Hepatocellular carcinoma(HCC)is a pressing global health problem and is the sixth most common cancer and the third leading cause of cancer mortality worldwide.Despite continuous advances in treatment modalities,the 5-...Hepatocellular carcinoma(HCC)is a pressing global health problem and is the sixth most common cancer and the third leading cause of cancer mortality worldwide.Despite continuous advances in treatment modalities,the 5-year survival rate is low with a high propensity for recurrence and metastasis1.This clinical challenge in treating HCC is largely attributed to the heterogeneity and intrinsic therapy resistance of cancer stem cells(CSCs),which are a subpopulation of cells with self-renewal capability and multidirectional differentiation potential to induce tumorigenicity2.The behavior and maintenance of CSCs are not autonomous but critically dependent on the complex bidirectional crosstalk between CSCs and the tumor immune microenvironment(TIME)1.In this review we first summarize the recent progress in characterizing CSCs and the interactions between CSCs and the TIME in HCC.Next,we discuss the emerging therapeutic strategies targeting CSC populations with the ongoing challenges.Finally,we give our perspectives on the future directions in HCC CSC research.展开更多
Haze pollution has become a severe environmental problem in the daily life of the people in China. PM2.s makes a significant contribution to poor air quality. The spatio-temporal features of China＇s PM2.s concentrati...Haze pollution has become a severe environmental problem in the daily life of the people in China. PM2.s makes a significant contribution to poor air quality. The spatio-temporal features of China＇s PM2.s concentrations should be investigated. This paper, based on ob- served data from 945 newly located monitoring sites in 2014 and industrial working population data obtained from International Standard Industrial Classification （ISIC）, reveals the spa- tio-temporal variations of PM2.5 concentrations in China and the correlations among different industries. We tested the spatial autocorrelation of PM2.5 concentrations in the cities of China with the spatial autocorrelation model. A correlation coefficient to examine the correlativity of PM2.5 concentrations and 23 characteristic variables for 190 cities in China in 2014, from which the most important ones were chosen, and then a regression model was built to further reveal the social and economic factors affecting PMg.g concentrations. Results： （1） The Hu Huanyong Line and the Yangtze River were the E-W divide and S-N divide between high and low values of China. （2） The PM2.5 concentrations shows great seasonal variation, which is high in autumn and winter but low in spring and summer. The monthly average shows a U-shaped pattern, and daily average presents a periodic and impulse-shaped change. （3） PM2.5 concentrations had a distinct characteristic of spatial agglomeration. The North China Plain was the predominant region of agglomeration, and the southeastern coastal area had stable good air quality.展开更多
Formation and evolution of rural settlement patterns in Lianzhou City,Guangdong Province were analyzed from the perspective of space and time,on the basis of its gazetteer and relevant historical data.The results show...Formation and evolution of rural settlement patterns in Lianzhou City,Guangdong Province were analyzed from the perspective of space and time,on the basis of its gazetteer and relevant historical data.The results show that Lianzhou was first founded in the sixth year of Yuanding Period of the Western Han Dynasty,and its development could be roughly classified into 6 stages according to the construction of south–north traffic lines and regional development progress,and it witnessed the fastest development in the Ming and Qing Dynasty.In terms of spatial distribution,rural settlements in the local area show spatial continuity,Lianzhou Town is the core of rural settlement growth in the city,and towns with the most concentrated rural settlements in all stages are located in central-west and northeast parts of the city,and those with lower density of rural settlements are mostly located in minority regions in the north and mountainous areas in the east.On the basis of the above facts,the paper studies the influence of natural geological conditions,immigrant,traffic,economic development and ethnic composition on the establishment and development of rural settlements in Lianzhou City.展开更多
Empirical Orthogonal Function (EOF) was performed to investigate spatial variation in January precipitation over Pakistan using ground observed mean monthly precipitation data from 1950-2000 with a combination of grid...Empirical Orthogonal Function (EOF) was performed to investigate spatial variation in January precipitation over Pakistan using ground observed mean monthly precipitation data from 1950-2000 with a combination of gridded reanalysis data of sea level pressure (SLP) and 500 hPa geopotential height. The leading EOF mode captures 37.51% of the total variance and the spatial-temporal variability of January precipitation was consistent in the study area. The temporal changes explicate non-periodic interannual variability and some tacit interdecadal variation. The anomalous condition is more prominent along the western bordering mountains and northern high mountainous region than any other region of Pakistan. Based on results the study reveals spatial-temporal variation in January precipitation and possible links with global teleconnections located both in the proximity as well as in the remote areas from the study locus.展开更多
As a significant city in the Yangtze River Delta regions,Hefei has experienced rapid changes in the sources of air pollution due to its high-speed economic development and urban expansion.However,there has been limite...As a significant city in the Yangtze River Delta regions,Hefei has experienced rapid changes in the sources of air pollution due to its high-speed economic development and urban expansion.However,there has been limited research in recent years on the spatial-temporal distribution and emission of its atmospheric pollutants.To address this,this study conducted mobile observations of urban roads using the Mobile-DOAS instrument from June 2021 to May 2022.The monitoring results exhibit a favourable consistent with TROPOMI satellite data and ground monitoring station data.Temporally,there were pronounced seasonal variations in air pollutants.Spatially,high concentration of HCHO and NO_(2)were closely associated with traffic congestion on roadways,while heightened SO_(2)levels were attributed to winter heating and industrial emissions.The study also revealed that with the implementation of road policies,the average vehicle speed increased by 95.4%,while the NO concentration decreased by 54.4%.In the estimation of urban NO_(x)emission flux,it was observed that in temporal terms,compared with inventory data,the emissions calculated viamobile measurements exhibitedmore distinct seasonal patterns,with the highest emission rate of 349 g/sec in winter and the lowest of 142 g/sec in summer.In spatial terms,the significant difference in emissions between the inner and outer ring roads also suggests the presence of the city’s primary NO_(x)emission sources in the area between these two rings.This study offers data support for formulating the next phase of air pollution control measures in urban areas.展开更多
