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Photovoltaic modules are impacted by overheating, which degrades their conversion efficiency and shortens their lifespan. This work attempts to study the cooling potential for a hybrid photovoltaic/thermal (PV/T) system by employing CuO and Fe2O3 nanofluids with 0.2% and 0.3% volume fractions (φ), circulated in a heat exchanger attached at the rear side of the PV module to lower the temperature of the PV cells and improve its energy and exergy efficiencies. Consequently, a 2D numerical model was analysed given the energy balance across the PV/T system layers, which is evaluated in line with measured experimental data. The results indicate that the successfully synthesised nanomaterials could improve the performance of the nanofluids and increase the heat exchange between PV/T system layers, reducing the PV cells’ temperature by 23.49% and 34.58% when cooling by CuO and Fe2O3 nanofluids at φ=0.3%. Compared to the uncooled PV module, the electrical efficiency has increased by 9.21% and 10.30%, while thermal efficiency increased by 38.9% and 43.3% under cooling with CuO and Fe2O3 nanofluids, respectively. Thereby, the exergy destruction (exergy losses) and entropy generation have decreased by about 26% and 68% when cooling with Fe2O3 nanofluid, which improved the exergy efficiency by 13% more than CuO nanofluid.

Recently, photovoltaic technology applications have occupied a wide range in electric generation. The temperature rising higher than the operating temperature permissible is the weak point facing this technology, which significantly influences the performance of the photovoltaic cells. Using nanofluids as the coolant of photovoltaic (PV) modules is an effective method, circulating nanofluids in the heat exchanger attached to the backside of the PV module to absorb excess heat and enhance the performance of the PV module. The current work investigates using zirconium oxide (ZrO 2) nanofluid as a coolant at different volume concentrations (0.015 vol%, 0.025 vol%, 0.0275 vol%) in deionized (DI) water to reduce the temperature of the photovoltaic PV cells and then analyses the performance from the energy/exergy viewpoints. The results indicate that the PV module temperature was reduced by 10.2 °C when cooled by ZrO 2 nanofluid at 0.0275% volume concentration in DI water compared to the reference PV module, resulting in remarkable system energy and exergy enhancement. Besides, the cooling by DI water has decreased the PV module temperature by 5.1 °C. The overall efficiencies gradually increment with an increase in volume concentration by 8.9%, 18.8 % and 24.4%, respectively, compared with PV modules cooled by DI water. Using ZrO 2 nanofluids with 0.0275 vol% could enhance the exergy efficiency by 66.8% and reduce the exergy losses and entropy generation by 7% and 26%, respectively.

In order to address the limitation of low flux in ultrafiltration (UF), a suitable additive is introduced into the base polymer to modify the membrane morphology, thereby enhancing flux rates. In this study, chamomile leaf nanoparticles (Chm NPs) were investigated as a novel green material for utilizing in UF membrane synthesizes. To enhance comprehension of the influence of Chm on the synthesis of PES UF membranes, a series of membranes were fabricated by including different quantities of Chm into the casting solution; (0, 0.5, 1.5, and 2 wt. %.). The synthesized membranes were fully characterized, through the porosity, pore size, hydrophilicity, membrane morphology, and UF efficiency. Manufactured PES/Chm membranes demonstrated significantly increased permeate water flux (PWF) (up to 498 kg/m2 h), which was four times that of the pristine PES membrane (116 kg/m2 h), besides that the bovine serum albumin (BSA) and Congo red dye (CR) rejection of PES/Chm membranes was still kept high. The enhanced PWF was mostly due to the more porous membrane structure and increased hydrophilicity. Meanwhile, the higher surface hydrophilicity of the PES/Chm membranes resulted in greater antifouling performance and the high flux recovery ratio (FRR) of 93 %. Based on the results of this research, the Chm may be used as a novel green additive with substantial application potential in the fabrication of UF membranes wastewater treatment.

The energy and exergy efficiency of a photovoltaic thermal (PV/T) system at various volume fractions is investigated with mono TiO2 nanofluid and new hybrid TiO2–Fe2O3 nanofluid. Serpentine tubes soldered on an absorbing plate attached to the rear of the PV module have been proposed to evaluate the effect of nanofluids on the PV/T temperature reduction, energy produced, and exergy losses. The study compared energy and exergy with previous studies and delivered an economic analysis to confirm the feasibility of applying nanofluids. The results indicated that using TiO2–Fe2O3 nanofluid reduced the PV cell's temperature by 42.19% compared to water, TiO2 nanofluid, which increased the electrical power by 74.5% and 46.22% when cooling by mono and hybrid nanofluid at 0.3 vol%. The PV/T system's maximum thermal and electrical efficiency recorded with mono and hybrid nanofluids was 34.6%, 8.44%, 47.2%, and 12.62%, respectively. Dispersion of hybrid nanocomposite in DI water has enhanced the Nu number and HTC by 42.72% and 23% higher than mono nanofluid, which improved the exergy efficiency of the PV/T system by 14.89%. A better payback period was achieved with a hybrid nanofluid by 54 days with reduced exergy losses by 45.5% and entropy generation by 86.29%.

