Search Results (2,755)

Minimally Invasive Surgery is often limited by the lack of tactile feedback. Indeed, surgeons have traditionally relied heavily on tactile feedback to estimate tissue stiffness - a critical factor in both diagnostics and treatment. With this in mind we present in this paper a flexible sensor foil, based on polymer optical waveguide. This sensor has been applied for real-time contact force measurement, material stiffness differentiation and surface texture reconstruction. Interrogated by a commercially available optoelectronic device, the sensor foil offers precise and reproducible feedback of contact forces up to 5 N, with a minimal detectable limit of 0.1 N. It also demonstrates distinct optical attenuation responses when indenting silicone samples of varying stiffnesses under controlled displacement. When integrated onto a 3D-printed module resembling an endoscopic camera and manipulated by a robotic arm, the sensor successfully generated spatial stiffness mapsof a phantom. Moreover, by sliding over structures with varying surface textures, the sensor foil was able to reconstruct surface profiles based on the light attenuation responses. The results demonstrate that the presented sensor foil possesses great potential for surgical applications by providing additional haptic information to surgeons. Full article

Background: Neurological disorders are the leading cause of disability, affecting over three billion people worldwide. Amyotrophic lateral sclerosis (ALS) is among the most feared and uniformly fatal neurodegenerative diseases, with no therapy capable of restoring lost function. Methods: We report the first application of therapeutic fever to ALS using Computerized Brain-Guided Intelligent Thermofebrile Therapy (CBIT²). This fully noninvasive treatment, delivered through an FDA-approved computerized platform, digitally reengineers the 1927 Nobel Prize-recognized malarial fever therapy into a modern treatment guided by the Brain–Eyelid Thermoregulatory Tunnel. CBIT² induces therapeutic fever through synchronized hypothalamic feedback, activating heat shock proteins, which are known to restore proteostasis and neuronal function. Case presentation: A 56-year-old woman was diagnosed with progressive ALS at the Mayo Clinic, with electromyography (EMG) demonstrating fibrillation and fasciculation indicative of denervation corroborated by neurological and MRI findings; the patient was informed that she had an expected survival of three to five years. A neurologist from Northwestern University confirmed the diagnosis and thus maintained the patient on FDA-approved ALS drugs (riluzole and edaravone). Her condition rapidly worsened despite pharmacological treatment, and she underwent CBIT², resulting in (i) electrophysiological reversal with complete disappearance of denervation; (ii) biomarker correction, including reductions in neurofilament and homocysteine, IL-10 normalization (previously linked to mortality), and robust HSP70 induction; (iii) restoration of gait, swallowing, respiration, speech, and cognition; (iv) reconstitution of tongue structure; and (v) return to complex motor tasks, including golf, pickleball, and swimming. Discussion: This case provides the first documented evidence that ALS can be reversed through digitally reengineered fever therapy aligned with thermoregulation, which induces heat shock response and upregulates heat shock proteins, resulting in the patient no longer meeting diagnostic criteria for ALS and discontinuation of ALS-specific medications. Beyond ALS, shared protein-misfolding pathology suggests that CBIT² may extend to Alzheimer’s, Parkinson’s, and related disorders. By modernizing this Nobel Prize-recognized therapeutic principle with computerized precision, CBIT² establishes a framework for large-scale clinical trials. A century after fever therapy restored lost brain function and so decisively reversed dementia paralytica such that it earned the 1927 Nobel Prize in Medicine, CBIT² now safely harnesses the therapeutic power of fever through noninvasive, intelligent, brain-guided thermal modulation. Amid a global brain health crisis, fever-based therapies may offer a path to preserve thought, memory, movement, and independence for the more than one-third of humanity currently affected by neurological disorders. Full article

