Re-fracturing horizontal wells is a critical strategy for enhancing recovery from tight oil reservoirs,but its success depends on the evaluation of candidate wells and locations.This process is complicated by producti...Re-fracturing horizontal wells is a critical strategy for enhancing recovery from tight oil reservoirs,but its success depends on the evaluation of candidate wells and locations.This process is complicated by production-induced alterations in reservoir pressure and geomechanical responses.This study introduces a workflow to evaluate re-fracturing potential by integrating coupled fluid flow and geomechanical modeling for the production of initial hydraulic fractures.We developed a numerical model that simulates the poroelastic response of a tight oil reservoir to depletion from an initial set of hydraulic fractures.To quantify the re-fracturing potential along the horizontal wellbore,a novel composite re-fracturing potential index is proposed where fracture shape,stress,and pressure are considered.This index considers four key physical factors:current reservoir pressure,fracture initiation ease,fracture geometry favorability,and fracture propagation efficiency considering tortuosity.Numerical simulations were conducted for scenarios with both uniform and non-uniform initial hydraulic fractures.The results consistently demonstrate that the optimal locations for re-fracturing are the midpoints between existing fractures,where a favorable balance of high reservoir pressure and altered stress conditions exists.The analysis reveals that the overall re-fracturing potential tends to increase with production time,suggesting that a period of depletion can enhance the geomechanical conditions for subsequent stimulation.Furthermore,a sensitivity analysis on the index weighting factors shows that the optimum re-fracturing strategy is highly dependent on the primary field objective,whether it is maximizing resource contact,ensuring geomechanical feasibility,or avoiding operational complexity.The study concludes that heterogeneity in the initial fracture network creates complex and asymmetric potential profiles,which implies the necessity of case-specific and integrated analysis over simplified assumptions.The proposed methodology provides a framework for optimizing re-fracturing designs in tight oil reservoirs.展开更多
With the widespread application of Internet of Things(IoT)technology,the processing of massive realtime streaming data poses significant challenges to the computational and data-processing capabilities of systems.Alth...With the widespread application of Internet of Things(IoT)technology,the processing of massive realtime streaming data poses significant challenges to the computational and data-processing capabilities of systems.Although distributed streaming data processing frameworks such asApache Flink andApache Spark Streaming provide solutions,meeting stringent response time requirements while ensuring high throughput and resource utilization remains an urgent problem.To address this,the study proposes a formal modeling approach based on Performance Evaluation Process Algebra(PEPA),which abstracts the core components and interactions of cloud-based distributed streaming data processing systems.Additionally,a generic service flow generation algorithmis introduced,enabling the automatic extraction of service flows fromthe PEPAmodel and the computation of key performance metrics,including response time,throughput,and resource utilization.The novelty of this work lies in the integration of PEPA-based formal modeling with the service flow generation algorithm,bridging the gap between formal modeling and practical performance evaluation for IoT systems.Simulation experiments demonstrate that optimizing the execution efficiency of components can significantly improve system performance.For instance,increasing the task execution rate from 10 to 100 improves system performance by 9.53%,while further increasing it to 200 results in a 21.58%improvement.However,diminishing returns are observed when the execution rate reaches 500,with only a 0.42%gain.Similarly,increasing the number of TaskManagers from 10 to 20 improves response time by 18.49%,but the improvement slows to 6.06% when increasing from 20 to 50,highlighting the importance of co-optimizing component efficiency and resource management to achieve substantial performance gains.This study provides a systematic framework for analyzing and optimizing the performance of IoT systems for large-scale real-time streaming data processing.The proposed approach not only identifies performance bottlenecks but also offers insights into improving system efficiency under different configurations and workloads.展开更多
The average stiffness performance indices throughout the workspace are commonly used as global stiffness performance indices to evaluate the overall stiffness performance of parallel mechanisms,which involves an analy...The average stiffness performance indices throughout the workspace are commonly used as global stiffness performance indices to evaluate the overall stiffness performance of parallel mechanisms,which involves an analysis of the stiffness performance of numerous discrete points in the workspace.This necessitates time-consuming and inefficient calculation,which is particularly pronounced in the optimization design stage of the mechanism,where the variations in the global stiffness performance indices versus various dimensional and structural parameters need to be analyzed.This paper presents a semi-analytical approach for stiffness modeling of the novel(R(RPS&RP))&2-UPS parallel mechanism(referred to as the Trifree mechanism)and proposes“local”stiffness performance indices as alternatives to global indices.Drawing on the screw theory,the Cartesian stiffness matrix of the Trifree mechanism is formulated explicitly by considering the compliances of all elastic elements and the over-constraint characteristics inherent in the mechanism.Based on the spherical motion pattern of the Trifree mechanism,four special reference configurations are extracted within the workspace.This yields“local”stiffness performance indices capable of accurately evaluating the overall stiffness performance of the mechanism and effectively improving the computational efficiency.The variations in global and“local”stiffness performance indices versus key design parameters are investigated.Furthermore,the proposed indices are applied to the Tricept and Trimule mechanisms.The results demonstrate that the proposed indices exhibit excellent computational accuracy and efficiency in evaluating the overall stiffness performance of these spherical parallel mechanisms.Moreover,the stiffness performance of the novel parallel mechanism investigated in this study closely resembles that of the well-known Tricept and Trimule mechanisms.This research proposes a semi-analytic stiffness model of the Trifree mechanism and“local”stiffness performance indices to evaluate the overall stiffness performance,thereby substantially improving the computational efficiency without sacrificing accuracy.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
The incidence of benign airway stenosis(BAS)is on the rise,and current treatment options are associated with a significant risk of restenosis.Therefore,there is an urgent need to explore new and effective prevention a...The incidence of benign airway stenosis(BAS)is on the rise,and current treatment options are associated with a significant risk of restenosis.Therefore,there is an urgent need to explore new and effective prevention and treatment methods.Animal models serve as essential tools for investigating disease mechanisms and assessing novel therapeutic strategies,and the scientific rigor of their construction and validation significantly impacts the reliability of research findings.This paper systematically reviews the research progress and evaluation systems of BAS animal models over the past decade,aiming to provide a robust foundation for the optimized construction of BAS models,intervention studies,and clinical translation.This effort is intended to facilitate the innovation and advancement in BAS prevention and treatment strategies.展开更多
