Cancer pain is one of the most prevalent and debilitating symptoms in patients with advanced malignancies,arising from multifactorial mechanisms involving peripheral,central,and systemic pathways.Conventional analgesi...Cancer pain is one of the most prevalent and debilitating symptoms in patients with advanced malignancies,arising from multifactorial mechanisms involving peripheral,central,and systemic pathways.Conventional analgesics,including opioids and nonsteroidal anti-inflammatory drugs,are often limited by their insufficient efficacy,tolerance,and risk of dependence.Traditional Chinese Medicine(TCM),characterized by its multi-component,multi-target,and systemic regulatory properties,has shown promising potential in cancer pain management.This review provides a comprehensive overview of the clinical classification and underlying mechanisms of cancer pain(including nerve infiltration,dysregulation of inflammatory mediators and ion channels,central sensitization,neuro-immune crosstalk,metabolic reprogramming,and gut-brain axis impairment),as well as the analgesic effects of representative TCM agents in cancer pain management.For example,bioactive components such as tetrahydroberberine,levo-tetrahydropalmatine,and piperine exert analgesic effects,thereby improving the quality of life of patients by inhibiting inflammatory cascades,regulating neurotransmitter systems,and preserving neural integrity.Commonly used preclinical models,including bone cancer pain,pancreatic cancer pain,and chemotherapy-induced peripheral neuropathy models,are summarized for their utility in mechanistic studies and efficacy evaluations.This review also discusses the current limitations of clinical evidence,such as small sample sizes,short follow-up periods,and limited translation from animal models,alongside major challenges in standardization,mechanistic elucidation,and clinical trial design.Future directions should focus on precise pain phenotyping,integrated multi-target interventions,rigorous efficacy safety validation,and innovations in drug delivery to facilitate the standardization and global adoption of TCM in cancer pain management.展开更多
Traumatic brain injury can be categorized into primary and secondary injuries.Secondary injuries are the main cause of disability following traumatic brain injury,which involves a complex multicellular cascade.Microgl...Traumatic brain injury can be categorized into primary and secondary injuries.Secondary injuries are the main cause of disability following traumatic brain injury,which involves a complex multicellular cascade.Microglia play an important role in secondary injury and can be activated in response to traumatic brain injury.In this article,we review the origin and classification of microglia as well as the dynamic changes of microglia in traumatic brain injury.We also clarify the microglial polarization pathways and the therapeutic drugs targeting activated microglia.We found that regulating the signaling pathways involved in pro-inflammatory and anti-inflammatory microglia,such as the Toll-like receptor 4/nuclear factor-kappa B,mitogen-activated protein kinase,Janus kinase/signal transducer and activator of transcription,phosphoinositide 3-kinase/protein kinase B,Notch,and high mobility group box 1 pathways,can alleviate the inflammatory response triggered by microglia in traumatic brain injury,thereby exerting neuroprotective effects.We also reviewed the strategies developed on the basis of these pathways,such as drug and cell replacement therapies.Drugs that modulate inflammatory factors,such as rosuvastatin,have been shown to promote the polarization of antiinflammatory microglia and reduce the inflammatory response caused by traumatic brain injury.Mesenchymal stem cells possess anti-inflammatory properties,and clinical studies have confirmed their significant efficacy and safety in patients with traumatic brain injury.Additionally,advancements in mesenchymal stem cell-delivery methods—such as combinations of novel biomaterials,genetic engineering,and mesenchymal stem cell exosome therapy—have greatly enhanced the efficiency and therapeutic effects of mesenchymal stem cells in animal models.However,numerous challenges in the application of drug and mesenchymal stem cell treatment strategies remain to be addressed.In the future,new technologies,such as single-cell RNA sequencing and transcriptome analysis,can facilitate further experimental studies.Moreover,research involving non-human primates can help translate these treatment strategies to clinical practice.展开更多
