横河电机与Fluence Analytics公司签署合作协议

横河电机公司宣布投资Fluence Analytics公司。这是一家总部位于美国的初创公司,为聚合物制造商提供硬件和软件分析解决方案。两家公司决定建立全球战略业务合作伙伴关系,以销售和部署Fluence Analytics的聚合反应自动连续在线监测(ACOMP)系统的新高端机型。根据合作协议的条款,横河将在2021年内针对现有的ACOMP机型在客户端推进试用,并对未来推出的新机型拥有独家销售权(部分地区为独家联合销售权)。横河还将负责该产品的工程和系统集成,并为化学行业的客户提供售后服务。

Orientation and Decision-Making for Soccer Based on Sports Analytics and AI:A Systematic Review

Due to ever-growing soccer data collection approaches and progressing artificial intelligence(AI) methods, soccer analysis, evaluation, and decision-making have received increasing interest from not only the professional sports analytics realm but also the academic AI research community. AI brings gamechanging approaches for soccer analytics where soccer has been a typical benchmark for AI research. The combination has been an emerging topic. In this paper, soccer match analytics are taken as a complete observation-orientation-decision-action(OODA) loop.In addition, as in AI frameworks such as that for reinforcement learning, interacting with a virtual environment enables an evolving model. Therefore, both soccer analytics in the real world and virtual domains are discussed. With the intersection of the OODA loop and the real-virtual domains, available soccer data, including event and tracking data, and diverse orientation and decisionmaking models for both real-world and virtual soccer matches are comprehensively reviewed. Finally, some promising directions in this interdisciplinary area are pointed out. It is claimed that paradigms for both professional sports analytics and AI research could be combined. Moreover, it is quite promising to bridge the gap between the real and virtual domains for soccer match analysis and decision-making.

A Weighted Multi-Layer Analytics Based Model for Emoji Recommendation

The developed system for eye and face detection using Convolutional Neural Networks(CNN)models,followed by eye classification and voice-based assistance,has shown promising potential in enhancing accessibility for individuals with visual impairments.The modular approach implemented in this research allows for a seamless flow of information and assistance between the different components of the system.This research significantly contributes to the field of accessibility technology by integrating computer vision,natural language processing,and voice technologies.By leveraging these advancements,the developed system offers a practical and efficient solution for assisting blind individuals.The modular design ensures flexibility,scalability,and ease of integration with existing assistive technologies.However,it is important to acknowledge that further research and improvements are necessary to enhance the system’s accuracy and usability.Fine-tuning the CNN models and expanding the training dataset can improve eye and face detection as well as eye classification capabilities.Additionally,incorporating real-time responses through sophisticated natural language understanding techniques and expanding the knowledge base of ChatGPT can enhance the system’s ability to provide comprehensive and accurate responses.Overall,this research paves the way for the development of more advanced and robust systems for assisting visually impaired individuals.By leveraging cutting-edge technologies and integrating them into amodular framework,this research contributes to creating a more inclusive and accessible society for individuals with visual impairments.Future work can focus on refining the system,addressing its limitations,and conducting user studies to evaluate its effectiveness and impact in real-world scenarios.

Game Theory Based Model for Predictive Analytics Using Distributed Position Function

This paper presents a game theory-based method for predicting the outcomes of negotiation and group decision-making problems. We propose an extension to the BDM model to address problems where actors’ positions are distributed over a position spectrum. We generalize the concept of position in the model to incorporate continuous positions for the actors, enabling them to have more flexibility in defining their targets. We explore different possible functions to study the role of the position function and discuss appropriate distance measures for computing the distance between the positions of actors. To validate the proposed extension, we demonstrate the trustworthiness of our model’s performance and interpretation by replicating the results based on data used in earlier studies.

Evaluation of a software positioning tool to support SMEs in adoption of big data analytics

Big data analytics has been widely adopted by large companies to achieve measurable benefits including increased profitability,customer demand forecasting,cheaper development of products,and improved stock control.Small and medium sized enterprises(SMEs)are the backbone of the global economy,comprising of 90%of businesses worldwide.However,only 10%SMEs have adopted big data analytics despite the competitive advantage they could achieve.Previous research has analysed the barriers to adoption and a strategic framework has been developed to help SMEs adopt big data analytics.The framework was converted into a scoring tool which has been applied to multiple case studies of SMEs in the UK.This paper documents the process of evaluating the framework based on the structured feedback from a focus group composed of experienced practitioners.The results of the evaluation are presented with a discussion on the results,and the paper concludes with recommendations to improve the scoring tool based on the proposed framework.The research demonstrates that this positioning tool is beneficial for SMEs to achieve competitive advantages by increasing the application of business intelligence and big data analytics.

