Silent information regulator sirtuin 1 ameliorates acute liver failure via the p53/glutathione peroxidase 4/gasdermin D axis

BACKGROUND Acute liver failure(ALF)has a high mortality with widespread hepatocyte death involving ferroptosis and pyroptosis.The silent information regulator sirtuin 1(SIRT1)-mediated deacetylation affects multiple biological processes,including cellular senescence,apoptosis,sugar and lipid metabolism,oxidative stress,and inflammation.AIM To investigate the association between ferroptosis and pyroptosis and the upstream regulatory mechanisms.METHODS This study included 30 patients with ALF and 30 healthy individuals who underwent serum alanine aminotransferase(ALT)and aspartate aminotransferase(AST)testing.C57BL/6 mice were also intraperitoneally pretreated with SIRT1,p53,or glutathione peroxidase 4(GPX4)inducers and inhibitors and injected with lipopolysaccharide(LPS)/D-galactosamine(D-GalN)to induce ALF.Gasdermin D(GSDMD)^(-/-)mice were used as an experimental group.Histological changes in liver tissue were monitored by hematoxylin and eosin staining.ALT,AST,glutathione,reactive oxygen species,and iron levels were measured using commercial kits.Ferroptosis-and pyroptosis-related protein and mRNA expression was detected by western blot and quantitative real-time polymerase chain reaction.SIRT1,p53,and GSDMD were assessed by immunofluorescence analysis.RESULTS Serum AST and ALT levels were elevated in patients with ALF.SIRT1,solute carrier family 7a member 11(SLC7A11),and GPX4 protein expression was decreased and acetylated p5,p53,GSDMD,and acyl-CoA synthetase long-chain family member 4(ACSL4)protein levels were elevated in human ALF liver tissue.In the p53 and ferroptosis inhibitor-treated and GSDMD^(-/-)groups,serum interleukin(IL)-1β,tumour necrosis factor alpha,IL-6,IL-2 and C-C motif ligand 2 levels were decreased and hepatic impairment was mitigated.In mice with GSDMD knockout,p53 was reduced,GPX4 was increased,and ferroptotic events(depletion of SLC7A11,elevation of ACSL4,and iron accumulation)were detected.In vitro,knockdown of p53 and overexpression of GPX4 reduced AST and ALT levels,the cytostatic rate,and GSDMD expression,restoring SLC7A11 depletion.Moreover,SIRT1 agonist and overexpression of SIRT1 alleviated acute liver injury and decreased iron deposition compared with results in the model group,accompanied by reduced p53,GSDMD,and ACSL4,and increased SLC7A11 and GPX4.Inactivation of SIRT1 exacerbated ferroptotic and pyroptotic cell death and aggravated liver injury in LPS/D-GalNinduced in vitro and in vivo models.CONCLUSION SIRT1 activation attenuates LPS/D-GalN-induced ferroptosis and pyroptosis by inhibiting the p53/GPX4/GSDMD signaling pathway in ALF.

Tuning the diffusion constant to optimize the readout of positional information of spatial concentration patterns

Positional information encoded in spatial concentration patterns is crucial for the development of multicellular organisms.However,it is still unclear how such information is affected by the physically dissipative diffusion process.Here we study one-dimensional patterning systems with analytical derivation and numerical simulations.We find that the diffusion constant of the patterning molecules exhibits a nonmonotonic effect on the readout of the positional information from the concentration patterns.Specifically,there exists an optimal diffusion constant that maximizes the positional information.Moreover,we find that the energy dissipation due to the physical diffusion imposes a fundamental upper limit on the positional information.

Characterization of Small-Scale Farmers and Assessment of Their Access to Crop Production Information in Selected Counties of Kenya

