In this work,we proposed a strategy for the hydrolysis of native corn starch after the treatment of corn starch in an ionic liquid aqueous solution,and it is an awfully“green”and simple means to obtain starch with l...In this work,we proposed a strategy for the hydrolysis of native corn starch after the treatment of corn starch in an ionic liquid aqueous solution,and it is an awfully“green”and simple means to obtain starch with low molecular weight and amorphous state.X-ray diffraction results revealed that the natural starch crystalline region was largely disrupted by ionic liquid owing to the broken intermolecular and intramolecular hydrogen bonds.After hydrolysis,the morphology of starch changed from particles of native corn starch into little pieces,and their molecular weight could be effectively regulated during the hydrolysis process,and also the hydrolyzed starch samples exhibited decreased thermal stability with the extension of hydrolysis time.This work would counsel as a powerful tool for the development of native starch in realistic applications.展开更多
In this paper,we present a necessary and sufficient condition for hyponormal block Toeplitz operators T on the vector-valued weighted Bergman space with symbolsΦ(z)=G^(*)(z)+F(z),where F(z)=∑^(N)_(i)=1 A_(i)z^(i)and...In this paper,we present a necessary and sufficient condition for hyponormal block Toeplitz operators T on the vector-valued weighted Bergman space with symbolsΦ(z)=G^(*)(z)+F(z),where F(z)=∑^(N)_(i)=1 A_(i)z^(i)and G(z)=∑^(N)_(i)=1 A_(−i)z^(i),A_(i)ae culants.展开更多
Modern battlefields exhibit high dynamism,where traditional static weighting methods in combat effectiveness assessment fail to capture real-time changes in indicator values,leading to limited assessment accuracy—esp...Modern battlefields exhibit high dynamism,where traditional static weighting methods in combat effectiveness assessment fail to capture real-time changes in indicator values,leading to limited assessment accuracy—especially critical in scenarios like sudden electronic warfare or degraded command,where static weights cannot reflect the operational value decay or surge of key indicators.To address this issue,this study proposes a dynamic adaptive weightingmethod for evaluation indicators based onG1-CRITIC-PIVW.First,theG1(Sequential Relationship Analysis Method)subjective weighting method—translates expert knowledge into indicator importance rankings—leverages expert knowledge to quantify the relative importance of indicators via sequential relationship ranking,while the CRITIC(Criteria Importance Through Intercriteria Correlation)objective weighting method—derives weights from data characteristics by integrating variability and inter-correlations—calculates weights by integrating indicator variability and inter-indicator correlations,ensuring data-driven objectivity.These two sets of weights are then fused using a deviation coefficient optimization model,minimizing the squared deviation from a reference weight and adjusting the fusion coefficient via Spearman’s rank correlation to resolve potential conflicts between subjective and objective judgments.Subsequently,the PIVW(Punishment-Incentive VariableWeight)theory—adapts weights to realtime indicator performance via penalty/incentive rules—is applied for dynamic adjustment.Scenario-specific penalty λ_(1) and incentive λ_(2) thresholds are set based on operational priorities and indicator volatility,penalizing indicators with values below λ_(1) and incentivizing those exceeding λ_(2) to reflect real-time indicator performance.Experimental validation was conducted using an Air Defense and Anti-Missile(ADAM)system effectiveness assessment framework,with data covering 7 indicators across 3 combat scenarios.Results show that compared to static weighting methods,the proposed method reduces MAE(Mean Absolute Error)by 15%-20% and weighted decision error rate by 84.2%,effectively reducing overestimation/underestimation of combat effectiveness in dynamic scenarios;compared to Entropy-TOPSIS,it lowers MAE by 12% while achieving a weighted Kendall’sτconsistency coefficient of 0.85,ensuring higher alignment with expert judgment.This method enhances the accuracy and scenario adaptability of effectiveness assessment,providing reliable decision support for dynamic battlefield environments.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
This paper is dedicated to fixed-time passivity and synchronization for multi-weighted spatiotemporal directed networks.First,to achieve fixed-time passivity,a type of decentralized power-law controller is developed,i...This paper is dedicated to fixed-time passivity and synchronization for multi-weighted spatiotemporal directed networks.First,to achieve fixed-time passivity,a type of decentralized power-law controller is developed,in which only one parameter needs to be adjusted in the power-law terms;this greatly decreases the inconvenience of parameter adjustment.Second,several fixed-time passivity criteria with LMI forms are derived by using a Gauss divergence theorem to deal with the spatial diffusion of nodes and by applying the Hölder’s inequality to dispose rigorously the power-law term greater than one in the designed control scheme;this improves the previous theoretical analysis.Additionally,the fixed-time synchronization of spatiotemporal directed networks with multi-weights is addressed as a direct result of fixed-time strict passivity.Finally,a numerical example is presented in order to show the validity of the theoretical analysis.展开更多
Ultra-high molecular weight polyethylene(UHMWPE)is a key material for marine applications owing to its outstanding self-lubrication and corrosion resistance.However,its long-term performance is compromised by plastic ...Ultra-high molecular weight polyethylene(UHMWPE)is a key material for marine applications owing to its outstanding self-lubrication and corrosion resistance.However,its long-term performance is compromised by plastic deformation in seawater.In this study,we performed a comparative analysis of the UHMWPE dynamics under seawater and water conditions to investigate the plastic deformation of UHMWPE induced by seawater.The results show that the plastic deformation of UHMWPE is amplified in seawater relative to the water conditions.Under thin fluid conditions,frictional interfaces exhibit a higher interfacial friction force and interaction energy in seawater than in water.Compared to freely diffused water molecules,hydrated ions occupy larger interchain spaces within polyethylene.Furthermore,the diffusion of hydrated ions weakens the interchain interactions,promoting more severe polyethylene chain rearrangement and accelerating seawater-induced plastic deformation in UHMWPE during friction.Furthermore,the diffused seawater accelerated the disentangling of the polyethylene chains and enhanced the orderly orientation distribution of polyethylene.Compared to free water molecules,the water molecules of hydrated ions exhibit enhanced attraction to free-flowing water molecules,thereby accelerating seawater flow across submerged UHMWPE surfaces.This flow enhancement promotes surface polyethylene chain mobility in seawater.展开更多