A review on edge analytics:Issues,challenges,opportunities,promises,future directions,and applications

Edge technology aims to bring cloud resources(specifically,the computation,storage,and network)to the closed proximity of the edge devices,i.e.,smart devices where the data are produced and consumed.Embedding computing and application in edge devices lead to emerging of two new concepts in edge technology:edge computing and edge analytics.Edge analytics uses some techniques or algorithms to analyse the data generated by the edge devices.With the emerging of edge analytics,the edge devices have become a complete set.Currently,edge analytics is unable to provide full support to the analytic techniques.The edge devices cannot execute advanced and sophisticated analytic algorithms following various constraints such as limited power supply,small memory size,limited resources,etc.This article aims to provide a detailed discussion on edge analytics.The key contributions of the paper are as follows-a clear explanation to distinguish between the three concepts of edge technology:edge devices,edge computing,and edge analytics,along with their issues.In addition,the article discusses the implementation of edge analytics to solve many problems and applications in various areas such as retail,agriculture,industry,and healthcare.Moreover,the research papers of the state-of-the-art edge analytics are rigorously reviewed in this article to explore the existing issues,emerging challenges,research opportunities and their directions,and applications.

Exploring the Association between Climate Change and Human Development: A Visual Analytics Study

This study explores the complex relationship between climate change and human development. The aim is to understand how climate change affects human development across countries, regions, and the global population. Visual analytics were used to examine the impact of various climate change indicators on different aspects of human development. The study highlights the urgent need for climate change action and encourages policymakers to make decisive moves. Climate change adversely affects numerous aspects of daily life, leading to significant consequences that must be addressed through policy changes and global governance recommendations. Key findings include that regions with higher CO2 emissions experience a significantly higher incidence of life-threatening diseases compared to regions with lower emissions. Additionally, higher CO2 emissions correlate with consistent death rates. Increased pollution exposure is associated with a higher prevalence of life-threatening diseases and higher rates of malnutrition. Moreover, greater mineral depletion is linked to more frequent life-threatening diseases, suggesting that industrialization contributes to adverse health effects. These results provide valuable insights for policy and decision-making aimed at mitigating the impact of climate change on human development.

Leveraging Predictive Analytics for Strategic Corporate Communications: Enhancing Stakeholder Engagement and Crisis Management

This study explores the integration of predictive analytics in strategic corporate communications, with a specific focus on stakeholder engagement and crisis management. Our mixed-methods approach, which combines a comprehensive literature review with case studies of five multinational corporations, allows us to investigate the applications, challenges, and ethical implications of leveraging predictive models in communication strategies. While our findings reveal significant potential for enhancing personalized content delivery, real-time sentiment analysis, and proactive crisis management, we stress the need for careful consideration of challenges such as data privacy concerns and algorithmic bias. This emphasis on ethical implementation is crucial in navigating the complex landscape of predictive analytics in corporate communications. To address these issues, we propose a framework that prioritizes ethical considerations. Furthermore, we identify key areas for future research, thereby contributing to the evolving field of data-driven communication management.

横河电机收购数字化聚合反应过程监测公司Fluence Analytics

横河电机株式会社宣布收购Fluence Analytics公司,这是一家总部位于美国的初创公司,为全球聚合物和生物制药公司提供实时分析解决方案。自2021年8月签署投资与合作协议以来,两家公司一直在探索潜在的商机。通过此次收购,Fluence Analytics将整合其业务与横河电机的现有业务,并进一步增强其技术能力。自今日起,Fluence Analytics将作为Yokogawa Fluence Analytics运营。

新《公司法》若干重要问题解读(笔谈)

新《公司法》修订所涉及的内容非常丰富,修订内容包括公司登记制度、股东出资责任、公司治理制度、公司资本制度、控股股东义务、董监高信义义务等方面。赵旭东教授指出,本次《公司法》修订在公司登记与信息公示制度、股东出资责任和法律后果、公司资本制度、公司治理制度、股东权益保护和控股股东义务这五个关键领域实现了重大突破和创新。周林彬教授集中解析了“国家出资公司组织机构的特别规定”一章,认为新《公司法》的亮点之一是通过新设这一章积极回应了我国国有企业治理的“本土实践”与“中国问题”,给出新时期国有企业治理的“中国方案”,推进了中国特色的国有企业治理制度的设计,重塑了国有企业的规范体系。刘凯湘教授对本次《公司法》修订中与公司资本制度相关的若干条文展开解析,包括限期认缴制、新增有限公司股东出资义务加速到期制度、股东违反出资义务的责任承担规则、董事会的催缴出资义务、股东失权制度、董监高对股东抽逃出资的连带责任、类别股的规定、授权资本制等。赵万一教授深入探讨了这次《公司法》修改的主要特点,认为新《公司法》既坚持了其商法属性,同时又充分考虑了《民法典》的既有制度内容,适当兼顾了与《民法典》之间的制度衔接关系,从而既为科学解决民法与商法的关系提供了理念和制度支持,也为中国式法律制度体系的创建提供了完美的立法实践样本。周友苏教授深入解析了新《公司法》在完善股东出资制度方面增加的股东出资缴纳、股东出资“加速到期”、股东失权、股东出资责任这四条新规定,认为新《公司法》在完善股东出资制度方面增加的这些新规定,积极回应了我国自2013年以来公司数量大幅增长所带来的股东盲目认缴、天价认缴、期限过长的现象突出,损害债权人利益的纠纷案件呈明显上升态势等问题,极大地强化了保护债权人的力度。李建伟教授深入解析了《公司法》修订中与法定代表人制度相关的若干条文,认为新《公司法》关于法定代表人的规定较之以往更加体系化,并有望基本解决困扰公司实践许多年的诸多难题,但其中亦存在不完全规范的问题。

