Search Results (833)

The increasing use of silver nanoparticles (AgNPs) as nanoagrochemicals raises important environmental and toxicological considerations of their usage. AgNPs influence soil microbiome functioning, which regulates essential nutrient availability. However, their effects on key chemical soil health indicators remain unclear, with existing studies limited to concentrations ≥10-fold above predicted environmental levels. The aim of the work was to evaluate the effect of AgNPs at a realistic concentration of 10 μg/kg on the principal chemical soil health indicators, including acidity, redox potential, electrical conductivity, contents of NPK, and soil organic carbon (SOC). In addition, dissolved organic carbon and nitrogen (DOC and DON) and water-extractable elements (Al, Ca, Fe, K, Mg, Na, P, S, and Si) were also examined. The laboratory experiment was carried out for 3 months on Retisol, Chernozem, and Solonetz. AgNPs stabilised with carboxymethylcellulose (AgNP-CMC) or polyvinylpyrrolidone (AgNP-PVP) were used. AgNP-induced changes exhibited non-monotonic patterns, peaking at 2–3 months of incubation. A statistically significant effect observed across all soils following AgNPs application included only increased water-extractable Fe. In addition, AgNPs increased nitrate content 1.1–1.4-fold in Retisol and Chernozem, while available phosphorus increased 1.4-fold in Solonetz. However, changes were transient, indicating no pronounced long-term impact on soil properties. Partial Least Square (PLS) analysis revealed that chemical soil health indicators and water-extractable elements do not reliably discriminate between control soils and soils amended with AgNPs. Although our study shows that AgNPs had neither markedly negative nor positive effects on chemical soil health indicators or water-extractable element contents, future research should prioritise field trials. Model experiments under optimised microbial activity conditions limit direct extrapolation to field scenarios. Full article

Background: Radio Electric Asymmetric Conveyer (REAC) neurobiological modulation is proposed as an approach designed to interact with endogenous bioelectrical processes involved in cortical regulation. However, its electrophysiological correlates in physiologically preserved neural systems remain insufficiently characterized. The present study explored whether a standardized REAC Brain Wave Optimization Gamma (BWO-G_B) protocol is associated with measurable changes in resting-state EEG activity in healthy adults. Methods: Nine neurologically healthy participants completed a standardized REAC BWO-G_B protocol consisting of 18 sessions administered over six consecutive days. Resting-state EEG recordings were obtained before and after the intervention. Spectral power was analyzed across the 1–100 Hz range. Multivariate organization of cortical activity was explored using Principal Component Analysis (PCA) and Canonical Discriminant Analysis (CDA), with CDA used only as a descriptive visualization of within-dataset multivariate organization. Cross-correlation analysis was applied to evaluate changes in inter-regional temporal synchronization. Individual-level non-parametric testing (Wilcoxon signed-rank test) was conducted only to characterize within-subject directional spectral modulation across the recorded montage. Results: Post-intervention EEG recordings showed a consistent redistribution of spectral power across cortical regions, predominantly within frequencies below approximately 20 Hz. This pattern was observed across subjects at the individual level. Multivariate analysis revealed a dissociation between PCA, which showed partial overlap between conditions, and CDA, which descriptively showed within-dataset separability between baseline and post-intervention cortical states. Cross-correlation analysis indicated a spatially differentiated redistribution of temporal synchronization across cortical regions. At the individual level, descriptive Wilcoxon analyses indicated broadband spectral differences in seven of nine participants (p < 0.05), with consistent directional trends across all subjects; these p-values should not be interpreted as confirmatory statistical evidence. Conclusions: The findings indicate the presence of a reproducible electrophysiological pattern observed after completion of the REAC BWO-G_B protocol in healthy adults. The observed combination of spectral redistribution, descriptive multivariate organization, and changes in temporal synchronization is consistent with a structured post-intervention modification of cortical activity organization within the present dataset. However, given the exploratory design, small sample size, absence of a control condition, and absence of objective vigilance monitoring, these results should be interpreted cautiously and should not be considered as evidence of intervention-specific effects. Further controlled studies are required to determine specificity, underlying mechanisms, and potential functional relevance. Full article

