Search Results (6,263)

The propagation characteristics of shear waves in granular sediments are usually used to assess the dynamic response and liquefaction potential of marine engineering foundations. However, the mesoscopic processes by which the excitation frequency influences the shear wave propagation and attenuation remain unclear. In this study, based on a triaxial bender element (BE) test model, the shear wave behavior in uniform spherical particles was simulated by the discrete element method (DEM). It revealed that the BE excites shear waves in a point source manner and that the propagation processes within a triaxial unit cell assembly follow exponential attenuation patterns. Near the vibration source (10–100 kHz), the attenuation law of spherical wave propagation is dominated by friction slip and geometric diffusion in particles. At 0.7–3.5 wavelengths, the shear waves progressively transition to plane waves, and the attenuation law is governed by boundary absorption and viscous damping. At 2.9–10 wavelengths, near-field effects diminish, and planar wave propagation stabilizes. Higher excitation frequencies enhance friction slip, boundary absorption, and viscous damping, leading to frequency-dependent attenuation. The granular system exhibits segmented filtering, with cutoff frequencies dependent on the receiver location but independent of the excitation frequency. Full article

Flood events have become more frequent as a result of seasonal changes, global warming, and changes in sea level. In terms of basin management, it is necessary to know the hydrodynamics of the basin in order to produce faster solutions in emergency action plans. The Filyos River is one of the two most important floodplains in the western Black Sea basin and has so far only been analyzed to a limited extent using modern hydrological and hydraulic models. In order to analyze the flood dynamics and determine the flood risks in the Filyos River. In this context, flood hydrographs, rainfall depths, peak flows, and excess water volumes were calculated for different return periods (2, 5, 10, 20, 50, and 100 years) using HEC-RAS, HEC-HMS, and Hyfran Plus software. The analyses showed that the rainfall depth and peak flow rate increased significantly as the return period increased. It was also observed that although the volume of precipitation increased, the amount of water converted into surface runoff remained limited due to infiltration and other losses. The results of the study contribute to the identification of high flood-risk areas in the Filyos River basin, the improvement of flood prevention infrastructure, and the development of sustainable water management policies. Analyses using modeling tools such as HEC-RAS and HEC-HMS provide a scientific basis to help local governments and decision makers strengthen flood prevention strategies, update risk maps, and make emergency response plans more effective while making flood scenarios more reliable. Full article

Water resources are a key constraint on sustainable development in arid regions, especially for agricultural production where water use is intensive. To assess the sustainability of agricultural water use in such environments, this study utilizes 2010–2020 agricultural data from the Turpan–Hami Basin and is among the first to integrate the water footprint (WF) theory with the DPSIR (driver–pressure–state–impact–response) model into a comprehensive framework for evaluating water resource sustainability in arid agricultural systems. The agricultural blue, green, and grey WF in the Turpan–Hami Basin were quantified for 2010–2020, followed by a sustainability assessment under the DPSIR framework using a comprehensive weighting method. The results showed a continuous increase in the WF, dominated by the blue WF (>60%), largely due to crops like cotton and grapes, intensifying regional water stress. Turpan experienced prolonged resource overload, while Hami exhibited slightly higher sustainability. DPSIR analysis revealed stronger policy responses in Turpan and significant ecological investments in Hami. Key influencing factors included the crop yield, WF modulus, per capita WF, and water quality shortage index. Overall, sustainability in the basin fluctuated between “Basically Sustainable (Level III)” and “Insufficiently Sustainable (Level IV)”, with slight improvement in 2020. The findings highlight the need for region-specific agricultural optimization, strengthened ecological governance, and improved water-saving strategies to enhance water use efficiency and sustainability in arid regions. Full article

Interorganizational risk management (IRM) in Canadian ports faces significant challenges due to the interconnected nature of operations and the interdependence of safety, security, environmental, organizational, and technological risks. Existing siloed risk management frameworks often fail to capture these dynamic interrelations, underscoring the need for a more integrated, systemic approach. This study introduces a Port Risk Control Structure (PRCS) designed specifically for Canadian Port Authorities (CPAs), based on the Systems-Theoretic Accident Model and Processes (STAMP). The PRCS maps control actions, feedback loops, and stakeholder roles across international, national, and local levels to better reflect the layered nature of port governance. The model aims to clarify the roles of key actors, such as the International Maritime Organization, Transport Canada, and local port stakeholders, and is designed to facilitate more structured risk identification, communication, and coordination across organizational levels. Although the model has not yet been empirically validated, its design suggests strong potential for scalability and adaptability across diverse port contexts. This research contributes to IRM literature by illustrating how STAMP principles can be operationalized within port systems. Future research will focus on integrating a taxonomy of IRM challenges to refine control structures and feedback mechanisms in response to evolving risks. Full article

