A comparison between culture and colony count, advanced molecular, and novel biosensors-based bacterial screening approaches, adapted and modified from [5].
\r\n\tThere are a variety of approaches to reversing biodiversity loss, ranging from economic, to ecological and ethical. The utilitarian approach to conservation, bolstered by the concept of ecosystem services, can be utilized to improve the conservation case by supplementing the burgeoning biodiversity rhetoric. To address this issue, a pluralistic approach to biodiversity is required for conservation and sustainability.
",isbn:"978-1-80356-339-8",printIsbn:"978-1-80356-338-1",pdfIsbn:"978-1-80356-340-4",doi:null,price:0,priceEur:0,priceUsd:0,slug:null,numberOfPages:0,isOpenForSubmission:!1,isSalesforceBook:!1,isNomenclature:!1,hash:"ab014f8ed1669757335225786833e9a9",bookSignature:"Dr. Gopal Shukla, Dr. Jahangeer Bhat and Dr. Sumit Chakravarty",publishedDate:null,coverURL:"https://cdn.intechopen.com/books/images_new/11460.jpg",keywords:"Ecosystem Services, Intrinsic Value, Global Trends in Biodiversity Loss, Convention on Biological Diversity, Utilitarian Value, Biodiversity Conservation, Perception, In Situ and Ex Situ Conservation, Nature Conservation, Sustainable Development Goals, Drivers of Degradation, Prioritizing Biodiversity",numberOfDownloads:null,numberOfWosCitations:0,numberOfCrossrefCitations:null,numberOfDimensionsCitations:null,numberOfTotalCitations:null,isAvailableForWebshopOrdering:!0,dateEndFirstStepPublish:"February 17th 2022",dateEndSecondStepPublish:"April 22nd 2022",dateEndThirdStepPublish:"June 21st 2022",dateEndFourthStepPublish:"September 9th 2022",dateEndFifthStepPublish:"November 8th 2022",dateConfirmationOfParticipation:null,remainingDaysToSecondStep:"2 months",secondStepPassed:!0,areRegistrationsClosed:!0,currentStepOfPublishingProcess:4,editedByType:null,kuFlag:!1,biosketch:"Dr. Gopal Shukla, prior to becoming an assistant professor, has worked under NAIP (National Agricultural Innovation Project), NICRA ( National Innovations on Climate Resilient Agriculture), and SERB (Science and Engineering Research Board) projects. 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His focus of research is vegetation ecology, ethnobotany, and evaluation of ecosystem services, forest plant biodiversity, climate change, and socio-cultural issues in forestry. Dr. Jahangeer is currently working at the College of Horticulture and Forestry, Rani Lakshmi Bai Central Agricultural University, Jhansi, India.",institutionString:"Central Agricultural University",position:null,outsideEditionCount:0,totalCites:0,totalAuthoredChapters:"0",totalChapterViews:"0",totalEditedBooks:"0",institution:{name:"Central Agricultural University",institutionURL:null,country:{name:"India"}}},coeditorTwo:{id:"94999",title:"Dr.",name:"Sumit",middleName:null,surname:"Chakravarty",slug:"sumit-chakravarty",fullName:"Sumit Chakravarty",profilePictureURL:"https://mts.intechopen.com/storage/users/94999/images/system/94999.jpg",biography:"Dr. Sumit Chakravarty, Ph.D., has wide experience in forestry training, research, and development. 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The current approaches are usually not performing well in complex mixtures of opposing microorganisms and environmental conditions devoid of enrichment step. These approaches comprise old-fashioned plating and antibodies-based assays. Therefore, in the skipping of enrichment step, almost all present experiments are not satisfactorily sensitive to sense a distinct or a very small quantity of target bacteria [2]. In contrast, the approaches like hybridization-based assays (ELISA) and polymerase chain reaction (PCR) are sensitive; however, these cannot differentiate the live cells from the dead ones, thus require an augmentation step for specificity and are laborious and expensive. These restrictions can be potentially overwhelmed by developing a biosensor. Biosensor development needs a specific and sensitive bio-probe that can withstand elevated temperature, extreme pH and remain active in diverse and complicated environment. Bacteriophages being sensitive and specific to host bacterium, and showing activity in diverse ionic concentrations are potent agents in biosensor development for detection of bacteria. Phages naturally deliver specificity in recognition of particular bacterial strain to attach, and specifically sense preferred bacterial spectra. Swift recognition offered by phage-based detection can improve the tracing and remediation of bacterial contamination [3]. The main issue that comes with development of phage based biosensor is active and oriented phages immobilization on substrate surface. The benefit of phage immobilization during biosensor development is that phages remain active for long time period, retain physiological activities with high densities, and having high bacterial cells capture efficiencies. Thus, showing improved detection limits that leads to possible development of phage-based biosensor for rapid and accurate bacterial detection [4]. Bacteriophage based biosensor development involve the following phage related approaches: (i) Observing the released phage particles during lytic cycle in the presence of host bacterium, (ii) monitoring released intracellular lysed cell component in the course of phage-mediated bacterial lysis, (iii) detection of inhibited bacterial growth in the presence of specific phages, (iv) use of stained phages for bacterial capture, and (v) observing the expression of cloned reporter gene in genetically modified phages that is expressed after bacterial infection [5].
The conventional bacterial detection techniques such as colony count, bio-chemical and immunological procedures (ELISA) [6], and the modern (PCR) [7] approaches are currently widely in use; however, these approaches are time consuming as these need enrichment step. Consequently, there is a need to develop rapid and sensitive detecting methods. To this end, the use of biosensor, which can sense bacteria at diverse concentrations, are considered well applicable platform owing to their low cost, simplicity, and sensitivity [5]. Figure 1 shows different bacterial detection approaches and Table 1 summarizes comparative study of different bacterial detection methods.
Representation of various bacterial detection approaches.
Bacterial detection method | Personals | Cost and detection time | Tools | Live and dead cells detection | On spot detection | Ref. |
---|---|---|---|---|---|---|
Culture & colony count | Trained users, laborious | Cheap, 5–7 days | Simple | Yes | No | [2, 13, 14] |
PCR | Trained users, laborious, | Costly, 1–4 h | Specialized | No | No | |
ELISA | Trained users, laborious, | Costly, approx.: 4 h | High-tech | No | No | |
Nucleic acids-based-biosensor | Simple, automatic | Expensive, 0.5–2 h | Simple | No | Yes | [2, 15, 16] |
Antibodies-based-biosensor | Simple, automatic | Very expensive, 0.5–2 h | Simple | No | Yes | |
Phage-based-biosensor | Simple, Automatic | Cheap, 0.5–2 h | Simple | Yes | Yes |
A comparison between culture and colony count, advanced molecular, and novel biosensors-based bacterial screening approaches, adapted and modified from [5].
In such methods, bacteria existing in a sample are cultured on different types of media so that to confirm their existence and isolate them. Two main culturing approaches are used, quantitative and qualitative. By qualitative culturing technique, the target bacterial colonies are produced on selective or differential media. In quantitative culturing technique, the specific bacteria are propagated to form specific colonies which can be calculated to evaluate the sum of microorganisms. Finally, different biochemical tests are performed [8].
Immunological approaches, such as ELISA, depend upon the reaction of an antigen with a particular specific antibody. This method is unable to differentiate among living and dead cells and also antibodies production is very expensive [6].
Molecular procedures involve the use of DNA for the detection of target bacteria. For example, PCR, first pronounced in 1980s, is nowadays frequently used for detection of bacteria [7]. Molecular approaches are popular for their high sensitivity and rapidity. Dedicated apparatuses, skilled operators and expensive nature mark their rejection.
