Current shipping,tourism,and resource development requirements call for more accurate predictions of the Arctic sea-ice concentration(SIC).However,due to the complex physical processes involved,predicting the spatiote...Current shipping,tourism,and resource development requirements call for more accurate predictions of the Arctic sea-ice concentration(SIC).However,due to the complex physical processes involved,predicting the spatiotemporal distribution of Arctic SIC is more challenging than predicting its total extent.In this study,spatiotemporal prediction models for monthly Arctic SIC at 1-to 3-month leads are developed based on U-Net-an effective convolutional deep-learning approach.Based on explicit Arctic sea-ice-atmosphere interactions,11 variables associated with Arctic sea-ice variations are selected as predictors,including observed Arctic SIC,atmospheric,oceanic,and heat flux variables at 1-to 3-month leads.The prediction skills for the monthly Arctic SIC of the test set(from January 2018 to December 2022)are evaluated by examining the mean absolute error(MAE)and binary accuracy(BA).Results showed that the U-Net model had lower MAE and higher BA for Arctic SIC compared to two dynamic climate prediction systems(CFSv2 and NorCPM).By analyzing the relative importance of each predictor,the prediction accuracy relies more on the SIC at the 1-month lead,but on the surface net solar radiation flux at 2-to 3-month leads.However,dynamic models show limited prediction skills for surface net solar radiation flux and other physical processes,especially in autumn.Therefore,the U-Net model can be used to capture the connections among these key physical processes associated with Arctic sea ice and thus offers a significant advantage in predicting Arctic SIC.展开更多
In this paper, condensation of water vapor from a mixture of COR2R/HR2RO is studied numerically. To simplify the study and focus on the physical model, a simple vertical plate was chosen. Two condensation models are d...In this paper, condensation of water vapor from a mixture of COR2R/HR2RO is studied numerically. To simplify the study and focus on the physical model, a simple vertical plate was chosen. Two condensation models are developed and numerical approach is considered to implement these models. The main objective in the cur-rent paper was to study the capability of numerical modeling in prediction of complex process. Results showed that developed condensation models in combination with numerical approach can predict the trends in condensation behavior of binary mixture very well. Results from this study can be developed further to be used in design of condensers which are suitable for oxy-fuel power plants.展开更多
构建了一种基于R^2LC^2(可靠、冗余、损耗、特性、成本)的中高压多电平统一电能质量调节器(Unified Power Quality Conditioner,UPQC)拓扑评估体系。选定多种应用于UPQC的多电平拓扑结构类型,建立多电平UPQC拓扑结构的损耗模型、故障模...构建了一种基于R^2LC^2(可靠、冗余、损耗、特性、成本)的中高压多电平统一电能质量调节器(Unified Power Quality Conditioner,UPQC)拓扑评估体系。选定多种应用于UPQC的多电平拓扑结构类型,建立多电平UPQC拓扑结构的损耗模型、故障模型、仿真模型、冗余模型和器件模型,分别用以分析并形成损耗与拓扑关系、拓扑可靠性、暂稳态特性、系统稳定性、结构与成本关系的评价指标。结合五种评价指标的相互影响关系,建立层次分析模型,定量得到五种评价指标的权重系数,构造成对比较矩阵,计算排序权向量,全面分析多种多电平UPQC拓扑结构的整体性能,实现多电平UPQC拓扑结构的综合准确评估,提供多电平UPQC变流器拓扑结构类型的选择依据。选取级联H桥、模块化多电平变流器和换桥臂多电平变流器为实际应用范例,验证了所提评估体系的可行性。展开更多
A series of(R)-2-phenyl-4,5-dihydrothiazole-4-carboxamide derivatives containing a sulfur ether moiety were synthesized and characterized on the basis of NMR and elemental analysis(EA). The crystal structure of(R)-N-(...A series of(R)-2-phenyl-4,5-dihydrothiazole-4-carboxamide derivatives containing a sulfur ether moiety were synthesized and characterized on the basis of NMR and elemental analysis(EA). The crystal structure of(R)-N-(2-methyl-1-(methylthio)propan-2-yl)-2-(4-nitrophenyl)-4,5-dihydrothiazole-4-carboxamide(13 d) was determined to show R configuration. The bioasssy results indicated that most title compounds displayed good and broad spectrum antifungal activities against several phytopathogenic fungi. The structure activity relationships were discussed. Based on the antifungal activity of title compounds against Phytophthora capsici, a CoMSIA calculation was performed to establish a 3 D-QSAR model, which revealed that electrostatic and hydrophobic fields were the two most significant factors for antifungal activity. According to the established 3D-QSAR model, structure optimization was carried out to find(R)-N-((R)-1-(methylthio)propan-2-yl)-2-(p-tolyl)-4,5-dihydrothiazole-4-carboxamide(15 h)with excellent activity against Phytophthora capsici, thus emerging as a new lead compound for novel antiphytopathogenic fungus agent development.展开更多
