Various velocity models have been built for Southeast Qinghai-Xizang Plateau with the purpose of revealing the internal dynamics and estimating local seismic hazards.In this study,we use a 3-D full-waveform modeling p...Various velocity models have been built for Southeast Qinghai-Xizang Plateau with the purpose of revealing the internal dynamics and estimating local seismic hazards.In this study,we use a 3-D full-waveform modeling package to systematically validate three published continental-scale velocity models,that is,Shen2016,FWEA18,and USTClitho1.0,leveraging the ample datasets in Southeast Qinghai-Xizang Plateau region.Travel time residuals and waveform similarities are measured between observed empirical Green’s functions and synthetic waveforms.The results show that the Shen2016 model,derived from traditional surface wave tomography,performs best in fitting Rayleigh waves in the Southeast Qinghai-Xizang Plateau,followed by FWEA18,built from full-waveform inversion of long-period body and surface waves.The USTClitho1.0 model,although inverted from body wave datasets,is comparable with FWEA18 in fitting Rayleigh waves.The results also show that all the models are faster than the ground-truth model and show relatively large travel-time residuals and poor waveform similarities at shorter period bands,possibly caused by small-scale structural heterogeneities in the shallower crust.We further invert the time residuals for spatial velocity residuals and reveal that all three models underestimate the amplitudes of high-and low-velocity anomalies.The underestimated amplitude is up to 4%,which is non-negligible considering that the overall amplitude of anomalies is only 5%−10%in the crust.These results suggest that datasets and the inversion method are both essential to building accurate models and further refinements of these models are necessary.展开更多
Given the severe toxicity and widespread presence of cadmium(Cd)in staple foods such as rice,accurate dietary exposure assessments are imperative for public health.In vitro bioavailability is commonly used to adjust d...Given the severe toxicity and widespread presence of cadmium(Cd)in staple foods such as rice,accurate dietary exposure assessments are imperative for public health.In vitro bioavailability is commonly used to adjust dietary exposure levels of risk factors;however,traditional planar Transwell models have limitations,such as cell dedifferentiation and lack of key intestinal components,necessitating a more physiologically relevant in vitro platform.This study introduces an innovative three-dimensional(3D)intestinal organoid model using a microfluidic chip to evaluate Cd bioavailability in food.Caco-2 cells were cultured on the chip to mimic small intestinal villi's 3D structure,mucus production,and absorption functions.The model's physiological relevance was thoroughly characterized,demonstrating the formation of a confluent epithelial monolayer with well-developed tight junctions(ZO-1),high microvilli density(F-actin),and significant mucus secretion(Alcian blue staining),closely resembling the physiological intestinal epithelium.Fluorescent particle tracking confirmed its ability to simulate intestinal transport and diffusion.The Cd bioavailability in rice measured by the 3D intestinal organoid model((9.07±0.21)%)was comparable to the mouse model((12.82±3.42)%)but significantly lower than the Caco-2 monolayer model((26.97±1.11)%).This 3D intestinal organoid model provides a novel and reliable strategy for in vitro assessment of heavy metal bioavailability in food,with important implications for food safety and risk assessment.展开更多
The constitutive model is essential for predicting the deformation and stability of rocksoil mass.The estimation of constitutive model parameters is a necessary and important task for the reliable characterization of ...The constitutive model is essential for predicting the deformation and stability of rocksoil mass.The estimation of constitutive model parameters is a necessary and important task for the reliable characterization of mechanical behaviors.However,constitutive model parameters cannot be evaluated accurately with a limited amount of test data,resulting in uncertainty in the prediction of stress-strain curves.This paper proposes a Bayesian analysis framework to address this issue.It combines the Bayesian updating with the structural reliability and adaptive conditional sampling methods to assess the equation parameter of constitutive models.Based on the triaxial and ring shear tests on shear zone soils from the Huangtupo landslide,a statistical damage constitutive model and a critical state hypoplastic constitutive model were used to demonstrate the effectiveness of the proposed framework.Moreover,the parameter uncertainty effects of the damage constitutive model on landslide stability were investigated.Results show that reasonable assessments of the constitutive model parameter can be well realized.The variability of stress-strain curves is strongly related to the model prediction performance.The estimation uncertainty of constitutive model parameters should not be ignored for the landslide stability calculation.Our study provides a reference for uncertainty analysis and parameter assessment of the constitutive model.展开更多
Characterized by special morphologic,geographic,hydrologic,and societal behaviors,the water resources management of the Mediterranean catchment often shows a higher level of complexity including security issues of wat...Characterized by special morphologic,geographic,hydrologic,and societal behaviors,the water resources management of the Mediterranean catchment often shows a higher level of complexity including security issues of water supply,inundation risks,and environment management under the perspective of climate change.To have a comprehensive understanding of the Mediterranean water-cycle system,a deterministic distributed hydrologic modeling approach has been developed and presented in this study based on an application in the Var catchment(2800 km^(2))located at the French Mediterranean region.A 1D and 2D coupled model of MIKE SHE and MIKE 11 has been set up under a series of hypotheses to represent the whole hydrologic and hydrodynamic processes including rainfall-runoff,snow-melting,channel flow,overland flow,and the water exchange between land surface and unsaturated/saturated zones.The developed model was first calibrated with 4 years daily records from 2008 to 2011,then to be validated and further run within hourly time interval to produce detailed representation of the catchment water-cycle from 2012 to 2014.The deterministic distributed modeling approach presented in this study is able to represent its complicated water-cycle and used for supporting the decision‐making process of the water resources management of the catchment.展开更多
