Search Results (155)

Background: Low-dose antibiotic contamination in animal feed is a persistent global food safety challenge. Transient early-life exposure to low-dose penicillin (LDP) is known to induce metabolic syndrome (MetS) in adult mice, but the underlying mechanisms are unclear. Introduction: This study investigated the role of gut microbiota (GM) and intestinal immunity in mediating the long-term metabolic effects of early-life LDP exposure. Methods: Mice were exposed to LDP transiently during early life. GM composition was analyzed. Intestinal IgA responses were quantified. Bacterial encroachment, systemic and adipose tissue inflammation, and diet-induced MetS were assessed. Germ-free (GF) mice received GM transplants from LDP-exposed or control mice to test causality and persistence. Results: Early-life LDP exposure significantly disrupted GM composition, particularly in the ileum, in 30-day-old mice. These GM alterations caused persistent suppression of intestinal IgA responses, evidenced by reduced IgA-producing cells and sIgA levels. This suppression was constrained to early-life exposure: transferring LDP-modified GM to GF mice produced only a transient reduction in fecal sIgA. The LDP-induced sIgA reduction decreased IgA binding of bacteria, leading to increased bacterial encroachment and systemic and adipose tissue inflammation. These pathological changes exacerbated diet-induced MetS. Discussion: Our findings demonstrate that early-life LDP exposure induces persistent intestinal IgA deficiency through lasting GM alterations initiated in early development. This deficiency drives bacterial encroachment, inflammation, and ultimately exacerbates MetS. Conclusions: The exacerbation of diet-induced metabolic syndrome by early-life LDP exposure occurs through an intestinal sIgA-dependent pathway triggered by persistent GM disruption. This highlights a critical mechanism linking early-life antibiotic exposure, gut immune dysfunction, and long-term metabolic health, with significant implications for food safety. Full article

Objectives: Feeding and eating disorders (FED) represent a major public health issue and are the second leading cause of death among psychiatric conditions in children and adolescents. Psychopathological comorbidities play a significant role in the onset and persistence of FED, yet research on their underlying structure remains limited. This study explores the psychiatric comorbidities associated with FED, focusing on common etiopathogenetic factors and their clinical implications. Methods: Data were retrospectively collected from the Italian Regional Center for FED in the Emilia-Romagna Region between June 2023 and April 2024. Diagnoses were assigned following DSM-5 criteria using the Italian version of the semi-structured K-SADS-PL diagnostic interview. Principal component analysis (PCA) was performed to identify latent psychological dimensions underlying FED psychopathology, retaining five components based on the scree plot. Additionally, an analysis of covariance (ANCOVA) was conducted to examine differences in factor scores across FED subtypes, while adjusting for potential confounders. Results: Seventy-two participants were included (mean age: 14.6 years; mean BMI: 18.3 kg/m²; male-to-female ratio: 1:8). Diagnoses were distributed as follows: 63.9% anorexia nervosa (AN), 13.9% other specified feeding and eating disorder (OSFED), 6.9% avoidant restrictive food intake disorder (ARFID), 4.2% binge eating disorder (BED), 4.2% unspecified feeding and eating disorder (UFED), and 2.7% bulimia nervosa (BN). All participants met the criteria for at least one psychiatric comorbidity. Identified psychopathological clusters include the following: (1) mood disorders (66.5%); (2) anxiety disorders (87.5%); (3) obsessive–compulsive and related disorders (47.2%); (4) neurodevelopmental disorders, i.e., attention-deficit/hyperactivity disorder (ADHD) (30.5%); (5) disruptive and impulse-control disorders (13.9%); and (6) psychotic symptoms (40.3%). No instances of tic or elimination disorders were detected. Conduct disorder was more prevalent among UFED, BED, and BN patients compared to other FED (p = 0.005), and moderate/severe ADHD was associated with higher body mass index (BMI) (p = 0.035). PCA revealed distinct psychological dimensions underlying FED, while ANCOVA indicated significant differences in factor scores across FED subtypes, supporting the presence of shared transdiagnostic mechanisms. Conclusions: This study highlights the complex interplay between FED and psychiatric comorbidities, emphasizing the need for early intervention and personalized treatment approaches. The dimensional structure identified through PCA suggests that common psychopathological factors may drive FED development, and ANCOVA findings support their differential expression across FED types. Future research should further investigate these transdiagnostic mechanisms to optimize clinical care. Full article

