Search Results (1,851)

Coccocypselum lanceolatum is a tropical, perennial, creeping, herbaceous C3 plant species that is found in deeply shaded humid forests. This species has potential for medicinal and culinary uses. Knowledge about this species and other herbaceous Rubiaceae is confined to phytocoenological and morpho-anatomical studies. Here, it was hypothesized that (1) leaf gas exchange dynamics over a one-year period in C. lanceolatum are related to light conditions, phenology and environmental seasonal changes; (2) photosynthetic performance is focused on enhanced carbon gains through a high leaf net assimilation rate (A_net) relative to light availability, a low dark respiration rate (R_d) and a light compensation point (LCP); and (3) these parameters will vary over leaf age. The photosynthetic photon flux density (PPFD), characterizing the growth and development of C. lanceolatum, was reduced to 4–11% of incoming light in the open area, while the red-to-far-red light ratio (R:FR) was reduced from 1.15 to mean diurnal values of 0.45–0.81, depending on forest canopy dynamics. Leaf gas exchange parameters [A_net, stomatal conductance (g_s), leaf transpiration (E), and intrinsic water use efficiency (iWUE)] were observed over a one-year period. A_net, g_s, and E were correlated with energy factors (PPFD and air temperature) during vegetative growth, while only iWUE showed a correlation with leaf gas exchange parameters during blooming and fruiting, indicating that seasonality and phenology were additional drivers of leaf gas exchange. As a deep-shade forest species, C. lanceolatum displayed low iWUE (3–21 μmol m⁻² s⁻¹) and was adapted to maximize carbon gain and prioritize high g_s rather than water economy. The extremely low LCP (4.2 μmol m⁻² s⁻¹), low R_d (0.2 to 0.43 μmol m⁻² s⁻¹), maximum net photosynthesis (A_max, 5 μmol m⁻² s⁻¹), and apparent quantum efficiency of CO₂ assimilation (Φ of 0.04 µmol µmol⁻¹) were adaptational traits of this species for low light. Finally, the A_net, g_s, E, iWUE, gross photosynthesis under light saturation, R_d, LCP, and light saturation point values were different when comparing young and adult leaves. The ecophysiological responses over a one-year period shown here could assist in the success of C. lanceolatum as a sustainable soil-cover plant in shaded areas. Full article

Indoor Air Quality (IAQ) monitoring, especially in multi-zone smart buildings, is typically limited by the high computational and energy requirements of continuous sensor processing, which makes event-driven methods desirable for efficiency. Energy proportionality, in this context, refers to a system whose computational cost scales with the significance of detected environmental changes rather than with the fixed sampling rate. This paper presents a spike-driven neuromorphic sensing framework for decentralized IAQ monitoring that combines adaptive Kalman filter preprocessing, dynamic threshold-based asynchronous spike encoding, and a Leaky Integrate-and-Fire neural network with Spike-Timing-Dependent Plasticity (STDP) learning. Multiple-parameter IAQ data including PM₁, PM_2.5, PM₁₀, CO₂, CO, TVOCs, and O₃ were sampled from nine functionally differing zones of an educational building in Metro Manila, Philippines. The neuromorphic model yielded a mean Sparse Firing Ratio of 10.94%, a Mean Response Time of 10.62 timesteps, and an energy efficiency proxy score of 9.28. Neuron population scaling and parameter robustness analyses revealed that the four neurons per parameter were enough to saturate the performance, and FLOP-based estimation indicated an 8.9-fold computational reduction (approximately 89% fewer FLOPs) compared to LSTM inference. In addition, the revised Performance Efficiency Index and composite efficiency score corroborated the stable and energy-proportional nature of behavior in all zones. These results illustrate that spike-based neuromorphic computation is an energy-efficient and scalable way for decentralized smart-building IAQ monitoring, though hardware-level validation on dedicated neuromorphic processors remains necessary for absolute power saving verification. Multi-seed validation (five seeds) with expanded baselines including GRU, Temporal CNN, XGBoost, and Logistic Regression confirmed the robustness and repeatability of reported metrics. Full article

