Hasil untuk "English literature"

A. Trotti, L. Bellm, J. Epstein et al.

Muath Algazo, Bilal Alsharif, Bilal Alsharif et al.

This study examines emphasis spread (ES) in Urban Jordanian Arabic (UJA), focusing on the phonological and phonetic mechanisms that govern its direction and domain. Emphasis, realized through tongue root retraction, affects both consonants and vowels and can propagate bidirectionally within the phonological word. Using autosegmental phonology, feature geometry, and Optimality Theory (OT), this research identifies coronal emphatics (/tˤ, dˤ, sˤ, ðˤ/) and the low back vowel /ɑ/ as primary triggers of ES. Moreover, the OT analyses reveal that alignment constraints (L-ALIGN, R-ALIGN V-[dor]) interact with faithfulness constraints (MAXLINK, NOGAP, DEPLINK) to shape the extent and direction of spread. The study provides a unified formal account of intra- and inter-word ES and highlights cross-dialectal variability in Arabic, offering new insights into the phonological representation of emphatic segments. These findings contribute to a more comprehensive understanding of the structural behavior of emphatics in Arabic and support the refinement of theoretical models dealing with feature spreading and secondary articulation. The implications extend to comparative dialectology, phonological theory, and the development of more precise feature-based representations across Semitic languages.

Nazmoon Falgunee Moon

In [4], the authors present the DisCoCirc (Distributed Compositional Circuits) formalism for the English language, a grammar-based framework derived from the production rules that incorporates circuit-like representations in order to give a precise categorical theoretical structure to the language. In this paper, we extend this approach to develop a similar framework for Bengali and apply it to translation tasks between English and Bengali. A central focus of our work lies in reassessing the effectiveness of DisCoCirc in reducing language bureaucracy. Unlike the result suggested in [5], our findings indicate that although it works well for a large part of the language, it still faces limitations due to the structural variation of the two languages. We discuss the possible methods that might handle these shortcomings and show that, in practice, DisCoCirc still struggles even with relatively simple sentences. This divergence from prior claims not only highlights the framework's constraints in translation but also suggest scope for future improvement. Apart from our primary focus on English-Bengali translation, we also take a short detour to examine English conjunctions, following [1], showing a connection between conjunctions and Boolean logic.

Kazi Mahathir Rahman, Naveed Imtiaz Nafis, Md. Farhan Sadik et al.

Helping deaf and hard-of-hearing people communicate more easily is the main goal of Automatic Sign Language Translation. Although most past research has focused on turning sign language into text, doing the reverse, turning spoken English into sign language animations, has been largely overlooked. That's because it involves multiple steps, such as understanding speech, translating it into sign-friendly grammar, and generating natural human motion. In this work, we introduce a complete pipeline that converts English speech into smooth, realistic 3D sign language animations. Our system starts with Whisper to translate spoken English into text. Then, we use a MarianMT machine translation model to translate that text into American Sign Language (ASL) gloss, a simplified version of sign language that captures meaning without grammar. This model performs well, reaching BLEU scores of 0.7714 and 0.8923. To make the gloss translation more accurate, we also use word embeddings such as Word2Vec and FastText to understand word meanings. Finally, we animate the translated gloss using a 3D keypoint-based motion system trained on Sign3D-WLASL, a dataset we created by extracting body, hand, and face key points from real ASL videos in the WLASL dataset. To support the gloss translation stage, we also built a new dataset called BookGlossCorpus-CG, which turns everyday English sentences from the BookCorpus dataset into ASL gloss using grammar rules. Our system stitches everything together by smoothly interpolating between signs to create natural, continuous animations. Unlike previous works like How2Sign and Phoenix-2014T that focus on recognition or use only one type of data, our pipeline brings together audio, text, and motion in a single framework that goes all the way from spoken English to lifelike 3D sign language animation.

