To study the uncertainty quantification of resonant states in open quantum systems,we developed a Bayesian framework by integrating a reduced basis method(RBM)emulator with the Gamow coupled-channel(GCC)approach.The R...To study the uncertainty quantification of resonant states in open quantum systems,we developed a Bayesian framework by integrating a reduced basis method(RBM)emulator with the Gamow coupled-channel(GCC)approach.The RBM,constructed via eigenvector continuation and trained on both bound and resonant configurations,enables the fast and accurate emulation of resonance properties across the parameter space.To identify the physical resonant states from the emulator’s output,we introduce an overlap-based selection technique that effectively isolates true solutions from background artifacts.By applying this framework to unbound nucleus ^(6)Be,we quantified the model uncertainty in the predicted complex energies.The results demonstrate relative errors of 17.48%in the real part and 8.24%in the imaginary part,while achieving a speedup of four orders of magnitude compared with the full GCC calculations.To further investigate the asymptotic behavior of the resonant-state wavefunctions within the RBM framework,we employed a Lippmann–Schwinger(L–S)-based correction scheme.This approach not only improves the consistency between eigenvalues and wavefunctions but also enables a seamless extension from real-space training data to the complex energy plane.By bridging the gap between bound-state and continuum regimes,the L–S correction significantly enhances the emulator’s capability to accurately capture continuum structures in open quantum systems.展开更多
The incremental capacity analysis(ICA)technique is notably limited by its sensitivity to variations in charging conditions,which constrains its practical applicability in real-world scenarios.This paper introduces an ...The incremental capacity analysis(ICA)technique is notably limited by its sensitivity to variations in charging conditions,which constrains its practical applicability in real-world scenarios.This paper introduces an ICA-compensation technique to address this limitation and propose a generalized framework for assessing the state of health(SOH)of batteries based on ICA that is applicable under differing charging conditions.This novel approach calculates the voltage profile under quasi-static conditions by subtracting the voltage increase attributable to the additional polarization effects at high currents from the measured voltage profile.This approach's efficacy is contingent upon precisely acquiring the equivalent impedance.To obtain the equivalent impedance throughout the batteries'lifespan while minimizing testing costs,this study employs a current interrupt technique in conjunction with a long short-term memory(LSTM)network to develop a predictive model for equivalent impedance.Following the derivation of ICA curves using voltage profiles under quasi-static conditions,the research explores two scenarios for SOH estimation:one utilizing only incremental capacity(IC)features and the other incorporating both IC features and IC sampling.A genetic algorithm-optimized backpropagation neural network(GABPNN)is employed for the SOH estimation.The proposed generalized framework is validated using independent training and test datasets.Variable test conditions are applied for the test set to rigorously evaluate the methodology under challenging conditions.These evaluation results demonstrate that the proposed framework achieves an estimation accuracy of 1.04%for RMSE and 0.90%for MAPE across a spectrum of charging rates ranging from 0.1 C to 1 C and starting SOCs between 0%and 70%,which constitutes a major advancement compared to established ICA methods.It also significantly enhances the applicability of conventional ICA techniques in varying charging conditions and negates the necessity for separate testing protocols for each charging scenario.展开更多
Leveraging big data signal processing offers a pathway to the development of artificial intelligencedriven equipment.The analysis of fluid flow signals and the characterization of fluid flow behavior are of critical i...Leveraging big data signal processing offers a pathway to the development of artificial intelligencedriven equipment.The analysis of fluid flow signals and the characterization of fluid flow behavior are of critical in two-phase flow studies.Significant research efforts have focused on discerning flow regimes using various signal analysis methods.In this review,recent advances in time series signals analysis algorithms for stirred tank reactors have been summarized,and the detailed methodologies are categorized into the frequency domain methods,time-frequency domain methods,and state space methods.The strengths,limitations,and notable findings of each algorithm are highlighted.Additionally,the interrelationships between these methodologies have also been discussed,as well as the present progress achieved in various applications.Future research directions and challenges are also predicted to provide an overview of current research trends in data mining of time series for analyzing flow regimes and chaotic signals.This review offers a comprehensive summary for extracting and characterizing fluid flow behavior and serves as a theoretical reference for optimizing the characterization of chaotic signals in future research endeavors.展开更多
In the context of digitalization,course resources exhibit multimodal characteristics,covering various forms such as text,images,and videos.Course knowledge and learning resources are becoming increasingly diverse,prov...In the context of digitalization,course resources exhibit multimodal characteristics,covering various forms such as text,images,and videos.Course knowledge and learning resources are becoming increasingly diverse,providing favorable conditions for students’in-depth and efficient learning.Against this backdrop,how to scientifically apply emerging technologies to automatically collect,process,and integrate digital learning resources such as voices,videos,and courseware texts,and better innovate the organization and presentation forms of course knowledge has become an important development direction for“artificial intelligence+education.”This article elaborates on the elements and characteristics of knowledge graphs,analyzes the construction steps of knowledge graphs,and explores the construction methods of multimodal course knowledge graphs from aspects such as dataset collection,course knowledge ontology identification,knowledge discovery,and association,providing references for the intelligent application of online open courses.展开更多
Software systems are vulnerable to security breaches as they expand in complexity and functionality.The confidentiality,integrity,and availability of data are gravely threatened by flaws in a system’s design,implemen...Software systems are vulnerable to security breaches as they expand in complexity and functionality.The confidentiality,integrity,and availability of data are gravely threatened by flaws in a system’s design,implementation,or configuration.To guarantee the durability&robustness of the software,vulnerability identification and fixation have become crucial areas of focus for developers,cybersecurity experts and industries.This paper presents a thorough multi-phase mathematical model for efficient patch management and vulnerability detection.To uniquely model these processes,the model incorporated the notion of the learning phenomenon in describing vulnerability fixation using a logistic learning function.Furthermore,the authors have used numerical methods to approximate the solution of the proposed framework where an analytical solution is difficult to attain.The suggested systematic architecture has been demonstrated through statistical analysis using patch datasets,which offers a solid basis for the research conclusions.According to computational research,learning dynamics improves security response and results in more effective vulnerability management.The suggested model offers a systematic approach to proactive vulnerability mitigation and has important uses in risk assessment,software maintenance,and cybersecurity.This study helps create more robust software systems by increasing patch management effectiveness,which benefits developers,cybersecurity experts,and sectors looking to reduce security threats in a growing digital world.展开更多
