Bulk silica-based luminescent materials by sol-gel processing of non-conventional precursors

The sol-gel synthesis of bulk silica-based luminescent materials using innocuous hexaethoxydisilane and hexamethoxydisilane monomers, followed by one hour thermal annealing in an inert atmosphere at 950oC-1150oC, is reported. As-synthesized hexamethoxydisilane-derived samples exhibit an intense blue photoluminescence band, whereas thermally treated ones emit stronger photoluminescence radiation peaking below 600 nm. For hexaethoxydisilane-based material, annealed at or above 1000oC, a less intense photoluminescence band, peaking between 780 nm and 850 nm that is attributed to nanocrystalline silicon is observed. Mixtures of both precursors lead to composed spectra, thus envisaging the possibility of obtaining pre-designed spectral behaviors by varying the mixture composition.

New kernel functions and learning methods for text and data mining

Recent advances in machine learning methods enable increasingly the automatic construction of various types of computer assisted methods that have been difficult or laborious to program by human experts. The tasks for which this kind of tools are needed arise in many areas, here especially in the fields of bioinformatics and natural language processing. The machine learning methods may not work satisfactorily if they are not appropriately tailored to the task in question. However, their learning performance can often be improved by taking advantage of deeper insight of the application domain or the learning problem at hand. This thesis considers developing kernel-based learning algorithms incorporating this kind of prior knowledge of the task in question in an advantageous way. Moreover, computationally efficient algorithms for training the learning machines for specific tasks are presented. In the context of kernel-based learning methods, the incorporation of prior knowledge is often done by designing appropriate kernel functions. Another well-known way is to develop cost functions that fit to the task under consideration. For disambiguation tasks in natural language, we develop kernel functions that take account of the positional information and the mutual similarities of words. It is shown that the use of this information significantly improves the disambiguation performance of the learning machine. Further, we design a new cost function that is better suitable for the task of information retrieval and for more general ranking problems than the cost functions designed for regression and classification. We also consider other applications of the kernel-based learning algorithms such as text categorization, and pattern recognition in differential display. We develop computationally efficient algorithms for training the considered learning machines with the proposed kernel functions. We also design a fast cross-validation algorithm for regularized least-squares type of learning algorithm. Further, an efficient version of the regularized least-squares algorithm that can be used together with the new cost function for preference learning and ranking tasks is proposed. In summary, we demonstrate that the incorporation of prior knowledge is possible and beneficial, and novel advanced kernels and cost functions can be used in algorithms efficiently.

Spontaneous rupture of ovarian cystadenocarcinoma: pre- and post-rupture computed tomography evaluation

AbstractEpithelial ovarian tumors are the most common malignant ovarian neoplasms and, in most cases, eventual rupture of such tumors is associated with a surgical procedure. The authors report the case of a 54-year-old woman who presented with spontaneous rupture of ovarian cystadenocarcinoma documented by computed tomography, both before and after the event. In such cases, a post-rupture staging tends to be less favorable, compromising the prognosis.

Automated flow-injection method for cadmium determination with pre-concentration and reagent preparation on-line

The spectrophotometric determination of Cd(II) using a flow injection system provided with a solid-phase reactor for cadmium preconcentration and on-line reagent preparation, is described. It is based on the formation of a dithizone-Cd complex in basic medium. The calibration curve is linear between 6 and 300 µg L-1 Cd(II), with a detection limit of 5.4 µg L-1, an RSD of 3.7% (10 replicates in duplicate) and a sample frequency of 11.4 h-1. The proposed method was satisfactorily applied to the determination of Cd(II) in surface, well and drinking waters.

Flow analysis by using solenoid valves for As(III) determination in natural waters by an on-line separation and pre-concentration system coupled to a tungsten coil atomizer

