Hasil untuk "American literature"

Cameron Mccarthy, Warren E. Crichlow

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.

Jessica Elliott, Liz Ryan, Leah East et al.

Introduction: A sustainable rural and remote healthcare workforce is critical for addressing healthcare access disparities globally. Attracting recent healthcare graduates to rural and remote areas is one proposed solution. The objective of rural placements is to expose healthcare students to the unique challenges and rewards of working in these areas, thereby encouraging them to consider long-term employment in such settings. It is essential to understand the events and experiences that significantly influence healthcare students' sense of belonging to these communities, as this sense of belonging is crucial for their commitment to future employment in rural areas. This scoping review aimed to investigate the events and experiences that influence medical, nursing and allied health students' sense of belonging to a rural and remote community when on clinical placement. Understanding these outcomes helps in designing placements that effectively foster a sense of community and commitment among students, ultimately contributing to a more suitable rural healthcare workforce. Methods: The scoping review followed the Joanna Briggs Institute methodology. Literature from 1995 to 2024 was systemically identified and mapped using five databases: CINAHL (via EBSCOhost), APA (American Psychological Association) PsycInfo, PubMed (via Ovid), ProQuest and Informit Health Collection. Peer-reviewed primary research with quantitative, qualitative or mixed-methods designs were included. A narrative analysis approach was adopted to identify and synthesise themes. Results: From the 3316 reports found, 13 were analysed. Three themes were generated encompassing rural environment and rural identity formation, social isolation and community activity engagement. Key findings highlight the positive impact of welcoming community environments in fostering belonging and mitigating social isolation among students. Conclusion: While clinical training among healthcare students remains pivotal, social integration for enhancing students' experiences and potentially bolstering future rural healthcare workforce retention is underscored. Gaps in the literature remain, particularly in understanding the intricate relationships between community involvement, social activities and student retention. Future research should explore student belonging to inform placement programs that address clinical and social integration.

Elizaveta A. Orlova

The Russian edition of Film Art: An Introduction by David Bordwell, Kristin Thompson and Jeff Smith (film and narratology scholars) has attracted interest of a wide range of readers, from film enthusiasts to high school teachers. At the same time, the new edition of the classical text inevitably posed a variety of prob­lems in translation. The article provides a concise overview of the production specifics that accompanied the release of Film Art. One of the main difficulties was the variety of alternatives available in the Russian language for translating terminology from the field of film production and film analysis. In addition, there was a discrepancy in the representation of precedent film texts by Russian and English-speaking cultures, which made it difficult to work with examples. In addition to factual translation problems, stylistic problems also arose. The trans­lator and editors faced the task of preserving both the academic orientation of the book (Film Art is widely used as a textbook in academic film studies) and the live­liness of the author’s narrative. Finally, the translator would note the difficulty of conveying the book’s intonational features, which make this university textbook fascinating for readers of any level of education, as well as a hallmark of Film Art. The range of translation problems raises the question of the relationship between academicism and creativity in the texts of Bordwell, Thompson and Smith, as well as the specifics of transposing film texts from one culture to another were discussed in the interview (published herewith) with co-authors of Film Art con­ducted by Diane Nemec Ignashev (film and Russian literature scholar). The range of problems faced by the book translator was also relevant for the translation of the interview.

Amélie MOISY

Adam Johnson’s “Interesting Facts,” collected in Fortune Smiles (2015) and featured in The Best American Science Fiction and Fantasy 2016, is a powerful novella. This essay considers that the double impulse of fantasy and mimesis there results in what Clayton Koelb calls a “truthful though incredible” fiction (33), which questions power and reflects the potential of our world.The story seems to be that of the narrator’s loss of power as she is treated for breast cancer that spreads: medicine, which is supposed to make her well, harms her, healthy women have designs on her husband, and people seem to “ghost” her. Though she imagines herself with a ghost’s power to wreak revenge on other women or to protect her children, and believes cancer gives her superpowers of perception, the character’s inability to connect with others is a clue that she is, in fact, a “real” ghost, a marvelous interpretation that appears logical within the realm of the story.Thus, the novella poses the question of the dynamics of fiction and reality, as suggested by a title that stands out in a speculative fiction anthology. Writing about his own wife’s cancer, Johnson blends facts of his family life with fantasy, in what may be deemed creative nonfiction. In a consideration of fantasy and mimesis, the mystery of the story echoing that of the human condition and the power of love apparent there are shown to add depth to the storyworld and make it believable.Finally, “Interesting Facts” is fantasy that raises and broadens consciousness, for Johnson questions the dynamics of power. He uses his wife’s voice and knowledge to question the society that alienates her, an opening onto a minority consciousness that ranks this work as counter literature as understood by Anthony Mangeon, for instance. His craft, spurred by the hope that the power of fate would alter, makes the world that the text opens onto, one in which new energy can enter and new spaces be made, a true picture of reality.

