This study analyzes the evolution of China's green technology innovation cooperation network from 2011 to 2020,utilizing green patent application data.Employing a Spatial Durbin Model(SDM),we scrutinized the netwo...This study analyzes the evolution of China's green technology innovation cooperation network from 2011 to 2020,utilizing green patent application data.Employing a Spatial Durbin Model(SDM),we scrutinized the network's influence on urban carbon emissions,utilizing panel data encompassing 323 city nodes.Results show network expansion and a shift in central nodes from eastern coastal areas to interior cities,with Beijing,Shenzhen,Nanjing,and Shanghai consistently acting as key innovation hubs.A core-periphery structure emerged,clustering cities into high-and low-cooperation clusters.Core cities,particularly Beijing,which gain informational advantages by bridging non-overlapping nodes and exhibit distinct characteristics in terms of the structural hole indexes,reflecting their multifaceted roles within the network.SDM analysis indicates that the green technology innovation cooperation network has a significant positive impact on urban carbon reduction efforts.Specifically,degree centrality,closeness centrality,effective size,efficiency,and hierarchy of node cities exhibit a negative correlation with carbon emissions,suggesting that higher centrality and efficiency within the network correlate with lower emissions.Conversely,betweenness centrality and constraint have a positive impact on emissions,indicating that cities that act as bridges in the network may paradoxically contribute to higher emissions.Moreover,the network's influence on carbon emissions is nuanced across different green technology sectors.Cooperation in areas such as waste management,alternative energy production,energy conservation,agriculture and forestry,and transportation is found to have a more substantial impact on carbon reduction than cooperation in nuclear power,and administrative,regulatory,and design fields.展开更多
The convergence of optical and wireless technologies is driving the evolution of intelligent indoor networks,with Fiber-to-the-Room(FTTR)emerging as a key ar⁃chitecture for delivering gigabit connectivity in both home...The convergence of optical and wireless technologies is driving the evolution of intelligent indoor networks,with Fiber-to-the-Room(FTTR)emerging as a key ar⁃chitecture for delivering gigabit connectivity in both home and enterprise environments.By deploying optical fiber directly to rooms and integrating it with advanced wireless so⁃lutions such as millimeter-wave and Wi-Fi 7,FTTR enables next-generation applications,including immersive Virtual Re⁃ality(VR)/Augmented Reality(AR)and industrial Internet of Things(IoT).Nevertheless,its large-scale deployment pres⁃ents challenges in network management,energy efficiency,in⁃terference mitigation,and intelligent root cause analysis.展开更多
With the rapid development of modern information technology,the Internet of Things(IoT)has been integrated into various fields such as social life,industrial production,education,and medical care.Through the connectio...With the rapid development of modern information technology,the Internet of Things(IoT)has been integrated into various fields such as social life,industrial production,education,and medical care.Through the connection of various physical devices,sensors,and machines,it realizes information intercommunication and remote control among devices,significantly enhancing the convenience and efficiency of work and life.However,the rapid development of the IoT has also brought serious security problems.IoT devices have limited resources and a complex network environment,making them one of the important targets of network intrusion attacks.Therefore,from the perspective of deep learning,this paper deeply analyzes the characteristics and key points of IoT intrusion detection,summarizes the application advantages of deep learning in IoT intrusion detection,and proposes application strategies of typical deep learning models in IoT intrusion detection so as to improve the security of the IoT architecture and guarantee people’s convenient lives.展开更多
In recent years,the network public opinion reversal governance events have occurred frequently.Over time,the repeated truth of the matter will not only weaken the rational judgment of the public to a certain extent,so...In recent years,the network public opinion reversal governance events have occurred frequently.Over time,the repeated truth of the matter will not only weaken the rational judgment of the public to a certain extent,so that its negative emotions accumulate,but also have a serious impact on the credibility of the media and the government,and may even further intensify social contradictions.Therefore,in the face of such a complex online public opinion space,accurately identifying the truth behind the incident and how to carry out the reversal of online public opinion governance is particularly critical.And blockchain technology,with its advantages of decentralization and immutable information,provides new technical support for the network public opinion reversal governance.Based on this,this paper gives an overview and analysis of blockchain technology and network public opinion reversal,and on this basis introduces the network public opinion reversal governance mechanism based on blockchain technology,aiming to further optimize the network public opinion reversal governance process,for reference only.展开更多
