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IntroductionMesenchymal stem cells/stromal cells from the Decidua Basalis of the human placenta (DBMSCs) express wide range of effector molecules that modulate the functions of their target cells. These properties make them potential candidate for use in cellular therapy. In this study, we have investigated the consequences of interaction between DBMSCs and natural killer (NK) cells for both cell types.MethodsDBMSCs were cultured with IL-2-activated and resting non-activated NK cells isolated from healthy human peripheral blood and various functional assays were performed including, NK cell proliferation and cytolytic activities. Flow cytometry and microscopic studies were performed to examine the expression of NK cell receptors that mediate these cytolytic activities against DBMSCs. Moreover, the mechanism underlying these effects was also investigated.ResultsOur findings revealed that, co-culture of DBMSCs and NK cells resulted in inhibition of proliferation of resting NK cells, while proliferation of IL-2 activated NK cells was increased. Contrarily, treatment of DBMSC’s with comparatively high numbers of IL-2 activated NK cells, resulted in their lysis, whereas treatment with low numbers resulted in reduction in their proliferation. Cytolytic activity of NK cells against DBMSCs was mediated by several activating NK cell receptors. In spite of the expression of HLA class I molecules by DBMSCs, they were still lysed by NK cells, excluding their involvement in cytolytic activity. In addition, preconditioning NK cells by DBMSCs, enhanced their ability to suppress tumor cell proliferation and in severe cases resulted in their partial lysis. Lysis and decrease of tumor cell proliferation is associated with increased expression of important molecules involved in anticancer activities.DiscussionWe conclude that DBMSCs exhibit dualfunctions on NK cells that enhance their anticancer therapeutic potential.

IntroductionWe reported that Ca2+-independent phospholipase A2β (iPLA2β)–derived lipids (iDLs) contribute to type 1 diabetes (T1D) onset. As CD4+ and CD8+ T cells are critical in promoting β-cell death, we tested the hypothesis that iDL signaling from these cells participates in T1D development. MethodsCD4+ and CD8+ T cells from wild-type non-obese diabetic (NOD) and NOD.iPLA2β+/- (NOD.HET) mice were administered in different combinations to immunodeficient NOD.scid. ResultsIn mice receiving only NOD T cells, T1D onset was rapid (5 weeks), incidence 100% by 20 weeks, and islets absent. In contrast, onset was delayed 1 week and incidence reduced 40%–50% in mice receiving combinations that included NOD.HET T cells. Consistently, islets from these non-diabetic mice were devoid of infiltrate and contained insulin-positive β-cells. Reduced iPLA2β led to decreased production of proinflammatory lipids from CD4+ T cells including prostaglandins and dihydroxyeicosatrienoic acids (DHETs), products of soluble epoxide hydrolase (sEH), and inhibition of their signaling decreased (by 82%) IFNγ+CD4+ cells abundance. However, only DHETs production was reduced from CD8+ T cells and was accompanied by decreases in sEH and granzyme B. DiscussionThese findings suggest that differential select iDL signaling in CD4+ and CD8+ T cells contributes to T1D development, and that therapeutics targeting such signaling might be considered to counter T1D.

With the continuous development of transportation electrification, Electric Vehicle Charging Stations (EVCS) have become pivotal components, necessitating robust cybersecurity frameworks to mitigate potential threats. This work explores the complex dynamics of Distributed Denial of Service (DDoS) attacks aimed at EVCS, highlighting the multifaceted interplay between the generation of attack traffic and its implications on grid stability. Introducing a novel mathematical model for extensive DDoS attacks on EVCS, this work simulates the attack methodology through a time-variant Poisson process, encapsulating the behaviors of attacks bots and their cumulative impact on the targeted EVCS. The model further incorporates the variability of attack intensity, utilizing the Ornstein-Uhlenbeck process to reflect on the temporal evolution and traceability of the attacks. Moreover, by integrating queueing theory, the model facilitates a detailed examination of traffic dynamics under DDoS conditions, providing insights into potential delays and service interruptions. The study also investigates the impact of DDoS attacks on both the dynamic and steady-state operation of the grid, offering a comprehensive perspective on the cybersecurity threat landscape. Simulation outcomes confirm that successful disruptions in EVCS due to DDoS attacks can lead to significant disturbances, underscoring the need for robust cybersecurity protocols.

