Assessment of challenges and strategies for driving energy transitions in emerging markets:A socio-technological systems perspective

The pursuit of improved quality of life standards has significantly influenced the contemporary mining model in the 21st century.This era is witnessing an unprecedented transformation driven by pressing concerns related to sustainability,climate change,the just energy transition,dynamic operating environments,and complex social challenges.Such transitions present both opportunities and obstacles.The aim of this study is to provide an extensive literature review on energy transition to identify the challenges and strategies associated with navigating transformations in energy systems.Understanding these transformations is particularly critical in the face of the severe consequences of global warming,where an accelerated energy transition is viewed as a universal remedy.Adopting a socio-technological systems perspective,specifically through the application of Actor Network Theory(ANT),this research provides a theoretical foundation while categorising challenges into five distinct domains and outlining strategies across these different dimensions.These insights are specifically tailored for emerging market countries to effectively navigate energy transition while fostering the development of resilient societies.Furthermore,our findings highlight that energy transition encompasses more than a mere technological shift;it entails fundamental changes in various systemic socio-economic imperatives.Through focusing on the role of social structures in transitions,this study makes a significant and innovative contribution to ANT,which has historically been criticised for its limited acknowledgement of social structures.Consequently,we propose an emerging market energy transition framework,which not only addresses technological aspects,but also integrates social considerations.This framework paves the way for future research and exploration of energy transition dynamics.The outcomes of this study offer valuable insights to policymakers,researchers,and practitioners engaged in the mining industry,enabling them to comprehend the multifaceted challenges involved and providing practical strategies for effective resolution.Through incorporating the social dimension into the analysis,we enhance the understanding of the complex nature of energy system transformations,facilitating a more holistic approach towards achieving sustainable and resilient energy transitions in emerging markets and beyond.

Surgeon Perspectives on Anastomotic Leaks and FluidAI’s StreamTM Platform: Integrating Qualitative Insights for Technological Innovation

Purpose: This article investigates the critical importance of integrating surgeons’ direct input into the development of innovative technologies that address gaps in surgical care, including those aimed at reducing anastomotic leaks (AL), a major complication in gastrointestinal surgery. While traditional quantitative research methods are prevalent, they often overlook the invaluable insights of the surgeons who manage these complications firsthand. Subjects and Methods: This study employs a qualitative approach, utilizing semi-structured interviews with 40 surgeons from various specialties, including general, bariatric, colorectal, trauma, hepato-biliary, and thoracic surgery. The interviews were designed to probe the needs of surgeons, challenges currently faced, and gaps in clinical practice, research, and technology for detection and/or management of AL. The data were analyzed using thematic analysis, which revealed significant gaps in current technologies for early detection and prevention of leaks. Results: Surgeons expressed strong interest in FluidAI’s Stream™ Platform, a non-invasive medical device designed to monitor postoperative drainage fluid in real-time, providing continuous data on AL risk. The ability of this platform to offer early prediction through pH and electrical conductivity analysis was particularly appealing to participants, who emphasized the importance of timely interventions in improving patient outcomes. The study’s findings highlight not only the clinical challenges but also the emotional toll that AL takes on surgeons, underlining the need for innovations that are both data-driven and humanistic. Conclusion: By centering surgeons’ perspectives, this research advocates for a human-centered approach to technological advancement, ensuring that new tools are both clinically effective and aligned with the real-world needs of surgical practitioners.

An Assessment on the Impact of Technological Addiction on Workplace Productivity: Case of the Public Sector in Zimbabwe

With the increasing integration of technology in modern workplaces, concerns have emerged regarding the addictive nature of technology and its potential consequences on employee productivity. This research aims to investigate the impact of technological addiction on workplace productivity within the public sector of Zimbabwe. The study employed a mixed-methods approach, combining surveys, interviews, and a case study analysis, to examine the prevalence and effects of technological addiction in affecting productivity in the public sector of Zimbabwe. The findings indicate that excessive use of social media, and other digital distractions is a growing concern in the public sector, leading to decreased focus, missed deadlines, and strained teamwork. Factors such as unrestricted internet access, lack of clear usage policies, and inadequate self-regulation contribute to the problem The research outcomes also highlight the need for awareness and interventions to address social media addiction in the workplace, promote healthier technology use, and uphold productivity and employee well-being.

Aiming Far Beyond the Moon--The Third Plenary Session highlights science and technological development

Change is the Chinese moon goddess.Named after her,the Chang'e-6 lunar module returned to Earth this June carrying 1,935.3grams of rocks and dust from the far side of the moon.China's lunar program began as recently as 2007 when Chang'e-I was placed in orbit to create a high resolution 3-D map of the moon's surface.As such,it illustrates China's enviable ability to concentrate its efforts on major tasks.This ability,as Chinese President Xi Jinping has suggested,is one of the major advantages of China's socialist system.

