Search Results (705)

Ampicillin residues in animal-derived foods may cause allergic reactions and promote antimicrobial resistance in consumers; however, data on residue behavior in poultry remain limited. This study aimed to evaluate the depletion of ampicillin in muscle and skin plus fat of broiler chickens. Thirty birds were treated with ampicillin intramuscularly (20 mg kg⁻¹ every 24 h for three days) and sacrificed at 0.5, 1, 2, 5, and 9 days post-administration. Samples were analyzed by liquid chromatography coupled with tandem mass spectrometry, a method successfully validated according to Commission Implementing Regulation (EU) 2021/808, VICH GL49 and GL2. Quantification was performed by linear regression from matrix-matched calibration curves. Residue depletion was evaluated following the European Medicines Agency guidelines. Ampicillin residues in muscle were detected only during the first 24 h post-administration (6.50–8.48 µg kg⁻¹). Residues in skin plus fat remained detectable until day 5 post-administration (6.87–59.88 µg kg⁻¹). Based on this, the withdrawal period calculated for skin plus fat was 9 days considering EU maximum residue limit (MRL) and 19 days considering method limit of quantification, with 95% confidence. These results provide critical data on ampicillin residue kinetics under controlled experimental conditions, supporting risk assessments and the establishment of MRLs in broiler chickens by the Codex Alimentarius. Full article

This study aimed to determine the optimal biochar application rate for sustaining cotton productivity in moderately saline soils under dry sowing with wet emergence (DSWE) conditions in Shaya County, Xinjiang. A two-year field experiment, arranged in a randomized complete block design with two replicates, evaluated six biochar application rates (S1–S6) against a non-amended control (CK). The biochar, derived from fruit-wood via limited-oxygen pyrolysis at 500 °C (pH 9.82, porosity 64.5%), was applied as a single pre-sowing amendment. Soil water–salt dynamics, crop emergence, and growth parameters were continuously monitored. The results indicated that biochar application consistently reduced soil salinity; specifically, seedling-stage salinity decreased by 30.1–42.2% in the first year compared with the CK. Cotton emergence and yield improved significantly across both seasons. However, the optimal application rate for maximizing yield varied between years. While a high rate (S5: 25 t·hm⁻²) produced the highest first-year yield (6243.8 kg·hm⁻²), a moderate rate (S3: 15 t·hm⁻²) demonstrated greater yield stability and achieved the maximum yield (5975.2 kg·hm⁻²) in the second year. This interannual shift is likely attributable to biochar aging and structural pore saturation in the high-dose plots. Combined with high regional evaporation, these factors exacerbated secondary salinization and reduced the residual benefits of the amendment over time. In contrast, the moderate dose maintained a more effective balance between continuous water–salt regulation and nutrient availability. Under the experimental conditions, a single pre-sowing application of 15 t·hm⁻² biochar, combined with a 375 m³·hm⁻² drip irrigation volume, is recommended as an effective strategy to ameliorate salinity and support long-term yield stability. Full article

In precision gear manufacturing, longitudinal crowning on tooth flanks is commonly produced by applying diagonal feed in worm-type generating processes using tools such as variable-tooth-thickness hobs and dressable grinding worms. However, precise twist control remains difficult because the geometric parameters of the generating tool are strongly coupled with the machine feed settings in the underlying generating kinematics. In addition, direct numerical optimization becomes unreliable near the standard tool state, where the sensitivity of the diagonal-feed coefficient degenerates and conventional linearized solvers may lose effectiveness. To address these issues, this study proposes a multi-variable optimization framework for twist-constrained worm-type gear generation. An iterative singular value decomposition (SVD) scheme is developed to construct and update the sensitivity matrix, while a warm-start continuation strategy is introduced to overcome the local singularity and improve numerical robustness. Two closed-form expressions for the diagonal-feed coefficient are also proposed as practically useful initial estimates, corresponding respectively to the minimum SVD topographic residual and the minimum tooth-flank twist. Numerical validation over a 60-case parameter sweep shows maximum relative errors below 1.6% within the tested range. The proposed framework coordinates the tool-geometry design and diagonal-feed selection to generate tooth flanks with prescribed crowning characteristics while satisfying a specified twist requirement and limiting the required diagonal shift. Numerical examples show that the iterative framework reduces the root-mean-square (RMS) topographic error from 1.14 μm to 0.027 μm relative to the analytical setting of Hsu and Fong. These results indicate that the proposed method provides a reliable computational basis for twist control and process-parameter design in advanced CNC gear generation. From a manufacturing standpoint, because the three design criteria are accessed by adjusting only the diagonal-feed ratio on the machine, a single generating-tool design can serve a range of crowning and twist requirements without retooling, reducing setup and tooling efforts in production. Full article

