Search Results (9,053)

Coupling interference in densely integrated high-frequency communication architectures leads to significant degradation in transmission efficiency, particularly in modern 5G and GHz-range platforms. From a mathematical perspective, mitigating such interference can be formulated as a multi-criteria optimization problem involving competing design objectives and interacting control mechanisms. In this paper, we develop an equilibrium-based optimization framework by modeling coupling suppression as a finite non-cooperative game. Isolation mechanisms are represented as strategic players whose actions are defined over constrained design spaces, while utility functions incorporate coupling minimization, insertion-loss penalties, and fabrication complexity. Under this formulation, stable mitigation strategies are characterized through Nash equilibrium conditions. To address the inherent trade-offs among performance metrics, the equilibrium computation is integrated with a Pareto multi-objective optimization scheme, yielding Nash–Pareto optimal configurations that balance electromagnetic isolation performance with implementation feasibility. Numerical full-wave simulations in the 2–12 GHz frequency band demonstrate that the proposed equilibrium solutions achieve substantial interference suppression, with reductions exceeding 30 dB compared with conventional baseline designs. The proposed framework provides a mathematically structured approach for interference mitigation and offers a generalizable methodology for multi-objective optimization in high-frequency communication systems. Full article

Macroalgal biomass accumulation in eutrophic coastal lagoons represents both an environmental challenge and an underexploited bioresource. This study evaluates the biostimulant potential of Chaetomorpha linum (C. linum) harvested in the Orbetello Lagoon (Italy) on tomato (Solanum lycopersicum) seed germination and early seedling development. Four extraction strategies were investigated: a phytohormone-enriched fraction (PO), a hydroethanolic reflux extract (CLE), a room-temperature aqueous maceration extract (CLWM), and a mild-water-bath aqueous extract (CLWB). Bioactivity was assessed through controlled laboratory germination assays, comparing germination performance, seedling growth traits, and vigor index against an untreated control and a commercial fertilizer. Across the tested conditions, aqueous formulations exhibited the strongest overall effects, with CLWB providing the most balanced response and increasing seedling vigor by approximately 20–30% relative to the control. Collectively, these results support the valorization of eutrophic C. linum biomass into natural, low-input biostimulants for seed priming applications within sustainable agriculture and circular economy frameworks. Full article

Meeting rising global food demand requires reconciling high productivity with environmental sustainability. While controlled-release fertilizers can improve nitrogen use efficiency, their combined N-P-K formulation and system-wide impacts remain poorly quantified. A two-year field experiment was conducted in a rice paddy field under a subtropical monsoon climate in Central China to evaluate controlled-release NPK fertilizer (CRNPK) across agronomic, environmental, energy, and economic dimensions. Five treatments were compared: no nitrogen (CK), farmer practice (FFP; 270 kg N ha⁻¹), controlled-release nitrogen (CRN; 225 kg N ha⁻¹), CRNPK (225 kg N ha⁻¹), and reduced-rate CRNPK (80%CRNPK; 180 kg N ha⁻¹). Compared to FFP, CRNPK and 80%CRNPK increased rice yield by 8–16% and nitrogen use efficiency by 38–171%, while reducing reactive nitrogen losses and nitrogen footprint by 39–56%, greenhouse gas emissions and carbon footprint by 22–57%, and enhancing ecosystem economic benefit by 86–109%. Notably, the 80%CRNPK treatment achieved the highest overall sustainability score (5) based on a comprehensive assessment normalizing seven key indicators—yield, economic benefit, energy productivity, carbon footprint, nitrogen footprint, ecosystem economic benefit (EEB), and emergy-based nutrient efficiency (UEV_Nmin), demonstrating that yield gains can be maintained or even enhanced with reduced nitrogen inputs. This study advances controlled-release fertilization from a yield-focused strategy to a quantified, system-level approach for sustainable rice intensification. Full article

