Comparison of pH-dependent sonodisruption of re-assembled casein micelles by 35 and 130 kHz ultrasounds

Sonodisruption behavior of re-assembled casein micelles was compared at two ultrasound frequencies (35 and 130 kHz) by turbidity measurement and laser-diffraction based particle size analysis. Sonochemical ultrasound (130 kHz) was more effective than power ultrasound (35 kHz) in micelle disruption. This was attributed to the higher strain rates generated upon implosion of cavities, as well as the liberation of more free radicals to the surrounding medium. The higher the pH of solution, the more effective was the ultrasonic disruption due to a looser expanded assembly of particles at higher pH values. Sonochemical ultrasound decreased the consistency coefficient of casein solutions and increased their flow index except at a pH value of 6.35, while power ultrasound did not affect the flow behavior of solutions across the whole pH range.     

Increasing the toughness of nylon 12 by the incorporation of functionalized graphene

The effect of functionalized graphene (FG) on the mechanical properties, especially toughness, of nylon12 was investigated. The results revealed that the incorporation of a very small amount (about 0.6 wt%) of the FG caused a significant improvement in ultimate tensile strength, elongation, impact strength and toughness. With 0.6 wt% FG ultimate tensile strength and elongation at break of the nylon 12 are improved by ∼35% and ∼200%, respectively. The K_Ic of the nylon 12 is ∼1.28 MPa m^0.5 and the incorporation of 0.6 wt% FG causes a significant increase of 72% (∼2.2 MPa m^0.5). 0.6 wt% FG also causes a significant improvement of 175% in impact failure energy of the nylon 12. The incorporation of FG resulted in an increase in amount of γ-phase of nylon12 which could be the direct reason for the increase of toughness.     

Preparation and characterization of new photoactive polyamides containing 4‐(4‐dimethylaminophenyl)urazole units

4‐(4‐dimethylaminophenyl)‐1,2,4‐triazolidine‐3,5‐dione ( DAPTD ) was prepared from 4‐dimethylaminobenzoic acid in five steps. The compound DAPTD was reacted with excess acetyl chloride in N,N‐dimethylacetamide (DMAc) solution and gave 1,2‐bisacetyl‐4‐[4‐(dimethylaminophenyl)]‐1,2,4‐triazolidine‐3,5‐dione as a model compound. Solution polycondensation reactions of monomer with succinyl chloride (SucC), suberoyl chloride (SubC), and sebacoyl chloride (SebC) were performed under conventional solution polymerization techniques in the presence of triethylamine and pyridine as a catalyst in N‐methylpyrrolidone (NMP) and led to the formation of novel aliphatic polyamides. These novel polyamides have inherent viscosities in the range of 0.09–0.21 dL/g in N,N‐dimethylformamide (DMF) at 25°C. Fluorimetric studies of the model compound as well as polymers were performed. © 2006 Wiley Periodicals, Inc. J Appl Polym Sci 103: 947–954, 2007     

Indoor radon levels and lung cancer risk estimates in seven cities of the Bahawalpur Division, Pakistan

Indoor radon concentration levels were measured in seven major cities of the Bahawalpur Division, Pakistan. These included Fort Abbas, Minchin Abad, Hasilpur, Bahawalpur, Liaqatpur, Rahimyar Khan and Sadiq Abad. In order to select houses for this survey, the inhabitants were approached through their school-registered children. Due to several constraints, only those 100 houses were chosen in each city that were relatively the best representatives of the built-up area. The selected houses were then divided into live categories according to the house locations and building characteristics. CR-39 detectors, placed in polyethylene bags. were installed at head height in bedrooms and sitting rooms of all the selected houses and were exposed to radon and its daughter products for 90 days. Four such measurements were performed over a year in order to average out the seasonal variation in radon levels. After exposure, all the detectors were etched and counted under an optical microscope. The track densities of four measurements were averaged out and related to radon concentration levels. The radon levels were found to be 20, 20, 26, 28, 34, 42, 47 Bq m(-3) in the bedrooms and 24, 26, 27, 26, 37, 40, 43 Bq m(-3) in sitting rooms of Hasilpur, Rahimyar Khan, Minchin Abad, Fort Abbas, Sadiq Abad, Bahawalpur and Liaqatpur respectively. The observed variation in the radon level may be attributed to the geological variation in the area. Based on the observed data, excess lung cancer risk was assessed using the risk factors recommended by the USEPA, UNSCEAR and the ICRP. According to the EPA model, the lifetime excess lung cancer risk due to the lifetime exposure is found to vary from 12-102 per million per year in the houses surveyed. This variation is from 16-114 and 26-62 per million per year if UNSCEAR and ICRP limits are applied respectively.     

