Faculty of Natural Sciences

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    1-Minute Rain Rate Distribution for Communication Link Design Based on Ground and Satellite Measurements in West Africa
    (Begell House, Inc., 2020) Sanyaolu, Modupe
    West Africa is in the tropical region and it is characterized by intense rainfall. Rain is a significant factor causing signal degradation on microwave links due to its variability; it causes scattering, absorption, and refraction of electromagnetic waves. Experimental studies have shown that rainfall intensities above 64 mm/h at 0.01% in this region results in noticeable digital television signal fading, squelching and complete outages. Hence the need for estimating rain rate distribution across West Africa. This paper analyzed the rain rate from six countries in West Africa, namely Benin, Cameroon, Cote d'Ivoire, Ghana, Nigeria, and Togo. Three locations were selected in each country. Rain data were obtained from the Tropical Rain Measuring Mission-Precipitation Radar (TRMM-PR) and the Global Precipitation Measurement (GPM) missions, and Tropospheric Data Acquisition Network (TRODAN) weather stations in Nigeria. This study used ITU-R and Moupfouma models for the conversion of the 5-minute rain rate to 1-minute integration time at a probability of exceedance ranging from 1% to 0.001%. The cumulative rain rate distribution from the measured rain rate is presented alongside the predictions of the models. ITU-R and Moupfouma predicted similar results at 0.1% probability of exceedance. ITU-R overestimates the rain rate above 0.01% probability of exceedance. On the other hand, the Moupfouma models prediction plots at 0.01% overlap for all locations, indicating that there will be a signal loss at 0.01% probability of exceedance across these locations. The result shows that the 5-minute conversion provides satisfactory performance and suitable for estimating the 1-minute rain rate statistics required for propagation planning over West Africa.
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    2-Aryl benzimidazoles: Synthesis, In vitro alpha-amylase inhibitory activity, and molecular docking study
    (Elsevier, 2018-03-06) Akande, Akinsola
    Despite of many diverse biological activities exhibited by benzimidazole scaffold, it is rarely explored for the -amylase inhibitory activity. For that purpose, 2-aryl benzimidazole derivatives 1-45 were synthesized and screened for in vitro -amylase inhibitory activity. Structures of all synthetic compounds were deduced by various spectroscopic techniques. All compounds revealed inhibition potential with IC50 values of 1.48 ± 0.38-2.99 ± 0.14 M, when compared to the standard acarbose (IC50 = 1.46 ± 0.26 M). Limited SAR suggested that the variation in the inhibitory activities of the compounds are the result of different substitutions on aryl ring. In order to rationalize the binding interactions of most active compounds with the active site of -amylase enzyme, in silico study was conducted.
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    A Lotka-Volterra Non-linear Differential Equation Model for Evaluating Tick Parasitism in Canine Populations
    (Mathematical Modelling of Engineering Problems, 2023-08-30) Adesina, Olumide Sunday
    This research employs a modified version of the Lotka-Volterra non-linear first-order ordinary differential equations to model and analyze the parasitic impact of ticks on dogs. The analysis reveals that fluctuations in pesticide effects significantly influence tick populations and the size of the canine host. The study also uncovers that alterations in the size of the interacting species can lead to both stable and unstable states. Interestingly, in a pesticide-free environment, a decline in the inter-competition coefficient catalyzes an increase in the sizes of both interacting species. This increase, although marginal for the tick population, contributes to overall system stability. The findings underscore the utility of the Lotka-Volterra non-linear first-order ordinary differential equations in modeling the parasitic effect of ticks on dogs. To protect pets, particularly dogs, from the harmful effects of tick infestation, this study recommends the appropriate and regular application of disinfectants.
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    A modified generalized class of exponential ratio type estimators in ranked set sampling
    (Scientific African, 2023-03-22) Adesina, Olumide Sunday
    Background: Researchers consider ranked set sampling (RSS) as an alternative to simple random sampling (SRS) for data collection because studies have shown that it is more efficient and less biased. Also, introducing population parameters to estimators increases the efficiency of such estimators. Aim: This study derived a modified generalized class of exponential ratio estimator in RSS by introducing available population parameters and compared the results with an existing version in SRS. Methodology: The biases and mean square errors (MSE) of the proposed estimators were derived up to the terms of first-order approximation using Taylor’s series expansion. Efficiency was used as the mode of comparison between the proposed and existing estimators. Results: Life data sets and simulated data supported the numerical illustration to corroborate the theoretical results. Conclusion: The MSEs of the modified generalized class of estimators under RSS were found to be smaller than those of the existing generalized class of estimators under SRS; hence they are more efficient estimators.
