Modelling and Analysis of Powerline Temperature Surveillance with Optisystem Simulation

A periodic variation of the index of refraction of a fiber optics is known as the Fiber Bragg Grating. It works on the principle of wavelength shifts in response to the modulation of the light source as a result of change in temperature above the reference point. This paper presents the design and analysis of Fiber Bragg Grating Sensor to measure and monitor the temperature change in powerlines for a particular range of temperature. Simulation was carried out on Optisystem to determine the peak reflectivity of the Bragg wavelength. It is seen that a change in the reflected spectrum of light is proportional to the change in temperature as shown in the FBG interrogator

THE IMPACT OF DIGITAL FINANCIAL SERVICES ON THE NIGERIAN ECONOMY

This paper investigated the impact of digital financial services on the Nigerian economy, a study of Nigerian deposit money banks (DMBs). An expo-facto data analysis was carried out on independent variables of digital financial services: volume of ATM transactions (VATM), volume of POS transactions (VPOS), volume of WEBPAY transactions (VWBP) and volume of mobile banking (VMOB) regressed on Gross Domestic Product (GDP) as a dependent variable. These were obtained from the 2017 Central Bank of Nigeria (CBN) Statistical Bulletin using the ordinary least square regression (OLS). Findings from the study revealed that the volume of mobile banking, point of sales, and volume of automatic teller machines transactions have positive impact on the economy of Nigeria with the volume of automatic teller machines having the highest impact on the gross domestic product of Nigeria as a proxy of economic growth while the volume of web services has a negative impact on the Nigerian gross domestic product. The study therefore recommends improvement on the operationalization of the independent variables: (ATM, POS, WEB PAY and MOB) by the monetary authorities, Fintech (financial technology), and the DMBs (Deposit money banks) to enhance the dependent variable of gross domestic product in Nigeria as a global economy while putting more effort on the security, safety, and literacy of these innovations to eliminate or reduce the negative impact of the web services innovation on the Nigerian economy

Learning analytics: Dataset for empirical evaluation of entry requirements into engineering undergraduate programs in a Nigerian university

In Nigerian universities, enrolment into any engineering undergraduate program requires that the minimum entry criteria established by the National Universities Commission(NUC)must be satisfied. Candidates seeking admission to study engineering discipline must have reached a predetermined entry age and met the cut-off marks set for Senior School Certificate Examination (SSCE), Unified Tertiary Matriculation Examination(UTME),and the post-UTME screening.However, limited effort has been made to show that these entry requirements eventually guarantee successful academic performance in engineering programs because the data required for such validation are not readily available.In this data article, a comprehensive data set for empirical evaluation of entry requirements into engineering undergraduate programs in a Nigerian university is presented and carefully analyzed. A total sample of 1445 undergraduates that were admitted between 2005 and 2009 to study Chemical Engineering(CHE), Civil Engineering (CVE), Computer Engineering(CEN), Electrical and Electronics Engineering (EEE),Information and Communication Engineering (ICE), Mechanical Engineering(MEE),and Petroleum Engineering (PET) at Covenant University,Nigeria were randomly selected. Entry age,SSCE aggregate, UTME score, Covenant University Scholastic Aptitude Screening(CUSAS)score, and the Cumulative Grade Point Average(CGPA) of the undergraduates were obtained from the Student Records and Academic Affairs unit. In order to facilitate evidence-based evaluation, the robust dataset is made publicly available in a Microsoft Excel spreadsheet file. On yearly basis, first-order descriptive statistics of the data set a represented in tables. Box plot representations, frequency distribution plots, and scatter plots of the dataset are provided to enrich its value. Furthermore, correlation and linear regression analyses are performed to understand the relationship between the entry requirements and the corresponding academic performance in engineering programs. The data provided in this article will help Nigerian universities, the NUC, engineering regulatory bodies,and relevant stakeholders to objectively evaluate and subsequently improve the quality of engineering education in the country

Towards building smart energy systems in sub-Saharan Africa: A conceptual analytics of electric power consumption

