Hasil untuk "English literature"

Masudul Hasan Masud Bhuiyan, Manish Kumar Bala Kumar, Cristian-Alexandru Staicu

The open-source software (OSS) community has historically been dominated by English as the primary language for code, documentation, and developer interactions. However, with growing global participation and better support for non-Latin scripts through standards like Unicode, OSS is gradually becoming more multilingual. This study investigates the extent to which OSS is becoming more multilingual, analyzing 9.14 billion GitHub issues, pull requests, and discussions, and 62,500 repositories across five programming languages and 30 natural languages, covering the period from 2015 to 2025. We examine six research questions to track changes in language use across communication, code, and documentation. We find that multilingual participation has steadily increased, especially in Korean, Chinese, and Russian. This growth appears not only in issues and discussions but also in code comments, string literals, and documentation files. While this shift reflects greater inclusivity and language diversity in OSS, it also creates language tension. The ability to express oneself in a native language can clash with shared norms around English use, especially in collaborative settings. Non-English or multilingual projects tend to receive less visibility and participation, suggesting that language remains both a resource and a barrier, shaping who gets heard, who contributes, and how open collaboration unfolds.

Nguyen Huu Nhat Minh, Tran Nguyen Anh, Truong Dinh Dung et al.

Cross-lingual phoneme recognition has emerged as a significant challenge for accurate automatic speech recognition (ASR) when mixing Vietnamese and English pronunciations. Unlike many languages, Vietnamese relies on tonal variations to distinguish word meanings, whereas English features stress patterns and non-standard pronunciations that hinder phoneme alignment between the two languages. To address this challenge, we propose a novel bilingual speech recognition approach with two primary contributions: (1) constructing a representative bilingual phoneme set that bridges the differences between Vietnamese and English phonetic systems; (2) designing an end-to-end system that leverages the PhoWhisper pre-trained encoder for deep high-level representations to improve phoneme recognition. Our extensive experiments demonstrate that the proposed approach not only improves recognition accuracy in bilingual speech recognition for Vietnamese but also provides a robust framework for addressing the complexities of tonal and stress-based phoneme recognition

Dragan Filimonovic, Christian Rutzer, Jeffrey Macher et al.

A growing literature documents that generative artificial intelligence (GenAI) is changing scientific writing, yet most studies focus on absolute changes in vocabulary or readability. An important question remains unanswered: Does GenAI use lead to systematic convergence, or a narrowing of stylistic gaps relative to the dominant form of scientific English? Unlike absolute changes, convergence signals whether language-related publication barriers are declining and suggests broader implications for participation and competition in global science. This study directly addresses this question using 5.65 million English-language scientific articles published from 2021 to 2024 and indexed in Scopus. We measure linguistic similarity to a U.S. benchmark corpus using SciBERT text embeddings, and estimate dynamic changes using an event-study difference-in-differences design with repeated cross-sections centered on the late-2022 release of ChatGPT. We find that GenAI-assisted publications from non-English-speaking countries exhibit statistically significant and increasing convergence toward U.S. scientific English, relative to non-GenAI-assisted publications from these countries. This effect is strongest for domestic author teams from countries more linguistically distant from English and for articles published in lower-impact journals -- precisely the contexts where language barriers have historically been most consequential. The results suggest that GenAI tools are reducing language-related barriers in scientific publications. Whether this represents genuine inclusion or a deepening dependence on a single linguistic standard remains an open question.

Christopher D. Yang, Christine K. Kim, Melissa M. Chang et al.

