A stochastic epidemic model with two age groups is established in this study,in which the susceptible(S),the exposed(E),the infected(I),the hospitalized(H)and the recovered(R)are involved within the total population,t...A stochastic epidemic model with two age groups is established in this study,in which the susceptible(S),the exposed(E),the infected(I),the hospitalized(H)and the recovered(R)are involved within the total population,the aging rates between two age groups are set to be constant.The existence-and-uniqueness of global positive solution is firstly showed.Then,by constructing several appropriate Lyapunov functions and using the high-dimensional Itô’s formula,the sufficient conditions for the stochastic extinction and stochastic persistence of the exposed individuals and the infected individuals are obtained.The stochastic extinction indicator and the stochastic persistence indicator are less-valued expressions compared with the basic reproduction number.Meanwhile,the main results of this study are modified into multi-age groups.Furthermore,by using the surveillance data for Fujian Provincial Center for Disease Control and Prevention,Fuzhou COVID-19 epidemic is chosen to carry out the numerical simulations,which show that the age group of the population plays the vital role when studying infectious diseases.展开更多
The high porosity and tunable chemical functionality of metal-organic frameworks(MOFs)make it a promising catalyst design platform.High-throughput screening of catalytic performance is feasible since the large MOF str...The high porosity and tunable chemical functionality of metal-organic frameworks(MOFs)make it a promising catalyst design platform.High-throughput screening of catalytic performance is feasible since the large MOF structure database is available.In this study,we report a machine learning model for high-throughput screening of MOF catalysts for the CO_(2) cycloaddition reaction.The descriptors for model training were judiciously chosen according to the reaction mechanism,which leads to high accuracy up to 97%for the 75%quantile of the training set as the classification criterion.The feature contribution was further evaluated with SHAP and PDP analysis to provide a certain physical understanding.12,415 hypothetical MOF structures and 100 reported MOFs were evaluated under 100℃ and 1 bar within one day using the model,and 239 potentially efficient catalysts were discovered.Among them,MOF-76(Y)achieved the top performance experimentally among reported MOFs,in good agreement with the prediction.展开更多
In this paper,we propose an RLC equivalent circuit model theory which can accurately predict the spectral response and resonance characteristics of metamaterial absorption structures,extend its design,and characterize...In this paper,we propose an RLC equivalent circuit model theory which can accurately predict the spectral response and resonance characteristics of metamaterial absorption structures,extend its design,and characterize the parameters of the model in detail.By employing this model,we conducted computations to characterize the response wavelength and bandwidth of variously sized metamaterial absorbers.A comparative analysis with Finite Difference Time Domain(FDTD)simulations demonstrated a remarkable level of consistency in the results.The designed absorbers were fabricated using micro-nano fabrication processes,and were experimentally tested to demonstrate absorption rates exceeding 90%at a wavelength of 9.28μm.The predicted results are then compared with test results.The comparison reveals good consistency in two aspects of the resonance responses,thereby confirming the rationality and accuracy of this model.展开更多
In this paper,a physical model of RIS of bistatic polarized radar cross section is derived starting from the Stratton-Chu equations under the assumptions of physical optics,PEC,far field and rectangular RIS element.In...In this paper,a physical model of RIS of bistatic polarized radar cross section is derived starting from the Stratton-Chu equations under the assumptions of physical optics,PEC,far field and rectangular RIS element.In the context of important physical characteristics of the backscattering polarization of RIS,the modeling of the RIS wireless channel requires a tradeoff between complexity and accuracy,as well as usability and simplicity.For channel modeling of RIS systems,RIS is modelled as multi-equivalent virtual base stations(BSs)induced by multi polarized electromagnetic waves from different incident directions.The comparison between test and simulation results demonstrates that the proposed algorithm effectively captures the key characteristics of the general RIS element polarization physical model and provides accurate results.展开更多
Using a dynamic laser monitoring technique,the solubility of 3-nitro-1,2,4-triazole-5-one(NTO)was investigated in two different binary systems,namely hydroxylamine nitrate(HAN)-water and boric acid(HB)-water ranging f...Using a dynamic laser monitoring technique,the solubility of 3-nitro-1,2,4-triazole-5-one(NTO)was investigated in two different binary systems,namely hydroxylamine nitrate(HAN)-water and boric acid(HB)-water ranging from 278.15 K to 318.15 K.The solubility in each system was found to be positively correlated with temperature.Furthermore,solubility data were analyzed using four equations:the modified Apelblat equation,Van’t Hoff equation,λh equation and CNIBS/R-K equations,and they provided satisfactory results for both two systems.The average root-mean-square deviation(105RMSD)values for these models were less than 13.93.Calculations utilizing the Van’t Hoff equation and Gibbs equations facilitated the derivation of apparent thermodynamic properties of NTO dissolution in the two systems,including values for Gibbs free energy,enthalpy and entropy.The%ζ_(H)is larger than%ζ_(TS),and all the%ζ_(H)data are≥58.63%,indicating that the enthalpy make a greater contribution than entropy to theΔG_(soln)^(Θ).展开更多
