bluuebunny/crossref_metadata_2025_split huggingface dataset:
Co‐creating digital educational resources to enhance quality in student nurses' clinical education in nursing homes: Report of a co‐creative process
Authors: Laugaland Kristin A. , Akerjordet Kristin , Frøiland Christina T. , Aase Ingunn 
Published: July 2023

AbstractAimTo report a methodological, co‐creative approach for developing an interactive digital educational resource to enhance the quality of student nurses' clinical education in nursing homes and to elucidate the lessons learned from this approach.DesignThis study applied a co‐design methodology that builds on participatory design principles.MethodsCo‐creating the digital educational resource included multiple sequential and interactive phases inspired by the design thinking framework. Workshops were employed as the primary co‐creative activity.ResultsSeven separate homogenous or joint heterogeneous workshops were conducted with student nurses, nurse educators, registered nurse mentors and e‐learning designers (n = 36) during the active stakeholder engagement phases to inform the educational content, design and functionality of the digital educational resource. These were informed by, and grounded in, learning theory and principles.ConclusionCo‐creative approaches in nursing education are an essential avenue for further research. We still lack systematic knowledge about the impact and benefits of co‐created initiatives, stakeholders' motivations, barriers, facilitators to participation and the role of context in supporting effective co‐creative processes to increase the quality of nursing education.ImpactThis paper demonstrates how digital educational initiatives to enhance quality in clinical nursing education can be co‐created with key stakeholders through a novel methodological approach inspired by design thinking. To date, the methodological development process of co‐created educational interventions has received limited attention and compared with the content and theoretical underpinnings of such interventions, has rarely been addressed. Therefore, this paper facilitates knowledge exchange and documents vital aspects to consider when co‐creating digital educational initiatives incorporating multistakeholder perspectives. This promotes a stronger academic–practice partnership to impact and enhance the quality of clinical nursing education in nursing homes.Public ContributionsStudent nurses, nurse educators, and registered nurse mentors worked alongside researchers and e‐learning designers in the co‐creative process.
‘We only come from one perspective’: Exploring experiences of allies supporting expert by experience leadership in mental health education
Authors: Happell Brenda , Gordon Sarah , Sharrock Julie , O Donovan Aine , Warner Terri 
Published: July 2023

AbstractIntroductionAcademics from health professional backgrounds have a crucial role in supporting the implementation and sustainability of academic positions for experts by experience in mental health education. Perspectives and experiences of these academics have yet to be extensively explored. A deeper understanding will add to our understanding of this important role and provide guidance for academics with similar aspirations.AimThe aim of the study was to explore the experiences of supporting academic positions for experts by experience in mental health education.MethodsA qualitative exploratory design was utilised. In‐depth interviews were conducted with academics who have actively supported academic positions for experts by experience.ResultsAllyship was a key theme identified. Participants described allyship as complex, time‐consuming and rewarding, through three sub‐themes: the tension of allyship, the impact of being an ally and interpersonal and relational issues with health professional academics.ConclusionsAllyship was influenced by the negative attitudes of many health professional academics, who do not appreciate the value of this work.Implications for PracticeAllyship has a crucial role in enhancing experts by experience leadership in the education of health professionals. Understanding the experience of allyship will assist in further understanding and developing these important roles.
Radiofrequency ablation of the occipital nerves for treatment of neuralgias and headache
Authors: Abd‐Elsayed Alaa , Yapo Sarah A. , Cao Nancy Nguyen , Keith Mitchell Kenneth , Fiala Kenneth James 
Published: July 2023

