This review paper examines the various types of electrical generators used to convert wave energy into electrical energy.The focus is on both linear and rotary generators,including their design principles,operational ...This review paper examines the various types of electrical generators used to convert wave energy into electrical energy.The focus is on both linear and rotary generators,including their design principles,operational efficiencies,and technological advancements.Linear generators,such as Induction,permanent magnet synchronous,and switched reluctance types,are highlighted for their direct conversion capability,eliminating the need for mechanical gearboxes.Rotary Induction generators,permanent magnet synchronous generators,and doubly-fed Induction generators are evaluated for their established engineering principles and integration with existing grid infrastructure.The paper discusses the historical development,environmental benefits,and ongoing advancements in wave energy technologies,emphasizing the increasing feasibility and scalability of wave energy as a renewable source.Through a comprehensive analysis,this review provides insights into the current state and future prospects of electrical generators in wave energy conversion,underscoring their potential to significantly reduce reliance on fossil fuels and mitigate environmental impacts.展开更多
Noise is inevitable in electrical capacitance tomography(ECT)measurements.This paper describes the influence of noise on ECT performance for measuring gas-solids fluidized bed characteristics.The noise distribution is...Noise is inevitable in electrical capacitance tomography(ECT)measurements.This paper describes the influence of noise on ECT performance for measuring gas-solids fluidized bed characteristics.The noise distribution is approximated by the Gaussian distribution and added to experimental capacitance data with various intensities.The equivalent signal strength(Ф)that equals the signal-to-noise ratio of packed beds is used to evaluate noise levels.Results show that the Pearson correlation coefficient,which indicates the similarity of solids fraction distributions over pixels,increases with Ф,and reconstructed images are more deteriorated at lower Ф.Nevertheless,relative errors for average solids fraction and bubble size in each frame are less sensitive to noise,attributed to noise compromise caused by the process of pixel values.These findings provide useful guidance for assessing the accuracy of ECT measurements of multiphase flows.展开更多
Ischemic stroke is a secondary cause of mortality worldwide,imposing considerable medical and economic burdens on society.Extracellular vesicles,serving as natural nanocarriers for drug delivery,exhibit excellent bioc...Ischemic stroke is a secondary cause of mortality worldwide,imposing considerable medical and economic burdens on society.Extracellular vesicles,serving as natural nanocarriers for drug delivery,exhibit excellent biocompatibility in vivo and have significant advantages in the management of ischemic stroke.However,the uncertain distribution and rapid clearance of extracellular vesicles impede their delivery efficiency.By utilizing membrane decoration or by encapsulating therapeutic cargo within extracellular vesicles,their delivery efficacy may be greatly improved.Furthermore,previous studies have indicated that microvesicles,a subset of large-sized extracellular vesicles,can transport mitochondria to neighboring cells,thereby aiding in the restoration of mitochondrial function post-ischemic stroke.Small extracellular vesicles have also demonstrated the capability to transfer mitochondrial components,such as proteins or deoxyribonucleic acid,or their sub-components,for extracellular vesicle-based ischemic stroke therapy.In this review,we undertake a comparative analysis of the isolation techniques employed for extracellular vesicles and present an overview of the current dominant extracellular vesicle modification methodologies.Given the complex facets of treating ischemic stroke,we also delineate various extracellular vesicle modification approaches which are suited to different facets of the treatment process.Moreover,given the burgeoning interest in mitochondrial delivery,we delved into the feasibility and existing research findings on the transportation of mitochondrial fractions or intact mitochondria through small extracellular vesicles and microvesicles to offer a fresh perspective on ischemic stroke therapy.展开更多
Graphene(Gr)has unique properties including high electrical conductivity;Thus,graphene/copper(Gr/Cu)composites have attracted increasing attention to replace traditional Cu for electrical applications. However,the pro...Graphene(Gr)has unique properties including high electrical conductivity;Thus,graphene/copper(Gr/Cu)composites have attracted increasing attention to replace traditional Cu for electrical applications. However,the problem of how to control graphene to form desired Gr/Cu composite is not well solved. This paper aims at exploring the best parameters for preparing graphene with different layers on Cu foil by chemical vapor deposition(CVD)method and studying the effects of different layers graphene on Gr/Cu composite’s electrical conductivity. Graphene grown on single-sided and double-sided copper was prepared for Gr/Cu and Gr/Cu/Gr composites. The resultant electrical conductivity of Gr/Cu composites increased with decreasing graphene layers and increasing graphene volume fraction. The Gr/Cu/Gr composite with monolayer graphene owns volume fraction of less than 0.002%,producing the best electrical conductivity up to59.8 ×10^(6)S/m,equivalent to 104.5% IACS and 105.3% pure Cu foil.展开更多
Supercapacitors are gaining popularity due to their high cycling stability,power density,and fast charge and discharge rates.Researchers are ex-ploring electrode materials,electrolytes,and separat-ors for cost-effecti...Supercapacitors are gaining popularity due to their high cycling stability,power density,and fast charge and discharge rates.Researchers are ex-ploring electrode materials,electrolytes,and separat-ors for cost-effective energy storage systems.Ad-vances in materials science have led to the develop-ment of hybrid nanomaterials,such as combining fil-amentous carbon forms with inorganic nanoparticles,to create new charge and energy transfer processes.Notable materials for electrochemical energy-stor-age applications include MXenes,2D transition met-al carbides,and nitrides,carbon black,carbon aerogels,activated carbon,carbon nanotubes,conducting polymers,carbon fibers,and nanofibers,and graphene,because of their thermal,electrical,and mechanical properties.Carbon materials mixed with conducting polymers,ceramics,metal oxides,transition metal oxides,metal hydroxides,transition metal sulfides,trans-ition metal dichalcogenide,metal sulfides,carbides,nitrides,and biomass materials have received widespread attention due to their remarkable performance,eco-friendliness,cost-effectiveness,and renewability.This article explores the development of carbon-based hybrid materials for future supercapacitors,including electric double-layer capacitors,pseudocapacitors,and hy-brid supercapacitors.It investigates the difficulties that influence structural design,manufacturing(electrospinning,hydro-thermal/solvothermal,template-assisted synthesis,electrodeposition,electrospray,3D printing)techniques and the latest car-bon-based hybrid materials research offer practical solutions for producing high-performance,next-generation supercapacitors.展开更多
The connection and interaction between the eye and the brain are crucial to understanding brain disorders(Marchesi et al.,2021).Both the eye and the brain have a limited regenerative capacity as there are few progenit...The connection and interaction between the eye and the brain are crucial to understanding brain disorders(Marchesi et al.,2021).Both the eye and the brain have a limited regenerative capacity as there are few progenitor cells,and nerve cells do not replicate.Hence,neurodegeneration implicates irreversible damage to the central nervous system,as observed in several neurodegenerative diseases(Marchesi et al.,2021).展开更多
