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The two major species infecting man are
All
For
Human echinococcosis occurs through the ingestion of
Cosmopolite distribution of
The distribution of
There are approximately 1.3 million people with echinococcosis in China, where the disease burden is greater than that of any other country. Of the 33 provinces, autonomous regions, and municipalities in China, at least 20 are considered to be endemic for
The initial phase of a primary infection is always asymptomatic for both AE and CE in humans and may remain so for a matter of months up to many (typically more than 10) years.
The metacestodes of
In CE,
Patients with AE and CE are diagnosed based on clinical parameters including assessment of hepatomegaly, jaundice and upper abdominal complaints, as well as by imaging techniques such as ultrasound (US), computed tomography (CT) scans and magnetic resonance imaging (MR). ELISA-based detection of serum
To assess the degree of hepatic involvement of the parasite mass, AE patients are classified according to PNM (P: hepatic localization of parasite; N: extrahepatic involvement of neighbouring organs; M: absence or presence of distant metastases) and staged as P1, P2, P3, or P4 as recommended by WHO guidelines and the European Network for concerted surveillance of alveolar echinococcosis classification. For CE patients, classification of disease is based on liver lesion type (CE1, CE2, CE3, CE4 and CE5) at initial diagnosis, as proposed by the WHO Informal Group on Echinococcosis.
Despite its public health significance, the susceptibility of human echinococcosis is poorly understood. The general factors that may render an individual more susceptible include malnutrition, co-infection, and immuno-suppression caused by other diseases or through the use of immuno-suppressive drugs. Several reports of children with cystic echinococcosis were predominantly located in the lungs. The reason for lung hydatidosis in children may be explained by either the weaker immune capability in their respiratory system or the faster cyst growth rate (or both) in young ages than that in adults. Pregnancy has also been thought to increase risk of infection or aggravate the disease due to the impaired cellular immunity frequently observed in pregnant women.
Immuno-suppression is frequently observed in patients with severe AE or CE. High levels of circulating
Despite the high morbidity and mortality associated with echinococcosis, relatively few studies to date have investigated the genetics underlying human susceptibility to the disease.
The case-control studies of candidate genes that have been previously undertaken have identified a number of associations with susceptibility to human echinococcosis in the HLA region for both AE and CE. Of these, however, many have not been replicated, likely reflecting the complexities and diversities of host susceptibility in different ethnic populations, different environmental conditions, and exposure to different
The extensive genetic variation of
To date, over five species are recognized in the genus and four species are already revealed to be involved in human diseases. The most common forms are
However, human behavioural changes with economic, technological development, and the spatial expansion of agriculture promoted encroachment into wildlife habits, driven by increasing human population, leading to ecosystem changes and bringing human, domestic animals into closer proximity to wildlife. Many recently emerged zoonoses originated in wildlife have been reported.
Many studies of echinococcosis have provided significant information on risk factors of infection, as well as on socio-economic influences and ecological determinants of parasite transmission. The new immunological/genetic research components for new therapeutic targets, in combination with standard imaging techniques, will enable rapid and efficient evaluation of echinococcosis patients. This will not only greatly assist in monitoring disease progression and treatment efficacy, but also in the development and deployment of new control strategies and disease surveillance fundamental to reducing morbidity caused by long-term chronic infection and at a low cost to the health care systems of areas where echinococcosis is endemic. Further, the genetic study aims that identification of the genes involved in disease susceptibility can provide valuable insight into the protective and pathogenic mechanisms involved in the different clinical outcomes of echinococcosis. Understanding these processes can provide novel therapeutic targets that are essential for the long-term control of the disease worldwide. A significant, but essential challenge will be to develop strategies for translating knowledge of novel susceptibility genes into improved patient outcomes from both AE and CE. Given the considerable inter-individual variation observed in susceptibility to the different clinical phenotypes and their associated clinical outcomes, it is anticipated that subtle manipulation of the host immune response will translate into clinical benefits. Genomics offers a powerful approach to dissect the relevant pathways and may offer novel therapeutic targets for new drugs against both AE and CE, which are urgently needed as the current albendazole treatment is far from satisfactory. Definition of the molecules and pathways that are important in individual patients may eventually lead to a personalised approach to care, with therapy tailored on the basis of an individual’s genetic background.
Various methods for animal host interventions have been employed in echinococcosis endemic regions, for example, the culling of dogs/foxes for CE/AE, culling of rodents for AE, and the anthelminthic treatment (with praziquantel (PZQ)) of dog/foxes for CE/AE. Vaccine development has been ongoing and whilst a vaccine targeting the definitive dog/fox hosts could be a “magic bullet”, all current candidates have low efficacy. A highly efficacious sheep vaccine for
The use of geographic information system (GIS) have become more common as a tool for public health investigations due to the increase in number and quality of satellites used for terrestrial observation. These systems integrate the use of geographic positions sensors (GPS) tool for infectious disease studies, including
To date, only five islands (Iceland, New Zealand, Tasmania, Falkland Islands, and Cyprus) have been able to successfully control echinococcosis. Control programmes were predominantly based on health education and control or elimination of home slaughter of sheep, with behaviour change, is central to their success.
Despite the range of intervention strategies, control in endemic regions of the world (especially the poor rural areas) has proved difficult, as demonstrated by the increasing number of cases over the last decade. This failure to effectively control echinococcosis can be attributed to a number of causes: 1) culling of animals has ethical challenges (e.g., use of rodenticides in NHAR resulted in the poisoning of domestic dogs); 2) PZQ is effective in killing adult
Hydatid disease is a major cause of morbidity and mortality in many parts of the world. Although immunological research has provided important insight into the mechanisms of immunity in CE and AE, the genetic variants within the host-participating genes may be too subtle or too few to cause much effect on individual risk. The genotypic variation of
Fund support from the National Health Medical Research Councils (NHMRCs, APP1009539), Australia, and National Nature Science Foundation of China (NNSFC, 30960339).
Gels can be defined as three-dimensional cross-linked polymeric networks which swollen in contact with a liquid. When the polymers forming the gel contain mainly hydrophilic functional groups, the liquid that causes the swelling is water, and the gel is called hydrogel [1]. Biopolymers are often used for the synthesis of hydrogels as the natural composition of the polymer leads to extremely high biocompatibility and potential applications in the biomedical field [2].