Wajdi Zaghouani, Md. Rafiul Biswas

This research introduces a bilingual dataset comprising 23,456 entries for Arabic and 10,036 entries for English, annotated for emotions and hope speech, addressing the scarcity of multi-emotion (Emotion and hope) datasets. The dataset provides comprehensive annotations capturing emotion intensity, complexity, and causes, alongside detailed classifications and subcategories for hope speech. To ensure annotation reliability, Fleiss' Kappa was employed, revealing 0.75-0.85 agreement among annotators both for Arabic and English language. The evaluation metrics (micro-F1-Score=0.67) obtained from the baseline model (i.e., using a machine learning model) validate that the data annotations are worthy. This dataset offers a valuable resource for advancing natural language processing in underrepresented languages, fostering better cross-linguistic analysis of emotions and hope speech.

Manish Pandey, Nageshwar Prasad Yadav, Mokshada Adduru et al.

With the growing presence of multilingual users on social media, detecting abusive language in code-mixed text has become increasingly challenging. Code-mixed communication, where users seamlessly switch between English and their native languages, poses difficulties for traditional abuse detection models, as offensive content may be context-dependent or obscured by linguistic blending. While abusive language detection has been extensively explored for high-resource languages like English and Hindi, low-resource languages such as Telugu and Nepali remain underrepresented, leaving gaps in effective moderation. In this study, we introduce a novel, manually annotated dataset of 2 thousand Telugu-English and 5 Nepali-English code-mixed comments, categorized as abusive and non-abusive, collected from various social media platforms. The dataset undergoes rigorous preprocessing before being evaluated across multiple Machine Learning (ML), Deep Learning (DL), and Large Language Models (LLMs). We experimented with models including Logistic Regression, Random Forest, Support Vector Machines (SVM), Neural Networks (NN), LSTM, CNN, and LLMs, optimizing their performance through hyperparameter tuning, and evaluate it using 10-fold cross-validation and statistical significance testing (t-test). Our findings provide key insights into the challenges of detecting abusive language in code-mixed settings and offer a comparative analysis of computational approaches. This study contributes to advancing NLP for low-resource languages by establishing benchmarks for abusive language detection in Telugu-English and Nepali-English code-mixed text. The dataset and insights can aid in the development of more robust moderation strategies for multilingual social media environments.

Sarah Désirée Lange, Sanna Pohlmann-Rother, Anna Plohmer et al.

The BLUME study founded by the German Research Foundation study (“Primary Teachers’ Beliefs Regarding Multilingualism”) describes the complexity and contradictions of primary school teachers’ beliefs. The aim is to empirically envision the whole range of beliefs held by primary school teachers. As part of the BLUME vignette study, qualitative, vignette-based interviews in the style of brief teaching case studies were conducted with 43 primary school teachers. In order to unveil the teachers’ beliefs, the study identified positioning statements that are precise statements independent of the situation and indicate the teachers’ beliefs. Using a basic coding for the positioning statements, in the first step of the analysis, text passages containing beliefs were identified, and a category system was developed inductively and deductively, presented in this article. The results show a high degree of variation in the beliefs of primary school teachers, ranging from strongly affirmative to strongly resistant beliefs. In addition, the teachers show ambivalence in dealing with multilingualism in class as well as in their reflections on their own positioning. The qualitative-empirical approach presented here makes it possible to visualise the theoretically assumed complexity and hierarchisation within the teachers’ belief systems.

Agata Małyszek, Sylwia Kiryk, Julia Kensy et al.

Tea is one of the most widely consumed beverages globally and a significant dietary source of fluoride. This systematic review aimed to identify and evaluate the factors influencing fluoride concentration in tea infusions. A comprehensive literature search was conducted in March 2025 across PubMed, Scopus, and Web of Science databases, following PRISMA guidelines (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines and the PICO framework. Eligible studies investigated fluoride release in tea infusions, published in English from the year 2000 onward. Thirty articles met the inclusion criteria, and the risk of bias in the articles was assessed using the Joanna Briggs Institute (JBI) quality checklist. Fluoride concentration in tea infusions varied widely across studies, ranging from 0.008 to over 8 mg/L. Key factors influencing fluoride release included tea type (with black and green teas showing the highest values), leaf form (powdered and bagged teas released more fluoride than loose leaves), brewing time and temperature, water composition, and the presence of additives such as spices. A longer brewing time and higher temperature consistently increased fluoride extraction. Lower pH or water hardness also significantly affected fluoride availability. Regional origin of tea and production methods were additional sources of variation. Fluoride release in tea is influenced by a complex interplay of botanical, environmental, and preparation-related factors. These findings are clinically relevant, particularly for populations at risk of fluoride overexposure. Further standardized research is needed to inform safe consumption guidelines and public health recommendations.

