PENERAPAN MODEL PEMBELAJARAN TIPE PICTURE AND PICTURE DALAM MENINGKATKAN HASIL BELAJAR DI KELAS VIII SMP NEGERI 2 PEULIMBANG

Banda Ace

What Drives Innovation?: Inferences from an Industry-Wide Survey in Nigeria

This chapter seeks to make some contributions to the literature on firm-level innovation in Africa by attempting to identify the significant factors that explain the capability of firms in Nigeria to innovate using the results of an industry-wide study. We focused on the product and process innovation activities of firms between 2003 and 2006 and found differences in the factors that drive them at the firm level. Our results further show that interactions matter more than most innovation-related variables and that the most important actors that influence a firm’s innovation efforts are its customers and suppliers. We conclude that product and process innovations are not mutually exclusive and that a major key to successful innovation is how and with whom a firm collaborates. The implication of this for firms and policy makers is that an effectively wired innovation system where all stakeholders are active is critical for firm-level innovation capability.innovation; drivers; manufacturing industry; Nigeria; determinants

ACACIA ATAXACANTHA (BARK): CHEMICAL COMPOSITION AND ANTIBACTERIAL ACTIVITY OF THE EXTRACTS

Objective: The present work aimed to investigate the phytochemical constituents and antibacterial activity of several extracts of Acacia ataxacantha bark on pathogenic microbes. Methods: The phytochemical study was performed using tube test and Thin layer chromatography methods. The growth inhibitory effect and the Minimum Inhibitory Concentration of hexane, dichloromethane, ethyl acetate, methanol and hydroalcolic extracts were determined using the microplate dilution method. Results: Phytochemical screening revealed the presence of alkaloid, tannins, lignan, triterpenoids, anthracene derivatives, flavonoids, saponins and coumarins at different level. The extracts exhibited different effect against the tested bacteria. The minimum inhibitory concentrations of extracts ranged from 325 µg/ml to 5 mg/ml. Ethyl acetate extract was more potent than other extracts with the MIC values of 325 µg/ml against S. aureus and 625 µg/ml against all other tested bacteria. Escherichia coli was resistant to all extracts. Conlusion: These findings suggest that the rich phytochemical content of Acacia ataxacantha and its good antibacterial activity may be responsible for its popular and wide traditional use

Development of a Test Statistic for Testing Equality of Two Means under Unequal Population Variances

In this paper, we propose a test statistic for testing equality of two independent sample means for unequal variances. When group variances differ, the pooled sample variance (  ) is inadequate as a single value for the variances. This problem is commonly known as the Behrens – Fisher problem. Instead, the sample harmonic mean of variances (  ) is proposed, examined and found to better represent the unequal variances. The distribution of  which is known to be generalized Beta is further approximated by the chi – square distribution with the degrees of freedom related to that of degrees of freedom of the chi – square distribution of   . Consequently, it is used to replace the pooled sample variance in the resulting proposed t – test. An example of application is provided. Keywords: Harmonic mean of variances, chi- square distribution, modified t – test statisti

VARIETAL CHARACTERIZATION OF THE PHYSICAL PROPERTIES, PROXIMATE AND MINERAL COMPOSITION OF IMPROVED SESAME (Sesamun indicum) SEEDS

The study was conducted to characterize the physical properties, proximate and mineral composition of improved sesame varieties. Fourteen improved varieties of sesame seeds were analyzed for their physical properties, proximate and mineral composition following standard analytical procedures. The arithmetic mean diameter (AMD), sphericity, geometric mean diameter (GMD), aspect ratio and surface area were in the range 1.51-1.91 mm, 0.57-0.64 mm, 1.32-1.70 mm, 61.50- 75.00%, and 84 - 8.94 mm2, respectively. Ca, Fe, Mg and K contents were also in the range 5.4-20.2 mg/kg, 0.5-3.0 mg/kg, 1.5-7.4 mg/kg, and 2.9-12.9 mg/kg, respectively. There was significant varietal differences (P<0.05) in the physical properties, proximate and mineral composition of the improved sesame seeds. The improved sesame varieties were characterized into three groups with distinct physical properties, proximate and mineral composition using hierarchical clustering procedure. Cluster 1 consists of varieties with relatively low proximate and mineral composition while cluster 2 comprises varieties with higher amounts of these nutrients. The variety in cluster 3 was characterized with exceptionally low content of minerals. The diversity obtained in the physical properties and proximate composition of the improved sesame seeds from this study underscores the huge potentials of the improved sesame seeds in food and non food use

Possibilities of sweet potato [Ipomoea batatas (L.) Lam] value chain upgrading as revealed by physico-chemical composition of ten elites landraces of Benin