This study aims to optimize operating parameters of the effect of embedded silica nanoparticles (SiO2 NPs) and modified silica NPs with polyethylenimine (PEI) (SiO2-g-PEI NPs) into polyethersulfone (PES) to fabricate a mixed matrix membranes (MMMs) for pharmaceutical wastewater treatment. The performance of modified MMMs was compared in the separation of Mebeverine hydrochloride (MBV) from aqueous pharmaceutical wastewater. In order to produce a particular quantity of flux and rejection above desired levels, an optimization technique was used to find the best values for various important process parameters. To enhance the effectiveness on a bigger scale, response surface methodology (RSM) and analysis of variance (ANOVA) were utilized as mathematical and statistical approaches. This study examined the effects of operational parameters on the PES-NPs membranes permeate flux and MBV rejection for each sample. These parameters included SiO2/or SiO2-g-PEI NPs content (0.7–1 wt %), solution feed pH values (4-10), and MBV concentration (10–100 ppm). A mathematical model to calculate the permeate flux and rejection (%) was established. The results showed that the SiO2 MMMs had the best performance of 38.27 LMH permeate flux and 81.26% of MBV rejection, while the permeate flux and MBV rejection % for SiO2-g-PEI MMMs were 104.11LMH and 99.00%. The SiO2 wt % of 0.8447%, MBV concentration of 98.18 ppm, and pH of 4 were the optimal parameters for the SiO2 MMMs, while the optimal parameters for SiO2-g-PEI MMMs were SiO2-g-PEI wt. % of 0.93%, MBV concentration of 22.7 ppm, and pH of 4.79 for eliciting the optimum response.

Overheating of photovoltaic (PV) cell is one of the most common issues that cause the degradation of their function and reduce conversion efficiency. This work investigates the effect of using a novel TiO2-CuO hybrid nanofluid to improve the energy and exergy of photovoltaic thermal (PVT) systems by reducing PV cell temperature. Serpentine tubes soldered on an absorbing plate attached behind the PV module were proposed to improve heat removal of the PV module with volume concentrations of 0.2 vol% and 0.3 vol%, with a flow rate of 1.16 L/min. Improving the thermophysical properties of the hybrid nanofluid has reduced the temperature of the PV module by 39% more than the uncooled PV module. The PVT system's electrical power and overall efficiency improved by 77.5% and 58.2%, respectively, at increased volume concentration to 0.3 vol% compared with the uncooled PV module. The exergy analysis indicated an increase in the overall exergy efficiency by 14.97 %, with thermal exergy dropping because of the closer the outlet nanofluid temperature to ambient temperature. Hybrid nanofluid cooling has improved exergy efficiency to 14.97%, reducing exergy losses by 37.9% and entropy generation by 69.6% at 0.3 vol%. The economic analysis shows a better payback period of 21 months when cooling with a hybrid nanofluid compared with the uncooled PV module.

Development and application of hybrid membranes containing multi-component materials are increasing day by day in the fields of environmental protection and water treatment. In this research, the efficiency of titania nanowire (TiO2 NW)-based self-supported hybrid membranes was investigated in the removal of Escherichia coli (E. coli) bacteria and MS2 bacteriophages from contaminated water mimicking the microorganism suspension. Furthermore, toxicology tests on the as-prepared membranes were also performed. TiO2 NWs were coated with iron(III) oxide (Fe2O3) and copper(II) oxide (CuO) nanoparticles, respectively, and cellulose was used as reinforcement material. It was found that, the functionalisation strongly affected the MS2 removal ability of as-prepared membranes, which can be due to the electrostatic interactions between the surface of hybrid membrane and the bacteriophages. The most efficient removal (greater than or equal to 99.99%) was obtained with the TiO2 NW-CuO-cellulose membrane at pH 7.0. The fabricated hybrid membranes were characterized by micro computed tomography (μCT), Raman spectroscopy, Fourier transform infrared spectroscopy (FT-IR), dynamic light scattering (DLS), contact angle measurement and inductively coupled optical emission spectrometry (ICP-OES) techniques. This study shows a simple route of the usage of novel and effective inorganic nanowire-based hybrid membranes for bacteria and virus removal, providing new pathways in the field of water filtration technologies.

