Chemical Composition and Antimicrobial Activity of Essential Oil of Matricaria recutita

Matricaria recutita is a herbaceous plant belonging to the Asteraceae family. The present study reports the chemical composition and antimicrobial activity of M. recutita essential oil and its main compounds. The essential oil was obtained from the aerial parts of the M. recutita by hydrodistillation and analyzed by gas chromatography-mass spectrometry. The major components were α-bisabolol oxide (38%), followed by camphene (9.11%), sabinene (4.87%), limonene (6%),1,8-cineole (7.12%), camphor (6.54%), and α-pinene (6%). Essential oil of chamomile was evaluated for its antibacterial activities against three gram-positive and four gram-negative pathogenic bacteria. The essential oil and its main compounds were particularly active against Bacillus cereus, with the lowest minimum inhibitory concentration and minimum bactericidal concentration value (0.022 and 1.5 μg /mL). In conclusion, these results support the use of the essential oil and its main compounds for their antimicrobial properties.     

Investigation of turbulent convective heat transfer and pressure drop of TiO2/water nanofluid in circular tube

Turbulent heat transfer behavior of titanium dioxide/water nanofluid in a circular pipe was investigated experimentally where the volume fraction of nanoparticles in the base fluid was less than 0.25%. The experimental measurements have been carried out in the fully-developed turbulent regime for various volumetric concentrations. The results indicated that addition of small amounts of nanoparticles to the base fluid augmented heat transfer remarkably. There was no much effect on heat transfer enhancement with increasing the volume fraction of nanoparticles. The measurements also showed that the pressure drop of nanofluid was slightly higher than that of the base fluid and increased with increasing the volume concentration. In this paper, experimental results have been compared with the existing correlations for nanofluid convective heat transfer coefficient in turbulent regime. Finally, a new correlation of the Nusselt number will be presented using the results of the experiments with titanium dioxide nanoparticles dispersed in water.     

Mechanical properties of wood plastic composite panels made from waste fiberboard and particleboard

The possibility of producing wood‐plastic panels using a melt blend/hot press method was studied in this research. The studied panels were compared with conventional medium density fiberboard (MDF) and particleboard (PB) panels. Wood‐plastic panels were made from high density polyethylene (as resin) and MDF waste and PB waste (as natural fiber) at 60, 70, and 80% by weight fiber loadings. Nominal density and dimensions of the panels were 1 g/cm³ and 35 × 35 × 1 cm³, respectively. Mechanical properties of the panels including flexural modulus, flexural strength, screw and nail withdrawal resistances, and impact strength were studied. Results indicated that the mechanical properties of the composites were strongly affected by the proportion of the wood flour and polymer. Maximum values of flexural modulus of wood plastic panels were reached at 70% fiber content. Flexural strength, screw and nail withdrawal resistance, and impact strength of wood plastic composites declined with the increase in fiber content from 60 to 80%. This was attributed to the lack of compatibility between the phases. The produced panels outperformed conventional PB panels regarding their mechanical properties, which were acceptable when compared with MDF panels as well. The best feature in the produced panels was their screw withdrawal resistance, which is extremely important for screw joints in cabinet making. POLYM. COMPOS., 2008. © 2008 Society of Plastics Engineers     

Numerical and experimental investigation of composite steel shear wall with opening

Shear walls are used in towers as lateral loading resistance. Composite steel shear wall (CSSW) because of high stiffness and deformability are widely used. This wall made of a thin steel plate with reinforced a concrete layer, which is attached to one or both sides of the steel plate. This system is similar to stiffened steel plate shear wall. The present experimental and numerical studies were focused on the effects of opening used as windows or doors in buildings on the CSSW behavior. Experimental studies results of one and three-story CSSWs with the scale of 1:3 are reported. In addition, the effects of opening size and location are insignificant on the composite steel shear walls behavior. Results showed that opening decrease CSSW strength. Opening at the sides and corners further reduces the resistance than Opening at the center.     

Level-direction decomposition analysis with a focus on image watermarking framework

This research addresses the new level-direction decomposition in the area of image watermarking as the further development of investigations. The main process of realizing a watermarking framework is to generate a watermarked image with a focus on contourlet embedding representation. The approach performance is evaluated through several indices including the peak signal-to-noise ratio and structural similarity, whereby a set of attacks are carried out using a module of simulated attacks. The obtained information is analyzed through a set of images, using different color models, to enable the calculation of normal correlation. The module of the inverse of contourlet embedding representation is correspondingly employed to obtain the present watermarked image, as long as a number of original images are applied to a scrambling module, to represent the information in disorder. This allows us to evaluate the performance of the proposed approach by analyzing a complicated system, where a deci-sion making system is designed to find the best level and the corresponding direction regarding contourlet embedding represen-tation. The results are illustrated in appropriate level-direction decomposition. The key contribution lies in using a new integration of a set of subsystems, employed based upon the novel mechanism in contourlet embedding representation, in association with the decision making system. The presented approach is efficient compared with state-of-the-art approaches, under a number of serious attacks. A number of benchmarks are obtained and considered along with the proposed framework outcomes. The results support our ideas.     

