Ungewöhnliche Präsentation einer Sigmadivertikulitis

Zusammenfassung: Ein 68-jähriger Patient stellte sich mit gering ausgeprägten suprasymphysären Schmerzen, Makrohämaturie und Dysurie vor. In unserem Fall fehlten initial die typischen Leitsymptome einer sigmavesikalen Fistel. Aufgrund der Makrohämaturie und des Zystoskopiebefundes galt als Arbeitsdiagnose ein Blasentumor. Wegweisend war die kontrastmittelgestützte Computertomographie mit rektaler Kontrastmittelapplikation. Neben einer Sigmadivertikulitis ("fat stranding"/"centipede sign") konnte in der urographischen Phase ein Kontrastmittelübertritt vom Harnblasenlumen in den Harnblasenwandabszess und von hier in das Sigma detektiert werde

Anisotropic electrical resistivity of LaFeAsO: evidence for electronic nematicity

Single crystals of LaFeAsO were successfully grown out of KI flux. Temperature dependent electrical resistivity was measured with current flow along the basal plane, \rho_perpend(T), as well as with current flow along the crystallographic c-axis, \rho_parallel(T), the latter one utilizing electron beam lithography and argon ion beam milling. The anisotropy ratio was found to lie between \rho_parallel/\rho_perpend = 20 - 200. The measurement of \rho_perpend(T) was performed with current flow along the tetragonal [1 0 0] direction and along the [1 1 0] direction and revealed a clear in-plane anisotropy already at T \leq 175 K. This is significantly above the orthorhombic distortion at T_0 = 147 K and indicates the formation of an electron nematic phase. Magnetic susceptibility and electrical resistivity give evidence for a change of the magnetic structure of the iron atoms from antiferromagnetic to ferromagnetic arrangement along the c-axis at T^\ast = 11 K.Comment: 10 pages, 6 figures, minor change

Use of stable isotopes, organic and inorganic chemistry to identify pollution sources and weathering processes in two small tropical rivers in southwestern India

The two main objectives of this study were to assess pollution dynamic from organic and inorganic major ion chemistry and stable isotopes (δ15N and δ18O) and to determine the weathering processes using carbon isotopes in two tropical river basins, i.e. Nethravati and Swarna, along southwest coast of India. These short length river basins (around 100 km) are characterized by high annual rainfall, warm temperature, high runo" (~3300mm) draining Precambrian basement rocks composed of green-stones, granitic-gneiss, charnockite and meta sediments. Intense silicate weathering is induced by high runo" and warm temperature (Gurumurthy et al., 2012). In this study, stable isotopes (δ15N & δ18O)of organic molecules from sewage and agricultural effluents,and carbon isotopes (δ13C) of dissolved organic carbon (DOC) and dissolved inorganic carbon (DIC) were measured to trace agricultural and domestic pollution and to identify the sources of inorganic carbon and the nature of chemical weathering in these river basins. Carbon isotopes measured on DIC reveals sources of carbon into the river, such as carbonate/silicate weathering of rocks, mineralization of organic matter from C3/C4 plants, soil and atmospheric CO2. The nitrate and phosphate levels remain low, with values ranging from 5 to 9 μM, and 0 to 2 μM respectively. The δ13C DIC values range from =-9.03 +/- 0.99 for the Swarna basin to -8.08 +/-0.78 for the Nethravati basin. These values point to a mixing of carbonate and silicate weathering products with a dominance of C3 vegetation, prevalent in the Western Ghats. The DOC values for both river basins are very low and very close: 0.72 +/- 0.09 mg/L (Swarna river) and 0.62 +/-0.11 mg/L (Nethravati river). This indicates that the contributions of organic matter from the adjacent forests and the $ood plains are very low during the sampling period. The analysis of organic acids reveals low amount of Oxalate and Acetate, and trace of Malate and Tartaric acids. The dissolved and particulate organic carbon (DOC and POC) concentrations are very low in these two rivers. During the dry season, river discharge is mainly supplied by groundwater with generally low contents in dissolved and particulate fractions. Even if we observe low concentration, we measured higher DOC and POC in the Swarna river. These higher DOC concentrations are accompanied with lower SUVA value. This indicates that more labile DOC (less aromaticity) is exported within this basin during dry season. C/N values in POC also show that the organic carbon is “fresher” and is probably more autochtonous than in the Nethravati river. Indeed, C/N value are closer of an autochthonous production (C/N : 2-6) than allochthonous one (C/N: 8-20). These observations can be explained as the Svarna watershed land use is more agricultural than in Nethravati. Agricultural lands generally export signi%cant amount of nutrients to rivers and participate to enhance autochthonous productivity. Autochthonous organic carbon production is more labile and less aromatic