Mangrove ecosystems along Vietnam’s coastline face significant degradation due to human activities,despite their crucial role in coastal protection against natural hazards.This study aims to assess the spatial and te...Mangrove ecosystems along Vietnam’s coastline face significant degradation due to human activities,despite their crucial role in coastal protection against natural hazards.This study aims to assess the spatial and temporal changes in mangrove coverage along Vietnam’s southern coast by integrating remote sensing techniques with hydrodynamic model simulations.The research methodology combines the Collect Earth tool analysis of Spot-4 and Planet satellite imagery(2000–2020)with Mike 21-HD two-dimensional(2D)hydrodynamic modeling to evaluate mangrove coverage changes by simulating shoreline erosion.Results analysis reveals that a significant increase of 109.83 ha in mangrove area within Vinh Chau Town of Soc Trang Province during the period 2010–2020,predominantly in the eastern region.Hydrodynamic simulations demonstrate that the coastal zone is primarily influenced by the interaction of nearshore currents,East Sea tides,and seasonal monsoon wave patterns.The model results effectively capture the complex interactions between these hydrodynamic factors and mangrove distribution.These findings not only validate the effectiveness of combining remote sensing and hydrodynamic modeling for mangrove assessment but also provide crucial insights for sustainable coastal ecosystem management.The study’s integrated approach offers a robust framework for monitoring mangrove dynamics and developing evidence-based conservation strategies,highlighting the importance of maintaining these vital ecosystems for coastal protection.展开更多
Multiorgan-on-a-chip(MOoC)systems are advanced microfluidic devices that integrate multiple organ models into a single modular unit,each composed of cells derived from various tissues or organs.These systems enable in...Multiorgan-on-a-chip(MOoC)systems are advanced microfluidic devices that integrate multiple organ models into a single modular unit,each composed of cells derived from various tissues or organs.These systems enable interorgan communication and accurately replicate physiological conditions,providing a more physiologically relevant modeling framework for constructing disease models and predicting drug efficacy and toxicity.MOoC systems also provide significant advantages in terms of flexibility,cost-effectiveness,and reproducibility,making them valuable tools for drug development and toxicity assessment.In this review,we first provide an overview of the MOoC technology,covering cell sources,stimulations,materials and fabrication techniques,and biosensors.We then examine the application of MOoC systems in disease modeling,focusing on cancer metastasis,metabolic disorders,and cardiovascular disease.We next discuss the use of MOoC systems in drug toxicity evaluation and drug screening,emphasizing their role in providing comprehensive assessments of drug effects.Finally,we address the challenges it faces and the future perspectives of the MOoC technology.展开更多
This article introduces and compares risk assessment models for venous thromboembolism in gynecological patients at home and abroad.The models assessed included the Caprini risk assessment model,the G-Caprini risk ass...This article introduces and compares risk assessment models for venous thromboembolism in gynecological patients at home and abroad.The models assessed included the Caprini risk assessment model,the G-Caprini risk assessment model,the Rogers risk assessment model,the Autar risk assessment model,the gynecological patient surgical venous thrombosis risk assessment scale,the Wells score,the COMPASS-CAT thrombus risk assessment model,the Khorana risk assessment model,the Padua risk assessment model,and the Chaoyang model.The purpose of this study is to provide a foundation for developing a risk assessment tool for gynecological venous thromboembolism tailored to Chinese patients and to assist clinical health care workers in selecting appropriate risk assessment tools and guiding individualized prevention measures.展开更多
In Hyperspectral Imaging(HSI),the detrimental influence of noise and distortions on data quality is profound,which has severely affected the following-on analytics and decisionmaking such as land mapping.This study pr...In Hyperspectral Imaging(HSI),the detrimental influence of noise and distortions on data quality is profound,which has severely affected the following-on analytics and decisionmaking such as land mapping.This study presents an innovative framework for assessing HSI band quality and reconstructing the low-quality bands,based on the Prophet model.By introducing a comprehensive quality metric to start,the authors approach factors in both spatial and spectral characteristics across local and global scales.This metric effectively captures the intricate noise and distortions inherent in the HSI data.Subsequently,the authors employ the Prophet model to forecast information within the low-quality bands,leveraging insights from neighbouring high-quality bands.To validate the effectiveness of the authors’proposed model,extensive experiments on three publicly available uncorrected datasets are conducted.In a head-to-head comparison,the framework against six state-ofthe-art band reconstruction algorithms including three spectral methods,two spatialspectral methods and one deep learning method is benchmarked.The authors’experiments also delve into strategies for band selection based on quality metrics and the quality evaluation of the reconstructed bands.In addition,the authors assess the classification accuracy utilising these reconstructed bands.In various experiments,the results consistently affirm the efficacy of the authors’method in HSI quality assessment and band reconstruction.Notably,the authors’approach obviates the need for manually prefiltering of noisy bands.This comprehensive framework holds promise in addressing HSI data quality concerns whilst enhancing the overall utility of HSI.展开更多
New energy-storage systems play a pivotal role in the development of the new power system for advancing the energy transition in China.In the“14th Five-Year Plan”for the New Energy-Storage Development,it is proposed...New energy-storage systems play a pivotal role in the development of the new power system for advancing the energy transition in China.In the“14th Five-Year Plan”for the New Energy-Storage Development,it is proposed to expand investment and construction models by promoting the deployment of energy-storage facilities through the ways of self-construction,leasing,and purchasing,and to encourage the development of the shared energy-storage.However,the current scarcity in the model of the shared energy-storage invest-ment and construction substantially restricts its development,particularly due to unclear mechanisms for cost and benefit allocation,which also discourages potential investors.To address the issue,this paper proposes investment and construction models for shared energy-storage that aligns with the present stage of energy storage development.In specific,three main models are introduced:(1)Cen-tralized Self-built Shared Energy-Storage model(CSSES),(2)Third-party Investment Shared Energy-Storage model(TISES),and(3)Distributed Self-built Shared Energy Storage(DSSES)model.The cost–benefit analysis is conducted for each model.The results indicate that the CSSES model achieves the highest internal rate of return(11.5%)and the shortest payback period,while the DSSES model per-forms acceptable with an IRR of 9.4%.In contrast,the TISES model shows the lowest IRR(6.7%)and requires higher electricity price for being feasible.Furthermore,the study employs the entropy weight method and the analytic hierarchy process(AHP)for indicator eval-uation,and integrates the technique for order preference by the similarity to an ideal solution(TOPSIS)for scheme optimization.The results show that both the CSSES model and the DSSES model achieve the highest proximity scores.Under environmental regulations,these models demonstrate superior economic benefits by optimizing energy storage utilization,reducing user costs,and enhancing overall profitability.展开更多
