Model evaluation using benchmark datasets is an important method to measure the capability of large language models(LLMs)in specific domains,and it is mainly used to assess the knowledge and reasoning abilities of LLM...Model evaluation using benchmark datasets is an important method to measure the capability of large language models(LLMs)in specific domains,and it is mainly used to assess the knowledge and reasoning abilities of LLMs.Therefore,in order to better assess the capability of LLMs in the agricultural domain,Agri-Eval was proposed as a benchmark for assessing the knowledge and reasoning ability of LLMs in agriculture.The assessment dataset used in Agri-Eval covered seven major disciplines in the agricultural domain:crop science,horticulture,plant protection,animal husbandry,forest science,aquaculture science,and grass science,and contained a total of 2283 questions.Among domestic general-purpose LLMs,DeepSeek R1 performed best with an accuracy rate of 75.49%.In the realm of international general-purpose LLMs,Gemini 2.0 pro exp 0205 standed out as the top performer,achieving an accuracy rate of 74.28%.As an LLMs in agriculture vertical,Shennong V2.0 outperformed all the LLMs in China,and the answer accuracy rate of agricultural knowledge exceeded that of all the existing general-purpose LLMs.The launch of Agri-Eval helped the LLM developers to comprehensively evaluate the model's capability in the field of agriculture through a variety of tasks and tests to promote the development of the LLMs in the field of agriculture.展开更多
Temperature-programmed desorption(TPD)is a fundamental technique in surface science and heterogeneous catalysis for characterizing adsorption behavior,and for extracting key parameters such as adsorption energy.Howeve...Temperature-programmed desorption(TPD)is a fundamental technique in surface science and heterogeneous catalysis for characterizing adsorption behavior,and for extracting key parameters such as adsorption energy.However,the majority of existing TPD data is accessible in the form of published images,which lacks structured and quantitative datasets.This constrains its utility for rigorous quantitative analysis and computational modelling.Using carbon monoxide(CO)which is a widely adopted probe molecule,a curated and standardized dataset of CO-TPD is constructed,encompassing 14 transition-metal single-crystal surfaces,including copper(Cu)and ruthenium(Ru).By systematically extracting numerical data points from published spectra and applying normalization,essential spectral features such as peak shape are fully preserved.The dataset also documents relevant experimental parameters,including heating rates,and was developed using a standardized protocol for data collection and quality control.This resource serves as both a reference library to support the deconvolution of TPD spectra from complex catalysts and an experimental benchmark for calibrating parameters in theoretical models.By providing a reliable and accessible data function,this work advances the microscopic understanding and the rational design of catalyst active centers.展开更多
This data set collects,compares and contrasts the capacities and structures of a series of hard carbon materials,and then searches for correlations between structure and electrochemical performance.The capacity data o...This data set collects,compares and contrasts the capacities and structures of a series of hard carbon materials,and then searches for correlations between structure and electrochemical performance.The capacity data of the hard carbons were obtained by charge/discharge tests and the materials were characterized by XRD,gas adsorption,true density tests and SAXS.In particular,the fitting of SAXS gave a series of structural parameters which showed good characterization.The related test details are given with the structural data of the hard carbons and the electrochemical performance of the sodium-ion batteries.展开更多