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The temperature rising of the photovoltaic (PV) modules is a major issue leading to a reduction in their conversion efficiency and low output power. Therefore, removing heat from the PV module is necessary to permanently work and improve the electrical power output. Serpentine pipes and a thermal absorber plate has proposed with fluid circulation to reduce the PV cell temperature and improve their efficiency. The current work experimentally investigates the effect of using tungsten trioxide (WO3) nanofluids on the PVT system's energy and exergy efficiency at different volume concentrations of 0. 5 vol%, 0. 75 vol%, and 1 vol%. The results indicated an increment in the electrical power output by 11.15 W due to reducing the PV temperature by 21.4% and enhancing the PVT overall efficiency by 29.6% compared with the cooling by Deionized (DI) water. Increasing the volume concentration of nanoparticles increased the Reynolds number, and the Nusselt number enhanced the heat transfer coefficient and increased the pressure drop. Improving the thermal properties of the nanofluid has increased the electrical exergy efficiency and lowered the thermal exergy efficiency due to the reduction in thermal exergy quality. Compared to DI water cooling, exergy losses and entropy generation were reduced by 10% and 34.8%, respectively.

In this study, Zr-pillared montmorillonite clays (Zr-PILCs) were synthesized using two different precursor materials: raw montmorillonite (CM) and sodium ion-saturated montmorillonite (Na-CM) at different Zr/clay ratios (2.5, 5 and 10 mmol/g). To study the effect of Zr concentration and clay pre-treatment with NaCl on pillaring, the modified clay samples were characterized in detail using X-ray diffraction (XRD), Fourier transform infrared spectroscopy (FT-IR), thermogravimetric analysis (TGA), high-resolution transmission electron microscopy (HRTEM), scanning transmission electron microscopy and energy-dispersive X-ray spectroscopy (STEM-EDX). The XRD analysis showed the increase of basal spacing of Zr-PILCs prepared from both precursor materials: from 1.26 to 1.74 nm in the case of CM, and from 1.13 to 1.93 nm for Na-CM. Results from FT-IR revealed new bands ascribed to Zr-O bonds in the range of 400–500 cm−1 in Zr-pillared samples obtained from Na-CM at Zr/clay ratios of 2.5 and 5 mmol/g. The distribution and nature of Zr species in between the silicate layers were studied using STEM-EDX and HAADF imaging. They were found to be separated by a distance of 1.5–3 nm and their thickness lies in the range of 1–2 nm. Pillared clays prepared from pre-treatment with NaCl were more thermally stable at higher temperatures.

In this study tungsten oxide and graphene oxide (GO-WO2.89) were successfully combined using the ultra-sonication method and embedded with polyphenylsulfone (PPSU) to prepare novel low-fouling membranes for ultrafiltration applications. The properties of the modified membranes and performance were investigated using Fourier-transform infrared spectroscopy (FT-IR), scanning electron microscopy (SEM), contact angle (CA), water permeation flux, and bovine serum albumin (BSA) rejection. It was found that the modified PPSU membrane fabricated from 0.1 wt.% of GO-WO2.89 possessed the best characteristics, with a 40.82° contact angle and 92.94% porosity. The permeation flux of the best membrane was the highest. The pure water permeation flux of the best membrane showcased 636.01 L·m−2·h−1 with 82.86% BSA rejection. Moreover, the membranes (MR-2 and MR-P2) manifested a higher flux recovery ratio (FRR %) of 92.66 and 87.06%, respectively, and were less prone to BSA solution fouling. The antibacterial performance of the GO-WO2.89 composite was very positive with three different concentrations, observed via the bacteria count method. These results significantly overtake those observed by neat PPSU membranes and offer a promising potential of GO-WO2.89 on activity membrane performance.

The emergence of mixed matrix membranes (MMMs) or nanocomposite membranes embedded with inorganic nanoparticles (NPs) has opened up a possibility for developing different polymeric membranes with improved physicochemical properties, mechanical properties and performance for resolving environmental and energy-effective water purification. This paper presents an overview of the effects of different hydrophilic nanomaterials, including mineral nanomaterials (e.g., silicon dioxide (SiO2) and zeolite), metals oxide (e.g., copper oxide (CuO), zirconium dioxide (ZrO2), zinc oxide (ZnO), antimony tin oxide (ATO), iron (III) oxide (Fe2O3) and tungsten oxide (WOX)), two-dimensional transition (e.g., MXene), metal–organic framework (MOFs), covalent organic frameworks (COFs) and carbon-based nanomaterials (such as carbon nanotubes and graphene oxide (GO)). The influence of these nanoparticles on the surface and structural changes in the membrane is thoroughly discussed, in addition to the performance efficiency and antifouling resistance of the developed membranes. Recently, GO has shown a considerable capacity in wastewater treatment. This is due to its nanometer-sized holes, ultrathin layer and light and sturdy nature. Therefore, we discuss the effect of the addition of hydrophilic GO in neat form or hyper with other nanoparticles on the properties of different polymeric membranes. A hybrid composite of various NPs has a distinctive style and high-quality products can be designed to allow membrane technology to grow and develop. Hybrid composite NPs could be used on a large scale in the future due to their superior mechanical qualities. A summary and future prospects are offered based on the current discoveries in the field of mixed matrix membranes. This review presents the current progress of mixed matrix membranes, the challenges that affect membrane performance and recent applications for wastewater treatment systems.

