scholarly journals Assessing the Seismicity of Shillong Plateau Using 'b value'

2021 ◽  
Vol 7 (2) ◽  
Author(s):  
Siangshai Double M ◽  
Walia Devesh ◽  
Saxena Atul ◽  
Lyngdoh Andrew Cuthbert
Keyword(s):  
B Value ◽  
Shillong Plateau

Mapping of b-value Beneath the Shillong Plateau

2005 ◽  
Vol 8 (2) ◽  
pp. 271-276 ◽  
Author(s):  
P.K. Khan
Keyword(s):  
B Value ◽  
Shillong Plateau

scholarly journals Recent seismic status of Shillong Plateau, Northeast India

BIBECHANA ◽  
2012 ◽  
Vol 9 ◽  
pp. 59-62
Author(s):  
Ananta Panthi ◽  
HN Singh
Keyword(s):  
Temporal Pattern ◽  
Depth Distribution ◽  
Focal Depth ◽  
B Value ◽  
Northeast India ◽  
Great Earthquake ◽  
Shillong Plateau ◽  
Middle Portion ◽  
Strong Activity ◽  
Intermediate Depth

Seismic status of Shillong Plateau of Northeast India has been studied, considering spatial and temporal pattern of the region and using seismicity data for the period 1808-2008. Cutoff magnitude and b-value has been estimated using earthquake data for the period 1963-2008. Seismic activity is observed to be very feeble along the major faults of Shillong Plateau and strong activity is found to occur slightly away from these faults and confined within middle portion at two locations of the region. The temporal pattern shows that the region is due for great earthquake. Focal depth distribution of the events shows that all the events are intermediate depth (less than 70 km). DOI: http://dx.doi.org/10.3126/bibechana.v9i0.7175 BIBECHANA 9 (2013) 59-62

Investigation of the optimal b value in diffusion weighted MR imaging for diagnosis of prostate cancer at 3-T

2015 ◽  
Vol 36 (4) ◽  
pp. 402
Author(s):  
Qing-song YANG ◽  
Zhen WANG ◽  
Yu-kun CHEN ◽  
Lu-guang CHEN ◽  
Chao MA ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Mr Imaging ◽  
B Value ◽  
Diffusion Weighted

Spatial and temporal b-value characterization at Popocatépetl volcano, Central Mexico

2021 ◽  
pp. 107320
Author(s):  
Quetzalcoatl Rodríguez-Pérez ◽  
Marisol Monterrubio-Velasco ◽  
F. Ramón Zúñiga ◽  
Carlos M. Valdés-González ◽  
Raúl Arámbula-Mendoza
Keyword(s):  
B Value ◽  
Central Mexico ◽  
Popocatépetl Volcano ◽  
Popocatepetl Volcano

scholarly journals The Primacy of High B-Value 3T-DWI Radiomics in the Prediction of Clinically Significant Prostate Cancer

Diagnostics ◽  
2021 ◽  
Vol 11 (5) ◽  
pp. 739
Author(s):  
Alessandro Bevilacqua ◽  
Margherita Mottola ◽  
Fabio Ferroni ◽  
Alice Rossi ◽  
Giampaolo Gavelli ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Quantitative Imaging ◽  
B Value ◽  
Support Vector ◽  
Svm Classifier ◽  
Primary Role ◽  
High B Value ◽  
Wilcoxon Rank Sum Test ◽  
Apparent Diffusion ◽  
Clinically Significant

Predicting clinically significant prostate cancer (csPCa) is crucial in PCa management. 3T-magnetic resonance (MR) systems may have a novel role in quantitative imaging and early csPCa prediction, accordingly. In this study, we develop a radiomic model for predicting csPCa based solely on native b2000 diffusion weighted imaging (DWIb2000) and debate the effectiveness of apparent diffusion coefficient (ADC) in the same task. In total, 105 patients were retrospectively enrolled between January–November 2020, with confirmed csPCa or ncsPCa based on biopsy. DWIb2000 and ADC images acquired with a 3T-MRI were analyzed by computing 84 local first-order radiomic features (RFs). Two predictive models were built based on DWIb2000 and ADC, separately. Relevant RFs were selected through LASSO, a support vector machine (SVM) classifier was trained using repeated 3-fold cross validation (CV) and validated on a holdout set. The SVM models rely on a single couple of uncorrelated RFs (ρ < 0.15) selected through Wilcoxon rank-sum test (p ≤ 0.05) with Holm–Bonferroni correction. On the holdout set, while the ADC model yielded AUC = 0.76 (95% CI, 0.63–0.96), the DWIb2000 model reached AUC = 0.84 (95% CI, 0.63–0.90), with specificity = 75%, sensitivity = 90%, and informedness = 0.65. This study establishes the primary role of 3T-DWIb2000 in PCa quantitative analyses, whilst ADC can remain the leading sequence for detection.