Allogeneic hematopoietic cell transplantation(allo-HCT) remains a cornerstone therapy for severe hematologic malignancies, offering a potential cure when conventional therapies are ineffective. However, not all patien...Allogeneic hematopoietic cell transplantation(allo-HCT) remains a cornerstone therapy for severe hematologic malignancies, offering a potential cure when conventional therapies are ineffective. However, not all patients are suitable recipients of allo-HCT, particularly the elderly patients and those with high comorbidity burdens.Furthermore, patients who develop relapse or graft failure after initial transplantation encounter additional challenges when evaluated for a second transplant.展开更多
Objective To explore the impact of mergers and acquisitions(M&A)on the innovation performance of the companies from both a patent perspective and a financial perspective by taking the case of M&A Company J as ...Objective To explore the impact of mergers and acquisitions(M&A)on the innovation performance of the companies from both a patent perspective and a financial perspective by taking the case of M&A Company J as an example.Methods The literature research method,patent data analysis method,and financial data analysis method were used.Results:The M&A has a positive impact on the innovation performance of Company J,and the results from the patent perspective and the financial perspective are consistent.Results and Conclusion The literature research method,patent data analysis method,and financial data analysis method were used.The M&A has a positive impact on the innovation performance of Company J,and the results from the patent perspective and the financial perspective are consistent.展开更多
Hardship The Double Take column looks at a single topic from an African and Chinese perspective.This month,we explore whether enduring hardship is still a necessary path to growth in a changing world.
In the current situation of decelerating economic expansion,examining the digital economy(DE)as a novel economic model is beneficial for the local economy’s sustainable and high-quality development(HQD).We analyzed p...In the current situation of decelerating economic expansion,examining the digital economy(DE)as a novel economic model is beneficial for the local economy’s sustainable and high-quality development(HQD).We analyzed panel data from the Yellow River(YR)region from 2013 to 2021 and discovered notable spatial variances in the composite index and coupling coordination of the two systems.Specifically,the downstream region exhibited the highest coupling coordination,while the upstream region had the lowest.We identified that favorable factors such as economic development,innovation,industrial upgrading,and government intervention can bolster the coupling.Our findings provide a valuable framework for promoting DE and HQD in the YR region.展开更多
Sodium-sulfur(Na-S)batteries are considered as a promising successor to the next-generation of high-capacity,low-cost and environmentally friendly sulfur-based battery systems.However,Na-S batteries still suffer from ...Sodium-sulfur(Na-S)batteries are considered as a promising successor to the next-generation of high-capacity,low-cost and environmentally friendly sulfur-based battery systems.However,Na-S batteries still suffer from the“shuttle effect”and sluggish ion transport kinetics due to the dissolution of sodium polysulfides and poor conductivity of sulfur.MXenes,as 2D transition metal carbides/nitrides,have exhibited excellent conductivity,diverse structure and tunable surface groups,particularly playing a crucial role in inhibiting polysulfide shuttle and sodium dendrite growth.In this review,achievements and advancements of MXene-based Na-S batteries are discussed,including applications of a sulfur cathode,separator,interlayer between separator and cathode,and sodium anode.In the end,perspectives and challenges on the future development of MXene-based materials in Na-S batteries are proposed.展开更多
Objective:This study aims to explore the experiences of social alienation among adolescents with depression,providing practical This study aims to explore the experiences of social alienation among adolescents with de...Objective:This study aims to explore the experiences of social alienation among adolescents with depression,providing practical This study aims to explore the experiences of social alienation among adolescents with depression,providing practical guidance for improving their interpersonal relationships and facilitating their reintegration into society.Methods:This qualitative research was conducted following the conventional content analysis method.20 adolescents with depression were employed to select from June to August 2024 for face-to-face semi-structured interviews.The collected data were analyzed using Colaizzi's seven-step method.Results:Three themes and eight sub-themes were analyzed and identified:individual level(feelings of helplessness and powerlessness,cognitive distortion,avoidance and withdrawal),family level(lack of family awareness,family conflict),social level(limitations of academic stress and social circle,lack and degradation of skills,generalization of virtual reality,social“stigma”).Conclusion:Adolescents with depression experience complex social alienation.Healthcare providers should enhance their self-awareness and social adaptation skills,improve family dynamics,and provide a comprehensive range of services and services to help them to cope with the challenges of depression.Healthcare providers should enhance their self-awareness and social adaptation skills,improve family dynamics,strengthen communication,bolster family support systems,and collaborate to develop comprehensive social networks and psychological services.This will create a supportive social atmosphere to help adolescents gradually alleviate their feelings of social alienation.展开更多
