Search Results (9,901)

The instability of many volatile organic compounds (VOCs) limits their usage in different fragrance carriers and products. In scratch-and-sniff applications, VOCs are bound so strongly that release cannot happen without an external trigger. On the other hand, other fixatives like cyclodextrins release unstable volatile molecules too rapidly. We engineered biodegradable gelatin films whose release profile can be tuned by glycerol plasticization and alkaline protease degradation. Digitalized VOC release profiles acquired with the described near-real-time analysis toolkit are digital twins that replicate the behavior of the evaluated films in silico. Seven formulations were cast from 10 % gelatin containing D-limonene, glycerol (5%, 20%), protease-C 30 kU mL⁻¹, and samples with additional water to establish a higher hydromodule for protease catalytic activity. Release profiles were monitored for nine days at 23 ± 2 °C in parallel by metal-oxide semiconductor (MOS) e-noses, gravimetric weight loss, and near-infrared measurements (NIR). These continuous measurements were cross-checked with gel electrophoresis, FTIR spectroscopy, hardness tests, and sensory intensity ratings. Results showed acceleration of VOC release by enzymatic treatment during the first days, as well as overall impact on the release profile. Differences in low and high glycerol films were observed, and principal component analysis of NIR spectra separated low and high glycerol groups, mirroring the MOS and FTIR data. Usability of MOS data was explored in comparison to more biased and subjective intensity results from sensory panel evaluation. Overall, the created toolkit showed good cross-checked results and enabled the possibility for close to real-time analysis for bio-based VOC carriers. Full article

The Tibetan Plateau’s lakes, serving as critical water towers for over two billion people, exhibit divergent responses to climate change that remain poorly quantified. This study develops a deep learning framework integrating Synthetic Aperture Radar (SAR) altimetry from Sentinel-3A with bias-corrected CMIP6 (Coupled Model Intercomparison Project Phase 6) climate projections under Shared Socioeconomic Pathways (SSP) scenarios (SSP2-4.5 and SSP5-8.5, adjusted via quantile mapping) to predict lake-level changes across eight Tibetan Plateau (TP) lakes. Using a Feed-Forward Neural Network (FFNN) optimized via Bayesian optimization using the Optuna framework, we achieve robust water level projections (mean validation R² = 0.861) and attribute drivers through Shapley Additive exPlanations (SHAP) analysis. Results reveal a stark north–south divergence: glacier-fed northern lakes like Migriggyangzham will rise by 13.18 ± 0.56 m under SSP5-8.5 due to meltwater inputs (temperature SHAP value = 0.41), consistent with the early (melt-dominated) phase of the IPCC’s ‘peak water’ framework. In comparison, evaporation-dominated southern lakes such as Langacuo face irreversible desiccation (−4.96 ± 0.68 m by 2100) as evaporative demand surpasses precipitation gains. Transitional western lakes exhibit “peak water” inflection points (e.g., Lumajang Dong’s 2060 maximum) signaling cryospheric buffer loss. These projections, validated through rigorous quantile mapping and rolling-window cross-validation, provide the first process-aware assessment of TP Lake vulnerabilities, informing adaptation strategies under the Sustainable Development Goals (SDGs) for water security (SDG 6) and climate action (SDG 13). The methodological framework establishes a transferable paradigm for monitoring high-altitude freshwater systems globally. Full article

