Search Results (15,139)

In Cambodia, farmers construct artificial household bat roosts to collect and sell guano as fertilizer. We investigated farming practices and attendant spillover risks using (1) surveys on guano production; (2) an estimation of bat population size and species present using carcasses, visual identification, and audio recordings; (3) surveys of guano-producing and neighboring households on water, sanitation, and hygiene practices; and (4) the testing of guano and household food, water, and surfaces for coronaviruses using RT-qPCR. Bat roosts are constructed using dried palm leaves with coconut tree and/or steel/concrete supports. Roosting areas ranged from 42 to 327 m², bat abundance varied from 0 to 11,187, guano production was between 5 and 120 kg/week, guano yields were from 0.15 to 0.4 kg/m²/week, and farmers earned USD ~100–200/household/month. Higher guano production in the peak (normally wet) season was associated with greater bat abundance (p = 0.016). The lesser Asiatic yellow house bat (Scotophilus kuhlii) was the only bat species identified. Roosts were <20 m from guano-producing households. Neighbors and households’ hygiene risks included not having handwashing stations and not covering food in storage/while drying. Coronaviruses (Alphacoronaviruses or Infectious Bronchitis Virus) were detected in 14.6%, 17.3%, 2.9%, 1.4%, and 0.0% of guano, urine, household surface, food, and water samples, respectively. While guano farming offers economic benefits, spillover risks exist. Safe guano collection and storage, handwashing, and food covering in guano-producing communities are necessary to mitigate spillover risks. Full article

Background/Objectives: Necrotic enteritis (NE), induced by Clostridium perfringens, is responsible for significant economic losses in the poultry industry worldwide. The growing restrictions on antibiotic use have driven the search for alternative strategies for disease control. The purpose of this study is to isolate and characterize lytic phages targeting multidrug-resistant C. perfringens type G recovered from chickens with NE. Methods: C. perfringens was isolated from chickens with NE using a culture method with selective TSC agar. Bacterial identification was carried out using biochemical tests and PCR. C. perfringens isolates were toxinotyped by PCR. Antibiotic susceptibility test was performed using the agar dilution method. Bacteriophages were isolated from chicken intestine samples collected from wet markets using the double-layer agar technique. Phage isolates were characterized by host range, one-step growth, stability, and whole genome sequencing. The efficacy of phage CPP8 in controlling multidrug-resistant C. perfringens type G was evaluated in GAM broth. Results: In this study, 16 C. perfringens strains were isolated from 100 chickens suspected of NE. Among these isolates, 10 (62.5%) belonged to type G, while the remaining 6 (37.5%) were type A. A total of 11 phages capable of lysing C. perfringens type G were isolated from the chicken intestine. Among them, phage CPP8 has the widest host range, short latent period, large burst size, and high stability. Moreover, the genome of CPP8 lacked genes related to antibiotic resistance, toxins, virulence factors, or lysogeny. Treatment with CPP8 resulted in a significant reduction in viable counts of C. perfringens at 37 °C. Conclusions: Our findings highlight phage CPP8 as a promising candidate for bio-control of multidrug-resistant C. perfringens type G. Full article

Expansive clay slopes are vulnerable to progressive strength loss induced by repeated wetting and drying, a mechanism that drives shallow failure in active moisture zones. Reproducing this degradation experimentally is time-consuming and resource-intensive. This study evaluates whether Fully Softened Strength (FSS) can serve as a practical substitute for five wet–dry cycles in expansive clay slope stability assessment. Direct shear tests were conducted on wet–dry-cycled and reconstituted FSS specimens across fourteen experimental water contents. Strength parameters were incorporated into homogeneous and heterogeneous limit equilibrium slope models, considering degraded layer thicknesses of 1–5 m and suspended water table conditions. Equivalence was assessed using root mean square error (RMSE), prediction bias, and physical representativeness. Five wet–dry cycles produced a dominant cohesion reduction of 70.4% with minor changes in friction angle, reaching a quasi-stationary degraded state. FSS reproduced an equivalent system response through mechanical compensation between cohesion and friction—not through equality of strength parameters—under shallow failure conditions. The best statistical fit was obtained at w = 43.5% (RMSE = 0.314); however, w = 42.0%, coinciding with the liquid limit, provided a physically more robust interpretation with near-zero bias. Equivalence was found to be valid only for normal stresses ≤ 50 kPa, representative of shallow failure depths of 1–4 m. Full article

