Global Strategy Research Articles

Combining Nanopore direct RNA sequencing with genetics and mass spectrometry for analysis of T-loop base modifications across 42 yeast tRNA isoacceptors.

Transfer RNAs (tRNAs) contain dozens of chemical modifications. These modifications are critical for maintaining tRNA tertiary structure and optimizing protein synthesis. Here we advance the use of Nanopore direct RNA-sequencing (DRS) to investigate the synergy between modifications that are known to stabilize tRNA structure. We sequenced the 42 cytosolic tRNA isoacceptors from wild-type yeast and five tRNA-modifying enzyme knockout mutants. These data permitted comprehensive analysis of three neighboring and conserved modifications in T-loops: 5-methyluridine (m5U54), pseudouridine (Ψ55),and 1-methyladenosine (m1A58). Our results were validated using direct measurements of chemical modifications by mass spectrometry. We observed concerted T-loop modification circuits-the potent influence of Ψ55 for subsequent m1A58 modification on more tRNA isoacceptors than previously observed. Growing cells under nutrient depleted conditions also revealed a novel condition-specific increase in m1A58 modification on some tRNAs. A global and isoacceptor-specific classification strategy was developed to predict the status of T-loop modifications from a user-input tRNA DRS dataset, applicable to other conditions and tRNAs in other organisms. These advancements demonstrate how orthogonal technologies combined with genetics enable precise detection of modification landscapes of individual, full-length tRNAs, at transcriptome-scale.

Political conditionality as an EU foreign policy and crisis management tool. The case of EU wartime political conditionality vis-à-vis Ukraine

ABSTRACT This article explores the compatibility between the EU’s political conditionality as a policy tool and the EU’s approach to conflict management, guided by the EU Global Strategy. It does so based on the unique case of the EU’s application of political conditionality vis-à-vis Ukraine amidst the war and the reinvigoration of the EU’s enlargement policy in response thereto. We find conditionality to fit the EU’s crisis management toolbox, especially when it comes to the long-term approach and building resilience of state institutions in a target country. Though not yet strongly visible in the case of Ukraine, the application of conditionality may come into contradiction with the principles of societal resilience and local ownership, embedded into the EU’s approach to conflict management and the EU Global Strategy, more broadly.

Global Health Indicators and Child Mortality Trends: Insights from a Global Panel Data Analysis of 200 Countries.

The aim of this study was to explore how medical resources and vaccine coverage relate to infant mortality rate (IMR) and under-five mortality rate (U-5MR), which are both key national health indicators. This longitudinal study was based on panel data from the national level of 200 countries. Data from 1990 to 2021 were grouped into seven regions based on geographic and epidemiological similarities. Regarding correlation, the high-income region showed a different trend from that shown by other regions. Health expenditure was positively associated with IMR and U-5MR globally. Number of medical doctors per 1,000 people was negatively associated with IMR and U-5MR globally. Hepatitis type B (HBV) and measles, first dose (MCV) were negatively associated with IMR and HBV, MCV, and Bacillus Calmette-Guérin were negatively associated with U-5MR globally. In quadratic regression, the correlation between the number of doctors and mortality stabilizes or plateaus at approximately four individuals. Overall vaccine coverage was positively correlated with mortality up to a certain threshold, beyond which it became negatively correlated. A higher number of doctors was consistently associated with decreased mortality, regardless of location, while other factors varied by region. Our study findings highlight the importance of implementing global strategies that are specific to each region's characteristics to reduce IMR and U-5MR.

Plant-based vaccines against viral hepatitis: A panoptic review.

The traditional vaccines against hepatitis have been instrumental in reducing the incidence of some types of viral hepatitis; however, the need for cost-effective, easily distributable, and needle-free vaccine alternatives has led to the exploration of plant-based vaccines. Plant-based techniques offer a promising avenue for producing viral hepatitis vaccines due to their low-cost cultivation, scalability, and the potential for oral administration. This review highlights the successful expression of hepatitis B surface antigens in plants and the subsequent formation of virus-like particles, which have shown immunogenicity in preclinical and clinical trials. The challenges such as achieving sufficient antigen expression levels, ensuring consistent dosing, and navigating regulatory frameworks, are addressed. The review considers the potential of plant-based vaccines to meet the demands of rapid vaccine deployment in response to outbreaks and their role in global immunization strategies, particularly in resource-limited settings. This review underscores the significant strides made in plant molecular farming and the potential of plant-based vaccines to complement existing immunization methods against viral hepatitis.