Pingquan City,the origin of five rivers,serves as the core water conservation zone for the Beijing-Tianjin-Hebei region and exemplifies the characteristics of small watersheds in hilly areas.In recent years,excessive ...Pingquan City,the origin of five rivers,serves as the core water conservation zone for the Beijing-Tianjin-Hebei region and exemplifies the characteristics of small watersheds in hilly areas.In recent years,excessive mining and intensified human activities have severely disrupted the local ecosystem,creating an urgent need for ecological vulnerability assessment to enhance water conservation functions.This study employed the sensitivity-resilience-pressure model,integrating various data sources,including regional background,hydro-meteorological data,field investigations,remote sensing analysis,and socio-economic data.The weights of the model indices were determined using an entropy weighting model that combines principal component analysis and the analytic hierarchy process.Using the ArcGIS platform,the spatial distribution and driving forces of ecological vulnerability in 2020 were analyzed,providing valuable insights for regional ecological restoration.The results indicated that the overall Ecological Vulnerability Index(EVI)was 0.389,signifying moderate ecological vulnerability,with significant variation between watersheds.The Daling River Basin had a high EVI,with ecological vulnerability primarily in levels IV and V,indicating high ecological pressure,whereas the Laoniu River Basin had a low EVI,reflecting minimal ecological pressure.Soil type was identified as the primary driving factor,followed by elevation,temperature,and soil erosion as secondary factors.It is recommended to focus on key regions and critical factors while conducting comprehensive monitoring and assessment to ensure the long-term success of ecological management efforts.展开更多
Design patterns offer reusable solutions for common software issues,enhancing quality.The advent of generative large language models(LLMs)marks progress in software development,but their efficacy in applying design pa...Design patterns offer reusable solutions for common software issues,enhancing quality.The advent of generative large language models(LLMs)marks progress in software development,but their efficacy in applying design patterns is not fully assessed.The recent introduction of generative large language models(LLMs)like ChatGPT and CoPilot has demonstrated significant promise in software development.They assist with a variety of tasks including code generation,modeling,bug fixing,and testing,leading to enhanced efficiency and productivity.Although initial uses of these LLMs have had a positive effect on software development,their potential influence on the application of design patterns remains unexplored.This study introduces a method to quantify LLMs’ability to implement design patterns,using Role-Based Metamodeling Language(RBML)for a rigorous specification of the pattern’s problem,solution,and transformation rules.The method evaluates the pattern applicability of a software application using the pattern’s problem specification.If deemed applicable,the application is input to the LLM for pattern application.The resulting application is assessed for conformance to the pattern’s solution specification and for completeness against the pattern’s transformation rules.Evaluating the method with ChatGPT 4 across three applications reveals ChatGPT’s high proficiency,achieving averages of 98%in conformance and 87%in completeness,thereby demonstrating the effectiveness of the method.Using RBML,this study confirms that LLMs,specifically ChatGPT 4,have great potential in effective and efficient application of design patterns with high conformance and completeness.This opens avenues for further integrating LLMs into complex software engineering processes.展开更多
With the large-scale promotion of distributed photovoltaics,new challenges have emerged in the photovoltaic consumptionwithin distribution networks.Traditional photovoltaic consumption schemes have primarily focused o...With the large-scale promotion of distributed photovoltaics,new challenges have emerged in the photovoltaic consumptionwithin distribution networks.Traditional photovoltaic consumption schemes have primarily focused on static analysis.However,as the scale of photovoltaic power generation devices grows and the methods of integration diversify,a single consumption scheme is no longer sufficient to meet the actual needs of current distribution networks.Therefore,this paper proposes an optimal evaluation method for photovoltaic consumption schemes based on BASS model predictions of installed capacity,aiming to provide an effective tool for generating and evaluating photovoltaic consumption schemes in distribution networks.First,the BASS diffusion model,combined with existing photovoltaic capacity data and roof area information,is used to predict the trends in photovoltaic installed capacity for each substation area,providing a scientific basis for consumption evaluation.Secondly,an improved random scenario simulation method is proposed for assessing the photovoltaic consumption capacity in distribution networks.This method generates photovoltaic integration schemes based on the diffusion probabilities of different regions and evaluates the consumption capacity of each scheme.Finally,the Technique for Order Preference by Similarity to an Ideal Solution(TOPSIS)is used to comprehensively evaluate the generated schemes,ensuring that the selected scheme not only meets the consumption requirements but also offers high economic benefits and reliability.The effectiveness and feasibility of the proposedmethod are validated through simulations of the IEEE 33-node system,providing strong support for optimizing photovoltaic consumption schemes in distribution networks.展开更多
Transient stability assessment(TSA)based on artificial intelligence typically has two distinct model management approaches:a unified management approach for all faulted lines and a separate management approach for eac...Transient stability assessment(TSA)based on artificial intelligence typically has two distinct model management approaches:a unified management approach for all faulted lines and a separate management approach for each faulted line.To address the shortcomings of the aforementioned approaches,namely accuracy,training time,and model management complexity,a multi-model management approach for power system TSA based on multi-moment feature clustering has been proposed.First,the steady-state and transient features present under fault conditions were obtained through a transient simulation of line faults.The input sample set was then constructed using the aforementioned multi-moment electrical features and the embedded faulty line numbers.Subsequently,K-means clustering was conducted on each line based on the similarity of their electrical features,employing t-SNE dimensionality reduction.The PSO-CNN model was trained separately for each cluster to generate several independent TSA models.Finally,a model effectiveness evaluation system consisting of five metrics was established,and the effect of the sample imbalance ratio on the model effectiveness was investigated.The model effectiveness was evaluated using the IEEE 39-bus system algorithm.The results showed that the multi-model management strategy based on multi-moment feature clustering can effectively combine the two advantages of superior evaluation performance and streamlined model management by fully extracting system features.Moreover,this approach allows for more flexible adjustments to line topology changes.展开更多
