Hasil untuk "German literature"

Oleg N. German

In this paper we describe the spectrum of values of weak uniform Diophantine exponents of lattices in arbitrary dimension.

Sylvie Anne Genier, Gessica Trivelli, Vera Ruth Mitter

STUDY AIMS: Streptococcus agalacticae is a pathogen associated with maternal and neonatal morbidity and mortality. The current gold standard for preventing neonatal sepsis is the intrapartum antibiotic prophylaxis (IAP) of Streptococcus agalacticae-positive mothers. Antimicrobial resistance is on the rise and increasingly threatens public health. Therefore, the responsible use of antibiotics is critical. Switzerland lacks unified IAP guidelines. IAP management varies by obstetric ward and is based on various national and international guidelines. This study aimed to gain an overview of the variability of existing internal protocols for IAP for Streptococcus agalacticae in Swiss obstetrics wards. METHOD: In March and April 2024, all identified obstetric wards in Switzerland were contacted and invited to submit their internal protocols so that they could be analysed for the choice of antibiotics for IAP, the referenced literature supporting their protocols and the professions involved in their development. RESULTS: Of 87 departments contacted, 43 (49%) shared their protocols. Three β-lactam antibiotics were identified as the first choice: penicillin G (56%, n = 24), amoxicillin (28%, n = 12) and co-amoxicillin (9%, n = 4). In 19% of the protocols (n = 8), there was no distinction between mild or severe allergy to penicillin derivatives. In this group (n = 8), 75% (n = 6) administered clindamycin as the second choice, with 50% (n = 3 of 6) offering vancomycin as an alternative in cases of known clindamycin resistance or allergy. In the group with allergy severity classification (n = 35), first- and second-generation cephalosporins were preferred for mild penicillin allergy: 71% (n = 25) used cefazolin, 26% (n = 9) used cefuroxime and erythromycin was mentioned by n = 1. In 21 of the 33 received protocols with references, Expert Letter No. 19 from the Swiss Society of Gynaecology and Obstetrics (SGGG) was referenced, making up 64 % of the used literature. This was followed by other literature (58 %, n = 19) and the revised guidelines of the Swiss Society of Neonatology in collaboration with the Paediatric Infectious Disease Group Switzerland (PIGS) (30 %, n = 10). Mostly gynaecologists (90%; n = 28 of 31) were involved as authors of internal protocols. Neonatologists were not mentioned by any. CONCLUSION: Our study highlights that the management of intrapartum antibiotic prophylaxis is heterogeneous, and antimicrobial stewardship is lacking in most Swiss obstetric wards. In terms of literature, German-speaking wards in Switzerland are more orientated towards German-speaking neighbouring countries than French- and Italian-speaking wards. There is a need to enhance interdisciplinarity in the development of internal protocols and to create a joint national guideline among professional societies.

Anikó Dušíková

The national literary canons that took shape in the 19th century were built on the exclusivity of the national language. The absence of a full translation of a text originally written in a non-national language could lead to its complete disappearance from public consciousness. This study examines the significance of the German novel Bendeguz (1841) in shaping the perception of the literary work of Slovak writer Ján Chalupka (1791 – 1871). The first attempt to incorporate this novel into the monolingual space of national literature was the publication of a Slovak translation of several chapters in the humoristic magazine Černokňažník [The sorcerer] in 1862 and 1863. The novel was rediscovered only in the early 1950s, thanks to two editions of a Slovak translation by Ján Vladimír Ormis (1953; expanded version 1959). While the new translation drew attention to the novel, its interpretation largely overlooked elements that did not align with the established image of Chalupka as an Enlightenment rationalist. The need to broaden the interpretative context is further emphasized by the novel’s paratexts, particularly its Hungarian-language mottos and the subtitle, “donquijotiáda podľa najnovšej módy” – “A Don Quixote story in the latest fashion.”

