Search Results (48)

Revealing correlations for styles in texts has been an interesting topic, providing an example of trans-disciplinarity between physics and linguistics. Typical cases can be seen for sound correlations in verses as well as for word correlations in prose. Of these, long-range correlations are of particular interest because of their connection to the Markovian nature in human cognition. For a famous novel written in an archaic style of Japanese, we conduct an analysis of a series of kanji compounds in the text. Here, kanji is a Japanese name for Chinese characters. Specifically, we focus on the number (equivalent to the length) of a compound. Subsequently, the sequence of numbers is expanded into 6-bit binary codes (equivalent to 64 modes). Replacing each compound in the text with an oscillator in a string, for the chain of the kanji compounds, one can find an analogy with the so-called Fermi-Pasta-Ulam-Tsingou (FPUT) model. Comparative analyses for 16 modern translations by humans and machines show, without exception, a strong dominance for a particular mode and its stability bearing a remote resemblance to a soliton, and at the same time, reproduce a statistical property far from a sort of ergodicity. Furthermore, comparison between the human and machine translations shows that the entropy of the latter is higher than that of the former because machines are subjected to neither a psychological bias nor an inspection by editors. Lastly, in addition to the above translated texts, 6 codices of the classic are also analyzed, and their results are compared with those of the modern translations. Note that the original of the classic has not been found yet. Full article

Compilation-based text editors, such as Overleaf for enable users to insert text alongside commands, which are then compiled into a formatted document such as a PDF. A major drawback of these editors is the inability to preview the final document layout without compiling. Consequently, users often resort to trial-and-error methods to condense documents to meet space constraints, making changes in the text editor and repeatedly compiling to check whether the document fits the required space. In addition, space-saving modifications may compromise the readability of the document. For example, reducing the size of a figure by 50% can render it unreadable. In this paper, we formally define the problem of optimizing document layout to fit space constraints while minimizing the magnitude of layout modifications and thereby reducing the likelihood of harming readability. To address this challenge, we propose an automated decision-support system that employs machine learning models to estimate the space saved by specific adjustments. This system provides recommendations for modifications that optimize space usage while favoring smaller geometric changes, with final readability and layout quality verified separately. To evaluate the quality and real-world applicability of our algorithms, we conducted extensive experiments. First, we tested our algorithms on a dataset of 329,000 generated files, achieving improved reductions in document length compared with baseline heuristics. To assess applicability to real-world scenarios, we further evaluated our algorithms on 140 articles accepted to AAAI and obtained from arXiv. These experiments show that, in this benchmark setting, the proposed method achieves the best observed performance among the compared approaches, with moderate but consistent improvements over simpler methods and heuristics. Full article

Background/Objectives: Metabolic dysfunction-associated steatotic liver disease (MASLD) is highly prevalent among patients with type 2 diabetes (T2D) and has been increasingly recognized as a potential contributor to cardiovascular (CV) disease. However, the relationship between MASLD and subclinical/clinical atherosclerosis remains controversial, with inconsistent findings across imaging modalities and study populations. Methods: A systematic review was conducted according to PRISMA guidelines and registered in PROSPERO (CRD420261347480). Literature searches were performed across the PubMed, Scopus, and Web of Science library databases from 1 January 2016 to 27 March 2026, using the terms: “MASLD AND (type 2 diabetes OR type 2 diabetes mellitus OR T2DM) AND atherosclerotic plaque” for each of the three databases. Inclusion criteria comprised original full-text English-language studies, published in the last 10 years and conducted in adults, reporting data regarding the evaluation of atherosclerosis in patients with T2D and MASLD/NAFLD. Exclusion criteria are letters to the editor, expert opinions, case reports, conference or meeting abstracts, reviews, and redundant publications; having unclear or incomplete data; and being performed in vitro (cell cultures) or in animal models. The quality of included studies was assessed using the Newcastle–Ottawa Scale. Results: The included studies, predominantly cross-sectional and a single longitudinal study, as well as different modalities of evaluating atherosclerosis, showed heterogeneous findings. MASLD is associated with increased carotid plaque progression, including in lean individuals. Its relationship with carotid intima-media thickness (CIMT) is inconsistent across studies, with some reporting higher values and others finding no significant association after adjustment. Hepatic fibrosis appears more strongly linked to vascular aging than steatosis alone, with variability likely due to differences in study methods and populations. Conclusions: The presence of both MASLD and T2D may be associated with atherosclerosis across different stages, from subclinical changes to clinically manifest disease, particularly at more advanced stages such as plaque presence or progression, whereas its relationship with early markers like pulse wave velocity or CIMT remains inconsistent. Liver fibrosis may represent a stronger determinant of atherosclerosis than hepatic steatosis alone. Although the evidence base is limited and largely derived from a small number of predominantly cross-sectional studies, further standardized and prospective research is warranted to better define these relationships and evaluate CV risk stratification in patients with T2D. Full article

