Search Results (175)

Background/Objectives: This in vitro study examined the potential enhancement in resistance to accelerated aging in room-temperature vulcanized (RTV) maxillofacial silicone, intrinsically pigmented in two skin tones, through the use of zirconium oxide (ZrO₂) nanoparticles. Methods: A total of 128 disc-shaped specimens were created in rose silk and soft brown shades, each containing zirconium oxide concentrations of 0%, 1%, 2%, and 3% by weight. Color variation (ΔE*) was assessed initially and following 252, 750, and 1252 h of artificial aging, tested with a colorimeter. Surface roughness characteristics (R_a, R_q, R_t) were evaluated before and after 1252 h using atomic force microscopy (AFM). Structural, vibrational, and morphological characteristics were analyzed through X-ray diffraction (XRD), Fourier transform infrared spectroscopy (FTIR), and field emission scanning electron microscopy (FESEM). Results: Non-parametric tests (Friedman, Kruskal–Wallis, and Bonferroni-adjusted paired testing; p < 0.05) indicated that accelerated aging significantly increased ΔE* in all specimens. The addition of ZrO₂ reduced these changes; however, the optimal concentration differed by pigment: 1% for rose silk and 3% for soft brown. The effect on surface roughness depended on pigment type. Higher nanoparticle concentrations generally improved post-aging smoothness in soft brown samples, whereas rose silk showed a more variable response. XRD and FTIR analyses confirmed successful nanoparticle incorporation without altering the fundamental silicone structure, while FESEM demonstrated improved filler–matrix interaction in modified groups. Conclusions: Adjusting ZrO₂ concentration according to pigment type can improve the future color retention and surface characteristics of maxillofacial silicone. Full article

Urban environments, particularly university campuses, are increasingly exposed to thermal discomfort due to the Urban Heat Island (UHI) effect and intense solar radiation. This study evaluates the effectiveness of passive and hybrid cooling strategies, specifically sun-sail shading and mist cooling, in enhancing outdoor thermal comfort (OTC) in a university courtyard. The Van Dyck courtyard at the American University of Beirut, located on the East Mediterranean coast, was selected due to its heavy use between 10 am and 2 pm during summer, when ambient temperatures ranged between 32 and 36 °C and relative humidity between 21 and 33%. Thermal variations across four seating areas were analyzed using ENVI-met, a high-resolution microscale model validated against on-site data, achieving Mean Absolute Percentage Errors of 4% for air temperature and 5.2% for relative humidity. Under baseline conditions, Physiological Equivalent Temperature (PET) exceeded 58 °C, indicating severe thermal stress. Several mitigation strategies were evaluated, including three shading configurations, two mist-cooling setups, and a combined system. Results showed that double-layer shading reduced PET by 17.1 °C, mist cooling by 1.2 °C, and the combined system by 20.7 °C. Shading minimized radiant heat gain, while mist cooling enhanced evaporative cooling, jointly bringing thermal sensations closer to slightly warm–comfortable conditions. These cooling interventions also have sustainability value by reducing dependence on mechanically cooled indoor spaces and lowering campus air-conditioning demand. As passive or low-energy measures, shading and mist cooling support climate-adaptive outdoor design in heat-stressed Mediterranean environments. Full article

Expansion of photovoltaic infrastructure in arid regions raises concerns about soil microhabitat degradation. Very few studies have systematically compared these recovery alternatives in reshaping the soil fungal communities during early recovery. This study investigated short-term effects (less that two-year recovery) of PV infrastructure and restoration (natural/artificial) on soil fungal diversity and enzymatic activities in Ningxia desert steppe. A total of 243 soil samples were analyzed to assess fungal diversity, composition, enzyme activities, and co-occurrence networks. The restoration method significantly affected soil fungal α-diversity and β-diversity in the experimental solar park. Specifically, at each recovery site, soil depth showed significant effect on fungal α-diversity. However, on a fine scale, artificial restoration significantly increased fungal species richness across soil depths. Ascomycota dominated across different sites, followed by Basidiomycota and Mucoromycota. Shared core genera Fusarium, Mortierella, and Geminibasidium were determined in both recovery sites. Sucrase/phenol oxidase (natural) and catalase/sucrase (artificial) were identified as key fungal drivers according to Random Forest models. Co-occurrence analysis suggested neither artificial restoration nor natural restoration has attained the level of natural habitats. Networks of artificial subsoil and natural topsoil were closest to natural habitat. These results emphasize the impact of restoration and PV shading on fungal communities via spatial heterogeneity and enzyme dynamics during initial recovery stage, providing insights for semi-arid ecosystem management under PV development. Full article

