Protecting rare,endemic,and endangered species requires careful habitat evaluation to set strategic plans for mitigating biodiversity loss and prioritizing conservation goals.The endangered Asian elephant(Elephas maxi...Protecting rare,endemic,and endangered species requires careful habitat evaluation to set strategic plans for mitigating biodiversity loss and prioritizing conservation goals.The endangered Asian elephant(Elephas maximus)exemplifies the urgent need for targeted conservation efforts,given its challenging habitat conditions.This study examines the impact of climate and land use changes on the suitable habitat distribution of Asian elephants.Utilizing ten predictor variables,including climatic,topographic,and land use data,and employing six ensemble Species Distribution Models(SDMs)alongside Coupled Model Intercomparison Project Phase 6 data,the study estimates spatial changes and potential habitat expansions for Asian elephants across Tropical Asia.Occurrence data were gathered from field surveys in Bangladesh and the Global Biodiversity Information Facility database for Sri Lanka,Myanmar,Bhutan,Cambodia,India,Laos,Nepal,Thailand,and Vietnam.To evaluate habitat suitability,the analysis considered two distinct socioeconomic pathways(SSP 245 and SSP 370)across two future periods(2041–2060 and 2061–2080).Results reveal a strong correlation between isothermality and habitat suitability,with higher isothermality enhancing the habitat conditions for Asian elephants.Among the SDMs,the random forest model demonstrated the highest performance.Projected scenarios indicate significant habitat fragmentation by 2061–2080,heightening the risk of species’vulnerability.Specifically,in SSP 245,the north zone is anticipated to experience a higher rate of habitat loss(588.443 km^(2)/year),whereas,in SSP 370,the west zone is expected to face a more severe rate of habitat loss(1,798.56 km^(2)/year).The eastern zone,which includes Cambodia,Vietnam,Laos,Thailand,and southern Myanmar,is notably at risk,with an estimated habitat loss of 14.8 million hectares.Anticipated changes in climate and land cover will impact the availability of essential resources such as food,water,and shelter,potentially driving the species to relocate to different elevation belts.The outcomes of the consensus map highlighting critical habitats and future fragmentation scenarios will support effective conservation and management strategies for the species.展开更多
Despite existing curative options like surgical removal,tissue destruction techniques,and liver transplantation for early-stage hepatocellular carcinoma(HCC),the rising incidence and mortality rates of this global hea...Despite existing curative options like surgical removal,tissue destruction techniques,and liver transplantation for early-stage hepatocellular carcinoma(HCC),the rising incidence and mortality rates of this global health burden necessitate continuous exploration of novel therapeutic strategies.This review critically assesses the dynamic treatment panorama for HCC,focusing specifically on the burgeoning role of immunotherapy in two key contexts:early-stage HCC and downstaging advanced HCC to facilitate liver transplant candidacy.It delves into the unique immunobiology of the liver and HCC,highlighting tumor-mediated immune evasion mechanisms.Analyzing the diverse immunothera-peutic approaches including checkpoint inhibitors,cytokine modulators,vaccines,oncolytic viruses,antigen-targeting antibodies,and adoptive cell therapy,this review acknowledges the limitations of current diagnostic markers alpha-fetoprotein and glypican-3 and emphasizes the need for novel biomarkers for patient selection and treatment monitoring.Exploring the rationale for neoadjuvant and adjuvant immunotherapy in early-stage HCC,current research is actively exploring the safety and effectiveness of diverse immunothera-peutic approaches through ongoing clinical trials.The review further explores the potential benefits and challenges of combining immunotherapy and liver transplant,highlighting the need for careful patient selection,meticulous monitoring,and novel strategies to mitigate post-transplant complications.Finally,this review delves into the latest findings from the clinical research landscape and future directions in HCC management,paving the way for optimizing treatment strategies and improving long-term survival rates for patients with this challenging malignancy.展开更多
As the world grapples with increasing environmental challenges,innovative technologies are essential for promoting sustainability and accountability.This study examined the impact of environmental performance indices(...As the world grapples with increasing environmental challenges,innovative technologies are essential for promoting sustainability and accountability.This study examined the impact of environmental performance indices(EPIs)on the growth and investment trends of blockchain-based sustainability-focused companies in 15 countries(Belgium,Czechia,Denmark,Estonia,Finland,France,Germany,Italy,Norway,Poland,Sweden,Spain,Switzerland,the United Kingdom,and the United States)from Europe and America during 2010-2022.This study used the negative binomial regression model to assess the relationship between EPIs and blockchain-based sustainability-focused companies based on the data from the CrunchBase and EarthData.Results indicated that in ecosystem vitality,national terrestrial biome protection efforts were negatively correlated the formation of blockchain-based sustainability-focused companies,while global terrestrial biome protection efforts and marine protected areas had a positive impact on the formation of these companies and the number of funding rounds.In environmental health,PM2.5 exposure had a positive impact on the number of funding rounds.Conversely,pollutants such as sulfur dioxide(SO_(2))and ocean plastics deterred the formation of blockchain-based sustainability-focused companies and reduced the number of funding rounds.In climate change performance,adjusted emission growth rate for carbon dioxide(CO_(2)),adjusted emission growth rate for F-gases,and adjusted emission growth rate for black carbon had a significantly positive impact on the formation of blockchain-based sustainability-focused companies.Conversely,adjusted emission growth rate for Nitrous Oxide(N_(2)O)and projected greenhouse gas emissions in 2050 negatively affected the formation of these companies.These findings highlight the dual role of EPIs as driving factors and barriers in the development and investment of blockchain-based sustainability-focused companies in countries from Europe and America.展开更多
Carbon(δ^(13)C)and oxygen(δ^(18)O)isotope compositions are considered indicators of the effect of water conditions on plant photosynthesis(δ^(13)C)and transpiration(δ^(18)O).Hydrogen isotope composition(δ^(2)H),t...Carbon(δ^(13)C)and oxygen(δ^(18)O)isotope compositions are considered indicators of the effect of water conditions on plant photosynthesis(δ^(13)C)and transpiration(δ^(18)O).Hydrogen isotope composition(δ^(2)H),tracks transpiration like δ^(18)O,while also affected by the organ trophism.Such dual behaviour,together with its highly exchangeable nature have hindered the use of δ^(2)H to assess plant performance.We compared the effect of contrasting water pressure deficit(VPD)on the signatures of the three isotopes across different durum wheat parts.Plants were hydroponically grown under conditions,differing in VPD and the isotopic labelling of the nutrient solution(natural abundance versus δ^(2)H and δ^(18)O-enriched)and isotopic signatures analysed at mid-grain filling.Higher VPD increased plant-matter δ^(13)C,δ^(2)H,and δ^(18)O,in accordance with atmospheric drought decreasing stomatal conductance and transpiration.Moreover,positive correlations within and across organs betweenδ2H and δ^(18)O of organicmatter and water further supported a similar source of variation related to evaporation.However,δ^(2)H was depleted in photoautotrophic(leaves and glumes),enriched in mixotrophic(peduncle and awns)and even more in heterotrophic(grains)organs.This study highlights the similarities and differences in mechanisms determining δ^(2)H,δ^(18)O,and δ^(13)C through the interactions of these isotopes with VPD and plant organs.展开更多