From adoption potential to transformative learning around Conservation Agriculture in Burkina Faso

Despite the substantial support of donors and development agencies, Conservation Agriculture (CA) has not moved from an invention to an innovation stage in sub-Saharan Africa. The results of the common strategy to transfer the technology from science through donors to farms in a top down manner have been disappointing (with Burkina Faso being a typical case). To make things worse, assessing the actual levels of adoption has been problematic due to the biases and weaknesses of the applied methods - including the Qualitative expert Assessment Tool for CA adoption in Africa (QAToCA). However, to promote sustainable farming pathways such as CA, we still see a need for methods that help to understand and foster transitions in agricultural practices. The purpose of this work is thus to design an approach that combines current insights in learning theory and practice. The starting point of the process is an assessment of the agro-ecosystem health of the farming system of interest, by exploring the social, economic and ecological characteristics of the system. Second, to create space for social learning, we apply participatory stakeholder mapping to make the roles, values, interests, and capabilities of the different stakeholders explicit. Third, the stakeholders jointly work on a historical timeline of CA promotion to identify key events, drivers and constraints of the innovation process. Then, to support individual experience, dialogue and different ways of learning, the stakeholders together create non-scripted, non-edited videos of their perspectives on challenges in the farming system. These videos are then screened in a multi-stakeholder meeting to stimulate the discussion on the innovation potential of CA. Discussions are structured by the framework of QAToCA. The results of all exercises feed into a proposal for an improved promotion of CA. We tested the approach in a farming community in Koumbia, Burkina Faso. The described learning elements helped to moderate the expert bias and rigidity of QAToCA. As a learning outcome, the results underlined that CA uptake will depend on the adaptation to the local conditions (e.g. competition over crop residue exacerbated by free-grazing) in order become a viable agricultural system

Spatio-temporal modelling of changes in air pollution exposure associated to the COVID-19 lockdown measures across Europe

The lockdown and related measures implemented by many European countries to stop the spread of the SARS-CoV-2 virus (COVID-19) pandemic have altered the economic activities and road transport in many cities. To rigorously evaluate how these measures have affected air quality in Europe, we developed Bayesian spatio-temporal (BST) models that assess changes in the surface nitrogen dioxide (NO2) and fine particulate matter (PM2.5) concentration across the continent. We fitted BST models to measurements of the two pollutants in 2020 using a lockdown indicator covariate, while accounting for the spatial and temporal correlation present in the data. Since other factors, such as weather conditions, local combustion sources and/or land surface characteristics may contribute to the variation of pollutant concentrations, we proposed two model formulations that allowed the differentiation between the variations in pollutant concentrations due to seasonality from the variations associated to the lockdown policies. The first model compares the changes in 2020, with the ones during the same period in the previous five years, by introducing an offset term, which controls for the long-term average concentrations of each pollutant during 2014-2019. The second approach models only the 2020 data, but adjusts for confounding factors. The results indicated that the latter can better capture the lockdown effect. The measures taken to tackle the virus in Europe reduced the average surface concentrations of NO2 and PM2.5 by 29.5% (95% Bayesian credible interval: 28.1%, 30.9%) and 25.9% (23.6%, 28.1%), respectively. To our knowledge, this research is the first to account for the spatio-temporal correlation present in the monitoring data during the pandemic and to assess how it affects estimation of the lockdown effect while accounting for confounding. The proposed methodology improves our understanding of the effect of COVID-19 lockdown policies on the air pollution burden across the continent