Electrocatalytic oxidation of formic acid and formaldehyde on platinum nanoparticles decorated carbon-ceramic substrate

Electrochemical characteristics of formic acid (FM) and formaldehyde (FM) oxidation on a potent catalyst, platinum nanoparticles supported on carbon-ceramic substrate (CC/Pt), were investigated via cyclic voltammetric and chronoamperometric analysis in mixed 0.75 M FM (or 0.75 M FM) and 0.1 M H₂SO₄ solutions. The results were compared to those at a polycrystalline platinum electrode and platinum particles deposited on platinum and glassy carbon electrodes. It was found that CC/Pt was catalytically more active than smooth platinum and platinum particles supported on platinum and glassy carbon electrodes. On the other hand, such nanoparticles on CC substrate exhibit better catalytic behavior towards FA and FM than the corresponding platinum and glassy carbon electrodes, which is raised form high porosity of CC substrate for better distribution of platinum particles and to produce of platinum particles in nano size. The effect of some experimental factors was studied and optimum conditions were suggested. Finally, the long-term stability of the modified electrode has also been investigated. These results indicate that the system studied in the present work is the most promising system for use in fuel cells.     

Irradiation grafting of methyl methacrylate monomer onto ultra‐high‐molecular‐weight polyethylene: An experimental design approach for improving adhesion to bone cement

The grafting of methyl methacrylate (MMA) onto ultra‐high‐molecular‐weight polyethylene (UHMWPE) and chromic acid etched UHMWPE was conducted with a preirradiation method in air in the presence of a Mohr salt and sulfuric acid. The grafted samples were characterized by Fourier transform infrared (FTIR) spectroscopy, a gravimetric method, differential scanning calorimetry, scanning electron microscopy (SEM), and interfacial bonding strength measurements. The FTIR results showed the presence of ether and carbonyl groups in the MMA‐grafted UHMWPE (MMA‐g‐UHMWPE) samples. The Taguchi experimental design method was used to find the best degree of grafting (DG) and bonding strength. The efficient levels for different variables were calculated with an analysis of variance of the results. SEM micrographs of MMA‐g‐UHMWPE samples showed that with increasing DG and chromic acid etching, the MMA‐g‐UHMWPE rich phase increased on the surface; this confirmed the high interfacial bonding strength of the grafted samples with bone cement. The grafting of the MMA units onto UHMWPE resulted in a lower crystallinity, and the crystallization process proceeded at a higher rate for the MMA‐g‐UHMWPE samples compared to the initial UHMWPE; this suggested that the MMA grafted units acted as nucleating agents for the crystallization of UHMWPE. © 2009 Wiley Periodicals, Inc. J Appl Polym Sci, 2010     

Meso-tetraarylporphyrin catalyzed highly regioselective ring opening of epoxides with acetic acid

Highly regioselective ring opening of styrene oxide with acetic acid in the presence of catalytic amounts of meso-tetra(4-CH₃)phenyl- or meso-tetraphenylporphyrin at room temperature is reported. Under the same reaction conditions, cyclohexene oxide is more reactive than styrene oxide and gives the trans-isomer as the sole product.     

Joint channel assignment and routing in multiradio multichannel wireless mesh networks with directional antennas

The aggregate capacity of a wireless mesh network (WMN) is severely affected by interflow interference. In this paper, we propose a network architecture that incorporates directional antennas with multiple orthogonal channels to effectively enhance the performance of WMNs. First, a sectored connectivity graph is introduced to model multiradio multichannel WMNs with directional antennas. Next we formulate the topology design, directional interface assignment, channel allocation, and routing mathematically as a mixed integer linear programming problem. This problem is solved using an iterated local search algorithm to obtain optimized network resource allocation. Simulation results indicate that the proposed architecture can achieve higher packet delivery ratio while providing better network fairness. Copyright © 2014 John Wiley & Sons, Ltd.     

