Search Results (51,408)

Slate typically contains significant bedding structures and often displays varying mechanical properties under different inclination conditions, with numerous adverse impacts on construction projects. In light of its anisotropic characteristics, a slate foundation pit in Changsha is considered in this study, and uniaxial and triaxial compression tests are initially conducted on slate under various bedding inclination angles. Through these tests, the mechanical parameters of the slate are obtained, and the laws governing the variation in the stress–strain curves and failure modes are analyzed. The results show that the peak strength and elastic modulus present an obvious “U-shaped” variation with the bedding dip angle, reaching the minimum values in the range of 45–60°, and the corresponding failure mode is mainly sliding failure along the bedding plane. The mechanical parameters obtained for slate are input into FLAC3D 6.0 software to simulate a triaxial compressive test of slate, and the calculation results are used to verify the accuracy of the parameters obtained from the tests. Based on these parameters, the foundation pit engineering in the background is simulated in order to analyze the deformation characteristics of the pit under different inclination angles. The simulation results indicate that the foundation pit deformation has significant asymmetry, with larger settlement on the dip side and greater horizontal displacement of the piles. The research findings of this paper can provide a reference for the design and construction of similar slate foundation pit projects. Full article

This study presents a multi-resolution and multi-temporal remote sensing approach to assess human-induced changes in cultural landscapes, with a focus on the archaeological site of Amrit (Syria) within the MapDam project. By integrating satellite archives (KH, Landsat series, NASADEM) with ancillary geospatial data (OpenStreetMap) and advanced analytical methods, four decades (1984–2024) of land-use/land-cover (LULC) change and shoreline dynamics were reconstructed. Machine learning classification (Random Forest) achieved high accuracy (Test Accuracy = 0.94; Kappa = 0.89), enabling robust LULC mapping, while predictive modelling of urban expansion, calibrated through a Gradient Boosting Machine, attained a Figure of Merit of 0.157, confirming strong predictive reliability. The results reveal path-dependent urban growth concentrated on low-slope terrains (≤5°) and consistent with proximity to infrastructure, alongside significant shoreline regression after 1974. A Business-as-Usual projection for 2024–2034 estimates 8.676 ha of new anthropisation, predominantly along accessible plains and peri-urban fringes. Beyond quantitative outcomes, this study demonstrates the replicability and scalability of open-source, data-driven workflows using Google Earth Engine and Python 3.14, making them applicable to other high-risk heritage contexts. This transparent methodology is particularly critical in conflict zones or in regions where cultural assets are neglected due to economic constraints, political agendas, or governance limitations, offering a powerful tool to document and safeguard endangered archaeological landscapes. Full article

Background/Objectives: Transportation is a critical social determinant of health with direct impacts on healthcare access and utilization. This study examines transportation challenges faced by low-income individuals with chronic conditions who participated in the Food as Medicine (FAM) program offered by their primary care provider and explores the strategies they employ to overcome those challenges, particularly during the COVID-19 pandemic. Methods: We conducted semi-structured interviews with 36 FAM participants from Grady Health System in Atlanta, Georgia between May 2022 and October 2023. Interviews explored their ability to access routine care, FAM, and healthy food as prescribed by their physicians and nutritionists, as well as how the COVID-19 pandemic affected their transportation challenges and solutions. Results: Participants reported various transportation barriers including long wait times, delays, cost burdens, unreliable services, and coordination failures, which contributed to missing doctor appointments and FAM attendance. To overcome those challenges, participants planned trips in advance, used multiple transportation options, relied on social networks, or reduced and sometimes forwent trips. The COVID-19 pandemic limited their accessibility to healthcare, FAM, and healthy food options by reducing business hours and disrupting transportation services. Alternatives such as telemedicine and online ordering were less utilized due to distrust, dissatisfaction, and limited digital literacy. Conclusions: Transportation barriers can substantially restrict healthcare and food access for low-income individuals managing chronic conditions, especially during public crises that may lead to service disruptions. Transportation assistance that accommodates individuals’ financial circumstances and health conditions, implemented through collaborative efforts of healthcare institutions, transportation agencies, and governments, is essential to facilitating chronic disease management and reducing health disparities. Full article