This study proposes an AI-powered digital twin (DT) platform designed to support real-time traffic risk prediction, decision-making, and sustainable mobility in smart cities. The system integrates multi-source data—including static infrastructure maps, historical traffic records, telematics data, and camera feeds—into a unified cyber–physical platform. AI models are employed for data fusion, anomaly detection, and predictive analytics. In particular, the platform incorporates telematics–video fusion for enhanced trajectory accuracy and LiDAR–camera fusion for high-definition work-zone mapping. These capabilities support dynamic safety heatmaps, congestion forecasts, and scenario-based decision support. A pilot deployment on Madison’s Flex Lane corridor demonstrates real-time data processing, traffic incident reconstruction, crash-risk forecasting, and eco-driving control using a validated Vehicle-in-the-Loop setup. The modular API design enables integration with existing Advanced Traffic Management Systems (ATMSs) and supports scalable implementation. By combining predictive analytics with real-world deployment, this research offers a practical approach to improving urban traffic safety, resilience, and sustainability. Full article

Antibiotic resistance has become a global health concern, driving the need for sustainable alternatives in animal husbandry. This study explores the potential of natural feed additives as a viable solution to enhance poultry growth and health while reducing reliance on antibiotics. Chinese herbal medicines and probiotics have been widely studied as green, healthy, and safe antibiotic alternatives in livestock and poultry production. A total of 120 chickens were randomly divided into four groups: a control group and three treatment groups supplemented with 1% Pulsatilla chinensis powder, 3% fresh Acer truncatum, or 1% Clostridium butyricum. The results showed that Pulsatilla chinensis powder significantly increased gamma-glutamylcysteine (p < 0.05), UDP-N-acetylglucosamine (p < 0.05), tyramine (p < 0.01), and leucine (p < 0.05). Acer truncatum notably altered cecal metabolites, including L-tyrosine (p < 0.05), α-ketoisovaleric acid (p < 0.01), myristoleic acid (p < 0.01), glutathione (p < 0.05), and PGA1 (p < 0.05). Clostridium butyricum modified cecal metabolites such as L-glutamine (p < 0.05), riboflavin (p < 0.05), L-Carnitine (p < 0.05), ergocalciferol (p < 0.01), and α-tocotrienol (p < 0.05). Full article

Building materials, including polyvinyl chloride (PVC), play a key role in construction engineering, influencing the durability, esthetics, and functionality of structures. PVC stands out for its lightness, thermal insulation, and corrosion resistance. This makes it competitive with wood, aluminum, or steel, particularly in the manufacture of window joinery. One of the key technological processes in the processing of PVC profiles is welding, the quality of which depends on the precise control of parameters such as the temperature, time, and pressure regulating the speed of the welding heads. In modern welding machines, the use of servo drives guarantees the adequate precision and repeatability of the process, which allows better adjustment to technological requirements than in older machines. This study aimed to determine the effect of the heating head feed rate for selected milling depths on the quality and strength of window frame welds. A criterion in the assessment of the strength of the window frames was the result of failure load tests on the welds. In addition, the tests took into account the quality of the welds. The tests showed that the welding head feed rate of 0.25 mm/s generated the highest-quality welds, taking into account the continuity and symmetry of the weld and its highest failure load. When milling the composite to a depth of 1 mm, the average value of the failure load was 3637 N. Meanwhile, for speeds of 0.19 mm/s and 0.31 mm/s, it was 3157 N and 3033 N, respectively. For the 0.5 mm milling variant and without milling the composite, the average load values were significantly smaller. Full article