Objective To evaluate the current body of literature pertaining to the use of ocular point-of-care ultrasound (POCUS) in the emergency department (ED). Methods A comprehensive literature search was conducted on Scopus, Web of Science, MEDLINE, and Cochrane Central Register of Controlled Trials (CENTRAL) databases. Inclusion criteria were studies written in English and primary clinical studies involving ocular POCUS scans in an ED setting. Exclusion criteria were nonprimary studies (e.g., reviews or case reports), studies written in a non-English language, nonhuman studies, studies performed in a nonemergency setting, studies involving non-POCUS ocular ultrasound modalities, or studies published more than 10 years prior. Data extraction was guided by the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) recommendations. Results The initial search yielded 391 results with 153 duplicates. Of the remaining 238 studies selected for retrieval and screening, 24 met the inclusion criteria. These 24 included studies encompassed 2,448 patients across prospective, retrospective, cross-sectional, and case series study designs. The majority of included studies focused on the use of POCUS in the ED to measure optic nerve sheath diameter as a proxy for papilledema and metabolic aberrations, while a minority of studies used ocular POCUS to assist in the diagnosis of orbital fractures or posterior segment pathology. Conclusion The vast majority of studies investigating the use of ocular POCUS in recent years emphasize its utility in measuring optic nerve sheath diameter and fluctuations in intracranial pressure, though additional outcomes of interest include pathology of the posterior segment, orbit, and globe.

Büşra Yılmaz

This literature review aims to examine the results of scientific studies conducted to date under the title of sports injuries, both their effects on the athletic performance of athletes and their changes on the financial stability of sports clubs from an interdisciplinary perspective. The study is founded upon a thorough review of extant literature. In the course of preparing the review, a number of databases were searched, including Google Scholar, PubMed, and ResearchGate. The following Turkish keywords were used: sports economics, rehabilitation, injury prevention and sports clubs. The same keywords were also searched for in their English equivalents. The following subjects will be covered: sports economics, rehabilitation, injury prevention, and sports clubs. The present study exclusively encompasses publications in Turkish and English. The findings emphasise the pivotal role of strategic approaches to load management and injury prevention, not only in optimising athlete performance but also in their substantial ramifications for the economic landscape of sport. In this context, the study emphasises that the prevention of sports injuries should not be regarded solely as a health issue, but also as a fundamental component of sports economics.

Caroline Sabty

Natural Language Processing (NLP) is a vital computational method for addressing language processing, analysis, and generation. NLP tasks form the core of many daily applications, from automatic text correction to speech recognition. While significant research has focused on NLP tasks for the English language, less attention has been given to Modern Standard Arabic and Dialectal Arabic. Globalization has also contributed to the rise of Code-Switching (CS), where speakers mix languages within conversations and even within individual words (intra-word CS). This is especially common in Arab countries, where people often switch between dialects or between dialects and a foreign language they master. CS between Arabic and English is frequent in Egypt, especially on social media. Consequently, a significant amount of code-switched content can be found online. Such code-switched data needs to be investigated and analyzed for several NLP tasks to tackle the challenges of this multilingual phenomenon and Arabic language challenges. No work has been done before for several integral NLP tasks on Arabic-English CS data. In this work, we focus on the Named Entity Recognition (NER) task and other tasks that help propose a solution for the NER task on CS data, e.g., Language Identification. This work addresses this gap by proposing and applying state-of-the-art techniques for Modern Standard Arabic and Arabic-English NER. We have created the first annotated CS Arabic-English corpus for the NER task. Also, we apply two enhancement techniques to improve the NER tagger on CS data using CS contextual embeddings and data augmentation techniques. All methods showed improvements in the performance of the NER taggers on CS data. Finally, we propose several intra-word language identification approaches to determine the language type of a mixed text and identify whether it is a named entity or not.

Zixian Huang, Wenhao Zhu, Gong Cheng et al.

Reasoning capabilities are crucial for Large Language Models (LLMs), yet a notable gap exists between English and non-English languages. To bridge this disparity, some works fine-tune LLMs to relearn reasoning capabilities in non-English languages, while others replace non-English inputs with an external model's outputs such as English translation text to circumvent the challenge of LLM understanding non-English. Unfortunately, these methods often underutilize the built-in skilled reasoning and useful language understanding capabilities of LLMs. In order to better utilize the minds of reasoning and language understanding in LLMs, we propose a new method, namely MindMerger, which merges LLMs with the external language understanding capabilities from multilingual models to boost the multilingual reasoning performance. Furthermore, a two-step training scheme is introduced to first train to embeded the external capabilities into LLMs and then train the collaborative utilization of the external capabilities and the built-in capabilities in LLMs. Experiments on three multilingual reasoning datasets and a language understanding dataset demonstrate that MindMerger consistently outperforms all baselines, especially in low-resource languages. Without updating the parameters of LLMs, the average accuracy improved by 6.7% and 8.0% across all languages and low-resource languages on the MGSM dataset, respectively.

