Sketch Me That Shoe

This project received support from the European Union’s Horizon 2020 research and innovation programme under grant agreement #640891, the Royal Society and Natural Science Foundation of China (NSFC) joint grant #IE141387 and #61511130081, and the China Scholarship Council (CSC). We gratefully acknowledge the support of NVIDIA Corporation for the donation of the GPUs used for this research

Cost-effective quaternion minimum mean square error estimation:From widely linear to four-channel processing

Widely linear estimation plays an important role in quaternion signal processing, as it caters for both proper and improper quaternion signals. However, widely linear algorithms are computationally expensive owing to the use of augmented variables and statistics. To reduce the computation cost while maintaining the performance level, we propose a four-channel estimation framework as an efficient alternative to quaternion widely linear estimation. This is achieved by using four linear models to estimate the four components of quaternion signals. We also show that any of the four channels is able to replace a strictly linear quaternion estimator when estimating strictly linear systems. The proposed method is shown to reduce computational complexity and provide more flexible algorithms, while preserving the physical meaning inherent in the quaternion domain. The proposed framework is next applied to quaternion minimum mean square error estimation to yield the reduced-complexity versions of the quaternion least mean square (QLMS), quaternion recursive least squares (QRLS), and quaternion nonlinear gradient decent (QNGD) algorithms. For the proposed QLMS algorithm, an adaptive step-size strategy is also explored. The effectiveness of the so introduced estimation techniques is validated by simulations on synthetic and real-world signals

Cumulative Attribute Space for Age and Crowd Density Estimation

A number of computer vision problems such as human age estimation, crowd density estimation and body/face pose (view angle) estimation can be formulated as a regression problem by learning a mapping function between a high dimensional vector-formed feature input and a scalarvalued output. Such a learning problem is made difficult due to sparse and imbalanced training data and large feature variations caused by both uncertain viewing conditions and intrinsic ambiguities between observable visual features and the scalar values to be estimated. Encouraged by the recent success in using attributes for solving classification problems with sparse training data, this paper introduces a novel cumulative attribute concept for learning a regression model when only sparse and imbalanced data are available. More precisely, low-level visual features extracted from sparse and imbalanced image samples are mapped onto a cumulative attribute space where each dimension has clearly defined semantic interpretation (a label) that captures how the scalar output value (e.g. age, people count) changes continuously and cumulatively. Extensive experiments show that our cumulative attribute framework gains notable advantage on accuracy for both age estimation and crowd counting when compared against conventional regression models, especially when the labelled training data is sparse with imbalanced sampling. 1

Trapped lipopolysaccharide and LptD intermediates reveal lipopolysaccharide translocation steps across the Escherichia coli outer membrane

Lipopolysaccharide (LPS) is a main component of the outer membrane of Gram-negative bacteria, which is essential for the vitality of most Gram-negative bacteria and plays a critical role for drug resistance. LptD/E complex forms a N-terminal LPS transport slide, a hydrophobic intramembrane hole and the hydrophilic channel of the barrel, for LPS transport, lipid A insertion and core oligosaccharide and O-antigen polysaccharide translocation, respectively. However, there is no direct evidence to confirm that LptD/E transports LPS from the periplasm to the external leaflet of the outer membrane. By replacing LptD residues with an unnatural amino acid p-benzoyl-L-phenyalanine (pBPA) and UV-photo-cross-linking in E.coli, the translocon and LPS intermediates were obtained at the N-terminal domain, the intramembrane hole, the lumenal gate, the lumen of LptD channel, and the extracellular loop 1 and 4, providing the first direct evidence and “snapshots” to reveal LPS translocation steps across the outer membrane

Robust control volume finite element methods for numerical wave tanks using extreme adaptive anisotropic meshes

