Assessment of sustained effects of levosimendan and dobutamine on left ventricular systolic functions by using novel tissue Doppler derived indices in patients with advanced heart failure

Background: Previous studies comparing levosimendan vs. dobutamine have revealed that levosimendan is better in relieving symptoms. Echocardiographic studies have been done using second measurements immediately following a dobutamine infusion or while it was still being administered. The aim of our study was assessment of sustained effects of 24 h levosimendan and dobutamine infusions on left ventricular systolic functions. Methods: A total of 61 patients with acutely decompensated heart failure with New York Heart Association (NYHA) class III or IV symptoms were randomized to receive either levosimendan or dobutamine 2:1 in an open label fashion. Before and 5 days after the initiation of infusions, functional class was assessed, N-terminal prohormone of B-type natriuretic peptide (NT-proBNP) levels and left ventricular ejection fraction (LVEF), mitral inflow peak E and A wave velocity, and E/A ratios were measured; using tissue Doppler imaging, isovolumic myocardial acceleration (IVA), peak myocardial velocity during isovolumic contraction (IVV), peak systolic velocity during ejection period (Sa), early (E’) and late (A’) diastolic velocities, and E’/A’ and E/E’ ratios were measured. Results: The NYHA class improved in both groups, but improvements were prominent in the levosimendan group. NT-proBNP levels were significantly reduced in the levosimendan group. Improvements in LVEF and diastolic indices were significant in the levosimendan group. Tissue Doppler-derived systolic indices of IVV and IVA increased significantly in the levosimendan group. Conclusions: Improvements in left ventricular systolic and diastolic functions continue after a levosimendan infusion.

Performance Comparison of Different Regression Methods for VO(2)max Estimation

21st Signal Processing and Communications Applications Conference (SIU) -- APR 24-26, 2013 -- CYPRUSWOS: 000325005300440The purpose of this paper is to develop maximal oxygen uptake (VO(2)max) models by using different regression methods such as Multilayer Feed-Forward Artificial Neural Networks (MFANN's), Support Vector Regression (SVR), Generalized Regression Neural Networks (GRNN's) and Multiple Linear Regression (MLR). The dataset includes data of 439 subjects and the input variables of the dataset are gender, age, body mass index (BMI), percent body fat (BF), respiratory exchange ratio (RER) from treadmill test, self-reported rating of perceived exertion (RPE) from treadmill test, heart rate (HR) and time to exhaustion from treadmill test. The performance of the models is evaluated by calculating their standard error of estimates (SEE) and multiple correlation coefficients (R). The results suggest that MFANN-based VO(2)max prediction models perform better than other prediction models

A detailed investigation of electronic and optical properties of the exciton, the biexciton and charged excitons in a multi-shell quantum dot nanocrystal

In the present study, the electronic and optical properties of the exciton (X), the biexciton (XX) and charged excitons (X- and X+) in a multi-shell quantum dot nanocrystal have been systematically explored in detail. The electronic properties have been determined in the framework of the single-band effective mass approximation. For this purpose, the Poisson-Schrodinger equations have been solved self-consistently in the Hartree approximation. In the electronic structure calculations for XX, X- and X+, the quantum mechanical exchange-correlation potentials between particles of the same type have been taken into account in the local density approximation. Some optical parameters, such as the overlap integrals, recombination oscillator strengths, radiative lifetimes, etc, have been determined by using the single-particle energy levels and wavefunctions obtained. A different approximation, reported in Sahin and Koc 2013 Appl. Phys. Lett. 102 183103, has been used in the recombination oscillator strength calculations. The results have been presented comparatively as a function of the shell thicknesses, and the well widths and probable physical reasons underlying them have been discussed in detail. In the present study, the electronic and optical properties of the exciton (X), the biexciton (XX) and charged excitons (X&minus; and X+) in a multi-shell quantum dot nanocrystal have been systematically explored in detail. The electronic properties have been determined in the framework of the single-band effective mass approximation. For this purpose, the Poisson&ndash;Schr&ouml;dinger equations have been solved self-consistently in the Hartree approximation. In the electronic structure calculations for XX, X&minus; and X+, the quantum mechanical exchange&ndash;correlation potentials between particles of the same type have been taken into account in the local density approximation. Some optical parameters, such as the overlap integrals, recombination oscillator strengths, radiative lifetimes, etc, have been determined by using the single-particle energy levels and wavefunctions obtained. A different approximation, reported in Sahin and Koc 2013 Appl. Phys. Lett. 102 183103, has been used in the recombination oscillator strength calculations. The results have been presented comparatively as a function of the shell thicknesses, and the well widths and probable physical reasons underlying them have been discussed in detail.</p