Zhou et al’s investigation on the creation of a non-invasive deep learning(DL)method for colorectal tumor immune microenvironment evaluation using preoperative computed tomography(CT)radiomics published in the World ...Zhou et al’s investigation on the creation of a non-invasive deep learning(DL)method for colorectal tumor immune microenvironment evaluation using preoperative computed tomography(CT)radiomics published in the World Journal of Gastrointestinal Oncology is thorough and scientific.The study analyzed preoperative CT images of 315 confirmed colorectal cancer patients,using manual regions of interest to extract DL features.The study developed a DL model using CT images and histopathological images to predict immune-related indicators in colorectal cancer patients.Pathological(tumor-stroma ratio,tumor-infiltrating lymphocytes infiltration,immunohistochemistry,tumor immune microenvir-onment and immune score)parameters and radiomics(CT imaging and model construction)data were combined to generate artificial intelligence-powered models.Clinical benefit and goodness of fit of the models were assessed using receiver operating characteristic,area under curve and decision curve analysis.The developed DL-based radiomics prediction model for non-invasive evaluation of tumor markers demonstrated potential for personalized treatment planning and immunotherapy strategies in colorectal cancer patients.The study,involving a small group from a single medical center,lacks inclusion/exclusion criteria and should include clinicopathological features for valuable therapeutic practice insights in colorectal cancer patients.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
The 5E model includes Engagement,Exploration,Explanation,Elaboration,and Evaluation,with“Evaluation”at the end,conflicting with teaching learning-evaluation consistency.Thus,formative levaluation is integrated into ...The 5E model includes Engagement,Exploration,Explanation,Elaboration,and Evaluation,with“Evaluation”at the end,conflicting with teaching learning-evaluation consistency.Thus,formative levaluation is integrated into the first four stages,and a summative evaluation table is designed for the fifth,enabling students to self-evaluate and reflect.Elementary school English picture book teaching is used as an example to demonstrate the optimized model's application.展开更多
BACKGROUND Liver transplantation aims to increase the survival of patients with end-stage liver diseases and improve their quality of life.The number of organs available for transplantation is lower than the demand.To...BACKGROUND Liver transplantation aims to increase the survival of patients with end-stage liver diseases and improve their quality of life.The number of organs available for transplantation is lower than the demand.To provide fair organ distribution,predictive mortality scores have been developed.AIM To compare the Acute Physiology and Chronic Health Evaluation IV(APACHE IV),balance of risk(BAR),and model for end-stage liver disease(MELD)scores as predictors of mortality.METHODS Retrospective cohort study,which included 283 adult patients in the postoperative period of deceased donor liver transplantation from 2014 to 2018.RESULTS The transplant recipients were mainly male,with a mean age of 58.1 years.Donors were mostly male,with a mean age of 41.6 years.The median cold ischemia time was 3.1 hours,and the median intensive care unit stay was 5 days.For APACHE IV,a mean of 59.6 was found,BAR 10.7,and MELD 24.2.The 28-day mortality rate was 9.5%,and at 90 days,it was 3.5%.The 28-day mortality prediction for APACHE IV was very good[area under the curve(AUC):0.85,P<0.001,95%CI:0.76-0.94],P<0.001,BAR(AUC:0.70,P<0.001,95%CI:0.58–0.81),and MELD(AUC:0.66,P<0.006,95%CI:0.55-0.78),P<0.008.At 90 days,the data for APACHE IV were very good(AUC:0.80,P<0.001,95%CI:0.71–0.90)and moderate for BAR and MELD,respectively,(AUC:0.66,P<0.004,95%CI:0.55–0.77),(AUC:0.62,P<0.026,95%CI:0.51–0.72).All showed good discrimination between deaths and survivors.As for the best value for liver transplantation,it was significant only for APACHE IV(P<0.001).CONCLUSION The APACHE IV assessment score was more accurate than BAR and MELD in predicting mortality in deceased donor liver transplant recipients.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
Vulnerability assessment is a systematic process to identify security gaps in the design and evaluation of physical protection systems.Adversarial path planning is a widely used method for identifying potential vulner...Vulnerability assessment is a systematic process to identify security gaps in the design and evaluation of physical protection systems.Adversarial path planning is a widely used method for identifying potential vulnerabilities and threats to the security and resilience of critical infrastructures.However,achieving efficient path optimization in complex large-scale three-dimensional(3D)scenes remains a significant challenge for vulnerability assessment.This paper introduces a novel A^(*)-algorithmic framework for 3D security modeling and vulnerability assessment.Within this framework,the 3D facility models were first developed in 3ds Max and then incorporated into Unity for A^(*)heuristic pathfinding.The A^(*)-heuristic pathfinding algorithm was implemented with a geometric probability model to refine the detection and distance fields and achieve a rational approximation of the cost to reach the goal.An admissible heuristic is ensured by incorporating the minimum probability of detection(P_(D)^(min))and diagonal distance to estimate the heuristic function.The 3D A^(*)heuristic search was demonstrated using a hypothetical laboratory facility,where a comparison was also carried out between the A^(*)and Dijkstra algorithms for optimal path identification.Comparative results indicate that the proposed A^(*)-heuristic algorithm effectively identifies the most vulnerable adversarial pathfinding with high efficiency.Finally,the paper discusses hidden phenomena and open issues in efficient 3D pathfinding for security applications.展开更多
基金supported by the Special Fund of the Institute of Geophysics,China Earthquake Administration(Nos.DQJB23R28 and DQJB22K40)the National Natural Science Foundation of China(Nos.42304078,U1839210 and 42104043).
文摘Various velocity models have been built for Southeast Qinghai-Xizang Plateau with the purpose of revealing the internal dynamics and estimating local seismic hazards.In this study,we use a 3-D full-waveform modeling package to systematically validate three published continental-scale velocity models,that is,Shen2016,FWEA18,and USTClitho1.0,leveraging the ample datasets in Southeast Qinghai-Xizang Plateau region.Travel time residuals and waveform similarities are measured between observed empirical Green’s functions and synthetic waveforms.The results show that the Shen2016 model,derived from traditional surface wave tomography,performs best in fitting Rayleigh waves in the Southeast Qinghai-Xizang Plateau,followed by FWEA18,built from full-waveform inversion of long-period body and surface waves.The USTClitho1.0 model,although inverted from body wave datasets,is comparable with FWEA18 in fitting Rayleigh waves.The results also show that all the models are faster than the ground-truth model and show relatively large travel-time residuals and poor waveform similarities at shorter period bands,possibly caused by small-scale structural heterogeneities in the shallower crust.We further invert the time residuals for spatial velocity residuals and reveal that all three models underestimate the amplitudes of high-and low-velocity anomalies.The underestimated amplitude is up to 4%,which is non-negligible considering that the overall amplitude of anomalies is only 5%−10%in the crust.These results suggest that datasets and the inversion method are both essential to building accurate models and further refinements of these models are necessary.
