Search Results (409)

Habitat selection is often activity-specific, as animals may use different environments depending on whether they are foraging, breeding, or moving through the habitat. Behavioural studies of nocturnal species are challenging, and conventional methods are limited in their applicability. In this study, we tested a thermal drone in combination with Artificial Intelligence (AI) for focal animal sampling and habitat use of mesopredators. A drone mounted with a thermal video camera recorded the movements and behaviours of red foxes (Vulpes vulpes), European badgers (Meles meles), and Eurasian otters (Lutra lutra), while simultaneously geocoding their position. Additionally, we tested an AI-based analysis, LabGym for species and behaviour detection of video recordings. In Danish agricultural areas, both habitat separation and spatial overlap among the three mesopredators, were observed. Foxes showed a higher degree of versatility in both behaviour and habitat choice compared to badgers and otters. Otters were primarily found near water bodies, while badgers preferred foraging under tree cover and in meadows. The optimised LabGym achieved 80.4% mAP for species identification and successfully classified four behaviours with more than 80% accuracy. Using the thermal drone in combination with geolocation data and AI enables spatial mapping of mesopredator activities, adding valuable insights into predator ecology. Full article

Powered instruments such as drills are commonly used in the endoscopic modified Lothrop procedure, also known as Draf III frontal sinusotomy. However, the use of drills may be associated with increased bone exposure, prolonged postoperative healing, synechiae and crust formation, and mechanical injury to the nasal vestibule. The objective of this study is to present a simple alternative method for manually performing the endoscopic modified Lothrop procedure using a Kerrison rongeur and a 0-degree endoscope. A surgical candidate for an endoscopic modified Lothrop procedure was identified, and informed consent was obtained to record surgical footage to illustrate the technique. This article describes an alternative technique for performing the endoscopic modified Lothrop procedure using manual instruments, thereby avoiding the use of powered drills and potentially allowing for maximal preservation of the frontal recess mucosa. In addition, the technique enables the procedure to be performed without the use of angled endoscopes, facilitating surgical maneuvers. A summary table outlining each step of the procedure with technical tips, as well as a surgical video illustrating the technique, are also presented. This manual Draf III frontal sinusotomy technique may complement the surgical armamentarium of the frontal sinus surgeon. Full article

In the digital economy era, Urban vitality has transitioned into an intertwined Virtual-Physical system. This study examines Changsha’s five urban districts through a dual-dimensional framework bridging physical (social, economic, cultural, and ecological) and virtual (video, social, and digital life) dimensions. Integrating Coupling Coordination Degree (CCD) and XGBoost-SHAP models, we elucidate the spatial patterns and nonlinear drivers of Virtual-Physical synergy. The results indicate that: (1) Urban Vitality exhibits a significant center-periphery gradient. Although the Coupling Degree between the two dimensions is high, the overall CCD remains relatively low, reflecting pervasive spatial mismatches. Notably, 55 units display a reverse pattern where Virtual Vitality surpasses Physical Vitality, suggesting that digital flows can reconfigure urban space by transcending traditional locational constraints. (2) Interactions within the built environment exert pronounced threshold effects. Structural elements require specific critical masses to activate synergy, beyond which marginal returns diminish, as exemplified by the U-shaped effect of the Green View Index and the inverted U-shaped effect of Spatial Enclosure on CCD. (3) Interaction analysis identifies building density as a multiplier, unlocking the synergistic potential of land-use mix and transport networks once critical thresholds are surpassed. Furthermore, the efficacy of population and transit relies on dense road networks and intersection, while functional diversity buffers against negative micro-environmental impacts. This study advocates for a shift from facility-increment to threshold-triggered precision strategies in urban regeneration, providing empirical support for human-centric planning in the digital twin era. Full article