Anastasia Zhukova, Christian E. Matt, Bela Gipp

Domain-adaptive continual pretraining (DAPT) is a state-of-the-art technique that further trains a language model (LM) on its pretraining task, e.g., masked language modeling (MLM), when common domain adaptation via LM fine-tuning is not possible due to a lack of labeled task data. Although popular, MLM requires a significant corpus of domain-related data, which is difficult to obtain for specific domains in languages other than English, such as the process industry in the German language. This paper introduces an efficient approach called ICL-augmented pretraining or ICL-APT that leverages in-context learning (ICL) and k-nearest neighbors (kNN) to augment target data with domain-related and in-domain texts, significantly reducing GPU time while maintaining strong model performance. Our results show that the best configuration of ICL-APT performed better than the state-of-the-art DAPT by 28.7% (7.87 points) and requires almost 4 times less GPU-computing time, providing a cost-effective solution for industries with limited computational capacity. The findings highlight the broader applicability of this framework to other low-resource industries, making NLP-based solutions more accessible and feasible in production environments.

Rainer Rehak, Christian R. Kuehne

Since SARS-CoV-2 started spreading in Europe in early 2020, there has been a strong call for technical solutions to combat or contain the pandemic, with contact tracing apps at the heart of the debates. The EU's General Data Protection Regulation (GDPR) requires controllers to carry out a data protection impact assessment (DPIA) where their data processing is likely to result in a high risk to the rights and freedoms (Art. 35 GDPR). A DPIA is a structured risk analysis that identifies and evaluates possible consequences of data processing relevant to fundamental rights in advance and describes the measures envisaged to address these risks or expresses the inability to do so. Based on the Standard Data Protection Model (SDM), we present the results of a scientific and methodologically clear DPIA of the German German Corona-Warn-App (CWA). It shows that even a decentralized architecture involves numerous serious weaknesses and risks, including larger ones still left unaddressed in current implementations. It also found that none of the proposed designs operates on anonymous data or ensures proper anonymisation. It also showed that informed consent would not be a legitimate legal ground for the processing. For all points where data subjects' rights are still not sufficiently safeguarded, we briefly outline solutions.

Gabriel German, Juan Carlos Hidalgo

We study inflationary constraints from reheating on two classes of single-field inflationary models: a generalized $α$-attractor with potential $V(φ) = V_0 \!\left(1 - \sech^p\!\left[φ/(\sqrt{6α}\,M_{Pl})\right]\right)$ and the $α$-Starobinsky model with potential $V(φ) = V_0 \!\left(1 - e^{- \sqrt{2/(3α)}\, φ/ M_{Pl}} \right)^2$. Using a semi-analytical relation that connects inflationary dynamics to reheating, we solve for the horizon-crossing field value and calculate the scalar spectral index $n_s$, the tensor-to-scalar ratio $r$, and the reheating temperature $T_{re}$. We consider three perturbative decay channels of the inflaton: gravitational, Yukawa (fermionic), and scalar. The parameter space spanned by $(α,p,ω_{re})$ for the first model and $(α,ω_{re})$ for the second is explored and compared with recent measurements from Planck and ACT DR6, as well as BAO from DESI DR2. For clarity, we emphasize that ACT DR6 alone is fully compatible with Planck regarding $n_s$. The upward shift toward $n_s \simeq 0.975$ appears only when DESI DR2 BAO are combined with CMB datasets (Planck+DESI, ACT+DESI, SPT-3G+DESI), and is likewise seen in the P--ACT--LB2+DESI combination. CMB-only combinations (e.g., Planck+ACT or Planck+ACT+SPT-3G) primarily refine constraints and do not by themselves raise $n_s$. Our comparisons and model assessments are therefore made with this distinction in mind: CMB-only constraints versus CMB+DESI combinations. We conclude that both models remain consistent with current CMB-only data in restricted regions of parameter space, and that residual tension with the higher $n_s$ favored by CMB+DESI persists.