Shortwave infrared (SWIR) imagery plays an important role in land–water boundary delineation, coastal monitoring, and complex aquatic environment observation. However, the spatial resolution of SWIR bands is usually lower than that of visible bands, which limits their capability to represent fine-scale targets and boundary structures. To address this problem, this study proposes MLE-ResUNet, a SWIR image super-resolution method that integrates along-track oversampling with visible-light-guided deep learning. The proposed method first exploits dual-view SWIR observations with sub-pixel displacement generated by increasing the sampling line rate in the push-broom imaging process. A maximum likelihood estimation (MLE)-based physical prior module is then introduced to transform multi-view degraded observations into a physically consistent latent high-resolution prior. Finally, high-resolution visible images are used to provide edge, texture, and structural guidance, and a ResUNet-based network is employed for multi-source feature fusion and residual reconstruction. Based on multi-region measured data acquired by the LHRSI (Lightweight High-Resolution Spectral Imager) payload onboard the BlueCarbon-1A satellite, a SWIR super-resolution dataset covering typical urban, farmland, and coastal scenarios was constructed. Comparative experiments were conducted against PCA, BDSD, PanNet, GPPNN, and two additional lightweight-guided deep learning baselines, namely LGPConv and a CANConv-style visible-guided baseline. The results show that MLE-ResUNet achieves the best performance across different scenarios and consistently outperforms the comparison methods in terms of SSIM, SAM, ERGAS, and Q-index. The proposed method effectively enhances spatial detail recovery while maintaining favorable spectral consistency. Ablation experiments further demonstrate that both along-track oversampling information and the MLE-based physical prior contribute to improved reconstruction quality and more stable training convergence. These findings indicate that the proposed method can enhance fine-scale SWIR observation capability without substantially increasing hardware complexity, providing an effective technical solution for shoreline identification, land–water boundary extraction, and complex surface target monitoring. Full article

Pesticides play a crucial role in modern agriculture by protecting crops from pests, diseases, and weeds, thereby contributing to increased agricultural productivity and food security. However, their extensive use may lead to the presence of residues in food products, particularly vegetables, which can pose potential risks to human health. Therefore, continuous monitoring of pesticide residues in vegetables is essential to ensure food safety, assess dietary exposure, and protect consumers from possible acute and chronic health effects associated with pesticide intake. In this study, the concentrations of pesticide residues were determined in 1236 samples of 44 vegetable species collected over a four-year period. Vegetables originated from 39 countries, including Serbia (n = 213). Pesticide residues were determined by liquid chromatography–tandem mass spectrometry (LC-MS/MS) and gas chromatography–tandem mass spectrometry (GC-MS/MS) after extraction using a modified QuEChERS protocol. A total of 148 pesticide residues were detected. Of the vegetable samples, 40.13% had pesticide residues at or above 0.01 mg/kg, and 1.78% exceeded the maximum residue limits (MRLs) set by the Serbian regulation. MRL values were most often exceeded in ginger, cucumber, and spinach. The most frequently found pesticide was imidacloprid (detected in 74 samples, 5.99%). Multiple pesticides were detected in 22.01% of the vegetable samples, and one tomato sample contained up to 10 pesticide residues. Based on the available data and further development of a representative dataset, together with appropriate statistical analyses, dietary exposure assessments for pesticides can be conducted. Full article

Groundwater resources are essential to global freshwater supply, and accurate groundwater level prediction is critical for sustainable water resource management. To overcome the limitations of traditional deep learning models in long-sequence groundwater forecasting, including weak generalization, reduced long-term prediction accuracy, and limited interpretability, this study proposes a dual-path Informer-p model integrated with residual theory. The main path captures nonlinear temporal dependencies and long-term hydrological patterns, while the residual path provides a stable linear prediction baseline to enhance local fluctuation representation and robustness to extreme events. The model was validated using long-term groundwater observations from 34 monitoring stations across five major ecosystems in China. Results from representative stations, including Ailao Mountain, showed that Informer-p achieved excellent predictive performance with RMSE = 0.05 m, MAPE = 1.2%, R² = 0.95, and KGE = 0.95, reducing RMSE and MAPE by 37.5% and 52%, respectively, compared with the original Informer. Across all stations, Informer-p outperformed the original Informer at 22 stations, with the greatest improvement observed in forest ecosystems. SHAP analysis identified window maximum, original groundwater level, and window minimum as the dominant predictive features. The proposed model provides an effective tool for national-scale groundwater level prediction and sustainable groundwater management. Full article

