Video-based face recognition in color space by graph-based discriminant analysis

Video-based face recognition has attracted significant attention in many applications such as media technology, network security, human-machine interfaces, and automatic access control system in the past decade. The usual way for face recognition is based upon the grayscale image produced by combining the three color component images. In this work, we consider grayscale image as well as color space in the recognition process. For key frame extractions from a video sequence, the input video is converted to a number of clusters, each of which acts as a linear subspace. The center of each cluster is considered as the cluster representative. Also in this work, for comparing the key frames, the three popular color spaces RGB, YCbCr, and HSV are used for mathematical representation, and the graph-based discriminant analysis is applied for the recognition process. It is also shown that by introducing the intra-class and inter-class similarity graphs to the color space, the problem is changed to determining the color component combination vector and mapping matrix. We introduce an iterative algorithm to simultaneously determine the optimum above vector and matrix. Finally, the results of the three color spaces and grayscale image are compared with those obtained from other available methods. Our experimental results demonstrate the effectiveness of the proposed approach

Production of Soluble Human Vascular Endothelial Growth Factor VEGF-A(165)-Heparin Binding Domain in Escherichia coli.

We report a method for production of soluble heparin binding domain (HBD) of human vascular endothelial growth factor VEGF-A(165). Recombinant VEGF-A(165)-HBD that contains four disulphide bridges was expressed in specialised E. coli SHuffle cells and its activity has been confirmed through interactions with neuropilin and heparin. The ability to produce significant quantities of a soluble active form of VEGF-A(165)-HBD will enable further studies addressing the role of VEGF-A in essential processes such as angiogenesis, vasculogenesis and vascular permeability

Concurrent Learning Approach for Estimation of Pelvic Tilt from Anterior–Posterior Radiograph

Data Availability Statement: Dataset available on request from the authors.Accurate and reliable estimation of the pelvic tilt is one of the essential pre-planning factors for total hip arthroplasty to prevent common post-operative complications such as implant impingement and dislocation. Inspired by the latest advances in deep learning-based systems, our focus in this paper has been to present an innovative and accurate method for estimating the functional pelvic tilt (PT) from a standing anterior–posterior (AP) radiography image. We introduce an encoder–decoder-style network based on a concurrent learning approach called VGG-UNET (VGG embedded in U-NET), where a deep fully convolutional network known as VGG is embedded at the encoder part of an image segmentation network, i.e., U-NET. In the bottleneck of the VGG-UNET, in addition to the decoder path, we use another path utilizing light-weight convolutional and fully connected layers to combine all extracted feature maps from the final convolution layer of VGG and thus regress PT. In the test phase, we exclude the decoder path and consider only a single target task i.e., PT estimation. The absolute errors obtained using VGG-UNET, VGG, and Mask R-CNN are 3.04 ± 2.49, 3.92 ± 2.92, and 4.97 ± 3.87, respectively. It is observed that the VGG-UNET leads to a more accurate prediction with a lower standard deviation (STD). Our experimental results demonstrate that the proposed multi-task network leads to a significantly improved performance compared to the best-reported results based on cascaded networks.This research received no external funding

Cloning, purification and preliminary crystallographic analysis of cobalamin methyltransferases fromRhodobacter capsulatus

Of the 30 biosynthetic steps necessary for the production of cobalamin (vitamin B-12), eight involve the addition of S-adenosylmethionine-derived methyl groups to the tetrapyrrole framework. These eight methyl additions are catalysed by six canonical methyltransferase domains and one noncanonical methyltransferase domain. Recombinant forms of four methyltransferases from Rhodobacter capsulatus, CobJ, CobM, CobF and CobL, and of the C-terminal noncanonical domain of CobL (CobL-C) have been crystallized, some in more than one crystal form. Most of the crystals diffracted to beyond 2.5 A resolution and all are suitable for structure determination. Crystals of CobM and CobJ, which are involved in ring contraction, and of CobL, which is involved in two methylations and decarboxylation, are reported for the first time

An enzyme-trap approach allows isolation of intermediates in cobalamin biosynthesis

The biosynthesis of many vitamins and coenzymes has often proven difficult to elucidate owing to a combination of low abundance and kinetic lability of the pathway intermediates. Through a serial reconstruction of the cobalamin (vitamin B 12) pathway in Escherichia coli and by His tagging the terminal enzyme in the reaction sequence, we have observed that many unstable intermediates can be isolated as tightly bound enzyme-product complexes. Together, these approaches have been used to extract intermediates between precorrin-4 and hydrogenobyrinic acid in their free acid form and permitted the delineation of the overall reaction catalyzed by CobL, including the formal elucidation of precorrin-7 as a metabolite. Furthermore, a substrate-carrier protein, CobE, that can also be used to stabilize some of the transient metabolic intermediates and enhance their onward transformation, has been identified. The tight association of pathway intermediates with enzymes provides evidence for a form of metabolite channeling