We discuss the set-valued dynamics related to the theory of functional equations.We look for selections of convex set-valued functions satisfying set-valued Euler-Lagrange inclusions.We improve and extend upon some of...We discuss the set-valued dynamics related to the theory of functional equations.We look for selections of convex set-valued functions satisfying set-valued Euler-Lagrange inclusions.We improve and extend upon some of the results in[13,20],but under weaker assumptions.Some applications of our results are also provided.展开更多
A way to extend operators in spaces of continuous functions to spaces of continuous set_valued functions is proposed. This extension is developed through the Steiner selections of the set_valued functions. Their prope...A way to extend operators in spaces of continuous functions to spaces of continuous set_valued functions is proposed. This extension is developed through the Steiner selections of the set_valued functions. Their properties and characteristics of the convergence of sequences of operators of this class are studied. In Part Ⅱ of this series some applications to approximation theory will be shown.展开更多
The concept of finitely continuous topological space is introduced and the basic properties of the space are given. Several continuous selection theorems and fixed point theorems for Ф-maps are established, and as ap...The concept of finitely continuous topological space is introduced and the basic properties of the space are given. Several continuous selection theorems and fixed point theorems for Ф-maps are established, and as applications of the above fixed point theorems, some section problems are discussed. The results generalize and improve many corresponding conclusions.展开更多
On the basis of Part (Ⅰ) of this series some applications to the approximation of set_valued functions are obtained: Korovkin type theorems, a method to extend classical approximation operators to the set_valued sett...On the basis of Part (Ⅰ) of this series some applications to the approximation of set_valued functions are obtained: Korovkin type theorems, a method to extend classical approximation operators to the set_valued setting and a Jackson type estimate.展开更多
In this paper,we prove that if X is an almost convex and 2-strictly convex space,linear operator T:X→Y is bounded,N(T)is an approximative compact Chebyshev subspace of X and R(T)is a 3-Chebyshev hyperplane,then there...In this paper,we prove that if X is an almost convex and 2-strictly convex space,linear operator T:X→Y is bounded,N(T)is an approximative compact Chebyshev subspace of X and R(T)is a 3-Chebyshev hyperplane,then there exists a homogeneous selection T^(σ)of T^(■)such that continuous points of T^(σ)and T^(■)are dense on Y.展开更多
We shall introduce 1-type Lipschitz multifunctions from R into generalized 2-normed spaces, and give some results about their 1-type Lipschitz selections.
Five male kiwifruit selections Truwind M1, M2, M3, M4 and M5 bred by Hunan Horticultural Research Institute (HHRI)have been observed on the suitability,of which Truwind M1,M2 and M3 are Actinidia chinensis,Truwind M4 ...Five male kiwifruit selections Truwind M1, M2, M3, M4 and M5 bred by Hunan Horticultural Research Institute (HHRI)have been observed on the suitability,of which Truwind M1,M2 and M3 are Actinidia chinensis,Truwind M4 and M5 are Actinidia deliciosa. In terms of flower period Truwind M1 is early and 7 days, which is the suitable pollinator for‘Fengyue’;Truwind M2 is intermediate with 15 days,suitable for ‘Kuimi’and‘Lushanxiang’;Truwind M3 and M4 are 14 days and 13 days respectively,suitable for‘Cuiyu’and‘Miliang 1’;Truwind M5 is late and 8 days, suitable for‘Jinkui’,‘Qinxiang’and‘Hayward’.展开更多
In this paper,we establish and study a single-species logistic model with impulsive age-selective harvesting.First,we prove the ultimate boundedness of the solutions of the system.Then,we obtain conditions for the asy...In this paper,we establish and study a single-species logistic model with impulsive age-selective harvesting.First,we prove the ultimate boundedness of the solutions of the system.Then,we obtain conditions for the asymptotic stability of the trivial solution and the positive periodic solution.Finally,numerical simulations are presented to validate our results.Our results show that age-selective harvesting is more conducive to sustainable population survival than non-age-selective harvesting.展开更多
To explore the formation mechanism of anisotropy in Ti-6Al-4V alloy fabricated by selective laser melting(SLM),the compressive mechanical properties,microhardness,microstructure,and crystallographic orientation of the...To explore the formation mechanism of anisotropy in Ti-6Al-4V alloy fabricated by selective laser melting(SLM),the compressive mechanical properties,microhardness,microstructure,and crystallographic orientation of the alloy across different planes were investigated.The anisotropy of SLM-fabricated Ti-6Al-4V alloys was analyzed,and the electron backscatter diffraction technique was used to investigate the influence of different grain types and orientations on the stress-strain distribution at various scales.Results reveal that in room-temperature compression tests at a strain rate of 10^(-3) s^(-1),both the compressive yield strength and microhardness vary along the deposition direction,indicating a certain degree of mechanical property anisotropy.The alloy exhibits a columnar microstructure;along the deposition direction,the grains appear equiaxed,and they have internal hexagonal close-packed(hcp)α/α'martensitic structure.α'phase has a preferential orientation approximately along the<0001>direction.Anisotropy arises from the high aspect ratio of columnar grains,along with the weak texture of the microstructure and low symmetry of the hcp crystal structure.展开更多
