Effect of Temperature on Fluidization Regimes

The probability of fluidization regimes at high temperature was determined experimentally by frequency domain analysis of pressure fluctuations. Fluidization regime probabilities were calculated for various gas velocities and temperatures. By increasing the temperature, larger bubbles became more stable which resulted in postponing transition from bubbling to turbulent fluidization. Results showed that the transition velocity from bubbling to turbulent increases by raising the temperature. A probability model was proposed and compared with experimental data indicating good accordance.     

Triiodide PVC membrane electrodes based on charge-transfer complexes

Three new electrodes were prepared by incorporating two different charge-transfer complexes and amino crown ether into plasticized PVC membranes. The electrodes showed Nernstian response to triiodide ion over the activity range from 1.0 x 10(-5) to 1.0 x 10(-1) mol x L(-1) with detection limits at approximately 1.0 x 10(-6) mol x L(-1). The resulting electrodes have fast response times (20-30 s) and good stabilities (4 months) and can be used over a wide pH range of 2.5-9.0. The proposed electrodes exhibit anti-Hofmeister behavior with excellent selectivity toward triiodide ion against a wide range of common interferences. Comparative study suggests that amino (aza) crown ether alone or in the form of a charge-transfer complex with iodine, as an ionophore in a PVC liquid membrane, is sensitive to triiodide ion. The electrodes were used as indicator electrodes in potentiometric titration of triiodide ion against thiosulfate ion.     

Model Selection by Predictive Validation

: Gaussian mixture modelling is used to provide a semi-parametric density estimate for a given data set. The fundamental problem with this approach is that the number of mixtures required to adequately describe the data is not known in advance. In our previous work , we described an algorithm, termed Predictive Validation, which attempted to automatically select the number of components. The aim of this paper is to investigate the influence of the various parameters in our model selection method in order to develop it into an operational tool. In this paper, we demonstrate the successful application of model validation to three applications in which the selected models are used for supervised classification, unsupervised classification and outlier detection tasks. Received: 23 Novenber 2000, Received in revised form: 24 April 2001, Accepted: 21 May 2001     

The Addiction-Stroop test: Theoretical considerations and procedural recommendations.

Decisions about using addictive substances are influenced by distractions by addiction-related stimuli, of which the user might be unaware. The addiction-Stroop task is a paradigm used to assess this distraction. The empirical evidence for the addiction-Stroop effect is critically reviewed, and meta-analyses of alcohol-related and smoking-related studies are presented. Studies finding the strongest effects were those in which participants had strong current concerns about an addictive substance or such concerns were highlighted through experimental manipulations, especially those depriving participants of the substance. Theories to account for addiction-related attentional bias are discussed, of which the motivational theory of current concerns appears to provide the most complete account of the phenomenon. Recommendations are made for maximizing the precision of the addiction-Stroop test in future research. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Watermark detection with zero-knowledge disclosure

Watermarking schemes embed information imperceptibly in digital objects and are proposed as primitives in various copyright protection applications, such as proofs of authorship, dispute resolving protocols or fingerprinting. In many applications, the presence of watermarks must be provable to any possibly dishonest party. Traditionally, watermark detection requires knowledge of sensitive information like the watermark or the embedding key. This is a major security risk, since this information is in most cases sufficient to remove the watermark and to defeat the goal of copyright protection. Zero-knowledge watermark detection is a promising approach to overcome security issues during the process of watermark detection: cryptographic techniques are used to prove that a watermark is detectable in certain data, without jeopardizing the watermark. This paper presents a formal definition of zero-knowledge watermark detection, discusses zero-knowledge watermark detection protocols and compares their properties.     

Increasing the aqueous solubility of acetaminophen in the presence of polyvinylpyrrolidone and investigation of the mechanisms involved

It was shown that the aqueous solubility of acetaminophen in the presence of polyvinylpyrrolidone (PVP) increased. The solubility at 25°C increased from 14.3 mg mL^-1 in the absence of PVP, to 19.7 mg mL^-1 in the presence of 4% w/v PVP, and to 26.7 mg mL^-1 in the presence of 8% w/v PVP. Dialysis studies indicated that there is a potential of binding between PVP and acetaminophen in their aqueous solutions. Dialysis studies also revealed that the nature of interaction between PVP and acetaminophen is physical and reversible, and there was no strong binding between PVP and acetaminophen in their solutions. Infrared spectroscopy of acetaminophen/PVP solid dispersion indicated that the mechanism of interaction between PVP and acetaminophen is via hydrogen bonding. Therefore, the increase in solubility of acetaminophen in the presence of PVP is probably attributed to its ability to form a water-soluble complex with PVP.     

