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MOLECULAR DYNAMICS OF TUBER AND SEED YIELD IN Sphenostylis stenocarpa (Hochst. ex A. Rich. Harms) (AFRICAN YAM BEAN)
Get PDFSphenostylis stenocarpa (African yam bean - AYB) is an understudied and opportunity crop
with the potential to contribute to food security It is a versatile legume that produces both edible
seeds and tubers. AYB faces under-exploitation due to limited understanding and challenges
as well as an unabetted threat to its diversity like several other indigenous plant species.
Expanding the diversity of global food sources has become imperative. This study investigated
the molecular dynamics in AYB by assessing the genetic diversity in non-tuber and tuberproducing
landraces, identified SNP markers associated with tuber formation and determined
the relationship between seed and tuber production. The study evaluated accessions from the
Genetic Resources Centre of the International Institute of Tropical Agriculture (IITA), Ibadan.
Phenotypic data was generated from monitored growth, genotyping was conducted using
DArTseq technology, with SNP data generated afterward. Phenotypic data employed
clustering, correlation analysis and distribution plots. Genome-wide Association Studies
(GWAS) using the GAPIT package in R elucidated population structure and identified SNPs
responsible for yield. Multiple traits such as NoPods, Hundred sdcount, TSdwghtPPL,
TPodwgth indicate a close association with each other showing a strong indication with the
accessions and yield. While clustering for seed and tubers showed four and five clusters each.
BLUEd traits and 2254 SNP markers from 92 genotypes were used for the association analysis.
Using the BLINK, FarmCPU, GLM, and MLM models. Twelve significant SNP markers were
identified to be associated with three African yam bean yield traits (Tuber weight, Seed
thickness, and Pod width). These results have the potential to accelerate marker-assisted
selection in molecular breeding
Design and Implementation of an IoT Based Greenhouse Monitoring and Controlling System
Get PDFSince the invention of the internet for military and academic research
purposes, it has evolved to meet the demands of the increasing number of
users on the network, who have their scope beyond military and academics.
As the scope of the network expanded maintaining its security became a
matter of increasing importance. With various users and interconnections of
more diversified networks, the internet needs to be maintained as securely as
possible for the transmission of sensitive information to be one hundred per
cent safe; several anomalies may intrude on private networks. Several
research works have been released around network security and this research
seeks to add to the already existing body of knowledge by expounding on
these attacks, proffering efficient measures to detect network intrusions, and
introducing an ensemble classifier: a combination of 3 different machine
learning algorithms. An ensemble classifier is used for detecting remote to
local (R2L) attacks, which showed the lowest level of accuracy when the
network dataset is tested using single machine learning models but the
ensemble classifier gives an overall efficiency of 99.8%
Strategic DG placement and sizing in developing nations' power systems using ISNT and modified forward-backward sweep
Get PDFThe power sector in many developing nations faces challenges in meeting consumers’ demands for a
reliable electricity supply due to increased load demand, primarily driven by population growth.
