Search Results (329)

As China’s first systematic assessment of high-risk Amaranthaceae invaders, this study addresses a critical knowledge gap identified in the National Invasive Species Inventory, in which four invasive Amaranthaceae species (Dysphania ambrosioides, Celosia argentea, Amaranthus palmeri, and Amaranthus spinosus) are prioritized due to CNY 2.6 billion annual ecosystem damages in China. By coupling multi-species comparative analysis with a parameter-optimized Maximum Entropy (MaxEnt) model integrating climate, soil, and topographical variables in China under Shared Socioeconomic Pathways (SSP) 126/245/585 scenarios, we reveal divergent expansion mechanisms (e.g., 247 km faster northward shift in A. palmeri than D. ambrosioides) that redefine invasion corridors in the North China Plain. Under current conditions, the suitable habitats of these species span from 92° E to 129° E and 18° N to 49° N, with high-risk zones concentrated in central and southern China, including the Yunnan–Guizhou–Sichuan region and the North China Plain. Temperature variables (Bio: Bioclimatic Variables; Bio6, Bio11) were the primary contributors based on permutation importance (e.g., Bio11 explained 56.4% for C. argentea), while altitude (e.g., 27.3% for A. palmeri) and UV-B (e.g., 16.2% for A. palmeri) exerted lower influence. Model validation confirmed high accuracy (mean area under the curve (AUC) > 0.86 and true skill statistic (TSS) > 0.6). By the 2090s, all species showed net habitat expansion overall, although D. ambrosioides exhibited net total contractions during mid-century under the SSP126/245 scenarios, C. argentea experienced reduced total suitability during the 2050s–2070s despite high-suitability growth, and A. palmeri and A. spinosus expanded significantly in both total and highly suitable habitat. All species shifted their distribution centroids northward, aligning with warming trends. Overall, these findings highlight the critical role of temperature in driving range dynamics and underscore the need for latitude-specific monitoring strategies to mitigate invasion risks, providing a scientific basis for adaptive management under global climate change. Full article

The current study examines the influence of a varying gravity field and its interaction with density stratification. This represents a novel area in baroclinic flow analysis. The classical vortex and internal wave structures in stratified flows are shown to be significantly modified when gravity varies with height. Vortices may shift, stretch, or weaken depending on the direction and strength of gravity variation, and internal waves develop asymmetries or damping that are not present under constant gravity. We examine the influence of gravity variation on the flow of both homogeneous and density-stratified fluids in a channel with topography consisting of a Gaussian obstacle lying at the bottom of the channel. The flow is without inertia, induced by the translation of the top plate. Both the density and gravity are assumed to vary linearly with height, with the minimum density at the moving top plate. The narrow-gap approach is used to generate the flow field in terms of the pressure gradient along the top plate, which, in turn, is obtained in terms of the bottom topography and the three parameters of the problem, namely, the Froude number and the density and gravity gradients. The resulting stream function is a fifth-order polynomial in the vertical coordinate. In the absence of stratification, the flow is smooth, affected rather slightly by the variable topography, with an essentially linear drop in the pressure induced by the contraction. For a weak stratified fluid, the streamlines become distorted in the form of standing gravity waves. For a stronger stratification, separation occurs, and a pair of vortices generally appears on the two sides of the obstacle, the size of which depends strongly on the flow parameters. The influence of gravity stratification is closely coupled to that of density. We examine conditions where the coupling impacts the pressure and the velocity fields, particularly the onset of gravity waves and vortex flow. Only a mild density gradient is needed for flow separation to occur. The influence of the amplitude and width of the obstacle is also investigated. Full article

Japan’s 8.5 million vacant homes (Akiyas) represent a paradox of scarcity amid surplus: while rural depopulation leaves properties abandoned, housing shortages and bureaucratic inefficiencies hinder their reuse. This study proposes AKI2ALL, an AI-blockchain framework designed to automate the circular repurposing of Akiyas into ten high-value community assets—guesthouses, co-working spaces, pop-up retail and logistics hubs, urban farming hubs, disaster relief housing, parking lots, elderly daycare centers, exhibition spaces, places for food and beverages, and company offices—through smart contracts and data-driven workflows. By integrating circular economy principles with decentralized technology, AKI2ALL streamlines property transitions, tax validation, and administrative processes, reducing operational costs while preserving embodied carbon in existing structures. Municipalities list properties, owners select uses, and AI optimizes assignments based on real-time demand. This work bridges gaps in digital construction governance, proving that automating trust and accountability can transform systemic inefficiencies into opportunities for community-led, low-carbon regeneration, highlighting its potential as a scalable model for global vacant property reuse. Full article