Small-scale farming accounts for 78% of total agricultural production in Kenya and contributes to 23.5% of the country’s GDP. Their crop production activities are mostly rainfed subsistence with any surplus being sold to bring in some income. Timely decisions on farm practices such as farm preparation and planting are critical determinants of the seasonal outcomes. In Kenya, most small-scale farmers have no reliable source of information that would help them make timely and accurate decisions. County governments have extension officers who are mandated with giving farmers advisory services to farmers but they are not able to reach most farmers due to facilitation constraints. The mode and format of sharing information is also critical since it’s important to ensure that it’s timely, well-understood and usable. This study sought to assess access to geospatial derived and other crop production information by farmers in four selected counties of Kenya. Specific objectives were to determine the profile of small-scale farmers in terms of age, education and farm size;to determine the type of information that is made available to them by County and Sub-County extension officers including the format and mode of provision;and to determine if the information provided was useful in terms of accuracy, timeliness and adequacy. The results indicated that over 80% of the farmers were over 35 years of age and over 56% were male. Majority had attained primary education (34%) or secondary education (29%) and most farmers in all the counties grew maize (71%). Notably, fellow farmers were a source of information (71%) with the frequency of sharing information being mostly seasonal (37%) and when information was available (43%). Over 66% of interviewed farmers indicating that they faced challenges while using provided information. The results from the study are insightful and helpful in determining effective ways of providing farmers with useful information to ensure maximum benefits.

Implantable Electrochemical Microsensors for In Vivo Monitoring of Animal Physiological Information

In vivo monitoring of animal physiological information plays a crucial role in promptly alerting humans to potential diseases in animals and aiding in the exploration of mechanisms underlying human diseases.Currently,implantable electrochemical microsensors have emerged as a prominent area of research.These microsensors not only fulfill the technical requirements for monitoring animal physiological information but also offer an ideal platform for integration.They have been extensively studied for their ability to monitor animal physiological information in a minimally invasive manner,characterized by their bloodless,painless features,and exceptional performance.The development of implantable electrochemical microsensors for in vivo monitoring of animal physiological information has witnessed significant scientific and technological advancements through dedicated efforts.This review commenced with a comprehensive discussion of the construction of microsensors,including the materials utilized and the methods employed for fabrication.Following this,we proceeded to explore the various implantation technologies employed for electrochemical microsensors.In addition,a comprehensive overview was provided of the various applications of implantable electrochemical microsensors,specifically in the monitoring of diseases and the investigation of disease mechanisms.Lastly,a concise conclusion was conducted on the recent advancements and significant obstacles pertaining to the practical implementation of implantable electrochemical microsensors.

Evaluation of the Living Conditions and Health Perceptions of Waste Electrical and Electronic Equipment Handlers in the Informal Sector in Dakar

Electrical and electronic devices are becoming an increasingly important part of our society. In Africa, and in Senegal in particular, the handling and management of electronic and electrical equipment (EEE) that has reached the end of its life is mainly informal. This professional environment is characterized by the disintegration of the sector and the social heterogeneity that can be found there. The objective of this study is to assess the standard of living of electrical and electronic equipment waste handlers in the Dakar region, as well as their perception of their health. A survey was used to obtain information on sociodemographic background, living arrangements, perception of health status, and good practices to be implemented in case of work-related health problems. Life style, perception of general health and health problems were ranged as excellent, very good, good, average and poor. Informal recyclers in the Dakar region lived mainly in rooms and buildings as tenants (49.1%), or in family homes (48.4%) before starting this activity, and 51.2% continue to live in rooms and buildings as tenants compared to 41.4% who still live in a family home. The perception of health status ranged from poor to excellent, and 4.9% believe that they are limited in work due to a disability or health problem. Informal work is a heterogeneous phenomenon that makes research and policymaking particularly complex. There are several external factors within informal WEEE re-cyclers that can cause health problems or functional disability. However, the living conditions and the perception they have of their state of health are contradictory to the working conditions and the social environment to which they belong. A biomedical approach would consolidate these achievements by confirming or invalidating them.

Improving the Effectiveness of Image Classification Structural Methods by Compressing the Description According to the Information Content Criterion

The research aims to improve the performance of image recognition methods based on a description in the form of a set of keypoint descriptors.The main focus is on increasing the speed of establishing the relevance of object and etalon descriptions while maintaining the required level of classification efficiency.The class to be recognized is represented by an infinite set of images obtained from the etalon by applying arbitrary geometric transformations.It is proposed to reduce the descriptions for the etalon database by selecting the most significant descriptor components according to the information content criterion.The informativeness of an etalon descriptor is estimated by the difference of the closest distances to its own and other descriptions.The developed method determines the relevance of the full description of the recognized object with the reduced description of the etalons.Several practical models of the classifier with different options for establishing the correspondence between object descriptors and etalons are considered.The results of the experimental modeling of the proposed methods for a database including images of museum jewelry are presented.The test sample is formed as a set of images from the etalon database and out of the database with the application of geometric transformations of scale and rotation in the field of view.The practical problems of determining the threshold for the number of votes,based on which a classification decision is made,have been researched.Modeling has revealed the practical possibility of tenfold reducing descriptions with full preservation of classification accuracy.Reducing the descriptions by twenty times in the experiment leads to slightly decreased accuracy.The speed of the analysis increases in proportion to the degree of reduction.The use of reduction by the informativeness criterion confirmed the possibility of obtaining the most significant subset of features for classification,which guarantees a decent level of accuracy.

