Search Results (4,099)

Wind speed prediction is an essential spatiotemporal forecasting task in wind energy systems, yet it remains challenging due to the nonlinear and dynamic characteristics of atmospheric processes. The evolution of wind is governed by physical laws, which can be effectively described using partial differential equations (PDEs). To improve forecasting reliability and accuracy, this paper proposes a novel network model, termed DynWindNet, which integrates equation-based dynamics with data-driven dynamics within a unified framework. Specifically, an interactive dual-branch architecture is designed, where a Physics–Data Coupling Module (PDCM) enables adaptive information exchange between the two dynamics via attention-based gating mechanisms. In addition, a frequency-aware enhancement module (FAEM) is introduced to refine the representations of the data-driven branch by selectively emphasizing informative frequency components. Experimental results on the ERA5 dataset demonstrate that DynWindNet consistently outperforms representative baseline methods across atmospheric pressure levels. Overall, the proposed framework provides an effective approach for integrating physics-guided evolution modeling with deep spatiotemporal representation learning in wind field forecasting. Full article

This study investigates tide–surge nonlinear interactions along the southeastern coast of China (SCC) using Typhoon Winnie as a case study. A coupled tide–surge model is established based on the Finite-Volume Community Ocean Model (FVCOM), incorporating realistic bathymetry, tidal constituents, wind fields, and atmospheric pressure. The results show that tide–surge interactions contribute up to 1.8 m to the total water level, with the most pronounced effects occurring in shallow, high-friction coastal regions such as Hangzhou Bay, the Yangtze River Estuary, and the Jiangsu coast. Sensitivity experiments reveal that the quadratic bottom friction term is the dominant mechanism driving the nonlinear interaction, while the advection term plays a secondary role. The interaction intensity is highly sensitive to water depth and topographic slope; reducing water depth generally intensifies the interaction, though the response is non-monotonic in regions with complex bathymetry such as the radial sand ridge field. The phase and period of astronomical tides also exert significant control. Notably, semi-diurnal constituents (e.g., M₂, S₂) dominate the interaction, accounting for up to 80% of the nonlinear effect, whereas diurnal constituents contribute negligibly (less than 0.1 m). Tide–surge coupling significantly affects both the magnitude and timing of extreme water levels, with enhanced interaction occurring during astronomical low tide at some stations (e.g., Dinghai). These findings underscore the necessity of incorporating tide–surge interactions, particularly with accurate bottom friction and semi-diurnal tidal forcing, into storm surge models for improved forecasting and disaster risk assessment along China’s southeastern coast. Full article

Addressing the urgent demand for high-precision pressure measurement in real-time barometric monitoring, aerospace, and industrial control, this paper presents a high-accuracy MEMS resonant pressure sensor based on electrostatic excitation and piezoresistive detection. The sensor incorporates a symmetric double-ended fixed-finger comb-drive resonator structure, driven into stable vibration at its natural frequency by an alternating electrostatic force. Piezoresistors integrated at the root of the resonant beams transduce the mechanical vibration into a frequency output, enabling precise external pressure measurement. Experimental results show that the developed sensor achieves an accuracy of 0.009% FS over a pressure range of 0–350 kPa across an operating temperature span from −30 °C to 50 °C, with a room-temperature repeatability error below 0.008% FS, demonstrating excellent measurement stability. Building on this performance, a real-time atmospheric pressure monitoring experiment was conducted, yielding a mean absolute percentage error of less than 0.05%, highlighting the sensor’s potential for engineering practicality. This work provides an effective technique for a high-precision, high-stability resonant pressure sensor, with clear potential for deployment in real-time barometric monitoring, aerospace, and industrial control applications. Full article

Xizang is characterized by high altitude, low air pressure, strong atmospheric transparency, and complex terrain, while sparse ground stations coexist with continuously available remotely sensed data, and systematic studies on SSR bias correction and meteorological influences under plateau conditions remain limited. This study focuses on a short-term spring case at one urban observation site in Lhasa, using observations collected from 4 to 30 April 2025 to investigate the bias correction of remotely sensed surface solar radiation (SSR) and the influence of meteorological factors. Ground observations and Himawari-8 remotely sensed data were first spatially and temporally matched and preprocessed. Spearman correlation analysis was then used to select key input variables. Support vector regression, random forest, XGBoost, and multiple linear regression models were subsequently developed, followed by a Stacking ensemble model for bias correction. Finally, local sensitivity analysis was conducted to examine the local response of the correction model to selected meteorological variables at a representative baseline point. The results showed that the correlation coefficient between remotely sensed SSR and ground-observed SSR was 0.88 ($p<0.001$). The Stacking ensemble model achieved the best performance, with a test set $R^2$ of 0.8796, an MAE of 118.54 W/m², and an RMSE of 152.41 W/m². Local sensitivity analysis showed that a +10 hPa perturbation in air pressure increased the model output by 173.45 W/m², while a +10 °C perturbation in air temperature increased the output by 23.76 W/m². This study provides a reference for improving the accuracy of remotely sensed SSR and for solar resource assessment in plateau regions. Full article

