Design patterns offer reusable solutions for common software issues,enhancing quality.The advent of generative large language models(LLMs)marks progress in software development,but their efficacy in applying design pa...Design patterns offer reusable solutions for common software issues,enhancing quality.The advent of generative large language models(LLMs)marks progress in software development,but their efficacy in applying design patterns is not fully assessed.The recent introduction of generative large language models(LLMs)like ChatGPT and CoPilot has demonstrated significant promise in software development.They assist with a variety of tasks including code generation,modeling,bug fixing,and testing,leading to enhanced efficiency and productivity.Although initial uses of these LLMs have had a positive effect on software development,their potential influence on the application of design patterns remains unexplored.This study introduces a method to quantify LLMs’ability to implement design patterns,using Role-Based Metamodeling Language(RBML)for a rigorous specification of the pattern’s problem,solution,and transformation rules.The method evaluates the pattern applicability of a software application using the pattern’s problem specification.If deemed applicable,the application is input to the LLM for pattern application.The resulting application is assessed for conformance to the pattern’s solution specification and for completeness against the pattern’s transformation rules.Evaluating the method with ChatGPT 4 across three applications reveals ChatGPT’s high proficiency,achieving averages of 98%in conformance and 87%in completeness,thereby demonstrating the effectiveness of the method.Using RBML,this study confirms that LLMs,specifically ChatGPT 4,have great potential in effective and efficient application of design patterns with high conformance and completeness.This opens avenues for further integrating LLMs into complex software engineering processes.展开更多
Backswimmers exhibit a high degree of mobility in water,and their different motion patterns have important implications for the design of micro-biomimetic underwater robots.This paper used three-dimensional high-speed...Backswimmers exhibit a high degree of mobility in water,and their different motion patterns have important implications for the design of micro-biomimetic underwater robots.This paper used three-dimensional high-speed cameras to extract the key points on the hind legs.The hind leg motion laws and the deformation laws of the setae were obtained in four motion patterns:rapid forward,cruising,in-motion turning,and in-place turning.The motion laws of each joint on the hind leg are modeled using a Fourier series.A kinematic model of hind legs was established based on the DH method,and the motion characteristics of hind legs under different motion patterns were analyzed.This paper provides basic data and theoretical models for micro-biomimetic robots.展开更多
A uniform longitudinal field applied to the transverse Ising model(TIM)distinguishes the antiferromagnetic Ising interaction from its ferromagnetic counterpart.While the ground state of the latter shows no quantum pha...A uniform longitudinal field applied to the transverse Ising model(TIM)distinguishes the antiferromagnetic Ising interaction from its ferromagnetic counterpart.While the ground state of the latter shows no quantum phase transition(QPT),the ground state of the former exhibits rich phases:paramagnetic,antiferromagnetic,and possibly disordered phases.Although the first two are clearly identified,the existence of the disordered phase remains controversial.Here,we use the pattern picture to explore the competition among the antiferromagnetic Ising interaction J,the transverse field hx and the longitudinal field h_(z),and uncover which patterns are responsible for these three competing energy scales,thereby determining the possible phases and the QPTs among them.The system size ranges from L=8 to 128 and the transverse field hx is fixed at 1.Under these parameters,our results show the existence of the disordered phase.For a small h_(z),the system transitions from a disordered phase to an antiferromagnetic phase as J increases.For a large h_(z),the system undergoes two phase transitions:from paramagnetic to disordered,and then to antiferromagnetic phase.These results not only unveil the rich physics of this paradigmatic model but also stimulate quantum simulation by using currently available experimental platforms.展开更多
Water scarcity and environment deterioration have become main constraints to sustainable economic and social development.Scientifically assessing Water Resources Carrying Capacity(WRCC)is essential for the optimal all...Water scarcity and environment deterioration have become main constraints to sustainable economic and social development.Scientifically assessing Water Resources Carrying Capacity(WRCC)is essential for the optimal allocation of regional water resources.The hilly area at the northern foot of Yanshan Mountains is a key water conservation zone and an important water source for Beijing,Tianjin and Hebei.Grasping the current status and temporal trends of water quality and WRCC in representative small watersheds within this region is crucial for supporting rational water resources allocation and environment protection efforts.This study focuses on Pingquan City,a typical watershed in northern Hebei Province.Firstly,evaluation index systems for surface water quality,groundwater quality and WRCC were estab-lished based on the Pressure-State-Response(PSR)framework.Then,comprehensive evaluations of water quality and WRCC at the sub-watershed scale were conducted using the Varying Fuzzy Pattern Recogni-tion(VFPR)model.Finally,the rationality of the evaluation results was verified,and future scenarios were projected.Results showed that:(1)The average comprehensive evaluation scores for surface water and groundwater quality in the sub-watersheds were 1.44 and 1.46,respectively,indicating that both met the national Class II water quality standard and reflected a high-quality water environment.(2)From 2010 to 2020,the region's WRCC steadily improved,with scores rising from 2.99 to 2.83 and an average of 2.90,suggesting effective water resources management in Pingquan City.(3)According to scenario-based predic-tion,WRCC may slightly decline between 2025 and 2030,reaching 2.92 and 2.94,respectively,relative to 2020 levels.Therefore,future efforts should focus on strengthening scientific management and promoting the efficient use of water resources.Proactive measures are necessary to mitigate emerging contradiction and ensure the long-term stability and sustainability of the water resources system in the region.The evalua-tion system and spatiotemporal evolution patterns proposed in this study can provide a scientific basis for refined water resource management and ecological conservation in similar hilly areas.展开更多
