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An in vitro evaluation of a novel airway staple for bronchial re-anastomosis.
The primary aim was to test a recently developed airway staple against standard sutures in an in vitro model. The secondary aim was to examine whether the model was sensitive to the variables of staple design, tissue type and length of stay. A tissue model of human bronchus was designed and tested using two different sections, each with a 0.5 cm length of bronchial trachea. Ten staples were tested in two groups, using three load levels with two measurements per staple under two different conditions, and with either 5 or 10 suture pairs. The suture force was recorded. The closed perimeter area showed significant differences (P Q:

rpy2 ImportError with pandas

I recently upgraded my Python from 2.7.2 to 3.4. I am using rpy2 0.9.6. My installation is in the following format:

C:\Data\Python36\Lib\site-packages\rpy2\site-packages\

When I import pandas using rpy2, I receive the following error.
>>> import pandas as pd
Traceback (most recent call last):
File “”, line 1, in
File “C:\Data\Python36\Lib\site-packages\rpy2\site-packages\pandas\__init__.py”, line 13, in
from pandas.core.generic import PandasError
File “C:\Data\Python36\Lib\site-packages

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Full Text Available Abstract (AIM: The cardiovascular response to exercise plays a major role in the description of the various exercise modes, as well as as a prognosis of the health of the individual. The most accurate measurement is the aortic pulse waveform (aPWV, which is currently considered the gold standard measurement for the prediction of asymptomatic or overt cardiovascular disease. However, due to the limitations of the equipment, the variability of the aPWV and its laborious nature, the measurement process requires a certain degree of physical fitness and the motivation of the participant. Therefore, in this work a new mathematical method has been proposed and applied to estimate aPWV by analyzing the time domain waveform of the pulse oximeter signal, in which the variation of two individual variables was investigated: the rate of the waveform deceleration (Rd and amplitude at the foot of the wave (A. The proposed method was compared with the standard method for estimating aPWV (Pearson’s correlation test. Twenty-four healthy men (age, 25 ± 7 years, with a body mass of 72 ± 8.4 kg were recruited. Forty-eight sets of pulse oximeter recordings were obtained using an oximeter (TitanLab, Graz, Austria, with the sit and stand test (60 s of each participant. The participants were placed on a treadmill at a starting speed of 9 km/h and 0.67 m/s. The results suggest that the time domain analysis, utilizing the aPWV estimation method that is based on the two variables, can be used as a rapid, easy-to-apply, and non-invasive tool for the prediction of the cardiovascular response to exercise. REVIEW STATEMENT: A mathematical method has been proposed and applied to estimate pulse wave velocity (PWV) by analyzing the time domain waveform of the pulse oximeter signal, in which the variation of two individual variables was investigated: the rate of the waveform deceleration (Rd) and amplitude at the foot of the wave (A. The proposed method was compared with the standard method for estimating aPWV (Pearson’s correlation test). Twenty-four healthy men (age, 25 ± 7 years, with a body mass of 72 ± 8.4 kg were recruited. Forty-eight sets of pulse oximeter recordings were obtained using an oximeter (TitanLab, Graz, Austria, with the sit and stand test (60