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This study explores the theoretical and political potentials of Édouard Glissant’s philosophy of relation and its approach to the issues of borders, migration, and the setup of political communities as proposed by his pensée nouvelle de la frontière (new border thought), against the background of the German migration crisis of 2015. The main argument of this article is that Glissant’s work offers an alternative epistemological and normative framework through which the contemporary political issues arising around the phenomenon of repressive border regimes can be studied. To demonstrate this point, this article works with Glissant’s border thought as an analytical lens and proposes a pathway for studying the contemporary German border regime. Particular emphasis is placed on the identification of potential areas where a Glissantian politics of relation could intervene with the goal of transforming borders from impermeable walls into points of passage. By exploring the political implications of his border thought, as well as the larger philosophical context from which it emerges, while using a transdisciplinary approach that borrows from literary and political studies, this work contributes to ongoing debates in postcolonial studies on borders and borderlessness, as well as Glissant’s political legacy in the twenty-first century.
There is an ongoing discussion in the literature whether the series of sentences ‘It’s not α that did P. α and β did P.’ is acceptable or not. Whereas the homogeneity approach in Büring & Križ 2013, Križ 2016, and Križ 2017 predicts these sentences to be unacceptable, the alternative-based approach predicts acceptability depending on the predicate being interpreted distributively or non- distributively (among others, Horn 1981, Velleman et al. 2012, Renans 2016a,b). We report on three experiments testing the predictions of both types of approaches. These studies provide empirical data that not only bears on these approaches, but also allows us to distinguish between different accounts of cleft exhaustivity that might otherwise make the same predictions. The results of the three studies reported here suggest that the acceptability of clefts depends on the interpretation of the predicate, thereby posing a serious challenge to the homogeneity approach, and contributing to the ongoing discussion on the semantics of it-clefts.
The author stems from the premise that modern anthroponymy effectively incorporates data from related fields of knowledge, primarily those of cultural and political history, thus getting enlarged through interdisciplinary research. An integrated approach allows one to deduce the extra-linguistic mechanisms which lay behind anthroponymic changes. In the same vein, the present paper focuses on the dynamics within the Russian anthroponymic paradigm caused by the changing vectors of political, ideological, cultural, and religious identity in the historical perspective of the New Time (1700-1920s). The study aims to establish the connection between specific trends in naming and the precedent names, events, and texts of political, cultural, and religious life. The mechanisms of anthroponymic shifts are illustrated by the cases of individual names becoming socially significant in a particular historical context. Using interdisciplinary methods of cultural anthropology, the study builds on textual sources, primarily name indexes to the collections of works by outstanding cultural figures and scholars, and biographical dictionaries. Some examples of pragmatic naming strategies in works of art (literature, opera, cinema) are also provided. Preliminary findings reveal some major trends in the Russian anthroponymic system of the New Age such as Europeization vs. Russification, modernization vs. archaization, as well as their synthesis. These tendencies remain key up to the present day and can be traced and characteristically defined within a set (or corpus) of names relating to the particular epoch, in terms of their frequency and the parameters of the sociolinguistic distribution. The diachronic perspective of the study also supports the sociolinguistic observation that the newly introduced names, which are currently in use, have a pronounced social resonance, which is getting neutralized as their frequency increases. Further development of the topic implies, among other things, statistical verification of preliminary findings.
Narcissists are assumed to lack the motivation and ability to share and understand the mental states of others. Prior empirical research, however, has yielded inconclusive findings and has differed with respect to the specific aspects of narcissism and socioemotional cognition that have been examined. Here, we propose a differentiated facet approach that can be applied across research traditions and that distinguishes between facets of narcissism (agentic vs. antagonistic) on the one hand, and facets of socioemotional cognition ability (SECA; self-perceived vs. actual) on the other. Using five nonclinical samples in two studies (total N = 602), we investigated the effect of facets of grandiose narcissism on aspects of socioemotional cognition across measures of affective and cognitive empathy, Theory of Mind, and emotional intelligence, while also controlling for general reasoning ability. Across both studies, agentic facets of narcissism were found to be positively related to perceived SECA, whereas antagonistic facets of narcissism were found to be negatively related to perceived SECA. However, both narcissism facets were negatively related to actual SECA. Exploratory condition-based regression analyses further showed that agentic narcissists had a higher directed discrepancy between perceived and actual SECA: They self-enhanced their socio-emotional capacities. Implications of these results for the multifaceted theoretical understanding of the narcissism-SECA link are discussed.
