Use of the Retarded Solution-Reprecipitation Process to Attain a Higher Initial Permeability in MnZn Ferrites

We investigated the effect of various amounts of liquid phase on microstructure development during sintering and the resulting magnetic permeability of MnZn ferrite (MZF) samples. Our results revealed that the microstructure and the final magnetic permeability depend on the thickness of the liquid-phase film during sintering. The solution-reprecipitation (S-R) process, which is associated with an intensive microstructure development in MZF, starts when a continuous liquid-phase film of critical thickness δ_o, which wets the MZF grains, is formed. The solid-state sintering that takes place before the formation of the continuous liquid-phase film is essential for the final microstructure of MZF.     

Reactor length-scale modeling of chemical vapor deposition of carbon nanotubes

Chemical Vapor Deposition (CVD) of carbon nanotubes from a gas mixture consisting of methane (carbon precursor) and hydrogen (a carrier gas) in the presence of cobalt, nickel or iron catalytic particles in a cylindrical reactor is modeled at the reactor length-scale by solving a continuum-based coupled boundary-layer laminar-flow hydrodynamics, heat-transfer, gas-phase chemistry and surface chemistry problem. The model allows determination of the gas-phase fields for temperature, velocity, and various species as well as the surface-species coverages and the carbon deposition rate. Various available experimental and theoretical assessments are used to construct the necessary database for gas-phase and surface chemistry and gas-phase transport parameters. A reasonably good agreement is found between the model predicted and the experimentally measured carbon nanotubes deposition rates over a relatively large range of processing conditions.     

Effect of martensitic transformation in Ti–15 at %V β-phase particles on lamellar boundary decohesion in γ-TiAl Part II Finite element analysis of crack-bridging phenomenon

The commercial finite element package ABAQUS has been used to analyse the crack bridging process by Ti-15 at%V -phase particles dispersed in -TiAl matrix in the presence of particle–matrix decohesion. Both the particle–matrix decohesion potential and the -phase materials constitutive relations are found to have a major effect on the ductility, fracture toughness and failure mode of the – two-phase material. The interface potential is found to primarily affect the distribution of the normal interface strength ahead of the advancing interfacial crack and the mode (gradual versus sudden) of decohesion. The -phase materials constitutive relations are found to influence the location of nucleation of the interfacial cracks and, in turn, the mode of decohesion. A metastable -phase that can plastically deform at low stress levels by undergoing a stress-assisted martensitic transformation, but experience a high rate of strain hardening is found to give rise to the largest levels of ductility and fracture toughness is the – two-phase material. © 1998 Kluwer Academic Publishers     

A quantitative analysis of the unit verification perspective on fault distributions in complex software systems: an operational replication

Unit verification, including software inspections and unit tests, is usually the first code verification phase in the software development process. However, principles of unit verification are weakly explored, mostly due to the lack of data, since unit verification data are rarely systematically collected and only a few studies have been published with such data from industry. Therefore, we explore the theory of fault distributions, originating in the quantitative analysis by Fenton and Ohlsson, in the weakly explored context of unit verification in large-scale software development. We conduct a quantitative case study on a sequence of four development projects on consecutive releases of the same complex software product line system for telecommunication exchanges. We replicate the operationalization from earlier studies, analyzed hypotheses related to the Pareto principle of fault distribution, persistence of faults, effects of module size, and quality in terms of fault densities, however, now from the perspective of unit verification. The patterns in unit verification results resemble those of later verification phases, e.g., regarding the Pareto principle, and may thus be used for prediction and planning purposes. Using unit verification results as predictors may improve the quality and efficiency of software verification.     

Simple and efficient ion imprinted polymer for recovery of uranium from environmental samples

Ion imprinted polymer material (IIP) was prepared by forming ternary complexes of uranyl imprint ion with 1-(prop-2-en-1-yl)-4-(pyridin-2-ylmethyl)piperazine and methacrylic acid followed by thermal copolymerization with ethylene glycol dimethacrylate as the cross-linking monomer in the presence of 1,1'-azobis(cyclohexanecarbonitrile) initiator and 2-methoxy ethanol porogenic solvent. HCl solution (5 mol/L) was used to leach out the uranyl template ion from the IIP particles. Similarly, the control polymer (CP) material was also prepared exactly under the same conditions as the IIP but without the uranyl ion template. Various parameters such as solution pH, initial concentration, aqueous phase volume, sorbent dosage, contact time and leaching solution volumes were investigated. SEM, IR and BET-surface area and pore size analysis were used for the characterization of IIP and CP materials. The extraction efficiency of the IIP and CP was compared using a batch and SPE mode of extraction. The optimal pH for quantitative removal is 4.0-8.0, sorbent amount is 20 mg, contact time is 20 min and the retention capacity is 120 mg of uranyl ion per g of IIP. The IIP prepared demonstrated superior selectivity towards coexisting cations and therefore it can be used for selective removal of uranium from complex matrices.     

A novel split-and-merge algorithm for hierarchical clustering of Gaussian mixture models

The paper presents a novel split-and-merge algorithm for hierarchical clustering of Gaussian mixture models, which tends to improve on the local optimal solution determined by the initial constellation. It is initialized by local optimal parameters obtained by using a baseline approach similar to k-means, and it tends to approach more closely to the global optimum of the target clustering function, by iteratively splitting and merging the clusters of Gaussian components obtained as the output of the baseline algorithm. The algorithm is further improved by introducing model selection in order to obtain the best possible trade-off between recognition accuracy and computational load in a Gaussian selection task applied within an actual recognition system. The proposed method is tested both on artificial data and in the framework of Gaussian selection performed within a real continuous speech recognition system, and in both cases an improvement over the baseline method has been observed.     

