Accurately estimating the State of Health(SOH)and Remaining Useful Life(RUL)of lithium-ion batteries(LIBs)is crucial for the continuous and stable operation of battery management systems.However,due to the complex int...Accurately estimating the State of Health(SOH)and Remaining Useful Life(RUL)of lithium-ion batteries(LIBs)is crucial for the continuous and stable operation of battery management systems.However,due to the complex internal chemical systems of LIBs and the nonlinear degradation of their performance,direct measurement of SOH and RUL is challenging.To address these issues,the Twin Support Vector Machine(TWSVM)method is proposed to predict SOH and RUL.Initially,the constant current charging time of the lithium battery is extracted as a health indicator(HI),decomposed using Variational Modal Decomposition(VMD),and feature correlations are computed using Importance of Random Forest Features(RF)to maximize the extraction of critical factors influencing battery performance degradation.Furthermore,to enhance the global search capability of the Convolution Optimization Algorithm(COA),improvements are made using Good Point Set theory and the Differential Evolution method.The Improved Convolution Optimization Algorithm(ICOA)is employed to optimize TWSVM parameters for constructing SOH and RUL prediction models.Finally,the proposed models are validated using NASA and CALCE lithium-ion battery datasets.Experimental results demonstrate that the proposed models achieve an RMSE not exceeding 0.007 and an MAPE not exceeding 0.0082 for SOH and RUL prediction,with a relative error in RUL prediction within the range of[-1.8%,2%].Compared to other models,the proposed model not only exhibits superior fitting capability but also demonstrates robust performance.展开更多
Objectives:To explore the efficacy and safety of virtual reality(VR)in relieving negative emotions in patients with breast cancer with different personalities.Methods:A randomized controlled trial was conducted.Betwee...Objectives:To explore the efficacy and safety of virtual reality(VR)in relieving negative emotions in patients with breast cancer with different personalities.Methods:A randomized controlled trial was conducted.Between April 2023 and October 2023,we enrolled patients with breast cancer treated in the Department of Breast Cancer and Oncology at Sun Yat-Sen Memorial Hospital,Sun Yat-Sen University,Guangdong Province.The patients were randomly divided into an intervention group(n=118)and a control group(n=119)using block randomization.The intervention group received the VR intervention 3-5 times over 5±2 weeks using natural landscapes with music or relaxation guidance,and the duration of each VR intervention was 15±3 min.The control group received routine nursing care,including disease education and psychological counseling.Patients were assessed using the Type D Scale,Positive and Negative Affect Scale,and Distress Thermometer,and adverse events during the intervention were recorded.Results:Overall,85 patients completed the study(44 in the intervention group and 41 in the control group).Patients with Type D personalities showed more negative emotions[25.0(21.5,27.5)vs.19.0(16.0,24.0),P=0.001]and distressed attitudes[4.0(2.0,5.0)vs.3.0(1.0,4.0),P=0.020]with fewer positive emotions(27.2±5.6 vs.31.0±5.9,P=0.014)than those with non-Type D personalities.Total population analysis revealed no significant differences between the groups.However,in the subgroup analysis,patients with Type D personalities in the intervention group showed greater relief from negative emotions than those in the control group[median difference,-5.0(-9.0,-2.5)vs.-2.0(-4.0,2.0),P=0.046].No significant differences were found between groups of patients with non-Type D personality traits.The proportion of adverse events was not significantly different between groups(P=0.110).Conclusions:Breast cancer patients with Type D personalities suffer more severe negative emotions and distress,and more attention should be paid to them.VR intervention significantly and safely reduced negative emotions in patients with Type D personalities.展开更多
The rapid expansion of railways,especially High-Speed Railways(HSRs),has drawn considerable interest from both academic and industrial sectors.To meet the future vision of smart rail communications,the rail transport ...The rapid expansion of railways,especially High-Speed Railways(HSRs),has drawn considerable interest from both academic and industrial sectors.To meet the future vision of smart rail communications,the rail transport industry must innovate in key technologies to ensure high-quality transmissions for passengers and railway operations.These systems must function effectively under high mobility conditions while prioritizing safety,ecofriendliness,comfort,transparency,predictability,and reliability.On the other hand,the proposal of 6 G wireless technology introduces new possibilities for innovation in communication technologies,which may truly realize the current vision of HSR.Therefore,this article gives a review of the current advanced 6 G wireless communication technologies for HSR,including random access and switching,channel estimation and beamforming,integrated sensing and communication,and edge computing.The main application scenarios of these technologies are reviewed,as well as their current research status and challenges,followed by an outlook on future development directions.展开更多
Adaptor signature,a new primitive that alleviates the scalability issue of blockchain to some extent,has been widely adopted in the off-chain payment channel and atomic swap.As an extension of standard digital signatu...Adaptor signature,a new primitive that alleviates the scalability issue of blockchain to some extent,has been widely adopted in the off-chain payment channel and atomic swap.As an extension of standard digital signature,adaptor signature can bind the release of a complete digital signature with the exchange of a secret value.Existing constructions of adaptor signatures are mainly based on Schnorr or ECDSA signature algorithms,which suffer low signing efficiency and long signature length.In this paper,to address these issues,we propose a new construction of adaptor signature using randomized EdDSA,which has Schnorr-like structure with higher signing efficiency and shorter signature length.We prove the required security properties,including unforgeability,witness extractability and pre-signature adaptability,of the new adaptor signature scheme in the random oracle model.We conduct a comparative analysis with an ECDSA-based adaptor signature scheme to demonstrate the effectiveness and feasibility of our new proposal.展开更多
Machine-learning is a robust technique for understanding pollution characteristics of surface ozone,which are at high levels in urban China.This study introduced an innovative approach combining trend decomposition wi...Machine-learning is a robust technique for understanding pollution characteristics of surface ozone,which are at high levels in urban China.This study introduced an innovative approach combining trend decomposition with Random Forest algorithm to investigate ozone dynamics and formation regimes in a coastal area of China.During the period of 2017–2022,significant inter-annual fluctuations emerged,with peaks in mid-2017 attributed to volatile organic compounds(VOCs),and in late-2019 influenced by air temperature.Multifaceted periodicities(daily,weekly,holiday,and yearly)in ozone were revealed,elucidating substantial influences of daily and yearly components on ozone periodicity.A VOC-sensitive ozone formation regime was identified,characterized by lower VOCs/NO_(x) ratios(average=0.88)and significant positive correlations between ozone and VOCs.This interplay manifested in elevated ozone duringweekends,holidays,and pandemic lockdowns.Key variables influencing ozone across diverse timescaleswere uncovered,with solar radiation and temperature driving daily and yearly ozone variations,respectively.Precursor substances,particularly VOCs,significantly shaped weekly/holiday patterns and long-term trends of ozone.Specifically,acetone,ethane,hexanal,and toluene had a notable impact on the multi-year ozone trend,emphasizing the urgency of VOC regulation.Furthermore,our observations indicated that NO_(x) primarily drived the stochastic variations in ozone,a distinguishing characteristic of regions with heavy traffic.This research provides novel insights into ozone dynamics in coastal urban areas and highlights the importance of integrating statistical and machinelearning methods in atmospheric pollution studies,with implications for targeted mitigation strategies beyond this specific region and pollutant.展开更多
