Search Results (246)

The aim of this retrospective clinical study was to assess surgical duration and surgical and post-operative complications associated with Video-Assisted Thoracoscopic Surgery (VATS) and lung biopsy in horses with severe Equine Pasture Asthma (EPA) and paired control horses. Twelve horses (6 EPA-affected, 6 control) were sex, age and breed matched. Twenty-four thoracic surgeries were performed. Surgery of each matched pair (EPA-affected and healthy) was performed during asthma exacerbation (summer) and remission (winter). Surgical times were shorter with uncomplicated thoracoscopy (85 min) and significantly longer (p < 0.001) when intra-operative complications necessitated conversion to thoracotomy (156 min). The overall surgical time of EPA-affected horses during asthma exacerbation was significantly longer than control horses at any time point, predicted mean difference of 78 min (p < 0.05). When comparing EPA-affected horses to themselves during asthma exacerbation and remission, surgical times were significantly longer (p < 0.01) with a predicted mean difference of 98 min; this effect of seasonality did not occur amongst control horses. Intra-operative surgical complications (6/24) were evenly divided between EPA and control horses, however, only severe EPA horses in exacerbation were noted to have lung hyperinflation. Post-operative complications: fever, colic, hemothorax, pneumothorax, subcutaneous emphysema, surgical site infection, and/or laminitis occurred in 13/24 surgical procedures (54%). No fatalities resulted from these procedures. Full article

This paper proposes a multi-hop peer-to-peer (P2P) video streaming architecture designed to support dynamic, conversation-aware communication. The primary contribution is a decentralized system built on WebRTC that eliminates reliance on a central media server by employing super node aggregation. In this architecture, video streams from multiple peer nodes are dynamically routed through a group of super nodes, enabling real-time reconfiguration of the network topology in response to conversational changes. To support this dynamic behavior, the system leverages WebRTC data channels for control signaling and overlay restructuring, allowing efficient dissemination of topology updates and coordination messages among peers. A key focus of this study is the rapid and efficient reallocation of network resources immediately following conversational events, ensuring that the streaming overlay remains aligned with ongoing interaction patterns. While the automatic detection of such events is beyond the scope of this work, we assume that external triggers are available to initiate topology updates. To validate the effectiveness of the proposed system, we construct a simulation environment using Docker containers and evaluate its streaming performance under dynamic network conditions. The results demonstrate the system’s applicability to adaptive, naturalistic communication scenarios. Finally, we discuss future directions, including the seamless integration of external trigger sources and enhanced support for flexible, context-sensitive interaction frameworks. Full article

In recent years, passive acoustic monitoring (PAM) technology has significantly contributed to advancements in aquaculture techniques, system iterations, and increased production yields within intelligent feeding systems for Penaeus vannamei. However, current PAM-based intelligent feeding systems do not incorporate environmental factors into the decision process, limiting the improvement of monitoring accuracy in complex environments such as ponds. To establish a connection between environmental factors and the feeding acoustics of P. vannamei, this study utilized PAM technology combined with video analysis to investigate the effects of three key environmental factors—temperature, ammonia nitrogen, and nitrite nitrogen—on the feeding behavioral characteristics of shrimp, with a specific focus on acoustic signals “clicks”. The results demonstrated a significant correlation between the number of clicks and feed consumption in shrimp across different treatments, establishing this stable relationship as a reliable indicator for assessing shrimp feeding status. When water temperature increased from 20 °C to 32 °C, shrimp feed consumption showed an elevation from 0.46 g to 0.95 g per 30 min, with the average number of clicks increasing from 388 to 2947.58 and sound pressure levels rising accordingly. Conversely, ammonia nitrogen at 12 mg/L reduced feed consumption by 0.15 g and decreased click counts by 911.75 pulses compared to controls, while nitrite nitrogen at 40 mg/L similarly suppressed feed consumption by 0.15 g and the average number of clicks by 304.75. A rise in water temperature stimulated shrimp behaviors such as feeding, swimming, and foraging, while elevated concentrations of ammonia nitrogen and nitrite nitrogen significantly inhibited shrimp activity. Redundancy analysis revealed that temperature was the most prominent factor among the three environmental factors influencing shrimp feeding. This study is the first to quantify the specific effects of common environmental factors on the acoustic feeding signals and feeding behavior of P. vannamei using PAM technology. It confirms the feasibility of using PAM technology to assess shrimp feeding conditions under diverse environmental conditions and the necessity of integrating environmental monitoring modules into future feeding systems. This study provides behavioral evidence for the development of precise feeding technologies and the upgrade of intelligent feeding systems for P. vannamei. Full article

