The study of the mechanical property and damage state of coal materials under compression is a fundamental area of research in underground mining engineering.Drawing upon the compaction effect and linear energy dissip...The study of the mechanical property and damage state of coal materials under compression is a fundamental area of research in underground mining engineering.Drawing upon the compaction effect and linear energy dissipation(LED)law,a novel compressive damage constitutive model for brittle coal is proposed.Utilizing the energy-defined damage method for mate-rials,the LED law is innovatively introduced to accurately characterize the energy dissipation during the loading process,and a novel formula for characterizing the damage variable of brittle coal is proposed.On this basis,considering that the constitutive model based on the hypothesis of strain equivalence is incapable of accurately describing the compaction effect exhibited by coal material during the compression process,a correction coefficient is proposed and apply it in the novel damage constitutive model.The established conventional monotone loading and single-cyclic loading-unloading uniaxial compression damage constitutive models have been validated using experimental data from cylindrical and cuboid coal specimens.In addition,compared with the constitutive model obtained via the traditional energy calculation method based on the hypothesis that the unloading curve is a straight line,the constitutive model employing LED law can describe the stress-strain state of brittle coal more precisely.This approach introduces a new perspective and enhances the convenience for constructing the constitutive model based on energy theory.展开更多
High ground temperature and unloading disturbance have emerged as critical factors impacting the property of cemented gauge-fly ash backfill(CGFB).The characteristics of energy and damage in CGFB were analyzed under c...High ground temperature and unloading disturbance have emerged as critical factors impacting the property of cemented gauge-fly ash backfill(CGFB).The characteristics of energy and damage in CGFB were analyzed under conditions of high ground temperature and unloading by conducting triaxial unloading tests with different initial confining pressures on CGFB that had been cured at various temperatures.Based on dissipative energy,triaxial unloading confining pressure damage constitutive model of CGFB was constructed.It has been demonstrated that the ratio of elastic strain energy in CGFB decreases and the ratio of dissipated energy increases at the end of unloading increases under higher curing temperature.The change in the elastic energy consumption ratio curve of CGFB,which shifts from a gradual increase to a swift rise at a certain"inflection point",can be utilized as a criterion for evaluating the failure of the unloading strength of CGFB.The triaxial unloading damage constitutive model for CGFB divides the damage progression into three distinct phases:initial damage stage,accelerated damage development stage,and rapid damage growth stage.The research findings offer a theoretical foundation for evaluating the extent of damage to CGFB caused by the combined influences of elevated ground temperature and unloading.展开更多
To explore the distribution law of the temperature field in the motor pump and the influence of the fanshaped DC channel with spoiler in the pump housing on its heat dissipation performance.This study takes the arc-ge...To explore the distribution law of the temperature field in the motor pump and the influence of the fanshaped DC channel with spoiler in the pump housing on its heat dissipation performance.This study takes the arc-gear type hydraulicmotor pump as the research object.In COMSOL,a coupled heat transfer simulationmodel of themotor pump’s fluid-solid coupling is established,and the internal temperature field characteristics are analyzed.To improve the heat dissipation effect of the motor pump,it is proposed to arrange spoiler in the fan-shaped DC channel of the pump housing to enhance heat dissipation.Three types of spoilers,namely,wing-shaped,inclined rectangle-shaped,and wave-shaped,are designed.The simulation results show that when the motor pump operates under rated conditions,due to the poor heat dissipation environment inside the motor pump,the high-temperature areas of the motor pump are concentrated in the rotor and permanent magnet parts.After arranging the spoiler,the turbulent kinetic energy and vorticity in the fan-shaped DC channel of the pump housing are significantly enhanced.All three spoiler structures can reduce the maximum temperature of each component of the motor.According to the comprehensive performance evaluation criterion(PEC),the inclined rectangle-shaped structure has the best comprehensive heat transfer performance(PEC=1.114),while the wave-shaped structure has higher heat transfer efficiency but greater pressure loss.The wing-shaped structure has relatively limited enhancement effect on heat dissipation.This study systematically quantifies the influence of different spoiler structures on heat dissipation performance and flowresistance characteristics,providing a solution for enhancing the heat dissipation of the motor pump.展开更多
