scholarly journals A Quantitative Model‐Based Assessment of Stony Desert Landscape Evolution in the Hami Basin, China: Implications for Plio‐Pleistocene Dust Production in Eastern Asia

2020 ◽  
Vol 47 (20) ◽  
Author(s):  
Jordan T. Abell ◽  
Stefan R. Rahimi ◽  
Alex Pullen ◽  
Zachary J. Lebo ◽  
Dehai Zhang ◽  
...  
Keyword(s):  
Landscape Evolution ◽  
Quantitative Model ◽  
Eastern Asia ◽  
Dust Production ◽  
Model Based ◽  
Desert Landscape

Quantitative Model-Based Image Analysis of NuMa Distribution Links Nuclear Organization with Cell Phenotype

2001 ◽  
Vol 7 (S2) ◽  
pp. 578-579
Author(s):  
David W. Knowles ◽  
Sophie A. Lelièvre ◽  
Carlos Ortiz de Solόrzano ◽  
Stephen J. Lockett ◽  
Mina J. Bissell ◽  
...  
Keyword(s):  
Image Analysis ◽  
Mammary Epithelial Cells ◽  
Nuclear Organization ◽  
Critical Role ◽  
Quantitative Model ◽  
Mammary Epithelial ◽  
Cell Phenotype ◽  
Proliferating Cells ◽  
Mitotic Apparatus ◽  
Model Based

The extracellular matrix (ECM) plays a critical role in directing cell behaviour and morphogenesis by regulating gene expression and nuclear organization. Using non-malignant (S1) human mammary epithelial cells (HMECs), it was previously shown that ECM-induced morphogenesis is accompanied by the redistribution of nuclear mitotic apparatus (NuMA) protein from a diffuse pattern in proliferating cells, to a multi-focal pattern as HMECs growth arrested and completed morphogenesis . A process taking 10 to 14 days.To further investigate the link between NuMA distribution and the growth stage of HMECs, we have investigated the distribution of NuMA in non-malignant S1 cells and their malignant, T4, counter-part using a novel model-based image analysis technique. This technique, based on a multi-scale Gaussian blur analysis (Figure 1), quantifies the size of punctate features in an image. Cells were cultured in the presence and absence of a reconstituted basement membrane (rBM) and imaged in 3D using confocal microscopy, for fluorescently labeled monoclonal antibodies to NuMA (fαNuMA) and fluorescently labeled total DNA.

scholarly journals Quantitative, model-based estimates of variability in the generation and serial intervals of Plasmodium falciparum malaria

2016 ◽  
Vol 15 (1) ◽  
Author(s):  
John H. Huber ◽  
Geoffrey L. Johnston ◽  
Bryan Greenhouse ◽  
David L. Smith ◽  
T. Alex Perkins
Keyword(s):  
Plasmodium Falciparum ◽  
Falciparum Malaria ◽  
Plasmodium Falciparum Malaria ◽  
Quantitative Model ◽  
Model Based

Striatal contributions to category learning: Quantitative modeling of simple linear and complex nonlinear rule learning in patients with Parkinson's disease

2001 ◽  
Vol 7 (6) ◽  
pp. 710-727 ◽  
Author(s):  
W. TODD MADDOX ◽  
J. VINCENT FILOTEO
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Frontal Lobe ◽  
Category Learning ◽  
Rule Learning ◽  
Quantitative Model ◽  
Perceptual Categorization ◽  
Model Based ◽  
Rule Application ◽  
Frontal Lobe Functioning

The contribution of the striatum to category learning was examined by having patients with Parkinson's disease (PD) and matched controls solve categorization problems in which the optimal rule was linear or nonlinear using the perceptual categorization task. Traditional accuracy-based analyses, as well as quantitative model-based analyses were performed. Unlike accuracy-based analyses, the model-based analyses allow one to quantify and separate the effects of categorization rule learning from variability in the trial-by-trial application of the participant's rule. When the categorization rule was linear, PD patients showed no accuracy, categorization rule learning, or rule application variability deficits. Categorization accuracy for the PD patients was associated with their performance on a test believed to be sensitive to frontal lobe functioning. In contrast, when the categorization rule was nonlinear, the PD patients showed accuracy, categorization rule learning, and rule application variability deficits. Furthermore, categorization accuracy was not associated with performance on the test of frontal lobe functioning. Implications for neuropsychological theories of categorization learning are discussed. (JINS, 2001, 7, 710–727.)

A quantitative model based on clinically relevant MRI features differentiates lower grade gliomas and glioblastoma

2020 ◽  
Vol 30 (6) ◽  
pp. 3073-3082
Author(s):  
Hang Cao ◽  
E. Zeynep Erson-Omay ◽  
Xuejun Li ◽  
Murat Günel ◽  
Jennifer Moliterno ◽  
...  
Keyword(s):  
Quantitative Model ◽  
Lower Grade ◽  
Model Based ◽  
Mri Features

Quantitative Model Based on Raman Spectra to Evaluate Contaminants in Crack (Cocaine)

2010 ◽  
Author(s):  
Ciro Penido ◽  
Marcos T. T. Pacheco ◽  
Landulfo Silveira ◽  
P. M. Champion ◽  
L. D. Ziegler
Keyword(s):  
Raman Spectra ◽  
Crack Cocaine ◽  
Quantitative Model ◽  
Model Based

Quantitative Model-Based Safety Analysis: A Case Study

2011 ◽  
Vol 29 (1) ◽  
pp. 5-16
Author(s):  
Matthias Güdemann ◽  
Frank Ortmeier
Keyword(s):  
Safety Analysis ◽  
Quantitative Model ◽  
Model Based

scholarly journals Multivariate Method Based on Raman Spectroscopy for Quantification of Dipyrone in Oral Solutions

2018 ◽  
Vol 2018 ◽  
pp. 1-10 ◽  
Author(s):  
Luciana Lopes Guimarães ◽  
Letícia Parada Moreira ◽  
Bárbara Faria Lourenço ◽  
Walber Toma ◽  
Renato Amaro Zângaro ◽  
...  
Keyword(s):  
Raman Spectroscopy ◽  
Quality Control ◽  
Principal Component Regression ◽  
Principal Component ◽  
Quantitative Model ◽  
Calibration Model ◽  
Analytical Methodology ◽  
Figures Of Merit ◽  
Model Based ◽  
Raman Probe

This work employed a quantitative model based on Raman spectroscopy and principal component regression (RS/PCR) to quantify the active ingredient dipyrone (metamizole) in commercially available formulations as an analytical methodology for quality control in the pharmaceutical industry. Raman spectra were collected using a dispersive Raman spectrometer (830 nm, 250 mW excitation, and 20 s exposure time) coupled to a Raman probe. Solutions of dipyrone diluted in water in the range of 80 to 120% of the concentration of commercial formulations (500 mg/mL) were used to develop a calibration model based on PCR to obtain the figures of merit for class I validation from the Brazilian Sanitary Surveillance Agency (ANVISA, RE no. 899/2003). This spectral model was then used to predict the concentration of dipyrone in commercial formulations from distinct brands with 500 mg/mL. A prediction error of 6.5 mg/mL (1.3%) was found for this PCR model using the diluted samples. Commercial formulations had predicted concentrations with a difference below 5.0% compared to the label concentration, indicating the applicability of Raman spectroscopy for quality control in the final product.

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