Ecological monitoring vehicles are equipped with a range of sensors and monitoring devices designed to gather data on ecological and environmental factors.These vehicles are crucial in various fields,including environ...Ecological monitoring vehicles are equipped with a range of sensors and monitoring devices designed to gather data on ecological and environmental factors.These vehicles are crucial in various fields,including environmental science research,ecological and environmental monitoring projects,disaster response,and emergency management.A key method employed in these vehicles for achieving high-precision positioning is LiDAR(lightlaser detection and ranging)-Visual Simultaneous Localization and Mapping(SLAM).However,maintaining highprecision localization in complex scenarios,such as degraded environments or when dynamic objects are present,remains a significant challenge.To address this issue,we integrate both semantic and texture information from LiDAR and cameras to enhance the robustness and efficiency of data registration.Specifically,semantic information simplifies the modeling of scene elements,reducing the reliance on dense point clouds,which can be less efficient.Meanwhile,visual texture information complements LiDAR-Visual localization by providing additional contextual details.By incorporating semantic and texture details frompaired images and point clouds,we significantly improve the quality of data association,thereby increasing the success rate of localization.This approach not only enhances the operational capabilities of ecological monitoring vehicles in complex environments but also contributes to improving the overall efficiency and effectiveness of ecological monitoring and environmental protection efforts.展开更多
Predicting the health status of stroke patients at different stages of the disease is a critical clinical task.The onset and development of stroke are affected by an array of factors,encompassing genetic predispositio...Predicting the health status of stroke patients at different stages of the disease is a critical clinical task.The onset and development of stroke are affected by an array of factors,encompassing genetic predisposition,environmental exposure,unhealthy lifestyle habits,and existing medical conditions.Although existing machine learning-based methods for predicting stroke patients’health status have made significant progress,limitations remain in terms of prediction accuracy,model explainability,and system optimization.This paper proposes a multi-task learning approach based on Explainable Artificial Intelligence(XAI)for predicting the health status of stroke patients.First,we design a comprehensive multi-task learning framework that utilizes the task correlation of predicting various health status indicators in patients,enabling the parallel prediction of multiple health indicators.Second,we develop a multi-task Area Under Curve(AUC)optimization algorithm based on adaptive low-rank representation,which removes irrelevant information from the model structure to enhance the performance of multi-task AUC optimization.Additionally,the model’s explainability is analyzed through the stability analysis of SHAP values.Experimental results demonstrate that our approach outperforms comparison algorithms in key prognostic metrics F1 score and Efficiency.展开更多
Variation in weather conditions during grain filling has substantial effects on maize kernel weight(KW). The objective of this work was to characterize variation in KW with sowing date-associated weather conditions an...Variation in weather conditions during grain filling has substantial effects on maize kernel weight(KW). The objective of this work was to characterize variation in KW with sowing date-associated weather conditions and examine the relationship between KW, grain filling parameters, and weather factors. Maize was sown on eight sowing dates(SD) at 15–20-day intervals from mid-March to mid-July during 2012 and 2013 in the North China Plain. With sowing date delay, KW increased initially and later declined, and the greatest KW was obtained at SD6 in both years. The increased KW at SD6 was attributed mainly to kernel growth rate(Gmean), and effective grain-filling period(P). Variations in temperature and radiation were the primary factors that influenced KW and grain-filling parameters. When the effective cumulative temperature(AT) and radiation(Ra)during grain filling were 950 °C and 1005.4 MJ m-2, respectively, P and KW were greatest. High temperatures(daily maximum temperature [Tmax] > 30.2 °C) during grain filling under early sowing conditions, or low temperatures(daily minimum temperature [Tmin] < 20.7 °C) under late sowing conditions combined with high diurnal temperature range(Tmax-min> 7.1 °C) decreased kernel growth rate and ultimately final KW. When sowing was performed from May 25 through June 27, higher KW and yield of maize were obtained. We conclude that variations in environmental conditions(temperature and radiation) during grain filling markedly affect growth rate and duration of grain filling and eventually affect kernel weight and yield of maize.展开更多
