Global Coordination Research Articles

Exploring Health Professionals’ Views on Hive: A Digital collaborative space for Health Emergencies

Abstract Background The rapidly changing media landscape has significantly affected how information is consumed, particularly during health emergencies. Conflicting information shared or information lacking in scientific rigour can be exploited nefariously online to undermine the health response and damage trust. Digital platforms have become increasingly vital for facilitating communication, and in response, the WHO developed the Hive digital space to provide a safe environment for public health professionals to convene, share information, ask questions, and learn from each other. This study aims to explore the experiences of public health professionals in health emergencies to assess the added value of the Hive platform to coordinate and connect health expertise globally. Methods This study uses a cross-sectional online survey distributed to Hive users focusing on their experiences of working in health emergencies. The responses will undergo descriptive and thematic analysis, as well as inferential statistics such as one-way ANOVA and post-hoc analysis. The survey will emphasize the practical application, value, satisfaction, perceptions, and strategy for the Hive platform to be utilised for global health emergency coordination. Expected Outcomes Insights from this study will delineate how the Hive platform is used by public health experts at all levels in emergency management. It will also highlight the challenges, needs and demands for digital tools to connect skills, experience and knowledge in one place. These insights will demonstrate how the Hive can streamline these processes and provide a safe space for information exchange for a coordinated response to health emergencies. Conclusions Understanding the needs and perceptions of Hive users involved in health emergency prevention, preparedness, response, and resilience will provide critical insights into optimizing the platform’s usability, connectiveness across emergency teams and sustainability of the platform. Key messages • Connecting communities, fostering collaboration and co-creation for improved health emergency management. • Hive enhances collaboration among health professionals, providing a safe environment for knowledge and information sharing.

From Algorithms to Market Dynamics: A Literature Review on High-Frequency Trading

Abstract: High-frequency trading (HFT) uses advanced technologies and sophisticated algorithms to make transactions at unprecedented speeds, which could significantly impact modern financial markets. This literature review examines the technological foundations, primary trading strategies, market impacts, regulatory environment, risk management practices, and future research directions in HFT. The findings reveal that HFT could increase market liquidity and price discovery but also increase volatility during periods of high market stress. Regulatory frameworks such as the SECs Market Access Rule and MiFID II aim to monitor and control HFT activities, at the same time effective risk management practices are crucial for maintaining market stability. Future research should focus on emerging technologies such as AI, ML, quantum computing, and blockchain, along with a better understanding of market structure and global regulatory coordination. This review provides valuable insights for market participants, regulators and researchers, contributing to a balanced perspective on HFTs role in contemporary financial markets.

Cooperative multi-agent reinforcement learning for multi-area integrated scheduling in wafer fabs

The existing scheduling methods of wafer fabs focus on single area, achieving local optimisation while failing to realise global optimisation due to neglecting the coordination of multi-area. Therefore, it is necessary to consider the complex opposing relationships between multi-area caused by constraints such as batch processing, re-entrance, and multiple residency times within and between areas to conduct integrated scheduling and shorten the production cycle time. For this issue, this paper proposes a cooperative multi-agent reinforcement learning for multi-area integrated scheduling. Aiming at the dynamic batching and scheduling considering the dynamic arrival lots in multi-area, a multi-agent reinforcement learning algorithm is presented to learn the optimal dynamic batching and scheduling policy firstly. Subsequently, a cooperative multi-agent framework is raised to achieve the global optimisation and coordination of multi-area. Furthermore, an adaptive exploration strategy is constructed to enhance the global exploration capability of the complex solution space caused by residency time constraints and re-entrant property. Moreover, a policy share enhanced Double DQN is employed to improve the generalisation and adaptability of the multi-agent. Finally, the experiments demonstrate that the proposed integrated scheduling method has better comprehensive performance compared to the previous area-separated scheduling methods.

