Search Results (1,221)

In response to the stress commonly experienced by young people in high-pressure daily environments, a music-based stress-relief interactive system was developed by integrating music-assisted care with emotion-sensing technology. The design principles of the system were established through a literature review on stress, music listening, emotion detection, and interactive devices. A prototype was created accordingly and refined through interviews with four experts and eleven users participating in a preliminary experiment. The system is grounded in a four-stage guided imagery and music framework, along with a static activity model focused on relaxation-based stress management. Emotion detection was achieved using a wearable EEG device (NeuroSky’s MindWave Mobile device) and a two-dimensional emotion model, and the emotional states were translated into visual representations using seasonal and weather metaphors. A formal experiment involving 52 users was conducted. The system was evaluated, and its effectiveness confirmed, through user interviews and questionnaire surveys, with statistical analysis conducted using SPSS 26 and AMOS 23. The findings reveal that: (1) integrating emotion sensing with music listening creates a novel and engaging interactive experience; (2) emotional states can be effectively visualized using nature-inspired metaphors, enhancing user immersion and understanding; and (3) the combination of music listening, guided imagery, and real-time emotional feedback successfully promotes emotional relaxation and increases self-awareness. Full article

Introduction: Myotonia is a rare neuromuscular condition characterized by impaired muscle relaxation. In this study, we provide normative values for clinical tests related to myotonia in the Hungarian population and compare them to patients with myotonic dystrophy type 1 (DM1). Methods: Relaxation tests (10 eye openings, tongue extension, and palm openings), handgrip strength, and the nine-hole peg test were conducted on 139 healthy individuals and 31 patients with DM1. Results: We observed non-significant declines in handgrip strength and relaxation tests with age (p < 0.05). Significant differences were found between controls (n:139) and patients with DM1 (n = 31) in all tests (p < 0.05). Sex differences were noted in the healthy population: men (n:68/139) had stronger handgrip (mean of men 42.45 ± 1.15 vs. women 24.3 ± 0.9) and slower relaxation tests (mean of eye openings in men 3.6 ± 0.2 vs. in women 4.2 ± 0.2, tongue extensions in men 3.7 ± 0.2 vs. in women 4.2 ± 0.2, palm openings in men 4 ± 0.2 vs. in women 4.9 ± 0.2 However, these differences were not present among patients with DM1. Discussion: Normal values for relaxation tests across different age groups were established. These results might be useful for further clinical investigations. Our study supports the usage of averages of healthy population instead of age groups of relaxation tests and their clinical relevance in the evaluation of patients with myotonia. Full article

The Pennes bioheat equation is the most widely used model for describing heat transfer in living tissue during thermal exposure. It is derived from the classical Fourier law of heat conduction and assumes energy exchange between blood vessels and surrounding tissues. The literature presents various numerical methods for solving the bioheat equation, with exact solutions developed for different boundary conditions and geometries. However, analytical models based on this framework are rarely reported. This study aims to develop an analytical three-dimensional model using MATHEMATICA software, with subsequent mathematical validation performed through COMSOL simulations, to characterize heat transfer in biological tissues induced by laser irradiation under various therapeutic conditions. The objective is to refine the conventional bioheat equation by introducing three key improvements: (a) incorporating a non-Fourier framework for the Pennes equation, thereby accounting for the relaxation time in thermal response; (b) integrating Dirac functions and the telegraph equation into the bioheat model to simulate localized point heating of diseased tissue; and (c) deriving a closed-form analytical solution for the Pennes equation in both its classical (Fourier-based) and improved (non-Fourier-based) formulations. This paper investigates the nuanced relationship between the relaxation time parameter in the telegraph equation and the thermal relaxation time employed in the bioheat transfer equation. Considering all these aspects, the optimal thermal relaxation time determined for these simulations was 1.16 s, while the investigated thermal exposure time ranged from 0.01 s to 120 s. This study introduces a generalized version of the model, providing a more realistic representation of heat exchange between biological tissue and blood flow by accounting for non-uniform temperature distribution. It is important to note that a reasonable agreement was observed between the two modeling approaches: analytical (MATHEMATICA) and numerical (COMSOL) simulations. As a result, this research paves the way for advancements in laser-based medical treatments and thermal therapies, ultimately contributing to more optimized therapeutic outcomes. Full article

