The three-dimensional spectral analysis method was applied to airglow data from September 2023 to August 2024 derivedfrom an OH airglow imager located at the Hejing station (42.79°N, 83.73°E) to study the pr...The three-dimensional spectral analysis method was applied to airglow data from September 2023 to August 2024 derivedfrom an OH airglow imager located at the Hejing station (42.79°N, 83.73°E) to study the propagation characteristics of gravity waves(GWs) over Northwest China. We found that obvious seasonal variations occur in the propagation of GWs. In spring, GWs mainlypropagate in the northeast direction. In summer and autumn, GWs mainly propagate in the north direction. However, GWs mainlypropagate in the south direction in winter. The direction of GW propagation in the zonal direction is controlled by the wind-filteringeffect, whereas the north–south meridional direction is mainly determined by the location of the wave source. We found that the averageenergy spectrum exhibits a 10%–20% higher intensity in summer and winter compared with spring and autumn. For the first time, wereport the seasonal variation characteristics of GWs over the inland areas of Northwest China, which is of great significance forunderstanding the regional distribution characteristics of GWs.展开更多
DNA microarray technology is an extremely effective technique for studying gene expression patterns in cells, and the main challenge currently faced by this technology is how to analyze the large amount of gene expres...DNA microarray technology is an extremely effective technique for studying gene expression patterns in cells, and the main challenge currently faced by this technology is how to analyze the large amount of gene expression data generated. To address this, this paper employs a mixed-effects model to analyze gene expression data. In terms of data selection, 1176 genes from the white mouse gene expression dataset under two experimental conditions were chosen, setting up two conditions: pneumococcal infection and no infection, and constructing a mixed-effects model. After preprocessing the gene chip information, the data were imported into the model, preliminary results were calculated, and permutation tests were performed to biologically validate the preliminary results using GSEA. The final dataset consists of 20 groups of gene expression data from pneumococcal infection, which categorizes functionally related genes based on the similarity of their expression profiles, facilitating the study of genes with unknown functions.展开更多
With the advent of the big data era,real-time data analysis and decision-support systems have been recognized as essential tools for enhancing enterprise competitiveness and optimizing the decision-making process.This...With the advent of the big data era,real-time data analysis and decision-support systems have been recognized as essential tools for enhancing enterprise competitiveness and optimizing the decision-making process.This study aims to explore the development strategies of real-time data analysis and decision-support systems,and analyze their application status and future development trends in various industries.The article first reviews the basic concepts and importance of real-time data analysis and decision-support systems,and then discusses in detail the key technical aspects such as system architecture,data collection and processing,analysis methods,and visualization techniques.展开更多
This paper analyzes the advantages of legal digital currencies and explores their impact on bank big data practices.By combining bank big data collection and processing,it clarifies that legal digital currencies can e...This paper analyzes the advantages of legal digital currencies and explores their impact on bank big data practices.By combining bank big data collection and processing,it clarifies that legal digital currencies can enhance the efficiency of bank data processing,enrich data types,and strengthen data analysis and application capabilities.In response to future development needs,it is necessary to strengthen data collection management,enhance data processing capabilities,innovate big data application models,and provide references for bank big data practices,promoting the transformation and upgrading of the banking industry in the context of legal digital currencies.展开更多
The fracture volume is gradually changed with the depletion of fracture pressure during the production process.However,there are few flowback models available so far that can estimate the fracture volume loss using pr...The fracture volume is gradually changed with the depletion of fracture pressure during the production process.However,there are few flowback models available so far that can estimate the fracture volume loss using pressure transient and rate transient data.The initial flowback involves producing back the fracturing fuid after hydraulic fracturing,while the second flowback involves producing back the preloading fluid injected into the parent wells before fracturing of child wells.The main objective of this research is to compare the initial and second flowback data to capture the changes in fracture volume after production and preload processes.Such a comparison is useful for evaluating well performance and optimizing frac-turing operations.We construct rate-normalized pressure(RNP)versus material balance time(MBT)diagnostic plots using both initial and second flowback data(FB;and FBs,respectively)of six multi-fractured horizontal wells completed in Niobrara and Codell formations in DJ Basin.In general,the slope of RNP plot during the FB,period is higher than that during the FB;period,indicating a potential loss of fracture volume from the FB;to the FB,period.We estimate the changes in effective fracture volume(Ver)by analyzing the changes in the RNP slope and total compressibility between these two flowback periods.Ver during FB,is in general 3%-45%lower than that during FB:.We also compare the drive mechanisms for the two flowback periods by calculating the compaction-drive index(CDI),hydrocarbon-drive index(HDI),and water-drive index(WDI).The dominant drive mechanism during both flowback periods is CDI,but its contribution is reduced by 16%in the FB,period.This drop is generally compensated by a relatively higher HDI during this period.The loss of effective fracture volume might be attributed to the pressure depletion in fractures,which occurs during the production period and can extend 800 days.展开更多
With the rapid development of the Internet and e-commerce,e-commerce platforms have accumulated huge amounts of user behavior data.The emergence of big data technology provides a powerful means for in-depth analysis o...With the rapid development of the Internet and e-commerce,e-commerce platforms have accumulated huge amounts of user behavior data.The emergence of big data technology provides a powerful means for in-depth analysis of these data and insight into user behavior patterns and preferences.This paper elaborates on the application of big data technology in the analysis of user behavior on e-commerce platforms,including the technical methods of data collection,storage,processing and analysis,as well as the specific applications in the construction of user profiles,precision marketing,personalized recommendation,user retention and churn analysis,etc.,and discusses the challenges and countermeasures faced in the application.Through the study of actual cases,it demonstrates the remarkable effectiveness of big data technology in enhancing the competitiveness of e-commerce platforms and user experience.展开更多
