Advancing the integration of artificial intelligence and polymer science requires high-quality,open-source,and large-scale datasets.However,existing polymer databases often suffer from data sparsity,lack of polymer-pr...Advancing the integration of artificial intelligence and polymer science requires high-quality,open-source,and large-scale datasets.However,existing polymer databases often suffer from data sparsity,lack of polymer-property labels,and limited accessibility,hindering system-atic modeling across property prediction tasks.Here,we present OpenPoly,a curated experimental polymer database derived from extensive lit-erature mining and manual validation,comprising 3985 unique polymer-property data points spanning 26 key properties.We further develop a multi-task benchmarking framework that evaluates property prediction using four encoding methods and eight representative models.Our re-sults highlight that the optimized degree-of-polymerization encoding coupled with Morgan fingerprints achieves an optimal trade-off between computational cost and accuracy.In data-scarce condition,XGBoost outperforms deep learning models on key properties such as dielectric con-stant,glass transition temperature,melting point,and mechanical strength,achieving R2 scores of 0.65-0.87.To further showcase the practical utility of the database,we propose potential polymers for two energy-relevant applications:high temperature polymer dielectrics and fuel cell membranes.By offering a consistent and accessible benchmark and database,OpenPoly paves the way for more accurate polymer-property modeling and fosters data-driven advances in polymer genome engineering.展开更多
The concept of seismic resilience has received significant attention from academia and industry during the last two decades. Different frameworks have been proposed for seismic resilience assessment of engineering sys...The concept of seismic resilience has received significant attention from academia and industry during the last two decades. Different frameworks have been proposed for seismic resilience assessment of engineering systems at different scales(e.g., buildings, bridges, communities, and cities). Testbeds including Centerville virtual community(CVC), Memphis testbed(MTB), and the virtual city of Turin, Italy(VC-TI) have been developed during the last decade. However, the resilience assessment results of Chinese cities still require calibration based on a unified evaluation model. Therefore, a geographic information system(GIS)-based benchmark model of a medium-sized city located in the southeastern coastal region of China was developed. The benchmark city can be used to compare existing assessment frameworks and calibrate the assessment results. The demographics, site conditions, and potential hazard exposure of the benchmark city, as well as land use and building inventory are described in this paper. Data of lifeline systems are provided, including power, transportation, water, drainage, and natural gas distribution networks, as well as the locations of hospitals, emergency shelters, and schools. Data from past earthquakes and the literature were obtained to develop seismic fragility models, consequence models, and recovery models, which can be used as basic data or calibration data in the resilience assessment process. To demonstrate the completeness of the data included in the benchmark city, a case study on the accessibility of emergency rescue after earthquakes was conducted, and the preliminary results were discussed. The ultimate goal of this benchmark city is to provide a platform for calibrating resilience assessment results and to facilitate the development of resilient cities in China.展开更多
The emergence of Medical Large Language Models has significantly transformed healthcare.Medical Large Language Models(Med-LLMs)serve as transformative tools that enhance clinical practice through applications in decis...The emergence of Medical Large Language Models has significantly transformed healthcare.Medical Large Language Models(Med-LLMs)serve as transformative tools that enhance clinical practice through applications in decision support,documentation,and diagnostics.This evaluation examines the performance of leading Med-LLMs,including GPT-4Med,Med-PaLM,MEDITRON,PubMedGPT,and MedAlpaca,across diverse medical datasets.It provides graphical comparisons of their effectiveness in distinct healthcare domains.The study introduces a domain-specific categorization system that aligns these models with optimal applications in clinical decision-making,documentation,drug discovery,research,patient interaction,and public health.The paper addresses deployment challenges of Medical-LLMs,emphasizing trustworthiness and explainability as essential requirements for healthcare AI.It presents current evaluation techniques that improve model transparency in high-stakes medical contexts and analyzes regulatory frameworks using benchmarking datasets such asMedQA,MedMCQA,PubMedQA,and MIMIC.By identifying ongoing challenges in biasmitigation,reliability,and ethical compliance,thiswork serves as a resource for selecting appropriate Med-LLMs and outlines future directions in the field.This analysis offers a roadmap for developing Med-LLMs that balance technological innovation with the trust and transparency required for clinical integration,a perspective often overlooked in existing literature.展开更多