The rapid integration of generative artificial intelligence into scientific publishing is reshaping how academic text can be produced, revised, and scaled. While transparent and limited use of AI for language support may be acceptable, a new structural vulnerability may be emerging in medical publishing: the large-scale production of short, plausible, and weakly individualized correspondence across multiple specialties. In this viewpoint, we describe and conceptualize a pattern that may be termed synthetic authorship, defined not as undisclosed AI use alone, but as a reproducible mode of scholarly output structurally facilitated by automation. We focus particularly on letters to the editor, a format that combines brevity, rapid editorial handling, and formal indexation, and may therefore be especially exposed to this phenomenon. Based on recurring patterns observed in PubMed-indexed literature, including unusually high publication velocity, abrupt thematic dispersion, and stylistic uniformity across unrelated domains, we argue that such outputs may challenge the authenticity, epistemic value, and editorial function of scientific correspondence. We do not present empirical proof of misconduct, but rather outline a conceptual framework for understanding this emerging risk and propose proportionate editorial safeguards, including cross-domain pattern detection and contextual assessment of authorship coherence. As AI lowers the threshold for generating domain-plausible commentary at scale, scientific publishing must adapt its integrity frameworks accordingly. In this context, vigilance toward synthetic authorship may become an essential component of editorial responsibility and post-publication quality control. Full article

This paper presents how an ontology-based Knowledge Graph (KG) for basketball box scores can be exploited to support several real use cases, and also presents competency questions, including sports analytics, complex question answering and data browsing with semantic filters. To illustrate this, we present the BBall ontology, the modeling decisions and the key advantages of creating a KG based on this ontology. Then, we introduce a KG covering 25 seasons of the EuroLeague and more than 5 million triples, and we showcase the functionality of three research prototypes based on that KG, particularly a faceted search application with semantic filters and two text-to-SPARQL applications leveraging LLMs, including support for multilingual queries. The first LLM-based application enables SPARQL query editing, and the second is a chat-based application offering interactive dialogue between the user and the system. For these applications, we describe their functionality and approach, and we compare them (along with a classical SPARQL query editor) in several dimensions. Finally, we provide the statistics for the constructed KG, indicative SPARQL queries addressing the competency questions, results and error analysis for the text-to-SPARQL method, efficiency results, and a historical analysis showing the evolution of several factors of EuroLeague basketball from 2000 to 2025. Full article

Prior research has overlooked interdependent effect sizes and moderating factors between machine translation post-editing (MTPE) and the post-editor’s cognition. To fill this void, the study employs a three-level meta-analysis. A total of 19 high-quality studies, with an average quality score of 8.158, were included in the analysis. These included studies encompass 193 effect sizes and 492 participants. The findings indicate a positive link between MTPE and the post-editor’s cognition (r = 0.474), suggesting higher levels of cognitive engagement in post-editing tasks. Among the moderators examined, several study-level characteristics were associated with variability in effect sizes. These characteristics include whether PE attitudes were reported, text types, cognition measurement tools, and cognitive indicators. In contrast, studies that reported MTPE attitudes showed a different pattern of effect sizes. Overall, this study provides rigorous evidence on the multifaceted impacts of MTPE on translators’ cognition. It also clarifies how dependent effect sizes should be modeled in translation cognition research. Full article

