Structural and topological phase transitions on the German Stock Exchange

We find numerical and empirical evidence for dynamical, structural and topological phase transitions on the (German) Frankfurt Stock Exchange (FSE) in the temporal vicinity of the worldwide financial crash. Using the Minimal Spanning Tree (MST) technique, a particularly useful canonical tool of the graph theory, two transitions of the topology of a complex network representing FSE were found. First transition is from a hierarchical scale-free MST representing the stock market before the recent worldwide financial crash, to a superstar-like MST decorated by a scale-free hierarchy of trees representing the market's state for the period containing the crash. Subsequently, a transition is observed from this transient, (meta)stable state of the crash, to a hierarchical scale-free MST decorated by several star-like trees after the worldwide financial crash. The phase transitions observed are analogous to the ones we obtained earlier for the Warsaw Stock Exchange and more pronounced than those found by Onnela-Chakraborti-Kaski-Kert\'esz for S&P 500 index in the vicinity of Black Monday (October 19, 1987) and also in the vicinity of January 1, 1998. Our results provide an empirical foundation for the future theory of dynamical, structural and topological phase transitions on financial markets

Multi-command Tactile Brain Computer Interface: A Feasibility Study

The study presented explores the extent to which tactile stimuli delivered to the ten digits of a BCI-naive subject can serve as a platform for a brain computer interface (BCI) that could be used in an interactive application such as robotic vehicle operation. The ten fingertips are used to evoke somatosensory brain responses, thus defining a tactile brain computer interface (tBCI). Experimental results on subjects performing online (real-time) tBCI, using stimuli with a moderately fast inter-stimulus-interval (ISI), provide a validation of the tBCI prototype, while the feasibility of the concept is illuminated through information-transfer rates obtained through the case study.Comment: Haptic and Audio Interaction Design 2013, Daejeon, Korea, April 18-19, 2013, 15 pages, 4 figures, The final publication will be available at link.springer.co

COMORBIDITY OF SUBSTANCE USE AND MENTAL DISORDERS

Introduction: Comorbidity is a term defined as the presence of two or more conditions occurring either at the same time or having a close relationship to the same individual. World Health Organization (WHO) define it as the “co-occurrence in the same individual of a psychoactive substance use disorder and another psychiatric disorder”. Progressive deinstitutionalisation, despite indisputable benefits and improvement of life quality in psychiatric patients, resulted in appearance of new burdens, such as deterioration of family life. Furthermore, wide availability of alcoholic beverages and drugs in communities where the patients live, led comorbid substance abuse disorders to emerge as one of the biggest challenges in the modern psychiatry. There is a limited amount of data concerning the background of the patients with a dual diagnosis, available in the literature, and therefore our aim was to create a sociodemographic profile of such individuals. Materials and methods: The study was conducted among the patients treated in a drug rehabilitation centre of the Upper Silesian Association “Familia” in Gliwice, Poland using authors’ own questionnaire, consisting of 75 items. The study group consisted of 9 females and 91 males (n=100), average age of the patients equalled 29.7 years (95%CI: 28.5-31 years; min/max value: 20/48 years), all the patients had an established dual diagnosis. Outcomes: 66% of the study group was single, with permanent residency, living with family either in city (47%) or in village (19%). Remaining 34% was spread through the other options (1-4%), with the highest percentage in “single, with permanent residency, living alone in the city” (4%). Conclusions: Obtained data, demonstrated high homogeneity among the patients with a dual diagnosis in terms of a sociodemographical profile