LiDAR-based 3D object detection is critical for autonomous driving perception. Ensuring robust sensing under adverse weather is essential for safe deployment. Current physics-based simulation methods focus on atmospheric effects but offer limited ground-level modeling, leading to domain gaps between simulated and real-world snowy data. Ground-level effects are challenging to model due to diverse physical interactions: wet surface reflectivity changes, vehicle-induced spray, and multi-layer snow scattering. This paper proposes a simulation method with more comprehensive ground-effect modeling for snowfall scenarios. Our approach introduces two modules: (i) an extended spray model with precipitation-controlled parameters that jointly models spray noise and wet ground attenuation, and (ii) a multi-layer dual-mode backscattering model that captures both diffuse and specular reflections on snow-covered ground. Both modules share a unified precipitation-driven parameterization. Higher snowfall rates simultaneously control spray generation, wet surface reflectivity, and snow accumulation depth. This design ensures physical consistency and makes the approach applicable across diverse LiDAR systems without sensor-specific tuning. Experiments on the STF dataset demonstrate consistent improvements over four state-of-the-art methods under both heavy and light snowfall. Clear-weather performance is preserved. Evaluations on roadside LiDAR further confirm generalizability to infrastructure-based scenarios. Full article

Based on monthly meteorological observations from 57 stations in Jiangsu Province during 1961–2022, the Standardized Precipitation Evapotranspiration Index (SPEI) was calculated to characterize regional dry–wet variability. Empirical Orthogonal Function (EOF) analysis was applied to extract the dominant spatially coherent dry–wet modes, and cross-wavelet analysis was further employed to examine, in the time–frequency domain, the mode-specific responses to multiscale climate drivers, including the El Niño–Southern Oscillation (ENSO), Sunspot Number (SSN), Arctic Oscillation (AO), and Pacific Decadal Oscillation (PDO). The results show that dry–wet variability in Jiangsu Province is primarily organized by a regionally coherent mode (EOF1, explaining 56.3% of the total variance) and a north–south dipole mode (EOF2, explaining 17.8%), with the zero-value line of EOF2 closely aligned with the Huaihe River–Subei Irrigation Canal climatic transition zone. The temporal coefficient of EOF1 (PC1) exhibits a significant regime shift around 2013, followed by a pronounced wetting trend across the entire region. This change may reflect recent hydroclimatic adjustments in the study area, although the present study does not attempt a formal attribution of the respective thermal and precipitation contributions. In contrast, the temporal coefficient of EOF2 (PC2) undergoes an abrupt change around 1980, indicating a transition of the spatial dry–wet pattern from “southern drought–northern flood” to “southern flood–northern drought,” broadly consistent with an interdecadal climatic transition. Cross-wavelet analysis further reveals that PC1 is closely associated with ENSO at interannual timescales, with a lag of approximately 4–6 months, while its long-term variability shows time–frequency coherence with SSN. PC2 also exhibits time–frequency coherence with SSN at longer timescales, with an apparent phase transition around the 1980s; however, this low-frequency signal should be interpreted cautiously because the underlying physical mechanism remains uncertain. Overall, this study shows that dry–wet variability in Jiangsu Province is organized by two leading spatial modes with distinct temporal evolution and scale-dependent climate linkages. These findings provide new evidence for understanding hydroclimatic variability in monsoon transition zones and offer a basis for spatially differentiated drought–flood risk assessment. Full article

