bluuebunny/crossref_metadata_2025_split huggingface dataset:
Trauma Patient Transitions From Critical Care: A Survey of U.S. Trauma Centers
Authors: Saucier Jason A. , Dietrich Mary S. , Maxwell Cathy , Lane-Fall Meghan Brooks , Minnick Ann 
Published: November 2023

BACKGROUND:
Transitions between clinical units are vulnerable periods for patients. A significant body of evidence describes the importance of structured transitions, but there is limited reporting of what happens. Describing transitions within a conceptual model will characterize the salient forces that interact during a patient transition and, perhaps, lead to improved outcomes.

OBJECTIVE:
To describe the processes and resources that trauma centers use to transition patients from critical care to nonintensive care units.

METHODS:
This cross-sectional study surveyed all Level I and II trauma centers listed in the American Trauma Society database from September 2020 to November 2020. Data were merged from the American Hospital Association 2018 Hospital Survey.

RESULTS:
A total of 567 surveys were distributed, of which 152 responded for a (27%) response rate. Results were organized in categories: capital input, organizational facets, employee behavior, employee terms/scope, and labor inputs. Resources and processes varied; the most important opportunities for transition improvement included: (1) handoff instruments were only reported at 36% (n = 27) of trauma centers, (2) mandatory resident education about transitions was only reported at 70% (n = 16) of trauma centers, and (3) only 6% (n = 4) of trauma centers reported electronic medical record applications that enact features to influence employee behavior.

CONCLUSIONS:
After years of focusing on transitions as a high-stake period, there remain many opportunities to develop resources and enact effective processes to address the variability in transition practice across trauma centers.
Right ventricular infarction: epidemiological, clinical, and angiographic characteristics and the outcomes through the experience of a Moroccan cardiology department
Authors: Bouhaddoune Youssra , Bouchlarhem Amine , Bazid Zakaria , Ismaili Nabila , El Ouafi Noha 
Published: November 2023

Background:
Acute myocardial infarction (MI) is a major cause of cardiovascular mortality, which is the leading cause of death in the world. Our objective in this study was to evaluate the epidemiological, clinical, and angiographic features of right ventricular infarction (RVI), as well as its complications and its therapeutic approaches.

Patients and methods:
It is a single-centered retrospective descriptive study conducted over a period of 2 years from November 2018 to October 2020. The authors included 82 patients with RVI hospitalized in the cardiovascular ICU during the initial phase of acute coronary syndrome with persistent ST segment elevation. Patients who were diagnosed with RVI at electrocardiogram and echocardiography were recruited.

Results:
The authors included 500 patients hospitalized for STEMI, 82 had MI extended to the RV, reflecting a rate of 16.4%. The mean age in our study was 64±12.3 years. Dyslipidemia, diabetes mellitus, and hypertension were the most common cardiovascular risk factors among these patients. RVI co-existed with inferior MI in 62.2 of cases and in 37.8% of anterior MI, while isolated RVI was seen in only one patient. Transthoracic echocardiography showed right ventricular (RV) systolic dysfunction in 24.39% of cases, while RV dilatation was seen in only 10.9% of patients. Therapeutic approach was based essentially on revascularization with thrombolysis and coronary angiography +/- PCI. The percentage of mortality was 2.4%.

Conclusion:
RVI is relatively rare and is mostly related to an extension of an inferior MI. Early diagnosis, prompt treatment, and appropriate are the keys to improve prognosis, and reduce complications.
Assessing the Effectiveness of ChatGPT as a Clinical Trainee: A Study on the Diagnostic Value of Large Language Models in a Complex Clinical Environment
Authors: Craig David , Nugent Chris 
Published: November 2023

AbstractWe tested the performance of Chat Generative Pre-trained Transformer (ChatGPT) in the role of a trainee clinician (Specialist Registrar or Resident) undergoing direct assessment by a human supervising specialist clinician (Consultant or Attending). The session consisted of a hospital ward round scenario presented to three versions of ChatGPT, namely OpenAI ChatGPT-3.5, Bing ChatGPT-4 and OpenAI ChatGPT-4. A specific test of memory and context was included via an end-of-teaching educator feedback exercise. Only OpenAI ChatGPT-4 provided responses comparable to the standard a trainee might offer during progress towards completion of training and specialist accreditation. Bing ChatGPT-4 responded with several clinically dubious statements, often in a repetitive and detached way, and was unable to retain awareness of the purpose of the session and the identities of participants.
Leveraging a large language model to predict protein phase transition: a physical, multiscale and interpretable approach
Authors: Frank Mor , Ni Pengyu , Jensen Matthew , Gerstein Mark B 
Published: November 2023