This work illustrates the application of the “Second Order Comprehensive Adjoint Sensitivity Analysis Methodology” (2<sup>nd</sup>-CASAM) to a mathematical model that can simulate the evolution and/or tr...This work illustrates the application of the “Second Order Comprehensive Adjoint Sensitivity Analysis Methodology” (2<sup>nd</sup>-CASAM) to a mathematical model that can simulate the evolution and/or transmission of particles in a heterogeneous medium. The model response is the value of the model’s state function (particle concentration or particle flux) at a point in phase-space, which would simulate a pointwise measurement of the respective state function. This paradigm model admits exact closed-form expressions for all of the 1<sup>st</sup>- and 2<sup>nd</sup>-order response sensitivities to the model’s uncertain parameters and domain boundaries. These closed-form expressions can be used to verify the numerical results of production and/or commercial software, e.g., particle transport codes. Furthermore, this paradigm model comprises many uncertain parameters which have relative sensitivities of identical magnitudes. Therefore, this paradigm model could serve as a stringent benchmark for inter-comparing the performances of all deterministic and statistical sensitivity analysis methods, including the 2<sup>nd</sup>-CASAM.展开更多
This work continues the illustrative application of the “Second Order Comprehensive Adjoint Sensitivity Analysis Methodology” (2<sup>nd</sup>-CASAM) to a benchmark mathematical model that can simulate th...This work continues the illustrative application of the “Second Order Comprehensive Adjoint Sensitivity Analysis Methodology” (2<sup>nd</sup>-CASAM) to a benchmark mathematical model that can simulate the evolution and/or transmission of particles in a heterogeneous medium. The model response considered in this work is a reaction-rate detector response, which provides the average interactions of particles with the respective detector or, alternatively, the time-average of the concentration of a mixture of substances in a medium. The definition of this model response includes both uncertain boundary points of the benchmark, thereby providing both direct and indirect contributions to the response sensitivities stemming from the boundaries. The exact expressions for the 1<sup>st</sup>- and 2<sup>nd</sup>-order response sensitivities to the boundary and model parameters obtained in this work can serve as stringent benchmarks for inter-comparing the performances of all (deterministic and statistical) sensitivity analysis methods.展开更多
Series compensation has proven to increase stability in transmission of electric power. On the other hand insertion of series capacitor results in severe subsynchronous torques. The subsynchronous torque leads to gene...Series compensation has proven to increase stability in transmission of electric power. On the other hand insertion of series capacitor results in severe subsynchronous torques. The subsynchronous torque leads to generator-turbine shaft damage. Mitigation of subsynchronous transient torques is achieved through resistor bank connected to generator terminals. The insertion of resistor bank is controlled by fuzzy logic controller. The proposed controller has been tested on IEEE First Benchmark Model and it proved to have good damping for the torsional torques.展开更多
Can large language models(LLMs)generate metaphor expressions as humans do?To address this question,we present CMGBench,a Chinese Metaphor Generation Benchmark specifically designed to evaluate the ability of LLMs to g...Can large language models(LLMs)generate metaphor expressions as humans do?To address this question,we present CMGBench,a Chinese Metaphor Generation Benchmark specifically designed to evaluate the ability of LLMs to generate metaphors.CMGBench offers a high-quality dataset comprising 810 examples,3,354 annotations,and two types of metaphor expressions:direct metaphor expressions and implicit metaphor expressions,the latter of which has received limited attention in previous research.To assess the quality of metaphors generated by LLMs,we introduce three evaluation criteria.The first criterion measures the disparity between the vehicles in the LLM-generated metaphors and those used by humans.The second criterion evaluates whether an LLM-generated metaphor contains unconventional semantic collocations.The third criterion calculates the proportion of implicit metaphor expressions within the LLM-generated metaphors.We conducted extensive experiments on both proprietary and open-source LLMs.The results demonstrate that,compared to human-generated metaphors,LLM-generated metaphors display a lack of variety in using the attributes of a vehicle,show limited innovation in semantic collocation,and tend to use direct expressions.Even top-performing LLMs such as GPT-4,when not explicitly prompted to generate implicit metaphors,produced them at a rate of only 23.9%.This highlights a significant gap between human and LLM capabilities in metaphor generation.展开更多
