Search Results (1,106)

Imaging technologies are widely used in surveillance, medical diagnostics, and other critical applications. However, under low-light conditions, captured images often suffer from insufficient brightness, blurred details, and excessive noise, degrading quality and hindering downstream tasks. Conventional low-light image enhancement (LLIE) methods not only require annotated data but also often involve heavy models with high computational costs, making them unsuitable for real-time processing. To tackle these challenges, a lightweight and unsupervised LLIE method utilizing a dual-stage frequency-domain calibration network (DFCNet) is proposed. In the first stage, the input image undergoes the preliminary feature modulation (PFM) module to guide the illumination estimation (IE) module in generating a more accurate illumination map. The final enhanced image is obtained by dividing the input by the estimated illumination map. The second stage is used only during training. It applies a frequency-domain residual calibration (FRC) module to the first-stage output, generating a calibration term that is added to the original input to darken dark regions and brighten bright areas. This updated input is then fed back to the PFM and IE modules for parameter optimization. Extensive experiments on benchmark datasets demonstrate that DFCNet achieves superior performance across multiple image quality metrics while delivering visually clearer and more natural results. Full article

Background/Objectives: Despite its significant impact on learning, classroom acoustics and students’ hearing difficulties are often overlooked compared with more visible issues like lighting. Hearing loss—frequently underestimated and invisible—affects both students and teachers, potentially leading to fatigue, reduced participation, and academic challenges. The A.BA.CO. project in Italy was developed to address these issues by promoting improved classroom design, technological solutions, and better auditory communication accessibility in schools. Objective: This article presents the A.BA.CO. project, offering context and an overview of the preliminary analyses conducted by its multidisciplinary team. The goal is to share insights and propose organizational frameworks, technical solutions, and best practices concerning the hearing, communication, and auditory learning challenges experienced by students with hearing impairments. Results: The A.BA.CO. team’s analyses identified key barriers to inclusion for students with (or without) hearing impairments, such as poor classroom acoustics, excessive noise, and suboptimal seating arrangements. The project underscores the importance of improved acoustic environments and the integration of assistive technologies, including speech-to-text systems. The findings highlight the need for interdisciplinary collaboration to design accessible and inclusive educational settings for all learners. Conclusions: Embedding educational audiology within school systems—alongside enhancements in classroom acoustics and the use of assistive technologies and other technological solutions—is essential to ensure that all students, regardless of hearing ability, have equitable access to learning and full participation in educational life. Full article

The growing number of daylighting metrics—often overlapping in scope or terminology—combined with the need for prior familiarization to interpret and apply them effectively, has created a barrier to their adoption beyond academic settings. Consequently, this study analyzes a representative set of established and emerging daylighting metrics to evaluate applicability, synergies, and limitations. Particular attention is given to their implications for occupant health, well-being, performance, and energy use, especially within the context of sensorless smart control systems. A virtual room model was simulated using DaySim 3.1 in two contrasting climates—Seville and London—with varying window-to-wall ratios, orientations, and occupancy schedules. The results show that no single metric provides a comprehensive daylighting assessment, highlighting the need for combined approaches. Daylighting Autonomy (DA) proved useful for task illumination, while Useful Daylight Illuminance (UDI) helped identify areas prone to excessive solar exposure. Spatial metrics such as Spatial Daylight Autonomy (sDA) and Annual Sunlight Exposure (ASE) offer an overview but lack necessary granularity. Circadian Stimulus Autonomy (CSA) appears promising for evaluating circadian entrainment, though its underlying models remain under refinement. Continuous Overcast Daylight Autonomy (DAo.con) shows the potential for sensorless lighting control when adjusted for orientation. A nuanced, multi-metric approach is therefore recommended. Full article