Background:Gene expression profiling plays a key role in cancer research,but its high dimensionality and redundancy pose challenges for effective analysis.Feature selection and robust classification are critical for i...Background:Gene expression profiling plays a key role in cancer research,but its high dimensionality and redundancy pose challenges for effective analysis.Feature selection and robust classification are critical for improving predictive performance,while explainable machine learning techniques support transparency and biomarker discovery.Methods:To propose a hybrid explainable machine learning framework that combines stability-guided multi-source(SGMS)feature selection with classification models for gene expression-based cancer prediction and biomarker identification.SGMS integrates Mutual Information,F-statistic,and random forest(RF)importance to select informative genes.These features are used to train classifiers,including novel elasticnet logistic regression(NEN-LR),RF,and Support Vector Machine(SVM).Performance is evaluated using accuracy,precision,recall,F1-score,and Matthews correlation coefficient(MCC).SHapley Additive exPlanations(SHAP)values are used to interpret gene-level contributions,and co-expression networks help identify functional gene modules.Results:The proposed NEN-LR classifier achieved the highest performance with 99.8%accuracy,99.9%precision,and 0.997 MCC using the top 200 SGMS-selected genes.Biomarker discovery identified both class-specific and shared genes across five cancer types,with top genes like gene_230,gene_5380,and gene_18570 consistently appearing across multiple classes.Visualization tools,including heatmaps,Venn diagrams,and co-expression networks,were used to interpret expression dynamics and regulatory patterns,enhancing the biological relevance of findings.SHAP analysis revealed top biomarkers with strong predictive influence,while co-expression clustering uncovered biologically meaningful gene modules.Other models also showed marked improvement using SGMS-selected features.Conclusion:The proposed framework successfully integrates feature selection,interpretable classification,and biomarker discovery,providing a powerful tool for precision oncology and molecular diagnostics.展开更多
We extend a semiclassical numerical method, bosonic auxiliary-field Monte Carlo, to quantum spin systems. This method breaks the lattice into clusters, solves each cluster precisely and couples them with classical aux...We extend a semiclassical numerical method, bosonic auxiliary-field Monte Carlo, to quantum spin systems. This method breaks the lattice into clusters, solves each cluster precisely and couples them with classical auxiliary fields through classical Monte Carlo simulation. We test the method with antiferromagnetic spin models in one-dimensional chains, square lattices and triangular lattices, and obtain reasonable results at finite temperatures. This algorithm builds a bridge between classical Monte Carlo method and quantum methods. The algorithm can be improved with either progress in classical Monte Carlo sampling or the development of quantum solvers, and can also be further applied to systems with different lattices or interactions.展开更多
Dengue is an arboviral disease caused by the dengue virus,with 390 million infections reported annually worldwide.It is classified into two categories:dengue without or with warning signs and severe dengue.[1]Given th...Dengue is an arboviral disease caused by the dengue virus,with 390 million infections reported annually worldwide.It is classified into two categories:dengue without or with warning signs and severe dengue.[1]Given the moderate efficacy of the dengue vaccine,[2]there is an urgent necessity to design host-directed therapeutic strategies,such as the repurposing of FDA-approved drugs,to combat dengue virus infection.展开更多
This study investigates the transmission dynamics of conjunctivitis using stochastic delay differential equations(SDDEs).A delayed stochastic model is formulated by dividing the population into five distinct compartme...This study investigates the transmission dynamics of conjunctivitis using stochastic delay differential equations(SDDEs).A delayed stochastic model is formulated by dividing the population into five distinct compartments:susceptible,exposed,infected,environmental irritants,and recovered individuals.The model undergoes thorough analytical examination,addressing key dynamical properties including positivity,boundedness,existence,and uniqueness of solutions.Local and global stability around the equilibrium points is studied with respect to the basic reproduction number.The existence of a unique global positive solution for the stochastic delayed model is established.In addition,a stochastic nonstandard finite difference scheme is developed,which is shown to be dynamically consistent and convergent toward the equilibrium states.The scheme preserves the essential qualitative features of the model and demonstrates improved performance when compared to existing numerical methods.Finally,the impact of time delays and stochastic fluctuations on the susceptible and infected populations is analyzed.展开更多
In the present study,two-layered stainless steel-copper composites with a thickness of 50μm were initially subjected to annealing at 800,900 and 1000℃for 5 min,respectively,to achieve diverse microstructural feature...In the present study,two-layered stainless steel-copper composites with a thickness of 50μm were initially subjected to annealing at 800,900 and 1000℃for 5 min,respectively,to achieve diverse microstructural features.Then the influence of annealing temperature on the formability of stainless steel-copper composites and the quality of micro composite cups manufactured by micro deep drawing(MDD)were investigated,and the underlying mechanism was analyzed.Three finite element(FE)models,including basic FE model,Voronoi FE model and surface morphological FE model,were developed to analyze the forming performance of stainless steel-copper composites during MDD.The results show that the stainless steel-copper composites annealed at 900℃possess the best plasticity owing to the homogeneous and refined microstructure in both stainless steel and copper matrixes,and the micro composite cup with specimen annealed at 900℃exhibits a uniform wall thickness as well as high surface quality with the fewest wrinkles.The results obtained from the surface morphological FE model considering material inhomogeneity and surface morphology of the composites are the closest to the experimental results compared to the basic and Voronoi FE model.During MDD process,the drawing forces decrease with increasing annealing temperature as a consequence of the strength reduction.展开更多
We review recent experimental and theoretical results for the electromagnetic form factors of hyperons(Y)in the timelike region,accessible in the reactions e^(+)e^(-)→YY.Specifically,we focus on the final statesΛΛ...We review recent experimental and theoretical results for the electromagnetic form factors of hyperons(Y)in the timelike region,accessible in the reactions e^(+)e^(-)→YY.Specifically,we focus on the final statesΛΛ,ΛΣ^(0)/Λ,Σ^(0)Λ,■■,andΩΩ.TheΛ_(c)Λ_(c)system is also discussed.展开更多