According to the proposed definition of biosensor by IUPAC, “Biosensor is a self-controlled imitated device, that is comprise a bio-recognition constituent (bio-prob/bio-receptor), connected to a transducer to translate the biological signal into a computer readable signal and is then presented on computer and analyzed [9] (Figure 2). The bio-probes used in general are bacteriophage, enzyme, whole cell, nucleic acid and antibody. The transducer is electrochemical, optical, or mass based, or combination of these. Typical features of biosensors include; selectivity, reproducibility, detection limit, stability, biocompatibility, sensitivity and linearity [10]. Biosensors are commonly used in medical, diagnostic, quality control, veterinary, food and dairy industry, viral and bacterial diagnostic, agriculture industry, drug production, mining, industrial waste water control, defense and military [11]. Classification of biosensor is based on the recognition element, that is, bio-probe (bacteriophage, enzyme, whole cell, nucleic acid and antibody) used or the type of transducer (electrical, optical, or thermal signals etc.) involved. A representative biosensor is comprised of analyte (target to be sensed), bio-receptor (bio-molecule that identifies the analyte), transducer (responsible for signal transduction) and electronics (display the transduced signal) [5].
Schematics representation of a generalized biosensors, reframed from [
As mentioned earlier, biosensor involves some biological recognition elements like bacteriophages [17], enzyme [18], whole cell [19], nucleic acid [20], and antibody [21], etc. These common bio-probe are briefed in the following sections:
To accomplish the requisite for up-to-date and fast bio-sensing schemes, antibodies (Abs) have become important affinity ligands to detect pathogens in clinical and food samples. Definitely, Abs when immobilized on a surface, these interact with specific antigens present on microbial surfaces, thus inducing a computable signal by an output detector. Abs popularity ascends from numerous benefits, for example, adaptability, ease of incorporation into diverse systems and are highly specific to their target antigens [21].
From the time of first biosensor (glucose sensor by Clark and Lyons in 1962), enzyme-based biosensors have shown immense progress in many applications. Enzymes are precise competent bioanalytical agents, having the ability to precisely mark out their substrates. This distinctive property mark enzymes potent implements in the development of analytical devices [18]. These biosensors company closely a biocatalyst-comprising a detecting coating with a transducer. Its operational principal is based on the catalysis and binding abilities for specific detection.
The sequence of nucleic acids for a precise detection was established in 1953 and is still developing widely [20]. These biosensors involve nucleic acids as a bio-recognition-prob. The high specific binding between the two single strands of DNA (ssDNA) sequences to make double stranded DNA (dsDNA) sequence is used to develop nucleic acids-based biosensor. This technique validated to develop DNA-built-biosensor from the old-style technique like pairing of radio iso-tropic and electrophoretic separations that are costly, dangerous, and time consuming.
These biosensors involve living cells as a bio-probe and detecting component. They are constructed on the basis of living cell ability to sense the physiological parameters, and the extracellular and intracellular micro-environmental conditions, and as a result a response is produced by the reaction between cell and stimulus [19]. Microbial cells, for example fungi and bacteria are commonly used to develop whole cell based biosensors to sense particular molecules or the inclusive “condition” of the nearby environs.
Phages are virus particles, infecting and reproducing only within bacterial cells. Because of their associated evolution along with bacteria, phages have extremely specific machineries to identify and then infect their host bacteria for propagation. Phages generally have two distinctive chunks, the head comprising genetic material while the tail accountable to recognize and attach to bacterial cell [22]. Phages have several biomedical applications, and owing to their specificity they are extensively used for specific and sensitive detection of bacteria [23]. Most significant feature of phages is that they can only identify, and attack living bacterial cells. This exciting feature was well demonstrated by Fernandes et al., to detect viable, viable but not culture-able, or totally dead
A phage as a bio-recognition probe offers numerous benefits in rapid bacterial sensing [17] as they are: (•) extremely specific to their host [26], (•) ability of producing extraordinary titers of descendant phages, (•) tolerant to extreme environmental conditions like ultrahigh temperatures, organic solvents and wide-ranging pH compared to Abs, [27], (•) safe handling, (•) discriminating among dead and live bacteria as they proliferate only in live bacterial cells [28], (•) production in bulk are artless and economical. These compensations make phages as leading bio-recognition probes to develop biosensors for bacterial screening [15]. Frequently designed phage-based biosensor schemes comprise the association of whole phage or phage-constituents, infecting/capturing target bacterial cells and ultimately resulting in the production of electrical, colorimetric, fluorescent, or luminescent etc. signals, based on the available biosensing system. Hence, phages are demonstrating themselves as novel troupes for cheap, fast, sensitive and specific bacterial detection in comparison to other available platforms [29].
Reporter bacteriophages are genetically edited phages used to import and insert a specific gene into the genome of target bacteria. The foreign gene inserted to host bacteria is expressed, bacteria are marked based on available platforms as a colorimetric, optical, or as a fluorescent marker and thus bacterial screening is permitted [30]. Irrespective of, whether reporter bacteriophages are lysogenic or lytic, both can detect potentially the particular pathogenic bacteria. A number of genes, such as insertion of firefly
Phages stained with different fluorescent dyes have been used for target bacterial detection involving various fluorescence sensing tools. Stained phage-probes can discriminate a target bacterium when they infect and attack host cells [33]. Like, phages were tagged with fluorescent quantum dots (QDs) and
Lytic phages infection results in cell burst and consequently intracellular organelles, descendant phages, and cell-lysis materials are released. Both the release of intracellular elements and released progeny phages provide a base to recognize the target bacterium [30]. For example, as a released cell component, adenosine-triphosphate can be detected through bioluminescence just after target bacterial cell lysis [35]. Also the amount of released progeny phages released after cell lysis by a particular phage is directly proportional to the amount of lysed cells and can be used for bacterial sensing [36]. The released progeny phages enumerated by various detection mechanisms such as plaque- or immuno assays, molecular methods like quantitative PCR (qPCR) and, or by isothermal nucleic acid amplification (ITNAA) [37].
Phages that are immobilized on solid matrix can be utilized for capturing specific bacterial cell from contained samples. Bacteriophages have a many functionally active groups like hydroxyl group (—OH), aldehyde group(—CHO), carboxyl group(—COOH), etc., on their exteriors, giving them inimitable characteristics permitting their interaction with other materials and to interact with bacterial surface receptor molecules [38]. Consequently phages have been successfully used to capture particular bacterial cells from different samples [39, 40]. Like streptavidin actuated gold nano-particles were used to immobilize GM T4 bacteriophage particles. Delay in impedance was observed due to bacterial cells binding that marked as a sign for the existence of bacterial cells [41].
Some phage components display natural magnetism to host cell for example receptor-binding proteins (RBPs), but they are highly subtle to variations in environmental conditions. Phage tail bears RBPs and helps in binding to host bacterium, proceeding to insert its genetic material within the cell and cell infection is established [42]. RPBs bind to cell surface with help of specific polypeptide or polysaccharide sequences that are present on the cell surface. Poshtiban and colleagues activated magnetic beads by immobilization of RBP protein Gp047 (from phage NCTC12673). These functionally active beads were then utilized for
It’s obvious from the literature that different approaches have been developed for immobilization of phages on surface of electrodes Figure 3. The common phage immobilization strategies on solid surfaces include physical adsorption [44], covalent bonding [45], entrapment of phages in solid matrix [46], etc.
