Search Results (170,032)

Producing high-quality analytical reports for the environmental domain is typically time-consuming and requires significant human expertise. This paper describes MeteoChat, a semi-automatic framework for efficiently generating specialized environmental reports from heterogeneous environmental data. MeteoChat utilizes a Large Language Model (LLM) fine-tuned and integrated with Retrieval-Augmented Generation (RAG). The system’s core is its plug-and-play philosophy, which separates analytical reasoning from the data source and the report’s intended audience. The fine-tuning phase uses data-agnostic, parameterized question–context–answer triples defined by an environmental expert to teach the LLM domain-specific analytical logic and audience-appropriate communication styles. Subsequently, the RAG phase integrates the model with actual datasets, which are processed via an Extract–Transform–Load (ETL) workflow to generate statistical summaries. This architectural separation ensures that the same reporting engine can operate on different sources, such as meteorological time series, satellite imagery, or geographical data, without additional training. Users interact with the system via a web-based conversational interface, where responses are tailored for either technical experts (using explicit calculations and tables) or the general public (using simplified, narrative language). MeteoChat has been tested with real data extracted from the micrometeorological network of ARPA Lazio. Full article

Life Cycle Assessment (LCA) is widely used to evaluate the environmental impact of power generation systems and inform energy and climate policy decisions. In recent years, numerous LCA studies have examined the life-cycle implications of power plants utilizing renewable, nuclear, and fossil fuel technologies. Nevertheless, the resultant data is fragmented, exhibiting significant diversity among investigations attributable to disparities in system boundaries, technical assumptions, and methodological selections. This document offers a systematic overview of peer-reviewed LCA studies and Environmental Product Declarations (EPDs) evaluating the environmental implications of predominant power production technologies, such as solar photovoltaic, wind, hydropower, nuclear, and natural gas power plants. Various environmental effect categories are evaluated, with a specific focus on Global Warming Potential as the most frequently reported and policy-relevant metric. The review consolidates documented impact ranges, assesses the effects of plant size and technological design, and evaluates the contribution of several life cycle stages to overall environmental performance. The findings emphasize prevalent tendencies and significant variability among technologies and studies, illustrating the susceptibility of LCA results to modeling assumptions and data sources. Although current LCAs offer relevant insights into the environmental impact of electricity generation, the review highlights enduring methodological deficiencies, particularly the inadequate handling of uncertainty, the static portrayal of long-lasting infrastructures, and the lack of explicit attention to technological risk. This study consolidates and critically evaluates existing literature, providing a thorough reference on the life-cycle environmental consequences of power plants and facilitating a more educated interpretation of LCA results within energy system planning and policy analysis. Full article

Aquaculture output, sustainability, and profitability can be enhanced by using functional feed additives. The effect of supplementation with two different dietary levels of propylene glycol (PG) and essential oils (EOs) was evaluated in Nile tilapia. A total of 150 juvenile fish were randomly allocated into five groups. Growth performance, feed utilization, serum biochemistry, hematology, and gene expression were assessed. PG supplementation significantly improved growth performance, feed conversion, protein efficiency, and energy utilization. Both additives significantly reduced cortisol and glucose levels and altered liver enzymes and lipid profiles. PG improved immunological indices, while hematological responses were dose-dependent; both EOs and PG increased hematocrit, mean corpuscular volume (MCV), and mean corpuscular hemoglobin (MCH). Moreover, the high PG dose significantly increased platelet counts, reduced hemoglobin (Hb), and elevated hematocrit. Additionally, EOs significantly upregulated antifreeze protein IV (AFPIV) and fat metabolism-related genes in a dose-dependent manner, indicating a potential role in lipid mobilization and stress tolerance. Expression analysis of the immunoglobulin H (IGMH) gene revealed a significant increase in PG-supplemented groups, suggesting its immunostimulatory potential. Overall, PG enhanced immunity and growth performance, while EOs promoted AFPIV and fat metabolism gene expression. Therefore, PG and EO supplementation could serve as an effective functional strategy to enhance O. niloticus growth, stress adaptation, and immune resilience. Full article