Xuanming Zhang, Anthony Diaz, Zixun Chen et al.

Coherence in writing, an aspect that second-language (L2) English learners often struggle with, is crucial in assessing L2 English writing. Existing automated writing evaluation systems primarily use basic surface linguistic features to detect coherence in writing. However, little effort has been made to correct the detected incoherence, which could significantly benefit L2 language learners seeking to improve their writing. To bridge this gap, we introduce DECOR, a novel benchmark that includes expert annotations for detecting incoherence in L2 English writing, identifying the underlying reasons, and rewriting the incoherent sentences. To our knowledge, DECOR is the first coherence assessment dataset specifically designed for improving L2 English writing, featuring pairs of original incoherent sentences alongside their expert-rewritten counterparts. Additionally, we fine-tuned models to automatically detect and rewrite incoherence in student essays. We find that incorporating specific reasons for incoherence during fine-tuning consistently improves the quality of the rewrites, achieving a result that is favored in both automatic and human evaluations.

Habtamu DEBASU, Asnakech Yitayew CHEKOL

The aim of reviewing inclusive education for Students with Autism Spectrum Disorder is to ensure that all students have access to high-quality education, support their holistic development, promote inclusivity and equity, and foster collaboration among stakeholders to create a more supportive and inclusive learning environment for Students with Autism Spectrum Disorder. Autism Spectrum Disorder as a neurodevelopmental disorder characterized by persistent challenges in social communication and interaction, as well as restricted and repetitive patterns of behavior, interests, or activities. The challenges faced by Students with Autism Spectrum Disorder, including difficulties in social interaction, communication, sensory sensitivities, academic support and adaptation, behavioral and emotional regulation, peer acceptance, teachers’ knowledge and training, collaboration and executive functioning. It emphasizes the importance of understanding and addressing these challenges to create an inclusive learning environment. However, various strategies to overcome the challenges faced by Students with Autism Spectrum Disorder. These strategies include providing individualized support, such as visual support, structured routines, social skills training, and assistive technology. It emphasizes the significance of collaboration among teachers, support staff, specialists, and families to implement these strategies effectively. Furthermore, the benefits of Inclusive Education for Students with Autism Spectrum Disorder state that inclusive education promotes social inclusion, academic achievement, and the development of essential life skills. It emphasizes that inclusive classrooms provide opportunities for peer interactions, positive role modeling, and the development of self-advocacy skills.

Oliver Sogard MD, John McDonald BS, Michael Elder Waters MD et al.

