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 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
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
In-space cable-driven manipulators exhibit several advantages,such as a large range of motion,high dexterity,and lightweight structure.However,kinematic and dynamic analysis play an essential role in designing a cable...In-space cable-driven manipulators exhibit several advantages,such as a large range of motion,high dexterity,and lightweight structure.However,kinematic and dynamic analysis play an essential role in designing a cable-driven manipulator.In this paper,the kinematic analysis of a type of cable-driven manipulator is performed,and a motion planning scheme is conducted to actuate this manipulator.Moreover,a flexible multi-body dynamic model of a cable-driven manipulator considering the frictional contact between the cables and pulleys is established.To describe properties such as flexibility,vibration,and variable length of the cable,this paper utilizes reducedorder beam elements of the Absolute Nodal Coordinates Formulation(ANCF)in Arbitrary Lagrangian Eulerian(ALE)framework.Additionally,a virtual element is introduced to model the contact segment in the cable-pulley system.A tension decay factor is employed to account for the friction in the contact segment.To validate the proposed method,a semi-analytical model based on D'Alembert's principle is established.Cross-verification is performed to validate the accuracy of both models.The model is further applied to simulate the rotation of the cable-driven manipulator with different structural parameters and frictional factors.The results from the analyses provide valuable guidance for the design and motion control of the in-space cable-driven manipulator.Finally,a prototype of a single module is manufactured and tested.Ground experiments are carried out to verify the kinematic and dynamic models.展开更多
This study traces the development of the Shanghai Typhoon Model(SHTM)from a traditional physics-based regional model toward a data-driven,machine-learning typhoon forecasting system.After upgrading its initial and bou...This study traces the development of the Shanghai Typhoon Model(SHTM)from a traditional physics-based regional model toward a data-driven,machine-learning typhoon forecasting system.After upgrading its initial and boundary conditions,SHTM now leverages large-scale constraints from machine-learning weather prediction(MLWP)models,resulting in an ML–physics hybrid framework.During Typhoon Danas(2025),the hybrid SHTM achieves substantially lower track errors than both the advanced ECMWF Integrated Forecasting System(IFS)and leading MLWP models such as PanGu and FuXi.Furthermore,the hybrid SHTM consistently maintains mean track errors below 200 km up to a forecast lead time of 108 hours,representing a significant advancement in forecast accuracy.In addition,this study highlights the technical roadmap for transitioning from a physics-based typhoon model to a fully data-driven ML typhoon forecast system.It also emphasizes that advances in the physical modeling framework provide a critical foundation for further improving the performance of future data-driven ML typhoon models.展开更多
Establishing a Regional Marine Innovation Ecosystem(RMIE)is crucial for advancing China’s maritime power strategy.Concurrently,developing a competitive RMIE serves as a strategic lever to enhance the global competiti...Establishing a Regional Marine Innovation Ecosystem(RMIE)is crucial for advancing China’s maritime power strategy.Concurrently,developing a competitive RMIE serves as a strategic lever to enhance the global competitiveness of China’s marine science sector.However,research on the competitiveness of RMIE is limited.To this end,this study constructs an evaluation index system based on ecological niche theory to assess the competitiveness of RMIE in China from 2008 to 2020.The findings indicate generally fluctuating upward trends in RMIE’s competitiveness,with Shandong,Jiangsu,and Guangdong showing relatively strong positions.Notably,there are significant intra-regional imbalances and inter-regional asynchrony in RMIE’s competitiveness across China’s three major marine economic circles.Recognizing that forecasting RMIE competitiveness can inform policy formulation,this paper proposes a systematic multivariate grey interval prediction model that incorporates spatial proximity effects.This model effectively captures the interval and uncertainty characteristics of RMIE’s competitiveness while considering spatial relationships among regions.Results from comparative analysis,robustness tests,and sensitivity analysis demonstrate its superior applicability and forecasting accuracy.Additionally,interval forecasts and scenario analyses suggest that RMIE competitiveness will maintain stable growth,although unbalanced and unsynchronized development is likely to persist.Overall,the approach developed for evaluating and forecasting RMIE competitiveness offers valuable insights for effective policy formulation.展开更多
Background:Chronic hyperuricemia is associated with complications such as gout and uric acid nephropathy,but uric acid also exhibits biological activities(e.g.,antioxidant effects,potential neuroprotective properties ...Background:Chronic hyperuricemia is associated with complications such as gout and uric acid nephropathy,but uric acid also exhibits biological activities(e.g.,antioxidant effects,potential neuroprotective properties against neurodegenerative diseases).Nonhuman primates are ideal models for studying neurodegenerative diseases;however,existing nonhuman primate hyperuricemia models cannot sustain long-term elevated serum uric acid levels,nor recapitulate the impaired uric acid excretion observed in clinical hyperuricemic patients.Methods:First,we detected uricase expression in cynomolgus monkeys and compared it with that in mice.Then,we established a cynomolgus monkey hyperuricemia model by administering a mixture of