Hasil untuk "German literature"

Prasanna K. Dhani, Konstantinos Pyretzidis, Selomit Ramírez-Uribe et al.

Finite Feynman integrals have been advocated as the optimal components for constructing a basis of master integrals in multiloop calculations, due to their improved analytic and numerical properties. In this paper, we show how the Loop-Tree Duality (LTD) is particularly well suited for systematically identifying finite integrals, as it makes the origin of infrared and threshold singularities fully transparent at the integrand level. This clear separation of singular and non-singular contributions enables a more efficient strategy for isolating and promoting finite integrals, thereby streamlining both reduction and numerical evaluation. We present a new strategy based on numerator and raised propagator Ansätze that provides results similar to other methods, although in a clearer and compact way. While this construction and other approaches establish a robust foundation, they often produce integrands that exhibit a rapid growth in the ultraviolet (UV) regime. To mitigate this bad UV behaviour, we introduce a generalized set of integrands fully defined within LTD. This new set is inherently infrared-finite and frequently free of threshold singularities, offering a more versatile framework for high-order calculations.

Ludwig Felder, Tobias Eisenreich, Mahsa Fischer et al.

Generative artificial intelligence (GenAI) tools have seen rapid adoption among software developers. While adoption rates in the industry are rising, the underlying factors influencing the effective use of these tools, including the depth of interaction, organizational constraints, and experience-related considerations, have not been thoroughly investigated. This issue is particularly relevant in environments with stringent regulatory requirements, such as Germany, where practitioners must address the GDPR and the EU AI Act while balancing productivity gains with intellectual property considerations. Despite the significant impact of GenAI on software engineering, to the best of our knowledge, no empirical study has systematically examined the adoption dynamics of GenAI tools within the German context. To address this gap, we present a comprehensive mixed-methods study on GenAI adoption among German software engineers. Specifically, we conducted 18 exploratory interviews with practitioners, followed by a developer survey with 109 participants. We analyze patterns of tool adoption, prompting strategies, and organizational factors that influence effectiveness. Our results indicate that experience level moderates the perceived benefits of GenAI tools, and productivity gains are not evenly distributed among developers. Further, organizational size affects both tool selection and the intensity of tool use. Limited awareness of the project context is identified as the most significant barrier. We summarize a set of actionable implications for developers, organizations, and tool vendors seeking to advance artificial intelligence (AI) assisted software development.

Talita Bordoni, Filippo Maria Dini, Roberta Galuppi

Canine systemic aspergillosis is a rare but highly serious condition, often associated with a fatal outcome. This review encompasses all reported cases of canine systemic aspergillosis from 1978 to the present, focusing exclusively on studies in which the diagnosis was confirmed through fungal culture. A total of 155 clinical cases reported in the literature were included. Among these, the German Shepherd was the most frequently affected breed (65.16%), followed by mixed-breed dogs (7.74%). The predominant <i>Aspergillus</i> species isolated was <i>A. terreus</i> (57.69%), although other species were also reported, including <i>A. deflectus</i>, <i>A. fumigatus</i>, <i>A. niger</i>, <i>A. caninus</i>, <i>A. versicolor</i>, <i>A. alabamensis</i>, <i>A. citrinoterreus</i>, and <i>A. floccosus</i>. Recognizing clinical signs and accurately interpreting laboratory findings are crucial for early diagnosis and timely intervention, both of which can potentially improve outcomes. This review provides a detailed discussion of these aspects.

Verena Blaschke, Miriam Winkler, Barbara Plank

Research on cross-dialectal transfer from a standard to a non-standard dialect variety has typically focused on text data. However, dialects are primarily spoken, and non-standard spellings cause issues in text processing. We compare standard-to-dialect transfer in three settings: text models, speech models, and cascaded systems where speech first gets automatically transcribed and then further processed by a text model. We focus on German dialects in the context of written and spoken intent classification -- releasing the first dialectal audio intent classification dataset -- with supporting experiments on topic classification. The speech-only setup provides the best results on the dialect data while the text-only setup works best on the standard data. While the cascaded systems lag behind the text-only models for German, they perform relatively well on the dialectal data if the transcription system generates normalized, standard-like output.

