Achieving room-temperature superconductivity has been an enduring scientific quest,while hydrogen-rich compounds have emerged as highly promising candidates.Here,we systematically investigated the thermodynamic stabil...Achieving room-temperature superconductivity has been an enduring scientific quest,while hydrogen-rich compounds have emerged as highly promising candidates.Here,we systematically investigated the thermodynamic stability,crystal structure,electronic properties,and superconductivity within the ternary Y-Hf-H system under high pressure.Several distinct hydrides have been revealed,in which the hydrogen atoms are present in various hydrogenic motifs.A15-type hydride P_(m)3-YHfH_(6)with isolated H−is predicted to be dynamically stabilized down to 10GPa.The H atoms form pentagonal graphene-like layered-H10 anions in the Hf plane of P6-YHfH_(19),with aT_(c)of 95K at 100GPa.There are H cages in C_(mmm)-Y_(3)HfH_(24),and attributed to the robust electron–phonon coupling and high electronic density of states of hydrogen at the Fermi level,it demonstrates near-room temperature superconductivity with a T_(c)of 275K at 250GPa.Our work makes contributions to the understanding of the fundamental properties of ternary hydrides under high pressure and provides essential references for further research in this field.展开更多
Objective Asymptomatic carotid stenosis(ACS)is closely associated to the incidence of severe cerebrovascular diseases.Early identifying the individuals with ACS and its associated risk factors could be beneficial for ...Objective Asymptomatic carotid stenosis(ACS)is closely associated to the incidence of severe cerebrovascular diseases.Early identifying the individuals with ACS and its associated risk factors could be beneficial for primary prevention of stroke.This study aimed to investigate a machine-learning algorithm for the detection of ACS among high-risk population of stroke based on the associated risk factors.Methods A novel model of machine learning was utilized to screen the associated predictors of ACS based on 30 potential risk factors.The algorithm of this model adopted a random forest pattern based on the training data and then was verified using the testing data.All of the original data were retrieved from the China National Stroke Screening and Prevention Project(CNSSPP),including demographic,clinical and laboratory characteristics.The individuals with high risk of stroke were enrolled and randomly divided into a training group and a testing group at a ratio of 4:1.The identification of carotid stenosis by carotid artery duplex scans was set as the golden standard.The receiver operating characteristic(ROC)curve and the area under the curve(AUC)was used to evaluate the efficacy of the model in detecting ACS.Results Of 2841 high risk individual of stroke enrolled,326(11.6%)were diagnosed as ACS by ultrasonography.The top five risk fectors contributing to ACS in this model were identified as family history of dyslipidemia,high level of lowdensity lipoprotein cholesterol(LDL-c),low level of high-density lipoprotein cholesterol(HDL-c),aging,and low body.展开更多
Radar Maneuvering Targets Tracking(RMTT) in clutter is a quite challenging issue due to the errors in the models and the varying dynamics of the processes. Modern radar tracking system calls for the adaptive signal an...Radar Maneuvering Targets Tracking(RMTT) in clutter is a quite challenging issue due to the errors in the models and the varying dynamics of the processes. Modern radar tracking system calls for the adaptive signal and data processing algorithm urgently to adapt the uncertainty of the environment. The mechanism of human cognition can help persons cope with the similar diffi-culties in visual tracking. Inspired by human cognition mechanism, a comprehensive method for RMTT is proposed. In the method, the model transition probability in Interacting Multiple Model(IMM) and the validation gate can be adjusted dynamically with target maneuver;the waveform in radar transmitter can vary with the perception of the environment. Experimental results in cluttered scenes show that the proposed algorithm is more accurate for perceiving the environment and targets, and the waveform selection algorithm is better than that with fixed waveform.展开更多
Memantine is a N-methyl-D-aspartate (NMDA) receptor antagonist approved for the treatment of moderate to severe Alzheimer's disease (AD). Environmental enrichment (EE) has shown significant beneficial effects on f...Memantine is a N-methyl-D-aspartate (NMDA) receptor antagonist approved for the treatment of moderate to severe Alzheimer's disease (AD). Environmental enrichment (EE) has shown significant beneficial effects on func- tional improvement in AD. In this study, we sought to determine whether combining these two distinct therapies would yield greater benefit than either drug used alone. We investigated the effect of memantine combined with EE on spatial learning and memory and AD-like pathology in a widely used AD model, the senescence-accelerated prone mice (SAMP8). The SAMP8 mice were randomly assigned to enriched housing (EH) or standard housing (SH), where either memantine (20 mg/kg) or saline was given by gastric lavage once daily continuously for eight weeks. Our results showed that, when provided separately, memantine and EE significantly improved spatial learning and memory by shortening escape latencies and increasing the frequency of entrance into the target quadrant. When combined, memantine and EE showed additive effect on learning and memory as evidenced by significant shorter escape latencies and higher frequency of target entrance than either drug alone. Consistent with the behavior results, pathological studies showed that both memantine and EE significantly reduced hippocampal CA1 neurofibrilliary tangles (NFTs) as well as amyloid beta precursor protein (APP) levels. Combining both therapies synergistically lessened NFTs and APP expression compared to either drug alone in SAMP8 mice, indicating that the combination of memantine with EE could offer a novel and efficient therapeutic strategy for the treatment of AD.展开更多
