The Roles of Video in the Design, Development, and Use of Interactive Electronic Conference Proceedings

In this paper, we discuss the design and development of a particular type of electronic publication that has gained recent popularity: electronic conference proceedings. We suggest that modern electronic proceedings should provide a high degree of interactivity. To support such interactivity, proceedings should include an extensive collection of features and diverse multimedia components. Features appropriate for electronic proceedings include annotation, presentation, and retrieval mechanisms. Conference papers and multimedia reproductions of conference presentations with features that allow readers to manipulate these reproductions particularly enhance the interactivity of electronic proceedings. Experience from interactive proceedings the authors have designed is also discussed. Special attention is given to the multiple roles video elements can and should play in interactive proceedings

Causal hierarchy within the thalamo-cortical network in spike and wave discharges

Background: Generalised spike wave (GSW) discharges are the electroencephalographic (EEG) hallmark of absence seizures, clinically characterised by a transitory interruption of ongoing activities and impaired consciousness, occurring during states of reduced awareness. Several theories have been proposed to explain the pathophysiology of GSW discharges and the role of thalamus and cortex as generators. In this work we extend the existing theories by hypothesizing a role for the precuneus, a brain region neglected in previous works on GSW generation but already known to be linked to consciousness and awareness. We analysed fMRI data using dynamic causal modelling (DCM) to investigate the effective connectivity between precuneus, thalamus and prefrontal cortex in patients with GSW discharges. Methodology and Principal Findings: We analysed fMRI data from seven patients affected by Idiopathic Generalized Epilepsy (IGE) with frequent GSW discharges and significant GSW-correlated haemodynamic signal changes in the thalamus, the prefrontal cortex and the precuneus. Using DCM we assessed their effective connectivity, i.e. which region drives another region. Three dynamic causal models were constructed: GSW was modelled as autonomous input to the thalamus (model A), ventromedial prefrontal cortex (model B), and precuneus (model C). Bayesian model comparison revealed Model C (GSW as autonomous input to precuneus), to be the best in 5 patients while model A prevailed in two cases. At the group level model C dominated and at the population-level the p value of model C was ∼1. Conclusion: Our results provide strong evidence that activity in the precuneus gates GSW discharges in the thalamo-(fronto) cortical network. This study is the first demonstration of a causal link between haemodynamic changes in the precuneus - an index of awareness - and the occurrence of pathological discharges in epilepsy. © 2009 Vaudano et al

Vertical profiles of CO\u3csub\u3e2\u3c/sub\u3e above eastern Amazonia suggest a net carbon flux to the atmosphere and balanced biosphere between 2000 and 2009

From 2000 until January 2010 vertical profiles were collected above eastern Amazonia to help determine regional-scale (∼105–106 km2) fluxes of carbon cycle-related greenhouse gases. Samples were collected aboard light aircraft between the surface and 4.3 km and a column integration technique was used to determine the CO2 flux. Measured CO2 profiles were differenced from the CO2 background determined from measurements in the tropical Atlantic. The observed annual flux between the coast and measurement sites was 0.40 ± 0.27 gC m−2 d−1 (90% confidence interval using a bootstrap analysis). The wet season (January–June) mean flux was 0.44 ± 0.38 gC m−2 d−1 (positive fluxes defined as a source to the atmosphere) and the dry season mean flux was 0.35 ± 0.17 gC m−2 d−1 (July–December). The observed flux variability is high, principally in the wet season. The influence of biomass burning has been removed using co-measured CO, and revealed the presence of a significant dry season sink. The annual mean vegetation flux, after the biomass burning correction, was 0.02 ± 0.27 gC m−2 d−1, and a clear sink was observed between August and November of −0.70 ± 0.21 gC m−2 d−1 where for all of the dry season it was −0.24 ± 0.17 gC m−2 d−1

An agent-based approach to assess drivers’ interaction with pre-trip information systems.

This article reports on the practical use of a multi-agent microsimulation framework to address the issue of assessing drivers’ responses to pretrip information systems. The population of drivers is represented as a community of autonomous agents, and travel demand results from the decision-making deliberation performed by each individual of the population as regards route and departure time. A simple simulation scenario was devised, where pretrip information was made available to users on an individual basis so that its effects at the aggregate level could be observed. The simulation results show that the overall performance of the system is very likely affected by exogenous information, and these results are ascribed to demand formation and network topology. The expressiveness offered by cognitive approaches based on predicate logics, such as the one used in this research, appears to be a promising approximation to fostering more complex behavior modelling, allowing us to represent many of the mental aspects involved in the deliberation process

TransCom model simulations of CH₄ and related species: linking transport, surface flux and chemical loss with CH₄ variability in the troposphere and lower stratosphere