With the increasing penetration of distributed energy resources, distribution networks face elevated risks of power disruptions, which call for rapid and flexible emergency response mechanisms. There are not enough traditional emergency generator vehicles, and they are not highly adaptable when it comes to operations, which makes it hard to meet changing dispatching needs. Electric vehicles (EVs), on the other hand, can be used as distributed emergency resources that can be dispatched through vehicle-to-grid (V2G) interaction. Electric vehicle charging stations (EVCSs), on the other hand, are integrated energy storage units that use existing charging infrastructure to provide on-site grid support. To address this gap, this study proposes a comprehensive V2G-powered pre- and post-disaster coordination framework for enhancing distribution network resilience, with three core novelties: first, a refined individual EV model considering dual power and energy constraints is developed, and the Minkowski summation method is applied to accurately quantify the real-time aggregate regulation potential of EVCSs for the first time; second, a two-stage robust optimization model is formulated for pre-event strategic planning, which jointly optimizes EVCS participant selection and distribution network topology to address photo-voltaic (PV) power generation uncertainties; third, a multi-source collaborative dynamic scheduling model is constructed for post-disaster recovery, which explicitly incorporates the spatiotemporal dynamics of EVs and coordinates EVCSs, gas turbine generators (GTGs) and other resources for the first time. We carried out simulations on a modified IEEE 33-bus system with a 10 h extreme fault scenario. The results show that the proposed strategy raises the average critical load recovery ratio to 97.7% (2% higher than traditional deterministic optimization), lowers the total load shedding power by 0.2 MW and the load reduction cost by 19,797.63 CNY, and gives a net V2G power output of 3.42 MW (86.9% higher than the comparison strategy). The proposed V2G-enabled coordinated pre- and post-disaster fault recovery strategy significantly improves the resilience of distribution networks compared to traditional methods. This makes it easier and faster to recover from extreme disaster scenarios, with the overall load recovery rate reaching 91.8% and the critical load restoration rate staying above 85% throughout the recovery process. Full article

Natural and sustainable cosmetics represent a rapidly evolving frontier in dermatological science, integrating plant-derived bioactive compounds with advanced delivery technologies and environmentally conscious formulation design. Botanical ingredients, including polyphenols, flavonoids, terpenoids, alkaloids, and polysaccharides, modulate key biological pathways involved in oxidative stress, inflammation, extracellular matrix remodeling, pigmentation, and immune responses, thereby supporting skin regeneration, protection, and homeostasis. To overcome limitations related to instability, compositional variability, and limited skin penetration, these compounds are increasingly incorporated into advanced delivery systems such as nanoemulsions, solid lipid nanoparticles (SLNs), nanostructured lipid carriers (NLCs), vesicular systems, microneedle platforms, three-dimensional matrices, and plant-derived extracellular vesicles (PDEVs). These technologies enhance cutaneous bioavailability, enable controlled release, and improve tissue targeting, linking formulation design to exposure–response relationships. In parallel, sustainability has become a critical component of product development. Circular economy strategies, including the upcycling of agro-industrial by-products, green extraction technologies, biodegradable packaging, and life cycle assessment, are reshaping cosmetic innovation. Regulatory frameworks are also evolving to address safety, efficacy, and transparency of natural claims, as well as the challenges of botanical standardization. This narrative review, conducted through a structured literature search, provides a mechanistically oriented analysis of botanical ingredients in dermatology, emphasizing molecular pathways, skin delivery science, and safety considerations. Rather than cataloguing ingredients, it proposes a translational framework linking phytochemistry, delivery science, safety-by-design principles, and sustainability to support the rational development of effective and safe dermatological formulations. Full article

