Weihnachtskaktus - Schlumbergera (Cactaceae)

Pflanzenporträt

Urban soils in the Ruhr Area

Die räumliche Konzentration menschlichen Wirkens im städtischen Raum führt seit jeher zu Veränderungen der Böden. Im Ruhrgebiet bewirkte vor allem die montan-industrielle Vergangenheit tiefgreifende Veränderungen, weshalb die heutigen Böden sich z. T. stark von den ursprünglichen natürlichen Bodenverhältnissen unterscheiden. Einige der neu entstandenen Böden finden in Europa keine natürlichen Äquivalente und bilden einzigartige Standorte. Auch wenn das eigentliche Merkmal städtischer Böden ihre gegenüber den natürlichen Verhältnissen erhöhte Diversität ist, lassen sich häufig anzutreffende Charakteristika wie erhöhte Skelettgehalte, pH-Werte und Schadstoffgehalte sowie Verdichtungen und Versiegelungen feststellen. Nicht zuletzt aufgrund der vielfältigen Einflussfaktoren auf die Bodenentwicklung hat sich im deutschen Sprachgebrauch nur teilweise eine eindeutige und einheitliche (verbindliche) Klassifikation durchgesetzt, sodass mehrere Ansätze und Nomenklaturen existieren. Zu den ruhrgebietstypischen Böden zählen etwa die Böden auf Bergematerial des Steinkohlenbergbaus, die Böden auf Hochofenschlacken oder die Böden auf brachliegenden Bahngleisen. Sie bilden z. T. extreme Pflanzenstandorte und unterscheiden sich stark voneinander, wie es beispielsweise der Gegensatz zwischen dem sehr sauren Bergematerial und den stark alkalischen Schlacken verdeutlicht. Diese Diversität wirkt sich auch entsprechend auf die Pflanzenartenvielfalt im urbanen Raum aus. Zudem speichern Stadtböden Informationen zu vergangenen Umweltzuständen und zur Entwicklung der Städte, die von archäologischer und siedlungsgeschichtlicher Bedeutung sind.The urban-industrial history of the Ruhr Area caused significant alteration of soils. Therefore, the characteristics of urban soils differ in many ways from the natural soils. This paper provides information about general soil properties in the urban environment. Soil development and soil characteristics on typical sites and substrates frequently found in the Ruhr Area are described in more detail. Urban-specific soil types and their German nomenclature and classification are summarized. Furthermore, the role of urban soils as archives of settlement development and the relationships between soil and vegetation are examined

An Ins(1,4,5)P3 receptor in Paramecium is associated with the osmoregulatory system

In the ciliate Paramecium, a variety of well characterized processes are regulated by Ca2+, e.g. exocytosis, endocytosis and ciliary beat. Therefore, among protozoa, Paramecium is considered a model organism for Ca2+ signaling, although the molecular identity of the channels responsible for the Ca2+ signals remains largely unknown. We have cloned - for the first time in a protozoan - the full sequence of the gene encoding a putative inositol (1,4,5)-trisphosphate (Ins(1,4,5)P3) receptor from Paramecium tetraurelia cells showing molecular characteristics of higher eukaryotic cells. The homologously expressed Ins(1,4,5)P3-binding domain binds [3H]Ins(1,4,5)P3, whereas antibodies unexpectedly localize this protein to the osmoregulatory system. The level of Ins(1,4,5)P3-receptor expression was reduced, as shown on a transcriptional level and by immuno-staining, by decreasing the concentration of extracellular Ca2+ (Paramecium cells rapidly adjust their Ca2+ level to that in the outside medium). Fluorochromes reveal spontaneous fluctuations in cytosolic Ca2+ levels along the osmoregulatory system and these signals change upon activation of caged Ins(1,4,5)P3. Considering the ongoing expulsion of substantial amounts of Ca2+ by the osmoregulatory system, we propose here that Ins(1,4,5)P3 receptors serve a new function, i.e. a latent, graded reflux of Ca2+ to fine-tune [Ca2+] homeostasis

Experimental Verification and Analysis of Dynamic Loop Scheduling in Scientific Applications

Scientific applications are often irregular and characterized by large computationally-intensive parallel loops. Dynamic loop scheduling (DLS) techniques improve the performance of computationally-intensive scientific applications via load balancing of their execution on high-performance computing (HPC) systems. Identifying the most suitable choices of data distribution strategies, system sizes, and DLS techniques which improve the performance of a given application, requires intensive assessment and a large number of exploratory native experiments (using real applications on real systems), which may not always be feasible or practical due to associated time and costs. In such cases, simulative experiments are more appropriate for studying the performance of applications. This motivates the question of ‘How realistic are the simulations of executions of scientific applications using DLS on HPC platforms?’ In the present work, a methodology is devised to answer this question. It involves the experimental verification and analysis of the performance of DLS in scientific applications. The proposed methodology is employed for a computer vision application executing using four DLS techniques on two different HPC platforms, both via native and simulative experiments. The evaluation and analysis of the native and simulative results indicate that the accuracy of the simulative experiments is strongly influenced by the approach used to extract the computational effort of the application (FLOP- or time-based), the choice of application model representation into simulation (data or task parallel), and the available HPC subsystem models in the simulator (multi-core CPUs, memory hierarchy, and network topology). The minimum and the maximum percent errors achieved between the native and the simulative experiments are 0.95% and 8.03%, respectively

