Invariant causal mechanisms

Qualitative methodologists generally treat process tracing methods and a mechanistic view of causation as natural allies. Two conjoined propositions form the basis for this alliance. The first proposition is that the identification of causal mechanisms is the sine qua non of distinguishing causal relations from mere correlations. The second proposition is that process-tracing methods are uniquely qualified to identify these critical causal mechanisms. In one admirably pithy formulation, Gary Goertz and James Mahoney state categorically: “No strong causal inference without process tracing.” There appears to be a tacit consensus that process tracing is both necessary and sufficient for causal inference

sMolBoxes: Dataflow Model for Molecular Dynamics Exploration

We present sMolBoxes, a dataflow representation for the exploration and analysis of long molecular dynamics (MD) simulations. When MD simulations reach millions of snapshots, a frame-by-frame observation is not feasible anymore. Thus, biochemists rely to a large extent only on quantitative analysis of geometric and physico-chemical properties. However, the usage of abstract methods to study inherently spatial data hinders the exploration and poses a considerable workload. sMolBoxes link quantitative analysis of a user-defined set of properties with interactive 3D visualizations. They enable visual explanations of molecular behaviors, which lead to an efficient discovery of biochemically significant parts of the MD simulation. sMolBoxes follow a node-based model for flexible definition, combination, and immediate evaluation of properties to be investigated. Progressive analytics enable fluid switching between multiple properties, which facilitates hypothesis generation. Each sMolBox provides quick insight to an observed property or function, available in more detail in the bigBox View. The case study illustrates that even with relatively few sMolBoxes, it is possible to express complex analyses tasks, and their use in exploratory analysis is perceived as more efficient than traditional scripting-based methods.Comment: 10 pages, 9 figures, IEEE VIS, TVC

sMolBoxes: Dataflow Model for Molecular Dynamics Exploration

We present sMolBoxes, a dataflow representation for the exploration and analysis of long molecular dynamics (MD) simulations. When MD simulations reach millions of snapshots, a frame-by-frame observation is not feasible anymore. Thus, biochemists rely to a large extent only on quantitative analysis of geometric and physico-chemical properties. However, the usage of abstract methods to study inherently spatial data hinders the exploration and poses a considerable workload. sMolBoxes link quantitative analysis of a user-defined set of properties with interactive 3D visualizations. They enable visual explanations of molecular behaviors, which lead to an efficient discovery of biochemically significant parts of the MD simulation. sMolBoxes follow a node-based model for flexible definition, combination, and immediate evaluation of properties to be investigated. Progressive analytics enable fluid switching between multiple properties, which facilitates hypothesis generation. Each sMolBox provides quick insight to an observed property or function, available in more detail in the bigBox View. The case studies illustrate that even with relatively few sMolBoxes, it is possible to express complex analytical tasks, and their use in exploratory analysis is perceived as more efficient than traditional scripting-based methods.acceptedVersio

Institutions, Path Dependence, and Democratic Consolidation."

ABSTRACT Formal political institutions have been assigned two roles in democratization theorizing: as contingent effects of strategic interaction and as predictable bases for democratic consolidation. These roles might be reconciled if we assume that institutions become persistent once in place. But patterns of behavior surrounding these institutions do not appear to conform to the expectations of path dependency or comparable frameworks: while unchallenged in some cases, these institutions are repeatedly contested and often enough revised in others. This is true even of 'low stakes' institutional designs. Consequently, groups often perceive institutional designs not as 'locked in' and instead as malleable over even a few years. Codified political institutions therefore appear unable to generate the reduced risks -in effect, the credible commitments -which Adam Przeworski's argument about democratic consolidation requires. This conclusion suggests that consolidation may result from reductions in political risks caused by non-institutional factors. It also has implications for diverse arguments which assume stability or predictability in formal institutions. KEY WORDS • credible commitments • democratic consolidation • institutions • path dependence The Two Roles Institutions Play in Democratization Theorizing This article's main claim is that formal political institutions cannot and do not play the decisive role in democratic consolidation which several theorists suggest. This is the case because these institutions -'electoral systems, constitutional provisions governing relations between the legislative and executive branches, and degrees of decentralization ' (Colomer, 1995: 74) are more contingent and susceptible to revision than has often been assumed, including by many democratization theorists. An emphasis on institutional contingency may seem more plausible today than in earlier decades, given substantial constitutional changes in numerous countries in the past few years. But the cases discussed here suggest that contingency Journal of Theoretical Politics 13(3): 249-7

