Traditional Chinese medicine(TCM)represents a paradigmatic approach to personalized medicine,developed through the systematic accumulation and refinement of clinical empirical data over more than 2000 years,and now en...Traditional Chinese medicine(TCM)represents a paradigmatic approach to personalized medicine,developed through the systematic accumulation and refinement of clinical empirical data over more than 2000 years,and now encompasses large-scale electronic medical records(EMR)and experimental molecular data.Artificial intelligence(AI)has demonstrated its utility in medicine through the development of various expert systems(e.g.,MYCIN)since the 1970s.With the emergence of deep learning and large language models(LLMs),AI’s potential in medicine shows considerable promise.Consequently,the integration of AI and TCM from both clinical and scientific perspectives presents a fundamental and promising research direction.This survey provides an insightful overview of TCM AI research,summarizing related research tasks from three perspectives:systems-level biological mechanism elucidation,real-world clinical evidence inference,and personalized clinical decision support.The review highlights representative AI methodologies alongside their applications in both TCM scientific inquiry and clinical practice.To critically assess the current state of the field,this work identifies major challenges and opportunities that constrain the development of robust research capabilities—particularly in the mechanistic understanding of TCM syndromes and herbal formulations,novel drug discovery,and the delivery of high-quality,patient-centered clinical care.The findings underscore that future advancements in AI-driven TCM research will rely on the development of high-quality,large-scale data repositories;the construction of comprehensive and domain-specific knowledge graphs(KGs);deeper insights into the biological mechanisms underpinning clinical efficacy;rigorous causal inference frameworks;and intelligent,personalized decision support systems.展开更多
To reduce the computation cost of a combined probabilistic graphical model and a deep neural network in semantic segmentation, the local region condition random field (LRCRF) model is investigated which selectively ap...To reduce the computation cost of a combined probabilistic graphical model and a deep neural network in semantic segmentation, the local region condition random field (LRCRF) model is investigated which selectively applies the condition random field (CRF) to the most active region in the image. The full convolutional network structure is optimized with the ResNet-18 structure and dilated convolution to expand the receptive field. The tracking networks are also improved based on SiameseFC by considering the frame relations in consecutive-frame traffic scene maps. Moreover, the segmentation results of the greyscale input data sets are more stable and effective than using the RGB images for deep neural network feature extraction. The experimental results show that the proposed method takes advantage of the image features directly and achieves good real-time performance and high segmentation accuracy.展开更多
Dear Editor,This letter proposes a dynamic switching soft slicing strategy for industrial mixed traffic in 5G networks. Considering two types of traffic, periodic delay-sensitive (PDS) traffic and sporadic delay-toler...Dear Editor,This letter proposes a dynamic switching soft slicing strategy for industrial mixed traffic in 5G networks. Considering two types of traffic, periodic delay-sensitive (PDS) traffic and sporadic delay-tolerant (SDT) traffic, we design a dynamic switching strategy based on a traffic-Qo S-aware soft slicing (TQASS) scheme and a resource-efficiency-aware soft slicing (REASS) scheme.展开更多
Objective Humans are exposed to complex mixtures of environmental chemicals and other factors that can affect their health.Analysis of these mixture exposures presents several key challenges for environmental epidemio...Objective Humans are exposed to complex mixtures of environmental chemicals and other factors that can affect their health.Analysis of these mixture exposures presents several key challenges for environmental epidemiology and risk assessment,including high dimensionality,correlated exposure,and subtle individual effects.Methods We proposed a novel statistical approach,the generalized functional linear model(GFLM),to analyze the health effects of exposure mixtures.GFLM treats the effect of mixture exposures as a smooth function by reordering exposures based on specific mechanisms and capturing internal correlations to provide a meaningful estimation and interpretation.The robustness and efficiency was evaluated under various scenarios through extensive simulation studies.Results We applied the GFLM to two datasets from the National Health and Nutrition Examination Survey(NHANES).In the first application,we examined the effects of 37 nutrients on BMI(2011–2016 cycles).The GFLM identified a significant mixture effect,with fiber and fat emerging as the nutrients with the greatest negative and positive effects on BMI,respectively.For the second application,we investigated the association between four pre-and perfluoroalkyl substances(PFAS)and gout risk(2007–2018 cycles).Unlike traditional methods,the GFLM indicated no significant association,demonstrating its robustness to multicollinearity.Conclusion GFLM framework is a powerful tool for mixture exposure analysis,offering improved handling of correlated exposures and interpretable results.It demonstrates robust performance across various scenarios and real-world applications,advancing our understanding of complex environmental exposures and their health impacts on environmental epidemiology and toxicology.展开更多
