Search Results (510)

Wearable and intelligent bioelectronic systems are emerging as a key enabling technology for continuous, non-invasive health monitoring, coupling physiological sensing with data-driven inference. Within this paradigm, electroencephalography (EEG) provides a wearable-compatible biosensing modality for capturing the pre-sleep neurophysiological dynamics linked to emotional regulation and sleep onset. Insomnia affects approximately 10–15% of adults worldwide and is often associated with dysregulated emotions and pre-sleep hyperarousal. Existing EEG-based affective and sleep-onset processing pipelines often rely either on deep-learning architectures with limited interpretability or on hand-crafted spectral descriptors with weak theoretical motivation. This study presents an exploratory proof-of-principle bioelectronic processing framework in which EEG sensing features are organized according to ANT-7 (artificial neurotransmitter seven-dimensional model), a neurotransmitter-inspired computational taxonomy introduced as a heuristic feature-design prior rather than as a validated neurochemical theory. The proposed feature set includes the alpha/theta power ratio, sample entropy, Higuchi fractal dimension, and phase-locking value extracted from the public DREAMER and DEAP datasets (23 and 32 subjects, respectively). SVM, Random Forest, and 1D-CNN classifiers are trained under subject-independent leave-one-subject-out cross-validation with strict within-fold normalization to prevent data leakage, and interpretability is assessed through SHAP values and permutation importance (PI). To stress-test whether this feature organization transfers beyond the affective benchmarks on which it is trained, classifier outputs are then related to sleep-onset latency in Sleep-EDF Expanded through a deliberately cautious cross-dataset transfer analysis. Within this protocol, the best model reaches 88.4% accuracy in three-class affective-state recognition (stress/neutral/relaxed; AUC-ROC = 0.93). As an exploratory secondary analysis, classifier-derived relaxation estimates show a statistically significant negative association with polysomnographic sleep-onset latency and improve over a single alpha/theta-ratio baseline; this cross-dataset result is reported as a proof of concept, not as a validated sleep-onset predictor. Interpretability analyses (SHAP and permutation importance) indicate that the learned feature rankings are internally consistent with the neurotransmitter-inspired feature design, a property we interpret as internal coherence rather than as independent confirmation of the taxonomy. Together, these elements outline a complete sensor-to-AI processing chain—from EEG biosensing, through neurotransmitter-inspired signal-feature extraction, to interpretable and computationally lightweight inference—designed for compatibility with low-density wearable EEG devices and edge deployment. However, EEG does not measure neurotransmitter concentrations, the study does not benchmark ANT-7 directly against competing taxonomies such as valence-arousal/circumplex or RDoC-inspired feature organizations, and the Sleep-EDF analysis should not be interpreted as evidence that the model measures a validated latent construct of sleep readiness. Accordingly, the manuscript should be read as a framework-validation study of one interpretable feature taxonomy, not as a theory-validation study of ANT-7 or as a clinical validation study. Full article

Stress relaxation tests on cylindrical samples of the Bellarosa potato cultivar were conducted over a wide range of deformation velocities, from 0.0002 m/s to 1.5 m/s. A three-element Maxwell model was applied to describe the response of potato tissue to the applied load. The effect of deformation velocity on the Maxwell model parameters and the values derived from the experimental stress relaxation curves was determined. The viscoelastic behavior of potato tissue was confirmed by the increase in the maximum force response with increasing deformation velocity. The relaxation times τ₁ and τ₃ decreased as the deformation velocity increased. The minimum force recorded at the end of the test and the elastic modulus E₃ were substantially higher under quasi-static than under impact loading conditions. These two parameters provide a good description of the material state after deformation and indicate a greater degree of cellular structure damage during impact loading compared with compression at low deformation velocities. Potato tissue contains approximately 80% water and only 3% air spaces. Therefore, changes in the cellular structure are expected to be associated mainly with water movement within cells and through intercellular spaces, with the intensity of these processes depending on the deformation velocity. Full article