Background/Objectives: Cardiovascular disease (CVD) burden decreased in the North Africa and Middle East (NAME) region between 1990 and 2019. This study used Global Burden of Disease (GBD) 2023 data to examine whether trends in mortality, disability-adjusted life years (DALYs), incidence, and prevalence continued through 2023 across all 21 NAME countries. Methods: We analysed age-standardised CVD mortality, incidence, prevalence, and DALY rates from 1990 to 2023. Joinpoint regression identified changes in temporal trends and calculated the annual percent change (APC) and average annual percent change (AAPC) with 95% confidence intervals (CIs). Results: Age-standardised CVD mortality decreased from 579.6 per 100,000 in 1990 to 358.2 in 2023 (AAPC: −1.42%; 95% CI: −1.48 to −1.35). However, no significant reduction occurred between 2019 and 2023 (APC: −0.33%; 95% CI: −1.37 to 1.75). DALY, incidence, and prevalence rates followed similar patterns, with no significant decline in the final years of this study. Egypt was the only country with a long-term increase in CVD mortality, which accelerated after 2020 (APC: +5.20%; 95% CI: 1.20 to 12.87). High systolic blood pressure, dietary risks, lead exposure, and air pollution were the leading modifiable risk factors. Conclusions: The earlier decline in CVD burden in the NAME region did not clearly continue after 2019. The region is currently off track to meet Sustainable Development Goal 3.4 by 2030. Future progress may depend on improved blood pressure control, lipid management, dietary habits, and environmental risk reduction. Full article

Climate projections indicate significant changes in temperature patterns and other meteorological parameters under different climate change scenarios, with temperature receiving special attention due to its influence on thermal conditions and human discomfort. This study examines the relationship between diurnal temperature range (DTR) and thermal discomfort in the five largest cities of Greece during summer. Thermal discomfort is assessed using Thom’s discomfort index (DI), where values ≥ 21 indicate the onset of thermal discomfort, focusing on thermal conditions at the upper (DI_h) and lower (DI_c) boundaries of daily variability. The analysis uses multiple CMIP6 projections for the reference period (1981–2010) and the near future (2031–2060) under the SSP2-4.5 and SSP5-8.5, representing intermediate and high greenhouse gas forcing pathways, respectively. The study aims to investigate associations between DTR and DI-based thermal discomfort. DTR is projected to increase in most cities in the near future relative to the reference period. This reflects a regional specific response that differs from the global tendency reported in the literature for minimum air temperatures (T_min) to increase faster than maximum air temperatures (T_max). Effect size analysis of DTR indicates generally small effects in Thessaloniki, medium to large effects in Larissa depending on the scenario, and large effects in Heraklion, Athens and Patra. Projected differences in DTR are consistent with the asymmetrical response of air temperature, specifically to the higher increase rate in T_max than in T_min in most cities. DI-based thermal discomfort shows a clear contrast between upper (DI_h) and lower (DI_c) boundaries of daily variability, reflected in higher discomfort classes for DI_h and lower classes for DI_c. Higher DTR values are associated with higher DI_h-based thermal discomfort, while the corresponding association between DTR and DI_c is weak or absent. The positive association observed for the DI_h-based conditions is largely governed by the shared contribution of T_max to both DTR and the discomfort index, whereas the absent or weak association for DI_c-based conditions may reflect the weaker association between DTR and T_min as well as the relatively smaller variability of T_min. Full article