Metal–organic frameworks(MOFs)hold great potential for gas separation and storage,and graph neural networks have proven to be a powerful tool for exploring material structure–property relationships and discovering n...Metal–organic frameworks(MOFs)hold great potential for gas separation and storage,and graph neural networks have proven to be a powerful tool for exploring material structure–property relationships and discovering new materials.Unlike traditional molecular graphs,crystal graphs require consideration of periodic invariance and modes.In addition,MOF structures such as covalent bonds,functional groups,and global structures impact adsorption performance in different ways.However,redundant atomic interactions can disrupt training accuracy,potentially leading to overfitting.In this paper,we propose a multi-scale crystal graph for describing periodic crystal structures,modeling interatomic interactions at different scales while preserving periodicity invariance.We also propose a multi-head attention crystal graph network in multi-scale graphs(MHACGN-MS),which learns structural characteristics by focusing on interatomic interactions at different scales,thereby reducing interference from redundant interactions.Using MOF adsorption for gases as an example,we demonstrate that MHACGN-MS outperforms traditional graph neural networks in predicting multi-component gas adsorption.We also visualize attention scores to validate effective learning and demonstrate the model’s interpretability.展开更多
Graphene （G） was dispersed uniformly in water and used as an inhibitor in waterborne epoxy coatings. The effect of dispersed G on anticorrosion performance of epoxy coatings was evaluated. The composite coatings dis...Graphene （G） was dispersed uniformly in water and used as an inhibitor in waterborne epoxy coatings. The effect of dispersed G on anticorrosion performance of epoxy coatings was evaluated. The composite coatings displayed outstanding barrier properties against H20 molecule compared to the neat epoxy coating. Open circuit potential （OCP）, Tafel and electrochemical impedance spectroscopy （EIS） analysis confirmed that the corrosion rate exhibited by composite coatings with 0.5 wt% G was an order of magnitude lower than that of neat epoxy coating. Salt spray test results revealed superior corrosion resistance offered by the composite coating.展开更多
1.Introduction Industrial automation is undergoing a significant innovation as information,communication,and operation technologies are deeply integrating with each other.Following this trend,industrial wireless contr...1.Introduction Industrial automation is undergoing a significant innovation as information,communication,and operation technologies are deeply integrating with each other.Following this trend,industrial wireless control networks(IWCNs)are becoming increasingly attractive to industrial automation since they can help speed up production efficiency,reduce cost,enhance safety,and finally realize intelligent manufacturing[1].展开更多
Protein O-GlcNAcylation is a monosaccharide post-translational modification maintained by two evolutionarily conserved enzymes, O-GlcNAc transferase (OGT) and O-GlcNAcase (OGA). Mutations in human OGT have recently be...Protein O-GlcNAcylation is a monosaccharide post-translational modification maintained by two evolutionarily conserved enzymes, O-GlcNAc transferase (OGT) and O-GlcNAcase (OGA). Mutations in human OGT have recently been associated with neurodevelopmental disorders, although the mechanisms linking O-GlcNAc homeostasis to neurodevelopment are not understood. Here, we investigate the effects of perturbing protein O-GlcNAcylation using transgenic Drosophila lines that overexpress a highly active OGA. We reveal that temporal reduction of protein O-GlcNAcylation in early embryos leads to reduced brain size and olfactory learning in adult Drosophila. Downregulation of O-GlcNAcylation induced by the exogenous OGA activity promotes nuclear foci formation of Polycomb-group protein Polyhomeotic and the accumulation of excess K27 trimethylation of histone H3 (H3K27me3) at the mid-blastula transition. These changes interfere with the zygotic expression of several neurodevelopmental genes, particularly short gastrulation (sog), a component of an evolutionarily conserved sog-Decapentaplegic (Dpp) signaling system required for neuroectoderm specification. Our findings highlight the importance of early embryonic O-GlcNAcylation homeostasis for the fidelity of facultative heterochromatin redeployment and initial cell fate commitment of neuronal lineages, suggesting a possible mechanism underpinning OGT-associated intellectual disability.展开更多