Upper limb disabilities resulting from stroke affect millions worldwide, yet current rehabilitation systems face limitations in portability, cost-effectiveness, and multi-joint integration. This study presents a cable-driven parallel exoskeleton integrating elbow, wrist, and finger assistance into a single portable device. The design strategically separates actuation components, housing all motors in a backpack unit, while limb-mounted modules serve as cable routing guides, achieving seven degrees of freedom within practical constraints of portability (1.2–1.5 kg) and cost-effectiveness (3D-printed components). The device incorporates seven servo motors controlled via Arduino with IMU feedback and PID algorithms. Kinematic and dynamic analyses informed mechanical design, while ARMAX system identification enabled controller optimization achieving 87.96% model fit. Experimental validation with eight healthy participants performing four upper limb exercises demonstrated consistent trends toward reduced activation in four monitored agonist muscles with exoskeleton assistance (21.3% average reduction, p = 0.087), with moderate effect sizes for proximal muscles (Cohen’s d = 0.70–0.79) and significant reductions in brachioradialis during radial/ulnar deviation (23.4%, p = 0.045). These findings provide preliminary evidence of the device’s potential to reduce muscular effort during assisted movements, warranting further clinical validation with patient populations. Full article

Nowadays, mobile applications are essential tools for everyday life, providing users with anytime, anywhere access to up-to-date information, communication, and entertainment. Needless to say, hardware limitations and the diverse needs of different user groups pose a number of design and development challenges. According to recent studies, usability is one of the most revealing among many others. However, few have made the direct effort to provide and discuss what countermeasures can be applied to avoid usability issues in mobile application development. Through a survey of 20 mobile software design and development practitioners, this study aims to fill this research gap. Given the qualitative nature of the data collected, and with the goal of capturing and preserving the intrinsic meanings embedded in the experts’ statements, we adopted in vivo coding. The analysis of the collected material enabled us to develop a novel framework consisting of ten guidelines and three activities with general applications. In addition, it can be noted that active collaboration with users in testing and collecting feedback was often emphasized at each stage of mobile application development. Future research should consider focused action research that evaluates the effectiveness of our recommendations and validates them across different stakeholder groups. In this regard, the development of automated tools to support early detection and mitigation of usability issues during mobile application development could also be considered. Full article

Silicon-Based Physical Unclonable Functions (PUFs) exploit inherent manufacturing variations to produce a unique, random, and ideally unclonable secret key. As electronic devices are decommissioned and sent for End of Life (EOL) recycling, the encrypted critical program information remains within the device. However, conventional PUFs remain vulnerable to invasive attacks and reverse engineering that with sufficient time, resources, and effort can enable an adversary to bypass the security enclave of the system and extract this secret data. Recent research has started to explore techniques to respond to tamper attempts using electromigration (EM) and time-dependent dielectric breakdown (TDDB) to the PUF entropy source, preventing future authentication attempts with well-known semiconductor reliability failure mechanisms. This work presents a Pre-Amplifier Physical Unclonable Function (Pre-Amp PUF) with a self-corruption function designed and manufactured in a 3 nm FinFET technology. This PUF can perform a destructive read operation as an EOL anti-counterfeit measure against recycled and reused electronics. The destructive read utilizes an accelerated aging technique that exploits both Hot Carrier Injection (HCI) and Bias Temperature Instability (BTI) degradations directly at the PUF entropy source bitcell data. This work demonstrates a silicon proven ability to irreversibly corrupt the encryption key, invalidating the PUF key, and blocking future authentication attempts. By utilizing HCI and BTI aging effects rather than physical damage a PUF that can self-corrupt its own key without being detectable with imaging techniques is demonstrated for the first time. A feedback loop enables corruption of up to ~30% of the PUF entropy source, which is approximately 3× more data corruption than the prior state of the art self-corrupting PUF. Our technique reuses on-chip stable (repeatable) PUF bitcells identifying circuitry and thereby minimizes the area overhead to support this differentiated feature. Full article

