Search Results (148)

Background/Objectives: Falls are a major cause of injury in older adults, closely related to declines in muscle strength, balance control, and sensory integration. Although exercise-based fall prevention programs are well supported, evidence on combining such programs with cerebellar transcranial direct-current stimulation (c-tDCS) remains limited. This study investigated the effects of c-tDCS applied before a modified Otago Exercise Program (OEP) on lower-extremity strength, balance, and fall efficacy in older adults. Methods: In this randomized controlled study, twenty-six community-dwelling older adults (median age [IQR]: experimental, 74.00 [10] years; control, 71.00 [10] years) were randomly assigned to either a c-tDCS + exercise group (n = 13) or a sham + exercise group (n = 13). The intervention was administered twice weekly for four weeks. The experimental group received 15 min of c-tDCS followed by 30 min of OEP-based exercise; the control group received sham stimulation under identical conditions. The outcome measures included the Five Times Sit to Stand Test (FTSST), Timed Up and Go (TUG), Balancia-based static balance (velocity average), and Falls Efficacy Scale—Korea (FES-K). Assessments were performed pre- and post-intervention. Results: The experimental group demonstrated significantly greater improvements than the control group (p < 0.05) in the Five Times Sit to Stand Test (r = 0.44) and Timed Up and Go test (r = 0.56). No significant changes were observed in static balance or fall efficacy in either group (p > 0.05). Conclusions: The combined use of c-tDCS and an OEP-based fall prevention exercise program effectively improved lower-extremity strength and dynamic balance in older adults. However, short-term intervention did not influence static balance or fall efficacy. Further studies using longer intervention periods and larger samples are warranted to verify these findings and clarify the mechanisms underlying c-tDCS-enhanced motor performance. Full article

The rapid increase in electric vehicle (EV) ownership necessitates the adaptation of fuel stations to charging infrastructure and the re-evaluation of capacity planning. In the literature, demand forecasting and installation costs are mostly examined; however, station-scale queue analyses supported by field data remain limited. This study aims to examine the integration of EV charging in fuel stations through simulation-based capacity analyses, taking current conditions into account. In this context, a scenario in which one and two dual-hose pumps at a fuel station located on the Turkey–Istanbul E-5 highway side-road is converted into a charging unit has been evaluated using a discrete-event microsimulation model. The analyses were conducted using a discrete event-based microsimulation model. The simulation inputs were derived from field observations and survey data, including the hourly arrival rates of internal combustion engine vehicles (ICEVs), the dwell times at the station, and the charging durations of EVs. In the study, station capacity and service performance were evaluated under scenarios representing EV shares of 5%, 10%, and 20% within the country’s passenger vehicle fleet. Within the scope of the study, the hourly arrival rates and dwell times of ICEVs were determined through field measurements, while EV charging durations were assessed by jointly analyzing field observations and survey data. Simulation results showed that the average number of waiting vehicles increases as the EV share rises; for example, in the 10% EV share scenario, 15.6 (±0.84) EVs were observed waiting within the station, while 34.06 (±1.23) EVs were identified in the 20% scenario. These queues constrict internal circulation within the station, limiting the maneuverability of ICEVs and causing delays in overall service operations. Furthermore, when two dual-hose pumps are replaced with charging units, noticeable increases in waiting times emerge, particularly during the evening peak period. Specifically, 5.88% of ICEVs experienced queuing between 17:00–18:00, rising to 12.33% between 18:00–19:00. In conclusion, this study provides a practical and robust model for short- and medium-term capacity planning and offers data-driven, actionable insights for decision-makers during the transition of fuel stations to EV charging infrastructure. Full article

