Track recording plastic compositions

Improved nuclear track recording plastic compositions are provided which exhibit greatly decreased surface roughness when etched to produce visible tracks of energetic nuclear particles which have passed into and/or through said plastic. The improved compositions incorporate a small quantity of a phthalic acid ester into the major plastic component which is derived from the polymerization of monomeric di-ethylene glycol bis allyl carbonate. Di-substituted phthalic acid esters are preferred as the added component, with the further perference that the ester substituent has a chain length of 2 or more carbon atoms. The inclusion of the phthalic acid ester to an extent of from about 1-2% by weight of the plastic compositions is sufficient to drastically reduce the surface roughness ordinarily produced when the track recording plastic is contacted by etchants

Heavy Nucleus Collector (HNC) project for the NASA Long Duration Exposure Facility (LDEF)

The primary goal of the heavy nucleus collector (HNC) experiment was to obtain high resolution composition measurements for cosmic ray nuclei in the platinum-lead and actinide region of the periodic table. Secondary objectives include studies of selected groups of elements of lower charge. These goals were to be realized by orbiting a large area array of dielectric nuclear track detectors in space for several years. In this time sufficient actinide nuclei would be collected to determine the nucleosynthetic age of the cosmic radiation and the relative mix of r- and s-process elements in the cosmic ray source. The detector consists of approximately 50 trays assembled in pressurized canisters. Each tray would contain 8 half-stacks (4 stacks total) and an event thermometer which would record the temperature of each event at the time of exposure. Each stack would contain 7 layers of Rodyne-P, CR-39 and Cronar plastic track detectors interleaved with copper stripping foils. Upon return to Earth, detectors would be removed for analysis. Ultraheavy nuclei would have left tracks through the detector sheets that would be made visible after etching in a hot sodium hydroxide solution

Constraints on the Intergalactic Transport of Cosmic Rays

Motivated by recent experimental proposals to search for extragalactic cosmic rays (including anti-matter from distant galaxies), we study particle propagation through the intergalactic medium (IGM). We first use estimates of the magnetic field strength between galaxies to constrain the mean free path for diffusion of particles through the IGM. We then develop a simple analytic model to describe the diffusion of cosmic rays. Given the current age of galaxies, our results indicate that, in reasonable models, a completely negligible number of particles can enter our Galaxy from distances greater than $\sim 100$ Mpc for relatively low energies ($E$ $< 10^6$ GeV/n). We also find that particle destruction in galaxies along the diffusion path produces an exponential suppression of the possible flux of extragalactic cosmic rays. Finally, we use gamma ray constraints to argue that the distance to any hypothetical domains of anti-matter must be roughly comparable to the horizon scale.Comment: 24 pages, AAS LaTex, 1 figure, accepted to Ap

Unbiased clustering estimates with the DESI fibre assignment

The Emission Line Galaxy survey made by the Dark Energy Spectroscopic Instrument (DESI) survey will be created from five passes of the instrument on the sky. On each pass, the constrained mobility of the ends of the fibres in the DESI focal plane means that the angular-distribution of targets that can be observed is limited. Thus, the clustering of samples constructed using a limited number of passes will be strongly affected by missing targets. In two recent papers, we showed how the effect of missing galaxies can be corrected when calculating the correlation function using a weighting scheme for pairs. Using mock galaxy catalogues we now show that this method provides an unbiased estimator of the true correlation function for the DESI survey after any number of passes. We use multiple mocks to determine the expected errors given one to four passes, compared to an idealised survey observing an equivalent number of randomly selected targets. On BAO scales, we find that the error is a factor 2 worse after one pass, but that after three or more passes, the errors are very similar. Thus we find that the fibre assignment strategy enforced by the design of DESI will not affect the cosmological measurements to be made by the survey, and can be removed as a potential risk for this experiment.Comment: 11 pages, 8 figure

Properties and Interactions of Elementary Particles

We summarize the accomplishments over the last renewal period in a broad program of research in experimental and theoretical High Energy Physics, conducted at the University of Michigan, and supported by the U.S. Department of Energy

Properties and Interactions of Elementary Particles

We summarize the accomplishments over the last renewal period in a broad program of research in experimental and theoretical High Energy Physics, conducted at the University of Michigan, and supported by the U.S. Department of Energy

Quem vai comprar esse CD?

TCC (graduação) - Universidade Federal de Santa Catarina. Centro de Comunicação e Expressão. Jornalismo.Documentário em vídeo acerca da trajetória dos novos artistas independentes da música brasileira, que desenvolvem e distribuem seu trabalho por meio da internet e de suas plataformas. Através do depoimento de seis artistas, o vídeo problematiza as transformações que a era digital provocou no cenário da música brasileira, não apenas no que se refere à produção e distribuição, mas também na estética. O principal objetivo é mostrar as possibilidades que a internet proporciona para os músicos, que agora têm mais liberdade para criar e mais independência para distribuir seu trabalho. São abordados aspectos como: o crescimento das empresas que oferecem serviços de streaming e os impactos disto na indústria fonográfica; o espaço que a internet abriu para o ativismo político; um comparativo entre a tradicional indústria fonográfica e os novos formatos de venda de produtos culturais na web; além de um breve panorama avaliando as diferenças existentes entre o mercado de músicas na web no Brasil e nos Estados Unidos

Optimizing automatic morphological classification of galaxies with machine learning and deep learning using Dark Energy Survey imaging

There are several supervised machine learning methods used for the application of automated morphological classification of galaxies; however, there has not yet been a clear comparison of these different methods using imaging data, or a investigation for maximising their effectiveness.We carry out a comparison between several common machine learning methods for galaxy classification (Convolutional Neural Network (CNN), K-nearest neighbour, LogisticRegression, Support Vector Machine, Random Forest, and Neural Networks) by using DarkEnergy Survey (DES) data combined with visual classifications from the Galaxy Zoo 1 project(GZ1). Our goal is to determine the optimal machine learning methods when using imaging data for galaxy classification. We show that CNN is the most successful method of these ten methods in our study. Using a sample of _2,800 galaxies with visual classification from GZ1, we reach an accuracy of _0.99 for the morphological classification of Ellipticals and Spirals. The further investigation of the galaxies that have a different ML and visual classification but with high predicted probabilities in our CNN usually reveals an the incorrect classification provided by GZ1. We further find the galaxies having a low probability of being either spirals or ellipticals are visually Lenticulars (S0), demonstrating that supervised learning is able to rediscover that this class of galaxy is distinct from both Es and Spirals.We confirm that _2.5% galaxies are misclassified by GZ1 in our study. After correcting these galaxies’ labels, we improve our CNN performance to an average accuracy of over 0.99 (accuracy of 0.994 is our best result)