Statistical Modelling and Prediction of Rainfall Time Series Data

Climate and rainfall are highly non-linear and complicated phenomena, which require classical, modern and detailed models to obtain accurate prediction. In order to attain precise forecast, a modern method termed fuzzy time series that belongs to the first order and time-variant method was used to analyse rainfall since it has become an attractive alternative to traditional and non-parametric statistical methods. In this paper, we present tools for modelling and predicting the behavioural pattern in rainfall phenomena based on past observations. The paper introduces three fundamentally different approaches for designing a model, the statistical method based on autoregressive integrated moving average (ARIMA), the emerging fuzzy time series(FST) model and the non-parametric method(Theil2019;s regression). In order to evaluate the prediction efficiency, we made use of 31 years of annual rainfall data from year 1982 to 2012 of Ibadan South West, Nigeria. The fuzzy time series model has it universe of discourse divided into 13 intervals and the interval with the largest number of rainfall data is divided into 4 sub-intervals of equal length. Three rules were used to determine if the forecast value under FST is upward 0.752013;point, middle or downward 0.25-point. ARIMA (1, 2, 1) was used to derive the weights and the regression coefficients, while the theil2019;s regression was used to fit a linear model. The performance of the model was evaluated using mean squared forecast error (MAE), root mean square forecast error (RMSE) and Coefficient of determination ( . The study reveals that FTS model can be used as an appropriate forecasting tool to predict the rainfall, since it outperforms the ARIMA and Theil2019;s models

Automatic Recognition of African Bust using Modified Principal Component Analysis (MPCA)

This study identified and analysed the pattern recognition features of African bust. It also developed and evaluated a Modified Principal Component Analysis (MPCA) for recognizing those features. This was with a view to providing information on the developed MPCA for a robust approach to recognition of African bust.The developed MPCA used varying number of eigenvectors in creating the bust space. The characteristics of the bust in terms of facial dimension, types of marks, structure of facial components such as the eye, mouth, chin etc were analysed for identification. The bust images were resized for proper reshaping and cropped to adjust their backgrounds using the Microsoft Office Picture Manager. The system code was developed and run on the Matrix Laboratory software (MatLab7.0).The use of varying values of eigenvectors has proven positive result as far as the system evaluation was concerned. For instance, a sensitivity test carried out revealed that thirteen out of seventeen bust’s images were recognized by selecting only vectors of highest eigenvalues while all the test images were recognized with the inclusion of some vectors of low energy level. That is, the modification made to the Conventional PCA (i.e. Eigenface Algorithm) gave rise an increment of about twenty five percent (25%) as far as recognizing the test images was concerned.The study concluded that the Modification made to the conventional PCA has shown very good performance as far as the parameters involved were concerned. The performance of the MPCA was justified by the identification of all the test images, that is, the MPCA proved more efficient than the Conventional PCA technique especially for the recognition of features of the African busts. Keywords: Eigenvectors, Bust recognition, Modified Principal Component Analysis Technique (MPCA), African Bust

Bootstrap Approach to Correlation Analysis of Two Mineral Components in a Geological Field

In this article we considered pairs bootstrap through a truncated geometric bootstrap method for stationary time series data. Construction of valid inferential procedures through the estimates of standard error, coefficient of variation and other measures of statistical precision such as bootstrap confidence interval were considered. The method was used to confirm the correlation between Silicon Oxide (SiO2) and Aluminium Oxide (Al2O3) from a geological data. A typical problem is that can these components exist together or they are mutually exclusive. We attempt to solve these problem through bootstrap approach to correlation analysis and show that pair bootstrap method through truncated geometric bootstrap method for stationary process revealed the correlation coefficient between Silicon oxide (SiO2) and Aluminium oxide (Al2O3) from the same geological field.  The computed measure of statistical precisions such as standard error, coefficient of variation and bootstrap-t confidence interval revealed the correlation analysis of the bivariate stochastic processes of SiO2 and Al2O3 components from the same geological field. The correlation analysis of the bivariate stochastic process of SiO2 and Al2O3 components through bootstrap method discussed in this paper revealed that the correlation coefficient are negative and bootstrap confidence intervals are negatively skewed for all bootstrap replicates. This implies that as one component increases, the other component decreases, which mean that the two components are mutually exclusive and the abundance of one mineral prevents the other in the same oil reservoir of the same geological field. Key words: Pair bootstrap, standard error, coefficient of variation, bootstrap-t confidence interval and correlation analysis