To enhance the monitoring and conservation efforts for China’s Class II endangered species, specifically the wild giant salamander and its ecosystems, this study addresses the urgent need to counteract the rapid decline of its wild population caused by habitat loss and insufficient surveillance. We present an innovative localization system based on passive Ultra-High-Frequency Radio Frequency Identification (UHF RFID) technology, employing a Double-Transform (D-Tr) methodology that integrates an enhanced 3D LANDMARC algorithm with GAIN generative adversarial networks. This system effectively reconstructs missing Received Signal Strength Indicator (RSSI) data due to environmental barriers by applying a log-distance path loss model. The D-Tr framework simultaneously generates RSSI sequences alongside their first-order differential characteristics, allowing for a comprehensive analysis of spatiotemporal signal relationships. Field tests conducted in the Hubei Xianfeng Zhongjian River Giant Salamander National Nature Reserve reveal that the positioning error consistently remains within 10 cm, with average accuracy improvements of 20.075%, 15.331%, and 12.925% along the X, Y, and Z axes, respectively, compared to traditional time-series models such as long short-term memory (LSTM) and gated recurrent unit (GRU). This system, designed to investigate the behavioral patterns and movement paths of farmed giant salamanders, achieves centimeter-level tracking of their cave-dwelling activities. It provides essential technical support for quantitatively assessing their daily activity patterns, habitat choices, and population trends, thereby promoting a shift from passive oversight to proactive monitoring in the conservation of endangered species. Full article

Background: Lung carcinoma remains the leading cause of cancer-related mortality worldwide, with smoking as the primary risk factor and radon exposure as the second, and the first among non-smokers. The combined effect of tobacco smoke and indoor radon increases disease risk up to 2.5 times, emphasizing the need for prevention and environmental risk assessment. Methods: This study analyzed the incidence of lung carcinoma in Bulgaria during 2013–2022 and examined its association with indoor radon exposure across different regions. Annual data were obtained from the National Statistical Institute and the National Survey of Indoor Radon Concentrations in Residential Buildings (2015–2016). Results: The average annual incidence was 43.5 per 100,000 population, showing a 3.4% annual decline, while the average prevalence was 131.7 per 100,000, decreasing by 1.4% per year. Considerable interregional variation was observed, with incidence ranging from 25.5 to 62.4 per 100,000. A moderate positive correlation was found between lung carcinoma incidence and mean indoor radon concentration, and a stronger to very strong correlation with the proportion of dwellings exceeding 300 Bq/m³ and 200 Bq/m³. Conclusions: These findings indicate a positive association between residential radon exposure and lung cancer morbidity and support maintaining the WHO-recommended reference level of 200 Bq/m³. Full article

Background: To promote exercise adherence, programs should consider not only functional effects but also a comprehensive affective response. This study analyzed the affective responses and functional performance in an age-based Block Strength Training (BST) for older women. Methods: Twenty-eight community-dwelling and Spanish-speaking older women participated in this study (age 68.39 ± 5.95 years) performed a 12-week age-based BST. Preference for and Tolerance of the Intensity of Exercise Questionnaire Spanish version (PRETIE-Q-Sv) was measured before and after each block four times. Additionally, Feeling Scale (FS) and Rating of Perceived Exertion session (sRPE) were measured. Functional performance was assessed before and after the BST using Timed Up and Go, Two-Minutes Step Test, and Five Times Stand-to-Sit Test. Statistical analyses included Cronbach’s alpha (α), Spearman’s (ρ, rho) and Pearson’s (r) coefficients, repeated-measures ANOVA or Friedman, and Paired comparison. The significance level was set at p < 0.05. Results: The PRETIE-Q-Sv showed acceptable internal consistency for both Preference (α = 0.80) and Tolerance (α = 0.78) constructs, with most items showing reliability with their construct scores (ρ ≥ 0.50). Preference remained stable (F (2.39, 64.59) = 2.64, p = 0.070, η²_p = 0.09), and Tolerance increased (F (2.09, 56.35) = 11.84, p < 0.001, η²_p = 0.30)., with overall average scores close to 22. These were not related to FS or sRPE (ρ/r = −0.02 to 0.14). All functional performance tests showed significant improvement after the BST (p < 0.001, d/r_b > 0.80). Conclusions: The PRETIE-Q-Sv adapted well to the language. Preference and Tolerance remained at intermediate levels, with BST programming aligned to individual tendencies and showing no association with FS or sRPE, whereas the increase in Tolerance suggests that BST enhances older women’s ability to persist under uncomfortable effort. Improvements in functional performance support the effectiveness of the BST as a precision exercise dose. 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

