model generation. The landslide risk map is employed to predict the expected spatial and temporal losses or damage by landslide incidences during a given region, which are the products of susceptibility or vulnerability, hazard, and elements in danger. Although landslide susceptibility, hazard, and risk maps are the results of the connection between landslide events and sets of landslide factors supported expert judgment or statistical analysis, hazard and risk maps become differ by some input parameters. For instance, a landslide hazard map will have additional landslide frequency, and magnitude input parameters whereas for a risk map, both susceptibility and hazard map become input parameters besides, the element in danger. As stated by Wubalem [3], landslide susceptibility and hazard map results from the sum of all weighted landslide factors employing a raster calculator or weighted overlay method in ArcGIS. Compare to landslide susceptibility mapping, landslide hazard mapping required excellent landslide inventories that contain magnitude, date of occurrence, and frequency. The shortage of frequency, date of occurrence, and magnitude of landslide, landslide hazard mapping become a difficult task. Thus, landslide research trends are shifted to landslide susceptibility mapping for the last twenty century. Now a day, thanks to technological advancement, landslide hazard mapping becomes a simple task for that area frequently suffering from landslide incidence. Lithological, geomorphological, geological structure, hydrological, climatological, anthropological, seismic, and land use/cover parameters and detailed landslide inventories are the foremost important input variables in GIS-based landslide susceptibility mapping. However, landslide frequency and magnitude are additional parameters in landslide hazard mapping. The susceptibility, hazard, and risk map produced from the expert judgment have a subjective problem for weight rating of the consequences of sets of parameters; however, the statistical analysis helps to develop maps supported the statistical relationship between sets of parameters and past or current landslide inventory data. Detailed landslide susceptibility, hazard, and risk map are often also developed for selected purpose at large scales using physical-based approaches. During this case, geotechnical properties of soil or rock slope material, angle of slope, and pore water pressure are the foremost important parameters to get a landslide susceptibility map supported the extent of an element of safety. Then, the hazard map are often produced by considering the factor of safety, landslide frequency, and magnitude. The danger map also can produce on large scale. Finally, the accuracy of the small-scale and detailed models are often validated using landslide inventory data using different techniques.
Landslide susceptibility or hazard zonation is a technique used to classify the slope into zones based on the level of actual or potential landslide susceptibility and hazard. Landslide susceptibility and hazard zonation are important for a rapid assessment of slope stability over a large area [21]. Landslide susceptibility map can forecast/provide important information about the spatial future landslide occurrence [3]. However, a landslide hazard map can forecast the spatial and temporal future landslide occurrence. In landslide susceptibility and hazard mapping, several approaches are developed, which may be categorized into qualitative, semi-quantitative, and quantitative methods [41, 42, 43, 44, 45].
The expert evaluation method is a widely used technique, but a relatively subjective approach that explains the level of landslide condition in a descriptive expression based on the decision of the expert. Qualitative methods are an expert-driven approach, which required field experience specialists [41, 43, 45, 46, 47, 48, 49]. Field geomorphological analysis, landslide inventory analysis, and parameter assignment superimposition are the main activities for qualitative landslide susceptibility, and hazard mapping. Relying on the experience and professional background knowledge of experts and subjectivity is the drawback of these methods [41, 43, 45, 46, 47, 49]. This method has included heuristic, landslide inventory mapping, landslide hazard evaluation factor and slope stability evaluation parameter.
This method is opinion based that is used to classify landslide susceptibility and hazard maps by mapping all landslide factors, and landslide through proper rating each factor classes to prepare a landslide susceptibility and hazard map. The demerits of this method are its subjectivity.
Inventory is a simple method, which records the location and dimension of events occurred in the given area [50]. Landslide inventory is the way that used to record landslide location, size, occurrence time, displace material and types of slope failure. This method has used as the base for landslide susceptibility, hazard, and risk assessments; however, it does not provide the spatial relationship between landslide and sets of landslide factors rather than it only shows the location and volume of a landslide [51]. In this approach, landslide data can obtain through field mapping, historical record, satellite image or Google Earth Imagery analysis, and aerial photograph interpretation [36, 52].
According to Anbalagan [21] this method is used for landslide susceptibility and hazard zonation /mapping with consideration of the inherent controlling factors only. It is simple and cost-effective over a large area. Nevertheless, this method has the following limitations.
Has a rating of low value for groundwater effect on slope instability.
It does not account the triggering factors.
The condition of the rock mass with structural discontinuity and characteristics of the structural discontinuity (roughness, aperture, etc.) are not considered.
It is Subjective
Give the same rating for lithology and structural discontinuity but discontinuities have great influence than lithology.
Slope stability evaluation parameters (SSEP) is a landslide hazard zonation technique that is used to evaluate both inherent (slope material, slope geometry, structural discontinuity, land use and land cover, groundwater) and external factors (rainfall, seismicity, and human activity) to prepare landslide susceptibility map. Raghuvashi et al. [24], develop this method considering the dynamic and static landslide causative parameters. This technique is simple and supported by much field data but it is subjective for weighting assignment.
Semi-quantitative methods are the combination of qualitative and quantitative methods, which introduce grading and weighting of the effects of landslide factors on landslide incidence [42, 53, 54]. In this method, both qualitative and quantitative methods can be applied to evaluate the effects of landslide governing factors on landslide occurrence [55]. Analytical hierarchy process, weighted linear combination, and expert knowledge/heuristic [42, 48, 56, 57, 58, 59] are examples of semi-quantitative methods. Although some statistical concepts are introduced in this method, it depends on the expert’s experience and the background of professional knowledge and some subjectivity remains [42, 60].
According to Canoglu [61]; Chen et al. [62], the quantitative methods are grouped into three categories such as machine learning/data mining, physical-based, and statistical methods. The statistical methods are indirect methods which is extensively or routinely used to assess the association between landslide governing factors and landslides based on mathematical [9, 41]. They are classified into multivariate and bivariate statistical methods [3]. The statistical methods are provided reliable results [4, 26, 42, 63, 64, 65, 66, 67, 68, 69]. The numerical methods rely on the mathematical model, expression, and less expert judgments, which provides comparatively reliable results, unlike the qualitative method. Among quantitative methods, the statistical method is the one, which used to evaluate the spatial slope instability based on the relationship between the past/active landslide and landslide factors [70]. A statistical method is an indirect method used to prepare a landslide hazard/susceptibility map, which is considered as objective and worked by integrated GIS tool with statistical analysis based on the landslide and sets of landslide factors spatial relationship. However, in this method, the most difficult thing that we have to consider is accurate database construction, model calibration, and model validation iteration procedures [71]. In this method, each factor has mapped and overlaid over past/active landslides to carry out the contribution of each factor and subclass on the instability of the slope [24, 52, 72]. The limitation of the statistical method is its requirement for detailed and quality landslide and landslide factor data, and it is time-consuming to acquire them over a large area Raghuvashi et al. [24]. The statistical method cannot apply to the area where a landslide has not occurred. This is one of the limitations of statistical methods in landslide susceptibility, hazard, and risk mapping.