The rapid integration of emerging technologies into organizational processes has fundamentally redefined the role of strategic human resource management (SHRM). This paper explores how digital innovations—such as artificial intelligence (AI), robotic process automation (RPA), blockchain, and immersive technologies—are reshaping the workforce and transforming the way organizations attract, develop, and retain talent. In the context of the digital era, human capital is no longer a passive input but a strategic enabler of sustainable competitive advantage. The purpose of the study is to analyze how SHRM practices must evolve to align with technology-driven organizational models, combining insights from a systematic literature review, institutional reports, and illustrative corporate cases. Findings indicate that agility, continuous reskilling, ethical AI governance, and employee well-being are critical levers for sustainable advantage. Comparative tables highlight differences between traditional HRM and SHRM in the digital era, while case studies (IBM, Walmart, Unilever, and UiPath) demonstrate the strategic value of predictive analytics, diversity and inclusion programs, virtual training, and people analytics. By proposing a conceptual model that links emerging technologies, SHRM, and competitiveness, the paper contributes to current debates on the transformation of work and organizational resilience. The study offers practical implications for HR leaders, policymakers, and academics navigating digital transformation while reinforcing human-centric performance and sustainability. Full article

A design science framework integrates sustainability into business development across sectors. The framework embeds sustainability, reflected in environmental, social, and governance (ESG) dimensions, within a structured process that links drivers, evaluation components, and outcome indicators. Six principles guide its structure: clarity, integration, adaptability, stakeholder engagement, performance feedback, and scoring consistency. Researchers applied the framework in energy, engineering, and agribusiness cases. Case results show how the framework improves opportunity selection, identifies capability gaps, strengthens prioritization, and structures stakeholder input without adding complexity. Findings confirm that incorporating sustainability factors during the initial stage of business development changes decision patterns, aligns projects with long-term goals, and increases transparency in portfolio planning. This design science approach moves sustainability and its ESG dimensions from a reporting concern to a central element of strategic evaluation and growth planning. Organizations gain a practical structure to align opportunity development with resilience, learning capacity, and sustainability outcomes. In addition, the framework provides a foundation for adaptation, digital tool development, and longitudinal feedback cycles as firms integrate sustainability and ESG dimensions within uncertain policy, market, and stakeholder environments. Full article

Smart Tourism Destinations (DTIs) represent innovative places established on the basis of an infrastructure of advanced technology, whose objective is to promote accessible, sustainable development for tourist regions to enrich tourist’s experiences and inhabitants’ quality of life. Therefore, the main objective of this research is to verify whether the phenomenon indicators of existing smart tourist destinations fit within all dimensions of a smart tourist destination. For data collection, the bibliographic survey method was used in renowned databases. Data analysis comprises two approaches, bibliometric and content analysis, applied sequentially. The results of the bibliometric analysis identify three main pillars in the current perspectives on DTIs: Management and Tourism Experience, Technology, and Sustainability, in addition, it revealed a duality between approaches from the Far East and Western Europe. The content analysis culminates in the proposition of two theoretical-conceptual models for the dimensions and indicators of DTIs, encompassing elements: Information and Communication Technologies (TICs), Governance, Innovation, Accessibility, Performance, Mobility and Infrastructure, as well as Segmented Sustainability in its economic, social, and environmental dimensions. However, the analysis highlights the lack of consensus among studies, especially DTI indicators. The results of the research highlight the insufficiency of these indicators for a comprehensive assessment, notably in the environmental dimension of sustainability. Full article

Real-time monitoring of atmospheric emissions is critical for ensuring transparency, compliance, and rapid response to environmental risks. However, traditional systems often suffer from latency and a lack of verifiable data integrity. This paper presents AABF+, an adaptive packetization and microblock model built on a permissioned blockchain that supports intelligent emissions monitoring. The proposed system dynamically groups sensor readings into microblocks and commits them using Byzantine Fault Tolerant (BFT) consensus, enabling both high throughput and verifiable traceability. Unlike fixed-window blockchains, AABF+ adapts the microblock size and time window based on incoming data rates, balancing responsiveness and reliability. The model was implemented and experimentally evaluated in an edge-class 1 GbE testbed under real MRV (Measurement–Reporting–Verification) conditions. Results show that AABF+ achieves a median end-to-end latency of 0.96 s for single-record transactions and 3.07 s for 1000-record batches, while maintaining strong cryptographic verification of all entries. These findings demonstrate that AABF+ provides second-level data freshness with verifiable provenance, offering a practical foundation for digital environmental governance and regulatory compliance in Industry 4.0 ecosystems. Full article

Although corporate tax avoidance strategies may increase internal funding that supports innovation, they can also undermine it by weakening governance and encouraging short-term financial objectives. However, the overall impact remains theoretically contested, with insufficient empirical research available. This study examines the relationship between corporate tax avoidance and innovation, focusing on the moderating role of environmental, social, and governance (ESG) practices. Using a panel dataset of 12,408 firm-year observations of South Korean listed companies from 2014 to 2023, Tobit regression analyses reveal a statistically significant negative association between tax avoidance and innovation. Notably, this negative relationship is significantly mitigated in ESG-engaged firms, particularly those with stronger ESG performance. Further analysis indicates that these moderating effects are driven primarily by the social and governance domains. These findings suggest that ESG practices can offset the detrimental effects of tax avoidance by strengthening governance and stakeholder alignment. This study underscores the importance of integrating ESG principles into corporate tax strategies to support long-term innovation and sustainable corporate development. Full article

