In this paper, a heterogeneous composite catalyst Cu₂O/(001)TiO₂ was prepared by the impregnation-reduction method. The crystal form, highly active facet content, morphology, optical properties, and the photogenerated electron-hole recombination rate of the as-prepared catalysts were investigated. The performance of Cu₂O/(001)TiO₂ was appraised by photocatalytic degradation of ammonia under sunlight and was compared with lone P25, Cu₂O, and (001)TiO₂ at the same reaction conditions. The results showed that 80% of the ammonia concentration (120 ± 3 ppm) was removed by Cu₂O/(001)TiO₂, which was a higher degradation rate than that of pure P25 (12%), Cu₂O (12%), and (001)TiO₂ (15%) during 120 min of reaction time. The reason may be due to the compound’s (Cu₂O/(001)TiO₂) highly active (001) facets content that increased by 8.2% and the band gap width decreasing by 1.02 eV. It was also found that the air flow impacts the photocatalytic degradation of ammonia. Therefore, learning how to maintain the degradation effect of Cu₂O/(001)TiO₂ with ammonia will be important in future practical applications.

C. vulgaris has a positive effect on the removal of nutrients from pig farm biogas slurry. However, swine wastewater often contains heavy metal ions, such as Cu (II), which may have impacts on the nutrient removal performance of C. vulgaris. Additionally, the heavy metal ions in wastewater can be adsorbed by microalgae. In this study, the stress effect of Cu (II) on the growth of Chlorella vulgaris, the Cu (II) removal by microalgae, and the effect of different concentrations of Cu (II) on the nutrient removal efficiency of C. vulgaris in biogas slurries were explored. The results showed that the microalgae biomass of microalgae on the sixth day of the experiment was the highest in the treatment with a Cu (II) concentration of 0.5 mg/L, which was 30.1% higher than that of the 2.5 mg/L group. C. vulgaris had higher removal efficiencies of Cu (II) at a Cu (II) concentration of 0.1~1.5 mg/L. The–OH, C=O, –COOH, and C–O groups on the surface of the algal cells play a significant role in the removal of Cu (II). The removal rates of COD, NH₃–N, TN, and TP by C. vulgaris at a Cu (II) concentration of 0.5 mg/L were the highest, which were 89.0%, 53.7%, 69.6%, and 47.3%, respectively.

{001}TiO₂/TiOF₂ photocatalytic composites with a high activity {001} crystal plane were prepared by one-step hydrothermal methods using butyl titanate as a titanium source and hydrofluoric acid as a fluorine source. X-ray diffraction (XRD), scanning electron microscopy (SEM), high-resolution transmission electron microscopy (HRTEM), raman spectroscopy, N₂ adsorption-desorption curve (BET), UV-Vis diffuse absorption spectroscopy (UV-Vis DRS), X-ray photoelectron spectroscopy (XPS), and fluorescence spectroscopy (PL) were used to evaluate the structure, morphology, specific surface area, optical properties, and photocarrier separation ability of {001}TiO₂/TiOF₂. Ammonia nitrogen was taken as the target pollutant, and the degradation performance of the catalyst was investigated. The results show that hydrofluoric acid improves the content of {001} crystal plane of TiO₂ with high activity; it also improves the specific surface area and dispersion of the composite material and adjusts the ratio of {001}TiO₂ to TiOF₂ in the composite material to enhance the absorption capacity of the composite material and reduce the band gap width of the composite material. The degradation rate of ammonia nitrogen by 100 mg F15 is 93.19% when the initial concentration of ammonia nitrogen is 100 mg/L and pH is 10. Throughout the reaction process, the {001}TiO₂/TiOF₂ composite produces superoxide anion radical (·O₂⁻) and hydroxyl radical (·OH) to oxidize NH₃·H₂O and generate N₂ accompanied by a small amount of NO₃⁻ and NO₂⁻.

The long multiplication time and extremely demanding enrichment environment requirements of Anammox bacteria (AAOB) have led to difficult reactor start-ups and hindered its practical dissemination. Few feasibility studies have been reported on the recovery of AAOB activity initiation after inlet substrate disconnection caused by an unfavorable condition, and few factors, such as indicators of the recovery process, have been explored. Therefore, in this experiment, two modified expanded granular sludge bed reactors (EGSB) were inoculated with 1.5 L anaerobic granular sludge (AGS) + 1 L Anammox sludge (AMS) (R1) and 2.5 L anaerobic granular sludge (AGS) (R2), respectively. After a long-term (140 days) starvation shock at a high temperature (38 °C), the bacteria population activity recovery experiments were conducted. After 160 days, both reactors were successfully started up, and the total nitrogen removal rates exceeded 87%. Due to the experimental period, the total nitrogen removal rate of R2 was slightly higher than that of R1 in the final stage. However, it is undeniable that R2 had a relatively long activity delay during startup, while R1 had no significant activity delay during startup. The sludge obtained from R1 had a higher specific anammox activity (SAA). Analysis of the extracellular polymer substances (EPS) results showed that the extracellular polymer content in R1 was higher than that in R2 throughout the recovery process, indicating that R1 had higher sludge stability and denitrification performance. Scanning electron microscopy (SEM) analysis showed that more extracellular filamentous bacteria could be seen in the R1 reactor with better morphology of Anammox bacteria. In contrast, the R2 reactor had fewer extracellular hyphae and micropores as a percentage and higher filamentous bacteria content. The results of microbial 16SrDNA analysis showed that R1 used AAOB as inoculum to initiate Anammox, and the reactor was enriched with Anammox bacteria earlier and in much greater abundance than R2. The experimental results indicated that inoculating mixed anaerobic granular sludge and Anammox sludge to initiate an anammox reactor was more effective.

Controlling the backfat thickness of sows within an appropriate range during different production stages helps to increase the number of pigs weaned per sow per year and ultimately enhances the economic benefit to the pig farm. To obtain the backfat thickness of sows automatically, a backfat thickness estimation method based on machine vision is proposed. First, the backfat thickness values and 3D images of the buttocks of 154 Landrace–Yorkshire crossbred sows were obtained using a veterinary ultrasound backfat meter and Azure Kinect DK camera. After preprocessing the 3D images utilizing Python 3.9.16 software, 10 external morphological parameters reflecting the area, width, height, and contour radius of the sow’s buttocks were extracted. The relationships between backfat thickness and external morphological parameters were analyzed in a randomly selected group of 100 sows. A significant positive correlation was observed between backfat thickness and buttock morphological parameters, with the Pearson coefficient for the fitted ellipse area achieving values up to 0.90. A backfat thickness estimation model was developed based on selected buttock feature parameters. The model’s generalization performance was evaluated using 54 additional sows that were not involved in the model development. The coefficient of determination (R²) between the estimated and actual backfat thicknesses was 0.8923, with a mean absolute error (MAE) of 1.23 mm and a mean absolute percentage error (MAPE) of 5.73%. These metrics indicate that the model can meet production requirements, and the proposed technique offers improved estimation accuracy compared to existing methods. Ultimately, a backfat thickness automatic estimation system was developed using LabVIEW 2023 Q1 (64-bit) software. This research helps to address the cumbersome process of measuring sow backfat thickness and promotes the automation of sow farms.