The ANFIS-PSO strategy as a novel method to predict interfacial tension of hydrocarbons and brine

The interfacial tension of hydrocarbons and brine is known as one of the important parameters which are measured in petroleum and petrochemical industries for example the interfacial tension has straight effect on trapping of oil in a reservoir. In the present work the Adaptive neuro-fuzzy inference system (ANFIS) algorithm was used as a novel approach for estimation of interfacial tension between hydrocarbons and brine as function of pressure, temperature, carbon number of hydrocarbon and ionic strength of brine then the particle swarm optimization (PSO) was used to optimize the predicting model parameters.in order to better evaluation of performance of predicting algorithm the coefficient of determination (R²), average absolute relative deviation (AARD) and root mean squared error (RMSE) were estimated for different steps. The outcomes of this investigation expressed that proposed model has high potential for prediction of interfacial tension between hydrocarbons and brine.     

Fibril density reduction in keratoconic corneas

This study aims to estimate the reduction in collagen fibril density within the central 6 mm radius of keratoconic corneas through the processing of microstructure and videokeratography data. Collagen fibril distribution maps and topography maps were obtained for seven keratoconic and six healthy corneas, and topographic features were assessed to detect and calculate the area of the cone in each keratoconic eye. The reduction in collagen fibril density within the cone area was estimated with reference to the same region in the characteristic collagen fibril maps of healthy corneas. Together with minimum thickness and mean central corneal refractive power, the cone area was correlated with the reduction in the cone collagen fibrils. For the corneas considered, the mean area of keratoconic cones was 3.30 ± 1.90 mm². Compared with healthy corneas, fibril density in the cones of keratoconic corneas was lower by as much as 35%, and the mean reduction was 17 ± 10%. A linear approximation was developed to relate the magnitude of reduction to the refractive power, minimum corneal thickness and cone area (R² = 0.95, p < 0.001). Outside the cone area, there was no significant difference between fibril arrangement in healthy and keratoconic corneas. The presented method can predict the mean fibril density in the keratoconic eye''s cone area. The technique can be applied in microstructure-based finite-element models of the eye to regulate its stiffness level and the stiffness distribution within the areas affected by keratoconus.     

Nanoparticulation of enzymatically cross-linked whey proteins to encapsulate caffeine via microemulsification/heat gelation procedure

A co-surfactant free microemulsion was formulated with sunflower oil, span 80 and whey protein solution and used as nanoreactor to generate caffeine-enveloping capsules through heat gelation of protein. Transglutaminase-induced cross-linking of proteins prior to microemulsification decreased the mean diameter from 478 to 318 nm for core-free particles and from 232 to 118 nm for capsules. As well, the lower limit of capsules size decreased from 78 nm to 45 nm due to enzymatic cross-linking. Scanning electron microscopy showed that morphology of particles and capsules was not completely spherical which was attributed to the protrusion of protein molecules out of aqueous droplets during gelation. The enzymatic treatment yielded in particles with higher glass transition temperature due to the reinforced structure of particulate gel. Fourier transform infrared spectroscopy confirmed the structural changes in proteins by heat and establishment of covalent cross-linkages by the enzyme action manifested by a band at 1078 cm⁻¹.     

Trans-free Iranian vanaspati through enzymatic and chemical transesterification of triple blends of fully hydrogenated soybean,rapeseed and sunflower oils

Production of trans-free Iranian vanaspati through enzymatic and chemical transesterification of triple blends of fully hydrogenated soybean (FHSBO), rapeseed (RSO) and sunflower (SFO) oils was investigated. The slip melting point (SMP), solid fat content (SFC) at 10–40 °C and induction period of oxidation at 120 °C (IP₁₂₀) of the transesterified and initial blends were evaluated. Results indicated that all the enzymatically and chemically transesterified blends had lower SMP, SFC and IP₁₂₀ than their initial blends. No significant differences (P < 0.05) were observed between the SMP of enzymatically and chemically transesterified blends. Some enzyme treated blends had higher SFC at some temperatures than chemically transesterified ones. Enzymatically transesterified blends had higher IP₁₂₀ than those prepared by chemical transesterification. Correlation between SFC at 20 °C and saturated fatty acid (SFA) content, and between SMP and SFA of transesterified blends indicated that the SFA must be between 27.2% and 36.6% for enzymatic and 28.4% and 37.8% for chemical transesterification to obtain transesterified fats suitable for use as vanaspati.     

