Background:The Yangtze River floodplain provides important wintering habitats for Hooded Cranes(Grus monacha) in China.Fluctuations in the water level change foraging habitat and food availability,affecting their temp...Background:The Yangtze River floodplain provides important wintering habitats for Hooded Cranes(Grus monacha) in China.Fluctuations in the water level change foraging habitat and food availability,affecting their temporal-spatial patterns of foraging activities.It is of considerable importance to investigate the effect of these fluctuations on food availability for wintering Hooded Cranes and their foraging response to these changes.Understanding their behavior patterns is beneficial in protecting the wintering crane population and restoring their wintering habitats.Methods:A field survey of the winter behavior of cranes was carried out at Shengjin Lake from November in 2013 to April in 2014.Habitat variables,as well as the spatial distribution and behavior patterns of wintering cranes at their foraging sites during five stages of water level fluctuation were collected.Based on this data we analyzed the relationship of foraging behavior relative to water level fluctuations and habitat types.Results:The foraging habitats used by Hooded Cranes varied at the different water level stages.As the water level decreased,the use of meadows and mudflats increased.When the water dropped to its lowest level,the use by the Hooded Crane in the mudflats reached a peak.There were statistically significant differences in time budget in the three types of habitats over the five stages of the water level.In the mudflats,the foraging behavior and maintenance behavior varied significantly with the water level,while the alert behavior showed little variation.Analysis of a generalized linear model showed that the five water level stages and three habitat types had a significant effect on foraging behavior,while the combined effect of these two variables was significant on the foraging time budget and the length of foraging activity of the Hooded Crane.Conclusions:With the decrease in the water level,the use of mudflats by Hooded Cranes increased correspondingly.Food availability in different habitats was affected by changes in the water level.The Hooded Crane adjusted its foraging patterns and made full use of the three available types of habitat in order to acquire enough food in response to fluctuations in the water level.展开更多
Temporal-spatial differentiation characteristics of green development efficiency in 17 prefecture-level cities of Shandong Province during 2005-2016 were studied by using SBM-undesirable model and spatial auto-correla...Temporal-spatial differentiation characteristics of green development efficiency in 17 prefecture-level cities of Shandong Province during 2005-2016 were studied by using SBM-undesirable model and spatial auto-correlation analysis.Results showed that ① green development efficiency considering unexpected output could more accurately represent the real cost of regional development,while lower green development efficiency considering unexpected output and traditional green development efficiency illustrated that Shandong Province has spent a lot of resources and environment in the long-term development process.② Green development efficiency of Shandong Province during 2005-2016 showed the change characteristics of "peak-valley-peak-valley",and standard deviation and coefficient of variation of green development efficiency showed fluctuation characteristics in the research period.③ Green development efficiency of Shandong Province had obvious spatial differentiation characteristics,and its polarization differentiation was obvious.展开更多
The accuracy of photovoltaic(PV)power prediction is significantly influenced by meteorological and environmental factors.To enhance ultra-short-term forecasting precision,this paper proposes an interpretable feedback ...The accuracy of photovoltaic(PV)power prediction is significantly influenced by meteorological and environmental factors.To enhance ultra-short-term forecasting precision,this paper proposes an interpretable feedback prediction method based on a parallel dual-stream Temporal Convolutional Network-Bidirectional Long Short-Term Memory(TCN-BiLSTM)architecture incorporating a spatiotemporal attention mechanism.Firstly,during data preprocessing,the optimal historical time window is determined through autocorrelation analysis while highly correlated features are selected as model inputs using Pearson correlation coefficients.Subsequently,a parallel dual-stream TCN-BiLSTM model is constructed where the TCN branch extracts localized transient features and the BiLSTM branch captures long-term periodic patterns,with spatiotemporal attention dynamically weighting spatiotemporal dependencies.Finally,Shapley Additive explanations(SHAP)additive analysis quantifies feature contribution rates and provides optimization feedback to the model.Validation using operational data from a PV power station in Northeast China demonstrates that compared to conventional deep learning models,the proposed method achieves a 17.6%reduction in root mean square error(RMSE),a 5.4%decrease in training time consumption,and a 4.78%improvement in continuous ranked probability score(CRPS),exhibiting significant advantages in both prediction accuracy and generalization capability.This approach enhances the application effectiveness of ultra-short-term PV power forecasting while simultaneously improving prediction accuracy and computational efficiency.展开更多
As metropolitan areas expand spatially,they encounter constraints imposed by the fixed daily time budget.Rail transit enhances transport efficiency,reduces costs,and facilitates the formation of a“transit economic fi...As metropolitan areas expand spatially,they encounter constraints imposed by the fixed daily time budget.Rail transit enhances transport efficiency,reduces costs,and facilitates the formation of a“transit economic field”centered on rail networks,thereby alleviating such temporal-spatial pressures.This paper adopts an integrated temporal-spatial analytical framework.Following a conceptual clarification of the transit economic field,it dissects the mechanisms through which rail transit improves mobility and examines how this field influences urban spatial patterns,temporal dynamics,and their interrelationships.It constructs a theoretical framework to explain the co-development of transit economic fields and cities,supplemented by empirical case studies.The key findings are as follows:Firstly,the transit economic field represents a high-density development model that expands both horizontally and vertically around rail networks.It mitigates temporal-spatial conflicts.Secondly,with rail networks as the core,the field integrates diverse spatial functions,facilitating the establishment of economic connections and stabilizing temporal-spatial relationships.Thirdly,the transit economic field contributes to the preservation of urban natural ecosystems and enhances urban livability.Overall,this research can provide insights for promoting rail transit-oriented development transitions in large cities and urban agglomerations.展开更多
Xishui National Forest Park in Heilongjiang Province hosts China's most pristine temperate forests and serves as a key site for ecotourism and forest therapy.However,the emission patterns of phytoncides(key bio ac...Xishui National Forest Park in Heilongjiang Province hosts China's most pristine temperate forests and serves as a key site for ecotourism and forest therapy.However,the emission patterns of phytoncides(key bio active compounds) remain poorly understood,limiting their therapeutic application.This study provides the first comprehensive characterization of spatiotemporal dynamics in airborne phytoncides and their synergistic interactions with environmental factors throughout the autumn-early spring seasonal transition in a temperate forest ecosystem.We analyzed the compositional dynamics of phytoncides and terpenoid content variations using thermal desorption-gas chromatography-mass spectrometry(TD-GC-MS) from September 2024 to March 2025.This period encompassed seasonal transitions from autumn to early spring,including diurnal variations in September and snowfall events in November.The method demonstrated detection limits(LODs) ranging from 1.35 to 5.33 ng m-3 and quantification limits(LOQs) from 4.09 to 16.15 ng m-3.Our results revealed pronounced seasonal fluctuations in phytoncide composition.In September,terpenoids,esters,alcohols,and alkanes displayed a diurnal "decrease-increase" trend,whereas aldehydes and ketones peaked at midday.Notably,esters and alcohols were undetectable in November and January.By January,terpenoids reached their lowest proportion(0.17±0.02%) at noon.Five terpenoids(α-pinene,myrcene,D-limonene,camphene,p-cymene) were detected in September,four(α-pinene,D-limonene,camphene,p-cymene) in November,two(D-limonene,p-cymene) in January,and only p-cymene in March.The total concentration and emission rate of the five terpenoids peaked in September afternoons at 1961.58±106.67 ng m^(-3) and653.86±35.56 ng m^(-3) h^(-1),respectively.Nocturnal emissions(32131.95±2522.21 ng m^(-3)) significantly surpassed daytime levels(14473.04±958.49 ng m^(-3)),with emission rates escalating from 1447.30±95.85 ng m^(-3) h^(-1)(day) to 5355.33±420.37 ng m^(-3) h^(-1)(night),marking a3.7-fold increase.Snowfall dramatically elevated terpenoid concentrations(pre-snowfall:158.58±14.12 ng m^(-3);post-snowfall:1080.57±57.76 ng m^(-3)) and emission rates(pre-snowfall:52.86±4.71 ng m^(-3) h^(-1);post-snowfall:360.19±19.25 ng m^(-3) h^(-1)),reflecting a 6.8-fold surge.This study underscores the profound influence of light intensity,seasonal shifts,and climatic conditions on airborne phytoncide levels,offering a scientific foundation for optimizing forest therapy and ecotourism strategies.展开更多
