Halide solid-state electrolytes have gained significant attention in recent years due to their high ionic conductivity,making them promising candidates for future all-solid-state batteries.Recent studies have identifi...Halide solid-state electrolytes have gained significant attention in recent years due to their high ionic conductivity,making them promising candidates for future all-solid-state batteries.Recent studies have identified numerous crystal structures with the Li_(3)MX_(6)composition,although many remain unexplored across various chemical systems.In this research,we developed a comprehensive method to examine all conceivable space groups and structures within theLi-M-X system,where M includes In,Ga,and La,and X includes F,Cl,Br,and 1.Our findings revealed two metastable structures:Li_(3)InF_(6)with P3c1 symmetry and Li_(3)InI_(6)with C2/c symmetry,exhibiting ionic conductivities of 0.55 and 2.18mS/cm at 300K,respectively.Notably,the trigonal symmetry of Li3InF6 demonstrates that high ionic conductivities are not limited to monoclinic structures but can also be achieved with trigonal symmetries.The electrochemical stability windows,mechanical properties,and reaction energies of these materials with known cathodes suggest their potential for use in all-solid-state batteries.Additionally,we predicted the stability of novel materials,including Li_(5)InCl_(8),Li_(5)InBr_(8),Li_(5)InI_(8),LiIn_(2)Cl_(9),LiIn_(2)Br_(9),and LiIn_(2)I_(9).展开更多
Magnesium(Mg)alloys are ideal candidates for automotive applications due to their high strength to weight ratio,castability,recyclability etc.,however,they lack corrosion and oxidation resistance.Solid-state depositio...Magnesium(Mg)alloys are ideal candidates for automotive applications due to their high strength to weight ratio,castability,recyclability etc.,however,they lack corrosion and oxidation resistance.Solid-state deposition techniques,such as cold spray,have been demonstrated to enhance their corrosion resistance as it relies on the severe plastic deformation of powder particles upon impact with the substrate to form a metallurgical bond with the substrate and within the coating.At cold sprayed interfaces,a heterogeneous microstructure is formed that includes some porosity,oxides and intermetallics which can significantly affect coating performance.Thus,establishing a direct correlation between the interface microstructure and its properties can aid in designing optimal cold spray parameters.In this study,we investigated the microstructure and mechanical properties of a zinc(Zn)coating deposited on a high pressure die cast(HPDC)AZ91 Mg substrate via high resolution scanning transmission electron microscopy,in situ micro-tensile testing,and finite element method(FEM)modeling.Micro-tensile pillars fabricated using the plasma focused ion beam(PFIB)successfully isolates the coating-substrate interface within the gauge length.The average bond strength of Zn-Mg interface was determined to be∼140 MPa with failure occurring partially at the interface and mostly into the coatings.A detailed microstructural characterization revealed evidence of a strong metallurgical bonding at the Zn-Mg interface and formation of the C14 MgZn_(2)laves phase interlayer resulting in a mixed mode of fracture during the micro-tensile experiments.FEM modeling reveals the stress distribution along the interfaces and suggests that a MgZn_(2)layer thickness between 200–400 nm is optimum to increase the bond strength and minimize the triaxiality.Such a site-specific interfacial analysis with correlative computational modeling provides crucial insight into the overall performance of cold spray interfaces.展开更多
The functional properties of glasses are governed by their formation history and the complex relaxation processes they undergo.However,under extreme conditions,glass behaviors are still elusive.In this study,we employ...The functional properties of glasses are governed by their formation history and the complex relaxation processes they undergo.However,under extreme conditions,glass behaviors are still elusive.In this study,we employ simulations with varied protocols to evaluate the effectiveness of different descriptors in predicting mechanical properties across both low-and high-pressure regimes.Our findings demonstrate that conventional structural and configurational descriptors fail to correlate with the mechanical response following pressure release,whereas the activation energy descriptor exhibits robust linearity with shear modulus after correcting for pressure effects.Notably,the soft mode parameter emerges as an ideal and computationally efficient alternative for capturing this mechanical behavior.These findings provide critical insights into the influence of pressure on glassy properties,integrating the distinct features of compressed glasses into a unified theoretical framework.展开更多
Adversarial Reinforcement Learning(ARL)models for intelligent devices and Network Intrusion Detection Systems(NIDS)improve systemresilience against sophisticated cyber-attacks.As a core component of ARL,Adversarial Tr...Adversarial Reinforcement Learning(ARL)models for intelligent devices and Network Intrusion Detection Systems(NIDS)improve systemresilience against sophisticated cyber-attacks.As a core component of ARL,Adversarial Training(AT)enables NIDS agents to discover and prevent newattack paths by exposing them to competing examples,thereby increasing detection accuracy,reducing False Positives(FPs),and enhancing network security.To develop robust decision-making capabilities for real-world network disruptions and hostile activity,NIDS agents are trained in adversarial scenarios to monitor the current state and notify management of any abnormal or malicious activity.The accuracy and timeliness of the IDS were crucial to the network’s availability and reliability at this time.This paper analyzes ARL applications in NIDS,revealing State-of-The-Art(SoTA)methodology,issues,and future research prospects.This includes Reinforcement Machine Learning(RML)-based NIDS,which enables an agent to interact with the environment to achieve a goal,andDeep Reinforcement Learning(DRL)-based NIDS,which can solve complex decision-making problems.Additionally,this survey study addresses cybersecurity adversarial circumstances and their importance for ARL and NIDS.Architectural design,RL algorithms,feature representation,and training methodologies are examined in the ARL-NIDS study.This comprehensive study evaluates ARL for intelligent NIDS research,benefiting cybersecurity researchers,practitioners,and policymakers.The report promotes cybersecurity defense research and innovation.展开更多