Different ways to potentially orient phages on solid surfaces. Green highlighted-bacterial binding proteins, (a) tailed phages-side-ways, head-down, or tail-down, (b) asymmetric icosahedral phages, (c) filamentous phages-through either side-ways or, pole, (d) filamentous phages are likely to be bundled or aggregated (left). Oriented typically parallel on the substrate (right), adapted from [
The quantity of randomly oriented phages on solid surfaces is the most straightforward way for enhancing signal in bio-sensing scheme [47]. Deposition of high number of phage particles creates a steric interruption between phage particles [39]. Thus number of phage particles immobilized on solid surface should not surpass a specific threshold per surface area [48]. For T4 phage, estimated optical density was 19 phages/ mm2 area beyond that clogging was happened, resulting in reduced signal [49]. Phage particles can be simply oriented on the surface of electrode as they bear positive and negative potential on their tail fibers and head respectively. Phage immobilization strategies are briefly highlighted in the following context.
Most common approach used for immobilization of phages is physisorption [50, 51]. This approach is very artless, but then again the adsorbed phage may possibly detach as of substrate surface because of shear, changes in pH, or temperature, or ionic concentrations caused in the medium that reduces principally their biosensing applications. Subsequently most phage particles having net negative charge at pH 7 [52], a number of investigators successfully used electrostatic binding for phages immobilization Figure 4, [52]. Also this methodology suffers due to variability and bacteriophage detachment in turn to the physico-chemical fluctuations in the analyte medium. Covalent bonding of phages offered a more stronger attachment and is not at risk to easy detachment of phages [53, 54]. Proper chemical studies can make easy selection of suitable substrate and then potential application. Covalent attachment resulted in a sophisticated bacteriophage surface mass that is principally necessary for phage application in biosensor development [55, 56]. To design bioactive surfaces with phages, phage infectivity is important or at least phage should be able to interact with host bacteria or analyte; therefore, optimization is needed to reduce the effect on bacteriophage integrity during immobilization.
Graphical representation of bacteriophage random immobilization and electrostatic, charge-directed orientated immobilization of T2 phage onto CNT electrode surface functionalized with polyethyleneimine (PEI) [
Bacteriophage-display tools can enable scientist to display peptides of choice present on the phage exterior, that is, phage envelope. Phages expressed peptide can consequently be adsorbed on material surfaces that are coated with peptides specific ligands Figure 5. Phage-display-libraries are produced by introducing DNA segments into specific phages to facilitate each phage to display a specific peptide expressed by the DNA segment inserted [58]. Technology of phage display developed as a combined influence of two central thoughts, fusion phage and combinatorial peptide libraries [59]. The first theory allows display of external peptides on bacteriophage surface [59]; while the second idea hires libraries of numerous peptides achieved in corresponding production as contrasting to production of single specific peptides [60]. Merging these two theories stemmed progress in phage-display-tools, multi-billion clone alignments of self-assembled and self-amplified bio-components [54]. It is significant to keep in mind that genetic alteration may alter the characteristics properties of bacteriophages. For example, biotin-carboxyl-carrier-protein (BCCP) gene or the cellulose-binding-module (CBM) gene to the small-outer-capsid-protein (SOCP) gene of T4 bacteriophage was attached, affecting bacteriophage infectivity, and result was decline in burst size, as well as extended latent period [61].
Current applications of phage display technologies as imaging agents. Icosahedral phages are mostly used as, aiming on moieties for bacterial detection, and substrates for signal amplification. While filamentous phages are mostly used as multifunctional probes, and a variety of sensors [
Bacteriophages immobilization in micro-porous matrices permits them functionally and also structurally stable, keeping them active for long time period. Phages immobilization by entrapment in a porous hydrogel, (bio)polymeric agar and alginate matrices, is a tool for selection of applications where protection of phage particles essential against severe environmental conditions [62]. Additionally, entrapment might aid to maintain moisture, which is important for many phages infectivity, or keep phage particles in lyophilized condition [63]. A fruitful marketable case in point of entrapped bacteriophage in matrix is PhagoBioDerm [64] that is 0.2 mm thick, porous-polymeric-wound-dressing saturated with a mixture of biocides and lytic phages [65]. The matrices used for bacteriophage entrapment, that might possibly delay interaction of entrapped bacteriophage particles with host bacterial cells or analytes that are present in the vicinity of medium [66], marking inefficiency of phage bioactive surface.
Many investigators discovered to possibly immobilize phages by alternative layering with polyelectrolytes having oppositely charges, and claimed observation of enhanced phage particle surface coverage [68, 69]. For instance, a layer by layer methodology for M13 bacteriophage was reported, and phage was sandwiched between oppositely charged layers of weak poly-electrolytes, that was capable to diffuse freely form a nearby packed phage monolayer [69].
The effectiveness of bio-sensing approaches is mostly measured in terms of minimum limit of detection (LOD) of bacterial or other analyte. Thus researchers attempted and focused to improve the bacteriophage surface coverage for pushing detection limits. Significantly keep in mind that the LOD has not been improved biosensors where phages are immobilized by covalent binding, in comparison to the approaches where phage is immobilized by physisorption [22]. Thus, bacteriophage surface coverage is not only the factor to necessarily increase and improve the sensitivity and LOD of bacteriophage-based biosensor. Limit of detection of biosensors, based on various transduction approaches can be different depending on the working principle of selected transduction platform.
Without any doubt, environmental monitoring and food safety are the main universal worries that we humans have to oppose and are constantly struggling to take them over. In this chapter, we evidently demonstrated the principle and development phage-based biosensor. We compared the conventional phage based detection methods and briefed an introduction to different bio-probes involved in biosensors development. Further, we reviewed demonstrative phage/phage-components used in sensors development for pathogenic bacterial detection. Finally, we briefed different techniques to immobilize phages on appropriate substrate that is the major step toward phage-based biosensor development. We intend at thought-provoking and comprehensive explanations in mounting phage-based sensors and enlightening their uses for bacterial detection. By collaboration of engineers and scientists from multidisciplinary area to design a field applicable sensor and make advancements in phage-based sensors for bacterial pathogens diagnosis, we expect that this chapter might bring together the technologies related to phage-based sensors. In short, phage based biosensors in the fields of food safety, environmental monitoring and infectious disease diagnostics is vital as they are;
Cheap (based on easy phages production)
Highly specific
Very sensitive
Versatile (based on phage components)
This work was supported by National Key Research and Development Program of China under Grant 2017YFC1104402, China Postdoctoral Science Foundation (2016 M602291), the initial Research fund from CSC; and 3551 Project, Optics Valley of China.
antibodies enzyme linked immunosorbent assay isothermal nucleic acid amplification International Union of Pure and Applied Chemistry limit of detection polymerase chain reaction quantum dots quantitative polymerase chain reaction receptor-binding proteins biotin-carboxyl-carrier-protein cellulose-binding-module small-outer-capsid-protein
Dental implant service is a life-changing treatment modality for many patients. Giving our patients a fixed restoration is a very rewarding procedure, especially if the patients have difficulties: gage reflex, bulky prostheses, lack in retention, stability, or support. Unfortunately, this is not applicable for all patients, especially patients who cannot afford multiple implants or bone grafting. By considering the strategic implants under the existing removable partial denture (RPD), we make implant treatment simple and affordable for more patients.
The removable partial denture (RPD) is the dental prostheses that the patient, who suffers the absence of some but not all the natural teeth, can readily insert and remove from his/her mouth. The prostheses restore the missing teeth as well as the gingiva and the missing bone if needed. Removable partial dentures (RPDs) are indicated for patients with a long edentulous span, too long for a fixed prosthesis. The RPD is indicated for a patient with no posterior abutment to support a fixed prosthesis, and the cantilever bridge is contraindicated. Also, it is preferred if excessive alveolar bone loss is encountered, especially in the esthetic zone. Those patients who are not indicated for bone grafting or unable to afford the costly treatment are good candidates for the removable denture (RD). The acrylic flang is a good approach to compensate for the bone and soft tissue deficiency within a short fabrication time and a less aggressive approach. Moreover, this treatment option allows the patient to remove his prostheses for easier intraoral access, subsequently, better oral hygiene. The RD enables the dentist to repair or adjust the prostheses easily.