The Static synchronous compensator (STATCOM) is a renowned FACTS (flexible alternating current transmission system) device used in power grids to cope with protean conditions. This article provides a comprehensive bibliographic review of various aspects of STATCOM developed over the last 16 years. The paper includes a detailed study presenting different models, test systems, and results of various researches. The study covers the modelling, control technology, stability, optimal location, applications, and installation of STATCOM. The modelling of STATCOM is diverse and include various models such as voltage source converters, software-based models, load flow models, pulse width modulation, and modular multilevel converters. The control technology includes a PI/PID controller, fuzzy-based, feedback controller, model predictive controller, sliding mode controller, and miscellaneous controller based on different schemes, algorithms, and controllers. In studying the stability analysis, all stability aspects such as steady-state stability, dynamic stability, and transient stability are considered for the stability analysis. The genetic algorithm, heuristic algorithm, probabilistic technique and branch and bound approach are mainly used for the optimal placement of STATCOM as described in the available research paper. Various applications of STATCOM in power system are identified such as optimal power flow, voltage stability, voltage fluctuation mitigation, fault analysis and total harmonic distortion. This paper, also mentions the current installation of STATCOM is also mentioned with their different locations such as China (2018), and Canada (2019). The current functions of STATCOM still have many limitations. So there is still a lot of room for improvement. This paper will help the researcher finding the reference of a particular topic of interest in different aspects of STATCOM. The finding of different sections of the paper can help the researchers to develop new ideas and work on different prospective of the device.

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Demand management of electric vehicles (EVs) in shared residential parking lots presents challenges for sustainable transportation systems. Especially, in shared parking lots where multiple EVs share the same parking space, such as residential apartments. This is challenging due to involvement of various factors such as limited number of chargers, limited capacity of transformer, and diverse driving behavior of EV owners. To address this issue, this study proposes an optimal demand management framework that addresses limited chargers, transformer capacity, and diverse driving behavior to promote sustainable EV integration. By estimating driving behavior, energy consumption, and utilizing a linear programming-based optimization model, power allocation to EVs is optimized based on multiple factors. A satisfaction index is introduced to measure the satisfaction level of the EV community, further emphasizing user-centric sustainability. Performance analysis includes factors such as power usage, charger utilization, and community satisfaction. The performance of the proposed method is compared with a conventional method and the proposed method increase the satisfaction index of the community by up to 10%. In addition, sensitivity analysis is used to explore the impact of factors like charger availability, EV penetration, and transformer capacity limits. Results show that with 3% EV penetration, satisfaction levels exceed 75%, reaching over 80% with five chargers and 6% EV penetration.

Background: The specialty of family medicine, established in Saudi Arabia in the 1980s, has rapidly progressed in healthcare settings and is increasingly utilized by the population as well as recent MBBS graduates. Universally, there is ambiguity in the duration, curriculum, and assessment methods used in family medicine specialization programs. Methodology: A cross-sectional study was conducted among 183 fresh graduates from a 3-year and 4-year residency program. Data were collected using electronic forms, which were subsequently transferred to Microsoft Excel. Following appropriate coding, the data were transferred to SPSS for analysis. The dataset was then cleaned, and statistical tests, such as Chi-square and independent t-tests, were used to draw inferences. Results: Males (50.3%) and females (49.7%) had almost equal distribution in the study. Overall, 67.6% of respondents had passed the final exam; the pass percentage was 69.3% for the 3-year residency program and 66.4% for the 4-year program. The overall mean score for perceived achievement of SaudiMED-FM 2020 competencies was 23.06 ± 5.52 out of a total score of 30. On comparing the 3-year versus 4-year residency program, there was no statistically significant difference between perceived competency scores and professional satisfaction scores. Among the study participants, 19 (10.4%) had ‘serious burnout’, and 22 (12%) had ‘extremely serious burnout’. Professional satisfaction was significantly associated with burnout (P = 0.006). Conclusions: Based on the study results, there was no significant difference regarding academic performance, perceived competencies, and professional satisfaction among the graduates of the 3-year versus 4-year residency program. Approximately more than half of the graduates had suffered from burnout which was reported more by the females and those with financial issues. The majority of the respondents suggested improvements in clinical rotation and assessment methods.