为深入研究光学遥感图像中的船舶检测问题,提升检测精度和降低模型复杂度,设计基于改进旋转区域卷积和神经网络(Rotational Region Convolutional Neural Networks),R^(2)CNN的两阶段旋转框检测模型。在模型的第一阶段使用水平框作为候...为深入研究光学遥感图像中的船舶检测问题,提升检测精度和降低模型复杂度,设计基于改进旋转区域卷积和神经网络(Rotational Region Convolutional Neural Networks),R^(2)CNN的两阶段旋转框检测模型。在模型的第一阶段使用水平框作为候选区域;在模型第二阶段引入水平框预测分支,并且设计一种间接预测角度的回归模型;在测试阶段进行旋转框非极大值抑制时,设计基于掩码矩阵的旋转框IoU(Intersection over Union)算法。试验结果显示:改进R^(2)CNN模型在HRSC2016(High Resolution Ship Collection 2016)数据集上取得81.0%的平均精确度,相比其他模型均有不同程度的提升,说明改进R^(2)CNN在简化模型的同时能有效提升使用旋转框检测船舶的性能。展开更多
In this paper,we study the approximate solutions for some of nonlinear Biomathematics models via the e-epidemic SI1I2R model characterizing the spread of viruses in a computer network and SIR childhood disease model.T...In this paper,we study the approximate solutions for some of nonlinear Biomathematics models via the e-epidemic SI1I2R model characterizing the spread of viruses in a computer network and SIR childhood disease model.The reduced differential transforms method(RDTM)is one of the interesting methods for finding the approximate solutions for nonlinear problems.We apply the RDTM to discuss the analytic approximate solutions to the SI1I2R model for the spread of virus HCV-subtype and SIR childhood disease model.We discuss the numerical results at some special values of parameters in the approximate solutions.We use the computer software package such as Mathematical to find more iteration when calculating the approximate solutions.Graphical results and discussed quantitatively are presented to illustrate behavior of the obtained approximate solutions.展开更多
In many animal-related studies, a high-performance animal behavior recognition system can help researchers reduce or get rid of the limitation of human assessments and make the experiments easier to reproduce. Recentl...In many animal-related studies, a high-performance animal behavior recognition system can help researchers reduce or get rid of the limitation of human assessments and make the experiments easier to reproduce. Recently, although deep learning models are holding state-of-the-art performances in human action recognition tasks, these models are not well-studied in applying to animal behavior recognition tasks. One reason is the lack of extensive datasets which are required to train these deep models for good performances. In this research, we investigated two current state-of-the-art deep learning models in human action recognition tasks, the I3D model and the R(2 + 1)D model, in solving a mouse behavior recognition task. We compared their performances with other models from previous researches and the results showed that the deep learning models that pre-trained using human action datasets then fine-tuned using the mouse behavior dataset can outperform other models from previous researches. It also shows promises of applying these deep learning models to other animal behavior recognition tasks without any significant modification in the models’ architecture, all we need to do is collecting proper datasets for the tasks and fine-tuning the pre-trained models using the collected data.展开更多
Financial support to agriculture is the main driving force to increase farmers＇ income. This paper applied the evaluation DEA （Data-embrasing Analysis） method to evaluate the effectiveness of financial support to a...Financial support to agriculture is the main driving force to increase farmers＇ income. This paper applied the evaluation DEA （Data-embrasing Analysis） method to evaluate the effectiveness of financial support to agriculture from 1990 to 2005. It is found that the trend of the financial support to agricultural effectiveness in China presented a downward trend in recent years. The results showed that the overall trend of the financial support to agriculture in China wasn＇t high, and some corresponding proposals were put forward to optimized.展开更多
提出了基于可变形部件模型(deformable part model,DPM)的高分二号(GaoFen-2,GF2)遥感影像船只检测方法,并与区域卷积网络(regional convolutional neural network,R-CNN)进行比较。先将遥感影像分段以获得船只的粗略感兴趣区域(regions...提出了基于可变形部件模型(deformable part model,DPM)的高分二号(GaoFen-2,GF2)遥感影像船只检测方法,并与区域卷积网络(regional convolutional neural network,R-CNN)进行比较。先将遥感影像分段以获得船只的粗略感兴趣区域(regions of interest,ROI),然后在ROI内计算方向梯度直方图(histogram of oriented gradients,HOG)和卷积特征,再分别由DPM和R-CNN采用HOG和卷积特征。为测试R-CNN的最佳性能,将具有5个卷积层(ZF网)和具有13个卷积层(VGG网)的网络应用于船只检测。使用8张GF2遥感影像的3 523艘船只的实验结果表明,DPM和R-CNN都能以高召回率和正确率检测水中的船只,但对于聚集船只而言,DPM的效果优于R-CNN。基于HOG+DPM,ZF网和VGG网的方法平均精度分别为95.031%,93.282%和93.683%。展开更多