Jenny SCHRÖDL

This article focuses on the heterogeneous stagings of gender in contemporary independent theatre and highlights three central, overarching characteristics: gender between fluidity and stability, gender diversity and intersectionality, and new forms of critique. It also discusses the extent to which the staging of gender in the independent scene can – still – be subsumed under the term “avant-garde” and where the limits of the concept become apparent.

Tomislav Zelić

GEM 5 ima za predmet mediteransku interkulturnost u njemačkom jeziku, književnosti i kulturi. Pet od ukupno šest radova temelje se na podnescima s međunarodnog znanstvenog skupa njemačkog Društva za interkulturnu germanistiku, Gesellschaft für interkulturelle Germanistik (GiG), u organizaciji Odjela za germanstiku Sveučilišta u Zadru, na temu „Interkulturni prostori: povijesne rute i pasaže u sadašnjosti s posebnim obzirom na Sredozemlje“, održan od 19. do 22. travnja 2022. godine virtualno s obzirom da u tom trenutku epidemiološke mjere još nisu bile stavljene izvan snage.

Esmaeil Safaei Asl

AbstractThe present study has been conducted in the framework of Systemic Functional Grammar and on the basis of systemic functional typology, specifically Matthiessen’s typological generalizations. Based on examples taken from various written documents in Azeri Turkic such as grammar books and a series of stories as well as constructed examples, this study aims to describe the typological behaviors of the MOOD TYPE system in the clause structure of Azeri Turkic in terms of Matthiessen’s typological generalizations regarding the MOOD system. Some results of the present study indicate that Azeri Turkic MOOD TYPE system (1) has all the three declarative, polar interrogative, and imperative moods, (2) uses negative polar interrogatives to indicate the speaker’s positive bias, (3) belongs to the ‘languages that have the Wh-interrogative category’ type, (4) queries just the participants and circumstantial adjuncts in the Wh-interrogatives, (5) belongs to the ‘Wh-in-situ languages’ type, and (6) differentiates the imperative mood from the other mood types.IntroductionThis study, conducted within the framework of Systemic Functional Grammar and based on Matthiessen’s (2004) typology of MOOD TYPE system, as a subsystem within the interpersonal metafunction, aims to investigate and describe the MOOD TYPE system in Azeri Turkic, which belongs to the Southwestern branch of Turkic languages, also known as the Western Oghuz group. Grounded in systemic functional typology, this research seeks empirical generalizations applicable across languages. Matthiessen (2004) has developed descriptive generalizations through comparative analysis of the experiential, logical, interpersonal, and textual systems of various languages, identifying typological universals and variations. Following Matthiessen’s claim that these generalizations can be applied to any language within a Systemic Functional Framework, this study explores the realization of the MOOD TYPE system in Azeri Turkic. Data was collected from diverse sources, including short story collections, academic articles, grammar books on Azeri Turkic, and original examples provided by the researcher. The paper is structured into five sections: introduction, review of related literature, theoretical framework, analysis of MOOD TYPE in Azeri Turkic, and concluding remarks presenting the findings.Literature ReviewThis section reviews several studies on the clause type system, including Mirahmadi’s (2004) Systemic Functional analysis of Persian mood types, Pahlavannajhad & Vazirnejad’s (2004) stylistic study of mood types in Zoya Pirzad’s novel, Najm’s (2008) cross-linguistic comparison of English and Arabic imperatives and exclamatives, Figuerdo’s (2010) description of Portuguese mood types, and traditional grammatical studies on Azerbaijani Turkish by Li (1996), Ahmadi Givi (2004), Dehqani (2000), and Zahedi & Bayan (2008).Unlike previous studies, this research contributes to Systemic Functional Typology by analyzing mood types in Azeri Turkic through a functional lens, aiming to determine whether Matthiessen’s descriptive generalizations can be effectively applied to this language.ResultsThe findings of the present study show that Azeri Turkic identifies four major mood types—declarative, polar interrogative, content interrogative (Wh-questions), and imperative. This confirms Matthiessen’s generalization that declarative, polar interrogative, and imperative clauses are universal, while the presence of content interrogatives places Azeri Turkic among languages that distinguish this category.   