Search results for: Isiaka S. Adedoyin

Authors: Olanike O. Akinwale, Isiaka S. Adedoyin

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Revenue is a fund realized by the government to meet both current and capital expenditures. The study found out the various ways through which local governments in Nigeria generate revenue or obtain funds and determined whether the people of Boripe local government are paying tax as at when due and also evaluated how the revenue generated is being used by the local government. During the course of this study, research questionnaires were drafted and distributed to respondents in the local government secretariat who supplied the information needed to carry out the research work. Data were collected by using simple random sampling technique where members of the population have been given equal chance of being picked as a member of the sample. Data were analysed using chart table; the chart analyzed the figure of the past two years revenue and expenditure of the local government. It was deduced from the result that revenue generated but this was not up to what one expected for this local government to finance the projected expenditure when the size was considered, its location as well as its natural endowment of this local government. This was due to lack of cooperation of the people and staffs within the local government in the local government jurisdiction as well as fraudulent activities the revenue collectors engaged in. Revenue generation is a fuel for development in any organization whether public or private. The ability of revenue drive of Boripe was not strong enough since the targeted revenue from taxation was not enough to meet the projected expenditure for a particular year as in 2016, the difference was carried forward to the next year.

Keywords: appraisal, expenditure, local government, questionnaire, revenue

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Authors: Hassan Adedoyin Rasaq

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The marketing efforts of the present day business is not just geared towards meeting the consumer’s needs at a price, but ensuring good customer satisfaction, and strategizing on how to retain such customers. Customer satisfaction and retention is achievable through the co-ordination of the marketing mixes; Product, Price, Promotion and Place; Relationship Marketing; After-Sales Service; Rebates/Discounts/Price reduction policy and Total Quality Management (TQM). A first-hand customer, If well satisfied, will become a company’s repeat customer, proceeds to become a client and goes further to become an advocate of the company by applauding the company’s products/services and encouraging others to buy from it. It is the objective of this paper, therefore, to guide business organizations on how to enhance customer satisfaction, and retain existing customers as a means of long-term survival in marketing. The responses of 72 randomly selected Marketing personnel spread across three (3) food and beverage companies in Nigeria were analyzed. One hypothesis was tested using a one-way analysis of variance (ANOVA) statistical tool, and it was discovered that Relationship marketing contributed to organizational profitability and growth.

Keywords: customer satisfaction, retention strategies, marketing, marketing mixes

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Authors: Gona Ayuba, Isiaka Mohammed, Kotom Mohammed Baba, Mohammed Aabubakar Maikasuwa

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The study examined the technical efficiency and its determinants of cattle fattening enterprises in Kebbi state, Nigeria. Data were collected from a sample of 160 fatteners between June 2010 and June 2011 using the multistage random sampling technique. Translog stochastic frontier production function was employed for the analysis. Results of the analysis show that technical efficiency indices varied from 0.74 to 0.98%, with a mean of 0.90%, indicating that there was no wide gap between the efficiency of best technical efficient fatteners and that of the average fattener. The result also showed that fattening experience and herd size influenced the level of technical efficiency at 1% levels. It is recommended that credit agencies should ensure that credit made available to the fatteners is monitored to ensure appropriate utilization.

Keywords: technical efficiency, determinants, cattle, fattening enterprises

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Authors: Festus Adedoyin, Nana Mbeah Otoo, Sofia Meacham

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Hypertension is one of the main health issues in Ghana, where prevalence is higher in rural than in urban areas. This is due to the challenges rural areas have in accessing technology and healthcare services for hypertension control. This study's goal is to create a digital healthcare solution to alleviate this inequality. Through an analysis of current technology and problems, using the ring onion methodology, the study determined the needs for the intervention and evaluated healthcare disparities. An online application with teleconsultation capabilities, reminder mechanisms, and clinical decision support is part of the suggested solution. In outlying areas, mobile clinics in containers with the required equipment will be established. Heuristic evaluation and think-aloud sessions were used to assess the prototype's usability and navigational problems. This study highlights the need to develop digital health interventions to help manage hypertension in rural locations and decrease healthcare disparities. To develop and improve digital healthcare solutions for rural areas worldwide and in Ghana, this study might be used as a tool for future research.

