A new remote data integrity checking scheme for cloud storage

Cloud storage services enable user to enjoy high-capacity and high-quality storage with less overhead, but it also brings many potential threats, for example, data integrality, data availability and so on. In this paper, we propose a new remote integrality and availability checking scheme for cloud storage. This new scheme can check mass file\u27s integrality and availability with less storage, computation and communication resource. The new scheme also supports data dynamic update, public verifiability and privacy preserving

The development of a rapid SYBR one step real-time RT-PCR for detection of porcine reproductive and respiratory syndrome virus

<p>Abstract</p> <p>Background</p> <p>Prompt detection of PRRSV in the field samples is important for effective PRRS control, thereby reducing the potentially serious economic damage which can result from an outbreak. In this study, a rapid SYBR-based, one step real-time RT-PCR quantitative reverse transcription PCR (qRT-PCR) has been developed for the detection of porcine reproductive and respiratory syndrome virus (PRRSV). Primers were designed based on the sequence of highly conservative region of PRRSV N gene.</p> <p>Results</p> <p>The sensitivity of the real-time qRT-PCR assay was achieved through PRRSV ch-1a RNA for the generation of a standard curve. The detection limit of the assay was found to be 9.6 RNA copies per reaction mixture. This assay had excellent intra- and inter-assay reproducibility as in total 65 field samples were screened for the presence of PRRSV by conventional RT-PCR in parallel with qRT-PCR, and the detection rate increased from 60.0% to 76.9%. Moreover, the specificity result indicated that this assay could reliably differentiate PRRSV from the other swine viral diseases, such as classical swine fever virus (CSFV), swine vesicular disease virus (SVDV) and vesicular exanthema of swine virus (VESV).</p> <p>Conclusion</p> <p>The real-time qRT-PCR assay described in this report allows the rapid, specific and sensitive laboratory detection of PRRSV in field samples.</p

Serodiagnosis of sheeppox and goatpox using an indirect ELISA based on synthetic peptide targeting for the major antigen P32

<p>Abstract</p> <p>Background</p> <p>Sheeppoxvirus (SPPV), goatpoxvirus (GTPV) and lumpy skin disease virus (LSDV) of cattle belong to the <it>Capripoxvirus </it>genus of the <it>Poxviridae </it>family and can cause significant economic losses in countries where they are endemic. Despite the considerable threat that these viruses pose to livestock production and global trade in sheep, goats, cattle and their products, convenient and effective serodiagnostic tools are not readily available. Toward this goal, two synthetic peptides corresponding to the major antigen P32 were synthesized. These synthetic peptides were then used as antigen to develop an ELISA method to detect anti-SPPV and GTPV antibodies.</p> <p>Results</p> <p>The results indicated that the optimal concentration of coated recombinant antigen was 0.2 μg per well for a serum dilution of 1:10. The ELISA performed favorably when sera from sheep immunized experimentally were tested.</p> <p>Conclusion</p> <p>This assay offers the prospect of synthetic peptide as antigens for indirect ELISA to detect SPPV and GTPV antibody in sheep and goat sera.</p

A High-Accuracy Algorithm for Surface Defect Detection of Steel Based on DAG-SVM

The quality of the steel surface is a crucial parameter. An improved method based on machine vision for steel surface defects detection is proposed. The experiment is based on 20 images for each of 6 distinct steel defects, a total of 120 defective images achieved from the detection system. 128 different features are extracted from the images and feature dimensions are reduced by the principle component analysis (PCA) based on the sample correlation coefficient matrix. Hierarchical clustering by Euclidean distance is implemented to find defect characteristics differentiation, the steel surface defects are classified based on directed acyclic graph support vector machine (DAG-SVM). The experimental results indicate that this method can recognize more than 98 % of the steel surface defects at a faster speed that can meet the demands on the steel surface quality online detection

A High-Accuracy Algorithm for Surface Defect Detection of Steel Based on DAG-SVM

The quality of the steel surface is a crucial parameter. An improved method based on machine vision for steel surface defects detection is proposed. The experiment is based on 20 images for each of 6 distinct steel defects, a total of 120 defective images achieved from the detection system. 128 different features are extracted from the images and feature dimensions are reduced by the principle component analysis (PCA) based on the sample correlation coefficient matrix. Hierarchical clustering by Euclidean distance is implemented to find defect characteristics differentiation, the steel surface defects are classified based on directed acyclic graph support vector machine (DAG-SVM). The experimental results indicate that this method can recognize more than 98 % of the steel surface defects at a faster speed that can meet the demands on the steel surface quality online detection

Association Between the Methylation Statuses at CpG Sites in the Promoter Region of the SLCO1B3, RNA Expression and Color Change in Blue Eggshells in Lushi Chickens

