Green Synthesis of Silver Nanoparticles Using Olea europaea Leaf Extract for Their Enhanced Antibacterial,Antioxidant, Cytotoxic and Biocompatibility Applications

Herein, we report the green synthesis of silver nanoparticles (OE-Ag NPs) by ecofriendly green processes using biological molecules of Olea europaea leaf extract. Green synthesized OE-Ag NPs were successfully characterized using different spectroscopic techniques. Antibacterial activity of OE-Ag NPs was assessed against four different bacteriological strains using the dilution serial method. The cytotoxic potential was determined against MCF-7 carcinoma cells using MTT assay in terms of cell viability percentage. Antioxidant properties were evaluated in terms of 2,2-diphenyl-1-picrylhydrazyl (DPPH) free radical scavenging. Biocompatibility was further examined by incubating the synthesized NPs with hMSC cells for 24 h. The results were demonstrated that synthesized OE-Ag NPs presented excellent log₁₀ reduction in the growth of all the tested bacterial strains, which as statistically equivalent (p > 0.05) to the standard antibiotic drug. Moreover, they also demonstrated excellent cytotoxic efficacy against the MCF-7 carcinoma cells compared to plant lead extract and Com-Ag NPs. Green synthesized OE-Ag NPs appeared more biocompatible to hMSC and 293T cells compared to Com-Ag NPs. Excellent biological results of the OE-Ag NPs might be attributed to the synergetic effect of NPs’ properties and the adsorbed secondary metabolites of plant leaf extract. Hence, this study suggests that synthesized OE-Ag NPs can be a potential contender for their various biological and nutraceutical applications. Moreover, this study will open a new avenue to produce biocompatible nanoparticles with additional biological functionalities from the plants.     

Isolation of powerful antioxidants from the medicinal halophyte Limoniastrum guyonianum

The antioxidant capacities of the crude extract, aqueous and ethyl acetate partitions of Limoniastrum guyonianum Boiss. (Zita) were investigated in this study. The ethyl acetate phase exhibited a significant antioxidant activity as judged by total antioxidant activity, DPPH test and reducing power. Fractionation of this extract by centrifugal partition chromatography (CPC) using quaternary Arizona solvent systems composed of n-heptane/ethyl acetate/methanol/water led to ten fractions. The antioxidant capacities of these fractions were assessed using the same previous tests. Fraction 8 showed the highest antioxidant capacity (1291.1mg GAE/g DR), the power ability to quench DPPH radical (IC(50)=2μg/ml) and to reduce Fe(3+) (EC(50)=65μg/ml). From this fraction, three powerful flavonoids were isolated (1-3): gallocatechin (1), epigallocatechin (2) and epigallocatechin-3-O-gallate (3). These findings suggest that the antioxidative property of L. guynianum is may be related to the presence of these flavonoids, which can be used in various industrial fields.     

A New Method for Sentiment Analysis Using Contextual Auto-Encoders

Sentiment analysis, a hot research topic, presents new challenges for understanding users’ opinions and judgments expressed online. They aim to classify the subjective texts by assigning them a polarity label. In this paper, we introduce a novel machine learning framework using auto-encoders network to predict the sentiment polarity label at the word level and the sentence level. Inspired by the dimensionality reduction and the feature extraction capabilities of the auto-encoders, we propose a new model for distributed word vector representation “PMI-SA” using as input pointwise-mutual-information “PMI” word vectors. The resulted continuous word vectors are combined to represent a sentence. An unsupervised sentence embedding method, called Contextual Recursive Auto-Encoders “CoRAE”, is also developed for learning sentence representation. Indeed, CoRAE follows the basic idea of the recursive auto-encoders to deeply compose the vectors of words constituting the sentence, but without relying on any syntactic parse tree. The CoRAE model consists in combining recursively each word with its context words (neighbors’ words: previous and next) by considering the word order. A support vector machine classifier with fine-tuning technique is also used to show that our deep compositional representation model CoRAE improves significantly the accuracy of sentiment analysis task. Experimental results demonstrate that CoRAE remarkably outperforms several competitive baseline methods on two databases, namely, Sanders twitter corpus and Facebook comments corpus. The CoRAE model achieves an efficiency of 83.28% with the Facebook dataset and 97.57% with the Sanders dataset.     

