Search Results (29,337)

The rapid increase of electric mobility is challenging the deployment design and operation of electric vehicle charging infrastructure in a scalable, sustainable, operationally reliable, and regulation-compliant manner. Although advances in both digitization and artificial intelligence in recent years have made smarter charging solutions possible, today’s approaches tend to concentrate on individual technical parts without considering holistic views. This paper introduces an AI-driven integrated management model for sustainable EV charging infrastructures, composed of four interconnected layers, namely, Eco-Design, Digital Tools, Risk Management, and Governance. In particular, each layer focuses on specific aspects of functionality, including environmentally friendly design decisions, digital monitoring capabilities, proactive risk reduction, and strategic coordination. Compared with existing approaches that address isolated technical or operational aspects, the proposed model provides an integrated, multi-layer architecture that unifies eco-design, digital intelligence, risk management and governance, offering a more holistic and scalable foundation for sustainable EV charging infrastructures. It represents the conceptual output of a structured integration of existing technologies, design principles and governance needs. Considering that fragmented, solution-specific advances are reduced by including interdependencies between layers, the model allows us to better integrate technical operations, resilience mechanisms and sustainability goals. The model is theoretical and offers a scalable point of reference for researchers, as well as infrastructure operators and politicians. Full article

Currently, a standardized process reference model specifically tailored for the business continuity management system (BCMS) is absent. Moreover, BCMS processes have not been a primary focus of ongoing research endeavors. This paper aims to fill this research gap by presenting findings from a process mapping study concerning BCMS processes within the most prominent and widely acknowledged standards for business continuity management, alongside insights gleaned from expert interviews. The authors propose a collection of BCMS processes that should comprise a BCMS process reference model intended for implementation at a maturity level tailored to individual organizational needs. It aims to strengthen the resilience of organizations to cyber threats and to optimize the processes for effective management within the disaster management cycle. The study identifies and maps the necessary processes required to build a comprehensive BCMS model. These processes include, among others, risk assessment, business impact analysis, the development of BC strategies and solutions, the creation of BC plans and procedures, incident and emergency management, and periodic reviews and exercises. The relevance of these processes was validated through expert interviews, making a clear distinction between core, management, and support processes. Full article

Ensuring the structural reliability of power transmission networks is a fundamental prerequisite for the stable operation of modern energy systems. To address the challenges posed by complex weather interference and the small scale of insulator defects during power line inspections, this paper proposes LID-YOLO, a lightweight insulator defect detection network. First, to mitigate image feature degradation caused by weather interference, we design the C3k2-CDGC module. By leveraging the input-adaptive characteristics of dynamic convolution and the spatial preservation properties of coordinate attention, this module enhances feature extraction capabilities and robustness in complex weather scenarios. Second, to address the detection challenges arising from the significant scale disparity between insulators and defects, we propose Detect-LSEAM, a detection head featuring an asymmetric decoupled architecture. This design facilitates multi-scale feature fusion while minimizing computational redundancy. Subsequently, we develop the NWD-MPDIoU hybrid loss function to balance the weights between distribution metrics and geometric constraints dynamically. This effectively mitigates gradient instability arising from boundary ambiguity and the minute size of insulator defects. Finally, we construct a synthetic multi-weather condition insulator defect dataset for training and validation. Compared to the baseline, LID-YOLO improves precision, recall, and mAP@0.5 by 1.7%, 3.6%, and 4.2%, respectively. With only 2.76 M parameters and 6.2 G FLOPs, it effectively maintains the lightweight advantage of the baseline, achieving an optimal balance between detection accuracy and computational efficiency for insulator inspections under complex weather conditions. This lightweight and robust framework provides a reliable algorithmic foundation for automated grid monitoring, supporting the continuous and resilient operation of modern energy systems. Full article

