Hasil untuk "French literature - Italian literature - Spanish literature - Portuguese literature"

A. Lebano, Sarah Hamed, H. Bradby et al.

Background There is increasing attention paid to the arrival of migrants from outwith the EU region to the European countries. Healthcare that is universally and equably accessible needs to be provided for these migrants throughout the range of national contexts and in response to complex and evolving individual needs. It is important to look at the evidence available on provision and access to healthcare for migrants to identify barriers to accessing healthcare and better plan necessary changes. Methods This review scoped 77 papers from nine European countries (Austria, Cyprus, France, Germany, Greece, Italy, Malta, Spain, and Sweden) in English and in country-specific languages in order to provide an overview of migrants’ access to healthcare. The review aims at identifying what is known about access to healthcare as well as healthcare use of migrants and refugees in the EU member states. The evidence included documents from 2011 onwards. Results The literature reviewed confirms that despite the aspiration to ensure equality of access to healthcare, there is evidence of persistent inequalities between migrants and non-migrants in access to healthcare services. The evidence shows unmet healthcare needs, especially when it comes to mental and dental health as well as the existence of legal barriers in accessing healthcare. Language and communication barriers, overuse of emergency services and underuse of primary healthcare services as well as discrimination are described. Conclusions The European situation concerning migrants’ and refugees’ health status and access to healthcare is heterogeneous and it is difficult to compare and draw any firm conclusions due to the scant evidence. Different diseases are prioritised by different countries, although these priorities do not always correspond to the expressed needs or priorities of the migrants. Mental healthcare, preventive care (immunization) and long-term care in the presence of a growing migrant older population are identified as priorities that deserve greater attention. There is a need to improve the existing data on migrants’ health status, needs and access to healthcare to be able to tailor care to the needs of migrants. To conduct research that highlights migrants’ own views on their health and barriers to access to healthcare is key.

N. Bragazzi, J. Kong, Naim Mahroum et al.

An emerging outbreak of monkeypox infection is quickly spreading worldwide, being currently reported in more than 30 countries, with slightly less than 1000 cases. In the present preliminary report, we collected and synthesized early data concerning epidemiological trends and clinical features of the ongoing outbreak and we compared them with those of previous outbreaks. Data were pooled from six clusters in Italy, Australia, the Czech Republic, Portugal, and the United Kingdom, totaling 124 cases (for 35 of which it was possible to retrieve detailed information). The ongoing epidemic differs from previous outbreaks in terms of age (54.29% of individuals in their thirties), sex/gender (most cases being males), risk factors, and transmission route, with sexual transmission being highly likely. Also, the clinical presentation is atypical and unusual, being characterized by anogenital lesions and rashes that relatively spare the face and extremities. The most prevalent sign/symptom reported was fever (in 54.29% of cases) followed by inguinal lymphadenopathy (45.71%) and exanthema (40.00%). Asthenia, fatigue, and headache were described in 22.86% and 25.71% of the subjects, respectively. Myalgia was present in 17.14% of the cases. Both genital and anal lesions (ulcers and vesicles) were reported in 31.43% of the cases. Finally, cervical lymphadenopathy was described in 11.43% of the sample, while the least commonly reported symptoms were diarrhea and axillary lymphadenopathy (5.71% of the case series for both symptoms). Some preliminary risk factors can be identified (being a young male, having sex with other men, engaging in risky behaviors and activities, including condomless sex, human immunodeficiency virus positivity (54.29% of the sample analyzed), and a story of previous sexually transmitted infections, including syphilis). On the other hand, being fully virally suppressed and undetectable may protect against a more severe infectious course. However, further research in the field is urgently needed.

