We present a detailed X-ray timing analysis of the highly variable narrow-line Seyfert 1 ( NLS1) galaxy IRAS 13224-3809. The source was recently monitored for 1.5Ms with XMM-Newton, which, combined with 500 ks archival data, makes this the best-studied NLS1 galaxy in X-rays to date. We apply standard time- and Fourier-domain techniques in order to understand the underlying variability process. The source flux is not distributed lognormally, as expected for all types of accreting sources. The first non-linear rms-flux relation for any accreting source in any waveband is found, with rms. flux2/3. The light curves exhibit significant strong non-stationarity, in addition to that caused by the rms-flux relation, and are fractionally more variable at lower source flux. The power spectrum is estimated down to similar to 10(-7) Hz and consists of multiple peaked components: a low-frequency break at similar to 10(-5) Hz, with slope alpha < 1 down to low frequencies, and an additional component breaking at similar to 10(-3) Hz. Using the high-frequency break, we estimate the black hole mass MBH = [0.5-2] x 10(6)M(circle dot) and mass accretion rate in Eddington units,. m Edd greater than or similar to 1. The broad-band power spectral density (PSD) and accretion rate make IRAS 13224-3809 a likely analogue of very high/intermediate-state black hole X-ray binaries. The non-stationarity is manifest in the PSD with the normalization of the peaked components increasing with decreasing source flux, as well as the low-frequency peak moving to higher frequencies. We also detect a narrow coherent feature in the soft-band PSD at 7 x 10(-4) Hz; modelled with a Lorentzian the feature has Q similar to 8 and an rms similar to 3 per cent. We discuss the implication of these results for accretion of matter on to black holes.
Variability among populations of Ziziphora clinopodioides Lam. subsp. bungeana (Juz.) was analyzed, to evaluate the level and distribution of differentiation among four distant populations from sub-humid, upper semi-arid and semi-arid bioclimates of Khorasan provinces, Iran. Analyses of variances and cluster analysis have been carried out to define the variability and significance of morphological differentiation. Morphological differentiation was correlated with ecological situations at the location of origination and a high variation among populations based on morphological traits was observed between the plants belonging to semi-arid populations vs. the sub-humid ones. Essential oil composition varied among populations. In all of the populations pulegone was the main component, followed by isomentone and thymol. The clustering, based on oil analysis generated two distinct clusters. Essential oils of the upper semi-arid and sub-humid populations were rich in Iso-menthone, while populations from the semi-arid bioclimate were characterized by high amounts of pulegone. The relatively low morpho-chemical diversity in the populations of Z. clinopodioides indicates that the maintenance of their evolutionary potential is at risk if population sizes are not maintained and if there is no protection of the habitats.
The proposed contribution of glucose variability to the development of the complications of diabetes beyond that of glycemic exposure is supported by reports that oxidative stress, the putative mediator of such complications, is greater for intermittent as opposed to sustained hyperglycemia. Variability of glycemia in ambulatory conditions defined as the deviation from steady state is a phenomenon of normal physiology. Comprehensive recording of glycemia is required for the generation of any measurement of glucose variability. To avoid distortion of variability to that of glycemic exposure, its calculation should be devoid of a time component. Diabetes 62:1398-1404, 2013
► The scaling ( ) of correlations between pairs of sites is examined in detail. ► is found to be linearly proportional to cloud speed, with the equation . ► Cloud speeds are found from numerical weather models. ► WVM simulations of PV output closely match RR statistics of measured power. The Wavelet Variability Model (WVM) for simulating solar photovoltaic (PV) powerplant output given a single irradiance sensor as input has been developed and validated previously. Central to the WVM method is a correlation scaling coefficient ( ) that calibrates the decay of correlation of wavelet modes as a function of distance and timescale, and which varies by day and geographic location. Previously, a local irradiance sensor network was required to derive . In this work, we determine from cloud speeds. Cloud simulator results indicated that the value is linearly proportional to the cloud speed (CS): . Cloud speeds from a numerical weather model (NWM) were then used to create a database of daily values for North America. For validation, the WVM was run to simulate a 48 MW PV plant with both NWM values and with ground values found from a sensor network. Both WVM methods closely matched the distribution of ramp rates (RRs) of measured power, and were a strong improvement over linearly scaling up a point sensor. The incremental error in using NWM values over ground values was small. The ability to use NWM-derived values means that the WVM can be used to simulate a PV plant anywhere a single high-frequency irradiance sensor exists. This can greatly assist in module siting, plant sizing, and storage decisions for prospective PV plants.
Abstract Kubios HRV is an advanced and easy to use software for heart rate variability (HRV) analysis. The software supports several input data formats for electrocardiogram (ECG) data and beat-to-beat RR interval data. It includes an adaptive QRS detection algorithm and tools for artifact correction, trend removal and analysis sample selection. The software computes all the commonly used time-domain and frequency-domain HRV parameters and several nonlinear parameters. There are several adjustable analysis settings through which the analysis methods can be optimized for different data. The ECG derived respiratory frequency is also computed, which is important for reliable interpretation of the analysis results. The analysis results can be saved as an ASCII text file (easy to import into MS Excel or SPSS), Matlab MAT-file, or as a PDF report. The software is easy to use through its compact graphical user interface. The software is available free of charge for Windows and Linux operating systems at http://kubios.uef.fi.
