Pattern Reification as the Basis for Description-Driven Systems

One of the main factors driving object-oriented software development for information systems is the requirement for systems to be tolerant to change. To address this issue in designing systems, this paper proposes a pattern-based, object-oriented, description-driven system (DDS) architecture as an extension to the standard UML four-layer meta-model. A DDS architecture is proposed in which aspects of both static and dynamic systems behavior can be captured via descriptive models and meta-models. The proposed architecture embodies four main elements - firstly, the adoption of a multi-layered meta-modeling architecture and reflective meta-level architecture, secondly the identification of four data modeling relationships that can be made explicit such that they can be modified dynamically, thirdly the identification of five design patterns which have emerged from practice and have proved essential in providing reusable building blocks for data management, and fourthly the encoding of the structural properties of the five design patterns by means of one fundamental pattern, the Graph pattern. A practical example of this philosophy, the CRISTAL project, is used to demonstrate the use of description-driven data objects to handle system evolution.Comment: 20 pages, 10 figure

QCD thermodynamics with continuum extrapolated Wilson fermions II

We continue our investigation of 2+1 flavor QCD thermodynamics using dynamical Wilson fermions in the fixed scale approach. Two additional pion masses, approximately 440 MeV and 285 MeV, are added to our previous work at 545 MeV. The simulations were performed at 3 or 4 lattice spacings at each pion mass. The renormalized chiral condensate, strange quark number susceptibility and Polyakov loop is obtained as a function of the temperature and we observe a decrease in the light chiral pseudo-critical temperature as the pion mass is lowered while the pseudo-critical temperature associated with the strange quark number susceptibility or the Polyakov loop is only mildly sensitive to the pion mass. These findings are in agreement with previous continuum results obtained in the staggered formulation.Comment: 19 pages, 13 figures, published versio

Charmonium spectral functions from 2+1 flavour lattice QCD

Finite temperature charmonium spectral functions in the pseudoscalar and vector channels are studied in lattice QCD with 2+1 flavours of dynamical Wilson quarks, on fine isotropic lattices (with a lattice spacing of 0.057 fm), with a non-physical pion mass of $m_{\pi} \approx$ 545 MeV. The highest temperature studied is approximately $1.4 T_c$. Up to this temperature no significant variation of the spectral function is seen in the pseudoscalar channel. The vector channel shows some temperature dependence, which seems to be consistent with a temperature dependent low frequency peak related to heavy quark transport, plus a temperature independent term at \omega>0. These results are in accord with previous calculations using the quenched approximation.Comment: 17 pages, 9 figures, 2 table

Controlled Deployment of Gossamer Spacecraft

Deployable gossamer structures for solar sails need to be deployed in a controlled way. Several strategies present have the disadvantage that the sail membrane cannot always be tensioned during the deployment process. In combination with a slow deployment, this involves the risk of an entanglement of the sail. Slow deployments of at least several minutes are desirable in order to keep inertial loads low and to implement Fault-Detection, Fault-Isolation and Recovery Techniques (FDIR). This might further require completely stopping and resuming the deployment process. For gossamer spacecraft based on crossed boom configurations with triangular sail segments, a deployment strategy is described that is assumed to allow such a controlled deployment process. With a combination of folding and coiling, it is ensured that the deployed sail area can be held taut between the partly deployed booms. During deployment, four deployment units with two spools each on which the sail is mounted (a half segment stowed on each) moves away from the central bus unit, the center of the deployed sail. The development was made in the Gossamer-1 project of the German Aerospace Center (DLR). The folding and coiling of the membrane is mathematically modelled. This allows an investigation of the deployment geometry. It provides the mathematical relation between the deployed boom length and the deployed sail membrane geometry. By modelling the coiled zig-zag folding lines it is possible to calculate the deployment force vector as function of the deployment time. The stowing and deployment strategy was verified by tests with an engineering qualification model of the Gossamer-1 deployment unit. According to a test-as-you-fly approach the tests included vibration tests, venting, thermal-vacuum tests and ambient deployment. In these tests the deployment strategy proved to be suitable for a controlled deployment of gossamer spacecraft. A deeper understanding of the deployment process is gained by analyzing the deployment strategy mathematically