Category: Ankle; Trauma Introduction/Purpose: Ankle instability associated with fractures have increased surgical complexity and worse outcomes. Both the deltoid ligament and the syndesmotic ligament complex play pivotal roles in maintaining ankle stability. Medial clear space (MCS) widening serves as an indicator for ankle instability. Trans-syndesmotic fixation following open reduction and internal fixation of distal fibula has been used commonly to restore stability in unstable ankle fractures with MCS widening. Alternatively, anatomic repair of the deltoid ligament offers another approach for addressing MCS widening. However, there is no consensus on the best method for stabilizing the ankle. This study aims to provide a comprehensive analysis of current literature to compare the outcomes of trans-syndesmotic fixation and anatomic deltoid ligament repair in the treatment of unstable ankle fractures with MCS widening. Methods: This comprehensive literature review followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, utilizing databases such as PubMed, Embase, Web of Science, and the Cochrane Library. The search was conducted on October 15, 2023. The criteria for including articles in this study were: (1) Patients who had undergone surgical fixation for unstable ankle fractures with medial clear space (MCS) widening, (2) Studies comparing clinical outcomes between trans-syndesmotic fixation and anatomic deltoid ligament repair to address MCS widening, (3) Studies reporting on at least one of the following outcomes: malreduction rates, necessity for hardware removal, wound complications, reoperation rates, and functional outcomes, including AOFAS (American Orthopaedic Foot and Ankle Society) scores and VAS (Visual Analog Scale) pain scores. Exclusion criteria eliminated studies involving: (1) Patients with medial malleolar fractures, (2) Revision surgeries, (3) Non-English publications, and (4) Case reports, systematic reviews, comments, editorials, surveys, or cadaver studies. Results: In this meta-analysis, a total of five studies were included. Medial clear space widening was treated with trans-syndesmotic screw fixation in 165 unstable ankle fractures, while 115 ankles underwent anatomic repair of the deltoid ligament. Anatomic deltoid ligament repair was significantly associated with a reduced risk of syndesmotic malreduction (Risk Ratio (RR)=0.26, 95% Confidence Interval (CI) = [0.10, 0.68]) and a lower likelihood of postoperative hardware removal (RR=0.06, 95% CI = [0.02, 0.14]). No significant differences were found in minor or major wound complications, reoperation rate, AOFAS and VAS scores. These findings highlight the advantages of anatomic deltoid ligament repair, which provides a more precise reduction of unstable ankle injuries with MCS widening and a reduced need for postoperative hardware removal, compared to trans-syndesmotic fixation. Conclusion: This study evaluated postoperative outcomes between trans-syndesmotic fixation and anatomic deltoid ligament repair in addressing MCS widening. Our analysis revealed that anatomic deltoid ligament repair resulted in a significantly lower rate of malreduction and a decreased necessity for postoperative hardware removal compared to trans-syndesmotic screw fixation. Both techniques showed similar rates of wound complications, reoperation, and equivalent functional and pain scores. These results call into question the trans-syndesmotic fixation alone for unstable ankle fractures with MCS widening. Anatomic repair of the deltoid ligament should be considered as a viable option to restore stability in unstable ankle fractures with MCS widening.

Ayush Maheshwari, Ashim Gupta, Amrith Krishna et al.

We release Sāmayik, a dataset of around 53,000 parallel English-Sanskrit sentences, written in contemporary prose. Sanskrit is a classical language still in sustenance and has a rich documented heritage. However, due to the limited availability of digitized content, it still remains a low-resource language. Existing Sanskrit corpora, whether monolingual or bilingual, have predominantly focused on poetry and offer limited coverage of contemporary written materials. Sāmayik is curated from a diverse range of domains, including language instruction material, textual teaching pedagogy, and online tutorials, among others. It stands out as a unique resource that specifically caters to the contemporary usage of Sanskrit, with a primary emphasis on prose writing. Translation models trained on our dataset demonstrate statistically significant improvements when translating out-of-domain contemporary corpora, outperforming models trained on older classical-era poetry datasets. Finally, we also release benchmark models by adapting four multilingual pre-trained models, three of them have not been previously exposed to Sanskrit for translating between English and Sanskrit while one of them is multi-lingual pre-trained translation model including English and Sanskrit. The dataset and source code is present at https://github.com/ayushbits/saamayik.

Francesco Antici, Andrea Galassi, Federico Ruggeri et al.

We develop novel annotation guidelines for sentence-level subjectivity detection, which are not limited to language-specific cues. We use our guidelines to collect NewsSD-ENG, a corpus of 638 objective and 411 subjective sentences extracted from English news articles on controversial topics. Our corpus paves the way for subjectivity detection in English and across other languages without relying on language-specific tools, such as lexicons or machine translation. We evaluate state-of-the-art multilingual transformer-based models on the task in mono-, multi-, and cross-language settings. For this purpose, we re-annotate an existing Italian corpus. We observe that models trained in the multilingual setting achieve the best performance on the task.

Megan Rose Readman, Fang Wan, Ian Fairman et al.

