Hasil untuk "American literature"

M. Hammond, D. Hayes, M. Dowsett et al.

M. Baumann, C. Strange, J. Heffner et al.

Ivor D. Hill, M. Dirks, Gregory S. Liptak et al.

Celiac disease is an immune-mediated enteropathy caused by a permanent sensitivity to gluten in genetically susceptible individuals. It occurs in children and adolescents with gastrointestinal symptoms, dermatitis herpetiformis, dental enamel defects, osteoporosis, short stature, delayed puberty and persistent iron deficiency anemia and in asymptomatic individuals with type 1 diabetes, Down syndrome, Turner syndrome, Williams syndrome, selective immunoglobulin (Ig)A deficiency and first degree relatives of individuals with celiac disease. The Celiac Disease Guideline Committee of the North American Society for Pediatric Gastroenterology, Hepatology and Nutrition has formulated a clinical practice guideline for the diagnosis and treatment of pediatric celiac disease based on an integration of a systematic review of the medical literature combined with expert opinion. The Committee examined the indications for testing, the value of serological tests, human leukocyte antigen (HLA) typing and histopathology and the treatment and monitoring of children with celiac disease. It is recommended that children and adolescents with symptoms of celiac disease or an increased risk for celiac disease have a blood test for antibody to tissue transglutaminase (TTG), that those with an elevated TTG be referred to a pediatric gastroenterologist for an intestinal biopsy and that those with the characteristics of celiac disease on intestinal histopathology be treated with a strict gluten-free diet. This document represents the official recommendations of the North American Society for Pediatric Gastroenterology, Hepatology and Nutrition on the diagnosis and treatment of celiac disease in children and adolescents.

D. Adams, A. Comrie

Jio Oh, Paul Vicinanza, Thomas Butler et al.

More than 80% of the 1.6 billion English speakers do not use Standard American English (SAE) and experience higher failure rates and stereotyped responses when interacting with LLMs as a result. Yet multi-dialectal performance remains underexplored. We introduce MDial, the first large-scale framework for generating multi-dialectal conversational data encompassing the three pillars of written dialect -- lexical (vocabulary), orthographic (spelling), and morphosyntactic (grammar) features -- for nine English dialects. Partnering with native linguists, we design an annotated and scalable rule-based LLM transformation to ensure precision. Our approach challenges the assumption that models should mirror users' morphosyntactic features, showing that up to 90% of the grammatical features of a dialect should not be reproduced by models. Independent evaluations confirm data quality, with annotators preferring MDial outputs over prior methods in 98% of pairwise comparisons for dialect naturalness. Using this pipeline, we construct the dialect-parallel MDialBenchmark with 50k+ dialogs, resulting in 97k+ QA pairs, and evaluate 17 LLMs on dialect identification and response generation tasks. Even frontier models achieve under 70% accuracy, fail to reach 50% for Canadian English, and systematically misclassify non-SAE dialects as American or British. As dialect identification underpins natural language understanding, these errors risk cascading failures into downstream tasks.

Catherine Girodet

Over the course of his forty-five-year music career, Australian singer-songwriter Nick Cave has been widely perceived as a baffling shape-shifter on the independent rock scene, on account of his extreme musical shifts and broad artistic palette spanning post-punk rock, blues rock ballads, garage rock, piano-led hymnals and more recently, looser meditative electronic music. Notwithstanding its stylistic diversity, Cave’s song-world presents two abiding features: a fascination with darkness and a propensity for intertextuality. As part of his aesthetic mingling, Cave the self-identified “literary musician” thus cross-pollinates rock music with a flurry of artistic influences such as Southern Gothic, hymnals, traditional folk-blues ballads, and indeed Romanticism, notably in his love-songs. The purpose of this article is to probe the scope of Cavian dark Romanticism in the seminal love-song albums Boatman’s Call (1997) and No More Shall We Part (2001), as well as in Murder Ballads (1996). In particular, the focus will be on Cave’s treatment of the love motif as eroticised pain and longing, as aestheticised violence, and as a path to the sublime. The paradoxical principle of pleasure in pain underpinning Cave’s love-songs evokes “Romantic Agony,” an aesthetics of counterpleasure which literary theorist Mario Praz identified as a Romantic structuring principle disseminating across media. Positing Cave’s dark love song as an idiosyncratic form of “Romantic Agony,” this research aims to demonstrate that in using the imprint of Romanticism as an aesthetic source, Cave brings forth a fresh musical idiom of Romantic Agony, whilst weaving it enduringly into the fabric of his songwriting.