This paper reviews the variability of passenger service time (PST) at the platform–train interface (PTI), a critical performance indicator in metro systems shaped by the infrastructure design, affecting passenger behavior and accessibility. Despite its operational importance, PST remains underexplored in relation to crowd management strategies. This review synthesizes findings from empirical and experimental research to clarify the main factors influencing PST and their implications for platform-level interventions. Key contributors to PST variability include door width, gap dimensions, crowd density, and user characteristics such as mobility impairments. Design elements—such as platform edge doors, yellow safety lines, and vertical handrails—affect flow efficiency and spatial dynamics during boarding and alighting. Advanced tracking and simulation tools (e.g., PeTrack and YOLO-based systems) are identified as essential for evaluating pedestrian behavior and supporting Level of Service (LOS) analysis. To complement traditional LOS metrics, the paper introduces Level of Interaction (LOI) and a multidimensional LOS framework that captures spatial conflicts and user interaction zones. Control strategies such as platform signage, seating arrangements, and visual cues are also reviewed, with experimental evidence showing that targeted design interventions can reduce PST by up to 35%. The review highlights a persistent gap between academic knowledge and practical implementation. It calls for greater integration of empirical evidence into policy, infrastructure standards, and operational contracts. Ultimately, it advocates for human-centered, data-informed approaches to PTI planning that enhance efficiency, inclusivity, and resilience in high-demand transit environments. Full article

Background/Objectives: Clinical Research Nurses (CRNs) have emerged as pivotal actors in the conduct, coordination, and oversight of clinical trials globally. Over the past three decades, the role of the CRN has evolved in response to the increasing complexity of research protocols, ethical standards, and regulatory frameworks. Originating as task-oriented support figures, CRNs have progressively assumed broader responsibilities that include patient advocacy, protocol integrity, ethical vigilance, and interprofessional coordination. By mapping the global literature on CRNs, this review will examine how their role has been defined, implemented, and evaluated over the past three decades. Methods: A scoping review was conducted using JBI methodology and PRISMA-ScR guidelines. The search covered the peer-reviewed and gray literature from 1990 to 2024 across major databases. Data analysis combined traditional extraction with topic modeling, Multiple Correspondence Analysis, and k-means clustering to identify key themes. Results: From the 128 included studies, four major themes emerged: clinical trial management, role perception and team integration, professional competencies and development, and systemic barriers. Despite formal competency frameworks, CRNs face inconsistencies in role recognition, unstable contracts, and limited career pathways. Emotional strain and professional isolation are recurrent. Over time, their functions have evolved from task execution to broader responsibilities, including advocacy and ethical oversight. However, no studies reported patient-level outcomes, revealing a critical gap in the evidence base. Conclusions: CRNs play a vital but undervalued role in clinical research. Persistent structural challenges hinder their development and visibility. Enhancing institutional support and generating outcome-based evidence are necessary steps toward fully integrating CRNs into research infrastructures. Full article

Risk management is crucial in engineering projects, especially in highly complex environments like petrochemical plants producing polyvinyl chloride (PVC). This study proposes a tailored risk management model, using analytic hierarchy process (AHP) and linear regression analysis, alongside MS Excel and IBM SPSS^® version 23, to identify, assess, and prioritize key risks. Surveys and interviews revealed seven management factors (budget, schedule, safety, productivity, contracting, quality, and environment) and 18 critical risks, including design errors and procurement delays. The model quantifies risk impacts, provides a regression equation for risk classification, and supports effective mitigation strategies. Based on this model, decision-making can be facilitated for the implementation of effective mitigation strategies. It also promotes continuous improvement, optimizing economic resources and minimizing environmental impacts, addressing a research gap in Colombia’s petrochemical sector and paving the way for broader industrial applications. Full article