The year of 2013 is considered the first year of smart city in China. With the development of informationization and urbanization in China, city diseases(traffic jam, medical problem and unbalanced education) are more...The year of 2013 is considered the first year of smart city in China. With the development of informationization and urbanization in China, city diseases(traffic jam, medical problem and unbalanced education) are more and more apparent. Smart city is the key to solving these diseases. This paper presents the overall smart city development in China in term of market scale and development stages, the technology standards, and industry layout. The paper claims that the issues and challenges facing smart city development in China and proposes to make polices to support smart city development.展开更多
This paper addresses the problem of coordinating multiple mobile robots in searching for and capturing a mobile target,with the aim of reducing the capture time.Compared with the previous algorithms,we assume that the...This paper addresses the problem of coordinating multiple mobile robots in searching for and capturing a mobile target,with the aim of reducing the capture time.Compared with the previous algorithms,we assume that the target can be detected by any robot and captured successfully by two or more robots.In this paper,we assume that each robot has a limited communication range.We maintain the robots within a mobile network to guarantee the successful capture.In addition,the motion of the target is modeled and incorporated into directing the motion of the robots to reduce the capture time.A coordination algorithm considering both aspects is proposed.This algorithm can greatly reduce the expected time of capturing the mobile target.Finally,we validate the algorithm by the simulations and experiments.展开更多
We study the tradeoff between network utility and network lifetime using a cross-layer optimization approach. The tradeoff model in this paper is based on the framework of layering as optimization decomposition. Our t...We study the tradeoff between network utility and network lifetime using a cross-layer optimization approach. The tradeoff model in this paper is based on the framework of layering as optimization decomposition. Our tradeoff model is the first one that incorporates time slots allocation into this framework. By using Lagrangian dual decomposition method, we decompose the tradeoff model into two subproblems： routing problem at network layer and resource allocation problem at medium access control （MAC） layer. The interfaces between the layers are precisely the dual variables. A partially distributed algorithm is proposed to solve the nonlinear, convex, and separable tradeoff model. Numerical simulation results are presented to support our algorithm.展开更多
Mountain biodiversity is of great importance to biogeography and ecology.However,it is unclear what ecological and evolutionary processes best explain the generation and maintenance of its high levels of species diver...Mountain biodiversity is of great importance to biogeography and ecology.However,it is unclear what ecological and evolutionary processes best explain the generation and maintenance of its high levels of species diversity.In this study,we determined which of six common hypotheses(e.g.,climate hypotheses,habitat heterogeneity hypothesis and island biogeography theory)best explain global patterns of species diversity in Rhododendron.We found that Rhododendron diversity patterns were most strongly explained by proxies of island biogeography theory(i.e.,mountain area)and habitat heterogeneity(i.e.,elevation range).When we examined other relationships important to island biogeography theory,we found that the planimetric area and the volume of mountains were positively correlated with the Rhododendron diversity,whereas the‘mountains-to-mainland’distance was negatively correlated with Rhododendron diversity and shared species.Our findings demonstrate that Rhododendron diversity can be explained by island biogeography theory and habitat heterogeneity,and mountains can be regarded as islands which supported island biogeography theory.展开更多
Objective To systematically summarize the published literature on the genetic variants associated with nonalcoholic fatty liver disease(NAFLD).Methods Literature from Web of Science,PubMed,and Embase between January 1...Objective To systematically summarize the published literature on the genetic variants associated with nonalcoholic fatty liver disease(NAFLD).Methods Literature from Web of Science,PubMed,and Embase between January 1980 and September 2022 was systematically searched.Meta-analyses of the genetic variants were conducted using at least five data sources.The epidemiologic credibility of the significant associations was graded using the Venice criteria.Results Based on literature screening,399 eligible studies were included,comprising 381 candidate gene association,16 genome-wide association,and 2 whole-exome sequencing studies.We identified 465 genetic variants in 173 genes in candidate gene association studies,and 25 genetic variants in 17 genes were included in the meta-analysis.The meta-analysis identified 11 variants in 10 genes that were significantly associated with NAFLD,with cumulative epidemiological evidence of an association graded as strong for two variants in two genes(HFE,TNF),moderate for four variants in three genes(TM6SF2,GCKR,and ADIPOQ),and weak for five variants in five genes(MBOAT7,PEMT,PNPLA3,LEPR,and MTHFR).Conclusion This study identified six variants in five genes that had moderate to strong evidence of an association with NAFLD,which may help understand the genetic architecture of NAFLD risk.展开更多