Soil nematodes are integral to soil micro-food webs and serve as sensitive bioindicators of soil ecological condition. However, how forest vegetation and soil properties interact to shape nematode community assembly, network structure, and functional stability remains inadequately understood. Using 18S rRNA gene amplicon sequencing coupled with phylogenetic null modeling, we examined soil nematode communities across four forest types along a succession gradient. Although taxonomic diversity (e.g., Shannon and Pielou indices) differed significantly among forest types, network topology and stochastic assembly processes were more closely associated with community restructuring and co-occurrence patterns. This suggests that, while diversity is not irrelevant, network- and assembly-based metrics provide complementary and often more sensitive indicators of nematode community responses to forest type. Co-occurrence network analysis revealed that mixed forests fostered more complex and potentially stable networks, whereas plantations formed dense but potentially vulnerable networks. Assembly processes were not dominated by strong deterministic selection (|βNTI| ≤ 2 for most comparisons), a pattern consistent with undominated processes (e.g., ecological drift, weak environmental filtering). Dispersal limitation played a negligible role in this system. Partial Least Square Path Modeling identified spatial factors and key soil properties (e.g., pH, electrical conductivity, soil water content, and organic carbon) as primary drivers of community structure. Our findings indicate that assessing soil food web health should integrate network analysis and stochasticity metrics rather than rely solely on taxonomic diversity. For sustainable forest management, mixed-species stands are preferable to monoculture plantations, and maintaining soil physicochemical heterogeneity is critical for community stability. Full article

Background/Objectives: Functional near-infrared spectroscopy (fNIRS) has emerged as a non-invasive, implant-compatible imaging modality capable of capturing cortical hemodynamics during ecologically valid auditory and linguistic tasks. Its silent operation and tolerance to electrical artifacts make it particularly well suited to the study of hearing-impaired individuals, including cochlear implant (CI) users. However, evidence on the application of fNIRS to investigate speech perception, cognitive performance, and proxy of cortical activation patterns in patients with hearing loss (HL) remains fragmented. This systematic review aims to provide a structured, population-stratified description of current fNIRS literature on auditory and cognitive processing in adults with age-related hearing loss (ARHL) and CI users. Methods: A systematic search on PubMed Central, Web of Science and Scopus, based on PRISMA (2020) guidelines, was conducted to identify original studies that evaluate speech perception by means of fNIRS to assess auditory and cognitive process in hearing-impaired populations. Results: Across studies, fNIRS consistently detected activation of superior temporal and frontal cortices during speech-related tasks. In ARHL, increased dorsolateral prefrontal cortex (DLPFC) recruitment during speech-in-noise indicated compensatory yet inefficient processing. Longitudinal auditory training led to reduced prefrontal overactivation and enhanced temporal–frontal connectivity. In CI users, cortical responses to phonological and comprehension tasks show partially overlapping activation patterns with normal hearing (NH) peers, although arising within different neurobiological contexts, and are modulated by device experience and residual hearing (AV) speech, and stimulus-level effects further shape cortical responses. When interpreted in light of developmental evidence, these findings may be contextualized as reflecting distinct trajectories of cortical reorganization, rather than a common mechanism. Conclusions: fNIRS provides a tool to investigate auditory and cognitive responses in distinct hearing-impaired populations under ecologically valid conditions. It detects maladaptive frontal inefficiency in ARHL, tracks neuroplastic changes after rehabilitation, and captures population-specific cortical recruitment patterns in CI users. These findings are descriptive and context-dependent, and do not support cross-population mechanistic generalizations. Standardized protocols and longitudinal pediatric studies are needed to clarify the potential clinical relevance of fNIRS-derived cortical measures. Full article

Modern electric vehicle (EV) charging stations must increase their adaptability to dynamic demand patterns driven by users’ heterogeneous charging behaviors, which often result in high spatial–temporal fluctuations. This study develops an agent-based model to accurately evaluate the potential of partial-charging strategy in addressing this issue, taking into account the influence of drivers’ heterogeneous waiting patience. The simulating results indicate that the operational efficiency of the charging station and the level of crowding are most sensitive to changes in vehicle arrival rates and the total number of charging stations. However, individual-level heterogeneity in waiting patience emerges as the core factor preventing limitless queuing increase. Compared with other strategies, the partial-charging strategy improves the turnover of charging stations by reducing per-vehicle charging duration, allowing stations to adapt to varying charging demand conditions without capacity expansions. Setting the charging threshold at 80% state of charge allows the stations to efficiently serve twice the demand level as under full-charging strategy, while a 70% threshold may increase this adaptability by approximately 2.5 times. This study provides structured recommendations for the strategic and adaptive deployment of the partial-charging strategy in alleviating queue-related inefficiencies of charging stations. Full article