The application of machine learning for pyrite discrimination establishes a robust foundation for constructing the ore-forming history of multi-stage deposits;however,published models face challenges related to limite...The application of machine learning for pyrite discrimination establishes a robust foundation for constructing the ore-forming history of multi-stage deposits;however,published models face challenges related to limited,imbalanced datasets and oversampling.In this study,the dataset was expanded to approximately 500 samples for each type,including 508 sedimentary,573 orogenic gold,548 sedimentary exhalative(SEDEX)deposits,and 364 volcanogenic massive sulfides(VMS)pyrites,utilizing random forest(RF)and support vector machine(SVM)methodologies to enhance the reliability of the classifier models.The RF classifier achieved an overall accuracy of 99.8%,and the SVM classifier attained an overall accuracy of 100%.The model was evaluated by a five-fold cross-validation approach with 93.8%accuracy for the RF and 94.9%for the SVM classifier.These results demonstrate the strong feasibility of pyrite classification,supported by a relatively large,balanced dataset and high accuracy rates.The classifier was employed to reveal the genesis of the controversial Keketale Pb-Zn deposit in NW China,which has been inconclusive among SEDEX,VMS,or a SEDEX-VMS transition.Petrographic investigations indicated that the deposit comprises early fine-grained layered pyrite(Py1)and late recrystallized pyrite(Py2).The majority voting classified Py1 as the VMS type,with an accuracy of RF and SVM being 72.2%and 75%,respectively,and confirmed Py2 as an orogenic type with 74.3% and 77.1%accuracy,respectively.The new findings indicated that the Keketale deposit originated from a submarine VMS mineralization system,followed by late orogenic-type overprinting of metamorphism and deformation,which is consistent with the geological and geochemical observations.This study further emphasizes the advantages of Machine learning(ML)methods in accurately and directly discriminating the deposit types and reconstructing the formation history of multi-stage deposits.展开更多
Objective:Based on multistage metabolomic profiling and Mendelian randomization analyses,the current study identified plasma metabolites that predicted the risk of developing gastric cancer(GC)and determined whether k...Objective:Based on multistage metabolomic profiling and Mendelian randomization analyses,the current study identified plasma metabolites that predicted the risk of developing gastric cancer(GC)and determined whether key metabolite levels modified the GC primary prevention effects.Methods:Plasma metabolites associated with GC risk were identified through a case-control study.Bi-directional two-sample Mendelian randomization analyses were performed to determine potential causal relationships utilizing the Shandong Intervention Trial(SIT),a nested case-control study of the Mass Intervention Trial in Linqu,Shandong province(MITS),China,the UK Biobank,and the Finn Gen project.Results:A higher genetic risk score for plasma L-aspartic acid was significantly associated with an increased GC risk in the northern Chinese population(SIT:HR=1.26 per 1 SD change,95%CI:1.07±1.49;MITS:HR=1.07,95%CI:1.00±1.14)and an increased gastric adenocarcinoma risk in Finn Gen(OR=1.68,95%CI:1.16±2.45).Genetically predicted plasma L-aspartic acid levels also modified the GC primary prevention effects with the beneficial effect of Helicobacter pylori eradication notably observed among individuals within the top quartile of L-aspartic acid level(P-interaction=0.098)and the beneficial effect of garlic supplementation only for those within the lowest quartile of L-aspartic acid level(P-interaction=0.02).Conclusions:Elevated plasma L-aspartic acid levels significantly increased the risk of developing GC and modified the effects of GC primary prevention.Further studies from other populations are warranted to validate the modification effect of plasma L-aspartic acid levels on GC prevention and to elucidate the underlying mechanisms.展开更多
The traditional academic warning methods for students in higher vocational colleges are relatively backward,single,and have many influencing factors,which have a limited effect on improving their learning ability.A da...The traditional academic warning methods for students in higher vocational colleges are relatively backward,single,and have many influencing factors,which have a limited effect on improving their learning ability.A data set was established by collecting academic warning data of students in a certain university.The importance of the school,major,grade,and warning level for the students was analyzed using the Pearson correlation coefficient,random forest variable importance,and permutation importance.It was found that the characteristic of the major has a great impact on the academic warning level.Countermeasures such as dynamic adjustment of majors,reform of cognitive adaptation of courses,full-cycle academic support,and data-driven precise intervention were proposed to provide theoretical support and practical paths for universities to improve the efficiency of academic warning and enhance students’learning ability.展开更多
The current study aimed to evaluate the efficacy and safety of Compound Danshen Dripping Pills(CDDP)in improving cardiac function in patients with acute anterior ST-segment elevation myocardial infarction(AAMI).Betwee...The current study aimed to evaluate the efficacy and safety of Compound Danshen Dripping Pills(CDDP)in improving cardiac function in patients with acute anterior ST-segment elevation myocardial infarction(AAMI).Between February 2021 and February 2023,247 eligible patients with AAMI after primary percutaneous coronary intervention were enrolled and randomly assigned(1∶1)to receive CDDP(n=126)or placebo(n=121),with a follow-up of 48 weeks.Compared with the placebo group,the CDDP group demonstrated a significant increase in left ventricular ejection fraction values after 24 weeks of treatment(least squares mean:3.31;95%confidence interval[CI]:1.72–4.90;P<0.001)and at the 48-week follow-up(least squares mean:4.35;95%CI:2.76–5.94;P<0.001).Significant reductions in N-terminal pro-B-type natriuretic peptide levels were observed in both groups at the 24-and 48-week visits with no significant difference between the two groups(P>0.1 for all).The incidence of major adverse cardiovascular and cerebrovascular events was 6.35%in the CDDP group and 5.79%in the placebo group(P=0.822).Notably,no serious adverse events were attributed to CDDP.These findings suggest that CDDP may be well tolerated and could improve left ventricular ejection fraction in patients with AAMI at 24 and 48 weeks.展开更多