With the improvement of living standards and the shift in societal consumption attitudes,consumers demand for the quality of aquatic products is increasingly stringent.Freshness and quality have become primary factors...With the improvement of living standards and the shift in societal consumption attitudes,consumers demand for the quality of aquatic products is increasingly stringent.Freshness and quality have become primary factors determining consumers purchasing decisions.However,due to the high moisture content,active endogenous enzymes,and rich nutrients in aquatic products,both fresh and processed products are highly susceptible to quality deterioration during procurement,distribution,and storage,which leads to a significant decline in sensory quality and nutritional value,while also compromising safety.Today,the consumption of high-quality aquatic products has become a prevailing trend.This paper reviewed the methods for freshness evaluation and quality grading of aquatic products in terms of sensory and nutritional aspects,aiming to support the market circulation principle of"higher price for better quality"and"price based on quality",and better meeting consumer demands.Therefore,it is imperative to enhance the analysis and evaluation of aquatic product quality and to continuously refine assessment systems and methods,which is crucial for promoting industry transformation and fostering a healthy market-consumer economic cycle.展开更多
The learning and inferencing capabilities of large language models(LLMs)that underlie generative artificial intelligence(GenAI)can be exploited to optimize cancer treatments and improve patient outcomes.The ability of...The learning and inferencing capabilities of large language models(LLMs)that underlie generative artificial intelligence(GenAI)can be exploited to optimize cancer treatments and improve patient outcomes.The ability of these models to learn from large amounts of clinical,molecular,and radiomic data on cancer patients and their treatments is driving research interest in their application to treatment decision-making.The learning and predictive power of LLMs make them uniquely suitable for supporting adaptive cancer therapy.However,the clinical validation of GenAI support for clinical decisions in oncology needs to address the complexity and unique challenges of GenAI clinical interventions.The United States Food and Drug Administration(FDA)guidelines on the clinical evaluation of software as a medical device(SaMD)are explored as a basis for the clinical evaluation of GenAI-assisted adaptive cancer therapy.Metrics are proposed to address clinical associations and analytical validation along with an outlook on randomized clinical trials.This article provides a much-needed and timely perspective on the clinical evaluation of GenAI-assisted cancer treatments and provides insights into overcoming the inherent challenges of GenAI in its acceptance and adoption in real-world clinical settings.展开更多
Although previous studies have demonstrated that transcranial focused ultrasound stimulation protects the ischemic brain,clear criteria for the stimulation time window and intensity are lacking.Electrical impedance to...Although previous studies have demonstrated that transcranial focused ultrasound stimulation protects the ischemic brain,clear criteria for the stimulation time window and intensity are lacking.Electrical impedance tomography enables real-time monitoring of changes in cerebral blood perfusion within the ischemic brain,but investigating the feasibility of using this method to assess post-stroke rehabilitation in vivo remains critical.In this study,ischemic stroke was induced in rats through middle cerebral artery occlusion surgery.Transcranial focused ultrasound stimulation was used to treat the rat model of ischemia,and electrical impedance tomography was used to measure impedance during both the acute stage of ischemia and the rehabilitation stage following the stimulation.Electrical impedance tomography results indicated that cerebral impedance increased after the onset of ischemia and decreased following transcranial focused ultrasound stimulation.Furthermore,the stimulation promoted motor function recovery,reduced cerebral infarction volume in the rat model of ischemic stroke,and induced the expression of brain-derived neurotrophic factor in the ischemic brain.Our results also revealed a significant correlation between the impedance of the ischemic brain post-intervention and improvements in behavioral scores and infarct volume.This study shows that daily administration of transcranial focused ultrasound stimulation for 20 minutes to the ischemic hemisphere 24 hours after cerebral ischemia enhanced motor recovery in a rat model of ischemia.Additionally,our findings indicate that electrical impedance tomography can serve as a valuable tool for quantitatively evaluating rehabilitation after ischemic stroke in vivo.These findings suggest the feasibility of using impedance data collected via electrical impedance tomography to clinically assess the effects of rehabilitatory interventions for patients with ischemic stroke.展开更多
Vacuum glazing is highly regarded for its ability to transmit light while providing heat preservation,sound insulation,lightweight characteristics,and resistance to condensation.Scholars have made significant strides ...Vacuum glazing is highly regarded for its ability to transmit light while providing heat preservation,sound insulation,lightweight characteristics,and resistance to condensation.Scholars have made significant strides in the study of vacuum glazing through their notable efforts.This study systematically reviewed vacuum glazing and its composite structures,including material selection,fabrication techniques,research methods,and performance evaluation.This review initially presented fundamental techniques for preparing vacuum glazing,with a focus on edge seal and support pillar arrangements,and introduced common composite structures such as hybrid and tinted vacuum glazing.Furthermore,this review summarized the analytical,numerical,and experimental methodologies used to assess the thermal performance of vacuum glazing.This study also outlined heat transfer coefficients associated with various vacuum glazing structures,investigated the influence of different parameters on their heat transfer coefficients,and evaluated their potential for energy conservation across diverse climatic regions.Finally,the research delineated future trends in the advancement of vacuum glazing to provide guidance for both theoretical studies and practical applications in industry.This research serves as a valuable resource for both theoretical exploration and practical integration of vacuum glazing,facilitating its improvement and optimization to advance sustainable low-carbon building practices.展开更多
