Bayesian Learning of Gas Transport in Three-Dimensional Fracture Networks

Modeling gas flow through fractures of subsurface rock is a particularly challenging problem because of the heterogeneous nature of the material. High-fidelity simulations using discrete fracture network (DFN) models are one methodology for predicting gas particle breakthrough times at the surface, but are computationally demanding. We propose a Bayesian machine learning method that serves as an efficient surrogate model, or emulator, for these three-dimensional DFN simulations. Our model trains on a small quantity of simulation data and, using a graph/path-based decomposition of the fracture network, rapidly predicts quantiles of the breakthrough time distribution. The approach, based on Gaussian Process Regression (GPR), outputs predictions that are within 20-30% of high-fidelity DFN simulation results. Unlike previously proposed methods, it also provides uncertainty quantification, outputting confidence intervals that are essential given the uncertainty inherent in subsurface modeling. Our trained model runs within a fraction of a second, which is considerably faster than other methods with comparable accuracy and multiple orders of magnitude faster than high-fidelity simulations

Experimental investigation of burnup credit for safe transport, storage, and disposal of spent nuclear fuel.

This report describes criticality benchmark experiments containing rhodium that were conducted as part of a Department of Energy Nuclear Energy Research Initiative project. Rhodium is an important fission product absorber. A capability to perform critical experiments with low-enriched uranium fuel was established as part of the project. Ten critical experiments, some containing rhodium and others without, were conducted. The experiments were performed in such a way that the effects of the rhodium could be accurately isolated. The use of the experimental results to test neutronics codes is demonstrated by example for two Monte Carlo codes. These comparisons indicate that the codes predict the behavior of the rhodium in the critical systems within the experimental uncertainties. The results from this project, coupled with the results of follow-on experiments that investigate other fission products, can be used to quantify and reduce the conservatism of spent nuclear fuel safety analyses while still providing the necessary level of safety

Entry, Exit, and the Determinants of Market Structure

This paper estimates a dynamic, structural model of entry and exit in an oligopolistic industry and uses it to quantify the determinants of market structure and long-run firm values for two U.S. service industries, dentists and chiropractors. Entry costs faced by potential entrants, fixed costs faced by incumbent producers, and the toughness of short-run price competition are all found to be important determinants of long-run firm values, firm turnover, and market structure. Estimates for the dentist industry allow the entry cost to differ for geographic markets that were designated as Health Professional Shortage Areas and in which entry was subsidized. The estimated mean entry cost is 11 percent lower in these markets. Using simulations, we compare entry-cost versus fixed-cost subsidies and find that entry-cost subsidies are less expensive per additional firm

Analysis of Breast Cancer Mortality in the US-1975 to 2019

IMPORTANCE: Breast cancer mortality in the US declined between 1975 and 2019. The association of changes in metastatic breast cancer treatment with improved breast cancer mortality is unclear. OBJECTIVE: To simulate the relative associations of breast cancer screening, treatment of stage I to III breast cancer, and treatment of metastatic breast cancer with improved breast cancer mortality. DESIGN, SETTING, AND PARTICIPANTS: Using aggregated observational and clinical trial data on the dissemination and effects of screening and treatment, 4 Cancer Intervention and Surveillance Modeling Network (CISNET) models simulated US breast cancer mortality rates. Death due to breast cancer, overall and by estrogen receptor and ERBB2 (formerly HER2) status, among women aged 30 to 79 years in the US from 1975 to 2019 was simulated. EXPOSURES: Screening mammography, treatment of stage I to III breast cancer, and treatment of metastatic breast cancer. MAIN OUTCOMES AND MEASURES: Model-estimated age-adjusted breast cancer mortality rate associated with screening, stage I to III treatment, and metastatic treatment relative to the absence of these exposures was assessed, as was model-estimated median survival after breast cancer metastatic recurrence. RESULTS: The breast cancer mortality rate in the US (age adjusted) was 48/100 000 women in 1975 and 27/100 000 women in 2019. In 2019, the combination of screening, stage I to III treatment, and metastatic treatment was associated with a 58% reduction (model range, 55%-61%) in breast cancer mortality. Of this reduction, 29% (model range, 19%-33%) was associated with treatment of metastatic breast cancer, 47% (model range, 35%-60%) with treatment of stage I to III breast cancer, and 25% (model range, 21%-33%) with mammography screening. Based on simulations, the greatest change in survival after metastatic recurrence occurred between 2000 and 2019, from 1.9 years (model range, 1.0-2.7 years) to 3.2 years (model range, 2.0-4.9 years). Median survival for estrogen receptor (ER)-positive/ERBB2-positive breast cancer improved by 2.5 years (model range, 2.0-3.4 years), whereas median survival for ER-/ERBB2- breast cancer improved by 0.5 years (model range, 0.3-0.8 years). CONCLUSIONS AND RELEVANCE: According to 4 simulation models, breast cancer screening and treatment in 2019 were associated with a 58% reduction in US breast cancer mortality compared with interventions in 1975. Simulations suggested that treatment for stage I to III breast cancer was associated with approximately 47% of the mortality reduction, whereas treatment for metastatic breast cancer was associated with 29% of the reduction and screening with 25% of the reduction

