bluuebunny/crossref_metadata_2025_split huggingface dataset:
EDI in academic–policy engagement: lived experience of university based knowledge brokers and marginalised academics
Authors: Bea Laura , Recio-Saucedo Alejandra 
Published: July 2024

Background:
Discourse surrounding Equality, Diversity and Inclusion (EDI) has received significant attention within the UK academy and knowledge brokerage contexts, and more recently within academic–policy engagement spaces (Walker et al, 2019a; Fawcett, 2021; GOV.UK, 2021; Morris et al, 2021). Key players in this space identify the need for diversifying academic participation, as well as diversifying knowledges (GOV.UK, 2021; UK Parliament, 2018; UKRI, 2023). However, conceptual and practical insight on embedding EDI principles (and what they mean in this context) within academic–policy engagement processes is missing.

Aims and objectives:
Underpinned by feminist and decolonial epistemological concepts, this article addresses this gap by outlining strategies, and surfacing ways in which EDI within academic–policy engagement is experienced, conceptualised, understood and considered.

Methods:
Two parallel qualitative studies, with a total of 20 semi-structured narrative and realist interviews conducted with marginalised researchers (n=10, Study A) and university based knowledge brokers (n=10, Study B), and a rapid literature review. The analysis used a narrative and thematic framework.

Findings and discussion:
We found a want for EDI to go beyond just diversity of people and representation, towards fostering foundational principles of epistemic justice, equitable access, value-driven engagement and plurality. Academics and knowledge brokers reported both negative and positive experiences within this space that related to known EDI issues. We conclude that EDI cannot be standardised across higher education contexts, and emphasise the need for holistic, relational and plural approaches to EDI across academic–policy engagement systems through a value-led, equitable and ethical lens.
A ‘forced holiday’ or ‘no escape route’? Contrasting experiences of survivors and perpetrators of domestic abuse during COVID-19
Authors: Bloomer Rachael , Morgan Karen , Bennett Laura , Dheensa Sandi , Eisenstadt Nathan , Feder Gene , Leach Rwth , Roberts Jo , Cramer Helen 
Published: July 2024

Drawing on a nested qualitative study within REPROVIDE, a randomised controlled trial examining the effectiveness of a group-based domestic abuse perpetrator programme, this article explores accounts of domestic abuse during the COVID-19 pandemic from the perspectives of victims/survivors and perpetrators. Based on interviews with male perpetrators and female survivors, including with partner/ex-partner dyads, our study reveals the gendered effects of the pandemic on abusive perpetrator behaviour.
Findings are presented through themes addressing the different experiences of victims/survivors and perpetrators during the pandemic. Through an exploration of victim/survivor attempts to ameliorate intensified abuse through compliance (Theme 1), the way perpetrators put on a masculine ‘front’ (Theme 2), the gendered burden of domestic responsibilities (Theme 3) and highlighting the importance of continued specialist support (Theme 4), this article contributes to an understanding of gender inequalities underpinning pre-pandemic domestic violence and abuse and how perpetrators utilised inequalities during COVID restrictions. Some dyads reported relationships feeling more settled in the first UK lockdown, however, this was associated with increased opportunities for control that lockdown provided perpetrators. Both parties experienced changes in service responses. We articulate implications for safe working with perpetrators and families during future pandemics or social crises.
Intervención para la enseñanza de la escritura de palabras y textos. Estudio comparativo en Argentina
Authors: Marder Sandra , Jaquenod Rocio Guadalupe 
Published: July 2024

