Effects of gravity and ambient pressure on liquid fuel droplet evaporation

An axisymmetric numerical model has been developed to conduct a study of single droplet evaporation over a wide range of ambient pressures both under normal and microgravity conditions. Results for droplet lifetime as a function of ambient pressure and initial droplet diameter are presented. The enhancement in the droplet evaporation rate due to natural convection is predicted. This enhancement becomes more dominant with increasing ambient pressure due to the increase in the Grashof number. The higher the ambient pressure, the closer the Grashof number remains to its initial value throughout most of the droplet lifetime because of the droplet swelling and the heat-up of the droplet interior. Results should be particularly of interest to researchers conducting experiments on droplet evaporation at elevated pressures within a normal gravity environment. The model developed is in good agreement with experimental data at low pressures. Explanations have been provided for its deviation at high pressures.     

Granulometric Distribution and X-Ray Diffraction of Two Brazilian Clays Used for Purification of Post-Consumption Vegetable Oils

Alternative fuels for diesel engines are becoming increasingly significant because of the decrease of oil reserves and thus, the increase in its price reaches levels that make impracticable to be used. The recycling of post consumption vegetable oils can help to reduce the disposal of these oils and have competitive price in the market. The aim of this study was to analyze by particle size distribution and X-ray diffraction two Brazilian clay （Tonsil and Aporofo） used for purification of vegetable oils after consumption for biodiesel production. To perform the particle size distribution technique for classifying particles by laser diffraction was used. The clays were characterized before and after the process of purification by X-ray diffraction. Techniques for particle size distribution and the X-ray diffraction analysis that were Tonsil clay showed better results in purification of vegetable oils after consumption compared to Aporofo clay. It could be concluded that the clays analyzed the Tonsil clay is the most suitable for the purification of post-consumer vegetable oils, withdrew because much of the impurities that were present in oils and gave him dark color and bad odor.     

Performance analysis of a fully-connected, full-duplex CDMA ALOHAnetwork with channel sensing and collision detection

In cases where machines having bursty data are equally likely to transmit to one another, code-division multiple-access (CDMA) ALOHA which allows for an individual “virtual channel” for each receiving station may be a better multiple-access protocol than simple ALOHA. With the use of a “receiver-based code” multiple-access protocol, it is also possible for a station to listen to the channel of the intended receiver before transmission, and also abort transmission when it detects others transmitting on the same channel. This paper describes a model for a fully-connected, full duplex, and slotted CDMA ALOHA network where channel sensing and collision detection are used. The model is analyzed using a discrete time Markov chain and some numerical results are presented. For a system with a large number of users, where Markov analysis is impractical, equilibrium point analysis is used to predict the stability of the system, and estimate the throughput as well as the delay performance of the system when it is stable. Finally, a comparison is made with a simple channel sense multiple-access with collision detection (CSMA-CD) network, showing that a substantial improvement in the performance is achieved by the proposed network     

Gaseous corrosion mechanisms of silicon carbides in Na2SO4 and V2O5 environments

Hot-pressed polycrystalline SiC (HPSiC) and single crystal SiC (SCSiC) were exposed to Na₂SO₄ and V₂O₅ vapours at 1000 °C. Vapours were carried by the argon gas over the specimens where corrosion studies were conducted. Mixed-kinetics mechanisms for HPSiC under gaseous environments have been developed in the form of corrosion weight loss per unit area with time. The decomposed gases diffusing through the SiO₂ film and the reaction products at the substrate surfaces are the two major steps that contribute to the overall reaction for this material. SCSiC was observed to have severe corrosion attacks on its surfaces and corrosion pits with honeycomb shapes were left.     

基于免疫算法的岩土工程可靠度分析

基于免疫算法原理和可靠度指标的几何涵义,提出了计算岩土工程可靠度指标和设计验算点的全局优化算法。该方法模拟了生物免疫系统,其主要步骤包括:B细胞与抗原之间的亲和度计算与选择、B细胞的克隆、变异和记忆细胞的产生等。对于功能函数的非线性和复杂性,避免了繁复的求导数工作。通过两个工程实例,证明了本文提出的方法进行岩土工程可靠度分析的有效性。     

Automated print inspection for cylindrical surfaces

The objective of this research was to determine the criteria for automated inspection of a string of alphanumeric characters printed directly to the surfaces of cylindrical containers. The technical problems encountered, because a curved surface was used instead of a flat surface, were container positioning for locating surface features, character position compensation due to curvature, resolution limits defined for sensor and reflected illumination. Automated print inspection requires the use of machine vision to perform the registration of characters, template comparison for correct text being produced and the interrogation of the individual characters for correctness, position, size and type.     