In image analysis,high-precision semantic segmentation predominantly relies on supervised learning.Despite significant advancements driven by deep learning techniques,challenges such as class imbalance and dynamic per...In image analysis,high-precision semantic segmentation predominantly relies on supervised learning.Despite significant advancements driven by deep learning techniques,challenges such as class imbalance and dynamic performance evaluation persist.Traditional weighting methods,often based on pre-statistical class counting,tend to overemphasize certain classes while neglecting others,particularly rare sample categories.Approaches like focal loss and other rare-sample segmentation techniques introduce multiple hyperparameters that require manual tuning,leading to increased experimental costs due to their instability.This paper proposes a novel CAWASeg framework to address these limitations.Our approach leverages Grad-CAM technology to generate class activation maps,identifying key feature regions that the model focuses on during decision-making.We introduce a Comprehensive Segmentation Performance Score(CSPS)to dynamically evaluate model performance by converting these activation maps into pseudo mask and comparing them with Ground Truth.Additionally,we design two adaptive weights for each class:a Basic Weight(BW)and a Ratio Weight(RW),which the model adjusts during training based on real-time feedback.Extensive experiments on the COCO-Stuff,CityScapes,and ADE20k datasets demonstrate that our CAWASeg framework significantly improves segmentation performance for rare sample categories while enhancing overall segmentation accuracy.The proposed method offers a robust and efficient solution for addressing class imbalance in semantic segmentation tasks.展开更多
The accessibility of urban public transit directly influences residents’quality of life,travel behavior,and social equity.Its correlation with housing prices has garnered significant attention across disciplines such...The accessibility of urban public transit directly influences residents’quality of life,travel behavior,and social equity.Its correlation with housing prices has garnered significant attention across disciplines such as geography,economics,and urban planning.Although much existing research focuses on the impact of individual transportation facilities on housing prices,there is a notable gap in comprehensive analyses that assess the influence of overall urban transit accessibility on housing market dynamics.This study selected the main urban area of Hefei,China,as a case to investigate the spatial distribution of housing prices and evaluate public transit accessibility in 2022.Employing techniques such as the optimized parameter geographical detector and local spatial regression models,the study aimed to elucidate the effects and underlying mechanisms of urban transit accessibility on housing prices.The findings revealed that:1)housing prices in Hefei exhibited a clustered spatial pattern,with high prices concentrated in the city center and lower prices in peripheral areas,forming three distinct high-price hotspots with a‘belt-like’distribution;2)public transit accessibility showed a‘coreperiphery’structure,with accessibility declining in a‘circumferential’pattern around the city center.Based on the‘housing price-accessibility’dimension,four categories were identified:high price-high accessibility(37.25%),high price-low accessibility(19.07%),low price-high accessibility(21.95%),and low price-low accessibility(21.73%);3)the impact of transit accessibility on housing prices was spatially heterogeneous,with bus travel showing the strongest explanatory power(0.692),followed by automobile,subway,and bicycle travel.The interaction of these transportation modes generated a synergistic effect on housing price differentiation,with most influencing factors contributing more than 25%.These findings offer valuable insights for optimizing the spatial distribution of public transit infrastructure and improving both urban housing quality and residents’living standards.展开更多
This study investigated the physicochemical properties,enzyme activities,volatile flavor components,microbial communities,and sensory evaluation of high-temperature Daqu(HTD)during the maturation process,and a standar...This study investigated the physicochemical properties,enzyme activities,volatile flavor components,microbial communities,and sensory evaluation of high-temperature Daqu(HTD)during the maturation process,and a standard system was established for comprehensive quality evaluation of HTD.There were obvious changes in the physicochemical properties,enzyme activities,and volatile flavor components at different storage periods,which affected the sensory evaluation of HTD to a certain extent.The results of high-throughput sequencing revealed significant microbial diversity,and showed that the bacterial community changed significantly more than did the fungal community.During the storage process,the dominant bacterial genera were Kroppenstedtia and Thermoascus.The correlation between dominant microorganisms and quality indicators highlighted their role in HTD quality.Lactococcus,Candida,Pichia,Paecilomyces,and protease activity played a crucial role in the formation of isovaleraldehyde.Acidic protease activity had the greatest impact on the microbial community.Moisture promoted isobutyric acid generation.Furthermore,the comprehensive quality evaluation standard system was established by the entropy weight method combined with multi-factor fuzzy mathematics.Consequently,this study provides innovative insights for comprehensive quality evaluation of HTD during storage and establishes a groundwork for scientific and rational storage of HTD and quality control of sauce-flavor Baijiu.展开更多
Background Birth weight is a critical economic trait in livestock production.However,its genetic architecture remains poorly understood due to historical limitations in sample size and reliance on low-density SNP arra...Background Birth weight is a critical economic trait in livestock production.However,its genetic architecture remains poorly understood due to historical limitations in sample size and reliance on low-density SNP arrays.In this study,we utilized low-coverage whole-genome sequencing(lcWGS)to genotype 3,007 Hu sheep,bypassing the cost and resolution constraints of conventional genotyping arrays while achieving scalable genome-wide variant detection.Results LcWGS with high imputation accuracy(97.8%allelic concordance)enabled genome-wide association studies(GWAS)identifying two novel quantitative trait loci(QTLs)on chromosomes 6 and 9.The chromosome 9 QTL encompassed a regulatory region functionally linked to PLAG1 expression through expression quantitative trait locus(eQTL)mapping.Compared with wild-type homozygotes,heterozygous carriers of the