Pre-sowing physicochemical properties of soil (0–0.30 m depth).
\r\n\tRisk management aims to develop an efficient organizational development environment through risk planning, assessment, analysis, and control. This process will apply in all areas of activity, and the evaluation framework is the same regardless of the field. This volume will aim to appeal to chapters that address methods, models, evaluation frameworks, benefits, barriers, and other dimensions of risk management.
\r\n\tSustainability and the circular economy are approaches approached by many companies and have become activities of global interest. Protecting the environment, streamlining the consumption of organizational resources, reducing the amount of waste generated, and other activities are objectives of these efforts. The circular economy contributes to the sustainable development of the company or country and the achievement of the global objectives of sustainable development. This book will aim to collect various studies for organizational and global sustainability.
\r\n\tLeadership has become a globally desirable approach that can help improve organizational competitiveness and reduce organizational risks. Risks and barriers in risk-free management can be well managed through effective organizational leadership. This book will aim to bring together chapters that explore different areas of leadership.
Maize (
To mitigate the problem of low yield and contamination in an eco-friendly way is to use effective microorganisms (EM) [5] also known as beneficial microorganism (BM). Microorganisms economically support the farmer community by improving the soil activities [6] and assimilate accumulation in the final product of the production which in turn maintains the balance of organic and inorganic mechanisms of the soil and plant [7]. Many researches reflected advantageous effects of BM on soil physicochemical status [8, 9]. Beneficial microorganism increases the decomposition rate of organic fertilizer and increases nutrients availability [10]. Beneficial microorganism also promotes soil fertility, crop growth, and yield [11]; also improves soil health, soil quality, yield, and quality [12] of various physiological attributes; and regulates various metabolites and atmospheric nitrogen [13].
Nitrogen significantly improves crop productivity [14]. Fertilizers are usually applied to soil for increasing or maintaining crop yields to meet the increasing demand of food [15, 16]. The application of inorganic fertilizers results in higher soil organic matter (SOM) accumulation and biological activity due to increased plant biomass production and organic matter return to the soil in the form of decaying roots, litter, and crop residues [17, 18]. The addition of SOM enhances soil organic carbon (SOC) content, which is an important indicator of soil quality and crop productivity [19]. Chemical fertilizer applications could also affect soil physical properties directly or indirectly such as aggregate stability, water holding capacity, porosity, infiltration rate, hydraulic conductivity, and bulk density due to increases in SOM and SOC content [20, 21]. In turn, the formation of stable aggregates enhances physical protection of SOM against microbial decomposition [22]. Some fertilizer additions also affect the chemical composition of soil solution which can be responsible for dispersion/flocculation of clay particles and thus affect the soil aggregation stability [21, 23]. We can see the plant and microbial interaction in the retention and improvement of N cycle for better plant growth (Figure 1).
Plants and microbial interaction in the retention and improvement of N cycle for better plant growth [
The present study aimed to investigate the effect of organic and inorganic nitrogen ratios along with the effect of beneficial diazotrophic bacteria on maize yield and quality and physio-chemical properties of soil.
The impact of beneficial microbes on enhancing efficiency of organic and inorganic N fertilizers sources was studied on spring maize cropping system in the year of 2014 at Agronomy Research Farm, The University of Agriculture Peshawar, Pakistan. The research area is geographically located at 17°, 35′ N and 35°, 41′ W and altitude of 450 m above sea level. The soil of the experimental farm was silt loam, well drained, and fine textured. The experimental site has a semiarid subtropical continental climate with a mean annual rainfall of about 550 mm. The soil is deficient in total N (<0.5%) and AB-DTPA extractable P (<4.0 mg kg−1 soil) but has adequate AB-DTPA extractable K (>100 mg kg−1 soil) with a pH of 7.60 and organic matter content <1% (Table 1). Rainfall and temperature data were collected from the weather station of Agronomy Research Farm and summarized in Figure 2. In addition to rainfall, crop water requirement was fulfilled by supplying water through surface irrigation according to crop requirement.
Property | Unit | Data |
---|---|---|
Clay | % | 2.8 |
Silt | % | 50 |
Sand | % | 47.2 |
Textural class | — | Silty loam |
pH (1:5) | — | 7.60 |
EC (1:5) | dS m−1 | 0.18 |
Organic matter | % | 0.39 |
Total nitrogen | % | 0.06 |
Phosphorus | ppm | 2.86 |
Potassium | Ppm | 120.48 |
Mineral nitrogen | mg kg−1 | 35 |
Pre-sowing physicochemical properties of soil (0–0.30 m depth).
Weather data of spring maize growing season from March to June, 2014.
The experimental field was irrigated before sowing for weed germination and then plowed with cultivator to prepare a fine seed bed for sowing. The experiment consisted of two factors, i.e., beneficial diazotrophic bacteria (
The experiment was conducted at three factorial randomized complete block designs (RCBD) with three replications. The size of plots was 4.2 × 4 m. Row-to-row distances for maize crop were 0.70 m, whereas plant-to-plant distances were 0.20 m. Each plot had six rows. There were 30 plots having treatment combination of two beneficial diazotrophic bacteria and five organic and inorganic source ratios.
Biological yield data was recorded by harvesting four central rows in each plot, sundried and weighed by electronic balance whereas harvested central rows were threshed individually through electric thresher and weighed through electronic balance to obtain grain yield and then converted into kg ha−1 by the following formula:
Organic matter in soil was determined by the modified method of Nelson and [25]. The nitrogen content in soil, stover, and grains were determined by following Kjeldahl method according to the proposed methodology of Bremner and Mulvaney [26].
The data recorded was analyzed statistically using analysis of variance techniques appropriate for randomized complete block design. Statistical analysis was done with Statistic-X software. Means were compared using LSD test at 0.05 level of probability, when the F-values was significant [27]. The possible interactions were graphically made using a software of Microsoft Excel 365.
Beneficial microbes significantly influenced biological yield (Table 2). Highest biological yield (11,708 kg ha−1) has been observed with the application of beneficial diazotrophic bacteria as compared to without beneficial microbes. This may be due to diazotrophic bacteria increase the speed of decomposition and mineralization that improve nutrients’ availability to the crop and total dry matter production [28]. Similarly, the application of organic and inorganic fertilizers also significantly affects the biological yield, and greater biological yield (12,092 kg ha−1) was achieved with the application of 50:50 N ratio of organic and inorganic fertilizers. Lower biological yield (10,961 kg ha−1) was attained with the application of 100% N from inorganic source. It might be due to the reason that nitrogen from organic sources are slow release, while inorganic nitrogen is readily available to plant which may not be available at later stages. The combined application of N from inorganic source (urea) and organic source in a ratio of 75:25 improved grain yield, straw yield, and biological yield, whereas 50:50 N ratio increased uptake of nitrogen [29]. Biological and grain yield was significantly improved with the application of 50% nitrogen from inorganic sources in combination with the application of 25% N from FYM and 25% N from poultry manure [30]. The applications of organic and inorganic N fertilizers significantly enhanced biological yield and grain yield [31, 32]. The application of organic and inorganic nitrogen 50% from urea and 50% from FYM or 50% poultry manure significantly enhanced biological yield, grain yield, and harvest index (%) [28].
Beneficial microbes | Biological yield (kg ha−1) | Grain yield (kg ha−1) | Soil organic matter (%) | Bulk density (g cm−3) |
---|---|---|---|---|
Without BM | 10,733 b | 3662 b | 0.87 b | 1.19 a |
With BM | 11,708 a | 3803 a | 1.19 a | 1.17 b |
LSD | 602.29 | 79.52 | 0.08 | 0.02 |
Organic and inorganic ratios | ||||
0:100 | 10,961 b | 3592 b | 0.87 c | 1.23 a |
25:75 | 11,401 ab | 3793 ab | 0.94 bc | 1.22 ab |
50:50 | 12,092 a | 3907 a | 1.02 b | 1.19 b |
75:25 | 10,621 b | 3684 b | 1.10 ab | 1.15 c |
100:0 | 11,027 ab | 3686 b | 1.22 a | 1.09 d |
LSD | 952.3 | 125.7 | 0.13 | 0.03 |
Interaction | ||||
BM × R | Figure 3 | ns | Figure 4 | ns |
Biological yield and grain yield of spring maize and soil organic matter and soil bulk density as influenced by beneficial microbes and organic and inorganic ratios.
Mean values of the different categories in each column with different letters discloses significant differences (p ≤ 0.05) using LSD test.
The graph trend showed that biological yield increased with organic and inorganic nitrogen ratio from 0:100 to 50:50, whereas a decreased trend in biological yield was observed from 50:50 to 100:0 with both beneficial microbes (Figure 3). This might be due to the fact that beneficial microbes rapidly decomposed organic matter, provided nutrients, and increased availability of nitrogen from both organic and inorganic sources [28].
Biological yield as affected by beneficial microbes and organic and inorganic ratios.
Beneficial diazotrophic bacteria significantly increased the grain yield (Table 2). Highest grain yield (3803 kg ha−1) has been noted with the application of beneficial microbes as compared to without beneficial microbes. This may be due to the reason that beneficial microbes increase decomposition and mineralization and improve nutrients availability for more total dry matter production [28].
Organic and inorganic fertilizer significantly influenced grain yield, and higher grain yield (3907 kg ha−1) was achieved with the application of 50:50 N organic and inorganic ratio, whereas lower grain yield (3592 kg ha−1) was observed with the application of 100% N from inorganic. It might be due to the reason that N from organic sources is slow release, whereas inorganic nitrogen is readily available to plant that may function in vegetative growth. The application of organic and inorganic N with a ratio of 75:25 prominently improved yield and yield indices, whereas a 50:50 ratio increases nitrogen uptake [29]. Biological and grain yield was significantly higher with the application of 50% nitrogen from inorganic sources with the application of 25% N from FYM and 25% N from poultry manure [30]. The application from organic and inorganic N fertilizer significantly influenced biological yield and grain yield [31, 32]. The application of organic and inorganic nitrogen 50% from urea and 50% from FYM or 50% poultry manure significantly enhanced biological yield, grain yield, and harvest index % [28].
