The high-resolution DEM-IMB-LBM model can accurately describe pore-scale fluid-solid interactions,but its potential for use in geotechnical engineering analysis has not been fully unleashed due to its prohibitive comp...The high-resolution DEM-IMB-LBM model can accurately describe pore-scale fluid-solid interactions,but its potential for use in geotechnical engineering analysis has not been fully unleashed due to its prohibitive computational costs.To overcome this limitation,a message passing interface(MPI)parallel DEM-IMB-LBM framework is proposed aimed at enhancing computation efficiency.This framework utilises a static domain decomposition scheme,with the entire computation domain being decomposed into multiple subdomains according to predefined processors.A detailed parallel strategy is employed for both contact detection and hydrodynamic force calculation.In particular,a particle ID re-numbering scheme is proposed to handle particle transitions across sub-domain interfaces.Two benchmarks are conducted to validate the accuracy and overall performance of the proposed framework.Subsequently,the framework is applied to simulate scenarios involving multi-particle sedimentation and submarine landslides.The numerical examples effectively demonstrate the robustness and applicability of the MPI parallel DEM-IMB-LBM framework.展开更多
One objective of developing machine learning(ML)-based material models is to integrate them with well-established numerical methods to solve boundary value problems(BVPs).In the family of ML models,recurrent neural ne...One objective of developing machine learning(ML)-based material models is to integrate them with well-established numerical methods to solve boundary value problems(BVPs).In the family of ML models,recurrent neural networks(RNNs)have been extensively applied to capture history-dependent constitutive responses of granular materials,but these multiple-step-based neural networks are neither sufficiently efficient nor aligned with the standard finite element method(FEM).Single-step-based neural networks like the multi-layer perceptron(MLP)are an alternative to bypass the above issues but have to introduce some internal variables to encode complex loading histories.In this work,one novel Frobenius norm-based internal variable,together with the Fourier layer and residual architectureenhanced MLP model,is crafted to replicate the history-dependent constitutive features of representative volume element(RVE)for granular materials.The obtained ML models are then seamlessly embedded into the FEM to solve the BVP of a biaxial compression case and a rigid strip footing case.The obtained solutions are comparable to results from the FEM-DEM multiscale modelling but achieve significantly improved efficiency.The results demonstrate the applicability of the proposed internal variable in enabling MLP to capture highly nonlinear constitutive responses of granular materials.展开更多
Multifield coupling is frequently encountered and also an active area of research in geotechnical engineering.In this work,a particle-resolved direct numerical simulation(PR-DNS)technique is extended to simulate parti...Multifield coupling is frequently encountered and also an active area of research in geotechnical engineering.In this work,a particle-resolved direct numerical simulation(PR-DNS)technique is extended to simulate particle-fluid interaction problems involving heat transfer at the grain level.In this extended technique,an immersed moving boundary(IMB)scheme is used to couple the discrete element method(DEM)and lattice Boltzmann method(LBM),while a recently proposed Dirichlet-type thermal boundary condition is also adapted to account for heat transfer between fluid phase and solid particles.The resulting DEM-IBM-LBM model is robust to simulate moving curved boundaries with constant temperature in thermal flows.To facilitate the understanding and implementation of this coupled model for non-isothermal problems,a complete list is given for the conversion of relevant physical variables to lattice units.Then,benchmark tests,including a single-particle sedimentation and a two-particle drafting-kissing-tumbling(DKT)simulation with heat transfer,are carried out to validate the accuracy of our coupled technique.To further investigate the role of heat transfer in particle-laden flows,two multiple-particle problems with heat transfer are performed.Numerical examples demonstrate that the proposed coupling model is a promising high-resolution approach for simulating the heat-particle-fluid coupling at the grain level.展开更多
In source detection in the Tianlai project,locating the interferometric fringe in visibility data accurately will influence downstream tasks drastically,such as physical parameter estimation and weak source exploratio...In source detection in the Tianlai project,locating the interferometric fringe in visibility data accurately will influence downstream tasks drastically,such as physical parameter estimation and weak source exploration.Considering that traditional locating methods are time-consuming and supervised methods require a great quantity of expensive labeled data,in this paper,we first investigate characteristics of interferometric fringes in the simulation and real scenario separately,and integrate an almost parameter-free unsupervised clustering method and seeding filling or eraser algorithm to propose a hierarchical plug and play method to improve location accuracy.Then,we apply our method to locate single and multiple sources’interferometric fringes in simulation data.Next,we apply our method to real data taken from the Tianlai radio telescope array.Finally,we compare with unsupervised methods that are state of the art.These results show that our method has robustness in different scenarios and can improve location measurement accuracy effectively.展开更多
