Geomodelling of a fluvial system with semi-supervised support vector regression

Fluvial deposits are a challenge for modelling flow in sub-surface reservoirs. Connectivity and continuity of permeable bodies have a major impact on fluid flow in porous media. Contemporary object-based and multipoint statistics methods face a problem of robust representation of connected structures. An alternative approach to model petrophysical properties is based on machine learning algorithm ? Support Vector Regression (SVR). Semi-supervised SVR is able to establish spatial connectivity taking into account the prior knowledge on natural similarities. SVR as a learning algorithm is robust to noise and captures dependencies from all available data. Semi-supervised SVR applied to a synthetic fluvial reservoir demonstrated robust results, which are well matched to the flow performance

Winter ecology of a female White-Backed Woodpecker Dendrocopos leucotos (Bechstein)

Summary

The prognostic value of semi-quantitative i-123 mibg scintigraphy at diagnosis in high risk neuroblastoma: validation of the siopen score method

Purpose: SIOPEN scoring of 123I mIBG imaging has been shown to predict response to induction chemotherapy and outcome at diagnosis in children with HRN.Method: Patterns of skeletal 123I mIBG uptake were assigned numerical scores (Mscore) ranging from 0 (no metastasis) to 72 (diffuse metastases) within 12 body areas as described previously. 271 anonymised, paired image data sets acquired at diagnosis and on completion of Rapid COJEC induction chemotherapy were reviewed, constituting a representative sample of 1602 children treated prospectively within the HR-NBL1/SIOPEN trial. Pre-and post-treatment Mscores were compared with bone marrow cytology (BM) and 3 year event free survival (EFS).Results: Results 224/271 patients showed skeletal MIBG-uptake at diagnosis and were evaluable forMIBG-response. Complete response (CR) on MIBG to Rapid COJEC induction was achieved by 66%, 34% and 15% of patients who had pre-treatment Mscores of <18 (n¼65, 29%), 18-44 (n¼95,42%) and Y ´ 45 (n¼64, 28.5%) respectively (chi squared test p<.0001). Mscore at diagnosis and on completion of Rapid COJEC correlated strongly with BM involvement (p<0.0001). The correlation of pre score with post scores and response was highly significant (p<0.001). Most importantly, the 3 year EFS in 47 children with Mscore 0 at diagnosis was 0.68 (A ` 0.07), by comparison with 0.42 (A` 0.06), 0.35 (A` 0.05) and 0.25 (A` 0.06) for patients in pre-treatment score groups <18, 18-44 and Y ´ 45, respectively (p<0.001). AnMscore threshold ofY ´ 45 at diagnosis was associated with significantly worse outcome by comparison with all other Mscore groups (p¼0.029). The 3 year EFS of 0.53 (A` 0.07) of patients in metastatic CR (mIBG and BM) after Rapid Cojec (33%) is clearly superior to patients not achieving metastatic CR (0.24 (A ` 0.04), p¼0.005).Conclusion: SIOPEN scoring of 123I mIBG imaging has been shown to predict response to induction chemotherapy and outcome at diagnosis in children with HRN.

Emission of nitrous oxide and carbon dioxide from semi-arid tropical soils in Chiapas México

The semi-arid region of Chiapas is dominated by N2 -fixing shrubs, e.g., Acacia angustissima. Urea-fertilized soil samples under maize were collected from areas covered and uncovered by A. angustissima in different seasons and N2O and CO2 emissions were monitored. The objective of this study was to determine the effects of urea and of the rainy and dry season on gas emissions from semi-arid soil under laboratory conditions. Urea and soil use had no effect on CO2 production. Nitrons oxide emission from soil was three times higher in the dry than in the rainy season, while urea fertilization doubled emissions. Emissions were twice as high from soil sampled under A. angustissima canopy than from arable land, but 1.2 lower than from soil sampled outside the canopy, and five times higher from soil incubated at 40 % of the water-holding capacity (WHC) than at soil moisture content, but 15 times lower than from soil incubated at 100 WHC. It was found that the soil sampling time and water content had a significant effect on N2O emissions, while N fertilizer and sampling location were less influent.