The Financial Technology(FinTech)sector has witnessed rapid growth,resulting in increasingly complex and high-volume digital transactions.Although this expansion improves efficiency and accessibility,it also introduce...The Financial Technology(FinTech)sector has witnessed rapid growth,resulting in increasingly complex and high-volume digital transactions.Although this expansion improves efficiency and accessibility,it also introduces significant vulnerabilities,including fraud,money laundering,and market manipulation.Traditional anomaly detection techniques often fail to capture the relational and dynamic characteristics of financial data.Graph Neural Networks(GNNs),capable of modeling intricate interdependencies among entities,have emerged as a powerful framework for detecting subtle and sophisticated anomalies.However,the high-dimensionality and inherent noise of FinTech datasets demand robust feature selection strategies to improve model scalability,performance,and interpretability.This paper presents a comprehensive survey of GNN-based approaches for anomaly detection in FinTech,with an emphasis on the synergistic role of feature selection.We examine the theoretical foundations of GNNs,review state-of-the-art feature selection techniques,analyze their integration with GNNs,and categorize prevalent anomaly types in FinTech applications.In addition,we discuss practical implementation challenges,highlight representative case studies,and propose future research directions to advance the field of graph-based anomaly detection in financial systems.展开更多
The carbon dioxide reduction reaction(CO_(2)RR)is a promising strategy for converting CO_(2)into high-value chemicals.However,the rational design of efficient catalysts for steering product selectivity toward specific...The carbon dioxide reduction reaction(CO_(2)RR)is a promising strategy for converting CO_(2)into high-value chemicals.However,the rational design of efficient catalysts for steering product selectivity toward specific high-value chemicals continues to be a central goal in electrocatalysis research.Recently,nanoporous confined electrocatalysts have garnered attention due to their unique pore structures,which not only increase the accessibility and utilization of active sites but also promote the enrichment and stabilization of key reaction intermediates and modulate the local reaction microenvironment.These combined effects contribute to improved reaction kinetics and enhanced product selectivity.This review systematically summarizes the mechanistic foundations of nanoporous confinement in CO_(2)RR,emphasizing its role in governing reaction pathways and selectivity.We introduce the fundamental design principles of nanoporous confined electrocatalysts,detailing how their pore size,tortuosity,and connectivity influence CO_(2)diffusion,local concentration gradients,and electrolyte accessibility.Then highlight how confinement-induced spatial regulation facilitates intermediate accumulation,directional proton transfer,and local pH modulation,collectively steering product selectivity toward desired C_(1) and multi-carbon(C_(2+))products.Representative material systems and structure-performance relationships are discussed to illustrate these effects.Finally,we summarize the current challenges in mechanistic understanding and practical implementation,and propose future directions for developing nanoporous systems that integrate controlled transport,catalytic reactivity,and system-level scalability.展开更多
With the increasing complexity of vehicular networks and the proliferation of connected vehicles,Federated Learning(FL)has emerged as a critical framework for decentralized model training while preserving data privacy...With the increasing complexity of vehicular networks and the proliferation of connected vehicles,Federated Learning(FL)has emerged as a critical framework for decentralized model training while preserving data privacy.However,efficient client selection and adaptive weight allocation in heterogeneous and non-IID environments remain challenging.To address these issues,we propose Federated Learning with Client Selection and Adaptive Weighting(FedCW),a novel algorithm that leverages adaptive client selection and dynamic weight allocation for optimizing model convergence in real-time vehicular networks.FedCW selects clients based on their Euclidean distance from the global model and dynamically adjusts aggregation weights to optimize both data diversity and model convergence.Experimental results show that FedCW significantly outperforms existing FL algorithms such as FedAvg,FedProx,and SCAFFOLD,particularly in non-IID settings,achieving faster convergence,higher accuracy,and reduced communication overhead.These findings demonstrate that FedCW provides an effective solution for enhancing the performance of FL in heterogeneous,edge-based computing environments.展开更多
BACKGROUND Post-stroke depression(PSD)is associated with hypothalamic-pituitary-adrenal(HPA)axis dysfunction and neurotransmitter deficits.Selective serotonin reuptake inhibitors(SSRIs)are commonly used,but their effi...BACKGROUND Post-stroke depression(PSD)is associated with hypothalamic-pituitary-adrenal(HPA)axis dysfunction and neurotransmitter deficits.Selective serotonin reuptake inhibitors(SSRIs)are commonly used,but their efficacy is limited.This study investigated whether combining SSRIs with traditional Chinese medicine(TCM)Free San could enhance their therapeutic effects.AIM To evaluate the clinical efficacy and safety of combining SSRIs with Free San in treating PSD,and to assess its impact on HPA axis function.METHODS Ninety-two patients with PSD were enrolled and randomly divided into control groups(n=46)and study groups(n=46).The control group received the SSRI paroxetine alone,whereas the study group received paroxetine combined with Free San for 4 weeks.Hamilton Depression Scale and TCM syndrome scores were assessed before and after treatment.Serum serotonin,norepinephrine,cortisol,cor-ticotropin-releasing hormone,and adrenocorticotropic hormone were measured.The treatment responses and adverse reactions were recorded.RESULTS After treatment,the Hamilton Depression Scale and TCM syndrome scores were significantly lower in the study group than in the control group(P<0.05).Serum serotonin and norepinephrine levels were significantly higher in the study group than in the control group,whereas cortisol,corticotropin-releasing hormone,and adrenocorticotropic hormone levels were significantly lower(P<0.05).The total efficacy rates were 84.78%and 65.22%in the study and control groups,respectively(P<0.05).No significant differences in adverse reactions were observed between the two groups(P>0.05).CONCLUSION Combining SSRIs with Free San can enhance therapeutic efficacy,improve depressive symptoms,and regulate HPA axis function in patients with PSD with good safety and clinical application value.展开更多
