A population-based case-control study on social factors and risk of testicular germ cell tumours

Objectives Incidence rates for testicular cancer have risen over the last few decades. Findings of an association between the risk of testicular cancer and social factors are controversial. The association of testicular cancer and different indicators of social factors were examined in this study.<p></p> Design Case–control study.<p></p> Setting Population-based multicentre study in four German regions (city states Bremen and Hamburg, the Saarland region and the city of Essen).<p></p> Participants The study included 797 control participants and 266 participants newly diagnosed with testicular cancer of which 167 cases were classified as seminoma and 99 as non-seminoma. The age of study participants ranged from 15 to 69 years.<p></p> Methods Social position was classified by educational attainment level, posteducational training, occupational sectors according to Erikson-Goldthorpe-Portocarrero (EGP) and the socioeconomic status (SES) on the basis of the International SocioEconomic Index of occupational status (ISEI). ORs and corresponding 95% CIs (95% CIs) were calculated for the whole study sample and for seminoma and non-seminoma separately.<p></p> Results Testicular cancer risk was modestly increased among participants with an apprenticeship (OR=1.7 (95% CI 1.0 to 2.8)) or a university degree (OR=1.6 (95% CI 0.9 to 2.8)) relative to those whose education was limited to school. Analysis of occupational sectors revealed an excess risk for farmers and farm-related occupations. No clear trend was observed for the analyses according to the ISEI-scale.<p></p> Conclusions Social factors based on occupational measures were not a risk factor for testicular cancer in this study. The elevated risk in farmers and farm-related occupations warrants further research including analysis of occupational exposures.<p></p&gt

Emerging Trade Patterns in a 3-Region Linear NEG Model: Three Examples

This chapter draws attention to a specific feature of a NEG model that uses linear (and not iso-elastic) demand functions, namely its ability to account for zero trade. Thus, it represents a suitable framework to study how changes in parameters that are typical for NEG models, such as trade costs and regional market size, not only shape the regional distribution of economic activity, but at the same time determine the emergence of additional trade links between formerly autarkic regions. We survey some related papers and present a three-region framework that potentially nests many possible trade patterns. To focus the analysis, we study in more detail three specific trade patterns frequently found in the EU trade network. We start with three autarkic regions; then we introduce the possibility that two regions trade with each other; and, finally, we allow for one region trading with the other two, but the latter are still not trading with each other. We find a surprising plethora of long-run equilibria each involving a specific regional distribution of economic activity and a specific pattern of trade links. We show how a reduction in trade costs shapes simultaneously industry location and the configuration of the trade network

USP7 controls NGN3 stability and pancreatic endocrine lineage development

AbstractUnderstanding the factors and mechanisms involved in beta-cell development will guide therapeutic efforts to generate fully functional beta cells for diabetes. Neurogenin 3 (NGN3) is the key transcription factor that marks endocrine progenitors and drives beta-cell differentiation. Here we screen for binding partners of NGN3 and identify the deubiquitylating enzyme USP7 as a key regulator of NGN3 stability. Mechanistically, USP7 interacts with, deubiquitinates and stabilizes NGN3. In vivo, conditional knockout of Usp7 in the mouse embryonic pancreas causes a dramatic reduction in islet formation and hyperglycemia in adult mice, due to impaired NGN3-mediated endocrine specification during pancreatic development. Furthermore, pharmacological inhibition of USP7 during endocrine specification in human iPSC models of beta-cell differentiation decreases NGN3 expressing progenitor cell numbers and impairs beta cell differentiation. Thus, the USP7-NGN3 axis is an essential mechanism for driving endocrine development and beta-cell differentiation, which can be therapeutically exploited.</jats:p

A pulsed, mono-energetic and angular-selective UV photo-electron source for the commissioning of the KATRIN experiment

The KATRIN experiment aims to determine the neutrino mass scale with a sensitivity of 200 meV/c^2 (90% C.L.) by a precision measurement of the shape of the tritium $\beta$-spectrum in the endpoint region. The energy analysis of the decay electrons is achieved by a MAC-E filter spectrometer. To determine the transmission properties of the KATRIN main spectrometer, a mono-energetic and angular-selective electron source has been developed. In preparation for the second commissioning phase of the main spectrometer, a measurement phase was carried out at the KATRIN monitor spectrometer where the device was operated in a MAC-E filter setup for testing. The results of these measurements are compared with simulations using the particle-tracking software "Kassiopeia", which was developed in the KATRIN collaboration over recent years.Comment: 19 pages, 16 figures, submitted to European Physical Journal

Dreidimensionale Modellierung von organischem Kohlenstoff im Boden basierend auf multi-skaliger Reliefanalyse und Methoden des Data Minings in Jiangxi, VR China