The bivariate statistical procedure is straightforward to use and update, which is capable to differentiate the consequences of every sub factor class for landslide occurrence. Within the bivariate statistical procedure, the presence of landslide has been considered because the variable and therefore the parameters that enhanced the occurrence of the landslide has been considered as the independent variable [73]. in this technique, each determinant map has been classified into sub-classes to work out the response of individual factor classes to landslide occurrence. The landslide factor classes are often combined with a landslide distribution map and weighting values supported the landslide densities of every determinant class. After weight value calculation, the weighted raster map is carefully sum up employing a raster calculator in Math algebra under the GIS tool to urge the landslide susceptibility index map. The landslide susceptibility or hazard index map are often reclassified using various methods like natural break under the GIS tool to urge the ultimate landslide susceptibility map. The benefits of bivariate statistical methods are they will cover an outsized area with effective cost; it is simple to apply; it can provide spatially distributed landslide information and its relationship with landslide factors. However, the bivariate statistical methods have the subsequent limitation 1. It cannot distinguish which factor is more influential and non-influential. 2. It cannot provides the knowledge about the inherent condition of the slope material like geotechnical method 3. It can predict the landslide susceptibility regions but it cannot be predicted when this landslide will occur and it needs landslide occurrence during a certain region to predict the opposite region which has some environmental factor. The load of evidence, information value, certainty factor, and frequency ratio is that the commonest techniques in bivariate statistical analysis.
This method will provide more realistic and accurate results. It also considers the mutual relationship among landslide factors, unlike bivariate statistical methods. The weight of causal factors indicates the relative contribution of every factor to the degree of hazard in a given land unit. The multivariate statistical procedure helps to perform multivariate statistical analysis unlike the bivariate statistical procedure. One among the merits of the multivariate method is capable to work out the influential power of individual landslide factors on landslide occurrence. Logistic regression, discriminant analysis, and cluster analysis are the foremost commonly applied techniques in this method.
In recent times, advanced data mining methods have been widely used in landslide susceptibility modeling., including random forest [56, 57, 58], boosted regression tree [74], classification and regression tree [74], Naïve Bayes [53, 75], support vector machines [32, 76], kernel LR [77], logistic model tree [56, 57, 58, 77], index of entropy [39], and artificial neural networks [56, 57, 58, 78, 79]. Data mining methods are incapable to work out the consequences of every landslide factor class, need high computing capacity, time-consuming, and therefore the internal calculation process of those methods is intensive and cannot easily be understood. Although both statistical and data mining methods have a bit little difference in the degree of predictive accuracy, they can provide reliable predictive accuracy landslide susceptibility map in landslide susceptibility or hazard mapping [78, 80].
The physical-based approach includes limit equilibrium and finite element numerical models. These methods can be applied for both soil and rock slope stability analysis. This method can provide hazard in absolute value /factor of safety or probability/quantitative results that can directly use for design purposes [52] and Raghuvashi et al. [24]. Physical-based methods are used to calculate the quantitative value of the inherent slope materials of the factor of safety over a defined area [81]. These methods can be applied when landslide types are simple (shallow landslides) and the intrinsic properties of slope material are homogeneous [81]. It requires detailed ground data such as unit weight of soil, soil strength, soil layer thickness, slope angle, pore water pressure, depth below the terrain surface, and slope height. The physical-based method has been employed over a small area, and oversimplification, data availability to acquire frequently is impossible are the drawback of these methods [81]. These methods can be focused on an on-site investigation to assess the geotechnical properties of soil/rock, soil depth, surface and subsurface water condition, the geometry of the slope, landslide location, failure mechanism, depth, and distance of landside. These methods are used to analyze slope conditions by calculating factors of safety using different software like PLAXIS and Slope/w in GeoStudio software package as two or three-dimensional models. The oversimplification of geological, geotechnical model and the difficulty to predict pore water pressure and its relationship with rainfall /snowmelt are the main problems that challenge use the of geotechnical approaches [82].
Landslide risk is the expected loss or damage due to landslide Incidences, which include fatalities, damage to properties, infrastructure, farmland, environment, interruption of services, and economic activities. As compare to landslide susceptibility, and hazard mapping, landslide risk mapping is not common so far due to it requires complex input parameters. It is a complex task due to the lack of necessary information to produce input parameters including vulnerability/susceptibility, hazard, and element at risk [33]. In addition to landslide susceptibility/vulnerability, and hazard maps, landslide risk map is very important in the regulation of land use, landslide risk management, and mitigation strategies. One has a plan to prepare a landslide risk map, it is necessary to estimate landslide susceptibility, hazard, and element at risk.
In landslide risk mapping, qualitative and quantitative techniques are commonly practiced methods. The qualitative (heuristic) method is used to estimate the level of risk in an area qualitatively, when the numerical estimation of hazard, vulnerability, and element at risk is difficult due to lack of landslide frequency, date of occurrence, and magnitude data [33, 83]. The landslide risk map can be produced based on the knowledge of experts about landslide vulnerability, hazard, and element at risk. In a quantitative approach, landslide risk can be estimated numerically using a mathematical equation developed by Varnes and IAEG Commission on landslides and other mass movements on slopes (1984). Risk = hazard*vulnerability*element at risk. Where the hazard is the probability of landslide occurrence in a particular type and magnitude in a given location within a referenced period. Vulnerability is the expected degree of loss due to landslides. Element at risk is potentially affected elements in landslide-affected areas.
In the case of model validation, landslide area has been classified based on time, space, and random partition [26, 84, 85]. The model can be validated by applied various validation techniques like predictive rate curve, success rate curve, simple overlay, a landslide percent comparison column chart, relative error, relative landslide density index (R – index), receiver operating characteristics (ROC), and landslide density.
As indicated in [26], the success rate curve can be plotted using training landslide against the landslide susceptibility or hazard or risk map area. Success rate and a predicted rate curve can be plotted using a cumulative percentage of training/testing landslide area against the cumulative percentage of the landslide susceptibility/hazard/risk map area [86]. For this purpose, the landslide susceptibility or hazard or risk index has to be reclassified into 100 classes by descending order of the value. Then landslide raster can be combined with these classes to obtain landslide pixels. Both landslide and map area pixels have converted into a cumulative percentage to plot the success and predicted rate curve. The success rate curve can be plotted using the cumulative percentage of training landslide vs. a cumulative percentage of map area while the predicted rate curve can be plotted using a cumulative percentage of testing or validation landslide area vs. map area. The success rate explains how well the model and how landslide susceptibility, hazard, and risk mapping results are classified the study area using training landslide data. The predict rate curve explains the predictive capability of the conditioning factor for the model. If the curve deflects and closes to the top left of the reference line along the diagonal, the model has higher accuracy.
As states by Pham et al., [87] and Fayez et al., [88], the landslide density has calculated using the equation of landslide density (LD). LD
Landslide susceptibility, hazard, and risk models can also be validated using the relative landslide density index, which is calculated using the following equation.
The other model validation technique relative error calculation is one of the techniques that help us to evaluate and determine the quality of the model and the number of landslides in the higher landslide susceptibility, hazard/risk classes. The higher the relative error value the poorer the model accuracy. When the relative error greater than 0.5, the model is not acceptable [90]. However when the relative error less than or equal to 0.5 and the number of landslide in the high landslide susceptibility/hazard/risk class more than half, the given model is accurate and reliable.