Traffic congestion has increased significantly in today’s rapidly urbanizing world, influencing people’s daily lives. Traffic signal control systems (TSCSs) play an important role in alleviating congestion by optimizing traffic light timings and improving road efficiency. Yet traditional TSCSs neglected pedestrians, cyclists, and other non-monitored road users, degrading traffic signal optimization (TSO). Therefore, this framework proposes a multi-object-based traffic flow analysis and intensity estimation model for efficient TSO using Upper Confidence Bound Multi-agent Reinforcement Learning Cubic Spline Fuzzy Logic (UCB-MRL-CSFL). Initially, the real-time traffic videos undergo frame conversion and redundant frame removal, followed by preprocessing. Then, the lanes are detected; further, the objects are detected using Temporal Context You Only Look Once (TC-YOLO). Now, the object counting in each lane is carried out using the Cumulative Vehicle Motion Kalman Filter (CVMKF), followed by queue detection using Vehicle Density Mapping (VDM). Next, the traffic flow is analyzed by Feature Variant Optical Flow (FVOF), followed by traffic intensity estimation. Now, based on the siren flashlight colors, emergency vehicles are separated. Lastly, UCB-MRL-CSFL optimizes the Traffic Signals (TSs) based on the separated emergency vehicle, pedestrian information, and traffic intensity. Therefore, the proposed framework outperforms the other conventional methodologies for TSO by considering pedestrians, cyclists, and so on, with higher computational efficiency (94.45%). Full article

Background/Objectives: The aim of this case series is to evaluate the outcomes and safety of video-assisted mastectomy, illustrating the harmonious collaboration of oncologic and plastic surgery. This novel minimally invasive technique allows immediate prosthetic reconstruction and represents a cost-effective alternative to robotic breast surgery. Methods: Video-assisted, single-port nipple-sparing mastectomies were performed in patients with small to medium-sized breasts, followed by immediate direct-to-implant reconstruction with either prepectoral or dual plane implant placement. The patients’ electronic medical records were analyzed, including demographic characteristics, operative times and histopathology reports. Results: A total of 18 patients underwent successful video-assisted mastectomy, without conversion to traditional open procedure. Fifteen of the operations were risk-reducing mastectomies. Twelve patients had complementary procedures performed concurrently on the previously operated contralateral breast (delayed reconstruction/expander-to-implant exchange). Moreover, three patients benefited from additional minimally invasive techniques during the same surgery (prophylactic laparoscopic hysterectomy). Immediate breast reconstruction with polyurethane or microtextured breast implants up to 450 cc was performed, with satisfactory aesthetic outcomes and no cancer recurrences at 6 to 12 months postoperative follow-up. Early complications included transient hypercapnia, areolar congestion and cellulitis. No skin necrosis or implant-related complications were reported. The most frequently encountered late issues were contour irregularities. Conclusions: Video-assisted mastectomy facilitates the safe removal of proven pathologic or healthy breast tissue with minimal damage to the breast’s skin envelope, facilitating single-stage breast reconstruction. Full article

