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The objective of the present study was to determine the effects of lower-limb muscular fatigue on stair gait. Twelve healthy young male adults between 20 and 30 years old participated in the experiment. There were two experimental sessions corresponding to a no fatigue condition and a lower-limb muscular fatigue condition, respectively. Lower-limb muscular fatigue was induced using repetitive lower-limb pushing exertions. Both ascent and descent were studied. Stair gait was assessed by lower-limb joints and trunk kinematics, and postural stability measures. It was found that lower-limb muscular fatigue compromised stair gait during descent, but did not make any difference during ascent. These findings highlighted the importance of minimizing exposures to lower-limb muscular fatigue during descent in stair accident prevention.

Previous studies have shown promising results in identifying individuals with autism spectrum disorder (ASD) by applying machine learning (ML) to eye-tracking data collected while participants viewed varying images (ie, pictures, videos, and web pages). Although gaze behavior is known to differ between face-to-face interaction and image-viewing tasks, no study has investigated whether eye-tracking data from face-to-face conversations can also accurately identify individuals with ASD.BACKGROUNDPrevious studies have shown promising results in identifying individuals with autism spectrum disorder (ASD) by applying machine learning (ML) to eye-tracking data collected while participants viewed varying images (ie, pictures, videos, and web pages). Although gaze behavior is known to differ between face-to-face interaction and image-viewing tasks, no study has investigated whether eye-tracking data from face-to-face conversations can also accurately identify individuals with ASD.The objective of this study was to examine whether eye-tracking data from face-to-face conversations could classify children with ASD and typical development (TD). We further investigated whether combining features on visual fixation and length of conversation would achieve better classification performance.OBJECTIVEThe objective of this study was to examine whether eye-tracking data from face-to-face conversations could classify children with ASD and typical development (TD). We further investigated whether combining features on visual fixation and length of conversation would achieve better classification performance.Eye tracking was performed on children with ASD and TD while they were engaged in face-to-face conversations (including 4 conversational sessions) with an interviewer. By implementing forward feature selection, four ML classifiers were used to determine the maximum classification accuracy and the corresponding features: support vector machine (SVM), linear discriminant analysis, decision tree, and random forest.METHODSEye tracking was performed on children with ASD and TD while they were engaged in face-to-face conversations (including 4 conversational sessions) with an interviewer. By implementing forward feature selection, four ML classifiers were used to determine the maximum classification accuracy and the corresponding features: support vector machine (SVM), linear discriminant analysis, decision tree, and random forest.A maximum classification accuracy of 92.31% was achieved with the SVM classifier by combining features on both visual fixation and session length. The classification accuracy of combined features was higher than that obtained using visual fixation features (maximum classification accuracy 84.62%) or session length (maximum classification accuracy 84.62%) alone.RESULTSA maximum classification accuracy of 92.31% was achieved with the SVM classifier by combining features on both visual fixation and session length. The classification accuracy of combined features was higher than that obtained using visual fixation features (maximum classification accuracy 84.62%) or session length (maximum classification accuracy 84.62%) alone.Eye-tracking data from face-to-face conversations could accurately classify children with ASD and TD, suggesting that ASD might be objectively screened in everyday social interactions. However, these results will need to be validated with a larger sample of individuals with ASD (varying in severity and balanced sex ratio) using data collected from different modalities (eg, eye tracking, kinematic, electroencephalogram, and neuroimaging). In addition, individuals with other clinical conditions (eg, developmental delay and attention deficit hyperactivity disorder) should be included in similar ML studies for detecting ASD.CONCLUSIONSEye-tracking data from face-to-face conversations could accurately classify children with ASD and TD, suggesting that ASD might be objectively screened in everyday social interactions. However, these results will need to be validated with a larger sample of individuals with ASD (varying in severity and balanced sex ratio) using data collected from different modalities (eg, eye tracking, kinematic, electroencephalogram, and neuroimaging). In addition, individuals with other clinical conditions (eg, developmental delay and attention deficit hyperactivity disorder) should be included in similar ML studies for detecting ASD.