Integrating GPT into the Journalism and Communication Industries:The Technological Logic,Ecosystem Reconstruction,and Ethical Chal enges

Generative AI,represented by GPT(Generative Pre-trained Transformer),is now leading the technological revolution and is reconstructing the journalism and communication industries'ecosystems because of its powerful generative capacity and diverse range of outputs.While GPT is busy revolutionizing and innovating the production of news content,working patterns,and operation modes,it has also given rise to ethical concerns in regard to news authenticity,data security,humanistic values,and other related aspects.Therefore,it is imperative to initiate strategies and approaches,such as establishing a mechanism for verifying information authenticity,enhancing data security and privacy regulations,and instituting an ethical supervision and governance framework for AI,in order to facilitate the systematic advancement of AI-based news production while reinstating public trust.

Problems and Countermeasures in the Training of Master of Translation and Interpreting Talents in the Context of Technological Empowerment

This paper aims to explore the problems and countermeasures in the training of Master of Translation and Interpreting(MTI)talents in the context of technological empowerment.Through methods such as questionnaires and literature review,the study analyzes the problems in the training of MTI talents under technological empowerment and,by examining the feasibility and applicability of technologies,proposes countermeasures to these problems.The research finds that there are still problems in four areas:training concept,teaching content,research in the current training of MTI talents,and mutual empowerment of technology and education.Four countermeasures are suggested to address these problems,including utilizing technology to promote personalized training and optimize teaching content.This study provides valuable references for future educators to leverage technology in the training of MTI talents.

Trust beyond Technology Algorithms: A Theoretical Exploration of Consumer Trust and Behavior in Technological Consumption and AI Projects

In an era dominated by artificial intelligence (AI), establishing customer confidence is crucial for the integration and acceptance of AI technologies. This interdisciplinary study examines factors influencing customer trust in AI systems through a mixed-methods approach, blending quantitative analysis with qualitative insights to create a comprehensive conceptual framework. Quantitatively, the study analyzes responses from 1248 participants using structural equation modeling (SEM), exploring interactions between technological factors like perceived usefulness and transparency, psychological factors including perceived risk and domain expertise, and organizational factors such as leadership support and ethical accountability. The results confirm the model, showing significant impacts of these factors on consumer trust and AI adoption attitudes. Qualitatively, the study includes 35 semi-structured interviews and five case studies, providing deeper insight into the dynamics shaping trust. Key themes identified include the necessity of explainability, domain competence, corporate culture, and stakeholder engagement in fostering trust. The qualitative findings complement the quantitative data, highlighting the complex interplay between technology capabilities, human perceptions, and organizational practices in establishing trust in AI. By integrating these findings, the study proposes a novel conceptual model that elucidates how various elements collectively influence consumer trust in AI. This model not only advances theoretical understanding but also offers practical implications for businesses and policymakers. The research contributes to the discourse on trust creation and decision-making in technology, emphasizing the need for interdisciplinary efforts to address societal challenges associated with technological advancements. It lays the groundwork for future research, including longitudinal, cross-cultural, and industry-specific studies, to further explore consumer trust in AI.

Research on the Digital Economy,Technological Innovation,and Transformation and Upgrading of the Manufacturing Industry in Shandong Province

Based on panel data from 16 cities in Shandong Province from 2013 to 2022,and grounded in theoretical analysis,this paper constructs a benchmark regression model,a mediating effect model,and a heterogeneity test for empirical analysis.The results show that:(1)the digital economy has a significant positive effect on promoting the transformation and upgrading of the manufacturing industry in Shandong Province;(2)the digital economy can drive the transformation and upgrading of the manufacturing industry through technological innovation;and(3)the impact of the digital economy on the transformation and upgrading of the manufacturing industry in Shandong Province is evidently heterogeneous.

基于Valued ERGMs模型的核心技术网络成长机制研究——以量子计算领域为例

对核心技术网络及其成长机制的研究有助于梳理核心技术之间的依赖和促进关系,为研究核心技术演化提供新的理论视角和方法。以技术演化相关理论为基础,归纳核心技术网络成长的影响因素,基于量子计算领域专利数据,识别以技术概念和技术关系为基础的量子计算领域核心技术网络,并基于Valued ERGMs模型构建核心技术网络成长机制模型。结果表明,技术要素中心性、专利技术研发能力、与TRIZ进化法则匹配程度以及技术要素同配性对核心技术网络成长具有正向促进作用;在技术路径方面,核心技术网络成长受到技术要素路径依赖性和技术突破的双重影响。最后,根据量子计算领域核心技术网络成长机制的实证研究结果,从技术研发层面、企业层面、政府层面为相关领域技术发展提出策略建议。

