Spatial Smoothing Techniques for the Assessment of Habitat Suitability

Precise knowledge about factors influencing the habitat suitability of a certain species forms the basis for the implementation of effective programs to conserve biological diversity. Such knowledge is frequently gathered from studies relating abundance data to a set of influential variables in a regression setup. In particular, generalised linear models are used to analyse binary presence/absence data or counts of a certain species at locations within an observation area. However, one of the key assumptions of generalised linear models, the independence of the observations is often violated in practice since the points at which the observations are collected are spatially aligned. While several approaches have been developed to analyse and account for spatial correlation in regression models with normally distributed responses, far less work has been done in the context of generalised linear models. In this paper, we describe a general framework for semiparametric spatial generalised linear models that allows for the routine analysis of non-normal spatially aligned regression data. The approach is utilised for the analysis of a data set of synthetic bird species in beech forests, revealing that ignorance of spatial dependence actually may lead to false conclusions in a number of situations

Total N difference method and 15N isotope dilution methode - A comparative study on N-fixation

In the study, the 15N fixation of a number of green manure crops were studied using either the 15N dilution technique, or the simple total N difference method. The results of the two methods were not very different, and the total N difference method seemed to give as good results as the more complicated and expencive 15N dillution method

Quantification of Cell Subpopulations, Fractions of Dead Cells and Debris in Cell Suspensions by Laser Diffractometry

Laser diffractometry was employed for size analysis in liver cell and blood cell suspensions to assess its suitability for characterizing cell populations. The method proved sensitive to detect subpopulations in liver cells (bimodal or trimodal distributions) and to quantify their volume fractions. Cell debris and aggregates of cells could also be quantified, dead cell populations recognized by their shift in the mean cell diameter. Laser diffractometry is therefore suitable for determining the quality of cell isolations (e.g. by liver perfusion) or for following alterations in cell populations during culture of cells in suspension. Analysis of human blood allowed differenciations to be made between thrombocytes and other blood cells. No peak separation was obtained for the populations of erythrocytes and granulocytes due to their similarity in size. Monocytes could not be detected due to their extremely low number in the blood indicating the limit of the metho

Rare Earths and the Balance Problem: How to Deal with Changing Markets?

The balance between the market demand and the natural abundance of the rare-earth elements (REEs) in ores, often referred to as the Balance Problem (or the Balancing Problem), is a major issue for REE suppliers. The ideal situation is a perfect match between the market demand for and the production of REEs, so that there are no surpluses of any of the REEs. This means that the rare-earth industry must find new uses for REEs that are available in excess and search for substitutes for REEs that have either limited availability or are high in demand. We present an overview of the trends in the applications for the different REEs and show that the demand for REEs for use in magnets, catalysts, and alloys is still increasing, while the application of REEs in polishing agents, glass, and ceramics are stable. On the other hand, the use of REEs in nickel–metal-hydride (NiMH) batteries and lamp phosphors is decreasing. These changes in the REE market have an influence on the Balance Problem, because the REEs that can be recycled from fluorescent lamps, cathode-ray tubes (CRTs), and NiMH batteries have to be at least partly reused in other applications. Magnesium and aluminum alloys offer an opportunity to mitigate the Balance Problem caused by these changes in the REE market. This is illustrated for REEs that can be recycled from fluorescent-lamp phosphor waste, CRT phosphors, and NiMH batteries. At present, five REEs (Nd, Eu, Tb, Dy, and Y) are being considered as very critical by Europe, the United States, and Japan, but we forecast that in the medium term, only neodymium will remain a critical REE. This paper discusses the relationship between criticality and the Balance Problem and shows how this relationship influences the market for specific REEs.This work has received funding from the European Union’s Horizon 2020 research and innovation programme under Grant Agreement No 680629 (REMAGHIC: New Recovery Processes to produce Rare Earth-Magnesium Alloys of High Performance and Low Cost) (project website: http://www.remaghic-project. eu). KB and PTJ acknowledge funding from the European Community’s Seventh Framework Programme ([FP7/2007–2013]) under Grant Agreement No. 607411 (MC-ITN EREAN: European Rare Earth Magnet Recycling Network) (project website of EREAN: http:// www.erean.eu). Paul McGuiness (Sciencewriter.si, Slovenia) is acknowledged for the drawing of the figures

Automated sample preparation for streamlined proteomic profiling of clinical specimens