This study evaluated spatial and seasonal patterns of physicochemical water quality in the Chiriquí Viejo River basin (western Panama), a tropical watershed characterized by strong seasonal variability. A total of 90 water samples were collected at ten stations during the rainy season (May to October 2024) and dry season (January to March 2025). Dissolved oxygen (DO), turbidity, potential of hydrogen (pH), apparent color, total dissolved solids (TDS), and electrical conductivity (EC) were analyzed following ISO/IEC 17025:2017 accredited methods, and precipitation patterns were characterized using spatial interpolation of meteorological data. Spatio-temporal variability was assessed using linear mixed-effects models, with season and basin position as fixed effects and sampling site as a random factor. Results showed a spatial and seasonal structuring of water quality, with the upper basin exhibiting high and stable DO concentrations and low turbidity and apparent color. In contrast, the middle and lower basin showed rainy-season increases in turbidity and apparent color, supported by a significant season × basin interaction, indicating that precipitation driven impacts are heterogeneous along the basin. EC and TDS displayed spatial gradients, while DO remained relatively stable across seasons and basin levels. These findings highlight turbidity and apparent color as sensitive indicators of precipitation-driven impacts. Full article

Hydrogen energy, owing to its advantages of low-carbon cleanliness, long-term storage capacity, and multi-energy coupling potential, has emerged as a crucial medium for enhancing renewable energy accommodation within integrated energy systems. However, the pronounced heterogeneity in hydrogen load behaviors, temporal characteristics, and regulation capabilities poses significant challenges for unified modeling approaches, which struggle to accurately capture the multi-modal regulation potential of hydrogen demand, thereby limiting the precision of system operation optimization. To address this issue, this paper proposes a data-driven hydrogen load flexibility modeling method for integrated energy system (IES) operation optimization. A hybrid LSTM-ISODATA framework is designed to extract deep temporal dependencies and identify six representative hydrogen consumption patterns from typical load sequences. Each hydrogen load category is decomposed into shiftable, transferable, and reducible flexible forms, and a category-specific time-varying flexibility constraint matrix is established to characterize differentiated regulation capabilities. An electricity–heat–hydrogen integrated energy system operation optimization model embedded with classified flexible hydrogen loads is developed and solved via mathematical programming. Simulation results show that the proposed method reduces system operating costs by 10.3% compared with conventional unified modeling, while significantly promoting renewable energy utilization and system operational flexibility. The effectiveness and engineering applicability of the proposed model in IES optimal scheduling are fully validated. Full article

This study investigates the time-periodic electroosmotic flow and solute transport of Maxwell fluid in a parallel microchannel with modulated surface charges. The Poisson–Boltzmann equation and the linearized momentum equations are solved using a superposition-based analytical approach. The influences of oscillation intensity, fluid elasticity, and electrokinetic parameters on the velocity and concentration distributions are examined. The results show that wall-potential modulation combined with a time-periodic electric field generates recirculating motion and oscillatory velocity patterns. Moderate oscillation strengthens both flow and solute transport, whereas stronger oscillation weakens transport efficiency. This work provides a quantitative analysis the interplay between oscillatory electroosmotic flow and solute transport in Maxwell fluid and clarifies the role of oscillation strength in controlling solute dispersion. Full article

This study presents a Bayesian framework for estimating electric vehicle (EV) conversion rates based on average daily vehicle kilometers traveled (ADVKT) in South Korea. Although maximizing the environmental benefits of EVs requires accounting for real-world driving patterns and vehicle usage, the current EV policies in South Korea largely focus on supply expansion and uniform subsidy schemes, with limited consideration of driver behavioral heterogeneity. Using 2023 national vehicle travel statistics and regional-level data, the study applies a Bayesian approach to estimate the posterior probability of EV conversion by ADVKT based on the ADVKT distributions of internal combustion engine vehicles (ICEVs) and EVs, with the overall EV conversion rate serving as the prior probability. The results reveal distinct conversion trends by vehicle type, usage, and region. Non-commercial passenger cars show peak conversion potential in the 70–75 km/day range across all regional classifications, supporting the feasibility of nationwide policies. In contrast, commercial vehicles (e.g., vans and trucks) exhibit more varied patterns, indicating the need for targeted approaches. A simulation-based validation demonstrates that the estimated conversion probabilities closely align with the observed distribution of EVs. These findings provide empirical guidance for distance-based EV subsidy design, charging infrastructure planning, and strategic vehicle targeting in South Korea’s transition to low-emission transport. Full article