Hypernuclei,nuclei containing one or more hyperons,serve as unique laboratories for probing the non-perturbative quantum chromodynamics(QCD).Recent progress in hypernuclear physics,driven by advanced experimental tech...Hypernuclei,nuclei containing one or more hyperons,serve as unique laboratories for probing the non-perturbative quantum chromodynamics(QCD).Recent progress in hypernuclear physics,driven by advanced experimental techniques and theoretical innovations,is briefly reviewed with a focus on key findings and unresolved challenges,such as the precise determination of the hypertriton binding energy,investigations of charge symmetry breaking in mirror hypernuclei,and the search for exotic systems,including the neutral nnΛstate.Experimental breakthroughs,including invariant-mass analyses and femtoscopy studies in heavy-ion collisions,as well as high-resolutionγ-spectroscopy,have enabled precise studies of light hypernuclei and offered critical insights into the hyperon–nucleon interaction.Theoretical progress,including ab initio calculations based on chiral effective field theory and lattice QCD,has further enhanced our understanding of hyperon–nucleon and hyperon–hyperon interactions.展开更多
With the development of radioactive-ion-beam facilities,many exotic phenomena have been discovered or predicted in the nuclei far from the stability line,including cluster structure,shell structure,deformed halo,and s...With the development of radioactive-ion-beam facilities,many exotic phenomena have been discovered or predicted in the nuclei far from the stability line,including cluster structure,shell structure,deformed halo,and shape decoupling effects.The study of exotic nuclear phenomena is at the frontier of nuclear physics nowadays.The covariant density functional theory(CDFT)is one of the most successful microscopic models in describing the structure of nuclei in almost the whole nuclear chart.Within the framework of CDFT,toward a proper treatment of deformation and weak binding,the deformed relativistic Hartree-Bogoliubov theory in continuum(DRHBc)has been developed.In this contribution,we review the applications and extensions of the DRHBc theory to the study of exotic nuclei.The DRHBc theory has been used to investigate the deformed halos in B,C,Ne,Na,and Mg isotopes and the theoretical descriptions are reasonably consistent with available data.A DRHBc Mass Table Collaboration has been founded,aiming at a high precision nuclear mass table with deformation and continuum effects included,which is underway.By implementing the angular momentum projection based on the DRHBc theory,the rotational excitations of deformed halos have been investigated and it is shown that the deformed halos and shape decoupling effects also exist in the low-lying rotational excitation states of deformed halo nuclei.展开更多
This study investigates the influence of electropolymerization conditions on the deposition of polypyrrole(PPy)onto cotton-derived carbon fiber(CF)modified with reduced graphene oxide(rGO)for supercapacitors applicati...This study investigates the influence of electropolymerization conditions on the deposition of polypyrrole(PPy)onto cotton-derived carbon fiber(CF)modified with reduced graphene oxide(rGO)for supercapacitors applications using an experimental/theorical approach.The surface modification of CF by rGO and/or by PPy electrodeposited at 10,25 and 50 mV s^(-1) was thoroughly examined physicochemical and electrochemically.Composite electrodes comprising CF-rGo-PPy,synthesized via electropolymerization at 25 mV s^(-1),demonstrated a remarkable increase in capacitance,showcasing~742 F g^(-1) compared to 153 F g^(-1) for CF.SEM,N_(2)-surface area,XPS,and TD-DFT approach revealed that the higher capacitance observed in CF-rGo-PPy electrodes underscores the influence of morphology and charged nitrogen species on the electrochemical performance of these modified electrodes.Notably,this electrode material achieves a specific capacitance retention of~96%of their initial capacitance after 10000 cycles at 0.5 A g^(-1) measured in a two-electrodes cell configuration.This work also discusses the influence of the scan rate used for pyrrole electropolymerization on the pseudocapacitance contribution of PPy and its possible effect on the porosity of the material.These results highlight the importance of appropriate electropolymerization conditions that allow obtaining the synergistic effect between CF,rGO and PPy.展开更多
The urban land-use allocation problem is a spatial optimization problem that allocates optimum land-uses to specific land units in urban areas.This problem is an NP(nondeterministic polynomial time)-hard problem becau...The urban land-use allocation problem is a spatial optimization problem that allocates optimum land-uses to specific land units in urban areas.This problem is an NP(nondeterministic polynomial time)-hard problem because of involving many objective functions,many constraints,and complex search space.Moreover,this subject is an important issue in smart cities and newly developed areas of cities to achieve a sustainable arrangement of land-uses.Different types ofMulti-Objective Optimization Algorithms(MOOAs)based on Artificial Intelligence(AI)have been frequently employed,but their ability and performance have not been evaluated and compared properly.This paper aims to employ and compare three commonly used MOOAs i.e.NSGA-II,MOPSO,and MOEA/D in urban land-use allocation problems.Selected algorithms belong to different categories of MOOAs family to investigate their advantage and disadvantages.The objective functions of this study are compatibility,dependency,suitability,and compactness of land-uses and the constraint is compensating of Per-Capita demand in the urban environment.Evaluation of results is based on the dispersion of the solutions,diversity of the solutions’space,and comparing the number of dominant solutions in Pareto-Fronts.The results showed that all three algorithms improved the objective functions related to the current arrangement of the land-uses.However,the run time of NSGA-II is the worst,related to the Diversity Metric(DM)which represents the regularity of the distance between solutions at the highest degree.Moreover,MOPSO provides the best Scattering Diversity Metric(SDM)which shows the diversity of solutions in the solution space.Furthermore,In terms of algorithm execution time,MOEA/D performed better than the other two.So,Decision-makers should consider different aspects in choosing the appropriate MOOA for land-use management problems.展开更多
The chemical composition and thermal properties of natural fibers are the most critical variables that determine the overall properties of the fibers and influence their processing and use in different sustainable app...The chemical composition and thermal properties of natural fibers are the most critical variables that determine the overall properties of the fibers and influence their processing and use in different sustainable applications,such as their conversion into bioenergy and biocomposites.Their thermal and mechanical properties can be estimated by evaluating the content of cellulose,lignin,and other extractives in the fibers.In this research work,the chemical composition and thermal properties of three fibers,namely bagasse,kenaf bast fibers,and cotton stalks,were evaluated to assess their potential utilization in producing biocomposites and bioenergy materials.The chemical composition analysis followed the Technical Association of the Pulp and Paper Industry Standards(TAPPI)methods.The total phenol content was quantified using the Folin-Ciocalteu method,while Fourier Transform Infrared Spectroscopy(FTIR)was employed to assess the light absorption by the bonds.To evaluate thermal stability and higher heating values,Thermogravimetric Analysis(TGA),Differential Scanning Calorimetry(DSC),and bomb calorimetry were performed.The chemical analysis revealed that bagasse contained 50.6%cellulose and 21.6%lignin,kenaf bast fibers had 58.5%cellulose and 10%lignin,and cotton stalks exhibited 40.3%cellulose and 21.3%lignin.The FTIR curves demonstrated a notable similarity among the fibers.The TGA analysis showed degradation temperatures of 321°C for bagasse,354°C for kenaf bast fibers,and 289°C for cotton stalks.The DSC analysis revealed glass transition temperatures of 81°C for bagasse,66.3°C for cotton stalks,and 64.5°C for kenaf bast fibers.The higher heating values were measured as 17.3,16.6 and 17.1 MJ/kg for bagasse,kenaf bast fibers,and cotton stalks,respectively.The three fibers have a high potential for biocomposites and bioenergy material manufacturing.展开更多