This paper presents a design method to implement an antenna array characterized by ultra-wide beam coverage,low profile,and low Sidelobe Level(SLL)for the application of Unmanned Aerial Vehicle(UAV)air-to-ground commu...This paper presents a design method to implement an antenna array characterized by ultra-wide beam coverage,low profile,and low Sidelobe Level(SLL)for the application of Unmanned Aerial Vehicle(UAV)air-to-ground communication.The array consists of ten broadside-radiating,ultrawide-beamwidth elements that are cascaded by a central-symmetry series-fed network with tapered currents following Dolph-Chebyshev distribution to provide low SLL.First,an innovative design of end-fire Huygens source antenna that is compatible with metal ground is presented.A low-profile,half-mode Microstrip Patch Antenna(MPA)is utilized to serve as the magnetic dipole and a monopole is utilized to serves as the electric dipole,constructing the compact,end-fire,grounded Huygens source antenna.Then,two opposite-oriented end-fire Huygens source antennas are seamlessly integrated into a single antenna element in the form of monopole-loaded MPA to accomplish the ultrawide,broadside-radiating beam.Particular consideration has been applied into the design of series-fed network as well as antenna element to compensate the adverse coupling effects between elements on the radiation performance.Experiment indicates an ultrawide Half-Power Beamwidth(HPBW)of 161°and a low SLL of-25 dB with a high gain of 12 d Bi under a single-layer configuration.The concurrent ultrawide beamwidth and low SLL make it particularly attractive for applications of UAV air-to-ground communication.展开更多
Switched Reluctance Motors(SRMs),outfitted with rugged construction,good speed range,high torque density,and rare earth-free nature that outweigh induction motors(IM)and permanent magnet synchronous motor(PMSM),afford...Switched Reluctance Motors(SRMs),outfitted with rugged construction,good speed range,high torque density,and rare earth-free nature that outweigh induction motors(IM)and permanent magnet synchronous motor(PMSM),afford a broad range of applications in the domain of electric vehicles(EVs).Standard copper magnetic wire and low-carbon steel laminations are used to construct SRMs,which give them high efficiency in the range of 85-95%.Despite SRM's desirable features over traditional motor-speed drives,high torque ripples and radial distortions constrain their deployment in EVs.Precise rotor position is imperative for effective management of the speed and torque of SRMs.This paper provides an illustrative compendium on review of the torque-speed control and ripple mitigation techniques using design enhancements and control methods for SRM drives for EV applications.The various schemes were evaluated on their performance metricsoperational speed range,control complexity,practical realization,need for pre-stored parameters(look-up tables of current,inductance and torque profiles)and motor controller memory requirements.The findings provide valuable insights into balancing the gains and trade-offs associated with EV applications.Furthermore,they pinpoint opportunities for enhancement by analyzing the cost and technical aspects of different SRM controllers.展开更多
This study aims to evaluate the safety status of electrical installations in residential and commercial buildings within the Suame ECG strategic business unit, Ghana, focusing on compliance with international and Ghan...This study aims to evaluate the safety status of electrical installations in residential and commercial buildings within the Suame ECG strategic business unit, Ghana, focusing on compliance with international and Ghanaian wiring standards. The research assesses key factors influencing safety, including the certification of electricians, the quality of cable brands used, proper cable sizing, adherence to wiring color codes, the awareness and use of Residual Current Circuit Breakers (RCCBs), and the protection of earth electrodes. A descriptive research design was utilized, involving extensive field surveys and electrical installation audits. Data were collected using standardized tools and analyzed with SPSS software to evaluate the professional competencies of artisans and their adherence to safety standards. The findings indicate significant safety risks, with 69.7% of electricians lacking proper certification, leading to the widespread use of non-approved cable brands, improper cable sizing, and deviations from wiring color codes. Additionally, deficiencies were found in the awareness and use of RCCBs and the protection of earth electrodes. The study concludes with recommendations to enhance electrical safety, including mandatory certification for electricians, public awareness campaigns, regular inspections, and ongoing training and development programs. These measures are crucial for improving the overall safety and quality of electrical installations in the Suame area, Ghana.展开更多
The burgeoning market for lithium-ion batteries has stimulated a growing need for more reliable battery performance monitoring. Accurate state-of-health(SOH) estimation is critical for ensuring battery operational per...The burgeoning market for lithium-ion batteries has stimulated a growing need for more reliable battery performance monitoring. Accurate state-of-health(SOH) estimation is critical for ensuring battery operational performance. Despite numerous data-driven methods reported in existing research for battery SOH estimation, these methods often exhibit inconsistent performance across different application scenarios. To address this issue and overcome the performance limitations of individual data-driven models,integrating multiple models for SOH estimation has received considerable attention. Ensemble learning(EL) typically leverages the strengths of multiple base models to achieve more robust and accurate outputs. However, the lack of a clear review of current research hinders the further development of ensemble methods in SOH estimation. Therefore, this paper comprehensively reviews multi-model ensemble learning methods for battery SOH estimation. First, existing ensemble methods are systematically categorized into 6 classes based on their combination strategies. Different realizations and underlying connections are meticulously analyzed for each category of EL methods, highlighting distinctions, innovations, and typical applications. Subsequently, these ensemble methods are comprehensively compared in terms of base models, combination strategies, and publication trends. Evaluations across 6 dimensions underscore the outstanding performance of stacking-based ensemble methods. Following this, these ensemble methods are further inspected from the perspectives of weighted ensemble and diversity, aiming to inspire potential approaches for enhancing ensemble performance. Moreover, addressing challenges such as base model selection, measuring model robustness and uncertainty, and interpretability of ensemble models in practical applications is emphasized. Finally, future research prospects are outlined, specifically noting that deep learning ensemble is poised to advance ensemble methods for battery SOH estimation. The convergence of advanced machine learning with ensemble learning is anticipated to yield valuable avenues for research. Accelerated research in ensemble learning holds promising prospects for achieving more accurate and reliable battery SOH estimation under real-world conditions.展开更多
