This paper proposes a maiden intelligent controller design that consists of a Fuzzy Proportional–Integral–Derivative–Double Derivative (FPIDD²) controller whose parameters are fine-tuned using the Gradient-Based Optimization algorithm (GBO). The proposed FPIDD² regulator is employed as a secondary regulator for stabilizing the combined voltage and frequency loops in a two-area interconnected power system. It has been shown that the GBO optimization algorithm outperforms other optimization strategies such as the Chimp Optimization Algorithm (ChOA), the Whale Optimization Algorithm (WOA), and the Gorilla Troops Optimization algorithm (GTO). The proposed FPIDD² controller is tested in a conventional two-area power system. Then, the investigation is expanded to a two-area hybrid system, with each area comprising a mix of traditional (thermal, gas, and hydraulic power plants) and renewable generation units (wind and solar power). Additionally, the proposed controller takes into account system nonlinearities (such as generation rate limitations, governor deadband, and communication time delays), system uncertainties, and load/renewables fluctuations. In the two tested systems, the dynamic responses of each system demonstrate that FPIDD² has a superior ability to attenuate the deviations in voltage and frequency in both areas of the system. In the studied conventional system, the proposed FPIDD² controller is compared with a PID controller tuned by the Multi-Objective Non-Linear Threshold Accepting Algorithm (MONLTA), which has been presented in the literature, and a Fuzzy PID (FPID) controller tuned by GBO. In the investigated hybrid system, the suggested FPIDD² regulator is compared to a GBO-tuned Integral Derivative-Tilted (ID-T) controller and FPID controller. As a fitness function (FF) for the GBO, the criteria of minimizing the integral time absolute error (ITAE) are applied. The results are presented in the form of MATLAB/SIMULINK time-domain simulations.
The broad spread of renewable energy sources (RESs) and storage systems increases modern power systems' challenges and may conflict with system operation requirements. Determination of the maximum hosting capacity (HC) is crucial for utilities to estimate the maximum capacity of RESs and storage units that a network can accommodate efficiently. Several models were developed in the literature that lacks studying the impact of reliability requirements and the size of other network components on the HC levels. This paper proposes a framework to effectively maximize the hosting of RESs and storage systems in power systems. An AC optimal power flow is used to formulate the problem and consider the networks' real operation. The objective function is formulated to expand transmission lines, allocate fault current limiters (FCLs), and ensure HC enhancement. The AC models are always complex and non-convex, and finding optimal solutions is critical. A hybrid artificial rabbits sine-cosine algorithm is developed to solve the problem, and its performance is compared to some well-known metaheuristics. The numerical studies on the Garver network and the IEE 24-bus system demonstrated that the size of different power technologies directly impacted the amount of RESs deployed. The penetration of RESs and storage systems was maximized by increasing the number of candidate circuits. The results revealed a 22 % increase in the size of RESs installed in the Garver network. Also, a 25.7 % increase in the size of RESs for the 24-bus system was obtained due to the increased candidate transmission lines. Further, an increase of 49 % was noticed in the size of storage systems built for the 24-bus system. The use of FCLs was necessary to maintain the short-circuit current below the required values. For both systems, the size of FCLs required was increased by 24.3 % and 28 %, respectively. The results also showed that the hybrid artificial rabbits sine-cosine optimizer was more efficient than other algorithms in solving the investigated problem. Ó 2022 THE AUTHORS. Published by Elsevier BV on behalf of Faculty of Engineering, Ain Shams University. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/ by-nc-nd/4.0/).
Normalized weight vector determination under bi-polar preferences is important in multi-criteria decision making and its related evaluation problems. In order to determine weights for the elements in partially ordered set which can embody bi-polar preferences, some new methods such as the ordered weighted averaging (OWA) aggregation on lattice using three-set formulation have been proposed. However, when there are no posets and orders but fuzzy relations available, some new effective generalized methods should be proposed. This work differentiates two types of special fuzzy relations, called incomplete fuzzy relation and contra-dictive fuzzy relation. Two objective methods to derive incomplete fuzzy relation from a set of vectors and basic uncertain information (BUI) granules are introduced. Two scaling methods to transform contradictive fuzzy relation into incomplete fuzzy relation are suggested. Based on those derived fuzzy relations and given convex/concave basic unit monotonic (BUM) functions, some weights allocation methods are proposed which can well embody the bi-polar preferences of decision makers. The method further generalizes the OWA aggregation on lattice. Some mathematical properties, four different instances and some numerical examples with application backgrounds or potentials are also provided.
