PREDICTING STUDENTS«¤?? ENROLLMENT USING GENERALIZED FEED-FORWARD NEURAL NETWORK

An important obligation of educational planning is the projection of students«¤?? enrollment which forms the basis for many of the investment decisions. Enrollment projection provides information for decision making and budget planning hence, it is important to the development of higher education. As many factors have impacts on the enrollment number, and for the above reasons, students«¤?? population and enrollment number should be considered as a chaotic system. In this research, a Generalized Feed-Forward Neural Network (GFFNN) for students«¤?? enrollment prediction was proposed. The architecture of the proposed model was in-line with eight steps involved in developing a neural network model for predicting a chaotic system. The data used was obtained from Academic Planning and Quality Control Unit of Tai Solarin University of Education, Ogun State Nigeria. The results from the study showed that the mean absolute percent error of GFFNN has an average of 0.0101% unlike linear regression and autoregression models that were compared with it, with an average of 0.0570% and 0.0725% respectively. The proposed methodology is expected to assist the school management to adequately plan for the future needs of the students in the provision of facilities.ª¤

PREDICTING STUDENTS«¤?? GRADE SCORES USING TRAINING FUNCTIONS OF ARTIFICIAL NEURAL NETWORK

The observed poor quality of graduates of some Nigerian Universities in recent times has been traced to non-availability of adequate mechanism. This mechanism is expected to assist the policy maker project into the future performance of students, in order to discover at the early stage, students who have no tendency of doing well in school. This study focuses on the use of artificial neural network (ANN) model for predicting students«¤?? academic performance in a University System, based on the previous datasets. The domain used in the study consists of sixty (60) students in the Department of Computer and Information Science, Tai Solarin University of Education in Ogun State, who have completed four academic sessions from the university. The codes were written and executed using MATLAB format. The students«¤?? CGPA from first year through their third year were used as the inputs to train the ANN models constructed using nntool and the Final Grades (CGPA) served as a target output. The output predicted by the networks is expressed in-line with the current grading system of the case study. CGPA values simulated by the network are compared with the actual final CGPA to determine the efficacy of each of the three feed-forward neural networks used. Test data evaluations showed that the ANN model is able to predict correctly, the final grade of students with 91.7% accuracy.ª¤

THE EFFECTS OF PALM OIL ON THE PHYSICAL APPEARANCE OF Clarias gariepinus DURING TRANSPORTATION

ABSTRACT:The study on the rate of water quality deterioration, bacterial load, survival percentage and physical appearance of transported adult Clarias gariepinus was carried out using palm oil as water additive and anti-stress at different concentrations, 904mgL -1 ,1808 mgL -1 and 2712 mgL -1 and compared to salt at 0.4% over a six hour transportation period. The adult fish were transported in a container at 2kg /litre of water in an open van while the water samples were at zero, second, fourth and sixth hours of transportation. Water quality, physical appearance and the survival rate of the fish within the various treatments were assessed at the end of the transportation exercise. The pH of transport water containing oil at 904mgL -1 , 1808mgL -1 and 2712mgL -1 was maintained during the course of transportation in contrast to the treatment containing 0.4% salt and the control whose pH changed at the second hour of transportation but the dissolved oxygen (DO), temperature, ammonium (NH 4 ), Nitrate (NO 3 ), Nitrite (NO 2 ) and chlorine (CI) of all the treatments followed the same trend while the bicarbonate (HCO 3 ) concentration of transport water containing 2712mgL -1 palm oil were maintained till the second hour before it changed at the fourth and sixth hours of transportation. The plate count agar (PCA) of all the treatments containing oil recorded more organisms than the treatment containing 0.4% salt and the control; but, the fish in all the treatments containing palm oil have an appearance not different from when freshly harvested in contrast to the control that had bruises and scars on the skin and the survival percentage of fish in all the treatments was between 95% -100%. It has been revealed that addition of palm oil at the varying concentrations kept the freshness of the fish during transportation thereby improving the market value of transported live catfish