Driven by the goal of carbon neutrality,prefabricated buildings,as an important form of green construction,have become a key focus in the study of lifecycle carbon footprint management.Based on this,this paper starts ...Driven by the goal of carbon neutrality,prefabricated buildings,as an important form of green construction,have become a key focus in the study of lifecycle carbon footprint management.Based on this,this paper starts from the perspective of carbon footprint and combines the digital and visual advantages of BIM technology to construct a green evaluation system for prefabricated buildings.It explores the carbon emissions in each stage of the building and proposes corresponding improvement measures,aiming to provide necessary references for the low-carbon transformation of prefabricated buildings.展开更多
Accurate traffic flow prediction has a profound impact on modern traffic management. Traffic flow has complex spatial-temporal correlations and periodicity, which poses difficulties for precise prediction. To address ...Accurate traffic flow prediction has a profound impact on modern traffic management. Traffic flow has complex spatial-temporal correlations and periodicity, which poses difficulties for precise prediction. To address this problem, a Multi-head Self-attention and Spatial-Temporal Graph Convolutional Network (MSSTGCN) for multiscale traffic flow prediction is proposed. Firstly, to capture the hidden traffic periodicity of traffic flow, traffic flow is divided into three kinds of periods, including hourly, daily, and weekly data. Secondly, a graph attention residual layer is constructed to learn the global spatial features across regions. Local spatial-temporal dependence is captured by using a T-GCN module. Thirdly, a transformer layer is introduced to learn the long-term dependence in time. A position embedding mechanism is introduced to label position information for all traffic sequences. Thus, this multi-head self-attention mechanism can recognize the sequence order and allocate weights for different time nodes. Experimental results on four real-world datasets show that the MSSTGCN performs better than the baseline methods and can be successfully adapted to traffic prediction tasks.展开更多
Parental educational anxiety has become a social symptom in China,and rural primary school students’mothers exhibit unique educational anxieties due to their special living environment.Based on interviews with 10 rur...Parental educational anxiety has become a social symptom in China,and rural primary school students’mothers exhibit unique educational anxieties due to their special living environment.Based on interviews with 10 rural primary school students’mothers,five typical educational anxiety experiences were selected for analysis,and themes such as rural life burden,children’s learning habits,mothers’educational expectations,mothers’educational methods,mothers’emotional state,deviation between reality and expectations,homework guidance ability,mothers’educational level,and attitudes towards children’s future development were refined.The root causes of educational anxiety among rural primary school students’mothers include the deviation between children’s actual performance and mothers’educational expectations,the sense of disparity under social comparison,physical and mental exhaustion caused by role overload,anxiety triggered by excessive economic burden,and a sense of powerlessness towards children’s educational outcomes.To alleviate the educational anxiety of rural primary school students’mothers,mothers should actively adjust themselves,fathers should actively participate in their children’s education,society should create a healthy atmosphere,and schools should strengthen family education guidance.展开更多
Ecological network(EN)identification and optimization is an essential research tool for safeguarding regional ecological security patterns and planning territorial space.Especially for the ecologically fragile inland ...Ecological network(EN)identification and optimization is an essential research tool for safeguarding regional ecological security patterns and planning territorial space.Especially for the ecologically fragile inland river basins,EN optimization is of significance in ensuring regional ecological security and virtuous cycle of ecosystems.In addition,EN is a dynamically changing structural system that is more applicable to the regional development by optimizing it from comprehensive future development perspective.EN of Shiyang River basin was constructed on account of the circuit theory,and land use/cover changes(LUCC)of the basin in 2035 was predicted by PLUS model,so as to explore the ecological conservation priorities and formulate optimization strategies.54 ecological sources(ESs)were identified,covering an area of 12,198 km^(2),mainly in the southern basin.133 ecological corridors(ECs)with an area of 3,176.92 km^(2)were extracted.38 ecological pinchpoints(EPs)and 22 ecological barriers(EBs)were identified respectively,which were mainly distributed in the lower basin.To effectively enhance the connectivity of EN in Minqin County,which has the worst ecological environment,we added five stepping stones based on the Ant Forest project.In addition,the optimal EPS is selected according to the development and limitation needs of inland river basins and the threat degree of warning points(WPs)under different scenarios.Scientific and reasonable optimization of future urban layout to prevent WPs can effectively alleviate the contradiction between ecological protection and economic development.The study is intended to provide basis for ecological sustainable development and rational planning territorial space in Shiyang River basin,as well as opinion for EN optimization in inland river basin.展开更多
The red cultural resources in rural areas bear the heavy historical and spiritual strength,and are the key rich ore and spiritual pillar in the field of education.This study discusses the connotation of red culture re...The red cultural resources in rural areas bear the heavy historical and spiritual strength,and are the key rich ore and spiritual pillar in the field of education.This study discusses the connotation of red culture resources and the current situation of educating people,and then analyzes how to integrate interdisciplinary learning theory into red culture to enhance the value of educating people.On this basis,it proposes to explore the educational path of optimizing rural red cultural resources from an interdisciplinary perspective by integrating multi-disciplinary knowledge and red cultural resources.展开更多
On the evening of May 3Oth,the parallel forum"Equality and Inclusiveness&Harmonious Coexistence:Multi-dimensional Narratives of Civilisations from Writers'Perspective",as part of the 4th Dialogue on ...On the evening of May 3Oth,the parallel forum"Equality and Inclusiveness&Harmonious Coexistence:Multi-dimensional Narratives of Civilisations from Writers'Perspective",as part of the 4th Dialogue on Exchanges and Mutual Learning among Civilisations,was held in Dunhuang.The forum was organised by the China Writers Association and co-organised by China National Publications Import&Export(Group)Corporation.展开更多