The acetylpolyamine oxidase(APAO),spermine oxidase(SMO),and spermidine/spermine N1-acetyltransferase(SSAT)are pivotal enzymes in polyamine metabolism,exerting direct influence on polyamine homeostasis regulation.Dysfu...The acetylpolyamine oxidase(APAO),spermine oxidase(SMO),and spermidine/spermine N1-acetyltransferase(SSAT)are pivotal enzymes in polyamine metabolism,exerting direct influence on polyamine homeostasis regulation.Dysfunctions in these enzymes are intricately linked to inflammatory diseases and cancers.Establishing their three-dimensional structures is essential for exploring enzymatic catalytic mechanisms and designing inhibitors at the atomic level.This article primarily assesses the precision of AlphaFold2 and molecular dynamics simulations in determining the three-dimensional structures of these enzymes,utilizing protein conformation rationality assessment,residue correlation matrix,and other techniques.This provides robust models for subsequent polyamine catabolic metabolism calculations and offers valuable insights for modeling proteins that have yet to acquire crystal structures.展开更多
It is well recognized that Structural Health Monitoring(SHM)reliability evaluation is a key aspect that needs to be urgently addressed to promote the wide application of SHM methods.However,the existing studies typica...It is well recognized that Structural Health Monitoring(SHM)reliability evaluation is a key aspect that needs to be urgently addressed to promote the wide application of SHM methods.However,the existing studies typically transfer the Non-Destructive Testing/Evaluation(NDT/E)reliability metrics to SHM without a systematic analysis of where these metrics originated.Seldom attentions are paid to the evaluation conditions which are very important to apply these metrics.Aimed at this issue,a new condition control-based Dual-Reliability Evaluation(Dual-RE)method for SHM is proposed.This new method is proposed based on a systematic analysis of the whole framework of reliability evaluation from instrument to NDT,and emphasis is paid to the evaluation condition control.Based on these analyses,considering the special online application scenario of SHM,the proposed Dual-RE method contains two key components:Integrated Sensor-based SHM-RE(IS-SHM-RE)and Critical Service Condition-based SHM-RE(CSC-SHM-RE).ISSHM-RE evaluates the reliability of integrated SHM sensor and system themselves under approximate repeatability conditions,while CSC-SHM-RE assesses SHM reliability under the dominant uncertainties during service,namely intermediate conditions.To demonstrate the Dual-RE,crack monitoring by using the Guided Wave-based-SHM(GW-SHM)on aircraft lug structures is taken as a case study.Both the crack detection and sizing performance are evaluated from accuracy and uncertainty.展开更多
Evaluating the adversarial robustness of classification algorithms in machine learning is a crucial domain.However,current methods lack measurable and interpretable metrics.To address this issue,this paper introduces ...Evaluating the adversarial robustness of classification algorithms in machine learning is a crucial domain.However,current methods lack measurable and interpretable metrics.To address this issue,this paper introduces a visual evaluation index named confidence centroid skewing quadrilateral,which is based on a classification confidence-based confusion matrix,offering a quantitative and visual comparison of the adversarial robustness among different classification algorithms,and enhances intuitiveness and interpretability of attack impacts.We first conduct a validity test and sensitive analysis of the method.Then,prove its effectiveness through the experiments of five classification algorithms including artificial neural network(ANN),logistic regression(LR),support vector machine(SVM),convolutional neural network(CNN)and transformer against three adversarial attacks such as fast gradient sign method(FGSM),DeepFool,and projected gradient descent(PGD)attack.展开更多
We present a comprehensive description and benchmark evaluation of the global–regional chemical transport model called the Emission and Atmospheric Processes Integrated and Coupled Community(EPICC)model.The framework...We present a comprehensive description and benchmark evaluation of the global–regional chemical transport model called the Emission and Atmospheric Processes Integrated and Coupled Community(EPICC)model.The framework incorporates(1)grid configuration,(2)transport dynamics,(3)chemical mechanisms,(4)aerosol processes,(5)wet/dry deposition parameterizations,and(6)heterogeneous chemistry treatments associated with sulfate,nitrous acid(HONO)chemistry,and aerosol/cloud–photolysis interactions(APIs/CPIs).Openly shared with the atmospheric research community,the model facilitates integration of advanced physicochemical schemes to enhance simulation accuracy.Globally,the model demonstrates realistic representations of ozone(O_(3))and aerosol optical depth.The EPICC model generally demonstrates robust performance in simulating regional concentrations of O_(3) and PM_(2.5)(and its components)in China.It successfully captures vertical profiles of both global and regional O_(3).Notably,the model mitigates frequently reported sulfate underestimations in highly industrialized regions of China.The model accurately captures two regional severe pollution episodes observed in eastern China(January/June 2021).Sensitivity experiments highlight the critical roles of heterogeneous chemical mechanisms associated with sulfate,HONO chemistry,APIs,and CPIs in capturing PM_(2.5) and O_(3) concentrations in China.Improved sulfate mechanisms result in an increase of approximately 32.4%(2.8μg m^(−3))in simulated winter sulfate concentrations when observations exceed 10μg m^(−3).Enhanced HONO elevates winter O_(3) and PM_(2.5) by≤20 and≤10μg m^(−3),respectively.Overall,CPIs dominate over APIs in improving O_(3) and PM_(2.5) simulations across China.Locally,APIs mitigate PM_(2.5) and O_(3) discrepancies in the Sichuan Basin.Seasonal cloud–chemistry coupling explains the weaker impact of PM_(2.5) in summer.展开更多
The China Seismo-Electromagnetic Satellite(CSES) was successfully launched in February 2018. The high precision magnetometer(HPM) on board the CSES has captured high-quality magnetic data that have been used to derive...The China Seismo-Electromagnetic Satellite(CSES) was successfully launched in February 2018. The high precision magnetometer(HPM) on board the CSES has captured high-quality magnetic data that have been used to derive a global lithospheric magnetic field model. While preparing the datasets for this lithospheric magnetic field model, researchers found that they still contained prominent residual trends within the magnetic anomaly even once signals from other sources had been eliminated. However, no processing was undertaken to deal with the residual trends during modeling to avoid subjective processing and represent the realistic nature of the data. In this work, we analyze the influence of these residual trends on the lithospheric magnetic field modeling.Polynomials of orders 0–3 were used to fit the trend of each track and remove it for detrending. We then derived four models through detrending-based processing, and compared their power spectra and grid maps with those of the CSES original model and CHAOS-7model. The misfit between the model and the dataset decreased after detrending the data, and the convergence of the inverted spherical harmonic coefficients improved. However, detrending reduced the signal strength and the power spectrum, while detrending based on high-order polynomials introduced prominent distortions in details of the magnetic anomaly. Based on this analysis, we recommend along-track detrending by using a zero-order polynomial(removing a constant value) on the CSES magnetic anomaly data to drag its mean value to zero. This would lead to only a slight reduction in the signal strength while significantly improving the stability of the inverted coefficients and details of the anomaly.展开更多
