301 research outputs found
Global surface-ocean pCO2 and seaâair CO2 flux variability from an observation-driven ocean mixed-layer scheme
A temporally and spatially resolved estimate of the global surface-ocean CO<sub>2</sub> partial pressure field and the seaâair CO<sub>2</sub> flux is presented, obtained by fitting a simple data-driven diagnostic model of ocean mixed-layer biogeochemistry to surface-ocean CO<sub>2</sub> partial pressure data from the SOCAT v1.5 database. Results include seasonal, interannual, and short-term (daily) variations. In most regions, estimated seasonality is well constrained from the data, and compares well to the widely used monthly climatology by Takahashi et al. (2009). Comparison to independent data tentatively supports the slightly higher seasonal variations in our estimates in some areas. We also fitted the diagnostic model to atmospheric CO<sub>2</sub> data. The results of this are less robust, but in those areas where atmospheric signals are not strongly influenced by land flux variability, their seasonality is nevertheless consistent with the results based on surface-ocean data. From a comparison with an independent seasonal climatology of surface-ocean nutrient concentration, the diagnostic model is shown to capture relevant surface-ocean biogeochemical processes reasonably well. Estimated interannual variations will be presented and discussed in a companion paper
Translucent zirconia in the ceramic scenario for monolithic restorations: A flexural strength and translucency comparison test
Objective: To compare three different compositions of Yttria-Tetragonal Zirconia Polycrystal (Y-TZP) ceramic and a lithium disilicate ceramic in terms of flexural strength and translucency. Methods: Three zirconia materials of different composition and translucency, Aadva ST [ST], Aadva EI [EI] and Aadva NT [NT](GC Tech, Leuven, Belgium) were cut with a slow speed diamond saw into beams and tabs in order to obtain, after sintering, dimensions of 1.2 Ă 4.0 Ă 15.0 mm and 15.0 Ă 15.0 Ă 1.0 mm respectively. Blocks of IPS e.max CAD LT were cut and crystallized in the same shapes and dimensions and used as a reference group [LD]. Beams (n = 15) were tested in a universal testing machine for three-point bending strength. Critical fracture load was recorded in N, flexural strength (Ï in MPa), Weibull modulus (m) and Weibull characteristic strength (Ï0 in MPa) were then calculated. Tabs (n = 10) were measured with a spectrophotometer equipped with an integrating sphere. Contrast Ratios were calculated as CR = Yb/Yw. SEM of thermally etched samples coupled with lineal line analysis (n = 6) was used to measure the tested zirconia grain size. Data were statistically analyzed. Results: Differences in translucency, flexural strength and grain size were found to be statistically significant. CR increased and flexural strength decreased in the following order ST(Ï 1215 ± 190 MPa, CR 0.74 ± 0.01) > EI(Ï 983 ± 182 MPa, CR 0.69 ± 0.01) > NT(Ï 539 ± 66 MPa, CR 0.65 ± 0.01) > LD (Ï 377 ± 39 Mpa, CR 0.56 ± 0.02). The average grain size was different for the three zirconia samples with NT(558 ± 38 nm) > ST(445 ± 34 nm) > EI(284 ± 11 nm). Conclusions: The zirconia composition heavily influenced both the flexural strength and the translucency. Different percentages of Yittria and Alumina result in new materials with intermediate properties in between the conventional zirconia and lithium disilicate. Clinical indications for Zirconia Aadva NT should be limited up to three-unit span bridges
Phase transitions in contagion processes mediated by recurrent mobility patterns
Human mobility and activity patterns mediate contagion on many levels,
including the spatial spread of infectious diseases, diffusion of rumors, and
emergence of consensus. These patterns however are often dominated by specific
locations and recurrent flows and poorly modeled by the random diffusive
dynamics generally used to study them. Here we develop a theoretical framework
to analyze contagion within a network of locations where individuals recall
their geographic origins. We find a phase transition between a regime in which
the contagion affects a large fraction of the system and one in which only a
small fraction is affected. This transition cannot be uncovered by continuous
deterministic models due to the stochastic features of the contagion process
and defines an invasion threshold that depends on mobility parameters,
providing guidance for controlling contagion spread by constraining mobility
processes. We recover the threshold behavior by analyzing diffusion processes
mediated by real human commuting data.Comment: 20 pages of Main Text including 4 figures, 7 pages of Supplementary
Information; Nature Physics (2011
Quantification of ocean heat uptake from changes in atmospheric O2 and CO2 composition
The ocean is the main source of thermal inertia in the climate system. Ocean heat uptake during recent decades has been quantified using ocean temperature measurements. However, these estimates all use the same imperfect ocean dataset and share additional uncertainty due to sparse coverage, especially before 2007. Here, we provide an independent estimate by using measurements of atmospheric oxygen (O2) and carbon dioxide (CO2) â levels of which increase as the ocean warms and releases gases â as a whole ocean thermometer. We show that the ocean gained 1.29â±â0.79âĂâ1022 Joules of heat per year between 1991 and 2016, equivalent to a planetary energy imbalance of 0.80â±â0.49âW watts per square metre of Earthâs surface. We also find that the ocean-warming effect that led to the outgassing of O2 and CO2 can be isolated from the direct effects of anthropogenic emissions and CO2 sinks. Our result â which relies on high-precision O2 atmospheric measurements dating back to 1991 â leverages an integrative Earth system approach and provides much needed independent confirmation of heat uptake estimated from ocean data
The effect of travel restrictions on the spread of a moderately contagious disease