Commercial phosphor-converted white LEDs(pc-WLEDs)face two inherent limitations,namely blue light hazard and low color rendering index,due to the use of blue LEDs as excitation source.To address these challenges,viole...Commercial phosphor-converted white LEDs(pc-WLEDs)face two inherent limitations,namely blue light hazard and low color rendering index,due to the use of blue LEDs as excitation source.To address these challenges,violet LEDs are proposed as an alternative solution.Currently,phosphors that can be efficiently excited by violet light(with wavelengths from 400 to 420 nm)remain under development still.In this study,we utilize large language models to construct a comprehensive database of Eu^(2+)and Ce^(3+)doped phosphors for discovering novel violet-excited phosphors.A total of 822 phosphor data entries,including elemental compositions,crystal structures and excitation/emission wavelengths,have been extracted and validated from 9551 research papers.Compared with Ce^(3+)doped phosphors,the Eu^(2+)are in general more suited for violet-excited phosphors,as well as red-emitting phosphors.In particular,Eu^(2+)doped nitrides and sulfides are worth of exploration for violet-excited phosphors.This database is expected to be useful in the future development of phosphors for pc-WLEDs based on artificial intelligence methods.The datasets in this article are listed in Science Data Bank at http://doi.org/10.57760/sciencedb.34314.展开更多
To investigate the influence of Al-Zn-Mg-Cu alloy with as-homogenized and as-rolled initial microstructures on the tensile flow behavior,isothermal tensile tests were conducted on a GLEEBLE-3500 isothermal simulator a...To investigate the influence of Al-Zn-Mg-Cu alloy with as-homogenized and as-rolled initial microstructures on the tensile flow behavior,isothermal tensile tests were conducted on a GLEEBLE-3500 isothermal simulator at temperatures of 380-440℃and strain rates of 0.05-1 s^(−1).The Johnson-Cook model,Hensel-Spittel model,strain-compensated Arrhenius model,and critical fracture strain model were established.Results show that through the evaluation of the models using the correlation coefficient(R)and the average absolute relative error,the strain-compensated Arrhenius model can represent the flow behavior of the alloy more accurately.Shear bands are more pronounced in the as-homogenized specimens,whereas dynamic recrystallization is predominantly observed in as-rolled specimens.Fracture morphology analysis reveals that a mixed fracture mechanism is prevalent in the as-homogenized specimen,whereas a ductile fracture mechanism is predominant in the as-rolled specimen.The processing maps indicate that the unstable region is reduced in the as-rolled specimens compared with that in the as-homogenized specimens.The optimal hot working windows for the as-homogenized and as-rolled specimens are determined as 410-440℃/0.14-1 s^(−1)and 380-400℃/0.05-0.29 s^(−1),respectively.展开更多
Under the backdrop of“Carbon Peak and Carbon Neutrality”(dual carbon)goal in China,the methane-carbon dioxide reforming reaction has attracted considerable attention due to its environmental benefits of converting t...Under the backdrop of“Carbon Peak and Carbon Neutrality”(dual carbon)goal in China,the methane-carbon dioxide reforming reaction has attracted considerable attention due to its environmental benefits of converting two greenhouse gases(methane and carbon dioxide)into syngas and its promising industrial applications.Nickel(Ni)-based catalysts,with high catalytic activity,low cost,and abundant resources,are considered ideal candidates for industrial applications.In this article,three reaction kinetic models were briefly introduced,namely the Power-Law(PL)model,the Eley-Rideal(ER)model,and the Langmuir-Hinshelwood-Hougen-Watson(LHHW)model.Based on the LHHW model,the reaction kinetics and mechanisms of different catalytic systems were systematically discussed,including the properties of supports,the doping of noble metals and transition metals,the role of promoters,and the influence of the geometric and electronic structures of Ni on the reaction mechanism.Furthermore,the kinetics of carbon deposition and elimination on various catalysts were analyzed.Based on the reaction rate expressions for carbon elimination,the reasons for the high activity of transition metal iron(Fe)-doped catalysts and core-shell structured catalysts in carbon elimination were explained.Based on the detailed collation and comparative analysis of the reaction mechanisms and kinetic characteristics across diverse Ni-based catalytic systems,a theoretical guidance for the designing of high-performance catalysts was provided in this work.展开更多
In this paper,we present a circuit model of single-quantum-well InGaN/GaN light-emitting diodes based on the standard rate equations.Two rate equations describe carrier transport processes occurring in sep-arate confi...In this paper,we present a circuit model of single-quantum-well InGaN/GaN light-emitting diodes based on the standard rate equations.Two rate equations describe carrier transport processes occurring in sep-arate confinement heterostructure and quantum well respectively,and the third equation describes the varied photons in quantum well.By using the presented model,impacts of quantum well thickness on the static and dynamic performances are investigated.Simulated results show that LED with 4 nm well exhibits better lightcurrent(L-I)performance,but LED with 3 nm well presents wider 3 dB modulation bandwidth.It reveals that high carrier density in quantum well is detrimental to the static performance,but beneficial to the dynamic performance.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
