1,042 research outputs found
Prediction of Turbulent Shear Stresses through Dysfunctional Bileaflet Mechanical Heart Valves using Computational Fluid Dynamics
There are more than 300,000 heart valves implanted annually worldwide with
about 50% of them being mechanical valves. The heart valve replacement is often
a common treatment for severe valvular disease. However, valves may dysfunction
leading to adverse hemodynamic conditions. The current computational study
investigated the flow around a bileaflet mechanical heart valve at different
leaflet dysfunction levels of 0%, 50%, and 100%, and documented the relevant
flow characteristics such as vortical structures and turbulent shear stresses.
Studying the flow characteristics through these valves during their normal
operation and dysfunction can lead to better understanding of their
performance, possibly improved designs, and help identify conditions that may
increase the potential risk of blood cell damage. Results suggested that
maximum flow velocities increased with dysfunction from 2.05 to 4.49 ms-1 which
were accompanied by growing eddies and velocity fluctuations. These
fluctuations led to higher turbulent shear stresses from 90 to 800 N.m-2 as
dysfunctionality increased. These stress values exceeded the thresholds
corresponding to elevated risk of hemolysis and platelet activation. The
regions of elevated stresses were concentrated around and downstream of the
functional leaflet where high jet velocity and stronger helical structures
existed
An Adaptive Feature Extraction Algorithm for Classification of Seismocardiographic Signals
This paper proposes a novel adaptive feature extraction algorithm for
seismocardiographic (SCG) signals. The proposed algorithm divides the SCG
signal into a number of bins, where the length of each bin is determined based
on the signal change within that bin. For example, when the signal variation is
steeper, the bins are shorter and vice versa. The proposed algorithm was used
to extract features of the SCG signals recorded from 7 healthy individuals
(Age: 29.44.5 years) during different lung volume phases. The output of
the feature extraction algorithm was fed into a support vector machines
classifier to classify SCG events into two classes of high and low lung volume
(HLV and LLV). The classification results were compared with currently
available non-adaptive feature extraction methods for different number of bins.
Results showed that the proposed algorithm led to a classification accuracy of
~90%. The proposed algorithm outperformed the non-adaptive algorithm,
especially as the number of bins was reduced. For example, for 16 bins, F1
score for the adaptive and non-adaptive methods were 0.910.05 and
0.630.08, respectively
Numerical Modeling of Pulse Wave Propagation in a Stenosed Artery using Two-Way Coupled Fluid Structure Interaction (FSI)
As the heart beats, it creates fluctuation in blood pressure leading to a
pulse wave that propagates by displacing the arterial wall. These waves travel
through the arterial tree and carry information about the medium that they
propagate through as well as information of the geometry of the arterial tree.
Pulse wave velocity (PWV) can be used as a non-invasive diagnostic tool to
study the functioning of cardiovascular system. A stenosis in an artery can
dampen the pulse wave leading to changes in the propagating pulse. Hence, PWV
analysis can be performed to detect a stenosed region in arteries. This paper
presents a numerical study of pulse wave propagation in a stenosed artery by
means of two-way coupled fluid structure interaction (FSI). The computational
model was validated by the comparison of the simulated PWV results with
theoretical values for a healthy artery. Propagation of the pulse waves in the
stenosed artery was compared with healthy case using spatiotemporal maps of
wall displacements. The analysis for PWV showed significance differences
between the healthy and stenosed arteries including damping of propagating
waves and generation of high wall displacements downstream the stenosis caused
by flow instabilities. This approach can be used to develop patient-specific
models that are capable of predicting PWV signatures associated with stenosis
changes. The knowledge gained from these models may increase utility of this
approach for managing patients at risk of stenosis occurrence
Development of Myxobolus dispar (Myxosporea : Myxobolidae) in an oligochaete alternate host, Tubifex tubifex
The development of Myxobolus dispar Thelohan, 1895, a myxosporean parasite of the gills of common carp (Cyprinus carpio L.) was studied in experimentally infected oligochaetes Tubifex tubifex Muller. After infection of uninfected tubificids with mature spores of M. dispar development of actinosporean stages was first observed light microscopically 21 days after initial exposure. In histological sections, early pansporocysts were located in the gut epithelium of experimental oligochaetes, while advanced stages occupied mostly the outer layers of the gut and the coelozoic space. Mature pansporocysts, each containing 8 raabeia spores, appeared 199 days after initial exposure. Following damage of the intestinal wall and rupture of the pansporocysts, free actinosporean stages were found in the gut lumen of the oligochaetes. Actinospores of M. dispar emerged from the worms after 217 days of intra-oligochaete development. They were floating in the water and showed a unique raabeia form. Each raabeia sport had three pyriform polar capsules and a cylindrical-shaped sporoplasm with approximately 32 secondary cells. The spore body joined the three caudal projections without a style. Caudal projections were bifurcated at the end and the two main branches had further small bifurcations. The total length of the raabeia sport was approximately 158 mu m. The prevalence of infection in 240 experimentally infected Tubifex specimens was 99.2%. No infection was found in the control oligochaetes