This study investigates a Solar Air Heating Façade (SAHF), architecturally enhanced through the integration of granular translucent Silica-Aerogel into multi-wall polycarbonate (PC) panels and the implementation of coated timber lamellas. The novelty of this work lies in the combined evaluation of thermal resistance and solar transmission properties of façade-integrated components, aiming to improve both energy efficiency and architectural integration. Two experimental campaigns were conducted: (i) thermal transmittance tests to determine the U-value of PC panels with and without Silica-Aerogel infill, and (ii) solar transmission measurements under controlled artificial solar radiation to evaluate the optical performance of various lamella configurations and coatings. Results show that the incorporation of Silica-Aerogel reduced the U-value by 41.8%, achieving a minimum of 1.19 W/m² K with the 20 mm thick PC panel, while decreasing the solar transmission of 43–53% depending on the incidence angle. The integration of reflective aluminum-coated timber lamella demonstrated promising results, enabling effective management of solar radiation. These findings highlight the potential of façade systems that combine high-performance insulation with visually integrated shading elements. Full article

The accumulation of photoassimilates in the sinks during the grain filling stage is affected by the conditions of the various source organs. This study was conducted to investigate changes in various source and sink organs when the flag leaves and spikes were shaded from heading to harvest in wheat. Shading the flag leaves increased chlorophyll content and chlorophyll fluorescence in the uppermost leaves by 34.9% and 0.3% in 2022 and 75.3% and 3.3% in 2023, respectively, maintaining a relatively high photosynthetic rate from heading to the mid-grain filling stage. However, shading the spikes had a more substantial negative impact on spike growth than the flag leaf shading. On the other hand, the uppermost leaves continued to serve as a source more actively even when the flag leaves were shaded, implying a compensating effect. At 35 days after treatment (DAT), the relative water content (RWC) of the spike in the spike shading (SS) treatment was 19.4% and 49.7% higher than that of the control in 2022 and 2023, respectively. However, grain weight in the SS treatment decreased by 39.7% in 2022 and 5.3% in 2023 compared with the control. In the flag leaf shading (FS) treatment, grain weight declined by 3.5% and 6.2% in 2022 and 2023, respectively. These results indicate that the reduction in grain weight due to shading was less pronounced in the SS treatment than in the FS and combined flag leaf and spike shading (FSS) treatments. The results suggest that spikes play a buffering role when assimilate-transport functions decline in the source organs. Our results provide a better understanding of the architectural properties, including flag leaf, spike, and the uppermost leaf, for photosynthetic contribution to grain filling in wheat. Also, identifying target characteristics for improving photosynthetic source organs will be valuable for developing wheat varieties with high yield stability. Full article

Understanding the impact of hydric stress on medicinal plants in the context of climate change is becoming increasingly important. This study aimed to assess the quality of a seed lot of Agastache mexicana subsp. mexicana (Amm) through a novel calculation of the Vigour Index on time basis (${VI}_T$). The evaluation was based on relationships among plant height, leaf number, survival time, and plant density across six irrigation regimes, referred to as stages, which differed in the timing and quantity of water, designed to impose water stress from seedling emergence until plant death. To maximise growth and survival time, we utilised two input factors: Artificial Shade Levels (ASLs) of 38%, 87%, and 94%, as well as Silicon Dioxide Levels (SDLs) of 0.0%, 0.2%, 0.4%, and 0.8%. The effects of these treatments were measured using the Survival Index (SI) and the ${VI}_T$. The plants achieved their highest SI and ${VI}_T$ values influenced by minimum mortality and maximum height and leaf number in stage three. This behaviour aligned with the field capacity of the substrate, supporting the evaluation of stages one and two as waterlogging stress, while the remaining stages were classified as drought stress. The ${VI}_T$ results showed statistically significant effects from ASL, particularly at 94%. However, the ${VI}_T$ in relation to SDL was not statistically significant. The ${VI}_T$ measurements were visualised using spline interpolation, a method that provides an effective approach to quantify adverse conditions affecting Amm’s development and that it can support to identify the hydric stresses type. Full article