Objective: This study aimed to investigate free sugar consumption (FSC) in relation to leisure screen time in children. Methods: Cross-sectional data of 424 healthy Saudi children ages 6 to 12 y were included in this study. Data pertaining to sociodemographic characteristics and leisure screen time (including time spent viewing TV, gaming, and use of electronic devices [e.g., computer, tablet, and smartphone]) in children were collected from mothers via an online questionnaire. A phone interview was later conducted with the mother and child to assess FSC using a previously validated 40-item food frequency questionnaire. Results: Our data found that a large proportion of children exceeded the maximum limit of screen time recommended for children, of ≤2 h/d (61.7%; n = 262). Child and maternal ages and child's birth order among siblings were significantly associated with the duration of leisure screen time (screen time within the recommendation of ≤2 h/d versus screen time that exceeded the recommendation; P < 0.050). Exceeding the recommendation of screen time predicted an increase of 8.96 g/d of FSC from liquid foods, 10.7 g/d of FSC from solid foods, and 19.3 g/d of total FSC. Conclusions: Exceeding the recommendation of screen time is associated with greater FSC in children. Future interventions should be directed toward restricting screen time and FSC in children.
In real world, decision-makers’ regret psychology often affects decision outcomes due to uncertain risks. Moreover, decision information may be missing in the process of data acquisitions or data storages. Three-way decision has been widely explored in the risky decision-making area by providing effective strategies to divide objects into three mutually disjoint regions. Existing three-way decision methods in fuzzy incomplete information systems rarely consider the influence of decision-makers’ psychological states on decision outcomes. In the current paper, we primarily study a new decision-making method that combines regret theory with three-way decision in fuzzy incomplete information systems. First, a prior probability tolerance dominance relation in a fuzzy incomplete information system is defined to handle a binary relation among evaluation values, and a method to calculate objective weights is designed as well. When an incomplete information system does not contain a fuzzy decision attribute value, we put forward a new method to calculate the decision attribute value of each object in the incomplete information system. Then, integrated utility perception values are obtained by combining with regret theory. Further, a regret theory-based three-way decision method with a priori probability tolerance dominance relation is proposed for fuzzy incomplete information systems. At last, the stability and validity of the presented method are verified via corresponding experimental and comparative analysis of realistic cases.
In this paper, a distributed filter is designed for time-varying systems corrupted by dynamic bias and packet disorders over sensor networks, where the plant under consideration includes stochastic bias which is governed by a dynamical equation. Moreover, the transmission delays are present in all sensor-to-filter communication channels, and such delays are described by using random variables that have known probability distributions. We focus on constructing a distributed yet recursive filter under the corruption of dynamic bias plus packet disorders. By means of the inductive method, upper bounds (on attained error covariances of the distributed filter) are first given and later minimized by properly parameterizing filter gains. Subsequently, a sufficient condition is presented to rigorously ensure the mean-square boundedness with respect to attained filtering errors. Finally, an example is given for effectiveness validation.
Increasing evidence shows the role of perceived risk in customers' attitude and intention to use online shopping services. However, the literature shows disagreement regarding the types of risks that influence purchase intention. Therefore, this study aims to empirically identify the most relevant sources of risks and uncertainties associated with online shopping services and to investigate the influence of sociodemographic characteristics (e.g., gender, age, and online shopping experience) on the levels of perceived risk using data collected through a survey questionnaire. A total of 558 participants were selected across three countries (Jordan, Saudi Arabia, and Kuwait). The responses were evaluated using structural equation modeling and multigroup analysis. The analysis showed that of the tested types of risks and uncertainty, only three had a significant influence on customers' purchase decisions: financial risk, information risk, and privacy risk. Regarding the moderating role of sociodemographic variables, the analysis showed that previous experience has a significant moderating effect. At the same time, gender and age were found not to affect the relationship between perceived risks and customers' purchase intention. These findings may help online stores understand customers’ concerns when considering online shopping. The limitations and theoretical and managerial implications of the present study are discussed.