Research on scale effects on flows over weirs has been conducted on a limited basis, primarily focusing on flows upstream of a single-type weir, such as ogee, broad-crested, and sharp-crested (linear and non-linear) w...Research on scale effects on flows over weirs has been conducted on a limited basis, primarily focusing on flows upstream of a single-type weir, such as ogee, broad-crested, and sharp-crested (linear and non-linear) weirs. However, the scale effects downstream of these single-type weirs have not been thoroughly investigated. This study examined the scale effects on flows over a combined weir system consisting of an ogee weir and a sharp-crested weir, both upstream and downstream, utilizing physical modeling at a 1:33.33 scale based on Froude similarity and three-dimensional (3D) computational fluid dynamics (CFD) modeling. The sharp-crested weir in this study was represented by two sluice gates that remain closed and submerged during flood events. The experimental data confirmed that the equivalent discharge coefficients of the combined weir system behaved similarly to those of a sharp-crested weir across various H/P (where H is the total head, and P is the weir height) values. However, scale effects on the discharge rating curve due to surface tension and viscosity could only be minimized when H/P > 0.4, Re > 26 959, and We > 240 (where Re and We are the Reynolds and Weber numbers, respectively), provided that the water depth exceeded 0.042 m above the crest. Additionally, Re greater than 4 × 104 was necessary to minimize scale effects caused by viscosity in flows in the spillway channel and stilling basin (with baffle blocks). The limiting criteria aligned closely with existing literature. This study offers valuable insights for practical applications in hydraulic engineering in the future.展开更多
Heterogeneous composites have strong anisotropy and are prone to dynamic recrystallization during hot compression,making the me-chanical response highly nonlinear.Therefore,it is a very challenging task to intellectua...Heterogeneous composites have strong anisotropy and are prone to dynamic recrystallization during hot compression,making the me-chanical response highly nonlinear.Therefore,it is a very challenging task to intellectually judge the thermal deformation characteristics of magnesium matrix composites(MgMCs).In view of this,this paper introduces a method to accurately solve the thermoplastic deformation of composites.Firstly,a hot compression constitutive model of magnesium matrix composites based on stress softening correction was established.Secondly,the complex quasi-realistic micromechanics modeling of heterogeneous magnesium matrix composites was conducted.By introducing the recrystallization softening factor and strain parameter into the constitutive equation,the accurate prediction of the global rheological response of the composites was realized,and the accuracy of the new constitutive model was proved.Finally,the thermal pro-cessing map of magnesium matrix composites was established,and the suitable processing range was chosen.This paper has certain guiding values for the prediction of the thermodynamic response and thermal processing of magnesium matrix composites.展开更多
Iron is an essential mineral element that plays important roles in plant growth,development,and human health.Peanut is a valuable source of iron for human nutrition.Improving iron content in peanut seeds can enhance b...Iron is an essential mineral element that plays important roles in plant growth,development,and human health.Peanut is a valuable source of iron for human nutrition.Improving iron content in peanut seeds can enhance both yield potential and nutritional value.In this study,the seed iron content of the 401 peanut germplasm accessions was estimated and substantial variation among these accessions was observed,ranging from 9.02 to 50.60 mg/kg.The seed iron content of valencia type accessions was significantly higher than that of Peruvian,Virginia,and Irregular types.Landraces showed the highest average iron content,followed by advanced cultivars,breeding lines and interspecific hybrid cultivars.Accessions with red seed coat exhibited significantly higher iron content compared with those with pink seed coat.Correlation analysis revealed that the seed iron content significantly negatively correlated with hundred seed weight(HSW),resveratrol and oleic acid.Eight accessions with high iron content were identified with an average iron content of 32.46 mg/kg,including two elite genotypes that Zh.h4280 showed high resveratrol levels(1057.34μg/kg)and Zh.h1976 exhibited large seeds(HSW over 90g).Association analysis identified four markers,one of which,AHGS2053 stably explained with 5.75%–5.84%phenotypic variation.Accessions containing the favorable allele AHGS2053-250bp exhibited significantly higher iron content compared to those with alternative alleles.The results provide valuable germplasm resources and associated markers for breeding programs targeting high iron content in peanuts.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
The dissolution of MgO-refractory into the slag had an obvious influence on the steel-slag reaction and the slag property,especially for high-aluminum steels.The dissolution behavior of MgO-refractory was investigated...The dissolution of MgO-refractory into the slag had an obvious influence on the steel-slag reaction and the slag property,especially for high-aluminum steels.The dissolution behavior of MgO-refractory was investigated under various conditions,including the temperature,the initial steel composition,and the initial slag composition.A steel-slag-refractory kinetic model for high-aluminum steel was developed,which incorporated the process of MgO-refractory dissolution.The dependence of the MgO mass transfer coefficient k_(MgO)^(r)on temperature T during MgO-refractory dissolution process was established,as described by ln k_(MgO)^(r)=63,754/T+24.38524.It was indicated that the MgO dissolution rate was significantly influenced by the temperature.A higher temperature increased the dissolution rate of MgO.The initial steel composition had a slight impact on the MgO dissolution rate.Additionally,the initial slag composition strongly impacted the MgO saturation concentration and the dissolution rate.A lower initial Al_(2)O_(3)/SiO_(2)ratio increased the MgO dissolution rate.The steel-slag-refractory kinetic model accurately predicted the dissolution of MgO-refractory and the influence of dissolved MgO on the viscosity and composition change during steel-slag-refractory reactions.It was suggested that a higher temperature can hardly reduce the viscosity due to the dissolution of the MgO-refractory.展开更多
Pull-ups are a very common fitness exercise that can be seen in many gyms.For athletes,it is very important to perform pull-ups correctly and scientifically.The pull-up scoring method designed in this paper can score ...Pull-ups are a very common fitness exercise that can be seen in many gyms.For athletes,it is very important to perform pull-ups correctly and scientifically.The pull-up scoring method designed in this paper can score the quality of pull-up movement scientifically and objectively,and provide guidance to help athletes better complete the pull-up movement.In this method,the OpenPose algorithm is used to identify the coordinates of skeleton points,and then the coordinate data are processed by a Kalman filter to obtain coordinates closer to the true values.Finally,the filtered data are input into the scoring algorithm designed based on the fuzzy comprehensive evaluation algorithm,and the results of the pull-up quality score and the corresponding guidance are obtained.展开更多
基金funding from the National Natural Science Foundation of China(No.U24B6001)the CNPC Innovation Fund(No.2021DQ02-0502).
