New Developments and Applications of the MP2RAGE Sequence - Focusing the Contrast and High Spatial Resolution R1 Mapping.

MR structural T1-weighted imaging using high field systems (>3T) is severely hampered by the existing large transmit field inhomogeneities. New sequences have been developed to better cope with such nuisances. In this work we show the potential of a recently proposed sequence, the MP2RAGE, to obtain improved grey white matter contrast with respect to conventional T1-w protocols, allowing for a better visualization of thalamic nuclei and different white matter bundles in the brain stem. Furthermore, the possibility to obtain high spatial resolution (0.65 mm isotropic) R1 maps fully independent of the transmit field inhomogeneities in clinical acceptable time is demonstrated. In this high resolution R1 maps it was possible to clearly observe varying properties of cortical grey matter throughout the cortex and observe different hippocampus fields with variations of intensity that correlate with known myelin concentration variations.

Responses of soil respiration and barley growth to modified supply of oxygen in the soil

Selostus: Maan hengityksen ja ohran kasvun reagointi hapensaannin muutoksiin maassa

Debris flow modeling for susceptibility mapping at regional to national scale in Norway

Debris flows and related landslide processes occur in many regions all over Norway and pose a significant hazard to inhabited areas. Within the framework of the development of a national debris flows susceptibility map, we are working on a modeling approach suitable for Norway with a nationwide coverage. The discrimination of source areas is based on an index approach, which includes topographic parameters and hydrological settings. For the runout modeling, we use the Flow-R model (IGAR, University of Lausanne), which is based on combined probabilistic and energetic algorithms for the assessment of the spreading of the flow and maximum runout distances. First results for different test areas have shown that runout distances can be modeled reliably. For the selection of source areas, however, additional factors have to be considered, such as the lithological and quaternary geological setting, in order to accommodate the strong variation in debris flow activity in the different geological, geomorphological and climate regions of Norway.

Fast low-specific absorption rate B0 -mapping along projections at high field using two-dimensional radiofrequency pulses.

PURPOSE: At 7 Tesla (T), conventional static field (B0 ) projection mapping techniques, e.g., FASTMAP, FASTESTMAP, lead to elevated specific absorption rates (SAR), requiring longer total acquisition times (TA). In this work, the series of adiabatic pulses needed for slab selection in FASTMAP is replaced by a single two-dimensional radiofrequency (2D-RF) pulse to minimize TA while ensuring equal shimming performance. METHODS: Spiral gradients and 2D-RF pulses were designed to excite thin slabs in the small tip angle regime. The corresponding selection profile was characterized in phantoms and in vivo. After optimization of the shimming protocol, the spectral linewidths obtained after 2D localized shimming were compared with conventional techniques and published values from (Emir et al NMR Biomed 2012;25:152-160) in six different brain regions. RESULTS: Results on healthy volunteers show no significant difference (P > 0.5) between the spectroscopic linewidths obtained with the adiabatic (TA = 4 min) and the new low-SAR and time-efficient FASTMAP sequence (TA = 42 s). The SAR can be reduced by three orders of magnitude and TA accelerated six times without impact on the shimming performances or quality of the resulting spectra. CONCLUSION: Multidimensional pulses can be used to minimize the RF energy and time spent for automated shimming using projection mapping at high field. Magn Reson Med, 2014. © 2014 Wiley Periodicals, Inc.

Estimation of soil nitrate in the spring as a basis for adjustment of nitrogen fertiliser rates

Selostus: Maassa olevan nitraattitypen arviointi simulointimallin avulla

Heated Optical Fiber for Distributed Soil-Moisture Measurements: A Lysimeter Experiment

An Actively Heated Fiber Optics (AHFO) method to estimate soil moisture is tested and the analysis technique improved on. The measurements were performed in a lysimeter uniformly packed with loam soil with variable water content profiles. In the first meter of the soil profi le, 30 m of fiber optic cable were installed in a 12 loops coil. The metal sheath armoring the fiber cable was used as an electrical resistance heater to generate a heat pulse, and the soil response was monitored with a Distributed Temperature Sensing (DTS) system. We study the cooling following three continuous heat pulses of 120 s at 36 W m(-1) by means of long-time approximation of radial heat conduction. The soil volumetric water contents were then inferred from the estimated thermal conductivities through a specifically calibrated model relating thermal conductivity and volumetric water content. To use the pre-asymptotic data we employed a time correction that allowed the volumetric water content to be estimated with a precision of 0.01-0.035 (m(3) m(-3)). A comparison of the AHFO measurements with soil-moisture measurements obtained with calibrated capacitance-based probes gave good agreement for wetter soils [discrepancy between the two methods was less than 0.04 (m(3) m(-3))]. In the shallow drier soils, the AHFO method underestimated the volumetric water content due to the longertime required for the temperature increment to become asymptotic in less thermally conductive media [discrepancy between the two methods was larger than 0.1 (m(3) m(-3))]. The present work suggests that future applications of the AHFO method should include longer heat pulses, that longer heating and cooling events are analyzed, and, temperature increments ideally be measured with higher frequency.

Reactivity of silicate liming materials from Northern Europe assessed by Soil Incubation and two pH Stat methods

Selostus: Pohjois-Euroopan silikaattisten kalkitusaineiden reaktiivisuus astiakoemenetelmällä ja kahdella pH-staattisella menetelmällä arvioituna

Tn5-directed cloning of pqq genes from Pseudomonas fluorescens CHA0: mutational inactivation of the genes results in overproduction of the antibiotic pyoluteorin.