potassium oxonate,hydrochlorothiazide,and adenine via fruits and vegetables.We further analyzed the regulatory effects of this model on uric acid metabolism(synthesis,degradation,and excretion)and the expression of uric acid transporter genes in the intestine and kidney.Results:Cynomolgus monkeys express functional uricase,but at a lower level than mice.The established model maintained stable,long-term hyperuricemia by three mechanisms:increasing intestinal and renal uric acid excretion load,inhibiting hepatic uric acid degradation,and promoting uric acid synthesis.Additionally,the model downregulated the expression of intestinal/renal uric acid-secreting transporter genes,while upregulating uric acid-reabsorbing transporter genes.Conclusions:This novel cynomolgus monkey hyperuricemia model provides a new tool for investigating the association between hyperuricemia and neurodegenerative diseases,and will help clarify the mechanism by which serum uric acid influences cognitive function.展开更多
The rapid advancement of machine learning based tight-binding Hamiltonian(MLTB)methods has opened new avenues for efficient and accurate electronic structure simulations,particularly in large-scale systems and long-ti...The rapid advancement of machine learning based tight-binding Hamiltonian(MLTB)methods has opened new avenues for efficient and accurate electronic structure simulations,particularly in large-scale systems and long-time scenarios.This review begins with a concise overview of traditional tight-binding(TB)models,including both(semi-)empirical and first-principles approaches,establishing the foundation for understanding MLTB developments.We then present a systematic classification of existing MLTB methodologies,grouped into two major categories:direct prediction of TB Hamiltonian elements and inference of empirical parameters.A comparative analysis with other ML-based electronic structure models is also provided,highlighting the advancement of MLTB approaches.Finally,we explore the emerging MLTB application ecosystem,highlighting how the integration of MLTB models with a diverse suite of post-processing tools from linear-scaling solvers to quantum transport frameworks and molecular dynamics interfaces is essential for tackling complex scientific problems across different domains.The continued advancement of this integrated paradigm promises to accelerate materials discovery and open new frontiers in the predictive simulation of complex quantum phenomena.展开更多
Background:Skeletal tuberculosis(TB)remains a persistent clinical and research chal-lenge due to its chronic course,osteolytic destruction,and the limitations of existing animal models,which often require high-level b...Background:Skeletal tuberculosis(TB)remains a persistent clinical and research chal-lenge due to its chronic course,osteolytic destruction,and the limitations of existing animal models,which often require high-level biosafety containment or fail to repli-cate human skeletal pathology.Methods:This study developed a biosafe,accessible,and versatile murine model of skeletal TB using Mycobacterium smegmatis,a fast-growing,nonpathogenic myco-bacterial species with high genomic homology to Mycobacterium tuberculosis.Three infection routes-subperiosteal calvarial injection,intratibial injection,and intra-cardiac inoculation-were systematically evaluated for their ability to induce lo-calized versus disseminated bone infection under standard biosafety level(BSL)-1 conditions.Results:Subperiosteal calvarial and intratibial injection of M.smegmatis induced local-ized bone lesions characterized by osteolysis,sequestrum formation,granulomatous inflammation,and increased osteoclast activity.Intratibial infection additionally trig-gered compartment-specific immune responses,including neutrophil and macrophage expansion,transient B-cell depletion,and activation of interferon-γ^(+)(IFN-γ^(+))T cells,reflecting active immune remodeling at the infection site.Systemic dissemination via intracardiac injection reproducibly generated progressive vertebral and tibial bone destruction with organized granuloma formation and immune cell infiltration but without prominent sequestrum formation.Compared to intratibial infection,intracar-diac delivery exhibited lower intragroup variability and more closely recapitulated the diffuse progression of extrapulmonary skeletal tuberculosis.Conclusions:This M.smegmatis-based murine model provides a straightforward,reliable,and immunopathologically relevant platform for exploring host-pathogen dynamics,immune-driven bone destruction,and early-stage therapeutic testing in skeletal TB,all within standard BSL-1 laboratories.This model fills a critical gap by enabling BSL-1 research into skeletal TB mechanisms and drug development.展开更多
To investigate the influence of coarse aggregate parent rock properties on the elastic modulus of concrete,the mineralogical properties and stress-strain curves of granite and dolomite parent rocks,as well as the stre...To investigate the influence of coarse aggregate parent rock properties on the elastic modulus of concrete,the mineralogical properties and stress-strain curves of granite and dolomite parent rocks,as well as the strength and elastic modulus of mortar and concrete prepared with mechanism aggregates of the corresponding lithology,and the stress-strain curves of concrete were investigated.In this paper,a coarse aggregate and mortar matrix bonding assumption is proposed,and a prediction model for the elastic modulus of mortar is established by considering the lithology of the mechanism sand and the slurry components.An equivalent coarse aggregate elastic modulus model was established by considering factors such as coarse aggregate particle size,volume fraction,and mortar thickness between coarse aggregates.Based on the elastic modulus of the equivalent coarse aggregate and the remaining mortar,a prediction model for the elastic modulus of the two and three components of concrete in series and then in parallel was established,and the predicted values differed from the measured values within 10%.It is proposed that the coarse aggregate elastic modulus in highstrength concrete is the most critical factor affecting the elastic modulus of concrete,and as the coarse aggregate elastic modulus increases by 27.7%,the concrete elastic modulus increases by 19.5%.展开更多