In the present work,seven Mg-Zn-Ag alloys with the nominal composition of Mg_(96-x)Zn_(x)Ag_(4)(x=17,20,23,26,29,32,35 in at.%)were prepared by induction melting and single-roller melt-spinning.The X-ray diffraction(X...In the present work,seven Mg-Zn-Ag alloys with the nominal composition of Mg_(96-x)Zn_(x)Ag_(4)(x=17,20,23,26,29,32,35 in at.%)were prepared by induction melting and single-roller melt-spinning.The X-ray diffraction(XRD)analyses indicate the metallic glasses with three composition of Mg_(73)Zn_(23)Ag_(4),Mg_(70)Zn_(26)Ag_(4),and Mg_(67)Zn_(29)Ag_(4)were obtained successfully.The differential scanning calorimetry(DSC)measurement was used to obtain the characteristic temperature of Mg-Zn-Ag metallic glasses for the glass-forming ability analysis.The maximum glass transition temperature(Trg)was found to be 0.525 with a composition close to Mg_(67)Zn_(29)Ag_(4),which results in the best glass-forming ability.Moreover,the immersion test in simulated body fluid(SBF)demonstrate the relative homogeneous corrosion behavior of the Mg-Zn-Ag metallic glasses.The corrosion rate of Mg-Zn-Ag metallic glasses in SBF solution decreases with the increase of Zn content.The sample Mg_(67)Zn_(29)Ag_(4)has the lowest corrosion rate of 0.19mm/yr,which could meet the clinical application requirement well.The in vitro cell experiments show that the Madin-Darby canine kidney(MDCK)cells cultured in sample Mg_(67)Zn_(29)Ag_(4)and its extraction medium have higher activity.However,the Mg-Zn-Ag metallic glasses exhibit obvious inhibitory effect on human rhabdomyosarcoma(RD)tumor cells.The present investigations on the glass-forming ability,corrosion behavior,cytocompatibility and tumor inhibition function of the Mg-Zn-Ag based metallic glass could reveal their biomedical application possibility.展开更多
In time-variant reliability problems,there are a lot of uncertain variables from different sources.Therefore,it is important to consider these uncertainties in engineering.In addition,time-variant reliability problems...In time-variant reliability problems,there are a lot of uncertain variables from different sources.Therefore,it is important to consider these uncertainties in engineering.In addition,time-variant reliability problems typically involve a complexmultilevel nested optimization problem,which can result in an enormous amount of computation.To this end,this paper studies the time-variant reliability evaluation of structures with stochastic and bounded uncertainties using a mixed probability and convex set model.In this method,the stochastic process of a limit-state function with mixed uncertain parameters is first discretized and then converted into a timeindependent reliability problem.Further,to solve the double nested optimization problem in hybrid reliability calculation,an efficient iterative scheme is designed in standard uncertainty space to determine the most probable point(MPP).The limit state function is linearized at these points,and an innovative random variable is defined to solve the equivalent static reliability analysis model.The effectiveness of the proposed method is verified by two benchmark numerical examples and a practical engineering problem.展开更多
Neural networks possess formidable representational power,rendering them invaluable in solving complex quantum many-body systems.While they excel at analyzing static solutions,nonequilibrium processes,including critic...Neural networks possess formidable representational power,rendering them invaluable in solving complex quantum many-body systems.While they excel at analyzing static solutions,nonequilibrium processes,including critical dynamics during a quantum phase transition,pose a greater challenge for neural networks.To address this,we utilize neural networks and machine learning algorithms to investigate time evolutions,universal statistics,and correlations of topological defects in a one-dimensional transverse-field quantum Ising model.Specifically,our analysis involves computing the energy of the system during a quantum phase transition following a linear quench of the transverse magnetic field strength.The excitation energies satisfy a power-law relation to the quench rate,indicating a proportional relationship between the excitation energy and the kink numbers.Moreover,we establish a universal power-law relationship between the first three cumulants of the kink numbers and the quench rate,indicating a binomial distribution of the kinks.Finally,the normalized kink-kink correlations are also investigated and it is found that the numerical values are consistent with the analytic formula.展开更多
Fail-safe topology optimization is valuable for ensuring that optimized structures remain operable even under damaged conditions.By selectively removing material stiffness in patches with a fixed shape,the complex phe...Fail-safe topology optimization is valuable for ensuring that optimized structures remain operable even under damaged conditions.By selectively removing material stiffness in patches with a fixed shape,the complex phenomenon of local failure is modeled in fail-safe topology optimization.In this work,we first conduct a comprehensive study to explore the impact of patch size,shape,and distribution on the robustness of fail-safe designs.The findings suggest that larger sizes and finer distribution of material patches can yield more robust fail-safe structures.However,a finer patch distribution can significantly increase computational costs,particularly for 3D structures.To keep computational efforts tractable,an efficient fail-safe topology optimization approach is established based on the framework of multi-resolution topology optimization(MTOP).Within the MTOP framework,the extended finite element method is introduced to establish a decoupling connection between the analysis mesh and the topology description model.Numerical examples demonstrate that the developed methodology is 2 times faster for 2D problems and over 25 times faster for 3D problems than traditional fail-safe topology optimization while maintaining similar levels of robustness.展开更多
This study explores a symmetric configuration approach in anion exchange membrane(AEM)water electrolysis,focusing on overcoming adaptability challenges in dynamic conditions.Here,a rapid and mild synthesis technique f...This study explores a symmetric configuration approach in anion exchange membrane(AEM)water electrolysis,focusing on overcoming adaptability challenges in dynamic conditions.Here,a rapid and mild synthesis technique for fabricating fibrous membrane-type catalyst electrodes is developed.Our method leverages the contrasting oxidation states between the sulfur-doped NiFe(OH)_(2) shell and the metallic Ni core,as revealed by electron energy loss spectroscopy.Theoretical evaluations confirm that the S–NiFe(OH)_(2) active sites optimize free energy for alkaline water electrolysis intermediates.This technique bypasses traditional energy-intensive processes,achieving superior bifunctional activity beyond current benchmarks.The symmetric AEM water electrolyzer demonstrates a current density of 2 A cm^(-2) at 1.78 V at 60℃ in 1 M KOH electrolyte and also sustains ampere-scale water electrolysis below 2.0 V for 140 h even in ambient conditions.These results highlight the system's operational flexibility and structural stability,marking a significant advance-ment in AEM water electrolysis technology.展开更多
基金funded by USAID’s Community Partnerships to Strengthen Sustainable Development(Compass)Program implemented by U.S.Forest Service International Programs(Grant No.Compass-SA-2023-073).
