Evaluating the effect of hydroxyapatite nanoparticles on morphology,thermal stability and dynamic mechanical properties of multicomponent blend systems based on polylactic acid/Starch/Polycaprolactone

A hybrid of hydroxyapatite (HA) nanoparticles and encapsulated triclosan (LATC) was utilized to improve the overall performance of Polylactic acid/Starch/Polycaprolactone ternary blends. The morphological evaluations demonstrated that the starch component becomes gelatinized during the melt mixing process in the absence of LATC particles. However, once encapsulated triclosan particles were also added to the formulation, the granular structure of starch phase was retained indicating no gelatinization during the preparation process. In the case of nanocomposite samples, only 1 wt% of HA nanoparticles was found to exhibit a uniform distribution throughout the whole system whereas the higher concentrations resulted in the aggregation of nanoparticles dividing the system into HA‐poor and HA‐rich areas. Thermogravimetric analysis (TGA) was utilized to prove that those HA‐rich areas were formed around the starch domains due to the strong chemical affinity. Moreover, TGA also showed that only 1 wt% of HA nanoparticles acts efficiently in delaying the initiation of thermal decomposition. Dynamic mechanical analysis results also confirmed that HA nanoparticles had a strong tendency to be absorbed onto the starch domains within the system. J. VINYL ADDIT. TECHNOL., 25:E83–E90, 2019. © 2018 Society of Plastics Engineers     

Health monitoring of an instrumented SRMF building using earthquake data

This paper is a study of a six‐story welded steel moment‐resisting frame instrumented by California Strong Motion Instrumentation Program. Several earthquakes had shaken the building, and its response of strong motion data recorded during the earthquakes were made available. In particular, the Whittier Narrows (October 1987), Sierra Madre (June 1991), Northridge (January 1994) and Chino Hills (July 2008) earthquakes were considered in the studies reported here. The paper investigates the capability of input–output system identification methods, namely eigensystem realization algorithm with data correlation, and observer Kalman filter identification, in identifying dynamic characteristics of typical office building structures subjected to strong ground motion. It explores the possibility to extend the above system identification procedures to near‐real‐time estimation of the building response under future earthquakes in order to estimate the likelihood of brittle damage in welded beam to column connections. The modal identification results are compared with those obtained using the spectral analysis and the deterministic‐stochastic subspace identification method to verify the accuracy of the identified modal parameters. Copyright © 2013 John Wiley & Sons, Ltd.     

On computational complexity of impossible differential cryptanalysis

Impossible differential cryptanalysis is one of the conventional methods in the field of cryptanalysis of block ciphers. In this paper, a general model of an impossible differential attack is introduced. Then, according to this model, the concept of an ideal impossible differential attack is defined and it is proven that the time complexity of an ideal attack only depends on the number of involved round key bits in the attack.     

Applying Fuzzy c-means approach as a novel method for prediction of interfacial tension between carbon dioxide and hydrocarbons

The worldwide demand for energy increases and also the price of crude oil increases so these reasons have been caused the searchers have motivated to investigate enhanced of oil recovery (EOR) processes. The carbon dioxide injection is recognized as one of the favorable approaches of EOR because of high displacement efficiency, environmentally aspects and lower cost. The Interfacial tension between crude oil and carbon dioxide is known as one of the critical factors which affect the performance of injection. The main objective of the present investigation is development of Fuzzy c-means (FCM) approach as novel method to estimate interfacial tension between carbon dioxide and hydrocarbons as function of pressure, temperature, liquid and gas densities and molecular weight of alkane. The performance of predicting model was evaluated statistically and graphically and the results confirmed the ability of the model to predict interfacial tension between carbon dioxide and hydrocarbons.     

Comparative evaluation of impacts of climate change and droughts on river flow vulnerability in Iran

Rivers in arid and semi-arid regions are threatened by droughts and climate change. This study focused on a comparative evaluation of the impacts of climate change and droughts on the vulnerability of river flows in three basins with diverse climates in Iran. The standardized precipitation-evapotranspiration index (SPEI) and precipitation effectiveness variables (PEVs) extracted from the conjunctive precipitation effectiveness index (CPEI) were used to analyze the drought severity. To investigate hydrological droughts in the basins, the normalized difference water index (NDWI) and the streamflow drought index (SDI) were calculated and compared. The effects of droughts were assessed under various representative concentration pathway (RCP) scenarios. Changes in the number of wet days and precipitation depth restricted hydrological droughts, whereas an increasing number of dry days amplified their severity. The projected increases in dry days and precipitation over short durations throughout a year under future climate scenarios would produce changes in drought and flood periods and ultimately impact the frequency and severity of hydrological droughts. Under RCP 4.5, an increase in the frequencies of moderate and severe meteorological/hydrological droughts would further affect the Central Desert Basin. Under RCPs 2.6 and 8.5, the frequencies of severe and extreme droughts would increase, but the drought area would be smaller than that under RCP 4.5, demonstrating less severe drought conditions. Due to the shallow depths of most rivers, SDI was found to be more feasible than NDWI in detecting hydrological droughts.     

Impossible Differential Attacks on 13-Round CLEFIA-128

CLEFIA,a new 128-bit block cipher proposed by Sony Corporation,is increasingly attracting cryptanalysts’ attention.In this paper,we present two new impossible differential attacks on 13 rounds of CLEFIA-128.The proposed attacks utilize a variety of previously known techniques,in particular the hash table technique and redundancy in the key schedule of this block cipher.The first attack does not consider the whitening layers of CLEFIA,requires 2 109.5 chosen plaintexts,and has a running time equivalent to about 2 112.9 encryptions.The second attack preserves the whitening layers,requires 2 117.8 chosen plaintexts,and has a total time complexity equivalent to about 2 121.2 encryptions.     

Effect of nanoclay on relaxation and breakup of polyamide 6 threads in polystyrene matrix

In this work, we investigate the compatibilizing mechanism of nanoclay in binary polymer blends by measuring the interfacial tension of polystyrene/polyamide 6, PS/PA6, as a typical system, in the presence of nanoclay. The interfacial tension of PA6 nanocomposites and PS are determined with the breaking thread method by employing the Tomotika theory. The interfacial tension is reduced when organoclay is incorporated in the PA6 phase. To investigate the effect of the localization of nanoclay, nanoclay is intentionally located at the interface of PA6 and PS. Microscopic observations show that PA6 fiber remain unchanged and does not go through break-up process; therefore, one can deduce that the apparent interfacial tension of the system reduces significantly when nanoclay particles saturate the interface.     

Application of grid partitioning based fuzzy inference system as a novel predictor to estimate dynamic viscosity of n-alkane

Abstract

The oil recovery and rate of production are highly dependent on viscosity of reservoir fluid so this term becomes one of the attractive parameters in petroleum engineering. The viscosity of fluid is highly function of composition, temperature, and pressure so in this article, Grid partitioning based Fuzzy inference system approach is utilized as novel predictor to estimate dynamic viscosity of different normal alkanes in the wide range of operational conditions. In order to comparison of model output with actual data, an experimental dataset related to dynamic viscosity of n-alkanes is gathered. The graphical and statistical comparisons between model outputs and experimental data show the high quality performance of predicting algorithm. The coefficients of determination (R²) of training and testing phases are 0.9985 and 0.9980, respectively. The mentioned statistical indexes represent the great accuracy of model in prediction of dynamic viscosity.