The formation mechanism underlying the blue eggshell characteristic has been discovered in birds, and SLCO1B3 is the key gene that regulates the blue eggshell color. Insertion of an endogenous retrovirus, EAV-HP, in the SLCO1B3 5′ flanking region promotes SLCO1B3 expression in the chicken shell gland, and this expression causes bile salts to enter the shell gland, where biliverdin is secreted into the eggshell, forming a blue shell. However, at different laying stages of the same group of chickens, the color of the eggshell can vary widely, and the molecular mechanism underlying the eggshell color change remains unknown. Therefore, to reveal the molecular mechanism of the blue eggshell color variations, we analyzed the change in the eggshell color during the laying period. The results indicated that the eggshell color in Lushi chickens can be divided into three stages: 20–25 weeks for dark blue, 26–45 weeks for medium blue, and 46–60 weeks for light blue. We further investigated the expression and methylation levels of the SLCO1B3 gene at eight different weeks, finding that the relative expression of SLCO1B3 was significantly higher at 25 and 30 weeks than at other laying weeks. Furthermore, the overall methylation rate of the SLCO1B3 gene in Lushi chickens increased gradually with increasing weeks of egg production, as shown by bisulfite sequencing PCR. Pearson correlation analysis showed that methylation of the promoter region of SLCO1B3 was significantly negatively correlated with both SLCO1B3 expression in the shell gland tissue and eggshell color. In addition, we predicted that CpG5 and CpG8 may be key sites for regulating SLCO1B3 gene transcription. Our findings show that as the level of methylation increases, methylation of the CpG5 and CpG8 sites hinders the binding of transcription factors to the promoter, reducing SLCO1B3 expression during the late period and resulting in a lighter eggshell color

3D Path prediction of moving objects in a video-augmented indoor virtual environment

Augmented virtual environments (AVE) combine real-time videos with 3D scenes in a Digital Earth System or 3D GIS to present dynamic information and a virtual scene simultaneously. AVE can provide solutions for continuous tracking of moving objects, camera scheduling, and path planning in the real world. This paper proposes a novel approach for 3D path prediction of moving objects in a video-augmented indoor virtual environment. The study includes 3D motion analysis of moving objects, multi-path prediction, hierarchical visualization, and path-based multi-camera scheduling. The results show that these methods can give a closed-loop process of 3D path prediction and continuous tracking of moving objects in an AVE. The path analysis algorithms proved accurate and time-efficient, costing less than 1.3 ms to get the optimal path. The experiment ran a 3D scene containing 295,000 triangles at around 35 frames per second on a laptop with 1 GB of graphics card memory, which means the performance of the proposed methods is good enough to maintain high rendering efficiency for a video-augmented indoor virtual scene

Detection of Schools in Remote Sensing Images Based on Attention-Guided Dense Network

The detection of primary and secondary schools (PSSs) is a meaningful task for composite object detection in remote sensing images (RSIs). As a typical composite object in RSIs, PSSs have diverse appearances with complex backgrounds, which makes it difficult to effectively extract their features using the existing deep-learning-based object detection algorithms. Aiming at the challenges of PSSs detection, we propose an end-to-end framework called the attention-guided dense network (ADNet), which can effectively improve the detection accuracy of PSSs. First, a dual attention module (DAM) is designed to enhance the ability in representing complex characteristics and alleviate distractions in the background. Second, a dense feature fusion module (DFFM) is built to promote attention cues flow into low layers, which guides the generation of hierarchical feature representation. Experimental results demonstrate that our proposed method outperforms the state-of-the-art methods and achieves 79.86% average precision. The study proves the effectiveness of our proposed method on PSSs detection

Study on effective extraction radius of bedding borehole under the impact of normal fault

The reasonable effective extraction radius of borehole is the key to ensure gas extraction effect. However, the research of effective extraction radius mainly focuses on the measurement method of effective extraction radius of borehole, and there is a lack of research on the effective extraction radius of borehole under special geological conditions of normal fault. Taking a coal working face in Guizhou as the engineering background, the fluid-solid coupling model is established, and the variation law of effective extraction radius of bedding borehole without fault impact is analyzed by means of mutual verification between numerical simulation and borehole gas extraction method. The results show that when the gas is extracted for 120 days, the effective extraction radius of the numerical simulation is 3.10 m, and that of the field test is 2.93 m. The field results are basically consistent with the numerical simulation results, which verifies the reliability of the fluid-solid coupling model. By using multi-physics field coupling simulation software, the variation law of effective extraction radius of bedding borehole under the impact of normal fault is analyzed. The results show that within a certain extraction time range, when the borehole is at a certain distance from the normal fault, the gas pressure curve will have a hump-like distribution, and the peak interval is about 3.5 m. The effective extraction radius of the borehole near the normal fault increases with the increase of the distance from the fault. The impact of the normal fault on the effective extraction radius of the borehole is within 70 m from the fault. Combined with the analysis results under the impact of normal faults, the spacing of gas drainage boreholes near the normal fault is arranged in sections under the premise of ensuring the extraction effect and not prolonging the extraction time. Within 30 m from the fault, the boreholes are densely arranged, and the spacing between the boreholes should not be greater than the effective extraction radius (1.83 m) when the distance from the fault is 10 m. Within the range of 30-70 m from the fault, under the condition of ensuring safety, the spacing of boreholes can be appropriately increased. After 70 m from the fault, the spacing can be gradually restored to the borehole spacing layout of bedding boreholes without the impact of the normal fault