The classical deviatoric hardening models are capable of characterizing the mechanical response of granular materials for a broad range of degrees of compaction.This work finds that it has limitations in accurately pr...The classical deviatoric hardening models are capable of characterizing the mechanical response of granular materials for a broad range of degrees of compaction.This work finds that it has limitations in accurately predicting the volumetric deformation characteristics under a wide range of confining/consolidation pressures.The issue stems from the pressure independent hardening law in the classical deviatoric hardening model.To overcome this problem,we propose a refined deviatoric hardening model in which a pressure-dependent hardening law is developed based on experimental observations.Comparisons between numerical results and laboratory triaxial tests indicate that the improved model succeeds in capturing the volumetric deformation behavior under various confining/consolidation pressure conditions for both dense and loose sands.Furthermore,to examine the importance of the improved deviatoric hardening model,it is combined with the bounding surface plasticity theory to investigate the mechanical response of loose sand under complex cyclic loadings and different initial consolidation pressures.It is proved that the proposed pressure-dependent deviatoric hardening law is capable of predicting the volumetric deformation characteristics to a satisfactory degree and plays an important role in the simulation of complex deformations for granular geomaterials.展开更多
Metal oxide charge transport materials are preferable for realizing long-term stable and potentially low-cost perovskite solar cells(PSCs).However,due to some technical difficulties(e.g.,intricate fabrication protocol...Metal oxide charge transport materials are preferable for realizing long-term stable and potentially low-cost perovskite solar cells(PSCs).However,due to some technical difficulties(e.g.,intricate fabrication protocols,high-temperature heating process,incompatible solvents,etc.),it is still challenging to achieve efficient and reliable all-metal-oxide-based devices.Here,we developed efficient inverted PSCs(IPSCs)based on solution-processed nickel oxide(NiO_(x))and tin oxide(SnO_(2))nanoparticles,working as hole and electron transport materials respectively,enabling a fast and balanced charge transfer for photogenerated charge carriers.Through further understanding and optimizing the perovskite/metal oxide interfaces,we have realized an outstanding power conversion efficiency(PCE)of 23.5%(the bandgap of the perovskite is 1.62 eV),which is the highest efficiency among IPSCs based on all-metal-oxide charge transport materials.Thanks to these stable metal oxides and improved interface properties,ambient stability(retaining 95%of initial PCE after 1 month),thermal stability(retaining 80%of initial PCE after 2 weeks)and light stability(retaining 90%of initial PCE after 1000 hours aging)of resultant devices are enhanced significantly.In addition,owing to the low-temperature fabrication procedures of the entire device,we have obtained a PCE of over 21%for flexible IPSCs with enhanced operational stability.展开更多
We are delighted to serve as guest editors for this special issue in the Journal of Rock Mechanics and Geotechnical Engineering.The purpose of this special issue is dedicated to gathering the latest research work on M...We are delighted to serve as guest editors for this special issue in the Journal of Rock Mechanics and Geotechnical Engineering.The purpose of this special issue is dedicated to gathering the latest research work on Multiscale&Multifield Coupling in Geomechanics,where we delve into the intricate interplay of various fields and scales that govern the behavior of geomaterials.In total,30 manuscripts from USA,China,UK,Germany,Canada,India and United Arab Emirates are selected to be included in this issue.展开更多
In engineering fields,time-varying matrix inversion(TVMI)issue is often encountered.Zeroing neural network(ZNN)has been extensively employed to resolve the TVMI problem.Nevertheless,the original ZNN(OZNN)and the integ...In engineering fields,time-varying matrix inversion(TVMI)issue is often encountered.Zeroing neural network(ZNN)has been extensively employed to resolve the TVMI problem.Nevertheless,the original ZNN(OZNN)and the integral-enhanced ZNN(IEZNN)usually fail to deal with the TVMI problem under unbounded noises,such as linear noises.Therefore,a neural network model that can handle the TVMI under linear noise interference is urgently needed.This paper develops a double integral-enhanced ZNN(DIEZNN)model based on a novel integral-type design formula with inherent linear-noise tolerance.Moreover,its convergence and robustness are verified by deriva-tion strictly.For comparison and verification,the OZNN and the IEZNN models are adopted to resolve the TVMI under multiple identical noise environments.The experi-ments proved that the DIEZNN model has excellent advantages in solving TVMI problems under linear noises.In general,the DIEZNN model is an innovative work and is proposed for the first time.Satisfyingly,the errors of DIEZNN are always less than 1�10−3 under linear noises,whereas the error norms of OZNN and IEZNN models are not convergent to zero.In addition,these models are applied to the control of the controllable permanent magnet synchronous motor chaotic system to indicate the superiority of the DIEZNN.展开更多
Purpose: This research aims to evaluate the potential threats to patient privacy and confidentiality posed by mHealth applications on mobile devices. Methodology: A comprehensive literature review was conducted, selec...Purpose: This research aims to evaluate the potential threats to patient privacy and confidentiality posed by mHealth applications on mobile devices. Methodology: A comprehensive literature review was conducted, selecting eighty-eight articles published over the past fifteen years. The study assessed data gathering and storage practices, regulatory adherence, legal structures, consent procedures, user education, and strategies to mitigate risks. Results: The findings reveal significant advancements in technologies designed to safeguard privacy and facilitate the widespread use of mHealth apps. However, persistent ethical issues related to privacy remain largely unchanged despite these technological strides.展开更多