The paper investigates and assesses the contract selection procedure used in Kuwait’s construction sector. The ideas and insights of engineers involved in significant Kuwaiti construction projects will be extensively considered. In the Kuwaiti building sector, various ways of choosing the contract form will be discussed. In order to gather pertinent data about the country’s primary construction projects, questionnaires will be used. This methodology ensures a first-hand account of the challenges and preferences within the industry. This data will be analyzed to determine the best ways to enhance the current system utilized for Kuwaiti building contracts for the choice of contract forms and payment terms that could benefit from the inclusion of measures to guarantee those types of task delivery systems and payment terms in the country’s future construction projects. This paper explores the typical contract types and payment mechanisms used in Kuwait, drawing on a thorough analysis of current literature, governmental regulations, and business practices. The Standard Forms of Contract, which offer fixed-priced payments, have become the most popular option. However, when used for extensive and technically challenging projects, this contract form’s simplicity presents difficulties. Additionally, the existing system encourages contract awards based on the lowest tender, which raises questions regarding appropriateness and proportionality. The study suggests an arsenal of criteria for improving the deal selection process, with an emphasis on diverse terms of payment inside the task delivery system, in order to allay these worries. It highlights the need for a more comprehensive approach for deal selection that takes project complexity, financial constraints, and long-term project interest into account. The proposed criteria additionally include adaptability to project complexity, ensuring flexibility for challenges in large projects. Financial considerations, aligning with budgetary requirements, are crucial. The emphasis is on long-term project success, and finding a balance between simplicity and adaptability in contracts is key. These comprehensive criteria aim to improve decision-making in selecting standard contract forms for construction projects, addressing challenges in large, technically demanding endeavors in Kuwait. This research contributes to the field by introducing a novel set of criteria for contract selection, tailored to the Kuwaiti construction context. The study’s originality lies in its approach to addressing the challenges posed by current practices and its focus on refining the system for future projects. Additionally, the study employs a rigorous questionnaire survey to extract firsthand insights from industry professionals, ensuring a robust and contextually relevant exploration of the contract selection landscape in Kuwait’s construction sector.

Renal involvement of systemic lupus erythematosus needs aggressive treatment. Despite the development of multiple international guidelines, differences in practices exist. This study aimed to explore the current practices of pediatric rheumatologists and nephrologists for the diagnosis, management, and monitoring of lupus nephritis (LN) in Saudi Arabia through a survey. Among the 61 respondents, 54.1% were pediatric nephrologists and 49.9% were pediatric rheumatologists. Predominantly, the participating physicians received training either nationally (57%) or in North America (45%). Most of the respondents (77%) did not have a combined rheumatology-nephrology clinic, primarily because of space or time limitations (75%), or a lack of the other specialty (13%). In terms of the decision to request a renal biopsy, the most common factors were nephrotic-range proteinuria (85%) and a lower level of proteinuria associated with hypocomplementemia or elevated anti-double-stranded (ds) DNA (73%). There was marginal agreement over monitoring the disease’s activity and treatment response; Complements 3 and 4, anti-dsDNA, protein-creatinine ratio, and estimated glomerular filtration rate were the most popular parameters. The main reason for repeating a renal biopsy was a new renal manifestation that was inconsistent with the previous biopsy. There was considerable variability in the induction therapies used to initiate and taper corticosteroids and conventional immunosuppressive drugs. Most respondents (91%) used angiotensin-converting enzyme agents to control proteinuria. Considerable agreement exists among Saudi physicians managing children with LN but significant variations exist regarding the therapeutic strategies. Additional endeavors are needed to establish a unified national clinical approach for managing LN in children.

Background: The COVID-19 pandemic has induced a substantial burden on healthcare organizations, with increased workload and stress for healthcare providers. Healthcare professionals working on the frontline are vulnerable to stress, putting their psychological and mental wellbeing in considerable jeopardy. Methods: This is a cross-sectional study using data collected from a self-administered questionnaire that was distributed electronically to healthcare workers. The validated Kessler Psychological Distress Scale (K10) and the General Self-Efficacy Scale (GSE) were used to measure the level of stress of the healthcare professionals and the psychological impact of the pandemic on them. Results: Two hundred and thirteen participants were included. A third of the responders (34.3%) were previously infected with COVID-19, while 72.3% had to self-isolate during the pandemic. The average score for the K10 questionnaire was 24.8 ± 9 out of 50, where almost a third of the responders (33.3%) had very high psychological stress levels. The average score for the GSE was 30.2 ± 5.3 points out of 40. Nurses and physicians (p = 0.033) showed significantly higher scores on the K10 survey. Furthermore, nurses between ages 20 and 29 (p = 0.025) and nurses of any age (p = 0.009) had significantly high levels of psychological stress. Conclusion: Healthcare professionals are at significant risk of psychological and mental adverse effects, particularly nurses on the frontline. Such findings should drive initiatives to prepare task forces that can put forward and implement strategies to minimize the risk imposed on the psychological and mental wellbeing of frontline health workers. [SJEMed 2022; 3(2.000): 138-144]

