A simple model for predicting solid concentration distribution in binary‐solid liquid fluidized beds

A simple mathematical model for predicting the solid concentration profile in binary‐solid liquid fluidized beds is presented. The main assumption is that the solid concentration distribution follows the logistic function, which is supported by the literature. Various equations have been derived to solve key system quantities (e.g., bed expansion height, length and position of the transition zone). In contrast to previous models that often involve adjustable parameters and strongly rely on the availability of experimental data, the present model only requires inputs of fluid and particle properties, operating conditions, and correlations for dispersion and slip velocity. The results showed that the model is applicable to different binary‐solid systems that have size and/or density differences. The model's capability of predicting the layer inversion phenomenon has also been demonstrated. The model is simple but proves capable of accurately predicting key information for the design, operation and scale up of liquid fluidized beds. © 2016 American Institute of Chemical Engineers AIChE J, 63: 469–484, 2017     

Encapsulation Efficiency of Food Flavours and Oils during Spray Drying

Microencapsulation is a rapidly expanding technology which is a unique way to package materials in the form of micro- and nano-particles, and has been well developed and accepted within the pharmaceutical, chemical, food and many other industries. Spray drying is the most commonly used encapsulation technique for food products. A successful spray drying encapsulation relies on achieving high retention of the core materials especially volatiles and minimum amounts of the surface oil on the powder particles for both volatiles and non-volatiles during the process and storage. The properties of wall and core materials and the prepared emulsion along with the drying process conditions will influence the efficiency and retention of core compounds. This review highlights the new developments in spray drying microencapsulation of food oils and flavours with an emphasis on the encapsulation efficiency during the process and different factors which can affect the efficiency of spray drying encapsulation.     

Hybrid binary arithmetic optimization algorithm with simulated annealing for feature selection in high-dimensional biomedical data

Gene expression data play a significant role in the development of effective cancer diagnosis and prognosis techniques. However, many redundant, noisy, and irrelevant genes (features) are present in the data, which negatively affect the predictive accuracy of diagnosis and increase the computational burden. To overcome these challenges, a new hybrid filter/wrapper gene selection method, called mRMR-BAOAC-SA, is put forward in this article. The suggested method uses Minimum Redundancy Maximum Relevance (mRMR) as a first-stage filter to pick top-ranked genes. Then, Simulated Annealing (SA) and a crossover operator are introduced into Binary Arithmetic Optimization Algorithm (BAOA) to propose a novel hybrid wrapper feature selection method that aims to discover the smallest set of informative genes for classification purposes. BAOAC-SA is an enhanced version of the BAOA in which SA and crossover are used to help the algorithm in escaping local optima and enhancing its global search capabilities. The proposed method was evaluated on 10 well-known microarray datasets, and its results were compared to other current state-of-the-art gene selection methods. The experimental results show that the proposed approach has a better performance compared to the existing methods in terms of classification accuracy and the minimum number of selected genes.

     

The Synthesis and Characterization of Hard-Soft Mn52Al45.7C2.3-α-Fe Nanocomposite Magnets

We report on the magnetic exchange coupling behavior in hard-soft Mn₅₂Al_45.7C_2.3-α-Fe nanocomposite magnets synthesized by high-energy ball milling at room temperature followed by post-annealing treatment at temperatures 300 to 600 °C. The analysis of hysteresis loops showed effective exchange coupling Mn₅₂Al_45.7C_2.3-α-Fe nanocomposite particles with smooth demagnetizing curves when annealed at 400 °C. But higher annealing temperatures pose kink in the hysteresis loop highlighting a weak exchange coupling with more magnetostatic interaction between hard and soft components. This trend was confirmed by the results on (BH)_max, which had the highest value for nanocomposite particles annealed at 400 °C. More detailed information on magnetic exchange coupling in nanocomposite particles was obtained by derivative magnetic curves and Henkel plots. Hard-soft Mn₅₂Al_45.7C_2.3-α-Fe magnets showed the sharpest high-field maximum in derivate magnetic curves when annealed at 400 °C as a signature of effective exchange coupling between Mn₅₂Al_45.7C_2.3 and α-Fe grains. In addition, Henkel plots display the dominance of positive peak for nanocomposite particles annealed at 300 and 400 °C, indicative of magnetic exchange-coupling. But the negative-peak dominated curves of those annealed at higher temperatures as well as single-phase Mn₅₂Al_45.7C_2.3 imply a significant magnetostatic interaction in the components owing to non-magnetic phases formed at elevated temperatures. Also, quantitative information obtained from recoil curve measurements assigned a higher degree of exchange coupling to nanocomposite magnets when annealed at 400 °C.

