Search Results (1,544)

Water quality monitoring is important for protecting aquatic life and supporting informed water quality assessment and environmental decision support. However, many existing systems mainly focus on data collection and threshold-based alerts, without connecting prediction, diagnosis, and intelligent assessment within a unified workflow. This paper proposes an integrated smart aquatic monitoring system using Southeast Texas (SETX) water quality data, advanced machine learning models, large language models (LLMs), and an agentic n8n workflow. Firstly, SETX water quality data are extracted, cleaned, and converted into a structured CSV format. Important water features such as pH, dissolved oxygen, temperature, conductivity, and total dissolved solids are used to train and evaluate four different machine learning models, including Transformer, Quantum Neural Network (QNN), XGBoost, and Random Forest. The ML model is then deployed to a backend system for use inside the n8n automation workflow. For simulation, a Python script is designed to emulate an IoT water quality sensor by reading dataset records, converting valid records into JSON objects, and sending them to an agentic n8n webhook. The n8n workflow receives the sensor data and forwards it to the deployed model to predict surface water quality status. Across three simulations with three different datasets, the ML models demonstrate strong performance in classifying safe and unsafe water conditions. On the SETX dataset, Random Forest achieved the best performance, with 99.97% accuracy and a 99.95% macro F1-score. XGBoost also performed strongly, achieving 99.91% accuracy and a 99.86% macro F1-score. The Transformer model achieved 95.98% accuracy and a 94.00% macro F1-score, while the QNN model achieved 94.78% accuracy and a 92.24% macro F1-score. These results demonstrate that the processed SETX dataset supports reliable water quality prediction and can be integrated into the proposed n8n-based intelligent monitoring workflow. The prediction results are subsequently analyzed by an LLM-based diagnosis agent to generate an LLM-based water quality assessment, risk classification, and assessment summary that explain the prediction and highlight the most influential water quality parameters. The proposed system demonstrates a practical framework for combining sensor simulation, predictive modeling, LLM-based decision support, and agentic workflow automation for intelligent water quality assessment and smart environmental monitoring. Full article

Cellulose-derived carbon inputs to paddy soils have increased with the widespread adoption of straw return as a sustainable rice cultivation practice. However, the effect of cellulose-derived carbon inputs on photosynthesized C allocation from aboveground to belowground and the utilization of the photosynthesized C by soil microbial groups remain poorly understood. In this study, using continuous ¹³CO₂ labeling, ¹³C allocated to the above- and belowground C pools was measured to study the effects of cellulose and nitrogen fertilization on photosynthetic dynamics and microbial rhizodeposit utilization. Cellulose, nitrogen, and combined fertilization of cellulose and nitrogen promoted the allocation of photosynthates to the shoots. The combined fertilization of cellulose and nitrogen maximally decreased the allocation of photosynthesized C in the belowground C pools, including roots, soil organic matter, dissolved organic C, microbial biomass C, and phospholipid fatty acids (PLFAs), leading to a dominant microbial community that utilized the rhizodeposit shift by different fertilization practices. Cellulose or nitrogen fertilization increased the percentage of ¹³C in the Gram-positive (G+) (a15:0, i15:0, and i16:0) and Gram-negative (G−) (17:1ω8c) groups, while the combined fertilization of cellulose and nitrogen stimulated the G+ (a17:0), actinomycetes (10Me16:0 and 10Me18:0), fungi (18:1ω9c), and anaerobes (cy19:0) groups. Moreover, cellulose promoted the incorporation of rhizodeposits into soil macro-aggregates, thereby decreasing the utilization of rhizodeposits by microorganisms (¹³C-PLFA). The findings of this study suggest that under the prevalent practice of cellulose-derived C and N fertilization inputs, belowground photosynthetic C allocation and microbial utilization may decrease, potentially facilitating the retention of rhizodeposit-derived C in paddy soils. Full article