Groundwater travel time distributions (TTDs) provide a robust description of the subsurface mixing behavior and hydrological response of a subsurface system. Lagrangian particle tracking is often used to derive the groundwater TTDs. The reliability of this approach is subjected to the uncertainty of external forcings, internal hydraulic properties, and the interplay between them. Here, we evaluate the uncertainty of catchment groundwater TTDs in an agricultural catchment using a 3-D groundwater model with an overall focus on revealing the relationship between external forcing, internal hydraulic properties, and TTD predictions. Eight recharge realizations are sampled from a high-resolution dataset of land surface fluxes and states. Calibration-constrained hydraulic conductivity fields (Ks fields) are stochastically generated using the null-space Monte Carlo (NSMC) method for each recharge realization. The random walk particle tracking (RWPT) method is used to track the pathways of particles and compute travel times. Moreover, an analytical model under the random sampling (RS) assumption is fit against the numerical solutions, serving as a reference for the mixing behavior of the model domain. The StorAge Selection (SAS) function is used to interpret the results in terms of quantifying the systematic preference for discharging young/old water. The simulation results reveal the primary effect of recharge on the predicted mean travel time (MTT). The different realizations of calibration-constrained Ks fields moderately magnify or attenuate the predicted MTTs. The analytical model does not properly replicate the numerical solution, and it underestimates the mean travel time. Simulated SAS functions indicate an overall preference for young water for all realizations. The spatial pattern of recharge controls the shape and breadth of simulated TTDs and SAS functions by changing the spatial distribution of particles' pathways. In conclusion, overlooking the spatial nonuniformity and uncertainty of input (forcing) will result in biased travel time predictions. We also highlight the worth of reliable observations in reducing predictive uncertainty and the good interpretability of SAS functions in terms of understanding catchment transport processes.
Permafrost warming has the potential to amplify global climate change, because when frozen sediments thaw it unlocks soil organic carbon. Yet to date, no globally consistent assessment of permafrost temperature change has been compiled. Here we use a global data set of permafrost temperature time series from the Global Terrestrial Network for Permafrost to evaluate temperature change across permafrost regions for the period since the International Polar Year (2007-2009). During the reference decade between 2007 and 2016, ground temperature near the depth of zero annual amplitude in the continuous permafrost zone increased by 0.39 +/- 0.15 degrees C. Over the same period, discontinuous permafrost warmed by 0.20 +/- 0.10 degrees C. Permafrost in mountains warmed by 0.19 +/- 0.05 degrees C and in Antarctica by 0.37 +/- 0.10 degrees C. Globally, permafrost temperature increased by 0.29 +/- 0.12 degrees C. The observed trend follows the Arctic amplification of air temperature increase in the Northern Hemisphere. In the discontinuous zone, however, ground warming occurred due to increased snow thickness while air temperature remained statistically unchanged.
Estimating parameters from multiple time series of population dynamics using bayesian inference
(2019)
Empirical time series of interacting entities, e.g., species abundances, are highly useful to study ecological mechanisms. Mathematical models are valuable tools to further elucidate those mechanisms and underlying processes. However, obtaining an agreement between model predictions and experimental observations remains a demanding task. As models always abstract from reality one parameter often summarizes several properties. Parameter measurements are performed in additional experiments independent of the ones delivering the time series. Transferring these parameter values to different settings may result in incorrect parametrizations. On top of that, the properties of organisms and thus the respective parameter values may vary considerably. These issues limit the use of a priori model parametrizations. In this study, we present a method suited for a direct estimation of model parameters and their variability from experimental time series data. We combine numerical simulations of a continuous-time dynamical population model with Bayesian inference, using a hierarchical framework that allows for variability of individual parameters. The method is applied to a comprehensive set of time series from a laboratory predator-prey system that features both steady states and cyclic population dynamics. Our model predictions are able to reproduce both steady states and cyclic dynamics of the data. Additionally to the direct estimates of the parameter values, the Bayesian approach also provides their uncertainties. We found that fitting cyclic population dynamics, which contain more information on the process rates than steady states, yields more precise parameter estimates. We detected significant variability among parameters of different time series and identified the variation in the maximum growth rate of the prey as a source for the transition from steady states to cyclic dynamics. By lending more flexibility to the model, our approach facilitates parametrizations and shows more easily which patterns in time series can be explained also by simple models. Applying Bayesian inference and dynamical population models in conjunction may help to quantify the profound variability in organismal properties in nature.
