Modeling broad-scale patterns of avian species richness across the Midwestern United States with measures of satellite image texture

Avian biodiversity is threatened, and in order to prioritize limited conservation resources and conduct effective conservation planning a better understanding of avian species richness patterns is needed. The use of image texture measures, as a proxy for the spatial structure of land cover and vegetation, has proven useful in explaining patterns of avian abundance and species richness. However, prior studies that modeled habitat with texture measures were conducted over small geographical extents and typically focused on a single habitat type. Our goal was to evaluate the performance of texture measures over broad spatial extents and across multiple habitat types with varying levels of vertical habitat structure. We calculated a suite of texture measures from 114 Landsat images over a study area of 1,498,000 km² in the Midwestern United States, which included habitats ranging from grassland to forest. Avian species richness was modeled for several functional guilds as a function of image texture. We subsequently compared the explanatory power of texture-only models with models fitted using landscape composition metrics derived from the National Land Cover Dataset, as well as models fitted using both texture and composition metrics. Measures of image texture were effective in modeling spatial patterns of avian species richness in multiple habitat types, explaining up to 51% of the variability in species richness of permanent resident birds. In comparison, landscape composition metrics explained up to 56% of the variability in permanent resident species richness. In the most heavily forested ecoregion, texture-measures outperformed landscape metrics, and the two types of measurements were complementary in multivariate models. However, in two out of three ecoregions examined, landscape composition metrics consistently performed slightly better than texture measures, and the variance explained by the two types of measures overlapped considerably. These results show that image texture measures derived from satellite imagery can be an important tool for modeling patterns of avian species richness at broad spatial extents, and thus assist in conservation planning. However, texture measures were slightly inferior to landscape composition metrics in about three-fourths of our models. Therefore texture measures are best considered in conjunction with landscape metrics (if available) and are best used when they show explanatory ability that is complementarity to landscape metrics.     

面向调度主站一体化的数据网格设计与实现

高性能电力应用致力于搭建用于调度数据的统一管理、集中处理平台。数据网格易于海量数据共享的特点使其适用于实现调度主站一体化。构建了调度主站数据网格的基本架构,利用网格软件Globus Toolkit建立网格环境,在此基础上配置数据库访问中间件OGSA-DAI来建立面向调度主站一体化的数据网格实验平台。     

Destruction of trichloroethylene (TCE) and trichloromethane (TCM) in the presence of selected VOCs over Pt-Pd-based catalyst

Catalytic oxidation of trichloroethylene (TCE) and trichloromethane (TCM) oxidized alone and in two-component mixtures with selected volatile organic compounds (VOCs) such as toluene, n-hexane, ethanol or acetone was investigated over a Pt-Pd-based catalyst on a monolithic, metallic, γ-Al₂O₃-washcoated support. TCE and TCM were more difficult to oxidize than VOCs and temperatures of their 50% conversion (T_50%) amouted to 420 and 330 °C, respectively. All the VOCs added were found to enhance the conversion of the two chlorinated compounds, drecreasing T_50% by 20 °C, at the most, for TCM in the presence of toluene and by 50 °C for TCE in the presence of acetone. Both the chlorinated compounds lowered the conversion of the VOCs added (except that of toluene), and this lowering was particularly distinct with n-heptane; they also raised the concentration of acetaldehyde formed during the oxidation of oxyderivative compounds.     

Cooperation and Competition in ALIAS: A Logic Framework for Agents that Negotiate

This paper presents ALIAS, an agent architecture based on intelligent logic agents, where the main form of agent reasoning is abduction. The system is particularly suited for solving problems where knowledge is incomplete, where agents may need to make reasonable hypotheses about the problem domain and other agents, and where the raised hypotheses have to be consistent for the overall set of agents. ALIAS agents are pro-active, exhibiting a goal-directed behavior, and autonomous, since each one can solve problems using its own private knowledge base. ALIAS agents are also social, because they are able to interact with other agents, in order to cooperatively solve problems. The coordination mechanisms are modeled by means of LAILA, a logic-based language which allows to express intra-agent reasoning and inter-agent coordination. As an application, we show how LAILA can be used to implement inter-agent dialogues, e.g., for negotiation. In particular, LAILA is well-suited to coordinate the process of negotiation aimed at exchanging resources between agents, thus allowing them to execute the plans to achieve their goals.     