Emergency treatment of algal blooms in lake and reservoir source waters requires coagulants that remain effective under changing raw water conditions. This study compared polyaluminum chloride (PAC) and chitosan (CTS) in raw water collected from Yangku Reservoir during wet and dry seasons. Jar tests evaluated algal density, algal biomass, and nitrogen and phosphorus fractions across a 3~15 mg/L reagent-mass dosage range. Treatment performance differed between seasons. Mean algal density and soluble reactive phosphorus (SRP) removals in the wet season were 63.12% and 68.51%, respectively, and an apparent 70.05% decrease in measured NH₄⁺-N concentration was also observed. Because the fate of dissolved inorganic nitrogen was not resolved, the NH₄⁺-N decrease should not be interpreted as direct coagulative removal. Dry season water had higher algal density and a higher SRP/TP ratio. PAC maintained relatively stable algal biomass removal across seasons and showed stronger phosphorus removal, whereas CTS was more sensitive to seasonal changes in the raw water matrix. These findings support season-specific preliminary screening of coagulants while highlighting the need for residual-Al, pilot-scale, and process-mechanism validation before full-scale application. Full article

This study proposes a new method for the topological synthesis of principal component projections and hydrogeochemical stoichiometric equality lines on self-organizing map (SOM) component planes to assess groundwater chemistry forming factors and quality in the Pleistocene unconfined aquifer of the Southern Bug and Sinyukha interfluve area, Ukraine. The hydrogeochemical characteristics clustered by the SOM were further examined using the graphical cross-validation method. The groundwater dataset used in the analysis consisted of 10 parameters (i.e., pH, total dissolved solids, $\mathrm{C}{\mathrm{a}}^{2+}$, $\mathrm{M}{\mathrm{g}}^{2+}$, $\mathrm{N}{\mathrm{a}}^{+}$, ${\mathrm{K}}^{+}$, $\mathrm{H}\mathrm{C}{\mathrm{O}}_3^{-}$, $\mathrm{C}{\mathrm{l}}^{-}$, $\mathrm{S}{\mathrm{O}}_4^{2-}$, and $\mathrm{N}{\mathrm{O}}_3^{-}$) from 91 samples collected during the dry season. Subsequently, for SOM construction, we utilized six log-ratio relationships of milliequivalent ion concentrations. Based on the results, the hydrogeochemical groundwater data were classified into three clusters, which revealed three water types and processes controlling their chemistry: salinity driven by sulfate inputs (Cluster 1), highly salinity driven by nitrate-chloride and sulfate pollution (Cluster 2), and relatively fresh water governed by natural carbonate dissolution and silicate weathering (Cluster 3). The salinity types were identifiable in the northern part of the study area, characterized as the primary zone of initial intense pollution. High salinity types were identified in the eastern and southeastern parts of the territory (with delayed water exchange), whereas relatively fresh types were identified in the central part (with active water exchange) as well as in the western and southwestern parts. Modeling confirmed that extensive sulfate, nitrate, and chloride contamination led to anthropogenic degradation of the aquifer system. Full article

Understanding habitat suitability and environmental preferences of shortbill spearfish (Tetrapturus angustirostris) is essential for assessing and mitigating bycatch risk in pelagic longline fisheries. Using observer data collected by the Chinese Pacific tuna longline fishery, including 19,932 longline sets collected during 2010–2021, we compared five individual modelling algorithms and three ensemble strategies to predict habitat suitability across the Pacific Ocean and identify key environmental drivers. Model performance was evaluated using repeated 10-fold cross-validation with three repetitions. The stacking ensemble achieved the highest predictive performance (AUC = 0.872; TSS = 0.591), followed closely by random forest (RF; AUC = 0.869), although the absolute difference between these two models was small. A sensitivity analysis including log-transformed observed hooks resulted in only minor improvements in RF and stacking performance and did not materially alter the main habitat-suitability patterns. Both generally outperformed the other individual and weighted ensemble models. Permutation-based importance analyses consistently identified salinity as the strongest environmental predictor of habitat suitability, followed by chlorophyll-a concentration, distance to shore, and dissolved oxygen concentration. Partial dependence analyses showed that the stacking ensemble produced smoother and more readily interpretable responses to environmental gradients, particularly salinity and dissolved oxygen, whereas RF placed greater importance on a limited number of dominant predictors. Highly suitable habitat was primarily predicted in subtropical offshore waters of the southeastern Pacific (10° S–25° S, 100° W–130° W), which were characterized by relatively high salinity, moderate dissolved oxygen concentrations, and low chlorophyll-a concentrations. A secondary area of elevated suitability was identified in the central North Pacific (160° E–180° E, 15° N–25° N). Overall, the stacking ensemble provided robust predictions of shortbill spearfish habitat suitability, whereas RF remained useful for identifying dominant environmental correlates. The predicted habitat maps provide a spatial basis for identifying potential bycatch-risk hotspots and supporting adaptive management strategies, such as spatially targeted monitoring and mitigation measures in tuna longline fisheries. Full article

