Search Results (3,621)

Though the pursuit of sustainable desalination processes with high water recovery has intensified the research interest in membrane distillation (MD), the influence of module connection configuration on performance stability remains poorly explored. The current study provided a comprehensive multiparameter assessment of hollow fibre membrane modules connected in parallel and series in direct contact membrane distillation (DCMD) for the first time. The configurations were evaluated under varying process parameters such as temperature (50–70 °C), flow rates (22.1–32.3 mL·s⁻¹), magnesium concentration as scalant (1.0–4.0 g·L⁻¹), and flow direction (co-current and counter-current), assessing their influence on temperature gradients (∆T), flux and pH stability, salt rejection, and crystallisation. Interestingly, the parallel module configuration maintained high operational stability with uniform flux and temperature differences (∆T) even at high recovery factors (>75%). On one hand, the serial configuration experienced fluctuating ∆T caused by thermal and concentration polarisation, causing an early crystallisation (abrupt drop in feed conductivity). Intensified polarisation effects with accelerated crystallisation increased the membrane risk of wetting, particularly at high recovery factors. Despite these changes, the salt rejection remained relatively high (99.9%) for both configurations across all tested conditions. The findings revealed that acidification trends caused by MgSO₄ were configuration-dependent, where the parallel setup-controlled rate of pH collapse. This study presented a novel framework connecting membrane module architecture to mass and heat transfer phenomena, providing a transformative DCMD module configuration design in water desalination. These findings not only provide the critical knowledge gaps in DCMD module configurations but also inform optimisation of MD water desalination to achieve high recovery and stable operation conditions under realistic brine composition. Full article

The synthesis of “green ammonia” from “green hydrogen” represents a critical pathway for renewable energy integration and industrial decarbonization. This study investigates the green ammonia synthesis process using an axial–radial fixed-bed reactor equipped with three catalyst layers. A simplified two-dimensional physical model was developed, and a multiscale simulation approach combining computational fluid dynamics (CFD) with physics-informed neural networks (PINNs) employed. The simulation results demonstrate that the majority of fluid flows axially through the catalyst beds, leading to significantly higher temperatures in the upper bed regions. The reactor exhibits excellent heat exchange performance, ensuring effective preheating of the feed gas. High-pressure zones are concentrated near the top and bottom gas outlets, while the ammonia mole fraction approaches 100% near the bottom outlet, confirming superior conversion efficiency. By integrating PINNs, the prediction accuracy was substantially improved, with flow field errors in the catalyst beds below 4.5% and ammonia concentration prediction accuracy above 97.2%. Key reaction kinetic parameters (pre-exponential factor k₀ and activation energy Ea) were successfully inverted with errors within 7%, while computational efficiency increased by 200 times compared to traditional CFD. The proposed CFD–PINN integrated framework provides a high-fidelity and computationally efficient simulation tool for green ammonia reactor design, particularly suitable for scenarios with fluctuating hydrogen supply. The reactor design reduces energy per unit ammonia and improves conversion efficiency. Its radial flow configuration enhances operational stability by damping feed fluctuations, thereby accelerating green hydrogen adoption. By reducing fossil fuel dependence, it promotes industrial decarbonization. Full article

Discovering, analyzing, and finding a key to understanding the physiological and biochemical responses that Vitis vinifera L. undertakes against drought stress is of fundamental importance for this profitable crop. Today’s considerable climatic fluctuations force researchers and farmers to focus on this issue with solutions inclined to respect the ecosystem. In this academic work, we focused on describing the drought stress consequences on several parameters of secondary metabolites on Vitis vinifera leaves (quercetins, kaempferol, resveratrol, proline, and xanthophylls) and on some ecophysiological characteristics (e.g., water potential, stomatal conductance, and leaf temperature) to compare the answers that diverse agronomic management techniques (i.e., irrigation with and without zeolite, pure zeolite and no application) could instaurate in the metabolic pathway of this important crop with the aim to find convincing and thought-provoking responses to use this captivating and versatile mineral, the zeolite known as the “magic rock”. Stressed grapevines reached 56.80 mmol/m²s gs at veraison and a more negative stem Ψ (+10.63%) compared to plants with zeolite. Resveratrol, in the hottest season, fluctuated from 0.18–0.19 mg/g in zeolite treatments to 0.37 mg/g in stressed vines. Quercetins were inclined to accumulate in response to drought stress too. In fact, we recorded a peak of quercetin (3-O-glucoside + 3-O-glucuronide) of 11.20 mg/g at veraison in stressed plants. It is interesting to note how the pool of metabolites was often unchanged for plants treated with zeolite and for plants treated with water only, thus elevating this mineral to a “stress reliever”. Full article

