Search Results (372)

This study investigates the effect of hemp shive granulometry on the thermal conductivity and microstructure of hemp–lime composites. Three distinct particle size fractions—fine, medium, and coarse—were characterized using high-resolution image analysis to determine geometric parameters such as Feret diameters, circularity, and elongation. Composite mixtures with varying binder-to-shive and water-to-shive ratios were prepared and compacted at a consistent level to isolate the influence of aggregate granulometry on thermal performance. Results demonstrate a clear inverse relationship between particle size and thermal conductivity, with coarse fractions reducing thermal conductivity by up to 7.6% compared to fine fractions. Composite density was also affected, decreasing with increasing particle size, confirming the impact of granulometry on pore structure and packing density. However, binder content exhibited the most significant effect on thermal conductivity, with a 20% increase observed for higher binder-to-shive ratios irrespective of shive size. The study further establishes that a 15 g sample size (~2400 particles) provides sufficient statistical accuracy for granulometric characterization using image analysis. These findings provide critical insights for optimizing hemp–lime composites for enhanced thermal insulation performance, supporting sustainable construction practices by informing material formulation and processing parameters. Full article

Elasmobranch species are considered a global conservation priority due to their susceptibility to fishing pressure. In the Madeira Archipelago, Northeastern Atlantic, most elasmobranch species are caught as bycatch in artisanal drifting longline fishery targeting scabbardfishes. All commercial elasmobranch landings carried out in this archipelago over three decades (1990–2020) were analysed, aiming to provide a reliable overview of Madeira’s elasmobranch fisheries and their evolution. A total of 2316 tonnes of elasmobranchs were landed during the study period, corresponding to approximately EUR 2.1 million in first-sale value. The most representative period occurred from 2003 to 2013, corresponding to 75.21% of the total elasmobranch landings. A general pattern of supply and demand was evident, with mean price values typically showing an inverse trend to landed tonnage. At the species level, Centrophorus squamosus appears as the dominant species, representing about 89% of the total elasmobranch species landed, followed by Prionace glauca, with approximately 3%. The high dominance of C. squamosus in the scabbardfish fishery raises significant ecological and management concerns, as this deep-water shark species is known for its vulnerability to overexploitation. Management measures currently in place need to be updated and ought to be based on studies on the type and size of hooks for each fishery, to ultimately infer about species-specific survival rates, as well as the fishing gears’ soak time. Moreover, studies on the enhancement of food supply through fisheries discards are still missing, even though it is highly likely that this input may alter the dynamics of marine food webs. Full article

Accurately monitoring terrestrial water storage (TWS) variations is essential due to global climate change and growing water demands. This study investigates TWS changes in Oregon, USA, using Global Navigation Satellite System (GNSS) data from the Nevada Geodetic Laboratory, Gravity Recovery and Climate Experiment (GRACE) level-3 mascon data from the Jet Propulsion Laboratory (JPL), and Noah model data from the Global Land Data Assimilation System (GLDAS) data. The results show that the GNSS inversion offers superior spatial resolution, clearly capturing a water storage gradient from 300 mm in the Cascades to 20 mm in the basin and accurately distinguishing between mountainous and basin areas. However, the GRACE data exhibit blurred spatial variability, with the equivalent water height amplitude ranging from approximately 100 mm to 145 mm across the study area, making it difficult to resolve terrestrial water storage gradients. Moreover, GLDAS exhibits limitations in mountainous regions. The GNSS can provide continuous dynamic monitoring, with results aligning well with seasonal trends seen in GRACE and GLDAS data, although with a 1–2 months phase lag compared to the precipitation data, reflecting hydrological complexity. Future work may incorporate geological constraints, region-specific elastic models, and regularization strategies to improve monitoring accuracy. This study demonstrates the strong potential of GNSS technology for monitoring TWS dynamics and supporting environmental assessment, disaster warning, and water resource management. Full article