Microneedle-based transdermal drug delivery enables painless and efficient drug administration but is limited by insufficient mechanical strength and high insertion forces. Inspired by the efficient penetration capability of cactus spines, this study investigated the microstructure and biomechanics of natural cactus spines and bioinspired microneedles. Finite element analysis showed that a groove width of 50 μm produced the highest stress and strain. Solid bioinspired microneedles were fabricated by 3D printing, while dissolvable hyaluronic acid, chitosan, and gelatin microneedles were prepared using femtosecond laser-fabricated titanium molds and replica molding. Optimized laser parameters generated micropores approximately 500 μm deep. Mechanical tests showed insertion forces of 60–100 mN for solid microneedles, with the 50 μm groove design exhibiting the highest value. Among dissolvable microneedles, gelatin displayed the greatest mechanical strength, whereas hyaluronic acid demonstrated the best overall potential for transdermal drug delivery. Full article

Environmental change can alter aboveground and belowground plant inputs, with consequences for soil carbon (C) and nitrogen (N) cycling and their coupling. However, how soil C and N respond differently to root and litter removal, and which factors regulate these responses, remain unclear. Here, we conducted a meta-analysis to quantify changes in soil C and N following root and aboveground litter (hereafter, litter) removal and to identify the factors associated with these changes. We found that (1) litter removal significantly decreased soil organic C (SOC), dissolved organic C, total N, microbial biomass N, ammonium N concentrations and nitrous oxide emissions by 11%–30%, whereas root removal increased nitrate N concentration by 88%; (2) the response ratios of microbial biomass C and N were not correlated under either root or litter removal, whereas those of total C and N concentrations were positively correlated; (3) the effects of root and litter removal on soil C and N varied with season and soil depth, with the strongest responses occurring in autumn and winter and in the surface soil layer (0–10 cm); and (4) these responses were moderated primarily by leaf type and, to a lesser extent, by ecosystem type, elevation, mean annual precipitation, soil properties and experimental duration. Overall, our results clarify how altered plant inputs affect soil C and N pools and identify the conditions under which these effects are strongest, thereby informing predictions of C and N cycling under global change. Full article

Low-fertility reconstructed soils in spoil heaps cause slow and fluctuating soil carbon (C) and nitrogen (N) accumulation over time; identifying key drivers is vital. We used metagenomics to examine restoration age and vegetation-type effects on rhizosphere nutrients, aggregate structure, core microbiota, and C–N-cycling genes in western Inner Mongolia spoil heaps. Key findings: (1) A. fruticosa increased mineral-associated organic carbon (MAOC) by 26.03% on average across 28 years compared to other vegetation ($p < 0.001$); M. sativa boosted transient dissolved organic carbon (DOC) by 41.94% in early restoration (6 years) versus one-year alfalfa ($p < 0.001$). (2) The 28-year M. sativa treatment enhanced organic carbon degradation gene abundance by 134.98% over 28-year A. fruticosa ($p < 0.05$), while A. fruticosa increased the nitrification-related nirK gene by 326.42% versus M. sativa ($p < 0.05$). (3) Core microbiota (e.g., Nocardioides) regulated iron-oxide-bound organic carbon (58.34% variance explained), and microbial C–N-cycling gene abundance correlated significantly with it ($r=0.665, p < 0.001$). These findings provide a theoretical basis for soil ecological function recovery in open-pit coal mine spoil heaps within the temperate semi-arid steppe–desert steppe ecotone and a scientific foundation for soil reconstruction technologies to accelerate rehabilitation in western Inner Mongolia. Full article

