985 resultados para Natural Bleaching Event


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The effect of conduction-convection-radiation on natural convection flow of Newtonian optically thick gray fluid, confined in a non-Darcian porous media square cavity is numerically studied. For the gray fluid consideration is given to Rosseland diffusion approximation. Further assuming that (i) the temperature of the left vertical wall is varying linearly with height, (ii) cooled right vertical and top walls and (iii) the bottom wall is uniformly-heated. The governing equations are solved using the Alternate Direct Implicit method together with the Successive Over Relaxation technique. The investigation of the effect of governing parameters namely the Forschheimer resistance (Γ), the Planck constant (Rd), and the temperature difference (Δ), on flow pattern and heat transfer characteristics has been carried out. It was seen that the reduction of flow and heat transfer occurs as the Forschheimer resistance is increased. On the other hand both the strength of flow and heat transfer increases as the temperature ratio, Δ, is increased.

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Courtney Pedersen and Charles Robb's A Natural History of Trees was a installation mounted at Blindside ARI in Melbourne's CBD in 2012. The work took the form of a pine-panelled room containing a pair of life-sized tree trunks composed entirely of stacks of cut paper discs. A faux bois stool reinforced the sense of artificiality. Claustrophic and precarious, the installation was simultaneously a response to the complexity of our relationship with nature and place, and an evocation of the precarious quality of the collaborative process. The exhibition was accompanied by a catalogue with an essay by writer/curator, Jane O'Neill.

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Through a forest inventory in parts of the Amudarya river delta, Central Asia, we assessed the impact of ongoing forest degradation on the emissions of greenhouse gases (GHG) from soils. Interpretation of aerial photographs from 2001, combined with data on forest inventory in 1990 and field survey in 2003 provided comprehensive information about the extent and changes of the natural tugai riparian forests and tree plantations in the delta. The findings show an average annual deforestation rate of almost 1.3% and an even higher rate of land use change from tugai forests to land with only sparse tree cover. These annual rates of deforestation and forest degradation are higher than the global annual forest loss. By 2003, the tugai forest area had drastically decreased to about 60% compared to an inventory in 1990. Significant differences in soil GHG emissions between forest and agricultural land use underscore the impact of the ongoing land use change on the emission of soil-borne GHGs. The conversion of tugai forests into irrigated croplands will release 2.5 t CO2 equivalents per hectare per year due to elevated emissions of N2O and CH4. This demonstrates that the ongoing transformation of tugai forests into agricultural land-use systems did not only lead to a loss of biodiversity and of a unique ecosystem, but substantially impacts the biosphere-atmosphere exchange of GHG and soil C and N turnover processes.

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Process mining encompasses the research area which is concerned with knowledge discovery from information system event logs. Within the process mining research area, two prominent tasks can be discerned. First of all, process discovery deals with the automatic construction of a process model out of an event log. Secondly, conformance checking focuses on the assessment of the quality of a discovered or designed process model in respect to the actual behavior as captured in event logs. Hereto, multiple techniques and metrics have been developed and described in the literature. However, the process mining domain still lacks a comprehensive framework for assessing the goodness of a process model from a quantitative perspective. In this study, we describe the architecture of an extensible framework within ProM, allowing for the consistent, comparative and repeatable calculation of conformance metrics. For the development and assessment of both process discovery as well as conformance techniques, such a framework is considered greatly valuable.

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Free association norms indicate that words are organized into semantic/associative neighborhoods within a larger network of words and links that bind the net together. We present evidence indicating that memory for a recent word event can depend on implicitly and simultaneously activating related words in its neighborhood. Processing a word during encoding primes its network representation as a function of the density of the links in its neighborhood. Such priming increases recall and recognition and can have long lasting effects when the word is processed in working memory. Evidence for this phenomenon is reviewed in extralist cuing, primed free association, intralist cuing, and single-item recognition tasks. The findings also show that when a related word is presented to cue the recall of a studied word, the cue activates it in an array of related words that distract and reduce the probability of its selection. The activation of the semantic network produces priming benefits during encoding and search costs during retrieval. In extralist cuing recall is a negative function of cue-to-distracter strength and a positive function of neighborhood density, cue-to-target strength, and target-to cue strength. We show how four measures derived from the network can be combined and used to predict memory performance. These measures play different roles in different tasks indicating that the contribution of the semantic network varies with the context provided by the task. We evaluate spreading activation and quantum-like entanglement explanations for the priming effect produced by neighborhood density.