Artificial Intelligence & the Capacity for Discrimination: The Imperative Need for Frameworks, Diverse Teams & Human Accountability

The increasing integration of Artificial Intelligence (AI) in various industries has led to concerns about how these systems can perpetuate discrimination, particularly in fields like employment, healthcare, and public policy. Multiple academic and business perspectives on AI discrimination, focusing on the need for global policy coordination and ethical oversight to mitigate biased outcomes, ask for our technical innovators to create contingencies that will better protect humanity’s experience with AI’s ever-expanding reach. Central to the key constructs such as biased datasets, algorithmic transparency, and the global governance of AI systems can function as a harmful drawback to these systems. Without adequate data governance and transparency, AI systems can perpetuate discrimination. AI's ability to discriminate stems primarily from biased data and the opacity of machine learning models, necessitating proactive research and policy implementation on a global scale. These frameworks must transcend the limitations of the experiences or perspectives of their programmers to ensure that AI innovations are ethically sound and that their use in global organizations adheres to principles of fairness and accountability. This synthesis will explore how these articles advocate for comprehensive, continuous monitoring of AI systems and policies that address both local and international concerns, offering a roadmap for organizations to innovate responsibly while mitigating the risks of AI-driven discrimination.

Vibration analysis of piping system coupled with conical-cylindrical combined shells

Fluid-filled piping system are widely used in power cooling, fuel transportation and underwater vessel, which not only produce vibration along the system, but also transmit to the connecting structure to generate noise in ambient environment. Most investigations have concentrated on either the vibration characteristics of piping systems or of combined shells separately. In this work, an analytical impedance synthesis method (ISM) is proposed to analyze the vibration characteristics of a pipe-hull coupled system, in which the hull can be simplified to a combined conical-stiffened cylindrical-hemisphere shell. The piping system is modeled by fluid-filled beams in three-dimensional configuration. Wave function and power series solution are used to describe the displacements of cylindrical and conical shell respectively. Based on exact analytical solutions, the impedance matrix of each segment is established separately and assembled in the global coordinate by displacement continuity and force balance boundary conditions. Forced responses are compared with the experimental results to verify the correctness of the method.

Global spillovers of US climate policy risk: Evidence from EU carbon emissions futures

International climate policy risk spillovers occur when expected changes to climate policy stringency in one country affect expected climate policy stringency in another country. We develop an event study procedure to identify such spillovers in emissions trading systems, specifically examining the impact from the United States (US) to the European Union (EU). Distinguishing between policy events likely to reduce US commitment to climate action (‘brown events’) and those likely to increase it (‘green events’), we find that the average brown US policy event is associated with an anticipated increase in future EU carbon permit supply, leading to a cumulative 7.1% drop in EU carbon prices over the event window. Conversely, green US policy events are linked to an expected decrease in future EU permit supply, resulting in a cumulative 4.7% rise in EU carbon prices. These findings suggest that financial markets anticipate EU regulators to align with the direction of US climate policy. Our results underscore the significance of regulatory risk spillovers in global climate policy coordination.

Enhancing global support to address complex sustainable development policy challenges: Learning from success in cross‐sectoral nutrition policy

AbstractMalnutrition is hampering achievement of the sustainable development goals (SDGs), and requires policy approaches that address food system drivers. However, this will require the adoption of cross‐sectoral policy measures for nutrition, which has proved challenging in practice. This qualitative co‐designed study drew on theories of policy learning to examine the roles of global organisations in fostering and supporting effective cross‐sectoral policy action to improve nutrition. Forty‐three in‐depth interviews were conducted with government actors at global, regional and national level. Key roles of global institutions to support scaling up of effective cross‐sectoral policy for nutrition included the development of best‐practice guidance, provision of operational and other forms of support, convening to enable political awareness and commitment and coordination to create shared vision. Opportunities to improve global support included improving global coordination, developing incentives to use global guidance and rethinking processes and strategies to support contextual adaptation of global guidance.