A flow system coupled to a tungsten coil atomizer in an atomic absorption spectrometer (TCA-AAS) was developed for As(III) determination in waters, by extraction with sodium diethyldithiocarbamate (NaDDTC) as complexing agent, and by sorption of the As(III)-DDTC complex in a micro-column filled with 5 mg C18 reversed phase (10 µL dry sorbent), followed by elution with ethanol. A complete pre-concentration/elution cycle took 208 s, with 30 s sample load time (1.7 mL) and 4 s elution time (71 µL). The interface and software for the synchronous control of two peristaltic pumps (RUN/ STOP), an autosampler arm, seven solenoid valves, one injection valve, the electrothermal atomizer and the spectrometer Read function were constructed. The system was characterized and validated by analytical recovery studies performed both in synthetic solutions and in natural waters. Using a 30 s pre-concentration period, the working curve was linear between 0.25 and 6.0 µg L-1 (r = 0.9976), the retention efficiency was 94±1% (6.0 µg L-1), and the pre-concentration coefficient was 28.9. The characteristic mass was 58 pg, the mean repeatability (expressed as the variation coefficient) was 3.4% (n=5), the detection limit was 0.058 µg L-1 (4.1 pg in 71 µL of eluate injected into the coil), and the mean analytical recovery in natural waters was 92.6 ± 9.5 % (n=15). The procedure is simple, economic, less prone to sample loss and contamination and the useful lifetime of the micro-column was between 200-300 pre-concentration cycles.

Identification of the Emerging Issues in Recycled Fiber Processing

The objectives of this research work “Identification of the Emerging Issues in Recycled Fiber processing” are discovering of emerging research issues and presenting of new approaches to identify promising research themes in recovered paper application and production. The projected approach consists of identifying technological problems often encountered in wastepaper preparation processes and also improving the quality of recovered paper and increasing its proportion in the composition of paper and board. The source of information for the problem retrieval is scientific publications in which waste paper application and production were discussed. The study has exploited several research methods to understand the changes related to utilization of recovered paper. The all assembled data was carefully studied and categorized by applying software called RefViz and CiteSpace. Suggestions were made on the various classes of these problems that need further investigation in order to propose an emerging research trends in recovered paper.

Machine Learning and Clinical Text. Supporting Health Information Flow

Fluent health information flow is critical for clinical decision-making. However, a considerable part of this information is free-form text and inabilities to utilize it create risks to patient safety and cost-­effective hospital administration. Methods for automated processing of clinical text are emerging. The aim in this doctoral dissertation is to study machine learning and clinical text in order to support health information flow.First, by analyzing the content of authentic patient records, the aim is to specify clinical needs in order to guide the development of machine learning applications.The contributions are a model of the ideal information flow,a model of the problems and challenges in reality, and a road map for the technology development. Second, by developing applications for practical cases,the aim is to concretize ways to support health information flow. Altogether five machine learning applications for three practical cases are described: The first two applications are binary classification and regression related to the practical case of topic labeling and relevance ranking.The third and fourth application are supervised and unsupervised multi-class classification for the practical case of topic segmentation and labeling.These four applications are tested with Finnish intensive care patient records.The fifth application is multi-label classification for the practical task of diagnosis coding. It is tested with English radiology reports.The performance of all these applications is promising. Third, the aim is to study how the quality of machine learning applications can be reliably evaluated.The associations between performance evaluation measures and methods are addressed,and a new hold-out method is introduced.This method contributes not only to processing time but also to the evaluation diversity and quality. The main conclusion is that developing machine learning applications for text requires interdisciplinary, international collaboration. Practical cases are very different, and hence the development must begin from genuine user needs and domain expertise. The technological expertise must cover linguistics,machine learning, and information systems. Finally, the methods must be evaluated both statistically and through authentic user-feedback.

The pre-history of cryoscopy: what was done before raoult?

Cryoscopy is considered one of the foundations of the modern theory of solutions and of physical chemistry. This paper shows in order the first regularities pointed out by several scientists on the subject, in the first chapter of its birth as a scientific discipline. The study is focused on the identification of the different steps that helped, first qualitatively and then quantitatively, to adjust the different classes of possible solutions, including those that formed hydrates, to a basic formulation that the French scientist François-Marie Raoult would later generalize in the law that bears his name.

Evaluation of sample processing methods for the polar contaminant analysis of sewage sludge using liquid chromatography - mass spectrometry (LC/MS)

Monitoring of sewage sludge has proved the presence of many polar anthropogenic pollutants since LC/MS techniques came into routine use. While advanced techniques may improve characterizations, flawed sample processing procedures, however, may disturb or disguise the presence and fate of many target compounds present in this type of complex matrix before analytical process starts. Freeze-drying or oven-drying, in combination with centrifugation or filtration as sample processing techniques were performed followed by visual pattern recognition of target compounds for assessment of pretreatment processes. The results shown that oven-drying affected the sludge characterization, while freeze-drying led to less analytical misinterpretations.