This study aimed to develop an effective method to overcome the challenge of straw return in cold-region soil. We systematically investigated the synergistic mechanism of montmorillonite (MMT) and composite amino acid (CAA) on straw humification and carbon sequestration through a low-temperature litterbag field experiment. The results indicate that the combined treatment (MMT-CAA) significantly increased the decomposition rate of straw by 42.1% compared to the control (CK), with MMT showing particular efficacy in lignin degradation (28.3% reduction), while the CAA preferentially decomposed cellulose (19.7% reduction). An FTIR analysis of the decomposition products confirmed these findings. Water-soluble organic carbon (WEOC) and its three-dimensional fluorescence spectra exhibited a 25.0% increase in MMT-CAA and enhanced aromaticity of humic acid-like substances. Humic substances and their ¹³C-NMR revealed that MMT-CAA enhanced humic acid formation and molecular stability by 31.4% (with a 47.8% increase in aromaticity). A further redundancy analysis and symbiotic network of microorganisms demonstrated that MMT-CAA increased the abundance of lignocellulose-degrading phyla (Actinomycetes and Stramenomycetes) and the formation of a complex co-degradation network. Field corn planting trials indicated that MMT-CAA increased plant height by 55.1%, stem thickness by 58.7%, leaf area by 70.2%, and the SPAD value by 41.1%. Additionally, MMT significantly reduced CO₂ and N₂O emission fluxes by 35.6% and 15.8%, respectively, while MMT-CAA increased CH₄ uptake fluxes by 13.4%. This study presents an innovative strategy, providing mechanistic insights and practical solutions to synergistically address the challenges of slow straw decomposition and carbon loss in cold regions. Full article

Accurate and spatially detailed soil information is essential for supporting sustainable land use planning, particularly in data-scarce regions such as Cyprus, where soil degradation risks are intensified by land fragmentation, water scarcity, and climate change pressure. This study aimed to generate national-scale predictive maps of key soil health descriptors by integrating satellite-based indicators with a recently released geo-referenced soil dataset. A machine learning model was applied to estimate a suite of soil properties, including organic carbon, pH, texture fractions, macronutrients, and electrical conductivity. The resulting maps reflect spatial patterns consistent with previous studies focused on Cyprus and provide high resolution insights into degradation processes, such as organic carbon loss, and salinization risk. These outputs provide added value for identifying priority zones for soil conservation and evidence-based land management planning. While predictive uncertainty is greater in areas lacking ground reference data, particularly in the northeastern part of the island, the modeling framework demonstrates strong potential for a national-scale soil health assessment. The outcomes are directly relevant to ongoing soil policy developments, including the forthcoming Soil Monitoring Law, and provide spatial prediction models and indicator maps that support the assessment and mitigation of soil degradation. Full article

The growing demand for effective water treatment solutions, particularly in smaller communities in Brazil, highlights the potential of ozonation. However, implementing this technology at a smaller scale presents challenges, including the need to adapt it for compact systems and optimize processes for both efficiency and feasibility. This study investigates the use of a corona discharge ozone generator operating at 60 Hz in compact systems. Experiments evaluated ozone production at different gas flow rates (0.2 to 1.0 L of ozone-containing gas per minute), with the total flow divided between two lines, A (60%) and C (40%), for simultaneous treatment applications. Mass balance tests were performed using caffeine (CAF) and atenolol (ATL) as model compounds to assess molecular interactions. The results highlight the need to stabilize ozone generation to ensure consistent production and process efficiency, confirming ozone’s effectiveness in degrading emerging compounds (ECs), CAF and ATL, by approximately 80%, after process optimization using the compact ozonation unit. Key factors such as the position and diameter of the flow divider, diffuser type, and pollutant characteristics were shown to affect gas distribution, head loss, and ozone transfer efficiency. Thus, this work underscores the critical role of system configuration in optimizing ozonation, offering insights to enhance its feasibility for providing safe potable water during water crises and emergencies in Brazil. Full article

The primary contradiction in mature oilfields during the high water-cut stage is the uneven vertical water drive, which prevents the effective utilization of residual oil in the upper part of thick sand bodies at small scales. To address this issue, ultra-short-radius horizontal wells are employed to establish large-diameter oil flow channels within the reservoir, thereby achieving precise exploitation of this type of residual oil. Optimizing the length of the horizontal section is a critical issue in the development of small-scale residual oil, but conventional methods for optimizing the length of horizontal sections cannot be directly applied to ultra-short-radius horizontal wells (USRHWs). Therefore, utilizing reservoir seepage mechanics theory, the reservoir numerical simulation method was employed to investigate variations in daily and cumulative oil production for different horizontal section lengths. The theoretical upper limit of the optimal horizontal section length for actual injection and production well patterns was determined. Considering the coupled flow characteristics in the bottom water drive reservoir formation and wellbore, as well as the impact of friction losses caused by the relative roughness of the pipe wall under turbulent flow conditions on productivity, a mathematical model was established for the optimal length of the horizontal section of USRHWs, and the technological optimal value was determined. On this basis, fully accounting for the influence of drilling costs and oil prices on the optimization of the horizontal section length, an economic model for optimizing horizontal section length was established, and we comprehensively determine the optimal length of horizontal sections from multiple perspectives, including simulation, technology, and economics. The effectiveness of this method was validated by the processing results of actual reservoir parameters and the production performance after drilling. Full article