Beneficial microbes significantly affected soil organic matter (Table 2). Highest soil organic matter (1.19%) has been perceived with the application of beneficial microbes as compared to without diazotrophic bacteria. This may be due to the beneficial microbe increases the speed of decomposition and increase mineralization and produced more exudes [28]. Organic and inorganic ratios significantly affected soil organic matter. More soil organic matter (1.22%) was achieved with the application of a 100:0 ratio of organic and inorganic fertilizer, whereas less soil organic matter (0.87%) was perceived by the application of 100% from inorganic fertilizer. It might be due to beneficial microbe rate of decomposition of organic fertilizer which improves soil organic matter and soil organic carbon. The combined application of organic and inorganic fertilizers improved soil organic matter and total nitrogen [33]. Organic manure linearly increased soil organic matter [34]. The integration of organic with inorganic fertilizer significantly improved crop production and N, P, K, soil pH, soil EC, and organic matter [35, 36]. Organic sources improved soil nutrient, soil organic matter, and soil organic carbon [37]. The graph trend showed that soil organic matter increased linearly with the increased of organic and inorganic ratio from 0:100 to 100:0 in both beneficial and without beneficial microbes (Figure 4). This might be due to organic matter was applied 100% from organic sources, and beneficial microbes rapidly decomposed organic matter, thus increasing mineralization and soil organic matter [28].
Soil organic matter as affected by beneficial microbes and organic and inorganic ratios.
Beneficial microbes significantly affected soil bulk density as highest soil bulk density (1.19 g cm−3) has been perceived without the application of beneficial microbes as compared to with beneficial microbes (Table 2). This may be due to beneficial microbes increase the speed of decomposition and increase mineralization and provide nutrients, thus decreasing bulk density; these results are in line with Muhammad et al. [28]. Organic and inorganic ratios significantly affected soil bulk density. Soil bulk density (1.23 g cm−3) was recorded with the application of a 0:100 ratio of organic and inorganic, whereas less soil bulk density (1.09 g cm−3) was determined by the application of 100% of organic. It might be due to the integration of organic and inorganic fertilizer which improved soil bulk density. Bulk density decreased with the application of FYM and poultry manure to soil [38]. Bulk density linearly decreased with soil organic matter [34]. The integration of organic with inorganic fertilizer significantly decreased bulk density of soil [35, 36].
Beneficial diazotrophic bacteria significantly affected soil nitrogen content (Table 3). Highest soil nitrogen content (0.39%) has been received with the application of beneficial microbes as compared to without beneficial microbes. It may be due to beneficial microbe increases the speed of decomposition and increases mineralization and provides nutrients, thus more nitrogen in soil; these results are in line with Muhammad et al. [28]. Organic and inorganic ratios significantly affected soil nitrogen content. More soil nitrogen content (0.47%) was achieved with the application of 50:50 ratio of organic and inorganic, whereas less soil nitrogen content (0.24%) was recorded by the application of 100% from inorganic. It might be due to the decomposition of organic matter is slow and the slow release of nutrients; therefore, plots of organic sources have higher N, P, and K than plots having inorganic fertilizer. Organic sources improved soil nutrient and organic carbon [37]. Soil mineral nitrogen increased (22.4%) with the addition of organic fertilizers like FYM, poultry, and legume residues [39]. For better crop growth and sustainability, addition of organic matter is best source of nutrient availability [34]. The integration of organic with inorganic fertilizer significantly improved crop production and N, P, K, soil pH, soil EC, and organic matter [35, 36].
Beneficial microbes | Soil nitrogen content (%) | Stover nitrogen content (%) | Grain nitrogen content (%) |
---|---|---|---|
Without BM | 0.34 b | 0.88 b | 1.74 b |
With BM | 0.39 a | 1.10 a | 1.91 a |
LSD | 0.01 | 0.08 | 0.01 |
Organic and inorganic ratios | |||
0:100 | 0.24 e | 0.89 b | 1.56 c |
25:75 | 0.30 d | 0.98 ab | 1.81 b |
50:50 | 0.38 c | 1.11 a | 2.01 a |
75:25 | 0.44 b | 0.99 ab | 1.97 ab |
100: 0 | 0.47 a | 0.98 ab | 1.78 b |
LSD | 0.02 | 0.13 | 0.16 |
Interaction | |||
BM × R | Figure 5 | ns | Figure 6 |
Soil nitrogen content, stover, and grain nitrogen content of spring maize as influenced by beneficial microbes and organic and inorganic ratios.
Mean values of the different categories in each column with different letters discloses significant differences (p ≤ 0.05) using LSD test.
The graph trend showed that soil organic matter increased linearly with the increased of organic and inorganic ratio from 0:100 to 100:0 in both beneficial and without beneficial microbes (Figure 5). This might be due to organic matter was applied 100% from organic sources, and beneficial microbes rapidly decomposed organic matter, thus increasing mineralization and soil organic matter [28].
Soil nitrogen content as affected by beneficial microbes and organic and inorganic ratios.
Beneficial diazotrophic bacteria significantly affected stover nitrogen content (Table 3). Highest stover nitrogen content (1.1%) has been perceived with the application of beneficial microbes as compared to without beneficial microbes. It can be due to beneficial microbes increase the speed of decomposition and increase mineralization and provide nutrients for crop to achieved more total nutrient production [28]. Our results indicated that organic and inorganic N ratios significantly influenced N stover content in maize crop. The application of a 50:50 ratio of organic and inorganic nitrogen resulted in higher stover N content (1.11%), whereas lower stover nitrogen content (0.89%) was attained with the application of 100% N from inorganic source. It might be due to the reason that inorganic fertilizer was quickly available, while organic fertilizer was slowly available to crop. The N, P, and K concentration in straw was significantly increased with the combined application of 10 t N ha−1 from poultry manure (PM) and 200 kg N ha−1 from NPK as compared to control [40]. N, P, and K uptake by straw and grains was significantly influenced by organic and inorganic fertilizer [41, 42, 43]. The application of chemical fertilizers, FYM, green manures, and compost to the soil resulted in improved uptake of N, P, and K [44, 45].
Beneficial diazotrophic bacteria significantly increase grain nitrogen content (Table 3). Highest grain nitrogen content (1.91%) has been perceived with the application of beneficial microbes as compared to without beneficial microbes. This may be due to beneficial microbes increase the speed of decomposition and increase mineralization, and more nitrogen content was transferred to grain [28]. Organic and inorganic ratios significantly improved grain nitrogen content, and higher grain nitrogen content (2.01%) was achieved with the application of a 50:50 organic and inorganic N ratio, whereas less grain nitrogen content (1.56%) was achieved with the application of 100% inorganic fertilizer. It may be due to the quick availability of inorganic fertilizer, whereas organic fertilizer is slowly available to the crop. Nitrogen and phosphorus are higher in grains than straw, while potassium content was higher in straw as compared to grains. N, P, and K content was significantly improved by organic fertilizer both in straw and grain [46]. Growth, yield, and NPK concentrations were significantly increased with integrated organic and inorganic fertilizers [3]. Macro- and micronutrients in the grains and straw of wheat were significantly improved with the application of FYM as inorganic N fertilizer [47]. Higher N, P, and K uptake by crop was observed with organic N sources [48].
The graph showed that grain nitrogen increased with organic and inorganic N ratio from 0:100 to 50:50. This trend was declined with N ratio from 50:50 to 100:0 for both beneficial microbes (Figure 6). This might be due to the reason that beneficial microbes rapidly decomposed organic matter, provided nutrients, and also increased availability of nitrogen from both organic and inorganic sources [28].
Grain nitrogen content as affected by beneficial microbes and organic and inorganic ratios.
High maize yield and nitrogen content was better observed with the application of beneficial microbes and organic and inorganic nitrogenous fertilizer with a ratio of 50:50. Soil bulk density, soil organic matter, and soil total nitrogen were significantly improved with beneficial microbes combinedly apply with organic and inorganic nitrogenous fertilizer in a ratio of 100:0. Therefore, the application of beneficial microbes and organic and inorganic nitrogenous fertilizer with a ratio of 50:50 has been recommended for better nitrogen uptake and higher yield of spring maize in Peshawar valley.
As water scarcity becomes even more present in underdeveloped countries, developed states have to face a different challenge: water pollution from emerging contaminants [1]. Pollutants such as pharmaceutical residues come in a variety of forms and origins causing great issues [2, 3]. Many measures are established to reduce such contamination mostly in the form of water treatments and legislation [1]. However, great limitations are associated with the traditional techniques used in wastewater treatment plants. Most of them are due to either their cost or their low removal efficiency on emerging contaminants [4, 5]. For instance, degradation processes such as ozonation or chlorination were proven efficient for the degradation of organic molecules [6, 7]. However, these techniques have high operational costs and often cause dangerous degradation by-products that would follow the water flow and end up in rivers and lakes [8].
A specific technique distinguishes itself from the others; sorption. Such a treatment has the advantage of capturing contaminants with lower operational costs and without generating any dangerous by-products [5]. The most exploited sorbent is activated carbon (AC) which has high adsorption capacity and low specificity [5, 9]. Its efficiency comes from its high surface area on which contaminants can be adsorbed through interaction forces such as van der Waals [5]. It is often used for water purification through commercially available filters. Activated carbon can be made from various biological residues giving value to waste [9, 10, 11]. However, the synthesis of ACs necessitates the carbonization of the material itself and an activation step which can be costly and not environmentally friendly [5].