Transformer models have emerged as pivotal tools within the realm of drug discovery,distinguished by their unique architectural features and exceptional performance in managing intricate data landscapes.Leveraging the...Transformer models have emerged as pivotal tools within the realm of drug discovery,distinguished by their unique architectural features and exceptional performance in managing intricate data landscapes.Leveraging the innate capabilities of transformer architectures to comprehend intricate hierarchical dependencies inherent in sequential data,these models showcase remarkable efficacy across various tasks,including new drug design and drug target identification.The adaptability of pre-trained trans-former-based models renders them indispensable assets for driving data-centric advancements in drug discovery,chemistry,and biology,furnishing a robust framework that expedites innovation and dis-covery within these domains.Beyond their technical prowess,the success of transformer-based models in drug discovery,chemistry,and biology extends to their interdisciplinary potential,seamlessly combining biological,physical,chemical,and pharmacological insights to bridge gaps across diverse disciplines.This integrative approach not only enhances the depth and breadth of research endeavors but also fosters synergistic collaborations and exchange of ideas among disparate fields.In our review,we elucidate the myriad applications of transformers in drug discovery,as well as chemistry and biology,spanning from protein design and protein engineering,to molecular dynamics(MD),drug target iden-tification,transformer-enabled drug virtual screening(VS),drug lead optimization,drug addiction,small data set challenges,chemical and biological image analysis,chemical language understanding,and single cell data.Finally,we conclude the survey by deliberating on promising trends in transformer models within the context of drug discovery and other sciences.展开更多
Recycling plastic waste into triboelectric nanogenerators(TENGs)presents a sustainable approach to energy harvesting,self-powered sensing,and environmental remediation.This study investigates the recycling of polyviny...Recycling plastic waste into triboelectric nanogenerators(TENGs)presents a sustainable approach to energy harvesting,self-powered sensing,and environmental remediation.This study investigates the recycling of polyvinyl chloride(PVC)pipe waste polymers into nanofibers(NFs)optimized for TENG applications.We focused on optimizing the morphology of recycled PVC polymer to NFs and enhancing their piezoelectric properties by incorporating ZnO nanoparticles(NPs).The optimized PVC/0.5 wt%ZnO NFs were tested with Nylon-6 NFs,and copper(Cu)electrodes.The Nylon-6 NFs exhibited a power density of 726.3μWcm^(-2)—1.13 times higher than Cu and maintained 90%stability after 172800 cycles,successfully powering various colored LEDs.Additionally,a 3D-designed device was developed to harvest energy from biomechanical movements such as finger tapping,hand tapping,and foot pressing,making it suitable for wearable energy harvesting,automatic switches,and invisible sensors in surveillance systems.This study demonstrates that recycling polymers for TENG devices can effectively address energy,sensor,and environmental challenges.展开更多
Software-related security aspects are a growing and legitimate concern,especially with 5G data available just at our palms.To conduct research in this field,periodic comparative analysis is needed with the new techniq...Software-related security aspects are a growing and legitimate concern,especially with 5G data available just at our palms.To conduct research in this field,periodic comparative analysis is needed with the new techniques coming up rapidly.The purpose of this study is to review the recent developments in the field of security integration in the software development lifecycle(SDLC)by analyzing the articles published in the last two decades and to propose a way forward.This review follows Kitchenham’s review protocol.The review has been divided into three main stages including planning,execution,and analysis.From the selected 100 articles,it becomes evident that need of a collaborative approach is necessary for addressing critical software security risks(CSSRs)through effective risk management/estimation techniques.Quantifying risks using a numeric scale enables a comprehensive understanding of their severity,facilitating focused resource allocation and mitigation efforts.Through a comprehensive understanding of potential vulnerabilities and proactive mitigation efforts facilitated by protection poker,organizations can prioritize resources effectively to ensure the successful outcome of projects and initiatives in today’s dynamic threat landscape.The review reveals that threat analysis and security testing are needed to develop automated tools for the future.Accurate estimation of effort required to prioritize potential security risks is a big challenge in software security.The accuracy of effort estimation can be further improved by exploring new techniques,particularly those involving deep learning.It is also imperative to validate these effort estimation methods to ensure all potential security threats are addressed.Another challenge is selecting the right model for each specific security threat.To achieve a comprehensive evaluation,researchers should use well-known benchmark checklists.展开更多
Traffic forecasting with high precision aids Intelligent Transport Systems(ITS)in formulating and optimizing traffic management strategies.The algorithms used for tuning the hyperparameters of the deep learning models...Traffic forecasting with high precision aids Intelligent Transport Systems(ITS)in formulating and optimizing traffic management strategies.The algorithms used for tuning the hyperparameters of the deep learning models often have accurate results at the expense of high computational complexity.To address this problem,this paper uses the Tree-structured Parzen Estimator(TPE)to tune the hyperparameters of the Long Short-term Memory(LSTM)deep learning framework.The Tree-structured Parzen Estimator(TPE)uses a probabilistic approach with an adaptive searching mechanism by classifying the objective function values into good and bad samples.This ensures fast convergence in tuning the hyperparameter values in the deep learning model for performing prediction while still maintaining a certain degree of accuracy.It also overcomes the problem of converging to local optima and avoids timeconsuming random search and,therefore,avoids high computational complexity in prediction accuracy.The proposed scheme first performs data smoothing and normalization on the input data,which is then fed to the input of the TPE for tuning the hyperparameters.The traffic data is then input to the LSTM model with tuned parameters to perform the traffic prediction.The three optimizers:Adaptive Moment Estimation(Adam),Root Mean Square Propagation(RMSProp),and Stochastic Gradient Descend with Momentum(SGDM)are also evaluated for accuracy prediction and the best optimizer is then chosen for final traffic prediction in TPE-LSTM model.Simulation results verify the effectiveness of the proposed model in terms of accuracy of prediction over the benchmark schemes.展开更多
This study introduces a comprehensive theoretical framework for accurately calculating the electronic band-structure of strained long-wavelength InAs/GaSb type-Ⅱsuperlattices.Utilizing an eight-band k·p Hamilto⁃...This study introduces a comprehensive theoretical framework for accurately calculating the electronic band-structure of strained long-wavelength InAs/GaSb type-Ⅱsuperlattices.Utilizing an eight-band k·p Hamilto⁃nian in conjunction with a scattering matrix method,the model effectively incorporates quantum confinement,strain effects,and interface states.This robust and numerically stable approach achieves exceptional agreement with experimental data,offering a reliable tool for analyzing and engineering the band structure of complex multi⁃layer systems.展开更多
