Search Results (471)

Animal welfare education requires pedagogical models that bridge conceptual knowledge with practice. This study presents GamifyWELL, a biomimetic, gamified learning environment for students, farmers, and veterinary technicians. Grounded in ecological principles of adaptation, diversification, and niche specialization, the design emulates how living systems evolve through feedback and cooperation. These principles were translated into an instructional model that integrates a core pathway (Pre-Test, Levels 1–4, Post-Test) with optional enrichment tasks and a role-specific Reward Marketplace. Question formats are constant across levels (MCQ, image-based, video-based) while cognitive difficulty increases, culminating in Positive Welfare scenarios. We describe the learning design structure and report preliminary implementation observations using a mixed-methods evaluation plan (pre/post knowledge assessments and engagement indicators). Results from early deployment indicate strong usability and engagement, with high voluntary uptake of enrichment tasks and positive learner feedback on role-tailored rewards; full empirical testing is in progress. Findings support the feasibility and pedagogical promise of biomimetic gamification to enhance knowledge, motivation, and intended practice in animal welfare education. GamifyWELL offers a replicable framework for nature-inspired instructional design that can be extended to allied sustainability domains. Full article

Nonverbal tests assess cognitive ability in multicultural and multilingual children, but language-based instructions disadvantage non-proficient children. This is a growing concern worldwide due to the increasing number of multilingual classrooms. The tablet-based FLUX (Fluid Intelligence Luxembourg) test was developed within a highly multicultural and multilingual educational context to offer not only nonverbal test content but also language-fair animated video instructions. A total of 703 third graders (M_age = 8.85, SD = 0.66; 48.8% females, 51.1% males, 0.1% with no gender specified) were included in the standardisation sample and were assessed with tasks measuring figural fluid intelligence, quantitative fluid intelligence, visual processing and short-term memory. The test proved sufficiently reliable (FLUX Full-scale: McDonald’s Omega = 0.94; split-half = 0.95). Test fairness was ensured by analysing each item for Differential Item Functioning (DIF) on children’s background characteristics (language spoken at home, socioeconomic status, gender). Its factorial structure was confirmed using Confirmatory Factor Analysis (CFA). Further validity evidence was provided by determining its concurrent and criterion-related validity (correlations with a test of cognitive ability and educational achievement scores). Research implications and future prospects in promoting equal opportunities in a heterogeneous multilingual educational context are discussed. Full article

Nasotracheal Intubation (NTI) is a common route of airway management in many situations. Over the years, numerous techniques and approaches have been described in performing NTI safely and effectively, including many innovative techniques being published in recent years. However, there hasn’t been a summary of the recent approaches to NTI, especially in an easy, clinically applicable decision making format. In fact, the last algorithmic approach to nasal intubation in the literature was published in 2008. This comprehensive review details an updated analysis of NTI techniques along with a new adapted algorithmic outline to approach NTI in a methodical and stepwise manner. There is also an extensive review of techniques to control epistaxis, which is the most commonly encountered complication during NTI. The newly adapted NTI algorithm simplifies the initial approach to three options: Routine Asleep NTI, Awake NTI, and an Initial Orotracheal Intubation (OTI) followed by Conversion to NTI. Older techniques, such as blind NTI, flexible intubation scope guided, “look before you leap” approach and cuff inflation technique, are discussed along with incorporation of newer techniques, such as videolaryngoscope guided, hybrid, alignment approach, and OTI to NTI conversion. Uniquely, this manuscript reviews all published techniques for converting OTI to NTI and categorizes them into two pathways: direct conversion (with glottic visualization) or indirect conversion (without glottic visualization). Furthermore, original animated videos have been created and attached to help elucidate these conversion techniques visually. Full article

This study investigated the preference behaviour of 24 four-week-old weaned piglets under different lighting conditions (0 lux with 0 Kelvin vs. 80 lux with 3000 Kelvin vs. 6500 Kelvin). Two trials with 12 piglets each were conducted over five weeks in a room with four interconnected pens, allowing free movement between the pens. Pens A and B were nearly dark (~0 lux), while pen C (80 lux, 3000 Kelvin) and pen D (80 lux, 6500 Kelvin) were illuminated. On three days in weeks 1, 3 and 5, behaviour (lying, eating and activity) was recorded using video observations and a 5 min time sampling method. Cleanliness was also monitored daily. In the first week, piglets in the first batch preferred the darkened pens, whereas piglets in the second batch preferred illuminated pens, especially when the colour temperature was 3000 Kelvin. By the third week, piglets in the second batch now preferred darker areas. In the fifth week, the piglets spent more time in the dark in the mornings and evenings but showed no preference for colour temperature. The darkened pens remained mostly clean, whereas pen D, which had a light colour temperature of 6500 Kelvin, was the most soiled. The results show that piglet behaviour changes with age and the time of day, suggesting that lighting concepts can be adapted to improve both animal welfare and pen hygiene. Full article