Patterns of taxonomic and phylogenetic beta diversity and their relationships with environmental correlates can help reveal the origin and evolutionary history of regional biota.The Qinghai-Tibet Plateau(QTP)harbors a...Patterns of taxonomic and phylogenetic beta diversity and their relationships with environmental correlates can help reveal the origin and evolutionary history of regional biota.The Qinghai-Tibet Plateau(QTP)harbors an exceptionally diverse flora,however,a phylogenetic perspective has rarely been used to investigate its beta diversity and floristic regions.In this study,we used a phylogenetic approach to identify patterns of beta diversity and quantitatively delimit floristic regions on the Qinghai-Tibet Plateau.We also examined the relationships between multifaceted beta diversity,geographical distance,and climatic difference,and evaluated the relative importance of various factors(i.e.,climate,topography and history)in shaping patterns of beta diversity.Sørensen dissimilarity indices indicated that patterns of species turnover among sites dominated the QTP.We also found that patterns of both taxonomic and phylogenetic beta diversity were significantly related to geographical distance and climatic difference.The environmental factors that contributed most to these patterns of beta diversity include annual precipitation,mean annual temperature,climatic gradients and climatic instability.Hierarchical dendrograms of dissimilarity and non-metric multidimensional scaling ordination based on phylogenetic beta diversity data identified ten floristic subregions in the QTP.Our results suggest that the contemporary environment and historical climate changes have filtered species composition among sites and eventually determined beta diversity patterns of plants in the QTP.展开更多
The concentrations of SiO,Al2O,KO,NaO,CaO,MgO,Fe2Oand TiO,and loss on ignition(L.O.I.) are the main inorganic components of geological samples.Concentrations of the eight oxides and L.O.I.are also the main indicators ...The concentrations of SiO,Al2O,KO,NaO,CaO,MgO,Fe2Oand TiO,and loss on ignition(L.O.I.) are the main inorganic components of geological samples.Concentrations of the eight oxides and L.O.I.are also the main indicators of concern in the production of building ceramics.Quantitative analysis of the eight oxides and L.O.I.was performed using fiber-laserbased laser-induced breakdown spectroscopy(LIBS).A combination of continuous background deduction,full width at half maximum(FWHM) intensity integral and spectral sum normalization was proposed for data processing.After the data processing combined the continuous background deduction,FWHM intensity integral and spectral sum normalization,the mean absolute errors(MAEs) of the calibration of L.O.I.,SiO,Al2O,KO,NaO,CaO,MgO,Fe2Oand TiOwas reduced from 2.03%,12.06%,4.84%,1.10%,0.69%,0.31%,0.11%,0.20%and 0.10% to 1.80%,9.48%,2.12%,0.36%,0.58%,0.11%,0.08%,0.19% and 0.05%,respectively.This multivariate method was further introduced and discussed to improve the analysis performance.The MAEs of L.O.I.,SiO,Al2O,KO and NaO were further reduced to1.12%,2.07%,1.38%,0.35% and 0.43%,respectively.The results show that the overall prediction error can meet the requirements for the production of building ceramics.The LIBS desktop analyzer has great potential in detection applications on geological samples.展开更多
A new method that stabilizes network-based systems with both bounded delay and packet disordering is discussed under the state feedback controller. A novel model, fully describing the dynamic characteristic of network...A new method that stabilizes network-based systems with both bounded delay and packet disordering is discussed under the state feedback controller. A novel model, fully describing the dynamic characteristic of network-based systems with packet disordering, is constructed. Different from the existing models of network-based systems, the number of delay items is time-varying in the model proposed. Further, this model is converted into a parameter-uncertain discrete-time system with time-varying delay item numbers in terms of matrix theory. Moreover, the less conservative stability condition is obtained by avoiding utilisation of Moon et al.’ inequality and bounding inequalities for quadratic functional terms. By solving a minization problem based on linear matrix inequalities, the state feedback controller is presented. A numerical example is given to illustrate the effectiveness of the proposed method.展开更多
基金supported by the National Key Research and Development Program (No.2023YFC3502604)the National Natural Science Foundation of China (Nos.U23B2062, 82274352,82174533, 82374302, 82204941)+3 种基金the Noncommunicable Chronic Diseases-National Science and Technology Major Project (No.2023ZD0505700)the Beijing-Tianjin-Hebei Basic Research Cooperation Project (No.22JCZXJC00070)the State Key Laboratory on Technologies for Chinese Medicine Pharmaceutical Process Control and Intelligent Manufacture (No.SKL2024Z0102)Key R&D project of Ningxia Autonomous Region (No.2022BEG02036).