Pseudomonas fluorescens CHA0 produces several secondary metabolites, e.g., the antibiotics pyoluteorin (Plt) and 2,4-diacetylphloroglucinol (Phl), which are important for the suppression of root diseases caused by soil-borne fungal pathogens. A Tn5 insertion mutant of strain CHA0, CHA625, does not produce Phl, shows enhanced Plt production on malt agar, and has lost part of the ability to suppress black root rot in tobacco plants and take-all in wheat. We used a rapid, two-step cloning-out procedure for isolating the wild-type genes corresponding to those inactivated by the Tn5 insertion in strain CHA625. This cloning method should be widely applicable to bacterial genes tagged with Tn5. The region cloned from P. fluorescens contained three complete open reading frames. The deduced gene products, designated PqqFAB, showed extensive similarities to proteins involved in the biosynthesis of pyrroloquinoline quinone (PQQ) in Klebsiella pneumoniae, Acinetobacter calcoaceticus, and Methylobacterium extorquens. PQQ-negative mutants of strain CHA0 were constructed by gene replacement. They lacked glucose dehydrogenase activity, could not utilize ethanol as a carbon source, and showed a strongly enhanced production of Plt on malt agar. These effects were all reversed by complementation with pqq+ recombinant plasmids. The growth of a pqqF mutant on ethanol and normal Plt production were restored by the addition of 16 nM PQQ. However, the Phl- phenotype of strain CHA625 was due not to the pqq defect but presumably to a secondary mutation. In conclusion, a lack of PQQ markedly stimulates the production of Plt in P. fluorescens.

Multiple Kernel Learning of Environmental Data. Case study: Analysis and Mapping of Wind Fields

The paper presents the Multiple Kernel Learning (MKL) approach as a modelling and data exploratory tool and applies it to the problem of wind speed mapping. Support Vector Regression (SVR) is used to predict spatial variations of the mean wind speed from terrain features (slopes, terrain curvature, directional derivatives) generated at different spatial scales. Multiple Kernel Learning is applied to learn kernels for individual features and thematic feature subsets, both in the context of feature selection and optimal parameters determination. An empirical study on real-life data confirms the usefulness of MKL as a tool that enhances the interpretability of data-driven models.

Advanced geostatistical and machine-learning models for spatial data analysis of radioactively contaminated regions

Radioactive soil-contamination mapping and risk assessment is a vital issue for decision makers. Traditional approaches for mapping the spatial concentration of radionuclides employ various regression-based models, which usually provide a single-value prediction realization accompanied (in some cases) by estimation error. Such approaches do not provide the capability for rigorous uncertainty quantification or probabilistic mapping. Machine learning is a recent and fast-developing approach based on learning patterns and information from data. Artificial neural networks for prediction mapping have been especially powerful in combination with spatial statistics. A data-driven approach provides the opportunity to integrate additional relevant information about spatial phenomena into a prediction model for more accurate spatial estimates and associated uncertainty. Machine-learning algorithms can also be used for a wider spectrum of problems than before: classification, probability density estimation, and so forth. Stochastic simulations are used to model spatial variability and uncertainty. Unlike regression models, they provide multiple realizations of a particular spatial pattern that allow uncertainty and risk quantification. This paper reviews the most recent methods of spatial data analysis, prediction, and risk mapping, based on machine learning and stochastic simulations in comparison with more traditional regression models. The radioactive fallout from the Chernobyl Nuclear Power Plant accident is used to illustrate the application of the models for prediction and classification problems. This fallout is a unique case study that provides the challenging task of analyzing huge amounts of data ('hard' direct measurements, as well as supplementary information and expert estimates) and solving particular decision-oriented problems.

Enantioselective transformation of alpha-hexachlorocyclohexane by the dehydrochlorinases LinA1 and LinA2 from the soil bacterium Sphingomonas paucimobilis B90A.

Sphingomonas paucimobilis B90A contains two variants, LinA1 and LinA2, of a dehydrochlorinase that catalyzes the first and second steps in the metabolism of hexachlorocyclohexanes (R. Kumari, S. Subudhi, M. Suar, G. Dhingra, V. Raina, C. Dogra, S. Lal, J. R. van der Meer, C. Holliger, and R. Lal, Appl. Environ. Microbiol. 68:6021-6028, 2002). On the amino acid level, LinA1 and LinA2 were 88% identical to each other, and LinA2 was 100% identical to LinA of S. paucimobilis UT26. Incubation of chiral alpha-hexachlorocyclohexane (alpha-HCH) with Escherichia coli BL21 expressing functional LinA1 and LinA2 S-glutathione transferase fusion proteins showed that LinA1 preferentially converted the (+) enantiomer, whereas LinA2 preferred the (-) enantiomer. Concurrent formation and subsequent dissipation of beta-pentachlorocyclohexene enantiomers was also observed in these experiments, indicating that there was enantioselective formation and/or dissipation of these enantiomers. LinA1 preferentially formed (3S,4S,5R,6R)-1,3,4,5,6-pentachlorocyclohexene, and LinA2 preferentially formed (3R,4R,5S,6S)-1,3,4,5,6-pentachlorocyclohexene. Because enantioselectivity was not observed in incubations with whole cells of S. paucimobilis B90A, we concluded that LinA1 and LinA2 are equally active in this organism. The enantioselective transformation of chiral alpha-HCH by LinA1 and LinA2 provides the first evidence of the molecular basis for the changed enantiomer composition of alpha-HCH in many natural environments. Enantioselective degradation may be one of the key processes determining enantiomer composition, especially when strains that contain only one of the linA genes, such as S. paucimobilis UT26, prevail.