文摘Re-fracturing horizontal wells is a critical strategy for enhancing recovery from tight oil reservoirs,but its success depends on the evaluation of candidate wells and locations.This process is complicated by production-induced alterations in reservoir pressure and geomechanical responses.This study introduces a workflow to evaluate re-fracturing potential by integrating coupled fluid flow and geomechanical modeling for the production of initial hydraulic fractures.We developed a numerical model that simulates the poroelastic response of a tight oil reservoir to depletion from an initial set of hydraulic fractures.To quantify the re-fracturing potential along the horizontal wellbore,a novel composite re-fracturing potential index is proposed where fracture shape,stress,and pressure are considered.This index considers four key physical factors:current reservoir pressure,fracture initiation ease,fracture geometry favorability,and fracture propagation efficiency considering tortuosity.Numerical simulations were conducted for scenarios with both uniform and non-uniform initial hydraulic fractures.The results consistently demonstrate that the optimal locations for re-fracturing are the midpoints between existing fractures,where a favorable balance of high reservoir pressure and altered stress conditions exists.The analysis reveals that the overall re-fracturing potential tends to increase with production time,suggesting that a period of depletion can enhance the geomechanical conditions for subsequent stimulation.Furthermore,a sensitivity analysis on the index weighting factors shows that the optimum re-fracturing strategy is highly dependent on the primary field objective,whether it is maximizing resource contact,ensuring geomechanical feasibility,or avoiding operational complexity.The study concludes that heterogeneity in the initial fracture network creates complex and asymmetric potential profiles,which implies the necessity of case-specific and integrated analysis over simplified assumptions.The proposed methodology provides a framework for optimizing re-fracturing designs in tight oil reservoirs.
基金funded by the Joint Project of Industry-University-Research of Jiangsu Province(Grant:BY20231146).
文摘With the widespread application of Internet of Things(IoT)technology,the processing of massive realtime streaming data poses significant challenges to the computational and data-processing capabilities of systems.Although distributed streaming data processing frameworks such asApache Flink andApache Spark Streaming provide solutions,meeting stringent response time requirements while ensuring high throughput and resource utilization remains an urgent problem.To address this,the study proposes a formal modeling approach based on Performance Evaluation Process Algebra(PEPA),which abstracts the core components and interactions of cloud-based distributed streaming data processing systems.Additionally,a generic service flow generation algorithmis introduced,enabling the automatic extraction of service flows fromthe PEPAmodel and the computation of key performance metrics,including response time,throughput,and resource utilization.The novelty of this work lies in the integration of PEPA-based formal modeling with the service flow generation algorithm,bridging the gap between formal modeling and practical performance evaluation for IoT systems.Simulation experiments demonstrate that optimizing the execution efficiency of components can significantly improve system performance.For instance,increasing the task execution rate from 10 to 100 improves system performance by 9.53%,while further increasing it to 200 results in a 21.58%improvement.However,diminishing returns are observed when the execution rate reaches 500,with only a 0.42%gain.Similarly,increasing the number of TaskManagers from 10 to 20 improves response time by 18.49%,but the improvement slows to 6.06% when increasing from 20 to 50,highlighting the importance of co-optimizing component efficiency and resource management to achieve substantial performance gains.This study provides a systematic framework for analyzing and optimizing the performance of IoT systems for large-scale real-time streaming data processing.The proposed approach not only identifies performance bottlenecks but also offers insights into improving system efficiency under different configurations and workloads.
基金Supported by National High-quality Development Project of China(Grant No.2340STCZB193).
文摘The average stiffness performance indices throughout the workspace are commonly used as global stiffness performance indices to evaluate the overall stiffness performance of parallel mechanisms,which involves an analysis of the stiffness performance of numerous discrete points in the workspace.This necessitates time-consuming and inefficient calculation,which is particularly pronounced in the optimization design stage of the mechanism,where the variations in the global stiffness performance indices versus various dimensional and structural parameters need to be analyzed.This paper presents a semi-analytical approach for stiffness modeling of the novel(R(RPS&RP))&2-UPS parallel mechanism(referred to as the Trifree mechanism)and proposes“local”stiffness performance indices as alternatives to global indices.Drawing on the screw theory,the Cartesian stiffness matrix of the Trifree mechanism is formulated explicitly by considering the compliances of all elastic elements and the over-constraint characteristics inherent in the mechanism.Based on the spherical motion pattern of the Trifree mechanism,four special reference configurations are extracted within the workspace.This yields“local”stiffness performance indices capable of accurately evaluating the overall stiffness performance of the mechanism and effectively improving the computational efficiency.The variations in global and“local”stiffness performance indices versus key design parameters are investigated.Furthermore,the proposed indices are applied to the Tricept and Trimule mechanisms.The results demonstrate that the proposed indices exhibit excellent computational accuracy and efficiency in evaluating the overall stiffness performance of these spherical parallel mechanisms.Moreover,the stiffness performance of the novel parallel mechanism investigated in this study closely resembles that of the well-known Tricept and Trimule mechanisms.This research proposes a semi-analytic stiffness model of the Trifree mechanism and“local”stiffness performance indices to evaluate the overall stiffness performance,thereby substantially improving the computational efficiency without sacrificing accuracy.
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.
基金National Natural Science Foundation of China,Grant/Award Number:82000102 and 82270112。
文摘The incidence of benign airway stenosis(BAS)is on the rise,and current treatment options are associated with a significant risk of restenosis.Therefore,there is an urgent need to explore new and effective prevention and treatment methods.Animal models serve as essential tools for investigating disease mechanisms and assessing novel therapeutic strategies,and the scientific rigor of their construction and validation significantly impacts the reliability of research findings.This paper systematically reviews the research progress and evaluation systems of BAS animal models over the past decade,aiming to provide a robust foundation for the optimized construction of BAS models,intervention studies,and clinical translation.This effort is intended to facilitate the innovation and advancement in BAS prevention and treatment strategies.
基金Supported by Tangshan Talent Funding Project in 2025(B202304018).
文摘With the improvement of living standards and the shift in societal consumption attitudes,consumers demand for the quality of aquatic products is increasingly stringent.Freshness and quality have become primary factors determining consumers purchasing decisions.However,due to the high moisture content,active endogenous enzymes,and rich nutrients in aquatic products,both fresh and processed products are highly susceptible to quality deterioration during procurement,distribution,and storage,which leads to a significant decline in sensory quality and nutritional value,while also compromising safety.Today,the consumption of high-quality aquatic products has become a prevailing trend.This paper reviewed the methods for freshness evaluation and quality grading of aquatic products in terms of sensory and nutritional aspects,aiming to support the market circulation principle of"higher price for better quality"and"price based on quality",and better meeting consumer demands.Therefore,it is imperative to enhance the analysis and evaluation of aquatic product quality and to continuously refine assessment systems and methods,which is crucial for promoting industry transformation and fostering a healthy market-consumer economic cycle.