Semantic communication(SemCom)aims to achieve high-fidelity information delivery under low communication consumption by only guaranteeing semantic accuracy.Nevertheless,semantic communication still suffers from unexpe...Semantic communication(SemCom)aims to achieve high-fidelity information delivery under low communication consumption by only guaranteeing semantic accuracy.Nevertheless,semantic communication still suffers from unexpected channel volatility and thus developing a re-transmission mechanism(e.g.,hybrid automatic repeat request[HARQ])becomes indispensable.In that regard,instead of discarding previously transmitted information,the incremental knowledge-based HARQ(IK-HARQ)is deemed as a more effective mechanism that could sufficiently utilize the information semantics.However,considering the possible existence of semantic ambiguity in image transmission,a simple bit-level cyclic redundancy check(CRC)might compromise the performance of IK-HARQ.Therefore,there emerges a strong incentive to revolutionize the CRC mechanism,thus more effectively reaping the benefits of both SemCom and HARQ.In this paper,built on top of swin transformer-based joint source-channel coding(JSCC)and IK-HARQ,we propose a semantic image transmission framework SC-TDA-HARQ.In particular,different from the conventional CRC,we introduce a topological data analysis(TDA)-based error detection method,which capably digs out the inner topological and geometric information of images,to capture semantic information and determine the necessity for re-transmission.Extensive numerical results validate the effectiveness and efficiency of the proposed SC-TDA-HARQ framework,especially under the limited bandwidth condition,and manifest the superiority of TDA-based error detection method in image transmission.展开更多
Cervical cancer,a leading malignancy globally,poses a significant threat to women's health,with an estimated 604,000 new cases and 342,000 deaths reported in 2020^([1]).As cervical cancer is closely linked to huma...Cervical cancer,a leading malignancy globally,poses a significant threat to women's health,with an estimated 604,000 new cases and 342,000 deaths reported in 2020^([1]).As cervical cancer is closely linked to human papilloma virus(HPV)infection,early detection relies on HPV screening;however,late-stage prognosis remains poor,underscoring the need for novel diagnostic and therapeutic targets^([2]).展开更多
The analysis of ancient genomics provides opportunities to explore human population history across both temporal and geographic dimensions(Haak et al.,2015;Wang et al.,2021,2024)to enhance the accessibility and utilit...The analysis of ancient genomics provides opportunities to explore human population history across both temporal and geographic dimensions(Haak et al.,2015;Wang et al.,2021,2024)to enhance the accessibility and utility of these ancient genomic datasets,a range of databases and advanced statistical models have been developed,including the Allen Ancient DNA Resource(AADR)(Mallick et al.,2024)and AdmixTools(Patterson et al.,2012).While upstream processes such as sequencing and raw data processing have been streamlined by resources like the AADR,the downstream analysis of these datasets-encompassing population genetics inference and spatiotemporal interpretation-remains a significant challenge.The AADR provides a unified collection of published ancient DNA(aDNA)data,yet its file-based format and reliance on command-line tools,such as those in Admix-Tools(Patterson et al.,2012),require advanced computational expertise for effective exploration and analysis.These requirements can present significant challenges forresearchers lackingadvanced computational expertise,limiting the accessibility and broader application of these valuable genomic resources.展开更多
The rising of aging and the declining of birth rates have forced the public to focus on the youth’s view on marriage.Based on critical discourse analysis and combined with Fairclough’s three-dimensional discourse an...The rising of aging and the declining of birth rates have forced the public to focus on the youth’s view on marriage.Based on critical discourse analysis and combined with Fairclough’s three-dimensional discourse analysis model,this paper builds a“Chinese media News Report Corpus on the topic of‘marriage’”whose news are collected from China Daily.It is found that the discourses are neutral and objective with regard to the advantages and disadvantages of marriage,but in general,it is still a traditional view of marriage that is inevitable and closely related to fertility.Although this is controlled by the policies and the social reasons including declining fertility rate,it deviates from the current view of the youth towards marriage,resulting in many serious consequences such as young people’s rejection.In addition,this research found that male and female have great differences in their views on marriage,and men’s resistance to marriage is far greater than that of women,which is departure from the public’s cognition.The reasons behind this need to be explored in order to solve the marriage and love problems of young people in today’s era and realize the healthy development of young marriage.展开更多
Maintaining the integrity and longevity of structures is essential in many industries,such as aerospace,nuclear,and petroleum.To achieve the cost-effectiveness of large-scale systems in petroleum drilling,a strong emp...Maintaining the integrity and longevity of structures is essential in many industries,such as aerospace,nuclear,and petroleum.To achieve the cost-effectiveness of large-scale systems in petroleum drilling,a strong emphasis on structural durability and monitoring is required.This study focuses on the mechanical vibrations that occur in rotary drilling systems,which have a substantial impact on the structural integrity of drilling equipment.The study specifically investigates axial,torsional,and lateral vibrations,which might lead to negative consequences such as bit-bounce,chaotic whirling,and high-frequency stick-slip.These events not only hinder the efficiency of drilling but also lead to exhaustion and harm to the system’s components since they are difficult to be detected and controlled in real time.The study investigates the dynamic interactions of these vibrations,specifically in their high-frequency modes,usingfield data obtained from measurement while drilling.Thefindings have demonstrated the effect of strong coupling between the high-frequency modes of these vibrations on drilling sys-tem performance.The obtained results highlight the importance of considering the interconnected impacts of these vibrations when designing and implementing robust control systems.Therefore,integrating these compo-nents can increase the durability of drill bits and drill strings,as well as improve the ability to monitor and detect damage.Moreover,by exploiting thesefindings,the assessment of structural resilience in rotary drilling systems can be enhanced.Furthermore,the study demonstrates the capacity of structural health monitoring to improve the quality,dependability,and efficiency of rotary drilling systems in the petroleum industry.展开更多