Manipulators actuate joints to let end effectors to perform precise path tracking tasks.Recurrent neural network which is described by dynamic models with parallel processing capability,is a powerful tool for kinemati...Manipulators actuate joints to let end effectors to perform precise path tracking tasks.Recurrent neural network which is described by dynamic models with parallel processing capability,is a powerful tool for kinematic control of manipulators.Due to physical limitations and actuation saturation of manipulator joints,the involvement of joint constraints for kinematic control of manipulators is essential and critical.However,current existing manipulator control methods based on recurrent neural networks mainly handle with limited levels of joint angular constraints,and to the best of our knowledge,methods for kinematic control of manipulators with higher order joint constraints based on recurrent neural networks are not yet reported.In this study,for the first time,a novel recursive recurrent network model is proposed to solve the kinematic control issue for manipulators with different levels of physical constraints,and the proposed recursive recurrent neural network can be formulated as a new manifold system to ensure control solution within all of the joint constraints in different orders.The theoretical analysis shows the stability and the purposed recursive recurrent neural network and its convergence to solution.Simulation results further demonstrate the effectiveness of the proposed method in end‐effector path tracking control under different levels of joint constraints based on the Kuka manipulator system.Comparisons with other methods such as the pseudoinverse‐based method and conventional recurrent neural network method substantiate the superiority of the proposed method.展开更多
With advanced communication technologies,cyberphysical systems such as networked industrial control systems can be monitored and controlled by a remote control center via communication networks.While lots of benefits ...With advanced communication technologies,cyberphysical systems such as networked industrial control systems can be monitored and controlled by a remote control center via communication networks.While lots of benefits can be achieved with such a configuration,it also brings the concern of cyber attacks to the industrial control systems,such as networked manipulators that are widely adopted in industrial automation.For such systems,a false data injection attack on a control-center-to-manipulator(CC-M)communication channel is undesirable,and has negative effects on the manufacture quality.In this paper,we propose a resilient remote kinematic control method for serial manipulators undergoing a false data injection attack by leveraging the kinematic model.Theoretical analysis shows that the proposed method can guarantee asymptotic convergence of the regulation error to zero in the presence of a type of false data injection attack.The efficacy of the proposed method is validated via simulations.展开更多
This paper explores some design parameters of an interior permanent magnet synchronous motor that contribute to enhancing motor performance.Various geometry parameters such as magnet dimension,machine diameter,stator ...This paper explores some design parameters of an interior permanent magnet synchronous motor that contribute to enhancing motor performance.Various geometry parameters such as magnet dimension,machine diameter,stator teeth height,and number of poles are analyzed to compare overall torque,power,and torque ripples in order to select the best design parameters and their ranges.Pyleecan,an open-source software,is used to design and optimize the motor for electric vehicle applications.Following optimization with Non-dominated Sorting Genetic Algorithm(NSGA-Ⅱ),two designs A and B were obtained for two objective functions and the corresponding torque ripples values of the design A and B were later reduced by 32%and 77%.Additionally,the impact of different magnet grades on the output performances is analyzed.展开更多
Biopolymers are promising environmentally benign materials applicable in multifarious applications.They are especially favorable in implantable biomedical devices thanks to their excellent unique properties,including ...Biopolymers are promising environmentally benign materials applicable in multifarious applications.They are especially favorable in implantable biomedical devices thanks to their excellent unique properties,including bioactivity,renewability,bioresorbability,biocompatibility,biodegradability and hydrophilicity.Additive manufacturing(AM)is a flexible and intricate manufacturing technology,which is widely used to fabricate biopolymer-based customized products and structures for advanced healthcare systems.Three-dimensional(3D)printing of these sustainable materials is applied in functional clinical settings including wound dressing,drug delivery systems,medical implants and tissue engineering.The present review highlights recent advancements in different types of biopolymers,such as proteins and polysaccharides,which are employed to develop different biomedical products by using extrusion,vat polymerization,laser and inkjet 3D printing techniques in addition to normal bioprinting and four-dimensional(4D)bioprinting techniques.It also incorporates the influence of nanoparticles on the biological and mechanical performances of 3D-printed tissue scaffolds,and addresses current challenges as well as future developments of environmentally friendly polymeric materials manufactured through the AMtechniques.Ideally,there is a need for more focused research on the adequate blending of these biodegradable biopolymers for achieving useful results in targeted biomedical areas.We envision that biopolymer-based 3D-printed composites have the potential to revolutionize the biomedical sector in the near future.展开更多