Background:This study aims to explore the establishment of an animal model of car-diac injury induced by trimethylamine-N-oxide(TMAO),a metabolite secreted by gut microorganisms,and to investigate its application in m...Background:This study aims to explore the establishment of an animal model of car-diac injury induced by trimethylamine-N-oxide(TMAO),a metabolite secreted by gut microorganisms,and to investigate its application in moderate-intensity continuous training(MICT)intervention.Methods:C57BL6/J mice were randomly divided into four groups:normal mice(Nor,n=15);mice administered TMAO(TMAO,n=15);mice undergoing(Nor+MICT,n=15);mice undergoing(MICT)and administered TMAO(TMAO+MICT,n=15).Mice in the TMAO and TMAO+MICT groups received daily gavage of high-dose TMAO for 8 weeks,whereas those in the Nor+MICT and TMAO+MICT groups underwent MICT for 8 weeks(60 min per session,5 days per week,at 50%maximal running capacity).Cardiac function was evaluated using ultrasound,myocardial histology was examined using hematoxylin and eosin(HE)staining,and nuclear magnetic resonance(NMR)-based metabolomics was employed for multivariate statistical and metabolic pathway analyses.Results:Relative to the Nor group,TMAO-treated mice exhibited significant weight loss,elevated heart rate,and reduced ejection fraction and left ventricular fractional shortening,indicating cardiac impairment.Importantly,the TMAO+MICT group dem-onstrated significant improvements in these parameters compared to the TMAO group,alongside distinct alterations in myocardial metabolic profiles.TMAO altered five metabolic pathways relative to controls,whereas MICT induced significant changes in three pathways in TMAO-treated mice.Conclusion:Eight weeks of high-dose TMAO administration induced significant cardiac dysfunction in mice,which was effectively mitigated by MICT intervention.Consequently,this animal model serves as a valuable tool for investigating the mecha-nisms underlying the impact of MICT on cardiovascular diseases.展开更多
Glassy polymers are widely used in biomedical applications in a solvent environment,yet their long-term performance is governed by the competing effects of physical aging and solvent-induced plasticization.Here,we dev...Glassy polymers are widely used in biomedical applications in a solvent environment,yet their long-term performance is governed by the competing effects of physical aging and solvent-induced plasticization.Here,we develop a constitutive model that explicitly couples the solvent concentration,structural relaxation,and mechanical response.This framework is built on a multiplicative decomposition of deformation and an Eyring-type flow rule,with structural evolution described by an effective temperature.A generalized shift factor is introduced to quantify how the solvent concentration and effective temperature jointly affect the relaxation time,thereby integrating physical aging and plasticization.The model is subsequently applied to methacrylate(MA)-based copolymer networks immersed in phosphate-buffered saline for up to nine months.Simulations accurately capture key experimental features,including the strong softening of highly swellable networks,the partial recovery due to aging,and the mitigating role of hydrophobic crosslinking in reducing solvent uptake.While the current single-mode description cannot reproduce the full relaxation spectrum,it establishes an efficient framework for predicting the long-term mechanical performance under coupled environmental and mechanical loading.This study provides a constitutive description of solvent-swollen glassy polymers,offering mechanistic insight into the interplay between plasticization and aging.Beyond biomedical MA networks,this framework establishes a foundation for predicting the long-term performance of polymer glasses under coupled aqueous environmental and mechanical loading.展开更多
Background:Healthy non-pharmacological lifestyle factors,such as regular physical exercise and dietary supplementation,have been shown to significantly improve cognitive outcomes over time compared to a more sedentary...Background:Healthy non-pharmacological lifestyle factors,such as regular physical exercise and dietary supplementation,have been shown to significantly improve cognitive outcomes over time compared to a more sedentary lifestyle and poor diet.Furthermore,exercise may serve as a potential protective factor in attenuating the effects associated with cognitive decline that are characteristic of neurodegenerative disorders,such as Alzheimer's disease(AD).Evidence indicates that certain dietary interventions can also attenuate the effects of neurodegeneration and positively impact longevity.Supplementation with polyphenols such as ellagic acid(EA),which is abundant in pomegranate juice,may help provide neuroprotective and longevity benefits.Methods:This study examined the potential protective potential of EA and exercise and provides insight into the combined use of a polyphenol-rich diet and exercise to enhance behavioral outcomes and lifespan in a transgenic Drosophila melanogaster(fruit fly)model of AD with the Aβ_(42) gene.Results:Fruit flies subjected to a 120-minute exercise regimen performed better on a climbing assay than flies that did not exercise.Conversely,flies that exercised for 30 min passed marginally more trials on a learning and memory assay using an aversive stimulus than flies that did not exercise,whereas both groups performed better than flies subjected to the more intense exercise condition.Conclusion:These results suggest a hormetic effect of exercise regarding memory performance.Finally,flies fed a low dose of dietary EA(0.24 mg/mL)lived significantly longer than flies fed the control diet or higher concentrations of EA,again suggesting a hormetic effect of EA on longevity.展开更多