Carassius auratus exhibits significant physiological and behavioral alterations under the combined stress of temperature and dissolved oxygen (DO) fluctuations, which are common challenges in aquaculture. In this investigation, we employed controlled thermal and DO gradients to characterize the multidimensional response profile of this species. The key findings revealed that thermal elevation profoundly influenced blood glucose and cortisol concentrations. Notably, exposure to hyperoxic conditions markedly attenuated stress responses relative to hypoxia at equivalent temperatures: cortisol levels were significantly suppressed (reductions of 60.11%, 118.06%, and 34.72%), while blood glucose levels exhibited concurrent increases (16.42%, 26.43%, and 26.34%). Distinctive behavioral patterns, including floating head behavior, surface swimming behavior, and rollover behavior, were identified as indicative behaviors of thermal–oxygen stress. Molecular analysis demonstrated the upregulated expression of stress-associated genes (HSP70, HSP90, HIF-1α, and Prdx3), which correlated temporally with elevated cortisol and glucose concentrations and the manifestation of stress behaviors. Furthermore, a muscle texture assessment indicated that increased DO availability mitigated the textural deterioration induced by heat stress. Collectively, this work establishes an authentic biomarker framework, providing crucial threshold parameters essential for the development of intelligent, real-time environmental monitoring and dynamic regulation systems to enhance climate-resilient aquaculture management. Full article

The process of urbanization has intensified the urban heat environment, with the degradation of thermal conditions closely linked to the morphological characteristics of different functional zones. This study delineated urban functional areas using a multivariate dataset and investigated the seasonal and threshold effects of landscape and architectural features on land surface temperature (LST) through boosted regression tree (BRT) modeling and Spearman correlation analysis. The key findings are as follows: (1) LST exhibits significant seasonal variation, with the strongest urban heat island effect occurring in summer, particularly within industry, business, and public service zones; residence zones experience the greatest temperature fluctuations, with a seasonal difference of 24.71 °C between spring and summer and a peak temperature of 50.18 °C in summer. (2) Fractional vegetation cover (FVC) consistently demonstrates the most pronounced cooling effect across all zones and seasons. Landscape indicators generally dominate the regulation of LST, with their relative contribution exceeding 45% in green land zones. (3) Population density (PD) exerts a significant, seasonally dependent dual effect on LST, where strategic population distribution can effectively mitigate extreme heat events. (4) Mean building height (MBH) plays a vital role in temperature regulation, showing a marked cooling influence particularly in residence and business zones. Both the perimeter-to-area ratio (LSI) and frontal area index (FAI) exhibit distinct seasonal variations in their impacts on LST. (5) This study establishes specific indicator thresholds to optimize thermal comfort across five functional zones; for instance, FVC should exceed 13% in spring and 31.6% in summer in residence zones to enhance comfort, while maintaining MBH above 24 m further aids temperature regulation. These findings offer a scientific foundation for mitigating urban heat waves and advancing sustainable urban development. Full article

Parametric changes in the first coordination shell (FCS) of a vitreous metallic Pd_42.5Cu₃₀Ni_7.5P₂₀ alloy are analysed, aiming to confirm the identification of the glass transition temperature (T_g) via processing of XRD patterns utilising radial and pair distribution functions (RDFs and PDFs) and their evolution with temperature. The Wendt–Abraham empirical criterion of glass transition and its modifications are confirmed in line with previous works, which utilised the kink of the temperature dependences of the minima and maxima of both the PDF and the maxima of the structure factor S(q). Massive fluctuations are, however, identified near the T_g of the derivatives of the minima and maxima of the PDF and maxima of S(q), which adds value to understanding the glass transition in the system as a true second-order-like phase transformation in the non-equilibrium system of atoms. Full article

