CRISPR/Cas9-mediated genome engineering technologies are now widely applied in various organisms,including mouse and human cells（Cong et al.,2013;Mali et al.,2013;Yang et al.,2013;Hsu et al.,2014）.The most widely us...CRISPR/Cas9-mediated genome engineering technologies are now widely applied in various organisms,including mouse and human cells（Cong et al.,2013;Mali et al.,2013;Yang et al.,2013;Hsu et al.,2014）.The most widely used customized CRISPR/Cas9（Sp Cas9）is derived from Streptococcus pyogenes（Cong et al.,2013）.展开更多
The retreating snowfields and glaciers of Glacier National Park, Montana, USA, present alpine plants with changes in habitat and hydrology. The adjacent and relic periglacial patterned ground consists of solifluction ...The retreating snowfields and glaciers of Glacier National Park, Montana, USA, present alpine plants with changes in habitat and hydrology. The adjacent and relic periglacial patterned ground consists of solifluction terraces of green, vegetation-rich stripes alternating with sparsely vegetated brown stripes. We established georeferenced transects on striped periglacial patterned ground for long-term monitoring and data collection on species distribution and plant functional traits at Siyeh Pass and at Piegan Pass at Glacier National Park. We documented species distribution and calculated the relative percent cover(RPC) of qualitative functional traits and used 16 S rRNA from soil samples to characterize microbial distribution on green and brown stripes. Plant species distribution varied significantly and there were key differences in microbial distribution between the green and brown stripes. The rare arctic-alpine plants Draba macounii, Papaver pygmaeum, and Sagina nivalis were restricted to brown stripes, where the RPC of xeromorphic taprooted species was significantly higher at the leading edge of the Siyeh Pass snowfield. Brown stripes had a higher percentage of the thermophilic bacteria Thermacetogenium and Thermoflavimicrobium. Green stripes were co-dominated by the adventitiously-rooted dwarf shrubs Salix arctica and the possibly N-fixing Dryas octopetala. Green stripes were inhabited by Krummholz and seedlings of Abies lasiocarpa and Pinus albicaulus. Prosthecobacter, a hydrophilic bacterial genus, was more abundant on the green stripes, which had 6,524 bacterial sequences in comparison to the 1,183 sequences from the brown stripes. While further research can determine which functional traits are critical for these plants, knowledge of the current distribution of plant species and their functional traits can be used in predictive models of the responses of alpine plants to disappearing snowfields and glaciers. This research is important in conservation of rare arctic-alpine species on periglacial patterned ground.展开更多
Multi-Valued Neuron (MVN) was proposed for pattern classification. It operates with complex-valued inputs, outputs, and weights, and its learning algorithm is based on error-correcting rule. The activation function of...Multi-Valued Neuron (MVN) was proposed for pattern classification. It operates with complex-valued inputs, outputs, and weights, and its learning algorithm is based on error-correcting rule. The activation function of MVN is not differentiable. Therefore, we can not apply backpropagation when constructing multilayer structures. In this paper, we propose a new neuron model, MVN-sig, to simulate the mechanism of MVN with differentiable activation function. We expect MVN-sig to achieve higher performance than MVN. We run several classification benchmark datasets to compare the performance of MVN-sig with that of MVN. The experimental results show a good potential to develop a multilayer networks based on MVN-sig.展开更多
The main symptom of patients with Alzheimer’s disease is cognitive dysfunction. Alzheimer’s disease is mainly diagnosed based on changes in brain structure. Functional connectivity reflects the synchrony of function...The main symptom of patients with Alzheimer’s disease is cognitive dysfunction. Alzheimer’s disease is mainly diagnosed based on changes in brain structure. Functional connectivity reflects the synchrony of functional activities between non-adjacent brain regions, and changes in functional connectivity appear earlier than those in brain structure. In this study, we detected resting-state functional connectivity changes in patients with Alzheimer’s disease to provide reference evidence for disease prediction. Functional magnetic resonance imaging data from patients with Alzheimer’s disease were used to show whether particular white and gray matter areas had certain functional connectivity patterns and if these patterns changed with disease severity. In nine white and corresponding gray matter regions, correlations of normal cognition, early mild cognitive impairment, and late mild cognitive impairment with blood oxygen level-dependent signal time series were detected. Average correlation coefficient analysis indicated functional connectivity patterns between white and gray matter in the resting state