AbstractObjectiveThe purpose of this study was to retrospectively assess the efficacy of radiofrequency ablation (RFA) therapy as a treatment for occipital neuralgias and headaches at health clinics in the United States between January 1, 2015 and June 20, 2022. We hypothesize that RFA is a minimally invasive treatment that provides significant pain relief long‐term for occipital neuralgias and associated headaches.MethodsThis retrospective analysis studies data collected from 277 occipital nerve RFA patients who had adequate pre‐procedure and post‐procedure follow‐up for data analysis. Data collected includes the patient's age, biological sex, BMI, headache diagnosis, pre‐procedure, and post‐procedure pain score using the visual analog scale (VAS), subjective percent improvement in symptom(s), and duration of symptom relief. Statistical analysis used SPSS software, version 26 (IBM), using a paired t‐test to assess the significance between pre and post‐occipital RFA therapy pain scores. p‐values were significant if found to be ≤0.05.ResultsThe mean pre‐procedure pain score before RFA therapy for patients who completed at least 6 months of follow‐up was 5.57 (SD = 1.87) and the mean post‐procedure pain score after RFA therapy was 2.39 (SD = 2.42). The improvement in pain scores between pre‐procedure and post‐procedure was statistically significant with a p‐value < 0.001. The mean patient‐reported percent improvement in pain following RFA therapy was 63.53% (SD = 36.37). The mean duration of pain improvement was 253.9 days after the initiation of therapy (SD = 300.5). When excluding patients who did not have any relief following their RFA procedure, the average pre‐procedure pain score was 5.54 (SD = 1.81) and post‐procedure pain score was 1.71 (SD = 1.81) with a p‐value < 0.001.ConclusionThis study demonstrates the minimally invasive, safe, and effective treatment of RFA in patients with refractory occipital neuralgias and headaches. Additional studies are necessary to illuminate ideal patient characteristics for RFA treatment and the potential for procedural complications and long‐term side effects associated with occipital nerve RFA therapy.
A new typology for comparing scientific advisory committees. Evidence from the Italian response to the COVID‐19 pandemic
Authors: Capano Giliberto , Casula Mattia , Malandrino Anna , Terlizzi Andrea , Toth Federico 
Published: July 2023

AbstractThe study of scientific advisory committees (SACs) is a recurrent topic of research in public policy and public administration. Scholars are increasingly interested in analyzing the scientization of policy advice as well as the role played by knowledge‐based policymaking processes. Despite recent developments in the field, SACs studies continue to face an analytical and empirical gap due to the lack of parsimonious conceptualizations of the characteristics that enable them to be both theoretically relevant and effective in driving comparative analysis. To fill this research gap, this article proposes a novel typology of SACs based on a specific conceptualization of the motivations of policymakers that allows the selection of two classificatory criteria: the origin of the members and the degree to which their expertise is homogeneous. The theoretical relevance of this typology is illustrated by applying it to the SACs established in the Italian regions to address the COVID‐19 pandemic. The article highlights the relevance of the typology to the theory underlying the empirical analysis. In doing so, it provides relevant insights into the composition and nature of SACs that is useful not only for the academic debate on evidence‐based policymaking but also for both practitioners and decision‐makers.
Prediction of Laminar Burning Speed of Propane/Hydrogen/Air Mixtures Using Power-Law Correlation and Two Machine Learning Models
Authors: Lu Zhenyu , Metghalchi Hameed 
Published: July 2023

Abstract
Propane (C3H8) and hydrogen (H2) are regarded as alternative fuels that are favorable to the environment. Hydrogen gas's low energy density, storage, and transportation are the main issues with using it as an alternative fuel. Addition of hydrogen gas in the combustion of propane will also improve flame stability, broaden lean flammability limits, and reduces pollutant emissions. Thus, utilizing propane and hydrogen mixtures as fuel is a good choice. Laminar burning speed is a fundamental property of a combustible mixture and can be used to provide information regarding the mixture’s reactivity, exothermicity, and diffusivity. In this study, power-law correlation and machine learning methods were used to create models that predict the laminar burning speed of propane/hydrogen/air mixtures at various states. Two machine learning models are artificial neural network (ANN) and support vector machine (SVM). The data were generated by using CANTRA code and a chemical kinetic mechanism. For a wide variety of input values, the models were able to determine the laminar burning speed with great accuracy. The ANN model yields the best performance. The main advantage of these models is the noticeably faster computing time when compared to chemical reaction mechanisms.
Opportunities and Challenges of Quantum Computing for Engineering Optimization
Authors: Wang Yan , Kim Jungin E. , Suresh Krishnan 
Published: July 2023

