Berufliche Stabilitäts- und Flexibilitätsorientierungen in Ostdeutschland: Ergebnisse eines Forschungspraktikums

Das im folgenden vorgestellte Projekt Stabilitäts- und Flexibilitätsorientierungen in ostdeutschen Lebensverläufen wurde am Institut für Soziologie der Universität Leipzig im Rahmen eines Lehrpraktikums durchgeführt. In dem Projekt wurden berufliche Stabilitäts- und Flexibilitätsorientierungen ostdeutscher Beschäftigter vor dem Hintergrund individueller Ressourcen und Gelegenheitsstrukturen untersucht. Anhand von 68 biographischen Interviews älterer und jüngerer Kohorten sollte gezeigt werden, in welchem Maße individuelle Merkmale sowie familiäre, arbeitsmarktliche, sozialpolitische und betriebliche Gelegenheitsstrukturen die individuellen Handlungsorientierungen beeinflussen. Vor dem Hintergrund der \"Entstandardisierung\" von Lebenslaufmustern und der \"Flexibilisierung\" von Erwerbsverläufen wurde dabei nach den Ursachen und Veränderungen kohortenspezifischer Unterscheidungen berufsbiographischer Entwürfe gefragt.:Vorbemerkung; Stabilität und Flexibilität im Lebensverlauf; Analytisches Modell und methodisches Vorgehen; Ergebnisse; Bewältigungsstrategien – Eine Zusammenfassung; Literatur, Anhan

BLOOM: A 176B-Parameter Open-Access Multilingual Language Model

Large language models (LLMs) have been shown to be able to perform new tasks based on a few demonstrations or natural language instructions. While these capabilities have led to widespread adoption, most LLMs are developed by resource-rich organizations and are frequently kept from the public. As a step towards democratizing this powerful technology, we present BLOOM, a 176B-parameter open-access language model designed and built thanks to a collaboration of hundreds of researchers. BLOOM is a decoder-only Transformer language model that was trained on the ROOTS corpus, a dataset comprising hundreds of sources in 46 natural and 13 programming languages (59 in total). We find that BLOOM achieves competitive performance on a wide variety of benchmarks, with stronger results after undergoing multitask prompted finetuning. To facilitate future research and applications using LLMs, we publicly release our models and code under the Responsible AI License

Hybrid cosmic ray measurements using the IceAct telescopes in coincidence with the IceCube and IceTop detectors

IceAct is a proposed surface array of compact (50 cm diameter) and cost-effective Imaging Air Cherenkov Telescopes installed at the site of the IceCube Neutrino Observatory at the geographic South Pole. Since January 2019, two IceAct telescope demonstrators, featuring 61 silicon photomultiplier (SiPM) pixels have been taking data in the center of the IceTop surface array during the austral winter. We present the first analysis of hybrid cosmic ray events detected by the IceAct imaging air-Cherenkov telescopes in coincidence with the IceCube Neutrino Observatory, including the IceTop surface array and the IceCube in-ice array. By featuring an energy threshold of about 10 TeV and a wide field-of-view, the IceAct telescopes show promising capabilities of improving current cosmic ray composition studies: measuring the Cherenkov light emissions in the atmosphere adds new information about the shower development not accessible with the current detectors, enabling significantly better primary particle type discrimination on a statistical basis. The hybrid measurement also allows for detailed feasibility studies of detector cross-calibration and of cosmic ray veto capabilities for neutrino analyses. We present the performance of the telescopes, the results from the analysis of two years of data, and an outlook of a hybrid simulation for a future telescope array

Photography-based taxonomy is inadequate, unnecessary, and potentially harmful for biological sciences

The question whether taxonomic descriptions naming new animal species without type specimen(s) deposited in collections should be accepted for publication by scientific journals and allowed by the Code has already been discussed in Zootaxa (Dubois & Nemésio 2007; Donegan 2008, 2009; Nemésio 2009a–b; Dubois 2009; Gentile & Snell 2009; Minelli 2009; Cianferoni & Bartolozzi 2016; Amorim et al. 2016). This question was again raised in a letter supported by 35 signatories published in the journal Nature (Pape et al. 2016) on 15 September 2016. On 25 September 2016, the following rebuttal (strictly limited to 300 words as per the editorial rules of Nature) was submitted to Nature, which on 18 October 2016 refused to publish it. As we think this problem is a very important one for zoological taxonomy, this text is published here exactly as submitted to Nature, followed by the list of the 493 taxonomists and collection-based researchers who signed it in the short time span from 20 September to 6 October 2016