Abstract Improvements in the high accuracy of micro‐phasor measurement unit (μPMU) and synchrophasor unit provide the distribution network a special perspective to access full observability in the presence of renewable distribution generations (DGs). In this regard, modelling the uncertainty effects for accurate fault detection in smart grids has become a novel turning point. This research work attempts to develop a novel stochastic architecture based on unscented transform (UT), which requires a very few number of μPMUs, to communicate in a secured blockchain‐enabled structure to allocate and detect the smart grid irregularities and faults. Such a blockchain‐based technique can be beneficial for encrypting the data transmitted among the μPMUs in the smart grid consisting of a variety of distributed energy sources (DERs) and high impedance fault events, while incorporating the uncertainties associated with the load and individual installation sensors. The proposed stochastic structure benefits from voltage measurement and uses its angle in event placement that performs more efficiently than the conventional sensors based on high‐voltage and current metering. The simulation results show the great precision and effectiveness of the proposed model during various fault scenarios in smart grid.

This paper presents a policy approach for the technological transition from hydropower to green energy in developing countries. Conventional electricity generation technologies have proven to be a burden on the economy of a country, as they have to depend on fossil fuels to meet their energy needs, such as diesel and gasoline. Pakistan has been taken as a case study to show the growing electricity demand of a developing country that implores major technological initiation. This serves as the assessment of suitability and resource regarding the installation of floating solar photovoltaic (FSPV) on reservoirs of hydroelectric dams, thus acting as a virtual battery. Generation from FSPV can complement the hydropower generation in the dry period, consequently meeting the peak demand. In real-time, by employing both technologies at the same substation, hydropower covers the intermittency issues of floating PV technology by improving power quality. Seven dams selected for this study have been analyzed based on their percentage surface area of the reservoir for electricity generation, water conservation, and emission reduction. Tarbela dam has been further analyzed for demonstrating the virtual battery effect by improving the electricity generation profile. The proposed approach meets the electricity needs of about 15.5% of the total population and serves the water need of 2.3 million people in the country.

This work primarily focuses on electrical characteristics of a hybrid power system (HPS) incorporating renewable energy generation (REG) (HPSREG). The major components of HPSREG are the resources coordinated with multi-unit of photovoltaic cells, multi-unit of wind turbine generators, a diesel engine generator (DEG), energy storage system (ESS) with diverse nature and an electric vehicle (EV). The performance characteristics of HPSREG are determined by constant generation of power from the various sources as well as varying load perturbations. As the variation in load demand will introduce fluctuation in frequency and power with constant generation. In few of overcome the frequency and power deviation under both the above-mentioned generation and load demand conditions, proper control technique is required. In order to control the deviation in frequency and power, an integration in the environment of fractional order (FO) calculus for proportional–integral–derivative (PID) controller and fuzzy controller, termed with FO-Fuzzy PID controller tuned with quasi-opposition based harmonic search (QOHS) algorithm has been proposed. The results acquired with the proposed FO-Fuzzy-PID controller are then analyzed along with FO-PID and PID controller route for quantify effectiveness for the same under the considered cases to determine the effectiveness of the algorithm undertaken. Sensitivity investigation is also conducted in order to show the strength of the technique under study of differences in HPSREG parameters of magnitude.

Thin-film phototransistors based on multilayer MoS2 are of great technological importance, but their photoresponsivity may be hindered by an indirect bandgap. Here, nano-patterning of multilayer MoS2 overcomes this limitation by inducing trap states within the bandgap, resulting in a high photoresponsivity of 622.2 A W−1.

In a data‐driven economy, virtually all industries benefit from advances in information technology—powerful computing systems are critically important for rapid technological progress. However, this progress might be at risk of slowing down if the discrepancy between the current computing power demands and what the existing technologies can offer is not addressed. Key limitations to improving energy efficiency are the excessive growth of data transfer costs associated with the von Neumann architecture and the fundamental limits of complementary metal–oxide–semiconductor (CMOS) technologies, such as transistors. Herein, three approaches that will likely play an essential role in future computing systems are discussed: memristive electronics, spintronics, and electronics based on 2D materials. The authors present how these technologies may transform conventional digital computers and contribute to the adoption of new paradigms, like neuromorphic computing.

This paper proposes a control technique for a large-scale grid-connected photovoltaic (PV) plant that maintains the connection of an inverter to the grid voltage under different types of faults, while injecting a reactive power to accommodate the required grid connection. This control strategy is suggested to improve the low-voltage ride-through (LVRT) capability of grid-connected PV power generation plants. A 20 MW solar PV power plant is modeled and simulated using Matlab/Simulink. The power plant is composed of 10 parallel groups of arrays with a power rating of 2 MWp. The solar PV arrays are connected to a medium-voltage side-rated 22 KV to the utility grid. A dynamic analysis of the grid-connected large-scale solar PV power plant is introduced. This analysis is accomplished in order to determine the impact of three-phase short-circuits at the point of common-coupling (PCC), where the solar PV power station is connected to ensure a practical voltage level by injecting active and reactive power. The reactive power support allows for faster restoration of voltage values at the PCC. When subjected to transient disturbances, the stability of the studied system relies on both the type of the disturbance and the initial operating situation. The disturbance may be either small, resulting from electrical load changes, or large, such as from a transmission line short-circuit (fault) and significant generator loss.