A two-year field experiment was conducted to clarify the regulatory effects of nitrogen (N), phosphorus (P), and potassium (K) combined with drip fertigation on the yield, yield components, and grain quality of winter wheat in lime concretion black soil (Calcaric Cambisols). The objective was to screen a sustainable fertilization model for coordinating high yield and quality in the Huang-Huai-Hai Plain. An L₁₆(4³) orthogonal design was adopted to investigate yield, protein content, wet gluten, test weight (TW), and grain hardness. Range analysis and ANOVA were used to evaluate factor effects and interactions. The results showed that N was the dominant factor affecting yield and quality (Rank 1), followed by K (Rank 2), while P showed the weakest effect. Compared to the control (N0P0K0), the optimized N–P–K combination increased grain yield by an average of 315.0% and enhanced grain crude protein by 55.3% over the two seasons. The optimal combination for maximum yield was N170P30K120 (kg/ha), which optimized the source–sink relationship by balancing spike density and 1000-grain weight. High N (220 kg/ha) combined with low P and high K achieved the best nutritional quality. The 3D response surface analysis confirmed significant synergistic interactions between N–K and N–P in promoting grain filling and protein synthesis. Rational NPK drip fertigation, particularly when synchronized with critical growth stages (jointing and grain filling), can simultaneously enhance grain yield and quality in this soil type. The optimized combination provides theoretical support and a robust fertilization strategy for green and efficient wheat production in the region. Full article

Meat serves as a prime medium for the growth of foodborne pathogens due to its rich protein content and high water activity, contributing significantly to the global burden of foodborne illnesses. This review synthesizes current advances in meat-borne bacterial pathogen detection with particular emphasis on emerging artificial intelligence (AI)-enabled applications. Major pathogens of concern, including Salmonella, Listeria monocytogenes, Escherichia coli, Campylobacter, Clostridium, and Staphylococcus aureus, are examined in relation to their relevance across the meat supply chain. Recent progress in biosensors (clustered regularly interspaced short palindromic repeats), CRISPR-based assays, isothermal amplification, and metagenomics is evaluated alongside the growing role of AI in automating signal interpretation, enhancing image-based diagnostics, and supporting early contamination prediction. AI-based systems have proved 96.4–104% recovery and 100% bacterial capture ability. Embedding AI methods in a wet lab demands technical and logical modeling, as well as learning and calibration decorum. Nonetheless, AI readiness and full-scale application for meat-borne pathogens surveillance are on the way. Furthermore, additional focus is aligned on meat-borne bacterial pathogen genomic databases, i.e., (NCBI Pathogen Detection, EnteroBase, VFDB, ComBase, and GenBank), which serve as critical training resources for AI models for outbreak tracking, virulence profiling, and antimicrobial resistance (AMR) prediction. By integrating molecular methods, genomic surveillance, and AI-driven analytics, this review presents a framework for strengthening meat safety systems. This will improve early detection capabilities and support data-driven public health interventions in the future. Full article

Agronomic practices can modify cereal grain chemical composition and processing performance. Long-term evidence linking agricultural management with functionality-related quality remains limited, especially in terms of combined tillage x crop residue management strategy. We evaluated the effects of long-term tillage simplifications and straw management on productivity and processing-relevant traits of winter wheat and spring barley in a split-plot field experiment (Lithuania). Straw was either removed (S0) or chopped and retained (S1), and six tillage systems were compared (conventional ploughing (CP), shallow ploughing (SP), shallow cultivation (SOW), stubble over winter, no-till with cover crops (NTC), and no-till without cover crops (NT)). The yield and starch content of winter wheat and spring barley groats increased with the addition of straw and the application of SOW, NTC, and NT systems. The hectolitre mass of winter wheat and spring barley grains increased with the addition and removal of straw using SP technology. The protein content and wet gluten content of winter wheat and spring barley grains decreased, while the starch content increased, with the addition and removal of straw using SC technology. In wheat, protein content showed weak separation among treatments, while wet gluten and Zeleny sedimentation displayed mostly directional trends (wet gluten–sedimentation correlation: r = 0.844 under S0 and r = 0.984 under S1). In terms of the tillage systems, it can be stated that in most cases, SP and NT increased grain yield and improved quality indicators, while SC and NTC technologies showed opposite results. Soil-function assessment (CEI, 10–25 cm) indicated substantially higher integrated soil functioning under conservation agriculture (e.g., SOW/NTC/NT: 5.28–5.70) than under conventional systems (CP: 3.23). The results support framing sustainable soil management for cereal functionality as a system package: residue retention enables the productivity benefits of reduced-tillage systems while maintaining key quality proxies. Full article

