Search Results (44,717)

Background: Existing XR simulators for enteral feeding rely mainly on self-reported learning outcomes and procedural checklists. As a result, they offer limited opportunities to capture objective behavioral data or to present dynamic patient reactions. This two-stage pilot study evaluated an XR-based gastrostomy tube-feeding simulator (ESTE-TF) that integrates sensor-derived performance metrics and two biological-reaction presentation modalities (projection mapping and tablet display). Methods: In Experiment 1, nursing students completed pre- and post-experience questionnaires assessing perceived learning across seven domains, alongside sensor-based measurements of feeding-start timing, dosing-rate characteristics, and total procedure time. Experiment 2 employed a tablet-based version with four learning items assessed for students and post-experience evaluations collected from registered nurses. Participants also compared the two XR presentation methods. Results: Students demonstrated perceived learning gains of small-to-large magnitude across both experiments (Experiment 1: d = 0.455–0.974; Experiment 2: d = 0.014–0.886), with wide 95% confidence intervals reflecting the exploratory nature of this pilot work. Sensor-derived data showed greater dosing-rate variability and longer procedure times among students than nurses. Participants reported that projection mapping offered a more embodied experience, whereas tablet displays provided clearer visibility. Conclusions: These findings indicate the feasibility and preliminary educational potential of integrating sensing technologies with XR-based biological-reaction presentation for gastrostomy-feeding training. Given the small samples and non-validated measures, results should be interpreted as exploratory. Future research will refine sensor accuracy, establish standardized performance metrics, and evaluate learning outcomes using validated instruments and controlled study designs. Full article

This article addresses issues related to power supply reliability for electronic security systems (ESSs) during their operational lifetime. ESS are deployed both in enclosed building structures, where environmental conditions are stabilised, and across large open areas exposed to natural environmental conditions, such as transport depots, airports, railway stations, ports, and other similar facilities. Laboratory tests on selected power supply units used in ESSs have been conducted by the authors, as well as a theoretical analysis of the reliability of the power supply process. The reliability analysis of the power supply took into account the reliability of delivering electrical energy with specified parameters to all components forming a system aimed at ensuring the safety of electronic security systems (ESSs). Power supply is essential for the correct operation of all modules, components, devices, and alarm control panels (ACPs) within ESSs. In addition to meeting the basic requirements for the provision of electrical power, the system designer must also give particular consideration to power supply reliability, especially in facilities classified as part of the state critical infrastructure (CI). This issue is particularly significant in the case of Fire Detection and Alarm Systems (FASs), which constitute the most critical safety systems responsible for protecting human life and health. Accordingly, this article discusses selected aspects of power supply for representative electronic security systems (ESSs). The subsequent part of this paper presents operational tests of selected ESS power supply units. A further topic addressed in the article is the definition of models of the operational process of power supply systems and the execution of computer simulations. The analysis of the operational process of ESS power supply units, expressed as models and graphs and supported by computer simulations, enabled the formulation of conclusions regarding reliability. The conclusions drawn from this article may be applied in the design, routine maintenance, and operation of ESSs. Full article

This paper presents the results of the electrical evaluation of a triple-junction solar cell obtained under two different lighting concentration systems: one using a solar simulator with an ellipsoid concentrator and the other using a parabolic concentrator solar furnace, both providing different concentration levels, from 220 to 670 suns inside of a surface of 1 × 1 cm², which correspond to the triple-union solar cell area. A characterization system using an automatized XY table was designed to put the solar cell at different position from the concentration systems, allowing the sample under study to be positioned in the center of the light beam where the concentrated radiative flux is most uniform. It was found that for the solar cell under study, using the solar simulator, the electric efficiency (η) behavior has a trend to reduce when the radiative flux concentration increases from 265 to 670 suns with a (η) values of 32.1% and 22.4%, respectively; while using the solar furnace, the η was around 30%. For the solar furnace, efficiency was around 30% in almost all concentration levels. Full article

