The 1945-1949 droughts in Switzerland

This paper studies the representation of a drought period that affected Central Europe from 1945 to 1949 in the “Twentieth Century Reanalysis” (20CR). We analysed temperature and precipitation fields in 20CR and compared them to other data products. From the monthly precipitation rate at a 20CR grid point in the Swiss Plateau, the Standardised Precipitation Index over six months (SPI6) was calculated and compared with the corresponding index calculated from station data. For additional analyses, 20CR soil moisture, run off, and evaporation data were used. 20CR well reproduces the temperature and precipitation anomalies over Central Europe during this period, although during 1947, the precipitation anomaly is shifted to the east as compared to observations. With respect to the SPI6 index, the agreement between 20CR and station data is good except again for 1947 (conversely, drought was overestimated in 20CR for 1945 and 1949). Low SPI values in 20CR are accompanied by negative soil moisture anomalies and a negative water balance. Thus, apart from the shift in the spatial drought pattern in 1947, the drought is depicted in a realistic way in 20CR.

Non-exponential return time distributions for vorticity extremes explained by fractional Poisson processes

Serial correlation of extreme midlatitude cyclones observed at the storm track exits is explained by deviations from a Poisson process. To model these deviations, we apply fractional Poisson processes (FPPs) to extreme midlatitude cyclones, which are defined by the 850 hPa relative vorticity of the ERA interim reanalysis during boreal winter (DJF) and summer (JJA) seasons. Extremes are defined by a 99% quantile threshold in the grid-point time series. In general, FPPs are based on long-term memory and lead to non-exponential return time distributions. The return times are described by a Weibull distribution to approximate the Mittag–Leffler function in the FPPs. The Weibull shape parameter yields a dispersion parameter that agrees with results found for midlatitude cyclones. The memory of the FPP, which is determined by detrended fluctuation analysis, provides an independent estimate for the shape parameter. Thus, the analysis exhibits a concise framework of the deviation from Poisson statistics (by a dispersion parameter), non-exponential return times and memory (correlation) on the basis of a single parameter. The results have potential implications for the predictability of extreme cyclones.

Swiss Alps Jungfrau Aletsch UNESCO World Heritage Site - The state of this World Heritage region as a starting point for regional monitoring

The UNESCO listing as World Heritage Site confirms the outstanding qualities of the high-mountain region around the Great Aletsch Glacier. The region of the World Heritage Site now faces the responsibility to make these qualities visible and to preserve them for future generations. Consequently the qualities of the site must not be regarded in isolation but in the context of the entire region with its dynamics and developments. Regional monitoring is the observation and evaluation of temporal changes in target variables. It is thus an obligation towards UNESCO, who demands regular reports about the state of the listed World Heritage assets. It also allows statements about sustainable regional development and can be the basis for early recognition of threats to the outstanding qualities. Monitoring programmes face three major challenges: first, great care must be taken in defining the target qualities to be monitored or the monitoring would remain vague. Secondly, the selection of ideal indicators to describe these qualities is impeded by inadequate data quality and availability, compromises are inevitable. Thirdly, there is always an element of insecurity in the interpretation of the results as to what influences and determines the changes in the target qualities. The first survey of the monitoring programme confirmed the exceptional qualities of the region and also highlighted problematic issues.

In vitro selection of Haemonchus contortus for benzimidazole resistance reveals a mutation at amino acid 198 of beta-tubulin

Benzimidazoles were the first broad-spectrum anthelmintics and are still in use today against gastro-intestinal nematodes of ruminants such as Haemonchus contortus. Benzimidazoles block the polymerization of nematode microtubules. However, their efficacy is jeopardized by the spread of drug-resistant parasites that carry point mutations in beta-tubulin. Here we use a novel in vitro selection-in vivo propagation protocol to breed drug-resistant H. contortus. After 8 generations of selection with thiabendazole an in vitro resistance factor of 1000 was reached that was also relevant in vivo in infected sheep. The same procedure carried out with ivermectin produced only a moderate resistance phenotype that was not apparent in sheep. Cloning and sequencing of the beta-tubulin genes from the thiabendazole-resistant H. contortus mutants revealed all of the isotype 1 alleles, and part of the isotype 2 alleles, to carry the mutation glutamate(198) to alanine (E198A). An allele-specific PCR was developed, which may be helpful in monitoring the prevalence of alanine(198) encoding alleles in the beta-tubulin isotype 1 gene pool of H. contortus in the field.

