Multivariate Analysis of Finnish Dialect Data An Overview of Lexical Variation

During the process of writing a comprehensive dictionary ofFinnish dialects, a large set of maps describing the regionaldistribution of the dialect words have been compiled in electronicform. In this article, we set out to analyse this corpus ofdata in order to gain new insight on the variation of Finnishdialects. We use a wide range of multivariate data analysismethods, including principal components analysis, independentcomponents analysis, clustering, and multidimensional scaling.We explain how to preprocess the data to overcome the problemof uneven sampling caused by the way the data has been collected.We discuss the results obtained by these methods and comparethem to the traditional view of Finnish dialect groups.     

Preparation and characterisation of α-methylstyrene–butadiene latexes for paper coating applications

The purpose of this work is to demonstrate how α-methylstyrene (AMS) can replace styrene in preparing styrene–butadiene (SB) type latexes and to compare the properties of the paper coating of the prepared α-methylstyrene–butadiene emulsion with the commercial styrene–butadiene latex reference sample. A lot of work is nowadays being conducted on different biorefinery concepts replacing fossil oil with biomass based raw materials due to the expected rise of the fossil oil cost. Aromatics can in principle be produced from renewable raw materials, such as lignin, sugars and terpenes for example. The potential methods include thermochemical conversions, catalytic fast pyrolysis, metabolic engineering, catalytic aromatisation and dehydrogenation among others. Terpenes, such as α-limonene and pinene, are possible sources of aromatics, and they can indeed be catalytically converted to p-cymene. Industrial hydrodealkylation and disproportionation processes developed by major petrochemical companies can further convert p-cymene to BTX aromatics or simultaneously dehydrogenate the alkyl chain of p-cymene to styrenic monomers such as α-methylstyrene. Based on the measured paper properties for uncalendered and calendered coated samples, AMS proved to be adequate to replace the oil based styrene in commercial reference SB latexes. Even though the emulsion polymerisation for the α-methylstyrene–butadiene latex was not optimised, almost all tested properties were at least equally good as in the commercial reference sample. α-Methylstyrene containing coating colours had slightly higher viscosity than the other coating colours. Coating colours containing α-methylstyrene seems to have an improved water retention compared to the commercial reference styrene–butadiene latex coating colour and the laboratory prepared styrene–butadiene coating colour. The paper coated with the commercial reference latex containing coating colour was less porous than the other coated papers. Despite of that, both dry and wet surface strength were at least equally good as in the case of the commercial reference latex. The results are promising when thinking of the future development of the bio-based latexes.     

Physical solvent extraction of levulinic acid from dilute aqueous solution with 2-methyltetrahydrofuran

The results of the present investigation reveal that 2-methyltetrahydrofuran is a potential solvent for the extraction of levulinic acid from dilute aqueous solution. This conclusion is based on the relatively high values of distribution coefficient K_d (1.3-1.6) measured for the system of levulinic acid – water – 2-methyltetrahydrofuran at temperatures 298.2 K, 313.2 K, and 328.2 K, as well as encouraging performance of the continuous counter current Kühni column. The results give reason to believe, that 2-methyltetrahydrofuran can be considered for the extraction of other low molecular weight acids, such as formic or lactic acid, as well.     

Characterization of polyesters prepared from three different phthalic acid isomers by CID-ESI-FT-ICR and PSD-MALDI-TOF mass spectrometry

Polyesters prepared from the same diol, 2-butyl-2-ethyl-1,3-propanediol, but different phthalic acid isomers, phthalic, isophthalic, and terephthalic acid, were characterized by collision-induced dissociation electrospray ionization Fourier transform ion cyclotron resonance (CID-ESI-FT-ICR) and postsource-decay matrix-assisted laser desorption/ionization time-of-flight (PSD-MALDI-TOF) mass spectrometry. Sodiated dihydroxyl-terminated polyester oligomers containing five repeating units at m/z 1634 were selected as precursor ions for dissociation studies. Two main mechanisms occurred in the fragmentation of all of the polyesters, since dissociation of the oligomers was initiated by hydrogen rearrangement or transesterification reactions. Polyesters prepared from different phthalic acid isomers could be distinguished by their fragmentation behavior. Polyester prepared from phthalic acid was easily identified by using both CID-ESI-FT-ICR and PSD-MALDI-TOF mass spectrometry. However, distinguishing between the polyesters prepared from isophthalic and terephthalic acid succeeded marginally only with CID-ESI-FT-ICR mass spectrometry. Molecular dynamics calculations were used to obtain an idea of the fragmentation behavior of the polyesters. The low-energy structures of the precursor ions were determined, and the coordination of the oxygen atoms of the polyester oligomers to the sodium cation was examined more closely. Both the experimental and the theoretical studies showed that the sodium ion affinity of polyester changed with the phthalic acid isomer.     