The purpose of this review is to explore the intersection of computational engineering and biomedical science,highlighting the transformative potential this convergence holds for innovation in healthcare and medical r...The purpose of this review is to explore the intersection of computational engineering and biomedical science,highlighting the transformative potential this convergence holds for innovation in healthcare and medical research.The review covers key topics such as computational modelling,bioinformatics,machine learning in medical diagnostics,and the integration of wearable technology for real-time health monitoring.Major findings indicate that computational models have significantly enhanced the understanding of complex biological systems,while machine learning algorithms have improved the accuracy of disease prediction and diagnosis.The synergy between bioinformatics and computational techniques has led to breakthroughs in personalized medicine,enabling more precise treatment strategies.Additionally,the integration of wearable devices with advanced computational methods has opened new avenues for continuous health monitoring and early disease detection.The review emphasizes the need for interdisciplinary collaboration to further advance this field.Future research should focus on developing more robust and scalable computational models,enhancing data integration techniques,and addressing ethical considerations related to data privacy and security.By fostering innovation at the intersection of these disciplines,the potential to revolutionize healthcare delivery and outcomes becomes increasingly attainable.展开更多
In this study,we design and numerically investigate a novel all optical D flip-flop(AODFF)based on linear photonic crystal(LPhC)structure that is composed of optical waveguides using the finite difference time domain(...In this study,we design and numerically investigate a novel all optical D flip-flop(AODFF)based on linear photonic crystal(LPhC)structure that is composed of optical waveguides using the finite difference time domain(FDTD)method.The proposed structure has the hexagonal close packed of 16×20 circular rods that are suspended in the air substrate with a lattice constant of 606 nm.The plane wave expansion(PWE)method is used to obtain the band diagram for AODFF at an operating wavelength of 1550 nm.The proposed optical flip-flop achieves a low delay time of 0.2 ps and a high contrast ratio(CR)of 10.33 dB.The main advantage of this design is that the input power as low as 1 mW/μm^(2) is sufficient for its operation,since no nonlinear rods are included.In addition,the footprint of the proposed AODFF is 100μm^(2),which is smaller compared to the structures reported in the literature,and it has a fast switching frequency of 5 Tbit/s.展开更多
As organic thin film transistors(OTFTs)are set to play a crucial role in flexible and cost-effective electronic applica-tions,this paper investigates a high-mobility 6,13-bis(triisopropylsilylethynyl)pentacene(TIPS-pe...As organic thin film transistors(OTFTs)are set to play a crucial role in flexible and cost-effective electronic applica-tions,this paper investigates a high-mobility 6,13-bis(triisopropylsilylethynyl)pentacene(TIPS-pentacene)OTFT for use in flexi-ble electronics.The development of such high-mobility devices necessitates precise device modeling to support technology opti-misation and circuit design.The details of numerical simulation technique is discussed,in which,the electrical behavior of the device is well captured by fine tuning basic semiconductor equations.This technology computer-aided design(TCAD)has been validated with exprimental data.In addition,we have discussed about compact model fitting of the devices as well as parameter extraction procedure employed.This includes verification of Silvaco ATLAS finite element method(FEM)based results against experimental data gained from fabricated OTFT devices.Simulations for p-type TFT-based inverter are also per-formed to assess the performance of compact model in simple circuit simulation.展开更多
In recent years,carbon nanotube field effect transistor(CNTFET)has become an attractive alternative to silicon for designing high-performance,highly stable,and low-power static random access memory(SRAM).SRAM serves a...In recent years,carbon nanotube field effect transistor(CNTFET)has become an attractive alternative to silicon for designing high-performance,highly stable,and low-power static random access memory(SRAM).SRAM serves as a cache memory in computers and many portable devices.Carbon nanotubes(CNTs),because of their exceptional transport capabilities,outstanding thermal conductivities,and impressive current handling capacities,have demonstrated great potential as an alternative device to the standard complementary metal-oxide-semiconductor(CMOS).The SRAM cell design using CNTFET is being compared to SRAM cell designs built using traditional CMOS technology.This paper presents the comprehensive analysis of CMOS&CNTFET based 8T SRAM cell design.Because of the nanoscale size,ballistic transport,and higher carrier mobility of the semiconducting nanotubes in CNTFET,it is integrated into the 8T SRAM cell.The approach incorporates several nonidealities,including the presence of quantum confinement consequences in the peripheral and transverse prescriptions,acoustic and transparent photon diffraction in the region surrounding the channel,as well as the screening effects by parallel CNTs in CNTFETs with multiple CNTs.By incorporating Stanford University CNTFET model in CADENCE(virtuoso)32 nm simulation,we have found that CNTFET SRAM cell is 4 times faster in terms of write/read delay and the write/read power delay product(PDP)value is almost 5 times lower compared to CMOS based SRAM.We have also analyzed the effect of temperature&different tube positions of CNTs on the performance evaluation of the 8T SRAM cell.展开更多
The global rise in energy demand, particularly in remote and sparsely populated regions, necessitates innovative and cost-effective electrical distribution solutions. Traditional Rural Electrification (RE) methods, li...The global rise in energy demand, particularly in remote and sparsely populated regions, necessitates innovative and cost-effective electrical distribution solutions. Traditional Rural Electrification (RE) methods, like Conventional Rural Electrification (CRE), have proven economically unfeasible in such areas due to high infrastructure costs and low electricity demand. Consequently, Unconventional Rural Electrification (URE) technologies, such as Capacitor Coupled Substations (CCS), are gaining attention as viable alternatives. This study presents the design and simulation of an 80 kW CCS system, which taps power directly from a 132 kV transmission line to supply low-voltage consumers. The critical components of the CCS, the capacitors are calculated, then a MATLAB/Simulink model with the attained results is executed. Mathematical representation and state-space representation for maintaining the desired tapped voltage area also developed. The research further explores the feasibility and operational performance of this CCS configuration, aiming to address the challenges of rural electrification by offering a sustainable and scalable solution. The results show that the desired value of the tapped voltage can be achieved at any level of High Voltage (HV) with the selection of capacitors that are correctly rated. With an adequately designed control strategy, the research also shows that tapped voltage can be attained under both steady-state and dynamic loads. By leveraging CCS technology, the study demonstrates the potential for delivering reliable electricity to underserved areas, highlighting the system’s practicality and effectiveness in overcoming the limitations of conventional distribution methods.展开更多
文摘This review paper examines the various types of electrical generators used to convert wave energy into electrical energy.The focus is on both linear and rotary generators,including their design principles,operational efficiencies,and technological advancements.Linear generators,such as Induction,permanent magnet synchronous,and switched reluctance types,are highlighted for their direct conversion capability,eliminating the need for mechanical gearboxes.Rotary Induction generators,permanent magnet synchronous generators,and doubly-fed Induction generators are evaluated for their established engineering principles and integration with existing grid infrastructure.The paper discusses the historical development,environmental benefits,and ongoing advancements in wave energy technologies,emphasizing the increasing feasibility and scalability of wave energy as a renewable source.Through a comprehensive analysis,this review provides insights into the current state and future prospects of electrical generators in wave energy conversion,underscoring their potential to significantly reduce reliance on fossil fuels and mitigate environmental impacts.