文摘Protecting rare,endemic,and endangered species requires careful habitat evaluation to set strategic plans for mitigating biodiversity loss and prioritizing conservation goals.The endangered Asian elephant(Elephas maximus)exemplifies the urgent need for targeted conservation efforts,given its challenging habitat conditions.This study examines the impact of climate and land use changes on the suitable habitat distribution of Asian elephants.Utilizing ten predictor variables,including climatic,topographic,and land use data,and employing six ensemble Species Distribution Models(SDMs)alongside Coupled Model Intercomparison Project Phase 6 data,the study estimates spatial changes and potential habitat expansions for Asian elephants across Tropical Asia.Occurrence data were gathered from field surveys in Bangladesh and the Global Biodiversity Information Facility database for Sri Lanka,Myanmar,Bhutan,Cambodia,India,Laos,Nepal,Thailand,and Vietnam.To evaluate habitat suitability,the analysis considered two distinct socioeconomic pathways(SSP 245 and SSP 370)across two future periods(2041–2060 and 2061–2080).Results reveal a strong correlation between isothermality and habitat suitability,with higher isothermality enhancing the habitat conditions for Asian elephants.Among the SDMs,the random forest model demonstrated the highest performance.Projected scenarios indicate significant habitat fragmentation by 2061–2080,heightening the risk of species’vulnerability.Specifically,in SSP 245,the north zone is anticipated to experience a higher rate of habitat loss(588.443 km^(2)/year),whereas,in SSP 370,the west zone is expected to face a more severe rate of habitat loss(1,798.56 km^(2)/year).The eastern zone,which includes Cambodia,Vietnam,Laos,Thailand,and southern Myanmar,is notably at risk,with an estimated habitat loss of 14.8 million hectares.Anticipated changes in climate and land cover will impact the availability of essential resources such as food,water,and shelter,potentially driving the species to relocate to different elevation belts.The outcomes of the consensus map highlighting critical habitats and future fragmentation scenarios will support effective conservation and management strategies for the species.
文摘Despite existing curative options like surgical removal,tissue destruction techniques,and liver transplantation for early-stage hepatocellular carcinoma(HCC),the rising incidence and mortality rates of this global health burden necessitate continuous exploration of novel therapeutic strategies.This review critically assesses the dynamic treatment panorama for HCC,focusing specifically on the burgeoning role of immunotherapy in two key contexts:early-stage HCC and downstaging advanced HCC to facilitate liver transplant candidacy.It delves into the unique immunobiology of the liver and HCC,highlighting tumor-mediated immune evasion mechanisms.Analyzing the diverse immunothera-peutic approaches including checkpoint inhibitors,cytokine modulators,vaccines,oncolytic viruses,antigen-targeting antibodies,and adoptive cell therapy,this review acknowledges the limitations of current diagnostic markers alpha-fetoprotein and glypican-3 and emphasizes the need for novel biomarkers for patient selection and treatment monitoring.Exploring the rationale for neoadjuvant and adjuvant immunotherapy in early-stage HCC,current research is actively exploring the safety and effectiveness of diverse immunothera-peutic approaches through ongoing clinical trials.The review further explores the potential benefits and challenges of combining immunotherapy and liver transplant,highlighting the need for careful patient selection,meticulous monitoring,and novel strategies to mitigate post-transplant complications.Finally,this review delves into the latest findings from the clinical research landscape and future directions in HCC management,paving the way for optimizing treatment strategies and improving long-term survival rates for patients with this challenging malignancy.
文摘As the world grapples with increasing environmental challenges,innovative technologies are essential for promoting sustainability and accountability.This study examined the impact of environmental performance indices(EPIs)on the growth and investment trends of blockchain-based sustainability-focused companies in 15 countries(Belgium,Czechia,Denmark,Estonia,Finland,France,Germany,Italy,Norway,Poland,Sweden,Spain,Switzerland,the United Kingdom,and the United States)from Europe and America during 2010-2022.This study used the negative binomial regression model to assess the relationship between EPIs and blockchain-based sustainability-focused companies based on the data from the CrunchBase and EarthData.Results indicated that in ecosystem vitality,national terrestrial biome protection efforts were negatively correlated the formation of blockchain-based sustainability-focused companies,while global terrestrial biome protection efforts and marine protected areas had a positive impact on the formation of these companies and the number of funding rounds.In environmental health,PM2.5 exposure had a positive impact on the number of funding rounds.Conversely,pollutants such as sulfur dioxide(SO_(2))and ocean plastics deterred the formation of blockchain-based sustainability-focused companies and reduced the number of funding rounds.In climate change performance,adjusted emission growth rate for carbon dioxide(CO_(2)),adjusted emission growth rate for F-gases,and adjusted emission growth rate for black carbon had a significantly positive impact on the formation of blockchain-based sustainability-focused companies.Conversely,adjusted emission growth rate for Nitrous Oxide(N_(2)O)and projected greenhouse gas emissions in 2050 negatively affected the formation of these companies.These findings highlight the dual role of EPIs as driving factors and barriers in the development and investment of blockchain-based sustainability-focused companies in countries from Europe and America.
基金funded in part through the Project PID2022138307OB-C21(HolisticWheat),from Ministerio de Ciencia,Innovación y Universidades,SpainThe Water Research Institute(IdRA)for their financial support to cover laboratory analyses。
文摘Carbon(δ^(13)C)and oxygen(δ^(18)O)isotope compositions are considered indicators of the effect of water conditions on plant photosynthesis(δ^(13)C)and transpiration(δ^(18)O).Hydrogen isotope composition(δ^(2)H),tracks transpiration like δ^(18)O,while also affected by the organ trophism.Such dual behaviour,together with its highly exchangeable nature have hindered the use of δ^(2)H to assess plant performance.We compared the effect of contrasting water pressure deficit(VPD)on the signatures of the three isotopes across different durum wheat parts.Plants were hydroponically grown under conditions,differing in VPD and the isotopic labelling of the nutrient solution(natural abundance versus δ^(2)H and δ^(18)O-enriched)and isotopic signatures analysed at mid-grain filling.Higher VPD increased plant-matter δ^(13)C,δ^(2)H,and δ^(18)O,in accordance with atmospheric drought decreasing stomatal conductance and transpiration.Moreover,positive correlations within and across organs betweenδ2H and δ^(18)O of organicmatter and water further supported a similar source of variation related to evaporation.However,δ^(2)H was depleted in photoautotrophic(leaves and glumes),enriched in mixotrophic(peduncle and awns)and even more in heterotrophic(grains)organs.This study highlights the similarities and differences in mechanisms determining δ^(2)H,δ^(18)O,and δ^(13)C through the interactions of these isotopes with VPD and plant organs.