Abstract
Quantum computing as the emerging paradigm for scientific computing has attracted significant research attention in the past decade. Quantum algorithms to solve the problems of linear systems, eigenvalue, optimization, machine learning, and others have been developed. The main advantage of utilizing quantum computer to solve optimization problems is that quantum superposition allows for massive parallel searching of solutions. This article provides an overview of fundamental quantum algorithms that can be utilized in solving optimization problems, including Grover search, quantum phase estimation, quantum annealing, quantum approximate optimization algorithm, variational quantum eigensolver, and quantum walk. A review of recent applications of quantum optimization methods for engineering design, including materials design and topology optimization, is also given. The challenges to develop scalable and reliable quantum algorithms for engineering optimization are discussed.
Generative Design by Embedding Topology Optimization into Conditional Generative Adversarial Network
Authors: Wang Zhichao , Melkote Shreyes , Rosen David W. 
Published: July 2023

Abstract
Generative design (GD) techniques have been proposed to generate numerous designs at early design stages for ideation and exploration purposes. Previous research on GD using deep neural networks required tedious iterations between the neural network and design optimization, as well as post-processing to generate functional designs. Additionally, design constraints such as volume fraction could not be enforced. In this paper, a two-stage non-iterative formulation is proposed to overcome these limitations. In the first stage, a conditional generative adversarial network (cGAN) is utilized to control design parameters. In the second stage, topology optimization (TO) is embedded into cGAN (cGAN + TO) to ensure that desired functionality is achieved. Tests on different combinations of loss terms and different parameter settings within topology optimization demonstrated the diversity of generated designs. Further study showed that cGAN + TO can be extended to different load and boundary conditions by modifying these parameters in the second stage of training without having to retrain the first stage. Results demonstrate that GD can be realized efficiently and robustly by cGAN+TO.
An Examination of the Challenge/Threat State and Sport-Performance Relationship While Controlling for Past Performance
Authors: Jewiss Matthew , Runswick Oliver R. , Greenlees Iain 
Published: July 2023

A challenge state is associated with superior performance compared to a threat state in a variety of performance domains (e.g., sport, aviation, education). However, in the challenge and threat (C/T) literature, between-subjects variability in past performance is often inconsistently controlled for. Here, we aimed to investigate the effects of C/T states on performance using two methods to control for past performance. Experiment 1 used previous performance statistics in a between-subjects design and Experiment 2 used a within-subject design. In Experiment 1, regression analysis showed that cardiovascular correlates of C/T states predicted cricket batting performance in 45 amateur cricketers. In Experiment 2, between- and within-subject analysis found that past performance was the only predictor of subsequent golf putting performance in 40 noncompetitive golfers. Taken together, the findings challenge the role that C/T states play in predicting performance under pressure after controlling for past performance.
Characterization of a novel aromatic substrate-processing microcompartment in Actinobacteria
Authors: Doron Lior , Sutter Markus , Kerfeld Cheryl A. 
Published: July 2023

ABSTRACT

We have discovered a new cluster of genes that is found exclusively in the Actinobacteria phylum. This locus includes genes for the 2-aminophenol
meta
-cleavage pathway and the shell proteins of a bacterial microcompartment (BMC) and has been named aromatics (ARO) for its putative role in the breakdown of aromatic compounds. In this study, we provide details about the distribution and composition of the ARO BMC locus and conduct phylogenetic, structural, and functional analyses of the first two enzymes in the catabolic pathway: a unique 2-aminophenol dioxygenase, which is exclusively found alongside BMC shell genes in Actinobacteria, and a semialdehyde dehydrogenase, which works downstream of the dioxygenase. Genomic analysis reveals variations in the complexity of the ARO loci across different orders. Some loci are simple, containing shell proteins and enzymes for the initial steps of the catabolic pathway, while others are extensive, encompassing all the necessary genes for the complete breakdown of 2-aminophenol into pyruvate and acetyl-CoA. Furthermore, our analysis uncovers two subtypes of ARO BMC that likely degrade either 2-aminophenol or catechol, depending on the presence of a pathway-specific gene within the ARO locus. The precise precursor of 2-aminophenol, which serves as the initial substrate and/or inducer for the ARO pathway, remains unknown, as our model organism
Micromonospora rosaria
cannot utilize 2-aminophenol as its sole energy source. However, using enzymatic assays, we demonstrate the dioxygenase’s ability to cleave both 2-aminophenol and catechol
in vitro
, in collaboration with the aldehyde dehydrogenase, to facilitate the rapid conversion of these unstable and toxic intermediates.

