Parallelized Solution Method of the Three-dimensional Gravitational Potential on the Yin-Yang Grid

We present a new method for solving the three-dimensional gravitational potential of a density field on the Yin-Yang grid. Our algorithm is based on a multipole decomposition and completely symmetric with respect to the two Yin-Yang grid patches. It is particularly efficient on distributed-memory machines with a large number of compute tasks, because the amount of data being explicitly communicated is minimized. All operations are performed on the original grid without the need for interpolating data onto an auxiliary spherical mesh.Comment: 8 pages, 4 figures; two minor additions after refereeing; accepted by Ap

Social Innovations in the extended Lake Constance area – an overview of the current activities

In recent years the importance of social innovation for societies is rising. Therefore, the European Union realized, that political goals can be successfully achieved through social innovations.1 The concept is offering solutions for social challenges broadly based and in a variety of different fields Thus, the focus of this paper will be to identify social innovation activities in the Lake Constance area and the problems which are being solved through those activities. It will therefore provide a quantitative analysis of the identified projects including the main idea of the activity as well as information about the innovators. The key outcomes of this paper are, that social innovators are mainly focusing on current political challenges such as the refugee crisis. Problems which the society is already facing for a longer period of time, are less focused. It could further be identified, that the majority of social innovators are students or graduates. Also, most of the activities have their origin in bigger cities such as Stuttgart, Karlsruhe or Heidelberg

Mapping the fractional coverage of the invasive shrub Ulex europaeus with multi-temporal Sentinel-2 imagery utilizing UAV orthoimages and a new spatial optimization approach

Mapping the occurrence patterns of invasive plant species and understanding their invasion dynamics is a crucial requirement for preventing further spread to so far unaffected regions. An established approach to map invasive species across large areas is based on the combination of satellite or aerial remote sensing data with ground truth data from fieldwork. Unmanned aerial vehicles (UAV, also referred to as unmanned aerial systems (UAS)) may represent an interesting and low-cost alternative to labor-intensive fieldwork. Despite the increasing use of UAVs in the field of remote sensing in the last years, operational methods to combine UAV and satellite data are still sparse. Here, we present a new methodological framework to estimate the fractional coverage (FC%) of the invasive shrub species Ulex europaeus (common gorse) on Chilo´e Island (south-central Chile), based on ultrahigh- resolution UAV images and a medium resolution intra-annual time-series of Sentinel-2. Our framework is based on three steps: 1) Land cover classification of the UAV orthoimages, 2) reduce the spatial shift between UAV-based land cover classification maps and Sentinel-2 imagery and 3) identify optimal satellite acquisition dates for estimating the actual distribution of Ulex europaeus. In Step 2 we translate the challenging co-registration task between two datasets with very different spatial resolutions into an (machine learning) optimization problem where the UAV-based land cover classification maps obtained in Step 1 are systematically shifted against the satellite images. Based on several Random Forest (RF) models, an optimal fit between varying land cover fractions and the spectral information of Sentinel-2 is identified to correct the spatial offset between both datasets. Considering the spatial shifts of the UAV orthoimages and using optimally timed Sentinel-2 acquisitions led to a significant improvement for the estimation of the current distribution of Ulex europaeus. Furthermore, we found that the Sentinel-2 acquisition from November (flowering time of Ulex europaeus) was particularly important in distinguishing Ulex europaeus from other plant species. Our mapping results could support local efforts in controlling Ulex europaeus. Furthermore, the proposed workflow should be transferable to other use cases where individual target species that are visually detectable in UAV imagery are considered. These findings confirm and underline the great potential of UAV-based groundtruth data for detecting invasive species

Combining remote sensing, habitat suitability models and cellular automata to model the spread of the invasive shrub Ulex europaeus

