Combinatorial Pharyngeal Taste Coding for Feeding Avoidance in Adult Drosophila.

Taste drives appropriate food preference and intake. In Drosophila, taste neurons are housed in both external and internal organs, but the latter have been relatively underexplored. Here, we report that Poxn mutants with a minimal taste system of pharyngeal neurons can avoid many aversive tastants, including bitter compounds, acid, and salt, suggesting that pharyngeal taste is sufficient for rejecting intake of aversive compounds. Optogenetic activation of selected pharyngeal bitter neurons during feeding events elicits changes in feeding parameters that can suppress intake. Functional dissection experiments indicate that multiple classes of pharyngeal neurons are involved in achieving behavioral avoidance, by virtue of being inhibited or activated by aversive tastants. Tracing second-order pharyngeal circuits reveals two main relay centers for processing pharyngeal taste inputs. Together, our results suggest that the pharynx can control the ingestion of harmful compounds by integrating taste input from different classes of pharyngeal neurons

Effect of Native Defects on Optical Properties of InxGa1-xN Alloys

The energy position of the optical absorption edge and the free carrier populations in InxGa1-xN ternary alloys can be controlled using high energy 4He+ irradiation. The blue shift of the absorption edge after irradiation in In-rich material (x > 0.34) is attributed to the band-filling effect (Burstein-Moss shift) due to the native donors introduced by the irradiation. In Ga-rich material, optical absorption measurements show that the irradiation-introduced native defects are inside the bandgap, where they are incorporated as acceptors. The observed irradiation-produced changes in the optical absorption edge and the carrier populations in InxGa1-xN are in excellent agreement with the predictions of the amphoteric defect model

Model Order Estimation in the Presence of multipath Interference using Residual Convolutional Neural Networks

Model order estimation (MOE) is often a pre-requisite for Direction of Arrival (DoA) estimation. Due to limits imposed by array geometry, it is typically not possible to estimate spatial parameters for an arbitrary number of sources; an estimate of the signal model is usually required. MOE is the process of selecting the most likely signal model from several candidates. While classic methods fail at MOE in the presence of coherent multipath interference, data-driven supervised learning models can solve this problem. Instead of the classic MLP (Multiple Layer Perceptions) or CNN (Convolutional Neural Networks) architectures, we propose the application of Residual Convolutional Neural Networks (RCNN), with grouped symmetric kernel filters to deliver state-of-art estimation accuracy of up to 95.2\% in the presence of coherent multipath, and a weighted loss function to eliminate underestimation error of the model order. We show the benefit of the approach by demonstrating its impact on an overall signal processing flow that determines the number of total signals received by the array, the number of independent sources, and the association of each of the paths with those sources . Moreover, we show that the proposed estimator provides accurate performance over a variety of array types, can identify the overloaded scenario, and ultimately provides strong DoA estimation and signal association performance

Government Data and the Invisible Hand

If President Barack Obama\u27s new administration really wants to embrace the potential of Internet-enabled government transparency, it should follow a counter-intuitive but ultimately compelling strategy: reduce the federal role in presenting important government information to citizens. Today, government bodies consider their own Web sites to be a higher priority than technical infrastructures that open up their data for others to use. We argue that this understanding is a mistake. It would be preferable for government to understand providing reusable data, rather than providing Web sites, as the core of its online publishing responsibility. During the presidential campaign, all three major candidates indicated that they thought the federal government could make better use of the Internet. Barack Obama\u27s platform went the furthest and explicitly endorsed maling government data available online in universally accessible formats. Hillary Clinton, meanwhile, remarked that she wanted to see much more government information online. John McCain\u27s platform called for a new Office of Electronic Government. But the situation to which these candidates were responding-the wide gap between the exciting uses of Internet technology by private parties, on the one hand, and the government\u27s lagging technical infrastructure, on the other-is not new. A minefield of federal rules and a range of other factors, prevent government Web masters from keeping pace with the evergrowing potential of the Internet

RPMDrate: Bimolecular chemical reaction rates from ring polymer molecular dynamics

We present RPMDrate, a computer program for the calculation of gas phase bimolecular reaction rate coefficients using the ring polymer molecular dynamics (RPMD) method. The RPMD rate coefficient is calculated using the Bennett–Chandler method as a product of a static (centroid density quantum transition state theory (QTST) rate) and a dynamic (ring polymer transmission coefficient) factor. The computational procedure is general and can be used to treat bimolecular polyatomic reactions of any complexity in their full dimensionality. The program has been tested for the H+H2, H+CH4, OH+CH4 and H+C2H6 reactions.United States. Dept. of Energy (Office of Basic Energy Sciences under the Energy Frontier Research Center for Combustion Science (Grant No. DE-SC0001198))United States. Dept. of Energy (Energy Frontier Research Center for Combustion Science, Combustion Energy Research Fellowship)King Abdullah University of Science and Technology (Award No. KUS-I1-010-01

Charge transfer between lead halide perovskite nanocrystals and single-walled carbon nanotubes

© 2020 The Royal Society of Chemistry. A charge transfer study between lead halide-based perovskite nanocrystals and single-walled carbon nanotubes (PNC@CNT nanocomposite) was performed. Solution-processed MAPbX3 PNCs displayed very bright luminescence, but it quenched in the presence of CNTs. This was attributed to the electron transfer from PNCs to CNTs. The detailed changes in fluorescence lifetime were investigated through time-correlated single-photon counting (TCSPC), which suggested mixed static and dynamic quenching along with a decrease in the lifetime. Morphological changes were investigated via transmission electron microscopy (TEM) and attributed to the incorporation of PNCs on long CNTs. Also, the PNC@CNT nanocomposite was explored for photoinduced current response, which indicated an ∼3 fold increase in photoconductivity under light illumination (with a 1 mV bias). This electron transfer study between PNCs and CNTs contributes to the exploration of charge dynamics