IMPORTANCE

Bacterial microcompartments (BMCs) are proteinaceous organelles that are widespread among bacteria and provide a competitive advantage in specific environmental niches. Studies have shown that the genetic information necessary to form functional BMCs is encoded in loci that contain genes encoding shell proteins and the enzymatic core. This allows the bioinformatic discovery of BMCs with novel functions and expands our understanding of the metabolic diversity of BMCs. ARO loci, found only in Actinobacteria, contain genes encoding for phylogenetically remote shell proteins and homologs of the
meta
-cleavage degradation pathway enzymes that were shown to convert central aromatic intermediates into pyruvate and acetyl-CoA in gamma Proteobacteria. By analyzing the gene composition of ARO BMC loci and characterizing two core enzymes phylogenetically, structurally, and functionally, we provide an initial functional characterization of the ARO BMC, the most unusual BMC identified to date, distinctive among the repertoire of studied BMCs.
Bacterial TANGO2 homologs are heme-trafficking proteins that facilitate biosynthesis of cytochromes
c
Authors: Han Sirui , Guo Kailun , Wang Wei , Tao Yizhi J. , Gao Haichun 
Published: July 2023

ABSTRACT

Heme, an essential molecule for virtually all living organisms, acts primarily as a cofactor in a large number of proteins. However, how heme is mobilized from the site of synthesis to the locations where hemoproteins are assembled remains largely unknown in cells, especially bacterial ones. In this study, with
Shewanella oneidensis
as the model, we identified HtpA (SO0126) as a heme-trafficking protein and homolog of TANGO2 proteins found in eukaryotes. We showed that HtpA homologs are widely distributed in all domains of living organisms and have undergone parallel evolution. In its absence, the cytochrome (cyt)
c
content and catalase activity decreased significantly. We further showed that both HtpA and representative TANGO2 proteins bind heme with 1:1 stoichiometry and a relatively low dissociation constant. Protein interaction analyses substantiated that HtpA directly interacts with the cytochrome
c
maturation system. Our findings shed light on cross-membrane transport of heme in bacteria and extend the understanding of TANGO2 proteins.

IMPORTANCE

The intracellular trafficking of heme, an essential cofactor for hemoproteins, remains underexplored even in eukaryotes, let alone bacteria. Here we developed a high-throughput method by which HtpA, a homolog of eukaryotic TANGO2 proteins, was identified to be a heme-binding protein that enhances cytochrome
c
biosynthesis and catalase activity in
Shewanella oneidensis
. HtpA interacts with the cytochrome
c
biosynthesis system directly, supporting that this protein, like TANGO2, functions in intracellular heme trafficking. HtpA homologs are widely distributed, but a large majority of them were found to be non-exchangeable, likely a result of parallel evolution. By substantiating the heme-trafficking nature of HtpA and its eukaryotic homologs, our findings provide general insight into the heme-trafficking process and highlight the functional conservation along evolution in all living organisms.
Distributional impact of infectious disease interventions in the Ethiopian Essential Health Service Package: a modelling study
Authors: Assebe Lelisa Fekadu , Norheim Ole 
Published: July 2023