Graphene was added to acrylic paint to be coated on two sets of unheated and heat-treated specimens of three commercial wood species (namely beech, poplar, and spruce) to protect against Coniophora puteana. Heat treatment was carried out at the mild temperature of 185 °C for four hours in a laboratory oven and under atmospheric pressure. Each of the two sets were divided into three sub-groups of uncoated (control), coated with plain paint, and coated with graphene-enriched paint to be exposed to the fungus. Results showed that coating of specimens with the plain acrylic paint significantly protected all three wood species against the fungus. Still, reinforcing effect of graphene resulted in an even higher degree of protection, and it slightly increased compression strength compared to grain as well. Heat treatment also improved biological resistance in all three wood species, which is seen in the drastic decrease of the mass losses. It also increased compression strength as a result of hornification and thermal alterations of cell-wall polymers. It was concluded that graphene-added acrylic paint can be recommended as an easy and available superficial protecting method to significantly protect both hard- and softwoods against C. puteana. Full article

This study aims to systematically elucidate the influence of various heat treatment methods on the phenolic compounds in highland barley and their potential antihypertensive processes via chemical, in vitro bioactivity, and bioinformatics prediction analyses. This work employed UHPLC-Q Exactive HFX-MS/MS targeted metabolomics technology to ascertain metabolites in barley treated with five different thermal conditions: steaming (ST), boiling at atmospheric pressure (BO), boiling at high pressure (PO), extrusion puffing (EX), and sand-roasting (SR). The data revealed 252 phenolic metabolites, comprising 19 phenolic acids and 233 flavonoids. Moreover, it was observed that, in comparison to the untreated group, various heat treatments yielded substantial differences in the profiles of phenolic compounds. Notably, extrusion puffing (EX) exhibited superior performance: it increased specific flavonoid glycosides such as Clitorin and Quercetin 3-O-rutinoside-(1-2)-O-rhamnoside, while also improving direct antioxidant capabilities such as DPPH and FRAP. In addition, network pharmacology analysis of differentially expressed metabolites in the puffed group identified 44 potential targets, including TNF, IL-6, MMP-9, HIF-1A, and ACE. The KEGG and GO enrichment analyses revealed a substantial enrichment of these targets in classic hypertension-related pathways, including lipid metabolism, atherosclerosis and fluid shear stress. The molecular docking findings indicated that Apigenin 7-O-(2G-rhamnosyl) gentiobioside had significant binding affinities for the target proteins MMP9 and ACE. This study demonstrated that EX is an efficient processing method, with highland barley polyphenols showing potential antihypertensive activity. The findings provide a novel theoretical foundation and research direction for optimizing highland barley processing to maximize functional component utilization and elucidate its food-derived antihypertensive mechanisms. Full article

The European spruce bark beetle (Ips typographus) is the main pest of spruce in northwestern European Russia, particularly in the Leningrad Region. Its outbreaks occur quite frequently. However, the population dynamics of Ips typographus in this region remain poorly understood. The aim of this study is to identify the life cycle characteristics of the species based on data obtained using pheromone traps in the Leningrad Region, to clarify the influence of various factors, and to evaluate the effectiveness of this monitoring method. From 2022 to 2025, observations using barrier pheromone traps north and south of St. Petersburg at several points were carried out. There were 3 traps placed at each point. The traps were inspected at 5-day intervals from early May to late August. The dynamics of beetle flight was obtained based on standardized values of beetle catches. The relationship between beetle swarming and temperature was estimated based on calculated Growing Degree-Days for 2022, 2023 and 2025. A graphical representation of 5-day moving average for daily temperature, relative humidity, wind speed and atmospheric pressure in accordance with calculated swarming dynamics were illustrated. The spring mass flight of the parent generation correlated strongly with daily temperature, but no significant correlation was found with other factors or outside the spring period. Catches after spring flight did not reflect actual population levels. Pheromone traps reliably reflect population density only during the spring flight of the parent generation. Full article