Multimodal sentiment analysis utilizes multimodal data such as text,facial expressions and voice to detect people’s attitudes.With the advent of distributed data collection and annotation,we can easily obtain and sha...Multimodal sentiment analysis utilizes multimodal data such as text,facial expressions and voice to detect people’s attitudes.With the advent of distributed data collection and annotation,we can easily obtain and share such multimodal data.However,due to professional discrepancies among annotators and lax quality control,noisy labels might be introduced.Recent research suggests that deep neural networks(DNNs)will overfit noisy labels,leading to the poor performance of the DNNs.To address this challenging problem,we present a Multimodal Robust Meta Learning framework(MRML)for multimodal sentiment analysis to resist noisy labels and correlate distinct modalities simultaneously.Specifically,we propose a two-layer fusion net to deeply fuse different modalities and improve the quality of the multimodal data features for label correction and network training.Besides,a multiple meta-learner(label corrector)strategy is proposed to enhance the label correction approach and prevent models from overfitting to noisy labels.We conducted experiments on three popular multimodal datasets to verify the superiority of ourmethod by comparing it with four baselines.展开更多
Integrated data and energy transfer(IDET)enables the electromagnetic waves to transmit wireless energy at the same time of data delivery for lowpower devices.In this paper,an energy harvesting modulation(EHM)assisted ...Integrated data and energy transfer(IDET)enables the electromagnetic waves to transmit wireless energy at the same time of data delivery for lowpower devices.In this paper,an energy harvesting modulation(EHM)assisted multi-user IDET system is studied,where all the received signals at the users are exploited for energy harvesting without the degradation of wireless data transfer(WDT)performance.The joint IDET performance is then analysed theoretically by conceiving a practical time-dependent wireless channel.With the aid of the AO based algorithm,the average effective data rate among users are maximized by ensuring the BER and the wireless energy transfer(WET)performance.Simulation results validate and evaluate the IDET performance of the EHM assisted system,which also demonstrates that the optimal number of user clusters and IDET time slots should be allocated,in order to improve the WET and WDT performance.展开更多
Internal multiples are commonly present in seismic data due to variations in velocity or density of subsurface media.They can reduce the signal-to-noise ratio of seismic data and degrade the quality of the image.With ...Internal multiples are commonly present in seismic data due to variations in velocity or density of subsurface media.They can reduce the signal-to-noise ratio of seismic data and degrade the quality of the image.With the development of seismic exploration into deep and ultradeep events,especially those from complex targets in the western region of China,the internal multiple eliminations become increasingly challenging.Currently,three-dimensional(3D)seismic data are primarily used for oil and gas target recognition and drilling.Effectively eliminating internal multiples in 3D seismic data of complex structures and mitigating their adverse effects is crucial for enhancing the success rate of drilling.In this study,we propose an internal multiple prediction algorithm for 3D seismic data in complex structures using the Marchenko autofocusing theory.This method can predict the accurate internal multiples of time difference without an accurate velocity model and the implementation process mainly consists of several steps.Firstly,simulating direct waves with a 3D macroscopic velocity model.Secondly,using direct waves and 3D full seismic acquisition records to obtain the upgoing and down-going Green's functions between the virtual source point and surface.Thirdly,constructing internal multiples of the relevant layers by upgoing and downgoing Green's functions.Finally,utilizing the adaptive matching subtraction method to remove predicted internal multiples from the original data to obtain seismic records without multiples.Compared with the two-dimensional(2D)Marchenko algo-rithm,the performance of the 3D Marchenko algorithm for internal multiple prediction has been significantly enhanced,resulting in higher computational accuracy.Numerical simulation test results indicate that our proposed method can effectively eliminate internal multiples in 3D seismic data,thereby exhibiting important theoretical and industrial application value.展开更多
In the health field,longitudinal studies involve the recording of clinical observations of the same sample of pa-tients over successive periods,referred to as waves.This type of database serves as a valuable source of...In the health field,longitudinal studies involve the recording of clinical observations of the same sample of pa-tients over successive periods,referred to as waves.This type of database serves as a valuable source of infor-mation and insights,particularly when examining the temporal aspect,allowing the extraction of relevant and non-obvious knowledge.The triadic concept analysis theory has been proposed to describe the ternary re-lationships between objects,attributes,and conditions.In this study,we present a methodology for exploring longitudinal health databases using both the triadic theory and triadic rules,which are similar to association rules but incorporate temporal relations.Through four case studies,we demonstrate the potential of applying triadic analysis to longitudinal databases to identify risk patterns,enhance decision-making processes,and deepen our understanding of temporal dynamics.These findings suggest a promising approach for describing longitudinal databases and obtaining insights to improve clinical decision-support systems for disease treatment.展开更多
The highly efficient electrochemical treatment technology for dye-polluted wastewater is one of hot research topics in industrial wastewater treatment.This study reported a three-dimensional electrochemical treatment ...The highly efficient electrochemical treatment technology for dye-polluted wastewater is one of hot research topics in industrial wastewater treatment.This study reported a three-dimensional electrochemical treatment process integrating graphite intercalation compound(GIC)adsorption,direct anodic oxidation,and·OH oxidation for decolourising Reactive Black 5(RB5)from aqueous solutions.The electrochemical process was optimised using the novel progressive central composite design-response surface methodology(CCD-NPRSM),hybrid artificial neural network-extreme gradient boosting(hybrid ANN-XGBoost),and classification and regression trees(CART).CCD-NPRSM and hybrid ANN-XGBoost were employed to minimise errors in evaluating the electrochemical process involving three manipulated operational parameters:current density,electrolysis(treatment)time,and initial dye concentration.The optimised decolourisation efficiencies were 99.30%,96.63%,and 99.14%for CCD-NPRSM,hybrid ANN-XGBoost,and CART,respectively,compared to the 98.46%RB5 removal rate observed experimentally under optimum conditions:approximately 20 mA/cm^(2) of current density,20 min of electrolysis time,and 65 mg/L of RB5.The optimised mineralisation efficiencies ranged between 89%and 92%for different models based on total organic carbon(TOC).Experimental studies confirmed that the predictive efficiency of optimised models ranked in the descending order of hybrid ANN-XGBoost,CCD-NPRSM,and CART.Model validation using analysis of variance(ANOVA)revealed that hybrid ANN-XGBoost had a mean squared error(MSE)and a coefficient of determination(R^(2))of approximately 0.014 and 0.998,respectively,for the RB5 removal efficiency,outperforming CCD-NPRSM with MSE and R^(2) of 0.518 and 0.998,respectively.Overall,the hybrid ANN-XGBoost approach is the most feasible technique for assessing the electrochemical treatment efficiency in RB5 dye wastewater decolourisation.展开更多