An Approach for Realistically Simulating the Performance of Scientific Applications on High Performance Computing Systems

Scientific applications often contain large, computationally-intensive, and irregular parallel loops or tasks that exhibit stochastic characteristics. Applications may suffer from load imbalance during their execution on high-performance computing (HPC) systems due to such characteristics. Dynamic loop self-scheduling (DLS) techniques are instrumental in improving the performance of scientific applications on HPC systems via load balancing. Selecting a DLS technique that results in the best performance for different problems and system sizes requires a large number of exploratory experiments. A theoretical model that can be used to predict the scheduling technique that yields the best performance for a given problem and system has not yet been identified. Therefore, simulation is the most appropriate approach for conducting such exploratory experiments with reasonable costs. This work devises an approach to realistically simulate computationally-intensive scientific applications that employ DLS and execute on HPC systems. Several approaches to represent the application tasks (or loop iterations) are compared to establish their influence on the simulative application performance. A novel simulation strategy is introduced, which transforms a native application code into a simulative code. The native and simulative performance of two computationally-intensive scientific applications are compared to evaluate the realism of the proposed simulation approach. The comparison of the performance characteristics extracted from the native and simulative performance shows that the proposed simulation approach fully captured most of the performance characteristics of interest. This work shows and establishes the importance of simulations that realistically predict the performance of DLS techniques for different applications and system configurations

Experimental Verification and Analysis of Dynamic Loop Scheduling in Scientific Applications

Scientific applications are often irregular and characterized by large computationally-intensive parallel loops. Dynamic loop scheduling (DLS) techniques improve the performance of computationally-intensive scientific applications via load balancing of their execution on high-performance computing (HPC) systems. Identifying the most suitable choices of data distribution strategies, system sizes, and DLS techniques which improve the performance of a given application, requires intensive assessment and a large number of exploratory native experiments (using real applications on real systems), which may not always be feasible or practical due to associated time and costs. In such cases, simulative experiments are more appropriate for studying the performance of applications. This motivates the question of How realistic are the simulations of executions of scientific applications using DLS on HPC platforms? In the present work, a methodology is devised to answer this question. It involves the experimental verification and analysis of the performance of DLS in scientific applications. The proposed methodology is employed for a computer vision application executing using four DLS techniques on two different HPC plat- forms, both via native and simulative experiments. The evaluation and analysis of the native and simulative results indicate that the accuracy of the simulative experiments is strongly influenced by the approach used to extract the computational effort of the application (FLOP- or time-based), the choice of application model representation into simulation (data or task parallel), and the available HPC subsystem models in the simulator (multi-core CPUs, memory hierarchy, and network topology). The minimum and the maximum percent errors achieved between the native and the simulative experiments are 0.95% and 8.03%, respectively

The 24/7 approach to promoting optimal welfare for captive wild animals

We have an ethical responsibility to provide captive animals with environments that allow them to experience good welfare. Husbandry activities are often scheduled for the convenience of care staff working within the constraints of the facility, rather than considering the biological and psychological requirements of the animals themselves. The animal welfare 24/7 across the lifespan concept provides a holistic framework to map features of the animal’s life cycle, taking into account their natural history, in relation to variations in the captive environment, across day and night, weekdays, weekends, and seasons. In order for animals to have the opportunity to thrive, we argue the need to consider their lifetime experience, integrated into the environments we provide, and with their perspective in mind. Here, we propose a welfare assessment tool based upon 14 criteria, to allow care staff to determine if their animals’ welfare needs are met. We conclude that animal habitat management will be enhanced with the use of integrated technologies that provide the animals with more opportunities to engineer their own environments, providing them with complexity, choice and control

Exkursion: Hattingen-Niederbonsfeld, geologisch-geomorphologische Exkursion im Ruhrtal am Isenberg

Am steilen Prallhang der Ruhr zwischen Hattingen und Niederwenigern ist die vermutlich längste zusammenhängende Gesteinsfolge des Ruhrgebiets aufgeschlossen, deren südlicher Abschnitt im Rahmen der Exkursion näher betrachtet wurde. Im Mittelpunkt standen die besonders deutlich ausgeprägten Zusammenhänge zwischen der inneren geologischen Struktur des Steinkohlengebirges und dem heutigen Oberflächenrelief mit seinen markanten Bergrücken (Eggen). Die Eggen sind südlich des Ruhrtals zwischen Kettwig und Witten derart bestimmend für das Landschaftsbild, dass die entsprechenden Gebiete im Rahmen der naturräumlichen Gliederung des Ruhrgebiets durch VON KÜRTEN (1970) als Ruhr- Eggenland und Märkisches Eggenland bezeichnet werden