Purpose–The deformation of the roadbed is easily influenced by the external environment to improve the accuracy of high-speed railway subgrade settlement prediction.Design/methodology/approach–A high-speed railway s...Purpose–The deformation of the roadbed is easily influenced by the external environment to improve the accuracy of high-speed railway subgrade settlement prediction.Design/methodology/approach–A high-speed railway subgrade settlement interval prediction method using the secretary bird optimization(SBOA)algorithm to optimize the BP neural network under the premise of gray relational analysis is proposed.Findings–Using the SBOA algorithm to optimize the BP neural network,the optimal weights and thresholds are obtained,and the best parameter prediction model is combined.The data were collected from the sensors deployed through the subgrade settlement monitoring system,and the gray relational analysis is used to verify that all four influencing factors had a great correlation to the subgrade settlement,and the collected data are verified using the model.Originality/value–The experimental results show that the SBOA-BP model has higher prediction accuracy than the BP model,and the SBOA-BP model has a wider range of prediction intervals for a given confidence level,which can provide higher guiding value for practical engineering applications.展开更多
In this study,a machine learning-based predictive model was developed for the Musa petti Wind Farm in Sri Lanka to address the need for localized forecasting solutions.Using data on wind speed,air temperature,nacelle ...In this study,a machine learning-based predictive model was developed for the Musa petti Wind Farm in Sri Lanka to address the need for localized forecasting solutions.Using data on wind speed,air temperature,nacelle position,and actual power,lagged features were generated to capture temporal dependencies.Among 24 evaluated models,the ensemble bagging approach achieved the best performance,with R^(2) values of 0.89 at 0 min and 0.75 at 60 min.Shapley Additive exPlanations(SHAP)analysis revealed that while wind speed is the primary driver for short-term predictions,air temperature and nacelle position become more influential at longer forecasting horizons.These findings underscore the reliability of short-term predictions and the potential benefits of integrating hybrid AI and probabilistic models for extended forecasts.Our work contributes a robust and explainable framework to support Sri Lanka’s renewable energy transition,and future research will focus on real-time deployment and uncertainty quantification.展开更多
BACKGROUND Colorectal cancer(CRC)remains one of the leading causes of cancer-related morbidity and mortality worldwide.Growing evidence suggests that gut microbial dysbiosis plays a crucial role in tumorigenesis and c...BACKGROUND Colorectal cancer(CRC)remains one of the leading causes of cancer-related morbidity and mortality worldwide.Growing evidence suggests that gut microbial dysbiosis plays a crucial role in tumorigenesis and can influence therapeutic responses.AIM To explore the associations between serum S100A12 and soluble CD14(sCD14)levels and gut microbiota alterations in patients with CRC,and to assess the predictive utility of these biomarkers in forecasting chemotherapy response.METHODS A retrospective analysis was conducted on 104 patients diagnosed with advanced CRC(CRC group)and 104 age-matched and sex-matched healthy controls.Serum concentrations of S100A12 and sCD14 were measured using enzyme-linked immunosorbent assay.Fecal samples collected before chemotherapy were subjected to 16S rRNA sequencing to profile gut microbial composition.Pearson correlation analysis was used to evaluate the relationship between biomarker levels and microbial abundance.Receiver operating characteristic(ROC)curves were used to assess the predictive performance of S100A12 and sCD14 for chemotherapy response.RESULTS CRC patients exhibited significantly higher serum levels of S100A12 and sCD14 compared to healthy individuals(P<0.05).Patients with moderate to severe gut dysbiosis showed the highest elevations of these biomarkers(P<0.05).Elevated levels of S100A12 and sCD14 were positively correlated with Fusobacterium nucleatum and Prevotella abundance,and negatively correlated with Faecalibacterium prausnitzii and Akkermansia muciniphila(P<0.05).Both biomarkers significantly decreased following chemotherapy(P<0.05).Non-responders to chemotherapy had higher pre-treatment levels of S100A12 and sCD14 compared to responders(P<0.05).Combined ROC analysis showed improved diagnostic accuracy compared to either marker alone.CONCLUSION Serum S100A12 and sCD14 levels are closely associated with gut microbiota imbalance and chemotherapy response in CRC patients.These markers may serve as promising predictive indicators for treatment efficacy and offer potential value in individualized treatment strategies.展开更多
Soil desiccation cracking is ubiquitous in nature and has significantpotential impacts on the engineering geological properties of soils.Previous studies have extensively examined various factors affecting soil cracki...Soil desiccation cracking is ubiquitous in nature and has significantpotential impacts on the engineering geological properties of soils.Previous studies have extensively examined various factors affecting soil cracking behavior through a numerous small-sample experiments.However,experimental studies alone cannot accurately describe soil cracking behavior.In this study,we firstly propose a modeling framework for predicting the surface crack ratio of soil desiccation cracking based on machine learning and interpretable analysis.The framework utilizes 1040 sets of soil cracking experimental data and employs random forest(RF),extreme gradient boosting(XGBoost),and artificialneural network(ANN)models to predict the surface crack ratio of soil desiccation cracking.To clarify the influenceof input features on soil cracking behavior,feature importance and Shapley additive explanations(SHAP)are applied for interpretability analysis.The results reveal that ensemble methods(RF and XGBoost)provide better predictive performance than the deep learning model(ANN).The feature importance analysis shows that soil desiccation cracking is primarily influencedby initial water content,plasticity index,finalwater content,liquid limit,sand content,clay content and thickness.Moreover,SHAP-based interpretability analysis further explores how soil cracking responds to various input variables.This study provides new insight into the evolution of soil cracking behavior,enhancing the understanding of its physical mechanisms and facilitating the assessment of potential regional development of soil desiccation cracking.展开更多
The endpoint carbon content in the converter is critical for the quality of steel products,and accurately predicting this parameter is an effective way to reduce alloy consumption and improve smelting efficiency.Howev...The endpoint carbon content in the converter is critical for the quality of steel products,and accurately predicting this parameter is an effective way to reduce alloy consumption and improve smelting efficiency.However,most scholars currently focus on modifying methods to enhance model accuracy,while overlooking the extent to which input parameters influence accuracy.To address this issue,in this study,a prediction model for the endpoint carbon content in the converter was developed using factor analysis(FA)and support vector machine(SVM)optimized by improved particle swarm optimization(IPSO).Analysis of the factors influencing the endpoint carbon content during the converter smelting process led to the identification of 21 input parameters.Subsequently,FA was used to reduce the dimensionality of the data and applied to the prediction model.The results demonstrate that the performance of the FA-IPSO-SVM model surpasses several existing methods,such as twin support vector regression and support vector machine.The model achieves hit rates of 89.59%,96.21%,and 98.74%within error ranges of±0.01%,±0.015%,and±0.02%,respectively.Finally,based on the prediction results obtained by sequentially removing input parameters,the parameters were classified into high influence(5%-7%),medium influence(2%-5%),and low influence(0-2%)categories according to their varying degrees of impact on prediction accuracy.This classi-fication provides a reference for selecting input parameters in future prediction models for endpoint carbon content.展开更多
Objective To explore the clinical characteristics and methods for syndrome differentiation prediction,as well as to construct a predictive model for Qi deficiency and blood stasis syndrome in patients with acute ische...Objective To explore the clinical characteristics and methods for syndrome differentiation prediction,as well as to construct a predictive model for Qi deficiency and blood stasis syndrome in patients with acute ischemic stroke(AIS).Methods This study employed a retrospective case-control design to analyze patients with AIS who received inpatient treatment at the Neurology Department of The First Hospital of Hunan University of Chinese Medicine from January 1,2013 to December 31,2022.AIS patients meeting the diagnostic criteria for Qi deficiency and blood stasis syndrome were stratified into case group,while those without Qi deficiency and blood stasis syndrome were stratified into control group.The demographic characteristics(age and gender),clinical parameters[time from onset to admission,National Institutes of Health Stroke Scale(NIHSS)score,and blood pressure],past medical history,traditional Chinese medicine(TCM)diagnostic characteristics(tongue and pulse),neurological symptoms and signs,imaging findings[magnetic resonance imaging-diffusion weighted imaging(MRI-DWI)],and biochemical indicators of the two groups were collected and compared.The indicators with statistical difference(P<0.05)in univariate analysis were included in multivariate logistic regression analysis to evaluate their predictive value for the diagnosis of Qi deficiency and blood stasis syndrome,and the predictive