Los datos de reportes regionales y nacionales sugieren que la escritura de textos resulta una problemática menos estudiada, aunque muy claramente reportada por los docentes como área de profunda dificultad en los alumnos.
El presente estudio tiene como objetivo explorar los resultados de la intervención del programa de desarrollo integral y alfabetización “QA” en la escritura de palabras y textos de un grupo de alumnos de primer y segundo año de primaria de Argentina y, comparar los resultados, con un grupo de la misma escuela que ha recibido un tipo de enseñanza basada en la perspectiva del Whole language.
Para ello, se realizó un diseño exploratorio y longitudinal en el que se evaluó la escritura de palabras y textos pre (al inicio de primer grado) y post intervención (antes de finalizar ese año y a mediados de segundo grado). Entre las diferencias encontradas entre los grupos se destacan, a favor del grupo intervenido, una mejora en los procesos básicos de transcripción (escritura de palabras con complejidad silábica, mayor longitud y baja frecuencia), un incremento en la cantidad de palabras utilizadas en la producción textual, una mejor legibilidad, puntuación y la presencia de marcadores temporales. En la narración, los eventos se relacionan de manera cohesiva y se componen en la mayoría de los casos de una escena, una orientación, una complicación y un desenlace. De dichos resultados se desprende que, para lograr desempeños adecuados en la producción escrita de los alumnos, es fundamental la intervención sistemática en la enseñanza de la escritura que aborde todos los aspectos incluidos en el programa presentado, a partir de la formación docente y la enseñanza planificada.
Characteristics of atmospheric temperature in the vicinity of the Hefei area based on Rayleigh lidar
Authors: Qiu Feng , Wang Jie , Yuan Kee , Li Shenbo 
Published: July 2024

Temperature is an extremely important meteorological parameter in atmospheric research. Accurate measurements of it are of profound significance for studying global greenhouse effects, meteorological forecasting, and other related aspects. Processing and statistical analysis were conducted on the temperature data observed throughout 2021 by the self-developed L1000 Rayleigh lidar. Comparison analyses were subsequently carried out with data from the U.S. Standard Atmosphere Model and satellite observations, revealing good consistency in trend and magnitude between the lidar and both counterparts. Statistical analysis of the time–space evolution characteristics of the atmospheric temperature of the vicinity of the Hefei area was performed at night, in the month, and in the quarter. We found the monthly average atmospheric temperature exhibits a distinct altitudinal structure of time–space change, with the highest temperature being spatially located in the 48–51 km region and the temperature range being 240–272 K. Within the temperature rise range for 20–49 km, temperature profiles across different months also exhibit consistent trends. Temporally, temperatures are lowest in October and highest in August, gradually rising from March to August and declining from August to October, with a slight increase from October to November. Compared to monthly temperature profiles, seasonal temperature profiles exhibit stable variation trends, with the highest temperatures observed in the 49–50 km region, ranging from 251–270 K. Spring, autumn, and winter temperature profiles intertwine, while the summer temperature profile notably surpasses those of the other three seasons, demonstrating a distinct seasonal variation trend.
The First Generative AI Prompt-A-Thon in Healthcare: A Novel Approach to Workforce Engagement with a Private Instance of ChatGPT
Authors: Small William R. , Malhotra Kiran , Major Vincent J. , Wiesenfeld Batia , Lewis Marisa , Grover Himanshu , Tang Huming , Banerjee Arnab , Jabbour Michael J. , Aphinyanaphongs Yindalon , Testa Paul , Austrian Jonathan S. 
Published: July 2024

Background
Healthcare crowdsourcing events (e.g. hackathons) facilitate interdisciplinary collaboration and encourage innovation. Peer-reviewed research has not yet considered a healthcare crowdsourcing event focusing on generative artificial intelligence (GenAI), which generates text in response to detailed prompts and has vast potential for improving the efficiency of healthcare organizations. Our event, the New York University Langone Health (NYULH) Prompt-a-thon, primarily sought to inspire and build AI fluency within our diverse NYULH community, and foster collaboration and innovation. Secondarily, we sought to analyze how participants’ experience was influenced by their prior GenAI exposure and whether they received sample prompts during the workshop.

Methods
Executing the event required the assembly of an expert planning committee, who recruited diverse participants, anticipated technological challenges, and prepared the event. The event was composed of didactics and workshop sessions, which educated and allowed participants to experiment with using GenAI on real healthcare data. Participants were given novel “project cards” associated with each dataset that illuminated the tasks GenAI could perform and, for a random set of teams, sample prompts to help them achieve each task (the public repository of project cards can be found at https://github.com/smallw03/NYULH-Generative-AI-Prompt-a-thon-Project-Cards). Afterwards, participants were asked to fill out a survey with 7-point Likert-style questions.