Under the influence of human activities,landscape fragmentation in the Wei River Basin(WRB)has become increasingly severe.Upstream development has intensified soil erosion,and industrial and agricultural pollution in ...Under the influence of human activities,landscape fragmentation in the Wei River Basin(WRB)has become increasingly severe.Upstream development has intensified soil erosion,and industrial and agricultural pollution in the middle reaches has degraded water quality.Rapid urbanization has further caused habitat fragmentation and biodiversity loss.Collectively,these challenges threaten human well-being and hinder sustainable development,making the construction and optimization of an ecological security pattern(ESP)urgently necessary.However,existing studies often fail to systematically integrate future landscape ecological risk(LER)assessment with ESP optimization.This study evaluated regional LER using the“ecological patches-ecological resistance surface(ERS)-ecological corridor”framework,combined with land-use predictions under three development scenarios,and optimized the ESP by adjusting the ERS and extracting ecological corridors.The results indicate that the LER in the WRB follows an“inverted N”distribution,with low-risk areas concentrated in forested mountain regions and high-risk areas mainly in cultivated land subject to intensive human activity.Across future scenarios,ESPs showed fewer ecological breakpoints and improved landscape connectivity than the 2020 baseline.Scenario-based differences emerged in the spatial configuration of ERS adjustments,with the ecological protection scenario yielding the lowest LER and most favorable ESP.This study demonstrates the deep integration of multi-scenario simulation with LER assessment,providing a new framework for ESP optimization.The findings have guiding significance for ecological protection and coordinated development in the WRB and offer a novel paradigm for sustainable development in ecologically fragile basins worldwide.展开更多
Traditional Chinese medicine(TCM)is a holistic medical system that classifies and treats diseases based on the concept of patterns.These patterns describe the pathophysiological process of a disease at a specific stag...Traditional Chinese medicine(TCM)is a holistic medical system that classifies and treats diseases based on the concept of patterns.These patterns describe the pathophysiological process of a disease at a specific stage,reflecting both external signs and internal features.TCM patterns are central to pattern differentiation,treatment,clinical practice,and theoretical development in TCM.However,scientific explanation of TCM patterns remains limited because of subjective diagnostic criteria,the absence of a standardized experimental medical system,and unclear biological mechanisms,which restrict the modernization and globalization of TCM.Addressing challenges such as strong subjectivity in diagnosis,lack of standardized experimental systems,and unclear biological mechanisms is necessary to clarify the scientific meaning of TCM patterns and to provide technical approaches for the modernization and globalization of TCM.A strategy focused on“pathogenic factors,genetic predisposition,and disease progression stages”was adopted.This approach included the following:(Ⅰ)constructing disease-pattern integrated biological models with animal models,organoids,and multi-organ chips;(Ⅱ)applying multi-omics technologies,such as spatial omics,single-cell omics,and dynamic metabolic flux omics;(Ⅲ)using artificial intelligence(AI)and big data for data integration and prediction of pattern evolution;and(Ⅳ)validating formula–pattern associations through the“pattern differentiation through formula efficacy”approach.These strategies directly address the main obstacles in TCM pattern research by providing objective,quantifiable,and reproducible methodologies.Constructing disease-pattern integrated models enabled cross-scale research platforms.Applying multi-omics technologies allowed analysis of complex biological bases.AI and big data approaches addressed challenges related to heterogeneous data.The“formula-based pattern differentiation”approach supported precise interventions and the development of new drugs.This interdisciplinary framework advances TCM pattern research by moving from empirical description to objective quantification.By integrating innovative approaches,the study establishes a foundation for systematic,evidence-based TCM diagnosis and treatment,supporting accuracy and promoting international recognition and modernization of TCM.The study shows that combining multi-omics technologies,AI-driven data analysis,and disease-pattern models enables objective quantification of TCM patterns and clarifies their biological mechanisms.展开更多
Dear Editor,Understanding patterns of species diversity is a primary research focus in macroecology,with its distribution patterns having been described and theoretically validated on a global scale(Peters et al.,2016...Dear Editor,Understanding patterns of species diversity is a primary research focus in macroecology,with its distribution patterns having been described and theoretically validated on a global scale(Peters et al.,2016;Sonne et al.,2025).Numerous studies have found that species richness of different taxa tends to decrease with increasing elevation and is modulated by latitudinal gradients(Peters et al.,2016;Dolson et al.,2024).This principle provides a crucial scientific basis for regional conservation planning.However,it still exhibits significant variations across different mountain ranges and taxa.展开更多
Urban forests are essential components of green infrastructure,however,rapid urbanization-induced changes in landscape patterns may affect their ecosystem services through complex ecological processes.A total of 184 s...Urban forests are essential components of green infrastructure,however,rapid urbanization-induced changes in landscape patterns may affect their ecosystem services through complex ecological processes.A total of 184 sample plots in the built-up areas of Nanchang,China,were used as research sites.Urbanization intensities were categorized by the rate of impervious surface area,and forest types were classified into landscape and relaxation forest,attached forest(AF),road forest(RF),and ecological public welfare forest.This study aimed to explore the spatial variations in vegetation characteristics and landscape pattern indices of different forest types under rapid urbanization.The results indicated that the largest patch index(LPI),aggregation index(AI),and percentage of landscape(PLAND)in RF and AF were lower than those in the other forest types(p<0.05).With increasing urbanization intensity,the mean perimeter-area ratio increased by 130.84%,whereas the PLAND,LPI,and AI decreased by 22−86%(p<0.05).Redundancy analysis and variation partitioning suggested that the interpretation rate of landscape pattern indices for variations in vegetation characteristics increased from low to heavy urbanization areas.Especially,the landscape shape index,patch connection index,PLAND,and mean patch size were significantly correlated with vegetation characteristics(e.g.,tree richness,herb coverage,and tree height).In the future,appropriate landscape layout superiority cases should be considered in different urbanization areas and forest types;for instance,increasing the patch connection index will beneficially improve the diversity of trees and herbs in heavy urbanization areas and the RF.This study serves as a reference for maximizing the ecosystem services of urban forests.展开更多
The performance of data restore is one of the key indicators of user experience for backup storage systems.Compared to the traditional offline restore process,online restore reduces downtime during backup restoration,...The performance of data restore is one of the key indicators of user experience for backup storage systems.Compared to the traditional offline restore process,online restore reduces downtime during backup restoration,allowing users to operate on already restored files while other files are still being restored.This approach improves availability during restoration tasks but suffers from a critical limitation:inconsistencies between the access sequence and the restore sequence.In many cases,the file a user needs to access at a given moment may not yet be restored,resulting in significant delays and poor user experience.To this end,we present Histore,which builds on the user’s historical access sequence to schedule the restore sequence,in order to reduce users’access delayed time.Histore includes three restore approaches:(i)the frequency-based approach,which restores files based on historical file access frequencies and prioritizes ensuring the availability of frequently accessed files;(ii)the graph-based approach,which preferentially restores the frequently accessed files as well as their correlated files based on historical access patterns,and(iii)the trie-based approach,which restores particular files based on both users’real-time and historical access patterns to deduce and restore the files to be accessed in the near future.We implement a prototype of Histore and evaluate its performance from multiple perspectives.Trace-driven experiments on two datasets show that Histore significantly reduces users’delay time by 4-700×with only 1.0%-14.5%additional performance overhead.展开更多
