20 research outputs found

    Predicting the Future of the CMS Detector: Crystal Radiation Damage and Machine Learning at the LHC

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    The 75,848 lead tungstate crystals in CMS experiment at the CERN Large Hadron Collider are used to measure the energy of electrons and photons produced in the proton-proton collisions. The optical transparency of the crystals degrades slowly with radiation dose due to the beam-beam collisions. The transparency of each crystal is monitored with a laser monitoring system that tracks changes in the optical properties of the crystals due to radiation from the collision products. Predicting the optical transparency of the crystals, both in the short-term and in the long-term, is a critical task for the CMS experiment. We describe here the public data release, following FAIR principles, of the crystal monitoring data collected by the CMS Collaboration between 2016 and 2018. Besides describing the dataset and its access, the problems that can be addressed with it are described, as well as an example solution based on a Long Short-Term Memory neural network developed to predict future behavior of the crystals

    Rankitect: Ranking Architecture Search Battling World-class Engineers at Meta Scale

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    Neural Architecture Search (NAS) has demonstrated its efficacy in computer vision and potential for ranking systems. However, prior work focused on academic problems, which are evaluated at small scale under well-controlled fixed baselines. In industry system, such as ranking system in Meta, it is unclear whether NAS algorithms from the literature can outperform production baselines because of: (1) scale - Meta ranking systems serve billions of users, (2) strong baselines - the baselines are production models optimized by hundreds to thousands of world-class engineers for years since the rise of deep learning, (3) dynamic baselines - engineers may have established new and stronger baselines during NAS search, and (4) efficiency - the search pipeline must yield results quickly in alignment with the productionization life cycle. In this paper, we present Rankitect, a NAS software framework for ranking systems at Meta. Rankitect seeks to build brand new architectures by composing low level building blocks from scratch. Rankitect implements and improves state-of-the-art (SOTA) NAS methods for comprehensive and fair comparison under the same search space, including sampling-based NAS, one-shot NAS, and Differentiable NAS (DNAS). We evaluate Rankitect by comparing to multiple production ranking models at Meta. We find that Rankitect can discover new models from scratch achieving competitive tradeoff between Normalized Entropy loss and FLOPs. When utilizing search space designed by engineers, Rankitect can generate better models than engineers, achieving positive offline evaluation and online A/B test at Meta scale.Comment: Wei Wen and Kuang-Hung Liu contribute equall

    Functional Assessment of EnvZ/OmpR Two-Component System in Shewanella oneidensis

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    EnvZ and OmpR constitute the bacterial two-component signal transduction system known to mediate osmotic stress response in a number of Gram-negative bacteria. In an effort to understand the mechanism through which Shewanella oneidensis senses and responds to environmental osmolarity changes, structure of the ompR-envZ operon was determined with Northern blotting assay and roles of the EnvZ/OmpR two-component system in response to various stresses were investigated with mutational analysis, quantitative reverse transcriptase PCR (qRT-PCR), and phenotype microarrays. Results from the mutational analysis and qRT-PCR suggested that the EnvZ/OmpR system contributed to osmotic stress response of S. oneidensis and very likely engaged a similar strategy employed by E. coli, which involved reciprocal regulation of two major porin coding genes. Additionally, the ompR-envZ system was also found related to cell motility. We further showed that the ompR-envZ dependent regulation of porin genes and motility resided almost completely on ompR and only partially on envZ, indicating additional mechanisms for OmpR phosphorylation. In contrast to E. coli lacking ompR-envZ, however, growth of S. oneidensis did not show a significant dependence on ompR-envZ even under osmotic stress. Further analysis with phenotype microarrays revealed that the S. oneidensis strains lacking a complete ompR-envZ system displayed hypersensitivities to a number of agents, especially in alkaline environment. Taken together, our results suggest that the function of the ompR-envZ system in S. oneidensis, although still connected with osmoregulation, has diverged considerably from that of E. coli. Additional mechanism must exist to support growth of S. oneidensis under osmotic stress