家庭农场数字农业技术采纳作用机制——基于ISM-MICMAC模型分析

为探究家庭农场数字农业技术采纳作用机制,通过构建技术采纳影响因素体系,利用ISM-MICMAC模型得出各层次因素、驱动力-依赖性矩阵。ISM层次模型表明,技术安全性感知是直接表层因素,社会网络、设备操作能力、家庭收入、耕地面积、组织化程度、土地细碎化程度、是否参加培训、技术有用性感知和技术易用性感知是中层间接因素,家庭农场主的政治身份、受教育程度、年龄、家庭劳动力人数、居住地理位置、政府宣传引导、政府经济补贴和基础设施是深层本质因素,对技术采纳起决定性作用;驱动力-依赖性矩阵表明,家庭农场主政治身份、受教育程度属高驱动力、低依赖性独立因素。据此提出完善数字基础设施、强化宣传推广、开展教育培训和增加政策扶持等对策。

基于HRM技术开发水稻糊化温度基因ALK功能标记

【目的】糊化温度是影响稻米蒸煮食味品质的重要指标,ALK是控制水稻糊化温度的主效基因,开发可快速高通量鉴定ALK基因型的功能标记有助于提高水稻品质改良的效率。【方法】根据ALK基因4198位、4329位和4330位存在的单碱基差异,设计基于HRM技术检测的基因功能标记。【结果】通过PCR检测结合测序分析,筛选了ALK基因2个功能区域的功能标记ALKH4、ALKH5。利用ALKH4、ALKH5对81份籼稻品种、279份粳稻品种进行了ALK基因型检测,结果发现,16份粳稻和19份籼稻为G-GC基因型;51份粳稻为A-GC基因型;212份粳稻和62份籼稻为G-TT基因型。【结论】基于HRM技术开发的基因功能标记ALKH4、ALKH5可以快速高通量鉴定控制糊化温度ALK不同基因型,具有重要的应用价值。

980MPa级先进高强钢的发展

选用轻量化汽车材料时应综合考虑材料的性能、质量和成本。目前,先进高强钢被广泛用于汽车工业。先进高强钢有双相钢、相变诱导塑性钢、马氏体钢、复相钢、淬火-配分钢、DH钢等。综述了980 MPa及以上高强钢的分类和主要钢种,汽车用高强钢的化学成分、显微组织、力学性能和使用性能,并结合实际零件的制造过程对这些高强钢的焊接和成形性能作了较深入的探讨,简述了其发展现状和研究进展。

MOA框架下关键核心技术突破路径研究——以光刻技术领域为例

[研究目的]识别关键核心技术突破路径,加快实现科技自立自强对维护我国产业链供应链安全具有重要的现实意义。[研究方法]基于组织行为视角,通过MOA(动机-机会-能力)分析框架厘清7个变量作为企业突破关键核心技术的前因条件。在此基础上,考虑到我国光刻技术领域的阶段性特征,选取35家光刻技术领域的上市企业为研究对象,并采用NCA和fsQCA方法,分追赶、跟随和攻坚三阶段识别关键核心技术突破路径。[研究结论]机会感知能力是企业加快实现关键核心技术突破的必要条件,且政府支持发挥了普适作用。三阶段共存在7条突破路径,概括为四种驱动类型:追赶阶段的动机-政府-吸收能力驱动型、感知能力驱动型;跟随阶段的政府-吸收能力驱动型;攻坚阶段的政府-适应能力驱动型。突破路径在三阶段间存在演变现象,形成三种演变轨迹包括“缓冲主导轨迹”“转折轨迹”和“主导轨迹”。

广东省科技成果转化效率测量与时空特征——基于DEA-Malmquist指数模型

为有效识别广东省科技成果转化的效率与时空特征,促进科技成果更好赋能经济社会高质量发展,运用DEA-Malmquist模型,测算广东省21个地级市在2010—2019年的科技成果转化效率。研究发现,2010年与2019年,全省整体科技成果转化综合效率未达到DEA有效,且2019年的综合效率更低;同时,全要素生产率指数普遍波动较大,各市历年全要素生产率指数差异普遍显著,其中技术进步是影响全要素生产率指数的主要指标。基于此,研究提出平衡研发与转化、推动“政产学研金用服”协同、实施差异化的成果转化战略和加强区域交流合作的政策建议。