The virtual energy storage system (VESS) is one of the emerging novel concepts among current energy storage systems (ESSs) due to the high effectiveness and reliability. In fact, VESS could store surplus energy and inject the energy during the shortages, at high power with larger capacities, compared to the conventional ESSs in smart grids. This study investigates the optimal operation of a multi-carrier VESS, including batteries, thermal energy storage (TES) systems, power to hydrogen (P2H) and hydrogen to power (H2P) technologies in hydrogen storage systems (HSS), and electric vehicles (EVs) in dynamic ESS. Further, demand response program (DRP) for electrical and thermal loads has been considered as a tool of VESS due to the similar behavior of physical ESS. In the market, three participants have considered such as electrical, thermal and hydrogen markets. In addition, the price uncertainties were calculated by means of scenarios as in stochastic programming, while the optimization process and the operational constraints were considered to calculate the operational costs in different ESSs. However, congestion in the power systems is often occurred due to the extreme load increments. Hence, this study proposes a bi-level formulation system, where independent system operators (ISO) manage the congestion in the upper level, while VESS operators deal with the financial goals in the lower level. Moreover, four case studies have considered to observe the effectiveness of each storage system and the simulation was modeled in the IEEE 33-bus system with CPLEX in GAMS.
We are interested in studying some qualitative analysis and wave propagation and their applications to the Konopelchenko-Dubrovsky equation.Using the qualitative theory of planar systems and a complete discriminant system, we propose a new method. The proposed method is more efficient because it only creates real bounded wave solutions, which are desirable in real-world applications, as well as it is applicable to large classes of nonlinear partial differential equations. We present an algorithm for the proposed method to facilitate and clarify its applicability. Some new solutions are introduced using this method, and they are classified as periodic and solitary wave solutions. These solutions are graphically represented by displaying 3D and 2D graphic representations, as well as the contour plot. Furthermore, we investigate the impact of the included parameters on the obtained solutions. We numerically examine the 2D and 3D phase portraits after permitting a certain periodic additional term to arise, revealing the existence of quasi-periodic behavior.
In this research, the model under consideration is the Fokas system that simulates the dynamics of wave through single mode fiber optics. Dark, bright, kink and periodic optical solitons are yielded using Painlevé approach and semi-inverse variational principle. The constraint conditions for the existence of the solutions also merge during the derivation. The obtained solutions are discussed to depict and support theoretical outcomes through the phase portraits. Further, we have applied the idea of bifurcation and chaos theories to get a better understanding of the planar dynamical system obtained from the studied system. The chaotic solutions for the perturbed dynamical system are also obtained and displayed through graphs. The sensitivity analysis of the model is also investigated, and the results show that the given model is not highly sensitive and is stable. These unique ideas employ symbolic computations to provide dynamical as well as potent mathematical tool related to tackling diverse benign nonlinear wave problems. The dynamics analysis method and numerical results are meaningful and helpful to further study on the reliability control of Fokas system.
Macrobenthic organisms are useful bioindicators to assess ecological quality status. On the south-central coast of Peru (13°15.15′ S, 76°18.5′ W), a Liquefied Natural Gas (LNG) marine terminal has been operating since 2010. We investigated the macrobenthic communities and sediment parameters from 2011 to 2020 to evaluate the ecological quality status in the surrounding area of the marine terminal, using the AZTI Marine Biotic Index (AMBI) and its multivariate version (M-AMBI). We analyzed the diversity and community composition of macrobenthic invertebrates and the physico-chemical parameters of the sediment from 29 sampling sites, ranging from 0 to 15m depth. The sampling design considered: the direct influence zone (“DIZ”, surroundings of the marine terminal), and northern (NCZ) and southern (SCZ) control zones. Our results indicated that abundance was high at SCZ and decreased with depth. Species richness and diversity were high at DIZ and NCZ, respectively, and increased up to 10m but dropped at 15m. High sand content was recorded in shallow depths, while in deeper areas and DIZ, mud and organic matter increased and redox potential was negative. AMBI indicated a “slightly disturbed” status in general, while M-AMBI indicated “good” or “moderate” status at depths ≤ 12m, and “poor” status at 15m. Overall, the season/year factor was not important, and variables were mostly significantly different across depths. Redox potential and organic matter were correlated with M-AMBI at 15m. In general, our results indicate an acceptable ecological quality surrounding the marine terminal, likely because the study area is not influenced by an important input of an anthropogenic stressor. This study highlights the importance of monitoring benthic communities in the surroundings of human-made structures and the use of ecological quality indices for understanding potential impacts.