As artificial intelligence (AI) technology continues to advance and iterate, various industries have undergone intelligent reformation. China’s animal husbandry industry, given its importance for people’s livelihoods, is no exception to this transformation. Using AI technology in this field is becoming increasingly common since it not only improves production efficiency but also revolutionizes traditional business models. Animal science is a fundamental discipline that drives the progress of animal husbandry by studying the growth, breeding, nutritional needs, and feeding management of livestock and poultry. This discipline also explores advanced veterinary theories and technologies for epidemic prevention and control. The ultimate objective of this discipline is to ensure the production of high-quality and sufficient animal products to fulfill the demands of both production and daily life. It is predicted that the deep integration of AI technology into animal science will bring unprecedented opportunities to the animal husbandry industry. This study aims to explore the impact of artificial intelligence (AI) on students’ learning experiences and future educational directions. By situating the research within the context of current developments in educational technology, we hope to provide valuable insights for educators and policymakers and employ a questionnaire survey to explore the perceptions and attitudes of students majoring in animal science from various agricultural institutions in China toward this integration. The results of the study provide valuable and practical references for the cultivation and development of artificial intelligence talent in China’s livestock industry. Full article

This study aimed to explore the impacts of Lactiplantibacillus plantarum (L), Saccharomyces cerevisiae (Y), tannase-producing bacteria (D), cellulase (M), and their combined treatment (L + Y + D + M) on the sensory quality, chemical composition, silage quality, and microbial community of Caragana korshinskii. In light of the scarcity of research on the use of tannase-producing bacteria, Lactiplantibacillus plantarum, Saccharomyces cerevisiae, and cellulase as composite silage additives in the utilization of desert shrubs as feed resources, this study centers on this area and endeavors to offer a novel theoretical foundation for relevant fields. Different microorganisms and enzymes were individually added to 500 g of Caragana korshinskii, and anaerobic fermentation was carried out in an incubator at 40 °C for 14 days. The results show that compared to the control group (CK) without any additives, the sensory evaluation of all treatments improved, with the L + Y + D + M treatment being the best (p < 0.05). All treatments reduced the contents of acid detergent fiber, neutral detergent fiber, and tannin (p < 0.05), while increasing the content of crude protein and relative feeding value (p < 0.05), with the L + Y + D + M treatment showing the most significant effect (p < 0.05). Lactic acid levels significantly increased (p < 0.05) and the pH significantly decreased (p < 0.05) in all treatments, with the L + Y + D + M treatment outperforming the other treatments (p < 0.05). The L + Y + D + M treatment increased the abundance of Lactiplantibacillus plantarum and Weissella (p < 0.05), significantly reduced harmful microbial abundance and diversity (p < 0.05), and improved the microbial community structure in silage. In summary, the addition of Lactiplantibacillus plantarum (L), Saccharomyces cerevisiae (Y), tannase-producing bacteria (D), cellulase (M), and their combined treatment (L + Y + D + M) can promote the silage-related characteristics of Caragana korshinskii, with the L + Y + D + M treatment performing better compared to the other treatments. The research shows that the compound bacterial and enzymatic preparation is more effective than the single-component. The components exert synergistic effects and can effectively enhance the quality aspects of silaged Caragana korshinskii. This research provides theoretical underpinnings for the utilization of Caragana korshinskii as feedstuff. This application has the potential to alleviate feed scarcity, reduce reliance on traditional feed, enhance the stability and diversity of the feed supply system, and thereby drive the development of the animal husbandry industry. Full article

Peanut (Arachis hypogaea L.) is an important oil and economic crop, widely cultivated across various regions, with China leading global peanut production. The mechanization of peanut harvesting plays a crucial role in advancing the entire peanut industry. Half-feed peanut combine harvesters, characterized by high operational integration, can complete the harvesting of mature peanuts in a single pass and are widely used in major production areas such as Henan and Shandong in China. This paper summarizes the development history of half-feed peanut combine harvesters in the context of current peanut-planting and harvesting models, outlining their main types and operational characteristics. It also reviews the information technologies applied to these machines, including autonomous driving, harvesting quality detection, and adaptive control of operational parameters, summarizing their main types and working principles. Based on the current demand for intelligent and automated operations, the paper analyzes the main issues and development strategies for half-feed peanut combine harvesters, providing a theoretical basis for their development and the advancement of the peanut industry. Full article