Hydrogels can be classified as physical hydrogels when the properties of the gel depend on chain entanglements and other interactions, mainly hydrogen bonds or hydrophobic interactions [3]. In this case, properties are highly dependent on chain molecular weight as well as concentration, as mobility of the chains modifies the structure of the hydrogel and therefore its physical properties. Water temperature, salt content, and pH can also affect the mobility of the chains and interactions and must be controlled [4].
Chemically crosslinked hydrogels present a much more stable structure than physical hydrogels. In chemical hydrogels, the polymeric chains are covalently bonded using one or more crosslinking agents, using a chemical process [5]. In general, crosslinked hydrogels are less biocompatible than physical hydrogels, but this is compensated by other advantages: cross-linked hydrogels are insoluble, more stable, and rheological properties such as elasticity or viscosity, their pore size, and their degradation rate can be more optimized than with physical hydrogels.
Hydrogels can present different physical forms: from macrogels to micro and nanogels, which are particulate systems with similar chemical structure but different macroscopic size; implantable gels, with strong physical properties, or injectable gels, more fluids or composed of nano-microparticles which can pass through a needle; hydrogel coatings, where hydrogel nano or microlayer is immobilized on a surface; thermoresponsive or pH-responsive gels, where a trigger modulates the sol–gel properties, can be easily injected in a liquid form before gelation in physiological conditions [6].
Physical properties of physically and chemically crosslinked hydrogels, are similar to several soft biological tissues, and therefore they can be used as substitutes or supplements when the biological function of these soft tissues is compromised. Such hydrogels have been widely used as medical devices for different applications: in traumatology, as substitute or supplement of synovial fluid in osteoarthritis; in ophthalmology, as a substitute of aqueous humor during in cataract surgery; in esthetics and reconstructive surgery, as dermal fillers for rid correction and lipoatrophy for patients with VIH; in wound healing, as wound dressings to promote regeneration and healing of wounds [7].
The biomedical use of the hydrogels can be expanded by the employ of the hydrogels as a sustained release system. Concerning this the controlled release of pharmaceutical ingredients leads to important advantages as a control of the biodisponibility, dose control, local delivery and less side effects [8]. This chapter aims to cover a general overview concerning the sustained drug release from hydrogels and hydrogel coatings. In that regard,
The release of drugs from hydrogels can be achieved by different mechanisms such as swelling/deswelling, diffusion, and chemical mechanism. As previously mentioned, hydrogels are three-dimensional crosslinked polymeric networks that swelled in the presence of water. The crosslink can be physical (hydrophobic interactions, electrostatic interactions and hydrogen bonding) or chemical (covalent bonding) and is responsible of the network structure of the hydrogel. Such networks display open spaces, the size of which is referred to as the mesh size of the hydrogel [9]. Importantly, the mesh size of the hydrogels is one of the main parameters that affect how drugs diffuse through the hydrogel network, being dependent on polymer and crosslinker concentrations, as well as external stimuli. The gelation of hydrogels by polymerization means leads to network irregularities and polymer polydispersity upon formation, and as a result, the mesh size is usually heterogeneous. A number of approaches exist to determine the mesh size [9].
When the mesh is larger than the drug (rmesh/rdrug > 1), the drug release process is dominated by diffusion. Small drug molecules migrate freely through the network, and diffusion is largely independent of the mesh size. The diffusivity, D, in this situation depends on the radius of the drug molecule (rdrug) and the viscosity of the solution (η) via the Stokes–Einstein equation Eq. (1) [10]:
where R is the gas constant and T is the absolute temperature.
When the mesh size is close to the drug size (rmesh/rdrug ≈ 1), the effect of steric hindrance on drug diffusion becomes relevant. Finally, for an extremely small mesh size and/or very large drug molecules (rmesh/rdrug < 1), strong steric hindrance immobilizes the drugs and it remains physically entrapped inside the network, unless the network degrades or the mesh size expands in response for example, to external stimuli.
Several methods accompanied by mathematical model development have been created in parallel to hydrogel technology, in order to predict drug release from the network. The drug release fitting models (i.e. the zero order equation; the first order equation; the Higuchi’s equation; the Korsmeyer-Peppas’ equation; the Hixon-Crowell’s equation, the Weibull equation, among others) are the most abundant, however, they are not predictive but simple mathematical fitting equations. In the last years, mechanistic and statistical models are growing quite fast. Mechanistic models combining the mass transport with the system mechanics developed with a “fully coupled” approach considers the influence of the mass transport on the mechanics as well as the opposite, which makes this approach the only candidate to produce reliable first-principle models.
Statistical models, are receiving a lot of attention due to the consensus of the regulatory authority and the possibility to predict the hydrogels behavior, in the analyzed design space, regardless the complicate phenomenology, with quick and inexpensive experimental designs [11]. Recently, Wu and Brazel developed a method for the simulation of water uptake profile and drug release from homogeneous hydrogels. This model successfully predicted the initial burst release observed experimentally [12]. Sheth et al. developed a mathematical and computational model using time snapshots of diffusivity and hydrogel geometry data measured experimentally as inputs to predict release profiles of two model proteins of varying molecular weights from degradable hydrogels [13].
Physical hydrogels are those formed by reversible and dynamic crosslinks grounded on noncovalent interactions. In this regard the network of physical hydrogels is reversibly held together by molecular entanglements, resulting from a dynamic competition between pro-assembly forces (for example, hydrophobic interactions, attractive electrostatic forces and hydrogen bonding) and anti-assembly forces (for example, solvation and electrostatic repulsion [3]. These interactions that occur in this type of hydrogels are usually weak. However, they are numerous and contribute to the presence of complex behaviors.
Polyampholytes may also be used to construct physical hydrogels, with randomly dispersed cationic and anionic groups. The randomness leads to a wide distribution of strengths: The strong bonds serve as structural crosslinks, imparting elasticity, whereas the weak bonds reversibly break and re-form, dissipating energy. Consequently, physical hydrogels have reversible liquid to solid transition, also called sol–gel transition, in response to different changes in environmental conditions such as temperature, ionic strength, pH, or others [14]. Since the interactions depend significantly on external stimuli, they allow hydrogels to be highly versatile concerning the environment, unlike covalently bonded materials [15].