文摘The learning and inferencing capabilities of large language models(LLMs)that underlie generative artificial intelligence(GenAI)can be exploited to optimize cancer treatments and improve patient outcomes.The ability of these models to learn from large amounts of clinical,molecular,and radiomic data on cancer patients and their treatments is driving research interest in their application to treatment decision-making.The learning and predictive power of LLMs make them uniquely suitable for supporting adaptive cancer therapy.However,the clinical validation of GenAI support for clinical decisions in oncology needs to address the complexity and unique challenges of GenAI clinical interventions.The United States Food and Drug Administration(FDA)guidelines on the clinical evaluation of software as a medical device(SaMD)are explored as a basis for the clinical evaluation of GenAI-assisted adaptive cancer therapy.Metrics are proposed to address clinical associations and analytical validation along with an outlook on randomized clinical trials.This article provides a much-needed and timely perspective on the clinical evaluation of GenAI-assisted cancer treatments and provides insights into overcoming the inherent challenges of GenAI in its acceptance and adoption in real-world clinical settings.
基金supported by the Fundamental Research Funds for the Central Universities,Nos.G2021KY05107,G2021KY05101the National Natural Science Foundation of China,Nos.32071316,32211530049+1 种基金the Natural Science Foundation of Shaanxi Province,No.2022-JM482the Education and Teaching Reform Funds for the Central Universities,No.23GZ230102(all to LL and HH).
文摘Although previous studies have demonstrated that transcranial focused ultrasound stimulation protects the ischemic brain,clear criteria for the stimulation time window and intensity are lacking.Electrical impedance tomography enables real-time monitoring of changes in cerebral blood perfusion within the ischemic brain,but investigating the feasibility of using this method to assess post-stroke rehabilitation in vivo remains critical.In this study,ischemic stroke was induced in rats through middle cerebral artery occlusion surgery.Transcranial focused ultrasound stimulation was used to treat the rat model of ischemia,and electrical impedance tomography was used to measure impedance during both the acute stage of ischemia and the rehabilitation stage following the stimulation.Electrical impedance tomography results indicated that cerebral impedance increased after the onset of ischemia and decreased following transcranial focused ultrasound stimulation.Furthermore,the stimulation promoted motor function recovery,reduced cerebral infarction volume in the rat model of ischemic stroke,and induced the expression of brain-derived neurotrophic factor in the ischemic brain.Our results also revealed a significant correlation between the impedance of the ischemic brain post-intervention and improvements in behavioral scores and infarct volume.This study shows that daily administration of transcranial focused ultrasound stimulation for 20 minutes to the ischemic hemisphere 24 hours after cerebral ischemia enhanced motor recovery in a rat model of ischemia.Additionally,our findings indicate that electrical impedance tomography can serve as a valuable tool for quantitatively evaluating rehabilitation after ischemic stroke in vivo.These findings suggest the feasibility of using impedance data collected via electrical impedance tomography to clinically assess the effects of rehabilitatory interventions for patients with ischemic stroke.
基金supported by the National Key R&D Program of China(2023YFC3806202)the National Natural Science Foundation of China(52308093)+3 种基金the Natural Science Foundation of Hunan Province(2023JJ40154)the Science and Technology Innovation Leading Talent Program of Hunan Province(2023RC1042)the Natural Science Foundation of Changsha(kq2208032)the China Postdoctoral Science Foundation(2023M741132 and 2024T170263)。
文摘Vacuum glazing is highly regarded for its ability to transmit light while providing heat preservation,sound insulation,lightweight characteristics,and resistance to condensation.Scholars have made significant strides in the study of vacuum glazing through their notable efforts.This study systematically reviewed vacuum glazing and its composite structures,including material selection,fabrication techniques,research methods,and performance evaluation.This review initially presented fundamental techniques for preparing vacuum glazing,with a focus on edge seal and support pillar arrangements,and introduced common composite structures such as hybrid and tinted vacuum glazing.Furthermore,this review summarized the analytical,numerical,and experimental methodologies used to assess the thermal performance of vacuum glazing.This study also outlined heat transfer coefficients associated with various vacuum glazing structures,investigated the influence of different parameters on their heat transfer coefficients,and evaluated their potential for energy conservation across diverse climatic regions.Finally,the research delineated future trends in the advancement of vacuum glazing to provide guidance for both theoretical studies and practical applications in industry.This research serves as a valuable resource for both theoretical exploration and practical integration of vacuum glazing,facilitating its improvement and optimization to advance sustainable low-carbon building practices.
基金National Natural Science Foundation of China(22073023)Natural Science Foundation of Henan Province(242300421134)+1 种基金the Young Backbone Teacher in Colleges and Universities of Henan Province(2021GGJS020)Foundation of State Key Laboratory of Antiviral Drugs。
文摘The acetylpolyamine oxidase(APAO),spermine oxidase(SMO),and spermidine/spermine N1-acetyltransferase(SSAT)are pivotal enzymes in polyamine metabolism,exerting direct influence on polyamine homeostasis regulation.Dysfunctions in these enzymes are intricately linked to inflammatory diseases and cancers.Establishing their three-dimensional structures is essential for exploring enzymatic catalytic mechanisms and designing inhibitors at the atomic level.This article primarily assesses the precision of AlphaFold2 and molecular dynamics simulations in determining the three-dimensional structures of these enzymes,utilizing protein conformation rationality assessment,residue correlation matrix,and other techniques.This provides robust models for subsequent polyamine catabolic metabolism calculations and offers valuable insights for modeling proteins that have yet to acquire crystal structures.
基金the support from National Natural Science Foundation of China(No.52275153)the Frontier Technologies R&D Program of Jiangsu,China(No.BF2024068)+1 种基金The Fund of Prospective Layout of Scientific Research for Nanjing University of Aeronautics and Astronautics,ChinaResearch Fund of State Key Laboratory of Mechanics and Control for Aerospace Structures(Nanjing University of Aeronautics and Astronautics),China(Nos.MCAS-I-0425K01,MCAS-I-0423G01)。
文摘It is well recognized that Structural Health Monitoring(SHM)reliability evaluation is a key aspect that needs to be urgently addressed to promote the wide application of SHM methods.However,the existing studies typically transfer the Non-Destructive Testing/Evaluation(NDT/E)reliability metrics to SHM without a systematic analysis of where these metrics originated.Seldom attentions are paid to the evaluation conditions which are very important to apply these metrics.Aimed at this issue,a new condition control-based Dual-Reliability Evaluation(Dual-RE)method for SHM is proposed.This new method is proposed based on a systematic analysis of the whole framework of reliability evaluation from instrument to NDT,and emphasis is paid to the evaluation condition control.Based on these analyses,considering the special online application scenario of SHM,the proposed Dual-RE method contains two key components:Integrated Sensor-based SHM-RE(IS-SHM-RE)and Critical Service Condition-based SHM-RE(CSC-SHM-RE).ISSHM-RE evaluates the reliability of integrated SHM sensor and system themselves under approximate repeatability conditions,while CSC-SHM-RE assesses SHM reliability under the dominant uncertainties during service,namely intermediate conditions.To demonstrate the Dual-RE,crack monitoring by using the Guided Wave-based-SHM(GW-SHM)on aircraft lug structures is taken as a case study.Both the crack detection and sizing performance are evaluated from accuracy and uncertainty.