Landslide susceptibility prediction(LSP)is significantly affected by the uncertainty issue of landslide related conditioning factor selection.However,most of literature only performs comparative studies on a certain c...Landslide susceptibility prediction(LSP)is significantly affected by the uncertainty issue of landslide related conditioning factor selection.However,most of literature only performs comparative studies on a certain conditioning factor selection method rather than systematically study this uncertainty issue.Targeted,this study aims to systematically explore the influence rules of various commonly used conditioning factor selection methods on LSP,and on this basis to innovatively propose a principle with universal application for optimal selection of conditioning factors.An'yuan County in southern China is taken as example considering 431 landslides and 29 types of conditioning factors.Five commonly used factor selection methods,namely,the correlation analysis(CA),linear regression(LR),principal component analysis(PCA),rough set(RS)and artificial neural network(ANN),are applied to select the optimal factor combinations from the original 29 conditioning factors.The factor selection results are then used as inputs of four types of common machine learning models to construct 20 types of combined models,such as CA-multilayer perceptron,CA-random forest.Additionally,multifactor-based multilayer perceptron random forest models that selecting conditioning factors based on the proposed principle of“accurate data,rich types,clear significance,feasible operation and avoiding duplication”are constructed for comparisons.Finally,the LSP uncertainties are evaluated by the accuracy,susceptibility index distribution,etc.Results show that:(1)multifactor-based models have generally higher LSP performance and lower uncertainties than those of factors selection-based models;(2)Influence degree of different machine learning on LSP accuracy is greater than that of different factor selection methods.Conclusively,the above commonly used conditioning factor selection methods are not ideal for improving LSP performance and may complicate the LSP processes.In contrast,a satisfied combination of conditioning factors can be constructed according to the proposed principle.展开更多
Brain-derived neurotrophic factor is a crucial neurotrophic factor that plays a significant role in brain health. Although the vast majority of meta-analyses have confirmed that exercise interventions can increase bra...Brain-derived neurotrophic factor is a crucial neurotrophic factor that plays a significant role in brain health. Although the vast majority of meta-analyses have confirmed that exercise interventions can increase brain-derived neurotrophic factor levels in children and adolescents, the effects of specific types of exercise on brain-derived neurotrophic factor levels are still controversial. To address this issue, we used meta-analytic methods to quantitatively evaluate, analyze, and integrate relevant studies. Our goals were to formulate general conclusions regarding the use of exercise interventions, explore the physiological mechanisms by which exercise improves brain health and cognitive ability in children and adolescents, and provide a reliable foundation for follow-up research. We used the Pub Med, Web of Science, Science Direct, Springer, Wiley Online Library, Weipu, Wanfang, and China National Knowledge Infrastructure databases to search for randomized controlled trials examining the influences of exercise interventions on brain-derived neurotrophic factor levels in children and adolescents. The extracted data were analyzed using Review Manager 5.3. According to the inclusion criteria, we assessed randomized controlled trials in which the samples were mainly children and adolescents, and the outcome indicators were measured before and after the intervention. We excluded animal experiments, studies that lacked a control group, and those that did not report quantitative results. The mean difference(MD;before versus after intervention) was used to evaluate the effect of exercise on brain-derived neurotrophic factor levels in children and adolescents. Overall, 531 participants(60 children and 471 adolescents, 10.9–16.1 years) were included from 13 randomized controlled trials. Heterogeneity was evaluated using the Q statistic and I^(2) test provided by Review Manager software. The meta-analysis showed that there was no heterogeneity among the studies(P = 0.67, I^(2) = 0.00%). The combined effect of the interventions was significant(MD = 2.88, 95% CI: 1.53–4.22, P < 0.0001), indicating that the brain-derived neurotrophic factor levels of the children and adolescents in the exercise group were significantly higher than those in the control group. In conclusion, different types of exercise interventions significantly increased brain-derived neurotrophic factor levels in children and adolescents. However, because of the small sample size of this meta-analysis, more high-quality research is needed to verify our conclusions. This metaanalysis was registered at PROSPERO(registration ID: CRD42023439408).展开更多
The girder end restraint devices such as bearings and dampers on long span suspension bridge will deteriorate over time.However,it is difficult to achieve the quantitative assessment of the performance of the restrain...The girder end restraint devices such as bearings and dampers on long span suspension bridge will deteriorate over time.However,it is difficult to achieve the quantitative assessment of the performance of the restraint device through existing detection methods in actual inspections,making it difficult to obtain the impact of changes in the performance of the restraint device on the bridge structure.In this paper,a random vehicle load model is firstly established based on the WIM data of Jiangyin Bridge,and the displacement of girder end under the actual traffic flow is simulated by using finite element dynamic time history analysis.On this basis,according to the performance test data of the bearings and dampers,the performance degradation laws of the above two restraint devices are summarized,and the performance degradation process of the two restraint devices and the effects of different restraint parameters on the bridge structure are simulated.The results show that the performance degradation of the damper will significantly reduce the damping force at low speed,resulting in a significant increase in the cumulative displacement of the girder end;in the presence of longitudinal dampers,the increase in the friction coefficient caused by the deterioration of the bearing sliding plate has little effect on the cumulative displacement,but excessive wear of the bearing sliding plate adversely affects the structural dynamic performance.展开更多
The proliferation of robot accounts on social media platforms has posed a significant negative impact,necessitating robust measures to counter network anomalies and safeguard content integrity.Social robot detection h...The proliferation of robot accounts on social media platforms has posed a significant negative impact,necessitating robust measures to counter network anomalies and safeguard content integrity.Social robot detection has emerged as a pivotal yet intricate task,aimed at mitigating the dissemination of misleading information.While graphbased approaches have attained remarkable performance in this realm,they grapple with a fundamental limitation:the homogeneity assumption in graph convolution allows social robots to stealthily evade detection by mingling with genuine human profiles.To unravel this challenge and thwart the camouflage tactics,this work proposed an innovative social robot detection framework based on enhanced HOmogeneity and Random Forest(HORFBot).At the core of HORFBot lies a homogeneous graph enhancement strategy,intricately woven with edge-removal techniques,tometiculously dissect the graph intomultiple revealing subgraphs.Subsequently,leveraging the power of contrastive learning,the proposed methodology meticulously trains multiple graph convolutional networks,each honed to discern nuances within these tailored subgraphs.The culminating stage involves the fusion of these feature-rich base classifiers,harmoniously aggregating their insights to produce a comprehensive detection outcome.Extensive experiments on three social robot detection datasets have shown that this method effectively improves the accuracy of social robot detection and outperforms comparative methods.展开更多