Polar interrogatives in Azeri Turkic appear in both biased and unbiased forms, marked by particles such as ɒjɒ ‘whether’ for neutral questions and mæjær, mæjæ, bæjæ, or bæ ‘don't/doesn't, didn't’ for biased questions. These markers typically appear at the beginning of the clause, contradicting Matthiessen’s generalization that such particles occur at the end in SOV languages. Additionally, polar interrogatives may be unmarked but distinguished by falling intonation. Content interrogatives are used to inquire about specific elements and are marked by Wh-words such as cim ‘who’, hɒrɒ ‘where’, and nijæ ‘why’. These clauses are clearly differentiated from declaratives through question words and rising intonation, aligning Azeri Turkic with typologically similar languages like English and Japanese, where content and polar interrogatives form a distinct mood type separate from declaratives. In terms of word order, Azeri Turkic follows the canonical position of Wh-elements within the clause rather than fronting them, placing it in the typological category of "Wh-in-situ" languages alongside Persian, Chinese, and Japanese, as opposed to English, French, and German.In Azeri Turkic, as in Persian and English, the imperative mood is marked by the absence of an overt subject, which is usually implied. Unlike in languages such as Mandarin Chinese and Hebrew, where negation in imperatives differs morphologically from declaratives, Azeri Turkic —similar to Persian and English—uses the same negative form across both imperative and non-imperative clauses. This indicates a syntactic independence between the imperative mood and the system of polarity in Azeri Turkic. Another typological feature of imperative clauses is the realization of speech functions relative to the speaker-listener relationship. Azeri Turkic, like German, Persian, and English, offers more delicate choices within the imperative mood to express politeness. For instance, all three languages can use polar interrogatives to represent polite commands.ConclusionThis study was an effort to describe the MOOD TYPE system in Azeri Turkic within a Systemic Functional Typological Framework.Drawing on diverse sources—including short story collections, academic articles, grammar books on Azeri Turkic, and the researcher's linguistic intuition—the study demonstrates that the MOOD TYPE system in Azeri Turkic:includes the three universal mood types: declarative, polar interrogative, and imperative.uses negative polar interrogatives to express the speaker’s positive bias.allows polar interrogatives to be expressed in declarative structure, without any formal marking other than intonation.belongs to the typological category of languages that distinguish content interrogatives (Wh-questions).questions only about participants and peripheral adjuncts—not processes—as interrogative elements in Wh-questions.is classified typologically as a "Wh-in-situ" language, where question words remain in their canonical position rather than being fronted.clearly distinguishes the imperative mood from other mood types.typically omits the addressee (second person) as an unmarked feature in imperative clauses.treats the imperative mood and the system of polarity independently, with no morphological distinction between negative forms in imperatives and non-imperatives.can metaphorically express the speech function of command through polar interrogatives, depending on the social relationship between speaker and listener.Overall, Azeri Turkic exhibits a well-differentiated MOOD TYPE system that aligns with broader systemic functional typological generalizations regarding mood types and their typological variations across languages.

Selomit Ramírez-Uribe, Prasanna K. Dhani, German F. R. Sborlini et al.

We propose multiloop vacuum amplitudes as the optimal building blocks for efficiently assembling theoretical predictions at high-energy colliders. This hypothesis is strongly supported by the manifestly causal properties of the loop-tree duality (LTD) representation of a vacuum amplitude. The vacuum amplitude, acting as a kernel, encodes all the final states contributing to a given scattering or decay process through residues in the on-shell energies of the internal propagators. It also naturally implements gauge invariance and the wave function renormalisation of the external legs. This methodological approach, dubbed LTD causal unitary, leads to a novel representation of differential cross sections and decay rates that is locally free of ultraviolet and infrared singularities at all orders in perturbation theory. Threshold singularities also match between different phase-space residues. Most notably, it allows us to conjecture for the first time the local functional form of initial-state collinear singularities. The fulfillment of all these properties provides a theoretical description of differential observables at colliders that is well defined in the four physical dimensions of the space-time.