lead SNP(chr9:g.35920172A>G)presented a 9.85%increase in birth weight(3.35 kg vs.3.68 kg;Δ=0.33 kg).Notably,the derived allele of this SNP exhibited low frequencies of<0.1 across most global sheep breeds except Dorper,highlighting its potential for selective breeding applications.Leveraging lcWGS data,haplotype-based fine-mapping prioritized three candidate causal variants.A secondary QTL on chromosome 6 colocalized with the FecB mutation,a well-established locus associated with increased litter size.Intriguingly,individuals carrying one FecB allele showed a 6.18%reduction(0.22 kg)in birth weight,which tentatively indicates potential pleiotropic influences on both growth and reproductive traits.Conclusion This study demonstrates the utility of lcWGS as a cost-effective,high-resolution tool for dissecting complex traits in livestock.Our findings not only advance the understanding of birth weight genetics in sheep but also offer a blueprint for accelerating genetic improvement programs in global livestock production through costeffective,genome-wide approaches.展开更多
Grain yield variation has been associated to variation in grain number per unit area(GN).It has been shown in the last about 40 years that GN is linearly associated to the spike dry weight(SDW)at anthesis in wheat,fac...Grain yield variation has been associated to variation in grain number per unit area(GN).It has been shown in the last about 40 years that GN is linearly associated to the spike dry weight(SDW)at anthesis in wheat,fact that has been useful to understand mechanistically potential grain yield.Fruiting efficiency(FE,grains per gram of spike dry weight),the slope between GN and SDW relationship,has been proposed as a possible trait to improve wheat yield potential.The linear relationship between GN and SDW implies a constant increase in GN per unit increase in spike growth and,then a constant FE.However,there are empirical and theoretical elements suggesting that this relationship would not be linear.In this study,we hypothesised and showed that the linearity of the relationship between GN and SDW would be non-linear for extreme values of SDW,implying that the FE would be noticeably reduced at these extreme cases of dry matter allocation to the juvenile spikes.These results have implications for both,genetic and management improvements in grain yield.展开更多
Prediction of stability in SG(Smart Grid)is essential in maintaining consistency and reliability of power supply in grid infrastructure.Analyzing the fluctuations in power generation and consumption patterns of smart ...Prediction of stability in SG(Smart Grid)is essential in maintaining consistency and reliability of power supply in grid infrastructure.Analyzing the fluctuations in power generation and consumption patterns of smart cities assists in effectively managing continuous power supply in the grid.It also possesses a better impact on averting overloading and permitting effective energy storage.Even though many traditional techniques have predicted the consumption rate for preserving stability,enhancement is required in prediction measures with minimized loss.To overcome the complications in existing studies,this paper intends to predict stability from the smart grid stability prediction dataset using machine learning algorithms.To accomplish this,pre-processing is performed initially to handle missing values since it develops biased models when missing values are mishandled and performs feature scaling to normalize independent data features.Then,the pre-processed data are taken for training and testing.Following that,the regression process is performed using Modified PSO(Particle Swarm Optimization)optimized XGBoost Technique with dynamic inertia weight update,which analyses variables like gamma(G),reaction time(tau1–tau4),and power balance(p1–p4)for providing effective future stability in SG.Since PSO attains optimal solution by adjusting position through dynamic inertial weights,it is integrated with XGBoost due to its scalability and faster computational speed characteristics.The hyperparameters of XGBoost are fine-tuned in the training process for achieving promising outcomes on prediction.Regression results are measured through evaluation metrics such as MSE(Mean Square Error)of 0.011312781,MAE(Mean Absolute Error)of 0.008596322,and RMSE(Root Mean Square Error)of 0.010636156 and MAPE(Mean Absolute Percentage Error)value of 0.0052 which determine the efficacy of the system.展开更多
Red-green-blue(RGB)beam combiners are widely used in scenarios such as augmented reality/virtual reality(AR/VR),laser projection,biochemical detection,and other fields.Optical waveguide combiners have attracted extens...Red-green-blue(RGB)beam combiners are widely used in scenarios such as augmented reality/virtual reality(AR/VR),laser projection,biochemical detection,and other fields.Optical waveguide combiners have attracted extensive attention due to their advantages of small size,high multiplexing efficiency,convenient mass production,and low cost.An RGB beam combiner based on directional couplers is designed,with a core-cladding relative refractive index difference of 0.75%.The RGB beam combiner is optimized from the perspective of parameter optimization.Using the beam propagation method(BPM),the relationship between the performance of the RGB beam combiner and individual parameters is studied,achieving preliminary optimization of the device’s performance.The key parameters of the RGB beam combiner are optimized using the entropy weight-technique for order preference by similarity to an ideal solution TOPSIS method,establishing the optimal parameter scheme and further improving the device’s performance indicators.The results show that after optimization,the multiplexing efficiencies for red,green,and blue lights,as well as the average multiplexing efficiency,reached 99.17%,99.76%,96.63%and 98.52%,respectively.The size of the RGB beam combiner is 4.768 mm×0.062 mm.展开更多
Objective To investigate the association between birth weight and dementia risk and the mediating roles of chronic diseases,and to assess potential biological pathways underlying the birth weight-associated dementia r...Objective To investigate the association between birth weight and dementia risk and the mediating roles of chronic diseases,and to assess potential biological pathways underlying the birth weight-associated dementia risk based on large-scale proteomics.Methods We used data from 279743 participants aged 40 to 69 years enrolled in the UK Biobank.Birth weight was categorized into low birth weight(≤2500 g),normal birth weight(2500-3999 g),and macrosomia(≥4000 g).Multivariable Cox proportional hazards regression models were used to assess the associations between birth weight categories and all-cause dementia and its subtypes(Alzheimer's disease and vascular dementia).Proteomics analyses were conducted to identify proteins and the potential pathways involved.Results Low birth weight was associated with higher risks for all-cause dementia and its