of patients with Alzheimer’s disease. Functional connectivity pattern variation correlated with disease severity, with some regions having relatively strong or weak correlations. We found that the correlation coefficients of five regions were 0.3–0.5 in patients with normal cognition and 0–0.2 in those developing Alzheimer’s disease. Moreover, in the other four regions, the range increased to 0.45–0.7 with increasing cognitive impairment. In some white and gray matter areas, there were specific connectivity patterns. Changes in regional white and gray matter connectivity patterns may be used to predict Alzheimer’s disease;however, detailed information on specific connectivity patterns is needed. All study data were obtained from the Alzheimer’s Disease Neuroimaging Initiative Library of the Image and Data Archive Database.展开更多
Vegetation biomass is an important component of terrestrial ecosystem carbon stocks. Grasslands are one of the most widespread biomes worldwideplaying an important role in global carbon cycling. Thereforestudying spat...Vegetation biomass is an important component of terrestrial ecosystem carbon stocks. Grasslands are one of the most widespread biomes worldwideplaying an important role in global carbon cycling. Thereforestudying spatial patterns of biomass and their correlations to environment in grasslands is fundamental to quantifying terrestrial carbon budgets. The Eurasian steppean important part of global grasslandsis the largest and relatively well preserved grassland in the world. In this studywe analyzed the spatial pattern of aboveground biomass（AGB）and correlations of AGB to its environment in the Eurasian steppe by meta-analysis. AGB data used in this study were derived from the harvesting method and were obtained from three data sources（literatureglobal NPP database at the Oak Ridge National Laboratory Distributed Active Archive Center（ORNL）some data provided by other researchers）. Our results demonstrated that：（1） as for the Eurasian steppe overallthe spatial variation in AGB exhibited significant horizontal and vertical zonality. In detailAGB showed an inverted parabola curve with the latitude and with the elevationwhile a parabola curve with the longitude. In additionthe spatial pattern of AGB had marked horizontal zonality in the Black Sea-Kazakhstan steppe subregion and the Mongolian Plateau steppe subregionwhile horizontal and vertical zonality in the Tibetan Plateau alpine steppe subregion.（2） Of the examined environmental variablesthe spatial variation of AGB was related to mean annual precipitation（MAP）mean annual temperature（MAT）mean annual solar radiation（MAR）soil Gravel contentsoil p H and soil organic content（SOC） at the depth of 0–30 cm. NeverthelessMAP dominated spatial patterns of AGB in the Eurasian steppe and its three subregions.（3） A Gaussian function was found between AGB and MAP in the Eurasian steppe overallwhich was primarily determined by unique patterns of grasslands and environment in the Tibetan Plateau. AGB was significantly positively related to MAP in the Black Sea-Kazakhstan steppe subregion（elevation 〈 3000 m）the Mongolian Plateau steppe subregion（elevation 〈 3000 m） and the surface（elevation ≥ 4800 m） of the Tibetan Plateau. Neverthelessthe spatial variation in AGB exhibited a Gaussian function curve with the increasing MAP in the east and southeast margins（elevation 〈 4800 m） of the Tibetan Plateau. This study provided more knowledge of spatial patterns of AGB and their environmental controls in grasslands than previous studies only conducted in local regions like the Inner Mongolian temperate grasslandthe Tibetan Plateau alpine grasslandetc.展开更多
The maximum of k numerical functions defined on , , by , ??is used here in Statistical classification. Previously, it has been used in Statistical Discrimination [1] and in Clustering [2]. We present first some theore...The maximum of k numerical functions defined on , , by , ??is used here in Statistical classification. Previously, it has been used in Statistical Discrimination [1] and in Clustering [2]. We present first some theoretical results on this function, and then its application in classification using a computer program we have developed. This approach leads to clear decisions, even in cases where the extension to several classes of Fisher’s linear discriminant function fails to be effective.展开更多
For exploring the aftershock occurrence process of the 2008 Wenchuan strong earthquake, the spatio-temporal point pattern analysis method is employed to study the sequences of aflershocks with magnitude M≥4.0, M≥4.5...For exploring the aftershock occurrence process of the 2008 Wenchuan strong earthquake, the spatio-temporal point pattern analysis method is employed to study the sequences of aflershocks with magnitude M≥4.0, M≥4.5, and M≥5.0. It is found that these data exhibit the spatio-temporal clustering on a certain distance scale and on a certain time scale. In particular, the space-time interaction obviously strengthens when the distance is less than 60 km and the time is less than 260 h for the first two aftershock sequences; however, it becomes strong when the distance scale is less than 80 km and the time scale is less than 150 h for the last aftershock sequence. The completely spatial randomness analysis on the data regardless of time component shows that the spatial clustering of the aftershocks gradually strengthens on the condition that the distance is less than 60 km. The results are valuable for exploring the occurrence rules of the Wenchuan strong earthquake and for predicting the aftershocks.展开更多
