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The U.S. Department of Agriculture–Agricultural Research Service (USDA-ARS) has been a leader in weed science research covering topics ranging from the development and use of integrated weed management (IWM) tactics to basic mechanistic studies, including biotic resistance of desirable plant communities and herbicide resistance. ARS weed scientists have worked in agricultural and natural ecosystems, including agronomic and horticultural crops, pastures, forests, wild lands, aquatic habitats, wetlands, and riparian areas. Through strong partnerships with academia, state agencies, private industry, and numerous federal programs, ARS weed scientists have made contributions to discoveries in the newest fields of robotics and genetics, as well as the traditional and fundamental subjects of weed–crop competition and physiology and integration of weed control tactics and practices. Weed science at ARS is often overshadowed by other research topics; thus, few are aware of the long history of ARS weed science and its important contributions. This review is the result of a symposium held at the Weed Science Society of America’s 62nd Annual Meeting in 2022 that included 10 separate presentations in a virtual Weed Science Webinar Series. The overarching themes of management tactics (IWM, biological control, and automation), basic mechanisms (competition, invasive plant genetics, and herbicide resistance), and ecosystem impacts (invasive plant spread, climate change, conservation, and restoration) represent core ARS weed science research that is dynamic and efficacious and has been a significant component of the agency’s national and international efforts. This review highlights current studies and future directions that exemplify the science and collaborative relationships both within and outside ARS. Given the constraints of weeds and invasive plants on all aspects of food, feed, and fiber systems, there is an acknowledged need to face new challenges, including agriculture and natural resources sustainability, economic resilience and reliability, and societal health and well-being.
The science of extra-solar planets is one of the most rapidly changing areas of astrophysics and since 1995 the number of planets known has increased by almost two orders of magnitude. A combination of ground-based surveys and dedicated space missions has resulted in 560-plus planets being detected, and over 1200 that await confirmation. NASA's Kepler mission has opened up the possibility of discovering Earth-like planets in the habitable zone around some of the 100,000 stars it is surveying during its 3 to 4-year lifetime. The new ESA's Gaia mission is expected to discover thousands of new planets around stars within 200 parsecs of the Sun. The key challenge now is moving on from discovery, important though that remains, to characterisation: what are these planets actually like, and why are they as they are?
In the past ten years, we have learned how to obtain the first spectra of exoplanets using transit transmission and emission spectroscopy. With the high stability of Spitzer, Hubble, and large ground-based telescopes the spectra of bright close-in massive planets can be obtained and species like water vapour, methane, carbon monoxide and dioxide have been detected. With transit science came the first tangible remote sensing of these planetary bodies and so one can start to extrapolate from what has been learnt from Solar System probes to what one might plan to learn about their faraway siblings. As we learn more about the atmospheres, surfaces and near-surfaces of these remote bodies, we will begin to build up a clearer picture of their construction, history and suitability for life.
The Exoplanet Characterisation Observatory, EChO, will be the first dedicated mission to investigate the physics and chemistry of Exoplanetary Atmospheres. By characterising spectroscopically more bodies in different environments we will take detailed planetology out of the Solar System and into the Galaxy as a whole.
EChO has now been selected by the European Space Agency to be assessed as one of four M3 mission candidates.
We introduce basic ideas of binary separation by a linear hyperplane, which is a technique exploited in the support vector machine (SVM) concept. This is a decision-making tool for pattern recognition and related problems. We describe a fundamental standard problem (SP) and show how this is used in most existing research to develop a dual-based algorithm for its solution. This algorithm is shown to be deficient in certain aspects, and we develop a new primal-based SQP-like algorithm, which has some interesting features. Most practical SVM problems are not adequately handled by a linear hyperplane. We describe the nonlinear SVM technique, which enables a nonlinear separating surface to be computed, and we propose a new primal algorithm based on the use of low-rank Cholesky factors.
It may be, however, that exact separation is not desirable due to the presence of uncertain or mislabelled data. Dealing with this situation is the main challenge in developing suitable algorithms. Existing dual-based algorithms use the idea of L1 penalties, which has merit. We suggest how penalties can be incorporated into a primal-based algorithm. Another aspect of practical SVM problems is often the huge size of the data set, which poses severe challenges both for software package development and for control of ill-conditioning. We illustrate some of these issues with numerical experiments on a range of problems.
Children with spina bifida and hydrocephalus (SBH) have long
been known to have difficulties with visual perception. We studied
how children with SBH perform 12 visual perception tasks requiring
object identification, multistable representations of visual
space, or visually guided overt actions. Four tasks required
object-based processing (visual constancy illusions, face
recognition, recognition of fragmented objects, line orientation).
Four tasks required the representation of visual space in
egocentric coordinates (stereopsis, visual figure-ground
identification, perception of multistable figures, egocentric
mental rotation). Four tasks required the coupling of visual
space to overt movement (visual pursuit, figure drawing, visually
guided route finding, visually guided route planning). Effect
sizes, measuring the magnitude of the difference between SBH
children and controls, were consistently larger for action-based
than object-based visual perception tasks. Within action-based
tasks, effect sizes were large and roughly comparable for tasks
requiring the representation of visual space and for tasks
requiring visually guided action. The results are discussed
in terms of the physical and brain problems of children with
SBH that limit their ability to build effective situation models
of space. (JINS, 2002, 8, 95–106.)
It is now generally accepted that prior to the outbreak of the First World War German Social Democracy did not, as a rule, count foreign policy among its more central concerns. It is often further assumed that the right wing of the prewar German labor movement was still less interested in foreign policy problems than were left-wing or centrist party spokesmen. This assumption requires qualification, for the work of East German historians and others has shown that social imperialist thought had made heavy inroads into the revisionist wing of prewar Social Democracy. In fact, revisionists and reformists from Vollmar onwards frequently manifested a deep and enduring concern with the problems of Germany's position in the world. Yet there remains in the person of Eduard Bernstein—in many ways the father of revisionism and certainly its intellectual leader and chief publicist—one prominent revisionist whose pre-1914 foreign policy position continues to defy satisfactory categorization and generalization.
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