Business Process Modelling(BPM)is essential for analyzing,improving,and automating the flow of information within organizations,but traditional approaches based on manual interpretation are slow,error-prone,and requir...Business Process Modelling(BPM)is essential for analyzing,improving,and automating the flow of information within organizations,but traditional approaches based on manual interpretation are slow,error-prone,and require a high level of expertise.This article proposes an innovative alternative solution that overcomes these limitations by automatically generating comprehensive Business Process Modelling and Notation(BPMN)diagrams solely from verbal descriptions of the processes to be modeled,utilizing Large Language Models(LLMs)and multimodal Artificial Intelligence(AI).Experimental results,based on video recordings of process explanations provided by an expert from an organization(in this case,the Commercial Courts of a public justice administration),demonstrate that the proposed methodology successfully enables the automatic generation of complete and accurate BPMN diagrams,leading to significant improvements in the speed,accuracy,and accessibility of process modeling.This research makes a substantial contribution to the field of business process modeling,as its methodology is groundbreaking in its use of LLMs and multimodal AI capabilities to handle different types of source material(text and video),combining several tools to minimize the number of queries and reduce the complexity of the prompts required for the automatic generation of successful BPMN diagrams.展开更多
Pathological scarring,manifested in the form of hypertrophic scars(HTS)and keloid scars(KS),represents a major clinical challenge due to its aesthetic and functional implications for patients.Understanding the molecul...Pathological scarring,manifested in the form of hypertrophic scars(HTS)and keloid scars(KS),represents a major clinical challenge due to its aesthetic and functional implications for patients.Understanding the molecular mechanisms involved in these types of scars and developing effective treatments requires the use of controlled ex-perimental models,especially animals,to overcome the limitations of clinical studies.The aim of this sistematic review is to critically analyze the animal models used in the last five years(2020-2025)for the study of pathological scars,highlighting their advantages,limitations and applicability in the development of new therapeutic strat-egies.Murine,rabbit and porcine models,as well as alternative models,offer varied perspectives on the formation and treatment of HTS and KS,with an emphasis on histological and molecular correlations with human pathology.By synthesizing recent data,the paper highlights the essential role of preclinical research in optimizing an-tifibrotic treatments and in advancing the translation of data into the clinical sphere.Overall,animal models remain essential for bridging mechanistic insights with clinical translation,supporting the development of more effective and personalized anti-scar therapies.展开更多
Against the backdrop of continuous social development and growing public health demands,the efficiency and scientific nature of the emergency care system are of paramount importance.This paper focuses on researching t...Against the backdrop of continuous social development and growing public health demands,the efficiency and scientific nature of the emergency care system are of paramount importance.This paper focuses on researching the construction of an emergency care system based on the concept of“linkage”,delving into its theoretical foundations,exploring innovative construction models,and analyzing practical cases.The study indicates that an emergency care system under the“linkage”concept can effectively integrate resources and enhance efficiency,providing new insights for improving the construction of the emergency care system.It aims to promote the development of the emergency care system towards a more scientific,efficient,and collaborative direction.展开更多
Activation pruning reduces neural network complexity by eliminating low-importance neuron activations,yet identifying the critical pruning threshold—beyond which accuracy rapidly deteriorates—remains computationally...Activation pruning reduces neural network complexity by eliminating low-importance neuron activations,yet identifying the critical pruning threshold—beyond which accuracy rapidly deteriorates—remains computationally expensive and typically requires exhaustive search.We introduce a thermodynamics-inspired framework that treats activation distributions as energy-filtered physical systems and employs the free energy of activations as a principled evaluation metric.Phase-transition-like phenomena in the free-energy profile—such as extrema,inflection points,and curvature changes—yield reliable estimates of the critical pruning threshold,providing a theoretically grounded means of predicting sharp accuracy degradation.To further enhance efficiency,we propose a renormalized free energy technique that approximates full-evaluation free energy using only the activation distribution of the unpruned network.This eliminates repeated forward passes,dramatically reducing computational overhead and achieving speedups of up to 550×for MLPs.Extensive experiments across diverse vision architectures(MLP,CNN,ResNet,MobileNet,Vision Transformer)and text models(LSTM,BERT,ELECTRA,T5,GPT-2)on multiple datasets validate the generality,robustness,and computational efficiency of our approach.Overall,this work establishes a theoretically grounded and practically effective framework for activation pruning,bridging the gap between analytical understanding and efficient deployment of sparse neural networks.展开更多
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 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.