Alessandro Bensa, Alessandro Sangiorgio, Luca Deabate et al.

Aims: Robotic-assisted unicompartmental knee arthroplasty (R-UKA) has been proposed as an approach to improve the results of the conventional manual UKA (C-UKA). The aim of this meta-analysis was to analyze the studies comparing R-UKA and C-UKA in terms of clinical outcomes, radiological results, operating time, complications, and revisions. Methods: The literature search was conducted on three databases (PubMed, Cochrane, and Web of Science) on 20 February 2024 according to the guidelines for Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA). Inclusion criteria were comparative studies, written in the English language, with no time limitations, on the comparison of R-UKA and C-UKA. The quality of each article was assessed using the Downs and Black Checklist for Measuring Quality. Results: Among the 3,669 articles retrieved, 21 studies on 19 series of patients were included. A total of 3,074 patients (59.5% female and 40.5% male; mean age 65.2 years (SD 3.9); mean BMI 27.4 kg/m2 (SD 2.2)) were analyzed. R-UKA obtained a superior Knee Society Score improvement compared to C-UKA (mean difference (MD) 4.9; p < 0.001) and better Forgotten Joint Score postoperative values (MD 5.5; p = 0.032). The analysis of radiological outcomes did not find a statistically significant difference between the two approaches. R-UKA showed longer operating time (MD 15.6; p < 0.001), but reduced complication and revision rates compared to C-UKA (5.2% vs 10.1% and 4.1% vs 7.2%, respectively). Conclusion: This meta-analysis showed that the robotic approach for UKA provided a significant improvement in functional outcomes compared to the conventional manual technique. R-UKA showed similar radiological results and longer operating time, but reduced complication and revision rates compared to C-UKA. Overall, R-UKA seems to provide relevant benefits over C-UKA in the management of patients undergoing UKA. Cite this article: Bone Jt Open 2024;5(5):374–384.

Muhammad Adnan Akbar, Maria Farooq Maan

This study investigates the integration of Sartrean ethical principles in Kafka's literary works and challenges the usefulness of existentialist ethics. Sartre's Notebook for An Ethics (1983) argues that existentialism is a practical ethical theory that challenges the separation of theoretical and practical aspects. Warnock echoes this in Existential Ethics (1967). By examining key works by Sartre, including Existentialism and Humanism (1946) and Being and Nothingness (1943), the research explores the fundamental concepts of Sartrean ethics, which include freedom, bad faith, responsibility, and anguish. Sartre rejects absolute values, prioritizing subjectivity while acknowledging authenticity and good faith. Although Kierkegaard and Heidegger do not explicitly address existential ethics, they contribute to ethical concerns. The study employs a qualitative d phenomenological approach, emphasizing Ricoeur's hermeneutic phenomenology. The theoretical framework is based on Sartre's Ethics and Emotive Nuisance concepts. The epistemological position aligns with Heidegger's interpretive technique. In the Kafkaesque World, characters struggle with existential perplexity amid modern-age horrors, exploring the traumas of existence. The research develops systematic frameworks to understand the ethical standpoint of this world, where characters face entanglement in chaotic existential paraphernalia and emotive nuisance. Emotions linked to existential ethics are examined to clarify the impact of emotion on ethical conduct.