The Internet of Things technology provides a comprehensive solution for the real-time monitoring of cold chain logistics by integrating sensors,wireless communication,cloud computing,and big data analysis.Based on thi...The Internet of Things technology provides a comprehensive solution for the real-time monitoring of cold chain logistics by integrating sensors,wireless communication,cloud computing,and big data analysis.Based on this,this paper deeply explores the overview and characteristics of the Internet of Things technology,the feasibility analysis of the Internet of Things technology in the cold chain logistics monitoring,the application analysis of the Internet of Things technology in the cold chain logistics real-time monitoring to better improve the management level and operational efficiency of the cold chain logistics,to provide consumers with safer and fresh products.展开更多
Objective:To study the effect of transcranial magnetic stimulation(TMS)on improving motor symptoms in patients with Parkinson’s disease(PD).Methods:60 PD patients who visited the hospital from September 2023 to Augus...Objective:To study the effect of transcranial magnetic stimulation(TMS)on improving motor symptoms in patients with Parkinson’s disease(PD).Methods:60 PD patients who visited the hospital from September 2023 to August 2024 were selected as samples and randomly divided into two groups.Group A received conventional medication plus TMS treatment,while Group B received medication only.The efficacy of motor function improvement,neurological symptoms,mental state,sleep quality,quality of life,and adverse reactions was compared between the two groups.Results:The efficacy of Group A was higher than that of Group B(P<0.05).The scores of the Scales for Outcomes in Parkinson’s Disease-Autonomic(SCOPA-AUT),Mini-Mental State Examination(MMSE),and Pittsburgh Sleep Quality Index(PSQI)in Group A were lower than those in Group B(P<0.05).The quality of life scale(SF-36)score in Group A was higher than that in Group B(P<0.05).The adverse reaction rate in Group A was lower than that in Group B(P<0.05).Conclusion:TMS used in the treatment of PD patients can improve patients’mental state and motor function,optimize sleep quality and quality of life,and is safe and efficient.展开更多
The 2024 MRE HP Special Volume selects papers on new theoretical and experimental developments in the use of static largevolume presses(LVPs)1–3 and dynamic compression4,5 for studies under extreme high-pressure and ...The 2024 MRE HP Special Volume selects papers on new theoretical and experimental developments in the use of static largevolume presses(LVPs)1–3 and dynamic compression4,5 for studies under extreme high-pressure and high-temperature(HPHT)conditions.It also continues the previous year’s6 contemporary focus on superhydrides7–11 with extremely high superconducting temperatures Tc and addresses some controversial issues.12–14 In addition,it explores unconventional pressure-induced chemistry,particularly novel chemical stoichiometry and its impact on geochemistry and cosmochemistry in the deep interiors of Earth and other planets.18–21.展开更多
With the accelerating aging process of China’s population,the demand for community elderly care services has shown diversified and personalized characteristics.However,problems such as insufficient total care service...With the accelerating aging process of China’s population,the demand for community elderly care services has shown diversified and personalized characteristics.However,problems such as insufficient total care service resources,uneven distribution,and prominent supply-demand contradictions have seriously affected service quality.Big data technology,with core advantages including data collection,analysis and mining,and accurate prediction,provides a new solution for the allocation of community elderly care service resources.This paper systematically studies the application value of big data technology in the allocation of community elderly care service resources from three aspects:resource allocation efficiency,service accuracy,and management intelligence.Combined with practical needs,it proposes optimal allocation strategies such as building a big data analysis platform and accurately grasping the elderly’s care needs,striving to provide operable path references for the construction of community elderly care service systems,promoting the early realization of the elderly care service goal of“adequate support and proper care for the elderly”,and boosting the high-quality development of China’s elderly care service industry.展开更多
In recent years,Blockchain Technology has become a paradigm shift,providing Transparent,Secure,and Decentralized platforms for diverse applications,ranging from Cryptocurrency to supply chain management.Nevertheless,t...In recent years,Blockchain Technology has become a paradigm shift,providing Transparent,Secure,and Decentralized platforms for diverse applications,ranging from Cryptocurrency to supply chain management.Nevertheless,the optimization of blockchain networks remains a critical challenge due to persistent issues such as latency,scalability,and energy consumption.This study proposes an innovative approach to Blockchain network optimization,drawing inspiration from principles of biological evolution and natural selection through evolutionary algorithms.Specifically,we explore the application of genetic algorithms,particle swarm optimization,and related evolutionary techniques to enhance the performance of blockchain networks.The proposed methodologies aim to optimize consensus mechanisms,improve transaction throughput,and reduce resource consumption.Through extensive simulations and real-world experiments,our findings demonstrate significant improvements in network efficiency,scalability,and stability.This research offers a thorough analysis of existing optimization techniques,introduces novel strategies,and assesses their efficacy based on empirical outputs.展开更多
基金supported by the National Natural Science Foundation of China(72573020,72103022).