Ag-doped ZnO is a promising photocatalyst. However, the combined influence of the Ag doping concentration and furnace temperature has not been adequately explored, hindering the optimization of ZnO/Ag materials for practical applications. In this study, ZnO/Ag materials were synthesized via ultrasonic spray pyrolysis by systematically varying both the furnace calcination temperature and the Ag doping concentration. The synthesized materials were analyzed through a range of spectroscopic methods to investigate their structural, morphological, and surface characteristics. Their photocatalytic activity was assessed by monitoring the degradation of methylene blue (MB) under ultraviolet light exposure. The findings indicate that the ZnO sample that was calcined at 400 °C exhibited the highest degradation efficiency among the undoped samples, which can be attributed to its submicron particle size, moderate crystallinity, and high surface hydroxylation. The sample with 5-wt% Ag doping achieved enhanced performance, demonstrating the best photocatalytic activity (65% MB degradation). This improvement was attributed to the synergistic effects of surface plasmon resonance and optimized interaction between the Ag nanoparticles and surface hydroxyl groups. Excessive Ag loading (10 wt%) led to reduced activity owing to potential agglomeration and recombination centers. These results highlight the critical role of both the thermal and chemical parameters in tailoring ZnO-based photocatalysts for wastewater treatment applications. Full article

As a globally significant economic crop, pepper (Capsicum annuum L.) plants display excessive plant height (etiolation) in greenhouse production under an undesirable environment, leading to lodging-prone plants with reduced stress resistance. In the present study, we provided supplementary ultraviolet-B (UV-B, 280–315 nm) light to pepper plants grown in a greenhouse to assess the influences of UV-B on pepper growth, with an emphasis on the molecular mechanisms mediated through the gibberellin (GA) signaling pathway. The results indicated that UV-B significantly decreased the plant height and the fresh weight of pepper plants. However, no significant differences were observed in the chlorophyll content of pepper plants grown under natural light and supplementary UV-B radiation. The results of the transcriptomic and metabolomic analyses indicated that differentially expressed genes (DEGs) were significantly enriched in plant hormone signal transduction and that UV radiation altered the gibberellin synthesis pathway of pepper plants. Specifically, the GA3 content of the pepper plants grown with UV-B radiation decreased by 39.1% compared with those grown without supplementary UV-B radiation; however, the opposite trend was observed in GA34, GA7, and GA51 contents. In conclusion, UV-B exposure significantly reduced plant height, a phenotypic response mechanistically linked to an alteration in GA homeostasis, which may be caused by a decrease in GA3 content. Our study elucidated the interplay between UV-B and gibberellin biosynthesis in pepper morphogenesis, offering a theoretical rationale for developing UV-B photoregulation technologies as alternatives to chemical growth inhibitors. Full article

The increasing deployment of photovoltaic and energy storage systems (ESSs) in modern power grids has highlighted the critical challenge of component degradation, which significantly impacts system efficiency, operational costs, and long-term reliability. Conventional energy dispatch and optimization approaches fail to adequately mitigate the progressive efficiency loss in PV modules and battery storage, leading to suboptimal performance and reduced system longevity. To address these challenges, this paper proposes a quantum-enhanced degradation pathway optimization framework that dynamically adjusts operational strategies to extend the lifespan of PV storage systems while maintaining high efficiency. By leveraging quantum-assisted Monte Carlo simulations and hybrid quantum–classical optimization, the proposed model evaluates degradation pathways in real time and proactively optimizes energy dispatch to minimize efficiency losses due to aging effects. The framework integrates a quantum-inspired predictive maintenance algorithm, which utilizes probabilistic modeling to forecast degradation states and dynamically adjust charge–discharge cycles in storage systems. Unlike conventional optimization methods, which struggle with the complexity and stochastic nature of degradation mechanisms, the proposed approach capitalizes on quantum parallelism to assess multiple degradation scenarios simultaneously, significantly enhancing computational efficiency. A three-layer hierarchical optimization structure is introduced, ensuring real-time degradation risk assessment, periodic dispatch optimization, and long-term predictive adjustments based on PV and battery aging trends. The framework is tested on a 5 MW PV array coupled with a 2.5 MWh lithium-ion battery system, with real-world degradation models applied to reflect light-induced PV degradation (0.7% annual efficiency loss) and battery state-of-health deterioration (1.2% per 100 cycles). A hybrid quantum–classical computing environment, utilizing D-Wave’s Advantage quantum annealer alongside a classical reinforcement learning-based optimization engine, enables large-scale scenario evaluation and real-time operational adjustments. The simulation results demonstrate that the quantum-enhanced degradation optimization framework significantly reduces efficiency losses, extending the PV module’s lifespan by approximately 2.5 years and reducing battery-degradation-induced wear by 25% compared to conventional methods. The quantum-assisted predictive maintenance model ensures optimal dispatch strategies that balance energy demand with system longevity, preventing excessive degradation while maintaining grid reliability. The findings establish a novel paradigm in degradation-aware energy optimization, showcasing the potential of quantum computing in enhancing the sustainability and resilience of PV storage systems. This research paves the way for the broader integration of quantum-based decision-making in renewable energy infrastructure, enabling scalable, high-performance optimization for future energy systems. Full article