This study develops an integrated bi-level operations–assignment model to optimise express service on the Gyeongin Line, a core corridor connecting Seoul and Incheon. The upper level jointly selects express stops and time-of-day headways under coverage constraints—a minimum share of key stations and a maximum inter-stop spacing—while the lower level assigns passengers under user equilibrium using a generalised time function that incorporates in-vehicle time, 0.5× headway wait, walking and transfers, and crowding-sensitive dwell times. Undergrounding and alignment straightening are incorporated into segment run-time functions, enabling the co-design of infrastructure and operations. Using automatic-fare-collection-calibrated origin–destination matrices, seat-occupancy records, and station-area population grids, we evaluate five rail scenarios and one intermodal extension. The results indicate substantial system-wide gains: peak average door-to-door times fall by approximately 44–46% in the AM (07:00–09:00) and 30–38% in the PM (17:30–19:30) for rail-only options, and by up to 55% with the intermodal extension. Kernel density estimation (KDE) and cumulative distribution function (CDF) analyses show a leftward shift and tail compression (median −8.7 min; 90th percentile (P90) −11.2 min; ≤45 min share: 0.0% → 47.2%; ≤60 min: 59.7% → 87.9%). The 45-min isochrone expands by ≈12% (an additional 0.21 million residents), while the 60-min reach newly covers Incheon Jung-gu and Songdo. Backcasting against observed express/local ratios yields deviations near the ±10% band (PM one comparator within and one slightly above), and the Kolmogorov–Smirnov (KS) statistic and Mann–Whitney (MW) test results confirm significant post-implementation shifts. The most cost-effective near-term package combines mixed stopping with modest alignment and capacity upgrades and time-differentiated headways; the intermodal express–transfer scheme offers a feasible long-term upper bound. The methodology is fully transparent through provision of pseudocode, explicit convergence criteria, and all hyperparameter settings. We also report SDG-aligned indicators—traction energy and CO₂-equivalent (CO₂-eq) per passenger-kilometre, and jobs reachable within 45- and 60-min isochrones—providing indicative yet robust evidence consistent with SDG 9, 11, and 13. Full article

This paper solves the stabilization problem of the continuous-time switched systems with partly unstabilizable subsystems subject to actuator saturation and data quantization. The static quantizer is designed by properly restraining the density of the finite partition. The relationship between an ellipse and a polyhedral is established and a suitable expression for the controller suffered by data quantization and actuator saturation is obtained. By defining the attraction domain and the invariant set based on the union or intersection of ellipses, we guarantee the decrement of the Lyapunov function in the optimal case if the state is within a given annular area. On this basis, if average dwell time and activation time of stabilizable subsystems meet some constraints, we derive that every trajectory whose initial state is within the given region will fall into a small ellipsoid and stay in a slightly larger ellipsoid. An illustrative example is given to verify the validity of the theoretical analysis. Full article

The polymer deposition layer (PDL) formed during inductively coupled plasma (ICP) processing significantly limits the figuring accuracy and surface quality of fused silica optics. This study investigates the formation mechanism, composition, and evolution of the PDL under varying dwell times and proposes an innovative dwell time gradient strategy to suppress roughness deterioration. A significant disparity in hardness and elastic modulus between the deposition layer and the substrate is revealed, explaining its preferential removal and protective buffering effect in computer-controlled optical surfacing (CCOS). A hybrid ICP-CCOS polishing process was developed for processing a ϕ100 mm fused silica mirror. The results show that within 33 min, the surface graphic error RMS was significantly reduced from 58.006 nm to 12.111 nm, and within 90 min, the surface roughness was ultra-precisely reduced from Ra 1.719 nm to Ra 0.151 nm. The average processing efficiency was approximately 0.63 cm²/min. Critically, a damage-free, ultra-smooth surface without subsurface damage (SSD) was successfully achieved. This hybrid process enables the simultaneous optimization of figure accuracy and roughness, eliminating the need for iterative figuring cycles. It provides a novel theoretical framework for high-precision figuring and post-ICP polymer removal, advancing the efficient fabrication of high-performance optics. Full article