Zefei Xie, Yuhan Guo, Kai Xu

There are different goals for literature research, from understanding an unfamiliar topic to generate hypothesis for the next research project. The nature of literature research also varies according to user's familiarity level of the topic. For inexperienced researchers, identifying gaps in the existing literature and generating feasible hypothesis are crucial but challenging. While general ``deep research'' tools can be used, they are not designed for such use case, thus often not effective. In addition, the ``black box" nature and hallucination of Large Language Models (LLMs) often lead to distrust. In this paper, we introduce a human-agent collaborative visualization system AwesomeLit to address this need. It has several novel features: a transparent user-steerable agentic workflow; a dynamically generated query exploring tree, visualizing the exploration path and provenance; and a semantic similarity view, depicting the relationships between papers. It enables users to transition from general intentions to detailed research topics. Finally, a qualitative study involving several early researchers showed that AwesomeLit is effective in helping users explore unfamiliar topics, identify promising research directions, and improve confidence in research results.

Barbara Eigenschenk, A. Thomann, Mike McClure et al.

The combination of physical activity and being in nature is recognized as providing a range of significant benefits. The objective of this literature review was to compile an overview of the social benefits and costs associated with outdoor sports within the academic literature and to reflect on the quality of underlying evidence that supports the relationship. A systematic review was carried out with seven partners from different European countries, including Bulgaria, France, Germany, United Kingdom, Italy, Portugal, and Spain. From a total of 17,560 studies identified, 133 studies were selected with relevant data extracted to standardized forms. The selected studies have been analyzed with qualitative research methods. A meta-analysis could not be conducted due to the heterogeneity of the study designs and outcome measures. As a result, the review gives an overview of the social impacts associated with outdoor sports which have been clustered to six broad categories: physical health, mental health and wellbeing, education and lifelong learning, active citizenship, crime reduction, and anti-social behavior, as well as additional benefits. The review furthermore revealed gaps in the evidence base which are especially notable in the long-term effects that outdoor sports can have on personal and social development.

Ryusuké Ebiné

In his art criticism of the 1840s, Baudelaire sought, by emphasising the importance of colour over drawing, a parallel between the artistic unity created by a superior artist and the collective unity of artists who gather around a master. However, from the 1850s onwards, he was not always seeking unity in art as a symbol of collective order among men, because, in his view, there were no longer any artists capable of leading mediocre individuals. Nevertheless, Baudelaire also understood that freedom and equality lead to universal violence. This explains, on the one hand, his pessimistic view of the world, based on the idea of original sin, and, on the other hand, the dynamic nature of his poetic works, in which a stable ideal state is never established.

Gianni Iotti

Anita Staroń

Simra Shahid, Marissa Radensky, Raymond Fok et al.

Automated scientific idea generation systems have made remarkable progress, yet the automatic evaluation of idea novelty remains a critical and underexplored challenge. Manual evaluation of novelty through literature review is labor-intensive, prone to error due to subjectivity, and impractical at scale. To address these issues, we propose the Idea Novelty Checker, an LLM-based retrieval-augmented generation (RAG) framework that leverages a two-stage retrieve-then-rerank approach. The Idea Novelty Checker first collects a broad set of relevant papers using keyword and snippet-based retrieval, then refines this collection through embedding-based filtering followed by facet-based LLM re-ranking. It incorporates expert-labeled examples to guide the system in comparing papers for novelty evaluation and in generating literature-grounded reasoning. Our extensive experiments demonstrate that our novelty checker achieves approximately 13% higher agreement than existing approaches. Ablation studies further showcases the importance of the facet-based re-ranker in identifying the most relevant literature for novelty evaluation.

Aminul Islam, Mukta Bansal, Lena Felix Stephanie et al.

Writing literature reviews is a common component of university curricula, yet it often poses challenges for students. Since generative artificial intelligence (GenAI) tools have been made publicly accessible, students have been employing them for their academic writing tasks. However, there is limited evidence of structured training on how to effectively use these GenAI tools to support students in writing literature reviews. In this study, we explore how university students use one of the most popular GenAI tools, ChatGPT, to write literature reviews and how prompting frameworks can enhance their output. To this aim, prompts and literature reviews written by a group of university students were collected before and after they had been introduced to three prompting frameworks, namely CO-STAR, POSE, and Sandwich. The results indicate that after being exposed to these prompting frameworks, the students demonstrated improved prompting behaviour, resulting in more effective prompts and higher quality literature reviews. However, it was also found that the students did not fully utilise all the elements in the prompting frameworks, and aspects such as originality, critical analysis, and depth in their reviews remain areas for improvement. The study, therefore, raises important questions about the significance of utilising prompting frameworks in their entirety to maximise the quality of outcomes, as well as the extent of prior writing experience students should have before leveraging GenAI in the process of writing literature reviews. These findings are of interest for educators considering the integration of GenAI into academic writing tasks such as literature reviews or evaluating whether to permit students to use these tools.