Lithium-ion batteries(LIBs)are widely used in electrochemical battery energy storage systems(BESS)because of their high energy density,lack of memory effects,low self-discharge rate,and long cycle life.However,inadequ...Lithium-ion batteries(LIBs)are widely used in electrochemical battery energy storage systems(BESS)because of their high energy density,lack of memory effects,low self-discharge rate,and long cycle life.However,inadequate heat dissipation during their discharge process can significantly degrade battery performance.The improvement of BESS efficiency depends on the optimization of thermal management structures.In this work,we integrate the pseudo-two-dimensional(P2D)electrochemical model with a three-dimensional thermal model to analyze the heat generation and transfer processes within the BESS.The simulation results are closely aligned with the experimental results in terms of voltage and temperature rise curves.Under air cooling conditions of 293.15 K and 3 m·s^(-1),the BESS has a maximum temperature of 308.60 K and a temperature difference of 9.22 K,ensuring safe operation.At 1 C,we suggest that enlarging the inlet and outlet areas improves the air-cooling efficiency,and transitioning environmental air-cooling temperatures after 2400 s of discharge effectively reduces the temperature difference and the energy consumption of the cooling equipment.This work provides valuable theoretical insights for optimizing the thermal design of BESS.展开更多
By combining the merits of radiative cooling(RC)and evaporation cooling(EC),radiative coupled evaporative cooling(REC)has attracted considerable attention for sub-ambient cooling purposes.However,for outdoor devices,t...By combining the merits of radiative cooling(RC)and evaporation cooling(EC),radiative coupled evaporative cooling(REC)has attracted considerable attention for sub-ambient cooling purposes.However,for outdoor devices,the interior heating power would increase the working temperature and fire risk,which would suppress their above-ambient heat dissipation capabilities and passive water cycle properties.In this work,we introduced a REC design based on an all-in-one photonic hydrogel for above-ambient heat dissipation and flame retardancy.Unlike conventional design RC film for heat dissipation with limited cooling power and fire risk,REC hydrogel can greatly improve the heat dissipation performance in the daytime with a high workload,indicating a 12.0℃lower temperature than the RC film under the same conditions in the outdoor experiment.In the nighttime with a low workload,RC-assisted adsorption can improve atmospheric water harvesting to ensure EC in the daytime.In addition,our REC hydrogel significantly enhanced flame retardancy by absorbing heat without a corresponding temperature rise,thus mitigating fire risks.Thus,our design shows a promising solution for the thermal management of outdoor devices,delivering outstanding performance in both heat dissipation and flame retardancy.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
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
To enhance the mechanical reliability of dental prostheses under long-term service conditions,this study aimed to evaluate the fracture behavior and energy dissipation characteristics of three commonly used prosthetic...To enhance the mechanical reliability of dental prostheses under long-term service conditions,this study aimed to evaluate the fracture behavior and energy dissipation characteristics of three commonly used prosthetic materials,namely,zirconia ceramics(ZrO_(2)),cobalt-chromium alloy(Co-Cr),and titanium-zirconium alloy(Ti-13Zr),under various crack configurations.A three-dimensional finite element model of a single-crown prosthesis incorporating predefined cracks was established,and both axial and oblique multidirectional loads were applied.Using LS-DYNA software,the deformation patterns,principal stress distribution,and energy release characteristics during crack propagation were systematically analyzed.The experimental results indicate that Ti-13Zr alloy exhibited the highest crack resistance,making it particularly suitable for patients with insufficient bone volume or limited implant space.Co-Cr alloy demonstrated favorable structural stability and mechanical performance under high-load conditions.In contrast,due to its inherent brittleness,ZrO_(2)was more prone to rapid fracture propagation in long-span or high-stress scenarios,although it remains a preferred option for anterior esthetic zones and patients with metal sensitivities.Furthermore,the simulation outcomes were theoretically validated using Griffith's energy-based fracture criterion,reinforcing the accuracy of failure predictions based on principal stress analysis.This study elucidates the differences in clinical applicability among prosthetic materials and reveals their distinct fracture mechanisms,thereby providing a theoretical foundation for optimizing material selection and structural design.The findings contribute to improving the long-term safety and functional stability of implant-supported dental restorations.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
Recommendation systems are key to boosting user engagement,satisfaction,and retention,particularly on media platforms where personalized content is vital.Sequential recommendation systems learn from user-item interact...Recommendation systems are key to boosting user engagement,satisfaction,and retention,particularly on media platforms where personalized content is vital.Sequential recommendation systems learn from user-item interactions to predict future items of interest.However,many current methods rely on unique user and item IDs,limiting their ability to represent users and items effectively,especially in zero-shot learning scenarios where training data is scarce.With the rapid development of Large Language Models(LLMs),researchers are exploring their potential to enhance recommendation systems.However,there is a semantic gap between the linguistic semantics of LLMs and the collaborative semantics of recommendation systems,where items are typically indexed by IDs.Moreover,most research focuses on item representations,neglecting personalized user modeling.To address these issues,we propose a sequential recommendation framework using