GEMIN5 is a predominantly cytoplasmic multifunctional protein, known to be involved in recognizing snRNAs through its WD40 repeats domain placed at the N-terminus. A dimerization domain in the middle region acts as a ...GEMIN5 is a predominantly cytoplasmic multifunctional protein, known to be involved in recognizing snRNAs through its WD40 repeats domain placed at the N-terminus. A dimerization domain in the middle region acts as a hub for protein–protein interaction, while a non-canonical RNA-binding site is placed towards the C-terminus. The singular organization of structural domains present in GEMIN5 enables this protein to perform multiple functions through its ability to interact with distinct partners, both RNAs and proteins. This protein exerts a different role in translation regulation depending on its physiological state, such that while GEMIN5 down-regulates global RNA translation, the C-terminal half of the protein promotes translation of its mRNA. Additionally, GEMIN5 is responsible for the preferential partitioning of mRNAs into polysomes. Besides selective translation, GEMIN5 forms part of distinct ribonucleoprotein complexes, reflecting the dynamic organization of macromolecular complexes in response to internal and external signals. In accordance with its contribution to fundamental cellular processes, recent reports described clinical loss of function mutants suggesting that GEMIN5 deficiency is detrimental to cell growth and survival. Remarkably, patients carrying GEMIN5 biallelic variants suffer from neurodevelopmental delay, hypotonia, and cerebellar ataxia. Molecular analyses of individual variants, which are defective in protein dimerization, display decreased levels of ribosome association, reinforcing the involvement of the protein in translation regulation. Importantly, the number of clinical variants and the phenotypic spectrum associated with GEMIN5 disorders is increasing as the knowledge of the protein functions and the pathways linked to its activity augments. Here we discuss relevant advances concerning the functional and structural features of GEMIN5 and its separate domains in RNA-binding, protein interactome, and translation regulation, and how these data can help to understand the involvement of protein malfunction in clinical variants found in patients developing neurodevelopmental disorders.展开更多
Electrocatalytic nitrate reduction reaction(NO3RR)represents a sustainable and environmentally benign route for ammonia(NH3)synthesis.However,NO3RR is still limited by the competition from hydrogen evolution reaction(...Electrocatalytic nitrate reduction reaction(NO3RR)represents a sustainable and environmentally benign route for ammonia(NH3)synthesis.However,NO3RR is still limited by the competition from hydrogen evolution reaction(HER)and the high energy barrier in the hydrogenation step of nitrogen-containing intermediates.Here,we report a selective etching strategy to construct Ru M nanoalloys(M=Fe,Co,Ni,Cu)uniformly dispersed on porous nitrogen-doped carbon substrates for efficient neutral NH3electrosynthesis.Density functional theory calculations confirm that the synergic effect between Ru and transition metal M modulates the electronic structure of the alloy,significantly lowering the energy barrier for the conversion of*NO_(2)to*HNO_(2).Experimentally,the optimized Ru Fe-NC catalyst achieves 100%Faraday efficiency with a high yield rate of 0.83 mg h^(-1)mg^(-1)catat a low potential of-0.1 V vs.RHE,outperforming most reported catalysts.In situ spectroscopic analyses further demonstrate that the Ru M-NC effectively promotes the hydrogenation of nitrogen intermediates while inhibiting the formation of hydrogen radicals,thereby reducing HER competition.The Ru FeNC assembled Zn-NO_(3)^(-)battery achieved a high open-circuit voltage and an outstanding power density and capacity,which drive selective NO_(3)^(-)conversion to NH3.This work provides a powerful synergistic design strategy for efficient NH3electrosynthesis and a general framework for the development of advanced multi-component catalysts for sustainable nitrogen conversion.展开更多
Developing biomass platform compounds into high value-added chemicals is a key step in renewable resource utilization.Herein,we report porous carbon-supported Ni-ZnO nanoparticles catalyst(Ni-ZnO/AC)synthesized via lo...Developing biomass platform compounds into high value-added chemicals is a key step in renewable resource utilization.Herein,we report porous carbon-supported Ni-ZnO nanoparticles catalyst(Ni-ZnO/AC)synthesized via low-temperature coprecipitation,exhibiting excellent performance for the selective hydrogenation of 5-hydroxymethylfurfural(HMF).A linear correlation is first observed between solvent polarity(E_(T)(30))and product selectivity within both polar aprotic and protic solvent classes,suggesting that solvent properties play a vital role in directing reaction pathways.Among these,1,4-dioxane(aprotic)favors the formation of 2,5-bis(hydroxymethyl)furan(BHMF)with 97.5%selectivity,while isopropanol(iPrOH,protic)promotes 2,5-dimethylfuran production with up to 99.5%selectivity.Mechanistic investigations further reveal that beyond polarity,proton-donating ability is critical in facilitating hydrodeoxygenation.iPrOH enables a hydrogen shuttle mechanism where protons assist in hydroxyl group removal,lowering the activation barrier.In contrast,1,4-dioxane,lacking hydrogen bond donors,stabilizes BHMF and hinders further conversion.Density functional theory calculations confirm a lower activation energy in iPrOH(0.60 eV)compared to 1,4-dioxane(1.07 eV).This work offers mechanistic insights and a practical strategy for solvent-mediated control of product selectivity in biomass hydrogenation,highlighting the decisive role of solvent-catalyst-substrate interactions.展开更多
Automated essay scoring(AES)systems have gained significant importance in educational settings,offering a scalable,efficient,and objective method for evaluating student essays.However,developing AES systems for Arabic...Automated essay scoring(AES)systems have gained significant importance in educational settings,offering a scalable,efficient,and objective method for evaluating student essays.However,developing AES systems for Arabic poses distinct challenges due to the language’s complex morphology,diglossia,and the scarcity of annotated datasets.This paper presents a hybrid approach to Arabic AES by combining text-based,vector-based,and embeddingbased similarity measures to improve essay scoring accuracy while minimizing the training data required.Using a large Arabic essay dataset categorized into thematic groups,the study conducted four experiments to evaluate the impact of feature selection,data size,and model performance.Experiment 1 established a baseline using a non-machine learning approach,selecting top-N correlated features to predict essay scores.The subsequent experiments employed 5-fold cross-validation.Experiment 2 showed that combining embedding-based,text-based,and vector-based features in a Random Forest(RF)model achieved an R2 of 88.92%and an accuracy of 83.3%within a 0.5-point tolerance.Experiment 3 further refined the feature selection process,demonstrating that 19 correlated features yielded optimal results,improving R2 to 88.95%.In Experiment 4,an optimal data efficiency training approach was introduced,where training data portions increased from 5%to 50%.The study found that using just 10%of the data achieved near-peak performance,with an R2 of 85.49%,emphasizing an effective trade-off between performance and computational costs.These findings highlight the potential of the hybrid approach for developing scalable Arabic AES systems,especially in low-resource environments,addressing linguistic challenges while ensuring efficient data usage.展开更多