Non-deferrable loads equipped with distributed energy resources, such as solar photovoltaic generation and energy storage, can offer a wide range of benefits to the power system, including load leveling, hedging against forecast uncertainty, and ancillary services. This paper presents a techno-economic approach to optimally equip a flexible energy resource, namely a battery energy storage system (BESS), with non-deferrable loads for capacity enhancement of a distribution grid. The proposed approach is generic in applicability, and includes two different optimization mathematical models. The first model quantifies the needed flexibility with non-deferrable loads, based on a consideration of distribution grid limitations, while the second model determines the optimal flexibility amount associated with non-deferrable loads considering investor profitability. Thereafter, a distribution operations model is developed to evaluate the impact of non-deferrable loads, equipped with an optimal size of BESS, on the distribution system loading capacity. An example of non-deferrable loads considered in this paper is that of the rapid charging loads of plug-in electric vehicles (PEVs) that cannot be controlled or shifted due to the short stay of PEVs at a charging facility. Hence, a probabilistic model for PEV rapid charging loads is first developed. Case studies and simulation findings, considering a 32-bus distribution system, demonstrate that the proposed approach helps reduces the impact of non-deferrable loads on a distribution system and enhances the system power margin, which defers the need for system upgrades.

In this paper, a self-learning multi-class intelligent model for wind turbine fault diagnosis is proposed by using MFQL (Modified-Fuzzy-Q-Learning) technique. The MFQL is adaptive in nature and extension of fuzzy-Q-learning method where look-up table of Q-learning is conquered by fuzzy based approximation strategy to reduce the curse of dimensionality of the Q-learning. The proposed MFQL classifier diagnoses the mechanical and imbalance faults without using mechanical sensors. Proposed methodology is addressed with relying on PMSG (Permanent Magnet Synchronous Generator) stator current signals, which is already being used by protection system of wind turbines. According to the aforementioned description, non-stationary current signals of PMSG have been pre-processed to extract the input features by empirical mode decomposition followed with J48 algorithm based most relevant input feature selection. For the one-step ahead performance demonstration of the proposed MFQL approach, results have been compared with neural network, support vector machines, fuzzy logic, and conventional Fuzzy-Q-Learning techniques. Demonstrated results outperform the capability of proposed MFQL approach. Moreover, MFQL is developed first time to implement in the area of WTGS fault diagnosis in the literature.

The fast globalization of renewable energy-based technologies has enabled its wide speared utilization as well. This has shaped a new prospect of operation in the modern electricity system. But, its dependency on environmental factors leads to an uncertain scenario in the day-ahead electricity market. During this period, compromises are made in the genuine process of expenditure and resources of the producers to offset the capacity that decreases the profits for the producers. In general, a significant variety of scenarios need to be taken into account when describing uncertainty, thereby necessitating the need for techniques of scenario reduction. Therefore, to manage the intractable effects of solar radiation and wind speed instability, the function of the Beta and Weibull distribution of probability is implemented, respectively, and scenarios are minimized using forward-reduction algorithms. Besides, an underestimation and overestimation of the cost function are used to calculate the deviation of renewable influence. Thus, this paper is suggesting a valuable bidding strategy to maximize the remuneration of electricity producers in the presence of rival competitors and the instability of solar and wind energy. This problem has been prepared by taking the benchmark IEEE 30-bus network with and without renewable energy sources, and this problem has been solved by using the Gravitational Search Algorithm. The observations of the outcome demonstrate the appropriateness of the projected bid strategy in the presence of volatility of renewable energy.

The conventional neutral point clamped (NPC) multilevel inverter topology needs voltage balancing circuits to balance the dc-link capacitor, the number of component count is high and output voltage is half of the input voltage which increase the size of the source side dc/dc converter in PV applications. In this paper, a new topology of seven level neutral point clamped inverter is developed. The proposed inverter has a self-voltage boosting capability using a floating capacitor to boost the output voltage one and half of the input voltage. In this proposed topology, no additional sensors are required for the floating capacitor voltage stability, which results in minimizing the complexity of designing the inverter. The direct link between the neutral point and the mid-point of the dc-link capacitors significantly reduces the leakage current and common mode voltage in this inverter. A thorough comparison between the developed topology and recent suggested topologies is carried out which set the benchmark for the proposed one due to its lower switch count and higher voltage gain. The proposed topology is verified in simulation and prototype hardware model and results are discussed with dynamic load variations. The efficiency of the inverter is 97.1% @200W and low as 88.1 % @ inductive load. The voltage THD is 17.01% for simulation and 19.3% I for experimental is results.