Red mud discharged during alumina production via the Bayer process is characterized by high contents of sodium carbonate, sodium sulfate, and other soluble salts, and it remains poorly utilized and accumulates in long-term stockpiles. Sodium percarbonate has found extensive industrial applications, and its synthesis via the salting-out method represents one of the dominant industrial routes. In this context, sodium sulfate was employed as a salting-out agent. On the basis of relevant ternary systems, the phase equilibrium of the quaternary system Na₂CO₃–Na₂SO₄–H₂O₂–H₂O at 5 °C was systematically investigated and calculated. The objective was to utilize red mud as a waste resource and develop a novel integrated process that favored the wet synthesis of sodium percarbonate while enabling the efficient separation of sodium salts. The solubility data for the ternary subsystems constituting the above quaternary system were correlated using the Pitzer model, yielding the corresponding ion interaction parameters and activity coefficients. The validated model was then applied to predict the phase equilibrium data of the quaternary system. Verification results indicate that the calculated values are in satisfactory agreement with the experimental data. On the basis of the phase equilibrium data of the Na₂CO₃–Na₂SO₄–H₂O₂–H₂O system at 5 °C, a phase diagram was constructed. Along with five solid-phase crystallization fields, three invariant points were identified: the co-saturation point of Na₂SO₄·10H₂O, Na₂CO₃·10H₂O, and Na₂CO₃·1.5H₂O₂·H₂O; the co-saturation point of Na₂SO₄·10H₂O, Na₂CO₃·1.5H₂O₂·H₂O, and Na₂SO₄·0.5H₂O₂·H₂O; and the co-saturation point of Na₂CO₃·1.5H₂O₂·H₂O, Na₂SO₄·0.5H₂O₂·H₂O, and Na₂CO₃·2H₂O₂·H₂O. From phase diagram analysis, a novel wet process route for sodium percarbonate production using waste red mud is proposed. The process involves chemical reaction, crystallization, separation, and drying to obtain the final product. A new process flow diagram for the value-added production of sodium percarbonate is also presented. Full article

Hyperspectral airborne data combined with machine learning has proven effective for characterizing plant nutritional quality. However, terrain, viewing geometry, and illumination can distort spectral signatures, leading to biased models with limited generalizability for large-scale mapping across farms with a heterogeneous landscape. In this study, we developed a framework for mapping pasture quality using airborne hyperspectral imaging while explicitly accounting for in-field acquisition and environmental effects. Nitrogen content (N%) and metabolizable energy (ME) were used as reference indicators across four hill country farms in New Zealand with contrasting environmental and management conditions. Ground truth was obtained using standard laboratory wet chemistry methods and paired with AisaFENIX airborne hyperspectral data, resulting in 1610 spectral samples derived from 161 spatially independent ground plots. Gaussian Process Regression (GPR) and a one-dimensional convolutional neural network (1D-CNN) were trained and evaluated on an independent test dataset. Both models achieved strong predictive performance (R² > 0.8); however, GPR provided more reliable estimates through predictive uncertainty. Using a 95% confidence interval threshold to mask uncertain predictions increased overall performance (R² > 0.9) and consequently improved the reliability of the mapped outputs. This approach enables spatially explicit pasture nutrient assessment to support precision land management for carbon and nitrogen. Full article

