scholarly journals A novel background reduction strategy for high level triggers and processing in gamma-ray Cherenkov detectors

2008 ◽  
Author(s):  
G. Cabras ◽  
A. De Angelis ◽  
B. De Lotto ◽  
M. M. De Maria ◽  
F. De Sabata ◽  
...  
Keyword(s):  
Gamma Ray ◽  
Cherenkov Detectors ◽  
Reduction Strategy ◽  
Background Reduction ◽  
High Level

scholarly journals Progress on next generation gamma-ray Cherenkov detectors for the National Ignition Facility

2018 ◽  
Vol 89 (10) ◽  
pp. 10I148 ◽  
Author(s):  
H. W. Herrmann ◽  
Y. H. Kim ◽  
A. B. Zylstra ◽  
H. Geppert-Kleinrath ◽  
K. D. Meaney ◽  
...  
Keyword(s):  
Gamma Ray ◽  
Next Generation ◽  
National Ignition Facility ◽  
Cherenkov Detectors

scholarly journals Aluminum abundance on the surface of Mercury: Application of a new background-reduction technique for the analysis of gamma-ray spectroscopy data

2012 ◽  
Vol 117 (E12) ◽  
pp. n/a-n/a ◽  
Author(s):  
Patrick N. Peplowski ◽  
Edgar A. Rhodes ◽  
David K. Hamara ◽  
David J. Lawrence ◽  
Larry G. Evans ◽  
...  
Keyword(s):  
Gamma Ray ◽  
Reduction Technique ◽  
Spectroscopy Data ◽  
Background Reduction ◽  
Gamma Ray Spectroscopy

Evaluation of gamma ray-induced gastrointestinal tract morphological and proliferative activity changes in rhesus monkeys

2016 ◽  
Vol 35 (10) ◽  
pp. 1133-1144
Author(s):  
T Chen ◽  
L Wang ◽  
K Chen ◽  
S Qiu ◽  
X Cen ◽  
...  
Keyword(s):  
Gastrointestinal Tract ◽  
Rhesus Monkeys ◽  
Gamma Ray ◽  
Radiation Group ◽  
Brdu Labeling ◽  
Brdu Immunohistochemistry ◽  
Gamma Ray Irradiation ◽  
Colon And Rectum ◽  
Total Body ◽  
High Level

To provide support for future pharmacology and preclinical studies, we have established a stable nonhuman primate animal model to demonstrate the histopathological changes in the gastrointestinal tract following gamma ray irradiation. In this study, 12 healthy rhesus monkeys were divided into 2 groups (control and radiation groups). Animals in the radiation group were exposed to gamma rays (cobalt 60 source) at a dose level of 6.5 Gy total body irradiation bilaterally (i.e. 3.25 Gy on each side). Control animals were sham exposed using identical procedures. After a 5-day in-life observation period, gastrointestinal tract tissues (esophagus, stomach, duodenum, jejunum, ileum, colon, and rectum) were collected and fixed in 10% neutral-buffered formalin for subsequent hematoxylin and eosin and 5-bromo-2-deoxyuridine (BrdU) immunohistochemistry processing. The results showed that the esophagus was undergoing degeneration without obvious inflammatory changes, while the stomach and duodenum exhibited both degeneration and inflammation. From the jejunum to the rectum, late-stage inflammation with glandular regeneration, as well as a high-level BrdU labeling index, was present.

Subsurface Characterization Using Ensemble Machine Learning

2021 ◽  
Author(s):  
Gorka G Leiceaga ◽  
Robert Balch ◽  
George El-kaseeh
Keyword(s):  
Machine Learning ◽  
Reservoir Characterization ◽  
Gamma Ray ◽  
Complex Model ◽  
Scientific Model ◽  
Adequate Model ◽  
Subsurface Characterization ◽  
Ensemble Machine Learning ◽  
Data Driven Approach ◽  
High Level

Abstract Reservoir characterization is an ambitious challenge that aims to predict variations within the subsurface using fit-for-purpose information that follows physical and geological sense. To properly achieve subsurface characterization, artificial intelligence (AI) algorithms may be used. Machine learning, a subset of AI, is a data-driven approach that has exploded in popularity during the past decades in industries such as healthcare, banking and finance, cryptocurrency, data security, and e-commerce. An advantage of machine learning methods is that they can be implemented to produce results without the need to have first established a complete theoretical scientific model for a problem – with a set of complex model equations to be solved analytically or numerically. The principal challenge of machine learning lies in attaining enough training information, which is essential in obtaining an adequate model that allows for a prediction with a high level of accuracy. Ensemble machine learning in reservoir characterization studies is a candidate to reduce subsurface uncertainty by integrating seismic and well data. In this article, a bootstrap aggregating algorithm is evaluated to determine its potential as a subsurface discriminator. The algorithm fits decision trees on various sub-samples of a dataset and uses averaging to improve the accuracy of the prediction without over-fitting. The gamma ray results from our test dataset show a high correlation with the measured logs, giving confidence in our workflow applied to subsurface characterization.

