International Journal of Science for Global Sustainability
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Strategy for Improving the Effectiveness of Appointment System in Yariman Bakura Specialist Hospital Gusau, Zamfara State
Get PDFAppointment system is a method use for effective clinic preparation in such a way that, every patient is giving a specific date and time in order to see their attending physicians. Appointment system encounter with a number of challenges such as queuing system causing a long waiting time as an inefficiency of healthcare delivery system. The study therefore investigated the Effectiveness of Appointment System (EAS) in Yariman Bakura Specialist Hospital Gusau, Zamfara State. Survey research design was adopted for the study. The population of this study was Health Information Management Personnel. A total enumeration was use for the study. A structured and validated checklist was used for data collection. Data were analyzed using descriptive and inferential statistics at 5% level of significance. Findings showed that effectiveness of the appointment system in Yariman Bakura Specialist are rated positive, but equipment used are to be considered for future improvement of appointment system at the hospital. The study concluded that human efforts and procedural efficiencies are rated positively, but equipment use, remain significantly weak and negative. The study recommends that, there is need for management and government to provide the hospital with adequate materials use for effective appointment system.  
Heat And Mass Transfer Analysis on Magnetohydrodynamics (Mhd) Unsteady Free Convection Flow in the Presence Of Viscous Dissipation in A Vertical Channel
Get PDFThis study investigates the effectiveness of treating biogas with 20% calcium hydroxide solution to improve its
This research numerically investigated the impact of heat and mass transfer analysis in an unsteady free convection flow with viscous dissipation in a vertical channel affected by constant suction/injection factors. The nonlinear partial differential equation regulating flow formation is solved with the implicit finite difference method. Several physical parameters were studied, including skin friction, Nusselt number, thermal Grashof number, solutal Grashof number, magnetic field, and porous parameters, which lead to an increase in fluid velocity. However, in the case of viscous dissipation, the parameter increases the fluid velocity as it increases, and also significantly improves the energy of the temperature profile with its increase. In all the conditions described, thermal management may be accomplished by understanding the influence of each flow parameter and adjusting it accordingly
Availability and Utilization of Information and Communication Technology in Instructional Delivery in Senior Secondary Schools in Zamfara State, Nigeria
Get PDFThis study assessed availability and utilization of information and communication technology (ICT) in instructional delivery in senior secondary schools in Zamfara State, Nigeria. Structured questionnaire was adopted for data collection, a simple random sampling technique was used to select respondents in this study. A descriptive survey was used to analyze the data. The analysis revealed inadequate ICT facilities in secondary schools with a mean score of 2.44 on a scale of 1 to 5. The standard deviation of 1.12 suggests variability in responses, with some schools having slightly better facilities than others. However, the overall picture is insufficiency which hinders the effective use of ICT in education. Teachers in Zamfara State exhibit low levels of ICT knowledge, with a mean score of 2.03. The low standard deviation (0.76) indicates a widespread issue, with little variation among teachers. The study concludes that ICT integration in secondary schools in Zamfara State hindered by inadequate infrastructure, low teachers’ competency, limited utilization of available resources. Teachers perceive minimal benefits from ICT, and significant barriers prevent its effective use in teaching and learning. The implications for educational outcomes in Zamfara Stateas lack of ICT integration limits students' exposure to digital tools and modern educational practices
Comparison of Methods for Estimating Correctly Specified and Misspecified Linear Regression Models