Pressure has an important effect on chemical bonds and their chemical properties. The atypical compounds NaCl_(3) and CsF_(3) are predicted to be stable at high pressure and show unique physical and chemical propertie...Pressure has an important effect on chemical bonds and their chemical properties. The atypical compounds NaCl_(3) and CsF_(3) are predicted to be stable at high pressure and show unique physical and chemical properties. By using ab initio random structure searching and density functional theory calculations, we predicted multiple thermodynamically stable atypical compounds, which are RbF_(2), RbF_(3), RbF_(4), and RbF_(5) in the pressure range of 0–300 GPa. In these stable compounds, homonuclear bondings of F_(3), F_(4), and F_(5) species are easily formed. The electron structure calculation showed that except for Fd-3 m phase of RbF_(2), these stable compounds are insulators and F 5 p orbitals play an important role in the Fermi level. It is interesting that the compounds RbF_(5) could be stable at nearly ambient pressure and 0 K which will stimulate experimental studies in the future.展开更多
Room temperature superconductivity is a dream that mankind has been chasing for a century.In recent years,the synthesis of H3S,LaH10,and C-S-H compounds under high pressures has gradually made that dream become a real...Room temperature superconductivity is a dream that mankind has been chasing for a century.In recent years,the synthesis of H3S,LaH10,and C-S-H compounds under high pressures has gradually made that dream become a reality.But the extreme high pressure required for stabilization of hydrogen-based superconductors limit their applications.So,the next challenge is to achieve room-temperature superconductivity at significantly low pressures,even ambient pressure.In this work,we design a series of high temperature superconductors that can be stable at moderate pressures by incorporating heavy rare earth elements Yb/Lu into sodalite-like clathrate hexahydrides.In particular,the critical temperatures(T_(c))of Y_(3)LuH_(24),YLuH_(12),and YLu_(3)H_(24)can reach 283 K at 120 GPa,275 K at 140 GPa,and 288 K at 110 GPa,respectively.Their critical temperatures are close to or have reached room temperature,and minimum stable pressures are significantly lower than that of reported room temperature superconductors.Our work provides an effective method for the rational design of low-pressure stabilized hydrogen-based superconductors with room-temperature superconductivity simultaneously and will stimulate further experimental exploration.展开更多
The theoretical predictions and experimental synthesis of H_(3)S and LaH_(10) superconductors with record high superconducting transition temperatures(T_(c))have promoted the hydrogen-based superconducors to be a rese...The theoretical predictions and experimental synthesis of H_(3)S and LaH_(10) superconductors with record high superconducting transition temperatures(T_(c))have promoted the hydrogen-based superconducors to be a research hotspot in the field of solid-state physics.Here,we predict an unprecedented layered structure CaH15,with high T_(c) of 189 K at 200 GPa using ab initio calculations.As concerns the novel structure,one layer is made of a hydrogen nonagon,the other layer consists of a Ca atom and six H_(2) molecular units surrounding the Ca atom.This layered structure was also found in SrH_(15),YH_(15),and LaH_(15) at high pressures,each materials exhibit high T_(c) especially YH_(15) can reach above 200 K at 220 GPa.It represents the second class of layered superhydrides with high value of Tc after pentagraphene like HfH10.展开更多
The advent of antibiotics revolutionized the management of bacterial infections,yet their clinical efficacy is catastrophically undermined by the global emergence of antimicrobial resistance(AMR).Furthermore,the situa...The advent of antibiotics revolutionized the management of bacterial infections,yet their clinical efficacy is catastrophically undermined by the global emergence of antimicrobial resistance(AMR).Furthermore,the situation is aggravated by the fact that the formation of bacterial biofilm on material surfaces significantly enhances their tolerance to antibiotics.Therefore,there is an urgent need for new approaches that employ antibacterial mechanisms distinct from those of conventional antibiotics to mitigate the risk of AMR.Recently,naturally occurring surfaces found on typical plants and insects that take advantage of physical topography can either inhibit bacterial adhesion or directly inactivate bacterial cells,showing innovative“outside-the-box”prospects for antibacterial applications and garnering considerable interest due