bluuebunny/crossref_metadata_2025_split huggingface dataset:
DrivR-Base: A Feature Extraction Toolkit For Variant Effect Prediction Model Construction
Authors: Francis Amy , Campbell Colin , Gaunt Tom 
Published: January 2024

AbstractMotivationRecent advancements in sequencing technologies have led to the discovery of numerous variants in the human genome. However, understanding their precise roles in diseases remains challenging due to their complex functional mechanisms. Various methodologies have emerged to predict the pathogenic significance of these genetic variants. Typically, these methods employ an integrative approach, leveraging diverse data sources that provide critical insights into genomic function. Despite the abundance of publicly available data sources and databases, the process of navigating, extracting, and pre-processing features for machine learning models can be daunting. Furthermore, researchers often invest substantial effort in feature extraction, only to later discover that these features lack informativeness.ResultsIn this paper, we presentDrivR-Base, an innovative resource that efficiently extracts and integrates molecular information (features) for single nucleotide variants from a wide range of databases and tools, including AlphaFold, ENCODE, andVariant Effect Predictor. The resulting features can be used as input for machine learning models designed to predict the pathogenic impact of human genome variants in disease. Moreover, these feature sets have applications beyond this, including haploinsufficiency prediction and the development of drug repurposing tools. We describe the resource’s development, practical applications, and potential for future expansion and enhancement.Availability and ImplementationDrivR-Basesource code is available athttps://github.com/amyfrancis97/DrivR-Base.
An AI Method for Assessing Coding Consistency in a Large Dataset
Authors: Nelson Stuart J. , Yin Ying , Shao Yijun , Ma Phillip , Tuttle Mark S. , Zeng-Treitler Qing 
Published: January 2024

AbstractObjectiveWe developed a method to assess the consistency of the assignment of ICD codes, using coding performed at a United States health system at the time of the transition from ICD-9CM to ICD-10CM.MethodsUsing clusters of equivalent codes derived from the US Centers for Disease Control General Equivalence Mapping (GEM) tables, ICD assignments occurring during the ICD-9CM to ICD-10CM transition were evaluated in EHR data from the US Veterans Administration Central Data Warehouse, using a deep learning model based on 860 covariates. The model was then used to detect abrupt changes across the transition; additionally changes at each VA station were examined.ResultsMany of the 687 most-used code clusters had ICD-10CM assignments differing greatly from that predicted by the GEM from the codes used in ICD-9CM. Notably, the observed transition patterns varied widely across care locations.ConclusionMachine learning can model variability across time and across location, enabling an assessment of coding consistency. Expert review is not scalable, deep learning model applied to a large dataset of EHR records provides an approximation of ground truth.
Experiences and observations from a care point for displaced Ukrainians: a community case study in Antwerp, Belgium
Authors: Morreel Stefan , Verhoeven Veronique , Bastians Hilde , Monten Katrien , van Olmen Josefien 
Published: January 2024

AbstractBackground7307 Ukrainians refugees moved to Antwerp, Belgium during the study period (01/04/2023-31/12/2023). The city’s administration set up three care centers where these people were introduced in the Belgian primary care system, a medical file was created, and acute/preventive/chronic care was delivered. This community case study analyses the organization and contents of care and reflects upon its meaning for the mainstream health care system.MethodsThis is an observational study using routine electronic medical record data to measure uptake of care. For a sample of 200 subjects, a retrospective chart review was conducted in order to extract data from patient records.Participantsall refugees with a medical file at one of the three participating care centers.Main OutcomesFor the observational study, 2261 patients were reached (30% of the potential users) and 6450 contacts were studied. The nurses (including midwives) did 4929/6450 (76%) of all consultations, the GPs 1521/6450 (24%). Out of the 4929 nurse consultations, 955 (19%) were followed by another nurse consultation and 866 (18%) by a GP consultation. In the structured case reviews most contacts concerned acute problems (609/1074, 57%). The most prevalent reasons for encounter and diagnoses concerned typical primary care issues. The nurses were able to manage half of the cases independently (327, 55%), referred to the GP in 37% (N=217), and consulted a GP (live, by telephone or a dedicated app) for 8% (48). GPs mostly prescribed drugs, referred to a medical specialist and advised over-the-counter drugs while nurses more often advised over-the-counter drugs (mostly paracetamol, nose sprays and anti-inflammatory drugs), gave non-medical advice or ordered lab tests.DiscussionThe medical care points delivered mostly typical acute primary care in this first phase, with a key role for nurses. These results will inform policy makers on the use of primary care centers for newly arriving patients in times of crisis. A nurse first model seems feasible and efficient, but evaluation of safety and quality of care are needed. Once the acute phase of this crises fades away, questions about the comprehensiveness, continuity, and integration of care for migrants remain relevant.
Goal setting in mental health: a scoping review to inform occupational therapy practice
Authors: Okita Yuho , Kaneko Takao , Imai Hiroaki , Nair Monique , Tomori Kounosuke 
Published: January 2024

Purpose
Goal setting is a crucial aspect of client-centered practice in occupational therapy (OT) for mental health conditions. However, it remains to be seen how goal-setting has been delivered in mental health, particularly the OT process. The purpose of this scoping review was to explore the nature and extent of goal setting delivered in mental health and informed OT practice.