Urban areas receive 24 h power, while extensive losses within the system limit coverage. Setting up
centralised stations offers a temporary solution, but the capacity of the ageing transmission lines is
uncertain. This study proposes integrating distributed generators (DG) into the power system, using
Inherent Structural Network Topology (ISNT) forDGsiting and a modified Forward-Backward
Sweep model for sizing. Voltage Stability Index (VPI) assesses network stability. The model considers
voltage profile and line losses, optimizingDGsites and sizes. Results demonstrate the model’s efficacy,
offering insights for optimalDGplanning to minimize losses and enhance voltage profiles. The study
informs power system engineers for future planning, aiding decisions onDGlocation and size,
potentially reducing line losses and improving voltage profiles, thus assisting in network upgrades or
expansions
Adept Domestic Energy Load Profile Development Using Computational Intelligence-Based Modelling
Get PDFMost studies undertaken on energy usage in buildings have shown that energy utilization is widely in0uenced by occupancy
presence and occupants’ activities relative to the indoor environment, which may be widely dependent on weather conditions and
user behaviors. However, the core drawback that has negated the pro3cient estimation of energy is the modelling of occupant
behavior relative to energy use. Occupants’ behavior is a complex phenomenon and has a dynamic nature in0uenced by numerous
internal, individual, and circumstantial factors. ,is research proposes a computational intelligence-based model for household
electricity usage pro3le development as impacted by core input variables—household activities, household 3nancial status, and
occupancy presence. ,e incorporation of these variables and their adaptiveness is expected to address and resolve unpredictability
or nonlinearity concerns, thus allowing for adept energy usage estimation. ,e model addresses issues unresolved in
many other studies, such as occupancy determination (deduction) and the impact on energy consumption. ,e performance
precision of this approach has been demonstrated by trend series analysis, demand analysis, and correlation analysis. Based on the
performance indicators including mean absolute percentage error (MAPE), mean square error (MSE), and root mean square error
(RMSE), the model has shown pro3cient predictive output with respect to the metered (actual) energy usage data. ,e proposed
model, compared to actual data, showed that average MAPE values for the respective day standard, morning peak, and night peak
demand period (TOUs) are 2.8%, 1.88%, and 0.31% for all income groups, respectively. ,e aptitude to improve on energy
prediction and evaluation accuracy, especially in these periods, makes it a highly suited tool for demand-side management, power
generation, and distribution planning activity. ,is will translate into power system reliability, reduce operation cost (lowest cost),
and reduce greenhouse emissions (environmental pollution), thereby cumulating into sustainable cities
NATIONAL HEALTH INSTITUTIONS, WORLD HEALTH ORGANISATION AND THE MANAGEMENT OF COVID-19 PANDEMIC IN NIGERIA (2020-2022)
Get PDFThe Coronavirus Disease (COVID-19) pandemic, which originated in Wuhan, China, in December 2019, rapidly became a global pandemic that ravaged the entire world. The effect was devastating despite global attention to the pandemic early enough. With its spread to over 200 countries, nearly 700 million cases, and about 7 million deaths, COVID-19’s global devastation has left long-lasting impacts that will take several years to heal. Hence, this study examines the health governance role of the Nigeria Centre for Disease Control and Prevention (NCDC), the World Health Organisation (WHO), and its frameworks on infectious diseases, focusing on managing the COVID-19 pandemic in Nigeria. The theory of global governance was adopted for this study. The theory posits that global organisations offer solutions to common problems beyond the scope of national governments, and the more general the problems and solutions an international organisation offers, the more influence and power it holds. The research adopted ex post facto and cross-sectional survey research designs. The data reviewed were sourced from PubMed, ScienceDirect, and WHO databases and a series of in-depth interviews conducted in Nigeria. Furthermore, an analysis based on the World Health Organisation’s health system strengthening framework, textual analysis, and social network analysis (SNA) was also conducted to demonstrate actor ties, roles, and collaborations. Findings revealed that there were a lot of actors who got involved in the COVID-19 response with varying degrees of collaboration. The Nigeria Centre for Disease Control and Prevention (NCDC) was pivotal in harnessing these collaborations and partnerships with other health organisations like the West African Health Organisation (WAHO), Africa