Physical hydrogels can be engineered to undergo spontaneous biodegradation under physiological conditions, which constitutes another way of controlling the release of active molecules [16]. Degradation is typically mediated by hydrolysis [17, 18] or enzyme activity [19]. The erosion or loss of polymer mass through degradation, can take place simultaneously in the bulk or on the surface of the hydrogel. For a variety of hydrogels, the bulk and surface erosion can be tuned to obtain desirable release kinetics ranging from weeks to months. Bulk erosion occurs because of the permeability to water or degrading enzymes when the rate of diffusion of these agents is rapid compared to the rate of bond degradation. Surface erosion, in contrast, results when the rate of bond breakage is more rapid than the rate of enzyme or water diffusion from the exterior into the bulk of the gel [13].
Representatives of reversible physical hydrogels are the shear-thinning hydrogels which flow like low-viscosity fluids under shear stress during injection, but quickly recover their initial stiffness after removal of shear stress in the body [3]. Alginate hydrogels are shear-thinning, formed via electrostatic interactions between alginate and multivalent cations (for example, calcium and zinc). They can be readily injected via a needle after gelation in a syringe and have been used to achieve sustained local delivery of bioactive vascular endothelial growth factor (VEGF) in ischemic murine hindlimbs for 15 days [20, 21].
Another example of physical hydrogels forming materials are the self-assembling peptide systems, where amino acid-based chains undergo the sol–gel transition without the need of any chemical crosslinking agent. This property makes them useful materials to safely in situ encapsulate living cells or sensitive drugs, among others. In addition, this peptide-driven self-assembly into physical hydrogels is highly specific, sourced mainly by the biorecognition of peptide segments scattered among the macromolecular chains. They form dynamic well-defined, hierarchically organized 3D structures with reversibility of the assembly and disassembly processes [22]. Another example are elastin-like polypeptides cross-linked via electrostatic interactions between their cationic lysine residues and anionic organophosphorus cross-linkers [23]. Non-covalent interactions between heparin and heparin-binding peptides and proteins can also be used to form hydrogels for growth factor delivery [24, 25].
Peptide self-assembly can also be achieved by taking advantage of interactions between metal cations and amino acid residues of the peptides. This was demonstrated with gelation of a β-sheet-rich fibrillar hydrogel with zinc ions [26].
Additional interesting example of physical hydrogels for drug release applications are pectin-chitosan hydrogels, which showed to be thermo-reversible and capable of prolonging the release of three different model hydrophobic drugs: mesalamin, curcumin and progesterone. In vitro drug-release studies revealed that lower percentage of pectin in the hydrogel led to slower release rates owing to smaller mesh size arising from stronger interactions between the polyelectrolytes. Also, the release was slower when the total polymer concentration was higher. Finally, a slower release in PBS solution compared to HCl solution was attributed to the fact that at pH 7.4, both polymers are charged, with strong electrostatic forces and consequently, smaller mesh size. At the molecular scale, the polymer chains can possess abundant binding sites for the drugs. DSC and FTIR analysis exhibited some interactions between the drugs and both chitosan and pectin that can contribute to the prolonged release of the drugs [27]. Another in situ-gelling hydrogel was formed with a polyelectrolyte complex, which showed a sustained release of insulin and avidin proteins [28].
Crosslinking of biopolymers provide a stable and non-soluble biomaterial which preserves the properties of the original biopolymer and displays a longer durability. Consequently, the half-life time of the hydrogels is increased when performing its biological application [5].
Usually, biopolymer crosslinking can be accomplished in two ways: by direct addition of a cross-linking agent followed by formation of a the three-dimensional (3D) network, or by chemical modification of the biopolymer chains with functional groups suitable for crosslinking with a compatible cross-linker. The first approach takes advance of the functional groups already present in the biopolymer, typically amine (NH2), hydroxyl (-OH), carboxylic acid (-COOH), amide (-CONH-, -CONH2), thiol (-SH) or sulfate (-SO3H) groups [29]. Examples of cross-linkers are dialdehyde derivatives, NH2-PEG-NH2 molecules, COOH-PEG-COOH derivatives, diglycidyl ether compounds, vinyl sulfone groups, etc. These agents cross-link through Michael-type addition, thiol exchange/disulfide cross-linking or Schiff-base processes among others [30]. In some case the addition of coupling agents such as carbodiimides derivatives, N-hydroxysuccinimide (NHS) or N-hydroxybenzo triazole (HOBt), is required for the cross-linking. In the second approach new active functionalities are created in the biopolymer [31, 32] which are appropriate for a broad range of cross-linking processes such as azide–alkyne cycloadditions, Diels–Alder reactions, ultraviolet (UV) photoinitiated crosslinking, (meth)acrylation reactions [5, 32]. Examples of cross-linkers are oxanorbornadiene, cyclooctyne, maleimide, trans-cyclooctene, norbornene, PEG-di(meth)acrylates among others.
The crosslinking of biopolymers produces hydrogels with elastic and deformable structures and great topochemical accessibility which is able to accommodate different kind of active molecules, such as drugs, for sustained release (Figure 1).
Left: Image of a hydrogel based on crosslinked hyaluronic acid. Right: Scanning electron microscopy (SEM) picture of the hydrogel. Figure produced by the authors.
Chitosan (CHI) is a linear polysaccharide formed by arbitrarily allocated β-(1 → 4)-linked D-glucosamine (deacetylated unit) and N-acetyl-D-glucosamine (acetylated unit). Chitosan is one of the most versatile biopolymers due to its unique properties: biodegradability, biocompatibility, non-toxicity, antioxidant, anti-inflammatory, antifungal, and antibacterial “contact killing” [33]. Therefore the applicability of this polysaccharide extends to a wide range of various biomedical areas, such as cosmetics, drug delivery, and tissue engineering, among others [34].