The natural visibility graph method has been widely used in physiological signal analysis,but it fails to accurately handle signals with data points below the baseline.Such signals are common across various physiologi...The natural visibility graph method has been widely used in physiological signal analysis,but it fails to accurately handle signals with data points below the baseline.Such signals are common across various physiological measurements,including electroencephalograph(EEG)and functional magnetic resonance imaging(fMRI),and are crucial for insights into physiological phenomena.This study introduces a novel method,the baseline perspective visibility graph(BPVG),which can analyze time series by accurately capturing connectivity across data points both above and below the baseline.We present the BPVG construction process and validate its performance using simulated signals.Results demonstrate that BPVG accurately translates periodic,random,and fractal signals into regular,random,and scale-free networks respectively,exhibiting diverse degree distribution traits.Furthermore,we apply BPVG to classify Alzheimer’s disease(AD)patients from healthy controls using EEG data and identify non-demented adults at varying dementia risk using resting-state fMRI(rs-fMRI)data.Utilizing degree distribution entropy derived from BPVG networks,our results exceed the best accuracy benchmark(77.01%)in EEG analysis,especially at channels F4(78.46%)and O1(81.54%).Additionally,our rs-fMRI analysis achieves a statistically significant classification accuracy of 76.74%.These findings highlight the effectiveness of BPVG in distinguishing various time series types and its practical utility in EEG and rs-fMRI analysis for early AD detection and dementia risk assessment.In conclusion,BPVG’s validation across both simulated and real data confirms its capability to capture comprehensive information from time series,irrespective of baseline constraints,providing a novel method for studying neural physiological signals.展开更多
Spatial-temporal traffic prediction technology is crucial for network planning,resource allocation optimizing,and user experience improving.With the development of virtual network operators,multi-operator collaboratio...Spatial-temporal traffic prediction technology is crucial for network planning,resource allocation optimizing,and user experience improving.With the development of virtual network operators,multi-operator collaborations,and edge computing,spatial-temporal traffic data has taken on a distributed nature.Consequently,noncentralized spatial-temporal traffic prediction solutions have emerged as a recent research focus.Currently,the majority of research typically adopts federated learning methods to train traffic prediction models distributed on each base station.This method reduces additional burden on communication systems.However,this method has a drawback:it cannot handle irregular traffic data.Due to unstable wireless network environments,device failures,insufficient storage resources,etc.,data missing inevitably occurs during the process of collecting traffic data.This results in the irregular nature of distributed traffic data.Yet,commonly used traffic prediction models such as Recurrent Neural Networks(RNN)and Long Short-Term Memory(LSTM)typically assume that the data is complete and regular.To address the challenge of handling irregular traffic data,this paper transforms irregular traffic prediction into problems of estimating latent variables and generating future traffic.To solve the aforementioned problems,this paper introduces split learning to design a structured distributed learning framework.The framework comprises a Global-level Spatial structure mining Model(GSM)and several Nodelevel Generative Models(NGMs).NGM and GSM represent Seq2Seq models deployed on the base station and graph neural network models deployed on the cloud or central controller.Firstly,the time embedding layer in NGM establishes the mapping relationship between irregular traffic data and regular latent temporal feature variables.Secondly,GSM collects statistical feature parameters of latent temporal feature variables from various nodes and executes graph embedding for spatial-temporal traffic data.Finally,NGM generates future traffic based on latent temporal and spatial feature variables.The introduction of the time attention mechanism enhances the framework’s capability to handle irregular traffic data.Graph attention network introduces spatially correlated base station traffic feature information into local traffic prediction,which compensates for missing information in local irregular traffic data.The proposed framework effectively addresses the distributed prediction issues of irregular traffic data.By testing on real world datasets,the proposed framework improves traffic prediction accuracy by 35%compared to other commonly used distributed traffic prediction methods.展开更多
Atomically precise metal nanoclusters are an emerging type of nanomaterial which has diverse interfacial metal-ligand coordination motifs that can significantly affect their physicochemical properties and functionalit...Atomically precise metal nanoclusters are an emerging type of nanomaterial which has diverse interfacial metal-ligand coordination motifs that can significantly affect their physicochemical properties and functionalities.Among that,Cu nanoclusters have been gaining continuous increasing research attentions,thanks to the low cost,diversified structures,and superior catalytic performance for various reactions.In this review,we first summarize the recent progress regarding the synthetic methods of atomically precise Cu nanoclusters and the coordination modes between Cu and several typical ligands and then discuss the catalytic applications of these Cu nanoclusters with some explicit examples to explain the atomical-level structure-performance relationship.Finally,the current challenges and future research perspectives with some critical thoughts are elaborated.We hope this review can not only provide a whole picture of the current advances regarding the synthesis and catalytic applications of atomically precise Cu nanoclusters,but also points out some future research visions in this rapidly booming field.展开更多
基金supported by the Hong Kong Research Grants Council Theme-based Research Scheme(Grant No.T12-716/22-R)Innovation and Technology Commission grant for State Key Laboratory of Liver Research(Grant No.ITC PD/17-9)University Development Fund of The University of Hong Kong,and Loke Yew Endowed Professorship award.I.O.L.Ng is Loke Yew Professor in Pathology.