Animal welfare assessments increasingly aim to quantify enclosure use and activity to support naturalistic behavior and improve Quality of Life (QoL). Traditionally, this is achieved through manual observations, which are time-consuming, subject to observer bias, and limited in temporal resolution due to short observation periods. Here, we compared manual tracking using ZooMonitor with automated pose estimation (SLEAP) in a mother–son pair of black-headed spider monkeys (Ateles fusciceps) at Aalborg Zoo. We collected manual observations on six non-consecutive days (median daily duration: 62 min, mean: 66 min, range: 52–90 min) and visualized this as spatial heatmaps. We applied pose estimation to the same video footage, tracking four body parts to generate corresponding heatmaps. Across most days, the methods showed strong agreement (overlap 83–99%, Pearson’s r = 0.93–1.00), with both highlighting core activity areas on the floor near the central climbing structures and by the door with feeding gutters. Both methods also produced comparable estimates of time spent being active, with no significant difference across days (p = 0.952). Our results demonstrate that computer vision technology can provide a reliable and scalable tool for monitoring enclosure use and activity, enhancing the efficiency and consistency of zoo-based welfare assessments while reducing reliance on labor-intensive manual observations. Full article

The management of chronic rumination syndrome in professionally cared-for animals requires a comprehensive and individualized approach. In this case study, a multimodal approach incorporating pharmacological treatment, feeding modifications, and behavioral management was applied to a California sea lion (Zalophus californianus) with rumination syndrome, megaesophagus, and hypothyroidism. Behavioral observations were collected through video recordings both prior to and post-intervention. Interventions included oral naltrexone and contingent reinforcement post-feed to provide alternative enrichment activities after feeding sessions to reduce rumination syndrome, as well as levothyroxine for hypothyroidism. Additionally, dietary modifications involved offering smaller food portions, spreading meals across longer time periods, and feeding in a more upright position to facilitate esophageal passage. Results showed a reduction in the frequency of rumination syndrome, with no visible regurgitated material observed five months post-intervention. The sea lion demonstrated improved engagement in training sessions, voluntary husbandry tasks, and open-water activities, as well as improved interactions with conspecifics. The combination of pharmacological, dietary, and behavioral strategies reduced rumination behavior and improved the animal’s overall quality of life, reinforcing the value of individualized care strategies and multimodal treatment plans in addressing complex medical and behavioral comorbidities. These findings show the importance of individualized, multimodal care plans in managing complex behavioral and medical conditions, and they contribute to advancing animal-welfare practices across species. Full article

Social media has emerged as a dominant platform for sharing human–animal interactions, creating a powerful tool for public engagement and wildlife conservation. Consequently, we sought to determine whether analyzing user preferences for animals on social networks could inform the management of effective conservation campaigns. We analyzed 5129 videos from three channels (Brave Wilderness, BBC Earth, and Nat Geo Wild) available on YouTube, which have millions of followers each. The mean number of “likes” was used as a proxy for animal species preferences. Contrary to the general expectation that humans predominantly prefer charismatic animals (e.g., terrestrial mammals), the most preferred animals on these channels were from the classes Amphibia, Arachnida, and Insecta, which significantly outperformed mammals and birds. Viewers most frequently consumed videos of stinging insects or threatening animals, and domestic animals received more likes than wild animals. Furthermore, contrary to expectations, body mass, IUCN conservation status, and daytime activity of mammals and birds did not significantly influence human preferences. Our results suggest that although viewing animal videos may have a negligible direct conservation impact, the analysis of preferences reveals that creators successfully captured human attention toward less popular animal taxa, highlighting potential indirect benefits. Future research should integrate audience enjoyment of frightening content with conservation intentions. Full article

Disbudding is a common practice on dairy farms, with the hot iron method (HID) widely used, though it causes considerable pain if no analgesia is provided. This study included two experiments. In Experiment 1, an alternative method using policresulen (POD) was evaluated in 24 Holstein calves randomly assigned to either POD or HID at 21 ± 2 days of age. Calves in the POD group received 0.2 mL of 36% policresulen per horn bud, while those in the HID group were fully cauterized. The cornual nerve was blocked with 5 mL of 2% lidocaine in both treatments, and all calves received meloxicam (0.5 mg/kg body weight) for three days post-procedure. Calves treated with POD exhibited fewer pain-related behaviors, such as scratching the horn buds, rubbing against objects, and head shaking, and showed faster horn bud regression. However, 12-month observations revealed that 9 of 12 POD-treated calves showed horn regrowth, indicating limited long-term effectiveness. Experiment 2 assessed consumer perceptions through a questionnaire and video with 236 participants. Participants with farming experience were more familiar with disbudding and preferred HID. In contrast, individuals with less agricultural contact demonstrated a greater willingness to pay for products from farms implementing animal welfare practices, with 76% favoring POD. Overall, participants experienced in agribusiness prioritized technical knowledge and practicality, while others valued animal welfare and were willing to pay higher prices for welfare-friendly practices. Full article

