Power-law persistence and trends in the atmosphere: A detailed study of long temperature records

We use several variants of the detrended fluctuation analysis to study the appearance of long-term persistence in temperature records, obtained at 95 stations all over the globe. Our results basically confirm earlier studies. We find that the persistence, characterized by the correlation C(s) of temperature variations separated by s days, decays for large s as a power law, C(s) ~ s^(-gamma). For continental stations, including stations along the coastlines, we find that gamma is always close to 0.7. For stations on islands, we find that gamma ranges between 0.3 and 0.7, with a maximum at gamma = 0.4. This is consistent with earlier studies of the persistence in sea surface temperature records where gamma is close to 0.4. In all cases, the exponent gamma does not depend on the distance of the stations to the continental coastlines. By varying the degree of detrending in the fluctuation analysis we obtain also information about trends in the temperature records.Comment: 5 pages, 4 including eps figure

Baseline characteristics and patient reported outcome data of patients prescribed etanercept: web-based and telephone evaluation

<p>Background: The anti-TNF inhibitor, etanercept is administered as a once or twice weekly subcutaneous injection for the treatment of rheumatoid arthritis, psoriasis, ankylosing spondylitis, psoriatic arthritis and juvenile idiopathic arthritis (JIA). Limited data from the patients' perspective are available on the use of biologics in the treatment of these chronic conditions and this evaluation was designed to collect data from patients who had been prescribed etanercept for the first time. This manuscript describes the self-reported baseline characteristics and health-related quality of life of patients prior to treatment. Follow-up data will be reported separately.</p> <p>Methods: Patients throughout the United Kingdom prescribed etanercept were invited to participate in an evaluation of their condition and treatment using a data collection tool consisting of a web-based system supplemented by telephone reporting (PROBE). Outcome measures reported at baseline included demographic data, the condition being treated, previous treatment with biologic agents and current and previous medications. Questions modified from standard, validated quality of life questionnaires such as EQ-5D were incorporated and patients made a global assessment of the severity of their own illness using the CGI-S scale.</p> <p>Results: A total of 344 patients/carers/parents participated in the evaluation at baseline, 290 (84%) by online questionnaire and 54 (16%) by telephone. Overall, the study population had a mean age of 53 years, was predominantly female (62%) and 20% had been previously treated with a biologic agent. A total of 191 (56%) patients were receiving treatment with etanercept for rheumatoid arthritis, 44 (13%) for psoriatic arthritis, 43 (13%) for ankylosing spondylitis, 35 (10%) for psoriasis, 9 (3%) for known juvenile idiopathic arthritis (JIA) and 22 (6%) for another condition/patient unsure/missing response. All patients were prescribed the 50 mg weekly dose of etanercept except for 1 patient with JIA (40 mg) dose and 2 patients with psoriasis (100 mg). Thirty-eight percent of patients with rheumatoid arthritis were not receiving treatment with methotrexate.</p> <p>Conclusions: The baseline characteristics and health-related quality of life of first time users of etanercept can be adequately described using self-reported patient data collected using an online questionnaire with a telephone option (PROBE).</p&gt

Nonlinear Volatility of River Flux Fluctuations

We study the spectral properties of the magnitudes of river flux increments, the volatility. The volatility series exhibits (i) strong seasonal periodicity and (ii) strongly power-law correlations for time scales less than one year. We test the nonlinear properties of the river flux increment series by randomizing its Fourier phases and find that the surrogate volatility series (i) has almost no seasonal periodicity and (ii) is weakly correlated for time scales less than one year. We quantify the degree of nonlinearity by measuring (i) the amplitude of the power spectrum at the seasonal peak and (ii) the correlation power-law exponent of the volatility series.Comment: 5 revtex pages, 6 page

Statistical Properties of Share Volume Traded in Financial Markets

We quantitatively investigate the ideas behind the often-expressed adage `it takes volume to move stock prices', and study the statistical properties of the number of shares traded $Q_{\Delta t}$ for a given stock in a fixed time interval $\Delta t$. We analyze transaction data for the largest 1000 stocks for the two-year period 1994-95, using a database that records every transaction for all securities in three major US stock markets. We find that the distribution $P(Q_{\Delta t})$ displays a power-law decay, and that the time correlations in $Q_{\Delta t}$ display long-range persistence. Further, we investigate the relation between $Q_{\Delta t}$ and the number of transactions $N_{\Delta t}$ in a time interval $\Delta t$, and find that the long-range correlations in $Q_{\Delta t}$ are largely due to those of $N_{\Delta t}$. Our results are consistent with the interpretation that the large equal-time correlation previously found between $Q_{\Delta t}$ and the absolute value of price change $| G_{\Delta t} |$ (related to volatility) are largely due to $N_{\Delta t}$.Comment: 4 pages, two-column format, four figure