A novel method is introduced to optimize the traditional Skanavi model by decomposing the electric field of molecules into the electric field of ions and quantitatively describing the ionic-scale electric field by the...A novel method is introduced to optimize the traditional Skanavi model by decomposing the electric field of molecules into the electric field of ions and quantitatively describing the ionic-scale electric field by the structural coefficient of the effective electric field.Furthermore,the optimization of the Skanavi model is demonstrated and the ferroelectric phase transition of BaTiO_(3)crystals is revealed by calculating the optical and static permittivities of BaTiO_(3),CaTiO_(3),and SrTiO_(3)crystals and the structure coefficients of the effective electric field of BT crystals after Ti4+displacement.This research compensates for the deficiencies of the traditional Skanavi model and refines the theoretical framework for analyzing dielectric properties in high permittivity materials.展开更多
The integration of artificial intelligence(AI)technology,particularly large language models(LLMs),has become essential across various sectors due to their advanced language comprehension and generation capabilities.De...The integration of artificial intelligence(AI)technology,particularly large language models(LLMs),has become essential across various sectors due to their advanced language comprehension and generation capabilities.Despite their transformative impact in fields such as machine translation and intelligent dialogue systems,LLMs face significant challenges.These challenges include safety,security,and privacy concerns that undermine their trustworthiness and effectiveness,such as hallucinations,backdoor attacks,and privacy leakage.Previous works often conflated safety issues with security concerns.In contrast,our study provides clearer and more reasonable definitions for safety,security,and privacy within the context of LLMs.Building on these definitions,we provide a comprehensive overview of the vulnerabilities and defense mechanisms related to safety,security,and privacy in LLMs.Additionally,we explore the unique research challenges posed by LLMs and suggest potential avenues for future research,aiming to enhance the robustness and reliability of LLMs in the face of emerging threats.展开更多
BACKGROUND:Intracranial hemorrhage (ICH),a severe complication among adults receiving extracorporeal membrane oxygenation (ECMO),is often related to poor outcomes.This study aimed to establish a predictive model for I...BACKGROUND:Intracranial hemorrhage (ICH),a severe complication among adults receiving extracorporeal membrane oxygenation (ECMO),is often related to poor outcomes.This study aimed to establish a predictive model for ICH in adults receiving ECMO treatment.METHODS:Adults who received ECMO between January 2017 and June 2022 were the subjects of a single-center retrospective study.Patients under the age of 18 years old,with acute ICH before ECMO,with less than 24 h of ECMO support,and with incomplete data were excluded.ICH was diagnosed by a head computed tomography scan.The outcomes included the incidence of ICH,in-hosptial mortality and 28-day mortality.Multivariate logistic regression analysis was used to identify relevant risk factors of ICH,and a predictive model of ICH with a nomogram was constructed.RESULTS:Among the 227 patients included,22 developed ICH during ECMO.Patients with ICH had higher in-hospital mortality (90.9%vs.47.8%,P=0.001) and higher 28-day mortality (81.8%vs.47.3%,P=0.001) than patients with non-ICH.ICH was associated with decreased grey-white-matter ratio (GWR)(OR=0.894,95%CI:0.841–0.951,P<0.001),stroke history (OR=4.265,95%CI:1.052–17.291,P=0.042),fresh frozen plasma (FFP) transfusion (OR=1.208,95%CI:1.037–1.408,P=0.015)and minimum platelet (PLT) count during ECMO support (OR=0.977,95%CI:0.958–0.996,P=0.019).The area under the receiver operating characteristic curve of the ICH predictive model was 0.843 (95%CI:0.762–0.924,P<0.001).CONCLUSION:ECMO-treated patients with ICH had a higher risk of death.GWR,stroke history,FFP transfusion,and the minimum PLT count were independently associated with ICH,and the ICH predictive model showed that these parameters performed well as diagnostic tools.展开更多
In order to solve the problems of short network lifetime and high data transmission delay in data gathering for wireless sensor network(WSN)caused by uneven energy consumption among nodes,a hybrid energy efficient clu...In order to solve the problems of short network lifetime and high data transmission delay in data gathering for wireless sensor network(WSN)caused by uneven energy consumption among nodes,a hybrid energy efficient clustering routing base on firefly and pigeon-inspired algorithm(FF-PIA)is proposed to optimise the data transmission path.After having obtained the optimal number of cluster head node(CH),its result might be taken as the basis of producing the initial population of FF-PIA algorithm.The L′evy flight mechanism and adaptive inertia weighting are employed in the algorithm iteration to balance the contradiction between the global search and the local search.Moreover,a Gaussian perturbation strategy is applied to update the optimal solution,ensuring the algorithm can jump out of the local optimal solution.And,in the WSN data gathering,a onedimensional signal reconstruction algorithm model is developed by dilated convolution and residual neural networks(DCRNN).We conducted experiments on the National Oceanic and Atmospheric Administration(NOAA)dataset.It shows that the DCRNN modeldriven data reconstruction algorithm improves the reconstruction accuracy as well as the reconstruction time performance.FF-PIA and DCRNN clustering routing co-simulation reveals that the proposed algorithm can effectively improve the performance in extending the network lifetime and reducing data transmission delay.展开更多