Three-year performance of the IceAct telescopes at the IceCube Neutrino Observatory

IceAct is an array of compact Imaging Air Cherenkov Telescopes at the ice surface as part of the IceCube Neutrino Observatory. The telescopes, featuring a camera of 61 silicon photomultipliers and fresnel-lens-based optics, are optimized to be operated in harsh environmental conditions, such as at the South Pole. Since 2019, the first two telescopes have been operating in a stereoscopic configuration in the center of IceCube\u27s surface detector IceTop. With an energy threshold of about 10 TeV and a wide field-of-view, the IceAct telescopes show promising capabilities of improving current cosmic-ray composition studies: measuring the Cherenkov light emissions in the atmosphere adds new information about the shower development not accessible with the current detectors. First simulations indicate that the added information of a single telescope leads, e.g., to an improved discrimination between flux contributions from different primary particle species in the sensitive energy range. We review the performance and detector operations of the telescopes during the past 3 years (2020-2022) and give an outlook on the future of IceAct

Towards a cosmic ray composition measurement with the IceAct telescopes at the IceCube Neutrino Observatory

The IceCube Neutrino Observatory is equipped with the unique possibility to measure cosmic ray induced air showers simultaneously by their particle footprint on the surface with the IceTop detector and by the high-energy muonic shower component at a depth of more than 1.5 km. Since 2019 additionally, two Imaging Air Cherenkov Telescopes, called IceAct, measure the electromagnetic component of air showers in the atmosphere above the IceCube detector. This opens the possibility to measure air shower parameters in three independent detectors and allows to improve mass composition studies with the IceCube data. One IceAct camera consists of 61 SiPM pixels in a hexagonal grid. Each pixel has a field of view of 1.5 degree resulting in an approximately 12-degree field of view per camera. A single telescope tube has a diameter of 50 cm, is built robust enough to withstand the harsh Antarctic conditions, and is able to detect cosmic ray particles with energies above approximately 10 TeV. A Graph Neural Network (GNN) is trained to determine the air shower properties from IceAct data. The composition analysis is then performed using Random Forest Regression (RF). Since all three detectors have a different energy threshold, we train several RFs with different inputs, combining the different detectors and taking advantage of the lower energy threshold of the IceAct telescopes. This will result in composition measurements for different detector combinations and enables cross-checks of the results in overlapping energy bands. We present the method, parameters for data selection, and the status of this analysis

Early diagnosis and better rhythm management to improve outcomes in patients with atrial fibrillation: the 8th AFNET/EHRA consensus conference

Aims Despite marked progress in the management of atrial fibrillation (AF), detecting AF remains difficult and AF-related complications cause unacceptable morbidity and mortality even on optimal current therapy.Methods and results This document summarizes the key outcomes of the 8th AFNET/EHRA Consensus Conference of the Atrial Fibrillation NETwork (AFNET) and the European Heart Rhythm Association (EHRA). Eighty-three international experts met in Hamburg for 2 days in October 2021. Results of the interdisciplinary, hybrid discussions in breakout groups and the plenary based on recently published and unpublished observations are summarized in this consensus paper to support improved care for patients with AF by guiding prevention, individualized management, and research strategies. The main outcomes are (i) new evidence supports a simple, scalable, and pragmatic population-based AF screening pathway; (ii) rhythm management is evolving from therapy aimed at improving symptoms to an integrated domain in the prevention of AF-related outcomes, especially in patients with recently diagnosed AF; (iii) improved characterization of atrial cardiomyopathy may help to identify patients in need for therapy; (iv) standardized assessment of cognitive function in patients with AF could lead to improvement in patient outcomes; and (v) artificial intelligence (AI) can support all of the above aims, but requires advanced interdisciplinary knowledge and collaboration as well as a better medico-legal framework.Conclusions Implementation of new evidence-based approaches to AF screening and rhythm management can improve outcomes in patients with AF. Additional benefits are possible with further efforts to identify and target atrial cardiomyopathy and cognitive impairment, which can be facilitated by AI.</p