Physicochemical assessment of fresh chilled dairy dessert supplemented with wheat germ

Wheat germ is an available and economical source of protein, vitamins and antioxidants with an increasing application in food products. The main aim of this study was to investigate the effects of different levels (0.0, 2.5, 5.0, 7.5 and 10.0%) and particle sizes (120, 210 and 354 μm) of wheat germ on physicochemical properties of fresh chilled dairy dessert. With increasing wheat germ level, dry matter of the dessert increased while the pH decreased. Particle size had no significant effect on these parameters. Increasing the wheat germ content and particle size enhanced darkness, hardness, cohesiveness and gumminess of the desserts while decreasing springiness and water release of the samples. Wheat germ level had greater effects on different quality aspects of the desserts than its particle size. The most acceptable dessert was produced with no more than 5.0% wheat germ with either of the particle sizes used in this study.     

FeO0.7F1.3/C Nanocomposite as a High‐Capacity Cathode Material for Sodium‐Ion Batteries

Searching high capacity cathode materials is one of the most important fields of the research and development of sodium‐ion batteries (SIBs). Here, we report a FeO_0.7F_1.3/C nanocomposite synthesized via a solution process as a new cathode material for SIBs. This material exhibits a high initial discharge capacity of 496 mAh g^?1 in a sodium cell at 50 °C. From the 3^rd to 50^th cycle, the capacity fading is only 0.14% per cycle (from 388 mAh g^?1 at 3^rd the cycle to 360 mAh g^?1 at the 50^th cycle), demonstrating superior cyclability. A high energy density of 650 Wh kg^?1 is obtained at the material level. The reaction mechanism studies of FeO_0.7F_1.3/C with sodium show a hybridized mechanism of both intercalation and conversion reaction.     

A self‐learning stream classifier for flow‐based botnet detection

Botnets have been recently recognized as one of the most formidable threats on the Internet. Different approaches have been designed to detect these types of attacks. However, as botnets evolve their behavior to mislead the signature‐based detection systems, learning‐based methods may be deployed to provide a generalization capacity in identifying unknown botnets. Developing an adaptable botnet detection system, which incrementally evolves with the incoming flow stream, remains as a challenge. In this paper, a self‐learning botnet detection system is proposed, which uses an adaptable classification model. The system uses an ensemble classifier and, in order to enhance its generalization capacity, updates its model continuously on receiving new unlabeled traffic flows. The system is evaluated with a comprehensive data set, which contains a wide variety of botnets. The experiments demonstrate that the proposed system can successfully adapt in a dynamic environment where new botnet types are observed during the system operation. We also compare the system performance with other methods.     

Community Structure and Information Cascade in Signed Networks

In this paper, we study information cascade in networks with positive and negative edges. The cascade depth is correlated with community structure of signed networks where communities are defined such that positive inter-community and negative intra-community links are minimized. The cascade is initialized from a number of nodes that are selected randomly. Finally, the number of nodes that have participated in the cascade is interpreted as cascade depth; the more the number of such nodes, the more the depth of the cascade. We investigate influence of community structure (i.e., percentage of inter-community positive and intra-community negative links) on the cascade depth. We find significant influence of community structure on cascade depth in both model and real networks. Our results show that the more the intra-community negative links (i.e., the worse the community structure), the more the cascade depth.     

Synthesis and characterization of PVAm/SBA-15 as a novel organic–inorganic hybrid basic catalyst

Composite polyvinyl amine/SBA-15 (PVAm/SBA-15) in various amounts of SBA-15 were prepared and characterized. The physical and chemical properties of PVAm/SBA-15 were investigated using FT-IR, XRD, BET, SEM and TGA techniques. The catalytic performance of each material was determined for the Knoevenagel condensation reaction between carbonyl compounds and ethyl cyanoacetate in the presence of ethanol as solvent. The effects of reaction temperature, solvent and the amounts of catalyst as well as recyclability of the catalyst were investigated. The catalyst used for this synthetically useful transformation showed a considerable degree of reusability besides being very active.     

Development of healthy extruded maize snacks; Effects of soybean flour and feed moisture content

The main aim of this research was to introduce a green and clean method of increasing the nutritional quality while preserving the quality of extruded maize snacks. This was achieved by addition of soybean flour (5%, 10%, 15% and 20%, w/w) as a source of plant protein, fibre and bioactive compounds and changing the feed moisture content. Extruded samples were produced using a single-screw extruder. Increasing the soybean flour and feed moisture content resulted in reduced specific mechanical energy of the extruder and consequently several changes in physicochemical properties of the snacks including higher moisture content, lower expansion and volume, reduced crispiness, reduction in L-and a-values but an increase in b-value and formation of more wrinkly and thicker air bubbles cell walls as observed under scanning electron microscope. The addition of <20% soybean flour and feed moisture content resulted in snacks with improved nutritional value and physical properties.     

RAPID: a knowledge-based assistant for designing web APIs

Requirements Engineering - With the rise in initiatives such as software ecosystems and Internet of Things (IoT), developing web Application Programming Interfaces (web APIs) has become an...     

The effects of the challenges in the transliteration of Persian names into English on the recall of retrieved results in the web of science

Scientometrics - The objective of this study was to examine the effects of the challenges in the transliteration of Persian names into English on the recall of retrieved results in the Web of...