Characteristics and outcomes of patients treated with apremilast in the real world: results from the APPRECIATE study

Background APPRECIATE is a multinational, observational, retrospective, cross‐sectional study in patients treated for psoriasis with apremilast, an oral phosphodiesterase 4 inhibitor. Objectives To describe the characteristics of patients with psoriasis treated with apremilast in the clinical setting, to evaluate real‐world outcomes of psoriasis treatment with apremilast and to better understand the perspectives of patients and physicians on treatment outcomes. Methods In six European countries, patients with chronic plaque psoriasis treated in clinical practice who could be contacted 6 (±1) months after apremilast initiation were enrolled. Patient characteristics, Dermatology Life Quality Index (DLQI) and Psoriasis Area and Severity Index (PASI) were obtained from medical records when available. Outcomes were evaluated using patient/physician questionnaires. Results In 480 patients at treatment initiation, mean [median; 95% confidence interval (CI)] PASI and DLQI scores were 12.5 (10.7; 11.6–13.4) and 13.4 (13.0; 11.4–14.2), respectively. At 6 (±1) months, 72.3% of patients (n = 347) continued apremilast treatment [discontinuations: lack of efficacy (13.5%), safety (11.7%), other (2.5%)]. In patients continuing treatment, 48.6% achieved a ≥75% reduction in PASI score; mean (95% CI) DLQI score was 5.7 (4.5–6.9), and mean (SD) Patient Benefit Index score was 2.8 (1.2). Physicians perceived clinical improvement in 75.6% of patients. Physicians’ perspective on overall success of apremilast in meeting expectations correlated with patients’ perception of treatment benefit (r = 0.691). Most commonly reported adverse events (>5% of patients) were diarrhoea, nausea and headache. Conclusions Patients in APPRECIATE reported high disease burden despite more moderate skin involvement than those who enrolled in clinical trials of apremilast. Findings from APPRECIATE demonstrate the real‐world value of apremilast for psoriasis treatment, as 7 of 10 patients continued therapy and showed notable improvement in disease severity and quality of life 6 (±1) months after apremilast initiation

Effect of Trends on Detrended Fluctuation Analysis

Detrended fluctuation analysis (DFA) is a scaling analysis method used to estimate long-range power-law correlation exponents in noisy signals. Many noisy signals in real systems display trends, so that the scaling results obtained from the DFA method become difficult to analyze. We systematically study the effects of three types of trends -- linear, periodic, and power-law trends, and offer examples where these trends are likely to occur in real data. We compare the difference between the scaling results for artificially generated correlated noise and correlated noise with a trend, and study how trends lead to the appearance of crossovers in the scaling behavior. We find that crossovers result from the competition between the scaling of the noise and the ``apparent'' scaling of the trend. We study how the characteristics of these crossovers depend on (i) the slope of the linear trend; (ii) the amplitude and period of the periodic trend; (iii) the amplitude and power of the power-law trend and (iv) the length as well as the correlation properties of the noise. Surprisingly, we find that the crossovers in the scaling of noisy signals with trends also follow scaling laws -- i.e. long-range power-law dependence of the position of the crossover on the parameters of the trends. We show that the DFA result of noise with a trend can be exactly determined by the superposition of the separate results of the DFA on the noise and on the trend, assuming that the noise and the trend are not correlated. If this superposition rule is not followed, this is an indication that the noise and the superimposed trend are not independent, so that removing the trend could lead to changes in the correlation properties of the noise.Comment: 20 pages, 16 figure

Markov Properties of Electrical Discharge Current Fluctuations in Plasma

Using the Markovian method, we study the stochastic nature of electrical discharge current fluctuations in the Helium plasma. Sinusoidal trends are extracted from the data set by the Fourier-Detrended Fluctuation analysis and consequently cleaned data is retrieved. We determine the Markov time scale of the detrended data set by using likelihood analysis. We also estimate the Kramers-Moyal's coefficients of the discharge current fluctuations and derive the corresponding Fokker-Planck equation. In addition, the obtained Langevin equation enables us to reconstruct discharge time series with similar statistical properties compared with the observed in the experiment. We also provide an exact decomposition of temporal correlation function by using Kramers-Moyal's coefficients. We show that for the stationary time series, the two point temporal correlation function has an exponential decaying behavior with a characteristic correlation time scale. Our results confirm that, there is no definite relation between correlation and Markov time scales. However both of them behave as monotonic increasing function of discharge current intensity. Finally to complete our analysis, the multifractal behavior of reconstructed time series using its Keramers-Moyal's coefficients and original data set are investigated. Extended self similarity analysis demonstrates that fluctuations in our experimental setup deviates from Kolmogorov (K41) theory for fully developed turbulence regime.Comment: 25 pages, 9 figures and 4 tables. V3: Added comments, references, figures and major correction