Objective:Metabolic dysfunction-associated steatohepatitis(MASH),a progressive subtype of metabolic dysfunction-associated steatotic liver disease(MASLD),is characterized by hepatic steatosis,lobular inflammation,and ...Objective:Metabolic dysfunction-associated steatohepatitis(MASH),a progressive subtype of metabolic dysfunction-associated steatotic liver disease(MASLD),is characterized by hepatic steatosis,lobular inflammation,and hepatocyte ballooning,and may further progress to liver fibrosis and cirrhosis.Lectin-like oxidized low-density lipoprotein receptor-1(LOX-1),a member of the scavenger receptor family,recognizes and binds oxidized low-density lipoprotein.This study aims to investigate the role of LOX-1 in MASH progression.Methods:LOX-1 expression in MASLD mouse liver was analyzed using Gene Expression Omnibus(GEO)datasets.Immunofluorescence staining was performed to detect LOX-1 and alpha-smooth muscle actin(α-SMA)levels and co-localization in fibrotic liver tissues and LX-2 cells.LOX-1 knockout(Lox-1^(−/−))mice were generated using CRISPR/caspase-9(Cas9)and genotyped by PCR and Sanger sequencing.Wild-type(WT)and Lox-1^(−/−)mice were randomized into control and Western diet model groups.Serum and liver samples were collected for alanine aminotransferase(ALT)and aspartate aminotransferase(AST)measurement by biochemical kits,liver structure evaluation by hematoxylin and eosin(HE)staining,collagen deposition by Masson staining,lipid accumulation by Oil Red O staining,and fibrotic marker gene expression by real-time quantitative PCR(RT-qPCR).Network pharmacology and search tool for the retrieval of interacting genes/proteins(STRING)-based protein-protein interaction(PPI)with Gene Ontology(GO)enrichment were used to predict downstream targets and pathways.Results:The results from the GEO datasets GSE30552 and GSE40041 indicated LOX-1 mRNA was upregulated in high fat diet(HFD)and bile duct ligation(BDL)mouse models(both P<0.001).LOX-1 and α-SMA levels were elevated in fibrotic liver tissues.Lox-1^(−/−)mice were successfully established.Biochemical tests showed that serum AST and ALT levels were significantly elevated in WT mice fed a Western diet(both P<0.001),and these levels decreased after LOX-1 knockout(both P<0.05).HE staining revealed that WT mice on the Western diet exhibited marked hepatocellular ballooning degeneration,steatosis,inflammatory cell infiltration,and periportal fibroplasia,which were significantly ameliorated by LOX-1 knockout.Masson staining demonstrated increased blue-stained collagen fibers in the liver tissues of WT mice fed the Western diet compared with controldiet mice,and LOX-1 knockout inhibited collagen fiber deposition(all P<0.05).RT‑qPCR results showed that hepatic mRNA levels of Acta2,Col1a1,and Timp1 were significantly increased in Western diet-fed mice,and LOX-1 knockout reduced the expression of these fibrogenic marker genes.Oil Red O staining indicated that hepatocytes in WT mice fed the Western diet were notably enlarged,displayed macrovesicular steatosis,and exhibited diffusely distributed red lipid droplets,whereas LOX-1 knockout alleviated hepatic lipid accumulation(both P<0.001).RT‑qPCR results further demonstrated that knockdown of LOX-1 reduced Acta2,Col1a1,and Timp1 mRNA levels in LX‑2 cells(all P<0.05).Immunofluorescence analysis revealed co‑localization of LOX-1 and α‑SMA in LX‑2 cells,and LOX-1 silencing suppressed α‑SMA expression.Network pharmacology suggested LOX-1 may promote MASH via lipid and cholesterol metabolism networks.Conclusion:LOX-1 gene knockout ameliorates Western diet-induced MASH in mice and may serve as a potential therapeutic target.展开更多