The widespread use of antibacterial agents in livestock production is associated with antibiotic residues in animal products and feed, posing a potential threat to food safety and contributing to antimicrobial resistance. The aim of this study was to assess contamination levels of beef, pork, and feed with antibiotic residues in the Kostanay region. The results demonstrated the presence of antibiotic residues in beef, pork, and feed, while all detected concentrations remained below established maximum residue limits. Despite compliance with regulatory standards, residues were detected frequently, and their levels differed significantly depending on feed type (p < 0.001). Microbiological analysis confirmed the presence of Escherichia coli and Staphylococcus aureus in meat samples, with isolates exhibiting moderate to high antimicrobial resistance, particularly in pork. The highest resistance was observed to tetracycline, streptomycin, and thiamphenicol. The obtained data indicate that even trace antibiotic concentrations entering the “feed–animal–product” chain may be associated with selective pressure on microbiota and the circulation of resistant microorganisms. The results highlight the need for comprehensive monitoring of feed and animal products to assess and mitigate antimicrobial resistance spread within the food chain. Full article

Ethylene oxide (EtO) has been banned in the European Union since 1991 as a fumigant for food commodities. Nevertheless, recurrent contamination incidents, especially since 2020, involving imports from India, have raised significant food safety concerns. Despite regulatory measures, EtO and its metabolite, 2-chloroethanol (2-CE), continue to be detected in a variety of food products, including dried foods, dietary supplements, and food additives. This study presents a QuEChERS-based method involving the conversion of EtO into 2-CE, which is subsequently quantified by isotope dilution gas chromatography–tandem mass spectrometry (GC-MS/MS). In contrast to previously published methods, this protocol utilises an Agilent HP-5ms Ultra Inert column (30 m × 250 μm × 0.25 mm), routinely employed in our laboratory for multi-residue pesticide analysis. The proposed approach is therefore readily adaptable to laboratories already performing multi-residue analyses, as it does not require modifications to existing instrumental configurations. The method was validated in accordance with SANTE/11312/2021 guidelines. A total of 84 samples, primarily imported from India, as well as from Brazil, Argentina, and the United Kingdom, were analysed. 2-CE was detected in four samples, and in two cases, the sum of EtO and 2-CE, expressed as EtO, exceeded the European Union (EU) maximum residue limit (MRL). Full article

Composite materials, known for their enhanced mechanical strength through fiber reinforcement, are increasingly used in industrial applications. However, like metals, they suffer strength degradation from cyclic loading, making fatigue failure a critical concern. The fatigue behavior of polymer composites is strongly influenced by factors such as stress amplitude, stress ratio, and loading frequency. Conventional stress-life approaches often treat these factors independently, which limits their predictive accuracy. This study introduces a novel frequency–stress–ratio fatigue index, integrated into a residual-strength degradation approach, to predict fatigue life under constant amplitude, tension-tension loading conditions. To the best of the authors’ knowledge, the majority of models available in the literature require substantial experimental data to calibrate the parameters essential for their application in real-world scenarios. The proposed model requires only two material parameters and assumes failure occurs when the residual strength degrades to the level of the applied maximum stress. The results demonstrate that the proposed formulation provides a unified representation of fatigue behavior influenced by both cycle-dominated and time-dependent mechanisms, offering robust predictive capabilities. This approach not only addresses a critical need for reliable and practical fatigue prediction methods in composite materials but also contributes significantly to the optimization of engineering design processes. Full article

