Search Results (7,984)

The transition toward intelligent and sustainable power systems requires practical schemes to integrate industrial demand flexibility into short-term operation, particularly in emerging electricity markets. This paper proposes an integrated framework that combines data-driven flexibility characterisation with a bi-level optimisation model for an industrial demand-side aggregator participating in the short-term balancing market. Flexibility is identified from AMI data and process information of large consumers, yielding around 2 MW of interruptible load and 3 MW of reducible load over a 24 h horizon. At the upper level, the aggregator maximises its profit by submitting flexibility offers; at the lower level, the system operator minimises balancing costs by co-optimising thermal generation and activated flexibility. The problem is formulated as a mixed-integer linear programming model and is evaluated on a real subtransmission and distribution network of a local utility in Ecuador, with ex-post power flow validation in DIgSILENT PowerFactory. Numerical results show that, despite the limited flexible capacity, the aggregator reduces the maximum energy price from USD/MWh 172.32 to 139.59 (about 19%), generating a daily revenue of USD 2475.15. From a network perspective, demand flexibility eliminates undervoltage at the most critical bus (from 0.93 to 1.03 p.u.) without creating overvoltages, while line loadings remain below 50% in all cases and total daily technical losses decrease from 89.46 to 89.10 MWh (about 0.4%). These results highlight both the potential and current limitations of industrial demand flexibility in short-term markets. Full article

As low-carbon supply chains increasingly integrate green transition strategies with digital transformation, coordinating high-cost green technology investments with data-driven marketing (DDM) becomes a complex managerial task. While these dual investments are essential for market growth, the inherent tension between economic efficiency and fairness concerns often triggers strategic friction phenomenon whose impact under cap-and-trade regulations remains insufficiently explored. This paper investigates the strategic implications of fairness concerns in a low-carbon supply chain in which a manufacturer invests in carbon emission reduction and a retailer engages in data-driven marketing (DDM), under a cap-and-trade regulation. We formulate four Stackelberg game models—Neutral Benchmark (NF), Retailer Fairness (RF), Manufacturer Fairness (MF), and Bilateral Fairness (BF)—to analyze the interplay between behavioral equity and economic efficiency. The main analytical results indicate that (1) fairness concerns universally function as an “efficiency tax” on the supply chain system, where the rational benchmark consistently yields the highest system efficiency. In contrast, bilateral fairness concerns lead to the worst performance due to double friction effects. (2) Counter-intuitively, the retailer can “weaponize” fairness concerns to extract surplus from the leader. Specifically, in environments with high carbon emission reduction costs, a fairness-concerned retailer compels the manufacturer to grant significant wholesale price concessions, thereby achieving higher profits than in a purely rational setting. (3) The manufacturer’s fairness creates a “Benevolence Trap” for the follower; to balance equity, a fair manufacturer tends to underinvest in green technologies, which severely contracts market demand and, unlike the retailer fairness scenario, fails to yield economic benefits for the retailer. (4) A critical “regime-switching” dynamic exists regarding the carbon trading price. While the retailer benefits from fairness strategies in nascent carbon markets, a pivot to rationality becomes optimal as carbon prices surge and efficiency dividends dominate. These findings offer novel managerial insights for supply chain members to navigate behavioral complexities and for policymakers to align incentive mechanisms. Full article