Intelligent Space(IS)is widely regarded as a promising paradigm for improving quality of life through using service task processing.As the field matures,various state-of-the-art IS architectures have been proposed.Mos...Intelligent Space(IS)is widely regarded as a promising paradigm for improving quality of life through using service task processing.As the field matures,various state-of-the-art IS architectures have been proposed.Most of the IS architectures designed for service robots face the problems of fixedfunction modules and low scalability when performing service tasks.To this end,we propose a hybrid cloud service robot architecture based on a Service-Oriented Architecture(SOA).Specifically,we first use the distributed deployment of functional modules to solve the problem of high computing resource occupancy.Then,the Socket communication interface layer is designed to improve the calling efficiency of the function module.Next,the private cloud service knowledge base and the dataset for the home environment are used to improve the robustness and success rate of the robot when performing tasks.Finally,we design and deploy an interactive system based on Browser/Server(B/S)architecture,which aims to display the status of the robot in real-time as well as to expand and call the robot service.This system is integrated into the private cloud framework,which provides a feasible solution for improving the quality of life.Besides,it also fully reveals how to actively discover and provide the robot service mechanism of service tasks in the right way.The results of extensive experiments show that our cloud system provides sufficient prior knowledge that can assist the robot in completing service tasks.It is an efficient way to transmit data and reduce the computational burden on the robot.By using our cloud detection module,the robot system can save approximately 25% of the averageCPUusage and reduce the average detection time by 0.1 s compared to the locally deployed system,demonstrating the reliability and practicality of our proposed architecture.展开更多
Background: Dual Practice (DP) allows full-time public sector doctors to concurrently offer the same clinical services in the private sector. The debate against this practice seems to be largely influenced by its pote...Background: Dual Practice (DP) allows full-time public sector doctors to concurrently offer the same clinical services in the private sector. The debate against this practice seems to be largely influenced by its potential to reduce the contracted hours in the public sector and shift attention to private work. Purpose: The purpose of this secondary research is to estimate the monetary value of hours lost to the Nigerian public healthcare system when full-time government employee doctors are engaged in private practice. It attempts to quantify the amount of resource outflow from the public system due to absences and lateness arising from competition for time between the public system’s contracted hours and private practice. Methods: Sensitivity analysis in Excel 2010 was used to calculate doctors’ hourly pay in the public sector using the 2015 Consolidated Medical Salary Structure for medical and dental officers in Nigeria’s federal public service. The parameters used for the calculation were the official 40-hour working week and the average monthly gross pay of doctors on different grade levels. Hypothetical scenarios of hours lost due to absences associated with DP were created. The value of different hypothetical hour losses by the percentage of doctors assumed to engage in dual practice across all doctor grade levels was then computed. Results: The estimated annual value of hours lost from dual practice to a single public tertiary care hospital was N4,851,754 or 15,855 USD (best case scenario) and N19,407,017 or 63,422 USD (worst case scenario) for the normal routine work and N1,800,133 or 5883 USD (best case scenario) and N3,600,266 or 11,766 USD (worst case scenario) for the on-call duty. Conclusion: The government may have been paying salaries for large volumes of work not rendered in the public sector. The overall financial impact of dual practice in the Nigerian public system might be negative.展开更多
Over the last two decades,extensive study has been done on two-dimensional Molybdenum Sulphide(MoS_(2))due to its outstanding features in energy storage applications.Although MoS_(2)has a lot of active sulphur edges,t...Over the last two decades,extensive study has been done on two-dimensional Molybdenum Sulphide(MoS_(2))due to its outstanding features in energy storage applications.Although MoS_(2)has a lot of active sulphur edges,the presence of inactive surfaces leads to limit conductivity and efficiency.Hence,in this article,we aimed to promote the additional active sites by doping various weight percentages(2%,4%,6%,8%and 10%)of Nickel(Ni)into the MoS_(2)matrix by simple hydrothermal technique,and their doping effects were investigated with the help of Physio-chemical analyses.X-ray diffraction(XRD)pattern,Raman,and chemical composition(XPS)analyses were used to confirm the Ni incorporation in MoS_(2)nanosheets.Microscopic investigations demonstrated that Ni-doped MoS_(2)nanosheets were vertically aligned with enhanced interlayer spacing.Cyclic voltammetry,Galvanostatic charge-discharge,and electrochemical impedance spectroscopy investigations were used to characterize the electrochemical characteristics.The 6%Ni-doped MoS_(2)electrode material showed better CSPof 528.7 F/g@1 A/g and excellent electrochemical stability(85%of capacitance retention after 10,000 cycles at 5 A/g)compared to other electrode materials.Furthermore,the solid-state asymmetric supercapacitor was assembled using Nidoped MoS_(2)and graphite as anode and cathode materials and analysed the electrochemical properties in the two-electrode system.To determine the impact of the Ni-atom on the MoS_(2)surface,firstprinciples computations were performed.Further,it was examined for electronic band structure,the projected density of states(PDOS)and Bader charge transfer analyses.展开更多
基金financially supported by the National Natural Science Foundation of China(Grant Nos.12072217 and 42077254)the Natural Science Foundation of Hunan Province,China(Grant No.2022JJ30567).