The design of coal room and pillar panels has traditionally focused primarily on pillar behaviour. However, if the design process were approached from first principles, one would start with the design of the rooms and first look at the redistribution of the stresses around the rooms. Numerical simulations (elastic and elasto-plastic behaviour) clearly demonstrate the development of relaxed zones in both the roof and floor strata, as well as along the sidewalls in the pillars. The extent of these relaxed zones is governed by factors such as excavation geometry and the ratio of vertical-to-horizontal in situ stresses. A second concern is the widespread tendency to approximate in situ pillar behaviour through vertically loading experiments, such as uniaxial compression tests. These experiments would only be representative if pillars were constructed structures. More complex stress paths develop within the coal pillars during mining, and the load is far from uniform. The current design practices are based on the average pillar load, while the rock behaviour is not determined by average stresses but by local stresses. This paper concludes by proposing directions for future research and by identifying opportunities to improve current understanding and design methodologies for coal room and pillar workings. Full article

An approach based on a multi-relaxation (MR) test, in conjunction with a spring-dashpot model for data analysis, was employed to evaluate the influence of hydrothermal treatment at 65 °C on the viscous and quasi-static stress responses of polycarbonate (pure PC) and its short glass fibre composite (GF-PC) during the relaxation stages. The findings indicate that while this hydrothermal treatment did not affect the ductility of pure PC, it resulted in a significant ductility decrease in GF-PC. Furthermore, results from the modelling indicated that a parallel three-branch model was sufficient to simulate the stress decay during the relaxation stages of pure PC, but an additional branch (designated as the M-branch) was required for GF-PC. The study also found that for GF-PC, the hydrothermal treatment led to a distinct increase in the viscous stress response of the M-branch, but not in the other two viscous branches. This phenomenon is believed to stem from the coexistence of two types of PC matrix in GF-PC: one influenced by the presence of fibres and the other unaffected. Without the hydrothermal treatment, both types of PC matrix exhibit a similar deformation-dependence (based on stroke of the test machine) in their stress response; however, because the hydrothermal treatment affects the strength at the fibre–matrix interface, the stress responses of the two matrix types differ during relaxation. Consequently, the M-branch is believed to capture the altered stress response of the fibre-influenced PC matrix. The study concludes that under the investigated hydrothermal conditions, the reinforcing effect of the short fibre on the mechanical strength of GF-PC could be lost. Therefore, the addition of short glass fibre does not inherently guarantee mechanical reinforcement of PC. Full article

In order to promote the sustainable development of road engineering, this study used waste tire rubber powder (RP) and surface organic layered double hydroxide (SOM-LDHs) to modify 70# matrix asphalt. The Box–Behnken design response surface method with three factors (rubber powder content, surface organic layered double hydroxide content, shear temperature) and three responses (penetration, ductility, softening point) was used to optimize the preparation parameters. The optimum formula was determined to be 21.7% rubber powder content, 4.8% surface organic layered double hydroxide content, and 160 °C shear temperature. The effect of the modifier on the surface morphology was analyzed using a rotating film oven test and ultraviolet aging test. The high and low temperature rheological properties of asphalt were evaluated by dynamic shear rheometer (DSR), bending beam rheometer (BBR), and the multi-stress creep recovery test (MSCR). The microstructure was observed by scanning electron microscopy (SEM) and atomic force microscopy (AFM). The aging mechanism was investigated by Fourier transform infrared spectroscopy (FTIR) and gel permeation chromatography (GPC). The results show that after aging, the complex shear modulus of rubber powder/surface organic layered double hydroxide composite modified asphalt is the highest, which is 27.35% higher than that of matrix asphalt. The rutting factor reaches 79.86 kPa at 46 °C, the phase angle decreases by 11.83% after UV aging, and the high temperature plastic deformation resistance is the best. In the low temperature range of −18 °C to −24 °C, the creep stiffness of the composite modified asphalt is about 30% lower than that of the matrix asphalt, while the m value is increased by about 15%, and the low temperature stress relaxation performance is significantly improved. The strain recovery rate of composite modified asphalt under 3.2 kPa stress reaches 78.5%, and the unrecoverable creep compliance is as low as 0.18 kPa⁻¹, which is better than that of matrix asphalt and single rubber powder modified asphalt. Full article