This article presents an innovative methodology for assessing the durability of power engineering components under thermo-mechanical fatigue conditions. The approach integrates laboratory low-cycle fatigue tests of alloy specimens at elevated temperatures, measurements of working-medium parameters obtained from operating industrial equipment, and numerical simulations performed using the finite element method. Durability is estimated on the basis of curves describing the relationships between critical parameters such as the Coffin–Manson and Ostergren parameters and the number of cycles to failure. Within the region of the structure identified as the most susceptible to fatigue damage, the orientation of the critical plane is determined with respect to the corresponding criterion functions. This allows the calculated criterion values to be correlated with experimental data, enabling the determination of the incremental durability loss of the component. The proposed methodology is distinguished by its practical applicability and the possibility of incorporating both proprietary fatigue test results and data reported in the literature. Full article

Advances in high-performance computing have expanded the use of computational fluid dynamics (CFD) for reacting-flow analysis; however, simulations involving detailed flame kinetics remain computationally intensive for many practical systems. Efficient modeling approaches are therefore essential for predicting flame behavior in swirl-stabilized combustors. This study examines the influence of main-stage swirl intensity on near-lean blow-off characteristics in a multistage swirl combustor using a hybrid RANS–LES framework. The Stress Blended Eddy Simulation (SBES) model, coupled with a Flamelet Generated Manifold (FGM) combustion formulation, is employed to capture key turbulence–chemistry interactions. Results indicate that reducing swirl intensity suppresses the formation of a swirl-stabilized flame, while excessive swirl negatively affects emission performance. For the baseline (S2) and high-swirl (S3) configurations, flame lift-off height increases by 21.0% and 11.96%, respectively, for every 0.1 reduction in equivalence ratio. The S3 case also demonstrates reduced combustion efficiency, with CO emissions rising by 156.4% relative to S2. Local flame extinction is observed in regions of strong droplet–flame interaction, highlighting enhanced quenching susceptibility under near-blow-off conditions. The present study investigates the flame dynamics in a multi-stage swirl combustor using high-fidelity CFD simulations. This study has yet to be validated through experimental analysis and the results presented in this work are entirely computational. Further experimental validation is necessary to verify the results. Full article

This paper presents a miniaturized tunable bandpass filter chip fabricated using a gallium arsenide (GaAs) technology. In the layout design, a quasi-lumped element is utilized to replace conventional spiral inductors, complemented by on-chip PN-junction varactor diodes and Metal-Insulator-Metal (MIM) capacitors. The integration of a source-load coupling structure and grounded series LC resonators introduces three transmission zeros (TZs), enhancing the frequency selectivity. By independently tuning the coupling capacitance and the grounded series LC resonant structures, the operating frequency of the filter achieves continuous tunability. An equivalent circuit model is established to analyze the filter’s performance. For experimental verification, the proposed filter was fabricated and measured, occupying a compact die area of 1.35 × 1.365 mm². The measured results demonstrate a center frequency tuning range from 5.4 to 6.2 GHz, showing good agreement with simulation and thus validating the proposed miniaturized continuously tunable filter. Full article