In this paper, the optimal designing of passive power filter (PPF) is formulated as a multi-objective optimization (MOO) problem under several constraints of system's performance indices (PIs) such as individual as well as total harmonic distortion (THD) in the line current and the point of common coupling's (PCC) voltage, distribution line's ampacity under harmonic currents overloading, steady-state voltage profile, load power factor (PF) and a few associated with the filter itself. The optimal design parameters of a third-order damped filter are simultaneously determined for achieving maximum PF at the PCC while keeping system's other indices such as total demand distortion (TDD) in the line current, total voltage harmonic distortion (TVHD) at the PCC and total filter cost (FC) incurred at a minimum by obtaining a best-compromised solution using the newly proposed multi-objective Pareto-based firefly algorithm (pb-MOFA). A novel MOO approach inspired by the modified firefly algorithm and Pareto front is established in order to deal with PPF design problems. The extension of MOFA is considered for producing the Pareto optimal front and various conclusions are drawn by analysing the trade-offs among the objectives. The efficiency and accuracy of the proposed pb-MOFA, in solving the concerned MOO problem, is validated by comparing an obtained solution and three computed PIs viz. convergence metric (CM), generational distance (GD) and diversity metric (DM) with those obtained from popular multi-objective Pareto-based PSO (pb-MOPSO), non-dominated sorting genetic algorithm (NSGA-II) and recently introduced multi-objective slime mould algorithm (MOSMA). The need for true Pareto front (TPF) is served by the one obtained by Monte Carlo method. At last, the impacts of different background voltage distortion (BVD) levels and load-side's nonlinearity levels (NLLs) on filter performance are analysed.

The penetration of plug-in electric vehicles (PEVs) has increased in the transportation sector in the last few years and it has increased the uncertain load in the power sector. In order to analyze the impact on the power grid and plan infrastructure, modeling of PEV load profiles is required. Determining realistic PEV load profiles is challenging due to the involvement of serval uncertainties and complex interdependencies among different factors and to date, there are no benchmark load profiles of PEVs. In this paper, realistic and ready-to-use load profiles for PEVs are developed by considering vehicle mobility, charging infrastructure, and the market share of PEVs. Firstly, the U.S. National Household Travel Survey (NHTS) data is filtered to remove vehicles with unrealistic, duplicate, and missing data. Secondly, a set of relevant parameters is extracted to estimate different features of PEVs, such as arrival time, departure time, and daily mileage. Then, all the commercially available PEVs are grouped into four clusters using the K-means algorithm. Finally, the per unit (per PEV) load profiles are estimated using the information of the available PEVs in the market, charging levels in the residential sector, and features extracted in the previous step. A large set of scenarios are considered for each PEV cluster in determining the load profiles. The pre-unit profiles estimated in this study are ready-to-use for researchers and planners in the PEV industry and are realistic due to consideration of different relevant factors and a large traveling database of vehicles. The developed per-unit load profiles are used to estimate and analyze the PEV load profiles of the top four countries with the highest penetration percentage of PEVs.

Background: The COVID-19 pandemic has affected many individuals in the past year through increased mortality, morbidity, and economic disturbances while also affecting individual lifestyles. Healthy lifestyle practices can reduce mortality and morbidity and improve quality of life. We aimed to identify daily lifestyle changes during the COVID-19 pandemic. To do so, we examined factors related to family, livelihood, and other associated changes. Methodology: A cross-sectional study was conducted among attendees visiting selected primary health care centers of Qassim province. The data was collected through direct interview method, and 365 individuals participated during the study period. Data was entered in SPSS version 21.0, and necessary statistical tests were applied. Results: Out of 365 individuals, 27.4% were male and 72.6% were female. There was a drastic decrease in the frequency of in-person shopping (74.2%) and a steep increase in online shopping (41.4%). The mean weight increase was 4.5 (SD = 3.09) kg. Telemedicine use was 43.6%. There was a statistically significant association found between male gender and fear about COVID-19 (P = 0.019). Conclusions: We noticed adverse lifestyle changes in the study population during the COVID-19 pandemic. Health promotional measures and lifestyle modifications are still required to combat COVID-19.