Non-contact Structural Displacement Measurement using UAV and DIC with Non-coplanar Fixed Region of Interest

The use of unmanned aerial vehicles (UAV) for displacement measurement using Digital Image Correlation (DIC) has been popular. A fixed region of interest (FROI) is often used to calibrate the UAV camera. Existing techniques require the FROI to be coplanar with the target plane, such that a corner of the FROI can be taken directly as the origin of the global coordinates. However, this condition does not exist when the target plane is in motion, and this has been a significant challenge in the correction of the UAV images. This paper proposed an algorithm to estimate the posture of the UAV camera for solving this issue. Numerical simulation shows that the proposed algorithm has high computation accuracy and stability, and it is robust to the amplitude of motion of the target image or camera. Field experiments confirm the feasibility of the proposed algorithm for images with non-coplanar conditions with a maximum error of less than 2.3 mm and a peak error below 5 %. In comparison to the traditional coplanar correction method, the CPS method demonstrates lower errors, making it better suited for cases where the FROI and the target plane are not coplanar.

The 2030 Declaration on Scientific Plant and Fungal Collecting

Societal Impact StatementBiological samples and their associated information are an essential resource used by scientists, governments, policymakers, practitioners and communities to ensure that biodiversity can be appropriately protected and sustainably used. Yet, considering the enormous task of documenting the vast numbers of as‐yet‐unknown plant and fungal species, greater international coordination for biological collecting and recording is necessary, built on equitable collecting practices and standards. Here, we propose five commitments to accelerate and enhance scientific knowledge of plant and fungal diversity, while increasing collaboration, benefit sharing and efficiency.SummaryAlmost all life depends on plants and fungi, making knowledge of their diversity and distribution—primarily derived from biological collections—fundamental to national and international conservation, restoration and sustainable use commitments. However, it is estimated that some 15% of all plant species and over 90% of all fungal species have not yet been scientifically described, hampering our ability to assess and demonstrate the impact of efforts to halt biodiversity loss. In addition, organisations and researchers around the world lack a concerted strategy for increasing complementarity and avoiding overlap in botanical and mycological research, particularly in relation to the collection of specimens. We here present the 2030 Declaration on Scientific Plant and Fungal Collecting, summarising a commitment towards such a necessary strategy. Its components were identified from discussions during and after a series of four workshops and plenary discussions at the 2023 State of the World's Plants and Fungi symposium convened by the Royal Botanic Gardens, Kew, and were then consolidated into the present form by the authors. The Declaration was subsequently opened up for endorsement by signatories. Collectively, we agree on a set of five commitments for cataloguing the world's flora and funga, designed to maximise efficiency, facilitate knowledge exchange and promote equitable collaborations: (1) use evidence‐based collection strategies; (2) strengthen local capacity; (3) collaborate across taxa and disciplines; (4) collect for the future; and (5) share the benefits. This Declaration is a first step towards increased global and regional coordination of scientific collecting efforts.

A new triangular thin shell element based on the absolute nodal coordinate formulation for complex surfaces

Abstract This work proposed a new Hermite triangular thin shell element based on the absolute nodal coordinate formulation to model thin shells with complex curved surfaces. Three techniques are adopted to enhance its universality and efficiency. Firstly, local numerical curvilinear coordinates are used on each node for those curved surfaces whose global curvilinear coordinates cannot be obtained analytically, and the Lie group interpolation is used for obtaining the curvilinear coordinates on the non-nodal domain. Secondly, the slope vector of the element is obtained by cross-producing the two gradient vectors only on each node; but interpolated inside the element to ensure its continuity. Additionally, this processing maintains the linear relationships between the shape functions and nodal coordinates, resulting in constant elastic constants. Thirdly, the enhanced assumed strains (EAS) and the assumed natural strains(ANS) methods are adopted respectively to accelerate the convergence speed and avoid locking problems of the element. Several numerical examples show that this new element is universal for irregularly curved surfaces without locking problems. In addition, the efficiency is much higher than the traditional triangular shell element.