Compressive sensing (CS) is capable of resolving high frequencies from subsampled data. However, it is challenging to apply CS in non-periodic flow fields with multiple frequencies. This study introduces a novel data fusion CS approach aimed at reconstructing temporally resolved flow fields from subsampled particle image velocimetry (PIV) data, integrating constraints derived from a limited number of high-frequency pointwise measurements. The approach combines measurements from particle image velocimetry (PIV), which have high spatial resolution but low temporal resolution, and a few pointwise probes, which have high temporal resolution but low spatial resolution. In the proposed method, proper orthogonal decomposition (POD) is conducted first to the PIV data, thus acquiring spatial modes and low-temporally resolved coefficients. To reconstruct the non-periodic and multiple-frequency coefficients from the PIV data, the traditional CS yields strong high-frequency noise. In this regard, the coefficients obtained from the pointwise measurements using least square (LS) regression can serve as a reciprocal space to suppress the high-frequency noise in the CS reconstruction. Using relaxation factors, the results from LS regression apply the upper and lower boundaries for the CS. By fusing the pointwise measurement and PIV data, the reconstruction performance can be significantly improved. To verify the performance, non-periodic and multiple frequency flow fields in the wake of two cylinders with different diameters are used. Compared to the ground truth, CS and LS reconstruction give an error of about 7% and 13%, respectively. On the other hand, the data fusion CS only has an error of about 2%. The dependency of this method on the number of pointwise probes is also examined. Full article

Huntington’s disease (HD) is a severe and progressive neurodegenerative disease for which therapeutic options have so far been confined to symptomatic treatment. Currently, the diagnosis relies on the signs and symptoms shown by patients; however, by that stage, the psychomotor issues have progressed to a point where reversal of the condition is unattainable. Although numerous clinical trials have been actively investigating therapeutic agents aimed at preventing the onset of disease or slowing down the disease progression, there has been a constant need for reliable biomarkers to assess neurodegeneration, monitor disease progression, and assess the efficacy of treatments accurately. Therefore, to discover the key biomarkers associated with the progression of HD, we employed bioinformatics and machine learning (ML) to create a robust pipeline that integrated differentially expressed gene (DEG) analysis with ML to select potential biomarkers. We performed a meta-analysis to identify DEGs using three Gene Expression Omnibus (GEO) microarray datasets from different platforms related to HD-affected brain tissue, applying both relaxed and strict criteria to identify differentially expressed genes. Subsequently, focusing only on genes identified through the inclusive threshold, we employed 19 diverse ML techniques to explore the common genes that contributed to the top three selected ML algorithms and the shared genes that had an impact on the ML algorithms and were observed in the meta-analysis using the stringent condition were selected. Additionally, a receiver operating characteristic (ROC) analysis was conducted on external datasets to validate the discriminatory power of the identified genes. Based on the results of an inverse variance weighted meta-analysis of the AUCs across both human and mouse cohorts, GABRD and PHACTR1 were identified as the most robust candidates and were selected as key biomarkers for HD. Our comprehensive methodology, which integrates DEG meta-analysis with ML techniques, enabled a systematic prioritization of these biomarkers, providing valuable insights into their biological significance and potential for further validation in clinical research. Full article