Previous weighted frequent pattern （WFP） mining algorithms are not suitable for data streams for they need multiple database scans. In this paper, we present an efficient algorithm SWFP-Miner to mine weighted freque...Previous weighted frequent pattern （WFP） mining algorithms are not suitable for data streams for they need multiple database scans. In this paper, we present an efficient algorithm SWFP-Miner to mine weighted frequent pattern over data streams. SWFP-Miner is based on sliding window and can discover important frequent pattern from the recent data. A new refined weight definition is proposed to keep the downward closure property, and two pruning strategies are presented to prune the weighted infrequent pattern. Experimental studies are performed to evaluate the effectiveness and efficiency of SWFP-Miner.展开更多
Secretion systems, macromolecules to pass which can mediate the across cellular membranes, are essential for virulent and genetic material exchange among bacterial species[1]. Type IV secretion system （T4SS） is one ...Secretion systems, macromolecules to pass which can mediate the across cellular membranes, are essential for virulent and genetic material exchange among bacterial species[1]. Type IV secretion system （T4SS） is one of the secretion systems and it usually consists of 12 genes： VirB1, VirB2 ...VirB11, and VirD4[2]. The structure and molecular mechanisms of these genes have been well analyzed in Gram-negative strains[3] and Gram-positive strains were once believed to be lack of T4SS. However, some recent studies revealed that one or more virB/D genes also exist in some kinds of Gram-positive bacteria and play similar role, and form a T4SS-like system[3]. The VirBl-like, VirB4, VirB6, and VirD4 genes were identified in the chromosome of Gram-positive bacterium Streptococcus suis in our previous studies and their role as important mobile elements for horizontal transfer to recipients in an 89 K pathogenicity island （PAl） was demonstrated[45]. However, their structure and molecular mechanisms in other strains, especially in Gram-positive strains, are remained unclear.展开更多
In recent years, with the development of the enhanced oil recovery technique, researchers understood that the foam generation in the underground oil-bearing porous medium can successfully improve oil recovery. One of ...In recent years, with the development of the enhanced oil recovery technique, researchers understood that the foam generation in the underground oil-bearing porous medium can successfully improve oil recovery. One of the important mechanisms of foam generation is the snap-off of gas bubbles in porous media.展开更多
The emerging two-dimensional(2D)materials,MXenes,play an important role in various fields of energy storage and exhibit excellent electrochemical performance.Herein,we prepared few-layered MXenes(F-Ti_(3)C_(2)T_(x))an...The emerging two-dimensional(2D)materials,MXenes,play an important role in various fields of energy storage and exhibit excellent electrochemical performance.Herein,we prepared few-layered MXenes(F-Ti_(3)C_(2)T_(x))and loaded Te on the surface of F-Ti_(3)C_(2)T_(x) by using a simple hightemperature evaporation method.In addition,the electrochemical performance of the aluminum battery with F-Ti_(3)C_(2)T_(x) as support material was studied.The initial charge/discharge specific capacities are 987/1096mAh g^(-1)at 0.2Ag^(-1).An obvious discharge voltage plateau of about 1.3V appears at various current densities.The specific capacity is about 258mAh g^(-1)with MXenes@Te as the active material in the aluminum battery,which benefits from the excellent electronic conductivity of the MXenes and their 2D layered structure.Density functional theory calculations were carried out to explore the mechanism.Ti_(3)C_(2)O_(2)@Te is more inclined to adsorb[AlCl_(4)]^(-) than Ti_(3)C_(2)O_(2).Furthermore,the valence change behavior of element Te was studied by using thermodynamic calculation(FactSage 7.1).X-ray photoelectron spectroscopy results show that when the battery is fully charged to 2.4V element Te and Ti ions(Ti^(3+),Ti^(2+))are oxidized to Te^(4+)and Ti^(4+).In contrast to the charging process,the high-valence Te^(4+)and Ti^(4+)are reduced again during discharging.Element Te is reduced to lower-valence Te^(2-)when the discharge voltage is lower than 0.6 V,and a higher charge voltage(2.56 V)is required for Te to be oxidized to Te^(6+).展开更多
Ebola virus (EBOV), a member of the filovirus family, is an enveloped negative-sense RNA virus that causes lethal infections in humans and primates. Thousands of people have died from the Ebola virus disease (EVD) in ...Ebola virus (EBOV), a member of the filovirus family, is an enveloped negative-sense RNA virus that causes lethal infections in humans and primates. Thousands of people have died from the Ebola virus disease (EVD) in West Africa, and no specific antiviral medication and treatment have been approved for EVD. Although the development of an EBOV vaccine is promising, immunity to any vaccine is not immediate. Here, we computationally analysed the structure of EBOV glycoprotein GP2 (GP2EBOV) and designed RNA aptamers that recognize and inhibit it. The aptamers specifically bind to conserved arginine residues (Arg587 and Arg596) located in the C-terminal coiled-coil region of GP2EBOV. Molecular docking of the synthetic RNA aptamers with the ectodomain of GP2EBOV revealed that the optimized orthogonal RNA aptamers have strong binding affinities with the coiled-coil region of GP2EBOV. The characterized RNA aptamers may facilitate strategies to block replication of EBOV and related Filoviruses, and thus may serve as important antivirals to reduce mortality associated with these infections.展开更多