The objective of this study was to determine the main and interactive effects of load carriage and fatigue on gait characteristics. Twelve young male participants were recruited in this study. Fatiguing protocol involved a running exercise, and fatigue was considered to be induced when the participants first gave an RPE rating at or above 17. Gait data were collected when the participants walked on a medical treadmill at their self-selected comfortable speed, both before and right after the fatiguing exercise. Different back-carrying loads (i.e. 0, 7.5, and 15 kg) were applied separately to the participants during the walking trials. Gait variability measures and kinematic measures were used to quantify gait characteristics. The results showed that gait width variability, hip range of motion, and trunk range of motion increased with fatigue and with the application of the heavy load. These findings suggest that both fatigue and load carriage compromise gait. Findings from this study can help better understand how fatigue and load carriage affect gait, and further aid in developing interventions that are able to minimize fall risks especially with the application of fatigue and/or external load.

Postural control is a complex skill based on the interaction of dynamic sensorimotor processes, and can be challenging for people with deficits in sensory functions. The foot plantar center of pressure (COP) has often been used for quantitative assessment of postural control. Previously, the foot plantar COP was mainly measured by force plates or complicated and expensive insole-based measurement systems. Although some low-cost instrumented insoles have been developed, their ability to accurately estimate the foot plantar COP trajectory was not robust. In this study, a novel individual-specific nonlinear model was proposed to estimate the foot plantar COP trajectories with an instrumented insole based on low-cost force sensitive resistors (FSRs). The model coefficients were determined by a least square error approximation algorithm. Model validation was carried out by comparing the estimated COP data with the reference data in a variety of postural control assessment tasks. We also compared our data with the COP trajectories estimated by the previously well accepted weighted mean approach. Comparing with the reference measurements, the average root mean square errors of the COP trajectories of both feet were 2.23 mm (±0.64) (left foot) and 2.72 mm (±0.83) (right foot) along the medial–lateral direction, and 9.17 mm (±1.98) (left foot) and 11.19 mm (±2.98) (right foot) along the anterior–posterior direction. The results are superior to those reported in previous relevant studies, and demonstrate that our proposed approach can be used for accurate foot plantar COP trajectory estimation. This study could provide an inexpensive solution to fall risk assessment in home settings or community healthcare center for the elderly. It has the potential to help prevent future falls in the elderly.

This study investigated the anti-inflammatory properties of Lonicera macranthoides and its active component isochlorogenic acid C (ILAC) through an integrated approach combining spectrum-effect relationship analysis, network pharmacology, and molecular docking. Five extracts (S1-S5) were evaluated in LPS-stimulated RAW 264.7 macrophages, with S4 demonstrating the strongest inhibition (45.53 ± 0.23%). HPLC fingerprinting identified 12 characteristic peaks, including ILAC and chlorogenic acid. PLS regression analysis revealed these two compounds were most positively correlated with the observed anti-inflammatory activity. Network pharmacology predicted 113 potential anti-inflammatory targets for ILAC, with PPI network analysis identifying 10 core targets (e.g., CASP3, HIF1A, NF-κB1, TLR4). Molecular docking studies suggested ILAC’s potential high binding affinity to these targets (<-5 kcal/mol). Together, these in vitro and in silico analyses indicated that ILAC is a key anti-inflammatory constituent in L. macranthoides, likely acting via multi-target interactions with critical inflammatory mediators. The study provided preliminary molecular-level insights into the traditional use of L. macranthoides for inflammatory conditions and suggested ILAC’s potential as a candidate for further anti-inflammatory research. Further in vivo studies are required to substantiate its therapeutic potential and mechanism of action.

Through room-temperature tensile testing, microstructural observation, and comparative analysis of dislocation configurations, this study investigates the deformation and damage behavior of a high-concentration Re/Ru single-crystal alloy. The results show that the alloy possesses excellent mechanical properties at room temperature, with a tensile strength of 875 MPa and a yield strength of 847 MPa. During tensile deformation, plastic strain primarily occurs through dislocation slip within the γ matrix and dislocation shear into the γ′ phase. Dislocations sheared into the γ′ phase exhibit distinct decomposition patterns. Microcracks initiate at γ′/γ interfaces where two slip systems intersect. As tensile loading continues, these microcracks coalesce, leading to increased local stress and unstable crack propagation along the γ/γ′ interfaces, ultimately resulting in fracture. This process constitutes the deformation and damage mechanism of the alloy during room-temperature tensile deformation. These findings suggest that high Re/Ru concentrations fundamentally alter low-temperature deformation pathways, which may improve resistance to brittle fracture during cold start or handling conditions.

