Experimental validation of a deep neural network—Sparse representation classification ensemble method

In the current study, a new pattern recognition‐based damage detection technique is developed using the frequency response function of the structure. Principal component analysis is employed as an authoritative feature extraction method for dimensional reduction of the measured frequency response function data and constructing distinct feature patterns. Subsequently, as a novel approach, an ensemble of 2 powerful classifiers containing deep neural networks and couple sparse coding classification is utilized for damage prediction of the structure because there is no individual optimal classifier for all the problems. Verification of the proposed method is evaluated by an aluminum beam experimental setup besides a numerical 3D finite element model of a truss bridge. Damage detection results elucidate that the ensemble method decisions are much more accurate compared with the individual classifier decision. The proposed ensemble method verifies to be a novel, robust, and powerful damage detection process.     

A Complex Network Methodology for Travel Demand Model Evaluation and Validation

Networks and Spatial Economics - Travel demand can be viewed as a weighted and directed graph where nodes are the origins and destinations and links represent the trips between nodes. This paper...     

Characteristics of vitamin E-loaded nanofibres from dextran

In this research, dextran nano?bres were produced as novel carriers for entrapment of vitamin E. Morphological studies indicated that developed fine fibres were in the nano range without spherical beads. Thermal behaviour, chemical structure, and crystalline structure of vitamin E-loaded nanofibres were analysed by differential scanning calorimetry, Fourier transform infrared spectroscopy, and X-ray diffraction which showed that the vitamin was well incorporated within the amorphous structure of fibres without chemical interactions. Nanofibres were used for fortification of cheese. Sensory analysis of the fortified product was performed which showed better acceptability and texture of cheese containing nanofibres in comparison to blank and direct fortified samples. Nanofibres showed the capability of holding water and thus increasing cheese firmness. The release of vitamin E in gastrointestinal media showed that about 14% of vitamin could be released in gastric media and about 30% released in intestinal media. Finally, the results revealed that electrospinning can be used for production of dextran ultrathin fibres to entrap hydrophobic compounds with high potential for design of novel functional foods.     

Investigation of the antibacterial activity and efflux pump inhibitory effect of co-loaded piperine and gentamicin nanoliposomes in methicillin-resistant Staphylococcus aureus

Objective: Antibiotic resistance has stimulated the research for developing novel strategies that can prevent bacterial growth. Methicillin-resistant Staphylococcus aureus (MRSA), regarded as one of the most serious antibiotic-resistant bacteria which has been conventionally recognized as a nosocomial pathogen.

Materials and methods: Nanoliposomal formulations of piperine and gentamicin were prepared by dehydration-rehydration (DRV) method and characterized for size, zeta potential and encapsulation efficiency. Antibactericidal activities of liposomal and free forms were evaluated against MRSA ATCC 43300 by the determination of minimum inhibitory concentration (MIC), minimum bactericidal concentration (MBC) and fractional inhibitory concentration index (FICI). The time-kill studies were carried out to evaluate the potency of antibacterial agents. The effect of piperine on bacterial efflux pumps was also investigated.

Results: MIC values of gentamicin and piperine were 32 and 100?µg/mL, respectively. Synergetic effects were observed by the combination of gentamicin and piperine and FICI was determined to be 0.5. Following incorporation of gentamicin into liposomal gentamicin and liposomal combination, the MIC values were reduced 16- and 32-fold, respectively. MBC values of gentamicin reduced 4 and 8 times following incorporation into gentamicin and combination liposomes, respectively. In comparison with vancomycin, liposomal combination was more effective in bacterial inhibition and killing. Liposomal combination was the most effective preparations in time-kill study. Our findings indicated that liposomal piperine was able to inhibit the efflux pump sufficiently.

Conclusion: The results of this study revealed that liposomal combination is a powerful nano-antibacterial agent to eradicate MRSA infection. This dual-loaded formulation was an effective approach for eradication of MRSA.     

