Search Results (1,363)

This study examines the relationship between energy consumption and energy-related CO₂ emissions for a sample of 79 reporting entities, grouped into seven regions, over the period 2013–2023. The methodology uses three empirical tools: (i) Tapio elasticity to classify types of decoupling; (ii) Kaya–LMDI decomposition to identify factors that determine emissions; and (iii) a log-difference panel model to separate year- and country-specific effects. The results indicate a reduction in carbon intensity in all regions, more pronounced in Europe and North America. According to the Tapio classification, Europe is in recessive decoupling, the Middle East is on the verge of expansive decoupling, North and South America are in strong expansive decoupling, and Asia Pacific, Africa, and CIS show only weak signals of expansive decoupling. The LMDI results show that, in regions with strong decoupling, the decrease in carbon intensity contributes to reducing emissions. In those with weak decoupling, the effects are partially canceled out by population growth and energy demand. Finally, the fixed-effects panel model does not identify any structural decoupling at the regional level. Overall, this study contributes to the literature by separating long-term structural effects from annual fluctuations. On this basis, we provide clear guidelines for designing regional energy policies. Full article

Interest in Zika virus (ZIKV, Orthoflavivirus zikaense) evolution and pathogenicity has attracted the attention of a wider circle of the research community ever since ZIKV emerged on the South American continent in 2015, after more or less island hopping across the Pacific Ocean from Southeast Asia on its way from Africa where it was first described in Uganda in 1947 [...] Full article

Background/Objectives: Antimicrobial resistance (AMR) is a major global health threat that reduces antibiotic effectiveness and increases healthcare burdens. Countries in the Asia–Pacific region face a particularly high AMR burden, necessitating international collaboration, education, and practical training to combat this growing crisis. This study describes the design, implementation, and educational outcomes of the Infection Diagnosis Workshop, a short-term international program primarily targeting undergraduate medical sciences students that integrates AMR-focused hands-on clinical microbiology training and lectures, alongside cross-cultural collaboration and scientific English communication. Methods: The Infection Diagnosis Workshop was implemented as a four-day program combining lectures with hands-on laboratory activities. Training emphasizes the detection and analysis of antibiotic-resistant bacteria through environmental sampling, bacterial culturing, phenotypic and genotypic resistance detection, and species identification, core components that have remained consistent since the workshop’s establishment. Students also attended lectures on AMR science, global impact, and management strategies. Group discussions and collaborative tasks encouraged interdisciplinary learning. A thematic analysis of student feedback essays from previous workshop cohorts was conducted to identify key concepts, learning outcomes, and shared experiences. All participants provided informed consent for the use of their written feedback. Results: Thematic analysis revealed key learning outcomes categorized into three themes: (1) Knowledge, Awareness, and Technical Skills; (2) Cultural Understanding and Cross-Cultural Collaboration; and (3) English Language and Communication Skills. Students reported increased AMR knowledge, improved laboratory proficiency, enhanced cultural adaptability, and greater confidence in English communication. They also expressed a deeper appreciation for interdisciplinary and international approaches to AMR. Conclusions: The Infection Diagnosis Workshop effectively integrated practical laboratory training with international and cross-cultural engagement. The program strengthened student competencies and contributed to building global partnerships essential for combating AMR. Full article

Applying two Lyapunov functions and the concepts of $\alpha$-/$\omega$-limit sets, this paper reexamines fractional-order and integer-order coupled Lorenz systems and simultaneously proves the existence of twelve heteroclinic orbits, i.e., four ones to $S_0$ and $S_{5,6,7,8}$, four pairs of ones to $S_1$ and $S_{5,7}$, $S_3$ and $S_{5,6}$, $S_2$ and $S_{6,8}$, $S_4$ and $S_{7,8}$ when $r-1>0$, $b\ge 2\sigma >0$ and $ac<0$. These orbits have not been reported in existing studies on coupled Lorenz-type systems and are verified via numerical simulations. The findings not only uncover new dynamics of the Lorenz system family and expand the application scope of Lyapunov-based methods but also provide insights into heteroclinic orbits of other fractional-order and integer-order Lorenz-like counterparts. Full article