Biosynthesized Gold Nanoclusters and Iron Complexes as Scaffolds for Multimodal Cancer Bioimaging

Cancer treatment has a far greater chance of success if the neoplasm is diagnosed before the onset of metastasis to vital organs. Hence, cancer early diagnosis is extremely important and remains a major challenge in modern therapeutics. In this contribution, facile and new method for rapid multimodal tumor bioimaging is reported by using biosynthesized iron complexes and gold nanoclusters via simple introduction of AuCl₄ ^? and Fe²⁺ ions. The observations demonstrate that the biosynthesized Au nanoclusters may act as fluorescent and computed tomography probes for cancer bioimaging while the iron complexes behave as effective contrast agent for magnetic resonance imaging. The biosynthesized iron complexes and gold nanoclusters are found biocompatible in vitro (MTT (3‐(4, 5‐dimethylthiazol‐2‐yl)‐2, 5‐diphenyltetrazolium bromide) assay) and in vivo for all the vital organs of circulatory and excretory system. These observations raise the possibility that the biosynthesized probes may find applications in future clinical diagnosis for deep seated early neoplasms by multimodal imaging.     

A survey on resource allocation in high performance distributed computing systems

An efficient resource allocation is a fundamental requirement in high performance computing (HPC) systems. Many projects are dedicated to large-scale distributed computing systems that have designed and developed resource allocation mechanisms with a variety of architectures and services. In our study, through analysis, a comprehensive survey for describing resource allocation in various HPCs is reported. The aim of the work is to aggregate under a joint framework, the existing solutions for HPC to provide a thorough analysis and characteristics of the resource management and allocation strategies. Resource allocation mechanisms and strategies play a vital role towards the performance improvement of all the HPCs classifications. Therefore, a comprehensive discussion of widely used resource allocation strategies deployed in HPC environment is required, which is one of the motivations of this survey. Moreover, we have classified the HPC systems into three broad categories, namely: (a) cluster, (b) grid, and (c) cloud systems and define the characteristics of each class by extracting sets of common attributes. All of the aforementioned systems are cataloged into pure software and hybrid/hardware solutions. The system classification is used to identify approaches followed by the implementation of existing resource allocation strategies that are widely presented in the literature.     

Evolving Recurrent Neural Network using Cartesian Genetic Programming to Predict The Trend in Foreign Currency Exchange Rates

Forecasting the foreign exchange rate is an uphill task. Numerous methods have been used over the years to develop an efficient and reliable network for forecasting the foreign exchange rate. This study utilizes recurrent neural networks (RNNs) for forecasting the foreign currency exchange rates. Cartesian genetic programming (CGP) is used for evolving the artificial neural network (ANN) to produce the prediction model. RNNs that are evolved through CGP have shown great promise in time series forecasting. The proposed approach utilizes the trends present in the historical data for its training purpose. Thirteen different currencies along with the trade-weighted index (TWI) and special drawing rights (SDR) is used for the performance analysis of recurrent Cartesian genetic programming-based artificial neural networks (RCGPANN) in comparison with various other prediction models proposed to date. The experimental results show that RCGPANN is not only capable of obtaining an accurate but also a computationally efficient prediction model for the foreign currency exchange rates. The results demonstrated a prediction accuracy of 98.872 percent (using 6 neurons only) for a single-day prediction in advance and, on average, 92% for predicting a 1000 days’ exchange rate in advance based on ten days of data history. The results prove RCGPANN to be the ultimate choice for any time series data prediction, and its capabilities can be explored in a range of other fields.     

Solving constrained optimisation problems using the improved imperialist competitive algorithm and Deb’s technique

ABSTRACT

In this paper, an improved imperialist competitive algorithm called I-ICA is proposed for solving constrained optimisation problems. In I-ICA, the use of differential evolution (DE)/rand/1 mutation operator at assimilation step enhances the population diversity. Also, the binomial crossover operator improves the speed of convergence to optimal solution by distributing good information among solutions. Furthermore, Deb’s rules were applied for handling constrains. Examinations were done on 24 well-known functions and 5 engineering design problems. The comparison of I-ICA with basic ICA and 22 state-of-the-art algorithms shows I-ICA’s superiority in terms of the rate of convergence and quality of the obtained solution.     

A biotechnological perspective on the application of iron oxide nanoparticles

In recent decades,magnetic iron nanoparticles (NPs) have attracted much attention due to properties such as superparamagnetism,high surface area,large surface-to-volume ratio,and easy separation under external magnetic fields.Therefore,magnetic iron oxides have potential for use in numerous applications,including magnetic resonance imaging contrast enhancement,tissue repair,immunoassay,detoxification of biological fluids,drug delivery,hyperthermia,and cell separation.This review provides an updated and integrated focus on the fabrication and characterization of suitable magnetic iron NPs for biotechnological applications.The possible perspective and some challenges in the further development of these NPs are also discussed.     

Feature Extraction Method Based on Social Network Analysis

Due to rapid development of Internet technology and electronic business, fraudulent activities have increased. One of the ways to cope with damages of them is fraud detection. In this field, there is a need for methods accurate and fast. Therefore, a novel and efficient feature extraction method based on social network analysis called FEMBSNA is proposed for fraud detection in banking accounts. In this method, in order to increase accuracy and control runtime in the first step, features based on network level are considered using social network analysis and extracted feature is combined with other features based on user level in the next phase. To evaluate our feature extraction method, we use PCK-means method as a basic method to learn. The results show using the proposed feature extraction as a pre-processing step in fraud detection improves the accuracy remarkably while it controls runtime in comparison with other methods.