model was constructed by receiver operating characteristic(ROC)curve analysis.Results The study included 1035 AIS patients,with 404 cases in case group and 631 cases in control group.Compared with control group,patients in case group were significantly older,had extended onset-to-admission time,lower diastolic blood pressure,and lower NIHSS scores(P<0.05).Case group showed lower incidence of hypertension history(P<0.05).Regarding tongue and pulse characteristics,pale and dark tongue colors,white tongue coating,fine pulse,astringent pulse,and sinking pulse were more common in case group.Imaging examinations demonstrated higher proportions of centrum semiovale infarction,cerebral atrophy,and vertebral artery stenosis in case group(P<0.05).Among biochemical indicators,case group showed higher proportions of elevated fasting blood glucose and glycated hemoglobin(HbA1c),while lower proportions of elevated white blood cell count,reduced hemoglobin,and reduced high-density lipoprotein cholesterol(HDL-C)(P<0.05).Multivariate logistic regression analysis identified significant predictors for Qi deficiency and blood stasis syndrome including:fine pulse[odds ratio(OR)=4.38],astringent pulse(OR=3.67),superficial sensory abnormalities(OR=1.86),centrum semiovale infarction(OR=1.57),cerebral atrophy(OR=1.55),vertebral artery stenosis(OR=1.62),and elevated HbA1c(OR=3.52).The ROC curve analysis of the comprehensive prediction model yielded an area under the curve(AUC)of 0.878[95%confidence interval(CI)=0.855-0.900].Conclusion This study finds out that Qi deficiency and blood stasis syndrome represents one of the primary types of AIS.Fine pulse,astringent pulse,superficial sensory abnormalities,centrum semiovale infarction,cerebral atrophy,vertebral artery stenosis,elevated blood glucose,elevated HbA1c,pale and dark tongue colors,and white tongue coating are key objective diagnostic indicators for the syndrome differentiation of AIS with Qi deficiency and blood stasis syndrome.Based on these indicators,a syndrome differentiation prediction model has been developed,offering a more objective basis for clinical diagnosis,and help to rapidly identify this syndrome in clinical practice and reduce misdiagnosis and missed diagnosis.展开更多
The SKP1 gene is an important component of the SCF(SKP1-Cullin1-F-box)complex and serves as a bridge connecting the F-box and Cullin1genes(F-box-SKP1-Cullin1).The pattern of S-RNase being ubiquitously labelled by the ...The SKP1 gene is an important component of the SCF(SKP1-Cullin1-F-box)complex and serves as a bridge connecting the F-box and Cullin1genes(F-box-SKP1-Cullin1).The pattern of S-RNase being ubiquitously labelled by the SCF complex and degraded by the 26S protease accounts for the bulk of the available self-incompatibility studies.In this study,15 ClSKP1s from the‘Xiangshui'lemon genome and ubiquitome exist in the same SKP1 conserved domain(CD)as SKP1s in other species.The q PCR results showed that SKP1-6 and SKP1-14 have tissue expression patterns specific for expression in pollen.In addition,SKP1-6 and SKP1-14 in the stigma,style and ovary were significantly upregulated after self-pollination compared to those after cross-pollination.A subcellular location showed that SKP1-6 and SKP1-14 were located in the nucleus.In addition,yeast two-hybrid(Y2H)assays,bimolecular fluorescence complementation(BiFC)and luciferase complementation imaging(LCI)assays showed that SKP1-6 interacted with F-box1,F-box33,F-box34,F-box17,F-box19,Cullin1-2 and 26S proteasome subunit 4 homolog A(26S PS4HA).SKP1-14 interacted with F-box17,F-box19,F-box35,Cullin1-2 and 26S PS4HA.The interaction of Cullin1-2 and the F-box with SKP1 as a bridge was verified by a yeast three-hybrid experiment.The ability of S3-RNase to inhibit pollen and pollen tube growth and development was assessed using in vitro pollen co-culture experiments with recombinant S3-RNase proteins.Overall,this study provides important experimental evidence and theoretical basis for understanding the mechanism of self-incompatibility in plants by revealing the key role of the SCF complex in‘Xiangshui'lemon,which is bridged by ClSKP1-6,in self-incompatibility.The results of this study are of great significance for the future indepth exploration of the molecular mechanism of the SCF complex and its wide application in the self-incompatibility of plants.展开更多
Peripheral nerve injury is a common neurological condition that often leads to severe functional limitations and disabilities.Research on the pathogenesis of peripheral nerve injury has focused on pathological changes...Peripheral nerve injury is a common neurological condition that often leads to severe functional limitations and disabilities.Research on the pathogenesis of peripheral nerve injury has focused on pathological changes at individual injury sites,neglecting multilevel pathological analysis of the overall nervous system and target organs.This has led to restrictions on current therapeutic approaches.In this paper,we first summarize the potential mechanisms of peripheral nerve injury from a holistic perspective,covering the central nervous system,peripheral nervous system,and target organs.After peripheral nerve injury,the cortical plasticity of the brain is altered due to damage to and regeneration of peripheral nerves;changes such as neuronal apoptosis and axonal demyelination occur in the spinal cord.The nerve will undergo axonal regeneration,activation of Schwann cells,inflammatory response,and vascular system regeneration at the injury site.Corresponding damage to target organs can occur,including skeletal muscle atrophy and sensory receptor disruption.We then provide a brief review of the research advances in therapeutic approaches to peripheral nerve injury.The main current treatments are conducted passively and include physical factor rehabilitation,pharmacological treatments,cell-based therapies,and physical exercise.However,most treatments only partially address the problem and cannot complete the systematic recovery of the entire central nervous system-peripheral nervous system-target organ pathway.Therefore,we should further explore multilevel treatment options that produce effective,long-lasting results,perhaps requiring a combination of passive(traditional)and active(novel)treatment methods to stimulate rehabilitation at the central-peripheral-target organ levels to achieve better functional recovery.展开更多
As a means of quantitative interpretation,forward calculations of the global lithospheric magnetic field in the Spherical Harmonic(SH)domain have been widely used to reveal geophysical,lithological,and geothermal vari...As a means of quantitative interpretation,forward calculations of the global lithospheric magnetic field in the Spherical Harmonic(SH)domain have been widely used to reveal geophysical,lithological,and geothermal variations in the lithosphere.Traditional approaches either do not consider the non-axial dipolar terms of the inducing field and its radial variation or do so by means of complicated formulae.Moreover,existing methods treat the magnetic lithosphere either as an infinitesimally thin layer or as a radially uniform spherical shell of constant thickness.Here,we present alternative forward formulae that account for an arbitrarily high maximum degree of the inducing field and for a magnetic lithosphere of variable thickness.Our simulations based on these formulae suggest that the satellite magnetic anomaly field is sensitive to the non-axial dipolar terms of the inducing field but not to its radial variation.Therefore,in forward and inverse calculations of satellite magnetic anomaly data,the non-axial dipolar terms of the inducing field should not be ignored.Furthermore,our results show that the satellite magnetic anomaly field is sensitive to variability in the lateral thickness of the magnetized shell.In particular,we show that for a given vertically integrated susceptibility distribution,underestimating the thickness of the magnetic layer overestimates the induced magnetic field.This discovery bridges the greatest part of the alleged gap between the susceptibility values measured from rock samples and the susceptibility values required to match the observed magnetic field signal.We expect the formulae and conclusions of this study to be a valuable tool for the quantitative interpretation of the Earth's global lithospheric magnetic field,through an inverse or forward modelling approach.展开更多
Because of the challenge of compounding lightweight,high-strength Ti/Al alloys due to their considerable disparity in properties,Al 6063 as intermediate layer was proposed to fabricate TC4/Al 6063/Al 7075 three-layer ...Because of the challenge of compounding lightweight,high-strength Ti/Al alloys due to their considerable disparity in properties,Al 6063 as intermediate layer was proposed to fabricate TC4/Al 6063/Al 7075 three-layer composite plate by explosive welding.The microscopic properties of each bonding interface were elucidated through field emission scanning electron microscope and electron backscattered diffraction(EBSD).A methodology combining finite element method-smoothed particle hydrodynamics(FEM-SPH)and molecular dynamics(MD)was proposed for the analysis of the forming and evolution characteristics of explosive welding interfaces at multi-scale.The results demonstrate that the bonding interface morphologies of TC4/Al 6063 and Al 6063/Al 7075 exhibit a flat and wavy configuration,without discernible defects or cracks.The phenomenon of grain refinement is observed in the vicinity of the two bonding interfaces.Furthermore,the degree of plastic deformation of TC4 and Al 7075 is more pronounced than that of Al 6063 in the intermediate layer.The interface morphology characteristics obtained by FEM-SPH simulation exhibit a high degree of similarity to the experimental results.MD simulations reveal that the diffusion of interfacial elements predominantly occurs during the unloading phase,and the simulated thickness of interfacial diffusion aligns well with experimental outcomes.The introduction of intermediate layer in the explosive welding process can effectively produce high-quality titanium/aluminum alloy composite plates.Furthermore,this approach offers a multi-scale simulation strategy for the study of explosive welding bonding interfaces.展开更多