Convex feasibility problems are widely used in image reconstruction, sparse signal recovery, and other areas. This paper is devoted to considering a class of convex feasibility problem arising from sparse signal recov...Convex feasibility problems are widely used in image reconstruction, sparse signal recovery, and other areas. This paper is devoted to considering a class of convex feasibility problem arising from sparse signal recovery. We first derive the projection formulas for a vector onto the feasible sets. The centralized circumcentered-reflection method is designed to solve the convex feasibility problem. Some numerical experiments demonstrate the feasibility and effectiveness of the proposed algorithm, showing superior performance compared to conventional alternating projection methods.展开更多
Zero-click attacks represent an advanced cybersecurity threat,capable of compromising devices without user interaction.High-profile examples such as Pegasus,Simjacker,Bluebugging,and Bluesnarfing exploit hidden vulner...Zero-click attacks represent an advanced cybersecurity threat,capable of compromising devices without user interaction.High-profile examples such as Pegasus,Simjacker,Bluebugging,and Bluesnarfing exploit hidden vulnerabilities in software and communication protocols to silently gain access,exfiltrate data,and enable long-term surveillance.Their stealth and ability to evade traditional defenses make detection and mitigation highly challenging.This paper addresses these threats by systematically mapping the tactics and techniques of zero-click attacks using the MITRE ATT&CK framework,a widely adopted standard for modeling adversarial behavior.Through this mapping,we categorize real-world attack vectors and better understand how such attacks operate across the cyber-kill chain.To support threat detection efforts,we propose an Active Learning-based method to efficiently label the Pegasus spyware dataset in alignment with the MITRE ATT&CK framework.This approach reduces the effort of manually annotating data while improving the quality of the labeled data,which is essential to train robust cybersecurity models.In addition,our analysis highlights the structured execution paths of zero-click attacks and reveals gaps in current defense strategies.The findings emphasize the importance of forward-looking strategies such as continuous surveillance,dynamic threat profiling,and security education.By bridging zero-click attack analysis with the MITRE ATT&CK framework and leveraging machine learning for dataset annotation,this work provides a foundation for more accurate threat detection and the development of more resilient and structured cybersecurity frameworks.展开更多
Wave energy is a promising form of marine renewable energy that offers a sustainable pathway for electricity generation in coastal regions.Despite Malaysia’s extensive coastline,the exploration of wave energy in Sara...Wave energy is a promising form of marine renewable energy that offers a sustainable pathway for electricity generation in coastal regions.Despite Malaysia’s extensive coastline,the exploration of wave energy in Sarawak remains limited due to economic,technical,and environmental challenges that hinder its implementation.Compared to other renewable energy sources,wave energy is underutilized largely because of cost uncertainties and the lack of local performance data.This research aims to identify themost suitable coastal zone in Sarawak that achieves an optimal balance between energy potential,cost-effectiveness,and environmental impact,particularly in relation to infrastructure and regional development.The findings indicate that wave energy generation in Sarawak is technically feasible based on MOGA analysis.Among the studied sites,Bintulu emerged as the most balanced option,with a levelized cost of electricity(LCOE)of 0.778–0.864 USD/kWh and a CO_(2) emission factor as low as 0.019–0.020 CO_(2)/k Wh.Miri,while producing lower emissions than Sematan,recorded a higher LCOE of 1.045 USD/kWh with moderate emissions at 0.029 CO_(2)/kWh.Sematan,characterized by weaker wave conditions and higher installation penalties,resulted in the least favorable outcome,with an LCOE of 3.735 USD/kWh.Bintulu’s strategic location reduces CAPEX requirements,making it the most suitable site for large-scale wave energy deployment in Sarawak.展开更多
This paper focuses on the effects of external geometrical modifications on the aerodynamic characteristics of the MQ-1 predator Unmanned Combat Aerial Vehicle(UCAV)using computational fluid dynamics.The investigations...This paper focuses on the effects of external geometrical modifications on the aerodynamic characteristics of the MQ-1 predator Unmanned Combat Aerial Vehicle(UCAV)using computational fluid dynamics.The investigations are performed for 16 flight conditions at an altitude of7.6 km and at a constant speed of 56.32 m/s.Two models are analysed,namely the baseline model and the model with external geometrical modifications installed on it.Both the models are investigated for various angles of attack from-4°to 16°,angles of bank from 0°to 6°and angles of yaw from 0°to 4°.Due to the unavailability of any experimental(wind tunnel or flight test)data for this UCAV in the literature,a thorough verification of calculations process is presented to demonstrate confidence level in the numerical simulations.The analysis quantifies the loss of lift and increase in drag for the modified version of the MQ-1 predator UCAV along with the identification of stall conditions.Local improvement(in drag)of up to 96%has been obtained by relocating external modifications,whereas global drag force reduction of roughly 0.5%is observed.The effects of external geometrical modifications on the control surfaces indicate the blanking phenomenon and reduction in forces on the control surfaces that can reduce the aerodynamic performance of the UCAV.展开更多
CXCR1 is a G-protein coupled receptor, transducing signals from chemokines, in particular the interleukin-8 （1L8） molecules. This study combines homology modeling and molecular dynamics simulation methods to study t...CXCR1 is a G-protein coupled receptor, transducing signals from chemokines, in particular the interleukin-8 （1L8） molecules. This study combines homology modeling and molecular dynamics simulation methods to study the structure of CXCRI-IL8 complex. By using CXCR4-vMIP-II crystallography structure as the homologous template, CXCRI-IL8 complex structure was constructed, and then refined using all-atom molecular dynamics simulations. Through extensive simulations, CXCRI-IL8 binding poses were investigated in detail. Furthermore, the role of the N-terminal of CXCR1 receptor was studied by comparing four complex models differing in the N-terminal sequences. The results indicate that the receptor N-terminal affects the binding of IL8 significantly. With a shorter N-terminal domain, the binding of IL8 to CXCR1 becomes unstable. The homology modeling and simulations also reveal the key receptor-ligand residues involved in the electrostatic interactions known to be vital for complex formation.展开更多