The ability to revise texts to meet the needs and expectations of the target audience requires sustained and deliberate practice. Revision becomes more complex when working on somebody’s else text and in a second language. Against this background, we conducted an exploratory and descriptive case study qualitatively shedding light on the characteristics of the processes and the products of revision. We collected data from three graduate students revising a business text in English (their second language) and from an experienced writer/editor, native English speaker, revising the same text in his first language. Using keystroke logging, screen recording, and text analysis, we observed an alternation between revision and rewriting, as well as a combination of expert features (e.g., inclusion of reader-oriented explanations) and less expert features (e.g., fewer rounds of revision) among graduate students. There were also differences between the students and the expert in the way in which they spatially organised their tasks. We interpreted these results within the context of cognitive and sociocultural models of writing, and especially the notion of agency. Full article

Background and Objectives: Acute and obstructive pyelonephritis (AOP) management, despite advancements in diagnostic imaging and antimicrobial therapy, is characterized by delayed recognition and increasing antimicrobial resistance. This review aimed to summarize current evidence regarding the clinical characteristics, microbiological spectrum, biomarkers, and imaging findings associated with AOP. Materials and Methods: A systematic review was conducted according to PRISMA guidelines and registered in PROSPERO (CRD420251162736). Literature searches were performed across the PubMed, Scopus, and Web of Science databases for articles published between January 2014 and 31 March 2025 using the term “acute obstructive pyelonephritis”. Inclusion criteria comprised original full-text English-language studies, published in the last 10 years and conducted in adults, reporting clinical, laboratory, microbiological, and imaging characteristics. Exclusion criteria are letters to the editor, expert opinions, case reports, conference or meeting abstracts, reviews, and redundant publications; having unclear or incomplete data; and being performed on cell cultures or on mammals. The quality of included studies was assessed using the Newcastle–Ottawa Scale. Results: Twenty-three studies met the inclusion criteria. AOP predominantly affected elderly patients with comorbidities, especially diabetes mellitus and urinary tract obstruction. Predictors of septic shock included thrombocytopenia, hypoalbuminemia, elevated procalcitonin (>1.12 µg/L), presepsin, and a neutrophil-to-lymphocyte ratio ≥ 8.7. Escherichia coli remained the leading pathogen (60–95%) with extended-spectrum β-lactamase (ESBL) rates between 20 and 70%, followed by Klebsiella pneumoniae. CT demonstrated 71–100% sensitivity for detecting obstructive complications, confirming its superiority over ultrasound, while MRI provided comparable diagnostic accuracy in selected cases. Source control through double-J stenting or percutaneous drainage significantly improved survival. Conclusions: AOP requires prompt recognition and early decompression to prevent sepsis-related mortality. Biomarkers such as procalcitonin, presepsin, and neutrophil to lymphocyte ratio enhance risk stratification, while CT remains the gold-standard imaging modality. The increasing prevalence of ESBL-producing pathogens underscores the need for antimicrobial stewardship and individualized therapeutic strategies guided by local resistance data. Full article

This study examines the adoption of artificial intelligence (AI) among micro and small hospitality enterprises in Slovenia, a small EU economy where digital transformation remains limited. It explores how organisational characteristics and managers’ attitudes toward AI are related to its adoption and firms’ operating revenues. Data were collected from 286 accommodation and food-and-beverage enterprises through a structured questionnaire completed by managers or owner–managers, complemented by secondary official financial data. Using ordinary least squares regression, the analysis examined associations among organisational characteristics, managerial attitudes, AI use intention and adoption, and financial performance. The results indicate that firm size and structural features alone are not closely linked to digital transformation. AI adoption shows stronger associations with managers’ positive attitudes and with factors such as non-family ownership and smaller firm size. The overall General Attitudes toward AI Scale (GAAIS) score showed no direct relationship with revenue, but two specific items—enthusiasm for AI and recognition of business opportunities—were positively associated with higher revenues. Among AI tools, only smart text editors and CRM systems were statistically associated with revenues, suggesting that better-performing firms are more likely to use simpler, more affordable technologies. The study provides contextual evidence on behavioural and organisational dimensions of AI adoption in resource-constrained hospitality SMEs. Full article

