Optical, physical and chemical characteristics of Australian continental aerosols: results from a field experiment

Mineral dust is one of the major components of the world's aerosol mix, having a number of impacts within the Earth system. However, the climate forcing impact of mineral dust is currently poorly constrained, with even its sign uncertain. As Australian deserts are more reddish than those in the Northern Hemisphere, it is important to better understand the physical, chemical and optical properties of this important aerosol. We have investigated the properties of Australian desert dust at a site in SW Queensland, which is strongly influenced by both dust and biomass burning aerosol. <br><br> Three years of ground-based monitoring of spectral optical thickness has provided a statistical picture of gross aerosol properties. The aerosol optical depth data showed a clear though moderate seasonal cycle with an annual mean of 0.06 ± 0.03. The Angstrom coefficient showed a stronger cycle, indicating the influence of the winter-spring burning season in Australia's north. AERONET size distributions showed a generally bimodal character, with the coarse mode assumed to be mineral dust, and the fine mode a mixture of fine dust, biomass burning and marine biogenic material. <br><br> In November 2006 we undertook a field campaign which collected 4 sets of size-resolved aerosol samples for laboratory analysis – ion beam analysis and ion chromatography. Ion beam analysis was used to determine the elemental composition of all filter samples, although elemental ratios were considered the most reliable output. Scatter plots showed that Fe, Al and Ti were well correlated with Si, and Co reasonably well correlated with Si, with the Fe/Al ratio somewhat higher than values reported from Northern Hemisphere sites (as expected). Scatter plots for Ca, Mn and K against Si showed clear evidence of a second population, which in some cases could be identified with a particular sample day or size fraction. These data may be used to attempt to build a signature of soil in this region of the Australian interior. <br><br> Ion chromatography was used to quantify water soluble ions for 2 of our sample sets, complementing the picture provided by ion beam analysis. The strong similarities between the MSA and SO<sub>4</sub><sup>2−</sup> size distributions argue strongly for a marine origin of much of the SO<sub>4</sub><sup>2−</sup>. The similarity of the Na<sup>+</sup>, Cl<sup>−</sup> and Mg<sup>2+</sup> size distributions also argue for a marine contribution. Further, we believe that both NO<sub>3</sub><sup>−</sup> and NH<sub>4</sub><sup>+</sup> are the result of surface reactions with appropriate gases

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

Evaluation of Macroscopic Properties in the Direct Simulation Monte Carlo Method

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/77021/1/AIAA-12542-230.pd

Retrodiction as a tool for micromaser field measurements

We use retrodictive quantum theory to describe cavity field measurements by successive atomic detections in the micromaser. We calculate the state of the micromaser cavity field prior to detection of sequences of atoms in either the excited or ground state, for atoms that are initially prepared in the excited state. This provides the POM elements, which describe such sequences of measurements.Comment: 20 pages, 4(8) figure

The Kinetic Sunyaev-Zel'dovich Effect from Radiative Transfer Simulations of Patchy Reionization

We present the first calculation of the kinetic Sunyaev-Zel'dovich (kSZ) effect due to the inhomogeneous reionization of the universe based on detailed large-scale radiative transfer simulations of reionization. The resulting sky power spectra peak at l=2000-8000 with maximum values of l^2C_l~1\times10^{-12}. The peak scale is determined by the typical size of the ionized regions and roughly corresponds to the ionized bubble sizes observed in our simulations, ~5-20 Mpc. The kSZ anisotropy signal from reionization dominates the primary CMB signal above l=3000. This predicted kSZ signal at arcminute scales is sufficiently strong to be detectable by upcoming experiments, like the Atacama Cosmology Telescope and South Pole Telescope which are expected to have ~1' resolution and ~muK sensitivity. The extended and patchy nature of the reionization process results in a boost of the peak signal in power by approximately one order of magnitude compared to a uniform reionization scenario, while roughly tripling the signal compared with that based upon the assumption of gradual but spatially uniform reionization. At large scales the patchy kSZ signal depends largely on the ionizing source efficiencies and the large-scale velocity fields: sources which produce photons more efficiently yield correspondingly higher signals. The introduction of sub-grid gas clumping in the radiative transfer simulations produces significantly more power at small scales, and more non-Gaussian features, but has little effect at large scales. The patchy nature of the reionization process roughly doubles the total observed kSZ signal for l~3000-10^4 compared to non-patchy scenarios with the same total electron-scattering optical depth.Comment: 14 pages, 13 figures (some in color), submitted to Ap

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 < 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

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

Frequency Tracking and Parameter Estimation for Robust Quantum State-Estimation

In this paper we consider the problem of tracking the state of a quantum system via a continuous measurement. If the system Hamiltonian is known precisely, this merely requires integrating the appropriate stochastic master equation. However, even a small error in the assumed Hamiltonian can render this approach useless. The natural answer to this problem is to include the parameters of the Hamiltonian as part of the estimation problem, and the full Bayesian solution to this task provides a state-estimate that is robust against uncertainties. However, this approach requires considerable computational overhead. Here we consider a single qubit in which the Hamiltonian contains a single unknown parameter. We show that classical frequency estimation techniques greatly reduce the computational overhead associated with Bayesian estimation and provide accurate estimates for the qubit frequencyComment: 6 figures, 13 page

Causal connectivity of evolved neural networks during behavior

To show how causal interactions in neural dynamics are modulated by behavior, it is valuable to analyze these interactions without perturbing or lesioning the neural mechanism. This paper proposes a method, based on a graph-theoretic extension of vector autoregressive modeling and 'Granger causality,' for characterizing causal interactions generated within intact neural mechanisms. This method, called 'causal connectivity analysis' is illustrated via model neural networks optimized for controlling target fixation in a simulated head-eye system, in which the structure of the environment can be experimentally varied. Causal connectivity analysis of this model yields novel insights into neural mechanisms underlying sensorimotor coordination. In contrast to networks supporting comparatively simple behavior, networks supporting rich adaptive behavior show a higher density of causal interactions, as well as a stronger causal flow from sensory inputs to motor outputs. They also show different arrangements of 'causal sources' and 'causal sinks': nodes that differentially affect, or are affected by, the remainder of the network. Finally, analysis of causal connectivity can predict the functional consequences of network lesions. These results suggest that causal connectivity analysis may have useful applications in the analysis of neural dynamics

Precursors of extreme increments

We investigate precursors and predictability of extreme increments in a time series. The events we are focusing on consist in large increments within successive time steps. We are especially interested in understanding how the quality of the predictions depends on the strategy to choose precursors, on the size of the event and on the correlation strength. We study the prediction of extreme increments analytically in an AR(1) process, and numerically in wind speed recordings and long-range correlated ARMA data. We evaluate the success of predictions via receiver operator characteristics (ROC-curves). Furthermore, we observe an increase of the quality of predictions with increasing event size and with decreasing correlation in all examples. Both effects can be understood by using the likelihood ratio as a summary index for smooth ROC-curves