The identification of specific galaxy populations in large-scale spectroscopic surveys represents an essential yet challenging task,particularly for rare or anomalous galaxies that deviate from the typical galaxy dist...The identification of specific galaxy populations in large-scale spectroscopic surveys represents an essential yet challenging task,particularly for rare or anomalous galaxies that deviate from the typical galaxy distributions.Traditional methods based on template-fitting or predefining spectral features face challenges in addressing the complexity and scale of modern astronomical data sets.To overcome these limitations,we propose GalSpecEncoder-KB,a modular and flexible framework that combines deep learning with knowledge base retrieval to enable efficient and interpretable analysis of galaxy spectra.The framework integrates a Transformerbased feature encoder,GalSpecEncoder,pre-trained with masked-modeling strategy to capture semantically rich and context-aware spectral representations.By leveraging a Retrieval-Augmented Analysis approach,the knowledge base constructed from catalogs enables metadata retrieval and weighted voting for target galaxy identification.Using the Sloan Digital Sky Survey as a comprehensive case study,we demonstrate the capabilities of the framework for target galaxy search.Experimental results demonstrate the exceptional generalizability and adaptability across diverse galaxy search tasks,including identification of LINERs,Strong Gravitational Lenses,and detection of Outliers,while maintaining robust performance and interpretable spectral analysis capabilities.展开更多
[Objective]Mental health is the essence of physical health,human beings pay more and more attention to the study of mental health recovery and after many studies,it is clear that the restorative environment has an imp...[Objective]Mental health is the essence of physical health,human beings pay more and more attention to the study of mental health recovery and after many studies,it is clear that the restorative environment has an important and positive significance for their mental recovery,and species as an important part of the environment since the natural environment has been used as an essential part of the research environment,based on the conditions of such a social reality,this paper analyzed the articles on species surveys in the last 30 years,used the data to reflect the importance of species survey,and the research hotspot of restorative environment.[Methods]The study analyzed the data in articles about species survey in CNKI database from 1994 to 2024 through Citespace visualization,and analyzed the data through the number of articles issued between years,keyword co-occurrence and other aspects,so as to give data support for the research of restorative environment.[Results]In the past 30 years,the number of articles published on species survey has increased year by year,and species survey is at the forefront of research hotspots.Clustering and timeline analysis results of insects,birds,diversity has become more important.[Conclusions]From the 621 articles,the following aspects could be concluded:(1)The importance of restorative environments research and the vast exchanges among scholars have been reflected and more research hotspots have been explored in this field;(2)For the research direction of restorative environments and this paper,the research hotspots were in line with the in-depth exploration of species diversity,which was not only in the field of species,but also in the field of health and the environment,and there were also investigations of the links;(3)The interdependence between species diversity and restorative environments was high,further research on restorative environments largely depended on the study of species surveys.展开更多
In clinical research,subgroup analysis can help identify patient groups that respond better or worse to specific treatments,improve therapeutic effect and safety,and is of great significance in precision medicine.This...In clinical research,subgroup analysis can help identify patient groups that respond better or worse to specific treatments,improve therapeutic effect and safety,and is of great significance in precision medicine.This article considers subgroup analysis methods for longitudinal data containing multiple covariates and biomarkers.We divide subgroups based on whether a linear combination of these biomarkers exceeds a predetermined threshold,and assess the heterogeneity of treatment effects across subgroups using the interaction between subgroups and exposure variables.Quantile regression is used to better characterize the global distribution of the response variable and sparsity penalties are imposed to achieve variable selection of covariates and biomarkers.The effectiveness of our proposed methodology for both variable selection and parameter estimation is verified through random simulations.Finally,we demonstrate the application of this method by analyzing data from the PA.3 trial,further illustrating the practicality of the method proposed in this paper.展开更多
The contact characteristics of the rough tooth surface during the meshing process are significantly affected by the lubrication state.The coupling effect of tooth surface roughness and lubrication on meshing character...The contact characteristics of the rough tooth surface during the meshing process are significantly affected by the lubrication state.The coupling effect of tooth surface roughness and lubrication on meshing characteristics of planetary gear is studied.An improved three-dimensional(3 D)anisotropic tooth surface roughness fractal model is proposed based on the experimental parameters.Considering asperity contact and elastohydrodynamic lubrication(EHL),the contact load and flexibility deformation of the tooth surface are derived,and the deformation compatibility equation of the 3 D loaded tooth contact analysis(3 D-LTCA)method is improved.The asperity of the tooth surface changes the system from EHL to mixed lubrication and reduces the stiffness of the oil film.Compared with the sun planet gear,the asperity has a greater effect on the meshing characteristics of the ring-planet gear.Compared with the proposed method,the comprehensive stiffness obtained by the traditional calculation method considering the lubrication effect is smaller,especially for the ring-planet gear.Compared with roughness,speed and viscosity,the meshing characteristics of planetary gears are most sensitive to torque.展开更多
基金supported by the National Science Foundation of China(Grant Nos.42374205 and 41974179)the Specialized Research Fund of the National Space Science Center,Chinese Academy of Sciences(Grant No.E4PD3010)supported by the Specialized Research Fund for State Key Laboratories.