Natalia Ankowska

The main aim of the article is to determine which neologisms were created in the German language at the time of the COVID-19 pandemic in the field of education. The choice to focus on education and school concepts is based on the fact that it is considered one of the fundamental areas of people’s lives. Since schooling is compulsory in Germany, this topic affects every citizen. The structure of the article is as follows: first, the pandemic-related changes in the field of education are briefly discussed. Next, the term neologism is explained in more detail, as well as the functions and the types of neologisms that can be distinguished. The core of the article is the presentation and discussion of the results of the empirical analysis. 81 neologisms from the field of education created during the coronavirus pandemic were subjected to the analysis. They refer to various branches of the education system and name, among other things, periods of time, but also persons and school concepts, which is why they were assigned to eight semantic categories: Change of the education system, evaluation of learning outcomes, character of learning and teaching, description of a particular period, description of individuals, feelings, support and final evaluation. Within the groups, antonyms and synonyms could be found. The article also explains the reasons for the creation of the neologisms.

Howard Choy

This paper is a study of humorous and satirical image-texts found in eleven Chinese women’s online diaries composed between 2020 and 2022 during the time of COVID-19, including three from Wuhan, one from Xi’an, two from Chongqing, one from Chengdu, one composed by a Shanghainese, and three by New Yorkers. The diarists’ intersectional positionings as social worker, medical practitioner, interactive designer, unemployed grassroots organizer, overseas student, filmmaker, teacher, journalists, writers, and mothers from different cities in China and the United States inform their individual articulations of concerns about sociopolitical changes, pandemic situations, everyday life, as well as gender and class issues.Epidemic humor and satire in these lockdown narratives will be introduced in light of multidisciplinary methods, including sociological studies, political philosophy, psychological theory, and literary criticism. These feminine expressions of comic feelings point to communal laughter as a strategy for survival, subversion, and nonviolent resistance against unprecedented state surveillance and interventions in everyday life. As Sinophone literature continues to go global together with the spread of the disease, the Chinese diaries tend to be more politically satiric, as seen in Fang Fang’s Wuhan Diary and its English, German, and Japanese renditions, while the American–Chinese journals are rather humorous in terms of recording life, such as daily diet and necessities during the quarantine. This is due to cultural and situational differences, yet they have all exhibited their feminine sensitivity and sensibilities and formed a structure of feeling representing popular responses to the official discourse among digital citizens in the time of coronavirus.

Anton Ehrmanntraut

Historic variations of spelling poses a challenge for full-text search or natural language processing on historical digitized texts. To minimize the gap between the historic orthography and contemporary spelling, usually an automatic orthographic normalization of the historical source material is pursued. This report proposes a normalization system for German literary texts from c. 1700-1900, trained on a parallel corpus. The proposed system makes use of a machine learning approach using Transformer language models, combining an encoder-decoder model to normalize individual word types, and a pre-trained causal language model to adjust these normalizations within their context. An extensive evaluation shows that the proposed system provides state-of-the-art accuracy, comparable with a much larger fully end-to-end sentence-based normalization system, fine-tuning a pre-trained Transformer large language model. However, the normalization of historical text remains a challenge due to difficulties for models to generalize, and the lack of extensive high-quality parallel data.

Stephen Meisenbacher, Tim Schopf, Weixin Yan et al.

The task of $\textit{keyword extraction}$ is often an important initial step in unsupervised information extraction, forming the basis for tasks such as topic modeling or document classification. While recent methods have proven to be quite effective in the extraction of keywords, the identification of $\textit{class-specific}$ keywords, or only those pertaining to a predefined class, remains challenging. In this work, we propose an improved method for class-specific keyword extraction, which builds upon the popular $\textbf{KeyBERT}$ library to identify only keywords related to a class described by $\textit{seed keywords}$. We test this method using a dataset of German business registry entries, where the goal is to classify each business according to an economic sector. Our results reveal that our method greatly improves upon previous approaches, setting a new standard for $\textit{class-specific}$ keyword extraction.