由于网络访问的快捷与便利,利用网络进行商品信息的管理与销售已经被广泛应用到各行各业中。针对珠宝这一特殊商品,利用Visual Studio 2010开发平台和SQL Sever 2008数据库软件,采用ASP.NET MVC架构设计一套网上珠宝销售系统,实现对珠...由于网络访问的快捷与便利,利用网络进行商品信息的管理与销售已经被广泛应用到各行各业中。针对珠宝这一特殊商品,利用Visual Studio 2010开发平台和SQL Sever 2008数据库软件,采用ASP.NET MVC架构设计一套网上珠宝销售系统,实现对珠宝信息的方便录入及快速查询,在保障珠宝安全的同时满足客户选购的需求。重点描述系统的整体设计模型,MVC架构在系统中的应用,并对数据建模与访问关键技术进行深入研究。该系统目前已应用于美国华尔街的某珠宝公司,实际应用证明该系统具有稳定、高效和安全的特点。展开更多
The sharp increase of the amount of Internet Chinese text data has significantly prolonged the processing time of classification on these data.In order to solve this problem,this paper proposes and implements a parall...The sharp increase of the amount of Internet Chinese text data has significantly prolonged the processing time of classification on these data.In order to solve this problem,this paper proposes and implements a parallel naive Bayes algorithm(PNBA)for Chinese text classification based on Spark,a parallel memory computing platform for big data.This algorithm has implemented parallel operation throughout the entire training and prediction process of naive Bayes classifier mainly by adopting the programming model of resilient distributed datasets(RDD).For comparison,a PNBA based on Hadoop is also implemented.The test results show that in the same computing environment and for the same text sets,the Spark PNBA is obviously superior to the Hadoop PNBA in terms of key indicators such as speedup ratio and scalability.Therefore,Spark-based parallel algorithms can better meet the requirement of large-scale Chinese text data mining.展开更多
To solve the path following control problem for unmanned surface vehicles(USVs),a control method based on deep reinforcement learning(DRL)with long short-term memory(LSTM)networks is proposed.A distributed proximal po...To solve the path following control problem for unmanned surface vehicles(USVs),a control method based on deep reinforcement learning(DRL)with long short-term memory(LSTM)networks is proposed.A distributed proximal policy opti-mization(DPPO)algorithm,which is a modified actor-critic-based type of reinforcement learning algorithm,is adapted to improve the controller performance in repeated trials.The LSTM network structure is introduced to solve the strong temporal cor-relation USV control problem.In addition,a specially designed path dataset,including straight and curved paths,is established to simulate various sailing scenarios so that the reinforcement learning controller can obtain as much handling experience as possible.Extensive numerical simulation results demonstrate that the proposed method has better control performance under missions involving complex maneuvers than trained with limited scenarios and can potentially be applied in practice.展开更多
文摘Model evaluation using benchmark datasets is an important method to measure the capability of large language models(LLMs)in specific domains,and it is mainly used to assess the knowledge and reasoning abilities of LLMs.Therefore,in order to better assess the capability of LLMs in the agricultural domain,Agri-Eval was proposed as a benchmark for assessing the knowledge and reasoning ability of LLMs in agriculture.The assessment dataset used in Agri-Eval covered seven major disciplines in the agricultural domain:crop science,horticulture,plant protection,animal husbandry,forest science,aquaculture science,and grass science,and contained a total of 2283 questions.Among domestic general-purpose LLMs,DeepSeek R1 performed best with an accuracy rate of 75.49%.In the realm of international general-purpose LLMs,Gemini 2.0 pro exp 0205 standed out as the top performer,achieving an accuracy rate of 74.28%.As an LLMs in agriculture vertical,Shennong V2.0 outperformed all the LLMs in China,and the answer accuracy rate of agricultural knowledge exceeded that of all the existing general-purpose LLMs.The launch of Agri-Eval helped the LLM developers to comprehensively evaluate the model's capability in the field of agriculture through a variety of tasks and tests to promote the development of the LLMs in the field of agriculture.
