The Acute Toxicity of SiO2 and Fe3O4 Nano-particles on Daphnia magna

Silicon - SiO2 nano-particles are applied in different industries such as ceramic producing, glass making, cosmetic products, medicines, magnetic mixtures, heat and electric insulators and glazing...     

A novel approach to predict shear strength of tilted angle connectors using artificial intelligence techniques

Shear connectors play a prominent role in the design of steel-concrete composite systems. The behavior of shear connectors is generally determined through conducting push-out tests. However, these tests are costly and require plenty of time. As an alternative approach, soft computing (SC) can be used to eliminate the need for conducting push-out tests. This study aims to investigate the application of artificial intelligence (AI) techniques, as sub-branches of SC methods, in the behavior prediction of an innovative type of C-shaped shear connectors, called Tilted Angle Connectors. For this purpose, several push-out tests are conducted on these connectors and the required data for the AI models are collected. Then, an adaptive neuro-fuzzy inference system (ANFIS) is developed to identify the most influencing parameters on the shear strength of the tilted angle connectors. Totally, six different models are created based on the ANFIS results. Finally, AI techniques such as an artificial neural network (ANN), an extreme learning machine (ELM), and another ANFIS are employed to predict the shear strength of the connectors in each of the six models. The results of the paper show that slip is the most influential factor in the shear strength of tilted connectors and after that, the inclination angle is the most effective one. Moreover, it is deducted that considering only four parameters in the predictive models is enough to have a very accurate prediction. It is also demonstrated that ELM needs less time and it can reach slightly better performance indices than those of ANN and ANFIS.

     

Predicting roadheader performance by using artificial neural network

With growing use of roadheaders in the world and its significant role in the successful accomplishment of a tunneling project, it is a necessity to accurately predict performance of this machine in different ground conditions. On the other hand, the existence of some shortcomings in the prediction models has made it necessary to perform more research on the development of the new models. This paper makes an attempt to model the rate of roadheader performance based on the geotechnical and geological site conditions. For achieving the aim, an artificial neural network (ANN), a powerful tool for modeling and recognizing the sophisticated structures involved in data, is employed to model the relationship between the roadheader performance and the parameters influencing the tunneling operations with a high correlation. The database used in modeling is compiled from laboratory studies conducted at Azad University at Science and Research Branch, Tehran, Iran. A model with architecture 4-10-1 trained by back-propagation algorithm is found to be optimum. A multiple variable regression (MVR) analysis is also applied to compare performance of the neural network. The results demonstrate that predictive capability of the ANN model is better than that of the MVR model. It is concluded that roadheader performance could be accurately predicted as a function of unconfined compressive strength, Brazilian tensile strength, rock quality designation, and alpha angle R ² = 0.987. Sensitivity analysis reveals that the most effective parameter on roadheader performance is the unconfined compressive strength.     

Spectral characterization and ASTER-based lithological mapping of an ophiolite complex: A case study from Neyriz ophiolite, SW Iran

The Neyriz ophiolite occurs along the Zagros suture zone in SW Iran, and is part of a 3000-km obduction belt thrusting over the edge of the Arabian continent during the late Cretaceous. This complex typically consists of altered dunites and peridotites, layered and massive gabbros, sheeted dykes and pillow lavas, and a thick sequence of radiolarites. Reflectance and emittance spectra of Neyriz ophiolite rock samples were measured in the laboratory and their spectra were used as endmembers in a spectral feature fitting (SFF) algorithm. Laboratory spectral reflectance measurements of field samples showed that in the visible through shortwave infrared (VNIR-SWIR) wavelength region the ultramafic and gabbroic rocks are characterized by ferrous-iron and Fe, MgOH spectral features, and the pillow lavas and radiolarites are characterized by spectral features of ferric-iron and AlOH. The laboratory spectral emittance spectra also revealed a wide wavelength range of SiO spectral features for the ophiolite rock units. After continuum removal of the spectra, the SFF classification method was applied to the VNIR + SWIR 9-band stack, and to the 11-band data set of SWIR and TIR data sets of the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) sensor, using field spectra as training sets for evaluating the potential of these data sets in discriminating ophiolite rock units. Output results were compared with the geological map of the area and field observations, and were assessed by the use of confusion matrices. The assessment showed, in terms of kappa coefficient, that the SFF classification method with continuum removal applied to the SWIR data achieved excellent results, which were distinctively better than those obtained using VNIR + SWIR data and TIR data alone.     

Effect of Mentha spicata L. and Mentha aquatica L. essential oils on the microbiological properties of fermented dairy product,kashk

The antibacterial activity of Mentha spicata and Mentha aquatica essential oils (EO) was tested against Staphylococcus aureus, Lactobacillus reuteri, Bifidobacterium animalis and Clostridium perfringens using agar well and disc diffusion techniques. Results showed that M. spicata EO had the highest inhibition activity against the studied microorganisms. Then, the antibacterial activity of both EO at 1500 and 2500 ppm was examined in industrial liquid kashk during the storage at 4 °C for 20 days. Both EO reduced the S. aureus viable count below 5 log CFU g^?1 after 4 days; however, the population of C. perfringens, L. reuteri and B. animalis decreased <1 log CFU g^?1 during the storage time. The least deteriorative effect on the lactic acid bacteria was related to M. aquatica. As revealed by organoleptic studies, kashk samples containing M. aquatica EO at 1500 and 2500 ppm were the most preferred samples.     