文摘Background:Gene expression profiling plays a key role in cancer research,but its high dimensionality and redundancy pose challenges for effective analysis.Feature selection and robust classification are critical for improving predictive performance,while explainable machine learning techniques support transparency and biomarker discovery.Methods:To propose a hybrid explainable machine learning framework that combines stability-guided multi-source(SGMS)feature selection with classification models for gene expression-based cancer prediction and biomarker identification.SGMS integrates Mutual Information,F-statistic,and random forest(RF)importance to select informative genes.These features are used to train classifiers,including novel elasticnet logistic regression(NEN-LR),RF,and Support Vector Machine(SVM).Performance is evaluated using accuracy,precision,recall,F1-score,and Matthews correlation coefficient(MCC).SHapley Additive exPlanations(SHAP)values are used to interpret gene-level contributions,and co-expression networks help identify functional gene modules.Results:The proposed NEN-LR classifier achieved the highest performance with 99.8%accuracy,99.9%precision,and 0.997 MCC using the top 200 SGMS-selected genes.Biomarker discovery identified both class-specific and shared genes across five cancer types,with top genes like gene_230,gene_5380,and gene_18570 consistently appearing across multiple classes.Visualization tools,including heatmaps,Venn diagrams,and co-expression networks,were used to interpret expression dynamics and regulatory patterns,enhancing the biological relevance of findings.SHAP analysis revealed top biomarkers with strong predictive influence,while co-expression clustering uncovered biologically meaningful gene modules.Other models also showed marked improvement using SGMS-selected features.Conclusion:The proposed framework successfully integrates feature selection,interpretable classification,and biomarker discovery,providing a powerful tool for precision oncology and molecular diagnostics.
基金supports by the National Key Research and Development Program of China (Grant No.2024YFA1409200)the National Natural Science Foundation of China (Grant Nos.12222412 and 12047503)+1 种基金CAS Project for Young Scientists in Basic Research (Grant No.YSBR-057)supports by the National Natural Science Foundation of China (Grant No.12374144)。
文摘We extend a semiclassical numerical method, bosonic auxiliary-field Monte Carlo, to quantum spin systems. This method breaks the lattice into clusters, solves each cluster precisely and couples them with classical auxiliary fields through classical Monte Carlo simulation. We test the method with antiferromagnetic spin models in one-dimensional chains, square lattices and triangular lattices, and obtain reasonable results at finite temperatures. This algorithm builds a bridge between classical Monte Carlo method and quantum methods. The algorithm can be improved with either progress in classical Monte Carlo sampling or the development of quantum solvers, and can also be further applied to systems with different lattices or interactions.
基金funded by grants Pronaii 302979A1-S-9005 CONACyT (México) from RMDA。
文摘Dengue is an arboviral disease caused by the dengue virus,with 390 million infections reported annually worldwide.It is classified into two categories:dengue without or with warning signs and severe dengue.[1]Given the moderate efficacy of the dengue vaccine,[2]there is an urgent necessity to design host-directed therapeutic strategies,such as the repurposing of FDA-approved drugs,to combat dengue virus infection.
基金supported by Princess Nourah bint Abdulrahman University Researchers Supporting Project number(PNURSP2025R899)Princess Nourah bint Abdulrahman University,Riyadh,Saudi Arabiasupported by the Deanship of Scientific Research,Vice Presidency for Graduate Studies and Scientific Research,King Faisal University,Saudi Arabia(KFU252831)。
文摘This study investigates the transmission dynamics of conjunctivitis using stochastic delay differential equations(SDDEs).A delayed stochastic model is formulated by dividing the population into five distinct compartments:susceptible,exposed,infected,environmental irritants,and recovered individuals.The model undergoes thorough analytical examination,addressing key dynamical properties including positivity,boundedness,existence,and uniqueness of solutions.Local and global stability around the equilibrium points is studied with respect to the basic reproduction number.The existence of a unique global positive solution for the stochastic delayed model is established.In addition,a stochastic nonstandard finite difference scheme is developed,which is shown to be dynamically consistent and convergent toward the equilibrium states.The scheme preserves the essential qualitative features of the model and demonstrates improved performance when compared to existing numerical methods.Finally,the impact of time delays and stochastic fluctuations on the susceptible and infected populations is analyzed.
基金Projects(51975398,52105392)supported by the National Natural Science Foundation of ChinaProject(YDZJSX2021A006)supported by the Central Government Guided Local Science and Technology Development Fund Project,China+1 种基金Project(20210035)supported by the Scientific Activities of Selected Returned Overseas Professionals in Shanxi Province,ChinaProject(2020-037)supported by the Fund Program for the Research Project Supported by Shanxi Scholarship Council,China。
文摘In the present study,two-layered stainless steel-copper composites with a thickness of 50μm were initially subjected to annealing at 800,900 and 1000℃for 5 min,respectively,to achieve diverse microstructural features.Then the influence of annealing temperature on the formability of stainless steel-copper composites and the quality of micro composite cups manufactured by micro deep drawing(MDD)were investigated,and the underlying mechanism was analyzed.Three finite element(FE)models,including basic FE model,Voronoi FE model and surface morphological FE model,were developed to analyze the forming performance of stainless steel-copper composites during MDD.The results show that the stainless steel-copper composites annealed at 900℃possess the best plasticity owing to the homogeneous and refined microstructure in both stainless steel and copper matrixes,and the micro composite cup with specimen annealed at 900℃exhibits a uniform wall thickness as well as high surface quality with the fewest wrinkles.The results obtained from the surface morphological FE model considering material inhomogeneity and surface morphology of the composites are the closest to the experimental results compared to the basic and Voronoi FE model.During MDD process,the drawing forces decrease with increasing annealing temperature as a consequence of the strength reduction.
基金the support from the National Natural Science Foundation of China(NSFC)under Grant Nos.12322502 and 12335002the Joint Large Scale Scientific Facility Funds of the NSFC and Chinese Academy of Sciences(CAS)under Contract No.U1932110+3 种基金the Hunan Provincial Natural Science Foundation under Grant No.2024JJ3004the Fundamental Research Funds for the central universitiessupported by the CAS President’s International Fellowship Initiative(PIFI)(Grant No.2025PD0022)by the MKW NRW under the funding code No.NW21-024-A and by ERC AdG EXOTIC(Grant No.101018170)。
文摘We review recent experimental and theoretical results for the electromagnetic form factors of hyperons(Y)in the timelike region,accessible in the reactions e^(+)e^(-)→YY.Specifically,we focus on the final statesΛΛ,ΛΣ^(0)/Λ,Σ^(0)Λ,■■,andΩΩ.TheΛ_(c)Λ_(c)system is also discussed.
基金supported by the the National Key R&D Program of China(Grant Nos.2022YFA1604900 and 2023YFA1606703)the National Natural Science Foundation of China(Grant Nos.12025501,12435007,12405133,and 12347180)+1 种基金China Postdoctoral Science Foundation(Grant No.2023M740189)the Postdoctoral Fellowship Program of CPSF(Grant No.GZC20233381).