On the other hand, RD is less secure with limited retention and stability than fixed prostheses. RD metal clasp may compromise the final esthetic result. It may act as a gum stripper and accelerate alveolar bone resorption. These drawbacks in the RD can be managed by upgrading the RD using strategic implants, which are “the implants that change the prosthetic support type to a more favorable configuration” [1].
In this chapter the folllowing points is going to be discussed:
Classification as a systematic approach for communication and planning:
Kennedy classification system
Steffel classification and modified Steffel classification
Implant-Corrected Kennedy (ICK) Classification System for Partially Edentulous Arches
Strategic mini dental implants (MDI) and standard dental implant (SDI) under existing RPD, how many implant?
The abutment prosthetic value
Immediate and delayed restoration/loading, what is the difference?
Why strategic implant?
Mini-implant-assisted removable partial denture
Conclusion
A classification is a systematic approach in which the items or units are categories in groups or subgroups according to specific criteria. This approach facilitates the discussion regarding the most suitable treatment options, eases the communication between the dentist and the technician. The classification also allows for visualization and differentiation between the RPD support types: tooth-supported, tooth tissue-supported, tissue-supported, implant-supported, implant tissue-supported, and implant tooth-supported.
In 1925 Dr. Edward Kennedy introduced his approach of categorizing partially edentulous arches into four classes. He categorized the partially edentulous arches in a way that considered the edentulous area position in the arch and if it was surrounded with teeth or not. This approach was beneficial in visualizing the cases and reaching the decisions regarding the RPD designs.
The following is the Kennedy classification:
Class I: Edentulous free-end areas located on both sides (bilateral), posterior to the remaining teeth (Figure 1).
Class I maxillary arch.
Class II: Edentulous free-end area located on one side (unilateral), posterior to the remaining teeth (Figure 2).
Class II maxillary arch.
Class III: Edentulous bounded area with natural teeth remaining both anterior and posterior to it (Figure 3). The area is located on one side (unilateral).
Class III maxillary arch.
Class IV: Edentulous bounded area with natural teeth remaining posterior to it. The area is located anteriorly and crossing the mid-line (Figure 4).
Class IV maxillary arch.
In 1965 Applegate’s added eight rules to the classification. The rules can be summarized by the following: The categorization (classification) is always determined by the most posterior edentulous region (or regions). Any additional edentulous area (other than those that define the categorization) is considered a modification (Figures 6 and 7). If the teeth posterior to the edentulous area are not used to support the RPD, the edentulous area is classified as a free end (Figures 5 and 7), and vice versa (Figures 6 and 7). If the posterior free end edentulous region is not going to receive artificial teeth, it will not be considered in the classification (Figures 6–8), and vice versa. Putting the design and the structure of the RPD into consideration is a cornerstone in giving the correct RPD classification. Subsequently, the classification will be the start point making the best clinical decision regarding the number and the position of strategic implants under the RPD.
No rest is going to be costructed on # 38 or 37 ➔ the arch has two free end areas ➔ Class I mandibular arch.
Direct retainer is going to be constructed on 37. No artificial teeth is going to replace 46, 47 or 48 ➔ no free end ➔ Class III mod 1 mandibular arch.
No artificial teeth is going to replace, 48. Direct retainer is going to be constructed on 37 but not on 47 ➔ one free end ➔ Class II mod 3 mandibular arch.
No artificial teeth is going to replace, 38, 37, 36, 47 or 48. Class IV mandibular arch.
In 1962 Steffel described six support possibilities that can be encountered in RPD.[2] He labeled the classification categories from A to F based on the fulcrum, and the number and distribution of the abutments, Figure 9. The fulcrum line is a hypothetical line formed between abutments, teeth or implants. The RPD may rotate somewhat around the fulcrum during function.
Steffel classification.
ICK I (# 25).
In this chapter, we suggest a modification to this classification to simplify the communication and decision-making regarding the strategic implant under the existing RPD. In the modification, B, C, and D will be labeled together.
The following is the
Punctual-support, only one abutment.
Linear-support, two abutments; separated with edentulous area or at least one tooth.
Triangular-support, three well-distributed abutments; separated with edentulous area or at least one tooth. One of the abutments should be on the opposite quadrant.
Quadrangular-support, two well-distributed abutments on every quadrant.
Providing the patient with a stable prosthesis is a crucial target for the dentist. However, the RPD is not rigidly attached to the intraoral hard (teeth) and soft (mucosa) tissues, which have different levels of compressibility and mobility. Subsequently, the chewing and occlusal forces may generate different levels of tissue stress and prosthesis mobility. Both (stress and mobility) should be within the physiological level and cause no harm or trauma. Achieving this critical goal depends on the clinician’s understanding of the biomechanics and the different design solutions. The RPD design should consider the unique nature of each clinical case and counter the expected RPD movement in response to loading. The design also should minimize the potentially destructive forces that may affect the supporting tissues; teeth, mucosa, and bone. That can be achieved by avoiding a long lever system, good selection for the RPD supporting elements, and wide symmetrical distribution of the functional forces [3, 4]. Many of the previous points (if not all) can be achieved (fully or partially) by delivering an RPD with quadrangular-support type.
According to the modified Steffel classification, there are four types of prosthetic support: punctual, linear, triangular, and quadrangular. The RPD support improves gradually as the classification change from I to IV. Classification IV provides the best support to the RPD with the highest resistance of rotation. The strategic implant aims to change the prosthetic support type to a more favorable configuration.
One of the simple classification systems for RPD supported with implants or implants and natural teeth is Implant-Corrected Kennedy (ICK) classification system for partially edentulous arches by Al-Johany et al.[5] The ICK is based on the Kennedy classification system and the Applegate eight rules (Applegate–Kennedy system).[6] According to the ICK classification system coding guidelines, the Kennedy classification comes first, followed by the number of modification spaces (Applegate rules). Finally, round brackets enclose # followed by the implant’s or implants’ position will be added, Figures 10–18.
ICK II mod 2 (# 33, 36). Direct retainer is going to be constructed on 28.
ICK II mod 3 (# 13, 23). Direct retainer is going to be constructed on 28.
Meeting our patient’s expectations is a priority. That cannot be reached if the dentist did not provide the patient with a full straightforward clarification for the treatment plan. The clarification should cover the advantages, disadvantages, risks, time, cost, and alternatives. The explanation should be done in a way that helps both the patient first and the dentist second to reach the decision that best matches the patients’ needs, health status, and financial ability, as well as respect the patient’s chief complaint and consideration. Generally speaking, teeth-implant- or implant-supported removable dentures reduce (and in many cases eliminate) traditional denture problems.[1, 7, 8, 9] It helps the dentist widen his options to meet the patient’s needs and expectations by inserting one or few implants in strategic positions, but how many implants?
The needed number of mini dental implants (MDIs) or standard dental implants (SDIs) under existing RPD is a multifactorial process (see paragraph 2.5) and taken on the quadrant level. To give the patient an RPD with acceptable retention, stability, and support, the abutments should be well distributed. Two abutments on every quadrant in symmetrical position as possible are needed. On every quadrant, the sum of the abutments prosthetic value should be ≥2, Table 1 and Figure 19.
ICK II mod 1 (# 16, 13, 23).