基金National Key Research and Development Program of China(2021YFA1501302)the National Natural Science Foundation of China(22121004,22122808)+1 种基金the Haihe Laboratory of Sustainable Chemical Transformations and the Program of Introducing Talents of Discipline to Universities(BP0618007)for financial supportsupported by the XPLORER PRIZE.
文摘Noise is inevitable in electrical capacitance tomography(ECT)measurements.This paper describes the influence of noise on ECT performance for measuring gas-solids fluidized bed characteristics.The noise distribution is approximated by the Gaussian distribution and added to experimental capacitance data with various intensities.The equivalent signal strength(Ф)that equals the signal-to-noise ratio of packed beds is used to evaluate noise levels.Results show that the Pearson correlation coefficient,which indicates the similarity of solids fraction distributions over pixels,increases with Ф,and reconstructed images are more deteriorated at lower Ф.Nevertheless,relative errors for average solids fraction and bubble size in each frame are less sensitive to noise,attributed to noise compromise caused by the process of pixel values.These findings provide useful guidance for assessing the accuracy of ECT measurements of multiphase flows.
基金supported by the grants from University of Macao,China,Nos.MYRG2022-00221-ICMS(to YZ)and MYRG-CRG2022-00011-ICMS(to RW)the Natural Science Foundation of Guangdong Province,No.2023A1515010034(to YZ)。
文摘Ischemic stroke is a secondary cause of mortality worldwide,imposing considerable medical and economic burdens on society.Extracellular vesicles,serving as natural nanocarriers for drug delivery,exhibit excellent biocompatibility in vivo and have significant advantages in the management of ischemic stroke.However,the uncertain distribution and rapid clearance of extracellular vesicles impede their delivery efficiency.By utilizing membrane decoration or by encapsulating therapeutic cargo within extracellular vesicles,their delivery efficacy may be greatly improved.Furthermore,previous studies have indicated that microvesicles,a subset of large-sized extracellular vesicles,can transport mitochondria to neighboring cells,thereby aiding in the restoration of mitochondrial function post-ischemic stroke.Small extracellular vesicles have also demonstrated the capability to transfer mitochondrial components,such as proteins or deoxyribonucleic acid,or their sub-components,for extracellular vesicle-based ischemic stroke therapy.In this review,we undertake a comparative analysis of the isolation techniques employed for extracellular vesicles and present an overview of the current dominant extracellular vesicle modification methodologies.Given the complex facets of treating ischemic stroke,we also delineate various extracellular vesicle modification approaches which are suited to different facets of the treatment process.Moreover,given the burgeoning interest in mitochondrial delivery,we delved into the feasibility and existing research findings on the transportation of mitochondrial fractions or intact mitochondria through small extracellular vesicles and microvesicles to offer a fresh perspective on ischemic stroke therapy.
基金supported substantially by the Southwest Jiaotong University for Material and Financial Support。
文摘Graphene(Gr)has unique properties including high electrical conductivity;Thus,graphene/copper(Gr/Cu)composites have attracted increasing attention to replace traditional Cu for electrical applications. However,the problem of how to control graphene to form desired Gr/Cu composite is not well solved. This paper aims at exploring the best parameters for preparing graphene with different layers on Cu foil by chemical vapor deposition(CVD)method and studying the effects of different layers graphene on Gr/Cu composite’s electrical conductivity. Graphene grown on single-sided and double-sided copper was prepared for Gr/Cu and Gr/Cu/Gr composites. The resultant electrical conductivity of Gr/Cu composites increased with decreasing graphene layers and increasing graphene volume fraction. The Gr/Cu/Gr composite with monolayer graphene owns volume fraction of less than 0.002%,producing the best electrical conductivity up to59.8 ×10^(6)S/m,equivalent to 104.5% IACS and 105.3% pure Cu foil.
文摘Supercapacitors are gaining popularity due to their high cycling stability,power density,and fast charge and discharge rates.Researchers are ex-ploring electrode materials,electrolytes,and separat-ors for cost-effective energy storage systems.Ad-vances in materials science have led to the develop-ment of hybrid nanomaterials,such as combining fil-amentous carbon forms with inorganic nanoparticles,to create new charge and energy transfer processes.Notable materials for electrochemical energy-stor-age applications include MXenes,2D transition met-al carbides,and nitrides,carbon black,carbon aerogels,activated carbon,carbon nanotubes,conducting polymers,carbon fibers,and nanofibers,and graphene,because of their thermal,electrical,and mechanical properties.Carbon materials mixed with conducting polymers,ceramics,metal oxides,transition metal oxides,metal hydroxides,transition metal sulfides,trans-ition metal dichalcogenide,metal sulfides,carbides,nitrides,and biomass materials have received widespread attention due to their remarkable performance,eco-friendliness,cost-effectiveness,and renewability.This article explores the development of carbon-based hybrid materials for future supercapacitors,including electric double-layer capacitors,pseudocapacitors,and hy-brid supercapacitors.It investigates the difficulties that influence structural design,manufacturing(electrospinning,hydro-thermal/solvothermal,template-assisted synthesis,electrodeposition,electrospray,3D printing)techniques and the latest car-bon-based hybrid materials research offer practical solutions for producing high-performance,next-generation supercapacitors.