文摘This study analyzes the evolution of China's green technology innovation cooperation network from 2011 to 2020,utilizing green patent application data.Employing a Spatial Durbin Model(SDM),we scrutinized the network's influence on urban carbon emissions,utilizing panel data encompassing 323 city nodes.Results show network expansion and a shift in central nodes from eastern coastal areas to interior cities,with Beijing,Shenzhen,Nanjing,and Shanghai consistently acting as key innovation hubs.A core-periphery structure emerged,clustering cities into high-and low-cooperation clusters.Core cities,particularly Beijing,which gain informational advantages by bridging non-overlapping nodes and exhibit distinct characteristics in terms of the structural hole indexes,reflecting their multifaceted roles within the network.SDM analysis indicates that the green technology innovation cooperation network has a significant positive impact on urban carbon reduction efforts.Specifically,degree centrality,closeness centrality,effective size,efficiency,and hierarchy of node cities exhibit a negative correlation with carbon emissions,suggesting that higher centrality and efficiency within the network correlate with lower emissions.Conversely,betweenness centrality and constraint have a positive impact on emissions,indicating that cities that act as bridges in the network may paradoxically contribute to higher emissions.Moreover,the network's influence on carbon emissions is nuanced across different green technology sectors.Cooperation in areas such as waste management,alternative energy production,energy conservation,agriculture and forestry,and transportation is found to have a more substantial impact on carbon reduction than cooperation in nuclear power,and administrative,regulatory,and design fields.
文摘The convergence of optical and wireless technologies is driving the evolution of intelligent indoor networks,with Fiber-to-the-Room(FTTR)emerging as a key ar⁃chitecture for delivering gigabit connectivity in both home and enterprise environments.By deploying optical fiber directly to rooms and integrating it with advanced wireless so⁃lutions such as millimeter-wave and Wi-Fi 7,FTTR enables next-generation applications,including immersive Virtual Re⁃ality(VR)/Augmented Reality(AR)and industrial Internet of Things(IoT).Nevertheless,its large-scale deployment pres⁃ents challenges in network management,energy efficiency,in⁃terference mitigation,and intelligent root cause analysis.
基金the research result of the 2022 Municipal Education Commission Science and Technology Research Plan Project“Research on the Technology of Detecting Double-Surface Cracks in Concrete Lining of Highway Tunnels Based on Image Blast”(KJQN02202403)the first batch of school-level classroom teaching reform projects“Principles Applications of Embedded Systems”(23JG2166)the school-level reform research project“Continuous Results-Oriented Practice Research Based on BOPPPS Teaching Model-Taking the‘Programming Fundamentals’Course as an Example”(22JG332).
文摘With the rapid development of modern information technology,the Internet of Things(IoT)has been integrated into various fields such as social life,industrial production,education,and medical care.Through the connection of various physical devices,sensors,and machines,it realizes information intercommunication and remote control among devices,significantly enhancing the convenience and efficiency of work and life.However,the rapid development of the IoT has also brought serious security problems.IoT devices have limited resources and a complex network environment,making them one of the important targets of network intrusion attacks.Therefore,from the perspective of deep learning,this paper deeply analyzes the characteristics and key points of IoT intrusion detection,summarizes the application advantages of deep learning in IoT intrusion detection,and proposes application strategies of typical deep learning models in IoT intrusion detection so as to improve the security of the IoT architecture and guarantee people’s convenient lives.
基金Gansu Provincial Department of Education:Innovation Fund Project for College Teachers:Research on the Governance of Network Public Opinion Reversal Based on Blockchain Technology(NO.2025A-137)Teaching Reform Research at the School Level of Gansu University of Political Science and Law in 2024:Research and Implementation of CSCW Cloud Storage Collective Lesson Preparation System Based on Blockchain Technology(NO.GZJG2024-A04)+1 种基金2024 Gansu University of Political Science and Law“Three in One Education”Research:Project Research and Implementation of CSCW Network Teaching Platform Based on Web in the Direction of Network Education(NO.GZSQYR-37)2024 Lanzhou Philosophy and Social Sciences Planning Project:Research on Cloud Governance of Network Public Opinion for Major Public Events in Lanzhou City(NO.24-B45)。
文摘In recent years,the network public opinion reversal governance events have occurred frequently.Over time,the repeated truth of the matter will not only weaken the rational judgment of the public to a certain extent,so that its negative emotions accumulate,but also have a serious impact on the credibility of the media and the government,and may even further intensify social contradictions.Therefore,in the face of such a complex online public opinion space,accurately identifying the truth behind the incident and how to carry out the reversal of online public opinion governance is particularly critical.And blockchain technology,with its advantages of decentralization and immutable information,provides new technical support for the network public opinion reversal governance.Based on this,this paper gives an overview and analysis of blockchain technology and network public opinion reversal,and on this basis introduces the network public opinion reversal governance mechanism based on blockchain technology,aiming to further optimize the network public opinion reversal governance process,for reference only.