scholarly journals Investigation of Feller-Buncher Performance Using Weibull Distribution

Forests ◽  
2021 ◽  
Vol 12 (3) ◽  
pp. 284
Author(s):  
Ebru Bilici
Keyword(s):  
Weibull Distribution ◽  
Shape Parameter ◽  
B Value ◽  
Productivity Analysis ◽  
Volume Data ◽  
Estimation Model ◽  
Distribution Method ◽  
Timber Volume ◽  
C Value ◽  
The Right

With the advancement of technology in forestry, the utilization of advanced machines in forest operations has been increasing in the last decades. Due to their high operating costs, it is crucial to select the right machinery, which is mostly done by using productivity analysis. In this study, a productivity estimation model was developed in order to determine the timber volume cut per unit time for a feller-buncher. The Weibull distribution method was used to develop the productivity model. In the study, the model of the theoretical (estimated) volume distributions obtained with the Weibull probability density function was generated. It was found that the c value was 1.96 and the b value was 0.58 (i.e., b is the scale parameter, and c is the shape parameter). The model indicated that the frequency of the volume data had moved away from 0 as the shape parameter of the Weibull distribution increased. Thus, it was revealed that the shape parameter gives preliminary information about the distribution of the volume frequency. The consistency of the measured timber volume with the estimated timber volume strongly indicated that this approach can be effectively used by decision makers as a key tool to predict the productivity of a feller-buncher used in harvesting operations.

scholarly journals Effects of Camu-Camu (Myrciaria dubia) Powder on the Physicochemical and Kinetic Parameters of Deteriorating Microorganisms and Salmonella enterica Subsp. enterica Serovar Typhimurium in Refrigerated Vacuum-Packed Ground Beef

Agriculture ◽  
2021 ◽  
Vol 11 (3) ◽  
pp. 252
Author(s):  
Jorge Luiz da Silva ◽  
Vasco Cadavez ◽  
José M. Lorenzo ◽  
Eduardo Eustáquio de Souza Figueiredo ◽  
Ursula Gonzales-Barron
Keyword(s):  
Ground Beef ◽  
Treated Group ◽  
B Value ◽  
Kinetics Parameters ◽  
Psychrotrophic Bacteria ◽  
Color Changes ◽  
A Value ◽  
Spoilage Bacteria ◽  
Serovar Typhimurium ◽  
And Control

This study aims to evaluate the effects of camu-camu powder (CCP), Amazonian berry fruit with documented bioactive properties, physicochemical meat parameters, and the growth kinetics parameters of S. enterica ser. Typhimurium, psychrotrophic bacteria (PSY), and lactic acid bacteria (LAB) in vacuum-packed ground beef. Batches of ground beef were mixed with 0.0%, 2.0%, 3.5%, and 5.0% CCP (w/w), vacuum-packed as 10 g portions, and stored at 5 °C for 16 days. Centesimal composition analyses (only on the initial day), pH, TBARS, and color were quantified on storage days 1, 7, and 15, while PSY and LAB were counted on days 0, 3, 6, 9, 13, and 16. Another experiment was conducted with the same camu-camu doses by inoculating S. enterica ser. Typhimurium microbial kinetic curves were modeled by the Huang growth and Weibull decay models. CCP decreased TBARS in beef from 0.477 to 0.189 mg MDA·kg−1. No significant differences in meat pH between treated and control samples were observed on day 15. CCP addition caused color changes, with color a* value decreases (from 14.45 to 13.44) and color b* value increases (from 17.41 to 21.25), while color L* was not affected. Higher CCP doses caused progressive LAB growth inhibition from 0.596 to 0.349 log CFU·day−1 at 2.0% and 5.0% CCP, respectively. Similarly, PSY growth rates in the treated group were lower (0.79–0.91 log CFU·day−1) compared to the control (1.21 log CFU·day−1). CCP addition at any of the investigated doses produced a steeper S. enterica ser. Typhimurium inactivation during the first cold storage day, represented by Weibull’s concavity α shape parameter, ranged from 0.37 to 0.51, in contrast to 1.24 for the control. At the end of the experiment, however, S. enterica ser. Typhimurium counts in beef containing CCP were not significantly different (p < 0.05) from the control. Although CCP affects bacterial kinetics, it does not protect ground beef against spoilage bacteria and Salmonella to the same degree it does against lipid peroxidation.

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