Environmental properties of cells improve machine learning-based phenotype recognition accuracy

To answer major questions of cell biology, it is often essential to understand the complex phenotypic composition of cellular systems precisely. Modern automated microscopes produce vast amounts of images routinely, making manual analysis nearly impossible. Due to their efficiency, machine learningbased analysis software have become essential tools to perform single-cell-level phenotypic analysis of large imaging datasets. However, an important limitation of such methods is that they do not use the information gained from the cellular micro-and macroenvironment: the algorithmic decision is based solely on the local properties of the cell of interest. Here, we present how various features from the surrounding environment contribute to identifying a cell and how such additional information can improve single-cell-level phenotypic image analysis. The proposed methodology was tested for different sizes of Euclidean and nearest neighbour-based cellular environments both on tissue sections and cell cultures. Our experimental data verify that the surrounding area of a cell largely determines its entity. This effect was found to be especially strong for established tissues, while it was somewhat weaker in the case of cell cultures. Our analysis shows that combining local cellular features with the properties of the cell's neighbourhood significantly improves the accuracy of machine learning-based phenotyping.Peer reviewe

QCD thermodynamics with Wilson fermions

QCD is investigated at finite temperature using Wilson fermions in the fixed scale approach. A 2+1 flavor stout and clover improved action is used at four lattice spacings allowing for control over discretization errors. The light quark masses in this first study are fixed to heavier than physical values. The renormalized chiral condensate, quark number susceptibility and the Polyakov loop is measured and the results are compared with the staggered formulation in the fixed N_t approach. The Wilson results at the finest lattice spacing agree with the staggered results at the highest N_t.Comment: 7 pages, Talk presented at the XXIX International Symposium on Lattice Field Theory (Lattice 2011), July 10-16, 2011, Squaw Valley, Lake Tahoe, California, US

Agri-food business: Global challenges â Innovative solutions

The rise of a western-style middle class in many successful emerging economies like China currently is inducing deep structural changes on agricultural world markets and within the global agri-food business. As a result of both higher incomes and concerns over product safety and quality the global demand for high-quality and safe food products is increasing significantly. In order to meet the new required quality, globally minimum quality standards are rising and private standards emerging. All over the world these developments cause adjustments at the enterprise, chain and market levels. At the same time, the tremendously increasing demand for renewable energy has led to the emergence of a highly promising market for biomass production. This has far-reaching consequences for resource allocation in the agri-food business, for the environment, for the poor in developing countries and for agricultural policy reforms. The challenges increase with ongoing liberalisation, globalisation and standardisation, all of which change trade patterns for agricultural and food commodities, and influence production costs and commodity prices. The objective of the IAMO Forum is to show opportunities as well as risks for all participants of the food economy in the ongoing globalisation process: for small peasants in developing countries, farmers in Europe and globally active food enterprises and retailers. The success of enterprises depends on the ability to find innovative solutions with regard to the organisation of enterprises, chains, and markets, as well as future policy design. Concerning bio-energy strategies has to be identified to combat global warming most efficiently and concurrently attenuate the competition between "tank and table" on farmland. IAMO Forum 2008, as well as this book, would not have been possible without the engagement of many people and institutions. We thank the authors of the papers, as well as the referees. Furthermore we are highly indebted to MARLIES LOHR, NADINE GIEMSA and RONNY RECKE who in an outstanding way contributed to the organisation of the Forum. This is true as well for the IAMO administration, whose work we gratefully acknowledge. Many sponsors has funded the IAMO Forum 2008. We are very grateful to the German Research Foundation (DFG), The Federal Ministry of Food, Agriculture and Consumer Production in Germany, The Ministry of Cultural Affairs of the Federal State Saxony-Anhalt, Germany and last but not least the City of Halle. Further Conference sponsors are the BIONADE Corporation, Gaensefurther Mineral Water, The Wine Growers Association of the Region Saale-Unstrut, Germany, Obsthof am SüÃen See GmbH, Monsanto Company, KWS Saat AG, Sachsen-Anhalt-Tours, Baumkuchen Salzwedel and the Hallesches Brauhaus.Agribusiness, Agricultural and Food Policy, Agricultural Finance, Community/Rural/Urban Development, Industrial Organization, Institutional and Behavioral Economics, International Development, Marketing, Political Economy,