Results
Our event was successful in educating and inspiring hundreds of enthusiastic in-person and virtual participants across our organization on the responsible use of GenAI in a low-cost and technologically feasible manner. All participants responded positively, on average, to each of the survey questions (e.g., confidence in their ability to use and trust GenAI). Critically, participants reported a self-perceived increase in their likelihood of using and promoting colleagues’ use of GenAI for their daily work. No significant differences were seen in the surveys of those who received sample prompts with their project task descriptions

Conclusion
The first healthcare Prompt-a-thon was an overwhelming success, with minimal technological failures, positive responses from diverse participants and staff, and evidence of post-event engagement. These findings will be integral to planning future events at our institution, and to others looking to engage their workforce in utilizing GenAI.
Current and lagged associations of meteorological variables and Aedes mosquito indices with dengue incidence in the Philippines
Authors: Cruz Estrella I. , Salazar Ferdinand V. , Aguila Ariza Minelle A. , Villaruel-Jagmis Mary Vinessa , Ramos Jennifer , Paul Richard E. 
Published: July 2024

BackgroundDengue is an increasing health burden that has spread throughout the tropics and sub-tropics. There is currently no effective vaccine and control is only possible through integrated vector management. Early warning systems (EWS) to alert potential dengue outbreaks are currently being explored but despite showing promise are yet to come to fruition. This study addresses the association of meteorological variables with both mosquito indices and dengue incidences and assesses the added value of additionally using mosquito indices for predicting dengue incidences.Methodology/Principal findingsEntomological surveys were carried out monthly for 14 months in six sites spread across three environmentally different cities of the Philippines. Meteorological and dengue data were acquired. Non-linear generalized additive models were fitted to test associations of the meteorological variables with both mosquito indices and dengue cases. Rain and the diurnal temperature range (DTR) contributed most to explaining the variation in both mosquito indices and number of dengue cases. DTR and minimum temperature also explained variation in dengue cases occurring one and two months later and may offer potentially useful variables for an EWS. The number of adult mosquitoes did associate with the number of dengue cases, but contributed no additional value to meteorological variables for explaining variation in dengue cases.Conclusions/SignificanceThe use of meteorological variables to predict future risk of dengue holds promise. The lack of added value of using mosquito indices confirms several previous studies and given the onerous nature of obtaining such information, more effort should be placed on improving meteorological information at a finer scale to evaluate efficacy in early warning of dengue outbreaks.
Prevalence of mortality among mechanically ventilated patients in the intensive care units of Ethiopian hospitals and the associated factors: A systematic review and meta-analysis
Authors: Ayenew Temesgen , Gedfew Mihretie , Fetene Mamaru Getie , Workneh Belayneh Shetie , Telayneh Animut Takele , Edmealem Afework , Tiruneh Bekele Getenet , Yinges Guadie Tewabe , Getie Addisu , Meselu Mengistu Abebe 
Published: July 2024

Background
In the intensive care unit (ICU), mechanical ventilation (MV) is a typical way of respiratory support. The severity of the illness raises the likelihood of death in patients who require MV. Several studies have been done in Ethiopia; however, the mortality rate differs among them. The objective of this systematic review and meta-analysis is to provide a pooled prevalence of mortality and associated factors among ICU-admitted patients receiving MV in Ethiopian hospitals.

Methods
We used the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020 criteria to conduct a comprehensive systematic review and meta-analysis in this study. We searched PubMed/Medline, SCOPUS, Embase, Hinari, and Web of Science and found 22 articles that met our inclusion criteria. We used a random-effects model. To identify heterogeneity within the included studies, meta-regression and subgroup analysis were used. We employed Egger’s regression test and funnel plots for assessing publication bias. STATA version 17.0 software was used for all statistical analyses.