Another option is the production of adsorbents from highly available natural polymers. Therefore, the product would be green, inexpensive and biocompatible. As many biosorbents are still being studied throughout the world, their potential is not fully exploited, and low attention is given to polymers such as lignin. Lignin, the second most abundant biopolymer after cellulose, is a naturally occurring polymer composing wood at 20–40% [12, 13]. Giving resistance and rigidity to the cell walls of plants, this biopolymer is water insoluble and resistant to organic solvents [12]. Lignin is also a highly variable biopolymer which is composed of its three main monomers (coniferyl alcohol, sinapyl alcohol and p-coumaryl alcohol) in a random pattern [13]. Its composition is further randomized by the addition of functional groups (mainly sulfate and carboxyl groups) during its extraction phase [13]. Even though it is variable, all lignins contain phenols, aliphatic alcohols and ethers [14]. Right now, lignin is mostly used to produce energy in the pulp and paper industry (where it is mainly extracted) and regenerate chemical reagents [15]. Although it is not its main use, lignin has already been used as an adsorbent for heavy metals or even dyes [16, 17, 18, 19]. However, to our best knowledge, lignin has never been tested for pharmaceutical residues removal at trace levels. Therefore, the development of this lignin-based electrospun nanofibrous materials open up new opportunities for reducing inputs of pharmaceuticals into the environment.
To be able to achieve a satisfying adsorption capacity for trace contaminants and compete with AC, it is necessary to increase the surface area of the material. A simple way is the transformation of the polymer into nanofibres through electrospinning. This technique exploits the stretching of polymers exposed to a high voltage under defined experimental conditions [20, 21]. In electrospinning, a polymer is dissolved and introduced into a syringe (see Figure 1). Voltage is applied between the needle of the syringe and a collector plate. As a drop is formed at the tip of the needle, its surface tension will be disrupted by the electrical field and cause a Taylor cone and the formation of the fibres [22, 23]. Typically, fibres as thin as the nanometres scale are obtainable through this method [20, 24]. Because of its limited known uses, the electrospinning of lignin is not popular even if its electrospinnability with a co-polymer is known [23, 24, 25]. Hence, the material and the application are unprecedented.
Typical electrospinning setup.
In this study, electrospun lignin nanofibres will be exploited for the adsorption of pharmaceutical residues in water. Precisely, fluoxetine and venlafaxine (antidepressant), carbamazepine (anticonvulsant) and ibuprofen (anti-inflammatory) will be tested for adsorption on developed nanofibres. The material’s adsorption will be characterized by kinetic and isotherm studies. Its capacity to be reusable will also be determined by using various desorption environments.
Alkali lignin (AL) low sulfur (28,000 Da, CAS 8064-05-1) and poly (vinyl alcohol) (PVA) 98–99% hydrolysis (31,000–50,000 Da, CAS 9002-89-5) were provided by Sigma-Aldrich (St-Louis, MO, USA). Sodium hydroxide pellets (NaOH) 98% (CAS 1310-73-2) and methanol HPLC grade (CAS-67-51-1) were provided by Alfa Aesar (Ward Hill, MA, USA). Hydrochloric acid (CAS 7647-01-0), acetonitrile HPLC grade (CAS 75-05-8), sodium citrate dihydrate (CAS 6132-04-3), sodium chloride (CAS 7647-14-5) and o-phosphoric acid HPLC grade 85% v/v (CAS 7664-38-2) were purchased from Fisher Scientific (Fair Lawn, NJ, USA). Fluoxetine hydrochloride (FLX) (CAS 56296-78-7), venlafaxine hydrochloride (VEN) (CAS 99300-78-4), carbamazepine (CAR) (CAS 298-46-4) and ibuprofen (IBU) (CAS 15687-27-1) were provided by Sigma-Aldrich (Oakville, ON, Canada). Citric acid anhydrous (CAS 77-92-9) was provided by Jungbunzlauer (Bale, Swiss). Commercial adsorbents used for comparison were Amberlyst® 15 (CAS 39389-20-3), Dowex® Marathon® C (CAS 69011-20-7), SiliaFlash® F60 40–60 μm particle size, fumed silica (CAS 112945-52-5) and Valfor® 100 sodium aluminosilicate zeolite respectively from Alfa Aesar (Ward Hill, MA, USA), Sigma-Aldrich (St-Louis, MO, USA), Silicycle (Quebec City, QC, Canada), and The PQ Corporation (Valley Forge, PA, USA).
The electrospinning setup was composed of a syringe pump (Kd scientific) and a power supply (Gamma High Voltage Research). Two laboratory ovens (Fisher Scientific Isotemp Oven and ThermoScientific HERATherm oven) were used for conservation and stabilization of the membranes. An orbital shaker (Lab Line model 3520) and an environmental orbital shaker incubator (Lab Line model 3528) were used for adsorption tests. Nanofibres were characterized using a Hitachi SUI510 scanning electron microscope (SEM). A Shimadzu Prominence I-series high performance liquid chromatograph (HPLC) coupled with a diode array detector (DAD) with a reverse phase column XB-C18, 100 Å, 150 × 3 mm, 2.6 μm particle size (Phenomenex, Kinetex®) was used to analyze contaminated water samples.
The electrospinning solutions were prepared as reported in Camire et al. [26]. Briefly, solution of AL and PVA 15% wt were prepared by dissolving AL in NaOH 1 M and PVA in water heated to 80°C for 60 min. After the dissolution, both solutions were mixed in a mass ratio of 1:1. This solution was stirred for an hour and settled at room temperature for another hour. The AL:PVA solution was then used directly for electrospinning or kept at 4°C in a refrigerator for a maximum of 1 month. Before use, the refrigerated solution was brought to room temperature in a hot water bath for an hour.
The previous prepared solution was injected in a 5 mL syringe with a 20-gauge needle for electrospinning. The syringe was set to the syringe pump and voltage was applied between the needle and the collector. The collector was a non-stick cookie sheet giving good electrospinning, reusability and easy recovery of the nanofibres. The electrospinning parameters were based on results obtained previously [26]. The conditions were a flow rate of 0.1 mL/h with an applied DC voltage of 15 kV. The collector was placed 20 cm away from the tip of the needle. The temperature was kept at 22°C and relative humidity maintained between 10 and 40%. A razor blade was used to recover the nanofibrous mat from the collector. All experiments were conducted in a customized electrospinning box. The electrospun nanofibre mat was then kept overnight in a laboratory oven at 80°C for drying and stabilization purposes.
Due to electrospun nanofibres’ high solubility in water, AL:PVA nanofibres mats were stabilized using two consecutive techniques. Both techniques are based on previous works [26]. The first method used the glass transition temperature of polymers to raise their crystallinity and hence their water resistance. Therefore, nanofibres were heated in a laboratory oven at 160°C for 3 h. Next, the membranes were immersed in a 0.5 M sodium citrate buffer pH 4.5 for a period of 3 h. This process aims to protonate AL’s phenol groups which were previously deprotonated during the preparation of the electrospinning solution in a method similar to the extraction methods of black liquor [15]. During this step, the morphology of the membrane changes drastically due to the dissolution of a part of the PVA. The dissolution causes a rise in the concentration of AL (the membranes become browner) and cross-linking of the nanofibres. After exposure to the buffer, the membranes were washed several times with purified water, stretched and dried on a metallic surface. Finally, the nanofibrous mats were recovered using a razor blade.
In this section, three types of tests were performed: adsorption of a single contaminant on AL:PVA membranes as well as commercial adsorbents, and adsorption of multiple contaminants on AL:PVA membranes. All adsorption tests were conducted in batches by adding a defined amount of adsorbent to a stirred solution containing a specific concentration of contaminants. All tested solutions were composed of purified water with 5% of methanol and contaminants adjusted at the targeted concentration. The organic solvent’s purpose was to ensure that pharmaceuticals were solubilized in water. Separate 2500 ppm standard solutions of FLX, VEN, CAR and IBU were prepared by dissolving the corresponding stock solutions in methanol. Those solutions were then diluted for adsorption tests. Before, during and after the adsorption test, aliquots of 500 μL of the contaminated water were sampled, diluted with 500 μL of mobile phase, vortexed and injected in HPLC-DAD to determine the concentration of contaminants in solution. For tests using one contaminant on AL:PVA membranes, 50 ppm FLX solution was used as a model contaminated water. For tests with commercial adsorbents, adjustments were made to compensate for the size difference between adsorbents. Therefore, solutions of 250 ppm FLX in 10 mL were prepared to keep the same contaminant to adsorbent mass ratio. For tests with multiple contaminants, 12.5 ppm of FLX, IBU, CAR and VEN were added to water to simulate contaminated water.
The adsorption tests were initialized by the addition of 25 mg of adsorbent (nanofibres or commercial adsorbent) to the solution. The tests were conducted over a period of 150 min to ensure that equilibrium was reached. Using a calibration curve and the area under the peaks on the chromatograms, the remaining concentration of the solution was calculated. From this value, the adsorption capacity at time
where
For samples containing one contaminant, samples injected in HPLC-DAD were eluted using a mobile phase composed of acetonitrile and a 0.1% solution of phosphoric acid (60:40% v/v ratio). The flow rate was adjusted at 0.45 mL/min for 3.75 min with a detection at 230 nm. For samples containing more than one contaminant, the mobile phase was composed of acetonitrile and 0.1% phosphoric acid with a ratio of 40:60% v/v. The flow rate was adjusted to 0.5 mL/min for a period of 20 min with a detection still at 230 nm. In all cases, 10 μL of the samples were injected using an autosampler. For all contaminants, a 10-point (0.5–100 ppm) calibration curve was established to determine the concentration. All tests were performed in triplicate.
