Informationization of coal enterprises and digital mine

Analyzed the main problems which were found in current conditions and prob- lems of informationization in coal enterprises.It clarified how to achieve informationization in coal mine and put forward a general configuration of informationization construction in which informationization in coal enterprises was divided into two parts: informationization of safety production and informationization of management.Planned a platform of inte- grated management of informationization in coal enterprises.Ultimately,it has brought forward that an overall integrated digital mine is the way to achieve the goal of informa- tionization in coal enterprises,which can promote the application of automation,digitaliza- tion,networking,informaitionization to intellectualization.At the same time,the competi- tiveness of enterprises can be improved entirely,and new type of coal industry can be supported by information technology.

Application of Big Data in Agricultural Informationization in Shandong Province under the Background of "Internet +"

This paper explains the basic concepts of " Internet + " and big data,analyzes the main problems in the application of big data technology in agricultural informationization of Shandong Province,summarizes corresponding solutions from the aspects of government guidance,financial input,open sharing of agricultural big data,big data storage and processing,data mining,etc.,and prospects the application trend of big data technology in agricultural informationization to achieve the connotative development of agriculture in Shandong Province.

On the informationization of accounting information in China： The perspective of accounting information systems and its regulatory framework in the USA

The informationization of accounting information systems has brought many improvements to those systems. This paper highlights some of those significant advances in the informationization of accounting information systems in China. As China has become a major industrial power in the international economy, further improvements for these information systems are critical to the continued successes of China. To additionally improve these systems, China can draw upon the systems from other world economic leaders. With its fully developed capital markets, the United States offers development experience for the external reporting components of a fully integrated information system. This paper discusses a typical integrated information system in the United States and addresses the regulatory milestones that were instrumental in the development of those external components of accounting information systems. Recommendations are presented for improving informationization of systems in China based on U.S. systems＇ responses to those milestones.

New Path for Integrated Reform of Urban and Rural Household Registration System in the Context of Informationization

In China, household registration system has the problems of unreasonable standard setting and relevant supporting measures failure to keep pace with the development trend. From analysis of current problems and situations, it is believed that household registration system should undertake reform and take a new road by means of informationization. Strengthening informationization management in land, population, education and labor market can better perform urban and rural integration.

Factors Obstructing Rural Informationization Development of Pingshan County of Hebei Province

The purpose of rural informationization is to provide effective information for farmers,increase production efficiency and income level of farmers in agricultural production.In recent years,under the guidance of No.1 document of central government,China's rural informationization has obtained considerable development.However,due to influence of terrain,mountain areas are still backward in informationization development.Combining actual conditions of Pingshan County of Hebei Province,the authors visited local farmers and made detailed survey on basic conditions of farmers,and analyzed factors obstructing agricultural informationization development in mountain areas,to provide theoretical reference for promoting informationization development in mountain areas and increasing income of local farmers.

Contribution Rate of Agricultural Informationization to Growth of Agricultural Economy in Hubei Province and Its Influencing Factors

Agricultural informationization is the objective demand for transforming the traditional agriculture and promoting the development of agricultural modernization. Using the statistical data of the gross agricultural output value of Hubei Province in 2005-2014,based on the C-D production function,it calculated the average contribution rate(2. 48%) of agricultural informationization to the growth of agricultural economy in Hubei Province,indicating that agricultural informationization can promote growth of agricultural economy. This is basically consistent with previous findings. In addition,investment in agricultural informationization and broadband access rate also influenced the growth of agricultural economy in Hubei Province. Therefore,government should further improve the infrastructure of agricultural informationization,strengthen training of farmers’ information skills,establish auxiliary mechanism for achievement feedback of information-based agricultural production,increase the contribution rate of informationization to agricultural operation and management,promote the contribution of informationization to the growth of agricultural economy,so as to increase agricultural income of farmers.