This paper investigates continuous-time asset-liability management under benchmark and mean-variance criteria in a jump diffusion market. Specifically, the authors consider one risk-free asset, one risky asset and one...This paper investigates continuous-time asset-liability management under benchmark and mean-variance criteria in a jump diffusion market. Specifically, the authors consider one risk-free asset, one risky asset and one liability, where the risky asset＇s price is governed by an exponential Levy process, the liability evolves according to a Levy process, and there exists a correlation between the risky asset and the liability. Two models are established. One is the benchmark model and the other is the mean-variance model. The benchmark model is solved by employing the stochastic dynamic programming and its results are extended to the mean-variance model by adopting the duality theory. Closed-form solutions of the two models are derived.展开更多
Full-scale experiments have been carried out to adapt the activated sludge model ASM2d to include the influence of metal dosage （Fe^3＋ and Al^3＋） for phosphorus removal. Phosphorus removal rates, nitrification rat...Full-scale experiments have been carried out to adapt the activated sludge model ASM2d to include the influence of metal dosage （Fe^3＋ and Al^3＋） for phosphorus removal. Phosphorus removal rates, nitrification rates, as well as pH and sludge settling performance, were evaluated as functions of the metal dosages. Furthermore, models relating certain parameters to the dosage of chemicals have been derived. Corresponding parameters in the ASM2d and the secondary settler models, included in the Benchmark Simulation Model No 1 （BSM1）, have been modified to take the metal influence into consideration. Based on the effluent limits and penalty policy of China, an equivalent evaluation method was derived for the total cost assessment. A large number of 300-day steady-state and 14-day open-loop dynamic simulations were performed to demonstrate the difference in behavior between the original and the modified BSM1. The results show that 1） both in low and high mole concentrations, Fe^3＋ addition results in a higher phosphorus removal rate than Al^3＋; 2） the sludge settling velocity will increase due to the metal addition; 3） the respiration rate of the activated sludge is decreased more by the dosage of Al^3＋ than Fe^3＋; 4） the inhibition of Al^3＋ on the nitrification rate is stronger than that of Fe^3＋; 5） the total operating cost will reach the minimum point for smaller dosages of Fe^3＋, but always increase with Al^3＋ addition.展开更多
基金financially supported by the National Natural Science Foundation of China (Nos. 92372126,52373203)the Excellent Young Scientists Fund Program
文摘Advancing the integration of artificial intelligence and polymer science requires high-quality,open-source,and large-scale datasets.However,existing polymer databases often suffer from data sparsity,lack of polymer-property labels,and limited accessibility,hindering system-atic modeling across property prediction tasks.Here,we present OpenPoly,a curated experimental polymer database derived from extensive lit-erature mining and manual validation,comprising 3985 unique polymer-property data points spanning 26 key properties.We further develop a multi-task benchmarking framework that evaluates property prediction using four encoding methods and eight representative models.Our re-sults highlight that the optimized degree-of-polymerization encoding coupled with Morgan fingerprints achieves an optimal trade-off between computational cost and accuracy.In data-scarce condition,XGBoost outperforms deep learning models on key properties such as dielectric con-stant,glass transition temperature,melting point,and mechanical strength,achieving R2 scores of 0.65-0.87.To further showcase the practical utility of the database,we propose potential polymers for two energy-relevant applications:high temperature polymer dielectrics and fuel cell membranes.By offering a consistent and accessible benchmark and database,OpenPoly paves the way for more accurate polymer-property modeling and fosters data-driven advances in polymer genome engineering.