Novel hybrid structures have attracted attention in several instances of scientific research and different technological applications in this decade due to their novel characteristics and wide range of applicability. Hybrid membranes with multiple components (three or more) are also increasingly used in water purification applications, and their ease of handling and reusability make them a promising candidate for the degradation of organic pollutants by photocatalysis. In this study, the preparation and characterization of tungsten trioxide nanowire (WO3 NW)-based hybrid membrane structures are reported. Furthermore, the adsorption properties and photocatalytic efficiency of the as-prepared membranes against methylene blue (MB) organic dye under UV irradiation is also presented. Characterization techniques, such as scanning electron microscopy (SEM), high-resolution transmission electron microscopy (HRTEM), energy-dispersive X-ray spectroscopy (EDS), and X-ray powder diffraction (XRD) are performed to study the morphology and surface of the as-prepared hybrid membranes. The removal efficiency of the hybrid membranes against MB is 77% in a 120 min decomposition reaction. The enhanced value can be attributed to the hybrid structure of the membrane that enhances not only the adsorption capability, but also the photocatalytic performance. Based on the results obtained, it is hoped that hybrid membrane technology could be a promising candidate for future photocatalysis-based water treatment applications.

Nowadays, the use of hybrid structures and multi-component materials is gaining ground in the fields of environmental protection, water treatment and removal of organic pollutants. This study describes promising, cheap and photoactive self-supported hybrid membranes as a possible solution for wastewater treatment applications. In the course of this research work, the photocatalytic performance of titania nanowire (TiO2 NW)-based hybrid membranes in the adsorption and degradation of methylene blue (MB) under UV irradiation was investigated. Characterization techniques such as scanning electron microscopy (SEM), transmission electron microscopy (TEM), energy-dispersive X-ray spectroscopy (EDS), X-ray powder diffractometry (XRD) were used to study the morphology and surface of the as-prepared hybrid membranes. We tested the photocatalytic efficiency of the as-prepared membranes in decomposing methylene blue (MB) under UV light irradiation. The hybrid membranes achieved the removal of MB with a degradation efficiency of 90% in 60 min. The high efficiency can be attributed to the presence of binary components in the membrane that enhanced both the adsorption capability and the photocatalytic ability of the membranes. The results obtained suggest that multicomponent hybrid membranes could be promising candidates for future photocatalysis-based water treatment technologies that also take into account the principles of circular economy.

Accurately estimating the state-of-charge (SOC) of lithium-ion batteries (LIBs) in electric vehicles is a challenging task due to the complex dynamics of the battery and the varying operating conditions. To address this, this paper proposes the establishment of an Industrial Internet-of-Things (IIoT)-based digital twin (DT) through the Microsoft Azure services, incorporating components for data collection, time synchronization, processing, modeling, and decision visualization. Within this framework, the readily available measurements in the LIB module, including voltage, current, and operating temperature, are utilized, providing advanced information about the LIBs' SOC and facilitating accurate determination of the electric vehicle (EV) range. This proposed data-driven SOC-estimation-based DT framework was developed with a supervised voting ensemble regression machine learning (ML) approach using the Azure ML service. To facilitate a more comprehensive understanding of historical driving cycles and ensure the SOC-estimation-based DT framework is accurate, this study used three application programming interfaces (APIs), namely Google Directions API, Google Elevation API, and OpenWeatherMap API, to collect the data and information necessary for analyzing and interpreting historical driving patterns, for the reference EV model, which closely emulates the dynamics of a real-world battery electric vehicle (BEV). Notably, the findings demonstrate that the proposed strategy achieves a normalized root mean square error (NRMSE) of 1.1446 and 0.02385 through simulation and experimental studies, respectively. The study's results offer valuable insights that can inform further research on developing estimation and predictive maintenance systems for industrial applications. [ABSTRACT FROM AUTHOR]

Proper operation of the grid-tie transformerless converters under unbalanced and distorted conditions entails a precise detection of the frequency and fundamental component of the grid voltage. One of the main problems that could arise during the estimation of grid parameters is the existence of a DC offset generated from measurement and A/D conversion. This undesirable induced DC offset could appear as a part of the reference sinusoidal current of grid-tie converters. Although literature has proposed the use of an extended complex Kalman filter (ECKF) for the estimation of positive and negative sequence voltage components as a promising competitor to phase locked loops, mitigating the effect of possible DC offsets when a Kalman filter is employed remains scarce. This paper proposes a new extended complex Kalman filter to improve the filter stability for estimating the frequency and the fundamental positive and negative symmetrical components of the grid voltages, where DC offset, scaling error, and noise can successfully be rejected. The theoretical findings are experimentally validated. [ABSTRACT FROM AUTHOR]

