Superparamagnetic particle dynamics and mixing in a rotating capillary tube with a stationary magnetic field

The dynamics of superparamagnetic particles subject to competing magnetic and viscous drag forces have been examined with a uniform, stationary, external magnetic field. In this approach, competing drag and magnetic forces were created in a fluid suspension of superparamagnetic particles that was confined in a capillary tube; competing viscous drag and magnetic forces were established by rotating the tube. A critical Mason number was determined for conditions under which the rotation of the capillary prevents the formation of chains from individual particles. The statistics of chain length was investigated by image analysis while varying parameters such as the rotation speed and the viscosity of the liquid. The measurements showed that the rate of particle chain formation was decreased with increased viscosity and rotation speed; the particle dynamics could be quantified by the same dimensionless Mason number that has been demonstrated for rotating magnetic fields. The potential for enhancement of mixing in a bioassay was assessed using a fast chemical reaction that was diffusion-limited. Reducing the Mason number below the critical value, so that chains were formed in the fluid, gave rise to a modest improvement in the time to completion of the reaction.     

The thermal stability of AlN

The thermal stability of AlN powders and thin films has been investigated using reflection high-energy electron diffraction (RHEED) and X-ray diffraction. AlN powder was treated thermally and chemically to assess the oxidation resistance of this compound and to identify the phases formed. The results show that AlN is stable up to 1000° C in air and remains stable up to 1400° Cin vacuo. -AIOOH is formed when AlN is treated with water at 100° C but AlN does not react readily with atmospheric moisture at room temperature. The thermal stability of thin films of AlN on GaAs has been evaluated at temperatures between 900 and 1100° C in a nitrogen atomosphere. It was found that AlN did not oxidize under these conditions. Pure AlN is a suitable encapsulant for GaAs at high annealing temperatures in an inert atmosphere.     

Activating pulp toward acetylation by chemical or mechanical means

Activation of pulps during acetylation, by prior mechanical or chemical treatment, has been investigated. The effect of degree of beating on the acetylation rate of wood and bagasse pulps has been studied. It is found that the acetylation rate of pulps increases when the degree of beating of pulps is increased to a definite degree, after which it slows down. The maximum reactivity of bagasse pulp is obtained at 50°SR, while that of wood pulp is observed at 30°SR. The effect of grafting of acrylonitrile onto bagasse and wood pulps on their reactivity during acetylation has been also studied. The results indicate that grafting of acrylonitrile onto pulps has a favorable effect on their acetylation rate. This is dependent on the degree of grafting as well as the origin of pulp fibers. The most suitable method of activation during acetylation reaction is dependent on the origin of the pulp. The reactivity of bagasse pulp during acetylation is influenced more by beating of pulp, prior to the reaction, than by the grafting of acrylonitrile onto pulp. On the other hand, the acetylation reaction of wood pulp is activated by grafting rather than by beating. Also the effect of the activation process, mechanical or chemical, on the strength properties of the paper sheets produced from acetylated pulps has been investigated. Chemical activation of wood pulp prior to acetylation resulted in pulp with slightly higher strength properties than that activated by mechanical means. But, in the case of bagasse pulp, mechanical activation resulted in a pulp with strength superior to that produced by chemical activation.     

Corrosion inhibition of triethanolammonium bromide mono- and dibenzoate as cationic inhibitors in an acidic medium

A weight loss technique was used to determine the corrosion inhibition efficiency of synthesized alkyl mono-and dibenzoate triethanolammonium bromide derivatives (TEAMB, TEADB) in an acidic medium (2 N HCl) at different doses (50, 100, and 200 ppm). The results showed that monoderivatives had a higher corrosion inhibition efficiency than diderivatives. The results were correlated with several factors, including the alkyl chain length of the hydrophobic chains, interfacial tension (IT), critical micelle concentration (CMC), and adsorption free energy of these inhibitors. Increasing the geometric length of the alkyl chains in the synthesized inhibitors had an increasing effect on their corrosion inhibition efficiency, whereas decreasing the CMC and IT had an increasing effect on their tendency toward corrosion inhibition. The number of hydrophobic chains attached to the inhibitor molecules had a vital influence on their efficiency as corrosion inhibitors.     

