The high dimensions of hyperspectral imagery have caused burden for further processing. A new Fast Independent Component Analysis (FastICA) approach to dimensionality reduction for hyperspectral imagery is presented. ...The high dimensions of hyperspectral imagery have caused burden for further processing. A new Fast Independent Component Analysis (FastICA) approach to dimensionality reduction for hyperspectral imagery is presented. The virtual dimensionality is introduced to determine the number of dimensions needed to be preserved. Since there is no prioritization among independent components generated by the FastICA,the mixing matrix of FastICA is initialized by endmembers,which were extracted by using unsupervised maximum distance method. Minimum Noise Fraction (MNF) is used for preprocessing of original data,which can reduce the computational complexity of FastICA significantly. Finally,FastICA is performed on the selected principal components acquired by MNF to generate the expected independent components in accordance with the order of endmembers. Experimental results demonstrate that the proposed method outperforms second-order statistics-based transforms such as principle components analysis.展开更多
During the Asian summer monsoon(ASM)season,the process of stratosphere-troposphere exchange significantly affects the concentration and spatial distribution of chemical constituents in the upper troposphere and lower ...During the Asian summer monsoon(ASM)season,the process of stratosphere-troposphere exchange significantly affects the concentration and spatial distribution of chemical constituents in the upper troposphere and lower stratosphere(UTLS).However,the effect of the intensity of the Asian summer monsoon anticyclone(ASMA)on the horizontal distribution of chemical species within and around the ASMA,especially on the daily time scale,remains unclear.Here,the authors use the MERRA-2 reanalysis dataset and Aura Microwave Limb Sounder observations to study the impact of ASMA intensity on chemical distributions at 100 hPa during the ASM season.The intraseasonal variation of ASMA is classified into a strong period(SP)and weak period(WP),which refer to the periods when the intensity of ASMA remains strong and weak,respectively.The relatively low ozone(O_(3))region is found to be larger at 100 hPa during SPs,while its mixing ratio is lower than during WPs in summer.In June,analysis shows that the O_(3) horizontal distribution is mainly related to the intensity of AMSA,especially during SPs in June,while deep convections also impact the O_(3) horizontal distribution in July and August.These results indicate that the intraseasonal variation of the ASMA intensity coupled to deep convection can significantly affect the chemical distribution in the UTLS region during the ASM season.展开更多
Partial differential equations(PDEs)are important tools for scientific research and are widely used in various fields.However,it is usually very difficult to obtain accurate analytical solutions of PDEs,and numerical ...Partial differential equations(PDEs)are important tools for scientific research and are widely used in various fields.However,it is usually very difficult to obtain accurate analytical solutions of PDEs,and numerical methods to solve PDEs are often computationally intensive and very time-consuming.In recent years,Physics Informed Neural Networks(PINNs)have been successfully applied to find numerical solutions of PDEs and have shown great potential.All the while,solitary waves have been of great interest to researchers in the field of nonlinear science.In this paper,we perform numerical simulations of solitary wave solutions of several PDEs using improved PINNs.The improved PINNs not only incorporate constraints on the control equations to ensure the interpretability of the prediction results,which is important for physical field simulations,in addition,an adaptive activation function is introduced.By introducing hyperparameters in the activation function to change the slope of the activation function to avoid the disappearance of the gradient,computing time is saved thereby speeding up training.In this paper,the m Kd V equation,the improved Boussinesq equation,the Caudrey–Dodd–Gibbon–Sawada–Kotera equation and the p-g BKP equation are selected for study,and the errors of the simulation results are analyzed to assess the accuracy of the predicted solitary wave solution.The experimental results show that the improved PINNs are significantly better than the traditional PINNs with shorter training time but more accurate prediction results.The improved PINNs improve the training speed by more than 1.5 times compared with the traditional PINNs,while maintaining the prediction error less than 10~(-2)in this order of magnitude.展开更多
Obesity is increasingly prevalent in the post-industrial era,with increased mortality rates.The gut microbiota has a central role in immunological,nutritional and metabolism mediated functions,and due to its multiplex...Obesity is increasingly prevalent in the post-industrial era,with increased mortality rates.The gut microbiota has a central role in immunological,nutritional and metabolism mediated functions,and due to its multiplexity,it is considered an independent organ.Modern high-throughput sequencing techniques have allowed phylogenetic exploration and quantitative analyses of gut microbiome and improved our current understanding of the gut microbiota in health and disease.Its role in obesity and its changes following bariatric surgery have been highlighted in several studies.According to current literature,obesity is linked to a particular microbiota profile that grants the host an augmented potential for calorie release,while limited diversity of gut microbiome has also been observed.Moreover,bariatric surgery procedures represent effective interventions for sustained weight loss and restore a healthier microbiota,contributing to the observed fat mass reduction and lean mass increase.However,newer evidence has shown that gut microbiota is only partially recovered following bariatric surgery.Moreover,several targets including FGF15/19(a gutderived peptide),could be responsible for the favorable metabolic changes of bariatric surgery.More randomized controlled trials and larger prospective studies that include well-defined cohorts are required to better identify associations between gut microbiota,obesity,and bariatric surgery.展开更多
Software defined networking （SDN） achieves network routing management with logically centralized con- trol software that decouples the network data plane from the control plane. This new design paradigm greatly eman...Software defined networking （SDN） achieves network routing management with logically centralized con- trol software that decouples the network data plane from the control plane. This new design paradigm greatly emancipates network innovation. This paper introduces the background of SDN technology with its design principles, explains its differentiation, and summarizes the research efforts on SDN network architecture, components and applications. Based on the observation of current SDN development, this paper ana- lyzes the potential driving forces of SDN deployment and its future trend.展开更多
基金Supported by the National Natural Science Foundation of China (No. 60572135)
文摘The high dimensions of hyperspectral imagery have caused burden for further processing. A new Fast Independent Component Analysis (FastICA) approach to dimensionality reduction for hyperspectral imagery is presented. The virtual dimensionality is introduced to determine the number of dimensions needed to be preserved. Since there is no prioritization among independent components generated by the FastICA,the mixing matrix of FastICA is initialized by endmembers,which were extracted by using unsupervised maximum distance method. Minimum Noise Fraction (MNF) is used for preprocessing of original data,which can reduce the computational complexity of FastICA significantly. Finally,FastICA is performed on the selected principal components acquired by MNF to generate the expected independent components in accordance with the order of endmembers. Experimental results demonstrate that the proposed method outperforms second-order statistics-based transforms such as principle components analysis.