Near-infrared (NIR) imaging, including NIR-I (800–1000 nm) and NIR-II (1000–1700 nm), has been primarily evaluated using separate cameras with different detectors, limiting comparison. We investigated whether using a single-camera system capable of both NIR-I and NIR-II acquisition, NIR-II improves spatial resolution and contrast-to-noise ratio (CNR) for nanoparticle-based imaging. Dual-mode, dual-Gd ICG (DMDG-ICG) nanoparticles were characterized for absorption and fluorescence. A custom NIR imaging system using a single InGaAs camera enabled visualizing both NIR-I and -II windows. In vitro, capillary tubes containing nanoparticles in water, in tissue-mimicking Intralipid, or covered with mouse skin were imaged, and full-width-half maximum (FWHM) and CNR were measured. In vivo, the mouse femoral artery was imaged after IV nanoparticle delivery. DMDG-ICG showed strong fluorescence at both NIR-I and NIR-II. Scatter greater at NIR-I than NIR-II increased with depth and tissue layers. FWHM was lower and CNR higher at NIR-II versus NIR-I for up to 10 mm depth (p < 0.05, n = 3) in Intralipid. In vivo, femoral artery CNR was also higher at NIR-II (p < 0.05, n = 3). Using a single-camera system allowing direct comparison, NIR-II imaging provided greater penetration, spatial resolution, and CNR compared to NIR-I. The findings support the utility of NIR-II for vascular and molecular imaging applications. Full article

Contingency epidemic outbreaks, such as the novel coronavirus (COVID-19) pandemic in 2020, have underscored the vital function of public health emergency response systems within national strategic frameworks. Public health surveillance and early warnings are imperative for safeguarding peoples’ lives, maintaining social stability, and promoting economic development. Existing studies are inadequate for accurately evaluating the efficiency of an urban public health surveillance system from a comprehensive perspective. In this work, an integrated framework was proposed for the evaluation of the spatial allocation efficiency of urban public health surveillance. This integrated approach incorporates three key aspects, spatial coverage, overlap, and accessibility, enabling a measurable evaluation of the overall spatial allocation efficiency. We utilized the proposed method to investigate the placement efficiency of the nucleic acid testing sites during the epidemic in Nanchang, China. The findings showed that using the integrated evaluation method based on coverage, overlap, and accessibility provides a more accurate reflection of the efficiency of existing site placements. It offers a flexible measurement system for evaluating urban surveillance site allocation strategies. This study introduces a novel perspective for the efficiency assessment of public health surveillance site placements, contributes to the development of public health emergency response systems, and provides a technical foundation for future contingency planning in public health surveillance. Full article

The swimming tilt angle of fish is one of the key factors influencing the estimation of target strength (TS). Therefore, understanding how TS varies with changes in swimming tilt angle is essential. This study employed the Kirchhoff-ray-mode (KRM) model to estimate TS and examine variations in the swimming tilt angle of sardines under flowing water conditions. Swimming tilt angles were measured at flow velocities of 30 and 50 cm/s. The KRM model was utilized to estimate TS for 17 sardine samples (total length: 13.0–24.6 cm) across four frequency bands (38, 70, 120, and 200 kHz). At a flow velocity of 30 cm/s, sardines swimming against the flow exhibited a mean swimming tilt angle of 4.0° ± 14.0°, with normalized mean TS_cm values of −64.7 dB at 38 kHz, −65.7 dB at 70 kHz, −66.4 dB at 120 kHz, and −66.9 dB at 200 kHz. At a flow velocity of 50 cm/s, sardines swimming against the flow showed a mean swimming tilt angle of −2.2° ± 10.1°, with normalized mean TS_cm values of −62.9 dB at 38 kHz, −63.7 dB at 70 kHz, −64.3 dB at 120 kHz, and −64.8 dB at 200 kHz. Considering the results of this study and the swimming behavior of sardines against the flow, the target strength of sardines swimming with the flow may be of less concern. Therefore, when conducting acoustic surveys, it is more efficient to account for flow velocity conditions rather than swimming direction. Full article

Energy obtained by green ways with releasing environmental pollution is still a challenge for sustainable development for model society. Among energy technologies, photothermal conversion by using solar energy has become a new field and a hot topic in recent years. Based on the exploration of nanomaterials in the past decades, photothermal nanomaterials by using nanomaterials bring new chances for expending the utilization of green energy with high efficiency, mainly including metal semiconductors and carbon nanomaterials. Their modulated structure for enhancing light absorption, accelerating transformation of photon into heat, and located heat management were also considered important for promoting the utilization of solar energy and therefore, the strategies for designed and controllable preparing of photothermal nanomaterials were also summarized. The applications of photothermal nanomaterials were also reviewed to reveal the new chances for energy conversion engineering or promoting the solar energy utilization of solar energy in some cold regions or somewhere with low solar irradiation. Full article

