Search Results (619)

Large language models (LLMs) show limited capability in processing low-resource historical languages due to insufficient training data and domain-specific linguistic structures. Korean Literary Sinitic (KLS), the principal written medium of the Joseon dynasty, remains particularly under-resourced despite its lexical overlap with modern Korean and shared script with classical Chinese. To enable systematic evaluation in this domain, we introduce KLSBench, a comprehensive benchmark for assessing LLM performance on KLS. KLSBench contains 7871 instances sourced from Joseon dynasty civil service examination archives and parallel corpora of the Four Books, and encompasses five task categories: classification, retrieval, punctuation restoration, natural language inference, and translation. Our evaluation suggests KLSBench could work as an effective diagnostic tool that distinguishes lexical recall from deeper linguistic comprehension in low-resource historical languages. Beyond establishing evaluation baselines, KLSBench provides practical frameworks for deploying LLM-based tools in digital humanities contexts, including automated annotation systems and intelligent search interfaces for classical text repositories. Full article

Since the 19th century, Protestant missionaries in Guangdong have extensively engaged in the translation and publication of religious texts, employing localized strategies in the illustration of Christian novels. Within the local cultural context of late Qing Guangdong, missionaries collaborated with local scholars, used Cantonese for writing, and designed novel illustrations to overcome barriers in doctrinal dissemination, thereby facilitating the spread of Christianity. The illustrations in missionary-published novels, such as The Pilgrim’s Progress in Vernacular and The Spiritual Warfare in Vernacular, adopted the stylistic features of Ming and Qing novel woodcuts in terms of lines, composition, character attire, and settings. Furthermore, they skillfully incorporated the Confucian moral framework of loyalty, filial piety, chastity, and righteousness, as represented in the Sacred Edict, into their narrative ethics, while integrating elements such as Buddhist causality and Daoist imagery into a “didactic” system. This localization strategy, combined with a “trinity” reading guidance model comprising images, text, and biblical annotations, visually elucidated the tenets of the Bible and encouraged the public to embrace Christianity. The localized practice of missionary novel illustrations served as a conscious and effective visual strategy aimed at bridging cultural divides and promoting the dissemination of the Gospel. It profoundly reflects the visual agency in modern Sino–Western cultural exchanges and significantly advanced the propagation of Christianity. Full article

Background: Vitamin E has been studied for its role in reducing the growth of colorectal cancer (CRC). CRC is a worldwide health concern. A meta-analysis reported that CRC patients have a lower concentration of serum vitamin E, suggesting it to be a risk factor. Although rodent models are widely used in disease research, their application in studying vitamin E as a preventive or therapeutic agent in CRC is not well characterized. To address this gap, we conducted a scoping review to examine the available evidence, adhering to the PRISMA-ScR checklist. Methods: We searched PubMed, Google Scholar, Scopus, and Web of Science (WoS) for full-text English original articles published before May 2024, using Medical Subject Headings (MeSH) terms and free text. The following search string strategy was applied: (Vitamin E OR tocopherol$ OR tocotrienol$) AND (Colo$ cancer OR colo$ carcinoma) AND (Rodentia OR mouse OR Rodent$ OR mice OR murine OR rats OR guinea OR rabbit OR hamsters OR Animal model OR Animal testing OR animals) AND (neoplasm$ OR “tumor mass” OR tumor volume OR tumor weight OR tumor burden). Data were charted into five categories using a standardized, pretested form. The charted data were synthesized using descriptive and narrative methods. Conclusions: This study highlights that γ- and δ-tocopherols, as well as δ-tocotrienol and its metabolites, were reported to reduce tumor volume and formation in various rodent models. While these results are promising, this scoping review identifies a need for further research to address translational barriers such as dosing, bioavailability, and long-term safety before clinical application. Full article