This study investigates geothermal clusters in the middle reaches of the Dawen River Basin, focusing on the developmental characteristics and genetic mechanisms of typical geothermal water exposures at key sites, including Daidaoan (Taishan), Qiaogou (Culai Town), and Anjiazhuang (Feicheng). Utilizing hydrogeochemical and environmental isotope analyses, we identify a dual groundwater recharge mechanism: (1) rapid infiltration via preferential flow through fissure media and (2) slow seepage with evaporative loss along gas-bearing zones. Ion sources are influenced by water–rock interactions and positive cation exchange. The hydrochemical types of surface water and geothermal water can be divided into five categories, with little difference within the same geothermal area. The thermal reservoir temperatures range from 53.54 to 101.49 °C, with the Anjiazhuang and Qiaogou geothermal areas displaying higher temperatures than the Daidaoan area. Isotope calculations indicate that the recharge elevation ranges from 2865.76 to 4126.69 m. The proportion of cold water mixed in the shallow part is relatively large. A comparative analysis of the genetic models of the three geothermal water groups shows that they share the common feature of being controlled by fault zones. However, they differ in that the Daidao’an geothermal area in Mount Tai is of the karst spring type with a relatively low geothermal water temperature, whereas the Qiaogou geothermal area in Culai Town and the Anjiazhuang geothermal area in Feicheng are of the gravel or sandy shale spring types with a relatively high geothermal water temperature. Full article

The erosion plot method (EPM) is the most accurate method for measuring total runoff and soil loss in the field, but it is expensive, time-consuming, and tedious to use, thereby limiting the scope of soil erosion research. Alternatively, the fractional method (FM) involves measuring a portion of total runoff and soil loss to estimate the total erosion. Although the FM may be easier to use in rainforest agroecology, it has not been evaluated under vetiver grass technology (VGT). Thus, a 2-year field study was conducted to verify the efficacy of the FM under VGT by comparing soil nutrient erosion between the FM and the EPM on two slopes (5% and 10%). Three piped drums (left, central, and right) were used to collect total runoff under the EPM, while only a central piped drum was used under the FM (usual practice). The FM’s runoff and soil loss values were similar to those under the EPM (R² = 0.98–0.99; p < 0.001). Runoff nutrients (R² = 0.90; p < 0.001) and eroded nutrients (R² = 0.97; p < 0.001) from the FM were highly similar to those of the EPM on the 5% slope. Similarly, runoff nutrients (R² = 0.86; p < 0.001) and eroded nutrients (R² = 0.95; p < 0.001) from the FM were strongly similar to those of the EPM on a 10% slope. The FM accounted for 92% of the total nutrient erosion measured by the EPM under VGT management. Thus, the FM will make research more efficient, cost-effective, and attractive, particularly in large-scale water erosion studies. Full article

The evolution of mining-induced overburden fractures (MIOFs) and their dynamic monitoring are critical for preventing roof water hazards and gas disasters in coal mines. Conventional methods often fail to provide sufficient accuracy under the thin soft–hard interbedded roof strata, necessitating advanced alternatives. Here, we address this challenge by proposing a borehole resistivity method (BRM) based on Back-Propagation Neural Network full-space inversion (BPNN-FSI). Based on the Carboniferous Taiyuan Formation in the North China Coalfield, geoelectric models of MIOFs were established for different mining stages. Finite element simulations generated apparent resistivity responses to train and validate the BPNN-FSI model. At the 9-204 working face of Dianping Coal Mine (Shanxi Province), we compared the proposed BRM based on BPNN-FSI with an empirical formula, numerical simulation, similarity physical simulation, and underground inclined drilling water-loss observations (UIDWLOs). Results demonstrate that the BRM based on BPNN-FSI achieves sub-1% error in height of MIOF (HMIOF) monitoring, with a maximum detected fracture height of 52 m—significantly outperforming conventional methods. This study validates the accuracy and robustness of BRM based on BPNN-FSI for MIOF monitoring in thin soft–hard interbedded roof strata, offering a reliable tool for roof hazard prevention and sustainable mining practices. Full article