With the rapid advancement of urbanization in China, the demand for community-based elderly care facilities (CECFs) has been increasing. One pressing challenge is the question of how to provide CECFs that not only meet the health needs of the elderly but also make efficient use of limited urban land resources. This study addresses this issue by adopting an integrated multi-method research framework that combines multi-objective optimization (MOO) algorithms, Spearman rank correlation analysis, ensemble learning methods (Random Forest combined with SHapley Additive exPlanations (SHAP), where SHAP enhances the interpretability of ensemble models), and Self-Organizing Map (SOM) neural networks. This framework is employed to identify optimal building configurations and to examine how different architectural parameters influence key daylight performance indicators—Useful Daylight Illuminance (UDI) and Daylight Factor (DF). Results indicate that when UDI and DF meet the comfort thresholds for elderly users, the minimum building area can be controlled to as little as 351 m² and can achieve a balance between natural lighting and spatial efficiency. This ensures sufficient indoor daylight while mitigating excessive glare that could impair elderly vision. Significant correlations are observed between spatial form and daylight performance, with factors such as window-to-wall ratio (WWR) and wall thickness (WT) playing crucial roles. Specifically, wall thickness affects indoor daylight distribution by altering window depth and shading. Moreover, the ensemble learning models combined with SHAP analysis uncover nonlinear relationships between various architectural parameters and daylight performance. In addition, a decision support method based on SOM is proposed to replace the subjective decision-making process commonly found in traditional optimization frameworks. This method enables the visualization of a large Pareto solution set in a two-dimensional space, facilitating more informed and rational design decisions. Finally, the findings are translated into a set of practical design strategies for application in real-world projects. Full article

The procedure for the generation of azirinyl-substituted nitrile oxides by the reaction of 2-(diazoacetyl)-2H-azirines with tert-butyl nitrite while preserving the azirine ring has been developed. The [3+2] cycloaddition of azirinyl-substituted nitrile oxides to terminal acetylenes produced azirinyl(isoxazolyl)ketones with various substituents in position 3 of azirine and position 5 of isoxazole fragments in a 51–91% yield at room temperature in DCM. DFT calculations and experimental data are consistent with the assumption that the formation of azirinyl-substituted nitrile oxides is accelerated by the acid catalyst. Cycloadducts of nitrile oxides with aryl/hetarylacetylenes and DMAD can be obtained by catalysis with boron trifluoride etherate, which significantly expands the scope of application of the reaction. Expansion of the azirine ring of the prepared cycloadducts allows obtaining a wide range of structurally diverse functionalized isoxazole-containing heterocyclic hybrids. LED light induces isomerization of the azirinecarbonyl moiety of the azirinyl(isoxazolyl)ketones, resulting in the formation of a set of 3,5’-biisoxazoles in a 40–71% yield, while the catalytic reaction of the azirine moiety with 1,3-diketones opens the way to pyrrole- and isoxazole-containing hybrids. 2-(Isoxazole-3-ylcarbonyl)-3-arylazirines were also easily isomerized to 3-(oxazol-5-yl)isoxazoles in methanol in the presence of excess potassium carbonate at room temperature. Full article