Unstructured POI name texts are widely used in fine-grained urban analysis, yet missing labels and semantic ambiguity often limit their value for spatial inference. This study proposes a large language model-based semantic–spatial inference framework (LLM-SSIF), a lightweight semantic–spatial pipeline that translates POI texts into interpretable, fine-grained spatial evidence through an end-to-end workflow that couples scalable label expansion with scale-controlled spatial diagnostics at a 500 m resolution. A key advantage of LLM-SSIF is its deployability: LoRA-based parameter-efficient fine-tuning of an open LLM enables lightweight adaptation under limited compute while scaling fine-label coverage. Trained on a nationwide cuisine-labeled dataset (~220,000 records), the model achieves strong multi-class short-text recognition (macro-F1 = 0.843) and, in the Guangzhou–Shenzhen demonstration, expands usable fine-category labels by ~14–15× to support grid-level inference under long-tail sparsity. The spatial module then isolates cuisine-specific over/under-representation beyond overall restaurant intensity, revealing contrasting cultural configurations between Guangzhou and Shenzhen. Overall, LLM-SSIF provides a reproducible and transferable way to translate unstructured POI texts into spatial–statistical evidence for comparative urban analysis. Full article

Acute lung injury (ALI) is in part precipitated by hyperbaric oxygen or other mechanical insults. It constitutes the fundamental pathological process underlying acute respiratory distress syndrome (ARDS). The manifestation of the condition is characterized by an uncontrolled inflammatory response and alveolar edema, consequent to the disruption of the alveolar–capillary barrier. This phenomenon is associated with elevated morbidity and mortality rates. The current therapeutic interventions for ALI are not well researched or articulated. However, recent studies have indicated that stem cells may possess therapeutic potential in the context of ALI. The present study demonstrates that these exosome preparations have the capacity to significantly ameliorate radiographic findings, histological parameters, and vascular permeability in murine models of ALI. Concurrently, they attenuate the inflammatory response to a certain extent. The present review commences with an examination of the pathogenic mechanisms and manifestations of pulmonary injury induced by hyperbaric oxygen or other external factors. The subsequent sections of the text provide detailed accounts of the latest advances in exosome-based therapies for mitigating such injury, including their mechanisms of action and future translational prospects. While exosome-based treatments have demonstrated considerable advancement in preclinical research, numerous challenges must be surmounted before their widespread implementation in clinical settings can be realized, underscoring the necessity for sustained research in this domain. Full article

Low back pain (LBP) represents a major societal and economic burden, with annual costs in the United States estimated at $90–134.5 billion. LBP disproportionately impacts postmenopausal women relative to age-matched men, suggesting a role for sex-specific biological factors. Although the mechanisms underlying this disparity are not fully understood, hormonal imbalance during menopause may contribute to LBP pathophysiology. This narrative review aimed to elucidate the impact of menopause on LBP, with emphasis on hormonal effects on spinal tissues and systemic processes. A literature search was conducted, followed by screening of titles, abstracts, and full texts of original clinical studies, preclinical research using human or animal samples, and relevant reviews. Rigour and reproducibility were evaluated using the ARRIVE Guidelines and the Modified Downs & Black Checklist. Evidence indicates that menopause is associated with changes in intervertebral discs, facet joint, ligamentum flavum, skeletal muscle, sympathetic innervation, and systemic systems such as the gut microbiome. However, most findings are correlational rather than causal. Evidence supporting hormone replacement therapy for LBP remains inconclusive, whereas exercise and other treatments, including parathyroid hormones, show more consistent benefits. Future studies should focus on causal mechanisms and adhere to rigour guidelines to improve translational potential. Full article

Targeted multimodal sentiment classification is frequently impeded by the semantic sparsity of social media content, where text is brief and context is implicit. Traditional methods that rely on direct concatenation of textual and visual features often fail to resolve the ambiguity of specific targets due to a lack of alignment between modalities. In this paper, we propose the Complementary Description Network (CDNet) to bridge this informational gap. CDNet incorporates automatically generated image descriptions as an additional semantic bridge, in contrast to methods that handle text and images as distinct streams. The framework enhances the input representation by directly translating visual content into text, allowing for more accurate interactions between the opinion target and the visual narrative. We further introduce a complementary reconstruction module that functions as a regularizer, forcing the model to retain deep semantic cues during fusion. Empirical results on the Twitter-2015 and Twitter-2017 benchmarks confirm that CDNet outperforms existing baselines. The findings suggest that visual-to-text augmentation is an effective strategy for compensating for the limited context inherent in short texts. Full article