Present-day artificial intelligence systems (AI), virtual assistants, and devices connected to the Internet of Things (IoT) are playing an increasingly important role in decision-making processes in the everyday lives of individuals and daily operations of organizations. In this respect, the users’ trust is a key factor determining their acceptance and effective use. In contemporary digital ecosystems, this trust increasingly becomes a component of sustainable digital marketing, in which transparent data practices and responsible communication shape long-term consumer–technology relationships. This paper analyzes the halo effect as a psychological mechanism affecting the perception of competences, reliability, and ethics in the case of technologies based on AI. Based on the literature on behavioral economics, it was shown how positive associations with the interface, brand, or previous experience of the user may lead to excessive trust in technology. Such mechanisms also play a significant role in shaping sustainable consumption patterns, as users—guided by cognitive shortcuts—can adopt technologies in ways that either strengthen or weaken responsible digital behaviors. Moreover, the potential risks associated with this phenomenon were also indicated. The aim of this paper was to present how the utilization of the halo effect influences the generation of trust in smart systems and the formulation of implication for management practices and technology design. These implications are increasingly important in the context of sustainable digital marketing policy, where organizations must align persuasive communication with ethical standards and with rising expectations regarding sustainable digital transformation. Relationships between variables were analyzed using structural equation modeling (SEM), making it possible to verify complex dependencies between the perceived image of technology, the halo effect, and the users’ trust. This study tested three core hypotheses regarding the halo effect’s role, the foundational importance of security, and the mediating function of trust in technology adoption. The results of these analyses indicate that the halo effect significantly affects the level of trust in each of the investigated areas, with the strongest effect observed in the case of virtual assistants, where perception of the human-like characteristics of the interface considerably strengthened trust in the competences and reliability of the system. This finding has particular relevance for AI-driven personalization mechanisms, which increasingly guide consumer decision-making and shape their long-term behavioral patterns in online environments, with direct implications for sustainable consumption. This paper provides contribution to innovation management and technical marketing, stressing the importance of cognitive and emotional factors in the acceptance of new technologies. At the same time, it highlights the theoretical need to integrate responsible AI design with sustainable digital marketing strategies The findings suggest that ensuring trust, once established, has the potential to support not only technological innovation but broader societal goals related to responsible consumption, environmental stewardship, and long-term digital well-being aligned with sustainable development principles. However, this study stops short of empirically measuring sustainable consumption behaviors, offering instead a conceptual link that requires further empirical validation. Full article

Multimodal epileptic seizure detection using physiological biosignals remains challenging due to signal noise, inter-subject variability, weak cross-modal alignment, and the limited interpretability of many machine learning models. To address these challenges, this study proposes a parameterized multimodal feature-fusion framework that unifies normalization, modality weighting, and nonlinear cross-modal interaction within a single mathematical representation. Four fusion parameters, the fusion exponent $\rho$, interaction weight $\left(\delta \right)$, normalization factor $\left(\lambda \right),$ and the cross-modal interaction term $\left(\eta \right)$, are introduced at the feature-fusion level, while all classifiers retain their original learning mechanisms. The framework is evaluated using synchronized EEG, ECG, EMG, and accelerometer signals from 120 subjects, segmented into 2 s windows at 512 Hz and analyzed using twelve classical and deep learning classifiers. Principal Component Analysis (PCA) applied to the fused feature space reveals improved class separability compared to unimodal representations, with EEG exhibiting the strongest intrinsic discrimination and peripheral modalities contributing complementary structure when fused. SHapley Additive exPlanations (SHAP) further identify entropy as the most influential feature across all modalities, followed by RMS and energy, yielding physiologically coherent attributions. Quantitative performance evaluation and ablation analysis confirm that the observed improvements arise from the proposed representation design rather than classifier-specific modifications. Unlike existing architecture-dependent fusion strategies, the proposed method introduces a mathematically parameterized feature-space formulation that enhances separability and interpretability without modifying classifier architectures, thereby establishing a representation-driven paradigm for explainable multimodal seizure detection. These results demonstrate that mathematically principled feature-space modeling can simultaneously enhance predictive performance and interpretability, providing a transparent and robust foundation for explainable multimodal seizure detection. Full article