Background: Multiple Chemical Sensitivity (MCS) is a complex, disabling condition marked by non-specific symptoms in response to low-level chemical exposures. It often leads to substantial impairments in quality of life, psychological health, and daily functioning. Although non-pharmacological approaches—such as lifestyle and psychological interventions—are widely used, their clinical effectiveness remains unclear. Objective: We aim to evaluate the effectiveness of lifestyle-based approaches in improving clinical and psychosocial outcomes in adults with Multiple Chemical Sensitivity. Methods: A systematic review was conducted in accordance with PRISMA guidelines (PROSPERO: CRD420251013537). Literature searches were carried out in MEDLINE (PubMed), CINAHL, Google Scholar, and ResearchGate between March and April 2025. Eligible studies included adults (≥18 years) with a confirmed diagnosis of MCS and reported outcomes such as perceived stress, anxiety, depressive symptoms, or quality of life. Methodological quality and risk of bias were independently assessed using the PEDro scale, NIH Quality Assessment Tool, CEBMa checklist, and Cochrane RoB 2.0. Results: Twelve studies (N = 378) met the inclusion criteria. Cognitive and behavioral therapies demonstrated the most consistent evidence of efficacy, with reductions in symptom severity, maladaptive cognitive patterns, and functional limitations. Mindfulness-based stress reduction showed favorable outcomes, while other mindfulness-based interventions yielded mixed results. Exposure-based therapies contributed to increased chemical tolerance and reduced avoidance behavior. Electromagnetic and biomedical approaches demonstrated preliminary but limited effectiveness. Aromatherapy was well tolerated and perceived as relaxing, though its clinical impact was modest. Conclusions: Cognitive and behavioral therapies appear to be most effective among lifestyle-based interventions for MCS/IEI. However, study heterogeneity limits the generalizability of findings, underscoring the need for more rigorous research. Full article

Security checks (SCs) at metro stations are regarded as an effective measure to address the heightened security risks associated with high ridership. Introducing SCs without exacerbating congestion requires a thorough understanding of their impact on passenger flow. Most existing studies were conducted where SCs are mandatory and fixed at certain locations. This study presents a method for advising the scale and placement for SCs under a more relaxed security setting. Using agent-based simulation with heterogeneous profiles for both inbound and outbound passenger flow, existing bottlenecks are first identified. By varying different percentages of passengers for SCs and locations to deploy SCs, we observe the influence on existing bottlenecks and suggest a suitable configuration. In our experiments, key bottlenecks are identified before tap-in fare gantries. When deploying SCs near tap-in fare gantries as seen in current practices, a screening percentage of beyond 10% could exacerbate existing bottlenecks and also create new bottlenecks at SC waiting areas. Relocating the SC to a point beyond the fare gantries helps alleviate congestion. This method provides a reference for station managers and transport authorities for balancing security and congestion. Full article

S-nitrosoglutathione (GSNO), a promising S-nitrosothiol, has been recognized for its ability to modulate vascular tone through its vasodilatory, antiplatelet, and antiproliferative effects. However, data on its vasodilatory effects in human vessels remain limited, and its mechanisms of action have yet to be fully elucidated. In this study, we aimed to investigate the vasorelaxant effect of GSNO and its underlying mechanisms, with particular focus on the soluble guanylate cyclase (sGC)/nitric oxide (NO) pathway and potassium channels in isolated human saphenous veins (SVs) obtained from patients undergoing coronary artery bypass grafting (CABG). GSNO (10⁻⁸–10⁻⁴ M) produced concentration-dependent relaxations in SV rings precontracted with phenylephrine. These relaxations were unaffected by NO synthase inhibition with L-NAME (10⁻⁴ M, 30 min) or NO scavenging with PTIO (10⁻⁴ M, 30 min), but were significantly reduced by the sGC inhibitor, ODQ (10⁻⁵ M, 30 min). Inhibition of ATP-sensitive (glibenclamid; 10⁻⁵ M, 30 min.), high-conductance Ca²⁺-activated (charybdotoxin; 10⁻⁷ M, 30 min), small-conductance Ca²⁺-activated (apamin; 10⁻⁶ M, 30 min), or voltage-dependent (4-aminopyridine; 10⁻³ M, 30 min) potassium channels did not alter the maximum relaxant responses to GSNO. Furthermore, pretreatment with GSNO (10⁻⁴ M, 30 min) significantly attenuated both the contractile response and sensitivity to phenylephrine. Collectively, these findings demonstrate that GSNO exerts acute vasorelaxant and modulatory effects in human SV primarily via cGMP-dependent mechanisms, highlighting its potential as a local therapeutic agent for preventing graft spasm in CABG. Full article