The abutments prosthetic value | ||
---|---|---|
Teeth | Upper or lower incisor or lateral incisor | 0–0.5* |
Upper or lower canine | 1.3** | |
Upper or lower premolar or molar | 1*** | |
MDI | Upper MDI | 0.5–0.7**** |
lower MDI | 1 | |
SDI | Upper Standard Implant | 1 |
Lower Standard Implant | 1 |
The prosthetic value of the available teeth and the planned MDIs and SDIs. The recommendations are on the quadrant level.
The numbers represent the prosthetic value if abutment rest is planned; if not, the value will be 0.
If the four natural anterior abutment teeth are missing (11, 12, 13, 14), strategic implant/s is recommended even if all posterior teeth are available, and vice versa.
If there is no space ( edentulous area or at least one natural tooth) between the abutment teeth, the prosthetic value will decrease to 0.5 for each abutment.
Bone quality impacts the MDI prosthetic value.
ICK II (# 35, 33, 43).
For partially edentulous patients, the abutments can be implants or natural teeth and should be well-distributed with a sum of the prosthetic value ≥2 on quadrant level.
ICK III mod 3 (# 41).
In the course of formulating the prosthodontic plan, not all teeth or abutments have the same prosthetic value. The prosthetic value stands for the importance of the tooth or implant from a specific prosthodontic point of view. The last first molar (#36) in Figure 20 has a very high prosthetic value than the lateral incisor #32. Extracting #36 shifts the treatment modality (if an implant is not feasible) from fixed partial denture to removable partial denture. Suppose the dentist changes his prosthodontic point of view by selecting RPD as a treatment modality. In that case, the prosthetic value of #36 will be reduced a little for this specific treatment modality. However, the prosthetic value for the same tooth (#36, Figure 20) and the same treatment modality (RPD) will be very high if the patient has a knife-edge thin, sensitive mucosa. Usually, this type of patient can tolerate tooth-tooth-supported RPD better than tooth tissue-supported RPD. Therefore, it can be concluded that:
ICK III mod 1 (# 34, 42).
ICK III mod 1 (# 13, 23).
ICK IV (# 33, 43). Direct retainers are going to be constructed on 36 and 47. No artificial teeth are going to replace 37 or 38.
(A1 upper jaw and A2 lower jaw to G1 upper jaw): The recommended number of strategic standard implants (SDIs) or mini dental implants (MDIs) under existing RPD.
The #36 has a very high prosthetic value because the extracting change the treatment modality (if implant is not feasible) from fixed partial denture to removable partial denture.
The SDI #23 and MDI #33 have very high esthetic value as they help the dentist avoiding anterior metal clasps. #27 and MDI 35 have relatively high prosthetic value as they shift the RPD from tooth tissue supported to more implant tooth-supprted or implat implant-supported RPD.
Upgrading the existing clasp retained lower RPD by inserting strategic mini-implants, immediate restoration with immediate loading/soft material. A- Intraoral image with lower RPD before implantation. B- Partial edentulous lower jaw before implantation. C- Tissue surface of the RPD before implantation. D- Four strategic mini-implants in the interforaminal region, tooth 32 was extracted. E- Tissue surface of the RPD after implantation, soft relining in the areas opposing the implants’ head. F- Tissue surface of the RPD after 4 months, the matrix pick-up (housings). G- Intraoral image with lower RPD after the housing, clasps in esthetic zone were removed.
Narrow bone can be treated with bone grafting. Unfortunately, this is not always feasible. A- Biomechanically, the narrow implant is not always the best approach, see paragraph 5. B- Osteoplasty is used to insert a wider implant by increasing the bone width, which will impact the crown-implant ratio negatively and may place the implant near vital anatomical structure. C- One-piece mini-implant with ball attachment and preferable crown-implant ratio can be used to stabilize a complete removable denture or partial removable denture.
Upgrading the existing double crown retained upper RPD by inserting strategic mini-implants, immediate restoration, and delayed loading. A- Partial edentulous upper jaw before implantation. B- Tissue surface of the RPD before implantation. C- Five strategic mini-implants. D- Tissue surface of the RPD after implantation, recesses (empty notches) against the mini-implants. E- Tissue surface of the RPD after 4 months, the matrix pick-up (housings). The palate coverage was reduced. F- Intraoral image with the RPD after the housing.
Upgrading the existing double crown retained lower RPD by inserting strategic mini-implants, immediate restoration and immediate loading. A- Partial edentulous lower jaw before implantation. B- Tissue surface of the RPD before implantation. C- Two strategic mini-implants. D- Tissue surface of the RPD after implantation, the matrix pick-up (housings) inserted in the same implantation session. E- Intraoral image with the RPD in place after implantation.
The hidden #23 MDI under the saddle (Figure 21) has a very high esthetic value as it helps the dentist avoid metal clasp in the esthetic zone. In some cases, strategic implants enable the dentist to reduce or remove the flange to achieve a better esthetic result by reducing lip protrusion. In other cases, it gives the dentist the ability to minimize the RPD size (palate, Figure 24) and increase patient acceptance.
The prosthetic value (importance) for each abutment is estimated according to Table 1 and mainly the following points: [11, 12, 17, 18].
Periodontal status, mobility, and bone level around the abutment.
Crown-root ratio.
Tooth vitality, size of the defect (caries), size, and type of the restoration.
The shape and number of the abutment roots.
Occlusion, parafunctional activity and opposite jaw status: natural teeth, implant, fixed partial denture, complete denture, or partial denture.
In 1981 Albrektsson et al. suggested a protocol in which the implants are left to heal in situ for at least 3 to 4 months without loading.[19] He considered the non-loading phase a crucial period to achieve successful osseointegration and avoid fibrous tissue formation between the implant surface and the bone. On the other hand, many clinical studies proved that immediate restoration, immediate loading, or early loading are acceptable treatment modalities.[20, 21] These studies were in response to the social and psychological needs of many patients. The immediate or early treatment modalities aim to reduce the overall recovery time between the surgical intervention and the insertion of the final restoration. These approaches are known as immediate restoration protocol, immediate loading protocol, and early loading protocol.
Patients typically are uncomfortable and, in many cases, refuse to stay without their RPD for a long time, especially if it restores a lot of missing teeth or teeth in the esthetic zone. The immediate protocols can reduce the patient concerns related to the final restoration by reducing the waiting period. In some cases, a temporary restoration is immediately delivered to give the patient a hint on the form, size, and position (in some cases, the shade) of the final restoration. Moreover, the second surgical intervention can be averted through immediate protocols. To achieve a good success rate in this treatment modality, a good understanding of the topic, terminology, limitation, and biology is essential. These topics will be discussed in other chapters, but it is crucial to clarify a few terms.
The loading can be classified into four categories:
Conventional loading: The implants are left without loading for around two to three months.
Delayed loading: If the loading on the implant is applied after the conventional loading time, it is classified as delayed. That can be indicated if the tissue needs more healing time, such as external sinus lift with bone grafting. In such cases, the final restoration and implant loading may be applied after six to nine months.
Early loading: The implant is loaded by placing dental restoration in contact with opposing dentition at any time after one week but within two months after implant insertion.
Immediate loading: The dental restoration is inserted intraorally and placed in contact with opposing dentition within one week after the surgical intervention.
The timing of dental restoration can also be categorized to:
Conventional restoration in which the implant is left without temporary or final restoration for around two to three months.
Immediate restoration: The temporary or final restoration is placed within one week after surgical intervention.
Early restoration: The temporary or final restoration is placed any time after one week but within two months after implant insertion.
Delayed restoration: If the dental restoration is placed intraorally after the conventional loading time, the restoration is classified as delayed restoration.
According to the previous classifications, the dentist has different types of intervention. For example, he can go for immediate restoration with conventional loading or implement early restoration with delayed loading.