New quality agricultural productivity is essential for advancing agricultural modernization, consolidating and expanding achievements in poverty alleviation, and driving rural revitalization. However, leveraging this productivity to facilitate industrial upgrading and support the transition of smallholder farmers remains challenging. This paper constructs a tripartite evolutionary game model involving the government, agricultural enterprises, and farmers within the policy framework of new quality agricultural productivity. By applying evolutionary game theory, we analyze the strategic interactions among policy implementation, farmer welfare, and the development of new quality agricultural productivity. Equilibrium analysis reveals that the government, as a regulatory actor, should provide appropriate subsidies to agricultural enterprises and farmers, undertake initial infrastructure improvements, diversify subsidy instruments, establish special incentives for agricultural technology innovation, and increase investment in cultivating new agricultural talent. Agricultural enterprises, as dynamic agents, should adopt proactive and systematic transformation strategies. Furthermore, they need to strengthen benefit-linked mechanisms with farmers to ensure sustained collaboration. Full article

The mechanical performance of cast iron is strongly governed by the morphology of its graphite phase, yet establishing a quantitative link between microstructure and macroscopic properties remains a challenge. In this study, a three-dimensional finite element method (FEM)-based micromechanical framework is proposed to analyze and predict the mechanical behavior of cast iron with representative graphite morphologies, spheroidal and flake graphite. Realistic representative volume elements (RVEs) are reconstructed based on experimental microstructural characterization and literature-based X-ray computed tomography data, ensuring geometric fidelity and statistical representativeness. Cohesive zone modeling (CZM) is implemented at the graphite/matrix interface and within the graphite phase to simulate interfacial debonding and brittle fracture, respectively. Full-field simulations of plastic strain and stress evolution under uniaxial tensile loading reveal that spheroidal graphite promotes uniform deformation, delayed damage initiation, and enhanced ductility through effective stress distribution and progressive plastic flow. In contrast, flake graphite induces severe stress concentration at sharp tips, leading to early microcrack nucleation and rapid crack propagation along the flake planes, resulting in brittle-like failure. The simulated stress–strain responses and failure modes are consistent with experimental observations, validating the predictive capability of the model. This work establishes a microstructure–property relationship in multiphase alloys through a physics-informed computational approach, demonstrating the potential of FEM-based modeling as a powerful tool for performance prediction and microstructure-guided design of cast iron and other heterogeneous materials. Full article

As the transformative influence of novel technologies sweeps across industries, organisations are called upon to position their staff in the equally dynamic operational environment, which includes embedding technical and legal communication skills in their training programs. For many organisations, internal and external communication of data modelling and related concepts, reporting, and monitoring still pose major challenges. The aim of this research is to develop an effective data training framework for learners with or without mathematical or computational maturity. It also addresses subtle aspects such as the legal and ethical implications of dealing with organisational data. Data was collected from a training course in Python, delivered to government employees in different departments in the United Arab Emirates (UAE). A structured questionnaire was designed to measure the effectiveness of the training program using Python, from the employees’ perspective, based on three key attributes: their personal characteristics, professional characteristics, and technical knowledge. A descriptive analysis of aggregations, deviations, and proportions was used to describe the data attributes gathered for the study. The main findings revealed a huge knowledge gap across disciplines regarding the core skills of big data analytics. In addition, the findings highlighted that previous knowledge about statistical methods of data analysis along with prior programming knowledge made it easier for employees to gain skills in data analytics. While the results of this study showed that their training program was beneficial for the vast majority of participants, responses from the survey indicate that providing a solid knowledge of technical communication, legal and ethical aspects would offer significant insights into the big data analytics field. Based on the findings, we make recommendations for adapting conventional data analytics approaches to align with the complexity or the attainment of the non-orthogonal United Nations Sustainable Development Goals (SDG). Associations of selected responses from the survey with some of the key data attributes indicate that the research highlights vital roles that technology and data-driven skills will play in ensuring a more prosperous and sustainable future for all. Full article

