Determination of the Joint Confidence Region of Optimal Operating Conditions in Robust Design by Bootstrap Technique

Robust design has been widely recognized as a leading method in reducing variability and improving quality. Most of the engineering statistics literature mainly focuses on finding "point estimates" of the optimum operating conditions for robust design. Various procedures for calculating point estimates of the optimum operating conditions are considered. Although this point estimation procedure is important for continuous quality improvement, the immediate question is "how accurate are these optimum operating conditions?" The answer for this is to consider interval estimation for a single variable or joint confidence regions for multiple variables. In this paper, with the help of the bootstrap technique, we develop procedures for obtaining joint "confidence regions" for the optimum operating conditions. Two different procedures using Bonferroni and multivariate normal approximation are introduced. The proposed methods are illustrated and substantiated using a numerical example.Comment: Two tables, Three figure

The Book of Enoch

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Application of Bayesian model averaging to measurements of the primordial power spectrum

Cosmological parameter uncertainties are often stated assuming a particular model, neglecting the model uncertainty, even when Bayesian model selection is unable to identify a conclusive best model. Bayesian model averaging is a method for assessing parameter uncertainties in situations where there is also uncertainty in the underlying model. We apply model averaging to the estimation of the parameters associated with the primordial power spectra of curvature and tensor perturbations. We use CosmoNest and MultiNest to compute the model Evidences and posteriors, using cosmic microwave data from WMAP, ACBAR, BOOMERanG and CBI, plus large-scale structure data from the SDSS DR7. We find that the model-averaged 95% credible interval for the spectral index using all of the data is 0.940 < n_s < 1.000, where n_s is specified at a pivot scale 0.015 Mpc^{-1}. For the tensors model averaging can tighten the credible upper limit, depending on prior assumptions.Comment: 7 pages with 7 figures include

A Bayesian spatio-temporal model of panel design data: airborne particle number concentration in Brisbane, Australia

This paper outlines a methodology for semi-parametric spatio-temporal modelling of data which is dense in time but sparse in space, obtained from a split panel design, the most feasible approach to covering space and time with limited equipment. The data are hourly averaged particle number concentration (PNC) and were collected, as part of the Ultrafine Particles from Transport Emissions and Child Health (UPTECH) project. Two weeks of continuous measurements were taken at each of a number of government primary schools in the Brisbane Metropolitan Area. The monitoring equipment was taken to each school sequentially. The school data are augmented by data from long term monitoring stations at three locations in Brisbane, Australia. Fitting the model helps describe the spatial and temporal variability at a subset of the UPTECH schools and the long-term monitoring sites. The temporal variation is modelled hierarchically with penalised random walk terms, one common to all sites and a term accounting for the remaining temporal trend at each site. Parameter estimates and their uncertainty are computed in a computationally efficient approximate Bayesian inference environment, R-INLA. The temporal part of the model explains daily and weekly cycles in PNC at the schools, which can be used to estimate the exposure of school children to ultrafine particles (UFPs) emitted by vehicles. At each school and long-term monitoring site, peaks in PNC can be attributed to the morning and afternoon rush hour traffic and new particle formation events. The spatial component of the model describes the school to school variation in mean PNC at each school and within each school ground. It is shown how the spatial model can be expanded to identify spatial patterns at the city scale with the inclusion of more spatial locations.Comment: Draft of this paper presented at ISBA 2012 as poster, part of UPTECH projec

Synthetic LISA: Simulating Time Delay Interferometry in a Model LISA

We report on three numerical experiments on the implementation of Time-Delay Interferometry (TDI) for LISA, performed with Synthetic LISA, a C++/Python package that we developed to simulate the LISA science process at the level of scientific and technical requirements. Specifically, we study the laser-noise residuals left by first-generation TDI when the LISA armlengths have a realistic time dependence; we characterize the armlength-measurements accuracies that are needed to have effective laser-noise cancellation in both first- and second-generation TDI; and we estimate the quantization and telemetry bitdepth needed for the phase measurements. Synthetic LISA generates synthetic time series of the LISA fundamental noises, as filtered through all the TDI observables; it also provides a streamlined module to compute the TDI responses to gravitational waves according to a full model of TDI, including the motion of the LISA array and the temporal and directional dependence of the armlengths. We discuss the theoretical model that underlies the simulation, its implementation, and its use in future investigations on system characterization and data-analysis prototyping for LISA.Comment: 18 pages, 14 EPS figures, REVTeX 4. Accepted PRD version. See http://www.vallis.org/syntheticlisa for information on the Synthetic LISA software packag

The effects of an alpha-2-adrenoceptor agonist, antagonist, and their combination on the blood insulin, glucose, and glucagon concentrations in insulin sensitive and dysregulated horses