Kinetic curves were obtained by sampling at intervals during the adsorption process. Samples were collected at 0, 5, 10, 15, 20, 30, 40, 50, 60, 75, 90, 120 and 150 min after the addition of the adsorbent. The equilibrium time of 150 min was determined by an initial kinetic test. The same sampling and injection processes as traditional adsorption tests were conducted for kinetic studies. By calculating the adsorption capacity through time, it is possible to obtain a kinetic curve which can be compared to adsorption kinetic models. Adsorption kinetic models give crucial information on the adsorption parameters and the limiting processes occurring during the adsorption. Typically, three steps occur during the adsorption: transfer of the adsorbate to the external surface of the adsorbent, internal diffusion of the adsorbate to active sites and sorption reaction with the adsorbent [27, 28]. In this study, three models were compared: pseudo-first order, pseudo-second order and Elovich. In all cases, the kinetic constants were calculated using Matlab’s curve fitting app. To determine the best fitting model, determination coefficients and root of mean square errors (RMSE) were compared. The pseudo-first order model is represented by Eq. (2):
In Eq. (2),
where
where
The adsorption isotherms were performed for AL:PVA membranes to obtain information on the adsorption sites and the type of reaction occurring. For these tests, 50 ppm solutions of FLX were prepared as typical adsorption tests. Samples were collected at 0 and 180 min (equilibrium). From those samples, the concentration (
Models | Non-linear equation | Equation |
---|---|---|
Freundlich | (5) | |
Langmuir | (6) | |
Sips | (7) | |
Redlich-Peterson | (8) |
Here,
The thermodynamic parameters (enthalpy, entropy and Gibbs’s free energy) are calculated through a thermodynamic study. These parameters are obtained by using the
where
where
The capacity of an adsorbent to be desorbed is also an important characteristic value since it can have a significant contribution on economics and life cycle assessment of the process. Therefore, the reusability of the AL:PVA membranes was evaluated by desorption. For this purpose, multiple conditions were tested to recover the contaminant safely. Hence, the nanofibres were exposed to solutions of methanol (to create an environment in which the contaminant is highly soluble), purified water (to verify the risk of desorption due to equilibrium), heated solutions (might be able to revert the sorption reaction), salts (ion exchange and/or competition) and combined techniques (except heated methanol solutions). In all cases, the membranes were immersed in 50 mL of solution for 4 h. For temperature effect, solutions were heated to 60°C to verify desorption. The salt used for desorption was sodium chloride since it is a simple and non-toxic substance, largely found in typical wastewater. Concentrations of sodium chloride of 1, 2 and 3 M were tested. Initial and final samples were injected in HPLC-DAD to determine the concentration of FLX recovered. The desorption solution showing the best desorption efficiency was used for repeated adsorption/desorption cycles to evaluate the reusability. Between each test, the membranes were recovered and dried in a vacuum desiccator to prevent humidity from interfering with the measured masses. For membranes exposed to salts, these were washed several times with purified water to dissolve salts, and then dried in a vacuum desiccator.
Mixed solutions of AL and PVA were prepared for the production of membranes for adsorption tests. Using the specified electrospinning parameters, it was possible to obtain steady nanofibre formation for periods of a few hours to produce thin nanofibrous mats. Those were thermally stabilized giving the nanofibres a brownish colour and more rigidity. Their immersion in a sodium citrate buffer finalized the stabilization process to provide fibres stability at various pHs enabling their use for adsorption. As shown in Figure 2, the stabilization process had a slight impact on the visual aspects of the membranes. However, the impact is more obvious when seen by scanning electron microscopy. Figure 2b shows that nanofibres of 183 ± 5 nm in diameter were obtained by the electrospinning with a low number of beads or defects. This size does not technically correspond to nanofibres (0–100 nm), but the adsorption properties shall be akin to real nanofibres considering the small difference. Figure 2d shows the nanofibres after a thermal process. This image shows a similar nanofibrous aspect with small variations of the nanofibre diameter (156 ± 5 nm). However, nanofibres seem to be closer to each other with slight cross-linking giving it rigidity. With the chemical stabilization (Figure 2f), the cross-linking is obvious due to swelling and fusing of nanofibres (188 ± 10 nm). However, it should be emphasized that this kind of treatment often causes the loss of porosity of the material. In fact, without the thermal process, the acid treatment causes the nanofibres to completely fuse together lowering the porosity of the material [26, 32].
Images of AL:PVA nanofibres after electrospinning (a), after thermal treatment (c) and after final chemical treatment (e) and corresponding MEB images at 2500× (b, d and f, respectively).
Interestingly, humidity had a real impact on the different steps of electrospinning. In fact, at low humidity (e.g., 10%), it was possible to electrospin, but the efficiency was lower. This might be due to the fast evaporation of the solvent during electrospinning which caused the drop of polymers at the tip of the needle to dry before electrospinning or the electrospinning jet to break before reaching the collector surface. The recovery of nanofibres was also more difficult due to higher adherence to the metal plates. At higher humidity (between 30 and 40%), the electrospinning resulted in a larger nanofibre mat surface area on the collector, which was easily peeled off, almost without the use of a razor blade. The advantages of the higher humidity also appeared during the stabilization step. Indeed, a higher humidity reduced the drying speed of the membranes, but also reduced their stickiness to the collector plate. It is therefore important to control the humidity within a certain range to achieve good nanofibre mat formation and easy processability.
The adsorption tests were first conducted for FLX since it has the most potential for adsorption. Therefore, 25mg of AL:PVA nanofibres were used to adsorb 50 ppm of FLX in a 50 mL solution. The test lasted 150 min with a sample collected at the beginning and at the end. Table 2 shows the results obtained for this adsorption test. For comparison purposes of the adsorption, the same test was also carried out using commercial adsorbents. However, considering the smaller size of the commercial adsorbent, adjustments were necessary to conduct adsorption tests without any bias. Hence, the volume of the solution was reduced to 10 mL and the concentration was risen to 250 ppm to keep the same mass of FLX (2.5 mg solution) for the same mass of adsorbents. Therefore, the maximum adsorption capacity obtainable for each test was 100 mg/g. The summary of these results is available in Table 2.
Adsorbent | Adsorption capacity (mg/g) |
---|---|
AL:PVA nanofibres | 78.24 ± 1.35 |
Amberlyst® 15 | 80.96 ± 0.35 |
Dowex® Marathon® C | 77.03 ± 0.94 |
Valfor® 100 | 49.00 ± 4.39 |
Fumed silica | 8.54 ± 0.62 |
Siliaflash® F60 | 4.25± 0.35 |
Adsorption capacity comparison of AL:PVA membranes with commercially available adsorbents.
As expected, unfunctionalized silica adsorbents (Siliaflash® and fumed silica) had low adsorption potential for FLX. This is due to the lack of functional groups for adsorption and/or ionic charges. Due to its ion-exchange properties, Valfor® had a better adsorption propensity than silica. However, considering the exchange mechanism (exchange with a sodium ion from the adsorbent) and the size of the FLX molecules, it is possible that the adsorption was limited by the number of available sites and competition between FLX molecules. This type of sorbent might be more appropriate for metal ions [33]. Both ion-exchange resins had good adsorption capacities. Both being cation exchange resins and strongly acidic, they possessed functional groups (sulfate) appropriate for the adsorption of ionic molecules such as alkaline pharmaceutical residues. It is therefore encouraging that a biosorbent made of lignin can yield similar or better adsorption capacities than commercial sorbents.
For a potential application in wastewater treatments, it is important to evaluate its capacity to adsorb multiple and various contaminants at the same time. Hence, the adsorption capacities of the developed nanofibres were compared with four contaminants, fluoxetine (antidepressant), venlafaxine (antidepressant), carbamazepine (anticonvulsant) and ibuprofen (anti-inflammatory). The adsorption was evaluated separately and simultaneously to detect possible competitions between contaminants (see Table 3).
Contaminant | Simultaneous adsorption capacity* (mg/g) | Individual adsorption capacity** (mg/g) |
---|---|---|
Fluoxetine (FLX) | 22.85 ± 0.28 | 78.24 ± 1.35 |
Venlafaxine (VEN) | 11.05 ± 1.02 | 49.76 ± 2.80 |
Carbamazepine (CAR) | 1.02 ± 0.02 | 8.04 ± 0.01 |
Ibuprofen (IBU) | 0.62 ± 0.39 | 5.00 ± 0.46 |
Affinity comparison of the AL:PVA nanofibres for various pharmaceutical contaminants.
Initial concentration of 12.5 ppm.
Initial concentration of 50 ppm.
The contaminants having the most affinity for the membranes were in the decreasing order FLX, VEN, CAR and IBU. IBU and CAR had a low affinity for the nanofibres with almost no adsorption in simultaneous adsorption. This follows the logical assumption that could be made from the structures of the molecules and their chemical properties. For instance, both FLX and VEN are alkaline pharmaceuticals that are easily protonated at a neutral pH. However, fluoxetine has more aromatic rings and possesses Fluor promoting hydrogen bonding and π-stacking. For CAR and IBU, the molecules are respectively neutral and anionic at pH 7 which completely prevent any ionic bonding between lignin’s phenols and cationic groups from pharmaceuticals. AL is also a weak acid which would hardly make any ionic bonds with an acidic compound such as IBU.
Kinetic studies give interesting data about the reaction order, type and time necessary to reach equilibrium. For this purpose, kinetic curves were plotted by observing the adsorption capacity at multiple times for FLX alone and for the simultaneous adsorption of contaminants. First, adsorption capacity for fluoxetine was measured at 0, 5, 10, 15, 20, 30, 40, 50, 60, 75, 90, 120 and 150 min to obtain a kinetic curve. Using Matlab®, the kinetic models’ parameters were calculated using non-linear regression analysis. These results are shown in Table 4. From Figure 3, it is possible to observe the different kinetic curves corresponding to pseudo-first and pseudo-second order and Elovich kinetic models as well as the experimental values. From Figure 3 and Table 4, it is clear that the pseudo-first order best fitted the experimental data. The pseudo-first order indicates that the adsorption occurs in one step. Good correlation with this model also shows that the reaction is regulated by the time necessary for the reaction and not by the diffusion in the nanofibrous material. However, the literature shows that no assumptions can be made from the kinetic model to determine the adsorption mechanism (physisorption or chemisorption for instance) [28]. Still, considering the chemical structure of lignin, physisorption is more logical. For physisorption, the main possible interaction forces are van der Waals, π-stacking, hydrogen bonds, hydrophobicity, steric and polarity interactions [10].