Exploring the Global Reaction Coordinate for Retinal Photoisomerization: A Graph Theory-Based Machine Learning Approach.

Unraveling the reaction pathway of photoinduced reactions poses a great challenge owing to its complexity. Recently, graph theory-based machine learning combined with nonadiabatic molecular dynamics (NAMD) has been applied to obtain the global reaction coordinate of the photoisomerization of azobenzene. However, NAMD simulations are computationally expensive as they require calculating the nonadiabatic coupling vectors at each time step. Here, we showed that ab initio molecular dynamics (AIMD) can be used as an alternative to NAMD by choosing an appropriate initial condition for the simulation. We applied our methodology to determine a plausible global reaction coordinate of retinal photoisomerization, which is essential for human vision. On rank-ordering the internal coordinates, based on the mutual information (MI) between the internal coordinates and the HOMO energy, NAMD and AIMD give a similar trend. Our results demonstrate that our AIMD-based machine learning protocol for retinal is 1.5 times faster than that of NAMD to study reaction coordinates.

A Well-Defined Magnesium Complex of C70 6.

Controlling and understanding charge state and metal coordination in carbon nanomaterials is crucial to harnessing their unique properties. Here we describe the synthesis of the well-defined fulleride complex [{(Mesnacnac)Mg}6C70], 2, (Mesnacnac)=HC(MeCNMes)2, Mes=2,4,6-Me3C6H2, from the reaction of the β-diketiminate magnesium(I) complex [{(Mesnacnac)Mg}2] with C70 in aromatic solvents. The molecular structure of complex 2 was determined, providing the first high-quality structural study of a complex with the C70 6- ion. In combination with solution state NMR spectroscopic and DFT computational studies, the changes in geometry and charge distribution in the various atom and bond types of the fulleride unit were investigated. Additionally, the influence of the (Mesnacnac)Mg+ cations on the global and local fulleride coordination environment was examined.

Global Health Security: Preparing For Future Pandemics

The interconnectedness of modern societies and global mobility has amplified the risk of infectious disease outbreaks escalating into pandemics. Global health security involves proactive efforts to detect, prevent, and respond to emerging health threats before they become widespread crises. Historical pandemics like the Black Death and the Spanish flu highlight the catastrophic consequences of uncontained outbreaks. Despite advancements in healthcare infrastructure, the COVID-19 pandemic has exposed gaps in preparedness, emphasizing the need for enhanced global surveillance, cross-sectoral collaboration, and technological innovations. This paper explores the historical context of pandemics, key components of pandemic preparedness, and the role of global coordination and technology in mitigating future health threats. It calls for stronger international collaboration and investment in healthcare systems to ensure resilience in the face of future pandemics. Keywords: Global health security, pandemic preparedness, pandemic response, historical pandemics, COVID-19, global surveillance.

Intelligent mission planning for autonomous distributed satellite systems

System autonomy plays a critical role in the success of next generation Distributed Satellite Systems (DSS) mission architectures, enabling the inference of external and internal environment conditions to support system adaptation in unexpected and unfamiliar situations. Artificial Intelligence (AI) based techniques show promise in achieving this desired self-adaptive capability by offering on-board predictive real time analytics, supporting an evolution towards Trusted Autonomous Satellite Operations (TASO). In parallel, TASO requires an evolution of the control and coordination of increasingly autonomous large scale DSS, achieved in the design and operation of intelligent Mission Planning Systems (MPS). In this paper, we focus on intelligent mission planning functionality problem utilising a distributed ant colony optimisation approach to achieve local task allocation and platform coordination. The approach is implemented in the context of a Space-Based Space Surveillance (SBSS) mission architecture that considers self-adaptive capabilities, global coordination and supervisory control aspects. The effectiveness of the approach is shown, demonstrating that the proposed solution based on metaheuristics supports an efficient and pervasive SBSS capability.