Floristic Structure of Some Selected Plots in Olokemeji Forest Reserve, Ogun State, Nigeria

Deforestation disrupts forest structure and function with negative impacts on biodiversity and natural regeneration of the forests. In Nigeria, forests are lost through burning, shifting cultivation and logging of trees. These describe the state of degradation in Olokemeji forest reserve. Hence, a need to evaluate the species composition and floristic structure of the woody species in selected plots of the forest reserve. The forest reserve, situated in the lowland rain forest of south-western Nigeria occupies a total land area of 58.88 km2. Six sample plots of 50 m2 each were randomly selected and designated as Frequently Burnt Plot 1, Frequently burnt Plot 2, Harvested Plot, Unharvested unburnt Plot, Arable Plot 1 and Arable Plot 2. One hundred and eighty two stands were enumerated, with Unharvested unburnt plot having the highest number of trees at 50. The highest percentage cover was recorded at frequently burnt plot 1, Frequently burnt plot 2 and Unharvested unburnt plot which ranged from 21-50%. Trees in Unharvested Unburnt Plot had the highest mean diameters at breast height (78.46cm) and mean heights (14.44 m), while the Arable Plots had lowest mean diameters at breast height and mean heights. There is a high level of anthropogenic interference at the forest reserve, and the structure and composition of the tree species enumerated in the study plots reflected some of the nature of impact. Indiscriminate logging of trees as fuelwood should be greatly curtailed and improvised by the neighbouring communities

Geospatial modelling of Forest Canopy Density and Landscape Assessment in Omo Biosphere Reserve, South-western Nigeria

Forest has an important role in the global carbon cycle that covers over one-fourth of the world’s geographical area. It is one of the major natural resources and magnificent terrestrial ecosystems of the world. Forest Canopy Density (FCD) is imperative in the assessment of forest status and is a primary indicator of potential management interventions. Landsat images of 1990 and 2018 were used in this study. Remote Sensing has demonstrated to be very cost-effective in mapping and monitoring changes in forests, and other environmental issues. Forest cover change and fragmentation were analysed using FCD and Landscape metrics. The FCD was obtained from the combination of data from the Advance Vegetation Density Index (AVI), Bare Soil Index (BI), and Forest Shadow Index (FSI). Four categories of change were identified in the reserve, no change, growth, degradation and deforestation. There was no change in 222.57 ha (52.98%), growth had 81.54 ha (0.69%), degradation with 116.01 ha (27.61%) and deforestation with the least change with 0.81 ha (0.19%). Degradation with a change rate of 0.97% contributed more in terms of change. There is a slight increase in the values of the three diversity indices (SHDI, SHEI, SIDI) while a high degree of homogeneity is recorded in the no forest class and the three others classes were fragmented. Understanding the dynamics of the forests is important in mitigating climate change and support for biological resources

On Application of Cointegration and Vector Error Correction Model to Macroeconomic Time Series Data