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    A non-parametric analysis of the effect of Covid-19 pandemic on Nigerians’ well-being based on geopolitical zones
    (JP Journal of Biostatistics, 2024-02-12) Adesina, Olumide Sunday
    The COVID-19 pandemic has crippled the economic activities of so many nations across the globe since its outbreak in 2019. This study is focused on the consequential effect of the COVID-19 pandemic in terms of standard of living, and perception of economic and security situation of Nigerians. A non-parametric approach was adopted on a primary data obtained through the administration of questionnaires online by NoiPolls during the COVID-19 period. The result obtained from this study depicts that there is a significant relationship between the security situation and perception of the country’s economic situation. Kruskal-Wallis test was used to check if there is a significant difference in economic perception, security situation and standard of living where it was observed that there exists a significant difference based on the geopolitical zone. We, therefore, recommend that efforts should be made by the government towards improving the economic state of affairs especially in the southern part of the country as this will in the long run lead to sustainable cities and communities across the geopolitical zones which is one of the goals of SDGs. Moreover, efforts should also be made by the government towards improving the security situation in the north and southeast as improvement in the country’s economic situation has a direct influence on the security position of the country.
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    a-Amylase Inhibition, Anti-glycation Property and Characterization of the Binding Interaction of Citric Acid with a-Amylase Using Multiple Spectroscopic, Kinetics and Molecular Docking Approaches
    (Elsevier, 2022-07-15) Oyetunde, Temidayo
    The quest to suppress complications associated with diabetes mellitus is ever increasing, while food additives and preservatives are currently being considered to play additional roles besides their uses in food enhancement and preservation. In the present study, the protective prowess of a common food preservative (citric acid, CA) against advanced glycation end-products (AGEs) formation and its binding interaction mechanism with a-amylase (AMY), an enzyme linked with hyperglycemia management, were examined. Enzyme inhibition kinetics, intrinsic fluorescence, synchronous and 3D fluorescence spectroscopies, ultraviolet–visible (UV–Vis) absorption spectroscopy, Fourier transform-infrared (FT-IR) spectroscopy, thermodynamics, and molecular docking analyses were employed. Results obtained showed that citric acid decreased a-amylase activity via mixed inhibition (IC50 = 5.01 ± 0.87 mM, Kic = 2.42 mM, Kiu = 160.34 mM) and suppressed AGEs formation (IC50 = 0.795 ± 0.001 mM). The intrinsic fluorescence of free a-amylase was quenched via static mechanism with high bimolecular quenching constant (Kq) and binding constant (Ka) values. Analysis of thermodynamic properties revealed that AMY-CA complex was spontaneously formed (DG < 0), entropy driven (TDS > DH), with involvement of electrostatic forces. UV–Vis, FT-IR and 3D fluorescence spectroscopies affirmed alterations in aamylase native conformation due to CA binding interaction. CA interacted with His-101, Asp-197, His- 299, and Glu-233 within AMY active site. Our findings indicated that CA could impair formation of AGEs and interact with a-amylase to slow down starch hydrolysis; vital properties in management of type 2 diabetes complications.
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    Acoustic Vibrational Resonance in a Rayleigh-Plesset Bubble Oscillator
    (Elsevier, 2020-09-23) Vincent, Uchechukwu
    The phenomenon of vibrational resonance (VR) has been investigated in a Rayleigh-Plesset oscillator for a gas bubble oscillating in an incompressible liquid while driven by a dual-frequency force consisting of high-frequency, amplitude-modulated, weak, acoustic waves. The complex equation of the Rayleigh-Plesset bubble oscillator model was expressed as the dynamics of a classical particle in a potential well of the Liénard type, thus allowing us to use both numerical and analytic approaches to investigate the occurrence of VR. We provide clear evidence that an acoustically-driven bubble oscillates in a time-dependent single or double-well potential whose properties are determined by the density of the liquid and its surface tension. We show both theoretically and numerically that, besides the VR effect facilitated by the variation of the parameters on which the high-frequency depends, amplitude modulation, the properties of the liquid in which the gas bubble oscillates contribute significantly to the occurrence of VR. In addition, we discuss the observation of multiple resonances and their origin for the double-well case, as well as their connection to the low frequency, weak, acoustic force field.
