scholarly journals ScatterJn: An ImageJ Plugin for Scatterplot-Matrix Analysis and Classification of Spatially Resolved Analytical Microscopy Data

2016 ◽  
Vol 4 ◽  
Keyword(s):  
Matrix Analysis ◽  
Spatially Resolved ◽  
Analytical Microscopy ◽  
Microscopy Data ◽  
Scatterplot Matrix ◽  
Imagej Plugin

scholarly journals Automated tracking of S. pombe spindle elongation dynamics

2020 ◽  
Author(s):  
Ana Sofía M. Uzsoy ◽  
Parsa Zareiesfandabadi ◽  
Jamie Jennings ◽  
Alexander F. Kemper ◽  
Mary Williard Elting
Keyword(s):  
Principal Axis ◽  
Model Organism ◽  
Data Sets ◽  
Mitotic Progression ◽  
Automated Tracking ◽  
Spindle Elongation ◽  
Microscopy Data ◽  
Spindle Structure ◽  
Over Time ◽  
Imagej Plugin

The mitotic spindle is a microtubule-based machine that pulls the two identical sets of chromosomes to opposite ends of the cell during cell division. The fission yeast Schizosaccharomyces pombe is an important model organism for studying mitosis due to its simple, stereotyped spindle structure and well-established genetic toolset. S. pombe spindle length is a useful metric for mitotic progression, but manually tracking spindle ends in each frame to measure spindle length over time is laborious and can limit experimental throughput. We have developed an ImageJ plugin that can automatically track S. pombe spindle length over time and replace manual or semi-automated tracking of spindle elongation dynamics. Using an algorithm that detects the principal axis of the spindle and then finds its ends, we reliably track the length and angle of the spindle as the cell divides. The plugin integrates with existing ImageJ features, exports its data for further analysis outside of ImageJ, and does not require any programming by the user. Thus, the plugin provides an accessible tool for quantification of S. pombe spindle length that will allow automatic analysis of large microscopy data sets and facilitate screening for effects of cell biological perturbations on mitotic progression.

scholarly journals Analysis and Classification of Liquid Samples Using Spatial Heterodyne Raman Spectroscopy

2019 ◽  
Vol 73 (12) ◽  
pp. 1409-1419
Author(s):  
Ardian B. Gojani ◽  
Dávid J. Palásti ◽  
Andrea Paul ◽  
Gábor Galbács ◽  
Igor B. Gornushkin
Keyword(s):  
Raman Spectra ◽  
Michelson Interferometer ◽  
Principal Component ◽  
Resolving Power ◽  
Calibration Plot ◽  
Least Squares Regression ◽  
Spatially Resolved ◽  
Liquid Samples ◽  
Diode Pumped

Spatial heterodyne spectroscopy (SHS) is used for quantitative analysis and classification of liquid samples. SHS is a version of a Michelson interferometer with no moving parts and with diffraction gratings in place of mirrors. The instrument converts frequency-resolved information into a spatially resolved one and records it in the form of interferograms. The back-extraction of spectral information is done by the fast Fourier transform. A SHS instrument is constructed with the resolving power 5000 and spectral range 522–593 nm. Two original technical solutions are used as compared to previous SHS instruments: the use of a high-frequency diode-pumped solid-state laser for excitation of Raman spectra and a microscope-based collection system. Raman spectra are excited at 532 nm at the repetition rate 80 kHz. Raman shifts between 330 cm−1 and 1600 cm−1 are measured. A new application of SHS is demonstrated: for the first time, it is used for quantitative Raman analysis to determine concentrations of cyclohexane in isopropanol and glycerol in water. Two calibration strategies are employed: univariate based on the construction of a calibration plot and multivariate based on partial least squares regression. The detection limits for both cyclohexane in isopropanol and glycerol in water are at a 0.5 mass% level. In addition to the Raman–SHS chemical analysis, classification of industrial oils (biodiesel, poly(1-decene), gasoline, heavy oil IFO380, polybutenes, and lubricant) is performed using the Raman–fluorescence spectra of the oils and principal component analysis. The oils are easily discriminated showing distinct non-overlapping patterns in the principal component space.

scholarly journals AutoNeuriteJ: An ImageJ plugin for measurement and classification of neuritic extensions

PLoS ONE ◽  
2020 ◽  
Vol 15 (7) ◽  
pp. e0234529
Author(s):  
Benoit Boulan ◽  
Anne Beghin ◽  
Charlotte Ravanello ◽  
Jean-Christophe Deloulme ◽  
Sylvie Gory-Fauré ◽  
...  
Keyword(s):  
Imagej Plugin

Atomistic Simulation and Density Functional Analysis of Ni(111)-ZrO2(100)(Cubic) and NiO(111)-Ni(111)-ZrO2(100)(Cubic) Interfaces

2000 ◽  
Vol 654 ◽  
Author(s):  
Chang-Xin Guo ◽  
Donald E. Ellis ◽  
Vinayak P. Dravid ◽  
Luke Brewer
Keyword(s):  
First Principles ◽  
Atomistic Simulation ◽  
Density Functional ◽  
Depth Profiling ◽  
Interface Plane ◽  
Functional Theory ◽  
Spatially Resolved ◽  
Microscopy Data ◽  
Energy Profiling ◽  
Good Agreement

AbstractThe atomic arrangement and electronic structure in the vicinity of Ni(111)- ZrO2(100)(Cubic) and NiO(111)-Ni(111)-ZrO2(100)(Cubic) interfaces have been studied by atomistic simulation and by first-principles Density Functional theory. “Depth Profiling” is carred out in both methodologies, to determine modifications of cohesive energy and electron distribution of atomic layers from the interface plane. The energy profiling results show the interface consists of only a few atomic layers. Simulation results and electron density analyses are in good agreement with High Resolution Spatially Resolved Electron Microscopy data.

[ITAL]HST[/ITAL]/FOS Spatially Resolved Spectral Classification of Compact OB Groups in the Large Magellanic Cloud

1999 ◽  
Vol 118 (4) ◽  
pp. 1684-1699 ◽  
Author(s):  
Nolan R. Walborn ◽  
Laurent Drissen ◽  
Joel Wm. Parker ◽  
Abhijit Saha ◽  
John W. MacKenty ◽  
...  
Keyword(s):  
Large Magellanic Cloud ◽  
Magellanic Cloud ◽  
Spectral Classification ◽  
Spatially Resolved
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