文摘Hepatocellular carcinoma(HCC)is a pressing global health problem and is the sixth most common cancer and the third leading cause of cancer mortality worldwide.Despite continuous advances in treatment modalities,the 5-year survival rate is low with a high propensity for recurrence and metastasis1.This clinical challenge in treating HCC is largely attributed to the heterogeneity and intrinsic therapy resistance of cancer stem cells(CSCs),which are a subpopulation of cells with self-renewal capability and multidirectional differentiation potential to induce tumorigenicity2.The behavior and maintenance of CSCs are not autonomous but critically dependent on the complex bidirectional crosstalk between CSCs and the tumor immune microenvironment(TIME)1.In this review we first summarize the recent progress in characterizing CSCs and the interactions between CSCs and the TIME in HCC.Next,we discuss the emerging therapeutic strategies targeting CSC populations with the ongoing challenges.Finally,we give our perspectives on the future directions in HCC CSC research.
基金Major Program of the Natural Science Foundation of China,No.41590842
文摘Haze pollution has become a severe environmental problem in the daily life of the people in China. PM2.s makes a significant contribution to poor air quality. The spatio-temporal features of China＇s PM2.s concentrations should be investigated. This paper, based on ob- served data from 945 newly located monitoring sites in 2014 and industrial working population data obtained from International Standard Industrial Classification （ISIC）, reveals the spa- tio-temporal variations of PM2.5 concentrations in China and the correlations among different industries. We tested the spatial autocorrelation of PM2.5 concentrations in the cities of China with the spatial autocorrelation model. A correlation coefficient to examine the correlativity of PM2.5 concentrations and 23 characteristic variables for 190 cities in China in 2014, from which the most important ones were chosen, and then a regression model was built to further reveal the social and economic factors affecting PMg.g concentrations. Results： （1） The Hu Huanyong Line and the Yangtze River were the E-W divide and S-N divide between high and low values of China. （2） The PM2.5 concentrations shows great seasonal variation, which is high in autumn and winter but low in spring and summer. The monthly average shows a U-shaped pattern, and daily average presents a periodic and impulse-shaped change. （3） PM2.5 concentrations had a distinct characteristic of spatial agglomeration. The North China Plain was the predominant region of agglomeration, and the southeastern coastal area had stable good air quality.
基金Sponsored by Fundamental Research Funds for the Central Universities(GK201303006)National Natural Science Foundation of China(41171139)Key Projects of Humanities and Social Sciences Research Base of Guangdong Colleges and Universities(09JDXM84001)
文摘Formation and evolution of rural settlement patterns in Lianzhou City,Guangdong Province were analyzed from the perspective of space and time,on the basis of its gazetteer and relevant historical data.The results show that Lianzhou was first founded in the sixth year of Yuanding Period of the Western Han Dynasty,and its development could be roughly classified into 6 stages according to the construction of south–north traffic lines and regional development progress,and it witnessed the fastest development in the Ming and Qing Dynasty.In terms of spatial distribution,rural settlements in the local area show spatial continuity,Lianzhou Town is the core of rural settlement growth in the city,and towns with the most concentrated rural settlements in all stages are located in central-west and northeast parts of the city,and those with lower density of rural settlements are mostly located in minority regions in the north and mountainous areas in the east.On the basis of the above facts,the paper studies the influence of natural geological conditions,immigrant,traffic,economic development and ethnic composition on the establishment and development of rural settlements in Lianzhou City.
文摘Empirical Orthogonal Function (EOF) was performed to investigate spatial variation in January precipitation over Pakistan using ground observed mean monthly precipitation data from 1950-2000 with a combination of gridded reanalysis data of sea level pressure (SLP) and 500 hPa geopotential height. The leading EOF mode captures 37.51% of the total variance and the spatial-temporal variability of January precipitation was consistent in the study area. The temporal changes explicate non-periodic interannual variability and some tacit interdecadal variation. The anomalous condition is more prominent along the western bordering mountains and northern high mountainous region than any other region of Pakistan. Based on results the study reveals spatial-temporal variation in January precipitation and possible links with global teleconnections located both in the proximity as well as in the remote areas from the study locus.
基金supported by the National Natural Science Foundation of China(Nos.U19A2044,42105132,42030609,41975037,and 42105133)the National Key Research and Development Program of China(No.2022YFC3703502)+1 种基金the Plan for Anhui Major Provincial Science&Technology Project(No.202203a07020003)Hefei Ecological Environment Bureau Project(No.2020BFFFD01804).