The early stage of architectural design plays a decisive role in determining building energy performance, yet conventional evaluation is typically deferred to later phases, restricting timely and data-informed feedback. This paper proposes EnergAI, a generative design framework that incorporates energy optimization objectives directly into the scheme generation process through large language models (e.g., GPT-4o, DeepSeek-V3.1-Think, Qwen-Max, and Gemini-2.5 pro). A dedicated dataset, LowEnergy-FormNet, comprising 2160 cases with site parameters, massing descriptors, and simulation outputs, was constructed to model site, form, and energy relationships. The framework encodes building massing into a parametric vector representation and employs hierarchical prompt strategies to establish a closed-loop compatibility with ClimateStudio. Experimental evaluations demonstrate that geometry-oriented and fuzzy-goal prompts achieve average annual reductions of approximately 16–17% in energy use intensity and 3–4% in energy cost compared with human designs, while performance-oriented structured prompts deliver the most reliable improvements, eliminating high-energy outliers and yielding an average EUI-saving rate above 50%. In cross-model comparisons under an identical toolchain, GPT-4o delivered the strongest and most stable optimization, achieving 63.3% mean EUI savings, nearly 13% higher than DeepSeek-V3.1-Think, Qwen-Max, and Gemini-2.5 baselines. These results demonstrate the feasibility and indicate the potential robustness of embedding performance constraints at the generation stage, providing a feasible approach to support proactive, data-informed early design. Full article

This study examined changes in the attitudes of early childhood teachers resulting from their participation in the ONDAS Training Program, a Colombian government strategy designed to strengthen professional skills and dispositions through reflective practice and the integration of research into training. A quantitative, non-experimental longitudinal design with a descriptive-comparative scope was employed. The sample consisted of 56 female teachers evaluated before and after the program. The 12-month intervention combined a three-module virtual course on innovation, research, and academic writing with an editorial stage and expert mentoring. Data were collected through a validated survey on three dimensions: support and resources, research skills, and pedagogical appropriation. Analyses applied descriptive statistics and intra-group non-parametric tests, with the Benjamini–Hochberg adjustment used to control Type I error. The results revealed improvements in research skills, stronger pedagogical appropriation, and more positive evaluations of support and resources. These transformations also included shifts in teachers’ attitudes toward research, greater openness to feedback, and increased confidence in implementing innovative proposals. Findings confirm that early childhood teacher education is a complex process that benefits from reflective, collaborative, and situated approaches, underscoring the program’s role in strengthening professional competences and enhancing teachers’ ability to critically examine practice and adapt to diverse educational contexts. Importantly, these results provide evidence to inform national teacher training strategies in Colombia, offering practical guidance for policymakers and institutions seeking to strengthen research-based, reflective, and contextually responsive professional development programs. Full article

South Africa’s overlapping crises, namely ecological overshoot, energy insecurity, unemployment, and inequality, are not isolated challenges but systemic outcomes of a political economy dependent on growth. This article advances a degrowth by design framework that positions systems thinking as the primary driver of transformative change. By embedding Meadows’ leverage points within canonical archetypes such as Limits to Growth, Shifting the Burden, Success to the Successful, and Tragedy of the Commons the analysis demonstrates how reinforcing and balancing feedbacks perpetuate overshoot and social inequity and how targeted leverage strategies can reorient systems toward sufficiency, equity, and ecological repair. The framework integrates decolonial ethics, Ubuntu-informed relational dignity, pluriversal design perspectives, and legislative anchors such as South Africa’s Climate Change Act and Just Energy Transition. While the contribution is primarily conceptual, it is strengthened by illustrative vignettes, descriptive statistics, and the proposal of measurable indicators including material footprint per capita and energy intensity of wellbeing. Acknowledging the limitations of qualitative mapping and partial empirical application, the article outlines a research agenda centred on empirical validation, comparative municipal case studies, participatory action research, and open indicator repositories. The unique contribution lies in reframing degrowth as a diagnostic and prescriptive leverage strategy that is both contextually grounded and transferable. Rooted in South Africa yet relevant across the Global South, the degrowth compass functions as a normative and analytical benchmark to guide contested transitions toward just and ecologically restorative futures. Full article