文摘The high-resolution DEM-IMB-LBM model can accurately describe pore-scale fluid-solid interactions,but its potential for use in geotechnical engineering analysis has not been fully unleashed due to its prohibitive computational costs.To overcome this limitation,a message passing interface(MPI)parallel DEM-IMB-LBM framework is proposed aimed at enhancing computation efficiency.This framework utilises a static domain decomposition scheme,with the entire computation domain being decomposed into multiple subdomains according to predefined processors.A detailed parallel strategy is employed for both contact detection and hydrodynamic force calculation.In particular,a particle ID re-numbering scheme is proposed to handle particle transitions across sub-domain interfaces.Two benchmarks are conducted to validate the accuracy and overall performance of the proposed framework.Subsequently,the framework is applied to simulate scenarios involving multi-particle sedimentation and submarine landslides.The numerical examples effectively demonstrate the robustness and applicability of the MPI parallel DEM-IMB-LBM framework.
基金supported by the National Natural Science Foundation of China(NSFC)(Grant No.12072217).
文摘One objective of developing machine learning(ML)-based material models is to integrate them with well-established numerical methods to solve boundary value problems(BVPs).In the family of ML models,recurrent neural networks(RNNs)have been extensively applied to capture history-dependent constitutive responses of granular materials,but these multiple-step-based neural networks are neither sufficiently efficient nor aligned with the standard finite element method(FEM).Single-step-based neural networks like the multi-layer perceptron(MLP)are an alternative to bypass the above issues but have to introduce some internal variables to encode complex loading histories.In this work,one novel Frobenius norm-based internal variable,together with the Fourier layer and residual architectureenhanced MLP model,is crafted to replicate the history-dependent constitutive features of representative volume element(RVE)for granular materials.The obtained ML models are then seamlessly embedded into the FEM to solve the BVP of a biaxial compression case and a rigid strip footing case.The obtained solutions are comparable to results from the FEM-DEM multiscale modelling but achieve significantly improved efficiency.The results demonstrate the applicability of the proposed internal variable in enabling MLP to capture highly nonlinear constitutive responses of granular materials.
基金financially supported by the Natural Science Foundation of Hunan Province,China(Grant No.2022JJ30567)the support of EPSRC Grant(UK):PURIFY(EP/V000756/1)the Scientific Research Foundation of Education Department of Hunan Province,China(Grant No.20B557).
文摘Multifield coupling is frequently encountered and also an active area of research in geotechnical engineering.In this work,a particle-resolved direct numerical simulation(PR-DNS)technique is extended to simulate particle-fluid interaction problems involving heat transfer at the grain level.In this extended technique,an immersed moving boundary(IMB)scheme is used to couple the discrete element method(DEM)and lattice Boltzmann method(LBM),while a recently proposed Dirichlet-type thermal boundary condition is also adapted to account for heat transfer between fluid phase and solid particles.The resulting DEM-IBM-LBM model is robust to simulate moving curved boundaries with constant temperature in thermal flows.To facilitate the understanding and implementation of this coupled model for non-isothermal problems,a complete list is given for the conversion of relevant physical variables to lattice units.Then,benchmark tests,including a single-particle sedimentation and a two-particle drafting-kissing-tumbling(DKT)simulation with heat transfer,are carried out to validate the accuracy of our coupled technique.To further investigate the role of heat transfer in particle-laden flows,two multiple-particle problems with heat transfer are performed.Numerical examples demonstrate that the proposed coupling model is a promising high-resolution approach for simulating the heat-particle-fluid coupling at the grain level.
基金supported by the National Natural Science Foundation of China(NSFC,grant Nos.42172323 and 12371454)。
文摘In source detection in the Tianlai project,locating the interferometric fringe in visibility data accurately will influence downstream tasks drastically,such as physical parameter estimation and weak source exploration.Considering that traditional locating methods are time-consuming and supervised methods require a great quantity of expensive labeled data,in this paper,we first investigate characteristics of interferometric fringes in the simulation and real scenario separately,and integrate an almost parameter-free unsupervised clustering method and seeding filling or eraser algorithm to propose a hierarchical plug and play method to improve location accuracy.Then,we apply our method to locate single and multiple sources’interferometric fringes in simulation data.Next,we apply our method to real data taken from the Tianlai radio telescope array.Finally,we compare with unsupervised methods that are state of the art.These results show that our method has robustness in different scenarios and can improve location measurement accuracy effectively.
