马士基集团成立于1904年，总部位于丹麦哥本哈根，在全球135个国家设有办事机构，拥有约89,000名员工，在集装箱运输、物流、码头运营、石油和天然气开采与生产，以及与航运和零售行业相关其它活动中，为客户提供了一流的服务。 马士基集团旗下的马士基航运是全球最大的集装箱承运输公司，服务网络遍及全球。2014年马士基集团位列世界500强第172名。 2018年7月，《财富》世界500强排行榜发布，马士基公司在"2018年《财富》世界500强"中排行第305位。 2018年12月18日，世界品牌实验室发布《2018世界品牌500强》，马士基排名第313。
Digital Twins are becoming central enablers of Europe’s digital and green transitions, yet their data-intensive and autonomous nature exposes them to one of the most complex regulatory environments in the world. This article presents a comprehensive scoping review of how six principal European digital laws—the General Data Protection Regulation, Data Governance Act, Data Act, Artificial Intelligence Act, NIS2 Directive, and Cyber Resilience Act—jointly govern the design, deployment, and operation of Digital Twin systems. Building on the PRISMA-ScR methodology, the study constructs a Unified Digital Twin Compliance Framework (UDTCF) that consolidates overlapping obligations across data governance, privacy, cybersecurity, transparency, interoperability, and ethical responsibility. The framework is operationalised through a Digital Twin Compliance Evaluation Matrix (DTCEM) that enables qualitative assessment of compliance maturity in research and innovation projects. Applying these tools to representative European cases in Smart Cities, Industrial Manufacturing, Transportation, and Energy Systems reveals strong convergence in data governance, security, and interoperability, but also persistent gaps in the transparency, explainability, and accountability of AI-driven components. The findings demonstrate that European digital legislation forms a coherent yet fragmented ecosystem that increasingly requires integration through compliance-by-design methodologies. The article concludes that Digital Twins can act not only as regulated technologies but also as compliance infrastructures themselves, embedding legal, ethical, and technical safeguards that reinforce Europe’s vision for trustworthy, resilient, and human-centric digital transformation.
As global trade shifts from an era of efficiency-driven globalisation to a new compliance-centred paradigm, customs administrations face mounting challenges – ranging from forced labour and environmental enforcement to fractured supply chain visibility and escalating transaction volumes, particularly in e-commerce. This article introduces federated learning as a practical, privacy-preserving solution for enabling secure data collaboration across public and private actors without commingling or centralising sensitive information. We trace the structural failures of Globalisation 1.0 and propose a modernised model of border management built on federated system architecture and trusted networks. These systems allow customs authorities to apply actionable intelligence across multi-tier value chains, strengthen enforcement capabilities, and expedite legitimate trade. The article outlines key steps towards implementation, including legal, technical and institutional reforms, and argues that federated architectures can form the foundation for next-generation risk management and trade facilitation strategies. The future of effective customs governance will depend on embracing secure, data-driven collaboration within and across borders.
Early diagnosis of psychomotor diseases such as Parkinson's requires timely and effective medical care, which is often expensive and resource‐intensive. This study proposes a remote‐control system for assisting medical care related to hand movement. Human hand motion is captured using a comfortable, wearable sensory glove, while actuation is achieved via a fabric‐based pneumatic system that drives finger bending. Finite element modeling is conducted to examine how the ratio of the stiff to soft sheet's Young's modulus affects actuator performance, showing that increased ratios lead to greater bending angles. A machine learning model is developed to relate finger angle to actuator pressure. For remote operation, data from the glove are transmitted—physically or virtually—to a separate system, where a medical professional controls the actuator using MATLAB‐based algorithms. This teleoperation method for healthcare is relatively unexplored in current literature. In addition to medical applications such as rehabilitation or Parkinson's monitoring, the system offers the potential for reducing human risk in hazardous settings—such as operating heavy industrial machinery, handling high‐risk lab chemicals, or performing maintenance in contaminated environments.
Presents a panel discussion on the topic of Abhinav Kimothi on Retrieval-Augmented Generation.