Ralf Otte

This article presents a heuristic view that shows that the inner states of consciousness experienced by every human being have a physical but imaginary hypercomplex basis. The hypercomplex description is necessary because certain processes of consciousness cannot be physically measured in principle, but nevertheless exist. Based on theoretical considerations, it could be possible - as a result of mathematical investigations into a so-called bicomplex algebra - to generate and use hypercomplex system states on machines in a targeted manner. The hypothesis of the existence of hypercomplex system states on machines is already supported by the surprising performance of highly complex AI systems. However, this has yet to be proven. In particular, there is a lack of experimental data that distinguishes such systems from other systems, which is why this question will be addressed in later articles. This paper describes the developed bicomplex algebra and possible applications of these findings to generate hypercomplex energy states on machines. In the literature, such system states are often referred to as machine consciousness. The article uses mathematical considerations to explain how artificial consciousness could be generated and what advantages this would have for such AI systems.

Frank W. Stearns

Mohammed Bin Sumait, Aleksandra Gabryszak, Leonhard Hennig et al.

Factuality can play an important role when automatically processing clinical text, as it makes a difference if particular symptoms are explicitly not present, possibly present, not mentioned, or affirmed. In most cases, a sufficient number of examples is necessary to handle such phenomena in a supervised machine learning setting. However, as clinical text might contain sensitive information, data cannot be easily shared. In the context of factuality detection, this work presents a simple solution using machine translation to translate English data to German to train a transformer-based factuality detection model.

Jean Anthony Grand-Guillaume-Perrenoud, Franziska Geese, Katja Uhlmann et al.

Abstract Background Quantitative and qualitative procedures are necessary components of instrument development and assessment. However, validation studies conventionally emphasise quantitative assessments while neglecting qualitative procedures. Applying both methods in a mixed methods design provides additional insights into instrument quality and more rigorous validity evidence. Drawing from an extensive review of the methodological and applied validation literature on mixed methods, we showcase our use of mixed methods for validation which applied the quality criteria of congruence, convergence, and credibility on data collected with an instrument measuring interprofessional collaboration in the context of Swiss healthcare, named the Swiss Instrument for Evaluating Interprofessional Collaboration. Methods We employ a convergent parallel mixed methods design to analyse quantitative and qualitative questionnaire data. Data were collected from staff, supervisors, and patients of a university hospital and regional hospitals in the German and Italian speaking regions of Switzerland. We compare quantitative ratings and qualitative comments to evaluate the quality criteria of congruence, convergence, and credibility, which together form part of an instrument’s construct validity evidence. Results Questionnaires from 435 staff, 133 supervisors, and 189 patients were collected. Analysis of congruence potentially provides explanations why respondents’ comments are off topic. Convergence between quantitative ratings and qualitative comments can be interpreted as an indication of convergent validity. Credibility provides a summary evaluation of instrument quality. These quality criteria provide evidence that questions were understood as intended, provide construct validity, and also point to potential item quality issues. Conclusions Mixed methods provide alternative means of collecting construct validity evidence. Our suggested procedures can be easily applied on empirical data and allow the congruence, convergence, and credibility of questionnaire items to be evaluated. The described procedures provide an efficient means of enhancing the rigor of an instrument and can be used alone or in conjunction with traditional quantitative psychometric approaches.

Mariola Smolińska

Yanick Schraner, Christian Scheller, Michel Plüss et al.

We present an in-depth evaluation of four commercially available Speech-to-Text (STT) systems for Swiss German. The systems are anonymized and referred to as system a-d in this report. We compare the four systems to our STT model, referred to as FHNW from hereon after, and provide details on how we trained our model. To evaluate the models, we use two STT datasets from different domains. The Swiss Parliament Corpus (SPC) test set and a private dataset in the news domain with an even distribution across seven dialect regions. We provide a detailed error analysis to detect the three systems' strengths and weaknesses. This analysis is limited by the characteristics of the two test sets. Our model scored the highest bilingual evaluation understudy (BLEU) on both datasets. On the SPC test set, we obtain a BLEU score of 0.607, whereas the best commercial system reaches a BLEU score of 0.509. On our private test set, we obtain a BLEU score of 0.722 and the best commercial system a BLEU score of 0.568.

