Human Health Indicator Prediction from Gait Video

Body Mass Index (BMI), age, height and weight are important indicators of human health conditions, which can provide useful information for plenty of practical purposes, such as health care, monitoring and re-identification. Most existing methods of health indicator prediction mainly use front-view body or face images. These inputs are hard to be obtained in daily life and often lead to the lack of robustness for the models, considering their strict requirements on view and pose. In this paper, we propose to employ gait videos to predict health indicators, which are more prevalent in surveillance and home monitoring scenarios. However, the study of health indicator prediction from gait videos using deep learning was hindered due to the small amount of open-sourced data. To address this issue, we analyse the similarity and relationship between pose estimation and health indicator prediction tasks, and then propose a paradigm enabling deep learning for small health indicator datasets by pre-training on the pose estimation task. Furthermore, to better suit the health indicator prediction task, we bring forward Global-Local Aware aNd Centrosymmetric Encoder (GLANCE) module. It first extracts local and global features by progressive convolutions and then fuses multi-level features by a centrosymmetric double-path hourglass structure in two different ways. Experiments demonstrate that the proposed paradigm achieves state-of-the-art results for predicting health indicators on MoVi, and that the GLANCE module is also beneficial for pose estimation on 3DPW

Efficient Smooth Non-Convex Stochastic Compositional Optimization via Stochastic Recursive Gradient Descent

Stochastic compositional optimization arises in many important machine learning applications. The objective function is the composition of two expectations of stochastic functions, and is more challenging to optimize than vanilla stochastic optimization problems. In this paper, we investigate the stochastic compositional optimization in the general smooth non-convex setting. We employ a recently developed idea of Stochastic Recursive Gradient Descent to design a novel algorithm named SARAH-Compositional, and prove a sharp Incremental First-order Oracle (IFO) complexity upper bound for stochastic compositional optimization: ((n + m)1/2ε-2) in the finite-sum case and (ε-3) in the online case. Such a complexity is known to be the best one among IFO complexity results for non-convex stochastic compositional optimization. Numerical experiments on risk-adverse portfolio management validate the superiority of SARAH-Compositional over a few rival algorithms

Entropy-Based Model for Interpreting Life Systems in Traditional Chinese Medicine

Traditional Chinese medicine (TCM) treats qi as the core of the human life systems. Starting with a hypothetical correlation between TCM qi and the entropy theory, we address in this article a holistic model for evaluating and unveiling the rule of TCM life systems. Several new concepts such as acquired life entropy (ALE), acquired life entropy flow (ALEF) and acquired life entropy production (ALEP) are propounded to interpret TCM life systems. Using the entropy theory, mathematical models are established for ALE, ALEF and ALEP, which reflect the evolution of life systems. Some criteria are given on physiological activities and pathological changes of the body in different stages of life. Moreover, a real data-based simulation shows life entropies of the human body with different ages, Cold and Hot constitutions and in different seasons in North China are coincided with the manifestations of qi as well as the life evolution in TCM descriptions. Especially, based on the comparative and quantitative analysis, the entropy-based model can nicely describe the evolution of life entropies in Cold and Hot individuals thereby fitting the Yin–Yang theory in TCM. Thus, this work establishes a novel approach to interpret the fundamental principles in TCM, and provides an alternative understanding for the complex life systems

Design, Synthesis, and In vitro Antitumor Activity Evaluation of Novel 4‐pyrrylamino Quinazoline Derivatives

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/88050/1/j.1747-0285.2011.01234.x.pd

Synthesis and Sensing Properties of ZnO/ZnS Nanocages

Large-scale uniform ZnO dumbbells and ZnO/ZnS hollow nanocages were successfully synthesized via a facile hydrothermal route combined with subsequent etching treatment. The nanocages were formed through preferential dissolution of the twinned (0001) plane of ZnO dumbbells. Due to their special morphology, the hollow nanocages show better sensing properties to ethanol than ZnO dumbbells. The gain in sensitivity is attributed to both the interface between ZnO and ZnS heterostructure and their hollow architecture that promotes analyte diffusion and increases the available active surface area