In this study, hexagonal titanium dioxide nanotubes (hTNTs) fabricated by sonoelectrochemical anodization were thermally modified in air to investigate the influence of annealing temperature and heating/cooling rate on phase evolution, structural stability and electrochemical behavior. The samples were annealed at 450 °C, 550 °C, and 650 °C for 2 h using heating/cooling rates of 6 °C/min, 10 °C/min, and 20 °C/min. The hexagonal nanotubular morphology remained preserved after thermal treatment. However, increasing annealing temperature and heating/cooling rate promoted crack formation due to the thermally induced stress relaxation and phase transformation. The anatase content increased with increasing heating/cooling rate, indicating kinetically limited anatase-to-rutile transformation, whereas annealing at 650 °C promoted partial rutile formation. Electrochemical studies demonstrated that annealing temperature and heating/cooling rate affected the electrochemical behavior of hTNTs through different mechanisms. Increasing annealing temperature promoted structural ordering and partial anatase-to-rutile transformation, leading to reduced current response and enhanced electrochemical stability. In contrast, heating/cooling rate significantly affected impedance behavior and diffusion-related processes, indicating changes in charge transfer kinetics and ion transport within the nanotubular oxide layer. The results demonstrate that thermal treatment kinetics play an important role in controlling the phase composition and electrochemical behavior of hTNTs, providing insight into the thermal optimization of hexagonal TiO₂ nanotubes for advanced functional applications. Full article

The growing share of intermittent renewable electricity has increased the need for long-duration storage in industrial energy systems. Meanwhile, many industrial processes still release recoverable low-grade waste heat. Introducing this heat into pumped thermal energy storage (PTES) can improve thermal integration, but industrial waste heat is often unsteady, and its temperature and mass flow fluctuations may disturb the charging process. This study investigates an air-based reverse Brayton PTES system assisted by an industrial hot-water waste heat stream of approximately 100 °C. A dynamic model was developed in Simulink/Simscape. The shaft speed is fixed at 3000 rpm, and a PID controller regulates the molten-salt flow rate to maintain the thermal storage temperature. The results show that increasing the waste heat temperature from 95 °C to 105 °C mainly changes the charging-side heat distribution. The waste heat utilization power increases from 36.0 MW to 37.9 MW, while the regenerator power decreases from 126.8 MW to 122.0 MW. The thermal storage power increases slightly from 117.0 MW to 119.0 MW, with the mechanical input fixed at 81.0 MW. The influence of waste heat temperature is concentrated near the low-temperature heat exchanger, regenerator, and turbine outlet. Under dynamic disturbances, faster temperature ramps increase short-term deviations, but the PID-based molten-salt flow regulation keeps the storage temperature close to 550 °C, indicating that the proposed control strategy can suppress moderate thermal disturbances during charging. When waste heat temperature and mass flow rate vary together, same-direction changes strengthen the disturbance, whereas opposite-direction changes partly offset it. These results clarify the disturbance propagation mechanism of fluctuating industrial waste heat in the PTES charging loop and provide a basis for the dynamic design and temperature-control strategy of waste-heat-assisted PTES systems. Full article

This study analyzes surface air temperature (SAT) trends at 158 stations located on or above the Arctic Circle over the 2000–2024 period, aiming to assess whether recent temperature shifts could serve as indirect indicators of a slowing Atlantic Meridional Overturning Circulation (AMOC). Regression analysis reveals that only 40% of stations show statistically significant warming trends (p < 0.05), while 33% exhibit no significant trend. Applying the Pettitt and Buishand tests, we detect abrupt regime shifts at 38 stations, with breakpoints concentrated between 2009 and 2014. Notably, 36 of these stations display a weakening of the warming trend after the breakpoint: at 13 stations (including key Arctic archipelagos and the White Sea coast), an initial increase shifts to a decrease; at 17 stations, warming continues but at a slower rate; and at 6 stations (near the Bering Strait), a decrease intensifies. These spatial patterns suggest a potential fingerprint of AMOC slowdown, consistent with recent modeling studies that predict cooling in northwestern Europe and possible Little Ice Age-type environmental conditions. Our findings have implications for assessing future Arctic navigation, coastal infrastructure, and resource extraction under changing climate regimes. Full article