This article investigates the robust current tracking control problem of three-phase grid-connected inverters with LCL filter under external disturbance by a dynamic state feedback control method.First,this paper cons...This article investigates the robust current tracking control problem of three-phase grid-connected inverters with LCL filter under external disturbance by a dynamic state feedback control method.First,this paper constructs an internal model to learn the information of the states and input of the grid-connected inverter under steady state.Second,by utilizing the internal model principle,the paper turns the tracking control problem into the robust stabilization control problem based on some appropriate coordinate transformations.Then,The paper designs a dynamics state feedback control law to deal with this robust stabilization problem,and thus the solution of the robust current tracking control problem of three-phase grid-connected inverters can be obtained.This control method can ensure the asymptotic stability of the closedloop system.Finally,the paper illustrates the effectiveness of the proposed control approach through several groups of simulations,and compares it with the feedforward control method to verify the robustness of the proposed control method to uncertain parameters.展开更多
Utilizing finite element analysis,the ballistic protection provided by a combination of perforated D-shaped and base armor plates,collectively referred to as radiator armor,is evaluated.ANSYS Explicit Dynamics is empl...Utilizing finite element analysis,the ballistic protection provided by a combination of perforated D-shaped and base armor plates,collectively referred to as radiator armor,is evaluated.ANSYS Explicit Dynamics is employed to simulate the ballistic impact of 7.62 mm armor-piercing projectiles on Aluminum AA5083-H116 and Steel Secure 500 armors,focusing on the evaluation of material deformation and penetration resistance at varying impact points.While the D-shaped armor plate is penetrated by the armor-piercing projectiles,the combination of the perforated D-shaped and base armor plates successfully halts penetration.A numerical model based on the finite element method is developed using software such as SolidWorks and ANSYS to analyze the interaction between radiator armor and bullet.The perforated design of radiator armor is to maintain airflow for radiator function,with hole sizes smaller than the bullet core diameter to protect radiator assemblies.Predictions are made regarding the brittle fracture resulting from the projectile core′s bending due to asymmetric impact,and the resulting fragments failed to penetrate the perforated base armor plate.Craters are formed on the surface of the perforated D-shaped armor plate due to the impact of projectile fragments.The numerical model accurately predicts hole growth and projectile penetration upon impact with the armor,demonstrating effective protection of the radiator assemblies by the radiator armor.展开更多
Rice is one of the most important staple crops globally.Rice plant diseases can severely reduce crop yields and,in extreme cases,lead to total production loss.Early diagnosis enables timely intervention,mitigates dise...Rice is one of the most important staple crops globally.Rice plant diseases can severely reduce crop yields and,in extreme cases,lead to total production loss.Early diagnosis enables timely intervention,mitigates disease severity,supports effective treatment strategies,and reduces reliance on excessive pesticide use.Traditional machine learning approaches have been applied for automated rice disease diagnosis;however,these methods depend heavily on manual image preprocessing and handcrafted feature extraction,which are labor-intensive and time-consuming and often require domain expertise.Recently,end-to-end deep learning(DL) models have been introduced for this task,but they often lack robustness and generalizability across diverse datasets.To address these limitations,we propose a novel end-toend training framework for convolutional neural network(CNN) and attention-based model ensembles(E2ETCA).This framework integrates features from two state-of-the-art(SOTA) CNN models,Inception V3 and DenseNet-201,and an attention-based vision transformer(ViT) model.The fused features are passed through an additional fully connected layer with softmax activation for final classification.The entire process is trained end-to-end,enhancing its suitability for realworld deployment.Furthermore,we extract and analyze the learned features using a support vector machine(SVM),a traditional machine learning classifier,to provide comparative insights.We evaluate the proposed E2ETCA framework on three publicly available datasets,the Mendeley Rice Leaf Disease Image Samples dataset,the Kaggle Rice Diseases Image dataset,the Bangladesh Rice Research Institute dataset,and a combined version of all three.Using standard evaluation metrics(accuracy,precision,recall,and F1-score),our framework demonstrates superior performance compared to existing SOTA methods in rice disease diagnosis,with potential applicability to other agricultural disease detection tasks.展开更多