Agroforestry systems offer clear environmental and agronomic advantages, but their effect on plant–biotic stressor interactions remains poorly understood. Specifically, the shade from companion trees can create microclimates favorable to fungal diseases on herbaceous crops. This potential drawback may offset other benefits, highlighting the urgent need for advanced plant health monitoring in these systems. This study assessed the potential of hyperspectral reflectance to detect the single and combined effects of simulated tree shading and infection by the fungal pathogen Alternaria alternata on grain sorghum (Sorghum bicolor L. Moench) under rainfed field conditions. Sorghum was grown either under full light or 50% shading conditions. Half of the plots were artificially inoculated with an A. alternata spore suspension (2 × 10⁸ CFU mL⁻¹), while the others served as controls. Leaf and ground-canopy measurements were acquired with a full range spectroradiometer (VNIR-SWIR, 400–2,400 nm) and UAV imagery covered the VIS-NIR range (400–1,000 nm) before the onset of visible symptoms. Permutational multivariate analysis of variance of leaf and ground-canopy data revealed significant effects of shading (Sh), infection (Aa), and their interaction (p < 0.05), allowing early detection of infection two days before symptom appearance, while UAV data showed only singular significant effects. Partial least squares discriminant analysis accuracy reached 78% at the leaf level, 90% at the ground-canopy level, and 74% (Sh) and 75% (Aa) at the UAV scale. Furthermore, vegetation spectral indices derived from the spectra confirmed greater physiological stress in shaded and infected plants, consistent with disease incidence assessments. Our results establish scale-specific hyperspectral reflectance spectroscopy as a powerful, non-destructive technique for early plant health surveillance in agroforestry. This advanced optical sensing capability is poised to illuminate complex stressor interactions, marking a significant step forward for precision agroforestry management. Full article

Background and Objectives: The rapid increase of whitening products use raises questions about enamel safety. We compared three high-concentration protocols—Opalescence Quick (45% carbamide peroxide ≈ 15% H₂O₂), Opalescence Boost (40% H₂O₂), and BlancOne Ultra (35% H₂O₂ + LED)—under controlled conditions to balance color change (ΔE) with enamel integrity (microhardness, FTIR). We also constructed a qualitative cytotoxicity risk profile from published data; no biological assays were performed in this study. Methods: Seventy-two matched half-crowns were randomized to Control or one of the three protocols. Outcomes were a change in Vickers microhardness, spectrophotometric color difference, and FTIR carbonate-to-phosphate ratio after 24 h in artificial saliva. We also compiled a qualitative cytotoxicity risk profile from published evidence; no biological assays were performed. One-way ANOVA with Tukey HSD on Δ-scores, Shapiro–Wilk and Levene’s tests for assumptions, Welch’s t-tests for tooth-class comparisons, and Pearson correlation between ΔE and ΔMH. Results: All active protocols produced clearly visible whitening (mean ΔE 5.7–6.3). Hydrogen-peroxide gels showed greater hardness loss and carbonate depletion than the carbamide-peroxide gel under similar contact time. The association between greater shade change and hardness loss was moderate and not predictive for individuals. Conclusions: Under harmonized conditions, all systems whitened effectively. Pursuing changes beyond ~6 units offered little extra benefit while increasing enamel impact. Carbamide-based Opalescence Quick achieved comparable aesthetics with lower acute enamel effects. Clinicians should individualize exposure time and pair in-office whitening with short-term remineralising care. Cytotoxicity comments are qualitative and literature-based only. Full article