Attitude of Iranian physicians and nurses toward a clinical decision support system for pulmonary embolism and deep vein thrombosis

This research project sought to design and implement a computerized clinical decision support system (CDSS) that was able to identify patients who were at risk of pulmonary embolism (PE) and deep vein thrombosis (DVT), as well as produce reminders for prophylactic action for these diseases. The main purpose of the CDSS was to attempt to reduce the morbidity and mortality caused by embolism and thrombosis in patients admitted to hospitals. After implementation of this system in one of the large educational hospitals of Iran, a standard questionnaire was used, and interviews were conducted with physicians and nurses to evaluate the performance of the designed system for reducing the incidence of pulmonary embolism and thrombosis. From physicians and nurses’ point of view, a system which assists the medical staff in making better decisions regarding patient care, and also reminds pulmonary embolism and thrombosis preventive procedures with timely warnings, can influence patient care quality improvement and lead to the improved performance of the medical staff in preventing the incidence of pulmonary embolism and thrombosis.     

The release rate and antimicrobial activity of calcium-alginate films containing self-microemulsifying Thymus vulgaris essential oil against Escherichia coli and Staphylococcus aureus

The aim of this study was to fabricate antimicrobial calcium-alginate-based films containing the self-microemulsifying thyme essential oil (TEO) formulations using Tween 80 as the surfactant, and acetic (AA) or propionic (PA) acids as the cosurfactants. A Ca-alginate film containing nano-emulsified TEO as well as a neat Ca-alginate film were considered as the controls. The scanning electron microscopy micrographs showed a highly porous texture for SME films, which resulted in an increase in water vapor permeability and water absorption capacity of these films. The SME films released the TEO completely within 155 min and inhibited the growth of S. aureus and E. coli in in vitro antimicrobial tests. The population of S. aureus and E. coli reduced significantly in ground beef covered with SME films. The results of this study showed that self-microemulsifying TEO films could effectively increase the shelf life of ground beef by controlling its microbial population.     

Polybutadiene/polyhedral oligomeric silsesquioxane nanohybrid: investigation of various reactants in polyesterification reaction

Nano‐sized polyhedral oligomeric silsesquioxane (POSS) diol or ethylene glycol (EG) as diol monomer was incorporated into hydroxyl‐terminated polybutadiene (HTPBD) chain in the presence of fumaryl or thionyl chloride as extenders. Using these polyesterification reactions, two fumarate‐based polyesters and two polyester sulfites were synthesized. Each couple of polyesters and polyester sulfites includes a linear (diol:EG) and a nanohybrid macromer (diol:POSS). Full structural characterization was performed using Fourier transform infrared, ¹H NMR and ¹³C NMR spectroscopies. Gel permeation chromatography was undertaken to study polyesterification mechanisms by deconvolution of the obtained traces. Finally, differential scanning calorimetry, thermogravimetric analysis and cell culture were performed to evaluate the structure–property relationship for the synthesized macromers in comparison with unreacted HTPBD. © 2016 Society of Chemical Industry     

A crossover‐UNIQUAC model for critical and noncritical LLE calculations

A new model, named the crossover‐UNIQUAC model, has been proposed based on the crossover procedure for predicting constant‐pressure liquid–liquid equilibria (LLE). In this manner, critical fluctuations were incorporated into the classical UNIQUAC equation. Coexistence curves were estimated for systems having a diverse range of asymmetries. These systems included the LLE of five different mixtures, composed of nitrobenzene with one of the members of the alkane homologous family (either pentane, octane, decane, dodecane, or tetradecane), as well as an extra system having a different chemical nature, namely the mixture of n‐perfluorohexane and hexane, to further check the validity of the proposed approach. Using these nonideal mixtures, the validity of the new model was investigated within wide ranges, covering near‐critical to regions falling far away from the critical point. The graphical trends, as well as the quantitative comparison with experimental data indicated the good agreement of the proposed model results with the experimental data. A maximum AARD% value of 3.97% was obtained in calculating molar compositions by the proposed model for such challenging systems covering noncritical, as well as critical regions. In addition, to show the strength of the proposed crossover approach to describe properties other than LLE, molar heat capacities were investigated for the system of nitrobenzene + dodecane. © 2015 American Institute of Chemical Engineers AIChE J, 61: 3094–3103, 2015     

Poly1‐hexene: New impact modifier in HIPS technology

Poly1‐hexene was prepared using a conventional heterogeneous Ziegler–Natta catalyst and its stereoregularity was characterized using ¹³C‐NMR analysis. New kind of high impact polystyrene (HIPS) was prepared by radical polymerization of styrene in the presence of different amounts of synthesized poly1‐hexene (PH) as impact modifier (HIPS/PH) and compared with conventional high impact polystyrene with polybutadiene (HIPS/PB) as rubber phase. Scanning electron microscopy (SEM) revealed that the dispersion of poly1‐hexene in polystyrene matrix was more uniform compared with it in HIPS/PB. The impact strength of HIPS/PH was 29–79% and 80–289% higher than that in HIPS/PB and neat polystyrene, respectively. FTIR was used to confirm more durability of HIPS/PH samples toward ozonation. To study the effect of rubber type and amount on the T_gs of polystyrene, differential scanning calorimetry was employed. Results obtained from TGA demonstrated higher thermal stability of HIPS/PH sample in comparison with conventional HIPS/PB one. Our obtained results suggest new high impact polystyrene that in all studied aspects has better performance than the conventional HIPS. © 2016 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2016 , 133, 43882.