Mar Suarez, Maria Soledad Beato

In the globalized world we live in, it is increasingly common for people to speak more than one language. Although research in psychology has been widely interested in the study of false memories with the Deese/Roediger-McDermott (DRM) paradigm, to date, there is a scarcity of studies comparing false memories in the first and the second language (L1 and L2, respectively). It is noteworthy that one of the most studied variables in the DRM paradigm, the backward associative strength (BAS), has hardly been studied in the L2. Moreover, the only study that recently examined this matter found differences in the knowledge of L2-word meaning between the high-BAS and low-BAS lists, which would hinder the interpretation of the BAS effect in L2 false memories. Taking all this into account, the current work examined false memories in the L1 (Spanish) and the L2 (English) as a function of BAS overcoming the limitations of the previous study. We selected DRM lists using both Spanish and English free association norms and lists were constructed to vary in BAS values while controlling the knowledge of word meaning. Results showed that false recognition was greater in the L1 or dominant language than in the L2 or non-dominant language. Furthermore, BAS modulated the false recognition in both the L1 and the L2. That is, false recognition was higher in high-BAS than low-BAS lists in both languages. Sensitivity index from the signal-detection theory helped us gain further insight into these results. The main findings are discussed in the light of theoretical models from both the false memory and the second language processing literature. Finally, practical implications and future research are provided.

Mario Esparza

Audio recordings of collaborative learning environments contain a constant presence of cross-talk and background noise. Dynamic speech recognition between Spanish and English is required in these environments. To eliminate the standard requirement of large-scale ground truth, the thesis develops a simulated dataset by transforming audio transcriptions into phonemes and using 3D speaker geometry and data augmentation to generate an acoustic simulation of Spanish and English speech. The thesis develops a low-complexity neural network for recognizing Spanish and English phonemes (available at github.com/muelitas/keywordRec). When trained on 41 English phonemes, 0.099 PER is achieved on Speech Commands. When trained on 36 Spanish phonemes and tested on real recordings of collaborative learning environments, a 0.7208 LER is achieved. Slightly better than Google's Speech-to-text 0.7272 LER, which used anywhere from 15 to 1,635 times more parameters and trained on 300 to 27,500 hours of real data as opposed to 13 hours of simulated audios.

Abhinav Rao, Ho Thi-Nga, Chng Eng-Siong

This paper presents the work of restoring punctuation for ASR transcripts generated by multilingual ASR systems. The focus languages are English, Mandarin, and Malay which are three of the most popular languages in Singapore. To the best of our knowledge, this is the first system that can tackle punctuation restoration for these three languages simultaneously. Traditional approaches usually treat the task as a sequential labeling task, however, this work adopts a slot-filling approach that predicts the presence and type of punctuation marks at each word boundary. The approach is similar to the Masked-Language Model approach employed during the pre-training stages of BERT, but instead of predicting the masked word, our model predicts masked punctuation. Additionally, we find that using Jieba1 instead of only using the built-in SentencePiece tokenizer of XLM-R can significantly improve the performance of punctuating Mandarin transcripts. Experimental results on English and Mandarin IWSLT2022 datasets and Malay News show that the proposed approach achieved state-of-the-art results for Mandarin with 73.8% F1-score while maintaining a reasonable F1-score for English and Malay, i.e. 74.7% and 78% respectively. Our source code that allows reproducing the results and building a simple web-based application for demonstration purposes is available on Github.