Structural Modeling and Biochemical Characterization of Recombinant KPN_02809, a Zinc-Dependent Metalloprotease from Klebsiella pneumoniae MGH 78578

Klebsiella pneumoniae is a Gram-negative, cylindrical rod shaped opportunistic pathogen that is found in the environment as well as existing as a normal flora in mammalian mucosal surfaces such as the mouth, skin, and intestines. Clinically it is the most important member of the family of Enterobacteriaceae that causes neonatal sepsis and nosocomial infections. In this work, a combination of protein sequence analysis, structural modeling and molecular docking simulation approaches were employed to provide an understanding of the possible functions and characteristics of a hypothetical protein (KPN_02809) from K. pneumoniae MGH 78578. The computational analyses showed that this protein was a metalloprotease with zinc binding motif, HEXXH. To verify this result, a ypfJ gene which encodes for this hypothetical protein was cloned from K. pneumoniae MGH 78578 and the protein was overexpressed in Escherichia coli BL21 (DE3). The purified protein was about 32 kDa and showed maximum protease activity at 30 °C and pH 8.0. The enzyme activity was inhibited by metalloprotease inhibitors such as EDTA, 1,10-phenanthroline and reducing agent, 1,4-dithiothreitol (DTT). Each molecule of KPN_02809 protein was also shown to bind one zinc ion. Hence, for the first time, we experimentally confirmed that KPN_02809 is an active enzyme with zinc metalloprotease activity.     

A multi‐GPU algorithm for large‐scale neuronal networks

Large‐scale simulations of parts of the brain using detailed neuronal models to improve our understanding of brain functions are becoming a reality with the usage of supercomputers and large clusters. However, the high acquisition and maintenance cost of these computers, including the physical space, air conditioning, and electrical power, limits the number of simulations of this kind that scientists can perform. Modern commodity graphical cards, based on the CUDA platform, contain graphical processing units (GPUs) composed of hundreds of processors that can simultaneously execute thousands of threads and thus constitute a low‐cost solution for many high‐performance computing applications. In this work, we present a CUDA algorithm that enables the execution, on multiple GPUs, of simulations of large‐scale networks composed of biologically realistic Hodgkin–Huxley neurons. The algorithm represents each neuron as a CUDA thread, which solves the set of coupled differential equations that model each neuron. Communication among neurons located in different GPUs is coordinated by the CPU. We obtained speedups of 40 for the simulation of 200k neurons that received random external input and speedups of 9 for a network with 200k neurons and 20M neuronal connections, in a single computer with two graphic boards with two GPUs each, when compared with a modern quad‐core CPU. Copyright © 2010 John Wiley & Sons, Ltd.     

Regulation of Proteolytic Activity to Improve the Recovery of Macrobrachium rosenbergii Nodavirus Capsid Protein

The causative agent of white tail disease (WTD) in the giant freshwater prawn is Macrobrachium rosenbergii nodavirus (MrNV). The recombinant capsid protein (CP) of MrNV was previously expressed in Escherichia coli, and it self-assembled into icosahedral virus-like particles (VLPs) with a diameter of approximately 30 nm. Extensive studies on the MrNV CP VLPs have attracted widespread attention in their potential applications as biological nano-containers for targeted drug delivery and antigen display scaffolds for vaccine developments. Despite their advantageous features, the recombinant MrNV CP VLPs produced in E. coli are seriously affected by protease degradations, which significantly affect the yield and stability of the VLPs. Therefore, the aim of this study is to enhance the stability of MrNV CP by modulating the protease degradation activity. Edman degradation amino acid sequencing revealed that the proteolytic cleavage occurred at arginine 26 of the MrNV CP. The potential proteases responsible for the degradation were predicted in silico using the Peptidecutter, Expasy. To circumvent proteolysis, specific protease inhibitors (PMSF, AEBSF and E-64) were tested to reduce the degradation rates. Modulation of proteolytic activity demonstrated that a cysteine protease was responsible for the MrNV CP degradation. The addition of E-64, a cysteine protease inhibitor, remarkably improved the yield of MrNV CP by 2.3-fold compared to the control. This innovative approach generates an economical method to improve the scalability of MrNV CP VLPs using individual protease inhibitors, enabling the protein to retain their structural integrity and stability for prominent downstream applications including drug delivery and vaccine development.     

A systematic approach in load disaggregation utilizing a multi-stage classification algorithm for consumer electrical appliances classification

The potential to save energy in existing consumer electrical appliances is very high. One of the ways to achieve energy saving and improve energy use awareness is to recognize the energy consumption of individual electrical appliances. To recognize the energy consumption of consumer electrical appliances, the load disaggregation methodology is utilized. Non-intrusive appliance load monitoring (NIALM) is a load disaggregation methodology that disaggregates the sum of power consumption in a single point into the power consumption of individual electrical appliances. In this study, load disaggregation is performed through voltage and current waveform, known as the V-I trajectory. The classification algorithm performs cropping and image pyramid reduction of the V-I trajectory plot template images before utilizing the principal component analysis (PCA) and the k-nearest neighbor (k-NN) algorithm. The novelty of this paper is to establish a systematic approach of load disaggregation through V-I trajectory-based load signature images by utilizing a multi-stage classification algorithm methodology. The contribution of this paper is in utilizing the “k-value,” the number of closest data points to the nearest neighbor, in the k-NN algorithm to be effective in classification of electrical appliances. The results of the multi-stage classification algorithm implementation have been discussed and the idea on future work has also been proposed.