Membrane Deployment Technology Development at DLR for Solar Sails and Large-Scale Photovoltaics

Following the highly successful flight of the first interplanetary solar sail, JAXA's IKAROS, with missions in the pipeline such as NASA's NEASCOUT nanospacecraft solar sail and JAXA's Solar Power Sail solar-electric propelled mission to a Jupiter Trojan asteroid, and on the back-ground of the ever increasing power demand of GEO satellites now including all-electric spacecraft, there is renewed interest in large lightweight structures in space. Among these, deployable membrane or 'gossamer' structures can provide very large functional area units for innovative space applications which can be stowed into the limited volumes of launch vehicle fairings as well as secondary payload launch slots, depending on the scale of the mission. Large area structures such as solar sails or high-power photovoltaic generators require a technology that allows their controlled and thereby safe deployment. Before employing such technology for a dedicated science or commercial mission, it is necessary, to demonstrate its reliability, i.e., TRL 6 or higher. A reliable technology that enables controlled deployment was developed in the GOSSAMER-1 solar sail deployment demonstrator project of the German Aerospace Center, DLR, including verification of its functionality with various laboratory tests to qualify the hardware for a first demonstration in low Earth orbit. We provide an overview of the GOSSAMER-1 hardware development and qualification campaign. The design is based on a crossed boom configuration with triangular sail segments. Employing engineering models, all aspects of the deployment were tested under ambient environment. Several components were also subjected to environmental qualification testing. An innovative stowing and deployment strategy for a controlled deployment and the required mechanisms are described. The tests conducted provide insight into the deployment process and allow a mechanical characterization of this process, in particular the measurement of the deployment forces. The stowing and deployment strategy was verified by tests with an engineering qualification model of one out of four GOSSAMER-1 deployment units. According to a test-as-you-fly approach the tests included vibration tests, venting, thermal-vacuum tests and ambient deployment. In these tests the deployment strategy proved to be suitable for a controlled deployment of gossamer spacecraft, and deployment on system level was demonstrated to be robust and controllable. The GOSSAMER-1 solar sail membranes were also equipped with small thin-film photovoltaic arrays intended to supply the core spacecraft. In our follow-on project GOSOLAR, the focus is now entirely on deployment systems for huge thin-film photovoltaic arrays. Based on the GOSSAMER-1 experience, deployment technology and qualification strategies, new technologies for the integration of thin-film photovoltaics are being developed and qualified for a first in-orbit technology demonstration within five years. Main objective is the further development of deployment technology for a 25 m² gossamer solar power generator and a flexible photovoltaic membrane. GOSOLAR enables a wider range of deployment concepts beyond solar sail optimized methods. It uses the S²TEP bus system developed at the Institute of Space Systems as part of the DLR satellite roadmap

nucleAIzer : A Parameter-free Deep Learning Framework for Nucleus Segmentation Using Image Style Transfer

Single-cell segmentation is typically a crucial task of image-based cellular analysis. We present nucleAIzer, a deep-learning approach aiming toward a truly general method for localizing 2D cell nuclei across a diverse range of assays and light microscopy modalities. We outperform the 739 methods submitted to the 2018 Data Science Bowl on images representing a variety of realistic conditions, some of which were not represented in the training data. The key to our approach is that during training nucleAIzer automatically adapts its nucleus-style model to unseen and unlabeled data using image style transfer to automatically generate augmented training samples. This allows the model to recognize nuclei in new and different experiments efficiently without requiring expert annotations, making deep learning for nucleus segmentation fairly simple and labor free for most biological light microscopy experiments. It can also be used online, integrated into CellProfiler and freely downloaded at www.nucleaizer.org. A record of this paper's transparent peer review process is included in the Supplemental Information.Peer reviewe