基金supported by National key research and development program of China(2022YFF1102500)。
文摘Given the severe toxicity and widespread presence of cadmium(Cd)in staple foods such as rice,accurate dietary exposure assessments are imperative for public health.In vitro bioavailability is commonly used to adjust dietary exposure levels of risk factors;however,traditional planar Transwell models have limitations,such as cell dedifferentiation and lack of key intestinal components,necessitating a more physiologically relevant in vitro platform.This study introduces an innovative three-dimensional(3D)intestinal organoid model using a microfluidic chip to evaluate Cd bioavailability in food.Caco-2 cells were cultured on the chip to mimic small intestinal villi's 3D structure,mucus production,and absorption functions.The model's physiological relevance was thoroughly characterized,demonstrating the formation of a confluent epithelial monolayer with well-developed tight junctions(ZO-1),high microvilli density(F-actin),and significant mucus secretion(Alcian blue staining),closely resembling the physiological intestinal epithelium.Fluorescent particle tracking confirmed its ability to simulate intestinal transport and diffusion.The Cd bioavailability in rice measured by the 3D intestinal organoid model((9.07±0.21)%)was comparable to the mouse model((12.82±3.42)%)but significantly lower than the Caco-2 monolayer model((26.97±1.11)%).This 3D intestinal organoid model provides a novel and reliable strategy for in vitro assessment of heavy metal bioavailability in food,with important implications for food safety and risk assessment.
基金supported by the Opening Fund of Key Laboratory of Geological Survey and Evaluation of Ministry of Education(No.GLAB 2024ZR03)the National Natural Science Foundation of China(No.42407248)+2 种基金the Guizhou Provincial Basic Research Program(Natural Science)(No.QKHJC-[2023]-YB066)the Key Laboratory of Smart Earth(No.KF2023YB04-02)the Fundamental Research Funds for the Central Universities。
文摘The constitutive model is essential for predicting the deformation and stability of rocksoil mass.The estimation of constitutive model parameters is a necessary and important task for the reliable characterization of mechanical behaviors.However,constitutive model parameters cannot be evaluated accurately with a limited amount of test data,resulting in uncertainty in the prediction of stress-strain curves.This paper proposes a Bayesian analysis framework to address this issue.It combines the Bayesian updating with the structural reliability and adaptive conditional sampling methods to assess the equation parameter of constitutive models.Based on the triaxial and ring shear tests on shear zone soils from the Huangtupo landslide,a statistical damage constitutive model and a critical state hypoplastic constitutive model were used to demonstrate the effectiveness of the proposed framework.Moreover,the parameter uncertainty effects of the damage constitutive model on landslide stability were investigated.Results show that reasonable assessments of the constitutive model parameter can be well realized.The variability of stress-strain curves is strongly related to the model prediction performance.The estimation uncertainty of constitutive model parameters should not be ignored for the landslide stability calculation.Our study provides a reference for uncertainty analysis and parameter assessment of the constitutive model.
基金supported by the National Key R&D Program of China(No.2023YFC3006702)the Natural Science Foundation of Beijing Municipality(IS23117).
文摘Characterized by special morphologic,geographic,hydrologic,and societal behaviors,the water resources management of the Mediterranean catchment often shows a higher level of complexity including security issues of water supply,inundation risks,and environment management under the perspective of climate change.To have a comprehensive understanding of the Mediterranean water-cycle system,a deterministic distributed hydrologic modeling approach has been developed and presented in this study based on an application in the Var catchment(2800 km^(2))located at the French Mediterranean region.A 1D and 2D coupled model of MIKE SHE and MIKE 11 has been set up under a series of hypotheses to represent the whole hydrologic and hydrodynamic processes including rainfall-runoff,snow-melting,channel flow,overland flow,and the water exchange between land surface and unsaturated/saturated zones.The developed model was first calibrated with 4 years daily records from 2008 to 2011,then to be validated and further run within hourly time interval to produce detailed representation of the catchment water-cycle from 2012 to 2014.The deterministic distributed modeling approach presented in this study is able to represent its complicated water-cycle and used for supporting the decision‐making process of the water resources management of the catchment.
基金supported by Environmental Protection Project 2023-2024,with the Joint Vietnam-Russia Tropical Science and Technology Research Center(Southern Branch)as the lead Institution.
文摘Mangrove ecosystems along Vietnam’s coastline face significant degradation due to human activities,despite their crucial role in coastal protection against natural hazards.This study aims to assess the spatial and temporal changes in mangrove coverage along Vietnam’s southern coast by integrating remote sensing techniques with hydrodynamic model simulations.The research methodology combines the Collect Earth tool analysis of Spot-4 and Planet satellite imagery(2000–2020)with Mike 21-HD two-dimensional(2D)hydrodynamic modeling to evaluate mangrove coverage changes by simulating shoreline erosion.Results analysis reveals that a significant increase of 109.83 ha in mangrove area within Vinh Chau Town of Soc Trang Province during the period 2010–2020,predominantly in the eastern region.Hydrodynamic simulations demonstrate that the coastal zone is primarily influenced by the interaction of nearshore currents,East Sea tides,and seasonal monsoon wave patterns.The model results effectively capture the complex interactions between these hydrodynamic factors and mangrove distribution.These findings not only validate the effectiveness of combining remote sensing and hydrodynamic modeling for mangrove assessment but also provide crucial insights for sustainable coastal ecosystem management.The study’s integrated approach offers a robust framework for monitoring mangrove dynamics and developing evidence-based conservation strategies,highlighting the importance of maintaining these vital ecosystems for coastal protection.
