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Positive state reachability for positive linear control systems in continuous time
No full textPositive control systems is the established framework for studying control systems where both the state- and control/input-variables are constrained to remain positive (more accurately, nonnegative). Numerous models of applied interest fall into this setting. However, an interesting and often important perspective is to retain positivity of the state variables, whilst relaxing sign constraints on the input variables. This is a distinct concept to the input/state trajectories associated with positive systems. Here, reachability properties of continuous-time positive linear control systems with positive state are considered. Using tools from linear algebra and positive systems theory, the so-called positive state reachable space is described, and positive state reachability is compared and contrasted to both positive input reachability, as well positive state reachability in discrete time. The theory is illustrated with examples
Nomophobia and Its Association with Sleep Quality, Communication Skills, and Stress Among Nursing Students: A Cross-sectional Study
Get PDFBackground:Nomophobia, the fear of being without mobile phone connectivity, is increasingly prevalent among university students, particularly nursing students who face rigorous academic and clinical demands.Objectives:This study examines the prevalence of nomophobia and its associations with sleep quality, communication skills, and perceived stress in nursing students to inform targeted interventions for their well-being and professional competencies.Methods:A cross-sectional study was conducted from March to May 2025 with 208 undergraduate nursing students from two universities in Kashan, Iran, using stratified sampling. Participants completed validated Persian versions of the Nomophobia Questionnaire (NMP-Q), Pittsburgh Sleep Quality Index (PSQI), Communication Skills Attitude Scale (CSAS), and Stress Index in Nursing Students (SINS). Data were collected via paper-based questionnaires during class and clinical sessions. Descriptive statistics, Pearson correlations, hierarchical regression, and Bayesian regression with a Jeffreys-Zellner-Siow (JZS) prior were used to analyze relationships between nomophobia and study variables, controlling for demographics. The sample size was calculated using G*Power, targeting a minimum of 200 participants for adequate power.Results:The mean NMP-Q score indicated moderate-to-high nomophobia levels. Participants reported poor sleep quality (mean PSQI = 7.91) and elevated stress (mean SINS = 82.38). Nomophobia was positively correlated with poor sleep quality (R = 0.42, P < 0.001) and stress (R = 0.51, P < 0.001), and negatively correlated with positive communication attitudes (R = -0.26, P < 0.001). Hierarchical regression showed that stress (β = 0.39, P < 0.001) and poor sleep quality (β = 0.28, P < 0.001) were the strongest predictors of nomophobia, with positive communication attitudes offering a protective effect (β = -0.16, P = 0.014). Bayesian analysis confirmed these findings (BF10 = 142.6). Daily smartphone use was not significant after controlling for psychosocial variables. The cross-sectional design limits causal inference.Conclusions:Nomophobia is prevalent among nursing students and significantly associated with poor sleep quality and high stress, while positive communication attitudes mitigate its impact. These findings suggest the possibility of interventions targeting stress management, sleep hygiene, and communication skills to reduce nomophobia. Future longitudinal studies should explore causality and evaluate intervention efficacy to support nursing students’ well-being
Guest Editorial of the Special section on Large Language Models for Consumer Health
No full textThe rapid advancement of Large Language Models (LLMs), driven by recent progress in natural language processing and deep learning, has created new opportunities for consumer-focused healthcare. These models are transforming traditional health care by enabling intelligent and personalized services. Applications now include virtual health assistants, intelligent symptom analysis, customized wellness recommendations, and improved interpretation of consumer health data
The Role of Digital Twin in 6G-Based URLLCs: Current Contributions, Research Challenges, and Next Directions
Get PDFSubstantial improvements in the area of ultra reliable and low-latency communication (URLLC) capabilities, as well as possibilities of meeting the rising demand for high-capacity and high-speed connectivity are expected to be achieved with the deployment of next generation 6G wireless communication networks. This thank to the adoption of key technologies such as unmanned aerial vehicles (UAVs), reflective intelligent surfaces (RIS), and mobile edge computing (MEC), which hold the potential to enhance coverage, signal quality, and computational efficiency. However, the integration of these technologies presents new optimization challenges, particularly for ensuring network reliability and maintaining stringent latency requirements. The Digital Twin (DT) paradigm, coupled with artificial intelligence (AI) and deep reinforcement learning (DRL), is emerging as a promising solution, enabling real-time optimization by digitally replicating network devices to support informed decision-making. This paper reviews recent advances in DT-enabled URLLC frameworks, highlights critical challenges, and suggests future research directions for realizing the full potential of 6G networks in supporting next-generation services under URLLCs requirements
Between recolonisation and decolonisation: Documenta 15 and the political decontextualisation of art
Get PDFDocumenta 15, a global exhibition of contemporary art that took place in 2022 in Germany, over a period of 100 days, stands out for two reasons: (1) for the first time documenta was under artistic directorship of an art collective, and (2) it was scandalised for displaying allegedly antisemitic art, mainly blaming Taring Padi (TP), a group of progressive artists and activists from Indonesia. In this paper we argue that the political decontextualisation of TP’s work and the virality of its scapegoating led to the recolonisation of art that reinforced existing power hierarchies and denied space for dialogue and education. In a second part, we change the scene and provide insight into TP’s work in Indonesia, as one of the creative forces leading to the end of the authoritarian Suharto regime in 1998 and evolving in the ensuing reformation era. Only through continuous political and cultural contextualisation can the artwork, and its symbolism, be understood as a way to come to terms with a violent past. In a third part, we discuss the arts, hegemony and decolonisation more generally and in part four possible ways forward and how ‘the scandal’ can actually create productive dialogues and begin an unprecedented process of decolonising art exhibitions and museums