Kinetic model | Parameter | Value |
---|---|---|
Pseudo-first order | 0.9989 | |
RMSE | 0.7117 | |
0.086 | ||
63.98 | ||
Pseudo-second order | 0.9790 | |
RMSE | 3.046 | |
0.0017 | ||
71.14 | ||
Elovich | 0.9229 | |
RMSE | 5.832 | |
33.37 | ||
0.08453 |
Kinetic parameters for pseudo-first order, pseudo-second order and Elovich models.
Kinetic curve for the adsorption of FLX on AL:PVA nanofibres.
More information can also be obtained from Figure 3. For instance, following the observation of the graph, it is possible to conclude that equilibrium is obtained within 1 h and that most of the adsorption occurs in the first 20 min. Such a fast adsorption could allow multiple applications to the adsorbent in addition to the retention of contaminants in wastewater. Also, due to the sampling, the total amount of contaminant available is lower which causes a lower adsorption capacity during kinetics. During the test, it was also possible to follow the adsorption process by monitoring of the pH becoming more acid as the alkaline FLX was removed from the solution.
A kinetic experiment was also conducted with simultaneous contaminants. The kinetic curve for each contaminant is presented in Figure 4. For FLX, the curve was almost identical to the individual curve which suggests that no significant competition occurred for FLX. For VEN, the adsorption was significantly longer with equilibrium at 90 min. Its final adsorption capacity, however, remained similar by roughly adsorbing half of the initial concentration. For IBU and CAR, the adsorption was fast (equilibrium within 5 min) and their adsorption capacity was low. Their low adsorption capacities show that AL:PVA membranes might be ineffective for such contaminants except for really low quantities. Coupling AL:PVA nanofibres with other adsorbents could be an alternative to adsorb a wider pharmaceutical contaminants spectrum. For instance, recent studies on chitosan and poly (ethylene oxide) showed good adsorption capacities for IBU in water [32].
Kinetic curve for simultaneous adsorption of FLX, VEN, CAR and IBU.
The goal of the experiment is to understand the behaviour of adsorption sites while specific changes are made. By monitoring the variation of concentration and adsorption capacity at equilibrium while varying the mass of adsorbents, it is possible to obtain an isotherm curve which can be compared to isotherm models. The Freundlich, Langmuir, Sips (or Langmuir-Freundlich) and Redlich-Peterson models were compared to the data. The isotherm constants and statistical analysis of the fitting at various temperatures are presented in Table 5.
Isotherm | Parameter | 25°C | 40°C | 60°C |
---|---|---|---|---|
Freundlich | 0.9655 | 0.9510 | 0.8486 | |
RMSE | 4.716 | 6.200 | 6.113 | |
11.22 | 2.298 | 8.093 | ||
0.6441 | 1.131 | 0.6326 | ||
Langmuir | 0.9783 | 0.9374 | 0.8242 | |
RMSE | 3.746 | 7.006 | 5.893 | |
249.2 | 3.242e+4 | 175.3 | ||
0.02292 | 1.083e−4 | 0.02223 | ||
Sips | 0.9899 | 0.9510 | 0.8877 | |
RMSE | 2.859 | 6.933 | 6.079 | |
140.3 | 9.285e+4 | 82.32 | ||
0.05902 | 8.513e−5 | 0.06166 | ||
1.83 | 1.132 | 3.277 | ||
Redlich-Peterson | 0.9855 | 0.9510 | 0.8669 | |
RMSE | 3.423 | 6.933 | 6.620 | |
4.499 | 117.5 | 2.983 | ||
3.122e−4 | 50.23 | 1.523e−4 | ||
2.021 | −0.135 | 2.183 |
Isotherm parameters for various isotherm models at 25, 40 and 60°C.
Results show that, for all temperatures, the Sips model best fitted the experimental data with the highest R2 and RMSE coefficients. This model indicates that a contaminant will link to multiple adsorption sites simultaneously. Also, this model can also be reduced to both Freundlich and Langmuir isotherms depending on the concentration of contaminants (low concentration and high concentration respectively) [10, 27, 30]. Considering that in real remediation conditions the concentrations are lower, it would be appropriate to predict the adsorption to be closer to a Freundlich isotherm. In the Freundlich model, the adsorption occurs in multi-layers with heterogenous sites adsorbing a single molecule [10]. In the Langmuir model, however, the adsorption is in monolayers on homogenous sites [10]. In these types of models, the pH, the temperature and the concentration remain the dominating factors affecting adsorption. This is further observed when the temperature increased and the adsorption capacity accordingly got lower. However, the isotherm models had much lower correlation as the temperature went up.
Thermodynamic parameters give interesting information on energy transfers during adsorption. Using the experimental data obtained from fluoxetine’s isotherms and Eqs. (9) and (10), standard enthalpy, standard entropy, standard Gibbs’s free energy were calculated. For enthalpy, a value of −7987 J/mol or −7.99 kJ/mol was obtained which indicates that the adsorption reaction is exothermic. This means that no heat is necessary for efficient adsorption and that supplying heat would be unfavourable for adsorption in this case. Also, this value falls into the energy range normally associated with hydrogen bonds (4–50 kJ/mol) and π-stacking (8–12 kJ/mol) [34, 35]. For entropy, a value of 42.01 J/mol. k was obtained. A positive value indicates that there is a gain in entropy and that the reaction is favourable. For ∆G° (at 25°C), a value of −20.51 kJ/mol was calculated which shows that the reaction is spontaneous. Moreover, values close to −20 kJ indicate that physisorption is prevalent [31].
Hence, the adsorption seems to be an appropriate method for water remediation against pharmaceutical contaminants since it consumes low to no energy. Its exothermic nature is also advantageous in cold climate countries like Canada since heating costs would be higher. In addition, it is possible to use the information obtained through thermodynamic to develop a desorption method for nanofibres. For this reason, the use of heated solutions for desorption will be investigated in the next section.
One of the benefits of sorption is the possibility of desorption. In this way, multiple adsorption and desorption cycles are possible, and the material is reusable. For these reasons, various desorption solutions were tested on AL:PVA nanofibres for the recovery of FLX. This step’s purpose also was obtaining a simpler matrix in which the contaminants can easily be recovered (dried form) or disposed safely. The solutions used had to be either non-toxic or easily evaporated and reused. The effect of temperature was also investigated for a simple desorption method. Results obtained for each tested desorption method are presented in Table 6. As shown in this table, the use of an organic solvent such as methanol has the disadvantage of causing degradation of the membranes in addition to the desorption. Even, it is possible that the desorption detected is due to the degradation of nanofibres. Therefore, pure methanol and 50% methanol solution were discarded. Using pure water, almost no desorption occurred which means that the strength of the bond is sufficiently strong to prevent a new equilibrium. When pure water is heated, however, FLX can be desorbed to some extent (30%) which follows the assumptions made in thermodynamic study. Then, sodium chloride was tested for the desorption of FLX. First, 1 M NaCl solution was tested at room temperature which indicated that salts were effective to recover the pharmaceutical contaminant. Afterwards, the same desorption was tested at 60°C. With this method, more than 90% of the fluoxetine could be recovered without affecting the membrane’s integrity. The concentration of salt was also varied to verify if a higher concentration would give a better desorption. Instead, higher salt concentrations reduced desorption capacity. Considering the difference in size of FLX compared to NaCl, this might be due to the saturation of the solution in which the fluoxetine cannot be dissolved.
Desorption solution | Fluoxetine recovered (%) | Qualitative result |
---|---|---|
100% methanol | 89 | High mass loss |
50% methanol | 36 | Slight mass loss |
100% water | 1 | None |
100% water 60°C | 30 | None |
1M NaCl 25°C | 52 | None |
1M NaCl 60°C | 92 | None |
2M NaCl 60°C | 76 | None |
3M NaCl 60°C | 19 | None |
Impact of various desorption solutions on desorption of fluoxetine and AL:PVA nanofibres.
To attest the reusability of the membranes, the best desorption method (1M NaCl solution heated to 60°C) was tested for three adsorption/desorption cycles (see Figure 5). In this process, the membranes were dried and weighed before each adsorption or desorption tests to observe possible mass loss.
Adsorption/desorption cycles for FLX using 60°C 1 M NaCl solution.
To simplify comparison, Figure 5 shows the mass of FLX instead of the adsorption capacity. First, it is interesting to observe that the amount desorbed is increasing with desorption cycles. This can be due to a higher number of FLX molecules on the membranes on the second and third cycle (the amount not desorbed on the previous cycles plus the amount adsorbed on the current cycle). Moreover, the adsorption capacity of the membranes was not affected by the desorption as shown by the small rise in mass adsorbed on the third cycle. The small weight gain could have been caused by a slight rise in porosity of the material due to stretching during adsorption and desorption tests. During this test, no significant mass losses were measured through the 3 cycles. Since the membranes are not degrading and do not lose adsorption capacity after the third cycle, it would be logical to assume that the synthetized membranes could still be used for even more cycles.
The potential of AL:PVA nanofibres was clearly demonstrated through our study. This promising new technology can be exploited in many fields that require adsorption. For instance, the main application dedicated in this study is the adsorption of pharmaceutical contaminants in wastewater. In such application, the membranes produced could be incorporated in dynamic systems in wastewater treatment plants or even at the source in hospitals or medical centre effluents. In this way, most of the potentially harmful pharmaceutical residues would be removed and would not enter aquatic ecosystems.
Meanwhile, our research is also investigating the use of nanofibres for the collection and analysis of illicit drugs such as cocaine or methamphetamine. Results obtained from this study will be the object of a future study. However, encouraging results with more than 90% of retention was obtained for both drugs (unpublished results). Moreover, desorption is also efficient. In this way, illicit drugs in complex matrices could be transferred to a simpler matrix for direct analysis in liquid chromatography during forensic investigation.
As of now, the efficiency of the nanofibres was proven for alkaline pharmaceutical contaminants. However, its efficiency is rather poor for contaminants that are neutral or acidic such as CAR or IBU. Therefore, an interesting avenue would be the coupling or sequential use of AL:PVA nanofibres and another biosorbent such as chitosan. In fact, works from our research group showed that chitosan nanofibres are efficient for adsorption of IBU in aqueous medium [32]. Therefore, it would be interesting to test a nanofibrous structure composed of AL and chitosan or a sandwich-like structure made of both types of fibres on mixtures of contaminants. In addition, surface chemical modifications are considered in the near future.