基金supported by grants from City University of Hong Kong,China (Project No.SRG-Fd7005632,SRG-Fd 7005854SIRG 7020058)(to LLHC)。
文摘The connection and interaction between the eye and the brain are crucial to understanding brain disorders(Marchesi et al.,2021).Both the eye and the brain have a limited regenerative capacity as there are few progenitor cells,and nerve cells do not replicate.Hence,neurodegeneration implicates irreversible damage to the central nervous system,as observed in several neurodegenerative diseases(Marchesi et al.,2021).
基金supported by the National Natural Science Foundation of China(No.62371080 and 62031006)the National Science Foundation of Chongqing,China(No.CSTB2022NSCQ-MSX0597)the Venture&Innovation Support Program for Chongqing Overseas Returnees,China(No.cx2022063)。
文摘This paper presents a design method to implement an antenna array characterized by ultra-wide beam coverage,low profile,and low Sidelobe Level(SLL)for the application of Unmanned Aerial Vehicle(UAV)air-to-ground communication.The array consists of ten broadside-radiating,ultrawide-beamwidth elements that are cascaded by a central-symmetry series-fed network with tapered currents following Dolph-Chebyshev distribution to provide low SLL.First,an innovative design of end-fire Huygens source antenna that is compatible with metal ground is presented.A low-profile,half-mode Microstrip Patch Antenna(MPA)is utilized to serve as the magnetic dipole and a monopole is utilized to serves as the electric dipole,constructing the compact,end-fire,grounded Huygens source antenna.Then,two opposite-oriented end-fire Huygens source antennas are seamlessly integrated into a single antenna element in the form of monopole-loaded MPA to accomplish the ultrawide,broadside-radiating beam.Particular consideration has been applied into the design of series-fed network as well as antenna element to compensate the adverse coupling effects between elements on the radiation performance.Experiment indicates an ultrawide Half-Power Beamwidth(HPBW)of 161°and a low SLL of-25 dB with a high gain of 12 d Bi under a single-layer configuration.The concurrent ultrawide beamwidth and low SLL make it particularly attractive for applications of UAV air-to-ground communication.
基金supported in part by the Universitat Politècnica de València under grant PAID-10-21supported through AMRITA Seed Grant(Proposal ID:ASG2022188)。
文摘Switched Reluctance Motors(SRMs),outfitted with rugged construction,good speed range,high torque density,and rare earth-free nature that outweigh induction motors(IM)and permanent magnet synchronous motor(PMSM),afford a broad range of applications in the domain of electric vehicles(EVs).Standard copper magnetic wire and low-carbon steel laminations are used to construct SRMs,which give them high efficiency in the range of 85-95%.Despite SRM's desirable features over traditional motor-speed drives,high torque ripples and radial distortions constrain their deployment in EVs.Precise rotor position is imperative for effective management of the speed and torque of SRMs.This paper provides an illustrative compendium on review of the torque-speed control and ripple mitigation techniques using design enhancements and control methods for SRM drives for EV applications.The various schemes were evaluated on their performance metricsoperational speed range,control complexity,practical realization,need for pre-stored parameters(look-up tables of current,inductance and torque profiles)and motor controller memory requirements.The findings provide valuable insights into balancing the gains and trade-offs associated with EV applications.Furthermore,they pinpoint opportunities for enhancement by analyzing the cost and technical aspects of different SRM controllers.
文摘This study aims to evaluate the safety status of electrical installations in residential and commercial buildings within the Suame ECG strategic business unit, Ghana, focusing on compliance with international and Ghanaian wiring standards. The research assesses key factors influencing safety, including the certification of electricians, the quality of cable brands used, proper cable sizing, adherence to wiring color codes, the awareness and use of Residual Current Circuit Breakers (RCCBs), and the protection of earth electrodes. A descriptive research design was utilized, involving extensive field surveys and electrical installation audits. Data were collected using standardized tools and analyzed with SPSS software to evaluate the professional competencies of artisans and their adherence to safety standards. The findings indicate significant safety risks, with 69.7% of electricians lacking proper certification, leading to the widespread use of non-approved cable brands, improper cable sizing, and deviations from wiring color codes. Additionally, deficiencies were found in the awareness and use of RCCBs and the protection of earth electrodes. The study concludes with recommendations to enhance electrical safety, including mandatory certification for electricians, public awareness campaigns, regular inspections, and ongoing training and development programs. These measures are crucial for improving the overall safety and quality of electrical installations in the Suame area, Ghana.
基金National Natural Science Foundation of China (52075420)Fundamental Research Funds for the Central Universities (xzy022023049)National Key Research and Development Program of China (2023YFB3408600)。
文摘The burgeoning market for lithium-ion batteries has stimulated a growing need for more reliable battery performance monitoring. Accurate state-of-health(SOH) estimation is critical for ensuring battery operational performance. Despite numerous data-driven methods reported in existing research for battery SOH estimation, these methods often exhibit inconsistent performance across different application scenarios. To address this issue and overcome the performance limitations of individual data-driven models,integrating multiple models for SOH estimation has received considerable attention. Ensemble learning(EL) typically leverages the strengths of multiple base models to achieve more robust and accurate outputs. However, the lack of a clear review of current research hinders the further development of ensemble methods in SOH estimation. Therefore, this paper comprehensively reviews multi-model ensemble learning methods for battery SOH estimation. First, existing ensemble methods are systematically categorized into 6 classes based on their combination strategies. Different realizations and underlying connections are meticulously analyzed for each category of EL methods, highlighting distinctions, innovations, and typical applications. Subsequently, these ensemble methods are comprehensively compared in terms of base models, combination strategies, and publication trends. Evaluations across 6 dimensions underscore the outstanding performance of stacking-based ensemble methods. Following this, these ensemble methods are further inspected from the perspectives of weighted ensemble and diversity, aiming to inspire potential approaches for enhancing ensemble performance. Moreover, addressing challenges such as base model selection, measuring model robustness and uncertainty, and interpretability of ensemble models in practical applications is emphasized. Finally, future research prospects are outlined, specifically noting that deep learning ensemble is poised to advance ensemble methods for battery SOH estimation. The convergence of advanced machine learning with ensemble learning is anticipated to yield valuable avenues for research. Accelerated research in ensemble learning holds promising prospects for achieving more accurate and reliable battery SOH estimation under real-world conditions.