Harmful Algal Blooms (HABs) are a growing environmental concern due to their adverse impacts on aquatic ecosystems, human health, and economic activities. These blooms are driven by a combination of factors, including nutrient enrichment, environmental factors, and hydrological conditions, leading to the excessive growth of algae. HABs produce toxins that threaten aquatic biodiversity, contaminate drinking water, and cause economic losses in fisheries and tourism. The causes of HABs are multifaceted, involving interactions between environmental factors such as temperature, light availability, and nutrient levels. Agricultural runoff, wastewater discharge, and industrial pollution introduce excessive nitrogen and phosphorus into water bodies, fueling bloom formation. Climate change further exacerbates the problem by altering precipitation patterns, increasing water temperatures, and intensifying coastal upwelling events, all of which create favorable conditions for HAB proliferation. This review explores the causes, ecological consequences, and potential mitigation strategies for HABs. Effective monitoring and detection methods, including satellite remote sensing, molecular biotechnology, and artificial intelligence-driven predictive models, offer promising avenues for early intervention. Sustainable management strategies such as nutrient load reductions, bioremediation, and regulatory policies can help mitigate the adverse effects of HABs. Public awareness and community involvement also play a crucial role in preventing and managing HAB events by promoting responsible agricultural practices, reducing waste discharge, and supporting conservation efforts. By examining existing literature and case studies, this study underscores the urgent need for comprehensive and interdisciplinary approaches to regulate HABs. Full article

Heavy metal pollution of lake sediments is one of the prominent ecological and environmental problems worldwide, and it is of great significance to conduct research on heavy metal pollution in lake sediments to protect the ecological environment, safeguard human health, and promote sustainable development. As an integral part of Dongting Lake, Datong Lake holds a crucial ecological position. More than 10 years ago, due to a series of factors, including excessive fertilizer application and fishing, the water quality of Datong Lake declined, resulting in varying degrees of contamination by Cd, Mn, and other heavy metals in the sediments. After 2017, Datong Lake began to establish a mechanism for protecting and managing the lake, and its ecological and environmental problems have been significantly improved. To clarify the current situation of heavy metal contamination in the sediments of Datong Lake, 15 sediment samples were collected from the lake, and the contents of soil heavy metals Cd, As, Pb, Cr, Cu, Mn, Ni, and Zn were determined. A Monte Carlo simulation was introduced to carry out the ecological and human health risk evaluation of the sediments in the study area to overcome the problem of low reliability of the results of ecological and human health risk evaluation due to the randomness and incompleteness of the environmental data as well as the differences in the human body parameters. The results and conclusions show that (1) the average values of Cd, Pb, Cr, Cu, Mn, Ni, and Zn contents in the sediments of Datong Lake are higher than the background values of soil elements in the sediments of Dongting Lake, and the average values of As contents of heavy metals are lower than the background values of the soil, and the heavy metal contamination in the sediments in the study area is dominated by slight contamination, and the possibility of point-source contamination is slight. (2) The results of both the Geo-accumulation index and Enrichment factor evaluation showed that the degree of heavy metal contamination of sediments was Ni > Cu > Cr > Mn > Cd > Pb > Zn > As. (3) The average value of the single ecological risk index of heavy metal elements, in descending order, was as follows: Cd > As > Pb > Cu > Ni > Cr > Zn > Mn; all the heavy metal elements were at the level of light pollution, and the average value of the comprehensive ecological risk index was 32.83, which is a slight ecological risk level. (4) Both non-carcinogenic and carcinogenic risks for all populations in the study area remain low following heavy metal exposure via ingestion and dermal pathways. Ecological and health risk assessments identified As and Cd as exhibiting significantly higher sensitivity than other heavy metals. Consequently, continuous monitoring and source-tracking of these elements are recommended to safeguard long-term ecological integrity and public health in the region. Full article