The non-uniform production contribution caused by insufficient reservoir stimulation during initial fracturing significantly constrains the lifecycle and estimated ultimate recovery (EUR) of horizontal wells. Refracturing is therefore urgently required to reconstruct fracture networks and activate undeveloped reserves. In this study, a coupled geomechanics-matrix-fracture-seepage model is developed based on the Unconventional Fracturing Model (UFM) to characterize formation energy evolution and residual oil distribution. Simulation results indicate that initial fracturing creates a limited pressure diffusion radius (5–30 m), resulting in a “strong near-well, weak far-field” pressure distribution and inefficient residual oil utilization. To address this, a synergistic strategy is proposed, integrating “re-pressurization of existing fractures” for energy replenishment with “infill fracturing” for activating bypassed reserves. This strategy significantly outperforms conventional refracturing, increasing the predicted cumulative oil production by 55.86%. Parameter optimization indicates that maintaining a pumping rate of 10–12 m³/min and a fluid intensity of 1700–1900 m³/stage, while optimizing proppant ratios for conductivity, maximizes recovery. This work provides theoretical guidance for sweet spot evaluation and refracturing design in ultra-low permeability reservoirs. Full article

Sugar beet (Beta vulgaris L.) is an economically important crop that accounts for approximately 20% of global sugar production. The success of future breeding programs depends on the effective utilization of existing genetic resources. The aim of this study was to assess the genetic diversity and population structure of 192 sugar beet (Beta vulgaris L.) genotypes, including commercial cultivars and accessions obtained from the USDA gene bank, using SCoT and ISSR molecular markers, and to identify potential genetic resources for sugar beet breeding programs. In this study, a total of 192 sugar beet genotypes, including 187 accessions from the USDA (U.S. Department of Agriculture) gene bank and 5 commercial cultivars, were evaluated for genetic diversity using Start Codon Targeted (SCoT) and Inter Simple Sequence Repeat (ISSR) markers. A total of 68 scorable bands were obtained from five SCoT and three ISSR primers, and all bands were found to be polymorphic (100% polymorphism). Parameters such as polymorphic information content (PIC), Nei’s genetic diversity, and Shannon’s index indicated a high level of variation within the gene pool, with SCoT markers being more informative than ISSR markers. Dendrogram analyses based on Nei’s genetic distance revealed that the populations were separated into two main groups, while the sub-clusterings contained broad genetic variation. STRUCTURE analysis identified four (K = 4) populations for the SCoT data and three (K = 3) populations for the ISSR data; the inclusion of a high number of individuals in the admixture population indicated extensive gene flow. Principal component analysis (PCA) revealed both homogeneous groups and differentiated genotypes contributing to within-population diversity. The results demonstrate that the combined use of SCoT and ISSR markers provides powerful and complementary tools for assessing genetic diversity in sugar beet. The findings provide a solid scientific basis for the development of new, high-yielding and high-quality sugar beet cultivars as well as for the conservation of existing genetic resources. Molecular data constitute an important reference for guiding sugar beet breeding programs and for the effective utilization of genetic resources. Full article

