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This detection has been an issue due to protein competition and electrode fouling.
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The neurophysiological correlates of this detection have been extensively studied in 'oddball' paradigms.
This detection had a higher incidence on T24 and 5637 cell lines and markedly increased in the combined treatment.
This increased detection has challenged the diagnosis and management of nGGOs, which have been addressed extensively in the last ten years.
However, this early detection has led to overdiagnosis and overtreatment with resultant impact on the quality of life of men with PCa [ 2].
This method of detection has a precedent.
This scheme of detection has never been performed up to now and special attention is given in this article to prove its feasibility.
In contrast to this study, CTC detection has previously been described using an EpCAM-based method in a murine xenograft model [ 9].
In other words, following the Bayes theorem, attempting to detect anomalies using this form of random detection has the following property: P ( anomaly | rand ) = P ( rand | anomaly ) ∗ P ( anomaly ) P ( rand ) (8).
Furthermore, identification of the animal is based on centre of gravity so that alteration in a small number of pixels is recognised as movement; this way of activity detection has a higher resolution of ambulatory activity.
In this step, if the automatic detection has been wrong, the supervisor can modify this value by simply clicking on the correct eye.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com