Mathematical modeling of falling liquid film evaporation process

A mathematical model of evaporation process from a laminar falling liquid film on a vertical plate of constant temperature is presented. The model is developed with and without interfacial shear stress due to the vapor flow at the liquid film surface. The vapor pressure drop, vapor exit velocity and cooling rate are calculated for different liquid mass flow values. It is shown that lower liquid mass flow produces higher cooling rate. The results also show that the interfacial shear stress has a considerable negative effect on the cooling rate. It is proved that there exists an optimum distance between the plates, which gives the maximum volumetric cooling rate.     

Heat and Mass Transfer Analogy Studies of Binary Liquid Mixture in Comparison with Eteanol-n-Heptane Evaporating to Air

An expenmental and theoretical study of heat and mass transfer analogy and a comparison of that to a binary liquid mixture evaporation is presented. Common organic solvents, ethanol and n-heptane, were used to form an alcohol - hydrocarbon mixture. Studies were carried out in a horizontal rectangular channel having air flow velocities of 0.2 - 0.9 m/s. Heat transfer coefficients were measured with a copper plate resistor and mass transfer coefficients with a square pool. The heat and mass transfer analogy is presented for a system having two evaporating compounds with a fixed value of air flow and verified by measuring and comparing mass transfer coefficients for distilled water with air flow velocities of 0.2 - 0.9 mls. An illustrative example of the use of the theory for industrial ventilation is presented.     

Biobased thermosets from the free‐radical copolymerization of conjugated linseed oil

New polymeric thermosets were prepared through the bulk free‐radical copolymerization of 100% conjugated linseed oil, acrylonitrile, and divinylbenzene. Under the appropriate reaction conditions and with the appropriate curing sequence, 61–96 wt % of the oil was incorporated into the crosslinked thermosets. The resulting yellow, transparent thermosets varied from being soft and flexible to being hard and brittle. Dynamic mechanical analysis and thermogravimetric analysis showed that these thermosets had good mechanical properties and thermal stability. © 2007 Wiley Periodicals, Inc. J Appl Polym Sci 104: 979–985, 2007     

Characteristic study of N07718 superalloy surface prepared by cold spray

For better performance in erosive–corrosive, wear and other extreme environmental conditions surface properties of metals and alloys are usually altered by different techniques. Amongst the various surface coating techniques cold spraying is a relatively new and less reported method. Coating formation at energy lower than the melting stage of materials brings novelty to this process. In this study surface of UNS No. - N07718 alloy is altered by cold spraying chromium-carbide (nickel-chromium) layer. The microstructure properties of this cold sprayed surface are observed by various characterization techniques and the results are used to study mechanism of coating layer formation by cold spray process. This newly developed cold sprayed surface is found to be eligible for further testing in wear and erosive-corrosive environmental conditions.     

Temporal Kohonen Map and the Recurrent Self-Organizing Map: Analytical and Experimental Comparison

This paper compares two Self-Organizing Map (SOM) based models for temporal sequence processing (TSP) both analytically and experimentally. These models, Temporal Kohonen Map (TKM) and Recurrent Self-Organizing Map (RSOM), incorporate leaky integrator memory to preserve the temporal context of the input signals. The learning and the convergence properties of the TKM and RSOM are studied and we show analytically that the RSOM is a significant improvement over the TKM, because the RSOM allows simple derivation of a consistent learning rule. The results of the analysis are demonstrated with experiments.     

Introducing Glycolinkers for the Functionalization of Cytotoxic Drugs and Applications in Antibody–Drug Conjugation Chemistry

Antibody–drug conjugates (ADCs) are promising alternatives to naked antibodies for selective drug‐delivery applications and treatment of diseases such as cancer. Construction of ADCs relies upon site‐selective, efficient and mild conjugation technologies. The choice of a chemical linker is especially important, as it affects the overall properties of the ADC. We envisioned that hydrophilic bifunctional chemical linkers based on carbohydrates would be a useful class of derivatization agents for the construction of linker–drug conjugates and ADCs. Herein we describe the synthesis of carbohydrate‐based derivatization agents, glycolinker–drug conjugates featuring the tubulin inhibitor monomethyl auristatin E and an ADC based on an anti‐EGFR antibody. In addition, an initial in vitro cytotoxicity evaluation of the individual components and the ADC is provided against EGFR‐positive cancer cells.     