The Zhenshimingjing 真實名經, a Chinese Buddhist scripture translated from the Tibetan Nāmasaṃgīti, is preserved in multiple Tripitaka editions and multilingual manuscripts. Previous studies either confined themselves to intra-Chinese collation without the Tibetan source, or to multilingual comparison based solely on the Taisho Tripitaka. This study integrates both approaches by analyzing Chinese Tripitaka editions alongside two multilingual versions of the Zhenshimingjing. It clarifies the interrelationships among the extant versions and evaluates their correspondence to the Tibetan source text, thereby determining their philological value. The results show that the earliest Tripitaka editions already contained numerous graphic and phonetic corruptions, which later recensions largely perpetuated. Although the Yonglebei Tripitaka represents the most extensively collated recension, it remained limited by the collators’ lack of Tibetan knowledge. By contrast, the multilingual manuscripts—especially the Vira edition—preserve readings closer to the Tibetan Nāmasaṃgīti and demonstrate the diachronic continuity of transmission independent of the Tripitaka. The study underscores the necessity of combining intra-Chinese collation with multilingual comparison to reconstruct a more reliable text and reassess long-standing issues in the philological study of Chinese Buddhist translations. Full article

Despite being the most popular sutra tableau in Dunhuang, the utter lack of any comprehensive, or chronological academic analysis even in Chinese calls for a thorough research on the Medicine Buddha Sutra iconography at Dunhuang. This paper will explore the Medicine Buddha both in the literary form, the sutras, and the visual form, the sutra tableaux, when they first appeared in China during the Sui Dynasty. First, the relevant sections of the four Medicine Buddha Sutra translated in Chinese will be examined in detail. Then, the earliest four pictorial representations, namely Caves 417, 433, 436, and 394 at Dunhuang, will be scrutinized to establish a firm foundation of this said sutra tableau for later periods. By comparing the deities, and other special attributes presented in these images with what were recorded in the sutras, this paper reveals how the anonymous monastics and artists “re-presented” the Medicine Buddha from literary form to pictorial form, which embodies the intermediallity during the Sui Dynasty in Dunhuang. After analyzing how the textual elements such as the Medicine Buddha, attendant Bodhisattvas, Twelve Demigods, Four Heavenly Kings, and the magical life-prolonging instruments were depicted in the paintings, intermediality between the texts and imagery is brought to light. Two most decisive details, the small sizes of the cartouches for the inscriptions of the Twelve Demigods, and the number of Medicine statues that should be present at the ritual, clearly show the Medicine Buddha Sutra imagery painted during the Sui Dynasty in Dunhuang is based on the earliest Chinese edition, Sutra on the Initiation to Remove Unwholesome Deeds and Attain Salvation from Birth and Death Taught by the Buddha, translated by Śrīmitra. Full article