Compost-based biostimulants (CBB) have emerged as a promising tool in sustainable agriculture, offering an eco-friendly approach to improving soil health, crop productivity, and environmental resilience. Derived from the controlled biodegradation of organic waste, CBB contains a diverse array of beneficial microorganisms, humic substances, and bioactive compounds that act synergistically to stimulate plant growth and soil biological activity. Mechanistically, CBB enhances nutrient acquisition by increasing plant-available nitrogen and phosphate solubility, promoting root development through phytohormone synthesis, and improving stress tolerance by modulating plant defense pathways and antioxidant activity. Additionally, their application enhances soil structure, microbial diversity, and carbon sequestration, making them integral to climate-smart agriculture. Despite their growing relevance, several challenges impede the widespread adoption of CBB. Variability in compost quality, lack of standardized production protocols, limited field-scale validation, and inconsistent regulatory frameworks hinder reproducibility and commercialization. Addressing these gaps requires interdisciplinary research that integrates microbiology, biochemistry, agronomy, and data science to better understand how microbial metabolites interact and optimize formulation strategies. Future research should prioritize the standardization of composting methods, long-term multi-crop field evaluations, and integration with precision agriculture tools for real-time soil monitoring. Policy harmonization, quality assurance frameworks, and farmer education are also vital for ensuring safe and effective use of CBB. Full article

Skin aging is driven by intrinsic factors, such as the accumulation of reactive oxygen species, and extrinsic factors, including ultraviolet (UV) radiation, which accelerate oxidative stress and extracellular matrix degradation. Strategies to mitigate skin aging often focus on antioxidant and anticollagenase activities. Several studies have shown that Pomegranate (Punica granatum L.) peel is an underutilized by-product rich in ellagitannins, which can be hydrolyzed into ellagic acid, a compound with well-documented bioactivity. Therefore, this study aims to investigate the effect of microbial fermentation using Lactiplantibacillus plantarum and Saccharomyces cerevisiae on the physicochemical properties and bioactivity of pomegranate peel juice. Non-fermented juice (NFJ), L. plantarum-fermented juice (LFJ), and S. cerevisiae-fermented juice (SFJ) were used for comparative evaluation. The results showed that fermentation (LFJ and SFJ) led to decreased pH and sugar content, along with significant increases in ellagic acid concentration, antioxidant activity, and collagenase inhibition compared to NFJ. After 168 h, ellagic acid levels increased to 329.87 µg/mL in LFJ and 341.41 µg/mL in SFJ, compared to 263.86 µg/mL in NFJ. Antioxidant activity also increased to 73.82%, 83.25%, and 82.70% for NFJ, LFJ, and SFJ, respectively. Meanwhile, collagenase inhibition was 67.43%, 71.81%, and 73.66% for NFJ, LFJ, and SFJ, respectively. These results provide scientific evidence that microbial fermentation enhances the bioactivity of pomegranate peel juice, showing its potential as a sustainable source of natural ingredients for future cosmetic applications. Further studies on formulation, stability, and safety are needed to translate the results into practical skincare products. Full article

The rising environmental impact of building energy consumption has intensified the demand for sustainable energy solutions. Latent heat thermal energy storage (LHTES) using phase-change materials (PCMs) offers a highly effective approach to improve energy efficiency; however, the intrinsically low thermal conductivity of most PCMs limits their practical performance. This study explores the thermophysical properties of a commercially available bio-based PCM (CrodaTherm^TM 60) enhanced with graphene nanoplatelets (GNPs) to improve heat transfer performance. Nano-enhanced PCMs (NePCMs) were prepared using a two-step process combining magnetic stirring and ultrasonication, incorporating GNPs at 2, 4, and 6 wt.%. Solid-phase density measurements of the NePCMs and viscosity measurements of the pure PCM were also conducted to support material characterisation. The results indicate distinct behaviours for the two nanoparticle sizes. At 6 wt.% nanoparticle loading, for 2 nm particles, the thermal conductivity increases by up to 13.9%, whereas for 6–8 nm particles, the enhancement is 148.9% of the pure PCM. Additionally, a reduction in latent heat is observed, with a proportional relationship to mass loading, as expected. These findings underscore the need for improved nanoparticle dispersion and formulation strategies to optimise both thermal performance and stability. Full article