The inter-model difference in the tropical Pacific SST warming pattern is a big stumbling block for reliable projections of global climate change. Here by conducting an inter-model Empirical Orthogonal Function(EOF) a...The inter-model difference in the tropical Pacific SST warming pattern is a big stumbling block for reliable projections of global climate change. Here by conducting an inter-model Empirical Orthogonal Function(EOF) analysis as well as an ocean mixed-layer heat budget, we find that the first two modes of inter-model difference in the SST warming pattern projected by 30 CMIP6 models, explaining more than three-quarters of the total inter-model variance, are both tied to different cloud–radiation feedbacks. The EOF1 mode that captures the different magnitudes of El Ni?o-like warming as well as the largest inter-model variance in the far eastern equatorial Pacific, is likely driven by highly diverse cloud–radiation feedbacks in the east and, to a lesser extent, by differing changes in the oceanic vertical temperature gradient. The EOF2 mode that mainly represents the different magnitudes of SST warming in the western equatorial Pacific, is associated with differing levels of negative cloud–radiation feedback over the central equatorial Pacific through a dynamic air–sea coupled process involving both the Bjerknes feedback and the wind–evaporation–SST feedback.Considering in isolation the robust common model bias of a weak negative cloud–radiation feedback over the central equatorial Pacific, the projected SST warming in the western equatorial Pacific is likely to be smaller than the multi-model ensemble mean, thereby presenting a more weakeened zonal SST gradient than expected, implying the potential for more severe climate extremes under global warming.展开更多
Understanding spatial patterns of plant species diversity and the factors(e.g.,climate and human)that drive these patterns is essential for biodiversity conservation.We used data from 1700.1-ha forest plots in the She...Understanding spatial patterns of plant species diversity and the factors(e.g.,climate and human)that drive these patterns is essential for biodiversity conservation.We used data from 1700.1-ha forest plots in the Shettihalli tropical forest landscape of the Western Ghats biodiversity hotspot,India,to analyse tree community composition and the drivers ofα-diversity(Shannon)andβ-diversity(LCBD).Compositional patterns were visualized using Non-Metric Multidimensional Scaling(NMDS),and hybrid feature selection with structural equation modeling(SEM)was employed to evaluate the direct and indirect effects of environmental variables on diversity.NMDS identified four distinct forest types in the Shettihalli landscape:semi-evergreen,dry deciduous,moist deciduous,and plantation forests,each with distinct plant composition.Shannon diversity and ecological uniqueness was significantly higher in semi-evergreen forest than in deciduous forest plots.The SEMs explained about 79%and 39–45%of the variation inα-diversity andβ-diversity.Our analysis indicated that current diversity patterns result from multiple processes,with structure,disturbance,and edaphic parameters exerting the strongest direct and indirect effects onα-diversity.β-diversity,in contrast,was largely influenced by climate,topography,stand structure,and edaphic factors.Overall,our findings indicate that various factors(e.g.,climate,topography,and human disturbance)interact to shape tree diversity patterns in tropical forests.These findings will help develop unique conservation and management strategies for distinct forest types in tropical forest ecosystems.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
Research on the distribution and development of black shales in the Lianggaoshan Formation has been deficient,which has hindered exploration for lacustrine shale oil in the Sichuan Basin.Our study characterized the we...Research on the distribution and development of black shales in the Lianggaoshan Formation has been deficient,which has hindered exploration for lacustrine shale oil in the Sichuan Basin.Our study characterized the well logging data,core samples,outcrops,and geochemistry of black shales in the Lianggaoshan Formation in the Sichuan Basin.Our analysis focused on the lake basin evolution and the migration characteristics,paleoenvironmental features,formation mechanisms,and developmental model of the black shales.The results indicated that black shales in the Lianggaoshan Formation exhibited significant lateral migration,with an overall thickening trend from east to west.Within the 1st Member of the formation,black shale occurred as a single thick layer in the eastern region that gradually thinned toward the central region.Multiple sets of shale developed within the 2nd and 3rd members,and these had lower thicknesses than the 1st Member and migrated toward central Sichuan.Paleoproductivity and terrigenous input were the main factors controlling the deposition of black shales.A semi-humid climate influenced the deposition of black shales,bringing abundant freshwater,terrigenous debris,and nutrients into the basin.Decomposition of organic matter consumed oxygen in sediment and bottom water,causing localized oxygen deficiency in the strata.展开更多
Model evaluation using benchmark datasets is an important method to measure the capability of large language models(LLMs)in specific domains,and it is mainly used to assess the knowledge and reasoning abilities of LLM...Model evaluation using benchmark datasets is an important method to measure the capability of large language models(LLMs)in specific domains,and it is mainly used to assess the knowledge and reasoning abilities of LLMs.Therefore,in order to better assess the capability of LLMs in the agricultural domain,Agri-Eval was proposed as a benchmark for assessing the knowledge and reasoning ability of LLMs in agriculture.The assessment dataset used in Agri-Eval covered seven major disciplines in the agricultural domain:crop science,horticulture,plant protection,animal husbandry,forest science,aquaculture science,and grass science,and contained a total of 2283 questions.Among domestic general-purpose LLMs,DeepSeek R1 performed best with an accuracy rate of 75.49%.In the realm of international general-purpose LLMs,Gemini 2.0 pro exp 0205 standed out as the top performer,achieving an accuracy rate of 74.28%.As an LLMs in agriculture vertical,Shennong V2.0 outperformed all the LLMs in China,and the answer accuracy rate of agricultural knowledge exceeded that of all the existing general-purpose LLMs.The launch of Agri-Eval helped the LLM developers to comprehensively evaluate the model's capability in the field of agriculture through a variety of tasks and tests to promote the development of the LLMs in the field of agriculture.展开更多