Traditional settlements exhibit remarkable climatic adaptability, representing a form of “Morphological Intelligence” developed over centuries. However, this inherent, physics-based wisdom remains underutilized in contemporary urban planning and design. This systematic review aims to decode such intelligence by analyzing the relationship between the morphological characteristics of traditional settlements and their thermal performance. Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) protocol, literature retrieval and evaluation were conducted via the databases of Web of Science, Scopus, and China National Knowledge Infrastructure (CNKI) for articles published during 2004~2024. A total of 82 related articles with available full texts were selected from 1227 records for in-depth analysis, including peer-reviewed journal articles and reputable conference publications. This study first presents an overview of bibliometric and methodological landscapes, revealing that research is increasingly concentrated in Asia’s tropical and subtropical climates, predominantly employing case studies and computational simulations. Secondly, we synthesize a few key climate-adaptive morphological features across macro- (e.g., settlement layout), meso- (e.g., street canyon geometry), and microscales (e.g., courtyards). The findings illustrate a reliance on methods and metrics developed for modern urban contexts, which could not fully capture the specific morphological characteristics of traditional settlements. Most importantly, this study summarizes four core principles of “Morphological Intelligence” in traditional settlements, i.e., strategic solar control, facilitated natural ventilation, use of thermal mass, and integration of natural elements and creation of thermal buffer zones. By identifying the limitations of existing investigations, this study highlights a few directions for future studies, including conducting more systematic multi-scalar integrated analysis, focusing on the development of dedicated quantitative metrics and analytical frameworks, delving into more mechanism-oriented investigation, assessing morphological resilience under urbanization, and translating principles into contemporary design guidelines. This study provides a foundational framework for translating the “Morphological Intelligence” of traditional settlements into actionable, evidence-based strategies for resilient and energy-efficient urban planning and design amidst climate change. Full article

This paper offers a series of reflections and observations derived from my experience as a (semi-) professional literary translator and as a teacher of translation studies. I openly recognise the subjective nature of any meta-reflection on the ethical challenges faced by the translator as an intercultural mediator. After briefly examining several central theses that have been defended, illustrated, and adopted to produce a translation that is politically correct from both a professional and deontological standpoint, I then list and analyse the major obstacles to the reception of a novel featuring “Romanian subject matter” written by a French author: cultural, historical, and political allusions as well as culinary and civilizational culture-specific elements. The examples come from Lionel Duroy’s novels Eugenia (2018) and Mes pas dans leurs ombres (2023), which revisit the pogroms of Iași, Bucharest, Bessarabia, and Ukraine, leading to the extermination of the Jewish population (1940–1941)—a significant and painful chapter of Romanian history, often overlooked or silenced. These cases enable us to argue more convincingly for the strategies, techniques, and procedures that can be considered when translating a text laden with profound cultural and ideological significance, aiming to help the Romanian/French and Francophone reader to understand sensitive realia and listen to History. Full article

This study presents a real-time, bidirectional system for translating American Sign Language (ASL) to and from English using computer vision and transformer-based models to enhance accessibility for deaf and hard of hearing users. Leveraging publicly available sign language and text–to-gloss datasets, the system integrates MediaPipe-based holistic landmark extraction with CNN- and transformer-based architectures to support translation across video, text, and speech modalities within a web-based interface. In the ASL-to-English direction, the sign-to-gloss model achieves a 25.17% word error rate (WER) on the RWTH-PHOENIX-Weather 2014T benchmark, which is competitive with recent continuous sign language recognition systems, and the gloss-level translation attains a ROUGE-L score of 79.89, indicating strong preservation of sign content and ordering. In the reverse English-to-ASL direction, the English-to-Gloss transformer trained on ASLG-PC12 achieves a ROUGE-L score of 96.00, demonstrating high-fidelity gloss sequence generation suitable for landmark-based ASL animation. These results highlight a favorable accuracy-efficiency trade-off achieved through compact model architectures and low-latency decoding, supporting practical real-time deployment. Full article

Green fintech merges sustainable finance with data-intensive innovation, but national translations of EU rules can create regulatory risk. This study examines how such risk manifests in Central Europe and which policy tools mitigate it. We develop a three-dimension framework—regulatory clarity and scope, supervisory consistency, and innovation facilitation—and apply a comparative qualitative design to Hungary, Slovakia, Czechia, and Poland. Using a common EU baseline, we compile coded national snapshots from primary legal texts, supervisory documents, and recent scholarship. Results show material cross-country variation in labelling practice, soft-law use, and testing infrastructure: Hungary combines central-bank green programmes with an innovation hub/sandbox; Slovakia aligns with ESMA and runs hub/sandbox, though the green-fintech pipeline is nascent; Czechia applies a principles-based safe harbour and lacks a national sandbox; and Poland relies on a virtual sandbox and binding interpretations with limited soft law. These choices shape approval timelines, retail penetration, and cross-border portability of green-labelled products. We conclude with a policy toolkit: labelling convergence or explicit safe harbours, a cross-border sandbox federation, ESRS/ESAP-ready proportionate disclosures, consolidation of recurring interpretations into soft law, investment in suptech for green-claims analytics, and inclusion metrics in sandbox selection. Full article