This study presents a dataset of meteorological and soil-hydrological instrumental observations collected at three agrometeorological stations in the East Kazakhstan Region during the growing seasons of 2022–2025. The dataset includes time series from automatic weather stations: WS “OCES-1” (Solnechnoe village) provides hourly data over four years (2022–2025; 14,614 records; 65 variables), while WS “OCES-2” (Lugovoe village; 203,279 records) and WS “Altyn Kazan” (Sulusary village; 207,115 records) provide minute-resolution data for 2025 (49 variables each). Measured parameters at 200 cm height include air temperature and humidity, atmospheric pressure, precipitation, wind speed and direction; soil measurements down to 100 cm depth include temperature and moisture. Also, field-based express measurements of volumetric soil moisture within a 1 m profile (every 10 cm) were collected during three campaigns (May–August 2025), resulting in a total of 253 measurements. The stations are located across steppe and forest-steppe landscapes of the transboundary Altai–Sayan mountain region on active agricultural lands under diverse soil–climatic conditions. Climate types correspond to Dfb and Dfa per the Köppen–Geiger classification. Soils are classified under WRB as Chernozems and Calcic Chernozems. The dataset is published in CSV format on Zenodo under a CC-BY 4.0 license. Full article

This study aimed to optimize the nitriding parameters for Plasma Immersion Ion Implantation (PIII) of stainless steels. UNS S32750 super duplex stainless steel, widely employed in the petrochemical industry, was subjected to PIII under varying nitriding atmospheres (mixtures of H₂ and N₂) and treatment pressures. The fixed PIII nitriding parameters included a temperature of 300 °C, a duration of 3 h, a bias voltage of approximately −10 kV, a frequency of 500 Hz, and a pulse width of 30 μs. Following the treatments, the phases were characterized by X-ray diffraction (XRD), while the hardness and elastic modulus of the modified surfaces were evaluated via nanoindentation. Regarding the nitriding atmosphere, gas mixtures approaching a 60% N₂/40% H₂ (vol.) ratio yielded a higher volume fraction of nitrogen-rich expanded phases in solid solution. Furthermore, higher treatment pressures promoted the formation of these expanded phases, consequently enhancing the surface hardness up to 2.7 times the hardness value of the untreated sample. These findings stand in contrast to those found for low-energy plasma nitriding (PN) processes. 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

This narrative review develops fermentation-oriented viticulture as an agronomic-oenological framework linking vineyard environment, management and must ecology to fermentation performance. The literature from 2010 to April 2026 was synthesized through structured searches in PubMed and Google Scholar, complemented by targeted searches in MDPI, Frontiers, Nature, ScienceDirect, OENO One, PNAS and European Union regulatory sources, with emphasis on 2020–2026 publications and retention of older foundational sources. Current evidence indicates that must microbiota is not a linear derivative of soil or berry surfaces, but a network outcome of connected habitats spanning the viticultural biotope and grapevine-associated biocenosis (soil, rhizosphere, phyllosphere, berry, insect, atmospheric and winery). Climate warming, drought, altered phenology, soil fertility, nitrogen nutrition, crop-protection programs and bio-based inputs jointly modify berry chemistry, yeast-assimilable nitrogen (YAN), microbial inocula and pre-fermentative selection pressures. The review distinguishes fermentation-oriented viticulture from descriptive microbial terroir by defining practical endpoints: fermentation onset and completion, sluggish or stuck fermentation risk, microbial stability, spoilage taxa, volatilome development and wine typicity. It also proposes operational indicators and a decision matrix for integrating vineyard and winery management. The framework supports future multi-vintage studies combining climate, soil, agronomic metadata, YAN, microbiome profiling and microvinification outcomes. Full article

Concerns about human exposure to micro- and nanoplastics (MNPLs), particularly nanoplastics (NPLs), have intensified in recent years. Consequently, there is a growing need for validated quantitative analytical methods capable of assessing NPLs in complex human biological matrices. Current approaches for NPL analysis are still limited by the absence of standardised protocols, difficulties in avoiding background contamination, and challenges associated with the selective identification and quantification of polymer-specific nanoparticles. Moreover, most common approaches for quantification by particle counting cannot be applied for NPLs < 500 nm. In this study, we developed and validated an analytical method for the detection and quantification of NPLs in human faeces. As an initial step, polyethylene (PE) and polypropylene (PP) nanoparticles (NPs) were synthesised using bottom-up methods and characterised by dynamic light scattering (DLS) and electron microscopy (SEM and TEM). To optimise and assess the extraction, synthetic faeces were prepared and used in spiking experiments to avoid background contamination from plastics. Two digestion strategies were evaluated: (i) Fenton’s reagent followed by strong acid digestion, and (ii) alkaline digestion. Quantitative determination of polymer-specific NPLs was performed by size-exclusion liquid chromatography coupled with high-resolution mass spectrometry and atmospheric-pressure photoionization (SEC-APPI-HRMS). Polymer identification was based on characteristic monomer-loss patterns and Kendrick Mass Defect analysis. Fenton-based digestion showed superior performance, yielding recoveries about 55–66% for PE and 59–61% for PP. The validated method achieved limits of detection and quantification of 0.015 and 0.058 μg/kg for PE, and 0.025 and 0.083 μg/kg for PP, respectively. Precision, expressed as %RSD, was 10.1% for PE and 20.1% for PP. These results demonstrate that SEC-APPI-HRMS combined with Fenton-based digestion provides a sensitive and reliable approach for the quantification of polymer-specific NPLs in human faeces. The method represents an important advance for human biomonitoring studies and supports future research aimed at assessing human exposure and the potential health risks associated with nanoplastics. Full article