This study explores a sensitivity analysis method based on the boundary element method(BEM)to address the computational complexity in acoustic analysis with ground reflection problems.The advantages of BEM in acoustic...This study explores a sensitivity analysis method based on the boundary element method(BEM)to address the computational complexity in acoustic analysis with ground reflection problems.The advantages of BEM in acoustic simulations and its high computational cost in broadband problems are examined.To improve efficiency,a Taylor series expansion is applied to decouple frequency-dependent terms in BEM.Additionally,the SecondOrder Arnoldi(SOAR)model order reduction method is integrated to reduce computational costs and enhance numerical stability.Furthermore,an isogeometric sensitivity boundary integral equation is formulated using the direct differentiation method,incorporating Cauchy principal value integrals and Hadamard finite part integrals to handle singularities.The proposed method improves the computational efficiency,and the acoustic sensitivity analysis provides theoretical support for further acoustic structure optimization.展开更多
BACKGROUND Meta-analysis is a critical tool in evidence-based medicine,particularly in cardiology,where it synthesizes data from multiple studies to inform clinical decisions.This study explored the potential of using...BACKGROUND Meta-analysis is a critical tool in evidence-based medicine,particularly in cardiology,where it synthesizes data from multiple studies to inform clinical decisions.This study explored the potential of using ChatGPT to streamline and enhance the meta-analysis process.AIM To investigate the potential of ChatGPT to conduct meta-analyses in interventional cardiology by comparing the results of ChatGPT-generated analyses with those of randomly selected,human-conducted meta-analyses on the same topic.METHODS We systematically searched PubMed for meta-analyses on interventional cardiology published in 2024.Five metaanalyses were randomly chosen.ChatGPT 4.0 was used to perform meta-analyses on the extracted data.We compared the results from ChatGPT with the original meta-analyses,focusing on key effect sizes,such as risk ratios(RR),hazard ratios,and odds ratios,along with their confidence intervals(CI)and P values.RESULTS The ChatGPT results showed high concordance with those of the original meta-analyses.For most outcomes,the effect measures and P values generated by ChatGPT closely matched those of the original studies,except for the RR of stent thrombosis in the Sreenivasan et al study,where ChatGPT reported a non-significant effect size,while the original study found it to be statistically significant.While minor discrepancies were observed in specific CI and P values,these differences did not alter the overall conclusions drawn from the analyses.CONCLUSION Our findings suggest the potential of ChatGPT in conducting meta-analyses in interventional cardiology.However,further research is needed to address the limitations of transparency and potential data quality issues,ensuring that AI-generated analyses are robust and trustworthy for clinical decision-making.展开更多
Six new lanthanide complexes:[Ln(3,4-DEOBA)3(4,4'-DM-2,2'-bipy)]2·2C_(2)H_(5)OH,[Ln=Dy(1),Eu(2),Tb(3),Sm(4),Ho(5),Gd(6);3,4-DEOBA-=3,4-diethoxybenzoate,4,4'-DM-2,2'-bipy=4,4'-dimethyl-2,2'...Six new lanthanide complexes:[Ln(3,4-DEOBA)3(4,4'-DM-2,2'-bipy)]2·2C_(2)H_(5)OH,[Ln=Dy(1),Eu(2),Tb(3),Sm(4),Ho(5),Gd(6);3,4-DEOBA-=3,4-diethoxybenzoate,4,4'-DM-2,2'-bipy=4,4'-dimethyl-2,2'-bipyridine]were successfully synthesized by the volatilization of the solution at room temperature.The crystal structures of six complexes were determined by single-crystal X-ray diffraction technology.The results showed that the complexes all have a binuclear structure,and the structures contain free ethanol molecules.Moreover,the coordination number of the central metal of each structural unit is eight.Adjacent structural units interact with each other through hydrogen bonds and further expand to form 1D chain-like and 2D planar structures.After conducting a systematic study on the luminescence properties of complexes 1-4,their emission and excitation spectra were obtained.Experimental results indicated that the fluorescence lifetimes of complexes 2 and 3 were 0.807 and 0.845 ms,respectively.The emission spectral data of complexes 1-4 were imported into the CIE chromaticity coordinate system,and their corre sponding luminescent regions cover the yellow light,red light,green light,and orange-red light bands,respectively.Within the temperature range of 299.15-1300 K,the thermal decomposition processes of the six complexes were comprehensively analyzed by using TG-DSC/FTIR/MS technology.The hypothesis of the gradual loss of ligand groups during the decomposition process was verified by detecting the escaped gas,3D infrared spectroscopy,and ion fragment information detected by mass spectrometry.The specific decomposition path is as follows:firstly,free ethanol molecules and neutral ligands are removed,and finally,acidic ligands are released;the final product is the corresponding metal oxide.CCDC:2430420,1;2430422,2;2430419,3;2430424,4;2430421,5;2430423,6.展开更多
Border-associated macrophages are located at the interface between the brain and the periphery, including the perivascular spaces, choroid plexus, and meninges. Until recently, the functions of border-associated macro...Border-associated macrophages are located at the interface between the brain and the periphery, including the perivascular spaces, choroid plexus, and meninges. Until recently, the functions of border-associated macrophages have been poorly understood and largely overlooked. However, a recent study reported that border-associated macrophages participate in stroke-induced inflammation, although many details and the underlying mechanisms remain unclear. In this study, we performed a comprehensive single-cell analysis of mouse border-associated macrophages using sequencing data obtained from the Gene Expression Omnibus(GEO) database(GSE174574 and GSE225948). Differentially expressed genes were identified, and enrichment analysis was performed to identify the transcription profile of border-associated macrophages. CellChat analysis was conducted to determine the cell communication network of border-associated macrophages. Transcription factors were predicted using the ‘pySCENIC' tool. We found that, in response to hypoxia, borderassociated macrophages underwent dynamic transcriptional changes and participated in the regulation of inflammatory-related pathways. Notably, the tumor necrosis factor pathway was activated by border-associated macrophages following ischemic stroke. The pySCENIC analysis indicated that the activity of signal transducer and activator of transcription 3(Stat3) was obviously upregulated in stroke, suggesting that Stat3 inhibition may be a promising strategy for treating border-associated macrophages-induced neuroinflammation. Finally, we constructed an animal model to investigate the effects of border-associated macrophages depletion following a stroke. Treatment with liposomes containing clodronate significantly reduced infarct volume in the animals and improved neurological scores compared with untreated animals. Taken together, our results demonstrate comprehensive changes in border-associated macrophages following a stroke, providing a theoretical basis for targeting border-associated macrophages-induced neuroinflammation in stroke treatment.展开更多