Conventional production methods of aragonite production utilize chemical inducers to promote the evolution of the calcite crystalline phase to the aragonite phase of calcium carbonate. The chemical inducers used require a considerable amount of magnesium chloride (MgCl₂) to induce crystallization, which is a major operational cost. Application of such materials in large amounts can be a deterrent to achieving a sustainable and economically feasible end-product derived from carbon dioxide (CO₂) molecules. A number of previous research works focused mainly on optimizing the usage of MgCl₂ or introducing alternative chemical inducers for aragonite production. In this work, we are proposing the usage of natural seawater as it is a naturally available and abundant resource to induce the synthesis and continuous production of aragonite compounds. Due to inconsistent quality and salinity of the natural seawater sampled, harvested, and dried, Red Sea Salt is utilized, blended at 33 g/L throughout the laboratory experiments for better statistical control, and is referred to as blended or artificial seawater. A methodology of utilizing seawater, which has a considerable concentration of MgCl₂ compound, can be utilized as a sustainable, natural, and economically feasible natural inducer to synthesize aragonite has been developed by utilizing artificial seawater for laboratory proof of concept. The main effects identified for the optimization of aragonite synthesis are lime (CaO) feedstock concentration in seawater, reaction temperature, and reaction duration. The experiment results indicated that only by increasing temperature and reaction duration, or both, can the aragonite yield be increased. It is suggested that the range of operation to obtain > 80% aragonite purity has been identified with the reaction temperature at 90 °C, reaction duration of 10 min, and CaO concentration in seawater at 1 g/L. The quality of the aragonite synthesized via seawater is characterized using XRD, ICP, FESEM, and TGA, and compared with aragonite particles synthesized using MgCl₂ inducers. In comparison, seawater aragonite has lower residual alkalinity compared to both calcite and aragonite via MgCl₂ and has a mixture of predominantly needle-shaped crystalline structure and remnants of cubic-shaped particles, presumably calcite, suitable for application in food, beverages, and pharmaceuticals (calcium antacids, nutritional supplements, chewable, lozenges). Full article

Thousand-seed weight (TSW) is a critical determinant of yield in rapeseed (Brassica napus L.). Developing germplasm with high TSW is therefore a key strategy in high-yield rapeseed breeding. However, the genetic and molecular mechanisms underlying TSW in rapeseed remain poorly understood. In our earlier work, we identified a mutant, designated GRG177, which exhibits a remarkably high TSW exceeding 7 g. To unravel the mechanisms driving this elevated TSW, we conducted a comprehensive analysis of GRG177, integrating morphological, genetic, developmental, anatomical, and physiological approaches. Compared with the control germplasm GRD328 (TSW ≈ 3.5 g), GRG177 displayed a significant increase in seed weight and seed volume, larger silique surface area, and higher yield per plant. However, it also showed a notable reduction in both silique number per plant and seed number per silique. Genetic analysis of a segregating population revealed that the high-TSW trait in GRG177 is governed by two pairs of dominant epistatic major genes plus polygenes. Endogenous hormone analysis revealed significantly higher zeatin riboside (ZR) content in the early stage of seed development in GRG177, whereas indole-3-acetic acid (IAA) and abscisic acid (ABA) levels were significantly up-regulated in the late stage of seed development. Anatomical observation using paraffin sections further confirmed that enhanced cell division activity in the early stage and improved cell expansion capacity in the later stage underpin the formation of high TSW. Furthermore, BSA-seq was utilized to map four TSW-related Quantitative Trait Loci (QTLs) and screen 13 candidate genes involved in IAA, ZR, and ABA signaling pathways. In conclusion, these findings provide novel insights into the regulatory mechanisms governing high-TSW formation in rapeseed and present valuable genetic resources for high-yield breeding. Full article

Background/Objectives: Identification of tools to minimize opioid-related harms is critical in the U.S. The purpose of this study was to better understand community responder and healthcare provider perceptions and preferences regarding the design and function of a potential new opioid sensor device (OSD). Methods: Adults aged ≥ 18 years employed as community responders or healthcare providers in Alabama were recruited via email to participate in an anonymous online cross-sectional survey informed by the Unified Theory of Acceptance and Use of Technology (UTAUT). Primary outcomes were assessed via multiple-choice and 7-point Likert-type scales (1 = strongly disagree, 7 = strongly agree) and included the following topics: (1) past OSD utilization (4 items); (2) perceived importance of OSD design elements (15 items); (3) OSD function and cost preferences (3 items); and (4) UTAUT measures including perceived usefulness of OSDs (3 items), ease of use (4 items), social factors (4 items), resources (4 items), concerns (3 items), and intentions (3 items). Differences in UTAUT measures across professions were assessed via Mann–Whitney U tests, and predictors of OSD utilization intention were analyzed via multiple linear regression. Results: Respondents (N = 145) included pharmacists (40.0%), nurses (23.4%), physicians (14.5%), behavioral health (4.8%), social work (4.8%), and law enforcement (0.7%). Availability in hospital emergency departments was rated as the most important device element (mean [SD] score: 6.66 [0.80]), followed by sensitivity and specificity of the test (6.42 [0.98]), rapid detection time (6.42 [0.88]), ability to detect opioids in a broad range of substance (6.42 [0.93]), and availability in law enforcement offices (6.33 [1.08]). A 2–5 min detection time was rated as reasonable by 32.6% of respondents, with 53.0% preferring to pay <USD 15 per test. There were no statistically significant differences in UTAUT scale scores across professions. Perceived usefulness (β = 0.493; p < 0.001), social acceptance (β = 0.281; p = 0.023), and resource availability (β = 0.708; p = 0.002) were positive predictors and perceived ease of use was a negative predictor (β = −0.472; p = 0.007) of intention to use an OSD. Conclusions: Newly developed OSDs should consider prioritizing accessibility in hospital emergency departments and law enforcement offices, ability to detect a broad range of opioids, detection time between 2 and 5 min, and cost less than USD 15 per test. Future research may explore perspectives from a more diverse sample across multiple states and different professional roles. Full article