Existing feature selection methods for intrusion detection systems in the Industrial Internet of Things often suffer from local optimality and high computational complexity.These challenges hinder traditional IDS from...Existing feature selection methods for intrusion detection systems in the Industrial Internet of Things often suffer from local optimality and high computational complexity.These challenges hinder traditional IDS from effectively extracting features while maintaining detection accuracy.This paper proposes an industrial Internet ofThings intrusion detection feature selection algorithm based on an improved whale optimization algorithm(GSLDWOA).The aim is to address the problems that feature selection algorithms under high-dimensional data are prone to,such as local optimality,long detection time,and reduced accuracy.First,the initial population’s diversity is increased using the Gaussian Mutation mechanism.Then,Non-linear Shrinking Factor balances global exploration and local development,avoiding premature convergence.Lastly,Variable-step Levy Flight operator and Dynamic Differential Evolution strategy are introduced to improve the algorithm’s search efficiency and convergence accuracy in highdimensional feature space.Experiments on the NSL-KDD and WUSTL-IIoT-2021 datasets demonstrate that the feature subset selected by GSLDWOA significantly improves detection performance.Compared to the traditional WOA algorithm,the detection rate and F1-score increased by 3.68%and 4.12%.On the WUSTL-IIoT-2021 dataset,accuracy,recall,and F1-score all exceed 99.9%.展开更多
Atomically ordered precious intermetallic nanoparticles have garnered significant attention for diverse applications due to their well-defined surface atomic arrangements and exceptional electronic and geometric prope...Atomically ordered precious intermetallic nanoparticles have garnered significant attention for diverse applications due to their well-defined surface atomic arrangements and exceptional electronic and geometric properties.However,synthesizing non-precious ordered intermetallics that exhibit high stability under operating conditions remains a formidable challenge,primarily owing to their strong oxyphilicity,highly negative reduction potentials,and low corrosion resistance.In this work,we report a facile yet versatile seed-mediated solid-phase approach for fabricating uniform Ni_(3)Ga_(1) intermetallic nanocubes(NCs)fully encapsulated within N-doped carbon layers(denoted as Ni_(3)Ga_(1)@NC-800).Extensive characterization confirms the formation of a unique core-shell architecture,with atomic-resolution structural analysis and X-ray absorption fine structure measurements unequivocally verifying the atomically ordered Ni_(3)Ga_(1) intermetallic phase.The Ni_(3)Ga_(1)@NC-800 catalyst demonstrates exceptional performance in the 1,4-hydrogenation of α,β-unsaturated carbonyl compounds,exhibiting both remarkable activity and exclusive selectivity while maintaining high stability over multiple reaction cycles without observable performance decay.Combined experimental and theoretical calculations reveal that the strong interatomic p-d orbital hybridization facilitates electron transfer from Ga to Ni atoms,resulting in electron localization on ordered Ni atoms.This electronic configuration positively influences H_(2)activation and optimizes substrate adsorption strength,thereby substantially improving catalytic efficiency.Furthermore,this synthetic strategy proves generalizable,successfully extending to the synthesis of other non-precious ordered Ni_(1)Sn_(1) and Ni_(2)In_(3) intermetallics confined within N-doped carbon matrices.展开更多
Radiative cooling textiles with spectrally selective surfaces offer a promising energy-efficient approach for sub-ambient cooling of outdoor objects and individuals.However,the spectrally selective mid-infrared emissi...Radiative cooling textiles with spectrally selective surfaces offer a promising energy-efficient approach for sub-ambient cooling of outdoor objects and individuals.However,the spectrally selective mid-infrared emission of these textiles significantly hinders their efficient radiative heat exchange with self-heated objects,thereby posing a significant challenge to their versatile cooling applicability.Herein,we present a bicomponent blow spinning strategy for the production of scalable,ultra-flexible,and healable textiles featuring a tailored dual gradient in both chemical composition and fiber diameter.The gradient in the fiber diameter of this textile introduces a hierarchically porous structure across the sunlight incident area,thereby achieving a competitive solar reflectivity of 98.7%on its outer surface.Additionally,the gradient in the chemical composition of this textile contributes to the formation of Janus infrared-absorbing surfaces:The outer surface demonstrates a high mid-infrared emission,whereas the inner surface shows a broad infrared absorptivity,facilitating radiative heat exchange with underlying self-heated objects.Consequently,this textile demonstrates multi-scenario radiative cooling capabilities,enabling versatile outdoor cooling for unheated objects by 7.8℃ and self-heated objects by 13.6℃,compared to commercial sunshade fabrics.展开更多
文摘We discuss the set-valued dynamics related to the theory of functional equations.We look for selections of convex set-valued functions satisfying set-valued Euler-Lagrange inclusions.We improve and extend upon some of the results in[13,20],but under weaker assumptions.Some applications of our results are also provided.
