Binodal and spinodal curves: a simulation for various high polymer mixtures

Flory's equation-of-state theory has been used to predict the lower critical solution temperature behaviour of polymer—polymer mixtures. The spinodal phase boundary of numbers of high molecular weight polymer mixtures have been previously simulated using this theory. In this paper a procedure for simultaneous predictions of the binodal and the spinodal curves by equating the chemical potential of each component in the mixture is presented. The method is tested for five different mixtures. The effects of the binary and pure component state parameters on the simulated curves are discussed and the simulated phase diagrams are compared with the experimental cloud point curves. It is found that in most cases the results are more consistent with the cloud point curve being closer to the spinodal curve than the binodal.     

Kinetic analysis of plasma VLDL-TG and VLDL-remnant-TG turnover in anesthetized rats

We have estimated the turnover and relative pool sizes of nascent-VLDL-TG and VLDL-remnants-TG in anesthetized rats. [1-¹⁴C]Palmitoyl- and [2-³H]glyceryl-labeled “VLDL”-TG (including nascent VLDL-TG and VLDL-remnants-TG) were prepared by injecting labeled palmitate and glycerol into donor rats. Labeled serum from these rats was then injected intravenously into nembutalized male rats and serial blood samples taken for 30 min. Special care was taken to define any early components in the labeled “VLDL”-TG disappearance curves. In other experiments, the donors were rendered functionally hepatectomized 30 min after injection of³H-glycerol and the endogenous labeled VLDL-TG was allowed to circulate 30–60 min before collection of the TG-labeled VLDL-remnants-containing serum. The latter was injected into 4 recipient nembutalized rats and the remnant-TG-turnover measured by serial sampling as above. In two cases,¹⁴C-“VLDL” and³H-VLDL-remnants were injected as a single bolus into ether-anesthetized rats. Despite its complex composition, “VLDL”-TG in most cases disappeared in a single exponential fashion for 30 min with an average half-life of 5.9 min in nembutalized and 2.8 in ether-anesthetized rats. VLDL-remnants-TG showed a more complex behavior, but contained a major rapid component with a mean t_1/2 of ca. 1.5 min in both groups. The data, analyzed by multicompartmental analysis, were fitted to a simple model in which turnover of a larger nascent VLDL-TG pool with formation of a more rapidly turning over smaller pool of VLDL-remnant-TG is the rate-limiting step in overall TG removal from the d<1.006 fraction of rat serum. The data are consistent with our theoretical prediction that under these conditions the kinetics of the VLDL-remnants cannot be resolved from analysis of the total composite “VLDL” (nascent plus remnant) pool.     

Counting eosinophils in bronchoalveolar lavage fluid images with fuzzy methodology

This paper proposes a new fuzzy approach to count eosinophils, as a measure of inflammation, in bronchoalveolar lavage fluid images, provided by digital camera through microscope. We use fuzzy cluster analysis and fuzzy classification algorithm to determine the number of objects in an image. For this purpose, a fuzzy image processing procedure consisting of five main stages is presented. The first stage is pre-highlighting the objects in the images by using an image pre-processing method for enhancement, which is sharpening the image with the Laplaian high pass filter in order to have acceptable contrast in the image. The second stage is segmentation by clustering with fuzzy c-mean algorithm for portioning. In this stage the clustered data are the rough symbols of objects in the image containing noise. In the third step, first, a Gaussian low pass filter is used for noise reduction. Then, a contrast adoption in the image is done by modifying the membership functions in the image [H.R. Tizhoosh, G. Krell, B. Michaelis, Knowledge-based enhancement of megavoltage images in radiation therapy using a hybrid neuro-fuzzy system, Image and Vision Computing 19(July) (2000) 217–233]. Object recognition, the fourth stage, will be done by using fuzzy labeling for the objects in the image, using a fuzzy classification method. The number of labeled images shows the number of eosinophils in an image which is an index for diagnosing inflammation. The last stage is tuning parameters and verification of the system performance by using a feed forward Neural Network.     

Semantic partitioning of peer-to-peer search space

Peer-to-peer (P2P) networks are beginning to form the infrastructure of future applications. Computers are organized in P2P overlay networks to facilitate search queries with reasonable cost. So, scalability is a major aim in design of P2P networks. In this paper, to obtain a high factor of scalability, we partition network search space using a consistent static shared upper ontology. We name our approach semantic partition tree (SPT). All resources and queries are annotated using the upper ontology and queries are semantically routed in the overlay network. Also, each node indexes addresses of other nodes that possess contents expressible by the concept it maintains. So, our approach can be conceived as an ontology-based distributed hash table (DHT). Also, we introduce a lookup service for the network which is very scalable and independent of the network size and just depends on depth of the ontology tree. Further, we introduce a broadcast algorithm on the network. We present worst case analysis of both lookup and broadcast algorithms and measure their performance using simulation. The results show that our scheme is highly scalable and can be used in real P2P applications.     

A hybrid modeling approach for forecasting the volatility of S&P 500 index return

Forecasting volatility is an essential step in many financial decision makings. GARCH family of models has been extensively used in finance and economics, particularly for estimating volatility. The motivation of this study is to enhance the ability of GARCH models in forecasting the return volatility. We propose two hybrid models based on EGARCH and Artificial Neural Networks to forecast the volatility of S&P 500 index. The estimates of volatility obtained by an EGARCH model are fed forward to a Neural Network. The input to the first hybrid model is complemented by historical values of other explanatory variables. The second hybrid model takes as inputs both series of the simulated data and explanatory variables. The forecasts obtained by each of those hybrid models have been compared with those of EGARCH model in terms of closeness to the realized volatility. The computational results demonstrate that the second hybrid model provides better volatility forecasts.     

Novel NGR anchored pullulan micelles for controlled and targeted delivery of doxorubicin to HeLa cancerous cells

Doxorubicin (DOX) is used to treat different kinds of cancers, including cervix carcinoma. However, it has various side effects such as cardiotoxicity. Nano-sized controlled releasing carriers such as polymeric micelles are of interesting approaches to overcome these side effects of doxorubicin in cancer chemotherapy. Regarding the up-regulation of CD13/APN receptors on the cervix carcinoma cells, which can bind to peptide sequences specially NGR (asparagine–glycine–arginine) with high affinity, peptide sequence (NGR) targeted micelles would lead to effective treatment of this carcinoma. In this study, the NGR peptide sequence was synthesized using the solution-phase strategy from asparagine, glycine, and arginine residues. The pullulan–retinoic acid conjugate and pullulan–retinoic acid–NGR conjugate were prepared by the amide and ester bond formation between the hydroxyl groups of pullulan and carboxylic acid groups of retinoic acid and peptide sequence. Pullulan–retinoic acid–NGR micelles were prepared by the direct dissolution method. The optimized micelles, according to their particle size (124.5 nm), zeta potential (? 3.65 mV), entrapment efficiency (85%), and release of DOX (70%, within 72 h) were assessed for their cytotoxicity on HeLa cells using MTT assay. NGR-targeted pullulan/retinoic acid micelles had higher cytotoxicity than the free DOX in cell culture studies on the HeLa cell line, and this can be a promising result in the treatment of cervix carcinoma.