Euphorbia helioscopia L. (Zeqi, ZQ) is a traditional Chinese herb used to treat various tumors, but its molecular mechanisms against hepatocellular carcinoma (HCC) remain unclear. This study aims to elucidate the anti-HCC mechanisms of ZQ using chemical profiling, bioinformatics, Mendelian randomization (MR), and experimental validation. A total of 104 compounds were identified from ZQ, with 18 targeting HCC-related proteins. Bioinformatics and MR analyses revealed PTK2 as a core target associated with HCC risk. ZQ significantly suppressed H22 tumor growth in male ICR mice and inhibited PTK2/PI3K/AKT phosphorylation. Molecular docking and dynamics simulations confirmed stable binding between key ZQ compounds and PTK2. These results suggest that ZQ exerts anti-HCC effects through PTK2 inhibition and modulation of the PI3K/AKT pathway, supporting its potential as a multi-targeted therapeutic for HCC. Full article

Introduction: The availability of toxicokinetic data is critical for detecting and monitoring the intake of psychoactive substances. Timely characterization of novel psychoactive substances (NPS) is particularly important to assess their abuse potential and inform public health responses. Methods: Toxicometabolomics offers a powerful approach to characterize xenobiotic metabolism through high-resolution profiling of biochemical transformations. It thus allows the finding of exogenous biomarkers, such as new drug metabolites, and endogenous biomarkers, which could be indications of acute drug ingestions or sample manipulation, as well as offering information on the mode of action of drugs. In this study, we applied a liquid chromatography–high-resolution mass spectrometry workflow to investigate the toxicometabolomics of two N1-sulfonated N,N-dimethyltryptamine derivatives with potential for both therapeutic use and recreational abuse. Results: Zebrafish (Danio rerio), an increasingly valuable model for preclinical pharmacology and toxicology studies, along with pooled human liver S9 fractions were used to elucidate metabolic pathways and identify key phase I and phase II biotransformations. Furthermore, untargeted metabolomics revealed significant downregulation of L-threonine associated with compound exposure. Conclusions: These findings advance the current understanding of tryptamine metabolism and underscore the utility of toxicometabolomics in the analytical evaluation of NPS. Full article

Drought is a slow-onset hazard whose economic impacts can propagate across sectors with multi-year delays. This study develops a non-linear autoregressive model with exogenous drought inputs (ARX) to assess whether U.S. drought severity, measured by the Drought Severity and Coverage Index (DSCI), contains incremental predictive information for monthly stock returns. Using weekly DSCI and stock price data from 2013 to 2023, we constructed monthly compound returns and multi-year drought lags spanning 1–5 years for four sector-representative firms: a water utility (American Water Works, AWK), two food service firms (Chipotle Mexican Grill, CMG; Starbucks, SBUX), and an industrial manufacturer (Tesla, TSLA). We compared regularized linear ARX baselines (Elastic Net, Ridge) with a non-linear Histogram Gradient Boosting Regressor (HGB) ARX model and used permutation importance to diagnose drought-relevant lag horizons. Results showed a clear, delayed drought signal for the water utility, with a dominant ~48-month drought lag, consistent with multi-year transmission through operations, regulation, and investment cycles. In contrast, drought lags added limited or unstable information for the food service firms and negligible information for TSLA, whose dynamics were dominated by non-drought drivers. Overall, the findings indicate that drought–return relationships are sector-specific and can emerge at multi-year lags, and that non-linear ARX models provide a flexible tool for detecting these delayed climate-risk signals. Full article