958 resultados para Landscape photography -- Utah -- Great Salt Lake


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O presente estudo foi realizado na Bacia Hidrográfica do Rio Passa-Cinco, onde existem elementos da paisagem de grande interesse ecoturístico, além de patrimônios naturais que, se preservados e aproveitados mediante ações de gestão ambiental serão potenciais agentes de desenvolvimento sustentável na região. Apesar da área possuir atrativos naturais como cachoeiras, corredeiras, cavernas, canions, lagos, paredões, mirantes, entre outros, indicando alto potencial de uso sustentável do ponto de vista ecoturístico, a região ainda não recebeu investimentos suficientes para que toda a diversidade paisagística seja usufruída. Portanto, este trabalho tem o objetivo de elaborar um Inventario Ecoturístico da Bacia do Rio Passa-Cinco, inserido nos municípios de Itirapina-SP e Ipeúna-SP, utilizando ferramentas de Geoprocessamento. Para tanto, realizou-se um trabalho de campo com visita aos locais que apresentam valor cênico considerável e potencial ecoturístico. Os locais identificados e visitados foram caracterizados usando fotografias, textos explicativos, tabelas e MDTs (Modelo Digital de Terreno). A integração destas informações constitui um Banco de Dados Geográfico Digital Georreferenciado (BDGDG) em ambiente ArcGIS 9.0, disponível em http://ceapla.rc.unesp.br/atlas/. Os resultados obtidos subsidiam ações de gestão ambiental, como o planejamento ecoturístico na bacia, favorecendo o desenvolvimento sustentável das comunidades envolvidas. Palavras-chaves: Bacia do Rio Passa-Cinco, Inventário Ecoturismo, Geoprocessamento, Banco de Dados Geográfico Digital Georreferenciado.

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Learning by reinforcement is important in shaping animal behavior, and in particular in behavioral decision making. Such decision making is likely to involve the integration of many synaptic events in space and time. However, using a single reinforcement signal to modulate synaptic plasticity, as suggested in classical reinforcement learning algorithms, a twofold problem arises. Different synapses will have contributed differently to the behavioral decision, and even for one and the same synapse, releases at different times may have had different effects. Here we present a plasticity rule which solves this spatio-temporal credit assignment problem in a population of spiking neurons. The learning rule is spike-time dependent and maximizes the expected reward by following its stochastic gradient. Synaptic plasticity is modulated not only by the reward, but also by a population feedback signal. While this additional signal solves the spatial component of the problem, the temporal one is solved by means of synaptic eligibility traces. In contrast to temporal difference (TD) based approaches to reinforcement learning, our rule is explicit with regard to the assumed biophysical mechanisms. Neurotransmitter concentrations determine plasticity and learning occurs fully online. Further, it works even if the task to be learned is non-Markovian, i.e. when reinforcement is not determined by the current state of the system but may also depend on past events. The performance of the model is assessed by studying three non-Markovian tasks. In the first task, the reward is delayed beyond the last action with non-related stimuli and actions appearing in between. The second task involves an action sequence which is itself extended in time and reward is only delivered at the last action, as it is the case in any type of board-game. The third task is the inspection game that has been studied in neuroeconomics, where an inspector tries to prevent a worker from shirking. Applying our algorithm to this game yields a learning behavior which is consistent with behavioral data from humans and monkeys, revealing themselves properties of a mixed Nash equilibrium. The examples show that our neuronal implementation of reward based learning copes with delayed and stochastic reward delivery, and also with the learning of mixed strategies in two-opponent games.

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MP2RAGE has proven to be a bias-free MR acquisition with excellent contrast between grey and white matter. We investigated the ability of three state-of-the-art algorithms to automatically extract white matter (WM), grey matter (GM) and cerebrospinal fluid (CSF) from MPRAGE and MP2RAGE images: unified Segmentation (S) in SPM82 , its extension New Segment (NS), and an in-house Expectation-Maximization Markov Random Field tissue classification3 (EM-MRF) with Graph Cut (GC) optimization4 . Our goal is to quantify the differences between MPRAGE and MP2RAGE-based brain tissue probability maps.

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One letter from Harris, the University Librarian, to President Everett, enclosed with a historical account of the Great Salt and its donor, Richard Harris, and sketches of the new engravings on the Great Salt, Stoughton Cup, and Browne Cup bearing donor names. Harris writes that he hopes to have his account of the Great Salt published in the Cambridge Chronicle and is gratified to hear of Everett’s plans to use an excerpt in his Commencement dinner speech. In a short note of reply, Everett writes that Harris’ account of the silver was "received with great favor" during the dinner.

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One letter addressed "Dear Sir," enclosed with a one-page biographical sketch of Richard Harris. Walters indicates in the letter he had been permitted to examine the college silver, including the Great Salt, in the spring of 1905.

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Black and white composition book sent to the Harvard College Library containing a typed "copy of notes made in the spring of 1886" by John H. Buck. Includes historical information, and physical descriptions and valuations of the Great Salt, the Stoughton Cup, the Browne Cup, and the christening basin acquired with the donation of Oliver Wendell, as well as notes on other gifts of silver.

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Mode of access: Internet.

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"... a newly revised Catalogue of our Stereoscopic Views ..."--Page 1.

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Caption title.

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"Only 50 copies of this four-books-in-one ... were ever issued ... This is no. 27."

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Mode of access: Internet.