subtypes.The hazard ratios were 1.18(95%CI,1.08-1.30)for all-cause dementia,1.14(95%CI,1.00-1.31)for Alzheimer's disease,and 1.22(95%CI,1.01-1.48)for vascular dementia.A non-linear relationship was observed between birth weight and dementia risk(P for nonlinearity<0.001).Certain cardiometabolic diseases in middle-aged adults,such as diabetes,stroke,hypertension,and dyslipidemia,played a significant mediating role in the relationship between low birth weight and dementia risk,with the mediation proportion being 6.3%to 15.8%.Proteomic analyses identified 21 proteins linked to both low birth weight and all-cause dementia risk,which were significantly enriched in the pathways for viral protein interaction with cytokines and cytokine receptors,adipocytokine signaling,and cytokine-cytokine receptor interaction.Conclusion Low birth weight is positively associated with dementia risk.Cardiometabolic diseases in middle-aged adults may mediate the relationship between low birth weight and dementia risk.A number of proteins and the associated pathways underscore the relationship between low birth weight and dementia risk.展开更多
Inhomogeneous Calderon-Zygmund operator T maps each atom into an approximate molecule of weighted local Hardy space if and only if some approximate cancellation condition holds for T.An equivalent norm for weighted Le...Inhomogeneous Calderon-Zygmund operator T maps each atom into an approximate molecule of weighted local Hardy space if and only if some approximate cancellation condition holds for T.An equivalent norm for weighted Lebesgue space which has vanishing moments up to order s plays an important role,where s∈N.展开更多
In this paper,the Paley-Wiener theorem is extended to the analytic function spaces with general weights.We first generalize the theorem to weighted Hardy spaces Hp(0<p<∞)on tube domains by constructing a sequen...In this paper,the Paley-Wiener theorem is extended to the analytic function spaces with general weights.We first generalize the theorem to weighted Hardy spaces Hp(0<p<∞)on tube domains by constructing a sequence of L^(1)functions converging to the given function and verifying their representation in the form of Fourier transform to establish the desired result of the given function.Applying this main result,we further generalize the Paley-Wiener theorem for band-limited functions to the analytic function spaces L^(p)(0<p<∞)with general weights.展开更多
Since the discovery of carbon dots(CDs)in 2004,the unique photoluminescence phenomenon of CDs has attracted widespread attention.However,the molecular weight of CDs has not been adequately quantified at present,due to...Since the discovery of carbon dots(CDs)in 2004,the unique photoluminescence phenomenon of CDs has attracted widespread attention.However,the molecular weight of CDs has not been adequately quantified at present,due to CDs are atomically imprecise and their molecular weight distribution is broad.In this paper,a series of Pluronic-modified CDs were prepared and the structure of the CDs was briefly analyzed.Subsequently,a molecular weight measurement method based on colligative properties was developed,and the correction coefficient in the algorithm was briefly analyzed.The calculated molecular weight was applied to the determination of surface adsorption capacity.This work provided a method for averaging the molecular weight of atomically imprecise particulate materials,which is expected to provide new opportunities in related fields.展开更多
The boundness and compactness of products of multiplication,composition and differentiation on weighted Bergman spaces in the unit ball are studied.We define the differentiation operator on the space of holomorphic fu...The boundness and compactness of products of multiplication,composition and differentiation on weighted Bergman spaces in the unit ball are studied.We define the differentiation operator on the space of holomorphic functions in the unit ball by radial derivative.Then we extend the Sharma's results.展开更多
Background: Birth weight has been identified as one of the most significant predictors of a child’s physical growth, development, and survival in later life. A quest to provide an answer on the impact of maternal ant...Background: Birth weight has been identified as one of the most significant predictors of a child’s physical growth, development, and survival in later life. A quest to provide an answer on the impact of maternal anthropometry on neonatal birth weight necessitated this study. Materials and methods: It is a cross-sectional descriptive hospital based study that involved 130 participants selected using a systematic sampling method, utilizing a semi-structured, pre-tested interviewer administered questionnaire. Data were collected using a standard procedure and were summarized using proportions, and the Chi square test was used to explore the association between categorical variables. Predictors of birth weight were determined using logistic regression. The level of statistical significance was set at p Results: Participants had a mean age of 28.6 ± 5.1 years, mean weight of 72.2 ± 11.2 kg and mean height of 1.63 ± 0.07m while the mean fetal birth weight was 3.10 ± 0.56 kg. There was a significant association between maternal delivery body mass index and neonatal birth weight (p Conclusion: The prevalence of low birth weight and macrosomia in this study population was high. The focus should be geared towards balanced nutrition support for all mothers at booking so as to mitigate the risks associated with these extremes of birth weight.展开更多
The aim of the present paper is to study 2-complex symmetric bounded weighted composition operators on the Fock space of C^(N) with the conjugations J and J_(t,A,b) defined by ■ respectively,where k(z_(1),...,z_N)=(...The aim of the present paper is to study 2-complex symmetric bounded weighted composition operators on the Fock space of C^(N) with the conjugations J and J_(t,A,b) defined by ■ respectively,where k(z_(1),...,z_N)=(■,...,■),t∈C,b∈C^(N) and A is a linear operator on C^(N).An example of 2-complex symmetric bounded weighted composition operator with the conjugation J_(t,A,b) is given.展开更多
文摘In this work,we proposed a strategy for the hydrolysis of native corn starch after the treatment of corn starch in an ionic liquid aqueous solution,and it is an awfully“green”and simple means to obtain starch with low molecular weight and amorphous state.X-ray diffraction results revealed that the natural starch crystalline region was largely disrupted by ionic liquid owing to the broken intermolecular and intramolecular hydrogen bonds.After hydrolysis,the morphology of starch changed from particles of native corn starch into little pieces,and their molecular weight could be effectively regulated during the hydrolysis process,and also the hydrolyzed starch samples exhibited decreased thermal stability with the extension of hydrolysis time.This work would counsel as a powerful tool for the development of native starch in realistic applications.