Enhancing the kinetic stability of glasses typically requires deepening their thermodynamic stability,which increases structural rigidity and degrades ductility;decoupling these properties remains a major challenge.He...Enhancing the kinetic stability of glasses typically requires deepening their thermodynamic stability,which increases structural rigidity and degrades ductility;decoupling these properties remains a major challenge.Here,we demonstrate that spatial patterning in metallic glasses produces exceptional kinetic ultrastability that coexists with a thermodynamically metastable,high-energy state and excellent plasticity.Guided by atomistic simulations using replica exchange molecular dynamics and machine learning interatomic potentials,we reveal that oxygen,through reaction-diffusion-coupled pattern dynamics,self-organizes into oxygen-centered pinned structures(OPSs)that serve as localized kinetic constraints.These motifs drastically slow structural relaxation,delivering kinetic stability comparable to ultrastable glasses even as the system retains the high inherent energy of rapidly quenched states.The OPSs’topology yields a spatially uniform activation of plastic events,promoting strain delocalization under mechanical load.By geometrically tailoring oxygen patterns,we increase the glass transition onset temperature(Tonset)by about 200 K with negligible loss of deformability.Our findings establish a practicable paradigm for decoupling kinetic and thermodynamic stability and point to a scalable,additive route for designing amorphous materials that combine hyperstability with plasticity.展开更多
Owing to the exceptional optoelectronic properties,metal halide perovskites have emerged as leading semiconductor materials for next-generation display technologies,providing perovskite light-emitting diodes(Pe LEDs)g...Owing to the exceptional optoelectronic properties,metal halide perovskites have emerged as leading semiconductor materials for next-generation display technologies,providing perovskite light-emitting diodes(Pe LEDs)great potential for high-quality color displays with a wide color gamut and pure color emission.Although laboratory-scale Pe LEDs have achieved neartheoretical efficiencies,challenges such as achieving uniform large-area films,improving material stability,and enhancing patterning precision remain barriers to commercialization.This review presents a systematic analysis of scalable manufacturing and precision patterning strategies for Pe LEDs,focusing on their applications in large-area lighting and full-color displays.Fabrication methods are categorized into film deposition techniques(spin-coating,blade-coating,and thermal evaporation)and patterning strategies,including top-down(photolithography,laser/e-beam lithography,and nanoimprinting)and bottom-up(patterned crystal growth,inkjet printing,and electrohydrodynamic jet printing)approaches.In this review,we discuss the advantages and limitations of each strategy,highlight current challenges,and outlook possible pathways towards scalable,high-performance Pe LEDs for advanced optoelectronic applications.展开更多
Tajikistan represents a core region of the biodiversity hotspot in Central Asian mountains and has exceptional vascular plant diversity.However,the species diversity of the country faces urgent conservation challenges...Tajikistan represents a core region of the biodiversity hotspot in Central Asian mountains and has exceptional vascular plant diversity.However,the species diversity of the country faces urgent conservation challenges.There has been a lack of a comprehensive and multidimensional assessment to inform strategic conservation planning.Therefore,this study integrated 4 key biodiversity indices including species richness(SR),phylogenetic diversity(PD),threatened species richness(TSR),and endemic species richness(ESR)to map species diversity distribution patterns,identify conservation gaps,and elucidate their effects of climatic factors.This study revealed that species diversity shows a clear trend of decreasing from the western region to the eastern region of Tajikistan.The central–western mountains(specifically the Gissar-Darvasian and Zeravshanian regions)emerge as irreplaceable biodiversity hotspots.However,we found a severe spatial mismatch between these priority areas and the existing protected areas(PAs).Protection coverage for all hotspots was alarmingly low,ranging from 31.00%to 38.00%.Consequently,a critical 64.80%of integrated priority areas fall outside of the current PAs,representing a major conservation gap.This study identified precipitation seasonality and isothermality as the principal drivers,collectively explaining over 50.00%of the diversity variation and suggesting high vulnerability to hydrological shifts.Furthermore,we detected significant geographic sampling bias in the public biodiversity databases,with the most critical hotspot being systematically under-sampled.This study provides a robust scientific basis for conservation action,highlighting the urgent need to strategically expand PAs in the under-protected southwestern region and to mitigate critical sampling gaps through targeted data digitization and field surveys.These measures are indispensable for securing Tajikistan’s unique biodiversity and achieving the Kunming-Montreal Global Biodiversity Framework Target 3(“30×30 Protection”).展开更多
Wide-field mesoscopy provides the capabilities of cortex-wide field of view(FOV),cellular resolution and high frame rate for neuronal imaging in the mouse brain.However,inherent background fluorescence degrades the im...Wide-field mesoscopy provides the capabilities of cortex-wide field of view(FOV),cellular resolution and high frame rate for neuronal imaging in the mouse brain.However,inherent background fluorescence degrades the image quality and hinders neuronal signal extraction.To address this problem,we first introduce a cortex-wide,high-resolution lineillumination mesoscope with a moving slit designed for in vivo mouse brain imaging.This system achieves a 6.6×6.6 mm FOV,microscale cellular resolution,a high frame rate of 10 Hz,as well as the background rejection ability.Furthermore,we integrated patterned illumination into the system to enhance the background suppression.Experimental results show that the proposed system successfully captures neurodynamics in the living mouse brain.Compared with conventional wide-field mesoscopes,the cortex-wide patterned line-illumination mesoscope(PLIM)achieves a threefold increase in the signal-to-background ratio(SBR).With patterned illumination integrated,the SBR enhancement further reaches four-anda-half-fold.展开更多
A design idea for single-component metamaterial plates is proposed to achieve the thermal stability of flexural wave bandgap by the perforated and pre-curved patterns.The band structure analysis suggests that perforat...A design idea for single-component metamaterial plates is proposed to achieve the thermal stability of flexural wave bandgap by the perforated and pre-curved patterns.The band structure analysis suggests that perforation can release part of the in-plane thermal expansion to weaken the softening effect of thermal stress.Introducing precurved components to the perforated structure will stop the decrement of the bandgap frequency in thermal environment,and even make the frequency higher with appropriate structural parameters.The bending stiffness of the heated plate is enhanced by the thermal deflection induced stiffening effect of the pre-curved components.The segmented pre-curved component presents a strong ability to resist the thermal influence on the flexural wave bandgap.A simplified model is established for the local structure of the precurved component.The theoretical calculations explain the thermally induced frequency increment of the bandgap and the discrepancy in the thermal response between the two pre-curved models.The transmittance of flexural wave validates the effectiveness of the proposed design.展开更多
The development of pattern-based traditional Chinese medicine(TCM)compound preparations constitutes a core domain that represents the principle of pattern differentiation-based treatment,a hallmark of TCM.However,the ...The development of pattern-based traditional Chinese medicine(TCM)compound preparations constitutes a core domain that represents the principle of pattern differentiation-based treatment,a hallmark of TCM.However,the field has long been constrained by scientific and regulatory challenges in animal modeling,efficacy evaluation,and clinical positioning.This article proposes a new research and development(R&D)paradigm strategically based on human use experience(HUE)and centered on the patient as the key to overcoming these bottlenecks and achieving high-quality progress.We systematically dissect the traditional problems in this field and demonstrate the pivotal role of high-quality HUE in enabling precise clinical positioning and optimizing R&D pathways(e.g.,applying for exemptions from non-clinical studies).HUE guides the implementation of the“pattern-symptom integration”model.Furthermore,we detail the implementation of the patient-centered concept throughout the process of clinical trial design,collection of patients’experience data,clinical outcome assessment,and benefit-risk assessment.The integrative application of artificial intelligence in the R&D of pattern-based TCM drugs is also specifically explored.By synthesizing the“TCM theory,HUE,and clinical trials”evidence system,this article aims to provide a systematic strategic framework for establishing an R&D pathway that adheres to the intrinsic principles of TCM while simultaneously meeting modern scientific standards.展开更多
