Approximate high energy alpha-particle nucleus collision model

Alpha particle-nucleus collision model for nucleon energy and angular distribution prediction and residual nuclei cross section

Piggyback Weather Experimentation: Superimposing Randomized Treatment Comparisons on Commercial Cloud Seeding Operation

Cover series statement: Technical Report 81/2ISWS Publications Catalog (1995, p. 22) lists as Contract Report no. 255, with series statement Technical Report 81/2 in the citation.published or submitted for publicationis peer reviewedOpe

Spacial distributions of major phytoplankton community components in Narragansett Bay at the peak of the winter-spring bloom

The horizontal distribution of phytoplankton in western Narragansett Bay at the height of the 1978 winter-spring bloom was characterized using data from an airborne fluorosensor to extend in situ point measurements of chlorophyll a and phytoplankton population composition to linear or area coverage...

The Assessment of Statistical-physical Techniques for the Evaluation of Weather Modification Operations

published or submitted for publicationis peer reviewedOpe

The holographic RG flow in a field theory on a curved background

As shown by Freedman, Gubser, Pilch and Warner, the RG flow in ${\cal N}=4$ super-Yang-Mills theory broken to an ${\cal N}=1$ theory by the addition of a mass term can be described in terms of a supersymmetric domain wall solution in five-dimensional ${\cal N}=8$ gauged supergravity. The FGPW flow is an example of a holographic RG flow in a field theory on a flat background. Here we put the field theory studied by Freedman, Gubser, Pilch and Warner on a curved $AdS_4$ background, and we construct the supersymmetric domain wall solution which describes the RG flow in this field theory. This solution is a curved (non Ricci flat) domain wall solution. This example demonstrates that holographic RG flows in supersymmetric field theories on a curved $AdS_4$ background can be described in terms of curved supersymmetric domain wall solutions.Comment: 14 pages, LaTe

Robust computer vision system for marbling meat segmentation

In this study, we developed a robust automatic computer vision system for marbling meat segmentation. Our approach can segment muscle fat in various marbled meat samples using images acquired with different quality devices in an uncontrolled environment, where there was external ambient light and artificial light; thus, professionals can apply this method without specialized knowledge in terms of sample treatments or equipment, as well as without disruption to normal procedures, thereby obtaining a robust solution. The proposed approach for marbling segmentation is based on data clustering and dynamic thresholding. Experiments were performed using two datasets that comprised 82 images of 41 longissimus dorsi muscles acquired by different sampling devices. The experimental results showed that the computer vision system performed well with over 98% accuracy and a low number of false positives, regardless of the acquisition device employed