文摘A way to extend operators in spaces of continuous functions to spaces of continuous set_valued functions is proposed. This extension is developed through the Steiner selections of the set_valued functions. Their properties and characteristics of the convergence of sequences of operators of this class are studied. In Part Ⅱ of this series some applications to approximation theory will be shown.
文摘The concept of finitely continuous topological space is introduced and the basic properties of the space are given. Several continuous selection theorems and fixed point theorems for Ф-maps are established, and as applications of the above fixed point theorems, some section problems are discussed. The results generalize and improve many corresponding conclusions.
文摘On the basis of Part (Ⅰ) of this series some applications to the approximation of set_valued functions are obtained: Korovkin type theorems, a method to extend classical approximation operators to the set_valued setting and a Jackson type estimate.
基金supported by the“China Natural Science Fund under grant 11871181”the“China Natural Science Fund under grant 11561053”。
文摘In this paper,we prove that if X is an almost convex and 2-strictly convex space,linear operator T:X→Y is bounded,N(T)is an approximative compact Chebyshev subspace of X and R(T)is a 3-Chebyshev hyperplane,then there exists a homogeneous selection T^(σ)of T^(■)such that continuous points of T^(σ)and T^(■)are dense on Y.
文摘We shall introduce 1-type Lipschitz multifunctions from R into generalized 2-normed spaces, and give some results about their 1-type Lipschitz selections.
文摘Five male kiwifruit selections Truwind M1, M2, M3, M4 and M5 bred by Hunan Horticultural Research Institute (HHRI)have been observed on the suitability,of which Truwind M1,M2 and M3 are Actinidia chinensis,Truwind M4 and M5 are Actinidia deliciosa. In terms of flower period Truwind M1 is early and 7 days, which is the suitable pollinator for‘Fengyue’;Truwind M2 is intermediate with 15 days,suitable for ‘Kuimi’and‘Lushanxiang’;Truwind M3 and M4 are 14 days and 13 days respectively,suitable for‘Cuiyu’and‘Miliang 1’;Truwind M5 is late and 8 days, suitable for‘Jinkui’,‘Qinxiang’and‘Hayward’.
基金Supported by the National Natural Science Foundation of China(12261018)Universities Key Laboratory of Mathematical Modeling and Data Mining in Guizhou Province(2023013)。
文摘In this paper,we establish and study a single-species logistic model with impulsive age-selective harvesting.First,we prove the ultimate boundedness of the solutions of the system.Then,we obtain conditions for the asymptotic stability of the trivial solution and the positive periodic solution.Finally,numerical simulations are presented to validate our results.Our results show that age-selective harvesting is more conducive to sustainable population survival than non-age-selective harvesting.
基金National Natural Science Foundation of China(51504138,51674118,52271177)Hunan Provincial Natural Science Foundation of China(2023JJ50181)Supported by State Key Laboratory of Materials Processing and Die&Mould Technology,Huazhong University of Science and Technology(P2024-022)。
文摘To explore the formation mechanism of anisotropy in Ti-6Al-4V alloy fabricated by selective laser melting(SLM),the compressive mechanical properties,microhardness,microstructure,and crystallographic orientation of the alloy across different planes were investigated.The anisotropy of SLM-fabricated Ti-6Al-4V alloys was analyzed,and the electron backscatter diffraction technique was used to investigate the influence of different grain types and orientations on the stress-strain distribution at various scales.Results reveal that in room-temperature compression tests at a strain rate of 10^(-3) s^(-1),both the compressive yield strength and microhardness vary along the deposition direction,indicating a certain degree of mechanical property anisotropy.The alloy exhibits a columnar microstructure;along the deposition direction,the grains appear equiaxed,and they have internal hexagonal close-packed(hcp)α/α'martensitic structure.α'phase has a preferential orientation approximately along the<0001>direction.Anisotropy arises from the high aspect ratio of columnar grains,along with the weak texture of the microstructure and low symmetry of the hcp crystal structure.
基金supported by Ho Chi Minh City Open University,Vietnam under grant number E2024.02.1CD and Suan Sunandha Rajabhat University,Thailand.
文摘The Financial Technology(FinTech)sector has witnessed rapid growth,resulting in increasingly complex and high-volume digital transactions.Although this expansion improves efficiency and accessibility,it also introduces significant vulnerabilities,including fraud,money laundering,and market manipulation.Traditional anomaly detection techniques often fail to capture the relational and dynamic characteristics of financial data.Graph Neural Networks(GNNs),capable of modeling intricate interdependencies among entities,have emerged as a powerful framework for detecting subtle and sophisticated anomalies.However,the high-dimensionality and inherent noise of FinTech datasets demand robust feature selection strategies to improve model scalability,performance,and interpretability.This paper presents a comprehensive survey of GNN-based approaches for anomaly detection in FinTech,with an emphasis on the synergistic role of feature selection.We examine the theoretical foundations of GNNs,review state-of-the-art feature selection techniques,analyze their integration with GNNs,and categorize prevalent anomaly types in FinTech applications.In addition,we discuss practical implementation challenges,highlight representative case studies,and propose future research directions to advance the field of graph-based anomaly detection in financial systems.