Canada goldenrod (Solidago canadensis L.), a short-day plant commonly cultivated as a cut flower, depends on proper lighting management to obtain long stems and higher commercial value. Thus, this study aimed to determine the effect of modifying the light spectrum through the installation of light-emitting diodes (LEDs) and the use of colored shade nets on the production and quality of Canada goldenrod stems. The treatments used were colored shade nets and different LED lighting treatments. Production per plant and productivity per square meter were determined. Twenty stems were selected and evaluated for: stem length; inflorescence length and width; number of floral ramets per inflorescence; number of leaves; stem base diameter (mm); and fresh stem biomass (g). Canada goldenrod plants require an extension of the light period with artificial lighting to produce higher-quality stems, regardless of whether the bulbs emit red or white light. The use of nets with 50% red and white shading promoted higher production and elongation of Canada goldenrod stems, with a production that reached up to 4.2 floral stems per plant and 100.3 floral stems per square meter using the red shade net and white LED. These floral stems were of high commercial standard, with a length of up to 81.35 cm with the red shade net and red LED, and were 31 cm in diameter for the inflorescences, approximately, under black or white shade nets and white or red LEDs. More robust floral stems with greater biomass were observed using any shade net color and LED lamps. Full article

The yellowing effect of camphorquinone (CQ) has led manufacturers to add alternative initiators into resin composites (RCs) to reduce the amount of CQ used. The aim of this study was to investigate the color change in commercial RCs with alternative photoinitiators besides CQ. Color change upon polymerization and aging in air and artificial saliva for up to 3 months was tested for seven commercial RCs (traditional and bulk-fill) with either CQ only or CQ and additional photoinitiators (CQ+). Color measurements were obtained with a spectrophotometer. Color change (ΔE) was calculated using the CIELab and CIEDE2000 formulae. ANOVA and a post hoc SNK test were conducted for statistical analysis. Upon polymerization, the ΔE of CQ+ was greater than that of CQ only, except in the case of dual-cure HyperFIL. The storage conditions did not affect the color change within 24 h for either air or artificial saliva, whereas they did have an influence on color stability when RCs were aged for 1 month and 3 months. The color changes in the RCs aged in artificial saliva were considered clinically acceptable for all RCs tested except HyperFIL. Additional photoinitiator systems tended to result in a greater color change upon polymerization but did not affect color change upon aging. During shade selection, especially when additional photoinitiators besides CQ are used, a guide reflecting the color after polymerization should be used. Full article

Plants can sense light signals using specific photoreceptors, activating light signaling pathways to precisely regulate photomorphogenesis and shade-avoidance responses. This study examines the molecular responses of Arabidopsis thaliana to the CoeLux^® lighting system, a unique LED-based light source designed to simulate natural sunlight. Previous studies found that the CoeLux^® light type, characterized by a higher blue-to-green ratio and reduced blue light levels, stimulates responses in plants comparable to those displayed in shade conditions. This research compared the effects of CoeLux^® lighting to conventional high-pressure sodium (HPS) lamps, focusing on the expression of critical photomorphogenesis-related genes under both long- and short-term light treatments. Lower HY5 and elevated HFR1 expression levels were observed under the CoeLux^® light type and low-intensity light conditions. On the contrary, the influence of the CoeLux^® light type on COP1 and PIFs expression levels seems more marginal. These responses suggest a complex regulation involving both gene expression and protein-level adjustments. Additionally, mutant plants lacking these essential regulatory genes displayed altered morphologies under CoeLux^® light, underscoring the functional contribution of these genes in the adaptation to light. Our findings are twofold, advancing the understanding of plant–light relationships and plant adaptation to artificial light environments. These may foster strategies for optimizing indoor plant growth under simulated sunlight conditions. Full article

