Microsoft公司发布了新版Windows Live Local（local、live．com）。这是基于航空影像的在线地点搜索，访问者可以找到地图，收件地址等信息。新增的功能包括实时交通流和事故报告，使用者保存和分享定位经验的新的社交网络工具，因Wind...Microsoft公司发布了新版Windows Live Local（local、live．com）。这是基于航空影像的在线地点搜索，访问者可以找到地图，收件地址等信息。新增的功能包括实时交通流和事故报告，使用者保存和分享定位经验的新的社交网络工具，因Windows Live Local扩展到Outlook和Windows Live Messenger中，从而提高了生产力。展开更多
The Vehicle Routing Problem with Time Windows(VRPTW)presents a significant challenge in combinatorial optimization,especially under real-world uncertainties such as variable travel times,service durations,and dynamic ...The Vehicle Routing Problem with Time Windows(VRPTW)presents a significant challenge in combinatorial optimization,especially under real-world uncertainties such as variable travel times,service durations,and dynamic customer demands.These uncertainties make traditional deterministic models inadequate,often leading to suboptimal or infeasible solutions.To address these challenges,this work proposes an adaptive hybrid metaheuristic that integrates Genetic Algorithms(GA)with Local Search(LS),while incorporating stochastic uncertainty modeling through probabilistic travel times.The proposed algorithm dynamically adjusts parameters—such as mutation rate and local search probability—based on real-time search performance.This adaptivity enhances the algorithm’s ability to balance exploration and exploitation during the optimization process.Travel time uncertainties are modeled using Gaussian noise,and solution robustness is evaluated through scenario-based simulations.We test our method on a set of benchmark problems from Solomon’s instance suite,comparing its performance under deterministic and stochastic conditions.Results show that the proposed hybrid approach achieves up to a 9%reduction in expected total travel time and a 40% reduction in time window violations compared to baseline methods,including classical GA and non-adaptive hybrids.Additionally,the algorithm demonstrates strong robustness,with lower solution variance across uncertainty scenarios,and converges faster than competing approaches.These findings highlight the method’s suitability for practical logistics applications such as last-mile delivery and real-time transportation planning,where uncertainty and service-level constraints are critical.The flexibility and effectiveness of the proposed framework make it a promising candidate for deployment in dynamic,uncertainty-aware supply chain environments.展开更多
High efficiency and low-cost catalyst-driven electrocatalytic CO_(2)reduction to CO production are of great significance for energy storage and development.The severe competitive hydrogen evolution reaction occurs at ...High efficiency and low-cost catalyst-driven electrocatalytic CO_(2)reduction to CO production are of great significance for energy storage and development.The severe competitive hydrogen evolution reaction occurs at large negative potential window limits the achievement of the target product from CO_(2)at high efficiency.Here,we successfully prepared Cu_(x)/CdcO_(3)composite catalyst rich in interfaces,in which achieved high CO Faraday eficiency exceeded 90%in a wide potential window of 700 mV and highest value up to 97.9%at-0.90V vs.RHE.The excellent performance can be ascribed to the positive contribution of Cu_(x)/CdcO_(3),which maintains a suitable high local pH value during electrochemical reduction,thus inhibiting the competitive hydrogen evolution reaction.Moreover,the compact structure between Cu and CdCO_(3)ensures fast electron transfer both inside catalysts and interface,thus speeding up the reaction kinetics of CO_(2)to CO conversion.Theoretically calculations further prove that the combination of Cu and CdcO_(3)provides the well-defined electronic structure for intermediates adsorption,significantly reducing the reaction barrier for the formation of co.This work provides new insights into the design of eficient electrochemical CO_(2)reduction catalysts for inhibiting hydrogen evolution by adjusting the local pH effect.展开更多
Omics data provides an essential means for molecular biology and systems biology to capture the systematic properties of inner activities of cells. And one of the strongest challenge problems biological researchers ha...Omics data provides an essential means for molecular biology and systems biology to capture the systematic properties of inner activities of cells. And one of the strongest challenge problems biological researchers have faced is to find the methods for discovering biomarkers for tracking the process of disease such as cancer. So some feature selection methods have been widely used to cope with discovering biomarkers problem. However omics data usually contains a large number of features, but a small number of samples and some omics data have a large range distribution, which make feature selection methods remains difficult to deal with omics data. In order to overcome the problems, wepresent a computing method called localized statistic of abundance distribution based on Gaussian window(LSADBGW) to test the significance of the feature. The experiments on three datasets including gene and protein datasets showed the accuracy and efficiency of LSADBGW for feature selection.展开更多
