8 research outputs found
Monthly sunspot number time series analysis and its modeling through autoregressive artificial neural network
This study reports a statistical analysis of monthly sunspot number time
series and observes non homogeneity and asymmetry within it. Using Mann-Kendall
test a linear trend is revealed. After identifying stationarity within the time
series we generate autoregressive AR(p) and autoregressive moving average
(ARMA(p,q)). Based on minimization of AIC we find 3 and 1 as the best values of
p and q respectively. In the next phase, autoregressive neural network
(AR-NN(3)) is generated by training a generalized feedforward neural network
(GFNN). Assessing the model performances by means of Willmott's index of second
order and coefficient of determination, the performance of AR-NN(3) is
identified to be better than AR(3) and ARMA(3,1).Comment: 17 pages, 4 figure
Predictions of the Maximum Amplitude, Time of Occurrence, and Total Length of Solar Cycle 24
In this work we predict the maximum amplitude, its time of occurrence, and
the total length of Solar Cycle 24 by linear regression to the curvature
(second derivative) at the preceding minimum of a smoothed version of the
sunspots time series. We characterise the predictive power of the proposed
methodology in a causal manner by an incremental incorporation of past solar
cycles to the available data base. In regressing maximum cycle intensity to
curvature at the leading minimum we obtain a correlation coefficient R \approx
0.91 and for the upcoming Cycle 24 a forecast of 78 (90% confidence interval:
56 - 106). Ascent time also appears to be highly correlated to the second
derivative at the starting minimum (R \approx -0.77), predicting maximum solar
activity for October 2013 (90% confidence interval: January 2013 to September
2014). Solar Cycle 24 should come to an end by February 2020 (90% confidence
interval: January 2019 to July 2021), although in this case correlational
evidence is weaker (R \approx -0.56).Comment: Accepted in Solar Physic
Monitoring quality and coverage of harm reduction services for people who use drugs: A consensus study
Background and aims: Despite advances in our knowledge of effective services for people who use drugs over the last decades globally, coverage remains poor in most countries, while quality is often unknown. This paper aims to discuss the historical development of successful epidemiological indicators and to present a framework for extending them with additional indicators of coverage and quality of harm reduction services, for monitoring and evaluation at international, national or subnational levels. The ultimate aim is to improve these services in order to reduce health and social problems among people who use drugs, such as human immunodeficiency virus (HIV) and hepatitis C virus (HCV) infection, crime and legal problems, overdose (death) and other morbidity and mortality. Methods and results: The framework was developed collaboratively using consensus methods involving nominal group meetings, review of existing quality standards, repeated email commenting rounds and qualitative analysis of opinions/experiences from a broad range of professionals/experts, including members of civil society and organisations representing people who use drugs. Twelve priority candidate indicators are proposed for opioid agonist therapy (OAT), needle and syringe programmes (NSP) and generic cross-cutting aspects of harm reduction (and potentially other drug) services. Under the specific OAT indicators, priority indicators included 'coverage', 'waiting list time', 'dosage' and 'availability in prisons'. For the specific NSP indicators, the priority indicators included 'coverage', 'number of needles/syringes distributed/collected', 'provision of other drug use paraphernalia' and 'availability in prisons'. Among the generic or cross-cutting indicators the priority indicators were 'infectious diseases counselling and care', 'take away naloxone', 'information on safe use/sex' and 'condoms'. We discuss conditions for the successful development of the suggested indicators and constraints (e.g. funding, ideology). We propose conducting a pilot study to test the feasibility and applicability of the proposed indicators before their scaling up and routine implementation, to evaluate their effectiveness in comparing service coverage and quality across countries. Conclusions: The establishment of an improved set of validated and internationally agreed upon best practice indicators for monitoring harm reduction service will provide a structural basis for public health and epidemiological studies and support evidence and human rights-based health policies, services and interventions. © 2017 The Author(s)