Endophytic microorganisms inhabiting plant tissues constitute a unique and largely untapped reservoir of bioactive metabolites, including phenolics, terpenoids, alkaloids, polysaccharides, and anthraquinones, among others. This review focuses on the potential of these compounds to modulate the complex processes of wound repair, such as hemostasis, inflammation, proliferation, and remodeling. Uniquely, this review delineates the specific mechanisms supported not only by indirect evidence but by primary research directly linking endophytic metabolites to wound repair. We synthesized and evaluated evidence from 18 studies, of which over 75% directly assessed wound healing effects through in vitro and in vivo models. Metabolites from endophytic microorganisms promoted wound contraction, suppressed biofilm formation by key pathogens (e.g., MRSA, P. aeruginosa), and accelerated tissue re-epithelialization in animal models. Other compounds demonstrated >99% wound closure in rats, while several extracts showed anti-inflammatory and cytocompatible profiles. Nevertheless, the majority of studies applied unstandardized methods and used crude extracts, hindering precise structure–activity assessment. The originality of this review lies in drawing attention to direct evidence for wound healing from diverse endophytic sources and systematically identifying gaps between preclinical promise and clinical translation, positioning endophytes as a sustainable platform for next-generation wound therapeutics. Full article

Informal groundwater markets, where farmers with wells sell surplus water to neighbors, are a widespread adaptive response to water scarcity, particularly in South Asia where they are most prevalent and well-documented. This review (1990–2025) examines the evolving patterns of these markets by synthesizing global literature and viewing them through the lens of three transformative trends: energy transition (especially solar pumps), digital innovations (e.g., blockchain and IoT), and new policy pathways. We synthesize literature to evaluate market structures, contract forms, efficiency and equity outcomes, environmental impacts, and the influence of energy policies and digital tools. The review assesses whether these informal trades fulfill their promise of enhancing water productivity and equity or if new challenges are creating pitfalls. Key objectives include documenting historical evolution, analyzing market performance, discussing externalities like aquifer depletion, examining policy interactions, reviewing digital pilots, exploring social inclusion, comparing governance frameworks, identifying research gaps linked to SDGs, and proposing a policy roadmap for harnessing benefits while ensuring sustainability. Full article

Aluminum alloy, due to its low melting point and high thermal conductivity, deforms and contracts significantly during welding. To mitigate this and achieve full penetration in a single pass, this study uses GTAW (Gas Tungsten Arc Welding) additive manufacturing and optimizes welding groove parameters via the Box-Behnken Response Surface Methodology. The focus is on improving tensile strength and penetration depth by analyzing the effects of groove angle, root face width, and root gap. The results show that groove angle most significantly affects tensile strength and penetration depth. Hardness profiles exhibit a W-shape, with base material hardness decreasing and weld zone hardness increasing as groove angle rises. Root face width reduces hardness fluctuation in the weld zone, and an appropriate root gap compensates for thermal expansion, enhancing joint performance. The interaction between root face width and root gap most impacts tensile strength, while groove angle and root face width interaction most affects penetration depth. The optimal welding parameters for 7xxx aluminum alloy GTAW are a groove angle of 70.8°, root face width of 1.38 mm, and root gap of 0 mm. This results in a tensile strength of 297.95 MPa and penetration depth of 5 mm, a 90.38% increase in tensile strength compared to the RSM experimental worst group. Microstructural analysis reveals the presence of β-Mg₂Si and η-MgZn₂ strengthening phases, which contribute to the material’s enhanced mechanical properties. Fracture surface examination exhibits characteristic ductile fracture features, including dimples and shear lips, confirming the material’s high ductility. The coexistence of these strengthening phases and ductile fracture behavior indicates excellent overall mechanical performance, balancing strength and plasticity. Full article