Background: Obesity is a major health concern worldwide and the World Health Organization (WHO) has declared it a global epidemic. We aimed to analyze temporal trends of obesity prevalence worldwide. Methods: We used data of “The Global Health Observatory” of the WHO and analyzed data from the Global Burden of Disease (GBD) Study 2023. Obesity prevalence (crude estimates) among adults in different worldwide WHO regions and temporal trends from 1976 and 2016 were analyzed. Results: Obesity prevalence showed large regional differences. In 2016, obesity prevalence was highest in the WHO European region and the region of the Americas, at more than 20%, whereas prevalence was lower in the WHO African region, the WHO Western Pacific region and the WHO South-East Asia region, at less than 10%. The absolute increase from 1976 to 2016 comprised an increase of 19.7% in the region of the Americas, of 14.8% and 14.2% in the WHO European region and the WHO Eastern Mediterranean region, followed by 7.3% in the WHO African region, 6.0% in the WHO Western Pacific region, and 4.2% in the WHO South-East Asia region. We observed a substantially higher prevalence of obesity in females. High BMI has risen sharply in rank worldwide, now ranging among the top six global risk factors for death. Major BMI-related causes include ischemic heart disease, type 2 diabetes mellitus, hypertensive heart disease, and ischemic stroke. Conclusions: Obesity prevalence showed large regional differences and was highest in Europe and America. The prevalence of obesity increased worldwide between 1976 and 2016. Obesity prevalence was higher in females than in males. The importance of obesity for premature death increased between 1990 and 2023. Full article

The Asia Pacific, led by the resource-dependent ASEAN-5, is the largest carbon contributor, yet its firms exhibit critically low transparency. This study examines the relationship between voluntary Sustainability Assurance (SA) and carbon disclosure transparency using 875 firm-year observations (2018–2022). Applying panel regression and several robustness tests, we find that SA adoption has a positive relationship with the magnitude of disclosed carbon emissions, indicating enhanced transparency. This positive relationship is significantly more pronounced in firms with high environmental performance and greater property, plant, and equipment (PPE) efficiency, suggesting SA aligns with genuine sustainability efforts rather than symbolic reporting. Furthermore, SA increases the likelihood of disclosing the complex Scope 3 emissions. However, the effectiveness of SA is conditional: its transparency benefit is statistically significant only within mandatory sustainability reporting (SR) regimes and in non-environmentally sensitive industries, highlighting crucial variations across regulatory and industrial contexts within ASEAN-5. This research provides evidence on the role of SA in emerging markets, extending Agency Theory by demonstrating its function as a credibility signal that reduces information asymmetry. We offer practical guidance for managers seeking market differentiation, and for regulators aiming to align voluntary SA with IFRS S1/S2 to enhance disclosure quality. Full article

The construction industry continues to grapple with persistently high accident rates and fragmented workforce management systems, where manual record-keeping and siloed data impede effective safety compliance. While digital interventions exist, they often rely on centralized databases that are vulnerable to manipulation and opaque. This systematic literature review critically examines the application of blockchain technology as a decentralized infrastructure for enhancing safety compliance in construction. Adhering to the PRISMA 2020 guidelines, this study synthesizes findings from 115 peer-reviewed articles (2020–2025) retrieved from Scopus, Web of Science, IEEE Xplore, and Google Scholar. The analysis focuses on three core mechanisms: (1) the creation of immutable, timestamped safety logs to prevent retroactive data tampering; (2) the integration of IoT sensors for real-time, trustless hazard monitoring; and (3) the deployment of smart contracts to automate compliance verification and incentive distribution. The review juxtaposes theoretical frameworks with empirical evidence from global case studies, including pilot projects in North America and the Asia-Pacific, to quantify benefits such as reduced reporting latency and improved data integrity. Despite promising results, the analysis reveals significant barriers to widespread adoption, notably the “oracle problem,” scalability limitations of consensus protocols, and the lack of legal recognition for blockchain records. This paper concludes that while blockchain is not a panacea, it offers a necessary layer of trust and accountability absent in traditional Common Data Environments (CDEs). Future research directions are proposed to address interoperability with BIM standards (ISO 19650) and to develop energy-efficient consensus mechanisms suitable for resource-constrained construction sites. Full article