Background:The integration of intelligent healthcare technologies with traditional Chinese medicine(TCM)diagnostic practices holds significant potential to address longstanding challenges in subjectivity and standardi...Background:The integration of intelligent healthcare technologies with traditional Chinese medicine(TCM)diagnostic practices holds significant potential to address longstanding challenges in subjectivity and standardization;nevertheless,a systematic analysis of research trends,technological foci,and interdisciplinary collaboration within this field remains underexplored.Methods:This study employs bibliometric analysis to examine 497 articles(2003-2025)retrieved from Web of Science,PubMed,and CNKI.Visualization tools(VOSviewer and CiteSpace)were utilized to map research evolution,collaboration networks,and thematic clusters.Results:The analysis indicates a marked upsurge in research on this topic after 2019.Key research clusters identified through bibliometric analysis encompass AI-enabled pattern recognition,neural network architectures,algorithmic classification models,digital tongue image analysis,and computational syndrome differentiation frameworks.These clusters collectively address the subjectivity and standardization challenges inherent in TCM diagnosis.Conclusion:Intelligent healthcare technologies can significantly improve the accuracy,efficiency,and reproducibility of TCM diagnostic practices.Future work should foster international collaboration and develop multi-modal,clinically validated diagnostic models.展开更多
Background:Receptor-interacting protein kinases(RIPKs)regulate cell death,inflammation,and immune responses,yet their roles in cancer are not fully understood.This study investigates the expression,genomic alterations...Background:Receptor-interacting protein kinases(RIPKs)regulate cell death,inflammation,and immune responses,yet their roles in cancer are not fully understood.This study investigates the expression,genomic alterations,and functional implications of RIPK family members across various cancers.Methods:We collected multi-omics data from The Cancer Genome Atlas and other public databases,including gene expression,copy number variation(CNV),mutation,methylation,tumor mutation burden(TMB),and microsatellite instability(MSI).Differential expression and survival analyses were performed using DESeq2 and Cox proportional hazards models.CNV and mutation data were analyzed with GISTIC2 and Mutect2,and methylation data with the ChAMP package.Correlations with TMB and MSI were assessed using Pearson coefficients,and gene set enrichment analysis was conducted with the MSigDB Hallmark gene sets.Results:RIPK family members show significant differential expression in various cancers,with RIPK1 and RIPK4 frequently altered.Survival analysis reveals heterogeneous impacts on overall survival.CNV and mutation analyses identify high alteration frequencies for RIPK2 and RIPK7,affecting gene expression.RIPK1 and RIPK7 are hypermethylated in several cancers,inversely correlating with RIPK3 expression.RIPK1,RIPK2,RIPK5,RIPK6,and RIPK7 correlate positively with TMB,while RIPK3 shows negative correlations in some cancers.MSI analysis indicates associations with DNA mismatch repair.G ene set enrichment analysis highlights immune-related pathway enrichment for RIPK1,RIPK2,RIPK3,and RIPK6,and cell proliferation and DNA repair pathways for RIPK4 and RIPK5.RIPK family members showed heterogeneous alterations across cancers:for example,RIPK7 was mutated in up to~15%of u terine c orpus e ndometrial c arcinoma and l ung s quamous c ell c arcinoma cases,and RIPK1 and RIPK7 exhibited frequent promoter hypermethylation in multiple tumor types.Several genes displayed context-dependent associations with overall survival and with TMB/MSI.Conclusion:This pan-cancer analysis of the RIPK family reveals their diverse roles and potential as biomarkers and therapeutic targets.The findings emphasize the importance of RIPK genes in tumorigenesis and suggest context-dependent functions across cancer types.Further studies are needed to explore their mechanisms in cancer development and clinical applications.展开更多
The sulfation and decomposition process has proven effective in selectively extracting lithium from lepidolite.It is essential to clarify the thermochemical behavior and kinetic parameters of decomposition reactions.A...The sulfation and decomposition process has proven effective in selectively extracting lithium from lepidolite.It is essential to clarify the thermochemical behavior and kinetic parameters of decomposition reactions.Accordingly,comprehensive kinetic study by employing thermalgravimetric analysis at various heating rates was presented in this paper.Two main weight loss regions were observed during heating.The initial region corresponded to the dehydration of crystal water,whereas the subsequent region with overlapping peaks involved complex decomposition reactions.The overlapping peaks were separated into two individual reaction peaks and the activation energy of each peak was calculated using isoconversional kinetics methods.The activation energy of peak 1 exhibited a continual increase as the reaction conversion progressed,while that of peak 2 steadily decreased.The optimal kinetic models,identified as belonging to the random nucleation and subsequent growth category,provided valuable insights into the mechanism of the decomposition reactions.Furthermore,the adjustment factor was introduced to reconstruct the kinetic mechanism models,and the reconstructed models described the kinetic mechanism model more accurately for the decomposition reactions.This study enhanced the understanding of the thermochemical behavior and kinetic parameters of the lepidolite sulfation product decomposition reactions,further providing theoretical basis for promoting the selective extraction of lithium.展开更多
AIM:To present an overview of the research on global glaucoma treatment in the last decade in terms of publication year,journals,countries/regions,organizations,references,and keywords,to investigate the current resea...AIM:To present an overview of the research on global glaucoma treatment in the last decade in terms of publication year,journals,countries/regions,organizations,references,and keywords,to investigate the current research international trends and hot topics in this area.METHODS:Bibliometric analysis was conducted on 9128 articles in the Web of Science Core Collection(WoSCC;Clarivate)database.Quantitative and qualitative analysis was employed using VOSviewer(v1.6.18),Pajek(v1.0.0.0),and CiteSpace(v6.1.R2)software.RESULTS:The 9128 papers relating to glaucoma treatment were published from April 2013 to April 2023,of which 7482 articles(82%)were original research articles and 1464(18%)were review articles.The United States(2867)and Johns Hopkins University(166)were the most productive country and institution,respectively,but the University College London had the highest h-index(54).The Journal of Glaucoma was the most productive and Ophthalmology had the highest h-index compared with other journals.The Keywords of interest included treatment surgery,cyclophotocoagulation,minimally invasive glaucoma surgery(MIGS),trabeculectomy,baerveldt,epidemiology,medication adherence,nanoparticle,optical coherence tomography(OCT),gene therapy,and artificial intelligence(AI).Glaucoma surgery appeared as a current research hotspot through the analysis of keywords.CONCLUSION:This study provides insights into the research trends and potential research hotspots in the treatment of glaucoma.This will help researchers to evaluate research policies and to promote international cooperation.展开更多
This paper investigates the reliability of internal marine combustion engines using an integrated approach that combines Fault Tree Analysis(FTA)and Bayesian Networks(BN).FTA provides a structured,top-down method for ...This paper investigates the reliability of internal marine combustion engines using an integrated approach that combines Fault Tree Analysis(FTA)and Bayesian Networks(BN).FTA provides a structured,top-down method for identifying critical failure modes and their root causes,while BN introduces flexibility in probabilistic reasoning,enabling dynamic updates based on new evidence.This dual methodology overcomes the limitations of static FTA models,offering a comprehensive framework for system reliability analysis.Critical failures,including External Leakage(ELU),Failure to Start(FTS),and Overheating(OHE),were identified as key risks.By incorporating redundancy into high-risk components such as pumps and batteries,the likelihood of these failures was significantly reduced.For instance,redundant pumps reduced the probability of ELU by 31.88%,while additional batteries decreased the occurrence of FTS by 36.45%.The results underscore the practical benefits of combining FTA and BN for enhancing system reliability,particularly in maritime applications where operational safety and efficiency are critical.This research provides valuable insights for maintenance planning and highlights the importance of redundancy in critical systems,especially as the industry transitions toward more autonomous vessels.展开更多