LLMs,called CIT-Rec,a model that integrates Collaborative semantics for user representation and Image and Text information for item representation to enhance Recommendations.Specifically,by aligning intuitive image information with text containing semantic features,we can more accurately represent items,improving item representation quality.We focus not only on item representations but also on user representations.To more precisely capture users’personalized preferences,we use traditional sequential recommendation models to train on users’historical interaction data,effectively capturing behavioral patterns.Finally,by combining LLMs and traditional sequential recommendation models,we allow the LLM to understand linguistic semantics while capturing collaborative semantics.Extensive evaluations on real-world datasets show that our model outperforms baseline methods,effectively combining user interaction history with item visual and textual modalities to provide personalized recommendations.展开更多
The National Geophysical Data Center(NGDC)of the United States has collected aeromagnetic data for input into a series of geomagnetic models to improve model resolution;however,in the Tibetan Plateau region,ground-bas...The National Geophysical Data Center(NGDC)of the United States has collected aeromagnetic data for input into a series of geomagnetic models to improve model resolution;however,in the Tibetan Plateau region,ground-based observations remain insufficient to clearly reflect the characteristics of the region’s lithospheric magnetism.In this study,we evaluate the lithospheric magnetism of the Tibetan Plateau by using a 3D surface spline model based on observations from>200 newly constructed repeat stations(portable stations)to determine the spatial distribution of plateau geomagnetism,as well as its correlation with the tectonic features of the region.We analyze the relationships between M≥5 earthquakes and lithospheric magnetic field variations on the Tibetan Plateau and identify regions susceptible to strong earthquakes.We compare the geomagnetic results with those from an enhanced magnetic model(EMM2015)developed by the NGDC and provide insights into improving lithospheric magnetic field calculations in the Tibetan Plateau region.Further research reveals that these magnetic anomalies exhibit distinct differences from the magnetic-seismic correlation mechanisms observed in other tectonic settings;here,they are governed primarily by the combined effects of compressional magnetism,thermal magnetism,and deep thermal stress.This study provides new evidence of geomagnetic anomalies on the Tibetan Plateau,interprets them physically,and demonstrates their potential for identifying seismic hazard zones on the Plateau.展开更多
(Quasi-)closed-form results for the statistical properties of unmanned aerial vehicle(UAV)airto-ground channels are derived for the first time using a novel spatial-vector-based method from a threedimensional(3-D)arbi...(Quasi-)closed-form results for the statistical properties of unmanned aerial vehicle(UAV)airto-ground channels are derived for the first time using a novel spatial-vector-based method from a threedimensional(3-D)arbitrary-elevation one-cylinder model.The derived results include a closed-form expression for the space-time correlation function and some quasi-closed-form ones for the space-Doppler power spectrum density,the level crossing rate,and the average fading duration,which are shown to be the generalizations of those previously obtained from the two-dimensional(2-D)one-ring model and the 3-D low-elevation one-cylinder model for terrestrial mobile-to-mobile channels.The close agreements between the theoretical results and the simulations as well as the measurements validate the utility of the derived channel statistics.Based on the derived expressions,the impacts of some parameters on the channel characteristics are investigated in an effective,efficient,and explicable way,which leads to a general guideline on the manual parameter estimation from the measurement description.展开更多
Effective management of mining areas in the Luo River Basin,located in the eastern Qinling Mountains,is vital for the integrated protection and restoration needed to support the high-quality development of the Yellow ...Effective management of mining areas in the Luo River Basin,located in the eastern Qinling Mountains,is vital for the integrated protection and restoration needed to support the high-quality development of the Yellow River Basin.Using the‘cupball'model,this study analyzes the limiting factors and restoration characteristics across four mining areas and proposes a conceptual model for selecting appropriate restoration approaches.A second conceptual model is then introduced to address regional development needs,incorporating ecological conservation,safety protection,and people's wellbeing.The applicability of the integrated model selection framework is demonstrated through a case study on the south bank of the Qinglongjian River.The results indicate that:(1)The key limiting factors are similar across cases,but the degree of ecological degradation varies.(2)Mildly degraded areas are represented by a shallower and narrower‘cup',where natural recovery is the preferred approach,whereas moderately and severely degraded systems call for assisted regeneration and ecological reconstruction,respectively.(3)When the restoration models determined based on limiting factors and development needs are consistent,the model is directly applicable;if they differ,the option involving less artificial intervention is preferred;(4)Monitoring of the restored mining area on the Qinglongjian River's south bank confirms significant improvements in soil erosion control and vegetation coverage.This study provides a transferable methodology for balancing resource extraction with ecosystem conservation,offering practical insights for other ecologically vulnerable mining regions.展开更多