基金supported by the National Natural Science Foundation of China(No.32371475)the Natural Science Foundation of Jiangsu Province,Major Project(No.BK20222008).
文摘Multiorgan-on-a-chip(MOoC)systems are advanced microfluidic devices that integrate multiple organ models into a single modular unit,each composed of cells derived from various tissues or organs.These systems enable interorgan communication and accurately replicate physiological conditions,providing a more physiologically relevant modeling framework for constructing disease models and predicting drug efficacy and toxicity.MOoC systems also provide significant advantages in terms of flexibility,cost-effectiveness,and reproducibility,making them valuable tools for drug development and toxicity assessment.In this review,we first provide an overview of the MOoC technology,covering cell sources,stimulations,materials and fabrication techniques,and biosensors.We then examine the application of MOoC systems in disease modeling,focusing on cancer metastasis,metabolic disorders,and cardiovascular disease.We next discuss the use of MOoC systems in drug toxicity evaluation and drug screening,emphasizing their role in providing comprehensive assessments of drug effects.Finally,we address the challenges it faces and the future perspectives of the MOoC technology.
基金funded by the National College Students Innovation and Entrepreneurship Training Program(S202310760049).
文摘This article introduces and compares risk assessment models for venous thromboembolism in gynecological patients at home and abroad.The models assessed included the Caprini risk assessment model,the G-Caprini risk assessment model,the Rogers risk assessment model,the Autar risk assessment model,the gynecological patient surgical venous thrombosis risk assessment scale,the Wells score,the COMPASS-CAT thrombus risk assessment model,the Khorana risk assessment model,the Padua risk assessment model,and the Chaoyang model.The purpose of this study is to provide a foundation for developing a risk assessment tool for gynecological venous thromboembolism tailored to Chinese patients and to assist clinical health care workers in selecting appropriate risk assessment tools and guiding individualized prevention measures.
基金National Natural Science Foundation Major Project of China,Grant/Award Number:42192580Guangdong Province Key Construction Discipline Scientific Research Ability Promotion Project,Grant/Award Number:2022ZDJS015。
文摘In Hyperspectral Imaging(HSI),the detrimental influence of noise and distortions on data quality is profound,which has severely affected the following-on analytics and decisionmaking such as land mapping.This study presents an innovative framework for assessing HSI band quality and reconstructing the low-quality bands,based on the Prophet model.By introducing a comprehensive quality metric to start,the authors approach factors in both spatial and spectral characteristics across local and global scales.This metric effectively captures the intricate noise and distortions inherent in the HSI data.Subsequently,the authors employ the Prophet model to forecast information within the low-quality bands,leveraging insights from neighbouring high-quality bands.To validate the effectiveness of the authors’proposed model,extensive experiments on three publicly available uncorrected datasets are conducted.In a head-to-head comparison,the framework against six state-ofthe-art band reconstruction algorithms including three spectral methods,two spatialspectral methods and one deep learning method is benchmarked.The authors’experiments also delve into strategies for band selection based on quality metrics and the quality evaluation of the reconstructed bands.In addition,the authors assess the classification accuracy utilising these reconstructed bands.In various experiments,the results consistently affirm the efficacy of the authors’method in HSI quality assessment and band reconstruction.Notably,the authors’approach obviates the need for manually prefiltering of noisy bands.This comprehensive framework holds promise in addressing HSI data quality concerns whilst enhancing the overall utility of HSI.
基金supported by the Humanities and Social Sciences of Ministry of Education Planning Fund of China(Grant No.21YJA790009)the National Natural Science Foundation of China(Grant No.72140001).
文摘New energy-storage systems play a pivotal role in the development of the new power system for advancing the energy transition in China.In the“14th Five-Year Plan”for the New Energy-Storage Development,it is proposed to expand investment and construction models by promoting the deployment of energy-storage facilities through the ways of self-construction,leasing,and purchasing,and to encourage the development of the shared energy-storage.However,the current scarcity in the model of the shared energy-storage invest-ment and construction substantially restricts its development,particularly due to unclear mechanisms for cost and benefit allocation,which also discourages potential investors.To address the issue,this paper proposes investment and construction models for shared energy-storage that aligns with the present stage of energy storage development.In specific,three main models are introduced:(1)Cen-tralized Self-built Shared Energy-Storage model(CSSES),(2)Third-party Investment Shared Energy-Storage model(TISES),and(3)Distributed Self-built Shared Energy Storage(DSSES)model.The cost–benefit analysis is conducted for each model.The results indicate that the CSSES model achieves the highest internal rate of return(11.5%)and the shortest payback period,while the DSSES model per-forms acceptable with an IRR of 9.4%.In contrast,the TISES model shows the lowest IRR(6.7%)and requires higher electricity price for being feasible.Furthermore,the study employs the entropy weight method and the analytic hierarchy process(AHP)for indicator eval-uation,and integrates the technique for order preference by the similarity to an ideal solution(TOPSIS)for scheme optimization.The results show that both the CSSES model and the DSSES model achieve the highest proximity scores.Under environmental regulations,these models demonstrate superior economic benefits by optimizing energy storage utilization,reducing user costs,and enhancing overall profitability.
基金supported by the project of China Geological Survey(No.DD20220954)Open Funding Project of the Key Laboratory of Groundwater Sciences and Engineering,Ministry of Natural Resources(No.SK202301-4)+1 种基金Open Foundation of the Key Laboratory of Coupling Process and Effect of Natural Resources Elements(No.2022KFKTC009)Yanzhao Shanshui Science and Innovation Fund of Langfang Integrated Natural Resources Survey Center,China Geological Survey(No.YZSSJJ202401-001).