This study investigates the effectiveness of passive design in low-rise residential buildings located in arid desert climates, using the Dubai Solar Decathlon Middle East (SDME) competition as a case study. This full-scale experiment offers a unique opportunity to evaluate design solutions under controlled, realistic conditions; prescriptive, modeled performance; and monitored performance assessments. The prescriptive assessment reviews geometry, orientation, envelope thermal properties, and shading. Most houses adopt compact forms, with envelope-to-volume and envelope-to-floor area ratios averaging 1 and 3.7, respectively, and window-to-wall ratios of approximately 17%, favoring north-facing openings to optimize daylight while reducing heat gain. Shading is strategically applied, horizontal on south façades and vertical on east and west. The thermal properties significantly exceed the local code requirements, with wall performance up to 80% better than that mandated. The modeled assessment uses Building Energy Models (BEMs) to simulate the impact of prescriptive measures on energy performance. Three variations are applied: assigning minimum local code requirements to all the houses to isolate the geometry (baseline); removing shading; and applying actual envelope properties. Geometry alone accounts for up to 60% of the variation in cooling intensity; shading reduces loads by 6.5%, and enhanced envelopes lower demand by 14%. The monitored assessment uses contest-period data. Indoor temperatures remain stable (22–25 °C) despite outdoor fluctuations. Energy use confirms that houses with good designs and airtightness have lower cooling loads. Airtightness varies widely (avg. 14.5 m³/h/m²), with some well-designed houses underperforming due to construction flaws. These findings highlight the critical role of passive design as the first layer for improving the energy performance of the built environment and advancing toward net-zero targets, specifically in arid desert climates. Full article

To further enhance the economic performance of fuel cell vehicles (FCVs), this study develops a model-adaptive model predictive control (MPC) strategy. This strategy leverages the dynamic relationship between proton exchange membrane fuel cell (PEMFC) output characteristics and temperature to track its optimal operating temperature (OOT), addressing challenges of temperature control accuracy and high energy consumption in the PEMFC thermal management system (TMS). First, PEMFC and TMS models were developed and experimentally validated. Subsequently, the PEMFC power–temperature coupling curve was experimentally determined under multiple operating conditions to serve as the reference trajectory for TMS multi-objective optimization. For MPC controller design, the TMS model was linearized and discretized, yielding a predictive model adaptable to different load demands for stack temperature across the full operating range. A multi-constrained quadratic cost function was formulated, aiming to minimize the deviation of the PEMFC operating temperature from the OOT while accounting for TMS parasitic power consumption. Finally, simulations under Worldwide Harmonized Light Vehicles Test Cycle (WLTC) conditions evaluated the OOT tracking performance of both PID and MPC control strategies, as well as their impact on stack efficiency and TMS energy consumption at different ambient temperatures. The results indicate that, compared to PID control, MPC reduces temperature tracking error by 33%, decreases fan and pump speed fluctuations by over 24%, and lowers TMS energy consumption by 10%. These improvements enhance PEMFC operational stability and improve FCV energy efficiency. Full article

There has been growing interest in constructing mid- and high-rise wooden buildings in recent years. To ensure the feasibility of these structures, it is necessary to provide evidence that their long-term reliability can be guaranteed. While long-term testing is typically necessary, a continuous monitoring system for the moisture content of wood materials used in buildings has been proposed as an alternative. The proposed method measures the change in the local moisture content using the equilibrium moisture content calculated from the temperature and humidity measured using temperature and humidity sensors. The study used Japanese cypress specimens with dimensions of 50 mm, 75 mm, and 100 mm cubes and Douglas fir specimens of 50 mm cubes. The moisture content was measured under various external environments. Results showed that this system effectively captured changes in local moisture content, reflecting fluctuations in temperature and humidity in a controlled thermo-hygrostat over a three-day moisture absorption environment (20 °C, 95% humidity). Additionally, it was observed that higher moisture content levels yielded correspondingly higher local moisture content measurements compared to those obtained using the oven-drying method. Full article