This study presents a novel integrated manufacturing approach that combines fused deposition modeling (FDM) 3D printing with in situ electrospinning to fabricate hierarchical composite structures composed of polylactic acid (PLA) reinforced with polyacrylonitrile (PAN) nanofibers. A mounting fixture was employed to enable layer-by-layer nanofiber deposition directly onto printed PLA layers in a continuous automated process, eliminating the need for prefabricated electrospun nanofiber mats. The influences of nozzle temperature (210–230 °C) and electrospinning time (5–15 min per layer) on mechanical, thermal, and morphological properties were systematically investigated. Optimal performance was achieved at an FDM nozzle temperature of 220 °C with 5 min of electrospinning time (sample E1), showing a 36.5% increase in tensile strength (71 MPa), a 33.3% increase in Young’s modulus (2.8 GPa), and a 62.0% increase in flexural strength (128 MPa) compared with the neat PLA. This enhancement resulted from the complete infiltration of molten PLA into the thin nanofiber mats, creating true fiber–matrix integration. Excessive nanofiber content (15 min ES) caused a 36.5% reduction in strength due to delamination and incomplete infiltration. Thermal analysis revealed a decrease in glass transition temperature (1.2 °C) and onset of thermal degradation (5.3–15.2 °C) with nanofiber integration. Fracture morphology confirmed that to achieve optimal properties, it was critical to balance the nanofiber reinforcement content with the depth of infiltration, as excessive content created poorly bonded interleaved layers. This integrated fabrication platform enables the production of lightweight hierarchical composites with multiscale, custom-made reinforcement for applications in biomedical scaffolds, protective equipment, and structural components. Full article

This study is dedicated to analysing Ukraine’s transition to utilising renewable energy sources within the broader context of European integration, the decarbonization process, and the challenges significantly intensified by the full-scale Russia-Ukraine war in 2022. The objective of this study is to assess the effectiveness of managing Ukraine’s energy transition compared with selected European Union countries and to identify governance-related determinants of transition performance. The energy transition process is viewed as a cornerstone for ensuring national resilience, food security, and strategic post-war recovery planning. Despite significant growth rates in installed capacity, stimulated primarily by the implementation of green tariffs and foreign investments, Ukraine faces a range of systemic barriers. These include regulatory uncertainty, war-related infrastructure damage, and institutional fragility. To comprehensively assess managerial effectiveness, a comparative approach is employed, integrating data from the Energy Transition Index, the Worldwide Governance Indicators, and the Bertelsmann Transformation Index for the period 2015–2023. Within the scope of this research, a comparative analysis is conducted of Ukraine with Poland, Romania, and Slovakia, countries that share a post-socialist legacy and experience in European integration. The obtained results demonstrate that, although Ukraine exhibits a relatively high growth index for renewable energy development, at 54.56%, it significantly lags behind its regional partners in the parameters of quality of state governance, policy implementation consistency, and strategic coordination. It is concluded that managerial effectiveness, defined as the complex interplay between institutional capacity, policy stability, and implementation efficiency, is a decisive factor for the success of the energy transition. The research recommendations encompass enhancing regulatory transparency, strengthening strategic planning, and intensifying the attraction of international investments. Full article

Background/Objectives: Multidisciplinary care is the gold-standard approach for delivering comprehensive pediatric healthcare. For children undergoing cochlear implant (CI) evaluation, multiple appointments are required to assess candidacy, set realistic expectations, and counsel families on rehabilitation and the psychosocial impact of hearing loss. Established pediatric CI users also need coordinated follow-up to address ongoing auditory, educational, and psychosocial needs. This study evaluated the satisfaction and family perspectives of the implementation of a virtual, team-based multidisciplinary model for both CI candidates and established CI users. Methods: Thirty-nine children and their families participated in discipline-specific telehealth consultations, including audiology, listening and spoken language (LSL) therapy, psychology, and educational services, followed by a 60 min multidisciplinary team meeting. Team meetings occurred during pre-implantation and at six months post-activation for CI candidates. Team meetings for established CI users were scheduled following completion of individual consultations. Providers summarized findings from their individual visits before transitioning to a caregiver-led discussion. Post-visit surveys assessed satisfaction and perceived benefit from the multidisciplinary model. Results: Thirty-nine dyads were enrolled (11 Pre-CI; 28 Established CI). Caregivers were predominantly mothers (89.7%), most identified as Hispanic (55.3%) and White (71.1%). Over half of children identified as Hispanic (59%) and White (71.8%); most were diagnosed with hearing loss at birth (55.9%). Satisfaction with the virtual model was uniformly high: 100% of caregivers were satisfied or very satisfied, and most rated care quality as “very good” or “excellent.” LSL therapy was most frequently rated as the most beneficial visit (70% Pre-CI; 45% Established CI). Caregivers strongly preferred ongoing team-based care, with 55–80% reporting that they would like it to occur every six months and 95–100% preferring remote meetings. Conclusions: A virtual multidisciplinary model offers a high-quality, family-centered approach for both CI evaluations and ongoing management of established CI users. By integrating simultaneous team-based sessions, this model not only supports the ‘whole child’ but also strengthens the family system by improving communication, streamlining care, and reducing the burden of multiple in-person appointments. Families consistently report high levels of satisfaction with the convenience, clarity, and collaboration provided through virtual team visits. Incorporating routine check-ins with families is essential to ensure their needs are addressed, reinforce progress, and guide timely, targeted interventions that maximize each child’s developmental outcomes. Full article

