The LHC Olympics 2020 a community challenge for anomaly detection in high energy physics.

A new paradigm for data-driven, model-agnostic new physics searches at colliders is emerging, and aims to leverage recent breakthroughs in anomaly detection and machine learning. In order to develop and benchmark new anomaly detection methods within this framework, it is essential to have standard datasets. To this end, we have created the LHC Olympics 2020, a community challenge accompanied by a set of simulated collider events. Participants in these Olympics have developed their methods using an R&D dataset and then tested them on black boxes: datasets with an unknown anomaly (or not). Methods made use of modern machine learning tools and were based on unsupervised learning (autoencoders, generative adversarial networks, normalizing flows), weakly supervised learning, and semi-supervised learning. This paper will review the LHC Olympics 2020 challenge, including an overview of the competition, a description of methods deployed in the competition, lessons learned from the experience, and implications for data analyses with future datasets as well as future colliders.

Estimating COVID-19 mortality in Italy early in the COVID-19 pandemic.

Estimating rates of COVID-19 infection and associated mortality is challenging due to uncertainties in case ascertainment. We perform a counterfactual time series analysis on overall mortality data from towns in Italy, comparing the population mortality in 2020 with previous years, to estimate mortality from COVID-19. We find that the number of COVID-19 deaths in Italy in 2020 until September 9 was 59,000-62,000, compared to the official number of 36,000. The proportion of the population that died was 0.29% in the most affected region, Lombardia, and 0.57% in the most affected province, Bergamo. Combining reported test positive rates from Italy with estimates of infection fatality rates from the Diamond Princess cruise ship, we estimate the infection rate as 29% (95% confidence interval 15-52%) in Lombardy, and 72% (95% confidence interval 36-100%) in Bergamo.

Measurement and modelling of x-direction apparent mass of the seated human body-cushioned seat system.

For modelling purposes and for evaluation of driver's seat performance in the vertical direction various mechano-mathematical models of the seated human body have been developed and standardized by the ISO. No such models exist hitherto for human body sitting in an upright position in a cushioned seat upper part, used in industrial environment, where the fore-and-aft vibrations play an important role. The interaction with the steering wheel has to be taken into consideration, as well as, the position of the human body upper torso with respect to the cushioned seat back as observed in real driving conditions. This complex problem has to be simplified first to arrive at manageable simpler models, which still reflect the main problem features. In a laboratory study accelerations and forces in x-direction were measured at the seat base during whole-body vibration in the fore-and-aft direction (random signal in the frequency range between 0.3 and 30 Hz, vibration magnitudes 0.28, 0.96, and 2.03 ms(-2) unweighted rms). Thirteen male subjects with body masses between 62.2 and 103.6 kg were chosen for the tests. They sat on a cushioned driver seat with hands on a support and backrest contact in the lumbar region only. Based on these laboratory measurements a linear model of the system-seated human body and cushioned seat in the fore-and-aft direction has been developed. The model accounts for the reaction from the steering wheel. Model parameters have been identified for each subject-measured apparent mass values (modulus and phase). The developed model structure and the averaged parameters can be used for further bio-dynamical research in this field.

Phase III study of R-CVP compared with cyclophosphamide, vincristine, and prednisone alone in patients with previously untreated advanced follicular lymphoma.

PURPOSE: To compare the long-term outcome of patients with previously untreated follicular lymphoma (FL) needing therapy, after treatment with cyclophosphamide, vincristine and prednisone (CVP) versus CVP plus rituximab (R-CVP) and to evaluate the predictive value of known prognostic factors after treatment with R-CVP. PATIENTS AND METHODS: Patients with previously untreated CD20-positive stage III/IV FL were randomly assigned to eight cycles of R-CVP (n = 159) or CVP alone (n = 162). The median follow-up period was 53 months. RESULTS: The primary end point-time to treatment failure (TTF), which included patients without a response after four cycles as an event-was significantly prolonged in patients receiving R-CVP versus CVP (P < .0001). Improvements in all other end points, including overall and complete response rates (P < .0001), time to progression (TTP; P < .0001), response duration (P < .0001), time to next antilymphoma treatment (P < .0001), and overall survival (OS; P = .029; 4-year OS: 83% v 77%;) were achieved with R-CVP versus CVP alone. Univariate analyses demonstrated an improvement in TTP with R-CVP versus CVP irrespective of the Follicular Lymphoma International Prognostic Index (FLIPI) subgroup, the International Prognostic Index (IPI) subgroup, baseline histology, and the presence or absence of B symptoms or bulky disease. By multivariate analysis, FLIPI retains a strong predictive power for TTP in the presence of the trial treatment effect. CONCLUSION: Analysis of all outcome measures, including OS, confirm the benefit of adding R to CVP in the front-line treatment of FL.