Background/Objectives: Mature adipocytes were previously regarded as terminally differentiated cells that are restricted to lipid storage. Recent studies have shown that they can dedifferentiate into fibroblast-like progenitor cells, termed dedifferentiated fat (DFAT) cells. These cells exhibit stem cell-like properties and multilineage potential, highlighting their promising role in regenerative medicine and disease pathology. This systematic review aims to explore and consolidate the evidence regarding mechanisms, culture methods, pathophysiological roles, and therapeutic potential of adipocyte dedifferentiation. Methods: A systematic review was conducted in PubMed using the terms “dedifferentiation”, “de-differentiation”, “transdifferentiation”, and related variants in combination with “adipocyte”. Studies were screened and selected according to the PRISMA 2020 guidelines. Non-English articles, non-full texts, and non-review papers were excluded. After duplicate removal and eligibility assessment, 53 studies were included. Further, these were classified into categories according to their abstracts. Results: The evidence from the included articles indicates that mature adipocytes can dedifferentiate both in vitro, via ceiling culture, and in vivo, yielding DFAT cells with proliferative and multilineage differentiation capacity. Dedifferentiation involves lipid droplet secretion (liposecretion) and is characterized by downregulation of adipogenic genes such as PPARG and C/EBPα, alongside upregulation of proliferation, stemness, and lineage-associated markers. Functionally, DFAT cells contribute positively to tissue regeneration and wound repair, but they can drive adverse outcomes such as fibrosis, insulin resistance, and tumor progression through signaling pathways, including Wnt/β-catenin and TGF-β. Conclusions: Mature adipocyte dedifferentiation marks a dynamic reprogramming mechanism with dual roles—beneficial in regenerative medicine and wound healing, yet detrimental in cancer and metabolic disease. Further research is required to identify in vivo regulators, establish definitive markers, and translate adipocyte plasticity into regenerative medicine applications. Full article

Deep anomaly detection in multilingual environments remains challenging due to limited labeled data, semantic inconsistency across languages, and the unstable distribution of rare abnormal patterns. These challenges are particularly severe in low-resource scenarios—characterized by scarce labeled anomaly data and non-standardized terminology—where conventional supervised or transfer-based models suffer from semantic drift and feature mismatch. To address these limitations, a data-driven cross-lingual anomaly detection framework, LR-SSAD, is proposed. Targeting paired text and behavioral data without requiring parallel translation corpora, the framework is built upon the joint optimization of complementary self-supervised objectives. A cross-lingual masked prediction module is designed to capture language-invariant semantic structures to align semantic spaces, while a Mamba-based sequence reconstruction module leverages its linear computational complexity ($\mathcal{O}\left(N\right)$) to efficiently model long-range dependencies in transaction histories, overcoming the computational bottlenecks of quadratic attention mechanisms. To further enhance robustness under noisy supervision, a noise-aware pseudo-label refinement mechanism is introduced. Evaluated on a newly constructed real-world financial dataset (spanning January–June 2023) comprising 1.2 million multilingual texts and 420,000 transaction sequences, experimental results demonstrate that LR-SSAD achieves substantial improvements over state-of-the-art baselines. The model achieves an accuracy of 0.932, a precision of 0.914, a recall of 0.891, and an F1-score of 0.902, with the Area Under the Curve (AUC) reaching 0.948. The proposed framework provides a scalable and data-efficient solution for anomaly detection in real-world multilingual environments. Full article