Joint Multimodal Aspect-based Sentiment Analysis(JMASA)is a significant task in the research of multimodal fine-grained sentiment analysis,which combines two subtasks:Multimodal Aspect Term Extraction(MATE)and Multimo...Joint Multimodal Aspect-based Sentiment Analysis(JMASA)is a significant task in the research of multimodal fine-grained sentiment analysis,which combines two subtasks:Multimodal Aspect Term Extraction(MATE)and Multimodal Aspect-oriented Sentiment Classification(MASC).Currently,most existing models for JMASA only perform text and image feature encoding from a basic level,but often neglect the in-depth analysis of unimodal intrinsic features,which may lead to the low accuracy of aspect term extraction and the poor ability of sentiment prediction due to the insufficient learning of intra-modal features.Given this problem,we propose a Text-Image Feature Fine-grained Learning(TIFFL)model for JMASA.First,we construct an enhanced adjacency matrix of word dependencies and adopt graph convolutional network to learn the syntactic structure features for text,which addresses the context interference problem of identifying different aspect terms.Then,the adjective-noun pairs extracted from image are introduced to enable the semantic representation of visual features more intuitive,which addresses the ambiguous semantic extraction problem during image feature learning.Thereby,the model performance of aspect term extraction and sentiment polarity prediction can be further optimized and enhanced.Experiments on two Twitter benchmark datasets demonstrate that TIFFL achieves competitive results for JMASA,MATE and MASC,thus validating the effectiveness of our proposed methods.展开更多
Permeable roads generally exhibit inferior mechanical properties and shorter service life than traditional dense-graded/impermeable roads.Furthermore,the incorporation of recycled aggregates in their construction may ...Permeable roads generally exhibit inferior mechanical properties and shorter service life than traditional dense-graded/impermeable roads.Furthermore,the incorporation of recycled aggregates in their construction may exacerbate these limitations.To address these issues,this study introduced a novel cement-stabilized permeable recycled aggregate material.A total of 162 beam specimens prepared with nine different levels of cement-aggregate ratio were tested to evaluate their permeability,bending load,and bending fatigue life.The experimental results indicate that increasing the content of recycled aggregates led to a reduction in both permeability and bending load.Additionally,the inclusion of recycled aggregates diminished the energy dissipation capacity of the specimens.These findings were used to establish a robust relationship between the initial damage in cement-stabilized permeable recycled aggregate material specimens and their fatigue life,and to propose a predictive model for their fatigue performance.Further,a method for assessing fatigue damage based on the evolution of fatigue-induced strain and energy dissipation was developed.The findings of this study provide valuable insights into the mechanical behavior and fatigue performance of cement-stabilized permeable recycled aggregate materials,offering guidance for the design of low-carbon-emission,permeable,and durable roadways incorporating recycled aggregates.展开更多
Background China is seeing a growing demand for rehabilitation treatments for post-stroke upper limb spastic paresis(PSSP-UL).Although acupuncture is known to be effective for PSSP-UL,there is room to enhance its effi...Background China is seeing a growing demand for rehabilitation treatments for post-stroke upper limb spastic paresis(PSSP-UL).Although acupuncture is known to be effective for PSSP-UL,there is room to enhance its efficacy.Objective This study explored a semi-personalized acupuncture approach for PSSP-UL that used three-dimensional kinematic analysis(3DKA)results to select additional acupoints,and investigated the feasibility,efficacy and safety of this approach.Design,setting,participants and interventions This single-blind,single-center,randomized,controlled trial involved 74 participants who experienced a first-ever ischemic or hemorrhagic stroke with spastic upper limb paresis.The participants were then randomly assigned to the intervention group or the control group in a 1:1 ratio.Both groups received conventional treatments and acupuncture treatment 5 days a week for 4 weeks.The main acupoints in both groups were the same,while participants in the intervention group received additional acupoints selected on the basis of 3DKA results.Follow-up assessments were conducted for 8 weeks after the treatment.Main outcome measures The primary outcome was the Fugl-Meyer Assessment for Upper Extremity(FMA-UE)response rate(≥6-point change)at week 4.Secondary outcomes included changes in motor function(FMA-UE),Brunnstrom recovery stage(BRS),manual muscle test(MMT),spasticity(Modified Ashworth Scale,MAS),and activities of daily life(Modified Barthel Index,MBI)at week 4 and week 12.Results Sixty-four participants completed the trial and underwent analyses.Compared with control group,the intervention group exhibited a significantly higher FMA-UE response rate at week 4(χ^(2)=5.479,P=0.019)and greater improvements in FMA-UE at both week 4 and week 12(both P<0.001).The intervention group also showed bigger improvements from baseline in the MMT grades for shoulder adduction and elbow flexion at weeks 4 and 12 as well as thumb adduction at week 4(P=0.007,P=0.049,P=0.019,P=0.008,P=0.029,respectively).The intervention group showed a better change in the MBI at both week 4 and week 12(P=0.004 and P=0.010,respectively).Although the intervention group had a higher BRS for the hand at week 12(P=0.041),no intergroup differences were observed at week 4(all P>0.05).The two groups showed no differences in MAS grades as well as in BRS for the arm at weeks 4 and 12(all P>0.05).Conclusion Semi-personalized acupuncture prescription based on 3DKA results significantly improved motor function,muscle strength,and activities of daily living in patients with PSSP-UL.展开更多
Advanced geological prediction is a crucial means to ensure safety and efficiency in tunnel construction.However,diff erent advanced geological forecasting methods have their own limitations,resulting in poor detectio...Advanced geological prediction is a crucial means to ensure safety and efficiency in tunnel construction.However,diff erent advanced geological forecasting methods have their own limitations,resulting in poor detection accuracy.Using multiple methods to carry out a comprehensive evaluation can eff ectively improve the accuracy of advanced geological prediction results.In this study,geological information is combined with the detection results of geophysical methods,including transient electromagnetic,induced polarization,and tunnel seismic prediction,to establish a comprehensive analysis method of adverse geology.First,the possible main adverse geological problems are determined according to the geological information.Subsequently,various physical parameters of the rock mass in front of the tunnel face can then be derived on the basis of multisource geophysical data.Finally,based on the analysis results of geological information,the multisource data fusion algorithm is used to determine the type,location,and scale of adverse geology.The advanced geological prediction results that can provide eff ective guidance for tunnel construction can then be obtained.展开更多
Maintaining the integrity and longevity of structures is essential in many industries,such as aerospace,nuclear,and petroleum.To achieve the cost-effectiveness of large-scale systems in petroleum drilling,a strong emp...Maintaining the integrity and longevity of structures is essential in many industries,such as aerospace,nuclear,and petroleum.To achieve the cost-effectiveness of large-scale systems in petroleum drilling,a strong emphasis on structural durability and monitoring is required.This study focuses on the mechanical vibrations that occur in rotary drilling systems,which have a substantial impact on the structural integrity of drilling equipment.The study specifically investigates axial,torsional,and lateral vibrations,which might lead to negative consequences such as bit-bounce,chaotic whirling,and high-frequency stick-slip.These events not only hinder the efficiency of drilling but also lead to exhaustion and harm to the system’s components since they are difficult to be detected and controlled in real time.The study investigates the dynamic interactions of these vibrations,specifically in their high-frequency modes,usingfield data obtained from measurement while drilling.Thefindings have demonstrated the effect of strong coupling between the high-frequency modes of these vibrations on drilling sys-tem performance.The obtained results highlight the importance of considering the interconnected impacts of these vibrations when designing and implementing robust control systems.Therefore,integrating these compo-nents can increase the durability of drill bits and drill strings,as well as improve the ability to monitor and detect damage.Moreover,by exploiting thesefindings,the assessment of structural resilience in rotary drilling systems can be enhanced.Furthermore,the study demonstrates the capacity of structural health monitoring to improve the quality,dependability,and efficiency of rotary drilling systems in the petroleum industry.展开更多