文摘As a significant city in the Yangtze River Delta regions,Hefei has experienced rapid changes in the sources of air pollution due to its high-speed economic development and urban expansion.However,there has been limited research in recent years on the spatial-temporal distribution and emission of its atmospheric pollutants.To address this,this study conducted mobile observations of urban roads using the Mobile-DOAS instrument from June 2021 to May 2022.The monitoring results exhibit a favourable consistent with TROPOMI satellite data and ground monitoring station data.Temporally,there were pronounced seasonal variations in air pollutants.Spatially,high concentration of HCHO and NO_(2)were closely associated with traffic congestion on roadways,while heightened SO_(2)levels were attributed to winter heating and industrial emissions.The study also revealed that with the implementation of road policies,the average vehicle speed increased by 95.4%,while the NO concentration decreased by 54.4%.In the estimation of urban NO_(x)emission flux,it was observed that in temporal terms,compared with inventory data,the emissions calculated viamobile measurements exhibitedmore distinct seasonal patterns,with the highest emission rate of 349 g/sec in winter and the lowest of 142 g/sec in summer.In spatial terms,the significant difference in emissions between the inner and outer ring roads also suggests the presence of the city’s primary NO_(x)emission sources in the area between these two rings.This study offers data support for formulating the next phase of air pollution control measures in urban areas.
基金supported by National Natural Science Foundation of China (No. 82370215).
文摘Allogeneic hematopoietic cell transplantation(allo-HCT) remains a cornerstone therapy for severe hematologic malignancies, offering a potential cure when conventional therapies are ineffective. However, not all patients are suitable recipients of allo-HCT, particularly the elderly patients and those with high comorbidity burdens.Furthermore, patients who develop relapse or graft failure after initial transplantation encounter additional challenges when evaluated for a second transplant.
文摘Objective To explore the impact of mergers and acquisitions(M&A)on the innovation performance of the companies from both a patent perspective and a financial perspective by taking the case of M&A Company J as an example.Methods The literature research method,patent data analysis method,and financial data analysis method were used.Results:The M&A has a positive impact on the innovation performance of Company J,and the results from the patent perspective and the financial perspective are consistent.Results and Conclusion The literature research method,patent data analysis method,and financial data analysis method were used.The M&A has a positive impact on the innovation performance of Company J,and the results from the patent perspective and the financial perspective are consistent.
文摘Hardship The Double Take column looks at a single topic from an African and Chinese perspective.This month,we explore whether enduring hardship is still a necessary path to growth in a changing world.
基金supported by the National Office for Philosophy and Social Sciences(grant reference 22&ZD067).
文摘In the current situation of decelerating economic expansion,examining the digital economy(DE)as a novel economic model is beneficial for the local economy’s sustainable and high-quality development(HQD).We analyzed panel data from the Yellow River(YR)region from 2013 to 2021 and discovered notable spatial variances in the composite index and coupling coordination of the two systems.Specifically,the downstream region exhibited the highest coupling coordination,while the upstream region had the lowest.We identified that favorable factors such as economic development,innovation,industrial upgrading,and government intervention can bolster the coupling.Our findings provide a valuable framework for promoting DE and HQD in the YR region.
基金supported by the National Natural Science Foundation of China(Nos.51972198 and 61633015)the Natural Science Foundation of Shandong Province(No.ZR2020JQ19)+1 种基金Taishan Scholars Program of Shandong Province(No.ts20190908)Shenzhen Fundamental Research Program(No.JCYJ20190807093405503).
文摘Sodium-sulfur(Na-S)batteries are considered as a promising successor to the next-generation of high-capacity,low-cost and environmentally friendly sulfur-based battery systems.However,Na-S batteries still suffer from the“shuttle effect”and sluggish ion transport kinetics due to the dissolution of sodium polysulfides and poor conductivity of sulfur.MXenes,as 2D transition metal carbides/nitrides,have exhibited excellent conductivity,diverse structure and tunable surface groups,particularly playing a crucial role in inhibiting polysulfide shuttle and sodium dendrite growth.In this review,achievements and advancements of MXene-based Na-S batteries are discussed,including applications of a sulfur cathode,separator,interlayer between separator and cathode,and sodium anode.In the end,perspectives and challenges on the future development of MXene-based materials in Na-S batteries are proposed.
基金2024 Annual project of National Social Science Foundation“Research on Problem Identification and Governance Countermeasures of Minor Mental Health Network Support”(Project No.:24BXW044).
文摘Objective:This study aims to explore the experiences of social alienation among adolescents with depression,providing practical This study aims to explore the experiences of social alienation among adolescents with depression,providing practical guidance for improving their interpersonal relationships and facilitating their reintegration into society.Methods:This qualitative research was conducted following the conventional content analysis method.20 adolescents with depression were employed to select from June to August 2024 for face-to-face semi-structured interviews.The collected data were analyzed using Colaizzi's seven-step method.Results:Three themes and eight sub-themes were analyzed and identified:individual level(feelings of helplessness and powerlessness,cognitive distortion,avoidance and withdrawal),family level(lack of family awareness,family conflict),social level(limitations of academic stress and social circle,lack and degradation of skills,generalization of virtual reality,social“stigma”).Conclusion:Adolescents with depression experience complex social alienation.Healthcare providers should enhance their self-awareness and social adaptation skills,improve family dynamics,and provide a comprehensive range of services and services to help them to cope with the challenges of depression.Healthcare providers should enhance their self-awareness and social adaptation skills,improve family dynamics,strengthen communication,bolster family support systems,and collaborate to develop comprehensive social networks and psychological services.This will create a supportive social atmosphere to help adolescents gradually alleviate their feelings of social alienation.