Many datasets in E-commerce have rich information about items and users who purchase or rate them. This information can enable advanced machine learning algorithms to extract and assign user sentiments to various aspe...Many datasets in E-commerce have rich information about items and users who purchase or rate them. This information can enable advanced machine learning algorithms to extract and assign user sentiments to various aspects of the items thus leading to more sophisticated and justifiable recommendations. However, most Collaborative Filtering (CF) techniques rely mainly on the overall preferences of users toward items only. And there is lack of conceptual and computational framework that enables an understandable aspect-based AI approach to recommending items to users. In this paper, we propose concepts and computational tools that can sharpen the logic of recommendations and that rely on users’ sentiments along various aspects of items. These concepts include: The sentiment of a user towards a specific aspect of a specific item, the emphasis that a given user places on a specific aspect in general, the popularity and controversy of an aspect among groups of users, clusters of users emphasizing a given aspect, clusters of items that are popular among a group of users and so forth. The framework introduced in this study is developed in terms of user emphasis, aspect popularity, aspect controversy, and users and items similarity. Towards this end, we introduce the Aspect-Based Collaborative Filtering Toolbox (ABCFT), where the tools are all developed based on the three-index sentiment tensor with the indices being the user, item, and aspect. The toolbox computes solutions to the questions alluded to above. We illustrate the methodology using a hotel review dataset having around 6000 users, 400 hotels and 6 aspects.展开更多
The aim of the present study is to contribute to the knowledge about the functioning of the neuronal circuits. We built a mathematical-computational model using graph theory for a complex neurophysiological circuit co...The aim of the present study is to contribute to the knowledge about the functioning of the neuronal circuits. We built a mathematical-computational model using graph theory for a complex neurophysiological circuit consisting </span><span style="font-family:Verdana;">of a reverberating neuronal circuit and a parallel neuronal circuit, which</span><span style="font-family:Verdana;"> could </span><span style="font-family:Verdana;">be coupled. Implementing our model in C++ and applying</span><span style="font-family:Verdana;"> neurophysiological values found in the literature, we studied the discharge pattern of the reverberant circuit and the parallel circuit separately for the same input signal pattern, examining the influence of the refractory period and the synaptic delay on the respective output signal patterns. Then, the same study was performed for the complete circuit, in which the two circuits were coupled, and the parallel circuit could then influence the functioning of the reverberant. The results showed that the refractory period played an important role in forming the pattern of the output spectrum of a reverberating circuit. The inhibitory action of the parallel circuit was able to regulate the reverberation frequency, suggesting that parallel circuits may be involved in the control of reverberation circuits related to motive activities underlying precision tasks and perhaps underlying neural work processes and immediate memories.展开更多
Polymerases are protein enzymes that move along nucleic acid chains and catalyze template-based polymerization reactions during gene transcription and replication. The polymerases also substantially improve transcript...Polymerases are protein enzymes that move along nucleic acid chains and catalyze template-based polymerization reactions during gene transcription and replication. The polymerases also substantially improve transcription or replica- tion fidelity through the non-equilibrium enzymatic cycles. We briefly review computational efforts that have been made toward understanding mechano--chemical coupling and fidelity control mechanisms of the polymerase elongation. The polymerases are regarded as molecular information motors during the elongation process. It requires a full spectrum of computational approaches from multiple time and length scales to understand the full polymerase functional cycle. We stay away from quantum mechanics based approaches to the polymerase catalysis due to abundant former surveys, while ad- dressing statistical physics modeling approaches along with all-atom molecular dynamics simulation studies. We organize this review around our own modeling and simulation practices on a single subunit T7 RNA polymerase, and summarize commensurate studies on structurally similar DNA polymerases as well. For multi-subunit RNA polymerases that have been actively studied in recent years, we leave systematical reviews of the simulation achievements to latest computational chemistry surveys, while covering only representative studies published very recently, including our own work modeling structure-based elongation kinetic of yeast RNA polymerase II. In the end, we briefly go through physical modeling on elongation pauses and backtracking activities of the multi-subunit RNAPs. We emphasize on the fluctuation and control mechanisms of the polymerase actions, highlight the non-equilibrium nature of the operation system, and try to build some perspectives toward understanding the polymerase impacts from the single molecule level to a genome-wide scale.展开更多
A metamaterial absorber is computed numerically and measured experimentally in a 150-THz^300-THz range.The measured absorber achieves high absorption rate for both transverse electric（TE） and transverse magnetic（TM...A metamaterial absorber is computed numerically and measured experimentally in a 150-THz^300-THz range.The measured absorber achieves high absorption rate for both transverse electric（TE） and transverse magnetic（TM） polarizations at large angles of incidence.An absorption sensor scheme is proposed based on the measured absorber and the variations of surrounding media.Different surrounding media are applied to the surface of the absorption sensor（including air,water,and glucose solution）.Measured results show that high figure of merit（FOM） values are obtained for different surrounding media.The proposed sensor does not depend on the substrate,which means that it can be transplanted to different sensing platforms conveniently.展开更多
People power is the fundamental concept of democracy and power of the people is exercised though voting. People decide who should be elected to make decisions for them. However, if people do not properly participate i...People power is the fundamental concept of democracy and power of the people is exercised though voting. People decide who should be elected to make decisions for them. However, if people do not properly participate in the voting process and only two-thirds of all eligible voters participate in an election, the democratic institution loses its credibility and becomes vulnerable. This paper investigates various changes in voting institutions throughout the USAwith a simulation model that analyzes the efficacy of such methods to attain higher voter turnout.展开更多