Phospholipases A2 (PLA2s) catalyze hydrolysis of the sn-2 substituent from glycerophospholipids to yield a free fatty acid (i.e., arachidonic acid), which can be metabolized to pro- or anti-inflammatory eicosanoids. Macrophages modulate inflammatory responses and are affected by Ca2+-independent phospholipase A2 (PLA2)β (iPLA2β). Here, we assessed the link between iPLA2β-derived lipids (iDLs) and macrophage polarization. Macrophages from WT and KO (iPLA2β−/−) mice were classically M1 pro-inflammatory phenotype activated or alternatively M2 anti-inflammatory phenotype activated, and eicosanoid production was determined by ultra-performance LC ESI-MS/MS. As a genotypic control, we performed similar analyses on macrophages from RIP.iPLA2β.Tg mice with selective iPLA2β overexpression in β-cells. Compared with WT, generation of select pro-inflammatory prostaglandins (PGs) was lower in iPLA2β−/−, and that of a specialized pro-resolving lipid mediator (SPM), resolvin D2, was higher; both changes are consistent with the M2 phenotype. Conversely, macrophages from RIP.iPLA2β.Tg mice exhibited an opposite landscape, one associated with the M1 phenotype: namely, increased production of pro-inflammatory eicosanoids (6-keto PGF1α, PGE2, leukotriene B4) and decreased ability to generate resolvin D2. These changes were not linked with secretory PLA2 or cytosolic PLA2α or with leakage of the transgene. Thus, we report previously unidentified links between select iPLA2β-derived eicosanoids, an SPM, and macrophage polarization. Importantly, our findings reveal for the first time that β-cell iPLA2β-derived signaling can predispose macrophage responses. These findings suggest that iDLs play critical roles in macrophage polarization, and we posit that they could be targeted therapeutically to counter inflammation-based disorders.

Common geometrical layouts could potentially be bottlenecks, particularly during emergency and high density situations. When pedestrians are interacting with such complex geometrical settings, the congestion effect might not be uniform over the bottleneck area. This study uses the trajectory data collected through a controlled laboratory experiment to explore the spatial variation of speeds when a group of people navigates through bends. Four turning angles, i.e., 45°, 90°, 135° and 180°, with a straight corridor and two speed levels, i.e., normal speed walking and slow running (jogging), were considered in these experiments. Results explained that the speeds are significantly different over the space within the bend for all angles (except 0°) under both speed levels. In particular, average walking speeds are significantly lower near the inner corner of the bend as compared to the outer corner. Further, such speed variations are magnified when the angle of the bend and desired speed increase. These outcomes indicate that even smaller turning angles, e.g., 45° could create bottlenecks near the inner corner of the bend, particularly when the walking speeds are high. The findings of this study could be useful in understanding the congestion and bottleneck effects associated with complex geometrical settings, and calibrating microscopic simulation tools to accurately reproduce such effects.

Transactive energy is a highly effective technique for peers to exchange and trade energy resources. Several interconnected blocks, such as generation businesses, prosumers, the energy market, energy service providers, transmission and distribution networks, and so on, make up a transactive energy framework. By incorporating the prosumers concept and digitalization into energy systems at the transmission and distribution levels, transactive energy systems have the exciting potential to reduce transmission losses, lower electric infrastructure costs, increase reliability, increase local energy use, and lower customers’ electricity bills at the transmission and distribution levels. This article provides a state-of-the-art review of transactive energy concepts, primary drivers, architecture, the energy market, control and management, network management, new technologies, and the flexibility of the power system, which will help researchers comprehend the various concepts involved.

This paper comprehensively reviews the current status of multidisciplinary technologies in electric vehicles. Because the electric vehicle market will expand dramatically in the coming few years, research accomplishments in power electronics technology for electric vehicles will be highly attractive. Challenges in power electronics technology for driving electric vehicles, charging batteries, and circuit topologies are being explored. This paper aims primarily to address the practical issues of the future electric vehicles and help researchers obtain an overview of the latest techniques in electric vehicles, focusing on power electronics-based solutions for both current and future electric vehicle technologies. In this work, different medium-and high-voltage DC-AC inverter topologies are investigated and compared in terms of power losses and component requirements. Recent research on electric vehicle power converters is also discussed, with highlighting on soft-switching and multilevel inverters for electric vehicle motor drives. In this paper, a methodical overview and general classification of DC-AC power converters are presented. In specific topologies, drawbacks such as voltage stresses on active switches and control complications may occur, which can make them difficult for immediate commercialization. However, various modified circuit topologies have been recommended to overcome these drawbacks and enhance the system performance.

