Purification and characterization of an amylase from Opuntiaficus‐indica seeds

BACKGROUND: In Tunisia, prickly pear fruit grow spontaneously; it is consumed as fresh fruit, juice or jam. When the fruit is used for juice production, the seeds are discarded and go to waste. Our study aimed to extract biomolecules from seeds by producing value‐added products from the fruits. RESULTS: An amylase from Opuntia ficus‐indica seeds was extracted and purified to homogeneity. An increase in specific activity of 113‐fold was observed. The apparent molecular mass of the enzyme is 64 kDa. The optimum pH and temperature for enzyme activity were pH 5 and 60 °C, respectively. Under these conditions, the specific activity is 245.5 U mg^?1. The enzyme was activated by Co²⁺ and Mg²⁺ (relative activity 117% and 113% respectively) at lower ion concentrations. It was strongly inhibited by Mn²⁺ and Fe²⁺. Cu²⁺ inhibited totally the activity of this enzyme, but Ca²⁺ has an inhibitory effect which increases with ion concentration. CONCLUSION: The extracted enzyme belongs to the exo type of amylases and is classified as a β‐cyclodextrin glycosyltransferase since it generates mainly β‐cyclodextrin from starch. It exhibits high thermal stability and a broad range of pH stability, making it a promising prospect for industrial and food applications. Copyright © 2012 Society of Chemical Industry     

Purification of Bacillus licheniformis Lipase and its Application as an Additive in Detergent for Destaining

In this study, we aimed to optimize the nutritional and environmental conditions for the production of a novel lipase (LBL) from Bacillus licheniformis (GenBank accession no. MT118724). This strain was characterized by morphological and biochemical assays and Sanger sequencing of 16S rDNA. The crude lipolytic activity reached a maximum level 7.5 U mL⁻¹ at 40 °C and pH 8.0 using olive oil as substrate. Additionally, the crude enzyme maintained 100% of its initial activity after incubation for 1 h at 50 °C and pH 9.0. It is mandatory to note that LBL lipase displayed appreciable stability over a wide pH range and extreme temperatures. After purification, the optimal lipolytic activity was observed at pH 8.0 and 40 °C. LBL was shown to be a monomeric protein with an estimated molecular weight of 40 kDa. This novel lipase exhibited high stability and excellent compatibility compared to lipase extracted from Thermomyces lanuginosa (Lipolase® from Novozymes, Denmark) toward various detergents. Washing performance analysis revealed that it efficiently removes tomato sauce stain from cotton cloth. All these interesting enzymatic properties favor this new lipase as a potent candidate for applications in detergent formulations.     

Real-time H.264/AVC baseline decoder implementation on TMS320C6416

The H.264/AVC Advanced Video Coding standard (AVC) is poised to enable a wide range of applications. However, its increased complexity creates a big challenge for efficient software implementations. This work develops and optimises the H.264/AVC video decoder level two on the TMS320C6416 Digital Signal Processor (DSP) for video conference applications. In order to accelerate the decoding speed, several algorithmic optimisations have been ported to inverse entropy decoding and intra-prediction modules. The parallelism between algorithm execution and data transfers was fully exploited using Enhanced Direct Memory Access (EDMA) engine. Furthermore, based on the DSP architectural features, various core-specific optimisation techniques were adopted leading to an increase in speed by up to 70%. Intensive experimental tests prove that a real-time decoding on TMS320C6416 DSP running at 720?MHz is obtained for Common Intermediate Format resolution (CIF 352?×?288).     

Robust Arabic speech recognition in noisy environments using prosodic features and formant

This paper investigates the contribution of formants and prosodic features such as pitch and energy in Arabic speech recognition under real-life conditions. Our speech recognition system based on Hidden Markov Models (HMMs) is implemented using the HTK Toolkit. The front-end of the system combines features based on conventional Mel-Frequency Cepstral Coefficient (MFFC), prosodic information and formants. The experiments are performed on the ARADIGIT corpus which is a database of Arabic spoken words. The obtained results show that the resulting multivariate feature vectors, in noisy environment, lead to a significant improvement, up to 27%, in word accuracy relative the word accuracy obtained from the state-of-the-art MFCC-based system.     

Toward intrusion detection using belief decision trees for big data

Big data refers to datasets that we cannot manage with standard tools and within which lie valuable information previously hidden. New data mining techniques are needed to deal with the increasing size of such data, their complex structure as well as their veracity which is on covering questions of data imperfection and uncertainty. Even though big data veracity is often overlooked, it is very challenging and important for an accurate and reliable mining and knowledge discovery. This paper proposes MapReduce-based belief decision trees for big data as classifiers of uncertain large-scale datasets. The proposed averaging and conjunctive classification approaches are experimented for intrusion detection on KDD’99 massive intrusion dataset. Several granularity attacks’ levels have been considered depending on whether dealing with whole kind of attacks, or grouping them in categories or focusing on distinguishing normal and abnormal connections.     