Objectives:To explore the use of a traditional Chinese medicine(TCM)pattern scale as an outcome measure to evaluate the management of patients with chronic low back pain(CLBP).Methods:A total of 204 participants were ...Objectives:To explore the use of a traditional Chinese medicine(TCM)pattern scale as an outcome measure to evaluate the management of patients with chronic low back pain(CLBP).Methods:A total of 204 participants were recruited and randomly allocated into three CLBP treatment groups:Tuina only,physiotherapy only,and a combined physiotherapy+Tuina group.All participants were assessed for treatment outcomes using the TCM pattern scale as a substudy to a randomized controlled trial in which the Visual Analog Scale(VAS)was the primary outcome measure.TCM pattern scores were recorded by non-TCM research assistants who were trained to administer a TCM pattern questionnaire developed by the authors in collaboration with TCM experts.Results:Most participants(83%)were classified as having kidney deficiency pattern as the primary TCM pattern at baseline.All three intervention groups showed a significant decrease in overall TCM pattern score at month 2(M2)and month 5(M5).However,when the nimodipine method was applied,none of the three treatment arms showed a statistically significant change in the effective rate,even though the parent study reported a significant decrease in VAS scores in all treatment arms.Conclusion:This study found improvements in both the dominant TCM pattern score and the overall TCM pattern score for each group.These findings suggest that TCM pattern diagnosis,including entities recognized in International Classification of Diseases,11th Revision(ICD)-11,may be used as a quantitative outcome measure to reflect response to TCM-based intervention.The TCM pattern scale reported here may potentially be applied in other chronic pain studies involving TCM patterns.Further studies are warranted to validate this scale in other clinical conditions.展开更多
Existing studies on the Regional Comprehensive Economic Partnership(RCEP)mainly focused on institutional features,macro-economic impacts,and trade-network structures,while its geographic attributes and their implicati...Existing studies on the Regional Comprehensive Economic Partnership(RCEP)mainly focused on institutional features,macro-economic impacts,and trade-network structures,while its geographic attributes and their implications remain underexplored.Taking the RCEP as a case,this paper examines how the FTA reshapes China’s trade geography and validates these effects with an enhanced GTAP model,providing an empirical basis for advancing trade-geography theory.Key findings include:(1)RCEP significantly reduces regional trade costs.After full implementation of the agreement,the average tariffs among member countries will decrease to 40.5%of the pre-implementation level,while import and export trade facilitation levels improve by 34.3%and 29.6%,respectively.However,these improvements exhibit marked regional disparities.(2)RCEP asymmetrically promotes China’s foreign trade growth,with stronger import stimulation than export expansion,alongside significant product-specific variations.(3)The agreement reshapes China’s trade geography,driving a 7.66%increase in intra-RCEP trade while reducing extra-RCEP trade by 0.80%.(4)The restructuring of China’s trade patterns under RCEP emerges from the complex interplay of trade creation,diversion,and crowding-out effects.Accordingly,China should further harmonize regional tariff schedules,enhance trade-facilitation mechanisms,strengthen industrial competitiveness and expand multilateral partnerships.展开更多
BACKGROUND Drug utilization research has an important role in assisting the healthcare administration to know,compute,and refine the prescription whose principal objective is to enable the rational use of drugs.Resear...BACKGROUND Drug utilization research has an important role in assisting the healthcare administration to know,compute,and refine the prescription whose principal objective is to enable the rational use of drugs.Research in developing nations relating to the cost of treatment is scarce when compared with developed countries.Thus,the drug utilization research studies from developing nations are most needed,and their number has been growing.AIM To evaluate patterns of utilization of antipsychotic drugs and direct medical cost analysis in patients newly diagnosed with schizophrenia.METHODS The present study was observational in type and based on a retrospective cohort to evaluate patterns of utilization of antipsychotic drugs using World Health Organization(WHO)core prescribing indicators and anatomical therapeutic chemical/defined daily dose indicators.We also calculated direct medical costs for a period of 6 months.RESULTS This study has found that atypical antipsychotics are the mainstay of treatment for schizophrenia in every age group and subcategories of schizophrenia.The evaluation based on WHO prescribing indicators showed a low average number of drugs per prescription and low prescribing frequency of antipsychotics from the National List of Essential Medicines 2015 and the WHO Essential Medicines List 2019.The total mean drug cost of our study was 1396 Indian rupees.The total mean cost due to the investigation in our study was 1017.34 Indian rupees.Therefore,the total mean direct medical cost incurred on patients in our study was 4337.28 Indian rupees.CONCLUSION The information from the present study can be used for reviewing and updating treatment policy at the institutional level.展开更多
The Qaidam Basin,a typical alpine arid inland basin on the northern Qinghai-Xizang Plateau,China,hosts wetland ecosystems that are strongly constrained by topography and extreme climate.These ecosystems exhibit pronou...The Qaidam Basin,a typical alpine arid inland basin on the northern Qinghai-Xizang Plateau,China,hosts wetland ecosystems that are strongly constrained by topography and extreme climate.These ecosystems exhibit pronounced spatiotemporal heterogeneity and fragmented distribution patterns,rendering them highly sensitive to environmental change.This study integrated Sentinel-2 remote sensing imagery with the SedInConnect model to delineate wetland patch distributions and calculate the Index of Connectivity(IC)values across the basin.Based on IC values,we stratified field sampling sites into high-,moderate-,and lowconnectivity gradient groups to analyze the relationships among plant community characteristics,vegetation spatial patterns,and wetland connectivity in the Qaidam Basin.Partial Least Squares Path Modeling(PLSPM)was further employed to quantify the driving mechanisms underlying wetland vegetation characteristics.The results revealed that wetland connectivity across the basin was generally low,with IC values up to 1.32 and displaying a west-to-east decreasing gradient.The west and northwest were characterized by relatively continuous high-connectivity wetland networks,while fragmented and low-connectivity wetlands predominated in the east and southeast.Connectivity regulated wetland vegetation patterns primarily by affecting patch size,fragmentation,and internal adjacency.High-connectivity areas had higher class area(CA),largest patch index(LPI),and area-weighted mean patch size(AREA_AM)than low-connectivity areas.Connectivity had the strongest effect on vegetation coverage,which declined sharply from 87.577%in highconnectivity areas to 12.152%in low-connectivity areas.Meanwhile,species diversity showed a moderately negative response to connectivity changes,whereas species evenness remained relatively unaffected.PLS-PM explained 78.300%and 67.500%of the variance in vegetation community and vegetation pattern,respectively.Climate played a dominant role in shaping vegetation characteristics,with significant negative effects on both vegetation community and pattern.Topography influenced vegetation indirectly through climate,and connectivity was influenced by both drivers and exerted positive effects on vegetation community and pattern.This study reveals the multi-pathway driving mechanisms underlying vegetation pattern formation in alpine wetlands,providing a theoretical foundation and decision-support framework for the scientific conservation and adaptive management of wetlands in the Qaidam Basin.展开更多
基金supported by the National Natural Science Foundation of China(Grant no.31172117,31472020)the Graduate Student Innovation Research Projects of Anhui University(YQH100269)
文摘Background:The Yangtze River floodplain provides important wintering habitats for Hooded Cranes(Grus monacha) in China.Fluctuations in the water level change foraging habitat and food availability,affecting their temporal-spatial patterns of foraging activities.It is of considerable importance to investigate the effect of these fluctuations on food availability for wintering Hooded Cranes and their foraging response to these changes.Understanding their behavior patterns is beneficial in protecting the wintering crane population and restoring their wintering habitats.Methods:A field survey of the winter behavior of cranes was carried out at Shengjin Lake from November in 2013 to April in 2014.Habitat variables,as well as the spatial distribution and behavior patterns of wintering cranes at their foraging sites during five stages of water level fluctuation were collected.Based on this data we analyzed the relationship of foraging behavior relative to water level fluctuations and habitat types.Results:The foraging habitats used by Hooded Cranes varied at the different water level stages.As the water level decreased,the use of meadows and mudflats increased.When the water dropped to its lowest level,the use by the Hooded Crane in the mudflats reached a peak.There were statistically significant differences in time budget in the three types of habitats over the five stages of the water level.In the mudflats,the foraging behavior and maintenance behavior varied significantly with the water level,while the alert behavior showed little variation.Analysis of a generalized linear model showed that the five water level stages and three habitat types had a significant effect on foraging behavior,while the combined effect of these two variables was significant on the foraging time budget and the length of foraging activity of the Hooded Crane.Conclusions:With the decrease in the water level,the use of mudflats by Hooded Cranes increased correspondingly.Food availability in different habitats was affected by changes in the water level.The Hooded Crane adjusted its foraging patterns and made full use of the three available types of habitat in order to acquire enough food in response to fluctuations in the water level.
