Melting of multipass surface tracks in steel incorporating titanium carbide powders

Overlapping tracks were processed by melting preplaced titanium carbide (TiC) powder on steel surfaces using a tungsten inert gas torch. The tracks produced ～1·0 mm melt depth free from cracks, but occasional pores were observed. The microstructure consisted of unmelted and partially melted TiC particulates together with reprecipitated TiC particles, which were prominent in tracks processed in the initial stage. A greater number of reprecipitated globular and cubic TiC particles were observed in tracks processed in the later stages, indicating more dissolution of TiC particulates from the overlapping operation. Those multitracks processed in the initial stage developed a maximum hardness of 850–1000 HV, which was lower in most other tracks, although comparable hardness values were recorded in the last track.     

Secure and economic management of a power system in the presence of wind generation

Nowadays, large-scale integration of wind power is a challenge in terms of the minimization of the insecurity risk, that is, of the expected cost associated with the expected load not served. In fact, when there is an elevated proportion of wind power, the electrical power quality in the sense of continuity of supply may be low, since energy from wind power cannot be dispatched in the classical sense and its output varies as weather conditions change. However, continuity of supply may also be undermined by other uncertain factors, such as the occurrence of random events like line outages, generator failures or sudden demand variations. Assuming the insecurity risk as a part of the overall expected cost for a secure management of a deregulated power system, this paper proposes a DC formulation of an AC Economically correct Secure Economic Dispatch (EcSED), modified also for the introduction of uncertain Wind Power Generation (WPG) sources. Finally, simulations were carried out in order to investigate how the above overall expected cost changes, as a function of varying penetration levels and varying installation locations of a WPG plant.     

Structure optimization of neural network for dynamic system modeling using multi-objective genetic algorithm

The problem of constructing an adequate and parsimonious neural network topology for modeling non-linear dynamic system is studied and investigated. Neural networks have been shown to perform function approximation and represent dynamic systems. The network structures are usually guessed or selected in accordance with the designer’s prior knowledge. However, the multiplicity of the model parameters makes it troublesome to get an optimum structure. In this paper, an alternative algorithm based on a multi-objective optimization algorithm is proposed. The developed neural network model should fulfil two criteria or objectives namely good predictive accuracy and minimum model structure. The result shows that the proposed algorithm is able to identify simulated examples correctly, and identifies the adequate model for real process data based on a set of solutions called the Pareto optimal set, from which the best network can be selected.     

Synthesis and Electrochemical Properties of LaCr<Subscript>1−x</Subscript>Co<Subscript>x</Subscript>O<Subscript>3</Subscript> (0 ≤ x ≤ 0.5) via Co-precipitation Method

Perovskite LaCr_1?xCo_xO₃ (0 ≤ x ≤ 0.5) oxides synthesized by co precipitation method were investigated. X-ray diffraction, thermo gravimetric and differential thermal analysis, Fourier transform infrared spectroscopy, scanning electron microscopy (SEM) and electrochemical measurements, were used to characterize the structure, morphology, electrochemical properties of the samples. The studied compounds have orthorhombic and rhombohedral systems in the ranges (0 ≤ x ≤ 0.2) and (0.3 ≤ x ≤ 0.5) respectively. Thermal analysis results indicate that the pure phase was obtained at temperature above 800 °C. The structure and morphology of the samples characterized by SEM measurements indicate that particles have nearly spherical shapes and are agglomerated. The electrochemical measurements indicate that the catalytic activity is strongly influenced by cobalt doping. The highest electrode performance is achieved with large cobalt content.     

A Method for the Detection of Potential Fraud of Bringing Feline Meat in Food Chain

Adulteration of meat in processed food is a sensitive issue since certain meat species are prohibited in some religions such as Islam and Judaism. Some meat types are also potential carrier of some deadly diseases such as severe acute respiratory syndrome, anthrax, and hepatitis. Furthermore, unconscious consumption of certain meat might lead to an allergic reaction. Feline meat is not only taboo in most cultures but also under religious prohibition. However, cat meat has been consumed in certain countries including Cambodia, South Korea, China, and Vietnam. Several polymerase chain reaction assays are proposed for the detection of feline meat. However, those assays are not tested under processed food matrices. They are also based on longer targets (672, 331, 274, 180, and 108 bp) which breakdown under compromised states. Here we documented a very short-amplicon-length (69 bp) polymerase chain reaction assay and produced strong evidence that short targets are more stable than the longer ones. Feline specificity was confirmed by cross-challenging against 17 non-target species and target stability was tested after boiling, microwaving, and autoclaving treatments under complex matrices. The tested detection limit was 0.01% (w/w) of feline meat in ternary mixtures and 0.1% (w/w) in cooked meatballs.     

Composition of peel essential oils from four selected Tunisian Citrus species: Evidence for the genotypic influence

The peel essential oils from four selected Tunisian Citrus species: sweet orange (Citrus sinensis Osbeck), mandarin (Citrus reticulata Blanco); sour orange (Citrus aurantium L.) and pummelo (Citrus grandis Osbeck), cultivated under the same pedoclimatic and cultural conditions have been analysed by gas chromatography (GC) and gas chromatography–mass spectrometry (GC–MS). The essential oils content ranged from 1.06% to 4.62% (w/w) in pummelo and mandarin, respectively. The qualitative and quantitative analysis led to the identification of 70 components in all oil samples. The analysed oils consist mainly in monoterpene hydrocarbons (97.59–99.3%), with limonene (92.52–97.3%) and β-pinene (1.37–1.82) being the major constituents. The remaining chemical classes were weakly represented (<1%). Both qualitative and quantitative differences between oil samples have been observed and numerous components have been proposed as marker compounds. Since the influence of different environmental factors has been eliminated, the observed chemical variability between the studied species and cultivars seems likely to results from the genetic variability.