Heterogeneity at the grain scale strongly influences hydraulic fracturing in crystalline rock; however, systematic studies quantifying its impacts on the evolution of injection pressure and crack propagation remain limited. To address this gap, we employ a hydro-mechanical phase-field model incorporating Voronoi-based microstructures to systematically quantify the effects of grain-scale heterogeneity on hydraulic fracturing. Two numerical experimental programs are designed to examine the effects of (i) mean grain size and (ii) mineral distribution under different axial stresses. The simulations reveal a close coupling between injection pressure and crack-length evolution, and both responses are strongly governed by grain-scale heterogeneity. When the fracture enters weak minerals, it advances rapidly and pressure drops; when it encounters on strong minerals, growth slows or arrests and pressure builds until a threshold triggers the next advance. Moreover, peak pressure statistics further indicate that mineral distribution dominates the response scatter, while axial stress plays a secondary role. Specifically, the mean peak pressures at 0 and 10 MPa are similar (about 14.31 and 14.21 MPa), whereas rearranging minerals within the same Voronoi tessellation changes peak pressure by more than 4 MPa. Higher peaks occur when strong minerals lie ahead of the initial crack tip, increasing resistance to initiation and early growth. Finally, the stress state modulates fracture trajectories: under low axial stress, fractures preferentially follow mineral boundaries, whereas higher axial stress strengthens macroscopic stress guidance and shifts the path toward a direction closer to being perpendicular to the maximum principal stress. This trend is consistent with energy minimization, since interface detouring under high axial stress incurs a larger elastic free energy penalty. Full article

Effective oral interventions for alcohol-induced metabolic stress and liver injury remain limited. Pre-absorptive gastrointestinal alcohol handling is gaining interest as a non-pharmacological strategy to reduce hepatic burden. In this study, we developed a formulation-integrated, food-compatible lyophilized recombinant whole-cell catalyst based on Escherichia coli Nissle 1917 engineered to express alcohol dehydrogenase and acetaldehyde dehydrogenase. Rather than focusing exclusively on strain-level genetic modification, the engineered cells were protected by lyophilization combined with a food-grade chitosan–alginate layer-by-layer coating, forming an artificial cell wall designed to enhance survivability during oral delivery. The formulation resisted simulated gastric acid, sodium taurocholate, and ethanol, retained enzymatic activity after storage, and demonstrated formulation stability. In alcohol-exposed mice, oral administration reduced blood ethanol and acetaldehyde levels, improved liver biochemical parameters, attenuated hepatic steatosis, and partially restored oxidative stress indicators. Integrated multi-omics analyses indicated coordinated gut-associated metabolic and inflammatory responses to alcohol and intervention, rather than a single dominant pathway. These findings provide hypothesis-generating evidence; causality remains to be established. Overall, this study demonstrates a proof-of-concept, food-compatible lyophilized recombinant whole-cell catalyst that integrates enzymatic function with formulation stability and gastrointestinal resilience, highlighting an applied, food-compatible microbial framework for exploring alcohol-related metabolic stress. Full article

The effects of reproductive technologies, namely, artificial insemination (AI) and multiple ovulation embryo transfer (MOET), on the production, health, and longevity of Holstein–Friesian cows were evaluated. Data were obtained from the time period between 2017 and 2024 on a Hungarian dairy farm and consisted of 1783 cows (1544 AI and 239 MOET). Deep-frozen semen from identical bulls was used for both the AI and MOET groups. Disease incidence, productive life, and early-lactation milk production phenotypes were collected in these cows. MOET cows demonstrated significantly higher milk yield during the first 100 days of lactation but had a 43.9% greater risk of culling compared with AI cows (p < 0.05). Metabolic and reproductive disorders were the most common reasons for culling cows, with increased frequency of health issues correlating with higher culling risk ratios (p < 0.05). While MOET cows showed lower incidences of metabolic disorders, reproductive problems, and mastitis, their shorter productive lifespan likely limited overall disease exposure. Nevertheless, when MOET cows experienced illness, the impact was more severe, particularly in relation to metabolic issues (p < 0.05). These findings highlight trade-offs between improved genetic potential and health resilience in MOET-derived cows. Despite their higher productivity, their management may require greater health vigilance. This study offers practical insights for dairy producers in selecting reproductive strategies to balance genetic gain, herd health, and longevity under intensive production systems. Full article