文摘In this paper,we present a necessary and sufficient condition for hyponormal block Toeplitz operators T on the vector-valued weighted Bergman space with symbolsΦ(z)=G^(*)(z)+F(z),where F(z)=∑^(N)_(i)=1 A_(i)z^(i)and G(z)=∑^(N)_(i)=1 A_(−i)z^(i),A_(i)ae culants.
基金funded by the National Natural Science Foundation of China(NSFC)under Grant Number 72071209.
文摘Modern battlefields exhibit high dynamism,where traditional static weighting methods in combat effectiveness assessment fail to capture real-time changes in indicator values,leading to limited assessment accuracy—especially critical in scenarios like sudden electronic warfare or degraded command,where static weights cannot reflect the operational value decay or surge of key indicators.To address this issue,this study proposes a dynamic adaptive weightingmethod for evaluation indicators based onG1-CRITIC-PIVW.First,theG1(Sequential Relationship Analysis Method)subjective weighting method—translates expert knowledge into indicator importance rankings—leverages expert knowledge to quantify the relative importance of indicators via sequential relationship ranking,while the CRITIC(Criteria Importance Through Intercriteria Correlation)objective weighting method—derives weights from data characteristics by integrating variability and inter-correlations—calculates weights by integrating indicator variability and inter-indicator correlations,ensuring data-driven objectivity.These two sets of weights are then fused using a deviation coefficient optimization model,minimizing the squared deviation from a reference weight and adjusting the fusion coefficient via Spearman’s rank correlation to resolve potential conflicts between subjective and objective judgments.Subsequently,the PIVW(Punishment-Incentive VariableWeight)theory—adapts weights to realtime indicator performance via penalty/incentive rules—is applied for dynamic adjustment.Scenario-specific penalty λ_(1) and incentive λ_(2) thresholds are set based on operational priorities and indicator volatility,penalizing indicators with values below λ_(1) and incentivizing those exceeding λ_(2) to reflect real-time indicator performance.Experimental validation was conducted using an Air Defense and Anti-Missile(ADAM)system effectiveness assessment framework,with data covering 7 indicators across 3 combat scenarios.Results show that compared to static weighting methods,the proposed method reduces MAE(Mean Absolute Error)by 15%-20% and weighted decision error rate by 84.2%,effectively reducing overestimation/underestimation of combat effectiveness in dynamic scenarios;compared to Entropy-TOPSIS,it lowers MAE by 12% while achieving a weighted Kendall’sτconsistency coefficient of 0.85,ensuring higher alignment with expert judgment.This method enhances the accuracy and scenario adaptability of effectiveness assessment,providing reliable decision support for dynamic battlefield environments.
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 the National Natural Science Foundation of China(62373317)the Tianshan Talent Training Program(2022TSYCCX0013)+3 种基金the Key Project of Natural Science Foundation of Xinjiang(2021D01D10)the Basic Research Foundation for Universities of Xinjiang(XJEDU2023P023)the Xinjiang Key Laboratory of Applied Mathematics(XJDX1401)the Intelligent Control and Optimization Research Platform in Xinjiang University.
文摘This paper is dedicated to fixed-time passivity and synchronization for multi-weighted spatiotemporal directed networks.First,to achieve fixed-time passivity,a type of decentralized power-law controller is developed,in which only one parameter needs to be adjusted in the power-law terms;this greatly decreases the inconvenience of parameter adjustment.Second,several fixed-time passivity criteria with LMI forms are derived by using a Gauss divergence theorem to deal with the spatial diffusion of nodes and by applying the Hölder’s inequality to dispose rigorously the power-law term greater than one in the designed control scheme;this improves the previous theoretical analysis.Additionally,the fixed-time synchronization of spatiotemporal directed networks with multi-weights is addressed as a direct result of fixed-time strict passivity.Finally,a numerical example is presented in order to show the validity of the theoretical analysis.
基金financially supported by the National Natural Science Foundation of China(Nos.51909023 and 51775077)the Natural Science Foundation of Liaoning Province(No.2021-MS-140)the Fundamental Research Funds for the Central Universities(No.3132025114)。
文摘Ultra-high molecular weight polyethylene(UHMWPE)is a key material for marine applications owing to its outstanding self-lubrication and corrosion resistance.However,its long-term performance is compromised by plastic deformation in seawater.In this study,we performed a comparative analysis of the UHMWPE dynamics under seawater and water conditions to investigate the plastic deformation of UHMWPE induced by seawater.The results show that the plastic deformation of UHMWPE is amplified in seawater relative to the water conditions.Under thin fluid conditions,frictional interfaces exhibit a higher interfacial friction force and interaction energy in seawater than in water.Compared to freely diffused water molecules,hydrated ions occupy larger interchain spaces within polyethylene.Furthermore,the diffusion of hydrated ions weakens the interchain interactions,promoting more severe polyethylene chain rearrangement and accelerating seawater-induced plastic deformation in UHMWPE during friction.Furthermore,the diffused seawater accelerated the disentangling of the polyethylene chains and enhanced the orderly orientation distribution of polyethylene.Compared to free water molecules,the water molecules of hydrated ions exhibit enhanced attraction to free-flowing water molecules,thereby accelerating seawater flow across submerged UHMWPE surfaces.This flow enhancement promotes surface polyethylene chain mobility in seawater.