In their recent paper Pereira et al.(2025)claim that validation is overlooked in mapping and modelling of ecosystem services(ES).They state that“many studies lack critical evaluation of the results and no validation ...In their recent paper Pereira et al.(2025)claim that validation is overlooked in mapping and modelling of ecosystem services(ES).They state that“many studies lack critical evaluation of the results and no validation is provided”and that“the validation step is largely overlooked”.This assertion may have been true several years ago,for example,when Ochoa and Urbina-Cardona(2017)made a similar observation.However,there has been much work on ES model validation over the last decade.展开更多
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
基金supported by the National Natural Science Foundation of China(No.82360238,82071245)。
文摘Cancer pain is one of the most prevalent and debilitating symptoms in patients with advanced malignancies,arising from multifactorial mechanisms involving peripheral,central,and systemic pathways.Conventional analgesics,including opioids and nonsteroidal anti-inflammatory drugs,are often limited by their insufficient efficacy,tolerance,and risk of dependence.Traditional Chinese Medicine(TCM),characterized by its multi-component,multi-target,and systemic regulatory properties,has shown promising potential in cancer pain management.This review provides a comprehensive overview of the clinical classification and underlying mechanisms of cancer pain(including nerve infiltration,dysregulation of inflammatory mediators and ion channels,central sensitization,neuro-immune crosstalk,metabolic reprogramming,and gut-brain axis impairment),as well as the analgesic effects of representative TCM agents in cancer pain management.For example,bioactive components such as tetrahydroberberine,levo-tetrahydropalmatine,and piperine exert analgesic effects,thereby improving the quality of life of patients by inhibiting inflammatory cascades,regulating neurotransmitter systems,and preserving neural integrity.Commonly used preclinical models,including bone cancer pain,pancreatic cancer pain,and chemotherapy-induced peripheral neuropathy models,are summarized for their utility in mechanistic studies and efficacy evaluations.This review also discusses the current limitations of clinical evidence,such as small sample sizes,short follow-up periods,and limited translation from animal models,alongside major challenges in standardization,mechanistic elucidation,and clinical trial design.Future directions should focus on precise pain phenotyping,integrated multi-target interventions,rigorous efficacy safety validation,and innovations in drug delivery to facilitate the standardization and global adoption of TCM in cancer pain management.
基金supported by the Natural Science Foundation of Yunnan Province,No.202401AS070086(to ZW)the National Key Research and Development Program of China,No.2018YFA0801403(to ZW)+1 种基金Yunnan Science and Technology Talent and Platform Plan,No.202105AC160041(to ZW)the Natural Science Foundation of China,No.31960120(to ZW)。
文摘Traumatic brain injury can be categorized into primary and secondary injuries.Secondary injuries are the main cause of disability following traumatic brain injury,which involves a complex multicellular cascade.Microglia play an important role in secondary injury and can be activated in response to traumatic brain injury.In this article,we review the origin and classification of microglia as well as the dynamic changes of microglia in traumatic brain injury.We also clarify the microglial polarization pathways and the therapeutic drugs targeting activated microglia.We found that regulating the signaling pathways involved in pro-inflammatory and anti-inflammatory microglia,such as the Toll-like receptor 4/nuclear factor-kappa B,mitogen-activated protein kinase,Janus kinase/signal transducer and activator of transcription,phosphoinositide 3-kinase/protein kinase B,Notch,and high mobility group box 1 pathways,can alleviate the inflammatory response triggered by microglia in traumatic brain injury,thereby exerting neuroprotective effects.We also reviewed the strategies developed on the basis of these pathways,such as drug and cell replacement therapies.Drugs that modulate inflammatory factors,such as rosuvastatin,have been shown to promote the polarization of antiinflammatory microglia and reduce the inflammatory response caused by traumatic brain injury.Mesenchymal stem cells possess anti-inflammatory properties,and clinical studies have confirmed their significant efficacy and safety in patients with traumatic brain injury.Additionally,advancements in mesenchymal stem cell-delivery methods—such as combinations of novel biomaterials,genetic engineering,and mesenchymal stem cell exosome therapy—have greatly enhanced the efficiency and therapeutic effects of mesenchymal stem cells in animal models.However,numerous challenges in the application of drug and mesenchymal stem cell treatment strategies remain to be addressed.In the future,new technologies,such as single-cell RNA sequencing and transcriptome analysis,can facilitate further experimental studies.Moreover,research involving non-human primates can help translate these treatment strategies to clinical practice.