基金the funding support from Basic Science Center Program for Multiphase Media Evolution in Hypergravity of the National Natural Science Foundation of China(Grant No.51988101).
文摘The classical deviatoric hardening models are capable of characterizing the mechanical response of granular materials for a broad range of degrees of compaction.This work finds that it has limitations in accurately predicting the volumetric deformation characteristics under a wide range of confining/consolidation pressures.The issue stems from the pressure independent hardening law in the classical deviatoric hardening model.To overcome this problem,we propose a refined deviatoric hardening model in which a pressure-dependent hardening law is developed based on experimental observations.Comparisons between numerical results and laboratory triaxial tests indicate that the improved model succeeds in capturing the volumetric deformation behavior under various confining/consolidation pressure conditions for both dense and loose sands.Furthermore,to examine the importance of the improved deviatoric hardening model,it is combined with the bounding surface plasticity theory to investigate the mechanical response of loose sand under complex cyclic loadings and different initial consolidation pressures.It is proved that the proposed pressure-dependent deviatoric hardening law is capable of predicting the volumetric deformation characteristics to a satisfactory degree and plays an important role in the simulation of complex deformations for granular geomaterials.
基金UK Engineering and Physical Sciences Research Council(EPSRC)New Investigator Award(2018,EP/R043272/1)Newton Advanced Fellowship(192097)for financial support+3 种基金the Royal Society,the Engineering and Physical Sciences Research Council(EPSRC,EP/R023980/1,EP/V027131/1)the European Research Council(ERC)under the European Union's Horizon 2020 research and innovation program(HYPERION,Grant Agreement Number 756962)the Royal Society and Tata Group(UF150033)EPSRC SPECIFIC IKC(EP/N020863/1)
文摘Metal oxide charge transport materials are preferable for realizing long-term stable and potentially low-cost perovskite solar cells(PSCs).However,due to some technical difficulties(e.g.,intricate fabrication protocols,high-temperature heating process,incompatible solvents,etc.),it is still challenging to achieve efficient and reliable all-metal-oxide-based devices.Here,we developed efficient inverted PSCs(IPSCs)based on solution-processed nickel oxide(NiO_(x))and tin oxide(SnO_(2))nanoparticles,working as hole and electron transport materials respectively,enabling a fast and balanced charge transfer for photogenerated charge carriers.Through further understanding and optimizing the perovskite/metal oxide interfaces,we have realized an outstanding power conversion efficiency(PCE)of 23.5%(the bandgap of the perovskite is 1.62 eV),which is the highest efficiency among IPSCs based on all-metal-oxide charge transport materials.Thanks to these stable metal oxides and improved interface properties,ambient stability(retaining 95%of initial PCE after 1 month),thermal stability(retaining 80%of initial PCE after 2 weeks)and light stability(retaining 90%of initial PCE after 1000 hours aging)of resultant devices are enhanced significantly.In addition,owing to the low-temperature fabrication procedures of the entire device,we have obtained a PCE of over 21%for flexible IPSCs with enhanced operational stability.
文摘We are delighted to serve as guest editors for this special issue in the Journal of Rock Mechanics and Geotechnical Engineering.The purpose of this special issue is dedicated to gathering the latest research work on Multiscale&Multifield Coupling in Geomechanics,where we delve into the intricate interplay of various fields and scales that govern the behavior of geomaterials.In total,30 manuscripts from USA,China,UK,Germany,Canada,India and United Arab Emirates are selected to be included in this issue.
基金National Natural Science Foundation of China,Grant/Award Numbers:61962023,62066015。
文摘In engineering fields,time-varying matrix inversion(TVMI)issue is often encountered.Zeroing neural network(ZNN)has been extensively employed to resolve the TVMI problem.Nevertheless,the original ZNN(OZNN)and the integral-enhanced ZNN(IEZNN)usually fail to deal with the TVMI problem under unbounded noises,such as linear noises.Therefore,a neural network model that can handle the TVMI under linear noise interference is urgently needed.This paper develops a double integral-enhanced ZNN(DIEZNN)model based on a novel integral-type design formula with inherent linear-noise tolerance.Moreover,its convergence and robustness are verified by deriva-tion strictly.For comparison and verification,the OZNN and the IEZNN models are adopted to resolve the TVMI under multiple identical noise environments.The experi-ments proved that the DIEZNN model has excellent advantages in solving TVMI problems under linear noises.In general,the DIEZNN model is an innovative work and is proposed for the first time.Satisfyingly,the errors of DIEZNN are always less than 1�10−3 under linear noises,whereas the error norms of OZNN and IEZNN models are not convergent to zero.In addition,these models are applied to the control of the controllable permanent magnet synchronous motor chaotic system to indicate the superiority of the DIEZNN.