The ROC is the curve used to evaluate the performance of the landslide susceptibility, hazard, and risk models. ROC curve is the graphical representation of true positive rate (TPR) as y-axis and false positive rate (FPR) as x-axis. In the ROC curve, the area under the curve (AUC) is the most important diagnostic feature that helps to evaluate whether the model performance is accurate or not accurate. As stated by Yesilnacar and Topal [91], the value of AUC is usually found in between 0.5–1. The model has excellent performance when the AUC value is in between 0.9–1; the model has very good performance when the AUC value is in between 0.8–0.9. The model has good performance when the AUC value is between 0.7–0.8. When the value of AUC is between 0.6–0.7, the model has average performance however if the AUC value is between the range of 0.5–0.6 and equal to 0.5 or less than o.5, the model has poor and useless results.
Recent unconsolidated soil deposits, rugged topography, active gully, riverbank erosion, and improper land use practice characterize the study area (Uatzau), making it vulnerable to a variety of landslides, including earth fall, soil creep, weathered rockslide, soil slide, earth flow, and debris flow. Landslide susceptibility zones of the study area were determine using Frequency ratio (FR), certainty factor (CF), and information value (IV) models. These maps also depict the spatial distribution of projected landslides and the locations where they are expected to occur. The maps, on the other hand, may not be able to predict the amount of material that will be displaced, as well as the time and frequency with which the landslide will occur. The landslide susceptibility models can also helpful for preventative and mitigation measure of landslide hazard in regional land use planning [81, 82, 92, 93, 94, 95, 96]. The success rate curve and predictive rate curve were used to validate the maps using training and testing/validation landslide data sets. The success rate curve was used to assess how successfully the models identified the location and supported the landslide events that were occurring at the time [26, 96]. The prediction rate curve was created to assess how effectively the models can forecast future landslide events that are unknown [94, 96]. Within the region, steep slopes covered by very loose shallow soil deposits, closer to the stream, agricultural land on a steep slope, active gully erosion, and concave slope shapes resulted in the high and very high susceptibility classes, while the moderate susceptibility class is found in highland landscapes. Low plain landscapes and areas covered by vast weathering-resistant rock masses are into the realm of very low and low susceptibility of a region.
Zine et al. [97] stated that higher prediction accuracy (AUC = 89.05%) and AUC = 85.57%) was received using the information value and frequency ratio methods. Similarly, the frequency ratio approach outperformed the information value methods for both success rates (AUC = 83.27%) and prediction rate curve (AUC = 88.8%) in this investigation. The accuracy of the two models falls within the same ranges, which may be a good performance. The frequency ratio model revealed a slight difference in the AUC value. Qiqing et al. [40] stated that a high predictive accuracy of AUC value of 75 was received using a certainty factor model when compared to the prediction rate curve value (AUC = 64.08%) of information value model. However, their accuracy values were within the same ranges, suggesting that they performed well. Similarly, in the current model, the certainty factor model had a greater prediction rate value (AUC = 87.03%) than the information value model, which had a lower prediction rate value (AUC = 84.8%), but they both required an equivalent accuracy range, which may be a good performance. The work of Haoyuan et al. [98] supported the predictive rate value of the area under the receiver operating characteristic curve (AUC), showing that the frequency ratio and certainty factor models have the more or less similar predictive capacity, with the certainty factor model having 81.18% and the frequency ratio model having 80.14%, respectively. The Frequency ratio model, on the other hand, performed worse than the CF model. The two models in this study had essentially identical AUC values for the prediction rate curve (87.03% for the certainty factor model and 88.8% for the frequency ratio model) (Figure 5). The closer prediction capacity with AUC > 64% and AUC > 80%, respectively, fall within the range of good and extremely good performance, according to the three bivariate statistical methods in the literature and this work [91]. High and extremely high susceptibility classes encompassed nearly 20% of the research area in this study (Table 3). The landslide validation findings for the three models are more similar than they are dissimilar, and they are all in the same region of outstanding performance. Aside from that, the percentages of landslides that fall into the high and highly susceptible classes are nearly the same (60.4%, 65.5% & 68.1% for FR, CF, and IV, respectively). Because of these findings, the research effort concludes that in landslide susceptibility mapping, the three models have similar potential for identifying landslide-prone locations, although factor selection should take precedence over methodologies. However, when compared to the FR and CF approaches, the IV models’ moderate, high, and very high susceptibility area coverage exhibited minor differences in a single example. This is frequently due to flaws discovered in IV during weight rating for each factor class, i.e. when there is no landslide in a certain component class the IV results become zero. This gives a good indication of the model’s overall accuracy. FR and CF models are better for regional land use planning, landslide hazard mitigation, and prevention based on the prediction accuracy of AUC value. Although the generated maps cannot predict when and how often landslides will occur, they do show the spatial distribution of landslide risk.
Landslide susceptibility maps of frequency ratio (FR), certainty factor (CF), information value (IV) methods [
Information value method | LSI Value | LSI | Factor class area (%) | Validation data set (%) | Training data set (%) | AUC for validation landslide | AUC for training landslide |
---|---|---|---|---|---|---|---|
−0.5-0.9 | VLS | 15.5 | 3.9 | 6.3 | 0.848323 | 0.808265 | |
0.9–1.5 | LS | 24.3 | 7.9 | 11.8 | |||
1.5–2 | MS | 31.5 | 20.1 | 23.8 | |||
2.0–2.6 | HS | 21.1 | 40.8 | 31.8 | |||
2.6–4.1 | VHS | 7.6 | 27.3 | 26.3 | |||
−2.2- −0.97 | VLS | 17.8 | 4.7 | 6.0 | 0.870348 | 0.871933 | |
-0.97- −0.47 | LS | 31.0 | 12.3 | 16.4 | |||
-0.47-0.04 | MS | 28.8 | 17.5 | 24.8 | |||
0.04–0.74 | HS | 19.0 | 34.8 | 33.0 | |||
0.74–2.61 | VHS | 3.4 | 30.7 | 19.7 | |||
3.1–4.3 | VLS | 22.7 | 5.4 | 9.3 | 0.888337 | 0.832718 | |
4.3–4.8 | LS | 30.8 | 14.7 | 17.8 | |||
4.8–5.3 | MS | 22.4 | 19.5 | 20.0 | |||
5.3–6 | HS | 19.3 | 43.7 | 35.0 | |||
6–7.7 | VHS | 4.8 | 16.7 | 17.8 | |||
VLS is for very low susceptibility, LS stands for low susceptibility, MS stands for moderate susceptibility, HS stands for high susceptibility, VHS stands for very high susceptibility, LSI stands for landslide susceptibility index and AUC stands for area under the curve. |
Statistical summary of information value, certainty factor, and frequency ratio methods [36].
This chapter introduces and overview the concepts of landslide, type, factors, inventories, susceptibility, hazard, and risk. Moreover, different mapping and validation approaches were introduced. The confusing between the term susceptibility and hazard is clearly discussed. Detail and quality data should tend emphasis in getting quality landslide susceptibility, hazard, and risk maps. Field landslide investigation integrated with Google Earth Imagery analysis is vital to work out and record, the relative occurrence date, magnitude, dimension, type, and state of landslide. GIS-based landslide susceptibility, hazard, and risk mapping is suitable for regional scale where as physical based mapping is recommendable for detail landslide study where geotechnical investigation is require.
