Chemical and physical properties of short rotation tree species

The European Union’s growth strategy (Europe 2020) requires reductions in greenhouse gas (GHG) emissions and increases in both renewable energy sources and energy efficiency. Short rotation forestry (SRF) has achieved greater awareness due to these targets. Short rotations (1–12 years), rapid growth and the ability to coppice are typical for SRF. Salix, Populus, Alnus and Betula have smaller GHG emissions of biomass production than annual agricultural plant species, since management and harvesting are not needed every year. Physicochemical properties of these species must be known when their utilisation is planned and optimised. Seven tree species were studied: three willows (Salix myrsinifolia, Salix schwerinii and Klara), one aspen (Populus tremula), one alder (Alnus glutinosa) and two birches (Betula pendula and Betula pubescens). One stem wood (S) sample and one stem wood and bark (SB) sample of each tree were investigated. Furthermore, seven surface soil samples and four incineration ash samples (two S. myrsinifolia and two S. schwerinii) were also studied. Heating values, densities, ash contents as well as carbon, hydrogen and nitrogen contents of all short rotation biomass samples were usually quite typical for the corresponding tree species. Additional observations included the accumulation of cadmium in willow and aspen samples, small chloride content values, and higher ash- and element contents in SB samples than in the corresponding S samples. Nutrient content of ash was usually higher in the S sample, contradictory to biomass samples, and finally the cadmium content of the ash samples was very high.     

Susceptibility of Listeria monocytogenes strains to disinfectants and chlorinated alkaline cleaners at cold temperatures

Minimal inhibitory concentration (MIC), suspension and biofilm tests were used in evaluating the disinfecting efficacy of eight commercially available disinfectants and four chlorinated alkaline cleaners against 10 strains of Listeria monocytogenes at refrigerated temperatures. The adaptive response and cross-adaptation of L. monocytogenes to the disinfectants and chlorinated alkaline cleaners were investigated. The bactericidal components in the agents used were chlorine, quaternary ammonium compound (QAC), peracetic acid, ethanol and isopropanol. With some exceptions the disinfectants were efficient against the L. monocytogenes strains. One alkaline hypochlorite containing disinfectant was not efficient in the suspension and MIC tests at the lowest concentration recommended by the manufacturer. The chlorinated alkaline cleaners were effective against L. monocytogenes. A QAC-based disinfectant was found to be the least-effective agent on both glass bead-blasted polyethylene and stainless-steel surfaces. Adaptive and cross-adaptive responses of L. monocytogenes strains were observed towards the QAC-based agent, but over 2-fold increases to other agents were not observed. These results suggest that the adaptive responses of L. monocytogenes to disinfectants or chlorinated alkaline cleaners are of a minor concern.     

Clustering based on conditional distributions in an auxiliary space.

We study the problem of learning groups or categories that are local in the continuous primary space but homogeneous by the distributions of an associated auxiliary random variable over a discrete auxiliary space. Assuming that variation in the auxiliary space is meaningful, categories will emphasize similarly meaningful aspects of the primary space. From a data set consisting of pairs of primary and auxiliary items, the categories are learned by minimizing a Kullback-Leibler divergence-based distortion between (implicitly estimated) distributions of the auxiliary data, conditioned on the primary data. Still, the categories are defined in terms of the primary space. An online algorithm resembling the traditional Hebb-type competitive learning is introduced for learning the categories. Minimizing the distortion criterion turns out to be equivalent to maximizing the mutual information between the categories and the auxiliary data. In addition, connections to density estimation and to the distributional clustering paradigm are outlined. The method is demonstrated by clustering yeast gene expression data from DNA chips, with biological knowledge about the functional classes of the genes as the auxiliary data.     

Atomistic modelling of the Fe-Cr-C system

For the purpose of modelling the impact of carbon on radiation damage phenomena in steels, we have performed an extensive set of first principle calculations on the Fe-Cr-C system. The calculated solution and diffusion enthalpies of carbon in iron and in chromium agree well with experimental data, as do the relative formation energies of mono-carbides, cementite, Hägg and M₂₃C₆ carbides. Our data further indicate that interstitial carbon is attracted to a solute iron atom in bcc chromium, while the reaction between carbon and a solute chromium atom in bcc iron is repulsive. An empirical potential fitted to data for iron carbides is capable of reproducing melting behaviour of cementite, while the predicted interaction with point defects agrees less well with DFT data than a potential recently published by Hepburn and Ackland.     