Background and Objectives: The management of periprosthetic tibial fractures distal to revision Total Knee Arthroplasty (TKA) presents a biomechanical challenge, often requiring extramedullary locking plates when long stems preclude nailing. While in femoral fractures the gap between the stem and plate is a well-documented stress riser, requiring implant overlap to prevent an inter-implant fracture, this specific biomechanical scenario has not been studied in the tibia, and it remains unclear if the femoral dogma of mandatory overlap applies to the straight, centrically loaded tibial anatomy. This study utilized Finite Element Analysis (FEA) to evaluate stress distribution in the tibial inter-implant gap. Materials and Methods: A comparative FEA was performed using a validated standardized tibia model simulating a healed distal fracture. Two cemented revision TKA constructs (50 mm and 80 mm stems) were modeled. These were paired with medial locking plates of varying lengths (10, 12, and 14 holes) to create different inter-implant distances. Eight distinct configurations, including non-plated controls, were subjected to physiological axial compression and three-point bending. Outcome measures included von Mises stress and total displacement. Results: The analysis revealed no significant stress concentration in the bone within the inter-implant zone across all plated models, regardless of the gap size. Instead, the addition of plates universally reduced bone stress compared to controls, effectively transferring load to the fixation hardware. Peak stresses were consistently observed in the proximal locking screws rather than the bone gap. The longest plates (14 holes) offered superior construct rigidity and stress distribution. Conclusions: Under the conditions evaluated in this preclinical finite element model, the tibia does not exhibit a biomechanical requirement for implant overlap to prevent stress risers. Our findings suggest that extramedullary fixation with the longest available anatomical locking plate represents a biomechanically plausible strategy for these fractures, even if an inter-implant gap remains. Full article

Segmental tunnel linings represent a conventional method commonly employed in tunnel boring machine (TBM) operations. However, this approach presents notable limitations, including handling challenges and the presence of numerous joints prone to leakage. An alternative method involving cast-in-place tunnel lining was experimentally investigated through a scaled mock-up test conducted at approximately 1:4 scale, with a total length of 0.85 m and 2 m lining diameter. In this setup, two reinforced concrete rings were constructed to simulate the surrounding geological conditions and internal formwork. Fiber-reinforced concrete was then pumped into the annular space between the rings, forming a cast-in-place lining with a thickness of 170 mm. To replicate the thrust force exerted by hydraulic actuators of a TBM, a hydrostatic pressure up to 5 MPa was applied from the front side. The experiment demonstrated a linear compaction of fresh concrete by approximately 3%, greater resistance to compaction in the lower section, and a uniformly well-compacted concrete structure throughout the entire volume. Full article

Discrete Body Dynamics (DBD) is a recently developed approach for solving multibody dynamics problems that aims to improve the numerical treatment of systems with joint compliance. Conventional multibody formulations typically rely on kinematic constraints, which can increase numerical complexity and sensitivity, particularly in closed-chain systems. In this work, DBD is presented as a unified framework that combines a new modeling approach with a new numerical solution strategy. Mechanical joints are modeled explicitly using sets of springs and dampers, replacing ideal constraints and transforming the governing equations from a differential-algebraic system into a purely differential one. Based on this modeling framework, the numerical solution avoids global matrix operations and relies on element-wise computations, resulting in linear computational complexity with respect to the number of bodies. The numerical performance of the DBD method is investigated using a set of closed-chain benchmark systems, which are known to be challenging for conventional constraint-based solvers. The analysis examines the influence of joint stiffness, system dynamics, time-step selection, and mechanism topology on numerical stability, energy dissipation, and computational efficiency. The results show that DBD maintains robust and accurate solutions across the examined scenarios and exhibits a well-defined operating region with low numerical dissipation. Across the examined compliant-joint benchmarks, DBD shows the potential for up to three orders of magnitude lower energy drift at comparable simulation-time-to-real-world time (SRT), or up to about one order of magnitude higher SRT at comparable energy drift, relative to ADAMS/View. These findings indicate that DBD is well suited for the simulation of realistic multibody systems with compliant joints, including closed-chain configurations. Full article