Accurate monitoring of soil moisture in arid agricultural regions is essential for improving crop production and the efficient management of water resources. This study focuses on Shihezi City in Xinjiang, China. We propose a novel method for soil moisture retrieval by integrating Sentinel-1 and Sentinel-2 remote sensing data. Dual-polarization parameters (VV + VH and VV × VH) were constructed and tested. Pearson correlation analysis showed that these polarization combinations carried the most useful information for soil moisture estimation. We then applied Shapley Additive exPlanations (SHAP) for feature selection, and a Stacking model was used to perform soil moisture inversion based on the selected features. SHAP values derived from the coupled support vector regression (SVR) and random forest regression (RFR) models were used to select an additional six key features for model construction. Building on this framework, a comparative analysis was conducted to evaluate the predictive performance of multivariate linear regression (MLR), RFR, SVR, and a Stacking model that integrates these three models. The results demonstrate that the Stacking model outperformed other approaches in soil moisture retrieval, achieving a higher R² of 0.70 compared to 0.52, 0.61, and 0.62 for MLR, RFR, and SVR, respectively. This process concluded with the use of the Stacking model to generate a county-level farmland soil moisture distribution map, which provides an objective and practical approach to guide agricultural management and the optimized allocation of water resources in arid regions. Full article

Titanium dioxide (TiO₂) is a benchmark photocatalyst for environmental applications, but its limited visible-light activity due to a wide band gap and fast charge recombination restricts its practical efficiency. This study presents the development of heterostructured Ag (Au)/MoS₂-TiO₂ inverse opal (IO) films that synergistically integrate photonic, plasmonic, and semiconducting functionalities to overcome these limitations. The materials were synthesized via a one-step evaporation-induced co-assembly approach, embedding MoS₂ nanosheets and plasmonic nanoparticles (Ag or Au) within a nanocrystalline TiO₂ photonic framework. The inverse opal architecture enhances light harvesting through slow-photon effects, while MoS₂ and plasmonic nanoparticles improve visible-light absorption and charge separation. By tuning the template sphere size, the photonic band gap was aligned with the TiO₂-MoS₂ absorption edge and the localized surface plasmon resonance of Ag, enabling optimal spectral overlap. The corresponding Ag/MoS₂-TiO₂ photonic films exhibited superior photocatalytic and photoelectrocatalytic degradation of tetracycline under visible light. Ultraviolet photoelectron spectroscopy and Mott–Schottky analysis confirmed favorable band alignment and Fermi level shifts that facilitate interfacial charge transfer. These results highlight the potential of integrated photonic–plasmonic-semiconductor architectures for efficient solar-driven water treatment. Full article

The safe disposal of high-level radioactive waste (HLW) is imperative for sustaining China’s rapidly expanding nuclear power sector, with deep geological repositories requiring rigorous site evaluation via underground research laboratories (URLs). This study presents a controlled-source audio-frequency magnetotellurics (CSAMT) survey at the Xinchang site in China’s Beishan area, a region dominated by high-resistivity metamorphic rocks. To overcome electrical data acquisition challenges in such resistive terrains, salt-saturated water was applied to transmitting and receiving electrodes to enhance grounding efficiency. Using excitation frequencies of 9600 Hz to 1 Hz, the survey achieved a 1000 m investigation depth. Data processing incorporated static effect removal via low-pass filtering and smoothness-constrained 2D inversion. The results showed strong consistency between observed and modeled data, validating inversion reliability. Borehole correlations identified a 600-m-thick intact rock mass, confirming favorable geological conditions for URL construction. The study demonstrates CSAMT’s efficacy in characterizing HLW repository sites in high-resistivity environments, providing critical geophysical insights for China’s HLW disposal program. These findings advance site evaluation methodologies for deep geological repositories, though integrated multidisciplinary assessments remain essential for comprehensive site validation. This work underscores the feasibility of the Xinchang site while establishing a technical framework that is applicable to analogous challenging terrains globally. Full article