文摘Temporal-spatial differentiation characteristics of green development efficiency in 17 prefecture-level cities of Shandong Province during 2005-2016 were studied by using SBM-undesirable model and spatial auto-correlation analysis.Results showed that ① green development efficiency considering unexpected output could more accurately represent the real cost of regional development,while lower green development efficiency considering unexpected output and traditional green development efficiency illustrated that Shandong Province has spent a lot of resources and environment in the long-term development process.② Green development efficiency of Shandong Province during 2005-2016 showed the change characteristics of "peak-valley-peak-valley",and standard deviation and coefficient of variation of green development efficiency showed fluctuation characteristics in the research period.③ Green development efficiency of Shandong Province had obvious spatial differentiation characteristics,and its polarization differentiation was obvious.
基金funded by the National Natural Science Foundation of China(NSFC)(No.62066024)funded by Basic Scientific Research Projects of Higher Education Institutions in Liaoning Province(LJ212411632063)the National Undergraduate Training Program for Innovation and Entrepreneurship(S202511632045).
文摘The accuracy of photovoltaic(PV)power prediction is significantly influenced by meteorological and environmental factors.To enhance ultra-short-term forecasting precision,this paper proposes an interpretable feedback prediction method based on a parallel dual-stream Temporal Convolutional Network-Bidirectional Long Short-Term Memory(TCN-BiLSTM)architecture incorporating a spatiotemporal attention mechanism.Firstly,during data preprocessing,the optimal historical time window is determined through autocorrelation analysis while highly correlated features are selected as model inputs using Pearson correlation coefficients.Subsequently,a parallel dual-stream TCN-BiLSTM model is constructed where the TCN branch extracts localized transient features and the BiLSTM branch captures long-term periodic patterns,with spatiotemporal attention dynamically weighting spatiotemporal dependencies.Finally,Shapley Additive explanations(SHAP)additive analysis quantifies feature contribution rates and provides optimization feedback to the model.Validation using operational data from a PV power station in Northeast China demonstrates that compared to conventional deep learning models,the proposed method achieves a 17.6%reduction in root mean square error(RMSE),a 5.4%decrease in training time consumption,and a 4.78%improvement in continuous ranked probability score(CRPS),exhibiting significant advantages in both prediction accuracy and generalization capability.This approach enhances the application effectiveness of ultra-short-term PV power forecasting while simultaneously improving prediction accuracy and computational efficiency.
基金Hubei Social Science Foundation Project“Research on the Relationship Between Rail Transit and Intensive and Sustainable Development of Large Cities”(2020052)。
文摘As metropolitan areas expand spatially,they encounter constraints imposed by the fixed daily time budget.Rail transit enhances transport efficiency,reduces costs,and facilitates the formation of a“transit economic field”centered on rail networks,thereby alleviating such temporal-spatial pressures.This paper adopts an integrated temporal-spatial analytical framework.Following a conceptual clarification of the transit economic field,it dissects the mechanisms through which rail transit improves mobility and examines how this field influences urban spatial patterns,temporal dynamics,and their interrelationships.It constructs a theoretical framework to explain the co-development of transit economic fields and cities,supplemented by empirical case studies.The key findings are as follows:Firstly,the transit economic field represents a high-density development model that expands both horizontally and vertically around rail networks.It mitigates temporal-spatial conflicts.Secondly,with rail networks as the core,the field integrates diverse spatial functions,facilitating the establishment of economic connections and stabilizing temporal-spatial relationships.Thirdly,the transit economic field contributes to the preservation of urban natural ecosystems and enhances urban livability.Overall,this research can provide insights for promoting rail transit-oriented development transitions in large cities and urban agglomerations.
基金supported by the Key Research and Development Plan Project of Heilongjiang Province (2022ZX02C13)。
文摘Xishui National Forest Park in Heilongjiang Province hosts China's most pristine temperate forests and serves as a key site for ecotourism and forest therapy.However,the emission patterns of phytoncides(key bio active compounds) remain poorly understood,limiting their therapeutic application.This study provides the first comprehensive characterization of spatiotemporal dynamics in airborne phytoncides and their synergistic interactions with environmental factors throughout the autumn-early spring seasonal transition in a temperate forest ecosystem.We analyzed the compositional dynamics of phytoncides and terpenoid content variations using thermal desorption-gas chromatography-mass spectrometry(TD-GC-MS) from September 2024 to March 2025.This period encompassed seasonal transitions from autumn to early spring,including diurnal variations in September and snowfall events in November.The method demonstrated detection limits(LODs) ranging from 1.35 to 5.33 ng m-3 and quantification limits(LOQs) from 4.09 to 16.15 ng m-3.Our results revealed pronounced seasonal fluctuations in phytoncide composition.In September,terpenoids,esters,alcohols,and alkanes displayed a diurnal "decrease-increase" trend,whereas aldehydes and ketones peaked at midday.Notably,esters and alcohols were undetectable in November and January.By January,terpenoids reached their lowest proportion(0.17±0.02%) at noon.Five terpenoids(α-pinene,myrcene,D-limonene,camphene,p-cymene) were detected in September,four(α-pinene,D-limonene,camphene,p-cymene) in November,two(D-limonene,p-cymene) in January,and only p-cymene in March.The total concentration and emission rate of the five terpenoids peaked in September afternoons at 1961.58±106.67 ng m^(-3) and653.86±35.56 ng m^(-3) h^(-1),respectively.Nocturnal emissions(32131.95±2522.21 ng m^(-3)) significantly surpassed daytime levels(14473.04±958.49 ng m^(-3)),with emission rates escalating from 1447.30±95.85 ng m^(-3) h^(-1)(day) to 5355.33±420.37 ng m^(-3) h^(-1)(night),marking a3.7-fold increase.Snowfall dramatically elevated terpenoid concentrations(pre-snowfall:158.58±14.12 ng m^(-3);post-snowfall:1080.57±57.76 ng m^(-3)) and emission rates(pre-snowfall:52.86±4.71 ng m^(-3) h^(-1);post-snowfall:360.19±19.25 ng m^(-3) h^(-1)),reflecting a 6.8-fold surge.This study underscores the profound influence of light intensity,seasonal shifts,and climatic conditions on airborne phytoncide levels,offering a scientific foundation for optimizing forest therapy and ecotourism strategies.
基金supported by the National Natural Science Foundation of China[Grant No.42361040].
