57,358 research outputs found

    Analysis of cross-correlations in electroencephalogram signals as an approach to proactive diagnosis of schizophrenia

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    We apply flicker-noise spectroscopy (FNS), a time series analysis method operating on structure functions and power spectrum estimates, to study the clinical electroencephalogram (EEG) signals recorded in children/adolescents (11 to 14 years of age) with diagnosed schizophrenia-spectrum symptoms at the National Center for Psychiatric Health (NCPH) of the Russian Academy of Medical Sciences. The EEG signals for these subjects were compared with the signals for a control sample of chronically depressed children/adolescents. The purpose of the study is to look for diagnostic signs of subjects' susceptibility to schizophrenia in the FNS parameters for specific electrodes and cross-correlations between the signals simultaneously measured at different points on the scalp. Our analysis of EEG signals from scalp-mounted electrodes at locations F3 and F4, which are symmetrically positioned in the left and right frontal areas of cerebral cortex, respectively, demonstrates an essential role of frequency-phase synchronization, a phenomenon representing specific correlations between the characteristic frequencies and phases of excitations in the brain. We introduce quantitative measures of frequency-phase synchronization and systematize the values of FNS parameters for the EEG data. The comparison of our results with the medical diagnoses for 84 subjects performed at NCPH makes it possible to group the EEG signals into 4 categories corresponding to different risk levels of subjects' susceptibility to schizophrenia. We suggest that the introduced quantitative characteristics and classification of cross-correlations may be used for the diagnosis of schizophrenia at the early stages of its development.Comment: 36 pages, 6 figures, 2 tables; to be published in "Physica A

    Multi-Scale Simulation Modeling for Prevention and Public Health Management of Diabetes in Pregnancy and Sequelae

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    Diabetes in pregnancy (DIP) is an increasing public health priority in the Australian Capital Territory, particularly due to its impact on risk for developing Type 2 diabetes. While earlier diagnostic screening results in greater capacity for early detection and treatment, such benefits must be balanced with the greater demands this imposes on public health services. To address such planning challenges, a multi-scale hybrid simulation model of DIP was built to explore the interaction of risk factors and capture the dynamics underlying the development of DIP. The impact of interventions on health outcomes at the physiological, health service and population level is measured. Of particular central significance in the model is a compartmental model representing the underlying physiological regulation of glycemic status based on beta-cell dynamics and insulin resistance. The model also simulated the dynamics of continuous BMI evolution, glycemic status change during pregnancy and diabetes classification driven by the individual-level physiological model. We further modeled public health service pathways providing diagnosis and care for DIP to explore the optimization of resource use during service delivery. The model was extensively calibrated against empirical data.Comment: 10 pages, SBP-BRiMS 201

    Comparison of different classification algorithms for fault detection and fault isolation in complex systems

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    Due to the lack of sufficient results seen in literature, feature extraction and classification methods of hydraulic systems appears to be somewhat challenging. This paper compares the performance of three classifiers (namely linear support vector machine (SVM), distance-weighted k-nearest neighbor (WKNN), and decision tree (DT) using data from optimized and non-optimized sensor set solutions. The algorithms are trained with known data and then tested with unknown data for different scenarios characterizing faults with different degrees of severity. This investigation is based solely on a data-driven approach and relies on data sets that are taken from experiments on the fuel system. The system that is used throughout this study is a typical fuel delivery system consisting of standard components such as a filter, pump, valve, nozzle, pipes, and two tanks. Running representative tests on a fuel system are problematic because of the time, cost, and reproduction constraints involved in capturing any significant degradation. Simulating significant degradation requires running over a considerable period; this cannot be reproduced quickly and is costly

    Płaszczyzny budowania zaufania do funduszy emerytalnych działających w Polsce

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    Celem artykułu jest analiza zaufania do otwartych funduszy emerytalnych (OFE) jako podmiotów funkcjonujących w polskim systemie emerytalnym. Zadaniem OFE jest gromadzenie funduszy zaoszczędzonych przez Polaków i zarządzanie nimi w celu zabezpieczenia kapitałów po przejściu na emeryturę. Polacy często lekceważą potrzebę oszczędzania środków na starość, mimo że polski system emerytalny zakłada indywidualne przedsięwzięcia emerytalne. W artykule wskazano czynniki i płaszczyzny budowania zaufania do OFE jako instytucji funkcjonujących w II filarze systemu emerytalnego. Zaufanie do systemu emerytalnego może być budowane przez zaufanie do poszczególnych instytucji funkcjonujących w danym systemie. Wydzielenie czynników zaufania do OFE może wskazać metody budowania zaufania do całego systemu emerytalnego.The purpose of this article is to analyze the trust in Open Pension Funds (OPF) as entities operating in the Polish pension system. The task of OPFs is to collect and manage the funds accumulated by Poles in order to secure their capital after retirement. Poles often ignore the need to save money for old age, despite the fact that the Polish pension system provides for individual pension schemes. This article indicates the factors for building the trust in OPFs as institutions operating within the second pillar of the pension system. The trust in the pension system can be built through the trust in the individual institutions operating in the given system. Separating trust factors related to OPFs can indicate the methods of building the trust in the entire pension system

    Rhythmic dynamics and synchronization via dimensionality reduction : application to human gait

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    Reliable characterization of locomotor dynamics of human walking is vital to understanding the neuromuscular control of human locomotion and disease diagnosis. However, the inherent oscillation and ubiquity of noise in such non-strictly periodic signals pose great challenges to current methodologies. To this end, we exploit the state-of-the-art technology in pattern recognition and, specifically, dimensionality reduction techniques, and propose to reconstruct and characterize the dynamics accurately on the cycle scale of the signal. This is achieved by deriving a low-dimensional representation of the cycles through global optimization, which effectively preserves the topology of the cycles that are embedded in a high-dimensional Euclidian space. Our approach demonstrates a clear advantage in capturing the intrinsic dynamics and probing the subtle synchronization patterns from uni/bivariate oscillatory signals over traditional methods. Application to human gait data for healthy subjects and diabetics reveals a significant difference in the dynamics of ankle movements and ankle-knee coordination, but not in knee movements. These results indicate that the impaired sensory feedback from the feet due to diabetes does not influence the knee movement in general, and that normal human walking is not critically dependent on the feedback from the peripheral nervous system
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