Challenges and Opportunities Associated With the MD Anderson IMPACT2 Randomized Study in Precision Oncology

We investigated the challenges of conducting IMPACT2, an ongoing randomized study that evaluates molecular testing and targeted therapy (ClinicalTrials.gov: NCT02152254). Patients with metastatic cancer underwent tumor profiling and were randomized between the two arms when eligibility criteria were met (Part A). In Part B, patients who declined randomization could choose the study arm. In Part A, 69 (21.8%) of 317 patients were randomized; 78.2% were not randomized because of non-targetable alterations (39.8%), unavailability of clinical trial (21.8%), other reasons (12.6%), or availability of US Food and Drug Administration (FDA)-approved drugs for the indication (4.1%). In Part B, 32 (20.4%) of 157 patients were offered randomization; 16 accepted and 16 selected their treatment arm; 79.0% were not randomized (patient\u27s/physician\u27s choice, 29.3%; treatment selection prior to genomic reports, 16.6%; worsening performance status/death, 12.7%; unavailability of clinical trials, 6.4%; other, 6.4%; non-targetable alterations, 5.7%; or availability of FDA-approved drugs for the indication, 1.9%). In conclusion, although randomized controlled trials have been considered the gold standard for drug development, the execution of randomized trials in precision oncology in the advanced metastatic setting is complicated. We encountered various challenges conducting the IMPACT2 study, a large precision oncology trial in patients with diverse solid tumor types. The adaptive design of IMPACT2 enables patient randomization despite the continual FDA approval of targeted therapies, the evolving tumor biomarker landscape, and the plethora of investigational drugs. Outcomes for randomized patients are awaited

Learning robotics: a review

Purpose of Review: With the growing interest for STEM/STEAM, new robotic platforms are being created with different characteristics, extras and options. There are so many diverse solutions, that it is difficult for a teacher/student to choose the ideal one. This paper intends to provide an analysis to the most common robotic platforms existent on the market. The same is happening regarding robotic events all around the world, with objectives so distinctive, and with complexity from easy to very difficult. This paper also describes some of those events which occur in many countries. Recent Findings: As the literature is showing, there has been a visible effort from schools and educators to teach robotics from very young ages, not only because robotics is the future, but also as a tool to teach STEM/STEAM areas. But as time progresses, the options for the right platforms also evolves making difficult to choose among them. Some authors opt to first choose a robotic platform and carry on from there. Others choose first a development environment and then look for which robots can be programmed from it. Summary: An actual review on learning robotics is here presented, firstly showing some literature background on history and trends of robotic platforms used in education in general, the different development environments for robotics and finishing on competitions and events. A comprehensive characterization list of robotic platforms along with robotic competitions and events is also shown

Measurements of Higgs boson production and couplings in diboson final states with the ATLAS detector at the LHC

Measurements are presented of production properties and couplings of the recently discovered Higgs boson using the decays into boson pairs, H →γ γ, H → Z Z∗ →4l and H →W W∗ →lνlν. The results are based on the complete pp collision data sample recorded by the ATLAS experiment at the CERN Large Hadron Collider at centre-of-mass energies of √s = 7 TeV and √s = 8 TeV, corresponding to an integrated luminosity of about 25 fb−1. Evidence for Higgs boson production through vector-boson fusion is reported. Results of combined fits probing Higgs boson couplings to fermions and bosons, as well as anomalous contributions to loop-induced production and decay modes, are presented. All measurements are consistent with expectations for the Standard Model Higgs boson