Get PDFIf a probability model of observed data is misspecified, then the interpretation of its Parameter estimates May be invalid, leading to incomplete or incorrect conclusions. The comparison of Weighted Maximum Likelihood (WLE) and Conditional Maximum Likelihood Estimates (CMLE) on their predictive performance when applied to correctly specified and misspecified linear regression was extensively studied. To carry out this analysis, we utilized simulated data that effectively mimicked various scenarios, allowing us to compare the performance of these estimators under small and large sample sizes. Specifically, we focused on the Mean Squared Error (MSE) and Root Mean Squared Error (RMSE) as our primary metrics for evaluating the efficiency of the estimated models, as these statistics provide a clear understanding of the average prediction error associated with each method. The results of our study revealed a significant trend: the WLE consistently outperformed the CMLE across all tested conditions. Notably, it exhibited the least MSE for linear regression models characterized by one dependent and one independent variable, irrespective of whether smaller sample sizes or larger ones were utilized for the comparison. Moreover, when we extended our analysis to multiple linear regression scenarios, the superiority of the WLE remained evident, reinforcing its position as a more efficient estimator than its counterpart. Furthermore, we took a step further by applying both methodologies to real-life data sets. The findings demonstrated that the advantages of the WLE were not constrained to theoretical or simulated environments but also persisted in practical applications, further validating its efficiency and robustness
An Assessment on the Predictive Performance of Arima-Garch and Arimax-Garch Models on Nigerian Inflation Rate
Get PDFAccurate inflation forecasting is critical for effective economic planning and decision-making in Nigeria, yet it remains challenging due to exchange rate fluctuations, oil price shocks, and shifts in monetary policy. Traditional models such as ARIMA often fail to capture these complex dynamics, particularly during periods of high volatility. This study evaluates the predictive performance of two hybrid time series models, ARIMA-GARCH and ARIMAX-GARCH, using monthly inflation data from 1997 to 2024. While ARIMA-GARCH models the conditional mean and volatility of inflation, ARIMAX-GARCH extends this by incorporating exogenous variables, including the exchange rate, premium motor spirit (PMS) price, and money supply. Stationarity was tested using the Augmented Dickey-Fuller (ADF) test, model selection guided by AIC and BIC, and volatility clustering confirmed with the ARCH-LM test. Forecast accuracy was assessed using RMSE, MAE, and MAPE. Results demonstrate that ARIMAX-GARCH consistently outperforms ARIMA-GARCH, yielding more accurate forecasts. The study recommends ARIMAX-GARCH for inflation forecasting in Nigeria, as it provides robust, reliable predictions that support improved policy and investment strategy
Local Stability Analysis of Modeling the Effect of Double Dose Vaccination of Measles Disease Dynamics in Zamfara State and Nigeria
Get PDFMeasles is one of communicable diseases caused by the measles virus. In this research paper, we proposed and established a model for Measles disease dynamics, we incorporated the Treatment rate of both Exposed and Infected individuals, Enlightenment Rate and Effectiveness of Drug usage. We analyzed and shown the dynamics of the model system is in the region and the model equations is considered epidemiologically and mathematically well posed with the invariant region method. The non-negativity solutions was presented and we found that the system is positive and remain in . The equilibrium states were obtained and we present the effective reproduction number of the model system. Analysis of the reproduction number was obtained. The Local stability analysis of the model equation was obtained and we found that the model is locally asymptotically stable if
Valorization of Waste LDPE Using Isoberlina Wood Fillers: Mechanical Properties, Creep Resistance, and Dynamic Viscoelastic Behavior of Sustainable Composites
Get PDFIn an effort to develop eco-conscious technologies for waste reduction, this study explores the potential of Isoberlina wood fibre (IWF) as a reinforcing agent in recycled low-density polyethylene (rLDPE) composites, aiming to enhance mechanical performance while promoting sustainable reuse of plastic waste. Using standardized mechanical testing, dynamic mechanical analysis (DMA), and creep evaluation, the influence of IWF on the composite’s structural and viscoelastic properties was evaluated. At 20 wt% fibre content, the rLDPE composite exhibited significant improvements: tensile strength (11.5 MPa), elastic modulus (167 MPa), flexural strength (70.4 MPa), and Shore hardness (68). DMA results revealed a substantial increase in storage modulus from 330 MPa to 1.2 GPa, indicating enhanced load-bearing capacity. A decline in loss modulus with increasing temperature and frequency suggested reduced energy dissipation and improved stiffness. Creep analysis demonstrated a lower strain rate over time, with the reinforced composite reaching equilibrium at 38.1 minutes, outperforming the unreinforced rLDPE polymer and confirming improved resistance to long-term deformation. These results underscore the effectiveness of Isoberlina fibre in enhancing the mechanical, thermal and creep performance of rLDPE, offering a viable pathway for eco-friendly composite development
