A Novel Self-Intersection Penalty Term for Statistical Body Shape Models and Its Applications in 3D Pose Estimation

Statistical body shape models are widely used in 3D pose estimation due to their low-dimensional parameters representation. However, it is difficult to avoid self-intersection between body parts accurately. Motivated by this fact, we proposed a novel self-intersection penalty term for statistical body shape models applied in 3D pose estimation. To avoid the trouble of computing self-intersection for complex surfaces like the body meshes, the gradient of our proposed self-intersection penalty term is manually derived from the perspective of geometry. First, the self-intersection penalty term is defined as the volume of the self-intersection region. To calculate the partial derivatives with respect to the coordinates of the vertices, we employed detection rays to divide vertices of statistical body shape models into different groups depending on whether the vertex is in the region of self-intersection. Second, the partial derivatives could be easily derived by the normal vectors of neighboring triangles of the vertices. Finally, this penalty term could be applied in gradient-based optimization algorithms to remove the self-intersection of triangular meshes without using any approximation. Qualitative and quantitative evaluations were conducted to demonstrate the effectiveness and generality of our proposed method compared with previous approaches. The experimental results show that our proposed penalty term can avoid self-intersection to exclude unreasonable predictions and improves the accuracy of 3D pose estimation indirectly. Further more, the proposed method could be employed universally in triangular mesh based 3D reconstruction

Effects of Drought Stress and Postdrought Rewatering on Winter Wheat: A Meta-Analysis

Drought is a major stress that restricts the growth and development of winter wheat (Triticum aestivum L.), and recovery after drought is the key to coping with adversity. So, we used a meta-analysis to quantitatively evaluate the responses of winter wheat to drought stress and rewatering and investigated the differences caused by several moderators (e.g., stress intensity, treatment durations, growth stages, planting methods, and experimental areas). The results show that drought can cause many negative effects on winter wheat. However, in most cases, rewatering can offset these adverse effects. Winter wheat under short-term or mild stress was less affected, and rewatering can restore it to the control level. Net photosynthetic rate (Pn), transpiration rate (Tr), and stomatal conductance (gs) are sensitive to environmental water change. Drought reduced the quantum yield of electron transport (ΦPSII), with insignificant effects on the efficiency of PSII (Fv/Fm). Additionally, the responses to drought and rewatering also varied with different growth stages. The regreening stage and the anthesis-filling stage are both critical water management periods. Rewatering after the jointing stage had no significant effect on leaf area (LA) and plant height (PH). The drought tolerance and recovery ability of field-grown wheat were better than those of pot-grown wheat. Winter wheat planted on the Loess Plateau was less affected than that on the Huang-Huai-Hai Plain and the Middle–Lower Yangtze Plain. Overall, different moderators may lead to different degrees of responsiveness of wheat to drought stress and postdrought rewatering. This study provides a reference for winter wheat to cope with drought stress and a useful guidance to wheat breeding programs

A Novel Self-Intersection Penalty Term for Statistical Body Shape Models and Its Applications in 3D Pose Estimation

Statistical body shape models are widely used in 3D pose estimation due to their low-dimensional parameters representation. However, it is difficult to avoid self-intersection between body parts accurately. Motivated by this fact, we proposed a novel self-intersection penalty term for statistical body shape models applied in 3D pose estimation. To avoid the trouble of computing self-intersection for complex surfaces like the body meshes, the gradient of our proposed self-intersection penalty term is manually derived from the perspective of geometry. First, the self-intersection penalty term is defined as the volume of the self-intersection region. To calculate the partial derivatives with respect to the coordinates of the vertices, we employed detection rays to divide vertices of statistical body shape models into different groups depending on whether the vertex is in the region of self-intersection. Second, the partial derivatives could be easily derived by the normal vectors of neighboring triangles of the vertices. Finally, this penalty term could be applied in gradient-based optimization algorithms to remove the self-intersection of triangular meshes without using any approximation. Qualitative and quantitative evaluations were conducted to demonstrate the effectiveness and generality of our proposed method compared with previous approaches. The experimental results show that our proposed penalty term can avoid self-intersection to exclude unreasonable predictions and improves the accuracy of 3D pose estimation indirectly. Further more, the proposed method could be employed universally in triangular mesh based 3D reconstruction

Engineering an electroactive Escherichia coli for the microbial electrosynthesis of succinate from glucose and CO2

Abstract Background Electrochemical energy is a key factor of biosynthesis, and is necessary for the reduction or assimilation of substrates such as CO2. Previous microbial electrosynthesis (MES) research mainly utilized naturally electroactive microbes to generate non-specific products. Results In this research, an electroactive succinate-producing cell factory was engineered in E. coli T110(pMtrABC, pFccA-CymA) by expressing mtrABC, fccA and cymA from Shewanella oneidensis MR-1, which can utilize electricity to reduce fumarate. The electroactive T110 strain was further improved by incorporating a carbon concentration mechanism (CCM). This strain was fermented in an MES system with neutral red as the electron carrier and supplemented with HCO3 +, which produced a succinate yield of 1.10 mol/mol glucose—a 1.6-fold improvement over the parent strain T110. Conclusions The strain T110(pMtrABC, pFccA-CymA, pBTCA) is to our best knowledge the first electroactive microbial cell factory engineered to directly utilize electricity for the production of a specific product. Due to the versatility of the E. coli platform, this pioneering research opens the possibility of engineering various other cell factories to utilize electricity for bioproduction