104,492 research outputs found
Digestive enzymes of vine weevil (Otiorhynchus sulcatus) as potential targets for insect control strategies.
No full textOver the previous quarter century the vine weevil (Otiorhynchus sulcatus) has become a pest of horticultural and agricultural plants. The vine weevil is a polyphagous coleopteran insect and is able to attack over one hundred different plant species. Its spread has been limited by its lack of flight but modern world trade in live container grown plants has spread the insect to new habitats. Damage to plants caused by vine weevil is two fold, with the larvae destroying root balls while the adults attack the, leaves. The larval stage, in particular is difficult to treat with conventional insecticides unless environmentally undesirable soil treatments are used. The current lack of defence against the vine weevil has opened the door for methods of crop protection through the generation of genetically modified plants. The design of an efficient GM approach to control the vine weevil requires a sound knowledge of the insect’s digestive enzymes, which may be used as potential targets for insecticidal proteins. This approach was achieved for the vine weevil through analysis of active digestive proteases in the insects gut and the identification of suitable proteinase inhibitors which would reduce the overall level of protein hydrolysis. Using this method it was discovered that the vine weevil contained both serine and cysteine proteases in addition to a range of other digestive hydrolases. This biochemical data was supported by a molecular approach to isolate cDNA clones associated with the insect's digestive tract. Using a gut specific cDNA library clones encoding a cathepsin B protease, two trypsin proteases, a pectinesterase, a lipase and a cellulase were isolated and characterised. The cellulase isolated from vine weevil has been shown to originate from the insect genome as shown through Southern Blot analysis and sequencing across several intronic regions. Evidence presented herein shows that the vine weevil gut extract hydrolyses both cellulose and cellobiose. Similar results were observed with recombinant protein expressed in the eukaryotic yeast P.pastoris. Furthermore data presented here shows that the vine weevil has the full complement of enzymes needed for the complete digestion of crystalline cellulose, which was until recently believed to be the sole domain of several species of bacteria and yeast. In addition a cDNA clone encoded a vine weevil endogenous chitinase was isolated from the cDNA library. This chitinase cDNA and one encoding the proteinase inhibitor Oryzacystatin-I were used to generate transgenic tobacco plants which have been shown to express the transgene. These transgenic plants are the first step in developing a strategy for plant protection against vine weevil based on genetic modification
Vine Copula Based Modeling
No full textWith the availability of massive multivariate data comes a need to develop flexible multivariate distribution classes. The copula approach allows marginal models to be constructed for each variable separately and joined with a dependence structure characterized by a copula. The class of multivariate copulas was limited for a long time to elliptical (including the Gaussian and t-copula) and Archimedean families (such as Clayton and Gumbel copulas). Both classes are rather restrictive with regard to symmetry and tail dependence properties. The class of vine copulas overcomes these limitations by building a multivariate model using only bivariate building blocks. This gives rise to highly flexible models that still allow for computationally tractable estimation and model selection procedures. These features made vine copula models quite popular among applied researchers in numerous areas of science. This article reviews the basic ideas underlying these models, presents estimation and model selection approaches, and discusses current developments and future directions.Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.Statistic
Note on new prospects on vines
No full textIn this paper, we present a new methodology based on vine copulas to estimate multivariate distributions in high dimensions, taking advantage of the diversity of vine copulas. Considering the huge number of vine copulas in dimension n, we introduce an efficient selection algorithm to build and select vine copulas with respect to any test T. Our methodology offers a great flexibility to practitioners to compute VaR associated to a portfolio in high dimension.Vines; multivariate copulas; model selection
Political Elite Recruitment and Political Structure in French-Speaking Africa
No full textLe Vine Victor T. Political Elite Recruitment and Political Structure in French-Speaking Africa. In: Cahiers d'études africaines, vol. 8, n°31, 1968. pp. 369-389
New Prospects on Vines
No full textIn this paper, we present a new methodology based on vine copulas to estimate multivariate distributions in high dimensions, taking advantage of the diversity of vine copulas. Considering the huge number of vine copulas in dimension n, we introduce an efficient selection algorithm to build and select vine copulas with respect to any test T. Our methodology offers a great flexibility to practitioners to compute VaR associated to a portfolio in high dimension.Vine copulas, multivariate copulas, model selection, VaR.
Robotic Grasping of Vine Tomatoes: A Learning Approach
No full textCurrently, vine tomato weighing and packaging require a significant amount of manual work. The main barrier to automation lies in the difficulty of developing a reliable robotic grasping system for grasping already harvested vine tomatoes. We propose a method to grasp harvested vine tomatoes that lay in a horizontal position with considerable clutter, which is how they are commonly stored in a crate after harvest. The method consists of a computer vision pipeline to first identify individual trusses in the crate and then determine a suitable grasping location on the stem. The robot then executes a pinch grasp on the stem without the need for touch sensors or mechanistic models. Lab experiments were conducted using a robotic manipulator equipped with an eye-in-hand RGB-D camera, which resulted in a success rate of 89.3%. Furthermore, due to the continuous, online learning capabilities of the system, the robot was successfully able to pick and relocate all presented vine tomatoes when allowed to retry after a failed attempt.Lastly, the method is tried on objects other than vine tomatoes by training on synthetic data, which shows promising results.Mechanical Engineering | Vehicle Engineering | Cognitive Robotic
Selections of vine structures and their applications
No full textCopulas are important models that allow to capture the dependence among variables. There are many types of bivariate parametric copula families, which allow to model data sets with different properties: symmetric and asymmetric dependence, upper (lower) tail dependence. In higher dimensions popular families of copulas, e.g., Gaussian, Student-t and canonical Archimedean are not sufficiently flexible in representing different types of dependence that they can realize. By decomposing the multivariate copula into a sequence of bivariate (conditional) copulas, based on a graph called vine (which is a nested set of trees), one is able to construct a n dimensional copula with the bivariate copulas that can have different types of dependence (e.g., tail behavior and asymmetries). The model constructed this way is called the vine copulamodel...Applied Probabilit
VICTOR T. LE VINE
No full textVictor T. Le Vine, professor emeritus of political science, analyst, and commentator, died on May 7, 2010, after a brief illness. Le Vine, an only son, was born in Berlin in 1928. His family fled Nazi Germany and lived in France until they immigrated to the United States in 1938. A polyglot, fluent in French, German, and Russian, he was a rigorous researcher, a dedicated teacher, and an encyclopedic repository of classical works in politics, history, literature, and music. He mentored hundreds of graduate and undergraduate students in his 47 years as an academic and was known for using his multilingual skills and photographic memory to make every class lecture come alive—at times accompanying them with his vivid newspaper clippings that he collected from his travels. In his classroom, the politics of the postcolonial world were peppered with vignettes of his experiences as a participant observer in the heyday of Africa's decolonization. He shared with his students the emergence of the political systems of diverse countries such as Benin, Cameroon, Cyprus, the Czech Republic, Eritrea, Ghana, France, Israel, the PRC, Rwanda, Saudi Arabia, Turkey, and Zaire (DRC).</jats:p
Vizentin-Bugoni, J., J. H. Sperry, J. P. Kelley, J. T. Foster, D. R. Drake, S. B. Case, J. M. Gleditsch, A. M. Hruska, R. C. Wilcox, C. E. Tarwater. "Dataset from: Mechanisms underlying interaction frequencies and robustness in a novel seed dispersal network"
No full textSeed dispersal and species traits data collected on the Oahu island, Hawaii. Dataset from Vizentin-Bugoni et al. "Mechanisms underlying interaction frequencies and robustness in a novel seed dispersal network". in revie
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