The investigations of physical attributes of oceans,including parameters such as heat flow and bathymetry,have garnered substantial attention and are particularly valuable for examining Earth’s thermal structures and...The investigations of physical attributes of oceans,including parameters such as heat flow and bathymetry,have garnered substantial attention and are particularly valuable for examining Earth’s thermal structures and dynamic processes.Nevertheless,classical plate cooling models exhibit disparities when predicting observed heat flow and seafloor depth for extremely young and old lithospheres.Furthermore,a comprehensive analysis of global heat flow predictions and regional ocean heat flow or bathymetry data with physical models has been lacking.In this study,we employed power-law models derived from the singularity theory of fractal density to meticulously fit the latest ocean heat flow and bathymetry.Notably,power-law models offer distinct advantages over traditional plate cooling models,showcasing robust self-similarity,scale invariance,or scaling properties,and providing a better fit to observed data.The outcomes of our singularity analysis concerning heat flow and bathymetry across diverse oceanic regions exhibit a degree of consistency with the global ocean spreading rate model.In addition,we applied the similarity method to predict a higher resolution(0.1°×0.1°)global heat flow map based on the most recent heat flow data and geological/geophysical observables refined through linear correlation analysis.Regions displaying significant disparities between predicted and observed heat flow are closely linked to hydrothermal vent fields and active structures.Finally,combining the actual bathymetry and predicted heat flow with the power-law models allows for the quantitative and comprehensive detection of anomalous regions of ocean subsidence and heat flow,which deviate from traditional plate cooling models.The anomalous regions of subsidence and heat flow show different degrees of anisotropy,providing new ideas and clues for further analysis of ocean topography or hydrothermal circulation of mid-ocean ridges.展开更多
Wax gourd(Benincasa hispida)is an important cucurbit crop with economic and medicinal value.The myeloblastosis(MYB)gene family is one of the largest gene families in plants and regulates various biological processes,w...Wax gourd(Benincasa hispida)is an important cucurbit crop with economic and medicinal value.The myeloblastosis(MYB)gene family is one of the largest gene families in plants and regulates various biological processes,whereas the MYB gene family has not been systematically studied in wax gourd.In this study,we performed genome-wide identification of the MYB gene family in wax gourd and analyzed their phylogenetic relationship,MYB DNA-binding domain(MYB DBD),gene structure,protein motif,synteny,duplication mode and expression pattern.As a result,a total of 215 BhMYB genes(BhMYBs)were identified,belonging to four subfamilies:1R-,2R-,3R-and 4R-MYB subfamilies.Genes of 1R-MYB subfamily and 2R-MYB subfamily were subdivided into different subgroups respectively.The analysis of MYB DBD,gene structure and protein motif showed that the most genes in the same subgroup had similar characteristics and the 2R-MYB genes were more conserved than the 1R-MYB genes.Interestingly,the long terminal retrotransposons(LTR-RTs)were found in the long introns of several BhMYBs.The results of synteny analysis showed that there were more syntenic gene pairs between wax gourd and other cucurbit crops,while the least number of syntenic gene pairs existed between wax gourd and rice.Gene duplication was the main reason for the expansion of the MYB gene family in wax gourd,with the transposed duplication(TRD)mode contributing more.All duplication BhMYB genes were under purifying selection pressure.Further expression analysis showed that many BhMYBs exhibited obvious tissue-specific expression and several BhMYBs were significantly induced by one or more abiotic stresses.BhMYB79 was particularly expressed in roots and significantly induced by salt,drought,cold and heat stresses,overexpression of which led to reduced tolerance to salt stress in Arabidopsis.In conclusion,our results provide a systematic analysis of wax gourd MYB gene family and facilitate the biological role study of BhMYB79 during wax gourd salt stress response process.展开更多
Objective:To investigate mutations in the Chikungunya(CHIKV)envelope genome region and evaluate their potential impact on B lymphocyte epitopes via in silico analysis.Methods:E1,E2 and 6K protein genes were sequenced ...Objective:To investigate mutations in the Chikungunya(CHIKV)envelope genome region and evaluate their potential impact on B lymphocyte epitopes via in silico analysis.Methods:E1,E2 and 6K protein genes were sequenced from viral RNA isolated from 13 CHIKV-positive serum samples from Alagoas State,Brazil,during the 2016 outbreak.Phylogenetic analysis,experimental epitope identification in the immune epitope database(IEDB)and in silico approaches were employed to predict the potential impact of the detected mutations.Results:The sequences were clustered via phylogenetic analysis.The CHIKV isolates belong to the ECSA genotype,with 13 detected amino acid mutations.Five mutations are located on the surface of the viral particle in regions critical for cellular receptor interaction.Nine mutations are known experimentally validated epitopes for B and T cells.In B-cell epitope predictions,mutations affect sequences within three conformational epitopes in E2 and one in E1,as well as linear epitopes.Notably,the E2-G60D mutation found in the Alagoas strain has been previously reported to influence the vector competence of Aedes aegypti,the primary vector in Brazil.Conclusions:Genomic surveillance and an in-depth understanding of viral mutations are crucial for adapting public health strategies and improving the outbreak response.These findings could have significant public health implications,such as the development of more effective vaccines,diagnostic tests,and antiviral therapies.展开更多
The efficient market hypothesis in traditional financial theory struggles to explain the short-term irrational fluctuations in the A-share market,where investor sentiment fluctuations often serve as the core driver of...The efficient market hypothesis in traditional financial theory struggles to explain the short-term irrational fluctuations in the A-share market,where investor sentiment fluctuations often serve as the core driver of abnormal stock price movements.Traditional sentiment measurement methods suffer from limitations such as lag,high misjudgment rates,and the inability to distinguish confounding factors.To more accurately explore the dynamic correlation between investor sentiment and stock price fluctuations,this paper proposes a sentiment analysis framework based on large language models(LLMs).By constructing continuous sentiment scoring factors and integrating them with a long short-term memory(LSTM)deep learning model,we analyze the correlation between investor sentiment and stock price fluctuations.Empirical results indicate that sentiment factors based on large language models can generate an annualized excess return of 9.3%in the CSI 500 index domain.The LSTM stock price prediction model incorporating sentiment features achieves a mean absolute percentage error(MAPE)as low as 2.72%,significantly outperforming traditional models.Through this analysis,we aim to provide quantitative references for optimizing investment decisions and preventing market risks.展开更多
As a mathematical analysis method,fractal analysis can be used to quantitatively describe irregular shapes with self-similar or self-affine properties.Fractal analysis has been used to characterize the shapes of metal...As a mathematical analysis method,fractal analysis can be used to quantitatively describe irregular shapes with self-similar or self-affine properties.Fractal analysis has been used to characterize the shapes of metal materials at various scales and dimensions.Conventional methods make it difficult to quantitatively describe the relationship between the regular characteristics and properties of metal material surfaces and interfaces.However,fractal analysis can be used to quantitatively describe the shape characteristics of metal materials and to establish the quantitative relationships between the shape characteristics and various properties of metal materials.From the perspective of two-dimensional planes and three-dimensional curved surfaces,this paper reviews the current research status of the fractal analysis of metal precipitate interfaces,metal grain boundary interfaces,metal-deposited film surfaces,metal fracture surfaces,metal machined surfaces,and metal wear surfaces.The relationship between the fractal dimensions and properties of metal material surfaces and interfaces is summarized.Starting from three perspectives of fractal analysis,namely,research scope,image acquisition methods,and calculation methods,this paper identifies the direction of research on fractal analysis of metal material surfaces and interfaces that need to be developed.It is believed that revealing the deep influence mechanism between the fractal dimensions and properties of metal material surfaces and interfaces will be the key research direction of the fractal analysis of metal materials in the future.展开更多
文摘Purpose–The deformation of the roadbed is easily influenced by the external environment to improve the accuracy of high-speed railway subgrade settlement prediction.Design/methodology/approach–A high-speed railway subgrade settlement interval prediction method using the secretary bird optimization(SBOA)algorithm to optimize the BP neural network under the premise of gray relational analysis is proposed.Findings–Using the SBOA algorithm to optimize the BP neural network,the optimal weights and thresholds are obtained,and the best parameter prediction model is combined.The data were collected from the sensors deployed through the subgrade settlement monitoring system,and the gray relational analysis is used to verify that all four influencing factors had a great correlation to the subgrade settlement,and the collected data are verified using the model.Originality/value–The experimental results show that the SBOA-BP model has higher prediction accuracy than the BP model,and the SBOA-BP model has a wider range of prediction intervals for a given confidence level,which can provide higher guiding value for practical engineering applications.