Background: The efficacy of a single oral dose of Ivermectin as prophylaxis for SARS-CoV-2 is uncertain. This trial sought to evaluate the effectiveness of a single oral low dose of Ivermectin to prevent SARS-CoV-2 infection or reduce symptoms if infection did occur. Methods: Asymptomatic community-dwelling adults were enrolled in this study within 72 h of close contact with a case of SARS-CoV-2. Participants were randomised, stratified by vaccination status and exposure site, to a single oral 200 µg/kg dose of Ivermectin or placebo. The primary outcome was conversion to a positive polymerase chain reaction (PCR) or rapid antigen test (RAT) for SARS-CoV-2 within 14 days of close contact. Secondary outcomes were restricted to those who met the primary outcome. They included the following: days alive free of symptoms in the 14 (DAFS1-14) and 28 (DAFS1-28) days following intervention and days from close contact until a positive PCR or RAT for SARS-CoV-2. Results: A total of 536 participants registered for this trial. Of these, 86 met inclusion criteria and were randomised. 68 adhered to the trial protocol and were included in the analysis. A total of 11/36 (Ivermectin arm) and 11/32 (placebo arm) met the primary outcome. After controlling for age and prior SARS-CoV-2 infection, the estimate (95% confidence interval (95% CI)) of the effect of Ivermectin (compared to placebo) on the absolute value of the proportion of participants converting to a positive PCR or RAT was −0.051 (−0.26 to 0.16), p = 0.63. After controlling for prior SARS-CoV-2 infection, age, body mass index, hypertension and lung disease, the average treatment effect (Ivermectin versus placebo) on DAFS1-14 was 2.5 days (95%CI 1.1 to 4.5), p = 0.036, and for DAFS1-28, was 2.3 days (95% CI 0.7 to 3.3), p = 0.35. The mean (standard deviation) number of days from close contact until a positive PCR or RAT was 5.0 (4.1) days for the Ivermectin group versus 2.6 (0.8) days for the placebo group. After controlling for age and prior SARS-CoV-2 infection, the average treatment effect (95%CI), Ivermectin versus placebo, on days from close contact until a positive PCR or RAT was 2.3 days (95% CI 1.1 to 3.4), p = 0.033. Conclusions: We did not demonstrate that a single oral low dose of Ivermectin administered to asymptomatic adults within 72 h of close contact with a case of SARS-CoV-2 prevents conversion to a positive PCR or RAT. However, the trial had a small sample size and does not exclude a clinically meaningful effect of Ivermectin on conversion to a positive PCR or RAT. Amongst those who did convert to a positive PCR or RAT, the use of Ivermectin significantly lengthened the time from close contact to conversion and increased the number of days alive free of symptoms following intervention. Full article

The thermal energy simulation of residential buildings involves estimating electricity consumption from both household appliances and air conditioning systems, whose use is influenced by the ambient temperatures of each municipality. However, existing mathematical simulation models face limitations in accurately reproducing electricity consumption patterns in homes across different climate types. This study proposes an enhanced CDH method, developed through a new function aimed at improving the accuracy of residential cooling demand estimation by incorporating behavioral and climatic variability. The function introduces the use of adaptive comfort temperature thresholds specific to each climate type and a time-selective activation mechanism that calculates cooling demand only during the hours when ambient temperature exceeds the adaptive threshold. These activation periods are determined analytically using a Fourier-based temperature model. A representative sample of 35 municipalities in Mexico was selected, covering different climate types and domestic electricity rates. The construction characteristics and average energy use habits of typical dwellings were defined using national housing and energy data to support the simulations. The results show that integrating adaptive thresholds into the CDH equations reduces the simulation error to below 10% when compared to actual residential electricity consumption. The proposed model is applicable across all Mexican municipalities, regardless of climate variability. Full article