Objectives: To investigate whether a Multimodal Rehabilitation Program (MRP) affects the change in visual–spatial abilities, especially attention, information-processing speed, visual–spatial learning, the severity of depression, and strategies for coping with pain in Complex Regional Pain Syndrome (CRPS) participants. Methods: The study was conducted between October 2021 and February 2023, with a 4-week rehabilitation program that included individual physiotherapy, manual and physical therapy, and psychological intervention such as psychoeducation, relaxation, and Graded Motor Imagery therapy. Twenty participants with CRPS and twenty healthy participants, forming a control group, were enlisted. The study was a 2-arm parallel: a CRPS group with MRP intervention and a healthy control group matched to the CRPS group according to demographic variables. Before and after, the MRP participants in the CRPS group were assessed for visual–spatial learning, attention abilities, severity of depression, and pain-coping strategy. The healthy control group underwent the same assessment without intervention before two measurements. The primary outcome measure was Reproduction on Rey–Osterrieth’s Complex Figure Test assessing visual–spatial learning. Results: In the post-test compared to the pre-test, the participants with CRPS obtained a significantly high score in visual–spatial learning (p < 0.01) and visual information-processing speed (p = 0.01). They made significantly fewer omission mistakes in visual working memory (p = 0.01). After the MRP compared to the pre-test, the CRPS participants indicated a decrease in the severity of depression (p = 0.04) and used a task-oriented strategy for coping with pain more often than before the rehabilitation program (p = 0.02). Conclusions: After a 4-week MRP, the following outcomes were obtained: an increase in visual–spatial learning, visual information-processing speed, a decrease in severity of depression, and a change in the pain-coping strategies—which became more adaptive. Full article

Background/Objectives: Tegoprazan (TPZ) is a potassium-competitive acid blocker (P-CAB) used to treat conditions such as gastroesophageal reflux disease, peptic ulcer, and Helicobacter pylori infection. It exists in three solid forms: amorphous, Polymorph A, and Polymorph B. This study investigates the molecular basis of polymorph selection, focusing on conformational bias and solvent-mediated phase transformations (SMPTs). Methods: The conformational energy landscapes of two TPZ tautomers were constructed using relaxed torsion scans with the OPLS4 force field and validated by nuclear Overhauser effect (NOE)-based nuclear magnetic resonance (NMR). Hydrogen-bonded dimers were analyzed using DFT-D. Powder X-ray diffraction (PXRD), differential scanning calorimetry (DSC), solubility, and slurry tests were conducted using methanol, acetone, and water. Kinetic profiles were modeled with the Kolmogorov–Johnson–Mehl–Avrami (KJMA) equation. Results: Polymorph A was thermodynamically stable across all analyses. Both amorphous TPZ and Polymorph B converted to A in a solvent-dependent manner. Methanol induced direct A formation, while acetone showed a B → A transition. Crystallization was guided by solution conformers and hydrogen bonding. Conclusions: TPZ polymorph selection is governed by solution-phase conformational preferences, tautomerism, and solvent-mediated hydrogen bonding. DFT-D and NMR analyses showed that protic solvents favor the direct crystallization of stable Polymorph A, while aprotic solvents promote the transient formation of metastable Polymorph B. Elevated temperatures and humidity accelerate polymorphic transitions. This crystal structure prediction (CSP)-independent strategy offers a practical framework for rational polymorph control and the mitigation of disappearing polymorph risks in tautomeric drugs. Full article