基金supported by the Funds for Central-Guided Local Science and Technology Development(Grant No.202407AC110005)Key Technologies for the Construction of a Whole-Process Intelligent Service System for Neuroendocrine Neoplasm.Supported by 2023 Opening Research Fund of Yunnan Key Laboratory of Digital Communications(YNJTKFB-20230686,YNKLDC-KFKT-202304).
文摘In image analysis,high-precision semantic segmentation predominantly relies on supervised learning.Despite significant advancements driven by deep learning techniques,challenges such as class imbalance and dynamic performance evaluation persist.Traditional weighting methods,often based on pre-statistical class counting,tend to overemphasize certain classes while neglecting others,particularly rare sample categories.Approaches like focal loss and other rare-sample segmentation techniques introduce multiple hyperparameters that require manual tuning,leading to increased experimental costs due to their instability.This paper proposes a novel CAWASeg framework to address these limitations.Our approach leverages Grad-CAM technology to generate class activation maps,identifying key feature regions that the model focuses on during decision-making.We introduce a Comprehensive Segmentation Performance Score(CSPS)to dynamically evaluate model performance by converting these activation maps into pseudo mask and comparing them with Ground Truth.Additionally,we design two adaptive weights for each class:a Basic Weight(BW)and a Ratio Weight(RW),which the model adjusts during training based on real-time feedback.Extensive experiments on the COCO-Stuff,CityScapes,and ADE20k datasets demonstrate that our CAWASeg framework significantly improves segmentation performance for rare sample categories while enhancing overall segmentation accuracy.The proposed method offers a robust and efficient solution for addressing class imbalance in semantic segmentation tasks.
基金Under the auspices of the National Natural Science Foundation of China(No.42271224,41901193)Ministry of Edu cation Humanities and Social Sciences Research Planning Fund Project of China(No.24YJAZH190)+1 种基金Anhui Province Excellent Youth Research Project in Universities(No.2022AH030019)Anhui Social Sciences Innovation Development Research Project(No.2024CXQ503)。
文摘The accessibility of urban public transit directly influences residents’quality of life,travel behavior,and social equity.Its correlation with housing prices has garnered significant attention across disciplines such as geography,economics,and urban planning.Although much existing research focuses on the impact of individual transportation facilities on housing prices,there is a notable gap in comprehensive analyses that assess the influence of overall urban transit accessibility on housing market dynamics.This study selected the main urban area of Hefei,China,as a case to investigate the spatial distribution of housing prices and evaluate public transit accessibility in 2022.Employing techniques such as the optimized parameter geographical detector and local spatial regression models,the study aimed to elucidate the effects and underlying mechanisms of urban transit accessibility on housing prices.The findings revealed that:1)housing prices in Hefei exhibited a clustered spatial pattern,with high prices concentrated in the city center and lower prices in peripheral areas,forming three distinct high-price hotspots with a‘belt-like’distribution;2)public transit accessibility showed a‘coreperiphery’structure,with accessibility declining in a‘circumferential’pattern around the city center.Based on the‘housing price-accessibility’dimension,four categories were identified:high price-high accessibility(37.25%),high price-low accessibility(19.07%),low price-high accessibility(21.95%),and low price-low accessibility(21.73%);3)the impact of transit accessibility on housing prices was spatially heterogeneous,with bus travel showing the strongest explanatory power(0.692),followed by automobile,subway,and bicycle travel.The interaction of these transportation modes generated a synergistic effect on housing price differentiation,with most influencing factors contributing more than 25%.These findings offer valuable insights for optimizing the spatial distribution of public transit infrastructure and improving both urban housing quality and residents’living standards.
文摘This study investigated the physicochemical properties,enzyme activities,volatile flavor components,microbial communities,and sensory evaluation of high-temperature Daqu(HTD)during the maturation process,and a standard system was established for comprehensive quality evaluation of HTD.There were obvious changes in the physicochemical properties,enzyme activities,and volatile flavor components at different storage periods,which affected the sensory evaluation of HTD to a certain extent.The results of high-throughput sequencing revealed significant microbial diversity,and showed that the bacterial community changed significantly more than did the fungal community.During the storage process,the dominant bacterial genera were Kroppenstedtia and Thermoascus.The correlation between dominant microorganisms and quality indicators highlighted their role in HTD quality.Lactococcus,Candida,Pichia,Paecilomyces,and protease activity played a crucial role in the formation of isovaleraldehyde.Acidic protease activity had the greatest impact on the microbial community.Moisture promoted isobutyric acid generation.Furthermore,the comprehensive quality evaluation standard system was established by the entropy weight method combined with multi-factor fuzzy mathematics.Consequently,this study provides innovative insights for comprehensive quality evaluation of HTD during storage and establishes a groundwork for scientific and rational storage of HTD and quality control of sauce-flavor Baijiu.
基金supported by the Biological Breeding-National Science and Technology Major Project(2022ZD0401403)Shaanxi Provincial Key Research and Development Program(2024NC2-GJHX-15)Shaanxi Livestock and Poultry Breeding Double-chain Fusion Key Project(2022GD-TSLD-46-0401).