Tree bark, an abundant by-product of the timber industry, represents a promising feedstock for sustainable construction. This study investigates the thickness swelling, water absorption, hygroscopicity and mechanical (compressive strength) properties of insulation panels produced from hardwood bark (Tilia spp. and Robinia pseudoacacia) via hydromechanical treatment and a wet-forming process. The panels were produced without added adhesives, relying on the formation of hydrogen bonds during the drying phase to ensure structural integrity. Both bark-based insulation boards (thermal conductivity coefficient 0.055–0.057 W/m·K) showed similar hygroscopic behavior, reaching equilibrium moisture contents of max. 25% at 93.9% RH. Water absorption after 24 h immersion was highly material-dependent; Tilia-based panels showed 57.11 ± 5.81%, and Robinia-based panels 320.61 ± 11.34%. Thickness swelling remained low (max. 6% for Robinia), showing significant orthotropic anisotropy. At 10% compressive strain, the Tilia and Robinia bark-based panels showed compressive strengths of 188 ± 14.6 kPa and 298 ± 18.1 kPa, accordingly. These findings demonstrate that hardwood bark can be successfully valorized into high-performance, binderless insulation, supporting circular economic strategies. Full article

Water pollution control for wetland lakes has undergone a fluctuating development process. Effective pollution management requires not only scientific water quality monitoring data but also clear identification of pollution sources within the study area. Accordingly, this study investigated Mudong Lake, the core area of the Huixian Wetland, and conducted water quality monitoring in January 2023 (dry season) and June 2023 (wet season). Based on the Water Quality Index (WQI) assessment results, water quality was better in the wet season than in the dry season. To identify pollution sources, the Absolute Principal Component Score-Multiple Linear Regression (APCS-MLR) model was applied. The results showed that pollution in the dry season was mainly derived from aquaculture and agricultural non-point source pollution, anthropogenic point source pollution, and internal release from sediments, while pollution in the wet season exhibited mixed characteristics, driven by agricultural non-point sources, domestic sewage discharge, and natural factors. Source apportionment analysis indicated that composite pollution sources (domestic sewage and aquaculture wastewater), agricultural non-point source pollution, and other unidentified sources contributed 43.71%, 34.11%, and 22.18% of the total pollution load, respectively. The findings of this study can provide a scientific basis for pollution control, emission reduction, and the targeted management of Mudong Lake. Full article

Atalantia ceylanica, locally known as Yaki naran (YK), is a native plant of Sri Lanka, growing commonly in the dry and wet–intermediate zones. In this study, powdered samples of Yaki naran (YK) were sequentially extracted using hexane, ethyl acetate (EtOAc), and methanol (MeOH). The resulting extracts were assessed for total phenolic content, antioxidant potentials, and in vitro α-amylase, α-glucosidase, and lipase inhibitory activities using relevant assays. The crude extracts were then subjected to separation and purification by column chromatography and preparative thin-layer chromatography. Although twelve compounds were obtained from the three crude extracts, only three had sufficient yields to proceed. Out of the three pure isolates, compound SAC 4 was identified as 2,4-di-tert-butylphenol, a phenolic compound, by using ¹H and ¹³C NMR data and FTIR spectroscopic data, followed by evaluation of bioactivities such as antioxidant properties, enzyme inhibitory assays, etc. Based on the results of the bioassays, compound SAC 4 was identified to show strong α-glucosidase inhibitory activity, moderate antioxidant activity, and lipase inhibitory activity. Full article