Observations that hearing loss is a substantial risk factor for dementia may be accounted for by a common pathology. Mitochondrial oxidative stress and alterations in α-synuclein pathology may be common pathology candidates. Crucially, these candidate pathologies are implicated in Parkinson’s disease (PD). Consequently, hearing loss may be a risk factor for PD. Subsequently, this prospective cohort study of the English Longitudinal Study of Ageing examines whether hearing loss is a risk factor for PD longitudinally. Participants reporting self-reported hearing capabilities and no PD diagnosis prior to entry (<i>n</i> = 14,340) were used. A joint longitudinal and survival model showed that during a median follow up of 10 years (SD = 4.67 years) increased PD risk (<i>p</i> < 0.001), but not self-reported hearing capability (<i>p</i> = 0.402). Additionally, an exploratory binary logistic regression modelling the influence of hearing loss identified using a screening test (<i>n</i> = 4812) on incident PD indicated that neither moderate (<i>p</i> = 0.794), nor moderately severe/severe hearing loss (<i>p</i> = 0.5210), increased PD risk, compared with normal hearing. Whilst discrepancies with prior literature may suggest a neurological link between hearing loss and PD, further large-scale analyses using clinically derived hearing loss are needed.

Jascha Grübel, Tyler Thrash, Leonel Aguilar et al.

Smart Cities already surround us, and yet they are still incomprehensibly far from directly impacting everyday life. While current Smart Cities are often inaccessible, the experience of everyday citizens may be enhanced with a combination of the emerging technologies Digital Twins (DTs) and Situated Analytics. DTs represent their Physical Twin (PT) in the real world via models, simulations, (remotely) sensed data, context awareness, and interactions. However, interaction requires appropriate interfaces to address the complexity of the city. Ultimately, leveraging the potential of Smart Cities requires going beyond assembling the DT to be comprehensive and accessible. Situated Analytics allows for the anchoring of city information in its spatial context. We advance the concept of embedding the DT into the PT through Situated Analytics to form Fused Twins (FTs). This fusion allows access to data in the location that it is generated in an embodied context that can make the data more understandable. Prototypes of FTs are rapidly emerging from different domains, but Smart Cities represent the context with the most potential for FTs in the future. This paper reviews DTs, Situated Analytics, and Smart Cities as the foundations of FTs. Regarding DTs, we define five components (Physical, Data, Analytical, Virtual, and Connection environments) that we relate to several cognates (i.e., similar but different terms) from existing literature. Regarding Situated Analytics, we review the effects of user embodiment on cognition and cognitive load. Finally, we classify existing partial examples of FTs from the literature and address their construction from Augmented Reality, Geographic Information Systems, Building/City Information Models, and DTs and provide an overview of future direction

Xuefeng Xu, Huaping Dai, Jinglan Zhang

Abstract Objectives Interleukin (IL)‐25, IL‐33, and thymic stromal lymphopoietin (TSLP) are the important drivers for excessive type‐2 immunity. It has been well elucidated that IL‐25/IL‐33/TSLP plays an important role in allergic airway inflammation and remodeling, whereas their roles in idiopathic pulmonary fibrosis (IPF) still remained largely unclear. Herein, the aim of the review is to discuss the potential role and mechanism of IL‐25/IL‐33/TSLP on IPF by literature analysis and summary. Data source We have done a literature search using the following terms: (“idiopathic pulmonary fibrosis” OR “IPF” OR “lung fibrosis”) and (TSLP or “thymic stromal lymphopoietin” or IL‐25 OR IL‐17E OR IL‐33) from the database of PubMed published in English up to July 2018. Study selection We have totally found 58 articles by using the retrieval terms mentioned above. By careful title and abstract reading, 10 original research articles of high quality were enrolled for the full text reading and analysis. Two additional relevant studies were also included during the course of literature readings. Results IL‐25/IL‐33/TSLP and their corresponding receptors, that is, IL‐17BR/ST2L/TSLPR, are shown to be up‐regulated both in IPF patients and bleomycin (BLM)‐induced lung fibrosis mice model. IL‐25 may promote lung fibrosis by activating IL‐17BR+fibroblast and IL‐17BR+ILC2 (type 2 innate lymphoid cell). Full length (fl)‐IL‐33, as a transcription factor mainly in the cell nucleus, mediated non‐atopic lung inflammation and fibrosis by modulating expressions of several pro‐fibrotic mediators, including transforming growth factor (TGF)‐b1. By contrast, mature (m)‐IL‐33 potentiates lung fibrosis by recruiting ST2L+M2 macrophages and ST2L+ILC2 to enlarge type 2 immunity. TSLP was shown to directly promote CCL2 expression in primary human lung fibroblasts (pHLFs). Conclusion IL‐25/IL‐33/TSLP contributes to non‐allergic lung fibrosis by mediating persistent abnormal epithelial‐mesenchymal crosstalk. IL‐25/IL‐33/TSLP may serve the promising novel target for the treatment of IPF.