Within the SILVARSTAR project,a user-friendly frequency-based hybrid prediction tool has been developed to assess the environmental impact of railway-induced vibration.This tool is integrated in existing noise mapping...Within the SILVARSTAR project,a user-friendly frequency-based hybrid prediction tool has been developed to assess the environmental impact of railway-induced vibration.This tool is integrated in existing noise mapping software.Following modern vibration standards and guidelines,the vibration velocity level in a building in each frequency band is expressed as the sum of a force density(source term),line source transfer mobility(propagation term)and building correction factor(receiver term).A hybrid approach is used that allows for a combination of experimental data and numerical predictions,providing increased flexibility and applicability.The train and track properties can be selected from a database or entered as numerical values.The user can select soil impedance and transfer functions from a database,pre-computed for a wide range of parameters with state-of-the-art models.An experimental database of force densities,transfer functions,free field vibration and input parameters is also provided.The building response is estimated by means of building correction factors.Assumptions within the modelling approach are made to reduce computation time but these can influence prediction accuracy;this is quantified for the case of a nominal intercity train running at different speeds on a ballasted track supported by homogeneous soil of varying stiffness.The paper focuses on the influence of these parameters on the compliance of the track–soil system and the free field response.We also demonstrate the use and discuss the validation of the vibration prediction tool for the case of a high-speed train running on a ballasted track in Lincent(Belgium).展开更多
Salt cavern energy storage technology contributes to energy reserves and renewable energy scale-up.This study focuses on salt cavern gas storage in Jintan to assess the long-term stability of its surrounding rock unde...Salt cavern energy storage technology contributes to energy reserves and renewable energy scale-up.This study focuses on salt cavern gas storage in Jintan to assess the long-term stability of its surrounding rock under frequent operation.The fatigue test results indicate that stress holding significantly reduces fatigue life,with the magnitude of stress level outweighing the duration of holding time in determining peak strain.Employing a machine learning approach,the impact of various factors on fatigue life and peak strain was quantified,revealing that higher stress limits and stress holding adversely impact the fatigue index,whereas lower stress limits and rate exhibit a positive effect.A novel fatigue-creep composite damage constitutive model is constructed,which is able to consider stress magnitude,rate,and stress holding.The model,validated through multi-path tests,accurately captures the elasto-viscous behavior of salt rock during loading,unloading,and stress holding.Sensitivity analysis further reveals the time-and stress-dependent behavior of model parameters,clarifying that strain changes stem not only from stress variations but are also influenced by alterations in elasto-viscous parameters.This study provides a new method for the mechanical assessment of salt cavern gas storage surrounding rocks.展开更多
With the rapid advancement of machine learning technology and its growing adoption in research and engineering applications,an increasing number of studies have embraced data-driven approaches for modeling wind turbin...With the rapid advancement of machine learning technology and its growing adoption in research and engineering applications,an increasing number of studies have embraced data-driven approaches for modeling wind turbine wakes.These models leverage the ability to capture complex,high-dimensional characteristics of wind turbine wakes while offering significantly greater efficiency in the prediction process than physics-driven models.As a result,data-driven wind turbine wake models are regarded as powerful and effective tools for predicting wake behavior and turbine power output.This paper aims to provide a concise yet comprehensive review of existing studies on wind turbine wake modeling that employ data-driven approaches.It begins by defining and classifying machine learning methods to facilitate a clearer understanding of the reviewed literature.Subsequently,the related studies are categorized into four key areas:wind turbine power prediction,data-driven analytic wake models,wake field reconstruction,and the incorporation of explicit physical constraints.The accuracy of data-driven models is influenced by two primary factors:the quality of the training data and the performance of the model itself.Accordingly,both data accuracy and model structure are discussed in detail within the review.展开更多