The sustainable utilization of multiple reclaimed pavement materials is a critical pathway toward green highway construction. This study investigates the performance and synergistic mechanisms of cold-recycled mixtures incorporating both Reclaimed Asphalt Pavement (RAP) and Reclaimed Cement-Stabilized Base (RCSB), using emulsified asphalt as the primary binder. A comprehensive experimental program was conducted to evaluate the effects of reclaimed material proportions, mixing sequences, and curing ages on the mechanical strength, moisture susceptibility, and high-temperature stability of the mixtures. Microscopic characterization via Scanning Electron Microscope (SEM) and Energy Dispersive Spectroscopy (EDS) were employed to elucidate the Interfacial Transition Zone (ITZ) evolution. Results indicate that an optimal RCSB incorporation range of 20–40% establishes a robust “stone-to-stone” rigid skeleton, significantly enhancing the splitting strength (up to 0.87 MPa) and durability (Splitting Strength Ratio, TSR > 91%). SEM observations confirm the formation of a dense interpenetrating network structure within this range, where cement hydration products and asphalt films achieve optimal chemo-physical bonding. Exceeding 40% RCSB leads to a moisture-starved state and a sharp decline in dynamic stability due to insufficient binder coating. Micro-morphological characterization reveals that the transition from macro-interfacial debonding to a robust cohesive failure mode is the fundamental driver for the performance peak at 20–40% RCSB. SEM observations confirm the formation of a dense interpenetrating network structure, where cement hydration products successfully anchor into the asphalt film. This optimized ITZ effectively eliminates the stress concentration and aggregate crushing seen in high-RAP mixtures, thereby ensuring superior mechanical integrity. Furthermore, a pre-wetting mixing sequence ensures a high-energy mineral surface that promotes the heterogeneous nucleation of cement. SEM results show that this prevents the competitive adsorption between cement and asphalt, transforming the ITZ from a friable, loose state into a densified crystalline adhesive matrix. Full article

Physics-based simulation of debris flows over complex terrain is essential for hazard assessment, but repeated numerical integration is costly when many scenarios must be explored. We develop a general deep-learning surrogate modelling framework for two-dimensional (2D) debris-flow propagation, here applied to the Morino–Rendinara area (central Italy) using a three-dimensional (3D) Fourier Neural Operator (FNO) trained on synthetic simulations generated by a validated in-house finite-volume shallow-water solver. The solver reproduces debris-flow propagation over complex terrain and is specifically developed for artificial intelligence (AI) applications. It is based on a depth-averaged 2D formulation using the Harten–Lax–van Leer–Contact (HLLC) approximate Riemann solver, hydrostatic reconstruction, positivity-preserving wet–dry treatment, and Voellmy-type basal friction, and was verified through analytical benchmarks, numerical tests, and back-analyses of real events. The dataset was built from four site-specific release settings derived from real topography, combining different released volumes and bulk densities while preserving local geomorphological and rheological characteristics. Each simulation was stored as a full spatio-temporal tensor and used to train an FNO conditioned on coordinates, topography, friction parameters, bulk density, and initial release thickness. Training used a novel loss to emphasize active-flow areas and improve velocity reconstruction, and was performed using a graphics processing unit (GPU). The surrogate shows effective generalization to within-distribution validation samples, with global relative mean squared errors of 5.49% for flow thickness, 5.34% for velocity component u, and 2.60% for v, and mean $R^2$ values of 0.95, 0.94, and 0.97. For a representative sample, the surrogate predicts the full spatio-temporal solution in $0.52$ s, versus about 47 s for the first-order finite-volume solver, corresponding to a speed-up of about $91\times$, with an even larger gap expected for higher-order solvers, since, whilst the computation time of the solver increases as its complexity increases, the computation time of the FNO remains essentially unchanged. These results indicate that the proposed FNO is a reliable site-specific surrogate for rapid approximation of 2D debris-flow dynamics over real terrain, with potential for uncertainty propagation, Monte Carlo analysis, large-ensemble simulation, and hazard-oriented scenario assessment. Full article