Search Results (602)

(1) Background: The sophisticated function of the aortic root relies on the coordinated movement of its constituent components. This study examines the extracellular components of the interleaflet triangles (ILTs) and characterises the cells that are present within this region of the aortic root. (2) Methods: A total of 10 human aortic valves and 6 porcine aortic valves were processed for immunohistochemical staining, scanning, and transmission electron microscopy. (3) Results: The three ILTs differed in size and macroscopic appearance. Each triangle comprised up to five distinct layers of tissue: an innermost endothelial layer, an inner elastin-rich layer, a thicker outer layer comprising densely packed layers of collagen and glycosaminoglycans, and an outer layer of intermingled myocardial and adipose tissue. A band of cells near the luminal surfaces of all ILTs expressed smooth muscle cell α-actin with variable expression of smooth muscle myosin heavy chain. In all the ILTs, there was evidence of neurofilament staining, indicating the presence of nerve fibres. (4) Conclusions: Each ILT is unique in its structure and organisation, with differing amounts of elastin and collagen, as well as myocardial, adipose, and fibrous content. The ILTs contain multiple cell types in varying abundance. Functional studies are required to determine the role of the different cells and their organisation in contributing to the sophisticated, dynamic behaviour of the aortic root. Full article

Inefficient inland repositioning of empty containers between depots remains a persistent challenge in container logistics, contributing significantly to unnecessary truck movements, elevated operational costs, and increased CO₂ emissions. Acknowledging the importance of this problem, a large amount of relevant literature has appeared. The objective of this paper is to track the empty container flow between ports, empty depots, inland terminals, and customer premises. Additionally, it aims to simulate and assess CO₂ emissions, capturing the dynamic interactions between different agents. In this study, agent-based modeling (ABM) was proposed to simulate the empty container movements with an emphasis on inland transportation. ABM is an emerging approach that is increasingly used to simulate complex economic systems and artificial market behaviours. NetLogo was used to incorporate real-world geographic data and quantify CO₂ emissions based on truckload status and to evaluate the other operational aspects. Behavior Space was also utilized to systematically conduct multiple simulation experiments, varying parameters to analyze different scenarios. The results of the study show that customer demand frequency plays a crucial role in system efficiency, affecting container availability and logistical tension. Full article

Eczema, or atopic dermatitis (AD), is a chronic inflammatory skin condition characterized by persistent itching and scratching, significantly impacting patients’ quality of life. Effective monitoring of scratching behaviour is crucial for assessing disease severity, treatment efficacy, and understanding the relationship between itch and sleep disturbances. This review explores current technological approaches for detecting and monitoring scratching and itching in AD patients, categorising them into contact-based and non-contact-based methods. Contact-based methods primarily involve wearable sensors, such as accelerometers, electromyography (EMG), and piezoelectric sensors, which track limb movements and muscle activity associated with scratching. Non-contact methods include video-based motion tracking, thermal imaging, and acoustic analysis, commonly employed in sleep clinics and controlled environments to assess nocturnal scratching. Furthermore, emerging artificial intelligence (AI)-driven approaches leveraging machine learning for automated scratch detection are discussed. The advantages, limitations, and validation challenges of these technologies, including accuracy, user comfort, data privacy, and real-world applicability, are critically analysed. Finally, we outline future research directions, emphasizing the integration of multimodal monitoring, real-time data analysis, and patient-centric wearable solutions to improve disease management. This review serves as a comprehensive resource for clinicians, researchers, and technology developers seeking to advance objective itch and scratch monitoring in AD patients. Full article