First and foremost, I want to express my gratitude to the almighty God for allowing me to complete this study project. Next, I would like to express my gratitude to my wonderful family and friends for their unwavering support during the research process. Finally, I would like to express my gratitude to the University of Gondar.
I was responsible for all aspects of the project, including the conception and design of the work, model development, statistical analysis, and interpretation of the results.
In this scenario, it is not appropriate.
Data and materials are readily available.
The corresponding author can provide all of the datasets that were utilized and analyzed during the current investigation.
There are no competing interests.
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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:"August 2nd, 2022",hasOnlineFirst:!0,numberOfPublishedBooks:33,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:4,paginationItems:[{id:"14",title:"Cell and Molecular Biology",coverUrl:"https://cdn.intechopen.com/series_topics/covers/14.jpg",isOpenForSubmission:!0,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},{id:"15",title:"Chemical Biology",coverUrl:"https://cdn.intechopen.com/series_topics/covers/15.jpg",isOpenForSubmission:!0,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},{id:"17",title:"Metabolism",coverUrl:"https://cdn.intechopen.com/series_topics/covers/17.jpg",isOpenForSubmission:!0,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},{id:"18",title:"Proteomics",coverUrl:"https://cdn.intechopen.com/series_topics/covers/18.jpg",isOpenForSubmission:!0,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. He is also Associate Editor of Biotech.",institutionString:null,institution:{name:"University of Pavia",institutionURL:null,country:{name:"Italy"}}},editorTwo:{id:"201414",title:"Dr.",name:"Simona",middleName:null,surname:"Viglio",slug:"simona-viglio",fullName:"Simona Viglio",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRKDHQA4/Profile_Picture_1630402531487",biography:"Simona Viglio is an Associate Professor of Biochemistry at the Department of Molecular Medicine at the University of Pavia. She has been working since 1995 on the determination of proteolytic enzymes involved in the degradation process of connective tissue matrix and on the identification of biological markers of lung diseases. She gained considerable experience in developing and validating new methodologies whose applications allowed her to determine both the amount of biomarkers (Desmosine and Isodesmosine) in the urine of patients affected by COPD, and the activity of proteolytic enzymes (HNE, Cathepsin G, Pseudomonas aeruginosa elastase) in the sputa of these patients. Simona Viglio was also involved in research dealing with the supplementation of amino acids in patients with brain injury and chronic heart failure. She is presently engaged in the development of 2-DE and LC-MS techniques for the study of proteomics in biological fluids. The aim of this research is the identification of potential biomarkers of lung diseases. She is an author of about 90 publications (According to Scopus: H-Index: 23; According to WOS: H-Index: 20) on peer-reviewed journals, a member of the “Società Italiana di Biochimica e Biologia Molecolare,“ and a Consultant Reviewer for International Journal of Molecular Science, Journal of Chromatography A, COPD, Plos ONE and Nutritional Neuroscience.",institutionString:null,institution:{name:"University of Pavia",institutionURL:null,country:{name:"Italy"}}},editorThree:null}]},overviewPageOFChapters:{paginationCount:42,paginationItems:[{id:"82914",title:"Glance on the Critical Role of IL-23 Receptor Gene Variations in Inflammation-Induced Carcinogenesis",doi:"10.5772/intechopen.105049",signatures:"Mohammed El-Gedamy",slug:"glance-on-the-critical-role-of-il-23-receptor-gene-variations-in-inflammation-induced-carcinogenesis",totalDownloads:15,totalCrossrefCites:0,totalDimensionsCites:0,authors:null,book:{title:"Chemokines Updates",coverURL:"https://cdn.intechopen.com/books/images_new/11672.jpg",subseries:{id:"18",title:"Proteomics"}}},{id:"82875",title:"Lipidomics as a Tool in the Diagnosis and Clinical Therapy",doi:"10.5772/intechopen.105857",signatures:"María Elizbeth Alvarez Sánchez, Erick Nolasco Ontiveros, Rodrigo Arreola, Adriana Montserrat Espinosa González, Ana María García Bores, Roberto Eduardo López Urrutia, Ignacio Peñalosa Castro, María del Socorro Sánchez Correa and Edgar Antonio Estrella Parra",slug:"lipidomics-as-a-tool-in-the-diagnosis-and-clinical-therapy",totalDownloads:9,totalCrossrefCites:0,totalDimensionsCites:0,authors:null,book:{title:"Fatty Acids - Recent Advances",coverURL:"https://cdn.intechopen.com/books/images_new/11669.jpg",subseries:{id:"17",title:"Metabolism"}}},{id:"82440",title:"Lipid Metabolism and Associated Molecular Signaling Events in Autoimmune Disease",doi:"10.5772/intechopen.105746",signatures:"Mohan Vanditha, Sonu Das and Mathew John",slug:"lipid-metabolism-and-associated-molecular-signaling-events-in-autoimmune-disease",totalDownloads:17,totalCrossrefCites:0,totalDimensionsCites:0,authors:null,book:{title:"Fatty Acids - Recent Advances",coverURL:"https://cdn.intechopen.com/books/images_new/11669.jpg",subseries:{id:"17",title:"Metabolism"}}},{id:"82483",title:"Oxidative Stress in Cardiovascular Diseases",doi:"10.5772/intechopen.105891",signatures:"Laura Mourino-Alvarez, Tamara Sastre-Oliva, Nerea Corbacho-Alonso and Maria G. 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Waisundara",profilePictureURL:"https://mts.intechopen.com/storage/users/194281/images/system/194281.jpg",biography:"Dr. Viduranga Waisundara obtained her Ph.D. in Food Science\nand Technology from the Department of Chemistry, National\nUniversity of Singapore, in 2010. She was a lecturer at Temasek Polytechnic, Singapore from July 2009 to March 2013.\nShe relocated to her motherland of Sri Lanka and spearheaded the Functional Food Product Development Project at the\nNational Institute of Fundamental Studies from April 2013 to\nOctober 2016. She was a senior lecturer on a temporary basis at the Department of\nFood Technology, Faculty of Technology, Rajarata University of Sri Lanka. She is\ncurrently Deputy Principal of the Australian College of Business and Technology –\nKandy Campus, Sri Lanka. She is also the Global Harmonization Initiative (GHI)",institutionString:"Australian College of Business & Technology",institution:{name:"Kobe College",institutionURL:null,country:{name:"Japan"}}}]},{type:"book",id:"6820",title:"Keratin",subtitle:null,coverURL:"https://cdn.intechopen.com/books/images_new/6820.jpg",slug:"keratin",publishedDate:"December 19th 2018",editedByType:"Edited by",bookSignature:"Miroslav Blumenberg",hash:"6def75cd4b6b5324a02b6dc0359896d0",volumeInSeries:2,fullTitle:"Keratin",editors:[{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"}}}]},{type:"book",id:"7978",title:"Vitamin A",subtitle:null,coverURL:"https://cdn.intechopen.com/books/images_new/7978.jpg",slug:"vitamin-a",publishedDate:"May 15th 2019",editedByType:"Edited by",bookSignature:"Leila Queiroz Zepka, Veridiana Vera de Rosso and Eduardo Jacob-Lopes",hash:"dad04a658ab9e3d851d23705980a688b",volumeInSeries:3,fullTitle:"Vitamin A",editors:[{id:"261969",title:"Dr.",name:"Leila",middleName:null,surname:"Queiroz Zepka",slug:"leila-queiroz-zepka",fullName:"Leila Queiroz Zepka",profilePictureURL:"https://mts.intechopen.com/storage/users/261969/images/system/261969.png",biography:"Prof. Dr. Leila Queiroz