77 resultados para Indicators of global mindset


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This study explored transient changes in EEG microstates and spatial Omega complexity associated with changes in multistable perception. 21-channel EEG was recorded from 13 healthy subjects viewing an alternating dot pattern that induced illusory motion with ambiguous direction. Baseline epochs with stable motion direction were compared to epochs immediately preceding stimuli that were perceived with changed motion direction ('reference stimuli'). About 750 ms before reference stimuli, Omega complexity decreased as compared to baseline, and two of four classes of EEG microstates changed their probability of occurrence. About 300 ms before reference stimuli, Omega complexity increased and the previous deviations of EEG microstates were reversed. Given earlier results on Omega complexity and microstates, these sub-second EEG changes might parallel longer-lasting fluctuations in vigilance. Assumedly, the discontinuities of illusory motion thus occur during sub-second dips in arousal, and the following reconstruction of the illusion coincides with a state of relative over-arousal.

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Methylation of cytosine residues at CpG sites is involved in various biological processes to control gene regulation and gene expression. Global DNA methylation is changed in different tumors and in cloned animals. Global DNA methylation can be accurately quantified by dot blot analysis with infrared (IR) fluorophores. Methylated lambda DNA was used as model DNA to develop and validate an immunochemical assay with IR fluorescence detection. Two different IR fluorophores were used, one to detect 5-methylcytosine and another to account for DNA loading. A sensitive infrared detection method was established which is suitable for accurate and reproducible quantification of global DNA methylation across a wide dynamic range. This method was subsequently employed to quantify global DNA methylation in liver and in muscle tissues of boars which have received either a control diet or a methyl supplemented diet in an ongoing study. A significant difference in global DNA methylation is indicated in muscle but not in liver tissue between the two groups of boars.

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Global complexity of spontaneous brain electric activity was studied before and after chewing gum without flavor and with 2 different flavors. One-minute, 19-channel, eyes-closed electroencephalograms (EEG) were recorded from 20 healthy males before and after using 3 types of chewing gum: regular gum containing sugar and aromatic additives, gum containing 200 mg theanine (a constituent of Japanese green tea), and gum base (no sugar, no aromatic additives); each was chewed for 5 min in randomized sequence. Brain electric activity was assessed through Global Omega (Ω)-Complexity and Global Dimensional Complexity (GDC), quantitative measures of complexity of the trajectory of EEG map series in state space; their differences from pre-chewing data were compared across gum-chewing conditions. Friedman Anova (p < 0.043) showed that effects on Ω-Complexity differed significantly between conditions and differences were maximal between gum base and theanine gum. No differences were found using GDC. Global Omega-Complexity appears to be a sensitive measure for subtle, central effects of chewing gum with and without flavor.

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The ancient southern highlands on Mars (~3.5 Gyr old) contain > 600 regions that display spectral evidence in the infrared for the presence of chloride-bearing materials. Many of these locations were previously reported to display polygonal cracking patterns. We studied more than 80 of the chloride-bearing terrains using high-resolution (0.25-0.5 m/pixel) images, as well as near-infrared spectral data, to characterize the surface textures and the associated cracking patterns and mineralogies. Our study indicates that ~75% of the studied locations display polygonal cracks that resemble desiccation cracks, while some resemble salt expansion/thrust polygons. Furthermore, we detect, spectrally, the presence of smectites in association with ~30% of the studied fractured terrains. We note that smectites are a special class of swelling clay minerals that can induce formation of large desiccation cracks. As such, we suggest that the cracking patterns are indicative of the presence of smectite phyllosilicates even in the absence of spectral confirmation. Our results suggest that many chloride-bearing terrains have a lacustrine origin and a geologic setting similar to playas on Earth. Such locations would have contained ephemeral lakes that may have undergone repeated cycles of desiccation and recharging by a near-surface fluctuating water table in order to account for the salt-phyllosilicates associations. These results have notable implications for the ancient hydrology of Mars. We propose that the morphologies and sizes of the polygonal cracks can be used as paleoenvironmental, as well as lithological, indicators that could be helpful in planning future missions.