Zhi Zhang, Yan Liu, Zhejing Hu et al.

Compounding errors pose a significant challenge in automatic literature review generation, as inaccuracies can cascade across multi-stage retrieval and generation workflows. Existing self-correction strategies often lack mechanisms to effectively track and consolidate verified information throughout the process, making it difficult to prevent error accumulation and propagation. In this paper, we propose Structure-Guided Memory Consolidation (SGMC), a novel framework that incrementally consolidates and verifies information using structured representations at each stage of the literature review pipeline. SGMC consists of three key modules: Tree-Guided Memory for hierarchical literature retrieval and outline generation, Hub-Guided Memory for evidence extraction and iterative content refinement, and Self-Loop Memory for proactive error correction via historical feedback. Extensive experiments on public benchmarks and a newly constructed large-scale dataset demonstrate that SGMC achieves state-of-the-art performance in citation accuracy and content quality, significantly mitigating compounding errors in long-form literature review generation.

Xiao Hu, Yuansheng Lian, Ke Zhang et al.

This study proposes an interpretable prediction framework with literature-informed fine-tuned (LIFT) LLMs for truck driving risk prediction. The framework integrates an LLM-driven Inference Core that predicts and explains truck driving risk, a Literature Processing Pipeline that filters and summarizes domain-specific literature into a literature knowledge base, and a Result Evaluator that evaluates the prediction performance as well as the interpretability of the LIFT LLM. After fine-tuning on a real-world truck driving risk dataset, the LIFT LLM achieved accurate risk prediction, outperforming benchmark models by 26.7% in recall and 10.1% in F1-score. Furthermore, guided by the literature knowledge base automatically constructed from 299 domain papers, the LIFT LLM produced variable importance ranking consistent with that derived from the benchmark model, while demonstrating robustness in interpretation results to various data sampling conditions. The LIFT LLM also identified potential risky scenarios by detecting key combination of variables in truck driving risk, which were verified by PERMANOVA tests. Finally, we demonstrated the contribution of the literature knowledge base and the fine-tuning process in the interpretability of the LIFT LLM, and discussed the potential of the LIFT LLM in data-driven knowledge discovery.

D. Koriak

The article focuses on the category of artistic means of quotation in the novel “Cousin Bazilio” by J.M. Eça de Queirós, the most influential representative of Portuguese realism of the XIX century. The purpose of the study is to identify the specificity of the novel in terms of its connections with works of European literature. The objectives of the study consist in identifying the artistic means of quotation in the novel, analyzing these artistic means and determining their functions in the text, as well as building the typology, based on the characteristics of the considered artistic means and the tasks they perform in the text. The presence of numerous interliterary and intercultural connections in “Cousin Bazilio” distinguishes it both from Queirós’s first novel “The Crime of Father Amaro”, his subsequent novels, and from the works of the author’s main Portuguese predecessors: Camilo Castelo Branco and Júlio Dinis. From the analysis carried out in the article, it follows that the literary and cultural connections of “Cousin Bazilio” are introduced into the text through allusions, reminiscences and quotations. They can be divided into three categories depending on the artistic task performed: 1) narrative (“Madame Bovary” by G. Flaubert, “Eugénie Grandet” by H. Balzac); 2) thematic (“Faust” by J.W. Goethe, “The Divine Comedy” by Dante); 3) literaryanthropological (“Mademoiselle Giraud: my wife” by A. Belot, “The Maiden of Mabille” by H. Escoffier, etc.). The use of allusions, reminiscences and quotations in the novel aims to highlight the influence of French literature on shaping the aesthetic tastes of the Portuguese society and of the author himself, to fulfill plot-forming tasks in the novel and to place “Cousin Basilio” in the European cultural context, to reveal the inner world of the characters more completely and also to give them deeper features.

