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People may be more likely to exercise if they have self-efficacy for exercise (SEE). We conducted an exploratory analysis of SEE using data from a clinical trial designed to increase physical activity (N = 340). We evaluated correlates of baseline SEE and the relationship between baseline SEE and physical activity. Low SEE at baseline was correlated with lower well-being, physical activity, and higher depression at baseline. Participants with high (vs. low) baseline SEE had higher physical activity (but no differential change in activity) over time. These data highlight the potential role of SEE in psychological health and physical activity.

High particulate matter levels in cage-free (CF) houses have led to concerns from producers, as that can pose significant risks to the health and well-being of hens and their caretakers. This study aimed to assess the effectiveness of an electrostatic particle ionization (EPI) + bedding management (BM) treatment in reducing particulate matter (PM) concentrations. Four identical CF rooms each housed 175 hens for six weeks, with two rooms assigned to the EPI + BM treatment (EPI + 20% wood chip topping over 81-week-old litter) and the other two as controls. Measurements of PM were conducted twice a week for 10 min using TSI DustTrak. Additionally, small and large particle concentrations were monitored continuously using a Dylos monitor, with a sampling period of one minute. Footpad scoring was recorded for logistic analysis. Statistical analysis was performed using ANOVA with the Tukey HSD method (p < 0.05). Results demonstrated that the EPI + BM treatment significantly reduced particle counts (37.83% decrease in small particles, 55.90% decrease in large particles) compared to the control group (p < 0.01). PM concentrations were also substantially lowered across different size fractions, ranging from 58.41% to 64.17%. These findings underscore the effectiveness of the EPI + BM treatment in reducing PM in CF houses. The integration of EPI and bedding management innovated in this study holds promise for improving air quality and contributing to the well-being of hens and caretakers in CF housing systems.

The poultry industry is shifting towards more sustainable and ethical practices, including adopting cage-free (CF) housing to enhance hen behavior and welfare. However, ensuring optimal indoor air quality, particularly concerning particulate matter (PM), remains challenging in CF environments. This study explores the effectiveness of electrostatic particle ionization (EPI) technology in mitigating PM in CF hen houses while considering the height at which the technology is placed and the duration of the electric supply. The primary objectives are to analyze the impact of EPI in reducing PM and investigate its power consumption correlation with electric supply duration. The study was conducted in a laying hen facility with four identical rooms housing 720 laying hens. The study utilized a Latin Square Design method in two experiments to assess the impact of EPI height and electric supply durations on PM levels and electricity consumption. Experiment 1 tested four EPI heights: H1 (1.5 m or 5 ft), H2 (1.8 m or 6 ft), H3 (2.1 m or 7 ft), and H4 (2.4 m or 8 ft). Experiment 2 examined four electric supply durations: D1 (control), D2 (8 h), D3 (16 h), and D4 (24 h), through 32 feet corona pipes. Particulate matter levels were measured at three different locations within the rooms for a month, and statistical analysis was conducted using ANOVA with a significance level of ≤0.05. The study found no significant differences in PM concentrations among different EPI heights (p > 0.05). However, the duration of EPI system operation had significant effects on PM1, PM2.5, and PM4 concentrations (p < 0.05). Longer EPI durations resulted in more substantial reductions: D2—17.8% for PM1, 11.0% for PM2.5, 23.1% for PM4, 23.7% for PM10, and 22.7% for TSP; D3—37.6% for PM1, 30.4% for PM2.5, 39.7% for PM4, 40.2% for PM10, and 41.1% for TSP; D4—36.6% for PM1, 24.9% for PM2.5, 38.6% for PM4, 36.3% for PM10, and 37.9% for TSP compared to the D1. These findings highlight the importance of prolonged EPI system operation for enhancing PM reduction in CF hen houses. However, utilizing 16 h EPI systems during daylight may offer a more energy-efficient approach while maintaining effective PM reduction. Further research is needed to optimize PM reduction strategies, considering factors like animal activities, to improve air quality and environmental protection in CF hen houses.