RAIENet:End-to-End Multitasking Road All Information Extractor

Road lanes and markings are the bases for autonomous driving environment perception.In this paper,we propose an end-to-end multi-task network,Road All Information Extractor named RAIENet,which aims to extract the full information of the road surface including road lanes,road markings and their correspondences.Based on the prior knowledge of pavement information,we explore and use the deep progressive relationship between lane segmentation and pavement mark-ing detection.Then,different attention mechanisms are adapted for different tasks.A lane detection accuracy of 0.807 F1-score and a ground marking accuracy of 0.971 mean average precision at intersection over union(IOU)threshold 0.5 were achieved on the newly labeled see more on road plus(CeyMo+)dataset.Of course,we also validated it on two well-known datasets Berkeley Deep-Drive 100K(BDD100K)and CULane.In addition,a post-processing method for generating bird’s eye view lane(BEVLane)using lidar point cloud information is proposed,which is used for the construction of high-definition maps and subsequent decision-making planning.The code and data are available at https://github.com/mayberpf/RAIEnet.

Privacy-Preserving Information Fusion Technique for Device to Server-Enabled Communication in the Internet of Things:A Hybrid Approach

Due to the overwhelming characteristics of the Internet of Things(IoT)and its adoption in approximately every aspect of our lives,the concept of individual devices’privacy has gained prominent attention from both customers,i.e.,people,and industries as wearable devices collect sensitive information about patients(both admitted and outdoor)in smart healthcare infrastructures.In addition to privacy,outliers or noise are among the crucial issues,which are directly correlated with IoT infrastructures,as most member devices are resource-limited and could generate or transmit false data that is required to be refined before processing,i.e.,transmitting.Therefore,the development of privacy-preserving information fusion techniques is highly encouraged,especially those designed for smart IoT-enabled domains.In this paper,we are going to present an effective hybrid approach that can refine raw data values captured by the respectivemember device before transmission while preserving its privacy through the utilization of the differential privacy technique in IoT infrastructures.Sliding window,i.e.,δi based dynamic programming methodology,is implemented at the device level to ensure precise and accurate detection of outliers or noisy data,and refine it prior to activation of the respective transmission activity.Additionally,an appropriate privacy budget has been selected,which is enough to ensure the privacy of every individualmodule,i.e.,a wearable device such as a smartwatch attached to the patient’s body.In contrast,the end module,i.e.,the server in this case,can extract important information with approximately the maximum level of accuracy.Moreover,refined data has been processed by adding an appropriate nose through the Laplace mechanism to make it useless or meaningless for the adversary modules in the IoT.The proposed hybrid approach is trusted from both the device’s privacy and the integrity of the transmitted information perspectives.Simulation and analytical results have proved that the proposed privacy-preserving information fusion technique for wearable devices is an ideal solution for resource-constrained infrastructures such as IoT and the Internet ofMedical Things,where both device privacy and information integrity are important.Finally,the proposed hybrid approach is proven against well-known intruder attacks,especially those related to the privacy of the respective device in IoT infrastructures.

Analysis of Secured Cloud Data Storage Model for Information

This paper was motivated by the existing problems of Cloud Data storage in Imo State University, Nigeria such as outsourced data causing the loss of data and misuse of customer information by unauthorized users or hackers, thereby making customer/client data visible and unprotected. Also, this led to enormous risk of the clients/customers due to defective equipment, bugs, faulty servers, and specious actions. The aim if this paper therefore is to analyze a secure model using Unicode Transformation Format (UTF) base 64 algorithms for storage of data in cloud securely. The methodology used was Object Orientated Hypermedia Analysis and Design Methodology (OOHADM) was adopted. Python was used to develop the security model;the role-based access control (RBAC) and multi-factor authentication (MFA) to enhance security Algorithm were integrated into the Information System developed with HTML 5, JavaScript, Cascading Style Sheet (CSS) version 3 and PHP7. This paper also discussed some of the following concepts;Development of Computing in Cloud, Characteristics of computing, Cloud deployment Model, Cloud Service Models, etc. The results showed that the proposed enhanced security model for information systems of cooperate platform handled multiple authorization and authentication menace, that only one login page will direct all login requests of the different modules to one Single Sign On Server (SSOS). This will in turn redirect users to their requested resources/module when authenticated, leveraging on the Geo-location integration for physical location validation. The emergence of this newly developed system will solve the shortcomings of the existing systems and reduce time and resources incurred while using the existing system.

