Path planning for Unmanned Aerial Vehicles(UAVs)in complex environments presents several challenges.Traditional algorithms often struggle with the complexity of high-dimensional search spaces,leading to inefficiencies...Path planning for Unmanned Aerial Vehicles(UAVs)in complex environments presents several challenges.Traditional algorithms often struggle with the complexity of high-dimensional search spaces,leading to inefficiencies.Additionally,the non-linear nature of cost functions can cause algorithms to become trapped in local optima.Furthermore,there is often a lack of adequate consideration for real-world constraints,for example,due to the necessity for obstacle avoidance or because of the restrictions of flight safety.To address the aforementioned issues,this paper proposes a dynamic weighted spherical particle swarm optimization(DW-SPSO)algorithm.The algorithm adopts a dual Sigmoid-based adaptive weight adjustment mechanism for balancing global exploration and local exploitation,as well as a lens-based opposition learning one to improve search flexibility and solution diversity.Simulation experiments on real digital elevation models demonstrate that DW-SPSO significantly outperforms recent state-of-the-art particle swarm optimization(PSO)variants in terms of path safety,smoothness,and convergence speed.The performance superiority is statistically validated by the Wilcoxon signed-rank test.The results confirm the algorithm’s effectiveness in generating high-quality UAV paths under diverse threat conditions,offering a robust solution for autonomous navigation systems.展开更多
Renewable electricity-driven production of value-added sulfur and H_(2)via electrocatalytic H_(2)S decomposition represents a sustainable route to conventional thermocatalysis.Both the electrocatalyst and electrolyte ...Renewable electricity-driven production of value-added sulfur and H_(2)via electrocatalytic H_(2)S decomposition represents a sustainable route to conventional thermocatalysis.Both the electrocatalyst and electrolyte solution strongly impact the H_(2)S decomposition performance.Despite significant progress in developing sophisticated electrocatalysts,a well-designed electrolyte solution in conjunction with industrial catalysts is an attractive strategy to advance the industrialization process of electrocatalytic H_(2)S decomposition,but remains unexplored.Here,for the first time,we design a solid-liquid-gas three-phase indirect electrolysis system based on a kind of CS_(2)-N electrolyte solution and Ni-Mo_(2)C that can efficiently enable H_(2)S decomposition into valuable H_(2)and sulfur.Specifically,the solid-phase Ni-Mo_(2)C as a heterogeneous redox mediator presents excellent electrocatalytic efficiency for the H_(2)S removal efficiency of up to 99%,and the formation of liquid-phase sulfur product(CS_(2)-N electrolyte solution dissolves sulfur,yield up to 95%)with the generation of gas-phase H_(2)product(~1.32 mL min^(-1)),resulting in an interesting three-phase indirect electrolysis system.Remarkably,it enables the scale-up production(~6 g in a batch experiment)of sulfur with continuous operation for 120 h without attenuation.This work may inaugurate a new electrocatalytic H_(2)S decomposition avenue to explore porous metal materials and electrolyte systems in simultaneous production of value-added sulfur and H_(2).展开更多
Feature selection serves as a critical preprocessing step inmachine learning,focusing on identifying and preserving the most relevant features to improve the efficiency and performance of classification algorithms.Par...Feature selection serves as a critical preprocessing step inmachine learning,focusing on identifying and preserving the most relevant features to improve the efficiency and performance of classification algorithms.Particle Swarm Optimization has demonstrated significant potential in addressing feature selection challenges.However,there are inherent limitations in Particle Swarm Optimization,such as the delicate balance between exploration and exploitation,susceptibility to local optima,and suboptimal convergence rates,hinder its performance.To tackle these issues,this study introduces a novel Leveraged Opposition-Based Learning method within Fitness Landscape Particle Swarm Optimization,tailored for wrapper-based feature selection.The proposed approach integrates:(1)a fitness-landscape adaptive strategy to dynamically balance exploration and exploitation,(2)the lever principle within Opposition-Based Learning to improve search efficiency,and(3)a Local Selection and Re-optimization mechanism combined with random perturbation to expedite convergence and enhance the quality of the optimal feature subset.The effectiveness of is rigorously evaluated on 24 benchmark datasets and compared against 13 advancedmetaheuristic algorithms.Experimental results demonstrate that the proposed method outperforms the compared algorithms in classification accuracy on over half of the datasets,whilst also significantly reducing the number of selected features.These findings demonstrate its effectiveness and robustness in feature selection tasks.展开更多