Accessibility of TB diagnostic services at primary healthcare clinics in the eThekwini district, South Africa: a geospatial analysis

BackgroundImproving geographic access can aid in managing tuberculosis (TB) by enabling early diagnosis and treatment initiation. Although geospatial techniques have been used to map the transmission patterns of drug-resistant TB...

FROM OBSCURITY TO CLARITY: THE TRANSFORMATIVE IMPACT OF MARKET TRANSPARENCY ON FINANCIAL CRISIS PREVENTION

This paper delves into the transformative impact of market transparency on financial crisis prevention, offering a comprehensive analysis of how transparency influences financial stability. The study begins by examining the role of transparency in mitigating information asymmetry, which is often a root cause of market inefficiencies and crises. Through case studies of the 2008 global financial crisis and the Asian financial crisis of 1997-1998, the paper illustrates how opaque financial practices and inadequate information dissemination led to significant economic downturns. The research also explores the post-crisis regulatory landscape, focusing on initiatives like the Dodd-Frank Act, which sought to enhance transparency through mandatory disclosures and stricter oversight. Additionally, the paper addresses the challenges of implementing transparency, such as resistance from financial institutions, technological hurdles, and the need for global coordination. By integrating emerging technologies like blockchain and artificial intelligence, the paper suggests that the future of market transparency is promising, with the potential to create more resilient financial systems. The findings underscore the necessity of transparency not only as a regulatory requirement but as a strategic imperative for fostering investor confidence, reducing systemic risk, and ensuring sustainable economic growth.

The Impact of the Global Minimum Tax Reform on China and Its Countermeasures

Abstract Significant corporate tax reform was agreed upon by more than 140 nations in 2021, with implementation set for 2023 and beyond. Many people throughout the globe are discussing the possible effects of the Organization for Economic Cooperation and Development (OECD) planned adjustment to the global minimum tax (GMT) on their respective economies. The OECD has formulated a “two-pillar” scheme for international tax rules for 137 countries and regions within the overall framework. Pillar 2 is to set the tax rate at 15%, the world’s lowest corporate tax. The GMT is a reclassification of the taxing authority mechanism for the profits of multinational corporations, which has made significant adjustments to the global tax coordination and governance mechanism. People living in China and earning money from China must pay university fees, which are all of a nationality. Progressive rates ranging from 3 to 45% apply to the complete income. Therefore, taking the initiative in policy is crucial to address this challenge actively. This article makes an in-depth assessment and prediction of the impact of the GMT reform on China’s tax system and enterprises and proposes countermeasures. However, approximately 20% of the earnings can be exposed to the 15% tax rate that governments can apply. If the entire process is mixed in tandem, the tax rate equals 0.2%. Hence, an important amount of tax revenue can proceed down the drain. From the numerical outcomes, the minimum tax with jurisdictional blending was set at 12.5% under Pillar 2; the disparity between the sample’s top and lowest EATRs would decrease by 2.8% points.

The Global Measles and Rubella Laboratory Network Supports High-Quality Surveillance.

With 762 laboratories, the Global Measles and Rubella Laboratory Network (GMRLN) is the largest laboratory network coordinated by the World Health Organization (WHO). Like the Global Polio Laboratory Network, the GMRLN has multiple tiers, including global specialized laboratories, regional reference laboratories, national laboratories, and, in some countries, subnational laboratories. Regional networks are supervised by regional laboratory coordinators reporting to a global coordinator at WHO headquarters. Laboratories in the GMRLN have strong links to national disease control and vaccination programs. The GMRLN's goal is to support member states in obtaining timely, complete, and reliable laboratory-based surveillance data for measles and rubella as part of the strategy for achieving measles and rubella elimination. Surveillance data are reported to the national program and are included in annual reports on the status of measles and rubella elimination to national verification committees for review by regional verification commissions. Quality within the GMRLN is ensured by monitoring performance through external quality assurance programs, confirmatory and quality control testing, accreditation, and coordination of corrective action and training where needed. The overall performance of the laboratories has remained high over the years despite many challenges, particularly the COVID-19 pandemic. The GMRLN is well-positioned to support high-quality laboratory-based surveillance for measles and rubella and to transition to supporting laboratory testing for other pathogens, including vaccine-preventable diseases.

