The potential of low-intensity and online interventions for depression in low- and middle-income countries

The World Health Organization (WHO) reports that low- and middle-income countries (LMICs) are confronted with a serious ‘mental health gap’, indicating an enormous disparity between the number of individuals in need of mental health care and the availability of professionals to provide such care (WHO in 2010). Traditional forms of mental health services (i.e. face-to-face, individualised assessments and interventions) are therefore not feasible. We propose three strategies for addressing this mental health gap: delivery of evidence-based, low-intensity interventions by non-specialists, the use of transdiagnostic treatment protocols, and strategic deployment of technology to facilitate access and uptake. We urge researchers from all over the world to conduct feasibility studies and randomised controlled studies on the effect of low-intensity interventions and technology supported (e.g. online) interventions in LMICs, preferably using an active control condition as comparison, to ensure we disseminate effective treatments in LMICs

Random matrix approach in search for weak signals immersed in background noise

We present new, original and alternative method for searching signals coded in noisy data. The method is based on the properties of random matrix eigenvalue spectra. First, we describe general ideas and support them with results of numerical simulations for basic periodic signals immersed in artificial stochastic noise. Then, the main effort is put to examine the strength of a new method in investigation of data content taken from the real astrophysical NAUTILUS detector, searching for the presence of gravitational waves. Our method discovers some previously unknown problems with data aggregation in this experiment. We provide also the results of new method applied to the entire respond signal from ground based detectors in future experimental activities with reduced background noise level. We indicate good performance of our method what makes it a positive predictor for further applications in many areas.Comment: 15 pages, 16 figure

Roughness and Finite Size Effect in the NYSE Stock-Price Fluctuations

We consider the roughness properties of NYSE (New York Stock Exchange) stock-price fluctuations. The statistical properties of the data are relatively homogeneous within the same day but the large jumps between different days prevent the extension of the analysis to large times. This leads to intrinsic finite size effects which alter the apparent Hurst (H) exponent. We show, by analytical methods, that finite size effects always lead to an enhancement of H. We then consider the effect of fat tails on the analysis of the roughness and show that the finite size effects are strongly enhanced by the fat tails. The non stationarity of the stock price dynamics also enhances the finite size effects which, in principle, can become important even in the asymptotic regime. We then compute the Hurst exponent for a set of stocks of the NYSE and argue that the interpretation of the value of H is highly ambiguous in view of the above results. Finally we propose an alternative determination of the roughness in terms of the fluctuations from moving averages with variable characteristic times. This permits to eliminate most of the previous problems and to characterize the roughness in useful way. In particular this approach corresponds to the automatic elimination of trends at any scale.Comment: 13 pages, 11 fugure

Analysis techniques for evaluating the fuel savings associated with wind assistance

Before steam and diesel engines, all cargo merchant ships were propelled by wind power. The arrival of cheap, high-density energy sources such as coal and oil and the economic benefits of the service speed and reliability that this enabled removed wind as a form of propulsion for much of the 20th century. However, higher prices for these energy commodities and environmental regulation, has led some to speculate that wind could return once again as a source of at least some share of a modern merchant ship’s propulsion energy requirement. A number of proposals for the technology that could enable this exist (e.g. soft-sails, wingsails and flettners), all share in common difficulties in their fair assessment, both relative to each other and relative to a conventionally powered ship. A moderately sized rig can supply anywhere between 0-100% of a merchant ship’s propulsion requirements, but this varies as a function of wind speed and direction, which in turn could vary several times a day over the course of multiple-day voyage. The weather, its variability and the specifics of a ship’s route are therefore all key components that render simpler ‘generic’ energy savings assessments meaningless. Furthermore, whilst conventional ships might sail a shortest distance route that avoids extreme weather, a wind-assisted ship might undertake more extreme variation in route and speed over the course of the voyage to maximize benefit obtained from the wind, and this in turn therefore needs to be taken into account in a fair comparison. This paper describes an analysis process that can be applied to any ship design and wind-assistance technology, to fairly evaluate the performance over a range of conditions, and then simulate the performance on a specific voyage using historical records of metocean parameters. The process is applied to an example design to illustrate the method

Developmental variation in predictors of reading comprehension amongst Maltese students

This study examined cognitive and language skills that are predictive of reading comprehension in Maltese in typically developing students of different ages. A structured random sample of three different grade groups of Maltese state school students, aged between 9 and 12 years participated in this study. This sample was representative of the population. They were administered a Maltese Reading Comprehension test together with three word-level tests (Non-Word Reading, Digit Span, and Rapid Naming), and three understanding-level tests (Jumbled Sentences, Listening Comprehension, and Ravens Progressive Matrices). Statistical analyses indicated that Reading Comprehension scores were primarily related to scores on listening comprehension and syntactic awareness (Jumbled Sentences). However, the youngest students showed greater influence of word-level processes on reading comprehension in contrast to their older peers.peer-reviewe

Exact Results for the Roughness of a Finite Size Random Walk

We consider the role of finite size effects on the value of the effective Hurst exponent H. This problem is motivated by the properties of the high frequency daily stock-prices. For a finite size random walk we derive some exact results based on Spitzer's identity. The conclusion is that finite size effects strongly enhance the value of H and the convergency to the asymptotic value (H=1/2) is rather slow. This result has a series of conceptual and practical implication which we discuss.Comment: 5 pages, 3 figure

Multifractal detrending moving average cross-correlation analysis

There are a number of situations in which several signals are simultaneously recorded in complex systems, which exhibit long-term power-law cross-correlations. The multifractal detrended cross-correlation analysis (MF-DCCA) approaches can be used to quantify such cross-correlations, such as the MF-DCCA based on detrended fluctuation analysis (MF-X-DFA) method. We develop in this work a class of MF-DCCA algorithms based on the detrending moving average analysis, called MF-X-DMA. The performances of the MF-X-DMA algorithms are compared with the MF-X-DFA method by extensive numerical experiments on pairs of time series generated from bivariate fractional Brownian motions, two-component autoregressive fractionally integrated moving average processes and binomial measures, which have theoretical expressions of the multifractal nature. In all cases, the scaling exponents $h_{xy}$ extracted from the MF-X-DMA and MF-X-DFA algorithms are very close to the theoretical values. For bivariate fractional Brownian motions, the scaling exponent of the cross-correlation is independent of the cross-correlation coefficient between two time series and the MF-X-DFA and centered MF-X-DMA algorithms have comparative performance, which outperform the forward and backward MF-X-DMA algorithms. We apply these algorithms to the return time series of two stock market indexes and to their volatilities. For the returns, the centered MF-X-DMA algorithm gives the best estimates of $h_{xy}(q)$ since its $h_{xy}(2)$ is closest to 0.5 as expected, and the MF-X-DFA algorithm has the second best performance. For the volatilities, the forward and backward MF-X-DMA algorithms give similar results, while the centered MF-X-DMA and the MF-X-DFA algorithms fails to extract rational multifractal nature.Comment: 15 pages, 4 figures, 2 matlab codes for MF-X-DMA and MF-X-DF