Presentation of machine learning methods to determine the most important factors affecting road traffic accidents on rural roads

The purpose of this research was to develop statistical and intelligent models for predicting the severity of road traffic accidents (RTAs) on rural roads. Multiple Logistic Regression (MLR) was used to predict the likelihood of RTAs. For more accurate prediction, Multi-Layer Perceptron (MLP) and Radius Basis Function (RBF) neural networks were applied. Results indicated that in MLR, the model obtained from the backward method with the correct percent of 84.7% and R² value of 0.893 was the best method for predicting the likelihood of RTAs. Also, MLR showed that the variables of not paying attention to the front not paying attention to the frontroad ahead, followed byand then vehicle-motorcycle/bike accidents were the greatest problems. Among the models, MLP had a better performance, so that the prediction accuracy of MLR, MLP, and RBF were 84.7%, 96.7%, and 92.1%, respectively. MLP model, due to higher accuracy, showed that the variable of reason of accident had the highest effect on the prediction of accidents, and considering MLR results, the variables of not paying attention to the front and then vehicle-motorcycle/bike accidents had the most influence on the occurrence of accidents. Therefore, motorcyclists and cyclists are more prone to accidents, and appropriate solutions should be adopted to enhance their safety.     

Nucleation and growth of Pd nanoparticles during electrocrystallization on pencil graphite

The aim of present study was to investigate the mechanism of palladium electrodeposition on a pencil graphite surface from an aqueous solution containing 1 mM PdCl₂ and 500 mM H₂SO₄. Cyclic voltammetry revealed that the electrodeposition process proceeds via an initial underpotential deposition (UPD) and subsequently, it follows by the overpotential deposition (OPD) under diffusion control. Current transients showed a complex deposition trend, i.e. the electrodeposition of Pd includes at least three stages: adsorption on the surface, and two types of nucleation courses; two-dimensional (2D) and three-dimensional (3D) which limited by the lattice incorporation of Pd adatoms and the diffusion of Pd ions, respectively. Therefore the electrocrystallization of Pd on pencil graphite conforms to the Stranski–Krastanov growth mechanism. Furthermore, theoretical models were applied to evaluate each of above mentioned stages for different electrode potentials and to estimate the electrochemical parameters of Pd electrodeposition. The micrographs of electrodeposited Pd at relatively high frequency of the nucleation rate, illustrated a well dispersed Pd nanoparticles with a relatively narrow size distribution.     

Adsorptive separation of meta-xylene from C8 aromatics

Industrial adsorptive separation process for liquids is most successful when the involved species have very close boiling points, making distillation expensive or are thermally sensitive at convenient distillation temperatures. The adsorption process was studied for separating meta-xylene from a feed mixture containing all C₈ aromatics on binder-free X and Y zeolites in the liquid phase. Zeolitic adsorbents with different SiO₂/Al₂O₃ were synthesized by the hydrothermal method and ion-exchanged with alkaline metal cations like lithium, sodium and potassium. The adsorption process was carried out in a breakthrough system at temperature of 110–160 °C and pressure of 6–8 atm. The influence of adsorbent moisture content on the separation process was studied. The optimization of adsorption process was also investigated by the changing operation conditions. The isotherms for each isomer of C₈ aromatics and the desorbent possess the adsorption characteristics of Langmuir type. The selectivity factor of meta-xylene and the saturation adsorption capacities of adsorbates were determined. It was observed that the selectivity of meta-xylene increased by sodium ion-exchanging of cationic sites in Y zeolite and the selectivity factor of meta-xylene/para-xylene, meta-xylene/ortho-xylene and meta-xylene/ethylbenzene in the optimum conditions was determined to be 2.62, 2.83 and 5.93, respectively.     

Introduction of two polyvinyl alcohol resins for efficient solid support Cu-catalyzed N-arylation of α-aminoacids with aryl halides in aqueous media

In this article, two polyvinyl alcohol (PVA)-based resins were prepared by crosslinking of epoxidized PVA-chains using of 4-(4-aminobenzyl)benzenamine as a crosslinker and polymerization of acrylated PVA chains in the another approach. The prepared PVA resins showed well hydrophilic and swelling properties in various organic solvents, which are used in solid-phase organic synthesis (SPOS). Swelling properties of these resins were examined in dimethylformamide, tetrahydrofuran, water, ethanol, methanol, dichloromethane, and dioxane. Furthermore, the both resins were characterized by FTIR and ¹H-NMR and their properties such as epoxy equivalent weight (EEW) of epoxidized PVA and density of the resins were determined by analytical methods. Then, α-amino acids such as L-aspartic acid, L-leucine, L-alanine, L-serine, L-valine, L-threonine, and L-tyrosine were immobilized on both resins through esterification reaction between these α-amino acids with the present hydroxyl groups on PVA resines, to carry out their solid-phase N-arylation reaction in the presence of CuI as a catalyst in milder and greener conditions than free resin protocols. Hydrolysis of the correponding N-arylated α-amino acids immobilized on the resins gave the N-arylated α-amino acids in high to excellent yields. © 2019 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2019 , 136, 47597.