During the global transition of energy structures toward renewable sources, offshore wind power has experienced rapid advancement, coinciding with increasingly complex wave environments. This study focuses on the wave conditions of an offshore wind farm project in Vietnam. A dual-nested numerical framework (WAVEWATCH III + SWAN) is established, integrated with 32-year (1988–2019) high-resolution WRF wind fields and fused bathymetry data (GEBCO + in situ measurements). This framework overcomes the limitations of short-term datasets (10–22 years) in prior studies and achieves 1′ × 1′ (≈1.8 km) intra-farm resolution—critical for capturing topographic modulation of waves. A systematic analysis of the regional wave climate characteristics is performed, encompassing wave roses, joint distributions of significant wave height and spectral peak period, wave–wind direction correlations, and significant wave height–wind speed relationships. Extreme value theory, specifically the Pearson Type-III distribution, is applied to estimate extreme wave heights and corresponding periods for return periods ranging from 1 to 100 years, yielding critical design wave parameters for wind turbine foundations and support structures. Key findings reveal that the wave climate is dominated by E–SE (90°–120°) monsoon-driven waves (60% of $H_s$ = 0.5–1.5 m), while extreme waves are uniquely concentrated at 120°—attributed to westward Pacific typhoon track alignment and long fetch. For the outmost site (A55, 7.18 m water depth), the 100-year return period significant wave height ($H_{s100}$ = 4.66 m, $T_{p100}$ = 13.05 s) is 38% higher than sheltered shallow-water sites (A28, $H_{s100}$ = 2.7 m), reflecting strong bathymetric control on wave energy. This study makes twofold contributions: (1) Methodologically, it validates a robust framework for long-term wave simulation in tropical monsoon–typhoon regions, combining 32-year high-resolution data with dual-nested models. (2) Scientifically, it reveals the directional dominance and spatial variability of waves in the Mekong estuary, advancing understanding of typhoon–wave–topography interactions. Practically, it provides standardized design parameters (compliant with DNV-OS-J101/IEC 61400-3) for offshore wind projects in Southeast Asia. Full article

Dust accumulation on photovoltaic (PV) modules is a major factor contributing to reduced power output, lower efficiency, and accelerated material degradation, particularly in arid and industrialized regions. This study presents a comprehensive review and analysis of the influence of dust deposition on PV performance, covering its optical, thermal, and electrical impacts. Findings from global literature indicate that dust-induced efficiency losses typically range from 10% to 70%, depending on particle characteristics, environmental conditions, and surface orientation. Experimental and modeled I–V and P–V characteristics further reveal significant declines in current and power output as soiling levels increase. Through an extensive literature assessment, this paper identifies Machine Learning (ML)-based approaches as emerging and highly effective techniques for dust detection and mitigation. Recent studies demonstrate the integration of image processing, drone-assisted monitoring, and convolutional neural networks (CNNs) to enable automated, real-time soiling assessment. These intelligent methods outperform conventional manual and time-based cleaning strategies in accuracy, scalability, and cost efficiency. By synthesizing current research trends, this review highlights the growing role of ML and data-driven technologies in enhancing PV system reliability, informing predictive maintenance, and supporting sustainable solar energy generation. Full article