基金co-supported by the National Natural Science Foundation of China(Nos.12102034 and 12125201)the Open Fund of State Key Laboratory of Robotics and Systems(HIT),China。
文摘In-space cable-driven manipulators exhibit several advantages,such as a large range of motion,high dexterity,and lightweight structure.However,kinematic and dynamic analysis play an essential role in designing a cable-driven manipulator.In this paper,the kinematic analysis of a type of cable-driven manipulator is performed,and a motion planning scheme is conducted to actuate this manipulator.Moreover,a flexible multi-body dynamic model of a cable-driven manipulator considering the frictional contact between the cables and pulleys is established.To describe properties such as flexibility,vibration,and variable length of the cable,this paper utilizes reducedorder beam elements of the Absolute Nodal Coordinates Formulation(ANCF)in Arbitrary Lagrangian Eulerian(ALE)framework.Additionally,a virtual element is introduced to model the contact segment in the cable-pulley system.A tension decay factor is employed to account for the friction in the contact segment.To validate the proposed method,a semi-analytical model based on D'Alembert's principle is established.Cross-verification is performed to validate the accuracy of both models.The model is further applied to simulate the rotation of the cable-driven manipulator with different structural parameters and frictional factors.The results from the analyses provide valuable guidance for the design and motion control of the in-space cable-driven manipulator.Finally,a prototype of a single module is manufactured and tested.Ground experiments are carried out to verify the kinematic and dynamic models.
基金supported by the Special Project-Original Exploration(Grant No.42450163)the National Youth Science Foundation of China Project(Grant No.4240050560)the Research and Development of Key Technologies for Artificial Intelligence Regional Typhoon Forecasting Model project.
文摘This study traces the development of the Shanghai Typhoon Model(SHTM)from a traditional physics-based regional model toward a data-driven,machine-learning typhoon forecasting system.After upgrading its initial and boundary conditions,SHTM now leverages large-scale constraints from machine-learning weather prediction(MLWP)models,resulting in an ML–physics hybrid framework.During Typhoon Danas(2025),the hybrid SHTM achieves substantially lower track errors than both the advanced ECMWF Integrated Forecasting System(IFS)and leading MLWP models such as PanGu and FuXi.Furthermore,the hybrid SHTM consistently maintains mean track errors below 200 km up to a forecast lead time of 108 hours,representing a significant advancement in forecast accuracy.In addition,this study highlights the technical roadmap for transitioning from a physics-based typhoon model to a fully data-driven ML typhoon forecast system.It also emphasizes that advances in the physical modeling framework provide a critical foundation for further improving the performance of future data-driven ML typhoon models.
基金National Social Science Fund of China,No.24BTJ037Significant Project of the National Social Science Foundation of China,No.23&ZD102+1 种基金The Key Research Base for Philosophy and Social Sciences in Hangzhou:ESG and Sustainable Development Research Center,No.25JD053Zhejiang Provincial Statistical Scientific Research Project,No.25TJZZ12。
文摘Establishing a Regional Marine Innovation Ecosystem(RMIE)is crucial for advancing China’s maritime power strategy.Concurrently,developing a competitive RMIE serves as a strategic lever to enhance the global competitiveness of China’s marine science sector.However,research on the competitiveness of RMIE is limited.To this end,this study constructs an evaluation index system based on ecological niche theory to assess the competitiveness of RMIE in China from 2008 to 2020.The findings indicate generally fluctuating upward trends in RMIE’s competitiveness,with Shandong,Jiangsu,and Guangdong showing relatively strong positions.Notably,there are significant intra-regional imbalances and inter-regional asynchrony in RMIE’s competitiveness across China’s three major marine economic circles.Recognizing that forecasting RMIE competitiveness can inform policy formulation,this paper proposes a systematic multivariate grey interval prediction model that incorporates spatial proximity effects.This model effectively captures the interval and uncertainty characteristics of RMIE’s competitiveness while considering spatial relationships among regions.Results from comparative analysis,robustness tests,and sensitivity analysis demonstrate its superior applicability and forecasting accuracy.Additionally,interval forecasts and scenario analyses suggest that RMIE competitiveness will maintain stable growth,although unbalanced and unsynchronized development is likely to persist.Overall,the approach developed for evaluating and forecasting RMIE competitiveness offers valuable insights for effective policy formulation.
基金The Yunnan“Xingdian Talent Program”Yunling Scholar Project,(Grant No.CA24129L025A)National Natural Science Foundation of China,Grant/Award Number:32160157 and 82160564Major Science and Technology Project of Yunnan Province(Grant No.202202AG050008)。
文摘Background:Chronic hyperuricemia is associated with complications such as gout and uric acid nephropathy,but uric acid also exhibits biological activities(e.g.,antioxidant effects,potential neuroprotective properties against neurodegenerative diseases).Nonhuman primates are ideal models for studying neurodegenerative diseases;however,existing nonhuman primate hyperuricemia models cannot sustain long-term elevated serum uric acid levels,nor recapitulate the impaired uric acid excretion observed in clinical hyperuricemic patients.Methods:First,we detected uricase expression in cynomolgus monkeys and compared it with that in mice.Then,we established a cynomolgus monkey hyperuricemia model by administering a mixture of potassium oxonate,hydrochlorothiazide,and adenine via fruits and vegetables.We further analyzed the regulatory effects of this model on uric acid metabolism(synthesis,degradation,and excretion)and the expression of uric acid transporter genes in the intestine and kidney.Results:Cynomolgus monkeys express functional uricase,but at a lower level than mice.The established model maintained stable,long-term hyperuricemia by three mechanisms:increasing intestinal and renal uric acid excretion load,inhibiting hepatic uric acid degradation,and promoting uric acid synthesis.Additionally,the model downregulated the expression of intestinal/renal uric acid-secreting transporter genes,while upregulating uric acid-reabsorbing transporter genes.Conclusions:This novel cynomolgus monkey hyperuricemia model provides a new tool for investigating the association between hyperuricemia and neurodegenerative diseases,and will help clarify the mechanism by which serum uric acid influences cognitive function.