Passengers typically spend much time in commercial zones of terminals for retail,meals,and other services.Enhancing the study of thermal comfort in this local space is necessary.The climate in the Eastern China Region...Passengers typically spend much time in commercial zones of terminals for retail,meals,and other services.Enhancing the study of thermal comfort in this local space is necessary.The climate in the Eastern China Region is variable and complex,making it more challenging to maintain the indoor thermal environment.This study conducted field measurements in winter in a commercial zone of one terminal to assess the thermal environment.Numerical simulations and PMV-PPD analyses were performed using the Computational Fluid Dynamics(CFD)program The results showed that the overall humidity in the commercial zone was low.There were notable differences in the temperatures and velocities of supply air among different air vents on the commercial island.Based on these initial conditions obtained by measurements,the simulations showed that localized areas under the breathing plane are either too hot(24℃and above)or too cold(18℃and below).The dissatisfaction percentage of the population exceeds 27%.This paper proposed that through enhancements in the air vent dimensions,layout,and air supply conditions,the temperature can be maintained in the range of 20-24℃.Furthermore,the PMV could be controlled within the range of-0.5 to 0.5.PPD was below 10%,reflecting compliance with Class I heating standards.Overall,findings from this study provide a less costly modification for thermal comfort improvement in commercial zones,and serve as a reference for the design and operation of air-conditioning systems to ensure thermal comfort in airport terminals’commercial zones.展开更多
Organic semiconductor lasers are attractive for low thresholds and cost,but triplet accumulation hampers their electrically pumped development.Compared to existing organic lasing materials,triplet-triplet annihilation...Organic semiconductor lasers are attractive for low thresholds and cost,but triplet accumulation hampers their electrically pumped development.Compared to existing organic lasing materials,triplet-triplet annihilation(TTA)systems are capable of tolerating high triplet concentrations and may facilitate stable laser emission under electrical pumping.To avoid energy losses in doped multicomponent TTA systems,herein,we report an organic semiconductor lasing material BH001 with TTA properties,which combines concurrent triplet harvesting and lasing within a single molecular framework.Dislocations betweenπ-conjugated planes reduceπ-πstacking-induced fluorescence quenching,yielding high photoluminescence quantum yield(PLQY)in the crystal.The TTA process in BH001 can be observed through a color change from red to blue by the sensitization of PtOEP.Given that nanosecond/femtosecond transient absorption(ns-TA and fs-TA)spectroscopy has demonstrated the appreciable ability of BH001 to generate triplet states,TTA-delayed fluorescence of pure BH001 crystal was directly detected using a streak camera.A laser constructed from this TTA crystal achieved low-threshold blue emission at 440 nm(P_(th)=15.4μJ/cm^(2)),which is increased in an oxygen atmosphere,suggesting the involvement of triplets.Upon excitation with nanosecond laser pulses that are more prone to cause triplet stacking,the BH001 crystal exhibits stimulated emission behavior.This study demonstrates a lasing molecule with TTA properties,highlighting its potential in continuous wave(CW)pumped and ultimately electrically pumped systems.展开更多
Jihei buffer zone of the Second Songhua River in lower reaches of Songyuan City of the Songhua River was taken as the research object,and the current water quality,point source and non-point source pollution,and regio...Jihei buffer zone of the Second Songhua River in lower reaches of Songyuan City of the Songhua River was taken as the research object,and the current water quality,point source and non-point source pollution,and regional social and economic conditions of the buffer zone and its upstream water functional area were investigated.According to pollution sources and pollutant carrying capacity of water functional areas,analysis on main pollution factors in buffer zone was completed.展开更多
