Reversible Watermarking in Deep Convolutional Neural Networks for Integrity Authentication

Deep convolutional neural networks have made outstanding contributions in many fields such as computer vision in the past few years and many researchers published well-trained network for downloading. But recent studies have shown serious concerns about integrity due to model-reuse attacks and backdoor attacks. In order to protect these open-source networks, many algorithms have been proposed such as watermarking. However, these existing algorithms modify the contents of the network permanently and are not suitable for integrity authentication. In this paper, we propose a reversible watermarking algorithm for integrity authentication. Specifically, we present the reversible watermarking problem of deep convolutional neural networks and utilize the pruning theory of model compression technology to construct a host sequence used for embedding watermarking information by histogram shift. As shown in the experiments, the influence of embedding reversible watermarking on the classification performance is less than 0.5% and the parameters of the model can be fully recovered after extracting the watermarking. At the same time, the integrity of the model can be verified by applying the reversible watermarking: if the model is modified illegally, the authentication information generated by original model will be absolutely different from the extracted watermarking information.Comment: Accepted to ACM MM 202

Combination analysis of genome-wide association and transcriptome sequencing of residual feed intake in quality chickens

GO mapping for genes within the 50 bp flanking regions of the significant RFI-related SNPs. (XLS 31 kb

Polymorphisms of the IGF1R gene and their genetic effects on chicken early growth and carcass traits

<p>Abstract</p> <p>Background</p> <p>The insulin-like growth factor I receptor (IGF1R) has an important effect on growth, carcass, and meat quality traits in many species. However, few studies on associations of the <it>IGF1R </it>gene with growth and carcass traits have been reported in chickens. The objectives of the present study were to study the associations of the <it>IGF1R </it>gene with chicken early growth and carcass traits using a neutral test, variation scan of the gene, genetic diversity, linkage disequilibrium and association analyses.</p> <p>Results</p> <p>The tree generated from the amino acid sequences of 15 species showed that the <it>IGF1R </it>gene was conservative in the whole evolution among the mammalian animals and chickens. In a total of 10,818 bp of sequence, 70 single nucleotide polymorphisms were identified in the chicken <it>IGF1R </it>gene. The allelic and genotypic frequency distribution, genetic diversity and linkage disequilibrium of 18 single nucleotide polymorphisms (SNPs) in the Xinghua and White Recessive Rock chickens showed that six of them were possibly associated with growth traits. Association analyses showed that the A17299834G SNP was significantly associated with chicken carcass body weight, eviscerated weight with giblets, eviscerated weight, body weights at 28, 35, and 56 d of age, leg length at 56 d of age, and daily weight gain at 0–4 weeks. The haplotypes of the A17307750G and A17307494G were associated with early growth traits. The haplotypes of the A17299834G and C17293932T were significantly associated with most of the early growth traits and carcass traits.</p> <p>Conclusion</p> <p>There were rich polymorphisms in the chicken <it>IGF1R </it>gene. Several SNPs associated with chicken early growth traits and carcass traits were identified in the <it>IGF1R </it>gene by genetic diversity, linkage disequilibrium, and association analyses in the present study.</p

SNP mapping of QTL affecting growth and fatness on chicken GGA1

An F2 chicken population was established from a crossbreeding between a Xinghua line and a White Recessive Rock line. A total of 502 F2 chickens in 17 full-sib families from six hatches was obtained, and phenotypic data of 488 individuals were available for analysis. A total of 46 SNP on GGA1 was initially selected based on the average physical distance using the dbSNP database of NCBI. After the polymorphism levels in all F0 individuals (26 individuals) and part of the F1 individuals (22 individuals) were verified, 30 informative SNP were potentially available to genotype all F2 individuals. The linkage map was constructed using Cri-Map. Interval mapping QTL analyses were carried out. QTL for body weight (BW) of 35 d and 42 d, 49 d and 70 d were identified on GGA1 at 351–353 cM and 360 cM, respectively. QTL for abdominal fat weight was on GGA1 at 205 cM, and for abdominal fat rate at 221 cM. Two novel QTL for fat thickness under skin and fat width were detected at 265 cM and 72 cM, respectively

Genomic Insights Into the Multiple Factors Controlling Abdominal Fat Deposition in a Chicken Model

Genetic selection for an increased growth rate in meat-type chickens has been accompanied by excessive fat accumulation particularly in abdominal cavity. These progressed to indirect and often unhealthy effects on meat quality properties and increased feed cost. Advances in genomics technology over recent years have led to the surprising discoveries that the genome is more complex than previously thought. Studies have identified multiple-genetic factors associated with abdominal fat deposition. Meanwhile, the obesity epidemic has focused attention on adipose tissue and the development of adipocytes. The aim of this review is to summarize the current understanding of genetic/epigenetic factors associated with abdominal fat deposition, or as it relates to the proliferation and differentiation of preadipocytes in chicken. The results discussed here have been identified by different genomic approaches, such as QTL-based studies, the candidate gene approach, epistatic interaction, copy number variation, single-nucleotide polymorphism screening, selection signature analysis, genome-wide association studies, RNA sequencing, and bisulfite sequencing. The studies mentioned in this review have described multiple-genetic factors involved in an abdominal fat deposition. Therefore, it is inevitable to further study the multiple-genetic factors in-depth to develop novel molecular markers or potential targets, which will provide promising applications for reducing abdominal fat deposition in meat-type chicken

Identification and characterization of single nucleotide polymorphisms in 12 chicken growth-correlated genes by denaturing high performance liquid chromatography