Simultaneous Culturing of Cell Monolayers and Spheroids on a Single Microfluidic Device for Bridging the Gap between 2D and 3D Cell Assays in Drug Research

Two‐dimensional (2D) cell cultures have been the primary screening tools to predict drug impacts in vitro for decades. However, owing to the lack of tissue‐specific architecture of 2D cultures, secondary screening using three‐dimensional (3D) cell culture models is often necessary. A microfluidic approach that facilitates side‐by‐side 2D and 3D cell culturing in a single microchannel and thus combines the benefits of both set‐ups in drug screening; that is, the uniform spatiotemporal distributions of oxygen, nutrients, and metabolic wastes in 2D, and the tissue‐like architecture, cell–cell, and cell–extracellular matrix interactions only achieved in 3D. The microfluidic platform is made from an organically modified ceramic material, which is inherently biocompatible and supports cell adhesion (2D culture) and metal adhesion (for integration of impedance electrodes to monitor cell proliferation). To induce 3D spheroid formation on another area, a single‐step lithography process is used to fabricate concave microwells, which are made cell‐repellant by nanofunctionalization (i.e., plasma porosification and hydrophobic coating). Thanks to the concave shape of the microwells, the spheroids produced on‐chip can also be released, with the help of microfluidic flow, for further off‐chip characterization after culturing. In this study, the methodology is evaluated for drug cytotoxicity assessment on human hepatocytes.     

Firefly-inspired algorithm for discrete optimization problems: An application to manufacturing cell formation

The canonical firefly algorithm is basically developed for continuous optimization problems. However, lots of practical problems are formulated as discrete optimization problems. The main purpose of this paper is to present the discrete firefly algorithm (DFA) to solve discrete optimization problems. In the DFA, we define a firefly's position in terms of changes of probabilities that will be in one state or the other. Then by using this metaheuristic algorithm, the manufacturing cell formation problem is solved. To illustrate the behavior of the proposed model and verify the performance of the algorithm, we introduce a number of numerical examples to illustrate the use of the foregoing algorithm. The performance evaluation shows the effectiveness of the DFA. The proposed metaheuristic algorithm should thus be useful to both researchers and practitioners.     

Hyperspectral anomaly detection using spectral–spatial features based on the human visual system

ABSTRACT

Anomaly detection (AD) is one of the most attracting topics within the recent 10 years in hyperspectral imagery (HSI). The goal of the AD is to label the pixels with significant spectral or spatial differences to their neighbours, as targets. In this paper, we propose a method that uses both spectral and spatial information of HSI based on human visual system (HVS). By inspiring the retina and the visual cortex functionality, the multiscale multiresolution analysis is applied to some principal components of hyperspectral data, to extract features from different spatial levels of the image. Then the global and local relations between features are considered based on inspiring the visual attention mechanism and inferotemporal (IT) part of the visual cortex. The effects of the attention mechanism are implemented using the logarithmic function which well highlights, small variations in pixels’ grey levels in global features. Also, the maximum operation is used over the local features for imitating the function of IT. Finally, the information theory concept is used for generating the final detection map by weighting the global and local detection maps to obtain the final anomaly map. The result of the proposed method is compared with some state-of-the-art methods such as SSRAD, FLD, PCA, RX, KPCA, and AED for two well-known real hyperspectral data which are San Diego airport and Pavia city, and a synthetic hyperspectral data. The results demonstrate that the proposed method effectively improves the AD capabilities, such as enhancement of the detection rate, reducing the false alarm rate and the computation complexity.     

Belief revision in structured probabilistic argumentation

In real-world applications, knowledge bases consisting of all the available information for a specific domain, along with the current state of affairs, will typically contain contradictory data, coming from different sources, as well as data with varying degrees of uncertainty attached. An important aspect of the effort associated with maintaining such knowledge bases is deciding what information is no longer useful; pieces of information may be outdated; may come from sources that have recently been discovered to be of low quality; or abundant evidence may be available that contradicts them. In this paper, we propose a probabilistic structured argumentation framework that arises from the extension of Presumptive Defeasible Logic Programming (PreDeLP) with probabilistic models, and argue that this formalism is capable of addressing these basic issues. The formalism is capable of handling contradictory and uncertain data, and we study non-prioritized belief revision over probabilistic PreDeLP programs that can help with knowledge-base maintenance. For belief revision, we propose a set of rationality postulates — based on well-known ones developed for classical knowledge bases — that characterize how these belief revision operations should behave, and study classes of operators along with theoretical relationships with the proposed postulates, including representation theorems stating the equivalence between classes of operators and their associated postulates. We then demonstrate how our framework can be used to address the attribution problem in cyber security/cyber warfare.