With the rising trend of health-conscious consumers, demand for gluten-free alternatives is increasing, and rice flour is a promising gluten-free alternative for chicken batter. This study examines the effects of particle size variations in Baromi-2 rice flour on batter rheology and the quality attributes of deep-fat fried chicken. Baromi-2 is a rice variety specifically developed to meet the demands of the modern food processing industry, especially for applications requiring dry milling. Five particle sizes (60, 100, 120, 160, and 180 mesh) were evaluated on the basis of their physicochemical properties, including water-holding capacity (WHC), amylose content, and damaged starch levels. Batter consistency was assessed and frying performance was analyzed with regard to coating pickup, cooking loss, moisture content, crust color, and textural attributes. Results demonstrated that finer particle sizes (e.g., 180 mesh) exhibited high WHC and batter viscosity, resulting in reduced flowability and enhanced adhesion. These properties contributed to high coating pickup, improved moisture retention, and reduced cooking loss during frying. Fried chicken prepared with finer particles showed soft textures, great cohesiveness, and light crust colors with high lightness (L*) and reduced redness (a*) and yellowness (b*), producing a visually appealing product. By contrast, larger particle sizes (e.g., 60 mesh) resulted in low viscosity, uneven coatings, and high cooking loss. This study highlights the critical role of rice flour particle size in optimizing batter functionality and improving the quality of fried foods. Furthermore, these findings suggest the potential to bridge the gap between consumer demand for healthier fried foods and the food industry’s demands. Full article

This study provides a comprehensive assessment of water infrastructure, consumption management, and educational practices across all public pre-university educational institutions in Cluj County, Romania. The research addresses the increasingly urgent imperative of sustainable water resource management within educational settings, in alignment with both European and global priorities. This analysis is based on a comprehensive data set collected in June 2025 from all 392 public pre-university educational institutions in Cluj County, encompassing both urban and rural areas, all educational levels, and all types of institutions. Data was gathered using a standardized questionnaire, which was validated with the official support of the Cluj County School Inspectorate. The quantitative analysis highlights significant urban–rural disparities: 95.566% of urban institutions are equipped with modern meters and connected to public water networks, compared to only 68.254% in rural areas. Water consumption monitoring relies predominantly on invoice data (69.388%), while the adoption of advanced monitoring technologies remains limited. Reported water losses are minimal (1.531%), and only 0.765% of educational institutions have indicated non-compliance issues related to water quality in the past three years. Educational measures and water-saving awareness campaigns are present in 65.562% of institutions, yet only about one-third (32.908%) have implemented dedicated projects or partnerships. The financial analysis reveals that 90.487% of annual water and sewerage costs are borne by urban institutions. The study highlights both the progress achieved and the persistent challenges, particularly in rural infrastructure and the expansion of educational interventions. The results provide a robust empirical basis for informing regional and national policies, supporting targeted investments, integrated educational programs, and continuous monitoring to ensure sustainable water resource management in the Romanian educational system. Full article

Focusing on the Lingshan section of Guangxi’s Pinglu Canal, this study addresses frequent waterlogging during construction under subtropical monsoon rainfall. Human disturbances alter hydrological processes, causing project delays and economic losses. We developed a coupled Storm Water Management Model (SWMM 1D hydrological) and Hydrologic Engineering Center—River Analysis System 2D (HEC-RAS 2D hydrodynamic) model. High-resolution Unmanned Aerial Vehicle—Light Detection and Ranging (UAV-LiDAR) Digital Elevation Model (DEM) delineated sub-catchments, while the Green-Ampt model quantified soil conductivity decay. Synchronized runoff data drove high-resolution HEC-RAS 2D simulations of waterlogging evolution under design storms (1–100-year return periods) and a real event (10 May 2025). Key results: Water depth exhibits nonlinear growth with return period—slow at low intensities but accelerating beyond 50-year events, particularly at temporary road junctions where embankments impede flow. Additionally, intensive intermittent rainfall causes significant ponding at excavation pit-road intersections, and optimized drainage drastically shortens recession time. The study reveals a “rapid runoff generation–restricted convergence–prolonged ponding” mechanism under construction disturbance, validates the model’s capability for complex scenarios, and provides critical data for real-time waterlogging risk prediction and drainage optimization during the canal’s construction. Full article