基金supported in part by National Institute of Health(NIH),USA(Grant Nos.:R01GM126189,R01AI164266,and R35GM148196)the National Science Foundation,USA(Grant Nos.DMS2052983,DMS-1761320,and IIS-1900473)+3 种基金National Aero-nautics and Space Administration(NASA),USA(Grant No.:80NSSC21M0023)Michigan State University(MSU)Foundation,USA,Bristol-Myers Squibb(Grant No.:65109)USA,and Pfizer,USAsupported by the National Natural Science Foundation of China(Grant Nos.:11971367,12271416,and 11972266).
文摘Transformer models have emerged as pivotal tools within the realm of drug discovery,distinguished by their unique architectural features and exceptional performance in managing intricate data landscapes.Leveraging the innate capabilities of transformer architectures to comprehend intricate hierarchical dependencies inherent in sequential data,these models showcase remarkable efficacy across various tasks,including new drug design and drug target identification.The adaptability of pre-trained trans-former-based models renders them indispensable assets for driving data-centric advancements in drug discovery,chemistry,and biology,furnishing a robust framework that expedites innovation and dis-covery within these domains.Beyond their technical prowess,the success of transformer-based models in drug discovery,chemistry,and biology extends to their interdisciplinary potential,seamlessly combining biological,physical,chemical,and pharmacological insights to bridge gaps across diverse disciplines.This integrative approach not only enhances the depth and breadth of research endeavors but also fosters synergistic collaborations and exchange of ideas among disparate fields.In our review,we elucidate the myriad applications of transformers in drug discovery,as well as chemistry and biology,spanning from protein design and protein engineering,to molecular dynamics(MD),drug target iden-tification,transformer-enabled drug virtual screening(VS),drug lead optimization,drug addiction,small data set challenges,chemical and biological image analysis,chemical language understanding,and single cell data.Finally,we conclude the survey by deliberating on promising trends in transformer models within the context of drug discovery and other sciences.
基金supported by the research projects AP23486880 from the Ministry of Higher EducationScience of the Republic of Kazakhstan and 111024CRP2010,20122022FD4135 from Nazarbayev University.
文摘Recycling plastic waste into triboelectric nanogenerators(TENGs)presents a sustainable approach to energy harvesting,self-powered sensing,and environmental remediation.This study investigates the recycling of polyvinyl chloride(PVC)pipe waste polymers into nanofibers(NFs)optimized for TENG applications.We focused on optimizing the morphology of recycled PVC polymer to NFs and enhancing their piezoelectric properties by incorporating ZnO nanoparticles(NPs).The optimized PVC/0.5 wt%ZnO NFs were tested with Nylon-6 NFs,and copper(Cu)electrodes.The Nylon-6 NFs exhibited a power density of 726.3μWcm^(-2)—1.13 times higher than Cu and maintained 90%stability after 172800 cycles,successfully powering various colored LEDs.Additionally,a 3D-designed device was developed to harvest energy from biomechanical movements such as finger tapping,hand tapping,and foot pressing,making it suitable for wearable energy harvesting,automatic switches,and invisible sensors in surveillance systems.This study demonstrates that recycling polymers for TENG devices can effectively address energy,sensor,and environmental challenges.
文摘Software-related security aspects are a growing and legitimate concern,especially with 5G data available just at our palms.To conduct research in this field,periodic comparative analysis is needed with the new techniques coming up rapidly.The purpose of this study is to review the recent developments in the field of security integration in the software development lifecycle(SDLC)by analyzing the articles published in the last two decades and to propose a way forward.This review follows Kitchenham’s review protocol.The review has been divided into three main stages including planning,execution,and analysis.From the selected 100 articles,it becomes evident that need of a collaborative approach is necessary for addressing critical software security risks(CSSRs)through effective risk management/estimation techniques.Quantifying risks using a numeric scale enables a comprehensive understanding of their severity,facilitating focused resource allocation and mitigation efforts.Through a comprehensive understanding of potential vulnerabilities and proactive mitigation efforts facilitated by protection poker,organizations can prioritize resources effectively to ensure the successful outcome of projects and initiatives in today’s dynamic threat landscape.The review reveals that threat analysis and security testing are needed to develop automated tools for the future.Accurate estimation of effort required to prioritize potential security risks is a big challenge in software security.The accuracy of effort estimation can be further improved by exploring new techniques,particularly those involving deep learning.It is also imperative to validate these effort estimation methods to ensure all potential security threats are addressed.Another challenge is selecting the right model for each specific security threat.To achieve a comprehensive evaluation,researchers should use well-known benchmark checklists.
文摘Traffic forecasting with high precision aids Intelligent Transport Systems(ITS)in formulating and optimizing traffic management strategies.The algorithms used for tuning the hyperparameters of the deep learning models often have accurate results at the expense of high computational complexity.To address this problem,this paper uses the Tree-structured Parzen Estimator(TPE)to tune the hyperparameters of the Long Short-term Memory(LSTM)deep learning framework.The Tree-structured Parzen Estimator(TPE)uses a probabilistic approach with an adaptive searching mechanism by classifying the objective function values into good and bad samples.This ensures fast convergence in tuning the hyperparameter values in the deep learning model for performing prediction while still maintaining a certain degree of accuracy.It also overcomes the problem of converging to local optima and avoids timeconsuming random search and,therefore,avoids high computational complexity in prediction accuracy.The proposed scheme first performs data smoothing and normalization on the input data,which is then fed to the input of the TPE for tuning the hyperparameters.The traffic data is then input to the LSTM model with tuned parameters to perform the traffic prediction.The three optimizers:Adaptive Moment Estimation(Adam),Root Mean Square Propagation(RMSProp),and Stochastic Gradient Descend with Momentum(SGDM)are also evaluated for accuracy prediction and the best optimizer is then chosen for final traffic prediction in TPE-LSTM model.Simulation results verify the effectiveness of the proposed model in terms of accuracy of prediction over the benchmark schemes.