The whale shark Rhincodon typus is the largest known extant omnivorous fish species, reaching up to 17 m in length. Because of its slow growth and late maturity, R. typus is particularly vulnerable to human activities and is listed as endangered on the IUCN Red List. Understanding its biological characteristics, such as growth rate, is essential for their conservation. Non-invasive methods, including stereo-image measurements, have been used to measure the body length of the species over the years, which aggregates in coastal areas during specific life stages. This method enables us to estimate fish length by recording the target using a stereo camera, which commonly consists of two cameras. However, measurement errors increase in the setup as the target moves away from the camera. Therefore, we conducted a multi-stereo video shoot of a free-swimming whale shark in an aquarium tank and compared the performance of stereo cameras using two, three, and four cameras. The setups with three and four cameras outperformed the traditional two-camera stereo setup in terms of precision and accuracy, suggesting that a multi-stereo camera system can effectively estimate the body length of large animals such as whale sharks from a considerable distance. Full article

Animal behavior recognition is an important research area that provides insights into areas such as neural functions, gene mutations, and drug efficacy, among others. The manual coding of behaviors based on video recordings is labor-intensive and prone to inconsistencies and human error. Machine learning approaches have been used to automate the analysis of animal behavior with promising results. Our work builds on existing developments in animal behavior analysis and state-of-the-art approaches in computer vision to identify rodent social behaviors. Specifically, our proposed approach, called Vision Transformer for Rat Social Interactions (ViT-RSI), leverages the existing Global Context Vision Transformer (GC-ViT) architecture to identify rat social interactions. Experimental results using five behaviors of the publicly available Rat Social Interaction (RatSI) dataset show that the ViT-RatSI approach can accurately identify rat social interaction behaviors. When compared with prior results from the literature, the ViT-RatSI approach achieves best results for four out of five behaviors, specifically for the “Approaching”, “Following”, “Moving away”, and “Solitary” behaviors, with F1 scores of 0.81, 0.81, 0.86, and 0.94, respectively. Full article

This study proposes a behavioral monitoring framework for newborn piglets based on SPMF-YOLO object detection and ByteTrack multi-object tracking, which enables precise quantification of early postnatal activity levels and health assessment. The method enhances small-object detection performance by incorporating the SPDConv module, the MFM module, and the NWD loss function into YOLOv11. When combined with the ByteTrack algorithm, it achieves stable tracking and maintains trajectory continuity for multiple targets. An annotated dataset containing both detection and tracking labels was constructed using video data from 10 piglet pens for evaluation. Experimental results indicate that SPMF-YOLO achieved a recognition accuracy rate of 95.3% for newborn piglets. When integrated with ByteTrack, it achieves 79.1% HOTA, 92.2% MOTA, and 84.7% IDF1 in multi-object tracking tasks, thereby outperforming existing methods. Building upon this foundation, this study further quantified the cumulative movement distance of each newborn piglet within 30 min after birth and proposed a health-assessment method based on statistical thresholds. The results demonstrated an overall consistency rate of 98.2% across pens and an accuracy rate of 92.9% for identifying abnormal individuals. The results validated the effectiveness of this method for quantifying individual behavior and assessing health status in newborn piglets within complex farming environments, providing a feasible technical pathway and scientific basis for health management and early intervention in precision animal husbandry. Full article

A straightforward ex vivo approach has been developed and refined to enable high-resolution imaging and quantitative assessment of motile cilia function in mouse airway epithelial tissue, allowing critical insights into cilia motility and cilia generated flow using different mouse models or following different sample treatments. In this method, freshly excised mouse trachea is cut longitudinally through the trachealis muscle which is then sandwiched between glass coverslips within a thin silicon gasket. By orienting the tissue along its longitudinal axis, the natural curling of the trachealis muscle helps maintain the sample in a configuration optimal for imaging along the full tracheal length. High-speed video microscopy, utilizing differential interference contrast (DIC) optics and a fast digital camera capturing at >200 frames per second is then used to record ciliary motion. This enables detailed measurement of both cilia beat frequency (CBF) and waveform characteristics. The application of 1 µm microspheres to the bathing media during imaging allows for additional analysis of fluid flow generated by ciliary activity. The entire procedure typically takes around 40 min to complete per animal: ~30 min for tissue harvest and sample mounting, then ~10 min for imaging samples and acquiring data. Full article