Liver cancer is an extremely heterogeneous malignant tumor characterized by high morbidity and mortality rates.Despite significant advancements in cancer care,the outcomes of liver cancer patients remain poor.Artifici...Liver cancer is an extremely heterogeneous malignant tumor characterized by high morbidity and mortality rates.Despite significant advancements in cancer care,the outcomes of liver cancer patients remain poor.Artificial intelligence(AI)is a major discipline in computer science that attempts to simulate human intelligence using machines or systems.Owing to the availability of multidimensional databases and recent algorithmic advancements,AI offers tremendous potential to overcome current obstacles in oncology research and practice.There is a growing body of evidence suggesting that AI models enable pathologists to diagnose liver cancer more accurately,customize personalized therapies,and predict cancer prognosis.Therefore,the increasing adoption of AI is expected to improve healthcare accuracy and patients’quality of life.However,only a few AI models are currently authorized for clinical use.This review outlines recent developments in research on the biomedical application of AI technology in liver cancer and discusses both the potential hurdles and future implications of employing AI for clinical cancer management,thereby providing insights for further research.Overall,the clinical implementation of AI technology is anticipated to induce a paradigm shift in medical oncology,leading to significant improvements in patient outcomes.展开更多
The dissolved hydrogen, rather than gaseous hydrogen, plays a crucial role in the hydrogenation process. A thorough understanding of hydrogen dissolution is essential for optimizing the hydrogenation process. In this ...The dissolved hydrogen, rather than gaseous hydrogen, plays a crucial role in the hydrogenation process. A thorough understanding of hydrogen dissolution is essential for optimizing the hydrogenation process. In this paper, the dynamic pressure step method was modified to reduce the temperature difference between the hydrogen and solution, from which the hydrogen solubility and volumetric liquid-side mass transfer coefficient (k_(L)a) of the vacuum residue were obtained. It was discovered that temperature was the most critical factor in hydrogen dissolution, simultaneously enhancing both the hydrogen solubility and k_(L)a. Pressure played a significant role in promoting hydrogen solubility, but had a relatively small impact on kLa. Stirring speed, although it enhanced k_(L)a, did not affect hydrogen solubility. By normalizing the dissolution parameter, the results showed that the gas-liquid mass transfer rate decreased continuously during hydrogen dissolution and that the SD-tD curves after normalization were almost the same in all experimental conditions.展开更多
Background:Coronavirus disease 2019(COVID-19)is a global pandemic with high mortality,and the treatment options for the severe patients remain limited.Previous studies reported the altered gut mi-crobiota in severe CO...Background:Coronavirus disease 2019(COVID-19)is a global pandemic with high mortality,and the treatment options for the severe patients remain limited.Previous studies reported the altered gut mi-crobiota in severe COVID-19.But there are no comprehensive data on the role of microbial metabolites in COVID-19 patients.Methods:We identified 153 serum microbial metabolites and assessed the changes in 72 COVID-19 pa-tients upon admission and one-month after their discharge,comparing these changes to those in 133 healthy control individuals from the outpatient department during the same period.Results:Our study revealed that microbial metabolites varied across different stages and severity of COVID-19 patients.These altered microbial metabolites included tryptophan,bile acids,fatty acids,amino acids,vitamins and those containing benzene.A total of 13 distinct microbial metabolites were identi-fied in COVID-19 patients compared to healthy controls.Notably,correlations were found among these disrupted metabolites and organ injury and inflammatory responses related to COVID-19.Furthermore,these metabolites did not restore to the normal levels one month after discharge.Importantly,two mi-crobial metabolites were the core microbial metabolites related to the severity of COVID-19 patients.Conclusions:The microbial metabolites were altered in the acute and recovery stage,correlating with dis-ease severity of COVID-19.These results indicated the important role of gut microbiota in the progression of COVID-19,and facilitated the potential therapeutic microbial target for severe COVID-19 patients.展开更多
