Die Juden einst und jetzt : ein Beitr. zur Lösung d. "Judenfrage"

von Emil Lehmann

Die Reformation und der Talmud : Vortr., geh. am 5. Dez. im Verein f. jüd. Geschichte u. Litteratur zu Aachen

von [Ludwig] Schuster

Projected pH reductions by 2100 might put deep North Atlantic biodiversity at risk

This study aims to evaluate the potential for impacts of ocean acidification on North Atlantic deep-sea ecosystems in response to IPCC AR5 Representative Concentration Pathways (RCPs). Deep-sea biota is likely highly vulnerable to changes in seawater chemistry and sensitive to moderate excursions in pH. Here we show, from seven fully coupled Earth system models, that for three out of four RCPs over 17% of the seafloor area below 500 m depth in the North Atlantic sector will experience pH reductions exceeding −0.2 units by 2100. Increased stratification in response to climate change partially alleviates the impact of ocean acidification on deep benthic environments. We report on major pH reductions over the deep North Atlantic seafloor (depth >500 m) and at important deep-sea features, such as seamounts and canyons. By 2100, and under the high CO2 scenario RCP8.5, pH reductions exceeding −0.2 (−0.3) units are projected in close to 23% (~15%) of North Atlantic deep-sea canyons and ~8% (3%) of seamounts – including seamounts proposed as sites of marine protected areas. The spatial pattern of impacts reflects the depth of the pH perturbation and does not scale linearly with atmospheric CO2 concentration. Impacts may cause negative changes of the same magnitude or exceeding the current target of 10% of preservation of marine biomes set by the convention on biological diversity, implying that ocean acidification may offset benefits from conservation/management strategies relying on the regulation of resource exploitation.

SNPs for parentage testing and traceability in globally diverse breeds of sheep

DNA-based parentage determination accelerates genetic improvement in sheep by increasing pedigree accuracy. Single nucleotide polymorphism (SNP) markers can be used for determining parentage and to provide unique molecular identifiers for tracing sheep products to their source. However, the utility of a particular "parentage SNP" varies by breed depending on its minor allele frequency (MAF) and its sequence context. Our aims were to identify parentage SNPs with exceptional qualities for use in globally diverse breeds and to develop a subset for use in North American sheep. Starting with genotypes from 2,915 sheep and 74 breed groups provided by the International Sheep Genomics Consortium (ISGC), we analyzed 47,693 autosomal SNPs by multiple criteria and selected 163 with desirable properties for parentage testing. On average, each of the 163 SNPs was highly informative (MAF≥0.3) in 48±5 breed groups. Nearby polymorphisms that could otherwise confound genetic testing were identified by whole genome and Sanger sequencing of 166 sheep from 54 breed groups. A genetic test with 109 of the 163 parentage SNPs was developed for matrix-assisted laser desorption/ionization-time-of-flight mass spectrometry. The scoring rates and accuracies for these 109 SNPs were greater than 99% in a panel of North American sheep. In a blinded set of 96 families (sire, dam, and non-identical twin lambs), each parent of every lamb was identified without using the other parent's genotype. In 74 ISGC breed groups, the median estimates for probability of a coincidental match between two animals (PI), and the fraction of potential adults excluded from parentage (PE) were 1.1×10(-39) and 0.999987, respectively, for the 109 SNPs combined. The availability of a well-characterized set of 163 parentage SNPs facilitates the development of high-throughput genetic technologies for implementing accurate and economical parentage testing and traceability in many of the world's sheep breeds.

Der polnische Resident Berend Lehmann, der Stammvater der israelitischen Religionsgemeinde zu Dresden

von Emil Lehmann

Green Wireless-Energy Efficiency in Wireless Networks

Wireless networks have become more and more popular because of ease of installation, ease of access, and support of smart terminals and gadgets on the move. In the overall life cycle of providing green wireless technology, from production to operation and, finally, removal, this chapter focuses on the operation phase and summarizes insights in energy consumption of major technologies. The chapter also focuses on the edge of the network, comprising network access points (APs) and mobile user devices. It discusses particularities of most important wireless networking technologies: wireless access networks including 3G/LTE and wireless mesh networks (WMNs); wireless sensor networks (WSNs); and ad-hoc and opportunistic networks. Concerning energy efficiency, the chapter discusses challenges in access, wireless sensor, and ad-hoc and opportunistic networks.

Belowground herbivore tolerance involves delayed overcompensatory root regrowth in maize

Plants can tolerate leaf-herbivore attack through metabolic reconfigurations that allow for the rapid regrowth of lost leaves. Several studies indicate that root-attacked plants can re-allocate resources to the aboveground parts. However, the connection between tolerance and root regrowth remains poorly understood. We investigated the timing and extent of root regrowth of tolerant and susceptible lines of maize, Zea mays L. (Poaceae), attacked by the western corn rootworm, Diabrotica virgifera virgifera LeConte (Coleoptera: Chrysomelidae), in the laboratory and the field. Infested tolerant maize plants produced more root biomass and even overcompensated for the lost roots, whereas this effect was absent in susceptible lines. Furthermore, the tolerant plants slowed growth of new roots in the greenhouse and in the field 4–8 days after infestation, whereas susceptible plants slowed growth of new roots only in the field and only after 12 days of infestation. The quick response of tolerant lines may have enabled them to escape root attack by starving the herbivores and by saving resources for regrowth after the attack had ceased. We conclude that both timing and the extent of regrowth may determine plant tolerance to root herbivory.

Fast Prediction of Femoral Biomechanics Using Supervised Machine Learning and Statistical Shape Modeling

Finite element (FE) analysis is an important computational tool in biomechanics. However, its adoption into clinical practice has been hampered by its computational complexity and required high technical competences for clinicians. In this paper we propose a supervised learning approach to predict the outcome of the FE analysis. We demonstrate our approach on clinical CT and X-ray femur images for FE predictions ( FEP), with features extracted, respectively, from a statistical shape model and from 2D-based morphometric and density information. Using leave-one-out experiments and sensitivity analysis, comprising a database of 89 clinical cases, our method is capable of predicting the distribution of stress values for a walking loading condition with an average correlation coefficient of 0.984 and 0.976, for CT and X-ray images, respectively. These findings suggest that supervised learning approaches have the potential to leverage the clinical integration of mechanical simulations for the treatment of musculoskeletal conditions.