The Satellite Internet of Things (IoT) sector is undergoing rapid transformation, driven by breakthroughs in satellite communications and the pressing need for seamless global coverage—especially in remote and poorly connected regions. In locations where terrestrial infrastructure is limited or non-existent, Low Earth Orbit (LEO) satellites are proving to be a game-changing solution, delivering low-latency and high-throughput links well-suited for IoT deployments. While North America currently dominates the market in terms of revenue, the Asia-Pacific region is projected to lead in growth rate. Nevertheless, the development of satellite IoT networks still faces hurdles, including spectrum regulation and international policy alignment. In this evolving landscape, the LoRa and LoRaWAN protocols have been enhanced to support direct communication with LEO satellites, typically operating at altitudes between 500 km and 2000 km. This paper offers a comprehensive review of current research on LoRa/LoRaWAN technologies integrated with LEO satellite systems, also providing a performance assessment of this combined architecture in terms of theoretical achievable bitrate, Bit Error Rate (BER), and path loss. The results highlight the main performance trends of LoRa LR-FHSS in direct-to-LEO links. Path loss increases sharply with distance, reaching approximately 150 dB at 500 km and 165–170 dB at 2000 km, significantly reducing achievable data rates. At 500 km, bitrates range from approximately 7–8 kbps for SF7 to below 2 kbps for SF12. BER follows a similar trend: below 200 km, values remain low (${10}^{-4}$–${10}^{-3}$) for all spreading factors. At 1000 km, BER rises to approximately $3.9\times {10}^{-3}$ for SF7 and $1.5\times {10}^{-3}$ for SF12. At 2000 km, BER reaches approximately $4.7\times {10}^{-2}$ for SF7 but stays below $2\times {10}^{-2}$ for SF12, showing a 2–$3\times$ improvement with higher spreading factors. Overall, many links exhibit path loss above 160 dB and BER in the ${10}^{-3}$–${10}^{-2}$ range at long distances. These results underscore the importance of adaptive spreading factor selection and LR-FHSS gain for reliable long-range satellite IoT connectivity, highlighting the trade-off between robustness and spectral efficiency. Full article

Cryptosporidiosis is a globally important protozoan disease that causes severe gastrointestinal illness in immunocompromised humans and animals and has been associated with chronic wasting and death in reptiles. This study investigated the role of Cryptosporidium infection in wasting syndrome among captive leopard geckos from a commercial breeding facility in Chiang Mai, Thailand. Thirty-five geckos housed in twenty-three enclosures were observed for four months, with fecal samples collected over three consecutive days every two weeks and pooled for molecular analysis. Clinical evaluations included body weight (BW), tail diameter, and body condition score (BCS) to assess wasting. Nested PCR targeting the 18S rRNA gene and subsequent sequencing were performed. Cryptosporidium was detected in 51.43% of geckos and 52.17% of enclosures, while 20% exhibited wasting syndrome. BLAST (v. 2.17.0) and phylogenetic analyses identified C. varanii, which showed 100% identity with isolates from leopard geckos in Spain and from snakes in Thailand and China. Multivariable logistic regression demonstrated a significant association between Cryptosporidium infection and wasting syndrome (OR = 11.15, 95% CI: 1.78–69.98, p = 0.027), with persistent oocyst shedding observed. This study provides new insights into C. varanii infection among leopard gecko breeders in Thailand and highlights the potential for infected breeding stock to disseminate Cryptosporidium, underscoring the need for enhanced awareness, surveillance, and biosecurity measures across Thailand and the Asia-Pacific region. Full article

Based on CMIP6 model data and reanalysis data, two multi-model ensemble means—the “best” model ensemble (BMME) and the negative correlation ensemble (NCE)—were derived from 30 models to simulate the August Asian–Pacific Oscillation (APO) and the influence of the August APO on September precipitation over northern Xinjiang (NXPI). The results show that BMME performs better than individual models in simulating the eddy temperature in August. Overall, the BMME-simulated APO intensity shows a general decreasing trend from 2015 to 2100. Based on NCE, regressions of the precipitation and 850-hPa wind fields onto the APOI reproduce spatial patterns similar to the observations under the historical scenario. Furthermore, the NCE-simulated correlation between APO Index (APOI) and NXPI remains steadily negative during 2021–2040 under both SSP2-4.5 and SSP5-8.5 scenarios, but the negative correlation weakens significantly over the subsequent 60 years. This may be related to the southeastward shift of the negative geopotential height anomaly center over East Asia. Full article