Global burden and health inequality of nutritional deficiencies from 1990 to 2019.

Nutritional deficiencies (NDs) manifest in various forms and are widespread globally. However, a systematic evaluation of the epidemiology of NDs across all causes and age groups in different countries and regions has not been conducted. This study aimed to utilize data from the 2019 Global Burden of Disease (GBD) study to assess the burden and trends of NDs, including their incidence, prevalence, mortality, and disability-adjusted life years (DALYs). Additionally, the study evaluated health inequalities at global, regional, and national levels from 1990 to 2019. In 2019, the age-standardized incidence rate of NDs was 2,207.71 per 100,000 individuals (95% UI 1,863.04-2,604.67), and the age-standardized DALYs (ASR-DALYs) was 680.12 per 100,000 individuals (95% UI 507.21-894.89). Among the causes of NDs, dietary iron deficiency had the highest ASR-DALYs and exhibited minimal variation. Children under the age of 5 years faced the greatest risk of NDs. Sex disparity was evident, with males having lower rates than females. Although the gap in the burden of NDs between regions classified as poor and wealthy decreased, disparities persist. These findings provide critical insights for the development of global health strategies aimed at mitigating NDs and may guide policymakers in implementing effective and economically viable interventions.

The multiscale response of global cropland cropping intensity to urban expansion

CONTEXTUrban expansion(UE) and multiple cropping(MC) are key factors in anthropogenic impacts on global environmental change. However, the multi-scale response patterns of UE and MC have not yet been revealed, and how urbanization affects cropland intensification is still not deeply explored. OBJECTIVEThis study examines the spatial and temporal trends in global UE and MC and analyses the multi-scale response patterns of both. METHODSThe GEE (Google Earth Engine) platform was used to count global cropland cropping intensity (CCI) and impervious surface rasters on an image-by-image basis, while GIS was employed for spatial analyses, and the generalized additive model (GAM) was applied to inscribe variable response trajectories. RESULTS AND CONCLUSIONThe global multiple cropping index(MCI) increased significantly (by 4.1 %) over the period 2001–2019, with growth in double- and triple-cropped cropland dominating this change. Double cropping, as a widespread global farming strategy, has led to a shift towards the intensification of agriculture, with countries in the northern hemisphere contributing more. Global UE significantly expands to twice the baseline level at an average annual growth rate of 2. 42 × 104 km2 over the period 2001–2019, with the expansion of world-class urban agglomerations in China, the United States and Europe dominates this trend. The spatial clustering of MC and UE has continued to intensify, with high-intensity cropping strategies progressively clustering towards areas of significant UE, and this tendency has a clear decreasing urban-rural gradient effect. The global CCI grows significantly and non-linearly with UE, but an important inflection point in the growth trajectory has occurred under the influence of threshold effects. Developed countries tend to be more flexible in their cropping intensity strategies as they move forward with urbanization. There is a clear increasing effect of the urban-rural gradient in the degree of non-linearity in the response of urbanization and cropping intensity. SIGNIFICANCEThe results of the study contribute to the understanding of the complex spatial and temporal coupling mechanisms between UE and MC, and provide useful insights for the development of trade-offs between urbanization and maturity strategies.