A 0.2-W Heterostructure Barrier Varactor Frequency Tripler at 113 GHz

We present a high-power InAlAs/InGaAs/InP heterostructure barrier varactor (HBV) frequency tripler. The HBV device topology was designed for efficient thermal dissipation and high efficiency. To verify simulations, the device was flip-chip soldered onto embedding microstrip circuitry on an aluminum nitride substrate. This hybrid circuit was then mounted in a waveguide block without any movable tuners. From the resulting RF measurements, the maximum output power was 195 mW at 113 GHz, with a conversion efficiency of 15%. The measured 3-dB bandwidth was 1.5%     

Investigating the effect of nanoparticles on the rutting behaviour of hot-mix asphalt

Rutting is considered as one of the major damages in asphalt mixtures. In this study, different types of nanoparticles such as TiO₂, Al₂O₃, Fe₂O₃ and ZnO in different percentages were added to the base asphalt binder in order to decrease the rutting potential of hot-mix asphalt (HMA). In the first step, asphalt binder tests for characteristics such as penetration grade, ductility, softening point and viscosity were performed on the asphalt binder modified by the nanoparticles. Then, after preparing HMA samples, the static creep test was done at two stress levels at a specific temperature. Results of this study showed that using the nanoparticles improved the behavioural properties of the asphalt binder and decreased rutting in asphalt mix samples. Furthermore, scanning electron microscope images taken from the asphalt binder samples modified by the nanoparticles demonstrated that these nanoparticles were properly distributed in the asphalt binder space and had a positive effect on the rutting performance of the asphalt mixes.     

Organometallic Bonding in an Ullmann‐Type On‐Surface Chemical Reaction Studied by High‐Resolution Atomic Force Microscopy

The on‐surface Ullmann‐type chemical reaction synthesizes polymers by linking carbons of adjacent molecules on solid surfaces. Although an organometallic compound is recently identified as the reaction intermediate, little is known about the detailed structure of the bonded organometallic species and its influence on the molecule and the reaction. Herein atomic force microscopy at low temperature is used to study the reaction with 3,9‐diiododinaphtho[2,3‐b:2′,3′‐d]thiophene (I‐DNT‐VW), which is polymerized on Ag(111) in vacuum. Thermally sublimated I‐DNT‐VW picks up a Ag surface atom, forming a C? Ag bond at one end after removing an iodine. The C? Ag bond is usually short‐lived, and a C? Ag? C organometallic bond immediately forms with an adjacent molecule. The existence of the bonded Ag atoms strongly affects the bending angle and adsorption height of the molecular unit. Density functional theory calculations reveal the bending mechanism, which reveals that charge from the terminus of the molecule is transferred via the Ag atom into the organometallic bond and strengths the local adsorption to the substrate. Such deformations vanish when the Ag atoms are removed by annealing and C? C bonds are established.     

A NEW DISTRIBUTED JOB SCHEDULING ALGORITHM FOR GRID SYSTEMS

Job scheduling is one of the key issues in the design of grid environments. The performance of the grid system severely degrades if a method does not exist to efficiently schedule the user jobs. In this article, a fully distributed, learning automata–based job scheduling algorithm is proposed for grid environments. The proposed method is composed of two types of procedures: in the first, a procedure is run at the grid nodes and in the second, the procedure is run at the schedulers. The proposed algorithm synchronizes the performance of the schedulers by the learning automata that select their actions using the pseudo-random number generators with the same seed. In this method, the grid computational capacity that is allocated to each scheduler is proportional to its workload. To show the efficiency of the proposed method, several simulation experiments were conducted under different grid scenarios. The obtained results show that the proposed algorithm outperforms several well-known methods in terms of makespan, flow time, and load balancing.