A framework for generating tunable test functions for multimodal optimization

Multimodal function optimization, where the aim is to locate more than one solution, has attracted growing interest especially in the evolutionary computing research community. To evaluate experimentally the strengths and weaknesses of multimodal optimization algorithms, it is important to use test functions representing different characteristics and various levels of difficulty. The available selection of multimodal test problems is, however, rather limited and no general framework exists. This paper describes an attempt to construct a software framework which includes a variety of easily tunable test functions. The aim is to provide a general and easily expandable environment for testing different methods of multimodal optimization. Several function families with different characteristics are included. The framework implements new parameterizable function families for generating desired landscapes. Additionally the framework implements a selection of well known test functions from the literature, which can be rotated and stretched. The software module can easily be imported to any optimization algorithm implementation compatible with the C programming language. As an application example, 8 optimization approaches are compared by their ability to locate several global optima over a set of 16 functions with different properties generated by the proposed module. The effects of function regularity, dimensionality and number of local optima on the performance of different algorithms are studied.     

WATER FLOW AND BINDER MIGRATION DURING DRYING OF COATED PAPER

The aim of this study has been to develop a mathematical model for water flow and binder migration in coated paper. The model can be used for simulation of the stages starting after the coating applicator including infrared and air drying sections. On the basis of the model the moisture, temperature and binder distribution can be determined across the paper thickness. Approximating equations concerning the paper properties are used in the model. We have measured the diffusion coefficient between the water and binder substances. Representative numerical examples are presented for separate and combined infrared and air drying processes.     

Fixation of distal femoral osteotomies with self-reinforced poly(L/DL)lactide 70 : 30/bioactive glass composite rods. An experimental study on rats

Self-reinforced poly(L/DL)lactide 70:30/bioactive glass [SR-P(L/DL)LA/bioactive glass] composite rods, 2 mm in diameter and 36 mm in length, were implanted into the dorsal subcutaneous tissue of 16 rats. Osteotomies of the distal femur were fixed with these rods (2 x 15 mm) in 64 other rats. The follow-up times varied from one week to one year. After sacrifice, three-point bending and shear tests, and molecular weight measurements were performed for subcutaneously placed rods. Radiological, histological, histomorphometrical, microradiographic, and oxytetracycline-fluorescence studies of the osteotomized and intact control femora were performed. At 24 weeks the mechanical properties had decreased significantly. Thirty-nine osteotomies healed uneventfully. One of the 64 evaluated osteotomies showed signs of infection at six weeks, and there were 19 non-unions and six delayed unions. In 20 operations the fixation was loose and out of these 14 non-unions were observed. No gross signs of inflammatory or foreign-body reactions were observed. The present investigation showed that the mechanical strength and fixation properties of SR-P(L/DL)LA/bioactive glass composite rods are suitable for fixation of cancellous bone osteotomies in rats as long as the operative technique is correct. The present article is the first report on the application of SR-P(L/DL)LA/bioactive glass composite rods for fixation of cancellous bone osteotomies.     

Differential evolution based nearest prototype classifier with optimized distance measures for the features in the data sets

In this paper a further generalization of differential evolution based data classification method is proposed, demonstrated and initially evaluated. The differential evolution classifier is a nearest prototype vector based classifier that applies a global optimization algorithm, differential evolution, for determining the optimal values for all free parameters of the classifier model during the training phase of the classifier. The earlier version of differential evolution classifier that applied individually optimized distance measure for each new data set to be classified is generalized here so, that instead of optimizing a single distance measure for the given data set, we take a further step by proposing an approach where distance measures are optimized individually for each feature of the data set to be classified. In particular, distance measures for each feature are selected optimally from a predefined pool of alternative distance measures. The optimal distance measures are determined by differential evolution algorithm, which is also determining the optimal values for all free parameters of the selected distance measures in parallel. After determining the optimal distance measures for each feature together with their optimal parameters, we combine all featurewisely determined distance measures to form a single total distance measure, that is to be applied for the final classification decisions. The actual classification process is still based on the nearest prototype vector principle; A sample belongs to the class represented by the nearest prototype vector when measured with the above referred optimized total distance measure. During the training process the differential evolution algorithm determines optimally the class vectors, selects optimal distance metrics for each data feature, and determines the optimal values for the free parameters of each selected distance measure. Based on experimental results with nine well known classification benchmark data sets, the proposed approach yield a statistically significant improvement to the classification accuracy of differential evolution classifier.