Inhibition of 11βHSD1 （11-beta-hydroxysteroid dehydrogenase 1） is a promising strategy in drug treatment of diabetes. Several 11βHSDI inhibitors have been proposed; however, their selectivity to 11βHSD1 over its ...Inhibition of 11βHSD1 （11-beta-hydroxysteroid dehydrogenase 1） is a promising strategy in drug treatment of diabetes. Several 11βHSDI inhibitors have been proposed; however, their selectivity to 11βHSD1 over its isozyme 11βHSD2 （11-beta-hydroxysteroid dehydrogenase 2） has not been fully reported. The authors sought to provide a short list of top potent and selective compounds along with their detailed binding modes and pharmacophore models, Molecular docking was used for initial screening of a set of 23 potent inhibitors reported by previous experimental studies. After that, selected promising entries were reassessed by molecular dynamics simulations, followed by hydrogen bond analysis. Pharmacophore models of all drug candidates and binding modes of some selected drugs were analyzed. Among the 23 compounds, only four inhibitors were identified as potent and selective drug candidates. Binding energies, 3D pharmacophores and binding modes of the four compounds with 11βHSDI are also discussed in detail in this study.展开更多
Magnetics,ferroelectrics,and multiferroics have attracted great attentions because they are not only extremely im-portant for investigating fundamental physics,but also have important applications in information techn...Magnetics,ferroelectrics,and multiferroics have attracted great attentions because they are not only extremely im-portant for investigating fundamental physics,but also have important applications in information technology.Here,recent computational studies on magnetism and ferroelectricity are reviewed.We first give a brief introduction to magnets,fer-roelectrics,and multiferroics.Then,theoretical models and corresponding computational methods for investigating these materials are presented.In particular,a new method for computing the linear magnetoelectric coupling tensor without applying an external field in the first principle calculations is proposed for the first time.The functionalities of our home-made Property Analysis and Simulation Package for materials(PASP)and its applications in the field of magnetism and ferroelectricity are discussed.Finally,we summarize this review and give a perspective on possible directions of future computational studies on magnetism and ferroelectricity.展开更多
Recently, smoothed particle hydrodynamics (SPH) method has become popular in computational fluid dynamic and heat transfer simulation. The simplicity offered by this method made some complex system in physics such as ...Recently, smoothed particle hydrodynamics (SPH) method has become popular in computational fluid dynamic and heat transfer simulation. The simplicity offered by this method made some complex system in physics such as moving interface in multiphase flow, heat conductivity jumping in multiple material boundaries and many geometrical difficulties become relative easy to calculate. We will treat a relative easy example of melting process to test the method in solving fluid motion equation coupled by heat transfer process. The main heat transfer processes are caused by solid-liquid (medium to medium) heat diffusion and convection. System interaction with ambient temperature can be modeled by gas surrounding fluid-solid system. For the ambient temperature, we proposed surface particle heat transfer governed by convectional heat flux. Using local particle number density value as surface detection method, we applied cooling and heating to surface particle on the melting ice cube and water system. The simulation result is also verified by experiment.展开更多
Computational tools on top of first principle calculations have played an indispensable role in revealing the molecular details,thermodynamics,and kinetics in catalytic reactions.Here we proposed a highly efficient dy...Computational tools on top of first principle calculations have played an indispensable role in revealing the molecular details,thermodynamics,and kinetics in catalytic reactions.Here we proposed a highly efficient dynamic strategy for the calculation of thermodynamic and kinetic properties in heterogeneous catalysis on the basis of efficient potential energy surface(PES)and MD simulations.Taking CO adsorbate on Ru(0001)surface as the illustrative model system,we demonstrated the PES-based MD can efficiently generate reliable two-dimensional potential-of-mean-force(PMF)surfaces in a wide range of temperatures,and thus temperature-dependent thermodynamic properties can be obtained in a comprehensive investigation on the whole PMF surface.Moreover,MD offers an effective way to describe the surface kinetics such as adsorbate on-surface movement,which goes beyond the most popular static approach based on free energy barrier and transition state theory(TST).We further revealed that the dynamic strategy significantly improves the predictions of both thermodynamic and kinetic properties as compared to the popular ideal statistic mechanics approaches such as harmonic analysis and TST.It is expected that this accurate yet efficient dynamic strategy can be powerful in understanding mechanisms and reactivity of a catalytic surface system,and further guides the rational design of heterogeneous catalysts.展开更多
In this paper,we present local functional law of the iterated logarithm for Cs?rg?-Révész type increments of fractional Brownian motion.The results obtained extend works of Gantert[Ann.Probab.,1993,21(2):104...In this paper,we present local functional law of the iterated logarithm for Cs?rg?-Révész type increments of fractional Brownian motion.The results obtained extend works of Gantert[Ann.Probab.,1993,21(2):1045-1049]and Monrad and Rootzén[Probab.Theory Related Fields,1995,101(2):173-192].展开更多
In this paper,we propose a three-term conjugate gradient method for solving unconstrained optimization problems based on the Hestenes-Stiefel(HS)conjugate gradient method and Polak-Ribiere-Polyak(PRP)conjugate gradien...In this paper,we propose a three-term conjugate gradient method for solving unconstrained optimization problems based on the Hestenes-Stiefel(HS)conjugate gradient method and Polak-Ribiere-Polyak(PRP)conjugate gradient method.Under the condition of standard Wolfe line search,the proposed search direction is the descent direction.For general nonlinear functions,the method is globally convergent.Finally,numerical results show that the proposed method is efficient.展开更多
基金supported by the Higher Education and Science Committee of Armenia in the frames of the research projects 20TTSG-2F010, 23AA-2F033 and ANSEF (EN-matsc-2660) grant.
