The globally concerning per-and polyfluoroalkyl substances(PFASs)were widely detected in the environment,yet their environmental occurrences and behaviors remain elusive in the grassland soils.In this study,the region...The globally concerning per-and polyfluoroalkyl substances(PFASs)were widely detected in the environment,yet their environmental occurrences and behaviors remain elusive in the grassland soils.In this study,the region-specific distributions,sources and potential ecological risk of 31 legacy and novel PFASs were investigated in 74 grassland soils from Xilingol League,China.The 20 out of 31 PFASs were detected with the detection frequencies>50%,and the total concentrations of 31 PFASs were in the range of 263.7-16795.8 pg/g dry weight(d.w.).The novel PFASs were the dominant congeners,followed by legacy PFASs and PFAS precursors,indicating the widespread contamination of novel PFASs in the grassland soils.Elevated PFAS concentrations were detected in the soils adjacent to the industrial and urban areas.Industrial,fire-fighting and household activities,and long-range atmospheric transport were discovered as the main sources of PFASs in the grassland soils from Xilingol League.The calculated risk quotient values(<0.01)only indicated the low ecological risk of 12 target PFASs in the grassland soils.Our work enriches the data of PFAS contamination in the grassland soils,which provides the critical reference for the implementation of Action Plan on Controlling New Pollutants in China.展开更多
Dolomite is one of the most important rock types for the development of the Ordovician effective reservoirs in the Ordos Basin.Its genesis remains controversial due to its complex and variable rock texture and occurre...Dolomite is one of the most important rock types for the development of the Ordovician effective reservoirs in the Ordos Basin.Its genesis remains controversial due to its complex and variable rock texture and occurrence.In this paper,through analysis of macroscopic regional geological background,microscopic rock texture,mineralogy,and geochemistry,the Ordovician dolomites in this area are divided into three types,i.e.,micriteefine-powder crystal,coarse-powder crystal,and fine(medium)crystal.It is pointed out that they were formed in three different dolomitization diagenetic environments,namely,penecontemporaneous dolomitization by evaporative pumping,mixture dolomitization of freshwater and magnesium-rich brine,and seepageereflux dolomitization,respectively.In terms of horizon and spatial distribution,they represent the features of“strata-controlled”and“region-specific”.The analysis of genesis provides the following findings.First,the three types of dolomitization are correlated to certain extent in terms of temporalespatial evolution.In other words,they were all originated along with the deposition of gypsum mineral under evaporation background.Second,the main pore types,i.e.,dissolved pores,intercrystalline pores,and organic framework,were respectively formed in three types of dolomites.They generally distributed in“specific”type of dolomite,which indicates that the pore genesis is closely related to dolomitization diagenesis environment.Third,the development and distribution of effective dolomite reservoirs is mainly subject to three types of elements,such as primary sedimentary facies belts,diagenetic environment controlling regional dolomitization,and sequence boundary caused by variation of relative sea level.展开更多
Understanding the characteristics of extreme rainfall is crucial for effective flood management planning, as it enables the incorporation of insights from past extreme rainfall patterns and their spatiotemporal distri...Understanding the characteristics of extreme rainfall is crucial for effective flood management planning, as it enables the incorporation of insights from past extreme rainfall patterns and their spatiotemporal distribution. This work investigated the changes in the frequency and pattern of extreme rainfall over Uganda, using daily datasets sourced from Climate Hazard Group InfraRed Precipitation with Station (CHIRPS-v2) for the period 1981 to 2022. The study utilized the extreme weather Indices provided by the Expert Team on Climate Change Detection and Indices (ETCCDI). Attention was directed towards September to November (SON) rainfall season with precise analysis of four indices (Rx1day, Rx5day, R95p, and R99p). The Sequential Mann-Kendall (SQMK) non-parametric test was applied to identify abrupt changes in SON extreme rainfall trends. Results showed that October consistently recorded the highest count of extreme rainfall days across all four indices. The long-term analysis revealed fluctuations in extreme rainfall events across years, with certain periods exhibiting heightened intensity. The analysis portrayed a shift in the decadal variations and region-specific distribution of extreme rainfall, with Eastern Uganda and areas around Lake Victoria standing out compared to other regions. The findings further revealed an increase in extreme rainfall for all indices in the recent decade (2011-2022) with 2019/2020 standing out as the extreme years of SON for the study period. While trendlines suggested a slight increase in intense daily rainfall events, the SQMK tests revealed statistical significance in the trend of prolonged periods of intense daily rainfall. This study contributes to the understanding of the spatiotemporal variability and trends of extreme rainfall events over Uganda during the SON season, which is crucial for the assessment of climate change impacts and adaptation strategies. It provides valuable information for seasonal extreme rainfall forecasting, development of early warning systems, flood risk management, and disaster preparedness plans.展开更多