Study on the Interactivity of Controlled and Automatic Information Processing in L2 Reading

L2 reading is not only an important channel for people to obtain information and knowledge,but also the main way for people to learn a foreign language.Reading information processing can be divided into controlled processing and automatic processing.Controlled information processing is a conscious and resource-intensive processing model,while automatic information processing is an unconscious and automatic processing model.This study investigates the characteristics and interactivity of controlled and automatic information processing in L2 reading,and explores the roles of controlled and automatic information processing strategies in improving L2 reading ability.The findings are as follows:(a)controlled and automatic information processing is interactive in L2 reading;and(b)the uses of controlled and automatic information processing strategies are beneficial to the improvement of the reading ability of L2 learners.This study has important theoretical and practical value in improving the efficiency of L2 reading teaching and learning.

Orbit Weighting Scheme in the Context of Vector Space Information Retrieval

This study introduces the Orbit Weighting Scheme(OWS),a novel approach aimed at enhancing the precision and efficiency of Vector Space information retrieval(IR)models,which have traditionally relied on weighting schemes like tf-idf and BM25.These conventional methods often struggle with accurately capturing document relevance,leading to inefficiencies in both retrieval performance and index size management.OWS proposes a dynamic weighting mechanism that evaluates the significance of terms based on their orbital position within the vector space,emphasizing term relationships and distribution patterns overlooked by existing models.Our research focuses on evaluating OWS’s impact on model accuracy using Information Retrieval metrics like Recall,Precision,InterpolatedAverage Precision(IAP),andMeanAverage Precision(MAP).Additionally,we assessOWS’s effectiveness in reducing the inverted index size,crucial for model efficiency.We compare OWS-based retrieval models against others using different schemes,including tf-idf variations and BM25Delta.Results reveal OWS’s superiority,achieving a 54%Recall and 81%MAP,and a notable 38%reduction in the inverted index size.This highlights OWS’s potential in optimizing retrieval processes and underscores the need for further research in this underrepresented area to fully leverage OWS’s capabilities in information retrieval methodologies.

Photodynamic patterning of living bacterial biofilms with high resolutions for information encryption and antibiotic screening

Controlling the growth of bacterial biofilms in a specific pattern greatly enhances the study of cell-to-cell interactions and paves the way for expanding their biolog-ical applications.However,the development of simple,cost-effective,and highly resolved biopatterning approaches remains a persistent challenge.Herein,a pio-neering photodynamic biopatterning technique for the creation of living bacterial biofilms with customized geometries at high resolutions is presented.First of all,an outstanding aggregation-induced emission photosensitizer is synthesized to enable efficient photodynamic bacterial killing at a low concentration.By combining with custom-designed photomasks featuring both opaque and transparent patterns,the viability of photosensitizer-coated bacteria is successfully manipulated by control-ling the degree of light transmittance.This process leads to the formation of living bacterial biofilms with specific patterns replicated from the photomask.Such an innovative strategy can be employed to generate living bacterial biofilms composed of either mono-or multispecies,with a spatial resolution of approximately 24µm.Furthermore,its potential applications in information storage/encryption and antibi-otic screening are explored.This study provides an alternative way to understand and investigate the intricate interactions among bacteria within 3D biofilms,hold-ing great promise in the controlled fabrication of dynamic biological systems for advanced applications.

Compensatory Damages in Personal Information Public Interest Litigation in China: Challenges and Prospects

In contrast to private interest litigation,public interest litigation provides a more potent solution to personal information infringements marked by extensive scope,unspecified victims,and limited individual loss.However,com⁃pensatory damages remain a contentious issue,both in theory and in practice,within the legal framework of personal in⁃formation public interest litigation.Through an empirical study conducted within China's judicial practice,this paper reveals that the pending issue concerning the nature and function of compensatory damages has caused highly contra⁃dictory verdicts regarding their calculation and allocation,as well as their relationship with other forms of pecuniary li⁃abilities.Only by acknowledging the role of compensatory damages imposed in personal information public interest liti⁃gation as"Skimming off Excess Profits",and affirming their function as deterrence rather than compensation can they truly achieve the broader objective of safeguarding personal information security and promoting public welfare,as well as avoid disrupting the harmony of the existing legal landscape.

