Public Articles
Thermoluminescence and Electron Traps: Charlesby, Partridge, Boustead
Параллельные находки: "The Effect of Oxygen on the Thermoluminescence of Irradiated Polyethylene"\cite{Charlesby_1963a}; "Molecular Oxygen as an Electron Trap in the Thermoluminescence of Saturated Hydrocarbons"\cite{BOUSTEAD_1970}; "Thermoluminescence in hydrocarbon polymers"\cite{Boustead_1970b}; "Thermoluminescence in Polyethylene. I. Electron Traps"\cite{Boustead_1970a}; "Electron Traps in Polyethylene"\cite{Partridge_1965}; ""\cite{Partridge_1982}; "Electron Trapping and Hydrogen‐Atom Reactions in Irradiated Polyethylene"\cite{Partridge_1970}
Описание ТЛ: "The mechanism proposed for the TL is that after ionization some electrons are trapped at various sites in the polymer, leaving behind positive ions. On subsequent warming the electrons are expelled from the traps and recombine with the positive charges. The energy released in this process appears as a luminescence which is characteristic of impurity molecules present in the polyethylene. The work described below was undertaken in order to get direct evidence of the charge trapping and charge movement implied by this model. By simultaneous examination of the TL and TSC after irradiation, correlations in the behaviour of the two phenomena would provide support for a mechanism involving the untrapping and movement of electrons."
Fog and IoT: An Overview of Research Opportunities
Title
Reproducible research using Authorea, markdown and github
We start to write a paper in Authorea using markdown. Then we add a table
Apps | Helps Us in what? |
---|---|
Overleaf | Excellent tool for writing $$LaTeX$$ |
Authorea | Excellent tool for writing in all forms |
Diilinger | Great tool for markdown composing |
We can add an image in one of the two ways.
This image was added using Authorea's image function by first hunting for the image on the web, saving locally or uploading to Authorea.
It puts the image outside of the markdown box.
Image B was added using markdown syntax
Figure 2. Image B
We can add citations in only one way. If I want to cite basu, I just upload a bibtex file in the search box or search for Basu in Authorea's in built search for scholarly literature and do it. Here is the citation \cite{Smith_2012}
Then I connect Authorea paper to github. I can use github to work on the paper if I want, or use a markdown editor to work on it, and remember to upload the bibtex entries to the right folders or add the images properly in the markdown syntax. This way markdown becomes my powerful tool and github becomes my powerful tool to write any paper anywhere.
Then I create a github bridge. Port the paper over to github and start writing. When I save the paper, the paper gets saved automatically on Authorea. I do not need to worry about saving it anywhere else. I can add another reference to myself by first adding thus \cite{kassebaum2014global}
@article{kassebaum2014global,
title={Global, regional, and national levels and causes of maternal mortality during 1990--2013: a systematic analysis for the Global Burden of Disease Study 2013},
author={Kassebaum, Nicholas J and Bertozzi-Villa, Amelia and Coggeshall, Megan S and Shackelford, Katya A and Steiner, Caitlyn and Heuton, Kyle R and Gonzalez-Medina, Diego and Barber, Ryan and Huynh, Chantal and Dicker, Daniel and others},
journal={The Lancet},
volume={384},
number={9947},
pages={980--1004},
year={2014},
publisher={Elsevier}
}
Lesson 16: Integral and Comparison tests for Convergence
Title
Automatic Detection and Classification of Ca2+ Release Events in Confocal Line- and Framescan Images
and 1 collaborator
Analysis of Ca2+ signaling in cardiac cells is always a trade-off between acquisition speed and signal-to-noise ratio. This becomes especially apparent in confocal microscopy, during fast 2D scanning or when recording fluorescence signals from the sarcoplasmic reticulum, for example. Methods have been developed to remedy this via 'denoising' the image by fitting each pixel with a transient function. So far, adoption of such methods has been hindered by a number of limitations (e.g., inability to fit local, concurrent and consecutive events) and the limited availability of a customizable implementation.
Here we present a novel method for performing per-pixel denoising of confocal frame- and linescans. Our algorithm permits the extraction of spatiotemporally overlapping events (e.g., a Ca2+ spark occurring during the decaying phase of a Ca2+ wave) and is able to detect various different types of events within a pixel time course. The method estimates a non-constant baseline for each pixel, negating the necessity of using background regions or self-ratio methods prior to performing the analysis. Furthermore, by applying a clustering algorithm, detected single-pixel events are grouped into physiologically relevant events spanning multiple pixels (sparks, waves, puffs,transients, etc.), from which traditional parameters such as FDHM, FWHM, amplitude, wave speed, rise and decay times, can be easily extracted.
The method has been implemented as a cross-platform open source software with a comprehensive and easy to use graphical user interface. We have applied our method to analyzing linescans of repetitive Ca2+ sparks from individual RyR clusters in isolated ventricular cardiomyocytes; high-speed (150 frames/sec) framescans containing alterations in Ca2+ release events in atrial myocytes; and parallel analysis of Ca2+ release dynamics in the sarcoplasmic reticulum and cytosol.
Foot notes
Mi primer artículo
and 1 collaborator
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A Treatise on the Nature of Life