中国式员工持股计划与公司违规:监督者抑或合谋者

以我国员工持股计划重启为背景,以2011—2019年A股上市公司为样本,验证员工持股计划对公司违规的影响。结果显示,员工持股计划降低了公司违规概率与频率。机制检验发现,员工持股计划一方面通过促进中小股东投票与委派董事涉入公司内部治理,另一方面通过信息传递提升独立董事履职效率并增加分析师跟踪。进一步地,区分违规类型后发现,员工持股计划的抑制作用主要存在于信息披露违规与一般违规;区分员工持股计划方案后发现,员工持股规模高、锁定期长、高购买折价、无杠杆、无控股股东担保或兜底、无业绩条件的员工持股计划对公司违规的抑制更显著。经济后果分析发现,员工持股计划对公司违规的监督能够抑制股价崩盘风险。研究结论从公司违规角度验证了员工持股计划的监督者角色,为我国员工持股计划实施效果提供了新的经验证据。

论公司法规制国家出资公司的口径与路径

新修订的公司法增加了第七章“国家出资公司组织机构的特别规定”,实现公司法对国家出资公司的规制体例编排“从节到章”、条款数量“从少到多”以及适用范围“从国有独资到国家出资”的重要进步,相当程度上克服了原公司法中存在的规制理念陈旧、口径局限、路径紊乱等缺陷。但新公司法仍存在规制口径模糊、组织规范制度供给不足等痼疾,需要进一步校准国家出资公司的规制口径,将国有独资公司的全资子公司纳入其中,保证规制逻辑的周延性;继续改进规制路径与立法技术,通过引致技术简化关联部门法的重复性规定,增加具有制度特色的治理规则供给,包括完善党组织条款,细化外部董事条款,鼓励并引导国有控股公司章程设置赋权性的差异化治理条款,以提升公司法的适应性品格。

ESG表现如何赋能企业绿色技术创新?--来自中国上市公司的微观证据

经济新发展阶段下ESG是可持续导向下企业运营的重要理念。在绿色发展导向下,如何将企业环境、社会与公司治理(ESG)等多重责任嵌入到企业创新体系之中,驱动传统创新向绿色创新与绿色发展转型,成为了学界关注的焦点议题。本文以2011年—2019年中国沪深A股上市公司为研究样本,考察了上市公司ESG表现对企业绿色技术创新的影响及其内在作用机制。研究结果表明:(1)企业ESG表现驱动了企业绿色技术创新,对企业绿色技术创新具有显著的促进效应,在考虑内生性问题后研究结论依然稳健;区分ESG表现各类维度,企业环境责任、社会责任与公司治理表现对企业绿色技术创新均产生显著的促进效应。(2)内在机制检验结果表明,ESG表现主要通过强化企业环保投入、缓解企业融资约束以及提高企业内部控制质量以促进企业绿色技术创新。(3)调节机制检验结果表明,外部环境规制(环保补助与排污收费)与内部高管激励(薪酬激励与股权激励)在ESG表现与企业绿色技术创新之间产生显著的正向调节效应,即在ESG表现驱动企业绿色技术创新过程中,外部环境规制与内部高管激励制度具有外部的资源补偿效应、合法性倒逼效应以及内部激励效应。(4)异质性分析结果表明,ESG表现对企业绿色技术创新的驱动效应在国有企业、通过国际ISO14001环境认证企业与制造业企业中更为明显。而且经济效应检验结果表明,ESG表现驱动企业绿色技术创新有助于企业改善经济绩效。本研究为绿色发展导向下强化企业ESG理念,基于可持续导向与企业社会责任融入企业创新体系驱动企业绿色转型发展,最终实现企业与社会环境的共生融合发展提供政策启示。