In this paper,we establish and study a single-species logistic model with impulsive age-selective harvesting.First,we prove the ultimate boundedness of the solutions of the system.Then,we obtain conditions for the asy...In this paper,we establish and study a single-species logistic model with impulsive age-selective harvesting.First,we prove the ultimate boundedness of the solutions of the system.Then,we obtain conditions for the asymptotic stability of the trivial solution and the positive periodic solution.Finally,numerical simulations are presented to validate our results.Our results show that age-selective harvesting is more conducive to sustainable population survival than non-age-selective harvesting.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
This study presents a teaching reform for the Object-oriented Software Construction(OOSC)course by integrating outcome-based education(OBE)and the BOPPPS(bridge-In,objectives,pre-assessment,participatory learning,post...This study presents a teaching reform for the Object-oriented Software Construction(OOSC)course by integrating outcome-based education(OBE)and the BOPPPS(bridge-In,objectives,pre-assessment,participatory learning,post-assessment,summary)instructional model.The reform addresses the gap between syntax-based programming instruction and the need for higher-level skills in abstraction,modularity,and software architecture.The course is anchored in a semester-long,project-based learning platform centered on a Java-based Aircraft Battle Game,progressing through six iterative experiments.Each experiment targets specific competencies within the structured BOPPPS teaching cycle and is aligned with specific OBE learning outcomes.A case study on the Factory Pattern illustrates how the BOPPPS model fosters conceptual understanding and practical application.Evaluation results from the 2023 and 2024 spring semesters show improved outcomes:Project completion rose from 87%to 95%,37%of students implemented innovative features,and average final grades increased by 7%.The results affirm that the OBE+BOPPPS integration strengthens engagement,deepens understanding,and equips students with real-world software development competencies.展开更多
In their recent paper Pereira et al.(2025)claim that validation is overlooked in mapping and modelling of ecosystem services(ES).They state that“many studies lack critical evaluation of the results and no validation ...In their recent paper Pereira et al.(2025)claim that validation is overlooked in mapping and modelling of ecosystem services(ES).They state that“many studies lack critical evaluation of the results and no validation is provided”and that“the validation step is largely overlooked”.This assertion may have been true several years ago,for example,when Ochoa and Urbina-Cardona(2017)made a similar observation.However,there has been much work on ES model validation over the last decade.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
In recent years,there has been an increasing need for climate information across diverse sectors of society.This demand has arisen from the necessity to adapt to and mitigate the impacts of climate variability and cha...In recent years,there has been an increasing need for climate information across diverse sectors of society.This demand has arisen from the necessity to adapt to and mitigate the impacts of climate variability and change.Likewise,this period has seen a significant increase in our understanding of the physical processes and mechanisms that drive precipitation and its variability across different regions of Africa.By leveraging a large volume of climate model outputs,numerous studies have investigated the model representation of African precipitation as well as underlying physical processes.These studies have assessed whether the physical processes are well depicted and whether the models are fit for informing mitigation and adaptation strategies.This paper provides a review of the progress in precipitation simulation overAfrica in state-of-the-science climate models and discusses the major issues and challenges that remain.展开更多
Background:Large language models(LLMs)have shown considerable promise in supporting clinical decision-making.However,their adoption and evaluation in dermatology remains limited.This study aimed to explore the prefere...Background:Large language models(LLMs)have shown considerable promise in supporting clinical decision-making.However,their adoption and evaluation in dermatology remains limited.This study aimed to explore the preferences of Chinese dermatologists regarding LLM-generated responses in clinical psoriasis scenarios and to assess how they prioritize key quality dimensions,including accuracy,traceability,and logicality.Methods:A cross-sectional,web-based survey was conducted between December 25,2024,and January 22,2025,following the Checklist for Reporting Results of Internet E-Surveys guidelines.A total of 1247 valid responses were collected from practicing dermatologists across 33 of China's provincial-level administrative divisions.Participants evaluated responses to five categories of clinical questions(etiology,clinical presentation,differential diagnosis,treatment,and case study)generated by five LLMs:ChatGPT-4o,Kimi.ai,Doubao,ZuoYiGPT,and Lingyi-agent.Statistical associations between participant characteristics and model preferences were examined using chi-square tests.Results:ChatGPT-4o(Model 1)emerged as the most preferred model across all clinical tasks,consistently receiving the highest number of votes in case study(n=740),clinical presentation(n=666),differential diagnosis(n=707),etiology(n=602),and treatment(n=656).Significant variation in model preference by professional title was observed only for the differential diagnosis task(χ^(2)=21.13,df=12,p=0.0485),while no significant differences were found across hospital tiers(p>0.05).In terms of evaluation dimensions,accuracy was most frequently rated as“very important”(n=635).A significant association existed between hospital tier and the most valued dimension(χ^(2)=27.667,df=9,p=0.0011),with dermatologists in primary hospitals prioritizing traceability more than their peers in higher-tier hospitals.No significant associations were found across professional titles(p=0.127).Conclusions:Chinese dermatologists suggest a strong preference for ChatGPT-4o over domestic LLMs in psoriasis-related clinical tasks.While accuracy remains the primary criterion,traceability and logicality are also critical,particularly for clinicians in lower-tier hospitals.These findings suggest that future clinical LLMs should prioritize not only content accuracy but also source transparency and structural clarity to meet the diverse needs of different clinical settings.展开更多