文摘Halide solid-state electrolytes have gained significant attention in recent years due to their high ionic conductivity,making them promising candidates for future all-solid-state batteries.Recent studies have identified numerous crystal structures with the Li_(3)MX_(6)composition,although many remain unexplored across various chemical systems.In this research,we developed a comprehensive method to examine all conceivable space groups and structures within theLi-M-X system,where M includes In,Ga,and La,and X includes F,Cl,Br,and 1.Our findings revealed two metastable structures:Li_(3)InF_(6)with P3c1 symmetry and Li_(3)InI_(6)with C2/c symmetry,exhibiting ionic conductivities of 0.55 and 2.18mS/cm at 300K,respectively.Notably,the trigonal symmetry of Li3InF6 demonstrates that high ionic conductivities are not limited to monoclinic structures but can also be achieved with trigonal symmetries.The electrochemical stability windows,mechanical properties,and reaction energies of these materials with known cathodes suggest their potential for use in all-solid-state batteries.Additionally,we predicted the stability of novel materials,including Li_(5)InCl_(8),Li_(5)InBr_(8),Li_(5)InI_(8),LiIn_(2)Cl_(9),LiIn_(2)Br_(9),and LiIn_(2)I_(9).
基金the support of the U.S. Department of Energy Vehicle Technologies Office
文摘Magnesium(Mg)alloys are ideal candidates for automotive applications due to their high strength to weight ratio,castability,recyclability etc.,however,they lack corrosion and oxidation resistance.Solid-state deposition techniques,such as cold spray,have been demonstrated to enhance their corrosion resistance as it relies on the severe plastic deformation of powder particles upon impact with the substrate to form a metallurgical bond with the substrate and within the coating.At cold sprayed interfaces,a heterogeneous microstructure is formed that includes some porosity,oxides and intermetallics which can significantly affect coating performance.Thus,establishing a direct correlation between the interface microstructure and its properties can aid in designing optimal cold spray parameters.In this study,we investigated the microstructure and mechanical properties of a zinc(Zn)coating deposited on a high pressure die cast(HPDC)AZ91 Mg substrate via high resolution scanning transmission electron microscopy,in situ micro-tensile testing,and finite element method(FEM)modeling.Micro-tensile pillars fabricated using the plasma focused ion beam(PFIB)successfully isolates the coating-substrate interface within the gauge length.The average bond strength of Zn-Mg interface was determined to be∼140 MPa with failure occurring partially at the interface and mostly into the coatings.A detailed microstructural characterization revealed evidence of a strong metallurgical bonding at the Zn-Mg interface and formation of the C14 MgZn_(2)laves phase interlayer resulting in a mixed mode of fracture during the micro-tensile experiments.FEM modeling reveals the stress distribution along the interfaces and suggests that a MgZn_(2)layer thickness between 200–400 nm is optimum to increase the bond strength and minimize the triaxiality.Such a site-specific interfacial analysis with correlative computational modeling provides crucial insight into the overall performance of cold spray interfaces.
基金supported by the National Natural Science Foundation of China (Grant Nos.T2325004 and 52161160330)the National Natural Science Foundation of China (Grants No.12504233)+2 种基金Advanced MaterialsNational Science and Technology Major Project (Grant No.2024ZD0606900)the Talent Hub for “AI+New Materials” Basic Researchthe Key Research and Development Program of Ningbo (Grant No.2025Z088)。
文摘The functional properties of glasses are governed by their formation history and the complex relaxation processes they undergo.However,under extreme conditions,glass behaviors are still elusive.In this study,we employ simulations with varied protocols to evaluate the effectiveness of different descriptors in predicting mechanical properties across both low-and high-pressure regimes.Our findings demonstrate that conventional structural and configurational descriptors fail to correlate with the mechanical response following pressure release,whereas the activation energy descriptor exhibits robust linearity with shear modulus after correcting for pressure effects.Notably,the soft mode parameter emerges as an ideal and computationally efficient alternative for capturing this mechanical behavior.These findings provide critical insights into the influence of pressure on glassy properties,integrating the distinct features of compressed glasses into a unified theoretical framework.
文摘Adversarial Reinforcement Learning(ARL)models for intelligent devices and Network Intrusion Detection Systems(NIDS)improve systemresilience against sophisticated cyber-attacks.As a core component of ARL,Adversarial Training(AT)enables NIDS agents to discover and prevent newattack paths by exposing them to competing examples,thereby increasing detection accuracy,reducing False Positives(FPs),and enhancing network security.To develop robust decision-making capabilities for real-world network disruptions and hostile activity,NIDS agents are trained in adversarial scenarios to monitor the current state and notify management of any abnormal or malicious activity.The accuracy and timeliness of the IDS were crucial to the network’s availability and reliability at this time.This paper analyzes ARL applications in NIDS,revealing State-of-The-Art(SoTA)methodology,issues,and future research prospects.This includes Reinforcement Machine Learning(RML)-based NIDS,which enables an agent to interact with the environment to achieve a goal,andDeep Reinforcement Learning(DRL)-based NIDS,which can solve complex decision-making problems.Additionally,this survey study addresses cybersecurity adversarial circumstances and their importance for ARL and NIDS.Architectural design,RL algorithms,feature representation,and training methodologies are examined in the ARL-NIDS study.This comprehensive study evaluates ARL for intelligent NIDS research,benefiting cybersecurity researchers,practitioners,and policymakers.The report promotes cybersecurity defense research and innovation.
