A PCA-based approach for subtracting thermal background emission in high-contrast imaging data

Ground-based observations at thermal infrared wavelengths suffer from large background radiation due to the sky, telescope and warm surfaces in the instrument. This significantly limits the sensitivity of ground-based observations at wavelengths longer than 3 microns. We analyzed this background emission in infrared high contrast imaging data, show how it can be modelled and subtracted and demonstrate that it can improve the detection of faint sources, such as exoplanets. We applied principal component analysis to model and subtract the thermal background emission in three archival high contrast angular differential imaging datasets in the M and L filter. We describe how the algorithm works and explain how it can be applied. The results of the background subtraction are compared to the results from a conventional mean background subtraction scheme. Finally, both methods for background subtraction are also compared by performing complete data reductions. We analyze the results from the M dataset of HD100546 qualitatively. For the M band dataset of beta Pic and the L band dataset of HD169142, which was obtained with an annular groove phase mask vortex vector coronagraph, we also calculate and analyze the achieved signal to noise (S/N). We show that applying PCA is an effective way to remove spatially and temporarily varying thermal background emission down to close to the background limit. The procedure also proves to be very successful at reconstructing the background that is hidden behind the PSF. In the complete data reductions, we find at least qualitative improvements for HD100546 and HD169142, however, we fail to find a significant increase in S/N of beta Pic b. We discuss these findings and argue that in particular datasets with strongly varying observing conditions or infrequently sampled sky background will benefit from the new approach.Comment: 12 pages, 17 figures, 1 table, Accepted for publication in A&

Measurement and Calibration of Noise Bias in Weak Lensing Galaxy Shape Estimation

Weak gravitational lensing has the potential to constrain cosmological parameters to high precision. However, as shown by the Shear TEsting Programmes (STEP) and GRavitational lEnsing Accuracy Testing (GREAT) Challenges, measuring galaxy shears is a nontrivial task: various methods introduce different systematic biases which have to be accounted for. We investigate how pixel noise on the image affects the bias on shear estimates from a Maximum-Likelihood forward model-fitting approach using a sum of co-elliptical S\'{e}rsic profiles, in complement to the theoretical approach of an an associated paper. We evaluate the bias using a simple but realistic galaxy model and find that the effects of noise alone can cause biases of order 1-10% on measured shears, which is significant for current and future lensing surveys. We evaluate a simulation-based calibration method to create a bias model as a function of galaxy properties and observing conditions. This model is then used to correct the simulated measurements. We demonstrate that this method can effectively reduce noise bias so that shear measurement reaches the level of accuracy required for estimating cosmic shear in upcoming lensing surveys.Comment: 12 pages, 4 figures, submitted to MNRA

A Model for the Development of Sustainable Innovations for the Early Phase of the Innovation Process

Current industrial development is faced by the global challenge to meet the continuously growing demand for capital and consumer goods in emerging countries while simultaneously ensuring a sustainable industrial growth in the social, environmental and economic dimension. By means of market dynamics of cooperation and competition in global value creation and knowledge networks, innovations geared towards sustainability can be essential drivers for realizing a sustainable development. The targeted development of new sustainable innovations is consequently a key activity in order to move towards sustainable industrial growth. This paper will describe a model for the development of sustainable innovations. The model focuses on idea generation in the early phase of the innovations process, addressing the fuzzy front end of innovation. In this context, specific goals and principles of sustainable development are integrated into a problem-solving approach. This integrated approach is subsequently used as a foundation for the targeted development of sustainable innovations in the frame of a workshop concept

Ethyl 4-[3-(2-methyl­benzo­yl)thio­ureido]benzoate

The mol­ecular conformation of the title compound, C18H18N2O3S, is stabilized by an intra­molecular N—H⋯O hydrogen bond. The crystal packing shows centrosymmetric dimers connected by N—H⋯S hydrogen bonds. The terminal eth­oxy substituents are statistically disordered [occupancy ratio 0.527 (5):0.473 (5)]

Sodium channel γENaC mediates IL-17 synergized high salt induced inflammatory stress in breast cancer cells

Chronic inflammation is known to play a critical role in the development of cancer. Recent evidence suggests that high salt in the tissue microenvironment induces chronic inflammatory milieu. In this report, using three breast cancer-related cell lines, we determined the molecular basis of the potential synergistic inflammatory effect of sodium chloride (NaCl) with interleukin-17 (IL-17). Combined treatment of high NaCl (0.15M) with sub-effective IL-17 (0.1nM) induced enhanced growth in breast cancer cells along with activation of reactive nitrogen and oxygen (RNS/ROS) species known to promote cancer. Similar effect was not observed with equi-molar mannitol. This enhanced of ROS/RNS activity correlates with upregulation of γENaC an inflammatory sodium channel. The similar culture conditions have also induced expression of pro-inflammatory cytokines such as IL-6, TNFα etc. Taken together, these data suggest that high NaCl in the cellular microenvironment induces a γENaC mediated chronic inflammatory response with a potential pro-carcinogenic effect

Differential Modulation of Human Glutamate Transporter Subtypes by Arachidonic Acid

Arachidonic acid has been proposed to be a messenger molecule released following synaptic activation of glutamate receptors and during ischemia. Here we demonstrate that micromolar levels of arachidonic acid inhibit glutamate uptake mediated by EAAT1, a human excitatory amino acid transporter widely expressed in brain and cerebellum, by reducing the maximal transport rate approximately 30%. In contrast, arachidonic acid increased transport mediated by EAAT2, a subtype abundantly expressed in forebrain and midbrain, by causing the apparent affinity for glutamate to increase more than 2-fold. The results demonstrate that the response of different glutamate transporter subtypes to arachidonic acid could influence synaptic transmission and modulate excitotoxicity via positive or negative feedback according to the transporter(s) present in a particular region

Electrogenic uptake of gamma-aminobutyric acid by a cloned transporter expressed in Xenopus oocytes

GAT-1, a gamma-aminobutyric acid (GABA) transporter cloned from rat brain, was expressed in Xenopus oocytes. Voltage-clamp measurements showed concentration-dependent, inward currents in response to GABA (K0.5 4.7 microM). The transport current required extracellular sodium and chloride ions; the Hill coefficient for chloride was 0.7, and that for sodium was 1.7. Correlation of current and [3H]GABA uptake measurements indicate that flux of one positive charge occurs per molecule of GABA transported. Membrane hyperpolarization from -40 to -100 mV increased the transport current approximately 3-fold. The results indicate that the transport of one molecule of GABA involves the co-transport of two sodium ions and one chloride ion