Accurate acquisition of the rock stress is crucial for various rock engineering applications.The hollow inclusion (HI) technique is widely used for measuring in-situ rock stress.This technique calculates the stress te...Accurate acquisition of the rock stress is crucial for various rock engineering applications.The hollow inclusion (HI) technique is widely used for measuring in-situ rock stress.This technique calculates the stress tensor by measuring strain using an HI strain cell.However,existing analytical solutions for stress calculation based on an HI strain cell in a double-layer medium are not applicable when an HI strain cell is used in a three-layer medium,leading to erroneous stress calculations.To address this issue,this paper presents a method for calculating stress tensors in a three-layer medium using numerical simulations,specifically by obtaining a constitutive matrix that relates strain measurements to stress tensors in a three-layer medium.Furthermore,using Latin hypercube sampling (LHS) and orthogonal experimental design strategies,764 groups of numerical models encompassing various stress measurement scenarios have been established and calculated using FLAC^(3D)software.Finally,a surrogate model based on artificial neural network (ANN) was developed to predict constitutive matrices,achieving a goodness of fit (R^(2)) of 0.999 and a mean squared error (MSE) of 1.254.A software program has been developed from this surrogate model for ease of use in practical engineering applications.The method’s accuracy was verified through numerical simulations,analytical solution and laboratory experiment,demonstrating its effectiveness in calculating stress in a three-layer medium.The surrogate model was applied to calculate mining-induced stress in the roadway roof rock of a coal mine,a typical case for stress measurement in a three-layer medium.Errors in stress calculations arising from the use of existing analytical solutions were corrected.The study also highlights the significant errors associated with using double-layer analytical solutions in a three-layer medium,which could lead to inappropriate engineering design.展开更多
The generalized rheological tests on sandstone were conducted under both dynamic stress and seepage fields.The results demonstrate that the rheological strain of the specimen under increased stress conditions is great...The generalized rheological tests on sandstone were conducted under both dynamic stress and seepage fields.The results demonstrate that the rheological strain of the specimen under increased stress conditions is greater than that under creep conditions,indicating that the dynamic stress field significantly influences the rheological behaviours of sandstone.Following the rheological tests,the number of small pores in the sandstone decreased,while the number of medium-sized pores increased,forming new seepage channels.The high initial rheological stress accelerated fracture compression and the closure of seepage channels,resulting in reduction in the permeability of sandstone.Based on the principles of generalized rheology and the experimental findings,a novel rock rheological constitutive model incorporating both the dynamic stress field and seepage properties has been developed.Numerical simulations of surrounding rock deformation in geotechnical engineering were carried out using a secondary development version of this model,which confirmed the applicability of the generalized rheological numerical simulation method.These results provide theoretical support for the long-term stability evaluation of engineering rock masses and for predicting the deformation of surrounding rock.展开更多
We derive the transport equations from the Vlasov–Fokker–Planck equation when the velocity space is spherically symmetric.The Shkarofsky's form of Fokker–Planck–Rosenbluth collision operator is employed in the...We derive the transport equations from the Vlasov–Fokker–Planck equation when the velocity space is spherically symmetric.The Shkarofsky's form of Fokker–Planck–Rosenbluth collision operator is employed in the Vlasov–Fokker–Planck equation.A closed-form relaxation model for homogeneous plasmas could be presented in terms of Gauss hypergeometric2F1functions.This has been accomplished based on the Maxwellian mixture model.Furthermore,we demonstrate that classic models such as two-temperature thermal equilibrium model and thermodynamic equilibrium model are special cases of our relaxation model and the zeroth-order Braginskii heat transfer model can also be derived.The present relaxation model is a nonequilibrium model based on the hypothesis that the plasmas system possesses finitely distinguishable independent features,without relying on the conventional near-equilibrium assumption.展开更多
We propose a fractional-order improved Fitz Hugh–Nagumo(FHN)neuron model in terms of a generalized Caputo fractional derivative.Following the existence of a unique solution for the proposed model,we derive the numeri...We propose a fractional-order improved Fitz Hugh–Nagumo(FHN)neuron model in terms of a generalized Caputo fractional derivative.Following the existence of a unique solution for the proposed model,we derive the numerical solution using a recently proposed L1 predictor–corrector method.The given method is based on the L1-type discretization algorithm and the spline interpolation scheme.We perform the error and stability analyses for the given method.We perform graphical simulations demonstrating that the proposed FHN neuron model generates rich electrical activities of periodic spiking patterns,chaotic patterns,and quasi-periodic patterns.The motivation behind proposing a fractional-order improved FHN neuron model is that such a system can provide a more nuanced description of the process with better understanding and simulation of the neuronal responses by incorporating memory effects and non-local dynamics,which are inherent to many biological systems.展开更多
基金Supported by National Natural Science Foundation of China(61911530398,12231012)Consultancy Project by the Chinese Academy of Engineering(2022-JB-06,2023-JB-12)+3 种基金the Natural Science Foundation of Fujian Province of China(2021J01621)Special Projects of the Central Government Guiding Local Science and Technology Development(2021L3018)Royal Society of Edinburgh(RSE1832)Engineering and Physical Sciences Research Council(EP/W522521/1).