Beach nourishment is a widely adopted nature-based solution for coastal erosion; however, its design efficacy and morphodynamic resilience under extreme wave conditions remain inadequately quantified, posing challenges for coastal hazard assessment. This study integrates physical-model experiments and XBeach numerical simulations to investigate the hydrodynamic and morphodynamic behavior of nourished beaches subjected to typhoon-driven extreme wave conditions at a headland-bay beach on Meizhou Island, China. Physical-model experiments were conducted to examine shoreline response and sediment redistribution under extreme waves for three nourishment tests. XBeach simulations resolved wave-induced currents, water-level variations, and sediment transport processes, enabling continuous tracking of nearshore hydrodynamics and beach profile evolution for three nourishment tests during Typhoon Doksuri. Results indicate that nourishment geometry and groin configuration play a dominant role in wave breaking patterns, sediment transport pathways and erosion–deposition distributions. Groin positions strongly influence alongshore sediment transport. Relocating the groin to an accretional zone reduces lee-side erosion and promotes a more stable shoreline. Steeper nourishment foreshore slopes promote offshore wave shoaling and breaking, enhancing fast wave-energy dissipation, shifting erosion seaward and limiting landward erosion extent. Consistent responses from both experimental and numerical results demonstrate that nourishment stability under extreme wave conditions is better characterized by the combined effects of erosion extent, erosion length, erosion depth, erosion volume, and alongshore and cross-shore sediment redistribution. The integrated physical–numerical approach provides a practical framework for assessing beach nourishment stability during coastal hazard events and offers guidance for the design and evaluation of resilient beach nourishment in wave-dominated, typhoon-prone coastal regions. Full article

Mountain Social–Ecological Systems (MtSES) are global assets, providing essential ecosystem services to nearly half of humanity, yet they are disproportionately vulnerable to global change, experiencing “polytraps” of depopulation, poverty, and environmental degradation. Despite the inherent human dimension in sustainability, the social pillar remains conceptually chaotic, forming a highly fragmented “publication labyrinth”, and is often neglected in favor of more easily quantifiable environmental and economic metrics. These oversights leave mountain communities in a precarious state, underscoring an urgent need for robust, context-specific assessment tools. This paper addresses this critical gap by employing a two-step methodology: first, a literature review identifies prevailing social sustainability issues in mountain contexts; second, a comparative analysis evaluates prominent frameworks and indicator-based tools against these themes, using Ostrom’s multi-tier Social–Ecological Systems (SES) framework as the theoretical lens. Our findings reveal a persistent environmental bias in MtSES research and highlight the necessity for frameworks that integrate local knowledge, address power imbalances, and support bottom-up governance. A tool is proposed with indicators specifically for mountainous contexts. This study contributes to theory by offering a structured approach to unpack the elusive “social” in SES and to practice by providing a model and tool for developing actionable, context-sensitive social sustainability assessments, thereby fostering resilience and equitable development in vulnerable mountain regions. Ultimately, by operationalizing these social dimensions, this research provides a direct roadmap for achieving key United Nations Sustainable Development Goals in marginalized high-altitude contexts, particularly focusing on No Poverty (SDG 1), Good Health and Well-being (SDG 3), Reduced Inequalities (SDG 10), Sustainable Communities (SDG 11), and Peace, Justice, and Strong Institutions (SDG 16). Full article

The correct valuation of collateral supporting real estate loans has always been a key issue for the stability of the credit system. Substandard lending practices and the absence of uniform valuation approaches have historically contributed to the accumulation of non-performing loans. In recent years, several regulatory measures operating at both the European and national level have introduced principles, rules and procedures aimed at standardizing the valuation of properties pledged as collateral for credit exposures. These interventions seek to promote greater transparency, consistency, and prudence in property appraisals, thereby enhancing the soundness and resilience of the financial system. In January 2025, the updated Regulation (EU) 575/2013 came into force, incorporating the Basel III reform (also referred to as Basel 3+ or Basel IV). Among the innovations introduced, the concept of property value (PV) is particularly relevant, a prudential value that excludes expectations of price growth and considers the sustainability of the value over time in relation to the duration of the loan. PV is defined as a derived value with respect to market value (MV), determined by considering the main current and forward-looking risk factors that may arise during the life of the loan, including environmental, social and governance (ESG) risks, the intrinsic characteristics of the property and expectations regarding the economic cycle. This paper proposes a quantitative model for the determination of PV, applied to a practical case involving a residential property located in a medium-sized city in Italy’s Veneto region. The model adopts a deterministic and a probabilistic approach, the latter implemented through Monte Carlo simulation, which is indeed a generalization of the deterministic one. The model links the assessment of PV to the possible evolution of the property’s key parameters and the real estate cycle over the duration of the loan. It was tested under the assumption of a twenty-year mortgage originated in 2025 for the purchase of a residential property in Italy, considering two alternative locations: a suburban area and a city-centre area. The analysis conducted showed a substantially higher MV haircut for the suburban property compared with the central location. This difference reflects the fact that PV is less sensitive to real estate cycle fluctuations in more premium, central locations. Furthermore, the use of Monte Carlo simulation in the probabilistic approach enabled the calibration of the haircut according to a predefined confidence level, confirming the pattern observed in the deterministic framework. The combined evidence strengthens the empirical robustness of the model and highlights the importance of locational and cyclical dynamics in collateral valuation. Full article