AbstractProtein phase transitions (PPTs) from the soluble state to a dense liquid phase (forming droplets via liquid-liquid phase separation) or to solid aggregates (such as amyloids) play key roles in pathological processes associated with age-related diseases such as Alzheimer’s disease. Several computational frameworks are capable of separately predicting the formation of droplets or amyloid aggregates based on protein sequences, yet none have tackled the prediction of both within a unified framework. Recently, large language models (LLMs) have exhibited great success in protein structure prediction; however, they have not yet been used for PPTs. Here, we fine-tune a LLM for predicting PPTs and demonstrate its usage in evaluating how sequence variants affect PPTs, an operation useful for protein design. In addition, we show its superior performance compared to suitable classical benchmarks. Due to the ”black-box” nature of the LLM, we also employ a classical random forest model along with biophysical features to facilitate interpretation. Finally, focusing on Alzheimer’s disease-related proteins, we demonstrate that greater aggregation is associated with reduced gene expression in AD, suggesting a natural defense mechanism.Significance StatementProtein phase transition (PPT) is a physical mechanism associated with both physiological processes and age-related diseases. We present a modeling approach for predicting the protein propensity to undergo PPT, forming droplets or amyloids, directly from its sequence. We utilize a large language model (LLM) and demonstrate how variants within the protein sequence affect PPT. Because the LLM is naturally domain-agnostic, to enhance interpretability, we compare it with a classical knowledge-based model. Furthermore, our findings suggest the possible regulation of PPT by gene expression and transcription factors, hinting at potential targets for drug development. Our approach demonstrates the usefulness of fine-tuning a LLM for downstream tasks where only small datasets are available.
DNA Methylation (DM) data format and DMtools for efficient DNA methylation data storage and analysis
Authors: Zhou Qiangwei , Zhou Cong , Zhu Zhixian , Sun Yuanhui , Li Guoliang 
Published: November 2023

AbstractDNA methylation is a critical epigenetic mechanism that plays a pivotal role in various biological processes. Currently, larger datasets from whole-genome bisulfite sequencing for DNA methylation pose challenges throughout the computational analysis pipeline, including storage and memory constraints. Unfortunately, storage formats and analysis tools have not kept pace with these increased resource demands. In this study, we present a new and efficient design for storing DNA methylation (DM) data after mapping in compressed binary indexed DM format. Our format significantly reduces storage space by 80%-95% compared to commonly used file formats for DNA methylation data after mapping. To enhance the processing of DNA methylation data in DM format, we have developed DMtools, a comprehensive toolkit that offers utilities such as rapid and random access, computation of DNA methylation profiles across genes, and analysis of differential DNA methylation. The analysis speed is improved by over 100 times compared to existing methods. Furthermore, we have created pyDMtools, a Python package that efficiently processes DM format files for Python users. The integration of the DM format and its associated tools represents significant progress in handling and exploring DNA methylation data, offering the potential to significantly reduce storage needs and improve downstream analysis capabilities.
Analytical hierarchy process for ranking green neighbourhood efforts in the Middle East and North Africa region
Authors: Asaad Moureen , Hassan Ghada Farouk , Elshater Abeer , Afifi Samy 
Published: November 2023

PurposeResearch on green certificate rankings in the MENA region primarily focuses on building scale, relying on the certified project count. This assessment approach overlooks the spatial factor, failing to capture their influence on the urban built environment, thus potentially undermining other efforts not reflected by the project count. This research aims to rank countries in the Middle East and Northern Africa (MENA) region based on their ongoing efforts regarding green neighbourhood certification.Design/methodology/approachThis study employs a three-phase methodology to rank MENA countries' adoption of green neighbourhood certification systems: content analysis, multicriteria analysis (MCA) using the analytical hierarchy process (AHP) and spatial analysis.FindingsBased on the content analysis, four major performance indicators were identified and the conventional ranking using projects count was presented. Using AHP, the MCA could rank the countries in the region according to their unique performance indicators score, clarifying the differences between conventional and AHP-based rankings. Finally, the spatial analysis phase uncovers shortcomings in the traditional ranking method, revealing inaccuracies and misrepresentations for several countries.Originality/valueThe study presents an innovative ranking methodology to monitor the green neighbourhood actions of countries in future development and establish a pioneering framework to evaluate the impact of green certifications within the region.
A novel quality risk evaluation framework for complex equipment development integrating PHFS-QFD and grey clustering
Authors: Wang Huan , Wang Daao , Wang Peng , Fang Zhigeng 
Published: November 2023