The Influence of Information Technology(IT)on Accrual Accounting Adoption:The Case of the Jordanian Public Sector

Jordan is one of many countries that intends to reform its public sector by adopting accrual accounting,which is primarily carried out through the International Public Sector Accounting Standards(IPSAS)implementation plan,scheduled to be completed by 2021.Considering the difficulties of adoption,this process cannot be completed without an appropriate Information Technology(IT)system capable of providing the accounting information required for this reform.Therefore,this study aims to examine the influence of IT on accrual accounting adoption in the Jordanian public sector.The study employed the quantitative survey approach.Based on 331 usable questionnaires,the descriptive findings showed that the use of IT in the Jordanian public sector is relevant to daily accounting transactions in general and to accrual accounting in particular.The regression analysis showed a positive,significant relationship between IT use and accrual accounting practice.The IT specialist should be able to understand the needs of public sector in adopting accrual-based accounting.In line with today’s digitalization age,which integrates advanced technologies and numerous techniques,this study suggests that a combination of accounting and IT experts is a value added to sharpen the competitiveness of public sector reform.This study contributes to the extant literature in public sector,concerning the relationship between IT and accrual accounting adoption in the context of Jordan.

Applying the Technology Acceptance Model (TAM) in Information Technology System to Evaluate the Adoption of Decision Support System

With the beginning of the information systems’ spreading, people started thinking about using them for making business decisions. Computer technology solutions, such as the Decision Support System, make the decision-making process less complex and simpler for problem-solving. In order to make a high-quality business decision, managers need to have a great deal of appropriate information. Nonetheless, this complicates the process of making appropriate decisions. In a situation like that, the possibility of using DSS is quite logical. The aim of this paper is to find out the intended use of DSS for medium and large business organizations in USA by applying the Technology Acceptance Model (TAM). Different models were developed in order to understand and predict the use of information systems, but the information systems community mostly used TAM to ensure this issue. The purpose of the research model is to determine the elements of analysis that contribute to these results. The sample for the research consisted of the target group that was supposed to have completed an online questionnaire about the manager’s use of DSS in medium and large American companies. The information obtained from the questionnaires was analyzed through the SPSS statistical software. The research has indicated that, this is primarily used due to a significant level of Perceived usefulness and For the Perceived ease of use.

Application and prospects of spatial information technology in CO_(2)sequestration monitoring

This paper systematically reviews the current applications of various spatial information technologies in CO_(2)sequestration monitoring,analyzes the challenges faced by spatial information technologies in CO_(2)sequestration monitoring,and prospects the development of spatial information technologies in CO_(2)sequestration monitoring.Currently,the spatial information technologies applied in CO_(2)sequestration monitoring mainly include five categories:eddy covariance method,remote sensing technology,geographic information system,Internet of Things technology,and global navigation satellite system.These technologies are involved in three aspects:monitoring data acquisition,positioning and data transmission,and data management and decision support.Challenges faced by the spatial information technologies in CO_(2)sequestration monitoring include:selecting spatial information technologies that match different monitoring purposes,different platforms,and different monitoring sites;establishing effective data storage and computing capabilities to cope with the broad sources and large volumes of monitoring data;and promoting collaborative operations by interacting and validating spatial information technologies with mature monitoring technologies.In the future,it is necessary to establish methods and standards for designing spatial information technology monitoring schemes,develop collaborative application methods for cross-scale monitoring technologies,integrate spatial information technologies with artificial intelligence and high-performance computing technologies,and accelerate the application of spatial information technologies in carbon sequestration projects in China.

The Customer Requirements Analysis Method of Engineering Products Based on Multiple Preference Information

To effectively evaluate the fuzziness of the market environment in product planning,a customer requirements analysis method based on multiple preference information is proposed.Firstly,decision-makers use a preferred information form to evaluate the importance of each customer requirement.Secondly,a transfer function is employed to unify various forms of preference information into a fuzzy complementary judgment matrix.The ranking vector is then calculated using row and normalization methods,and the initial importance of customer requirements is obtained by aggregating the weights of decision members.Finally,the correction coefficients of initial importance and each demand are synthesized,and the importance of customer requirements is determined through normalization.The development example of the PE jaw crusher demonstrates the effectiveness and feasibility of the proposed method.