8-Sphingolipid desaturase is the key enzyme that catalyses desaturation at the C8 position of the long-chain base of sphingolipids in higher plants. There have been no previous studies on the genes encoding AS-sphingo...8-Sphingolipid desaturase is the key enzyme that catalyses desaturation at the C8 position of the long-chain base of sphingolipids in higher plants. There have been no previous studies on the genes encoding AS-sphingolipid desaturases in Brassica rapa. In this study, four genes encoding AS-sphingolipid desaturases from B. rapa were isolated and characterised. Phylogenetic analyses indicated that these genes could be divided into two groups： BrD8A, BrD8C and BrD8D in group I, and BrD8B in group II. The two groups of genes diverged before the separation of Arabidopsis and Brassica. Though the four genes shared a high sequence similarity, and their coding desaturases all located in endoplasmic reticulum, they exhibited distinct expression patterns. Heterologous expression in Saccharomyces cerevisiae revealed that BrD8A/B/C/D were functionally diverse AS-sphingolipid desaturases that catalyse different ratios of the two products 8（Z）- and 8（E）-C18-phytosphingenine. The aluminium tolerance of transgenic yeasts expressing BrD8A/B/C/D was enhanced compared with that of control cells. Expression of BrD8A in Arabidopsis changed the ratio of 8（Z）：8（E）-C 18-phytosphingenine in transgenic plants. The information reported here provides new insights into the biochemical functional diversity and evolutionary relationship of AS-sphingolipid desaturase in plants and lays a foundation for further investigation of the mechanism of 8（Z）- and 8（E）-C18- phytosphingenine biosynthesis.展开更多
China＇s economy has undergone rapid transition and industrial restructuring. The term ＂urban industry＂ describes a particular type of industry within Chinese cities experiencing restructuring. Given the high percen...China＇s economy has undergone rapid transition and industrial restructuring. The term ＂urban industry＂ describes a particular type of industry within Chinese cities experiencing restructuring. Given the high percentage of industrial firms that have either closed or relo- cated from city centres to the urban fringe and beyond, emergent global cities such as Shanghai, are implementing strategies for local economic and urban development, which involve urban industrial upgrading numerous firms in the city centre and urban fringe. This study aims to analyze the location patterns of seven urban industrial sectors within the Shanghai urban region using 2008 micro-geography data. To avoid Modifiable Areal Unit Problem （MAUP） issue, four distance-based measures including nearest neighbourhood analysis, Kernel density estimation, K-function and co-location quotient have been exten- sively applied to analyze and compare the concentration and co-location between the seven sectors. The results reveal disparate patterns varying with distance and interesting co-location as well. The results are as follows： the city centre and the urban fringe have the highest intensity of urban industrial firms, but the zones with 20-30 km from the city centre is a watershed for most categories; the degree of concentration varies with distance, weaker at shorter distance, increasing up to the maximum distance of 30 km and then decreasing until 50 km; for all urban industries, there are three types of patterns, mixture of clustered, random and dispersed distribution at a varied range of distances. Consequently, this paper argues that the location pattern of urban industry reflects the stage-specific industrial restructuring and spatial transformation, conditioned by sustainability objectives.展开更多
In this paper, an incremental learning model called Resource Allocating Network with Long-Term Memory (RAN-LTM) is extended such that the learning is conducted with some autonomy for the following functions: 1) data c...In this paper, an incremental learning model called Resource Allocating Network with Long-Term Memory (RAN-LTM) is extended such that the learning is conducted with some autonomy for the following functions: 1) data collection for initial learning, 2) data normalization, 3) addition of radial basis functions (RBFs), and 4) determination of RBF cen-ters and widths. The proposed learning algorithm called Autonomous Learning algorithm for Resource Allocating Network (AL-RAN) is divided into the two learning phases: initial learning phase and incremental learning phase. And the former is further