Optical dot gain on newsprint determined with the Lund nuclear microprobe

A technique for measuring optical dot gain, i.e. the relative difference between the actual screen dot and the optically perceived one, is presented. By combining measurements from the non-optical nuclear microprobe with data from image analyzing technique the optical dot gain can be determined. The procedure to reach pixel by pixel correlation on a micrometer scale is discussed. In the newsprint sample studied in this investigation a typical optical dot gain between 15 and 20% was deduced. The variation in the optical dot gain was correlated with other characteristic parameters of the print and newsprint and especially a positive correlation to the mass density of the newsprint was observed.     

New CAMAC based data acquisition and beam control system for Lund nuclear microprobe

A new CAMAC based data acquisition system has been installed at the Lund Nuclear Microprobe facility. This paper reports on the development and present status of the data acquisition system. The system is a true multiparameter CAMAC based system with fast Fera bus readout and in crate memory buffer. The user interface is based on Sparrow Kmax software for a Power Macintosh platform. The system read out and tag the event data with position on-line, which make fast on-line monitoring of spectra or element maps possible.Simultaneously, all data can be saved event by event for off-line analysis. The beam scanning part is software controlled through a timed D/A converter, this allows fast scanning of the beam. With a CCD-camera and video card the area to be analysed could be defined directly from the image, and the sample position can be moved. Any kind of irregular scan patterns could be defined.     

Enhancing oil–solid and oil–water separation in heavy oil recovery by CO2-responsive surfactants

Interfacial properties are of critical importance to various separation applications. In heavy oil recovery, for example, a low oil–water interfacial tension (IFT) benefits the separation of heavy oil from their host rocks, which becomes problematic in the later stage of oil–water separation. CO₂-responsive surfactants were investigated to enhance the overall heavy oil recovery by switching their interfacial activity to the desired state in each stage. The surfactants at interfacially active state greatly enhanced the separation of heavy oil from hosting solids, as demonstrated by measuring contact angle and oil liberation using a custom-designed on-line visualization system. Meanwhile, the resulting heavy oil-in-water emulsions could also be easily demulsified by the bubbling of CO₂ gas, which switched off the interfacial activity of the surfactants. Furthermore, CO₂-responsive surfactants could be partially recycled in process water to improve sustainability, making CO₂-responsive surfactants to be promising chemical aids in heavy oil production and many other vital industries.     

Melt processing of nanocomposites of cellulose nanocrystals with biobased thermoplastic polyurethane

Nanocomposites of thermoplastic polyurethane (TPU) with cellulose nanocrystals (CNC) without and with surface treatment are obtained by melt processing. Nanocomposites are obtained with nanofiller weight content near of the theoretical percolation threshold (3.9 wt%). Visual observation of CNC agglomerates is sufficient to prove the inefficiency of the mixing in systems with untreated CNC. The crystallization kinetics of the TPU changes with the addition of CNC and this is confirmed by differential scanning calorimetry analysis. Thermogravimetric analysis prove that the addition of CNC increases the thermal stability of the TPU. From the rheological analysis it is possible to verify the absence of percolation and an intermediate state of sol–gel transition in the nanocomposites. CNC/TPU nanocomposites with 5 wt% of treated CNC present better mechanical performance than de neat TPU and the other processed nanocomposites and display around 130% increase in Young's modulus while retaining significant values of toughness, tensile strength and elongation at break.     

Spectroscopic Multicomponent Analysis Using Multi-objective Optimization for Variable Selection

The multiple determination tasks of chemical properties are a classical problem in analytical chemistry. The major problem is concerned in to find the best subset of variables that better represents the compounds. These variables are obtained by a spectrophotometer device. This device measures hundreds of correlated variables related with physicocbemical properties and that can be used to estimate the component of interest. The problem is the selection of a subset of informative and uncorrelated variables that help the minimization of prediction error. Classical algorithms select a subset of variables for each compound considered. In this work we propose the use of the SPEA-II （strength Pareto evolutionary algorithm II）. We would like to show that the variable selection algorithm can selected just one subset used for multiple determinations using multiple linear regressions. For the case study is used wheat data obtained by NIR （near-infrared spectroscopy） spectrometry where the objective is the determination of a variable subgroup with information about E protein content （%）, test weight （Kg/HI）, WKT （wheat kernel texture） （%） and farinograph water absorption （%）. The results of traditional techniques of multivariate calibration as the SPA （successive projections algorithm）, PLS （partial least square） and mono-objective genetic algorithm are presents for comparisons. For NIR spectral analysis of protein concentration on wheat, the number of variables selected from 775 spectral variables was reduced for just 10 in the SPEA-II algorithm. The prediction error decreased from 0.2 in the classical methods to 0.09 in proposed approach, a reduction of 37%. The model using variables selected by SPEA-II had better prediction performance than classical algorithms and full-spectrum partial least-squares.     