基金Supported by the Natural Science Foundation of Guangxi Province(Grant Nos.2023GXNSFAA026067,2024GXN SFAA010521)the National Natural Science Foundation of China(Nos.12361079,12201149,12261026).
文摘Convex feasibility problems are widely used in image reconstruction, sparse signal recovery, and other areas. This paper is devoted to considering a class of convex feasibility problem arising from sparse signal recovery. We first derive the projection formulas for a vector onto the feasible sets. The centralized circumcentered-reflection method is designed to solve the convex feasibility problem. Some numerical experiments demonstrate the feasibility and effectiveness of the proposed algorithm, showing superior performance compared to conventional alternating projection methods.
文摘Zero-click attacks represent an advanced cybersecurity threat,capable of compromising devices without user interaction.High-profile examples such as Pegasus,Simjacker,Bluebugging,and Bluesnarfing exploit hidden vulnerabilities in software and communication protocols to silently gain access,exfiltrate data,and enable long-term surveillance.Their stealth and ability to evade traditional defenses make detection and mitigation highly challenging.This paper addresses these threats by systematically mapping the tactics and techniques of zero-click attacks using the MITRE ATT&CK framework,a widely adopted standard for modeling adversarial behavior.Through this mapping,we categorize real-world attack vectors and better understand how such attacks operate across the cyber-kill chain.To support threat detection efforts,we propose an Active Learning-based method to efficiently label the Pegasus spyware dataset in alignment with the MITRE ATT&CK framework.This approach reduces the effort of manually annotating data while improving the quality of the labeled data,which is essential to train robust cybersecurity models.In addition,our analysis highlights the structured execution paths of zero-click attacks and reveals gaps in current defense strategies.The findings emphasize the importance of forward-looking strategies such as continuous surveillance,dynamic threat profiling,and security education.By bridging zero-click attack analysis with the MITRE ATT&CK framework and leveraging machine learning for dataset annotation,this work provides a foundation for more accurate threat detection and the development of more resilient and structured cybersecurity frameworks.
基金supported by Swinburne University of Technology Sarawak Campus and Birmingham City University.
文摘Wave energy is a promising form of marine renewable energy that offers a sustainable pathway for electricity generation in coastal regions.Despite Malaysia’s extensive coastline,the exploration of wave energy in Sarawak remains limited due to economic,technical,and environmental challenges that hinder its implementation.Compared to other renewable energy sources,wave energy is underutilized largely because of cost uncertainties and the lack of local performance data.This research aims to identify themost suitable coastal zone in Sarawak that achieves an optimal balance between energy potential,cost-effectiveness,and environmental impact,particularly in relation to infrastructure and regional development.The findings indicate that wave energy generation in Sarawak is technically feasible based on MOGA analysis.Among the studied sites,Bintulu emerged as the most balanced option,with a levelized cost of electricity(LCOE)of 0.778–0.864 USD/kWh and a CO_(2) emission factor as low as 0.019–0.020 CO_(2)/k Wh.Miri,while producing lower emissions than Sematan,recorded a higher LCOE of 1.045 USD/kWh with moderate emissions at 0.029 CO_(2)/kWh.Sematan,characterized by weaker wave conditions and higher installation penalties,resulted in the least favorable outcome,with an LCOE of 3.735 USD/kWh.Bintulu’s strategic location reduces CAPEX requirements,making it the most suitable site for large-scale wave energy deployment in Sarawak.
文摘This paper focuses on the effects of external geometrical modifications on the aerodynamic characteristics of the MQ-1 predator Unmanned Combat Aerial Vehicle(UCAV)using computational fluid dynamics.The investigations are performed for 16 flight conditions at an altitude of7.6 km and at a constant speed of 56.32 m/s.Two models are analysed,namely the baseline model and the model with external geometrical modifications installed on it.Both the models are investigated for various angles of attack from-4°to 16°,angles of bank from 0°to 6°and angles of yaw from 0°to 4°.Due to the unavailability of any experimental(wind tunnel or flight test)data for this UCAV in the literature,a thorough verification of calculations process is presented to demonstrate confidence level in the numerical simulations.The analysis quantifies the loss of lift and increase in drag for the modified version of the MQ-1 predator UCAV along with the identification of stall conditions.Local improvement(in drag)of up to 96%has been obtained by relocating external modifications,whereas global drag force reduction of roughly 0.5%is observed.The effects of external geometrical modifications on the control surfaces indicate the blanking phenomenon and reduction in forces on the control surfaces that can reduce the aerodynamic performance of the UCAV.