Accurate forecasting of tropical cyclone(TC)tracks and intensities is essential.Although the TianXing large weather model,a six-hourly forecasting model surpassing operational forecasts,exhibits superior performance,i...Accurate forecasting of tropical cyclone(TC)tracks and intensities is essential.Although the TianXing large weather model,a six-hourly forecasting model surpassing operational forecasts,exhibits superior performance,its TC forecasts still require enhancement.Prediction errors persist due to biases in the training data and smoothing effects in data-driven methods.To address this,we introduce CycloneBCNet,a deep-learning model designed to correct TianXing’s TC forecast biases by leveraging spatial and temporal data.CycloneBCNet utilizes the SimVP(simpler yet better video prediction)framework with spatial attention to highlight cyclone core regions in forecast fields.It also incorporates TC trend information(center position,maximum wind speed,and minimum sea level pressure)via an LSTM(long short-term memory)module.These TC vectors are derived from post-processed TianXing forecasts.By fusing features from forecast fields and TC vectors,CycloneBCNet corrects biases across multiple lead times.At a 96-h lead time,the track error reduces from 162.4 to 86.4 km,the wind speed error from 17.2 to 6.69 m s^(-1),and the pressure error from 22.2 to 9.36 hPa.Interpretability analysis shows that CycloneBCNet adjusts its attention across forecast lead times.Intensity corrections prioritize inner-core dynamics,particularly the eye and eyewall,while track corrections shift from lower-level variables and the cyclone’s core to broader environmental factors and mid-to upper-level features as the forecast duration increases.These findings demonstrate that CycloneBCNet effectively captures key TC dynamics consistent with meteorological principles,including the dominance of near-surface conditions for intensity and the increasing influence of steering currents on track prediction.展开更多
Climate model prediction has been improved by enhancing model resolution as well as the implementation of sophisticated physical parameterization and refinement of data assimilation systems[section 6.1 in Wang et al.(...Climate model prediction has been improved by enhancing model resolution as well as the implementation of sophisticated physical parameterization and refinement of data assimilation systems[section 6.1 in Wang et al.(2025)].In relation to seasonal forecasting and climate projection in the East Asian summer monsoon season,proper simulation of the seasonal migration of rain bands by models is a challenging and limiting factor[section 7.1 in Wang et al.(2025)].展开更多
The collection and annotation of lar ge-scale bird datasets are resource-intensive and time-consuming processes that significantly limit the scalability and accuracy of biodiversity monitoring systems.While self-super...The collection and annotation of lar ge-scale bird datasets are resource-intensive and time-consuming processes that significantly limit the scalability and accuracy of biodiversity monitoring systems.While self-supervised learning(SSL)has emerged as a promising approach for leveraging unannotated data,current SSL methods face two critical challenges in bird species recognition:(1)long-tailed data distributions that result in poor performance on underrepresented species;and(2)domain shift issues caused by data augmentation strategies designed to mitigate class imbalance.Here we present SDNet,a novel SSL-based bird recognition framework that integrates diffusion models with large language models(LLMs)to overcome these limitations.SDNet employs LLMs to generate semantically rich textual descriptions for tail-class species by prompting the models with species taxonomy,morphological attributes,and habitat information,producing detailed natural language priors that capture fine-grained visual characteristics(e.g.,plumage patterns,body proportions,and distinctive markings).These textual descriptions are subsequently used by a conditional diffusion model to synthesize new bird image samples through cross-attention mechanisms that fuse textual embeddings with intermediate visual feature representations during the denoising process,ensuring generated images preserve species-specific morphological details while maintaining photorealistic quality.Additionally,we incorporate a Swin Transformer as the feature extraction backbone whose hierarchical window-based attention mechanism and shifted windowing scheme enable multi-scale local feature extraction that proves particularly effective at capturing finegrained discriminative patterns(such as beak shape and feather texture)while mitigating domain shift between synthetic and original images through consistent feature representations across both data sources.SDNet is validated on both a self-constructed dataset(Bird_BXS)an d a publicly available benchmark(Birds_25),demonstrating substantial improvements over conventional SSL approaches.Our results indicate that the synergistic integration of LLMs,diffusion models,and the Swin Transformer architecture contributes significantly to recognition accuracy,particularly for rare and morphologically similar species.These findings highlight the potential of SDNet for addressing fundamental limitations of existing SSL methods in avian recognition tasks and establishing a new paradigm for efficient self-supervised learning in large-scale ornithological vision applications.展开更多
基金supported by the National Science Fund for Distinguished Young Scholars(52225403)the National Natural Science Foundation of China(42077244).