Performance analysis of hybrid/single nanofluids on augmentation of heat transport in lid-driven undulated cavity

This numerical study reveals the heat transfer performance of hybrid/single nanofluids inside a lid-driven sinusoidal trapezoidal-shaped enclosure. The right and left inclined surfaces of the trapezium have been considered as insulated, whereas the bottom sinusoidal wavy and the flat top surfaces of the enclosure as hot and cold, respectively. The governing partial differential equations of fluid's velocity and temperature have been resolved by applying the finite element method. The implications of Prandtl number (4.2-6.2), Richardson number (0.1-10.0), undulation number (0-3), nanoparticles volume fraction (0%-3%), and nanofluid/base fluid (water, water–copper (Cu), water–Cu–carbon nanotube, water–Cu–copper oxide (CuO), water–Cu–TiO₂, and water–Cu–Al₂O₃) on the velocity and temperature profiles have been studied. Simulated findings have been represented by means of streamlines, isothermal lines, and average Nusselt number of above-mentioned hybrid nanofluids for varying the governing parameters. The comparison of heat transfer rates using hybrid nanofluids and pure water has been also shown. The heat transfer rate is increased about 15% for varying Richardson number from 0.1 to 10.0. Blending of two nanoparticles suspension in base fluid has a higher heat transfer rate—approximately 5% than a mononanoparticle. Moreover, a higher average Nusselt number is obtained by 14.7% using the wavy surface than the flat surface of the enclosure. Thus, this study showed that applying hybrid nanofluid may be beneficial to obtain expected thermal performance.     

Preparation of Au nanoparticles by Q switched laser ablation and their application in 4-nitrophenol reduction

Clean Technologies and Environmental Policy - This work reports the fabrication of Au nanoparticles (NPs) by laser ablation of a gold metal plate immersed in water in the absence of stabilizing...     

Deep Learning and Machine Learning for Early Detection of Stroke and Haemorrhage

Stroke and cerebral haemorrhage are the second leading causes of death in the world after ischaemic heart disease. In this work, a dataset containing medical, physiological and environmental tests for stroke was used to evaluate the efficacy of machine learning, deep learning and a hybrid technique between deep learning and machine learning on the Magnetic Resonance Imaging (MRI) dataset for cerebral haemorrhage. In the first dataset (medical records), two features, namely, diabetes and obesity, were created on the basis of the values of the corresponding features. The t-Distributed Stochastic Neighbour Embedding algorithm was applied to represent the high-dimensional dataset in a low-dimensional data space. Meanwhile,the Recursive Feature Elimination algorithm (RFE) was applied to rank the features according to priority and their correlation to the target feature and to remove the unimportant features. The features are fed into the various classification algorithms, namely, Support Vector Machine (SVM), K Nearest Neighbours (KNN), Decision Tree, Random Forest, and Multilayer Perceptron. All algorithms achieved superior results. The Random Forest algorithm achieved the best performance amongst the algorithms; it reached an overall accuracy of 99%. This algorithm classified stroke cases with Precision, Recall and F1 score of 98%, 100% and 99%, respectively. In the second dataset, the MRI image dataset was evaluated by using the AlexNet model and AlexNet + SVM hybrid technique. The hybrid model AlexNet + SVM performed is better than the AlexNet model; it reached accuracy, sensitivity, specificity and Area Under the Curve (AUC) of 99.9%, 100%, 99.80% and 99.86%, respectively.     

Evaluation of ZnO-Vitamin B1 Nanoparticles on Bioactivity and Physiochemical Properties of the Polycaprolactone-Based Nanocomposites

In the present study, we investigated the use of thiamine chloride hydrochloride (vitamin B₁)-modified ZnO nanoparticles (ZnO-VB₁ NPs) to reinforce polycaprolactone matrix. The stable and bioactive PCL/ZnO-VB₁ nanocomposites were fabricated with the combination of ultrasonication and solution casting methods. Transmission electron microscope results indicated that the ZnO-VB₁ NPs were uniformly dispersed in the matrix. The nanocomposites showed high hydroxyapatite formation (high bioactivity) in the simulated body fluid. The nanocomposites with 2?wt% of the modified nanoparticles were found to have highest mechanical strength. The nanocomposites with more nanofiller concentrations exhibited high wettability.