Effect of polygonimitin C on bone formation and resorption in human osteoblast-like MG63 cells

Purpose: To investigate the effect of polygonimitin C (PC) on bone formation and resorption in human osteoblast-like MG63 cells.Methods: MG63 cells were treated with PC at doses of 0, 20, 40 or 80 μg/mL for 48 h, with an untreated group as control. The effect of PC on alkaline phosphatase (ALP) activity in MG63 cells was investigated by p-nitrophenyl phosphate disodium hexahydrate assay. Western blot assay was used to evaluate the effect of PC on the expressions of osterix (OSX), bone morphogenetic protein-2 (BMP-2), runt-related transcription factor 2 (RUNX-2), osteocalcin (OC), fibronectin (FN), type I collagen (COL I), osteoprotegerin (OPG) and receptor activator of NF-κB ligand (RANKL) proteins in MG63 cells.Results: ALP relative activity in MG63 cells treated with PC at 20, 40 or 80 μg/mL (123.58, 137.74 or 159.62 %, respectively) was significantly (p < 0.05 or 0.01) higher than that in control group (99.37 %). Expressions of OSX, BMP-2, RUNX-2, OC, FN, COL I and OPG proteins in MG63 cells treated with PC at 20, 40 or 80 μg/mL were significantly (p < 0.01) higher than those in control group. However, there were no statistically significant differences in RANKL protein expression between PC-treated MG63 cells and control group.Conclusion: These results show that PC exerts protective effects against osteoporosis by promoting bone formation and inhibiting bone resorption. Thus, PC may be useful in the development of new antiosteoporosis drugs.Keywords: Polygonimitin C, MG63 cells, Bone formation, Bone resorption, Osteoporosi

Distinguishing Smilax glabra and Smilax china rhizomes by flow-injection mass spectrometry combined with principal component analysis

Flow-injection mass spectrometry (FIMS) coupled with a chemometric method is proposed in this study to profile and distinguish between rhizomes of Smilax glabra (S. glabra) and Smilax china (S. china). The proposed method employed an electrospray-time-of-flight MS. The MS fingerprints were analyzed using principal component analysis (PCA) and orthogonal partial least squares discriminant analysis (OPLS-DA) with the aid of SIMCA software. Findings showed that the two kinds of samples perfectly fell into their own classes. Further predictive study showed desirable predictability and the tested samples were successfully and reliably identified. The study demonstrated that the proposed method could serve as a powerful tool for distinguishing between S. glabra and S. china

Electroacupuncture Treatment Normalized Sleep Disturbance in Morphine Withdrawal Rats

Sleep disturbance is considered as an important symptom of acute and protracted opiate withdrawal. Current results suggest that sleep disturbance may be taken as a predictor of relapse. Appropriate sleep enhancement therapy will be in favor of the retention in treatment for opiate addicts. Our previous studies have shown that electroacupuncture (EA) is effective in suppressing morphine withdrawal syndrome. The aim of the present study is to investigate the effect of 2 and 100 Hz EA on the sleep disturbance during morphine withdrawal. Rats were made dependent on morphine by repeated morphine injections (escalating doses of 5–80 mg kg−1, subcutaneously, twice a day) for 5 days. EA of 2 or 100 Hz was given twice a day for 3 days, starting at 48 h after the last morphine injection. Electroencephalogram and electromyogram were monitored at the end of the first and the last EA treatments, respectively. Results showed that non-rapid eye movement (NREM) sleep, REM sleep and total sleep time decreased dramatically, while the sleep latency prolonged significantly during acute morphine withdrawal. Both 2 and 100 Hz EA produced a significant increase in NREM sleep, REM sleep and total sleep time. It was suggested that EA could be a potential treatment for sleep disturbance during morphine withdrawal