Microplastic (MPs) pollution has emerged as a critical environmental issue due to its persistent accumulation in ecosystems, posing risks to aquatic life, food safety, and human health. In this study, magnetic Fe₃O₄ nanoparticles functionalized with citric acid (Fe₃O₄@AC) were used to remove high-density polyethylene (HDPE), low-density polyethylene (LDPE), and polypropylene (PP) MPs from an aqueous medium. Fe₃O₄@AC was synthesized via the coprecipitation method and characterized by morphology (SEM), crystalline phases (XRD), chemical aspects (FTIR), and surface area (nitrogen sorption isotherms). The MPs removal efficiency of Fe₃O₄@AC was evaluated based on the initial concentration, contact time, and pH. The adsorption isotherm and kinetics data were best described by the Sips and pseudo-second-order models, respectively. Fe₃O₄@AC removed 80% of the MPs at a pH of 6. Based on experimental observations (zeta potential, porosity, and SEM) and theoretical insights, it was concluded that hydrogen bonding, pore filling, and van der Waals forces governed the adsorption mechanism. Reusability tests showed that Fe₃O₄@AC could be reused up to five times, with a removal efficiency above 50%. These findings suggest that Fe₃O₄@AC is a sustainable and promising material for the efficient removal of microplastics from wastewater, offering a reusable and low-impact alternative that contributes to environmentally responsible wastewater treatment strategies. Full article

Public safety personnel (PSP) are known to experience difficult and demanding occupational environments, which were further complicated by the COVID-19 crisis. While public safety research typically focuses on the impact of operational stressors on PSP functioning and wellbeing, relatively less is known about the types and impacts of organizational stressors and how all these affect social wellbeing during the pandemic. The current study surveyed Canadian firefighters (n = 123), paramedics (n = 246), and public safety communicators (n = 48) that continued to serve the public over the course of the pandemic. Participants responded to two open-ended survey questions about how COVID-19 affected their lives at work and home. Using an inductive thematic analysis approach, responses were coded to identify emergent, data-driven themes while drawing on existing theory for analysis. Across occupational groups, qualitative analyses revealed that the public safety measures imposed by the COVID-19 pandemic further exacerbated existing operational and organizational strains, including increased exposure to distressing calls, absenteeism and coping with alcohol, and a lack of support from management. Participants also identified financial strain and housing insecurity as stressors, as well as frustration and helplessness at others’ non-compliance with public health advisories and protocols. Communication surrounding the rationale behind government decision-making, the efficacy of serology tests, and rates of infection were also identified. Together, these findings offer a nuanced understanding of the interplay among operational, organizational, and social stressors experienced by Canadian PSP during the COVID-19 pandemic, illuminating their impact on mental health and wellbeing, and identifying targeted areas of focus for future planning and meaningful intervention to support PSP wellness. Full article

The uncontrolled urbanization of Brazilian cities accentuates the imbalance between population demands and urban space planning. The integrated management of human and technological resources constitutes a fundamental governance strategy for the proposition of sustainable and effective responses to the challenges faced by cities. To generate references to public management, the objective of this research was to develop a management tool to verify the maturity level of Brazilian cities for smart city actions. A performance measurement system (PMS) organized smart city actions into 11 thematic areas, quantitatively measuring smart city actions in a down–top structure since the indicators and metrics are described in a standardized scale to obtain the general maturity index (GMI). The PMS was implemented in the city of Santa Maria/Brazil, where its GMI equal to 43.72% indicated a currently intermediate maturity level of smart city actions, mainly related to the low performance in the thematic areas of mobility, coexistence and reciprocity, and security and protection. To improve the current performance, five incremental actions were proposed, contemplating the key performance indicators “Public roads”, “Multipurpose lanes”, “Public accessibility”, “Accessibility signage”, and “Monitoring”, projecting a GMI equal to 49.75% and 55.78%, respectively, for an intermediate and an advanced maturity level scenario. Full article

In the fast-growing new energy vehicle (NEV) industry, selecting an appropriate technological innovation strategy is vital for enterprises to achieve a competitive market position while effectively coordinating their resources to align with their technical capabilities. This paper integrates ambidextrous innovation theory and the resource-based view to propose a configurational model that examines how the synergy between technological innovation and resources influences NEV firm performance. Using regression analysis and qualitative comparative analysis (QCA) for 52 listed Chinese NEV companies, this study uncovered multiple growth paths and mechanisms. The findings include the following: (1) No single factor was a necessary condition for performance, but effective combinations of innovation strategies and resource elements led to multiple success paths. (2) Government subsidies and R&D investment emerged as key drivers of performance. (3) Four distinct configuration paths were identified, with variations across firms with different resource bases. (4) In response to reduced government subsidies, NEV firms must shift from policy-driven strategies to resource- and market-driven innovation approaches. These insights provide strategic guidance for NEV enterprises in selecting innovation strategies suited to their unique resource bases in the evolving post-subsidy market environment. Full article