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    Activated Carbon from Nauclea diderrichii Agricultural Waste–a Promising Adsorbent for Ibuprofen, Methylene Blue and CO2
    (Elsevier, 2021-03-15) Omorogie, Martins
    The adsorption potential of activated carbon derived from Nauclea diderrichii biomass (NDAC) was scrupulously harnessed as a low cost and ubiquitous adsorbent for the removal of greenhouse gas (CO2), and organic pollutants such as methylene blue (MB) and ibuprofen (IB) from water. NDAC was fully characterized by scanning electron microscopy (SEM), thermo-gravimetric analysis (TGA), X-ray diffraction (XRD), universal attenuated total reflectance-infra red (UATR-IR), Raman spectroscopy, X-ray photoelectron spectroscopy (XPS), solid state nuclear magnetic resonance (NMR) and nitrogen gas adsorption–desorption by Brunauer-Emmett-Teller (BET) technique. This study showed that NDAC comprises graphitic carbons that had some surface functional groups such as C C, C O, etc, which adsorbed these environmental contaminants. The adsorption equilibrium and kinetic data that the adsorption of these environmental contaminants formed multilayers (homogeneous surfaces) with the surface of NDAC. The adsorption mechanism of CO2, MB and IB onto NDAC occurred by via electrostatic attractions and π-π conjugal interactions. The adsorption capacity of NDAC for CO2 was ca. 3.2 cm3.g−1 at 298 K. The Langmuir maximum adsorption capacity, qmax of NDAC for MB and IB was obtained as 35.09 mg.g−1 and 70.92 mg.g−1 at 328 K respectively.
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    Adaptive Models for Tails of Distributions
    (International Journal of Statistics and Economics, 2019) Adesina, Olumide Sunday
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    Adaptive Regression Model for Highly Skewed Count Data.
    (IAEME, 2019-01-11) Adesina, Olumide Sunday
    A big task often faced by practitioners is in deciding the appropriate model to adopt in fitting count datasets. This paper is aimed at investigating a suitable model for fitting highly skewed count datasets. Among other models, COM-Poisson regression model was proposed in this paper for fitting count data due to its varying normalizing constant. Some statistical models were investigated along with the proposed model; these include Poisson, Negative Binomial, Zero-Inflated, Zero-inflated Poisson and Quasi- Poisson models. A real life dataset relating to visits to Doctor within a given period was equally used to test the behavior of the underlying models. From the findings, it is recommended that COM-Poisson regression model should be adopted in fitting highly skewed count datasets irrespective of the type of dispersion.
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    An Adaptive Thresholding Algorithm-Based Optical Character Recognition System for Information Extraction in Complex Images
    (2021) Odim, Mba
    Extracting texts from images with complex backgrounds is a major challenge today. Many existing Optical Character Recognition (OCR) systems could not handle this problem. As reported in the literature, some existing methods that can handle the problem still encounter major difficulties with extracting texts from images with sharp varying contours, touching word and skewed words from scanned documents and images with such complex backgrounds. There is, therefore, a need for new methods that could easily and efficiently extract texts from these images with complex backgrounds, which is the primary reason for this work. This study collected image data and investigated the processes involved in image processing and the techniques applied for data segmentation. It employed an adaptive thresholding algorithm to the selected images to properly segment text characters from the image’s complex background. It then used Tesseract, a machine learning product, to extract the text from the image file. The images used were coloured images sourced from the internet with different formats like jpg, png, webp and different resolutions. A custom adaptive algorithm was applied to the images to unify their complex backgrounds. This algorithm leveraged on the Gaussian thresholding algorithm. The algorithm differs from the conventional Gaussian algorithm as it dynamically generated the blocksize to apply threshing to the image. This ensured that, unlike conventional image segmentation, images were processed area-wise (in pixels) as specified by the algorithm at each instance. The system was implemented using Python 3.6 programming language. Experimentation involved fifty different images with complex backgrounds. The results showed that the system was able to extract English character-based texts from images with complex backgrounds with 69.7% word-level accuracy and 81.9% character-level accuracy. The proposed method in this study proved to be more efficient as it outperformed the existing methods in terms of the character level percentage accuracy.
