100 research outputs found

    The Application of Downhole Vibration Factor in Drilling Tool Reliability Big Data Analytics - A Review

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    In the challenging downhole environment, drilling tools are normally subject to high temperature, severe vibration, and other harsh operation conditions. The drilling activities generate massive field data, namely field reliability big data (FRBD), which includes downhole operation, environment, failure, degradation, and dynamic data. Field reliability big data has large size, high variety, and extreme complexity. FRBD presents abundant opportunities and great challenges for drilling tool reliability analytics. Consequently, as one of the key factors to affect drilling tool reliability, the downhole vibration factor plays an essential role in the reliability analytics based on FRBD. This paper reviews the important parameters of downhole drilling operations, examines the mode, physical and reliability impact of downhole vibration, and presents the features of reliability big data analytics. Specifically, this paper explores the application of vibration factor in reliability big data analytics covering tool lifetime/failure prediction, prognostics/diagnostics, condition monitoring (CM), and maintenance planning and optimization. Furthermore, the authors highlight the future research about how to better apply the downhole vibration factor in reliability big data analytics to further improve tool reliability and optimize maintenance planning

    Radiation Dose Calculations for a Hypothetical Accident in Xianning Nuclear Power Plant

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    Atmospheric dispersion modeling and radiation dose calculations have been performed for a hypothetical AP1000 SGTR accident by HotSpot code 3.03. TEDE, the respiratory time-integrated air concentration, and the ground deposition are calculated for various atmospheric stability classes, Pasquill stability categories A–F with site-specific averaged meteorological conditions. The results indicate that the maximum plume centerline ground deposition value of 1.2E+2 kBq/m2 occurred at about 1.4 km and the maximum TEDE value of 1.41E-05 Sv occurred at 1.4 km from the reactor. It is still far below the annual regulatory limits of 1 mSv for the public as set in IAEA Safety Report Series number 115. The released radionuclides might be transported to long distances but will not have any harmful effect on the public

    An Empirical Study of the Landscape of Open Source Projects in Baidu, Alibaba, and Tencent

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    Open source software has drawn more and more attention from researchers, developers and companies nowadays. Meanwhile, many Chinese technology companies are embracing open source and choosing to open source their projects. Nevertheless, most previous studies are concentrated on international companies such as Microsoft or Google, while the practical values of open source projects of Chinese technology companies remain unclear. To address this issue, we conduct a mixed-method study to investigate the landscape of projects open sourced by three large Chinese technology companies, namely Baidu, Alibaba, and Tencent (BAT). We study the categories and characteristics of open source projects, the developer's perceptions towards open sourcing effort for these companies, and the internationalization effort of their open source projects. We collected 1,000 open source projects that were open sourced by BAT in GitHub and performed an online survey that received 101 responses from developers of these projects. Some key findings include: 1) BAT prefer to open source frontend development projects, 2) 88\% of the respondents are positive towards open sourcing software projects in their respective companies, 3) 64\% of the respondents reveal that the most common motivations for BAT to open source their projects are the desire to gain fame, expand their influence and gain recruitment advantage, 4) respondents believe that the most common internationalization effort is "providing an English version of readme files", 5) projects with more internationalization effort (i.e., include an English readme file) are more popular. Our findings provide directions for software engineering researchers and provide practical suggestions to software developers and Chinese technology companies

    Development of a risk model to predict prognosis in breast cancer based on cGAS-STING-related genes