In this regard a covalently crosslinked chitosan hydrogel was produced Diels Alder reaction of furan and maleimide functionalized CHI. The resulting biopolymer held the typical pH sensitivity and antibacterial properties of non-functionalized CHI. The drug delivery capabilities of this system were evaluated with model drug antibiotic chloramphenicol (ClPh). Drug release experiment did not show an initial burst, which indicated that the ClPh was successfully encapsulated, whereas it displayed a sustained delivery of the drug with a complete release of the total amount of drug loaded (2.61 ± 0.036 mg ClPh/g hydrogel) after 4 hours [35].
CHI was also crosslinked with genipin (GP) to obtain biocompatible, antibacterial and anti-inflammatory hydrogels with wound healing properties. Sustained release of acetylsalicylic acid (ASA), cefuroxime (CFX), tetracycline (TCN) and amoxicillin (AMX) from the hydrogels displayed a Pharmacologic Half Life t1/2 values of 88 h, 62 h, 135 h, and 240 h for ASA, CFX, TCN and AMX respectively. These antibiotic releases generated antibacterial activity against
Moreover, dialdehyde-β-cyclodextrin (DA-β-CD) crosslinked carboxymethyl chitosan (CMCS) hydrogels were prepared from carboxymethyl chitosan (CMCS) and periodate oxidized β-CD. Phenolphthalein (PhP), a formerly used laxative agent, [16] was selected as a model molecule to investigate the drug loading and sustained release capabilities of such hydrogels. PhP release results show that increasing crosslinking rate between DA-β-CD and CMCS delays the drug liberation process. On the other hand, DA-β-CD/CMCS system displays faster releases, with a 50% release in 2 h and about 90% within 12 h, compared to CMCS crosslinked with glyoxal dialdehyde which only releases 19% of PhP after 24 h [37].
CHI based hydrogels (N-succinyl chitosan-g-Poly(acrylamide-co-acrylic acid) were synthesized by free radical mediated cross-linking of N-succinyl chitosan, acrylamide and acrylic acid [38]. Drug delivery capabilities of the system were tested by encapsulation of theophylline, a phosphodiesterase inhibiting drug used for the treatment of respiratory diseases. The drug release experiments showed a pH dependent behavior. In this regard, at pH 1.2 the theophylline released rate was found to be between 14 and 24% whereas at pH 7.4 the release of the drug reached 67–93%. CHI itself has been used as a cross-linking agent for poly(acrylic acid). The resulting hydrogels display pH sensitive properties that have been exploited to control the release of antibiotic amoxicillin and anti-inflammatory drug meloxicam. Concerning this, the release rates of these molecules rise with increasing pH due to the disruption of hydrogen bonds between the hydrogel components and the drugs. As a result 30%, ∼60% and ∼80% of amoxicillin is released after 800 min at pH 1.2, 6.8 and 7.4, respectively. The corresponding release data for meloxicam are ∼20%, ∼70% and ∼90% at pH 1.2, 6.8 and 7.4, respectively [39].
Hyaluronic acid (HA) is a non-sulfated glycosaminoglycan constituted by repeating disaccharide β-1,4-D-glucuronic acid–β-1,3 N-acetyl-D-glucosamine units that form hydrogels in aqueous solutions. This naturally occurring polysaccharide is found in connective tissues, skin, and synovial joint fluids of the human body. HA displays bio-functionality, biocompatibility, and physicochemical properties, such as viscoelasticity and high-water retention. As a result hyaluronic acid is used for the treatment of dry eye disease, dermatological conditions as well as a as a viscosupplement for the treatment of osteoarthritis [5].
Biocompatible antibacterial hydrogels of HA were synthetized by crosslinking HA solution with divinyl sulfone (DVS) followed by loading with antibiotic molecules. This way cefuroxime (CFX), tetracycline (TCN) and amoxicillin (AMX) loaded hydrogels displayed in vitro antibacterial activity against S. aureus. The antibacterial properties of the hydrogels were synergically enhanced by merging antibiotics with anti-inflammatory agent acetyl salicylic acid (ASA). Consequently it was observed an increase in the log10 reduction value (R) from 3.2, in the absence of ASA, to R 5.55 when TCN or CFX were combined with ASA [40].
Hyaluronic acid was crosslinked with 1,4-butanediol diglycidyl ether (BDDE) and loaded with quetiapine (QTP), an antipsychotic drug, and quercetin (QCT), a hyaluronidase (HAase) inhibitor that decreases the biodegradation of HA. Subcutaneous injection in rats of the system showed that the cHA hydrogel with QCT exhibited a lower maximum QTP concentration (Cmax. 782.6 ± 174.4 ng/mL) and longer half-life (t1/2 23.5 ± 2.7 h) and mean residence time values (MRT 30.9 ± 3.9 h) compared to the hydrogel without QCT (Cmax. 1827.6 ± 481.3 ng/mL, t1/2 13.4 ± 4.9 h, MRT 14.3 ± 4.8 h). These results demonstrated that HAase containing HA hydrogels are suitable systems for sustained drug delivery applications [41].
A thiol functionalized hyaluronic acid HA-SH was used, together with DMSO, for the fabrication of HA-SS-HA hydrogels. This system was loaded with antitumoral drugs such as doxorubicin (DOX), zinc phthalocyanine (ZnPc), and indocyanine green ICG, for implant post peritumoral administration. In vivo experiments validated that drug loaded hydrogel implant possessed satisfactory biocompatibility and succeeded in long term sustained release of drugs. As a result the system to ensured high tumor aggregation efficiency and adequate tumor suppression [42]. Hyaluronic acid (HA) functionalized with thiol and hydrazide moieties has been combined with oxidized sodium alginate (ALG)to produced cross-linked hydrogels (HA/ALG). These materials display tunable physicochemical properties and drug release behavior as a function of the HA/ALG precursor concentration. In this regard for HA2/ALG2 (2% w/v), HA3/ALG3 (3% w/v) and HA4/ALG4 (4% w/v) the yield stress of hydrogels were 1724, 4349 and 5306 Pa, and the degradation percentage were about 64%, 51%, and 42% after 35 days incubation, respectively. Thus, in vitro cumulative release of Bovine serum albumin (BSA) for HA2/ALG2, HA3/ALG3 and HA4/ALG4 were 79%, 72%, and 69% respectively for a 20 day release assay [43].