Carbon storage of terrestrial ecosystems is highly susceptible to land use/cover change (LUCC). In order to optimize land use patterns and advance the dual carbon goals (carbon peaking and carbon neutrality), it is imperative to clarify the role of LUCC in controlling regional terrestrial carbon storage. This study utilized a land use dataset spanning from 1990 to 2020 and incorporated 12 pivotal driving factors. Based on these data and factors, this study constructs four distinct future development scenarios: natural development scenario (ND), cropland protection scenario (CP), ecological protection scenario (EP), and urban development scenario (UD). By integrating the Integrated Valuation of Ecosystem Services and Trade-offs model (InVEST) with the Patch-Generating Land Use Simulation model (PLUS), this study simulated the dynamic changes in land use types and the spatiotemporal evolution of carbon storage in the Qinba Mountains (QBMs). The results revealed that between 1990 and 2020, built-up area and water area experienced substantial expansion with growth rates of 67.89% and 20.39%, respectively. In addition, cropland decreased by 3.09% and grassland decreased by 2.49%. Notably, cropland exhibited the most pronounced conversion intensity among all land use types during this period. Correspondingly, the total terrestrial carbon storage in the study area declined slightly from 7471.08 × 10⁶ t in 1990 to 7437.25 × 10⁶ t in 2020. Forestland dominated the regional carbon pool, accounting for an average of 47.67% of the total carbon storage over the three decades. Further analysis identified natural factors as the primary drivers of LUCC and associated carbon storage changes, with DEM exerting the greatest influence, followed by mean annual temperature and mean annual precipitation. Projection analyses for 2030 reveal divergent carbon storage outcomes across different land use scenarios relative to the 2020 baseline. Under the natural development (ND) and urban development (UD) scenarios, total carbon stocks are projected to decline by 37.63 × 10⁶ t and 19.99 × 10⁶ t, respectively. Conversely, implementation of conservation-oriented strategies yields substantial increases, with the cropland protection (CP) and ecological protection (EP) scenarios enhancing carbon storage by 16.87 × 10⁶ t and 13.07 × 10⁶ t, respectively. These findings underscore the critical role of protection-focused land use policies in strengthening ecosystem carbon sequestration capacity. The study provides a scientific foundation for formulating targeted forestry management policies and enhancing the terrestrial ecosystems’ capacity to act as carbon sinks in mountainous areas. Full article

Promoting substantive green innovation is the core pathway for enterprises to achieve sustainable development. However, its inherent characteristics of high investment and high risk often result in insufficient innovation motivation among enterprises. Rooted in the Resource-Based View (RBV) and Dynamic Capability Theory (DCT), the research investigates the influence of underlying technology digital transformation on enterprises’ substantive green innovation. Using panel data from Chinese A-share listed firms (2009–2024), this analysis reveals a significant promotional effect of underlying technology digital transformation on substantive green innovation. The robustness of this conclusion is confirmed by a battery of tests. Mechanism analysis demonstrates that this effect functions mainly through two pathways: “technology empowerment” and “governance optimization”, namely enhancing corporate R&D capability and improving ESG performance. Heterogeneity analysis further indicates that this promotional effect is more prominent in enterprises with higher environmental disclosure levels and better internal control quality. This study elucidates the internal mechanism and boundary constraints by which underlying technology digital transformation empowers substantive green innovation, thereby offering micro-level evidence for comprehending the in-depth integration of digital technologies and eco-friendly development. The findings offer important practical implications for firms in formulating effective “digitalization–greenization” synergy strategies. Full article

