Statistical mechanics and artificial intelligence to model the thermodynamic properties of pure and mixture of ionic liquids

In this paper, the volumetric properties of pure and mixture of ionic liquids are predicted using the developed statistical mechanical equation of state in different temperatures, pressures and mole fractions. The temperature dependent parameters of the equation of state have been calculated using corresponding state correlation based on only the density at 298.15 K as scaling constants. The obtained mean of deviations of modified equation of state for density of al pure ionic liquids for 1662 data points was 0.25%. In addition, the performance of the arti-ficial neural network (ANN) with principle component analysis (PCA) based on back propagation training with 28 neurons in hidden layer for predicting of behavior of binary mixtures of ionic liquids was investigated. The AADs of a col ection of 568 data points for al binary systems using the EOS and the ANN at various temperatures and mole fractions are 1.03%and 0.68%, respectively. Moreover, the excess molar volume of all binary mixtures is predicted using obtained densities of EOS and ANN, and the results show that these properties have good agree-ment with literature.     

Changes in the physicochemical,microstructural and rheological properties of traditional Kope cheese during ripening

The effect of ripening time on the microstructural, physicochemical and rheological characteristics of traditional Kope cheese ripened in clay pots was investigated. The moisture content, pH and total nitrogen (TN)/dry matter (DM) of the cheese decreased, and DM, fat in DM and water‐soluble nitrogen/TN increased during this period. Storage and loss moduli increased, while loss tangent decreased; as a result, the elasticity characteristics were greater than the viscous characteristics of the samples. Microstructure images showed that the size of pores and casein network density increased significantly during ripening and, after 90 days, the structure of many pores became very similar to each other.     

Fuzzy Logic Based Distance and Energy-Aware Routing Protocol in Delay-Tolerant Mobile Sensor Networks

In challenged networks such as Wireless Sensor Networks, limitations such as nodes mobility, short radio range and sparse network density can prevent communications among nodes. Consequently, it can result in long delays in exchanging messages among nodes. Designing Delay-Tolerant Networks is considered to be an approach for dealing with lengthy breakdown of communication between nodes. Using multi-replica methods seems rational for these networks. However, a majority of these methods inject a large amount of replications of a message in the network so as to enhance message delivery probability which consequently leads to the loss of energy and reduction of network efficiency. Two major issues should be considered to achieve data delivery in such challenging networking environments: a routing strategy for the network and a buffer management policy. This study proposes a new routing protocol called Fuzzy-Logic based Distance and Energy Aware Routing protocol (FLDEAR) in delay tolerant mobile sensor network. A FLDEAR is a distance and energy aware protocol that reduces the number of message replications and uses two fuzzy inference systems in routing and buffer management. The results of conducted simulations indicated that this routing algorithm can be used for enhancing data packet delivery ratios and reducing data transmission overhead than several current Delay-Tolerant Mobile Sensor Networks routing protocols.     

Air pollution prediction by using an artificial neural network model

Clean Technologies and Environmental Policy - Air pollutants impact public health, socioeconomics, politics, agriculture, and the environment. The objective of this study was to evaluate the...     

Dy2BaCuO5/Ba4DyCu3O9.09 S-scheme heterojunction nanocomposite with enhanced photocatalytic and antibacterial activities

Semiconductor heterogeneous photocatalysis has been received much attention from the scientific and researchers in the last decade. The combination of two semiconductors with various energy diagram can dramatically enhance the lifetime and separation of the charge carriers, restrain photogenerated electron-hole recombination, and considerably enhance photocatalytic performance as compared with other single or binary components. In this regard, we introduced the Dy₂BaCuO₅/Ba₄DyCu₃O_9.09 nanocomposites as active photocatalysts below UV radiation. Dy₂BaCuO₅/Ba₄DyCu₃O_9.09 nanocomposites were prepared by a simple hydrothermal method and applied as a catalyst to treat water containing organic pollutions and microorganisms. Dy₂BaCuO₅/Ba₄DyCu₃O_9.09 nanocomposites degraded Methyl Orange (MO) about 87.0% after 120 min. In addition, these nanocomposites show antimicrobial activity against Gram-positive species, including a pathogenic strain of Enterococcus faecalis, and Staphylococcus aureus, and a Gram-negative species, including Klebsiella pneumonia and Escherichia coli.     

Programmable Self-Regulation with Wrinkled Hydrogels and Plasmonic Nanoparticle Lattices

This paper describes a self-regulating system that combines wrinkle-patterned hydrogels with plasmonic nanoparticle (NP) lattices. In the feedback loop, the wrinkle patterns flatten in response to moisture, which then allows light to reach the NP lattice on the bottom layer. Upon light absorption, the NP lattice produces a photothermal effect that dries the hydrogel, and the system then returns to the initial wrinkled configuration. The timescale of this regulatory cycle can be programmed by tuning the degree of photothermal heating by NP size and substrate material. Time-dependent finite element analysis reveals the thermal and mechanical mechanisms of wrinkle formation. This self-regulating system couples morphological, optical, and thermo-mechanical properties of different materials components and offers promising design principles for future smart systems.     

An evolutionary computation approach to solving repairable multi-state multi-objective redundancy allocation problems

Neural Computing and Applications - The redundancy allocation problem (RAP) is an optimization problem for maximizing system reliability at a predetermined time. Among the several extensions of...     

Cogrinding as an approach to enhance dissolution rate of a poorly water-soluble drug (gliclazide)

Gliclazide is practically insoluble in water. In order to improve the drug dissolution rate, cogrinding method was used as an approach to prepare gliclazide coground/solid dispersions (SDs) in the carriers such as povidone (PVP-K30), crospovidone and microcrystalline cellulose (Avicel PH 101) with different drug to carrier ratios. The dissolution rate of gliclazide from the SDs was measured at two physiological pH values of 1.2 and 7.2 simulating gastric and intestinal fluids using USP dissolution apparatus II. The concentration of the dissolved drug in the medium was determined by direct or first-derivative UV spectroscopy. The dissolution rates of the formulations were dependent on the nature and ratio of drug to carriers in SDs and the corresponding physical mixtures as well as the pH of the medium. At a higher pH the drug has a faster dissolution than at a lower pH. The fastest dissolution rates were observed from coground formulations with the drug to carrier ratio of 1:5. The amount of drug dissolved in 15 min from these SDs was varied from 96% in the case of Avicel SD to 100% for SD of PVP. Whereas the amount of drug released in the same time from unground drug powder (UD), ground drug powder (GD) and all physical mixtures was between 60 and 80%. These results indicate that the dissolution rate is highly enhanced from the SDs. DSC as well as X-ray diffraction showed reduced drug crystallinity in SDs. Scanning electron microscopy and particle size analysis revealed significant decreased particle size of the drug in SDs. FT-IR spectroscopy demonstrated no detectable interactions between the drug and carriers. In addition to latter evidence, increased wettability and hydrophilicity of drug particles and deaggregation brought about by the carriers are the reasons for enhanced drug dissolution from the SDs. One of the possible advantages of formulating an insoluble drug such as gliclazide is that if it is used in preparation of capsules or tablets of the drug, its dose might be reduced which is economically beneficial.