Near-infrared (NIR) light-triggered and reactive oxygen species (ROS)-degradable hyaluronic acid hydrogels (HPTG) were synthesized through the formation of dynamic covalent acylhydrazone bonds. Such system was loaded with photosensitizer protophorphyrin IX (PpIX) and anticancer drug doxorubicin (DOX), to obtain a with light-tunable on-demand drug release for chemo-photodynamic therapy. In this regard NIR light irradiation generated ROS that induced the required degradation of hydrogel and subsequent on-demand DOX release for cascaded chemotherapy. In vivo imaging-guided antitumor study using 4 T1 tumor- mouse model demonstrated that the treatment of DOX-loaded HPTG with laser irradiation nearly accomplished the suppression of tumor growth without noticeable regrowth [44].
Tyramine functionalized HA solutions were combined silk fibroin (SF) to produce a series of HA/SF hydrogels for application in cartilage tissue engineering an and drug delivery. These hydrogels were loaded with Vanillic acid (VA) or Epimedin C (Epi C), both with anti-catabolic, anti-inflammatory and anabolic effects on human cartilage cells. Hydrogels with HA20/SF80 polymeric ratios displayed the longest and the most sustained release profile with 70.1% release of VA after 60 days of release assay and 54% release of Epi C after 7 days of release. Such behavior makes HA20/SF80 hydrogels a prospective material for the treatment of osteoarthritic joint conditions [45].
Polyethylene glycol (PEG)-HA was modified also with a small biologically active molecule, as dopamine, to fabricate a HD-PEG polymer. This polymer was crosslinked with α -cyclodextrin (α-CD) to afford a polypseudorotaxane supramolecular complex HD-PEG/α-CD. The system was loaded with poly(lactic-co-glycolic acid) (PLGA)/donepezil microspheres (PDM) in order to evaluate the drug delivery capabilities of the system. The released amounts of donepezil, a drug used for the treatment of mental conditions, reaches 39.9% and 56.7%, after 7 and 14 days respectively. These results demonstrate that the HD-PEG/α-CD/PDM system could be used for the subcutaneous injection of long acting donepezil [46]. Similarly, poly(L-lactide-co-glycolide) (PLGA) – dexamethasone (DEX) nanoparticles PLGADEX were combined with crosslinked HA for drug release applications. In this case the chemical crosslinking occurred doubly, by mixing amino-hyaluronic acid and aldehyde-hyaluronic acid in the presence of genipin as a cross-linker agent. Drug delivery experiments showed full DEX release after 2 months for a HPLGADEX hydrogel [47].
Oxidized hyaluronic acid (OHA) was combined with carboxymethyl chitosan (CMC) via Schiff base reaction to fabricate a hydrogel (OHA-CMC) with antibacterial and hemostatic activities. The drug delivery potential of the system was exploited by encapsulating PLGA-PEG nanoparticles of curcumin (CNP) and epidermal growth factor (EGF) that afforded a OHA-CMC/CNP/EGF hydrogel. This system displayed outstanding anti-inflammatory, antioxidant and cell migration-promoting effects
Finally, HA has been used as well as a biopolymer for the fabrication of a 3D printable dual-network hydrogel with drug delivery capabilities. For that acrylamide-modified HA was synthesized and subsequently mixed with folic acid and Fe3+ to form a physical crosslinking network. Afterwards acrylamide residues were polymerized by ultraviolet radiation affording a material suitable for wound dressing with high elasticity and fatigue resistance. The drug delivery properties were investigated using acetylsalicylic acid (ASA) as a drug model and resulted in a pH responsive hydrogels with the sustained release of ASA over 300 hours [49].
Lignin is a sustainable biopolymer derived from lignol precursors that has been historically related to the paper industry. Hydrogels of hardwood lignin (TCA) have been synthesized through crosslinking with poly(ethylene) glycol diglycidyl ether (PEGDGE) and loaded with paracetamol for drug release applications. Here, decreasing amounts of crosslinker diminishes the interaction paracetamol - hydrogel network and, as a result, the release of paracetamol increases. In this regard, hydrogels produced with a lignin:PEGDGE 1:1 ratio displayed up to 30% of paracetamol release after 120 h assay. The release data follow a pseudo-Fickian behavior of diffusion when fitted to the Korsmeyer-Peppas model [50]. Furthermore, lignin polymers have been mixed with cellulose to generate drug delivery systems. Mechanical and sustained release performances of these gels are tailored by varying the ratio of the precursors: cellulose, hardwood lignin (TCA), and epichlorohydrin (ECH) cross-linker. TCA containing hydrogels display the best release rate (>90%) for drug model paracetamol comparing to the pure cellulose hydrogels (~40%) after 7 hours of release experiment. This behavior is attributed to the lower affinity of paracetamol for lignin compared to cellulose [51].
Cellulose itself have been used for the fabrication of hydrogels with drug release properties. In this regard, carboxymethyl cellulose (CMC) functionalized with ꞵ-cyclodextrin and nucleic acids have been crosslinked by using of arylazopyrazoles (AAPs) and loaded with anti-cancer molecule Doxorubicin (DOX). The resulting hydrogel behaves as a functional matrix for the UV light mediated ON/OFF release DOX. Irradiation of the matrix provokes the photoisomerization of the trans-AAP to cis-AAP residues and the generation of the low-stiffness hydrogel that releases DOX. Therefore, the liberation of the DOX could be changed between ON and OFF states by oscillating the photoisomerization of the hydrogel by employing UV/Vis irradiation [52].
Xanthan is a heteropolysaccharide produced by fermentation from the bacteria
Casein is a proline-rich, open-structured protein found in raw milk. It displays high hydrophilicity, good biocompatibility and a lack of toxicity that makes of it a potential candidate for hydrogel development. Casein can be chemically cross-linked with enzymes such as microbial transglutaminase (MTG). This feature was utilized to produced crosslinked casein -γ-polyglutamic acid (PGA) hydrogels in 1/5 and 1/9 ratio. Drug release experiments showed that both composition displayed similar release rate values for aspirin (~ 100% after 10 h), while 1/9 hydrogels possessed a higher release rate for vitamin B12, ~100% after nearly 12 h versus ~20% for 1/5 casein/γ-PGA hydrogels [56].