基金National Key Research and Development Program of China(2021YFB3500501)。
文摘Commercial phosphor-converted white LEDs(pc-WLEDs)face two inherent limitations,namely blue light hazard and low color rendering index,due to the use of blue LEDs as excitation source.To address these challenges,violet LEDs are proposed as an alternative solution.Currently,phosphors that can be efficiently excited by violet light(with wavelengths from 400 to 420 nm)remain under development still.In this study,we utilize large language models to construct a comprehensive database of Eu^(2+)and Ce^(3+)doped phosphors for discovering novel violet-excited phosphors.A total of 822 phosphor data entries,including elemental compositions,crystal structures and excitation/emission wavelengths,have been extracted and validated from 9551 research papers.Compared with Ce^(3+)doped phosphors,the Eu^(2+)are in general more suited for violet-excited phosphors,as well as red-emitting phosphors.In particular,Eu^(2+)doped nitrides and sulfides are worth of exploration for violet-excited phosphors.This database is expected to be useful in the future development of phosphors for pc-WLEDs based on artificial intelligence methods.The datasets in this article are listed in Science Data Bank at http://doi.org/10.57760/sciencedb.34314.
文摘To investigate the influence of Al-Zn-Mg-Cu alloy with as-homogenized and as-rolled initial microstructures on the tensile flow behavior,isothermal tensile tests were conducted on a GLEEBLE-3500 isothermal simulator at temperatures of 380-440℃and strain rates of 0.05-1 s^(−1).The Johnson-Cook model,Hensel-Spittel model,strain-compensated Arrhenius model,and critical fracture strain model were established.Results show that through the evaluation of the models using the correlation coefficient(R)and the average absolute relative error,the strain-compensated Arrhenius model can represent the flow behavior of the alloy more accurately.Shear bands are more pronounced in the as-homogenized specimens,whereas dynamic recrystallization is predominantly observed in as-rolled specimens.Fracture morphology analysis reveals that a mixed fracture mechanism is prevalent in the as-homogenized specimen,whereas a ductile fracture mechanism is predominant in the as-rolled specimen.The processing maps indicate that the unstable region is reduced in the as-rolled specimens compared with that in the as-homogenized specimens.The optimal hot working windows for the as-homogenized and as-rolled specimens are determined as 410-440℃/0.14-1 s^(−1)and 380-400℃/0.05-0.29 s^(−1),respectively.
基金Supported by Innovation Capability Support Program of Shaanxi(2024RS-CXTD-53,2024ZC-KJXX-096)the Key R&D Program of Shaanxi Province(2022QCY-LL-69)Xi’an Science and Technology Project(24GXFW0089)。
文摘Under the backdrop of“Carbon Peak and Carbon Neutrality”(dual carbon)goal in China,the methane-carbon dioxide reforming reaction has attracted considerable attention due to its environmental benefits of converting two greenhouse gases(methane and carbon dioxide)into syngas and its promising industrial applications.Nickel(Ni)-based catalysts,with high catalytic activity,low cost,and abundant resources,are considered ideal candidates for industrial applications.In this article,three reaction kinetic models were briefly introduced,namely the Power-Law(PL)model,the Eley-Rideal(ER)model,and the Langmuir-Hinshelwood-Hougen-Watson(LHHW)model.Based on the LHHW model,the reaction kinetics and mechanisms of different catalytic systems were systematically discussed,including the properties of supports,the doping of noble metals and transition metals,the role of promoters,and the influence of the geometric and electronic structures of Ni on the reaction mechanism.Furthermore,the kinetics of carbon deposition and elimination on various catalysts were analyzed.Based on the reaction rate expressions for carbon elimination,the reasons for the high activity of transition metal iron(Fe)-doped catalysts and core-shell structured catalysts in carbon elimination were explained.Based on the detailed collation and comparative analysis of the reaction mechanisms and kinetic characteristics across diverse Ni-based catalytic systems,a theoretical guidance for the designing of high-performance catalysts was provided in this work.
文摘In this paper,we present a circuit model of single-quantum-well InGaN/GaN light-emitting diodes based on the standard rate equations.Two rate equations describe carrier transport processes occurring in sep-arate confinement heterostructure and quantum well respectively,and the third equation describes the varied photons in quantum well.By using the presented model,impacts of quantum well thickness on the static and dynamic performances are investigated.Simulated results show that LED with 4 nm well exhibits better lightcurrent(L-I)performance,but LED with 3 nm well presents wider 3 dB modulation bandwidth.It reveals that high carrier density in quantum well is detrimental to the static performance,but beneficial to the dynamic performance.