Partial shading in photovoltaic (PV) systems causes multiple local maximum power points (LMPPs), complicating tracking and reducing energy efficiency. Conventional maximum power point tracking (MPPT) methods, such as Perturb and Observe (P&O), often fail because of oscillations and entrapment at local maxima. To address these shortcomings, this study proposes a hybrid MPPT strategy combining artificial neural networks (ANNs) and the P&O algorithm to enhance tracking accuracy under partial shading while maintaining implementation simplicity. The research employs a detailed PV cell model in MATLAB/Simulink (2019b) that incorporates dynamic shading to simulate non-uniform irradiance. Within this framework, an ANN trained with the Levenberg–Marquardt algorithm predicts global maximum power points (GMPPs) from voltage and irradiance data, guiding and accelerating subsequent P&O operation. In the hybrid system, the ANN predicts the maximum power points (MPPs) to provide initial estimates, after which the P&O fine-tunes the duty cycle optimization in a DC-DC converter. The proposed hybrid ANN–P&O MPPT method achieved relative improvements of 15.6–49% in tracking efficiency, 16–20% in stability, and 14–54% in convergence speed compared with standalone P&O, depending on the irradiance scenario. This research highlights the potential of ANN-enhanced MPPT systems to maximize energy harvest in PV systems facing shading variability. Full article

The urban thermal environment poses a significant challenge to public health and sustainable urban development. Conventional pre-defined classification schemes, such as the Local Climate Zone (LCZ) system, often fail to capture the highly heterogeneous structure of complex urban areas, thus limiting their applicability. This study introduces a novel framework for urban thermal environment analysis, leveraging multi-source data and eXplainable Artificial Intelligence to investigate the driving mechanisms of Land Surface Temperature (LST) across various urban form types. Focusing on the area within Beijing’s 5th Ring Road, this study employs a K-Means clustering algorithm to classify urban blocks into nine distinct types based on their building morphology. Subsequently, an eXtreme Gradient Boosting (XGBoost) model, coupled with the SHapley Additive exPlanations (SHAP) method, is utilized to analyze the non-linear impacts of ten selected driving factors on LST. The findings reveal that: (1) The Compact Mid-rise type exhibits the highest annual average LST at 296.59 K, with a substantial difference of 11.29 K observed between the hottest and coldest block types. (2) SHAP analysis identifies the Normalized Difference Built-up Index (NDBI) as the most significant warming factor across all types, while the Sky View Factor (SVF) plays a crucial cooling role in high-rise areas. Conversely, road density (RD) shows a negative correlation with LST in Open Low-rise areas. (3) The influence of urban form is twofold: increased building height (BH) can induce warming by trapping heat while simultaneously providing a cooling effect through shading. (4) The impact of land use functional zones on LST is significantly modulated by urban form, with temperature differences of up to 2 K observed between different functional zones within compact block types. The analytical framework proposed herein holds significant theoretical and practical implications for achieving fine-grained thermal environment governance and fostering sustainable development in the context of global urbanization. Full article

Cities need photovoltaic (PV) systems to meet climate-neutral goals, yet dense urban forms and variable weather limit their output. This review synthesizes how machine learning (ML) models capture both static factors (orientation, roof, and façade geometry) and dynamic drivers (irradiance, transient shading, and meteorology) to predict and optimize urban PV performance. Following PRISMA 2020, we screened 111 records and analyzed 61 peer-reviewed studies (2020–2025), eight Horizon-Europe projects, as well as market reports. Deep learning models—mainly artificial and convolutional neural networks—typically reduce the mean absolute error by 10–30% (median ≈ 15%) compared with physical or empirical baselines, while random forests support transparent feature ranking. Short-term irradiance variability and local shading are the dominant dynamic drivers; roof shape and façade tilt lead the static set. Industry evidence aligns with these findings: ML-enabled inverters and module-level power electronics increase the measured annual yields by about 3–15%. A compact meta-analysis shows a pooled correlation of r ≈ 0.966 (R² ≈ 0.933; 95% CI 0.961–0.970) and a pooled log error ratio of −0.16 (≈15% relative error reduction), with moderate heterogeneity. Key gaps remain, such as limited data from equatorial megacities, sparse techno-economic or life-cycle metrics, and few validations under heavy soiling. We call for open datasets from multiple cities and climates, and for on-device ML (Tiny Machine Learning) with uncertainty reporting to support bankable, city-scale PV deployment.” Full article