Gabriel German

Reheating in inflationary cosmology is essential for understanding the early universe, influencing particle production, thermalization, and the primordial power spectrum. Crucial quantities defined during the reheating epoc, such as the equation of state parameter $ω_{re}$, reheating temperature $T_{re}$, and the number of $e$-folds $N_{re}$, affect inflationary observables like the scalar spectral index $n_s$ and the tensor-to-scalar ratio $r$. We analyze two classes of inflationary models: generalized $α$-attractor models and the $α$-Starobinsky generalization. These models, motivated by supergravity and string theory, exhibit attractor behavior, ensuring strong predictions and have been studied extensively before. A salient novelty of this study, compared to previous works, is the inclusion of an analytical expression for the reheating temperature, $T_{\text{re}}$, which makes it a dynamical quantity. This is crucial for determining all the cosmological quantities analyzed in this work. Our results show a universal scaling behavior for a tightly bounded $T_{re}$ in both models. We believe this is the first time that $T_{re}$ is so closely determined. This work complements previous Bayesian and numerical studies by providing detailed numerical and analytical insights into the evolution of cosmological observables and reheating parameters, offering also constraints on inflationary models based on observational data.

Verena Blaschke, Christoph Purschke, Hinrich Schütze et al.

Natural language processing (NLP) has largely focused on modelling standardized languages. More recently, attention has increasingly shifted to local, non-standardized languages and dialects. However, the relevant speaker populations' needs and wishes with respect to NLP tools are largely unknown. In this paper, we focus on dialects and regional languages related to German -- a group of varieties that is heterogeneous in terms of prestige and standardization. We survey speakers of these varieties (N=327) and present their opinions on hypothetical language technologies for their dialects. Although attitudes vary among subgroups of our respondents, we find that respondents are especially in favour of potential NLP tools that work with dialectal input (especially audio input) such as virtual assistants, and less so for applications that produce dialectal output such as machine translation or spellcheckers.

Aswathy Velutharambath, Amelie Wührl, Roman Klinger

The statement "The earth is flat" is factually inaccurate, but if someone truly believes and argues in its favor, it is not deceptive. Research on deception detection and fact checking often conflates factual accuracy with the truthfulness of statements. This assumption makes it difficult to (a) study subtle distinctions and interactions between the two and (b) gauge their effects on downstream tasks. The belief-based deception framework disentangles these properties by defining texts as deceptive when there is a mismatch between what people say and what they truly believe. In this study, we assess if presumed patterns of deception generalize to German language texts. We test the effectiveness of computational models in detecting deception using an established corpus of belief-based argumentation. Finally, we gauge the impact of deception on the downstream task of fact checking and explore if this property confounds verification models. Surprisingly, our analysis finds no correlation with established cues of deception. Previous work claimed that computational models can outperform humans in deception detection accuracy, however, our experiments show that both traditional and state-of-the-art models struggle with the task, performing no better than random guessing. For fact checking, we find that Natural Language Inference-based verification performs worse on non-factual and deceptive content, while prompting Large Language Models for the same task is less sensitive to these properties.

Anne Heinze, Manès Weisskircher

How do political parties respond to street protest by political outsiders widely considered to be ‘pariahs’ (i.e. radical or extremist actors)? Bridging the literature on responses to ‘populist’ radical right parties with insights from social movement studies, we propose a theoretical model that conceptualises potential party responses to pariah protest. Innovatively, our typology distinguishes between a set of formal and substantive responses to street mobilisation. Empirically, we apply this model by providing the first systematic study of how political parties have responded to the ‘anti-Corona’ protests of Querdenken, contributing to social science research on the politics of the COVID-19 pandemic. Analysing the critical case of Germany, we underline the stark difference between how the populist radical right AfD and all other Bundestag parties respond to anti-Corona mobilisation, showing how political protest may sharpen the polarisation of party politics. Moreover, we highlight the more nuanced but still important differences in responses by established German parties. Theoretically, the article provides an analytical framework valuable in times of increasing street mobilisation by radical and extremist actors. Methodologically, our analysis relies on a systematic media analysis of articles from two major German newspapers. Empirically, it contributes to our understanding of the difficult but crucial relationship between the German protest and party arena during the COVID-19 pandemic.