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Supported by the Fundamental Research Funds for the Central Universities(2024ZYGXZR047)the National Natural Science Foundation of China(62373156)the Guangdong Basic and Applied Basic Research Foundation(2024A1515011736)。
文摘This article investigates the robust current tracking control problem of three-phase grid-connected inverters with LCL filter under external disturbance by a dynamic state feedback control method.First,this paper constructs an internal model to learn the information of the states and input of the grid-connected inverter under steady state.Second,by utilizing the internal model principle,the paper turns the tracking control problem into the robust stabilization control problem based on some appropriate coordinate transformations.Then,The paper designs a dynamics state feedback control law to deal with this robust stabilization problem,and thus the solution of the robust current tracking control problem of three-phase grid-connected inverters can be obtained.This control method can ensure the asymptotic stability of the closedloop system.Finally,the paper illustrates the effectiveness of the proposed control approach through several groups of simulations,and compares it with the feedforward control method to verify the robustness of the proposed control method to uncertain parameters.
文摘Utilizing finite element analysis,the ballistic protection provided by a combination of perforated D-shaped and base armor plates,collectively referred to as radiator armor,is evaluated.ANSYS Explicit Dynamics is employed to simulate the ballistic impact of 7.62 mm armor-piercing projectiles on Aluminum AA5083-H116 and Steel Secure 500 armors,focusing on the evaluation of material deformation and penetration resistance at varying impact points.While the D-shaped armor plate is penetrated by the armor-piercing projectiles,the combination of the perforated D-shaped and base armor plates successfully halts penetration.A numerical model based on the finite element method is developed using software such as SolidWorks and ANSYS to analyze the interaction between radiator armor and bullet.The perforated design of radiator armor is to maintain airflow for radiator function,with hole sizes smaller than the bullet core diameter to protect radiator assemblies.Predictions are made regarding the brittle fracture resulting from the projectile core′s bending due to asymmetric impact,and the resulting fragments failed to penetrate the perforated base armor plate.Craters are formed on the surface of the perforated D-shaped armor plate due to the impact of projectile fragments.The numerical model accurately predicts hole growth and projectile penetration upon impact with the armor,demonstrating effective protection of the radiator assemblies by the radiator armor.
基金the Begum Rokeya University,Rangpur,and the United Arab Emirates University,UAE for partially supporting this work。
文摘Rice is one of the most important staple crops globally.Rice plant diseases can severely reduce crop yields and,in extreme cases,lead to total production loss.Early diagnosis enables timely intervention,mitigates disease severity,supports effective treatment strategies,and reduces reliance on excessive pesticide use.Traditional machine learning approaches have been applied for automated rice disease diagnosis;however,these methods depend heavily on manual image preprocessing and handcrafted feature extraction,which are labor-intensive and time-consuming and often require domain expertise.Recently,end-to-end deep learning(DL) models have been introduced for this task,but they often lack robustness and generalizability across diverse datasets.To address these limitations,we propose a novel end-toend training framework for convolutional neural network(CNN) and attention-based model ensembles(E2ETCA).This framework integrates features from two state-of-the-art(SOTA) CNN models,Inception V3 and DenseNet-201,and an attention-based vision transformer(ViT) model.The fused features are passed through an additional fully connected layer with softmax activation for final classification.The entire process is trained end-to-end,enhancing its suitability for realworld deployment.Furthermore,we extract and analyze the learned features using a support vector machine(SVM),a traditional machine learning classifier,to provide comparative insights.We evaluate the proposed E2ETCA framework on three publicly available datasets,the Mendeley Rice Leaf Disease Image Samples dataset,the Kaggle Rice Diseases Image dataset,the Bangladesh Rice Research Institute dataset,and a combined version of all three.Using standard evaluation metrics(accuracy,precision,recall,and F1-score),our framework demonstrates superior performance compared to existing SOTA methods in rice disease diagnosis,with potential applicability to other agricultural disease detection tasks.
文摘In their recent paper Pereira et al.(2025)claim that validation is overlooked in mapping and modelling of ecosystem services(ES).They state that“many studies lack critical evaluation of the results and no validation is provided”and that“the validation step is largely overlooked”.This assertion may have been true several years ago,for example,when Ochoa and Urbina-Cardona(2017)made a similar observation.However,there has been much work on ES model validation over the last decade.
基金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.