In eutrophic shallow lakes, dissolved oxygen (DO) exhibits significant temporal variations, regulated by the combined effects of photosynthesis and water temperature (WT). High-frequency monitoring enables a detailed capture of DO diel cycles, providing a more comprehensive understanding of the dynamic changes within lake ecosystems. This study involved high-frequency (10 min intervals) in situ monitoring of DO over a three-year period (2020–2022) in the littoral zone of Taihu Lake, China. Random forest regression analysis identified WT, photosynthetically active radiation (PAR), and relative humidity (RH) as the three most influential variables governing DO dynamics. The relative importance of these factors varied seasonally (0.117–0.392), with PAR dominating in summer (0.383), whereas WT had the highest importance in other seasons (0.312–0.392). Cusum analysis further revealed that the DO-WT relationship changed from a dome-shaped pattern in spring, autumn, and winter to a bowl-shaped pattern in summer, indicating that thermal stratification intensified oxygen gradients. In addition, the majority of DO recovery occurred in the late afternoon during summer, suggesting that severe oxygen consumption delayed the daytime accumulation of DO. Our findings emphasize the critical roles of photosynthesis, respiration, and abiotic factors in shaping DO dynamics. This research enhances our understanding of DO fluctuations in eutrophic shallow lakes and provides valuable insights for ecosystem management, supporting the development of effective strategies to prevent and mitigate hypoxia. Full article

Background/Objectives: Sublingual vaccination offers a non-invasive route for inducing both systemic and mucosal immunity, yet the formulation properties that govern its success remain poorly defined. This study investigated the relationships among key formulation parameters for sublingual vaccines, such as viscosity, mucoadhesion, and mucosal residence, to understand their impact on in vivo immune responses in the sublingual delivery context. Methods: Ovalbumin (OVA)-based vaccine formulations containing cholera toxin B (CTB) adjuvant and mucoadhesive excipients such as hydroxypropyl methylcellulose (HPMC) or methylglycol chitosan (MGC), were evaluated for: (1) their respective rheological properties—characterized by viscosity and mucoadhesion parameters, as well as (2) in situ mucosal retention (assessed using Cy7-labeled formulations tracked by IVIS in vivo imaging system) and (3) in vivo immunogenicity via systemic (IgG) and mucosal (IgA) responses measured by ELISA, following sublingual administration to mice. Correlations between rheology, in situ/ex situ mucosal residence, and in vivo immune outcomes were determined. Results: Sublingual vaccine formulations containing HPMC exhibited the highest viscosity, mucoadhesion, and mucosal retention profiles, but paradoxically elicited the weakest systemic and mucosal antibody responses. In contrast, chitosan-based formulations enhanced immune responses even at reduced antigen and adjuvant doses, likely due to its permeation-enhancing and adjuvant effects. Correlation analyses revealed that while formulation viscosity and mucoadhesive strength were positively associated with mucosal retention, both rheological and retentive properties showed a significant inverse relationship with immunogenicity in the context of sublingual vaccine delivery. Conclusions: While viscosity and mucoadhesion are essential for in situ retention of sublingual vaccines, prolonged residence driven by excipient’s excessive rheological strength was found to reduce vaccine immunogenicity—likely due to restricted antigen release and mucosal uptake. Accordingly, HPMC appears suboptimal as a sublingual vaccine excipient, while chitosan shows promise for sublingual delivery as a permeation-enhancing adjuvant. These findings may shift the design paradigm for sublingual vaccine formulations, highlighting the need to balance mucosal retention with efficient antigen absorption for maximizing immune responses. Full article

Sandstone quarrying in Lekokoaneng contributes to both local and national economic development, yet it raises concerns about environmental degradation and community livelihoods. Using a mixed-methods design framed by the Sustainable Livelihood Framework (SLF) and the Sustainable Development Theory (SDT), 203 households were surveyed across five buffer zones (0–1000 m) around the formal quarry site in Lekokoaneng, Berea District, Lesotho. Quantitative data were analysed descriptively, while qualitative responses underwent thematic analysis and were transformed into quantifiable categories. Quarrying generated employment and small-business opportunities concentrated within 0–600 m of the site, alongside elevated reports of dust, soil degradation and water contamination that undermined agriculture and health. Households nearest the quarry reported the highest income benefits (e.g., 35% via employment) but also the greatest environmental burdens. Households furthest away reported fewer risks but also limited economic gain. Thematic analysis yielded four domains: Socio-Economic Empowerment, Livelihood Vulnerability, Health and Safety Risks, and Environmental Degradation and Control. Integrating SLF and SDT shows quarrying as a double-edged livelihood system with short-term financial gains that coincide with erosion of natural, human and social capitals. Targeted environmental safeguards, labour formalisation and community-inclusive governance are essential to realign quarrying with resilience and sustainability goals. Full article