Characteristic set method of polynomial equation solving has been widely spread and its implementation in software has been urged to consider in recent years. Several packages for the method are implemented in some co...Characteristic set method of polynomial equation solving has been widely spread and its implementation in software has been urged to consider in recent years. Several packages for the method are implemented in some computer algebra systems, such as REDUCE and Maple. In order to improve the efficiency of the method, we have developed a computer algebra system ″ELIMINO″ written in C language and implemented on Linux operation system on a PC. The authors wish to share with the reader the knowledge and experiences about the design and development of software package of the characteristic set method.展开更多
Objective To design amplicons-based target sequencing panels using high-throughput next generation sequencing (NGS) and multiplex PCR techniques to sequence type 2 diabetes susceptibility genes and to assess their rel...Objective To design amplicons-based target sequencing panels using high-throughput next generation sequencing (NGS) and multiplex PCR techniques to sequence type 2 diabetes susceptibility genes and to assess their relationship with clinical characteristics in patients with type 2 diabetes.展开更多
Dear Editor,A disulfide bond that formed between the thiol groups of two spatially close cysteine residues is essential for protein folding, stability, and function (Creighton et al., 1995) (Fass, 2012). Driven by con...Dear Editor,A disulfide bond that formed between the thiol groups of two spatially close cysteine residues is essential for protein folding, stability, and function (Creighton et al., 1995) (Fass, 2012). Driven by conformational entropy, native disulfide bonds stabilize the conformation of protein molecules (Dill, 1990), while removal of native disulfides usually causes reduced stability of the target protein (Liu and Cowburn, 2016).展开更多
基金supported by the project“GEF9874:Strengthening Coordinated Approaches to Reduce Invasive Alien Species(lAS)Threats to Globally Significant Agrobiodiversity and Agroecosystems in China”funding from the Excellent Talent Training Funding Project in Dongcheng District,Beijing,with project number 2024-dchrcpyzz-9.
文摘Ecological monitoring vehicles are equipped with a range of sensors and monitoring devices designed to gather data on ecological and environmental factors.These vehicles are crucial in various fields,including environmental science research,ecological and environmental monitoring projects,disaster response,and emergency management.A key method employed in these vehicles for achieving high-precision positioning is LiDAR(lightlaser detection and ranging)-Visual Simultaneous Localization and Mapping(SLAM).However,maintaining highprecision localization in complex scenarios,such as degraded environments or when dynamic objects are present,remains a significant challenge.To address this issue,we integrate both semantic and texture information from LiDAR and cameras to enhance the robustness and efficiency of data registration.Specifically,semantic information simplifies the modeling of scene elements,reducing the reliance on dense point clouds,which can be less efficient.Meanwhile,visual texture information complements LiDAR-Visual localization by providing additional contextual details.By incorporating semantic and texture details frompaired images and point clouds,we significantly improve the quality of data association,thereby increasing the success rate of localization.This approach not only enhances the operational capabilities of ecological monitoring vehicles in complex environments but also contributes to improving the overall efficiency and effectiveness of ecological monitoring and environmental protection efforts.
基金funded by the Excellent Talent Training Funding Project in Dongcheng District,Beijing,with project number 2024-dchrcpyzz-9.
文摘Predicting the health status of stroke patients at different stages of the disease is a critical clinical task.The onset and development of stroke are affected by an array of factors,encompassing genetic predisposition,environmental exposure,unhealthy lifestyle habits,and existing medical conditions.Although existing machine learning-based methods for predicting stroke patients’health status have made significant progress,limitations remain in terms of prediction accuracy,model explainability,and system optimization.This paper proposes a multi-task learning approach based on Explainable Artificial Intelligence(XAI)for predicting the health status of stroke patients.First,we design a comprehensive multi-task learning framework that utilizes the task correlation of predicting various health status indicators in patients,enabling the parallel prediction of multiple health indicators.Second,we develop a multi-task Area Under Curve(AUC)optimization algorithm based on adaptive low-rank representation,which removes irrelevant information from the model structure to enhance the performance of multi-task AUC optimization.Additionally,the model’s explainability is analyzed through the stability analysis of SHAP values.Experimental results demonstrate that our approach outperforms comparison algorithms in key prognostic metrics F1 score and Efficiency.
