162 research outputs found

    Justin Isenhour and Ryan C. Lewis in a Faculty Chamber Recital

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    This is the program for the faculty chamber recital featuring trombonist Justin R. Isenhour and percussionist Ryan C. Lewis. This recital took place on April 17, 2012, in the W. Francis McBeth Recital Hall

    Brass and Percussion Ensembles Concert, Fall 2012

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    This is the program for the Fall 2012 Brass and Percussion Ensembles concert

    Brass and Percussion Ensembles Concert, Fall 2011

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    This is the program from the Fall 2011 Brass and Percussion Ensembles concert

    An approach to convert vertex-based 3D representations to combinatorial B-splines for real-time visual collaboration

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    Scientific Visualization and Virtual Reality are increasingly being used for the design of complex systems. These technologies offer powerful capabilities to make decisions that are cost and time effective. The next logical extension is to collaborate with these visual models in real-time, where parts of a design team are geographically separated. Specifically, visual collaboration enables ideas and proposed changes to be discussed exactly on a virtual model of a product. However, high-end visualization hardware and Internet technologies impede widespread use of real-time visual collaboration due to the large amount of data from which these representations are created. These data are typically in the form of 3D vertex-based models, which offer a high degree of realism when displayed, but at a price of storage, rendering speeds and processing efficiency. The more realistic the representation desired, the larger the number of vertices required and hence the higher the file size. In this paper, we propose a new data modeling and handling technique where traditional vertex-based models are converted into combinatorial B-Spline based wire-frame models that allow realtime visual collaboration in the context of typical virtual reality systems. Using appropriate filtering methods, parametric equations are computed for each curved segment in a vertexbased representation and bundled together with sampled linear segments of the model. The computed parametric equation based models occupy only a fraction of the size when compared to the original vertex-based models. These lightweight models can easily be transmitted over the Internet, in real-time, for viewing with a platform independent visual client program. The proposed methods were tested on several example data files to prove the method’s effectiveness

    Enabling transformative economic change in the post‐2020 biodiversity agenda

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    Abstract: The COVID‐19 pandemic, its impact on the global economy, and current delays in the negotiation of the post‐2020 global biodiversity agenda of the Convention on Biological Diversity heighten the urgency to build back better for biodiversity, sustainability, and well‐being. In 2019, the Intergovernmental Science‐Policy Platform on Biodiversity and Ecosystem Services (IPBES) concluded that addressing biodiversity loss requires a transformative change of the global economic system. Drawing on the IPBES findings, this policy perspective discusses actions in four priority areas to inform the post‐2020 agenda: (1) Increasing funding for conservation; (2) redirecting incentives for sustainability; (3) creating an enabling regulatory environment; and (4) reforming metrics to assess biodiversity impacts and progress toward sustainable and just goals. As the COVID‐19 pandemic has made clear, and the negotiations for the post‐2020 agenda have emphasized, governments are indispensable in guiding economic systems and must take an active role in transformations, along with businesses and civil society. These key actors must work together to implement actions that combine short‐term impacts with structural change to shift economic systems away from a fixation with growth toward human and ecological well‐being. The four priority areas discussed here provide opportunities for the post‐2020 agenda to do so

    Natural Distribution of Parasitoids of Larvae of the Fall Armyworm, Spodoptera frugiperda, in Argentina

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    To develop a better understanding of the natural distribution of the fall armyworm, Spodoptera frugiperda (Smith) (Lepidoptera: Noctuidae), and to update the knowledge of the incidence of its complex of parasitoids. S. frugiperda, samplings in whorl-stage corn were carried out in provinces of Argentina from 1999 to 2003. S. frugiperda larvae were collected from corn in localities of the provinces of Tucumán, Salta, Jujuy, Santiago del Estero, La Rioja, Córdoba, San Luis, Chaco and Misiones. In each locality 30 corn plants were sampled and only larvae located in those plants were collected. The parasitoids that emerged from S. frugiperda larvae were identified and counted. The abundance of the parasitoids and the parasitism rate were estimated. The S. frugiperda parasitoids collected were Campoletis grioti (Blanchard) (Hymenoptera: Ichneumonidae), Chelonus insularis (Cresson) (Hymenoptera: Braconidae), Archytas marmoratus (Townsend) (Diptera Tachinidae) and/or A. incertus (Macquart), Ophion sp. (Hymenoptera: Ichneumonidae), Euplectrus platyhypenae Howard (Hymenoptera: Eulophidae), and Incamyia chilensis (Aldrich) (Diptera Tachinidae). C. grioti was the most abundant and frequent during the five-year survey. Similar diversity of parasitoids was obtained in all the provinces, with the exception of I. chilensis and E. platyhypenae that were recovered only in the province of Salta. In the Northwestern region, in Tucumán, C. grioti and species of Archytas were the most abundant and frequent parasitoids. On the contrary, in Salta and Jujuy Ch. insularis was the parasitoid most abundant and frequently recovered. The parasitism rate obtained in Tucumán, Salta and Jujuy provinces were 21.96%, 17.87% and 6.63% respectively with an average of 18.93%. These results demonstrate that hymenopteran and dipteran parasitoids of S. frugiperda occurred differentially throughout the Argentinian provinces and played an important role on the natural control of the S. frugiperda larval population
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