Taraxacum, a genus in the Asteraceae family, is widely distributed across temperate regions and plays a vital ecological role by providing nectar and pollen to pollinators during the early flowering season. Floral nectar is a key reward that plants use to attract pollinators, and its production is tightly regulated by genes such as SWEET sugar transporters and CELL WALL INVERTASE (CWIN), which govern sugar efflux and hydrolysis. Despite their ecological importance, the molecular mechanisms underlying nectar secretion in Taraxacum remain poorly understood. In this study, we performed RNA sequencing of flower tissues from five Taraxacum species—T. coreanum, T. monogolicum, T. ohwianum, T. hallaisanense, and T. officinale—to investigate the expression of nectar-related genes. De novo transcriptome assembly revealed that T. coreanum had the highest unigene count (74,689), followed by T. monogolicum (69,234), T. ohwianum (64,296), T. hallaisanense (59,599), and T. officinale (58,924). Functional annotation and phylogenetic analyses identified 17 putative SWEET and 18 CWIN genes across the five species. Differential gene expression analysis highlighted tarSWEET9 and tarCWIN4 as consistently up-regulated during the flowering stage. Quantitative PCR in T. officinale further validated that tarSWEET9, tarCWIN4, tarCWIN6, and tarSPAS2 show significant expression during floral development but are down-regulated after pollination. These genes are likely central to the regulation of nectar secretion in response to pollination cues. Our findings suggest that T. officinale may have evolved to have an efficient, pollinator-responsive nectar secretion system, contributing to its global adaptability. This study sheds light on how pollinator interactions influence gene expression patterns and may drive evolutionary divergence among Taraxacum species. Full article

Biosecurity is vital to Australia’s efforts to prevent and respond to pests and diseases. Here, we report on testing suspected illegal goods (SIGs) as part of an active Australian biosecurity response in Sydney. The Australian Government, Department of Agriculture, Fisheries and Forestry detected and secured consignments containing tuber products of unknown biosecurity risk and origin. Swab samples were collected from vacuum-sealed yam products, organic packing material (background negative controls), and field negative controls to assess possible cross-contamination from the storage facility. DNA from all samples was analysed using high-throughput metabarcoding targeting the Internal Transcribed Spacer 2 (ITS2) and the chloroplast trnL (UAA) P6 Loop gene regions by two independent teams in Australia. A plant community profile comprising Australian native species and other non-native established species would support the notion of produce being harvested and/or packaged domestically, while their absence would suggest foreign production. Of the 5,764,942 total reads produced, the bioinformatic analysis generated 5,181,530 amplicon sequencing variants employed for species identification. Twenty plant taxa were identified via ITS2 and 15 via trnL, corresponding to worldwide distributed plants, non-native species established in Australia, or species not recorded in Australia. No Australian endemic species were detected. The absence of common Australian native plants, combined with the presence of species not known to occur in Australia, provided strong evidence that the suspect tuber products were illegally imported. Full article

Addressing the escalating complexity of global sustainability challenges requires interventions that are not only technically effective but also cognitively and philosophically grounded. While the leverage points perspective has provided a useful framework for understanding systemic change, it can be enhanced through more operational coherence and cultural pluralism. This paper introduces the Deep and Shallow Sustainability Intervention (DSSI) framework, a novel conceptual model that integrates Taoist philosophical insights with contemporary systems thinking and the leverage points literature. Structured across five interconnected Taoist-inspired domains and ten leverage points, the framework extends and enriches Meadows’ leverage point theory by integrating pre-paradigmatic meta-cognitions, systemic momentum, and context-sensitive action. It emphasizes that sustainable transitions require the dynamic interplay between foundational source-code shifts and operational implementation. This framework contributes to the growing field of transformative sustainability science by (1) embedding non-Western epistemologies into systems transformation theory, (2) offering a structured yet flexible model for multi-level intervention design, and (3) enabling transdisciplinary dialogue between philosophy, paradigmatic shift, meta-systemic logic, governance, and practice. Preliminary applications in European rural transition contexts suggest its potential to enhance context-sensitive action and value-aligned systems innovation. The DSSI framework thus offers a timely and integrative approach for guiding long-term, systemic, and culturally responsive sustainability transitions. Full article