The efficient and precise identification of urban slums is a significant challenge for urban planning and sustainable development, as their morphological diversity and complex spatial distribution make it difficult to use traditional remote sensing inversion methods. Current deep learning (DL) methods mainly face challenges such as limited receptive fields and insufficient sensitivity to spatial locations when integrating multi-source remote sensing data, and high-quality datasets that integrate multi-spectral and geoscientific indicators to support them are scarce. In response to these issues, this study proposes a DL model (coordinate-attentive U²-DeepLab network [CAU²DNet]) that integrates multi-source remote sensing data. The model integrates the multi-scale feature extraction capability of U²-Net with the global receptive field advantage of DeepLabV3+ through a dual-branch architecture. Thereafter, the spatial semantic perception capability is enhanced by introducing the CoordAttention mechanism, and ConvNextV2 is adopted to optimize the backbone network of the DeepLabV3+ branch, thereby improving the modeling capability of low-resolution geoscientific features. The two branches adopt a decision-level fusion mechanism for feature fusion, which means that the results of each are weighted and summed using learnable weights to obtain the final output feature map. Furthermore, this study constructs the São Paulo slums dataset for model training due to the lack of a multi-spectral slum dataset. This dataset covers 7978 samples of 512 × 512 pixels, integrating high-resolution RGB images, Normalized Difference Vegetation Index (NDVI)/Modified Normalized Difference Water Index (MNDWI) geoscientific indicators, and POI infrastructure data, which can significantly enrich multi-source slum remote sensing data. Experiments have shown that CAU²DNet achieves an intersection over union (IoU) of 0.6372 and an F1 score of 77.97% on the São Paulo slums dataset, indicating a significant improvement in accuracy over the baseline model. The ablation experiments verify that the improvements made in this study have resulted in a 16.12% increase in precision. Moreover, CAU²DNet also achieved the best results in all metrics during the cross-domain testing on the WHU building dataset, further confirming the model’s generalizability. Full article

Seasonally frozen soils are widely distributed across the Qinghai–Tibet Plateau and play a crucial role in regional hydrological processes, ecosystem stability, and infrastructure development. In this study, a custom-designed freeze–thaw apparatus was employed to investigate the freezing behavior of clayey sand with varying initial volumetric water contents. The relationship between electrical resistivity and unfrozen water content was examined through laboratory tests, while six-month resistivity monitoring tests were conducted in a representative frozen soil region of the plateau. The results show that the freezing points for samples with initial volumetric water contents of 30%, 18.5%, and 10% were −2.34 °C, −4.69 °C, and −6.48 °C, respectively, whereas the thawing temperature remained approximately −4 °C across all cases. A strong inverse correlation between resistivity and unfrozen water content was observed during the freezing process. Moreover, the resistivity exhibited a typical U-shaped trend with increasing initial water content, with a minimum level observed at 6~10%. Field resistivity profiles demonstrated limited variation between July and September, while in December, a pronounced thickening of the transition zone and an upward shift in the high-resistivity layer were evident. These findings enhance the understanding of the freeze–thaw mechanisms and the spatiotemporal evolution of frozen soils in high-altitude environments. Full article

Hydrogel particles, renowned for their high water content and biocompatibility in drug delivery and tissue engineering, typically rely on complex, costly microfluidic systems to reach sub 5 µm dimensions. We present a vortex-based inverse-emulsion polymerization strategy in which UV crosslinking of polyethylene glycol diacrylate (PEGDA) dispersed in n-hexadecane and squalene yields tunable micro- and nanogels while delineating the parameters that govern particle size and uniformity. Systematic variation in surfactant concentration, vessel volume, continuous phase viscosity, vortex speed and duration, oil-to-polymer ratio, polymer molecular weight, and pulsed vortexing revealed that increases in surfactant level, vortex intensity/duration, vessel volume, and oil-to-polymer ratio each reduced mean diameter and PDI, whereas higher polymer molecular weight and continuous phase viscosity broadened the size distribution. We further investigated how these same parameters can be tuned to shift particle populations between nano- and microscale regimes. Under optimized conditions, microhydrogels achieved a coefficient of variation of 0.26 and a PDI of 0.07, with excellent reproducibility, and nanogels measured 161 nm (PDI = 0.05). This rapid, cost-effective method enables precise and scalable control over hydrogel dimensions using only standard laboratory equipment, without specialized training. Full article