This study utilizes the drift–flux model to develop a new flow pattern map designed to facilitate an accurate estimation of gas void fraction (${\alpha }_g$) in vertical upward flow. The map is parameterized by mixture velocity ($u_m$) and gas volumetric quality (${\beta }_g$), integrating transition criteria from the established literature. For applications characterized by significant pressure gradients, such as gas lift, these criteria were reformulated as functions of pressure, enabling direct estimation from operational data. A critical component of this methodology for the estimation of ${\alpha }_g$ is the estimation of the distribution parameter ($C_0$). An analysis of experimental data, spanning pipe diameters from 1.27 to 15 cm across the full void fraction ranges (${0<\alpha }_g<1$), revealed a critical ${\alpha }_g$ threshold beyond which $C_0$ exhibits a distinct decreasing trend. To characterize this phenomenon, the parameter of the distribution-weighted void fraction (${\alpha }_c={\alpha }_g{C}_0$) is introduced. This parameter, representing the dynamically effective void fraction, identifies the critical threshold at its inflection point. The proposed model subsequently defines $C_0$ using a two-part function of ${\alpha }_c$. This generalized approach simplifies the complexity inherent in existing correlations and demonstrates superior predictive accuracy, reducing the average error in ${\alpha }_g$ estimations to 5.4% and outperforming established methods. Furthermore, the model’s parametric architecture is explicitly designed to support the optimization and fine-tuning of coefficients, enabling future use of machine learning for various fluids and complex industrial cases. Full article

In complex industrial environments, surveillance videos often exhibit large parallax, low illumination, low texture, and low overlap rate, making it difficult to extract reliable image feature points and consequently leading to video suboptimal stitching performance. To address these challenges, this study proposes a real-time panoramic surveillance video stitching method specifically designed for complex industrial scenarios. In the image registration stage, the Efficient Channel Attention (ECA) and Channel Attention (CA) modules are integrated with ResNet to enhance the feature extraction layers of the UDIS algorithm, thereby improving feature extraction and matching accuracy. A loss function incorporating similarity loss $L_{sim}$ and smoothness loss $L_{smooth}$ is designed to optimize registration errors. In the image fusion stage, gradient terms and motion terms are introduced for improving the energy function of the optimal seam line, enabling the optimal seam line to avoid moving objects in overlapping regions and thus achieve video stitching. Experimental validation is conducted by comparing the proposed image registration method with SIFT + RANSAC, UDIS, UDIS++, and NIS, and the proposed image fusion method with weighted average fusion, dynamic programming, and graph cut. The results show that, in image registration experiments, the proposed method achieves RMSE, PSNR, and SSIM values of 1.965, 25.338, and 0.8366, respectively. In image fusion experiments, the seam transition is smoother and effectively avoids moving objects, significantly improving the visual quality of the stitched videos. Moreover, the real-time stitching frame rate reaches 23 fps, meeting the real-time requirements of industrial surveillance applications. Full article