基金the National Natural Science Foundation of China(Nos.52122312,22209024,and 52473294)Tongcheng R&D Foundation(No.CPCIF-RA-0102)the State Key Laboratory of Advanced Fiber Materials,Donghua University.
文摘The carbon dioxide reduction reaction(CO_(2)RR)is a promising strategy for converting CO_(2)into high-value chemicals.However,the rational design of efficient catalysts for steering product selectivity toward specific high-value chemicals continues to be a central goal in electrocatalysis research.Recently,nanoporous confined electrocatalysts have garnered attention due to their unique pore structures,which not only increase the accessibility and utilization of active sites but also promote the enrichment and stabilization of key reaction intermediates and modulate the local reaction microenvironment.These combined effects contribute to improved reaction kinetics and enhanced product selectivity.This review systematically summarizes the mechanistic foundations of nanoporous confinement in CO_(2)RR,emphasizing its role in governing reaction pathways and selectivity.We introduce the fundamental design principles of nanoporous confined electrocatalysts,detailing how their pore size,tortuosity,and connectivity influence CO_(2)diffusion,local concentration gradients,and electrolyte accessibility.Then highlight how confinement-induced spatial regulation facilitates intermediate accumulation,directional proton transfer,and local pH modulation,collectively steering product selectivity toward desired C_(1) and multi-carbon(C_(2+))products.Representative material systems and structure-performance relationships are discussed to illustrate these effects.Finally,we summarize the current challenges in mechanistic understanding and practical implementation,and propose future directions for developing nanoporous systems that integrate controlled transport,catalytic reactivity,and system-level scalability.
文摘With the increasing complexity of vehicular networks and the proliferation of connected vehicles,Federated Learning(FL)has emerged as a critical framework for decentralized model training while preserving data privacy.However,efficient client selection and adaptive weight allocation in heterogeneous and non-IID environments remain challenging.To address these issues,we propose Federated Learning with Client Selection and Adaptive Weighting(FedCW),a novel algorithm that leverages adaptive client selection and dynamic weight allocation for optimizing model convergence in real-time vehicular networks.FedCW selects clients based on their Euclidean distance from the global model and dynamically adjusts aggregation weights to optimize both data diversity and model convergence.Experimental results show that FedCW significantly outperforms existing FL algorithms such as FedAvg,FedProx,and SCAFFOLD,particularly in non-IID settings,achieving faster convergence,higher accuracy,and reduced communication overhead.These findings demonstrate that FedCW provides an effective solution for enhancing the performance of FL in heterogeneous,edge-based computing environments.
基金Supported by Open Project of Jiangsu Province Key Laboratory of Integrated Traditional Chinese and Western Medicine for the Prevention and Treatment of Geriatric Diseases,No.202232.
文摘BACKGROUND Post-stroke depression(PSD)is associated with hypothalamic-pituitary-adrenal(HPA)axis dysfunction and neurotransmitter deficits.Selective serotonin reuptake inhibitors(SSRIs)are commonly used,but their efficacy is limited.This study investigated whether combining SSRIs with traditional Chinese medicine(TCM)Free San could enhance their therapeutic effects.AIM To evaluate the clinical efficacy and safety of combining SSRIs with Free San in treating PSD,and to assess its impact on HPA axis function.METHODS Ninety-two patients with PSD were enrolled and randomly divided into control groups(n=46)and study groups(n=46).The control group received the SSRI paroxetine alone,whereas the study group received paroxetine combined with Free San for 4 weeks.Hamilton Depression Scale and TCM syndrome scores were assessed before and after treatment.Serum serotonin,norepinephrine,cortisol,cor-ticotropin-releasing hormone,and adrenocorticotropic hormone were measured.The treatment responses and adverse reactions were recorded.RESULTS After treatment,the Hamilton Depression Scale and TCM syndrome scores were significantly lower in the study group than in the control group(P<0.05).Serum serotonin and norepinephrine levels were significantly higher in the study group than in the control group,whereas cortisol,corticotropin-releasing hormone,and adrenocorticotropic hormone levels were significantly lower(P<0.05).The total efficacy rates were 84.78%and 65.22%in the study and control groups,respectively(P<0.05).No significant differences in adverse reactions were observed between the two groups(P>0.05).CONCLUSION Combining SSRIs with Free San can enhance therapeutic efficacy,improve depressive symptoms,and regulate HPA axis function in patients with PSD with good safety and clinical application value.
基金partially supported by grants PID2020-115096RB-I00 and PID2023-148273NB-I00 from Ministerio de Ciencia y Universidad (MICIU/AEI)(to EMS)。
文摘GEMIN5 is a predominantly cytoplasmic multifunctional protein, known to be involved in recognizing snRNAs through its WD40 repeats domain placed at the N-terminus. A dimerization domain in the middle region acts as a hub for protein–protein interaction, while a non-canonical RNA-binding site is placed towards the C-terminus. The singular organization of structural domains present in GEMIN5 enables this protein to perform multiple functions through its ability to interact with distinct partners, both RNAs and proteins. This protein exerts a different role in translation regulation depending on its physiological state, such that while GEMIN5 down-regulates global RNA translation, the C-terminal half of the protein promotes translation of its mRNA. Additionally, GEMIN5 is responsible for the preferential partitioning of mRNAs into polysomes. Besides selective translation, GEMIN5 forms part of distinct ribonucleoprotein complexes, reflecting the dynamic organization of macromolecular complexes in response to internal and external signals. In accordance with its contribution to fundamental cellular processes, recent reports described clinical loss of function mutants suggesting that GEMIN5 deficiency is detrimental to cell growth and survival. Remarkably, patients carrying GEMIN5 biallelic variants suffer from neurodevelopmental delay, hypotonia, and cerebellar ataxia. Molecular analyses of individual variants, which are defective in protein dimerization, display decreased levels of ribosome association, reinforcing the involvement of the protein in translation regulation. Importantly, the number of clinical variants and the phenotypic spectrum associated with GEMIN5 disorders is increasing as the knowledge of the protein functions and the pathways linked to its activity augments. Here we discuss relevant advances concerning the functional and structural features of GEMIN5 and its separate domains in RNA-binding, protein interactome, and translation regulation, and how these data can help to understand the involvement of protein malfunction in clinical variants found in patients developing neurodevelopmental disorders.
