486 research outputs found
PreFallKD: Pre-Impact Fall Detection via CNN-ViT Knowledge Distillation
Fall accidents are critical issues in an aging and aged society. Recently,
many researchers developed pre-impact fall detection systems using deep
learning to support wearable-based fall protection systems for preventing
severe injuries. However, most works only employed simple neural network models
instead of complex models considering the usability in resource-constrained
mobile devices and strict latency requirements. In this work, we propose a
novel pre-impact fall detection via CNN-ViT knowledge distillation, namely
PreFallKD, to strike a balance between detection performance and computational
complexity. The proposed PreFallKD transfers the detection knowledge from the
pre-trained teacher model (vision transformer) to the student model
(lightweight convolutional neural networks). Additionally, we apply data
augmentation techniques to tackle issues of data imbalance. We conduct the
experiment on the KFall public dataset and compare PreFallKD with other
state-of-the-art models. The experiment results show that PreFallKD could boost
the student model during the testing phase and achieves reliable F1-score
(92.66%) and lead time (551.3 ms)
A Single-Step Digital Nucleic Acid Amplification Platform by Digital Plasma Separation on a Chip
Extraction of single-trial cortical beta oscillatory activities in EEG signals using empirical mode decomposition
<p>Abstract</p> <p>Background</p> <p>Brain oscillatory activities are stochastic and non-linearly dynamic, due to their non-phase-locked nature and inter-trial variability. Non-phase-locked rhythmic signals can vary from trial-to-trial dependent upon variations in a subject's performance and state, which may be linked to fluctuations in expectation, attention, arousal, and task strategy. Therefore, a method that permits the extraction of the oscillatory signal on a single-trial basis is important for the study of subtle brain dynamics, which can be used as probes to study neurophysiology in normal brain and pathophysiology in the diseased.</p> <p>Methods</p> <p>This paper presents an empirical mode decomposition (EMD)-based spatiotemporal approach to extract neural oscillatory activities from multi-channel electroencephalograph (EEG) data. The efficacy of this approach manifests in extracting single-trial post-movement beta activities when performing a right index-finger lifting task. In each single trial, an EEG epoch recorded at the channel of interest (CI) was first separated into a number of intrinsic mode functions (IMFs). Sensorimotor-related oscillatory activities were reconstructed from sensorimotor-related IMFs chosen by a spatial map matching process. Post-movement beta activities were acquired by band-pass filtering the sensorimotor-related oscillatory activities within a trial-specific beta band. Signal envelopes of post-movement beta activities were detected using amplitude modulation (AM) method to obtain post-movement beta event-related synchronization (PM-bERS). The maximum amplitude in the PM-bERS within the post-movement period was subtracted by the mean amplitude of the reference period to find the single-trial beta rebound (BR).</p> <p>Results</p> <p>The results showed single-trial BRs computed by the current method were significantly higher than those obtained from conventional average method (<it>P </it>< 0.01; matched-pair Wilcoxon test). The proposed method provides high signal-to-noise ratio (SNR) through an EMD-based decomposition and reconstruction process, which enables event-related oscillatory activities to be examined on a single-trial basis.</p> <p>Conclusions</p> <p>The EMD-based method is effective for artefact removal and extracting reliable neural features of non-phase-locked oscillatory activities in multi-channel EEG data. The high extraction rate of the proposed method enables the trial-by-trial variability of oscillatory activities can be examined, which provide a possibility for future profound study of subtle brain dynamics.</p
Biological Activities and Applications of Dioscorins, the Major Tuber Storage Proteins of Yam
AbstractYam tubers, a common tuber crop and an important traditional Chinese medicine in Taiwan, have many bioactive substances, including phenolic compounds, mucilage polysaccharides, steroidal saponins and proteins. Among the total soluble proteins, 80% of them are dioscorins. In the past two decades, many studies showed that dioscorins exhibited biological activities both in vitro and in vivo, including the enzymatic, antioxidant, antihypertensive, immunomodulatory, lectin activities and the protecting role on airway epithelial cells against allergens in vitro. Some of these activities are survived after chemical, heating process or enzymatic digestion. Despite of lacking the intact structural information and the detail action mechanisms in the cells, yam dioscorins are potential resources for developing as functional foods and interesting targets for food protein researchers
Twin-Free GaAs Nanosheets by Selective Area Growth: Implications for Defect-Free Nanostructures