The Reynolds-averaged Navier-Stokes(RANS)technique enables critical engineering predictions and is widely adopted.However,since this iterative computation relies on the fixed-point iteration,it may converge to unexpec...The Reynolds-averaged Navier-Stokes(RANS)technique enables critical engineering predictions and is widely adopted.However,since this iterative computation relies on the fixed-point iteration,it may converge to unexpected non-physical phase points in practice.We conduct an analysis on the phase-space characteristics and the fixed-point theory underlying the k-ε turbulence model,and employ the classical Kolmogorov flow as a framework,leveraging its direct numerical simulation(DNS)data to construct a one-dimensional(1D)system under periodic/fixed boundary conditions.The RANS results demonstrate that under periodic boundary conditions,the k-ε model exhibits only a unique trivial fixed point,with asymptotes capturing the phase portraits.The stability of this trivial fixed point is determined by a mathematically derived stability phase diagram,indicating the fact that the k-ε model will never converge to correct values under periodic conditions.In contrast,under fixed boundary conditions,the model can yield a stable non-trivial fixed point.The evolutionary mechanisms and their relationship with boundary condition settings systematically explain the inherent limitations of the k-ε model,i.e.,its deficiency in computing the flow field under periodic boundary conditions and sensitivity to boundary-value specifications under fixed boundary conditions.These conclusions are finally validated with the open-source code OpenFOAM.展开更多
Utilizing finite element analysis,the ballistic protection provided by a combination of perforated D-shaped and base armor plates,collectively referred to as radiator armor,is evaluated.ANSYS Explicit Dynamics is empl...Utilizing finite element analysis,the ballistic protection provided by a combination of perforated D-shaped and base armor plates,collectively referred to as radiator armor,is evaluated.ANSYS Explicit Dynamics is employed to simulate the ballistic impact of 7.62 mm armor-piercing projectiles on Aluminum AA5083-H116 and Steel Secure 500 armors,focusing on the evaluation of material deformation and penetration resistance at varying impact points.While the D-shaped armor plate is penetrated by the armor-piercing projectiles,the combination of the perforated D-shaped and base armor plates successfully halts penetration.A numerical model based on the finite element method is developed using software such as SolidWorks and ANSYS to analyze the interaction between radiator armor and bullet.The perforated design of radiator armor is to maintain airflow for radiator function,with hole sizes smaller than the bullet core diameter to protect radiator assemblies.Predictions are made regarding the brittle fracture resulting from the projectile core′s bending due to asymmetric impact,and the resulting fragments failed to penetrate the perforated base armor plate.Craters are formed on the surface of the perforated D-shaped armor plate due to the impact of projectile fragments.The numerical model accurately predicts hole growth and projectile penetration upon impact with the armor,demonstrating effective protection of the radiator assemblies by the radiator armor.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
Coordinate transformation models often fail to account for nonlinear and spatially dependent distortions,leading to significant residual errors in geospatial applications.Here,we propose a residual-based neural correc...Coordinate transformation models often fail to account for nonlinear and spatially dependent distortions,leading to significant residual errors in geospatial applications.Here,we propose a residual-based neural correction(RBNC)strategy,in which a neural network learns to model only the systematic distortions left by an initial geometric transformation.By focusing solely on residual patterns,RBNC reduces model complexity and improves performance,particularly in scenarios with sparse or structured control point configurations.We evaluate the method using both simulated datasets(with varying distortion intensities and sampling strategies)and real-world image georeferencing tasks.Compared with direct neural network coordinate converters and classical transformation models,RBNC delivers more accurate and stable results under challenging conditions,while maintaining comparable performance in ideal cases.These findings demonstrate the effectiveness of residual modelling as a light-weight and robust alternative for improving coordinate transformation accuracy.展开更多
文摘Design patterns offer reusable solutions for common software issues,enhancing quality.The advent of generative large language models(LLMs)marks progress in software development,but their efficacy in applying design patterns is not fully assessed.The recent introduction of generative large language models(LLMs)like ChatGPT and CoPilot has demonstrated significant promise in software development.They assist with a variety of tasks including code generation,modeling,bug fixing,and testing,leading to enhanced efficiency and productivity.Although initial uses of these LLMs have had a positive effect on software development,their potential influence on the application of design patterns remains unexplored.This study introduces a method to quantify LLMs’ability to implement design patterns,using Role-Based Metamodeling Language(RBML)for a rigorous specification of the pattern’s problem,solution,and transformation rules.The method evaluates the pattern applicability of a software application using the pattern’s problem specification.If deemed applicable,the application is input to the LLM for pattern application.The resulting application is assessed for conformance to the pattern’s solution specification and for completeness against the pattern’s transformation rules.Evaluating the method with ChatGPT 4 across three applications reveals ChatGPT’s high proficiency,achieving averages of 98%in conformance and 87%in completeness,thereby demonstrating the effectiveness of the method.Using RBML,this study confirms that LLMs,specifically ChatGPT 4,have great potential in effective and efficient application of design patterns with high conformance and completeness.This opens avenues for further integrating LLMs into complex software engineering processes.