Both remote sensing and medical fields benefited a lot from the machine learning methods, originally developed for computer vision and multimedia. We investigate the applicability of the same data mining-based machine learning (ML) techniques for exploring the structure of both Earth observation (EO) and medical image data. Support Vector Machine (SVM) is an explainable active learning tool to discover the semantic relations between the EO image content classes, extending this technique further to medical images of various types. The EO image dataset was acquired by multispectral and radar sensors (WorldView-2, Sentinel-2, TerraSAR-X, Sentinel-1, RADARSAT-2, and Gaofen-3) from four different urban areas. In addition, medical images were acquired by camera, microscope, and computed tomography (CT). The methodology has been tested by several experts, and the semantic classification results were checked by either comparing them with reference data or through the feedback given by these experts in the field. The accuracy of the results amounts to 95% for the satellite images and 85% for the medical images. This study opens the pathway to correlate the information extracted from the EO images (e.g., quality-of-life-related environmental data) with that extracted from medical images (e.g., medical imaging disease phenotypes) to obtain geographically refined results in epidemiology. Full article

Background: Visual, vestibular, proprioceptive and cutaneous sensory information is important for postural control during quiet stance. When the reliability of one source of sensory information used to detect self-motion for postural control is reduced, there may be a reweighting of inputs within and/or across the remaining sensory systems determining self-motion for postural control. Muscle vibration, which creates an illusion of muscle stretch and a compensatory movement to shorten the vibrated muscle, may be used to determine the weighting of muscle spindle Ia proprioception in postural control. The objective of this study was to determine the effect of vision occlusion on triceps surae (TS) Ia proprioceptive weighting in postural control during quiet stance, utilizing an 80 Hz muscle vibration stimulus and a quantitative measure of the body’s anterior to posterior ground center of pressure (COP) response to TS muscle vibration in subjects standing freely. Methods: Subjects (N = 41; mean (standard deviation), 19.6(2.0) years) were examined as they stood with eyes open (EO) or eyes closed (EC). Ground COP was measured during quiet standing with and without bilateral vibration of the TS muscles. Results: The mean backward COP shift induced by TS vibration was significantly greater during the EC condition compared to EO (EC: −4.93(1.62) centimeters; EO: −3.21(1.33) centimeters; p = 6.85 × 10⁻¹⁰; Cohen’s d = 1.29). Thirty-seven subjects increased, and two subjects decreased their vibration-induced COP backward shift in the EC condition compared to EO, although the magnitude of the change varied. Conclusions: The results support the idea that, for most young subjects, there is an increased triceps surae Ia proprioceptive weighting for postural control during EC stance, possibly due to the need for postural control to depend more on non-visual feedback. Full article

Background: The Warburg effect, historically regarded as a hallmark of cancer metabolism, is often interpreted as a universal metabolic feature of tumor cells. However, accumulating experimental evidence challenges this paradigm, revealing a more nuanced and context-dependent metabolic landscape. Methods: In this study, we present a hybrid multiscale model of tumor metabolism that integrates cellular and environmental dynamics to explore the emergence of metabolic phenotypes under varying conditions of stress. Our model combines a reduced yet mechanistically informed description of intracellular metabolism with an agent-based framework that captures spatial and temporal heterogeneity across tumor tissue. Each cell is represented as an autonomous agent whose behavior is shaped by local concentrations of key diffusive species—oxygen, glucose, lactate, and protons—and governed by internal metabolic states, gene expression levels, and environmental feedback. Building on our previous work, we extend existing metabolic models to include the reversible transport of lactate and the regulatory role of acidity in glycolytic flux. Results: Simulations under different environmental perturbations—such as oxygen oscillations, acidic shocks, and glucose deprivation—demonstrate that the Warburg effect is neither universal nor static. Instead, metabolic phenotypes emerge dynamically from the interplay between a cell’s history and its local microenvironment, without requiring genetic alterations. Conclusions: Our findings suggest that tumor metabolic behavior is better understood as a continuum of adaptive states shaped by thermodynamic and enzymatic constraints. This systems-level perspective offers new insights into metabolic plasticity and may inform therapeutic strategies targeting the tumor microenvironment rather than intrinsic cellular properties alone. Full article