文摘Hypernuclei,nuclei containing one or more hyperons,serve as unique laboratories for probing the non-perturbative quantum chromodynamics(QCD).Recent progress in hypernuclear physics,driven by advanced experimental techniques and theoretical innovations,is briefly reviewed with a focus on key findings and unresolved challenges,such as the precise determination of the hypertriton binding energy,investigations of charge symmetry breaking in mirror hypernuclei,and the search for exotic systems,including the neutral nnΛstate.Experimental breakthroughs,including invariant-mass analyses and femtoscopy studies in heavy-ion collisions,as well as high-resolutionγ-spectroscopy,have enabled precise studies of light hypernuclei and offered critical insights into the hyperon–nucleon interaction.Theoretical progress,including ab initio calculations based on chiral effective field theory and lattice QCD,has further enhanced our understanding of hyperon–nucleon and hyperon–hyperon interactions.
文摘With the development of radioactive-ion-beam facilities,many exotic phenomena have been discovered or predicted in the nuclei far from the stability line,including cluster structure,shell structure,deformed halo,and shape decoupling effects.The study of exotic nuclear phenomena is at the frontier of nuclear physics nowadays.The covariant density functional theory(CDFT)is one of the most successful microscopic models in describing the structure of nuclei in almost the whole nuclear chart.Within the framework of CDFT,toward a proper treatment of deformation and weak binding,the deformed relativistic Hartree-Bogoliubov theory in continuum(DRHBc)has been developed.In this contribution,we review the applications and extensions of the DRHBc theory to the study of exotic nuclei.The DRHBc theory has been used to investigate the deformed halos in B,C,Ne,Na,and Mg isotopes and the theoretical descriptions are reasonably consistent with available data.A DRHBc Mass Table Collaboration has been founded,aiming at a high precision nuclear mass table with deformation and continuum effects included,which is underway.By implementing the angular momentum projection based on the DRHBc theory,the rotational excitations of deformed halos have been investigated and it is shown that the deformed halos and shape decoupling effects also exist in the low-lying rotational excitation states of deformed halo nuclei.
基金CONCYTEC and PROCIENCIA agencies from Peru in the framework of the call for Basic Research Projects2019-01[contract number401-2019-FONDECYT].
文摘This study investigates the influence of electropolymerization conditions on the deposition of polypyrrole(PPy)onto cotton-derived carbon fiber(CF)modified with reduced graphene oxide(rGO)for supercapacitors applications using an experimental/theorical approach.The surface modification of CF by rGO and/or by PPy electrodeposited at 10,25 and 50 mV s^(-1) was thoroughly examined physicochemical and electrochemically.Composite electrodes comprising CF-rGo-PPy,synthesized via electropolymerization at 25 mV s^(-1),demonstrated a remarkable increase in capacitance,showcasing~742 F g^(-1) compared to 153 F g^(-1) for CF.SEM,N_(2)-surface area,XPS,and TD-DFT approach revealed that the higher capacitance observed in CF-rGo-PPy electrodes underscores the influence of morphology and charged nitrogen species on the electrochemical performance of these modified electrodes.Notably,this electrode material achieves a specific capacitance retention of~96%of their initial capacitance after 10000 cycles at 0.5 A g^(-1) measured in a two-electrodes cell configuration.This work also discusses the influence of the scan rate used for pyrrole electropolymerization on the pseudocapacitance contribution of PPy and its possible effect on the porosity of the material.These results highlight the importance of appropriate electropolymerization conditions that allow obtaining the synergistic effect between CF,rGO and PPy.
文摘The urban land-use allocation problem is a spatial optimization problem that allocates optimum land-uses to specific land units in urban areas.This problem is an NP(nondeterministic polynomial time)-hard problem because of involving many objective functions,many constraints,and complex search space.Moreover,this subject is an important issue in smart cities and newly developed areas of cities to achieve a sustainable arrangement of land-uses.Different types ofMulti-Objective Optimization Algorithms(MOOAs)based on Artificial Intelligence(AI)have been frequently employed,but their ability and performance have not been evaluated and compared properly.This paper aims to employ and compare three commonly used MOOAs i.e.NSGA-II,MOPSO,and MOEA/D in urban land-use allocation problems.Selected algorithms belong to different categories of MOOAs family to investigate their advantage and disadvantages.The objective functions of this study are compatibility,dependency,suitability,and compactness of land-uses and the constraint is compensating of Per-Capita demand in the urban environment.Evaluation of results is based on the dispersion of the solutions,diversity of the solutions’space,and comparing the number of dominant solutions in Pareto-Fronts.The results showed that all three algorithms improved the objective functions related to the current arrangement of the land-uses.However,the run time of NSGA-II is the worst,related to the Diversity Metric(DM)which represents the regularity of the distance between solutions at the highest degree.Moreover,MOPSO provides the best Scattering Diversity Metric(SDM)which shows the diversity of solutions in the solution space.Furthermore,In terms of algorithm execution time,MOEA/D performed better than the other two.So,Decision-makers should consider different aspects in choosing the appropriate MOOA for land-use management problems.
基金the Tenure Track Position“Bois:Biobased materials”part of E2S UPPA supported by the“Investissements d’Avenir”French Program managed by ANR(ANR-16-IDEX-0002).
文摘The chemical composition and thermal properties of natural fibers are the most critical variables that determine the overall properties of the fibers and influence their processing and use in different sustainable applications,such as their conversion into bioenergy and biocomposites.Their thermal and mechanical properties can be estimated by evaluating the content of cellulose,lignin,and other extractives in the fibers.In this research work,the chemical composition and thermal properties of three fibers,namely bagasse,kenaf bast fibers,and cotton stalks,were evaluated to assess their potential utilization in producing biocomposites and bioenergy materials.The chemical composition analysis followed the Technical Association of the Pulp and Paper Industry Standards(TAPPI)methods.The total phenol content was quantified using the Folin-Ciocalteu method,while Fourier Transform Infrared Spectroscopy(FTIR)was employed to assess the light absorption by the bonds.To evaluate thermal stability and higher heating values,Thermogravimetric Analysis(TGA),Differential Scanning Calorimetry(DSC),and bomb calorimetry were performed.The chemical analysis revealed that bagasse contained 50.6%cellulose and 21.6%lignin,kenaf bast fibers had 58.5%cellulose and 10%lignin,and cotton stalks exhibited 40.3%cellulose and 21.3%lignin.The FTIR curves demonstrated a notable similarity among the fibers.The TGA analysis showed degradation temperatures of 321°C for bagasse,354°C for kenaf bast fibers,and 289°C for cotton stalks.The DSC analysis revealed glass transition temperatures of 81°C for bagasse,66.3°C for cotton stalks,and 64.5°C for kenaf bast fibers.The higher heating values were measured as 17.3,16.6 and 17.1 MJ/kg for bagasse,kenaf bast fibers,and cotton stalks,respectively.The three fibers have a high potential for biocomposites and bioenergy material manufacturing.