基金financially supported by National Natural Science Foundation of China(22466010)Guizhou Provincial Basic Research Program(Natural Science)ZK[2023]47 and key program ZD[2025]075+6 种基金Innovation and Entrepreneurship Project for overseas Talents in Guizhou Province[2022]02Specific Natural Science Foundation of Guizhou University(X202207)the national undergraduate innovation and entrepreneurship training program(gzugc2023006gzusc2024012)SRT project of Guizhou university(2023SRT0292023SRT024)supported by Shanghai Technical Service Center of Science and Engineering Computing,Shanghai University。
文摘Electrocatalytic nitrate reduction reaction(NO3RR)represents a sustainable and environmentally benign route for ammonia(NH3)synthesis.However,NO3RR is still limited by the competition from hydrogen evolution reaction(HER)and the high energy barrier in the hydrogenation step of nitrogen-containing intermediates.Here,we report a selective etching strategy to construct Ru M nanoalloys(M=Fe,Co,Ni,Cu)uniformly dispersed on porous nitrogen-doped carbon substrates for efficient neutral NH3electrosynthesis.Density functional theory calculations confirm that the synergic effect between Ru and transition metal M modulates the electronic structure of the alloy,significantly lowering the energy barrier for the conversion of*NO_(2)to*HNO_(2).Experimentally,the optimized Ru Fe-NC catalyst achieves 100%Faraday efficiency with a high yield rate of 0.83 mg h^(-1)mg^(-1)catat a low potential of-0.1 V vs.RHE,outperforming most reported catalysts.In situ spectroscopic analyses further demonstrate that the Ru M-NC effectively promotes the hydrogenation of nitrogen intermediates while inhibiting the formation of hydrogen radicals,thereby reducing HER competition.The Ru FeNC assembled Zn-NO_(3)^(-)battery achieved a high open-circuit voltage and an outstanding power density and capacity,which drive selective NO_(3)^(-)conversion to NH3.This work provides a powerful synergistic design strategy for efficient NH3electrosynthesis and a general framework for the development of advanced multi-component catalysts for sustainable nitrogen conversion.
基金the National Nature Science Foundation of China for Excellent Young Scientists Fund(32222058)Fundamental Research Foundation of CAF(CAFYBB2022QB001).
文摘Developing biomass platform compounds into high value-added chemicals is a key step in renewable resource utilization.Herein,we report porous carbon-supported Ni-ZnO nanoparticles catalyst(Ni-ZnO/AC)synthesized via low-temperature coprecipitation,exhibiting excellent performance for the selective hydrogenation of 5-hydroxymethylfurfural(HMF).A linear correlation is first observed between solvent polarity(E_(T)(30))and product selectivity within both polar aprotic and protic solvent classes,suggesting that solvent properties play a vital role in directing reaction pathways.Among these,1,4-dioxane(aprotic)favors the formation of 2,5-bis(hydroxymethyl)furan(BHMF)with 97.5%selectivity,while isopropanol(iPrOH,protic)promotes 2,5-dimethylfuran production with up to 99.5%selectivity.Mechanistic investigations further reveal that beyond polarity,proton-donating ability is critical in facilitating hydrodeoxygenation.iPrOH enables a hydrogen shuttle mechanism where protons assist in hydroxyl group removal,lowering the activation barrier.In contrast,1,4-dioxane,lacking hydrogen bond donors,stabilizes BHMF and hinders further conversion.Density functional theory calculations confirm a lower activation energy in iPrOH(0.60 eV)compared to 1,4-dioxane(1.07 eV).This work offers mechanistic insights and a practical strategy for solvent-mediated control of product selectivity in biomass hydrogenation,highlighting the decisive role of solvent-catalyst-substrate interactions.
基金funded by Deanship of Graduate studies and Scientific Research at Jouf University under grant No.(DGSSR-2024-02-01264).
文摘Automated essay scoring(AES)systems have gained significant importance in educational settings,offering a scalable,efficient,and objective method for evaluating student essays.However,developing AES systems for Arabic poses distinct challenges due to the language’s complex morphology,diglossia,and the scarcity of annotated datasets.This paper presents a hybrid approach to Arabic AES by combining text-based,vector-based,and embeddingbased similarity measures to improve essay scoring accuracy while minimizing the training data required.Using a large Arabic essay dataset categorized into thematic groups,the study conducted four experiments to evaluate the impact of feature selection,data size,and model performance.Experiment 1 established a baseline using a non-machine learning approach,selecting top-N correlated features to predict essay scores.The subsequent experiments employed 5-fold cross-validation.Experiment 2 showed that combining embedding-based,text-based,and vector-based features in a Random Forest(RF)model achieved an R2 of 88.92%and an accuracy of 83.3%within a 0.5-point tolerance.Experiment 3 further refined the feature selection process,demonstrating that 19 correlated features yielded optimal results,improving R2 to 88.95%.In Experiment 4,an optimal data efficiency training approach was introduced,where training data portions increased from 5%to 50%.The study found that using just 10%of the data achieved near-peak performance,with an R2 of 85.49%,emphasizing an effective trade-off between performance and computational costs.These findings highlight the potential of the hybrid approach for developing scalable Arabic AES systems,especially in low-resource environments,addressing linguistic challenges while ensuring efficient data usage.