文摘Under the influence of human activities,landscape fragmentation in the Wei River Basin(WRB)has become increasingly severe.Upstream development has intensified soil erosion,and industrial and agricultural pollution in the middle reaches has degraded water quality.Rapid urbanization has further caused habitat fragmentation and biodiversity loss.Collectively,these challenges threaten human well-being and hinder sustainable development,making the construction and optimization of an ecological security pattern(ESP)urgently necessary.However,existing studies often fail to systematically integrate future landscape ecological risk(LER)assessment with ESP optimization.This study evaluated regional LER using the“ecological patches-ecological resistance surface(ERS)-ecological corridor”framework,combined with land-use predictions under three development scenarios,and optimized the ESP by adjusting the ERS and extracting ecological corridors.The results indicate that the LER in the WRB follows an“inverted N”distribution,with low-risk areas concentrated in forested mountain regions and high-risk areas mainly in cultivated land subject to intensive human activity.Across future scenarios,ESPs showed fewer ecological breakpoints and improved landscape connectivity than the 2020 baseline.Scenario-based differences emerged in the spatial configuration of ERS adjustments,with the ecological protection scenario yielding the lowest LER and most favorable ESP.This study demonstrates the deep integration of multi-scenario simulation with LER assessment,providing a new framework for ESP optimization.The findings have guiding significance for ecological protection and coordinated development in the WRB and offer a novel paradigm for sustainable development in ecologically fragile basins worldwide.
基金supported by the National Key Research and Development Program of China(2022YFC3500100)the National Natural Science Foundation of China(82230126 and U24A20800)+3 种基金Noncommunicable Chronic Diseases-National Science and Technology Major Project(2023ZD0502600 and 2023ZD0502601)National Science Fund for Excellent Young Scholars(82222075)the Incubation Program for the Science and Technology Development of Chinese Medicine Guangdong Laboratory(HQL2024PZ045 and HQCML-C-2024003)Guangdong Provincial Key Laboratory of Pattern and Formula(2022B1212010012).
文摘Traditional Chinese medicine(TCM)is a holistic medical system that classifies and treats diseases based on the concept of patterns.These patterns describe the pathophysiological process of a disease at a specific stage,reflecting both external signs and internal features.TCM patterns are central to pattern differentiation,treatment,clinical practice,and theoretical development in TCM.However,scientific explanation of TCM patterns remains limited because of subjective diagnostic criteria,the absence of a standardized experimental medical system,and unclear biological mechanisms,which restrict the modernization and globalization of TCM.Addressing challenges such as strong subjectivity in diagnosis,lack of standardized experimental systems,and unclear biological mechanisms is necessary to clarify the scientific meaning of TCM patterns and to provide technical approaches for the modernization and globalization of TCM.A strategy focused on“pathogenic factors,genetic predisposition,and disease progression stages”was adopted.This approach included the following:(Ⅰ)constructing disease-pattern integrated biological models with animal models,organoids,and multi-organ chips;(Ⅱ)applying multi-omics technologies,such as spatial omics,single-cell omics,and dynamic metabolic flux omics;(Ⅲ)using artificial intelligence(AI)and big data for data integration and prediction of pattern evolution;and(Ⅳ)validating formula–pattern associations through the“pattern differentiation through formula efficacy”approach.These strategies directly address the main obstacles in TCM pattern research by providing objective,quantifiable,and reproducible methodologies.Constructing disease-pattern integrated models enabled cross-scale research platforms.Applying multi-omics technologies allowed analysis of complex biological bases.AI and big data approaches addressed challenges related to heterogeneous data.The“formula-based pattern differentiation”approach supported precise interventions and the development of new drugs.This interdisciplinary framework advances TCM pattern research by moving from empirical description to objective quantification.By integrating innovative approaches,the study establishes a foundation for systematic,evidence-based TCM diagnosis and treatment,supporting accuracy and promoting international recognition and modernization of TCM.The study shows that combining multi-omics technologies,AI-driven data analysis,and disease-pattern models enables objective quantification of TCM patterns and clarifies their biological mechanisms.
基金supported by the Guizhou Provincial Science and Technology Projects(Grant Nos.ZK[2022]540 and[2023]099)the Survey of Amphibian and Reptile Resources in Leigongshan Nature Reserve and Literature Publishing Services(P5226002023000019).
文摘Dear Editor,Understanding patterns of species diversity is a primary research focus in macroecology,with its distribution patterns having been described and theoretically validated on a global scale(Peters et al.,2016;Sonne et al.,2025).Numerous studies have found that species richness of different taxa tends to decrease with increasing elevation and is modulated by latitudinal gradients(Peters et al.,2016;Dolson et al.,2024).This principle provides a crucial scientific basis for regional conservation planning.However,it still exhibits significant variations across different mountain ranges and taxa.
基金supported by the National Natural Science Foundation of China(32460380,42007042)State Key Laboratory of Subtropical Silviculture(SKLSSKF2023-06)+2 种基金Natural Science Foundation of Jiangxi Province(20242BAB25389)National Undergraduate Innovation and Entrepreneurship Training Program(202410410029X)Jiangxi Province Graduate Student Innovation Special Fund Project(YC2024-S330).
文摘Urban forests are essential components of green infrastructure,however,rapid urbanization-induced changes in landscape patterns may affect their ecosystem services through complex ecological processes.A total of 184 sample plots in the built-up areas of Nanchang,China,were used as research sites.Urbanization intensities were categorized by the rate of impervious surface area,and forest types were classified into landscape and relaxation forest,attached forest(AF),road forest(RF),and ecological public welfare forest.This study aimed to explore the spatial variations in vegetation characteristics and landscape pattern indices of different forest types under rapid urbanization.The results indicated that the largest patch index(LPI),aggregation index(AI),and percentage of landscape(PLAND)in RF and AF were lower than those in the other forest types(p<0.05).With increasing urbanization intensity,the mean perimeter-area ratio increased by 130.84%,whereas the PLAND,LPI,and AI decreased by 22−86%(p<0.05).Redundancy analysis and variation partitioning suggested that the interpretation rate of landscape pattern indices for variations in vegetation characteristics increased from low to heavy urbanization areas.Especially,the landscape shape index,patch connection index,PLAND,and mean patch size were significantly correlated with vegetation characteristics(e.g.,tree richness,herb coverage,and tree height).In the future,appropriate landscape layout superiority cases should be considered in different urbanization areas and forest types;for instance,increasing the patch connection index will beneficially improve the diversity of trees and herbs in heavy urbanization areas and the RF.This study serves as a reference for maximizing the ecosystem services of urban forests.
基金supported in part by National Key R&D Program of China(2022YFB4501200),National Natural Science Foundation of China(62332018)Science and Technology Program(2024NSFTD0031,2024YFHZ0339 and 2025ZNSFSC0497).
文摘The performance of data restore is one of the key indicators of user experience for backup storage systems.Compared to the traditional offline restore process,online restore reduces downtime during backup restoration,allowing users to operate on already restored files while other files are still being restored.This approach improves availability during restoration tasks but suffers from a critical limitation:inconsistencies between the access sequence and the restore sequence.In many cases,the file a user needs to access at a given moment may not yet be restored,resulting in significant delays and poor user experience.To this end,we present Histore,which builds on the user’s historical access sequence to schedule the restore sequence,in order to reduce users’access delayed time.Histore includes three restore approaches:(i)the frequency-based approach,which restores files based on historical file access frequencies and prioritizes ensuring the availability of frequently accessed files;(ii)the graph-based approach,which preferentially restores the frequently accessed files as well as their correlated files based on historical access patterns,and(iii)the trie-based approach,which restores particular files based on both users’real-time and historical access patterns to deduce and restore the files to be accessed in the near future.We implement a prototype of Histore and evaluate its performance from multiple perspectives.Trace-driven experiments on two datasets show that Histore significantly reduces users’delay time by 4-700×with only 1.0%-14.5%additional performance overhead.