Historically, the development of medical implants has been a great concern for biomedical community. Besides, their need has risen dramatically due to the increased number of surgical procedures that are predicted to be even higher in 2030 [57]. Thus, improving the performance of implantable biomaterials has become a high-priority trend, which is reflected in the large number of research realized to successfully meet the upward demand [58].
Implantable medical devices (e. g. coronary stents, cardiac pacemakers, prostheses, insulin pumps) are classified in four main groups: ceramics [59], polymers [60], composites [61], and metals [62]. Among them, metallic biomaterials as titanium and its alloys are of outmost interest thanks to their inert chemical and biological behavior
The use of these bioactive coatings entails the development of an improved version of bioactive materials that modulates biological systems response by the establishment of interactions with adjacent tissues and bones [65]. Nevertheless, these coatings require the most suitable physicochemical, mechanical, and biological functionality for a successful implantation and integration so as not to produce any counterproductive disorder in humans [66]. Therefore, it is imperative to develop functional bioactive coatings onto the surface of biomaterials (Figure 2, produced by the authors) that combine biocompatibility [67], antibacterial [68], anti-inflammatory [69], self-healing [70], wound healing [71], bone tissue engineering [72], and osseointegration [73] properties.
Bioactive properties of functional hydrogel coatings for biomaterials successful implantation. Figure produced by the authors.
Such features can be incorporated onto the surface of biomaterials by the use of biopolymer-based coatings, mostly based on hyaluronic acid and chitosan [74]. Moreover, these coatings acquire hydrogel-like three dimensional microstructure after crosslinking for bioactive agents delivery applications (Figure 3, produced by the authors). In such manner, bioactive properties that already possess biomaterials can be upgraded or even provide novel outstanding properties [75]. Specifically, hydrogel coatings take advantage of hydrogels peculiar ability of releasing in a controlled space–time manner to the therapeutic target the entrapped bioactive agents (drugs, proteins, peptides, growth factors, inorganic or polymeric nanoparticles, and nucleic acids) through their polymeric network [76].
Bioactive agents loading and controlled release ability from hydrogel-based coatings. Figure produced by the authors.
Bioactive agents controlled delivery reduces side effects in patients undergoing implant procedures. In addition, highly stable (from hours to months) hydrogel coatings with great loading ability provide a not sudden, uniform, and prolonged release of specific low- to high-doses [77]. This way, therapeutic effect of bioactive substances is extended, and the over-excessed concentration peaks of conventional methods are diminished. These features endow hydrogel coatings with privileged pharmacokinetic profiles, which can be modulated for personalized therapies [78]. Further, hydrogel coatings do not need to modulate specific linkages to release bioactive agents since their release mechanisms are mainly governed by simple diffusion, swelling, and degradation processes [79].
Nowadays, researchers are focusing their attention is the hinder of hydrogel coatings attachment to surfaces, which occurs due to hydrogels excessively huge swelling and macroscale thickness. One promising alternative approach to create highly adhesive hydrogel coatings with strong and resistant hydrogel-surface attachment is the
A) Conventional and B)
The number of works related to the development of novel biopolymer-based hydrogel systems, mainly those synthesized with hyaluronic acid and chitosan, that promote the sustained release of bioactive agents increases year by year. In the current chapter we have summarized the recent accomplishments of biopolymer based physical and chemically crosslinked hydrogels, as well as hydrogel coatings for drug delivery and sustained release applications. The future perspectives in this field involve the development of hydrogel based medicines with specific temporal and spatial controlled release of drugs. Such medicines afford dose control, local delivery and reduced side effects that increase the efficacy and security of the treatment and the adherence of the patient to it. This strategy will lower pharmaceutical costs and improve the quality of life of the patient and the society overall.
Jon Andrade del Olmo thanks Basque Government for “Program of Industrial Doctorates. Bikaintek 2018” (exp number 01-AF-W2-2018-00002).
All the authors are employees of the company i+Med S. Coop.
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His studies in robotics lead him not only to a PhD degree but also inspired him to co-found and build the International Journal of Advanced Robotic Systems - world's first Open Access journal in the field of robotics.",institutionString:null,institution:{name:"TU Wien",country:{name:"Austria"}}},{id:"441",title:"Ph.D.",name:"Jaekyu",middleName:null,surname:"Park",slug:"jaekyu-park",fullName:"Jaekyu Park",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/441/images/1881_n.jpg",biography:null,institutionString:null,institution:{name:"LG Corporation (South Korea)",country:{name:"Korea, South"}}},{id:"465",title:"Dr",name:"Christian",middleName:null,surname:"Martens",slug:"christian-martens",fullName:"Christian Martens",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:null},{id:"479",title:"Dr.",name:"Valentina",middleName:null,surname:"Colla",slug:"valentina-colla",fullName:"Valentina Colla",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/479/images/358_n.jpg",biography:null,institutionString:null,institution:{name:"Sant'Anna School of Advanced Studies",country:{name:"Italy"}}},{id:"494",title:"PhD",name:"Loris",middleName:null,surname:"Nanni",slug:"loris-nanni",fullName:"Loris Nanni",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/494/images/system/494.jpg",biography:"Loris Nanni received his Master Degree cum laude on June-2002 from the University of Bologna, and the April 26th 2006 he received his Ph.D. in Computer Engineering at DEIS, University of Bologna. On September, 29th 2006 he has won a post PhD fellowship from the university of Bologna (from October 2006 to October 2008), at the competitive examination he was ranked first in the industrial engineering area. He extensively served as referee for several international journals. He is author/coauthor of more than 100 research papers. He has been involved in some projects supported by MURST and European Community. His research interests include pattern recognition, bioinformatics, and biometric systems (fingerprint classification and recognition, signature verification, face recognition).",institutionString:null,institution:null},{id:"496",title:"Dr.",name:"Carlos",middleName:null,surname:"Leon",slug:"carlos-leon",fullName:"Carlos Leon",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"University