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    An Adaptive Thresholding Algorithm-Based Optical Character Recognition System for Information Extraction in Complex Images
    (Journal of Computer Science, 2020-06-12) Ogunde, Adewale Opeoluwa
    Extracting texts from images with complex backgrounds is a major challenge today. Many existing Optical Character Recognition (OCR) systems could not handle this problem. As reported in the literature, some existing methods that can handle the problem still encounter major difficulties with extracting texts from images with sharp varying contours, touching word and skewed words from scanned documents and images with such complex backgrounds. There is, therefore, a need for new methods that could easily and efficiently extract texts from these images with complex backgrounds, which is the primary reason for this work. This study collected image data and investigated the processes involved in image processing and the techniques applied for data segmentation. It employed an adaptive thresholding algorithm to the selected images to properly segment text characters from the image’s complex background. It then used Tesseract, a machine learning product, to extract the text from the image file. The images used were coloured images sourced from the internet with different formats like jpg, png, webp and different resolutions. A custom adaptive algorithm was applied to the images to unify their complex backgrounds. This algorithm leveraged on the Gaussian thresholding algorithm. The algorithm differs from the conventional Gaussian algorithm as it dynamically generated the blocksize to apply threshing to the image. This ensured that, unlike conventional image segmentation, images were processed area-wise (in pixels) as specified by the algorithm at each instance. The system was implemented using Python 3.6 programming language. Experimentation involved fifty different images with complex backgrounds. The results showed that the system was able to extract English character-based texts from images with complex backgrounds with 69.7% word-level accuracy and 81.9% character-level accuracy. The proposed method in this study proved to be more efficient as it outperformed the existing methods in terms of the character level percentage accuracy.
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    An Adaptive Thresholding Algorithm-Based Optical Character Recognition System for Information Extraction in Complex Images
    (Journal of Computer Science, 2020) Oguntunde, Bosede
    Extracting texts from images with complex backgrounds is a major challenge today. Many existing Optical Character Recognition (OCR) systems could not handle this problem. As reported in the literature, some existing methods that can handle the problem still encounter major difficulties with extracting texts from images with sharp varying contours, touching word and skewed words from scanned documents and images with such complex backgrounds. There is, therefore, a need for new methods that could easily and efficiently extract texts from these images with complex backgrounds, which is the primary reason for this work. This study collected image data and investigated the processes involved in image processing and the techniques applied for data segmentation. It employed an adaptive thresholding algorithm to the selected images to properly segment text characters from the image’s complex background. It then used Tesseract, a machine learning product, to extract the text from the image file. The images used were coloured images sourced from the internet with different formats like jpg, png, webp and different resolutions. A custom adaptive algorithm was applied to the images to unify their complex backgrounds. This algorithm leveraged on the Gaussian thresholding algorithm. The algorithm differs from the conventional Gaussian algorithm as it dynamically generated the blocksize to apply threshing to the image. This ensured that, unlike conventional image segmentation, images were processed area-wise (in pixels) as specified by the algorithm at each instance. The system was implemented using Python 3.6 programming language. Experimentation involved fifty different images with complex backgrounds. The results showed that the system was able to extract English character-based texts from images with complex backgrounds with 69.7% word-level accuracy and 81.9% character-level accuracy. The proposed method in this study proved to be more efficient as it outperformed the existing methods in terms of the character level percentage accuracy.
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    Adicardin and Other Coumarins from Breonadia salicina (Vahl) Hepper
    (Tropical Journal of Natural Product Research, 2019) Ajibade, Sunday
    Breonadia salicina is an ethnomedicinal plant used in North Central Nigeria to treat sleeping sickness and respiratory diseases. The stem bark of the plant was extracted with methanol and the extract partitioned between dichloromethane and water. The dichloromethane soluble portion was subjected to column chromatography which resulted in the isolation of 7-(β-D apiofuranosyl (1-6)-β-D-glucopyranosyl) umbelliferone, α-amyrin, stigmasterol, 7-hydroxycoumarin and 6- hydroxy-7-methoxy coumarin. The structures of these compounds were elucidated based on NMR spectral analysis. This is the first report of these compounds from the plant.