文摘Purpose: This research aims to evaluate the potential threats to patient privacy and confidentiality posed by mHealth applications on mobile devices. Methodology: A comprehensive literature review was conducted, selecting eighty-eight articles published over the past fifteen years. The study assessed data gathering and storage practices, regulatory adherence, legal structures, consent procedures, user education, and strategies to mitigate risks. Results: The findings reveal significant advancements in technologies designed to safeguard privacy and facilitate the widespread use of mHealth apps. However, persistent ethical issues related to privacy remain largely unchanged despite these technological strides.
文摘Manipulators actuate joints to let end effectors to perform precise path tracking tasks.Recurrent neural network which is described by dynamic models with parallel processing capability,is a powerful tool for kinematic control of manipulators.Due to physical limitations and actuation saturation of manipulator joints,the involvement of joint constraints for kinematic control of manipulators is essential and critical.However,current existing manipulator control methods based on recurrent neural networks mainly handle with limited levels of joint angular constraints,and to the best of our knowledge,methods for kinematic control of manipulators with higher order joint constraints based on recurrent neural networks are not yet reported.In this study,for the first time,a novel recursive recurrent network model is proposed to solve the kinematic control issue for manipulators with different levels of physical constraints,and the proposed recursive recurrent neural network can be formulated as a new manifold system to ensure control solution within all of the joint constraints in different orders.The theoretical analysis shows the stability and the purposed recursive recurrent neural network and its convergence to solution.Simulation results further demonstrate the effectiveness of the proposed method in end‐effector path tracking control under different levels of joint constraints based on the Kuka manipulator system.Comparisons with other methods such as the pseudoinverse‐based method and conventional recurrent neural network method substantiate the superiority of the proposed method.
基金This work was supported in part by the National Natural Science Foundation of China(62206109)the Fundamental Research Funds for the Central Universities(21620346)。
文摘With advanced communication technologies,cyberphysical systems such as networked industrial control systems can be monitored and controlled by a remote control center via communication networks.While lots of benefits can be achieved with such a configuration,it also brings the concern of cyber attacks to the industrial control systems,such as networked manipulators that are widely adopted in industrial automation.For such systems,a false data injection attack on a control-center-to-manipulator(CC-M)communication channel is undesirable,and has negative effects on the manufacture quality.In this paper,we propose a resilient remote kinematic control method for serial manipulators undergoing a false data injection attack by leveraging the kinematic model.Theoretical analysis shows that the proposed method can guarantee asymptotic convergence of the regulation error to zero in the presence of a type of false data injection attack.The efficacy of the proposed method is validated via simulations.
基金funded by the Advanced Sustainable Manufacturing Technologies(ASTUTE2020)operation supporting manufacturing companies across Wales,which has been part-funded by the European Regional Development Fund through the Welsh Government and the participating Higher Education Institutions。
文摘This paper explores some design parameters of an interior permanent magnet synchronous motor that contribute to enhancing motor performance.Various geometry parameters such as magnet dimension,machine diameter,stator teeth height,and number of poles are analyzed to compare overall torque,power,and torque ripples in order to select the best design parameters and their ranges.Pyleecan,an open-source software,is used to design and optimize the motor for electric vehicle applications.Following optimization with Non-dominated Sorting Genetic Algorithm(NSGA-Ⅱ),two designs A and B were obtained for two objective functions and the corresponding torque ripples values of the design A and B were later reduced by 32%and 77%.Additionally,the impact of different magnet grades on the output performances is analyzed.
文摘Biopolymers are promising environmentally benign materials applicable in multifarious applications.They are especially favorable in implantable biomedical devices thanks to their excellent unique properties,including bioactivity,renewability,bioresorbability,biocompatibility,biodegradability and hydrophilicity.Additive manufacturing(AM)is a flexible and intricate manufacturing technology,which is widely used to fabricate biopolymer-based customized products and structures for advanced healthcare systems.Three-dimensional(3D)printing of these sustainable materials is applied in functional clinical settings including wound dressing,drug delivery systems,medical implants and tissue engineering.The present review highlights recent advancements in different types of biopolymers,such as proteins and polysaccharides,which are employed to develop different biomedical products by using extrusion,vat polymerization,laser and inkjet 3D printing techniques in addition to normal bioprinting and four-dimensional(4D)bioprinting techniques.It also incorporates the influence of nanoparticles on the biological and mechanical performances of 3D-printed tissue scaffolds,and addresses current challenges as well as future developments of environmentally friendly polymeric materials manufactured through the AMtechniques.Ideally,there is a need for more focused research on the adequate blending of these biodegradable biopolymers for achieving useful results in targeted biomedical areas.We envision that biopolymer-based 3D-printed composites have the potential to revolutionize the biomedical sector in the near future.