An Improved NER Methodology to the Portuguese Language

Mobile Networks and Applications - The text mining process typically involves the application of natural language processing (NLP) techniques, in order to obtain important information and extract...     

Characterization of Extra Virgin Olive Oil from Southern Brazil

Six olive oils extracted from the cultivars Arbequina, Arbosana, Coratina, Frantoio, Koroneiki, and Picual from 2017 and 2018 harvests, cultivated in Pinheiro Machado, Rio Grande do Sul, Brazil, are evaluated for standard oil composition parameters and bioactive constituents (pigments, tocopherols, and phenolic compounds). Multivariate principal component analysis (PCA) and univariate ANOVA and Fisher's LSD test are used to verify the effect of cultivar and harvest year on oil composition. Olive oil composition met extra virgin olive oil (EVOO) standard parameters and is influenced by both cultivar and harvest year. EVOO produced in 2018 has greater chlorophyll, caffeic acid, ligstroside aglycone, hydroxyoleuropein aglycone, syringic acid, and hydroxytyrosol acetate contents than the EVOOs from 2017. Linoleic acid, ferulic acid, ligstroside aglycone, and hydroxytyrosol acetate are the variables whose contents most contributed to the differentiation of oils by cultivar in both harvest years. Chemical characterization analyses allow for the differentiation of oil composition based on harvest year and cultivar. Metabolic quality data obtained here support the establishment of a local EVOO profile and the compounds that most contributed to treatment differentiation may serve as markers that can be utilized in determining origin, cultivar, and harvest year. Practical Applications: Olive production in Brazil is recent and is based on European cultivars which have not been bred for the local environmental conditions. Therefore, the measurement of olive oil metabolic quality will determine cultivar adaptability to local edaphoclimatic conditions as well as assist in the establishment of a standard of identity for the product and promote the development of its market. Olive oil produced in Southern Brazil shows high quality, and is especially rich in phenolic compounds. Although harvest year influences oil composition, oil from both harvests meet EVOO standards and cultivar specific metabolic markers are observed. This study provides the foundation for olive producers in Southern Brazil to seek authentication of the geographical origin of olive oil.     

Fiber introduction mass spectrometry: fully direct coupling of solid-phase microextraction with mass spectrometry

This work describes the first fully direct coupling of solid-phase microextraction (SPME) with mass spectrometry. An inlet system using a septum as the only interface between the ambient and the high-vacuum mass spectrometer was constructed to allow the introduction of the SPME needle directly into the ionization region of a mass spectrometer. The PDMS-coated fiber was then placed and exposed exactly between the two ionization filaments. Uniform heating of the fiber, efficient thermal desorption, and electron ionization of the analytes were achieved. Using this new analytical technique, here termed fiber introduction mass spectrometry (FIMS), we have been able to detect and quantitate several volatile (VOC) and semivolatile (SVOC) organic chemicals (carbon tetrachloride, benzene, toluene, xylenes, gamma-terpinene, diisoamyl ether, chlorobenzene, and many PAHs) and two herbicides (Sylvex and its methyl ether) from aqueous solutions at low-ppb to ppt levels using either SPME headspace or solution extraction. FIMS shows high sensitivity (ng/L), good reproducibility, and accuracy, providing therefore a simple and effective approach to rapid analysis of VOC and SVOC in various matrixes.     

Partial Characterization of Ultrafiltrated Soy Protein Hydrolysates with Antioxidant and Free Radical Scavenging Activities

Soy protein isolate (SPI) was hydrolyzed with Flavourzyme® (SHF) or chymotrypsin (SHC). Hydrolysates were sequencially fractionated by ultrafiltration using different membrane pore sizes (50, 10, and 3 kDa). The antioxidant ability of each hydrolysate protein fraction was tested in a liposome oxidizing system and their free radical scavenging activity (FRSA) was evaluated with the DPPH method (diphenylpicrilhydrazine radical). Molecular weight (MW) distribution, solubility, surface hydrophobicity, and amino acid composition of each SPI hydrolysate fraction were measured and their effect on antioxidant and scavenging activities was established by multivariate correlation. The most active ultrafiltrated peptide fractions (P < 0.05), from SHF and SHC, had of MW of <3 kDa (F3 and C3, respectively). These fractions decreased liposome oxidation by 83.2% and 84.5%, respectively, and also showed the highest FRSA (F3: 21.3% and C3: 24.4%). In addition to molecular size, the antioxidant activity and FRSA of soy protein fractions were related to their amino acid composition, especially to an increased content of Phe and a lowered content of Lys. Also, hydrophobicity of ultrafiltrated peptide fractions was an important characteristic (P < 0.001) associated with their ability to trap free radicals. Ultrafiltered peptide fractions with low MW have a high potential to be used as natural alternatives to prevent lipid oxidation in foods.