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A HPLC with gradient elution method for the determination of the synthetic phenolic antioxidants (SPAs) propyl gallate (PG), tertiary butyl hydroquinone (TBHQ), butylated hydroxyanisole (BHA), and butylated hydroxytoluene (BHT) in food items is described. A C18 column served as the stationary phase; the gradient elution was formed by acetonitrile and water:acetic acid (1%). The UV detector was set at 280 nm. Under the recommended conditions, separation of the four SPAs was achieved in less than 8 min. Analytical characteristics of the HPLC method such as limit of detection, linear range, and reproducibility were evaluated. Extraction parameters were optimized for the recoveries of the SPAs in different types of food items (cooking oil, margarine and butter, and cheese). Before the HPLC separation, the SPAs were extracted with methanol/acetonitrile (1:1, v/v) and were subjected to vortex/ultrasonic treatment. The extracts were next kept in a freezer (∼2 h) to precipitate co-extracted components. Recoveries of the SPAs when spiked to cooking oil, margarine, butter and cheese at 50 and 200 mg l−1 were in the ranges 93.3–108.3% for PG, 85.3–108.3% for TBHQ, 96.7–101.2% for BHA and 73.9–94.6% for BHT. The method was applied to the determination of SPAs in 38 food items (16 cooking oils, ten margarine, six butter and six cheese samples). The levels of SPAs in positive samples are all below the legal limits of Malaysia.

Power flow study has been identified as the most important issue in power systems especially in the field of assessing the power system operability, survivability and also its security. It is considered as the back bone prior to further power system analysis, operation and planning. There have been various ready made products for power flow study packages in the market. Nonetheless, any attempts to solve power flow solution utilizing new developed algorithm or techniques can be considered as a brave trial. This paper proposes the Evolutionary Programming (EP) optimization technique to address the power flow problems through optimization technique. EP is based on the survivors of the fittest technique; where it is a sub-division of evolutionary computation (EC) under the hierarchy of Artificial Intelligence (AI). Its capability in solving multi-variables, non- convex, non-linear and/or single or mufti-objective optimization problems have been highlighted as the strength of EP. In realizing the effectiveness of EP in solving power problems, standard test system was utilized to ensure its workability in solving non-linear equations involving several pre-determined equality and inequality constraints equations. Results obtained from this study were compared with the existing established techniques; promising results were discovered implying that this technique is feasible to be implemented in addressing further optimization problems.