This paper proposes an efficient object localization method based on a vanishing line. The proposed method can be much improved in time efficiency since it requires scanning only vanishing line area. It requires the t...This paper proposes an efficient object localization method based on a vanishing line. The proposed method can be much improved in time efficiency since it requires scanning only vanishing line area. It requires the time complexity of O(n) while the existing sliding window method requires the time complexity O(n<sup>2</sup>) for detecting all objects in the entire image. In addition, the range of detection area can be also remarkably reduced when compared with the sliding window method. As a result, the total range and times for searching in the proposed method can be significantly reduced by considering together the distance and position of the object. The experiment on the proposed method is performed with the virtual road data set known as SYNTHIA, and the competitive results are obtained.展开更多
Mechanomyography (MMG) acquires the oscillatory waves of contracting muscles. Electromyography (EMG) is a tool for monitoring muscle overall electrical activity. During muscle contractions, both techniques can investi...Mechanomyography (MMG) acquires the oscillatory waves of contracting muscles. Electromyography (EMG) is a tool for monitoring muscle overall electrical activity. During muscle contractions, both techniques can investigate the changes that occur in the muscle properties. EMG and MMG parameters have been used for detecting muscle fatigue with diverse test protocols, sensors and filtering. Depending on the analysis window length (WLA), monitoring physiological events could be compromised due to imprecision in the determination of parameters. Therefore, this study investigated the influence of WLA variation on different MMG and EMG parameters during submaximal isometric contractions monitoring MMG and EMG parameters. Ten male volunteers performed isometric contractions of elbow joint. Triaxial accelerometer-based MMG sensor and EMG electrodes were positioned on the biceps brachii muscle belly. Torque was monitored with a load cell. Volunteers remained seated with hip and elbow joint at angles of 110° and 90°, respectively. The protocol consisted in maintaining torque at 70% of maximum voluntary contraction as long as they could. Parameter data of EMG and the modulus of MMG were determined for four segments of the signal. Statistical analysis consisted of analyses of variance and Fisher’s least square differences post-hoc test. Also, Pearson’s correlation was calculated to determine whether parameters that monitor similar physiological events would have strong correlation. The modulus of MMG mean power frequency (MPF) and the number of crossings in the baseline could detect changes between fresh and fatigued muscle with 1.0 s WLA. MPF and the skewness of the spectrum (μ3), parameters related to the compression of the spectrum, behaved differently when monitored with a triaxial MMG sensor. The EMG results show that for the 1.0 s and 2.0 s WLAs have normalized RMS difference with fatigued muscle and that there was strong correlation between parameters of different domains.展开更多
文摘Microsoft公司发布了新版Windows Live Local（local、live．com）。这是基于航空影像的在线地点搜索，访问者可以找到地图，收件地址等信息。新增的功能包括实时交通流和事故报告，使用者保存和分享定位经验的新的社交网络工具，因Windows Live Local扩展到Outlook和Windows Live Messenger中，从而提高了生产力。
文摘The Vehicle Routing Problem with Time Windows(VRPTW)presents a significant challenge in combinatorial optimization,especially under real-world uncertainties such as variable travel times,service durations,and dynamic customer demands.These uncertainties make traditional deterministic models inadequate,often leading to suboptimal or infeasible solutions.To address these challenges,this work proposes an adaptive hybrid metaheuristic that integrates Genetic Algorithms(GA)with Local Search(LS),while incorporating stochastic uncertainty modeling through probabilistic travel times.The proposed algorithm dynamically adjusts parameters—such as mutation rate and local search probability—based on real-time search performance.This adaptivity enhances the algorithm’s ability to balance exploration and exploitation during the optimization process.Travel time uncertainties are modeled using Gaussian noise,and solution robustness is evaluated through scenario-based simulations.We test our method on a set of benchmark problems from Solomon’s instance suite,comparing its performance under deterministic and stochastic conditions.Results show that the proposed hybrid approach achieves up to a 9%reduction in expected total travel time and a 40% reduction in time window violations compared to baseline methods,including classical GA and non-adaptive hybrids.Additionally,the algorithm demonstrates strong robustness,with lower solution variance across uncertainty scenarios,and converges faster than competing approaches.These findings highlight the method’s suitability for practical logistics applications such as last-mile delivery and real-time transportation planning,where uncertainty and service-level constraints are critical.The flexibility and effectiveness of the proposed framework make it a promising candidate for deployment in dynamic,uncertainty-aware supply chain environments.