Management Economic Systems and Governance to Reduce Potential Risks in Digital Silk Road Investments: Legal Cooperation between Hainan Free Trade Port and Ethiopia

This research explores the interplay between innovation, economic systems, governance structures, and law, and how they interact with one another in the context of China and Ethiopia’s investments in the Digital Silk Road. The way cutting-edge methods related to governance and economic systems might help lower the risks involved in major infrastructure projects, like the Digital Silk Road, particularly in light of law and 5G developments, is investigated. China–Africa connections are to be strengthened, sustainable development is to be encouraged, and healthy economic progress is the goal of the partnership between Ethiopia and the Hainan Free Trade Port. The impact of these transnational investments on fair growth and sustainable development is assessed, while exploring the evolving agendas and procedures governing investments. This research draws attention to how the law and legal cooperation between Ethiopia and China may promote mutually advantageous outcomes, promote transparency and governance mechanisms, and lessen the likelihood of disputes. This research on the factors influencing the future of the Digital Silk Road and its consequences for long-term, sustainable economic growth, and business in the area, aims to provide valuable insights for policymakers, development professionals, and academics, and for the copromotion of China and Ethiopia in terms of digital investment. This research relates to the promotion of the African Continental Free Trade Area (AfCFTA), in terms of construction and economic development. It also examines how the DSR raises concerns about data security and privacy, cross-border transactions, technology transfer, and cyberterrorism, as well as encourages digital investment, such as through enhancing digital governance regulations, modernizing international investment agreements (IIAs), and bolstering global health, coordination, and cooperation; the article concludes by analyzing the implications for Africa. The findings show that such cooperation would support Africa’s digital transformation and sustainable development, while strengthening China–Africa cooperation.

Novel multi-degree-of-freedom force–displacement mixed control framework for low loading rate substructure hybrid testing

In substructure hybrid tests, imposing realistic multi-degree-of-freedom (MDOF) displacement and force boundary conditions on a specimen involves controlling several actuators to emulate the MDOF boundary conditions of the experimental substructure. This setup presents significant challenges for decoupling control in MDOF systems. Due to the typically high stiffness of the specimen in the axial direction, force control is preferred over displacement control, which has limited accuracy in this direction. Typically, force control in the axial direction is combined with simultaneous displacement control in the softer direction, forming an MDOF force-displacement mixed control scheme. This scheme transforms force control into displacement control in the inner loop in the axial direction to ensure safe loading. The scheme involves addressing two major challenges: the nonlinear force–displacement transformation and the nonlinear coordinate transformation from the local actuator space (LAS) to the global Cartesian coordinate (GCC) system. To address these challenges, the Modified Newton–Raphson iteration integrated with proportional integral plus feed-forward (MNR-PIFF) and incremental kinematic transformation integrated with proportional integral plus feed-forward (IKT-PIFF) methods are proposed. Based on these methods, a novel MDOF force–displacement mixed control (NMFDC) framework is developed for substructure hybrid testing. A 6-DOF cyclic test simulation using the NMFDC framework was conducted to demonstrate its superiority. Furthermore, a 6-DOF cyclic test and substructure hybrid test at low loading rates were performed to validate the NMFDC framework because of the loading equipment limit. Experimental results and numerical simulations indicate that the NMFDC framework achieves swifter response with lower error levels. For applications in fast and real-time hybrid testing, dynamic loading equipment need to be used, the PIFF controller in the NMFDC framework should be replaced by adaptive time delay compensation in future developments.