This study presents an integrated approach for the processing of technogenic tailings from the Balkhash concentrator, combining hydrocyclone classification, microfluidic separation, bioleaching, and geopolymer synthesis. The tailings are characterized by a fine-dispersed silicate matrix and low concentrations of valuable metals, which limit the efficiency of conventional processing methods. Hydrocyclone classification enables effective size separation and stabilization of particle size distribution, providing suitable feed for downstream processes. Microfluidic separation demonstrated selective concentrations of copper, increasing its content in the central fraction up to 0.52–0.58% with recovery up to 70–75% under optimal flow conditions. Bioleaching experiments using acidophilic microorganisms (Acidithiobacillus ferrooxidans and A. thiooxidans) revealed strong dependence on process parameters, achieving maximum recoveries of Cu (63%), Zn (58%), and Fe (43%) at pH 1.8–1.9 and 31–32 °C. The solid residues after bioleaching, composed mainly of aluminosilicates, were successfully utilized for geopolymer synthesis. The obtained geopolymer samples exhibited low water absorption (not exceeding 9.1%) and high compressive strength, meeting the requirements of Kazakhstan standard 26633-2015 (ISO 22965-1). The production of geopolymer materials from these residues contributes to the environmental rehabilitation of tailings storage facilities. The novelty of this work lies in the integration of microfluidic separation with bioleaching for fine tailing processing, enabling both selective metal recovery and subsequent conversion of residues into functional geopolymer materials. The proposed approach provides a sustainable pathway for simultaneous resource recovery and waste valorization, contributing to circular economy strategies in the metallurgical industry. Full article

Starch-degrading enzymes are key biocatalysts in industrial applications, particularly when derived from thermophilic microorganisms with potential to operate under elevated temperatures. In this study, three recombinant starch-degrading enzymes were heterologously produced, purified, and biochemically characterized: an α-amylase from Geobacillus kaustophilus, and an α-glucosidase and a type I pullulanase from Geobacillus sp. G4, a thermophilic strain isolated from a geothermal field in southern Peru. The three enzymes were successfully expressed in soluble form in Escherichia coli and purified by one-step affinity chromatography. Biochemical characterization showed that α-glucosidase and α-amylase displayed optimum activity at pH 6–7, whereas pullulanase exhibited a broader pH profile, retaining high activity up to pH 9. All three enzymes reached maximum activity at 60 °C, although their thermal stability profiles differed markedly, with pullulanase showing the highest thermostability. Metal ion assays revealed enzyme-dependent effects, with pullulanase being stimulated by Ca²⁺ and Mg²⁺, while α-amylase and α-glucosidase showed limited responses to divalent ions. Kinetic analysis using soluble potato starch indicated that α-amylase had the most favorable catalytic profile, with the lowest K_m and the highest catalytic efficiency among the three enzymes. Functional hydrolysis assays demonstrated that all enzymes were active on soluble starch and pretreated potato peel, while the enzymatic mixture consistently released the highest concentration of reducing sugars. These results expand the biochemical knowledge of thermophilic amylolytic enzymes from Geobacillus and support their potential use in future enzymatic systems for the conversion of starch-rich residues. Full article

To overcome the limited high-temperature capability of silica-based fiber Bragg gratings (FBGs) and the accuracy degradation of gold-coated FBGs induced by residual stress, a temperature sensor based on a gold-coated FBG with high-temperature alloy packaging is proposed and fabricated. By introducing a high-temperature annealing pretreatment to the gold-coated fiber, residual stress is effectively relieved, enabling high-precision temperature measurement in high-temperature environments. Within the range of 20–800 °C, the annealed sensor achieves an accuracy of 0.72% F.S., a sensitivity of 9.65 pm/°C, and a linearity of 0.9997, in close agreement with theoretical predictions. After ambient vibration and high-temperature thermo-vibration tests, the maximum center wavelength shifts are 13 pm and 46 pm, corresponding to temperature variations of approximately 1.35 °C@24 °C and 4.77 °C@800 °C. These results demonstrate stable sensor performance under high-temperature testing conditions. In addition, a fitting formula applicable to different center wavelengths is proposed, significantly reducing calibration effort. The sensor features a simple structure, easy installation, and reliable performance, providing an effective solution for temperature sensing in extreme environments. Full article

