Genetic variation at Exon2 of TLR4 gene and its association with resistant traits in chicken

This study was conducted to analyze the polymorphisms of chicken Toll-like receptors 4(TLR4) gene and aimed to provide a theoretical foundation for a further research on correlation between chicken TLR4 gene and disease resistance. Genetic variations at exon 2 of TLR4 gene in 14 chicken breeds and the red jungle fowl were detected by PCR-SSCP method and two alleles and three genotypes were found, Tibetan chicken and red jungle fowl only had BB genotype, while the others presented three genotypes of AA, BB and AB. Sequencing results showed two mutations, G114A and G142A, located at exon 2 of TLR4 gene. The results of Chi square test showed that all populations, except Xianju chicken, were in accordance with Hardy-Weinberg equilibrium at this locus (P > 0.05). According to analysis of population genetic variation, all the populations were at moderate polymorphism (0.25 < PIC < 0.5) except red jungle fowl and Tibetan chicken (PIC = 0). The study demonstrated that there were differences of normal anti-disease ability in Chinese indigenous chicken breeds and appeared no significant correlation with body size, product type and geographical location. The associated analysis of results showed that the SNPs of TLR4 gene in the study were not linked with potential major loci or genes affecting some resistant traits.Key words: Chicken, TLR4 gene, polymorphism, resistant traits

3D Geometric Analysis of Tubular Objects based on Surface Normal Accumulation

This paper proposes a simple and efficient method for the reconstruction and extraction of geometric parameters from 3D tubular objects. Our method constructs an image that accumulates surface normal information, then peaks within this image are located by tracking. Finally, the positions of these are optimized to lie precisely on the tubular shape centerline. This method is very versatile, and is able to process various input data types like full or partial mesh acquired from 3D laser scans, 3D height map or discrete volumetric images. The proposed algorithm is simple to implement, contains few parameters and can be computed in linear time with respect to the number of surface faces. Since the extracted tube centerline is accurate, we are able to decompose the tube into rectilinear parts and torus-like parts. This is done with a new linear time 3D torus detection algorithm, which follows the same principle of a previous work on 2D arc circle recognition. Detailed experiments show the versatility, accuracy and robustness of our new method.Comment: in 18th International Conference on Image Analysis and Processing, Sep 2015, Genova, Italy. 201

Comparison of total variation algorithms for electrical impedance tomography

The applications of total variation (TV) algorithms for electrical impedance tomography (EIT) have been investigated. The use of the TV regularisation technique helps to preserve discontinuities in reconstruction, such as the boundaries of perturbations and sharp changes in conductivity, which are unintentionally smoothed by traditional l2 norm regularisation. However, the non-differentiability of TV regularisation has led to the use of different algorithms. Recent advances in TV algorithms such as the primal dual interior point method (PDIPM), the linearised alternating direction method of multipliers (LADMM) and the spilt Bregman (SB) method have all been demonstrated successful EIT applications, but no direct comparison of the techniques has been made. Their noise performance, spatial resolution and convergence rate applied to time difference EIT were studied in simulations on 2D cylindrical meshes with different noise levels, 2D cylindrical tank and 3D anatomically head-shaped phantoms containing vegetable material with complex conductivity. LADMM had the fastest calculation speed but worst resolution due to the exclusion of the second-derivative; PDIPM reconstructed the sharpest change in conductivity but with lower contrast than SB; SB had a faster convergence rate than PDIPM and the lowest image errors

The role of insulin receptor substrate 2 in hypothalamic and beta cell function

Insulin receptor substrate 2 (Irs2) plays complex roles in energy homeostasis. We generated mice lacking Irs2 in beta cells and a population of hypothalamic neurons (RIPCreIrs2KO), in all neurons (NesCreIrs2KO), and in proopiomelanocortin neurons (POMCCreIrs2KO) to determine the role of Irs2 in the CNS and beta cell. RIPCreIrs2KO mice displayed impaired glucose tolerance and reduced P cell mass. Overt diabetes did not ensue, because beta cells escaping Cre-mediated recombination progressively populated islets. RIPCreIrs2KO and NesCreIrs2KO mice displayed hyperphagia, obesity, and increased body length, which suggests altered melanocortin action. POMCCreIrs2KO mice did not display this phenotype. RIPCreIrs2KO and NesCreIrs2KO mice retained leptin sensitivity, which suggests that CNS Irs2 pathways are not required for leptin action. NesCreIrs2KO and POMCCreIrs2KO mice did not display reduced beta cell mass, but NesCreIrs2KO mice displayed mild abnormalities of glucose homeostasis. RIPCre neurons did not express POMC or neuropeptide Y. Insulin and a melanocortin agonist depolarized RIPCre neurons, whereas leptin was ineffective. Insulin hyperpolarized and leptin depolarized POMC neurons. Our findings demonstrate a critical role for IRS2 in beta cell and hypothalamic function and provide insights into the role of RIPCre neurons, a distinct hypothalamic neuronal population, in growth and energy homeostasis

Region Graph Embedding Network for Zero-Shot Learning

© 2020, Springer Nature Switzerland AG. Most of the existing Zero-Shot Learning (ZSL) approaches learn direct embeddings from global features or image parts (regions) to the semantic space, which, however, fail to capture the appearance relationships between different local regions within a single image. In this paper, to model the relations among local image regions, we incorporate the region-based relation reasoning into ZSL. Our method, termed as Region Graph Embedding Network (RGEN), is trained end-to-end from raw image data. Specifically, RGEN consists of two branches: the Constrained Part Attention (CPA) branch and the Parts Relation Reasoning (PRR) branch. CPA branch is built upon attention and produces the image regions. To exploit the progressive interactions among these regions, we represent them as a region graph, on which the parts relation reasoning is performed with graph convolutions, thus leading to our PRR branch. To train our model, we introduce both a transfer loss and a balance loss to contrast class similarities and pursue the maximum response consistency among seen and unseen outputs, respectively. Extensive experiments on four datasets well validate the effectiveness of the proposed method under both ZSL and generalized ZSL settings

Lower hybrid current drive and ion cyclotron range of frequencies heating experiments in H-mode plasmas in experimental advanced superconducting Tokomak

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LHCD and ICRF heating experiments in H-mode plasmas on EAST

An ICRF system with power up to 6.0 MW and a LHCD system up to 4MW have been applied for heating and current drive experiments on EAST. Intensive lithium wall coating was intensively used to reduce particle recycling and Hydrogen concentration in Deuterium plasma, which is needed for effective ICRF and LHCD power absorption in high density plasmas. Significant progress has been made with ICRF heating and LHW current drive for realizing the H-mode plasma operation in EAST. In 2010, H-mode was generated and sustained by LHCD alone, where lithium coating and gas puffing launcher mouth were applied to improve the LHCD power coupling and penetration into the core plasmas at high density of H-modes. During the last two experimental campaigns, ICRF Heating experiments were carried out at the fixed frequency of 27MHz, achieving effective ions and electrons heating with the H Minority Heating (H-MH) mode, where electrons are predominantly heated by collisions with high energy minority ions. The H-MH mode gave the best plasma performance, and realized H-mode alone in 2012. Combination of ICRF and LHW power injection generated the H-mode plasmas with various ELMy characteristics. The first successful application of the ICRF Heating in the D (He3) plasma was also achieved. The progress on ICRF heating, LHCD experiments and their application in achieving H-mode operation from last two years will be discussed in this report