Global Fight against Malaria: Goals and Achievements 1900–2022

This article examines the historical and ongoing efforts to fight malaria, a parasitic disease caused by Plasmodium species and transmitted by Anopheles mosquitoes. Despite over a century of control efforts, malaria remains a major global health issue. In 2022, there were an estimated 249 million cases across 85 countries, leading to approximately 600,000 deaths. In the recently published Global Technical Strategy for Malaria 2016–2030, the World Health Organization (WHO) has prioritized malaria eradication. The main goals are to reduce malaria incidence and mortality by 90% by 2030 compared to 2015 levels. However, as of 2022, progress has been limited, with only a 2% reduction in incidence and a 6% reduction in mortality. This review traces the historical context of malaria, highlighting its ancient origins and the pivotal scientific discoveries in the late 19th century that paved the way for modern control measures. The Global Malaria Eradication Programme launched by the WHO in 1955 initially showed promise, largely due to the insecticide DDT, but ultimately failed to achieve its goals mainly due to logistical problems, vector resistance to DDT, and inadequate funding. Despite significant advances in the early 21st century, including the Roll Back Malaria initiative and increased international funding, malaria eradication remains a distant goal. Persistent challenges, such as weak healthcare systems, parasite and vector resistance to drugs and insecticides, and inadequate funding, continue to hamper global efforts. Therefore, this article underscores the need for a deeper understanding of malaria’s history and recent evolution to inform future strategies for eradication.

A variational framework for Cahn–Hilliard-type diffusion coupled with Allen–Cahn-type multi-phase transformations in elastic and dissipative solids

This article presents a variational framework for coupled chemo-mechanical solids undergoing irreversible micro-structural changes at infinitesimal strains. The coupled problem is characterised by phenomena such as phase transitions, micro-structure coarsening and swelling. It is an extension of our previous work on variational inelasticity for a conserved chemo-mechanical setting to a unified conserved and non-conserved setting which include multi-phase transformations. The variational framework, again governed by continuous-time, discrete-time and discrete-space–time incremental variational principles, is outlined for coupled diffusion-phase transformation phenomena in elastic and dissipative solids. For the sake of simplicity, focus is restricted to isothermal conditions. It is shown that the governing macro- and micro-balance equations of the coupled problem appear as Euler equations of these minimisation and saddle point principles. In contrast to our previous work, extended variational principles (with the gradient of the chemical potential and phase fractions) are constructed that account for diffusion-phase transformation coupling. This is achieved by Legendre transformations. Note that the local–global solution strategy is still preserved and the resulting system of symmetric non-linear algebraic equations are solved by Newton–Raphson-type iterative methods. The applicability of the proposed framework is demonstrated by numerical simulations that qualitatively characterise lower bainitic micro-structure.

Exploring ESL Learners’ Reading Strategies Based on the Theory of Reciprocal Determinism

The purpose of this study is to explore the relationship between reading strategies and Bandura’s (1986) theory of Reciprocal Determinism. Previous research acknowledged the concept of Reciprocal Determinism as an effective teaching approach, however, limited research has been done to consider how reading is influenced by learners’ personal factors, behavior and environment. Based on four Research Questions, the study explores the perceived use of reading strategies by 225 undergraduates who completed a critical reading course at a local university. These learners of English as a Second Language responded to an online questionnaire adapted from Mokhtari and Sheorey’s (2002) Survey of Reading Strategies. Based on the learners’ ratings of the reading strategies, namely Global Reading Strategies, Problem-Solving Strategies and Support Strategies, the findings revealed that there is a significant relationship between the learners’ perceived use of reading strategies and the three factors of Reciprocal Determinism, namely Personal Factors, Behaviour and Environment indicating a cyclical effect that infuences learners’ reading comprehension. This exploration of reading strategies through this theory has pedagogical implications on how reading is taught to scaffold and help learners increase metacognitive awareness and self-efficacy. Overall, this study contributes to a further understanding of the importance of taking into account the three factors in a reading environment and the relationship between reading strategies and RD. Future studies could be an extension of how the cyclical effects of Reciprocal Determinism and reading strategies could be strategically integrated into the teaching of skilled and unskilled readers and in other learning domains.