Keywords: digital health, health inequalities, hypertension management, rural areas

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Authors: Isiaka Akinwale, Tolulope Babatunde, Oladepo Sowemimo

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A cross-sectional study was conducted between March and April, 2016 among pre-school and school-aged children in two peri-urban communities in Osun State, Southwest Nigeria. Urine samples were collected from the pre-school and school-aged children, tested for microhaematuria using reagent strips, processed and examined for Schistosoma haematobium ova. Out of 274 pupils examined, 132 (48.2%) had infection, with no statistically significant difference (P > 0.05) in infection between male (48.6%) and female pupils (47.6%). The prevalence of infection increases significantly with age (P < 0.05), with the peak (93.3%) of infection recorded in pupils aged 15 to 16 years and the lowest infection (10.0%) in pupils aged 3 to 4 years. There was no statistically significant association (P > 0.05) between intensity in male pupils (156.0 ± 34.5/10 ml) and female pupils (141.7 ± 29.5/10 ml). The prevalence of pupils with microhaematuria was 65.0% and it increased significantly with age (P < 0.001). The conclusion drawn from the study is that to reduce the transmission of S. haematobium in endemic communities, health education and provision of potable water are advocated.

Keywords: Schistosoma haematobium, microhaeamturia, prevalence, urinary schistosomiasis, school aged children, Nigeria

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Authors: Adedoyin Opeyemi Osokoya

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The study assesses the influence of social media on perceived learning outcome of agricultural science students in tertiary institutions in Oyo state, Nigeria. The four-stage sampling procedure was used to select participants. All students in the seven tertiary institutions that offer agriculture science as a course of study in Oyo State was the population. A university, a college of agriculture and a college of education were sampled, and a department from each was randomly selected. Twenty percent of the students’ population in the respective selected department gave a sample size of 165. Questionnaire was used to collect information on respondents’ personal characteristics and information related to access to social media. Data were analysed using descriptive statistics, chi-square, correlation, and multiple regression at the 0.05 confidence level. Age and household size were 21.13 ± 2.64 years and 6 ± 2.1 persons respectively. All respondents had access to social media, majority (86.1%) owned Android phone, 57.6% and 52.7% use social media for course work and entertainment respectively, while the commonly visited sites were WhatsApp, Facebook, Google, Opera mini. Over half (53.9%) had an unfavourable attitude towards the use of social media for learning; benefits of the use of social media for learning was high (56.4%). Removal of information barrier created by distance (x̄=1.58) was the most derived benefit, while inadequate power supply (x̄=2.36), was the most severe constraints. Age (β=0.23), sex (β=0.37), ownership of Android phone (β=-1.29), attitude (β=0.37), constraints (β =-0.26) and use of social media (β=0.23) were significant predictors of influence on perceived learning outcomes.

Keywords: use of social media, agricultural science students, undergraduates of tertiary institutions, Oyo State of Nigeria

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Authors: Adedoyin Akintunde Adedayo, Onilude Abiodun Anthony

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The continuous usage of synthetic antibiotics in livestock production has led to the resistance of microbial pathogens. This has prompted research to find alternative sources. This study aims to compare the growth and intestinal health of broilers fed scent leaf meal (SLM) as an alternative to synthetic antibiotics. The study used a completely randomized design (CRD) with 300 one-week-old Arbor Acres broiler chicks. The chicks were divided into six treatments with five replicates of ten birds each. The feeding trial lasted 49 days, including a one-week acclimatization period. Commercial broiler diets were used. The diets included a negative control (no leaf meal or antibiotics), a positive control (0.10% oxy-tetracycline), and four diets with different levels of SLM (0.5%, 1.0%, 1.5%, and 2.0%). The supplementation of both oxy-tetracycline and SLM improved feed intake during the finisher phase. Birds fed SLM at a 1% inclusion level showed significantly (P<0.05) improved average body weight gain (ABWG), lowered feed-to-gain ratio, and cost per kilogram of weight gain compared to other diets. The mortality (2.0%) rate was significantly higher in the negative control group. White blood cell levels varied significantly (P<0.05) in birds fed SLM-supplemented diets, and the use of 2% SLM led to an increase in liver weight. However, welfare indices were not compromised.