文摘A stochastic epidemic model with two age groups is established in this study,in which the susceptible(S),the exposed(E),the infected(I),the hospitalized(H)and the recovered(R)are involved within the total population,the aging rates between two age groups are set to be constant.The existence-and-uniqueness of global positive solution is firstly showed.Then,by constructing several appropriate Lyapunov functions and using the high-dimensional Itô’s formula,the sufficient conditions for the stochastic extinction and stochastic persistence of the exposed individuals and the infected individuals are obtained.The stochastic extinction indicator and the stochastic persistence indicator are less-valued expressions compared with the basic reproduction number.Meanwhile,the main results of this study are modified into multi-age groups.Furthermore,by using the surveillance data for Fujian Provincial Center for Disease Control and Prevention,Fuzhou COVID-19 epidemic is chosen to carry out the numerical simulations,which show that the age group of the population plays the vital role when studying infectious diseases.
基金financial support from the National Key Research and Development Program of China(2021YFB 3501501)the National Natural Science Foundation of China(No.22225803,22038001,22108007 and 22278011)+1 种基金Beijing Natural Science Foundation(No.Z230023)Beijing Science and Technology Commission(No.Z211100004321001).
文摘The high porosity and tunable chemical functionality of metal-organic frameworks(MOFs)make it a promising catalyst design platform.High-throughput screening of catalytic performance is feasible since the large MOF structure database is available.In this study,we report a machine learning model for high-throughput screening of MOF catalysts for the CO_(2) cycloaddition reaction.The descriptors for model training were judiciously chosen according to the reaction mechanism,which leads to high accuracy up to 97%for the 75%quantile of the training set as the classification criterion.The feature contribution was further evaluated with SHAP and PDP analysis to provide a certain physical understanding.12,415 hypothetical MOF structures and 100 reported MOFs were evaluated under 100℃ and 1 bar within one day using the model,and 239 potentially efficient catalysts were discovered.Among them,MOF-76(Y)achieved the top performance experimentally among reported MOFs,in good agreement with the prediction.
基金Supported by the National Natural Science Foundation of China(62174092)the Open Fund of State Key Laboratory of Infrared Physics(SITP-NLIST-ZD-2023-04)the Strategic Priority Research Program of the Chinese Academy of Sciences(XDB0580000)。
文摘In this paper,we propose an RLC equivalent circuit model theory which can accurately predict the spectral response and resonance characteristics of metamaterial absorption structures,extend its design,and characterize the parameters of the model in detail.By employing this model,we conducted computations to characterize the response wavelength and bandwidth of variously sized metamaterial absorbers.A comparative analysis with Finite Difference Time Domain(FDTD)simulations demonstrated a remarkable level of consistency in the results.The designed absorbers were fabricated using micro-nano fabrication processes,and were experimentally tested to demonstrate absorption rates exceeding 90%at a wavelength of 9.28μm.The predicted results are then compared with test results.The comparison reveals good consistency in two aspects of the resonance responses,thereby confirming the rationality and accuracy of this model.
基金supported by Ministry of Science and Technology of the People’s Republic of China(2020YFB1808101)the Project“5G evolution wireless air interface intelligent R&D and verification public platform project”supported by Ministry of Industry and Information Technology of the People’s Republic of China(TC220A04M).
文摘In this paper,a physical model of RIS of bistatic polarized radar cross section is derived starting from the Stratton-Chu equations under the assumptions of physical optics,PEC,far field and rectangular RIS element.In the context of important physical characteristics of the backscattering polarization of RIS,the modeling of the RIS wireless channel requires a tradeoff between complexity and accuracy,as well as usability and simplicity.For channel modeling of RIS systems,RIS is modelled as multi-equivalent virtual base stations(BSs)induced by multi polarized electromagnetic waves from different incident directions.The comparison between test and simulation results demonstrates that the proposed algorithm effectively captures the key characteristics of the general RIS element polarization physical model and provides accurate results.
文摘Using a dynamic laser monitoring technique,the solubility of 3-nitro-1,2,4-triazole-5-one(NTO)was investigated in two different binary systems,namely hydroxylamine nitrate(HAN)-water and boric acid(HB)-water ranging from 278.15 K to 318.15 K.The solubility in each system was found to be positively correlated with temperature.Furthermore,solubility data were analyzed using four equations:the modified Apelblat equation,Van’t Hoff equation,λh equation and CNIBS/R-K equations,and they provided satisfactory results for both two systems.The average root-mean-square deviation(105RMSD)values for these models were less than 13.93.Calculations utilizing the Van’t Hoff equation and Gibbs equations facilitated the derivation of apparent thermodynamic properties of NTO dissolution in the two systems,including values for Gibbs free energy,enthalpy and entropy.The%ζ_(H)is larger than%ζ_(TS),and all the%ζ_(H)data are≥58.63%,indicating that the enthalpy make a greater contribution than entropy to theΔG_(soln)^(Θ).