Stefania Sylos Labini, Pasquale di Biase, Elisabetta D'Apolito

Insurance companies are demonstrating increased sensitivity to environmental, social and governance sustainability issues (ESG - Environmental, Social and Governance). Products in the insurance sector are naturally attractive for social and environment goals as they respond to the requirements of customer protection and the growing need for stability in society. For this reason, activity in the insurance sector can contribute to the UN Sustainable Development Goals (SDGs) and be used to support the goals of climate neutrality by 2050. This study investigates sustainability-oriented management practices to determine whether they impact the financial performance of insurance companies. An international sample of 167 insurance companies, over the period 2018–2022, was analyzed to reveal whether investments in sustainability produce returns in terms of an economic advantage. Results show that American insurance companies are characterized by quality governance that is committed to environmental, social and governance sustainability policies which is linked to good financial performance. These results are robust to arbitrary heteroskedasticity and cluster correlation. Our findings add to the literature on Insurance Company by shedding light on the relationship between financial performance and sustainability.

Markus Matoni, Arno Kesper, Gabriele Taentzer

The digital transformation of our society is a constant challenge, as data is generated in almost every digital interaction. To use data effectively, it must be of high quality. This raises the question: what exactly is data quality? A systematic literature review of the existing literature shows that data quality is a multifaceted concept, characterized by a number of quality dimensions. However, the definitions of data quality vary widely. We used feature-oriented domain analysis to specify a taxonomy of data quality definitions and to classify the existing definitions. This allows us to identify research gaps and future topics.

Hira Naveed, Scott Barnett, Chetan Arora et al.

Context: Dynamic production environments make it challenging to maintain reliable machine learning (ML) systems. Runtime issues, such as changes in data patterns or operating contexts, that degrade model performance are a common occurrence in production settings. Monitoring enables early detection and mitigation of these runtime issues, helping maintain users' trust and prevent unwanted consequences for organizations. Aim: This study aims to provide a comprehensive overview of the ML monitoring literature. Method: We conducted a multivocal literature review (MLR) following the well established guidelines by Garousi to investigate various aspects of ML monitoring approaches in 136 papers. Results: We analyzed selected studies based on four key areas: (1) the motivations, goals, and context; (2) the monitored aspects, specific techniques, metrics, and tools; (3) the contributions and benefits; and (4) the current limitations. We also discuss several insights found in the studies, their implications, and recommendations for future research and practice. Conclusion: Our MLR identifies and summarizes ML monitoring practices and gaps, emphasizing similarities and disconnects between formal and gray literature. Our study is valuable for both academics and practitioners, as it helps select appropriate solutions, highlights limitations in current approaches, and provides future directions for research and tool development.

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.

David K Stevenson, Gary L Darmstadt, Yin Jien Lee et al.

Introduction In 2018, the American College of Obstetricians and Gynecologists recommended low-dose aspirin to prevent the onset of pre-eclampsia among women who were at high risk. Factors influencing women’s acceptance of this recommendation span multiple sectors and levels. Understanding how these factors interact will help stakeholders design effective population-level intervention strategies. Our study aims to identify and map relationships among factors influencing the medication decisions of pregnant women at risk of hypertensive disorders.Methods and analysis Preferred Reporting Items for Systematic Reviews and Meta-Analyses for Scoping Reviews (PRISMA-ScR) guidelines will be followed for this review. A research librarian developed a comprehensive search strategy to retrieve published and unpublished English studies after 1 January 1980, involving factors that influence pregnant women’s uptake and adherence to medication for gestational hypertensive disorders. This literature includes perceptions, patterns, acceptance, refusal, tendencies, probability and service utilisation. We will search PubMed, Embase, Web of Science and CINAHL. Reference lists of the selected papers will be searched manually to identify more relevant studies. A two-stage independent screening, consisting of title and abstract screening, followed by full-text screening, will be conducted by two independent reviewers to identify eligible articles. Extracted data will be recorded in a customised variable extraction form and input into a Microsoft Access database. The PRISMA-ScR will be used to guide the presentation of the results, which will be presented in a table and causal map to demonstrate the relationships between extracted variables and medication uptake and adherence. A conceptual simulation model will be formulated to validate the logic of the relationships between variables and identify knowledge gaps. Lastly, experts and stakeholders will be invited to critique and comment on the results.Ethics and dissemination This study does not require ethical approval. The full review results will be presented at a relevant conference and submitted to a peer-reviewed scientific journal for publication.