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    Background: Breast cancer (BRCA) is regarded as a lethal and aggressive cancer with increasing morbidity and mortality worldwide. cGAS-STING signaling regulates the crosstalk between tumor cells and immune cells in the tumor microenvironment (TME), emerging as an important DNA-damage mechanism. However, cGAS-STING-related genes (CSRGs) have rarely been investigated for their prognostic value in breast cancer patients.Methods: Our study aimed to construct a risk model to predict the survival and prognosis of breast cancer patients. We obtained 1087 breast cancer samples and 179 normal breast tissue samples from the Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression (GTEX) database, 35 immune-related differentially expression genes (DEGs) from cGAS-STING-related genes were systematically assessed. The Cox regression was applied for further selection, and 11 prognostic-related DEGs were used to develop a machine learning-based risk assessment and prognostic model.Results: We successfully developed a risk model to predict the prognostic value of breast cancer patients and its performance acquired effective validation. The results derived from Kaplan-Meier analysis revealed that the low-risk score patients had better overall survival (OS). The nomogram that integrated the risk score and clinical information was established and had good validity in predicting the overall survival of breast cancer patients. Significant correlations were observed between the risk score and tumor-infiltrating immune cells, immune checkpoints and the response to immunotherapy. The cGAS-STING-related genes risk score was also relevant to a series of clinic prognostic indicators such as tumor staging, molecular subtype, tumor recurrence, and drug therapeutic sensibility in breast cancer patients.Conclusion: cGAS-STING-related genes risk model provides a new credible risk stratification method to improve the clinical prognostic assessment for breast cancer

    ARES: A Parallel Discrete Ordinates Transport Code for Radiation Shielding Applications and Reactor Physics Analysis

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    ARES is a multidimensional parallel discrete ordinates particle transport code with arbitrary order anisotropic scattering. It can be applied to a wide variety of radiation shielding calculations and reactor physics analysis. ARES uses state-of-the-art solution methods to obtain accurate solutions to the linear Boltzmann transport equation. A multigroup discretization is applied in energy. The code allows multiple spatial discretization schemes and solution methodologies. ARES currently provides diamond difference with or without linear-zero flux fixup, theta weighted, directional theta weighted, exponential directional weighted, and linear discontinuous finite element spatial differencing schemes. Discrete ordinates differencing in angle and spherical harmonics expansion of the scattering source are adopted. First collision source method is used to eliminate or mitigate the ray effects. Traditional source iteration and Krylov iterative method preconditioned with diffusion synthetic acceleration are applied to solve the linear system of equations. ARES uses the Koch-Baker-Alcouffe parallel sweep algorithm to obtain high parallel efficiency. Verification and validation for the ARES transport code system have been done by lots of benchmarks. In this paper, ARES solutions to the HBR-2 benchmark and C5G7 benchmarks are in excellent agreement with published results. Numerical results are presented which demonstrate the accuracy and efficiency of these methods

    Chitosan as a coupling agent for phosphate glass fibre/polycaprolactone composites

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    This study shows that chitosan (CS) could be highly useful as a coupling agent in phosphate glass fibre/polycaprolactone (PGF/PCL) composites, as it improved the interfacial shear strength by up to 78%. PGFs of the composition 45P2O5–5B2O3–5Na2O–24CaO–10MgO–11Fe2O3 were dip-coated with CS (with a degree of deacetylation >80%) dissolved in acetic acid solution (2% v/v). Different CS concentrations (3–9 g L−1) and coating processes were investigated. Tensile and fragmentation tests were conducted to obtain the mechanical properties of the single fibres and interfacial properties of the PGF/PCL composites, respectively. It was observed that post-cleaning, the treated fibres had their tensile strength reduced by around 20%; however, the CS-coated fibres experienced strength increases of up to 1.1–11.5%. TGA and SEM analyses were used to confirm the presence of CS on the fibre surface. FTIR, Raman, and X-ray photoelectron spectroscopy (XPS) analyses further confirmed the presence of CS and indicated the protonation of CS amine groups. Moreover, the nitrogen spectrum of XPS demonstrated a minimum threshold of CS coating required to provide an improved interface

    Single-Cell Rna Sequencing Deconvolutes the in Vivo Heterogeneity of Human Bone Marrow-Derived Mesenchymal Stem Cells