Joanna Szczęk

Diego GASPAR CELAYA

This paper analyses and recounts the movement of Germans and their transit experiences of crossing the French-Spanish border between 1920 and 1947. It places them in the context of population movement between France and Spain at the time and identifies six different German groups: war volunteers, refugees, politicians, intelligence agents, soldiers and other Third Reich security force members. These experiences are presented in the context of the European Civil War, the transnational war volunteering phenomena and the clandestine crossing of the French-Spanish border. These population movements, whether they were forced or not, confirm the permeability of the border territory, which allowed contacts between populations of more distant origins who used this space as a place of transit, as well as the transnational nature of the border as it became an exceptional exchange space.

Maurizio Titz, Sebastian Pütz, Dirk Witthaut

The transition to a sustainable energy supply challenges the operation of electric power systems in manifold ways. Transmission grid loads increase as wind and solar power are often installed far away from the consumers. In extreme cases, system operators must intervene via countertrading or redispatch to ensure grid stability. In this article, we provide a data-driven analysis of congestion in the German transmission grid. We develop an explainable machine learning model to predict the volume of redispatch and countertrade on an hourly basis. The model reveals factors that drive or mitigate grid congestion and quantifies their impact. We show that, as expected, wind power generation is the main driver, but hydropower and cross-border electricity trading also play an essential role. Solar power, on the other hand, has no mitigating effect. Our results suggest that a change to the market design would alleviate congestion.

Nathalie Rzepka, Katharina Simbeck, Hans-Georg Mueller et al.

Since adaptive learning comes in many shapes and sizes, it is crucial to find out which adaptations can be meaningful for which areas of learning. Our work presents the result of an experiment conducted on an online platform for the acquisition of German spelling skills. We compared the traditional online learning platform to three different adaptive versions of the platform that implement machine learning-based student-facing interventions that show the personalized solution probability. We evaluate the different interventions with regard to the error rate, the number of early dropouts, and the users competency. Our results show that the number of mistakes decreased in comparison to the control group. Additionally, an increasing number of dropouts was found. We did not find any significant effects on the users competency. We conclude that student-facing adaptive learning environments are effective in improving a persons error rate and should be chosen wisely to have a motivating impact.

Lisa Taruttis, C. Weber

The German government aims at a climate-neutral building stock by 2050 to reach the goals defined in the Climate Action Plan 2050. Increasing the energy efficiency of existing buildings is therefore a high priority. For this purpose, investments of private homeowners will play a major role since about 46.5% of the German dwellings are owner-occupied. To identify potential monetary benefits of investing in energetic retrofits, we investigate whether energy efficiency is reflected in property values of single-family houses in Germany. Thereby we examine possible heterogeneous effects among regions. With 455,413 individual observations on a 1km²-grid level for 2014 to 2018, this study adds to the literature 1) by examining the effect of energy efficiency on housing values for Germany on a more small-scale level and specifically investigating regional disparities in this context and 2) by estimating an energy efficiency value-to-cost ratio. Applying a hedonic analysis, we find a positive relationship between energy efficiency and asking prices. We also find evidence for regional disparities. Effects are significantly weaker in large cities compared to other urban areas, whereas the impact in rural areas is much stronger. Since property values are expected to decline in rural regions, homeowners could alleviate this development by increasing the energy efficiency of their dwellings.

Karsten Rinas

This article discusses an essay by Karl Heinrich Seibt on differences in writing styles. The essay was published in Prague in 1768. It reflects important changes in writing practices that occurred in the Age of Enlightenment. Seibt’s essay is interesting because it recommends the usage of very progressive writing styles that come close to early Romantic approaches (the ‘Sturm und Drang’). On the other hand, Seibt also defends a very traditional (periodical) style in official or formal contexts. It is argued that this sharp contrast is a consequence of Seibt’s difficult role as a teacher of modern language style in the traditional Habsburg Empire.