Artificial Intelligence (AI) is widely recognized as a force that will fundamentally transform traditional chicken farming models. It can reduce labor costs while ensuring welfare and at the same time increase output and quality. However, the breadth of AI’s contribution to chicken farming has not been systematically quantified on a large scale; few people know how far current AI has actually progressed or how it will improve chicken farming to enhance the sector’s sustainability. Therefore, taking “AI + sustainable chicken farming” as the theme, this study retrieved 254 research papers for a comprehensive descriptive analysis from the Web of Science (May 2003 to March 2025) and analyzed AI’s contribution to the sustainable in recent years. Results show that: In the welfare dimension, AI primarily targets disease surveillance, behavior monitoring, stress detection, and health scoring, enabling earlier, less-invasive interventions and more stable, longer productive lifespans. In economic dimension, tools such as automated counting, vision-based weighing, and precision feeding improve labor productivity and feed use while enhancing product quality. In the environmental dimension, AI supports odor prediction, ventilation monitoring, and control strategies that lower emissions and energy use, reducing farms’ environmental footprint. However, large-scale adoption remains constrained by the lack of open and interoperable model and data standards, the compute and reliability burden of continuous multi-sensor monitoring, the gap between AI-based detection and fully automated control, and economic hurdles such as high upfront costs, unclear long-term returns, and limited farmer acceptance, particularly in resource-constrained settings. Environmental applications are also underrepresented because research has been overly vision-centric while audio and IoT sensing receive less attention. Looking ahead, AI development should prioritize solutions that are low cost, robust, animal friendly, and transparent in their benefits so that return on investment is visible in practice, supported by open benchmarks and standards, edge-first deployment, and staged cost–benefit pilots. Technically, integrating video, audio, and environmental sensors into a perception–cognition–action loop and updating policies through online learning can enable full-process adaptive management that improves welfare, enhances resource efficiency, reduces emissions, and increases adoption across diverse production contexts. Full article

Keel bone lesions (KBLs) represent a relevant welfare concern in laying hens, arising from complex interactions among genetics, housing systems, and management practices. This study presents the development of an image analysis system for the automated detection and classification of KBLs in slaughterhouse videos, enabling scalable and retrospective welfare assessment. In addition to lesion classification, the system can track and count individual carcasses, providing estimates of the total number of specimens with and without significant lesions. Videos of brown laying hens from a commercial slaughterhouse in northeastern Italy were recorded on the processing line using a smartphone. Six hundred frames were extracted and annotated by three independent observers using a three-scale scoring system. A dataset was constructed by combining the original frames with crops centered on the keel area. To address class imbalance, samples of class 1 (damaged keel bones) were augmented by a factor of nine, compared to a factor of three for class 0 (no or mild lesion). A YOLO-based model was trained for both detection and classification tasks. The model achieved an F1 score of 0.85 and a mAP@0.5 of 0.892. A BoT-SORT tracker was evaluated against human annotations on a 5 min video, achieving an F1 score of 0.882 for the classification task. Potential improvements include increasing the number and variability of annotated images, refining annotation protocols, and enhancing model performance under varying slaughterhouse lighting and positioning conditions. The model could be applied in routine slaughter inspections to support welfare assessment in large populations of animals. Full article

Growing engagement with online animal videos has raised questions about their potential psychological benefits. While prior research links pet attachment to reduced loneliness, little is known about whether similar effects arise from online animal interactions. This study introduces the concept of cyber-mediated animal attachment—emotional bonds formed with animals in digital media—and investigates its role in mediating the relationship between video engagement and loneliness. The model’s incremental validity was further assessed beyond the explanatory power of personality traits and emotional states. Two sub-studies were conducted, comprising a questionnaire survey and an experimental study. The findings revealed that (1) engagement with online animal videos was significantly negatively associated with levels of loneliness, and this relationship was linear rather than nonlinear; (2) cyber-mediated animal attachment mediated the relationship between video engagement and loneliness; and (3) compared to humorous human videos that elicit similar positive emotions, animal videos were more likely to evoke attachment toward the video character, which in turn contributed to reduced loneliness. These results provide empirical support for the role of online animal videos in alleviating loneliness, help clarify the psychological mechanisms of virtual attachment, and offer new perspectives and intervention strategies for addressing loneliness through digital means. Full article