Effects of combined wrist deviation and forearm rotation on discomfort score

The aim of the study was to examine the pattern of the change in discomfort for combined wrist deviation and forearm rotation as joint angles increased away from neutral in a repetitive task. There were five levels of wrist deviation (neutral, 35% and 55% of the range of motion (ROM) in radial and ulnar deviation) and five levels of forearm rotation (neutral, 30% and 60% of the ROM in pronation and supination). Twenty-five participants performed a repetitive flexion task with a force of 10 N +/- 1 N at a frequency of 15 exertions per min, with replication after 1 week for six of the participants. A visual analogue scale was used for recording the discomfort scores. Repeated measures analysis of covariance with the Greenhouse-Geisser correction, where necessary, was used on transformed values of the discomfort scores. Grip test endurance time at 50% of maximum voluntary contraction was included as a covariate. Wrist deviation (p = 0.007) and forearm rotation (p = 0.001) were found to have significant effects. Interactions of the main factors were not significant and nor was the covariate. Quadratic regression equations were derived and were used to generate iso-discomfort contours, which show a useful area of low discomfort around the central neutral zone of wrist postures, but with steep increases in discomfort at the extreme combinations of wrist ulnar/radial deviation with forearm pronation/supination. Discomfort equations and contours, showing wrist and forearm postures, which are either acceptable or potentially injurious, are useful for the design of industrial tools, machine controls and workspaces. Reference to these can help to reduce the risk of musculoskeletal injury associated with the tasks or tools by avoiding poor postures with unacceptable deviations from neutral posture.     

Applying Dynamic Training‐Subset Selection Methods Using Genetic Programming for Forecasting Implied Volatility

Volatility is a key variable in option pricing, trading, and hedging strategies. The purpose of this article is to improve the accuracy of forecasting implied volatility using an extension of genetic programming (GP) by means of dynamic training‐subset selection methods. These methods manipulate the training data in order to improve the out‐of‐sample patterns fitting. When applied with the static subset selection method using a single training data sample, GP could generate forecasting models, which are not adapted to some out‐of‐sample fitness cases. In order to improve the predictive accuracy of generated GP patterns, dynamic subset selection methods are introduced to the GP algorithm allowing a regular change of the training sample during evolution. Four dynamic training‐subset selection methods are proposed based on random, sequential, or adaptive subset selection. The latest approach uses an adaptive subset weight measuring the sample difficulty according to the fitness cases' errors. Using real data from S&P500 index options, these techniques are compared with the static subset selection method. Based on mean squared error total and percentage of non‐fitted observations, results show that the dynamic approach improves the forecasting performance of the generated GP models, especially those obtained from the adaptive‐random training‐subset selection method applied to the whole set of training samples.     

Identifying Objects in Procedural Programs Using Clustering Neural Networks

This paper presents a general approach for the identification of objects in procedural programs. The approach is based on neural architectures that perform an unsupervised learning of clusters. We describe two such neural architectures, explain how to use them in identifying objects in software systems and briefly describe a prototype tool, which implements the clustering algorithms. With the aid of several examples, we explain how our approach can identify abstract data types as well as groups of routines which reference a common set of data. The clustering results are compared to the results of many other object identification techniques. Finally, several case studies were performed on existing programs to evaluate the object identification approach. Results concerning two representative programs and their generated clusters are discussed.     

Polyamides incorporating furan moieties. 5. Synthesis and characterisation of furan-aromatic homologues

2,2′-Bis (5-chloroformyl 2-furyl) propane and various aromatic diamines were used as monomers in the study of their interfacial polycondensation and the properties of the ensuing furanic-aromatic polyamides. The effects of such variables as the nature of the organic phase, the temperature, the reaction time, and the type and concentration of the catalyst were investigated as well as the properties of the polyamides in terms of structure, average chain length, T_g, T_m and thermal stability.     

Facile Synthesis of ZSM-5/TiO2/Ni Novel Nanocomposite for the Efficient Photocatalytic Degradation of Methylene Blue Dye

It is critical to develop an appropriate dye degrading technique to preserve the natural environment and human health owing to the dangerous water pollution caused by effluent dyes. So, in this work, a ZSM-5/TiO₂/Ni photocatalyst was synthesized as a novel composite and used for degrading methylene blue dye in the solution. The sol–gel approach was used to immobilize titanium dioxide nanoparticles on the ZSM-5 surface, and the resulting photocatalyst was then modified using nickel nanoparticles to improve its photocatalytic performance. The nanocomposite was characterized using different tools such as FE-SEM, EDX, XRD, FT-IR, TGA, and UV–Vis spectrophotometer. The XRD confirmed that the synthesized composite has the characteristic TiO₂ peaks. FE-SEM images of ZSM-5 exhibited rough, uneven, and jagged surfaces. A distinct shift in the morphology of the surface resulted when titanium dioxide was fully immobilized on the surface of ZSM-5. Shape complexity and surface roughness of the particles are elevated in the case of the ZSM-5/TiO₂/Ni nanocomposite. The maximum % degradation of 50 mL of 15 mg/L of methylene blue dye is 99.17% and achieved at pH?=?8, irradiation time?=?140 min, and photocatalyst dosage?=?0.05 g. The synthesized composite can be regenerated and reused several times without losing its efficacy.