Keywords: Arbor Acres, phyto-biotic, synthetic antibiotic, white blood cell, liver weight

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Authors: Foluke E. Sola-Ojo, Ibraheem A. Abubakar, Semiu F. Bello, Isiaka H. Fatima, Sule Bisola, Adesina M. Olusegun, Adeniyi C. Adeola

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The domesticated pigeon, Columba livia domestica, has many valuable characteristics, including high nutritional value and fast growth rate. There is a lack of information on its genetic diversity in Nigeria; thus, the genetic variability in mitochondrial cytochrome oxidase subunit I (COI) sequences of 150 domestic pigeons from four different locations was examined. Three haplotypes (HT) were identified in Nigerian populations; the most common haplotype, HT1, was shared with wild and domestic pigeons from Europe, America, and Asia, while HT2 and HT3 were unique to Nigeria. The overall haplotype diversity was 0.052± 0.025, and nucleotide diversity was 0.026± 0.068 across the four investigated populations. The phylogenetic tree showed significant clustering and genetic relationship of Nigerian domestic pigeons with other global pigeons. The median-joining network showed a star-like pattern suggesting population expansion. AMOVA results indicated that genetic variations in Nigerian pigeons mainly occurred within populations (99.93%), while the Neutrality tests results suggested that the Nigerian domestic pigeons’ population experienced recent expansion. This study showed a low genetic diversity and population differentiation among Nigerian domestic pigeons consistent with a relatively conservative COI sequence with few polymorphic sites. Furthermore, the COI gene could serve as a candidate molecular marker to investigate the genetic diversity and origin of pigeon species. The current data is insufficient for further conclusions; therefore, more research evidence from multiple molecular markers is required.

Keywords: Nigeria pigeon, COI, genetic diversity, genetic variation, conservation

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Authors: Timothy Kayode Samson, Adedoyin Isola Lawal

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The past five years have shown a sharp increase in public interest in the crypto market, with its market capitalization growing from $100 billion in June 2017 to $2158.42 billion on April 5, 2022. Despite the outrageous nature of the volatility of cryptocurrencies, the use of skewed error innovation distributions in modelling the volatility behaviour of these digital currencies has not been given much research attention. Hence, this study models the volatility of 5 largest cryptocurrencies by market capitalization (Bitcoin, Ethereum, Tether, Binance coin, and USD Coin) using four variants of GARCH models (GJR-GARCH, sGARCH, EGARCH, and APARCH) estimated using three skewed error innovation distributions (skewed normal, skewed student- t and skewed generalized error innovation distributions). Daily closing prices of these currencies were obtained from Yahoo Finance website. Finding reveals that the Binance coin reported higher mean returns compared to other digital currencies, while the skewness indicates that the Binance coin, Tether, and USD coin increased more than they decreased in values within the period of study. For both Bitcoin and Ethereum, negative skewness was obtained, meaning that within the period of study, the returns of these currencies decreased more than they increased in value. Returns from these cryptocurrencies were found to be stationary but not normality distributed with evidence of the ARCH effect. The skewness parameters in all best forecasting models were all significant (p<.05), justifying of use of skewed error innovation distributions with a fatter tail than normal, Student-t, and generalized error innovation distributions. For Binance coin, EGARCH-sstd outperformed other volatility models, while for Bitcoin, Ethereum, Tether, and USD coin, the best forecasting models were EGARCH-sstd, APARCH-sstd, EGARCH-sged, and GJR-GARCH-sstd, respectively. This suggests the superiority of skewed Student t- distribution and skewed generalized error distribution over the skewed normal distribution.