Andy Lücking, Manuel Stoeckel, Giuseppe Abrami et al.

HeidelTime is one of the most widespread and successful tools for detecting temporal expressions in texts. Since HeidelTime's pattern matching system is based on regular expression, it can be extended in a convenient way. We present such an extension for the German resources of HeidelTime: HeidelTime-EXT . The extension has been brought about by means of observing false negatives within real world texts and various time banks. The gain in coverage is 2.7% or 8.5%, depending on the admitted degree of potential overgeneralization. We describe the development of HeidelTime-EXT, its evaluation on text samples from various genres, and share some linguistic observations. HeidelTime ext can be obtained from https://github.com/texttechnologylab/heideltime.

Marco Di Giovanni, Francesco Pierri, Christopher Torres-Lugo et al.

Despite the increasing limitations for unvaccinated people, in many European countries there is still a non-negligible fraction of individuals who refuse to get vaccinated against SARS-CoV-2, undermining governmental efforts to eradicate the virus. We study the role of online social media in influencing individuals' opinion towards getting vaccinated by designing a large-scale collection of Twitter messages in three different languages -- French, German and Italian -- and providing public access to the data collected. Focusing on the European context, our VaccinEU dataset aims to help researchers to better understand the impact of online (mis)information about vaccines and design more accurate communication strategies to maximize vaccination coverage.

David Pomerenke

Gender-inclusive language is important for achieving gender equality in languages with gender inflections, such as German. While stirring some controversy, it is increasingly adopted by companies and political institutions. A handful of tools have been developed to help people use gender-inclusive language by identifying instances of the generic masculine and providing suggestions for more inclusive reformulations. In this report, we define the underlying tasks in terms of natural language processing, and present a dataset and measures for benchmarking them. We also present a model that implements these tasks, by combining an inclusive language database with an elaborate sequence of processing steps via standard pre-trained models. Our model achieves a recall of 0.89 and a precision of 0.82 in our benchmark for identifying exclusive language; and one of its top five suggestions is chosen in real-world texts in 44% of cases. We sketch how the area could be further advanced by training end-to-end models and using large language models; and we urge the community to include more gender-inclusive texts in their training data in order to not present an obstacle to the adoption of gender-inclusive language. Through these efforts, we hope to contribute to restoring justice in language and, to a small extent, in reality.

Philipp Glaum, Fabian Hofmann

The German government recently announced that 80\% of the power supply should come from renewable energy by 2030. One key task lies in reorganizing the transmission system such that power can be transported from sites with good renewable potentials to the load centers. Dynamic Line Rating (DLR), which allows the dynamic calculation of transmission line capacities based on prevailing weather conditions rather than conservative invariant ratings, offers the potential to exploit existing grid capacities better. In this paper, we analyze the effect of DLR on behalf of a detailed power system model of Germany including all of today's extra high voltage transmission lines and substations. The evolving synergies between DLR and an increased wind power generation lead to savings of around 400 million euro per year in the short term and 900 million per year in a scenario for 2030.

A. Pflugfelder, C. Kochs, A. Blum et al.

Johann Frei, Frank Kramer

The current state of adoption of well-structured electronic health records and integration of digital methods for storing medical patient data in structured formats can often considered as inferior compared to the use of traditional, unstructured text based patient data documentation. Data mining in the field of medical data analysis often needs to rely solely on processing of unstructured data to retrieve relevant data. In natural language processing (NLP), statistical models have been shown successful in various tasks like part-of-speech tagging, relation extraction (RE) and named entity recognition (NER). In this work, we present GERNERMED, the first open, neural NLP model for NER tasks dedicated to detect medical entity types in German text data. Here, we avoid the conflicting goals of protection of sensitive patient data from training data extraction and the publication of the statistical model weights by training our model on a custom dataset that was translated from publicly available datasets in foreign language by a pretrained neural machine translation model. The sample code and the statistical model is available at: https://github.com/frankkramer-lab/GERNERMED