Salt-affected soil constrains maize establishment, and rhizosphere and non-rhizosphere responses to soil biochar remain difficult to establish. We evaluated soil physical and nitrogen properties, qPCR marker genes, 16S and ITS communities, and molecular profiles of dissolved organic matter (DOM) in a 90-day randomized complete block pot experiment (four biochar rates; five blocks; 20 pots). Control maize did not survive; control pots therefore yielded only non-rhizosphere soil, whereas rhizosphere and non-rhizosphere samples from biochar pots were paired. Block-adjusted comparisons showed higher water content and porosity and lower bulk density in all biochar non-rhizosphere groups than in the control (Holm-adjusted p < 0.05). Biochar-associated shifts in mineral-N partitioning and selected DNA-level marker-gene abundances accompanied design-aware community differences for NR treatment, R dose and pooled compartment (16S R² = 0.360, 0.435 and 0.218; ITS R² = 0.720, 0.712 and 0.304; all p < 0.001); fungal differences also included heterogeneous dispersion. D90 FT-ICR MS profiles described relative DOM molecular variation, but cross-layer residual associations did not survive false-discovery rate correction. Thus, biochar-associated physical and nitrogen changes coincided with microbial and relative DOM restructuring under the tested pot conditions. Because control survival was confounded with treatment, these are observed-group associations rather than pure causal biochar effects. Full article

The invasive golden apple snail (Pomacea canaliculata) threatens rice agroecosystems, yet its direct density-dependent effects on flooded paddy soil biogeochemistry and bacterial communities remain unclear. We established flooded soil microcosms with four snail densities (0, 2, 4, and 6 snails/box) for 20 days, without external food inputs. Soil dissolved organic carbon (DOC), ammonium nitrogen (NH₄⁺-N), nitrate nitrogen (NO₃⁻-N), and the activities of β-glucosidase, N-acetyl-β-D-glucosaminidase, urease, and dehydrogenase were measured, and bacterial communities were characterized by full-length 16S rRNA gene amplicon sequencing. Snail density was significantly and positively related to all three nutrient variables and all four enzyme activities. The dominant bacterial phyla and genera remained stable, and bacterial α-diversity changed little among treatments, despite a small but significant increase in Simpson diversity in the high-density treatment. PERMANOVA detected significant differences in overall bacterial community structure among density treatments, while environmental fitting identified DOC, urease, and dehydrogenase as variables significantly associated with community variation. These findings indicate that living golden apple snails can alter nutrient availability, soil biochemical activity, and bacterial community organization in flooded paddy soil, revealing a belowground pathway through which this invader may influence paddy ecosystem functioning. Full article

Dissolving microneedles offers a minimally invasive approach for transdermal drug delivery by facilitating drug transport across the stratum corneum while overcoming several limitations associated with conventional routes of administration. Benzhydroxamic acid has demonstrated biochemical and computational evidence associated with inflammatory and pain-related pathways; however, its incorporation into a dissolving microneedle platform has not been extensively explored.This study aimed to fabricate and characterize benzhydroxamic acid-loaded dissolving microneedles using a 3D-printing-assisted mold fabrication approach for transdermal drug delivery. A stereolithography-based 3D-printed master mold was used to prepare a reverse polydimethylsiloxane mold. Benzhydroxamic acid-loaded dissolving microneedles were fabricated using a PVA/PVP polymeric matrix and evaluated for their physicochemical, mechanical, insertional, and drug-delivery characteristics. The developed microneedles exhibited shear-thinning behavior, uniform morphology, and satisfactory mechanical properties, with a compression force of 3.5 ± 0.01 N/needle and tensile strength of 3.84 ± 0.21 MPa. The formulation demonstrated a drug-loading efficiency of 94.6 ± 0.35% and effective insertion into the Parafilm^® M skin-simulant model. In vitro drug release reached 97.24% over 24 h, while ex vivo skin permeation reached 94.83% over 24 h. FTIR and XRD analyses indicated successful incorporation of benzhydroxamic acid into the PVA/PVP matrix without major evidence of drug–polymer incompatibility. The findings demonstrate the feasibility of incorporating benzhydroxamic acid into a PVA/PVP dissolving microneedle platform using a 3D-printing-assisted mold fabrication approach. The developed system exhibited suitable physicochemical and mechanical characteristics, efficient drug loading, effective insertion, and satisfactory in vitro and ex vivo drug-delivery performance, supporting its potential as a transdermal drug delivery platform. Full article