文摘This study introduces a comprehensive theoretical framework for accurately calculating the electronic band-structure of strained long-wavelength InAs/GaSb type-Ⅱsuperlattices.Utilizing an eight-band k·p Hamilto⁃nian in conjunction with a scattering matrix method,the model effectively incorporates quantum confinement,strain effects,and interface states.This robust and numerically stable approach achieves exceptional agreement with experimental data,offering a reliable tool for analyzing and engineering the band structure of complex multi⁃layer systems.
文摘The purpose of this review is to explore the intersection of computational engineering and biomedical science,highlighting the transformative potential this convergence holds for innovation in healthcare and medical research.The review covers key topics such as computational modelling,bioinformatics,machine learning in medical diagnostics,and the integration of wearable technology for real-time health monitoring.Major findings indicate that computational models have significantly enhanced the understanding of complex biological systems,while machine learning algorithms have improved the accuracy of disease prediction and diagnosis.The synergy between bioinformatics and computational techniques has led to breakthroughs in personalized medicine,enabling more precise treatment strategies.Additionally,the integration of wearable devices with advanced computational methods has opened new avenues for continuous health monitoring and early disease detection.The review emphasizes the need for interdisciplinary collaboration to further advance this field.Future research should focus on developing more robust and scalable computational models,enhancing data integration techniques,and addressing ethical considerations related to data privacy and security.By fostering innovation at the intersection of these disciplines,the potential to revolutionize healthcare delivery and outcomes becomes increasingly attainable.
文摘In this study,we design and numerically investigate a novel all optical D flip-flop(AODFF)based on linear photonic crystal(LPhC)structure that is composed of optical waveguides using the finite difference time domain(FDTD)method.The proposed structure has the hexagonal close packed of 16×20 circular rods that are suspended in the air substrate with a lattice constant of 606 nm.The plane wave expansion(PWE)method is used to obtain the band diagram for AODFF at an operating wavelength of 1550 nm.The proposed optical flip-flop achieves a low delay time of 0.2 ps and a high contrast ratio(CR)of 10.33 dB.The main advantage of this design is that the input power as low as 1 mW/μm^(2) is sufficient for its operation,since no nonlinear rods are included.In addition,the footprint of the proposed AODFF is 100μm^(2),which is smaller compared to the structures reported in the literature,and it has a fast switching frequency of 5 Tbit/s.
基金The DST government of India is appreciated by the researchers for giving them the early career research grant under the project ECR/2017/000179。
文摘As organic thin film transistors(OTFTs)are set to play a crucial role in flexible and cost-effective electronic applica-tions,this paper investigates a high-mobility 6,13-bis(triisopropylsilylethynyl)pentacene(TIPS-pentacene)OTFT for use in flexi-ble electronics.The development of such high-mobility devices necessitates precise device modeling to support technology opti-misation and circuit design.The details of numerical simulation technique is discussed,in which,the electrical behavior of the device is well captured by fine tuning basic semiconductor equations.This technology computer-aided design(TCAD)has been validated with exprimental data.In addition,we have discussed about compact model fitting of the devices as well as parameter extraction procedure employed.This includes verification of Silvaco ATLAS finite element method(FEM)based results against experimental data gained from fabricated OTFT devices.Simulations for p-type TFT-based inverter are also per-formed to assess the performance of compact model in simple circuit simulation.
文摘In recent years,carbon nanotube field effect transistor(CNTFET)has become an attractive alternative to silicon for designing high-performance,highly stable,and low-power static random access memory(SRAM).SRAM serves as a cache memory in computers and many portable devices.Carbon nanotubes(CNTs),because of their exceptional transport capabilities,outstanding thermal conductivities,and impressive current handling capacities,have demonstrated great potential as an alternative device to the standard complementary metal-oxide-semiconductor(CMOS).The SRAM cell design using CNTFET is being compared to SRAM cell designs built using traditional CMOS technology.This paper presents the comprehensive analysis of CMOS&CNTFET based 8T SRAM cell design.Because of the nanoscale size,ballistic transport,and higher carrier mobility of the semiconducting nanotubes in CNTFET,it is integrated into the 8T SRAM cell.The approach incorporates several nonidealities,including the presence of quantum confinement consequences in the peripheral and transverse prescriptions,acoustic and transparent photon diffraction in the region surrounding the channel,as well as the screening effects by parallel CNTs in CNTFETs with multiple CNTs.By incorporating Stanford University CNTFET model in CADENCE(virtuoso)32 nm simulation,we have found that CNTFET SRAM cell is 4 times faster in terms of write/read delay and the write/read power delay product(PDP)value is almost 5 times lower compared to CMOS based SRAM.We have also analyzed the effect of temperature&different tube positions of CNTs on the performance evaluation of the 8T SRAM cell.
文摘The global rise in energy demand, particularly in remote and sparsely populated regions, necessitates innovative and cost-effective electrical distribution solutions. Traditional Rural Electrification (RE) methods, like Conventional Rural Electrification (CRE), have proven economically unfeasible in such areas due to high infrastructure costs and low electricity demand. Consequently, Unconventional Rural Electrification (URE) technologies, such as Capacitor Coupled Substations (CCS), are gaining attention as viable alternatives. This study presents the design and simulation of an 80 kW CCS system, which taps power directly from a 132 kV transmission line to supply low-voltage consumers. The critical components of the CCS, the capacitors are calculated, then a MATLAB/Simulink model with the attained results is executed. Mathematical representation and state-space representation for maintaining the desired tapped voltage area also developed. The research further explores the feasibility and operational performance of this CCS configuration, aiming to address the challenges of rural electrification by offering a sustainable and scalable solution. The results show that the desired value of the tapped voltage can be achieved at any level of High Voltage (HV) with the selection of capacitors that are correctly rated. With an adequately designed control strategy, the research also shows that tapped voltage can be attained under both steady-state and dynamic loads. By leveraging CCS technology, the study demonstrates the potential for delivering reliable electricity to underserved areas, highlighting the system’s practicality and effectiveness in overcoming the limitations of conventional distribution methods.