NeFT-Net: N-window extended frequency transformer for rhythmic motion prediction
Get PDFAdvancements in prediction of human motion sequences are critical for enabling online virtual reality (VR) users to dance and move in ways that accurately mirror real-world actions, delivering a more immersive and connected experience. However, latency in networked motion tracking remains a significant challenge, disrupting engagement and necessitating predictive solutions to achieve real-time synchronization of remote motions. To address this issue, we propose a novel approach leveraging a synthetically generated dataset based on supervised foot anchor placement timings for rhythmic motions, ensuring periodicity and reducing prediction errors. Our model integrates a discrete cosine transform (DCT) to encode motion, refine high-frequency components, and smooth motion sequences, mitigating jittery artifacts. Additionally, we introduce a feed-forward attention mechanism designed to learn from N-window pairs of 3D key-point pose histories for precise future motion prediction. Quantitative and qualitative evaluations on the Human3.6M dataset highlight significant improvements in mean per joint position error (MPJPE) metrics, demonstrating the superiority of our technique over state-of-the-art approaches. We further introduce novel result pose visualizations through the use of generative AI methods
What is and what is not 360° video: conceptual definitions for the research field
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Advancing 6G: Survey for Explainable AI on Communications and Network Slicing
Get PDFThe unprecedented advancement of Artificial Intelligence (AI) has positioned Explainable AI (XAI) as a critical enabler in addressing the complexities of next-generation wireless communications. With the evolution of the 6G networks, characterized by ultra-low latency, massive data rates, and intricate network structures, the need for transparency, interpretability, and fairness in AI-driven decision-making has become more urgent than ever. This survey provides a comprehensive review of the current state and future potential of XAI in communications, with a focus on network slicing, a fundamental technology for resource management in 6G. By systematically categorizing XAI methodologies–ranging from modelagnostic to model-specific approaches, and from pre-model to post-model strategies–this paper identifies their unique advantages, limitations, and applications in wireless communications. Moreover, the survey emphasizes the role of XAI in network slicing for vehicular network, highlighting its ability to enhance transparency and reliability in scenarios requiring real-time decision-making and high-stakes operational environments. Real-world use cases are examined to illustrate how XAI-driven systems can improve resource allocation, facilitate fault diagnosis, and meet regulatory requirements for ethical AI deployment. By addressing the inherent challenges of applying XAI in complex, dynamic networks, this survey offers critical insights into the convergence of XAI and 6G technologies. Future research directions, including scalability, real-time applicability, and interdisciplinary integration, are discussed, establishing a foundation for advancing transparent and trustworthy AI in 6G communications systems
Effectiveness of postoperative cephalosporins in reducing urinary tract infections and other parameters following transurethral resection of the prostate: a systematic review and meta-analysis
Get PDFBackgroundTransurethral resection of the prostate (TURP) is the standard surgical procedure for alleviating bladder obstruction caused by benign prostatic hyperplasia (BPH). Although effective, TURP is associated with the risk of urinary tract infection (UTI), which may be reduced by postoperative cephalosporin use.ObjectiveThis study aimed to determine the efficacy of cephalosporins in reducing the risk and complications of UTI following TURP.MethodsThe MEDLINE, Embase, and Cochrane Central databases were searched for randomized controlled trials (RCTs) that compared cephalosporin antibiotics with no intervention in patients undergoing TURP. The outcomes of interest for this systematic review and meta-analysis were UTI, length of stay, adverse effects, and postoperative days. Evaluations were reported as risk ratios (RR) and mean differences (MD) with 95% confidence intervals, using weighted random-effects models.ResultsThe Data Analysis included 668 participants from seven RCTs. Postoperative cephalosporin treatment after TURP significantly reduced the incidence of UTI compared with that in the control group (OR 0.37, 95% CI [0.22, 0.61], P<0.001, I²=30%). However, no significant difference was observed between postoperative cephalosporin use and the length of stay (MD -0.36, 95%CI [-1.13, 0.40], P=0.35, I²=81%), postoperative days (MD 0.20, 95% CI [-0.12, 0.53], P=0.22, I²=74%), and rate of adverse events (OR 0.94, 95% CI [0.58, 1.51], P=0.79; I²=0%).ConclusionCephalosporins effectively reduced the risk of UTI in patients undergoing TURP. Further research in this field is warranted to determine the efficacy of other antibiotics individually and provide a better comparison to implement standardized practices
Simulation Activity in Health Education and Care Sectors: Report from the 2024 National Simulation Survey
No full textThe Association for Simulated Practice in Healthcare (ASPiH) has published its anticipated 2024 Simulation Survey Report, offering a comprehensive overview of simulation activities and practice across the UK and Ireland. The report builds on the foundational 2014 survey and provides critical insights into the evolution, impact, and future direction of simulation in health and social care.The 2024 report gathered responses from 107 survey responses and five focus groups with representatives from NHS Trusts, Higher Education Institutions, Primary Care, and Commercial Organisations. The findings reveal both significant advancements and enduring barriers in the integration of simulation into healthcare education and delivery
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