Tropos: An Agent-Oriented Software Development Methodology

Our goal in this paper is to introduce and motivate a methodology, called Tropos,¹ for building agent oriented software systems. Tropos is based on two key ideas. First, the notion of agent and all related mentalistic notions (for instance goals and plans) are used in all phases of software development, from early analysis down to the actual implementation. Second, Tropos covers also the very early phases of requirements analysis, thus allowing for a deeper understanding of the environment where the software must operate, and of the kind of interactions that should occur between software and human agents. The methodology is illustrated with the help of a case study. The Tropos language for conceptual modeling is formalized in a metamodel described with a set of UML class diagrams.     

A 2 MV Van de Graaff accelerator as a tool for planetary and impact physics research

Investigating the dynamical and physical properties of cosmic dust can reveal a great deal of information about both the dust and its many sources. Over recent years, several spacecraft (e.g., Cassini, Stardust, Galileo, and Ulysses) have successfully characterised interstellar, interplanetary, and circumplanetary dust using a variety of techniques, including in situ analyses and sample return. Charge, mass, and velocity measurements of the dust are performed either directly (induced charge signals) or indirectly (mass and velocity from impact ionisation signals or crater morphology) and constrain the dynamical parameters of the dust grains. Dust compositional information may be obtained via either time-of-flight mass spectrometry of the impact plasma or direct sample return. The accurate and reliable interpretation of collected spacecraft data requires a comprehensive programme of terrestrial instrument calibration. This process involves accelerating suitable solar system analogue dust particles to hypervelocity speeds in the laboratory, an activity performed at the Max Planck Institut fu?r Kernphysik in Heidelberg, Germany. Here, a 2 MV Van de Graaff accelerator electrostatically accelerates charged micron and submicron-sized dust particles to speeds up to 80 km s(-1). Recent advances in dust production and processing have allowed solar system analogue dust particles (silicates and other minerals) to be coated with a thin conductive shell, enabling them to be charged and accelerated. Refinements and upgrades to the beam line instrumentation and electronics now allow for the reliable selection of particles at velocities of 1-80 km s(-1) and with diameters of between 0.05 μm and 5 μm. This ability to select particles for subsequent impact studies based on their charges, masses, or velocities is provided by a particle selection unit (PSU). The PSU contains a field programmable gate array, capable of monitoring in real time the particles' speeds and charges, and is controlled remotely by a custom, platform independent, software package. The new control instrumentation and electronics, together with the wide range of accelerable particle types, allow the controlled investigation of hypervelocity impact phenomena across a hitherto unobtainable range of impact parameters.     

Competitive snoopy caching

In a snoopy cache multiprocessor system, each processor has a cache in which it stores blocks of data. Each cache is connected to a bus used to communicate with the other caches and with main memory. Each cache monitors the activity on the bus and in its own processor and decides which blocks of data to keep and which to discard. For several of the proposed architectures for snoopy caching systems, we present new on-line algorithms to be used by the caches to decide which blocks to retain and which to drop in order to minimize communication over the bus. We prove that, for any sequence of operations, our algorithms' communication costs are within a constant factor of the minimum required for that sequence; for some of our algorithms we prove that no on-line algorithm has this property with a smaller constant.A preliminary and condensed version of this paper appeared in theProceedings of the 27th Annual Symposium on the Foundations of Computer Science, IEEE, 1986.This author received support from an IBM doctoral fellowship, and did part of this work while a research student associate at IBM Almaden Research Center.     

ADAM10 and ADAM17—Novel Players in Retinoblastoma Carcinogenesis

A disintegrin and metalloproteinase (ADAM) family proteins, acting as sheddases, are important factors in a number of pathologies, including cancer, and have been suggested as promising therapeutic targets. The study presented focuses on the involvement of ADAM10 and ADAM17 in retinoblastoma (RB), the most common malignant intraocular childhood tumor. A significant correlation between ADAM17 expression levels and RB laterality and RB staging was observed. Levels of ADAM10 or ADAM17 regulating miRNAs miR-145, -152, and -365 were significantly downregulated in RB cell lines, and reduced miR levels with simultaneously upregulated ADAM10 and ADAM17 expression were found in RB patients. The involvement of both ADAMs analyzed in ectodomain shedding of the neuronal cell adhesion molecule L1 (L1CAM), shown to induce pro-tumorigenic effects in RB, was confirmed. Lentiviral ADAM10 and ADAM17 single or ADAM10/17 double knockdown (KD) induced caspase-dependent apoptosis and reduced cell viability, proliferation, growth, and colony formation capacity of RB cells. Moreover, differential phosphorylation of the serine/threonine kinase AKT was observed following ADAM17 KD in RB cells. Chicken chorioallantoic membrane (CAM) assays revealed that ADAM17 and ADAM10/17 depletion decreases the tumorigenic and migration potential of RB cells in vivo. Thus, ADAMs are potential novel targets for future therapeutic RB approaches.