of Seville",country:{name:"Spain"}}},{id:"512",title:"Dr.",name:"Dayang",middleName:null,surname:"Jawawi",slug:"dayang-jawawi",fullName:"Dayang Jawawi",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"University of Technology Malaysia",country:{name:"Malaysia"}}},{id:"528",title:"Dr.",name:"Kresimir",middleName:null,surname:"Delac",slug:"kresimir-delac",fullName:"Kresimir Delac",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/528/images/system/528.jpg",biography:"K. Delac received his B.Sc.E.E. degree in 2003 and is currentlypursuing a Ph.D. degree at the University of Zagreb, Faculty of Electrical Engineering andComputing. His current research interests are digital image analysis, pattern recognition andbiometrics.",institutionString:null,institution:{name:"University of Zagreb",country:{name:"Croatia"}}},{id:"557",title:"Dr.",name:"Andon",middleName:"Venelinov",surname:"Topalov",slug:"andon-topalov",fullName:"Andon Topalov",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/557/images/1927_n.jpg",biography:"Dr. Andon V. Topalov received the MSc degree in Control Engineering from the Faculty of Information Systems, Technologies, and Automation at Moscow State University of Civil Engineering (MGGU) in 1979. He then received his PhD degree in Control Engineering from the Department of Automation and Remote Control at Moscow State Mining University (MGSU), Moscow, in 1984. From 1985 to 1986, he was a Research Fellow in the Research Institute for Electronic Equipment, ZZU AD, Plovdiv, Bulgaria. In 1986, he joined the Department of Control Systems, Technical University of Sofia at the Plovdiv campus, where he is presently a Full Professor. He has held long-term visiting Professor/Scholar positions at various institutions in South Korea, Turkey, Mexico, Greece, Belgium, UK, and Germany. And he has coauthored one book and authored or coauthored more than 80 research papers in conference proceedings and journals. His current research interests are in the fields of intelligent control and robotics.",institutionString:null,institution:{name:"Technical University of Sofia",country:{name:"Bulgaria"}}},{id:"585",title:"Prof.",name:"Munir",middleName:null,surname:"Merdan",slug:"munir-merdan",fullName:"Munir Merdan",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/585/images/system/585.jpg",biography:"Munir Merdan received the M.Sc. degree in mechanical engineering from the Technical University of Sarajevo, Bosnia and Herzegovina, in 2001, and the Ph.D. degree in electrical engineering from the Vienna University of Technology, Vienna, Austria, in 2009.Since 2005, he has been at the Automation and Control Institute, Vienna University of Technology, where he is currently a Senior Researcher. His research interests include the application of agent technology for achieving agile control in the manufacturing environment.",institutionString:null,institution:null},{id:"605",title:"Prof",name:"Dil",middleName:null,surname:"Hussain",slug:"dil-hussain",fullName:"Dil Hussain",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/605/images/system/605.jpg",biography:"Dr. Dil Muhammad Akbar Hussain is a professor of Electronics Engineering & Computer Science at the Department of Energy Technology, Aalborg University Denmark. Professor Akbar has a Master degree in Digital Electronics from Govt. College University, Lahore Pakistan and a P-hD degree in Control Engineering from the School of Engineering and Applied Sciences, University of Sussex United Kingdom. Aalborg University has Two Satellite Campuses, one in Copenhagen (Aalborg University Copenhagen) and the other in Esbjerg (Aalborg University Esbjerg).\n· He is a member of prestigious IEEE (Institute of Electrical and Electronics Engineers), and IAENG (International Association of Engineers) organizations. \n· He is the chief Editor of the Journal of Software Engineering.\n· He is the member of the Editorial Board of International Journal of Computer Science and Software Technology (IJCSST) and International Journal of Computer Engineering and Information Technology. \n· He is also the Editor of Communication in Computer and Information Science CCIS-20 by Springer.\n· Reviewer For Many Conferences\nHe is the lead person in making collaboration agreements between Aalborg University and many universities of Pakistan, for which the MOU’s (Memorandum of Understanding) have been signed.\nProfessor Akbar is working in Academia since 1990, he started his career as a Lab demonstrator/TA at the University of Sussex. After finishing his P. hD degree in 1992, he served in the Industry as a Scientific Officer and continued his academic career as a visiting scholar for a number of educational institutions. In 1996 he joined National University of Science & Technology Pakistan (NUST) as an Associate Professor; NUST is one of the top few universities in Pakistan. In 1999 he joined an International Company Lineo Inc, Canada as Manager Compiler Group, where he headed the group for developing Compiler Tool Chain and Porting of Operating Systems for the BLACKfin processor. The processor development was a joint venture by Intel and Analog Devices. In 2002 Lineo Inc., was taken over by another company, so he joined Aalborg University Denmark as an Assistant Professor.\nProfessor Akbar has truly a multi-disciplined career and he continued his legacy and making progress in many areas of his interests both in teaching and research. 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On the product of a symplectic manifold and an almost contact metric manifold, we induce some relations between Gromov-Witten type invariant and quantum cohomology and quantum type invariant. 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Despite their attractive properties, these algorithms are developed based on different geometric intuitions, and only partial information from the true geometric structure of the underlying manifold is learned by each method. In order to discover the underlying manifold structure more faithfully, we introduce a novel method to fuse the geometric information learned from different local manifold learning algorithms in this chapter. First, we employ local tangent coordinates to compute the local objects from different local algorithms. Then, we utilize the truncation function from differential manifold to connect the local objects with a global functional and finally develop an alternating optimization‐based algorithm to discover the low‐dimensional embedding. 