Drivers and Barriers to eLearning Adoption by Academic Staff in Bayero University, Kano, Nigeria

eLearning is the utilization of electronic technology and media for teaching and learning. This type of pedagogy has become a main stay in higher institutions in developed countries. Despite its advantages over traditional methods of teaching as found in the literature, only few have made it requirement for teaching or have adopted it their pedagogy. As such, this paper seeks to uncover the drivers and barriers to eLearning adoption by academic staff in Bayero University, Kano one of the Second generation universities in Nigeria. A descriptive cross-sectional approach was adopted for this study which involved 187 respondents (179 retrieved). Data was descriptively analyzed using SPSS version 27. Majority of the respondents reported to have a Master degree as their highest level of qualification. Also, more than half of the respondents(58.1%) strongly disagreed that the management is aware of the benefits of eLearning while more than one third of the respondents stated that they intend to use eLearning if given the opportunity. Furthermore, nearly half of the respondents strongly disagreed that eLearning increases workload, and more than half of the respondents representing (59.8%) strongly agreed that eLearning eases work and more than one third of the respondents (45.3%) believed that access to ICT is a facilitating factor in adoption of e-leaning among academic staff in Bayero University, Kano. In this regard, the university management need to encourage staff to use eLearning including provision of supportive infrastructure and personnel.&nbsp

DISASTER CONTROL PRACTICES BY LIBRARIANS FOR ENHANCED PRESERVATION OF INFORMATION RESOURCES IN ACADEMIC LIBRARIES IN BAUCHI STATE, NIGERIA

The objective of the study is to determine the types of disaster control practices by librarians in academic libraries in Bauchi state, Nigeria. Descriptive survey research design was adopted for this study. The study covers academic libraries in Bauchi state, Nigeria. Questionnaires were used to elicit data from the respondents. The population of the study comprises 70 librarians in the academic libraries covered in the area of study. The researchers employed the total enumeration sampling technique which involves studying the entire respondents. 70 copies of the questionnaires were distributed to the respondents; 65 copies of the Questionnaire were retrieved representing 93% response rate. The data collected from the respondents were analysed using simple percentage and frequency count. The study revealed that the types of disasters prevalent in academic libraries in Bauchi state, Nigeria are; fire outbreak, wind storm, book mutilation, theft of library materials, negligence of library staff, kidnapping, terrorism, biological agents and leaking roofs. The study also revealed that most libraries under study, indicated that there is no any established disaster control practices. The only available facilities for disaster control are fire extinguishers, smoke alarms, sand filled buckets, CCTV cameras, emergency exit door and fire alarms. The study recommended that university libraries should have a proper surveillance and adequate security personnel in place to reduce theft and book mutilation of library information resources. Academic libraries in Bauchi state, should establish a disaster control plan in their libraries to safeguard any occurrences that may damage library resources and loss of lives and properties

Proximate and Elemental Analysis of African Star Apple ( Chrysophyllum albidum )

The proximate and elemental analysis of African star apple (Chrysophyllum albidum) using standard analytical techniques was investigated. The proximate composition of the plant showed the values of 54.57 % for carbohydrate, 13.25 % of fat, and 3.85 % of crude protein. The crude fiber and ash content indicates the values of 6.60 % and 4.70 % respectively. The moisture content present (17.03 %) reveals the possibility of having low antimicrobial activities of the plant. The mineral elements present in different concentrations are Ca (706.850 mg/kg), Mg (325.500 mg/kg), Fe (40.875 mg/kg), Cu (3.275 mg/kg), and Zn (4.625 mg/kg). The result shows that the fruit have essential minerals required by human for normal life activities

Influence of Building Contractors’ Performance on Construction Process in Nigeria: A Review of Emerging Literature

Building construction is a process that involves the interplay of many actors in the building industry. One of the actors that play a significant role, from inception to completion of a building project, is the building contractor. However, his performance is greatly influenced by some factors. Such factors include labour, building material, construction methods, equipment, site management and the likes. The study attempts to extensively review such factors that affect the building contractor’s performance and productivity during the construction process. The findings of the extensive review of related literature are cross-sectional in nature. It was discovered that such factors varies from location to location and based on the settlement pattern, culture and social cohesion of people. The study concludes that, for a proper measurement of building contractor’s performance to be achieved, all such factors should be incorporated and earnestly observed. Keywords: Building Contractor, Building Performance Indicator, Construction Process, Contractor’s Performance and Performance Measurement