Aiming at the problem that it is difficult for existing path planning methods to plan UAV paths in real time in complex atmospheric turbulence environments, this work proposes a dynamic path planning method for UAVs based on an improved artificial lemming algorithm. First, using temperature, pressure, and wind vectors from WRF/NWP forecast data, a dynamic turbulence-change environment model in the airspace is constructed. Then, a UAV dynamic path planning model is formulated by comprehensively considering the turbulence change rate and path safety evaluation factors. Next, to address premature convergence of existing algorithms under turbulence influence, a solving method for the UAV dynamic path planning model based on an improved artificial lemming algorithm is developed. Simulation results show that, under the proposed replanning mechanism, the improved algorithm reduces the final fitness by 36.19% and cumulative turbulence exposure by 16.28% on average compared with all competing methods. Full article

This work investigates Ferro-Rock concrete as a carbon-negative alternative to ordinary Portland cement (OPC), which accounts for 5–9% of global CO₂ emissions, and evaluates its viability as a sustainable construction material. Ferro-Rock is an iron-based binder comprising recycled iron powder, fly ash, metakaolin, limestone powder, and oxalic acid. This is enhanced by a carbonation reaction in which iron particles react with CO₂ and water to form iron (II) carbonate (FeCO₃), the main binding phase, thereby locking in atmospheric CO₂. The experimental program was divided into two groups. Group 1 studied 100% Ferro-Rock binders with different types of aggregate, specimen sizes, and CO₂ curing periods (0–6 days) with a new locally manufactured stainless steel curing chamber that provided a controlled CO₂ environment of 99.9% and 1.2–1.5 bar gauge pressure. Group 2 investigated Ferro-Rock as a partial cement replacement at 0%, 5%, 10%, 15% and 20% levels of substitution with 5% increments. The 7 and 28 days of compressive, flexural and indirect tensile strengths were determined. The results showed the Ferro-Rock with 100% iron ductile waste aggregates (Mix F4) achieved a 28-day compressive strength of 5.5 MPa, 37.5% higher than the standard Ferro-Rock reference mix. The optimum replacement range of Group 2 was 5–10% with an increase in compressive strength by 5–10%, flexural strength by 11%, and indirect tensile strength by 16% over the OPC control. When replacement exceeded 25%, the bonding was weakened, and all strength measures decreased significantly, reaching a 46% reduction in compressive strength at 50% substitution. Scanning electron microscopy–energy-dispersive X-ray spectroscopy (SEM–EDS) microstructural analysis verified the gradual formation of the iron carbonate crystalline phase and provided mechanistic insights into the observed strength trends. Fully cured Ferro-Rock specimens sequestered as much as 11% CO₂ by weight, with a verifiably carbon-negative profile that no OPC-based system can match. Full article

Climate change remains among the most pressing environmental challenges confronting the world, exerting profound pressure on both ecological systems and socio-economic development. To advance understanding of the evolution patterns and driving mechanisms governing hydroclimatic systems in arid and semi-arid regions, this study employed an integrated framework encompassing trend testing, change-point detection, periodicity and persistence analysis, and machine learning-based attribution. Focusing on the Mu Us Sandy Land from 1982 to 2023, we systematically investigated the spatiotemporal evolution, periodic characteristics, and driving mechanisms of hydroclimatic factors. Furthermore, future climate risks were assessed using CMIP6 multi-model data. The results showed that: (1) All four variables exhibited positive slopes, but only soil moisture showed a statistically significant long-term wetting trend (β = 0.025 × 10⁻³, p = 0.0008) and a clear global abrupt change in 2011; the upward tendencies of precipitation (p = 0.3946), potential evapotranspiration (p = 0.4970), and surface runoff (p = 0.1097) did not reach the 0.05 significance level. (2) Meteorological elements showed weak periodicity and strong anti-persistence (mean Hurst index = 0.379 for precipitation and 0.222 for PET), whereas hydrological elements exhibited clear seasonal–interannual periods and more random future variability with greater spatial heterogeneity (mean Hurst index = 0.436 for runoff and 0.414 for soil moisture). (3) Monthly changes were mainly associated with local surface processes. Vegetation dynamics were key predictors of precipitation, runoff, and soil moisture, while potential evapotranspiration was dominated by atmospheric demand, with limited influence from large-scale climate indices. (4) Under high-emission scenarios, imbalanced water–heat increases may lead to a higher likelihood of drought conditions. Full article