This article presents internal model control (IMC) based decentralized reinforce‐control of renewable dynamic virtual power plant (DVPP) so that, it can be integrated into the power system as a substitution of fuel‐based conventional generators. Such grid integration towards net‐zero targets could not be possible without providing additional ancillary service (AS) to the power system, as the traditional AS would fall short with the retirement/substitution of conventional generators. The theory of DVPP from a technical perspective (i.e., TDVPP) is presented in a detailed and simplified manner, including the formulation of a generalized control objective (desired specification) for DVPP integration. The solution approach includes two steps: (1) disaggregation of desired specification and (2) decentralized reinforce‐control to match the disaggregated specification. The theory and solution approach for DVPP integration is presented in a generalized manner enabling the DVPP to offer multiple ASs, but the case study is limited only to frequency control AS (FCAS) in this article. The study is performed on the 'western system coordinating council (WSCC)' test system, in which an attempt is made towards net‐zero targets by substituting the largest thermal generator with renewable DVPP ensuring the grid's operation or dynamics safe. [ABSTRACT FROM AUTHOR]

Background Opioids are frequently added to neuroaxial local anesthetics (LAs). Intrathecal (IT) opioid is not devoid of adverse effects such as postoperative nausea and vomiting (PONV), respiratory depression, and pruritis. IT atropine also carries a significant antiemetic effect, and this can be a valuable modality for the prevention of IT opioidrelated PONV. The antagonist of 5-HT3 receptors such as ondasetron which is usually used to decrease the incidence of nausea and vomiting was considered for the prevention and treatment of neuroaxial opioid-induced (PONV). Method 100 cases of ASA I-II aged 18 and 45 who planned to do elective perineal surgery, and receiving bupivacaine spinal anesthesia were randomly divided into two equal groups. Group (A) cases received IT hyperbaric bupivacaine (10mg 0.5%) in combination with morphine 250 μg and atropine sulphate 100 μg. Before anesthesia, group (B) participants received IT hyperbaric bupivacaine (10mg 0.5%) and 250 μg of morphine and 4mg IV ondansetron. Follow-up for PONV attacks, vital signs, and side effects in the two groups. Results The occurrence of postoperative nausea were 4 and 18% in group A and B, respectively (P value=0.049) while postoperative vomiting was 0 and 12% in group A and B, respectively (P value=0.027). The occurrence of sedation, mouth dryness, headache, and drowsiness were more in group A compared with group B. Conclusion IT atropine is more effective than IV ondasetron preoperative in relieving PONV related to IT morphine, sedation is the frequent side effect occurred in IT atropine, headache is the frequent side effect occurred in the ondasetron group [ABSTRACT FROM AUTHOR]

Very recent work has demonstrated tremendous improvements in facial expression recognition (FER) on laboratory-controlled datasets. However, recognizing facial expressions under in-the-wild conditions still remains challenging, especially on unseen subjects due to high inter-subject variations. In this paper, we propose a novel Probabilistic Attribute Tree Convolutional Neural Network (PAT-CNN) to explicitly deal with large intra-class variations caused by identity-related attributes, e.g., age, race, and gender. Specifically, a PAT module with an associated PAT loss is proposed to learn features in a hierarchical tree structure organized according to identity-related attributes, where the final features are less affected by the attributes. Then, expression-related features are extracted from leaf nodes. Samples are probabilistically assigned to tree nodes at different levels such that expression-related features can be learned from all samples weighted by probabilities. Furthermore, the proposed PAT-CNN can be learned from limited attribute-annotated samples to make the best use of available data. Experimental results on four spontaneous facial expression datasets, i.e., RAF-DB, SFEW, ExpW, and FER-2013, have demonstrated that the proposed PAT-CNN achieves the best performance when compared to state-of-the-art methods by explicitly modeling attributes. Impressively, a single model PAT-CNN achieves the best performance on the SFEW test dataset when compared to the state-of-the-art methods using an ensemble of hundreds of CNNs. [ABSTRACT FROM AUTHOR]

