Traditional Chinese Mind and Body Exercises for Promoting Balance Ability of Old Adults: A Systematic Review and Meta-Analysis

The purpose of this study was to provide a quantitative evaluation of the effectiveness of traditional Chinese mind and body exercises in promoting balance ability for old adults. The eligible studies were extensively searched from electronic databases (Medline, CINAHL, SportDicus, and Web of Science) until 10 May 2016. Reference lists of relevant publications were screened for future hits. The trials used randomized controlled approaches to compare the effects of traditional Chinese mind and body exercise (TCMBE) on balance ability of old adults that were included. The synthesized results of Berg Balance Scale (BBS), Timed Up and Go Test (TUG), and static balance with 95% confidence intervals were counted under a random-effects model. Ten studies were selected based on the inclusion criteria, and a total of 1,798 participants were involved in this review. The results of the meta-analysis showed that TCMBE had no significant improvement on BBS and TUG, but the BBS and TUG could be obviously improved by prolonging the intervention time. In addition, the results showed that TCMBE could significantly improve the static balance compared to control group. In conclusion, old adults who practiced TCMBE with the time not less than 150 minutes per week for more than 15 weeks could promote the balance ability

Experiments and simulations of MEMS thermal sensors for wall shear-stress measurements in aerodynamic control applications

MEMS thermal shear-stress sensors exploit heat-transfer effects to measure the shear stress exerted by an air flow on its solid boundary, and have promising applications in aerodynamic control. Classical theory for conventional, macroscale thermal shear-stress sensors states that the rate of heat removed by the flow from the sensor is proportional to the 1/3-power of the shear stress. However, we have observed that this theory is inconsistent with experimental data from MEMS sensors. This paper seeks to develop an understanding of MEMS thermal shear-stress sensors through a study including both experimental and theoretical investigations. We first obtain experimental data that confirm the inadequacy of the classical theory by wind-tunnel testing of prototype MEMS shear-stress sensors with different dimensions and materials. A theoretical analysis is performed to identify that this inadequacy is due to the lack of a thin thermal boundary layer in the fluid flow at the sensor surface, and then a two-dimensional MEMS shear-stress sensor theory is presented. This theory incorporates important heat-transfer effects that are ignored by the classical theory, and consistently explains the experimental data obtained from prototype MEMS sensors. Moreover, the prototype MEMS sensors are studied with three-dimensional simulations, yielding results that quantitatively agree with experimental data. This work demonstrates that classical assumptions made for conventional thermal devices should be carefully examined for miniature MEMS devices

PNI Biomarkers and Health Outcomes in College Women

Sleep disturbance has been found to trigger a stress response with a subsequent activation of the psychoneuroimmunological (PNI) pathway associated with adverse health outcomes. This study aimed to assess the association among selected PNI biomarkers, sleep disturbances, and adverse health outcomes (depressive symptoms, physical symptoms). A stratified, quota sample (14 poor sleepers and 15 good sleepers) was drawn from a pool of healthy college women from a larger scale of study. The participants reported their sleep, stress, depressive, and physical symptoms. Wrist actigraphy was used to collect objective sleep data, and the Enzyme-Linked ImmunoSorbent Assay was used to assess PNI biomarkers. Poor sleep quality, higher stress perception, elevated serum serotonin, and lower serum interleukin-10 explained 75.3% of the variances for the depressive symptoms. Poor sleep quality along with delayed peak activity rhythms accounted 31.4% of the physical symptoms. High serotonin and tumor necrosis factor-α were the significant predictors for poor sleep efficiency, and serotonin was the single significant predictor for poor daytime functioning. Stress and sleep disturbances negatively impact the health of college women and should be as part of regular check-ups on campus. PNI effects on health outcomes should be further explored. Educational materials in the areas of sleep hygiene, health impacts from sleep disturbances, and strategies to maintain synchronized circadian rhythms should be mandatorily included in the college curriculum

THREE DIMENSIONAL SMOOTHING TECHNIQUES USING QUATERNIONS APPLIED TO GAIT

The purpose of this study was to implement a three-dimensional (3D) technique for smoothing gait analysis data. Three dimensional smoothing is problematic as it relies on one-dimensional smoothing techniques that are ill-posed to preserve the integrity of the real, raw data. Since Davis et al, (1991) method many researchers (e.g. Baker, 2006) have emphasized the problems of three dimensional gait analysis

Preparation and characterization of solid lipid nanoparticles loaded with frankincense and myrrh oil