Novel alkali lignin and poly (vinyl alcohol) (AL:PVA) nanofibrous membranes were tested for adsorption of pharmaceutical contaminants. Its efficiency to adsorb was first studied on a model contaminant, fluoxetine. An adsorption capacity of 78 mg/g was obtained which corresponds to the adsorption of 78% of fluoxetine present in the water. With further adsorption cycles, the membranes can adsorb up to 90% of contaminants. Compared to commercially available adsorbents (ion-exchange resins, zeolites and silica), the results are similar to costly ion-exchange resins (75–80 mg/g). Using kinetic and isotherm models, it is possible to conclude that nanofibres follow a pseudo-first order kinetic model and Sips’ isotherm model which indicate that the adsorbent is of the physical type with adsorption of the contaminants on multiple sites at the same time in a multi- or monolayer pattern (depending on the concentration). Looking at thermodynamics, adsorption on AL:PVA nanofibres is a favourable, spontaneous and exothermic reaction. This information could be used for the design of a desorption method in which the fluoxetine can be retrieved safely, and the membrane reused for at least two more cycles. The adsorption of multiple pharmaceutical contaminants (fluoxetine, venlafaxine, carbamazepine and ibuprofen) showed that nanofibres have more affinity for alkaline compounds, which adsorb more given the right amount of possible intermolecular forces occurring. Hence, for remediation applications, it would become necessary to combine this adsorbent with another one for maximum retention efficiency.
The authors would like to thank the UQTR Foundation, the Innovations Institute for Ecomaterials, Ecoproducts and Ecoenergies Biomass Based, the EcotoQ Research Group and the Forensic Research Group for their financial support during this study. Special thanks are addressed to Agnes Lejeune for her assistance during the collection of SEM images. All technicians at the UQTR are also acknowledged for their technical support.
No conflict of interest to declare.
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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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Its first known use in rehabilitation published by Max North named as “Virtual Environments and Psychological Disorders” (1994). Virtual reality uses special programmed computers, visual devices and artificial environments for the clients’ rehabilitation. Throughout technological improvements, virtual reality devices changed from therapeutic gloves to augmented reality environments. Virtual reality was being used in different rehabilitation professions such as occupational therapy, physical therapy, psychology and so on. In spite of common virtual reality approach of different professions, each profession aims different outcomes in rehabilitation. Virtual reality in occupational therapy generally focuses on hand and upper extremity functioning, cognitive rehabilitation, mental disorders, etc. Positive effects of virtual reality were mentioned in different studies, which are higher motivation than non‐simulated environments, active participation of the participants, supporting motor learning, fun environment and risk‐free environment. Additionally, virtual reality was told to be used as assessment. This chapter will focus on usage of virtual reality in occupational therapy, history and recent developments, types of virtual reality technologic equipment, pros and cons, usage for pediatric, adult and geriatric people and recent research and articles.",book:{id:"5711",slug:"occupational-therapy-occupation-focused-holistic-practice-in-rehabilitation",title:"Occupational Therapy",fullTitle:"Occupational Therapy - Occupation Focused Holistic Practice in Rehabilitation"},signatures:"Orkun Tahir Aran, Sedef Şahin, Berkan Torpil, Tarık Demirok and\nHülya Kayıhan",authors:[{id:"172938",title:"Prof.",name:"Hulya",middleName:null,surname:"Kayihan",slug:"hulya-kayihan",fullName:"Hulya Kayihan"},{id:"183079",title:"Ph.D.",name:"Sedef",middleName:null,surname:"Şahin",slug:"sedef-sahin",fullName:"Sedef Şahin"},{id:"196848",title:"M.Sc.",name:"Orkun Tahir",middleName:null,surname:"Aran",slug:"orkun-tahir-aran",fullName:"Orkun Tahir Aran"},{id:"197159",title:"Mr.",name:"Tarık",middleName:null,surname:"Demirok",slug:"tarik-demirok",fullName:"Tarık Demirok"},{id:"197312",title:"M.Sc.",name:"Berkan",middleName:null,surname:"Torpil",slug:"berkan-torpil",fullName:"Berkan Torpil"}]},{id:"61806",doi:"10.5772/intechopen.78312",title:"Executive Functions and Neurology in Children and Adolescents",slug:"executive-functions-and-neurology-in-children-and-adolescents",totalDownloads:1728,totalCrossrefCites:3,totalDimensionsCites:5,abstract:"This chapter discusses the theoretical and methodological issues of creating a developmental perspective on executive function (EF) in childhood and adolescence. Focusing on school periods, this section outlines the development of the basic components of EF—inhibition, working memory, and attention. Cognitive and neurophysiological evaluations show that despite the emergence of EF in the first few years of life, it continues to grow significantly in childhood and adolescence. The components vary slightly according to their developmental sequence. The chapter links findings to long-standing developmental issues (i.e. developmental sequences and processes) and suggests the necessary research to establish a developmental framework covering early childhood throughout adolescence.",book:{id:"6772",slug:"occupational-therapy-therapeutic-and-creative-use-of-activity",title:"Occupational Therapy",fullTitle:"Occupational Therapy - Therapeutic and Creative Use of Activity"},signatures:"Gokcen Akyurek",authors:[{id:"197265",title:"Dr.",name:"Gokcen",middleName:null,surname:"Akyurek",slug:"gokcen-akyurek",fullName:"Gokcen Akyurek"}]},{id:"56049",doi:"10.5772/intechopen.69101",title:"Measurement of Participation: The Role Checklist Version 3: Satisfaction and Performance",slug:"measurement-of-participation-the-role-checklist-version-3-satisfaction-and-performance",totalDownloads:2794,totalCrossrefCites:3,totalDimensionsCites:4,abstract:"Participation in society is an area of interest to both clinicians and population researchers. Measurement of participation is therefore important, yet differences in definition, in terms of both content and scope, have made general agreement on one instrument tool elusive. What is recognized is the need for a theoretically based tool that captures both the insider and the outsider perspective. The outsider perspective, inclusive of the generally held views of a society, supports the utility for aggregating population data, whereas the insider perspective provides the internally held views of an individual needed for client-centered treatment planning. The Role Checklist Version 3 modifies one of the most commonly used assessment tools in occupational therapy practice, has good preliminary psychometric properties, and is theoretically consistent with both the ICF and the Model of Human Occupation. The Model of Human Occupation is the most widely used theoretical model in occupational therapy. This chapter provides an overview of the theoretical development, empirical testing, and implications for use of this participation measure by occupational therapists along with implications for population researchers.",book:{id:"5711",slug:"occupational-therapy-occupation-focused-holistic-practice-in-rehabilitation",title:"Occupational Therapy",fullTitle:"Occupational Therapy - Occupation Focused Holistic Practice in Rehabilitation"},signatures:"Patricia J. Scott, Kelsey McKinney, Jeff Perron, Emily Ruff and Jessica\nSmiley",authors:[{id:"195495",title:"Dr.",name:"Patricia J",middleName:null,surname:"Scott",slug:"patricia-j-scott",fullName:"Patricia J Scott"},{id:"208801",title:"Dr.",name:"Kelsey G.",middleName:null,surname:"McKinney",slug:"kelsey-g.-mckinney",fullName:"Kelsey G. McKinney"},{id:"208802",title:"Mr.",name:"Jeffrey M.",middleName:null,surname:"Perron",slug:"jeffrey-m.-perron",fullName:"Jeffrey M. Perron"},{id:"208803",title:"Dr.",name:"Emily G.",middleName:null,surname:"Ruff",slug:"emily-g.-ruff",fullName:"Emily G. Ruff"},{id:"208804",title:"Dr.",name:"Jessica L.",middleName:null,surname:"Smiley",slug:"jessica-l.-smiley",fullName:"Jessica L. Smiley"}]},{id:"55024",doi:"10.5772/intechopen.68463",title:"Occupational Therapy in Oncology and Palliative Care",slug:"occupational-therapy-in-oncology-and-palliative-care",totalDownloads:2655,totalCrossrefCites:1,totalDimensionsCites:4,abstract:"Cancer is a chronic disease that may occur in both children and adults. Occupational therapy focuses on the activity limitations and participation problems in their life. Oncology rehabilitation involves in helping an individual with cancer to regain maximum physical, psychological, cognitive, social, and vocational functioning with the limits up to disease and its treatments in an interdisciplinary team concept. These treatment options are associated with the risk of some side effects, including fatigue, pain, cognitive problems, decrease in bone density and muscle endurance, weight loss, and stress- or anxiety-related psychosocial problems. Occupational therapy approaches are a holistic view in a client center and use training in activities of daily living, assistive technology, education of energy conservation techniques, and management of treatment-related problems, such as pain, fatigue, and nausea. In palliative and hospice care, occupational therapists support clients with cancer by minimizing the secondary symptoms related to cancer and its treatments. At the end of life, occupational therapy offers to identify the roles and activities that are meaningful and purposeful to the client with cancer and try to determine the barriers that limit their performance. Clients with cancer who have childhood cancer or adult cancer can face problems about body structure and functions, activity, and participation, which may limit their participation to their daily life.",book:{id:"5711",slug:"occupational-therapy-occupation-focused-holistic-practice-in-rehabilitation",title:"Occupational Therapy",fullTitle:"Occupational Therapy - Occupation Focused Holistic Practice in Rehabilitation"},signatures:"Sedef Şahin, Semin Akel and Meral Zarif",authors:[{id:"183079",title:"Ph.D.",name:"Sedef",middleName:null,surname:"Şahin",slug:"sedef-sahin",fullName:"Sedef Şahin"},{id:"183078",title:"Dr.",name:"Burcu Semin",middleName:null,surname:"Akel",slug:"burcu-semin-akel",fullName:"Burcu Semin Akel"},{id:"198859",title:"Dr.",name:"Meral",middleName:null,surname:"Zarif",slug:"meral-zarif",fullName:"Meral Zarif"}]},{id:"62493",doi:"10.5772/intechopen.79366",title:"Occupational Therapy in Forensic Settings",slug:"occupational-therapy-in-forensic-settings",totalDownloads:2506,totalCrossrefCites:2,totalDimensionsCites:2,abstract:"It is necessary for a person to comply with the expectations of society and the rules of law to which these expectations are