Linda Kaljee, Doreen Dankerlui, Alfred Pach et al.

Abstract Background The United States has the highest maternal mortality rate among high-income countries. Black/African American women and infants experience significant disparities in mortality rates. Henry Ford Global Health Initiative implemented a mixed-methods study to explore the association of hopefulness and burn out among healthcare workers (HCWs) and health experiences and outcomes of Black/African American pregnant and post-partum healthcare recipients (HCRs). Methods Quantitative data included demographics and the Herth Hope Index (HHI). Qualitative research included focus groups and individual interviews with HCWs and HCRs from two Henry Ford Health Women’s Health clinics. Prior to data collection, a literature review was completed. Descriptive data and bivariate analysis were completed. Qualitative data used semi-structured interview guides and were audio-taped, transcribed, and coded using Dedoose. Final data tables included codes, sub-themes, and representative quotes. Stakeholder workshops were held in 2020 and 2024. Results Sixty-six HCWs completed the demographic form and HHI. In 2021, 34 (87.2%) HCWs participated in focus groups or interviews and 25 (92.6%) in 2023. Sixty-one HCRs completed the demographic form and HHI and 27 (44.3%) participated in focus groups. On the 48-point HHI scale, HCWs scored 41.7 (SD 4.6) and HCRs scored 40.8 (SD 7.0) indicating a relatively high level of hopefulness. HCW qualitative outcomes included: (1) definitions of hopefulness and hopelessness: (2) personal and work-related sources of care and support; and (3) clinical and systemic challenges and facilitators to meeting patient needs. HCR qualitative outcomes included: (1) definitions of hopefulness and hopelessness; (2) personal, familial, and social sources of care and support; and (3) pregnancy and post-partum healthcare experiences. In 2020, workshop participants generated factors affecting hope in both HCRs and HCWs and potential solutions to reduce burnout and improve pre- and post-partum care for Black/African American women. In 2024, workshop participants reviewed data and prioritized recommendations for interventions. Conclusion This study explored the role of hope as a contributing factor in the experiences of HCWs and Black/African American pregnant and post-partum HCRs. It generated recommendations to address hopelessness and support positive experiences and outcomes. Next steps include identifying resources to pilot and evaluate recommendations at the health system and clinical levels.

J. Ruiz, P. Steffen, Timothy B. Smith

Aleksander Sivilov

The text examines the manifestations of censorship on socially engaged literature in the USA during the first half of the 20th century, focusing on three emblematic works: Upton Sinclair’s The Jungle, Theodore Dreiser’s An American Tragedy, and John Steinbeck’s The Grapes of Wrath. The author considers censorship not only as the restriction of information but also as a means of political and moral control within so-called democratic societies. Each of the three works provoked sharp public and institutional reactions due to its social critique, leading to bans, surveillance by agencies, and pressure on the authors. Specific censorship mechanisms are indicated – from laws like the Comstock Acts to self-censorship by publishers and editors. The text defends the thesis that social literature in the USA played a crucial role in exposing societal contradictions, despite efforts to suppress it.

Carol Neidle

There have been recent advances in computer-based recognition of isolated, citation-form signs from video. There are many challenges for such a task, not least the naturally occurring inter- and intra- signer synchronic variation in sign production, including sociolinguistic variation in the realization of certain signs. However, there are several significant factors that make recognition of signs from continuous signing an even more difficult problem. This article presents an overview of such challenges, based in part on findings from a large corpus of linguistically annotated video data for American Sign Language (ASL). Some linguistic regularities in the structure of signs that can boost handshape and sign recognition are also discussed.

Facundo Gómez

Reseña del libro de Carla Daniela Benisz. Aporías de la letra. Apuestas críticas para la literatura paraguaya. Asunción, Arandurá, 2022. DOI: https://zenodo.org/record/8212697