文摘The three-dimensional spectral analysis method was applied to airglow data from September 2023 to August 2024 derivedfrom an OH airglow imager located at the Hejing station (42.79°N, 83.73°E) to study the propagation characteristics of gravity waves(GWs) over Northwest China. We found that obvious seasonal variations occur in the propagation of GWs. In spring, GWs mainlypropagate in the northeast direction. In summer and autumn, GWs mainly propagate in the north direction. However, GWs mainlypropagate in the south direction in winter. The direction of GW propagation in the zonal direction is controlled by the wind-filteringeffect, whereas the north–south meridional direction is mainly determined by the location of the wave source. We found that the averageenergy spectrum exhibits a 10%–20% higher intensity in summer and winter compared with spring and autumn. For the first time, wereport the seasonal variation characteristics of GWs over the inland areas of Northwest China, which is of great significance forunderstanding the regional distribution characteristics of GWs.
文摘DNA microarray technology is an extremely effective technique for studying gene expression patterns in cells, and the main challenge currently faced by this technology is how to analyze the large amount of gene expression data generated. To address this, this paper employs a mixed-effects model to analyze gene expression data. In terms of data selection, 1176 genes from the white mouse gene expression dataset under two experimental conditions were chosen, setting up two conditions: pneumococcal infection and no infection, and constructing a mixed-effects model. After preprocessing the gene chip information, the data were imported into the model, preliminary results were calculated, and permutation tests were performed to biologically validate the preliminary results using GSEA. The final dataset consists of 20 groups of gene expression data from pneumococcal infection, which categorizes functionally related genes based on the similarity of their expression profiles, facilitating the study of genes with unknown functions.
文摘With the advent of the big data era,real-time data analysis and decision-support systems have been recognized as essential tools for enhancing enterprise competitiveness and optimizing the decision-making process.This study aims to explore the development strategies of real-time data analysis and decision-support systems,and analyze their application status and future development trends in various industries.The article first reviews the basic concepts and importance of real-time data analysis and decision-support systems,and then discusses in detail the key technical aspects such as system architecture,data collection and processing,analysis methods,and visualization techniques.
文摘This paper analyzes the advantages of legal digital currencies and explores their impact on bank big data practices.By combining bank big data collection and processing,it clarifies that legal digital currencies can enhance the efficiency of bank data processing,enrich data types,and strengthen data analysis and application capabilities.In response to future development needs,it is necessary to strengthen data collection management,enhance data processing capabilities,innovate big data application models,and provide references for bank big data practices,promoting the transformation and upgrading of the banking industry in the context of legal digital currencies.
文摘The fracture volume is gradually changed with the depletion of fracture pressure during the production process.However,there are few flowback models available so far that can estimate the fracture volume loss using pressure transient and rate transient data.The initial flowback involves producing back the fracturing fuid after hydraulic fracturing,while the second flowback involves producing back the preloading fluid injected into the parent wells before fracturing of child wells.The main objective of this research is to compare the initial and second flowback data to capture the changes in fracture volume after production and preload processes.Such a comparison is useful for evaluating well performance and optimizing frac-turing operations.We construct rate-normalized pressure(RNP)versus material balance time(MBT)diagnostic plots using both initial and second flowback data(FB;and FBs,respectively)of six multi-fractured horizontal wells completed in Niobrara and Codell formations in DJ Basin.In general,the slope of RNP plot during the FB,period is higher than that during the FB;period,indicating a potential loss of fracture volume from the FB;to the FB,period.We estimate the changes in effective fracture volume(Ver)by analyzing the changes in the RNP slope and total compressibility between these two flowback periods.Ver during FB,is in general 3%-45%lower than that during FB:.We also compare the drive mechanisms for the two flowback periods by calculating the compaction-drive index(CDI),hydrocarbon-drive index(HDI),and water-drive index(WDI).The dominant drive mechanism during both flowback periods is CDI,but its contribution is reduced by 16%in the FB,period.This drop is generally compensated by a relatively higher HDI during this period.The loss of effective fracture volume might be attributed to the pressure depletion in fractures,which occurs during the production period and can extend 800 days.
文摘With the rapid development of the Internet and e-commerce,e-commerce platforms have accumulated huge amounts of user behavior data.The emergence of big data technology provides a powerful means for in-depth analysis of these data and insight into user behavior patterns and preferences.This paper elaborates on the application of big data technology in the analysis of user behavior on e-commerce platforms,including the technical methods of data collection,storage,processing and analysis,as well as the specific applications in the construction of user profiles,precision marketing,personalized recommendation,user retention and churn analysis,etc.,and discusses the challenges and countermeasures faced in the application.Through the study of actual cases,it demonstrates the remarkable effectiveness of big data technology in enhancing the competitiveness of e-commerce platforms and user experience.
基金supported in part by the National Key Research and Development Program of China under Grant 2024YFE0200600in part by the National Natural Science Foundation of China under Grant 62071425+3 种基金in part by the Zhejiang Key Research and Development Plan under Grant 2022C01093in part by the Zhejiang Provincial Natural Science Foundation of China under Grant LR23F010005in part by the National Key Laboratory of Wireless Communications Foundation under Grant 2023KP01601in part by the Big Data and Intelligent Computing Key Lab of CQUPT under Grant BDIC-2023-B-001.