As significant fungal pathogens of crops, Fusaria species contaminate various food and feed commodities. Some of the Fusarium spp. secondary metabolites (e.g., trichothecenes, zearalenone, and fumonisins) are widely known toxic molecules (mycotoxins) with chronic and acute effects on humans and animals. The growing demand for safer, pesticide-free food drives us to increase biological control during crop growing. Recent research suggests that lactic acid bacteria (LABs) as biocontrol are the best choice for extenuating Fusarium mycotoxins. Newly isolated LABs were tested as antifungal agents against Fusarium verticillioides, F. graminearum, and F. oxysporum. The characterized and genetically identified LABs belonged to Limosilactobacillus fermentum (SD4) and Lactiplantibacillus plantarum (FCW4 and CB2) species. All tested LABs and their cell-free culture supernatants showed antagonism on the MRS solid medium. The antifungal activity was also demonstrated on surface-sterilized wheat and peanuts. The germination test of corn kernels proved that the LAB strains SD4 and FCW4 significantly (p < 0.05) enhanced root and shoot development in plantlets while simultaneously suppressing the outgrowth of F. verticillioides. Small-scale corn silage fermentation revealed the significant effects of SD4 supplementation (decreased zearalenone, lower mold count, and total reduction of deoxynivalenol) within the mixed populations. Full article

Heterotis niloticus is a fascinating freshwater fish species popularly referred to as the African bonytongue. It offers great potential for aquaculture due to its rapid growth, flesh quality, adaptability to low oxygen environments, and high market value. Domestication efforts for this species have been initiated to optimize its production and meet the increasing global demand for sustainable protein sources. This review explores the current state of H. niloticus domestication and highlights the key challenges and opportunities. Despite their promising potential, several obstacles remain, including the development of efficient hatchery techniques, optimization of feed formulations, and disease control. Overcoming these challenges is essential to promote the full potential of H. niloticus aquaculture and contribute to improved food security. Future research should focus on refining breeding programs, improving water quality management, and exploring innovative aquaculture systems. Policy support is key to driving investments, innovation, conservation efforts, and the sustainable development of H. niloticus aquaculture. Full article

This paper introduces an enhanced APF method to address challenges in automatic lane changing and collision avoidance for autonomous vehicles, targeting issues of infeasible target points, local optimization, inadequate safety margins, and instability when using DLQR. By integrating a distance adjustment factor, this research aims to rectify traditional APF limitations. A safety distance model and a sub-target virtual potential field are established to facilitate collision-free path generation for autonomous vehicles. A path tracking system is designed, combining feed-forward control with DLQR. Linearization and discretization of the vehicle’s dynamic state space model, with constraint variables set to minimize control-command costs, aligns with DLQR objectives. The aim is precise steering angle determination for path tracking, negating lateral errors due to external disturbances. A Simulink–CarSim co-simulation platform is utilized for obstacle and speed scenarios, validating the autonomous vehicle’s dynamic hazard avoidance, lane changing, and overtaking capabilities. The refined APF method enhances path safety, smoothness, and stability. Experimental data across three speeds reveal reasonable steering angle and lateral deflection angle variations. The controller ensures stable reference path tracking at 40, 50, and 60 km/h around various obstacles, verifying the controller’s effectiveness and driving stability. Comparative analysis of visual trajectories pre-optimization and post-optimization highlights improvements. Vehicle roll and sideslip angle peaks, roll-angle fluctuation, and front/rear wheel steering vertical support forces are compared with traditional LQR, validating the optimized controller’s enhancement of vehicle performance. Simulation results using MATLAB/Simulink and CarSim demonstrate that the optimized controller reduces steering angles by 5 to 10°, decreases sideslip angles by 3 to 5°, and increases vertical support forces from 1000 to 1450 N, showcasing our algorithm’s superior obstacle avoidance and lane-changing capabilities under dynamic conditions. Full article

