Phytoextract assisted hydrothermal synthesis of ZnO–NiO nanocomposites using neem leaves extract

This work represents the synthesis of zinc oxide nanorods, nickel oxide nanoparticles, and zinc oxide-nickel oxide nanocomposites by combining Neem leave extract with hydrothermal synthesis. Five samples were prepared by green synthesis which is based on Neem leaves aqueous extract followed by hydrothermal treatment at 250 °C for 2.5 h. The five prepared samples are: 100% NiO (N100), 75% NiO: 25% ZnO (Z25-N75), 50% NiO: 50% ZnO (Z50-N50), 25% NiO: 75% ZnO (Z75-N25), and 100% ZnO (Z100). The prepared nanoparticles and nanocomposites were characterized by FTIR, XRD, SEM, and TEM. The XRD results show that the ZnO formed as a hexagonal wurtzite phase and NiO as a cubic phase. The microstructure of the formed samples is versatile with nanorods ZnO and spherical NiO. The nanocomposites microstructure appears as a heterostructure of both oxides with NiO particles on the surface of ZnO rods. The TEM confirms the nanosize and the crystallinity of samples.     

Liquid-liquid extraction of metal ions,DFT and TD-DFT analysis for some pyrane derivatives with high selectivity for Fe(II) and Pb(II)

Liquid-liquid extraction of metal ions using pyrane derivatives was studied. Fe²⁺, Zn²⁺, Cu²⁺, Co²⁺, Cd²⁺, Ni²⁺, and Pb²⁺ were extracted from the aqueous phase into the organic phase and the extractability for each metal was determined by atomic absorption. Interestingly, a competitive extraction was also investigated and then examined at different pH in order to explore the effect of the different substituent groups on metal extraction. We found high selectivity towards Fe²⁺ (91.8%) and Pb²⁺ (90.7%). In addition, geometry optimizations of the ground and excited-states of the selective ligands in order to get better insight into the geometry and the electronic structure were carried out by DFT and TD-DFT calculations.     

Evolutionary Algorithsm with Machine Learning Based Epileptic Seizure Detection Model

Machine learning (ML) becomes a familiar topic among decision makers in several domains, particularly healthcare. Effective design of ML models assists to detect and classify the occurrence of diseases using healthcare data. Besides, the parameter tuning of the ML models is also essential to accomplish effective classification results. This article develops a novel red colobuses monkey optimization with kernel extreme learning machine (RCMO-KELM) technique for epileptic seizure detection and classification. The proposed RCMO-KELM technique initially extracts the chaotic, time, and frequency domain features in the actual EEG signals. In addition, the min-max normalization approach is employed for the pre-processing of the EEG signals. Moreover, KELM model is used for the detection and classification of epileptic seizures utilizing EEG signal. Furthermore, the RCMO technique was utilized for the optimal parameter tuning of the KELM technique in such a way that the overall detection outcomes can be considerably enhanced. The experimental result analysis of the RCMO-KELM technique has been examined using benchmark dataset and the results are inspected under several aspects. The comparative result analysis reported the better outcomes of the RCMO-KELM technique over the recent approaches with the of 0.956.     

Une plate-forme de validation multi-protocoles et multi-services Résultats d’expérimentation

This article presents the implementation of a validation platform based on formal methods and the experimental results obtained. This platform allows performing conformance and interoperability tests, analysing the specification and constructing a performance model for the services. It covers all stages of the validation which are: formal specification, test architecture definition, test generation and execution for the defined architecture, and performance evaluation. The test methods and architectures used here make it easier to detect and localise errors. The platform has been constructed within the framework of theRnrt (National Telecommunications Research Network) platform project, platonis. This platform is composed of a network integrating the different sites of the project partners. The principal application domains for the platform are telecommunication systems and mobile telephony. In particular, two different cases study are presented that illustrate the platform’s applicability to the test of mobile 3rd generation protocols and services usingWap, gprs andUmts. Nevertheless, the platform is generic and can be used for other types of communication protocols and services.     