文摘Pingquan City,the origin of five rivers,serves as the core water conservation zone for the Beijing-Tianjin-Hebei region and exemplifies the characteristics of small watersheds in hilly areas.In recent years,excessive mining and intensified human activities have severely disrupted the local ecosystem,creating an urgent need for ecological vulnerability assessment to enhance water conservation functions.This study employed the sensitivity-resilience-pressure model,integrating various data sources,including regional background,hydro-meteorological data,field investigations,remote sensing analysis,and socio-economic data.The weights of the model indices were determined using an entropy weighting model that combines principal component analysis and the analytic hierarchy process.Using the ArcGIS platform,the spatial distribution and driving forces of ecological vulnerability in 2020 were analyzed,providing valuable insights for regional ecological restoration.The results indicated that the overall Ecological Vulnerability Index(EVI)was 0.389,signifying moderate ecological vulnerability,with significant variation between watersheds.The Daling River Basin had a high EVI,with ecological vulnerability primarily in levels IV and V,indicating high ecological pressure,whereas the Laoniu River Basin had a low EVI,reflecting minimal ecological pressure.Soil type was identified as the primary driving factor,followed by elevation,temperature,and soil erosion as secondary factors.It is recommended to focus on key regions and critical factors while conducting comprehensive monitoring and assessment to ensure the long-term success of ecological management efforts.
文摘Design patterns offer reusable solutions for common software issues,enhancing quality.The advent of generative large language models(LLMs)marks progress in software development,but their efficacy in applying design patterns is not fully assessed.The recent introduction of generative large language models(LLMs)like ChatGPT and CoPilot has demonstrated significant promise in software development.They assist with a variety of tasks including code generation,modeling,bug fixing,and testing,leading to enhanced efficiency and productivity.Although initial uses of these LLMs have had a positive effect on software development,their potential influence on the application of design patterns remains unexplored.This study introduces a method to quantify LLMs’ability to implement design patterns,using Role-Based Metamodeling Language(RBML)for a rigorous specification of the pattern’s problem,solution,and transformation rules.The method evaluates the pattern applicability of a software application using the pattern’s problem specification.If deemed applicable,the application is input to the LLM for pattern application.The resulting application is assessed for conformance to the pattern’s solution specification and for completeness against the pattern’s transformation rules.Evaluating the method with ChatGPT 4 across three applications reveals ChatGPT’s high proficiency,achieving averages of 98%in conformance and 87%in completeness,thereby demonstrating the effectiveness of the method.Using RBML,this study confirms that LLMs,specifically ChatGPT 4,have great potential in effective and efficient application of design patterns with high conformance and completeness.This opens avenues for further integrating LLMs into complex software engineering processes.
基金supported in part by theThe Planning Subject Project of Guangdong Power Grid Co.,Ltd.(62273104).
文摘With the large-scale promotion of distributed photovoltaics,new challenges have emerged in the photovoltaic consumptionwithin distribution networks.Traditional photovoltaic consumption schemes have primarily focused on static analysis.However,as the scale of photovoltaic power generation devices grows and the methods of integration diversify,a single consumption scheme is no longer sufficient to meet the actual needs of current distribution networks.Therefore,this paper proposes an optimal evaluation method for photovoltaic consumption schemes based on BASS model predictions of installed capacity,aiming to provide an effective tool for generating and evaluating photovoltaic consumption schemes in distribution networks.First,the BASS diffusion model,combined with existing photovoltaic capacity data and roof area information,is used to predict the trends in photovoltaic installed capacity for each substation area,providing a scientific basis for consumption evaluation.Secondly,an improved random scenario simulation method is proposed for assessing the photovoltaic consumption capacity in distribution networks.This method generates photovoltaic integration schemes based on the diffusion probabilities of different regions and evaluates the consumption capacity of each scheme.Finally,the Technique for Order Preference by Similarity to an Ideal Solution(TOPSIS)is used to comprehensively evaluate the generated schemes,ensuring that the selected scheme not only meets the consumption requirements but also offers high economic benefits and reliability.The effectiveness and feasibility of the proposedmethod are validated through simulations of the IEEE 33-node system,providing strong support for optimizing photovoltaic consumption schemes in distribution networks.
基金supported by the Science and Technology Project of SGCC(5100-202199558A-0-5-ZN).
文摘Transient stability assessment(TSA)based on artificial intelligence typically has two distinct model management approaches:a unified management approach for all faulted lines and a separate management approach for each faulted line.To address the shortcomings of the aforementioned approaches,namely accuracy,training time,and model management complexity,a multi-model management approach for power system TSA based on multi-moment feature clustering has been proposed.First,the steady-state and transient features present under fault conditions were obtained through a transient simulation of line faults.The input sample set was then constructed using the aforementioned multi-moment electrical features and the embedded faulty line numbers.Subsequently,K-means clustering was conducted on each line based on the similarity of their electrical features,employing t-SNE dimensionality reduction.The PSO-CNN model was trained separately for each cluster to generate several independent TSA models.Finally,a model effectiveness evaluation system consisting of five metrics was established,and the effect of the sample imbalance ratio on the model effectiveness was investigated.The model effectiveness was evaluated using the IEEE 39-bus system algorithm.The results showed that the multi-model management strategy based on multi-moment feature clustering can effectively combine the two advantages of superior evaluation performance and streamlined model management by fully extracting system features.Moreover,this approach allows for more flexible adjustments to line topology changes.
文摘Zhou et al’s investigation on the creation of a non-invasive deep learning(DL)method for colorectal tumor immune microenvironment evaluation using preoperative computed tomography(CT)radiomics published in the World Journal of Gastrointestinal Oncology is thorough and scientific.The study analyzed preoperative CT images of 315 confirmed colorectal cancer patients,using manual regions of interest to extract DL features.The study developed a DL model using CT images and histopathological images to predict immune-related indicators in colorectal cancer patients.Pathological(tumor-stroma ratio,tumor-infiltrating lymphocytes infiltration,immunohistochemistry,tumor immune microenvir-onment and immune score)parameters and radiomics(CT imaging and model construction)data were combined to generate artificial intelligence-powered models.Clinical benefit and goodness of fit of the models were assessed using receiver operating characteristic,area under curve and decision curve analysis.The developed DL-based radiomics prediction model for non-invasive evaluation of tumor markers demonstrated potential for personalized treatment planning and immunotherapy strategies in colorectal cancer patients.The study,involving a small group from a single medical center,lacks inclusion/exclusion criteria and should include clinicopathological features for valuable therapeutic practice insights in colorectal cancer patients.