For the layered transition metal dichalcogenide 1T-TaS2, we establish through a unique experimental approach and density functional theory, how ultrafast charge transfer in 1T-TaS2 takes on isotropic three-dimensional character or anisotropic two-dimensional character, depending on the commensurability of the charge density wave phases of 1T-TaS2. The X-ray spectroscopic core-hole-clock method prepares selectively in-and out-of-plane polarized sulfur 3p orbital occupation with respect to the 1T-TaS2 planes and monitors sub-femtosecond wave packet delocalization. Despite being a prototypical two-dimensional material, isotropic three-dimensional charge transfer is found in the commensurate charge density wave phase (CCDW), indicating strong coupling between layers. In contrast, anisotropic two-dimensional charge transfer occurs for the nearly commensurate phase (NCDW). In direct comparison, theory shows that interlayer interaction in the CCDW phase - not layer stacking variations - causes isotropic three-dimensional charge transfer. This is presumably a general mechanism for phase transitions and tailored properties of dichalcogenides with charge density waves.
In active mountain belts with steep terrain, bedrock landsliding is a major erosional agent. In the Himalayas, landsliding is driven by annual hydro-meteorological forcing due to the summer monsoon and by rarer, exceptional events, such as earthquakes. Independent methods yield erosion rate estimates that appear to increase with sampling time, suggesting that rare, high-magnitude erosion events dominate the erosional budget. Nevertheless, until now, neither the contribution of monsoon and earthquakes to landslide erosion nor the proportion of erosion due to rare, giant landslides have been quantified in the Himalayas. We address these challenges by combining and analysing earthquake- and monsoon-induced landslide inventories across different timescales. With time series of 5 m satellite images over four main valleys in central Nepal, we comprehensively mapped landslides caused by the monsoon from 2010 to 2018. We found no clear correlation between monsoon properties and landsliding and a similar mean landsliding rate for all valleys, except in 2015, where the valleys affected by the earthquake featured similar to 5-8 times more landsliding than the pre-earthquake mean rate. The longterm size-frequency distribution of monsoon-induced landsliding (MIL) was derived from these inventories and from an inventory of landslides larger than similar to 0.1 km(2) that occurred between 1972 and 2014. Using a published landslide inventory for the Gorkha 2015 earthquake, we derive the size-frequency distribution for earthquakeinduced landsliding (EQIL). These two distributions are dominated by infrequent, large and giant landslides but under-predict an estimated Holocene frequency of giant landslides (> 1 km(3)) which we derived from a literature compilation. This discrepancy can be resolved when modelling the effect of a full distribution of earthquakes of variable magnitude and when considering that a shallower earthquake may cause larger landslides. In this case, EQIL and MIL contribute about equally to a total long-term erosion of similar to 2 +/- 0.75 mm yr(-1) in agreement with most thermo-chronological data. Independently of the specific total and relative erosion rates, the heavy-tailed size-frequency distribution from MIL and EQIL and the very large maximal landslide size in the Himalayas indicate that mean landslide erosion rates increase with sampling time, as has been observed for independent erosion estimates. Further, we find that the sampling timescale required to adequately capture the frequency of the largest landslides, which is necessary for deriving long-term mean erosion rates, is often much longer than the averaging time of cosmogenic Be-10 methods. This observation presents a strong caveat when interpreting spatial or temporal variability in erosion rates from this method. Thus, in areas where a very large, rare landslide contributes heavily to long-term erosion (as the Himalayas), we recommend Be-10 sample in catchments with source areas > 10 000 km(2) to reduce the method mean bias to below similar to 20 % of the long-term erosion.
Arctic lowlands are characterized by large numbers of small waterbodies, which are known to affect surface energy budgets and the global carbon cycle. Statistical analysis of their size distributions has been hindered by the shortage of observations at sufficiently high spatial resolutions. This situation has now changed with the high-resolution (<5 m) circum-Arctic Permafrost Region Pond and Lake (PeRL) database recently becoming available. We have used this database to make the first consistent, high-resolution estimation of Arctic waterbody size distributions, with surface areas ranging from 0.0001 km(2) (100 m(2)) to 1 km(2). We found that the size distributions varied greatly across the thirty study regions investigated and that there was no single universal size distribution function (including power-law distribution functions) appropriate across all of the study regions. We did, however, find close relationships between the statistical moments (mean, variance, and skewness) of the waterbody size distributions from different study regions. Specifically, we found that the spatial variance increased linearly with mean waterbody size (R-2 = 0.97, p < 2.2e-16) and that the skewness decreased approximately hyperbolically. We have demonstrated that these relationships (1) hold across the 30 Arctic study regions covering a variety of (bio)climatic and permafrost zones, (2) hold over time in two of these study regions for which multi-decadal satellite imagery is available, and (3) can be reproduced by simulating rising water levels in a high-resolution digital elevation model. The consistent spatial and temporal relationships between the statistical moments of the waterbody size distributions underscore the dominance of topographic controls in lowland permafrost areas. These results provide motivation for further analyses of the factors involved in waterbody development and spatial distribution and for investigations into the possibility of using statistical moments to predict future hydrologic dynamics in the Arctic.