INTRODUCTION: We investigated whether markers of airway and systemic inflammation, as well as heart rate variability (HRV) in asthmatics, change in response to fluctuations in ambient particulate matter (PM) in the coarse [PM with aerodynamic diameter 2.5-10 mu M (PM2.5-10)] and fine (PM2.5) size range. METHODS: Twelve adult asthmatics, living within a 30-mile radius of an atmospheric monitoring site in Chapel Hill, North Carolina, were followed over a 12-week period. Daily PM2.5-10 and PM2.5 concentrations were measured separately for each 24-hr period. Each subject had nine clinic visits, at which spirometric measures and peripheral blood samples for analysis of lipids, inflammatory cells, and coagulation-associated proteins were obtained. We also assessed HRV [SDNN24HR (standard deviation of all normal-to-normal intervals in a 24-hr recording), ASDNN5 (mean of the standard deviation in A 5-min segments of a 24-hr recording)] with four consecutive 24-hr ambulatory electrocardiogram measurements. Linear mixed models with a spatial covariance matrix structure and a 1-day lag were used to assess potential associations between PM levels and cardio- pulmonary end points. RESULTS: For a 1-mu g/m(3) increase in coarse PM, SDNN24HR, and ASDNN5 decreased 3.36% (p 0.02), and 0.77%, (p = 0.05) respectively. With a 1-mu g/m(3) increase in coarse PM, circulating eosinophils increased 0.16% (p = 0.01), triglycerides increased 4.8% (p = 0.02), and very low-density lipoprotein increased 1.15% (p = 0.01). No significant associations were found with fine PM, and none with lung function. CONCLUSION: These data suggest that small temporal increases in ambient coarse PM are sufficient to affect important cardiopulmonary and lipid parameters in adults with asthma. Coarse PM may have underappreciated health effects in susceptible populations.
Responses of sensory neurons differ across repeated measurements. This variability is usually treated as stochasticity arising within neurons or neural circuits. However, some portion of the variability arises from fluctuations in excitability due to factors that are not purely sensory, such as arousal, attention and adaptation. To isolate these fluctuations, we developed a model in which spikes are generated by a Poisson process whose rate is the product of a drive that is sensory in origin and a gain summarizing stimulus-independent modulatory influences on excitability. This model provides an accurate account of response distributions of visual neurons in macaque lateral geniculate nucleus and cortical areas V1, V2 and MT, revealing that variability originates in large part from excitability fluctuations that are correlated over time and between neurons, and that increase in strength along the visual pathway. The model provides a parsimonious explanation for observed systematic dependencies of response variability and covariability on firing rate.
The international scientific community has highlighted decadal and multidecadal climate variability as a priority area for climate research. The Indian Ocean rim region is home to one-third of the world's population, mostly living in developing countries that are vulnerable to climate variability and to the increasing pressure of anthropogenic climate change. Yet, while prominent decadal and multidecadal variations occur in the Indian Ocean, they have been less studied than those in the Pacific and Atlantic Oceans. This paper reviews existing literature on these Indian Ocean variations, including observational evidence, physical mechanisms, and climatic impacts. This paper also identifies major issues and challenges for future Indian Ocean research on decadal and multidecadal variability.
On 2015 June 16, Fermi- LAT observed a giant outburst from the flat spectrum radio quasar 3C 279 with a peak >100 MeV flux of similar to 3.6 x 10(-5) photons cm(-2) s(-1), averaged over orbital period intervals. It is historically the highest gamma-ray flux observed from the source, including past EGRET observations, with the gamma-ray isotropic luminosity reaching similar to 10(49) erg s(-1). During the outburst, the Fermi spacecraft, which has an orbital period of 95.4 minutes, was operated in a special pointing mode to optimize the exposure for 3C 279. For the first time, significant flux variability at sub-orbital timescales was found in blazar observations by Fermi- LAT. The source flux variability was resolved down to 2-minute binned timescales, with flux doubling times of less than 5 minutes. The observed minute-scale variability suggests a very compact emission region at hundreds of Schwarzschild radii from the central engine in conical jet models. A minimum bulk jet Lorentz factor (Gamma) of 35 is necessary to avoid both internal gamma-ray absorption and super-Eddington jet power. In the standard external radiation Comptonization scenario, G should be at least 50 to avoid overproducing the synchrotron self-Compton component. However, this predicts extremely low magnetization (similar to 5 x 10(-4)). Equipartition requires Gamma as high as 120, unless the emitting region is a small fraction of the dissipation region. Alternatively, we consider. rays originating as synchrotron radiation of gamma e similar to 1.6 x 10(6) electrons, in a magnetic field B similar to 1.3 kG, accelerated by strong electric fields E similar to B in the process of magnetoluminescence. At such short distance scales, one cannot immediately exclude the production of gamma-rays in hadronic processes.