文摘Semantic communication(SemCom)aims to achieve high-fidelity information delivery under low communication consumption by only guaranteeing semantic accuracy.Nevertheless,semantic communication still suffers from unexpected channel volatility and thus developing a re-transmission mechanism(e.g.,hybrid automatic repeat request[HARQ])becomes indispensable.In that regard,instead of discarding previously transmitted information,the incremental knowledge-based HARQ(IK-HARQ)is deemed as a more effective mechanism that could sufficiently utilize the information semantics.However,considering the possible existence of semantic ambiguity in image transmission,a simple bit-level cyclic redundancy check(CRC)might compromise the performance of IK-HARQ.Therefore,there emerges a strong incentive to revolutionize the CRC mechanism,thus more effectively reaping the benefits of both SemCom and HARQ.In this paper,built on top of swin transformer-based joint source-channel coding(JSCC)and IK-HARQ,we propose a semantic image transmission framework SC-TDA-HARQ.In particular,different from the conventional CRC,we introduce a topological data analysis(TDA)-based error detection method,which capably digs out the inner topological and geometric information of images,to capture semantic information and determine the necessity for re-transmission.Extensive numerical results validate the effectiveness and efficiency of the proposed SC-TDA-HARQ framework,especially under the limited bandwidth condition,and manifest the superiority of TDA-based error detection method in image transmission.
基金supported by a project funded by the Hebei Provincial Central Guidance Local Science and Technology Development Fund(236Z7714G)。
文摘Cervical cancer,a leading malignancy globally,poses a significant threat to women's health,with an estimated 604,000 new cases and 342,000 deaths reported in 2020^([1]).As cervical cancer is closely linked to human papilloma virus(HPV)infection,early detection relies on HPV screening;however,late-stage prognosis remains poor,underscoring the need for novel diagnostic and therapeutic targets^([2]).
基金by the National Key Research and Development Program of China(2023YFC3303701-02 and 2024YFC3306701)the National Natural Science Foundation of China(T2425014 and 32270667)+3 种基金the Natural Science Foundation of Fujian Province of China(2023J06013)the Major Project of the National Social Science Foundation of China granted to Chuan-Chao Wang(21&ZD285)Open Research Fund of State Key Laboratory of Genetic Engineering at Fudan University(SKLGE-2310)Open Research Fund of Forensic Genetics Key Laboratory of the Ministry of Public Security(2023FGKFKT07).
文摘The analysis of ancient genomics provides opportunities to explore human population history across both temporal and geographic dimensions(Haak et al.,2015;Wang et al.,2021,2024)to enhance the accessibility and utility of these ancient genomic datasets,a range of databases and advanced statistical models have been developed,including the Allen Ancient DNA Resource(AADR)(Mallick et al.,2024)and AdmixTools(Patterson et al.,2012).While upstream processes such as sequencing and raw data processing have been streamlined by resources like the AADR,the downstream analysis of these datasets-encompassing population genetics inference and spatiotemporal interpretation-remains a significant challenge.The AADR provides a unified collection of published ancient DNA(aDNA)data,yet its file-based format and reliance on command-line tools,such as those in Admix-Tools(Patterson et al.,2012),require advanced computational expertise for effective exploration and analysis.These requirements can present significant challenges forresearchers lackingadvanced computational expertise,limiting the accessibility and broader application of these valuable genomic resources.
文摘The rising of aging and the declining of birth rates have forced the public to focus on the youth’s view on marriage.Based on critical discourse analysis and combined with Fairclough’s three-dimensional discourse analysis model,this paper builds a“Chinese media News Report Corpus on the topic of‘marriage’”whose news are collected from China Daily.It is found that the discourses are neutral and objective with regard to the advantages and disadvantages of marriage,but in general,it is still a traditional view of marriage that is inevitable and closely related to fertility.Although this is controlled by the policies and the social reasons including declining fertility rate,it deviates from the current view of the youth towards marriage,resulting in many serious consequences such as young people’s rejection.In addition,this research found that male and female have great differences in their views on marriage,and men’s resistance to marriage is far greater than that of women,which is departure from the public’s cognition.The reasons behind this need to be explored in order to solve the marriage and love problems of young people in today’s era and realize the healthy development of young marriage.
文摘Maintaining the integrity and longevity of structures is essential in many industries,such as aerospace,nuclear,and petroleum.To achieve the cost-effectiveness of large-scale systems in petroleum drilling,a strong emphasis on structural durability and monitoring is required.This study focuses on the mechanical vibrations that occur in rotary drilling systems,which have a substantial impact on the structural integrity of drilling equipment.The study specifically investigates axial,torsional,and lateral vibrations,which might lead to negative consequences such as bit-bounce,chaotic whirling,and high-frequency stick-slip.These events not only hinder the efficiency of drilling but also lead to exhaustion and harm to the system’s components since they are difficult to be detected and controlled in real time.The study investigates the dynamic interactions of these vibrations,specifically in their high-frequency modes,usingfield data obtained from measurement while drilling.Thefindings have demonstrated the effect of strong coupling between the high-frequency modes of these vibrations on drilling sys-tem performance.The obtained results highlight the importance of considering the interconnected impacts of these vibrations when designing and implementing robust control systems.Therefore,integrating these compo-nents can increase the durability of drill bits and drill strings,as well as improve the ability to monitor and detect damage.Moreover,by exploiting thesefindings,the assessment of structural resilience in rotary drilling systems can be enhanced.Furthermore,the study demonstrates the capacity of structural health monitoring to improve the quality,dependability,and efficiency of rotary drilling systems in the petroleum industry.
基金supported by STI 2030-Major Projects 2021ZD0200400National Natural Science Foundation of China(62276233 and 62072405)Key Research Project of Zhejiang Province(2023C01048).
