Taguchi orthogonal array design for the optimization of hydrogel nanoparticles for the intravenous delivery of small‐molecule drugs

In this study, a 16 runs Taguchi method was applied as an experimental design to establish the optimum conditions for hydrogel nanoparticle preparation. Five relevant factors, chitosan (CS) concentration, pentasodium tripolyphosphate (TPP) concentration, CS‐to‐TPP volume ratio, addition time of the TPP solution to the CS solution, and temperature, were selected as the main determinants, and the effects of each factor on the size of the hydrogel nanoparticles were studied at four levels. The statistical analysis revealed that the most important factors contributing to the achievement of minimum particle size were the CS‐to‐TPP volume ratio and the CS concentration. By solving a set of equations derived from the differentiation of the final model, we established the optimum conditions for hydrogel nanoparticle preparation as follows: CS concentration = 0.28% w/v, TPP concentration = 3.17% w/v, TPP/CS = 1 : 8, temperature = 25.66°C, and addition time of the TPP solution to the CS solution = 0.4 min. Also, an analysis of response at the different levels of the factors indicated that there was no remarkable interaction between them. © 2012 Wiley Periodicals, Inc. J. Appl. Polym. Sci., 2012     

Histopathological lesions and toxicity in common carp (Cyprinus carpio L. 1758) induced by copper nanoparticles

Different types of metal oxide nanoparticles (NPs) have been suggested for various applications such as water treatment and construction of agricultural pesticides; however, there are concerns about the potential toxicity of these compounds for the nontarget organism especially aquatic organisms. The aims of this study were assessing toxicity and histopathological effects of copper oxide NPs (NPs‐CuO) on common carp (Cyprinus carpio) as a model organism. For this purpose 150 common carp with an average weight 7 ± 1 g were exposed to 0, 10, 20, 30, 40, 60, 80, 100, 150, and 200 mg/l of CuO‐NPs (10 treatment with three replicates) for 96 hrs. After 24, 48, 72, and 96 hrs exposures, mortality rates recorded and gill samples were collected. Statistical analysis showed significant differences in carp survival between control and treatment groups (p < 0.05); regression between fish mortality rate and NPs‐CuO concentration was also revealed (p < 0.01). The LC₅₀ 96h of NPs‐CuO for common carp was estimated as 124.9 mg/l in this study. Various tissue damages were observed in gill of treatments; such as, hypertrophy, hyperplasia, lamellar fusions, erythrocyte infiltration, epithelial lifting; also, there was significant correlation between intensity of tissue lesions and concentration of NPs‐CuO (p < 0.01). The findings of the present study demonstrate that sublethal concentration of NPs‐CuO can lead to serious tissue lesions. Whats more, concentrations above 30 ml/l of NPs‐CuO can lead to some clinical signs; such as skin darkening and death with open mouth as well as definite fish death.     

A Learning Automata-Based Solution to the Priority-Based Target Coverage Problem in Directional Sensor Networks

In recent years, directional sensor networks composed of directional sensors have attracted a great deal of attention due to their extensive applications. The main difficulties associated with directional sensors are their limited battery power and restricted sensing angle. Moreover, each target may have a different coverage quality requirement that can make the problem even more complicated. Therefore, satisfying the coverage quality requirement of all the targets in a specific area and maximizing the network lifetime, known as priority-based target coverage problem, has remained a challenge. As sensors are often densely deployed, organizing the sensor directions into several cover sets and then activating these cover sets successively is a promising solution to this problem. In this paper, we propose a learning automata-based algorithm to organize the directional sensors into several cover sets in such a way that each cover set can satisfy coverage quality requirement of all the targets. In order to verify the performance of the proposed algorithm, several simulations were conducted. The obtained results showed that the proposed algorithm was successful in extending the network lifetime.     

Solving Target Coverage Problem Using Cover Sets in Wireless Sensor Networks Based on Learning Automata

Recent years have witnessed a significant increase in employing wireless sensor networks (WSNs) for a variety of applications. Monitoring a set of discrete targets and, at the same time, extending the network lifetime is a critical issue in WSNs. One method to solve this problem is designing an efficient scheduling algorithm that is able to organize sensor nodes into several cover sets in such a way that each cover set could monitor all the targets. This study presents three learning automata-based scheduling algorithms to solve the problem. Moreover, several pruning rules are devised to avoid the selection of redundant sensors and manage critical sensors for extending the network lifetime. To evaluate the performance of proposed algorithms, we conducted several experiments, and the obtained results indicated that Algorithm 3 was more successful in terms of extending the network lifetime.     

