Anthocyanins characterization of 15 Iranian pomegranate (Punica granatum L.) varieties and their variation after cold storage and pasteurization

Anthocyanins (ACs) are phenolic compounds that are distributed widely in fruits and vegetables. Apart from imparting color to plants, ACs also have an array of health-promoting benefits. In this research, the amounts of major ACs of 15 pomegranate (Punica granatum L.) varieties obtained from Yazd province were determined. The major ACs detected in the studied varieties were as follows: delphinidin 3-glucoside (2.19–16.29 mg/L), delphinidin 3,5-diglucoside (2.36–63.07 mg/L), pelargonidin 3-glucoside (0.26–1.36 mg/L), pelargonidin 3,5-diglucoside (0.01–8.11 mg/L), cyanidin 3-glucoside (5.78–30.38 mg/L), and cyanidin 3,5-diglucoside (4.39–166.32 mg/L). The effect of storage time of unprocessed and pasteurized juices on ACs content of four selected varieties was also studied. Average degradation percentage of each AC was between 23.0 and 83.0% during 10 days at 4 °C. Moreover, in pasteurized juices average degradation of ACs was 42.8 ± 0.5% after 10 weeks storage at 4 °C.     

Intelligent non-linear modelling of an industrial winding process using recurrent local linear neuro-fuzzy networks

This study deals with the neuro-fuzzy (NF) modelling of a real industrial winding process in which the acquired NF model can be exploited to improve control performance and achieve a robust fault-tolerant system. A new simulator model is proposed for a winding process using non-linear identification based on a recurrent local linear neuro-fuzzy (RLLNF) network trained by local linear model tree (LOLIMOT), which is an incremental tree-based learning algorithm. The proposed NF models are compared with other known intelligent identifiers, namely multilayer perceptron (MLP) and radial basis function (RBF). Comparison of our proposed non-linear models and associated models obtained through the least square error (LSE) technique (the optimal modelling method for linear systems) confirms that the winding process is a non-linear system. Experimental results show the effectiveness of our proposed NF modelling approach.     

On the application of Harris hawks optimization (HHO) algorithm to the design of microchannel heat sinks

Engineering with Computers - A novel Harris hawks optimization algorithm is applied to microchannel heat sinks for the minimization of entropy generation. In the formulation of the heat transfer...     

Supporting multiple perspectives in feature-based configuration

Feature diagrams have become commonplace in software product line engineering as a means to document variability early in the life cycle. Over the years, their application has also been extended to assist stakeholders in the configuration of software products. However, existing feature-based configuration techniques offer little support for tailoring configuration views to the profiles of the various stakeholders. In this paper, we propose a lightweight, yet formal and flexible, mechanism to leverage multidimensional separation of concerns in feature-based configuration. We propose a technique to specify concerns in feature diagrams and to generate automatically concern-specific configuration views. Three alternative visualisations are proposed. Our contributions are motivated and illustrated through excerpts from a real web-based meeting management application which was also used for a preliminary evaluation. We also report on the progress made in the development of a tool supporting multi-view feature-based configuration.     

A Model for Identifying the Behavior of Alzheimer’s Disease Patients in Smart Homes

Wireless Personal Communications - In recent years, Smart Cities and Smart Homes have been studied as an important field of research. The design and construction of smart homes have flourished so...     

Modeling soft granular materials

Soft-grain materials such as clays and other colloidal pastes share the common feature of being composed of grains that can undergo large deformations without rupture. For the simulation of such materials, we present two alternative methods: (1) an implicit formulation of the material point method (MPM), in which each grain is discretized as a collection of material points, and (2) the bonded particle model (BPM), in which each soft grain is modeled as an aggregate of rigid particles using the contact dynamics method. In the MPM, a linear elastic behavior is used for the grains. In order to allow the aggregates in the BPM to deform without breaking, we use long-range center-to-center attraction forces between the primary particles belonging to each grain together with steric repulsion at their contact points. We show that these interactions lead to a plastic behavior of the grains. Using both methods, we analyze the uniaxial compaction of 2D soft granular packings. This process is nonlinear and involves both grain rearrangements and large deformations. High packing fractions beyond the jamming state are reached as a result of grain shape change for both methods. We discuss the stress-strain and volume change behavior as well as the evolution of the connectivity of the grains. Similar textures are observed at large deformations although the BPM requires higher stress than the MPM to reach the same level of packing fraction.     

On the Efficiency of Runs Rules Schemes for Process Monitoring

There are two main types of variations, namely, common and special causes leading to in‐control and out‐of‐control states, respectively. Control charts are popular tools used to differentiate between these two states of a process. Implementation of runs rules schemes with control charts is an attractive approach for process monitoring. This study is designed to describe the methodology of runs rules schemes and discuss their implementation for different types of control charts. We have considered memory‐less charts, namely, , S, and R charts for our study purposes. It is examined that the efficiency gain depends on the number of decision points utilized to implement a given rule. Moreover, superiority of runs rules schemes may vary for different types of location and dispersion charts. An application example using a dataset is also included in the study for practical considerations. Copyright © 2015 John Wiley & Sons, Ltd.     

Improving the running time of embedded upward planarity testing

We consider the standard algorithm by Bertolazzi et al. to test the upward planarity of embedded digraphs. We show how to improve its running time from O(n+r²) to , where r is the number of sources and sinks in the digraph. We also discuss an application of this technique: improving the running time of getting a quasi-upward planar drawing for an embedded digraph with minimum number of bends.     

Interactions of inorganic oxide nanoparticles with sewage biosolids

The use of nanoparticles (NPs) in manufacturing continues to increase despite the growing concern over their potential environmental and health effects. Understanding the interaction of NPs and sewage sludge is crucial for determining the ultimate fate of NPs released to municipal wastewater treatment plants (WWTPs) as those interactions will determine whether the bulk of the material is retained in the sludge or released in the effluent stream. Analyzing the affinity of aluminum oxide, cerium oxide, and silicon oxide NPs, which are commonly used in semiconductor manufacturing processes, for biosolids used in municipal WWTPs provides a basis for estimating their removal efficiency. Batch studies were performed and the NPs were shown to partition onto the cellular surface. At the maximum equilibrium values tested (75-92 mg nanoparticles/L), the concentration of Al(2)O(3), CeO(2) and SiO(2) associated with the sludge was 137, 238, and 28 mg/g-sludge VSS, respectively. These results suggest that electrostatic interactions play a major role in determining NP association with biosolids.     

Prediction of the Failure Time of Glass Fiber Reinforced Plastic Reinforced Concrete Beams under Fire Conditions

A model is proposed to predict the time to failure of reinforced concrete beams in a fire. The model is developed specifically to predict the lifetime of beams reinforced with glass fiber reinforced plastic rebar, but is applicable to beams with any form of reinforcement. The model is based on the calculations for flexural capacity and shear capacity of beams embedded within ACI design codes where time and temperature dependent values for rebar modulus and strength and concrete strength replace the static design values. The base equations are modified to remove safety factors and where necessary the temperature induced reductions in strength for concrete and steel are derived using the equations presented by EUROCODE 2. In order to validate the model it was used to predict the failure times of steel rebar reinforced beams that had been documented in the literature. There was excellent agreement between the model and the reported lifetimes for these conventional beams. The model was applied to predict the lifetimes of two beams that had been manufactured and tested for destruction in a fire by the research group. The model predicted that the failure mode of the beams would be because of rebar rupture as opposed to the design condition of concrete crushing and this was confirmed by the experimental test results. The model provided reasonable agreement with experimental results with a lifetime of 108?min predicted based on flexural failure and 94 and 128?min observed in the experiments.