To ensure the safe transportation of radioactive materials,numerous countries have established specific standards.For the transfer of fissile materials,it is imperative that the material within the packaging remains i...To ensure the safe transportation of radioactive materials,numerous countries have established specific standards.For the transfer of fissile materials,it is imperative that the material within the packaging remains in a subcritical state during routine,normal,and accidental transport conditions.In the event of an accident,the rods within the storage tank may become rearranged,introducing uncertainty that must be accounted for to ensure that criticality analysis results are conservative.Historically,this uncertainty was addressed overly conservatively due to limited research on non-uniform arrangement scenarios,which proved unsuitable for criticality safety analysis of spent fuel packages.This paper introduced three distinct methods to non-uniformly rearrange fuel rods—Uniform Arrangement by Blocks,Layer-by-Layer Determination,and Birdcage Deformation—and meticulously evaluates the influences of rod rearrangement on the effective multiplication factor of neutrons,k eff,utilizing the Monte Carlo method.Ultimately,this study presents a holistic method capable of encompassing the entire spectrum of potential effects stemming from the rearrangement of fuel rods during rods mispositioning accident.By augmenting the safety margin,this approach proves to be adeptly suited for the criticality safety analysis of nuclear fuel transport containers.展开更多
Industrial waste salts are commonly used to make value-added snow-melting agents to ensure traffic safety in northern China during winter and spring after snowfall.However,heavy metals in industrial waste salts may po...Industrial waste salts are commonly used to make value-added snow-melting agents to ensure traffic safety in northern China during winter and spring after snowfall.However,heavy metals in industrial waste salts may pose certain environmental risks.Snow-melting agents and snow samples were collected and analyzed from highways,arterial roads,footbridges,and other locations in Beijing after the snowstorm in December 2023.It was found that the main component of snow-melting agents was sodium chloride with high concentrations of Cu,Mn,and Zn,which are not regulated in the current policies,despite the recent promotion of environmentally friendly snow-melting agents.The Pb,Zn and Cr contents of some snow samples exceeded the limitation value of surface water quality standards,potentially affecting the soil and water environment near roadsides,although the snow-melting agents comply with relevant standards,which indicates the policy gap in the management of recycled industrial salts.We reviewed and analyzed the relevant standards for snow-melting agents and industrial waste salts proposed nationally and internationally over the past 30 years.Through comparative analysis,we proposed relevant policy recommendations to the existing quality standards of snow-melting agents and the management regulations of industrial waste salts,and the formulation of corresponding usage strategies,aimed at reducing the potential environmental release of heavy metals from the use of snow-melting agents,thereby promoting more sustainable green urban development and environmentally sound waste management.展开更多
Background:Epidemiological studies have confirmed that longer exposure to insecticides like cypermethrin(CYP)significantly increases the risk of male reproductive toxicity.Crocus sativus L.has been recognized due to i...Background:Epidemiological studies have confirmed that longer exposure to insecticides like cypermethrin(CYP)significantly increases the risk of male reproductive toxicity.Crocus sativus L.has been recognized due to its therapeutic properties,but its exact role and molecular mechanisms in treatment of reproductive dysfunction remain unclear.Methods:During this study,36 rats were randomly divided into six groups(n=6):control,CYP-induced(60 mg/kg),standard(leuprolide 3 mg/kg)and three treatment groups receiving aqueous,ethanolic,and oil extracts(50 mg/kg or 20 mL/kg)for post-toxicity induction.Results:The finding represented that exposure of CYP significantly increased oxidative stress,disrupted testicular architecture,and markedly reduced testosterone levels(P<0.05).Importantly,Crocus sativus L.treatment alleviated these changes by increasing the expression of Nrf2(nuclear factor erythroid 2-related factor 2),restoring the activity of antioxidant enzymes,and enhancing testicular histomorphology.Surprisingly,molecular docking established a high binding affinity of Crocus sativus L.phytoconstituents such as gallic acid,cinnamic acid and quercetin to the Nrf2-Keap1 complex.It is worth noting that,Crocus sativus L.exhibited a high level of protection against reproductive toxicity caused by CYP in male rats,which was mediated by the activation of Nrf2 pathway,reduction of oxidative damage,and favorable ADMET characteristics.Conclusion:Notably,this research provides a more valid,safe,and effective method of developing new drugs for reproductive disorders,however,further investigation is needed to support the research findings and implement it in clinical practice.展开更多
In mineral exploration, the apparent resistivity and apparent frequency （or apparent polarizability） parameters of induced polarization method are commonly utilized to describe the induced polarization anomaly. When...In mineral exploration, the apparent resistivity and apparent frequency （or apparent polarizability） parameters of induced polarization method are commonly utilized to describe the induced polarization anomaly. When the target geology structure is significantly complicated, these parameters would fail to reflect the nature of the anomaly source, and wrong conclusions may be obtained. A wavelet approach and a metal factor method were used to comprehensively interpret the induced polarization anomaly of complex geologic bodies in the Adi Bladia mine. Db5 wavelet basis was used to conduct two-scale decomposition and reconstruction, which effectively suppress the noise interference of greenschist facies regional metamorphism and magma intrusion, making energy concentrated and boundary problem unobservable. On the basis of that, the ore-induced anomaly was effectively extracted by the metal factor method.展开更多
The purpose of this study is to apply some statistical and soft computing methods such as Fisher discriminant analysis （FDA） and support vector machines （SVMs） methodology to the determination of pillar stability ...The purpose of this study is to apply some statistical and soft computing methods such as Fisher discriminant analysis （FDA） and support vector machines （SVMs） methodology to the determination of pillar stability for underground mines selected from various coal and stone mines by using some index and mechanical properties, including the width, the height, the ratio of the pillar width to its height, the uniaxial compressive strength of the rock and pillar stress. The study includes four main stages： sampling, testing, modeling and assessment of the model performances. During the modeling stage, two pillar stability prediction models were investigated with FDA and SVMs methodology based on the statistical learning theory. After using 40 sets of measured data in various mines in the world for training and testing, the model was applied to other 6 data for validating the trained proposed models. The prediction results of SVMs were compared with those of FDA as well as the measured field values. The general performance of models developed in this study is close; however, the SVMs exhibit the best performance considering the performance index with the correct classification rate Prs by re-substitution method and Pcv by cross validation method. The results show that the SVMs approach has the potential to be a reliable and practical tool for determination of pillar stability for underground mines.展开更多
基金supported by the National Key Research and Development Program(MOST 2023YFA1606404 and MOST 2022YFA1602303)the National Natural Science Foundation of China(Nos.12347106,12147101,and 12447122)the China Postdoctoral Science Foundation(No.2024M760489).