PurposeThe purpose of this research is to provide a theoretical framework for complex equipment quality risk evaluation. The primary aim of the framework is to enhance the ability to identify risks and improve risk control efficiency during the development phase.Design/methodology/approachA novel framework for quality risk evaluation in complex equipment is proposed, which integrates probabilistic hesitant fuzzy set-quality function deployment (PHFS-QFD) and grey clustering. PHFS-QFD is applied to identify the quality risk factors, and grey clustering is used to evaluate quality risks in cases of poor quality information during the development stage. The unfolding function of QFD is applied to simplify complex evaluation problems.FindingsThe methodology presents an innovative approach to quality risk evaluation for complex equipment development. The case analysis demonstrates that this method can efficiently evaluate the quality risks for aircraft development and systematically trace back the risk factors through hierarchical relationships. In comparison to traditional failure mode and effects analysis methods for quality risk assessment, this approach exhibits superior effectiveness and reliability in managing quality risks for complex equipment development.Originality/valueThis study contributes to the field by introducing a novel theoretical framework that combines PHFS-QFD and grey clustering. The integration of these approaches significantly improves the quality risk evaluation process for complex equipment development, overcoming challenges related to data scarcity and simplifying the assessment of intricate systems.
A rural dermatology outreach service – a new model
Authors: Abraham Kirstin , Thomas Huw , Bryden Alyson 
Published: November 2023

PurposeThe dermatology service on the islands of Orkney, with a population of approximately 22,500, was taken over by National Health Service (NHS) Tayside in August 2018. This paper aims to provide an overview of the planning and review of a highly efficient and effective dermatology service for a rural island population.Design/methodology/approachThe service includes visiting dermatology consultants, enhanced electronic referral vetting, skin surgery services, a General Practice (GP) with extended role (GPwER) in dermatology, specialist virtual clinics, urgent advice for inpatients at the local district general hospital and remote systemic therapy monitoring. A new phototherapy service has been set up in an island GP practice.FindingsLocal GPs and consultant dermatologists find the enhanced vetting service useable, efficient and educational. Between August 2018 and November 2022, there have been 1,749 referrals. Of these referrals, 60% were seen in clinic or a GPwER surgery, with 40% managed remotely by providing advice back to the referring GP. The number of consultations performed by the GPwER has grown over the past 3 years, and in the last year, it accounted for more than 50% of patient appointments. The waiting time has been significantly reduced using this model.Originality/valueThis remote service uses an integrated approach of teledermatology (TD) whilst offering continual in-person services using local capabilities including a GPwER and island general surgeons. New treatment facilities are provided to the island population. Continual educational feedback to the primary care referrer is provided, and it enhances relationships that greatly aid the high-quality dermatology service provided.
Diversity in online self-organizing teams: longitudinal evidence from an open innovation community
Authors: Ma Jifeng , Lu Yaobin , Gong Yeming , Li Ran 
Published: November 2023

PurposeThe development of information technologies has fueled the emergence of online self-organizing teams that involve members with diverse backgrounds to work on a shared goal voluntarily. However, the differences in members' attributes give rise to diversity. Therefore, the authors’ research is to figure out how diversity affects team performance in the context of online self-organizing teams and how this effect changes over team tenure.Design/methodology/approachThe authors use a dynamic approach to the diversity-team performance relationship and collect a publicly longitudinal dataset on 3,970 collaborative items from 2,550 online self-organizing teams spanning nine years in an open innovation community of an online game.FindingsThe empirical results show that culture separation is negatively related to team performance, and this negative relationship weakens as team tenure increases. While skill variety and contribution disparity are positively related to team performance, and these positive relationships strengthen as team tenure increases.Originality/valueThe study provides a research framework to examine the relationship between diversity and team performance and explore how this relationship varies over team tenure in the context of online self-organizing teams. The results not only demonstrate the double-edged role of diversity in affecting the success of online self-organizing teams but also advance the understanding on the temporal effect of diversity on team performance.
Six decades of corporate disclosure research: a bibliometric review
Authors: Srivastava Anjali , Anand  
Published: November 2023

PurposeCorporate disclosures are essential because they provide transparent and accurate information about a company's financial health, performance, risks and governance practices. They enable investors to make informed decisions, promote market efficiency and maintain trust in the financial system. This paper uses bibliometrics to identify the intellectual composition of the literature on corporate disclosure.Design/methodology/approachBased on the bibliometric information of 4,551 articles on corporate disclosure research, the authors conducted citation, keyword co-occurrence, bibliographic coupling and publication analyses to elucidate the leading articles, authors, sources, institutions, countries, themes and topics in the field of corporate disclosure from the 1960s to 2021.FindingsThe findings of this review demonstrate that corporate disclosure research is based on four broad themes – the role of disclosure in capital markets, non-financial disclosure, determinants of corporate disclosure and firm risk and intellectual capital disclosure. This review suggests that management should pay attention to the financial and non-financial corporate information that investors, regulators and the government emphasise.Originality/valueThis paper is the first comprehensive bibliometric review on corporate disclosure. It summarises the regulatory shifts, technological changes and industry trends that have influenced corporate disclosure research. Besides identifying broad research themes, the authors performed bibliographic coupling for research on disclosure sources, including annual reports, management forecasts, earnings calls, press releases, the Internet and social media, to reveal the thematic clusters related to these sources.
Comparison of life cycle assessment for wooden pallet and different plastic pallets based on SimaPro
Authors: Shao Fenjuan , Cui Qingbin 
Published: November 2023