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The WOCAT network has collected, documented, and assessed more than 350 case studies on promising and good practices of SLM. Information on on- and off-site benefits of different SLM types, as well as on investment and maintenance costs is available, sometimes in quantitative and often in qualitative form. The objective of the present paper is to analyse what kind of economic benefits accrue to local stakeholders, and to better understand how these benefits compare to investment and maintenance costs. The large majority of the technologies contained in the database are perceived by land users as having positive benefits that outweigh costs in the long term. About three quarters of them also have positive or at least neutral benefits in the short term. The analysis shows that many SLM measures exist which can generate important benefits to land users, but also to other stakeholders. However, methodological issues need to be tackled and further quantitative and qualitative data are needed to better understand and support the adoption of SLM measures. Keywords: Sustainable Land Management, Costs, Benefits, Technologies

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Computational network analysis provides new methods to analyze the human connectome. Brain structural networks can be characterized by global and local metrics that recently gave promising insights for diagnosis and further understanding of neurological, psychiatric and neurodegenerative disorders. In order to ensure the validity of results in clinical settings the precision and repeatability of the networks and the associated metrics must be evaluated. In the present study, nineteen healthy subjects underwent two consecutive measurements enabling us to test reproducibility of the brain network and its global and local metrics. As it is known that the network topology depends on the network density, the effects of setting a common density threshold for all networks were also assessed. Results showed good to excellent repeatability for global metrics, while for local metrics it was more variable and some metrics were found to have locally poor repeatability. Moreover, between subjects differences were slightly inflated when the density was not fixed. At the global level, these findings confirm previous results on the validity of global network metrics as clinical biomarkers. However, the new results in our work indicate that the remaining variability at the local level as well as the effect of methodological characteristics on the network topology should be considered in the analysis of brain structural networks and especially in networks comparisons.

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Methane is an important greenhouse gas, responsible for about 20 of the warming induced by long-lived greenhouse gases since pre-industrial times. By reacting with hydroxyl radicals, methane reduces the oxidizing capacity of the atmosphere and generates ozone in the troposphere. Although most sources and sinks of methane have been identified, their relative contributions to atmospheric methane levels are highly uncertain. As such, the factors responsible for the observed stabilization of atmospheric methane levels in the early 2000s, and the renewed rise after 2006, remain unclear. Here, we construct decadal budgets for methane sources and sinks between 1980 and 2010, using a combination of atmospheric measurements and results from chemical transport models, ecosystem models, climate chemistry models and inventories of anthropogenic emissions. The resultant budgets suggest that data-driven approaches and ecosystem models overestimate total natural emissions. We build three contrasting emission scenarios � which differ in fossil fuel and microbial emissions � to explain the decadal variability in atmospheric methane levels detected, here and in previous studies, since 1985. Although uncertainties in emission trends do not allow definitive conclusions to be drawn, we show that the observed stabilization of methane levels between 1999 and 2006 can potentially be explained by decreasing-to-stable fossil fuel emissions, combined with stable-to-increasing microbial emissions. We show that a rise in natural wetland emissions and fossil fuel emissions probably accounts for the renewed increase in global methane levels after 2006, although the relative contribution of these two sources remains uncertain.

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The Wetland and Wetland CH4 Intercomparison of Models Project (WETCHIMP) was created to evaluate our present ability to simulate large-scale wetland characteristics and corresponding methane (CH4) emissions. A multi-model comparison is essential to evaluate the key uncertainties in the mechanisms and parameters leading to methane emissions. Ten modelling groups joined WETCHIMP to run eight global and two regional models with a common experimental protocol using the same climate and atmospheric carbon dioxide (CO2) forcing datasets. We reported the main conclusions from the intercomparison effort in a companion paper (Melton et al., 2013). Here we provide technical details for the six experiments, which included an equilibrium, a transient, and an optimized run plus three sensitivity experiments (temperature, precipitation, and atmospheric CO2 concentration). The diversity of approaches used by the models is summarized through a series of conceptual figures, and is used to evaluate the wide range of wetland extent and CH4 fluxes predicted by the models in the equilibrium run. We discuss relationships among the various approaches and patterns in consistencies of these model predictions. Within this group of models, there are three broad classes of methods used to estimate wetland extent: prescribed based on wetland distribution maps, prognostic relationships between hydrological states based on satellite observations, and explicit hydrological mass balances. A larger variety of approaches was used to estimate the net CH4 fluxes from wetland systems. Even though modelling of wetland extent and CH4 emissions has progressed significantly over recent decades, large uncertainties still exist when estimating CH4 emissions: there is little consensus on model structure or complexity due to knowledge gaps, different aims of the models, and the range of temporal and spatial resolutions of the models.