文摘Multimodal sentiment analysis utilizes multimodal data such as text,facial expressions and voice to detect people’s attitudes.With the advent of distributed data collection and annotation,we can easily obtain and share such multimodal data.However,due to professional discrepancies among annotators and lax quality control,noisy labels might be introduced.Recent research suggests that deep neural networks(DNNs)will overfit noisy labels,leading to the poor performance of the DNNs.To address this challenging problem,we present a Multimodal Robust Meta Learning framework(MRML)for multimodal sentiment analysis to resist noisy labels and correlate distinct modalities simultaneously.Specifically,we propose a two-layer fusion net to deeply fuse different modalities and improve the quality of the multimodal data features for label correction and network training.Besides,a multiple meta-learner(label corrector)strategy is proposed to enhance the label correction approach and prevent models from overfitting to noisy labels.We conducted experiments on three popular multimodal datasets to verify the superiority of ourmethod by comparing it with four baselines.
基金supported in part by the MOST Major Research and Development Project(Grant No.2021YFB2900204)the National Natural Science Foundation of China(NSFC)(Grant No.62201123,No.62132004,No.61971102)+3 种基金China Postdoctoral Science Foundation(Grant No.2022TQ0056)in part by the financial support of the Sichuan Science and Technology Program(Grant No.2022YFH0022)Sichuan Major R&D Project(Grant No.22QYCX0168)the Municipal Government of Quzhou(Grant No.2022D031)。
文摘Integrated data and energy transfer(IDET)enables the electromagnetic waves to transmit wireless energy at the same time of data delivery for lowpower devices.In this paper,an energy harvesting modulation(EHM)assisted multi-user IDET system is studied,where all the received signals at the users are exploited for energy harvesting without the degradation of wireless data transfer(WDT)performance.The joint IDET performance is then analysed theoretically by conceiving a practical time-dependent wireless channel.With the aid of the AO based algorithm,the average effective data rate among users are maximized by ensuring the BER and the wireless energy transfer(WET)performance.Simulation results validate and evaluate the IDET performance of the EHM assisted system,which also demonstrates that the optimal number of user clusters and IDET time slots should be allocated,in order to improve the WET and WDT performance.
文摘Internal multiples are commonly present in seismic data due to variations in velocity or density of subsurface media.They can reduce the signal-to-noise ratio of seismic data and degrade the quality of the image.With the development of seismic exploration into deep and ultradeep events,especially those from complex targets in the western region of China,the internal multiple eliminations become increasingly challenging.Currently,three-dimensional(3D)seismic data are primarily used for oil and gas target recognition and drilling.Effectively eliminating internal multiples in 3D seismic data of complex structures and mitigating their adverse effects is crucial for enhancing the success rate of drilling.In this study,we propose an internal multiple prediction algorithm for 3D seismic data in complex structures using the Marchenko autofocusing theory.This method can predict the accurate internal multiples of time difference without an accurate velocity model and the implementation process mainly consists of several steps.Firstly,simulating direct waves with a 3D macroscopic velocity model.Secondly,using direct waves and 3D full seismic acquisition records to obtain the upgoing and down-going Green's functions between the virtual source point and surface.Thirdly,constructing internal multiples of the relevant layers by upgoing and downgoing Green's functions.Finally,utilizing the adaptive matching subtraction method to remove predicted internal multiples from the original data to obtain seismic records without multiples.Compared with the two-dimensional(2D)Marchenko algo-rithm,the performance of the 3D Marchenko algorithm for internal multiple prediction has been significantly enhanced,resulting in higher computational accuracy.Numerical simulation test results indicate that our proposed method can effectively eliminate internal multiples in 3D seismic data,thereby exhibiting important theoretical and industrial application value.
文摘In the health field,longitudinal studies involve the recording of clinical observations of the same sample of pa-tients over successive periods,referred to as waves.This type of database serves as a valuable source of infor-mation and insights,particularly when examining the temporal aspect,allowing the extraction of relevant and non-obvious knowledge.The triadic concept analysis theory has been proposed to describe the ternary re-lationships between objects,attributes,and conditions.In this study,we present a methodology for exploring longitudinal health databases using both the triadic theory and triadic rules,which are similar to association rules but incorporate temporal relations.Through four case studies,we demonstrate the potential of applying triadic analysis to longitudinal databases to identify risk patterns,enhance decision-making processes,and deepen our understanding of temporal dynamics.These findings suggest a promising approach for describing longitudinal databases and obtaining insights to improve clinical decision-support systems for disease treatment.
文摘The highly efficient electrochemical treatment technology for dye-polluted wastewater is one of hot research topics in industrial wastewater treatment.This study reported a three-dimensional electrochemical treatment process integrating graphite intercalation compound(GIC)adsorption,direct anodic oxidation,and·OH oxidation for decolourising Reactive Black 5(RB5)from aqueous solutions.The electrochemical process was optimised using the novel progressive central composite design-response surface methodology(CCD-NPRSM),hybrid artificial neural network-extreme gradient boosting(hybrid ANN-XGBoost),and classification and regression trees(CART).CCD-NPRSM and hybrid ANN-XGBoost were employed to minimise errors in evaluating the electrochemical process involving three manipulated operational parameters:current density,electrolysis(treatment)time,and initial dye concentration.The optimised decolourisation efficiencies were 99.30%,96.63%,and 99.14%for CCD-NPRSM,hybrid ANN-XGBoost,and CART,respectively,compared to the 98.46%RB5 removal rate observed experimentally under optimum conditions:approximately 20 mA/cm^(2) of current density,20 min of electrolysis time,and 65 mg/L of RB5.The optimised mineralisation efficiencies ranged between 89%and 92%for different models based on total organic carbon(TOC).Experimental studies confirmed that the predictive efficiency of optimised models ranked in the descending order of hybrid ANN-XGBoost,CCD-NPRSM,and CART.Model validation using analysis of variance(ANOVA)revealed that hybrid ANN-XGBoost had a mean squared error(MSE)and a coefficient of determination(R^(2))of approximately 0.014 and 0.998,respectively,for the RB5 removal efficiency,outperforming CCD-NPRSM with MSE and R^(2) of 0.518 and 0.998,respectively.Overall,the hybrid ANN-XGBoost approach is the most feasible technique for assessing the electrochemical treatment efficiency in RB5 dye wastewater decolourisation.