Modeling the past or future spread patterns of invasive plant species is challenging and in an ideal case requires multi-temporal and spatially explicit data on the occurrences of the target species as well as information on the habitat suitability of the areas at risk of being invaded. Most studies either focus on modeling the habitat suitability of a given area for an invasive species or try to model the spreading behavior of an invasive species based on temporally or spatially limited occurrence data and some environmental variables. Here we suggest a workflow that combines habitat suitability maps, occurrence data from multiple time steps collected from remote sensing data, and cellular automata models to first reconstruct the spreading patterns of the invasive shrub Ulex europaeus on the island Chiloé in Chile and then make predictions for the future spread of the species. First, U. europaeus occurrences are derived for four time steps between 1988 and 2020 using remote sensing data and a supervised classification. The resulting occurrence data is combined with occurrence data of the native range of U. europaeus from the GBIF database and selected environmental variables to derive habitat suitability maps using Maxent. Then, cellular automata models are calibrated using the occurrence estimates of the four time steps, the suitability map, and some additional geo-layer containing information about soils and human infrastructure. Finally, a set of calibrated cellular automata models are used to predict the potential spread of U. europaeus for the years 2070 and 2100 using climate scenarios. All individual steps of the workflow where reference data was available led to sufficient results (supervised classifications Overall Accuracy > 0.97; Maxent AUC > 0.85; cellular automata Balanced Accuracy > 0.91) and the spatial patterns of the derived maps matched the experiences collected during the field surveys. Our model predictions suggest a continuous expansion of the maximal potential range of U. europaeus, particularly in the Eastern and Northern part of Chiloé Island. We deem the suggested workflow to be a good solution to combine the static habitat suitability information—representing the environmental constraints—with a temporally and spatially dynamic model representing the actual spreading behavior of the invasive species. The obtained understanding of spreading patterns and the information on areas identified to have a high invasion probability in the future can support land managers to plan prevention and mitigation measures

Ground-based imaging remote sensing of ice clouds: uncertainties caused by sensor, method and atmosphere

In this study a method is introduced for the retrieval of optical thickness and effective particle size of ice clouds over a wide range of optical thickness from ground-based transmitted radiance measurements. Low optical thickness of cirrus clouds and their complex microphysics present a challenge for cloud remote sensing. In transmittance, the relationship between optical depth and radiance is ambiguous. To resolve this ambiguity the retrieval utilizes the spectral slope of radiance between 485 and 560aEuro-nm in addition to the commonly employed combination of a visible and a short-wave infrared wavelength. An extensive test of retrieval sensitivity was conducted using synthetic test spectra in which all parameters introducing uncertainty into the retrieval were varied systematically: ice crystal habit and aerosol properties, instrument noise, calibration uncertainty and the interpolation in the lookup table required by the retrieval process. The most important source of errors identified are uncertainties due to habit assumption: Averaged over all test spectra, systematic biases in the effective radius retrieval of several micrometre can arise. The statistical uncertainties of any individual retrieval can easily exceed 10aEuro-A mu m. Optical thickness biases are mostly below 1, while statistical uncertainties are in the range of 1 to 2.5. For demonstration and comparison to satellite data the retrieval is applied to observations by the Munich hyperspectral imager specMACS (spectrometer of the Munich Aerosol and Cloud Scanner) at the Schneefernerhaus observatory (2650aEuro-maEuro-a.s.l.) during the ACRIDICON-Zugspitze campaign in September and October 2012. Results are compared to MODIS and SEVIRI satellite-based cirrus retrievals (ACRIDICON - Aerosol, Cloud, Precipitation, and Radiation Interactions and Dynamics of Convective Cloud Systems;MODIS - Moderate Resolution Imaging Spectroradiometer;SEVIRI - Spinning Enhanced Visible and Infrared Imager). Considering the identified uncertainties for our ground-based approach and for the satellite retrievals, the comparison shows good agreement within the range of natural variability of the cloud situation in the direct surrounding

Evaluation of convective cloud microphysics in numerical weather prediction models with dual-wavelength polarimetric radar observations: methods and examples

The representation of cloud microphysical processes contributes substantially to the uncertainty of numerical weather simulations. In part, this is owed to some fundamental knowledge gaps in the underlying processes due to the difficulty of observing them directly. On the path to closing these gaps, we present a setup for the systematic characterization of differences between numerical weather model and radar observations for convective weather situations. Radar observations are introduced which provide targeted dual-wavelength and polarimetric measurements of convective clouds with the potential to provide more detailed information about hydrometeor shapes and sizes. A convection-permitting regional weather model setup is established using five different microphysics schemes (double-moment, spectral bin ("Fast Spectral Bin Microphysics", FSBM), and particle property prediction (P3)). Observations are compared to hindcasts which are created with a polarimetric radar forward simulator for all measurement days. A cell-tracking algorithm applied to radar and model data facilitates comparison on a cell object basis. Statistical comparisons of radar observations and numerical weather model runs are presented on a data set of 30 convection days. In general, simulations show too few weak and small-scale convective cells. Contoured frequency by altitude diagrams of radar signatures reveal deviations between the schemes and observations in ice and liquid phase. Apart from the P3 scheme, high reflectivities in the ice phase are simulated too frequently. Dual-wavelength signatures demonstrate issues of most schemes to correctly represent ice particle size distributions, producing too large or too dense graupel particles. Comparison of polarimetric radar signatures reveals issues of all schemes except the FSBM to correctly represent rain particle size distributions

