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The clinically used glitazones (rosiglitazone and pioglitazone) for type 2 diabetes mellitus therapy have been linked to serious side effects such as fluid retention, congestive heart failure, weight gain, bone loss, and an increased risk of bladder cancer. The complete activation of PPAR-γ receptors in target tissues is linked to these effects. Many studies have demonstrated that partial PPAR-γ activators (GW0072, PAT5A, GQ16) give equivalent therapeutic benefits to full PPAR-γ agonists without the associated side effects. These breakthroughs cleared the path for the development of partial agonists or selective PPAR-γ modulators (SPPARγMs). This study combined pharmacophore modeling, molecular docking, and an adipogenesis experiment to identify thiazolidine analogs as SPPARMs/partial agonists. A custom library of 220 molecules was created and virtual screened to discover 90 compounds as SPPARγMs/ partial agonists. The chosen eight compounds were synthesized and tested for adipogenesis using 3T3L1 cell lines. These compounds' partial agonistic activity was evaluated in 3T3L1 cell lines by comparing their capacity to stimulate PPAR-γ mediated adipogenesis to that of a full agonist, rosiglitazone. The findings of the adipogenesis experiment demonstrate that all eight compounds examined had a partial potential to stimulate adipogenesis when compared to the full agonist, rosiglitazone. The current investigation identified eight possible PPAR-γ partial agonists or SPPARγMs that may be effective in the treatment of type 2 diabetes mellitus.

With the continuous uptick in world energy consumption, green energy plays an increasingly significant role in alleviating energy depletion and promoting economic development. Due to regional differences, transportation restrictions, national policies and other reasons, there is a mismatch between green energy needs and resources across regions in China, which leads to misallocation of capital and labor between heavily polluting and nonpolluting enterprises. In this context, this paper first proposes a new measurement method: namely, the capital and labor mismatch index. Panel data of 30 Chinese provinces from 2008 to 2018 are utilized to calculate the index. The results show significant resource mismatch across provinces in China. In addition, we extend the green Solow model by combining capital mismatch, technological progress and environmental regulation into a dynamic analysis framework of economic growth. The empirical results show that all three factors have significant spatial spillover effects. Specifically, capital misallocation exerts a strong negative impact on economic growth, while the other factors increase it.

A new method is proposed to estimate snow depth by using observations of the GNSS single-frequency signal collected by a ground-based receiver. The proposed method utilizes the pseudorange and carrier phase observations to form the geometry-free combination. Based on mathematical formulas of the amplitude attenuation factor, the pseudorange multipath error, and the carrier phase multipath error, a function is derived serving as the theoretical model that describes the relationship between the antenna height and the peak frequency of a series of function values associated with the range of satellite elevation angles. In the observation data processing stage, the moving average filtering method is used to remove the ionospheric delay from the combined observation series, followed by spectrum analysis to obtain the peak frequency, which is used to determine the antenna height and hence snow depth based on the theoretical model. A weighting method is proposed to combine individual snow depth estimates related to the use of signals of individual satellites to enhance the estimation accuracy. Each weighting coefficient is proportional to the maximum of the power spectral density of the combined observation series. The proposed method is substantiated by simulations and observations from geodetic-grade receivers, which can process multi-constellations and multi-frequency GNSS signals. Two field GNSS data sets collected in Heilongjing, China, and Colorado, USA, were used to evaluate the method. The results show that the root-mean-square error of GPS, BDS, and Galileo-based snow depth estimations is in the range of 2–6 cm when the topography around the GNSS receiver is flat.

In optical tracking system, the macropixels method in which macropixels are used to estimate initial target region and to accurately localize target by choosing appropriate weight function and ratio function has stronger anti-noise ability than the general center of mass for unsymmetry target with low SNR. It is proved that the method can improve precision and speed efficiently: the centroid error is only 0.38 pixel when SNR is −5dB, and processing speed is 20 frame/s for the unsymmetry target of 4 × 4 pixels in infrared spot image of 128 × 128 pixels.