In this paper,large deviations principle(LDP)and moderate deviations principle(MDP)of record numbers in random walks are studied under certain conditions.The results show that the rate functions of LDP and MDP are dif...In this paper,large deviations principle(LDP)and moderate deviations principle(MDP)of record numbers in random walks are studied under certain conditions.The results show that the rate functions of LDP and MDP are different from those of weak record numbers,which are interesting complements of the conclusions by Li and Yao[1].展开更多
OBJECTIVE:In recent years,the number of clinical research reports on acupuncture and manipulation for the treatment of greater occipital neuralgia has gradually increased,but the quality is uneven.There is currently n...OBJECTIVE:In recent years,the number of clinical research reports on acupuncture and manipulation for the treatment of greater occipital neuralgia has gradually increased,but the quality is uneven.There is currently no literature evaluating the quality of published reports,which is not conducive to the promotion of clinical use of these therapies.Therefore,this article assessed the reporting quality of randomized controlled trials on acupuncture and manipulation for greater occipital neuralgia.METHODS:Cochrane Library,PubMed,Web of Science,Embase,China National Knowledge Infrastructure(CNKI),VIP,WanFang Data,and Chinese BioMedical Literature Database(CBM)from inception to May 20,2024 were searched.The reporting quality of included randomized controlled trials was independently evaluated by two investigators using the CONSORT statement,STRICTA checklist,and Cochrane bias of risk assessment tool.A third investigator resolved any disagreement.RESULTS:A total of 62 articles were included.Based on the CONSORT statement,59.46%(22/37)of all entries had a reporting rate of less than 50%,mainly including“Identification as a randomized trial in the title(1/62,1.61%),”“How sample size was determined(7/62,11.29%),”“Implementation(1/62,1.61%),”“Blinding(1/62,1.61%),”and“Reports of Funding(4/62,6.45%).”According to the STRICTA checklist,29.41%(5/17)of all entries had a reporting rate of less than 50%,mainly including“Details of other interventions(7/58,12.07%),”“Setting and context of treatment(0/58,0%),”and“Description of participating acupuncturists(0/58,0%).”CONCLUSION:The reporting quality of randomized controlled trials on acupuncture and manipulation therapy for greater occipital neuralgia remains low.Future researchers need to make greater efforts to strictly adhere to the CONSORT statement and STRICTA checklist during trial design,implementation,and reporting.This will facilitate the standardization of research in this field and enhance the reliability and reproducibility of the research results.展开更多
The complete convergence for weighted sums of sequences of independent,identically distributed random variables under sublinear expectation space is studied.By moment inequality and truncation methods,we establish the...The complete convergence for weighted sums of sequences of independent,identically distributed random variables under sublinear expectation space is studied.By moment inequality and truncation methods,we establish the equivalent conditions of complete convergence for weighted sums of sequences of independent,identically distributed random variables under sublinear expectation space.The results complement the corresponding results in probability space to those for sequences of independent,identically distributed random variables under sublinear expectation space.展开更多
In this paper,by utilizing the Marcinkiewicz-Zygmund inequality and Rosenthal-type inequality of negatively superadditive dependent(NSD)random arrays and truncated method,we investigate the complete f-moment convergen...In this paper,by utilizing the Marcinkiewicz-Zygmund inequality and Rosenthal-type inequality of negatively superadditive dependent(NSD)random arrays and truncated method,we investigate the complete f-moment convergence of NSD random variables.We establish and improve a general result on the complete f-moment convergence for Sung’s type randomly weighted sums of NSD random variables under some general assumptions.As an application,we show the complete consistency for the randomly weighted estimator in a nonparametric regression model based on NSD errors.展开更多
Creutzfeldt-Jakob disease(CJD)is a rare neurodegenerative disorder characterized by abnormalities in the prion protein(PrP),the most common form of human prion disease.Although Genome-Wide Association Studies(GWAS)hav...Creutzfeldt-Jakob disease(CJD)is a rare neurodegenerative disorder characterized by abnormalities in the prion protein(PrP),the most common form of human prion disease.Although Genome-Wide Association Studies(GWAS)have identified numerous risk genes for CJD,the mechanisms underlying these risk loci remain poorly understood.This study aims to elucidate novel genetically prioritized candidate proteins associated with CJD in the human brain through an integrative analytical pipeline.Utilizing datasets from Protein Quantitative Trait Loci(pQTL)(NpQTL1=152,NpQTL2=376),expression QTL(eQTL)(N=452),and the CJD GWAS(NCJD=4110,NControls=13569),we implemented a systematic analytical pipeline.This pipeline included Proteome-Wide Association Study(PWAS),Mendelian randomization(MR),Bayesian colocalization,and Transcriptome-Wide Association Study(TWAS)to identify novel genetically prioritized candidate proteins implicated in CJD pathogenesis within the brain.Through PWAS,we identified that the altered abundance of six brain proteins was significantly associated with CJD.Two genes,STX6 and PDIA4,were established as lead causal genes for CJD,supported by robust evidence(False Discovery Rate<0.05 in MR analysis;PP4/(PP3+PP4)≥0.75 in Bayesian colocalization).Specifically,elevated levels of STX6 and PDIA4 were associated with an increased risk of CJD.Additionally,TWAS demonstrated that STX6 and PDIA4 were associated with CJD at the transcriptional level.展开更多
In this paper, we consider the existence of pullback random exponential attractor for non-autonomous random reaction-diffusion equation driven by nonlinear colored noise defined onR^(N) . The key steps of the proof ar...In this paper, we consider the existence of pullback random exponential attractor for non-autonomous random reaction-diffusion equation driven by nonlinear colored noise defined onR^(N) . The key steps of the proof are the tails estimate and to demonstrate the Lipschitz continuity and random squeezing property of the solution for the equation defined on R^(N) .展开更多
基金funded by the Pyramid Talent Training Project of Beijing University of Civil Engineering and Architecture under Grant GJZJ20220802。
文摘Accurately estimating the State of Health(SOH)and Remaining Useful Life(RUL)of lithium-ion batteries(LIBs)is crucial for the continuous and stable operation of battery management systems.However,due to the complex internal chemical systems of LIBs and the nonlinear degradation of their performance,direct measurement of SOH and RUL is challenging.To address these issues,the Twin Support Vector Machine(TWSVM)method is proposed to predict SOH and RUL.Initially,the constant current charging time of the lithium battery is extracted as a health indicator(HI),decomposed using Variational Modal Decomposition(VMD),and feature correlations are computed using Importance of Random Forest Features(RF)to maximize the extraction of critical factors influencing battery performance degradation.Furthermore,to enhance the global search capability of the Convolution Optimization Algorithm(COA),improvements are made using Good Point Set theory and the Differential Evolution method.The Improved Convolution Optimization Algorithm(ICOA)is employed to optimize TWSVM parameters for constructing SOH and RUL prediction models.Finally,the proposed models are validated using NASA and CALCE lithium-ion battery datasets.Experimental results demonstrate that the proposed models achieve an RMSE not exceeding 0.007 and an MAPE not exceeding 0.0082 for SOH and RUL prediction,with a relative error in RUL prediction within the range of[-1.8%,2%].Compared to other models,the proposed model not only exhibits superior fitting capability but also demonstrates robust performance.