Background: Directly printed aligners are advancing rapidly, but the mechanical behavior of the resins behind them is still only partly understood. This in vitro study compared the static flexural behavior, short-term stress relaxation, and FTIR profiles of five Class IIa-certified 3D-printable resins for direct orthodontic aligners. Methods: The five resins, TC-85, TA-28, DCA, Clear-A V2, and Ortho Flex, were printed as standardized rectangular bars and tested at 37 °C. Three-point bending to 1 mm deflection yielded the maximum flexural stress and the flexural modulus, while a 30 min hold at fixed deflection captured stress relaxation. FTIR added a qualitative chemical characterization. Results: Differences between resins were substantial. DCA led on every static measure, pairing the highest flexural stress and modulus with the highest final relaxation modulus and the best stiffness retention. Clear-A V2 was also statically stiff but retained force only intermediately, whereas TC-85 combined high stiffness with pronounced relaxation. Ortho Flex performed modestly under static loading yet held on to a moderate fraction of its stiffness, and TA-28 relaxed the most. Conclusions: Directly printed aligner resins are mechanically heterogeneous, and static bending alone did not predict short-term force stability. Relaxation metrics should therefore accompany static testing whenever a resin is selected for a specific clinical purpose. Full article

A new micropolar peridynamic framework incorporating stress- and stretch-based failure criteria was developed for simulating concrete structures. A nonlocal micropolar peridynamic stress tensor was employed to solve plane stress problems; this approach inherently manages cracks and damage. A direct correspondence was established between the classical constitutive stress–strain tensor and the associated micropolar peridynamic stress tensor for linearly elastic materials. Moreover, in contrast to standard peridynamic models that treat the material horizon as a purely abstract parameter, this research defines the horizon based on Poisson’s ratio, material strength, and fracture toughness. In addition, a numerical matrix-based scheme was implemented to model concrete problems using a nonlinear explicit dynamic relaxation solver. To assess the model’s performance, concrete structures under plane stress were examined. The model’s results align closely with the crack paths and experimental data from physical testing and demonstrate mesh independence. The implementation of the model with stress and stretch failure criteria mitigates spurious boundary effects, ensuring spatial convergence. Full article

To accurately characterize the nonlinear hyper-viscoelastic mechanical behavior of rubber materials under large deformation and stress relaxation conditions, this study investigates fluororubber (FKM) and hydrogenated nitrile rubber (HNBR) with different hardness levels through uniaxial mechanical tests and stress relaxation experiments. A constitutive parameter identification method based on hyperelastic models and the parallel rheological framework (PRF) model is established. First, several representative hyperelastic models, including the Neo-Hookean, Mooney–Rivlin, Yeoh, Ogden, Arruda–Boyce, and Van der Waals models, are comparatively evaluated. The results show that the Ogden model with (N = 3) provides the highest fitting accuracy for the large-deformation responses of FKM and HNBR with different hardness levels, with coefficients of determination (R²) ranging from 0.9879 to 0.9948. Subsequently, the Prony series parameters are identified from the stress relaxation data and converted into the initial parameters of the linear PRF model. To overcome the limitations of the linear PRF model in predicting nonlinear relaxation behavior, the PRF parameters are further optimized using the Isight data matching method combined with the Hooke–Jeeves algorithm. Finite element validation demonstrates that the optimized nonlinear PRF model can accurately predict the stress relaxation behavior of both FKM and HNBR. The mean absolute percentage errors of FKM60, FKM70, and FKM80 are 2.67%, 1.57%, and 2.56%, respectively, while those of HNBR60, HNBR70, and HNBR80 are 2.16%, 2.72%, and 2.58%, respectively. These results indicate that the combination of the Ogden (N = 3) hyperelastic model and the optimized nonlinear PRF model can effectively describe the large-deformation and time-dependent viscoelastic responses of rubber materials, providing a reliable constitutive modeling basis for finite element analysis and parameter calibration of rubber sealing structures. Full article