ABSTRACT: Chickens’ behaviors and activities are important information for managing animal health and welfare in commercial poultry houses. In this study, convolutional neural networks (CNN) models were developed to monitor the chicken activity index. A dataset consisting of 1,500 top-view images was utilized to construct tracking models, with 900 images allocated for training, 300 for validation, and 300 for testing. Six different CNN models were developed, based on YOLOv5, YOLOv8, ByteTrack, DeepSORT, and StrongSORT. The final results demonstrated that the combination of YOLOv8 and DeepSORT exhibited the highest performance, achieving a multiobject tracking accuracy (MOTA) of 94%. Further application of the optimal model could facilitate the detection of abnormal behaviors such as smothering and piling, and enabled the quantification of flock activity into 3 levels (low, medium, and high) to evaluate footpad health states in the flock. This research underscores the application of deep learning in monitoring poultry activity index for assessing animal health and welfare.

Background: Recently, Otoendoscopy, a novel technique, serves as a pivotal non-invasive diagnostic tool for the initial evaluation of ear disorders. Retraction pockets of the tympanic membrane are clinically significant because they can lead to hearing loss. Therefore, they necessitate careful evaluation and ongoing monitoring. Oto-endoscope because of the wide viewing angle gives a good view of the tympanic membrane status. The objective of this study was to clinically evaluate and grade tympanic membrane retractions and compare otoscopy and otoendoscopy findings. Material and Methods: This was a cross-sectional prospective study. A total 190 ears with tympanic membrane retractions of 111 patients were included in the study. Each of the patients was evaluated for retractions grade according to the Sade and Tos system of classification using pneumatic otoscope and otoendoscope. Results: In 79 (71.2%) patients had bilateral tympanic retraction whereas 32 (28.8%) patients had unilateral. Isolated pars tensa and pars flaccida retraction was found in 109 (57.3%) ears, and 4 (2.1%) ears respectively, while 77 (40.5%) ears having both type of retraction. A cross-tabulation of retraction grades revealed a significant association (p

Imitation learning (IL), a burgeoning frontier in machine learning, holds immense promise across diverse domains. In recent years, its integration into robotics has sparked significant interest, offering substantial advancements in autonomous control processes. This paper presents an exhaustive insight focusing on the implementation of imitation learning techniques in agricultural robotics. The survey rigorously examines varied research endeavors utilizing imitation learning to address pivotal agricultural challenges. Methodologically, this survey comprehensively investigates multifaceted aspects of imitation learning applications in agricultural robotics. The survey encompasses the identification of agricultural tasks that can potentially be addressed through imitation learning, detailed analysis of specific models and frameworks, and a thorough assessment of performance metrics employed in the surveyed studies. Additionally, it includes a comparative analysis between imitation learning techniques and conventional control methodologies in the realm of robotics. The findings derived from this survey unveil profound insights into the applications of imitation learning in agricultural robotics. These methods are highlighted for their potential to significantly improve task execution in dynamic and high-dimensional action spaces prevalent in agricultural settings, such as precision farming. Despite promising advancements, the survey discusses considerable challenges in data quality, environmental variability, and computational constraints that IL must overcome. The survey also addresses the ethical and social implications of implementing such technologies, emphasizing the need for robust policy frameworks to manage the societal impacts of automation. These findings hold substantial implications, showcasing the potential of imitation learning to revolutionize processes in agricultural robotics. This research significantly contributes to envisioning innovative applications and tools within the agricultural robotics domain, promising heightened productivity and efficiency in robotic agricultural systems. It underscores the potential for remarkable enhancements in various agricultural processes, signaling a transformative trajectory for the sector, particularly in the realm of robotics and autonomous systems.

Dengue virus (DENV), a common and prevalent mosquito-borne endemic disease, is caused by four serotypes (DENV-1–4) and has spread rapidly on a global scale over the past decade. A crucial step in the development of antiviral therapeutics requires the utilization of in vitro cell-based techniques, such as plaque assays and focus-forming assays (FFA) for virus quantification. Vero cells have been widely used for FFA and plaque assay; however, there are instances when their efficacy and efficiency in the detection of certain clinical DENV isolates are low. Here, we showed that BHK-21 cells are more sensitive than Vero cells in the detection of all DENV-1–4 plaques and foci. In addition, we developed an improved FFA protocol for the quantification of all four DENV serotypes. Using a pan-flavivirus envelope (E) antibody, we reduce the possibility of false positives by defining a focus to consist of a minimum of eight infected cells. We outlined a protocol using the Operetta® high-content imaging system to automate the digital capture of these infected cells. A pipeline was also designed using the CellProfilerTM automated image analysis software to detect these foci. We then compare the results of the improved FFA with plaque assay. Notably, the improved FFA detected clear foci of the DENV-4 strain that does not form distinct plaques. We subsequently demonstrated the potential application of the improved FFA protocol in antiviral testing, utilizing a nucleoside inhibitor of DENV, NITD008 as a control. The protocol is amenable to a diverse array of applications, including high-throughput compound screening (HTS).