Investment in the stock market is long term in nature. Any development that could affect the stability of the economy usually has serious impact on the stock market performance. This research work examines the impact of some macroeconomic variables (Inflation, Interest and Exchange rates as well as Real Gross Domestic Product) on Nigerian stock market index. The methodologies used are cointegration and vector error correction model using annually data collected from Nigeria stock exchange fact book and Central Bank of Nigeria statistical bulletin (2013). From the results obtained the Augmented Dickey-Fuller (ADF) test reveals that all other macroeconomic indicators were stationary at the first order of difference except for SMI and RGDP that were stationary at the second order of difference, I(2). The Johansen co-integration test shows there are at least three co-integrated variables out of the five economic series considered in this study at 5% level of significance. The vector error correction models obtained generalised that there exists dynamic relationship between all the macro economic variables, but the four macroeconomic   indicators jointly affect and influence the stock market index.The portmanteau test for residual autocorrelation in the VEC show no autocorrelation is left at lag(1) and VEC(1) is the better specification for analysing the interaction between stock market index and macroeconomic variables. In conclusion, government should implement policies that will reduce inflation rate and poverty level through infrastructural development and improved standard of living. Also, interest rates should be made moderate in order to encourage investment and transactions in stocks in the Nigerian Capital Market. The negative exchange rate shows that the Nigeria economy is readily open for international trade. And finally, the RGDP indicates positive impact with the stock market index. Keywords: Market Interaction, VEC, Cointegration and Macroeconomic variables

Tree Species Diversity and Distribution in the Natural Forest of Onigambari Forest Reserve, Oyo State, Nigeria

Anthropogenic activities has caused depletion of majority of Nigeria forest reserves, reducing forest lands to agricultural lands and grasslands. These prompted this study to consider the diversity of species as well as their species composition in the forest in February 2021. Four sub-plots were established in a cluster with an area of 50m by 50m, with 20m distance between each plots and 10m as edge effect. Twenty five tree species belonging to fifteen families were found in the study site. Family Malvaceae was the most represented. Triplochiton scleroxylon recorded the highest relative importance value (11.23). The diversity indices across the study plots assessed were species richness, evenness, Shannon index and dominance. Dominance indices across the study plots were low, asides for Plot 4 where. Triplochiton scleroxylon was dominant. Simpson index was highest in Plot 1 and lowest at Plot 4. Shannon index was highest, though in moderation in Plot 1 and relatively low in the remaining plots. Evenness indices across the four plots were high. However, the summarized diversity indices for the study site reflected dominance was generally low, Simpson index was high, Shannon index was moderate and Evenness index was moderate. The dendrogram depicted the relationship among  the tree species population based on similarities and dissimilarities. Triplochiton scleroxylon belonged to a cluster while every other species with close similarity were categorized under cluster 2

Efficacy and Safety of Three Antiretroviral Regimens for Initial Treatment of HIV-1: A Randomized Clinical Trial in Diverse Multinational Settings

Background:Antiretroviral regimens with simplified dosing and better safety are needed to maximize the efficiency of antiretroviral delivery in resource-limited settings. We investigated the efficacy and safety of antiretroviral regimens with once-daily compared to twice-daily dosing in diverse areas of the world.Methods and Findings:1,571 HIV-1-infected persons (47% women) from nine countries in four continents were assigned with equal probability to open-label antiretroviral therapy with efavirenz plus lamivudine-zidovudine (EFV+3TC-ZDV), atazanavir plus didanosine-EC plus emtricitabine (ATV+DDI+FTC), or efavirenz plus emtricitabine-tenofovir-disoproxil fumarate (DF) (EFV+FTC-TDF). ATV+DDI+FTC and EFV+FTC-TDF were hypothesized to be non-inferior to EFV+3TC-ZDV if the upper one-sided 95% confidence bound for the hazard ratio (HR) was ≤1.35 when 30% of participants had treatment failure.An independent monitoring board recommended stopping study follow-up prior to accumulation of 472 treatment failures. Comparing EFV+FTC-TDF to EFV+3TC-ZDV, during a median 184 wk of follow-up there were 95 treatment failures (18%) among 526 participants versus 98 failures among 519 participants (19%; HR 0.95, 95% CI 0.72-1.27; p = 0.74). Safety endpoints occurred in 243 (46%) participants assigned to EFV+FTC-TDF versus 313 (60%) assigned to EFV+3TC-ZDV (HR 0.64, CI 0.54-0.76; p<0.001) and there was a significant interaction between sex and regimen safety (HR 0.50, CI 0.39-0.64 for women; HR 0.79, CI 0.62-1.00 for men; p = 0.01). Comparing ATV+DDI+FTC to EFV+3TC-ZDV, during a median follow-up of 81 wk there were 108 failures (21%) among 526 participants assigned to ATV+DDI+FTC and 76 (15%) among 519 participants assigned to EFV+3TC-ZDV (HR 1.51, CI 1.12-2.04; p = 0.007).Conclusion: EFV+FTC-TDF had similar high efficacy compared to EFV+3TC-ZDV in this trial population, recruited in diverse multinational settings. Superior safety, especially in HIV-1-infected women, and once-daily dosing of EFV+FTC-TDF are advantageous for use of this regimen for initial treatment of HIV-1 infection in resource-limited countries. ATV+DDI+FTC had inferior efficacy and is not recommended as an initial antiretroviral regimen.Trial Registration:http://www.ClinicalTrials.gov NCT00084136