Background: Sarcopenia is a progressive muscle disease that compromises mobility and quality of life in older adults. Although dual-energy X-ray absorptiometry (DXA) is the standard for assessing Appendicular Lean Mass Index (ALMI), it is costly and often inaccessible. This study aims to develop machine learning models using anthropometric measurements to predict low ALMI for the diagnosis of sarcopenia. Methods: A cross-sectional study was conducted on 183 Mexican adults (67.2% women and 32.8% men, ≥60 years old). ALMI was measured using DXA, and anthropometric data were collected following the International Society for the Advancement of Kinanthropometry (ISAK) protocols. Predictive models were developed using Logistic Regression (LR), Decision Trees (DTs), Random Forests (RFs), Artificial Neural Networks (ANNs), and LASSO regression. The dataset was split into training (70%) and testing (30%) sets. Model performance was evaluated using classification performance metrics and the area under the ROC curve (AUC). Results: ALMI indicated strong correlations with BMI, corrected calf girth, and arm relaxed girth. Among models, DT achieved the best performance in females (AUC = 0.84), and ANN indicated the highest AUC in males (0.92). Regarding the prediction of low ALMI, specificity values were highest in DT for females (100%), while RF performed best in males (92%). The key predictive variables varied depending on sex, with BMI and calf girth being the most relevant for females and arm girth for males. Conclusions: Anthropometry combined with machine learning provides an accurate, low-cost approach for identifying low ALMI in older adults. This method could facilitate sarcopenia screening in clinical settings with limited access to advanced diagnostic tools. Full article

This study systematically investigates the effects of trap concentration on self-heating and terahertz (THz) responses in GaN HEMTs using Sentaurus TCAD. Traps, inherently unavoidable in semiconductors, can be strategically introduced to engineer specific energy levels that establish competitive dynamics between the electron momentum relaxation time and the carrier lifetime. A simulation-based exploration of this mechanism provides significant scientific value for enhancing device performance through self-heating mitigation and THz response optimization. An AlGaN/GaN heterojunction HEMT model was established, with trap concentrations ranging from 0 to $5\times {10}^{17} {\mathrm{c}\mathrm{m}}^{-3}$. The analysis reveals that traps significantly enhance channel current (achieving 3× gain at $1\times 10^{17} {\mathrm{c}\mathrm{m}}^{-3}$) via new energy levels that prolong carrier lifetime. However, elevated trap concentrations (>$1\times {10}^{16} {\mathrm{c}\mathrm{m}}^{-3}$) exacerbate self-heating-induced current collapse, reducing the min-to-max current ratio to 0.9158. In THz response characterization, devices exhibit a distinct DC component (${\mathrm{U}}_{\mathrm{d}\mathrm{c}}$) under non-resonant detection ($\mathsf{\omega }\mathsf{\tau }\ll 1$). At a trap concentration of $1\times {10}^{15} {\mathrm{c}\mathrm{m}}^{-3}$, ${\mathrm{U}}_{\mathrm{d}\mathrm{c}}$ peaks at $0.12 \mathrm{V}$ when ${\mathrm{V}}_{\mathrm{g}}\mathrm{D}\mathrm{C}=-7.8 \mathrm{V}$. Compared to trap-free devices, a maximum response attenuation of 64.89% occurs at ${\mathrm{V}}_{\mathrm{g}}\mathrm{D}\mathrm{C}=-4.9 \mathrm{V}$. Furthermore, ${\mathrm{U}}_{\mathrm{d}\mathrm{c}}$ demonstrates non-monotonic behavior with concentration, showing local maxima at $4\times {10}^{15} {\mathrm{c}\mathrm{m}}^{-3}$ and $7\times {10}^{15} {\mathrm{c}\mathrm{m}}^{-3}$, attributed to plasma wave damping and temperature-gradient-induced electric field variations. This research establishes trap engineering guidelines for GaN HEMTs: a concentration of $4\times {10}^{15} {\mathrm{c}\mathrm{m}}^{-3}$ optimally enhances conductivity while minimizing adverse impacts on both self-heating and the THz response, making it particularly suitable for high-sensitivity terahertz detectors. Full article