文摘To study the uncertainty quantification of resonant states in open quantum systems,we developed a Bayesian framework by integrating a reduced basis method(RBM)emulator with the Gamow coupled-channel(GCC)approach.The RBM,constructed via eigenvector continuation and trained on both bound and resonant configurations,enables the fast and accurate emulation of resonance properties across the parameter space.To identify the physical resonant states from the emulator’s output,we introduce an overlap-based selection technique that effectively isolates true solutions from background artifacts.By applying this framework to unbound nucleus ^(6)Be,we quantified the model uncertainty in the predicted complex energies.The results demonstrate relative errors of 17.48%in the real part and 8.24%in the imaginary part,while achieving a speedup of four orders of magnitude compared with the full GCC calculations.To further investigate the asymptotic behavior of the resonant-state wavefunctions within the RBM framework,we employed a Lippmann–Schwinger(L–S)-based correction scheme.This approach not only improves the consistency between eigenvalues and wavefunctions but also enables a seamless extension from real-space training data to the complex energy plane.By bridging the gap between bound-state and continuum regimes,the L–S correction significantly enhances the emulator’s capability to accurately capture continuum structures in open quantum systems.
基金funded by the Bavarian State Ministry of ScienceResearch and Art(Grant number:H.2-F1116.WE/52/2)。
文摘The incremental capacity analysis(ICA)technique is notably limited by its sensitivity to variations in charging conditions,which constrains its practical applicability in real-world scenarios.This paper introduces an ICA-compensation technique to address this limitation and propose a generalized framework for assessing the state of health(SOH)of batteries based on ICA that is applicable under differing charging conditions.This novel approach calculates the voltage profile under quasi-static conditions by subtracting the voltage increase attributable to the additional polarization effects at high currents from the measured voltage profile.This approach's efficacy is contingent upon precisely acquiring the equivalent impedance.To obtain the equivalent impedance throughout the batteries'lifespan while minimizing testing costs,this study employs a current interrupt technique in conjunction with a long short-term memory(LSTM)network to develop a predictive model for equivalent impedance.Following the derivation of ICA curves using voltage profiles under quasi-static conditions,the research explores two scenarios for SOH estimation:one utilizing only incremental capacity(IC)features and the other incorporating both IC features and IC sampling.A genetic algorithm-optimized backpropagation neural network(GABPNN)is employed for the SOH estimation.The proposed generalized framework is validated using independent training and test datasets.Variable test conditions are applied for the test set to rigorously evaluate the methodology under challenging conditions.These evaluation results demonstrate that the proposed framework achieves an estimation accuracy of 1.04%for RMSE and 0.90%for MAPE across a spectrum of charging rates ranging from 0.1 C to 1 C and starting SOCs between 0%and 70%,which constitutes a major advancement compared to established ICA methods.It also significantly enhances the applicability of conventional ICA techniques in varying charging conditions and negates the necessity for separate testing protocols for each charging scenario.
基金the National Natural Science Foundation of China(22078030)the National Key Research and Development Project(2019YFC1905802,2022YFB3504305)+1 种基金the Joint Funds of the National Natural Science Foundation of China(U1802255,CSTB2022NSCQ-LZX0014)the Key Project of Independent Research Project of State Key Laboratory of Coal Mine Disaster Dynamics and Control(2011DA105287-zd201902).
文摘Leveraging big data signal processing offers a pathway to the development of artificial intelligencedriven equipment.The analysis of fluid flow signals and the characterization of fluid flow behavior are of critical in two-phase flow studies.Significant research efforts have focused on discerning flow regimes using various signal analysis methods.In this review,recent advances in time series signals analysis algorithms for stirred tank reactors have been summarized,and the detailed methodologies are categorized into the frequency domain methods,time-frequency domain methods,and state space methods.The strengths,limitations,and notable findings of each algorithm are highlighted.Additionally,the interrelationships between these methodologies have also been discussed,as well as the present progress achieved in various applications.Future research directions and challenges are also predicted to provide an overview of current research trends in data mining of time series for analyzing flow regimes and chaotic signals.This review offers a comprehensive summary for extracting and characterizing fluid flow behavior and serves as a theoretical reference for optimizing the characterization of chaotic signals in future research endeavors.
基金University-level Scientific Research Project in Natural Sciences“Research on the Retrieval Method of Multimodal First-Class Course Teaching Content Based on Knowledge Graph Collaboration”(GKY-2024KYYBK-31)。
文摘In the context of digitalization,course resources exhibit multimodal characteristics,covering various forms such as text,images,and videos.Course knowledge and learning resources are becoming increasingly diverse,providing favorable conditions for students’in-depth and efficient learning.Against this backdrop,how to scientifically apply emerging technologies to automatically collect,process,and integrate digital learning resources such as voices,videos,and courseware texts,and better innovate the organization and presentation forms of course knowledge has become an important development direction for“artificial intelligence+education.”This article elaborates on the elements and characteristics of knowledge graphs,analyzes the construction steps of knowledge graphs,and explores the construction methods of multimodal course knowledge graphs from aspects such as dataset collection,course knowledge ontology identification,knowledge discovery,and association,providing references for the intelligent application of online open courses.
基金supported by grants received by the first author and third author from the Institute of Eminence,Delhi University,Delhi,India,as part of the Faculty Research Program via Ref.No./IoE/2024-25/12/FRP.
文摘Software systems are vulnerable to security breaches as they expand in complexity and functionality.The confidentiality,integrity,and availability of data are gravely threatened by flaws in a system’s design,implementation,or configuration.To guarantee the durability&robustness of the software,vulnerability identification and fixation have become crucial areas of focus for developers,cybersecurity experts and industries.This paper presents a thorough multi-phase mathematical model for efficient patch management and vulnerability detection.To uniquely model these processes,the model incorporated the notion of the learning phenomenon in describing vulnerability fixation using a logistic learning function.Furthermore,the authors have used numerical methods to approximate the solution of the proposed framework where an analytical solution is difficult to attain.The suggested systematic architecture has been demonstrated through statistical analysis using patch datasets,which offers a solid basis for the research conclusions.According to computational research,learning dynamics improves security response and results in more effective vulnerability management.The suggested model offers a systematic approach to proactive vulnerability mitigation and has important uses in risk assessment,software maintenance,and cybersecurity.This study helps create more robust software systems by increasing patch management effectiveness,which benefits developers,cybersecurity experts,and sectors looking to reduce security threats in a growing digital world.