Design/methodology/approach
The authors followed the guidelines of Arksey and O’Malley (2005) and searched three databases using key search terms: “mental disorder,” “goal setting,” and “occupational therapy” and their synonyms.

Findings
After excluding duplicate records, the authors initially screened 883 records and resulted in 20 records in total after the screening process. Most of the identified articles used goal-setting delivered by both a health professional and a client (n = 14), and focused on people with schizophrenia or schizoaffective disorder (n = 13), but three interventions were delivered by occupational therapists. Further research needs on goal-setting in mental health OT, exploring the reliability and validity of different goal-setting strategies and investigating the effectiveness of goal-setting for promoting behavior change and client engagement across various mental health conditions and settings.

Research limitations/implications
The scoping review has some limitations, such as not investigating the validity and reliability of goal-setting strategies identified, and excluding conference papers and non-English articles.

Originality/value
This scoping review presents a mapping of how goal-setting has been delivered in mental health and informed OT practice. The findings suggest limited research in OT and highlight the need for more studies to address the evidence gap in individualized client-centered OT.
Does internal cash flow-external financing sensitivity react to economic policy uncertainty and geopolitical risk? Evidence from Saudi Arabia
Authors: Guizani Moncef 
Published: January 2024

Purpose
This study aims to investigate the influence of economic policy uncertainty (EPU) and geopolitical risk (GPR) on the relationship between internal cash flow and external financing in an emerging market, Saudi Arabia. It also examines the role of asset tangibility and financial crisis in establishing this relationship.

Design/methodology/approach
The sample was taken from non-financial sector companies listed on the Saudi Stock Exchange between 2002 and 2019. The data were analyzed using panel data regression analysis, including ordinary least squares and fixed effects model. The author addresses potential endogeneity through the generalized method of moments.

Findings
This study found that both EPU and GPR reduce the sensitivity of external financing to internal cash flow. This implies that firms depend more on internally generated funds during periods of increased EPU and GPR. Besides, this study found that the influence of EPU and GPR on the sensitivity of external financing to internal cash flow is more (less) negative for more tangible firms (during the financial crisis period). This result implies that Saudi firms boasting a higher level of tangibility are more flexible when it comes to seeking external financing. However, the presence of uncertainty during the crisis period makes the external financing costly, and therefore, firms will be less likely to raise funds from external sources.

Practical implications
This study has important implications for managers, policymakers and regulators. First, the paper findings provide insights for corporate decision-makers in helping them to focus on internal funds to finance their investment during uncertain times. Second, the findings help managers to understand the role of asset tangibility in raising external funding when firms face financial constraints due to uncertainty. Third, this study also helps corporates to focus on internal funds to finance their investment during the crisis period because EPU and GPR increase the cost of external finance. Finally, the results provide guidelines for policymakers and regulators to make appropriate policy measures to increase the easy availability of external finance during periods of increased EPU and GPR.

Originality/value
This paper is the first to shed light on the impact of internal funds on external financing while paying close attention to the role of EPU and GPR.
Polarization and reliability of news sources in Wikipedia
Authors: Yang Puyu , Colavizza Giovanni 
Published: January 2024

PurposeWikipedia's inclusive editorial policy permits unrestricted participation, enabling individuals to contribute and disseminate their expertise while drawing upon a multitude of external sources. News media outlets constitute nearly one-third of all citations within Wikipedia. However, embracing such a radically open approach also poses the challenge of the potential introduction of biased content or viewpoints into Wikipedia. The authors conduct an investigation into the integrity of knowledge within Wikipedia, focusing on the dimensions of source political polarization and trustworthiness. Specifically, the authors delve into the conceivable presence of political polarization within the news media citations on Wikipedia, identify the factors that may influence such polarization within the Wikipedia ecosystem and scrutinize the correlation between political polarization in news media sources and the factual reliability of Wikipedia's content.Design/methodology/approachThe authors conduct a descriptive and regression analysis, relying on Wikipedia Citations, a large-scale open dataset of nearly 30 million citations from English Wikipedia. Additionally, this dataset has been augmented with information obtained from the Media Bias Monitor (MBM) and the Media Bias Fact Check (MBFC).FindingsThe authors find a moderate yet significant liberal bias in the choice of news media sources across Wikipedia. Furthermore, the authors show that this effect persists when accounting for the factual reliability of the news media.Originality/valueThe results contribute to Wikipedia’s knowledge integrity agenda in suggesting that a systematic effort would help to better map potential biases in Wikipedia and find means to strengthen its neutral point of view policy.
Does individuals' age matter? A comparative study of generation X and generation Y on green housing purchase intention
Authors: Kumar Jitender , Rani Vinki , Rani Garima , Rani Manju 
Published: January 2024