Background Dengue is a major global health threat with varied clinical manifestations across age groups,countries,and regions.This study aims to estimate global dengue disability weights(DWs)based on clinical manifest...Background Dengue is a major global health threat with varied clinical manifestations across age groups,countries,and regions.This study aims to estimate global dengue disability weights(DWs)based on clinical manifestations data and examine variations across different demographics and geographical areas.These findings will inform public health strategies and interventions to reduce the global burden of dengue.Methods We conducted a systematic search across six databases(Scopus,Web of Science,PubMed,China National Knowledge Infrastructure,Wanfang Data,and Database of Chinese sci-tech periodicals)for studies on human dengue clinical manifestations or infection from the establishment of each database through December 31,2023.DWs were estimated by combining clinical manifestations frequencies with corresponding DW values derived from the Global Burden of Disease(GBD)study,using Monte Carlo simulations to generate uncertainty intervals.Odds ratios(ORs)with 95%confidence intervals(CI)and Chi-square tests were performed to compare clinical manifestations between adults and children.Results A total of 35 adult studies(7109 cases)and 17 pediatric studies(2996 cases)were analysed.Adults had higher rates of muscle pain(OR=9.18;95%CI:8.17–10.33)and weak(OR=4.95;95%CI 4.12–5.98).Children showed higher frequencies of decreased appetite(OR=0.12;95%CI:0.11–0.14)and lymphadenectasis(OR=0.04;95%CI:0.03–0.06).Severe dengue was more prevalent in children(8.2%)than adults(4.6%).The global DW for universal dengue was 0.3258 in adults and 0.4022 in children,with Indian children showing the highest DW for severe dengue(0.6991)and Chinese adult showing the highest DW for severe dengue(0.7214).Regionally,most studies were from South and Southeast Asia,with India contributing the largest number of publications(80 articles).Additionally,India had the highest dengue disease burden in 2021(352,468.54 person-years).Conclusions These findings reveal important age and regional differences in dengue disease burden.There is a relative lack of research on dengue clinical manifestations in several high-burden countries in the Americas,and these gaps may affect the comprehensiveness and accuracy of global dengue disability weight estimates.These highlight the urgent need for targeted interventions and optimized resource allocation to mitigate its global impact.展开更多
Under cold conditions,the driving range of electric vehicles decreases significantly,and inaccuracies in the displayed remaining driving range(RDR)exacerbate range anxiety.This study proposes a knowledge-enhanced hier...Under cold conditions,the driving range of electric vehicles decreases significantly,and inaccuracies in the displayed remaining driving range(RDR)exacerbate range anxiety.This study proposes a knowledge-enhanced hierarchical framework that breaks down the RDR estimation problem into the prediction of energy consumption rate and effective energy coefficient.Both modules employ deep learning as their core models,using data sourced from a cloud-based big data platform with a focus on cold regions in Northeast China.To address real-world driving scenarios,the energy consumption rate module uses a switching mechanism:a base model,using region-specific collaborative features as inputs,is applied in the early stages of trips,while a sequential neural network is used in the later stages.The effective energy coefficient module incorporates battery degradation and environmental factors,correcting discrepancies in nominal battery energy under low-temperature and aging conditions.The model’s performance is validated using real-world data from 8 electric vehicles under cold conditions,demonstrating a 15–20%improvement in prediction accuracy over traditional methods,thereby enhancing RDR accuracy and reliability.展开更多
Alzheimer’s disease(AD)is a multifactorial neurodegenerative disorder associated with aging.Due to its insidious onset,protracted progression,and unclear pathogenesis,it is considered one of the most obscure and intr...Alzheimer’s disease(AD)is a multifactorial neurodegenerative disorder associated with aging.Due to its insidious onset,protracted progression,and unclear pathogenesis,it is considered one of the most obscure and intractable brain disorders,and currently,there are no effective therapies for it.Convincing evidence indicates that the irreversible decline of cognitive abilities in patients coincides with the deterioration and degeneration of neurons and synapses in the AD brain.Human neural stem cells(NSCs)hold the potential to functionally replace lost neurons,reinforce impaired synaptic networks,and repair the damaged AD brain.They have therefore received extensive attention as a possible source of donor cells for cellular replacement therapies for AD.Here,we review the progress in NSC-based transplantation studies in animal models of AD and assess the therapeutic advantages and challenges of human NSCs as donor cells.We then formulate a promising transplantation approach for the treatment of human AD,which would help to explore the disease-modifying cellular therapeutic strategy for the treatment of human AD.展开更多
基金supported by the National Natural Science Foundation of China(No.41907311)the Fundamental Research Funds for the Central Universities of China(No.3132023505)the Liaoning Revitalization Talents Program,China(No.XLYC1802036).
