Search

The separation performance, energy demand, and operating costs of electro-coagulation (EC) are compared to conventional chemical coagulation for oil–water separation using a simulated oil-and gas-produced water matrix. An iron-based chemical coagulant and sacrificial iron electrodes are evaluated. Effluent turbidity, chemical oxygen demand (COD), total organic carbon (TOC), and oil and grease (O&G) removal were determined for various coagulant concentrations and reaction times and current densities. Chemical coagulation produced superior turbidity removal when scaled by the total iron dose. At lower iron doses (

Water resources are fundamental to economic and social development. Improving agricultural water-use efficiency is essential for alleviating water scarcity, ensuring food security, and fostering sustainable growth. This study examines the effects of irrigation levels (severe water deficit, W0: 45–55% θFC; moderate water deficit, W1: 55–65% θFC; mild water deficit, W2: 65–75% θFC; full irrigation, W3: 75–85% θFC) and nitrogen application rates (N0: 0 kg·hm−2, N1: 150 kg·hm−2, N2: 300 kg·hm−2, N3: 450 kg·hm−2) on soil environment, crop yield, and water–nitrogen use efficiencies in Lycium barbarum under integrated water–fertilizer drip irrigation. The coordinated application of water and nitrogen significantly influenced yield and efficiencies (p < 0.05) by modifying rhizosphere conditions such as soil moisture, temperature, salinity, and enzyme activities. Soil temperature increased with nitrogen application (N1 > N2 > N0 > N3), with N1 raising soil temperature by 4.98–8.02% compared to N0, N2, and N3. Electrical conductivity was lowest under N0, showing a 7.53–18.74% reduction compared to N1, N2, and N3. Urease activity peaked under N3 (31.84–96.78% higher than other treatments), while alkaline phosphatase and catalase activities varied across treatments. The yield was highest under N2, at 6.79–41.31% higher than other nitrogen treatments. Water use efficiency (WUE), growth use efficiency (GUE), and nitrogen agronomic efficiency (NAE) peaked under N2, while nitrogen use efficiency (NUE) decreased with higher nitrogen rates. Among irrigation levels, W0 showed the highest soil temperature, while W3 exhibited the lowest conductivity in the 0–40 cm layer. W2 had the highest soil enzyme activities, yielding 4.41–42.86% more than other levels, with maximum efficiencies for WUE, GUE, NUE, and NAE. The combination of mild water deficit (65–75% θFC) and 300 kg·hm−2 nitrogen application (W2N2) resulted in the highest yield (2701.78 kg·hm−2). This study provides key insights for implementing integrated drip irrigation in northwest China's arid regions. [ABSTRACT FROM AUTHOR]

In the process of steel strip production, the accuracy of defect detection remains a challenge due to the diversity of defect types, complex backgrounds, and noise interference. To improve the effectiveness of surface defect detection in steel strips, we propose an enhanced detection model known as YOLOv8-BSPB. First, we propose a novel pooling layer module, SCRD, which replaces max pooling with average pooling. This module introduces the receptive field block (RFB) and deformable convolutional network version 4 (DCNv4) to obtain learnable offsets, allowing convolutional kernels to flexibly move and deform on the input feature map, thus, more effectively extracting multi-scale features. Second, we integrate a polarized self-attention (PSA) mechanism to improve the model's feature representation and enhance its ability to focus on relevant information. Additionally, we incorporate the BAM attention mechanism after the C2f module to strengthen the model's feature selection capabilities. A bidirectional feature pyramid network is introduced at the neck of the model to improve feature transmission efficiency. Finally, the WIoU loss function is employed to accelerate the model's convergence speed and enhance regression accuracy. Experimental results on the NEU-DET dataset demonstrate that the improved model achieves a classification accuracy of 81.3%, an increase of 4.9% over the baseline, with a mean average precision of 86.9%. The model has a parameter count of 5.5 M and operates at 103.1 FPS. To validate the model's effectiveness, we conducted tests on the Kaggle steel strip dataset and our custom dataset, where the average accuracy improved by 2.3% and 5.5%, respectively. The experimental results indicate that the model meets the requirements for real-time, lightweight, and portable deployment. [ABSTRACT FROM AUTHOR]

The operation of reservoir is to optimize the utilization of water resources and bring its maximum benefit. Most studies of reservoir scheduling generally pursue the maximization of revenue, and rarely consider the demand of water supply from reservoirs to agriculture or factories in the scheduling process. The few studies that have taken this into account have included this demand in the objective function or constraint, rather than in terms of marginal benefits. This work presents a method to determine water supply decision of reservoir based on marginal benefit. By iteratively linearizing the cascaded reservoir scheduling model and calculating the optimal solution to the dual problem of the model, this method provides a reference for the water supply plan of reservoir to agricultural departments and factories. The proposed method has been applied to 8 reservoirs on the Jinsha River cascade. Convergence in water head is achieved after 15 iterations, and numerical comparisons of the marginal value of water resources at different locations and periods across various reservoirs are obtained.