基金supported by the National Natural Science Foundation of China(52475307)the Shandong Provincial Natural Science Foundation(ZR2023ME041).
文摘Backswimmers exhibit a high degree of mobility in water,and their different motion patterns have important implications for the design of micro-biomimetic underwater robots.This paper used three-dimensional high-speed cameras to extract the key points on the hind legs.The hind leg motion laws and the deformation laws of the setae were obtained in four motion patterns:rapid forward,cruising,in-motion turning,and in-place turning.The motion laws of each joint on the hind leg are modeled using a Fourier series.A kinematic model of hind legs was established based on the DH method,and the motion characteristics of hind legs under different motion patterns were analyzed.This paper provides basic data and theoretical models for micro-biomimetic robots.
基金supported by the National Key Research and Development Program of China(Grant No.2022YFA1402704)the National Natural Science Foundation of China(Grant No.12247101)。
文摘A uniform longitudinal field applied to the transverse Ising model(TIM)distinguishes the antiferromagnetic Ising interaction from its ferromagnetic counterpart.While the ground state of the latter shows no quantum phase transition(QPT),the ground state of the former exhibits rich phases:paramagnetic,antiferromagnetic,and possibly disordered phases.Although the first two are clearly identified,the existence of the disordered phase remains controversial.Here,we use the pattern picture to explore the competition among the antiferromagnetic Ising interaction J,the transverse field hx and the longitudinal field h_(z),and uncover which patterns are responsible for these three competing energy scales,thereby determining the possible phases and the QPTs among them.The system size ranges from L=8 to 128 and the transverse field hx is fixed at 1.Under these parameters,our results show the existence of the disordered phase.For a small h_(z),the system transitions from a disordered phase to an antiferromagnetic phase as J increases.For a large h_(z),the system undergoes two phase transitions:from paramagnetic to disordered,and then to antiferromagnetic phase.These results not only unveil the rich physics of this paradigmatic model but also stimulate quantum simulation by using currently available experimental platforms.
基金financially supported by China Geological Survey Project(No.DD20220954)Open Funding Project of the Key Laboratory of Groundwater Sciences and Engineering,Ministry of Natural Resources(No.SK202301-4)+2 种基金Science and Technology Innovation Foundation of Comprehensive Survey&Command Center for Natural Resources(No.KC20240003)Yanzhao Shanshui Science and Innovation Fund of Langfang Integrated Natural Resources Survey Center,China Geological Survey(No.YZSSJJ202401-001)Open Foundation of the Key Laboratory of Coupling Process and Effect of Natural Resources Elements(No.2022KFKTC009).
文摘Water scarcity and environment deterioration have become main constraints to sustainable economic and social development.Scientifically assessing Water Resources Carrying Capacity(WRCC)is essential for the optimal allocation of regional water resources.The hilly area at the northern foot of Yanshan Mountains is a key water conservation zone and an important water source for Beijing,Tianjin and Hebei.Grasping the current status and temporal trends of water quality and WRCC in representative small watersheds within this region is crucial for supporting rational water resources allocation and environment protection efforts.This study focuses on Pingquan City,a typical watershed in northern Hebei Province.Firstly,evaluation index systems for surface water quality,groundwater quality and WRCC were estab-lished based on the Pressure-State-Response(PSR)framework.Then,comprehensive evaluations of water quality and WRCC at the sub-watershed scale were conducted using the Varying Fuzzy Pattern Recogni-tion(VFPR)model.Finally,the rationality of the evaluation results was verified,and future scenarios were projected.Results showed that:(1)The average comprehensive evaluation scores for surface water and groundwater quality in the sub-watersheds were 1.44 and 1.46,respectively,indicating that both met the national Class II water quality standard and reflected a high-quality water environment.(2)From 2010 to 2020,the region's WRCC steadily improved,with scores rising from 2.99 to 2.83 and an average of 2.90,suggesting effective water resources management in Pingquan City.(3)According to scenario-based predic-tion,WRCC may slightly decline between 2025 and 2030,reaching 2.92 and 2.94,respectively,relative to 2020 levels.Therefore,future efforts should focus on strengthening scientific management and promoting the efficient use of water resources.Proactive measures are necessary to mitigate emerging contradiction and ensure the long-term stability and sustainability of the water resources system in the region.The evalua-tion system and spatiotemporal evolution patterns proposed in this study can provide a scientific basis for refined water resource management and ecological conservation in similar hilly areas.