The contribution of members of the agri-food system to achieving the Sustainable Development Goals is a key element in the global transition to sustainable development. The use of sustainable management systems supports the development of an integrated approach with a spirit of continuous improvement. Such organization is based on risk-management tools that are applied to multiple stakeholders, e.g., those responsible for product quality, occupational health and safety, and environmental impact, thus enabling better global performance. In this review, the term “ethical food systems” is used in our discussion of the concrete methods that can be used to endorse fairness and concern across the food chain. This comprises safeguarding equitable access to nutritious foods, defending animal welfare, assisting ecologically accountable production, and addressing social and labor justice within supply chains. Ethical factors also include transparency, cultural respect, and intergenerational responsibility. Consequently, the objective of this review is to address how these ethical values can be implemented within a One Health framework, predominantly by assimilating plant-based diets, developing governance tools, and resolving nutritional insecurity. Within the One Health framework, decoding ethical principles into practice necessitates a set of concrete interventions: (i) raising awareness of animal rights; (ii) distributing nutritional and environmental knowledge; (iii) endorsing plant-based food research, commercialization, and consumption; (iv) development of social inclusion and positive recognition of vegan/vegetarian identity. At the same time, it should be noted that this perspective represents only one side of the coin, as many populations continue to consume meat and rely on animal proteins for their nutritional value; thus, the role and benefits of meat and other animal-derived foods must also be recognized and discussed. This operational definition provides a foundation for asking how ethical perspectives can be applied. A case study from Africa shows the implementation of a sustainable and healthy future through the One Health approach. Full article

This study develops a machine-learning-based framework for multiclass soil classification using Cone Penetration Test (CPT) data, aiming to overcome the limitations of traditional empirical Soil Behavior Type (SBT) charts and improve the automation, continuity, robustness, and reliability of stratigraphic interpretation. A dataset of 340 CPT soundings from 26 sites in Shanghai is compiled, and a sliding-window feature engineering strategy is introduced to transform point measurements into local pattern descriptors. An XGBoost-based multiclass classifier is then constructed using fifteen engineered features, integrating second-order optimization, regularized tree structures, and probability-based decision functions. Results demonstrate that the proposed method achieves strong classification performance across nine soil categories, with an overall classification accuracy of approximately 92.6%, an average F1-score exceeding 0.905, and a mean Average Precision (mAP) of 0.954. The confusion matrix, P–R curves, and prediction probabilities show that soil types with distinctive CPT signatures are classified with near-perfect confidence, whereas transitional clay–silt facies exhibit moderate but geologically consistent misclassification. To evaluate depth-wise prediction reliability, an Accuracy Coverage Rate (ACR) metric is proposed. Analysis of all CPTs reveals a mean ACR of 0.924, and the ACR follows a Weibull distribution. Feature importance analysis indicates that depth-dependent variables and smoothed p_s statistics are the dominant predictors governing soil behavior differentiation. The proposed XGBoost-based framework effectively captures nonlinear CPT–soil relationships, offering a practical and interpretable tool for high-resolution soil classification in subsurface investigations. Full article