Automatic segmentation of newborns’ skull and fontanel from CT data using model-based variational level set

The newborn’s cranium is composed of flat cranial bone and fontanels forming together the envelope of the cerebral cavity. The fontanels are relatively flexible since they consist of fibrous membrane that ossifies during maturation becoming flat cranial bone as well. Fontanels give less contrast in computerized tomography (CT) images; they can be identified as gaps between the cranial bones. In this paper, we propose an automatic model-based method using variational level set to segment the skull and fontanels from CT images. In this approach, firstly a skull model consisting of cranial bones and fontanels is created and then used as constraint for level set evolution. Then, by removing the cranial bones from the segmented skulls, the fontanels are obtained. To verify the validity of the achieved results, automatically segmented skull and fontanels have been compared with the ones manually segmented by an expert using Dice similarity and Hausdorff dissimilarity measures, which show the good agreement between them. Furthermore, the surface areas of cranium and fontanel have been determined for these segmentations. The results for both, manual and automatic segmentation, are in good agreement.     

Relative pressure estimation from 4D flow MRI using generalized Bernoulli equation in a phantom model of arterial stenosis

Magnetic Resonance Materials in Physics, Biology and Medicine - Arterial stenosis is a significant cardiovascular disease requiring accurate estimation of the pressure gradients for determining...     

Size dependence of concrete fracture energy determined by RILEM work-of-fracture method

The paper analyzes the size dependence of the fracture energy of concrete obtained according to the existing RILEM recommendation proposed by Hillerborg and based on the work-of-fracture method of Nakayama, Tattersal and Tappin, in which the energy dissipated at the fracture front is evaluated from the measured load-displacement curve. The analysis is based on the size effect law proposed by Baant, which has been shown to be applicable to the size ranges up to about 1:20 and apply in the same form for all specimen geometries. The analysis utilizes the previously developed method for calculating the R-curve from the size effect, and the load-deflection curve from the R-curve. The R-curve is dependent on the geometry of the specimen. The results show that the fracture energy according to the existing RILEM recommendation is not size-independent, as desired, but depends strongly on the specimen size. This dependence is even stronger than that of the R-curve. When the specimen size is extrapolated to infinity, the fracture energy according to the RILEM recommendation coincides with the fracture energy obtained by the size effect method. It is also found that, in fracture specimens of usual sizes, the pre-peak contribution of the work of the load to the fracture energy is relatively small. Finally, as a by-product, the analysis also verifies the fact that, in three-point bend fracture specimens, the fracture energy according to the RILEM definition is dependent on the notch depth.     

Self-adaptive multi-population genetic algorithms for dynamic resource allocation in shared hosting platforms

This paper presents a self-adaptive multi-population approach based on genetic algorithm (GA) for solving dynamic resource allocation in shared hosting platforms. The proposed method, self-adaptive multi-population genetic algorithm (SAMPGA), is a multi-population GA strategy aimed at locating and tracking optima. This approach is based on preventing populations from searching in the same areas. Two adaptations to the basic approach are then proposed to further improve its performance. The first adapted algorithm, memory-based SAMPGA, is based on using explicit memory to store promising solutions and retrieve them upon detecting change in the environment. The second adapted algorithm, immigrants-based SAMPGA, is aimed at improving the technique used by SAMPGA to maintain a sustainable level of diversity needed for quick adaptation to the environmental changes. An extensive set of experiments is conducted on a variety of dynamic resource allocation scenarios, to evaluate the performance of the proposed approach. Results are also compared with those of self-organizing random immigrants GA using three well-known performance metrics. The experimental results indicate the effectiveness of the proposed approach.     

TAPAS: Trustworthy privacy-aware participatory sensing

With the advent of mobile technology, a new class of applications, called participatory sensing (PS), is emerging, with which the ubiquity of mobile devices is exploited to collect data at scale. However, privacy and trust are the two significant barriers to the success of any PS system. First, the participants may not want to associate themselves with the collected data. Second, the validity of the contributed data is not verified, since the intention of the participants is not always clear. In this paper, we formally define the problem of privacy and trust in PS systems and examine its challenges. We propose a trustworthy privacy-aware framework for PS systems dubbed TAPAS, which enables the participation of the users without compromising their privacy while improving the trustworthiness of the collected data. Our experimental evaluations verify the applicability of our proposed approaches and demonstrate their efficiency.