Search Results (375)

Background/Objectives: Over the past decade, the popularity of smokeless tobacco products, particularly heated tobacco products (HTPs), has increased among adolescents and young adults. This study aimed to determine the effects of HTPs and conventional cigarettes on oral health and quality of life (QoL). Methods: This stratified cross-sectional study included 90 participants divided into three groups: conventional cigarette smokers (N = 30), HTP users (N = 30), and non-smokers (N = 30). Sociodemographic data and oral-medical status [salivary pH, halitosis, sialometric measurements, Decayed, Missing, Filled Teeth (DMFT) index, and oral lesions] were recorded for all participants. Results: There was no statistically significant difference in salivary pH, unstimulated whole saliva (UWS), or stimulated whole saliva (SWS) among the three groups (p = 0.343, p = 0.982, and p = 0.793, respectively). There was also no statistically significant difference in DMFT index values (p = 0.495) or total QoL (p = 0.856) among the groups. However, there was a statistically significant difference in halitosis among the groups (p < 0.0001), with moderate (40.0%, N = 12) and strong (33.3%, N = 10) halitosis most frequent among HTP users. There was no statistically significant difference in the incidence of pathological oral lesions among the groups (p = 0.112), with 63.3% (N = 19) among conventional cigarette smokers. Conclusions: HTP users exhibited a higher frequency of moderate and strong halitosis, while conventional cigarette smokers more frequently presented with smoker’s melanosis and lesions located on the hard palate. Full article

This study addresses, within the framework of fracture mechanics, the structural analysis of the DEMO (demonstration power plant) divertor—a key component in fusion reactors—subjected to particularly severe loading conditions. A global model of the divertor was developed using Finite Element Method (FEM) analysis through the software ANSYS Workbench 2024, including all structural subcomponents. Thermal and internal pressure load cases were considered. The FEM analysis enabled the identification of critical areas prone to stress concentration. Based on the global results, a submodeling technique was applied to analyze locally critical components with higher resolution. On these submodels, a Linear Elastic Fracture Mechanics (LEFM) analysis was performed using the FRANC3D (v 8.6.2) software. Static semi-elliptical cracks were introduced in various configurations, and the stress intensity factor was evaluated to assess their criticality. Subsequently, an incremental crack growth analysis was conducted to simulate crack propagation based on the local stress field, also accounting for directional variations. Finally, a lifetime analysis was carried out using Paris’ law, estimating the fatigue cycles for an arbitrary crack propagation under the given loading conditions. The entire procedure was repeated for each subcomponent and loading condition, resulting in a broad and detailed understanding of the fracture response of the system. This approach provides crucial insights for the design, inspection, and long-term maintenance of the divertor. Full article

Future fusion power plants like DEMO must be remotely maintained for safety, including breeding blankets (BBs) weighing up to 180 $\mathrm{t}$. The BB vertical transporter (BBVT), a crane-like redundant robot with 7 joints, has been previously designed for handling the five unique BB segments per sector. This includes grasping, preloading and collision-free spatial manipulation of BB segments in a space-constrained environment, necessitating advanced motion planning and real-time control. To achieve this, the challenge of obtaining accurate and performant inverse kinematic (IK) solutions for the redundant BBVT must be addressed. Therefore, a kinematic model is presented, and the redundant IK probelm is solved analytically for task-relevant cases, including derivation and analysis of the Jacobian. The model is verified by comparison with an MSC Adams model. Meanwhile, the analytical IK is found to be 53× to 84× faster than a gradient projection-based numerical solver in Matlab while providing multiple solutions. The IK and Jacobian are applied to create collision-free waypoints, verified in Matlab, for handling each BB segment while minimizing static joint loads in key configurations. A first-order estimate of the total BB handling time for a maintenance of nine days is calculated. These developments support the feasibility of the BBVT robot for the BB maintenance task in DEMO, and underpin future efforts in modelling dynamics and achieving real-time resilient control. Full article

FHIR was designed for transactional interoperability but is less well suited to querying and exploratory analysis because its resource-centric structure distributes meaning across deeply nested resources. To address this limitation, we transformed MIMIC-IV Demo FHIR data into an OWL-compliant knowledge graph by flattening nested elements, normalizing repeating arrays, resolving inter-resource references, and promoting frequently queried attributes to direct properties. We also aligned diagnosis and procedure codes to ICD-9-CM and ICD-10-CM terminologies and developed a schema-grounded NL2SPARQL interface for natural-language querying. Structural validation was performed with SHACL and OWL reasoning. Across a curated evaluation set, NL2SPARQL achieved a mean accuracy exceeding 95% relative to expert-authored queries. These results suggest that ontologizing FHIR can improve analytic accessibility while preserving clinically meaningful assertions. Full article