shea wesley martin, Henry “Cody” Miller

The COVID-19 pandemic, coupled with the ensuing lockdown and political turmoil, ruptured many young people’s experiences and well-being, particularly students who face additional marginalization due to systemic oppression. A national survey conducted by the Trevor Project (2021) found that nearly 70% of LGBTQ youth noted that their health was “poor” most or all of the time during the COVID-19 pandemic. Factors contributing to this deterioration include LGBTQ youth being isolated from the supportive communities formed at school, lacking access to social services provided by schools, and being quarantined with family members who were unsupportive (Cohen, 2021; Valencia, 2020). These fissures in support and resource structures curtailed potentially affirming and integral education, social, and emotional experiences, particularly for LGBTQ youth who thrived in traditional schooling settings. However, it is also important to note that even prior to the COVID-19 pandemic, many schools were not idealized institutions for LGBTQ youth. K-12 schools, situated in the broader socio-political landscape of the United States, are bastions of homo-, trans-, and queerphobia (Mayo, 2014). Still, many LGBTQ young people employed resilience and ingenuity to create affirming and loving social circles, which were thus interrupted by restrictions, trauma, and isolation during the pandemic. As LGBTQ educators we sought to co-create an online community that could reflect the brilliance and joy of LGBTQ youth during the 2020-2021 school year. Through both our own experiences and the research, we know that LGBTQ youth find ways to construct community through online avenues, even when said avenues are limited and flawed, such as Tumblr (Cavalcante, 2019; Haimson, et al., 2021; Wargo, 2017). Building on our experiences as secondary English language arts teachers, we constructed a national online book club dedicated to reading, analyzing, and celebrating LGBTQ young adult literature with LGBTQ youth. After a summer of planning, we launched the online book club that resulted in over 125 secondary students from across the United States (and some international students) joining us for a year to engage in readings of Abdi Nazemian’s Like a Love Story (2019), Dean Atta’s Black Flamingo (2019), Gabby Rivera’s Juliet Takes a Breath (2016), and Mark Oshiro’s Anger is a Gift (2018). This article details how we structured a community of readers who worked to analyze young adult literature through intersectional and anti-oppressive lenses (Blackburn & Smith, 2010; Durand, 2015; Herman-Wilmarth & Ryan, 2015), deepen their critical consciousness relating to contemporary LGBTQ socio-political topics (Kelly & Currie, 2020), and leveraged social media and online avenues to construct community that expanded the boundaries of school hallways (Lucero, 2017; Mayo, 2014). Collectively, we seek to illustrate how LGBTQ+ communities (and queer pedagogies) can flourish and develop outside the limitations of K-12 institutions.

Tuti Hidayati

Indonesian ELT is complex for numerous reasons, and the level of students' outcome has been regarded unsatisfactory by a number of researchers and academics. This paper considers ICT as one of possible alternatives to deal with the complexity of Indonesian ELT and to improve its outcomes. It widely explores ICT integration in English LTL, especially on how ICT has been used in this field. It further investigates the benefits and challenges of integrating ICT in LTL. The paper argues that the integration of ICT is promising for changing and improving the effectiveness of the current Indonesian ELT condition when it is carried out in line with the effective LTL principles. The integration of ICT will enable teachers to vary teaching and learning activities, to gradually change the teaching style to be more student-centred, to train students to have more active role in learning, and to access a huge range of authentic learning materials. The paper also acknowledges the contraints that will emerge in an effort of integrating ICT in Indonesian English LTL. Hence, some recommedations for action are proposed at the end.

Marianna M. Korenkova

The article discusses an introductory lecture from the series «Lectures on the Present Position of Catholics in England» by J. H. Newman. John Henry Newman is a versatile figure in 19th century English society, with his interests spanning philosophy, theology, church history and education; he opened Catholic oratorio schools and the new Catholic University in Dublin. He wrote tracts on vision for the Church of England and the search for a middle way between the high and low church of England during his activity as one of the leaders of the Oxford movement, which he joined a Protestant and left it a Catholic, becoming a cardinal in 1879. After some controversy, Newman was beatified by Pope Benedict XVI on September 19, 2010. Since becoming a Catholic, Newman had devoted himself to the apologetics of the Catholic Church in England and the development of education for Catholics. It was for this purpose that he wrote Lectures on the Present Position of Catholics in England. The article concerns the first lecture of the entire series, since its rhetoric sets the perspective of a dispute with English Protestants with the aim of further revealing the complex issue of the social practice of anti-Catholicism and, at the same time, apologetics of the Catholic Church in the next eight lectures of the cycle. The practice of accusing and attacking Catholics by Protestants gave rise to Newman’s public protest against it. However, the lecturer remained within the framework of a respectful attitude towards the Protestant part of the audience, illustrating its incorrectness and one-sidedness of judgments with fables and examples from literature.

Bill Yuchen Lin, Seyeon Lee, Xiaoyang Qiao et al.