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In this paper, we propose an approach which attempts to solve the problem of surveillance event detection, assuming that we know the definition of the events. To facilitate the discussion, we first define two concepts. The event of interest refers to the event that the user requests the system to detect; and the background activities are any other events in the video corpus. This is an unsolved problem due to many factors as listed below: 1) Occlusions and clustering: The surveillance scenes which are of significant interest at locations such as airports, railway stations, shopping centers are often crowded, where occlusions and clustering of people are frequently encountered. This significantly affects the feature extraction step, and for instance, trajectories generated by object tracking algorithms are usually not robust under such a situation. 2) The requirement for real time detection: The system should process the video fast enough in both of the feature extraction and the detection step to facilitate real time operation. 3) Massive size of the training data set: Suppose there is an event that lasts for 1 minute in a video with a frame rate of 25fps, the number of frames for this events is 60X25 = 1500. If we want to have a training data set with many positive instances of the event, the video is likely to be very large in size (i.e. hundreds of thousands of frames or more). How to handle such a large data set is a problem frequently encountered in this application. 4) Difficulty in separating the event of interest from background activities: The events of interest often co-exist with a set of background activities. Temporal groundtruth typically very ambiguous, as it does not distinguish the event of interest from a wide range of co-existing background activities. However, it is not practical to annotate the locations of the events in large amounts of video data. This problem becomes more serious in the detection of multi-agent interactions, since the location of these events can often not be constrained to within a bounding box. 5) Challenges in determining the temporal boundaries of the events: An event can occur at any arbitrary time with an arbitrary duration. The temporal segmentation of events is difficult and ambiguous, and also affected by other factors such as occlusions.

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Monetite is a phosphate mineral formed by the reaction of the chemicals in bat guano with calcite substrates and is commonly found in caves. The analog of the mineral monetite CaHPO4 has been synthesized and the Raman and infrared spectra of the natural monetite originating from the Murra-el-elevyn Cave, Eucla, Western Australia, compared. Monetite is characterized by a complex set of phosphate bands that arise because of two sets of pairs of phosphate units in the unit cell. Raman and infrared bands are assigned to HPO4(2-), OH stretching and bending vibrations. Infrared bands at 1346 and 1402 cm−1 are assigned to POH deformation modes. Vibrational spectroscopy confirms the presence of monetite in the cave system.

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Analyzing emotional states under duress or during heightened, life-and-death situations is extremely difficult, especially given the inability of laboratory experiments to replicate the environment and given the inherent biases of post event surveys. This is where natural experiments, such as the pager communications from September 11th can provide the kind of natural experiment emotion researchers have been seeking. We demonstrate that positive and pro-social communications are the first to emerge followed by the slower and lower negative communications. Religious sentiment is the last to emerge, as individual attempt to make sense of event. Additionally we provide a methodological discussion about the preparation and analysis of such natural experiments (the pager message content) and show the importance of using multiple methods to extract the broadest possible understanding.

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Extracting and aggregating the relevant event records relating to an identified security incident from the multitude of heterogeneous logs in an enterprise network is a difficult challenge. Presenting the information in a meaningful way is an additional challenge. This paper looks at solutions to this problem by first identifying three main transforms; log collection, correlation, and visual transformation. Having identified that the CEE project will address the first transform, this paper focuses on the second, while the third is left for future work. To aggregate by correlating event records we demonstrate the use of two correlation methods, simple and composite. These make use of a defined mapping schema and confidence values to dynamically query the normalised dataset and to constrain result events to within a time window. Doing so improves the quality of results, required for the iterative re-querying process being undertaken. Final results of the process are output as nodes and edges suitable for presentation as a network graph.

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Laminar two-dimensional natural convection boundary-layer flow of non-Newtonian fluids along an isothermal horizontal circular cylinder has been studied using a modified power-law viscosity model. In this model, there are no unrealistic limits of zero or infinite viscosity. Therefore, the boundary-layer equations can be solved numerically by using marching order implicit finite difference method with double sweep technique. Numerical results are presented for the case of shear-thinning as well as shear thickening fluids in terms of the fluid velocity and temperature distributions, shear stresses and rate of heat transfer in terms of the local skin-friction and local Nusselt number respectively.

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