基金supported by a project of the National Natural Science Foundation of China:Research on the integration of artificial intelligence and virtual reality technology to promote psychological rehabilitation of breast cancer patients with different personalities(project approval no.82073408).
文摘Objectives:To explore the efficacy and safety of virtual reality(VR)in relieving negative emotions in patients with breast cancer with different personalities.Methods:A randomized controlled trial was conducted.Between April 2023 and October 2023,we enrolled patients with breast cancer treated in the Department of Breast Cancer and Oncology at Sun Yat-Sen Memorial Hospital,Sun Yat-Sen University,Guangdong Province.The patients were randomly divided into an intervention group(n=118)and a control group(n=119)using block randomization.The intervention group received the VR intervention 3-5 times over 5±2 weeks using natural landscapes with music or relaxation guidance,and the duration of each VR intervention was 15±3 min.The control group received routine nursing care,including disease education and psychological counseling.Patients were assessed using the Type D Scale,Positive and Negative Affect Scale,and Distress Thermometer,and adverse events during the intervention were recorded.Results:Overall,85 patients completed the study(44 in the intervention group and 41 in the control group).Patients with Type D personalities showed more negative emotions[25.0(21.5,27.5)vs.19.0(16.0,24.0),P=0.001]and distressed attitudes[4.0(2.0,5.0)vs.3.0(1.0,4.0),P=0.020]with fewer positive emotions(27.2±5.6 vs.31.0±5.9,P=0.014)than those with non-Type D personalities.Total population analysis revealed no significant differences between the groups.However,in the subgroup analysis,patients with Type D personalities in the intervention group showed greater relief from negative emotions than those in the control group[median difference,-5.0(-9.0,-2.5)vs.-2.0(-4.0,2.0),P=0.046].No significant differences were found between groups of patients with non-Type D personality traits.The proportion of adverse events was not significantly different between groups(P=0.110).Conclusions:Breast cancer patients with Type D personalities suffer more severe negative emotions and distress,and more attention should be paid to them.VR intervention significantly and safely reduced negative emotions in patients with Type D personalities.
基金National Natural Science Foundation of China(U2468201,62122012,62221001).
文摘The rapid expansion of railways,especially High-Speed Railways(HSRs),has drawn considerable interest from both academic and industrial sectors.To meet the future vision of smart rail communications,the rail transport industry must innovate in key technologies to ensure high-quality transmissions for passengers and railway operations.These systems must function effectively under high mobility conditions while prioritizing safety,ecofriendliness,comfort,transparency,predictability,and reliability.On the other hand,the proposal of 6 G wireless technology introduces new possibilities for innovation in communication technologies,which may truly realize the current vision of HSR.Therefore,this article gives a review of the current advanced 6 G wireless communication technologies for HSR,including random access and switching,channel estimation and beamforming,integrated sensing and communication,and edge computing.The main application scenarios of these technologies are reviewed,as well as their current research status and challenges,followed by an outlook on future development directions.
基金supported by the National Key R&D Program of China(2022YFB2701500)the National Natural Science Foundation of China(62272385,62311540156)+2 种基金Shaanxi Distinguished Youth Project(2022JC-47)the Key Research and Development Program of Shaanxi(2021ZDLGY06-04)Major Program of Shandong Provincial Natural Science Foundation for the Fundamental Research(ZR2022ZD03).
文摘Adaptor signature,a new primitive that alleviates the scalability issue of blockchain to some extent,has been widely adopted in the off-chain payment channel and atomic swap.As an extension of standard digital signature,adaptor signature can bind the release of a complete digital signature with the exchange of a secret value.Existing constructions of adaptor signatures are mainly based on Schnorr or ECDSA signature algorithms,which suffer low signing efficiency and long signature length.In this paper,to address these issues,we propose a new construction of adaptor signature using randomized EdDSA,which has Schnorr-like structure with higher signing efficiency and shorter signature length.We prove the required security properties,including unforgeability,witness extractability and pre-signature adaptability,of the new adaptor signature scheme in the random oracle model.We conduct a comparative analysis with an ECDSA-based adaptor signature scheme to demonstrate the effectiveness and feasibility of our new proposal.
基金supported by Ningbo Natural Science Foundation(No.2023J059)Ningbo Commonweal Programme Key Project(No.2023S038)Guangxi Key Research and Development Programme(No.GuikeAB21220063).