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    Adsorption and Desorption Kinetics of Toxic Organic and Inorganic Ions using an Indigenous Biomass: Terminalia ivorensis Seed Waste
    (Springer, 2017-05-15) Omorogie, Martins
    Environmental remediation has been a strategy employed by scientists to combat water pollution problems that have led to the scarcity of potable water. Hence, in this study, Terminalia ivorensis seed waste (TISW) was explored for the removal of Congo Red, Methylene Blue, Cadmium and Lead from aqueous solutions. Some experimental variables such as pH, biosorbent dose, initial solute ion concentration, agitation time and temperature were optimised. The surface microstructures of TISW were studied using proximate analysis, bulk density, specific surface area, pH of Point of Zero Charge, Fourier Transform Infra Red Spectroscopy, Thermogravimetric/Differential Thermal Analysis, Scanning Electron Microscopy and Energy Dispersive Analysis of X-ray. The maximum Langmuir monolayer saturation adsorption capacity, qmaxL, was obtained as 175.44 mg/g for the removal of Methylene Blue by TISW. Also, the qmaxL for CR, Cd(II) ion and Pb(II) ion were 85.47, 12.58 and 52.97 mg/g, respectively. Also, the pseudo-first-order constant, k1, and pseudo-second-order rate constant, k2, are 0.008–0.026/min and 0.012–0.417 mg/g min, respectively. Hence, TISW is recommended as a good adsorbent for the removal of both toxic industrial dyes and toxic metal ions from polluted water.
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    Adsorption Efficacy of Cedrela odorata Seed Waste for Dyes: Non linear Fractal Kinetics and non linear Equilibrium Studies
    (Elsevier, 2016-08-15) Omorogie, Martins
    Alteration of the structural and functional integrity of the aquatic ecosystems due to contamination from toxic industrial dyes warrants cost effective remedial strategies. Cedrela odorata Seed Chaff (COSC) was locally sourced, indigenous and ubiquitous. In support of this proposition, the efficacy of the COSC was assessed for the adsorption of some toxic industrial dyes, namely Methylene Blue (MB), Congo Red (CR), Methyl Violet (MV) and Methyl Orange (MO) from aqueous solutions. The microstructures of Cedrela odorata Seed Chaff (COSC) were carried out using pH of Point of Zero Charge (PZC), Specific Surface Area (SSA), Bulk Density (BD), Fourier Transform Infra Red Spectroscopy (FTIR), X-Ray Diffraction (XRD), Thermogravimetric Analysis (TGA) and Scanning Electron Microscopy (SEM) which indicated that various organic moieties were present in COSC, which the toxic industrial dyes studied were adsorbed onto. Non linear equilibrium and non linear fractal models were used to fit experimental data. The experimental data best fit the Fritz-Schlunder four-parameter isotherm and the fractal-like pseudo-second order (three-parameter) kinetic equation. The Langmuir monolayer adsorption capacities, qmaxL of COSC for the uptake of MB, CR, MV and MO were 88.32–111.88 mg/g, 79.46–128.84 mg/g, 75.11–121.23 mg/g and 57.35–68.23 mg/g respectively as temperature increased from 298 to 318 K. The results support the use of Cedrela odorata Seed Chaff (COSC) as a cost effective material for removal of toxic industrial dye from an aquatic system. Large scale studies are required in the future to prove the efficacy of Cedrela odorata Seed Chaff (COSC) for toxic industrial dyes from varied environmental conditions.
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    Adsorption Kinetics of 4-Nitrophenol onto a Cellulosic Material, Mansonia Wood Sawdust and Multistage Batch Adsorption Process Optimization.
    (Elsevier, 2010-09-18) Unuabonah, Emmanuel
    The kinetics of 4-nitrophenol biosorption from aqueous solution using mansonia wood sawdust, a cellulosic material at different dose is probably a two step mechanism involving the adsorption of a hydrogen ion from solution onto the biosorbent surface followed by electrostatic attraction between the positive surface and the anionic adsorbate. The Wu’s expression for the initial biosorption showed that limitations to intraparticle diffusion were higher for higher biosorbent dose. The switch of the rate-controlling step to intraparticle diffusion was observed in the pattern of the intraparticle diffusion plots as three distinct sections. Multistage optimization studies suggested that 193.8 g of Mansonia wood sawdust, three countercurrent batch adsorption stages and 12 min 48 s are required for the removal of 99.5% of 120 mg dm−3 of 4-nitophenol from aqueous solution. The minimum contact time for removal of 4-nitrophenol in each stage is independent of the percentage removal for each stage.