Progress and challenges of demand-led co-produced sub-seasonal-to-seasonal (S2S) climate forecasts in Nigeria

This paper identifies fundamental issues which prevent the effective uptake of climate information services in Nigeria. We propose solutions which involve the extension of short-range (1 to 5 days) forecasts beyond that of medium-range (7 to 15 days) timescales through the operational use of current forecast data as well as improve collaboration and communication with forecast users. Using newly available data to provide seamless operational forecasts from short-term to sub-seasonal timescales, we examine evidence to determine if effective demand-led sub-seasonal-to-seasonal (S2S) climate forecasts can be co-produced. This evidence involves: itemization of forecast products delivered to stakeholders, with their development methodology; enumeration of inferences of forecast products and their influences on decisions taken by stakeholders; user-focused discussions of improvements on co-produced products; and the methods of evaluating the performance of the forecast products. We find that extending the production pipeline of short-range forecast timescales beyond the medium-range, such that the medium-range forecast timescales can be fed into existing tools for applying short-range forecasts, assisted in mitigating the risks of sub-seasonal climate variability on socio-economic activities in Nigeria. We also find that enhancing of collaboration and communication channels between the producers and the forecast product users helps to: enhance the development of user-tailored impact-based forecasts; increases users’ trusts in the forecasts; and, seamlessly improves forecast evaluations. In general, these measures lead to more smooth delivery and increase in uptake of climate information services in Nigeria

Connecting Network Properties of Rapidly Disseminating Epizoonotics

To effectively control the geographical dissemination of infectious diseases, their properties need to be determined. To test that rapid microbial dispersal requires not only susceptible hosts but also a pre-existing, connecting network, we explored constructs meant to reveal the network properties associated with disease spread, which included the road structure.Using geo-temporal data collected from epizoonotics in which all hosts were susceptible (mammals infected by Foot-and-mouth disease virus, Uruguay, 2001; birds infected by Avian Influenza virus H5N1, Nigeria, 2006), two models were compared: 1) 'connectivity', a model that integrated bio-physical concepts (the agent's transmission cycle, road topology) into indicators designed to measure networks ('nodes' or infected sites with short- and long-range links), and 2) 'contacts', which focused on infected individuals but did not assess connectivity.THE CONNECTIVITY MODEL SHOWED FIVE NETWORK PROPERTIES: 1) spatial aggregation of cases (disease clusters), 2) links among similar 'nodes' (assortativity), 3) simultaneous activation of similar nodes (synchronicity), 4) disease flows moving from highly to poorly connected nodes (directionality), and 5) a few nodes accounting for most cases (a "20:80" pattern). In both epizoonotics, 1) not all primary cases were connected but at least one primary case was connected, 2) highly connected, small areas (nodes) accounted for most cases, 3) several classes of nodes were distinguished, and 4) the contact model, which assumed all primary cases were identical, captured half the number of cases identified by the connectivity model. When assessed together, the synchronicity and directionality properties explained when and where an infectious disease spreads.Geo-temporal constructs of Network Theory's nodes and links were retrospectively validated in rapidly disseminating infectious diseases. They distinguished classes of cases, nodes, and networks, generating information usable to revise theory and optimize control measures. Prospective studies that consider pre-outbreak predictors, such as connecting networks, are recommended

Ecological and epidemiological findings associated with zoonotic rabies outbreaks and control in Moshi, Tanzania, 2017–2018