Joselyn González Pasten, J. Aguayo, J. Aburto et al.

Background: Chronic obstructive pulmonary disease (COPD) is characterized by important extrapulmonary alterations that could affect the performance in dual task (DT) (motor and cognitive tasks executed simultaneously), which is defined as DT interference (DTI). Objective: To compare the performance of DT between individuals with COPD and healthy control subjects (HCSs). Methods: The literature search was conducted in seven databases (Medline, Scopus, Web of Science, PEDro, SciELO, LILACS, and Google Scholar) up to December 2023, including studies published in English, Spanish, or Portuguese. Studies with individuals diagnosed with COPD older than 60 years, who were evaluated with any DT assessment, and compared with HCS were included. The quality of the studies was evaluated using the risk of bias in nonrandomized studies of interventions (ROBINS-I). The meta-analysis was performed with JAMOVI software 5.4. The study protocol was registered on PROSPERO (CRD42023435212). Results: From a total of 128 articles, 5 observational studies were selected in this review, involving 252 individuals aged between 60 and 80 years, from France, Italy, Canada, Turkey, and Belgium. Notable DTI was observed in individuals with COPD compared to HCS (standard mean difference [SMD] = 0.91; 95% confidence interval (CI) 0.06–1.75, p = 0.04). Individuals with COPD had impaired gait speed, balance control, muscle strength, and cognitive interference during DT compared to HCS. DT assessment protocols included different combination of motor and cognitive tasks, using functional test, gait analysis, and muscle strength paired with countdown and verbal fluency tasks. Studies presented low (n = 2), moderate (n = 1), and serious (n = 2) overall risk of bias. Conclusion: Older adults diagnosed with COPD exhibited a significant DTI compared to HCSs, which is characterized by poorer physical and cognitive performance during DT execution. These findings highlight the importance of incorporating DT assessments into clinical practice for individuals with COPD.

Rita Lopes da Silva, Ana Rita Jesus Maria, David Rodrigues et al.

Abstract Background: The number of informal caregivers continues to rise worldwide. In Portugal, 10% of the population are informal caregivers and recent studies suggest that current government policies may not adequately support this population. This review aimed to find and synthesize relevant research on perceptions of unmet needs of informal caregivers of older people in Portugal. Methods/Design: A qualitative synthesis approach will be used. Electronic searches will be conducted on PubMed, EMBASE, PsycINFO, Web of Science, Academic Search Complete, and CINAHL. Gray literature will be searched through Portuguese databases and contact with researchers and patient organizations. Qualitative studies that evaluated Portuguese caregivers’ perceptions of unmet needs will be eligible. We will restrict to papers written in Spanish, English, or Portuguese and no date limitations will be applied. Data will be synthesized, and quality assessment will be done using CASP tool for qualitative research. PROSPERO registration number ID: CRD42022334859. Discussion: Findings from this future systematic review may lead to a better understanding of informal caregiving of older people in Portugal and may lead to the development of new policies and recommendations.

Tom Lorenz Klein, Clemens Thielen

Most activities in hospitals require the presence of the patient. Delays in patient transport can disrupt operations, potentially resulting in idle staff, underutilized equipment, and postponed procedures, which in turn lead to lost revenue, unnecessary costs across many different areas and departments, and lower patient satisfaction. Consequently, patient transport planning is a central operational task in hospitals. This paper provides the first literature review of Operations Research and Management Science approaches for non-emergency, intra-hospital patient transport. We structure the different patient transport problems considered in the literature according to several main characteristics and introduce a five-field notation that allows for a concise representation of different problem variants. We then analyze the relevant literature with respect to different aspects related to the considered problem variant, the employed modeling and solution techniques, as well as the data used and the level of practical implementation achieved. Based on our literature analysis and semi-structured interviews with hospital practitioners, we compare current hospital practices and the existing literature, identify research gaps, and formulate an agenda for relevant future research.

Kexin Chen, Yuyang Du, Junyou Li et al.

