Gang Tang

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Epidemiologic studies evaluating the association of whole-grain intake with risk for coronary heart disease (CHD) have produced inconsistent results. The aim of this meta-analysis was to summarize the evidence from observed studies regarding the association between whole-grain intake and risk for CHD. Pertinent studies were identified by searching the Web(More)
OBJECTIVE Leptin, a multifunctional peptide hormone encoded by the obese (ob) gene, plays an important role in modulating lipid metabolism and energy equilibrium. Leptin reportedly acts as a cell growth factor and enhances the proliferation of various tumors. We investigated the effect of leptin on aromatase (P450arom) expression and estradiol (E2)(More)
The Shannon sampling principle requires substantial amounts of data to ensure the accuracy of on-line monitoring of roller bearing fault signals. Challenges are often encountered as a result of the cumbersome data monitoring, thus a novel method focused on compressed vibration signals for detecting roller bearing faults is developed in this study.(More)
Glypican‑3 (GPC3) is a membrane heparan sulfate proteoglycan involved in cell proliferation, differentiation, adhesion, migration and the development of the majority of mesodermal tissues and organs. GPC3 has been found to be important for the occurrence and development of hepatocellular carcinoma (HCC). Therefore,(More)
A Compound fault signal usually contains multiple characteristic signals and strong confusion noise, which makes it difficult to separate week fault signals from them through conventional ways, such as FFT-based envelope detection, wavelet transform or empirical mode decomposition individually. In order to improve the compound faults diagnose of rolling(More)
The traditional approaches for condition monitoring of roller bearings are almost always achieved under Shannon sampling theorem conditions, leading to a big-data problem. The compressed sensing (CS) theory provides a new solution to the big-data problem. However, the vibration signals are insufficiently sparse and it is difficult to achieve sparsity using(More)
In the condition monitoring of roller bearings, the measured signals are often compounded due to the unknown multi-vibration sources and complex transfer paths. Moreover, the sensors are limited in particular locations and numbers. Thus, this is a problem of underdetermined blind source separation for the vibration sources estimation, which makes it(More)