Rapidly Evaluating Species at Risk Using Endemic Plants of Kosrae, Federated States of Micronesia

The International Union for Conservation of Nature (IUCN)'s Red List of Threatened Species is regarded as the primary source of global extinction risk for species. Despite this importance, the IUCN has assessed less than 20% of the world′s estimated 400,000 flowering plants due to issues like insufficient data or a lack of experts. Thousands of conservation status assessments were generated recently in response to the call to action by the revised Target 2 of the Global Strategy for Plant Conservation (GSPC), “An assessment of the conservation status of all known plant species, as far as possible, to guide conservation action.” Accelerated extinction risk assessments are needed to identify species that are most at risk of extinction, which can then be thoroughly evaluated by the Red List assessment procedure. The land area in the Pacific Islands is significantly smaller than in other parts of the world. Plant species restricted to these islands may be identified as “At Risk” due to the limited land area of these islands, despite being widespread locally. Distribution and abundance data of single-island endemic plant taxa of Kosrae, Federated States of Micronesia, are analyzed and combined with digital elevation model files from this island, ArcGIS, and herbarium data, to calculate the percentage of land area that is available within a species′ elevational occurrence, a metric we have coined the Extent of Inhabitable Elevation of Island Occurrence (EIEIO). This metric can be used as a streamlined system to rapidly identify species that need plant conservation attention and allows for a swifter response to Target 2 of the GSPC.

Donor‐derived infections: Current practice, global strategies, and future challenges

Donor‐derived infections: Current practice, global strategies, and future challenges

Effective Utilisation of AI to Improve Global Warming Mitigation Strategies through Predictive Climate Modelling

Effective Utilisation of AI to Improve Global Warming Mitigation Strategies through Predictive Climate Modelling

Global Integration vs. Local Responsiveness: Managing Strategic Dilemmas in Multinational Corporations

In the dynamic landscape of multinational corporations (MNCs), achieving a balance between global integration and local responsiveness poses a significant strategic dilemma. This study investigates how MNCs navigate this dual challenge to maintain competitive advantage and operational efficiency in diverse global markets. theoretical frameworks and empirical evidence to understand the strategic choices made by MNCs in integrating global operations while responding to local market demands. the tensions between standardized global strategies aimed at achieving economies of scale and localized strategies tailored to meet unique customer preferences, regulatory requirements, and cultural nuances. Key aspects analyzed include the strategic decision-making processes, organizational structures, and management practices that facilitate or hinder effective global-local integration. The study reviews case studies and comparative analyses of MNCs across different industries to illustrate successful strategies and best practices in managing these strategic dilemmas.

SaDENAS: A self-adaptive differential evolution algorithm for neural architecture search

Evolutionary neural architecture search (ENAS) and differentiable architecture search (DARTS) are all prominent algorithms in neural architecture search, enabling the automated design of deep neural networks. To leverage the strengths of both methods, there exists a framework called continuous ENAS, which alternates between using gradient descent to optimize the supernet and employing evolutionary algorithms to optimize the architectural encodings. However, in continuous ENAS, there exists a premature convergence issue accompanied by the small model trap, which is a common issue in NAS. To address this issue, this paper proposes a self-adaptive differential evolution algorithm for neural architecture search (SaDENAS), which can reduce the interference caused by small models to other individuals during the optimization process, thereby avoiding premature convergence. Specifically, SaDENAS treats architectures within the search space as architectural encodings, leveraging vector differences between encodings as the basis for evolutionary operators. To achieve a trade-off between exploration and exploitation, we integrate both local and global search strategies with a mutation scaling factor to adaptively balance these two strategies. Empirical findings demonstrate that our proposed algorithm achieves better performance with superior convergence compared to other algorithms.

A Comparison of Local and Global Strategies for Exploiting Field Inversion on Separated Flows at Low Reynolds Number

The prediction of separated flows at low Reynolds numbers is crucial for several applications in aerospace and energy fields. Reynolds-averaged Navier–Stokes (RANS) equations are widely used but their accuracy is limited in the presence of transition or separation. In this work, two different strategies for improving RANS simulations by means of field inversion are discussed. Both strategies require solving an optimization problem to identify a correction field by minimizing the error on some measurable data. The obtained correction field is exploited with two alternative strategies. The first strategy aims to the identification of a relation that allows to express the local correction field as a function of some local flow features. However, this regression can be difficult or even impossible because the relation between the assumed input variables and the local correction could not be a function. For this reason, an alternative is proposed: a U-Net model is trained on the original and corrected RANS results. In this way, it is possible to perform a prediction with the original RANS model and then correct it by means of the U-Net. The methodologies are evaluated and compared on the flow around the NACA0021 and the SD7003 airfoils.