Plasma Enhancement Gases (PEGs) are a set of gaseous elements studied for converting plasma thermal energy and mitigating the heat load on the plasma-facing components of a tokamak fusion power plant. In particular, PEG separation is part of the Plasma Exhaust Processing System of EU-DEMO. This work addresses issues related to the purification of Deuterium-Tritium fusion fuel, introducing ceramic membranes having a low specific area to process and purify unburned streams throughout the fuel cycle. A commercial microporous mono-channel α-Alumina membrane was considered for the evaluation of its efficacy in separating binary mixtures of H₂ with a PEG (Ar and N₂), D₂, or He. Several tests were carried out, feeding equimolar streams of H₂-Ar, H₂-N₂, D₂-Ar, and He-Ar, and the separation factor (SF) of the aforementioned binary mixtures was experimentally assessed. Finally, based on the results from the experimental campaign, the separation factors of several gas mixtures that had not been experimentally investigated were theoretically calculated and proposed. Full article

This paper presents a Proof of Concept (PoC) for PredictiveMaintenance MCP, an open-source server based on the Model Context Protocol (MCP) that supports machine condition monitoring and predictive maintenance via natural language interaction with Large Language Models (LLMs). The server constrains the LLM within an explicit perimeter of deterministic resources and tools for vibration-based diagnostics, including FFT spectral analysis with peak identification, envelope analysis for rolling element bearing defects, time-domain indicators, vibration severity assessment consistent with ISO standards and semi-supervised anomaly detection on extracted features. Each tool invocation produces structured outputs and artifacts that record inputs, parameters, and results. The LLM acts as an orchestrator that selects resources, configures parameters, invokes tools, and synthesizes conclusions anchored to computed evidence, thereby improving traceability and repeatability compared to unconstrained text-only interaction. End-to-end workflows are demonstrated in a reproducible package with code, examples, and demo data to support community-driven validation and extension toward industrial requirements. The software is archived on Zenodo and the GitHub repository serves as the collaboration hub. Full article

This study investigated energy-efficient renovation strategies for traditional Thai wooden houses through constructing a demo building and computational assessments. The study addresses the challenges posed by climate change and increasing comfort demands, which have led to increasing use of air conditioning in these historically significant structures. A demo building, designed to replicate a traditional Thai house, was constructed, featuring two rooms: one insulated with magnesium-bonded Typha boards and the other uninsulated. The effectiveness of the insulation was evaluated through hygrothermal simulations and real-time temperature and humidity measurements. The frequently occurring problem of missing measurement data was solved by approximately determining unknown variables through iterative adjustment and comparison of simulation results with measured data. The results indicate that the Typha-insulated room maintained a stable indoor climate, with significantly lower energy consumption from air conditioning than the uninsulated room. Since the air conditioning system was insufficiently powerful in the uninsulated room, it is not possible to quantify the energy savings precisely using measurement technology. However, subsequent hygrothermal simulations enabled a comparative assessment of the energy-saving potential of various measures. Depending on insulation measures and manner of room use, savings of 75–80% could be achieved. Such computational and practical studies can contribute to the preservation of historic buildings. Full article

Automated landslide change detection using remote sensing imagery is critical for rapid disaster response. However, landslide change detection using bi-temporal optical imagery is frequently degraded by cross-region domain shifts and by the elongated, anisotropic morphology of landslide boundaries, leading to substantial pseudo-change alarms. To suppress pseudo-changes and improve cross-region robustness, we propose a DEM-assisted topography-conditioned and orientation-adaptive Siamese network (DEMO-Net) that injects topographic inductive bias through terrain-conditioned feature modulation and orientation-adaptive convolutions. Specifically, DEM-derived multi-channel priors are encoded to predict spatially varying FiLM parameters that recalibrate shallow optical features, suppressing spurious changes while preserving discriminative cues. In addition, we introduce an adaptive-oriented attention convolution that leverages a DEM-derived aspect to guide sparse multi-orientation aggregation via shared-kernel transformation, enabling direction-aware receptive-field alignment for elongated and direction-varying landslide structures without costly global attention. Experiments on the GVLM benchmark under a 5-fold site-wise cross-region protocol show that DEMO-Net achieves 85.17% F1 and 74.26% mIoU, outperforming the strongest CNN baseline FC-EF by 5.05% and 7.20%, respectively. These results demonstrate the effectiveness of jointly leveraging terrain-conditioned calibration and physically consistent orientation-aligned feature extraction for robust cross-region landslide change detection. Full article

