In vitro antimicrobial effects of Myristica fragrans essential oil on foodborne pathogens and its influence on beef quality during refrigerated storage

Nutmeg (Myristica fragrans) seed was subjected to the hydro-distillation method to extract its essential oil (NEO). Its main constituents were α-pinene (20.16%), sabinene (14.45%), and β-pinene (13.26%) with great antimicrobial and antioxidant actions. A novel edible coating was then fabricated based on the sage seed mucilage (SSM) and NEO, to ameliorate the quality and shelf-life of beef slices. The NEO-loaded SSM coating was able to significantly decrease the population of total viable count, Escherichia coli, Staphylococcus aureus, psychrotrophic bacteria, and fungi. Moreover, lipid oxidation of beef slices was remarkably suppressed upon the application of bioactive NEO-loaded SSM edible coating, as compared with the control by Day 6. The coated beef sample, especially NEO-rich SSM coated ones perceived a higher consumer acceptance and firmness than the SSM coated and noncoated samples. The SSM edible coating containing NEO could therefore have the potential to control the growth of pathogenic microorganisms and lipid oxidation, and to improve the color stability and sensory properties of meat and meat products.     

A Fuzzy Logic-Based Method for Replica Placement in the Peer to Peer Cloud Using an Optimization Algorithm

The Peer to Peer-Cloud (P2P-Cloud) is a suitable alternative to distributed cloud-based or peer-to-peer (P2P)-based content on a large scale. The P2P-Cloud is used in many applications such as IPTV, Video-On-Demand, and so on. In the P2P-Cloud network, overload is a common problem during overcrowds. If a node receives many requests simultaneously, the node may not be able to respond quickly to user requests, and this access latency in P2P-Cloud networks is a major problem for their users. The replication method in P2P-Cloud environments reduces the time to access and uses network bandwidth by making multiple data copies in diverse locations. The replication improves access to the information and increases the reliability of the system. The data replication's main problem is identifying the best possible placement of replica data nodes based on user requests for data access time and an NP-hard optimization problem. This paper proposes a new replica replacement to improve average access time and replica cost using fuzzy logic and Ant Colony Optimization algorithm. Ants can find the shortest path to discover the optimal node to place the duplicate file with the least access time latency. The fuzzy module evaluates the historical information of each node to analyze the pheromone value per iteration. The fuzzy membership function is also used to determine each node's degree based on the four characteristics. The simulation results showed that the access time and replica cost are improved compared to other replica replacement algorithms.

     

Effect of Roasting on Physicochemical Properties of Wild Almonds (Amygdalus scoparia)

Roasting enhances sensory quality of wild almonds (Amygdalus scoparia). The aim of the study was to evaluate the use of microwaves (480 W for 3 or 4 min) in roasting of wild almonds in comparison with traditional Spanish (165 °C for 20 min) and Iranian (soaking in 20 % NaCl in water for 30 min, drying at 60 °C for 2 h and roasting at 135 °C for 20 min) hot‐air processes. The influence of roasting wild almonds on moisture and oil contents, crispness, fatty acid profile, volatile compounds, and odour intensity was investigated. Roasting causes changes in appearance, texture and flavour, due to dehydration, browning, lipid oxidation, and diverse structural changes. The moisture content and hardness of the samples significantly decreased with all roasting methods. Roasting resulted in higher amounts of characteristics aroma compounds and only microwave roasting increased the oil content. The final recommendation is that microwave roasting at 480 W for 4 min led to roasted almonds of high physicochemical [dark and intense colour (L*44.9, a*8.4, and b*19.6), the highest content of total volatile compounds (132 mg kg^?1), 85.2 % of unsaturated fatty acids], and sensory (high intensity of “roasted almond” aroma) quality. Microwaves can be used for roasting wild almond as a quick, safe, and economical method.     

