Graphs of calculations of energy deposition and air fluorescence from radiation produced by a nuclear explosion in space /

"Part of this work done under ARPA Order 631, Program Code No. 5820."

Effects of nuclear ground state correlations on pion scattering /

"LA-UR-76-1844."

Air fluorescence excited by high-altitude nuclear explosions /

"United States Atomic Energy Commission Contract W-7405-Eng. 36"--Cover.

Elastic pion-nucleus scattering for studies of the nuclear surface /

"Issued : June 1972"

Physical methods applicable to the detection of Trichinella spiralis in pork,

Mode of access: Internet.

Molecular bandpass amplifiers. Contract AF33(616)-7252. Interim scientific report no. 1- [of the] Development Laboratory, Semiconductor Division, Hughes Aircraft Co.

Mode of access: Internet.

HiberActive: Pro-Active Archiving of Web References from Scholarly Articles

Presentation at Open Repositories 2014, Helsinki, Finland, June 9-13, 2014

Experiencing Science in Action: The Use of Exhibition Techniques in Guided Tours to a Scientific Laboratory

The current paper presents a study conducted at CERN, Switzerland, to investigate visitors' and tour guides' use and appreciation of existing panels at visit itinerary points. The results were used to develop a set of recommendations for constructing optimal panels to assist the guides' explanation.

USLE and WEPP Soil Erosion Models: Their Applicability and Use in Generating Cover Values to Stabilize Soil in the Los Alamos, New Mexico Area

Soil erosion is a naturally occurring process that involves the detachment, transport, and deposition of soil particles. Disturbances such as thinning and wildfire can reduce cover greatly and increase erosion rates. Forest managers may use erosion prediction tools, such as the Universal Soil Loss Equation (USLE) and Water Erosion Prediction Project (WEPP) to estimate erosion rates and develop techniques to manage erosion. However, it is important to understand the differences and the applications of each model. Erosion rates were generated by each model and the model most applicable to the study site, Los Alamos, New Mexico was determined. It was also used to find the amount of cover needed to stabilize soil. The USLE is a simpler model and less complicated than a computer model like WEPP, and thus easier to manipulate to estimate cover values. Predicted cover values were compared to field cover values. Cover is necessary to establish effective erosion control guidelines.

Introduction to quantum mechanics : a course at Los Alamos University /

Mode of access: Internet.

CTSS mini-reference /

"Under the auspices of the U.S. Department of Energy by the Los Alamos National Laboratory under contract W-7405-Eng.36"--P. [3] of cover.

DECISION TREE CLASSIFIERS FOR STAR/GALAXY SEPARATION

We study the star/galaxy classification efficiency of 13 different decision tree algorithms applied to photometric objects in the Sloan Digital Sky Survey Data Release Seven (SDSS-DR7). Each algorithm is defined by a set of parameters which, when varied, produce different final classification trees. We extensively explore the parameter space of each algorithm, using the set of 884,126 SDSS objects with spectroscopic data as the training set. The efficiency of star-galaxy separation is measured using the completeness function. We find that the Functional Tree algorithm (FT) yields the best results as measured by the mean completeness in two magnitude intervals: 14 <= r <= 21 (85.2%) and r >= 19 (82.1%). We compare the performance of the tree generated with the optimal FT configuration to the classifications provided by the SDSS parametric classifier, 2DPHOT, and Ball et al. We find that our FT classifier is comparable to or better in completeness over the full magnitude range 15 <= r <= 21, with much lower contamination than all but the Ball et al. classifier. At the faintest magnitudes (r > 19), our classifier is the only one that maintains high completeness (> 80%) while simultaneously achieving low contamination (similar to 2.5%). We also examine the SDSS parametric classifier (psfMag - modelMag) to see if the dividing line between stars and galaxies can be adjusted to improve the classifier. We find that currently stars in close pairs are often misclassified as galaxies, and suggest a new cut to improve the classifier. Finally, we apply our FT classifier to separate stars from galaxies in the full set of 69,545,326 SDSS photometric objects in the magnitude range 14 <= r <= 21.

Distributed Repositories of Medieval Calendars and Crowd-Sourcing of Transcription

Presentation at Open Repositories 2014, Helsinki, Finland, June 9-13, 2014