基金Supported by the Robotic AI-Scientist Platform of Chinese Academy of SciencesNational Natural Science Foundation of China(22372185)+2 种基金Youth Talent Development Program of SKLCC(2025BWZ009)Natural Science Foundation of Shanxi Province(202203021221219)Research on the Construction of Scientific and Technological Innovation Think Tank of Shanxi Association for Science and Technology(KXKT202542)。
文摘Temperature-programmed desorption(TPD)is a fundamental technique in surface science and heterogeneous catalysis for characterizing adsorption behavior,and for extracting key parameters such as adsorption energy.However,the majority of existing TPD data is accessible in the form of published images,which lacks structured and quantitative datasets.This constrains its utility for rigorous quantitative analysis and computational modelling.Using carbon monoxide(CO)which is a widely adopted probe molecule,a curated and standardized dataset of CO-TPD is constructed,encompassing 14 transition-metal single-crystal surfaces,including copper(Cu)and ruthenium(Ru).By systematically extracting numerical data points from published spectra and applying normalization,essential spectral features such as peak shape are fully preserved.The dataset also documents relevant experimental parameters,including heating rates,and was developed using a standardized protocol for data collection and quality control.This resource serves as both a reference library to support the deconvolution of TPD spectra from complex catalysts and an experimental benchmark for calibrating parameters in theoretical models.By providing a reliable and accessible data function,this work advances the microscopic understanding and the rational design of catalyst active centers.
基金supported by the National Natural Science Foundation of China(22379157)CAS Project for Young Scientists in Basic Research(YSBR-102)+2 种基金Institute of Coal Chemistry,Chinese Academy of Sciences(SCJC-XCL-2023-13,SCJCXCL-2023-10)Talent Projects for Outstanding Doctoral Students to Work in Shanxi Province(E3SWR4791Z)Fundamental Research Program of Shanxi Province(202403021222485).
文摘This data set collects,compares and contrasts the capacities and structures of a series of hard carbon materials,and then searches for correlations between structure and electrochemical performance.The capacity data of the hard carbons were obtained by charge/discharge tests and the materials were characterized by XRD,gas adsorption,true density tests and SAXS.In particular,the fitting of SAXS gave a series of structural parameters which showed good characterization.The related test details are given with the structural data of the hard carbons and the electrochemical performance of the sodium-ion batteries.
基金supported by the Natural Science Foundation of Hunan Province,China(211142095031)。
文摘Objective:Metabolic dysfunction-associated steatohepatitis(MASH),a progressive subtype of metabolic dysfunction-associated steatotic liver disease(MASLD),is characterized by hepatic steatosis,lobular inflammation,and hepatocyte ballooning,and may further progress to liver fibrosis and cirrhosis.Lectin-like oxidized low-density lipoprotein receptor-1(LOX-1),a member of the scavenger receptor family,recognizes and binds oxidized low-density lipoprotein.This study aims to investigate the role of LOX-1 in MASH progression.Methods:LOX-1 expression in MASLD mouse liver was analyzed using Gene Expression Omnibus(GEO)datasets.Immunofluorescence staining was performed to detect LOX-1 and alpha-smooth muscle actin(α-SMA)levels and co-localization in fibrotic liver tissues and LX-2 cells.LOX-1 knockout(Lox-1^(−/−))mice were generated using CRISPR/caspase-9(Cas9)and genotyped by PCR and Sanger sequencing.Wild-type(WT)and Lox-1^(−/−)mice were randomized into control and Western diet model groups.Serum and liver samples were collected for alanine aminotransferase(ALT)and aspartate aminotransferase(AST)measurement by biochemical kits,liver structure evaluation by hematoxylin and eosin(HE)staining,collagen deposition by Masson staining,lipid accumulation by Oil Red O staining,and fibrotic marker gene expression by real-time quantitative PCR(RT-qPCR).Network pharmacology and search tool for the retrieval of interacting genes/proteins(STRING)-based protein-protein interaction(PPI)with Gene Ontology(GO)enrichment were used to predict downstream targets and pathways.Results:The