Böden als endliche Ressource sind eine der wichtigsten und größten terrestrischen Speicher für Kohlenstoff (SOC). Die räumliche und tiefenbezogene Quantifizierung von SOC ermöglicht eine wesentlich bessere Beschreibung spezifischer Bodenfunktionen (z.B. Bodenqualität, Wasserrückhaltevermögen, Nährstoffkreislauf und -speicherung). Bisherige Modellierungen des SOC nutzen zumeist spezifische Tiefenstufen im zweidimensionalen Sinne, sodass Schichtmodelle eine quasi dreidimensionale, limitierte Abbildung ermöglichen. Wenige Ansätze der digitalen Bodenlandschaftsmodellierung, insbesondere in der Anwendung von Methoden des maschinellen Lernens, beschäftigen sich mit der Quantifizierung des SOC in Form von räumlich modellierten Tiefenfunktionen. Im Rahmen des in den feuchten Subtropen angesiedelten Biodiversitätsexperiments BEF China (FOR 891) wird in einem 40 ha großen heterogenen Einzugsgebiet, mit Hilfe unterschiedlicher nicht-linearer Verfahren (Random Forests [RF], Multiple Adaptive Regression Splines [MARS], Support Vector Machines [SVM]), eine sowohl räumliche, als auch tiefenbezogene Quantifizierung des Bodenkohlenstoffs getestet. Ausgangspunkt der Analyse sind 67 plot-bezogene Mischproben, die um weitere 90 punktbezogene Proben ergänzt wurden. An allen Standorten wurden 5 Tiefenstufen (0-5, 5-10, 10-20, 20-30, 30-40, 40-50 cm) beprobt. Die methodischen Arbeitsschritte gliedern sich in (i) Ableitung der beschreibenden Umweltparameter auf unterschiedlichen Skalen (290), (ii) Ableitung der Tiefenfunktionen mit Hilfe von Polynominalfunktionen 3. Grades, (iii) Räumliche Modellierung der Funktionsparameter und (iv) der Vergleich der Aussagekraft unterschiedlicher nicht-linearer Verfahren. Der Fehler (RMSE) der Tiefenfunktionen liegt zwischen 0.1 % und 0.17 % SOC, mit einem R² über 0.9. Die räumliche Modellierung der Funktionsparameter der plotbezogenen Proben mit SVM ist dabei mit einem mittleren R² von 0.32 besser als MARS (0.31) und RF (0.28). Gemittelt über alle Koeffizienten liegt der RMSE bei 0.22 (RF), 0.23 (SVM) und 0.25 (MARS). Die Modelle der punktbezogenen Proben erreichen im Mittel ein R² von 0.2, bzw. 0.35 im RMSE. Modelle, die beide Stichprobensätze kombinieren, sind dabei unsicherer (R²=0.14). Zum einen kann das am räumlichen Clustering der punktbezogenen Proben liegen, zum anderen vermuten wir, dass die Mittelwertbildung in den verschiedenen Beprobungsverfahren verschiedene Skalenniveaus abbildet und daher nicht ergänzend verwendet werden sollte

The ConMap approach for terrain-based digital soil mapping

We present a new digital terrain analysis framework for digital soil mapping, referred to as contextual elevation mapping (ConMap). In contrast to common regression approaches based on features from digital terrain analysis, ConMap is not based on standard terrain attributes, but on elevation differences from the centre pixel to each pixel in circular neighbourhoods only. These differences are used as features in random forest regressions. We applied and validated the framework by predicting topsoil silt content in a loess region of 1150 km2 in Rhineland-Palatinate and Hesse, Germany. Three hundred and forty-two samples and a 20-m resolution digital elevation model were used for this illustration and validation. We compared ConMap with standard and multi-scale terrain analysis approaches as well as with ordinary kriging interpolations. Cross-validation root mean square error (RMSE) decreased from 16.1 when the standard digital terrain analysis was used to 11.2 when ConMap was used. This corresponds to an increase in variance explained (R2) from 15 to 61%. Even though ordinary kriging out-performed standard terrain analysis as well, the variance explained was 6% smaller compared with that using ConMap. The results show that the geomorphic settings in the study area must have induced the spatial trend, which can be accounted for by ConMap over different scales. We conclude that ConMap shows great potential for digital soil mapping studies

Heterogeneous Catalysis under pressure - In-situ neutron diffraction under industrial conditions

The present work describes the application of a tubular reactor that allows in-situ neutron diffraction on working catalysts at high pressures. The designed reactor enables the application to a sample of industrially-relevant reaction conditions, i.e., in a temperature range up to 330° C and 60 bar pressure, coupled with online gas-analysis. Application of the cell is demonstrated by ammonia synthesis over a commercial catalyst with diffraction data obtained from the high-resolution powder diffractometer, Echidna, at the Australian Nuclear Science and Technology Organisation, ANSTO

Multi-scale digital soil mapping with deep learning

We compared different methods of multi-scale terrain feature construction and their relative effectiveness for digital soil mapping with a Deep Learning algorithm. The most common approach for multi-scale feature construction in DSM is to filter terrain attributes based on different neighborhood sizes, however results can be difficult to interpret because the approach is affected by outliers. Alternatively, one can derive the terrain attributes on decomposed elevation data, but the resulting maps can have artefacts rendering the approach undesirable. Here, we introduce ‘mixed scaling’ a new method that overcomes these issues and preserves the landscape features that are identifiable at different scales. The new method also extends the Gaussian pyramid by introducing additional intermediate scales. This minimizes the risk that the scales that are important for soil formation are not available in the model. In our extended implementation of the Gaussian pyramid, we tested four intermediate scales between any two consecutive octaves of the Gaussian pyramid and modelled the data with Deep Learning and Random Forests. We performed the experiments using three different datasets and show that mixed scaling with the extended Gaussian pyramid produced the best performing set of covariates and that modelling with Deep Learning produced the most accurate predictions, which on average were 4–7% more accurate compared to modelling with Random Forests

Chirp mitigation of plasma-accelerated beams using a modulated plasma density

Plasma-based accelerators offer the possibility to drive future compact light sources and high-energy physics applications. Achieving good beam quality, especially a small beam energy spread, is still one of the major challenges. For stable transport, the beam is located in the focusing region of the wakefield which covers only the slope of the accelerating field. This, however, imprints a longitudinal energy correlation (chirp) along the bunch. Here, we propose an alternating focusing scheme in the plasma to mitigate the development of this chirp and thus maintain a small energy spread