文摘Driven by the goal of carbon neutrality,prefabricated buildings,as an important form of green construction,have become a key focus in the study of lifecycle carbon footprint management.Based on this,this paper starts from the perspective of carbon footprint and combines the digital and visual advantages of BIM technology to construct a green evaluation system for prefabricated buildings.It explores the carbon emissions in each stage of the building and proposes corresponding improvement measures,aiming to provide necessary references for the low-carbon transformation of prefabricated buildings.
基金supported by the National Natural Science Foundation of China(Grant Nos.62472149,62376089,62202147)Hubei Provincial Science and Technology Plan Project(2023BCB04100).
文摘Accurate traffic flow prediction has a profound impact on modern traffic management. Traffic flow has complex spatial-temporal correlations and periodicity, which poses difficulties for precise prediction. To address this problem, a Multi-head Self-attention and Spatial-Temporal Graph Convolutional Network (MSSTGCN) for multiscale traffic flow prediction is proposed. Firstly, to capture the hidden traffic periodicity of traffic flow, traffic flow is divided into three kinds of periods, including hourly, daily, and weekly data. Secondly, a graph attention residual layer is constructed to learn the global spatial features across regions. Local spatial-temporal dependence is captured by using a T-GCN module. Thirdly, a transformer layer is introduced to learn the long-term dependence in time. A position embedding mechanism is introduced to label position information for all traffic sequences. Thus, this multi-head self-attention mechanism can recognize the sequence order and allocate weights for different time nodes. Experimental results on four real-world datasets show that the MSSTGCN performs better than the baseline methods and can be successfully adapted to traffic prediction tasks.
基金Hunan Provincial Social Science Foundation“A Phenomenological Study on the Educational Life Experiences of Rural Young Teachers”(20YBA017)。
文摘Parental educational anxiety has become a social symptom in China,and rural primary school students’mothers exhibit unique educational anxieties due to their special living environment.Based on interviews with 10 rural primary school students’mothers,five typical educational anxiety experiences were selected for analysis,and themes such as rural life burden,children’s learning habits,mothers’educational expectations,mothers’educational methods,mothers’emotional state,deviation between reality and expectations,homework guidance ability,mothers’educational level,and attitudes towards children’s future development were refined.The root causes of educational anxiety among rural primary school students’mothers include the deviation between children’s actual performance and mothers’educational expectations,the sense of disparity under social comparison,physical and mental exhaustion caused by role overload,anxiety triggered by excessive economic burden,and a sense of powerlessness towards children’s educational outcomes.To alleviate the educational anxiety of rural primary school students’mothers,mothers should actively adjust themselves,fathers should actively participate in their children’s education,society should create a healthy atmosphere,and schools should strengthen family education guidance.
基金funded by the National Natural Science Foundation of China(Grant No.42101276)。
文摘Ecological network(EN)identification and optimization is an essential research tool for safeguarding regional ecological security patterns and planning territorial space.Especially for the ecologically fragile inland river basins,EN optimization is of significance in ensuring regional ecological security and virtuous cycle of ecosystems.In addition,EN is a dynamically changing structural system that is more applicable to the regional development by optimizing it from comprehensive future development perspective.EN of Shiyang River basin was constructed on account of the circuit theory,and land use/cover changes(LUCC)of the basin in 2035 was predicted by PLUS model,so as to explore the ecological conservation priorities and formulate optimization strategies.54 ecological sources(ESs)were identified,covering an area of 12,198 km^(2),mainly in the southern basin.133 ecological corridors(ECs)with an area of 3,176.92 km^(2)were extracted.38 ecological pinchpoints(EPs)and 22 ecological barriers(EBs)were identified respectively,which were mainly distributed in the lower basin.To effectively enhance the connectivity of EN in Minqin County,which has the worst ecological environment,we added five stepping stones based on the Ant Forest project.In addition,the optimal EPS is selected according to the development and limitation needs of inland river basins and the threat degree of warning points(WPs)under different scenarios.Scientific and reasonable optimization of future urban layout to prevent WPs can effectively alleviate the contradiction between ecological protection and economic development.The study is intended to provide basis for ecological sustainable development and rational planning territorial space in Shiyang River basin,as well as opinion for EN optimization in inland river basin.
基金Supported by the Research Project of Jiangsu Second Normal University"Research on the Construction and Application of Economics MOOC(Micro Course)from the Perspective of Ideological and Political Education JSSNUJXGG 2023YB08".
文摘The red cultural resources in rural areas bear the heavy historical and spiritual strength,and are the key rich ore and spiritual pillar in the field of education.This study discusses the connotation of red culture resources and the current situation of educating people,and then analyzes how to integrate interdisciplinary learning theory into red culture to enhance the value of educating people.On this basis,it proposes to explore the educational path of optimizing rural red cultural resources from an interdisciplinary perspective by integrating multi-disciplinary knowledge and red cultural resources.