Background and Objectives: Systemic conversion of stage III–IV non-small-cell lung cancer (NSCLC) to a surgically resectable state with immune checkpoint inhibitors (ICIs) or tyrosine kinase inhibitors (TKIs) creates an emerging cohort of candidates for “salvage” pulmonary resection. No comprehensive evidence synthesis has yet evaluated the feasibility, safety, or oncologic value of this strategy. We aimed to systematically review peri-operative and survival outcomes of salvage lung resection following ICI or TKI therapy. Methods: MEDLINE, Embase, and PubMed were searched (inception–1 May 2025). Studies reporting ≥5 adult NSCLC patients who underwent anatomical lung resection after at least one cycle of ICI or TKI were eligible. Two reviewers screened records, extracted predefined variables, and assessed risk of bias with the Newcastle–Ottawa Scale. Pooled proportions were calculated with a random-effects model. Results: Fourteen observational series (n = 312 patients) met inclusion. Median age was 62 years (range 38–81); 58% were male. Lobectomy (63%) and segmentectomy (21%) were most frequent. Video-assisted/robotic approaches were achieved in 48%. The pooled R0 rate was 93% (95% CI 89–97%); pathologic complete response occurred in 27% (95% CI 19–36%). Major complications (Clavien–Dindo ≥ III) were 11% (95% CI 7–16%), and 30-day mortality was 1.3% (95% CI 0–3%). One-year disease-free and overall survival were 68% and 88%, respectively. Conclusions: Current evidence—albeit heterogeneous—indicates that salvage pulmonary resection after modern systemic conversion therapy is technically feasible, associated with acceptably low morbidity, and yields encouraging short-term oncologic outcomes. Prospective, registry-based studies are needed to define selection criteria and long-term benefit. Full article

The flight capability of drones expands the surveillance area and allows drones to be mobile platforms. Therefore, it is important to estimate the kinematic state of drones. In this paper, the kinematic state of a mini drone in flight is estimated based on the video captured by its camera. A novel frame-to-frame template-matching technique is proposed. The instantaneous velocity of the drone is measured through image-to-position conversion and frame-to-frame template matching using optimal windows. Multiple templates are defined by their corresponding windows in a frame. The size and location of the windows are obtained by minimizing the sum of the least square errors between the piecewise linear regression model and the nonlinear image-to-position conversion function. The displacement between two consecutive frames is obtained via frame-to-frame template matching that minimizes the sum of normalized squared differences. The kinematic state of the drone is estimated by a Kalman filter based on the velocity computed from the displacement. The Kalman filter is augmented to simultaneously estimate the state and velocity bias of the drone. For faster processing, a zero-order hold scheme is adopted to reuse the measurement. In the experiments, two 150 m long roadways were tested; one road is in an urban environment and the other in a suburban environment. A mini drone starts from a hovering state, reaches top speed, and then continues to fly at a nearly constant speed. The drone captures video 10 times on each road from a height of 40 m at a 60-degree camera tilt angle. It will be shown that the proposed method achieves average distance errors at low meter levels after the flight. Full article

The events of 2020 reached a fever pitch with the May 25th murder of George Floyd, but earlier on the same morning, a chance encounter between dogwalker Amy Cooper and birding enthusiast Christian Cooper also laid bare enduring social relations. As video footage of the encounter spread across social media, it sparked both public outrage and discourse regarding Black nature enthusiasts. Employing a historical-interpretive method informed by conversation analysis and guided by “whiteness as property,” I assemble news articles, social media posts, and video footage to analyze the events in Central Park and their aftermath. To unsettle existing paradigms regarding who we imagine are entitled to the great outdoors, I identify potential collaborative partners across scales who can further the goals of education, recruitment, and visibility for Black nature enthusiasts and professionals. I demonstrate how expanding environmental justice to include anti-Black racial violence allows us to recognize that the specter of lynching defies geographic boundaries, diffusing across space and time, occasionally coalescing to defend white privilege and historic racial orders. Full article

Aims: Cue exposure therapy (CET) is a promising treatment approach for cocaine substance use disorder (SUD). CET specifically targets the psychological and physiological responses elicited by drug-related cues, aiming to reduce their motivational impact. To advance understanding of CET for cocaine treatment, this systematic review aims to categorise the range of cocaine cues used in research. Methods: A systematic review of the existing literature with searches conducted on PubMed and Web of Science bibliographic databases with no time constraints in August 2024 (PROSPERO: CRD42024554361). Three reviewers were independently involved in the screening, review and data extraction process, in line with PRISMA guidelines. Data extracted included participant demographics, study design, data on the cocaine cue task, and examples (if provided). Each study was appraised and received a quality score. The secondary outcome was to summarise examples for each category type identified. The data are presented as a narrative synthesis. Results: 3600 articles were identified and screened. 235 articles were included in the analysis. Cues identified included images, paraphernalia, drug-related words, cocaine smell, auditory stimuli presented via audiotapes, video recordings, scripts, and virtual reality environments, often combining multiple modalities. Included studies recruited cocaine-dependent individuals, recreational users, polydrug users, and non-cocaine-using controls. The sample sizes of the studies ranged from a single case study to a study including 1974 participants. Conclusions: This review found that studies employed a wide range of cue categories, but detailed examples were often lacking, limiting replication. The number and combination of cues varied: some studies used only cocaine-related images, while others included images, videos, physical items, and audiotapes. The level of immersion and personalisation also differed considerably. All studies used cocaine-specific cues, most commonly images or representations of cocaine substance, cocaine use or drug paraphernalia, drug preparation items, or conversations of cocaine use and its effects. The overall quality of the included studies was deemed good, with all adhering to standard research norms. While this review highlights the breath of cue types used in the literature, further research should focus on enhancing cue exposure techniques by incorporating more immersive and personalised stimuli, and by providing clearer documentation of cue characteristics to support replication and clinical translation. Full article

