bluuebunny/crossref_metadata_2025_split huggingface dataset:
Embedded-Error Bayesian Calibration of Thermal Decomposition of Organic Materials
Authors: Frankel Ari , Wagman Ellen , Keedy Ryan , Houchens Brent , Scott Sarah N. 
Published: June 2021

Abstract
Organic materials are an attractive choice for structural components due to their light weight and versatility. However, because they decompose at low temperatures relative to traditional materials, they pose a safety risk due to fire and loss of structural integrity. To quantify this risk, analysts use chemical kinetics models to describe the material pyrolysis and oxidation using thermogravimetric analysis (TGA). This process requires the calibration of many model parameters to closely match experimental data. Previous efforts in this field have largely been limited to finding a single best-fit set of parameters even though the experimental data may be very noisy. Furthermore, the chemical kinetics models are often simplified representations of the true decomposition process. The simplification induces model-form errors that the fitting process cannot capture. In this work, we propose a methodology for calibrating decomposition models to TGA data that accounts for uncertainty in the model-form and experimental data simultaneously. The methodology is applied to the decomposition of a carbon fiber epoxy composite with a three-stage reaction network and Arrhenius kinetics. The results show a good overlap between the model predictions and TGA data. Uncertainty bounds capture deviations of the model from the data. The calibrated parameter distributions are also presented. The distributions may be used in forward propagation of uncertainty in models that leverage this material.
Using Principal Component Analysis to Compare the Physical Qualities Between Academy and International Youth Rugby League Players
Authors: McCormack Sam , Jones Ben , Scantlebury Sean , Collins Neil , Owen Cameron , Till Kevin 
Published: June 2021

Purpose:To compare the physical qualities between academy and international youth rugby league (RL) players using principal component analysis.Methods:Six hundred fifty-four males (age = 16.7 [1.4] y; height = 178.4 [13.3] cm; body mass = 82.2 [14.5] kg) from 11 English RL academies participated in this study. Participants completed anthropometric, power (countermovement jump), strength (isometric midthigh pull; IMTP), speed (10 and 40 m speed), and aerobic endurance (prone Yo-Yo IR1) assessments. Principal component analysis was conducted on all physical quality measures. A 1-way analysis of variance with effect sizes was performed on 2 principal components (PCs) to identify differences between academy and international backs, forwards, and pivots at under 16 and 18 age groups.Results: Physical quality measures were reduced to 2 PCs explaining 69.4% of variance. The first PC (35.3%) was influenced by maximum and 10-m momentum, absolute IMTP, and body mass. Ten and forty-meter speed, body mass and fat, prone Yo-Yo, IMTP relative, maximum speed, and countermovement jump contributed to PC2 (34.1%). Significant differences (P < .05, effect size = −1.83) were identified between U18 academy and international backs within PC1.Conclusion:Running momentum, absolute IMTP, and body mass contributed to PC1, while numerous qualities influenced PC2. The physical qualities of academy and international youth RL players are similar, excluding U18 backs. Principal component analysis can reduce the dimensionality of a data set and help identify overall differences between playing levels. Findings suggest that RL practitioners should measure multiple physical qualities when assessing physical performance.
Converting Raw Accelerometer Data to Activity Counts Using Open-Source Code: Implementing a MATLAB Code in Python and R, and Comparing the Results to ActiLife
Authors: Brondeel Ruben , Kestens Yan , Rahimipour Anaraki Javad , Stanley Kevin , Thierry Benoit , Fuller Daniel 
Published: June 2021

Background: Closed-source software for processing and analyzing accelerometer data provides little to no information about the algorithms used to transform acceleration data into physical activity indicators. Recently, an algorithm was developed in MATLAB that replicates the frequently used proprietary ActiLife activity counts. The aim of this software profile was (a) to translate the MATLAB algorithm into R and Python and (b) to test the accuracy of the algorithm on free-living data. Methods: As part of the INTErventions, Research, and Action in Cities Team, data were collected from 86 participants in Victoria (Canada). The participants were asked to wear an integrated global positioning system and accelerometer sensor (SenseDoc) for 10 days on the right hip. Raw accelerometer data were processed in ActiLife, MATLAB, R, and Python and compared using Pearson correlation, interclass correlation, and visual inspection. Results: Data were collected for a combined 749 valid days (>10 hr wear time). MATLAB, Python, and R counts per minute on the vertical axis had Pearson correlations with the ActiLife counts per minute of .998, .998, and .999, respectively. All three algorithms overestimated ActiLife counts per minute, some by up to 2.8%. Conclusions: A MATLAB algorithm for deriving ActiLife counts was implemented in R and Python. The different implementations provide similar results to ActiLife counts produced in the closed source software and can, for all practical purposes, be used interchangeably. This opens up possibilities to comparing studies using similar accelerometers from different suppliers, and to using free, open-source software.
Diagnostic accuracy of swept source optical coherence tomography classification algorithms for detection of gonioscopic angle closure
Authors: Tan Shayne S , Tun Tin A , Sultana Rehena , Tan Marcus , Quah Joanne HuiMin , Mani Baskaran , Allen John C , Cheng Ching Yu , Nongpiur Monisha Esther , Aung Tin 
Published: June 2021