Fault detection and diagnosis (FDD) are critical for maintaining efficiency and operational stability of comminution systems. However, conventional methods struggle to capture their complex dynamic behaviour, while data-driven approaches are constrained by limited labelled fault data and the need for interpretable diagnostic models. Progress is further hindered by the scarcity of publicly available industrial datasets. This study presents an explainable FDD framework that integrates unsupervised autoencoder (AE)-based anomaly detection with variance-based global sensitivity analysis (GSA) for quantitative fault diagnosis. A simulated comminution control system was developed to enable controlled validation under realistic operating variability. Multiple AE architectures were trained with hyperparameters optimised using chaotic particle swarm optimisation and evaluated using statistical and reconstruction-based metrics combined with multi-criteria decision analysis. The sparse AE achieved the best performance, with an MSE of 5.6 × 10⁻⁵, F1-score of 0.9930, and accuracy of 0.986 in detecting faults in $P_{80}$ and $P_{20}$. To diagnose detected faults, Sobol’s variance-based GSA was applied to quantify both the main and interaction effects of operational variables on particle size distribution. The results identify circuit feed rate, ball mill critical speed, and the pulp solids fraction supplied to the hydrocyclones as dominant drivers of faults associated with product coarsening, whereas circuit feed rate and ball mill critical speed primarily govern ultrafine particle generation. By integrating deep learning with explainable sensitivity analysis, this study advances transparent and quantitative diagnosis of complex mineral processing systems. Full article

Up to now, most hydrogel-related studies have been devoted to the preparation of drug-containing macromolecular gels via the introduction of polymer matrices, together with the clarification of their assembly mechanisms and biomedical applications. In contrast, studies concerning the design of small-molecule gel systems remain relatively limited. As gel research progresses, drug small-molecule hydrogels have attracted growing interest for formulation development. This study investigated whether designing a small-molecule hydrogel could serve as an effective solubilization approach for sulindac (SUL)—a nonsteroidal anti-inflammatory drug clinically restricted by its poor aqueous solubility. Then, a SUL small-molecule hydrogel was prepared by straightforward mixing of SUL with biologically safe meglumine (MEG) in a minimal volume of deionized water, which exhibited a characteristic three-dimensional network structure and favorable viscoelastic properties. The characterization and simulation results indicated that the hydrogel formation was contingent upon the SUL-MEG miscibility, dissolution-aggregation equilibrium and intermolecular self-assembly. Consequently, the resulting SUL-MEG hydrogel exhibited 546 times higher solubility compared to the pure SUL. Meanwhile, the SUL-MEG hydrogel demonstrated superior release kinetics and supersaturation capacity, characterized by rapid attainment of peak concentrations and sustained supersaturated release. These enhanced performances were attributed to the high-energy state of the hydrogel itself and the molecular complexation between SUL and MEG. In conclusion, this study presents a feasible formulation strategy for overcoming the poor water solubility of insoluble drugs through the development of small-molecule hydrogel formulations. Full article

Critical Thinking (CT) is recognized as a foundational competency for professional readiness, innovation, and ethical reasoning in higher education, enabling students to analyze information, evaluate evidence, and make reasoned decisions in complex environments. The rapid integration of Generative Artificial Intelligence (GenAI) tools, such as large language models, presents new opportunities and risks for CT development. This study conducts a systematic literature review to synthesize empirical evidence on the pedagogical implications and cognitive impact of GenAI on students’ CT. Following PRISMA guidelines, and search terms around GenAI Tools, Critical Thinking And Higher Education, on five major education research databases—Web of Science; Scopus; EBSCOhost (Education Source, ERIC, and APA PsycInfo); and Compendex and Inspec (Elsevier)—63 empirical studies published between January 2023 and April 2025 were analyzed across higher education contexts, disciplines, and intervention designs. Results indicate that GenAI offers notable cognitive affordances, including scaffolding reflective reasoning, promoting self-regulation, and facilitating iterative dialogue and argument evaluation. Pedagogical strategies clustered into four primary integration typologies: AI-based feedback prompts, dialogue simulation and reflection, AI-supported peer review, and critical engagement with AI-generated content. Nearly half of the studies reported statistically significant CT improvements, particularly when GenAI use was guided by structured prompts, reflective activities, and performance-based assessment. However, multiple risks persist, including cognitive offloading, uncritical acceptance of AI outputs, and diminished intellectual autonomy, especially in unguided or surface-level usage. This review highlights the need for intentional pedagogical design, validated CT assessment tools, and longitudinal studies to ensure GenAI acts as a catalyst rather than a substitute for human reasoning. By identifying effective integration strategies and outlining potential pitfalls, this study provides evidence-informed guidance for educators and institutions aiming to responsibly leverage GenAI to strengthen students’ CT skills. Full article