文摘In this study,a machine learning-based predictive model was developed for the Musa petti Wind Farm in Sri Lanka to address the need for localized forecasting solutions.Using data on wind speed,air temperature,nacelle position,and actual power,lagged features were generated to capture temporal dependencies.Among 24 evaluated models,the ensemble bagging approach achieved the best performance,with R^(2) values of 0.89 at 0 min and 0.75 at 60 min.Shapley Additive exPlanations(SHAP)analysis revealed that while wind speed is the primary driver for short-term predictions,air temperature and nacelle position become more influential at longer forecasting horizons.These findings underscore the reliability of short-term predictions and the potential benefits of integrating hybrid AI and probabilistic models for extended forecasts.Our work contributes a robust and explainable framework to support Sri Lanka’s renewable energy transition,and future research will focus on real-time deployment and uncertainty quantification.
文摘BACKGROUND Colorectal cancer(CRC)remains one of the leading causes of cancer-related morbidity and mortality worldwide.Growing evidence suggests that gut microbial dysbiosis plays a crucial role in tumorigenesis and can influence therapeutic responses.AIM To explore the associations between serum S100A12 and soluble CD14(sCD14)levels and gut microbiota alterations in patients with CRC,and to assess the predictive utility of these biomarkers in forecasting chemotherapy response.METHODS A retrospective analysis was conducted on 104 patients diagnosed with advanced CRC(CRC group)and 104 age-matched and sex-matched healthy controls.Serum concentrations of S100A12 and sCD14 were measured using enzyme-linked immunosorbent assay.Fecal samples collected before chemotherapy were subjected to 16S rRNA sequencing to profile gut microbial composition.Pearson correlation analysis was used to evaluate the relationship between biomarker levels and microbial abundance.Receiver operating characteristic(ROC)curves were used to assess the predictive performance of S100A12 and sCD14 for chemotherapy response.RESULTS CRC patients exhibited significantly higher serum levels of S100A12 and sCD14 compared to healthy individuals(P<0.05).Patients with moderate to severe gut dysbiosis showed the highest elevations of these biomarkers(P<0.05).Elevated levels of S100A12 and sCD14 were positively correlated with Fusobacterium nucleatum and Prevotella abundance,and negatively correlated with Faecalibacterium prausnitzii and Akkermansia muciniphila(P<0.05).Both biomarkers significantly decreased following chemotherapy(P<0.05).Non-responders to chemotherapy had higher pre-treatment levels of S100A12 and sCD14 compared to responders(P<0.05).Combined ROC analysis showed improved diagnostic accuracy compared to either marker alone.CONCLUSION Serum S100A12 and sCD14 levels are closely associated with gut microbiota imbalance and chemotherapy response in CRC patients.These markers may serve as promising predictive indicators for treatment efficacy and offer potential value in individualized treatment strategies.
基金supported by the National Key Research and Development Program of China(Grant Nos.2023YFC3707900 and 2024YFC3012700)the National Natural Science Foundation of China(Grant No.42230710).
文摘Soil desiccation cracking is ubiquitous in nature and has significantpotential impacts on the engineering geological properties of soils.Previous studies have extensively examined various factors affecting soil cracking behavior through a numerous small-sample experiments.However,experimental studies alone cannot accurately describe soil cracking behavior.In this study,we firstly propose a modeling framework for predicting the surface crack ratio of soil desiccation cracking based on machine learning and interpretable analysis.The framework utilizes 1040 sets of soil cracking experimental data and employs random forest(RF),extreme gradient boosting(XGBoost),and artificialneural network(ANN)models to predict the surface crack ratio of soil desiccation cracking.To clarify the influenceof input features on soil cracking behavior,feature importance and Shapley additive explanations(SHAP)are applied for interpretability analysis.The results reveal that ensemble methods(RF and XGBoost)provide better predictive performance than the deep learning model(ANN).The feature importance analysis shows that soil desiccation cracking is primarily influencedby initial water content,plasticity index,finalwater content,liquid limit,sand content,clay content and thickness.Moreover,SHAP-based interpretability analysis further explores how soil cracking responds to various input variables.This study provides new insight into the evolution of soil cracking behavior,enhancing the understanding of its physical mechanisms and facilitating the assessment of potential regional development of soil desiccation cracking.
基金financially supported by the National Natural Science Foundation of China(No.52174297).
文摘The endpoint carbon content in the converter is critical for the quality of steel products,and accurately predicting this parameter is an effective way to reduce alloy consumption and improve smelting efficiency.However,most scholars currently focus on modifying methods to enhance model accuracy,while overlooking the extent to which input parameters influence accuracy.To address this issue,in this study,a prediction model for the endpoint carbon content in the converter was developed using factor analysis(FA)and support vector machine(SVM)optimized by improved particle swarm optimization(IPSO).Analysis of the factors influencing the endpoint carbon content during the converter smelting process led to the identification of 21 input parameters.Subsequently,FA was used to reduce the dimensionality of the data and applied to the prediction model.The results demonstrate that the performance of the FA-IPSO-SVM model surpasses several existing methods,such as twin support vector regression and support vector machine.The model achieves hit rates of 89.59%,96.21%,and 98.74%within error ranges of±0.01%,±0.015%,and±0.02%,respectively.Finally,based on the prediction results obtained by sequentially removing input parameters,the parameters were classified into high influence(5%-7%),medium influence(2%-5%),and low influence(0-2%)categories according to their varying degrees of impact on prediction accuracy.This classi-fication provides a reference for selecting input parameters in future prediction models for endpoint carbon content.
基金National Natural Science Foundation of China(U22A20377)Natural Science Foundation of Hunan Province of China(23C0168).
文摘Objective To explore the clinical characteristics and methods for syndrome differentiation prediction,as well as to construct a predictive model for Qi deficiency and blood stasis syndrome in patients with acute ischemic stroke(AIS).Methods This study employed a retrospective case-control design to analyze patients with AIS who received inpatient treatment at the Neurology Department of The First Hospital of Hunan University of Chinese Medicine from January 1,2013 to December 31,2022.AIS patients meeting the diagnostic criteria for Qi deficiency and blood stasis syndrome were stratified into case group,while those without Qi deficiency and blood stasis syndrome were stratified into control group.The demographic characteristics(age and gender),clinical parameters[time from onset to admission,National Institutes of Health Stroke Scale(NIHSS)score,and blood pressure],past medical history,traditional Chinese medicine(TCM)diagnostic characteristics(tongue and pulse),neurological symptoms and signs,imaging findings[magnetic resonance imaging-diffusion weighted imaging(MRI-DWI)],and biochemical indicators of the two groups were collected and compared.The indicators with statistical difference(P<0.05)in univariate analysis were included in multivariate logistic regression analysis to evaluate their predictive value for the diagnosis of Qi deficiency and blood stasis syndrome,and the predictive model was constructed by receiver operating characteristic(ROC)curve analysis.Results The study included 1035 AIS patients,with 404 cases in case group and 631 cases in control group.Compared with control group,patients in case group were significantly older,had extended onset-to-admission time,lower diastolic blood pressure,and lower NIHSS scores(P<0.05).Case group showed lower incidence of hypertension history(P<0.05).Regarding tongue and pulse characteristics,pale and dark tongue colors,white tongue coating,fine pulse,astringent pulse,and sinking pulse were more common in case group.Imaging examinations demonstrated higher proportions of centrum semiovale infarction,cerebral atrophy,and vertebral artery stenosis in case group(P<0.05).Among biochemical indicators,case group showed higher proportions of elevated fasting blood glucose and glycated hemoglobin(HbA1c),while lower proportions of elevated white blood cell count,reduced hemoglobin,and reduced high-density lipoprotein cholesterol(HDL-C)(P<0.05).Multivariate logistic regression analysis identified significant predictors for Qi deficiency and blood stasis syndrome including:fine pulse[odds ratio(OR)=4.38],astringent pulse(OR=3.67),superficial sensory abnormalities(OR=1.86),centrum semiovale infarction(OR=1.57),cerebral atrophy(OR=1.55),vertebral artery stenosis(OR=1.62),and elevated HbA1c(OR=3.52).The ROC curve analysis of the comprehensive prediction model yielded an area under the curve(AUC)of 0.878[95%confidence interval(CI)=0.855-0.900].Conclusion This study finds out that Qi deficiency and blood stasis syndrome represents one of the primary types of AIS.Fine pulse,astringent pulse,superficial sensory abnormalities,centrum semiovale infarction,cerebral atrophy,vertebral artery stenosis,elevated blood glucose,elevated HbA1c,pale and dark tongue colors,and white tongue coating are key objective diagnostic indicators for the syndrome differentiation of AIS with Qi deficiency and blood stasis syndrome.Based on these indicators,a syndrome differentiation prediction model has been developed,offering a more objective basis for clinical diagnosis,and help to rapidly identify this syndrome in clinical practice and reduce misdiagnosis and missed diagnosis.