A fast emerging source of knowledge acquisition through inference from available data is analytics. The convergence of maturity, ubiquity and ease of deployment of Internet of Things (IoT) enabling technologies has engendered this possibility. The need to leverage on available data from credible sources to develop sustainable systems within the smart and connected communities (SCC) paradigm cannot be overemphasized. In this paper, the architecture of an IoT-enabled smart micro-grid system is proposed to harness the potentials of emerging independent power projects in sub-Saharan Africa. As a case study, this paper examines the interrelation between the economy and electric power consumption in Nigeria, Africa's energy giant and most populous nation, from 1981 to 2014 using the off-the-shelf IBM Watson analytics software. The predictive analytics tool provided an in-depth analysis of the determinants of energy-driven economic growth, as a basis for developing a sustainable smart energy system in Nigeria. Insights gained from this predictive analytics afford private investors, policy makers, consumers and other stakeholders an opportunity to work together to meet the increasing demand for energy production in sub-Saharan Africa

Occurrence of Surgical Site Infections at a Tertiary Healthcare Facility in Abuja, Nigeria: A Prospective Observational Study

Surgical site infection (SSI) is one of the most frequent complications of surgical interventions. Several factors have been identified as major determinants of occurrence of SSIs. The present study determined the occurrence and possible risk factors associated with SSIs at a tertiary healthcare facility in Abuja, Nigeria. All patients scheduled for operation in the hospital during the study period and who consented to participate willingly in the study were observed prospectively for the occurrence of SSI based on criteria stipulated by the United States Centre for Disease Control and Prevention (CDC). Data on sociodemographic characteristics, lifestyle, surgical procedure and co-morbidity were collected into a pre-tested data collection tool and analysed using IBM SPSS Statistics software v.24. Predictors of SSIs were identified using multivariate logistic regression model and p-value less than 0.05 was considered statistically significant. Of the 127 surgical patients that met the inclusion criteria comprising 65 (51.2%) females and 62 (48.8%) males between 1 and 83 years with mean age of 25.64 ± 1.66 years, 35 (27.56%; 95% Confidence Interval (CI): 0.205–0.360) developed SSIs. Prolonged post-operative hospital stays (p < 0.05), class of wound (p < 0.0001) and some comorbid conditions were found to be significantly associated with higher SSI rate. The SSI rate was highest among patients that had Kirschner-wire insertion (75.0%), followed by an unexpectedly high infection rate among patients that had mastectomy (42.9%), while lower percentages (33.3%) were recorded among patients that had exploratory laparotomy and appendicectomy. The overall magnitude of SSIs in this facility is high (27.6%; 95% CI: 0.205–0.360). Several factors were found to be independent predictors of occurrence of SSI. The findings thus highlight the need for improved surveillance of SSIs and review of infection control policies of the hospital

Genomic features of an isolate of Empedobacter falsenii harbouring a novel variant of metallo-β-lactamase, blaEBR-4 gene

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First whole genome sequence of Paenalcaligenes suwonensis bearing bla(VIM-5) Metallo-beta-lactamase: A clinical isolate responsible for acute gastroenteritis

Carbapenemase-producing Alcaligenes species has been described in only few studies, with none so far from the African continent. Here, we report the whole genome sequence of Peanalcaligenes suwonensis bearing bla(VIM-5) metallo-beta-lactamase and first detection of carbapenemase producing Alcaligenes faecalis isolated from patients attending tertiary healthcare facilities in Nigeria. The isolates were identified by MALDI-TOF Mass Spectrometry. Antibiotic susceptibility assay, modified Carba NP test and genomic investigation revealed that two isolates of Alcaligenes faecalis and an isolate of Paenalcaligenes suwonensis harboured bla(VIM-5) gene. The genome sequence analysis of the P. suwonensis 191B isolate, responsible for acute gastroenteritis, reveal the presence of 18 antibiotic resistance genes coding for resistance to five different classes of antibiotics. Three of the genes (bla(OXA-368), bla(CARB-4) and bla(VIM-5)) codes for resistance to beta-lactam antibiotics. To our best knowledge, we describe here the first genome sequence of P. suwonensis species and the first detection of class B carbapenemase bla(VIM-5) in a clinical isolate of P. suwonensis species and Alcaligenes faecalis in Nigeria. The finding of this study is of concern, as lateral dissemination of the genes into clinically important Gram-negative pathogens is highly likely

Correction to: Bhargavaea massiliensis sp. nov. and Dietzia massiliensis sp. nov., Novel Bacteria Species Isolated from Human Urine Samples in Nigeria

International audienc

Bhargavaea massiliensis sp. nov. and Dietzia massiliensis sp. nov., Novel Bacteria Species Isolated from Human Urine Samples in Nigeria

International audienc