Sustainable energy technologies,particularly fuel cells,are gaining attraction for their potential to reduce carbon emissions and provide efficient power.Proton exchange membrane fuel cells(PEMFCs)have been central to...Sustainable energy technologies,particularly fuel cells,are gaining attraction for their potential to reduce carbon emissions and provide efficient power.Proton exchange membrane fuel cells(PEMFCs)have been central to this development.However,one persistent issue with lowtemperature PEMFCs is the dehydration of Nafion ionomer at elevated temperatures,which severely limits proton conductivity.Wang et al.tackle this by introducing a covalent organic framework(COF)interwoven with Nafion,addressing the challenge of maintaining proton conductivity and oxygen transport in medium temperatures(100–120℃).展开更多
To overcome the limitations of microscale experimental techniques and molecular dynamics(MD)simulations,a coarse-grained molecular dynamics(CGMD)method was used to simulate the wetting processes of clay aggregates.Bas...To overcome the limitations of microscale experimental techniques and molecular dynamics(MD)simulations,a coarse-grained molecular dynamics(CGMD)method was used to simulate the wetting processes of clay aggregates.Based on the evolution of swelling stress,final dry density,water distribution,and clay arrangements under different target water contents and dry densities,a relationship between the swelling behaviors and microstructures was established.The simulated results showed that when the clay-water well depth was 300 kcal/mol,the basal spacing from CGMD was consistent with the X-ray diffraction(XRD)data.The effect of initial dry density on swelling stress was more pronounced than that of water content.The anisotropic swelling characteristics of the aggregates are related to the proportion of horizontally oriented clay mineral layers.The swelling stress was found to depend on the distribution of tactoids at the microscopic level.At lower initial dry density,the distribution of tactoids was mainly controlled by water distribution.With increase in the bound water content,the basal spacing expanded,and the swelling stresses increased.Free water dominated at higher water contents,and the particles were easily rotated,leading to a decrease in the number of large tactoids.At higher dry densities,the distances between the clay mineral layers decreased,and the movement was limited.When bound water enters the interlayers,there is a significant increase in interparticle repulsive forces,resulting in a greater number of small-sized tactoids.Eventually,a well-defined logarithmic relationship was observed between the swelling stress and the total number of tactoids.These findings contribute to a better understanding of coupled macro-micro swelling behaviors of montmorillonite-based materials,filling a study gap in clay-water interactions on a micro scale.展开更多
基金supported by the National Natural Science Foundation of China(Grant No.62106092)the Natural Science Foundation of Fujian Province(Grant Nos.2024J01822,2025J01981)the Natural Science Foundation of Zhangzhou City(Grant No.ZZ2024J28).
文摘Path planning for Unmanned Aerial Vehicles(UAVs)in complex environments presents several challenges.Traditional algorithms often struggle with the complexity of high-dimensional search spaces,leading to inefficiencies.Additionally,the non-linear nature of cost functions can cause algorithms to become trapped in local optima.Furthermore,there is often a lack of adequate consideration for real-world constraints,for example,due to the necessity for obstacle avoidance or because of the restrictions of flight safety.To address the aforementioned issues,this paper proposes a dynamic weighted spherical particle swarm optimization(DW-SPSO)algorithm.The algorithm adopts a dual Sigmoid-based adaptive weight adjustment mechanism for balancing global exploration and local exploitation,as well as a lens-based opposition learning one to improve search flexibility and solution diversity.Simulation experiments on real digital elevation models demonstrate that DW-SPSO significantly outperforms recent state-of-the-art particle swarm optimization(PSO)variants in terms of path safety,smoothness,and convergence speed.The performance superiority is statistically validated by the Wilcoxon signed-rank test.The results confirm the algorithm’s effectiveness in generating high-quality UAV paths under diverse threat conditions,offering a robust solution for autonomous navigation systems.
基金supported by the National Natural Science Foundation of China(No.22278439 and 21776313).