基金supported by the Shanxi Scholarship Council of China(Grant No.2023-036)the Natural Science Foundation of Shanxi Province(Grant No.202303021222020).
文摘This study explores a sensitivity analysis method based on the boundary element method(BEM)to address the computational complexity in acoustic analysis with ground reflection problems.The advantages of BEM in acoustic simulations and its high computational cost in broadband problems are examined.To improve efficiency,a Taylor series expansion is applied to decouple frequency-dependent terms in BEM.Additionally,the SecondOrder Arnoldi(SOAR)model order reduction method is integrated to reduce computational costs and enhance numerical stability.Furthermore,an isogeometric sensitivity boundary integral equation is formulated using the direct differentiation method,incorporating Cauchy principal value integrals and Hadamard finite part integrals to handle singularities.The proposed method improves the computational efficiency,and the acoustic sensitivity analysis provides theoretical support for further acoustic structure optimization.
文摘BACKGROUND Meta-analysis is a critical tool in evidence-based medicine,particularly in cardiology,where it synthesizes data from multiple studies to inform clinical decisions.This study explored the potential of using ChatGPT to streamline and enhance the meta-analysis process.AIM To investigate the potential of ChatGPT to conduct meta-analyses in interventional cardiology by comparing the results of ChatGPT-generated analyses with those of randomly selected,human-conducted meta-analyses on the same topic.METHODS We systematically searched PubMed for meta-analyses on interventional cardiology published in 2024.Five metaanalyses were randomly chosen.ChatGPT 4.0 was used to perform meta-analyses on the extracted data.We compared the results from ChatGPT with the original meta-analyses,focusing on key effect sizes,such as risk ratios(RR),hazard ratios,and odds ratios,along with their confidence intervals(CI)and P values.RESULTS The ChatGPT results showed high concordance with those of the original meta-analyses.For most outcomes,the effect measures and P values generated by ChatGPT closely matched those of the original studies,except for the RR of stent thrombosis in the Sreenivasan et al study,where ChatGPT reported a non-significant effect size,while the original study found it to be statistically significant.While minor discrepancies were observed in specific CI and P values,these differences did not alter the overall conclusions drawn from the analyses.CONCLUSION Our findings suggest the potential of ChatGPT in conducting meta-analyses in interventional cardiology.However,further research is needed to address the limitations of transparency and potential data quality issues,ensuring that AI-generated analyses are robust and trustworthy for clinical decision-making.
文摘Six new lanthanide complexes:[Ln(3,4-DEOBA)3(4,4'-DM-2,2'-bipy)]2·2C_(2)H_(5)OH,[Ln=Dy(1),Eu(2),Tb(3),Sm(4),Ho(5),Gd(6);3,4-DEOBA-=3,4-diethoxybenzoate,4,4'-DM-2,2'-bipy=4,4'-dimethyl-2,2'-bipyridine]were successfully synthesized by the volatilization of the solution at room temperature.The crystal structures of six complexes were determined by single-crystal X-ray diffraction technology.The results showed that the complexes all have a binuclear structure,and the structures contain free ethanol molecules.Moreover,the coordination number of the central metal of each structural unit is eight.Adjacent structural units interact with each other through hydrogen bonds and further expand to form 1D chain-like and 2D planar structures.After conducting a systematic study on the luminescence properties of complexes 1-4,their emission and excitation spectra were obtained.Experimental results indicated that the fluorescence lifetimes of complexes 2 and 3 were 0.807 and 0.845 ms,respectively.The emission spectral data of complexes 1-4 were imported into the CIE chromaticity coordinate system,and their corre sponding luminescent regions cover the yellow light,red light,green light,and orange-red light bands,respectively.Within the temperature range of 299.15-1300 K,the thermal decomposition processes of the six complexes were comprehensively analyzed by using TG-DSC/FTIR/MS technology.The hypothesis of the gradual loss of ligand groups during the decomposition process was verified by detecting the escaped gas,3D infrared spectroscopy,and ion fragment information detected by mass spectrometry.The specific decomposition path is as follows:firstly,free ethanol molecules and neutral ligands are removed,and finally,acidic ligands are released;the final product is the corresponding metal oxide.CCDC:2430420,1;2430422,2;2430419,3;2430424,4;2430421,5;2430423,6.
基金supported by Qingdao Key Medical and Health Discipline ProjectThe Intramural Research Program of the Affiliated Hospital of Qingdao University,No. 4910Qingdao West Coast New Area Science and Technology Project,No. 2020-55 (all to SW)。
文摘Border-associated macrophages are located at the interface between the brain and the periphery, including the perivascular spaces, choroid plexus, and meninges. Until recently, the functions of border-associated macrophages have been poorly understood and largely overlooked. However, a recent study reported that border-associated macrophages participate in stroke-induced inflammation, although many details and the underlying mechanisms remain unclear. In this study, we performed a comprehensive single-cell analysis of mouse border-associated macrophages using sequencing data obtained from the Gene Expression Omnibus(GEO) database(GSE174574 and GSE225948). Differentially expressed genes were identified, and enrichment analysis was performed to identify the transcription profile of border-associated macrophages. CellChat analysis was conducted to determine the cell communication network of border-associated macrophages. Transcription factors were predicted using the ‘pySCENIC' tool. We found that, in response to hypoxia, borderassociated macrophages underwent dynamic transcriptional changes and participated in the regulation of inflammatory-related pathways. Notably, the tumor necrosis factor pathway was activated by border-associated macrophages following ischemic stroke. The pySCENIC analysis indicated that the activity of signal transducer and activator of transcription 3(Stat3) was obviously upregulated in stroke, suggesting that Stat3 inhibition may be a promising strategy for treating border-associated macrophages-induced neuroinflammation. Finally, we constructed an animal model to investigate the effects of border-associated macrophages depletion following a stroke. Treatment with liposomes containing clodronate significantly reduced infarct volume in the animals and improved neurological scores compared with untreated animals. Taken together, our results demonstrate comprehensive changes in border-associated macrophages following a stroke, providing a theoretical basis for targeting border-associated macrophages-induced neuroinflammation in stroke treatment.
基金supported by National Key R&D Program of China(2022YFC3502300)the Fundamental Research Funds for the Central public welfare research institutes(Z0876).
