Knowledge-based systems using neural networks for electron beam welding process of reactive material (Zircaloy-4)

Bead-on-plate welding of zircaloy-4 (a reactive material) plates was conducted using electron beam according to central composite design of experiments. Its predictive models were developed in the form of knowledge-based systems in both forward and reverse directions using neural networks. Input parameters considered for this welding of reactive metals were accelerating voltage, beam current and weld speed. The responses of the welding process were measured in terms of bead width, depth of penetration and micro-hardness. Forward mapping of the welding process was conducted using regression analysis, back-propagation neural network (BPNN), genetic algorithm-tuned neural network (GANN) and particle swarm optimization algorithm-tuned neural network (PSONN). Reverse mapping of this process was also carried out using the BPNN, GANN and PSONN-based approaches. Neural network-based approaches could model this welding process of reactive material in both forward and reverse directions efficiently, which is required for the automation of the same. The performance of the neural network models was found to be data-dependent. The BPNN could outperform the other two approaches for most of the cases but not all in both the forward and reverse mappings.     

Catalysts based in cerium oxide for wet oxidation of acrylic acid in the prevention of environmental risks

Acrylic acid is a refractory compound for the non-catalytic wet oxidation (WO) process and can seriously damage the environment when released in industrial effluents. Oxidation of acrylic acid by catalytic wet oxidation (CWO) was studied in slurry conditions in a high-pressure batch reactor at 200 °C and 15 bar of oxygen partial pressure. Several solid cerium-based catalysts prepared in our laboratory were used (Ag/Ce, Co/Ce, Mn/Ce, CeO, MnO) and evaluated in terms of activity, selectivity and stability. Mn/Ce shows the higher activity in 2 h with 97.7% reduction of total organic carbon (TOC) followed by: MnO(95.5%)>Ag/Ce(85.0%)>Co/Ce(65.1%)>CeO(61.2%). Attempts were also carried out to analyze the influence of different Mn/Ce molar ratios. High percentages of Mn lead to practically total organic carbon concentration (TOC) abatements while low ratios lead to the formation of non-oxidizable compounds. Acrylic acid was readily degraded by all the catalysts pointing out the high importance of using a catalytic process. pH was an indicator of the reaction pathway and acetic acid was found as the major reaction intermediate compound; however it is completely oxidized after 2 h with exception for Co/Ce, CeO and MnO. Carbon adsorption and leaching of metals were poorly found for Mn/Ce indicating high stability. The catalyst microstructure after the reaction was analyzed and formation of whiskers of β-MnO₂ (or less probably MnOOH) were observed at the catalyst surface. Therefore, Mn/Ce revealed to be a promising catalyst for the treatment of effluents containing acrylic acid; nevertheless, its commercialization depends on further research.     

Structure of Polymeric PbTiO3 Gels

The structural features of PbTiO₃ gels were found to be highly dependent on hydrolysis conditions. Gels formed from acid-catalyzed solutions were clear and rubbery, whereas base-catalyzed gels were translucent or cloudy with phase separation. Direct TEM observations determined that acid-catalyzed gels were fibrous in character and physically homogeneous, whereas base-catalyzed gels had a coarse texture. Analyses by EDX and SAD indicated that acidic gels were chemically homogeneous and microcrystalline, whereas basic gels were heterogeneous and amorphous.     

Produkte der Dimerisierung ungesättigter Fettsäuren IX: Kinetische Untersuchungen zur Dimerisierung von Linolsäure

Products of the Dimerisation of Unsaturated Fatty Acids IX: Kinetic Studies about the Dimerisation of Linoleic Acid To clarify the dimerisation process of linoleic acid, we investigated samples taken in different time intervals. The first reaction step is a water addition at double bonds of the starting material and not double bond isomerisation as previously assumed. The resulting unsaturated monohydroxy fatty acids can cyclize with the second double bond in an intramolecular reaction forming 2,5-disubstituted tetrahydrofuran respectively 2,6-disubstituted tetrahydropyran derivates. Linolenic acid, present nearly always in small amounts in linoleic acid, reacts to first dimerisation products with linoleic acid by formation of a C-C-bond. The aliphatic dimers cyclize in an intramolecular reaction to mono-cyclic compounds. No dimeric acids, which would result from a Diels-Alder-reaction, could be identified. Bicyclic and aromatic dimeric acids can also be found in the early phase of the dimerisation. In the further progress of the reaction isomerisations, hydrogenations and dehydrogenations of the primary reaction products occur, thus the content of aromatic substances increases steadily.     