Fully automatic segmentation of AP pelvis X-rays via random forest regression with efficient feature selection and hierarchical sparse shape composition

In clinical practice, traditional X-ray radiography is widely used, and knowledge of landmarks and contours in anteroposterior (AP) pelvis X-rays is invaluable for computer aided diagnosis, hip surgery planning and image-guided interventions. This paper presents a fully automatic approach for landmark detection and shape segmentation of both pelvis and femur in conventional AP X-ray images. Our approach is based on the framework of landmark detection via Random Forest (RF) regression and shape regularization via hierarchical sparse shape composition. We propose a visual feature FL-HoG (Flexible- Level Histogram of Oriented Gradients) and a feature selection algorithm based on trace radio optimization to improve the robustness and the efficacy of RF-based landmark detection. The landmark detection result is then used in a hierarchical sparse shape composition framework for shape regularization. Finally, the extracted shape contour is fine-tuned by a post-processing step based on low level image features. The experimental results demonstrate that our feature selection algorithm reduces the feature dimension in a factor of 40 and improves both training and test efficiency. Further experiments conducted on 436 clinical AP pelvis X-rays show that our approach achieves an average point-to-curve error around 1.2 mm for femur and 1.9 mm for pelvis.

Performance of HBsAg point-of-care tests for detection of diagnostic escape-variants in clinical samples

BACKGROUND Hepatitis B viruses (HBV) harboring mutations in the a-determinant of the Hepatitis B surface antigen (HBsAg) are associated with reduced reactivity of HBsAg assays. OBJECTIVES To evaluate the sensitivity and specificity of three HBsAg point-of-care tests for the detection of HBsAg of viruses harboring HBsAg mutations. STUDY DESIGN A selection of 50 clinical plasma samples containing HBV with HBsAg mutations was used to evaluate the performance of three HBsAg point-of-care tests (Vikia(®), bioMérieux, Marcy-L'Étoile, France. Alere Determine HBsAg™, Iverness Biomedical Innovations, Köln, Germany. Quick Profile™, LumiQuick Diagnostics, California, USA) and compared to the ARCHITECT HBsAg Qualitative(®) assay (Abbott Laboratories, Sligo, Ireland). RESULTS The sensitivity of the point-of-care tests ranged from 98% to 100%. The only false-negative result occurred using the Quick Profile™ assay with a virus harboring a D144A mutation. CONCLUSIONS The evaluated point-of-care tests revealed an excellent sensitivity in detecting HBV samples harboring HBsAg mutations.

SOP: Parallel surrogate global optimization with Pareto center selection for computationally expensive single objective problems

This paper presents a parallel surrogate-based global optimization method for computationally expensive objective functions that is more effective for larger numbers of processors. To reach this goal, we integrated concepts from multi-objective optimization and tabu search into, single objective, surrogate optimization. Our proposed derivative-free algorithm, called SOP, uses non-dominated sorting of points for which the expensive function has been previously evaluated. The two objectives are the expensive function value of the point and the minimum distance of the point to previously evaluated points. Based on the results of non-dominated sorting, P points from the sorted fronts are selected as centers from which many candidate points are generated by random perturbations. Based on surrogate approximation, the best candidate point is subsequently selected for expensive evaluation for each of the P centers, with simultaneous computation on P processors. Centers that previously did not generate good solutions are tabu with a given tenure. We show almost sure convergence of this algorithm under some conditions. The performance of SOP is compared with two RBF based methods. The test results show that SOP is an efficient method that can reduce time required to find a good near optimal solution. In a number of cases the efficiency of SOP is so good that SOP with 8 processors found an accurate answer in less wall-clock time than the other algorithms did with 32 processors.