文摘Background Birth weight is a critical economic trait in livestock production.However,its genetic architecture remains poorly understood due to historical limitations in sample size and reliance on low-density SNP arrays.In this study,we utilized low-coverage whole-genome sequencing(lcWGS)to genotype 3,007 Hu sheep,bypassing the cost and resolution constraints of conventional genotyping arrays while achieving scalable genome-wide variant detection.Results LcWGS with high imputation accuracy(97.8%allelic concordance)enabled genome-wide association studies(GWAS)identifying two novel quantitative trait loci(QTLs)on chromosomes 6 and 9.The chromosome 9 QTL encompassed a regulatory region functionally linked to PLAG1 expression through expression quantitative trait locus(eQTL)mapping.Compared with wild-type homozygotes,heterozygous carriers of the lead SNP(chr9:g.35920172A>G)presented a 9.85%increase in birth weight(3.35 kg vs.3.68 kg;Δ=0.33 kg).Notably,the derived allele of this SNP exhibited low frequencies of<0.1 across most global sheep breeds except Dorper,highlighting its potential for selective breeding applications.Leveraging lcWGS data,haplotype-based fine-mapping prioritized three candidate causal variants.A secondary QTL on chromosome 6 colocalized with the FecB mutation,a well-established locus associated with increased litter size.Intriguingly,individuals carrying one FecB allele showed a 6.18%reduction(0.22 kg)in birth weight,which tentatively indicates potential pleiotropic influences on both growth and reproductive traits.Conclusion This study demonstrates the utility of lcWGS as a cost-effective,high-resolution tool for dissecting complex traits in livestock.Our findings not only advance the understanding of birth weight genetics in sheep but also offer a blueprint for accelerating genetic improvement programs in global livestock production through costeffective,genome-wide approaches.
基金mainly funded by the State Research Agency of Spain through the Competitive Project PID2021-127415OB-I00 on "Spike fertility in wheat" with some contribution from an AGROTECNIO Seed-funding on "Analysing the physiology of spike density to provide support to selection in breeding programs"RAS did part of the work in this project during a research stay at the Crop Physiology Lab of the University of Lleida co-funded by AUIP (Postgraduate Iberoamerican University Association) grants+1 种基金core funds Crop Physiology Lab of the Ud L. CSC held a Maria Zambrano’s fellowship from the University of Lleida funded by the Spanish Ministry of Universities and the European Social Fund and is a member of CONICET (the Scientific Research Council of Argentina)INTA (the National Institute of Agriculture Technology of Argentina)
文摘Grain yield variation has been associated to variation in grain number per unit area(GN).It has been shown in the last about 40 years that GN is linearly associated to the spike dry weight(SDW)at anthesis in wheat,fact that has been useful to understand mechanistically potential grain yield.Fruiting efficiency(FE,grains per gram of spike dry weight),the slope between GN and SDW relationship,has been proposed as a possible trait to improve wheat yield potential.The linear relationship between GN and SDW implies a constant increase in GN per unit increase in spike growth and,then a constant FE.However,there are empirical and theoretical elements suggesting that this relationship would not be linear.In this study,we hypothesised and showed that the linearity of the relationship between GN and SDW would be non-linear for extreme values of SDW,implying that the FE would be noticeably reduced at these extreme cases of dry matter allocation to the juvenile spikes.These results have implications for both,genetic and management improvements in grain yield.
基金Prince Sattam bin Abdulaziz University project number(PSAU/2023/R/1445)。
文摘Prediction of stability in SG(Smart Grid)is essential in maintaining consistency and reliability of power supply in grid infrastructure.Analyzing the fluctuations in power generation and consumption patterns of smart cities assists in effectively managing continuous power supply in the grid.It also possesses a better impact on averting overloading and permitting effective energy storage.Even though many traditional techniques have predicted the consumption rate for preserving stability,enhancement is required in prediction measures with minimized loss.To overcome the complications in existing studies,this paper intends to predict stability from the smart grid stability prediction dataset using machine learning algorithms.To accomplish this,pre-processing is performed initially to handle missing values since it develops biased models when missing values are mishandled and performs feature scaling to normalize independent data features.Then,the pre-processed data are taken for training and testing.Following that,the regression process is performed using Modified PSO(Particle Swarm Optimization)optimized XGBoost Technique with dynamic inertia weight update,which analyses variables like gamma(G),reaction time(tau1–tau4),and power balance(p1–p4)for providing effective future stability in SG.Since PSO attains optimal solution by adjusting position through dynamic inertial weights,it is integrated with XGBoost due to its scalability and faster computational speed characteristics.The hyperparameters of XGBoost are fine-tuned in the training process for achieving promising outcomes on prediction.Regression results are measured through evaluation metrics such as MSE(Mean Square Error)of 0.011312781,MAE(Mean Absolute Error)of 0.008596322,and RMSE(Root Mean Square Error)of 0.010636156 and MAPE(Mean Absolute Percentage Error)value of 0.0052 which determine the efficacy of the system.
基金Project(52175445)supported by the National Natural Science Foundation of ChinaProject(2022JJ30743)supported by the Natural Science Foundation of Hunan Province,China+1 种基金Project(2023GK2024)supported by the Key Research and Development Program of Hunan Province,ChinaProject(2023ZZTS0391)supported by the Fundamental Research Funds for the Central Universities of China。
文摘Red-green-blue(RGB)beam combiners are widely used in scenarios such as augmented reality/virtual reality(AR/VR),laser projection,biochemical detection,and other fields.Optical waveguide combiners have attracted extensive attention due to their advantages of small size,high multiplexing efficiency,convenient mass production,and low cost.An RGB beam combiner based on directional couplers is designed,with a core-cladding relative refractive index difference of 0.75%.The RGB beam combiner is optimized from the perspective of parameter optimization.Using the beam propagation method(BPM),the relationship between the performance of the RGB beam combiner and individual parameters is studied,achieving preliminary optimization of the device’s performance.The key parameters of the RGB beam combiner are optimized using the entropy weight-technique for order preference by similarity to an ideal solution TOPSIS method,establishing the optimal parameter scheme and further improving the device’s performance indicators.The results show that after optimization,the multiplexing efficiencies for red,green,and blue lights,as well as the average multiplexing efficiency,reached 99.17%,99.76%,96.63%and 98.52%,respectively.The size of the RGB beam combiner is 4.768 mm×0.062 mm.