Shutdown dose rate (SDDR) assessments have been performed for the DEMO tokamak model, including the latest design and environmental configurations. The main objective of this study was to evaluate the shutdown radiation fields and establish dose rate limits to ensure safe personnel access to the Vacuum Vessel (VV) and nearby components. The simulations were based on the DEMO baseline model, further refined with the minor updates of the lower port, equatorial port limiter, and upper port assemblies. The computational approach employed the Monte Carlo particle transport code MCNP for neutron and photon transport calculations, coupled with the activation and decay code FISPACT-II to determine time-dependent decay gamma source terms. The mesh-coupled Rigorous Two-Step (R2Smesh) methodology developed in KIT was applied to achieve spatially resolved decay of photon source distributions and to compute corresponding SDDR 3D maps within the DEMO reactor configuration. The results provide a detailed characterization of the residual radiation environment inside the VV, offering insight into the accumulated activity, shielding performance of different materials, and potential access scenarios for maintenance operations in next-generation fusion devices. Full article

Achieving reliable, grid-scale electricity generation from nuclear fusion, as envisioned by the DEMOnstration Fusion Power Plant (DEMO) and future commercial reactors, requires unprecedented plasma stability and long-term control. This operational goal is fundamentally challenged by, among others, the dynamic nature of the high temperature plasma and the need to monitor high-Z impurities, such as tungsten, which can severely compromise energy confinement, resulting in discharge disruption and damage to internal reactor walls. Real-time Soft X-ray (SXR) diagnostic systems are therefore an integral and critical component of fusion power plant infrastructure, providing essential temporal and spatial resolution data on these fast-evolving phenomena. To address the severe demands imposed by the extreme operating environment of future fusion reactors, such as DEMO (including intense neutron and gamma fluxes), this work details a current stage in the long-term development of an advanced and robust diagnostic system engineered specifically for technological preparation and future application in these high-fluence environments. This paper presents the third generation of the SXR measurement system, GEM3k, based on Gas Electron Multiplier (GEM) technology. This novel diagnostic utilizes a Field Programmable Gate Array (FPGA)-based architecture, specifically designed for the high-rate acquisition of energy- and spatially resolved plasma radiation distributions. The GEM3k design exploits the inherent radiation hardness of GEM detectors, positioning them as robust sensor units for monitoring plasma dynamics and impurity emissions in future fusion environments. The system readout comprises approximately 34,000 individual pixels mapped to nearly 3000 measurement channels in an XYUV coordinate configuration. This layout enables submillimeter spatial resolution simultaneously with a time resolution better than 10 ms. Addressing the engineering challenges of such a complex high-density readout, this work details the comprehensive design of the GEM3k system, focusing on its architecture, electronics, performance estimations, and data distribution strategies. By enabling precise tracking of impurities and fast plasma behavior, the GEM3k system contributes to the stable, high-gain operation required for future fusion reactors. This directly supports the development of sustainable fusion energy and its eventual integration into modern electricity grids. Furthermore, the planned enhancement to a real-time operating mode could pave a way for a next-generation system for direct integration into reactor control loops. Currently in the prototype phase with initial hardware tests completed, the GEM3k design leverages our extensive experience with diagnostics developed for the JET and WEST tokamaks. Full article

Habitat fragmentation is reshaping ecosystems worldwide, reducing connectivity, eroding genetic diversity, and limiting species’ capacity to adapt to rapid environmental change. Conservation management responses to fragmentation generally follow three pathways: restoring habitats to rebuild connectivity, translocating individuals to bolster declining populations, and, more recently, directly managing adaptive genetic variation. We synthesize the ecological and genetic consequences of fragmentation and evaluate these management pathways along a continuum from landscape-scale interventions to genome-level strategies. Habitat restoration can reconnect patches and improve demo-graphic stability, but its genetic outcomes remain uncertain without baseline and post-restoration monitoring. Translocation offers a more immediate means of restoring gene flow but introduces demographic risks, potential impacts on source populations, and uncertainties in establishment and long-term fitness. Emerging genomic technologies now support a third approach: Targeted Genetic Intervention (TGI), which aims to accelerate the spread of beneficial genetic variants or enhance adaptive potential directly. Although promising, TGI faces significant challenges, including polygenic trait architecture, risks to genome-wide diversity, and the need for robust ethical and governance frameworks. Across all pathways, genetic data are essential for prioritizing actions, diagnosing vulnerable species and populations, and restoring the evolutionary potential necessary for long-term persistence in increasingly fragmented landscapes. Full article