基金Project supported by the National Natural Science Foundation of China(Grant Nos.11575021,U1530401,and U1430237)the National Research Foundation of Korea(Grant Nos.NRF-2017R1A2B2008483 and NRF-2016R1A6A3A04010213)
文摘CXCR1 is a G-protein coupled receptor, transducing signals from chemokines, in particular the interleukin-8 （1L8） molecules. This study combines homology modeling and molecular dynamics simulation methods to study the structure of CXCRI-IL8 complex. By using CXCR4-vMIP-II crystallography structure as the homologous template, CXCRI-IL8 complex structure was constructed, and then refined using all-atom molecular dynamics simulations. Through extensive simulations, CXCRI-IL8 binding poses were investigated in detail. Furthermore, the role of the N-terminal of CXCR1 receptor was studied by comparing four complex models differing in the N-terminal sequences. The results indicate that the receptor N-terminal affects the binding of IL8 significantly. With a shorter N-terminal domain, the binding of IL8 to CXCR1 becomes unstable. The homology modeling and simulations also reveal the key receptor-ligand residues involved in the electrostatic interactions known to be vital for complex formation.
文摘Many datasets in E-commerce have rich information about items and users who purchase or rate them. This information can enable advanced machine learning algorithms to extract and assign user sentiments to various aspects of the items thus leading to more sophisticated and justifiable recommendations. However, most Collaborative Filtering (CF) techniques rely mainly on the overall preferences of users toward items only. And there is lack of conceptual and computational framework that enables an understandable aspect-based AI approach to recommending items to users. In this paper, we propose concepts and computational tools that can sharpen the logic of recommendations and that rely on users’ sentiments along various aspects of items. These concepts include: The sentiment of a user towards a specific aspect of a specific item, the emphasis that a given user places on a specific aspect in general, the popularity and controversy of an aspect among groups of users, clusters of users emphasizing a given aspect, clusters of items that are popular among a group of users and so forth. The framework introduced in this study is developed in terms of user emphasis, aspect popularity, aspect controversy, and users and items similarity. Towards this end, we introduce the Aspect-Based Collaborative Filtering Toolbox (ABCFT), where the tools are all developed based on the three-index sentiment tensor with the indices being the user, item, and aspect. The toolbox computes solutions to the questions alluded to above. We illustrate the methodology using a hotel review dataset having around 6000 users, 400 hotels and 6 aspects.
文摘The aim of the present study is to contribute to the knowledge about the functioning of the neuronal circuits. We built a mathematical-computational model using graph theory for a complex neurophysiological circuit consisting </span><span style="font-family:Verdana;">of a reverberating neuronal circuit and a parallel neuronal circuit, which</span><span style="font-family:Verdana;"> could </span><span style="font-family:Verdana;">be coupled. Implementing our model in C++ and applying</span><span style="font-family:Verdana;"> neurophysiological values found in the literature, we studied the discharge pattern of the reverberant circuit and the parallel circuit separately for the same input signal pattern, examining the influence of the refractory period and the synaptic delay on the respective output signal patterns. Then, the same study was performed for the complete circuit, in which the two circuits were coupled, and the parallel circuit could then influence the functioning of the reverberant. The results showed that the refractory period played an important role in forming the pattern of the output spectrum of a reverberating circuit. The inhibitory action of the parallel circuit was able to regulate the reverberation frequency, suggesting that parallel circuits may be involved in the control of reverberation circuits related to motive activities underlying precision tasks and perhaps underlying neural work processes and immediate memories.
基金supported by the National Natural Science Foundation(Grant No.11275022)
文摘Polymerases are protein enzymes that move along nucleic acid chains and catalyze template-based polymerization reactions during gene transcription and replication. The polymerases also substantially improve transcription or replica- tion fidelity through the non-equilibrium enzymatic cycles. We briefly review computational efforts that have been made toward understanding mechano--chemical coupling and fidelity control mechanisms of the polymerase elongation. The polymerases are regarded as molecular information motors during the elongation process. It requires a full spectrum of computational approaches from multiple time and length scales to understand the full polymerase functional cycle. We stay away from quantum mechanics based approaches to the polymerase catalysis due to abundant former surveys, while ad- dressing statistical physics modeling approaches along with all-atom molecular dynamics simulation studies. We organize this review around our own modeling and simulation practices on a single subunit T7 RNA polymerase, and summarize commensurate studies on structurally similar DNA polymerases as well. For multi-subunit RNA polymerases that have been actively studied in recent years, we leave systematical reviews of the simulation achievements to latest computational chemistry surveys, while covering only representative studies published very recently, including our own work modeling structure-based elongation kinetic of yeast RNA polymerase II. In the end, we briefly go through physical modeling on elongation pauses and backtracking activities of the multi-subunit RNAPs. We emphasize on the fluctuation and control mechanisms of the polymerase actions, highlight the non-equilibrium nature of the operation system, and try to build some perspectives toward understanding the polymerase impacts from the single molecule level to a genome-wide scale.
基金Project supported by the National Natural Science Foundation of China(Grant No.11547196)the Key Projects of Sichuan Provincial Department of Education,China(Grant No.15ZA0224)+1 种基金the Project of Sichuan Provincial Key Laboratory of Artificial Intelligence,China(Grant No.2014RYJ01)the Key Plan Projects of Science and Technology of Zigong,China(Grant No.2016CXM05)
文摘A metamaterial absorber is computed numerically and measured experimentally in a 150-THz^300-THz range.The measured absorber achieves high absorption rate for both transverse electric（TE） and transverse magnetic（TM） polarizations at large angles of incidence.An absorption sensor scheme is proposed based on the measured absorber and the variations of surrounding media.Different surrounding media are applied to the surface of the absorption sensor（including air,water,and glucose solution）.Measured results show that high figure of merit（FOM） values are obtained for different surrounding media.The proposed sensor does not depend on the substrate,which means that it can be transplanted to different sensing platforms conveniently.
文摘People power is the fundamental concept of democracy and power of the people is exercised though voting. People decide who should be elected to make decisions for them. However, if people do not properly participate in the voting process and only two-thirds of all eligible voters participate in an election, the democratic institution loses its credibility and becomes vulnerable. This paper investigates various changes in voting institutions throughout the USAwith a simulation model that analyzes the efficacy of such methods to attain higher voter turnout.