Permanent magnet (PM) machines with fractional slot concentrated windings (FSCW) constitute a notably remarkable proposition for electric vehicles. Additionally, an integrated onboard battery charger (IOBC) provides another superiority as it exploits the components of the powertrain to charge the battery without any additional components. Interior permanent magnet (IPM) motor arises as a credible choice due to its high torque density, resulting from the high saliency ratio. The optimal design of an IPM motor has been extensively presented from different perspectives, but the optimal design of a motor employed for IOBC application for both propulsion and charging modes has not been studied extensively. In this paper, the design and optimization of a 12-slot/10-pole IPM motor with IOBC are studied under both propulsion and charging modes. A finite-element-based optimization with the aid of a genetic algorithm technique is proposed to obtain the optimal machine by maximizing the average torque and minimizing the torque ripple, core losses, and magnet size. [ABSTRACT FROM AUTHOR]

Lysine succinylation is a kind of post-translational modification (PTM) that plays a crucial role in regulating the cellular processes. Aberrant succinylation may cause inflammation, cancers, metabolism diseases and nervous system diseases. The experimental methods to detect succinylation sites are time-consuming and costly. This thus calls for computational models with high efficacy, and attention has been given in the literature to develop such models, albeit with only moderate success in the context of different evaluation metrics. One crucial aspect in this context is the biochemical and physicochemical properties of amino acids, which appear to be useful as features for such computational predictors. However, some of the existing computational models did not use the biochemical and physicochemical properties of amino acids. In contrast, some others used them without considering the inter-dependency among the properties. The combinations of biochemical and physicochemical properties derived through our optimization process achieve better results than the results achieved by combining all the properties. We propose three deep learning architectures: CNN+Bi-LSTM (CBL), Bi-LSTM+CNN (BLC) and their combination (CBL_BLC). We find that CBL_BLC outperforms the other two. Ensembling of different models successfully improves the results. Notably, tuning the threshold of the ensemble classifiers further improves the results. Upon comparing our work with other existing works on two datasets, we successfully achieve better sensitivity and specificity by varying the threshold value. [ABSTRACT FROM AUTHOR]

Multiphase drives exhibit remarkable advantages (e.g., fault tolerance) over three-phase ones. Six-phase drives are particularly attractive, given their moderate complexity and suitability for off-the-shelf three-phase converters. Regarding the stator winding arrangement, the symmetrical one offers superior postfault capabilities in most scenarios. On the other hand, resistance asymmetry in the stator phases or connections may arise due to different causes. The conventional full-range minimum-loss strategy (FRMLS) generates stator-current references under open-phase (infinite resistance) faults so that torque ripple is prevented while minimizing the losses for each torque ($\boldsymbol{d}$ - $\boldsymbol{q}$ current) value and maximizing the torque range; however, this method is unsuitable for unequal resistances of finite value. This article proposes an FRMLS for setting the current references to reach these goals in symmetrical six-phase drives with any resistance asymmetry. The optimum references are found online depending on the resistances, without lookup tables. The phase currents are individually limited by an iterative algorithm, so that minimum stator copper loss (SCL) is achieved over the maximum admissible torque range. In this manner, unlike the conventional FRMLS, minimum SCL and maximum torque range are attained even for finite resistance imbalance. The currents in phases affected by high resistances are suitably reduced. Experimental results are provided. [ABSTRACT FROM AUTHOR]

Power converters generate switching common mode voltage (CMV) through the pulse width modulation (PWM). Several problems occur in the drive systems due to the generated CMV. These problems can be dangerous to the insulation and bearings of the electric machine windings. In recent years, many modulation methods have been developed to reduce the CMV in multiphase machines. Symmetrical nine-phase machines with single-neutral are considered in this paper. In this case, conventional PWM uses eight active vectors of different magnitudes in combination with two zero states in a switching cycle, and this generates maximum CMV. This paper proposes two PWM schemes to reduce the CMV in such a system. The first scheme is called active zero state (AZS). It replaces the zero vectors with suitable opposite active vectors. The second scheme uses ten large active vectors during switching and is called SVM-10L. Compared with conventional strategies, the AZS reduces the peak CMV by 22.2%, and the SVM-10L reduces the peak CMV by 88.8%. Moreover, this paper presents a carrier-based implementation of the proposed schemes to simplify the implementation. The proposed schemes are assessed using simulations and experimental studies for an induction motor load under different case studies. [ABSTRACT FROM AUTHOR]

Battery electric vehicles (BEVs) have started to play a significant role in the transport sector and automotive industries. The broader market penetration of BEVs has still not been achieved due to significant barriers associated with initial costs and short driving ranges. The purchase price and a limited driving range are barriers that are inevitably associated with battery technology. Therefore, the growing demand for BEVs has expedited new innovative approaches to improve battery capacity and performance and to reduce battery costs. Considerable advancements have been employed to meet the challenges. However, there are still many challenges to make BEVs affordable and convenient for users. In this review, the main aims are to identify and address challenges by considering the prospects of BEVs in the future market and to explore the technological and financial difficulties of low energy density of battery materials, fast charging rate, battery lifetime, and cost-effectiveness, associated with effectively implementing and adopting BEVs. Moreover, potential suggestions are proposed for researchers, manufacturers, users, and government policy planners. Finally, a concrete conclusion is drawn by disseminating a vision about the future adoption of BEVs. This review of technologies, challenges, prospects, and potential solutions associated with BEVs could provide a base for effective strategic policy and could help policymakers to frame strategies for adapting and achieving targets. This review could help to achieve sustainable BEV transport and to adopt next-generation green vehicles. [ABSTRACT FROM AUTHOR]