A Building Information Modeling-Life Cycle Cost Analysis Integrated Model to Enhance Decisions Related to the Selection of Construction Methods at the Conceptual Design Stage of Buildings

Life Cycle Cost Analysis (LCCA) provides a systematic approach to assess the total cost associated with owning, operating, and maintaining assets throughout their entire life. BIM empowers architects and designers to perform real-time evaluations to explore various design options. However, when integrated with LCCA, BIM provides a comprehensive economic perspective that helps stakeholders understand the long-term financial implications of design decisions. This study presents a methodology for developing a model that seamlessly integrates BIM and LCCA during the conceptual design stage of buildings. This integration allows for a comprehensive evaluation and analysis of the design process, ensuring that the development aligns with the principles of low carbon emissions by employing modular construction, 3D concrete printing methods, and different building design alternatives. The model considers the initial construction costs in addition to all the long-term operational, maintenance, and salvage values. It combines various tools and data through different modules, including energy analysis, Life Cycle Assessment (LCA), and Life Cycle Cost Analysis (LCCA) to execute a comprehensive assessment of the financial implications of a specific design option throughout the lifecycle of building projects. The development of the said model and its implementation involves the creation of a new plug-in for the BIM tool (i.e., Autodesk Revit) to enhance its functionalities and capabilities in forecasting the life-cycle costs of buildings in addition to generating associated cash flows, creating scenarios, and sensitivity analyses in an automatic manner. This model empowers designers to evaluate and justify their initial investments while designing and selecting potential construction methods for buildings, and enabling stakeholders to make informed decisions by assessing different design alternatives based on long-term financial considerations during the early stages of design.

The Claimed Revolution to Understand Consciousness:Information Plays the Driving/Essential Role for the Structuration and Behavior of the Living Organisms

A prestigious conference claimed recently a revolution in neuroscience to understand consciousness.In this paper it is shown that this revolution already came,revealing the determinant role of information for human and living structures,both for their structuration and behavior,explaining consciousness at human as the result of the activity of the Informational System of Human and Living Structures.For this,it is emphasized and discussed the informational structure of the eukaryotic cell,the basic/representative composing unit of the multicellular body of human,animals,and plants,showing that the composition and functions of the informational system are basically similar with that of human.To reveal the driving role of informational mechanisms in human and subhuman organisms,it is introduced the concept of matter-related information,showing that information can be hidden/“embodied”or released/“disembodied”in or from the elemental micro/macro components of the body,during the multiple chain/cascade interactions including transduction processes.It is shown that such interactions are initiated from two main categories of informational sources:implicit(genetic)and explicit(external/internal)sources,the first category leading to structuration of the body and the second the reactive behavior.Consciousness in human and subhuman organisms,expressed by two corresponding informational relations,is the result of the release of information by the mind,acting as an informational operator/device,the development degree of mind and consciousness depending on the complexity degree and adaptation.An analogy of this Informational Model of Human and Living Structures(IMHLS)with the ancient model of chakras is highlighted,showing that these models support each other,applied with beneficial effects in Reiki technique and music-based cognitive multi-task therapy for neuro-rehabilitation.

高速铁路日常客运量的EMD-Informer组合预测方法

铁路客流需求的科学预测是进行运输组织方案决策的重要依据。以高速铁路历史客票数据为基础,结合经验模态分解(empirical mode decomposition,EMD)与机器深度学习中的注意力机制,提出高速铁路日客流量的EMD-Informer组合预测方法。首先采用EMD方法分解高速铁路客流量序列,获得具有周期特征和线路客流内在特征的模态分量,再利用Informer模型分别训练和预测各模态分解分量,并通过多头注意力机制高效挖掘客流数据内在规律和捕捉数据序列中的关键特征,在此基础上重组各分量预测值,从而得到高速铁路日常客流的整体高精度预测值。同时,根据结合问题特征的大量实验,明确可供实际运用参考的超参数设置规则。基于京沪高速铁路全线的实例计算分析表明,相对对比预测方法,EMD-Informer组合预测方法在高速铁路客流的单步预测及超前预测上均具有明显更小的预测误差。