Coaching is an important form of professional development for the early childhood education and care (ECEC) workforce. However, educators working in remote contexts do not always have access to this type of support. This paper explores the effectiveness of a virtual (online and telephone) coaching program focusing on the implementation of evidence-informed Conversational Reading strategies in supported playgroups for Aboriginal families in the Northern Territory of Australia. Fourteen Family Educators and Family Liaison Officers across ten Families as First Teachers playgroups in the Northern Territory participated in the coaching program over twelve months. Coaching records, planning documents, participant feedback, and video recordings of participants’ practice were analysed to explore the impact and acceptability of the coaching program. The findings indicate that participation in the cycle of virtual coaching, planning, and reflection supported participants in implementing evidence-informed teaching strategies, offering language-rich experiences to children frequently and with increased fidelity, and engaging with families about their use of these strategies in the home. The model of coaching developed shows promise for wider implementation in ECEC contexts, particularly in remote communities where access to high-quality professional learning and development can be limited. Full article

As recent advancements in large language models enhance reasoning across various domains, educators are increasingly exploring their use in conversation-based tutoring systems. However, since LLMs are black-box models to users and lack human-like problem-solving strategies, users are hardly convinced by the answers provided by LLMs. This lack of trust can potentially undermine the effectiveness of learning in educational scenarios. To address these issues, we introduce a novel approach that integrates multi-agent debates into a lecture video Q&A system, aiming to assist computer science (CS) university students in self-learning by using LLMs to simulate debates between affirmative and negative debaters and a judge to reach a final answer and presenting the entire process to users for review. This approach is expected to lead to better learning outcomes and the improvement of students’ critical thinking. To validate the effectiveness of this approach, we carried out a user study through a prototype system and conducted preliminary experiments based on video lecture learning involving 90 CS students from three universities. The study compared different conditions and demonstrated that students who had access to a combination of video-based Q&A and multi-agent debates performed significantly better on quizzes compared to those who only had access to the video or video-based Q&A. These findings indicate that integrating multi-agent debates with lecture videos can substantially enhance the learning experience, which is also beneficial for the development of students’ high-order thinking abilities in the future. Full article

Historically, the field of discourse marker research has moved from relying on intuition to more and more ecological data, with written, spoken, and now multimodal corpora available to study these pervasive pragmatic devices. For some topics, video is necessary to capture the complexity of interactive phenomena, such as feedback in dialogue. Feedback is the process of communicating engagement, alignment, and affiliation (or lack thereof) to the other speaker, and has attracted a lot of attention recently, from fields such as psycholinguistics, conversation analysis, or second language acquisition. Feedback can be expressed by a variety of verbal/vocal and visual/gestural devices, from questions to head nods and, crucially, discourse or pragmatic markers such as “okay, alright, yeah”. Verbal-vocal and visual-gestural forms often co-occur, which calls for more investigation of their combinations. In this study, we analyze multimodal pragmatic markers of feedback in a corpus of French dialogues, where all feedback devices have previously been categorized into either “alignment” (expression of mutual understanding) or “affiliation” (expression of shared stance). After describing the distribution and forms within each modality taken separately, we will focus on interesting multimodal combinations, such as [negative oui ‘yes’ + head tilt] or [mais oui ‘but yes’ + forward head move], thus showing how the visual modality can affect the semantics of verbal markers. In doing so, we will contribute to defining multimodal pragmatic markers, a status which has so far been restricted to verbal markers and manual gestures, at the expense of other devices in the visual modality. Full article