The mechanism of a solvent consisting of choline chloride and glycerol (ChCl/GLY) for extracting phenolic compounds from coal tar was theoretically studied using density functional theory calculations and molecular dynamics simulations. The thermodynamic properties, interaction essence, and molecular dynamics properties of the extraction system were investigated, as well as the influence of ChCl/GLY on the vibration spectra of phenolic compounds. The results show that the solvation free energy of phenolic compounds in ChCl/GLY is more negative than that in coal tar, leading to the spontaneous transfer of phenolic compounds from coal tar to ChCl/GLY. The electrostatic and dispersion interactions between phenolic compounds and ChCl/GLY have similar significance in the extraction process, with interaction energies ranging from −46 to −53 kJ mol−1. The mixing of phenolic compounds with ChCl/GLY has minimal impact on their internal molecular structure, however, it does reduce the diffusion coefficients of each component in ChCl/GLY and shortens the lifetime of hydrogen bonds in both phenolic compounds and ChCl/GLY. The first shell of each phenolic compound is surrounded by 1.15 chloride ions. Following dissolving in ChCl/GLY, the stretching vibration peaks of phenolic compounds, namely the –OH and C–H/–CH3 regions, undergo a shift. The results enhance comprehension of the extraction process of phenolic compounds by DES. [ABSTRACT FROM AUTHOR]

The uncertainty of natural inflows and market behavior challenges ensuring a reliable power balance in hydropower-dominated electricity markets. This study proposes a novel framework integrating hourly load balancing on typical days into a monthly scheduling model solved with Gurobi11.0.1 to evaluate demand-met reliability across storage and inflow states. By employing total storage as a system state to reduce dimensional complexity and simulating future runoff scenarios based on current inflows, the method performs multi-year statistical simulations to assess reliability over the following year. Applied to a system of 39 hydropower reservoirs in China, the case studies of present models and procedures suggest: (1) controlling reservoir storage levels during the dry season is crucial for ensuring the power demand-met rate in the following year, with May being the most critical month; (2) the power demand-met rate does not monotonically increase with higher storage levels—there is an optimal storage level that maximizes the demand-met rate; and (3) June and October offer the greatest flexibility in storage adjustment to achieve the highest demand-met reliability. [ABSTRACT FROM AUTHOR]

This paper addresses the issue of detecting welding defects in steel plates during the welding process by proposing a method that combines the laser vibrometer with transient feature extraction technology. The method employs a high-resolution laser vibrometer to collect vibration signals from excited weld plates, followed by feature extraction and analysis for defect detection and identification. The focus of the research is on the optimization and application of the transient extraction transform algorithm, which plays a crucial role in signal feature extraction for defect recognition. By optimizing the short-time Fourier transform, we further propose the use of the transient extraction transform algorithm to effectively characterize and extract transient components from defect signals. To validate the proposed algorithm, we compare the defect recognition performance of several algorithms using quantitative metrics such as Rényi entropy and kurtosis. The results indicate that the proposed method yields a more centralized time–frequency representation and significantly increases the kurtosis of transient components, providing a new approach for detecting welding defects in steel plates. [ABSTRACT FROM AUTHOR]

The increasing scarcity of water and soil resources, combined with inefficient water and fertilizer management, poses significant challenges to agriculture in arid regions. This study aimed to determine an optimal water and nitrogen regulation model to alleviate water shortages and improve agricultural productivity and quality. In this study, a two-year experiment was conducted to investigate the effects of varying irrigation and nitrogen levels on the soil environment and crop growth in a Lycium barbarum||alfalfa system (LB||AS). The experiment involved four moisture gradients and four nitrogen application levels (using urea as the nitrogen source). The results indicated that soil moisture decreased during crop development, followed by a slow increase, with significant variation across soil depths. Soil temperature peaked during the fruiting stage of Lycium barbarum in July, decreasing significantly with soil depth. Higher temperatures were recorded in N0 under the same irrigation level and in W3 under the same nitrogen level. Soil organic carbon (SOC) levels increased by 16.24% in W3N0 and by 18.05% in W2N1, compared to W0N3. Easily oxidizable organic carbon (EOC) and soluble organic carbon (DOC) levels exhibited significant variations depending on irrigation and nitrogen treatments. Irrigation and nitrogen had a stronger individual impact on alfalfa height and stem thickness than their combined effects. Water and nitrogen regulation significantly influenced Lycium barbarum yield, its 100-fruit weight, and economic efficiency (p < 0.05). The W0N2 treatment produced the highest yield (3238 kg·ha−1), exceeding other treatments by up to 29.52%. In conclusion, the optimal water–nitrogen regulation model for the LB||AS system is full irrigation (75–85% θfc) with a nitrogen application rate of 300 kg·ha−1. These findings offer critical insights for improving water and nitrogen management strategies in arid regions. [ABSTRACT FROM AUTHOR]