文摘Machine-learning is a robust technique for understanding pollution characteristics of surface ozone,which are at high levels in urban China.This study introduced an innovative approach combining trend decomposition with Random Forest algorithm to investigate ozone dynamics and formation regimes in a coastal area of China.During the period of 2017–2022,significant inter-annual fluctuations emerged,with peaks in mid-2017 attributed to volatile organic compounds(VOCs),and in late-2019 influenced by air temperature.Multifaceted periodicities(daily,weekly,holiday,and yearly)in ozone were revealed,elucidating substantial influences of daily and yearly components on ozone periodicity.A VOC-sensitive ozone formation regime was identified,characterized by lower VOCs/NO_(x) ratios(average=0.88)and significant positive correlations between ozone and VOCs.This interplay manifested in elevated ozone duringweekends,holidays,and pandemic lockdowns.Key variables influencing ozone across diverse timescaleswere uncovered,with solar radiation and temperature driving daily and yearly ozone variations,respectively.Precursor substances,particularly VOCs,significantly shaped weekly/holiday patterns and long-term trends of ozone.Specifically,acetone,ethane,hexanal,and toluene had a notable impact on the multi-year ozone trend,emphasizing the urgency of VOC regulation.Furthermore,our observations indicated that NO_(x) primarily drived the stochastic variations in ozone,a distinguishing characteristic of regions with heavy traffic.This research provides novel insights into ozone dynamics in coastal urban areas and highlights the importance of integrating statistical and machinelearning methods in atmospheric pollution studies,with implications for targeted mitigation strategies beyond this specific region and pollutant.
基金the National Key Research and Development Program of China(2021YFC2900300)the Natural Science Foundation of Guangdong Province(2024A1515030216)+2 种基金MOST Special Fund from State Key Laboratory of Geological Processes and Mineral Resources,China University of Geosciences(GPMR202437)the Guangdong Province Introduced of Innovative R&D Team(2021ZT09H399)the Third Xinjiang Scientific Expedition Program(2022xjkk1301).
文摘The application of machine learning for pyrite discrimination establishes a robust foundation for constructing the ore-forming history of multi-stage deposits;however,published models face challenges related to limited,imbalanced datasets and oversampling.In this study,the dataset was expanded to approximately 500 samples for each type,including 508 sedimentary,573 orogenic gold,548 sedimentary exhalative(SEDEX)deposits,and 364 volcanogenic massive sulfides(VMS)pyrites,utilizing random forest(RF)and support vector machine(SVM)methodologies to enhance the reliability of the classifier models.The RF classifier achieved an overall accuracy of 99.8%,and the SVM classifier attained an overall accuracy of 100%.The model was evaluated by a five-fold cross-validation approach with 93.8%accuracy for the RF and 94.9%for the SVM classifier.These results demonstrate the strong feasibility of pyrite classification,supported by a relatively large,balanced dataset and high accuracy rates.The classifier was employed to reveal the genesis of the controversial Keketale Pb-Zn deposit in NW China,which has been inconclusive among SEDEX,VMS,or a SEDEX-VMS transition.Petrographic investigations indicated that the deposit comprises early fine-grained layered pyrite(Py1)and late recrystallized pyrite(Py2).The majority voting classified Py1 as the VMS type,with an accuracy of RF and SVM being 72.2%and 75%,respectively,and confirmed Py2 as an orogenic type with 74.3% and 77.1%accuracy,respectively.The new findings indicated that the Keketale deposit originated from a submarine VMS mineralization system,followed by late orogenic-type overprinting of metamorphism and deformation,which is consistent with the geological and geochemical observations.This study further emphasizes the advantages of Machine learning(ML)methods in accurately and directly discriminating the deposit types and reconstructing the formation history of multi-stage deposits.
基金funded by the National Natural Science Foundation of China(No.82273704)Noncommunicable Chronic Diseases-National Science and Technology Major Project(No.2023ZD0501400-2023ZD0501402)+4 种基金Beijing Hospitals Authority’s Ascent Plan(DFL20241102)Beijing Hospitals Authority Clinical Medicine Development of Special Funding Support(No.ZLRK202325)China Postdoctoral Science Foundation(2024M760152)Peking University Medicine Fund for World’s Leading Discipline or Discipline Cluster Development(No.BMU2022XKQ004)Science Foundation of Peking University Cancer Hospital(Nos.BJCH2024BJ02,XKFZ2410,BJCH2025CZ04,and 2022-27)。
文摘Objective:Based on multistage metabolomic profiling and Mendelian randomization analyses,the current study identified plasma metabolites that predicted the risk of developing gastric cancer(GC)and determined whether key metabolite levels modified the GC primary prevention effects.Methods:Plasma metabolites associated with GC risk were identified through a case-control study.Bi-directional two-sample Mendelian randomization analyses were performed to determine potential causal relationships utilizing the Shandong Intervention Trial(SIT),a nested case-control study of the Mass Intervention Trial in Linqu,Shandong province(MITS),China,the UK Biobank,and the Finn Gen project.Results:A higher genetic risk score for plasma L-aspartic acid was significantly associated with an increased GC risk in the northern Chinese population(SIT:HR=1.26 per 1 SD change,95%CI:1.07±1.49;MITS:HR=1.07,95%CI:1.00±1.14)and an increased gastric adenocarcinoma risk in Finn Gen(OR=1.68,95%CI:1.16±2.45).Genetically predicted plasma L-aspartic acid levels also modified the GC primary prevention effects with the beneficial effect of Helicobacter pylori eradication notably observed among individuals within the top quartile of L-aspartic acid level(P-interaction=0.098)and the beneficial effect of garlic supplementation only for those within the lowest quartile of L-aspartic acid level(P-interaction=0.02).Conclusions:Elevated plasma L-aspartic acid levels significantly increased the risk of developing GC and modified the effects of GC primary prevention.Further studies from other populations are warranted to validate the modification effect of plasma L-aspartic acid levels on GC prevention and to elucidate the underlying mechanisms.
基金supported by the Basic Ability Improvement Project of Young and Middle-Aged Teachers in Colleges and Universities of Guangxi(2022KY1922,2021KY1938).
文摘The traditional academic warning methods for students in higher vocational colleges are relatively backward,single,and have many influencing factors,which have a limited effect on improving their learning ability.A data set was established by collecting academic warning data of students in a certain university.The importance of the school,major,grade,and warning level for the students was analyzed using the Pearson correlation coefficient,random forest variable importance,and permutation importance.It was found that the characteristic of the major has a great impact on the academic warning level.Countermeasures such as dynamic adjustment of majors,reform of cognitive adaptation of courses,full-cycle academic support,and data-driven precise intervention were proposed to provide theoretical support and practical paths for universities to improve the efficiency of academic warning and enhance students’learning ability.