This article presents a ground theory to explain why some individuals choose to be unhappy rather than happy,supported by empirical data collected from a sample of 750 professionals in Greece’s public and private sec...This article presents a ground theory to explain why some individuals choose to be unhappy rather than happy,supported by empirical data collected from a sample of 750 professionals in Greece’s public and private sectors.We begin by reviewing the existing literature on happiness and well-being,highlighting the debate between hedonic and eudaimonic perspectives.We then introduce our research questions and rationale,and describe our methods,sample,and psychometric tools used to measure happiness and other variables of interest.Our results indicate that various factors,including cultural influences,past experiences,and personal values,contribute to individuals’pursuit of unhappiness.We conclude with a thorough discussion of our results and their implications for future research and interventions aimed at promoting well-being.展开更多
γ-Aminobutyric acid（GABA）,plays a key role in all stages of life,also is considered the main inhibitory neurotransmitter.GABA activates two kind of membrane receptors known as GABAA and GABAB,the first one is respo...γ-Aminobutyric acid（GABA）,plays a key role in all stages of life,also is considered the main inhibitory neurotransmitter.GABA activates two kind of membrane receptors known as GABAA and GABAB,the first one is responsible to render tonic inhibition by pentameric receptors containing α4-6,β3,δ,or ρ1-3 subunits,they are located at perisynaptic and/or in extrasynaptic regions.The biophysical properties of GABAA tonic inhibition have been related with cellular protection against excitotoxic injury and cell death in presence of excessive excitation.On this basis,GABAA tonic inhibition has been proposed as a potential target for therapeutic intervention of Huntington＇s disease.Huntington＇s disease is a neurodegenerative disorder caused by a genetic mutation of the huntingtin protein.For experimental studies of Huntington＇s disease mouse models have been developed,such as R6/1,R6/2,Hdh Q92,Hdh Q150,as well as YAC128.In all of them,some key experimental reports are focused on neostriatum.The neostriatum is considered as the most important connection between cerebral cortex and basal ganglia structures,its cytology display two pathways called direct and indirect constituted by medium sized spiny neurons expressing dopamine D1 and D2 receptors respectively,they display strong expression of many types of GABAA receptors,including tonic subunits.The studies about of GABAA tonic subunits and Huntington＇s disease into the neostriatum are rising in recent years,suggesting interesting changes in their expression and localization which can be used as a strategy to delay the cellular damage caused by the imbalance between excitation and inhibition,a hallmark of Huntington＇s disease.展开更多
基金supported by the National Key Research and Development Program of China[grant number 2022YFE0106800]an Innovation Group Project of the Southern Marine Science and Engineering Guangdong Laboratory(Zhuhai)[grant number 311024001]+3 种基金a project supported by the Southern Marine Science and Engineering Guangdong Laboratory(Zhuhai)[grant number SML2023SP209]a Research Council of Norway funded project(MAPARC)[grant number 328943]a Nansen Center´s basic institutional funding[grant number 342624]the high-performance computing support from the School of Atmospheric Science at Sun Yat-sen University。
文摘Current shipping,tourism,and resource development requirements call for more accurate predictions of the Arctic sea-ice concentration(SIC).However,due to the complex physical processes involved,predicting the spatiotemporal distribution of Arctic SIC is more challenging than predicting its total extent.In this study,spatiotemporal prediction models for monthly Arctic SIC at 1-to 3-month leads are developed based on U-Net-an effective convolutional deep-learning approach.Based on explicit Arctic sea-ice-atmosphere interactions,11 variables associated with Arctic sea-ice variations are selected as predictors,including observed Arctic SIC,atmospheric,oceanic,and heat flux variables at 1-to 3-month leads.The prediction skills for the monthly Arctic SIC of the test set(from January 2018 to December 2022)are evaluated by examining the mean absolute error(MAE)and binary accuracy(BA).Results showed that the U-Net model had lower MAE and higher BA for Arctic SIC compared to two dynamic climate prediction systems(CFSv2 and NorCPM).By analyzing the relative importance of each predictor,the prediction accuracy relies more on the SIC at the 1-month lead,but on the surface net solar radiation flux at 2-to 3-month leads.However,dynamic models show limited prediction skills for surface net solar radiation flux and other physical processes,especially in autumn.Therefore,the U-Net model can be used to capture the connections among these key physical processes associated with Arctic sea ice and thus offers a significant advantage in predicting Arctic SIC.