Purpose
The study aims to compare and analyze the impact of the commonly used pallets (wooden pallet and plastic pallets), using life cycle assessment (LCA), then provide certain suggestions for the development of green packaging.

Design/methodology/approach
In this study, software Simapro was used to calculate and analyze the whole life cycle of pallets from the stage of raw materials and production to processing and waste disposal.

Findings
A total of 12 environmental categories were used to quantitatively analyze the environmental impact of the four different pallets. The results showed that, regardless of raw material, processing, or waste stage, the environmental impact of wooden pallet was lower than that of plastic pallet. Wooden pallet was better than plastic pallets.

Research limitations/implications
This study compared and analyzed the pallet of 1 × 1.2m with different materials.

Practical implications
Green packaging is the development trend of the future packaging, which follows the principle of 3R1D. According to the calculation results, corresponding suggestions can be put forward from production, processing, using, wasting and other aspects, and make corresponding contributions to the development of green packaging.

Originality/value
The contribution and impact of each stage of the product on the environment can be studied. The environmental impact, such as global warming potential, water scarcity, can be reduced through different solutions such as the use of green materials, good processing techniques and higher recycling rates.
Internship and career adaptability: addressing occupational stigma and identity for hospitality management students
Authors: Peng Fei , Li Yaoqi , Xu Wenting 
Published: November 2023

Purpose
The high turnover rate among interns exacerbates the shortage of human resources in the hospitality industry. This study is based on previous concerns about the impact of occupational stigma and internship on turnover intention. This study aims to explore how the career adaptability of interns influences their perception of occupational stigma and occupational identity.

Design/methodology/approach
By using stratified sampling, semistructured interviews were conducted with 34 respondents who had academic and vocational education backgrounds. The data analysis was performed using the thematic analysis method.

Findings
This study demonstrates that a high level of career adaptability helps to reduce interns’ perception of occupational stigma and strengthen their occupational identity. Students from academic and vocational schools display different levels of career adaptability in terms of job matching and career promotion. In addition, the long-term influence on occupational identity is more significant from professional development potential compared to job adaptation.

Research limitations/implications
This study provides valuable insights into the complex relationship between occupational stigma and occupational identity from the perspective of career adaptability. Moreover, it highlights the importance of job adaption, matching, promotion and professional development in retaining talent within the hospitality industry.

Originality/value
This study innovatively focuses on job matching and career promotion for coping with occupational stigma. It also considers interns’ educational backgrounds, facilitating further understanding of occupational identity under the influence of stigma. A fresh perspective on talent adaptation and retention in the hospitality industry is provided.
Sherlock—A flexible, low‐resource tool for processing camera‐trapping images
Authors: Penn Matthew J. , Miles Verity , Astley Kelly L. , Ham Cally , Woodroffe Rosie , Rowcliffe Marcus , Donnelly Christl A. 
Published: November 2023

Abstract

The use of camera traps to study wildlife has increased markedly in the last two decades. Camera surveys typically produce large data sets which require processing to isolate images containing the species of interest. This is time consuming and costly, particularly if there are many empty images that can result from false triggers. Computer vision technology can assist with data processing, but existing artificial intelligence algorithms are limited by the requirement of a training data set, which itself can be challenging to acquire. Furthermore, deep‐learning methods often require powerful hardware and proficient coding skills.

We present Sherlock, a novel algorithm that can reduce the time required to process camera trap data by removing a large number of unwanted images. The code is adaptable, simple to use and requires minimal processing power.

We tested Sherlock on 240,596 camera trap images collected from 46 cameras placed in a range of habitats on farms in Cornwall, United Kingdom, and set the parameters to find European badgers (Meles meles). The algorithm correctly classified 91.9% of badger images and removed 49.3% of the unwanted ‘empty’ images. When testing model parameters, we found that faster processing times were achieved by reducing both the number of sampled pixels and ‘bouncing’ attempts (the number of paths explored to identify a disturbance), with minimal implications for model sensitivity and specificity. When Sherlock was tested on two sites which contained no livestock in their images, its performance greatly improved and it removed 92.3% of the empty images.

Although further refinements may improve its performance, Sherlock is currently an accessible, simple and useful tool for processing camera trap data.