This study elucidates the dynamic tribo-mechanical response of laser-cladded FeNiCr-B₄C metal matrix composite (MMC) coatings on AISI 1040 steel substrate, unraveling the intricate interplay between microstructural features and phase transformations. A multi-faceted approach, employing high-resolution scanning electron microscopy (SEM) and advanced X-ray diffraction/Raman spectroscopy techniques, provided a comprehensive characterization of the coatings’ behavior under mechanical and scratch testing, shedding light on the mechanisms governing their wear resistance. Specifically, microstructural analysis revealed uniform coatings with a columnar structure and controlled defect density, showcasing an average thickness of 250 ± 20 μm and a transition zone of 80 ± 10 μm. X-ray diffraction and Raman spectroscopy confirmed the presence of α-Fe (Im-3m), γ-FeNiCr (Fm-3m), Fe₂B (I-42m), and B₄C (R-3m) phases, highlighting the successful incorporation of B₄C reinforcement. The addition of 5 and 7 wt.% B₄C significantly increased microhardness, showing enhancements up to 201% compared to the B₄C-free FeNiCr coating and up to 351% relative to the AISI 1040 steel substrate, respectively. Boron carbide addition promoted a synergistic strengthening effect between the in situ formed Fe₂B and the retained B₄C phases. Furthermore, scratch test analysis clarified improved wear resistance, excellent adhesion, and a tailored hardness gradient. These findings demonstrated that optimized short-pulsed laser cladding, combined with moderate B₄C reinforcement, is a promising route for creating robust, high-strength FeNiCr-B₄C MMC coatings suitable for demanding engineering applications. Full article

As public institutions increasingly adopt AI-driven virtual assistants to support transparency and citizen engagement, the need for explainable, accurate, and context-aware language systems becomes vital. While traditional retrieval-augmented generation (RAG) frameworks effectively integrate external knowledge into Large Language Models (LLMs), their reliance on flat, unstructured document retrieval limits multi-hop reasoning and interpretability, especially with complex, structured e-government datasets. This study introduces a modular, extensible, multi-agent graph retrieval-augmented generation (GraphRAG) framework designed to enhance policy-focused question answering. This research aims to provide an overview of hybrid multi-agent GraphRAG architecture designed for operational deployment in e-government settings to support explainable AI systems. The study focuses on how the hybrid integration of standard RAG, embedding-based retrieval, real-time web search, and LLM-generated structured Graphs can optimize knowledge discovery from public e-government data, thereby reinforcing factual grounding, reducing hallucinations, and enhancing the quality of complex responses. To validate the proposed approach, we implement and evaluate the framework using the European Commission’s Press Corner as a data source, constructing graph-based knowledge representations and embeddings, and incorporating web search. This work establishes a reproducible blueprint for deploying AI systems in e-government that require structured reasoning in comprehensive and factually accurate question answering. Full article

One significant digital initiative that is changing Greece’s tax environment is the myDATA platform. The platform, which is a component of the wider digital governance agenda, provides significant added value to enterprises and the tax administration, despite the challenges of adaption. Despite the positive response, we find that the development of the platform could have been carried out quickly and at a significantly lower cost and could have been able to cope much faster with the rapid and necessary changes that the platform will have to comply with. For these reasons, development in WordPress would be considered essential as this CMS platform guarantees a fast and developer-friendly environment. In this publication, as a contribution, we provide all the necessary information to develop a myDATA-like platform in a fast, economical and functional way using the WordPress CMS. Our contribution also contains the analysis of the minimum necessary amount of services of the myDATA platform in order to perform its basic functionalities, the description of the according database relational model, which must be implemented in order to provide the same functionality with the myDATA platform, and the analysis of available methods to quickly create the necessary forms and services. In addition, we study how to develop Artificial Intelligence mechanisms with a success rate reaching up to 90% for automatic tax violation detection algorithms. Full article

Induction quenching is critical for high-strength bulb flat steel, yet the influence of the heating temperature on mechanical property uniformity across sections remains underexplored. This study systematically investigates the effect of the induction heating temperature on mechanical property uniformity, prior austenite grain size, and microstructural evolution in bulb flat steel. Experimental results reveal that increasing the induction heating temperature from 845 °C to 1045 °C induces distinct mechanical responses: the yield strength disparity between the bulb and flat sections decreases by 93% (from 94 MPa), significantly improving sectional uniformity. Microstructural analysis indicates that prior austenite grain size coarsens with higher induction heating temperatures. The quenched microstructure comprises martensite and bainite in the bulb core, while the flat section is entirely martensitic. The yield strength differential between the bulb and flat sections is governed by temperature-dependent strengthening mechanisms: dislocation strengthening dominates at 845 °C~985 °C, with the bulb region exhibiting higher strength due to increased dislocation density, while grain boundary strengthening prevails at 1045 °C, where the flat region benefits from finer grains. Full article