Facial expressions transmit information about internal states, both during social interaction and in response to shared stimuli such as films. When individuals view the same content, synchrony in their expressions reflects shared information processing, and the degree to which their expressions correlate indicates how similarly their perceptual and affective systems are responding to the common input. This makes interindividual expression synchrony a potential marker of engagement and subjective experience. However, the acquisition and analysis of facial data pose both ethical and technical challenges to researchers. ‘Trace’ is a research media player implemented in PsychoPy’s online platform Pavlovia, which captures anonymised facial landmark coordinates through a webcam, without the ethical and technical constraints of capturing and storing video images of participants. Nonetheless, its usefulness is currently limited due to the lack of available preprocessing and analysis tools. This paper describes the functionality of TraceLAB, a MATLAB-based toolbox designed for the preprocessing of Trace data: specifically, the formatting, aligning, and filtering of data. In addition, TraceLAB implements some novel analysis techniques to allow researchers to quantify interindividual synchrony of expressions (through correlated component analysis) and head movements (through Surrogate Synchrony), which may be interpreted as measures of shared information processing. These techniques are demonstrated here on both simulated and real datasets. Full article

Competency in musculoskeletal (MSK) ultrasound requires learners to relate probe manipulation to spatial reasoning, image projection, and the appearance of characteristic artefacts, which remains challenging during early training due to the limited spatial context provided by conventional instructional resources. This study investigates whether reconstructing real MSK ultrasound examinations in an immersive extended reality (XR) environment is perceived as useful for early familiarisation with probe handling and image interpretation. The proposed system reproduces ultrasound acquisitions using synchronised ultrasound video, six-degree-of-freedom probe tracking, and surface scans acquired from cadaveric specimens, enabling the reconstruction of spatially accurate probe trajectories with each ultrasound frame linked to a corresponding position and orientation. Within the XR environment, users can interactively explore these trajectories or observe automated playback in which the recorded probe motion is presented together with the corresponding ultrasound sequence. An exploratory evaluation with healthcare professionals was conducted to assess perceived usefulness and clarity of spatial relationships. The results indicate that participants perceived spatially coherent playback of real ultrasound examinations in XR as a potentially useful aid for understanding probe–image relationships. These findings suggest the feasibility of this approach as a complementary resource for introductory MSK ultrasound training. Full article

Objective: This study aimed to compare the efficacy of immersive 360-degree Virtual Reality (VR) videos depicting local (Malaysian) versus overseas (Western European) natural environments on the mental health of medical students. The primary outcome was overall mental well-being (WHO-5), and the co-secondary outcomes were changes in anxiety, stress, and depression symptoms (DASS-21). Methods: A two-arm parallel randomized trial was conducted with 84 fourth-year and fifth-year medical students. Participants were randomized into two groups (n = 42 each) using a custom, gender-balancing minimization algorithm: Group 1 viewed local environments, and Group 2 viewed overseas environments. Each participant underwent two 15-min VR sessions spaced two weeks apart. Outcomes were measured at baseline (T0), after the first intervention (T1), and at the primary time point after the second intervention (T2). Data were analyzed using a repeated-measures ANOVA with Greenhouse–Geisser and Bonferroni corrections. Results: The VR intervention demonstrated a statistically significant improvement in well-being (p < 0.001, ${\eta }_p^2$ = 0.380) and a significant reduction in anxiety (p < 0.001, ${\eta }_p^2$ = 0.255) and stress (p < 0.001, ${\eta }_p^2$ = 0.311) across all participants over time. No significant change was observed in depression scores (p = 0.122, ${\eta }_p^2$ = 0.028). Notably, there were no statistically significant differences between the local and overseas groups for well-being (p = 0.399, ${\eta }_p^2$ = 0.011), anxiety (p = 0.593, ${\eta }_p^2$ = 0.005), stress (p = 0.945, ${\eta }_p^2$ < 0.001), or depression (p = 0.546, ${\eta }_p^2$ = 0.006). Conclusions: A two-session immersive VR nature intervention is effective for improving well-being and reducing anxiety and stress in medical students. The geographical familiarity of the environment did not significantly impact therapeutic effectiveness, suggesting that the restorative effects of virtual nature may generalize across different environmental and cultural contexts. Trial Registration: NCT07447310; retrospectively registered on 25 February 2026. Full article