CDC, and Coalition Against COVID-19 (CACOVID), among others. The research findings highlight the partnership between NCDC, Nigeria Institute of Medical Research (NIMR), private sector actors like CACOVID and global health organisations like Africa CDC and WAHO towards eliminating the health crisis. However, the preparedness for the outbreak was significantly low and inadequate in terms of contact tracing, quarantine facilities, and isolation centres, among others, significantly affecting the outcomes of the curative efforts to a large extent. The research findings highlighted the deployment of disease monitoring and reporting systems, the digitalisation of data gathering and analysis, and the private sector collaboration with the government. The findings expose the challenges of funding, accountability, and resource allocation that were hindrances to success. It also pointed out the regional and global structures that supported Nigeria with vaccines, technical support, information sharing, detection and prevention of newer strains, among others. Therefore, it is recommended that public-private partnerships such as CACOVID be strengthened to build more effective and efficient capacities for early warning and prevention of future outbreaks by increasing support, funding, and technical resources. In conclusion, the task of pandemic preparedness cannot be left to national institutions alone due to competing national needs, and neither can global health bodies cater for all nationalities in times of health crisis; therefore, private sector involvement in pandemic management should be encouraged
Fabrication and investigation of local clay-based insulators for high voltage applications
Get PDFNigeria has a large deposit of clay which is the major raw material for the fabrication of porcelain
insulators for high voltage applications. However, the country depends largely on
imported porcelain insulators to meet its high voltage needs even in the face of the worsening
exchange rate of the Nigerian currency compared to the US dollar and other foreign
currencies. As a result, it becomes necessary to sort for local means of fabricating high voltage
pin insulators from locally available raw materials. In this study, clay sourced from three
different geographical locations (Auchi, Ikorodu, and Ota) are used to fabricate three samples
of high voltage insulators. The fourth sample of insulator is also fabricated from the
Ota clay with Plaster of Paris (POP) as an additive to enhance workability. The physical and
electrical properties of the insulator samples are investigated and compared with imported
porcelain insulators. The results show that the insulator fabricated using the clay from Auchi
has the highest breakdown voltage of 5 kV and lowest leakage current of 2mA and thus
can be adopted for low-tension insulation instead of the high-tension insulation speculated
from the onset of the research
Surface Corrosion Inhibition of Mild Steel in an Acidic Environment by an Anthelmintic Drug: Experimental, RSM, DFT and MD Simulation Studies
Get PDFGravimetric, electrochemical, surface investigation, RSM and theoretical computational studies,
using DFT and MD, were employed to investigate Ecorr inhibition of MS surfaces in 0.5 M H2SO4,
by a worm expelling drug (Wormin® MBZ). The results from computational and RSM
optimization and experimental methodologies were all in good accord. After 24 h, IE(%) of 1.5 g/L
MBZ on MS corrosion, calculated from WL data, was 96.610%. Maximum IE(%) of 1.0 g MBZ
was 96.903% (303 K) and 99.998% (333 K). PDP confirmed MBZ mixed nature of adsorption.
The impact of the inhibitor C and IT of MS on IE(%) of MBZ was revealed by statistical evaluation
and optimization, using Design Expert software package (Stat-Ease). The optimized IE(%) of
96.6103% was obtained with the inhibitor C of 1.061 g/L, at MS 48.58 h IT. On the MS surface,
MBZ behaved according to Langmuir’s adsorption isotherm. MD showed that MBZ had an
Einteraction of -536.33 and -694.53 kcal/mol, at 303 and 333 K, respectively. Negative Einteraction
forecasts confirmed MBZ-MS surface interaction capability, which reinforced the experimental
investigations IE(%) findings
Agricultural Waste Valorization for Nanoparticles Synthesis and Enhancement of Vapour Compression Refrigeration System’s Performance
Get PDFWaste management has been a major concern in the society and agricultural wastes can be utilized
in the synthesis of nanoparticles and deployed in the vapour compression refrigeration system
(VCRS) to enhance its performance. This study analysed the thermophysical properties,
performance, energy consumption, pull-down time, and capacities of VCRS using bio-nanoparticles
produced from orange and pineapple peels. Eco-friendly refrigerants R600a and R134a with pure
polyolester (POE) as the lubricating oil for the compressor were used. The nanolubricants were
dispersed in three volume fractions of 0.05%, 0.10% and 0.20% concentration in the lubricant using