This paper examines the impact of carbon capture and storage (CCS) deployment on national carbon intensity (CI) across 43 countries from 2010 to 2020. Using a dynamic common correlated effects (DCCE) log–log panel, we estimate the elasticity of CI with respect to sectoral CCS facility counts within four income-group panels and the full sample. In the high-income panel, CCS in direct air capture, cement, iron and steel, power and heat, and natural gas processing sectors produces statistically significant CI declines of 0.15%, 0.13%, 0.095%, 0.092%, and 0.087% per 1% increase in facilities, respectively (all p < 0.05). Upper-middle-income countries exhibit strong CI reductions in direct air capture (–0.22%) and cement (–0.21%) but mixed results in other sectors. Lower-middle- and low-income panels show attenuated or positive elasticities—reflecting early-stage CCS adoption and infrastructure barriers. Robustness checks confirm these patterns both before and after the 2015 Paris Agreement and between emerging and developed economy panels. Spatial analysis reveals that the United States and United Kingdom achieved 30–40% CI reductions over the decade, whereas China, India, and Indonesia realized only 10–20% declines (relative to a 2010 baseline), highlighting regional deployment gaps. Drawing on these detailed income-group insights, we propose tailored policy pathways: in high-income settings, expand tax credits and public–private infrastructure partnerships; in upper-middle-income regions, utilize blended finance and technology-transfer programs; and in lower-income contexts, establish pilot CCS hubs with international support and shared storage networks. We further recommend measures to manage CCS’s energy and water penalties, implement rigorous monitoring to mitigate leakage risks, and design risk-sharing contracts to address economic uncertainties. Full article

To address the issue of excessive pessimism caused by demand and supply uncertainties in the green hydrogen supply chain, this study develops a two-tier green hydrogen supply chain model comprising upstream hydrogen production stations and downstream hydrogen refueling stations. This research work investigates optimal ordering and production strategies under stochastic demand and supply conditions. Additionally, option contracts are introduced to share the risks associated with the stochastic output of green hydrogen. This study shows the following: (1) Under decentralized decision-making, the optimal ordering quantity when the hydrogen refueling station is excessively pessimistic is not necessarily lower than the optimal ordering quantity when it is in a rational state, and hydrogen production stations will only operate when the degree of excessive pessimism is relatively low. (2) The initial option ordering quantity is always larger than the minimum execution quantity under the option contract; higher first-order option prices and lower second-order option prices can help to increase the initial option ordering quantity. (3) The option contract is effective in circumventing the negative impact of excessive pessimism at hydrogen production stations on planned production quantities. This study addresses the gap in the existing research regarding excessively pessimistic behaviors and the application of option contracts within the green hydrogen supply chain, providing both theoretical insights and practical guidance for decision-making optimization. This advancement further promotes the sustainable development of the green hydrogen industry. Full article

The rapid integration of AI into IoT systems has outpaced the ability to explain and audit automated decisions, resulting in a serious transparency gap. We address this challenge by proposing a blockchain-based framework to create immutable audit trails of AI-driven IoT decisions. In our approach, each AI inference comprising key inputs, model ID, and output is logged to a permissioned blockchain ledger, ensuring that every decision is traceable and auditable. IoT devices and edge gateways submit cryptographically signed decision records via smart contracts, resulting in an immutable, timestamped log that is tamper-resistant. This decentralized approach guarantees non-repudiation and data integrity while balancing transparency with privacy (e.g., hashing personal data on-chain) to meet data protection norms. Our design aligns with emerging regulations, such as the EU AI Act’s logging mandate and GDPR’s transparency requirements. We demonstrate the framework’s applicability in two domains: healthcare IoT (logging diagnostic AI alerts for accountability) and industrial IoT (tracking autonomous control actions), showing its generalizability to high-stakes environments. Our contributions include the following: (1) a novel architecture for AI decision provenance in IoT, (2) a blockchain-based design to securely record AI decision-making processes, and (3) a simulation informed performance assessment based on projected metrics (throughput, latency, and storage) to assess the approach’s feasibility. By providing a reliable immutable audit trail for AI in IoT, our framework enhances transparency and trust in autonomous systems and offers a much-needed mechanism for auditable AI under increasing regulatory scrutiny. Full article