Traditional villages are integral to the broader context of global socio-economic transition. This study developed a resilience evaluation model centred on built-environment indicators. This model integrates the community, economy, ecology, and culture dimensions. Clarifying the typology and key driving factors of traditional village built environment resilience can effectively activate the inherent potential of villages. The study provides a holistic approach to identifying traditional village built environment resilience types and analysing the key influencing factors. Utilising a method combining the SOM-K-means clustering model and the interpretable XGBoost-SHAP model, the study provides a holistic analytical framework for identifying traditional village built environment resilience types and quantifying the nonlinear action characteristics of various indicators across different types. Taking the Yangtze River Delta (YRD) region as an example, the study demonstrates that traditional villages can be categorised into six potential resilience types, with differentiated key indicator combinations across these types. Furthermore, the nonlinear action characteristics and operational thresholds of the same key indicator differ significantly across various traditional village types. For instance, at medium-to-high threshold levels, the accessibility of cultural buildings contributes significantly to the sustainability of culture–service-driven villages but, conversely, becomes a detriment in ecology-cultural composite archetypes. Similarly, in industry–creative driven villages, once the density of cultural and creative spaces reaches a specific threshold, it exerts a significant positive effect on traditional village development and stabilises into a sustained positive state. However, in ecology–agriculture–organisation-driven villages, exceeding a certain threshold in the density of cultural and creative spaces has a significant negative influence. The results provide an analytical framework for the resilience typology and influencing factors of traditional village built environments, consequently offering a scientific basis for formulating refined, differentiated policies for traditional villages. Full article

Vector-borne infections are a growing public health concern in Romania, influenced by ecological diversity, climate change, and socioeconomic factors. West Nile virus, tick-borne encephalitis, and Lyme borreliosis represent the most significant threats, with additional risks posed by emerging pathogens, such as leishmaniasis, and the potential reintroduction of malaria. While surveillance systems exist for human cases and, to a lesser extent, vectors, these remain fragmented, underfunded, and limited in their integration across human, veterinary, and environmental health domains. By highlighting both gaps and opportunities, this review provides a forward-looking perspective on strengthening Romania’s capacity to anticipate and manage vector-borne disease threats. Transitioning from reactive surveillance to proactive, prediction-driven strategies will be critical to safeguarding public health in the context of accelerating environmental change. Full article

Opophytum forskahlii has a well-established ethnopharmacological significance. This study aimed to assess the skin anti-aging and hair growth-promoting activities of O. forskahlii seed oil (OFSO) and the underlying mechanism. GC-MS profiling revealed high levels of unsaturated fatty acids, linoleic acid (55.46%), and oleic acid (38.54%). The skin anti-aging activity of OFSO (3.125–100 µg/mL) was evaluated in normal human dermal fibroblasts (NHDFs) using MTT and enzyme inhibition assays. OFSO was non-cytotoxic and enhanced fibroblast proliferation in a dose-dependent manner, reaching 145.5% of control at 100 µg/mL (p < 0.05). OFSO significantly (p < 0.05) inhibited collagenase (48%), hyaluronidase (53%), elastase (57%), and tyrosinase (55%). The oil showed anti-inflammatory activity by inhibiting COX-1 and COX-2 (0.01–100 µg/mL) with IC₅₀ = 0.125 and 0.014 µg/mL, respectively. The hair growth promoting efficacy was assessed using adult male Wistar rats, randomly divided into control, OFSO-treated, and 2% minoxidil-treated groups (5 rats/group). Hair growth was assessed through visual scoring over 14 days of topical application and confirmed by histological examination and hair follicle counting. On day 14, the OFSO-treated group displayed almost complete hair coverage (score about 5.0), exceeding minoxidil (about 4.0), and significantly increased hair follicle number (14.0 ± 1 vs. 9.2 ± 0.8, p < 0.05). Histology confirmed that OFSO promoted hair follicle growth, differentiation, and transition from the telogen to the anagen phase. Network pharmacology analysis, integrating targets predicted via SwissTargetPrediction and disease-associated genes from GeneCards, identified PPARG, ESR1, and IL6 as key hub genes underlying OFSO’s effects. PPARG enhances antioxidant defenses, anti-inflammatory responses, and sebaceous gland function; ESR1 supports collagen production, skin elasticity, and follicle vascularization; and IL6 modulates inflammation and triggers the anagen phase of hair growth. Functional enrichment revealed modulation of PPAR, estrogen, prolactin, and arachidonic acid metabolism pathways, suggesting that OFSO may regulate lipid metabolism, inflammation, hormonal signaling, and tissue regeneration. OFSO demonstrated promising anti-aging and hair growth activities, supporting further development and testing of cosmetic formulations. Full article