基金supported in part by the National Natural Science Foundation of China under Grant 62273203,Grant U1813215in part by the Special Fund for the Taishan Scholars Program of Shandong Province(ts201511005).
文摘Intelligent Space(IS)is widely regarded as a promising paradigm for improving quality of life through using service task processing.As the field matures,various state-of-the-art IS architectures have been proposed.Most of the IS architectures designed for service robots face the problems of fixedfunction modules and low scalability when performing service tasks.To this end,we propose a hybrid cloud service robot architecture based on a Service-Oriented Architecture(SOA).Specifically,we first use the distributed deployment of functional modules to solve the problem of high computing resource occupancy.Then,the Socket communication interface layer is designed to improve the calling efficiency of the function module.Next,the private cloud service knowledge base and the dataset for the home environment are used to improve the robustness and success rate of the robot when performing tasks.Finally,we design and deploy an interactive system based on Browser/Server(B/S)architecture,which aims to display the status of the robot in real-time as well as to expand and call the robot service.This system is integrated into the private cloud framework,which provides a feasible solution for improving the quality of life.Besides,it also fully reveals how to actively discover and provide the robot service mechanism of service tasks in the right way.The results of extensive experiments show that our cloud system provides sufficient prior knowledge that can assist the robot in completing service tasks.It is an efficient way to transmit data and reduce the computational burden on the robot.By using our cloud detection module,the robot system can save approximately 25% of the averageCPUusage and reduce the average detection time by 0.1 s compared to the locally deployed system,demonstrating the reliability and practicality of our proposed architecture.
文摘Background: Dual Practice (DP) allows full-time public sector doctors to concurrently offer the same clinical services in the private sector. The debate against this practice seems to be largely influenced by its potential to reduce the contracted hours in the public sector and shift attention to private work. Purpose: The purpose of this secondary research is to estimate the monetary value of hours lost to the Nigerian public healthcare system when full-time government employee doctors are engaged in private practice. It attempts to quantify the amount of resource outflow from the public system due to absences and lateness arising from competition for time between the public system’s contracted hours and private practice. Methods: Sensitivity analysis in Excel 2010 was used to calculate doctors’ hourly pay in the public sector using the 2015 Consolidated Medical Salary Structure for medical and dental officers in Nigeria’s federal public service. The parameters used for the calculation were the official 40-hour working week and the average monthly gross pay of doctors on different grade levels. Hypothetical scenarios of hours lost due to absences associated with DP were created. The value of different hypothetical hour losses by the percentage of doctors assumed to engage in dual practice across all doctor grade levels was then computed. Results: The estimated annual value of hours lost from dual practice to a single public tertiary care hospital was N4,851,754 or 15,855 USD (best case scenario) and N19,407,017 or 63,422 USD (worst case scenario) for the normal routine work and N1,800,133 or 5883 USD (best case scenario) and N3,600,266 or 11,766 USD (worst case scenario) for the on-call duty. Conclusion: The government may have been paying salaries for large volumes of work not rendered in the public sector. The overall financial impact of dual practice in the Nigerian public system might be negative.
文摘Over the last two decades,extensive study has been done on two-dimensional Molybdenum Sulphide(MoS_(2))due to its outstanding features in energy storage applications.Although MoS_(2)has a lot of active sulphur edges,the presence of inactive surfaces leads to limit conductivity and efficiency.Hence,in this article,we aimed to promote the additional active sites by doping various weight percentages(2%,4%,6%,8%and 10%)of Nickel(Ni)into the MoS_(2)matrix by simple hydrothermal technique,and their doping effects were investigated with the help of Physio-chemical analyses.X-ray diffraction(XRD)pattern,Raman,and chemical composition(XPS)analyses were used to confirm the Ni incorporation in MoS_(2)nanosheets.Microscopic investigations demonstrated that Ni-doped MoS_(2)nanosheets were vertically aligned with enhanced interlayer spacing.Cyclic voltammetry,Galvanostatic charge-discharge,and electrochemical impedance spectroscopy investigations were used to characterize the electrochemical characteristics.The 6%Ni-doped MoS_(2)electrode material showed better CSPof 528.7 F/g@1 A/g and excellent electrochemical stability(85%of capacitance retention after 10,000 cycles at 5 A/g)compared to other electrode materials.Furthermore,the solid-state asymmetric supercapacitor was assembled using Nidoped MoS_(2)and graphite as anode and cathode materials and analysed the electrochemical properties in the two-electrode system.To determine the impact of the Ni-atom on the MoS_(2)surface,firstprinciples computations were performed.Further,it was examined for electronic band structure,the projected density of states(PDOS)and Bader charge transfer analyses.