基金Project supported by the National Natural Science Foundation of China(Grant No.51277138)the Natural Science Basic Research Program of Shaanxi Province of China(Grant No.2021JM-442)the Fund from the Shaanxi Provincial Science and Technology Department for Qin Chuangyuan Scientist+Engineer Team(Grant No.2024QCY-KXJ-194)。
文摘A novel method is introduced to optimize the traditional Skanavi model by decomposing the electric field of molecules into the electric field of ions and quantitatively describing the ionic-scale electric field by the structural coefficient of the effective electric field.Furthermore,the optimization of the Skanavi model is demonstrated and the ferroelectric phase transition of BaTiO_(3)crystals is revealed by calculating the optical and static permittivities of BaTiO_(3),CaTiO_(3),and SrTiO_(3)crystals and the structure coefficients of the effective electric field of BT crystals after Ti4+displacement.This research compensates for the deficiencies of the traditional Skanavi model and refines the theoretical framework for analyzing dielectric properties in high permittivity materials.
基金supported by the National Key R&D Program of China under Grant No.2022YFB3103500the National Natural Science Foundation of China under Grants No.62402087 and No.62020106013+3 种基金the Sichuan Science and Technology Program under Grant No.2023ZYD0142the Chengdu Science and Technology Program under Grant No.2023-XT00-00002-GXthe Fundamental Research Funds for Chinese Central Universities under Grants No.ZYGX2020ZB027 and No.Y030232063003002the Postdoctoral Innovation Talents Support Program under Grant No.BX20230060.
文摘The integration of artificial intelligence(AI)technology,particularly large language models(LLMs),has become essential across various sectors due to their advanced language comprehension and generation capabilities.Despite their transformative impact in fields such as machine translation and intelligent dialogue systems,LLMs face significant challenges.These challenges include safety,security,and privacy concerns that undermine their trustworthiness and effectiveness,such as hallucinations,backdoor attacks,and privacy leakage.Previous works often conflated safety issues with security concerns.In contrast,our study provides clearer and more reasonable definitions for safety,security,and privacy within the context of LLMs.Building on these definitions,we provide a comprehensive overview of the vulnerabilities and defense mechanisms related to safety,security,and privacy in LLMs.Additionally,we explore the unique research challenges posed by LLMs and suggest potential avenues for future research,aiming to enhance the robustness and reliability of LLMs in the face of emerging threats.
基金supported by the National Natural Science Foundation of China (82072159)。
文摘BACKGROUND:Intracranial hemorrhage (ICH),a severe complication among adults receiving extracorporeal membrane oxygenation (ECMO),is often related to poor outcomes.This study aimed to establish a predictive model for ICH in adults receiving ECMO treatment.METHODS:Adults who received ECMO between January 2017 and June 2022 were the subjects of a single-center retrospective study.Patients under the age of 18 years old,with acute ICH before ECMO,with less than 24 h of ECMO support,and with incomplete data were excluded.ICH was diagnosed by a head computed tomography scan.The outcomes included the incidence of ICH,in-hosptial mortality and 28-day mortality.Multivariate logistic regression analysis was used to identify relevant risk factors of ICH,and a predictive model of ICH with a nomogram was constructed.RESULTS:Among the 227 patients included,22 developed ICH during ECMO.Patients with ICH had higher in-hospital mortality (90.9%vs.47.8%,P=0.001) and higher 28-day mortality (81.8%vs.47.3%,P=0.001) than patients with non-ICH.ICH was associated with decreased grey-white-matter ratio (GWR)(OR=0.894,95%CI:0.841–0.951,P<0.001),stroke history (OR=4.265,95%CI:1.052–17.291,P=0.042),fresh frozen plasma (FFP) transfusion (OR=1.208,95%CI:1.037–1.408,P=0.015)and minimum platelet (PLT) count during ECMO support (OR=0.977,95%CI:0.958–0.996,P=0.019).The area under the receiver operating characteristic curve of the ICH predictive model was 0.843 (95%CI:0.762–0.924,P<0.001).CONCLUSION:ECMO-treated patients with ICH had a higher risk of death.GWR,stroke history,FFP transfusion,and the minimum PLT count were independently associated with ICH,and the ICH predictive model showed that these parameters performed well as diagnostic tools.