基金supported by the National Natural Science Foundation of China (Grant Nos.42227901, 42476020)the Scientific Research Fund of the Second Institute of Oceanography, Ministry of Natural Resources (Grant No.QNYC2001)+4 种基金the Oceanic Interdisciplinary Program of Shanghai Jiao Tong University (Project No.SL2023MS020)the Innovation Group Project of Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai) (No.311024001)supported by the Natural Environment Research Council grant NE/W005239/1supported by the open fund of the State Key Laboratory of Satellite Ocean Environment Dynamics, Second Institute of Oceanography, MNR (No.QNHX2328)supported by the National Natural Science Foundation of China (Grant No.42222502)。
文摘The inter-model difference in the tropical Pacific SST warming pattern is a big stumbling block for reliable projections of global climate change. Here by conducting an inter-model Empirical Orthogonal Function(EOF) analysis as well as an ocean mixed-layer heat budget, we find that the first two modes of inter-model difference in the SST warming pattern projected by 30 CMIP6 models, explaining more than three-quarters of the total inter-model variance, are both tied to different cloud–radiation feedbacks. The EOF1 mode that captures the different magnitudes of El Ni?o-like warming as well as the largest inter-model variance in the far eastern equatorial Pacific, is likely driven by highly diverse cloud–radiation feedbacks in the east and, to a lesser extent, by differing changes in the oceanic vertical temperature gradient. The EOF2 mode that mainly represents the different magnitudes of SST warming in the western equatorial Pacific, is associated with differing levels of negative cloud–radiation feedback over the central equatorial Pacific through a dynamic air–sea coupled process involving both the Bjerknes feedback and the wind–evaporation–SST feedback.Considering in isolation the robust common model bias of a weak negative cloud–radiation feedback over the central equatorial Pacific, the projected SST warming in the western equatorial Pacific is likely to be smaller than the multi-model ensemble mean, thereby presenting a more weakeened zonal SST gradient than expected, implying the potential for more severe climate extremes under global warming.
基金supported by the Department of Biotechnology,Ministry of Science and Technology,Govt.India,under grant No.BT/Coord.II/10/02/2016/22.03.2018the Indian Council of Social Science Research,New Delhi,India,for providing a short-term doctoral fellowship(RFD/Short-Term/2022-23/ENV/ST/66).
文摘Understanding spatial patterns of plant species diversity and the factors(e.g.,climate and human)that drive these patterns is essential for biodiversity conservation.We used data from 1700.1-ha forest plots in the Shettihalli tropical forest landscape of the Western Ghats biodiversity hotspot,India,to analyse tree community composition and the drivers ofα-diversity(Shannon)andβ-diversity(LCBD).Compositional patterns were visualized using Non-Metric Multidimensional Scaling(NMDS),and hybrid feature selection with structural equation modeling(SEM)was employed to evaluate the direct and indirect effects of environmental variables on diversity.NMDS identified four distinct forest types in the Shettihalli landscape:semi-evergreen,dry deciduous,moist deciduous,and plantation forests,each with distinct plant composition.Shannon diversity and ecological uniqueness was significantly higher in semi-evergreen forest than in deciduous forest plots.The SEMs explained about 79%and 39–45%of the variation inα-diversity andβ-diversity.Our analysis indicated that current diversity patterns result from multiple processes,with structure,disturbance,and edaphic parameters exerting the strongest direct and indirect effects onα-diversity.β-diversity,in contrast,was largely influenced by climate,topography,stand structure,and edaphic factors.Overall,our findings indicate that various factors(e.g.,climate,topography,and human disturbance)interact to shape tree diversity patterns in tropical forests.These findings will help develop unique conservation and management strategies for distinct forest types in tropical forest ecosystems.
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funded by Science and Technology Cooperation Project of the CNPC-SWPU Innovation Alliance(2020CX050103).
文摘Research on the distribution and development of black shales in the Lianggaoshan Formation has been deficient,which has hindered exploration for lacustrine shale oil in the Sichuan Basin.Our study characterized the well logging data,core samples,outcrops,and geochemistry of black shales in the Lianggaoshan Formation in the Sichuan Basin.Our analysis focused on the lake basin evolution and the migration characteristics,paleoenvironmental features,formation mechanisms,and developmental model of the black shales.The results indicated that black shales in the Lianggaoshan Formation exhibited significant lateral migration,with an overall thickening trend from east to west.Within the 1st Member of the formation,black shale occurred as a single thick layer in the eastern region that gradually thinned toward the central region.Multiple sets of shale developed within the 2nd and 3rd members,and these had lower thicknesses than the 1st Member and migrated toward central Sichuan.Paleoproductivity and terrigenous input were the main factors controlling the deposition of black shales.A semi-humid climate influenced the deposition of black shales,bringing abundant freshwater,terrigenous debris,and nutrients into the basin.Decomposition of organic matter consumed oxygen in sediment and bottom water,causing localized oxygen deficiency in the strata.