Good Agreement Between Modeled and Measured Sulfur and Nitrogen Deposition in Europe, in Spite of Marked Differences in Some Sites

Atmospheric nitrogen and sulfur deposition is an important effect of atmospheric pollution and may affect forest ecosystems positively, for example enhancing tree growth, or negatively, for example causing acidification, eutrophication, cation depletion in soil or nutritional imbalances in trees. To assess and design measures to reduce the negative impacts of deposition, a good estimate of the deposition amount is needed, either by direct measurement or by modeling. In order to evaluate the precision of both approaches and to identify possible improvements, we compared the deposition estimates obtained using an Eulerian model with the measurements performed by two large independent networks covering most of Europe. The results are in good agreement (bias <25%) for sulfate and nitrate open field deposition, while larger differences are more evident for ammonium deposition, likely due to the greater influence of local ammonia sources. Modeled sulfur total deposition compares well with throughfall deposition measured in forest plots, while the estimate of nitrogen deposition is affected by the tree canopy. The geographical distribution of pollutant deposition and of outlier sites where model and measurements show larger differences are discussed

Combining multiple isotopes and metagenomic to delineate the role of tree canopy nitrification in European forests along nitrogen deposition and climate gradients

Forest canopies influence our climate through carbon, water and energy exchanges with the atmosphere. However, less investigated is whether and how tree canopies change the chemical composition of precipitation, with important implications on forest nutrient cycling. Recently, we provided for the first time isotopic evidence that biological nitrification in tree canopies was responsible for significant changes in the amount of nitrate from rainfall to throughfall across two UK forests at high nitrogen (N) deposition [1]. This finding strongly suggested that bacteria and/or Archaea species of the phyllosphere are responsible for transforming atmospheric N before it reaches the soil. Despite microbial epiphytes representing an important component of tree canopies, attention has been mostly directed to their role as pathogens, while we still do not know whether and how they affect nutrient cycling. Our study aims to 1) characterize microbial communities harboured in tree canopies for two of the most dominant species in Europe (Fagus sylvatica L. and Pinus sylvestris L.) using metagenomic techniques, 2) quantify the functional genes related to nitrification but also to denitrification and N fixation, and 3) estimate the contribution of NO3 derived from biological canopy nitrification vs. atmospheric NO3 input by using \u3b415N, \u3b418O and \u3b417O of NO3in forest water. We considered i) twelve sites included in the EU ICP long term intensive forest monitoring network, chosen along a climate and nitrogen deposition gradient, spanning from Fennoscandia to the Mediterranean and ii) a manipulation experiment where N mist treatments were carried out either to the soil or over tree canopies. We will present preliminary results regarding microbial diversity in the phyllosphere, water (rainfall and throughfall) and soil samples over the gradient. Furthermore, we will report differences between the two investigated tree species for the phyllosphere core microbiome in terms of relative abundance of bacterial and Archaea classes and those species related to N cycling. Finally we will assess whether there are differences among tree species and sites in the number of functional genes related to N cycling and how they are related to the N deposition and/or climate. [1] Guerrieri et al. 2015 Global Change and Biology 21 (12): 4613-4626

Assessing the response of forest productivity to climate extremes in Switzerland using model-data fusion