secured. Offenders turn back to the community after the penalty was executed by isolating from society and some occupations. An occupational imbalance is seen in the individuals, during this penalty period and afterward, because of limited occupational participation. As an occupational being, this affects their physical, mental and psychological well-being. Imprisonment is an important practice in criminal law to punish criminals. This may be necessary for the protection of society from criminals, but successful integration into a community after exiting the prison is the most important factor in preventing recidivism. Occupational therapy focuses on health and well-being by using meaningful and purposeful occupations. Occupation involves any activity that people perform or participate in, such as giving care to themselves or others, working, learning, playing games, and interacting with others. From this perspective, the role of occupational therapists in forensic settings is to determine the abilities of these individuals to congregate their deprived freedoms and use them to train them for an independent and autonomous life; to provide a professional orientation, career counseling, and self-esteem; to gain some habits for physical, spiritual and moral life and to reinforce.",book:{id:"6772",slug:"occupational-therapy-therapeutic-and-creative-use-of-activity",title:"Occupational Therapy",fullTitle:"Occupational Therapy - Therapeutic and Creative Use of Activity"},signatures:"Esma Ozkan, Sümeyye Belhan, Mahmut Yaran and Meral Zarif",authors:null}],mostDownloadedChaptersLast30Days:[{id:"55080",title:"Life Skills in Occupational Therapy",slug:"life-skills-in-occupational-therapy",totalDownloads:6017,totalCrossrefCites:3,totalDimensionsCites:0,abstract:"Occupational therapy is a health profession that uses the purposeful activities to achieve multiple and complex rehabilitation aims. The main goals of the occupational therapy are to support the reintegration of individuals in daily living skills as well as to increase their independence and autonomy. Interventions of occupational therapists have primarily focused on self-care, productivity, and leisure time activities. Since the life skills includes a wide range of abilities that enable a person to perform personal care and more complicated tasks such as traveling, shopping, community participation etc., occupational therapists provide life skills training programs to meet the needs of the clients. This chapter aims to contribute to the current understanding and practices of life skills from an occupational therapy perspective. The chapter starts with a brief discussion of the importance of life skills in occupational therapy. After this introduction, the first part takes a look at the definition of life skills and identifies core components of life skills. The second part describes assessment and interventions of life skills. The third one gives an overview about school life skills programs for children and adolescents. Finally, the last part explains some life skills programs in people with disadvantages.",book:{id:"5711",slug:"occupational-therapy-occupation-focused-holistic-practice-in-rehabilitation",title:"Occupational Therapy",fullTitle:"Occupational Therapy - Occupation Focused Holistic Practice in Rehabilitation"},signatures:"Hatice Abaoğlu, Özge Buket Cesim, Sinem Kars and Zeynep Çelik",authors:[{id:"197551",title:"Dr.",name:"Hatice",middleName:null,surname:"Abaoğlu",slug:"hatice-abaoglu",fullName:"Hatice Abaoğlu"},{id:"205199",title:"Dr.",name:"Sinem",middleName:null,surname:"Kars",slug:"sinem-kars",fullName:"Sinem Kars"},{id:"205200",title:"Dr.",name:"Zeynep",middleName:null,surname:"Celik",slug:"zeynep-celik",fullName:"Zeynep Celik"},{id:"205203",title:"Ms.",name:"Özge Buket",middleName:null,surname:"Cesim",slug:"ozge-buket-cesim",fullName:"Özge Buket Cesim"}]},{id:"62493",title:"Occupational Therapy in Forensic Settings",slug:"occupational-therapy-in-forensic-settings",totalDownloads:2506,totalCrossrefCites:2,totalDimensionsCites:2,abstract:"It is necessary for a person to comply with the expectations of society and the rules of law to which these expectations are secured. Offenders turn back to the community after the penalty was executed by isolating from society and some occupations. An occupational imbalance is seen in the individuals, during this penalty period and afterward, because of limited occupational participation. As an occupational being, this affects their physical, mental and psychological well-being. Imprisonment is an important practice in criminal law to punish criminals. This may be necessary for the protection of society from criminals, but successful integration into a community after exiting the prison is the most important factor in preventing recidivism. Occupational therapy focuses on health and well-being by using meaningful and purposeful occupations. Occupation involves any activity that people perform or participate in, such as giving care to themselves or others, working, learning, playing games, and interacting with others. From this perspective, the role of occupational therapists in forensic settings is to determine the abilities of these individuals to congregate their deprived freedoms and use them to train them for an independent and autonomous life; to provide a professional orientation, career counseling, and self-esteem; to gain some habits for physical, spiritual and moral life and to reinforce.",book:{id:"6772",slug:"occupational-therapy-therapeutic-and-creative-use-of-activity",title:"Occupational Therapy",fullTitle:"Occupational Therapy - Therapeutic and Creative Use of Activity"},signatures:"Esma Ozkan, Sümeyye Belhan, Mahmut Yaran and Meral Zarif",authors:null},{id:"62210",title:"Occupational Therapy’s Role in the Treatment of Children with Autism Spectrum Disorders",slug:"occupational-therapy-s-role-in-the-treatment-of-children-with-autism-spectrum-disorders",totalDownloads:2720,totalCrossrefCites:0,totalDimensionsCites:0,abstract:"Occupational therapists (OT) offer a wide range of therapies for individuals with ASD on the basis of specific deficits and difficulties. This chapter explores the role that OT plays, and the expertise, in relation to the interdisciplinary team. In addition, it discusses and presents empirical support for several therapeutic approaches commonly used by OTs working with individuals with ASD.",book:{id:"6772",slug:"occupational-therapy-therapeutic-and-creative-use-of-activity",title:"Occupational Therapy",fullTitle:"Occupational Therapy - Therapeutic and Creative Use of Activity"},signatures:"Bryan M. Gee, Amy Nwora and Theodore W. Peterson",authors:null},{id:"55049",title:"Community Participation in People with Disabilities",slug:"community-participation-in-people-with-disabilities",totalDownloads:2401,totalCrossrefCites:2,totalDimensionsCites:2,abstract:"Despite the fact that participation is an important building and a valuable target, the conceptualization, identification and measurement methods vary widely. This chapter tried to gain an insider’s perspective from the obstacles that summarize what meaning participation means, how to characterize it, and what prevents and supports participation. Participation is seen as a right and a responsibility attributed to and attributed to both the person and the community. Participation does not take place in a vacuum; the environment dynamically influences participation. The effects of this conceptual framework are discussed for change at the level of evaluation, research and systems to support the participation of the people with disability.",book:{id:"5711",slug:"occupational-therapy-occupation-focused-holistic-practice-in-rehabilitation",title:"Occupational Therapy",fullTitle:"Occupational Therapy - Occupation Focused Holistic Practice in Rehabilitation"},signatures:"Gokcen Akyurek and Gonca Bumin",authors:[{id:"32431",title:"Prof.",name:"Gonca",middleName:null,surname:"Bumin",slug:"gonca-bumin",fullName:"Gonca Bumin"},{id:"197265",title:"Dr.",name:"Gokcen",middleName:null,surname:"Akyurek",slug:"gokcen-akyurek",fullName:"Gokcen Akyurek"}]},{id:"56049",title:"Measurement of Participation: The Role Checklist Version 3: Satisfaction and Performance",slug:"measurement-of-participation-the-role-checklist-version-3-satisfaction-and-performance",totalDownloads:2794,totalCrossrefCites:3,totalDimensionsCites:4,abstract:"Participation in society is an area of interest to both clinicians and population researchers. Measurement of participation is therefore important, yet differences in definition, in terms of both content and scope, have made general agreement on one instrument tool elusive. What is recognized is the need for a theoretically based tool that captures both the insider and the outsider perspective. The outsider perspective, inclusive of the generally held views of a society, supports the utility for aggregating population data, whereas the insider perspective provides the internally held views of an individual needed for client-centered treatment planning. The Role Checklist Version 3 modifies one of the most commonly used assessment tools in occupational therapy practice, has good preliminary psychometric properties, and is theoretically consistent with both the ICF and the Model of Human Occupation. The Model of Human Occupation is the most widely used theoretical model in occupational therapy. This chapter provides an overview of the theoretical development, empirical testing, and implications for use of this participation measure by occupational therapists along with implications for population researchers.",book:{id:"5711",slug:"occupational-therapy-occupation-focused-holistic-practice-in-rehabilitation",title:"Occupational Therapy",fullTitle:"Occupational Therapy - Occupation Focused Holistic Practice in Rehabilitation"},signatures:"Patricia J. Scott, Kelsey McKinney, Jeff Perron, Emily Ruff and Jessica\nSmiley",authors:[{id:"195495",title:"Dr.",name:"Patricia J",middleName:null,surname:"Scott",slug:"patricia-j-scott",fullName:"Patricia J Scott"},{id:"208801",title:"Dr.",name:"Kelsey G.",middleName:null,surname:"McKinney",slug:"kelsey-g.-mckinney",fullName:"Kelsey G. McKinney"},{id:"208802",title:"Mr.",name:"Jeffrey M.",middleName:null,surname:"Perron",slug:"jeffrey-m.-perron",fullName:"Jeffrey M. 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The whole process of submitting an article and editing of the submitted article goes extremely smooth and fast, the number of reads and downloads of chapters is high, and the contributions are also frequently cited.",author:{id:"55578",name:"Antonio",surname:"Jurado-Navas",institutionString:null,profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRisIQAS/Profile_Picture_1626166543950",slug:"antonio-jurado-navas",institution:{id:"720",name:"University of Malaga",country:{id:null,name:"Spain"}}}},{id:"6",text:"It is great to work with the IntechOpen to produce a worthwhile collection of research that also becomes a great educational resource and guide for future research endeavors.",author:{id:"259298",name:"Edward",surname:"Narayan",institutionString:null,profilePictureURL:"https://mts.intechopen.com/storage/users/259298/images/system/259298.jpeg",slug:"edward-narayan",institution:{id:"3",name:"University of Queensland",country:{id:null,name:"Australia"}}}}]},series:{item:{id:"14",title:"Artificial Intelligence",doi:"10.5772/intechopen.79920",issn:"2633-1403",scope:"Artificial Intelligence (AI) is a rapidly developing multidisciplinary research area that aims to solve increasingly complex problems. 