Dependence of disperse dye diffusion on the structure and morphology of oriented heat–set polyester fibres

The structural parameters that predominantly influence dye diffusion behaviour in heat–set polyester fibres have been identified. Dye diffusion has been shown to depend on two factors: the volume of the accessible region (amorphous region) and the tortuosity of the dye diffusion path. The accessible region can be represented in terms of the amorphous volume per crystal, and the tortuosity can be expressed quantitatively by combining the orientation of the amorphous phase and the nature of coupling between the amorphous and the crystalline regions. An integrated model has been proposed by combining these parameters, and has been shown to correlate well with dye uptake in polyester fibres heat–set under slack and taut conditions.     

The Effect of Melt Extrusion Process Parameters on Rotary‐Evaporated Poly(propylene) Nanocomposites

Design of experiments is employed to investigate the interrelationships between processing and nanotube surface chemistry on the properties of PP nanocomposites. Statistically significant effects of nanomaterial type and concentration, extrusion temperature, screw speed, and recirculation time, and their interactions, on nanocomposite thermal properties and stability are isolated. The effects of these factors on the shear storage modulus, the low‐frequency slope of the shear storage modulus, decomposition temperature, and melt temperature are explored. Nanotube concentration has the most significant effect in enhancing the decomposition temperature of the nanocomposite, while long extrusion time and higher temperatures lead to deteriorated properties.

     

Effect of the surface roughness of conducting polypyrrole thin-film electrodes on the electrocatalytic reduction of nitrobenzene

Conducting polypyrrole (PPy) thin-film electrodes were prepared by the electropolymerization of pyrrole on gold-coated glass plates. Films of various roughnesses were obtained by the variation of the scan rates during electropolymerization. These thin films were modified by doping with 6mM of the dopant NiCl₂. The surface morphology of the films was studied by scanning electron microscopy and atomic force microscopy (AFM), which suggested films prepared with a high scan rate were rougher in nature than the films produced with a low scan rate. The electrocatalytic reduction of nitrobenzene was carried out with these electrodes with the cyclic voltammetry technique in acetonitrile containing 0.1M HClO₄ as a supporting electrolyte. The various results obtained show that the conducting PPy thin-film electrodes were catalytically active toward the electroreduction process. The modified PPy film electrodes doped with NiCl₂ were more active toward nitrobenzene electroreduction than the PPy film alone. The results indicate that the roughness of the films played a very important role in determining their catalytic activity. The PPy films that were more rough in nature were catalytically more active than the smooth films; this may have been due to the availability of more reactive sites in the case of rough films. The apparent diffusion coefficients of the PPy film electrodes were also calculated. © 2012 Wiley Periodicals, Inc. J Appl Polym Sci, 2012     

A convolutional neural network (CNN)-based direct method to detect stiction in control valves

Control valves are considered important capital assets in any process industry. A properly maintained control valve can have a significant impact on how well the process is controlled as well as the overall cost of the plant. However, control valves can suffer from poor control performance due to valve non-linearities. One of the main reasons for non-linearity is control valve stiction. Stiction not only causes oscillations in the process variables but also shortens the life of the control valve, resulting in an economic loss for the process. In a process plant, a control engineer generally analyzes the time series plot of process value (PV), set point (SP), and controller output (OP) data and identifies stiction based on the typical shape pattern of PV/SP/OP plot. In this study, the same shape pattern methodology is adapted to identify stiction using convolutional neural network (CNN) technique. A one-dimensional convolution neural network (Conv1D) algorithm is developed, which works directly on PV/SP/OP time series data for stiction detection. The proposed CNN algorithm is tested on both simulated and industrial control loop data. The suggested method provides promising results with a combined stiction prediction accuracy of 92% (92.2% in predicting non-sticky and 91.53% in predicting sticky loops) for the industrial loops data studied.     

Photoradical-Mediated Catalyst-Independent Protein Cross-Link with Unusual Fluorescence Properties