This paper presents a secure 2.4 GHz frequency shift keying (FSK) transmitter front-end with minimal overhead on the data stream using analog obfuscation techniques applied to the modulated waveform. An off-chip true random number generator (TRNG) unit is used to generate the required key for the encryption. Moving away from traditional FSK schemes, which benefit from constant local oscillator (LO) frequency within the channel, the proposed secure FSK scheme shifts the LO frequency in very small steps using an innovative capacitor-bank structure with a calibrated digitally controlled oscillator (DCO). The proposed capacitor bank uses a combination of parallel switches and series capacitors to minimize the impact of the layout parasitics on the minimum capacitor in the bank, thereby reliably creating sub-fF unit capacitors. When combined with the proposed capacitor bank, the cross-coupled CMOS LC voltage-controlled oscillator (VCO) forms a digitally controlled oscillator (DCO). The post-layout simulation results of the DCO reveal that the proposed scheme can achieve a resolution of <20 kHz for the LO frequency shifting while maintaining the phase-noise performance. The reported phase shift allows an equivalent entropy > 6 bits in the implemented analog-inspired secure transmitter front-end. Full article

With the increasing complexity of power grid operations, operator training requires timely feedback and objective assessment. Traditional approaches based on lectures and scripted simulations provide limited personalization and weak explainability. This paper presents AI Instructors, an intelligent simulation training system for power-grid control and dispatching. The system is organized into learning, training, assessment, and analysis modules, and is built around two core technical components: (i) parameterized item generation from rule/knowledge bases using a phrase-enhanced transformer (PET), and (ii) solver-grounded, topology-aware grading with hierarchical feedback for both numeric and free-text responses. A voice interaction module is integrated to simulate telephone-based dispatch orders. We validate the system through a pilot deployment with licensed dispatch operators and scenario experiments on benchmark cases. Compared with a conventional scripted DTS workflow, AI Instructors achieves higher stepwise procedure accuracy (68%→90%), a lower topology-violation rate (32%→11%), and shorter response time (120 s→72 s), while increasing the proportion of parameterized questions and accelerating skill acquisition. These results suggest that combining adaptive sequencing with topology-safe, explainable evaluation can improve training effectiveness and operational safety. Full article

The high-temperature engine nozzle is a critical component of a rocket motor, and its stability and performance are significantly influenced by internal high-temperature gas radiative heat transfer. Due to the non-gray nature of the nozzle medium and the complexity of the Radiative Transfer Equation (RTE), rapid and accurate simulation of radiative heat transfer is crucial for engineering applications. This paper presents a high-efficiency solution coupling the Full-Spectrum Correlated k-Distribution (FSCK) model with the Null-Collision Monte Carlo Method (NCMCM). To address the inherent computational bottleneck of linear traversal in unstructured grids, a hybrid ray-localization model integrating KD-tree and Bounding Volume Hierarchy (BVH) is proposed. This model shifts the search mechanism from element-wise iteration to spatial topological indexing, achieving logarithmic search complexity and significantly mitigating the sensitivity of computational cost to grid scale. Furthermore, a collaborative MPI–OpenMP parallel framework is established to maximize hardware utilization, where an optimized guided scheduling strategy effectively counteracts the stochastic load imbalances encountered in traditional static schemes. Results indicate that the proposed method reduces the total execution time to approximately 1/4 compared to traditional models. Simulations identify the convergent section as the primary radiation zone, where CO₂ contributes less to the radiative source term than H₂O under high-temperature conditions. Full article