Infectious diseases and global security: Analysis of global control and vaccination strategies

Introduction: Given the recent experience with the COVID-19 vaccine campaign, an optimal global policy to control future pandemics and ensure infectious security globally is highly relevant. Objective: The study aims to determine the optimal vaccination strategy to reduce COVID-19 morbidity and mortality during a pandemic.Methods: A systematic search of studies on infectious disease control and vaccination strategies for the period 2000-2023 in PubMed, Scopus, Web of Science and Google Scholar databases using keywords was conducted for the review. Relevant publications, data extraction and systematisation were selected.Results: The findings of the analysis highlight the importance of integrated interventions in global vaccination strategies, including health systems strengthening, innovative technologies for outbreak detection and international collaboration. Vaccination, as an effective preventive measure, significantly reduces the spread of infectious diseases. Vaccination with different types of vaccines has been shown to improve immune response compared to the use of the same type of vaccine. This approach, where the first and second vaccine doses are different, may increase the effectiveness of the immune response.Conclusions: Studies confirm that vaccination reduces the number of cases and deaths, reducing the economic burden. A variety of vaccines, including mRNA, vector, and inactivated vaccines, provide high efficacy in preventing COVID-19 infection and mortality, especially when a heterologous vaccination regimen is used. This review identifies the most effective infectious disease control strategies for the development of global health recommendations

Enhancing Tuberculosis Treatment Adherence: Evaluating the Efficacy of the Support for Treatment Adherence and Medication Protocols (STAMP) Device for Automatic Dispensing and Real-Time Medication Monitoring.

Tuberculosis (TB) remains a significant global health challenge, necessitating strict adherence to medication for successful treatment and prevention of drug resistance. Adherence to a regular medication regimen is crucial in TB management, yet achieving high adherence rates among patients proves challenging due to various factors including forgetfulness, complexity of treatment schedules, and socioeconomic barriers. This study explores the potential of an automatic medicine dispenser (AMD) anchored system to improve medication adherence among TB patients and evaluates its impact through monitoring and feedback mechanisms. The AMD integrates advanced technology to dispense medications at scheduled times, thereby reducing reliance on patient memory and manual adherence tracking. This device is complemented by a monitoring system where healthcare mentors oversee adherence data in real-time via a web-linked dashboard. Such real-time monitoring enables mentors to promptly intervene in cases of non-adherence, offering personalized support and guidance tailored to individual patient needs. The study employs a mixed-methods approach, combining quantitative analysis of adherence rates derived from the AMD anchored system with qualitative data from patient surveys. These surveys gather insights into patient experiences and perceptions regarding the use of the AMD anchored system, including feedback on the accuracy of medication intake recorded by the device. Data obtained from the surveys are analyzed alongside adherence metrics from the dashboard to elucidate factors influencing adherence behavior and the device's effectiveness in fostering sustained treatment adherence. Preliminary findings indicate promising outcomes associated with the AMD anchored system intervention. High rates of adherence are observed among patients utilizing the device, attributed to the device's automated dispensing mechanism and the supportive role of healthcare mentors. Challenges such as technical malfunctions and patient acceptance are also identified, prompting continuous refinement of the AMD and mentorship strategies. In conclusion, the integration of an AMD coupled with real-time monitoring through a web-linked dashboard represents a significant advancement in TB treatment adherence management. Future research should focus on the scalability and sustainability of this technology-augmented, holistic approach across diverse healthcare settings to maximize its impact on global TB management strategies.