文摘The globally concerning per-and polyfluoroalkyl substances(PFASs)were widely detected in the environment,yet their environmental occurrences and behaviors remain elusive in the grassland soils.In this study,the region-specific distributions,sources and potential ecological risk of 31 legacy and novel PFASs were investigated in 74 grassland soils from Xilingol League,China.The 20 out of 31 PFASs were detected with the detection frequencies>50%,and the total concentrations of 31 PFASs were in the range of 263.7-16795.8 pg/g dry weight(d.w.).The novel PFASs were the dominant congeners,followed by legacy PFASs and PFAS precursors,indicating the widespread contamination of novel PFASs in the grassland soils.Elevated PFAS concentrations were detected in the soils adjacent to the industrial and urban areas.Industrial,fire-fighting and household activities,and long-range atmospheric transport were discovered as the main sources of PFASs in the grassland soils from Xilingol League.The calculated risk quotient values(<0.01)only indicated the low ecological risk of 12 target PFASs in the grassland soils.Our work enriches the data of PFAS contamination in the grassland soils,which provides the critical reference for the implementation of Action Plan on Controlling New Pollutants in China.
文摘Dolomite is one of the most important rock types for the development of the Ordovician effective reservoirs in the Ordos Basin.Its genesis remains controversial due to its complex and variable rock texture and occurrence.In this paper,through analysis of macroscopic regional geological background,microscopic rock texture,mineralogy,and geochemistry,the Ordovician dolomites in this area are divided into three types,i.e.,micriteefine-powder crystal,coarse-powder crystal,and fine(medium)crystal.It is pointed out that they were formed in three different dolomitization diagenetic environments,namely,penecontemporaneous dolomitization by evaporative pumping,mixture dolomitization of freshwater and magnesium-rich brine,and seepageereflux dolomitization,respectively.In terms of horizon and spatial distribution,they represent the features of“strata-controlled”and“region-specific”.The analysis of genesis provides the following findings.First,the three types of dolomitization are correlated to certain extent in terms of temporalespatial evolution.In other words,they were all originated along with the deposition of gypsum mineral under evaporation background.Second,the main pore types,i.e.,dissolved pores,intercrystalline pores,and organic framework,were respectively formed in three types of dolomites.They generally distributed in“specific”type of dolomite,which indicates that the pore genesis is closely related to dolomitization diagenesis environment.Third,the development and distribution of effective dolomite reservoirs is mainly subject to three types of elements,such as primary sedimentary facies belts,diagenetic environment controlling regional dolomitization,and sequence boundary caused by variation of relative sea level.
文摘Understanding the characteristics of extreme rainfall is crucial for effective flood management planning, as it enables the incorporation of insights from past extreme rainfall patterns and their spatiotemporal distribution. This work investigated the changes in the frequency and pattern of extreme rainfall over Uganda, using daily datasets sourced from Climate Hazard Group InfraRed Precipitation with Station (CHIRPS-v2) for the period 1981 to 2022. The study utilized the extreme weather Indices provided by the Expert Team on Climate Change Detection and Indices (ETCCDI). Attention was directed towards September to November (SON) rainfall season with precise analysis of four indices (Rx1day, Rx5day, R95p, and R99p). The Sequential Mann-Kendall (SQMK) non-parametric test was applied to identify abrupt changes in SON extreme rainfall trends. Results showed that October consistently recorded the highest count of extreme rainfall days across all four indices. The long-term analysis revealed fluctuations in extreme rainfall events across years, with certain periods exhibiting heightened intensity. The analysis portrayed a shift in the decadal variations and region-specific distribution of extreme rainfall, with Eastern Uganda and areas around Lake Victoria standing out compared to other regions. The findings further revealed an increase in extreme rainfall for all indices in the recent decade (2011-2022) with 2019/2020 standing out as the extreme years of SON for the study period. While trendlines suggested a slight increase in intense daily rainfall events, the SQMK tests revealed statistical significance in the trend of prolonged periods of intense daily rainfall. This study contributes to the understanding of the spatiotemporal variability and trends of extreme rainfall events over Uganda during the SON season, which is crucial for the assessment of climate change impacts and adaptation strategies. It provides valuable information for seasonal extreme rainfall forecasting, development of early warning systems, flood risk management, and disaster preparedness plans.
基金supported by the National Natural Science Foundation of China(82260655)the National Key Research and Development Program of People’s Republic of China(Grant No.2021YFC2300800 and 2021YFC2300804)+1 种基金the Basic and applied basic research project jointly funded by the University of Guangzhou(Grant No.2023A03J0810)the Key R&D Program of Guangdong Province(Grant No.2022B1111030002).