This article examines how young adults in higher education (Generation Z) perceive the usefulness of ChatGPT by analyzing five learning-support roles within the Technology Acceptance Model (TAM), Expectation–Confirmation Theory (ECT), and Task–Technology Fit (TTF). Drawing on an online survey of 409 students from Polish universities and nonparametric analyses, this study consistently finds that students rate ChatGPT’s potential higher than its current usefulness. The tool is evaluated most favorably as a tutor, task assistant, text editor, and teacher, while its motivational role is rated least effective. Usage patterns matter: students who used ChatGPT for writing tasks rated its assistance with educational assignments more highly, and those who used it for learning activities rated its teaching role more strongly. The strongest evaluations appear when model capabilities such as structuring, summarizing, step-by-step explanations, and personalization align with task requirements. By integrating TAM, ECT, and TTF, this study advances evidence on how Gen Z engages with conversational AI and offers practical guidance for educators, support services, and youth-focused policymakers on equitable and responsible use. Full article

The Dīpavaṃsa (Dīp), the first historical account of the Buddhist religion that has survived in Pali, is widely known through Oldenberg’s late-19th century edition (designated hereafter O). The editor himself admitted it was faulty due to the quality of his Sri Lankan manuscript sources, all of which he thought were derived from a faulty Burmese exemplar. This problematic edition prompted new printed editions of Dīp in Sri Lanka and Myanmar in the 1920s, but Western scholarship established it as a ‘problem’ text, and it was thus generally neglected in favour of the later Mahāvaṃsa. A new edition of Dīp has long been a desideratum, and in 2004 Frasch pointed out the existence of a Burmese manuscript of a different text of the work, which, for the purposes of the present discussion, we designate B1. The present authors identified two further mss. of this version and have begun editing a new edition based on this in comparison to Oldenberg and other Burmese mss. The Burmese sources reveal an occasionally faulty but widely disseminated text, designated B2, that is not dissimilar to O, plus the rather ‘better’ text of B1. In addition, we have also identified the so-called ‘Dīpavaṃsa-ṭīkā’, properly named the Sāsanajotikā, as a commentary on B1 by the major 19th century Burmese scholar Jāgara. The present article will give details of this analysis. Full article

This paper re-examines the Inner Alchemy methods found in The Secret of Golden Flower, or Taiyi Jinhua Zongzhi (太乙金華宗旨, abbreviated as JZ), a text created through fuji (spirit-writing) attributed to Lüzu (呂祖) in Changzhou 常州 during the late 17th century. Recent research has shown that Pan Yi’an (潘易庵), one of the primary editors of JZ, was, in fact, the same person as Pan Jingguan (潘靜觀), who assisted in the editing of Illuminating the Mystery of Concordance of the Three According to the Book of Changes (Cangtongqi chanyou, 参同契闡幽) and Illuminating the Mystery of Awakening the Perfection (Wuzhen pian chanyou, 悟真篇闡幽) as a disciple of Zhu Yuanyu (朱元育), the editor of these works. Meanwhile, in my recent research, I have reconstructed the Inner Alchemy methods described in these two works. (For the sake of convenience, in this discussion, I will refer to this system as the “Chanyou neidan method”, as both works include the term “Chanyou” in their titles.) Upon re-examining JZ with this framework in mind, I began to suspect that its content might be based on the Chanyou neidan method. This hypothesis is rendered highly plausible by the fact that Pan Yi’an, a key editor of JZ, was the same individual as Pan Jingguan, who assisted in the editing of the two Chanyou works. The aim of this paper is to analyze the similarities and differences between the content of JZ and the Chanyou neidan method, demonstrating that the former is indeed based on the latter. Furthermore, I intend to show that while JZ incorporates the Chanyou neidan method, it also simplifies its content significantly, making it a practical manual designed for literati (士大夫 shidafu) of the Qing dynasty to integrate Inner Alchemy into their daily lives. Additionally, although JZ was created through fuji (spirit-writing), I propose that fuji also functioned as a means for Qing-era literati to adapt Daoist cultivation practices to their own lifestyles. Full article

