Study of distribution and diversity of Polychaeta due to impact bottom trawling in Bahrakan fishing area (Persian Gulf)

The study took place to survey the changes in diversity and distribution of Polychaetes in fishing area of Bahrakan, due to the trawling. Sampling was taken before (15 May) of trawling and two weeks (5 Sep) and three months (14 Nov) after trawling in 2010, in three period in Bahrakan coast. Therefore, eighteen stations placed with the depth of 6 meters and 10 meters.The amount abundance Polychaetes had decreased significantlyin both depths two weeks after trawling (P0.05). Only in 10m depth, abundance Polychaetes after three months comparing to two weeks after trawling had increased significantly (p<0.05). Changing biomass Polychaetes was similar to Changing abundance. After the trawling, small size individuals became dominant.Abundance Species ofCossura longicirrattahad increased in both depths in two weeks after the trawling. Also in both depths, Shannon Diversity and Margalef Species Richness indices showedprocess decreasing and Simpson dominant Index showedprocess increasing. In both depths, Pielou Evenness Index two after trawling had increased. While, after three months comparing to two weeks after trawling had decreased and most effects of trawling were on 6m depth

Identification of biomolecule mass transport and binding rate parameters in living cells by inverse modeling

BACKGROUND: Quantification of in-vivo biomolecule mass transport and reaction rate parameters from experimental data obtained by Fluorescence Recovery after Photobleaching (FRAP) is becoming more important. METHODS AND RESULTS: The Osborne-Moré extended version of the Levenberg-Marquardt optimization algorithm was coupled with the experimental data obtained by the Fluorescence Recovery after Photobleaching (FRAP) protocol, and the numerical solution of a set of two partial differential equations governing macromolecule mass transport and reaction in living cells, to inversely estimate optimized values of the molecular diffusion coefficient and binding rate parameters of GFP-tagged glucocorticoid receptor. The results indicate that the FRAP protocol provides enough information to estimate one parameter uniquely using a nonlinear optimization technique. Coupling FRAP experimental data with the inverse modeling strategy, one can also uniquely estimate the individual values of the binding rate coefficients if the molecular diffusion coefficient is known. One can also simultaneously estimate the dissociation rate parameter and molecular diffusion coefficient given the pseudo-association rate parameter is known. However, the protocol provides insufficient information for unique simultaneous estimation of three parameters (diffusion coefficient and binding rate parameters) owing to the high intercorrelation between the molecular diffusion coefficient and pseudo-association rate parameter. Attempts to estimate macromolecule mass transport and binding rate parameters simultaneously from FRAP data result in misleading conclusions regarding concentrations of free macromolecule and bound complex inside the cell, average binding time per vacant site, average time for diffusion of macromolecules from one site to the next, and slow or rapid mobility of biomolecules in cells. CONCLUSION: To obtain unique values for molecular diffusion coefficient and binding rate parameters from FRAP data, we propose conducting two FRAP experiments on the same class of macromolecule and cell. One experiment should be used to measure the molecular diffusion coefficient independently of binding in an effective diffusion regime and the other should be conducted in a reaction dominant or reaction-diffusion regime to quantify binding rate parameters. The method described in this paper is likely to be widely used to estimate in-vivo biomolecule mass transport and binding rate parameters

False Alarm Reduction in Atrial Fibrillation Detection Using Deep Belief Networks

We propose and validate a novel method to reduce the false alarm (FA) rate caused by poor-quality electrocardiogram (ECG) signal measurement during atrial fibrillation (AFib) detection. A deep belief network is used to differentiate acceptable from unacceptable ECG segments. To validate the method, eight different levels of ECG quality are provided by artificially contaminating ECG records, from the MIT-BIH AFib database, with motion artifact from the MIT-BIH noise stress test database. ECG segments classified as ``unacceptable,'' in terms of signal quality, are restricted from AFib detection process. Results are evaluated for each level of quality and compared to AFib detection algorithm performance when ECGs of each level of quality are applied to it without performing any classification. Our results show that AFib detection performance for ECG with high signal-to-noise ratio (SNR) is minimally affected by this FA reduction approach. For clean ECG (no added noise), the AFib detection accuracy was 87&#x0025;, without and with FA reduction. For ECG, with an SNR of -20 dB, the performance of AFib detection is markedly decreased with an accuracy of 58.7&#x0025;; however, with FA reduction (using our method) the accuracy was increased to 81&#x0025;

Effect of Pressure on Skin-Electrode Impedance in Wearable Biomedical Measurement Devices

Objective: This paper investigates the effect of applied pressure on the skin-electrode impedance. Applied pressure, which affects the skin-electrode impedance, can fluctuate in many acquisition setups, particularly in wearable devices. The skin-electrode impedance, in turn, impacts the quality of the recorded signal in biomedical monitoring devices. Methods: Three types of electrodes were examined: Ag/AgCl electrodes, conductive textile electrodes, and dry electrodes with surface microfeatures (Orbital Research Inc.). Impedance measurements were conducted as pressure was repeatedly applied (P = 4 kPa) and removed (P = 0 kPa) over several trials. A Cole-Cole impedance model was utilized to model the skin-electrode interface. Significance and Results: Results demonstrated large decreases in the skin-electrode impedance of dry electrodes (conductive textile and orbital electrodes), especially with the initial application of the pressure. Model parameters also proved to be highly dependent on the level of pressure in dry electrodes but less dependent and more stable in wet electrodes. Decreases in skin-electrode impedance associated with applied pressure were thought to be caused by an increased effective electrode contact area. Changes in skin-electrode impedance were irreversible, lasting even after the applied pressure was released. Differences skin-electrode impedance associated with changes in applied pressure, decreased as the number of trials increased. Conclusion: Applied pressure has larger effect on dry electrodes than wet electrodes. Wearable devices that employ dry electrodes may have poorer biomedical signal quality when initially donned; however, the advantage of wet electrodes with their lower sensitivity to applied pressure is diminished in long-term monitoring applications