Results
In this systematic review and meta-analysis, the pooled prevalence of mortality among 7507 ICU-admitted patients from 22 articles, who received MV was estimated to be 54.74% [95% CI = 47.93, 61.55]. In the subgroup analysis by region, the Southern Nations, Nationalities, and Peoples (SNNP) subgroup (64.28%, 95% CI = 51.19, 77.37) had the highest prevalence. Patients with COVID-19 have the highest mortality rate (75.80%, 95% CI = 51.10, 100.00). Sepsis (OR = 6.85, 95%CI = 3.24, 14.46), Glasgow Coma Scale (GCS) score<8 (OR = 6.58, 95%CI = 1.96, 22.11), admission with medical cases (OR = 4.12, 95%CI = 2.00, 8.48), Multi Organ Dysfunction Syndrome (MODS) (OR = 2.70, 95%CI = 4.11, 12.62), and vasopressor treatment (OR = 19.06, 95%CI = 9.34, 38.88) were all statistically associated with mortality.

Conclusion
Our review found that the pooled prevalence of mortality among mechanically ventilated ICU-admitted patients in Ethiopia was considerably high compared to similar studies in the United States (US), China, and other countries. Sepsis, GCS<8, medical cases, MODS, and use of vasopressors were statistically associated with mortality. Clinicians should exercise caution while mechanically ventilating ICU-admitted patients with these factors. However, it should be noted that the exact cause and effect relationship could not be established with this meta-analysis, as the available evidence is not sufficient. Thus, more studies using prospective methods will be required.
Development and validation of a predictive model for postpartum endometritis
Authors: Wang Xiujuan , Shao Hui , Liu Xueli , Feng Lili 
Published: July 2024

Objective
The aim was to develop a predictive tool for anticipating postpartum endometritis occurrences and to devise strategies for prevention and control.

Methods
Employing a retrospective approach, the baseline data of 200 women diagnosed with postpartum endometritis in a tertiary maternity hospital in Zhejiang Province, spanning from February 2020 to September 2022, was examined. Simultaneously, the baseline data of 1,000 women without endometritis during the same period were explored with a 1:5 ratio. Subsequently, 1,200 women were randomly allocated into a training group dataset and a test group dataset, adhering to a 7:3 split. The selection of risk factors for postpartum endometritis involved employing random forests, lasso regression, and traditional univariate and multifactor logistic regression on the training group dataset. A nomogram was then constructed based on these factors. The model’s performance was assessed using the area under the curve (AUC), calculated through plotting the receiver operating characteristic (ROC) curve. Additionally, the Brier score was employed to evaluate the model with a calibration curve. To gauge the utility of the nomogram, a clinical impact curve (CIC) analysis was conducted. This comprehensive approach not only involved identifying risk factors but also included a visual representation (nomogram) and thorough evaluation metrics, ensuring a robust tool for predicting, preventing, and controlling postpartum endometritis.

Results
In the multivariate analysis, six factors were identified as being associated with the occurrence of maternal endometritis in the postpartum period. These factors include the number of negative finger tests (OR: 1.159; 95%CI: 1.091–1.233; P < 0.05), postpartum hemorrhage (1.003; 1.002–1.005; P < 0.05), pre-eclampsia (9.769; 4.64–21.155; P < 0.05), maternity methods (2.083; 1.187–3.7; P < 0.001), prenatal reproductive tract culture (2.219; 1.411–3.47; P < 0.05), and uterine exploration (0.441; 0.233–0.803; P < 0.001).A nomogram was then constructed based on these factors, and its predictive performance was assessed using the area under the curve (AUC). The results in both the training group data (AUC: 0.803) and the test group data (AUC: 0.788) demonstrated a good predictive value. The clinical impact curve (CIC) further highlighted the clinical utility of the nomogram.

Conclusion
The development of an individualized nomogram for postpartum endometritis infection holds promise for doctors in screening high-risk women, enabling early intervention and ultimately reducing the rate of postpartum endometritis infection. This comprehensive approach, integrating key risk factors and predictive tools, enhances the potential for timely and targeted medical intervention.
La Experiencia Corporal: Desentrañando Develaciones de Sentido y Realidad
Authors: Montoya-Rivera Irene , Rodríguez Linna Carolina 
Published: July 2024