基金supported by the Advanced Materials-National Science and Technology Major Project(Grant No.2025ZD0618401)the National Natural Science Foundation of China(Grant No.12504285)+1 种基金the Natural Science Foundation of Jiangsu Province(Grant No.BK20250472)NFSG grant from BITS-Pilani,Dubai campus。
文摘The rapid advancement of machine learning based tight-binding Hamiltonian(MLTB)methods has opened new avenues for efficient and accurate electronic structure simulations,particularly in large-scale systems and long-time scenarios.This review begins with a concise overview of traditional tight-binding(TB)models,including both(semi-)empirical and first-principles approaches,establishing the foundation for understanding MLTB developments.We then present a systematic classification of existing MLTB methodologies,grouped into two major categories:direct prediction of TB Hamiltonian elements and inference of empirical parameters.A comparative analysis with other ML-based electronic structure models is also provided,highlighting the advancement of MLTB approaches.Finally,we explore the emerging MLTB application ecosystem,highlighting how the integration of MLTB models with a diverse suite of post-processing tools from linear-scaling solvers to quantum transport frameworks and molecular dynamics interfaces is essential for tackling complex scientific problems across different domains.The continued advancement of this integrated paradigm promises to accelerate materials discovery and open new frontiers in the predictive simulation of complex quantum phenomena.
基金Southwest Hospital Boqing Innovation Fund,Grant/Award Number:2024BQCXJJ-9Fundings for Young Investigators of PLA,Grant/Award Number:2022-JCJQ-QT-004+3 种基金NSFC Key Projects of the Regional Innovation and Development Joint Fund,Grant/Award Number:U23A20413China Postdoctoral Science Foundation,Grant/Award Number:2023M744280National Natural Science Foundation of China,Grant/Award Number:82103778,82172449 and 82172489Southwest Hospital Postdoctoral Starting Fund,Grant/Award Number:5175ZA36BP。
文摘Background:Skeletal tuberculosis(TB)remains a persistent clinical and research chal-lenge due to its chronic course,osteolytic destruction,and the limitations of existing animal models,which often require high-level biosafety containment or fail to repli-cate human skeletal pathology.Methods:This study developed a biosafe,accessible,and versatile murine model of skeletal TB using Mycobacterium smegmatis,a fast-growing,nonpathogenic myco-bacterial species with high genomic homology to Mycobacterium tuberculosis.Three infection routes-subperiosteal calvarial injection,intratibial injection,and intra-cardiac inoculation-were systematically evaluated for their ability to induce lo-calized versus disseminated bone infection under standard biosafety level(BSL)-1 conditions.Results:Subperiosteal calvarial and intratibial injection of M.smegmatis induced local-ized bone lesions characterized by osteolysis,sequestrum formation,granulomatous inflammation,and increased osteoclast activity.Intratibial infection additionally trig-gered compartment-specific immune responses,including neutrophil and macrophage expansion,transient B-cell depletion,and activation of interferon-γ^(+)(IFN-γ^(+))T cells,reflecting active immune remodeling at the infection site.Systemic dissemination via intracardiac injection reproducibly generated progressive vertebral and tibial bone destruction with organized granuloma formation and immune cell infiltration but without prominent sequestrum formation.Compared to intratibial infection,intracar-diac delivery exhibited lower intragroup variability and more closely recapitulated the diffuse progression of extrapulmonary skeletal tuberculosis.Conclusions:This M.smegmatis-based murine model provides a straightforward,reliable,and immunopathologically relevant platform for exploring host-pathogen dynamics,immune-driven bone destruction,and early-stage therapeutic testing in skeletal TB,all within standard BSL-1 laboratories.This model fills a critical gap by enabling BSL-1 research into skeletal TB mechanisms and drug development.
