Numerical study of thermal aspects of electric discharge machining process

This paper presents numerical results concerning the temperature distribution due to electric discharge machining process. From these thermal results, the material removal rate and the total roughness are deduced and compared with experimental observations. It is shown that taking into account the temperature variation of conductivity is of crucial importance and gives the better correlations with experimental data.     

Differential Impact of Sex on Seasonal Changes in Mantle and Tentacle Phospholipids and Triacylglycerols in Sepia officinalis

The aim of the present work was to study the effect of season on phospholipids and triacylglycerols (TAG) of mantle and tentacles of female and male wild Sepia officinalis. The identified phospholipids were phosphatidylethanolamine (PtdEtn), phosphatidylcholine (PtdCho), phosphatidylserine (PtdSer), and phosphatidylinositol (PtdIns), and PtdEtn was the major fraction. Results showed apparent seasonal variation of phospholipid content, particularly with female samples. Fatty acid composition of phospholipid classes showed a differentiation much more in the proportions than in the diversity of fatty acids. Results showed that the major saturated fatty acids were 16:0 and 18:0, the major monounsaturated fatty acids were 18:1 and 20:l, and the major polyunsaturated fatty acids were docosahexaenoic acid (22:6n-3) (DHA) and eicosapentaenoic acid (20:5n-3) (EPA). The results relative to TAG demonstrated significant variations. Principal component analysis confirmed the seasonal and sexual effects. This study could be appropriate for the improvement of consistent monitoring of phospholipid and TAG accumulation in cephalopod, which might be important for both physiological studies and food industries.     

Treatment of a mixture of three pesticides by photo- and electro-Fenton processes

In the present work, a comparative study of a mixture of three pesticides (chlortoluron, carbofuran and bentazon) has been investigated by advanced oxidation processes such as photo-Fenton and electro-Fenton. These processes are based on the in situ production of hydroxyl radical, a highly strong oxidant, which allows the degradation of organic pollutants until their mineralization into CO₂ and H₂O. For the photo-Fenton process, the effect of key parameters such as initial catalyst (Fe³⁺) concentration and hydrogen peroxide (H₂O₂) dosage were studied. Under optimal operating conditions, the evolution of total organic carbon (TOC) has been investigated for the two processes. Obtained results showed that more than 90% of TOC removal was obtained after only 2 h of photo-Fenton treatment whereas the electro-Fenton process needed 8 h of treatment. Nevertheless, the comparison of cost treatment shows that the photo-Fenton process is more expensive than electro-Fenton. The evolution of pesticide's concentration during treatment was determined by high performance liquid chromatography (HPLC). Inorganic ions released such as chloride, nitrate, sulphate and ammonium ions are identified and their kinetic evolution was measured by ion chromatographic analyses.     

Oxaphosphole‐Based Monophosphorus Ligands for Palladium‐Catalyzed Amination Reactions

A novel class of C‐2‐substituted oxaphosphole‐based monophosphines 1–4 has been synthesized. Palladium complexes derived from these ligands and their C‐2‐unsubstituted analogs provide general catalysts for amination reactions of challenging aryl and heteroaryl halides with sterically hindered anilines and alkylamines.     

Enabling heterogeneous cycle-based and event-driven simulation in a design flow integrated using the SPIRIT consortium specifications

The practical application of electronic system-level (ESL) design has been a key challenge of transaction-level modeling (TLM) methodologies in the past few years. While the benefits of ESL are well known, making the investment pay-off has required two key factors to be resolved: the simulation speed of the virtual platform model has to be fast enough to enable software design, and the flow from ESL design to implementation has to be seamless. We introduce two themes to address these issues: cycle-based simulation and a multi-vendor design-flow integrated using the IP-XACT^TM specifications from The SPIRIT Consortium. Through experimentation with the ARM RealView^® SoC Designer flow, and the Synopsys coreAssembler tool and Galaxy suite of tools, we show that competent solutions to both of these adoption issues exist in the industry today.     

An early development of the nonenal potential in the malting process

The scarce knowledge of the significance of enzymatic oxidation of polyunsaturated fatty acids throughout the malting process led the authors to conduct studies on the monitoring of a set of selected parameters involved in the reaction. Lipoxygenase (LOX) activity, the nonenal potential, the temperature and the moisture content were assessed for the top and bottom malt layers in various stages of an industrial kilning process. Significant differences were obtained between the lower and upper malt bed, suggesting that the moisture content and temperature gradient play a key role on the production of E-2-nonenal during the early stages of kilning. The residual nonenal potential already present in the finished malt (malt-RNP) may account for approximately 25% of the total nonenal potential in the mash, depending on the residual LOX activity. LOX showed a good degree of relationship with the nonenal potential for micro-malts (r=0.79, p<0.05), whereas for commercial malts no correlation was found. These results suggest that the malt-RNP plays a prominent role for commercial malts, probably owing to the great heterogeneity observed for the malt bed in the industrial kiln. On the other hand, a major role of LOX during mashing was observed for micro-malts, emphasizing that the intrinsic properties of the barley and malt may be overwhelmed by technological factors. Therefore, kilning programmes should be adopted in order to minimize formation of malt-RNP during the drying phase of the malting process.     

Machine translation between Hebrew and Arabic

Hebrew and Arabic are related but mutually incomprehensible languages with complex morphology and scarce parallel corpora. Machine translation between the two languages is therefore interesting and challenging. We discuss similarities and differences between Hebrew and Arabic, the benefits and challenges that they induce, respectively, and their implications on machine translation. We highlight the shortcomings of using English as a pivot language and advocate a direct, transfer-based and linguistically-informed (but still statistical, and hence scalable) approach. We report preliminary results of the two systems we are currently developing, for translation in both directions.     

A finite mixture model for simultaneous high-dimensional clustering, localized feature selection and outlier rejection

Model-based approaches and in particular finite mixture models are widely used for data clustering which is a crucial step in several applications of practical importance. Indeed, many pattern recognition, computer vision and image processing applications can be approached as feature space clustering problems. For complex high-dimensional data, however, the use of these approaches presents several challenges such as the presence of many irrelevant features which may affect the speed and also compromise the accuracy of the used learning algorithm. Another problem is the presence of outliers which potentially influence the resulting model’s parameters. For this purpose, we propose and discuss an algorithm that partitions a given data set without a priori information about the number of clusters, the saliency of the features or the number of outliers. We illustrate the performance of our approach using different applications involving synthetic data, real data and objects shape clustering.     

Spatial color image segmentation based on finite non-Gaussian mixture models

Finite mixture models are one of the most widely and commonly used probabilistic techniques for image segmentation. Although the most well known and commonly used distribution when considering mixture models is the Gaussian, it is certainly not the best approximation for image segmentation and other related image processing problems. In this paper, we propose and investigate the use of several other mixture models based namely on Dirichlet, generalized Dirichlet and Beta–Liouville distributions, which offer more flexibility in data modeling, for image segmentation. A maximum likelihood (ML) based algorithm is applied for estimating the resulted segmentation model’s parameters. Spatial information is also employed for figuring out the number of regions in an image and several color spaces are investigated and compared. The experimental results show that the proposed segmentation framework yields good overall performance, on various color scenes, that is better than comparable techniques.