Biomass to Biofuel: Sawdust Conversion into Bio-Oil via Pyrolysis
Get PDFThis study investigates the conversion of sawdust into liquid fuel via pyrolysis. The bio-oil derived from sawdust pyrolysis was analyzed using gas chromatography-mass spectrometry (GC-MS). The results reveal a complex mixture of organic compounds, including phenolic compounds, ketones, aldehydes, and fatty acids. Phenolic compounds, such as phenol-2-methoxy- and Phenol-2,6-dimethyl are the most abundant group in the bio-oil, likely derived from the lignin component of the sawdust. The presence of these compounds suggests that the bio-oil could be used as a potential feedstock for the production of chemicals and fuels. Further studies are needed to optimize the pyrolysis process and upgrade the bio-oil for practical applications. This study provides valuable insights into the composition of bio-oil derived from sawdust pyrolysis and its potential applications
Antioxidants-rich Supplement Ameliorates Chromium-induced Oxidative Stress in Albino Wistar Rats
Get PDFChromium (Cr), a naturally occurring element widely used in various industries, has recently been implicated to generate free radicals by its divalent and hexavalent forms inducing oxidative states. The carcinogenicity of Cr was suggested to be through inducing oxidative stress. Supplementation with antioxidants was reported to ameliorate oxidative stress in several studies. In this study, oxidative stress was induced using 20 mg/kg K2Cr2O7 in albino Wistar rats’ groups B, C and D. After 14 days, the rats in groups C and D were treated with 250 and 500 mg/kg/body weight antioxidant-rich supplements. The serum chromium level, activities of antioxidant enzymes (SOD, CAT, GPx) and GSH, antioxidant minerals (Se, Zn, Cu, Fe and Mn) and vitamins (A, C, and E) concentrations, and malondialdehyde (MDA) level were determined. The results showed significant (p<0.05) weight gain in all the groups. Serum Cr level decreased significantly (p< 0.05) compared to control group (B). Significant (p<0.05) increase in serum activity of enzymes (SOD, CAT and GPx), concentrations of GSH, vitamins, and minerals was observed in supplemented groups C and D compared to B. MDA levels were significantly (p < 0.05) reduced in group C compared to B. The results suggest that antioxidant-rich supplements could ameliorate chromium-induced oxidative stress
Flood Risk Mapping in the River-Rima Basin, Kebbi State, Nigeria: A Geographic Information System-Based Approach
Get PDFFloods are a growing menace to human life, as well as to infrastructure and agricultural yields in emerging river floodplain regions. The River Rima floodplain is well known in Birnin Kebbi for its agricultural production, especially rice production, which is essential to local livelihood and food security. This study employs an integrated GIS and Analytic Hierarchy Process (AHP) approach to evaluate flood risk zones within the River Rima basin, Nigeria. Six geomorphological and hydrological factors (elevation, slope, drainage density, rainfall, soil type, and land use) were weighted through pairwise comparisons to generate hazard and vulnerability indices. The Flood Hazard Index was accomplished. Settlement distribution was taken as a susceptibility criterion to create the Flood Vulnerability Index. By linking these maps with indices, a flood risk map was generated, which shows that the study area is divided into high (25.29%), moderate (29.64%), and low (45.07%) flood risk classes, indicating that more than half of the floodplain is at risk of floods. The research identifies six main flood hazard predictors: elevation (38.1%), drainage density (19.6%), slope (17.8%), mean annual rainfall (12.2%), soil type (6.4%), and land use (6.0%). This means that elevation and drainage density, which are geomorphological factors, play a major role in causing floods in the area. Urban expansion poses a great threat to settlements like Ambursa, Birnin Kebbi, and Dagere, whereas settlements like Makerah, Anguwar Kayi, and Maurida are located in the floodplain and are therefore very prone to the effects. Farmland and built-up land are the most at-risk elements, with 64.7% of farmland and 70.2% of built-up areas classified as highly or moderately vulnerable. Based on these findings, the study recommends incorporating land-use zoning, community-based flood preparedness, and relocating critical infrastructure. The implementation of long-term planning strategies demands both climate change projections and machine learning technologies for future flood modelling