文摘Traditional Chinese medicine(TCM)represents a paradigmatic approach to personalized medicine,developed through the systematic accumulation and refinement of clinical empirical data over more than 2000 years,and now encompasses large-scale electronic medical records(EMR)and experimental molecular data.Artificial intelligence(AI)has demonstrated its utility in medicine through the development of various expert systems(e.g.,MYCIN)since the 1970s.With the emergence of deep learning and large language models(LLMs),AI’s potential in medicine shows considerable promise.Consequently,the integration of AI and TCM from both clinical and scientific perspectives presents a fundamental and promising research direction.This survey provides an insightful overview of TCM AI research,summarizing related research tasks from three perspectives:systems-level biological mechanism elucidation,real-world clinical evidence inference,and personalized clinical decision support.The review highlights representative AI methodologies alongside their applications in both TCM scientific inquiry and clinical practice.To critically assess the current state of the field,this work identifies major challenges and opportunities that constrain the development of robust research capabilities—particularly in the mechanistic understanding of TCM syndromes and herbal formulations,novel drug discovery,and the delivery of high-quality,patient-centered clinical care.The findings underscore that future advancements in AI-driven TCM research will rely on the development of high-quality,large-scale data repositories;the construction of comprehensive and domain-specific knowledge graphs(KGs);deeper insights into the biological mechanisms underpinning clinical efficacy;rigorous causal inference frameworks;and intelligent,personalized decision support systems.
文摘To reduce the computation cost of a combined probabilistic graphical model and a deep neural network in semantic segmentation, the local region condition random field (LRCRF) model is investigated which selectively applies the condition random field (CRF) to the most active region in the image. The full convolutional network structure is optimized with the ResNet-18 structure and dilated convolution to expand the receptive field. The tracking networks are also improved based on SiameseFC by considering the frame relations in consecutive-frame traffic scene maps. Moreover, the segmentation results of the greyscale input data sets are more stable and effective than using the RGB images for deep neural network feature extraction. The experimental results show that the proposed method takes advantage of the image features directly and achieves good real-time performance and high segmentation accuracy.
基金supported by the Liaoning Revitalization Talents Program(XLYC2203148)
文摘Dear Editor,This letter proposes a dynamic switching soft slicing strategy for industrial mixed traffic in 5G networks. Considering two types of traffic, periodic delay-sensitive (PDS) traffic and sporadic delay-tolerant (SDT) traffic, we design a dynamic switching strategy based on a traffic-Qo S-aware soft slicing (TQASS) scheme and a resource-efficiency-aware soft slicing (REASS) scheme.
基金supported in part by the Young Scientists Fund of the National Natural Science Foundation of China(Grant Nos.82304253)(and 82273709)the Foundation for Young Talents in Higher Education of Guangdong Province(Grant No.2022KQNCX021)the PhD Starting Project of Guangdong Medical University(Grant No.GDMUB2022054).
文摘Objective Humans are exposed to complex mixtures of environmental chemicals and other factors that can affect their health.Analysis of these mixture exposures presents several key challenges for environmental epidemiology and risk assessment,including high dimensionality,correlated exposure,and subtle individual effects.Methods We proposed a novel statistical approach,the generalized functional linear model(GFLM),to analyze the health effects of exposure mixtures.GFLM treats the effect of mixture exposures as a smooth function by reordering exposures based on specific mechanisms and capturing internal correlations to provide a meaningful estimation and interpretation.The robustness and efficiency was evaluated under various scenarios through extensive simulation studies.Results We applied the GFLM to two datasets from the National Health and Nutrition Examination Survey(NHANES).In the first application,we examined the effects of 37 nutrients on BMI(2011–2016 cycles).The GFLM identified a significant mixture effect,with fiber and fat emerging as the nutrients with the greatest negative and positive effects on BMI,respectively.For the second application,we investigated the association between four pre-and perfluoroalkyl substances(PFAS)and gout risk(2007–2018 cycles).Unlike traditional methods,the GFLM indicated no significant association,demonstrating its robustness to multicollinearity.Conclusion GFLM framework is a powerful tool for mixture exposure analysis,offering improved handling of correlated exposures and interpretable results.It demonstrates robust performance across various scenarios and real-world applications,advancing our understanding of complex environmental exposures and their health impacts on environmental epidemiology and toxicology.
基金supported by the National Natural Science Foundation of China(NSFC)(61821005).
文摘Metal–organic frameworks(MOFs)hold great potential for gas separation and storage,and graph neural networks have proven to be a powerful tool for exploring material structure–property relationships and discovering new materials.Unlike traditional molecular graphs,crystal graphs require consideration of periodic invariance and modes.In addition,MOF structures such as covalent bonds,functional groups,and global structures impact adsorption performance in different ways.However,redundant atomic interactions can disrupt training accuracy,potentially leading to overfitting.In this paper,we propose a multi-scale crystal graph for describing periodic crystal structures,modeling interatomic interactions at different scales while preserving periodicity invariance.We also propose a multi-head attention crystal graph network in multi-scale graphs(MHACGN-MS),which learns structural characteristics by focusing on interatomic interactions at different scales,thereby reducing interference from redundant interactions.Using MOF adsorption for gases as an example,we demonstrate that MHACGN-MS outperforms traditional graph neural networks in predicting multi-component gas adsorption.We also visualize attention scores to validate effective learning and demonstrate the model’s interpretability.
