Microstructure and Sliding Wear Behaviour of Ni(Cr)-TiB_2 Coatings Deposited by HVOF Spraying of SHS Powders

THERMAL SPRAYING provides a large range ofcoatings,which increase the wear resistance ofsubstrates[1].One of the major coating families is thecermet,composed of hard ceramic particles with ametallic binder.The most commonly used cermetcoatings in industrial applications are based on eitherthe WC-Co or the Cr3C2-Ni(Cr)systems with WC-17wt%Co and Cr3C2-25wt%Ni(Cr)being typicalcompositions[2,3].Although WC-Co deposits are hardand wear resistant at ambient temperatures their rangeof ap…     

Preparation and Characterization of Magnetite–Chitosan Nanoparticles and Evaluation of Their Cytotoxicity Effects on MCF7 and Fibroblast Cells

Nowadays, magnetic nanoparticles play a key role in drug treatment. However, if they are uncoated, they might aggregate and cause embolism in drug delivery. To avoid this, they are generally coated with polymers. In this investigation, magnetic nanoparticles (MNPs) were coated with chitosan through in situ co-precipitation process and their properties in addition to their cytotoxicity in MCF7 and fibroblast cells were analyzed. The results showed MNPs–chitosan nanoparticles would contain an average mean diameter of 32 nm and a saturation magnetization (M _S) value of 38.87 emu/g. To characterize the synthesized nanoparticles in terms of structural, morphological and magnetic properties, Fourier transform infrared (FTIR), X-ray diffraction (XRD), scanning electron microscopy (SEM), transmission electron microscopy (TEM), thermal gravimetric analysis (TGA) and vibrating sample magnetometry (VSM) studies were used. Toxicity test was also done to investigate whether their presence would cause any toxicity in the body; in addition, antibacterial assay was done to analyze if nanoparticles could be used as an antimicrobial agent.     

The voting analytic hierarchy process method for discriminating among efficient decision making units in data envelopment analysis

Making optimal use of available resources has always been of interest to humankind, and different approaches have been used in an attempt to make maximum use of existing resources. Limitations of capital, manpower, energy, etc., have led managers to seek ways for optimally using such resources. In fact, being informed of the performance of the units under the supervision of a manager is the most important task with regard to making sensible decisions for managing them. Data envelopment analysis (DEA) suggests an appropriate method for evaluating the efficiency of homogeneous units with multiple inputs and multiple outputs. DEA models classify decision making units (DMUs) into efficient and inefficient ones. However, in most cases, managers and researchers are interested in ranking the units and selecting the best DMU. Various scientific models have been proposed by researchers for ranking DMUs. Each of these models has some weakness(es), which makes it difficult to select the appropriate ranking model. This paper presents a method for ranking efficient DMUs by the voting analytic hierarchy process (VAHP). The paper reviews some ranking models in DEA and discusses their strengths and weaknesses. Then, we provide the method for ranking efficient DMUs by VAHP. Finally we give an example to illustrate our approach and then the new method is employed to rank efficient units in a real world problem.     

Characterization of renal tumours based on Raman spectra classification

In this study, we propose to evaluate the potential of Raman spectroscopy (RS) to assess renal tumours at surgery. Different classes of Raman renal spectra acquired during a clinical protocol are discriminated using support vector machines classifiers. The influence on the classification scores of various preprocessing steps generally involved in RS are also investigated and evaluated in the particular context of renal tumour characterization. Encouraging results show the interest of RS to evaluate kidney cancer and suggest the potential of this technique as a surgical assistance during partial nephrectomy.     

User Activities Outliers Detection; Integration of Statistical and Computational Intelligence Techniques

In this article, a hybrid technique for user activities outliers detection is introduced. The hybrid technique consists of a two‐stage integration of principal component analysis and fuzzy rule‐based systems. In the first stage, the Hamming distance is used to measure the differences between different activities. Principal component analysis is then applied to the distance measures to find two indices of Hotelling's T² and squared prediction error. In the second stage of the process, the calculated indices are provided as inputs to the fuzzy rule‐based systems to model them heuristically. The model is used to identify the outliers and classify them. The proposed system is tested in real home environments, equipped with appropriate sensory devices, to identify outliers in the activities of daily living of the user. Three case studies are reported to demonstrate the effectiveness of the proposed system. The proposed system successfully identifies the outliers in activities distinguishing between the normal and abnormal behavioral patterns.     

Local commute-time guided MDS for 3D non-rigid object retrieval

In this paper, we propose a 3D non-rigid shape retrieval method based on canonical shape analysis. Our main idea is to transform the problem of non-rigid shape retrieval into a rigid shape retrieval problem via the well-known multidimensional scaling (MDS) approach and random walk on graphs. We first segment the non-rigid shape into local partitions based on its salient features. Then, we calculate a local MDS problem for each partition, where the local commute time distance is used as weighting function in order to preserve local shape details. Finally, we aggregate the set of local MDS problems as a global constrained problem. The constraint is formulated using the biharmonic function between local salient features. In contrast to MDS method, the proposed local MDS is computationally efficient, parameters free and gives isometry-invariant forms with minimum features distortion. Due to these advantageous properties, the proposed method achieved good retrieval accuracy on non-rigid shape benchmark datasets.     

Thermal,structural, and optical properties of γ‐irradiated poly(vinyl alcohol)/poly(ethylene glycol) thin film

Poly(vinyl alcohol)/poly(ethylene glycol) (PVA/PEG) copolymer was prepared using casting technique. The obtained PVA/PEG thin films have been irradiated with gamma rays with doses ranging from 1.5 to 20 Gy. The resultant effect of gamma irradiation on the thermal properties of PVA/PEG has been investigated using thermogravimetric analysis (TGA) and differential thermal analysis (DTA). The onset temperature of decomposition T_o and activation energy of thermal decomposition E_a were calculated, results indicating that the PVA/PEG thin film decomposes in one main weight loss stage. Also, the gamma irradiation in dose range 4–12 Gy led to a more compact structure of PVA/PEG copolymer, which resulted in an improvement in its thermal stability with an increase in the activation energy of thermal decomposition. The variation of transition temperatures with gamma dose has been determined using DTA. The PVA/PEG thermograms were characterized by the appearance of an endothermic peak due to melting of crystalline phase. In addition, structural property studies using X‐ray diffraction and infrared spectroscopy were performed on both nonirradiated and irradiated samples. Furthermore, the transmission of the PVA/PEG samples and any color changes were studied. The color intensity (E was greatly increased with increasing the gamma dose and was accompanied by a significant increase in the blue and green color components. © 2011 Wiley Periodicals, Inc. J Appl Polym Sci, 2012     

Compositional characteristics and aromatic profile of date palm seeds from seven varieties grown in Tunisia

This paper reports a discrimination study based on the physico‐chemical characteristics, fatty acids and profile of volatile compounds of the seeds from seven date palm varieties (Phoenix dactylifera L.) grown in Tunisia. Date seeds contained 10.49–14.76% moisture; 6.28–11.2% fat (on a dry weight basis); 2.67–12.85% protein; 0.91–6.06% reducing sugar; 0.61–2.98% sucrose and 0.97–1.17% ash. Gas liquid chromatography revealed that the oil fraction of the date palm seeds contained eighteen fatty acids, with oleic acid (30.77–42.50%) and lauric acid (18.51–27.48%) as the main unsaturated and saturated ones. Volatile profile showed differences among varieties. In total, forty‐five compounds were identified, mainly alcohols, aldehydes and unsaturated hydrocarbons ones. This study provides evidence that the seeds of date may be a potential source of valuable nutrients with interesting functionality.