我国农业上市公司资本结构对财务绩效影响研究

农业在我国国民经济中发挥着至关重要的作用,农业上市公司良好的绩效水平对产业结构调整具有一定导向作用,而资本结构既影响企业的财务绩效,也影响农业企业价值的提升。文章以资本结构为切入点,研究我国农业上市公司资本结构与财务绩效之间的关系,选取农业上市公司2017—2022年数据作为研究样本,建立评价我国农业上市公司财务绩效的多元线性回归模型,以揭示其资本结构与财务绩效的关系。研究结果表明,我国农业上市公司的资产负债率与财务绩效之间呈显著负相关关系,流动负债率与财务绩效之间呈线性负相关关系但不显著,第一大股东持股比例与财务绩效之间呈显著正相关关系。根据研究结果,提出优化农业上市公司资本结构,提高企业财务绩效的相关建议。

上市公司ESG报告“漂绿”行为治理

“双碳”目标提出以来,社会各界对生态环境保护和经济绿色转型发展的关切与日俱增,但是上市公司ESG报告的披露质量良莠不齐,“漂绿”问题成为我国生态文明建设中极不和谐的音符。文章首先介绍了影响上市公司“漂绿”ESG报告的内外部因素,再结合我国ESG信息披露的要求和治理现状,从公司内部治理的角度出发,提出将党组织融入公司治理体系、贯彻“高层承诺原则”、加强董事会能力建设、强化监事会权责、培养绿色诚信的公司文化、主动披露ESG鉴证报告等治理措施。从公司内部治理角度加强对“漂绿”的研究和治理,完善公司内部治理机制,有助于从长远提高公司环境和经济绩效、提高ESG报告的质量。

国际能源化工公司生物化工业务发展策略分析

生物化工通常以生物质为原料,或采用相对温和的生物发酵过程,具有典型的绿色特征,已成为“净零碳”目标下国际能源化工公司战略布局的重点之一。巴斯夫、道达尔能源、杜邦、埃克森美孚4家公司生物化工业务入局较早,且非常重视技术创新,结合自身优势各有侧重地部署新业务。巴斯夫推出生物质平衡方案,重视关键中间体的生物替代,围绕工业生物技术超前布局;道达尔能源以生物燃料为切入点,上下游统筹布局,不断强化产品优势;杜邦公司敏锐捕捉市场机遇,持续追求差异化竞争优势;埃克森美孚坚持油品业务主线,适时调整生物燃料布局重点,保持技术的领先性。我国企业可借鉴国际主要能源化工公司的发展模式及经验,结合公司业务定位,加速科技创新向产业应用转变。

基于ISM-AHP-Entropy航空公司风险因素研究

针对航空公司风险因素研究,引入ISM-AHP-Entropy综合评价方法对风险因素进行评价。构建了风险因素指标体系,利用解析结构模型(ISM)将因素指标分为表层和深层致因,构建结构模型;根据问卷结果,用AHP-Entropy求出综合权重,结果表明人因和管理因素对风险影响最为显著;进一步运用AHP-Entropy综合法分别计算表层和深层致因权重并分析,结果表明表层致因中机组资源管理水平、签派员应急处置能力影响最为显著,深层致因中安全规章方针的制定情况、应急管理培训与实施情况影响最为显著;从多个现实角度出发,结合CBTA理念,为航空公司降低风险、提高安全意识与水平提出多条建议,可供航空公司参考采纳。

基于机器学习的上市公司审计风险识别

审计风险的准确识别有助于提高会计师事务所执业质量、规范上市公司行为,对于促进资本市场健康运行至关重要。因此,本文提出了一种机器学习框架,主要由因变量增强、自变量筛选和LightGBM模型训练三部分组成,以准确识别上市公司的审计风险水平。通过利用沪深两市A股上市公司2005—2019年的28918个样本进行实证分析,结果表明本文所提出的机器学习框架在高审计风险样本中的识别准确性达到94%,显著优于传统的审计风险识别方法,并且发现真实盈余管理、市场化程度、会计稳健性、预付账款和其他应收款占总资产的比重、每股经营活动现金流量等变量对于准确识别审计风险起到重要作用。

商业银行设立理财子公司能够实现风险隔离吗?

本文以中国商业银行设立理财子公司为准自然实验,基于2018—2021年84家银行的季度财务数据,采用渐进双重差分模型(DID)考察商业银行设立理财子公司的风险隔离效应。研究发现:设立理财子公司显著降低了母公司商业银行的风险承担,能够实现理财业务与其他业务的风险隔离,且设立时间越长,风险隔离效应越显著。异质性检验和机制分析表明,这种风险隔离效应在城商行与农商行中最弱;“去嵌套、降杠杆”和“去池化、缓错配”是实现风险隔离的主要机制。对母公司商业银行和理财子公司并表的进一步分析发现,设立理财子公司不能降低银行控股集团的整体风险承担,仅能实现风险隔离。这些研究发现对于完善商业银行内部控制和外部监管具有重要启示。

系统重要性金融科技公司的法律规制

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