基金Scientific Research Fund of Institute of Engineering Mechanics,China Earthquake Administration under Grant Nos. 2019EEEVL0505,2019B02 and 2019A02Heilongjiang Touyan Innovation Team Program。
文摘The concept of seismic resilience has received significant attention from academia and industry during the last two decades. Different frameworks have been proposed for seismic resilience assessment of engineering systems at different scales(e.g., buildings, bridges, communities, and cities). Testbeds including Centerville virtual community(CVC), Memphis testbed(MTB), and the virtual city of Turin, Italy(VC-TI) have been developed during the last decade. However, the resilience assessment results of Chinese cities still require calibration based on a unified evaluation model. Therefore, a geographic information system(GIS)-based benchmark model of a medium-sized city located in the southeastern coastal region of China was developed. The benchmark city can be used to compare existing assessment frameworks and calibrate the assessment results. The demographics, site conditions, and potential hazard exposure of the benchmark city, as well as land use and building inventory are described in this paper. Data of lifeline systems are provided, including power, transportation, water, drainage, and natural gas distribution networks, as well as the locations of hospitals, emergency shelters, and schools. Data from past earthquakes and the literature were obtained to develop seismic fragility models, consequence models, and recovery models, which can be used as basic data or calibration data in the resilience assessment process. To demonstrate the completeness of the data included in the benchmark city, a case study on the accessibility of emergency rescue after earthquakes was conducted, and the preliminary results were discussed. The ultimate goal of this benchmark city is to provide a platform for calibrating resilience assessment results and to facilitate the development of resilient cities in China.
文摘The emergence of Medical Large Language Models has significantly transformed healthcare.Medical Large Language Models(Med-LLMs)serve as transformative tools that enhance clinical practice through applications in decision support,documentation,and diagnostics.This evaluation examines the performance of leading Med-LLMs,including GPT-4Med,Med-PaLM,MEDITRON,PubMedGPT,and MedAlpaca,across diverse medical datasets.It provides graphical comparisons of their effectiveness in distinct healthcare domains.The study introduces a domain-specific categorization system that aligns these models with optimal applications in clinical decision-making,documentation,drug discovery,research,patient interaction,and public health.The paper addresses deployment challenges of Medical-LLMs,emphasizing trustworthiness and explainability as essential requirements for healthcare AI.It presents current evaluation techniques that improve model transparency in high-stakes medical contexts and analyzes regulatory frameworks using benchmarking datasets such asMedQA,MedMCQA,PubMedQA,and MIMIC.By identifying ongoing challenges in biasmitigation,reliability,and ethical compliance,thiswork serves as a resource for selecting appropriate Med-LLMs and outlines future directions in the field.This analysis offers a roadmap for developing Med-LLMs that balance technological innovation with the trust and transparency required for clinical integration,a perspective often overlooked in existing literature.
文摘This work illustrates the application of the “Second Order Comprehensive Adjoint Sensitivity Analysis Methodology” (2<sup>nd</sup>-CASAM) to a mathematical model that can simulate the evolution and/or transmission of particles in a heterogeneous medium. The model response is the value of the model’s state function (particle concentration or particle flux) at a point in phase-space, which would simulate a pointwise measurement of the respective state function. This paradigm model admits exact closed-form expressions for all of the 1<sup>st</sup>- and 2<sup>nd</sup>-order response sensitivities to the model’s uncertain parameters and domain boundaries. These closed-form expressions can be used to verify the numerical results of production and/or commercial software, e.g., particle transport codes. Furthermore, this paradigm model comprises many uncertain parameters which have relative sensitivities of identical magnitudes. Therefore, this paradigm model could serve as a stringent benchmark for inter-comparing the performances of all deterministic and statistical sensitivity analysis methods, including the 2<sup>nd</sup>-CASAM.
文摘This work continues the illustrative application of the “Second Order Comprehensive Adjoint Sensitivity Analysis Methodology” (2<sup>nd</sup>-CASAM) to a benchmark mathematical model that can simulate the evolution and/or transmission of particles in a heterogeneous medium. The model response considered in this work is a reaction-rate detector response, which provides the average interactions of particles with the respective detector or, alternatively, the time-average of the concentration of a mixture of substances in a medium. The definition of this model response includes both uncertain boundary points of the benchmark, thereby providing both direct and indirect contributions to the response sensitivities stemming from the boundaries. The exact expressions for the 1<sup>st</sup>- and 2<sup>nd</sup>-order response sensitivities to the boundary and model parameters obtained in this work can serve as stringent benchmarks for inter-comparing the performances of all (deterministic and statistical) sensitivity analysis methods.
