The use of Donryu rats as a model for the humans in the formulation of dietary protein

The effects of brewery spent grain formulated diet on the performance of Donryu rats were investigated. The rats were allocated into 6 dietary treatment groups of 6 rats each and fed with diet containing graded levels of BSG 0, 3, 6, 9, 12 and 100%. The experimental feeding lasted for fifteen days. The BSG formulated diet was found to have a positive effect on the growth performance of the rats up to levels of 12% including the control(0%). The histopathological evaluation shows that 3–9% BSG could be used as protein supplement in human foods

PQ TREES, CONSECUTIVE ONES PROBLEM AND APPLICATIONS

A PQ tree is an advanced tree–based data structure, which represents a family of permutations on a set of elements. In this research article, we considered the significance of PQ trees and the Consecutive ones Problem to Computer Science and bioinformatics and their various applications. We also went further to demonstrate the operations of the characteristics of the Consecutive ones property by simulation, using high level programming languages. Attempt was also made at developing a PQ tree–Consecutive Ones analyzer, which could be instrumental not only as an educative tool to inquisitive students, but also serve as an important tool in developing clustering software in the field of bioinformatics and other application domains, with respect to solving real life problems

HISTOLOGICAL STUDIES OF BREWERY SPENT GRAINS IN DIETARY PROTEIN FORMULATION IN DONRYU RATS

The increasing production of large tonnage of products in brewing industries continually generates lots of solid waste which includes spent grains, surplus yeast, malt sprout and cullet. The disposal of spent grains is often a problem and poses major health and environmental challenges, thereby making it imminently necessary to explore alternatives for its management. This paper focuses on investigating the effects of Brewery Spent Grain formulated diet on haematological, biochemical, histological and growth performance of Donryu rats. The rats were allocated into six dietary treatment groups and fed on a short-term study with diet containing graded levels of spent grains from 0, 3, 6, 9, 12 and 100% weight/weight. The outcome demonstrated that formulated diet had a positive effect on the growth performance of the rats up to levels of 6% inclusions, while the haematological and biochemical evaluation revealed that threshold limit should not exceed 9% of the grain. However, the histological study on the liver indicated a limit of 3% inclusion in feed without serious adverse effect. Thus invariably showing that blend between ranges 1-3% is appropriate for the utilization of the waste in human food without adverse effect on the liver organ. The economic advantage accruing from this waste conversion process not only solves problem of waste disposal but also handle issues of malnutrition in feeding ration

A Simple Data Driven Yoruba Language Dictionary

The language of a people is an integral part of their lives, because it is synonymous with their identity, culture and environment. Traditionally, the language people speak tells others about their identity but in a country like Nigeria where a lingua franca, English has been adopted, the identity of the people is being suppressed such that the first language of some Nigerians is English instead of their mother tongue and in some extreme cases the indigenous language has been lost. The use of a lingua franca, globalization and civilization should not bring about the death of our indigenous languages, instead, amid all these, Information Technology as the bedrock of our time can be harnessed to propagate our indigenous languages. This work focused on the development of an electronic Yoruba language dictionary that is data driven. The tools and techniques used in this work produced results. Keywords: Yoruba, dictionary, database, language translation, machine learnin

HIERARCHICAL MODELLING OF INDOOR AND OUTDOOR (RESIDENTIAL) RADON DATA (RRD)