Sweet potato is one of the most important food security promoted root crops in the world, especially in sub-Saharan Africa. Unfortunately, the crop is still neglected and underutilized in Benin Republic. To establish baseline data for its better utilization for upgrading its value chain, 10 selected local varieties (01 cream, 02 white, 03 yellow, and 04 orange flesh-colored) were compared for their macro-nutritional composition assessed using standard Association of Official Analytical Chemists (AOAC) procedures and spectrophotometry methods. The results indicate that sweet potato dry matter, protein, fiber, and ash content ranged from 46.11 to 25.9%, 4.09 to 1.97%, 1.81 to 3.00%, and 4.70 to 2.56%, respectively and orange flesh cultivars were found very rich. Pearson correlation analysis of variables revealed that dry mater content is positively correlated with carbohydrate and energy values, but negatively correlated with ash and fiber content, while starch content is strongly correlated with fiber content. Principal component analysis allowed us to classify the sweet potato varieties into 03 varietal groups among which Group 2 (05 varieties) exhibited rich fiber, ash, and protein contents and may be recommended for infant foods formulations. These results constitute important orientation for sweet potato processing chain organization in Benin and for the establishment of future nutrition and breeding programme.Key words: Benin, sweet potato, Ipomoea batatas, nutritional composition, orange flesh cultivar, value chain

Evaluation of Inhibitive Performance of Some Plants Extracts on Low Carbon Steel Corrosion

The corrosion inhibitive potential of Plumeria Alba, Blighia Sapida and Secamone Afezeli plants extracts on heat-treated and non-heat-treated mild steel samples immersed in different concentrations of hydrochloric acid (HCl) were investigated using weight loss technique. The mild steel samples were cut and prepared for the corrosion test in the acid media mixed with the plant extracts obtained by natural drying, grinding and chemical extraction using hexane. The plants were collected from the botanical garden of University of Lagos, Nigeria. Samples of the mild steel were weighed before immersion and at regular interval of 7 days for a period of 56 days after immersion. The experiment was repeated using 0.1 M and 0.2 M of an inorganic inhibitor. Results obtained showed that the extract of Blighia Sapida exhibited the highest inhibitive power, while annealed samples have the least corrosion rate in the Hcl solution

Effect of frying treatments on texture and colour parameters of deep fat fried yellow fleshed cassava chips

Effects of frying treatments on texture (hardness) and colour parameters (L, a, b, Delta) during deep fat frying of yellowfleshed cassava root slices (TMS 01/1371) were investigated. Slices (dimension of 40mm × 25mm × 3 mm) were divided into three portions and subjected to vacuum frying (fresh slices) and atmospheric frying (fresh and predried slices) and equivalent thermal driving forces (ETDF) of 60∘C, 70∘C, and 80∘C were maintained during frying. The quality attributes investigated were best preserved in vacuum fried chips. The overall colour change in chips fried under vacuum conditions at 118∘C and 8 min was the least (21.20) compared to fresh and atmospherically predried ones (16.69 and 14.81, resp.). A sharp reduction in the breaking force was obtained for all frying treatments after 8 min and this effect was the least in vacuum fried chips. First-order kinetics modeled the changes in quality attributes for all the temperatures investigated. Rate constants k (min−1) obtained for vacuum frying were almost equal to that of atmospheric frying while activation energies for hardness and colour change were 53.30 and 467.11 KJ/mol, respectively. Quality attributes studied were best preserved during vacuum frying

Machine learning - based framework for construction delay mitigation

The construction industry, for many decades, has been underperforming in terms of the success of project delivery. Construction delays have become typical of many construction projects leading to lawsuits, project termination, and ultimately dissatisfied stakeholders. Experts have highlighted the lack of adoption of modern technologies as a cause of underproductivity. Nevertheless, the construction industry has an opportunity to tackle many of its woes through Construction 4.0, driven by enabling digital technologies such as machine learning. Consequently, this paper describes a framework based on the application of machine learning for delay mitigation in construction projects. The key areas identified for machine learning application include "cost estimation", "duration estimation", and "delay risk assessment". The developed framework is based on the CRISP-DM graphical framework. Relevant data were obtained to implement the framework in the three key areas identified, and satisfactory results were obtained. The machine learning methods considered include Multi Linear Regression Analysis, K-Nearest Neighbours, Artificial Neural Networks, Support Vector Machines, and Ensemble methods. Finally, interviews with professional experts were carried out to validate the developed framework in terms of its applicability, appropriateness, practicality, and reliability. The main contribution of this research is in its conceptualization and validation of a framework as a problem-solving strategy to mitigate construction delays. The study emphasized the cross-disciplinary campaign of the modern construction industry and the potential of machine learning in solving construction problems

Adsorption isotherms and thermodynamics properties of water yam flour

Adsorption isotherms of water yam flour were determined by static gravimetric method of saturated salt solutions in the range of water activities between 0.11 and 0.96 and at temperatures of 25, 35 and 45 °C. The experimental sorption data was fitted to five models: Guggenheim-Anderson-De Boer (GAB), Peleg, Iglesias-Chirife, Exponential and Oswin and the differential enthalpy and entropies were determined. Equilibrium moisture contents decreased with increase in temperature at all the water activities studied. Peleg model gave the best fit for the sorption isotherm of water yam flour. Monolayer moisture content values estimated from the GAB-model were found to decrease with increases in temperature. The differential enthalpy and entropy decreased with increases in moisture content. The isokinetic temperature was 371.32 K and the compensation theory was satisfied