基金partially supported by the National Natural Science Foundation of China(62161016)the Key Research and Development Project of Lanzhou Jiaotong University(ZDYF2304)+1 种基金the Beijing Engineering Research Center of Highvelocity Railway Broadband Mobile Communications(BHRC-2022-1)Beijing Jiaotong University。
文摘In order to solve the problems of short network lifetime and high data transmission delay in data gathering for wireless sensor network(WSN)caused by uneven energy consumption among nodes,a hybrid energy efficient clustering routing base on firefly and pigeon-inspired algorithm(FF-PIA)is proposed to optimise the data transmission path.After having obtained the optimal number of cluster head node(CH),its result might be taken as the basis of producing the initial population of FF-PIA algorithm.The L′evy flight mechanism and adaptive inertia weighting are employed in the algorithm iteration to balance the contradiction between the global search and the local search.Moreover,a Gaussian perturbation strategy is applied to update the optimal solution,ensuring the algorithm can jump out of the local optimal solution.And,in the WSN data gathering,a onedimensional signal reconstruction algorithm model is developed by dilated convolution and residual neural networks(DCRNN).We conducted experiments on the National Oceanic and Atmospheric Administration(NOAA)dataset.It shows that the DCRNN modeldriven data reconstruction algorithm improves the reconstruction accuracy as well as the reconstruction time performance.FF-PIA and DCRNN clustering routing co-simulation reveals that the proposed algorithm can effectively improve the performance in extending the network lifetime and reducing data transmission delay.
基金the project SILVARSTAR funded from the Shift2Rail Joint Undertaking under the European Union’s Horizon 2020 Research and Innovation Programme under Grant Agreement 101015442。
文摘Within the SILVARSTAR project,a user-friendly frequency-based hybrid prediction tool has been developed to assess the environmental impact of railway-induced vibration.This tool is integrated in existing noise mapping software.Following modern vibration standards and guidelines,the vibration velocity level in a building in each frequency band is expressed as the sum of a force density(source term),line source transfer mobility(propagation term)and building correction factor(receiver term).A hybrid approach is used that allows for a combination of experimental data and numerical predictions,providing increased flexibility and applicability.The train and track properties can be selected from a database or entered as numerical values.The user can select soil impedance and transfer functions from a database,pre-computed for a wide range of parameters with state-of-the-art models.An experimental database of force densities,transfer functions,free field vibration and input parameters is also provided.The building response is estimated by means of building correction factors.Assumptions within the modelling approach are made to reduce computation time but these can influence prediction accuracy;this is quantified for the case of a nominal intercity train running at different speeds on a ballasted track supported by homogeneous soil of varying stiffness.The paper focuses on the influence of these parameters on the compliance of the track–soil system and the free field response.We also demonstrate the use and discuss the validation of the vibration prediction tool for the case of a high-speed train running on a ballasted track in Lincent(Belgium).
基金supported by the National Natural Science Foundation of China(Nos.52374078,U24A20616 and 52074043)the Sichuan-Chongqing Science and Technology Innovation Cooperation Program Project(No.2024TIAD-CYKJCXX0011)the Fundamental Research Funds for the Central Universities(No.2023CDJKYJH021)。
文摘Salt cavern energy storage technology contributes to energy reserves and renewable energy scale-up.This study focuses on salt cavern gas storage in Jintan to assess the long-term stability of its surrounding rock under frequent operation.The fatigue test results indicate that stress holding significantly reduces fatigue life,with the magnitude of stress level outweighing the duration of holding time in determining peak strain.Employing a machine learning approach,the impact of various factors on fatigue life and peak strain was quantified,revealing that higher stress limits and stress holding adversely impact the fatigue index,whereas lower stress limits and rate exhibit a positive effect.A novel fatigue-creep composite damage constitutive model is constructed,which is able to consider stress magnitude,rate,and stress holding.The model,validated through multi-path tests,accurately captures the elasto-viscous behavior of salt rock during loading,unloading,and stress holding.Sensitivity analysis further reveals the time-and stress-dependent behavior of model parameters,clarifying that strain changes stem not only from stress variations but are also influenced by alterations in elasto-viscous parameters.This study provides a new method for the mechanical assessment of salt cavern gas storage surrounding rocks.
基金Supported by the National Natural Science Foundation of China under Grant No.52131102.
文摘With the rapid advancement of machine learning technology and its growing adoption in research and engineering applications,an increasing number of studies have embraced data-driven approaches for modeling wind turbine wakes.These models leverage the ability to capture complex,high-dimensional characteristics of wind turbine wakes while offering significantly greater efficiency in the prediction process than physics-driven models.As a result,data-driven wind turbine wake models are regarded as powerful and effective tools for predicting wake behavior and turbine power output.This paper aims to provide a concise yet comprehensive review of existing studies on wind turbine wake modeling that employ data-driven approaches.It begins by defining and classifying machine learning methods to facilitate a clearer understanding of the reviewed literature.Subsequently,the related studies are categorized into four key areas:wind turbine power prediction,data-driven analytic wake models,wake field reconstruction,and the incorporation of explicit physical constraints.The accuracy of data-driven models is influenced by two primary factors:the quality of the training data and the performance of the model itself.Accordingly,both data accuracy and model structure are discussed in detail within the review.