Multiple sclerosis (MS) affects approximately 2.9 million people in the world, exerting a significant economic and societal burden. The disease is increasingly identified among populations considered as uncommonly affected. MS is reported in all regions of the World Health Organization (WHO) member states in Africa, the Americas, South-East Asia, Europe, the Eastern Mediterranean and the Western Pacific, affecting all ethnicities while exhibiting substantially variable prevalences. Countries with high MS prevalence and some with moderate frequencies generally have economically better structured healthcare systems. Nevertheless, health disparities in these countries are accentuated by suboptimal accessibility of care for their minorities, immigrants and other underserved populations. Social Determinants of Health (SDOH) might have an impact on morbidity and higher rates of disability. Large segments of the world population (i.e., African, Latin American, people from the Middle East and Southeast Asia) do not have access to adequate MS diagnostic procedures, compounded by reduced availability of neurologists. Healthcare disparities exist practically in every country of the world. Active wars and a large number of refugees resulting from conflict augments the challenges to healthcare systems. These global factors constitute obstacles to the adequate management of MS. A collective international path is required to facilitate access to highly effective, albeit onerous treatments, some already approved and being utilized, i.e., monoclonal antibodies and B-lymphocyte depletory agents, and others foreseen in the future as advanced therapeutic molecules continue to develop. Full article

Background: The COVID-19 pandemic accelerated the development of diverse vaccine platforms, including mRNA, adenoviral vector, and protein subunit vaccines. Given the growing evidence that the gut microbiome modulates vaccine-induced immunity, this study compared the effects of a protein subunit vaccine (NVX-CoV2373), an mRNA vaccine (BNT162b2), and an adenoviral vector vaccine (ChAdOx1) on gut microbiome diversity following booster vaccination. Methods: We conducted a prospective cohort study involving 35 healthy adults who received an NVX-CoV2373 booster. Stool and blood samples were collected before vaccination and three weeks afterward. Gut microbiome profiles were analyzed using 16S rRNA gene sequencing, and the results were compared with our previous cohorts who received BNT162b2 or ChAdOx1 vaccines. Results: The NVX-CoV2373 booster was associated with a significant increase in the Shannon diversity index (p = 0.027), indicating enhanced alpha diversity. This finding contrasts with the decrease or absence of significant short-term change observed following repeated administrations of adenoviral vector and mRNA vaccines, respectively. Notably, NVX-CoV2373 vaccination was accompanied by an increased relative abundance of beneficial taxa such as Bacteroides fragilis and a decrease in Prevotella bivia. In comparison, repeated ChAdOx1 doses resulted in a sustained reduction in alpha diversity, whereas BNT162b2 showed a transient post-booster rise followed by a long-term decline in species richness. Conclusions: In the booster setting, the protein subunit vaccine NVX-CoV2373 exerted a distinct and favorable effect on gut microbiome diversity, increasing alpha diversity in contrast to the patterns observed with mRNA and adenoviral vector booster vaccines. Full article

Recent botulinum neurotoxin type A (BoNT/A) formulations have shifted towards the use of polysorbate 20 (PS20) and polysorbate 80 (PS80) as a non-human-derived excipient to enhance product stability. Polysorbates are a distinct class of synthetic non-ionic surfactants with high heterogeneity in chemical structure and properties. Accumulating mechanistic and clinical evidence suggests that they may trigger immunological reactions, including hypersensitivity and immunogenicity. Such risks are largely associated with their susceptibility to degradation via hydrolysis and oxidation, forming reactive byproducts that can interact with proteins and immune pathways. Despite these mechanistic insights, data on the association between polysorbate excipients and observed immune outcomes in practice is relatively sparse and excipient-related immunogenicity and hypersensitivity is often underrecognized in practice. This review provides a summary of polysorbate excipients in BoNT/A formulations, focusing on their chemical properties and degradation pathways, characterizing downstream immune effects and appraising available clinical data of polysorbate-containing BoNT/A formulations. Finally, we discuss potential risk mitigation strategies including process modifications that could prevent degradation, and consideration of alternative excipients, such as human serum albumin, that has been shown to be immunologically inert and has an established safety profile. By integrating chemical, mechanistic, and clinical perspectives, this review seeks to clarify the implications of polysorbate use in BoNT/A formulations and inform both clinical practice and future formulation strategies. Full article