The use of hybrid classes, where face-to-face classroom and asynchronous activities are combined in an online environment, helps save time and provides students with resources to study and review the materials. Although numerous empirical studies have analyzed the effectiveness of this teaching approach in university degrees in different areas of knowledge, conclusive results regarding academic performance and technical skill acquisition have not yet been provided in architecture and building engineering degrees. These disciplines require specific investigation due to their high visual and practical complexity. In this context, this study aims to evaluate the effectiveness of a video-based hybrid model to improve student performance. Using a mixed-methods design, hybrid teaching was implemented in the construction and installation subject (N = 119) during the 2022/2023 academic year. The results obtained were then analyzed with a holistic approach, including students’ performance, behavior, feelings, and opinions. The results have shown how using the hybrid classroom led to an improvement in student performance rate compared to the previous academic year with traditional teaching methodologies. These findings suggest that hybrid models are a viable solution to reduce high failure rates in technical degrees. Full article

Urban traffic signal control heavily impacts vehicle emissions, yet most reinforcement learning models falsely assume flat terrain, ignoring the energy penalties of uphill stop-and-go driving. This omission creates a structural misalignment between generic, delay-focused rewards and the energetic realities of hilly corridors. In this work, we propose a topography-aware deep reinforcement learning framework that mitigates this hidden ecological cost. Our Context-Specific Reward Design procedure selects, normalizes, and calibrates reward terms based on physical conditions and traffic composition. The controller was trained using a microscopic simulation calibrated from video-derived traffic data, featuring a 3.8-degree uphill approach, 14,800 vehicles over 9 h, and a 20% heavy-vehicle fleet. In the uphill setting, the specialized controller reduced total CO₂ emissions to 256.97 million milligrams, corresponding to 8.6% and 4.7% reductions relative to a pressure-based and a standard deep Q-learning controller, respectively. The proposed method also achieved the lowest mean trip duration of 72.09 s and a queue length of 1.31 vehicles. Welch’s t-tests confirmed that these CO₂, duration, and queue improvements were significant. Overall, treating topography as a foundational design variable is crucial for sustainable urban mobility. Full article

Current 360-degree video streaming systems consider viewport prediction, adaptive bitrate allocation, tile selection, and quality-of-experience (QoE) estimation as independent activities, yielding fragmented pipelines that do not scale well across content type and network conditions and do not scale well to individual users. We propose ImmerseFM-3D, a foundation model that jointly solves all four sub-tasks through a single shared representation. Seven input modalities, namely video frames, network traces, head-motion trajectories, ambisonics audio, depth maps, eye-tracking signals, and CLIP scene semantics, are fused by four-layer cross-modal attention and compressed into a 256-dimensional bottleneck latent via a variational information bottleneck. Four task-specific decoders operate on this shared latent simultaneously. A model-agnostic meta-learning adapter augmented with episodic memory and a hypernetwork personalizes the model from as little as 1 s of user interaction data. An extended branch supports six-degrees-of-freedom volumetric content through spherical harmonic viewport decoding and depth-aware tile importance weighting. Trained and evaluated on the IMMERSE-1M combined dataset (1000 h of 360° and volumetric video, 524 users, and over 50,000 mean opinion scores), ImmerseFM-3D reduces the mean angular viewport error by 34%, lowers the bandwidth violation rate from 8.3% to 3.1%, and achieves a QoE Pearson correlation of 0.891. The personalization adapter reaches 90% of peak performance in 22 s, while zero-shot cross-format transfer attains 72% of full in-domain accuracy. Full article