Due to new treatment options, the number of patients living longer with advanced cancer is rapidly growing. While this is promising, many long-term responders (LTRs) face difficulties adapting to life with cancer due to persistent uncertainty, feeling misunderstood, and insufficient tools to navigate their “new normal”. Using the Person-Based Approach, this study developed and evaluated a website in co-creation with LTRs, healthcare professionals, and service providers, offering evidence-based information and tools for LTRs. We identified the key issues (i.e., living with uncertainty, relationships with close others, mourning losses, and adapting to life with cancer) and established the website’s main goals: acknowledging and normalizing emotions, difficulties, and challenges LTRs face and providing tailored information and practical tools. The prototype was improved through repeated feedback from a user panel (n = 9). In the evaluation phase (n = 43), 68% of participants rated the website’s usability as good or excellent. Interview data indicated that participants experienced recognition through portrait videos and quotes, valued the psycho-education via written text and (animated) videos, and made use of the practical tools (e.g. conversation aid), confirming that the main goals were achieved. Approximately 90% of participants indicated they would recommend the website to other LTRs. The Dutch website—Doorlevenmetkanker (i.e., continuing life with cancer) was officially launched in March 2025 in the Netherlands. Full article

Background: Previous studies have shown that ventilation strategies used in general anesthesia influence perioperative outcomes of video-assisted thoracoscopic surgery (VATS). This study investigated the perioperative effects of non-intubated anesthesia (NIA) versus intubated anesthesia (IA) in patients with early-stage non-small cell lung cancer (NSCLC) undergoing VATS. Methods: This retrospective cohort study analyzed patients who underwent elective VATS for early-stage NSCLC between January 2015 and December 2022. Patients were categorized into the NIA and IA groups based on the ventilation strategies during general anesthesia. Comprehensive outcome data, including intraoperative and postoperative variables, were compared between the two groups. Univariate and multivariate logistic regression models were used to assess the odds ratios for conversion from NIA to IA. Results: A total of 372 patients who received NIA and 1560 who received IA for VATS were eligible for analysis. After propensity score matching, 336 patients were included in each group. In the matched analysis, patients who received NIA demonstrated favorable perioperative outcomes, including reduced opioid consumption, lower postoperative complication rates, and shorter hospital stays, compared to those who received IA. Additionally, patients with a lower baseline oxygen saturation and those who experienced intraoperative pulmonary and cardiovascular adverse events had a higher risk of conversion from NIA to IA. Conclusions: NIA during VATS in patients with early-stage NSCLC was associated with superior perioperative outcomes. Prospective studies are warranted to further evaluate the impact of NIA on perioperative outcomes in this patient population. Full article

Pedestrian panic behavior is a primary cause of overcrowding and stampede accidents in public micro-road network areas with high pedestrian density. However, reliably detecting such behaviors remains challenging due to their inherent complexity, variability, and stochastic nature. Current detection models often rely on single-modality features, which limits their effectiveness in complex and dynamic crowd scenarios. To overcome these limitations, this study proposes a contour-driven multimodal framework that first employs a CNN (CDNet) to estimate density maps and, by analyzing steep contour gradients, automatically delineates a candidate panic zone. Within these potential panic zones, pedestrian trajectories are analyzed through LSTM networks to capture irregular movements, such as counterflow and nonlinear wandering behaviors. Concurrently, semantic recognition based on Transformer models is utilized to identify verbal distress cues extracted through Baidu AI’s real-time speech-to-text conversion. The three embeddings are fused through a lightweight attention-enhanced MLP, enabling end-to-end inference at 40 FPS on a single GPU. To evaluate branch robustness under streaming conditions, the UCF Crowd dataset (150 videos without panic labels) is processed frame-by-frame at 25 FPS solely for density assessment, whereas full panic detection is validated on 30 real Itaewon-Stampede videos and 160 SUMO/Unity simulated emergencies that include explicit panic annotations. The proposed system achieves 91.7% accuracy and 88.2% F1 on the Itaewon set, outperforming all single- or dual-modality baselines and offering a deployable solution for proactive crowd safety monitoring in transport hubs, festivals, and other high-risk venues. Full article