Intelligent techniques, harmonically coupled and SARIMA models in forecasting solar radiation data: A hybridization approach

The unsteady and intermittent feature (mainly due to atmospheric mechanisms and diurnal cycles) of solar energy resource is often a stumbling block, due to its unpredictable nature, to receiving high-intensity levels of solar radiation at ground level. Hence, there has been a growing demand for accurate solar irradiance forecasts that properly explain the mixture of deterministic and stochastic characteristic (which may be linear or nonlinear) in which solar radiation presents itself on the earth’s surface. The seasonal autoregressive integrated moving average (SARIMA) models are popular for accurately modelling linearity, whilst the neural networks effectively capture the aspect of nonlinearity embedded in solar radiation data at ground level. This comparative study couples sinusoidal predictors at specified harmonic frequencies with SARIMA models, neural network autoregression (NNAR) models and the hybrid (SARIMA-NNAR) models to form the respective harmonically coupled models, namely, HCSARIMA models, HCNNAR models and HCSARIMA-NNAR models, with the sinusoidal predictor function, SARIMA, and NNAR parts capturing the deterministic, linear and nonlinear components, respectively. These models are used to forecast 10-minutely and 60-minutely averaged global horizontal irradiance data series obtained from the RVD Richtersveld solar radiometric station in the Northern Cape, South Africa. The forecasting accuracy of the three above-mentioned models is undertaken based on the relative mean square error, mean absolute error and mean absolute percentage error. The HCNNAR model and HCSARIMA-NNAR model gave more accurate forecasting results for 60-minutely and 10-minutely data, respectively. Highlights HCSARIMA models were outperformed by both HCNNAR models and HCSARIMA-NNAR models in the forecasting arena. HCNNAR models were most appropriate for forecasting larger time scales (i.e. 60-minutely). HCSARIMA-NNAR models were most appropriate for forecasting smaller time scales (i.e. 10-minutely). Models fitted on the January data series performed better than those fitted on the June data series

An analysis of recent stroke cases in South Africa: Trend, seasonality and predictors

Background. South Africa (SA) is experiencing an epidemiological transition as a result of sociodemographic and lifestyle changes. This process is leading to an increase in non-communicable diseases, which in turn may result in an upswing of stroke cases. Stroke is among the top 10 leading causes of disability in SA, and accounts for ~25 000 deaths annually and 95 000 years lived with disability (YLD). This huge burden of stroke hampers socioeconomic development as a result of YLD. Objectives. To investigate the seasonality and trend of stroke cases in SA, and determine the risk factors associated with stroke. Methods. Using recent hospital-based data (January 2014 - December 2017 inclusive) from SA private and public hospitals (33% private and 67% public), a sample of 14 645 suspected stroke cases was drawn. Associations between suspected stroke cases and potential predictors were assessed using χ2 tests and bivariate analysis. Time series analysis tools for trend and seasonality components included both time domain and frequency domain techniques. A Poisson generalised linear model was used, as there was no over-dispersion inherent in the data. Multiple logistic regression analysis was used to assess the effect of several predictors on stroke cases. Results. Of the 14 645 suspected cases of stroke, 51.5% were confirmed. Seasonality analysis gave an approximate seasonal change of 120 cases, the highest seasonal peak occurring in mid-winter and the lowest dip in mid-summer. Both upward trend and seasonality parameters were found to be statistically significant. Predictors significantly associated with an increased likelihood of stroke were heart problems (odds ratio (OR) 8.86; 95% confidence interval (CI) 8.23 - 9.55; p<0.0001), diabetes (OR 14.53; 95% CI 13.36 - 15.79; p<0.0001), female sex (OR 18.23; 95% CI 16.75 - 19.85; p<0.0001), age 59 - 77 years (OR 1.37; 95% CI 1.24 - 1.50; p<0.0001) and 78 - 98 years (OR 1.25; 95% CI 1.16 - 1.35; p<0.0001) and white ethnic group (OR 2.00; 95% CI 1.86 - 2.15; p<0.0001), compared with the respective reference groups. The prevalence ratios of stroke cases as measured by Poisson regression were in agreement with logistic regression results. Conclusions. The increasing trend of stroke in SA should be arrested urgently, taking into account both the associated risk factors and seasonality.Statistic