The response of forest productivity to climate extremes strongly depends on ambient environmental and site conditions. To better understand these relationships at a regional scale, we used nearly 800 observation years from 271 permanent long-term forest monitoring plots across Switzerland, obtained between 1980 and 2017. We assimilated these data into the 3-PG forest ecosystem model using Bayesian inference, reducing the bias of model predictions from 14% to 5% for forest stem carbon stocks and from 45% to 9% for stem carbon stock changes. We then estimated the productivity of forests dominated by Picea abies and Fagus sylvatica for the period of 1960-2018, and tested for productivity shifts in response to climate along elevational gradient and in extreme years. Simulated net primary productivity (NPP) decreased with elevation (2.86 +/- 0.006 Mg C ha(-1) year(-1) km(-1) for P. abies and 0.93 +/- 0.010 Mg C ha(-1) year(-1) km(-1) for F. sylvatica). During warm-dry extremes, simulated NPP for both species increased at higher and decreased at lower elevations, with reductions in NPP of more than 25% for up to 21% of the potential species distribution range in Switzerland. Reduced plant water availability had a stronger effect on NPP than temperature during warm-dry extremes. Importantly, cold-dry extremes had negative impacts on regional forest NPP comparable to warm-dry extremes. Overall, our calibrated model suggests that the response of forest productivity to climate extremes is more complex than simple shift toward higher elevation. Such robust estimates of NPP are key for increasing our understanding of forests ecosystems carbon dynamics under climate extremes.Peer reviewe

Coming Back to Life: The Permeability of Past and Present, Mortality and Immortality, Death and Life in the Ancient Mediterranean

The lines between death and life were neither fixed nor finite to the peoples of the ancient Mediterranean. For most, death was a passageway into a new and uncertain existence. The dead were not so much extinguished as understood to be elsewhere, and many perceived the deceased to continue to exercise agency among the living. Even for those more skeptical of an afterlife, notions of coming back to life provided frameworks in which to conceptualize the on-going social, political, and cultural influence of the past. This collection of essays examines how notions of coming back to life shape practices and ideals throughout the ancient Mediterranean. All contributors focus on the common theme of coming back to life as a discursive and descriptive space in which antique peoples construct, maintain, and negotiate the porous boundaries between past and present, mortality and immortality, death and life

Metabolic and molecular imaging in inflammatory arthritis

It is known that metabolic shifts and tissue remodelling precede the development of visible inflammation and structural organ damage in inflammatory rheumatic diseases such as the inflammatory arthritides. As such, visualising and measuring metabolic tissue activity could be useful to identify biomarkers of disease activity already in a very early phase. Recent advances in imaging have led to the development of so-called ‘metabolic imaging’ tools that can detect these changes in metabolism in an increasingly accurate manner and non-invasively.Nuclear imaging techniques such as 18F-D-glucose and fibroblast activation protein inhibitor-labelled positron emission tomography are increasingly used and have yielded impressing results in the visualisation (including whole-body staging) of inflammatory changes in both early and established arthritis. Furthermore, optical imaging-based bedside techniques such as multispectral optoacoustic tomography and fluorescence optical imaging are advancing our understanding of arthritis by identifying intra-articular metabolic changes that correlate with the onset of inflammation with high precision and without the need of ionising radiation.Metabolic imaging holds great potential for improving the management of patients with inflammatory arthritis by contributing to early disease interception and improving diagnostic accuracy, thereby paving the way for a more personalised approach to therapy strategies including preventive strategies. In this narrative review, we discuss state-of-the-art metabolic imaging methods used in the assessment of arthritis and inflammation, and we advocate for more extensive research endeavours to elucidate their full field of application in rheumatology.http://dx.doi.org/10.13039/501100001659Deutsche Forschungsgemeinschafthttp://dx.doi.org/10.13039/501100000781European Research Councilhttp://dx.doi.org/10.13039/501100001652Friedrich-Alexander-Universität Erlangen-Nürnberghttp://dx.doi.org/10.13039/501100010767Innovative Medicines Initiativehttp://dx.doi.org/10.13039/501100002347Bundesministerium für Bildung und Forschung2022 GRAPPA Pilot Research Gran