to their drug-free nature.Bioinspired micro-/nanostructures that mimic natural surface patterns have been replicated on various biomaterials to enhance their antibacterial properties.This review summarizes and explains the current advances in bioinspired antibacterial surfaces,as well as the underlying mechanisms of various strategies.Subsequently,synergistic antimicrobial surfaces,comprising a combination of various physical antibacterial strategies,are reviewed to highlight their potential for highly efficient disinfection and long-lasting antibacterial performance.Finally,the biomedical applications,coupled with the future challenges of bio-inspired antibacterial strategies,were further discussed.We hope this review could provide valuable insights for developing innovative,antibiotic-free antibacterial strategies that deliver powerful performance in combating AMR.展开更多
Managing massive electric power data is a typical big data application because electric power systems generate millions or billions of status,debugging,and error records every single day.To guarantee the safety and su...Managing massive electric power data is a typical big data application because electric power systems generate millions or billions of status,debugging,and error records every single day.To guarantee the safety and sustainability of electric power systems,massive electric power data need to be processed and analyzed quickly to make real-time decisions.Traditional solutions typically use relational databases to manage electric power data.However,relational databases cannot efficiently process and analyze massive electric power data when the data size increases significantly.In this paper,we show how electric power data can be managed by using HBase,a distributed database maintained by Apache.Our system consists of clients,HBase database,status monitors,data migration modules,and data fragmentation modules.We evaluate the performance of our system through a series of experiments.We also show how HBase’s parameters can be tuned to improve the efficiency of our system.展开更多
基金supported by the National Natural Science Foundation of China(Grant Nos.52072188,12122405,and 12274169)Program for Science and Technology Innovation Team in Zhejiang Province,China(Grant No.2021R01004)+2 种基金Natural Science Foundation of Zhejiang Province,China(Grant No.LQ24A040001)the Natural Science Foundation of Ningbo City,China(Grant No.2024J200)the Fundamental Research Funds for the Provincial Universities of Zhejiang(Grant No.SJLY2023003)。
文摘Achieving room-temperature superconductivity has been an enduring scientific quest,while hydrogen-rich compounds have emerged as highly promising candidates.Here,we systematically investigated the thermodynamic stability,crystal structure,electronic properties,and superconductivity within the ternary Y-Hf-H system under high pressure.Several distinct hydrides have been revealed,in which the hydrogen atoms are present in various hydrogenic motifs.A15-type hydride P_(m)3-YHfH_(6)with isolated H−is predicted to be dynamically stabilized down to 10GPa.The H atoms form pentagonal graphene-like layered-H10 anions in the Hf plane of P6-YHfH_(19),with aT_(c)of 95K at 100GPa.There are H cages in C_(mmm)-Y_(3)HfH_(24),and attributed to the robust electron–phonon coupling and high electronic density of states of hydrogen at the Fermi level,it demonstrates near-room temperature superconductivity with a T_(c)of 275K at 250GPa.Our work makes contributions to the understanding of the fundamental properties of ternary hydrides under high pressure and provides essential references for further research in this field.
基金Fund supported by the Medical Science and Tech no logy Development Foundatio n(YKK18114)the Gen era I Social Development Medical and Health Project of Nanjing Science and Technology Commission(201803029).
文摘Objective Asymptomatic carotid stenosis(ACS)is closely associated to the incidence of severe cerebrovascular diseases.Early identifying the individuals with ACS and its associated risk factors could be beneficial for primary prevention of stroke.This study aimed to investigate a machine-learning algorithm for the detection of ACS among high-risk population of stroke based on the associated risk factors.Methods A novel model of machine learning was utilized to screen the associated predictors of ACS based on 30 potential risk factors.The algorithm of this model adopted a random forest pattern based on the training data and then was verified using the testing data.All of the original data were retrieved from the China National Stroke Screening and Prevention Project(CNSSPP),including demographic,clinical and laboratory characteristics.The individuals with high risk of stroke were enrolled and randomly divided into a training group and a testing group at a ratio of 4:1.The identification of carotid stenosis by carotid artery duplex scans was set as the golden standard.The receiver operating characteristic(ROC)curve and the area under the curve(AUC)was used to evaluate the efficacy of the model in detecting ACS.Results Of 2841 high risk individual of stroke enrolled,326(11.6%)were diagnosed as ACS by ultrasonography.The top five risk fectors contributing to ACS in this model were identified as family history of dyslipidemia,high level of lowdensity lipoprotein cholesterol(LDL-c),low level of high-density lipoprotein cholesterol(HDL-c),aging,and low body.