This study evaluated the effects of oligomeric ultrafine-nano hydrogen water (OUHW) on production performance, egg quality, egg nutrient deposition, systemic metabolism, intestinal barrier function, and reproductive status in late-laying hens. Unlike conventional hydrogen-rich water, which primarily delivers molecular hydrogen dissolved in water, OUHW integrates oligomeric water with ultrafine-nano-sized hydrogen bubbles, providing a distinct physicochemical form of hydrogen-water intervention. A total of 288 healthy 67-week-old Jingfen No. 8 laying hens were assigned to 2 treatments with 6 independent replicates per treatment (24 hens per replicate) and provided with either tap water or OUHW for 11 weeks. Compared with the control, OUHW reduced the feed conversion ratio and the rates of manure-spotting while increasing the laying rate, qualified egg rate, and total egg number during weeks 5–8 (p < 0.05). These productive and egg quality improvements were phase-specific effects observed in the late laying stage during the 11-week trial. At week 4, OUHW significantly increased egg weight (p < 0.05). At week 8, OUHW also improved eggshell compressive elastic deformation, eggshell thickness, albumen height, and Haugh unit (p < 0.05). At week 6, eggs from OUHW-treated hens had higher concentrations of glutamate, glycine, alanine, C18:0, C18:1n9c, C20:4n6, and C22:6n3 (p < 0.05). Serum metabolomics showed that 25 differential metabolites from the OUHW treatment group were predominantly enriched in glycerophospholipid, sphingolipid, branched-chain amino acid, histidine, and tryptophan metabolism. In the cecum, OUHW decreased p-cresol and increased isovaleric acid and acetic acid (p < 0.05). Notably, the overall community structures of the cecal and oviductal microbiota exhibited no significant treatment-related alterations, indicating limited structural changes in the microbial communities in response to the OUHW intervention. OUHW also reduced interleukin-2 and tumor necrosis factor-α, increased interleukin-10 in the jejunum and oviductal isthmus (p < 0.05), and upregulated the mRNA expression of ovarian steroidogenic acute regulatory protein and intestinal Occludin, Claudin-1, and Mucin-2 (p < 0.05). These findings indicate that OUHW improved laying performance, egg quality, and egg nutrient deposition, possibly through modulation of the metabolism, intestinal barrier function, ovarian function, and oviductal inflammation. Full article

Landfill leachate circuits that operate without discharge, by recirculating aerated leachate onto the waste mass, are widespread in South-East Europe, yet their long-term behaviour is rarely documented with sample-level data. This study reports a six-year (2020–2025) seasonal monitoring campaign at a sanitary landfill in northern Serbia (alluvial aquifer of the Sava River, transboundary Danube basin) and re-examines it with a transparent multivariate protocol. Seventy-two leachate samples (collection well, aeration lagoon, sedimentation lagoon; n = 24 each, 30 parameters), 28 realised surface-water campaigns, and six years of groundwater summaries were evaluated by principal component analysis/factor analysis (PCA/FA, Varimax normalized), hierarchical cluster analysis, PERMANOVA, non-parametric paired tests and, for benchmarking, supervised machine learning. The pooled leachate model (n = 72; 21 variables; KMO = 0.700; Bartlett χ² = 956, p < 0.001) retained four factors by parallel analysis, explaining 61.6% of total variance; after rotation the factors accounted for 27.7%, 14.3%, 10.4%, and 9.3%. Factor 1 grouped organic load with particle-reactive metals (COD, BOD₅, Fe, Ni, Cr, As, Zn), Factor 2 a reduced sulfur–fluoride–BTEX signature, Factor 3 temperature-driven nitritation, and Factor 4 a nitrate–manganese redox contrast. Crucially, paired campaign-by-campaign comparison showed no removal of the dominant pollutants along the circuit. Median COD, BOD₅ and NH₄-N were not lower in the sedimentation lagoon than in the collection well, while pH rose from 8.08 to 8.75 (p < 0.001); only Cu, Pb, NO₃-N, and NO₂-N decreased significantly. The circuit therefore homogenises and concentrates dissolved load rather than removing it. Downstream surface water was significantly enriched in electrical conductivity (+110 µS/cm), total dissolved solids, NH₄-N, and NO₂-N relative to upstream (Wilcoxon, p < 0.05), and groundwater showed episodic conductivity up to 12,760 µS/cm and NH₄-N up to 102 mg/L. Cytotoxicity (MTT) confirmed biological relevance, with MRC-5 viability falling to 37% after 24 h exposure to 50 vol.% groundwater (Pw3) versus 60% in A549 cells. A random-forest classifier separated circuit units far better than PCA-based discrimination (76.4% versus 54.2% cross-validated accuracy) and distinguished the 2020–2021 pandemic period from 2022–2025 with 94.2% accuracy, a period effect also confirmed by PERMANOVA (R² = 7.2%, p < 0.001). The results indicate that closed-loop recirculation without an engineered discharge barrier transfers, rather than eliminates, contaminant load, and that after-care of such systems requires mass-balance monitoring and polishing treatment. Full article