Approximately 1500 people die annually due to rabies in the United Republic of Tanzania. Moshi, in the Kilimanjaro Region, reported sporadic cases of human rabies between 2017 and 2018. In response and following a One Health approach, we implemented surveillance, monitoring, as well as a mass vaccinations of domestic pets concurrently in >150 villages, achieving a 74.5% vaccination coverage (n = 29, 885 dogs and cats) by September 2018. As of April 2019, no single human or animal case has been recorded. We have observed a disparity between awareness and knowledge levels of community members on rabies epidemiology. Self-adherence to protective rabies vaccination in animals was poor due to the challenges of costs and distances to vaccination centers, among others. Incidence of dog bites was high and only a fraction (65%) of dog bite victims (humans) received post-exposure prophylaxis. A high proportion of unvaccinated dogs and cats and the relative intense interactions with wild dog species at interfaces were the risk factors for seropositivity to rabies virus infection in dogs. A percentage of the previously vaccinated dogs remained unimmunized and some unvaccinated dogs were seropositive. Evidence of community engagement and multi-coordinated implementation of One Health in Moshi serves as an example of best practice in tackling zoonotic diseases using multi-level government e orts. The district-level establishment of the One Health rapid response team (OHRRT), implementation of a carefully structured routine vaccination campaign, improved health education, and the implementation of barriers between domestic animals and wildlife at the interfaces are necessary to reduce the burden of rabies in Moshi and communities with similar profiles.The USAID funded project—OSRO/GLO/507/USA on Global Health Security Agenda for the control of zoonosis in Africa.http://www.mdpi.com/journal/ijerpham2020Veterinary Tropical Disease

Global burden and strength of evidence for 88 risk factors in 204 countries and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

Background: Understanding the health consequences associated with exposure to risk factors is necessary to inform public health policy and practice. To systematically quantify the contributions of risk factor exposures to specific health outcomes, the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 aims to provide comprehensive estimates of exposure levels, relative health risks, and attributable burden of disease for 88 risk factors in 204 countries and territories and 811 subnational locations, from 1990 to 2021. Methods: The GBD 2021 risk factor analysis used data from 54 561 total distinct sources to produce epidemiological estimates for 88 risk factors and their associated health outcomes for a total of 631 risk–outcome pairs. Pairs were included on the basis of data-driven determination of a risk–outcome association. Age-sex-location-year-specific estimates were generated at global, regional, and national levels. Our approach followed the comparative risk assessment framework predicated on a causal web of hierarchically organised, potentially combinative, modifiable risks. Relative risks (RRs) of a given outcome occurring as a function of risk factor exposure were estimated separately for each risk–outcome pair, and summary exposure values (SEVs), representing risk-weighted exposure prevalence, and theoretical minimum risk exposure levels (TMRELs) were estimated for each risk factor. These estimates were used to calculate the population attributable fraction (PAF; ie, the proportional change in health risk that would occur if exposure to a risk factor were reduced to the TMREL). The product of PAFs and disease burden associated with a given outcome, measured in disability-adjusted life-years (DALYs), yielded measures of attributable burden (ie, the proportion of total disease burden attributable to a particular risk factor or combination of risk factors). Adjustments for mediation were applied to account for relationships involving risk factors that act indirectly on outcomes via intermediate risks. Attributable burden estimates were stratified by Socio-demographic Index (SDI) quintile and presented as counts, age-standardised rates, and rankings. To complement estimates of RR and attributable burden, newly developed burden of proof risk function (BPRF) methods were applied to yield supplementary, conservative interpretations of risk–outcome associations based on the consistency of underlying evidence, accounting for unexplained heterogeneity between input data from different studies. Estimates reported represent the mean value across 500 draws from the estimate's distribution, with 95% uncertainty intervals (UIs) calculated as the 2·5th and 97·5th percentile values across the draws. Findings: Among the specific risk factors analysed for this study, particulate matter air pollution was the leading contributor to the global disease burden in 2021, contributing 8·0% (95% UI 6·7–9·4) of total DALYs, followed by high systolic blood pressure (SBP; 7·8% [6·4–9·2]), smoking (5·7% [4·7–6·8]), low birthweight and short gestation (5·6% [4·8–6·3]), and high fasting plasma glucose (FPG; 5·4% [4·8–6·0]). For younger demographics (ie, those aged 0–4 years and 5–14 years), risks such as low birthweight and short gestation and unsafe water, sanitation, and handwashing (WaSH) were among the leading risk factors, while for older age groups, metabolic risks such as high SBP, high body-mass index (BMI), high FPG, and high LDL cholesterol had a greater impact. From 2000 to 2021, there was an observable shift in global health challenges, marked by a decline in the number of all-age DALYs broadly attributable to behavioural risks (decrease of 20·7% [13·9–27·7]) and environmental and occupational risks (decrease of 22·0% [15·5–28·8]), coupled with a 49·4% (42·3–56·9) increase in DALYs attributable to metabolic risks, all reflecting ageing populations and changing lifestyles on a global scale. Age-standardised global DALY rates attributable to high BMI and high FPG rose considerably (15·7% [9·9–21·7] for high BMI and 7·9% [3·3–12·9] for high FPG) over this period, with exposure to these risks increasing annually at rates of 1·8% (1·6–1·9) for high BMI and 1·3% (1·1–1·5) for high FPG. By contrast, the global risk-attributable burden and exposure to many other risk factors declined, notably for risks such as child growth failure and unsafe water source, with age-standardised attributable DALYs decreasing by 71·5% (64·4–78·8) for child growth failure and 66·3% (60·2–72·0) for unsafe water source. We separated risk factors into three groups according to trajectory over time: those with a decreasing attributable burden, due largely to declining risk exposure (eg, diet high in trans-fat and household air pollution) but also to proportionally smaller child and youth populations (eg, child and maternal malnutrition); those for which the burden increased moderately in spite of declining risk exposure, due largely to population ageing (eg, smoking); and those for which the burden increased considerably due to both increasing risk exposure and population ageing (eg, ambient particulate matter air pollution, high BMI, high FPG, and high SBP). Interpretation: Substantial progress has been made in reducing the global disease burden attributable to a range of risk factors, particularly those related to maternal and child health, WaSH, and household air pollution. Maintaining efforts to minimise the impact of these risk factors, especially in low SDI locations, is necessary to sustain progress. Successes in moderating the smoking-related burden by reducing risk exposure highlight the need to advance policies that reduce exposure to other leading risk factors such as ambient particulate matter air pollution and high SBP. Troubling increases in high FPG, high BMI, and other risk factors related to obesity and metabolic syndrome indicate an urgent need to identify and implement interventions