基金supported by Tasly Pharmaceutical Group Co.,Ltd.(Grant No.303100031BA20)。
文摘The current study aimed to evaluate the efficacy and safety of Compound Danshen Dripping Pills(CDDP)in improving cardiac function in patients with acute anterior ST-segment elevation myocardial infarction(AAMI).Between February 2021 and February 2023,247 eligible patients with AAMI after primary percutaneous coronary intervention were enrolled and randomly assigned(1∶1)to receive CDDP(n=126)or placebo(n=121),with a follow-up of 48 weeks.Compared with the placebo group,the CDDP group demonstrated a significant increase in left ventricular ejection fraction values after 24 weeks of treatment(least squares mean:3.31;95%confidence interval[CI]:1.72–4.90;P<0.001)and at the 48-week follow-up(least squares mean:4.35;95%CI:2.76–5.94;P<0.001).Significant reductions in N-terminal pro-B-type natriuretic peptide levels were observed in both groups at the 24-and 48-week visits with no significant difference between the two groups(P>0.1 for all).The incidence of major adverse cardiovascular and cerebrovascular events was 6.35%in the CDDP group and 5.79%in the placebo group(P=0.822).Notably,no serious adverse events were attributed to CDDP.These findings suggest that CDDP may be well tolerated and could improve left ventricular ejection fraction in patients with AAMI at 24 and 48 weeks.
基金funded by the Natural Science Foundation of China(Grant Nos.42377164 and 41972280)the Badong National Observation and Research Station of Geohazards(Grant No.BNORSG-202305).
文摘Landslide susceptibility prediction(LSP)is significantly affected by the uncertainty issue of landslide related conditioning factor selection.However,most of literature only performs comparative studies on a certain conditioning factor selection method rather than systematically study this uncertainty issue.Targeted,this study aims to systematically explore the influence rules of various commonly used conditioning factor selection methods on LSP,and on this basis to innovatively propose a principle with universal application for optimal selection of conditioning factors.An'yuan County in southern China is taken as example considering 431 landslides and 29 types of conditioning factors.Five commonly used factor selection methods,namely,the correlation analysis(CA),linear regression(LR),principal component analysis(PCA),rough set(RS)and artificial neural network(ANN),are applied to select the optimal factor combinations from the original 29 conditioning factors.The factor selection results are then used as inputs of four types of common machine learning models to construct 20 types of combined models,such as CA-multilayer perceptron,CA-random forest.Additionally,multifactor-based multilayer perceptron random forest models that selecting conditioning factors based on the proposed principle of“accurate data,rich types,clear significance,feasible operation and avoiding duplication”are constructed for comparisons.Finally,the LSP uncertainties are evaluated by the accuracy,susceptibility index distribution,etc.Results show that:(1)multifactor-based models have generally higher LSP performance and lower uncertainties than those of factors selection-based models;(2)Influence degree of different machine learning on LSP accuracy is greater than that of different factor selection methods.Conclusively,the above commonly used conditioning factor selection methods are not ideal for improving LSP performance and may complicate the LSP processes.In contrast,a satisfied combination of conditioning factors can be constructed according to the proposed principle.
基金supported by the STI 2030-Major Projects,No. 2021ZD0200500 (to XS)。
文摘Brain-derived neurotrophic factor is a crucial neurotrophic factor that plays a significant role in brain health. Although the vast majority of meta-analyses have confirmed that exercise interventions can increase brain-derived neurotrophic factor levels in children and adolescents, the effects of specific types of exercise on brain-derived neurotrophic factor levels are still controversial. To address this issue, we used meta-analytic methods to quantitatively evaluate, analyze, and integrate relevant studies. Our goals were to formulate general conclusions regarding the use of exercise interventions, explore the physiological mechanisms by which exercise improves brain health and cognitive ability in children and adolescents, and provide a reliable foundation for follow-up research. We used the Pub Med, Web of Science, Science Direct, Springer, Wiley Online Library, Weipu, Wanfang, and China National Knowledge Infrastructure databases to search for randomized controlled trials examining the influences of exercise interventions on brain-derived neurotrophic factor levels in children and adolescents. The extracted data were analyzed using Review Manager 5.3. According to the inclusion criteria, we assessed randomized controlled trials in which the samples were mainly children and adolescents, and the outcome indicators were measured before and after the intervention. We excluded animal experiments, studies that lacked a control group, and those that did not report quantitative results. The mean difference(MD;before versus after intervention) was used to evaluate the effect of exercise on brain-derived neurotrophic factor levels in children and adolescents. Overall, 531 participants(60 children and 471 adolescents, 10.9–16.1 years) were included from 13 randomized controlled trials. Heterogeneity was evaluated using the Q statistic and I^(2) test provided by Review Manager software. The meta-analysis showed that there was no heterogeneity among the studies(P = 0.67, I^(2) = 0.00%). The combined effect of the interventions was significant(MD = 2.88, 95% CI: 1.53–4.22, P < 0.0001), indicating that the brain-derived neurotrophic factor levels of the children and adolescents in the exercise group were significantly higher than those in the control group. In conclusion, different types of exercise interventions significantly increased brain-derived neurotrophic factor levels in children and adolescents. However, because of the small sample size of this meta-analysis, more high-quality research is needed to verify our conclusions. This metaanalysis was registered at PROSPERO(registration ID: CRD42023439408).
基金supported by the National Key Research and Development Program of China(No.2022YFB3706704)the Academician Special Science Research Project of CCCC(No.YSZX-03-2022-01-B).
文摘The girder end restraint devices such as bearings and dampers on long span suspension bridge will deteriorate over time.However,it is difficult to achieve the quantitative assessment of the performance of the restraint device through existing detection methods in actual inspections,making it difficult to obtain the impact of changes in the performance of the restraint device on the bridge structure.In this paper,a random vehicle load model is firstly established based on the WIM data of Jiangyin Bridge,and the displacement of girder end under the actual traffic flow is simulated by using finite element dynamic time history analysis.On this basis,according to the performance test data of the bearings and dampers,the performance degradation laws of the above two restraint devices are summarized,and the performance degradation process of the two restraint devices and the effects of different restraint parameters on the bridge structure are simulated.The results show that the performance degradation of the damper will significantly reduce the damping force at low speed,resulting in a significant increase in the cumulative displacement of the girder end;in the presence of longitudinal dampers,the increase in the friction coefficient caused by the deterioration of the bearing sliding plate has little effect on the cumulative displacement,but excessive wear of the bearing sliding plate adversely affects the structural dynamic performance.
基金Funds for the Central Universities(grant number CUC24SG018).