文摘The Internet of Things technology provides a comprehensive solution for the real-time monitoring of cold chain logistics by integrating sensors,wireless communication,cloud computing,and big data analysis.Based on this,this paper deeply explores the overview and characteristics of the Internet of Things technology,the feasibility analysis of the Internet of Things technology in the cold chain logistics monitoring,the application analysis of the Internet of Things technology in the cold chain logistics real-time monitoring to better improve the management level and operational efficiency of the cold chain logistics,to provide consumers with safer and fresh products.
文摘Objective:To study the effect of transcranial magnetic stimulation(TMS)on improving motor symptoms in patients with Parkinson’s disease(PD).Methods:60 PD patients who visited the hospital from September 2023 to August 2024 were selected as samples and randomly divided into two groups.Group A received conventional medication plus TMS treatment,while Group B received medication only.The efficacy of motor function improvement,neurological symptoms,mental state,sleep quality,quality of life,and adverse reactions was compared between the two groups.Results:The efficacy of Group A was higher than that of Group B(P<0.05).The scores of the Scales for Outcomes in Parkinson’s Disease-Autonomic(SCOPA-AUT),Mini-Mental State Examination(MMSE),and Pittsburgh Sleep Quality Index(PSQI)in Group A were lower than those in Group B(P<0.05).The quality of life scale(SF-36)score in Group A was higher than that in Group B(P<0.05).The adverse reaction rate in Group A was lower than that in Group B(P<0.05).Conclusion:TMS used in the treatment of PD patients can improve patients’mental state and motor function,optimize sleep quality and quality of life,and is safe and efficient.
基金financial support from the Shanghai Key Laboratory of MFree,China(Grant No.22dz2260800)the Shanghai Science and Technology Committee,China(Grant No.22JC1410300).
文摘The 2024 MRE HP Special Volume selects papers on new theoretical and experimental developments in the use of static largevolume presses(LVPs)1–3 and dynamic compression4,5 for studies under extreme high-pressure and high-temperature(HPHT)conditions.It also continues the previous year’s6 contemporary focus on superhydrides7–11 with extremely high superconducting temperatures Tc and addresses some controversial issues.12–14 In addition,it explores unconventional pressure-induced chemistry,particularly novel chemical stoichiometry and its impact on geochemistry and cosmochemistry in the deep interiors of Earth and other planets.18–21.
文摘With the accelerating aging process of China’s population,the demand for community elderly care services has shown diversified and personalized characteristics.However,problems such as insufficient total care service resources,uneven distribution,and prominent supply-demand contradictions have seriously affected service quality.Big data technology,with core advantages including data collection,analysis and mining,and accurate prediction,provides a new solution for the allocation of community elderly care service resources.This paper systematically studies the application value of big data technology in the allocation of community elderly care service resources from three aspects:resource allocation efficiency,service accuracy,and management intelligence.Combined with practical needs,it proposes optimal allocation strategies such as building a big data analysis platform and accurately grasping the elderly’s care needs,striving to provide operable path references for the construction of community elderly care service systems,promoting the early realization of the elderly care service goal of“adequate support and proper care for the elderly”,and boosting the high-quality development of China’s elderly care service industry.
文摘In recent years,Blockchain Technology has become a paradigm shift,providing Transparent,Secure,and Decentralized platforms for diverse applications,ranging from Cryptocurrency to supply chain management.Nevertheless,the optimization of blockchain networks remains a critical challenge due to persistent issues such as latency,scalability,and energy consumption.This study proposes an innovative approach to Blockchain network optimization,drawing inspiration from principles of biological evolution and natural selection through evolutionary algorithms.Specifically,we explore the application of genetic algorithms,particle swarm optimization,and related evolutionary techniques to enhance the performance of blockchain networks.The proposed methodologies aim to optimize consensus mechanisms,improve transaction throughput,and reduce resource consumption.Through extensive simulations and real-world experiments,our findings demonstrate significant improvements in network efficiency,scalability,and stability.This research offers a thorough analysis of existing optimization techniques,introduces novel strategies,and assesses their efficacy based on empirical outputs.