Half-crosses were used in this experiment to compare eight inbred lines in 2020 in the autumn and spring season. A randomized complete block design (RCBD) was used in this experiment. The results were significantly different in all traits. This is an indication of the different parental inbred lines involved in the hybridization. Inbred line (2) showed the highest mean in plant height, number of ears, and grains yield, while inbred line (1) showed the highest mean in days to 50% silking, Also, in the characteristic of 300 grain weight, the average was higher in inbred line (5) and in inbred line (8) in the number of grains as for cross (5x7), the highest in both characteristics, 300 grain weight and grains yield. Genetic analysis showed that results were highly significant for MS gca and MS sca for all the traits, as inbred line (5) had best effect of MS gca for inbred line on the number of grains amounted to 1.069 and 300 grain weight amounted to 1.131 and the grains yield per plant amounted to 4.790. Also, the hybrid (5x7) had the best effect of MS sca for grains yield per plant, as it reached 23.429. The variance ratio for gca and sca was less than one in all the studied traits in crosses. [ABSTRACT FROM AUTHOR]

This article presents a study on real-time testing of synchrophasor-based "wide-area monitoring system's applications (WAMS application)." Considering the growing demand of real-time testing of "wide-area monitoring, protection, and control (WAMPAC)" applications, a systematic real-time testing methodology is formulated and delineated in diagrams. The diagrams propose several stages through which an application needs to be assessed (sequentially) for its acceptance prior to implementation into a production system. However, only one stage is demonstrated in this article which comprises the use of a prototyping software toolchain and whose potential is assessed as sufficient for preliminary real-time testing (PRTT) of WAMS applications. The software toolchain is composed of two components: the MATLAB software for application prototyping and other open-source software that allows ingesting prerecorded phasor measurement unit (PMU) signals. With this software toolchain, a PRTT study is presented for two WAMS applications: "testing of the PMU/phasor data concentrator (PDC)" and "testing of wide-area forced oscillation (FO) monitoring application." [ABSTRACT FROM AUTHOR]

All proteomes contain both proteins and polypeptide segments that don't form a defined three-dimensional structure yet are biologically active—called intrinsically disordered proteins and regions (IDPs and IDRs). Most of these IDPs/IDRs lack useful functional annotation limiting our understanding of their importance for organism fitness. Here we characterized IDRs using protein sequence annotations of functional sites and regions available in the UniProt knowledgebase ("UniProt features": active site, ligand-binding pocket, regions mediating protein-protein interactions, etc.). By measuring the statistical enrichment of twenty-five UniProt features in 981 IDRs of 561 human proteins, we identified eight features that are commonly located in IDRs. We then collected the genetic variant data from the general population and patient-based databases and evaluated the prevalence of population and pathogenic variations in IDPs/IDRs. We observed that some IDRs tolerate 2 to 12-times more single amino acid-substituting missense mutations than synonymous changes in the general population. However, we also found that 37% of all germline pathogenic mutations are located in disordered regions of 96 proteins. Based on the observed-to-expected frequency of mutations, we categorized 34 IDRs in 20 proteins (DDX3X, KIT, RB1, etc.) as intolerant to mutation. Finally, using statistical analysis and a machine learning approach, we demonstrate that mutation-intolerant IDRs carry a distinct signature of functional features. Our study presents a novel approach to assign functional importance to IDRs by leveraging the wealth of available genetic data, which will aid in a deeper understating of the role of IDRs in biological processes and disease mechanisms. Author summary: Intrinsically disordered regions (IDRs) in proteins are typically not considered to be functionally as important as the structured parts. However, it is becoming evident that both structured and disordered regions are essential for the repertoire of protein functions. Nevertheless, most of these largely flexible and functionally dynamic protein regions remain uncharacterized. Nevertheless, most of these largely flexible and functionally dynamic protein regions remain uncharacterized. Here, informed by human genetic diversity (i.e., genetic variations from the general population and patients), we identified the IDRs that are more frequently mutated in patients than in relatively healthy individuals, and further show that they carry a set of characteristic functional features. This approach provides a different and effective means to identify unannotated disordered protein segments that are biologically important and lead to pathogenesis upon mutation. [ABSTRACT FROM AUTHOR]