Vegetables constitute an essential component of the daily diet in Albania; however, they also represent a major pathway of human exposure to pesticide residues. This study investigates the presence of pesticide residues in widely used vegetables, including leafy, fruity, root, and bulb types, and evaluates the potential dietary health risks associated with their consumption. Vegetable samples were analyzed using gas chromatography–tandem mass spectrometry (GC-MS/MS) and liquid chromatography–tandem mass spectrometry (LC-MS/MS), for the presence of 417 pesticide analytes, ensuring high analytical sensitivity and reliability. Pesticide residues were present, with 42 distinct compounds, including metabolites, found in all the analyzed samples. Notably, some of the detected substances are not currently authorized for use as plant protection products, suggesting either environmental persistence or regulatory non-compliance. Exceedances of European Union maximum residue limits (MRLs) were most frequently detected in leafy vegetables (42.31%), followed by fruity vegetables (18.75%), whereas no MRL exceedances were observed in root and bulb vegetables. According to the dietary exposure assessment conducted using European Food Safety Authority Pesticide Residue Intake Model (EFSA PRIMo model v.3.1), chronic dietary exposure to pesticide residues was below the acceptable daily intake (ADI). According to this assessment, the acute exposure exceeded the acute reference dose (ARfD) for several pesticide–vegetable combinations, particularly among children. This highlights the need for ongoing monitoring and better agricultural management techniques to reduce potential health risks related to pesticide residues in vegetables. The study results indicate the need to strengthen national monitoring programs, enforce pesticide regulations more strictly, and promote the wider adoption of integrated pest management strategies to reduce dietary pesticide exposure and protect public health in Albania. Full article

Localized mechanical loading induces complex elastic–plastic interactions in anisotropic crystalline materials. However, quantitative orientation-resolved characterization of residual relative elastic strain heterogeneity remains limited. In this study, high-resolution electron backscatter diffraction was used to map residual in-plane relative elastic strain distributions beneath micro-indents in two annealed body-centered cubic ferritic non-oriented electrical steels, B35AV1900 and 35WW300. Grains oriented near (001), (101), and (111) were analyzed to evaluate the crystallographic effects on residual strain accommodation. Frequency distributions of the in-plane residual relative elastic strain components were constructed, and full width at half maximum values were extracted to quantify strain heterogeneity. The results revealed a pronounced orientation dependence. Near-(001) grains exhibited greater indentation depths and more widely distributed post-indentation deformation features. By contrast, near-(111) grains showed broader residual in-plane relative elastic strain distributions in both alloys. These results indicate that residual strain heterogeneity after unloading is influenced not only by indentation depth but also by crystallographic constraint and orientation-dependent strain redistribution. This study establishes a quantitative orientation-resolved framework for characterizing residual relative elastic strain heterogeneity beneath localized loading. It also provides a basis for linking crystallographic anisotropy, localized deformation, and residual strain redistribution in ferritic electrical steels. Full article

An issue of common concern in lemon production is finding a safe and efficient alternative to 2,4-dichlorophenoxyacetic acid (2,4-D). In this study, ‘Eureka’ lemon fruits were treated with three concentrations (1, 2 and 3) of fluroxypyr-meptyl (FME), a combination of fluroxypyr-meptyl and fluroxypyr (FLFM), 2,4-dichlorophenoxypropionic acid (2,4-DP), and 2-methyl-4-chlorophenoxyacetic acid (MCPA). Water and 2,4-D served as controls. We measured the storage performance indicators of fruit, such as weight loss rate and decay rate, and shelf-life quality parameters, such as juice yield, flavor compounds and pesticide residues. During storage, weight loss was significantly higher in water than under all other treatments. Weight loss rates under FME2 and 2,4-DP3 were significantly lower than under 2,4-D. Decay rates in FLFM1, 2,4-DP2, and the FME series were significantly lower than in 2,4-D and water, whereas those in 2,4-DP1 and the MCPA series were significantly higher than in 2,4-D at 200 days after treatment. Regarding shelf-life performance, juice yield in water (65.14%) and 2,4-D (68.26%) was significantly lower than under most other treatments. The highest juice yield was observed in FME2 (77.84%). Treatments 2,4-DP1, 2,4-DP2, and FME2 were superior to 2,4-D and water in maintaining total soluble solids, titratable acid, and vitamin C contents, while other treatments showed no negative effects on internal quality. Fruits under MCPA2, 2,4-DP3, 2,4-DP2, and FME2 maintained better flavor compound profiles than those in water. Notably, MCPA2 resulted in significantly higher levels of terpenes (e.g., D-limonene) and aldehydes (e.g., citral); FME2 effectively maintained linalool, geraniol, and α-terpineol; and 2,4-DP3 performed well in maintaining D-limonene, sesquiterpenes, and alcohols compared with other treatments. All treated fruits complied with Chinese National Food Safety Standard Maximum Residue Limits for Pesticides in Food GB 2763-2026 and meet the EU standard limits for citrus. Overall, FME2 treatment resulted in the best storage performance and quality, followed by 2,4-DP3, indicating that these treatments may serve as effective postharvest alternatives for lemon preservation. Full article