文摘Model evaluation using benchmark datasets is an important method to measure the capability of large language models(LLMs)in specific domains,and it is mainly used to assess the knowledge and reasoning abilities of LLMs.Therefore,in order to better assess the capability of LLMs in the agricultural domain,Agri-Eval was proposed as a benchmark for assessing the knowledge and reasoning ability of LLMs in agriculture.The assessment dataset used in Agri-Eval covered seven major disciplines in the agricultural domain:crop science,horticulture,plant protection,animal husbandry,forest science,aquaculture science,and grass science,and contained a total of 2283 questions.Among domestic general-purpose LLMs,DeepSeek R1 performed best with an accuracy rate of 75.49%.In the realm of international general-purpose LLMs,Gemini 2.0 pro exp 0205 standed out as the top performer,achieving an accuracy rate of 74.28%.As an LLMs in agriculture vertical,Shennong V2.0 outperformed all the LLMs in China,and the answer accuracy rate of agricultural knowledge exceeded that of all the existing general-purpose LLMs.The launch of Agri-Eval helped the LLM developers to comprehensively evaluate the model's capability in the field of agriculture through a variety of tasks and tests to promote the development of the LLMs in the field of agriculture.
基金Supported by the National Natural Science Foundation of China(12261018)Universities Key Laboratory of Mathematical Modeling and Data Mining in Guizhou Province(2023013)。
文摘In this paper,we establish and study a single-species logistic model with impulsive age-selective harvesting.First,we prove the ultimate boundedness of the solutions of the system.Then,we obtain conditions for the asymptotic stability of the trivial solution and the positive periodic solution.Finally,numerical simulations are presented to validate our results.Our results show that age-selective harvesting is more conducive to sustainable population survival than non-age-selective harvesting.
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 the Guangdong Province Education Science Planning Project(Higher Education Project,Project No.2024GXJK410)Shenzhen Education Science“14th Five-Year Plan”2023 Annual Project on Artificial Intelligence Special Project under Grant No.rgzn23001,the Guangdong Province Higher Education Research and Reform Project under Grant No.YueJiaoGaoHan(2024)No.9+1 种基金the Guangdong Province General Colleges and Universities Innovation Team Project under No.2022KCXTD038the Guangdong Provincial Hardware and System Teaching&Research Office Quality Engineering Project under No.HITSZERP22002.
文摘This study presents a teaching reform for the Object-oriented Software Construction(OOSC)course by integrating outcome-based education(OBE)and the BOPPPS(bridge-In,objectives,pre-assessment,participatory learning,post-assessment,summary)instructional model.The reform addresses the gap between syntax-based programming instruction and the need for higher-level skills in abstraction,modularity,and software architecture.The course is anchored in a semester-long,project-based learning platform centered on a Java-based Aircraft Battle Game,progressing through six iterative experiments.Each experiment targets specific competencies within the structured BOPPPS teaching cycle and is aligned with specific OBE learning outcomes.A case study on the Factory Pattern illustrates how the BOPPPS model fosters conceptual understanding and practical application.Evaluation results from the 2023 and 2024 spring semesters show improved outcomes:Project completion rose from 87%to 95%,37%of students implemented innovative features,and average final grades increased by 7%.The results affirm that the OBE+BOPPPS integration strengthens engagement,deepens understanding,and equips students with real-world software development competencies.
文摘In their recent paper Pereira et al.(2025)claim that validation is overlooked in mapping and modelling of ecosystem services(ES).They state that“many studies lack critical evaluation of the results and no validation is provided”and that“the validation step is largely overlooked”.This assertion may have been true several years ago,for example,when Ochoa and Urbina-Cardona(2017)made a similar observation.However,there has been much work on ES model validation over the last decade.
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the World Climate Research Programme(WCRP),Climate Variability and Predictability(CLIVAR),and Global Energy and Water Exchanges(GEWEX)for facilitating the coordination of African monsoon researchsupport from the Center for Earth System Modeling,Analysis,and Data at the Pennsylvania State Universitythe support of the Office of Science of the U.S.Department of Energy Biological and Environmental Research as part of the Regional&Global Model Analysis(RGMA)program area。
文摘In recent years,there has been an increasing need for climate information across diverse sectors of society.This demand has arisen from the necessity to adapt to and mitigate the impacts of climate variability and change.Likewise,this period has seen a significant increase in our understanding of the physical processes and mechanisms that drive precipitation and its variability across different regions of Africa.By leveraging a large volume of climate model outputs,numerous studies have investigated the model representation of African precipitation as well as underlying physical processes.These studies have assessed whether the physical processes are well depicted and whether the models are fit for informing mitigation and adaptation strategies.This paper provides a review of the progress in precipitation simulation overAfrica in state-of-the-science climate models and discusses the major issues and challenges that remain.