Alpha-2-adrenoceptor agonists are sedatives that can cause fluctuations in serum insulin and blood glucose (BG) concentrations in horses. The objectives of this study were to investigate the effects of detomidine and vatinoxan on BG, insulin, and glucagon concentrations in horses with and without insulin dysregulation (ID). In a blinded cross-over design, eight horses with ID and eight horses without ID were assigned to each of four treatments: detomidine (0.02 mg/kg; DET), vatinoxan (0.2 mg/kg; VAT), detomidine + vatinoxan (DET + VAT), and saline control (SAL). Blood samples were taken at 0,1, 2, 4, 6, and 8 h. Change from baseline was used as the response in modelling, and the differences between treatments were evaluated with repeated measures analysis of covariance. P values 2021 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).Peer reviewe

Heartbeat of the Southern Oscillation explains ENSO climatic resonances

The El Ni~no-Southern Oscillation (ENSO) nonlinear oscillator phenomenon has a far reaching influence on the climate and human activities. The up to 10 year quasi-period cycle of the El Ni~no and subsequent La Ni~na is known to be dominated in the tropics by nonlinear physical interaction of wind with the equatorial waveguide in the Pacific. Long-term cyclic phenomena do not feature in the current theory of the ENSO process. We update the theory by assessing low (>10 years) and high (<10 years) frequency coupling using evidence across tropical, extratropical, and Pacific basin scales. We analyze observations and model simulations with a highly accurate method called Dominant Frequency State Analysis (DFSA) to provide evidence of stable ENSO features. The observational data sets of the Southern Oscillation Index (SOI), North Pacific Index Anomaly, and ENSO Sea Surface Temperature Anomaly, as well as a theoretical model all confirm the existence of long-term and short-term climatic cycles of the ENSO process with resonance frequencies of {2.5, 3.8, 5, 12–14, 61–75, 180} years. This fundamental result shows long-term and short-term signal coupling with mode locking across the dominant ENSO dynamics. These dominant oscillation frequency dynamics, defined as ENSO frequency states, contain a stable attractor with three frequencies in resonance allowing us to coin the term Heartbeat of the Southern Oscillation due to its characteristic shape. We predict future ENSO states based on a stable hysteresis scenario of short-term and long-term ENSO oscillations over the next century

Baseline T cell dysfunction by single cell network profiling in metastatic breast cancer patients.

BackgroundWe previously reported the results of a multicentric prospective randomized trial of chemo-refractory metastatic breast cancer patients testing the efficacy of two doses of TGFβ blockade during radiotherapy. Despite a lack of objective responses to the combination, patients who received a higher dose of TGFβ blocking antibody fresolimumab had a better overall survival when compared to those assigned to lower dose (hazard ratio of 2.73, p = 0.039). They also demonstrated an improved peripheral blood mononuclear cell (PBMC) counts and increase in the CD8 central memory pool. We performed additional analysis on residual PBMC using single cell network profiling (SCNP).MethodsThe original trial randomized metastatic breast cancer patients to either 1 or 10 mg/kg of fresolimumab, every 3 weeks for 5 cycles, combined with radiotherapy to a metastatic site at week 1 and 7 (22.5 Gy given in 3 doses of 7.5 Gy). Trial immune monitoring results were previously reported. In 15 patients with available residual blood samples, additional functional studies were performed, and compared with data obtained in parallel from seven healthy female donors (HD): SCNP was applied to analyze T cell receptor (TCR) modulated signaling via CD3 and CD28 crosslinking and measurement of evoked phosphorylation of AKT and ERK in CD4 and CD8 T cell subsets defined by PD-1 expression.ResultsAt baseline, a significantly higher level of expression (p &lt; 0.05) of PD-L1 was identified in patient monocytes compared to HD. TCR modulation revealed dysfunction of circulating T-cells in patient baseline samples as compared to HD, and this was more pronounced in PD-1+ cells. Treatment with radiotherapy and fresolimumab did not resolve this dyfunctional signaling. However, in vitro PD-1 blockade enhanced TCR signaling in patient PD-1+ T cells and not in PD-1- T cells or in PD-1+ T cells from HD.ConclusionsFunctional T cell analysis suggests that baseline T cell functionality is hampered in metastatic breast cancer patients, at least in part mediated by the PD-1 signaling pathway. These preliminary data support the rationale for investigating the possible beneficial effects of adding PD-1 blockade to improve responses to TGFβ blockade and radiotherapy.Trial registrationNCT01401062

Quantum trajectories for the realistic measurement of a solid-state charge qubit

We present a new model for the continuous measurement of a coupled quantum dot charge qubit. We model the effects of a realistic measurement, namely adding noise to, and filtering, the current through the detector. This is achieved by embedding the detector in an equivalent circuit for measurement. Our aim is to describe the evolution of the qubit state conditioned on the macroscopic output of the external circuit. We achieve this by generalizing a recently developed quantum trajectory theory for realistic photodetectors [P. Warszawski, H. M. Wiseman and H. Mabuchi, Phys. Rev. A_65_ 023802 (2002)] to treat solid-state detectors. This yields stochastic equations whose (numerical) solutions are the ``realistic quantum trajectories'' of the conditioned qubit state. We derive our general theory in the context of a low transparency quantum point contact. Areas of application for our theory and its relation to previous work are discussed.Comment: 7 pages, 2 figures. Shorter, significantly modified, updated versio