Exploring the scale and scope of community policing in North-Western Ghana

Global urban population growth appears to challenge governments’ ability to ensure access to essential urban services, such as policing. This situation is impeding the achievement of SDG target 11.1. However, citizens’ role in co-producing safe and secure neighbourhoods has been instrumental in augmenting limited governments’ efforts in the provision of adequate security. Acknowledging the relevance of co-producing community policing (CP) outcomes in neighbourhood crime management, this study critically examines the awareness, knowledge, understanding, and effectiveness of community policing strategies in North-Western Ghana. In a mixed methods research design, the study revealed a low level of awareness of community policing strategies in North-Western Ghana, which constrains the efforts to initiate and benefit from the outcomes of co-producing community policing. Consequently, knowledge, understanding, and effectiveness of community policing strategies appear very limited and, therefore, draw back the desire for inclusive, safe, resilient and sustainable cities as detailed in SDG 11. Restoring community watch committees and enkindling effective co-production of community policing outcomes are critical parts to the global crime management strategies.

Adaptive PF-CZM for multiphysics fracture analysis in functionally graded materials

Functionally graded materials (FGM) hold significant relevance in engineering due to their tailored material property gradation, designed for specific engineering applications. The challenge in fracture analysis of FGM stems from the spatial variation of material properties, which complicates the prediction of crack topology. Local and global refinement strategies are impractical for fracture analysis in FGM due to the unpredictable nature of crack topology, which renders local refinement infeasible. Additionally, global refinement is not advisable as it leads to a significant increase in degrees of freedom, adversely affecting computational efficiency.The novelty of this research lies in the incorporation of spatial variation in both the length scale and material properties, enhancing the realism of FGM domain modeling. To preserve the required length scale, it is necessary to adopt a minimum mesh size, which consequently results in a substantial increase in the degrees of freedom and, thereby, escalates the computational cost. To address these challenges, the study employs an adaptive mesh refinement (AMR) algorithm integrated with a phase-field cohesive zone model (PF-CZM), providing a robust solution for accurate fracture analysis in FGM. Based on the ideas stemming from the need for efficient and realistic modeling, the AMR-PF-CZM framework refines the mesh efficiently in regions of crack growth based on crack-driving energy and phase field variable, thereby eliminating the need for pre-refinement. The findings demonstrate a 76%–85% increase in computational efficiency and accuracy of the AMR-PF-CZM approach compared to the non-adaptive PF-CZM. Furthermore, the developed algorithm’s applicability to dynamic fracture and multi-physics problems, specifically addressing mechanical and thermal fracture in FGM, underscores the importance of this approach in capturing complex fracture phenomena.

Exploring the Influencing Factors of Net Ecosystem Productivity (NEP) Based on Random Forest and SHAP

As global climate change intensifies, Net Ecosystem Productivity (NEP) serves as a crucial indicator for measuring the carbon absorption and release of ecosystems, playing a vital role in understanding the carbon cycle and shaping climate policy. The Northwestern region of China, characterized as a typical inland arid and semi-arid area, is particularly sensitive to global changes. Understanding the environmental drivers of NEP in this region is critical for both regional ecological protection and global environmental management. This study utilized environmental data from five provinces in Northwestern China, applying the Random Forest (RF) model and SHapley Additive exPlanation (SHAP) method to analyze the primary environmental factors influencing NEP. The research integrated climatic data (including temperature, precipitation, wind speed, and solar radiation), soil characteristics such as pH, organic carbon content, and soil texture, topographic attributes elevation and slope, and a Human Footprint. The RF model identified significant environmental factors impacting NEP, and SHAP values were used to explain the specific contributions of these factors. Furthermore, multiple linear regression analysis revealed interactions among environmental factors. The results indicate that solar radiation (Srad), precipitation, topsoil reference bulk density (T_REF_BULK), temperature, and the topsoil clay fraction (T_CLAY) significantly influence NEP. Notably, interactions between aspect and T_CLAY, aspect and T_REF_BULK, as well as the human footprint (HFP) and Srad, also show significant impacts on NEP. This study confirms that solar radiation, precipitation, soil characteristics, and human activities are the primary environmental drivers of NEP in the Northwest region of China, with solar radiation playing the most critical promotional role. The findings not only provide a scientific basis for the management of ecosystems in Northwestern China but also offer references for formulating global climate change mitigation strategies and estimating the global carbon budget. Future research should further explore the specific mechanisms and interactions of these drivers across different ecosystems to more comprehensively understand and predict the trends in NEP changes.