Seismocardiographic Signal Timing with Myocardial Strain
Speckle Tracking Echocardiography (STE) is a relatively new method for
cardiac function evaluation. In the current study, STE was used to investigate
the timing of heart-induced mostly subaudible (i.e., below the frequency limit
of human hearing) chest-wall vibrations in relation to the longitudinal
myocardial strain. Such an approach may help elucidate the genesis of these
vibrations, thereby improving their diagnostic value
Generation of Molecular Complexity from Cyclooctatetraene: Preparation of Optically Active Protected Aminocycloheptitols and Bicyclo[4.4.1]undecatriene
The racemic (6-cyclo-heptadienyl)Fe(CO)3+ cation ((±)-7), prepared from cyclooctatetraene, was treated with a variety of carbon and heteroatom nucleophiles. Attack took place at the less hindered C1 dienyl carbon and decomplexation of the (cycloheptadiene)Fe(CO)3 complexes gave products rich in functionality for further synthetic manipulation. In particular, a seven-step route was developed from racemic (6-styryl-2,4-cycloheptadien-1-yl)phthalimide ((±)-9âd) to afford the optically active aminocycloheptitols (â)-20 and (+)-20
Brain Based Learning: K-12 Teachersâ Preferred Methods of Science Instruction
The purpose of this quantitative study was to investigate Brain Based Learning (BBL) techniques in teaching science. Participants included 216 K-12, full-time, regular education teachers from 8 Northeast Tennessee school systems who taught at least 1 science class. Specifically this research was guided by 7 research questions on teachersâ perceptions and practices in teaching science.
Data were collected by a survey that consisted of 82 statements where teachers rated their level of agreement and was distributed online via Survey Monkey. The first portion of my survey included demographic identifiers, teachersâ knowledge of the term BBL, and inquiries regarding science background and training. The remainder of the statements were focused on teachersâ perceptions and practices of BBL strategies in teaching science. The final item was open-ended and allowed teachers to share comments related to teaching science. For statements 6-81, participants responded by using a 5-point Likert scale that ranged from 1 (strongly disagree) to 5 (strongly agree). Quantitative data were analyzed with a series of independent samples t tests, one-way analysis of variance tests, and a Pearson correlation coefficient.
The results of the study indicate that teachersâ perceptions are positively correlated to their self-reported practices. Females, in general, and elementary teachers tend to practice BBL strategies in teaching science significantly more than other subgroups
Brain Based Learning: K-12 Teachersâ Preferred Methods of Science Instruction
The purpose of this quantitative study was to investigate Brain Based Learning (BBL) techniques in teaching science. Participants included 216 K-12, full-time, regular education teachers from 8 Northeast Tennessee school systems who taught at least 1 science class. Specifically this research was guided by 7 research questions on teachersâ perceptions and practices in teaching science.
Data were collected by a survey that consisted of 82 statements where teachers rated their level of agreement and was distributed online via Survey Monkey. The first portion of my survey included demographic identifiers, teachersâ knowledge of the term BBL, and inquiries regarding science background and training. The remainder of the statements were focused on teachersâ perceptions and practices of BBL strategies in teaching science. The final item was open-ended and allowed teachers to share comments related to teaching science. For statements 6-81, participants responded by using a 5-point Likert scale that ranged from 1 (strongly disagree) to 5 (strongly agree). Quantitative data were analyzed with a series of independent samples t tests, one-way analysis of variance tests, and a Pearson correlation coefficient.
The results of the study indicate that teachersâ perceptions are positively correlated to their self-reported practices. Females, in general, and elementary teachers tend to practice BBL strategies in teaching science significantly more than other subgroups
Heart Rate Monitoring During Different Lung Volume Phases Using Seismocardiography
Seismocardiography (SCG) is a non-invasive method that can be used for
cardiac activity monitoring. This paper presents a new electrocardiogram (ECG)
independent approach for estimating heart rate (HR) during low and high lung
volume (LLV and HLV, respectively) phases using SCG signals. In this study,
SCG, ECG, and respiratory flow rate (RFR) signals were measured simultaneously
in 7 healthy subjects. The lung volume information was calculated from the RFR
and was used to group the SCG events into low and high lung-volume groups. LLV
and HLV SCG events were then used to estimate the subjects HR as well as the HR
during LLV and HLV in 3 different postural positions, namely supine, 45 degree
heads-up, and sitting. The performance of the proposed algorithm was tested
against the standard ECG measurements. Results showed that the HR estimations
from the SCG and ECG signals were in a good agreement (bias of 0.08 bpm). All
subjects were found to have a higher HR during HLV (HR) compared
to LLV (HR) at all postural positions. The
HR/HR ratio was 1.110.07, 1.080.05,
1.090.04, and 1.090.04 (meanSD) for supine, 45 degree-first
trial, 45 degree-second trial, and sitting positions, respectively. This heart
rate variability may be due, at least in part, to the well-known respiratory
sinus arrhythmia. HR monitoring from SCG signals might be used in different
clinical applications including wearable cardiac monitoring systems
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