Data‐Driven Modelling of Quality and Performance Indices in Sintermaking

In developing data‐driven models of complex real‐world systems, a common problem is how to select relevant inputs from a large set of measurements. If the observations of the outputs to be predicted by the model are scarce, which may be the case if the outputs are indices determined in toilsome laboratory tests, strict constraints have to be imposed on the number of model parameters. In neural network modelling, this limitation in practice also restricts the number of hidden nodes as well as the number of input variables, since the dimension of the weight vector strongly depends on these. This paper presents a systematic method for data‐driven modelling with feedforward layered neural networks, including a method for the selection of input variables. The method is illustrated on a problem from ironmaking industry, where sinter quality indices are predicted on the basis of raw material properties. Furthermore, an inversion technique of the resulting network models is proposed, where an optimization problem is solved to maximize the performance of the sintering operation by manipulating the inputs.     

Neural networks and genetic algorithms for bankruptcy predictions

We are focusing on three alternative techniques-linear discriminant analysis, logit analysis and genetic algorithms-that can be used to empirically select predictors for neural networks in failure prediction. The selected techniques all have different assumptions about the relationships between the independent variables. Linear discriminant analysis is based on linear combination of independent variables, logit analysis uses the logistical cumulative function and genetic algorithms is a global search procedure based on the mechanics of natural selection and natural genetics. In an empirical test all three selection methods chose different bankruptcy prediction variables. The best prediction results were achieved when using genetic algorithms.     

Development of LC/MS/MS methods for cocktail dosed Caco-2 samples using atmospheric pressure photoionization and electrospray ionization

Good reliability of Caco-2 permeability studies requires competent sampling and analytical methods to ensure the comparability of day-to-day experiments. In this work, two n-in-one LC/MS/MS methods based on two different ionization techniques were developed and validated for a group of reference compounds; eight of them are recommended by the Food and Drug Administration (FDA) for the evaluation of oral drug permeability. The performance of a new ionization technique, atmospheric pressure photoionization (APPI), as an interface for quantitative LC/MS analysis was evaluated in comparison to the electrospray ionization (ESI). Generally, the validation parameters, including sensitivity, accuracy, and repeatability, were comparable for the APPI and ESI methods. The main difference was that the linear quantitative range of APPI was 3-4 orders of magnitude (r(2) >/= 0.998) whereas in ESI it was typically 2-3 orders of magnitude (r(2) >/= 0.990). By the APPI and ESI methods, the simultaneous analysis of nine highly heterogeneous compounds was achieved within 5.5-7 min, which leads to significant savings in time and cost of the analyses. The successful validation data indicate the usefulness of both the methods for the rapid and sensitive (LOD values typically 相似文献   

Composable Mediation for Security-Aware Mobile Services

This article shows how service mediation can be used to add security features to services in a mobile service platform. This base platform takes care of security, charging, and other basic functions, which are then configured for services at runtime using a pluggable mediator framework. Service providers can focus on content, and thus leverage the signaling and mediation capabilities of the core platform. Mediators add specific functionality to a service, and are a specific form of service composition and selection. We examine how security technologies for authentication and authorization are integrated by mediators into a single policy infrastructure with a homogeneous interface for services. We consider here the Web services SAML and the 3GPP GBA security bootstrapping standard in the context of mobile services. We give an example using a video on demand service, and discuss how and when security concerns of services can be transferred from the services to mediators.