I. Duran-Cristobal, A. Noguero-Alegre, A. M. Matas-Ochoa et al.

Introduction One of the most important functions of sleep may be the promotion of brain development. The non-REM and REM sleep sequences show the succession of cerebral processing phenomena that underlie memory consolidation. The negative consequences of sleep loss on neural and behavioral plasticity has been examined. On the other hand, sleep disruption can be a crucial symptom to develop depression disorders. Recent literature suggests that maintenance insomnia may be a risk factor for dementia. It would be important to elucidate which factors may increase the risk of developing dementia and aggravating its progression. Objectives The aim of this scoping review is to point out the increased risk of developing dementia related to insomnia and depression. Methods Relevant literature was searched with PUBMED as electronic database. We used and combined the following MeSH terms: depression, insomnia, cognitive impairment and dementia. We chose sixteen recent studies from 2009 to 2021. Four of them were ruled out because the methodology and conclusions were not enough evident. Results We underlined an interesting research which was carried out with Chinese population in 2021. A total of 256 patients with insomnia disorder were diagnosed by neurologists, 45 of whom were diagnosed with amnesic mild cognitive impairment (aMCI) and 45 participants with intact cognition were chosen as controls matched for age and education. A case-control study was conducted to compare sleep structure between aMCI and control patients with insomnia disorder. An American prospective research in 2016 founded a statistically significant association with a higher MCI/dementia risk in women with either short (≤6 hours/night) or long (≥8 hours/night) sleep duration (vs.7 hours/night). The relationships between depression, cognitive function, serum brain-derived neurotrophic factor (BDNF) and volumetric MRI measurements in older adults were investigated. A total of 4352 individuals aged 65 years or older (mean age 72 years) participated in this Japanese study. Conclusions According to these researches, we emphasize the importance of detecting sleep disturbances as potential risk factors for MCI and dementia. All of them provide evidences that future studies should investigate dementia prevention among elderly individuals through the management of insomnia. At that point we have to consider personalized medicine and machine learning techniques for sleep and cognitive or mood symptoms. Disclosure of InterestNone Declared

Raimundo Leoberto Torres de Sousa, Thais de Araujo-Pereira, Anangela Ravena da Silva Leal et al.

<h4>Background</h4>Leishmaniases are vector borne diseases caused by Leishmania spp. parasites transmitted by female sandflies (Diptera: Psychodidae) whose geographic distribution is influenced by environmental factors. Among the main tools for studying the distribution of vector species, modeling techniques are used to analyze the influence of climatic and environmental factors on the distribution of these insects and their association with human cases of the disease.<h4>Methodology/principal findings</h4>Here, we used a multiscale ecological niche modeling approach to assess the environmental suitability of sandfly vectors of the etiological agents of Visceral (VL) and American Cutaneous Leishmaniasis (ACL) in Piauí state, northeastern Brazil, and then evaluated their relationship with human disease incidence. For this, we obtained the geographic coordinates of the vector species Lutzomyia longipalpis and Nyssomyia whitmani through literature review, online databases and unpublished records. These data were used for the development of predictive models of the distribution of both sandflies species based on climatic and environmental variables. Finally, the environmental suitability for the presence of these vectors was compared with the incidence of both the diseases at the municipality level. The final models for each sandfly species showed good predictive powers with performance metric values of 0.889 for Lu. longipalpis and 0.776 for Ny. whitmani. The areas with greater environmental suitability for the presence of these species were concentrated in the central-north region of Piauí and coincide with the location of those municipalities presenting higher incidences of VL and ACL, situated in the central-north and extreme north of the state, respectively. The south and southeast regions of Piauí state have low incidence of these diseases and presented low environmental suitability for the presence of both vectors.<h4>Conclusions/significance</h4>We discuss how predictive modeling can guide entomological and epidemiological surveillances and recommend an increased supervision and control activities in Teresina (capital of the state of Piaui), Altos and Pedro II, in addition to other municipalities with similar social and environmental characteristics.

Neha Patankar, Xiili Sarkela-Basset, Greg Schivley et al.

Land-use conflicts may constrain the unprecedented rates of renewable energy deployment required to meet the decarbonization goals of the Inflation Reduction Act (IRA). This paper employs geospatially resolved data and a detailed electricity system capacity expansion model to generate 160 affordable, zero-carbon electricity supply portfolios for the American west and evaluates the land use impacts of each portfolio. Less than 4% of all sites suitable for solar development and 17% of all wind sites appear in this set of portfolios. Of these sites, 53% of solar and 85% of wind sites exhibit higher development risk and potential for land use conflict. We thus find that clean electricity goals cannot be achieved in an affordable manner without substantial renewable development on sites with potential for land use conflict. However, this paper identifies significant flexibility across western U.S. states to site renewable energy or alter the composition of the electricity supply portfolio to ameliorate potential conflicts.

Weilin Fu, Zhuoran Li, Yupeng Zhang et al.

