École Mohammadia d'ingénieurs

Abstract: Like other heavy metals, Cr (VI) is a powerful carcinogen and mutagen agent. Its toxic effects on plants are well considered. In order to elucidate its adverse effects, the present work aims to study the mitosis aberrations of Cr (VI) on the Vicia faba root-cells and its molecular docking analysis to understand the genotoxicity mechanisms. In-vivo, Vicia faba plants were exposed to 50 and 100 μM Cr (VI) for 48 h. In-silico, molecular docking and molecular dynamics simulation were used to study the interactions between dichromate and tubulin tyrosine ligase T2R-TTL (PDBID: 5XIW) with reference to Colchicine (microtubule inhibitor). According to our results, Cr (VI) affects growth and cell division and also induces many mitosis aberrations such as chromosome sticking, anaphase/telophase bridges, lagging chromosomes and fragmentation during all phases of mitosis. On the one hand, Cr (VI) reduces mitotic index and promotes micronuclei induction. The in-silico results showed that dichromate establishes very strong bonds at the binding site of the tubulin tyrosine ligase T2R-TTL, with a binding affinity of −5.17 Kcal/Mol and an inhibition constant of 163.59 μM. These interactions are similar to those of colchicine with this protein, so dichromate could be a very potent inhibitor of this protein's activity. TTL plays a fundamental role in the tyrosination/detyrosination of tubulin, which is crucial to the regulation of the microtubule cytoskeleton. Its inhibition leads to the appearance of many morphogenic abnormalities such as mitosis aberrations. In conclusion, our data confirm the highest genotoxicity effects of Cr (VI) on Vicia faba root-cells.

Abstract: Wireless communication is used in many different situations such as mobile telephony, radio and TV broadcasting, satellite communication, wireless LANs, and military operations. In each of these situations a frequency assignment problem arises with application-specific characteristics. Researchers have developed different modelling ideas for each of the features of the problem, such as the handling of interference among radio signals, the availability of frequencies, and the optimization criterion. This paper presents a new approach for solving the problem of frequency allocation based on using initially a partial solution respecting all constraints according to a greedy algorithm. This partial solution is then used for the construction of our stimulation in the form of a neural network. In a second step, the approach will use searching techniques used in conjunction with iterative algorithms for the optimization of the parameters and topology of the network. The iterative algorithms used are named hierarchical genetic algorithms (HGA). Our approach has been tested on standard benchmark problems called Philadelphia problems of frequency assignment. The results obtained are equivalent to those of current methods. Moreover, our approach shows more efficiency in terms of flexibility and autonomy.

Abstract: The interest in trust-based routing protocols has grown with the advancements achieved in ad-hoc wireless networks.However, regardless of the many security approaches and trust metrics available, trust-based routing still faces some security challenges, especially with respect to privacy. In this paper, we propose a novel trust-based routing protocol based on a fully homomorphic encryption scheme. The new protocol allows nodes, which collaborate in a dynamic environment, to evaluate their knowledge on the trustworthiness of specific routes and securely share this knowledge.

Abstract: The graph model enables a broad range of analysis, thus graph processing is an invaluable tool in data analytics. At the heart of every graph processing system lies a concurrent graph data structure that stores the graph. Such a data structure needs to be highly efficient for both graph algorithms and queries. Due to the continuous evolution, the sparsity, and the scale-free nature of real-world graphs, graph processing systems face the challenge of providing an appropriate graph data structure that enables both fast analytical workloads and low-memory fast graph mutations. Existing graph structures offer a hard tradeoff between read-only performance, update friendliness, and memory consumption upon updates. In this paper, we introduce CSR++, a new graph data structure that removes these tradeoffs and enables both fast read-only analytics and quick and memory-friendly mutations. CSR++ combines ideas from CSR, the fastest read-only data structure, and adjacency lists to achieve the best of both worlds. We compare CSR++ to CSR, adjacency lists from the Boost Graph Library, as well as state-of-the-art update-friendly graph structures: LLAMA, STINGER, GraphOne, and Teseo. In our evaluation, which is based on popular graph processing algorithms executed over real-world graphs, we show that CSR++ remains close to CSR in read-only concurrent performance (within 10% on average), while significantly outperforming CSR (by an order of magnitude) and LLAMA (by almost 2×) with frequent updates. We also show that both CSR++’s update throughput and analytics performance exceed that of several state-of-the-art graph structures, while maintaining low memory consumption when the workload includes updates.