8 resultados para visit

em Boston University Digital Common


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http://www.archive.org/details/insouthernindivi00mitcuoft

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http://www.archive.org/details/englandsmissiont00barruoft

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Many animals in the tropics of Africa, Asia and South America regularly visit so-called salt or mineral licks to consume clay or drink clay-saturated water. Whether this behavior is used to supplement diets with locally limited nutrients or to buffer the effects of toxic secondary plant compounds remains unclear. In the Amazonian rainforest, pregnant and lactating bats are frequently observed and captured at mineral licks. We measured the nitrogen isotope ratio in wing tissue of omnivorous short-tailed fruit bats, Carollia perspicillata, and in an obligate fruit-eating bat, Artibeus obscurus, captured at mineral licks and at control sites in the rainforest. Carollia perspicillata with a plant-dominated diet were more often captured at mineral licks than individuals with an insect-dominated diet, although insects were more mineral depleted than fruits. In contrast, nitrogen isotope ratios of A. obscurus did not differ between individuals captured at mineral lick versus control sites. We conclude that pregnant and lactating fruit-eating bats do not visit mineral licks principally for minerals, but instead to buffer the effects of secondary plant compounds that they ingest in large quantities during periods of high energy demand. These findings have potential implications for the role of mineral licks for mammals in general, including humans.

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The necessity we face for the future of Methodism is the re-invention of traditions. To re-invent traditions is to re-visit the past with all of its richness; to discern what in our tradition is most central to Christian faith; to analyze those parts of our past that continue to give life; to discern and build upon what is of value in the newly emerging tradition; and to reflect on those aspects of the neglected and rejected past that challenge our present perspectives and practices. To re-invent traditions is to develop new perspectives and practices from the building blocks of the past and from the fresh movements of the Spirit in the present. To do so is to recognize that Christianity in general, and Methodism in particular, is marked by traditions that have continually been passed on, critiqued, eliminated, created, and re-invented for the sake of a living Christian witness. What we can hope for is that God is there in the future already, pulling us toward God’s own New Creation.

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In this paper we discuss a new type of query in Spatial Databases, called Trip Planning Query (TPQ). Given a set of points P in space, where each point belongs to a category, and given two points s and e, TPQ asks for the best trip that starts at s, passes through exactly one point from each category, and ends at e. An example of a TPQ is when a user wants to visit a set of different places and at the same time minimize the total travelling cost, e.g. what is the shortest travelling plan for me to visit an automobile shop, a CVS pharmacy outlet, and a Best Buy shop along my trip from A to B? The trip planning query is an extension of the well-known TSP problem and therefore is NP-hard. The difficulty of this query lies in the existence of multiple choices for each category. In this paper, we first study fast approximation algorithms for the trip planning query in a metric space, assuming that the data set fits in main memory, and give the theory analysis of their approximation bounds. Then, the trip planning query is examined for data sets that do not fit in main memory and must be stored on disk. For the disk-resident data, we consider two cases. In one case, we assume that the points are located in Euclidean space and indexed with an Rtree. In the other case, we consider the problem of points that lie on the edges of a spatial network (e.g. road network) and the distance between two points is defined using the shortest distance over the network. Finally, we give an experimental evaluation of the proposed algorithms using synthetic data sets generated on real road networks.

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Commonly, research work in routing for delay tolerant networks (DTN) assumes that node encounters are predestined, in the sense that they are the result of unknown, exogenous processes that control the mobility of these nodes. In this paper, we argue that for many applications such an assumption is too restrictive: while the spatio-temporal coordinates of the start and end points of a node's journey are determined by exogenous processes, the specific path that a node may take in space-time, and hence the set of nodes it may encounter could be controlled in such a way so as to improve the performance of DTN routing. To that end, we consider a setting in which each mobile node is governed by a schedule consisting of a ist of locations that the node must visit at particular times. Typically, such schedules exhibit some level of slack, which could be leveraged for DTN message delivery purposes. We define the Mobility Coordination Problem (MCP) for DTNs as follows: Given a set of nodes, each with its own schedule, and a set of messages to be exchanged between these nodes, devise a set of node encounters that minimize message delivery delays while satisfying all node schedules. The MCP for DTNs is general enough that it allows us to model and evaluate some of the existing DTN schemes, including data mules and message ferries. In this paper, we show that MCP for DTNs is NP-hard and propose two detour-based approaches to solve the problem. The first (DMD) is a centralized heuristic that leverages knowledge of the message workload to suggest specific detours to optimize message delivery. The second (DNE) is a distributed heuristic that is oblivious to the message workload, and which selects detours so as to maximize node encounters. We evaluate the performance of these detour-based approaches using extensive simulations based on synthetic workloads as well as real schedules obtained from taxi logs in a major metropolitan area. Our evaluation shows that our centralized, workload-aware DMD approach yields the best performance, in terms of message delay and delivery success ratio, and that our distributed, workload-oblivious DNE approach yields favorable performance when compared to approaches that require the use of data mules and message ferries.

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Controlling the mobility pattern of mobile nodes (e.g., robots) to monitor a given field is a well-studied problem in sensor networks. In this setup, absolute control over the nodes’ mobility is assumed. Apart from the physical ones, no other constraints are imposed on planning mobility of these nodes. In this paper, we address a more general version of the problem. Specifically, we consider a setting in which mobility of each node is externally constrained by a schedule consisting of a list of locations that the node must visit at particular times. Typically, such schedules exhibit some level of slack, which could be leveraged to achieve a specific coverage distribution of a field. Such a distribution defines the relative importance of different field locations. We define the Constrained Mobility Coordination problem for Preferential Coverage (CMC-PC) as follows: given a field with a desired monitoring distribution, and a number of nodes n, each with its own schedule, we need to coordinate the mobility of the nodes in order to achieve the following two goals: 1) satisfy the schedules of all nodes, and 2) attain the required coverage of the given field. We show that the CMC-PC problem is NP-complete (by reduction to the Hamiltonian Cycle problem). Then we propose TFM, a distributed heuristic to achieve field coverage that is as close as possible to the required coverage distribution. We verify the premise of TFM using extensive simulations, as well as taxi logs from a major metropolitan area. We compare TFM to the random mobility strategy—the latter provides a lower bound on performance. Our results show that TFM is very successful in matching the required field coverage distribution, and that it provides, at least, two-fold query success ratio for queries that follow the target coverage distribution of the field.