基金supported by the National Key R&D Program of China(2022YFF0711500)National Natural Science Foundation of China(NSFC,Grant Nos.12273077,12403102,12373110,and 12103070)+4 种基金Strategic Priority Research Program of the Chinese Academy of Sciences(XDB0550101)supported by China National Astronomical Data Center(NADC)CAS Astronomical Data CenterChinese Virtual Observatory(China-VO)supported by Astronomical Big Data Joint Research Center,co-founded by National Astronomical Observatories,Chinese Academy of Sciences and Alibaba Cloud.
文摘The identification of specific galaxy populations in large-scale spectroscopic surveys represents an essential yet challenging task,particularly for rare or anomalous galaxies that deviate from the typical galaxy distributions.Traditional methods based on template-fitting or predefining spectral features face challenges in addressing the complexity and scale of modern astronomical data sets.To overcome these limitations,we propose GalSpecEncoder-KB,a modular and flexible framework that combines deep learning with knowledge base retrieval to enable efficient and interpretable analysis of galaxy spectra.The framework integrates a Transformerbased feature encoder,GalSpecEncoder,pre-trained with masked-modeling strategy to capture semantically rich and context-aware spectral representations.By leveraging a Retrieval-Augmented Analysis approach,the knowledge base constructed from catalogs enables metadata retrieval and weighted voting for target galaxy identification.Using the Sloan Digital Sky Survey as a comprehensive case study,we demonstrate the capabilities of the framework for target galaxy search.Experimental results demonstrate the exceptional generalizability and adaptability across diverse galaxy search tasks,including identification of LINERs,Strong Gravitational Lenses,and detection of Outliers,while maintaining robust performance and interpretable spectral analysis capabilities.
基金Sponsored by The 2024 Inter-university Cooperation Project for Innovation and Entrepreneurship Training of College Students in Beijing Universities(202498025)National Natural Science Foundation of China(NSFC)(52278045).
文摘[Objective]Mental health is the essence of physical health,human beings pay more and more attention to the study of mental health recovery and after many studies,it is clear that the restorative environment has an important and positive significance for their mental recovery,and species as an important part of the environment since the natural environment has been used as an essential part of the research environment,based on the conditions of such a social reality,this paper analyzed the articles on species surveys in the last 30 years,used the data to reflect the importance of species survey,and the research hotspot of restorative environment.[Methods]The study analyzed the data in articles about species survey in CNKI database from 1994 to 2024 through Citespace visualization,and analyzed the data through the number of articles issued between years,keyword co-occurrence and other aspects,so as to give data support for the research of restorative environment.[Results]In the past 30 years,the number of articles published on species survey has increased year by year,and species survey is at the forefront of research hotspots.Clustering and timeline analysis results of insects,birds,diversity has become more important.[Conclusions]From the 621 articles,the following aspects could be concluded:(1)The importance of restorative environments research and the vast exchanges among scholars have been reflected and more research hotspots have been explored in this field;(2)For the research direction of restorative environments and this paper,the research hotspots were in line with the in-depth exploration of species diversity,which was not only in the field of species,but also in the field of health and the environment,and there were also investigations of the links;(3)The interdependence between species diversity and restorative environments was high,further research on restorative environments largely depended on the study of species surveys.
基金Supported by the Natural Science Foundation of Fujian Province(2022J011177,2024J01903)the Key Project of Fujian Provincial Education Department(JZ230054)。
文摘In clinical research,subgroup analysis can help identify patient groups that respond better or worse to specific treatments,improve therapeutic effect and safety,and is of great significance in precision medicine.This article considers subgroup analysis methods for longitudinal data containing multiple covariates and biomarkers.We divide subgroups based on whether a linear combination of these biomarkers exceeds a predetermined threshold,and assess the heterogeneity of treatment effects across subgroups using the interaction between subgroups and exposure variables.Quantile regression is used to better characterize the global distribution of the response variable and sparsity penalties are imposed to achieve variable selection of covariates and biomarkers.The effectiveness of our proposed methodology for both variable selection and parameter estimation is verified through random simulations.Finally,we demonstrate the application of this method by analyzing data from the PA.3 trial,further illustrating the practicality of the method proposed in this paper.
基金Project(2024A1515240020)supported by the Guangdong Basic and Applied Basic Research Foundation,China。
文摘The contact characteristics of the rough tooth surface during the meshing process are significantly affected by the lubrication state.The coupling effect of tooth surface roughness and lubrication on meshing characteristics of planetary gear is studied.An improved three-dimensional(3 D)anisotropic tooth surface roughness fractal model is proposed based on the experimental parameters.Considering asperity contact and elastohydrodynamic lubrication(EHL),the contact load and flexibility deformation of the tooth surface are derived,and the deformation compatibility equation of the 3 D loaded tooth contact analysis(3 D-LTCA)method is improved.The asperity of the tooth surface changes the system from EHL to mixed lubrication and reduces the stiffness of the oil film.Compared with the sun planet gear,the asperity has a greater effect on the meshing characteristics of the ring-planet gear.Compared with the proposed method,the comprehensive stiffness obtained by the traditional calculation method considering the lubrication effect is smaller,especially for the ring-planet gear.Compared with roughness,speed and viscosity,the meshing characteristics of planetary gears are most sensitive to torque.
