Extrusion of starch‐based loose‐fill packaging foams: effects of temperature,moisture and talc on physical properties

Starch‐based loose‐fill packaging foams were made in a single‐screw laboratory‐scale extruder. Corn starch was blended with polystyrene in the ratio of 70 : 30 and extruded into foams using talc and polycarbonate as additives. Extrusions were carried out at moisture contents of 16, 18 and 20% (dry basis), and at barrel temperatures of 140 and 160°C. The influences of extrusion temperature, moisture content of starch, talc and polycarbonate on the radial expansion and other selected physical properties of starch foams were investigated. The effects of moisture and talc contents on the radial expansion of foams were found to be critical, while the role of temperature was close to significant. The expansion ratio increased when the moisture content was increased from 16 to 18%, and then decreased when moisture content was increased to 20%. In general, the expansion ratios of foams were higher at 160°C as compared to 140°C. Although polycarbonate mixed well with the starch–polystyrene melt, it was not effective as a structural and anti‐shrinking agent, and it did not contribute to the radial expansion. In general, the bulk densities and unit densities of the starch foams decreased as the moisture content and extrusion temperature increased. Scanning electron microscope images showed that the addition of talc yielded foams with smaller‐sized cells, with less expansion of the foam melt, and thus a higher density. X‐ray diffractograms revealed that the crystallinity of starch foams increased post‐extrusion, and there was adequate dispersion of the starch and polystyrene polymers to make the foam water‐resistant. Copyright © 2008 John Wiley & Sons, Ltd.     

Utilization of chimeras between human (HM-175) and simian (AGM-27) strains of hepatitis A virus to study the molecular basis of virulence

Chimeras between human (HM-175) and simian (AGM-27) strains of hepatitis A virus (HAV) were constructed to evaluate the effect of the 2C gene of AGM-27 on HAV replication in cell culture and virulence in tamarins (Saguinus mystax) and chimpanzees (Pan troglodytes). Kinetic studies and radioimmunofocus assays demonstrated that replacement of the 2C gene of HAV/7, a cell culture-adapted strain of HM-175, with that of AGM-27 drastically reduced the ability of the virus to replicate in cultured cells. Intragenic chimeras containing AGM-27 sequences in either the 5' or 3' half of the 2C gene replicated in cell culture at an intermediate level. Whereas HAV/7 is attenuated for tamarins, a chimera containing the simian virus 2C gene in the HAV/7 background was virulent in tamarins, demonstrating that the simian virus 2C gene alone can confer the phenotype of virulence to an otherwise attenuated virus. Clusters of AGM-27-specific residues near both ends of the 2C protein were required for virulence since a chimera containing AGM-27 sequences in the carboxy-terminal half of 2C was partially attenuated for tamarins while one containing AGM-27 sequences only in the amino-terminal half of 2C was even more attenuated. Chimeras containing either the entire or only the 3' half of the simian virus 2C gene in the HAV/7 background were attenuated for chimpanzees.     

Network Traffic Prediction Using Radial Kernelized-Tversky Indexes-Based Multilayer Classifier

Accurate cellular network traffic prediction is a crucial task to access Internet services for various devices at any time. With the use of mobile devices, communication services generate numerous data for every moment. Given the increasing dense population of data, traffic learning and prediction are the main components to substantially enhance the effectiveness of demand-aware resource allocation. A novel deep learning technique called radial kernelized LSTM-based connectionist Tversky multilayer deep structure learning (RKLSTM-CTMDSL) model is introduced for traffic prediction with superior accuracy and minimal time consumption. The RKLSTM-CTMDSL model performs attribute selection and classification processes for cellular traffic prediction. In this model, the connectionist Tversky multilayer deep structure learning includes multiple layers for traffic prediction. A large volume of spatial-temporal data are considered as an input-to-input layer. Thereafter, input data are transmitted to hidden layer 1, where a radial kernelized long short-term memory architecture is designed for the relevant attribute selection using activation function results. After obtaining the relevant attributes, the selected attributes are given to the next layer. Tversky index function is used in this layer to compute similarities among the training and testing traffic patterns. Tversky similarity index outcomes are given to the output layer. Similarity value is used as basis to classify data as heavy network or normal traffic. Thus, cellular network traffic prediction is presented with minimal error rate using the RKLSTM-CTMDSL model. Comparative evaluation proved that the RKLSTM-CTMDSL model outperforms conventional methods.     

Elasto-plastic behaviour of a thin cylinder under thermal stress cycling

A simple biaxial model is chosen to represent the stress state of a thin cylinder and the elasto-plastic behaviour under thermal stress cycling is studied to determine:

1. 1. shakedown limits,

2. 2. plastic cycling limits,

3. 3. magnitude of cyclic strains and ratchet strains,

4. 4. strain ratios in various regimes.

The studies have been carried out for two material models: elastic-perfectly plastic and Prager-hardening. Results are given in the form of graphs and compared with the results of uniaxial models.     

On a Closed Form Expression for Phase-Locked Loop Pull-In Range

A closed form expression is derived for the pull-in range of second-order phase-locked loops (PLL's) with sinusoidal phase detectors. Pull-in range, normalized with respect to gainG, is expressed as a function of the damping factorzetaand normalized natural frequency β of the linearized loop model. Results are presented for various values of β andzetaand compared with earlier results.     

Single-walled carbon nanotube induces oxidative stress and activates nuclear transcription factor-kappaB in human keratinocytes

Carbon nanotubes are now becoming an important material for use in day to day life because of their unique physical properties. The toxicological impact of these materials has not yet been studied in detail, thereby limiting their use. In the present study, the toxicity of single-walled carbon nanotubes (SWCNT) was assessed in human keratinocyte cells. The results show increased oxidative stress and inhibition of cell proliferation in response to treatment of keratinocytes with SWCNT particles. In addition, the signaling mechanism in keratinocytes upon exposure to SWCNT particles was investigated. Results from the study suggest that SWCNT particles activate NF-kappaB in a dose-dependent manner in human keratinocytes. Further, the mechanism of activation of NF-kappaB was due to the activation of stress-related kinases by SWCNT particles in keratinocytes. In conclusion, these studies show the mechanism of toxicity induced by SWCNT particles.     

Harmonic response tests on distribution circuit potentialtransformers

Experimental data are presented that show the performances of distribution circuit potential transformers operating with nonsinusoidal waveforms. Four standard magnetic voltage transformers designed for 60 Hz power applications and rated from 7.2 kV to 20 kV were tested. Ratio correction factor and phase angle measurements were conducted at rated 60 Hz voltage with harmonic distortion levels at and below 8%. Test results indicate that potential transformers rated up to 20 kV experience errors of less than 5% at harmonic frequencies up to 3500 Hz when operating into typical induction watthour meter burdens. The phase angle response is essentially linear over the frequency range used to test the transformers, with a typical phase angle of about -10° at frequencies of approximately 3 to 3.5 kHz