基金National Key Research and Development Program of China(2018YFC1106702)Guangdong Basic and Applied Basic Research Foundation(2020A1515011301,2019A1515110067 and 2020A1515110055)+1 种基金Shenzhen Basic Research Project(JCYJ20210324120001003,JCYJ20200109144608205 and JCYJ20200109144604020)IER Foundation(HT-JDCXY-201902 and HT-JD-CXY-201907)for financial support.
文摘In the present work,seven Mg-Zn-Ag alloys with the nominal composition of Mg_(96-x)Zn_(x)Ag_(4)(x=17,20,23,26,29,32,35 in at.%)were prepared by induction melting and single-roller melt-spinning.The X-ray diffraction(XRD)analyses indicate the metallic glasses with three composition of Mg_(73)Zn_(23)Ag_(4),Mg_(70)Zn_(26)Ag_(4),and Mg_(67)Zn_(29)Ag_(4)were obtained successfully.The differential scanning calorimetry(DSC)measurement was used to obtain the characteristic temperature of Mg-Zn-Ag metallic glasses for the glass-forming ability analysis.The maximum glass transition temperature(Trg)was found to be 0.525 with a composition close to Mg_(67)Zn_(29)Ag_(4),which results in the best glass-forming ability.Moreover,the immersion test in simulated body fluid(SBF)demonstrate the relative homogeneous corrosion behavior of the Mg-Zn-Ag metallic glasses.The corrosion rate of Mg-Zn-Ag metallic glasses in SBF solution decreases with the increase of Zn content.The sample Mg_(67)Zn_(29)Ag_(4)has the lowest corrosion rate of 0.19mm/yr,which could meet the clinical application requirement well.The in vitro cell experiments show that the Madin-Darby canine kidney(MDCK)cells cultured in sample Mg_(67)Zn_(29)Ag_(4)and its extraction medium have higher activity.However,the Mg-Zn-Ag metallic glasses exhibit obvious inhibitory effect on human rhabdomyosarcoma(RD)tumor cells.The present investigations on the glass-forming ability,corrosion behavior,cytocompatibility and tumor inhibition function of the Mg-Zn-Ag based metallic glass could reveal their biomedical application possibility.
基金partially supported by the National Natural Science Foundation of China(52375238)Science and Technology Program of Guangzhou(202201020213,202201020193,202201010399)GZHU-HKUST Joint Research Fund(YH202109).
文摘In time-variant reliability problems,there are a lot of uncertain variables from different sources.Therefore,it is important to consider these uncertainties in engineering.In addition,time-variant reliability problems typically involve a complexmultilevel nested optimization problem,which can result in an enormous amount of computation.To this end,this paper studies the time-variant reliability evaluation of structures with stochastic and bounded uncertainties using a mixed probability and convex set model.In this method,the stochastic process of a limit-state function with mixed uncertain parameters is first discretized and then converted into a timeindependent reliability problem.Further,to solve the double nested optimization problem in hybrid reliability calculation,an efficient iterative scheme is designed in standard uncertainty space to determine the most probable point(MPP).The limit state function is linearized at these points,and an innovative random variable is defined to solve the equivalent static reliability analysis model.The effectiveness of the proposed method is verified by two benchmark numerical examples and a practical engineering problem.
基金partially supported by the National Natural Science Foundation of China(Grants No.11875095 and 12175008).
文摘Neural networks possess formidable representational power,rendering them invaluable in solving complex quantum many-body systems.While they excel at analyzing static solutions,nonequilibrium processes,including critical dynamics during a quantum phase transition,pose a greater challenge for neural networks.To address this,we utilize neural networks and machine learning algorithms to investigate time evolutions,universal statistics,and correlations of topological defects in a one-dimensional transverse-field quantum Ising model.Specifically,our analysis involves computing the energy of the system during a quantum phase transition following a linear quench of the transverse magnetic field strength.The excitation energies satisfy a power-law relation to the quench rate,indicating a proportional relationship between the excitation energy and the kink numbers.Moreover,we establish a universal power-law relationship between the first three cumulants of the kink numbers and the quench rate,indicating a binomial distribution of the kinks.Finally,the normalized kink-kink correlations are also investigated and it is found that the numerical values are consistent with the analytic formula.
基金financially supported by the National Natural Science Foundation of China(Grant Nos.12172095,11832009,and 12302008)the Natural Science Foundation of Guangdong Province(Grant No.2023A1515011770)Guangzhou Science and Technology Planning Project(Grant Nos.202201010570,202201020239,202201020193,and 202201010399)。
文摘Fail-safe topology optimization is valuable for ensuring that optimized structures remain operable even under damaged conditions.By selectively removing material stiffness in patches with a fixed shape,the complex phenomenon of local failure is modeled in fail-safe topology optimization.In this work,we first conduct a comprehensive study to explore the impact of patch size,shape,and distribution on the robustness of fail-safe designs.The findings suggest that larger sizes and finer distribution of material patches can yield more robust fail-safe structures.However,a finer patch distribution can significantly increase computational costs,particularly for 3D structures.To keep computational efforts tractable,an efficient fail-safe topology optimization approach is established based on the framework of multi-resolution topology optimization(MTOP).Within the MTOP framework,the extended finite element method is introduced to establish a decoupling connection between the analysis mesh and the topology description model.Numerical examples demonstrate that the developed methodology is 2 times faster for 2D problems and over 25 times faster for 3D problems than traditional fail-safe topology optimization while maintaining similar levels of robustness.
基金This research was supported by the“Regional Innovation Strategy(RIS)”through the National Research Foundation of Korea(NRF)funded by the Ministry of Education(MOE)(2021RIS-002)This work was supported by an NRF grant funded by the Ministry of Science,ICT,and Future Planning(No.NRF-2018R1C1B6005009,NRF-2021R1C1C1012676,and 2009-0082580).
文摘This study explores a symmetric configuration approach in anion exchange membrane(AEM)water electrolysis,focusing on overcoming adaptability challenges in dynamic conditions.Here,a rapid and mild synthesis technique for fabricating fibrous membrane-type catalyst electrodes is developed.Our method leverages the contrasting oxidation states between the sulfur-doped NiFe(OH)_(2) shell and the metallic Ni core,as revealed by electron energy loss spectroscopy.Theoretical evaluations confirm that the S–NiFe(OH)_(2) active sites optimize free energy for alkaline water electrolysis intermediates.This technique bypasses traditional energy-intensive processes,achieving superior bifunctional activity beyond current benchmarks.The symmetric AEM water electrolyzer demonstrates a current density of 2 A cm^(-2) at 1.78 V at 60℃ in 1 M KOH electrolyte and also sustains ampere-scale water electrolysis below 2.0 V for 140 h even in ambient conditions.These results highlight the system's operational flexibility and structural stability,marking a significant advance-ment in AEM water electrolysis technology.