The genes that are part of the somatotropic axis play a crucial role in the regulation of growth and development of chickens. The identification of genetic polymorphisms in these genes will enable the scientist to evaluate the biological relevance of such polymorphisms and to gain a better understanding of quantitative traits like growth. In the present study, 75 pairs of primers were designed and four chicken breeds, significantly differing in growth and reproduction characteristics, were used to identify single nucleotide polymorphisms (SNP) using the denaturing high performance liquid chromatography (DHPLC) technology. A total of 283 SNP were discovered in 31 897 base pairs (bp) from 12 genes of the growth hormone (GH), growth hormone receptor (GHR), ghrelin, growth hormone secretagogue receptor (GHSR), insulin-like growth factor I and II (IGF-I and -II), insulin-like growth factor binding protein 2 (IGFBP-2), insulin, leptin receptor (LEPR), pituitary-specific transcription factor-1 (PIT-1), somatostatin (SS), thyroid-stimulating hormone beta subunit (TSH-β). The observed average distances in bp between the SNP in the 5'UTR, coding regions (non- and synonymous), introns and 3'UTR were 172, 151 (473 and 222), 89 and 141 respectively. Fifteen non-synonymous SNP altered the translated precursors or mature proteins of GH, GHR, ghrelin, IGFBP-2, PIT-1 and SS. Fifteen indels of no less than 2 bps and 2 poly (A) polymorphisms were also observed in 9 genes. Fifty-nine PCR-RFLP markers were found in 11 genes. The SNP discovered in this study provided suitable markers for association studies of candidate genes for growth related traits in chickens

A Comparison of MERRA and NARR Reanalysis Datasets with the DOE ARM SGP Continuous Forcing data

In this study, the atmospheric state, precipitation, cloud fraction, and radiative fluxes from Modern Era Retrospective-analysis for Research and Applications (MERRA) and North American Regional Reanalysis (NARR) are collected and compared with the Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) continuous forcing during the period 1999-2001. For the atmospheric state, the three datasets have excellent agreement for the horizontal wind components and air temperature. NARR and ARM have generally good agreement for humidity, except for several biases in the PBL and in the upper troposphere. MERRA, on the other hand, suffers from a year-round negative bias in humidity except for the month of June. For the vertical pressure velocity, significant differences exist with the largest biases occurring during the spring upwelling and summer downwelling periods. Although NARR and MERRA share many resemblances to each other, ARM outperforms these reanalyses in terms of correlation with cloud fraction. Because the ARM forcing is constrained by observed precipitation that gives the adequate mass, heat, and moisture budgets, much of the precipitation (specifically during the late spring/early summer) is caused by smaller-scale forcing that is not captured by the reanalyses. Both NARR and MERRA capture the seasonal variation of CF observed by ARM radar-lidar and GOES with high correlations (0.92-0.78), but having negative biases of 14% and 3%, respectively. Compared to the ARM observations, MERRA shows a better agreement for both SW and LW fluxes except for LW-down (due to a negative bias in water vapor), NARR has significant positive bias for SW-down and negative bias for LW-down under clear- and all-sky conditions . The NARR biases result from a combination of too few clouds and a lack of sufficient extinction by aerosols and water vapor in the atmospheric column. The results presented here represent only one location for a limited time period, and more comparisons at different locations and longer time period are needed

The genetic effects of the dopamine D1 receptor gene on chicken egg production and broodiness traits

<p>Abstract</p> <p>Background</p> <p>The elevation of egg production and the inhibition of incubation behavior are the aims of modern poultry production. Prolactin (<it>PRL</it>) gene is confirmed to be critical for the onset and maintenance of these reproductive behaviors in birds. Through PRL, dopamine D1 receptor (DRD1) was also involved in the regulation of chicken reproductive behavior. However, the genetic effects of this gene on chicken egg production and broodiness have not been studied extensively. The objective of this research was to evaluate the genetic effects of the <it>DRD1 </it>gene on chicken egg production and broodiness traits.</p> <p>Results</p> <p>In this study, the chicken <it>DRD1 </it>gene was screened for the polymorphisms by cloning and sequencing and 29 variations were identified in 3,342 bp length of this gene. Seven single nucleotide polymorphism (SNPs) among these variations, including a non-synonymous mutation (A+505G, Ser169Gly), were located in the coding region and were chosen to analyze their association with chicken egg production and broodiness traits in 644 Ningdu Sanhuang individuals. Two SNPs, G+123A and C+1107T, were significantly associated with chicken broody frequency (P < 0.05). Significant association was also found between the G+1065A - C+1107T haplotypes and chicken broody frequency (P < 0.05). In addition, the haplotypes of G+123A and T+198C were significantly associated with weight of first egg (EW) (P = 0.03). On the other hand, the distribution of the <it>DRD1 </it>mRNA was observed and the expression difference was compared between broodiness and non-broodiness chickens. The <it>DRD1 </it>mRNA was predominantly expressed in subcutaneous fat and abdominal fat of non-broodiness chicken, and then in heart, kidney, oviduct, glandular stomach, hypothalamus, and pituitary. In subcutaneous fat and abdominal fat, the level of non-broodiness was 26 to 28 times higher than that of broodiness. In pituitary, it was 5-fold higher. In heart, oviduct, and kidney, a 2-3 times decrease from non-broodiness to broodiness was displayed. In glandular stomach and hypothalamus, the level seen in non-broodiness and broodiness was almost the same.</p> <p>Conclusion</p> <p>The polymorphisms of the <it>DRD1 </it>gene and their haplotypes were associated with chicken broody frequency and some egg production traits. The mRNA distribution was significant different between broodiness and non-broodiness chickens.</p