文摘Model evaluation using benchmark datasets is an important method to measure the capability of large language models(LLMs)in specific domains,and it is mainly used to assess the knowledge and reasoning abilities of LLMs.Therefore,in order to better assess the capability of LLMs in the agricultural domain,Agri-Eval was proposed as a benchmark for assessing the knowledge and reasoning ability of LLMs in agriculture.The assessment dataset used in Agri-Eval covered seven major disciplines in the agricultural domain:crop science,horticulture,plant protection,animal husbandry,forest science,aquaculture science,and grass science,and contained a total of 2283 questions.Among domestic general-purpose LLMs,DeepSeek R1 performed best with an accuracy rate of 75.49%.In the realm of international general-purpose LLMs,Gemini 2.0 pro exp 0205 standed out as the top performer,achieving an accuracy rate of 74.28%.As an LLMs in agriculture vertical,Shennong V2.0 outperformed all the LLMs in China,and the answer accuracy rate of agricultural knowledge exceeded that of all the existing general-purpose LLMs.The launch of Agri-Eval helped the LLM developers to comprehensively evaluate the model's capability in the field of agriculture through a variety of tasks and tests to promote the development of the LLMs in the field of agriculture.
基金Supported by the National Natural Science Foundation of China(12261018)Universities Key Laboratory of Mathematical Modeling and Data Mining in Guizhou Province(2023013)。
文摘In this paper,we establish and study a single-species logistic model with impulsive age-selective harvesting.First,we prove the ultimate boundedness of the solutions of the system.Then,we obtain conditions for the asymptotic stability of the trivial solution and the positive periodic solution.Finally,numerical simulations are presented to validate our results.Our results show that age-selective harvesting is more conducive to sustainable population survival than non-age-selective harvesting.
基金This paper is funded by Project Information:2023 Guangdong Undergraduate Colleges and Universities Teaching Quality and Teaching Reform Project Construction Project,Project Name:Action Research on Whole-area Nurturing of English Reading Teaching in Universities,Secondary and Primary Schools under the Perspective of Discipline Nurturing.Project serial number:895.
文摘The 5E model includes Engagement,Exploration,Explanation,Elaboration,and Evaluation,with“Evaluation”at the end,conflicting with teaching learning-evaluation consistency.Thus,formative levaluation is integrated into the first four stages,and a summative evaluation table is designed for the fifth,enabling students to self-evaluate and reflect.Elementary school English picture book teaching is used as an example to demonstrate the optimized model's application.
文摘BACKGROUND Liver transplantation aims to increase the survival of patients with end-stage liver diseases and improve their quality of life.The number of organs available for transplantation is lower than the demand.To provide fair organ distribution,predictive mortality scores have been developed.AIM To compare the Acute Physiology and Chronic Health Evaluation IV(APACHE IV),balance of risk(BAR),and model for end-stage liver disease(MELD)scores as predictors of mortality.METHODS Retrospective cohort study,which included 283 adult patients in the postoperative period of deceased donor liver transplantation from 2014 to 2018.RESULTS The transplant recipients were mainly male,with a mean age of 58.1 years.Donors were mostly male,with a mean age of 41.6 years.The median cold ischemia time was 3.1 hours,and the median intensive care unit stay was 5 days.For APACHE IV,a mean of 59.6 was found,BAR 10.7,and MELD 24.2.The 28-day mortality rate was 9.5%,and at 90 days,it was 3.5%.The 28-day mortality prediction for APACHE IV was very good[area under the curve(AUC):0.85,P<0.001,95%CI:0.76-0.94],P<0.001,BAR(AUC:0.70,P<0.001,95%CI:0.58–0.81),and MELD(AUC:0.66,P<0.006,95%CI:0.55-0.78),P<0.008.At 90 days,the data for APACHE IV were very good(AUC:0.80,P<0.001,95%CI:0.71–0.90)and moderate for BAR and MELD,respectively,(AUC:0.66,P<0.004,95%CI:0.55–0.77),(AUC:0.62,P<0.026,95%CI:0.51–0.72).All showed good discrimination between deaths and survivors.As for the best value for liver transplantation,it was significant only for APACHE IV(P<0.001).CONCLUSION The APACHE IV assessment score was more accurate than BAR and MELD in predicting mortality in deceased donor liver transplant recipients.
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supported by the fundings from 2024 Young Talents Program for Science and Technology Thinking Tanks(No.XMSB20240711041)2024 Student Research Program on Dynamic Simulation and Force-on-Force Exercise of Nuclear Security in 3D Interactive Environment Using Reinforcement Learning,Natural Science Foundation of Top Talent of SZTU(No.GDRC202407)+2 种基金Shenzhen Science and Technology Program(No.KCXFZ20240903092603005)Shenzhen Science and Technology Program(No.JCYJ20241202124703004)Shenzhen Science and Technology Program(No.KJZD20230923114117032)。
文摘Vulnerability assessment is a systematic process to identify security gaps in the design and evaluation of physical protection systems.Adversarial path planning is a widely used method for identifying potential vulnerabilities and threats to the security and resilience of critical infrastructures.However,achieving efficient path optimization in complex large-scale three-dimensional(3D)scenes remains a significant challenge for vulnerability assessment.This paper introduces a novel A^(*)-algorithmic framework for 3D security modeling and vulnerability assessment.Within this framework,the 3D facility models were first developed in 3ds Max and then incorporated into Unity for A^(*)heuristic pathfinding.The A^(*)-heuristic pathfinding algorithm was implemented with a geometric probability model to refine the detection and distance fields and achieve a rational approximation of the cost to reach the goal.An admissible heuristic is ensured by incorporating the minimum probability of detection(P_(D)^(min))and diagonal distance to estimate the heuristic function.The 3D A^(*)heuristic search was demonstrated using a hypothetical laboratory facility,where a comparison was also carried out between the A^(*)and Dijkstra algorithms for optimal path identification.Comparative results indicate that the proposed A^(*)-heuristic algorithm effectively identifies the most vulnerable adversarial pathfinding with high efficiency.Finally,the paper discusses hidden phenomena and open issues in efficient 3D pathfinding for security applications.