divided into the autonomous data collection and the initial network learning. In the initial learning phase, training data are first collected until the class separability is converged or has a significant dif-ference between normalized and unnormalized data. Then, an initial structure of AL-RAN is autonomously determined by selecting a moderate number of RBF centers from the collected data and by defining as large RBF widths as possible within a proper range. After the initial learning, the incremental learning of AL-RAN is conducted in a sequential way whenever a new training data is given. In the experiments, we evaluate AL-RAN using five benchmark data sets. From the experimental results, we confirm that the above autonomous functions work well and the efficiency in terms of network structure and learning time is improved without sacrificing the recognition accuracy as compared with the previous version of AL-RAN.展开更多
The multi-voxel pattern analysis technique is applied to fMRI data for classification of high-level brain functions using pattern information distributed over multiple voxels. In this paper, we propose a classifier en...The multi-voxel pattern analysis technique is applied to fMRI data for classification of high-level brain functions using pattern information distributed over multiple voxels. In this paper, we propose a classifier ensemble for multiclass classification in fMRI analysis, exploiting the fact that specific neighboring voxels can contain spatial pattern information. The proposed method converts the multiclass classification to a pairwise classifier ensemble, and each pairwise classifier consists of multiple sub-clas- sifiers using an adaptive feature set for each class-pair. Simulated and real fMRI data were used to verify the proposed method. Intra- and inter-subject analyses were performed to compare the proposed method with several well-known classitiers, including single and ensemble classifiers. The comparison results showed that the proposed method can be generally applied to multiclass classification in both simulations and real fMRI analyses.展开更多
基金supported by the grants from the Natural Science Foundation of China (No.81201181 to F.G.81473295 and 81670882 to Z.M.S and 81700885 to X.L.G.)+5 种基金Zhejiang Provincial & Ministry of Health research fund for medical sciences (WKJ2013-2-023 to F.G.WKJ-ZJ-1828 to J.Z.Z.and 2016KYA145 to X.L.G.)Science Technology Project of Zhejiang Province (2014C33260 to Z.M.S.and 2017C37176 to F.G.)Eye Hospital at Wenzhou Medical University (YNZD201602 to F.G.)Wenzhou City (Y20160008 to J.Z.Z.)Research Fund for Lin He's Academician Workstation of New Medicine and Clinical Translation (17331209 to C.B.L.)
文摘CRISPR/Cas9-mediated genome engineering technologies are now widely applied in various organisms,including mouse and human cells（Cong et al.,2013;Mali et al.,2013;Yang et al.,2013;Hsu et al.,2014）.The most widely used customized CRISPR/Cas9（Sp Cas9）is derived from Streptococcus pyogenes（Cong et al.,2013）.
文摘The retreating snowfields and glaciers of Glacier National Park, Montana, USA, present alpine plants with changes in habitat and hydrology. The adjacent and relic periglacial patterned ground consists of solifluction terraces of green, vegetation-rich stripes alternating with sparsely vegetated brown stripes. We established georeferenced transects on striped periglacial patterned ground for long-term monitoring and data collection on species distribution and plant functional traits at Siyeh Pass and at Piegan Pass at Glacier National Park. We documented species distribution and calculated the relative percent cover(RPC) of qualitative functional traits and used 16 S rRNA from soil samples to characterize microbial distribution on green and brown stripes. Plant species distribution varied significantly and there were key differences in microbial distribution between the green and brown stripes. The rare arctic-alpine plants Draba macounii, Papaver pygmaeum, and Sagina nivalis were restricted to brown stripes, where the RPC of xeromorphic taprooted species was significantly higher at the leading edge of the Siyeh Pass snowfield. Brown stripes had a higher percentage of the thermophilic bacteria Thermacetogenium and Thermoflavimicrobium. Green stripes were co-dominated by the adventitiously-rooted dwarf shrubs Salix arctica and the possibly N-fixing Dryas octopetala. Green stripes were inhabited by Krummholz and seedlings of Abies lasiocarpa and Pinus albicaulus. Prosthecobacter, a hydrophilic bacterial genus, was more abundant on the green stripes, which had 6,524 bacterial sequences in comparison to the 1,183 sequences from the brown stripes. While further research can determine which functional traits are critical for these plants, knowledge of the current distribution of plant species and their functional traits can be used in predictive models of the responses of alpine plants to disappearing snowfields and glaciers. This research is important in conservation of rare arctic-alpine species on periglacial patterned ground.