Abstract The inevitable drawbacks of petrochemical polymer‐based packaging (e.g., extreme loss of fossil resources, excessive products’ carbon footprint, and inordinate environmental pollution resulting from the accumulation of disposed nonbiodegradable plastic‐based packages) have urged scientists to develop novel packaging materials from nature‐inspired biopolymers. Due to their biodegradability, non‐toxicity, film‐forming ability, and barrier properties versus gasses/aroma, polysaccharides have been increasingly valued in developing food packaging materials at the lab or industrial scale. Nonetheless, these valuable biopolymers also suffer from some inherent deficiencies, that is, low resistance to water and poor mechanical attributes. Hitherto, tackling such bottlenecks via the modification of biopolymers through chemical/physical approaches and applying a combination of several biopolymers has been the main focus of numerous recent studies. In this context, the present article, for the first time, provides a comprehensive update on the most recent utilization of common polysaccharides (e.g., starch, chitosan, xanthan gum, gum Arabic, alginate, gellan, pectin, and carrageenan) for food packaging applications.

During the life of a well, treatments are carried out to boost productivity by stimulating initially unproduced zones. These treatments include hydraulic fracturing, matrix acidization, and acid fracturing, among others. Hydraulic fracturing treatment is generally applied to deeper reservoirs of oil or natural gas for enhanced recovery. By infusing proppant, water, and chemicals under extreme pressure during the fracturing procedure, fissures in and beneath the reservoir layer can be accessed and expanded. Another stimulating procedure, matrix acidization, involves injecting acid down the drilling hole to permeate the rock fissures at stresses lower than the fracture stress. In addition, carbonate reservoir acid fracturing stimulation is commonly used as an acid treatment technique whereby a pressure greater than the formation disintegration pressure or spontaneous fracture closure pressure is used to compress acid into the reservoir. These treatments allow existing wells to sustain hydrocarbon production without new wells being drilled. Diverters, when employed efficiently, can prevent the need to use a rig to provide momentary physical barriers, thus lowering the cost of the workover. Recent improvements in diversion technology make use of a variety of degradable particles that act as momentary bridges, either at the perforation entries or inside the existing fractures. The aim of this study is to introduce different types of mechanical and chemical diverters used to enhance the productivity of wells. This study explains the concepts of different types of diverters and their applications in several formations, it will also help readers to understand the selection procedures based on the suitability and requirements of diverter use by case studies from around the world.

The Fourth Industrial Revolution has ushered in several changes in the Oil and Gas (O&G) sector—all with a unified goal of improving, optimizing, and digitalizing existing processes and techniques. Digitalization in the O&G sector provides superior solutions for the efficiency of operations. In digitalization, the machines are connected to digital systems such as sensors; they generate accurate insights, respond in real-time and are efficient. Current digital narratives in the O&G sector are limited in space and use bottom-up technologies. However, a top-down strategy that not only overcomes the digital deluge but also assists O&G executives in following a digital revolution might be beneficial to the business. The advantages of prominent technologies such as artificial intelligence, the Internet of Things, and big data analytics are the same, yet they are interconnected. While conventional approaches like SCADA and wireless sensor networks (WSN) have served their purpose, the advent of edge computing and IoT heralds a new era of data-driven decision-making and operational efficiency. Digital transformation can deliver increased safety while minimising the environmental impact of the industry. The technologies that are used in the past and the development of such technologies are discussed in detail in this study.