Construct the Community of IT Education and Break the Bottleneck of Rural School Educational Informationization

Based on the current situation of rural educational informationization, my study found that the boost of rural elementary and secondary school’s educational informationization needed the cooperation of higher normal universities and local education administrative department. The construction of “IT education community” is the key to step off the predicament. The practice application and effect in Gaoping City further proved that the cooperation project broke the bottleneck of rural elementary and secondary school’s educational informationization.

Analysis on Development of Rural Financial Management Informationization

With the constant development of China's economy,rural financial management information gradually plays a major role in China's economic development. This paper mainly studied related management information of accounting information system and main characteristics of rural management. On the basis of analysis,it came up with pertinent recommendations,including improving software for financial informationization,improving the quality of rural financial personnel,strengthening government support for rural financial management informationization,and enhancing popularization of accounting computerized software.

Investigation of Enterprise Informationization Project Risk

The enterprise informationization （El） project has already become modernization level and synthesis power of the enterprise. However, information project risk. In order to reduce the El project risk, it is necessary to adopt reasonable incentive and constraint effectively and to structure perfect market environment. an urgent work to raise the asymmetry increases the EI investment mode, to carry on incentive and constraint effectively and to structure perfect market environment.

Analysis and Evaluation of Non-systematic Risks in Enterprise Informationization

Enterprise Informationization （El） is encountering a large variety of non-systematic risks in demanding and planning, designing and selecting, implementing and controlling, managerial and cultural aspects,due to which the investment in IT normally cannot simultaneously create the expected commercial values. Through analyzing the factors influencing non-systematic risks of EI, the paper established a risk evaluating index system and accordingly proposed a set of appropriate risk evaluating methodology, with which enterprise can well control informationization risks.

Problems and Countermeasures of Cultivating Autonomous English Learning Ability in Vocational Colleges based on Informationization

With the advent of 5G era,it has become an inevitable trend to drive educational modernization with educational informationization.The modern-day education uses science and technology as well as culture in cultivating independent learning as the ultimate goal.However,there are many drawbacks in the system and practical aspects of higher vocational education in which one of it is that the independent learning has been neglected in the learning process.This article analyzed the issues in the autonomous learning of the English language among higher vocational college students and discussed strategies to improve their autonomous learning ability based on informationization to promote bidirectional interaction between teachers and students,cultivate students'consciousness of lifelong learning,improve teachers5 technical skills,and perfect the development of a connotative system in higher vocational colleges.

LiDAR-Visual SLAM with Integrated Semantic and Texture Information for Enhanced Ecological Monitoring Vehicle Localization

Ecological monitoring vehicles are equipped with a range of sensors and monitoring devices designed to gather data on ecological and environmental factors.These vehicles are crucial in various fields,including environmental science research,ecological and environmental monitoring projects,disaster response,and emergency management.A key method employed in these vehicles for achieving high-precision positioning is LiDAR(lightlaser detection and ranging)-Visual Simultaneous Localization and Mapping(SLAM).However,maintaining highprecision localization in complex scenarios,such as degraded environments or when dynamic objects are present,remains a significant challenge.To address this issue,we integrate both semantic and texture information from LiDAR and cameras to enhance the robustness and efficiency of data registration.Specifically,semantic information simplifies the modeling of scene elements,reducing the reliance on dense point clouds,which can be less efficient.Meanwhile,visual texture information complements LiDAR-Visual localization by providing additional contextual details.By incorporating semantic and texture details frompaired images and point clouds,we significantly improve the quality of data association,thereby increasing the success rate of localization.This approach not only enhances the operational capabilities of ecological monitoring vehicles in complex environments but also contributes to improving the overall efficiency and effectiveness of ecological monitoring and environmental protection efforts.