Mechanical and thermal characterization of compression moulded polylactic acid natural fiber composites reinforced with hemp and lyocell fibers

This research evaluates the effects of PLA/PP blend ratio and Lyocell/hemp mixture ratio on the morphology, water absorption, mechanical and thermal properties of PLA‐based composites. The composites were fabricated with 30 mass % hemp using compression moulding. As a reference composites made from PP were also studied. Combining of hemp and Lyocell in PLA composite leads to the reduction of moisture absorption and can improve the impact, tensile, flexural properties when compared with PLA/hemp. Composite based on the PLA/PP blend‐matrix could not improve the tensile and flexural properties compared with PLA/hemp, however; the lighter composite with better impact properties was obtained. The crystallization temperature of the PLA‐PP/hemp increased compared with pure PLA. This result was also confirmed by the SEM micrographs. The moisture absorption of PLA‐PP/hemp was higher than PLA/hemp. Based on theoretical analysis of DMTA data, there was favorable adhesion in all composites. © 2014 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2014 , 131, 40534.     

Synthesis of TiO2-polymer nanocomposite in supercritical CO2 via RAFT polymerization

Polymer chains of PMMA were grown from nano titania (n-TiO₂) spherical surfaces by the Reversible Addition Fragmentation Chain Transfer Polymerization process (RAFT) using the green solvent, supercritical carbon dioxide (scCO₂). The RAFT agent (1), 4-cyano-4-(dodecylsulfanylthiocarbonylsulfanyl)pentanoic acid, with an available carboxyl group was first coordinated to the n-TiO₂ surface, with the SC(SC₁₂H₂₅) moiety subsequently used for RAFT polymerization of MMA to form the n-TiO₂/PMMA nanocomposites. The livingness of polymerization was verified using GPC, while the morphology of the nanocomposites was studied using thermogravimetric analysis (TGA), scanning electron microscopy (SEM) and dynamic light scattering (DLS). The rate of polymerization and molecular weights at different pressures in scCO₂ and in non-pressurized and pressurized organic solvent (THF) were compared, showing that increased CO₂ pressure provided a higher rate of polymerization and longer chain lengths indicating the utility of this approach.     

Effect of roasting on colour and volatile composition of pistachios (Pistacia vera L.)

Pistachios have been roasted following the Iranian traditional method (soaking in salty water, drying and roasting at 135 °C). Three Iranian pistachio cultivars (Ahmad Aghaei, Akbari and Kaleghouchi) were compared for their volatile compositions, colour and odour intensity. Lightness decreased in the course of roasting, which resulted from Maillard reaction. Raw pistachios had lower concentrations of most volatiles than roasted. A total of twenty‐six compounds were detected in roasted pistachios; these included aldehydes, terpenes, alcohols and only two pyrazines and one furan. These mixtures of volatiles implied that the Iranian roasting system is very soft, and samples retained most of the vegetable notes from fresh pistachios and some roasted notes were generated as well (from 2‐ethyl‐5‐methylpyrazine and 2,6‐dimethyl‐3‐ethylpyrazine). Sample from cultivar Akbari presented higher odour intensity than those by the other two cultivars, due mainly to higher concentrations of pyrazines developed during the roasting step.     

Optimization of Short Load Forecasting in Electricity Market of Iran Using Artificial Neural Networks

Accurate short-term load forecasting (STLF) is one of the essential requirements for power systems. In this paper, two different seasonal artificial neural networks (ANNs) are designed and compared in terms of model complexity, robustness, and forecasting accuracy. Furthermore, the performance of ANN partitioning is evaluated. The first model is a daily forecasting model which is used for forecasting hourly load of the next day. The second model is composed of 24 sub-networks which are used for forecasting hourly load of the next day. In fact, the second model is partitioning of the first model. Time, temperature, and historical loads are taken as inputs for ANN models. The neural network models are based on feed-forward back propagation which are trained and tested using data from electricity market of Iran during 2003 to 2005. Results show a good correlation between actual data and ANN outcomes. Moreover, it is shown that the first designed model consisting of single ANN is more appropriate than the second model consisting of 24 distinct ANNs. Finally ANN results are compared to conventional regression models. It is observed that in most cases ANN models are superior to regression models in terms of mean absolute percentage error (MAPE).     

Radiation pattern design of photonic crystal LED optimized by using multi-objective grey wolf optimizer

Photonic Network Communications - This paper proposes an effective method for shaping the radiation pattern intensity of photonic crystal (PhC) light-emitting diode (LED). In this method, the...