Climate change is increasing the frequency and intensity of natural hazards, placing additional stress on critical infrastructure systems. Addressing these challenges requires both robust evaluation frameworks and the inclusion of Nature-Based Solutions (NbSs) alongside conventional protection measures. Building on the RAMSSHEEP concept, originally proposed for risk-driven maintenance, and later further developed and applied in, e.g., previous Horizon projects and COST Action TU1406, this study integrates natural hazard considerations and NbS risk mitigation measures into a comprehensive approach to evaluate the resilience of critical infrastructure. The novel methodology involves a structured expert elicitation process with participants from the Horizon NATURE-DEMO project, to adapt and extend the RAMSSHEEP framework for resilience-oriented transformation. This also includes alignment with established hazard and risk assessment systems to ensure methodological consistency and applicability of the final concept. The resulting framework enables systematic evaluation of infrastructure vulnerability and resilience, explicitly accounting for natural hazards and the contribution of NbSs to risk mitigation. The expected outcome is an objective, repeatable assessment methodology that supports decision-makers in planning, prioritizing, and monitoring resilience-enhancing measures across the infrastructure life cycle. A particular focus of this contribution lies in the methodological approach, ensuring its applicability within interdisciplinary and multi-level decision-making contexts. Full article

Temperature Swing Absorption (TSA) is the primary candidate for the Isotope Rebalancing and Protium Removal (IRPR) system within the envisioned EU-DEMO fusion reactor fuel cycle. TSA separates a mixed hydrogen isotope stream into two product streams using a semi-continuous process. One stream, enriched in heavy isotopes, is used to re-establish the required deuterium-to-tritium fuel ratio. The second, enriched in protium, is stripped off from the fuel cycle to counteract the protium build-up. Separation is achieved by cycling an isotope mixture between two columns filled with metallic absorption materials that have opposite isotope effects of metal hydride formation. The selection of these materials, the operation parameters and the column geometry allow for adjusting the resulting enrichments. To identify suitable operation parameters, a TSA process model is developed which depicts the process dynamics and interactions between the columns. A modified process operation mode is introduced, which enables higher system throughputs and non-cryogenic operation, i.e., operational temperatures between 0 to 130 °C, while reducing the tritium inventory due to shorter cycling times by reduced amplitudes of the temperature swings. Finally, simulations of a TSA system at relevant scale confirm the suitability of TSA technology for the separation task of the EU-DEMO IRPR system. Full article

Accurate fruit detection and counting are fundamental requirements in the development of reliable computer vision applications for yield estimation. This work was conceived to provide farmers with a farmer-friendly approach for automatic grape bunch detection. This study exploits the free demo version of the Roboflow 3.0 platform to train five state-of-the-art computer vision models with RGB images of white and red grape bunches, acquired with a smartphone in the field, and compares their performance. The results were evaluated both quantitatively, in terms of precision, recall, and AP@50 calculated on the validation set, and qualitatively on the test set. The models that achieved the best performances, also in the presence of overlapping clusters, were Roboflow 3.0 Object Detection and YOLOv11, reaching precisions of 86.6% and 88%, respectively, for the detection of white bunches, and of 85.7% and 89.9% for red bunches. This study highlights the possibility of developing highly accurate computer vision models for table grape bunch detection using the Roboflow platform, offering an accessible and user-friendly tool for non-expert users, including farmers. Full article

Haptic feedback is important for narrative virtual reality (VR), yet authoring remains costly and difficult to scale due to device-specific tuning, placement constraints, and the need for semantically congruent timing. We systematically reviewed user studies on haptics in narrative VR to establish an empirical baseline and identify gaps for AI-powered procedural haptics. Following PRISMA 2020, we searched IEEE Xplore, ACM Digital Library, Scopus, Web of Science, PubMed, and PsycINFO (English; human participants; haptics synchronized to narrative events) and performed backward/forward citation chasing (final search: 31 July 2025). We also conducted a parallel scoping scan of grey literature (arXiv and CHI/SIGGRAPH workshops/demos), finalized on 7 September 2025; these records are summarized separately and were not included in the evidence synthesis. Of 493 records screened, 26 full texts were assessed, and 10 studies were included. Quantitatively, presence improved in 6/8 studies that measured it and immersion improved in 3/3; sample sizes ranged 8–108. Across varied modalities and placements, haptics improved presence and immersion and often enhanced affect; validated measures of narrative comprehension were rare. None of the included studies evaluated AI-generated procedural haptics in user studies. We conclude by proposing a structured, three-phase research roadmap designed to bridge this critical gap, moving the field from theoretical promise to the empirical validation of intelligent systems capable of making rich, adaptive, and scalable haptic narratives a reality. Full article