Communicable disease surveillance systems are crucial for global health security, particularly in low- and middle-income countries (LMICs) where infectious disease burdens remain high. Despite disease surveillance systems being in place, the evidence on their implementation, challenges, and integration with environmental health remains fragmented. This systematic review assesses the design, implementation, and challenges of these systems across LMICs, with a focus on South Africa and the broader Sub-Saharan African region. Using PRISMA guidelines and the PICOS framework, searches across four databases identified 325 articles published between 2010 and 2025, of which 56 (17%) were included for analysis. Thematic synthesis revealed key trends, disease priorities, and surveillance tools. South Africa contributed the highest number of articles (25%), while Sub-Saharan Africa accounted for 54% overall. COVID-19 was the most frequently studied disease (20%), followed by cholera, typhoid, and measles. The Integrated Disease Surveillance and Response (IDSR) framework appeared in 25% of articles, while District Health Information Systems 2 (DHIS2) was referenced in 11%, reflecting modest adoption of digital platforms. Reported challenges included underreporting, inconsistent case definitions, limited digital infrastructure, and weak feedback mechanisms. Although integration of environmental health was widely recommended, it was marginally implemented. Overall, LMICs surveillance systems remain constrained by operational and structural limitations, underscoring the need for digital investment, environmental indicators integration, and community-based approaches to strengthen epidemic preparedness. Full article

As Canada experiences a growing number of newcomer students with refugee backgrounds, K-12 educators face challenges to meet students’ unique academic, linguistic, and psychosocial needs. This paper examines the role of educational technology (EdTech) to bridge the resource and training gap by enhancing teacher preparedness through an accessible, inclusive, and trauma-informed digital resource. This study presents a qualitative case study methodology to analyze the interactive online manual, Supporting Teachers to Address the Mental Health of Students from War Zones. The research utilizes three data sources: feedback from 110 educators through a questionnaire, observational data from 69 students from two separate pre-service teacher cohorts, and an expert evaluation report conducted by university curriculum specialists. Findings suggest that successful EdTech for refugee-background student initiatives must be trauma-informed, strength-based, culturally responsive, and designed with usability and accessibility in mind. Furthermore, collaboration between K-12 educators, researchers, and developers is vital to ensure that there is alignment of pedagogy and technology. Full article

The increasing complexity of urban environments has exposed the limitations of prescriptive approaches in urban design and planning, highlighting the need for more adaptive, data-informed, and methodologically rigorous processes. Evidence-Based Design and Planning (EBDP) offers a promising response by embedding evidence as a continuous and iterative element throughout design and decision-making. Yet, its adoption in practice remains uneven, constrained by project limitations, data availability, and the challenge of operationalising analytical workflows. This paper addresses these challenges by proposing a transferable framework for EBDP, developed through the review of six realised projects, ranging from public space enhancements to metropolitan masterplans and policy studies, undertaken in both professional practice and academic research. Examined alongside existing theoretical models, these cases revealed recurring patterns that informed the framework. The resulting model consists of four interlinked phases: clarification and evidence-based project definition; integration of an evidence base through analysis and modelling; generation of options synthesising diverse evidence; and evaluations to guide adaptation and decision-making. Rather than a linear or prescriptive sequence of stages, the framework uses iteration and flexible feedback processes anchored by a unifying Hybrid Spatial Model to synthesise evidence, support the generation of design options, and underpin engagement and feedback processes considering project objectives. This paper offers a systematic yet flexible framework for EBDP that can be adapted across scales, project types, and contexts. Full article

This paper investigates the mean square exponential stability (MSES) and $H_{\infty }$ performance analysis of discrete networked control systems (NCSs) based on the FlexRay protocol (FRP) when confronted with randomly occurring cyber attacks (ROCAs). In order to deal with network congestion due to the limited bandwidth, the FRP is used to schedule the information exchange. Besides, a comprehensive attack model is built by simultaneously considering false data injection (FDI) attacks and denial-of-service (DoS) attacks. Then, a mode-dependent output feedback controller is designed on this basis. Furthermore, sufficient conditions for the MSES and $H_{\infty }$ performance of the considered system are derived under the mode-dependent Lyapunov function and average dwell time (ADT) constraints. Subsequently, the controller gains of two modes are determined by solving the recursive linear matrix inequalities (RLMIs) and the FRP-based MSES algorithm is also presented. The simulation verifies that the proposed algorithm maintains the system stability with good robustness and $H_{\infty }$ performance under ROCAs. Full article