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In addition, slant, semi-slant and pseudo-slant sub-manifolds are introduced by many geometers.",book:{id:"5488",slug:"manifolds-current-research-areas",title:"Manifolds",fullTitle:"Manifolds - Current Research Areas"},signatures:"Mehmet Atçeken, Ümit Yıldırım and Süleyman Dirik",authors:[{id:"191326",title:"Prof.",name:"Mehmet",middleName:null,surname:"Atceken",slug:"mehmet-atceken",fullName:"Mehmet Atceken"},{id:"196148",title:"Dr.",name:"Umit",middleName:null,surname:"Yildirim",slug:"umit-yildirim",fullName:"Umit Yildirim"}]},{id:"52886",title:"Head Pose Estimation via Manifold Learning",slug:"head-pose-estimation-via-manifold-learning",totalDownloads:1824,totalCrossrefCites:4,totalDimensionsCites:3,abstract:"For the last decades, manifold learning has shown its advantage of efficient non-linear dimensionality reduction in data analysis. Based on the assumption that informative and discriminative representation of the data lies on a low-dimensional smooth manifold which implicitly embedded in the original high-dimensional space, manifold learning aims to learn the low-dimensional representation following some geometrical protocols, such as preserving piecewise local structure of the original data. Manifold learning also plays an important role in the applications of computer vision, i.e., face image analysis. According to the observations that many face-related research is benefitted by the head pose estimation, and the continuous variation of head pose can be modelled and interpreted as a low-dimensional smooth manifold, we will focus on the head pose estimation via manifold learning in this chapter. Generally, head pose is hard to directly explore from the high-dimensional space interpreted as face images, which is, however, can be efficiently represented in low-dimensional manifold. Therefore, in this chapter, classical manifold learning algorithms are introduced and the corresponding application on head pose estimation are elaborated. Several extensions of manifold learning algorithms which are developed especially for head pose estimation are also discussed and compared.",book:{id:"5488",slug:"manifolds-current-research-areas",title:"Manifolds",fullTitle:"Manifolds - Current Research Areas"},signatures:"Chao Wang, Yuanhao Guo and Xubo Song",authors:[{id:"190308",title:"Dr.",name:"Chao",middleName:null,surname:"Wang",slug:"chao-wang",fullName:"Chao Wang"},{id:"190461",title:"Prof.",name:"Xubo",middleName:null,surname:"Song",slug:"xubo-song",fullName:"Xubo Song"},{id:"191562",title:"MSc.",name:"Yuanhao",middleName:null,surname:"Guo",slug:"yuanhao-guo",fullName:"Yuanhao Guo"}]},{id:"53109",title:"A Fusion Scheme of Local Manifold Learning Methods",slug:"a-fusion-scheme-of-local-manifold-learning-methods",totalDownloads:1711,totalCrossrefCites:1,totalDimensionsCites:0,abstract:"Spectral analysis‐based dimensionality reduction algorithms, especially the local manifold learning methods, have become popular recently because their optimizations do not involve local minima and scale well to large, high‐dimensional data sets. 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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. 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Ms. Mehtab has published seven papers in international conferences and one of her papers has been accepted for publication in a reputable international journal. She has won the best paper awards in two prestigious international conferences – BAICONF 2019, and ICADCML 2021, organized in the Indian Institute of Management, Bangalore, India in December 2019, and SOA University, Bhubaneswar, India in January 2021. Besides, Ms. Mehtab has also published two book chapters in two books. Seven of her book chapters will be published in a volume shortly in 2021 by Cambridge Scholars’ Press, UK. Currently, she is working as the joint editor of two edited volumes on Time Series Analysis and Forecasting to be published in the first half of 2021 by an international house. Currently, she is working as a Data Scientist with an MNC in Delhi, India.",institutionString:"NSHM College of Management and Technology",institution: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. 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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:"22",type:"subseries",title:"Applied Intelligence",keywords:"Machine Learning, Intelligence Algorithms, Data Science, Artificial Intelligence, Applications on Applied Intelligence",scope:"This field is the key in the current industrial revolution (Industry 4.0), where the new models and developments are based on the knowledge generation on applied intelligence. The motor of the society is the industry and the research of this topic has to be empowered in order to increase and improve the quality of our lives.",coverUrl:"https://cdn.intechopen.com/series_topics/covers/22.jpg",hasOnlineFirst:!0,hasPublishedBooks:!0,annualVolume:11418,editor:{id:"27170",title:"Prof.",name:"Carlos",middleName:"M.",surname:"Travieso-Gonzalez",slug:"carlos-travieso-gonzalez",fullName:"Carlos Travieso-Gonzalez",profilePictureURL:"https://mts.intechopen.com/storage/users/27170/images/system/27170.jpeg",biography:"Carlos M. Travieso-González received his MSc degree in Telecommunication Engineering at Polytechnic University of Catalonia (UPC), Spain in 1997, and his Ph.D. degree in 2002 at the University of Las Palmas de Gran Canaria (ULPGC-Spain). He is a full professor of signal processing and pattern recognition and is head of the Signals and Communications Department at ULPGC, teaching from 2001 on subjects on signal processing and learning theory. His research lines are biometrics, biomedical signals and images, data mining, classification system, signal and image processing, machine learning, and environmental intelligence. He has researched in 52 international and Spanish research projects, some of them as head researcher. He is co-author of 4 books, co-editor of 27 proceedings books, guest editor for 8 JCR-ISI international journals, and up to 24 book chapters. He has over 450 papers published in international journals and conferences (81 of them indexed on JCR – ISI - Web of Science). He has published seven patents in the Spanish Patent and Trademark Office. He has been a supervisor on 8 Ph.D. theses (11 more are under supervision), and 130 master theses. He is the founder of The IEEE IWOBI conference series and the president of its Steering Committee, as well as the founder of both the InnoEducaTIC and APPIS conference series. He is an evaluator of project proposals for the European Union (H2020), Medical Research Council (MRC, UK), Spanish Government (ANECA, Spain), Research National Agency (ANR, France), DAAD (Germany), Argentinian Government, and the Colombian Institutions. He has been a reviewer in different indexed international journals (<70) and conferences (<250) since 2001. He has been a member of the IASTED Technical Committee on Image Processing from 2007 and a member of the IASTED Technical Committee on Artificial Intelligence and Expert Systems from 2011. \n\nHe has held the general chair position for the following: ACM-APPIS (2020, 2021), IEEE-IWOBI (2019, 2020 and 2020), A PPIS (2018, 2019), IEEE-IWOBI (2014, 2015, 2017, 2018), InnoEducaTIC (2014, 2017), IEEE-INES (2013), NoLISP (2011), JRBP (2012), and IEEE-ICCST (2005)\n\nHe is an associate editor of the Computational Intelligence and Neuroscience Journal (Hindawi – Q2 JCR-ISI). He was vice dean from 2004 to 2010 in the Higher Technical School of Telecommunication Engineers at ULPGC and the vice dean of Graduate and Postgraduate Studies from March 2013 to November 2017. 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