860 resultados para Interactive Maps


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Due to the ongoing effects of climate change, phytoplankton are likely to experience enhanced irradiance, more reduced nitrogen, and increased water acidity in the future ocean. Here, we used Thalassiosira pseudonana as a model organism to examine how phytoplankton adjust energy production and expenditure to cope with these multiple, interrelated environmental factors. Following acclimation to a matrix of irradiance, nitrogen source, and CO2 levels, the diatom's energy production and expenditures were quantified and incorporated into an energetic budget to predict how photosynthesis was affected by growth conditions. Increased light intensity and a shift from inline image to inline image led to increased energy generation, through higher rates of light capture at high light and greater investment in photosynthetic proteins when grown on inline image. Secondary energetic expenditures were adjusted modestly at different culture conditions, except that inline image utilization was systematically reduced by increasing pCO2. The subsequent changes in element stoichiometry, biochemical composition, and release of dissolved organic compounds may have important implications for marine biogeochemical cycles. The predicted effects of changing environmental conditions on photosynthesis, made using an energetic budget, were in good agreement with observations at low light, when energy is clearly limiting, but the energetic budget over-predicts the response to inline image at high light, which might be due to relief of energetic limitations and/or increased percentage of inactive photosystem II at high light. Taken together, our study demonstrates that energetic budgets offered significant insight into the response of phytoplankton energy metabolism to the changing environment and did a reasonable job predicting them.

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Ocean acidification (OA) effects on larvae are partially attributed for the rapidly declining oyster production in the Pacific Northwest region of the United States. This OA effect is a serious concern in SE Asia, which produces >80% of the world's oysters. Because climate-related stressors rarely act alone, we need to consider OA effects on oysters in combination with warming and reduced salinity. Here, the interactive effects of these three climate-related stressors on the larval growth of the Pacific oyster, Crassostrea gigas, were examined. Larvae were cultured in combinations of temperature (24 and 30 °C), pH (8.1 and 7.4), and salinity (15 psu and 25 psu) for 58 days to the early juvenile stage. Decreased pH (pH 7.4), elevated temperature (30 °C), and reduced salinity (15 psu) significantly delayed pre- and post-settlement growth. Elevated temperature lowered the larval lipid index, a proxy for physiological quality, and negated the negative effects of decreased pH on attachment and metamorphosis only in a salinity of 25 psu. The negative effects of multiple stressors on larval metamorphosis were not due to reduced size or depleted lipid reserves at the time of metamorphosis. Our results supported the hypothesis that the C. gigas larvae are vulnerable to the interactions of OA with reduced salinity and warming in Yellow Sea coastal waters now and in the future.

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The video FireMovie_2000-2011.avi shows an animation with all MODIS fire product maps of the area sequenced over time. Colors in the video describe MODIS classes as follows: MODIS classification and color scale: Class 0 - not processed - Dark blue (1 frame) Class 3 - water - Light Blue (rivers and some lakes) Class 4 - clouds - Green blue Class 5 - non fire land - Yellow green Class 8 - nominal confidence fire - Red Class 9 - high confidence fire - Dark red

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Ocean warming and acidification are serious threats to marine life. While each stressor alone has been studied in detail, their combined effects on the outcome of ecological interactions are poorly understood. We measured predation rates and predator selectivity of two closely related species of damselfish exposed to a predatory dottyback. We found temperature and CO2 interacted synergistically on overall predation rate, but antagonistically on predator selectivity. Notably, elevated CO2 or temperature alone reversed predator selectivity, but the interaction between the two stressors cancelled selectivity. Routine metabolic rates of the two prey showed strong species differences in tolerance to CO2 and not temperature, but these differences did not correlate with recorded mortality. This highlights the difficulty of linking species-level physiological tolerance to resulting ecological outcomes. This study is the first to document both synergistic and antagonistic effects of elevated CO2 and temperature on a crucial ecological process like predator-prey dynamics.

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The Self-OrganizingMap (SOM) is a neural network model that performs an ordered projection of a high dimensional input space in a low-dimensional topological structure. The process in which such mapping is formed is defined by the SOM algorithm, which is a competitive, unsupervised and nonparametric method, since it does not make any assumption about the input data distribution. The feature maps provided by this algorithm have been successfully applied for vector quantization, clustering and high dimensional data visualization processes. However, the initialization of the network topology and the selection of the SOM training parameters are two difficult tasks caused by the unknown distribution of the input signals. A misconfiguration of these parameters can generate a feature map of low-quality, so it is necessary to have some measure of the degree of adaptation of the SOM network to the input data model. The topologypreservation is the most common concept used to implement this measure. Several qualitative and quantitative methods have been proposed for measuring the degree of SOM topologypreservation, particularly using Kohonen's model. In this work, two methods for measuring the topologypreservation of the Growing Cell Structures (GCSs) model are proposed: the topographic function and the topology preserving map

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The successful experience of the Jose Cabrera Nuclear Power Plant Interactive Graphical Simulator implementation in the Nuclear Engineering Department in the Universidad Polite´cnica de Madrid, for the Education and Training of nuclear engineers is shown in this paper. The paper starts with the objectives and the description of the Simulator Aula, and the methodology of work following the recommendations of the IAEA for the use of nuclear reactor simulators for education. The practices and material prepared for the students, as well as the operational and accident situations simulated are provided.

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The adaptation to the European Higher Education Area (EHEA) is becoming a great challenge for the University Community, especially for its teaching and research staff, which is involved actively in the teaching-learning process. It is also inducing a paradigm change for lecturers and students. Among the methodologies used for processes of teaching innovation, system thinking plays an important role when working mainly with mind maps, and is focused to highlighting the essence of the knowledge, allowing its visual representation. In this paper, a method for using these mind maps for organizing a particular subject is explained. This organization is completed with the definition of duration, precedence relationships and resources for each of these activities, as well as with their corresponding monitoring. Mind maps are generated by means of the MINDMANAGER package whilst Ms-PROJECT is used for establishing tasks relationships, durations, resources, and monitoring. Summarizing, a procedure and the necessary set of applications for self organizing and managing (timed) scheduled teaching tasks has been described in this paper.