The optimization and the engineering development of additive manufacturing (AM) products both require accurate, non-destructive techniques to extract their mechanical performances. The Instrumented Indentation Test (IIT) has such a potential, although it currently lacks standard procedures that are suitable for analyzing materials which are affected by internal residual stress (RS). Additionally, nanoindentation testing suffers from the presence of indentation size effects (ISE), which hamper the possibility of correlating the measured mechanical performance at different indentation depths or peak loads using the standard indentation hardness (H_IT) and modulus (E_IT). This paper presents a novel IIT methodology that is based on new indentation parameters, namely the loading stiffness rate (LSR) and the rate-derived hardness (H_R), which are then used to assign the desired mechanical performances of an L-PBF 316L austenitic stainless-steel alloy obtained via multiload/multiscale IIT strategy. The mean values of LSR, H_R, H_IT, and E_IT on the macroscale were 57.3 ± 1.4 GPa, 2.33 ± 0.059 GPa, 2.41 ± 0.13 GPa, and 201 ± 7.8 GPa, respectively, whereas on the nanoscale they were 56.1 ± 5.1 GPa, 2.30 ± 0.21 GPa, 3.00 ± 0.36 GPa, and 219 ± 24 GPa, respectively. Unlike the standard H_IT, the new indentation parameters of the nano- and macro-IITs are within the standard deviation, proving their ISE-free property. The obtained E_IT was slightly higher than the reference Young’s modulus (~190 GPa) of the 316L stainless steel. The loading secant stiffness versus depth plot can be used to assess the susceptibility of RS to relax during indentation, which is an important performance factor for the engineering design of AM components. The successful correlation that has been found between electron backscatter diffraction (EBSD) analysis (in terms of crystal anisotropy, grain size, and dislocation density) and nanoindentation testing at three subregions of the core zone of the investigated deposit confirms the validity of the proposed methodology. The proposed methodology is a step towards the full determination of the three Ps, that is, process, properties, and performance of advanced AM products. Full article

Glass-transition-driven shape memory polymers are promising materials for 4D printing because their thermally activated transition enables programmed deformation and recovery without relying on melting or crystallization-driven switching. In this study, PDMS-MMA-modified photocurable networks were designed for vat photopolymerization-based 4D printing by varying PDMS-MMA content and switching monomer structure while maintaining a fixed TMPTMA crosslinker content. The resin formulations were prepared using tert-butyl acrylate (tBA) or isobornyl acrylate (IBOA) as switching monomers, PDMS-MMA as a flexible mobility-regulating segment, and TMPTMA as a multifunctional crosslinker. The effects of formulation composition on printability, network formation, thermal stability, thermomechanical transition, mechanical properties, and shape memory behavior were systematically investigated. FT-IR analysis confirmed effective photocuring of the acrylate/methacrylate networks, while rheological evaluation showed that resin viscosity depended on monomer structure and PDMS-MMA content. DMA results revealed thermomechanical transition, although some formulations exhibited broad tan δ responses due to network heterogeneity and distributed segmental relaxation. Based on resin printability, printed-part resolution, and relatively well-defined tan δ transitions, T-15 and I-15 were selected as representative formulations for quantitative shape memory evaluation. Shape memory testing was conducted under force-control mode because stable strain-controlled programming was not achievable for the printed specimens. Both T-15 and I-15 exhibited high shape fixity over two programming–recovery cycles. I-15 showed stable recovery behavior with recovery ratios of 91.51% and 95.87%, whereas T-15 showed apparent over-recovery with recovery ratios exceeding 100%, likely due to residual stress release during reheating. Overall, these results demonstrate that thermally activated shape-memory performance is governed not only by the nominal transition temperature but also by the coupled effects of PDMS-mediated segmental mobility, switching monomer structure, mechanical integrity, and elastic energy storage within a fixed crosslinked network framework. Full article