文摘The proliferation of robot accounts on social media platforms has posed a significant negative impact,necessitating robust measures to counter network anomalies and safeguard content integrity.Social robot detection has emerged as a pivotal yet intricate task,aimed at mitigating the dissemination of misleading information.While graphbased approaches have attained remarkable performance in this realm,they grapple with a fundamental limitation:the homogeneity assumption in graph convolution allows social robots to stealthily evade detection by mingling with genuine human profiles.To unravel this challenge and thwart the camouflage tactics,this work proposed an innovative social robot detection framework based on enhanced HOmogeneity and Random Forest(HORFBot).At the core of HORFBot lies a homogeneous graph enhancement strategy,intricately woven with edge-removal techniques,tometiculously dissect the graph intomultiple revealing subgraphs.Subsequently,leveraging the power of contrastive learning,the proposed methodology meticulously trains multiple graph convolutional networks,each honed to discern nuances within these tailored subgraphs.The culminating stage involves the fusion of these feature-rich base classifiers,harmoniously aggregating their insights to produce a comprehensive detection outcome.Extensive experiments on three social robot detection datasets have shown that this method effectively improves the accuracy of social robot detection and outperforms comparative methods.
基金supported by the National Natural Science Foundation of China(Grant No.11671145)the Science and Technology Commission of Shanghai Municipality(Grant No.18dz2271000).
文摘In this paper,large deviations principle(LDP)and moderate deviations principle(MDP)of record numbers in random walks are studied under certain conditions.The results show that the rate functions of LDP and MDP are different from those of weak record numbers,which are interesting complements of the conclusions by Li and Yao[1].
文摘OBJECTIVE:In recent years,the number of clinical research reports on acupuncture and manipulation for the treatment of greater occipital neuralgia has gradually increased,but the quality is uneven.There is currently no literature evaluating the quality of published reports,which is not conducive to the promotion of clinical use of these therapies.Therefore,this article assessed the reporting quality of randomized controlled trials on acupuncture and manipulation for greater occipital neuralgia.METHODS:Cochrane Library,PubMed,Web of Science,Embase,China National Knowledge Infrastructure(CNKI),VIP,WanFang Data,and Chinese BioMedical Literature Database(CBM)from inception to May 20,2024 were searched.The reporting quality of included randomized controlled trials was independently evaluated by two investigators using the CONSORT statement,STRICTA checklist,and Cochrane bias of risk assessment tool.A third investigator resolved any disagreement.RESULTS:A total of 62 articles were included.Based on the CONSORT statement,59.46%(22/37)of all entries had a reporting rate of less than 50%,mainly including“Identification as a randomized trial in the title(1/62,1.61%),”“How sample size was determined(7/62,11.29%),”“Implementation(1/62,1.61%),”“Blinding(1/62,1.61%),”and“Reports of Funding(4/62,6.45%).”According to the STRICTA checklist,29.41%(5/17)of all entries had a reporting rate of less than 50%,mainly including“Details of other interventions(7/58,12.07%),”“Setting and context of treatment(0/58,0%),”and“Description of participating acupuncturists(0/58,0%).”CONCLUSION:The reporting quality of randomized controlled trials on acupuncture and manipulation therapy for greater occipital neuralgia remains low.Future researchers need to make greater efforts to strictly adhere to the CONSORT statement and STRICTA checklist during trial design,implementation,and reporting.This will facilitate the standardization of research in this field and enhance the reliability and reproducibility of the research results.
基金supported by Doctoral Scientific Research Starting Foundation of Jingdezhen Ceramic University(Grant No.102/01003002031)Re-accompanying Funding Project of Academic Achievements of Jingdezhen Ceramic University(Grant Nos.215/20506277,215/20506341)。
文摘The complete convergence for weighted sums of sequences of independent,identically distributed random variables under sublinear expectation space is studied.By moment inequality and truncation methods,we establish the equivalent conditions of complete convergence for weighted sums of sequences of independent,identically distributed random variables under sublinear expectation space.The results complement the corresponding results in probability space to those for sequences of independent,identically distributed random variables under sublinear expectation space.
基金supported by the National Social Science Fundation(Grant No.21BTJ040)the Project of Outstanding Young People in University of Anhui Province(Grant Nos.2023AH020037,SLXY2024A001).
文摘In this paper,by utilizing the Marcinkiewicz-Zygmund inequality and Rosenthal-type inequality of negatively superadditive dependent(NSD)random arrays and truncated method,we investigate the complete f-moment convergence of NSD random variables.We establish and improve a general result on the complete f-moment convergence for Sung’s type randomly weighted sums of NSD random variables under some general assumptions.As an application,we show the complete consistency for the randomly weighted estimator in a nonparametric regression model based on NSD errors.
文摘Creutzfeldt-Jakob disease(CJD)is a rare neurodegenerative disorder characterized by abnormalities in the prion protein(PrP),the most common form of human prion disease.Although Genome-Wide Association Studies(GWAS)have identified numerous risk genes for CJD,the mechanisms underlying these risk loci remain poorly understood.This study aims to elucidate novel genetically prioritized candidate proteins associated with CJD in the human brain through an integrative analytical pipeline.Utilizing datasets from Protein Quantitative Trait Loci(pQTL)(NpQTL1=152,NpQTL2=376),expression QTL(eQTL)(N=452),and the CJD GWAS(NCJD=4110,NControls=13569),we implemented a systematic analytical pipeline.This pipeline included Proteome-Wide Association Study(PWAS),Mendelian randomization(MR),Bayesian colocalization,and Transcriptome-Wide Association Study(TWAS)to identify novel genetically prioritized candidate proteins implicated in CJD pathogenesis within the brain.Through PWAS,we identified that the altered abundance of six brain proteins was significantly associated with CJD.Two genes,STX6 and PDIA4,were established as lead causal genes for CJD,supported by robust evidence(False Discovery Rate<0.05 in MR analysis;PP4/(PP3+PP4)≥0.75 in Bayesian colocalization).Specifically,elevated levels of STX6 and PDIA4 were associated with an increased risk of CJD.Additionally,TWAS demonstrated that STX6 and PDIA4 were associated with CJD at the transcriptional level.
基金supported by the NSFC(12271141)supported by the Fundamental Research Funds for the Central Universities(B240205026)the Postgraduate Research and Practice Innovation Program of Jiangsu Province(KYCX24_0821).
文摘In this paper, we consider the existence of pullback random exponential attractor for non-autonomous random reaction-diffusion equation driven by nonlinear colored noise defined onR^(N) . The key steps of the proof are the tails estimate and to demonstrate the Lipschitz continuity and random squeezing property of the solution for the equation defined on R^(N) .
