Identification of a Representative Stationary Period for Rainfall Variability Description in the Sudano-Sahelian Zone of West Africa during the 1901–2018 Period

Many studies have been undertaken on climate variability in West Africa since the drastic drought of 1970s. These studies rely in many cases on different baseline periods chosen with regard to the reference periods defined by the World Meteorological Organization. A method is developed in this study to determine a stationary baseline period for rainfall variability analysis. The method is based on an application of three statistic tests (on deviation and trend) and a test of shifts detection in rainfall time series. The application of this method on six different gridded rainfall data and observations from 1901 to 2018 shows that the 1917–1946 period is the longest stationary period. An assessment of the significance of the difference between the mean annual rainfall amount during this baseline period and the annual rainfall amount during the other years shows that the “Normal” annual rainfall amount is defined by an interval delineated by ±the standard deviation (STD). With regard to this interval, a very wet/dry year is defined with a surplus/gap over/below the STD. Overall the 1901–2018 period, the 1950–1970 period presents the most important number of significant wet years and the 1971–1990 period presents the most important number of significant dry years.

A Probabilistic Ensemble Prediction Method for PV Power in the Nonstationary Period

Due to the large number of grid connection of distributed power supply, the existing scheduling methods can not meet the demand gradually. The proposed virtual power plant provides a new idea to solve this problem. The photovoltaic power prediction provides the data basis for the scheduling of the virtual power plant. Prediction intervals of photovoltaic power is a powerful statistical tool used for quantifying the uncertainty of photovoltaic power generation in power systems. To improve the interval prediction accuracy during the non-stationary periods of photovoltaic power, this paper proposes a probabilistic ensemble prediction model, which combines the modules of data preprocessing, non-stationary period discrimination, feature extraction, deterministic prediction, uncertainty prediction, and optimization integration into a general framework. More specifically, in the non-stationary period discrimination module, the method of discriminating the difference of the power ratio difference is introduced and applied for identifying the non-stationary period of the data of photovoltaic output; in the deterministic point prediction module, a stacking- long-short-term memory neural network model is used for point forecasts; in the uncertainty interval prediction module, a BAYES neural network is introduced for probabilistic forecasts; in the optimization integration module, an optimization algorithm named Non-dominated Sorting Genetic Algorithm-II is applied for integrating and optimizing the results of the point forecast and probabilistic forecast. The proposed model is tested using two photovoltaic outputs and weather data measured from a grid-connected photovoltaic system. The results show that the proposed model outperforms conventional forecast methods to predict short-term photovoltaic power outputs and associated uncertainties. The interval width is reduced by 10–20%, and the prediction accuracy is improved by at least 10%; this can be a useful tool for photovoltaic power forecasting.

ANALYSIS OF THE STRUCTURE AND DYNAMICS OF VERBAL FUNCTIONS FOR THE FIRST YEAR AFTER ISCHEMIC STROKE

The results of psycho-correction speech therapy are analyzed in dynamics in 78 patients with varying severity and various forms of speech disorders in the early and late recovery periods of ischemic stroke. The effectiveness of conducting classes during the stay of patients in a neurological hospital and the positive impact of these exercises in the inpatient period (outpatient classes, classes at home with a speech therapist and trained relatives) are shown. Patients who did not conduct speech recovery classes during the inter-stationary period showed a decrease in speech activity, in some even a negative dynamic.

ANALYSIS OF THE STRUCTURE AND DYNAMICS OF VERBAL FUNCTIONS FOR THE FIRST YEAR AFTER ISCHEMIC STROKE

The results of psycho-correction speech therapy are analyzed in dynamics in 78 patients with varying severity and various forms of speech disorders in the early and late recovery periods of ischemic stroke. The effectiveness of conducting classes during the stay of patients in a neurological hospital and the positive impact of these exercises in the inpatient period (outpatient classes, classes at home with a speech therapist and trained relatives) are shown. Patients who did not conduct speech recovery classes during the inter-stationary period showed a decrease in speech activity, in some even a negative dynamic.

Time-motion analysis of competitive surfers: Portuguese championship

SUMMARY BACKGROUND: Time-motion analysis has been used to provide detailed insight into surfers’ performance. This study evaluated surfers’ activity times at the Portuguese surfing championship in order to account for the time spent in each surfing activity. METHODS: Eighty-seven individually recorded videos of surfers were analyzed, showing their activity over the entire heat, and video analysis software was used to obtain each surfer's activity profile in the competition. RESULTS: The results breakdown by time percentage show that the surfers were paddling 50.9% of the time, sprint paddling for wave 1.9%, were stationary 34.1% of the time, wave riding 3.7%, and involved in miscellaneous activities (e.g., duck diving, board recovery, etc.) 9.4% of the total time. Average times spent in each surfing activity were 18.6 seconds for paddling, 2.9 seconds for sprint paddling for a wave, 21.7 seconds for the stationary period, 11.5 seconds for wave riding, and 6.9 seconds for miscellaneous activities. CONCLUSIONS: The data revealed that the most performed heat activity was paddling, allowing us to conclude that surfing is basically a long-arm paddling activity and that this activity constitutes a specific surfing competition demand, which in turn means that individual surfer's data can be used as a starting point for the development of tailored conditioning training programs.

Modern Alterations of Climate Characteristics and Probabilistic Assessment of the Minimal Flow Alterations in the Volga River Basin

Unstationarity has been revealed in rows of minimal winter and summer/fall flow of the Volga basin and conventional stationary periods have been separated, the stationary regimes change dates have been determined. A method of obtaining of estimations of the minimal winter flow for future on the basis of correlation of minimal flow values changes with increments of ambient temperature to its average values over the previous conditionally stationary period.