PurposeTo evaluate the performance of swept source optical coherence tomography (SS-OCT) to detect gonioscopic angle closure using different classification algorithms.MethodsThis was a cross-sectional study of 2028 subjects without ophthalmic symptoms recruited from a community-based clinic. All subjects underwent gonioscopy and SS-OCT (Casia, Tomey Corporation, Nagoya, Japan) under dark room conditions. For each eye, 8 out of 128 frames (22.5° interval) were selected to measure anterior chamber parameters namely anterior chamber width, depth, area and volume (ACW, ACD, ACA, and ACV), lens vault (LV), iris curvature (IC), iris thickness (IT) from 750 µm and 2000 µm from the scleral spur, iris area and iris volume. Five diagnostic algorithms—stepwise logistic regression, random forest, multivariate adaptive regression splines, recursive partitioning and Naïve Bayes were evaluated for detection of gonioscopic angle closure (defined as ≥2 closed quadrants). The performance of the horizontal frame was compared with that of other meridians.ResultsData from 1988 subjects, including 143 (7.2%) with gonioscopic angle closure, were available for analysis. They were divided into two groups: training (1391, 70%) and validation (597, 30%). The best algorithm for detecting gonioscopic angle closure was stepwise logistic regression with an area under the curve of 0.91 (95% CI 0.88 to 0.93) using all parameters, and 0.88 (95% CI 0.82 to 0.93) using only ACA, LV and IC of the horizontal meridian scan.ConclusionsA stepwise logistic regression model incorporating SS-OCT measurements has a high diagnostic ability to detect gonioscopic angle closure.
Sleep and physical activity in relation to all-cause, cardiovascular disease and cancer mortality risk
Authors: Huang Bo-Huei , Duncan Mitch J , Cistulli Peter A , Nassar Natasha , Hamer Mark , Stamatakis Emmanuel 
Published: June 2021

ObjectivesAlthough both physical inactivity and poor sleep are deleteriously associated with mortality, the joint effects of these two behaviours remain unknown. This study aimed to investigate the joint association of physical activity (PA) and sleep with all-cause and cause-specific mortality risks.Methods380 055 participants aged 55.9 (8.1) years (55% women) from the UK Biobank were included. Baseline PA levels were categorised as high, medium, low and no moderate-to-vigorous PA (MVPA) based on current public health guidelines. We categorised sleep into healthy, intermediate and poor with an established composited sleep score of chronotype, sleep duration, insomnia, snoring and daytime sleepiness. We derived 12 PA–sleep combinations, accordingly. Mortality risks were ascertained to May 2020 for all-cause, total cardiovascular disease (CVD), CVD subtypes (coronary heart disease, haemorrhagic stroke, ischaemic stroke), as well as total cancer and lung cancer.ResultsAfter an average follow-up of 11.1 years, sleep scores showed dose-response associations with all-cause, total CVD and ischaemic stroke mortality. Compared with high PA-healthy sleep group (reference), the no MVPA-poor sleep group had the highest mortality risks for all-cause (HR (95% CIs), (1.57 (1.35 to 1.82)), total CVD (1.67 (1.27 to 2.19)), total cancer (1.45 (1.18 to 1.77)) and lung cancer (1.91 (1.30 to 2.81))). The deleterious associations of poor sleep with all outcomes, except for stroke, was amplified with lower PA.ConclusionThe detrimental associations of poor sleep with all-cause and cause-specific mortality risks are exacerbated by low PA, suggesting likely synergistic effects. Our study supports the need to target both behaviours in research and clinical practice.
Combined changes in albuminuria and kidney function and subsequent risk for kidney failure in type 2 diabetes
Authors: Oshima Megumi , Toyama Tadashi , Hara Akinori , Shimizu Miho , Kitajima Shinji , Iwata Yasunori , Sakai Norihiko , Furuichi Kengo , Haneda Masakazu , Babazono Tetsuya , Yokoyama Hiroki , Iseki Kunitoshi , Araki Shin-ichi , Ninomiya Toshiharu , Hara Shigeko , Suzuki Yoshiki , Iwano Masayuki , Kusano Eiji , Moriya Tatsumi , Satoh Hiroaki , Nakamura Hiroyuki , Makino Hirofumi , Wada Takashi 
Published: June 2021