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    Bone marrow-derived mesenchymal stem cells (BM-MSCs) are multipotent stromal cells that have a critical role in the maintenance of skeletal tissues such as bone, cartilage, and the fat in bone marrow. In addition to providing microenvironmental support for hematopoietic processes, BM-MSCs can differentiate into various mesodermal lineages including osteoblast/osteocyte, chondrocyte, and adipocyte that are crucial for bone metabolism. While BM-MSCs have high cell-to-cell heterogeneity in gene expression, the cell subtypes that contribute to this heterogeneity in vivo in humans have not been characterized. To investigate the transcriptional diversity of BM-MSCs, we applied single-cell RNA sequencing (scRNA-seq) on freshly isolated CD271+ BM-derived mononuclear cells (BM-MNCs) from two human subjects. We successfully identified LEPRhi CD45low BM-MSCs within the CD271+ BM-MNC population, and further codified the BM-MSCs into distinct subpopulations corresponding to the osteogenic, chondrogenic, and adipogenic differentiation trajectories, as well as terminal-stage quiescent cells. Biological functional annotations of the transcriptomes suggest that osteoblast precursors induce angiogenesis coupled with osteogenesis, and chondrocyte precursors have the potential to differentiate into myocytes. We also discovered transcripts for several clusters of differentiation (CD) markers that were either highly expressed (e.g., CD167b, CD91, CD130 and CD118) or absent (e.g., CD74, CD217, CD148 and CD68) in BM-MSCs, representing potential novel markers for human BM-MSC purification. This study is the first systematic in vivo dissection of human BM-MSCs cell subtypes at the single-cell resolution, revealing an insight into the extent of their cellular heterogeneity and roles in maintaining bone homeostasis

    Baiji genomes reveal low genetic variability and new insights into secondary aquatic adaptations

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    The baiji, or Yangtze River dolphin (Lipotes vexillifer), is a flagship species for the conservation of aquatic animals and ecosystems in the Yangtze River of China; however, this species has now been recognized as functionally extinct. Here we report a high-quality draft genome and three re-sequenced genomes of L. vexillifer using Illumina short-read sequencing technology. Comparative genomic analyses reveal that cetaceans have a slow molecular clock and molecular adaptations to their aquatic lifestyle. We also find a significantly lower number of heterozygous single nucleotide polymorphisms in the baiji compared to all other mammalian genomes reported thus far. A reconstruction of the demographic history of the baiji indicates that a bottleneck occurred near the end of the last deglaciation, a time coinciding with a rapid decrease in temperature and the rise of eustatic sea level

    Integrated transcriptomics and metabolomics analysis provide insight into the resistance response of rice against brown planthopper

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    IntroductionThe brown planthopper (Nilaparvata lugens Stål, BPH) is one of the most economically significant pests of rice. The Bph30 gene has been successfully cloned and conferred rice with broad-spectrum resistance to BPH. However, the molecular mechanisms by which Bph30 enhances resistance to BPH remain poorly understood.MethodsHere, we conducted a transcriptomic and metabolomic analysis of Bph30-transgenic (BPH30T) and BPH-susceptible Nipponbare plants to elucidate the response of Bph30 to BPH infestation.ResultsTranscriptomic analyses revealed that the pathway of plant hormone signal transduction enriched exclusively in Nipponbare, and the greatest number of differentially expressed genes (DEGs) were involved in indole 3-acetic acid (IAA) signal transduction. Analysis of differentially accumulated metabolites (DAMs) revealed that DAMs involved in the amino acids and derivatives category were down-regulated in BPH30T plants following BPH feeding, and the great majority of DAMs in flavonoids category displayed the trend of increasing in BPH30T plants; the opposite pattern was observed in Nipponbare plants. Combined transcriptomics and metabolomics analysis revealed that the pathways of amino acids biosynthesis, plant hormone signal transduction, phenylpropanoid biosynthesis and flavonoid biosynthesis were enriched. The content of IAA significantly decreased in BPH30T plants following BPH feeding, and the content of IAA remained unchanged in Nipponbare. The exogenous application of IAA weakened the BPH resistance conferred by Bph30.DiscussionOur results indicated that Bph30 might coordinate the movement of primary and secondary metabolites and hormones in plants via the shikimate pathway to enhance the resistance of rice to BPH. Our results have important reference significance for the resistance mechanisms analysis and the efficient utilization of major BPH-resistance genes
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