With increasing constraints on extensive farming—including soil degradation, salinisation and more frequent climatic anomalies—the development of ‘smart’ agriculture requires the integration of affordable, non-invasive methods for monitoring the physiological state of plants. A key indicator for assessing productivity and the early detection of stress is the rate of photosynthetic CO₂ assimilation (A); however, widely available commercial gas analysers are characterised by high cost, technical complexity and considerable weight, which limits their use in large-scale field studies. Here, a new handheld system for measuring assimilation was developed and tested, based on the accumulative principle of recording changes in CO₂ concentration using simple infrared sensors and without maintaining a constant air flow around the leaf. A comparison was carried out between a prototype of the developed system and a commercial gas analyser when measuring leaf assimilation under irrigation and simulated drought conditions. The results demonstrated the consistency of the readings from the two systems. The developed system is characterised by its compact size, low cost, and the absence of moving parts and consumables. The proposed system has the potential to be effective for large-scale screening tasks and rapid diagnosis of stress-induced changes; it represents a promising, affordable tool for addressing applied tasks in precision agriculture, environmental monitoring and physiological research. Full article

This study investigates the influence of PFAS-free superhydrophobic treatment on the performance of NYCO (50% Nylon 50% Cotton) fabric. The primary focus is to assess how these treatments influence key performance attributes, including water repellency, weight gain, air permeability, and color stability. The treatments were formulated using a silica/epoxy diluted with isopropanol (IPA), with the goal of achieving minimal weight gain (<10%) and high water repellency (AATCC22 rating of 80 or above) with a minimal impact on breathability and visual appearance. A series of formulations were prepared with a a constant silica to epoxy ratio (3:7) while varying the solids content of the suspension (1.8 to 5.2 wt.%). Treated fabrics were evaluated through water spray tests (AATCC TM 22), air permeability (ASTM D737), spectrophotometric color analysis, and SEM surface morphology. Samples treated with a formulation containing 2.0 wt.% solids content demonstrated the best performance characteristics: low weight gain, minimal breathability reduction, low color change, and water repellency. The findings reveal the potential for a PFAS-free treatment to achieve high water repellency while maintaining other key fabric performance characteristics. The results contribute to the advancement of sustainable, high-performance protective textiles for military applications. Full article

To address heat accumulation, localized hot spots, and non-uniform temperature distribution in large-capacity lithium iron phosphate energy storage battery modules under high ambient temperature and high-rate charge/discharge conditions, this study proposes a fin-enhanced phase change material (PCM)-air hybrid thermal management structure for a 100 Ah prismatic lithium iron phosphate battery and a 2P18S energy storage battery module. First, the battery thermal model is validated using single-cell experimental data reported in the literature. Subsequently, a three-dimensional transient fluid–solid coupled heat transfer model is established by considering transient battery heat generation, PCM solid–liquid phase change, air-side flow and heat transfer, and temperature-dependent thermophysical properties. User-defined functions are employed to implement the transient heat source and temperature-dependent material properties. Under identical boundary conditions, the thermal management performances of three configurations, namely Fin-Air, PCM-Air, and Fin-PCM-Air, are compared. The effects of ambient temperature (20 °C, 25 °C, and 30 °C) and inlet air velocity (1 m/s, 2 m/s, and 3 m/s) on the maximum module temperature, temperature uniformity, PCM liquid fraction evolution, and flow field distribution are quantitatively analyzed. The results show that, compared with the Fin–Air system without PCM and the PCM-Air system without fins, the Fin-PCM-Air configuration reduces the maximum module temperature by 1.57% and 0.25%, respectively, at an ambient temperature of 30 °C and an inlet air velocity of 3 m/s. After four charge–discharge cycles, the peak maximum temperature of the module is approximately 38.56 °C, and the peak maximum temperature difference remains below 3.6 K, indicating good temperature uniformity and latent heat buffering capability. In addition, the air velocity trade-off analysis indicates that increasing the inlet air velocity can improve cooling performance but also increases the air-channel pressure drop and fan power consumption. Therefore, the Fin-PCM-Air structure is more suitable for high-thermal-load conditions, and its practical application should comprehensively consider cooling benefits, additional mass, manufacturing cost, and long-term reliability. This study provides a reference for the design and engineering application of hybrid thermal management structures for large-capacity energy storage battery modules. Full article