Social media platforms have become primary communication channels for technical European universities. However, the extent to which global platform algorithms homogenize individual preferences across cultures remains underexplored. Although the current literature offers insights into the topic, none of the works consider the cross-national and multimodal nature of the phenomenon. In the current paper, we introduce the Media Information Processing System (MIPS), a privacy-preserving multimodal deep learning (DL) framework that incorporates large language models (LLMs), computer vision (CV), and knowledge graphs. We analyze data from 15,520 public videos shared by 2359 followers of six top technical universities from Romania, Germany, Italy, and Russia. The results of the study suggest that the degree of homogeneity of the followers’ interest profiles is markedly high. Statistical profiling of the data indicates that the interest profiles of the followers from different countries are positively correlated with a high degree of strength (mean Pearson r = 0.96; p > 0.90). Consensus clustering of the data reveals the existence of stable clusters of themes with high stability scores (>0.75), such as “Human Interaction Dynamics”. The results of the study contradict the traditional theory of regional cultural differentiation. Instead, the results suggest the existence of a new “digital student persona” that is characteristic of the academic lifestyle of students from different countries. Full article

Accurate perception of a diver’s position and orientation by Autonomous Underwater Vehicles (AUVs) is essential for effective human–robot collaboration in underwater environments. However, conventional position and orientation estimation methods that combine deep learning with Perspective-n-Point (PnP) algorithms are primarily designed for rigid objects. In contrast, divers exhibit highly variable postures underwater, with no fixed configuration. To address this limitation, this paper proposes a framework for estimating the six-degree-of-freedom (6-DoF) position and the orientation of a diver. In addition, a novel network architecture, termed “VideoPose5CH,” is proposed. In the proposed framework, temporal sequences of 2D joint coordinates are provided to VideoPose5CH, which then outputs the 3D joint coordinates of the current frame as well as the corresponding refined 2D joint locations. Subsequently, the diver’s 6-DoF position and orientation relative to the camera are further recovered via a PnP algorithm. To mitigate the scarcity of underwater 3D human pose datasets, a land-based 3D human pose dataset augmentation strategy tailored to underwater conditions is further proposed. With this strategy, diver pose estimation accuracy is improved and the robustness of the proposed method across diverse scenarios is enhanced. Experimental results demonstrate that the proposed method can stably estimate the 6-DoF position and orientation of the diver within a distance range of 2.643 m to 11.477 m. The average position errors along the three axes are 7.33 cm, 4.04 cm, and 27.15 cm, respectively, while the average orientation errors are 6.96°, 8.47°, and 2.62°. Full article

This study aimed to explore the feasibility of using OpenCap with a lab-based multi-camera motion capture (MOCAP) system and to evaluate the influence of camera configurations on the trunk and lower-limb kinematic accuracy for athletic movements. Six top-level female football players performed drop jump (DJ) and sidecut (SC) tasks while their motion was recorded synchronously by marker- and video-based cameras. Lower-limb and trunk joint angles, as well as pelvis translations and rotations, obtained with three camera configurations—two, four, and eight cameras—were compared with the marker-based reference. Statistical parametric mapping repeated measures ANOVAs revealed significant differences in kinematic waveforms, decreasing from 16 and 14 degrees of freedom in the two-camera configuration during DJ and SC, respectively, to 9 degrees of freedom in the eight-camera configuration. Improvements in root mean square error were also observed in pelvis anterior–posterior translation and pelvis rotation in both tasks; vertical translations, right ankle dorsiflexion, and inversion in DJ; lumbar bending, and right hip rotation in SC. The result suggested that using a lab-based MOCAP system with more cameras could modestly enhance accuracy and provide several advantages, e.g., broader camera coverage. However, further investigation is needed to ensure the differences are biomechanically meaningful. Full article

An algorithm has been implemented and it is provided in this article as an executable program to extract the five solar cell parameters within the one-diode solar cell model. Boole’s integration rule has been put into practice to integrate the current minus the short-circuit current, yielding a more accurate Co-Content function. Afterwards, the Co-Content function is fitted to a second-degree polynomial in two variables, namely, the voltage and the current minus the short-circuit current, providing six fitting constants. The five solar cells are deduced from these six fitting constants. This algorithm has been implemented in an automatic program that performs the calculations. The program also obtains the standard deviations of the fitting errors, which are used to obtain the standard deviations of the five solar cell parameters. The program reports to the user the results in three text files, from which the user can easily copy-paste the results into softwares like Origin, Word, or Excel. A program to smooth the current voltage curves is also provided. Two videos are also available, one explaining how to profit from this executable program, and the other one how to use the smoothing program. Full article