基金National Key Research and Development Program of China,Grant/Award Number:2024YFF0507404Special Clinical Business Fund for High-Level Hospitals of China-Japan Friendship Hospital,Grant/Award Number:2024-NHLHCRF-TS-01。
文摘Background:Large language models(LLMs)have shown considerable promise in supporting clinical decision-making.However,their adoption and evaluation in dermatology remains limited.This study aimed to explore the preferences of Chinese dermatologists regarding LLM-generated responses in clinical psoriasis scenarios and to assess how they prioritize key quality dimensions,including accuracy,traceability,and logicality.Methods:A cross-sectional,web-based survey was conducted between December 25,2024,and January 22,2025,following the Checklist for Reporting Results of Internet E-Surveys guidelines.A total of 1247 valid responses were collected from practicing dermatologists across 33 of China's provincial-level administrative divisions.Participants evaluated responses to five categories of clinical questions(etiology,clinical presentation,differential diagnosis,treatment,and case study)generated by five LLMs:ChatGPT-4o,Kimi.ai,Doubao,ZuoYiGPT,and Lingyi-agent.Statistical associations between participant characteristics and model preferences were examined using chi-square tests.Results:ChatGPT-4o(Model 1)emerged as the most preferred model across all clinical tasks,consistently receiving the highest number of votes in case study(n=740),clinical presentation(n=666),differential diagnosis(n=707),etiology(n=602),and treatment(n=656).Significant variation in model preference by professional title was observed only for the differential diagnosis task(χ^(2)=21.13,df=12,p=0.0485),while no significant differences were found across hospital tiers(p>0.05).In terms of evaluation dimensions,accuracy was most frequently rated as“very important”(n=635).A significant association existed between hospital tier and the most valued dimension(χ^(2)=27.667,df=9,p=0.0011),with dermatologists in primary hospitals prioritizing traceability more than their peers in higher-tier hospitals.No significant associations were found across professional titles(p=0.127).Conclusions:Chinese dermatologists suggest a strong preference for ChatGPT-4o over domestic LLMs in psoriasis-related clinical tasks.While accuracy remains the primary criterion,traceability and logicality are also critical,particularly for clinicians in lower-tier hospitals.These findings suggest that future clinical LLMs should prioritize not only content accuracy but also source transparency and structural clarity to meet the diverse needs of different clinical settings.
基金Project supported by the National Natural Science Foundation of China(Nos.12372214 and U2341231)。
文摘The Reynolds-averaged Navier-Stokes(RANS)technique enables critical engineering predictions and is widely adopted.However,since this iterative computation relies on the fixed-point iteration,it may converge to unexpected non-physical phase points in practice.We conduct an analysis on the phase-space characteristics and the fixed-point theory underlying the k-ε turbulence model,and employ the classical Kolmogorov flow as a framework,leveraging its direct numerical simulation(DNS)data to construct a one-dimensional(1D)system under periodic/fixed boundary conditions.The RANS results demonstrate that under periodic boundary conditions,the k-ε model exhibits only a unique trivial fixed point,with asymptotes capturing the phase portraits.The stability of this trivial fixed point is determined by a mathematically derived stability phase diagram,indicating the fact that the k-ε model will never converge to correct values under periodic conditions.In contrast,under fixed boundary conditions,the model can yield a stable non-trivial fixed point.The evolutionary mechanisms and their relationship with boundary condition settings systematically explain the inherent limitations of the k-ε model,i.e.,its deficiency in computing the flow field under periodic boundary conditions and sensitivity to boundary-value specifications under fixed boundary conditions.These conclusions are finally validated with the open-source code OpenFOAM.
文摘Utilizing finite element analysis,the ballistic protection provided by a combination of perforated D-shaped and base armor plates,collectively referred to as radiator armor,is evaluated.ANSYS Explicit Dynamics is employed to simulate the ballistic impact of 7.62 mm armor-piercing projectiles on Aluminum AA5083-H116 and Steel Secure 500 armors,focusing on the evaluation of material deformation and penetration resistance at varying impact points.While the D-shaped armor plate is penetrated by the armor-piercing projectiles,the combination of the perforated D-shaped and base armor plates successfully halts penetration.A numerical model based on the finite element method is developed using software such as SolidWorks and ANSYS to analyze the interaction between radiator armor and bullet.The perforated design of radiator armor is to maintain airflow for radiator function,with hole sizes smaller than the bullet core diameter to protect radiator assemblies.Predictions are made regarding the brittle fracture resulting from the projectile core′s bending due to asymmetric impact,and the resulting fragments failed to penetrate the perforated base armor plate.Craters are formed on the surface of the perforated D-shaped armor plate due to the impact of projectile fragments.The numerical model accurately predicts hole growth and projectile penetration upon impact with the armor,demonstrating effective protection of the radiator assemblies by the radiator armor.
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National Council for Scientific and Technological Development,Grant No.421278/2023-4,No.309248/2025-6。
文摘Coordinate transformation models often fail to account for nonlinear and spatially dependent distortions,leading to significant residual errors in geospatial applications.Here,we propose a residual-based neural correction(RBNC)strategy,in which a neural network learns to model only the systematic distortions left by an initial geometric transformation.By focusing solely on residual patterns,RBNC reduces model complexity and improves performance,particularly in scenarios with sparse or structured control point configurations.We evaluate the method using both simulated datasets(with varying distortion intensities and sampling strategies)and real-world image georeferencing tasks.Compared with direct neural network coordinate converters and classical transformation models,RBNC delivers more accurate and stable results under challenging conditions,while maintaining comparable performance in ideal cases.These findings demonstrate the effectiveness of residual modelling as a light-weight and robust alternative for improving coordinate transformation accuracy.