文摘Renewable electricity-driven production of value-added sulfur and H_(2)via electrocatalytic H_(2)S decomposition represents a sustainable route to conventional thermocatalysis.Both the electrocatalyst and electrolyte solution strongly impact the H_(2)S decomposition performance.Despite significant progress in developing sophisticated electrocatalysts,a well-designed electrolyte solution in conjunction with industrial catalysts is an attractive strategy to advance the industrialization process of electrocatalytic H_(2)S decomposition,but remains unexplored.Here,for the first time,we design a solid-liquid-gas three-phase indirect electrolysis system based on a kind of CS_(2)-N electrolyte solution and Ni-Mo_(2)C that can efficiently enable H_(2)S decomposition into valuable H_(2)and sulfur.Specifically,the solid-phase Ni-Mo_(2)C as a heterogeneous redox mediator presents excellent electrocatalytic efficiency for the H_(2)S removal efficiency of up to 99%,and the formation of liquid-phase sulfur product(CS_(2)-N electrolyte solution dissolves sulfur,yield up to 95%)with the generation of gas-phase H_(2)product(~1.32 mL min^(-1)),resulting in an interesting three-phase indirect electrolysis system.Remarkably,it enables the scale-up production(~6 g in a batch experiment)of sulfur with continuous operation for 120 h without attenuation.This work may inaugurate a new electrocatalytic H_(2)S decomposition avenue to explore porous metal materials and electrolyte systems in simultaneous production of value-added sulfur and H_(2).
基金supported by National Natural Science Foundation of China(62106092)Natural Science Foundation of Fujian Province(2024J01822,2024J01820,2022J01916)Natural Science Foundation of Zhangzhou City(ZZ2024J28).
文摘Feature selection serves as a critical preprocessing step inmachine learning,focusing on identifying and preserving the most relevant features to improve the efficiency and performance of classification algorithms.Particle Swarm Optimization has demonstrated significant potential in addressing feature selection challenges.However,there are inherent limitations in Particle Swarm Optimization,such as the delicate balance between exploration and exploitation,susceptibility to local optima,and suboptimal convergence rates,hinder its performance.To tackle these issues,this study introduces a novel Leveraged Opposition-Based Learning method within Fitness Landscape Particle Swarm Optimization,tailored for wrapper-based feature selection.The proposed approach integrates:(1)a fitness-landscape adaptive strategy to dynamically balance exploration and exploitation,(2)the lever principle within Opposition-Based Learning to improve search efficiency,and(3)a Local Selection and Re-optimization mechanism combined with random perturbation to expedite convergence and enhance the quality of the optimal feature subset.The effectiveness of is rigorously evaluated on 24 benchmark datasets and compared against 13 advancedmetaheuristic algorithms.Experimental results demonstrate that the proposed method outperforms the compared algorithms in classification accuracy on over half of the datasets,whilst also significantly reducing the number of selected features.These findings demonstrate its effectiveness and robustness in feature selection tasks.
基金supported by the National Natural Science Foundation of China(52478098)the Natural Science Foundation of Shanghai Municipality(21ZR1444800)the Shanghai Sailing Program(21YF1430700).
文摘Passengers typically spend much time in commercial zones of terminals for retail,meals,and other services.Enhancing the study of thermal comfort in this local space is necessary.The climate in the Eastern China Region is variable and complex,making it more challenging to maintain the indoor thermal environment.This study conducted field measurements in winter in a commercial zone of one terminal to assess the thermal environment.Numerical simulations and PMV-PPD analyses were performed using the Computational Fluid Dynamics(CFD)program The results showed that the overall humidity in the commercial zone was low.There were notable differences in the temperatures and velocities of supply air among different air vents on the commercial island.Based on these initial conditions obtained by measurements,the simulations showed that localized areas under the breathing plane are either too hot(24℃and above)or too cold(18℃and below).The dissatisfaction percentage of the population exceeds 27%.This paper proposed that through enhancements in the air vent dimensions,layout,and air supply conditions,the temperature can be maintained in the range of 20-24℃.Furthermore,the PMV could be controlled within the range of-0.5 to 0.5.PPD was below 10%,reflecting compliance with Class I heating standards.Overall,findings from this study provide a less costly modification for thermal comfort improvement in commercial zones,and serve as a reference for the design and operation of air-conditioning systems to ensure thermal comfort in airport terminals’commercial zones.
基金the NSFC(22303056,22173062,22150005,22433005,22090022,and 22275125)the National Key Research and Development Program of China(2022YFA1204402,2018YFA0704805,and 2018YFA0704802)+3 种基金the Natural Science Foundation of Beijing,China(KZ202110028043)R&D Program of Beijing Municipal Education Commission(KM202410028016,BPHR202203119)the Science and Technology Innovation Program of Hunan Province(2022RC4039)State Key Laboratory of Fine Chemicals,Dalian University of Technology(KF2313)for financial support.