磁共振T1rho序列、T2 mapping技术在膝关节早期软骨退变早期诊断中的评估价值

目的探讨磁共振T1rho序列、T2 mapping技术在膝关节早期软骨退变早期诊断中的评估价值。方法选取2020年1月至2022年11月在我院治疗的110例膝关节早期软骨退变患者(观察组),按照疾病严重程度分为轻度退变组及重度退变组,另选取同期在我院进行体检的64例健康者为对照组,受试者均行磁共振T1rho序列、T2 mapping技术扫描,测量受试者T2值及T1ρ值,探讨磁共振T1rho序列、T2 mapping技术在膝关节早期软骨退变早期诊断中的评估价值。结果观察组股骨外侧面、股骨内侧面、胫骨外侧面、胫骨内侧面、髋骨面T2值均明显高于对照组(P<0.05),重度退变亚组患者股骨外侧面、股骨内侧面、胫骨外侧面、胫骨内侧面、髋骨面T2值显著高于轻度退变者(P<0.05);观察组股骨内踝负重区、股骨内踝非负重区、股骨外踝负重区、股骨外踝非负重区、胫骨外侧平台区、胫骨内侧平台区、髌后软骨区磁共振T1ρ值明显高于对照组(P<0.05),重度退变亚组患者股骨内踝负重区、股骨内踝非负重区、股骨外踝负重区、股骨外踝非负重区、胫骨外侧平台区、胫骨内侧平台区、髌后软骨区磁共振T1ρ值明显高于轻度退变亚组患者(P<0.05);磁共振T1rho序列在膝关节早期软骨退变中早期诊断及严重程度评估中的的诊断ROC值及特异度明显高于T2 mapping技术(P<0.05),但后者具有更高的敏感度(P<0.05)。结论磁共振T1rho序列、T2 mapping技术均能有效反映膝关节早期软骨退变中软骨组织学成分变化情况,还可为膝关节软骨退变严重程度评估提供客观依据,二者具有一定互补价值。

基于改进LANDMARC定位算法的人员定位技术研究

在万物互联时代,通过定位系统完成人员定位监督成为了可能,同时该项技术也日益完善。当前,基于RFID无线视频技术的局域网人员定位被广泛应用于智慧园区员工管控、重点人员监管等方面。提出了一种基于RFID的局域网人员定位算法,通过优化LANDMARC算法,对采集到的信号分别引入高斯平滑滤波器和卡尔曼滤波器,去除影响信号强度的噪声,提升定位算法的稳定性;针对LANDMARC定位算法定位精度受K值影响较大的问题,引入Logistic回归模型,以提升算法定位的准确度,有效解决了RFID在有金属、水等障碍物情况下定位精度误差大的问题,降低了外界干扰,可为人员的精准定位提供技术手段。

基于Meta分析的绿色技术创新对碳减排的影响

碳达峰、碳中和是中国未来重要的战略目标之一,绿色技术创新有望成为实现碳减排的主要动力,但关于绿色技术创新对碳减排影响的判断仍未统一。基于国内外数据库的39篇文献,运用Meta分析方法探究中国范围内绿色技术创新对碳减排的影响并得出结论:从主效应来看,现阶段绿色技术创新能够促进碳减排目标实现。从调节效应来看,空间特征、时间跨度及文献特征是相关研究高度异质性的来源。绿色技术创新测度、数据来源则非显著影响因素,但仍有隐性条件需要探究。

用者为本,技之大道--评《以口译员为中心的技术可用性研究:以SmarTerp为例》

在口译学科“技术转向”的时代背景下,口译技术人性化和可持续发展的重要性日益凸显。《以口译员为中心的技术可用性研究:以SmarTerp为例》一书立足时代需求,介绍了全球首项使用可用性工程方法开发计算机辅助口译工具的案例研究,旨在反映口译领域技术变革,确保口译技术的公平可持续发展。该书通过采用人机交互的理论框架和方法论框架评估计算机辅助口译工具SmarTerp界面的可用性,弥补了当前计算机辅助口译实证研究的不足,对口译技术的研发和应用具有重要的启发意义和借鉴价值。

基于GT-CBR的汽轮机叶片智能CAM系统研发

针对目前小批量、多种类汽轮机叶片的数控加工程序编制效率低、耗时较长的问题,设计了基于GT-CBR的汽轮机叶片CAM系统。该系统依据实际工艺案例与叶片典型特征,利用成组技术生成工艺路线并简化多参数实例推理问题;提出了AHP属性权重法、距离加权的KNN算法与动态阈值算法相结合的策略,实现叶片数控加工工艺参数的实例推理与数控程序自动生成;利用UG/NX API与MySQL数据库开发了汽轮机叶片智能CAM系统原型,并对系统进行了测试,验证了系统的有效性。

Mental health in the virtual world:Challenges and opportunities in the metaverse era

Current rates of mental illness are worrisome.Mental illness mainly affects females and younger age groups.The use of the internet to deliver mental health care has been growing since 2020 and includes the implementation of novel mental health treatments using virtual reality,augmented reality,and artificial intelligence.A new three dimensional digital environment,known as the metaverse,has emerged as the next version of the Internet.Artificial intelligence,augmented reality,and virtual reality will create fully immersive,experiential,and interactive online environments in the metaverse.People will use a unique avatar to do anything they do in their“real”lives,including seeking and receiving mental health care.In this opinion review,we reflect on how the metaverse could reshape how we deliver mental health treatment,its opportunities,and its challenges.