The electrowetting display (EWD) device is a new type of electrowetting-on-dielectric (EWOD) equipment that can achieve a paper-like display effect under the control of an electric field. In this microfluidic system, the stability of grayscale can be affected by various factors, such as the physicochemical properties of the materials, the device structure, and electric field distribution. To improve the grayscale stability of active matrix electrowetting displays (AM-EWDs), the impact of different polarities of driving voltage on oil backflow was investigated in this study. Based on the driving principles of AM-EWD, an optimized inter-frame bipolar reset driving waveform was designed to overcome oil backflow. The proposed driving waveform maintained the stability of the oil state by periodically and rapidly releasing trapped charges in the dielectric layer through a reverse driving voltage. Additionally, the effect of feed-through voltage on pixel driving voltage was eliminated by compensating for the driving voltage on a common electrode. Finally, the performance of the designed driving waveform was evaluated with a 6-inch AM-EWD driving platform. Compared to the conventional unipolar reset driving waveform, the backflow speed decreased by 2.70 a.u./s. The standard deviation of the display luminance was also reduced by 11.24 a.u. Experimental results indicated that both the oil backflow speed and the fluctuation range of luminance were effectively suppressed by the proposed driving waveform. Full article

To improve the expandability, seeding accuracy, and operating speed range of the electric drive system (EDS) of precision seeders, this study constructed an EDS based on a controller area network (CAN) bus and designed a motor controller based on a field-orientated control (FOC) algorithm. Full-factorial bench and field tests based on seed spacing (0.1, 0.2, and 0.3 m) and operating speed (3, 6, 9, 12, and 15 km/h) were carried out to evaluate the performance of the EDS. The results of bench tests showed that seeding quality varied inversely with operating speed and positively with seed spacing. The average quality of feed index (QFI) at 0.1, 0.2, and 0.3 m seed spacing in bench tests was 88.38%, 96.67%, and 97.36%, with the average coefficient of variation (CV) being 20.13%, 16.27%, and 13.20%. Analysis of variance confirmed that both operating speed and seed spacing had a significant effect on QFI and CV (p < 0.001). The analysis of motor rotational speed accuracy showed that the relative error of motor rotational speed above 410 rpm did not exceed 2.24%, and the relative error had less influence on the seeding quality. The average QFI was 85.93%, 95.91%, and 96.24%, with the average CV being 21.12%, 15.50%, and 16.49% at 0.1, 0.2, and 0.3 m seed spacing in field tests. The methods and results of this study can provide a reference for the design and optimization of the EDS in a maize precision seeder and provide an effective solution for the improvement of maize yields. Full article

To compare and validate wind speed estimation algorithms applied to wind turbines, wind speed estimators were designed in this study, based on two methods presented in the literature, and their performance was validated using the NREL 5MW model. The first method for wind speed estimation involves a three-dimensional (3D) look-up table-based approach, constructed using drive train differential equations. The second method involves applying a continuous–discrete extended Kalman filter. To verify and compare the performance of the algorithms designed using these different methods, feed-forward control algorithms, available power estimation algorithms, and a linear quadratic regulator, based on fuzzy logic (LQRF) control algorithms, were selected and applied as verification means, using the estimated wind speed as the input. Based on the simulation results, the performance of the two methods was compared. The method using drive train differential equations demonstrated superior performance in terms of reductions in the standard deviations of rotor speed and electrical power, as well as in its prediction accuracy for the available power. Full article

In large-scale machine tool applications, the presence of low structural natural frequencies limits the cutting capabilities of the machine. The machine tool joints interact with the structural mode shapes, hence, the feed drive system characteristics can significantly influence the resultant dynamics at the cutting point. This paper investigates the effect of guideway non-linear friction and feed drive motion control parameters on chatter stability predictions. Field experimentation on seven machines reveals substantial differences between in-motion and idle dynamics, leading to errors in traditional process stability predictions. By using a one-degree-of-freedom model that incorporates non-linear friction and controller forces together with motion commands, the effect of axis motion on machine tool dynamics is analyzed. Later, the feed and force non-linearities are studied in a large-scale machine tool using traditional and alternative dynamic characterization techniques. The findings demonstrate that both feed and force non-linearities influence the frequency response functions at the cutting points, ultimately affecting the accuracy of process stability predictions. Proper selection of feed drive control parameters reduces the cutting point compliance, improving machine tool productivity by up to 50%. Full article