文摘Organic semiconductor lasers are attractive for low thresholds and cost,but triplet accumulation hampers their electrically pumped development.Compared to existing organic lasing materials,triplet-triplet annihilation(TTA)systems are capable of tolerating high triplet concentrations and may facilitate stable laser emission under electrical pumping.To avoid energy losses in doped multicomponent TTA systems,herein,we report an organic semiconductor lasing material BH001 with TTA properties,which combines concurrent triplet harvesting and lasing within a single molecular framework.Dislocations betweenπ-conjugated planes reduceπ-πstacking-induced fluorescence quenching,yielding high photoluminescence quantum yield(PLQY)in the crystal.The TTA process in BH001 can be observed through a color change from red to blue by the sensitization of PtOEP.Given that nanosecond/femtosecond transient absorption(ns-TA and fs-TA)spectroscopy has demonstrated the appreciable ability of BH001 to generate triplet states,TTA-delayed fluorescence of pure BH001 crystal was directly detected using a streak camera.A laser constructed from this TTA crystal achieved low-threshold blue emission at 440 nm(P_(th)=15.4μJ/cm^(2)),which is increased in an oxygen atmosphere,suggesting the involvement of triplets.Upon excitation with nanosecond laser pulses that are more prone to cause triplet stacking,the BH001 crystal exhibits stimulated emission behavior.This study demonstrates a lasing molecule with TTA properties,highlighting its potential in continuous wave(CW)pumped and ultimately electrically pumped systems.
文摘Jihei buffer zone of the Second Songhua River in lower reaches of Songyuan City of the Songhua River was taken as the research object,and the current water quality,point source and non-point source pollution,and regional social and economic conditions of the buffer zone and its upstream water functional area were investigated.According to pollution sources and pollutant carrying capacity of water functional areas,analysis on main pollution factors in buffer zone was completed.
基金supported by the Natural Science Foundation of Shandong Province,China(Grant No.:ZR2021MH018).
文摘Liver cancer is an extremely heterogeneous malignant tumor characterized by high morbidity and mortality rates.Despite significant advancements in cancer care,the outcomes of liver cancer patients remain poor.Artificial intelligence(AI)is a major discipline in computer science that attempts to simulate human intelligence using machines or systems.Owing to the availability of multidimensional databases and recent algorithmic advancements,AI offers tremendous potential to overcome current obstacles in oncology research and practice.There is a growing body of evidence suggesting that AI models enable pathologists to diagnose liver cancer more accurately,customize personalized therapies,and predict cancer prognosis.Therefore,the increasing adoption of AI is expected to improve healthcare accuracy and patients’quality of life.However,only a few AI models are currently authorized for clinical use.This review outlines recent developments in research on the biomedical application of AI technology in liver cancer and discusses both the potential hurdles and future implications of employing AI for clinical cancer management,thereby providing insights for further research.Overall,the clinical implementation of AI technology is anticipated to induce a paradigm shift in medical oncology,leading to significant improvements in patient outcomes.
基金supported by the National Key R&D Program of China(No.2022YFB4101300)National Natural Science Foundation of China(NSFC)(No.22278430 and 21878329)Project of R&D Department of CNPC(2020B-2011 and 21-CB-05-05).
文摘The dissolved hydrogen, rather than gaseous hydrogen, plays a crucial role in the hydrogenation process. A thorough understanding of hydrogen dissolution is essential for optimizing the hydrogenation process. In this paper, the dynamic pressure step method was modified to reduce the temperature difference between the hydrogen and solution, from which the hydrogen solubility and volumetric liquid-side mass transfer coefficient (k_(L)a) of the vacuum residue were obtained. It was discovered that temperature was the most critical factor in hydrogen dissolution, simultaneously enhancing both the hydrogen solubility and k_(L)a. Pressure played a significant role in promoting hydrogen solubility, but had a relatively small impact on kLa. Stirring speed, although it enhanced k_(L)a, did not affect hydrogen solubility. By normalizing the dissolution parameter, the results showed that the gas-liquid mass transfer rate decreased continuously during hydrogen dissolution and that the SD-tD curves after normalization were almost the same in all experimental conditions.