基金co-supported by the National Natural Science Foundation of China(No.61671453)the Anhui Province Natural Science Fund Project,China(No.1608085MF123)
文摘Radar Maneuvering Targets Tracking(RMTT) in clutter is a quite challenging issue due to the errors in the models and the varying dynamics of the processes. Modern radar tracking system calls for the adaptive signal and data processing algorithm urgently to adapt the uncertainty of the environment. The mechanism of human cognition can help persons cope with the similar diffi-culties in visual tracking. Inspired by human cognition mechanism, a comprehensive method for RMTT is proposed. In the method, the model transition probability in Interacting Multiple Model(IMM) and the validation gate can be adjusted dynamically with target maneuver;the waveform in radar transmitter can vary with the perception of the environment. Experimental results in cluttered scenes show that the proposed algorithm is more accurate for perceiving the environment and targets, and the waveform selection algorithm is better than that with fixed waveform.
基金supported by a grant from the Natural Sciences Foundation of Jiangsu Province (No. BK2008081)the Scientific Research Fund of Nanjing Medical University (No. 2010NJMU244)
文摘Memantine is a N-methyl-D-aspartate (NMDA) receptor antagonist approved for the treatment of moderate to severe Alzheimer's disease (AD). Environmental enrichment (EE) has shown significant beneficial effects on func- tional improvement in AD. In this study, we sought to determine whether combining these two distinct therapies would yield greater benefit than either drug used alone. We investigated the effect of memantine combined with EE on spatial learning and memory and AD-like pathology in a widely used AD model, the senescence-accelerated prone mice (SAMP8). The SAMP8 mice were randomly assigned to enriched housing (EH) or standard housing (SH), where either memantine (20 mg/kg) or saline was given by gastric lavage once daily continuously for eight weeks. Our results showed that, when provided separately, memantine and EE significantly improved spatial learning and memory by shortening escape latencies and increasing the frequency of entrance into the target quadrant. When combined, memantine and EE showed additive effect on learning and memory as evidenced by significant shorter escape latencies and higher frequency of target entrance than either drug alone. Consistent with the behavior results, pathological studies showed that both memantine and EE significantly reduced hippocampal CA1 neurofibrilliary tangles (NFTs) as well as amyloid beta precursor protein (APP) levels. Combining both therapies synergistically lessened NFTs and APP expression compared to either drug alone in SAMP8 mice, indicating that the combination of memantine with EE could offer a novel and efficient therapeutic strategy for the treatment of AD.
基金supported by the National Natural Science Foundation of China (Grant No. 11674122)。
文摘Pressure has an important effect on chemical bonds and their chemical properties. The atypical compounds NaCl_(3) and CsF_(3) are predicted to be stable at high pressure and show unique physical and chemical properties. By using ab initio random structure searching and density functional theory calculations, we predicted multiple thermodynamically stable atypical compounds, which are RbF_(2), RbF_(3), RbF_(4), and RbF_(5) in the pressure range of 0–300 GPa. In these stable compounds, homonuclear bondings of F_(3), F_(4), and F_(5) species are easily formed. The electron structure calculation showed that except for Fd-3 m phase of RbF_(2), these stable compounds are insulators and F 5 p orbitals play an important role in the Fermi level. It is interesting that the compounds RbF_(5) could be stable at nearly ambient pressure and 0 K which will stimulate experimental studies in the future.
基金This work was supported by National Natural Science Foundation of China(grant nos.12122405,52072188,and 51632002)National Key R&D Program of China(no.2018YFA0305900)+1 种基金Program for Changjiang Scholars and Innovative Research Team in University(no.IRT_15R23)Jilin Provincial Science and Technology Development Project(20210509038RQ).
文摘Room temperature superconductivity is a dream that mankind has been chasing for a century.In recent years,the synthesis of H3S,LaH10,and C-S-H compounds under high pressures has gradually made that dream become a reality.But the extreme high pressure required for stabilization of hydrogen-based superconductors limit their applications.So,the next challenge is to achieve room-temperature superconductivity at significantly low pressures,even ambient pressure.In this work,we design a series of high temperature superconductors that can be stable at moderate pressures by incorporating heavy rare earth elements Yb/Lu into sodalite-like clathrate hexahydrides.In particular,the critical temperatures(T_(c))of Y_(3)LuH_(24),YLuH_(12),and YLu_(3)H_(24)can reach 283 K at 120 GPa,275 K at 140 GPa,and 288 K at 110 GPa,respectively.Their critical temperatures are close to or have reached room temperature,and minimum stable pressures are significantly lower than that of reported room temperature superconductors.Our work provides an effective method for the rational design of low-pressure stabilized hydrogen-based superconductors with room-temperature superconductivity simultaneously and will stimulate further experimental exploration.