Jorge Aguilar Mora

Archivo histórico de Kipus: Revista Andina de Letras y Estudios Culturales, 1999.

Elena Altuna

Archivo histórico de Kipus: Revista Andina de Letras y Estudios Culturales, 1998.

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.

Yaqi Hua, Yaqi Hua, Yi Yuan et al.

ObjectivesTo systematically evaluate the risk prediction models for postoperative delirium in older adult hip fracture patients.MethodsRisk prediction models for postoperative delirium in older adult hip fracture patients were collected from the Cochrane Library, PubMed, Web of Science, and Ovid via the internet, covering studies from the establishment of the databases to March 15, 2023. Two researchers independently screened the literature, extracted data, and used Stata 13.0 for meta-analysis of predictive factors and the Prediction Model Risk of Bias Assessment Tool (PROBAST) to evaluate the risk prediction models for postoperative delirium in older adult hip fracture patients, evaluated the predictive performance.ResultsThis analysis included eight studies. Six studies used internal validation to assess the predictive models, while one combined both internal and external validation. The Area Under Curve (AUC) for the models ranged from 0.67 to 0.79. The most common predictors were preoperative dementia or dementia history (OR = 3.123, 95% CI 2.108–4.626, p < 0.001), American Society of Anesthesiologists (ASA) classification (OR = 2.343, 95% CI 1.146–4.789, p < 0.05), and age (OR = 1.615, 95% CI 1.387–1.880, p < 0.001). This meta-analysis shows that these were independent risk factors for postoperative delirium in older adult patients with hip fracture.ConclusionResearch on the risk prediction models for postoperative delirium in older adult hip fracture patients is still in the developmental stage. The predictive performance of some of the established models achieve expectation and the applicable risk of all models is low, but there are also problems such as high risk of bias and lack of external validation. Medical professionals should select existing models and validate and optimize them with large samples from multiple centers according to their actual situation. It is more recommended to carry out a large sample of prospective studies to build prediction models.Systematic review registrationThe protocol for this systematic review was published in the International Prospective Register of Systematic Reviews (PROSPERO) under the registered number CRD42022365258.

G. Zuckerman, C. Prakash, Matthew P. Askin et al.

Carlo Martinez

Review of Melville: guida a Moby-Dick by Giorgio Mariani

Faran Chaudry Bsc, Ihtisham Ahmad Bsc, Karim E. Gaber MD et al.

Category: Bunion Introduction/Purpose: The aim of this study was to evaluate the efficacy of percutaneous hemiepiphysiodesis for JHV by investigating the available literature on the procedure. Methods: The literature search was conducted by using the following bibliographic electronic databases: EMBASE, MEDLINE, and PubMed.gov. Study screening at all stages was completed in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) criteria. The Methodological Index for Non-Randomized Studies (MINORS) scale was used to evaluate the quality of included studies. Data on patient characteristics, radiological and clinical outcomes, and notable complications were also collected. Results: Of the 91 studies identified by our search strategy, 4 met the inclusion criteria. The identified studies included 62 patients and 109 feet. The mean hallux valgus angle (HVA) improved preoperative to postoperative at a range of Δ3.45 to Δ5.5. The mean intermetastartal angle (IMA) improved preoperative to postoperative at a range of Δ2.2 to Δ4.0. The mean HVA progression per month improved from preoperative to postoperative at a range of Δ0.07 degrees/month to Δ0.17 degrees/month. The mean IMA progression per month improved from preoperative to postoperative at a range of Δ0.046 degrees/month to Δ0.067 degrees/month. Of the studies that reported a mean American Orthopaedic Foot and Ankle Society (AOFAS) score or a mean Hallux Metatarsophalangeal Interphalangeal Scale (HMIS), there was an improvement at a range of Δ16.5 to Δ36. Conclusion: Percutaneous Hemiepiphysiodesis can serve as an effective procedure for treating Juvenile Hallux Valgus.