基金funding support from the National Natural Science Foundation of China (Nos. 42477208 and 52079134)the Natural Science Foundation of Hubei Province, China (No. 2024AFA072)+2 种基金the Youth Innovation Promotion Association CAS (No. 2022332)the National Key R&D Program of China (No. 2024YFF0508203)the Open Research Fund of State Key Laboratory of Geomechanics and Geotechnical Engineering Safety (Nos. SKLGME-JBGS2402 and SKLGME022022)。
文摘Accurate acquisition of the rock stress is crucial for various rock engineering applications.The hollow inclusion (HI) technique is widely used for measuring in-situ rock stress.This technique calculates the stress tensor by measuring strain using an HI strain cell.However,existing analytical solutions for stress calculation based on an HI strain cell in a double-layer medium are not applicable when an HI strain cell is used in a three-layer medium,leading to erroneous stress calculations.To address this issue,this paper presents a method for calculating stress tensors in a three-layer medium using numerical simulations,specifically by obtaining a constitutive matrix that relates strain measurements to stress tensors in a three-layer medium.Furthermore,using Latin hypercube sampling (LHS) and orthogonal experimental design strategies,764 groups of numerical models encompassing various stress measurement scenarios have been established and calculated using FLAC^(3D)software.Finally,a surrogate model based on artificial neural network (ANN) was developed to predict constitutive matrices,achieving a goodness of fit (R^(2)) of 0.999 and a mean squared error (MSE) of 1.254.A software program has been developed from this surrogate model for ease of use in practical engineering applications.The method’s accuracy was verified through numerical simulations,analytical solution and laboratory experiment,demonstrating its effectiveness in calculating stress in a three-layer medium.The surrogate model was applied to calculate mining-induced stress in the roadway roof rock of a coal mine,a typical case for stress measurement in a three-layer medium.Errors in stress calculations arising from the use of existing analytical solutions were corrected.The study also highlights the significant errors associated with using double-layer analytical solutions in a three-layer medium,which could lead to inappropriate engineering design.
基金supported and financed by Scientific Research Foundation for High-level Talents of Anhui University of Science and Technology (No.2024yjrc96)Anhui Provincial University Excellent Research and Innovation Team Support Project (No.2022AH010053)+2 种基金National Key Research and Development Program of China (Nos.2023YFC2907602 and 2022YFF1303302)Anhui Provincial Major Science and Technology Project (No.202203a07020011)Open Foundation of Joint National-Local Engineering Research Centre for Safe and Precise Coal Mining (No.EC2023020)。
文摘The generalized rheological tests on sandstone were conducted under both dynamic stress and seepage fields.The results demonstrate that the rheological strain of the specimen under increased stress conditions is greater than that under creep conditions,indicating that the dynamic stress field significantly influences the rheological behaviours of sandstone.Following the rheological tests,the number of small pores in the sandstone decreased,while the number of medium-sized pores increased,forming new seepage channels.The high initial rheological stress accelerated fracture compression and the closure of seepage channels,resulting in reduction in the permeability of sandstone.Based on the principles of generalized rheology and the experimental findings,a novel rock rheological constitutive model incorporating both the dynamic stress field and seepage properties has been developed.Numerical simulations of surrounding rock deformation in geotechnical engineering were carried out using a secondary development version of this model,which confirmed the applicability of the generalized rheological numerical simulation method.These results provide theoretical support for the long-term stability evaluation of engineering rock masses and for predicting the deformation of surrounding rock.
基金Project supported by the Strategic Priority Research Program of the Chinese Academy of Sciences(Grant Nos.XDB0500302 and LSKJ202300305)。
文摘We derive the transport equations from the Vlasov–Fokker–Planck equation when the velocity space is spherically symmetric.The Shkarofsky's form of Fokker–Planck–Rosenbluth collision operator is employed in the Vlasov–Fokker–Planck equation.A closed-form relaxation model for homogeneous plasmas could be presented in terms of Gauss hypergeometric2F1functions.This has been accomplished based on the Maxwellian mixture model.Furthermore,we demonstrate that classic models such as two-temperature thermal equilibrium model and thermodynamic equilibrium model are special cases of our relaxation model and the zeroth-order Braginskii heat transfer model can also be derived.The present relaxation model is a nonequilibrium model based on the hypothesis that the plasmas system possesses finitely distinguishable independent features,without relying on the conventional near-equilibrium assumption.
文摘We propose a fractional-order improved Fitz Hugh–Nagumo(FHN)neuron model in terms of a generalized Caputo fractional derivative.Following the existence of a unique solution for the proposed model,we derive the numerical solution using a recently proposed L1 predictor–corrector method.The given method is based on the L1-type discretization algorithm and the spline interpolation scheme.We perform the error and stability analyses for the given method.We perform graphical simulations demonstrating that the proposed FHN neuron model generates rich electrical activities of periodic spiking patterns,chaotic patterns,and quasi-periodic patterns.The motivation behind proposing a fractional-order improved FHN neuron model is that such a system can provide a more nuanced description of the process with better understanding and simulation of the neuronal responses by incorporating memory effects and non-local dynamics,which are inherent to many biological systems.