文摘Inhibition of 11βHSD1 （11-beta-hydroxysteroid dehydrogenase 1） is a promising strategy in drug treatment of diabetes. Several 11βHSDI inhibitors have been proposed; however, their selectivity to 11βHSD1 over its isozyme 11βHSD2 （11-beta-hydroxysteroid dehydrogenase 2） has not been fully reported. The authors sought to provide a short list of top potent and selective compounds along with their detailed binding modes and pharmacophore models, Molecular docking was used for initial screening of a set of 23 potent inhibitors reported by previous experimental studies. After that, selected promising entries were reassessed by molecular dynamics simulations, followed by hydrogen bond analysis. Pharmacophore models of all drug candidates and binding modes of some selected drugs were analyzed. Among the 23 compounds, only four inhibitors were identified as potent and selective drug candidates. Binding energies, 3D pharmacophores and binding modes of the four compounds with 11βHSDI are also discussed in detail in this study.
基金Project supported by the National Natural Science Foundation of China(Grant Nos.11825403,12188101,and 11804138)the Natural Science Foundation of Anhui Province,China(Grant No.1908085MA10)the Opening Foundation of the State Key Laboratory of Surface Physics of Fudan University(Grant No.KF2019_07)。
文摘Magnetics,ferroelectrics,and multiferroics have attracted great attentions because they are not only extremely im-portant for investigating fundamental physics,but also have important applications in information technology.Here,recent computational studies on magnetism and ferroelectricity are reviewed.We first give a brief introduction to magnets,fer-roelectrics,and multiferroics.Then,theoretical models and corresponding computational methods for investigating these materials are presented.In particular,a new method for computing the linear magnetoelectric coupling tensor without applying an external field in the first principle calculations is proposed for the first time.The functionalities of our home-made Property Analysis and Simulation Package for materials(PASP)and its applications in the field of magnetism and ferroelectricity are discussed.Finally,we summarize this review and give a perspective on possible directions of future computational studies on magnetism and ferroelectricity.
文摘Recently, smoothed particle hydrodynamics (SPH) method has become popular in computational fluid dynamic and heat transfer simulation. The simplicity offered by this method made some complex system in physics such as moving interface in multiphase flow, heat conductivity jumping in multiple material boundaries and many geometrical difficulties become relative easy to calculate. We will treat a relative easy example of melting process to test the method in solving fluid motion equation coupled by heat transfer process. The main heat transfer processes are caused by solid-liquid (medium to medium) heat diffusion and convection. System interaction with ambient temperature can be modeled by gas surrounding fluid-solid system. For the ambient temperature, we proposed surface particle heat transfer governed by convectional heat flux. Using local particle number density value as surface detection method, we applied cooling and heating to surface particle on the melting ice cube and water system. The simulation result is also verified by experiment.
基金financially supported by Fujian Science&Technology Innovation Laboratory for Optoelectronic Information of China(No.2021ZR109)the National Natural Science Foundation of China(Nos.21973094,22173104,22173105)the Opening Project of PCOSS of Xiamen University(No.201908)。
文摘Computational tools on top of first principle calculations have played an indispensable role in revealing the molecular details,thermodynamics,and kinetics in catalytic reactions.Here we proposed a highly efficient dynamic strategy for the calculation of thermodynamic and kinetic properties in heterogeneous catalysis on the basis of efficient potential energy surface(PES)and MD simulations.Taking CO adsorbate on Ru(0001)surface as the illustrative model system,we demonstrated the PES-based MD can efficiently generate reliable two-dimensional potential-of-mean-force(PMF)surfaces in a wide range of temperatures,and thus temperature-dependent thermodynamic properties can be obtained in a comprehensive investigation on the whole PMF surface.Moreover,MD offers an effective way to describe the surface kinetics such as adsorbate on-surface movement,which goes beyond the most popular static approach based on free energy barrier and transition state theory(TST).We further revealed that the dynamic strategy significantly improves the predictions of both thermodynamic and kinetic properties as compared to the popular ideal statistic mechanics approaches such as harmonic analysis and TST.It is expected that this accurate yet efficient dynamic strategy can be powerful in understanding mechanisms and reactivity of a catalytic surface system,and further guides the rational design of heterogeneous catalysts.
基金Supported by NSFC(Nos.11661025,12161024)Natural Science Foundation of Guangxi(Nos.2020GXNSFAA159118,2021GXNSFAA196045)+2 种基金Guangxi Science and Technology Project(No.Guike AD20297006)Training Program for 1000 Young and Middle-aged Cadre Teachers in Universities of GuangxiNational College Student's Innovation and Entrepreneurship Training Program(No.202110595049)。
文摘In this paper,we present local functional law of the iterated logarithm for Cs?rg?-Révész type increments of fractional Brownian motion.The results obtained extend works of Gantert[Ann.Probab.,1993,21(2):1045-1049]and Monrad and Rootzén[Probab.Theory Related Fields,1995,101(2):173-192].
基金Supported by the Science and Technology Project of Guangxi(Guike AD23023002)。
文摘In this paper,we propose a three-term conjugate gradient method for solving unconstrained optimization problems based on the Hestenes-Stiefel(HS)conjugate gradient method and Polak-Ribiere-Polyak(PRP)conjugate gradient method.Under the condition of standard Wolfe line search,the proposed search direction is the descent direction.For general nonlinear functions,the method is globally convergent.Finally,numerical results show that the proposed method is efficient.