ObjectivesReducing inequalities in health and financial risk are key goals on the path toward universal health coverage, particularly in low-income and middle-income countries. The design of the health benefit package creates an opportunity to select interventions through established criteria. The aim of this study is to examine the health equity and financial protection impact of selected interventions, along with their costs, at the national level in Ethiopia.DesignDistributional cost-effectiveness analysis.PopulationThe eligible population for all selected interventions is assumed to be 10 million.Data sourcesData on disease prevalence and population size were gathered from the Global Burden of Disease database, and average health benefits and program costs are sourced from the Ethiopian Essential Health Service Package (EHSP) database, national surveys and other publicly available sources.InterventionA total of 30 interventions were selected from the latest EHSP revision and analysed over a 1-year period.Outcome measuresHealth benefits, social welfare indices and financial protection metrics across income quintiles were reported.ResultsWe found 23 interventions that improve population health and reduce health inequality and four interventions reduce both population health and health inequality. Additionally, three interventions improve population health while increasing health inequality. Overall, the EHSP interventions provide a 0.021 improvement in health-adjusted life expectancy (HALE) per person, with a positive distributional equity impact: 0.029 (26.9%) HALE gained in the poorest and 0.015 (14.0%) in the richest quintile. Similarly, a total of 1 79 475 cases of catastrophic health expenditure were averted, including 82 100 (46.0%) cases in the poorest and 17 900 (10.0%) in the richest quintile.ConclusionIncreasing access to the EHSP improves health equity and financial protection. Improved access to selected EHSP interventions also has the potential to provide greater benefits to the poorest and thereby improve social welfare.
A Survey of Malware Analysis Using Community Detection Algorithms
Authors: Amira Abdelouahab , Derhab Abdelouahid , Karbab Elmouatez Billah , Nouali Omar 
Published: July 2023

In recent years, we have witnessed an overwhelming and fast proliferation of different types of malware targeting organizations and individuals, which considerably increased the time required to detect malware. The malware developers make this issue worse by spreading many variants of the same malware [
13
]. To deal with this issue, graph theory techniques, and particularly community detection algorithms, can be leveraged to achieve bulk detection of malware families and variants to identify malicious communities instead of focusing on the detection of an individual instance of malware, which could significantly reduce the detection time. In this article, we review the state-of-the-art malware analysis solutions that employ community detection algorithms and provide a taxonomy that classifies the solutions with respect to five facets: analysis task, community detection approach, target platform, analysis type, and source of features. We present the solutions with respect to the analysis task, which covers malware detection, malware classification, cyber-threat infrastructure detection, and feature selection. The findings of this survey indicate that there is still room for contributions to further improve the state of the art and address research gaps. Finally, we discuss the advantages and the limitations of the solutions, identify open issues, and provide future research directions.
Progress in the Understanding of Estrogen Receptor Alpha Signaling in Triple-Negative Breast Cancer: Reactivation of Silenced ER-α and Signaling through ER-α36
Authors: Al-Kabariti Aya Y. , Abbas Manal A. 
Published: July 2023

Abstract
Triple-negative breast cancer (TNBC) is an aggressive tumor that accounts for approximately 15% of total breast cancer cases. It is characterized by poor prognosis and high rate of recurrence compared to other types of breast cancer. TNBC has a limited range of treatment options that include chemotherapy, surgery, and radiation due to the absence of estrogen receptor alpha (ER-α) rendering hormonal therapy ineffective. However, possible targets for improving the clinical outcomes in TNBC exist, such as targeting estrogen signaling through membranous ER-α36 and reactivating silenced ER-α. It has been shown that epigenetic drugs such as DNA methyltransferase and histone deacetylase inhibitors can restore the expression of ER-α. This reactivation of ER-α, presents a potential strategy to re-sensitize TNBC to hormonal therapy. Also, this review provides up-to-date information related to the direct involvement of miRNA in regulating the translation of ER-α mRNA. Specific epi-miRNAs can regulate ER-α expression indirectly by post-transcriptional targeting of mRNAs of enzymes that are involved in DNA methylation and histone deacetylation. Furthermore, ER-α36, an alternative splice variant of ER-α66, is highly expressed in ER-negative breast tumors and activates MAPK/ERK pathway, promoting cell proliferation, escaping apoptosis, and enhancing metastasis. In the future, these recent advances may be helpful for researchers working in the field to obtain novel treatment options for TNBC, utilizing epigenetic drugs and epi-miRNAs that regulate ER-α expression. Also, there is some evidence to suggest that drugs that decrease the expression of ER-α36 may be effective in treating TNBC.