文摘Background Dengue is a major global health threat with varied clinical manifestations across age groups,countries,and regions.This study aims to estimate global dengue disability weights(DWs)based on clinical manifestations data and examine variations across different demographics and geographical areas.These findings will inform public health strategies and interventions to reduce the global burden of dengue.Methods We conducted a systematic search across six databases(Scopus,Web of Science,PubMed,China National Knowledge Infrastructure,Wanfang Data,and Database of Chinese sci-tech periodicals)for studies on human dengue clinical manifestations or infection from the establishment of each database through December 31,2023.DWs were estimated by combining clinical manifestations frequencies with corresponding DW values derived from the Global Burden of Disease(GBD)study,using Monte Carlo simulations to generate uncertainty intervals.Odds ratios(ORs)with 95%confidence intervals(CI)and Chi-square tests were performed to compare clinical manifestations between adults and children.Results A total of 35 adult studies(7109 cases)and 17 pediatric studies(2996 cases)were analysed.Adults had higher rates of muscle pain(OR=9.18;95%CI:8.17–10.33)and weak(OR=4.95;95%CI 4.12–5.98).Children showed higher frequencies of decreased appetite(OR=0.12;95%CI:0.11–0.14)and lymphadenectasis(OR=0.04;95%CI:0.03–0.06).Severe dengue was more prevalent in children(8.2%)than adults(4.6%).The global DW for universal dengue was 0.3258 in adults and 0.4022 in children,with Indian children showing the highest DW for severe dengue(0.6991)and Chinese adult showing the highest DW for severe dengue(0.7214).Regionally,most studies were from South and Southeast Asia,with India contributing the largest number of publications(80 articles).Additionally,India had the highest dengue disease burden in 2021(352,468.54 person-years).Conclusions These findings reveal important age and regional differences in dengue disease burden.There is a relative lack of research on dengue clinical manifestations in several high-burden countries in the Americas,and these gaps may affect the comprehensiveness and accuracy of global dengue disability weight estimates.These highlight the urgent need for targeted interventions and optimized resource allocation to mitigate its global impact.
基金supported by the National Natural Science Foundation of China under the Regional Innovation and Development Joint Fund(Grant No.U21A20166)the Jilin Provincial Department of Science and Technology(Grant No.20230508095RC).
文摘Under cold conditions,the driving range of electric vehicles decreases significantly,and inaccuracies in the displayed remaining driving range(RDR)exacerbate range anxiety.This study proposes a knowledge-enhanced hierarchical framework that breaks down the RDR estimation problem into the prediction of energy consumption rate and effective energy coefficient.Both modules employ deep learning as their core models,using data sourced from a cloud-based big data platform with a focus on cold regions in Northeast China.To address real-world driving scenarios,the energy consumption rate module uses a switching mechanism:a base model,using region-specific collaborative features as inputs,is applied in the early stages of trips,while a sequential neural network is used in the later stages.The effective energy coefficient module incorporates battery degradation and environmental factors,correcting discrepancies in nominal battery energy under low-temperature and aging conditions.The model’s performance is validated using real-world data from 8 electric vehicles under cold conditions,demonstrating a 15–20%improvement in prediction accuracy over traditional methods,thereby enhancing RDR accuracy and reliability.
基金This work was supported in part by the"Strategic Priority Research Program"of the Chinese Academy of Sciences,Grant No.(XDA16020501,XDA16020404)National Key Basic Research and Development Program of China(2018YFA0108000,2018YFA0107200,2017YFA0102700)the research developmental fund(RDF-21-01-021,PGRS2112030)of Xi’an Jiaotong-Liverpool University.
文摘Alzheimer’s disease(AD)is a multifactorial neurodegenerative disorder associated with aging.Due to its insidious onset,protracted progression,and unclear pathogenesis,it is considered one of the most obscure and intractable brain disorders,and currently,there are no effective therapies for it.Convincing evidence indicates that the irreversible decline of cognitive abilities in patients coincides with the deterioration and degeneration of neurons and synapses in the AD brain.Human neural stem cells(NSCs)hold the potential to functionally replace lost neurons,reinforce impaired synaptic networks,and repair the damaged AD brain.They have therefore received extensive attention as a possible source of donor cells for cellular replacement therapies for AD.Here,we review the progress in NSC-based transplantation studies in animal models of AD and assess the therapeutic advantages and challenges of human NSCs as donor cells.We then formulate a promising transplantation approach for the treatment of human AD,which would help to explore the disease-modifying cellular therapeutic strategy for the treatment of human AD.