文摘Background:The integration of intelligent healthcare technologies with traditional Chinese medicine(TCM)diagnostic practices holds significant potential to address longstanding challenges in subjectivity and standardization;nevertheless,a systematic analysis of research trends,technological foci,and interdisciplinary collaboration within this field remains underexplored.Methods:This study employs bibliometric analysis to examine 497 articles(2003-2025)retrieved from Web of Science,PubMed,and CNKI.Visualization tools(VOSviewer and CiteSpace)were utilized to map research evolution,collaboration networks,and thematic clusters.Results:The analysis indicates a marked upsurge in research on this topic after 2019.Key research clusters identified through bibliometric analysis encompass AI-enabled pattern recognition,neural network architectures,algorithmic classification models,digital tongue image analysis,and computational syndrome differentiation frameworks.These clusters collectively address the subjectivity and standardization challenges inherent in TCM diagnosis.Conclusion:Intelligent healthcare technologies can significantly improve the accuracy,efficiency,and reproducibility of TCM diagnostic practices.Future work should foster international collaboration and develop multi-modal,clinically validated diagnostic models.
基金supported by grants from the Tianjin Health Technology Project(Grant no.2022QN106).
文摘Background:Receptor-interacting protein kinases(RIPKs)regulate cell death,inflammation,and immune responses,yet their roles in cancer are not fully understood.This study investigates the expression,genomic alterations,and functional implications of RIPK family members across various cancers.Methods:We collected multi-omics data from The Cancer Genome Atlas and other public databases,including gene expression,copy number variation(CNV),mutation,methylation,tumor mutation burden(TMB),and microsatellite instability(MSI).Differential expression and survival analyses were performed using DESeq2 and Cox proportional hazards models.CNV and mutation data were analyzed with GISTIC2 and Mutect2,and methylation data with the ChAMP package.Correlations with TMB and MSI were assessed using Pearson coefficients,and gene set enrichment analysis was conducted with the MSigDB Hallmark gene sets.Results:RIPK family members show significant differential expression in various cancers,with RIPK1 and RIPK4 frequently altered.Survival analysis reveals heterogeneous impacts on overall survival.CNV and mutation analyses identify high alteration frequencies for RIPK2 and RIPK7,affecting gene expression.RIPK1 and RIPK7 are hypermethylated in several cancers,inversely correlating with RIPK3 expression.RIPK1,RIPK2,RIPK5,RIPK6,and RIPK7 correlate positively with TMB,while RIPK3 shows negative correlations in some cancers.MSI analysis indicates associations with DNA mismatch repair.G ene set enrichment analysis highlights immune-related pathway enrichment for RIPK1,RIPK2,RIPK3,and RIPK6,and cell proliferation and DNA repair pathways for RIPK4 and RIPK5.RIPK family members showed heterogeneous alterations across cancers:for example,RIPK7 was mutated in up to~15%of u terine c orpus e ndometrial c arcinoma and l ung s quamous c ell c arcinoma cases,and RIPK1 and RIPK7 exhibited frequent promoter hypermethylation in multiple tumor types.Several genes displayed context-dependent associations with overall survival and with TMB/MSI.Conclusion:This pan-cancer analysis of the RIPK family reveals their diverse roles and potential as biomarkers and therapeutic targets.The findings emphasize the importance of RIPK genes in tumorigenesis and suggest context-dependent functions across cancer types.Further studies are needed to explore their mechanisms in cancer development and clinical applications.
基金financially supported by the National Natural Science Foundation of China(Nos.52034002 and U2202254)the Fundamental Research Funds for the Central Universities,China(No.FRF-TT-19-001)。
文摘The sulfation and decomposition process has proven effective in selectively extracting lithium from lepidolite.It is essential to clarify the thermochemical behavior and kinetic parameters of decomposition reactions.Accordingly,comprehensive kinetic study by employing thermalgravimetric analysis at various heating rates was presented in this paper.Two main weight loss regions were observed during heating.The initial region corresponded to the dehydration of crystal water,whereas the subsequent region with overlapping peaks involved complex decomposition reactions.The overlapping peaks were separated into two individual reaction peaks and the activation energy of each peak was calculated using isoconversional kinetics methods.The activation energy of peak 1 exhibited a continual increase as the reaction conversion progressed,while that of peak 2 steadily decreased.The optimal kinetic models,identified as belonging to the random nucleation and subsequent growth category,provided valuable insights into the mechanism of the decomposition reactions.Furthermore,the adjustment factor was introduced to reconstruct the kinetic mechanism models,and the reconstructed models described the kinetic mechanism model more accurately for the decomposition reactions.This study enhanced the understanding of the thermochemical behavior and kinetic parameters of the lepidolite sulfation product decomposition reactions,further providing theoretical basis for promoting the selective extraction of lithium.
基金Suppotred by Tianjin Key Medical Discipline Construction Project(No.TJYXZDXK-3-004A-2).
文摘AIM:To present an overview of the research on global glaucoma treatment in the last decade in terms of publication year,journals,countries/regions,organizations,references,and keywords,to investigate the current research international trends and hot topics in this area.METHODS:Bibliometric analysis was conducted on 9128 articles in the Web of Science Core Collection(WoSCC;Clarivate)database.Quantitative and qualitative analysis was employed using VOSviewer(v1.6.18),Pajek(v1.0.0.0),and CiteSpace(v6.1.R2)software.RESULTS:The 9128 papers relating to glaucoma treatment were published from April 2013 to April 2023,of which 7482 articles(82%)were original research articles and 1464(18%)were review articles.The United States(2867)and Johns Hopkins University(166)were the most productive country and institution,respectively,but the University College London had the highest h-index(54).The Journal of Glaucoma was the most productive and Ophthalmology had the highest h-index compared with other journals.The Keywords of interest included treatment surgery,cyclophotocoagulation,minimally invasive glaucoma surgery(MIGS),trabeculectomy,baerveldt,epidemiology,medication adherence,nanoparticle,optical coherence tomography(OCT),gene therapy,and artificial intelligence(AI).Glaucoma surgery appeared as a current research hotspot through the analysis of keywords.CONCLUSION:This study provides insights into the research trends and potential research hotspots in the treatment of glaucoma.This will help researchers to evaluate research policies and to promote international cooperation.
基金supported by Istanbul Technical University(Project No.45698)supported through the“Young Researchers’Career Development Project-training of doctoral students”of the Croatian Science Foundation.
