With the powerfulness of convolution neural networks (CNN), CNN based face reconstruction has recently shown promising performance in reconstructing detailed face shape from 2D face images. The success of CNN-based methods relies on a large number of labeled data. The state-of-the-art synthesizes such data using a coarse morphable face model, which however has difficulty to generate detailed photo-realistic images of faces (with wrinkles). This paper presents a novel face data generation method. Specifically, we render a large number of photo-realistic face images with different attributes based on inverse rendering. Furthermore, we construct a fine-detailed face image dataset by transferring different scales of details from one image to another. We also construct a large number of video-type adjacent frame pairs by simulating the distribution of real video data. With these nicely constructed datasets, we propose a coarse-to-fine learning framework consisting of three convolutional networks. The networks are trained for real-time detailed 3D face reconstruction from monocular video as well as from a single image. Extensive experimental results demonstrate that our framework can produce high-quality reconstruction but with much less computation time compared to the state-of-the-art. Moreover, our method is robust to pose, expression and lighting due to the diversity of data.

Background and AimsSanqi ginseng (Panax notoginseng) growth is often hampered by replant failure. In this study, we aimed to examine the role of autotoxicity in Sanqi replant failures and assess the role of ginsenosides in autotoxicity.MethodsThe autotoxicities were measured using seedling emergence bioassays and root cell vigor staining. The ginsenosides in the roots, soils, and root exudates were identified with HPLC-MS.ResultsThe seedling emergence and survival rate decreased significantly with the continuous number of planting years from one to three years. The root exudates, root extracts, and extracts from consecutively cultivated soils also showed significant autotoxicity against seedling emergence and growth. Ginsenosides, including R1, Rg1, Re, Rb1, Rb3, Rg2, and Rd, were identified in the roots and consecutively cultivated soil. The ginsenosides, Rg1, Re, Rg2, and Rd, were identified in the root exudates. Furthermore, the ginsenosides, R1, Rg1, Re, Rg2, and Rd, caused autotoxicity against seedling emergence and growth and root cell vigor at a concentration of 1.0 µg/mL.ConclusionOur results demonstrated that autotoxicity results in replant failure of Sanqi ginseng. While Sanqi ginseng consecutively cultivated, some ginsenosides can accumulate in rhizosphere soils through root exudates or root decomposition, which impedes seedling emergence and growth.

These results suggest that in prediabetic adults, acute exercise has an immediate and intensity-dependent effect on improving postprandial glycemia and insulin sensitivity.

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Women with T1D have glycemic variability changes that are specific to the individual and are linked to phase of cycle. An increased risk of hyperglycemia was observed during periovulation and early luteal phases compared to the early follicular phase; these changes appear to be associated with decreased insulin sensitivity during the luteal phase.

The CGP has the potential to enable health care providers, investigators and patients to better understand the components of glycemic control and the effect of various interventions on the individual elements of that control. This can be done on a daily, weekly, or monthly basis. It also allows direct comparison of the effects on different interventions among clinical trials which is not possible using A1C alone. This new composite metric approach requires validation to determine if it provides a better predictor of long-term outcomes than A1C and/or better predictor of severe hypoglycemia than the low blood glucose index (LBGI).

Background and aims Ginsenosides are the main bioactive components of Panax plants which could be secreted by root and show autotoxicity to root cells or promote the growth of soil-borne pathogens. However, comprehensive understanding of the effect of ginsenosides on soil microbiota is still lacking. Methods The ginsenosides in root exudates of P. notoginseng were quantified and exogenous ginsenosides on soil microbiota were tested using 16S rRNA and ITS gene tag sequencing. Then its underlying mechanism was deciphered through studying effects of ginsenosides on growth of the ginsenoside-modified culturable fungi and bacteria as well as the relationships between these fungi and bacteria. Results Exogenous root exudates and mixtures of Rg 1 + Rb 1 + Rd had similar ability to drive the change of soil microbiota. Further studies demonstrated that Rg 1 + Rb 1 + Rd mixture could enrich or suppress special fungi and bacteria to modify soil community through differential utilization of carbon source during the early stage (30 days), followed by antagonism between ginsenoside-modified fungi and bacteria to determine soil microbial community modification at later stage (60 and 90 days). Conclusions Ginsenosides were the main substances in exogenous root exudates of P. notoginseng that drove the change in soil microbiota, mediating the special interaction between the plant and the microbiota.