Textile industries release effluent that contains the vast majority of heavy metals in which Cr (VI) is a toxic carcinogenic element that causes an environmental problem. The aim of the work is to synthesize algae-derived biochar derived from algae using slow pyrolysis at an operating temperature of 500 °C, a heating rate of 10 °C/min and a residence time of 60 min and to use it as an adsorbent to remove Cr (VI). The batch experiment was carried out using different concentrations of Cr (VI) (1, 10, 25, 50, 100, 125, 150 and 200 ppm) at different intervals of time (2.5, 5, 10, 15, 30, 60, 120 and 240 min). The maximum removal percentage of Cr (VI) is 97.88% for the metal concentration of 1 ppm exhibiting non-linear adsorption isotherm (Langmuir, Freundlich, Dubinin-Radushkevich, and Temkin models) and kinetic models (pseudo-first order, pseudo-second order, nth order, and intra-particle diffusion) were analyzed using a solver add-in of Microsoft Excel. According to the results, the Langmuir isotherm model (R2 = 0.999) and pseudo-nth order models are suitable to describe monolayer adsorption and the process kinetics, respectively. The maximum adsorption capacity of algal biochar to adsorb is 186.94 mg/g. For the prediction of the optimal removal efficacy, an artificial neural network of the MLP-2-7-1 model was used. The results obtained are useful for future work using algal biochar as an adsorbent of Cr (VI) from textile wastewater to achieve sustainable development goals.
The loss of balance between regulatory T (Treg) and T helper 17 (Th17) causes loss of tolerance against desmoglein (Dsg)-3 leading to pemphigus vulgaris (PV), an autoimmune bullous skin disorder associated with autoantibodies against Dsg-3. We aimed to elucidate the complex relationship of Th17 and Treg cells, their molecules, and the underlying mechanism in the development of PV disease. Using cytokine secretion assays, Th17 and Treg cells were sorted by FACS Aria-III within Dsg-3-responsive PBMC population and homogeneous T cell clones were generated in-vitro. Different cell surface molecules like CD25, GITR, CD122, CD152, CD45RO, IL-23R, STAT3, STAT5, CD127, HLA-DR, CCR4, CCR5, CCR6 and CCR7 were studied. The functional response of Th17 and Treg cells were elucidated by measuring the levels of various cytokines released by IL-10 and IL-17 T cells. The mRNA expression of transcription factors (FoxP3 and RORγt) was also analyzed. IL-17 secreting (Th17) cells with phenotype CD4+IL-17+ were greatly increased and IL-10 secreting (Treg) cells with phenotype CD4+IL-10+ were reduced in PV cases than healthy controls. The qPCR analysis showing high expression of retinoic acid receptor-related orphan receptor gamma (RORγt) mRNA in comparison to forkhead box P3 (FoxP3) mRNA confirmed the development of pro-inflammatory Th17 response in PV. Further, the cytokine profile of pro-inflammatory and anti-inflammatory cytokines suggested defective suppressive functions in Treg cells with high inflammatory response. Our findings indicate that autoantigen Dsg-3 specifically allows the proliferation of IL-17 secreting T cells though has a negative effect on IL-10 secreting T cells leading to dysregulation of immunity in PV patients. This antagonistic relationship between Dsg-3-specific Th17 and Treg cells may be critical for the onset and persistence of inflammation in PV cases.
Calcareous soils contain a high concentration of calcium carbonate (CaCO3), which influences soil properties related to plant growth. Humic acid (HA) and ammonium molybdate (AM) were added as treatments for calcareous soils at concentrations of 0.1, 0.5 and 1 g/l respectively. The pots were divided into three groups. The first set of groups were irrigated with AM, while the second set of groups were irrigated with HA. As a control, the third group was irrigated using only tap water. Many soil properties and plant characteristics were measured during the experiment. The results showed that most of the studied treatments aided to increase organic carbon of calcareous soil and improved sunflower height, leaf area and shoot and root biomass. All investigated treatments significantly enhanced carbohydrates content in the sunflower shoots, except the treatment with 0.1 g/l AM, while only the with AM (under all studied concentrations) significantly enhanced carbohydrates content in roots higher than untreated. Proteins content in the shoots and roots of sunflower significantly increased when treated only with 1 g/l HA higher than control. The amino acid content of sunflower roots enhanced when treated with 0.1 and 1 m/l HA and 0.5 g/l AM Evidently, acidifying materials enhanced the calcareous soil and increased productivity.