基金supported by the National Natural Science Foundation of China(Nos.22225808,22075111)Sino-German Cooperation Group Project(No.GZ1579)Jiangsu Province Innovation Support Program International Science and Technology Cooperation Project(No.BZ2022045).
文摘High efficiency and low-cost catalyst-driven electrocatalytic CO_(2)reduction to CO production are of great significance for energy storage and development.The severe competitive hydrogen evolution reaction occurs at large negative potential window limits the achievement of the target product from CO_(2)at high efficiency.Here,we successfully prepared Cu_(x)/CdcO_(3)composite catalyst rich in interfaces,in which achieved high CO Faraday eficiency exceeded 90%in a wide potential window of 700 mV and highest value up to 97.9%at-0.90V vs.RHE.The excellent performance can be ascribed to the positive contribution of Cu_(x)/CdcO_(3),which maintains a suitable high local pH value during electrochemical reduction,thus inhibiting the competitive hydrogen evolution reaction.Moreover,the compact structure between Cu and CdCO_(3)ensures fast electron transfer both inside catalysts and interface,thus speeding up the reaction kinetics of CO_(2)to CO conversion.Theoretically calculations further prove that the combination of Cu and CdcO_(3)provides the well-defined electronic structure for intermediates adsorption,significantly reducing the reaction barrier for the formation of co.This work provides new insights into the design of eficient electrochemical CO_(2)reduction catalysts for inhibiting hydrogen evolution by adjusting the local pH effect.
文摘Omics data provides an essential means for molecular biology and systems biology to capture the systematic properties of inner activities of cells. And one of the strongest challenge problems biological researchers have faced is to find the methods for discovering biomarkers for tracking the process of disease such as cancer. So some feature selection methods have been widely used to cope with discovering biomarkers problem. However omics data usually contains a large number of features, but a small number of samples and some omics data have a large range distribution, which make feature selection methods remains difficult to deal with omics data. In order to overcome the problems, wepresent a computing method called localized statistic of abundance distribution based on Gaussian window(LSADBGW) to test the significance of the feature. The experiments on three datasets including gene and protein datasets showed the accuracy and efficiency of LSADBGW for feature selection.
文摘This paper proposes an efficient object localization method based on a vanishing line. The proposed method can be much improved in time efficiency since it requires scanning only vanishing line area. It requires the time complexity of O(n) while the existing sliding window method requires the time complexity O(n<sup>2</sup>) for detecting all objects in the entire image. In addition, the range of detection area can be also remarkably reduced when compared with the sliding window method. As a result, the total range and times for searching in the proposed method can be significantly reduced by considering together the distance and position of the object. The experiment on the proposed method is performed with the virtual road data set known as SYNTHIA, and the competitive results are obtained.
基金CNPq and CAPES for the financial support and grants received.
文摘Mechanomyography (MMG) acquires the oscillatory waves of contracting muscles. Electromyography (EMG) is a tool for monitoring muscle overall electrical activity. During muscle contractions, both techniques can investigate the changes that occur in the muscle properties. EMG and MMG parameters have been used for detecting muscle fatigue with diverse test protocols, sensors and filtering. Depending on the analysis window length (WLA), monitoring physiological events could be compromised due to imprecision in the determination of parameters. Therefore, this study investigated the influence of WLA variation on different MMG and EMG parameters during submaximal isometric contractions monitoring MMG and EMG parameters. Ten male volunteers performed isometric contractions of elbow joint. Triaxial accelerometer-based MMG sensor and EMG electrodes were positioned on the biceps brachii muscle belly. Torque was monitored with a load cell. Volunteers remained seated with hip and elbow joint at angles of 110° and 90°, respectively. The protocol consisted in maintaining torque at 70% of maximum voluntary contraction as long as they could. Parameter data of EMG and the modulus of MMG were determined for four segments of the signal. Statistical analysis consisted of analyses of variance and Fisher’s least square differences post-hoc test. Also, Pearson’s correlation was calculated to determine whether parameters that monitor similar physiological events would have strong correlation. The modulus of MMG mean power frequency (MPF) and the number of crossings in the baseline could detect changes between fresh and fatigued muscle with 1.0 s WLA. MPF and the skewness of the spectrum (μ3), parameters related to the compression of the spectrum, behaved differently when monitored with a triaxial MMG sensor. The EMG results show that for the 1.0 s and 2.0 s WLAs have normalized RMS difference with fatigued muscle and that there was strong correlation between parameters of different domains.
