Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 6

Search results for: Boutemak Khalida

6 Effect of Hemicellulase on Extraction of Essential Oil from Algerian Artemisia campestris

Authors: Khalida Boutemak, Nasssima Benali, Nadji Moulai-Mostefa

Abstract:

Effect of enzyme on the yield and chemical composition of Artemisia campestris essential oil is reported in the present study. It was demonstrated that enzyme facilitated the extraction of essential oil with increase in oil yield and did not affect any noticeable change in flavour profile of the volatile oil. Essential oil was tested for antibacterial activity using Escherichia coli; which was extremely sensitive against control with the largest inhibition (29mm), whereas Staphylococcus aureus was the most sensitive against essential oil obtained from enzymatic pre-treatment with the largest inhibition zone (25mm). The antioxidant activity of the essential oil with hemicellulase pre-treatment (EO2) and control sample (EO1) was determined through reducing power. It was significantly lower than the standard drug (vitamin C) in this order: vitamin C˃EO2˃EO1.

Keywords: Artemisia campestris, enzyme pre-treatment, hemicellulase, antibacterial activity, antioxidant activity

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5 Effect of Cellulase Pretreatment for n-Hexane Extraction of Oil from Garden Cress Seeds

Authors: Boutemak Khalida, Dahmani Siham

Abstract:

Garden cress (Lepidium Sativum L.) belonging to the family Brassicaceae, is edible growing annual herb. Its various parts (roots, leaves and seeds) have been used to treat various human ailments. Its seed extracts have been screened for various biological activities like hypotensive, antimicrobial, bronchodilator, hypoglycaemic and antianemic. The aim of the present study is to optimize the process parameters (cellulase concentration and incubation time) of enzymatic pre-treatment of the garden cress seeds and to evaluate the effect of cellulase pre-treatment of the crushed seeds on the oil yield, physico-chemical properties and antibacterial activity and comparing to non-enzymatic method. The optimum parameters of cellulase pre-treatment were as follows: cellulase of 0,1% w/w and incubation time of 2h. After enzymatic pre-treatment, the oil was extracted by n-hexane for 1.5 h, the oil yield was 4,01% for cellulase pre-treatment as against 10,99% in the control sample. The decrease in yield might be caused a result of mucilage. Garden cress seeds are covered with a layer of mucilage which gels on contact with water. At the same time, the antibacterial activity was carried out using agar diffusion method against 4 food-borne pathogens (Escherichia coli, Salmonella typhi,Staphylococcus aureus, Bacillus subtilis). The results showed that bacterial strains are very sensitive to the oil with cellulase pre-treatment. Staphylococcus aureus is extremely sensitive with the largest zone of inhibition (40 mm), Escherichia coli and salmonella typhi had a very sensitive to the oil with a zone of inhibition (26 mm). Bacillus subtilizes is averagely sensitive which gave an inhibition of 16 mm. But it does not exhibit sensivity to the oil without enzymatic pre-treatment with a zone inhibition (< 8 mm). Enzymatic pre-treatment could be useful for antimicrobial activity of the oil, and hold a good potential for use in food and pharmaceutical industries.

Keywords: Lepidium sativum L., cellulase, enzymatic pretreatment, antibacterial activity.

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4 Adsorption of a Pharmaceutical Pollutant on Activated Carbon of Orange Peels

Authors: Faroudja Mohellebi, Fayrouz Khalida Kies, Moncef Rezzik El Marhoun, Feriel Yahiat

Abstract:

The purpose of this study is to valorize an agro-food waste (orange peels) by its use as an adsorbent in the treatment of water loaded with pharmaceutical micropollutant present in aquatic environments, oxytetracycline. The tests, carried out in batch mode, made it possible to study the influence on the sorptive capacity of calcined orange peels of several parameters: the contact time, the initial concentration of oxytetracycline, the adsorbent dose, and the initial pH of the solution. The pseudo-second-order model is best adapted to represent the adsorption kinetics. The Langmuir model describes the adsorption isotherm of oxytetracycline. The adsorption is favored in a basic environment.