Aeromagnetic, Gravity, and Differential Interferometric Synthetic Aperture Radar Analyses Reveal the Causative Fault of the 3 April 2017 M\u3csub\u3ew\u3c/sub\u3e 6.5 Moiyabana, Botswana, Earthquake

On 3 April 2017, a Mw 6.5 earthquake struck Moiyabana, Botswana, nucleating at \u3e20 km focal depth within the Paleoproterozoic Limpopo-Shashe orogenic belt separating the Archean Zimbabwe and Kaapvaal Cratons. We investigate the lithospheric structures associated with this earthquake using high-resolution aeromagnetic and gravity data integrated with Differential Interferometric Synthetic Aperture Radar (DInSAR) analysis. Here we present the first results that provide insights into the tectonic framework of the earthquake. The ruptured fault trace delineated by DInSAR aligns with a distinct NW striking and NE dipping magnetic lineament within the Precambrian basement. The fault plane solution and numerical modeling indicate that the cause of the earthquake was 1.8 m displacement along a NW striking and NE dipping normal fault, rupturing at 21-24 km depth. We suggest that this seismic event was due to extensional reactivation of a crustal-scale Precambrian thrust splay within the Limpopo-Shashe orogenic belt

Independent and combined effects of improved water, sanitation, and hygiene, and improved complementary feeding, on child stunting and anaemia in rural Zimbabwe: a cluster-randomised trial.

BACKGROUND: Child stunting reduces survival and impairs neurodevelopment. We tested the independent and combined effects of improved water, sanitation, and hygiene (WASH), and improved infant and young child feeding (IYCF) on stunting and anaemia in in Zimbabwe. METHODS: We did a cluster-randomised, community-based, 2 × 2 factorial trial in two rural districts in Zimbabwe. Clusters were defined as the catchment area of between one and four village health workers employed by the Zimbabwe Ministry of Health and Child Care. Women were eligible for inclusion if they permanently lived in clusters and were confirmed pregnant. Clusters were randomly assigned (1:1:1:1) to standard of care (52 clusters), IYCF (20 g of a small-quantity lipid-based nutrient supplement per day from age 6 to 18 months plus complementary feeding counselling; 53 clusters), WASH (construction of a ventilated improved pit latrine, provision of two handwashing stations, liquid soap, chlorine, and play space plus hygiene counselling; 53 clusters), or IYCF plus WASH (53 clusters). A constrained randomisation technique was used to achieve balance across the groups for 14 variables related to geography, demography, water access, and community-level sanitation coverage. Masking of participants and fieldworkers was not possible. The primary outcomes were infant length-for-age Z score and haemoglobin concentrations at 18 months of age among children born to mothers who were HIV negative during pregnancy. These outcomes were analysed in the intention-to-treat population. We estimated the effects of the interventions by comparing the two IYCF groups with the two non-IYCF groups and the two WASH groups with the two non-WASH groups, except for outcomes that had an important statistical interaction between the interventions. This trial is registered with ClinicalTrials.gov, number NCT01824940. FINDINGS: Between Nov 22, 2012, and March 27, 2015, 5280 pregnant women were enrolled from 211 clusters. 3686 children born to HIV-negative mothers were assessed at age 18 months (884 in the standard of care group from 52 clusters, 893 in the IYCF group from 53 clusters, 918 in the WASH group from 53 clusters, and 991 in the IYCF plus WASH group from 51 clusters). In the IYCF intervention groups, the mean length-for-age Z score was 0·16 (95% CI 0·08-0·23) higher and the mean haemoglobin concentration was 2·03 g/L (1·28-2·79) higher than those in the non-IYCF intervention groups. The IYCF intervention reduced the number of stunted children from 620 (35%) of 1792 to 514 (27%) of 1879, and the number of children with anaemia from 245 (13·9%) of 1759 to 193 (10·5%) of 1845. The WASH intervention had no effect on either primary outcome. Neither intervention reduced the prevalence of diarrhoea at 12 or 18 months. No trial-related serious adverse events, and only three trial-related adverse events, were reported. INTERPRETATION: Household-level elementary WASH interventions implemented in rural areas in low-income countries are unlikely to reduce stunting or anaemia and might not reduce diarrhoea. Implementation of these WASH interventions in combination with IYCF interventions is unlikely to reduce stunting or anaemia more than implementation of IYCF alone. FUNDING: Bill & Melinda Gates Foundation, UK Department for International Development, Wellcome Trust, Swiss Development Cooperation, UNICEF, and US National Institutes of Health.The SHINE trial is funded by the Bill & Melinda Gates Foundation (OPP1021542 and OPP113707); UK Department for International Development; Wellcome Trust, UK (093768/Z/10/Z, 108065/Z/15/Z and 203905/Z/16/Z); Swiss Agency for Development and Cooperation; US National Institutes of Health (2R01HD060338-06); and UNICEF (PCA-2017-0002)