Photo-actively modified natural amino acids have served as lucrative probes for precise mapping of the dynamics, interaction networks, and turnover of cytosolic proteins both in vivo and ex vivo. In our attempts to extend the utility of photoreactive reporters to map the molecular characteristics of vital membrane proteins, we carried out site-selective incorporation of 7-fluoro-indole in the human mitochondrial outer membrane protein VDAC2 (voltage-dependent anion channel isoform 2), with the aim of generating Trp−Phe/Tyr cross-links. Prolonged irradiation at 282 nm provided us with a surprisingly unusual fluorophore that displayed sizably red-shifted excitation (λ_ex-max=280 nm→360 nm) and emission (λ_em-max=330 nm→430 nm) spectra that was reversible with organic solvents. By measuring the kinetics of the photo-activated cross-linking with a library of hVDAC2 variants, we demonstrate that formation of this unusual fluorophore is kinetically retarded, independent of tryptophan, and is site-specific. Using other membrane (Tom40 and Sam50) and cytosolic (MscR and DNA Pol I) proteins, we additionally show that formation of this fluorophore is protein-independent. Our findings reveal the photoradical-mediated accumulation of reversible tyrosine cross-links, with unusual fluorescent properties. Our findings have immediate applications in protein biochemistry and UV-mediated protein aggregation and cellular damage, opening avenues for formulating therapeutics that prolong cell viability in humans.     

Modelling of packed bed adsorption columns for the separation of green tea catechins

Green tea is a rich source of catechins, which when purified have a high economic value as they can be used as a supplement in several products, to increase their health benefits. Catechins are regarded as desired components with several applications in a variety of areas such as foods, cosmetics and pharmaceuticals. A multicomponent sorption model has been developed for the separation of catechins from liquid tea streams, with macroporous resins in a packed bed column. Two commercially available food grade resins were considered: Amberlite XADHP and Diaion HP20. For the desorption step, two food grade solvents are used: water and ethanol. The adsorption and desorption behaviour is subsequently mathematically described with one-dimensional axial dispersed plug flow model that can accurately simulate the dynamics of the solvent swing sorption columns. The model parameters were regressed from experimental data. Five components are modelled in the competitive sorption: the main four catechins present in green tea and caffeine. The model was used for the process design and optimization for the recovery of catechins from green tea.     

Tocotrienol-rich fraction from palm oil affects gene expression in tumors resulting from MCF-7 cell inoculation in athymic mice

It has recently been shown that tocotrienols are the components of vitamin E responsible for inhibiting the growth of human breast cancer cells in vitro, through an estrogen-independent mechanism. Although tocotrienols act on cell proliferation in a dose-dependent manner and can induce programmed cell death, no specific gene regulation has yet been identified. To investigate the molecular basis of the effect of tocotrienols, we injected MCF-7 breast cancer cells into athymic nude mice. Mice were fed orally with 1 mg/d of tocotrienol-rich fraction (TRF) for 20 wk. At end of the 20 wk, there was a significant delay in the onset, incidence, and size of the tumors in nude mice supplemented with TRF compared with the controls. At autopsy, the tumor tissue was excised and analyzed for gene expression by means of a cDNA array technique. Thirty out of 1176 genes were significantly affected. Ten genes were down-regulated and 20 genes up-regulated with respect to untreated animals, and some genes in particular were involved in regulating the immune system and its function. The expression of the interferon-inducible transmembrane protein-1 gene was significantly up-regulated in tumors excised from TRF-treated animals compared with control mice. Within the group of genes related to the immune system, we also found that the CD59 glycoprotein precursor gene was up-regulated. Among the functional class of intracellular transducers/effectors/modulators, the c-myc gene was significantly down-regulated in tumors by TRF treatment. Our observations indicate that TRF supplementation significantly and specifically affects MCF-7 cell response after tumor formation in vivo and therefore the host immune function. The observed effect on gene expression is possibly exerted independently from the antioxidant activity typical of this family of molecules.     

Role of heat transfer and thermal conductivity in the crystallization behavior of polypropylene‐containing additives: A phenomenological model

The thermal conductivity of a filler and the thermal conductivity of a composite made from that filler influence the heat‐transfer process during melt processing. The heat‐transfer process from the melt to the mold wall becomes an important factor in developing the skin–core morphology. These aspects were examined in this study. The thermal conductivity of polypropylene–filler composites was estimated with a standard model for various fillers such as calcium carbonate, talc, silica, wollastonite, mica, and carbon fibers. The rate of cooling under given conditions, including the melting temperature, mold wall temperature, mass of the composite, and filler content, was estimated with standard heat‐transfer equations. The time to attain the crystallization temperature for polypropylene was evaluated with a regression method with differential temperature steps. The crystallization curves were experimentally determined for the different fillers, and from them, the induction period for the onset of crystallization was estimated. These observations were correlated with the expected trends from the aforementioned formalism. The excellent fit of the curves showed that in all these cases, the thermal conductivity of the filler and composite played a dominant role in controlling the onset of the crystallization process. However, the nucleation effects became important in the later stages after the crystallization temperature was attained. © 2003 Wiley Periodicals, Inc. J Appl Polym Sci 89: 2994–2999, 2003