A chemistry-transport model (CTM) intercomparison experiment (TransCom-CH₄) has been designed to investigate the roles of surface emissions, transport and chemical loss in simulating the global methane distribution. Model simulations were conducted using twelve models and four model variants and results were archived for the period of 1990–2007. All but one model transports were driven by reanalysis products from 3 different meteorological agencies. The transport and removal of CH₄ in six different emission scenarios were simulated, with net global emissions of 513 ± 9 and 514 ± 14 Tg CH₄ yr[superscript −1] for the 1990s and 2000s, respectively. Additionally, sulfur hexafluoride (SF₆) was simulated to check the interhemispheric transport, radon ([supercript 222]Rn) to check the subgrid scale transport, and methyl chloroform (CH₃CCl₃) to check the chemical removal by the tropospheric hydroxyl radical (OH). The results are compared to monthly or annual mean time series of CH₄, SF₆ and CH₃CCl₃ measurements from 8 selected background sites, and to satellite observations of CH₄ in the upper troposphere and stratosphere. Most models adequately capture the vertical gradients in the stratosphere, the average long-term trends, seasonal cycles, interannual variations (IAVs) and interhemispheric (IH) gradients at the surface sites for SF₆, CH₃CCl₃ and CH₄. The vertical gradients of all tracers between the surface and the upper troposphere are consistent within the models, revealing vertical transport differences between models. An average IH exchange time of 1.39 ± 0.18 yr is derived from SF₆ time series. Sensitivity simulations suggest that the estimated trends in exchange time, over the period of 1996–2007, are caused by a change of SF₆ emissions towards the tropics. Using six sets of emission scenarios, we show that the decadal average CH₄ growth rate likely reached equilibrium in the early 2000s due to the flattening of anthropogenic emission growth since the late 1990s. Up to 60% of the IAVs in the observed CH₄ concentrations can be explained by accounting for the IAVs in emissions, from biomass burning and wetlands, as well as meteorology in the forward models. The modeled CH₄ budget is shown to depend strongly on the troposphere-stratosphere exchange rate and thus on the model's vertical grid structure and circulation in the lower stratosphere. The 15-model median CH₄ and CH₃CCl₃ atmospheric lifetimes are estimated to be 9.99 ± 0.08 and 4.61 ± 0.13 yr, respectively, with little IAV due to transport and temperature.United States. National Aeronautics and Space Administration (NASA-AGAGE Grant NNX11AF17G

Off-line algorithm for calculation of vertical tracer transport in the troposphere due to deep convection

A modified cumulus convection parametrisation scheme is presented. This scheme computes the mass of air transported upward in a cumulus cell using conservation of moisture and a detailed distribution of convective precipitation provided by a reanalysis dataset. The representation of vertical transport within the scheme includes entrainment and detrainment processes in convective updrafts and downdrafts. Output from the proposed parametrisation scheme is employed in the National Institute for Environmental Studies (NIES) global chemical transport model driven by JRA-25/JCDAS reanalysis. The simulated convective precipitation rate and mass fluxes are compared with observations and reanalysis data. A simulation of the short-lived tracer [superscript 222]Rn is used to further evaluate the performance of the cumulus convection scheme. Simulated distributions of [superscript 222]Rn are evaluated against observations at the surface and in the free troposphere, and compared with output from models that participated in the TransCom-CH4 Transport Model Intercomparison. From this comparison, we demonstrate that the proposed convective scheme in general is consistent with observed and modeled results

Decreasing seasonal cycle amplitude of methane in the northern high latitudes being driven by lower-latitude changes in emissions and transport

Atmospheric methane (CH4) concentrations are rising, which are expected to lead to a corresponding increase in the global seasonal cycle amplitude (SCA) – the difference between its seasonal maximum and minimum values. The reaction between CH4 and its main sink, OH, is dependent on the amount of CH4 and OH in the atmosphere. The concentration of OH varies seasonally, and due to the increasing burden of CH4 in the atmosphere, it is expected that the SCA of CH4 will increase due to the increased removal of CH4 through a reaction with OH in the atmosphere. Spatially varying changes in the SCA could indicate long-term persistent variations in the seasonal sources and sinks, but such SCA changes have not been investigated. Here we use surface flask measurements and a 3D chemical transport model (TOMCAT) to diagnose changes in the SCA of atmospheric CH4 between 1995–2020 and attribute the changes regionally to contributions from different sectors. We find that the observed SCA decreased by 4 ppb (7.6 %) in the northern high latitudes (NHLs; 60–90∘ N), while the SCA increased globally by 2.5 ppb (6.5 %) during this time period. TOMCAT reproduces the change in the SCA at observation sites across the globe. Therefore, we use it to attribute regions which are contributing to the changes in the NHL SCA, which shows an unexpected change in the SCA that differs from the rest of the world. We find that well-mixed background CH4, likely from emissions originating in, and transported from, more southerly latitudes has the largest impact on the decreasing SCA in the NHLs (56.5 % of total contribution to NHLs). In addition to the background CH4, recent emissions from Canada, the Middle East, and Europe contribute 16.9 %, 12.1 %, and 8.4 %, respectively, to the total change in the SCA in the NHLs. The remaining contributions are due to changes in emissions and transport from other regions. The three largest regional contributions are driven by increases in summer emissions from the Boreal Plains in Canada, decreases in winter emissions across Europe, and a combination of increases in summer emissions and decreases in winter emissions over the Arabian Peninsula and Caspian Sea in the Middle East. These results highlight that changes in the observed seasonal cycle can be an indicator of changing emission regimes in local and non-local regions, particularly in the NHL, where the change is counterintuitive.</p