Zepka is currently an associate professor in the Department of Food Technology and Science, Federal University of Santa Maria, Brazil. She has more than fifteen years of teaching and research experience. She has published more than 550 scientific publications/communications, including 15 books, 50 book chapters, 100 original research papers, 380 research communications in national and international conferences, and 12 patents. She is a member of the editorial board of five journals and acts as a reviewer for several national and international journals. Her research interests include microalgal biotechnology with an emphasis on microalgae-based products.",institutionString:"Universidade Federal de Santa Maria",institution:{name:"Universidade Federal de Santa Maria",institutionURL:null,country:{name:"Brazil"}}}]},{type:"book",id:"7953",title:"Bioluminescence",subtitle:"Analytical Applications and Basic Biology",coverURL:"https://cdn.intechopen.com/books/images_new/7953.jpg",slug:"bioluminescence-analytical-applications-and-basic-biology",publishedDate:"September 25th 2019",editedByType:"Edited by",bookSignature:"Hirobumi Suzuki",hash:"3a8efa00b71abea11bf01973dc589979",volumeInSeries:4,fullTitle:"Bioluminescence - Analytical Applications and Basic Biology",editors:[{id:"185746",title:"Dr.",name:"Hirobumi",middleName:null,surname:"Suzuki",slug:"hirobumi-suzuki",fullName:"Hirobumi Suzuki",profilePictureURL:"https://mts.intechopen.com/storage/users/185746/images/system/185746.png",biography:"Dr. Hirobumi Suzuki received his Ph.D. in 1997 from Tokyo Metropolitan University, Japan, where he studied firefly phylogeny and the evolution of mating systems. He is especially interested in the genetic differentiation pattern and speciation process that correlate to the flashing pattern and mating behavior of some fireflies in Japan. He then worked for Olympus Corporation, a Japanese manufacturer of optics and imaging products, where he was involved in the development of luminescence technology and produced a bioluminescence microscope that is currently being used for gene expression analysis in chronobiology, neurobiology, and developmental biology. Dr. Suzuki currently serves as a visiting researcher at Kogakuin University, Japan, and also a vice president of the Japan Firefly Society.",institutionString:"Kogakuin University",institution:null}]}]},openForSubmissionBooks:{paginationCount:2,paginationItems:[{id:"11474",title:"Quality of Life Interventions - Magnitude of Effect and Transferability",coverURL:"https://cdn.intechopen.com/books/images_new/11474.jpg",hash:"5a6bcdaf5ee144d043bcdab893ff9e1c",secondStepPassed:!0,currentStepOfPublishingProcess:3,submissionDeadline:"July 7th 2022",isOpenForSubmission:!0,editors:[{id:"245319",title:"Ph.D.",name:"Sage",surname:"Arbor",slug:"sage-arbor",fullName:"Sage Arbor"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null},{id:"11473",title:"Social Inequality - Structure and Social Processes",coverURL:"https://cdn.intechopen.com/books/images_new/11473.jpg",hash:"cefab077e403fd1695fb2946e7914942",secondStepPassed:!0,currentStepOfPublishingProcess:3,submissionDeadline:"July 13th 2022",isOpenForSubmission:!0,editors:[{id:"313341",title:"Ph.D.",name:"Yaroslava",surname:"Robles-Bykbaev",slug:"yaroslava-robles-bykbaev",fullName:"Yaroslava Robles-Bykbaev"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null}]},onlineFirstChapters:{paginationCount:49,paginationItems:[{id:"83087",title:"Role of Cellular Responses in Periodontal Tissue Destruction",doi:"10.5772/intechopen.106645",signatures:"Nam Cong-Nhat Huynh",slug:"role-of-cellular-responses-in-periodontal-tissue-destruction",totalDownloads:4,totalCrossrefCites:0,totalDimensionsCites:0,authors:null,book:{title:"Periodontology - New Insights",coverURL:"https://cdn.intechopen.com/books/images_new/11566.jpg",subseries:{id:"1",title:"Oral Health"}}},{id:"83073",title:"Dental and Orofacial Trauma Impacts on Oral-Health-Related—Quality of Life in Children: Low- and Middle-Income Countries",doi:"10.5772/intechopen.105845",signatures:"Yolanda Malele-Kolisa, Nazia Khan, Mpho P. 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He has both an MS and Ph.D. in Biomedical Engineering. He was previously a research scientist at the University of California Los Angeles (UCLA) and visiting professor and researcher at the University of North Dakota. He is currently working in artificial intelligence and its applications in medical signal processing. In addition, he is using digital signal processing in medical imaging and speech processing. Dr. Asadpour has developed brain-computer interfacing algorithms and has published books, book chapters, and several journal and conference papers in this field and other areas of intelligent signal processing. 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Ms. Mehtab has published seven papers in international conferences and one of her papers has been accepted for publication in a reputable international journal. She has won the best paper awards in two prestigious international conferences – BAICONF 2019, and ICADCML 2021, organized in the Indian Institute of Management, Bangalore, India in December 2019, and SOA University, Bhubaneswar, India in January 2021. Besides, Ms. Mehtab has also published two book chapters in two books. Seven of her book chapters will be published in a volume shortly in 2021 by Cambridge Scholars’ Press, UK. Currently, she is working as the joint editor of two edited volumes on Time Series Analysis and Forecasting to be published in the first half of 2021 by an international house. Currently, she is working as a Data Scientist with an MNC in Delhi, India.",institutionString:"NSHM College of Management and Technology",institution:{name:"Association for Computing Machinery",country:{name:"United States of America"}}},{id:"226240",title:"Dr.",name:"Andri Irfan",middleName:null,surname:"Rifai",slug:"andri-irfan-rifai",fullName:"Andri Irfan Rifai",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/226240/images/7412_n.jpg",biography:"Andri IRFAN is a Senior Lecturer of Civil Engineering and Planning. He completed the PhD at the Universitas Indonesia & Universidade do Minho with Sandwich Program Scholarship from the Directorate General of Higher Education and LPDP scholarship. He has been teaching for more than 19 years and much active to applied his knowledge in the project construction in Indonesia. His research interest ranges from pavement management system to advanced data mining techniques for transportation engineering. He has published more than 50 papers in journals and 2 books.",institutionString:null,institution:{name:"Universitas Internasional Batam",country:{name:"Indonesia"}}},{id:"314576",title:"Dr.",name:"Ibai",middleName:null,surname:"Laña",slug:"ibai-lana",fullName:"Ibai Laña",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/314576/images/system/314576.jpg",biography:"Dr. Ibai Laña works at TECNALIA as a data analyst. He received his Ph.D. in Artificial Intelligence from the University of the Basque Country (UPV/EHU), Spain, in 2018. He is currently a senior researcher at TECNALIA. His research interests fall within the intersection of intelligent transportation systems, machine learning, traffic data analysis, and data science. He has dealt with urban traffic forecasting problems, applying machine learning models and evolutionary algorithms. He has experience in origin-destination matrix estimation or point of interest and trajectory detection. Working with large volumes of data has given him a good command of big data processing tools and NoSQL databases. He has also been a visiting scholar at the Knowledge Engineering and Discovery Research Institute, Auckland University of Technology.",institutionString:"TECNALIA Research & Innovation",institution:{name:"Tecnalia",country:{name:"Spain"}}},{id:"314575",title:"Dr.",name:"Jesus",middleName:null,surname:"L. Lobo",slug:"jesus-l.