PurposeThis comparative research examines the factors influencing individuals' purchase intention toward green housing. By examining these factors, this study provides fruitful insights into the purchase intentions and behaviors for greenhouses among individuals of different age groups in India.Design/methodology/approachData were gathered from Generation (Gen) X (313) and Generation (Gen) Y (297) using self-administered questionnaires. The “partial least squares structural equation modeling” was used to test the hypotheses.FindingsThe outcome shows that attitude and green trust substantially impact the green purchase intention of Gen X and Y. More specifically, environmental knowledge insignificantly influences the green purchase intention of Gen X while significantly influencing Gen Y. However, perceived risk insignificantly affects the purchase intention of both Gen X and Y. Consequently, green purchase intention substantially impacts the green purchase behavior in both studies.Research limitations/implicationsThis research focuses primarily on India; future research may be conducted in different geographical contexts. This study could also be extended to all age groups individuals.Practical implicationsThe findings of this article facilitate policymakers, real estate developers and professional bodies in formulating strategies for sustainable nations in the future.Originality/valueThe current article is the initial empirical attempt to examine the home-buying decisions of individuals in India. Moreover, the role of Generation X and Generation Y in green housing purchase decisions will provide fruitful insights into how different age groups impact the decision-making process of green housing.
Virtual influencer marketing: a study of millennials and gen Z consumer behaviour
Authors: Angmo Padma , Mahajan Rachna 
Published: January 2024

Purpose
Virtual influencers (VIs), who are fictional characters, have gained popularity in recent years, particularly among Generation Z and millennials. With the hype surrounding VIs, more research is required. Thus, this study aims to examine how Gen Z members and millennials react to VIs used for marketing purposes.

Design/methodology/approach
This study follows an exploratory approach. The data were collected from 29 participants (14 male and 15 female) through two focus groups and semi-structured interviews.

Findings
The authors found that opinions about VIs were mixed, and two main themes emerged from the study: (1) challenges and potential and (2) decision-making and psychological aspects.

Originality/value
This study broadens the paradigm for analysing the efficacy of VIs. This emerging topic is of relevance for the marketing sector as well as for transdisciplinary research and practice.
Modelling animal social networks: New solutions and future directions
Authors: Farine Damien R. 
Published: January 2024

AbstractResearch Highlight: Ross, C. T., McElreath, R., & Redhead, D. (2023). Modelling animal network data in R using STRAND. Journal of Animal Ecology. https://doi.org/10.1111/1365‐2656.14021. One of the most important insights in ecology over the past decade has been that the social connections among animals affect a wide range of ecological and evolutionary processes. However, despite over 20 years of study effort on this topic, generating knowledge from data on social associations and interactions remains fraught with problems. Redhead et al. present an R package—STRAND—that extends the current animal social network analysis toolbox in two ways. First, they provide a simple R interfaces to implement generative network models, which are an alternative to regression approaches that draw inference by simulating the data‐generating process. Second, they implement these models in a Bayesian framework, allowing uncertainty in the observation process to be carried through to hypothesis testing. STRAND therefore fills an important gap for hypothesis testing using network data. However, major challenges remain, and while STRAND represents an important advance, generating robust results continues to require careful study design, considerations in terms of statistical methods and a plurality of approaches.
Life history scaling in a tropical forest
Authors: Grady John M. , Read Quentin D. , Record Sydne , Rüger Nadja , Zarnetske Phoebe L. , Dell Anthony I. , Hubbell Stephen P. , Michaletz Sean T. , Enquist Brian J. 
Published: January 2024

Abstract

Both tree size and life history variation drive forest structure and dynamics, but little is known about how life history frequency changes with size. We used a scaling framework to quantify ontogenetic size variation and assessed patterns of abundance, richness, productivity and light interception across life history strategies from >114,000 trees in a primary, neotropical forest. We classified trees along two life history axes: a fast–slow axis characterized by a growth–survival trade‐off, and a stature–recruitment axis with tall, long‐lived pioneers at one end and short, short‐lived recruiters at the other.