Anaerobic digestion is a viable pathway to mitigate environmental impacts from swine manure in tropical regions while contributing to circular economy strategies. However, no standardized or integrated framework currently exists that simultaneously quantifies the closure of energy, material, carbon, nutrient, and water loops at the farm scale. This research presents the techno-economic design and environmental assessment of a covered, mechanically agitated lagoon biodigester for a 10,000-head swine fattening module located in Matanzas, Cuba. The system is sized by integrating hydraulic, thermal, and structural parameters, and its economic viability is assessed through Net Present Value (NPV = $1.09 million), Internal Rate of Return (IRR = 32%), and a payback period of approximately three years. A comparative screening-level life cycle assessment shows that biogas-based electricity generation substantially reduces impacts on climate change, air quality, and fossil fuel scarcity compared with conventional diesel-based generation, with trade-offs in eutrophication and ecotoxicity. As a key methodological contribution, five quantitative circular economy indicators are proposed and calculated: the Energy Self-Sufficiency Ratio (ESSR = 1.71), the Waste Valorization Index (WVI = 0.91), the Decarbonization Index (DCI = 6.7), the Fertilizer Substitution Rate (FSR = 16.3 t N year⁻¹), and the Water Closure Factor (WCF = 1.30). These indicators show that the system achieves a 71% net energy surplus, valorizes over 90% of the input mass, avoids 6.7 times more emissions than it generates, replaces synthetic fertilizers, and returns more water than it consumes. The findings provide quantitative evidence that the convergence of mesophilic operation without auxiliary heating, high carbon intensity of the power grid, and availability of agricultural land enhances circularity performance in tropical covered lagoon bioreactors, and the proposed integrated indicator framework, aligned with ISO 59020:2024, provides a reproducible and transferable methodological basis for the comparative assessment of anaerobic digestion systems for livestock waste. Full article

Solar chimneys represent an effective passive ventilation technology capable of improving indoor thermal comfort while reducing building energy consumption. In this study, the thermal and fluid dynamic performance of a solar chimney integrated into a residential building located in Bordj Bou Arréridj (Eastern Algeria) was investigated through a comprehensive numerical, predictive, and optimization framework. A transient mathematical model was developed to evaluate the influence of key geometric parameters, including chimney width and inlet opening width, as well as environmental factors such as solar radiation intensity and wind speed, on the system performance. The generated simulation database was subsequently employed to develop and compare four machine learning models, namely, Artificial Neural Networks with Bayesian Regularization (ANN-BR), Deep Neural Networks optimized by Improved Grey Wolf Optimization (DNN-IGWO), k-Nearest Neighbors (KNN), and Extreme Gradient Boosting (XGBoost), for predicting eight output parameters including glazing temperature, fluid temperature, absorber temperature, outlet temperature, thermal efficiency, air change rate (ACH), mass flow rate, and outlet velocity. The results demonstrated that increasing chimney and inlet widths significantly enhances ventilation performance by increasing airflow rate and ACH. Weather conditions and wind speed were also found to strongly affect thermal efficiency and buoyancy-driven airflow. Among the predictive models, XGBoost and DNN-IGWO exhibited the highest predictive accuracy, achieving coefficients of determination ($R^2$) close to unity and very low prediction errors for all output variables, confirming their robustness and generalization capability. The proposed methodology provides a reliable tool for rapid performance prediction and design optimization of solar chimney systems under different climatic and operating conditions, thereby supporting the development of energy-efficient passive ventilation strategies for residential buildings. Full article