Organic amendments can alter soil structure, root development, and carbon cycling, yet their coordinated effects remain unclear. Based on a long-term field microplot experiment established in 2009, four amendment systems with equivalent annual N, P, and K inputs but differing in amendment properties and nominal annual organic-material C inputs were compared: maize straw with NPK (CS), pig manure compost with NPK (PMC), biochar with NPK (BIO), and biochar-based fertilizer (BF). After 15 years, dry-sieved aggregate distribution, CT-resolved air-filled pores (>30 μm), peanut root morphology, and easily oxidizable organic carbon (EOC), microbial biomass carbon (MBC), and dissolved organic carbon (DOC) were determined. PMC had the highest CT-resolved total and connected porosities (19.01% and 10.86%), a greater proportion of small macroaggregates, and the largest root surface area. CS produced a greater proportion and mean size of large dry-sieved aggregates and the highest bulk-soil MBC content. BIO and BF showed lower CT-resolved total porosity but greater isolated porosity, anisotropy, mean pore diameter, and pore fractal dimension (collectively termed CT-resolved macropore heterogeneity); these treatments were also associated with greater root volume or length and increased EOC and DOC contents in small macroaggregate- and microaggregate-sized fractions. Root length correlated more strongly with macropore heterogeneity than with total porosity. Because measurements were obtained once from 12 microplots, these relationships and SEM results represent exploratory associations rather than causal pathways. Overall, traditional amendments were associated with aggregation or macropore connectivity, whereas carbonized amendments were associated with greater macropore heterogeneity. BF had the highest percentage of EOC in TOC (52.45%), indicating a greater relative contribution of labile carbon, not increased stable carbon stock. Full article

Riparian land use and land cover (LULC) exerts scale- and season-dependent controls on surface water quality, yet its influence in regulated agricultural–urban rivers is poorly characterized. We combined seasonal t-tests, one-way ANOVA, and redundancy analysis (RDA) at three riparian buffer scales (500, 1000, and 2000 m) to examine discharge, dissolved oxygen (DO), temperature, turbidity, and pH at four USGS stations along the Kansas River mainstem (2019–2026). DO and temperature showed the strongest seasonal contrasts: DO was 3.1–3.7 mg/L higher in the dry season and temperature 13–15 °C higher in the wet season, a coupling central to aquatic habitat suitability. Turbidity rose significantly in the wet season, consistent with agricultural runoff and sediment mobilization, whereas discharge showed no significant seasonal difference at three of four stations, reflecting upstream reservoir regulation. Spatial ANOVA detected station-level differences only for wet-season DO ($F_{3,28}=4.91$, $p=0.007$), which was lowest at the downstream urbanized station. RDA linked agricultural cover to turbidity and urban cover to reduced wet-season DO, although permutation tests were non-significant ($p\ge 0.42$) at $n=4$ replicates. Seasonality and riparian LULC jointly shape water quality along this regulated river, and the 500 m buffer is the most spatially discriminating scale for land-cover assessment. Full article