The constitutional roles of local governments in Nigeria: issues and challenges

The paper focuses on the constitutional roles of local governments in Nigeria: issues and challenges.The creation of local governments in Nigeria is meant to support the locals on their budding future in a platform purposely created for representation in the political administration of a State and the Federal Government.The aim of the paper is to discuss the roles of local governments as provided by the 1999 Constitution of the federal Republic of Nigeria, as amended 2011. In addition, to examine the laws of the local governments and further analyses the loopholes in the legal relations between the Local Governments in Nigeria and the States.The methodology adopted by the paper is content analysis approach wherein related literatures were discussed and analysed, particularly the local laws and other relevant documents.The findings of the paper reveal that firm control of local governments by the States especially through the Joint Accounts negates the developmental purposes of local government’s creation in Nigeria. In view of this, therefore, the paper suggests that for the realisation of the ultimate purpose of creation and maintaining the system, the silent constitutional lacuna of local government’s autonomy and other related issues highlighted in the paper should be address

Improvement of Leucaena (<em>Leucaena leucocephala</em>) Benth. Seeds Emergence Using Hot Saline Water Treatment Durations

Leucaena leucocephala is a leguminous shrub that has the potential for increasing animal production with diverse environmental and ecological significance. An experiment was conducted to investigate the effect of hot saline water treatment durations on the emergence of Leucaena seeds. The experiment was arranged in a completely randomized design with six treatments and three replicates. The treatments are control, soaking of seeds in hot saline water (20 g NaCl/1 L of distilled water) at 80°C for 1, 2, 3, 4 and 5-min durations. The percentage emergence, emergence index, plant height and leave numbers were measured. Hot saline water treatment durations had positive effect of breaking Leucaena seed dormancy and enhance germination. The highest percentage emergence and emergence index (53.9% and 7.95) were obtained at 2 min treatment durations but plant height and number of leaves were highest (6.29 cm and 7.00 cm) respectively in 4 min of treatment durations. It could be concluded that percentage emergence and seedling growth of Leucaena can be enhanced using 2 min hot saline water treatment duration. It is recommended that saline soils that have being degraded due to oil spillage to enable production of Leuceana as animal feed and control environmental degradation

COVID-19 Vaccine: Examining Nurses Attitude and Willingness to accept the inoculation in North Western Nigeria

Background: Healthcare providers are the first line of information in pandemics and the last line of support during infections spread.Objective: The study was conducted to examine Nurses Attitude and Willingness to accept COVID-19 vaccine in Northern Nigeria.Methods: Cross-sectional design and systematic sampling technique were used for the study where 300 pretested structured questionnaires were distributed to nurses attending Nursing and Midwifery Council of Nigeria’s Mandatory Continuing Professional Development Programme in Kano, Jigawa, Kaduna and Katsina states of Northwestern Nigeria. 89.3% of the questionnaires were successfully retrieved and analysed using frequency tables and spearman’s correlation coefficient.Result: The result revealed that majority (67.3%) had a positive attitude towards vaccines in general but 89.6% of the respondents were not willing to receive the COVID-19 vaccine. Spearman’s correlation analysis revealed a significant positive correlation between Knowledge of COVID-19 (ρ =0.402, p0.01), having long term medical condition (ρ =0.492, p0.01), highest educational qualification (ρ =0.291, p0.01), female gender (ρ =0.160, p0.01) and willingness to receive COVID-19 vaccine among the respondents. Significant positive correlation was also observed between age (ρ =0.186, p0.01) and refusing a recommended vaccine in the past. Significant negative correlations were observed between refusing a recommended vaccine in the past (ρ =-0.661, p0.05) and willingness to receive COVID-19 vaccine, knowledge of COVID-19 (ρ = - 0.132, p0.01), refusing a recommended vaccine in the past (ρ = - 0.132, p0.01) and years of working experience.Conclusion: It was recommended that awareness campaigns needs to be instituted targeting the eradication of COVID-19 vaccine hesitancy among all healthcare providers