Optimized background reduction in low-level gamma-ray spectrometry at a surface laboratory

2006 ◽  
Vol 64 (9) ◽  
pp. 1006-1012 ◽  
Author(s):  
S. Hurtado ◽  
M. García-León ◽  
R. García-Tenorio
Keyword(s):  
Gamma Ray ◽  
Gamma Ray Spectrometry ◽  
Background Reduction ◽  
Low Level

scholarly journals Fermi: Monitoring the Gamma-Ray Universe

Galaxies ◽  
2018 ◽  
Vol 6 (4) ◽  
pp. 117 ◽  
Author(s):  
David Thompson
Keyword(s):  
Response Time ◽  
Real Time ◽  
Gamma Ray ◽  
High Redshift ◽  
Large Area ◽  
Long Duration ◽  
Level Data ◽  
High Level ◽  
Atmospheric Phenomena ◽  
Scientific Return

Since 2008, the Large Area Telescope and the Gamma-ray Burst Monitor on the Fermi Gamma-ray Space Telescope have been monitoring the entire sky at energies from about 8 keV to more than 1 TeV. Photon-level data and high-level data products are made publicly available in near-real time, and efforts continue to improve the response time. This long-duration, all-sky monitoring has enabled a broad range of science, from atmospheric phenomena on Earth to signals from high-redshift sources. The Fermi instrument teams have worked closely with multiwavelength and multi-messenger observers and theorists to maximize the scientific return from the observatory, and they look forward to continued cooperative efforts as Fermi moves into its second decade of operation.

Gamma-ray spectrometry observations to monitor a presumed meteoritic signature at Maâdna crater (Talemzane, Algeria)

2020 ◽  
Author(s):  
Atmane Lamali ◽  
Lamine Hamai ◽  
Sid Ahmed Mokhtar ◽  
Abdelkrim Yelles-chaouche ◽  
Abdeslam Abtout ◽  
...  
Keyword(s):  
Gamma Ray ◽  
Sedimentary Rocks ◽  
Clay Content ◽  
Gamma Ray Spectrometry ◽  
Gamma Spectrometer ◽  
Geophysical Method ◽  
Impact Cratering ◽  
High Level ◽  
The Impact

<p>By measuring changes in radioelement concentrations, gamma-ray spectrometry is increasingly emerging as an efficient geophysical method that allows such changes to be geologically mapped according to lithology and soil type. At Maâdna crater in southern Algeria, this method has been used to monitor any changes in the composition of the target rocks that may be associated with the impact cratering process. For this purpose, several measurements were carried out in situ using a portable field gamma spectrometer. As a result, most predominantly calcareous surface lithologies, exposed on the rim and flanks of the crater, showed a very low emitted radiometric response over the three channels (K, Th, U). However, no more than 90 Cps were counted both inside and outside the crater. Such a rate is indeed expected in sedimentary rocks with low clay content, and this remains valid, as long as other exogenous mineralogical enrichments are excluded. On the other hand, the contoured radioelement concentrations maps, have demonstrated an anomalous enhanced gamma radiation levels of potassium-dominated peaks over the central part of the crater and in the surrounding wadis. Nevertheless, the central potassium anomaly is well correlated with the shallower magnetic one that has been described in previous studies (see e.g. Lamali et al., 2016). Therefore, either near the surrounding wadis or in the central part of this crater, this anomalously high level of radioactivity may be linked to an accumulation of later altered deposits. Consequently, there are no objective criteria to link these results to an impact event occurring at the Maâdna structure, similar to what was done at the Serra da Cangalha crater (Vasconcelos et al., 2012).</p>

scholarly journals Open high-level data formats and software for gamma-ray astronomy

2017 ◽  
Author(s):  
Christoph Deil ◽  
Catherine Boisson ◽  
Karl Kosack ◽  
Jeremy Perkins ◽  
Johannes King ◽  
...  
Keyword(s):  
Gamma Ray ◽  
Gamma Ray Astronomy ◽  
Data Formats ◽  
Level Data ◽  
High Level
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