基金supported by the National Natural Science Foundation of China(Grants Nos.T2325004)the Advanced Materials-National Science and Technology Major Project(Grant No.2024ZD0606900)+3 种基金the Talent Hub for‘AI+New Materials’Basic Researchsupported by the Strategic Priority Research Program of the Chinese Academy of Sciences(Grant Nos.XDB0620103 and XDB0510301)the National Natural Science Foundation of China(Grant No.12472112)R.S.acknowledges the Young Scientists Fund of the National Natural Science Foundation of China(51801046).
文摘Enhancing the kinetic stability of glasses typically requires deepening their thermodynamic stability,which increases structural rigidity and degrades ductility;decoupling these properties remains a major challenge.Here,we demonstrate that spatial patterning in metallic glasses produces exceptional kinetic ultrastability that coexists with a thermodynamically metastable,high-energy state and excellent plasticity.Guided by atomistic simulations using replica exchange molecular dynamics and machine learning interatomic potentials,we reveal that oxygen,through reaction-diffusion-coupled pattern dynamics,self-organizes into oxygen-centered pinned structures(OPSs)that serve as localized kinetic constraints.These motifs drastically slow structural relaxation,delivering kinetic stability comparable to ultrastable glasses even as the system retains the high inherent energy of rapidly quenched states.The OPSs’topology yields a spatially uniform activation of plastic events,promoting strain delocalization under mechanical load.By geometrically tailoring oxygen patterns,we increase the glass transition onset temperature(Tonset)by about 200 K with negligible loss of deformability.Our findings establish a practicable paradigm for decoupling kinetic and thermodynamic stability and point to a scalable,additive route for designing amorphous materials that combine hyperstability with plasticity.
基金supported by 14th Five-Year Plan Key R&D Plan,Ministry of Science and Technology of the People’s Republic of China,2024YFB3409002National Natural Science Foundation of China,12302142+4 种基金HKUSTHKUST(GZ)Collaborative Research Scheme,G035Yangcheng Scholars Research Project-Leading Talent Training Project,2024312156Guangzhou-HKUST(GZ)Joint Funding Scheme,2023A03J0157Guangzhou Basic and Applied Basic Research Project,2024A04J4765Shenzhen Basic Research Project,JCYJ20220530114417040。
文摘Owing to the exceptional optoelectronic properties,metal halide perovskites have emerged as leading semiconductor materials for next-generation display technologies,providing perovskite light-emitting diodes(Pe LEDs)great potential for high-quality color displays with a wide color gamut and pure color emission.Although laboratory-scale Pe LEDs have achieved neartheoretical efficiencies,challenges such as achieving uniform large-area films,improving material stability,and enhancing patterning precision remain barriers to commercialization.This review presents a systematic analysis of scalable manufacturing and precision patterning strategies for Pe LEDs,focusing on their applications in large-area lighting and full-color displays.Fabrication methods are categorized into film deposition techniques(spin-coating,blade-coating,and thermal evaporation)and patterning strategies,including top-down(photolithography,laser/e-beam lithography,and nanoimprinting)and bottom-up(patterned crystal growth,inkjet printing,and electrohydrodynamic jet printing)approaches.In this review,we discuss the advantages and limitations of each strategy,highlight current challenges,and outlook possible pathways towards scalable,high-performance Pe LEDs for advanced optoelectronic applications.
基金the Chinese Academy of Sciences Research Center for Ecology and Environment of Central Asia(RCEECA),the construction and joint research for the China-Tajikistan“Belt and Road”Joint Laboratory on Biodiversity Conservation and Sustainable Use(2024YFE0214200)the Shanghai Cooperation Organization Partnership and International Technology Cooperation Plan of Science and Technology Projects(2023E01018,2025E01056)the Chinese Academy of Sciences President’s International Fellowship Initiative(PIFI)(2024VBC0006).
文摘Tajikistan represents a core region of the biodiversity hotspot in Central Asian mountains and has exceptional vascular plant diversity.However,the species diversity of the country faces urgent conservation challenges.There has been a lack of a comprehensive and multidimensional assessment to inform strategic conservation planning.Therefore,this study integrated 4 key biodiversity indices including species richness(SR),phylogenetic diversity(PD),threatened species richness(TSR),and endemic species richness(ESR)to map species diversity distribution patterns,identify conservation gaps,and elucidate their effects of climatic factors.This study revealed that species diversity shows a clear trend of decreasing from the western region to the eastern region of Tajikistan.The central–western mountains(specifically the Gissar-Darvasian and Zeravshanian regions)emerge as irreplaceable biodiversity hotspots.However,we found a severe spatial mismatch between these priority areas and the existing protected areas(PAs).Protection coverage for all hotspots was alarmingly low,ranging from 31.00%to 38.00%.Consequently,a critical 64.80%of integrated priority areas fall outside of the current PAs,representing a major conservation gap.This study identified precipitation seasonality and isothermality as the principal drivers,collectively explaining over 50.00%of the diversity variation and suggesting high vulnerability to hydrological shifts.Furthermore,we detected significant geographic sampling bias in the public biodiversity databases,with the most critical hotspot being systematically under-sampled.This study provides a robust scientific basis for conservation action,highlighting the urgent need to strategically expand PAs in the under-protected southwestern region and to mitigate critical sampling gaps through targeted data digitization and field surveys.These measures are indispensable for securing Tajikistan’s unique biodiversity and achieving the Kunming-Montreal Global Biodiversity Framework Target 3(“30×30 Protection”).
基金support from the National Natural Science Foundation of China(Grant No.61971256)。
文摘Wide-field mesoscopy provides the capabilities of cortex-wide field of view(FOV),cellular resolution and high frame rate for neuronal imaging in the mouse brain.However,inherent background fluorescence degrades the image quality and hinders neuronal signal extraction.To address this problem,we first introduce a cortex-wide,high-resolution lineillumination mesoscope with a moving slit designed for in vivo mouse brain imaging.This system achieves a 6.6×6.6 mm FOV,microscale cellular resolution,a high frame rate of 10 Hz,as well as the background rejection ability.Furthermore,we integrated patterned illumination into the system to enhance the background suppression.Experimental results show that the proposed system successfully captures neurodynamics in the living mouse brain.Compared with conventional wide-field mesoscopes,the cortex-wide patterned line-illumination mesoscope(PLIM)achieves a threefold increase in the signal-to-background ratio(SBR).With patterned illumination integrated,the SBR enhancement further reaches four-anda-half-fold.
基金Project supported by the National Natural Science Foundation of China(Nos.12102321 and 52192633)the Natural Science Basic Research Plan in Shaanxi Province of China(No.2025JCYBMS-050)。
文摘A design idea for single-component metamaterial plates is proposed to achieve the thermal stability of flexural wave bandgap by the perforated and pre-curved patterns.The band structure analysis suggests that perforation can release part of the in-plane thermal expansion to weaken the softening effect of thermal stress.Introducing precurved components to the perforated structure will stop the decrement of the bandgap frequency in thermal environment,and even make the frequency higher with appropriate structural parameters.The bending stiffness of the heated plate is enhanced by the thermal deflection induced stiffening effect of the pre-curved components.The segmented pre-curved component presents a strong ability to resist the thermal influence on the flexural wave bandgap.A simplified model is established for the local structure of the precurved component.The theoretical calculations explain the thermally induced frequency increment of the bandgap and the discrepancy in the thermal response between the two pre-curved models.The transmittance of flexural wave validates the effectiveness of the proposed design.
基金supported by the Key Laboratory of Clinical Evaluation Technology for Human Experience with Chinese Medicine,Science and Technology Innovation Project of Guangdong Provincial Medical Products Administration(2022ZDB06)the Jointly Funded Project by Guangzhou Science and Technology Bureau,Research Institutes and Enterprises(2024A03j0355)+1 种基金the State Key Laboratory of Traditional Chinese Medicine Syndrome"Unveiling the List and Taking on Leadership"Project(SKLKY2025C0013)the National Key Research and Development Program of China(2025YFC3507902).