Deployment and validation of out of band IP traceback approach (OBTA) in wireless mesh network

Wireless mesh networks (WMNs) have acquired recently enormous attention and momentum; therefore, security aspects have been a fundamental concern for them. Among catastrophic threats on WMNs, Denial‐of‐Service attacks that have become a severe danger because of their plug‐and‐play structural design. Unfortunately, preventing a Denial‐of‐Service attack presents a challenging issue. This fact is induced with the appearance of the source IP addresses spoofing. The resolution key of this issue is to reveal the attack source based on the path through which the attack packet passes. For this, many researchers in IP traceability field propose various methods and techniques to deal with the issue. In this article, we conceive a novel approach named out of band IP traceback approach in WMN (IEEE 802.11s). We create a new architecture using signaling messages for discovering the real source(s) of IP packets. Our solution is based on a security‐oriented signaling protocol. This protocol allows specialized signaling entities to communicate via reliable signaling information. This fact permits us to perform a simple and efficient traceback. In our novel approach, we use 2 radios: the first one transmits normal data packets whereas the second is reserved to exchange IP traceback information. The performance of the proposed scheme is analyzed via simulation analysis using the Network Simulator 3. The simulation results show that our scheme is efficient in dealing with the traceback problem in WMN environments.     

Characterization of physicochemical properties of As2Se3–GeTe–AgI chalcohalide glasses for solar cell and IR applications: influence of adding AgI

Journal of Materials Science: Materials in Electronics - This work deals with the study of the influence of adding AgI content on the physicochemical properties of...     

Modelling and solution approaches for the interconnected city logistics

Achieving a sustainable delivery of goods in urban areas has become a challenging task for service providers and logistics managers. Under this context, the physical internet (PI) Manifesto offers through its emergent concept of interconnected city logistics (ICL) a solution toward a more sustainable transportation of PI containers within cities. In this article, we explore the operational urban transportation problem of PI containers under ICL considerations. For this variant, built on the multiplicity of urban logistics centres and their interconnection, a comprehensive modelling approach is proposed to include key features such as multiple time periods, multi-zone urban coverage, heterogeneous fleets, multi-trip and multi-hub pickups, and delivery constraints. In order to deal with solvability issues encountered with realistic instances of the problem, a heuristic solution approach is developed. This is done with the objective to come up with solutions offering the best trade-offs between economic and ecological attributes within a short computational time. To validate the approach, a realistic set of instances is built with data inspired from city freight movements in an urban area in France. Using these experiments, the solvability of the model and the performance of our heuristic approach are discussed and managerial insights are derived.     

Integrated production,statistical process control,and maintenance policy for unreliable manufacturing systems

The objective of this paper is to develop an integrated approach for the joint control of production, maintenance and quality for batch manufacturing systems. We consider such systems that are subject to degradation which is at the origin of the production of defective units. The quality control of lots produced is performed using an ‘x-bar’ control chart. This graphical tool will allow estimating the quality of the batch being produced and possibly undertake perfect preventive or corrective maintenance actions on the production system. A buffer stock is built to maintain continuity of supply during maintenance actions. The incurred total cost includes setup cost, inventory costs, the cost of unused products, maintenance costs and quality costs. Decision variables include the buffer stock size, the sample size, the sampling interval, the surveillance and the control limits of the control chart. Numerical experiments and sensitivity analyses are provided to evaluate the effectiveness of the proposed control policy and the robustness of the solving approach.     

Characterization of virgin olive oil from Southern Tunisia

Fruits from three Tunisian cultivars of Olea europea L. grown in the southeast of Tunisia were harvested at the maturity stage of ripeness and immediately processed with a laboratory mill. There are as yet no data on the chemical composition of virgin olive oils from the southeast of Tunisia, an area characterized by an arid condition of growth for olive trees. Our results showed significant differences in the analytical parameters examined for the three cultivars such as fatty acid composition, total phenols and o‐diphenols, and the content of chlorophylls and carotenoids, confirming the importance of genetic factors in the chemical characteristics of the oil. Headspace solid‐phase microextraction (HS‐SPME) was applied to the analysis of volatile compounds of virgin olive oils. Forty‐eight compounds were isolated and characterized by GC‐RI and GC‐MS, representing 94.1–98.1% of the total amount. (E)‐Hex‐2‐enal, the main compound extracted by SPME, characterized the olive oil headspace for all samples. So, it was clearly shown that there were qualitative and quantitative differences in the proportion of volatile constituents from oils of the various cultivars.