文摘Evaluating the adversarial robustness of classification algorithms in machine learning is a crucial domain.However,current methods lack measurable and interpretable metrics.To address this issue,this paper introduces a visual evaluation index named confidence centroid skewing quadrilateral,which is based on a classification confidence-based confusion matrix,offering a quantitative and visual comparison of the adversarial robustness among different classification algorithms,and enhances intuitiveness and interpretability of attack impacts.We first conduct a validity test and sensitive analysis of the method.Then,prove its effectiveness through the experiments of five classification algorithms including artificial neural network(ANN),logistic regression(LR),support vector machine(SVM),convolutional neural network(CNN)and transformer against three adversarial attacks such as fast gradient sign method(FGSM),DeepFool,and projected gradient descent(PGD)attack.
基金National Key Scientific and Technological Infrastructure project “Earth System Science Numerical Simulator Facility” (EarthLab)supported by the National Natural Science Foundation of China (Grant No. 92044302)the National Key Research Development Program of China (Grant No. 2022YFC3700703)
文摘We present a comprehensive description and benchmark evaluation of the global–regional chemical transport model called the Emission and Atmospheric Processes Integrated and Coupled Community(EPICC)model.The framework incorporates(1)grid configuration,(2)transport dynamics,(3)chemical mechanisms,(4)aerosol processes,(5)wet/dry deposition parameterizations,and(6)heterogeneous chemistry treatments associated with sulfate,nitrous acid(HONO)chemistry,and aerosol/cloud–photolysis interactions(APIs/CPIs).Openly shared with the atmospheric research community,the model facilitates integration of advanced physicochemical schemes to enhance simulation accuracy.Globally,the model demonstrates realistic representations of ozone(O_(3))and aerosol optical depth.The EPICC model generally demonstrates robust performance in simulating regional concentrations of O_(3) and PM_(2.5)(and its components)in China.It successfully captures vertical profiles of both global and regional O_(3).Notably,the model mitigates frequently reported sulfate underestimations in highly industrialized regions of China.The model accurately captures two regional severe pollution episodes observed in eastern China(January/June 2021).Sensitivity experiments highlight the critical roles of heterogeneous chemical mechanisms associated with sulfate,HONO chemistry,APIs,and CPIs in capturing PM_(2.5) and O_(3) concentrations in China.Improved sulfate mechanisms result in an increase of approximately 32.4%(2.8μg m^(−3))in simulated winter sulfate concentrations when observations exceed 10μg m^(−3).Enhanced HONO elevates winter O_(3) and PM_(2.5) by≤20 and≤10μg m^(−3),respectively.Overall,CPIs dominate over APIs in improving O_(3) and PM_(2.5) simulations across China.Locally,APIs mitigate PM_(2.5) and O_(3) discrepancies in the Sichuan Basin.Seasonal cloud–chemistry coupling explains the weaker impact of PM_(2.5) in summer.
基金a project funded by the China National Space Administration (CNSA) and the Ministry of Emergency Management of Chinasupported by the Civil Aerospace Technology Pilot Research Project (D040203)+1 种基金the National Natural Science Foundation of China (42004051, 42274214)the APSCO Earthquake Research Project Phase Ⅱ and Dragon 6 cooperation 2025-2029 (95437)。
文摘The China Seismo-Electromagnetic Satellite(CSES) was successfully launched in February 2018. The high precision magnetometer(HPM) on board the CSES has captured high-quality magnetic data that have been used to derive a global lithospheric magnetic field model. While preparing the datasets for this lithospheric magnetic field model, researchers found that they still contained prominent residual trends within the magnetic anomaly even once signals from other sources had been eliminated. However, no processing was undertaken to deal with the residual trends during modeling to avoid subjective processing and represent the realistic nature of the data. In this work, we analyze the influence of these residual trends on the lithospheric magnetic field modeling.Polynomials of orders 0–3 were used to fit the trend of each track and remove it for detrending. We then derived four models through detrending-based processing, and compared their power spectra and grid maps with those of the CSES original model and CHAOS-7model. The misfit between the model and the dataset decreased after detrending the data, and the convergence of the inverted spherical harmonic coefficients improved. However, detrending reduced the signal strength and the power spectrum, while detrending based on high-order polynomials introduced prominent distortions in details of the magnetic anomaly. Based on this analysis, we recommend along-track detrending by using a zero-order polynomial(removing a constant value) on the CSES magnetic anomaly data to drag its mean value to zero. This would lead to only a slight reduction in the signal strength while significantly improving the stability of the inverted coefficients and details of the anomaly.
基金supported by the Ministry of Public Works and Housing of Indonesia and Parahyangan Catholic University(Grant No.II/PD/2023-07/02-SJ).
文摘Research on scale effects on flows over weirs has been conducted on a limited basis, primarily focusing on flows upstream of a single-type weir, such as ogee, broad-crested, and sharp-crested (linear and non-linear) weirs. However, the scale effects downstream of these single-type weirs have not been thoroughly investigated. This study examined the scale effects on flows over a combined weir system consisting of an ogee weir and a sharp-crested weir, both upstream and downstream, utilizing physical modeling at a 1:33.33 scale based on Froude similarity and three-dimensional (3D) computational fluid dynamics (CFD) modeling. The sharp-crested weir in this study was represented by two sluice gates that remain closed and submerged during flood events. The experimental data confirmed that the equivalent discharge coefficients of the combined weir system behaved similarly to those of a sharp-crested weir across various H/P (where H is the total head, and P is the weir height) values. However, scale effects on the discharge rating curve due to surface tension and viscosity could only be minimized when H/P > 0.4, Re > 26 959, and We > 240 (where Re and We are the Reynolds and Weber numbers, respectively), provided that the water depth exceeded 0.042 m above the crest. Additionally, Re greater than 4 × 104 was necessary to minimize scale effects caused by viscosity in flows in the spillway channel and stilling basin (with baffle blocks). The limiting criteria aligned closely with existing literature. This study offers valuable insights for practical applications in hydraulic engineering in the future.