The berth allocation and crane assignment problem (BACAP) is a key challenge in port logistics, particularly under dynamic and uncertain vessel arrival conditions. To address the limitations of existing methods in handling large-scale and high-disturbance scenarios, this paper proposes a novel optimization framework: Ternary Historical Memory-based Robust Clustered Particle Swarm Optimization (THM-RCPSO). In this method, the initial particle swarm is divided into multiple clusters, each conducting local searches to identify regional optima. These clusters then exchange information to iteratively refine the global best solution. A ternary historical memory mechanism further enhances the optimization by recording and comparing the best solutions from three different strategies, ensuring guidance from historical performance during exploration. Experimental evaluations on 25 dynamic BACAP benchmark instances show that THM-RCPSO achieves the lowest average vessel dwell time in 22 out of 25 cases, with the lowest overall average rank among five tested algorithms. Specifically, it demonstrates significant advantages on large-scale instances with 150 vessels, where it consistently outperforms competing methods such as HRBA, ACO, and GAMCS in both solution quality and robustness. These results confirm THM-RCPSO’s strong capability in solving dynamic and large-scale DBACAP scenarios with high disturbance levels. Full article

To address the challenges of model uncertainty, strong nonlinearities, and controller tuning in high-precision trajectory tracking for hydraulic servo systems, this paper proposes a hierarchical GA-PID-MPC fusion strategy. The architecture integrates three functional layers: a Genetic Algorithm (GA) for online parameter optimization, a Model Predictive Controller (MPC) for future-oriented planning, and a Proportional–Integral–Derivative (PID) controller for fast feedback correction. These modules are dynamically coordinated through an adaptive cost-aware blending mechanism based on real-time performance evaluation. The MPC module operates on a linearized state–space model and performs receding-horizon control with weights and horizon length $\theta =[q,r,T_p]$ tuned by GA. In parallel, the PID controller is enhanced with online gain projection to mitigate nonlinear effects. The blending coefficient $\sigma \left(t\right)$ is adaptively updated to balance predictive accuracy and real-time responsiveness, forming a robust single-loop controller. Rigorous theoretical analysis establishes global input-to-state stability and $H_{\infty }$ performance under average dwell-time constraints. Full article

The stability of a class of quaternion-valued switching neural networks (QVSNNs) with time-varying delays is investigated in this paper. Limited prior research exists on the stability analysis of quaternion-valued neural networks (QVNNs). This paper addresses the stability analysis of quaternion-valued neural networks (QVNNs). With the help of some symmetric matrices with excellent properties, the stability analysis method in this paper is undecomposed. The QVSNN discussed herein evolves with average dwell time. Based on the Lyapunov theoretical framework and Wirtinger-based inequality, QVSNNs under any switching law have global asymptotic stability (GAS) and global exponential stability (GES). The state decay estimation of the system is also given and proved. Finally, the effective and practical applicability of the proposed method is demonstrated by two comprehensive numerical calculations. Full article

Tomato waste (TW) was employed as a sustainable source for the synthesis of fluorescent carbon dots (CDs) via a microwave-assisted hydrothermal carbonization (Mw-HTC) method, aiming at its valorization. Several amines were used as nitrogen additives to enhance the fluorescence quantum yield (QY) of CDs, and a set of reaction conditions, including additive/TW mass ratio (0.04–0.32), dwell time (15–60 min), and temperature (200–230 °C) of the HTC process, were scrutinized. The structural analysis of the tomato waste carbon dots (TWCDs) was undertaken by FTIR and ¹H NMR techniques, revealing their most relevant features. In solid state, transmission electron microscopy (TEM) analysis showed the presence of nearly spherical nanoparticles with an average lateral size of 8.1 nm. Likewise, the topographical assessment by atomic force microscopy (AFM) also indicated particles’ heights between 3 and 10 nm. Their photophysical properties, revealed by UV–Vis, steady-state, and time-resolved fluorescence spectroscopies, are fully discussed. Higher photoluminescent quantum yields (up to 0.08) were attained when the biomass residues were mixed with organic aliphatic amines during the Mw-HTC process. Emission tunability is a characteristic feature of these CDs, which display an intensity average fluorescence lifetime of 8 ns. The new TWCDs demonstrated good antioxidant properties by the ABTS radical cation method (75% inhibition at TWCDs’ concentration of 5 mg/mL), which proved to be related to the dwell time used in the CDs synthesis. Moreover, the synthesized TWCDs suppressed the growth of Escherichia coli and Staphylococcus aureus at concentrations higher than 2000 μg/mL, encouraging future antibacterial applications. Full article