基金supported by National Natural Science Foundation of China(61100159,61233007)National High Technology Research and Development Program of China(863 Program)(2011AA040103)+2 种基金Foundation of Chinese Academy of Sciences(KGCX2-EW-104)Financial Support of the Strategic Priority Research Program of Chinese Academy of Sciences(XDA06021100)the Cross-disciplinary Collaborative Teams Program for Science,Technology and Innovation,of Chinese Academy of Sciences-Network and System Technologies for Security Monitoring and Information Interaction in Smart Grid Energy Management System for Micro-smart Grid
基金supported by the National Natural Science Foundation of China (No.41506098)the China Postdoctoral Science Foundation (No.2015M580528)the Open Fund Project of Key Laboratory of Marine Materials and Related Technologies (No.LMMTKFKT-2014-008) in the Chinese Academy of Sciences
文摘Graphene （G） was dispersed uniformly in water and used as an inhibitor in waterborne epoxy coatings. The effect of dispersed G on anticorrosion performance of epoxy coatings was evaluated. The composite coatings displayed outstanding barrier properties against H20 molecule compared to the neat epoxy coating. Open circuit potential （OCP）, Tafel and electrochemical impedance spectroscopy （EIS） analysis confirmed that the corrosion rate exhibited by composite coatings with 0.5 wt% G was an order of magnitude lower than that of neat epoxy coating. Salt spray test results revealed superior corrosion resistance offered by the composite coating.
基金the National Key Research and Development Program of China(2020YFB1710900)the National Natural Science Foundation of China(62173322 and 61803368)+2 种基金the China Postdoctoral Science Foundation(2019M661156)the Liaoning Revitalization Talents Program(XLYC1801001)the Youth Innovation Promotion Association Chinese Academy of Sciences(2019202).
文摘1.Introduction Industrial automation is undergoing a significant innovation as information,communication,and operation technologies are deeply integrating with each other.Following this trend,industrial wireless control networks(IWCNs)are becoming increasingly attractive to industrial automation since they can help speed up production efficiency,reduce cost,enhance safety,and finally realize intelligent manufacturing[1].
基金supported by National Natural Science Foundation of China(61304263,61233007)the Cross-disciplinary Collaborative Teams Program for Science,Technology and Innovation of Chinese Academy of Sciences-Network and System Technologies for Security Monitoring and Information Interaction in Smart Arid
基金This project has been supported by the National Natural Science Foundation of China(grants 91853108,92153301,31771589,and 32170821 to K.Y,32101034 to F.C)Department of Science and Technology of Hunan Province(grants 2017RS3013,2017XK2011,2018DK2015,2019SK1012,and 2021JJ10054 to K.Y,and the innovative team program 2019RS1010)+2 种基金Central South University(2018CX032 to K.Y,2019zzts046 to Y.Z,2019zzts339 to X.L,2021zzts497 to H.Y,and the innovation-driven team project 2020CX016)D.M.F.v.A.is supported by Wellcome Trust Investigator Award(110061)a Novo Nordisk Foundation Laureate award(NNF21OC0065969).
文摘Protein O-GlcNAcylation is a monosaccharide post-translational modification maintained by two evolutionarily conserved enzymes, O-GlcNAc transferase (OGT) and O-GlcNAcase (OGA). Mutations in human OGT have recently been associated with neurodevelopmental disorders, although the mechanisms linking O-GlcNAc homeostasis to neurodevelopment are not understood. Here, we investigate the effects of perturbing protein O-GlcNAcylation using transgenic Drosophila lines that overexpress a highly active OGA. We reveal that temporal reduction of protein O-GlcNAcylation in early embryos leads to reduced brain size and olfactory learning in adult Drosophila. Downregulation of O-GlcNAcylation induced by the exogenous OGA activity promotes nuclear foci formation of Polycomb-group protein Polyhomeotic and the accumulation of excess K27 trimethylation of histone H3 (H3K27me3) at the mid-blastula transition. These changes interfere with the zygotic expression of several neurodevelopmental genes, particularly short gastrulation (sog), a component of an evolutionarily conserved sog-Decapentaplegic (Dpp) signaling system required for neuroectoderm specification. Our findings highlight the importance of early embryonic O-GlcNAcylation homeostasis for the fidelity of facultative heterochromatin redeployment and initial cell fate commitment of neuronal lineages, suggesting a possible mechanism underpinning OGT-associated intellectual disability.