La experiencia corporal es un punto de encuentro en los diálogos presentados entre las diversas apuestas reflexivas esbozadas en este dossier, como prueba irrefutable de los encarnamientos del ser en la construcción de la vida. Tejernos al mundo, asirnos a él desde nuestra subjetividad implica como experiencia dar cuenta de lo vivido, lo sentido y lo percibido, para ser en tanto somos y somos con otrxs, exhibiendo huellas de la existencia germinadas en la cotidianidad. Si de algo da cuenta el cuerpo a través de la experiencia es de su condición sintiente y viviente. De allí que, como epicentro de las indagaciones planteadas en campos diversos del conocimiento, se torne materia de descubrimientos de sentido, interpretando vivencias, afectos y acciones intersensibles de cara a la realidad social y cultural.
The effect of form presentation mode and language learning aptitude on the learning burden and decay of L2 vocabulary knowledge
Authors: Barclay Samuel 
Published: July 2024

Abstract
L2 words vary in how hard they are to learn and how quickly they are forgotten. This study explored two factors that may contribute to this variance: form presentation mode and language learning aptitude. English learners studied 32 words using electronic flashcard software in two conditions: unimodal (written form) and bimodal (spoken and written form). The frequency of exposure needed to learn each word was measured and used to determine learning burden. Learners, L2 users of English studying at a British university, completed immediate and two-week delayed tests, which were used to track any decay that occurred. Aptitude was measured using the LLAMA battery and incorporated into statistical modelling. The results showed that form presentation mode (bimodal > unimodal) and some aspects of aptitude impacted learning. No effects were found on decay. Pedagogical implications are discussed.
Multi-attribute perceptual fuzzy information decision-making technology in investment risk assessment of green finance Projects
Authors: Feng Jianjie 
Published: July 2024

Abstract
In the investment risk assessment of green finance (GF) projects, the application of multi-attribute perceptual fuzzy information decision technology is taken as the main research object. With the promotion of the concept of environmental protection and the development of green economy, the investment risk assessment of GF projects has become more and more important. However, this requires dealing with a large amount of fuzzy information and multi-attribute decision problems, which is a big challenge for traditional decision techniques. Based on this background, a new decision model, intuitionistic fuzzy preference theory-based tomada de decisão interativa multicritério (IF-PT-TODIM), is adopted, which can better deal with fuzzy information and multi-attribute decision problems by taking two different choices as reference. By knowing the weight distribution of experts, the model can better assess the influence of various factors on the decision. In the research results, the calculated results of expert weights are 0.2796, 0.2221, 0.1914, 0.1328, and 0.1745, respectively, showing that each expert has different degrees of influence on decision-making. In addition, the application of IF-PT-TODIM model can effectively reduce the investment risk. Compared with national bank of Kuwait, systematic review, evolutionary algorithm, the improved method can reduce the risk of venture capital by 28.14, 15.47, and 11.05%, respectively. This result further confirms the advantage of the IF-PT-TODIM model in dealing with fuzzy information and multi-attribute decision problems. This study has practical implications for understanding and improving the investment risk assessment of GF projects. It not only provides a new decision model for risk assessment, but also provides an effective method to deal with fuzzy information and multi-attribute decision problems. This provides new ideas and methods for the risk management of GF projects and also provides a new perspective and reference for research in related fields.
Multi-source auxiliary information tourist attraction and route recommendation algorithm based on graph attention network
Authors: Ding Tongtong 
Published: July 2024

Abstract
In the field of tourism recommendation systems, accurately recommending scenic spots and routes for users is one of the hot research directions. In order to better consider the complex interaction between user preferences and attraction features, as well as the potential connections between different information sources, this study constructed a graph attention network model using knowledge graphs for tourist attraction and route recommendations, and extracted features from visual images using visual geometry group-16. The results indicate that, in Xian, when the learning rate is 0.01, the area under the curve value is 0.916. The area under the curve of New York is 0.909, and the learning rate is 0.001. The area under the curve value of the Tokyo dataset is 0.895. When the learning rate is moderate, the model quickly stabilizes in the first 16 rounds and reaches its optimal state in 26–30 rounds. When the propagation depth is 2, the accuracy is 0.920, 0.905, and 0.895, respectively. After introducing visual features, the accuracy, recall, and F1 score improved by 10 to 15.7%. The multi-layer perceptron further increased the effect by 4–6%. These experimental data fully demonstrate the effectiveness and accuracy of the recommendation algorithm. This study provides a powerful tool for tourism recommendation systems, which helps to further improve user experience.