Abstract
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Abstract
In previous work, we introduced an 'invisible' ECG system with electrodes integrated into a toilet seat, capturing signals from the thighs. Here, we present the tOLIet dataset with single-lead thigh ECGs to advance cardiovascular assessment using this novel approach. The dataset includes 149 records from 86 individuals (50 females, 36 males; mean age 31.73 +/- 13.11 years; weight 66.89 +/- 10.70 kg; height 166.82 +/- 6.07 cm). Participants were recruited via the Centro Hospitalar Universit & aacute;rio de Lisboa Central (CHULC). Each recording features four differential signals from toilet-seat electrodes alongside reference data from a hospital-grade 12-lead ECG. Beyond signal collection and quality evaluation, we conducted a gender-specific analysis comparing valid signal percentages relative to Body Mass Index (BMI). This analysis explores anatomical or physiological factors affecting thigh-based ECG acquisition, guiding system design and customization to enhance signal reliability across populations.

Abstract
Background: The increasing complexity of musculoskeletal surgical nursing education requires innovative pedagogical strategies that integrate immersive technologies with structured instructional design to enhance clinical reasoning and theory-practice integration. An: To design and develop a nursing process-structured immersive virtual reality simulation for orthopaedic nursing education and to pilot test its usability and educational appraisal among undergraduate nursing students. Design Pilot mixed-methods study. Method: The simulation, Nurse TechGames, was designed as a three-dimensional orthopaedic inpatient scenario structured sequentially according to the nursing process and incorporating gamification elements to support chnical reasoning. The intervention was implemented using Meta Quest 3 head-mounted displays. Usability was assessed using the System Usability Scale, and educational appraisal was measured uring the Serious Educational Glime in Nursing Appraisal Scale. Open-ended responses were analysed through qualitative content analysis. Participants were monitored during and after the sessions for potential cybersickness symptoma Results: The simulation achieved a mean score of 83.15 on the System Usability Scale, indicating excellent us-ability. The total mean SEGINAS score was 95.58, reflecting a very high pedagogical evaluation across the di mensions of engagement, impact on learning, and content relevance. The qualitative analysis identified eight categories, with no reports of significant cyberzickness symptoms: Perceived Learning Value, Clinical Transfer, Realism and Immersion, Engagement and Motivation, Technical Robustness, Development Potential, Minor Technical Issues, and Time Constraints. Conclusion: The inmersive simulation NurseTechGames demonstrated high usability and strong pedagogical allceptance in musculoskeletal surgical nursing education. Future controlled and longitudinal studies are required to evaluate objective and sustained impact on learning outcomes.

Abstract
Cardiovascular diseases remain the leading cause of morbidity and mortality worldwide. Continuous electrocardiographic (ECG) monitoring is essential for prevention and treatment, but conventional approaches based on the need for some voluntary action often limit comfort and adherence in long-term use. This study investigates the feasibility of acquiring ECG signals from a toilet seat interface embedding dry electrodes in the posterior thighs. A total of 30 hospitalised patients with diverse cardiovascular conditions-including arrhythmias, ischemic heart disease, heart failure, structural abnormalities, and aneurysms-were enrolled. Thigh-acquired ECGs were recorded simultaneously with conventional limb-lead signals and analysed for morphology, heart rate variability (HRV), and disease-related clustering. Thigh-based ECGs demonstrated clear P-QRS-T complexes with preserved morphology, allowing reliable extraction of mean templates and HRV metrics. The comparison between pathological and normal groups showed that post-surgical aortic repair patients had ECG profiles closest to the normal cluster; in contrast, aortic stenosis (AS) appeared most distant. HRV analysis revealed disease-specific autonomic patterns: patients with tricuspid or mitral involvement exhibited higher variability (SDNN up to 140 ms), whereas those with aortic valve disease presented markedly reduced parasympathetic indices (RMSSD and pNN50). Principal component analysis of multi-feature ECG data identified overlapping groups of Acute Coronary Syndrome, Unstable Angina and Ascending Aortic Aneurysm. At the same time, hierarchical clustering confirmed the distinct separation of conditions with severe hemodynamic disruption, such as PS and AS. These findings support the feasibility of unobtrusive thigh-based ECG monitoring via a toilet-seat interface, enabling reliable signal acquisition, HRV analysis, and preliminary patient stratification. This approach may lay the groundwork for future home-based cardiovascular screening and telemedicine applications.

Abstract
The pursuit of bio-inspired locomotion requires control architectures that are computationally efficient, deterministically synchronized, and modular. While centralized controllers offer simplicity, they suffer from wiring complexity. Consequently, distributed systems reduce cabling but introduce challenges in time synchronization due to communication latency. This paper presents an evaluation of a distributed control system for a quadrupedal robot utilizing the Raspberry Pi Pico 2W. An analysis was performed on a decentralized topology in which independent microcontrollers control specific parts of the robot rather than the entire system or a limb, and are synchronized via Micro-ROS over a serial transport layer. Leveraging the RP2350's dual-core symmetric multiprocessing (SMP) capabilities and FreeRTOS, the system maintains a 1 kHz motor control loop on Core 1, employing a 'Hybrid SpinWait' strategy to minimize scheduling jitter. To systematically test the architecture, the system underwent five stress tests: Core Isolation Jitter Analysis, Dual-Board Step Response Latency, Safety Disconnect validation, and Time-based execution. Experimental data reveal a transport-induced bottleneck capping telemetry at $\approx$ 400 Hz, despite internal generation >500 Hz, confirming that the USB-Serial interface is the primary limiter for dynamic gait synchronization, requiring a future transition to UDP-based Ethernet.

Abstract
This special issue showcases state-of-the-art research at the intersection of analytics and retail operations. As the retail landscape becomes increasingly complex - driven by omnichannel strategies, evolving customer expectations, and a surge in data availability - analytics has emerged as a critical enabler of operational efficiency, customer experience, responsiveness, and sustainability and ethics. Collectively, these contributions demonstrate how advanced analytics can support retailers in navigating uncertainty, personalizing services, and scaling up innovation across formats and channels. The articles featured in this issue address a diverse set of decision domains, including warehousing, inventory and assortment planning, and distribution and last-mile delivery. Methodologically, they span descriptive, prescriptive, and hybrid approaches, leveraging tools such as machine learning, stochastic modeling, and dynamic optimization. By grounding models in real-world data and focusing on practical implementation, the issue provides actionable insights for both scholars and practitioners. It also highlights emerging opportunities for future research on behavioral integration, human-machine collaboration, and the ethical dimensions of retail analytics.