文摘The study of the mechanical property and damage state of coal materials under compression is a fundamental area of research in underground mining engineering.Drawing upon the compaction effect and linear energy dissipation(LED)law,a novel compressive damage constitutive model for brittle coal is proposed.Utilizing the energy-defined damage method for mate-rials,the LED law is innovatively introduced to accurately characterize the energy dissipation during the loading process,and a novel formula for characterizing the damage variable of brittle coal is proposed.On this basis,considering that the constitutive model based on the hypothesis of strain equivalence is incapable of accurately describing the compaction effect exhibited by coal material during the compression process,a correction coefficient is proposed and apply it in the novel damage constitutive model.The established conventional monotone loading and single-cyclic loading-unloading uniaxial compression damage constitutive models have been validated using experimental data from cylindrical and cuboid coal specimens.In addition,compared with the constitutive model obtained via the traditional energy calculation method based on the hypothesis that the unloading curve is a straight line,the constitutive model employing LED law can describe the stress-strain state of brittle coal more precisely.This approach introduces a new perspective and enhances the convenience for constructing the constitutive model based on energy theory.
基金Project(2024YFC2911000)supported by the National Key Research and Development Program Young Scientist Project,ChinaProject(2022HWYQ-078)supported by the Natural Science Foundation of Shandong Province of China+1 种基金Project(tsqn202103074)supported by the"Taishan Scholars Young Expert Program"of Shandong Province,ChinaProject(2023GX051)supported by the Tai'an Science and Technology Innovation Development Project(Policy Guidance),China。
文摘High ground temperature and unloading disturbance have emerged as critical factors impacting the property of cemented gauge-fly ash backfill(CGFB).The characteristics of energy and damage in CGFB were analyzed under conditions of high ground temperature and unloading by conducting triaxial unloading tests with different initial confining pressures on CGFB that had been cured at various temperatures.Based on dissipative energy,triaxial unloading confining pressure damage constitutive model of CGFB was constructed.It has been demonstrated that the ratio of elastic strain energy in CGFB decreases and the ratio of dissipated energy increases at the end of unloading increases under higher curing temperature.The change in the elastic energy consumption ratio curve of CGFB,which shifts from a gradual increase to a swift rise at a certain"inflection point",can be utilized as a criterion for evaluating the failure of the unloading strength of CGFB.The triaxial unloading damage constitutive model for CGFB divides the damage progression into three distinct phases:initial damage stage,accelerated damage development stage,and rapid damage growth stage.The research findings offer a theoretical foundation for evaluating the extent of damage to CGFB caused by the combined influences of elevated ground temperature and unloading.
基金supported by the Henan Provincial Key Research and Development Special Project(251111220200)Natural Science Foundation of Henan Province Project(252300420446).
文摘To explore the distribution law of the temperature field in the motor pump and the influence of the fanshaped DC channel with spoiler in the pump housing on its heat dissipation performance.This study takes the arc-gear type hydraulicmotor pump as the research object.In COMSOL,a coupled heat transfer simulationmodel of themotor pump’s fluid-solid coupling is established,and the internal temperature field characteristics are analyzed.To improve the heat dissipation effect of the motor pump,it is proposed to arrange spoiler in the fan-shaped DC channel of the pump housing to enhance heat dissipation.Three types of spoilers,namely,wing-shaped,inclined rectangle-shaped,and wave-shaped,are designed.The simulation results show that when the motor pump operates under rated conditions,due to the poor heat dissipation environment inside the motor pump,the high-temperature areas of the motor pump are concentrated in the rotor and permanent magnet parts.After arranging the spoiler,the turbulent kinetic energy and vorticity in the fan-shaped DC channel of the pump housing are significantly enhanced.All three spoiler structures can reduce the maximum temperature of each component of the motor.According to the comprehensive performance evaluation criterion(PEC),the inclined rectangle-shaped structure has the best comprehensive heat transfer performance(PEC=1.114),while the wave-shaped structure has higher heat transfer efficiency but greater pressure loss.The wing-shaped structure has relatively limited enhancement effect on heat dissipation.This study systematically quantifies the influence of different spoiler structures on heat dissipation performance and flowresistance characteristics,providing a solution for enhancing the heat dissipation of the motor pump.
基金sponsored by the National Key Research and Development Program of China(2022YFA1503501)the National Natural Science Foundation of China(22278127,22378112)+1 种基金the Fundamental Research Funds for the Central Universities(2022ZFJH004)21C Innovation Laboratory,Contemporary Amperex Technology Ltd by project No.21C-368 OP-202312,Shanghai Pilot Proaram for Basic Research(22T01400100-18)。
文摘Lithium-ion batteries(LIBs)are widely used in electrochemical battery energy storage systems(BESS)because of their high energy density,lack of memory effects,low self-discharge rate,and long cycle life.However,inadequate heat dissipation during their discharge process can significantly degrade battery performance.The improvement of BESS efficiency depends on the optimization of thermal management structures.In this work,we integrate the pseudo-two-dimensional(P2D)electrochemical model with a three-dimensional thermal model to analyze the heat generation and transfer processes within the BESS.The simulation results are closely aligned with the experimental results in terms of voltage and temperature rise curves.Under air cooling conditions of 293.15 K and 3 m·s^(-1),the BESS has a maximum temperature of 308.60 K and a temperature difference of 9.22 K,ensuring safe operation.At 1 C,we suggest that enlarging the inlet and outlet areas improves the air-cooling efficiency,and transitioning environmental air-cooling temperatures after 2400 s of discharge effectively reduces the temperature difference and the energy consumption of the cooling equipment.This work provides valuable theoretical insights for optimizing the thermal design of BESS.