In the case of the strategic implant under existing RPD, there are seven scenarios: immediate restoration with one of the four loading types, or early restoration with early, conventional, or delayed loading. The decision regarding the best approach is multifactorial: age, esthetic expectations, oral hygiene level, bone quality and quantity, and treatment expenses. According to the 2018 census supported by the International Team for Implantology (ITI), the most critical factors that may impact the loading protocol selection are patient-related factors, especially patient’s general health, implant primary stability (ISQ), bone grafting, the size and shape of the implant, and the doctor skills and experience.[22] Moreover, the ITI tried to unify the two classifications (loading and restoration timing) to make it less complicated for the clinician and easier for the researchers to perform clinical studies and compare their results. They described four protocols:
Immediate loading: Within one week after implant placement, dental implants are linked to a prosthesis in occlusion with the opposing arch.
Immediate restoration: Within one week after implant placement, dental implants are linked to the dental restoration and are kept out of occlusion.
Early loading: Between one week and two months following implant placement, dental implants are linked to the prosthesis.
Conventional loading: dental implants are linked to the prosthesis after two months of implantation.
Improving dental treatment output by using implants to enhance the functional performance of the complete denture is a well-known approach in prosthodontics. The McGill Consensus Statement stated that the first option in treating the lower jaw edentulous patient should be two implants retained overdenture and not lower jaw conventional complete denture (CD).[23] Overwhelming scientific evidence supports the statement.[23] The evidence emphasized the superiority of two implants retained overdenture treatment modality on the conventional CD in many aspects, such as patients’ chewing efficiency, positive modification in patients’ diet, patients’ satisfaction with the CD stability, retention, and comfort as well as quality of life.[23] Although a lot of scientific evidence highlighted the positive impact of inserting implants under existing RPD, no similar Consensus Statement is available regarding implant-retained or implant-assisted removable partial denture. [24, 25, 26].
Not all patients are suitable for implant-supported fixed dental prostheses. For example, many patients are unwilling to have an extra surgical intervention (bone grafting, sinus lifting, bone splitting, or expansion). Other patients are not suitable for such intervention because they are medically compromised or do not have adequate financial flexibility. As an alternative to inserting multiple implants, the dentist can improve the quality of the prosthodontic treatment by changing the support type of the RPD to the quadrangular-support type. The improvement can be achieved by inserting one/two standard implants or one/two/three mini-implants per quadrant to reach a symmetrical quadrangular-support type. The prostheses will be tooth implant-supported RPD instead of tooth tissue-supported RPD. This prosthodontic approach is affordable to many patients.
The strategic implant is “the implant that can change the prosthetic support type to a more favorable configuration”.[1] It is a reliable way of treatment with an implant survival rate of 91.7–100%.[4] Also, it can support both the RPD and the other abutments effectively. In two clinical studies with 2 and 3 years follow-up, the survival rate of the natural teeth abutments was 100%.[9, 24].
Moreover, it can improve the survival rate of the RPD. The 10-year survival rate of RPDs; clasp-retained removable partial dentures, conical crown-retained dentures, or a combination of conical crown and clasp-retained dentures is 71.3%.[27] On the other hand, clinical studies with observation periods between 1 and 12.2 years reported survival rates of 90–100% for the implant-assisted removable partial denture prostheses.[7, 28, 29, 30, 31] This remarked difference in the survival rate plays an essential role in formulating the prosthodontic plan.
Many clinical studies have shown that implant placement in strategic locations under an existing RPD can enhance chewing efficiency, dental health-related quality of life, and patient satisfaction with speaking and eating, as well as RPD retention, stability, and support.[1, 8, 32] Above that, it gives the dentist the ability to reduce the tissue coverage and reduce the size of the RPD, which can positively impact the patient’s acceptance of the RPD, especially if he suffers hyperactive gag reflex, Figure 24. Also, it can improve the final esthetic result by avoiding the traditional metal clasp, Figures 19 and 22.
Unfortunately, inserting a standard implant under the existing RPD is not always feasible. The patient may have a very narrow bone that prevents inserting a standard implant without bone grafting. A procedure that is not suitable or acceptable by some patients. In this case, mini-implants can be considered a good alternative, Figures 22 and 25 [1, 8, 16].
In 1976, the U.S. Food and Drug Administration (FDA) approved the 3 mm root-form dental implant. With time, dental implants proved to be a predictable and reliable prosthodontic treatment modality with a high success rate.[33, 34, 35] After 21 years, the approval was cleared for implants less than 3 mm. The approval widens the spectrum of the patients treated with dental implants, particularly the cases with reduced bone width.
In literature, there is no standardization regarding the terminology of dental implant diameter.[36] For example, some authors considered the implants with diameters from 1.8 to 2.9 mm as small implants; others call them mini-implants.[37] Some authors defined the mini-implant as the implant with 2.2 mm.[38] Al-Johany et al. proposed a classification scheme and used four terms: Extra-narrow <3.0 mm, Narrow ≥3.0 mm to <3.75 mm, Standard 3.75 mm to <5 mm, and Wide ≥5 mm.[36] In this text, we will follow the lead of Resnik et al. and Schiegnitz et al. by considering the mini-implant as the implant with a diameter < 3.0 and the narrow-diameter implant as the implant with a diameter ≤ 3.5.[25, 37] This implant type is mainly used in heavily atrophic jaws but with sufficient bone height. The mini-implant gives the dentist the ability to avoid bone augmentation procedure, which is considered a time and cost-consuming surgical intervention. Avoiding additional surgical procedures can reduce morbidity and possible complications such as nerve trauma, hemorrhage, postoperative pain, or infection.[25] The infection may lead to the failure of bone grafting.[25] Above that, it is less invasive than the standard implant as it requires a smaller implant bed and no flap in a considerable number of cases.[26] Therefore, it is more appropriate for the compromised or elderly patients. Moreover, it is cost-effective and affordable. On the other hand, the small diameter of the implant may create a shear load to the crestal bone. That may increase the risk of bone resorption.[37, 39] Narrow -implant has been linked to biomechanical risk factors as implant fatigue or fracture, particularly when used in the canine area where high occlusal loads are applied or in parafunctional habits patients.[40].
A systematic review and meta-analysis reported that mini-implants (diameter < 3.0 mm) performed substantially worse than standard diameter implants with survival rates of 94.7 ± 5%.[25] However, narrow implants with a diameter (3–3.5 mm) have a better survival rate of 97.7 ± 2.3%.[25] Therefore, some researchers believe the best approach for a thin bone is bone augmentation.[37] If this is not feasible, narrow implant, osteoplasty and standard implant, or one-piece mini-implant with ball attachment and removable denture can be considered, Figure 23.
The small diameter implant is used to replace missing individual teeth in the anterior region, lower and upper jaw [41, 42]. Mini-implant is used as an orthodontic implant or transitional or provisional implant to support interim prostheses during the healing period after extensive implantations or augmentations and bone grafting.[43] The one-piece mini-implant with ball attachment is used as assisting / anchoring element under the removable denture.[1] Strategic min-implant under existing RPD and CD proved to be a reliable and straightforward approach.[1, 8, 44] New studies reported that the one-piece mini-implant with ball attachment has a significant advantage on the final prosthodontic treatment.[1, 8].
The one-piece implant mimics nature by having a solid unibody structure with no microgaps between the implant and the abutment. As a result, the possible biological complication (bone resorption) and structural flaw are reduced. Also, the flap or flapless single-stage surgery allows the dentist to implement immediate loading or immediate restoration.[42] Moreover, delayed loading is possible by preparing a recess against the mini-implant in the RPD’s tissue surface. The treatment protocol can be conventional or delayed loading. However, the recess (cavity) distorts the fit of the RPD’s, Figure 24.