文摘In this paper, condensation of water vapor from a mixture of COR2R/HR2RO is studied numerically. To simplify the study and focus on the physical model, a simple vertical plate was chosen. Two condensation models are developed and numerical approach is considered to implement these models. The main objective in the cur-rent paper was to study the capability of numerical modeling in prediction of complex process. Results showed that developed condensation models in combination with numerical approach can predict the trends in condensation behavior of binary mixture very well. Results from this study can be developed further to be used in design of condensers which are suitable for oxy-fuel power plants.
文摘构建了一种基于R^2LC^2(可靠、冗余、损耗、特性、成本)的中高压多电平统一电能质量调节器(Unified Power Quality Conditioner,UPQC)拓扑评估体系。选定多种应用于UPQC的多电平拓扑结构类型,建立多电平UPQC拓扑结构的损耗模型、故障模型、仿真模型、冗余模型和器件模型,分别用以分析并形成损耗与拓扑关系、拓扑可靠性、暂稳态特性、系统稳定性、结构与成本关系的评价指标。结合五种评价指标的相互影响关系,建立层次分析模型,定量得到五种评价指标的权重系数,构造成对比较矩阵,计算排序权向量,全面分析多种多电平UPQC拓扑结构的整体性能,实现多电平UPQC拓扑结构的综合准确评估,提供多电平UPQC变流器拓扑结构类型的选择依据。选取级联H桥、模块化多电平变流器和换桥臂多电平变流器为实际应用范例,验证了所提评估体系的可行性。
基金financially supported by the Scientific Project of Tianjin Municipal Education Commission(No. 2018KJ008)Tianjin Natural Science Foundation(No. 16JCYBJC29400)
文摘A series of(R)-2-phenyl-4,5-dihydrothiazole-4-carboxamide derivatives containing a sulfur ether moiety were synthesized and characterized on the basis of NMR and elemental analysis(EA). The crystal structure of(R)-N-(2-methyl-1-(methylthio)propan-2-yl)-2-(4-nitrophenyl)-4,5-dihydrothiazole-4-carboxamide(13 d) was determined to show R configuration. The bioasssy results indicated that most title compounds displayed good and broad spectrum antifungal activities against several phytopathogenic fungi. The structure activity relationships were discussed. Based on the antifungal activity of title compounds against Phytophthora capsici, a CoMSIA calculation was performed to establish a 3 D-QSAR model, which revealed that electrostatic and hydrophobic fields were the two most significant factors for antifungal activity. According to the established 3D-QSAR model, structure optimization was carried out to find(R)-N-((R)-1-(methylthio)propan-2-yl)-2-(p-tolyl)-4,5-dihydrothiazole-4-carboxamide(15 h)with excellent activity against Phytophthora capsici, thus emerging as a new lead compound for novel antiphytopathogenic fungus agent development.
文摘In this paper,we study the approximate solutions for some of nonlinear Biomathematics models via the e-epidemic SI1I2R model characterizing the spread of viruses in a computer network and SIR childhood disease model.The reduced differential transforms method(RDTM)is one of the interesting methods for finding the approximate solutions for nonlinear problems.We apply the RDTM to discuss the analytic approximate solutions to the SI1I2R model for the spread of virus HCV-subtype and SIR childhood disease model.We discuss the numerical results at some special values of parameters in the approximate solutions.We use the computer software package such as Mathematical to find more iteration when calculating the approximate solutions.Graphical results and discussed quantitatively are presented to illustrate behavior of the obtained approximate solutions.