     

Robust image watermarking scheme using bit-plane of hadamard coefficients

Multimedia Tools and Applications - Nowadays, due to widespread usage of the Internet, digital contents are distributed quickly and inexpensively throughout the world. Watermarking techniques can...     

Microblogs recommendations based on implicit similarity in content social networks

With the development of online social networking applications, microblogs have become a necessary online communication network in daily life. Users are interested in obtaining personalized recommendations related to their tastes and needs. In some microblog systems, tags are not available, or the use of tags is rare. In addition, user-specified social relations are extremely rare. Hence, sparsity is a problem in microblog systems. To address this problem, we propose a new framework called Pblog to alleviate sparsity. Pblog identifies users’ interests via their microblogs and social relations and computes implicit similarity among users using a new algorithm. The experimental results indicated that the use of this algorithm can improve the results. In online social networks, such as Twitter, the number of microblogs in the system is high, and it is constantly increasing. Therefore, providing personalized recommendations to target users requires considerable time. To address this problem, the Pblog framework groups similar users using the analytic hierarchy process (AHP) method. Then, Pblog prunes microblogs of the target user group and recommends microblogs with higher ratings to the target user. In the experimental results section, the Pblog framework was compared with several other frameworks. All of these frameworks were run on two datasets: Twitter and Tumblr. Based on the results of these comparisons, the Pblog framework provides more appropriate recommendations to the target user than previous frameworks.

     

Synthesis and Characterization of Copper(II)–Cysteine/SiO2–Al2O3 as an Efficient and Reusable Heterogeneous Catalyst for the Oxidation of Aromatic Alcohols

In the present study, heterogeneous copper(II)–cysteine/SiO₂–Al₂O₃ catalyst was successfully prepared by a simple adsorption method. The physical and chemical properties of Cu(II)–cysteine/SiO₂–Al₂O₃ were investigated by X-ray diffraction, thermal gravimetric analyzer, FT–IR spectroscopy, Brunauer–Emmett–Teller, UV–Vis spectroscopy, scanning electron microscopy and atomic absorption spectrometer. The obtained composite was effectively employed as catalyst for selective oxidation of various aromatic alcohols to corresponding aldehydes in high yields using hydrogen peroxide as an oxidant under mild condition. The catalyst can be recycled over five times without significant loss of activity.     

An efficient extraction and clean‐up procedure for pesticide determination in olive oil

This work reports a simple, rapid, and effective extraction method based on liquid–liquid extraction (LLE) followed by matrix solid‐phase dispersion‐sonication for detection, identification and quantification of multiclass pesticides in virgin olive oil using liquid chromatography mass spectrometry (LC‐QTOF‐MS). LLE to extract pesticide residues in virgin olive oil was performed in order to study the centrifugation efficiency to obtain high recovery yield and low co‐extract fat residue in the final extract. Different suitable parameters of MSPD procedure were evaluated, such as nature of dispersing phase, clean‐up adsorbent, and volume of eluting solvent (acetonitrile) in different extraction conditions, with or without sonication. The best results were obtained using 5 g of virgin olive oil, 2 g of PSA as dispersant sorbent, 2 g of Florisil/GCB (70:30 w/w) as clean‐up sorbent, and 15 mL of acetonitrile as eluting solvent under conditions of 15 min ultrasonic bath at RT. Method validation was performed in order to study sensitivity, linearity, precision, and accuracy. Average recoveries ranged between 73.7 and 104.2% with relative SDs 5.3–13.4% at three concentration levels (25, 50, and 100 µg/kg). Detection and quantification limits ranged from 1.5 to 5 µg/kg and 3 to 9 µg/kg, respectively.