The aim of the present study was to prepare solid lipid nanoparticles (SLNs) for the oral delivery of frankincense and myrrh essential oils (FMO). Aqueous dispersions of SLNs were successfully prepared by a high-pressure homogenization method using Compritol 888 ATO as the solid lipid and soybean lecithin and Tween 80 as the surfactants. The properties of the SLNs such as particle size, zeta potential (ZP), and drug encapsulation efficiency (EE) were investigated. The morphology of SLNs was observed by transmission electron microscopy (TEM). The crystallinity of the formulation was analyzed by differential scanning calorimetry (DSC) and X-ray diffraction (XRD). In addition, drug evaporation release and antitumor activity were also studied. Round SLNs with a mean size of 113.3 ± 3.6 nm, a ZP of −16.8 ± 0.4 mV, and an EE of 80.60% ± 1.11% were obtained. DSC and XRD measurements revealed that less ordered structures were formed in the inner cores of the SLN particles. Evaporation loss of the active components in FMO could be reduced in the SLNs. Furthermore, the SLN formulation increased the antitumor efficacy of FMO in H22-bearing Kunming mice. Hence, the presented SLNs can be used as drug carriers for hydrophobic oil drugs extracted from traditional Chinese medicines

Learning by Analogy: Reliable Supervision from Transformations for Unsupervised Optical Flow Estimation

Unsupervised learning of optical flow, which leverages the supervision from view synthesis, has emerged as a promising alternative to supervised methods. However, the objective of unsupervised learning is likely to be unreliable in challenging scenes. In this work, we present a framework to use more reliable supervision from transformations. It simply twists the general unsupervised learning pipeline by running another forward pass with transformed data from augmentation, along with using transformed predictions of original data as the self-supervision signal. Besides, we further introduce a lightweight network with multiple frames by a highly-shared flow decoder. Our method consistently gets a leap of performance on several benchmarks with the best accuracy among deep unsupervised methods. Also, our method achieves competitive results to recent fully supervised methods while with much fewer parameters.Comment: Accepted to CVPR 2020, https://github.com/lliuz/ARFlo

Distill Gold from Massive Ores: Efficient Dataset Distillation via Critical Samples Selection

Data-efficient learning has drawn significant attention, especially given the current trend of large multi-modal models, where dataset distillation can be an effective solution. However, the dataset distillation process itself is still very inefficient. In this work, we model the distillation problem with reference to information theory. Observing that severe data redundancy exists in dataset distillation, we argue to put more emphasis on the utility of the training samples. We propose a family of methods to exploit the most valuable samples, which is validated by our comprehensive analysis of the optimal data selection. The new strategy significantly reduces the training cost and extends a variety of existing distillation algorithms to larger and more diversified datasets, e.g. in some cases only 0.04% training data is sufficient for comparable distillation performance. Moreover, our strategy consistently enhances the performance, which may open up new analyses on the dynamics of distillation and networks. Our method is able to extend the distillation algorithms to much larger-scale datasets and more heterogeneous datasets, e.g. ImageNet-1K and Kinetics-400. Our code will be made publicly available

Wheelchair Tai Chi Ball Exercise for Improving Neuromuscular Functions of Older Adults With Disability

The purposes of this perspective article were to summarize Wheelchair or Seated Tai Chi studies related to neuromuscular functions of older adults with disability; to describe the development of Wheelchair Tai Chi Ball (WTCB) exercise — a concept to combine mind-body exercise with strength training; and to propose a new Telehealth WTCB exercise for improving neuromuscular functions of old adults with spinal cord injury (SCI) and disability. With reference to neuromuscular functions, WTC intervention may have positive effects on simple reaction time, range of motion at the shoulder and trunk, static and dynamic sitting balance, handgrip strength, vagal activity, and sympathetic activity among older adults with disability. The developed WTCB intervention is a feasible and safe exercise which combines the mind-body exercise and strength conditioning into one exercise which possesses aerobic, stretching and strength trainings and may facilitate neuromuscular functions of older adults with disability. The proposed Telehealth WTCB 12 forms (TWTCB12) exercise with a “Moving Shadow” method in the telehealth may enable the learner to superimpose learner’s image on an expert’s demonstrating model to enhance the learning and practice effects. Since wheelchair users will learn and practice TWTCB12 movements in a seated position or sitting on a wheelchair the “Moving shadow” method on Zoom would provide an ideal telehealth learning and practice environment for the wheelchair users to learn and practice TWTCB12 exercise from home more feasible and user friendly

Absolute photoacoustic thermometry in deep tissue

Photoacoustic thermography is a promising tool for temperature measurement in deep tissue. Here we propose an absolute temperature measurement method based on the dual temperature dependences of the Grüneisen parameter and the speed of sound in tissue. By taking ratiometric measurements at two adjacent temperatures, we can eliminate the factors that are temperature irrelevant but difficult to correct for in deep tissue. To validate our method, absolute temperatures of blood-filled tubes embedded ∼9  mm deep in chicken tissue were measured in a biologically relevant range from 28°C to 46°C. The temperature measurement accuracy was ∼0.6°C. The results suggest that our method can be potentially used for absolute temperature monitoring in deep tissue during thermotherapy