This work, proposes a Hierarchical Modelling (HM) for the indoor and outdoor Residential Radon Data (RRD). Indoor RRD and outdoor RRD are seen as distinct «¤??hierarchies«¤?? of carcinogenic radioactive radon and both hierarchies constitute the least exposure that can be experienced by an individual. Works on this issue have always been based on complicated models, even for single instances of both indoor and outdoor residential radon. Our proposed method can be used to analyse effectively the many-to-many (it, however, becomes numerically clumsy if more than 5-to-5 instances are considered) instances of residential radon, although we have illustrated, here, using a three-to-three situation. Our preference of this method is based on its simplicity, and probable higher precision, as compared with the complexity involved in other methods on the same issue. The data used for the illustration of our models were taken from the indoors (i.e. living-room, bedroom and the kitchen) and the rest outdoors (i.e. verandah, car-park and the well-water shed) of a residential building in a lightly populated estate (i.e. Asero housing estate). Observations were taken on a daily basis throughout the dry season covering ninety days (i.e. January, February and March), this constitutes our season I (i.e. dry). The same was repeated in the season II (i.e. wet) which was taken at the beginning of June through July and August.ª¤?ª¤?ª¤?ª¤?ª¤?ª¤?ª¤?ª¤

STATISTICAL ANALYSIS OF TEMPORAL VARIATIONS IN INDOOR RADON DATA USING AN ADAPTED RESPONSE SURFACE METHOD

Temporary variations in indoor radon data (IRD), comprising radon concentration (RC), air temperature, relative humidity and barometric pressure were monitored hourly over a period of two months in a bungalow house in Abeokuta, Nigeria. A total of 1510 data was assembled and analyzed statistically using Shapiro-Wilk for normality test, response surface method (RSM) and adapted response surface method (ARSM) to investigate and model the influence of the meteorological parameters on the variations of RC in indoor air. The overall results showed that RC varies widely over time and correlates positively with relative humidity and temperature, but negatively with barometric pressure. Specific results of the two response surface methods were compared and contrasted and the multiple linear regression model of the ARSM was highlighted and established as the appropriate method for analyzing IRD. ARSM was presented in an easily reusable form that can easily be adopted by researchers and data analysts.ª¤

Functional and Nutritive Properties of Spent Grain Enhanced Cookies

The generation of large tonnages of spent grains as byproduct has become major disposal problem in brewing industry. This necessitate sourcing utilization alternatives to complement present use as animal feeds. The incorporation of this brewery spent grain, BSG, into cookie formulations to 15% maximum levels and its effects on the nutritional and functional properties of cookies was investigated. About 6.14% dried and 610 μm milled BSG were added to cookie formulation mix at 0, 3, 6, 9, 12 and 15% levels. Other recipes added include: wheat flour, salt, sodium carbonate, water, non-fatty milk and additives. The trace metal content of the blended products were also compared with local and imported cookies. The results obtained indicated free fatty acid, moisture content, extracted fat and sensory evaluation of the final cookies were limited to 6% optimum inclusion while the spread ratio analysis suggested 3% BSG usage. The undesirable flavor of BSG as additives influenced the taste of the cookies to a great extent and did not change the nutritional status of the samples from 6% BSG inclusion. The trace metals statistical analysis of the BSG supplemented cookies compared well with both locally baked and imported cookies (p≤0.05). However, addition of brewery spent grains significantly increased the nutritional properties of the cookies up to 6% level of BSG addition

STOCHASTIC PREDICTION OF MONTHLY INFLATION RATES THROUGH KALMAN FILTERING

Inflation measure is an important indicator of the state of an economy and the desire to determine it ahead of “time” cannot be overemphasised. This paper presents a step-by-step algorithm to predict the would-be monthly inflation rate of the Nigerian economy, using Kalman Filtering Predictor (KFP). The ordinary structural model for a time series (structTS) is highlighted to “fairly” compete against our proposed KFP. The structTS is a powerful “competitor”, it is in recommended R package “stats” and used for fitting basic structural models to “univariate” time series. It is quite reliable and fast, and is used as a benchmark in some comparisons of filtering techniques, it is indeed the “predictor” to “beat”, yet our proposed KFP has more to “offer”. The pertinent statistics and pictorial representation of the results obtained, through both techniques, is highlighted for any “incorruptible” judge’s perusal. All of these are contained in the couple of illustrative examples that exhibit the steps involved in the proposed algorithm, using a hypothetical monthly inflation rate and the monthly inflation rates data (January, 2011 to June, 2014) of the Nigerian economy.     &nbsp