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He is currently appointed as the Voigt Chair in Data Science in the Department of Industrial Engineering, with a joint appointment as Professor in the Computer Science Division, Stellenbosch University. Prior to his appointment at Stellenbosch University, he has been at the University of Pretoria, Department of Computer Science (1998-2018), where he was appointed as South Africa Research Chair in Artifical Intelligence (2007-2018), the head of the Department of Computer Science (2008-2017), and Director of the Institute for Big Data and Data Science (2017-2018). 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Travieso-González received his MSc degree in Telecommunication Engineering at Polytechnic University of Catalonia (UPC), Spain in 1997, and his Ph.D. degree in 2002 at the University of Las Palmas de Gran Canaria (ULPGC-Spain). He is a full professor of signal processing and pattern recognition and is head of the Signals and Communications Department at ULPGC, teaching from 2001 on subjects on signal processing and learning theory. His research lines are biometrics, biomedical signals and images, data mining, classification system, signal and image processing, machine learning, and environmental intelligence. He has researched in 52 international and Spanish research projects, some of them as head researcher. He is co-author of 4 books, co-editor of 27 proceedings books, guest editor for 8 JCR-ISI international journals, and up to 24 book chapters. He has over 450 papers published in international journals and conferences (81 of them indexed on JCR – ISI - Web of Science). He has published seven patents in the Spanish Patent and Trademark Office. He has been a supervisor on 8 Ph.D. theses (11 more are under supervision), and 130 master theses. He is the founder of The IEEE IWOBI conference series and the president of its Steering Committee, as well as the founder of both the InnoEducaTIC and APPIS conference series. He is an evaluator of project proposals for the European Union (H2020), Medical Research Council (MRC, UK), Spanish Government (ANECA, Spain), Research National Agency (ANR, France), DAAD (Germany), Argentinian Government, and the Colombian Institutions. He has been a reviewer in different indexed international journals (<70) and conferences (<250) since 2001. He has been a member of the IASTED Technical Committee on Image Processing from 2007 and a member of the IASTED Technical Committee on Artificial Intelligence and Expert Systems from 2011. \n\nHe has held the general chair position for the following: ACM-APPIS (2020, 2021), IEEE-IWOBI (2019, 2020 and 2020), A PPIS (2018, 2019), IEEE-IWOBI (2014, 2015, 2017, 2018), InnoEducaTIC (2014, 2017), IEEE-INES (2013), NoLISP (2011), JRBP (2012), and IEEE-ICCST (2005)\n\nHe is an associate editor of the Computational Intelligence and Neuroscience Journal (Hindawi – Q2 JCR-ISI). He was vice dean from 2004 to 2010 in the Higher Technical School of Telecommunication Engineers at ULPGC and the vice dean of Graduate and Postgraduate Studies from March 2013 to November 2017. He won the “Catedra Telefonica” Awards in Modality of Knowledge Transfer, 2017, 2018, and 2019 editions, and awards in Modality of COVID Research in 2020.\n\nPublic References:\nResearcher ID http://www.researcherid.com/rid/N-5967-2014\nORCID https://orcid.org/0000-0002-4621-2768 \nScopus Author ID https://www.scopus.com/authid/detail.uri?authorId=6602376272\nScholar Google https://scholar.google.es/citations?user=G1ks9nIAAAAJ&hl=en \nResearchGate https://www.researchgate.net/profile/Carlos_Travieso",institutionString:null,institution:{name:"University of Las Palmas de Gran Canaria",institutionURL:null,country:{name:"Spain"}}},editorTwo:null,editorThree:null},{id:"23",title:"Computational Neuroscience",coverUrl:"https://cdn.intechopen.com/series_topics/covers/23.jpg",isOpenForSubmission:!0,annualVolume:11419,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,annualVolume:11420,editor:{id:"294154",title:"Prof.",name:"George",middleName:null,surname:"Papakostas",slug:"george-papakostas",fullName:"George Papakostas",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002hYaGbQAK/Profile_Picture_1624519712088",biography:"George A. Papakostas has received a diploma in Electrical and Computer Engineering in 1999 and the M.Sc. and Ph.D. degrees in Electrical and Computer Engineering in 2002 and 2007, respectively, from the Democritus University of Thrace (DUTH), Greece. Dr. Papakostas serves as a Tenured Full Professor at the Department of Computer Science, International Hellenic University, Greece. Dr. Papakostas has 10 years of experience in large-scale systems design as a senior software engineer and technical manager, and 20 years of research experience in the field of Artificial Intelligence. Currently, he is the Head of the “Visual Computing” division of HUman-MAchines INteraction Laboratory (HUMAIN-Lab) and the Director of the MPhil program “Advanced Technologies in Informatics and Computers” hosted by the Department of Computer Science, International Hellenic University. He has (co)authored more than 150 publications in indexed journals, international conferences and book chapters, 1 book (in Greek), 3 edited books, and 5 journal special issues. His publications have more than 2100 citations with h-index 27 (GoogleScholar). His research interests include computer/machine vision, machine learning, pattern recognition, computational intelligence. \nDr. Papakostas served as a reviewer in numerous journals, as a program\ncommittee member in international conferences and he is a member of the IAENG, MIR Labs, EUCogIII, INSTICC and the Technical Chamber of Greece (TEE).",institutionString:null,institution:{name:"International Hellenic University",institutionURL:null,country:{name:"Greece"}}},editorTwo:null,editorThree:null},{id:"25",title:"Evolutionary Computation",coverUrl:"https://cdn.intechopen.com/series_topics/covers/25.jpg",isOpenForSubmission:!0,annualVolume:11421,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. 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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. 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He obtained both his M.Sc. and Ph.D. from the University of Liverpool, England, in the field of Intelligent Systems. He is a full professor at the Universidad Autonoma de Queretaro, Mexico, and a member of the National System of Researchers (SNI) since 2009. Dr. Aceves Fernandez has published more than 80 research papers as well as a number of book chapters and congress papers. He has contributed in more than 20 funded research projects, both academic and industrial, in the area of artificial intelligence, ranging from environmental, biomedical, automotive, aviation, consumer, and robotics to other applications. He is also a honorary president at the National Association of Embedded Systems (AMESE), a senior member of the IEEE, and a board member of many institutions. 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His research interests include swarm intelligence, parallel and distributed metaheuristics, machine learning, intelligent agents and multi-agent systems, resource planning, scheduling and optimization, combinatorial optimization. Dr. Aydin is currently a Fellow of Higher Education Academy, UK, a member of EPSRC College, a senior member of IEEE and a senior member of ACM. In addition to being a member of advisory committees of many international conferences, he is an Editorial Board Member of various peer-reviewed international journals. 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Waisundara",profilePictureURL:"https://mts.intechopen.com/storage/users/194281/images/system/194281.jpg",biography:"Dr. Viduranga Waisundara obtained her Ph.D. in Food Science\nand Technology from the Department of Chemistry, National\nUniversity of Singapore, in 2010. She was a lecturer at Temasek Polytechnic, Singapore from July 2009 to March 2013.\nShe relocated to her motherland of Sri Lanka and spearheaded the Functional Food Product Development Project at the\nNational Institute of Fundamental Studies from April 2013 to\nOctober 2016. She was a senior lecturer on a temporary basis at the Department of\nFood Technology, Faculty of Technology, Rajarata University of Sri Lanka. She is\ncurrently Deputy Principal of the Australian College of Business and Technology –\nKandy Campus, Sri Lanka. She is also the Global Harmonization Initiative (GHI)",institutionString:"Australian College of Business & Technology",institution:null}]},{type:"book",id:"6820",title:"Keratin",subtitle:null,coverURL:"https://cdn.intechopen.com/books/images_new/6820.jpg",slug:"keratin",publishedDate:"December 19th 2018",editedByType:"Edited by",bookSignature:"Miroslav Blumenberg",hash:"6def75cd4b6b5324a02b6dc0359896d0",volumeInSeries:2,fullTitle:"Keratin",editors:[{id:"31610",title:"Dr.",name:"Miroslav",middleName:null,surname:"Blumenberg",slug:"miroslav-blumenberg",fullName:"Miroslav Blumenberg",profilePictureURL:"https://mts.intechopen.com/storage/users/31610/images/system/31610.jpg",biography:"Miroslav Blumenberg, Ph.D., was born in Subotica and received his BSc in Belgrade, Yugoslavia. He completed his Ph.D. at MIT in Organic Chemistry; he followed up his Ph.D. with two postdoctoral study periods at Stanford University. Since 1983, he has been a faculty member of the RO Perelman Department of Dermatology, NYU School of Medicine, where he is codirector of a training grant in cutaneous biology. Dr. Blumenberg’s research is focused on the epidermis, expression of keratin genes, transcription profiling, keratinocyte differentiation, inflammatory diseases and cancers, and most recently the effects of the microbiome on the skin. 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He has both an MS and Ph.D. in Biomedical Engineering. He was previously a research scientist at the University of California Los Angeles (UCLA) and visiting professor and researcher at the University of North Dakota. He is currently working in artificial intelligence and its applications in medical signal processing. In addition, he is using digital signal processing in medical imaging and speech processing. Dr. Asadpour has developed brain-computer interfacing algorithms and has published books, book chapters, and several journal and conference papers in this field and other areas of intelligent signal processing. 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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:"