Compensation schemes and performance analysis of jointly nonlinear amplifier and timing errors for CP-OFDM based cognitive radio networks

The principal objective of cognitive radio (CR) networks is to configure and share dynamically the spectrum resources in order to avoid user interference and congestion. This goal is limited by the effect of errors synchronization between primary and secondary users. In this paper, we study the impact of the asynchronism on the cyclic prefix-based orthogonal frequency division multiplexing modulation (CP-OFDM) including nonlinear HPA model. The considered system includes a reference primary user perfectly synchronized with its reference base station and Nsu interfering secondary users. We provide a new theoretical aspect of interference analysis in the context of the OFDM based CR network. Furthermore, on the basis of this analysis, we derive the accurate expression of bit error rate in the presence of a Rayleigh flat fading channel. Finally, to solve the problems of asynchronism and nonlinearity, a hybrid iterative method of compensation and parallel interference cancellation have been developed based on these two conditions.

     

Experimental Investigation of Passive Fault Tolerant Control for Induction Machine Using Sliding Mode Approach

This paper presents a passive fault tolerant control approach dedicated to stator inter‐turn short‐circuit fault of an induction machine. This control is based on sliding mode strategy and is implemented for validation on real‐time data acquisition and control platform. The proposed work highlights the integral sliding mode controller benefits during healthy and faulty operations. It can make the induction machine outputs to track their desired reference signals in finite‐time and allows to obtain a better dynamic response performances even in presence of fault. Moreover to avoid the use of a flux sensor, a second order sliding mode observer is used to estimate the rotor flux. Since the used observer converges in finite time, the closed‐loop stability of the proposed system (controller+observer) is proved using the Lyapunov stability theorem. Experimental results are conducted for squirrel cage induction machine to highlight the efficiency and applicability of the proposed fault tolerant control.     

Influence of sulfur fertilization on S-containing, phenolic, and carbohydrate metabolites in rosy garlic (Allium roseum L.): a wild edible species in North Africa

Allium roseum L., a North African endemic species, is a rich source of many important nutrients and bioactive compounds responsible for many promising beneficial health physiological effects. The influence of sulfur fertilization (S fertilization) on the flavor, total polyphenols, and carbohydrates content in A. roseum was studied, using three sulfur concentrations (0.01, 1.50 and 4.50 mmol L^?1) under controlled conditions. S fertilization showed a significant increase in the allicin concentration of A. roseum bulbs with an average of 0.859–2.285 g kg^?1 FW for bulbs grown at 0.01 and 1.50 mmol L^?1 SO₄ ^2?, respectively. The same trend was observed for total polyphenol content. On the contrary, the highest level of S decreased the content of reduced carbohydrates. These results provide evidence that the concentrations of allicin and polyphenols in A. roseum are increased by S fertilization, potentially amplifying its beneficial impacts on health.     

Environmental impacts of single and successive breakwaters along the Mediterranean coastline at Radès–Ezzahra, NE Tunisia

The coastline between Radès and Ezzahra, NE Tunisia, suffered from erosion during a strong storm in 1981. As a consequence, between 1985 and 1988, a single breakwater was constructed in Radès and two successive breakwaters in Ezzahra. The paper reports a study of the effectiveness of these structures and considers the other factors which influence the accretion/erosion of the shoreline.     

High level of laccases production by Trametes trogii culture on olive mill wastewater‐based media,application in textile dye decolorization

BACKGROUND: Laccases are receiving increasing attention as potential industrial enzymes in various applications. Therefore, it is important to find inexpensive and optimized media for large‐scale commercial production. The present work aims to valorize olive mill wastewater (OMW) by its use as base media for laccases production by Trametes trogii and use of the laccases produced for decolorizing textile dyes. RESULTS: A high yield of 25 120 U L^?1 of laccases was obtained at an OMW:water ratio of 80:20 enriched with 2 g L^?1 of urea corresponding to initial biochemical oxygen demand (BOD₅), chemical oxygen demand (COD) and total phenol concentrations of 18.4, 46 and 4.6 g L^?1 respectively. The partially purified laccases resulted in 85% decolorization of blue tubantin GLL 300 and black tubantin VSF 600, and 45% decolorization of blue solophenyl after 6 h of incubation. Subsequent additions of the same dye dose to the reaction mixture resulted in a very significant decrease in laccases activity after the third dye addition. CONCLUSION: The use of OMW for laccases production is a cost effective process. The laccases produced can be applied to the decolorization of textile wastewaters. Copyright © 2009 Society of Chemical Industry     

The worst-case analysis of the Garey–Johnson algorithm

The Garey–Johnson algorithm is a well known polynomial-time algorithm constructing an optimal schedule for the maximum lateness problem with unit execution time tasks, two parallel identical processors, precedence constraints and release times. The paper is concerned with the worst-case analysis of a generalization of the Garey–Johnson algorithm to the case of arbitrary number of processors. In contrast to other algorithms for the maximum lateness problem, the tight performance guarantee for the even number of processors differs from the tight performance guarantee for the odd number of processors.