Urochloa brizantha (Brizantha) is cultivated under varying altitudinal and management conditions. Twelve full-sun (monoculture) plots and twelve shaded (silvopastoral) plots were established, proportionally distributed at 170, 503, 661, and 1110 masl. Evaluations were conducted 15, 30, 45, 60, and 75 days after establishment. The conservation and integration of trees in silvopastoral systems reflected a clear anthropogenic influence, evidenced by the preference for species of the Fabaceae family, likely due to their multipurpose nature. Although the altitudinal gradient did not show direct effects on soil properties, intermediate altitudes revealed a significant role of CaCO₃ in enhancing soil fertility. These edaphic conditions at mid-altitudes favored the leaf area development of Brizantha, particularly during the early growth stages, as indicated by significantly larger values (p < 0.05). However, at the harvest stage, no significant differences were observed in physiological or productive traits, nor in foliar chemical components, underscoring the species’ high hardiness and broad adaptation to both soil and altitude conditions. In Brizantha, a significant reduction (p < 0.05) in stomatal size and density was observed under shade in silvopastoral areas, where solar radiation and air temperature decreased, while relative humidity increased. Nonetheless, these microclimatic variations did not lead to significant changes in foliar chemistry, growth variables, or biomass production, suggesting a high degree of adaptive plasticity to microclimatic fluctuations. Foliar ash content exhibited an increasing trend with altitude, indicating greater efficiency of Brizantha in absorbing calcium, phosphorus, and potassium at higher altitudes, possibly linked to more favorable edaphoclimatic conditions for nutrient uptake. Finally, forage quality declined with plant age, as evidenced by reductions in protein, ash, and In Vitro Dry Matter Digestibility (IVDMD), alongside increases in fiber, Neutral Detergent Fiber (NDF), and Acid Detergent Fiber (ADF). These findings support the recommendation of cutting intervals between 30 and 45 days, during which Brizantha displays a more favorable nutritional profile, higher digestibility, and consequently, greater value for animal feeding. Full article

Fungi, from saprophytes to pathogens, face predictable daily fluctuations in light, temperature, humidity, and nutrient availability. To cope, they have evolved an internal circadian clock that confers a major adaptive advantage. This review critically synthesizes current knowledge on the molecular architecture and physiological relevance of fungal circadian systems, moving beyond the canonical Neurospora crassa model to explore the broader phylogenetic diversity of timekeeping mechanisms. We examine the core transcription-translation feedback loop (TTFL) centered on the FREQUENCY/WHITE COLLAR (FRQ/WCC) system and contrast it with divergent and non-canonical oscillators, including the metabolic rhythms of yeasts and the universally conserved peroxiredoxin (PRX) oxidation cycles. A central theme is the clock’s role in gating cellular defenses against oxidative, osmotic, and nutritional stress, enabling fungi to anticipate and withstand environmental insults through proactive regulation. We provide a detailed analysis of chrono-pathogenesis, where the circadian control of virulence factors aligns fungal attacks with windows of host vulnerability, with a focus on experimental evidence from pathogens like Botrytis cinerea, Fusarium oxysporum, and Magnaporthe oryzae. The review explores the downstream pathways—including transcriptional cascades, post-translational modifications, and epigenetic regulation—that translate temporal signals into physiological outputs such as developmental rhythms in conidiation and hyphal branching. Finally, we highlight critical knowledge gaps, particularly in understudied phyla like Basidiomycota, and discuss future research directions. This includes the exploration of novel clock architectures and the emerging, though speculative, hypothesis of “chrono-therapeutics”—interventions designed to disrupt fungal clocks—as a forward-looking concept for managing fungal infections. Full article

The Solar Agro Savior (SAS) is an innovative solution that is assisted by drones for the sustainable utilization of water and plant disease observation in the agriculture sector. This system integrates an alerting mechanism for humidity, moisture, and temperature variations, which affect the plants’ health and optimization in water utilization, which enhances plant yield productivity. A significant feature of the system is the efficient monitoring system in a larger region through drones’ high-resolution cameras, which enables real-time, efficient response and alerting for environmental fluctuations to the authorities. The machine learning algorithm, particularly recurrent neural networks, which is a pioneer with agriculture and pest control, is incorporated for intelligent monitoring systems. The proposed system incorporates a specialized form of a recurrent neural network, Long Short-Term Memory (LSTM), which effectively addresses the vanishing gradient problem. It also utilizes an attention-based mechanism that enables the model to assign meaningful weights to the most important parts of the data sequence. This algorithm not only enhances water utilization efficiency but also boosts plant yield and strengthens pest control mechanisms. This system also provides sustainability through the re-utilization of water and the elimination of electric energy through solar panel systems for powering the inbuilt irrigation system. A comparative analysis of variant algorithms in the agriculture sector with a machine learning approach was also illustrated, and the proposed system yielded 99% yield accuracy, a 97.8% precision value, 98.4% recall, and a 98.4% F1 score value. By encompassing solar irrigation and artificial intelligence-driven analysis, the proposed algorithm, Solar Argo Savior, established a sustainable framework in the latest agricultural sectors and promoted sustainability to protect our environment and community. Full article

