5 resultados para Examples

em Digital Commons at Florida International University


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Seagrass meadows in Florida Bay and Shark Bay, contain substantial stores of both organic carbon and nutrients. Soils from both systems are predominantly calcium carbonate, with an average of 82.1% CaCO3 in Florida Bay compared to 71.3% in Shark Bay. Soils from Shark Bay had, on average, 21% higher organic carbon content and 35% higher phosphorus content than Florida Bay. Further, soils from Shark Bay had lower mean dry bulk density (0.78 ± 0.01 g mL-1) than those from Florida Bay (0.84 ± 0.02 mg mL-1). The most hypersaline regions of both bays had higher organic carbon content in surficial soils. Profiles of organic carbon and phosphorus from Florida Bay indicate that this system has experienced an increase in P delivery and primary productivity over the last century; in contrast, decreasing organic carbon and phosphorus with depth in the soil profiles in Shark Bay point to a decrease in phosphorus delivery and primary productivity over the last 1000 y. The total ecosystem stocks of stored organic C in Florida Bay averages 163.5 MgCorg ha-1, lower than the average of 243.0 MgCorg ha-1 for Shark Bay; but these values place Shark and Florida Bays among the global hotspots for organic C storage in coastal ecosystems.

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This study determined the levels of algebra problem solving skill at which worked examples promoted learning of further problem solving skill and reduction of cognitive load in college developmental algebra students. Problem solving skill was objectively measured as error production; cognitive load was subjectively measured as perceived mental effort. ^ Sixty-three Ss were pretested, received homework of worked examples or mass problem solving, and posttested. Univarate ANCOVA (covariate = previous grade) were performed on the practice and posttest data. The factors used in the analysis were practice strategy (worked examples vs. mass problem solving) and algebra problem solving skill (low vs. moderate vs. high). Students in the practice phase who studied worked examples exhibited (a) fewer errors and reduced cognitive load, at moderate skill; (b) neither fewer errors nor reduced cognitive load, at low skill; and (c) only reduced cognitive load, at high skill. In the posttest, only cognitive load was reduced. ^ The results suggested that worked examples be emphasized for developmental students with moderate problem solving skill. Areas for further research were discussed. ^

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Background: Biologists often need to assess whether unfamiliar datasets warrant the time investment required for more detailed exploration. Basing such assessments on brief descriptions provided by data publishers is unwieldy for large datasets that contain insights dependent on specific scientific questions. Alternatively, using complex software systems for a preliminary analysis may be deemed as too time consuming in itself, especially for unfamiliar data types and formats. This may lead to wasted analysis time and discarding of potentially useful data. Results: We present an exploration of design opportunities that the Google Maps interface offers to biomedical data visualization. In particular, we focus on synergies between visualization techniques and Google Maps that facilitate the development of biological visualizations which have both low-overhead and sufficient expressivity to support the exploration of data at multiple scales. The methods we explore rely on displaying pre-rendered visualizations of biological data in browsers, with sparse yet powerful interactions, by using the Google Maps API. We structure our discussion around five visualizations: a gene co-regulation visualization, a heatmap viewer, a genome browser, a protein interaction network, and a planar visualization of white matter in the brain. Feedback from collaborative work with domain experts suggests that our Google Maps visualizations offer multiple, scale-dependent perspectives and can be particularly helpful for unfamiliar datasets due to their accessibility. We also find that users, particularly those less experienced with computer use, are attracted by the familiarity of the Google Maps API. Our five implementations introduce design elements that can benefit visualization developers. Conclusions: We describe a low-overhead approach that lets biologists access readily analyzed views of unfamiliar scientific datasets. We rely on pre-computed visualizations prepared by data experts, accompanied by sparse and intuitive interactions, and distributed via the familiar Google Maps framework. Our contributions are an evaluation demonstrating the validity and opportunities of this approach, a set of design guidelines benefiting those wanting to create such visualizations, and five concrete example visualizations.

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Melt inclusions are minute magma bodies trapped within growing crystals. Their chemical compositions are useful in deciphering pre-eruptive conditions and magma evolution. The present study examined melt inclusions trapped in phenocrysts from the 3rd and 4th magmatic cycles (1869-1988) at Volcan de Colima, Mexico. Melt inclusions have highly evolved chemical compositions: 65-77% SiO2, >12% A12O3, 3-6% Na2O and K20 and less than 5.5% Fe and Mg. Major element compositions suggest that they are strongly differentiated magmas controlled by fractionation of plagioclase, opx, cpx and hornblende. Water concentrations were measured to be 2.7-3.5 wt. % in cpx hosted inclusions and 0.3-0.7 wt % in opx and plagioclase. Trace element compositions are anomalously low and inversely correlate with water. From this we deduce that Colima lavas and scorias simultaneously differentiate and degas. Moreover, hornblende rim growth rates constrain the ascent of the Colima magmas to -100 days for passive eruptions and >4 days for plinian eruptions.