Keywords: adsorption, emerging pollutants, oxytetracycline, water treatment

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3 Denoising of Motor Unit Action Potential Based on Tunable Band-Pass Filter

Authors: Khalida S. Rijab, Mohammed E. Safi, Ayad A. Ibrahim

Abstract:

When electrical electrodes are mounted on the skin surface of the muscle, a signal is detected when a skeletal muscle undergoes contraction; the signal is known as surface electromyographic signal (EMG). This signal has a noise-like interference pattern resulting from the temporal and spatial summation of action potentials (AP) of all active motor units (MU) near electrode detection. By appropriate processing (Decomposition), the surface EMG signal may be used to give an estimate of motor unit action potential. In this work, a denoising technique is applied to the MUAP signals extracted from the spatial filter (IB2). A set of signals from a non-invasive two-dimensional grid of 16 electrodes from different types of subjects, muscles, and sex are recorded. These signals will acquire noise during recording and detection. A digital fourth order band- pass Butterworth filter is used for denoising, with a tuned band-pass frequency of suitable choice of cutoff frequencies is investigated, with the aim of obtaining a suitable band pass frequency. Results show an improvement of (1-3 dB) in the signal to noise ratio (SNR) have been achieved, relative to the raw spatial filter output signals for all cases that were under investigation. Furthermore, the research’s goal included also estimation and reconstruction of the mean shape of the MUAP.

Keywords: EMG, Motor Unit, Digital Filter, Denoising

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2 Exploring Data Leakage in EEG Based Brain-Computer Interfaces: Overfitting Challenges

Authors: Khalida Douibi, Rodrigo Balp, Solène Le Bars

Abstract:

In the medical field, applications related to human experiments are frequently linked to reduced samples size, which makes the training of machine learning models quite sensitive and therefore not very robust nor generalizable. This is notably the case in Brain-Computer Interface (BCI) studies, where the sample size rarely exceeds 20 subjects or a few number of trials. To address this problem, several resampling approaches are often used during the data preparation phase, which is an overly critical step in a data science analysis process. One of the naive approaches that is usually applied by data scientists consists in the transformation of the entire database before the resampling phase. However, this can cause model’ s performance to be incorrectly estimated when making predictions on unseen data. In this paper, we explored the effect of data leakage observed during our BCI experiments for device control through the real-time classification of SSVEPs (Steady State Visually Evoked Potentials). We also studied potential ways to ensure optimal validation of the classifiers during the calibration phase to avoid overfitting. The results show that the scaling step is crucial for some algorithms, and it should be applied after the resampling phase to avoid data leackage and improve results.

Keywords: data leackage, data science, machine learning, SSVEP, BCI, overfitting

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1 A Review on the Hydrologic and Hydraulic Performances in Low Impact Development-Best Management Practices Treatment Train

Authors: Fatin Khalida Abdul Khadir, Husna Takaijudin

Abstract:

Bioretention system is one of the alternatives to approach the conventional stormwater management, low impact development (LID) strategy for best management practices (BMPs). Incorporating both filtration and infiltration, initial research on bioretention systems has shown that this practice extensively decreases runoff volumes and peak flows. The LID-BMP treatment train is one of the latest LID-BMPs for stormwater treatments in urbanized watersheds. The treatment train is developed to overcome the drawbacks that arise from conventional LID-BMPs and aims to enhance the performance of the existing practices. In addition, it is also used to improve treatments in both water quality and water quantity controls as well as maintaining the natural hydrology of an area despite the current massive developments. The objective of this paper is to review the effectiveness of the conventional LID-BMPS on hydrologic and hydraulic performances through column studies in different configurations. The previous studies on the applications of LID-BMP treatment train that were developed to overcome the drawbacks of conventional LID-BMPs are reviewed and use as the guidelines for implementing this system in Universiti Teknologi Petronas (UTP) and elsewhere. The reviews on the analysis conducted for hydrologic and hydraulic performances using the artificial neural network (ANN) model are done in order to be utilized in this study. In this study, the role of the LID-BMP treatment train is tested by arranging bioretention cells in series in order to be implemented for controlling floods that occurred currently and in the future when the construction of the new buildings in UTP completed. A summary of the research findings on the performances of the system is provided which includes the proposed modifications on the designs.

Keywords: bioretention system, LID-BMP treatment train, hydrological and hydraulic performance, ANN analysis

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