Background/Objectives: As high-acuity vision is limited to a very small visual angle, examination of a scene requires multiple fixations. Simultanagnosia, a disorder wherein elements of a scene can be perceived correctly but cannot be integrated into a coherent whole, has been parsed into dorsal and ventral forms. In ventral simultanagnosia, limited visual integration is possible. This case study was the first to record gaze during the presentation of a series of visual stimuli, which required the processing of local and global elements. We hypothesised that gaze patterns would differ with successful processing and that feature integration could be disrupted by distractors. Methods: The patient received a neuropsychological assessment and underwent CT and MRI. Eye movements were recorded during the following tasks: (1) famous face identification, (2) facial emotion recognition, (3) identification of Ishihara colour plates, and (4) identification of both local and global letters in Navon composite letters, presented either alone or surrounded by filled black circles, which we hypothesised would impair global processing by disrupting fixation. Results: The patients identified no famous faces but scanned them qualitatively normally. The only emotion to be consistently recognised was happiness, whose scanpath differed from the other emotions. She identified none of the Ishihara plates, although her colour vision was normal on the FM-15, even mapping an unseen digit with fixations and tracing it with her finger. For plain Navon figures, she correctly identified 20/20 local and global letters; for the “dotted” figures, she was correct 19/20 times for local letters and 0/20 for global letters (chi-squared NS for local, p < 0.0001, global), with similar fixation of salient elements for both. Conclusions: Contrary to our hypothesis, gaze behaviour was largely independent of the ability to process global stimuli, showing for the first time that normal acquisition of visual information did not ensure its integration into a percept. The core defect lay in processing, not acquisition. In the novel Navon task, adding distractors abolished feature integration without affecting the fixation of the salient elements, confirming for the first time that distractors could disrupt the processing, not the acquisition, of visual information in this disorder. Full article

Mercury (Hg) pollution is a widespread ecological threat with sublethal effects on wildlife. Birds, due to their ecological diversity and sensitivity, serve as effective models for evaluating the behavioural impacts of Hg exposure. This review applies Tinbergen’s four questions: causation, ontogeny, function, and evolution, as an integrative framework. Mechanistically, Hg disrupts neuroendocrine pathways, gene expression, immune function, and hormone regulation, leading to behavioural changes such as reduced foraging, altered parental care, and impaired predator avoidance. Early-life exposure affects neural development, learning, and social behaviour into adulthood. Functionally, these changes reduce fitness by compromising reproduction and survival. Phylogenetic comparisons show interspecific variability, with piscivorous and insectivorous birds exhibiting high Hg burdens and sensitivity, linked to ecological roles and exposure. Behavioural responses often precede physiological or demographic effects, highlighting their value as early indicators. Both field and laboratory studies show that even low Hg concentrations can alter behaviour, though outcomes vary by species, life stage, and exposure route. Integrating behavioural endpoints into ecotoxicological risk assessments is essential to improve conservation strategies and understanding of sublethal pollutant effects on wildlife. Full article

Global warming is driving significant changes in aquatic ecosystems, where temperature fluctuations influence biological processes across multiple levels of organisation. As ectothermic organisms, fish are particularly susceptible, with even minor thermal shifts affecting their metabolism, behaviour, and overall fitness. Understanding these responses is essential for evaluating the ecological and evolutionary consequences of climate change. This study investigates the effects of acute (4-day) and chronic (21-day) exposure to three temperature regimes—18 °C (low), 26 °C (control), and 34 °C (high)—on the spatio-temporal shoaling behaviour of adult zebrafish (Danio rerio). Groups of four fish were tested for six minutes in water maintained at the same temperature as their prior acclimation. Shoaling behaviour was assessed by analysing shoal structure—encompassing shoal dimensions and cohesion—as well as spatial positioning. Parameters measured included inter-fish distance, shoal volume, shoal area, homogeneity index, distance to the centroid, and the shoal’s vertical and horizontal distribution. Results revealed complex behavioural changes influenced by both temperature and duration of exposure. At 18 °C, zebrafish showed a marked preference for the bottom zone and exhibited no significant temporal modulation in exploratory behaviour—patterns indicative of heightened anxiety-like responses. In contrast, exposure to 34 °C resulted in increased shoal cohesion, particularly under chronic conditions, and a progressive increase in environmental exploration over the six-minute test period. This enhancement in exploratory activity was especially evident when compared to the first minute of the test and was characterised by greater vertical movement—reflected in the increased use of the upper zone—and broader horizontal exploration, including more frequent occupation of peripheral areas. These findings align with previous research linking thermal variation to neurobiological and proteomic alterations in zebrafish. By elucidating how temperature modulates social behaviour in ectotherms, this study offers valuable insights into the potential behavioural impacts of climate change on aquatic ecosystems. Full article