Anna Thyberg

For novice students, developing disciplinary literacy in literature courses in English as a Foreign Language education (EFL) at university entails mastering a number of skills. The purpose of this small-scale action research study is to investigate the extent to which two different oral exam formats can serve to make explicit commonly held warrants in the discourse community of literary studies. The material consists of observation notes from Socratic seminars and Thought-Question-Epiphany (TQE) seminars, both of which are analyzed using qualitative content analysis. The results show that most students adopt disciplinary conventions, such as building on each other’s ideas, using critical lenses, showing contextual awareness, and supporting claims with textual evidence. While the Socratic seminar format generates lively discussions, the sole focus on questions prevents students from preparing textual evidence for specific literary elements in the analysis. In the TQE seminar, some students react negatively to the forced inclusion of an epiphany, but the format also gives an opportunity to identify significant quotes in advance and to expand on interpretative ideas prompted by the three components.

Safieh Kananikandeh, Farkhondeh Amin Shokravi, Mojgan Mirghafourvand et al.

Abstract Background Fear of childbirth is an anxiety associated with childbirth, which manifests itself in physical and concentration problems. It is often associated with requesting a cesarean section, and it is prevalent in nulliparous women. This is a study aimed to summarize the published research on the factors for fear of childbirth in nulliparous women in Iran. Methods This study was conducted based on the PRISMA statement. A literature search was performed on nine electronic databases (Web of Sciences, Since Direct, Scopus, PubMed, Cochrane Library, ProQuest, and Persian databases including Scientific Information Database, Irandoc, and Magiran) using keywords related to fear of childbirth, factors, nulliparous, and Iran from 2000 to 2020. This study included cross-sectional studies with full-text in English or Persian in Iran. The quality of the selected studies was evaluated independently by two authors and via the STROBE checklist. Results In this study, 93 articles were identified,13 duplicate articles were excluded, 80 articles were screened by title and abstract, 62 were excluded, and the full-text of 18 articles was assessed for analysis. Of these, 12 were excluded, and six articles were reviewed. Six studies were conducted in different provinces of Iran. Based on the study results, factors of the fear of childbirth in nulliparous women were: biological (the process of labor and childbirth and labor pain, concern for the baby (harm to the baby and baby infirmity), psychological (painful injections during labor and suturing in childbirth), and individual (loss of control during labor). Conclusions This study identified four main factors that affect fear of childbirth status in nulliparous women, and concern for the baby was a more common factor in this study. In conclusion, these factors can be reduced by increasing their assurance about child health, training during pregnancy, talking about positive experiences, and holding workshops.

Leshem Choshen, Matanel Oren, Dmitry Nikolaev et al.

SERRANT is a system and code for automatic classification of English grammatical errors that combines SErCl and ERRANT. SERRANT uses ERRANT's annotations when they are informative and those provided by SErCl otherwise.

Andreas Chandra, Affandy Fahrizain, Ibrahim et al.

Research in question answering datasets and models has gained a lot of attention in the research community. Many of them release their own question answering datasets as well as the models. There is tremendous progress that we have seen in this area of research. The aim of this survey is to recognize, summarize and analyze the existing datasets that have been released by many researchers, especially in non-English datasets as well as resources such as research code, and evaluation metrics. In this paper, we review question answering datasets that are available in common languages other than English such as French, German, Japanese, Chinese, Arabic, Russian, as well as the multilingual and cross-lingual question-answering datasets.