ABSTRACT: Cage-free (CF) housing systems are expected to be the dominant egg production system in North America and European Union countries by 2030. Within these systems, bumblefoot (a common bacterial infection and chronic inflammatory reaction) is mostly observed in hens reared on litter floors. It causes pain and stress in hens and is detrimental to their welfare. For instance, hens with bumblefoot have difficulty moving freely, thus hindering access to feeders and drinkers. However, it is technically challenging to detect hens with bumblefoot, and no automatic methods have been applied for hens' bumblefoot detection (BFD), especially in its early stages. This study aimed to develop and test artificial intelligence methods (i.e., deep learning models) to detect hens' bumblefoot condition in a CF environment under various settings such as epochs (number of times the entire dataset passes through the network during training), batch size (number of data samples processed per iteration during training), and camera height. The performance of 3 newly developed deep learning models (i.e., YOLOv5s-BFD, YOLOv5m-BFD, & YOLOv5x-BFD) were compared in detecting hens with bumblefoot of hens in CF environments. The result shows that the YOLOv5m-BFD model had the highest precision (93.7%), recall (84.6%), mAP@0.50 (90.9%), mAP@0.50:0.95 (51.8%), and F1-score (89.0%) compared with other models. The observed YOLOv5m-BFD model trained at 400 epochs and batch size 16 is recommended for bumblefoot detection in laying hens. This study provides a basis for developing an automatic bumblefoot detection system in commercial CF houses. This model will be modified and trained to detect the occurrence of broilers with bumblefoot in the future.

The present study focuses on the utilization of non-conventional starch (NS) derived from guinea grass seed to produce porous starch (PS) and octenyl succinic anhydride-modified PS (OSAPS). The study also introduces a novel approach to produce PS, aiming to overcome the high cost associated with glucoamylase. The formation of porous granules was successfully achieved through the combination of alpha-amylase and ultrasonication, as confirmed by electron micrographs and analysis of pore size and specific surface area. The results demonstrate that OSAPS exhibits superior emulsion stability, well-defined pore structures, and desirable amphiphilic characteristics. All three starches were loaded with lycopene, flaxseed oil, and a combination of both to prepare microcapsules. The presence of flaxseed oil within the starch matrix was confirmed through micrographs and functional group analysis. Notably, OSAPS exhibited the highest encapsulation efficiency at 74.80 %, along with a lycopene retention rate of up to 27.32 mg/100 g. Moreover, OSAPS showcased favorable antioxidant activity (89.29 %), phenolic content (0.45 mg GAE/g), and flavonoid content (97.61 mg QE/100 g). These findings underscore the remarkable potential of OSAPS as a delivery system for bioactive compounds, particularly for the co-encapsulation of oils and pigments.

ABSTRACT: The increasing demand for cage-free (CF) poultry farming raises concern regarding air pollutant emissions in these housing systems. Previous studies have indicated that air pollutants such as particulate matter (PM) and ammonia (NH3) pose substantial risks to the health of birds and workers. This study aimed to evaluate the efficacy of electrostatic particle ionization (EPI) technology with different lengths of ion precipitators in reducing air pollutants and investigate the relationship between PM reduction and electricity consumption. Four identical CF rooms were utilized, each accommodating 175 hens of 77 wk of age (WOA). A Latin Square Design method was employed, with 4 treatment lengths: T1 = control (0 m), T2 = 12 ft (3.7 m), T3 = 24 ft (7.3 m), and T4 = 36 ft (11.0 m), where room and WOA are considered as blocking factors. Daily PM concentrations, temperature, and humidity measurements were conducted over 24 h, while NH3 levels, litter moisture content (LMC), and ventilation were measured twice a week in each treatment room. Statistical analysis involved ANOVA, and mean comparisons were performed using the Tukey HSD method with a significance level of P ≤ 0.05. This study found that the EPI system with longer wires reduced PM2.5 concentrations (P ≤ 0.01). Treatment T2, T3, and T4 led to reductions in PM2.5 by 12.1%, 19.3%, and 31.7%, respectively, and in small particle concentrations (particle size >0.5 μm) by 18.0%, 21.1%, and 32.4%, respectively. However, no significant differences were observed for PM10 and large particles (particle size >2.5 μm) (P < 0.10), though the data suggests potential reductions in PM10 (32.7%) and large particles (33.3%) by the T4 treatment. Similarly, there was no significant impact of treatment on NH3 reduction (P = 0.712), possibly due to low NH3 concentration (

People may be more likely to exercise if they have self-efficacy for exercise (SEE). We conducted an exploratory analysis of SEE using data from a clinical trial designed to increase physical activity (N = 340). We evaluated correlates of baseline SEE and the relationship between baseline SEE and physical activity. Low SEE at baseline was correlated with lower well-being, physical activity, and higher depression at baseline. Participants with high (vs. low) baseline SEE had higher physical activity (but no differential change in activity) over time. These data highlight the potential role of SEE in psychological health and physical activity.