Misrepresentation: Case study of metabolizable energy determination in feed and ingredient samples

Nutritional value of feed and ingredients are evaluated using precise and accurate values predetermined quantitatively but not all parameters are determined using equipment. The values of such components may be determined by including a constant coefficient previously derived or endorsed and agreed upon by professionals to give a prediction equation. Such is the case of Metabolizable Energy which the World Poultry Science Association adopted to be 37% x Protein + 81.8 x % Fat +35.5 x % NFE as reported by Pauzenga in 1985. Several constant coefficients now crop up in references which does not represent the original text, thus the need to put the records straight so that new researchers can be rightly guided. Editors and reviewers can also take a cue from this. Keywords: Metabolizable Energy, Calculation, Pauzenga, Feed, Prediction equation

Analysis of thermal comfort in Lagos, Nigeria

This paper reports a thermal comfort survey conducted in three locations in Lagos between July 1996 and June 1997 in which 50 fully acclimatized subjects cast over 6,000 individual votes of their subjective assessments of the thermal environments. The survey covered only residential buildings constructed of sandcrete materials. A set of multiple linear regression equations relating comfort votes with the variations of air temperature and relative humidity has been developed. Other regression equations that describe how external climate is altered indoor by the building fabrics have also been derived. Maximum and minimum values of temperature and relative humidity were also obtained for the purpose of air conditioning load estimation. Frequency distribution of air temperatures and comfort votes show a comfortable temperature range of 260C to 280C, comfortably cool between 240C and 260C, and comfortably warm between 280C and 300C. Keywords: acclimatized subjects, thermal comfort, comfort vote, optimum dry bulb temperature, climatic index. [Global Jnl Environ Sci Vol.2(1) 2003: 59-65