Laser Powder Bed Fusion Processing of Fe-Mn-Al-Ni Shape Memory Alloy - On the Effect of Elevated Platform Temperatures

In order to overcome constraints related to crack formation during additive processing (laser powder bed fusion, L-BPF) of Fe-Mn-Al-Ni, the potential of high-temperature L-PBF processing was investigated in the present study. The effect of the process parameters on crack formation, grain structure, and phase distribution in the as-built condition, as well as in the course of cyclic heat treatment was examined by microstructural analysis. Optimized processing parameters were applied to fabricate cylindrical samples featuring a crack-free and columnar grained microstructure. In the course of cyclic heat treatment, abnormal grain growth (AGG) sets in, eventually promoting the evolution of a bamboo like microstructure. Testing under tensile load revealed a well-defined stress plateau and reversible strains of up to 4%

Handling software upgradeability problems with MILP solvers

Upgradeability problems are a critical issue in modern operating systems. The problem consists in finding the "best" solution according to some criteria, to install, remove or upgrade packages in a given installation. This is a difficult problem: the complexity of the upgradeability problem is NP complete and modern OS contain a huge number of packages (often more than 20 000 packages in a Linux distribution). Moreover, several optimisation criteria have to be considered, e.g., stability, memory efficiency, network efficiency. In this paper we investigate the capabilities of MILP solvers to handle this problem. We show that MILP solvers are very efficient when the resolution is based on a linear combination of the criteria. Experiments done on real benchmarks show that the best MILP solvers outperform CP solvers and that they are significantly better than Pseudo Boolean solvers.Comment: In Proceedings LoCoCo 2010, arXiv:1007.083

Deconvoluting lung evolution: from phenotypes to gene regulatory networks

Speakers in this symposium presented examples of respiratory regulation that broadly illustrate principles of evolution from whole organ to genes. The swim bladder and lungs of aquatic and terrestrial organisms arose independently from a common primordial "respiratory pharynx” but not from each other. Pathways of lung evolution are similar between crocodiles and birds but a low compliance of mammalian lung may have driven the development of the diaphragm to permit lung inflation during inspiration. To meet the high oxygen demands of flight, bird lungs have evolved separate gas exchange and pump components to achieve unidirectional ventilation and minimize dead space. The process of "screening” (removal of oxygen from inspired air prior to entering the terminal units) reduces effective alveolar oxygen tension and potentially explains why nonathletic large mammals possess greater pulmonary diffusing capacities than required by their oxygen consumption. The "primitive” central admixture of oxygenated and deoxygenated blood in the incompletely divided reptilian heart is actually co-regulated with other autonomic cardiopulmonary responses to provide flexible control of arterial oxygen tension independent of ventilation as well as a unique mechanism for adjusting metabolic rate. Some of the most ancient oxygen-sensing molecules, i.e., hypoxia-inducible factor-1alpha and erythropoietin, are up-regulated during mammalian lung development and growth under apparently normoxic conditions, suggesting functional evolution. Normal alveolarization requires pleiotropic growth factors acting via highly conserved cell-cell signal transduction, e.g., parathyroid hormone-related protein transducing at least partly through the Wingless/int pathway. The latter regulates morphogenesis from nematode to mammal. If there is commonality among these diverse respiratory processes, it is that all levels of organization, from molecular signaling to structure to function, co-evolve progressively, and optimize an existing gas-exchange framewor

Stärkung der Wettbewerbsfähigkeit der ökologischen Ferkelerzeugung in Bayern - ein interdisziplinäres Projekt

Die Wettbewerbsfähigkeit der für Süddeutschland typischen, bäuerlichen Ferkelerzeugung ist im ökologischen Landbau bisher gering. Dadurch besteht ein Umstellungshemmnis, das die weitere Entwicklung der Schweinhaltung im Ökolandbau behindert. Das vorgestellte interdisziplinäre Projekt soll mithilfe einer engen Zusammenarbeit von Forschung, Beratung und Praxis einen wesentlichen Beitrag zur Verbesserung der Produktionsbedingungen liefern. Ziel ist es, Grundlagen für eine Erhöhung von Leistung und Wertschöpfung in der ökologischen Ferkelerzeugung zu erarbeiten. Dies geschieht durch eine Verbesserung des Stands des Wissens über geeignete Haltungsverfahren, Stallbaulösungen, Arbeitsorganisation, Prozessqualität und Betriebswirtschaft. An dem Projekt sind sieben Arbeitsgruppen und elf Praxisbetriebe beteiligt. Das Projekt startete im Juli 2008 und wird voraussichtlich Ende 2010 abgeschlossen werden