文摘The year of 2013 is considered the first year of smart city in China. With the development of informationization and urbanization in China, city diseases(traffic jam, medical problem and unbalanced education) are more and more apparent. Smart city is the key to solving these diseases. This paper presents the overall smart city development in China in term of market scale and development stages, the technology standards, and industry layout. The paper claims that the issues and challenges facing smart city development in China and proposes to make polices to support smart city development.
基金supported by the National Natural Science Foundation of China(No.60434030)
文摘This paper addresses the problem of coordinating multiple mobile robots in searching for and capturing a mobile target,with the aim of reducing the capture time.Compared with the previous algorithms,we assume that the target can be detected by any robot and captured successfully by two or more robots.In this paper,we assume that each robot has a limited communication range.We maintain the robots within a mobile network to guarantee the successful capture.In addition,the motion of the target is modeled and incorporated into directing the motion of the robots to reduce the capture time.A coordination algorithm considering both aspects is proposed.This algorithm can greatly reduce the expected time of capturing the mobile target.Finally,we validate the algorithm by the simulations and experiments.
基金supported by National Natural Science Foundation of China(61100159,61233007,61503371)National High Technology Research and Development Program of China(863 Program)(2011AA040103)+2 种基金Foundation of Chinese Academy of Sciences(KGCX2-EW-104)the Strategic Priority Research Program of the Chinese Academy of Sciences(XDA06021100)the Cross-disciplinary Collaborative Teams Program for Science,Technology,and Innovation of Chinese Academy of Sciences-Network and System Technologies for Security Monitoring and Information Interaction in Smart Grid,Energy Management System for Micro-smart Grid
基金supported by the Natural Science Foundation of China(No.60704046,60725312,60804067)the National 863 High Technology Research and Development Plan(No.2007AA04Z173,2007AA041201)
文摘We study the tradeoff between network utility and network lifetime using a cross-layer optimization approach. The tradeoff model in this paper is based on the framework of layering as optimization decomposition. Our tradeoff model is the first one that incorporates time slots allocation into this framework. By using Lagrangian dual decomposition method, we decompose the tradeoff model into two subproblems： routing problem at network layer and resource allocation problem at medium access control （MAC） layer. The interfaces between the layers are precisely the dual variables. A partially distributed algorithm is proposed to solve the nonlinear, convex, and separable tradeoff model. Numerical simulation results are presented to support our algorithm.
基金supported by the National Natural Science Foundation of China(NO.41901060).
文摘Mountain biodiversity is of great importance to biogeography and ecology.However,it is unclear what ecological and evolutionary processes best explain the generation and maintenance of its high levels of species diversity.In this study,we determined which of six common hypotheses(e.g.,climate hypotheses,habitat heterogeneity hypothesis and island biogeography theory)best explain global patterns of species diversity in Rhododendron.We found that Rhododendron diversity patterns were most strongly explained by proxies of island biogeography theory(i.e.,mountain area)and habitat heterogeneity(i.e.,elevation range).When we examined other relationships important to island biogeography theory,we found that the planimetric area and the volume of mountains were positively correlated with the Rhododendron diversity,whereas the‘mountains-to-mainland’distance was negatively correlated with Rhododendron diversity and shared species.Our findings demonstrate that Rhododendron diversity can be explained by island biogeography theory and habitat heterogeneity,and mountains can be regarded as islands which supported island biogeography theory.
基金supported by grants from the National Natural Science Foundation of China[No.81872641]Natural Science Foundation of Hunan Province[No.2023JJ40357].
文摘Objective To systematically summarize the published literature on the genetic variants associated with nonalcoholic fatty liver disease(NAFLD).Methods Literature from Web of Science,PubMed,and Embase between January 1980 and September 2022 was systematically searched.Meta-analyses of the genetic variants were conducted using at least five data sources.The epidemiologic credibility of the significant associations was graded using the Venice criteria.Results Based on literature screening,399 eligible studies were included,comprising 381 candidate gene association,16 genome-wide association,and 2 whole-exome sequencing studies.We identified 465 genetic variants in 173 genes in candidate gene association studies,and 25 genetic variants in 17 genes were included in the meta-analysis.The meta-analysis identified 11 variants in 10 genes that were significantly associated with NAFLD,with cumulative epidemiological evidence of an association graded as strong for two variants in two genes(HFE,TNF),moderate for four variants in three genes(TM6SF2,GCKR,and ADIPOQ),and weak for five variants in five genes(MBOAT7,PEMT,PNPLA3,LEPR,and MTHFR).Conclusion This study identified six variants in five genes that had moderate to strong evidence of an association with NAFLD,which may help understand the genetic architecture of NAFLD risk.