On the other hand, if the mini-implants are inserted in a healthy, not compromised patent with insertion torque ≥35 Ncm, immediate loading can be considered. The immediate restoration with immediate loading can be implemented through one of two forms:
immediate loading using soft relining material, Figure 22.
immediate loading using the matrix pick-up (housings), Figure 25.
After implantation, soft relining material can restore the fit of the RPD, ease tissue pressure, and give the patient a secure feeling because the relining material encircles the implant head and minimizes RPD rocking. If all mini-implants have a high insertion torque, the patient can receive the final restoration with matrix pick-up (housings). Subsequently, no additional session for adjusting the RPD is needed. In this approach, the patient can directly feel and recognize the significant improvement in the RPD in many domains especially, retention, support stability, and chewing.[1, 8].
Studies proved that inserting strategic implants under existing RPD improves patient satisfaction on short- and medium-term follow-up (3-years).[1, 43] The improvement can be explained by the symmetrical distribution of the abutments and the increased number of the rests/abutments.[1, 17] Gorai S, et al. study reported a correlation between the rests number and denture usage.[17].
To sum it up, using strategic implants under existing RPD upgrade the design to more favorable support type and improve patient satisfaction with the RPD on several domains like speaking, chewing, retention, stability, and support of the RPD. This improvement could be reached earlier if the patient received immediate loading.[1].
In many cases, after putting into consideration the patient’s main complaint, expectation, desire, general health, intraoral/extraoral findings, evaluating the risks (do no harm) and the benefits of bone grafting and several implants, the dentist is able to provide his patient with one or few strategic standard or mini-implants that can satisfy the patients’ needs
Strategic implants can also improve chewing ability, stabilize the occlusion, increase bite force and improve patient oral health-related quality of life. Moreover, better distribution of occlusal forces that may reduce bone resorption may be gained. Furthermore, strategic implants can improve comfort, confidence, and esthetics by reducing the RPD size and removing metal clasps from the esthetic zone.
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He won the “Catedra Telefonica” Awards in Modality of Knowledge Transfer, 2017, 2018, and 2019 editions, and awards in Modality of COVID Research in 2020.\n\nPublic References:\nResearcher ID http://www.researcherid.com/rid/N-5967-2014\nORCID https://orcid.org/0000-0002-4621-2768 \nScopus Author ID https://www.scopus.com/authid/detail.uri?authorId=6602376272\nScholar Google https://scholar.google.es/citations?user=G1ks9nIAAAAJ&hl=en \nResearchGate https://www.researchgate.net/profile/Carlos_Travieso",institutionString:null,institution:{name:"University of Las Palmas de Gran Canaria",institutionURL:null,country:{name:"Spain"}}},editorTwo:null,editorThree:null},{id:"23",title:"Computational Neuroscience",coverUrl:"https://cdn.intechopen.com/series_topics/covers/23.jpg",isOpenForSubmission:!0,editor:{id:"14004",title:"Dr.",name:"Magnus",middleName:null,surname:"Johnsson",slug:"magnus-johnsson",fullName:"Magnus Johnsson",profilePictureURL:"https://mts.intechopen.com/storage/users/14004/images/system/14004.png",biography:"Dr Magnus Johnsson is a cross-disciplinary scientist, lecturer, scientific editor and AI/machine learning consultant from Sweden. \n\nHe is currently at Malmö University in Sweden, but also held positions at Lund University in Sweden and at Moscow Engineering Physics Institute. \nHe holds editorial positions at several international scientific journals and has served as a scientific editor for books and special journal issues. \nHis research interests are wide and include, but are not limited to, autonomous systems, computer modeling, artificial neural networks, artificial intelligence, cognitive neuroscience, cognitive robotics, cognitive architectures, cognitive aids and the philosophy of mind. \n\nDr. Johnsson has experience from working in the industry and he has a keen interest in the application of neural networks and artificial intelligence to fields like industry, finance, and medicine. \n\nWeb page: www.magnusjohnsson.se",institutionString:null,institution:{name:"Malmö University",institutionURL:null,country:{name:"Sweden"}}},editorTwo:null,editorThree:null},{id:"24",title:"Computer Vision",coverUrl:"https://cdn.intechopen.com/series_topics/covers/24.jpg",isOpenForSubmission:!0,editor:{id:"294154",title:"Prof.",name:"George",middleName:null,surname:"Papakostas",slug:"george-papakostas",fullName:"George Papakostas",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002hYaGbQAK/Profile_Picture_1624519712088",biography:"George A. 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He has (co)authored more than 150 publications in indexed journals, international conferences and book chapters, 1 book (in Greek), 3 edited books, and 5 journal special issues. His publications have more than 2100 citations with h-index 27 (GoogleScholar). His research interests include computer/machine vision, machine learning, pattern recognition, computational intelligence. \nDr. Papakostas served as a reviewer in numerous journals, as a program\ncommittee member in international conferences and he is a member of the IAENG, MIR Labs, EUCogIII, INSTICC and the Technical Chamber of Greece (TEE).",institutionString:null,institution:{name:"International Hellenic University",institutionURL:null,country:{name:"Greece"}}},editorTwo:null,editorThree:null},{id:"25",title:"Evolutionary Computation",coverUrl:"https://cdn.intechopen.com/series_topics/covers/25.jpg",isOpenForSubmission:!0,editor:{id:"136112",title:"Dr.",name:"Sebastian",middleName:null,surname:"Ventura Soto",slug:"sebastian-ventura-soto",fullName:"Sebastian Ventura Soto",profilePictureURL:"https://mts.intechopen.com/storage/users/136112/images/system/136112.png",biography:"Sebastian Ventura is a Spanish researcher, a full professor with the Department of Computer Science and Numerical Analysis, University of Córdoba. Dr Ventura also holds the positions of Affiliated Professor at Virginia Commonwealth University (Richmond, USA) and Distinguished Adjunct Professor at King Abdulaziz University (Jeddah, Saudi Arabia). Additionally, he is deputy director of the Andalusian Research Institute in Data Science and Computational Intelligence (DaSCI) and heads the Knowledge Discovery and Intelligent Systems Research Laboratory. He has published more than ten books and over 300 articles in journals and scientific conferences. Currently, his work has received over 18,000 citations according to Google Scholar, including more than 2200 citations in 2020. In the last five years, he has published more than 60 papers in international journals indexed in the JCR (around 70% of them belonging to first quartile journals) and he has edited some Springer books “Supervised Descriptive Pattern Mining” (2018), “Multiple Instance Learning - Foundations and Algorithms” (2016), and “Pattern Mining with Evolutionary Algorithms” (2016). He has also been involved in more than 20 research projects supported by the Spanish and Andalusian governments and the European Union. He currently belongs to the editorial board of PeerJ Computer Science, Information Fusion and Engineering Applications of Artificial Intelligence journals, being also associate editor of Applied Computational Intelligence and Soft Computing and IEEE Transactions on Cybernetics. Finally, he is editor-in-chief of Progress in Artificial Intelligence. He is a Senior Member of the IEEE Computer, the IEEE Computational Intelligence, and the IEEE Systems, Man, and Cybernetics Societies, and the Association of Computing Machinery (ACM). Finally, his main research interests include data science, computational intelligence, and their applications.",institutionString:null,institution:{name:"University of Córdoba",institutionURL:null,country:{name:"Spain"}}},editorTwo:null,editorThree:null},{id:"26",title:"Machine Learning and Data Mining",coverUrl:"https://cdn.intechopen.com/series_topics/covers/26.jpg",isOpenForSubmission:!0,editor:{id:"24555",title:"Dr.",name:"Marco Antonio",middleName:null,surname:"Aceves Fernandez",slug:"marco-antonio-aceves-fernandez",fullName:"Marco Antonio Aceves Fernandez",profilePictureURL:"https://mts.intechopen.com/storage/users/24555/images/system/24555.jpg",biography:"Dr. Marco Antonio Aceves Fernandez obtained his B.Sc. (Eng.) in Telematics from the Universidad de Colima, Mexico. 