This study is to examine changes of functional connectivity in patients with depressive disorder using synchronous brain activity. Event-related potentials (ERPs) were acquired during a visual oddball task in 14 patients with depressive disorder and 19 healthy controls. Electroencephalogram (EEG) recordings were analyzed using event-related phase coherence (ERPCOH) to obtain the functional network. Alteration of the phase synchronization index (PSI) of the functional network was investigated. Patients with depression showed a decreased number of significant electrode pairs in delta phase synchronization, and an increased number of significant electrode pairs in theta, alpha and beta phase synchronization, compared with controls. Patients with depression showed lower target-dependent PSI increment in the frontal-parietal/temporal/occipital electrode pairs in delta-phase synchronization than healthy participants. However, patients with depression showed higher target-dependent PSI increments in theta band in the prefrontal/frontal and frontal-temporal electrode pairs, higher PSI increments in alpha band in the prefrontal pairs and higher increments of beta PSI in the central and right frontal-parietal pairs than controls. It implied that the decrease in delta PSI activity in major depression may indicate impairment of the connection between the frontal and parietal/temporal/occipital regions. The increase in theta, alpha and beta PSI in the frontal/prefrontal sites might reflect the compensatory mechanism to maintain normal cognitive performance. These findings may provide a foundation for a new approach to evaluate the effectiveness of therapeutic strategies for depression.

Restricted and repetitive behavior is a core symptom of autism spectrum disorder (ASD) characterized by features of restrictedness, repetition, rigidity, and invariance. Few studies have investigated how restrictedness is manifested in motor behavior. This study aimed to address this question by instructing participants to perform the utmost complex movement. Twenty children with ASD and 23 children with typical development (TD) performed one-dimensional, left-right arm oscillations by demonstrating varying amplitudes and frequencies. The entropy of amplitude and velocity was calculated as an index of kinematic complexity. Results showed that the velocity entropy, but not the amplitude entropy, was significantly lower in ASD than in TD ( p < 0.01), suggesting restricted kinematics. Further analysis demonstrated that a significantly higher proportion of the velocity values was allocated at a low-speed level in the children with ASD ( p < 0.01). A qualitative comparison of the complex movement with movement at preferred frequency suggested that the children with ASD might be less likely to shift away from the preferred movement. However, our study can be improved in terms of recruiting a larger sample of participants, measuring the level of motivation, and collecting both complex and preferred movements of the same participant.

The evolution of superdislocation structures during the creep of a single-crystal alloy was investigated through creep performance testing, microstructural observations, and comparative analysis of dislocation configurations. The results revealed that, in the early stage of creep, dislocations activated in the γ phase first glide along the 111 plane and subsequently reach the 100 γ/γ′ interface. At this interface, they transform into 60°mixed dislocations, which gradually develop into a dislocation network. As creep deformation proceeds, these 60°mixed dislocations progressively convert into type dislocations at the γ/γ′ 100 interface via a specific climb mechanism driven by mismatch stress, eventually forming a dislocation network. During the middle and late stages of creep, dislocations begin to shear the rafted γ′ phase sequentially, first single dislocations, then anti-phase boundary (APB) plus dislocation pairs, and finally superlattice intrinsic stacking faults (SISFs) plus partial dislocation. Consequently, the strain-softening mechanism during creep is governed not only by the increased density of specific superdislocations but also by the continuous evolution and interaction of multiple dislocation types.

The main purpose of this study was to determine which body part is the best position to apply noise at so that balance control can be improved most. Twelve young healthy participants were recruited in this study. Balance control was assessed by center of pressure (COP) measures, which were collected when participants were blindfolded and stood upright quietly on a force platform. Low-level mechanical noise was separately applied at seven body parts during quiet upright stance, including the forehead, neck, shoulder, finger, abdomen, knee, and ankle. Results showed that dependent COP measures as a whole were not improved when noise was at the finger, shoulder, abdomen, knee, and ankle. In contrast, with the application of noise at the forehead and neck, the dependent COP measures as a whole significantly changed. The forehead appeared to be the better position at which noise should be applied, since the ANOVAs revealed that body sway significantly decreased with the application of noise at the forehead. Findings from this study can aid in the development of noise-based intervention strategies aimed at improving balance. A possible intervention solution might be embedding noise-based devices into head belt.