基金financially supported by the Science and Technology Innovation Program of Hunan Province(2024RC3003)the Central South University Innovation-Driven Research Programme(2023CXQD012)the Initiative for Sustainable Energy for its financial support。
文摘By combining the merits of radiative cooling(RC)and evaporation cooling(EC),radiative coupled evaporative cooling(REC)has attracted considerable attention for sub-ambient cooling purposes.However,for outdoor devices,the interior heating power would increase the working temperature and fire risk,which would suppress their above-ambient heat dissipation capabilities and passive water cycle properties.In this work,we introduced a REC design based on an all-in-one photonic hydrogel for above-ambient heat dissipation and flame retardancy.Unlike conventional design RC film for heat dissipation with limited cooling power and fire risk,REC hydrogel can greatly improve the heat dissipation performance in the daytime with a high workload,indicating a 12.0℃lower temperature than the RC film under the same conditions in the outdoor experiment.In the nighttime with a low workload,RC-assisted adsorption can improve atmospheric water harvesting to ensure EC in the daytime.In addition,our REC hydrogel significantly enhanced flame retardancy by absorbing heat without a corresponding temperature rise,thus mitigating fire risks.Thus,our design shows a promising solution for the thermal management of outdoor devices,delivering outstanding performance in both heat dissipation and flame retardancy.
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.
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Funded by the National Key R&D Program of China(No.2023YFC2412300)the Technology Development Project of Shan-dong Weigao Orthopedic Materials Co.,Ltd.(No.20221h0074)the Independent Innovation Research Fund of Wuhan University of Technology(No.104972024ZHZXhp0027)。
文摘To enhance the mechanical reliability of dental prostheses under long-term service conditions,this study aimed to evaluate the fracture behavior and energy dissipation characteristics of three commonly used prosthetic materials,namely,zirconia ceramics(ZrO_(2)),cobalt-chromium alloy(Co-Cr),and titanium-zirconium alloy(Ti-13Zr),under various crack configurations.A three-dimensional finite element model of a single-crown prosthesis incorporating predefined cracks was established,and both axial and oblique multidirectional loads were applied.Using LS-DYNA software,the deformation patterns,principal stress distribution,and energy release characteristics during crack propagation were systematically analyzed.The experimental results indicate that Ti-13Zr alloy exhibited the highest crack resistance,making it particularly suitable for patients with insufficient bone volume or limited implant space.Co-Cr alloy demonstrated favorable structural stability and mechanical performance under high-load conditions.In contrast,due to its inherent brittleness,ZrO_(2)was more prone to rapid fracture propagation in long-span or high-stress scenarios,although it remains a preferred option for anterior esthetic zones and patients with metal sensitivities.Furthermore,the simulation outcomes were theoretically validated using Griffith's energy-based fracture criterion,reinforcing the accuracy of failure predictions based on principal stress analysis.This study elucidates the differences in clinical applicability among prosthetic materials and reveals their distinct fracture mechanisms,thereby providing a theoretical foundation for optimizing material selection and structural design.The findings contribute to improving the long-term safety and functional stability of implant-supported dental restorations.
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supported by the National Key R&D Program of China[2022YFF0902703]the State Administration for Market Regulation Science and Technology Plan Project(2024MK033).
文摘Recommendation systems are key to boosting user engagement,satisfaction,and retention,particularly on media platforms where personalized content is vital.Sequential recommendation systems learn from user-item interactions to predict future items of interest.However,many current methods rely on unique user and item IDs,limiting their ability to represent users and items effectively,especially in zero-shot learning scenarios where training data is scarce.With the rapid development of Large Language Models(LLMs),researchers are exploring their potential to enhance recommendation systems.However,there is a semantic gap between the linguistic semantics of LLMs and the collaborative semantics of recommendation systems,where items are typically indexed by IDs.Moreover,most research focuses on item representations,neglecting personalized user modeling.To address these issues,we propose a sequential recommendation framework using LLMs,called CIT-Rec,a model that integrates Collaborative semantics for user representation and Image and Text information for item representation to enhance Recommendations.Specifically,by aligning intuitive image information with text containing semantic features,we can more accurately represent items,improving item representation quality.We focus not only on item representations but also on user representations.To more precisely capture users’personalized preferences,we use traditional sequential recommendation models to train on users’historical interaction data,effectively capturing behavioral patterns.Finally,by combining LLMs and traditional sequential recommendation models,we allow the LLM to understand linguistic semantics while capturing collaborative semantics.Extensive evaluations on real-world datasets show that our model outperforms baseline methods,effectively combining user interaction history with item visual and textual modalities to provide personalized recommendations.