基金Funded by State Railway Administration Research Project(No.2023JS007)National Natural Science Foundation of China(No.52438002)+1 种基金Research and Development Programs for Science and Technology of China Railways Corporation(No.J2023G003)New Cornerstone Science Foundation through the XPLORER PRIZE。
文摘To investigate the influence of coarse aggregate parent rock properties on the elastic modulus of concrete,the mineralogical properties and stress-strain curves of granite and dolomite parent rocks,as well as the strength and elastic modulus of mortar and concrete prepared with mechanism aggregates of the corresponding lithology,and the stress-strain curves of concrete were investigated.In this paper,a coarse aggregate and mortar matrix bonding assumption is proposed,and a prediction model for the elastic modulus of mortar is established by considering the lithology of the mechanism sand and the slurry components.An equivalent coarse aggregate elastic modulus model was established by considering factors such as coarse aggregate particle size,volume fraction,and mortar thickness between coarse aggregates.Based on the elastic modulus of the equivalent coarse aggregate and the remaining mortar,a prediction model for the elastic modulus of the two and three components of concrete in series and then in parallel was established,and the predicted values differed from the measured values within 10%.It is proposed that the coarse aggregate elastic modulus in highstrength concrete is the most critical factor affecting the elastic modulus of concrete,and as the coarse aggregate elastic modulus increases by 27.7%,the concrete elastic modulus increases by 19.5%.
基金National Natural Science Foundation of China,Grant/Award Number:32271496China Fundamental Research Funds for the Central Universities(Bejing Sport University)Grant/Award Number:2024TZJK001。
文摘Background:This study aims to explore the establishment of an animal model of car-diac injury induced by trimethylamine-N-oxide(TMAO),a metabolite secreted by gut microorganisms,and to investigate its application in moderate-intensity continuous training(MICT)intervention.Methods:C57BL6/J mice were randomly divided into four groups:normal mice(Nor,n=15);mice administered TMAO(TMAO,n=15);mice undergoing(Nor+MICT,n=15);mice undergoing(MICT)and administered TMAO(TMAO+MICT,n=15).Mice in the TMAO and TMAO+MICT groups received daily gavage of high-dose TMAO for 8 weeks,whereas those in the Nor+MICT and TMAO+MICT groups underwent MICT for 8 weeks(60 min per session,5 days per week,at 50%maximal running capacity).Cardiac function was evaluated using ultrasound,myocardial histology was examined using hematoxylin and eosin(HE)staining,and nuclear magnetic resonance(NMR)-based metabolomics was employed for multivariate statistical and metabolic pathway analyses.Results:Relative to the Nor group,TMAO-treated mice exhibited significant weight loss,elevated heart rate,and reduced ejection fraction and left ventricular fractional shortening,indicating cardiac impairment.Importantly,the TMAO+MICT group dem-onstrated significant improvements in these parameters compared to the TMAO group,alongside distinct alterations in myocardial metabolic profiles.TMAO altered five metabolic pathways relative to controls,whereas MICT induced significant changes in three pathways in TMAO-treated mice.Conclusion:Eight weeks of high-dose TMAO administration induced significant cardiac dysfunction in mice,which was effectively mitigated by MICT intervention.Consequently,this animal model serves as a valuable tool for investigating the mecha-nisms underlying the impact of MICT on cardiovascular diseases.
基金the funding support from the Smart Medicine and Engineering Interdisciplinary Innovation Project of Ningbo University(No.ZHYG003)。
文摘Glassy polymers are widely used in biomedical applications in a solvent environment,yet their long-term performance is governed by the competing effects of physical aging and solvent-induced plasticization.Here,we develop a constitutive model that explicitly couples the solvent concentration,structural relaxation,and mechanical response.This framework is built on a multiplicative decomposition of deformation and an Eyring-type flow rule,with structural evolution described by an effective temperature.A generalized shift factor is introduced to quantify how the solvent concentration and effective temperature jointly affect the relaxation time,thereby integrating physical aging and plasticization.The model is subsequently applied to methacrylate(MA)-based copolymer networks immersed in phosphate-buffered saline for up to nine months.Simulations accurately capture key experimental features,including the strong softening of highly swellable networks,the partial recovery due to aging,and the mitigating role of hydrophobic crosslinking in reducing solvent uptake.While the current single-mode description cannot reproduce the full relaxation spectrum,it establishes an efficient framework for predicting the long-term mechanical performance under coupled environmental and mechanical loading.This study provides a constitutive description of solvent-swollen glassy polymers,offering mechanistic insight into the interplay between plasticization and aging.Beyond biomedical MA networks,this framework establishes a foundation for predicting the long-term performance of polymer glasses under coupled aqueous environmental and mechanical loading.
基金supported by the Hartman Behavioral Neuroscience Laboratory.