Background: Adolescent idiopathic scoliosis (AIS) is associated with alterations in muscle tone, stiffness, and viscoelastic properties that may affect musculoskeletal function and rehabilitation outcomes. Myotonometry offers a non-invasive means of quantifying these properties, but its agreement across testing positions in scoliotic populations remains insufficiently characterized. This study aimed to evaluate the agreement across positions of the MyotonPRO device for assessing superficial back muscle properties in adolescents with mild-to-moderate S-shaped AIS across standing and prone positions, and to examine positional and side-to-side differences. Methods: Nineteen adolescents (18 female, 1 male; mean age 15.3 ± 1.8 years) with mild-to-moderate dextroconvex thoracic and sinistroconvex lumbar idiopathic scoliosis were assessed bilaterally at the middle trapezius, lower trapezius, latissimus dorsi, and lumbar erector spinae. Muscle tone, stiffness, elasticity (logarithmic decrement), stress relaxation time, and creep were recorded by a single examiner in both standing and prone positions. Agreement across positions was quantified using intraclass correlation coefficients (ICCs), and between-position differences were tested with paired t-tests. Results: Agreement across positions was poor for most muscle and parameter combinations. The decrement of the lumbar erector spinae showed the highest agreement bilaterally (ICCs 0.829–0.844, good), and the left middle trapezius showed moderate agreement for tone, stiffness, stress relaxation time and creep (ICCs 0.567–0.649); all other muscle and parameter combinations showed predominantly poor agreement (ICCs < 0.50). Between-position differences were muscle- and side-specific: the middle trapezius differed significantly in all five parameters bilaterally (with higher tone and stiffness in standing), whereas both lumbar erectors showed no significant positional differences. The left lower trapezius and both latissimus dorsi showed lower tone in standing, in contrast to the middle trapezius pattern. Conclusions: Across standing and prone positions, MyotonPRO measurements showed predominantly poor absolute agreement for the superficial back muscles examined in adolescents with S-shaped AIS; only the decrement of the lumbar erector spinae reached good agreement. Full article

Graphite foil is widely used as a sealing material in flange joints in the form of gaskets or gasket components. Predicting gasket permeability during stress relaxation remains challenging because both the compression state and the gas pressure affect leakage. No unified semi-empirical model based on the Darcy–Klinkenberg framework with compression pressure as a direct input has been available for use in flange-joint numerical simulations. Graphite foil gaskets with a density of about 1.0 g/cm³ and a thickness of ~1.5 mm were tested under compression pressures from 5 to 100 MPa. Helium leakage was measured at helium pressures from 0.5 to 8 MPa. Leakage and deformation during loading and unloading were recorded using EN 13555-based procedures. The results were analyzed using a Darcy–Klinkenberg formulation and equivalent slit- and capillary-based representations of the leakage channels. The second-order model reproduced the pressure-dependent leakage more accurately than the first-order Darcy approximation (R² ≥ 0.9985 vs. 0.916–0.992), particularly where slip-flow effects were significant. Exponential dependences of the intrinsic permeability and the Klinkenberg coefficient on deformation and power-law relations with compression pressure are proposed to model leakage during unloading. The proposed semi-empirical model allows estimation of graphite-foil permeability under stress relaxation with the use of EN 13555 test procedures and its subsequent implementation in numerical simulations of flange joints. Limits of the model’s applicability, including loading regime, ranges of compression pressure, gas pressure and anisotropic nature of permeability, are discussed. Full article

