Improved bounds for sparse recovery from adaptive measurements

It is shown here that adaptivity in sampling results in dramatic improvements in the recovery of sparse signals in white Gaussian noise. An adaptive sampling-and-refinement procedure called distilled sensing is discussed and analyzed, resulting in fundamental new asymptotic scaling relationships in terms of the minimum feature strength required for reliable signal detection or localization (support recovery). In particular, reliable detection and localization using non-adaptive samples is possible only if the feature strength grows logarithmically in the problem dimension. Here it is shown that using adaptive sampling, reliable detection is possible provided the feature strength exceeds a constant, and localization is possible when the feature strength exceeds any (arbitrarily slowly) growing function of the problem dimension

Finding needles in noisy haystacks

The theory of compressed sensing shows that samples in the form of random projections are optimal for recovering sparse signals in high-dimensional spaces (i.e., finding needles in haystacks), provided the measurements are noiseless. However, noise is almost always present in applications, and compressed sensing suffers from it. The signal to noise ratio per dimension using random projections is very poor, since sensing energy is equally distributed over all dimensions. Consequently, the ability of compressed sensing to locate sparse components degrades significantly as noise increases. It is possible, in principle, to improve performance by "shaping" the projections to focus sensing energy in proper dimensions. The main question addressed here is, can projections be adaptively shaped to achieve this focusing effect? The answer is yes, and we demonstrate a simple, computationally efficient procedure that does so

Improved bounds for sparse recovery from adaptive measurements

It is shown here that adaptivity in sampling results in dramatic improvements in the recovery of sparse signals in white Gaussian noise. An adaptive sampling-and-refinement procedure called distilled sensing is discussed and analyzed, resulting in fundamental new asymptotic scaling relationships in terms of the minimum feature strength required for reliable signal detection or localization (support recovery). In particular, reliable detection and localization using non-adaptive samples is possible only if the feature strength grows logarithmically in the problem dimension. Here it is shown that using adaptive sampling, reliable detection is possible provided the feature strength exceeds a constant, and localization is possible when the feature strength exceeds any (arbitrarily slowly) growing function of the problem dimension

The Average Kinetic Energy of the Superconducting State

Isothermal magnetization curves are plotted as the magnetization times the magnetic induction, $4 \pi M \cdot B$, versus the applied field, H. We show here that this new curve is the average kinetic energy of the superconducting state versus the applied field, for type-II superconductors with a high Ginzburg-Landau parameter $\kappa$. The maximum of $4 \pi M \cdot B$ occurs at a field, $H^{*}$, directly related to the upper critical field, $H_{c2}$, suggesting that $H_{c2}(T)$ may be extracted from such plots even in cases when it is too high for direct measurement. We obtain these plots both theoretically, from the Ginzburg-Landau theory, and experimentally, using a Niobium sample with $T_c = 8.5 K$, and compare them.Comment: 11 pages, 9 postscript figure

Random close packing of granular matter

We propose an interpretation of the random close packing of granular materials as a phase transition, and discuss the possibility of experimental verification.Comment: 6 page

Robustness of a Cellular Automata Model for the HIV Infection

An investigation was conducted to study the robustness of the results obtained from the cellular automata model which describes the spread of the HIV infection within lymphoid tissues [R. M. Zorzenon dos Santos and S. Coutinho, Phys. Rev. Lett. 87, 168102 (2001)]. The analysis focussed on the dynamic behavior of the model when defined in lattices with different symmetries and dimensionalities. The results illustrated that the three-phase dynamics of the planar models suffered minor changes in relation to lattice symmetry variations and, while differences were observed regarding dimensionality changes, qualitative behavior was preserved. A further investigation was conducted into primary infection and sensitiveness of the latency period to variations of the model's stochastic parameters over wide ranging values. The variables characterizing primary infection and the latency period exhibited power-law behavior when the stochastic parameters varied over a few orders of magnitude. The power-law exponents were approximately the same when lattice symmetry varied, but there was a significant variation when dimensionality changed from two to three. The dynamics of the three-dimensional model was also shown to be insensitive to variations of the deterministic parameters related to cell resistance to the infection, and the necessary time lag to mount the specific immune response to HIV variants. The robustness of the model demonstrated in this work reinforce that its basic hypothesis are consistent with the three-stage dynamic of the HIV infection observed in patients.Comment: 14 pages, 6 figures, 21 references, Latex style Elsar

Cloud condensation nuclei in polluted air and biomass burning smoke near the mega-city Guangzhou, China – Part 2: Size-resolved aerosol chemical composition, diurnal cycles, and externally mixed weakly CCN-active soot particles