文摘Background:Healthy non-pharmacological lifestyle factors,such as regular physical exercise and dietary supplementation,have been shown to significantly improve cognitive outcomes over time compared to a more sedentary lifestyle and poor diet.Furthermore,exercise may serve as a potential protective factor in attenuating the effects associated with cognitive decline that are characteristic of neurodegenerative disorders,such as Alzheimer's disease(AD).Evidence indicates that certain dietary interventions can also attenuate the effects of neurodegeneration and positively impact longevity.Supplementation with polyphenols such as ellagic acid(EA),which is abundant in pomegranate juice,may help provide neuroprotective and longevity benefits.Methods:This study examined the potential protective potential of EA and exercise and provides insight into the combined use of a polyphenol-rich diet and exercise to enhance behavioral outcomes and lifespan in a transgenic Drosophila melanogaster(fruit fly)model of AD with the Aβ_(42) gene.Results:Fruit flies subjected to a 120-minute exercise regimen performed better on a climbing assay than flies that did not exercise.Conversely,flies that exercised for 30 min passed marginally more trials on a learning and memory assay using an aversive stimulus than flies that did not exercise,whereas both groups performed better than flies subjected to the more intense exercise condition.Conclusion:These results suggest a hormetic effect of exercise regarding memory performance.Finally,flies fed a low dose of dietary EA(0.24 mg/mL)lived significantly longer than flies fed the control diet or higher concentrations of EA,again suggesting a hormetic effect of EA on longevity.
基金funded by Fundación CajaCanarias and Fundación Bancaria“la Caixa”,grant number 2023DIG11.
文摘Business Process Modelling(BPM)is essential for analyzing,improving,and automating the flow of information within organizations,but traditional approaches based on manual interpretation are slow,error-prone,and require a high level of expertise.This article proposes an innovative alternative solution that overcomes these limitations by automatically generating comprehensive Business Process Modelling and Notation(BPMN)diagrams solely from verbal descriptions of the processes to be modeled,utilizing Large Language Models(LLMs)and multimodal Artificial Intelligence(AI).Experimental results,based on video recordings of process explanations provided by an expert from an organization(in this case,the Commercial Courts of a public justice administration),demonstrate that the proposed methodology successfully enables the automatic generation of complete and accurate BPMN diagrams,leading to significant improvements in the speed,accuracy,and accessibility of process modeling.This research makes a substantial contribution to the field of business process modeling,as its methodology is groundbreaking in its use of LLMs and multimodal AI capabilities to handle different types of source material(text and video),combining several tools to minimize the number of queries and reduce the complexity of the prompts required for the automatic generation of successful BPMN diagrams.
基金Ministry of Research,Innovation and Digitization,CCCDI-UEFISCDI,Grant/Award Number:PN-IV-P7-7.1-PED-2024-1578,within PNCDI Ⅳ.
文摘Pathological scarring,manifested in the form of hypertrophic scars(HTS)and keloid scars(KS),represents a major clinical challenge due to its aesthetic and functional implications for patients.Understanding the molecular mechanisms involved in these types of scars and developing effective treatments requires the use of controlled ex-perimental models,especially animals,to overcome the limitations of clinical studies.The aim of this sistematic review is to critically analyze the animal models used in the last five years(2020-2025)for the study of pathological scars,highlighting their advantages,limitations and applicability in the development of new therapeutic strat-egies.Murine,rabbit and porcine models,as well as alternative models,offer varied perspectives on the formation and treatment of HTS and KS,with an emphasis on histological and molecular correlations with human pathology.By synthesizing recent data,the paper highlights the essential role of preclinical research in optimizing an-tifibrotic treatments and in advancing the translation of data into the clinical sphere.Overall,animal models remain essential for bridging mechanistic insights with clinical translation,supporting the development of more effective and personalized anti-scar therapies.
文摘Against the backdrop of continuous social development and growing public health demands,the efficiency and scientific nature of the emergency care system are of paramount importance.This paper focuses on researching the construction of an emergency care system based on the concept of“linkage”,delving into its theoretical foundations,exploring innovative construction models,and analyzing practical cases.The study indicates that an emergency care system under the“linkage”concept can effectively integrate resources and enhance efficiency,providing new insights for improving the construction of the emergency care system.It aims to promote the development of the emergency care system towards a more scientific,efficient,and collaborative direction.
基金output of a research project implemented as part of the Basic Research Program at HSE University。
文摘Activation pruning reduces neural network complexity by eliminating low-importance neuron activations,yet identifying the critical pruning threshold—beyond which accuracy rapidly deteriorates—remains computationally expensive and typically requires exhaustive search.We introduce a thermodynamics-inspired framework that treats activation distributions as energy-filtered physical systems and employs the free energy of activations as a principled evaluation metric.Phase-transition-like phenomena in the free-energy profile—such as extrema,inflection points,and curvature changes—yield reliable estimates of the critical pruning threshold,providing a theoretically grounded means of predicting sharp accuracy degradation.To further enhance efficiency,we propose a renormalized free energy technique that approximates full-evaluation free energy using only the activation distribution of the unpruned network.This eliminates repeated forward passes,dramatically reducing computational overhead and achieving speedups of up to 550×for MLPs.Extensive experiments across diverse vision architectures(MLP,CNN,ResNet,MobileNet,Vision Transformer)and text models(LSTM,BERT,ELECTRA,T5,GPT-2)on multiple datasets validate the generality,robustness,and computational efficiency of our approach.Overall,this work establishes a theoretically grounded and practically effective framework for activation pruning,bridging the gap between analytical understanding and efficient deployment of sparse neural networks.