The rotational spectra of xanthene and its oxidation product xanthone were investigated by combining quantum chemical calculations with Fourier transform microwave spectroscopy in a jet-cooled environment. Xanthone was unexpectedly generated in the experiment when water was present in the reservoir of xanthene leading to the total disappearance of xanthene after few hours. Structurally, xanthone shows a near planar disposition, whereas xanthene exhibits a non-planar geometry with both benzene rings twisted out of the molecular plane. This geometry enables an inversion motion between two equivalent conformers, giving rise to a splitting in the ground vibrational state. A two-state analysis of the vibration–rotation interaction for the $v=0$ and $v=1$ states gives an energy separation between these states (inversion splitting) of $\Delta E_{01}=4689.7095\left(10\right)\mathrm{MHz}$. This large-amplitude motion leads to vibration–rotation coupling of energy levels. A symmetric double-minimum inversion potential function was determined, resulting in a barrier of about 45 cm⁻¹ in good agreement with that obtained by DFT quantum chemical calculations. Full article

Soybean (Glycine max (L.) Merr.) is a critical crop in China, serving as a primary source of food, oil, and animal feed. Drought stress significantly impacts soybean growth and yield. MicroRNAs (miRNAs) play crucial roles in plant drought responses. The miR164 family is highly conserved across plant species and has been shown to participate in drought responses in a range of plants, yet the function of miR164 in soybean remains unclear. In this study, we identified GmNAC35 as a direct target of miR164 through published degradome sequencing data and 5′ RLM-RACE assays. Under drought stress, miR164 members (e.g., MIR164a, MIR164f, and MIR164k) rapidly down-regulated, reaching their lowest expression at 2 h and returning to basal levels within 6 h. Conversely, GmNAC35 showed an inverse pattern, indicating negative regulation by miR164. Overexpression of GmNAC35 enhanced drought tolerance in transgenic soybean plants, as evidenced by higher survival rates and reduced water loss. Transcriptomic analysis revealed that GmNAC35 modulates stress-responsive pathways, including ABA signaling and phenylpropanoid biosynthesis. Our findings indicate that miR164 negatively regulates GmNAC35, a positive regulator of drought tolerance. This enhances our understanding of the molecular mechanisms of drought tolerance in soybean and may inform strategies for breeding drought-resistant varieties. Full article

Semi-submerged curtain breakwaters are increasingly favored to protect marinas and other microtidal basins, yet they are still almost exclusively designed with deterministic wave transmission equations. This study introduces a fully probabilistic design framework that translates uncertainty in wave climate and water level design parameters into explicit confidence limits for transmitted wave height. Using Latin Hypercube Sampling, input uncertainty is propagated through a modified Wiegel transmission model, yielding empirical distributions of the transmission coefficients K_t and H_t. Our method uses the associated safety factor required to satisfy a 95% non-exceedance criterion, SF₉₅. Regression analysis reveals the existence of a strong inverse linear relationship (R = −0.9) between deterministic K_t and the probabilistic safety factor, indicating that designs trimmed to low nominal transmission (e.g., K_t ≤ 0.35) must be uprated by up to 55% once parameter uncertainty is acknowledged, whereas concepts with greater transmission require far smaller margins. Sobol indices show that uncertainty in H_m0 and T_p each contribute ≈40% of the variance in H_t for a tide signal standard deviation of σ_η = 0.16 m, while tides only become equally important when σ_η > 0.30 m. Model-based uncertainty is negligible, standing at under 8%. The resulting lookup equations allow designers to convert any deterministic K_t target into a site-specific probabilistic limit with a single step, thereby embedding reliability into routine breakwater sizing and reducing the risk of underdesigned marina and port structures. Full article