An analysis of recent stroke cases in South Africa: Trend, seasonality and predictors

Abstract: Background. South Africa (SA) is experiencing an epidemiological transition as a result of sociodemographic and lifestyle changes. This process is leading to an increase in non-communicable diseases, which in turn may result in an upswing of stroke cases. Stroke is among the top 10 leading causes of disability in SA, and accounts for ~25 000 deaths annually and 95 000 years lived with disability (YLD). This huge burden of stroke hampers socioeconomic development as a result of YLD. Objectives. To investigate the seasonality and trend of stroke cases in SA, and determine the risk factors associated with stroke. Methods. Using recent hospital-based data (January 2014 - December 2017 inclusive) from SA private and public hospitals (33% private and 67% public), a sample of 14 645 suspected stroke cases was drawn. Associations between suspected stroke cases and potential predictors were assessed using χ2 tests and bivariate analysis. Time series analysis tools for trend and seasonality components included both time domain and frequency domain techniques. A Poisson generalised linear model was used, as there was no over-dispersion inherent in the data. Multiple logistic regression analysis was used to assess the effect of several predictors on stroke cases. Results. Of the 14 645 suspected cases of stroke, 51.5% were confirmed. Seasonality analysis gave an approximate seasonal change of 120 cases, the highest seasonal peak occurring in mid-winter and the lowest dip in mid-summer. Both upward trend and seasonality parameters were found to be statistically significant. Predictors significantly associated with an increased likelihood of stroke were heart problems (odds ratio (OR) 8.86; 95% confidence interval (CI) 8.23 - 9.55; p<0.0001), diabetes (OR 14.53; 95% CI 13.36 - 15.79; p<0.0001), female sex (OR 18.23; 95% CI 16.75 - 19.85; p<0.0001), age 59 - 77 years (OR 1.37; 95% CI 1.24 - 1.50; p<0.0001) and 78 - 98 years (OR 1.25; 95% CI 1.16 - 1.35; p<0.0001) and white ethnic group (OR 2.00; 95% CI 1.86 - 2.15; p<0.0001), compared with the respective reference groups. The prevalence ratios of stroke cases as measured by Poisson regression were in agreement with logistic regression results. Conclusions. The increasing trend of stroke in SA should be arrested urgently, taking into account both the associated risk factors and seasonality

Geotechnical investigation of soil properties in Hatsalatladi village, Botswana; Insights from aeromagnetic, laboratory soil tests and Rayleigh wave dispersion datasets

Soil tests and Multichannel Analysis of Surface Waves (MASW) data were conducted in Hatsalatladi village, Botswana, to investigate the occurrence of ground fissures within the village and to identify the likely causes of the fissures and their depth extent. The MASW data were collected to gain insights into the variation of shear wave velocity with depth. The dataset shows that the shear wave velocity ranged from 150 m/s – 500 m/s, with Poisson's ratios ranging from 0.02 to 0.25. A low-velocity zone (LVZ) was observed in the upper 5 m of the subsurface with velocities ranging from 200 m/s to 350 m/s.The soil plasticity was measured through the plastic and liquid Atterberg tests. Atterberg limits measurements obtained from the three survey sites show that the plastic index of the soil samples collected from depths of 1 m fall within the 10–20% range. Specifically, the Filled Crack survey site had a plastic index of 16%, while the Abandoned House and Bridge sites had 18.7% and 13.5%, respectively. Soil samples from Filled Crack and Abandoned House site revealed a linear shrinkage of 6.4%, while the Bridge site soil sample had a linear shrinkage of 2.9%. The sieve analysis test results are also presented