Excessive use of short-form video platforms such as TikTok has raised growing concerns about digital addiction and its impact on young users’ emotional well-being. This study examines the relationship between continuous TikTok exposure and emotional engagement in young adults aged 20–23 through a multimodal experimental design. The purpose of this research is to determine whether emotional engagement increases, remains stable, or declines during prolonged exposure and to assess the degree of correspondence between facially inferred engagement and physiological arousal. To achieve this, multimodal biometric data were collected using the iMotions platform, integrating galvanic skin response (GSR) sensors and facial expression analysis via Affectiva’s AFFDEX SDK 5.1. Engagement levels were binarized using a logistic transformation, and a binomial test was conducted. GSR analysis, merged with a 50 ms tolerance, revealed no significant differences in skin conductance between engaged and non-engaged states. Findings indicate that although TikTok elicits strong initial emotional engagement, engagement levels significantly decline over time, suggesting habituation and emotional fatigue. The results refine our understanding of how algorithm-driven, short-form content affects users’ affective responses and highlight the limitations of facial metrics as sole indicators of physiological arousal. Implications for theory include advancing multimodal models of emotional engagement that account for divergences between expressivity and autonomic activation. Implications for practice emphasize the need for ethical platform design and improved digital well-being interventions. The originality and value of this study lie in its controlled experimental approach that synchronizes facial and physiological signals, offering objective evidence of the temporal decay of emotional engagement during continuous TikTok use and underscoring the complexity of measuring affect in highly stimulating digital environments. Full article

Background: In ectopic adrenocorticotropic hormone (ACTH) syndrome, locating the responsible lesion is often challenging. Case Presentation: A 68-year-old woman was transferred to Nara Medical University hospital for a detailed investigation of her ACTH-dependent Cushing’s syndrome. Because of hypercortisolism-induced immunosuppression, she subsequently developed severe Nocardia pneumonia and was forced to temporarily depend on noninvasive positive pressure ventilation (NIPPV). Intravenous antifungal agents and antibiotics were administered, resulting in significant symptomatic improvement. Metyrapone was administered to suppress excessive cortisol. Contrast-enhanced magnetic resonance imaging of the pituitary revealed a 4 mm sized poorly enhanced area, and microadenoma was suspected. Although cavernous venous sampling was indispensable prior to trans-spheroidal surgery (TSS), this examination could not be performed because of the presence of deep vein thrombosis. TSS was performed for both diagnostic and therapeutic purposes, but hypercortisolism did not improve. Moreover, immunohistochemical findings of the specimen revealed nonfunctional pituitary tumor. Methods: We re-evaluated the responsible lesion causing ACTH-dependent Cushing’s syndrome. Fluorine-18 fluorodeoxyglucose (FDG) positron emission tomography (PET) revealed weak and abnormal FDG uptake in the right pericardium, but the possibility of nonspecific uptake could not be ruled out. However, gallium-68 1,4,7,10-tetraazacyclododecane-N,N′,N′′,N′′′-tetraacetic-acid-D-Phe¹-Tyr³-octreotide (⁶⁸Ga-DOTATOC)-PET demonstrated the same degree of abnormal uptake; therefore, a functional pulmonary tumor was strongly suspected. Results: Video-Assisted Thoracic Surgery (VATS) was performed, and histopathological findings of the specimen revealed a neuroendocrine tumor with positive ACTH staining. After VATS, ACTH and cortisol levels were normalized. Conclusions: Here, we report a case of ACTH-dependent Cushing’s syndrome caused by a lung neuroendocrine tumor, in which ⁶⁸Ga-DOTATOC PET was helpful in detecting the functional tumors. Full article