Aluminum Nanoparticles Passivation of Multi-Crystalline Silicon Nanostructure for Solar Cells Applications

Silicon - In this paper, we demonstrated that aluminum films deposited on the front surface of multi-crystalline silicon (mc-Si) provide excellent surface passivation and high electronic quality of...     

Oil content,phenolic profiling and antioxidant potential of Tunisian olive drupes

BACKGROUND: The aim of this work was to investigate the effect of the maturation process of the olive fruit on oil content, phenolic profile and antioxidant activity of four Tunisian cultivars (Zelmati, Chemchali, Chemlali and Chétoui). RESULTS: The average oil content of the studied varieties ranged between 17.50% and 20.25% at the first stage of maturation and from 30.20% to 35% in the last harvest. Qualitative and quantitative analysis of phenolic compounds were carried out using HPLC and LC‐MS/MS. Twenty‐six biophenolic compounds were identified. In all samples, hydroxytyrosol and oleuropein were the major compounds identified while rutin and luteolin 7‐O‐glucoside were the two main flavonoids. The total phenolic content varied from 3.46 to 4.30 g kg^?1 at the first stage of maturation and from 8.71 to 11.52 g kg^?1 of fruit fresh weight at the last maturation phase. Total flavonoid content reached 432.80 mg kg^?1. The antioxidant activity of the extract was evaluated by DPPH and ABTS assays. The IC₅₀ values of the olive extracts ranged from 2.69 to 10.96 µg L^?1 and from 2.15 to 3.03 mmol L^?1 trolox equivalent at the last stage of maturation. CONCLUSION: A relationship between the changes in phenolic content and the physicochemical changes in Tunisian olive fruit during maturation was established. These findings could be used for controlling the production processes and correlating the oil sensorial characteristics to the polyphenolic pattern. Copyright © 2010 Society of Chemical Industry     

Stability of refined olive oil and olive‐pomace oil added by phenolic compounds from olive leaves

Refined olive oil and olive‐pomace oil were enriched with olive leaf phenolic compounds in order to enhance its quality and bring it closer to virgin olive oil. The changes that occurred in the concentrations of pure oleuropein, oleuropein aglycone, hydroxytyrosol acetyl and α‐tocopherol at 400 µg/kg of oil during the storage of refined olive oil and olive‐pomace oil under accelerated conditions (50 °C) were investigated. In a period of 4 months, α‐tocopherol decomposed by 75% whereas less than 40% of the phenols were lost. During storage, enzymatic olive leaf extract hydrolysate that contains two major compounds, hydroxytyrosol and oleuropein aglycone showed the highest antioxidant activity and the lowest detected stability, followed by oleuropein. The oleuropein in olive leaf extracts exhibited similar degradation profiles, reducing by 60–50% and 80% for the olive oil and olive‐pomace oil in 6 months, respectively. The acetylated extract, however, displayed a loss of 10 and 5% in olive oil and olive‐pomace oil, respectively. In the fatty acid composition, an increase in oleic acid and a decrease in linoleic acid were observed. The antiradical activities of the olive oil and olive‐pomace oil enriched with olive leaf phenolic compounds at 400 ppm showed that enzymatic hydrolysate extract had the highest protective effect against oil oxidation. Based on the Rancimat method, the oils with added leaf enzymatic hydrolysate extract had the lowest peroxide value and the highest stability. After 6 months of storage and at 120 °C, the oxidative resistance of refined olive oil and olive‐pomace oil reached 0.71 and 0.89 h, respectively, whereas that of the non‐enriched samples fell to zero.     

An effective and distributed particle swarm optimization algorithm for flexible job-shop scheduling problem

Flexible job-shop scheduling problem (FJSP) is very important in many research fields such as production management and combinatorial optimization. The FJSP problems cover two difficulties namely machine assignment problem and operation sequencing problem. In this paper, we apply particle swarm optimization (PSO) algorithm to solve this FJSP problem aiming to minimize the maximum completion time criterion. Various benchmark data taken from literature, varying from Partial FJSP and Total FJSP, are tested. Experimental results proved that the developed PSO is enough effective and efficient to solve the FJSP. Our other objective in this paper, is to study the distribution of the PSO-solving method for future implementation on embedded systems that can make decisions in real time according to the state of resources and any unplanned or unforeseen events. For this aim, two multi-agent based approaches are proposed and compared using different benchmark instances.     

Neural solutions to interact with computers by hand gesture recognition

This paper attempts to present a vision-based interface which interacts with computers by hand gesture recognition. This work aims at creating a natural and intuitive application employing both static and dynamic hand gestures. The proposed application can be summarized in three main steps: hands detection in a video, hands tracking and converting hand shapes or trajectories into computer commands. To accomplish this application, a classification phase is paramount whether at the part of hand detection, or at the phase of “commanding computers”. For this reason, we have proposed to use a wavelet network classifier (WNC) learnt by fast wavelet transform (FWT). To emphasize the robustness of this classifier, we have used a neural network classifier (NNC) version in order to compare the two classifiers’ performances aiming at proving the strength of our proposed one. Global rates given by experimental results show the effectiveness of our proposed approaches of hand detection, hand tracking and hand gesture recognition. The comparison of the two classifier’s result helps to choose the best classifier, which can improve the performances of our application.     

A review on simulation models applied to emergency medical service operations

Emergency medical services (EMS) are public safety systems responsible for the pre-hospital stabilization and transport of seriously injured patients. The goal of such systems is to respond adequately to population calls by providing first aid services and transferring patients, when needed, to the emergency department of the appropriate hospital. In order to achieve this goal, a variety of tools (e.g. simulation, mathematical programming and queuing theory models) have been used to improve the performance of EMS. This paper focuses specifically on computer simulation models used for the analysis and improvement of EMS. In particular, we give a critical overview of the existing international literature on simulation models for EMS by pinpointing the issues considered, the associated modeling assumptions as well as the results obtained. Such a contribution is lacking in the current literature.