基金supported by grants from the National Natural Science Foundation of China(Grant No.31960585)Science and Technology Major Project of Guangxi(Grant No.Guike AA22068092)+1 种基金Guangxi Science and Technology Vanguard Special Action Project(Grant No.202204)State Key Laboratory for Conservation and Utilization of Subtropical Agro-bioresources(Grant Nos.SKLCUSA-a201906,SKLCU-SA-c201901)。
文摘The SKP1 gene is an important component of the SCF(SKP1-Cullin1-F-box)complex and serves as a bridge connecting the F-box and Cullin1genes(F-box-SKP1-Cullin1).The pattern of S-RNase being ubiquitously labelled by the SCF complex and degraded by the 26S protease accounts for the bulk of the available self-incompatibility studies.In this study,15 ClSKP1s from the‘Xiangshui'lemon genome and ubiquitome exist in the same SKP1 conserved domain(CD)as SKP1s in other species.The q PCR results showed that SKP1-6 and SKP1-14 have tissue expression patterns specific for expression in pollen.In addition,SKP1-6 and SKP1-14 in the stigma,style and ovary were significantly upregulated after self-pollination compared to those after cross-pollination.A subcellular location showed that SKP1-6 and SKP1-14 were located in the nucleus.In addition,yeast two-hybrid(Y2H)assays,bimolecular fluorescence complementation(BiFC)and luciferase complementation imaging(LCI)assays showed that SKP1-6 interacted with F-box1,F-box33,F-box34,F-box17,F-box19,Cullin1-2 and 26S proteasome subunit 4 homolog A(26S PS4HA).SKP1-14 interacted with F-box17,F-box19,F-box35,Cullin1-2 and 26S PS4HA.The interaction of Cullin1-2 and the F-box with SKP1 as a bridge was verified by a yeast three-hybrid experiment.The ability of S3-RNase to inhibit pollen and pollen tube growth and development was assessed using in vitro pollen co-culture experiments with recombinant S3-RNase proteins.Overall,this study provides important experimental evidence and theoretical basis for understanding the mechanism of self-incompatibility in plants by revealing the key role of the SCF complex in‘Xiangshui'lemon,which is bridged by ClSKP1-6,in self-incompatibility.The results of this study are of great significance for the future indepth exploration of the molecular mechanism of the SCF complex and its wide application in the self-incompatibility of plants.
基金supported by grants from the Natural Science Foundation of Tianjin(General Program),Nos.23JCYBJC01390(to RL),22JCYBJC00220(to XC),and 22JCYBJC00210(to QL).
文摘Peripheral nerve injury is a common neurological condition that often leads to severe functional limitations and disabilities.Research on the pathogenesis of peripheral nerve injury has focused on pathological changes at individual injury sites,neglecting multilevel pathological analysis of the overall nervous system and target organs.This has led to restrictions on current therapeutic approaches.In this paper,we first summarize the potential mechanisms of peripheral nerve injury from a holistic perspective,covering the central nervous system,peripheral nervous system,and target organs.After peripheral nerve injury,the cortical plasticity of the brain is altered due to damage to and regeneration of peripheral nerves;changes such as neuronal apoptosis and axonal demyelination occur in the spinal cord.The nerve will undergo axonal regeneration,activation of Schwann cells,inflammatory response,and vascular system regeneration at the injury site.Corresponding damage to target organs can occur,including skeletal muscle atrophy and sensory receptor disruption.We then provide a brief review of the research advances in therapeutic approaches to peripheral nerve injury.The main current treatments are conducted passively and include physical factor rehabilitation,pharmacological treatments,cell-based therapies,and physical exercise.However,most treatments only partially address the problem and cannot complete the systematic recovery of the entire central nervous system-peripheral nervous system-target organ pathway.Therefore,we should further explore multilevel treatment options that produce effective,long-lasting results,perhaps requiring a combination of passive(traditional)and active(novel)treatment methods to stimulate rehabilitation at the central-peripheral-target organ levels to achieve better functional recovery.
基金supported by the National Natural Science Foundation of China(Grant Nos.42250103 and 42174090)the Opening Fund of Key Laboratory of Geological Survey and Evaluation of Ministry of Education(Grant No.GLAB2023ZR02)the Ministry of Science and Technology(MOST)Special Fund from the State Key Laboratory of Geological Processes and Mineral Resources(Grant No.MSFGPMR2022-4)。
文摘As a means of quantitative interpretation,forward calculations of the global lithospheric magnetic field in the Spherical Harmonic(SH)domain have been widely used to reveal geophysical,lithological,and geothermal variations in the lithosphere.Traditional approaches either do not consider the non-axial dipolar terms of the inducing field and its radial variation or do so by means of complicated formulae.Moreover,existing methods treat the magnetic lithosphere either as an infinitesimally thin layer or as a radially uniform spherical shell of constant thickness.Here,we present alternative forward formulae that account for an arbitrarily high maximum degree of the inducing field and for a magnetic lithosphere of variable thickness.Our simulations based on these formulae suggest that the satellite magnetic anomaly field is sensitive to the non-axial dipolar terms of the inducing field but not to its radial variation.Therefore,in forward and inverse calculations of satellite magnetic anomaly data,the non-axial dipolar terms of the inducing field should not be ignored.Furthermore,our results show that the satellite magnetic anomaly field is sensitive to variability in the lateral thickness of the magnetized shell.In particular,we show that for a given vertically integrated susceptibility distribution,underestimating the thickness of the magnetic layer overestimates the induced magnetic field.This discovery bridges the greatest part of the alleged gap between the susceptibility values measured from rock samples and the susceptibility values required to match the observed magnetic field signal.We expect the formulae and conclusions of this study to be a valuable tool for the quantitative interpretation of the Earth's global lithospheric magnetic field,through an inverse or forward modelling approach.
基金Opening Foundation of Key Laboratory of Explosive Energy Utilization and Control,Anhui Province(BP20240104)Graduate Innovation Program of China University of Mining and Technology(2024WLJCRCZL049)Postgraduate Research&Practice Innovation Program of Jiangsu Province(KYCX24_2701)。
文摘Because of the challenge of compounding lightweight,high-strength Ti/Al alloys due to their considerable disparity in properties,Al 6063 as intermediate layer was proposed to fabricate TC4/Al 6063/Al 7075 three-layer composite plate by explosive welding.The microscopic properties of each bonding interface were elucidated through field emission scanning electron microscope and electron backscattered diffraction(EBSD).A methodology combining finite element method-smoothed particle hydrodynamics(FEM-SPH)and molecular dynamics(MD)was proposed for the analysis of the forming and evolution characteristics of explosive welding interfaces at multi-scale.The results demonstrate that the bonding interface morphologies of TC4/Al 6063 and Al 6063/Al 7075 exhibit a flat and wavy configuration,without discernible defects or cracks.The phenomenon of grain refinement is observed in the vicinity of the two bonding interfaces.Furthermore,the degree of plastic deformation of TC4 and Al 7075 is more pronounced than that of Al 6063 in the intermediate layer.The interface morphology characteristics obtained by FEM-SPH simulation exhibit a high degree of similarity to the experimental results.MD simulations reveal that the diffusion of interfacial elements predominantly occurs during the unloading phase,and the simulated thickness of interfacial diffusion aligns well with experimental outcomes.The introduction of intermediate layer in the explosive welding process can effectively produce high-quality titanium/aluminum alloy composite plates.Furthermore,this approach offers a multi-scale simulation strategy for the study of explosive welding bonding interfaces.