文摘Objective To investigate the association between birth weight and dementia risk and the mediating roles of chronic diseases,and to assess potential biological pathways underlying the birth weight-associated dementia risk based on large-scale proteomics.Methods We used data from 279743 participants aged 40 to 69 years enrolled in the UK Biobank.Birth weight was categorized into low birth weight(≤2500 g),normal birth weight(2500-3999 g),and macrosomia(≥4000 g).Multivariable Cox proportional hazards regression models were used to assess the associations between birth weight categories and all-cause dementia and its subtypes(Alzheimer's disease and vascular dementia).Proteomics analyses were conducted to identify proteins and the potential pathways involved.Results Low birth weight was associated with higher risks for all-cause dementia and its subtypes.The hazard ratios were 1.18(95%CI,1.08-1.30)for all-cause dementia,1.14(95%CI,1.00-1.31)for Alzheimer's disease,and 1.22(95%CI,1.01-1.48)for vascular dementia.A non-linear relationship was observed between birth weight and dementia risk(P for nonlinearity<0.001).Certain cardiometabolic diseases in middle-aged adults,such as diabetes,stroke,hypertension,and dyslipidemia,played a significant mediating role in the relationship between low birth weight and dementia risk,with the mediation proportion being 6.3%to 15.8%.Proteomic analyses identified 21 proteins linked to both low birth weight and all-cause dementia risk,which were significantly enriched in the pathways for viral protein interaction with cytokines and cytokine receptors,adipocytokine signaling,and cytokine-cytokine receptor interaction.Conclusion Low birth weight is positively associated with dementia risk.Cardiometabolic diseases in middle-aged adults may mediate the relationship between low birth weight and dementia risk.A number of proteins and the associated pathways underscore the relationship between low birth weight and dementia risk.
文摘Inhomogeneous Calderon-Zygmund operator T maps each atom into an approximate molecule of weighted local Hardy space if and only if some approximate cancellation condition holds for T.An equivalent norm for weighted Lebesgue space which has vanishing moments up to order s plays an important role,where s∈N.
基金Supported by the National Natural Science Foundation of China(12301101)the Guangdong Basic and Applied Basic Research Foundation(2022A1515110019 and 2020A1515110585)。
文摘In this paper,the Paley-Wiener theorem is extended to the analytic function spaces with general weights.We first generalize the theorem to weighted Hardy spaces Hp(0<p<∞)on tube domains by constructing a sequence of L^(1)functions converging to the given function and verifying their representation in the form of Fourier transform to establish the desired result of the given function.Applying this main result,we further generalize the Paley-Wiener theorem for band-limited functions to the analytic function spaces L^(p)(0<p<∞)with general weights.
文摘Since the discovery of carbon dots(CDs)in 2004,the unique photoluminescence phenomenon of CDs has attracted widespread attention.However,the molecular weight of CDs has not been adequately quantified at present,due to CDs are atomically imprecise and their molecular weight distribution is broad.In this paper,a series of Pluronic-modified CDs were prepared and the structure of the CDs was briefly analyzed.Subsequently,a molecular weight measurement method based on colligative properties was developed,and the correction coefficient in the algorithm was briefly analyzed.The calculated molecular weight was applied to the determination of surface adsorption capacity.This work provided a method for averaging the molecular weight of atomically imprecise particulate materials,which is expected to provide new opportunities in related fields.
基金Supported by Natural Science Foundation of Guangdong Province in China(2018KTSCX161)。
文摘The boundness and compactness of products of multiplication,composition and differentiation on weighted Bergman spaces in the unit ball are studied.We define the differentiation operator on the space of holomorphic functions in the unit ball by radial derivative.Then we extend the Sharma's results.
文摘Background: Birth weight has been identified as one of the most significant predictors of a child’s physical growth, development, and survival in later life. A quest to provide an answer on the impact of maternal anthropometry on neonatal birth weight necessitated this study. Materials and methods: It is a cross-sectional descriptive hospital based study that involved 130 participants selected using a systematic sampling method, utilizing a semi-structured, pre-tested interviewer administered questionnaire. Data were collected using a standard procedure and were summarized using proportions, and the Chi square test was used to explore the association between categorical variables. Predictors of birth weight were determined using logistic regression. The level of statistical significance was set at p Results: Participants had a mean age of 28.6 ± 5.1 years, mean weight of 72.2 ± 11.2 kg and mean height of 1.63 ± 0.07m while the mean fetal birth weight was 3.10 ± 0.56 kg. There was a significant association between maternal delivery body mass index and neonatal birth weight (p Conclusion: The prevalence of low birth weight and macrosomia in this study population was high. The focus should be geared towards balanced nutrition support for all mothers at booking so as to mitigate the risks associated with these extremes of birth weight.
基金Supported by Sichuan Science and Technology Program (No.2022ZYD0010)。
文摘The aim of the present paper is to study 2-complex symmetric bounded weighted composition operators on the Fock space of C^(N) with the conjugations J and J_(t,A,b) defined by ■ respectively,where k(z_(1),...,z_N)=(■,...,■),t∈C,b∈C^(N) and A is a linear operator on C^(N).An example of 2-complex symmetric bounded weighted composition operator with the conjugation J_(t,A,b) is given.
