Filtern
Erscheinungsjahr
- 2022 (78) (entfernen)
Dokumenttyp
- Wissenschaftlicher Artikel (78) (entfernen)
Schlagworte
- CDK (2)
- water electrolysis (2)
- Arbeitszeit (1)
- Automatisierung (1)
- Befragung (1)
- Berufsfeldstudie (1)
- Betriebsrat (1)
- Biomechanics (1)
- Bundesverfassungsgericht (1)
- Catalysis (1)
Gerechter Zufall per Gesetz?
(2022)
Der Datenjournalismus wird gleichermaßen stark in der Nachrichtenbranche beobachtet und in der Journalismusforschung reflektiert. Dieser Beitrag beschreibt das Phänomen zunächst im Kontext des Megatrends der Automatisierung des Journalismus. Anschließend wird die erste Trendstudie zum Da-tenjournalismus in Deutschland vorgestellt: Die Berufsfeldstudie war 2012 und 2019 im Feld. Die ge-wählten Items ermöglichen einen Längsschnitt-Vergleich der Entwicklung des Datenjournalismus. Bei einem Vergleich mit den nationalen Daten der „Worlds of Journalism Study“ werden weitere Gemein-samkeiten und Unterschiede deutlich. Die Ergebnisse zeigen, dass sich der Datenjournalismus in Deutschland zunehmend institutionalisiert hat und Datenjournalist:innen sich stark einem investigati-ven politischen Journalismus verpflichtet fühlen.
Different charge treatment approaches are examined for cyclotide-induced plasma membrane disruption by lipid extraction studied with dissipative particle dynamics. A pure Coulomb approach with truncated forces tuned to avoid individual strong ion pairing still reveals hidden statistical pairing effects that may lead to artificial membrane stabilization or distortion of cyclotide activity depending on the cyclotide’s charge state. While qualitative behavior is not affected in an apparent manner, more sensitive quantitative evaluations can be systematically biased. The findings suggest a charge smearing of point charges by an adequate charge distribution. For large mesoscopic simulation boxes, approximations for the Ewald sum to account for mirror charges due to periodic boundary conditions are of negligible influence.
„Digital gestützte Lehrveranstaltungen“ im Sinne von § 1a Abs. 2 LVV (NRW) – eine erste Annäherung
(2022)
The use of molecular string representations for deep learning in chemistry has been steadily increasing in recent years. The complexity of existing string representations, and the difficulty in creating meaningful tokens from them, lead to the development of new string representations for chemical structures. In this study, the translation of chemical structure depictions in the form of bitmap images to corresponding molecular string representations was examined. An analysis of the recently developed DeepSMILES and SELFIES representations in comparison with the most commonly used SMILES representation is presented where the ability to translate image features into string representations with transformer models was specifically tested. The SMILES representation exhibits the best overall performance whereas SELFIES guarantee valid chemical structures. DeepSMILES perform in between SMILES and SELFIES, InChIs are not appropriate for the learning task. All investigations were performed using publicly available datasets and the code used to train and evaluate the models has been made available to the public.
The translation of images of chemical structures into machine-readable representations of the depicted molecules is known as optical chemical structure recognition (OCSR). There has been a lot of progress over the last three decades in this field, but the development of systems for the recognition of complex hand-drawn structure depictions is still at the beginning. Currently, there is no data for the systematic evaluation of OCSR methods on hand-drawn structures available. Here we present DECIMER — Hand-drawn molecule images, a standardised, openly available benchmark dataset of 5088 hand-drawn depictions of diversely picked chemical structures. Every structure depiction in the dataset is mapped to a machine-readable representation of the underlying molecule. The dataset is openly available and published under the CC-BY 4.0 licence which applies very few limitations. We hope that it will contribute to the further development of the field.