In recent years, air pollution and climate change issues have pushed people worldwide to switch to using electric vehicles (EVs) instead of gas-driven vehicles. Unfortunately, most distribution system facilities are neither designed nor well prepared to accommodate these new types of loads, which are characterized by random and uncertain behavior. Therefore, this paper provides a comprehensive investigation of EVs’ effect on a realistic distribution system. It provides a technical evaluation and analysis of a real distribution system’s load and voltage drop in the presence of EVs under different charging strategies. In addition, this investigation presents a new methodology for managing EV loads under a dynamic response strategy in response to the distribution system’s critical hours. The proposed methodology is applied to a real distribution network, using the Monte Carlo method and the CYME program. Random driver behavior is taken into account in addition to various factors that affect EV load parameters. Overall, the results show that the distribution system is significantly affected by the addition of EV charging loads, which create a severe risk to feeder limits and voltage drop. However, a significant reduction in the impact of EVs can be achieved if a proper dynamic demand response programme is implemented. We hope that the outcomes of this investigation will provide decision-makers and planners with prior knowledge about the expected impact of using EVs and, consequently, enable them to take the proper actions needed to manage such load.

In this paper, a new multi-port DC-DC power converter used to deal with the intermittent nature and slow response in renewable energy applications is proposed. The proposed converter integrates a DC-DC converter and a DC-AC inverter, and the proposed circuit integrates various renewable energy sources in addition to the energy storage unit. By combining renewable energy sources with a statistical trend to offset each other, the impact of the intermittency can be considerably minimized. This combination increases the overall system reliability and usability. Moreover, integrating such systems with energy storage systems can overcome the slow response issue of renewable sources. It can provide the additional energy required by the load or absorb the extra energy provided by the power sources, which greatly improves the dynamics of the overall system. The proposed converter can reduce the system cost and size and improve the efficiency and reliability. The operation principle is studied in detail, and the design considerations are provided. The proposed architecture and its control strategy were analyzed and studied using the Simulink/MATLAB environment. Finally, the feasibility of the proper operation of the studied converter was experimentally verified based on the results of experimental studies conducted on a 300 W prototype implemented in a laboratory.

Power transformers are located in the electrical transmission and distribution networks where different voltage levels are needed. The turn ratio of the low voltage and high voltage windings is mechanically controlled by an on-load tap changer or de-energized tap changer. As the tap changer is the transformer’s only moving part, it is highly susceptible to mechanical failure and aging degradation. While some diagnostic tools have been used to determine the mechanical condition of tap changer contacts, not much attention was given to use the frequency response analysis to diagnose the transformer’s tap changers’ mechanical integrity. This paper is taking one step forward into maturing the application of the frequency response analysis (FRA) technique to detect transformer tap changer faults. In this regard, two common tap changer faults are created, and experimental testing for four FRA test configurations is conducted. For a better understanding of the tap changer fault mechanism, an electrical equivalent circuit model is proposed and designed using Simulink. The simulation and implementation of the equivalent circuits using MATLAB\R2018a.

The Ca2+-independent phospholipase A2β (iPLA2β) is a member of the PLA2 family that has been proposed to have roles in multiple biological processes including membrane remodeling, cell proliferation, bone formation, male fertility, cell death, and signaling. Such involvement has led to the identification of iPLA2β activation in several diseases such as cancer, cardiovascular abnormalities, glaucoma, periodontitis, neurological disorders, diabetes, and other metabolic disorders. More recently, there has been heightened interest in the role that iPLA2β plays in promoting inflammation. Recognizing the potential contribution of iPLA2β in the development of autoimmune diseases, we review this issue in the context of an iPLA2β link with macrophages and T-cells.

This paper proposes an Exponentially Varying Whale Optimization Algorithm (EVWOA) to solve the single-objective non-convex Cogeneration Units problem. This problem seeks to evaluate the optimal output of the generator unit to minimize a CHP system’s fuel costs. The nonlinear and non-convex characteristics of the objective function demands a powerful optimization technique. The traditional Whale Optimization Algorithm (WOA) is improved by incorporating four different acceleration functions to fine-tune its performance during exploration and exploitation phases. Among the four variants of the proposed WOA, the emphasis is laid on the EVWOA which uses the exponentially varying acceleration function (EVAF). The proposed EVWOA is tested on six different small-scale to large-scale systems. The results obtained for these six test systems, followed by a statistical study highlight the supremacy of EVWOA for finding the best optimal solution and the convergence traits.

In the above article [1], a minor typo error should be corrected via this correction article. The unit of filter’s capac-itances, in Table 8, is microfarad (symbolized $\mu $ F) as per the obtained results.