-lobo",fullName:"Jesus L. Lobo",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/314575/images/system/314575.png",biography:"Dr. Jesús López is currently based in Bilbao (Spain) working at TECNALIA as Artificial Intelligence Research Scientist. In most cases, a project idea or a new research line needs to be investigated to see if it is good enough to take into production or to focus on it. That is exactly what he does, diving into Machine Learning algorithms and technologies to help TECNALIA to decide whether something is great in theory or will actually impact on the product or processes of its projects. So, he is expert at framing experiments, developing hypotheses, and proving whether they’re true or not, in order to investigate fundamental problems with a longer time horizon. He is also able to design and develop PoCs and system prototypes in simulation. He has participated in several national and internacional R&D projects.\n\nAs another relevant part of his everyday research work, he usually publishes his findings in reputed scientific refereed journals and international conferences, occasionally acting as reviewer and Programme Commitee member. Concretely, since 2018 he has published 9 JCR (8 Q1) journal papers, 9 conference papers (e.g. ECML PKDD 2021), and he has co-edited a book. He is also active in popular science writing data science stories for reputed blogs (KDNuggets, TowardsDataScience, Naukas). Besides, he has recently embarked on mentoring programmes as mentor, and has also worked as data science trainer.",institutionString:"TECNALIA Research & Innovation",institution:{name:"Tecnalia",country:{name:"Spain"}}},{id:"103779",title:"Prof.",name:"Yalcin",middleName:null,surname:"Isler",slug:"yalcin-isler",fullName:"Yalcin Isler",position:null,profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRyQ8QAK/Profile_Picture_1628834958734",biography:"Yalcin Isler (1971 - Burdur / Turkey) received the B.Sc. degree in the Department of Electrical and Electronics Engineering from Anadolu University, Eskisehir, Turkey, in 1993, the M.Sc. degree from the Department of Electronics and Communication Engineering, Suleyman Demirel University, Isparta, Turkey, in 1996, the Ph.D. degree from the Department of Electrical and Electronics Engineering, Dokuz Eylul University, Izmir, Turkey, in 2009, and the Competence of Associate Professorship from the Turkish Interuniversity Council in 2019.\n\nHe was Lecturer at Burdur Vocational School in Suleyman Demirel University (1993-2000, Burdur / Turkey), Software Engineer (2000-2002, Izmir / Turkey), Research Assistant in Bulent Ecevit University (2002-2003, Zonguldak / Turkey), Research Assistant in Dokuz Eylul University (2003-2010, Izmir / Turkey), Assistant Professor at the Department of Electrical and Electronics Engineering in Bulent Ecevit University (2010-2012, Zonguldak / Turkey), Assistant Professor at the Department of Biomedical Engineering in Izmir Katip Celebi University (2012-2019, Izmir / Turkey). He is an Associate Professor at the Department of Biomedical Engineering at Izmir Katip Celebi University, Izmir / Turkey, since 2019. In addition to academics, he has also founded Islerya Medical and Information Technologies Company, Izmir / Turkey, since 2017.\n\nHis main research interests cover biomedical signal processing, pattern recognition, medical device design, programming, and embedded systems. He has many scientific papers and participated in several projects in these study fields. He was an IEEE Student Member (2009-2011) and IEEE Member (2011-2014) and has been IEEE Senior Member since 2014.",institutionString:null,institution:{name:"Izmir Kâtip Çelebi University",country:{name:"Turkey"}}},{id:"339677",title:"Dr.",name:"Mrinmoy",middleName:null,surname:"Roy",slug:"mrinmoy-roy",fullName:"Mrinmoy Roy",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/339677/images/16768_n.jpg",biography:"An accomplished Sales & Marketing professional with 12 years of cross-functional experience in well-known organisations such as CIPLA, LUPIN, GLENMARK, ASTRAZENECA across different segment of Sales & Marketing, International Business, Institutional Business, Product Management, Strategic Marketing of HIV, Oncology, Derma, Respiratory, Anti-Diabetic, Nutraceutical & Stomatological Product Portfolio and Generic as well as Chronic Critical Care Portfolio. A First Class MBA in International Business & Strategic Marketing, B.Pharm, D.Pharm, Google Certified Digital Marketing Professional. Qualified PhD Candidate in Operations and Management with special focus on Artificial Intelligence and Machine Learning adoption, analysis and use in Healthcare, Hospital & Pharma Domain. Seasoned with diverse therapy area of Pharmaceutical Sales & Marketing ranging from generating revenue through generating prescriptions, launching new products, and making them big brands with continuous strategy execution at the Physician and Patients level. Moved from Sales to Marketing and Business Development for 3.5 years in South East Asian Market operating from Manila, Philippines. Came back to India and handled and developed Brands such as Gluconorm, Lupisulin, Supracal, Absolut Woman, Hemozink, Fabiflu (For COVID 19), and many more. In my previous assignment I used to develop and execute strategies on Sales & Marketing, Commercialization & Business Development for Institution and Corporate Hospital Business portfolio of Oncology Therapy Area for AstraZeneca Pharma India Ltd. Being a Research Scholar and Student of ‘Operations Research & Management: Artificial Intelligence’ I published several pioneer research papers and book chapters on the same in Internationally reputed journals and Books indexed in Scopus, Springer and Ei Compendex, Google Scholar etc. Currently, I am launching PGDM Pharmaceutical Management Program in IIHMR Bangalore and spearheading the course curriculum and structure of the same. I am interested in Collaboration for Healthcare Innovation, Pharma AI Innovation, Future trend in Marketing and Management with incubation on Healthcare, Healthcare IT startups, AI-ML Modelling and Healthcare Algorithm based training module development. I am also an affiliated member of the Institute of Management Consultant of India, looking forward to Healthcare, Healthcare IT and Innovation, Pharma and Hospital Management Consulting works.",institutionString:null,institution:{name:"Lovely Professional University",country:{name:"India"}}},{id:"310576",title:"Prof.",name:"Erick Giovani",middleName:null,surname:"Sperandio Nascimento",slug:"erick-giovani-sperandio-nascimento",fullName:"Erick Giovani Sperandio Nascimento",position:null,profilePictureURL:"https://intech-files.s3.amazonaws.com/0033Y00002pDKxDQAW/ProfilePicture%202022-06-20%2019%3A57%3A24.788",biography:"Prof. Erick Sperandio is the Lead Researcher and professor of Artificial Intelligence (AI) at SENAI CIMATEC, Bahia, Brazil, also working with Computational Modeling (CM) and HPC. He holds a PhD in Environmental Engineering in the area of Atmospheric Computational Modeling, a Master in Informatics in the field of Computational Intelligence and Graduated in Computer Science from UFES. He