A Modification on ECAP Process by Incorporating Twist Channel

In this study, a method that combines the equal channel angular pressing (ECAP) and twist extrusion (TE) techniques has been introduced as a severe plastic deformation process and investigated by means of the three-dimensional finite element analysis. Owing to the form of the mold which is used in this technique, it can be called the symmetrical channels angular pressing (SCAP) method. This method resembles the more common ECAP process for samples with rectangular cross sections, with the difference that, in this method, the entrance and exit channels at the intersecting corner of the mold also have a twist about their longitudinal axis (as in the TE technique). In this study, to show the characteristics of the SCAP method and to compare it with the ECAP technique, the former method has been simulated by the ABAQUS/Explicit software. Also, to validate the obtained results, the SCAP and ECAP methods were practically applied on samples made of pure commercial aluminum (AA1050). To get the strain distribution along the longitudinal and transverse directions of the samples, Vickers hardness was measured on these samples. The results obtained from these hardness measurements indicate that after one pass, the SCAP method can achieve a higher amount of hardness, compared with the ECAP technique. Moreover, the strain distributions obtained from the simulation and from the samples demonstrate that the SCAP method produces a more homogeneous distribution of strain in the workpieces.     

Electropolymerization of thionine as a stable film along with carbon nanotube for sensitive detection of tetracycline antibiotic drug

Iranian Polymer Journal - Herein, a simple, rapid, cost-effective and sensitive poly(thionine)-based electrochemical sensor is described to determine trace amounts of tetracycline. In the present...     

Server consolidation techniques in virtualized data centers of cloud environments: A systematic literature review

At the virtualized data centers, services are presented by active virtual machines (VMs) in physical machines (PMs). The manner in which VMs are mapped to PMs affects the performance of data centers and the energy efficiency. By employing the server consolidation technique, it is possible to configure the VMs on a smaller number of PMs, while the quality of service is guaranteed. In this way, the rate of active PM utilization increases and fewer active PMs would be required. Moreover, the server consolidation technique reacts to the management of underloaded and overloaded PMs by using the VM migration technology. Considering the capabilities of the server consolidation technique and its role in developing the cloud computing infrastructure, many researches have been conducted in this context. Still, a comprehensive and systematic study has not yet been performed on various consolidation techniques to check the capabilities, advantages, and disadvantages of current approaches. In this paper, a systematic study is conducted on a number of credible researches related to server consolidation techniques. In order to do so and by studying the selected works, proposed solutions are categorized based on the type of decision for running the consolidation algorithm in 4 groups of static method, dynamic method, prediction‐based dynamic method, and hybrid method. Thereafter, the advantages and disadvantages of suggested approaches are studied and compared in each research by specifying the technique and idea applied therein. In addition, by categorizing aims of researches and specifying assessment parameters, optimization approaches and type of architecture, a possibility has been provided to get familiarized with the views of the researchers.     

Structural characterization of high-density polyethylene nanocomposites: effect of compatibilizer type and high aspect ratio organoclay platelets

This research focuses on the possibility of improving properties of high-density polyethylene-based nanocomposite films for packaging applications, using a high aspect ratio layered silicate named fluoromica. Three different compatibilizers [ethylene vinyl acetate copolymer and two grades of maleic anhydride grafted high-density polyethylene (HDPE-g-MA) with different melt flow indices] were examined to explore the effects of compatibilizer polarity and molecular weight on the state of nanoclay dispersion. Owing to the direct correlation between nanocomposites morphology and rheological behavior, a quite extensive survey of the role of different material variables was carried out via measuring rheological properties in linear viscoelastic region. Percolation threshold ( \(\phi_{\text{p}}\) ) were determined by analyzing the improvement in dynamic viscosity in low-frequency region and also, by means of a predicted mathematical model obtained from experimental design. It was found that the HDPE-g-MA compatibilizers result in lower \(\phi_{\text{p}}\) and better clay dispersion, particularly in the case of high MFI resin. Microstructural characterization of the samples was studied by X-ray diffraction and transmission electron microscopy as well.     

Predicting Natural Gas Hydrate Formation Temperature Using Levenberg-Marquardt Algorithm

In this study, two new correlations are proposed to predict the natural gas hydrate formation temperature as a function of pressure and specific gravity. The first correlation has been developed using Vandermonde matrix and the coefficients of the second correlation have been obtained by Levenberg-Marquardt algorithm. The error analysis shows the good performance of the two new proposed correlations to predict hydrate formation temperature compared to correlations presented earlier and also the experimental values.