Chronic diabetic wounds affect 15–20% of patients and are characterized by impaired healing due to disrupted hemostasis, inflammation, proliferation, and extracellular matrix (ECM) remodeling. Low-level light therapy (LLLT) has emerged as a promising noninvasive strategy for enhancing tissue regeneration. Here, we developed a multispectral pulsed LED system combining red and near-infrared light to stimulate wound healing. In vitro photostimulation of human keratinocytes and fibroblasts on biomimetic hydrogels enhanced adhesion, spreading, migration, and proliferation via increased focal adhesion kinase (pFAK), paxillin, and F-actin expression. In vivo, daily LED treatment of streptozotocin-induced diabetic wounds accelerated closure and improved ECM remodeling. Histological and molecular analyses revealed elevated levels of MMPs, interleukins, collagen, fibronectin, FGF2, and TGF-β1, supporting regenerative healing without excessive fibrosis. These findings demonstrate that multispectral pulsed photobiomodulation enhances diabetic wound healing through focal adhesion-mediated cell migration and ECM remodeling, offering a cost-effective and clinically translatable approach for chronic wound therapy. Full article

Fabricating efficient photocatalysts that can be used in solar-to-fuel conversion and to enhance the photochemical reaction rate is essential to the current energy crisis and climate changes due to the excessive usage of nonrenewable fossil fuels. To attain high photo-to-chemical conversion efficiency, it is important to fabricate cost-effective and durable catalysts with high activity. One-dimensional cadmium sulfides (1D CdS), with higher surface area, charge carrier separation along the linear direction, and visible light harvesting properties, are promising candidates for converting solar energy to H₂, reducing CO₂ to commodity chemicals, and remediating environmental pollutants. The main disadvantage of CdS is photocorrosion due to the leaching of S²⁻ ions during the photochemical reactions, and further charge recombination rate leads to low quantum efficiency. Therefore, the implementation of core–shell heterostructured morphology, i.e., the growth of the shell on the surface of the 1D CdS, which offers unique features such as protection of CdS from photocorrosion, a tunable interface between the core CdS and shell, and photogenerated charge carrier separation via heterojunctions, provides additional active sites and enhanced visible light harvesting. Therefore, the viability of the core–shell synthesis strategy and synergetic effects offer a new way of designing photocatalysts with enhanced stability and improved charge separation in solar energy conversion systems. This review highlights some critical aspects of synthesizing 1D CdS core–shell heterostructures, underlying reaction mechanisms, and their performance in photoredox reactions. Finally, some challenges and considerations in the fabrication of 1D CdS-based core–shell nanostructures that can overcome the current barriers in industrial applications are discussed. Full article

