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In this study, four empirical models on the basis of linear Angstrom-Prescotte model for predicting monthly mean daily global solar radiation on horizontal surface were developed, correlating solar radiation to climatic parameters of sunshine hours, temperature and relative humidity. The models were used to predict Global solar radiation, an average solar radiation of 16.9690 and maximum and minimum of 19.2647 and 13.5222 C 0 were respectively predicted. For validation and the accuracy of the models, statistical coefficient of determination, R 2 , mean percentage error, (MPE), mean bias error, (MBE), and root mean square error (RMSE) were used. The result showed that, model correlating solar radiation with Sunshine hours, temperature and relative humidity gives the best fit for the study location with R 2 = 83.89%, that was;

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Onion is produce in large quantities at every harvest season in Nigeria and this is so in many part of the world, however storage of the crop has been a problem, thus, the need to study the thermal behavior of clay room for the storage of onion. In this work the transient heat transmission across various walls of an adobe room was determined using an Engineering Equation Solver (EES) software programme. It was found that the determined average hourly temperature has a root mean square of percentage deviation of 10.8238 and that of determined average relative humidity is 8.4158. Thus EES software could be use in forecasting the indoor condition of an adobe room.

Solar radiation is the main source of heat energy that raises the temperature of an adobe room mostly habituated by people in the rural areas of Northern part of Nigeria and in many other rural areas of the world. For this, it is important to study the temperature pattern inside the Adobe room. In this work a simulation using Sci-Lab is been carried out in order to predict the temperature pattern inside the adobe room in the work, an analytical model using Complex Finite Fourier Transform (CFFT) technique for the periodic solution is performed using SCILAB Software. The simulation model was also validated; again from the simulation, it was found that the deviation between the experimental and model for inside room temperature was only 10 percent. This shows that it is possible to predict the pattern of inside temperature for an adobe room by using Sci-Lab.

Adobe buildings have been in used over a long period of time in many parts of the world, more especially in the African continent. It has been used to satisfy the shelter need for human comfort, animals comfort and preservation of food crops that are very important for human lives. To prevent the heat from the sun radiation to have a severer effect on the items, Adobe building was used for its ability to control temperature and humidity fluctuations within the building. In this work, two rooms were constructed one with adobe and the other with an additives material to the adobe. A study on the thermal performance of the two rooms was carried out to compare the inside rooms temperature and relative humidity. It was found that the average differences in the inside temperature and relative humidity were -2 degrees and +1 percent respectively, which shows that averagely the temperature of the improved room is lower than that of the control room while the converse is the case for the relative humidity.

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The 90's have been marked by an increasing globalization which has revealed two major trends, if on the one hand there has been a more pronounced opening up, especially in the ranks of emerging countries, on the other hand there has been a considerable rise in inequalities. Despite an abundant literature on the link between trade openness and wage inequality, the latter remains relatively ambiguous, particularly in the absence of a consensus, especially for the developing countries. This article therefore focuses on the impact of trade openness on wage inequality, particularly between skilled and unskilled workers for the case of Tunisia. Our analysis took into account a number of factors that influence this relationship, such as labor market fluctuations, technological transfer and the effect of institutions. Our contribution to this work is that unlike the majority of work conducted on the Tunisian case, our analysis has not been limited to the manufacturing industry but we have extended it to the services sector and the whole economy by including the non-manufacturing sector in order to provide a comparative analysis between these different sectors The exploitation of the estimation results over the period 1990 to 2020 shows that, in general, openness has contributed to the increase in wage inequalities in Tunisia