A Phase Space Box-counting based Method for Arrhythmia Prediction from Electrocardiogram Time Series

Arrhythmia is one kind of cardiovascular diseases that give rise to the number of deaths and potentially yields immedicable danger. Arrhythmia is a life threatening condition originating from disorganized propagation of electrical signals in heart resulting in desynchronization among different chambers of the heart. Fundamentally, the synchronization process means that the phase relationship of electrical activities between the chambers remains coherent, maintaining a constant phase difference over time. If desynchronization occurs due to arrhythmia, the coherent phase relationship breaks down resulting in chaotic rhythm affecting the regular pumping mechanism of heart. This phenomenon was explored by using the phase space reconstruction technique which is a standard analysis technique of time series data generated from nonlinear dynamical system. In this project a novel index is presented for predicting the onset of ventricular arrhythmias. Analysis of continuously captured long-term ECG data recordings was conducted up to the onset of arrhythmia by the phase space reconstruction method, obtaining 2-dimensional images, analysed by the box counting method. The method was tested using the ECG data set of three different kinds including normal (NR), Ventricular Tachycardia (VT), Ventricular Fibrillation (VF), extracted from the Physionet ECG database. Statistical measures like mean (μ), standard deviation (σ) and coefficient of variation (σ/μ) for the box-counting in phase space diagrams are derived for a sliding window of 10 beats of ECG signal. From the results of these statistical analyses, a threshold was derived as an upper bound of Coefficient of Variation (CV) for box-counting of ECG phase portraits which is capable of reliably predicting the impeding arrhythmia long before its actual occurrence. As future work of research, it was planned to validate this prediction tool over a wider population of patients affected by different kind of arrhythmia, like atrial fibrillation, bundle and brunch block, and set different thresholds for them, in order to confirm its clinical applicability.

Ecological distribution of semi-demersal fishes in space and time on the shelf of Antalya Gulf

In this study we provide a baseline data on semidemersal fish assemblages and biology in a heterogeneous and yet less studied portion of the shelf of Antalya Gulf. The distribution of fish abundance in three transects subjected to different fisheries regulations (fishery vs non fishery areas), and including depths of 10, 25, 75, 125, 200 m, was studied between May 2014 and February 2015 in representative months of winter, spring, summer and autumn seasons. A total of 76 fish species belonging to 40 families was collected and semidemersal species distribution was analyzed in comparison with the whole community. Spatial distribution of fish was driven mainly by depth and two main assemblages were observed: shallow waters (10-25; 75 m) and deep waters (125-200 m). Significant differences among transects were found for the whole community but not for the semidemersal species. Analysis showed that this was due to a strong relation of these species with local environmental characteristics rather than to a different fishing pressure over transects. Firstly all species distribute according to the bathymetrical gradient and secondly to the bottom type structure. Semidemersal species were then found more related to zooplankton and suspended matter availability. The main morphological characteristics, sex and size distribution of the target semidemersal species Spicara smaris (Linnaeus, 1758), Saurida undosquamis (Richardson, 1848), Pagellus acarne (Risso, 1827) were also investigated.

Signalling ballet in space and time.

Although we have amassed extensive catalogues of signalling network components, our understanding of the spatiotemporal control of emergent network structures has lagged behind. Dynamic behaviour is starting to be explored throughout the genome, but analysis of spatial behaviours is still confined to individual proteins. The challenge is to reveal how cells integrate temporal and spatial information to determine specific biological functions. Key findings are the discovery of molecular signalling machines such as Ras nanoclusters, spatial activity gradients and flexible network circuitries that involve transcriptional feedback. They reveal design principles of spatiotemporal organization that are crucial for network function and cell fate decisions.

Performance evaluation of a miniature laser ablation time-of-flight mass spectrometer designed for in situ investigations in planetary space research

Key performance features of a miniature laser ablation time-of-flight mass spectrometer designed for in situ investigations of the chemical composition of planetary surfaces are presented. This mass spectrometer is well suited for elemental and isotopic analysis of raw solid materials with high sensitivity and high spatial resolution. In this study, ultraviolet laser radiation with irradiances suitable for ablation (< 1 GW/cm2) is used to achieve stable ion formation and low sample consumption. In comparison to our previous laser ablation studies at infrared wavelengths, several improvements to the experimental setup have been made, which allow accurate control over the experimental conditions and good reproducibility of measurements. Current performance evaluations indicate significant improvements to several instrumental figures of merit. Calibration of the mass scale is performed within a mass accuracy (Δm/m) in the range of 100 ppm, and a typical mass resolution (m/Δm) ~600 is achieved at the lead mass peaks. At lower laser irradiances, the mass resolution is better, about (m/Δm) ~900 for lead, and limited by the laser pulse duration of 3 ns. The effective dynamic range of the instrument was enhanced from about 6 decades determined in previous study up to more than 8 decades at present. Current studies show high sensitivity in detection of both metallic and non-metallic elements. Their abundance down to tens of ppb can be measured together with their isotopic patterns. Due to strict control of the experimental parameters, e.g. laser characteristics, ion-optical parameters and sample position, by computer control, measurements can be performed with high reproducibility. Copyright © 2012 John Wiley & Sons, Ltd.

Efficiency of frost-cracking processes through space and time: An example from the eastern Italian Alps

It is widely accepted that climate has a strong impact and exerts important feedbacks on erosional processes and sediment transport mechanisms. However, the extent at which climate influences erosion is still a matter of debate. In this paper we test whether frost-cracking processes and related temperature variations can influence the sediment production and surface erosion in a small catchment situated in the eastern Italian Alps. To this extent, we first present a geomorphic map of the region that we complement with published 10Be-based denudation rates. We then apply a preexisting heat-flow model in order to analyze the variations of the frost-cracking intensity (FCI) in the study area, which could have controlled the sediment production in the basin. Finally, we compare the model results with the pattern of denudation rates and Quaternary deposits in the geomorphic map. The model results, combined with field observations, mapping, and quantitative geomorphic analyses, reveal that frost-cracking processes have had a primary role in the production of sediment where the intensity of sediment supply has been dictated and limited by the combined effect of temperature variations and conditions of bedrock preservation. These results highlight the importance of a yet poorly understood process for the production of sediment in mountain areas.

A study of the time complexity of an Elitist Genetic Algorithm used for associating optical observations of MEO and GEO Space Debris

Currently several thousands of objects are being tracked in the MEO and GEO regions through optical means. The problem faced in this framework is that of Multiple Target Tracking (MTT). In this context both the correct associations among the observations, and the orbits of the objects have to be determined. The complexity of the MTT problem is defined by its dimension S. Where S stands for the number of ’fences’ used in the problem, each fence consists of a set of observations that all originate from dierent targets. For a dimension of S ˃ the MTT problem becomes NP-hard. As of now no algorithm exists that can solve an NP-hard problem in an optimal manner within a reasonable (polynomial) computation time. However, there are algorithms that can approximate the solution with a realistic computational e ort. To this end an Elitist Genetic Algorithm is implemented to approximately solve the S ˃ MTT problem in an e cient manner. Its complexity is studied and it is found that an approximate solution can be obtained in a polynomial time. With the advent of improved sensors and a heightened interest in the problem of space debris, it is expected that the number of tracked objects will grow by an order of magnitude in the near future. This research aims to provide a method that can treat the correlation and orbit determination problems simultaneously, and is able to e ciently process large data sets with minimal manual intervention.