currently coordinates, leads and participates in R&D projects in the areas of AI, computational modeling and supercomputing applied to different areas such as Oil and Gas, Health, Advanced Manufacturing, Renewable Energies and Atmospheric Sciences, advising undergraduate, master's and doctoral students. He is the Lead Researcher at SENAI CIMATEC's Reference Center on Artificial Intelligence. In addition, he is a Certified Instructor and University Ambassador of the NVIDIA Deep Learning Institute (DLI) in the areas of Deep Learning, Computer Vision, Natural Language Processing and Recommender Systems, and Principal Investigator of the NVIDIA/CIMATEC AI Joint Lab, the first in Latin America within the NVIDIA AI Technology Center (NVAITC) worldwide program. He also works as a researcher at the Supercomputing Center for Industrial Innovation (CS2i) and at the SENAI Institute of Innovation for Automation (ISI Automação), both from SENAI CIMATEC. He is a member and vice-coordinator of the Basic Board of Scientific-Technological Advice and Evaluation, in the area of Innovation, of the Foundation for Research Support of the State of Bahia (FAPESB). He serves as Technology Transfer Coordinator and one of the Principal Investigators at the National Applied Research Center in Artificial Intelligence (CPA-IA) of SENAI CIMATEC, focusing on Industry, being one of the six CPA-IA in Brazil approved by MCTI / FAPESP / CGI.br. He also participates as one of the representatives of Brazil in the BRICS Innovation Collaboration Working Group on HPC, ICT and AI. He is the coordinator of the Work Group of the Axis 5 - Workforce and Training - of the Brazilian Strategy for Artificial Intelligence (EBIA), and member of the MCTI/EMBRAPII AI Innovation Network Training Committee. He is the coordinator, by SENAI CIMATEC, of the Artificial Intelligence Reference Network of the State of Bahia (REDE BAH.IA). He leads the working group of experts representing Brazil in the Global Partnership on Artificial Intelligence (GPAI), on the theme \"AI and the Pandemic Response\".",institutionString:"Manufacturing and Technology Integrated Campus – SENAI CIMATEC",institution:null},{id:"1063",title:"Prof.",name:"Constantin",middleName:null,surname:"Volosencu",slug:"constantin-volosencu",fullName:"Constantin Volosencu",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/1063/images/system/1063.png",biography:"Prof. Dr. Constantin Voloşencu graduated as an engineer from\nPolitehnica University of Timișoara, Romania, where he also\nobtained a doctorate degree. He is currently a full professor in\nthe Department of Automation and Applied Informatics at the\nsame university. Dr. Voloşencu is the author of ten books, seven\nbook chapters, and more than 160 papers published in journals\nand conference proceedings. He has also edited twelve books and\nhas twenty-seven patents to his name. He is a manager of research grants, editor in\nchief and member of international journal editorial boards, a former plenary speaker, a member of scientific committees, and chair at international conferences. His\nresearch is in the fields of control systems, control of electric drives, fuzzy control\nsystems, neural network applications, fault detection and diagnosis, sensor network\napplications, monitoring of distributed parameter systems, and power ultrasound\napplications. He has developed automation equipment for machine tools, spooling\nmachines, high-power ultrasound processes, and more.",institutionString:'"Politechnica" University Timişoara',institution:null},{id:"221364",title:"Dr.",name:"Eneko",middleName:null,surname:"Osaba",slug:"eneko-osaba",fullName:"Eneko Osaba",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/221364/images/system/221364.jpg",biography:"Dr. Eneko Osaba works at TECNALIA as a senior researcher. He obtained his Ph.D. in Artificial Intelligence in 2015. He has participated in more than twenty-five local and European research projects, and in the publication of more than 130 papers. He has performed several stays at universities in the United Kingdom, Italy, and Malta. Dr. Osaba has served as a program committee member in more than forty international conferences and participated in organizing activities in more than ten international conferences. He is a member of the editorial board of the International Journal of Artificial Intelligence, Data in Brief, and Journal of Advanced Transportation. He is also a guest editor for the Journal of Computational Science, Neurocomputing, Swarm, and Evolutionary Computation and IEEE ITS Magazine.",institutionString:"TECNALIA Research & Innovation",institution:{name:"Tecnalia",country:{name:"Spain"}}},{id:"275829",title:"Dr.",name:"Esther",middleName:null,surname:"Villar-Rodriguez",slug:"esther-villar-rodriguez",fullName:"Esther Villar-Rodriguez",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/275829/images/system/275829.jpg",biography:"Dr. Esther Villar obtained a Ph.D. in Information and Communication Technologies from the University of Alcalá, Spain, in 2015. She obtained a degree in Computer Science from the University of Deusto, Spain, in 2010, and an MSc in Computer Languages and Systems from the National University of Distance Education, Spain, in 2012. Her areas of interest and knowledge include natural language processing (NLP), detection of impersonation in social networks, semantic web, and machine learning. Dr. Esther Villar made several contributions at conferences and publishing in various journals in those fields. Currently, she is working within the OPTIMA (Optimization Modeling & Analytics) business of TECNALIA’s ICT Division as a data scientist in projects related to the prediction and optimization of management and industrial processes (resource planning, energy efficiency, etc).",institutionString:"TECNALIA Research & Innovation",institution:{name:"Tecnalia",country:{name:"Spain"}}},{id:"49813",title:"Dr.",name:"Javier",middleName:null,surname:"Del Ser",slug:"javier-del-ser",fullName:"Javier Del Ser",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/49813/images/system/49813.png",biography:"Prof. Dr. Javier Del Ser received his first PhD in Telecommunication Engineering (Cum Laude) from the University of Navarra, Spain, in 2006, and a second PhD in Computational Intelligence (Summa Cum Laude) from the University of Alcala, Spain, in 2013. He is currently a principal researcher in data analytics and optimisation at TECNALIA (Spain), a visiting fellow at the Basque Center for Applied Mathematics (BCAM) and a part-time lecturer at the University of the Basque Country (UPV/EHU). His research interests gravitate on the use of descriptive, prescriptive and predictive algorithms for data mining and optimization in a diverse range of application fields such as Energy, Transport, Telecommunications, Health and Industry, among others. In these fields he has published more than 240 articles, co-supervised 8 Ph.D. theses, edited 6 books, coauthored 7 patents and participated/led more than 40 research projects. He is a Senior Member of the IEEE, and a recipient of the Biscay Talent prize for his academic career.",institutionString:"Tecnalia Research & Innovation",institution:{name:"Tecnalia",country:{name:"Spain"}}},{id:"278948",title:"Dr.",name:"Carlos Pedro",middleName:null,surname:"Gonçalves",slug:"carlos-pedro-goncalves",fullName:"Carlos Pedro Gonçalves",position:null,profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRcmyQAC/Profile_Picture_1564224512145",biography:'Carlos Pedro Gonçalves (PhD) is an Associate Professor at Lusophone University of Humanities and Technologies and a researcher on Complexity Sciences, Quantum Technologies, Artificial Intelligence, Strategic Studies, Studies in Intelligence and Security, FinTech and Financial Risk Modeling. He is also a progammer with programming experience in:\n\nA) Quantum Computing using Qiskit Python module and IBM Quantum Experience Platform, with software developed on the simulation of Quantum Artificial Neural Networks and Quantum Cybersecurity;\n\nB) Artificial Intelligence and Machine learning programming in Python;\n\nC) Artificial Intelligence, Multiagent Systems Modeling and System Dynamics Modeling in Netlogo, with models developed in the areas of Chaos Theory, Econophysics, Artificial Intelligence, Classical and Quantum Complex Systems Science, with the Econophysics models having been cited worldwide and incorporated in PhD programs by different Universities.