Keywords: skewed generalized error distribution, skewed normal distribution, skewed student t- distribution, APARCH, EGARCH, sGARCH, GJR-GARCH

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Authors: Isiaka Oladele Oladipo, Olusegun Adewale Ajayi

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The blood pressure fitness of female college students has been implicated in sedentary lifestyles. This study was designed to determine the effects of the Aerobic Dance Circuit Training Programme (ADCT) on blood pressure variables (Diastolic Blood Pressure (DBP) and Systolic Blood Pressure (SBP). Participants’ Pretest-Posttest control group quasi-experimental design using a 2x2x4 factorial matrix was adopted, while one (1) research question and two (2) research hypotheses were formulated. Seventy (70) untrained obese students-volunteers age 21.10±2.46 years were purposively selected from Oyo town, Nigeria; Emmanuel Alayande College of Education (experimental group and Federal College of Education (special) control group. The participants’ BMI, weight (kg), height (m), systolic bp(mmHg), and diastolic bp (mmHg) were measured before and completion of ADCT. Data collected were analysed using a pie chart, graph, percentage, mean, frequency, and standard deviation, while a t-test was used to analyse the stated hypotheses set at the critical level of 0.05. There were significant mean differences in baseline and post-treatment values of blood pressure variables in terms of SBP among the experimental group 136.49mmHg and 131.66mmHg; control group 130.82mmHg and 130.56mmHg (crit-t=2.00, cal.t=3.02, df=69, p<.0, the hypothesis was rejected; while DBP experimental group 88.65mmHg and 82.21mmHg; control group 69.91mmHg and 72.66mmHg (crit-t=2.00, cal.t=1.437, df=69, p>.05) in which the hypothesis was accepted). It was revealed from the findings that participants’ SBP decrease from week 4 to week 12 of ADCT indicated an effective reduction in blood pressure variables of obese female students. Therefore, the study confirmed that the use of ADCT is safe and effective in the management of blood pressure for the healthy benefit of obesity.

Keywords: aerobic dance circuit training, fitness lifestyles, obese college female students, systolic blood pressure, diastolic blood pressure

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Authors: Amarachukwu B. Isiaka, Vivian N. Anakwenze, Chinyere C. Ezemba, Chiamaka R. Ilodinso, Chikodili G. Anaukwu, Chukwuebuka M. Ezeokoli, Ugonna H. Uzoka

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Infectious diseases continue to pose significant threats to global public health, necessitating advanced and timely detection methods for effective outbreak management. This study explores the integration of artificial intelligence (AI) in the early detection and management of infectious disease outbreaks. Leveraging vast datasets from diverse sources, including electronic health records, social media, and environmental monitoring, AI-driven algorithms are employed to analyze patterns and anomalies indicative of potential outbreaks. Machine learning models, trained on historical data and continuously updated with real-time information, contribute to the identification of emerging threats. The implementation of AI extends beyond detection, encompassing predictive analytics for disease spread and severity assessment. Furthermore, the paper discusses the role of AI in predictive modeling, enabling public health officials to anticipate the spread of infectious diseases and allocate resources proactively. Machine learning algorithms can analyze historical data, climatic conditions, and human mobility patterns to predict potential hotspots and optimize intervention strategies. The study evaluates the current landscape of AI applications in infectious disease surveillance and proposes a comprehensive framework for their integration into existing public health infrastructures. The implementation of an AI-driven early detection system requires collaboration between public health agencies, healthcare providers, and technology experts. Ethical considerations, privacy protection, and data security are paramount in developing a framework that balances the benefits of AI with the protection of individual rights. The synergistic collaboration between AI technologies and traditional epidemiological methods is emphasized, highlighting the potential to enhance a nation's ability to detect, respond to, and manage infectious disease outbreaks in a proactive and data-driven manner. The findings of this research underscore the transformative impact of harnessing AI for early detection and management, offering a promising avenue for strengthening the resilience of public health systems in the face of evolving infectious disease challenges. This paper advocates for the integration of artificial intelligence into the existing public health infrastructure for early detection and management of infectious disease outbreaks. The proposed AI-driven system has the potential to revolutionize the way we approach infectious disease surveillance, providing a more proactive and effective response to safeguard public health.

Keywords: artificial intelligence, early detection, disease surveillance, infectious diseases, outbreak management

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