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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. 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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. He has also designed medical devices, including a laser Doppler monitoring system.",institutionString:"Kaiser Permanente Southern California",institution:null},{id:"169608",title:"Prof.",name:"Marian",middleName:null,surname:"Găiceanu",slug:"marian-gaiceanu",fullName:"Marian Găiceanu",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/169608/images/system/169608.png",biography:"Prof. Dr. Marian Gaiceanu graduated from the Naval and Electrical Engineering Faculty, Dunarea de Jos University of Galati, Romania, in 1997. He received a Ph.D. (Magna Cum Laude) in Electrical Engineering in 2002. Since 2017, Dr. Gaiceanu has been a Ph.D. supervisor for students in Electrical Engineering. He has been employed at Dunarea de Jos University of Galati since 1996, where he is currently a professor. Dr. Gaiceanu is a member of the National Council for Attesting Titles, Diplomas and Certificates, an expert of the Executive Agency for Higher Education, Research Funding, and a member of the Senate of the Dunarea de Jos University of Galati. He has been the head of the Integrated Energy Conversion Systems and Advanced Control of Complex Processes Research Center, Romania, since 2016. He has conducted several projects in power converter systems for electrical drives, power quality, PEM and SOFC fuel cell power converters for utilities, electric vehicles, and marine applications with the Department of Regulation and Control, SIEI S.pA. (2002–2004) and the Polytechnic University of Turin, Italy (2002–2004, 2006–2007). He is a member of the Institute of Electrical and Electronics Engineers (IEEE) and cofounder-member of the IEEE Power Electronics Romanian Chapter. He is a guest editor at Energies and an academic book editor for IntechOpen. He is also a member of the editorial boards of the Journal of Electrical Engineering, Electronics, Control and Computer Science and Sustainability. Dr. Gaiceanu has been General Chairman of the IEEE International Symposium on Electrical and Electronics Engineering in the last six editions.",institutionString:'"Dunarea de Jos" University of Galati',institution:{name:'"Dunarea de Jos" University of Galati',country:{name:"Romania"}}},{id:"4519",title:"Prof.",name:"Jaydip",middleName:null,surname:"Sen",slug:"jaydip-sen",fullName:"Jaydip Sen",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/4519/images/system/4519.jpeg",biography:"Jaydip Sen is associated with Praxis Business School, Kolkata, India, as a professor in the Department of Data Science. His research areas include security and privacy issues in computing and communication, intrusion detection systems, machine learning, deep learning, and artificial intelligence in the financial domain. He has more than 200 publications in reputed international journals, refereed conference proceedings, and 20 book chapters in books published by internationally renowned publishing houses, such as Springer, CRC press, IGI Global, etc. Currently, he is serving on the editorial board of the prestigious journal Frontiers in Communications and Networks and in the technical program committees of a number of high-ranked international conferences organized by the IEEE, USA, and the ACM, USA. He has been listed among the top 2% of scientists in the world for the last three consecutive years, 2019 to 2021 as per studies conducted by the Stanford University, USA.",institutionString:"Praxis Business School",institution:null},{id:"320071",title:"Dr.",name:"Sidra",middleName:null,surname:"Mehtab",slug:"sidra-mehtab",fullName:"Sidra Mehtab",position:null,profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0033Y00002v6KHoQAM/Profile_Picture_1584512086360",biography:"Sidra Mehtab has completed her BS with honors in Physics from Calcutta University, India in 2018. She has done MS in Data Science and Analytics from Maulana Abul Kalam Azad University of Technology (MAKAUT), Kolkata, India in 2020. Her research areas include Econometrics, Time Series Analysis, Machine Learning, Deep Learning, Artificial Intelligence, and Computer and Network Security with a particular focus on Cyber Security Analytics. Ms. Mehtab has published seven papers in international conferences and one of her papers has been accepted for publication in a reputable international journal. She has won the best paper awards in two prestigious international conferences – BAICONF 2019, and ICADCML 2021, organized in the Indian Institute of Management, Bangalore, India in December 2019, and SOA University, Bhubaneswar, India in January 2021. Besides, Ms. Mehtab has also published two book chapters in two books. Seven of her book chapters will be published in a volume shortly in 2021 by Cambridge Scholars’ Press, UK. Currently, she is working as the joint editor of two edited volumes on Time Series Analysis and Forecasting to be published in the first half of 2021 by an international house. Currently, she is working as a Data Scientist with an MNC in Delhi, India.",institutionString:"NSHM College of Management and Technology",institution:null},{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:"Polytechnic University of Timişoara",institution:{name:"Polytechnic University of Timişoara",country:{name:"Romania"}}},{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:null},{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:"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:"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:"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. Shukla",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:"356823",title:"MSc.",name:"Seonghee",middleName:null,surname:"Min",slug:"seonghee-min",fullName:"Seonghee Min",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Daegu University",country:{name:"Korea, South"}}},{id:"353307",title:"Prof.",name:"Yoosoo",middleName:null,surname:"Oh",slug:"yoosoo-oh",fullName:"Yoosoo Oh",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:"Yoosoo Oh received his Bachelor's degree in the Department of Electronics and Engineering from Kyungpook National University in 2002. He obtained his Master’s degree in the Department of Information and Communications from Gwangju Institute of Science and Technology (GIST) in 2003. In 2010, he received his Ph.D. degree in the School of Information and Mechatronics from GIST. In the meantime, he was an executed team leader at Culture Technology Institute, GIST, 2010-2012. In 2011, he worked at Lancaster University, the UK as a visiting scholar. In September 2012, he joined Daegu University, where he is currently an associate professor in the School of ICT Conver, Daegu University. Also, he served as the Board of Directors of KSIIS since 2019, and HCI Korea since 2016. From 2017~2019, he worked as a center director of the Mixed Reality Convergence Research Center at Daegu University. From 2015-2017, He worked as a director in the Enterprise Supporting Office of LINC Project Group, Daegu University. His research interests include Activity Fusion & Reasoning, Machine Learning, Context-aware Middleware, Human-Computer Interaction, etc.",institutionString:null,institution:{name:"Daegu Gyeongbuk Institute of Science and Technology",country:{name:"Korea, South"}}},{id:"262719",title:"Dr.",name:"Esma",middleName:null,surname:"Ergüner Özkoç",slug:"esma-erguner-ozkoc",fullName:"Esma Ergüner Özkoç",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Başkent University",country:{name:"Turkey"}}},{id:"346530",title:"Dr.",name:"Ibrahim",middleName:null,surname:"Kaya",slug:"ibrahim-kaya",fullName:"Ibrahim Kaya",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Izmir Kâtip Çelebi University",country:{name:"Turkey"}}},{id:"419199",title:"Dr.",name:"Qun",middleName:null,surname:"Yang",slug:"qun-yang",fullName:"Qun Yang",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"University of Auckland",country:{name:"New Zealand"}}}]}},subseries:{item:{id:"40",type:"subseries",title:"Ecosystems and Biodiversity",keywords:"Ecosystems, Biodiversity, Fauna, Taxonomy, Invasive species, Destruction of habitats, Overexploitation of natural resources, Pollution, Global warming, Conservation of natural spaces, Bioremediation",scope:"