Climate change and rapid urbanization are intensifying flood risks in China, particularly in regions with complex terrain and dense populations. Traditional risk assessment methods often lack the flexibility to handle uncertainties in multi-dimensional risk systems. This study proposes a probabilistic flood risk assessment framework integrating Monte Carlo simulation with a composite indicator system from the perspective of disaster system theory. Taking Hunan Province as a case study, we constructed a hierarchical indicator system encompassing environmental susceptibility, hazard intensity, exposure vulnerability, and mitigation capacity. The analytic hierarchy process (AHP) and coefficient of variation (CV) methods were combined for indicator weighting, and Monte Carlo simulation was employed to quantify uncertainties and classify risk levels. Results reveal significant spatial heterogeneity in flood risk across the province, with high-risk areas concentrated in regions exhibiting intense rainfall, dense river networks, and insufficient mitigation infrastructure. The study provides a transferable, data-driven approach for spatially explicit flood risk zoning, offering evidence-based insights for land-use planning, resilient infrastructure development, and sustainable flood governance. This research contributes to the integration of probabilistic modeling into land system science, supporting disaster risk reduction and climate adaptation strategies aligned with SDG 11. This study also provides policy-relevant insights for regional flood governance by supporting risk-informed land-use planning, targeted infrastructure investment, and adaptive flood management strategies, thereby contributing to more resilient and sustainable land system development under increasing climate uncertainty. Full article

In an era of rapid urbanisation and climate challenges, understanding how urban land patterns contribute to resilience is crucial for sustainable development. This theoretical review introduces a novel framework positing that greater heterogeneity in plot sizes and land uses enhances urban resilience by promoting the long-term preservation of built environments, multifunctional spaces, and socio-cultural adaptability. Drawing on urban morphology, assemblage theory, and resilience science, we argue that fragmented ownership in small-plot fabrics acts as a barrier to large-scale redevelopment, fostering diversity that buffers against shocks. Through comparative case studies of Venice (Italy), Tokyo (Japan), Hong Kong, Mexico City (Mexico), and York (UK), we illustrate how historical small-plot subdivisions have endured centuries, supporting ecological, economic, and social sustainability. The analysis reveals common patterns: ownership fragmentation preserves fine-grained urban forms, enabling adaptive reuse (exaptation) and inclusivity. The five case studies serve an illustrative function, demonstrating how the theoretical linkages between plot heterogeneity, institutional friction, incremental transformation, and long-term resilience outcomes can plausibly operate in real-world historic urban fabrics. This paper addresses a gap in the literature by synthesising plot-level heterogeneity with broader resilience outcomes, offering policy implications for protecting such fabrics amid global urbanisation pressures. The findings align with land system science, emphasising multifunctionality for regenerative urbanism. Full article

The transition towards sustainable energy systems is critically dependent on the reliable integration of renewable energy sources into the power grid. With the increasing penetration of renewable generation, hybrid grid-connected systems comprising grid-following (GFL) and grid-forming (GFM) converters have become essential in modern power stations. This paper addresses a key challenge to sustainable grid operation: maintaining stability and power delivery during grid faults. When faults cause voltage sags at the point of common coupling (PCC), different low-voltage ride-through (LVRT) strategies significantly impact both the voltage support capability and the active power transmission capacity, which are vital for a stable and resilient energy supply. To address this, the paper proposes a coordinated LVRT strategy for GFL/GFM converters that adapts to varying grid requirements, thereby promoting sustainable grid integration. First, the topology and control strategies of the hybrid system are briefly described. The conventional LVRT control strategies for both GFL and GFM converters are then improved. Based on the severity of the grid voltage sag, the converters’ active and reactive power output are adaptively adjusted. This dual-function approach not only effectively limits fault currents, protecting sensitive equipment, but also prioritizes the continuous transmission of active power, thereby minimizing the loss of renewable generation during faults and supporting grid stability. Subsequently, through an analysis of the voltage and active power characteristics of different LVRT modes, a coordinated strategy is designed. Unlike single-converter LVRT control, the proposed method flexibly selects and adjusts control modes to meet specific grid code requirements, ensuring robust voltage support and maximizing the utilization of clean energy even under adverse conditions. Finally, the effectiveness of this coordinated control strategy in ensuring a sustainable and resilient grid connection is validated through MATLAB R2022b/Simulink simulations. Full article