Monolayer (ML) molybdenum disulfide (MoS₂) is a typical valleytronic material which has important applications in, for example, polarization optics and information technology. In this study, we examine the effect of continuous wave (CW) laser pumping on the basic optoelectronic properties of ML MoS₂ placed on a sapphire substrate, where the pump photon energy is larger than the bandgap of ML MoS₂. The pump laser source is provided by a compact semiconductor laser with a 445 nm wavelength. Through the measurement of THz time-domain spectroscopy, we obtain the complex optical conductivity for ML MoS₂, which are found to be fitted exceptionally well with the Drude–Smith formula. Therefore, we expect that the reduction in conductivity in ML MoS₂ is mainly due to the effect of electronic backscattering or localization in the presence of the substrate. Meanwhile, one can optically determine the key electronic parameters of ML MoS₂, such as the electron density n_e, the intra-band electronic relaxation time τ, and the photon-induced electronic localization factor c. The dependence of these parameters upon CW laser pump intensity is examined here at room temperature. We find that 445 nm CW laser pumping results in the larger n_e, shorter τ, and stronger c in ML MoS₂ indicating that laser excitation has a significant impact on the optoelectronic properties of ML MoS₂. The origin of the effects obtained is analyzed on the basis of solid-state optics. This study provides a unique and tractable technique for investigating photo-excited carriers in ML MoS₂. Full article

(1) Background: Optimizing infill density in 3D-printed PLA parts reduces material usage, cost, and waste. This study examines mechanical behavior in the initial and hydration stages. The findings provide valuable data for numerical simulations and engineering applications in additive manufacturing. (2) Methods: PLA specimens were printed with infill densities of 100%, 75%, and 25%. Mechanical tests, including tensile and compression tests, and one-hour stress-relaxation at 2% strain were conducted. The digital image correlation method was used to obtain the strain fields on the samples’ surface under tensile loading. Mechanical properties, including the elastic modulus, strength values, and Poisson’s ratio, were assessed. Hydrolytic degradation effects over one month were also evaluated. (3) Results: Lowering the PLA infill density reduced the ultimate tensile strength (from 60.04 ± 2.24 MPa to 26.24 ± 0.77 MPa), Young’s modulus (from 2645.05 ± 204.15 MPa to 1245.41 ± 83.79 MPa), compressive strength (from 26.59 ± 0.80 MPa to 21.83 ± 1.01 MPa), and Poisson’s ratio (from 0.32 to 0.30). A 40% mass reduction (form 100% to 25% infill density) resulted in a 56% decrease in tensile strength and a 53% decrease in Young’s modulus. A 31% mass reduction was observed for compression samples. Stress relaxation decreased significantly from 100% to 75% density, with further reductions having minimal impact. Hydrated samples showed no mechanical changes compared to baseline specimens. (4) Conclusions: Optimizing infill density in 3D-printed PLA parts helps to balance mechanical performance with material efficiency. The best mechanical properties are typically achieved with an infill density of 100%, but results show that decreasing the mass of the part by a reduction in infill density from 75% to 25% does not significantly affect the ability to transfer tensile and compression loads. PLA’s biodegradability makes it a viable alternative to stable polymers. By minimizing material waste and enabling the efficient use of resources, additive manufacturing aligns with the principles of a closed-loop economy, supporting sustainable development. Full article

In midcourse guidance, strong constraints and dual-channel control coupling pose major challenges for trajectory optimization. To address this, this paper proposes an optimal guidance method based on terminal relaxation and range convex programming. The study first derived a range-domain dynamics model with the angle of attack and bank angle as dual control inputs, augmented with path constraints including heat flux limitations, to formulate the midcourse guidance optimization problem. A terminal relaxation strategy was then proposed to mitigate numerical infeasibility induced by rigid terminal constraints, thereby guaranteeing the solvability of successive subproblems. Through the integration of affine variable transformations and successive linearization techniques, the original nonconvex problem was systematically converted into a second-order cone programming (SOCP) formulation, with theoretical equivalence between the relaxed and original problems established under well-justified assumptions. Furthermore, a heuristic initial trajectory generation scheme was devised, and the solution was obtained via a sequential convex programming (SCP) algorithm. Numerical simulation results demonstrated that the proposed method effectively satisfies strict path constraints, successfully generates feasible midcourse guidance trajectories, and exhibits strong computational efficiency and robustness. Additionally, a systematic comparison was conducted to evaluate the impact of different interpolation methods and discretization point quantities on algorithm performance. Full article