The distortion of energy prices has become an important obstacle to the high-quality development of China’s economy. Moreover, energy price distortions are not merely a domestic issue. They may trigger carbon leakage by diverting emissions-intensive production to countries with cheaper energy. Although the existing literature has extensively examined the effects of energy price distortions, two significant research gaps remain. First, most studies treat energy price distortions merely as an influencing factor, lacking a systematic analysis that places it at the core. Second, the spatial correlation characteristics of energy price distortions are often overlooked. This study measures the degree of energy price distortions across Chinese provinces from 2000 to 2022 and employs methods such as the Global Moran’s I, Local Moran’s I, and kernel density estimation to systematically analyze the spatial correlation, spatial distribution of coordination indices, and dynamic evolution patterns of these distortions. The results reveal that: (1) the overall degree of energy price distortions in China exhibited a trend of rising first and then declining, with significant regional disparities; (2) the regional gap followed an “expansion-contraction” trajectory; (3) there is notable spatial autocorrelation, with high-distortion areas concentrated in Northeast China, the middle reaches of the Yellow River, and Northwest China; and (4) the dynamic evolution suggests that distortion levels in high- and medium-value regions may continue to decline, while those in low-value regions may increase. This study fills a critical gap in the systematic spatial analysis of energy price distortions and provides new empirical evidence and policy insights for advancing market-oriented reforms in energy markets. Full article

The impact of work engagement and burnout on medical activities, physicians’ performance, and quality of care has gained interest over the last decades. However, the effect of demographics, job-related, and organizational variables on burnout and work engagement in young endocrinologists has not been fully investigated. To assess the impact of demographics, job-related, and organizational variables on burnout and work engagement in young endocrinologists who joined the Italian Association of Clinical Endocrinologists. The levels of burnout and work engagement were assessed by the Maslach Burnout Inventory and the Utrecht Work Engagement Scale, respectively, as a part of an online survey of the “Associazione Medici Endocrinologi” addressed to young members (31–40 years). Eighteen MANOVAs were applied to analyze differences in burnout and work engagement based on demographic, job-related, and organizational factors. We collected responses from 160 young endocrinologists, mainly women (80.6%), aged 31–35 years (33.8%) and 36–40 years (66.2%). Most were in a stable relationship with (40%) or without (45%) children. Most of them worked in hospitals or local healthcare districts (35.6%), as independent contractors (31.9%), or as Ph.D. students or residents (25.6%). Multivariate analyses found no statistically significant differences in burnout and work engagement due to demographics (gender, age, and partnership) and job-related variables (type of job and contract). On the other hand, organizational variables (levels of conflict amongst colleagues, more than expected time spent working, and no involvement in team-building activities) were associated with higher emotional exhaustion, lower dedication, and less vigor. The novelty of the study is that both burnout and work engagement can be affected by organizational variables in early-career Italian endocrinologists, highlighting the need for supporting the healthcare system to overcome this gap. Full article

Methane (CH₄) emissions from dairy farming represent a substantial yet under-quantified share of agricultural greenhouse gas emissions. This study provides an in-depth, satellite-based fingerprinting analysis of methane emissions from Canada’s dairy sector, using Sentinel-5P/TROPOMI data. We utilized a robust quasi-experimental design, pairing 14 dairy-intensive zones with eight non-dairy reference regions, to analyze methane emissions from 2019 to 2024. A dynamic, region-specific baseline approach was implemented to remove temporal non-stationarity and isolate dairy-specific methane signals. Dairy regions exhibited consistently higher methane concentrations than reference areas, with an average methane anomaly of 17.4 ppb. However, this concentration gap between dairy and non-dairy regions notably narrowed by 57.23% (from 24.42 ppb in 2019 to 10.44 ppb in 2024), driven primarily by accelerated methane increases in non-dairy landscapes and a pronounced one-year contraction during 2022–2023 (−39.29%). Nationally, atmospheric methane levels rose by 3.83%, revealing significant spatial heterogeneity across provinces. Notably, an inverse relationship between the initial methane concentrations in 2019 and subsequent growth rates emerged, indicating spatial convergence. The seasonal analysis uncovered consistent spring minima and fall–winter maxima across regions, reflecting the combined effects of seasonal livestock management practices, atmospheric transport dynamics, and biogeochemical processes. The diminishing dairy methane anomaly suggests complex interplay of intensifying background methane emissions from climate-driven wetland fluxes, increasing fossil fuel extraction activities, and diffuse agricultural emissions. These findings underscore the emerging challenges in attributing sector-specific methane emissions accurately from satellite observations, highlighting both the capabilities and limitations of current satellite monitoring approaches. Full article