Secure Channel Estimation Using Norm Estimation Model for 5G Next Generation Wireless Networks

The emergence of next generation networks(NextG),including 5G and beyond,is reshaping the technological landscape of cellular and mobile networks.These networks are sufficiently scaled to interconnect billions of users and devices.Researchers in academia and industry are focusing on technological advancements to achieve highspeed transmission,cell planning,and latency reduction to facilitate emerging applications such as virtual reality,the metaverse,smart cities,smart health,and autonomous vehicles.NextG continuously improves its network functionality to support these applications.Multiple input multiple output(MIMO)technology offers spectral efficiency,dependability,and overall performance in conjunctionwithNextG.This article proposes a secure channel estimation technique in MIMO topology using a norm-estimation model to provide comprehensive insights into protecting NextG network components against adversarial attacks.The technique aims to create long-lasting and secure NextG networks using this extended approach.The viability of MIMO applications and modern AI-driven methodologies to combat cybersecurity threats are explored in this research.Moreover,the proposed model demonstrates high performance in terms of reliability and accuracy,with a 20%reduction in the MalOut-RealOut-Diff metric compared to existing state-of-the-art techniques.

Joint Feature Encoding and Task Alignment Mechanism for Emotion-Cause Pair Extraction

With the rapid expansion of social media,analyzing emotions and their causes in texts has gained significant importance.Emotion-cause pair extraction enables the identification of causal relationships between emotions and their triggers within a text,facilitating a deeper understanding of expressed sentiments and their underlying reasons.This comprehension is crucial for making informed strategic decisions in various business and societal contexts.However,recent research approaches employing multi-task learning frameworks for modeling often face challenges such as the inability to simultaneouslymodel extracted features and their interactions,or inconsistencies in label prediction between emotion-cause pair extraction and independent assistant tasks like emotion and cause extraction.To address these issues,this study proposes an emotion-cause pair extraction methodology that incorporates joint feature encoding and task alignment mechanisms.The model consists of two primary components:First,joint feature encoding simultaneously generates features for emotion-cause pairs and clauses,enhancing feature interactions between emotion clauses,cause clauses,and emotion-cause pairs.Second,the task alignment technique is applied to reduce the labeling distance between emotion-cause pair extraction and the two assistant tasks,capturing deep semantic information interactions among tasks.The proposed method is evaluated on a Chinese benchmark corpus using 10-fold cross-validation,assessing key performance metrics such as precision,recall,and F1 score.Experimental results demonstrate that the model achieves an F1 score of 76.05%,surpassing the state-of-the-art by 1.03%.The proposed model exhibits significant improvements in emotion-cause pair extraction(ECPE)and cause extraction(CE)compared to existing methods,validating its effectiveness.This research introduces a novel approach based on joint feature encoding and task alignment mechanisms,contributing to advancements in emotion-cause pair extraction.However,the study’s limitation lies in the data sources,potentially restricting the generalizability of the findings.

Structural Modal Parameter Recognition and Related Damage Identification Methods under Environmental Excitations: A Review

Modal parameters can accurately characterize the structural dynamic properties and assess the physical state of the structure.Therefore,it is particularly significant to identify the structural modal parameters according to the monitoring data information in the structural health monitoring(SHM)system,so as to provide a scientific basis for structural damage identification and dynamic model modification.In view of this,this paper reviews methods for identifying structural modal parameters under environmental excitation and briefly describes how to identify structural damages based on the derived modal parameters.The paper primarily introduces data-driven modal parameter recognition methods(e.g.,time-domain,frequency-domain,and time-frequency-domain methods,etc.),briefly describes damage identification methods based on the variations of modal parameters(e.g.,natural frequency,modal shapes,and curvature modal shapes,etc.)and modal validation methods(e.g.,Stability Diagram and Modal Assurance Criterion,etc.).The current status of the application of artificial intelligence(AI)methods in the direction of modal parameter recognition and damage identification is further discussed.Based on the pre-vious analysis,the main development trends of structural modal parameter recognition and damage identification methods are given to provide scientific references for the optimized design and functional upgrading of SHM systems.