Water pollution poses serious threats to public health and the environment, therefore requiring efficient and scalable monitoring solutions. This paper presents a cyber–physical system (CPS) that integrates paper-based biosensors with an edge IoT architecture and long-range wide area network (LoRaWAN) for real-time assessment of water quality. The biosensors detect pollutants such as arsenic, lead, and nitrates with a detection limit of 0.5 ppb. The system proposed was compared with existing LSTM systems based on two performance metrics: detection accuracy and latency. Paper-based biosensors were fabricated using silver nanoparticle-functionalized substrates to show high sensitivity and low-cost pollutant detection. TCN algorithm deployment at the edge allows for real-time processing for time-series data analysis due to its high accuracy and low latency properties compared with LSTM models, which were mainly chosen due to their usage in most applications dealing with time-series-based analysis. Experimentation was carried out by deploying the developed CPS in controlled environments, simulating pollutants at different levels, and executing the models to test their accuracy in detecting pollutants and the latency of data processing. The TCN framework achieved a detection accuracy of 98.7%, which surpassed LSTM by 92.4%. In addition, TCN reduced latency in processing by 38% to enable fast data analysis and decision making. LoRaWAN allowed for perfect packet transmission of up to 15 km, while the loss rate stayed as low as 2.1%. These results establish the proposed CPS as reliable, efficient, and scalable for real-time water contamination monitoring. Thus, this research introduces the integration of paper-based biosensors with advanced computational frameworks. Full article

Hurricanes cause significant destruction, disrupting transportation, and resulting in loss of life and property. High-precision marine meteorological data are essential for understanding hurricanes. ERA5 provides high temporal resolution and global coverage of analytical data; however, the accuracy of the data during hurricanes is uncertain. To investigate the applicability of ERA5 during hurricanes, this study used buoy data as reference values and assessed the applicability of ERA5 sea-surface wind speed (WS), sea-surface temperature (SST), and sea-surface pressure (SSP) during the 2020 Atlantic hurricane “ISAIAS” through spatial distribution and error analysis. The results indicate that there is a positive correlation and consistency between the trends of ERA5 and reference values. The average correlation coefficients for SSP, WS, and SST are 0.953, 0.822, and 0.607, respectively. Nearshore topography has a significant impact on data accuracy, resulting in greater errors compared to open-water areas. This study provides a theoretical basis for the application of ERA5 data during hurricanes. Full article

This study evaluated the effects of lasalocid sodium (LASA) and essential oils on the fermentation and nutritional quality of total mixed ration (TMR) silages. A 4 × 2 factorial design tested four additives—a control (distilled water), LASA (375 mg/kg DM), limonene essential oil (LEO), and a blend of cinnamaldehyde and carvacrol (EOB), both at 400 mg/kg DM—during summer and autumn. The TMRs were formulated to meet the nutritional requirements of lactating cows producing 20 kg of milk per day. After 110 days of ensiling, silages were analyzed for fermentation losses, pH, short-chain fatty acids, ammoniacal nitrogen (NH₃-N), aerobic stability (AS), and chemical composition. The additives significantly improved dry matter recovery (DMR), especially LASA and EOB in autumn. EOB showed the lowest effluent losses and highest AS, with higher acetic acid and lower NH₃-N contents. LEO and EOB increased lactic acid, while LASA reduced ethanol and butyric acid levels in summer. Crude protein increased with LEO in autumn, and LASA and LEO improved total digestible nutrients (TDNs) in summer. EOB-treated silages had higher fiber fractions in autumn, without compromising feed value. Therefore, LASA, LEO, and particularly EOB enhanced silage fermentation and nutrient preservation, with EOB showing the most consistent results across seasons. Full article