文摘On the evening of May 3Oth,the parallel forum"Equality and Inclusiveness&Harmonious Coexistence:Multi-dimensional Narratives of Civilisations from Writers'Perspective",as part of the 4th Dialogue on Exchanges and Mutual Learning among Civilisations,was held in Dunhuang.The forum was organised by the China Writers Association and co-organised by China National Publications Import&Export(Group)Corporation.
基金supported by the National Key Research and Development Program of China(Grant No.2023YFF1204803)the Natural Science Foundation of Jiangsu Province,China(Grant No.BK20190736)+1 种基金the Fundamental Research Funds for the Central Universities(Grant No.NJ2024029)the National Natural Science Foundation of China(Grant Nos.81701346 and 62201265).
文摘The natural visibility graph method has been widely used in physiological signal analysis,but it fails to accurately handle signals with data points below the baseline.Such signals are common across various physiological measurements,including electroencephalograph(EEG)and functional magnetic resonance imaging(fMRI),and are crucial for insights into physiological phenomena.This study introduces a novel method,the baseline perspective visibility graph(BPVG),which can analyze time series by accurately capturing connectivity across data points both above and below the baseline.We present the BPVG construction process and validate its performance using simulated signals.Results demonstrate that BPVG accurately translates periodic,random,and fractal signals into regular,random,and scale-free networks respectively,exhibiting diverse degree distribution traits.Furthermore,we apply BPVG to classify Alzheimer’s disease(AD)patients from healthy controls using EEG data and identify non-demented adults at varying dementia risk using resting-state fMRI(rs-fMRI)data.Utilizing degree distribution entropy derived from BPVG networks,our results exceed the best accuracy benchmark(77.01%)in EEG analysis,especially at channels F4(78.46%)and O1(81.54%).Additionally,our rs-fMRI analysis achieves a statistically significant classification accuracy of 76.74%.These findings highlight the effectiveness of BPVG in distinguishing various time series types and its practical utility in EEG and rs-fMRI analysis for early AD detection and dementia risk assessment.In conclusion,BPVG’s validation across both simulated and real data confirms its capability to capture comprehensive information from time series,irrespective of baseline constraints,providing a novel method for studying neural physiological signals.
基金supported by the Beijing Natural Science Foundation(Certificate Number:L234025).
文摘Spatial-temporal traffic prediction technology is crucial for network planning,resource allocation optimizing,and user experience improving.With the development of virtual network operators,multi-operator collaborations,and edge computing,spatial-temporal traffic data has taken on a distributed nature.Consequently,noncentralized spatial-temporal traffic prediction solutions have emerged as a recent research focus.Currently,the majority of research typically adopts federated learning methods to train traffic prediction models distributed on each base station.This method reduces additional burden on communication systems.However,this method has a drawback:it cannot handle irregular traffic data.Due to unstable wireless network environments,device failures,insufficient storage resources,etc.,data missing inevitably occurs during the process of collecting traffic data.This results in the irregular nature of distributed traffic data.Yet,commonly used traffic prediction models such as Recurrent Neural Networks(RNN)and Long Short-Term Memory(LSTM)typically assume that the data is complete and regular.To address the challenge of handling irregular traffic data,this paper transforms irregular traffic prediction into problems of estimating latent variables and generating future traffic.To solve the aforementioned problems,this paper introduces split learning to design a structured distributed learning framework.The framework comprises a Global-level Spatial structure mining Model(GSM)and several Nodelevel Generative Models(NGMs).NGM and GSM represent Seq2Seq models deployed on the base station and graph neural network models deployed on the cloud or central controller.Firstly,the time embedding layer in NGM establishes the mapping relationship between irregular traffic data and regular latent temporal feature variables.Secondly,GSM collects statistical feature parameters of latent temporal feature variables from various nodes and executes graph embedding for spatial-temporal traffic data.Finally,NGM generates future traffic based on latent temporal and spatial feature variables.The introduction of the time attention mechanism enhances the framework’s capability to handle irregular traffic data.Graph attention network introduces spatially correlated base station traffic feature information into local traffic prediction,which compensates for missing information in local irregular traffic data.The proposed framework effectively addresses the distributed prediction issues of irregular traffic data.By testing on real world datasets,the proposed framework improves traffic prediction accuracy by 35%compared to other commonly used distributed traffic prediction methods.
基金supported by the open funds of Key Laboratory of Functional Inorganic Material Chemistry (Heilongjiang University), Ministry of Education, Chinathe funding from Guangdong Natural Science Funds (No. 2023A0505050107)。
文摘Atomically precise metal nanoclusters are an emerging type of nanomaterial which has diverse interfacial metal-ligand coordination motifs that can significantly affect their physicochemical properties and functionalities.Among that,Cu nanoclusters have been gaining continuous increasing research attentions,thanks to the low cost,diversified structures,and superior catalytic performance for various reactions.In this review,we first summarize the recent progress regarding the synthetic methods of atomically precise Cu nanoclusters and the coordination modes between Cu and several typical ligands and then discuss the catalytic applications of these Cu nanoclusters with some explicit examples to explain the atomical-level structure-performance relationship.Finally,the current challenges and future research perspectives with some critical thoughts are elaborated.We hope this review can not only provide a whole picture of the current advances regarding the synthesis and catalytic applications of atomically precise Cu nanoclusters,but also points out some future research visions in this rapidly booming field.