基金supported by the Special Fund for Agro-scientific Research in the Public Interest(No.201203096)the National Key Technology R&D Program of China(Nos.2013BAD07B00 and 2013BAD08B00)the China Agriculture Research System(No.CARS-02)
文摘Variation in weather conditions during grain filling has substantial effects on maize kernel weight(KW). The objective of this work was to characterize variation in KW with sowing date-associated weather conditions and examine the relationship between KW, grain filling parameters, and weather factors. Maize was sown on eight sowing dates(SD) at 15–20-day intervals from mid-March to mid-July during 2012 and 2013 in the North China Plain. With sowing date delay, KW increased initially and later declined, and the greatest KW was obtained at SD6 in both years. The increased KW at SD6 was attributed mainly to kernel growth rate(Gmean), and effective grain-filling period(P). Variations in temperature and radiation were the primary factors that influenced KW and grain-filling parameters. When the effective cumulative temperature(AT) and radiation(Ra)during grain filling were 950 °C and 1005.4 MJ m-2, respectively, P and KW were greatest. High temperatures(daily maximum temperature [Tmax] > 30.2 °C) during grain filling under early sowing conditions, or low temperatures(daily minimum temperature [Tmin] < 20.7 °C) under late sowing conditions combined with high diurnal temperature range(Tmax-min> 7.1 °C) decreased kernel growth rate and ultimately final KW. When sowing was performed from May 25 through June 27, higher KW and yield of maize were obtained. We conclude that variations in environmental conditions(temperature and radiation) during grain filling markedly affect growth rate and duration of grain filling and eventually affect kernel weight and yield of maize.
文摘Previous weighted frequent pattern （WFP） mining algorithms are not suitable for data streams for they need multiple database scans. In this paper, we present an efficient algorithm SWFP-Miner to mine weighted frequent pattern over data streams. SWFP-Miner is based on sliding window and can discover important frequent pattern from the recent data. A new refined weight definition is proposed to keep the downward closure property, and two pruning strategies are presented to prune the weighted infrequent pattern. Experimental studies are performed to evaluate the effectiveness and efficiency of SWFP-Miner.
基金supported by the National Natural Science Foundation of China (No. 81201322)the Priority Project on Infectious Disease Control and Prevention 2011ZX10004-001 and 2013ZX10003006-002 by the Chinese Ministry of Science and Technology and the Chinese Ministry of Healththe Foundation of State Key Laboratory for Infectious Disease Prevention and Control (Grand No. 2011SKLID303)
文摘Secretion systems, macromolecules to pass which can mediate the across cellular membranes, are essential for virulent and genetic material exchange among bacterial species[1]. Type IV secretion system （T4SS） is one of the secretion systems and it usually consists of 12 genes： VirB1, VirB2 ...VirB11, and VirD4[2]. The structure and molecular mechanisms of these genes have been well analyzed in Gram-negative strains[3] and Gram-positive strains were once believed to be lack of T4SS. However, some recent studies revealed that one or more virB/D genes also exist in some kinds of Gram-positive bacteria and play similar role, and form a T4SS-like system[3]. The VirBl-like, VirB4, VirB6, and VirD4 genes were identified in the chromosome of Gram-positive bacterium Streptococcus suis in our previous studies and their role as important mobile elements for horizontal transfer to recipients in an 89 K pathogenicity island （PAl） was demonstrated[45]. However, their structure and molecular mechanisms in other strains, especially in Gram-positive strains, are remained unclear.
基金Project supported by the National Natural Science Foundation of China
文摘In recent years, with the development of the enhanced oil recovery technique, researchers understood that the foam generation in the underground oil-bearing porous medium can successfully improve oil recovery. One of the important mechanisms of foam generation is the snap-off of gas bubbles in porous media.
基金financially supported by the National Natural Science Foundation of China(51772025 and 51972023).
