Entity linking systems for literature reviews

Scientometrics - Computer-assisted methods and tools can help researchers automate the coding process of literature reviews and accelerate the literature review process. However, existing...     

Polymer derived ceramic materials from Si,B and MoSiB filler-loaded perhydropolysilazane precursor for oxidation protection

Silica-based coating systems were developed using polymer derived ceramics (PDCs) technology. Ceramic composites on the base of a SiO₂ and SiNO matrix and homogeneously distributed Mo₅SiB₂, SiB₆, Si and B fillers were manufactured. The coating systems have low porosity and provide a high oxidation resistance up to 100 h at 800 °C and 1100 °C in air. The influence of temperature and atmosphere of pyrolysis on the polymer precursor, the volume fraction of filler materials on the chemical composition of compacts as well as their high-temperature oxidation protection was investigated.     

Effect of complexation of oxidised corn starch with mineral elements on physicochemical properties

The objective of this study was to determine the effect of complexation of oxidised starch with mineral elements on its physicochemical properties. Corn starch was oxidised with sodium hypochlorite and, afterwards, modified with ions of potassium, magnesium and iron. Thus, native and modified starches were analysed for: contents of mineral elements, colour parameters (L*a*b*), water binding capacity and solubility in water at temperature of 60 and 80 °C. Thermodynamic characteristics of gelatinisation by DSC, molecular weight distribution by GPC, intrinsic viscosity and pasting properties by RVA were studied. The efficiency of incorporation of metal ions into oxidised corn starch was about 30%, 20% and 20% for potassium, magnesium and iron ions, respectively. The complexation with potassium ions caused the greatest changes in the molecular weight distribution and the intrinsic viscosity of starches and viscosity of starch pastes. Only modification of starch with iron ions affected the colour parameters of the starch. Incorporation of metal ions into starch resulted also in changes in its water binding capacity and solubility in water.     

Impact of adhesive ingredients on adhesion between rubber and brass-plated steel wire in tire

Proficiency on underlying mechanism of rubber-metal adhesion has been increased significantly in the last few decades. Researchers have investigated the effect of various ingredients, such as hexamethoxymethyl melamine, resorcinol, cobalt stearate, and silica, on rubber-metal interface. The role of each ingredient on rubber-metal interfacial adhesion is still a subject of scrutiny. In this article, a typical belt skim compound of truck radial tire is selected and the effect of each adhesive ingredient on adhesion strength is explored. Out of these ingredients, the effect of cobalt stearate is found noteworthy. It has improved adhesion strength by 12% (without aging) and by 11% (humid-aged), respectively, over control compound. For detailed understanding of the effect of cobalt stearate on adhesion, scanning electron microscopy and energy dispersive spectroscopy are utilized to ascertain the rubber coverage and distribution of elements. X-ray photoelectron spectroscopy results helped us to understand the impact of Cu_XS layer depth on rubber-metal adhesion. The depth profile of the Cu_XS layer was found to be one of the dominant factors of rubber-metal adhesion retention. Thus, this study has made an attempt to find the impact of different adhesive ingredients on the formation of Cu_XS layer depth at rubber-metal interface and establish a correlation with adhesion strength simultaneously.     

Cultivation and downstream processing of microalgae and cyanobacteria to generate protein-based technofunctional food ingredients

Abstract

Microalgae are unicellular microorganisms that can be rich in proteins and are therefore a valuable ingredient in different foods. So far microalgae are mainly utilized in foods in low concentrations as a whole-cell ingredient even though it is known that proteins extracted from microalgae can possibly posess various technofunctional properties, such as high protein solubility, emulsification, foaming, and gelation properties. The widespread usage of protein-rich ingredients obtained from microalgae is for the most part prevented by the high price of the biomass, the lack of efficient downstream processes, and the adverse taste. The aim of this review is to give insights into the fundamental properties of the growth and processing of microalgae, highlight the advantages of microalgae ingredients and show potential applications based on the technofunctional, nutritional and sensory properties that were reported. Moreover, the existing challenges and knowledge gaps that hinder the application of microalgal proteins in foods are discussed.     

Purification of the cardiac sarcoplasmic reticulum membrane protein phospholamban from recombinant Escherichia coli

Phospholamban (PLN) was expressed in Escherichia coli as a protein fusion with glutathione S-transferase (GST). GST-PLN was mostly present in the insoluble protein fraction and accounted for approximately 50% of total insoluble protein. Attempts to suppress inclusion body formation or to use GST as an affinity-purification tag failed. A successful purification method is based on preparative SDS/PAGE and electrodialysis. From 1 g cells we typically purified 13.5 mg fusion protein with a PLN content of 2.8 mg. We genetically inserted an enterokinase (EK) protease site just in front of the PLN sequence and demonstrated the proteolytical liberation of PLN from the carrier protein. The approach described represents a substantial advancement in PLN expression and purification.     

An artificial neural network approach on parametric optimization of laser micro-machining of die-steel

In the present research, laser micro machining (LMM) of tungsten-molybdenum general purpose high speed steel (Rex M2) has been studied. Selection of optimum machining parameter combinations for obtaining higher depth of groove and smaller height of recast layer is a challenging task in LMM due to the presence of a large number of process variables. There is no perfect combination of parameters which can simultaneously result in both the highest depth of groove and lowest height of recast layer. This paper presents an attempt to develop a strategy for predicting the optimum machining parameter setting for the generation of the maximum depth of groove with minimum height of recast layer. A feed forward back-propagation neural network has been developed to model the machining process. The model, after proper training, is capable of predicting the response parameters as a function of four different control parameters. Experimental results demonstrate that the machining model is suitable and the optimization strategy satisfies practical requirements. The developed model has been found to be quite unique, powerful and flexible.     

Enabling simulation interoperability

Over the past years a series of architectures have addressed the need to link multiple simulations. These efforts have been driven primarily by the desire to reuse existing "best of breed" simulations in new combinations to avoid developing any single, monolithic architecture with the impossible goal of meeting all simulation needs. The US Department of Defense began developing the high level architecture (HLA) for distributed computer simulation systems. The high level architecture addresses the need to link multiple computer simulation systems. HLA separates the data model from the architecture's functions for exchanging information.