基金supported by the National Natural Science Foundation of China with the project of No.52305158Youth Innovation Team of Shaanxi Universities(2024),Shaanxi Province Qin Chuangyuan“Scientist+Engineer”Team construction of No.2024QCY-KXJ-112,Funding from Aero Engine Cooperation of China(No.ZZCX-2022-020)the industry-university-research cooperation of Eighth Research Institute of China Aerospace Science and Technology Corporation with the project of No.USCAST2021-1.
文摘Heterogeneous composites have strong anisotropy and are prone to dynamic recrystallization during hot compression,making the me-chanical response highly nonlinear.Therefore,it is a very challenging task to intellectually judge the thermal deformation characteristics of magnesium matrix composites(MgMCs).In view of this,this paper introduces a method to accurately solve the thermoplastic deformation of composites.Firstly,a hot compression constitutive model of magnesium matrix composites based on stress softening correction was established.Secondly,the complex quasi-realistic micromechanics modeling of heterogeneous magnesium matrix composites was conducted.By introducing the recrystallization softening factor and strain parameter into the constitutive equation,the accurate prediction of the global rheological response of the composites was realized,and the accuracy of the new constitutive model was proved.Finally,the thermal pro-cessing map of magnesium matrix composites was established,and the suitable processing range was chosen.This paper has certain guiding values for the prediction of the thermodynamic response and thermal processing of magnesium matrix composites.
基金supported by the National Key Research and Development Program of China(2023YFD1200200)the earmarked funds for CARS(No.CARS-13)+2 种基金the Agricultural Science and Technology Innovation Program of Chinese Academy of Agricultural Sciences(CAAS-ASTIP-2025-OCRI)the National Program for Crop Germplasm Protection of China(22250402)the National Crop Germplasm Resources Center(NCGRC-2025-036)。
文摘Iron is an essential mineral element that plays important roles in plant growth,development,and human health.Peanut is a valuable source of iron for human nutrition.Improving iron content in peanut seeds can enhance both yield potential and nutritional value.In this study,the seed iron content of the 401 peanut germplasm accessions was estimated and substantial variation among these accessions was observed,ranging from 9.02 to 50.60 mg/kg.The seed iron content of valencia type accessions was significantly higher than that of Peruvian,Virginia,and Irregular types.Landraces showed the highest average iron content,followed by advanced cultivars,breeding lines and interspecific hybrid cultivars.Accessions with red seed coat exhibited significantly higher iron content compared with those with pink seed coat.Correlation analysis revealed that the seed iron content significantly negatively correlated with hundred seed weight(HSW),resveratrol and oleic acid.Eight accessions with high iron content were identified with an average iron content of 32.46 mg/kg,including two elite genotypes that Zh.h4280 showed high resveratrol levels(1057.34μg/kg)and Zh.h1976 exhibited large seeds(HSW over 90g).Association analysis identified four markers,one of which,AHGS2053 stably explained with 5.75%–5.84%phenotypic variation.Accessions containing the favorable allele AHGS2053-250bp exhibited significantly higher iron content compared to those with alternative alleles.The results provide valuable germplasm resources and associated markers for breeding programs targeting high iron content in peanuts.
基金the World Climate Research Programme(WCRP),Climate Variability and Predictability(CLIVAR),and Global Energy and Water Exchanges(GEWEX)for facilitating the coordination of African monsoon researchsupport from the Center for Earth System Modeling,Analysis,and Data at the Pennsylvania State Universitythe support of the Office of Science of the U.S.Department of Energy Biological and Environmental Research as part of the Regional&Global Model Analysis(RGMA)program area。
文摘In recent years,there has been an increasing need for climate information across diverse sectors of society.This demand has arisen from the necessity to adapt to and mitigate the impacts of climate variability and change.Likewise,this period has seen a significant increase in our understanding of the physical processes and mechanisms that drive precipitation and its variability across different regions of Africa.By leveraging a large volume of climate model outputs,numerous studies have investigated the model representation of African precipitation as well as underlying physical processes.These studies have assessed whether the physical processes are well depicted and whether the models are fit for informing mitigation and adaptation strategies.This paper provides a review of the progress in precipitation simulation overAfrica in state-of-the-science climate models and discusses the major issues and challenges that remain.
基金support from the National Key R&D Program of China(Grant No.2023YFB3709901)the National Natural Science Foundation of China(Grant No.U22A20171)+1 种基金China Baowu Low Carbon Metallurgy Innovation Foundation(Grant No.BWLCF202315)the High Steel Center(HSC)at North China University of Technology and University of Science and Technology Beijing,China.
文摘The dissolution of MgO-refractory into the slag had an obvious influence on the steel-slag reaction and the slag property,especially for high-aluminum steels.The dissolution behavior of MgO-refractory was investigated under various conditions,including the temperature,the initial steel composition,and the initial slag composition.A steel-slag-refractory kinetic model for high-aluminum steel was developed,which incorporated the process of MgO-refractory dissolution.The dependence of the MgO mass transfer coefficient k_(MgO)^(r)on temperature T during MgO-refractory dissolution process was established,as described by ln k_(MgO)^(r)=63,754/T+24.38524.It was indicated that the MgO dissolution rate was significantly influenced by the temperature.A higher temperature increased the dissolution rate of MgO.The initial steel composition had a slight impact on the MgO dissolution rate.Additionally,the initial slag composition strongly impacted the MgO saturation concentration and the dissolution rate.A lower initial Al_(2)O_(3)/SiO_(2)ratio increased the MgO dissolution rate.The steel-slag-refractory kinetic model accurately predicted the dissolution of MgO-refractory and the influence of dissolved MgO on the viscosity and composition change during steel-slag-refractory reactions.It was suggested that a higher temperature can hardly reduce the viscosity due to the dissolution of the MgO-refractory.
文摘Pull-ups are a very common fitness exercise that can be seen in many gyms.For athletes,it is very important to perform pull-ups correctly and scientifically.The pull-up scoring method designed in this paper can score the quality of pull-up movement scientifically and objectively,and provide guidance to help athletes better complete the pull-up movement.In this method,the OpenPose algorithm is used to identify the coordinates of skeleton points,and then the coordinate data are processed by a Kalman filter to obtain coordinates closer to the true values.Finally,the filtered data are input into the scoring algorithm designed based on the fuzzy comprehensive evaluation algorithm,and the results of the pull-up quality score and the corresponding guidance are obtained.