文摘The emerging two-dimensional(2D)materials,MXenes,play an important role in various fields of energy storage and exhibit excellent electrochemical performance.Herein,we prepared few-layered MXenes(F-Ti_(3)C_(2)T_(x))and loaded Te on the surface of F-Ti_(3)C_(2)T_(x) by using a simple hightemperature evaporation method.In addition,the electrochemical performance of the aluminum battery with F-Ti_(3)C_(2)T_(x) as support material was studied.The initial charge/discharge specific capacities are 987/1096mAh g^(-1)at 0.2Ag^(-1).An obvious discharge voltage plateau of about 1.3V appears at various current densities.The specific capacity is about 258mAh g^(-1)with MXenes@Te as the active material in the aluminum battery,which benefits from the excellent electronic conductivity of the MXenes and their 2D layered structure.Density functional theory calculations were carried out to explore the mechanism.Ti_(3)C_(2)O_(2)@Te is more inclined to adsorb[AlCl_(4)]^(-) than Ti_(3)C_(2)O_(2).Furthermore,the valence change behavior of element Te was studied by using thermodynamic calculation(FactSage 7.1).X-ray photoelectron spectroscopy results show that when the battery is fully charged to 2.4V element Te and Ti ions(Ti^(3+),Ti^(2+))are oxidized to Te^(4+)and Ti^(4+).In contrast to the charging process,the high-valence Te^(4+)and Ti^(4+)are reduced again during discharging.Element Te is reduced to lower-valence Te^(2-)when the discharge voltage is lower than 0.6 V,and a higher charge voltage(2.56 V)is required for Te to be oxidized to Te^(6+).
基金This study was supported by grants from National Science and Technology Major Project(2018ZX10101003-002-011)Major Infectious Diseases such as AIDS and Viral Hepatitis Prevention and Control Technology Major Projects(2018ZX10712001-003)+1 种基金State Key Laboratory of Pathogen and Biosecurity Program(SKLPBS1837)State Key Laboratory of Veterinary Biotechnology(SKLVBF201911).
文摘Ebola virus (EBOV), a member of the filovirus family, is an enveloped negative-sense RNA virus that causes lethal infections in humans and primates. Thousands of people have died from the Ebola virus disease (EVD) in West Africa, and no specific antiviral medication and treatment have been approved for EVD. Although the development of an EBOV vaccine is promising, immunity to any vaccine is not immediate. Here, we computationally analysed the structure of EBOV glycoprotein GP2 (GP2EBOV) and designed RNA aptamers that recognize and inhibit it. The aptamers specifically bind to conserved arginine residues (Arg587 and Arg596) located in the C-terminal coiled-coil region of GP2EBOV. Molecular docking of the synthetic RNA aptamers with the ectodomain of GP2EBOV revealed that the optimized orthogonal RNA aptamers have strong binding affinities with the coiled-coil region of GP2EBOV. The characterized RNA aptamers may facilitate strategies to block replication of EBOV and related Filoviruses, and thus may serve as important antivirals to reduce mortality associated with these infections.
文摘Characteristic set method of polynomial equation solving has been widely spread and its implementation in software has been urged to consider in recent years. Several packages for the method are implemented in some computer algebra systems, such as REDUCE and Maple. In order to improve the efficiency of the method, we have developed a computer algebra system ″ELIMINO″ written in C language and implemented on Linux operation system on a PC. The authors wish to share with the reader the knowledge and experiences about the design and development of software package of the characteristic set method.
文摘Objective To design amplicons-based target sequencing panels using high-throughput next generation sequencing (NGS) and multiplex PCR techniques to sequence type 2 diabetes susceptibility genes and to assess their relationship with clinical characteristics in patients with type 2 diabetes.
基金This work was supported by the National Nature Science Foundationof China grant 31330019(Z.-J.L),11575021(H.L.),U1530401(H.L.),U1430237(H.L.)and 31500593(G.S.)the Ministry of Science and Technology of China grants 2014CB910400(Z.-J.L)and2015CB910104(Z.-J.L)This research work is supported by aTianhe-2JK computing time award at the Beijing Computational Research Center(CSRC).
文摘Dear Editor,A disulfide bond that formed between the thiol groups of two spatially close cysteine residues is essential for protein folding, stability, and function (Creighton et al., 1995) (Fass, 2012). Driven by conformational entropy, native disulfide bonds stabilize the conformation of protein molecules (Dill, 1990), while removal of native disulfides usually causes reduced stability of the target protein (Liu and Cowburn, 2016).