the two-step method. The degradation of nanolubricants were analysed by examining the
thermophysical properties of the nanolubricants before and after use in the VCRS. At 0.2% volume
concentration, optimum COP of 6.31 and 5.01 were obtained for pineapple and orange peels
respectively for R600a. The nanolubricants of orange peels with the volume fraction of 0.2% had the
best pull-down time with a temperature of-2oC. The lowest power consumption was observed for
0.1% volume concentration of pineapple nanolubricants while 0.2% volume concentration of orange
nanolubricants was observed to have the least power consumption. Considering the R134a
refrigerant, the volume concentration with the optimum COP was 0.1 vol% concentration for the
orange bio-based nanolubricants with an increase in the COP of 36.3% when compared with pure
R134a while 0.2 vol% had the best pull-down time with a temperature of-3oC. There was a 14.2%
drop in the power consumption of 0.1 vol% concentration of pineapple nanolubricants when
compared to the various concentrations of the bio-based nanolubricants. From this study, the optimum performance was observed at 0.20 vol% concentration for the orange and pineapple
nanolubricants with a relatively less power consumption. R600a refrigerant can completely replace
R134a in its use in refrigeration systems and achieve similar pull-down time and coefficient of
performance when bio-nanolubricants are utilized in the systems
Conditional monitoring and fault detection of wind turbines based on Kolmogorov–Smirnov non-parametric test
Get PDFThis research presents a new method for conditional monitoring based on the wind turbine power curve. The
Kolmogorov-Smirnov (K-S) distribution test is employed in the assessment of turbine data and the detection of
abnormality (faults) in wind turbines. The process begins with anomaly detection and filtration of faulty SCADA
data by a quantile-based filtration approach. Suitable data comprising wind speed, air density, ambient temperature,
and pitch angle are utilized in the development of wind turbine power curve models that represents
actualities within wind farms. The radial basis function (RBF), multi-layer Perceptron (MLP), and gradient
boosting (GBR) methods utilized for model development are compared for predictive accuracy using Mariano-
Preve test. The null hypothesis assumes equal predictive ability (EPA); if rejected, an algorithm compares the
coefficients of correlation of the models and selects the closest to one (unity). The most accurate model is utilized
for the creation of a bin-wise distribution from past data, and bin-wise confidence levels from the plot of wind
speed and output power. Cochran’s method was utilized to validate the minimum sample size that will possess a
sampling distribution similar to that of the population, and a fault is detected if there is a reasonable difference
between the sample distribution and population distribution. The K-S test, having a null hypothesis of equivalent
distributions, signals a fault if the null hypothesis is rejected. Two wind turbine SCADA datasets associated with
two fault events are used for the assessment of our method. The results indicate that our method effectively
discovers abnormalities in power output relating to increased bearing temperature and reduced generator rpm,
thereby aiding in the detection of faults long before they occur
Data evaluation of the corrosion resistance properties of selected stainless and alloy steels in dilute electrolytes
Get PDFComparison of the corrosion resistance of 304 austenitic stainless steel (304ST), Atlas F20S
ferritic stainless steel (F20ST) and X77CrZn5 alloy steel (X77ST) was studied in 2 M H2SO4 solution at
specific NaCl concentration. Corrosion resistance of 304ST varies with changes in NaCl concentration
whereas the values observed for F20ST and X77ST were non-proportional. The alloys exhibit relative
stability with respect to exposure time after few hours. Lower NaCl concentration results in higher corrosion
rate for 304ST. The final corrosion rate values ranged from -0.029 mm/y at 0% NaCl to 0.261 mm/y at
3.25% NaCl. The values for F20ST andX77ST varied from -0.068 mm/y to 0.394 mm/y, and 2.406 mm/y
to 0.348 mm/y. Without NaCl, 304ST exhibited the highest corrosion resistance at -0.029 mm/y compared
to X77ST which exhibited the highest corrosion rate value of 2.406 mm/y. With NaCl 304ST has the highest
average corrosion rate and X77ST has the lowest. Data from ANOVA analysis showed NaCl concentration
is the dominant factor influencing the corrosion behaviour of the alloys at 99.74%, 99.08% and 97.05%
compared to exposure time. The average corrosion rate values for 304ST varies slightly with respect to NaCl
concentration compared to the values obtained for F20ST and X77ST signifying thermodynamic stability.
The percentage of corrosion rate values for 304ST, F20ST and X77ST below 1 mm/y without and in the
presence of NaCl concentration are 100%, 100% and 0%, and 76%,76% and 100%