基金sponsored by Strategic Priority Research Program of the Chinese Academy of Science[grant No.XDA17010106]the National Key Research and Development Program of China[grant Nos.2018YFC1505703 and 2018YFC1506704].
文摘During the Asian summer monsoon(ASM)season,the process of stratosphere-troposphere exchange significantly affects the concentration and spatial distribution of chemical constituents in the upper troposphere and lower stratosphere(UTLS).However,the effect of the intensity of the Asian summer monsoon anticyclone(ASMA)on the horizontal distribution of chemical species within and around the ASMA,especially on the daily time scale,remains unclear.Here,the authors use the MERRA-2 reanalysis dataset and Aura Microwave Limb Sounder observations to study the impact of ASMA intensity on chemical distributions at 100 hPa during the ASM season.The intraseasonal variation of ASMA is classified into a strong period(SP)and weak period(WP),which refer to the periods when the intensity of ASMA remains strong and weak,respectively.The relatively low ozone(O_(3))region is found to be larger at 100 hPa during SPs,while its mixing ratio is lower than during WPs in summer.In June,analysis shows that the O_(3) horizontal distribution is mainly related to the intensity of AMSA,especially during SPs in June,while deep convections also impact the O_(3) horizontal distribution in July and August.These results indicate that the intraseasonal variation of the ASMA intensity coupled to deep convection can significantly affect the chemical distribution in the UTLS region during the ASM season.
文摘Partial differential equations(PDEs)are important tools for scientific research and are widely used in various fields.However,it is usually very difficult to obtain accurate analytical solutions of PDEs,and numerical methods to solve PDEs are often computationally intensive and very time-consuming.In recent years,Physics Informed Neural Networks(PINNs)have been successfully applied to find numerical solutions of PDEs and have shown great potential.All the while,solitary waves have been of great interest to researchers in the field of nonlinear science.In this paper,we perform numerical simulations of solitary wave solutions of several PDEs using improved PINNs.The improved PINNs not only incorporate constraints on the control equations to ensure the interpretability of the prediction results,which is important for physical field simulations,in addition,an adaptive activation function is introduced.By introducing hyperparameters in the activation function to change the slope of the activation function to avoid the disappearance of the gradient,computing time is saved thereby speeding up training.In this paper,the m Kd V equation,the improved Boussinesq equation,the Caudrey–Dodd–Gibbon–Sawada–Kotera equation and the p-g BKP equation are selected for study,and the errors of the simulation results are analyzed to assess the accuracy of the predicted solitary wave solution.The experimental results show that the improved PINNs are significantly better than the traditional PINNs with shorter training time but more accurate prediction results.The improved PINNs improve the training speed by more than 1.5 times compared with the traditional PINNs,while maintaining the prediction error less than 10~(-2)in this order of magnitude.
文摘Obesity is increasingly prevalent in the post-industrial era,with increased mortality rates.The gut microbiota has a central role in immunological,nutritional and metabolism mediated functions,and due to its multiplexity,it is considered an independent organ.Modern high-throughput sequencing techniques have allowed phylogenetic exploration and quantitative analyses of gut microbiome and improved our current understanding of the gut microbiota in health and disease.Its role in obesity and its changes following bariatric surgery have been highlighted in several studies.According to current literature,obesity is linked to a particular microbiota profile that grants the host an augmented potential for calorie release,while limited diversity of gut microbiome has also been observed.Moreover,bariatric surgery procedures represent effective interventions for sustained weight loss and restore a healthier microbiota,contributing to the observed fat mass reduction and lean mass increase.However,newer evidence has shown that gut microbiota is only partially recovered following bariatric surgery.Moreover,several targets including FGF15/19(a gutderived peptide),could be responsible for the favorable metabolic changes of bariatric surgery.More randomized controlled trials and larger prospective studies that include well-defined cohorts are required to better identify associations between gut microbiota,obesity,and bariatric surgery.
文摘Software defined networking （SDN） achieves network routing management with logically centralized con- trol software that decouples the network data plane from the control plane. This new design paradigm greatly emancipates network innovation. This paper introduces the background of SDN technology with its design principles, explains its differentiation, and summarizes the research efforts on SDN network architecture, components and applications. Based on the observation of current SDN development, this paper ana- lyzes the potential driving forces of SDN deployment and its future trend.