Every financial crisis has caused a dual shock to the global economy. The shortage of market liquidity, such as default in debt and bonds, has led to the spread of bankruptcies, such as Lehman Brothers in 2008. Using the data for the ETFs of the S&P 500, Nasdaq 100, and Dow Jones Industrial Average collected from Yahoo Finance, this study implemented Deep Learning, Neuro Network, and Time-series to analyze the trend of the American Stock Market in the post-COVID-19 period. LSTM model in Neuro Network to predict the future trend, which suggests the US stock market keeps falling for the post-COVID-19 period. This study reveals a reasonable allocation method of Long Short-Term Memory for which there is strong evidence.

Jonathan David Farley

Let $P$ be a finite poset with an element $s$ such that (1) for all $x\in P$, either $s\vee x$ or $s\wedge x$ exists; and (2) for all $x,y\in P$ such that $x<y$, if $s\wedge x$ does not exist but $s\wedge y$ does exist, then $(s\wedge y)\vee x$ exists. Kozlov, the winner of the 2005 European Prize in Combinatorics ("for deep combinatorial results obtained by algebraic topology and particularly for the solution of a conjecture of Lovász"), conjectured in the 1998 Proceedings of the American Mathematical Society that the order complex of $P$ is non-evasive. We prove this conjecture.

Federico Tavella, Viktor Schlegel, Marta Romeo et al.

Signed Language Processing (SLP) concerns the automated processing of signed languages, the main means of communication of Deaf and hearing impaired individuals. SLP features many different tasks, ranging from sign recognition to translation and production of signed speech, but has been overlooked by the NLP community thus far. In this paper, we bring to attention the task of modelling the phonology of sign languages. We leverage existing resources to construct a large-scale dataset of American Sign Language signs annotated with six different phonological properties. We then conduct an extensive empirical study to investigate whether data-driven end-to-end and feature-based approaches can be optimised to automatically recognise these properties. We find that, despite the inherent challenges of the task, graph-based neural networks that operate over skeleton features extracted from raw videos are able to succeed at the task to a varying degree. Most importantly, we show that this performance pertains even on signs unobserved during training.

Walter Giordano

The contribution of this study is expressed in the following research question: is it possible to identify some implicit-explicit textual or visual elements that catalyze or distract audience attention on or from the advertised product? An analysis of a corpus of advertisements taken from the Instagram pages of the major companies operating in the US food and beverage market reveals that attracting or distracting attention on or from a product’s use or function is a frequent strategy. These elements may contribute to changing scripts in advertising and mental patterns in consumer perceptions. The items that signal the distraction or the catalyzation of consumer attention in the advertising message have been identified via the ARCO model (St.Amant forth., St.Amant 2022), based upon the concept of usability of products, which helps decode the process of recognition of a product in the consumer’s brain. Results are promising, as this theory may help advertisers make more effective moves in the dual, cooperative relationship with consumers and review promotional strategies to engage the audience in advertising communication.

Kendall J. Arslanian, Mireya Vilar-Compte, Graciela Teruel et al.

The Baby-Friendly Hospital Initiative (BFHI) has been shown to increase breastfeeding rates, improving maternal and child health and driving down healthcare costs via the benefits of breastfeeding. Despite its clear public health and economic benefits, one key challenge of implementing the BFHI is procuring funding to sustain the program. To address this need and help healthcare stakeholders advocate for funds, we developed a structured method to estimate the first-year cost of implementing BFHI staff training, using the United States (US) and Mexico as case studies. The method used a hospital system-wide costing approach, rather than costing an individual hospital, to estimate the average per birth BFHI staff training costs in US and Mexican hospitals with greater than 500 annual births. It was designed to utilize publicly available data. Therefore, we used the 2014 American Hospital Association dataset (n = 1401 hospitals) and the 2018 Mexican Social Security Institute dataset (n = 154 hospitals). Based on our review of the literature, we identified three key training costs and modelled scenarios via an econometric approach to assess the sensitivity of the estimates based on hospital size, level of obstetric care, and training duration and intensity. Our results indicated that BFHI staff training costs ranged from USD 7.27–125.39 per birth in the US and from PPP 2.68–6.14 per birth in Mexico, depending on hospital size and technological capacity. Estimates differed between countries because the US had more hospital staff per birth and higher staff salaries than Mexico. Future studies should examine whether similar, publicly available data exists in other countries to test if our method can be replicated or adapted for use in additional settings. Healthcare stakeholders can better advocate for the funding to implement the entire BFHI program if they are able to generate informed cost estimates for training as we did here.