Relative abundance, richness, productivity and light interception follow an approximate power law, systematically shifting over an order of magnitude with tree size. Slow saplings dominate the understorey, but slow trees decline to parity with rapidly growing fast and long‐lived pioneer species in the canopy.

Like the community as a whole, slow species are the closest to obeying the energy equivalence rule (EER)—with equal productivity per size class—but other life histories strongly increase productivity with tree size. Productivity is fuelled by resources, and the scaling of light interception corresponds to the scaling of productivity across life history strategies, with slow and all species near solar energy equivalence. This points towards a resource‐use corollary to the EER: the resource equivalence rule.

Fitness trade‐offs associated with tree size and life history may promote coexistence in tropical forests by limiting niche overlap and reducing fitness differences.

Synthesis. Tree life history strategies describe the different ways trees grow, survive and recruit in the understorey. We show that the proportion of trees with a pioneer life history strategy increases steadily with tree size, as pioneers become relatively more abundant, productive, diverse and capture more resources towards the canopy. Fitness trade‐offs associated with size and life history strategy offer a mechanism for coexistence in tropical forests.
Maternal chronic hypertension in women veterans
Authors: Harding Ceshae C. , Goldstein Karen M. , Goldstein Sarah A. , Wheeler Sarahn M. , Mitchell Nia S. , Copeland Laurel A. 
Published: January 2024

AbstractObjectiveTo describe the prevalence of maternal chronic hypertension (MCH), assess how frequently blood pressure is controlled before pregnancy among those with MCH, and explore management practices for antihypertensive medications (AHM) during the pre‐pregnancy and pregnancy periods.Data Sources, Study Setting, and Study DesignWe conducted a descriptive observational study using data abstracted from the Veterans Health Administration (VA) inclusive of approximately 11 million Veterans utilizing the VA in fiscal years 2010–2019.Data Collection/Extraction MethodsVeterans aged 18–50 were included if they had a diagnosis of chronic hypertension before a documented pregnancy in the VA EMR. We identified chronic hypertension and pregnancy with diagnosis codes and defined uncontrolled blood pressure as ≥140/90 mm Hg on at least one measurement in the year before pregnancy. Sensitivity models were conducted for individuals with at least two blood pressure measurements in the year prior to pregnancy. Multivariable logistic regression explored the association of covariates with recommended and non‐recommended AHMs received 0–6 months before pregnancy and during pregnancy.Principal FindingsIn total, 8% (3767/46,178) of Veterans with a documented pregnancy in VA data had MCH. Among 2750 with MCH meeting inclusion criteria, 60% (n = 1626) had uncontrolled blood pressure on at least one BP reading and 31% (n = 846) had uncontrolled blood pressure on at least two BP readings in the year before pregnancy. For medications, 16% (n = 437) received a non‐recommended AHM during pregnancy. Chronic kidney disease (OR = 3.2; 1.6–6.4) and diabetes (OR = 2.3; 1.7–3.0) were most strongly associated with use of a non‐recommended AHM during pregnancy.ConclusionsInterventions are needed to decrease the prevalence of MCH, improve preconception blood pressure control, and ensure optimal pharmacologic antihypertensive management among Veterans of childbearing potential.
Optical nanosensors based on noble metal nanoclusters for detecting food contaminants: A review
Authors: Pang Lidong , Pi Xiaowen , Zhao Qianyu , Man Chaoxin , Yang Xinyan , Jiang Yujun 
Published: January 2024

AbstractFood contaminants present a significant threat to public health. In response to escalating global concerns regarding food safety, there is a growing demand for straightforward, rapid, and sensitive detection technologies. Noble metal nanoclusters (NMNCs) have garnered considerable attention due to their superior attributes compared to other optical materials. These attributes include high catalytic activity, excellent biocompatibility, and outstanding photoluminescence properties. These features render NMNCs promising candidates for crafting nanosensors for food contaminant detection, offering the potential for the development of uncomplicated, swift, sensitive, user‐friendly, and cost‐effective detection approaches. This review investigates optical nanosensors based on NMNCs, including the synthesis methodologies of NMNCs, sensing strategies, and their applications in detecting food contaminants. Furthermore, it involves a comparative assessment of the applications of NMNCs in optical sensing and their performance. Ultimately, this paper imparts fresh perspectives on the forthcoming challenges. Hitherto, optical (particularly fluorescent) nanosensors founded on NMNCs have demonstrated exceptional sensing capabilities in the realm of food contaminant detection. To enhance sensing performance, future research should prioritize atomically precise NMNCs synthesis, augmentation of catalytic activity and optical properties, development of high‐throughput and multimode sensing, integration of NMNCs with microfluidic devices, and the optimization of NMNCs storage, shelf life, and transportation conditions.