基金supported by the Major Science and Technology Programs in Henan Province(No.241100210100)Henan Provincial Science and Technology Research Project(No.252102211085,No.252102211105)+3 种基金Endogenous Security Cloud Network Convergence R&D Center(No.602431011PQ1)The Special Project for Research and Development in Key Areas of Guangdong Province(No.2021ZDZX1098)The Stabilization Support Program of Science,Technology and Innovation Commission of Shenzhen Municipality(No.20231128083944001)The Key scientific research projects of Henan higher education institutions(No.24A520042).
文摘Existing feature selection methods for intrusion detection systems in the Industrial Internet of Things often suffer from local optimality and high computational complexity.These challenges hinder traditional IDS from effectively extracting features while maintaining detection accuracy.This paper proposes an industrial Internet ofThings intrusion detection feature selection algorithm based on an improved whale optimization algorithm(GSLDWOA).The aim is to address the problems that feature selection algorithms under high-dimensional data are prone to,such as local optimality,long detection time,and reduced accuracy.First,the initial population’s diversity is increased using the Gaussian Mutation mechanism.Then,Non-linear Shrinking Factor balances global exploration and local development,avoiding premature convergence.Lastly,Variable-step Levy Flight operator and Dynamic Differential Evolution strategy are introduced to improve the algorithm’s search efficiency and convergence accuracy in highdimensional feature space.Experiments on the NSL-KDD and WUSTL-IIoT-2021 datasets demonstrate that the feature subset selected by GSLDWOA significantly improves detection performance.Compared to the traditional WOA algorithm,the detection rate and F1-score increased by 3.68%and 4.12%.On the WUSTL-IIoT-2021 dataset,accuracy,recall,and F1-score all exceed 99.9%.
基金financially supported by the program of the National Natural Science Foundation of Shandong Province(No.ZR2023ZD23)the Shandong Province Key Research and Development Plan(No.2023CXGC010607).
文摘Atomically ordered precious intermetallic nanoparticles have garnered significant attention for diverse applications due to their well-defined surface atomic arrangements and exceptional electronic and geometric properties.However,synthesizing non-precious ordered intermetallics that exhibit high stability under operating conditions remains a formidable challenge,primarily owing to their strong oxyphilicity,highly negative reduction potentials,and low corrosion resistance.In this work,we report a facile yet versatile seed-mediated solid-phase approach for fabricating uniform Ni_(3)Ga_(1) intermetallic nanocubes(NCs)fully encapsulated within N-doped carbon layers(denoted as Ni_(3)Ga_(1)@NC-800).Extensive characterization confirms the formation of a unique core-shell architecture,with atomic-resolution structural analysis and X-ray absorption fine structure measurements unequivocally verifying the atomically ordered Ni_(3)Ga_(1) intermetallic phase.The Ni_(3)Ga_(1)@NC-800 catalyst demonstrates exceptional performance in the 1,4-hydrogenation of α,β-unsaturated carbonyl compounds,exhibiting both remarkable activity and exclusive selectivity while maintaining high stability over multiple reaction cycles without observable performance decay.Combined experimental and theoretical calculations reveal that the strong interatomic p-d orbital hybridization facilitates electron transfer from Ga to Ni atoms,resulting in electron localization on ordered Ni atoms.This electronic configuration positively influences H_(2)activation and optimizes substrate adsorption strength,thereby substantially improving catalytic efficiency.Furthermore,this synthetic strategy proves generalizable,successfully extending to the synthesis of other non-precious ordered Ni_(1)Sn_(1) and Ni_(2)In_(3) intermetallics confined within N-doped carbon matrices.
基金financial support from the National Natural Science Foundation of China(Grant No.52273067,52233006)the Fundamental Research Funds for the Central Universities(Grant No.2232023A-03)+3 种基金the Shuguang Program of Shanghai Education Development Foundation and Shanghai Municipal Education Commission(Grant No.23SG29)the Natural Science Foundation of Shanghai(Grant No.24ZR1402400)the Shanghai Scientific and Technological Innovation Project(Grant No.24520713000)Innovation Program of Shanghai Municipal Education Commission(Grant No.2021-01-07-00-03-E00108).
文摘Radiative cooling textiles with spectrally selective surfaces offer a promising energy-efficient approach for sub-ambient cooling of outdoor objects and individuals.However,the spectrally selective mid-infrared emission of these textiles significantly hinders their efficient radiative heat exchange with self-heated objects,thereby posing a significant challenge to their versatile cooling applicability.Herein,we present a bicomponent blow spinning strategy for the production of scalable,ultra-flexible,and healable textiles featuring a tailored dual gradient in both chemical composition and fiber diameter.The gradient in the fiber diameter of this textile introduces a hierarchically porous structure across the sunlight incident area,thereby achieving a competitive solar reflectivity of 98.7%on its outer surface.Additionally,the gradient in the chemical composition of this textile contributes to the formation of Janus infrared-absorbing surfaces:The outer surface demonstrates a high mid-infrared emission,whereas the inner surface shows a broad infrared absorptivity,facilitating radiative heat exchange with underlying self-heated objects.Consequently,this textile demonstrates multi-scenario radiative cooling capabilities,enabling versatile outdoor cooling for unheated objects by 7.8℃ and self-heated objects by 13.6℃,compared to commercial sunshade fabrics.