Commonsense reasoning research has so far been limited to English. We aim to evaluate and improve popular multilingual language models (ML-LMs) to help advance commonsense reasoning (CSR) beyond English. We collect the Mickey Corpus, consisting of 561k sentences in 11 different languages, which can be used for analyzing and improving ML-LMs. We propose Mickey Probe, a language-agnostic probing task for fairly evaluating the common sense of popular ML-LMs across different languages. In addition, we also create two new datasets, X-CSQA and X-CODAH, by translating their English versions to 15 other languages, so that we can evaluate popular ML-LMs for cross-lingual commonsense reasoning. To improve the performance beyond English, we propose a simple yet effective method -- multilingual contrastive pre-training (MCP). It significantly enhances sentence representations, yielding a large performance gain on both benchmarks.

Albert Cao, Felix Christian Clemen, Sean English et al.

In a Maker-Breaker game there are two players, Maker and Breaker, where Maker wins if they create a specified structure while Breaker wins if they prevent Maker from winning indefinitely. A $3$-term arithmetic progression, or $3$-AP, is a sequence of three distinct integers $a, b, c$ such that $b-a = c-b$. The $3$-AP game is a biased Maker-Breaker game played on $[n]$ where every round Breaker selects $q$ unclaimed integers for every Maker's one integer. Maker is trying to select points such that they have a $3$-AP and Breaker is trying to prevent this. The main question of interest is determining the threshold bias $q^*(n)$, that is the minimum value of $q=q(n)$ for which Breaker has a winning strategy. Kusch, Rué, Spiegel and Szabó initially asked this question and proved $\sqrt{n/12-1/6}\leq q^*(n)\leq \sqrt{3n}$. We find new strategies for both Maker and Breaker which improve the existing bounds to \[ (1+o(1))\sqrt{\frac{n}{5.6}} \leq q^*(n) \leq \sqrt{2n} +O(1). \]

Ceren Kocaman, Selvi Ali Fuad

Even though much has been said and written about commercial materials, our understanding is very limited when it comes to locally-produced (in-house, non-commercial) materials that are often used to replace or supplement existing published materials. In this piece, we share a review of literature on how gender and sexualities are represented in commercial coursebooks and our reflections on locally-produced instructional materials used in an Intensive English Program in an English Medium Instruction (EMI) university in Turkey. We underscore the vitality of materials in giving teachers agency in establishing in safe and inclusive classroom spaces, and countering systematic oppressions, discrimination and injustices in and beyond the classroom.

Zulamar Aguiar Cargnin, Dulcinéia Ghizoni Schneider, Mara Ambrosina de Oliveira Vargas

Objective: to identify strategies for the prevention and rehabilitation of low back pain in nursing workers. Method: integrative literature review. The searches took place in the LILACS, MEDLINE / PUBMED, and SCIELO databases, including articles in English, Spanish and Portuguese from 2009 to 2019. Results: the 14 publications found enabled the construction of three categories: “testing strategies”, “complementary rehabilitation strategies”, and “combined strategies”. Prevention consisted mainly of online education and strategies based on the Health Belief Model. The complementary strategies found were massage, myofascial release and yoga. Combined strategies such as the Spine School seem to provide a more adequate model for the management of non-specific lower back pain. Conclusion: because of the small number of publications on the subject, new studies are needed to obtain better results on these strategies usage rates and the adoption of mainly multimodal new approaches for this specific population in its work environment.

Gautam Krishna, Co Tran, Yan Han et al.

In this paper we demonstrate continuous noisy speech recognition using connectionist temporal classification (CTC) model on limited Chinese vocabulary using electroencephalography (EEG) features with no speech signal as input and we further demonstrate single CTC model based continuous noisy speech recognition on limited joint English and Chinese vocabulary using EEG features with no speech signal as input. We demonstrate our results using various EEG feature sets recently introduced in [1] as well as we propose a new deep learning architecture in this paper which can perform continuous speech recognition using raw EEG signals on limited joint English and Chinese vocabulary.