基金supported by the National Natural Science Foundation of China(Grant Nos.12122405,52072188,and 51632002)the National Key R&D Program of China(Grant No.2018YFA0305900)the Jilin Provincial Science and Technology Development Project(20210509038RQ)。
文摘The theoretical predictions and experimental synthesis of H_(3)S and LaH_(10) superconductors with record high superconducting transition temperatures(T_(c))have promoted the hydrogen-based superconducors to be a research hotspot in the field of solid-state physics.Here,we predict an unprecedented layered structure CaH15,with high T_(c) of 189 K at 200 GPa using ab initio calculations.As concerns the novel structure,one layer is made of a hydrogen nonagon,the other layer consists of a Ca atom and six H_(2) molecular units surrounding the Ca atom.This layered structure was also found in SrH_(15),YH_(15),and LaH_(15) at high pressures,each materials exhibit high T_(c) especially YH_(15) can reach above 200 K at 220 GPa.It represents the second class of layered superhydrides with high value of Tc after pentagraphene like HfH10.
基金financial support through the National Science Foundation of China(No.52305317)the research collaboration project between the National Natural Science Foundation of China and the National Research Foundation of Korea(No.W2412095)+1 种基金Natural Science Foundation of Shandong Province(No.ZR2022QB040,ZR2022QH006,ZR20230B113)the Youth Innovation Team of Shandong Province(2024KJH045).
文摘The advent of antibiotics revolutionized the management of bacterial infections,yet their clinical efficacy is catastrophically undermined by the global emergence of antimicrobial resistance(AMR).Furthermore,the situation is aggravated by the fact that the formation of bacterial biofilm on material surfaces significantly enhances their tolerance to antibiotics.Therefore,there is an urgent need for new approaches that employ antibacterial mechanisms distinct from those of conventional antibiotics to mitigate the risk of AMR.Recently,naturally occurring surfaces found on typical plants and insects that take advantage of physical topography can either inhibit bacterial adhesion or directly inactivate bacterial cells,showing innovative“outside-the-box”prospects for antibacterial applications and garnering considerable interest due to their drug-free nature.Bioinspired micro-/nanostructures that mimic natural surface patterns have been replicated on various biomaterials to enhance their antibacterial properties.This review summarizes and explains the current advances in bioinspired antibacterial surfaces,as well as the underlying mechanisms of various strategies.Subsequently,synergistic antimicrobial surfaces,comprising a combination of various physical antibacterial strategies,are reviewed to highlight their potential for highly efficient disinfection and long-lasting antibacterial performance.Finally,the biomedical applications,coupled with the future challenges of bio-inspired antibacterial strategies,were further discussed.We hope this review could provide valuable insights for developing innovative,antibiotic-free antibacterial strategies that deliver powerful performance in combating AMR.
基金supported by the National Key R&D Program of China(No.2017YFB1003000)the National Natural Science Foundation of China(Nos.61702096,61572129,61602112,61502097,61320106007,61632008,and 61702097)+5 种基金the International S&T Cooperation Program of China(No.2015DFA10490)the Natural Science Foundation of Jiangsu Province(Nos.BK20170689 and BK20160695)the Jiangsu Provincial Key Laboratory of Network and Information Security(No.BM2003201)the Key Laboratory of Computer Network and Information Integration of Ministry of Education of China(No.93K-9)the SGCC Science and Technology Program“the Distributed Data Management of Physical Distribution and Logical Integration”partially supported by the Collaborative Innovation Center of Novel Software Technology and Industrialization and Collaborative Innovation Center of Wireless Communications Technology.
文摘Managing massive electric power data is a typical big data application because electric power systems generate millions or billions of status,debugging,and error records every single day.To guarantee the safety and sustainability of electric power systems,massive electric power data need to be processed and analyzed quickly to make real-time decisions.Traditional solutions typically use relational databases to manage electric power data.However,relational databases cannot efficiently process and analyze massive electric power data when the data size increases significantly.In this paper,we show how electric power data can be managed by using HBase,a distributed database maintained by Apache.Our system consists of clients,HBase database,status monitors,data migration modules,and data fragmentation modules.We evaluate the performance of our system through a series of experiments.We also show how HBase’s parameters can be tuned to improve the efficiency of our system.
