Monte Carlo simulation of a clearance box monitor used for nuclear power plant decommissioning.

When decommissioning a nuclear facility it is important to be able to estimate activity levels of potentially radioactive samples and compare with clearance values defined by regulatory authorities. This paper presents a method of calibrating a clearance box monitor based on practical experimental measurements and Monte Carlo simulations. Adjusting the simulation for experimental data obtained using a simple point source permits the computation of absolute calibration factors for more complex geometries with an accuracy of a bit more than 20%. The uncertainty of the calibration factor can be improved to about 10% when the simulation is used relatively, in direct comparison with a measurement performed in the same geometry but with another nuclide. The simulation can also be used to validate the experimental calibration procedure when the sample is supposed to be homogeneous but the calibration factor is derived from a plate phantom. For more realistic geometries, like a small gravel dumpster, Monte Carlo simulation shows that the calibration factor obtained with a larger homogeneous phantom is correct within about 20%, if sample density is taken as the influencing parameter. Finally, simulation can be used to estimate the effect of a contamination hotspot. The research supporting this paper shows that activity could be largely underestimated in the event of a centrally-located hotspot and overestimated for a peripherally-located hotspot if the sample is assumed to be homogeneously contaminated. This demonstrates the usefulness of being able to complement experimental methods with Monte Carlo simulations in order to estimate calibration factors that cannot be directly measured because of a lack of available material or specific geometries.

Accuracy of indirect estimation of power output from uphill performance in cycling.

PURPOSE: To use measurement by cycling power meters (Pmes) to evaluate the accuracy of commonly used models for estimating uphill cycling power (Pest). Experiments were designed to explore the influence of wind speed and steepness of climb on accuracy of Pest. The authors hypothesized that the random error in Pest would be largely influenced by the windy conditions, the bias would be diminished in steeper climbs, and windy conditions would induce larger bias in Pest. METHODS: Sixteen well-trained cyclists performed 15 uphill-cycling trials (range: length 1.3-6.3 km, slope 4.4-10.7%) in a random order. Trials included different riding position in a group (lead or follow) and different wind speeds. Pmes was quantified using a power meter, and Pest was calculated with a methodology used by journalists reporting on the Tour de France. RESULTS: Overall, the difference between Pmes and Pest was -0.95% (95%CI: -10.4%, +8.5%) for all trials and 0.24% (-6.1%, +6.6%) in conditions without wind (<2 m/s). The relationship between percent slope and the error between Pest and Pmes were considered trivial. CONCLUSIONS: Aerodynamic drag (affected by wind velocity and orientation, frontal area, drafting, and speed) is the most confounding factor. The mean estimated values are close to the power-output values measured by power meters, but the random error is between ±6% and ±10%. Moreover, at the power outputs (>400 W) produced by professional riders, this error is likely to be higher. This observation calls into question the validity of releasing individual values without reporting the range of random errors.

Bevacizumab, Pemetrexed, and Cisplatin, or Bevacizumab and Erlotinib for Patients With Advanced Non-Small-Cell Lung Cancer Stratified by Epidermal Growth Factor Receptor Mutation: Phase II Trial SAKK19/09.

OBJECTIVE: The goal was to demonstrate that tailored therapy, according to tumor histology and epidermal growth factor receptor (EGFR) mutation status, and the introduction of novel drug combinations in the treatment of advanced non-small-cell lung cancer are promising for further investigation. METHODS: We conducted a multicenter phase II trial with mandatory EGFR testing and 2 strata. Patients with EGFR wild type received 4 cycles of bevacizumab, pemetrexed, and cisplatin, followed by maintenance with bevacizumab and pemetrexed until progression. Patients with EGFR mutations received bevacizumab and erlotinib until progression. Patients had computed tomography scans every 6 weeks and repeat biopsy at progression. The primary end point was progression-free survival (PFS) ≥ 35% at 6 months in stratum EGFR wild type; 77 patients were required to reach a power of 90% with an alpha of 5%. Secondary end points were median PFS, overall survival, best overall response rate (ORR), and tolerability. Further biomarkers and biopsy at progression were also evaluated. RESULTS: A total of 77 evaluable patients with EGFR wild type received an average of 9 cycles (range, 1-25). PFS at 6 months was 45.5%, median PFS was 6.9 months, overall survival was 12.1 months, and ORR was 62%. Kirsten rat sarcoma oncogene mutations and circulating vascular endothelial growth factor negatively correlated with survival, but thymidylate synthase expression did not. A total of 20 patients with EGFR mutations received an average of 16 cycles. PFS at 6 months was 70%, median PFS was 14 months, and ORR was 70%. Biopsy at progression was safe and successful in 71% of the cases. CONCLUSIONS: Both combination therapies were promising for further studies. Biopsy at progression was feasible and will be part of future SAKK studies to investigate molecular mechanisms of resistance.