Carbon incorporation in ZnSe grown by metalorganic chemical vapor deposition

Carbon incorporation in ZnSe films grown by metalorganic chemical vapor deposition is reported. Secondary‐ion mass spectrometry measurements in ZnSe films grown from methylallylselenide and dimethylzinc show an enhanced carbon accumulation at the interface between ZnSe and GaAs. The carbon incorporation in the bulk ZnSe increases with the VI/II ratio and for a value of VI/II=3–4, the amount of incorporated carbon abruptly jumps to concentrations of 10^(21) cm^(−3), whereupon the films become polycrystalline. A new shallow peak I^C at 2.7920 eV dominates the near‐band‐edge low‐temperature photoluminescence spectra of all carbon‐contaminated ZnSe films. The intensity and linewidth of I^C increase with the VI/II ratio in a similar manner to the carbon concentration. This peak is proposed to be due to the radiative decay of excitons bound to a complex defect, which is associated with the presence of carbon in the films

Quantification of Lipophilicity of 1,2,4-Triazoles Using Micellar Chromatography

High-performance liquid chromatography (HPLC), over-pressured-layer chromatography (OPLC) and thin-layer chromatography (TLC) techniques with micellar mobile phases were proposed to evaluate the lipophilicity of 21 newly synthesized 1,2,4-triazoles, compounds of potential importance in medicine or agriculture as fungicides. Micellar parameters log km were compared with extrapolated RM0 values determined from reversed-phase (RP) TLC experimental data obtained on RP-8 stationary phases as well as with log P values (Alog Ps, AClog P, Alog P, Mlog P, KowWin, xlog P2 and xlog P3) calculated from molecular structures of solutes tested. The results obtained by applying principal component analysis (PCA) and linear regression showed considerable similarity between partition and retention parameters as alternative lipophilicity descriptors, and indicated micellar chromatography as a suitable technique to study lipophilic properties of organic substances. In micellar HPLC, RP-8e column (Purospher) was applied, whereas in OPLC and TLC, RP-CN plates were applied, which was the novelty of this study and allowed the use of micellar effluents in planar chromatography measurements

Current Bibliography 2012

Current Bibliography 201

Nurses\u27 Alumnae Association Bulletin - Volume 2 Number 1

March of Activities Treasurer\u27s Report It\u27s a Date Loyalty Coming Events Jefferson News In Florida for Winter The A.N.A. Convention Greetings! Keeping Up the Fight Eight Hour Committee Nurses Wanted Class of 1926 Convention Notes Attention Members Pine Street News Class of 1915 Class of 1916 Fifth Anniversary Prize Winners - 1932 Class of 1940 Owners of Scrap Books Sick List - 1939 and 1940 A Program of Nursing Information Please Private Duty Section Excerpts from Alumnae Minutes Staff News Please Remember Personals Engagements Marriages Deaths Hospital News Ballot for Officers Recent Births Lest You Forget! Please Change My Addres

Current Bibliography 2008

Current Bibliography 200

Current Bibliography 2010

Current Bibliography 201

Project RISE: Recognizing Industrial Smoke Emissions

Industrial smoke emissions pose a significant concern to human health. Prior works have shown that using Computer Vision (CV) techniques to identify smoke as visual evidence can influence the attitude of regulators and empower citizens to pursue environmental justice. However, existing datasets are not of sufficient quality nor quantity to train the robust CV models needed to support air quality advocacy. We introduce RISE, the first large-scale video dataset for Recognizing Industrial Smoke Emissions. We adopted a citizen science approach to collaborate with local community members to annotate whether a video clip has smoke emissions. Our dataset contains 12,567 clips from 19 distinct views from cameras that monitored three industrial facilities. These daytime clips span 30 days over two years, including all four seasons. We ran experiments using deep neural networks to establish a strong performance baseline and reveal smoke recognition challenges. Our survey study discussed community feedback, and our data analysis displayed opportunities for integrating citizen scientists and crowd workers into the application of Artificial Intelligence for social good.Comment: Technical repor

Current Bibliography 2011

Current Bibliography 201

Current Bibliography 2009

Current Bibliography 200