利用聚类算法提高微地震初至拾取的稳定性

高效且准确地拾取有效信号的初至是微地震监测技术的关键。目前常用的微地震初至拾取算法是能量比算法,该算法应用简单且拾取效率高。但是能量比算法存在的主要问题是算法的抗噪性较差,拾取误差较大。为此,将聚类算法应用于微地震信号初至拾取,改进现有拾取算法。首先通过能量比算法对微地震初至进行一次拾取;然后通过聚类算法对一次拾取结果进行优化,提取其中的小误差初至;再对提取出的小误差初至的分布进行拟合,根据分布规律校正误差较大的初至;最后以优化后的初至为中心开时窗并利用AIC(Akaike Infor⁃mation Criteria)算法对微地震信号进行精细拾取。该算法结合了能量比算法和AIC算法的优点。实际数据测试结果表明,与传统算法相比该算法具有较高的拾取精度和抗噪性,而且可以有效识别多震相初至。此外,该算法的运算效率很高,适用于现场实时处理。

基于Revit平台的隔震支座快速建模模块开发与应用

随着隔震技术的推广应用以及建筑业信息化水平的持续提升,在隔震工程中对隔震层建筑信息模型(building information modeling, BIM)建模的需求逐渐增长,然而针对性的研究工作相对较少。为此,围绕隔震支座BIM模型的高效建模方法和应用模块开展了研究。首先,综合隔震支座应用情况和力学特性,可将其分为橡胶隔震支座、滑移摩擦隔震支座和其他类型隔震支座,据此提出了隔震支座BIM快速建模模块基本架构;随后,基于Revit和Visual Studio平台开发了三类隔震支座BIM模型的快速建模功能,并实现了连接节点参数化建模和支座批量/手动布置的操作功能;最后,开展了某化工公司的库房隔震加固项目的隔震层BIM模型建模实践,结果表明:利用快速建模模块可将隔震层BIM建模操作从7个步骤降低至2个步骤,且使用过程中对隔震支座构造细节的认知要求相对较低。同时,建成后的BIM模型与实际工程在建筑信息的多个方面具有较好的一致性。相关研究可为建筑和桥梁隔震工程的BIM建模提供参考和借鉴。

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.

Computing Power Network:A Survey

With the rapid development of cloud computing,edge computing,and smart devices,computing power resources indicate a trend of ubiquitous deployment.The traditional network architecture cannot efficiently leverage these distributed computing power resources due to computing power island effect.To overcome these problems and improve network efficiency,a new network computing paradigm is proposed,i.e.,Computing Power Network(CPN).Computing power network can connect ubiquitous and heterogenous computing power resources through networking to realize computing power scheduling flexibly.In this survey,we make an exhaustive review on the state-of-the-art research efforts on computing power network.We first give an overview of computing power network,including definition,architecture,and advantages.Next,a comprehensive elaboration of issues on computing power modeling,information awareness and announcement,resource allocation,network forwarding,computing power transaction platform and resource orchestration platform is presented.The computing power network testbed is built and evaluated.The applications and use cases in computing power network are discussed.Then,the key enabling technologies for computing power network are introduced.Finally,open challenges and future research directions are presented as well.

Deployment optimization for target perpetual coverage in energy harvesting wireless sensor network

Energy limitation of traditional Wireless Sensor Networks(WSNs)greatly confines the network lifetime due to generating and processing massive sensing data with a limited battery.The energy harvesting WSN is a novel network architecture to address the limitation of traditional WSN.However,existing coverage and deployment schemes neglect the environmental correlation of sensor nodes and external energy with respect to physical space.Comprehensively considering the spatial correlation of the environment and the uneven distribution of energy in energy harvesting WSN,we investigate how to deploy a collection of sensor nodes to save the deployment cost while ensuring the target perpetual coverage.The Confident Information Coverage(CIC)model is adopted to formulate the CIC Minimum Deployment Cost Target Perpetual Coverage(CICMTP)problem to minimize the deployed sensor nodes.As the CICMTP is NP-hard,we devise two approximation algorithms named Local Greedy Threshold Algorithm based on CIC(LGTA-CIC)and Overall Greedy Search Algorithm based on CIC(OGSA-CIC).The LGTA-CIC has a low time complexity and the OGSA-CIC has a better approximation rate.Extensive simulation results demonstrate that the OGSA-CIC is able to achieve lower deployment cost and the performance of the proposed algorithms outperforms GRNP,TPNP and EENP algorithms.