文摘The development of pattern-based traditional Chinese medicine(TCM)compound preparations constitutes a core domain that represents the principle of pattern differentiation-based treatment,a hallmark of TCM.However,the field has long been constrained by scientific and regulatory challenges in animal modeling,efficacy evaluation,and clinical positioning.This article proposes a new research and development(R&D)paradigm strategically based on human use experience(HUE)and centered on the patient as the key to overcoming these bottlenecks and achieving high-quality progress.We systematically dissect the traditional problems in this field and demonstrate the pivotal role of high-quality HUE in enabling precise clinical positioning and optimizing R&D pathways(e.g.,applying for exemptions from non-clinical studies).HUE guides the implementation of the“pattern-symptom integration”model.Furthermore,we detail the implementation of the patient-centered concept throughout the process of clinical trial design,collection of patients’experience data,clinical outcome assessment,and benefit-risk assessment.The integrative application of artificial intelligence in the R&D of pattern-based TCM drugs is also specifically explored.By synthesizing the“TCM theory,HUE,and clinical trials”evidence system,this article aims to provide a systematic strategic framework for establishing an R&D pathway that adheres to the intrinsic principles of TCM while simultaneously meeting modern scientific standards.
基金financially supported by the HEAD foundation(IO number GRTHF0000101).
文摘Objectives:To explore the use of a traditional Chinese medicine(TCM)pattern scale as an outcome measure to evaluate the management of patients with chronic low back pain(CLBP).Methods:A total of 204 participants were recruited and randomly allocated into three CLBP treatment groups:Tuina only,physiotherapy only,and a combined physiotherapy+Tuina group.All participants were assessed for treatment outcomes using the TCM pattern scale as a substudy to a randomized controlled trial in which the Visual Analog Scale(VAS)was the primary outcome measure.TCM pattern scores were recorded by non-TCM research assistants who were trained to administer a TCM pattern questionnaire developed by the authors in collaboration with TCM experts.Results:Most participants(83%)were classified as having kidney deficiency pattern as the primary TCM pattern at baseline.All three intervention groups showed a significant decrease in overall TCM pattern score at month 2(M2)and month 5(M5).However,when the nimodipine method was applied,none of the three treatment arms showed a statistically significant change in the effective rate,even though the parent study reported a significant decrease in VAS scores in all treatment arms.Conclusion:This study found improvements in both the dominant TCM pattern score and the overall TCM pattern score for each group.These findings suggest that TCM pattern diagnosis,including entities recognized in International Classification of Diseases,11th Revision(ICD)-11,may be used as a quantitative outcome measure to reflect response to TCM-based intervention.The TCM pattern scale reported here may potentially be applied in other chronic pain studies involving TCM patterns.Further studies are warranted to validate this scale in other clinical conditions.
基金National Natural Science Foundation of China,No.42471202,No.72441005。
文摘Existing studies on the Regional Comprehensive Economic Partnership(RCEP)mainly focused on institutional features,macro-economic impacts,and trade-network structures,while its geographic attributes and their implications remain underexplored.Taking the RCEP as a case,this paper examines how the FTA reshapes China’s trade geography and validates these effects with an enhanced GTAP model,providing an empirical basis for advancing trade-geography theory.Key findings include:(1)RCEP significantly reduces regional trade costs.After full implementation of the agreement,the average tariffs among member countries will decrease to 40.5%of the pre-implementation level,while import and export trade facilitation levels improve by 34.3%and 29.6%,respectively.However,these improvements exhibit marked regional disparities.(2)RCEP asymmetrically promotes China’s foreign trade growth,with stronger import stimulation than export expansion,alongside significant product-specific variations.(3)The agreement reshapes China’s trade geography,driving a 7.66%increase in intra-RCEP trade while reducing extra-RCEP trade by 0.80%.(4)The restructuring of China’s trade patterns under RCEP emerges from the complex interplay of trade creation,diversion,and crowding-out effects.Accordingly,China should further harmonize regional tariff schedules,enhance trade-facilitation mechanisms,strengthen industrial competitiveness and expand multilateral partnerships.
文摘BACKGROUND Drug utilization research has an important role in assisting the healthcare administration to know,compute,and refine the prescription whose principal objective is to enable the rational use of drugs.Research in developing nations relating to the cost of treatment is scarce when compared with developed countries.Thus,the drug utilization research studies from developing nations are most needed,and their number has been growing.AIM To evaluate patterns of utilization of antipsychotic drugs and direct medical cost analysis in patients newly diagnosed with schizophrenia.METHODS The present study was observational in type and based on a retrospective cohort to evaluate patterns of utilization of antipsychotic drugs using World Health Organization(WHO)core prescribing indicators and anatomical therapeutic chemical/defined daily dose indicators.We also calculated direct medical costs for a period of 6 months.RESULTS This study has found that atypical antipsychotics are the mainstay of treatment for schizophrenia in every age group and subcategories of schizophrenia.The evaluation based on WHO prescribing indicators showed a low average number of drugs per prescription and low prescribing frequency of antipsychotics from the National List of Essential Medicines 2015 and the WHO Essential Medicines List 2019.The total mean drug cost of our study was 1396 Indian rupees.The total mean cost due to the investigation in our study was 1017.34 Indian rupees.Therefore,the total mean direct medical cost incurred on patients in our study was 4337.28 Indian rupees.CONCLUSION The information from the present study can be used for reviewing and updating treatment policy at the institutional level.
基金funded by the National Natural Science Foundation of China(42230720)the 2023 Annual Qinghai Province"Kunlun Talents-High-end Innovation and Entrepreneurship Talent"Program Project.
文摘The Qaidam Basin,a typical alpine arid inland basin on the northern Qinghai-Xizang Plateau,China,hosts wetland ecosystems that are strongly constrained by topography and extreme climate.These ecosystems exhibit pronounced spatiotemporal heterogeneity and fragmented distribution patterns,rendering them highly sensitive to environmental change.This study integrated Sentinel-2 remote sensing imagery with the SedInConnect model to delineate wetland patch distributions and calculate the Index of Connectivity(IC)values across the basin.Based on IC values,we stratified field sampling sites into high-,moderate-,and lowconnectivity gradient groups to analyze the relationships among plant community characteristics,vegetation spatial patterns,and wetland connectivity in the Qaidam Basin.Partial Least Squares Path Modeling(PLSPM)was further employed to quantify the driving mechanisms underlying wetland vegetation characteristics.The results revealed that wetland connectivity across the basin was generally low,with IC values up to 1.32 and displaying a west-to-east decreasing gradient.The west and northwest were characterized by relatively continuous high-connectivity wetland networks,while fragmented and low-connectivity wetlands predominated in the east and southeast.Connectivity regulated wetland vegetation patterns primarily by affecting patch size,fragmentation,and internal adjacency.High-connectivity areas had higher class area(CA),largest patch index(LPI),and area-weighted mean patch size(AREA_AM)than low-connectivity areas.Connectivity had the strongest effect on vegetation coverage,which declined sharply from 87.577%in highconnectivity areas to 12.152%in low-connectivity areas.Meanwhile,species diversity showed a moderately negative response to connectivity changes,whereas species evenness remained relatively unaffected.PLS-PM explained 78.300%and 67.500%of the variance in vegetation community and vegetation pattern,respectively.Climate played a dominant role in shaping vegetation characteristics,with significant negative effects on both vegetation community and pattern.Topography influenced vegetation indirectly through climate,and connectivity was influenced by both drivers and exerted positive effects on vegetation community and pattern.This study reveals the multi-pathway driving mechanisms underlying vegetation pattern formation in alpine wetlands,providing a theoretical foundation and decision-support framework for the scientific conservation and adaptive management of wetlands in the Qaidam Basin.