Acrylamide (ACR), utilized as a precursor for producing polyacrylamide for water purification, has demonstrated neurotoxic properties. However, the mechanisms underlying its neurotoxicity remain inadequately understood. In this investigation, Caenorhabditis elegans were exposed to ACR at concentrations ranging from 250 to 1000 μg/mL and then their locomotor behavior, neuronal development, neurotransmitter concentrations, and gene expression profiles were assessed. Exposure to 250–1000 μg/mL ACR resulted in observable behaviors such as head swiveling and body bending, accompanied by a significant reduction in body size. Furthermore, ACR exposure caused damage to serotonergic, cholinergic, dopaminergic, and glutamatergic neuronal structures. In this context, elevated levels of serotonin, dopamine, acetylcholine, and glutamate were detected, along with notable upregulation of the expression of genes associated with neurotransmitters, including tph-1, cat-4, mod-1, mod-5, cat-1, ser-1, dat-1, dop-1, dop-3, unc-17, cho-1, eat-4, and glr-2. Moreover, ACR exposure elevated reactive oxygen species (ROS), O₂, and H₂O₂ levels while concurrently depleting glutathione (GSH), thereby compromising the antioxidant defense system. This led to a significant upsurge in the expression of genes involved in the nematode ACR detoxification pathway, specifically daf-16, skn-1, mlt-1, sod-3, gst-4, gcs-1, hsf-1, and hsp-16.2. Additionally, Spearman correlation analysis revealed a significant inverse relationship between certain neurotransmitter and antioxidant genes and locomotor activities, highlighting the role of these genes in mediating ACR-induced neurotoxicity in C. elegans. Collectively, this research enhances the understanding of the mechanisms related to ACR neurotoxicity. Full article

In this paper, a novel approximate triangular fuzzy finite element method (FEM) is proposed to solve the one-dimensional second-order unsteady nonlinear fuzzy partial differential Boussinesq equation. The physical problem concerns the case of the drought flow of a horizontal unconfined aquifer with a limited breath B and special boundary conditions: (a) at x = 0, the water level is equal to zero, and (b) at x = B, the flow rate is equal to zero due to the presence of an impermeable wall. The initial water table is assumed to be curvilinear, following the form of an inverse incomplete beta function. To account for uncertainties in the system, the hydraulic parameters—hydraulic conductivity (K) and porosity (S)—are treated as fuzzy variables, considering sources of imprecision such as measurement errors and human-induced uncertainties. The performance of the proposed fuzzy FEM scheme is compared with the previously developed orthogonal fuzzy FEM solution as well as with an analytical solution. The results are in close agreement with those of the other methods, with the mean error of the analytical solution found to be equal to $1.19·{10}^{-6}$. Furthermore, the possibility theory is applied and fuzzy estimators constructed, leading to strong probabilistic interpretations. These findings provide valuable insights into the hydraulic properties of unconfined aquifers, aiding engineers and water resource managers in making informed and efficient decisions for sustainable hydrological and environmental planning. Full article

This study addresses secondary soil salinization driven by shallow groundwater in the Yanqi Basin of southern Xinjiang, focusing on subsurface drainage system (SDS) optimization for salt regulation and oil sunflower productivity improvement in severe saline–alkali soils. Through controlled field experiments conducted (May–October 2024), we evaluated five SDS configurations: control (CK, no drainage) and four drain spacing/depth combinations (20/40 m × 1.2/1.5 m). Comprehensive monitoring revealed distinct spatiotemporal patterns, with surface salt accumulation (0–20 cm: 18.59–32.94 g·kg⁻¹) consistently exceeding subsurface levels (>20–200 cm: 6.79–17.69 g·kg⁻¹). The A3 configuration (20 m spacing, 1.5 m depth) demonstrated optimal root zone desalination (0–60 cm: 14.118 g·kg⁻¹), achieving 39.02% salinity reduction compared to CK (p < 0.01). Multivariate analysis revealed strong depth-dependent inverse correlations between groundwater level and soil salinity (R² = 0.529–0.919), with burial depth exhibiting 1.7-fold greater regulatory influence than spacing parameters (p < 0.01). Crop performance followed salinity gradients (A3 > A1 > A4 > A2 > CK), showing significant yield improvements across all SDS treatments versus CK (p < 0.05). Multi-criteria optimization integrating TOPSIS modeling and genetic algorithms identified A3 as the Pareto-optimal solution. The optimized configuration (20 m spacing, 1.5 m depth) effectively stabilized aquifer dynamics, reduced topsoil salinization (0–60 cm), and enhanced crop adaptability in silt loam soils. This research establishes an engineering framework for sustainable saline–alkali soil remediation in arid basin agroecosystems, providing critical insights for water–soil management in similar ecoregions. Full article