基金supported by the CAS Pioneer Hundred Talents Program and Second Tibetan Plateau Scientific Expedition Research Program(2019QZKK0708)as well as the Basic Research Program of Qinghai Province:Lithospheric Geomagnetic Field of the Qinghai-Tibet Plateau and the Relationship with Strong Earthquakes(2021-ZJ-969Q).
文摘The National Geophysical Data Center(NGDC)of the United States has collected aeromagnetic data for input into a series of geomagnetic models to improve model resolution;however,in the Tibetan Plateau region,ground-based observations remain insufficient to clearly reflect the characteristics of the region’s lithospheric magnetism.In this study,we evaluate the lithospheric magnetism of the Tibetan Plateau by using a 3D surface spline model based on observations from>200 newly constructed repeat stations(portable stations)to determine the spatial distribution of plateau geomagnetism,as well as its correlation with the tectonic features of the region.We analyze the relationships between M≥5 earthquakes and lithospheric magnetic field variations on the Tibetan Plateau and identify regions susceptible to strong earthquakes.We compare the geomagnetic results with those from an enhanced magnetic model(EMM2015)developed by the NGDC and provide insights into improving lithospheric magnetic field calculations in the Tibetan Plateau region.Further research reveals that these magnetic anomalies exhibit distinct differences from the magnetic-seismic correlation mechanisms observed in other tectonic settings;here,they are governed primarily by the combined effects of compressional magnetism,thermal magnetism,and deep thermal stress.This study provides new evidence of geomagnetic anomalies on the Tibetan Plateau,interprets them physically,and demonstrates their potential for identifying seismic hazard zones on the Plateau.
基金supported in part by the National Key Research and Development Program of China(2021YFB2900501)in part by the Shaanxi Science and Technology Innovation Team(2023-CX-TD-03)+3 种基金in part by the Science and Technology Program of Shaanxi Province(2021GXLH-Z-038)in part by the Natural Science Foundation of Hunan Province(2023JJ40607 and 2023JJ50045)in part by the Scientific Research Foundation of Hunan Provincial Education Department(23B0713 and 24B0603)in part by the National Natural Science Foundation of China(62401371,62101275,and 62372070).
文摘(Quasi-)closed-form results for the statistical properties of unmanned aerial vehicle(UAV)airto-ground channels are derived for the first time using a novel spatial-vector-based method from a threedimensional(3-D)arbitrary-elevation one-cylinder model.The derived results include a closed-form expression for the space-time correlation function and some quasi-closed-form ones for the space-Doppler power spectrum density,the level crossing rate,and the average fading duration,which are shown to be the generalizations of those previously obtained from the two-dimensional(2-D)one-ring model and the 3-D low-elevation one-cylinder model for terrestrial mobile-to-mobile channels.The close agreements between the theoretical results and the simulations as well as the measurements validate the utility of the derived channel statistics.Based on the derived expressions,the impacts of some parameters on the channel characteristics are investigated in an effective,efficient,and explicable way,which leads to a general guideline on the manual parameter estimation from the measurement description.
基金supported by Special major projects for research and development of Henan Provincial(Science and Technology Research Project)(No.252102321104)Humanities and Social Sciences Youth Foundation,Ministry of Education(24YJCZH410)。
文摘Effective management of mining areas in the Luo River Basin,located in the eastern Qinling Mountains,is vital for the integrated protection and restoration needed to support the high-quality development of the Yellow River Basin.Using the‘cupball'model,this study analyzes the limiting factors and restoration characteristics across four mining areas and proposes a conceptual model for selecting appropriate restoration approaches.A second conceptual model is then introduced to address regional development needs,incorporating ecological conservation,safety protection,and people's wellbeing.The applicability of the integrated model selection framework is demonstrated through a case study on the south bank of the Qinglongjian River.The results indicate that:(1)The key limiting factors are similar across cases,but the degree of ecological degradation varies.(2)Mildly degraded areas are represented by a shallower and narrower‘cup',where natural recovery is the preferred approach,whereas moderately and severely degraded systems call for assisted regeneration and ecological reconstruction,respectively.(3)When the restoration models determined based on limiting factors and development needs are consistent,the model is directly applicable;if they differ,the option involving less artificial intervention is preferred;(4)Monitoring of the restored mining area on the Qinglongjian River's south bank confirms significant improvements in soil erosion control and vegetation coverage.This study provides a transferable methodology for balancing resource extraction with ecosystem conservation,offering practical insights for other ecologically vulnerable mining regions.
