Generative Model with Coordinate Metric Learning for Object Recognition Based on 3D Models

Given large amount of real photos for training, Convolutional neural network shows excellent performance on object recognition tasks. However, the process of collecting data is so tedious and the background are also limited which makes it hard to establish a perfect database. In this paper, our generative model trained with synthetic images rendered from 3D models reduces the workload of data collection and limitation of conditions. Our structure is composed of two sub-networks: semantic foreground object reconstruction network based on Bayesian inference and classification network based on multi-triplet cost function for avoiding over-fitting problem on monotone surface and fully utilizing pose information by establishing sphere-like distribution of descriptors in each category which is helpful for recognition on regular photos according to poses, lighting condition, background and category information of rendered images. Firstly, our conjugate structure called generative model with metric learning utilizing additional foreground object channels generated from Bayesian rendering as the joint of two sub-networks. Multi-triplet cost function based on poses for object recognition are used for metric learning which makes it possible training a category classifier purely based on synthetic data. Secondly, we design a coordinate training strategy with the help of adaptive noises acting as corruption on input images to help both sub-networks benefit from each other and avoid inharmonious parameter tuning due to different convergence speed of two sub-networks. Our structure achieves the state of the art accuracy of over 50\% on ShapeNet database with data migration obstacle from synthetic images to real photos. This pipeline makes it applicable to do recognition on real images only based on 3D models.Comment: 14 page

Pyrite-Type CoS2 Nanoparticles Supported on Nitrogen-Doped Graphene for Enhanced Water Splitting

It is extremely meaningful to develop cheap, highly efficient, and stable bifunctional electrocatalysts for both hydrogen and oxygen evolution reactions (HER and OER) to promote large-scale application of water splitting technology. Herein, we reported the preparation of CoS2 nanoparticles supported on nitrogen-doped graphene (CoS2@N-GN) by one-step hydrothermal method and the enhanced electrochemical efficacy for catalyzing hydrogen and oxygen in water electrolysis. The CoS2@N-GN composites are composed of nitrogen-doped graphene and CoS2 nanocrystals with the average size of 73.5 nm. Benefitting from the improved electronic transfer and synergistic effect, the as-prepared CoS2@N-GN exhibits remarkable OER and HER performance in 1.0 M KOH, with overpotentials of 243 mV for OER and 204 mV for HER at 10 mA cm−2, and the corresponding Tafel slopes of 51.8 and 108 mV dec−1, respectively. Otherwise, the CoS2@N-GN hybrid also presents superior long-term catalytic durability. Moreover, an alkaline water splitting device assembled by CoS2@N-GN as both anode and cathode can achieve a low cell voltage of 1.53 V at 60 °C with a high faraday efficiency of 100% for overall water splitting. The tremendously enhanced electrochemical behaviors arise from favorable factors including small sized, homogenously dispersed novel CoS2 nanocrystals and coupling interaction with the underlying conductive nitrogen-doped graphene, which would provide insight into the rational design of transition metal chalcogenides for highly efficient and durable hydrogen and oxygen-involved electrocatalysis

Finishing the euchromatic sequence of the human genome

The sequence of the human genome encodes the genetic instructions for human physiology, as well as rich information about human evolution. In 2001, the International Human Genome Sequencing Consortium reported a draft sequence of the euchromatic portion of the human genome. Since then, the international collaboration has worked to convert this draft into a genome sequence with high accuracy and nearly complete coverage. Here, we report the result of this finishing process. The current genome sequence (Build 35) contains 2.85 billion nucleotides interrupted by only 341 gaps. It covers ∼99% of the euchromatic genome and is accurate to an error rate of ∼1 event per 100,000 bases. Many of the remaining euchromatic gaps are associated with segmental duplications and will require focused work with new methods. The near-complete sequence, the first for a vertebrate, greatly improves the precision of biological analyses of the human genome including studies of gene number, birth and death. Notably, the human enome seems to encode only 20,000-25,000 protein-coding genes. The genome sequence reported here should serve as a firm foundation for biomedical research in the decades ahead

A review of electrolyte materials and compositions for electrochemical supercapacitors

Electrolytes have been identified as some of the most influential components in the performance of electrochemical supercapacitors (ESs), which include: electrical double-layer capacitors, pseudocapacitors and hybrid supercapacitors. This paper reviews recent progress in the research and development of ES electrolytes. The electrolytes are classified into several categories, including: aqueous, organic, ionic liquids, solid-state or quasi-solid-state, as well as redox-active electrolytes. Effects of electrolyte properties on ES performance are discussed in detail. The principles and methods of designing and optimizing electrolytes for ES performance and application are highlighted through a comprehensive analysis of the literature. Interaction among the electrolytes, electro-active materials and inactive components (current collectors, binders, and separators) is discussed. The challenges in producing high-performing electrolytes are analyzed. Several possible research directions to overcome these challenges are proposed for future efforts, with the main aim of improving ESs' energy density without sacrificing existing advantages (e.g., a high power density and a long cycle-life) (507 references).Peer reviewed: YesNRC publication: Ye