Impact of transport model errors on the global and regional methane emissions estimated by inverse modelling

A modelling experiment has been conceived to assess the impact of transport model errors on methane emissions estimated in an atmospheric inversion system. Synthetic methane observations, obtained from 10 different model outputs from the international TransCom-CH[subscript 4] model inter-comparison exercise, are combined with a prior scenario of methane emissions and sinks, and integrated into the three-component PYVAR-LMDZ-SACS (PYthon VARiational-Laboratoire de Météorologie Dynamique model with Zooming capability-Simplified Atmospheric Chemistry System) inversion system to produce 10 different methane emission estimates at the global scale for the year 2005. The same methane sinks, emissions and initial conditions have been applied to produce the 10 synthetic observation datasets. The same inversion set-up (statistical errors, prior emissions, inverse procedure) is then applied to derive flux estimates by inverse modelling. Consequently, only differences in the modelling of atmospheric transport may cause differences in the estimated fluxes. In our framework, we show that transport model errors lead to a discrepancy of 27 Tg yr[superscript −1] at the global scale, representing 5% of total methane emissions. At continental and annual scales, transport model errors are proportionally larger than at the global scale, with errors ranging from 36 Tg yr[superscript −1] in North America to 7 Tg yr[superscript −1] in Boreal Eurasia (from 23 to 48%, respectively). At the model grid-scale, the spread of inverse estimates can reach 150% of the prior flux. Therefore, transport model errors contribute significantly to overall uncertainties in emission estimates by inverse modelling, especially when small spatial scales are examined. Sensitivity tests have been carried out to estimate the impact of the measurement network and the advantage of higher horizontal resolution in transport models. The large differences found between methane flux estimates inferred in these different configurations highly question the consistency of transport model errors in current inverse systems. Future inversions should include more accurately prescribed observation covariances matrices in order to limit the impact of transport model errors on estimated methane fluxes

Identifying and Seeing beyond Multiple Sequence Alignment Errors Using Intra-Molecular Protein Covariation

BACKGROUND: There is currently no way to verify the quality of a multiple sequence alignment that is independent of the assumptions used to build it. Sequence alignments are typically evaluated by a number of established criteria: sequence conservation, the number of aligned residues, the frequency of gaps, and the probable correct gap placement. Covariation analysis is used to find putatively important residue pairs in a sequence alignment. Different alignments of the same protein family give different results demonstrating that covariation depends on the quality of the sequence alignment. We thus hypothesized that current criteria are insufficient to build alignments for use with covariation analyses. METHODOLOGY/PRINCIPAL FINDINGS: We show that current criteria are insufficient to build alignments for use with covariation analyses as systematic sequence alignment errors are present even in hand-curated structure-based alignment datasets like those from the Conserved Domain Database. We show that current non-parametric covariation statistics are sensitive to sequence misalignments and that this sensitivity can be used to identify systematic alignment errors. We demonstrate that removing alignment errors due to 1) improper structure alignment, 2) the presence of paralogous sequences, and 3) partial or otherwise erroneous sequences, improves contact prediction by covariation analysis. Finally we describe two non-parametric covariation statistics that are less sensitive to sequence alignment errors than those described previously in the literature. CONCLUSIONS/SIGNIFICANCE: Protein alignments with errors lead to false positive and false negative conclusions (incorrect assignment of covariation and conservation, respectively). Covariation analysis can provide a verification step, independent of traditional criteria, to identify systematic misalignments in protein alignments. Two non-parametric statistics are shown to be somewhat insensitive to misalignment errors, providing increased confidence in contact prediction when analyzing alignments with erroneous regions because of an emphasis on they emphasize pairwise covariation over group covariation