An ensemble CRT, RVFLN, SVM method for estimating Propane Spot Price

In this paper, we propose an ensemble of the CRT-RVFLN-SVM (Classification and Regression Tree (CRT), Random Variable Functional Link Neural Network (RVFLN), and Support Vector Machine (SVM)) to improve robustness and effectiveness in estimating propane spot price. The propane spot price data which are collected from the Energy Information Administration of the US Department of Energy and Barchart were used to build an ensemble CRT-RVFLN-SVM model for the estimating of propane spot price. For the purpose of evaluation, the constituted intelligent computing technologies of the proposed ensemble methodology in addition to Multilayer Back-Propagation Neural Network (MBPNN) were also applied to estimate the propane spot price. Experimental results show that the proposed ensemble CRT-RVFLN-SVM model has improved the performance of CRT, RVFLN, SVM, and MBPNN. The can help to reduce the level of future uncertainty of the propane spot price. Propane investors can use our model as an alternative investment tool for generating more revenue because accurate estimations of future propane price implies generating more profit

Escherichia coli dominance and antimicrobial resistance in urinary tract infections among diabetic patients: Insights from Birnin Kebbi Metropolis, Nigeria

Background: The global rise in antibiotic-resistant urinary tract infections (UTIs) is a growing concern, particularly among diabetic patients. This study examines the antibiotic resistance patterns of bacterial uropathogens in diabetic patients at Sir Yahaya Memorial Hospital in Birnin Kebbi. Methods: A purposive sampling approach was used to collect 51 mid-stream urine samples in sterile containers. Cultural and biochemical methods were employed for the isolation and identification of uropathogenic bacteria. Antibiotic sensitivity testing was performed using the disc diffusion method, with results interpreted according to the Clinical Laboratory Standards Institute (CLSI) guidelines. Results: UTIs were prevalent in 23.5% (12/51) of the samples. Escherichia coli was the most prevalent uropathogen, accounting for 41.3% (7/17) of cases, followed by Klebsiella pneumoniae at 23.5% (4/17). Staphylococcus aureus and Proteus mirabilis each contributed to 17.6% (3/17) of cases. Notably, E. coli and K. pneumoniae exhibited 100% resistance to chloramphenicol and sparfloxacin, respectively. Conclusion: These findings underscore the need for further molecular research to characterize these uropathogens and identify the genes contributing to antibiotic resistance

Biometric information recognition using artificial intelligence algorithms : a performance comparison

Addressing crime detection, cyber security and multi-modal gaze estimation in biometric information recognition is challenging. Thus, trained artificial intelligence (AI) algorithms such as Support vector machine (SVM) and adaptive neuro-fuzzy inference system (ANFIS) have been proposed to recognize distinct and discriminant features of biometric information (intrinsic hand features and demographic cues) with good classification accuracy. Unfortunately, due to nonlinearity in distinct and discriminant features of biometric information, accuracy of SVM and ANFIS is reduced. As a result, optimized AI algorithms ((ANFIS) with subtractive clustering (ANFIS-SC) and SVM with error correction output code (SVM-ECOC)) have shown to be effective for biometric information recognition. In this paper, we compare the performance of the ANFIS-SC and SVM-ECOC algorithms in their effectiveness at learning essential characteristics of intrinsic hand features and demographic cues based on Pearson correlation coefficient (PCC) feature selection. Furthermore, the accuracy of these algorithms are presented, and their recognition performances are evaluated by root mean squared error (RMSE), mean absolute percentage error (MAPE), scatter index (SI), mean absolute deviation (MAD), coefficient of determination (R 2 ), Akaike’s Information Criterion (AICc) and Nash-Sutcliffe model efficiency index (NSE). Evaluation results show that both SVM-ECOC and ANFIS-SC algorithms are suitable for accurately recognizing soft biometric information on basis of intrinsic hand measurements and demographic cues. Moreover, comparison results demonstrated that ANFIS-SC algorithms can provide better recognition accuracy, with RMSE, AICc, MAPE, R 2 and NSE values of ≤ 3.85, 2.39E+02, 0.18%, ≥ 0.99 and ≥ 99, respectively.https://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=6287639Mathematics and Applied Mathematic