In this analysis, we use the high order cubic B-spline method to create approximating polynomial solutions for fractional Painlevé and Bagley-Torvik equations in the Captuo, Caputo-Fabrizio, and conformable fractional sense concerning boundary set conditions. Using a piecewise spline of a 3rd-degree polynomial; the discretization of the utilized fractional model problems is gained. Taking advantage of the Taylor series expansion; the error order behavior spline theorem is proved. We demonstrate applications of our spline method to several certain kinds including the 1st(2nd) Painlevé and Bagley-Torvik fractional models. For more detail, using Mathematica 11 several drawings and many tables were calculated and their explanations were mentioned. The computational results indicate that the suggested spline approach is most acceptable in terms of cost efficiency and precision of calculations. Highlight, conclusion, and future notes are provided to extract the ability of the discussed approach and the tendency of the utilized fractional models to extrapolate new application areas in the meshless numerical training.
Global optimization aims to identify the most interesting solution in the overall space of search, which is known as global optimum. But in reality, it is a misnomer because it is only the best of all discovered solutions in the explored search space, which depends, in turn, on initial positions of searching points over possibilities space. Practically, it is impossible to cover the entire search space of an NP hard problem, in an acceptable time, whatever the method used, since the size of this space is generally excessive. That is what justify, currently, the increased use of metaheuristics based mainly on two mechanisms: exploitation and exploration. Exploration guarantees that the used algorithm will reach the widest possible extent of the undiscovered areas in the search space, whereas exploitation guarantees that such algorithm will search for the best solutions inside the most promising areas i.e. around the best local and global optimums. Authors study, here, different implementations of exploration and exploitation mechanisms used in 12 well-known nature inspired metaheuristics. This study compares the aforementioned metaheuristics using 4 uni-model and 9 multi-model benchmarks. Uni-model benchmarks are used to test exploitation while multi-model benchmarks are used to test exploration. Obtained results show the superiority of TSO metaheuristic to find the adequate balance between exploration and exploitation leading it to discover, always, global optimum or one of the best near global optimums.
This paper employed an integrated model for examining behavioral intention to adopt blockchain technology in the supply chain management of manufacturing industries in Bangladesh. The proposed conceptual model was empirically tested using data collected from 189 supply chain managers working in manufacturing organizations in Bangladesh. The findings suggest that perceived usefulness, trading partners’ pressure, and competitive pressure are the most important determinant of behavioral intention.
This study investigated in the Saudi Arabian context the relationship between student-instructor interaction and students’ academic attainment. A survey secured reports from university students (n = 167) of their age, gender, interactions with instructors, and cumulative grade mean score for the previous three semesters. The results indicated a significant positive relationship between student-instructor interaction and student academic attainment. These findings have implications for teaching practices and suggest a need to implement a facilitative, interactive style of teaching, instead of relying on conventional instructor-centred teaching, both within and outside the classroom. We identify limitations of the current research and suggest directions for future research, with reference to the Saudi Arabian university context.
Purpose: To evaluate the outcomes of endodontic microsurgery (EMS) using mineral trioxide aggregate (MTA; Dentsply Sirona, Charlotte, NC, USA), EndoSequence root repair material (RRM putty; Brasseler, Savannah, GA), and injectable Bioceramic (BC) sealer (Brasseler USA) followed by the application of RRM putty (lid technique) as root-end filling materials. Methods: One hundred and ten patients who underwent EMS between 2016 and 2020 at King Abdulaziz University Dental Hospital were recruited for clinical and radiographic follow-up after a minimum of 1 year. Radiographic assessment was performed using periapical radiographs (PAs) and cone-beam computed tomography (CBCT). Volumetric analysis of periapical radiolucencies (PARLs) was performed using Amira software. Results: Seventy-nine patients (103 teeth: MTA group, n = 28; RRM putty, n = 41; lid technique, n = 34), attended the follow-up visit, with an average follow-up period of 24 months (recall rate = 74.5%). Of the 103 teeth, 40 were anteriors, 24 were premolars, and 39 were molars. All three groups of retrograde filling materials (MTA, RRM putty, and lid technique) showed high success rates on both PA (85.7, 85.4, 94.1%, respectively) and CBCT imaging (67.9, 75.6, 88.2%, respectively), without any significant difference among the success rates of different materials. Overall, a slight agreement was noted between the PA and CBCT outcomes, with a statistically significant difference (P = 0.029). None of the patient-, tooth-, or treatment-related factors significantly influenced the outcomes of EMS. Adequate density of root canal filling material was significantly associated with a high percentage of completely healed cases on CBCT (P = 0.044). PARL volumes were reduced significantly over 1-4 years follow-up after EMS (P < 0.001) CONCLUSIONS: EMS showed high success rates on both PA and CBCT when MTA, RRM putty or lid technique were used as retrograde filling materials. CBCT imaging is more precise than PA in detecting the healing outcomes of EMS.
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