Intelligent Regression Techniques for Non-Exercise Prediction of VO(2)max

21st Signal Processing and Communications Applications Conference (SIU) -- APR 24-26, 2013 -- CYPRUSWOS: 000325005300374The purpose of this study is to develop nonexercise (N-Ex) VO(2)max prediction models by using Support Vector Regression (SVR) and Multilayer Feed Forward Neural Networks (MFFNN). VO(2)max values of 100 subjects are measured using a maximal graded exercise test. The variables; gender, age, body mass index (BMI), perceived functional ability (PFA) to walk, jog or run given distances and current physical activity rating (PA-R) are used to build two N-Ex prediction models. Using 10-fold cross validation on the dataset, standard error of estimates (SEE) and multiple correlation coefficients (R) of both models are calculated. The MFFNN-based model yields lower SEE (3.23 ml.kg(-1).min(-1)) whereas the SVR-based model yields higher R (0.93). Compared with the results of the other N-Ex prediction models in literature that are developed using Multiple Linear Regression Analysis, the reported values of SEE and R in this study are considerably more accurate

Experimental Investigation And Performance Analysis Of Gasketed-Plate Heat Exchangers

In this study, the thermal and hydrodynamic performance analyses of sa elected gasketed-plate heat exchanger with different number of plates are performed experimentally. A gasketed-plate heat exchanger (GPHE) test set-up is designed and constructed to perform experimental measurements for thermal and hydrodynamic performance analyses of plate heat exchangers. The experiments are performed for an industrial chevron-type plate heat exchanger under different flow conditions for a wide range of Reynolds numbers between 450 and 5250. The temperatures at the inlet and outlet ports, the volumetric flow rates of the hot and cold fluids, and the pressure drops between the inlet and outlet ports are measured during the experiments. By using the experimental data, Nusselt number correlation for heat transfer analysis and a friction factor correlation for pressure drop calculations are developed for the chevron-type plate heat exchanger tested as a function of Reynolds number and Prandtl number. The results obtained from these new correlations are compared with several existing correlations in the literature, which were developed for different plates. Although the trends of the new correlations are similar with the ones in the literature, this study shows that every plate design needs its specific correlations for heat transfer and pressure drop calculations, since the specific correlations developed for the specific plates tested are different than the ones given in literature. Obtaining these kinds of correlations for local products is especially important for the related industry to improve with the help of local test set-ups.This research was supported by Turkish Ministry of Science, Technology and Industry and Tektes Inc. as a SANTEZ project, by Turkish Academy of Sciences TUBA-GEBIP Distinguished Young Scientists Awards Programme and TUBITAK 1001 programme (Project no:112M173). The authors are also thankful to cagin Gulenoglu for his assistance during the preparation of the revised manuscript

Experimental comparison of performances of three different plates for gasketed plate heat exchangers

In this study, an experimental set-up for testing chevron type gasketed plate heat exchangers is utilized to investigate the thermal and hydraulic characteristics of three different plate geometries. The experiments are performed using various number of plates, several flow rate and inlet and outlet temperature values so that the Reynolds numbers (300-5000) and Prandtl numbers vary for all the plates that have 30 degrees of chevron angle. Plate-specific correlations are derived for Nusselt number and friction factor by using the experimental results. (c) 2013 Elsevier Masson SAS. All rights reserved.This study is financially supported by TEKTES Teknolojik Tesisat Sistemleri Sanayi ve Ticaret A.S., Turkish Ministry of Science, Industry and Technology and TOBB University of Economics and Technology as a Santez project under grant number: STZ 2009-1-347 and by TUBA - GEBIP Distinguished Young Scientists Awards Programme of Turkish Academy of Sciences and Turkish Scientific and Research Council under grant 112M173

Artificial neural network-based model for predicting VO(2)max from a submaximal exercise test

WOS: 000284863200080The goal of this study is to develop an accurate artificial neural network (ANN)-based model to predict maximal oxygen uptake (VO(2)max) of fit adults from a single stage submaximal treadmill jogging test. Participants (81 males and 45 females), aged from 17 to 40 years, successfully completed a maximal graded exercise test (GXT) to determine VO(2)max. The variables; gender, age, body mass, steady-state heart rate and jogging speed are used to build the ANN prediction model. Using 10-fold cross validation on the dataset, the average values of standard error of estimate (SEE). Pearson's correlation coefficient (r) and multiple correlation coefficient (R) of the model are calculated as 1.80 ml kg(-1) min(-1), 0.95 and 0.93, respectively. Compared with the results of the other prediction models in literature that were developed using Multiple Linear Regression Analysis, the reported values of SEE, r and R in this study are considerably more accurate. (C) 2010 Elsevier Ltd. All rights reserved