The Effects of Physical Layer on the Routing Wireless Protocol

Mobile ad hoc networks (MANETs) are characterized by multiple entities, a frequently changing network topology and the need for efficient dynamic routing protocols. In MANETs, nodes are usually powered by batteries. Power control is tightly coupled with both the physical and medium access layers (MACs). However, if we increase the transmission power, at the same time we increase the interference to other nodes which diminish the transport capacity of wireless systems. Thus, the routing protocols based on hop count metric suffer from performance degradation when they operate over MANET. Routing in ad hoc wireless networks is not only a problem of finding a route with shortest length, but it is also a problem of finding a stable and good quality communication route in order to avoid any unnecessary packet loss. Cross-layer design of ad hoc wireless networks has been receiving increasing attention recently. Part of these researches suggests that routing should take into account physical layer characteristics. The goal of this paper is to improve the routing reliability in MANET and to reduce power consumption through cross-layer approach among physical, MAC and network layers. The proposed cross-layer approach is based on signal to interference plus noise ratio (SINR) and received signal strength indication (RSSI) coming from the physical layer. This solution performs in one hand the ad hoc on-demand distance vector routing protocol by choosing reliable routes with less interferences using SINR metric and in another hand; it permits to reduce the power transmission when sending the data packets by using RSSI metric.     

A Novel Mapping Technique for an Adaptive Length of Codes in SAC-OCDMA Systems

Wireless Personal Communications - In this paper an adaptive mapping technique (AMT) is proposed for spectral amplitude coding-optical code division multiple access (SAC-OCDMA) system. The main...     

CFD analysis of a supersonic air ejector. Part II: Relation between global operation and local flow features

This paper presents an original CFD analysis of the operation of a supersonic ejector. This study is based on CFD and experimental results obtained in the first part paper [A. Hemidi, F. Henry, S. Leclaire, J. M. Seynhaeve, Y. Bartosiewicz, Experimental and numerical analysis of the operation curve of a supersonic ejector, single-phase and two-phase operation, Submitted to Applied Thermal Engineering]. Results clearly demonstrates that a good predictions of the entrainment rate, even over a wide range of operating conditions, do not necessarily mean a good prediction of the local flow features. This issue is shown through the results obtained for two turbulence models, and also raises the problem of their assessment. In addition, an analysis based on the sonic line location in order to locate the choking cross-section is proposed in this paper. Based on this approach, this parameter allowed to propose an explanation of such disparities between good predictions of overall performances and significant discrepancies of local flow parameters.     

Building robust wavelet estimators for multicomponent images using Stein's principle.

Multichannel imaging systems provide several observations of the same scene which are often corrupted by noise. In this paper, we are interested in multispectral image denoising in the wavelet domain. We adopt a multivariate statistical approach in order to exploit the correlations existing between the different spectral components. Our main contribution is the application of Stein's principle to build a new estimator for arbitrary multichannel images embedded in additive Gaussian noise. Simulation tests carried out on optical satellite images show that the proposed method outperforms conventional wavelet shrinkage techniques.     

Two‐dimensional gel electrophoresis of apolipoprotein C‐III and other serum glycoproteins for the combined screening of human congenital disorders of O‐ and N‐glycosylation

Congenital disorders of glycosylation (CDG) are inherited diseases that can affect not only the N‐glycan (e.g. CDG type I and II) but also the O‐glycan biosynthesis pathway. In the absence of specific clinical symptoms, there is a need for a reliable biological screening of these two groups of CDG. Using a few microlitres of human serum, 2‐DE and immunoblotting were applied to the separation and simultaneous detection of the isoforms of the O‐glycosylated protein apolipoprotein C‐III (apoC‐III) and of four N‐glycosylated proteins, namely alpha‐antitrypsin, alpha‐1 acid glycoprotein, haptoglobin and transferrin. For the study of O‐glycosylation, this technique allowed the reliable separation of the three fractions of apoC‐III and the determination of normal percentage values in an adult population. Concerning N‐glycosylation, the study of serum samples from patients with CDG type Ia revealed marked abnormalities systematically affecting the four 2‐DE separated N‐linked glycoproteins. 2‐DE coupled to immunoblotting using a mixture of specific antibodies could be easily and reliably employed for the combined screening of both N‐ and O‐glycosylation disorders in humans.