Uncertainty and Narratives of the Future. A Theoretical Framework for Contemporary Fertility

Explanations for fertility decisions based on structural constraints—such as labor, housing condition, or income—do not account for the contemporary fertility downturn faced by many countries in Europe. In this paper, we posit that the rise of uncertainty is central for understanding contemporary fertility dynamics. We propose a theoretical framework (the Narrative Framework) for the study of fertility decisions under uncertain conditions based on expectations, imaginaries and narratives. Relying on the idea of future–oriented action, we argue that uncertainty needs to be conceptualized and operationalized taking into account that people use works of imagination, producing their own narrative of the future. Narratives of the future are potent driving forces helping people to act according to or despite uncertainty. We present the different elements of the Narrative Framework and address its causal validity. We conclude by highlighting the advantages of taking into account the narratives of the future in fertility research

Spatial Distribution of Cryptic Species Diversity in European Freshwater Amphipods (Gammarus fossarum) as Revealed by Pyrosequencing

In order to understand and protect ecosystems, local gene pools need to be evaluated with respect to their uniqueness. Cryptic species present a challenge in this context because their presence, if unrecognized, may lead to serious misjudgement of the distribution of evolutionarily distinct genetic entities. In this study, we describe the current geographical distribution of cryptic species of the ecologically important stream amphipod Gammarus fossarum (types A, B and C). We use a novel pyrosequencing assay for molecular species identification and survey 62 populations in Switzerland, plus several populations in Germany and eastern France. In addition, we compile data from previous publications (mainly Germany). A clear transition is observed from type A in the east (Danube and Po drainages) to types B and, more rarely, C in the west (Meuse, Rhone, and four smaller French river systems). Within the Rhine drainage, the cryptic species meet in a contact zone which spans the entire G. fossarum distribution range from north to south. This large-scale geographical sorting indicates that types A and B persisted in separate refugia during Pleistocene glaciations. Within the contact zone, the species rarely co-occur at the same site, suggesting that ecological processes may preclude long-term coexistence. The clear phylogeographical signal observed in this study implies that, in many parts of Europe, only one of the cryptic species is present

Cryptic species in a well-known habitat: applying taxonomics to the amphipod genus Epimeria (Crustacea, Peracarida)

Taxonomy plays a central role in biological sciences. It provides a communication system for scientists as it aims to enable correct identification of the studied organisms. As a consequence, species descriptions should seek to include as much available information as possible at species level to follow an integrative concept of ‘taxonomics’. Here, we describe the cryptic species Epimeria frankei sp. nov. from the North Sea, and also redescribe its sister species, Epimeria cornigera. The morphological information obtained is substantiated by DNA barcodes and complete nuclear 18S rRNA gene sequences. In addition, we provide, for the first time, full mitochondrial genome data as part of a metazoan species description for a holotype, as well as the neotype. This study represents the first successful implementation of the recently proposed concept of taxonomics, using data from highthroughput technologies for integrative taxonomic studies, allowing the highest level of confidence for both biodiversity and ecological research

Scintillation light detection in the 6-m drift-length ProtoDUNE Dual Phase liquid argon TPC

DUNE is a dual-site experiment for long-baseline neutrino oscillation studies, neutrino astrophysics and nucleon decay searches. ProtoDUNE Dual Phase (DP) is a 6  ×  6  ×  6 m 3 liquid argon time-projection-chamber (LArTPC) that recorded cosmic-muon data at the CERN Neutrino Platform in 2019-2020 as a prototype of the DUNE Far Detector. Charged particles propagating through the LArTPC produce ionization and scintillation light. The scintillation light signal in these detectors can provide the trigger for non-beam events. In addition, it adds precise timing capabilities and improves the calorimetry measurements. In ProtoDUNE-DP, scintillation and electroluminescence light produced by cosmic muons in the LArTPC is collected by photomultiplier tubes placed up to 7 m away from the ionizing track. In this paper, the ProtoDUNE-DP photon detection system performance is evaluated with a particular focus on the different wavelength shifters, such as PEN and TPB, and the use of Xe-doped LAr, considering its future use in giant LArTPCs. The scintillation light production and propagation processes are analyzed and a comparison of simulation to data is performed, improving understanding of the liquid argon properties

Long-range and short-range dihadron angular correlations in central PbPb collisions at √sNN=2.76 TeV

This is the pre-print version of the Published Article, which can be accessed from the link below.First measurements of dihadron correlations for charged particles are presented for central PbPb collisions at a nucleon-nucleon center-of-mass energy of 2.76TeV over a broad range in relative pseudorapidity ( ) and the full range of relative azimuthal angle ( ). The data were collected with the CMS detector, at the LHC. A broadening of the away-side ( ) azimuthal correlation is observed at all , as compared to the measurements in pp collisions. Furthermore, long-range dihadron correlations in are observed for particles with similar values. This phenomenon, also known as the \ridge", persists up to at least j j = 4. For particles with transverse momenta (pT) of 2-4 GeV/c, the ridge is found to be most prominent when these particles are correlated with particles of pT = 2-6 GeV/c, and to be much reduced when paired with particles of pT = 10-12 GeV/c

Separation of track- and shower-like energy deposits in ProtoDUNE-SP using a convolutional neural network

Liquid argon time projection chamber detector technology provides high spatial and calorimetric resolutions on the charged particles traversing liquid argon. As a result, the technology has been used in a number of recent neutrino experiments, and is the technology of choice for the Deep Underground Neutrino Experiment (DUNE). In order to perform high precision measurements of neutrinos in the detector, final state particles need to be effectively identified, and their energy accurately reconstructed. This article proposes an algorithm based on a convolutional neural network to perform the classification of energy deposits and reconstructed particles as track-like or arising from electromagnetic cascades. Results from testing the algorithm on data from ProtoDUNE-SP, a prototype of the DUNE far detector, are presented. The network identifies track- and shower-like particles, as well as Michel electrons, with high efficiency. The performance of the algorithm is consistent between data and simulation

Separation of track- and shower-like energy deposits in ProtoDUNE-SP using a convolutional neural network

Liquid argon time projection chamber detector technology provides high spatial and calorimetric resolutions on the charged particles traversing liquid argon. As a result, the technology has been used in a number of recent neutrino experiments, and is the technology of choice for the Deep Underground Neutrino Experiment (DUNE). In order to perform high precision measurements of neutrinos in the detector, final state particles need to be effectively identified, and their energy accurately reconstructed. This article proposes an algorithm based on a convolutional neural network to perform the classification of energy deposits and reconstructed particles as track-like or arising from electromagnetic cascades. Results from testing the algorithm on experimental data from ProtoDUNE-SP, a prototype of the DUNE far detector, are presented. The network identifies track- and shower-like particles, as well as Michel electrons, with high efficiency. The performance of the algorithm is consistent between experimental data and simulation