Suicide in children is a major global health crisis, with profound impacts on families, friends, and society. Understanding ways to ameliorate the rate of suicide attempt (SA) is critical given that it is a key factor in predicting future suicide risk. SA is the deliberate act of causing physical injury to oneself with the intent of death. The incidence of SA may be influenced by physical activity (PA). PA includes bodily movement via skeletal muscles that results in energy expenditure and physical fitness. While there is evidence to suggest that PA improves dysregulation of the parasympathetic nervous system which underpins the physiology of suicidal behaviour, evaluating the impact of PA on SA in children is required. Objectives: This systematic review aims to determine the relationship between PA and SA in children to inform alternative preventative and interventional strategies. Methods: This systematic review was registered with PROSPERO: CRD42023389415. Eight electronic databases were systematically searched. References were transferred to Covidence software for title and abstract screening and full text review were performed based on eligibility criteria: (1) children aged 6–18 years old; (2) participated in PA (individual, group exercise, or team sports); and (3) examined SA as a dependent variable. The JBI Checklist was used to measure the quality and level of bias of included studies. Results: Of the 2322 studies identified, 21 were included in the final analysis of the review. Twenty studies were cross-sectional in design, and one implemented a prospective study design. Thirteen studies (61.9%) yielded statistically significant results, indicating that increased PA, particularly team sport, may be associated with reduced odds of SA. There was some evidence to suggest that certain intensities and frequencies of PA may be beneficial to some and detrimental to other subgroups. Conclusions: The results suggest that PA may reduce the risk of suicide attempts. Although PA may be associated with reduced SA in children, future research is required, which (1) uses standardised outcome variables; (2) adopts longitudinal and experimental study designs; (3) explores qualitative research to determine distinctive factors that influence participation in PA not captured by quantitative research; and (4) examines different target populations such as children with a broad range of mental health issues. Full article

The review provides an overview of research concerning the assessment of cattle welfare in different housing systems. Hence, it restricts its scope to factors known to have a particular influence on the expression of their natural behaviours. It analyses the impact of housing systems on social and maternal bonds, as well as on the health and productivity of animals and on the feeding behaviour and physical activity of animals. It also pays attention to the occurrence of stereotypies, indicating the quality of the environment in which animals live, and attempts to determine the extent to which environmental enrichment improves welfare. It can be seen that welfare can vary significantly depending on the cattle rearing system. In intensive rearing environments, weaning calves and limited space often result in stress and behavioural disorders (e.g., cross-sucking). Extensive systems, offering access to pasture and longer cow–calf contact, usually provide higher levels of welfare. A freestall system allows greater freedom of movement and social contact but requires appropriate management to prevent aggression; in contrast, the tethering system limits movement, which increases the risk of stress and health problems. It has also been shown that enriching the living space of animals can significantly improve their welfare, regardless of the housing system. By balancing productivity with ensuring that the cattle are able to express their natural behaviours and maintain good health, it is possible to benefit both the animals and the agricultural sector as a whole, increasing its profitability and gaining consumer confidence. Full article

This article reviews and discusses the behaviours and patterns associated with panic evacuations, as documented in the literature, which must be considered when analysing and modelling such events. This article does not take the form of a typical research article but, rather, a review of previous studies alongside its own commentary. The studies analysed in this article were selected according their ability to provide a new perspective. Where possible, diverse perspectives from existing research have been contrasted with the author’s own observations and reflections. Structured as an overview, this article introduces subsequent analyses and highlights several non-intuitive questions that arose during the investigation. This study examines the relationship between movement velocity and crowd density, comparing experimental data with simulations conducted to date. It also explores the connections between flow rate, crowd density, and velocity and suggests potential directions for further research in this field. Additionally, this article addresses the loss of evacuation coordination under crowding conditions and presents studies that demonstrate optimal evacuation at speeds that differ from the so-called comfortable pace. The positive effects of strategically placed obstacles in reducing congestion and improving evacuation times are also analysed. This literature review is conducted from a practical perspective, with the primary aim of deepening our understanding of panic evacuation phenomena. Furthermore, this article categorises the impact of various phenomena associated with stampedes and panic evacuations on the requirements for safe evacuation. A tabular summary of the technical and structural measures for evacuation is provided, which may prove useful in designing effective evacuation strategies when dealing with heightened emotional states among evacuees. Full article