The development of AI-assisted chemical synthesis tools requires comprehensive datasets covering diverse reaction types, yet current high-throughput experimental (HTE) approaches are expensive and limited in scope. Chemical literature represents a vast, underexplored data source containing thousands of reactions published annually. However, extracting reaction information from literature faces significant challenges including varied writing styles, complex coreference relationships, and multimodal information presentation. This paper proposes ChemMiner, a novel end-to-end framework leveraging multiple agents powered by large language models (LLMs) to extract high-fidelity chemical data from literature. ChemMiner incorporates three specialized agents: a text analysis agent for coreference mapping, a multimodal agent for non-textual information extraction, and a synthesis analysis agent for data generation. Furthermore, we developed a comprehensive benchmark with expert-annotated chemical literature to evaluate both extraction efficiency and precision. Experimental results demonstrate reaction identification rates comparable to human chemists while significantly reducing processing time, with high accuracy, recall, and F1 scores. Our open-sourced benchmark facilitates future research in chemical literature data mining.

Christoforus Yoga Haryanto

This paper introduces LLAssist, an open-source tool designed to streamline literature reviews in academic research. In an era of exponential growth in scientific publications, researchers face mounting challenges in efficiently processing vast volumes of literature. LLAssist addresses this issue by leveraging Large Language Models (LLMs) and Natural Language Processing (NLP) techniques to automate key aspects of the review process. Specifically, it extracts important information from research articles and evaluates their relevance to user-defined research questions. The goal of LLAssist is to significantly reduce the time and effort required for comprehensive literature reviews, allowing researchers to focus more on analyzing and synthesizing information rather than on initial screening tasks. By automating parts of the literature review workflow, LLAssist aims to help researchers manage the growing volume of academic publications more efficiently.

Huawei Ji, Cheng Deng, Bo Xue et al.

With the development of data-centric AI, the focus has shifted from model-driven approaches to improving data quality. Academic literature, as one of the crucial types, is predominantly stored in PDF formats and needs to be parsed into texts before further processing. However, parsing diverse structured texts in academic literature remains challenging due to the lack of datasets that cover various text structures. In this paper, we introduce AceParse, the first comprehensive dataset designed to support the parsing of a wide range of structured texts, including formulas, tables, lists, algorithms, and sentences with embedded mathematical expressions. Based on AceParse, we fine-tuned a multimodal model, named AceParser, which accurately parses various structured texts within academic literature. This model outperforms the previous state-of-the-art by 4.1% in terms of F1 score and by 5% in Jaccard Similarity, demonstrating the potential of multimodal models in academic literature parsing. Our dataset is available at https://github.com/JHW5981/AceParse.

Harleen Kaur Bagga, Jasmine Bernard, Sahil Shaheen et al.

Sarcasm is hard to interpret as human beings. Being able to interpret sarcasm is often termed as a sign of intelligence, given the complex nature of sarcasm. Hence, this is a field of Natural Language Processing which is still complex for computers to decipher. This Literature Survey delves into different aspects of sarcasm detection, to create an understanding of the underlying problems faced during detection, approaches used to solve this problem, and different forms of available datasets for sarcasm detection.

Hengxing Cai, Xiaochen Cai, Junhan Chang et al.

Recent breakthroughs in Large Language Models (LLMs) have revolutionized scientific literature analysis. However, existing benchmarks fail to adequately evaluate the proficiency of LLMs in this domain, particularly in scenarios requiring higher-level abilities beyond mere memorization and the handling of multimodal data. In response to this gap, we introduce SciAssess, a benchmark specifically designed for the comprehensive evaluation of LLMs in scientific literature analysis. It aims to thoroughly assess the efficacy of LLMs by evaluating their capabilities in Memorization (L1), Comprehension (L2), and Analysis \& Reasoning (L3). It encompasses a variety of tasks drawn from diverse scientific fields, including biology, chemistry, material, and medicine. To ensure the reliability of SciAssess, rigorous quality control measures have been implemented, ensuring accuracy, anonymization, and compliance with copyright standards. SciAssess evaluates 11 LLMs, highlighting their strengths and areas for improvement. We hope this evaluation supports the ongoing development of LLM applications in scientific literature analysis. SciAssess and its resources are available at \url{https://github.com/sci-assess/SciAssess}.