文摘This paper investigates the reliability of internal marine combustion engines using an integrated approach that combines Fault Tree Analysis(FTA)and Bayesian Networks(BN).FTA provides a structured,top-down method for identifying critical failure modes and their root causes,while BN introduces flexibility in probabilistic reasoning,enabling dynamic updates based on new evidence.This dual methodology overcomes the limitations of static FTA models,offering a comprehensive framework for system reliability analysis.Critical failures,including External Leakage(ELU),Failure to Start(FTS),and Overheating(OHE),were identified as key risks.By incorporating redundancy into high-risk components such as pumps and batteries,the likelihood of these failures was significantly reduced.For instance,redundant pumps reduced the probability of ELU by 31.88%,while additional batteries decreased the occurrence of FTS by 36.45%.The results underscore the practical benefits of combining FTA and BN for enhancing system reliability,particularly in maritime applications where operational safety and efficiency are critical.This research provides valuable insights for maintenance planning and highlights the importance of redundancy in critical systems,especially as the industry transitions toward more autonomous vessels.
文摘To ensure the safe transportation of radioactive materials,numerous countries have established specific standards.For the transfer of fissile materials,it is imperative that the material within the packaging remains in a subcritical state during routine,normal,and accidental transport conditions.In the event of an accident,the rods within the storage tank may become rearranged,introducing uncertainty that must be accounted for to ensure that criticality analysis results are conservative.Historically,this uncertainty was addressed overly conservatively due to limited research on non-uniform arrangement scenarios,which proved unsuitable for criticality safety analysis of spent fuel packages.This paper introduced three distinct methods to non-uniformly rearrange fuel rods—Uniform Arrangement by Blocks,Layer-by-Layer Determination,and Birdcage Deformation—and meticulously evaluates the influences of rod rearrangement on the effective multiplication factor of neutrons,k eff,utilizing the Monte Carlo method.Ultimately,this study presents a holistic method capable of encompassing the entire spectrum of potential effects stemming from the rearrangement of fuel rods during rods mispositioning accident.By augmenting the safety margin,this approach proves to be adeptly suited for the criticality safety analysis of nuclear fuel transport containers.
基金supported by the National Natural Science Foundation of China(No.22176200)the Industrial Innovation Entrepreneurial Team Project of Ordos 2021.
文摘Industrial waste salts are commonly used to make value-added snow-melting agents to ensure traffic safety in northern China during winter and spring after snowfall.However,heavy metals in industrial waste salts may pose certain environmental risks.Snow-melting agents and snow samples were collected and analyzed from highways,arterial roads,footbridges,and other locations in Beijing after the snowstorm in December 2023.It was found that the main component of snow-melting agents was sodium chloride with high concentrations of Cu,Mn,and Zn,which are not regulated in the current policies,despite the recent promotion of environmentally friendly snow-melting agents.The Pb,Zn and Cr contents of some snow samples exceeded the limitation value of surface water quality standards,potentially affecting the soil and water environment near roadsides,although the snow-melting agents comply with relevant standards,which indicates the policy gap in the management of recycled industrial salts.We reviewed and analyzed the relevant standards for snow-melting agents and industrial waste salts proposed nationally and internationally over the past 30 years.Through comparative analysis,we proposed relevant policy recommendations to the existing quality standards of snow-melting agents and the management regulations of industrial waste salts,and the formulation of corresponding usage strategies,aimed at reducing the potential environmental release of heavy metals from the use of snow-melting agents,thereby promoting more sustainable green urban development and environmentally sound waste management.
文摘Background:Epidemiological studies have confirmed that longer exposure to insecticides like cypermethrin(CYP)significantly increases the risk of male reproductive toxicity.Crocus sativus L.has been recognized due to its therapeutic properties,but its exact role and molecular mechanisms in treatment of reproductive dysfunction remain unclear.Methods:During this study,36 rats were randomly divided into six groups(n=6):control,CYP-induced(60 mg/kg),standard(leuprolide 3 mg/kg)and three treatment groups receiving aqueous,ethanolic,and oil extracts(50 mg/kg or 20 mL/kg)for post-toxicity induction.Results:The finding represented that exposure of CYP significantly increased oxidative stress,disrupted testicular architecture,and markedly reduced testosterone levels(P<0.05).Importantly,Crocus sativus L.treatment alleviated these changes by increasing the expression of Nrf2(nuclear factor erythroid 2-related factor 2),restoring the activity of antioxidant enzymes,and enhancing testicular histomorphology.Surprisingly,molecular docking established a high binding affinity of Crocus sativus L.phytoconstituents such as gallic acid,cinnamic acid and quercetin to the Nrf2-Keap1 complex.It is worth noting that,Crocus sativus L.exhibited a high level of protection against reproductive toxicity caused by CYP in male rats,which was mediated by the activation of Nrf2 pathway,reduction of oxidative damage,and favorable ADMET characteristics.Conclusion:Notably,this research provides a more valid,safe,and effective method of developing new drugs for reproductive disorders,however,further investigation is needed to support the research findings and implement it in clinical practice.
基金Project(41174103)supported by the National Natural Science Foundation of ChinaProject(2010-211)supported by the Foreign Mineral Resources Venture Exploration Special Fund of China
文摘In mineral exploration, the apparent resistivity and apparent frequency （or apparent polarizability） parameters of induced polarization method are commonly utilized to describe the induced polarization anomaly. When the target geology structure is significantly complicated, these parameters would fail to reflect the nature of the anomaly source, and wrong conclusions may be obtained. A wavelet approach and a metal factor method were used to comprehensively interpret the induced polarization anomaly of complex geologic bodies in the Adi Bladia mine. Db5 wavelet basis was used to conduct two-scale decomposition and reconstruction, which effectively suppress the noise interference of greenschist facies regional metamorphism and magma intrusion, making energy concentrated and boundary problem unobservable. On the basis of that, the ore-induced anomaly was effectively extracted by the metal factor method.
基金Project (50934006) supported by the National Natural Science Foundation of ChinaProject (2010CB732004) supported by the National Basic Research Program of ChinaProject (CX2011B119) supported by the Graduated Students’ Research and Innovation Fund Project of Hunan Province of China
文摘The purpose of this study is to apply some statistical and soft computing methods such as Fisher discriminant analysis （FDA） and support vector machines （SVMs） methodology to the determination of pillar stability for underground mines selected from various coal and stone mines by using some index and mechanical properties, including the width, the height, the ratio of the pillar width to its height, the uniaxial compressive strength of the rock and pillar stress. The study includes four main stages： sampling, testing, modeling and assessment of the model performances. During the modeling stage, two pillar stability prediction models were investigated with FDA and SVMs methodology based on the statistical learning theory. After using 40 sets of measured data in various mines in the world for training and testing, the model was applied to other 6 data for validating the trained proposed models. The prediction results of SVMs were compared with those of FDA as well as the measured field values. The general performance of models developed in this study is close; however, the SVMs exhibit the best performance considering the performance index with the correct classification rate Prs by re-substitution method and Pcv by cross validation method. The results show that the SVMs approach has the potential to be a reliable and practical tool for determination of pillar stability for underground mines.