Due to simplicity, efficiency, and the ability to accommodate energy storage devices, DC distribution networks have been seen as an optimal alternative to AC distribution networks, especially aboard future electric ships. The emerging distribution DC system entails new control and management techniques. Therefore, an integrated DC power distribution network aboard an electric ship is selected as the case study in this paper. To meet the requirements of such a large-scale mobile power system, a multiport solid-state transformer (SST) based on silicon carbide (SiC) switches/MOSFETs is proposed. Thus, the system embodiment can significantly be reduced. Moreover, at the DC distribution level, a high penetration of renewable generation with energy storage is allowed and a six-phase asymmetrical induction machine (IM) can directly be integrated. Simulations have been conducted based on a 2 MW shipboard distribution network. The effects of the propulsion system dynamics on the SST are highlighted as well. Finally, a 2 kW lab-scale prototype has been implemented to validate the theoretical findings. [ABSTRACT FROM AUTHOR]

The traditional neutral point clamped (NPC) inverter has short-circuit problem. The risk of short-circuit can be decreased by using dead-time in the switching signals. However, the dead-time decreases the achievable output voltage and causes distortion in the waveforms. To overcome the short-circuit problem, dual-buck NPC (DB-NPC) and split-inductor NPC (SI-NPC) inverters have been researched. However, the voltage stress of the two external diodes in the DB-NPC inverter is higher. On the other hand, the SI-NPC inverter has a problem of generating huge voltage spikes in the dead-time, which can destroy the semiconductor devices. In addition, the SI-NPC inverter cannot provide reactive power. This article presents a family of NPC inverters consisting of single-phase, three-phase, and cascaded inverters. The proposed inverters have no short-circuit and dead-time issues, therefore no high voltage and current spikes are caused. Also, the dead-time in the switching signals can be minimized. As a result, the magnitude of the output waveforms can be increased, and quality can be improved. Unlike the DB-NPC inverter, the voltage stress of all the semiconductor in the proposed inverter is lower, and unlike the SI-NPC inverter the proposed inverter provides reactive power. In this article, the proposed three-level NPC inverter is analyzed, designed, and tested. The voltage stress of the semiconductor devices in the proposed inverter is half of the source voltage, whereas in the conventional DB-NPC inverter the voltage stress of the two external diodes is the source voltage. In addition to the aforementioned benefits, the proposed cascaded inverter reduces the total number of inductors. To verify the analysis, detailed simulation, and experimental results of the proposed three-level inverter with input voltage 640 V, output power 1.2 kW, and output voltage 220 Vrms are provided. [ABSTRACT FROM AUTHOR]

The modular multilevel converter (MMC) is a promising candidate for high-/medium-voltage high-power applications such as medium voltage ac drives due to its modularity, reliability, and scalability. The main challenge of a conventional MMC is low-frequency operation. Capacitor voltage ripple is inversely proportional to the operating frequency. Hence, operating at low frequency necessitates employing large submodule capacitances to limit voltage ripple or the utilization of energy equalization modules (EEMs). The first option negatively affects converter lifetime, and the second option requires a large number of semiconductor devices and isolating transformers. In this article, a modified MMC topology with self-energy equalization is proposed to ensure converter operation with balanced capacitor voltages with low ripple during zero-/low-frequency conditions. Operating with balanced capacitor voltages with low ripple is achieved by maintaining the same energy level in the involved upper and lower arms. A low device count alternative to the EEMs approach is proposed in this work. Detailed illustration of the operational concept and design of the associated passive components is presented. The performance of the proposed medium voltage ac drive is elucidated through simulation and experimental results. [ABSTRACT FROM AUTHOR]

Permanent magnet machines (PMs) equipped with fractional slot concentrated windings (FSCWs) have been preferably proposed for electric vehicle (EV) applications. Moreover, integrated on-board battery chargers (OBCs), which employ the powertrain elements in the charging process, promote the zero-emission future envisaged for transportation through the transition to EVs. Based on the available literature, the employed machine, as well as the adopted winding configuration, highly affects the performance of the integrated OBC. However, the optimal design of the FSCW-based PM machine in the charging mode of operation has not been conceived thus far. In this paper, the design and multi-objective optimization of an asymmetrical 12-slot/10-pole integrated OBC based on the efficient magnetic equivalent circuit (MEC) approach are presented, shedding light on machine performance during charging mode. An 'initial' surface-mounted PM (SPM) machine is first designed based on the magnetic equivalent circuit (MEC) model. Afterwards, a multi-objective genetic algorithm is utilized to define the optimal machine parameters. Finally, the optimal machine is compared to the 'initial' design using finite element (FE) simulations in order to validate the proposed optimization approach and to highlight the performance superiority of the optimal machine over its initial counterpart. [ABSTRACT FROM AUTHOR]