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: 29.4$\pm$4.5 years) during different lung volume phases. The output of the feature extraction algorithm was fed into a support vector machines classifier to classify SCG events into two classes of high and low lung volume (HLV and LLV). The classification results were compared with currently available non-adaptive feature extraction methods for different number of bins. Results showed that the proposed algorithm led to a classification accuracy of ~90%. The proposed algorithm outperformed the non-adaptive algorithm, especially as the number of bins was reduced. For example, for 16 bins, F1 score for the adaptive and non-adaptive methods were 0.91$\pm$0.05 and 0.63$\pm$0.08, 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 ((±)-9 d) to afford the optically active aminocycloheptitols (−)-20 and (+)-20

Brain Based Learning: K-12 Teachers’ 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 teachers’ 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, teachers’ knowledge of the term BBL, and inquiries regarding science background and training. The remainder of the statements were focused on teachers’ 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 teachers’ 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$_\text{HLV}$) compared to LLV (HR$_\text{LLV}$) at all postural positions. The HR$_\text{HLV}$/HR$_\text{LLV}$ ratio was 1.11$\pm$0.07, 1.08$\pm$0.05, 1.09$\pm$0.04, and 1.09$\pm$0.04 (mean$\pm$SD) 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

Brain Based Learning: K-12 Teachers’ 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 teachers’ 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, teachers’ knowledge of the term BBL, and inquiries regarding science background and training. The remainder of the statements were focused on teachers’ 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 teachers’ 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