The predominance of seafood allergy in Vietnamese adults: results from the first population-based questionnaire survey

Background: Food allergy (FA) is a serious, costly and growing health problem worldwide. FA occurs in both children and adults; however, there is a paucity of information on FA prevalence and its clinical features in the adult population, especially in Asia. We sought to assess the prevalence of FAs in Vietnamese adults and the distribution of offending food items among different regions throughout Vietnam. Methods: A nationwide, cross-sectional, population-based survey was conducted among University students aged 16-50 years. We used a structured, anonymous questionnaire, which was modified from recently published FA epidemiologic studies and based on European Academy of Allergy and Clinical Immunology (EAACI) guidelines, to collect data on FA prevalence, clinical presentations, and implicated food groups. Statistical analysis was performed to generate the prevalence of self-reported and doctor-diagnosed FA and to examine the association of key environmental factors and FA incidence in this population. Results: Of the 14,500 surveys distributed, a total of 9,039 responses were returned, resulting in a response rate of 62.4%. Among participants who reported food-induced adverse reactions, 48.0% have repeated reactions. 18.0% of the participants perceived FA symptoms, but less than half of them sought medical services for confirmation (37.9%). Stratifying for true FA symptoms, the prevalence of self-reported FA was 11.8% and of doctor-diagnosed FA, 4.6%. The most common doctordiagnosed FA was to crustacean (3.0%; 95% CI, 2.6-3.3), followed by fish (1.6%; 95% CI, 1.3-1.8), mollusk (1.3%; 95% CI, 1.0-1.5) and beef (1.0%; 95% CI, 0.8-1.2). The prevalence of doctordiagnosed FA differed among participants living in urban (6.5%) and rural regions (4.9%) (P< 0.001). Atopic family history was the strongest predictor for FA(odds ratio 8.0; 95% CI, 6.2-10.4). Conclusions: Seafood allergy among adults is predominant in Vietnam, followed by beef, milk, and egg, while peanut, soy, and tree nut allergy are much less common. Populations in rural regions have considerably less FA; however, the protective environmental factors have yet to be identified

Large expert-curated database for benchmarking document similarity detection in biomedical literature search

Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research.Peer reviewe

Measurement of the tt¯ charge asymmetry in events with highly Lorentz-boosted top quarks in pp collisions at s=13 TeV

The measurement of the charge asymmetry in top quark pair events with highly Lorentz-boosted top quarks decaying to a single lepton and jets is presented. The analysis is performed using proton-proton collisions at s=13TeV with the CMS detector at the LHC and corresponding to an integrated luminosity of 138 fb−1. The selection is optimized for top quarks produced with large Lorentz boosts, resulting in nonisolated leptons and overlapping jets. The top quark charge asymmetry is measured for events with a tt¯ invariant mass larger than 750 GeV and corrected for detector and acceptance effects using a binned maximum likelihood fit. The measured top quark charge asymmetry of (0.42−0.69+0.64)% is in good agreement with the standard model prediction at next-to-next-to-leading order in quantum chromodynamic perturbation theory with next-to-leading-order electroweak corrections. The result is also presented for two invariant mass ranges, 750–900 and >900GeV

Portable Acceleration of CMS Computing Workflows with Coprocessors as a Service

Computing demands for large scientific experiments, such as the CMS experiment at the CERN LHC, will increase dramatically in the next decades. To complement the future performance increases of software running on central processing units (CPUs), explorations of coprocessor usage in data processing hold great potential and interest. Coprocessors are a class of computer processors that supplement CPUs, often improving the execution of certain functions due to architectural design choices. We explore the approach of Services for Optimized Network Inference on Coprocessors (SONIC) and study the deployment of this as-a-service approach in large-scale data processing. In the studies, we take a data processing workflow of the CMS experiment and run the main workflow on CPUs, while offloading several machine learning (ML) inference tasks onto either remote or local coprocessors, specifically graphics processing units (GPUs). With experiments performed at Google Cloud, the Purdue Tier-2 computing center, and combinations of the two, we demonstrate the acceleration of these ML algorithms individually on coprocessors and the corresponding throughput improvement for the entire workflow. This approach can be easily generalized to different types of coprocessors and deployed on local CPUs without decreasing the throughput performance. We emphasize that the SONIC approach enables high coprocessor usage and enables the portability to run workflows on different types of coprocessors

Search for new heavy resonances decaying to WW, WZ, ZZ, WH, or ZH boson pairs in the all-jets final state in proton-proton collisions at s=13TeV

A search for new heavy resonances decaying to WW, WZ, ZZ, WH, or ZH boson pairs in the all-jets final state is presented. The analysis is based on proton-proton collision data recorded by the CMS detector in 2016–2018 at a centre-of-mass energy of 13 TeV at the CERN LHC, corresponding to an integrated luminosity of 138fb−1. The search is sensitive to resonances with masses between 1.3 and 6TeV, decaying to bosons that are highly Lorentz-boosted such that each of the bosons forms a single large-radius jet. Machine learning techniques are employed to identify such jets. No significant excess over the estimated standard model background is observed. A maximum local significance of 3.6 standard deviations, corresponding to a global significance of 2.3 standard deviations, is observed at masses of 2.1 and 2.9 TeV. In a heavy vector triplet model, spin-1 Z′ and W′ resonances with masses below 4.8TeV are excluded at the 95% confidence level (CL). These limits are the most stringent to date. In a bulk graviton model, spin-2 gravitons and spin-0 radions with masses below 1.4 and 2.7TeV, respectively, are excluded at 95% CL. Production of heavy resonances through vector boson fusion is constrained with upper cross section limits at 95% CL as low as 0.1fb

Study of azimuthal anisotropy of ϒ(1S) mesons in pPb collisions at sNN = 8.16 TeV

The azimuthal anisotropy of Image 1 mesons in high-multiplicity proton-lead collisions is studied using data collected by the CMS experiment at a nucleon-nucleon center-of-mass energy of 8.16TeV. The Image 1 mesons are reconstructed using their dimuon decay channel. The anisotropy is characterized by the second Fourier harmonic coefficients, found using a two-particle correlation technique, in which the Image 1 mesons are correlated with charged hadrons. A large pseudorapidity gap is used to suppress short-range correlations. Nonflow contamination from the dijet background is removed using a low-multiplicity subtraction method, and the results are presented as a function of Image 1 transverse momentum. The azimuthal anisotropies are smaller than those found for charmonia in proton-lead collisions at the same collision energy, but are consistent with values found for Image 1 mesons in lead-lead interactions at a nucleon-nucleon center-of-mass energy of 5.02 TeV