Reorganization of the Brain Extracellular Matrix in Hippocampal Sclerosis

The extracellular matrix (ECM) is an important regulator of excitability and synaptic plasticity, especially in its highly condensed form, the perineuronal nets (PNN). In patients with drug-resistant mesial temporal lobe epilepsy (MTLE), hippocampal sclerosis type 1 (HS1) is the most common histopathological finding. This study aimed to evaluate the ECM profile of HS1 in surgically treated drug-resistant patients with MTLE in correlation to clinical findings. Hippocampal sections were immunohistochemically stained for aggrecan, neurocan, versican, chondroitin-sulfate (CS56), fibronectin, Wisteria floribunda agglutinin (WFA), a nuclear neuronal marker (NeuN), parvalbumin (PV), and glial-fibrillary-acidic-protein (GFAP). In HS1, besides the reduced number of neurons and astrogliosis, we found a significantly changed expression pattern of versican, neurocan, aggrecan, WFA-specific glycosylation, and a reduced number of PNNs. Patients with a lower number of epileptic episodes had a less intense diffuse WFA staining in Cornu Ammonis (CA) fields. Our findings suggest that PNN reduction, changed ECM protein, and glycosylation expression pattern in HS1 might be involved in the pathogenesis and persistence of drug-resistant MTLE by contributing to the increase of CA pyramidal neurons’ excitability. This research corroborates the validity of ECM molecules and their modulators as a potential target for the development of new therapeutic approaches to drug-resistant epilepsy.     

Regulation of S100As Expression by Inflammatory Cytokines in Chronic Lymphocytic Leukemia

The calcium-binding proteins S100A4, S100A8, and S100A9 are upregulated in chronic lymphocytic leukemia (CLL), while the S100A9 promotes NF-κB activity during disease progression. The S100-protein family has been involved in several malignancies as mediators of inflammation and proliferation. The hypothesis of our study is that S100A proteins are mediators in signaling pathways associated with inflammation-induced proliferation, such as NF-κB, PI3K/AKT, and JAK/STAT. The mononuclear cells (MNCs) of CLL were treated with proinflammatory IL-6, anti-inflammatory IL-10 cytokines, inhibitors of JAK1/2, NF-κB, and PI3K signaling pathways, to evaluate S100A4, S100A8, S100A9, and S100A12 expression as well as NF-κB activation by qRT-PCR, immunocytochemistry, and immunoblotting. The quantity of S100A4, S100A8, and S100A9 positive cells (p < 0.05) and their protein expression (p < 0.01) were significantly decreased in MNCs of CLL patients compared to healthy controls. The S100A levels were generally increased in CD19⁺ cells compared to MNCs of CLL. The S100A4 gene expression was significantly stimulated (p < 0.05) by the inhibition of the PI3K/AKT signaling pathway in MNCs. IL-6 stimulated S100A4 and S100A8 protein expression, prevented by the NF-κB and JAK1/2 inhibitors. In contrast, IL-10 reduced S100A8, S100A9, and S100A12 protein expressions in MNCs of CLL. Moreover, IL-10 inhibited activation of NF-κB signaling (4-fold, p < 0.05). In conclusion, inflammation stimulated the S100A protein expression mediated via the proliferation-related signaling and balanced by the cytokines in CLL.     

Modifications in the AA5083 Johnson-Cook Material Model for Use in Friction Stir Welding Computational Analyses

Johnson-Cook strength material model is frequently used in finite-element analyses of various manufacturing processes involving plastic deformation of metallic materials. The main attraction to this model arises from its mathematical simplicity and its ability to capture the first-order metal-working effects (e.g., those associated with the influence of plastic deformation, rate of deformation, and the attendant temperature). However, this model displays serious shortcomings when used in the engineering analyses of various hot-working processes (i.e., those utilizing temperatures higher than the material recrystallization temperature). These shortcomings are related to the fact that microstructural changes involving: (i) irreversible decrease in the dislocation density due to the operation of annealing/recrystallization processes; (ii) increase in grain-size due to high-temperature exposure; and (iii) dynamic-recrystallization-induced grain refinement are not accounted for by the model. In this study, an attempt is made to combine the basic physical-metallurgy principles with the associated kinetics relations to properly modify the Johnson-Cook material model, so that the model can be used in the analyses of metal hot-working and joining processes. The model is next used to help establish relationships between process parameters, material microstructure and properties in friction stir welding welds of AA5083 (a non-age-hardenable, solid-solution strengthened, strain-hardened/stabilized Al-Mg-Mn alloy).     

Spall-Fracture Physics and Spallation-Resistance-Based Material Selection

Spallation is a fracture mode commonly observed in ballistically/blast-wave-loaded structures. The interaction between decompression waves generated within the target structure produces tensile stresses which, if of a sufficient magnitude, may cause material damage and ultimate fracture (spallation). In this study, the phenomenon of spall-fracture is analyzed within a one-dimensional Lagrangian framework. Two distinct analyses are carried out. Within the first analysis, decompression waves are treated as decompression shocks, which simplified the analysis and enabled the formation of spallation-strength-based material index. In the second analysis, decompression waves are treated as smooth (centered simple) waves. This increased the fidelity of the computational analysis, but the material-selection procedure could be done only numerically and an explicit formulation of the spallation-strength-based material-selection index could not be carried out. Overall, the two analyses yielded similar results for the spallation-strength-based material-selection criterion suggesting that the simpler (decompression shock based) one is still adequate for use in the material-selection process.