The evolving SARS-CoV-2 epidemic in Africa: Insights from rapidly expanding genomic surveillance

INTRODUCTION Investment in Africa over the past year with regard to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) sequencing has led to a massive increase in the number of sequences, which, to date, exceeds 100,000 sequences generated to track the pandemic on the continent. These sequences have profoundly affected how public health officials in Africa have navigated the COVID-19 pandemic. RATIONALE We demonstrate how the first 100,000 SARS-CoV-2 sequences from Africa have helped monitor the epidemic on the continent, how genomic surveillance expanded over the course of the pandemic, and how we adapted our sequencing methods to deal with an evolving virus. Finally, we also examine how viral lineages have spread across the continent in a phylogeographic framework to gain insights into the underlying temporal and spatial transmission dynamics for several variants of concern (VOCs). RESULTS Our results indicate that the number of countries in Africa that can sequence the virus within their own borders is growing and that this is coupled with a shorter turnaround time from the time of sampling to sequence submission. Ongoing evolution necessitated the continual updating of primer sets, and, as a result, eight primer sets were designed in tandem with viral evolution and used to ensure effective sequencing of the virus. The pandemic unfolded through multiple waves of infection that were each driven by distinct genetic lineages, with B.1-like ancestral strains associated with the first pandemic wave of infections in 2020. Successive waves on the continent were fueled by different VOCs, with Alpha and Beta cocirculating in distinct spatial patterns during the second wave and Delta and Omicron affecting the whole continent during the third and fourth waves, respectively. Phylogeographic reconstruction points toward distinct differences in viral importation and exportation patterns associated with the Alpha, Beta, Delta, and Omicron variants and subvariants, when considering both Africa versus the rest of the world and viral dissemination within the continent. Our epidemiological and phylogenetic inferences therefore underscore the heterogeneous nature of the pandemic on the continent and highlight key insights and challenges, for instance, recognizing the limitations of low testing proportions. We also highlight the early warning capacity that genomic surveillance in Africa has had for the rest of the world with the detection of new lineages and variants, the most recent being the characterization of various Omicron subvariants. CONCLUSION Sustained investment for diagnostics and genomic surveillance in Africa is needed as the virus continues to evolve. This is important not only to help combat SARS-CoV-2 on the continent but also because it can be used as a platform to help address the many emerging and reemerging infectious disease threats in Africa. In particular, capacity building for local sequencing within countries or within the continent should be prioritized because this is generally associated with shorter turnaround times, providing the most benefit to local public health authorities tasked with pandemic response and mitigation and allowing for the fastest reaction to localized outbreaks. These investments are crucial for pandemic preparedness and response and will serve the health of the continent well into the 21st century