Recent research in the area of physical literacy has revealed that the early years are a period that has not been well studied. Our research team designed a deductive review with the aim of investigating how preschool children’s physical literacy manifests across affective, physical, cognitive and social domains. The review includes scientific publications from the last four years, which investigate the elements of physical literacy in preschool children: motivation, confidence, motor competence, knowledge, understanding and use of physical activity. The characteristics of the elements were systematised into four domains, affective, physical, cognitive and social, as engagement in physical activities. Results. The majority of the articles explained physical literacy behaviours in 4- to 5-year-old children. The physical domain was most frequently described, mainly including the three basic motor skills of postural stability, object control, and locomotion, as well as physical qualities of movement. The second most frequently described domain was the social domain of the application of physical activities in preschool stages, including the types and amounts of physical activity used in both organised and leisure time. Conclusions. Physical literacy of preschool children is a purposefully organised and guided process, during which a child is given the opportunity to try and apply age-appropriate movement skills, without being limited by the child’s gender, parental attitudes, sporting choices, or the traditions of sport culture. Full article

Human Activity Recognition (HAR) is crucial for understanding human behaviour through sensor data, with applications in healthcare, smart environments, and surveillance. While traditional HAR often relies on ambient sensors, wearable devices or vision-based systems, these approaches can face limitations in dynamic settings and raise privacy concerns. Device-free HAR systems, utilising Wi-Fi Channel State Information (CSI) to human movements, have emerged as a promising privacy-preserving alternative for next-generation health activity monitoring and smart environments, particularly for multi-user scenarios. However, current research faces challenges such as the need for substantial annotated training data, class imbalance, and poor generalisability in complex, multi-user environments where labelled data is often scarce. This paper addresses these gaps by proposing a hybrid deep learning approach which integrates signal preprocessing, targeted data augmentation, and a customised integration of CNN and Transformer models, designed to address the challenges of multi-user recognition and data scarcity. A random transformation technique to augment real CSI data, followed by hybrid feature extraction involving statistical, spectral, and entropy-based measures to derive suitable representations from temporal sensory input, is employed. Experimental results show that the proposed model outperforms several baselines in single-user and multi-user contexts. Our findings demonstrate that combining real and augmented data significantly improves model generalisation in scenarios with limited labelled data. Full article

Anthropogenic underwater noise is an increasing form of pollution that negatively affects biota. The effect of this pollutant on many marine species is still largely unknown, especially those that are more sensitive to particle motion than to sound pressure. In these cases, experiments at sea are necessary, due to the difficulty of recreating the particle movement of a real acoustic field under laboratory conditions. This work aims to contribute to the knowledge of the effect of ship noise on the behaviour of mussels (Mytilus galloprovincialis), performing measurements at sea on a real mussel cultivation raft for the first time. The study is carried out on cluster-forming individuals living in the rafts where they are cultivated. Their behaviour is monitored by means of valvometry systems, which measure the magnitude of shell opening using a High-Frequency Non-Invasive (HFNI) system. Simultaneously, the acoustic field generated by the abundant traffic in the area is measured. The results show cause-and-effect relationships between ship noise and valve closure events. Full article