Aquatic vegetation plays a crucial role in freshwater ecosystems by providing habitats, regulating water quality, and supporting biodiversity. This study aims to monitor and analyze the dynamics of aquatic vegetation in Chimaditida Shallow Lake, Greece, using Sentinel-2 satellite imagery, with validation from field measurements. Data processing was performed using Google Earth Engine and QGIS. The study focuses on discriminating and mapping two classes of aquatic surface conditions: areas covered with Floating and Emergent Aquatic Vegetation and open water, covering all seasons from 1 March 2024, to 28 February 2025. Spectral bands such as B04 (red), B08 (near infrared), B03 (green), and B11 (shortwave infrared) were used, along with indices like the Modified Normalized Difference Water Index and Normalized Difference Vegetation Index. The classification was enhanced using Otsu’s thresholding technique to distinguish accurately between Floating and Emergent Aquatic Vegetation and open water. Seasonal fluctuations were observed, with significant peaks in vegetation growth during the summer and autumn months, including a peak coverage of 2.08 km² on 9 September 2024 and a low of 0.00068 km² on 28 December 2024. These variations correspond to the seasonal growth patterns of Floating and Emergent Aquatic Vegetation, driven by temperature and nutrient availability. The study achieved a high overall classification accuracy of 89.31%, with producer accuracy for Floating and Emergent Aquatic Vegetation at 97.42% and user accuracy at 95.38%. Validation with Unmanned Aerial Vehicle-based aerial surveys showed a strong correlation (R² = 0.88) between satellite-derived and field data, underscoring the reliability of Sentinel-2 for aquatic vegetation monitoring. Findings highlight the potential of satellite-based remote sensing to monitor vegetation health and dynamics, offering valuable insights for the management and conservation of freshwater ecosystems. The results are particularly useful for governmental authorities and natural park administrations, enabling near-real-time monitoring to mitigate the impacts of overgrowth on water quality, biodiversity, and ecosystem services. This methodology provides a cost-effective alternative for long-term environmental monitoring, especially in regions where traditional methods are impractical or costly. Full article

Global climate change is causing increasing fluctuations in winter temperatures, including episodes of warm conditions above 9 °C. Such events disrupt cold acclimation in plants and can induce deacclimation, reducing frost tolerance and altering, among other things, hormonal regulation. This study investigated hormonal and molecular changes associated with cold acclimation and deacclimation in oilseed rape (Brassica napus L.) cultivars Kuga and Thure. Plants were grown under different conditions: non-acclimated (17 °C for three weeks), cold-acclimated (4 °C for three weeks), and deacclimated (16/9 °C day/night for one week). Detailed hormone analysis included auxins, gibberellins, cytokinins, stress-related hormones, and the expression of hormone-related genes (BnABF2, BnAOS, BnARF1, BnARR6, BnICS1, BnRGA, and BnWRKY57). Hormone concentrations in leaves changed dynamically in response to deacclimation with increased amounts of growth-promoting hormones and decreased amounts of stress hormones. Additionally, alterations in gene expression during deacclimation, such as in BnABF2 and BnICS1, may function as protective mechanisms to help maintain or regain frost tolerance during reacclimation when temperatures decline again after the warm period. These findings improve the understanding of hormonal and molecular responses involved in the deacclimation of oilseed rape. Full article

Articulated arm coordinate measuring machines are designed for in situ use directly in manufacturing environments, enabling efficient dimensional control outside of climate-controlled laboratories. This study investigates the influence of ambient temperature variation on the accuracy of length measurements performed with the Hexagon Absolute Arm 8312. The experiment was carried out in a laboratory setting simulating typical shop floor conditions through controlled temperature changes in the range of approximately 20–31 °C. A calibrated steel gauge block was used as a reference standard, allowing separation of the influence of the measuring system from that of the measured object. The results showed that the gauge block length changed in line with the expected thermal expansion, while the articulated arm coordinate measuring machine exhibited only a minor residual thermal drift and stable performance. The experiment also revealed a constant measurement offset of approximately 22 µm, likely due to calibration deviation. As part of the study, an uncertainty budget was developed, taking into account all relevant sources of influence and enabling a more realistic estimation of accuracy under operational conditions. The study confirms that modern carbon composite articulated arm coordinate measuring machines with integrated compensation can maintain stable measurement behavior even under fluctuating temperatures in controlled environments. Full article