基金supported by the Science and Technology Project of Henan Province(No.222102210081).
文摘Joint Multimodal Aspect-based Sentiment Analysis(JMASA)is a significant task in the research of multimodal fine-grained sentiment analysis,which combines two subtasks:Multimodal Aspect Term Extraction(MATE)and Multimodal Aspect-oriented Sentiment Classification(MASC).Currently,most existing models for JMASA only perform text and image feature encoding from a basic level,but often neglect the in-depth analysis of unimodal intrinsic features,which may lead to the low accuracy of aspect term extraction and the poor ability of sentiment prediction due to the insufficient learning of intra-modal features.Given this problem,we propose a Text-Image Feature Fine-grained Learning(TIFFL)model for JMASA.First,we construct an enhanced adjacency matrix of word dependencies and adopt graph convolutional network to learn the syntactic structure features for text,which addresses the context interference problem of identifying different aspect terms.Then,the adjective-noun pairs extracted from image are introduced to enable the semantic representation of visual features more intuitive,which addresses the ambiguous semantic extraction problem during image feature learning.Thereby,the model performance of aspect term extraction and sentiment polarity prediction can be further optimized and enhanced.Experiments on two Twitter benchmark datasets demonstrate that TIFFL achieves competitive results for JMASA,MATE and MASC,thus validating the effectiveness of our proposed methods.
基金Project(2024JJ2073)supported by the Science Fund for Distinguished Young Scholars of Hunan Province,ChinaProjects(2023YFC3807205,2019YFC1904704)+4 种基金supported by the National Key R&D Program of ChinaProject(52178443)supported by the National Natural Science Foundation of ChinaProject(2024ZZTS0109)supported by Fundamental Research Funds for the Central Universities of Central South University,China。
文摘Permeable roads generally exhibit inferior mechanical properties and shorter service life than traditional dense-graded/impermeable roads.Furthermore,the incorporation of recycled aggregates in their construction may exacerbate these limitations.To address these issues,this study introduced a novel cement-stabilized permeable recycled aggregate material.A total of 162 beam specimens prepared with nine different levels of cement-aggregate ratio were tested to evaluate their permeability,bending load,and bending fatigue life.The experimental results indicate that increasing the content of recycled aggregates led to a reduction in both permeability and bending load.Additionally,the inclusion of recycled aggregates diminished the energy dissipation capacity of the specimens.These findings were used to establish a robust relationship between the initial damage in cement-stabilized permeable recycled aggregate material specimens and their fatigue life,and to propose a predictive model for their fatigue performance.Further,a method for assessing fatigue damage based on the evolution of fatigue-induced strain and energy dissipation was developed.The findings of this study provide valuable insights into the mechanical behavior and fatigue performance of cement-stabilized permeable recycled aggregate materials,offering guidance for the design of low-carbon-emission,permeable,and durable roadways incorporating recycled aggregates.
基金funded by Science Foundation for Youth supported by Shanghai Municipal Health Commission(No.20204Y0313)Sailing Program with the support of Science and Technology Commission of Shanghai Municipality(No.21YF1443800).
文摘Background China is seeing a growing demand for rehabilitation treatments for post-stroke upper limb spastic paresis(PSSP-UL).Although acupuncture is known to be effective for PSSP-UL,there is room to enhance its efficacy.Objective This study explored a semi-personalized acupuncture approach for PSSP-UL that used three-dimensional kinematic analysis(3DKA)results to select additional acupoints,and investigated the feasibility,efficacy and safety of this approach.Design,setting,participants and interventions This single-blind,single-center,randomized,controlled trial involved 74 participants who experienced a first-ever ischemic or hemorrhagic stroke with spastic upper limb paresis.The participants were then randomly assigned to the intervention group or the control group in a 1:1 ratio.Both groups received conventional treatments and acupuncture treatment 5 days a week for 4 weeks.The main acupoints in both groups were the same,while participants in the intervention group received additional acupoints selected on the basis of 3DKA results.Follow-up assessments were conducted for 8 weeks after the treatment.Main outcome measures The primary outcome was the Fugl-Meyer Assessment for Upper Extremity(FMA-UE)response rate(≥6-point change)at week 4.Secondary outcomes included changes in motor function(FMA-UE),Brunnstrom recovery stage(BRS),manual muscle test(MMT),spasticity(Modified Ashworth Scale,MAS),and activities of daily life(Modified Barthel Index,MBI)at week 4 and week 12.Results Sixty-four participants completed the trial and underwent analyses.Compared with control group,the intervention group exhibited a significantly higher FMA-UE response rate at week 4(χ^(2)=5.479,P=0.019)and greater improvements in FMA-UE at both week 4 and week 12(both P<0.001).The intervention group also showed bigger improvements from baseline in the MMT grades for shoulder adduction and elbow flexion at weeks 4 and 12 as well as thumb adduction at week 4(P=0.007,P=0.049,P=0.019,P=0.008,P=0.029,respectively).The intervention group showed a better change in the MBI at both week 4 and week 12(P=0.004 and P=0.010,respectively).Although the intervention group had a higher BRS for the hand at week 12(P=0.041),no intergroup differences were observed at week 4(all P>0.05).The two groups showed no differences in MAS grades as well as in BRS for the arm at weeks 4 and 12(all P>0.05).Conclusion Semi-personalized acupuncture prescription based on 3DKA results significantly improved motor function,muscle strength,and activities of daily living in patients with PSSP-UL.
基金National Natural Science Foundation of China(grant numbers 42293351,41877239,51422904 and 51379112).
文摘Advanced geological prediction is a crucial means to ensure safety and efficiency in tunnel construction.However,diff erent advanced geological forecasting methods have their own limitations,resulting in poor detection accuracy.Using multiple methods to carry out a comprehensive evaluation can eff ectively improve the accuracy of advanced geological prediction results.In this study,geological information is combined with the detection results of geophysical methods,including transient electromagnetic,induced polarization,and tunnel seismic prediction,to establish a comprehensive analysis method of adverse geology.First,the possible main adverse geological problems are determined according to the geological information.Subsequently,various physical parameters of the rock mass in front of the tunnel face can then be derived on the basis of multisource geophysical data.Finally,based on the analysis results of geological information,the multisource data fusion algorithm is used to determine the type,location,and scale of adverse geology.The advanced geological prediction results that can provide eff ective guidance for tunnel construction can then be obtained.
文摘Maintaining the integrity and longevity of structures is essential in many industries,such as aerospace,nuclear,and petroleum.To achieve the cost-effectiveness of large-scale systems in petroleum drilling,a strong emphasis on structural durability and monitoring is required.This study focuses on the mechanical vibrations that occur in rotary drilling systems,which have a substantial impact on the structural integrity of drilling equipment.The study specifically investigates axial,torsional,and lateral vibrations,which might lead to negative consequences such as bit-bounce,chaotic whirling,and high-frequency stick-slip.These events not only hinder the efficiency of drilling but also lead to exhaustion and harm to the system’s components since they are difficult to be detected and controlled in real time.The study investigates the dynamic interactions of these vibrations,specifically in their high-frequency modes,usingfield data obtained from measurement while drilling.Thefindings have demonstrated the effect of strong coupling between the high-frequency modes of these vibrations on drilling sys-tem performance.The obtained results highlight the importance of considering the interconnected impacts of these vibrations when designing and implementing robust control systems.Therefore,integrating these compo-nents can increase the durability of drill bits and drill strings,as well as improve the ability to monitor and detect damage.Moreover,by exploiting thesefindings,the assessment of structural resilience in rotary drilling systems can be enhanced.Furthermore,the study demonstrates the capacity of structural health monitoring to improve the quality,dependability,and efficiency of rotary drilling systems in the petroleum industry.