results from the GEO datasets GSE30552 and GSE40041 indicated LOX-1 mRNA was upregulated in high fat diet(HFD)and bile duct ligation(BDL)mouse models(both P<0.001).LOX-1 and α-SMA levels were elevated in fibrotic liver tissues.Lox-1^(−/−)mice were successfully established.Biochemical tests showed that serum AST and ALT levels were significantly elevated in WT mice fed a Western diet(both P<0.001),and these levels decreased after LOX-1 knockout(both P<0.05).HE staining revealed that WT mice on the Western diet exhibited marked hepatocellular ballooning degeneration,steatosis,inflammatory cell infiltration,and periportal fibroplasia,which were significantly ameliorated by LOX-1 knockout.Masson staining demonstrated increased blue-stained collagen fibers in the liver tissues of WT mice fed the Western diet compared with controldiet mice,and LOX-1 knockout inhibited collagen fiber deposition(all P<0.05).RT‑qPCR results showed that hepatic mRNA levels of Acta2,Col1a1,and Timp1 were significantly increased in Western diet-fed mice,and LOX-1 knockout reduced the expression of these fibrogenic marker genes.Oil Red O staining indicated that hepatocytes in WT mice fed the Western diet were notably enlarged,displayed macrovesicular steatosis,and exhibited diffusely distributed red lipid droplets,whereas LOX-1 knockout alleviated hepatic lipid accumulation(both P<0.001).RT‑qPCR results further demonstrated that knockdown of LOX-1 reduced Acta2,Col1a1,and Timp1 mRNA levels in LX‑2 cells(all P<0.05).Immunofluorescence analysis revealed co‑localization of LOX-1 and α‑SMA in LX‑2 cells,and LOX-1 silencing suppressed α‑SMA expression.Network pharmacology suggested LOX-1 may promote MASH via lipid and cholesterol metabolism networks.Conclusion:LOX-1 gene knockout ameliorates Western diet-induced MASH in mice and may serve as a potential therapeutic target.
文摘由于网络访问的快捷与便利,利用网络进行商品信息的管理与销售已经被广泛应用到各行各业中。针对珠宝这一特殊商品,利用Visual Studio 2010开发平台和SQL Sever 2008数据库软件,采用ASP.NET MVC架构设计一套网上珠宝销售系统,实现对珠宝信息的方便录入及快速查询,在保障珠宝安全的同时满足客户选购的需求。重点描述系统的整体设计模型,MVC架构在系统中的应用,并对数据建模与访问关键技术进行深入研究。该系统目前已应用于美国华尔街的某珠宝公司,实际应用证明该系统具有稳定、高效和安全的特点。
基金Project(KC18071)supported by the Application Foundation Research Program of Xuzhou,ChinaProjects(2017YFC0804401,2017YFC0804409)supported by the National Key R&D Program of China
文摘The sharp increase of the amount of Internet Chinese text data has significantly prolonged the processing time of classification on these data.In order to solve this problem,this paper proposes and implements a parallel naive Bayes algorithm(PNBA)for Chinese text classification based on Spark,a parallel memory computing platform for big data.This algorithm has implemented parallel operation throughout the entire training and prediction process of naive Bayes classifier mainly by adopting the programming model of resilient distributed datasets(RDD).For comparison,a PNBA based on Hadoop is also implemented.The test results show that in the same computing environment and for the same text sets,the Spark PNBA is obviously superior to the Hadoop PNBA in terms of key indicators such as speedup ratio and scalability.Therefore,Spark-based parallel algorithms can better meet the requirement of large-scale Chinese text data mining.
基金supported by the National Natural Science Foundation(61601491)the Natural Science Foundation of Hubei Province(2018CFC865)the China Postdoctoral Science Foundation Funded Project(2016T45686).
文摘To solve the path following control problem for unmanned surface vehicles(USVs),a control method based on deep reinforcement learning(DRL)with long short-term memory(LSTM)networks is proposed.A distributed proximal policy opti-mization(DPPO)algorithm,which is a modified actor-critic-based type of reinforcement learning algorithm,is adapted to improve the controller performance in repeated trials.The LSTM network structure is introduced to solve the strong temporal cor-relation USV control problem.In addition,a specially designed path dataset,including straight and curved paths,is established to simulate various sailing scenarios so that the reinforcement learning controller can obtain as much handling experience as possible.Extensive numerical simulation results demonstrate that the proposed method has better control performance under missions involving complex maneuvers than trained with limited scenarios and can potentially be applied in practice.