文摘Multi-Valued Neuron (MVN) was proposed for pattern classification. It operates with complex-valued inputs, outputs, and weights, and its learning algorithm is based on error-correcting rule. The activation function of MVN is not differentiable. Therefore, we can not apply backpropagation when constructing multilayer structures. In this paper, we propose a new neuron model, MVN-sig, to simulate the mechanism of MVN with differentiable activation function. We expect MVN-sig to achieve higher performance than MVN. We run several classification benchmark datasets to compare the performance of MVN-sig with that of MVN. The experimental results show a good potential to develop a multilayer networks based on MVN-sig.
基金supported by the National Natural Science Foundation of China,No.61401308,61572063(both to XHW)the Natural Science Foundation of Beijing of China,No.L172055(to XHW)+3 种基金the Beijing Municipal Science&Technology Commission Research Fund of China,No.Z171100000417004(to XHW)the China Postdoctoral Fund,No.2018M631755(to XHW)the Special Fund for Improving Comprehensive Strength of Hebei University in the Midwest of China,No.801260201011(to XHW)the High-Level Talent Funding Project—Selective Post-doctoral Research Project Fund of Hebei Province of China,No.B2018003002(to XHW)
文摘The main symptom of patients with Alzheimer’s disease is cognitive dysfunction. Alzheimer’s disease is mainly diagnosed based on changes in brain structure. Functional connectivity reflects the synchrony of functional activities between non-adjacent brain regions, and changes in functional connectivity appear earlier than those in brain structure. In this study, we detected resting-state functional connectivity changes in patients with Alzheimer’s disease to provide reference evidence for disease prediction. Functional magnetic resonance imaging data from patients with Alzheimer’s disease were used to show whether particular white and gray matter areas had certain functional connectivity patterns and if these patterns changed with disease severity. In nine white and corresponding gray matter regions, correlations of normal cognition, early mild cognitive impairment, and late mild cognitive impairment with blood oxygen level-dependent signal time series were detected. Average correlation coefficient analysis indicated functional connectivity patterns between white and gray matter in the resting state of patients with Alzheimer’s disease. Functional connectivity pattern variation correlated with disease severity, with some regions having relatively strong or weak correlations. We found that the correlation coefficients of five regions were 0.3–0.5 in patients with normal cognition and 0–0.2 in those developing Alzheimer’s disease. Moreover, in the other four regions, the range increased to 0.45–0.7 with increasing cognitive impairment. In some white and gray matter areas, there were specific connectivity patterns. Changes in regional white and gray matter connectivity patterns may be used to predict Alzheimer’s disease;however, detailed information on specific connectivity patterns is needed. All study data were obtained from the Alzheimer’s Disease Neuroimaging Initiative Library of the Image and Data Archive Database.