The genetic information of all life is encoded within DNA molecules that are translated into functional entities, so-called proteins. They are responsible for operating and controlling a vast array of molecular mechanisms in any biological system and ubiquitous in (patho)physiology as a result. Besides, proteins are the primary target of drugs and can have a central role as biomarkers for diagnostic, prognostic, or predictive purposes. Here, many regulatory mechanisms and spatiotemporal influences prevent an accurate prediction of a proteins’ abundance and its associated functionality based on the genome information alone. Nowadays, it has become possible to measure and quantify thousands of proteins simultaneously, however, involving comprehensive sample preparation procedures. Currently, no universally standardized method enables a routine application of proteome profiling in a clinical environment. In this thesis, an automated workflow for the efficient processing of the most common and quantity-limited specimens is described. In order to demonstrate the usefulness of the end-to- end pipeline, which was termed autoSP3, it was applied to the proteome profiling of histologically defined and WHO recognized growth patterns of pulmonary adenocarcinoma (ADC) that currently have a limited clinical implication. Secondly, we investigated the proteome composition of a molecularly well-defined cohort of Ependymoma (EPN) pediatric brain tumors. Despite the availability of substantial NGS data and their ability to differentiate nine distinct subgroups, the majority of tumors remained without a functional insight. Here, the proteome profiling could provide a missing link and emphasize several subgroup-specific protein targets. In summary, this thesis describes the optimization of SP3 and its automation into a robust and cost-efficient pipeline for quantity-limited sample preparation and biological insight into the proteome composition of ADC growth patterns and EPN tumor subgroups

Dynamic system classifier

Stochastic differential equations describe well many physical, biological and sociological systems, despite the simplification often made in their derivation. Here the usage of simple stochastic differential equations to characterize and classify complex dynamical systems is proposed within a Bayesian framework. To this end, we develop a dynamic system classifier (DSC). The DSC first abstracts training data of a system in terms of time dependent coefficients of the descriptive stochastic differential equation. Thereby the DSC identifies unique correlation structures within the training data. For definiteness we restrict the presentation of DSC to oscillation processes with a time dependent frequency {\omega}(t) and damping factor {\gamma}(t). Although real systems might be more complex, this simple oscillator captures many characteristic features. The {\omega} and {\gamma} timelines represent the abstract system characterization and permit the construction of efficient signal classifiers. Numerical experiments show that such classifiers perform well even in the low signal-to-noise regime.Comment: 11 pages, 8 figure

Catch Crops in Organic Farming Systems without Livestock Husbandry - Simulations with the DAISY model

This paper presents simulations of the soil-plant-atmosphere model DAISY based on an organic crop rotation with incorporation of different catch crops following pea as a leguminous cash crop. Special emphasise was put on the simulation of N-mineralisation/-immobilisation and of soil microbial biomass N. The DAISY model was able to simulate soil mineral N and soil microbial biomass N after soil incorporation of catch crop plant residues to some extend. Several processes need further attention and may be integrated into the DAISY model: (1) soil tillage induced mobilisation of organic material including considerable amounts of organic N, (2) winter killing of sensitive plant species and varieties, (3) decomposition of plant residues at the soil surface as occurring after winter killing, (4) decomposition of easily decomposable plant residues at low temperatures, (5) soil microbial residues as an organic pool temporarily protected against turnover. Furthermore, reliable criteria for the subdivision of green plant residues into an easily decomposable pool and a more recalcitrant pool have to be developed

A Near-Surface Layer Heat Treatment of Die Casting Dies by Means of Electron-Beam Technology

Increasing the service life of die casting dies is an important goal of the foundry industry. Approaches are either material- or process-related. Despite new material concepts, hot work steels such as H11 are still predominantly used in the uncoated condition for die casting dies. In order to withstand the stresses that occur, this steel is used exclusively in the quenched and tempered condition. Required properties such as high high-temperature strength and high hardness combined with high toughness are, in principle, contradictory and can only be adjusted consistently over the entire die by furnace-based heat treatment. However, the results of various investigations have shown that improvements in the thermal shock resistance and wear resistance of hot work tool steels can be achieved by thermally influencing the microstructure near the surface. Based on these studies and related findings, an approach to surface heat treatment using the electron beam was developed. Due to the particle character of the radiation and the associated possibility of high-frequency beam deflection, the electron beam offers significantly greater flexibility in energy input into the workpiece surface compared with lasers or induction. The overall technological concept envisages replacing furnace-based heat treatment in the production of casting dies by localized and demand-oriented boundary layer heat treatment with the electron beam. The experiments include, on the one hand, the experimental determination of a suitable temperature–time interval with a focus on short-term austenitization. On the other hand, a simulation-based approach of boundary layer heat treatment with validation of a suitable heat source is investigated. Regarding short-term austenitization, the corresponding temperature and time range could be narrowed down more precisely. Some of these parameter combinations seem to be very suitable for practical use. The test specimens show a hard surface layer with a depth of at least up to 6 mm and a very tough buffer layer. Numerical simulation is used to estimate the resulting metallurgical microstructure and the achievable hardness as a function of the temperature–time interval. In addition, the results provided show the possibility of determining and optimizing the material properties by means of a simulation-based approach within the framework of a purely digital process planning and subsequently transferring them into a process planning. In the technical implementation, a temperature control was first established by means of a two-color pyrometer. In the further course of research, the pyrometer will be supplemented by an internally installed infrared camera, which will allow the reproducible setting of specified temperature profiles even for complex, large-area contours in the future