This paper examines the practice of ‘Bible Noise’, a group which I led at a Church of England evangelical church that explored creative ways of reading aloud the Bible through sound art practice. Biblical engagement is central to evangelicals and I wanted to expand biblical engagement by using sonic performances through the use of our voices, thereby facilitating a more bodily encounter with scripture. ‘Noise’ in the group name alludes to the disruption that sound can generate and also alludes to the ‘noise’ of multivocality, since the Bible has many voices in it from authors, narrative characters, editors, compilers, translators, interpreters and so on. The ‘noise’ is also a disruption of the visual primacy of our current culture. Bible Noise explores ways in which different voices can be brought in to enrich our aural engagement with scripture by exploring five different ‘pieces’ or readings of scripture. In doing so it establishes a communal idea of scripture where the different voices within scripture can be heard, paying attention to their particularities. Listening to these voices and our own embodied enactment of them can enrich and deepen our perception and engagement of scripture by appreciating the chorus of voices that is the Bible, the collection of texts that forms a core of British evangelical practice and belief. Full article

This article examines the complex linguistic phenomenon of Hebrew–Yiddish diglossia within Hasidic homiletic literature, particularly focussing on sermons from the nineteenth and twentieth centuries. While previous scholarship has emphasised Hebrew’s dominance in Hasidic written works, this study demonstrates how Yiddish has played a crucial role in preserving and transmitting Hasidic teachings. Through analysis of primary sources, three distinct models of Hebrew–Yiddish integration are identified: parallel texts in both languages within the same volume, limited Yiddish passages integrated within predominantly Hebrew texts, and a complete amalgamation where the languages become nearly inseparable. Analysis indicates that Hasidic authors and editors deliberately preserved Yiddish elements to maintain the authenticity of the tzaddik’s original oral teachings while adhering to Hebrew’s traditional status in religious literature. This linguistic practice elevated Eastern Yiddish’s cultural position concurrent with similar (but different) developments in Haskalah literature. Furthermore, the study demonstrates how Hasidic literature’s incorporation of spoken Yiddish into sacred texts contributed to the language’s legitimisation as a medium for religious discourse. This examination offers new perspectives on linguistic hierarchies in religious Jewish texts and illuminates how Hasidic literature developed innovative solutions to balance authenticity and tradition in religious writing. Full article

Research expands the boundaries of a subject, economy, and civilization. Peer review is at the heart of research and is understandably an expensive process. This work, with human-in-the-loop, aims to support the research community in multiple ways. It predicts quality, and acceptance, and recommends reviewers. It helps the authors and editors to evaluate research work using machine learning models developed based on a dataset comprising 18,000+ research papers, some of which are from highly acclaimed, top conferences in Artificial Intelligence such as NeurIPS and ICLR, their reviews, aspect scores, and accept/reject decisions. Using machine learning algorithms such as Support Vector Machines, Deep Learning Recurrent Neural Network architectures such as LSTM, a wide variety of pre-trained word vectors using Word2Vec, GloVe, FastText, transformer architecture-based BERT, DistilBERT, Google’s Large Language Model (LLM), PaLM 2, and TF-IDF vectorizer, a comprehensive system is built. For the system to be readily usable and to facilitate future enhancements, a frontend, a Flask server in the cloud, and a NOSQL database at the backend are implemented, making it a complete system. The work is novel in using a unique blend of tools and techniques to address most aspects of building a system to support the peer review process. The experiments result in a 86% test accuracy on acceptance prediction using DistilBERT. Results from other models are comparable, with PaLM-based LLM embeddings achieving 84% accuracy. Full article