Multiphase inertia‐dominated flow simulations, and free surface flow models in particular, continue to this day to present many challenges in terms of accuracy and computational cost to industry and research communities. Numerical wave tanks and their use for studying wave‐structure interactions are a good example. Finite element method (FEM) with anisotropic meshes combined with dynamic mesh algorithms has already shown the potential to significantly reduce the number of elements and simulation time with no accuracy loss. However, mesh anisotropy can lead to mesh quality‐related instabilities. This article presents a very robust FEM approach based on a control volume discretization of the pressure field for inertia dominated flows, which can overcome the typically encountered mesh quality limitations associated with extremely anisotropic elements. Highly compressive methods for the water‐air interface are used here. The combination of these methods is validated with multiphase free surface flow benchmark cases, showing very good agreement with experiments even for extremely anisotropic meshes, reducing by up to two orders of magnitude the required number of elements to obtain accurate solutions

Complete chloroplast genome sequence of Holoparasite Cistanche Deserticola (Orobanchaceae) reveals gene loss and horizontal gene transfer from Its host Haloxylon Ammodendron (Chenopodiaceae)

The central function of chloroplasts is to carry out photosynthesis, and its gene content and structure are highly conserved across land plants. Parasitic plants, which have reduced photosynthetic ability, suffer gene losses from the chloroplast (cp) genome accompanied by the relaxation of selective constraints. Compared with the rapid rise in the number of cp genome sequences of photosynthetic organisms, there are limited data sets from parasitic plants. The authors report the complete sequence of the cp genome of Cistanche deserticola, a holoparasitic desert species belonging to the family Orobanchaceae

Type 2 Diabetes in Xinjiang Uygur Autonomous Region, China

BACKGROUND: The aim of this study was to estimate the prevalence and distribution of type 2 diabetes and to determine the status of type 2 diabetes awareness, treatment, and control in Xinjiang, China. Our data came from the Cardiovascular Risk Survey (CRS) study designed to investigate the prevalence and risk factors for cardiovascular diseases in Xinjiang from October 2007 to March 2010. A total of 14 122 persons (5583 Hans, 4620 Uygurs, and 3919 Kazaks) completed the survey and examination. Diabetes was defined by the American Diabetes Association 2009 criteria. METHODOLOGY/PRINCIPAL FINDINGS: Overall, 9.26% of the Han, 6.23% of the Uygur, and 3.65% of the Kazak adults aged ≥35 years had diabetes. Among diabetes patients, only 53.0% were aware of their blood glucose level, 26.7% were taking hypoglycemic agents, and 10.4% achieved blood glucose control in Han, 35.8% were aware of their blood glucose level, 7.3% were taking hypoglycemic agents, and 3.13% achieved blood glucose control in Uygur, and 23.8% were aware of their blood glucose level, 6.3% were taking hypoglycemic agents, and 1.4% achieved blood glucose control in Kazak, respectively. CONCLUSIONS/SIGNIFICANCE: Our results indicate that diabetes is highly prevalent in Xinjiang. The percentages of those with diabetes who are aware, treated, and controlled are unacceptably low. These results underscore the urgent need to develop national strategies to improve prevention, detection, and treatment of diabetes in Xinjiang, the west China

Ruthenium oxide-carbon-based nanofiller-reinforced conducting polymer nanocomposites and their supercapacitor applications.

In this review article, we have presented for the first time the new applications of supercapacitor technologies and working principles of the family of RuO2-carbon-based nanofiller-reinforced conducting polymer nanocomposites. Our review focuses on pseudocapacitors and symmetric and asymmetric supercapacitors. Over the last years, the supercapacitors as a new technology in energy storage systems have attracted more and more attention. They have some unique characteristics such as fast charge/discharge capability, high energy and power densities, and long stability. However, the need for economic, compatible, and easy synthesis materials for supercapacitors have led to the development of RuO2-carbon-based nanofiller-reinforced conducting polymer nanocomposites with RuO2. Therefore, the aim of this manuscript was to review RuO2-carbon-based nanofiller-reinforced conducting polymer nanocomposites with RuO2 over the last 17 years