Anxiety disorders pose an increasing challenge to the mental health of individuals, particularly in regions with limited healthcare access. This study investigated the potential of integrating a brain–computer interface for processing electroencephalography (EEG) data with deep learning models to accurately classify anxious and non-anxious states. In the first phase, a convolutional neural network (CNN) was developed and validated on the public GAMEEMO dataset, achieving a classification accuracy of 95.72%. In the second phase, we conducted a separate experimental validation with seven participants (aged 18–60 years) using a within-subjects design. The protocol comprised a custom Stroop test to elicit acute cognitive stress and anxiety-related arousal, followed by a guided 4–7–8 breathing exercise to induce relaxation. EEG data from this experiment were used to classify anxious versus non-anxious states with the same CNN architecture after domain adaptation. On this self-collected dataset, the CNN achieved an accuracy of 86.58%. These results demonstrate proof-of-concept transferability while highlighting the performance gap between controlled benchmark data and real-world, small-sample recordings. The deep learning model can subsequently be coupled with neurofeedback techniques to manage anxiety levels. Overall, the findings support the potential of the developed automated system for detecting stress-induced anxious states, with possible future integration into neurofeedback-based management systems. Full article

Titanium-doped diamond-like carbon (DLC:Ti) films were deposited by magnetron sputtering. The effects of Ti concentration on the microstructure, phase composition and piezoresistive properties of the films were systematically investigated. The surface morphology, crystal structure and chemical bonding states of the samples were characterized using SEM, XRD and XPS. The piezoresistive properties were then assessed by monitoring the resistance change in the thin films using a precision resistance meter under controlled external stimulation. The results demonstrate that the sp²/sp³ ratio of the DLC:Ti films increases with rising Ti concentration, and both Ti–C and Ti–Ti chemical bonds are formed within the films. An excessive β-Ti phase forms when the Ti concentration exceeds 39.7 at.%. The electrical resistance of DLC:Ti films decreases linearly as the applied normal stress increases from 0 to 35 MPa, with a maximum piezoresistive coefficient of −9.0 × 10⁻² GPa⁻¹ achieved for the film with a Ti doping concentration of 12.9 at.%. One hundred cyclic loading–unloading tests induce the structural transition from sp³ to sp², resulting in the graphitization of DLC:Ti films. In addition, external stress facilitates the fracture of Ti–C bonds and the relaxation of residual stress in the DLC:Ti films; the β- to α-Ti phase transformation induced by external loading is also observed in the films. Cyclic piezoresistive tests reveal that the piezoresistive stability of the DLC:Ti films is enhanced with increasing Ti concentration, which is attributed to the increased formation of Ti–C bonds in the films. Full article

Experiencing the forest landscape in its natural state is one of the factors that positively affect people, especially younger generations exposed to stress. The study assessed the impact of listening to nature sounds and observing forest landscapes on the mood and well-being of young adults exposed to a real forest environment. The experiment consisted of two sessions, allowing us to compare the regenerative effects of observing the forest with full engagement of the senses of sight and hearing, and by listening exclusively to the sounds of nature (birdsong, rustling leaves). The relaxation benefits were compared using psychological tests, including the Positive and Negative Affect Schedule (PANAS), Profile of Mood States (POMS), Restorative Outcome Scale (ROS), and Subjective Vitality Scale (SVS), administered before and after each exposure. The study involved 31 volunteers from Warsaw, the Polish capital (17 women and 14 men, with an average age of 25). A significant improvement in mood (as measured by the POMS) was observed, particularly through a reduction in Anger and Confusion. Both sessions (with and without a blindfold) significantly reduced negative affect (PANAS Negative) and increased restorative outcomes (ROS). However, no significant differences were found between full immersion (sight and hearing) and auditory-only exposure, suggesting that the acoustic layer of the forest environment plays a dominant role in the short-term psychological regeneration of young adults. In summary, these results suggest that both forms of exposure to nature have a relaxing effect on humans. However, full immersion, which involves being in the forest and viewing it, combined with listening to the sounds of nature, provides by far the most benefits for improving the well-being and mood of forest visitors. Full article