\n\nReceived an Arctic Code Vault Contributor status by GitHub, due to having developed open source software preserved in the \\"Arctic Code Vault\\" for future generations (https://archiveprogram.github.com/arctic-vault/), with the Strategy Analyzer A.I. module for decision making support (based on his PhD thesis, used in his Classes on Decision Making and in Strategic Intelligence Consulting Activities) and QNeural Python Quantum Neural Network simulator also preserved in the \\"Arctic Code Vault\\", for access to these software modules see: https://github.com/cpgoncalves. He is also a peer reviewer with outsanding review status from Elsevier journals, including Physica A, Neurocomputing and Engineering Applications of Artificial Intelligence. Science CV available at: https://www.cienciavitae.pt//pt/8E1C-A8B3-78C5 and ORCID: https://orcid.org/0000-0002-0298-3974',institutionString:"University of Lisbon",institution:{name:"Universidade Lusófona",country:{name:"Portugal"}}},{id:"241400",title:"Prof.",name:"Mohammed",middleName:null,surname:"Bsiss",slug:"mohammed-bsiss",fullName:"Mohammed Bsiss",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/241400/images/8062_n.jpg",biography:null,institutionString:null,institution:null},{id:"276128",title:"Dr.",name:"Hira",middleName:null,surname:"Fatima",slug:"hira-fatima",fullName:"Hira Fatima",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/276128/images/14420_n.jpg",biography:"Dr. Hira Fatima\nAssistant Professor\nDepartment of Mathematics\nInstitute of Applied Science\nMangalayatan University, Aligarh\nMobile: no : 8532041179\nhirafatima2014@gmal.com\n\nDr. Hira Fatima has received his Ph.D. degree in pure Mathematics from Aligarh Muslim University, Aligarh India. Currently working as an Assistant Professor in the Department of Mathematics, Institute of Applied Science, Mangalayatan University, Aligarh. She taught so many courses of Mathematics of UG and PG level. Her research Area of Expertise is Functional Analysis & Sequence Spaces. She has been working on Ideal Convergence of double sequence. She has published 17 research papers in National and International Journals including Cogent Mathematics, Filomat, Journal of Intelligent and Fuzzy Systems, Advances in Difference Equations, Journal of Mathematical Analysis, Journal of Mathematical & Computer Science etc. She has also reviewed few research papers for the and international journals. She is a member of Indian Mathematical Society.",institutionString:null,institution:null},{id:"414880",title:"Dr.",name:"Maryam",middleName:null,surname:"Vatankhah",slug:"maryam-vatankhah",fullName:"Maryam Vatankhah",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Borough of Manhattan Community College",country:{name:"United States of America"}}},{id:"414879",title:"Prof.",name:"Mohammad-Reza",middleName:null,surname:"Akbarzadeh-Totonchi",slug:"mohammad-reza-akbarzadeh-totonchi",fullName:"Mohammad-Reza Akbarzadeh-Totonchi",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Ferdowsi University of Mashhad",country:{name:"Iran"}}},{id:"414878",title:"Prof.",name:"Reza",middleName:null,surname:"Fazel-Rezai",slug:"reza-fazel-rezai",fullName:"Reza Fazel-Rezai",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"American Public University System",country:{name:"United States of America"}}},{id:"426586",title:"Dr.",name:"Oladunni A.",middleName:null,surname:"Daramola",slug:"oladunni-a.-daramola",fullName:"Oladunni A. Daramola",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Federal University of Technology",country:{name:"Nigeria"}}},{id:"357014",title:"Prof.",name:"Leon",middleName:null,surname:"Bobrowski",slug:"leon-bobrowski",fullName:"Leon Bobrowski",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Bialystok University of Technology",country:{name:"Poland"}}},{id:"302698",title:"Dr.",name:"Yao",middleName:null,surname:"Shan",slug:"yao-shan",fullName:"Yao Shan",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Dalian University of Technology",country:{name:"China"}}},{id:"354126",title:"Dr.",name:"Setiawan",middleName:null,surname:"Hadi",slug:"setiawan-hadi",fullName:"Setiawan Hadi",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Padjadjaran University",country:{name:"Indonesia"}}},{id:"125911",title:"Prof.",name:"Jia-Ching",middleName:null,surname:"Wang",slug:"jia-ching-wang",fullName:"Jia-Ching Wang",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"National Central University",country:{name:"Taiwan"}}},{id:"332603",title:"Prof.",name:"Kumar S.",middleName:null,surname:"Ray",slug:"kumar-s.-ray",fullName:"Kumar S. Ray",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Indian Statistical Institute",country:{name:"India"}}},{id:"415409",title:"Prof.",name:"Maghsoud",middleName:null,surname:"Amiri",slug:"maghsoud-amiri",fullName:"Maghsoud Amiri",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Allameh Tabataba'i University",country:{name:"Iran"}}},{id:"357085",title:"Mr.",name:"P. Mohan",middleName:null,surname:"Anand",slug:"p.-mohan-anand",fullName:"P. Mohan Anand",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Indian Institute of Technology Kanpur",country:{name:"India"}}},{id:"356696",title:"Ph.D. Student",name:"P.V.",middleName:null,surname:"Sai Charan",slug:"p.v.-sai-charan",fullName:"P.V. Sai Charan",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Indian Institute of Technology Kanpur",country:{name:"India"}}},{id:"357086",title:"Prof.",name:"Sandeep K.",middleName:null,surname:"Shukla",slug:"sandeep-k.-shukla",fullName:"Sandeep K. 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Thus all studies on metabolism will be considered for publication.",coverUrl:"https://cdn.intechopen.com/series_topics/covers/17.jpg",hasOnlineFirst:!0,hasPublishedBooks:!0,annualVolume:11413,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,series:{id:"11",title:"Biochemistry",doi:"10.5772/intechopen.72877",issn:"2632-0983"},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"}}}]},onlineFirstChapters:{paginationCount:18,paginationItems:[{id:"82875",title:"Lipidomics as a Tool in the Diagnosis and Clinical Therapy",doi:"10.5772/intechopen.105857",signatures:"María Elizbeth Alvarez Sánchez, Erick Nolasco Ontiveros, Rodrigo Arreola, Adriana Montserrat Espinosa González, Ana María García Bores, Roberto Eduardo López Urrutia, Ignacio Peñalosa Castro, María del Socorro Sánchez Correa and Edgar Antonio Estrella Parra",slug:"lipidomics-as-a-tool-in-the-diagnosis-and-clinical-therapy",totalDownloads:9,totalCrossrefCites:0,totalDimensionsCites:0,authors:null,book:{title:"Fatty Acids - 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