Processing of spent NiW/Al2O3 catalysts

Spent oxidized (500 ºC, 5 h) commercial NiW/Al2O3 catalysts were processed using two different routes: a) fusion with NaOH (650 ºC, 1 h), the roasted mass was leached in water; b) leaching with HCl or H2SO4 (70 ºC, 1-3 h). HCl was the best leachant. In both routes, soluble tungsten was extracted at pH 1 with Alamine 336 (10 vol.% in kerosene) and stripped with 2 mol L-1 NH4OH (25 ºC, one stage, aqueous/organic ratio = 1 v/v). Tungsten was isolated as ammonium paratungstate at very high yield (> 97.5%). The elements were better separated using the acidic route.

Bioanalytical method for the quantification of the monastrol derivative anticancer candidate lasom 65 in pre-clinical pharmacokinetic investigations

A simple HPLC/UV method was developed for the determination of the anticancer candidate LaSOM 65 in rat plasma. Samples were cleaned by protein precipitation with acetonitrile (recovery > 95%), after which they were subjected to chromatography under the isocratic elution of an acetonitrile:water (45:55, ν/ν) solution with detection at 303 nm. The method was linear (r² > 0.98) over the concentration range (0.05-2 µg mL-1) with intra- and inter-day precision ranging from 9.6% to 13.6% and 4.3% to 5.4%, respectively. The accuracy of the method ranged from 85% to 113.6%, and it showed sufficient sensitivity to determine pharmacokinetic parameters of LaSOM 65 after intravenous administration to Wistar rats.

Determination of Copper, Iron, Nickel and Zinc in fuel kerosene by FAAS after adsorption and pre-concentration on 2-aminothiazole-modified silica gel

Silica gel chemically modified with 2-Aminotiazole groups, abbreviated as SiAT, was used for preconcentration of copper, zinc, nickel and iron from kerosene, normally used as a engine fuel for airplanes. Surface characteristics and surface area of the silica gel were obtained before and after chemical modification using FT-IR, Kjeldhal and surface area analysis (B.E.T.). The retention and recovery of the analyte elements were studied by applying batch and column techniques. The experimental parameters, such as shaking time in batch technique, flow rate and concentration of the eluent (HCl- 0.25-2.00 mol L-1) and the amount of silica, on retention and elution, have been investigated. Detection limits of the method for copper, iron, nickel and zinc are 0.77, 2.92, 1.73 and 0.097 mg L-1, respectively. The sorption-desorption of the studied metal ions made possible the development of a preconcentration method for metal ions at trace level in kerosene using flame AAS for their quantification.

The Li+, Na+ and K+ ion exchange reaction process on the surface of mixed oxide SiO2/TiO2/Sb2O5 surface prepared by the sol-gel processing method

The porous mixed oxide SiO2/TiO2/Sb2O5 obtained by the sol-gel processing method presented a good ion exchange property and a high exchange capacity towards the Li+, Na+ and K+ ions. In the H+/M+ ion exchange process, the H+ / Na+ could be described as presenting an ideal character. The ion exchange equilibria of Li+ and K+ were quantitatively described with the help of the model of fixed tetradentate centers. The results of simulation evidence that for the H+ / Li+ exchange the usual situation takes place: the affinity of the material to the Li+ ions is decreased with increasing the degree of ion exchange. On the contrary, for K+ the effects of positive cooperativity, that facilitate the H+ / K+ exchange, were revealed.

Adsorption of hidrogen peroxide on the surface of silica - titania mixed oxide obtained by the sol-gel processing method

This work describes the sol-gel mixed oxide SiO2/TiO2 property, ST, as prepared, and submitted to heat treatment a 773 K, STC. SEM and EDS images show, within magnification used, a uniform distribution of the TiO2 particles in SiO2/TiO2 matrix. Both, ST and STC adsorb hydrogen peroxide on the surface and through EPR and UV-Vis diffuse reflectance spectra, it was possible to conclude that the species on the surface is the peroxide molecule attached to the Lewis acid site of titanium particle surface, alphaTi(H2O2)+. As the material is very porous, presumably the hydrogen peroxide molecule is confined in the matrix pores on the surface, a reason why the adsorbed species presents an exceptional long lived stability.