基金supported by grants from the National Key R&D Program of China(2021YFA1301001)the Natural Science Founda-tion of China(82170668)+1 种基金the Sino-German Center for Research Promotion(GZ1546)the CAMS Innovation Fund for Medical Sciences(2019-I2M-5-045).
文摘Background:Coronavirus disease 2019(COVID-19)is a global pandemic with high mortality,and the treatment options for the severe patients remain limited.Previous studies reported the altered gut mi-crobiota in severe COVID-19.But there are no comprehensive data on the role of microbial metabolites in COVID-19 patients.Methods:We identified 153 serum microbial metabolites and assessed the changes in 72 COVID-19 pa-tients upon admission and one-month after their discharge,comparing these changes to those in 133 healthy control individuals from the outpatient department during the same period.Results:Our study revealed that microbial metabolites varied across different stages and severity of COVID-19 patients.These altered microbial metabolites included tryptophan,bile acids,fatty acids,amino acids,vitamins and those containing benzene.A total of 13 distinct microbial metabolites were identi-fied in COVID-19 patients compared to healthy controls.Notably,correlations were found among these disrupted metabolites and organ injury and inflammatory responses related to COVID-19.Furthermore,these metabolites did not restore to the normal levels one month after discharge.Importantly,two mi-crobial metabolites were the core microbial metabolites related to the severity of COVID-19 patients.Conclusions:The microbial metabolites were altered in the acute and recovery stage,correlating with dis-ease severity of COVID-19.These results indicated the important role of gut microbiota in the progression of COVID-19,and facilitated the potential therapeutic microbial target for severe COVID-19 patients.
基金financial support from the National Natural Science Foundation of China(No.22301139)the Natural Science Foundation of Jiangsu Province(No.BK 20230375).
文摘Sustainable energy technologies,particularly fuel cells,are gaining attraction for their potential to reduce carbon emissions and provide efficient power.Proton exchange membrane fuel cells(PEMFCs)have been central to this development.However,one persistent issue with lowtemperature PEMFCs is the dehydration of Nafion ionomer at elevated temperatures,which severely limits proton conductivity.Wang et al.tackle this by introducing a covalent organic framework(COF)interwoven with Nafion,addressing the challenge of maintaining proton conductivity and oxygen transport in medium temperatures(100–120℃).
基金supported by the National Natural Science Foundation of China(Grant No.42172308)the Youth Innovation Promotion Association CAS(Grant No.2022331)the Key Research and Development Program of Hubei Province(Grant No.2022BAA036).
文摘To overcome the limitations of microscale experimental techniques and molecular dynamics(MD)simulations,a coarse-grained molecular dynamics(CGMD)method was used to simulate the wetting processes of clay aggregates.Based on the evolution of swelling stress,final dry density,water distribution,and clay arrangements under different target water contents and dry densities,a relationship between the swelling behaviors and microstructures was established.The simulated results showed that when the clay-water well depth was 300 kcal/mol,the basal spacing from CGMD was consistent with the X-ray diffraction(XRD)data.The effect of initial dry density on swelling stress was more pronounced than that of water content.The anisotropic swelling characteristics of the aggregates are related to the proportion of horizontally oriented clay mineral layers.The swelling stress was found to depend on the distribution of tactoids at the microscopic level.At lower initial dry density,the distribution of tactoids was mainly controlled by water distribution.With increase in the bound water content,the basal spacing expanded,and the swelling stresses increased.Free water dominated at higher water contents,and the particles were easily rotated,leading to a decrease in the number of large tactoids.At higher dry densities,the distances between the clay mineral layers decreased,and the movement was limited.When bound water enters the interlayers,there is a significant increase in interparticle repulsive forces,resulting in a greater number of small-sized tactoids.Eventually,a well-defined logarithmic relationship was observed between the swelling stress and the total number of tactoids.These findings contribute to a better understanding of coupled macro-micro swelling behaviors of montmorillonite-based materials,filling a study gap in clay-water interactions on a micro scale.