Methane oxy-combustion is a promising carbon capture pathway due to the high CO₂ concentration in the exhaust; however, combustion in pure oxygen produces excessively high flame temperatures that impair ignition and operational stability. To mitigate these effects, steam dilution is commonly applied, but it significantly prolongs ignition delay time (IDT). To address these limitations, hydrogen enrichment is proposed as a reactivity-enhancement strategy. The objective of this study is to quantify the combined effects of steam dilution and hydrogen enrichment on ignition behaviour, carbon species formation, and flame temperature in methane oxy-combustion, considering both ignition onset and equilibrium combustion states. A detailed numerical investigation is conducted using zero-dimensional constant-pressure simulations with detailed chemical kinetics implemented in Cantera, formulated in mixture-fraction space. IDT, CO/CO₂ formation, and adiabatic flame temperature are analysed over steam dilution levels of 0–40%, hydrogen enrichment up to 5% by mass, and initial temperatures between 1050 and 1200 K. The model is validated against experimental data for adiabatic flame temperature and key radical species. Results demonstrate that steam dilution effectively reduces the peak adiabatic flame temperature (by more than 300 K at 40% steam) and enhances the CO₂ mass fraction in the equilibrium state near the stoichiometric mixture fraction, but increases IDT by approximately 100–200% across the mixture-fraction range. Hydrogen enrichment strongly counteracts this inhibition, reducing IDT by up to one order of magnitude under high steam dilution (30–40%) while simultaneously suppressing CO. At the stoichiometric mixture fraction, H₂ addition decreases equilibrium CO₂ formation, indicating a trade-off between enhanced ignition reactivity and ultimate carbon conversion under equilibrium conditions. The use of steam dilution as a temperature-control strategy and hydrogen enrichment as a reactivity enhancer identifies a favourable mixture-fraction window. Full article

Vitamin D is a pleiotropic secosteroid with endocrine and intracrine actions that influence key phases of allogeneic hematopoietic stem cell transplantation. Epithelial barriers, antigen-presenting cells and effector lymphocytes express the vitamin D receptor and enzymes required for local activation, allowing circulating 25-hydroxyvitamin D to be converted into its active form and modulate immune interactions. During the peri-transplant period, sunlight deprivation, reduced intake, mucosal injury, cholestasis and corticosteroid exposure markedly reduce vitamin D levels at a time when antigen presentation and immune reconstitution occur. This review integrates mechanistic immunology with clinical observations and interventional data to outline strategies that prevent severe deficiency. It summarizes epidemiology before and after transplantation, associations with acute and chronic graft-versus-host disease, relapse, engraftment, infections, bone health and survival, and evaluates dosing approaches including pre-conditioning loading and reassessment at day thirty with escalation if needed. Absorption-savvy formulations such as oral thin-film and intramuscular cholecalciferol are considered when gastrointestinal function is compromised. Given the high prevalence of deficiency, biological plausibility, safety and low cost, a structured approach that includes screening, repletion and monitoring to achieve concentrations of at least thirty nanograms per milliliter by day thirty represents a pragmatic and low-risk component of supportive care pending definitive evidence. Full article

Background: The rapid growth of e-commerce has intensified the need for packaging strategies that reduce logistics costs and environmental impact. Traditional box recommendation methods select the best-fitting box from a fixed set of options, which limits their ability to minimize unused space and total costs. Methods: This study formulates the Shipping Box Configuration Problem (SBCP), which aims to determine an optimal set of box types and dimensions for multi-product orders. To solve this problem, we propose a Particle Swarm Optimization (PSO)-based heuristic that dynamically designs box configuration rather than selecting from predefined sizes. Results: The proposed method is evaluated using real order data from two South Korean e-commerce companies with different product characteristics and existing box configurations. Computational results show that the PSO-based approach reduces total packaging and shipping costs and improves space utilization compared to current box configurations. The analysis also indicates that increasing the number of box types and reducing safety ratios generally lead to cost savings, although these effects must be balanced against operational complexity. Conclusions: The results suggest that adaptive box configuration design can improve both economic efficiency and environmental performance, providing practical guidance for e-commerce logistics managers seeking to optimize packaging strategies under operational constraints. Full article