基金The Chinese Academy of Sciences Strategic Priority Research Program,No.XDA05050602The Key Program of National Natural Science Foundation of China,No.31290221
文摘Vegetation biomass is an important component of terrestrial ecosystem carbon stocks. Grasslands are one of the most widespread biomes worldwideplaying an important role in global carbon cycling. Thereforestudying spatial patterns of biomass and their correlations to environment in grasslands is fundamental to quantifying terrestrial carbon budgets. The Eurasian steppean important part of global grasslandsis the largest and relatively well preserved grassland in the world. In this studywe analyzed the spatial pattern of aboveground biomass（AGB）and correlations of AGB to its environment in the Eurasian steppe by meta-analysis. AGB data used in this study were derived from the harvesting method and were obtained from three data sources（literatureglobal NPP database at the Oak Ridge National Laboratory Distributed Active Archive Center（ORNL）some data provided by other researchers）. Our results demonstrated that：（1） as for the Eurasian steppe overallthe spatial variation in AGB exhibited significant horizontal and vertical zonality. In detailAGB showed an inverted parabola curve with the latitude and with the elevationwhile a parabola curve with the longitude. In additionthe spatial pattern of AGB had marked horizontal zonality in the Black Sea-Kazakhstan steppe subregion and the Mongolian Plateau steppe subregionwhile horizontal and vertical zonality in the Tibetan Plateau alpine steppe subregion.（2） Of the examined environmental variablesthe spatial variation of AGB was related to mean annual precipitation（MAP）mean annual temperature（MAT）mean annual solar radiation（MAR）soil Gravel contentsoil p H and soil organic content（SOC） at the depth of 0–30 cm. NeverthelessMAP dominated spatial patterns of AGB in the Eurasian steppe and its three subregions.（3） A Gaussian function was found between AGB and MAP in the Eurasian steppe overallwhich was primarily determined by unique patterns of grasslands and environment in the Tibetan Plateau. AGB was significantly positively related to MAP in the Black Sea-Kazakhstan steppe subregion（elevation 〈 3000 m）the Mongolian Plateau steppe subregion（elevation 〈 3000 m） and the surface（elevation ≥ 4800 m） of the Tibetan Plateau. Neverthelessthe spatial variation in AGB exhibited a Gaussian function curve with the increasing MAP in the east and southeast margins（elevation 〈 4800 m） of the Tibetan Plateau. This study provided more knowledge of spatial patterns of AGB and their environmental controls in grasslands than previous studies only conducted in local regions like the Inner Mongolian temperate grasslandthe Tibetan Plateau alpine grasslandetc.
文摘The maximum of k numerical functions defined on , , by , ??is used here in Statistical classification. Previously, it has been used in Statistical Discrimination [1] and in Clustering [2]. We present first some theoretical results on this function, and then its application in classification using a computer program we have developed. This approach leads to clear decisions, even in cases where the extension to several classes of Fisher’s linear discriminant function fails to be effective.
基金supported by the Key Project of Chinese National Programs for Fun-damental Research and Development (973 program) (2008CB425704)
文摘For exploring the aftershock occurrence process of the 2008 Wenchuan strong earthquake, the spatio-temporal point pattern analysis method is employed to study the sequences of aflershocks with magnitude M≥4.0, M≥4.5, and M≥5.0. It is found that these data exhibit the spatio-temporal clustering on a certain distance scale and on a certain time scale. In particular, the space-time interaction obviously strengthens when the distance is less than 60 km and the time is less than 260 h for the first two aftershock sequences; however, it becomes strong when the distance scale is less than 80 km and the time scale is less than 150 h for the last aftershock sequence. The completely spatial randomness analysis on the data regardless of time component shows that the spatial clustering of the aftershocks gradually strengthens on the condition that the distance is less than 60 km. The results are valuable for exploring the occurrence rules of the Wenchuan strong earthquake and for predicting the aftershocks.
基金supported by the National High-tech R&D Program(863 Program,No.2006AA10A113) of the Ministry of Science and Technology of Chinathe projects of Ministry of Agriculture of China for Transgenic Research (Nos.2009ZX08009-098B and 2008ZX08009-003)
文摘8-Sphingolipid desaturase is the key enzyme that catalyses desaturation at the C8 position of the long-chain base of sphingolipids in higher plants. There have been no previous studies on the genes encoding AS-sphingolipid desaturases in Brassica rapa. In this study, four genes encoding AS-sphingolipid desaturases from B. rapa were isolated and characterised. Phylogenetic analyses indicated that these genes could be divided into two groups： BrD8A, BrD8C and BrD8D in group I, and BrD8B in group II. The two groups of genes diverged before the separation of Arabidopsis and Brassica. Though the four genes shared a high sequence similarity, and their coding desaturases all located in endoplasmic reticulum, they exhibited distinct expression patterns. Heterologous expression in Saccharomyces cerevisiae revealed that BrD8A/B/C/D were functionally diverse AS-sphingolipid desaturases that catalyse different ratios of the two products 8（Z）- and 8（E）-C18-phytosphingenine. The aluminium tolerance of transgenic yeasts expressing BrD8A/B/C/D was enhanced compared with that of control cells. Expression of BrD8A in Arabidopsis changed the ratio of 8（Z）：8（E）-C 18-phytosphingenine in transgenic plants. The information reported here provides new insights into the biochemical functional diversity and evolutionary relationship of AS-sphingolipid desaturase in plants and lays a foundation for further investigation of the mechanism of 8（Z）- and 8（E）-C18- phytosphingenine biosynthesis.