This study investigates the efficient and enantioselective hydrolysis of ester bonds through a series of biotransformations employing various photobiocatalysts. A racemic mixture of 1-phenylethyl acetate served as the model substrate. The described research identified three strains exhibiting the highest biocatalytic activity: Nostoc cf-muscorum (CCALA 129), Leptolyngbya foveolarum (CCALA 76), and Synechococcus bigranulatus (CCALA 187). Their application led to the complete hydrolysis of the starting reagent, yielding both the unreacted ester and its corresponding alcohol in an enantioselective manner. Notably, the selectivity, expressed as S, reached an impressive value of 283 in certain outcomes. The photobiotransformations were conducted under varying conditions, with particular focus on two essential parameters: the duration of the process, crucial for kinetically controlled reactions, and light exposure, critical for light-dependent organisms. The representative results highlight the efficacy of these biocatalysts. For instance, using Leptolyngbya foveolarum (CCALA 76), Nostoc cf-muscorum (CCALA 129), and Synechococcus bigranulatus (CCALA 187) facilitated the production of 1-(R)-phenylethanol with enantiomeric excesses (ee) of 89%, 88%, and 86%, respectively, at a conversion degree of approximately 50%. These processes also yielded an optically enriched mixture of the unreacted substrate, 1-(S)-phenylethyl acetate. Specifically, in the case of Leptolyngbya foveolarum (CCALA 76), the ee of the unreacted ester reached up to 98%. Light exposure emerged as a key factor influencing selectivity factor (S). Adjusting this parameter allowed us to achieve an E value of up to 283 for the formation of 1-(R)-phenylethanol with an ee > 99% when utilizing the Nostoc cf-muscorum (CCALA 129) strain. Furthermore, light intensity proved crucial for scaling up these processes. Significant results were obtained with Synechococcus bigranulatus, particularly at substrate concentrations ranging from 1 to 10 mM under limited exposure. Here, the conversion degree was 55%, the ee of the (R)-alcohol was 86%, and the selectivity factor (S) value was 21. Full article

Obesity and metabolic disorders remain major global health concerns, traditionally attributed to excessive caloric intake and poor diet quality. Recent studies emphasize that the timing of meals plays a crucial role in determining metabolic health. This review explores chrononutrition, a growing field that examines how food intake patterns interact with endogenous circadian rhythms to influence energy balance, glucose and lipid metabolism, and cardiometabolic risk. The circadian system, which includes a central clock in the suprachiasmatic nucleus and peripheral clocks in metabolic tissues, regulates physiological functions on a 24 h cycle. While light entrains the central clock, feeding schedules act as key synchronizers for peripheral clocks. Disrupting this alignment—common in modern lifestyles involving shift work or late-night eating—can impair hormonal rhythms, reduce insulin sensitivity, and promote adiposity. Evidence from clinical and preclinical studies suggests that early time-restricted eating, where food intake is confined to the morning or early afternoon, offers significant benefits for weight control, glycemic regulation, lipid profiles, and mitochondrial efficiency, even in the absence of caloric restriction. These effects are particularly relevant for populations vulnerable to circadian disruption, such as adolescents, older adults, and night-shift workers. In conclusion, aligning food intake with circadian biology represents a promising, low-cost, and modifiable strategy to improve metabolic outcomes. Integrating chrononutrition into clinical and public health strategies may enhance dietary adherence and treatment efficacy. Future large-scale studies are needed to define optimal eating windows, assess long-term sustainability, and establish population-specific chrononutritional guidelines. Full article

This article presents a comprehensive overview of recent advancements in photonic crystal fiber (PCF)-based sensors, with a particular focus on the surface plasmon resonance (SPR) phenomenon for biosensing. With their ability to modify core and cladding structures, PCFs offer exceptional control over light guidance, dispersion management, and light confinement, making them highly suitable for applications in refractive index (RI) sensing, biomedical imaging, and nonlinear optical phenomena such as fiber tapering and supercontinuum generation. SPR is a highly sensitive optical phenomenon, which is widely integrated with PCFs to enhance detection performance through strong plasmonic interactions at metal–dielectric interfaces. The combination of PCF and SPR technologies has led to the development of innovative sensor geometries, including D-shaped fibers, slotted-air-hole structures, and internal external metal coatings, each optimized for specific sensing goals. These PCF-SPR-based sensors have shown promising results in detecting biomolecular targets such as excess cholesterol, glucose, cancer cells, DNA, and proteins. Furthermore, this review provides an in-depth analysis of key design parameters, plasmonic materials, and sensor models used in PCF-SPR configurations, highlighting their comparative performance metrics and application prospects in medical diagnostics, environmental monitoring, and chemical analysis. Thus, an exhaustive analysis of various sensing parameters, plasmonic materials, and sensor models used in PCF-SPR sensors is presented and explored in this article. Full article