基金supported by the Guangdong Province Introduced Innovative R&D Team of Big Data-Mathematical Earth Sciences and Extreme Geological Events Team(grant number 2021ZT09H399)the National Natural Science Foundation of China(grant number 42430111,42050103).
文摘The investigations of physical attributes of oceans,including parameters such as heat flow and bathymetry,have garnered substantial attention and are particularly valuable for examining Earth’s thermal structures and dynamic processes.Nevertheless,classical plate cooling models exhibit disparities when predicting observed heat flow and seafloor depth for extremely young and old lithospheres.Furthermore,a comprehensive analysis of global heat flow predictions and regional ocean heat flow or bathymetry data with physical models has been lacking.In this study,we employed power-law models derived from the singularity theory of fractal density to meticulously fit the latest ocean heat flow and bathymetry.Notably,power-law models offer distinct advantages over traditional plate cooling models,showcasing robust self-similarity,scale invariance,or scaling properties,and providing a better fit to observed data.The outcomes of our singularity analysis concerning heat flow and bathymetry across diverse oceanic regions exhibit a degree of consistency with the global ocean spreading rate model.In addition,we applied the similarity method to predict a higher resolution(0.1°×0.1°)global heat flow map based on the most recent heat flow data and geological/geophysical observables refined through linear correlation analysis.Regions displaying significant disparities between predicted and observed heat flow are closely linked to hydrothermal vent fields and active structures.Finally,combining the actual bathymetry and predicted heat flow with the power-law models allows for the quantitative and comprehensive detection of anomalous regions of ocean subsidence and heat flow,which deviate from traditional plate cooling models.The anomalous regions of subsidence and heat flow show different degrees of anisotropy,providing new ideas and clues for further analysis of ocean topography or hydrothermal circulation of mid-ocean ridges.
基金supported by the Key-Area Research and Development Program of Guangdong Province(Grant No.2020B020220003)National Natural Science Foundation of China(32202504)+2 种基金Guangdong Basic and Applied Basic Research Foundation(Grant No.2023A1515030049)Guangdong Rural Revitalization Strategy Special Project(Grant No.2023-NJS-00-003)Special fund for scientific and technological talents introduction of Guangdong Academy of Agricultural Sciences(Grant No.R2021YJ-YB2004)。
文摘Wax gourd(Benincasa hispida)is an important cucurbit crop with economic and medicinal value.The myeloblastosis(MYB)gene family is one of the largest gene families in plants and regulates various biological processes,whereas the MYB gene family has not been systematically studied in wax gourd.In this study,we performed genome-wide identification of the MYB gene family in wax gourd and analyzed their phylogenetic relationship,MYB DNA-binding domain(MYB DBD),gene structure,protein motif,synteny,duplication mode and expression pattern.As a result,a total of 215 BhMYB genes(BhMYBs)were identified,belonging to four subfamilies:1R-,2R-,3R-and 4R-MYB subfamilies.Genes of 1R-MYB subfamily and 2R-MYB subfamily were subdivided into different subgroups respectively.The analysis of MYB DBD,gene structure and protein motif showed that the most genes in the same subgroup had similar characteristics and the 2R-MYB genes were more conserved than the 1R-MYB genes.Interestingly,the long terminal retrotransposons(LTR-RTs)were found in the long introns of several BhMYBs.The results of synteny analysis showed that there were more syntenic gene pairs between wax gourd and other cucurbit crops,while the least number of syntenic gene pairs existed between wax gourd and rice.Gene duplication was the main reason for the expansion of the MYB gene family in wax gourd,with the transposed duplication(TRD)mode contributing more.All duplication BhMYB genes were under purifying selection pressure.Further expression analysis showed that many BhMYBs exhibited obvious tissue-specific expression and several BhMYBs were significantly induced by one or more abiotic stresses.BhMYB79 was particularly expressed in roots and significantly induced by salt,drought,cold and heat stresses,overexpression of which led to reduced tolerance to salt stress in Arabidopsis.In conclusion,our results provide a systematic analysis of wax gourd MYB gene family and facilitate the biological role study of BhMYB79 during wax gourd salt stress response process.
基金supported by Decit/SCTIE-Ministério da Saúde,Conselho Nacional de Desenvolvimento Científico e Tecnológico(CNPq),Fundação de AmparoàPesquisa do Estado de Alagoas(FAPEAL)and Secretaria de Estado da Saúde de Alagoas(SESAU-AL)[PPSUS 60030000841/2016].
文摘Objective:To investigate mutations in the Chikungunya(CHIKV)envelope genome region and evaluate their potential impact on B lymphocyte epitopes via in silico analysis.Methods:E1,E2 and 6K protein genes were sequenced from viral RNA isolated from 13 CHIKV-positive serum samples from Alagoas State,Brazil,during the 2016 outbreak.Phylogenetic analysis,experimental epitope identification in the immune epitope database(IEDB)and in silico approaches were employed to predict the potential impact of the detected mutations.Results:The sequences were clustered via phylogenetic analysis.The CHIKV isolates belong to the ECSA genotype,with 13 detected amino acid mutations.Five mutations are located on the surface of the viral particle in regions critical for cellular receptor interaction.Nine mutations are known experimentally validated epitopes for B and T cells.In B-cell epitope predictions,mutations affect sequences within three conformational epitopes in E2 and one in E1,as well as linear epitopes.Notably,the E2-G60D mutation found in the Alagoas strain has been previously reported to influence the vector competence of Aedes aegypti,the primary vector in Brazil.Conclusions:Genomic surveillance and an in-depth understanding of viral mutations are crucial for adapting public health strategies and improving the outbreak response.These findings could have significant public health implications,such as the development of more effective vaccines,diagnostic tests,and antiviral therapies.
文摘The efficient market hypothesis in traditional financial theory struggles to explain the short-term irrational fluctuations in the A-share market,where investor sentiment fluctuations often serve as the core driver of abnormal stock price movements.Traditional sentiment measurement methods suffer from limitations such as lag,high misjudgment rates,and the inability to distinguish confounding factors.To more accurately explore the dynamic correlation between investor sentiment and stock price fluctuations,this paper proposes a sentiment analysis framework based on large language models(LLMs).By constructing continuous sentiment scoring factors and integrating them with a long short-term memory(LSTM)deep learning model,we analyze the correlation between investor sentiment and stock price fluctuations.Empirical results indicate that sentiment factors based on large language models can generate an annualized excess return of 9.3%in the CSI 500 index domain.The LSTM stock price prediction model incorporating sentiment features achieves a mean absolute percentage error(MAPE)as low as 2.72%,significantly outperforming traditional models.Through this analysis,we aim to provide quantitative references for optimizing investment decisions and preventing market risks.
基金financially supported by the National Key R&D Program of China(No.2022YFE0121300)the National Natural Science Foundation of China(No.52374376)the Introduction Plan for High-end Foreign Experts(No.G2023105001L)。
文摘As a mathematical analysis method,fractal analysis can be used to quantitatively describe irregular shapes with self-similar or self-affine properties.Fractal analysis has been used to characterize the shapes of metal materials at various scales and dimensions.Conventional methods make it difficult to quantitatively describe the relationship between the regular characteristics and properties of metal material surfaces and interfaces.However,fractal analysis can be used to quantitatively describe the shape characteristics of metal materials and to establish the quantitative relationships between the shape characteristics and various properties of metal materials.From the perspective of two-dimensional planes and three-dimensional curved surfaces,this paper reviews the current research status of the fractal analysis of metal precipitate interfaces,metal grain boundary interfaces,metal-deposited film surfaces,metal fracture surfaces,metal machined surfaces,and metal wear surfaces.The relationship between the fractal dimensions and properties of metal material surfaces and interfaces is summarized.Starting from three perspectives of fractal analysis,namely,research scope,image acquisition methods,and calculation methods,this paper identifies the direction of research on fractal analysis of metal material surfaces and interfaces that need to be developed.It is believed that revealing the deep influence mechanism between the fractal dimensions and properties of metal material surfaces and interfaces will be the key research direction of the fractal analysis of metal materials in the future.