基金Foundation： National Natural Science Foundation of China, No.41571124
文摘China＇s economy has undergone rapid transition and industrial restructuring. The term ＂urban industry＂ describes a particular type of industry within Chinese cities experiencing restructuring. Given the high percentage of industrial firms that have either closed or relo- cated from city centres to the urban fringe and beyond, emergent global cities such as Shanghai, are implementing strategies for local economic and urban development, which involve urban industrial upgrading numerous firms in the city centre and urban fringe. This study aims to analyze the location patterns of seven urban industrial sectors within the Shanghai urban region using 2008 micro-geography data. To avoid Modifiable Areal Unit Problem （MAUP） issue, four distance-based measures including nearest neighbourhood analysis, Kernel density estimation, K-function and co-location quotient have been exten- sively applied to analyze and compare the concentration and co-location between the seven sectors. The results reveal disparate patterns varying with distance and interesting co-location as well. The results are as follows： the city centre and the urban fringe have the highest intensity of urban industrial firms, but the zones with 20-30 km from the city centre is a watershed for most categories; the degree of concentration varies with distance, weaker at shorter distance, increasing up to the maximum distance of 30 km and then decreasing until 50 km; for all urban industries, there are three types of patterns, mixture of clustered, random and dispersed distribution at a varied range of distances. Consequently, this paper argues that the location pattern of urban industry reflects the stage-specific industrial restructuring and spatial transformation, conditioned by sustainability objectives.
文摘In this paper, an incremental learning model called Resource Allocating Network with Long-Term Memory (RAN-LTM) is extended such that the learning is conducted with some autonomy for the following functions: 1) data collection for initial learning, 2) data normalization, 3) addition of radial basis functions (RBFs), and 4) determination of RBF cen-ters and widths. The proposed learning algorithm called Autonomous Learning algorithm for Resource Allocating Network (AL-RAN) is divided into the two learning phases: initial learning phase and incremental learning phase. And the former is further divided into the autonomous data collection and the initial network learning. In the initial learning phase, training data are first collected until the class separability is converged or has a significant dif-ference between normalized and unnormalized data. Then, an initial structure of AL-RAN is autonomously determined by selecting a moderate number of RBF centers from the collected data and by defining as large RBF widths as possible within a proper range. After the initial learning, the incremental learning of AL-RAN is conducted in a sequential way whenever a new training data is given. In the experiments, we evaluate AL-RAN using five benchmark data sets. From the experimental results, we confirm that the above autonomous functions work well and the efficiency in terms of network structure and learning time is improved without sacrificing the recognition accuracy as compared with the previous version of AL-RAN.
文摘The multi-voxel pattern analysis technique is applied to fMRI data for classification of high-level brain functions using pattern information distributed over multiple voxels. In this paper, we propose a classifier ensemble for multiclass classification in fMRI analysis, exploiting the fact that specific neighboring voxels can contain spatial pattern information. The proposed method converts the multiclass classification to a pairwise classifier ensemble, and each pairwise classifier consists of multiple sub-clas- sifiers using an adaptive feature set for each class-pair. Simulated and real fMRI data were used to verify the proposed method. Intra- and inter-subject analyses were performed to compare the proposed method with several well-known classitiers, including single and ensemble classifiers. The comparison results showed that the proposed method can be generally applied to multiclass classification in both simulations and real fMRI analyses.
