Learning a Neural Semantic Parser from User Feedback

We present an approach to rapidly and easily build natural language interfaces to databases for new domains, whose performance improves over time based on user feedback, and requires minimal intervention. To achieve this, we adapt neural sequence models to map utterances directly to SQL with its full expressivity, bypassing any intermediate meaning representations. These models are immediately deployed online to solicit feedback from real users to flag incorrect queries. Finally, the popularity of SQL facilitates gathering annotations for incorrect predictions using the crowd, which is directly used to improve our models. This complete feedback loop, without intermediate representations or database specific engineering, opens up new ways of building high quality semantic parsers. Experiments suggest that this approach can be deployed quickly for any new target domain, as we show by learning a semantic parser for an online academic database from scratch.Comment: Accepted at ACL 201

Assessment of Diverse Solid−State Accelerated Autoxidation Methods for Droperidol

The present study aimed to investigate methods for accelerating autoxidation of crystalline drugs in the solid-state that can potentially predict real−time stability. Solid droperidol (DPD) was selected as the model drug. A common free−radical initiator, 2,2′−azobisisobutyronitrile (AIBN), was used to induce autoxidation in solutions. AIBN decomposes at elevated temperatures to yield carbon−centred cyano−isopropyl free radicals that can auto−oxidize neighboring drug molecules. Although the reaction of AIBN is relatively straightforward in solution, it is less so in solids. In this study, we used solid AIBN mixed with DPD powder in the presence and absence of pressurized oxygen headspace. Samples were prepared directly in the form of binary mixtures with DPD and additionally in the form of powder compact/pellet with DPD. The main challenge in carrying out the reaction was related to the preservation of AIBN at elevated temperatures due to the disintegration of the pellet containing the latter. A commercially available free−radical coated silica particle (i.e., 2,2,6,6−tetramethyl−1−piperinyloxy (TEMPO) or (SiliaCAT(TM) TEMPO)) was tested as a potential stressor, but with limited success to induce autoxidation. The most valuable results were obtained when a physical mixture of pre−milled PVP K−60 containing free radicals and DPD was exposed to elevated oxygen−temperature conditions, which yielded significant degradation of DPD. The study highlights the practical challenges for conducting accelerated solid−state stress studies to assess the autoxidation susceptibility of drugs using traditional free−radical initiators and presents a proof of application of milled PVP with free−radical as a potential alternative

Wet Chemical Feasible Synthesis of PPy-Nickel Oxide nanocomposites and their photocatalytic effects on Methylene Blue

In this paper, we report, the synthesis of conducting polymer nanocomposites of nickel oxide polypyrrole (NiO-PPy) doped with dodecyl benzene sulphonic acid for its application as a photocatalyst. In-situ polymerization of the pyrrole technique was employed along with oxidant ammonium persulphate and dodecyl benzene sulphonic acid as a dopant. The nanostructures were synthesized at different concentrations of NiO nanoparticles viz. 0.05 wt.%, 0.1 wt.%, 0.2 wt.% and 0.3 wt.%. The development of nanostructures was explored by Fourier Transform Infrared Spectrophotometer, Field Emission Scanning Electron Microscope, X-ray diffraction spectrometer, and electrical conductivity measurements. FTIR studies revealed a shift in the absorption band when pure PPy and NiO-PPy nanocomposites were studied, exhibiting the substantial interaction between the PPy network and the NiO. FE-SEM analysis demonstrated the consistent distribution of NiO with globular-shaped metal oxide materials in the PPy host template. The XRD studies for pure PPy revealed its amorphous nature while nanocomposites indicated the prominent NiO peaks arising from (111), (200) and (220) planes. The nanocomposites' direct electrical conductivity at room temperature was much higher than pure PPy. It was observed that the electrical conductivity for pure PPy was 0.409×10-5 S/cm while it substantially increased to 4.2×10-5 (S/cm) for 0.3% nanocomposite. The electrical studies revealed that the electrical conductivity goes on increasing with increased NiO concentration and then after a saturation point more PPy encapsulates the NiO and in turn reduces the electrical conductivity. With 50 mg of 0.3% nanocomposite, the photocatalytic degradation of the Methylene-Blue dye was 84.98%

Strategies for Low Carbon Growth In India: Industry and Non Residential Sectors

This report analyzed the potential for increasing energy efficiency and reducing greenhouse gas emissions (GHGs) in the non-residential building and the industrial sectors in India. The first two sections describe the research and analysis supporting the establishment of baseline energy consumption using a bottom up approach for the non residential sector and for the industry sector respectively. The third section covers the explanation of a modeling framework where GHG emissions are projected according to a baseline scenario and alternative scenarios that account for the implementation of cleaner technology

An approximate superposition method to obtain a planet's orbit

We demonstrate that the deviation produced by one celestial object on the Keplerian orbit of another around the Sun is largely independent of the presence of the remaining ones. Hence, to calculate the net deviation of an object from its Keplerian orbit, we superpose the deviations produced by every other object. We show that this method will be useful when dealing with a system containing a large number of objects. As a demonstration, we apply our method to the solar system, with a particular focus on the orbit of Uranus

Strategies for Low Carbon Growth In India: Industry and Non Residential Sectors

This report analyzed the potential for increasing energy efficiency and reducing greenhouse gas emissions (GHGs) in the non-residential building and the industrial sectors in India. The first two sections describe the research and analysis supporting the establishment of baseline energy consumption using a bottom up approach for the non residential sector and for the industry sector respectively. The third section covers the explanation of a modeling framework where GHG emissions are projected according to a baseline scenario and alternative scenarios that account for the implementation of cleaner technology