基金This study was funded by the National Natural Science Foundation of China(grant no.31901212)Talent Start-up Foundation of Guangzhou University(grant no.RP2020079).
文摘Patterns of taxonomic and phylogenetic beta diversity and their relationships with environmental correlates can help reveal the origin and evolutionary history of regional biota.The Qinghai-Tibet Plateau(QTP)harbors an exceptionally diverse flora,however,a phylogenetic perspective has rarely been used to investigate its beta diversity and floristic regions.In this study,we used a phylogenetic approach to identify patterns of beta diversity and quantitatively delimit floristic regions on the Qinghai-Tibet Plateau.We also examined the relationships between multifaceted beta diversity,geographical distance,and climatic difference,and evaluated the relative importance of various factors(i.e.,climate,topography and history)in shaping patterns of beta diversity.Sørensen dissimilarity indices indicated that patterns of species turnover among sites dominated the QTP.We also found that patterns of both taxonomic and phylogenetic beta diversity were significantly related to geographical distance and climatic difference.The environmental factors that contributed most to these patterns of beta diversity include annual precipitation,mean annual temperature,climatic gradients and climatic instability.Hierarchical dendrograms of dissimilarity and non-metric multidimensional scaling ordination based on phylogenetic beta diversity data identified ten floristic subregions in the QTP.Our results suggest that the contemporary environment and historical climate changes have filtered species composition among sites and eventually determined beta diversity patterns of plants in the QTP.
基金supported by National Natural Science Foundation of China(No.62173321)the Key Research Program of Frontier Sciences,CAS(No.QYZDJ-SSW-JSC037)+2 种基金the Science and Technology Service Network Initiative Program,CAS(No.KFJ-STS-QYZD-2021-19-002)the Liaoning Provincial Natural Science Foundation(No.2021-BS-022)the Youth Innovation Promotion Association,CAS。
文摘The concentrations of SiO,Al2O,KO,NaO,CaO,MgO,Fe2Oand TiO,and loss on ignition(L.O.I.) are the main inorganic components of geological samples.Concentrations of the eight oxides and L.O.I.are also the main indicators of concern in the production of building ceramics.Quantitative analysis of the eight oxides and L.O.I.was performed using fiber-laserbased laser-induced breakdown spectroscopy(LIBS).A combination of continuous background deduction,full width at half maximum(FWHM) intensity integral and spectral sum normalization was proposed for data processing.After the data processing combined the continuous background deduction,FWHM intensity integral and spectral sum normalization,the mean absolute errors(MAEs) of the calibration of L.O.I.,SiO,Al2O,KO,NaO,CaO,MgO,Fe2Oand TiOwas reduced from 2.03%,12.06%,4.84%,1.10%,0.69%,0.31%,0.11%,0.20%and 0.10% to 1.80%,9.48%,2.12%,0.36%,0.58%,0.11%,0.08%,0.19% and 0.05%,respectively.This multivariate method was further introduced and discussed to improve the analysis performance.The MAEs of L.O.I.,SiO,Al2O,KO and NaO were further reduced to1.12%,2.07%,1.38%,0.35% and 0.43%,respectively.The results show that the overall prediction error can meet the requirements for the production of building ceramics.The LIBS desktop analyzer has great potential in detection applications on geological samples.
基金supported by the National Natural Science Foundation of China (60874057 60725312+3 种基金 61074029)the Liaoning Provincal Foundation of Science and Technology (20082023)the Natural Science Foundation of Liaoning Province (20092083)China Postdoctoral Science Foundation Project (20100471488)
文摘A new method that stabilizes network-based systems with both bounded delay and packet disordering is discussed under the state feedback controller. A novel model, fully describing the dynamic characteristic of network-based systems with packet disordering, is constructed. Different from the existing models of network-based systems, the number of delay items is time-varying in the model proposed. Further, this model is converted into a parameter-uncertain discrete-time system with time-varying delay item numbers in terms of matrix theory. Moreover, the less conservative stability condition is obtained by avoiding utilisation of Moon et al.’ inequality and bounding inequalities for quadratic functional terms. By solving a minization problem based on linear matrix inequalities, the state feedback controller is presented. A numerical example is given to illustrate the effectiveness of the proposed method.