基金supported by the Meteorological Joint Funds of the National Natural Science Foundation of China(Grant No.U2142211)the National Natural Science Foundation of China(Grant Nos.42075141,42341202 and 62088101)+1 种基金the National Key Research and Development Program of China(Grant No.2020YFA0608000)the Shanghai Municipal Science and Technology Major Project(Grant No.2021SHZDZX0100).
文摘Accurate forecasting of tropical cyclone(TC)tracks and intensities is essential.Although the TianXing large weather model,a six-hourly forecasting model surpassing operational forecasts,exhibits superior performance,its TC forecasts still require enhancement.Prediction errors persist due to biases in the training data and smoothing effects in data-driven methods.To address this,we introduce CycloneBCNet,a deep-learning model designed to correct TianXing’s TC forecast biases by leveraging spatial and temporal data.CycloneBCNet utilizes the SimVP(simpler yet better video prediction)framework with spatial attention to highlight cyclone core regions in forecast fields.It also incorporates TC trend information(center position,maximum wind speed,and minimum sea level pressure)via an LSTM(long short-term memory)module.These TC vectors are derived from post-processed TianXing forecasts.By fusing features from forecast fields and TC vectors,CycloneBCNet corrects biases across multiple lead times.At a 96-h lead time,the track error reduces from 162.4 to 86.4 km,the wind speed error from 17.2 to 6.69 m s^(-1),and the pressure error from 22.2 to 9.36 hPa.Interpretability analysis shows that CycloneBCNet adjusts its attention across forecast lead times.Intensity corrections prioritize inner-core dynamics,particularly the eye and eyewall,while track corrections shift from lower-level variables and the cyclone’s core to broader environmental factors and mid-to upper-level features as the forecast duration increases.These findings demonstrate that CycloneBCNet effectively captures key TC dynamics consistent with meteorological principles,including the dominance of near-surface conditions for intensity and the increasing influence of steering currents on track prediction.
文摘Climate model prediction has been improved by enhancing model resolution as well as the implementation of sophisticated physical parameterization and refinement of data assimilation systems[section 6.1 in Wang et al.(2025)].In relation to seasonal forecasting and climate projection in the East Asian summer monsoon season,proper simulation of the seasonal migration of rain bands by models is a challenging and limiting factor[section 7.1 in Wang et al.(2025)].
基金supported by the National Natural Science Foundation of China(32471964)。
文摘The collection and annotation of lar ge-scale bird datasets are resource-intensive and time-consuming processes that significantly limit the scalability and accuracy of biodiversity monitoring systems.While self-supervised learning(SSL)has emerged as a promising approach for leveraging unannotated data,current SSL methods face two critical challenges in bird species recognition:(1)long-tailed data distributions that result in poor performance on underrepresented species;and(2)domain shift issues caused by data augmentation strategies designed to mitigate class imbalance.Here we present SDNet,a novel SSL-based bird recognition framework that integrates diffusion models with large language models(LLMs)to overcome these limitations.SDNet employs LLMs to generate semantically rich textual descriptions for tail-class species by prompting the models with species taxonomy,morphological attributes,and habitat information,producing detailed natural language priors that capture fine-grained visual characteristics(e.g.,plumage patterns,body proportions,and distinctive markings).These textual descriptions are subsequently used by a conditional diffusion model to synthesize new bird image samples through cross-attention mechanisms that fuse textual embeddings with intermediate visual feature representations during the denoising process,ensuring generated images preserve species-specific morphological details while maintaining photorealistic quality.Additionally,we incorporate a Swin Transformer as the feature extraction backbone whose hierarchical window-based attention mechanism and shifted windowing scheme enable multi-scale local feature extraction that proves particularly effective at capturing finegrained discriminative patterns(such as beak shape and feather texture)while mitigating domain shift between synthetic and original images through consistent feature representations across both data sources.SDNet is validated on both a self-constructed dataset(Bird_BXS)an d a publicly available benchmark(Birds_25),demonstrating substantial improvements over conventional SSL approaches.Our results indicate that the synergistic integration of LLMs,diffusion models,and the Swin Transformer architecture contributes significantly to recognition accuracy,particularly for rare and morphologically similar species.These findings highlight the potential of SDNet for addressing fundamental limitations of existing SSL methods in avian recognition tasks and establishing a new paradigm for efficient self-supervised learning in large-scale ornithological vision applications.