Highly perfect, twin-free GaAs nanosheets grown on (111)B surfaces by selective area growth (SAG) are demonstrated. In contrast to GaAs nanowires grown by (SAG) in which rotational twins and stacking faults are almost universally observed, twin formation is either suppressed or eliminated within properly oriented nanosheets are grown under a range of growth conditions. A morphology transition in the nanosheets due to twinning results in surface energy reduction, which may also explain the high twin-defect density that occurs within some III–V semiconductor nanostructures, such as GaAs nanowires. Calculations suggest that the surface energy is significantly reduced by the formation of {111}-plane bounded tetrahedra after the morphology transition of nanowire structures. By contrast, owing to the formation of two vertical {11̅0} planes which comprise the majority of the total surface energy of nanosheet structures, the energy reduction effect due to the morphology transition is not as dramatic as that for nanowire structures. Furthermore, the surface energy reduction effect is mitigated in longer nanosheets which, in turn, suppresses twinning
Improving the 2d numerical simulations on local scour hole around spur dikes
Local scour is a common threat to structures such as bridge piers, abutments, and dikes that are constructed on natural rivers. To reduce the risk of foundation failure, the understanding of local scour phenomenon around hydraulic structures is important. The well-predicted scour depth can be used as a reference for structural foundation design and river management. Numerical simulation is relatively efficient at studying these issues. Currently, two-dimensional (2D) mobile-bed models are widely used for river engineering. However, a common 2D model is inadequate for solving the three-dimensional (3D) flow field and local scour phenomenon because of the depth-averaged hypothesis. This causes the predicted scour depth to often be underestimated. In this study, a repose angle formula and bed geometry adjustment mechanism are integrated into a 2D mobile-bed model to improve the numerical simulation of local scour holes around structures. Comparison of the calculated and measured bed variation data reveals that a numerical model involving the improvement technique can predict the geometry of a local scour hole around spur dikes with reasonable accuracy and reliability
Bian Zheng Lun Zhi
Background. Limited scientific evidence supports the positive effects of traditional Chinese medicine (TCM) for treating dysmenorrhea. Thus, an observation period of 3 months could verify the ancient indication that TCM treatments effectively alleviate menstrual cramps in women with primary dysmenorrhea or endometriosis. Methods. A prospective, nonrandomized study (primary dysmenorrhea and endometriosis groups) was conducted in women with dysmenorrhea for more than three consecutive menstrual cycles. All patients received TCM prescriptions based on bian zheng lun zhi theory 14 days before menstruation for a period of 12 weeks. Pain intensity was evaluated using a 10-cm visual analogue scale and two validated questionnaires (the Menstrual Distress Questionnaire and the World Health Organization Quality of Life questionnaire). Results. Of the initial 70 intent-to-treat participants, the women with dysmenorrhea reported significant alleviation of cramps during menstruation after the 12-week TCM treatment. Mixed model analysis revealed that TCM prescriptions were more effective in alleviating fatigue, hot flashes, dizziness, painful breasts, excitement, and irritability in the primary dysmenorrhea group (N=36) than in the endometriosis group (N=34). Conclusion. TCM prescriptions based on syndrome differentiation theory might be a potentially viable choice for treating painful menstruation and premenstrual symptoms after ruling out endometriosis
Chinese Herbal Medicine Therapy and the Risk of Mortality for Chronic Hepatitis B Patients with Concurrent Liver Cirrhosis: a Nationwide Population-Based Cohort Study
Chronic hepatitis B (CHB) is increasingly recognized as a public health problem in Taiwan. After affected patients are diagnosed with contaminant liver cirrhosis (LC), adverse clinical outcomes, especially death, are common. This study aimed to investigate the effect of Chinese herbal medicine (CHM), an essential branch of Traditional Chinese medicine (TCM), on the mortality risk among CHB patients with contaminant LC. This longitudinal cohort study used the Taiwanese National Health Insurance Research Database to identify 1522 patients 20–70 years of age with newly diagnosed CHB with LC during 1998–2007. Among them, 508 (33.37%) had received CHM products after the onset of CHB (CHM users), and the remaining 1014 patients (66.63%) were designated as a control group (non-CHM users). All enrollees were followed until the end of 2012 to determine deaths during the study period. We applied the Cox proportional hazards regression model to compute the hazard ratio for the association of CHM use and the subsequent risk of death. During the follow-up period, 156 CHM users and 493 non-CHM users died. After controlling for potential confounders, CHM users were found to have a significantly reduced risk of death compared with non-CHM users by 56%, and the effect was predominantly observed among those treated with CHM for \u3e 180 days. CHM therapy lowered the risk of death among CHB patients with contaminant LC, which supported CHM might provide further treatment options for those with chronic liver diseases
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