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Global wetlands are believed to be climate sensitive, and are the largest natural emitters of methane (CH4). Increased wetland CH4 emissions could act as a positive feedback to future warming. The Wetland and Wetland CH4 Inter-comparison of Models Project (WETCHIMP) investigated our present ability to simulate large-scale wetland characteristics and corresponding CH4 emissions. To ensure inter-comparability, we used a common experimental protocol driving all models with the same climate and carbon dioxide (CO2) forcing datasets. The WETCHIMP experiments were conducted for model equilibrium states as well as transient simulations covering the last century. Sensitivity experiments investigated model response to changes in selected forcing inputs (precipitation, temperature, and atmospheric CO2 concentration). Ten models participated, covering the spectrum from simple to relatively complex, including models tailored either for regional or global simulations. The models also varied in methods to calculate wetland size and location, with some models simulating wetland area prognostically, while other models relied on remotely sensed inundation datasets, or an approach intermediate between the two. Four major conclusions emerged from the project. First, the suite of models demonstrate extensive disagreement in their simulations of wetland areal extent and CH4 emissions, in both space and time. Simple metrics of wetland area, such as the latitudinal gradient, show large variability, principally between models that use inundation dataset information and those that independently determine wetland area. Agreement between the models improves for zonally summed CH4 emissions, but large variation between the models remains. For annual global CH4 emissions, the models vary by ±40% of the all-model mean (190 Tg CH4 yr−1). Second, all models show a strong positive response to increased atmospheric CO2 concentrations (857 ppm) in both CH4 emissions and wetland area. In response to increasing global temperatures (+3.4 °C globally spatially uniform), on average, the models decreased wetland area and CH4 fluxes, primarily in the tropics, but the magnitude and sign of the response varied greatly. Models were least sensitive to increased global precipitation (+3.9 % globally spatially uniform) with a consistent small positive response in CH4 fluxes and wetland area. Results from the 20th century transient simulation show that interactions between climate forcings could have strong non-linear effects. Third, we presently do not have sufficient wetland methane observation datasets adequate to evaluate model fluxes at a spatial scale comparable to model grid cells (commonly 0.5°). This limitation severely restricts our ability to model global wetland CH4 emissions with confidence. Our simulated wetland extents are also difficult to evaluate due to extensive disagreements between wetland mapping and remotely sensed inundation datasets. Fourth, the large range in predicted CH4 emission rates leads to the conclusion that there is both substantial parameter and structural uncertainty in large-scale CH4 emission models, even after uncertainties in wetland areas are accounted for.

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“Cultural diversity” has become one of the latest buzzwords on the international policymaking scene. It is employed in various contexts – sometimes as a term close to “biological diversity”, at other times as correlated to the “exception culturelle” and most often, as a generic concept that is mobilised to counter the perceived negative effects of economic globalisation. While no one has yet provided a precise definition of what cultural diversity is, what we can observe is the emergence of the notion of cultural diversity as incorporating a distinct set of policy objectives and choices at the global level. These decisions are not confined, as one might have expected, to cultural policymaking, but rather spill over to multiple governance domains because of the complex linkages inherent to the simultaneous pursuit of economic and other societal goals that cultural diversity encompasses and has effects on. Accounting for these intricate interdependencies, the present article clarifies the origins of the concept of cultural diversity as understood in global law and traces its evolution over time. Observing the dynamics of the concept and the surrounding political and legal developments, the article explores its justification and overall impact on the global legal regime, as well as its discrete effects on different domains of policymaking, such as media, intellectual property and culture. While the analysis is legal in essence, the article is meant to speak also to a broader transdisciplinary public. The article is part of the speacial issue on ethnic diversity and cultural pluralism, which is available under the creative commons licence: http://www.mdpi.com/journal/diversity/special_issues/ethnic-diversity/.

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Simulating the spatio-temporal dynamics of inundation is key to understanding the role of wetlands under past and future climate change. Earlier modelling studies have mostly relied on fixed prescribed peatland maps and inundation time series of limited temporal coverage. Here, we describe and assess the the Dynamical Peatland Model Based on TOPMODEL (DYPTOP), which predicts the extent of inundation based on a computationally efficient TOPMODEL implementation. This approach rests on an empirical, grid-cell-specific relationship between the mean soil water balance and the flooded area. DYPTOP combines the simulated inundation extent and its temporal persistency with criteria for the ecosystem water balance and the modelled peatland-specific soil carbon balance to predict the global distribution of peatlands. We apply DYPTOP in combination with the LPX-Bern DGVM and benchmark the global-scale distribution, extent, and seasonality of inundation against satellite data. DYPTOP successfully predicts the spatial distribution and extent of wetlands and major boreal and tropical peatland complexes and reveals the governing limitations to peatland occurrence across the globe. Peatlands covering large boreal lowlands are reproduced only when accounting for a positive feedback induced by the enhanced mean soil water holding capacity in peatland-dominated regions. DYPTOP is designed to minimize input data requirements, optimizes computational efficiency and allows for a modular adoption in Earth system models.