Background/Objectives: This article is a narrative review that examines the development of attachment from intrauterine life to the first thousand days of a child’s life, integrating psychoanalytic, neuroscientific, genetic, and cross-cultural perspectives. Biological, relational, neurological, and cultural factors interact and shape individual differences in socio-emotional functioning. This paper aims to propose a reinterpretation of early attachment, describing it as both a clinical and relational phenomenon and an adaptive process inscribed in human evolutionary history, according to the Four-Domain Integrative Framework described herein. Methods: The review examined three main areas of evidence: early attachment characteristics, cross-cultural caregiving variations, and genetic and epigenetic mechanisms underlying environmental sensitivity. Results: The review first identified seven characteristics of early attachment (proximity seeking, emotional attunement, intrauterine experiences, maternal holding, security patterns, brain plasticity, and maternal stress) which represent developmental mechanisms that generate individual differences in trust, self-regulation, resilience, and psychopathological vulnerability. Second, cross-cultural variations in six distinct caregiving contexts were examined, demonstrating that secure attachment emerges through culturally specific pathways, differentially influencing motor development, sleep patterns, hypothalamic–pituitary–adrenal axis maturation, and social skills. Finally, the differential susceptibility model was provided through the analysis of five genetic and epigenetic systems (oxytocin receptor gene, serotonin transporter gene, dopamine receptor gene, glucocorticoid receptor methylation, and fetal programming) that modulate environmental sensitivity. Conclusions: Biological, relational, neurological, and cultural factors interact and shape individual differences in socio-emotional functioning. Full article

Salt stress inhibits plant growth, requiring salt-tolerant genes for the development of resilient plants. A key tolerance mechanism is potassium/sodium homeostasis, governed by Shaker K⁺ channels. Given that Shaker K⁺ channels from salt-sensitive species have been extensively studied while their counterparts in salt-tolerant plants remain largely unexplored, this study investigates the evolution and function of these channels in salt-tolerant bermudagrass to address this knowledge gap. Genomic analysis identified 25 Shaker K⁺ channel genes, an expanded family relative to other species. Phylogenetics placed them into five groups (I–V), with groups I, II, III, and V expanded via segmental duplication. Salt stress response screening revealed that only CdKAT1.1 was rapidly upregulated. Functional assays in yeast demonstrated that both CdKAT1.1 and its closest homolog CdKAT1.2 improve potassium uptake and salt tolerance, but the enhancement from CdKAT1.1 was significantly greater. This work elucidates the expansion and functional divergence of Shaker K⁺ channels in bermudagrass. CdKAT1.1 emerges as a superior regulator of potassium efficiency and salt tolerance, making it a prime candidate for molecular breeding to improve plant resilience in saline-alkaline soils. Full article

To broaden the application of biomethanation for energy storage and renewable integration, this study investigates the performance of a trickle-bed reactor (TBR) for hydrogen (H₂) utilisation in biogas upgrading, using both pure Carbon dioxide (CO₂) and biogas-derived CO₂ as substrates for methane (CH₄) production. Renewable sources such as wind and solar are inherently variable, increasing the need for scalable storage solutions. Converting surplus electricity into H₂ and CH₄ via biological methanation offers an efficient and safer alternative to direct H₂ storage. By reducing CO₂ produced by biogas plants, methanogenic archaea produce CH₄, enabling H₂ valorisation and enhanced biogas yields. This study demonstrates that TBR technology can achieve CH₄ formation rates up to 15 L-CH₄/L-reactor/day under optimised conditions. Siporax carrier material supported dense biofilm formation and effective gas–liquid mass transfer, facilitating high conversion efficiency. The system showed operational robustness, with rapid recovery after prolonged idle periods and stable production rates of 10–12 L-CH₄/L/day. Wastewater was used as a realistic medium to assess reactor performance under complex, variable conditions. Reactor design focused primarily on enhancing gas–liquid mass transfer and supporting sustained microbial activity through adequate nutrient supply, ensuring sufficient buffer capacity to maintain pH stability. These results demonstrate the potential of TBR-based systems for high-rate, stable biomethanation and highlight their applicability in future energy infrastructures for integrating H₂ through decentralised biogas upgrading. Full article