COMORBIDITY OF SUBSTANCE USE AND MENTAL DISORDERS

Introduction: Comorbidity is a term defined as the presence of two or more conditions occurring either at the same time or having a close relationship to the same individual. World Health Organization (WHO) define it as the “co-occurrence in the same individual of a psychoactive substance use disorder and another psychiatric disorder”. Progressive deinstitutionalisation, despite indisputable benefits and improvement of life quality in psychiatric patients, resulted in appearance of new burdens, such as deterioration of family life. Furthermore, wide availability of alcoholic beverages and drugs in communities where the patients live, led comorbid substance abuse disorders to emerge as one of the biggest challenges in the modern psychiatry. There is a limited amount of data concerning the background of the patients with a dual diagnosis, available in the literature, and therefore our aim was to create a sociodemographic profile of such individuals. Materials and methods: The study was conducted among the patients treated in a drug rehabilitation centre of the Upper Silesian Association “Familia” in Gliwice, Poland using authors’ own questionnaire, consisting of 75 items. The study group consisted of 9 females and 91 males (n=100), average age of the patients equalled 29.7 years (95%CI: 28.5-31 years; min/max value: 20/48 years), all the patients had an established dual diagnosis. Outcomes: 66% of the study group was single, with permanent residency, living with family either in city (47%) or in village (19%). Remaining 34% was spread through the other options (1-4%), with the highest percentage in “single, with permanent residency, living alone in the city” (4%). Conclusions: Obtained data, demonstrated high homogeneity among the patients with a dual diagnosis in terms of a sociodemographical profile

Determination of the Hurst Exponent by Use of Wavelet Transforms

We propose a new method for (global) Hurst exponent determination based on wavelets. Using this method, we analyze synthetic data with predefined Hurst exponents, fracture surfaces and data from economy. The results are compared with those obtained from Fourier spectral analysis. When many samples are available, the wavelet and Fourier methods are comparable in accuracy. However, when one or only a few samples are available, the wavelet method outperforms the Fourier method by a large margin.Comment: 10 pages RevTeX, 13 Postscript figures. Some additional material compared to previous versio

Dopant clustering and vacancy ordering in neodymium doped ceria

Lanthanide doped cerias, show fast oxide ion conduction and have applications as electrolytes in intermediate temperature solid oxide fuel cells. Here, we examine the long- and short-range structures of Ce1−xNdxO2−x/2 (0.05 ≤ x ≤ 0.30, NDC) using reverse Monte Carlo modelling of total neutron scattering data, supported by measurements of electrical behaviour using a.c. impedance spectroscopy. Three distinct features are evident in the local structure of NDC, viz.: clustering of Nd3+ cations, preferred Nd3+-oxide ion vacancy association and oxide ion vacancy clustering with preferential alignment in the 〈100〉 direction. Interestingly, the presence of preferential dopant cation-oxide ion vacancy association is also observed at 600 °C, although diminished compared to the level at room temperature. This suggests a continued contribution of defect association enthalpy to activation energy at elevated temperatures and is reflected in similar compositional variation of high- and low-temperature activation energies

Heuristic Segmentation of a Nonstationary Time Series

Many phenomena, both natural and human-influenced, give rise to signals whose statistical properties change under time translation, i.e., are nonstationary. For some practical purposes, a nonstationary time series can be seen as a concatenation of stationary segments. Using a segmentation algorithm, it has been reported that for heart beat data and Internet traffic fluctuations--the distribution of durations of these stationary segments decays with a power law tail. A potential technical difficulty that has not been thoroughly investigated is that a nonstationary time series with a (scale-free) power law distribution of stationary segments is harder to segment than other nonstationary time series because of the wider range of possible segment sizes. Here, we investigate the validity of a heuristic segmentation algorithm recently proposed by Bernaola-Galvan et al. by systematically analyzing surrogate time series with different statistical properties. We find that if a given nonstationary time series has stationary periods whose size is distributed as a power law, the algorithm can split the time series into a set of stationary segments with the correct statistical properties. We also find that the estimated power law exponent of the distribution of stationary-segment sizes is affected by (i) the minimum segment size, and (ii) the ratio of the standard deviation of the mean values of the segments, and the standard deviation of the fluctuations within a segment. Furthermore, we determine that the performance of the algorithm is generally not affected by uncorrelated noise spikes or by weak long-range temporal correlations of the fluctuations within segments.Comment: 23 pages, 14 figure