文摘In many animal-related studies, a high-performance animal behavior recognition system can help researchers reduce or get rid of the limitation of human assessments and make the experiments easier to reproduce. Recently, although deep learning models are holding state-of-the-art performances in human action recognition tasks, these models are not well-studied in applying to animal behavior recognition tasks. One reason is the lack of extensive datasets which are required to train these deep models for good performances. In this research, we investigated two current state-of-the-art deep learning models in human action recognition tasks, the I3D model and the R(2 + 1)D model, in solving a mouse behavior recognition task. We compared their performances with other models from previous researches and the results showed that the deep learning models that pre-trained using human action datasets then fine-tuned using the mouse behavior dataset can outperform other models from previous researches. It also shows promises of applying these deep learning models to other animal behavior recognition tasks without any significant modification in the models’ architecture, all we need to do is collecting proper datasets for the tasks and fine-tuning the pre-trained models using the collected data.
文摘Financial support to agriculture is the main driving force to increase farmers＇ income. This paper applied the evaluation DEA （Data-embrasing Analysis） method to evaluate the effectiveness of financial support to agriculture from 1990 to 2005. It is found that the trend of the financial support to agricultural effectiveness in China presented a downward trend in recent years. The results showed that the overall trend of the financial support to agriculture in China wasn＇t high, and some corresponding proposals were put forward to optimized.
文摘提出了基于可变形部件模型(deformable part model,DPM)的高分二号(GaoFen-2,GF2)遥感影像船只检测方法,并与区域卷积网络(regional convolutional neural network,R-CNN)进行比较。先将遥感影像分段以获得船只的粗略感兴趣区域(regions of interest,ROI),然后在ROI内计算方向梯度直方图(histogram of oriented gradients,HOG)和卷积特征,再分别由DPM和R-CNN采用HOG和卷积特征。为测试R-CNN的最佳性能,将具有5个卷积层(ZF网)和具有13个卷积层(VGG网)的网络应用于船只检测。使用8张GF2遥感影像的3 523艘船只的实验结果表明,DPM和R-CNN都能以高召回率和正确率检测水中的船只,但对于聚集船只而言,DPM的效果优于R-CNN。基于HOG+DPM,ZF网和VGG网的方法平均精度分别为95.031%,93.282%和93.683%。
文摘This article presents a ground theory to explain why some individuals choose to be unhappy rather than happy,supported by empirical data collected from a sample of 750 professionals in Greece’s public and private sectors.We begin by reviewing the existing literature on happiness and well-being,highlighting the debate between hedonic and eudaimonic perspectives.We then introduce our research questions and rationale,and describe our methods,sample,and psychometric tools used to measure happiness and other variables of interest.Our results indicate that various factors,including cultural influences,past experiences,and personal values,contribute to individuals’pursuit of unhappiness.We conclude with a thorough discussion of our results and their implications for future research and interventions aimed at promoting well-being.
基金the programs for the postdoctoral fellowships-Chilean CONICYT-FONDECYT#3140218,Mexican CONACYT#164978 and DID-UACh S-2015-81Sistema Nacional de Investigadores#58512 to Abraham Rosas-Arellano+2 种基金supported by USACH PhD fellowshipsupported with a PhD fellowship from CONACYT(#299627)FONDECYT grants 1151206 and 1110571 to Maite A.Castro
文摘γ-Aminobutyric acid（GABA）,plays a key role in all stages of life,also is considered the main inhibitory neurotransmitter.GABA activates two kind of membrane receptors known as GABAA and GABAB,the first one is responsible to render tonic inhibition by pentameric receptors containing α4-6,β3,δ,or ρ1-3 subunits,they are located at perisynaptic and/or in extrasynaptic regions.The biophysical properties of GABAA tonic inhibition have been related with cellular protection against excitotoxic injury and cell death in presence of excessive excitation.On this basis,GABAA tonic inhibition has been proposed as a potential target for therapeutic intervention of Huntington＇s disease.Huntington＇s disease is a neurodegenerative disorder caused by a genetic mutation of the huntingtin protein.For experimental studies of Huntington＇s disease mouse models have been developed,such as R6/1,R6/2,Hdh Q92,Hdh Q150,as well as YAC128.In all of them,some key experimental reports are focused on neostriatum.The neostriatum is considered as the most important connection between cerebral cortex and basal ganglia structures,its cytology display two pathways called direct and indirect constituted by medium sized spiny neurons expressing dopamine D1 and D2 receptors respectively,they display strong expression of many types of GABAA receptors,including tonic subunits.The studies about of GABAA tonic subunits and Huntington＇s disease into the neostriatum are rising in recent years,suggesting interesting changes in their expression and localization which can be used as a strategy to delay the cellular damage caused by the imbalance between excitation and inhibition,a hallmark of Huntington＇s disease.