Modelling formation and growth of H2SO4-H2O aerosols: Uncertainty analysis and experimental evaluation

An aerosol dynamics model, AERO2, is presented, which describes the formation of H₂SO₄-H₂O aerosol in a smog chamber. The model is used to analyse how the uncertainties on four input parameters are propagated through an aerosol dynamics model. The input parameters are: the rate of the reaction between SO₂ and OH (k₁), the ratio between the nucleation rate used in AERO2 and that derived from classical nucleation theory (t_n), the H₂SO₄ mass accommodation coefficient () and a measure of the turbulence intensity in the reactor (k_e). Uncertainties for these parameters are taken from the literature. One of the results of the analysis is that AERO2 and aerosol dynamics models in general can only predict upper bounds for the total number (N_tot) and total volume (V_tot) concentrations of the particles. The uncertainties on N_tot and V_tot are mainly due to the uncertainties on k₁, and t_n. An uncertainty factor of 20–100 still remains when the uncertainty on k₁, is reduced to ±5%. Aerosol measurements from three smog chamber experiments have therefore been used, in an attempt to reduce the uncertainty on k₁ and t_n. Values for k₁ are obtained in the reduced range 7.8 × 10⁻¹³ to 1.0 × 10⁻¹² cm³ s⁻¹, which is within the range found in the literature. For t_n, values in the range 10⁴–10⁷ are obtained, which is close to the upper bound of the range in literature. These values for t_n are in marked contrast with a recent set of experiments on nucleation in H₂SO₄-H₂O mixtures, which suggests a value for t_n of at most 10⁻⁵.     

Genetic algorithm-based initial contour optimization for skin lesion border detection

Multimedia Tools and Applications - Automated segmentation has an essential role in detecting several diseases, such as skin lesions. In segmentation, the active contour (AC) is an efficient method...     

A globally asymptotically stabilizing trajectory tracking controller for fully actuated rigid bodies using landmark‐based information

In this paper, we address the problem of designing a control law based on sensor measurements that provides global asymptotic stabilization to a reference trajectory defined on the . The proposed control law is a function of the angular velocity, of vector measurements characterizing the position of some given landmarks, and of their rate of change. We provide sufficient conditions for the existence of synergistic potential functions on SO(3) which are pivotal in the generation of a suitable hybrid control law. We also provide sufficient conditions on the geometry of the landmarks to solve the given problem. Finally, the proposed solution is simulated and compared with a continuous feedback control law. Copyright © 2014 John Wiley & Sons, Ltd.     

Impact of white-matter mask selection on DTI histogram-based metrics as potential biomarkers in cerebral small vessel disease

Magnetic Resonance Materials in Physics, Biology and Medicine - Histogram-based metrics extracted from diffusion-tensor imaging (DTI) have been suggested as potential biomarkers for cerebral small...     

Electrohydrodynamic‐Induced SERS Immunoassay for Extensive Multiplexed Biomarker Sensing

Cancer diagnosis and patient monitoring require sensitive and simultaneous measurement of multiple cancer biomarkers considering that single biomarker analysis present inadequate information on the underlying biological transformations. Thus, development of sensitive and selective assays for multiple biomarker detection might improve clinical diagnosis and expedite the treatment process. Herein, a microfluidic platform for the rapid, sensitive, and parallel detection of multiple cancer‐specific protein biomarkers from complex biological samples is presented. This approach utilizes alternating current electrohydrodynamic‐induced surface shear forces that provide exquisite control over fluid flow thereby enhancing target–sensor interactions and minimizing non‐specific binding. Further, the use of surface‐enhanced Raman scattering‐based spectral encoding with individual barcodes for different targets enables specific and simultaneous detection of captured protein biomarkers. Using this approach, the specific and sensitive detection of clinically relevant biomarkers including human epidermal growth factor receptor 2 (HER2); Mucin 1, cell surface associated (MUC1); epidermal growth factor receptor; and Mucin 16, cell surface associated (MUC16) at concentrations as low as 10 fg mL^?1 in patient serum is demonstrated. Successful target detection from patient samples further demonstrates the potential of this current approach for the clinical diagnosis, which envisages a clinical translation for a rapid and sensitive appraisal of clinical samples in cancer diagnostics.