In this paper, the influence of voltage change rate on the process of steep pulse air discharge is studied under an environment of 7000 m atmospheric pressure. Six sets of nanosecond pulses with different voltage change rates are used, and the initial and breakdown gaps of the streamer are analyzed by numerical simulation and ICCD imaging. The results show that when the voltage change rate is large, the electric field develops rapidly, which can promote the early formation of the streamer. However, if the effective duration of the pulse is too short and the voltage duration is insufficient, the streamer cannot develop further, and partial breakdown occurs. As the voltage change rate decreases and the pulse width increases, the streamer is more likely to form a through channel, and the discharge penetration time decreases first and then increases. The experimental and simulation results are consistent. In the low-pressure environment, the pulse leading edge variation characteristics are more sensitive to the formation of streamers, which has a reference value for the gap insulation and pulse withstand voltage design of high-altitude electrical equipment. Full article

Background/Objectives: Obesity remains difficult to treat effectively, not because weight loss cannot be achieved, but because it is difficult to sustain in the face of physiological adaptations to energy restriction, including reductions in resting metabolic rate and loss of fat-free mass. Dietary strategies that preserve favorable body composition while supporting long-term adherence are therefore needed. The purpose of this study was to compare continuous caloric restriction (CCR) with an intermittent approach incorporating structured diet refeeds and planned diet breaks (DRF) on body composition outcomes in adult women with obesity. Methods: Thirty adult females (18–65 years; BMI 30–45 kg·m⁻²) were randomized to 12 weeks of CCR or DRF following a two-week maintenance phase used to determine individualized caloric needs. Both groups were prescribed a 25% caloric deficit and protein intake of 1.2 g·kg⁻¹·day⁻¹. Body composition, including body fat percentage, fat mass, and fat-free mass, was assessed using air-displacement plethysmography at baseline and post-intervention. Results: Repeated-measures ANOVA revealed a significant main effect of time for body fat percentage (p < 0.001), which decreased by 6.7 ± 2.1% in the CCR group and 6.0 ± 1.9% in the DRF group, with no significant group × time interaction (p > 0.05). Fat mass significantly declined in both groups (p < 0.001), with reductions of 9.30 ± 2.77 kg (CCR) and 9.21 ± 2.63 kg (DRF); between-group differences were negligible (p > 0.05; Cohen’s d = 0.03). Fat-free mass increased over time (p < 0.05); although the interaction was not significant (p = 0.08), the DRF group demonstrated a moderate effect size advantage. Despite similar changes in body composition, analysis of energy balance revealed a significantly greater daily energy deficit in the CCR group compared with DRF (−1005 ± 515 vs. −690 ± 120 kcal·day⁻¹, p = 0.041), indicating a higher achieved level of caloric restriction in CCR. Conclusions: Both dietary strategies effectively reduced fat mass in females with obesity; however, incorporating diet breaks was associated with a nonsignificant trend toward greater preservation or accrual of fat-free mass without compromising fat loss. Future studies should investigate this potential association in larger, adequately powered trials before any conclusions regarding metabolic adaptation or practical advantage can be drawn. Full article

This study implements a Data Envelopment Analysis (DEA) under both input- and output-orientation specifications to measure tourism technical eco-efficiencies and changes in total factor productivity for Eurozone countries from 1996 to 2019. Instead of employing hotel-specific measures or traditional proxies like length of stay or occupancy rate, this study relies on the heterogeneous nature of tourism, namely business and leisure tourism spending, distinguishing between international and domestic visits. Despite their significance for capturing the macroeconomic dynamics of tourism and interactions with the environment, this set of variables is rarely reported in the relevant literature. Efficiency and productivity scores are subsequently examined within a panel regression framework to evaluate the role of renewable energy adoption. The slack analysis reveals input excess and desirable output shortfalls, indicating structural inefficiencies in resource allocation and production performance. Regression findings suggest that the impact of renewables on tourism efficiency and productivity is regime-dependent, while panel causality tests evidence the neutrality hypothesis. The results underscore the need to improve air quality, resource allocation mechanisms, enhance sustainable sector-specific productivity strategies, and accelerate renewable transition policies. Full article