Principle of Learning Metrics for Exploratory Data Analysis

Visualization and clustering of multivariate data are usually based on mutual distances of samples, measured by heuristic means such as the Euclidean distance of vectors of extracted features. Our recently developed methods remove this arbitrariness by learning to measure important differences. The effect is equivalent to changing the metric of the data space. It is assumed that variation of the data is important only to the extent it causes variation in auxiliary data which is available paired to the primary data. The learning of the metric is supervised by the auxiliary data, whereas the data analysis in the new metric is unsupervised. We review two approaches: a clustering algorithm and another that is based on an explicitly generated metric. Applications have so far been in exploratory analysis of texts, gene function, and bankruptcy. Relationships of the two approaches are derived, which leads to new promising approaches to the clustering problem.     

Handover and Uplink Power Control Performance in the 3.84 Mcps TDD mode of UTRA Network

In this article we consider the performance of the 3.84 Mcpstime-division duplex (TDD) mode of UTRA (Universal TerrestrialRadio Access) network. We emphasize two of the radio resourcemanagement algorithms, handover and uplink power control, whoserole in the overall system performance is studied extensively.First, a handover algorithm used in WCDMA (Wideband Code DivisionMultiple Access) standard is considered in a TDD-mode operation.This gives rise to a careful setting of different handoverparameters, and the evaluation of the effects to the systemperformance. Secondly, the specified uplink power controlalgorithm is considered. Since it is based on several user-mademeasurements which may involve both random and systematic errors acareful study about the suitability of the power control scheme iscarried out.     

Regioisomeric structure determination of alpha- and gamma-linolenoyldilinoleoylglycerol in blackcurrant seed oil by silver ion high-performance liquid chromatography and mass spectrometry

Gamma-linolenic acid (Gla) and oils containing Gla have evident positive effects on a variety of disorders, and therefore, the structure of triacylglycerols (TAGs) containing Gla is of special interest. The regioisomeric structures of TAGs 18:3(n-3)/18:2/18:2 (Ala/L/L) and 18:3(n-6)/18:2/18:2 (Gla/L/L) in blackcurrant seed oil were determined by Ag-HPLC/APCI-MS and Ag-HPLC/ESI-MS/MS techniques. In the latter, silver ion adducts were prepared by adding silver nitrate to the postcolumn flow. A new Ag-HPLC solvent system containing nonchlorinated solvents for the separation of Gla- and Ala-containing TAGs is introduced. Ag-HPLC separation of Ala/L/L and Gla/L/L was sufficient and regioisomers sn-LnLL + sn-LLLn and sn-LLnL (Ln, linolenic acid) could be differentiated well with the MS methods used. No discrimination was made between the sn-1 and sn-3 positions. The results show that the methods used are suitable to discriminate and determine the regioisomeric structure of TAGs. The regioisomeric structure of TAG with the fatty acid combination Gla/L/L in blackcurrant seed oil was considered to be practically random (32.7-37.8% of sn-LGlaL). In the fatty acid combination Ala/L/L, the regioisomeric structure is nonrandom (7.3-12.1% of sn-LAlaL) with Ala preferentially in a primary position. It can be concluded that the positional distribution of Ala and Gla is different in Ln/L/L TAGs of blackcurrant seed oil.     

Ultrasonic assessment of cortical bone thickness in vitro and in vivo

In osteoporosis, total bone mass decreases and the thickness of the cortical layer diminishes in the shafts of the long bones. In this study, a simple ultrasonic in vivo method for determining the thickness of the cortical bone layer was applied, and the suitability of two different signal analysis techniques, i.e., envelope and cepstral methods, for measuring cortical thickness was compared. The values of cortical thickness, as determined with both techniques, showed high linear correlations (r ges 0.95) with the thickness values obtained from in vitro measurements with a caliper or in vivo measurements by peripheral quantitative CT (pQCT). No systematic errors that could be related to the cortical thickness were found. The in vivo accuracy of the measurements was 6.6% and 7.0% for the envelope and cepstral methods, respectively. Further, the in vivo precision for the envelope and cepstral methods was 0.26 mm and 0.28 mm, respectively. Although the results are similar for both of the techniques, the simplicity of the envelope method makes it more attractive for clinical applications. In conclusion, a simple ultrasound measurement provides an accurate estimate of the cortical bone thickness. The techniques investigated may have clinical potential for osteoporosis screening and therefore warrant more extensive clinical investigations with healthy and osteoporotic individuals.