This study maps the maturity of construction safety culture in Indonesia across the design and construction phases and identifies priorities for improving the safety management system in construction. Building on a literature-derived framework of categories and subcategories, we conducted a two-round questionnaire-based expert elicitation (pilot and final rounds) and focus group discussions (FGDs) with a purposive panel of 12 experts representing key stakeholders (government/owners, contractors, consultants, and academia). Expert validation was used to assess alignment with field conditions and refine recommendations. The results show average maturity scores of 3.11 in the design phase and 3.36 in the construction phase, indicating a position between the compliant and proactive levels. Sub-category analysis indicates comparatively stronger performance in regulatory mechanisms and operational controls but persistent weaknesses in early-stage planning competence, time and resource allocation for safety, digitalization of safety management, and hazardous waste management. A cross-phase gap is evident: safety is more institutionalized during execution than it is embedded in upstream design decisions. The findings suggest that advancing beyond compliance requires an integrated approach that links national regulations with international project management guidance and construction-specific practices. We conclude by outlining how these frameworks’ integration can support a transition toward more proactive and ultimately resilient safety culture maturity in Indonesia’s construction sector. Full article

Contemporary cities constitute both the primary site where the climate crisis manifests its most evident impacts and the privileged laboratory for testing strategies of adaptation and resilience. However, the growing emphasis on “climate neutrality” policies risks obscuring the social dimension of urban regeneration processes, thus generating new imbalances and forms of exclusion. This paper offers a critical reflection on the role of urban planning beyond climate neutrality, reorienting it towards a perspective of climate justice capable of integrating ecological transition goals with those of social and territorial cohesion. The research adopts a mixed-method approach, combining theoretical and documentary analysis with empirical case comparison, to investigate the relationship among urban regeneration, urban welfare, and spatial inequalities. The study aims to identify strategies for preventing climate gentrification, a phenomenon in which adaptation and mitigation measures—if not accompanied by adequate redistributive mechanisms—produce socio-spatial displacement effects that exclude the most vulnerable communities from the environmental benefits generated. The comparative analysis of two international case studies—Little Haiti (Miami) and the Green Corridors of Medellín (Colombia)—reveals two contrasting trajectories of the ecological transition: a regressive one, driven by market logics and real-estate valorization, and a progressive one, grounded in principles of equity, participation, and inclusive distribution of environmental benefits. Full article

Sustainable management of sediment-laden rivers is essential for balancing flood control, ecological protection, and socioeconomic development. The Upper Yellow River, supporting 160 million people, faces escalating challenges in maintaining channel stability under intensified water–sediment imbalances. This study investigates the Sipaikou reach in Ningxia—a representative wandering channel with multiple mid-channel shoals—through integrated UAV-USV-GNSS RTK field measurements and hydrodynamic and sediment transport modeling. Field measurements reveal that mid-channel shoal morphology coupled with bend circulation governs flow division patterns, with discharge ratios of 44.16% and 86.31% at the primary and secondary shoals, respectively. Gaussian kernel density estimation demonstrates velocity distributions evolving from right-skewed to left-skewed around shoals, while spur dike regions display strong left skewness with concentrated main flow. Numerical simulations under six discharge scenarios indicate: (1) Head loss exhibits diminishing marginal effects at the primary shoal, an inflection point at a critical discharge at the secondary shoal, and superlinear growth in the spur dike region. (2) The normal-flow period represents the critical threshold for erosion–deposition regime transition. (3) Spur dike series achieve bank protection through main flow constriction and inter-dike low-velocity zone creation. These findings provide scientific foundations for sustainable flood risk management and ecological restoration in wandering rivers. The integrated measurement–simulation framework offers a transferable methodology for adaptive river management under changing hydrological conditions. Full article