文摘Series compensation has proven to increase stability in transmission of electric power. On the other hand insertion of series capacitor results in severe subsynchronous torques. The subsynchronous torque leads to generator-turbine shaft damage. Mitigation of subsynchronous transient torques is achieved through resistor bank connected to generator terminals. The insertion of resistor bank is controlled by fuzzy logic controller. The proposed controller has been tested on IEEE First Benchmark Model and it proved to have good damping for the torsional torques.
基金supported by the National Key Research and Development Program of China(Grant No.2024YFE0203000).
文摘Can large language models(LLMs)generate metaphor expressions as humans do?To address this question,we present CMGBench,a Chinese Metaphor Generation Benchmark specifically designed to evaluate the ability of LLMs to generate metaphors.CMGBench offers a high-quality dataset comprising 810 examples,3,354 annotations,and two types of metaphor expressions:direct metaphor expressions and implicit metaphor expressions,the latter of which has received limited attention in previous research.To assess the quality of metaphors generated by LLMs,we introduce three evaluation criteria.The first criterion measures the disparity between the vehicles in the LLM-generated metaphors and those used by humans.The second criterion evaluates whether an LLM-generated metaphor contains unconventional semantic collocations.The third criterion calculates the proportion of implicit metaphor expressions within the LLM-generated metaphors.We conducted extensive experiments on both proprietary and open-source LLMs.The results demonstrate that,compared to human-generated metaphors,LLM-generated metaphors display a lack of variety in using the attributes of a vehicle,show limited innovation in semantic collocation,and tend to use direct expressions.Even top-performing LLMs such as GPT-4,when not explicitly prompted to generate implicit metaphors,produced them at a rate of only 23.9%.This highlights a significant gap between human and LLM capabilities in metaphor generation.
基金This research is supported by the National Science Foundation for Distinguished Young Scholars under Grant No. 70825002, the National Natural Science Foundation of China under Grant No. 70518001, and the National Basic Research Program of China 973 Program under Grant No. 2007CB814902.
文摘This paper investigates continuous-time asset-liability management under benchmark and mean-variance criteria in a jump diffusion market. Specifically, the authors consider one risk-free asset, one risky asset and one liability, where the risky asset＇s price is governed by an exponential Levy process, the liability evolves according to a Levy process, and there exists a correlation between the risky asset and the liability. Two models are established. One is the benchmark model and the other is the mean-variance model. The benchmark model is solved by employing the stochastic dynamic programming and its results are extended to the mean-variance model by adopting the duality theory. Closed-form solutions of the two models are derived.
文摘Full-scale experiments have been carried out to adapt the activated sludge model ASM2d to include the influence of metal dosage （Fe^3＋ and Al^3＋） for phosphorus removal. Phosphorus removal rates, nitrification rates, as well as pH and sludge settling performance, were evaluated as functions of the metal dosages. Furthermore, models relating certain parameters to the dosage of chemicals have been derived. Corresponding parameters in the ASM2d and the secondary settler models, included in the Benchmark Simulation Model No 1 （BSM1）, have been modified to take the metal influence into consideration. Based on the effluent limits and penalty policy of China, an equivalent evaluation method was derived for the total cost assessment. A large number of 300-day steady-state and 14-day open-loop dynamic simulations were performed to demonstrate the difference in behavior between the original and the modified BSM1. The results show that 1） both in low and high mole concentrations, Fe^3＋ addition results in a higher phosphorus removal rate than Al^3＋; 2） the sludge settling velocity will increase due to the metal addition; 3） the respiration rate of the activated sludge is decreased more by the dosage of Al^3＋ than Fe^3＋; 4） the inhibition of Al^3＋ on the nitrification rate is stronger than that of Fe^3＋; 5） the total operating cost will reach the minimum point for smaller dosages of Fe^3＋, but always increase with Al^3＋ addition.