BACKGROUND: Much research in epidemiology has been focused on evaluating conventional methods of control strategies in the event of an epidemic or pandemic. Travel restrictions are often suggested as an efficient way to reduce the spread of a contagious disease that threatens public health, but few papers have studied in depth the effects of travel restrictions. In this study, we investigated what effect different levels of travel restrictions might have on the speed and geographical spread of an outbreak of a disease similar to severe acute respiratory syndrome (SARS). METHODS: We used a stochastic simulation model incorporating survey data of travel patterns between municipalities in Sweden collected over 3 years. We tested scenarios of travel restrictions in which travel over distances >50 km and 20 km would be banned, taking into account different levels of compliance. RESULTS: We found that a ban on journeys >50 km would drastically reduce the speed and geographical spread of outbreaks, even when compliance is < 100%. The result was found to be robust for different rates of intermunicipality transmission intensities. CONCLUSION: This study supports travel restrictions as an effective way to mitigate the effect of a future disease outbreak
Surface and Temporal Biosignatures
Recent discoveries of potentially habitable exoplanets have ignited the
prospect of spectroscopic investigations of exoplanet surfaces and atmospheres
for signs of life. This chapter provides an overview of potential surface and
temporal exoplanet biosignatures, reviewing Earth analogues and proposed
applications based on observations and models. The vegetation red-edge (VRE)
remains the most well-studied surface biosignature. Extensions of the VRE,
spectral "edges" produced in part by photosynthetic or nonphotosynthetic
pigments, may likewise present potential evidence of life. Polarization
signatures have the capacity to discriminate between biotic and abiotic "edge"
features in the face of false positives from band-gap generating material.
Temporal biosignatures -- modulations in measurable quantities such as gas
abundances (e.g., CO2), surface features, or emission of light (e.g.,
fluorescence, bioluminescence) that can be directly linked to the actions of a
biosphere -- are in general less well studied than surface or gaseous
biosignatures. However, remote observations of Earth's biosphere nonetheless
provide proofs of concept for these techniques and are reviewed here. Surface
and temporal biosignatures provide complementary information to gaseous
biosignatures, and while likely more challenging to observe, would contribute
information inaccessible from study of the time-averaged atmospheric
composition alone.Comment: 26 pages, 9 figures, review to appear in Handbook of Exoplanets.
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Assessing fossil fuel COâ emissions in California using atmospheric observations and models
Analysis systems incorporating atmospheric observations could provide a powerful tool for validating fossil fuel CO2 (ffCO2) emissions reported for individual regions, provided that fossil fuel sources can be separated from other CO2 sources or sinks and atmospheric transport can be accurately accounted for. We quantified ffCO2 by measuring radiocarbon (14C) in CO2, an accurate fossil-carbon tracer, at nine observation sites in California for three months in 2014â15. There is strong agreement between the measurements and ffCO2 simulated using a high-resolution atmospheric model and a spatiotemporally-resolved fossil fuel flux estimate. Inverse estimates of total in-state ffCO2 emissions are consistent with the California Air Resources Board's reported ffCO2 emissions, providing tentative validation of California's reported ffCO2 emissions in 2014â15. Continuing this prototype analysis system could provide critical independent evaluation of reported ffCO2 emissions and emissions reductions in California, and the system could be expanded to other, more data-poor regions
Network 'small-world-ness': a quantitative method for determining canonical network equivalence
Background: Many technological, biological, social, and information networks fall into the broad class of 'small-world' networks: they have tightly interconnected clusters of nodes, and a shortest mean path length that is similar to a matched random graph (same number of nodes and edges). This semi-quantitative definition leads to a categorical distinction ('small/not-small') rather than a quantitative, continuous grading of networks, and can lead to uncertainty about a network's small-world status. Moreover, systems described by small-world networks are often studied using an equivalent canonical network model-the Watts-Strogatz (WS) model. However, the process of establishing an equivalent WS model is imprecise and there is a pressing need to discover ways in which this equivalence may be quantified.
Methodology/Principal Findings: We defined a precise measure of 'small-world-ness' S based on the trade off between high local clustering and short path length. A network is now deemed a 'small-world' if S. 1-an assertion which may be tested statistically. We then examined the behavior of S on a large data-set of real-world systems. We found that all these systems were linked by a linear relationship between their S values and the network size n. Moreover, we show a method for assigning a unique Watts-Strogatz (WS) model to any real-world network, and show analytically that the WS models associated with our sample of networks also show linearity between S and n. Linearity between S and n is not, however, inevitable, and neither is S maximal for an arbitrary network of given size. Linearity may, however, be explained by a common limiting growth process.
Conclusions/Significance: We have shown how the notion of a small-world network may be quantified. Several key properties of the metric are described and the use of WS canonical models is placed on a more secure footing
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