    News Video Summarization Combining SURF and Color Histogram Features

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    Because the data volume of news videos is increasing exponentially, a way to quickly browse a sketch of the video is important in various applications, such as news media, archives and publicity. This paper proposes a news video summarization method based on SURF features and an improved clustering algorithm, to overcome the defects in existing algorithms that fail to account for changes in shot complexity. Firstly, we extracted SURF features from the video sequences and matched the features between adjacent frames, and then detected the abrupt and gradual boundaries of the shot by calculating similarity scores between adjacent frames with the help of double thresholds. Secondly, we used an improved clustering algorithm to cluster the color histogram of the video frames within the shot, which merged the smaller clusters and then selected the frame closest to the cluster center as the key frame. The experimental results on both the public and self-built datasets show the superiority of our method over the alternatives in terms of accuracy and speed. Additionally, the extracted key frames demonstrate low redundancy and can credibly represent a sketch of news videos

    Typing discrepancy between phenotypic and molecular characterization revealing an emerging biovar 9 variant of smooth phage-resistant B. abortus strain 8416 in China

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    A newly isolated smooth colony morphology phage-resistant (SPR) strain 8416 isolated from a 45-year-old cattle farm cleaner with clinical features of brucellosis in China was reported. The most unusual phenotype was its resistance to two Brucella phages Tbilisi and Weybridge, but sensitive to Berkeley 2, a pattern similar to that of B. melitensis biovar 1. VITEK 2 biochemical identification system found that both strain 8416 and B. melitensis strains shared positive ILATk, but negative in other B. abortus strains. However, routine biochemical and phenotypic characteristics of strain 8416 were most similar to that of B. abortus biovar 9 except CO2 requirement. In addition, multiple PCR molecular typing assays including AMOS-PCR, B. abortus special PCR (B-ab PCR) and a novel sub-biovar typing PCR, indicated that strain 8416 may belong to either biovar 3b or 9 of B. abortus. Surprisingly, further MLVA typing results showed that strain 8416 was most closely related to B. abortus biovar 3 in the Brucella MLVA database, primarily differing in 4 out of 16 screened loci. Therefore, due to the unusual discrepancy between phenotypic (biochemical reactions and particular phage lysis profile) and molecular typing characteristics, strain 8416 couldn’t be exactly classified to any of the existing B. abortus biovars and might be a new variant of B. abortus biovar 9. The present study also indicates that the present phage typing scheme for Brucella spp. is subject to variation and the routine Brucella biovar typing needs further studies

    Changes in Dietary Intake of Methionine, Folate/Folic Acid and Vitamin B12 and Survival in Postmenopausal Women with Breast Cancer: A Prospective Cohort Study

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    Background: Previous experimental studies showed that limiting methionine in the diet of animals or in cell culture media suppresses mammary cancer cell proliferation or metastasis. However, no previous study has investigated the associations of changes in methionine intake with survival among breast cancer survivors. We aimed to examine the association between changes in dietary intake of methionine, folate/folic acid, and vitamin B12 from before to after diagnosis of breast cancer, and mortality among breast cancer survivors. Methods: We included 1553 postmenopausal women from the Women’s Health Initiative who were diagnosed with invasive breast cancer and completed a food frequency questionnaire both before and after breast cancer diagnosis. Multivariable Cox proportional hazards regression models were used to estimate adjusted hazard ratios (HRs) and 95% confidence (CIs) of all-cause and breast cancer mortality associated with changes in methionine intake and changes in folate/folic acid and vitamin B12 intake. Results: Relative to pre-diagnosis, 28% of women decreased methionine intake by ≥20%, 30% of women increased methionine intake by ≥20%, and 42% of women had a relatively stable methionine intake (±19.9%) following breast cancer diagnosis. During a mean 16.1 years of follow up, there were 772 deaths in total, including 195 deaths from breast cancer. Compared to women with relatively stable methionine intake, women with decreased methionine intake had lower risks of all-cause (HR 0.78, 95% CI 0.62–0.97) and breast cancer mortality (HR 0.58, 95% CI 0.37–0.91) in fully adjusted models. In contrast, increased methionine intake or changes in folate/folic acid or vitamin B12 intake were not associated with all-cause or breast cancer mortality. Conclusions: Among breast cancer survivors, decreased methionine intake after breast cancer diagnosis was associated with lower risk of all-cause and breast cancer mortality
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