Laser-induced graphene (LIG) is a porous carbon material produced in situ by direct laser irradiation of carbon-containing precursors. With its three-dimensional porous structure, high electrical conductivity, facile patternability, low cost, and environmentally friendly fabrication, LIG has attracted growing interest for flexible sensing applications. It shows strong potential in wearable electronics, health monitoring, human–machine interaction, environmental sensing, and intelligent robotics. Although LIG-based sensors have demonstrated excellent performance in mechanical and thermal signal detection, a systematic review of their basic materials, formation mechanisms, sensing principles, structural design, performance optimization, and applications remains limited. This review first summarizes the fundamental materials, processing parameters, and formation principles of LIG, and then highlights recent progress in LIG-based strain and temperature sensors, focusing on sensing mechanisms, key performance indicators, optimization strategies, and research status. The main challenges for practical application are also discussed. These include limited material uniformity and fabrication reproducibility, signal coupling and interference in multifunctional devices, and issues of process compatibility and packaging reliability. Future directions for high-performance, integrated, and scalable LIG sensors are then. Full article

The increasing competition for land between agriculture and electricity generation has driven the implementation agrivoltaic systems (AVSs) as a strategy aligned with Sustainable Development Goals 7 and 13. This study systematically analyzes how AVS design influences agricultural yield (AY), energy yield (EY), and overall sustainability. A systematic review was conducted following the PRISMA protocol, complemented by bibliometric analysis and an exploratory correlation analysis of design variables, productivity indicators, and environmental and economic metrics. From an initial set of 243 records, 79 studies published between 2018 and 2025 were included. The results identify general trends across heterogeneous studies, although these patterns should not be interpreted as universally applicable. Intermediate ground cover ratios (GCRs) (≈30–40%) are commonly associated with favorable trade-offs between AY and EY, often resulting in land equivalent ratios above 1.5 under specific conditions. Reported outcomes indicate that AVS can achieve increases in EY, improvements in water-use efficiency, reductions in CO₂ emissions, and competitive economic performance, although these results vary depending on crop type, climate, system configuration, and PV technology. Overall, the analysis highlights GCR as a key design parameter and underscores that AVS performance depends on multivariable and context-specific design rather than universally applicable thresholds, reinforcing its potential as a sustainable agri-energy solution. Full article

Analysis of Estates Return Information Collection (ERIC) 2018/19–2024/25 data for 1104 acute NHS hospital sites in England found persistently high energy use intensity (EUI), averaging 211 kWh/m² in 2024/25, with total acute-sector energy use of 9.99 billion kWh, with approximately 75% derived from gas. Longitudinal trends indicated relatively stable EUI despite portfolio growth. Cross-sectional exploratory analyses for 2024/25 showed that clinical floor area share (mean 59%) exhibited the strongest observed association with EUI (r = 0.52, R² = 0.27), followed by gross internal area (r = 0.39, R² = 0.15) and backlog intensity (r = 0.23). Associations between building age cohorts and EUI were generally weak or negligible, except for a weak positive association for 1985–94 buildings (r = 0.064) and a moderate negative association for 2005–14 buildings (r = −0.126). Among the decarbonization and operational indicators examined, renewable electricity fraction showed the strongest bivariate association with EUI (R² = 0.224), followed by water intensity (R² = 0.101), gas share (R² = 0.085), LED coverage (R² = 0.027), climate incidents (R² = 0.020), and waste intensity (R² = 0.004). Sites with heat decarbonization plans, high LED coverage, or heat pump installations tended to exhibit higher EUI values alongside differing renewable electricity uptake patterns, potentially reflecting the prioritization of interventions at more energy-intensive facilities. Overall, the findings suggest that hospital energy intensity is associated with functional mix, estate characteristics, and decarbonization-related indicators, although these relationships should be interpreted as exploratory associations rather than independent causal effects. The study provides a national-scale exploratory benchmarking assessment intended to inform future multivariable and longitudinal research on NHS estate decarbonization strategies. Full article