Size-resolved chemical composition, mixing state, and cloud condensation nucleus (CCN) activity of aerosol particles in polluted mega-city air and biomass burning smoke were measured during the PRIDE-PRD2006 campaign near Guangzhou, China, using an aerosol mass spectrometer (AMS), a volatility tandem differential mobility analyzer (VTDMA), and a continuous-flow CCN counter (DMT-CCNC). The size-dependence and temporal variations of the effective average hygroscopicity parameter for CCN-active particles (κa) could be parameterized as a function of organic and inorganic mass fractions (forg, finorg) determined by the AMS: κa,p=κorg·forg + κinorg·finorg. The characteristic κ values of organic and inorganic components were similar to those observed in other continental regions of the world: κorg≈0.1 and κinorg≈0.6. The campaign average κa values increased with particle size from ~0.25 at ~50 nm to ~0.4 at ~200 nm, while forg decreased with particle size. At ~50 nm, forg was on average 60% and increased to almost 100% during a biomass burning event. The VTDMA results and complementary aerosol optical data suggest that the large fractions of CCN-inactive particles observed at low supersaturations (up to 60% at S≤0.27%) were externally mixed weakly CCN-active soot particles with low volatility (diameter reduction <5% at 300 °C) and effective hygroscopicity parameters around κLV≈0.01. A proxy for the effective average hygroscopicity of the total ensemble of CCN-active particles including weakly CCN-active particles (κt) could be parameterized as a function of κa,p and the number fraction of low volatility particles determined by VTDMA (φLV): κt,p=κa,p−φLV·(κa,p−κLV). Based on κ values derived from AMS and VTDMA data, the observed CCN number concentrations (NCCN,S≈102–104 cm−3 at S = 0.068–0.47%) could be efficiently predicted from the measured particle number size distribution. The mean relative deviations between observed and predicted CCN concentrations were ~10% when using κt,p, and they increased to ~20% when using only κa,p. The mean relative deviations were not higher (~20%) when using an approximate continental average value of κ≈0.3, although the constant κ value cannot account for the observed temporal variations in particle composition and mixing state (diurnal cycles and biomass burning events). Overall, the results confirm that on a global and climate modeling scale an average value of κ≈0.3 can be used for approximate predictions of CCN number concentrations in continental boundary layer air when aerosol size distribution data are available without information about chemical composition. Bulk or size-resolved data on aerosol chemical composition enable improved CCN predictions resolving regional and temporal variations, but the composition data need to be highly accurate and complemented by information about particle mixing state to achieve high precision (relative deviations <20%)

Tumor infiltrating effector memory Antigen-Specific CD8+ T Cells predict response to immune checkpoint therapy

Immune checkpoint therapy (ICT) results in durable responses in individuals with some cancers, but not all patients respond to treatment. ICT improves CD8+ cytotoxic T lymphocyte (CTL) function, but changes in tumor antigen-specific CTLs post-ICT that correlate with successful responses have not been well characterized. Here, we studied murine tumor models with dichotomous responses to ICT. We tracked tumor antigen-specific CTL frequencies and phenotype before and after ICT in responding and non-responding animals. Tumor antigen-specific CTLs increased within tumor and draining lymph nodes after ICT, and exhibited an effector memory-like phenotype, expressing IL-7R (CD127), KLRG1, T-bet, and granzyme B. Responding tumors exhibited higher infiltration of effector memory tumor antigen-specific CTLs, but lower frequencies of regulatory T cells compared to non-responders. Tumor antigen-specific CTLs persisted in responding animals and formed memory responses against tumor antigens. Our results suggest that increased effector memory tumor antigen-specific CTLs, in the presence of reduced immunosuppression within tumors is part of a successful ICT response. Temporal and nuanced analysis of T cell subsets provides a potential new source of immune based biomarkers for response to ICT

Exploring the atmospheric chemistry of nitrous acid (HONO) at a rural site in Southern China

We performed measurements of nitrous acid (HONO) during the PRIDE-PRD2006 campaign in the Pearl River Delta region 60 km north of Guangzhou, China, for 4 weeks in June 2006. HONO was measured by a LOPAP in-situ instrument which was setup in one of the campaign supersites along with a variety of instruments measuring hydroxyl radicals, trace gases, aerosols, and meteorological parameters. Maximum diurnal HONO mixing ratios of 1–5 ppb were observed during the nights. We found that the nighttime build-up of HONO can be attributed to the heterogeneous NO2 to HONO conversion on ground surfaces and the OH + NO reaction. In addition to elevated nighttime mixing ratios, measured noontime values of ≈200 ppt indicate the existence of a daytime source higher than the OH + NO→HONO reaction. Using the simultaneously recorded OH, NO, and HONO photolysis frequency, a daytime additional source strength of HONO (PM) was calculated to be 0.77 ppb h−1 on average. This value compares well to previous measurements in other environments. Our analysis of PM provides evidence that the photolysis of HNO3 adsorbed on ground surfaces contributes to the HONO formation