Articular cartilage (AC) plays an important role in the biomechanics of synovial joints. Its task is to enable smooth movement and transfer of mechanical loads with minimised friction. AC is characterised by unique mechanical properties resulting from its complex structure, in which the dominant components are type II collagen, proteoglycans and water. Healthy articular cartilage shows elasticity in compression, viscoelastic properties, and the ability to relax stresses under the influence of cyclic loads. In response to different loading modes, it shows anisotropic and non-uniform behaviour, which translates into its cushioning and protective function for the subchondral bone. Significant changes occur in the structure and mechanical properties of cartilage with age as a result of mechanical overload or degenerative diseases, such as osteoarthritis. This results in a deterioration of the cushioning and mechanical function, which leads to progressive degradation of joint tissues. Understanding the mechanical properties of AC is crucial for developing effective diagnostic methods. Analysis of changes in mechanical properties contributes to the early detection of pathological changes. The aim of this paper is to review the current state of knowledge regarding the structure and biomechanical properties of articular cartilage, and to analyse conventional and alternative diagnostic methods in the context of their suitability for assessing the state of AC, particularly in the early stages of degenerative processes. Full article

Visual behaviour in zebrafish, often measured by the optokinetic reflex (OKR), serves as a valuable model for studying aspects of human neurological and ocular diseases and for conducting therapeutic or toxicology assays. Traditional methods for OKR analysis often rely on binarization techniques (threshold-based conversion of images to black and white) or costly software, which limits their utility in low-contrast settings or hypopigmented disease models. Here, we present a novel deep learning pipeline for OKR analysis, using ResNet-50 within the DeepLabCut framework in a Python Version 3.10 environment. Our approach employs object tracking to enable robust eye movement quantification, regardless of variations in contrast or pigmentation. OKR responses were elicited in both wild-type and slc45a2 (albino) mutant zebrafish larvae at 5 days post-fertilisation, using a mini-LED arena with a rotating visual stimulus. Eye movements were recorded and analysed using both conventional software and our deep learning approach. We demonstrate that the deep learning model achieves comparable accuracy to traditional methods, with the added benefits of applicability in diverse lighting conditions and in hypopigmented larvae. Statistical analyses, including Bland–Altman tests, confirmed the reliability of the deep learning model. While this study focuses on 5-day-old zebrafish larvae under controlled conditions, the pipeline is adaptable across developmental stages, pigmentation types, and behavioural assays. With appropriate adjustments to experimental parameters, it could be applied to broader behavioural studies, including social interactions and predator–prey dynamics in ocular and neurological disease models. Full article

Autism Spectrum Disorder (ASD) poses significant challenges in diagnosis due to its diverse symptomatology and the complexity of early detection. Atypical gait and gesture patterns, prominent behavioural markers of ASD, hold immense potential for facilitating early intervention and optimising treatment outcomes. These patterns can be efficiently and non-intrusively captured using modern computational techniques, making them valuable for ASD recognition. Various types of research have been conducted to detect ASD through deep learning, including facial feature analysis, eye gaze analysis, and movement and gesture analysis. In this study, we optimise a dual-stream architecture that combines image classification and skeleton recognition models to analyse video data for body motion analysis. The first stream processes Skepxels—spatial representations derived from skeleton data—using ConvNeXt-Base, a robust image recognition model that efficiently captures aggregated spatial embeddings. The second stream encodes angular features, embedding relative joint angles into the skeleton sequence and extracting spatiotemporal dynamics using Multi-Scale Graph 3D Convolutional Network(MSG3D), a combination of Graph Convolutional Networks (GCNs) and Temporal Convolutional Networks (TCNs). We replace the ViT model from the original architecture with ConvNeXt-Base to evaluate the efficacy of CNN-based models in capturing gesture-related features for ASD detection. Additionally, we experimented with a Stack Transformer in the second stream instead of MSG3D but found it to result in lower performance accuracy, thus highlighting the importance of GCN-based models for motion analysis. The integration of these two streams ensures comprehensive feature extraction, capturing both global and detailed motion patterns. A pairwise Euclidean distance loss is employed during training to enhance the consistency and robustness of feature representations. The results from our experiments demonstrate that the two-stream approach, combining ConvNeXt-Base and MSG3D, offers a promising method for effective autism detection. This approach not only enhances accuracy but also contributes valuable insights into optimising deep learning models for gesture-based recognition. By integrating image classification and skeleton recognition, we can better capture both global and detailed motion patterns, which are crucial for improving early ASD diagnosis and intervention strategies. Full article