Marine controlled source electromagnetic (CSEM) surveys have been proven to be an effective tool in hydrocarbon exploration, principally due to the method’s ability (in the right circumstances) to identify electrical resistivity contrasts between hydrocarbon-saturated and brine-saturated sedimentary units. However, the sensitivity of such surveys decreases in shallow water, for deeper targets, and for targets with limited horizontal extent. In principle, the resolution and sensitivity of a survey can be improved by moving either the transmitting or the receiving dipoles into the sub-surface. We have therefore investigated the sensitivity of Seafloor to Borehole CSEM (sbCSEM) survey geometries, specifically for the case of simplified targets with small lateral dimensions in shallow water areas—including targets whose depth of burial substantially exceeds their lateral extent. The results are encouraging. Neither small target size nor shallow water presents obstacles in principle to the use of this approach. Our models reveal distinct lobes in the patterns of electric field and current density amplitudes around a sub-seafloor transmitting dipole. The shape, positions and amplitudes of these lobes are all strongly modified by the presence of one or more small resistive targets, and they are strongly influenced by the positions of target edges. These effects significantly modify the pattern of electric fields at the seafloor and hence result in good sensitivity for realistic survey geometries. Small targets can be detected by seafloor receivers when the sub-seafloor transmitting dipole is located at some distance laterally outside the targets—leading to potential applications in ‘step-out’ prospecting. The asymmetry of responses at the seafloor from targets that are offset with respect to transmitter location has potential applications in field appraisal, while monitoring of reservoirs during production provides another possible application. Varying the depth of the transmitter down the borehole generates a Vertical EM Profiling (VEMP) survey—analogous to Vertical Seismic Profiling (VSP)—and we demonstrate that this too can have useful applications. Modelling for deeper (3 km sub-seafloor) targets continues to yield encouraging results and suggests that step-out sbCSEM may be effective at depths beyond the detection limit of conventional seafloor–seafloor CSEM. Full article

Artificial lighting accounts for roughly 30% of total electricity use in supermarkets and significantly affects product perception, customer experience, and purchasing behavior. Increasing the availability of natural light, combined with appropriate architectural energy retrofitting strategies, offers a major opportunity to reduce electricity demand. This study proposes a data-driven framework for evaluating energy retrofit strategies in commercial buildings, integrating Building Information Modeling (BIM) and Building Energy Modeling (BEM). A parametric methodology is used to evaluate multiple architectural retrofitting scenarios aimed at enhancing daylighting and reducing artificial lighting demand, while improving energy efficiency and environmental performance. The scenarios investigated include variations in skylight geometry and orientation, glazing type, photovoltaic integration, and advanced lighting controls. Three Key Performance Indicators (KPIs)—real energy effectiveness, lighting control performance, and environmental impact—are used to assess how design modifications influence energy use, indoor lighting quality, and environmental performance. The methodology is applied to three real food-retail buildings in Italy. Results show that lighting energy consumption can be reduced by up to 60% in scenarios combining LED technology with smart control systems, while total building electricity savings vary across case studies depending on building characteristics and usage patterns. Environmental impact reductions of approximately 15–20% are achieved, reflecting both operational and life-cycle improvements. The study demonstrates the potential of parametric architectural retrofitting to support multi-criteria decision-making for sustainable refurbishment of food-retail environments. Full article

This study examined relationships between electrical parameters, namely impedance (Z), admittance (Y), parallel capacitance (Cp), and series capacitance (Cs), and beef tenderness in the semimembranosus muscle during ageing for 3, 7, 14, and 28 days at 4 ± 1 °C. It also assessed selected compositional traits after 14 days. The effects of electrode configuration and signal frequency on measurement sensitivity were evaluated. Beef from Holstein–Friesian bulls (n = 8) representing two feeding treatments was used. Electrical measurements were performed with an in-house sensor and an LCR-based system. Two electrode configurations were applied: T, across the muscle fibres, and L, along the fibres. pH, Warner–Bratzler shear force (WBSF), and cooking loss were determined during ageing. Chemical composition and fatty acid profile were analysed after 14 days. WBSF decreased during ageing, whereas cooking loss showed a non-linear pattern, increasing up to day 14 and decreasing after 28 days. Electrical parameters were strongly affected by frequency and electrode configuration. After 14 days of ageing, the strongest relationship with tenderness was found for Z in the T configuration at 1 kHz (r = −0.834). The T configuration better reflected moisture content and fatty acid groups, whereas the L configuration was more informative for ash. Cs provided additional information related to protein. These findings indicate the potential usefulness of this approach for rapid beef quality screening under strictly standardised measurement conditions, although the observed relationships require confirmation in a larger sample set. Full article