Simple Summary: This study is the first to investigate the effects of E. mitis on the ileal microbiota and fecal metabolites of chickens. Non-targeted metabolic technology and 16S rRNA sequencing technology were used to study changes in the ileal microbiota and fecal metabolites after repeated infections with E. mitis. The results indicated that chickens developed solid immunity against a high dose of E. mitis infection after repeated infections with low-dose E. mitis and that repeated low-dose infections of E. mitis disrupted the ileal microbiota balance. Coccidiosis, caused by different species of Eimeria parasites, is an economically important disease in poultry and livestock worldwide. This study aimed to investigate the changes in the ileal microbiota and fecal metabolites in chickens after repeated infections with low-dose E. mitis. The chickens developed solid immunity against a high dose of E. mitis infection after repeated infections with low-dose E. mitis. The composition of the ileal microbiota and the metabonomics of the Eimeria-immunized group and the control group were detected using 16S rRNA sequencing and liquid chromatography–mass spectrometry (LC-MS). The relative abundance of Neisseria, Erysipelotrichaceae, Incertae sedis, Coprobacter, Capnocytophaga, Bifidobacterium, and the Ruminococcus torques group declined in the Eimeria-immunized chickens, whereas Alloprevotella, Staphylococcus, Haemophilus, and Streptococcus increased. Furthermore, 286 differential metabolites (including N-undecylbenzenesulfonic acid, 1,25-dihydroxyvitamin D3, gluconic acid, isoleucylproline, proline, and 1-kestose) and 19 significantly altered metabolic pathways (including galactose metabolism, ABC transporters, starch and sucrose metabolism, the ErbB signaling pathway, and the MAPK signaling pathway) were identified between the Eimeria-immunized group and the control group. These discoveries will help us learn more about the composition and dynamics of the gut microbiota as well as the metabolic changes in chickens infected with Eimeria spp. [ABSTRACT FROM AUTHOR]

Simple Summary: Necrotic enteritis, a severe intestinal disease in chickens caused by bacteria and parasites, poses a major challenge in poultry farming. Traditionally, antibiotics have been used to control this disease, but due to rising antibiotic resistance and regulatory restrictions, alternative treatments are needed. This study explored the use of four plant extracts—Astragalus, pomegranate peel, Sophora flavescens, and Artemisia annua—combined with a beneficial bacterium, Bacillus subtilis, to manage necrotic enteritis in chickens. Researchers found that pomegranate peel was effective, even surpassing a standard antibiotic in reducing inflammation and promoting growth. Some combinations, like S. flavescens extract with B. subtilis, showed increased tight junction proteins' expression, while others, like pomegranate peel extract with B. subtilis, had reduced growth performance. This research highlights the potential of natural treatments as safe, effective options for farmers to improve chicken health, reduce reliance on antibiotics, and support sustainable poultry production. Necrotic enteritis (NE), caused by Clostridium perfringens, represents a major economic challenge to poultry production. This study evaluated the effects of four plant extracts—Astragalus, pomegranate peel, Sophora flavescens, and Artemisia annua—in combination with B. subtilis, as potential antibiotic alternatives for controlling NE. Using an experimentally induced NE model produced by coinfection with Eimeria maxima and C. perfringens, 288 chickens were divided into 12 groups to assess growth performance, intestinal lesions, and inflammatory markers. Compared with the enramycin group, the pomegranate peel extract group had a 9.9% increase in body weight gain (BWG), significant enhancement in claudin-2 expression, and reduced production of inflammatory factors. Compared with the infected control group, the combination of A. annua extract and B. subtilis resulted in the lowest intestinal lesion scores. The claudin-2, occludin, and zonula occludens-1 expression levels in the group treated with S. flavescens extract combined with B. subtilis increased to the highest levels compared to those in the healthy control group. These findings emphasize the potential of plant extracts, particularly pomegranate peel and A. annua with B. subtilis, as natural alternatives for NE management in poultry, providing a promising approach to reducing reliance on antibiotics. [ABSTRACT FROM AUTHOR]

Avian coccidiosis, caused by several species of Eimeria, is a widespread and economically important poultry disease that inflicts severe losses in the poultry industry. Understanding the interplay between Eimeria and gut microbiota is critical for controlling coccidiosis and developing innovative treatments to ensure good poultry health. In the present study, chickens were immunized six times with a low dose of Eimeria tenella, resulting in complete immunity against Eimeria infection. The results of fecal microbiota transplantation showed that the gut microbiota of immunized chickens induced a certain degree of resistance to coccidial infection. To investigate the types of intestinal microbiota involved in the development of resistance to Eimeria, the intestinal contents and fecal samples from both immunized and unimmunized groups were collected for 16S rRNA gene sequencing. The results showed that, at the genus level, the abundance of the Eubacterium coprostanoligenes group, Erysipelatoclostridium, Shuttleworthia, and Colidextribacter was significantly increased in the intestinal content of immunized chickens, whereas the abundance of Eisenbergiella was significantly decreased. In fecal samples, the abundance of Clostridiaceae and Muribaculaceae significantly increased, whereas that of Bacillales significantly decreased. These findings will help to elucidate the interactions between E. tenella and the gut microbiota of chickens, providing a basis for isolating E. tenella-resistant strains from the gut microbiome and developing new vaccines against coccidiosis. [ABSTRACT FROM AUTHOR]