IntroductionChanges in albuminuria or estimated glomerular filtration rate (eGFR) can be used as a surrogate endpoint of end-stage kidney disease (ESKD) in people with type 2 diabetes. We investigated whether the combined changes in albuminuria and eGFR are more strongly associated with future risk of ESKD.Research design and methodsUsing data from a multicenter observational cohort study of people with type 2 diabetes, we evaluated the association of percentage change in urine albumin to creatinine ratio (UACR) and/or annual change in eGFR over 2 years with subsequent ESKD risk.ResultsAmong 1417 patients with repeated albuminuria and eGFR over 2 years, 129 (9.1%) developed ESKD. Patients with >30% UACR decline had lower ESKD risk (HR 0.47; 95% CI 0.29 to 0.77), whereas those with >30% UACR increase had higher ESKD risk (HR 2.31; 95% CI 1.52 to 3.51), compared with those with minor UACR change. Patients with greater eGFR decline had an increased ESKD risk than those with minor eGFR change (a decline of <2.5 mL/min/1.73 m2/year): HR 4.19 (95% CI 1.87 to 9.38) and 2.89 (95% CI 1.32 to 6.33) for those with a decline of >5 and 2.5–5 mL/min/1.73 m2/year, respectively. When the combined changes in UACR and eGFR were used, the highest ESKD risk (HR 5.60; 95% CI 2.08 to 15.09) was observed among patients with >30% UACR increase and an eGFR decline of >5 mL/min/1.73 m2/year compared with those with a minor change in UACR and eGFR.ConclusionsCombined changes in albuminuria and eGFR over 2 years were strongly associated with future risk of kidney failure in patients with type 2 diabetes.
Empowering the patient? Medication communication during hospital discharge: a qualitative study at an internal medicines ward in Norway
Authors: Rognan Stine Eidhammer , Kälvemark-Sporrong Sofia , Bengtsson Kajsa Rebecka , Lie Helene Berg , Andersson Yvonne , Mowé Morten , Mathiesen Liv 
Published: June 2021

ObjectiveEffective communication and patient empowerment before hospital discharge are important steps to ensure medication safety. Patients discharged from hospitals are often expected to assume self-management, frequently without healthcare personnel (HCP) having ensured patients’ knowledge, motivation and/or skills. In this substudy of a larger study, we explore how patients experience medication communication during encounters with HCPs and how they are empowered at hospital discharge.DesignThis is a qualitative case study. Data collection was done through qualitative observations of patient–HCP encounters, semistructured interviews with patients and drug reconciliation. Data were analysed using content analysis.SettingAn internal medicines ward at a university hospital in Norway.ParticipantsNine patients aged 49–90 years were included close to the day of discharge.ResultsThe analysis revealed the following themes: (1) patient-centred care (PCC), which included ‘understanding and involvement in the patient-as-person’, ‘establishment of a therapeutic alliance’, and ‘sharing power and responsibility’; and (2) biomedical (conventional) care, including the subthemes ‘HCPs in power and control’ and ‘optimising medical outcomes, following guidelines’. Even though the elements of PCC were observed in several encounters, overall communication was not sufficiently fostering patient empowerment. Spending time with patients and building relations based on mutual trust seemed undervalued.ConclusionsThe results provide a broader understanding of how patients experience medication communication at hospital discharge. Both the patients and the HCPs appear to be inculcated with biomedical traditions and are uncertain about the roles and opportunities associated with PCC. Attention should be paid to patient preferences and to the core elements of the PCC model from admission to discharge to empower patients in medication self-management.
Association between early child development trajectories and adult cognitive function in a 50-year longitudinal study in Guatemala
Authors: Gonzalez Casanova Ines , DiGirolamo Ann , Kroker-Lobos Maria F , Ochaeta Laura , Ramirez-Zea Manuel , Martorell Reynaldo , Stein Aryeh D 
Published: June 2021

ObjectivesFew studies have used longitudinal data to study the development of cognition over the life course in low-income and middle-income countries. The objectives of this study were to assess predictors of cognitive development trajectories from 6 months through 7 years, and if these trajectories predicted adult cognitive function in a birth cohort from Guatemala.DesignWe analysed data from the INCAP Nutrition Supplementation Trial Longitudinal Study in Guatemala. Cognition was assessed at eight different time points between 6 months and 7 years. We derived childhood development trajectories using latent class growth analysis. We assessed predictors of the trajectories using ordinal logistic regression, and associations between childhood trajectories and adult non-verbal intelligence and literacy at age 18–52 years (mean±SD =42.7±6.4 years) using mixed models.SettingThe study was conducted in four Guatemalan villages.ParticipantsThe study included 927 participants from Guatemala with repeated measurements of cognitive function during the first 7 years of life.ResultsWe identified three trajectories of cognitive development (high: n=214, average: n=583, low: n=130). Participants whose mothers were taller (proportional log odds (PO)=0.03, 95% CI=0.01 to 0.06), had more years of schooling (PO=0.15, 95% CI=0.06 to 0.25), or lived in households with higher socioeconomic scores (PO=0.19, 95% CI=0.09 to 0.29) were more likely to follow higher trajectories. Childhood trajectories predicted adult non-verbal intelligence (high=18.4±0.3, average=14.6±0.53, low=11.4±0.9) and literacy (high=63.8±2.0, average=48.6±1.2, low=33.9± 2.6) scores.ConclusionsIn this sample from Guatemala, cognitive development trajectories from 6 months through 7 years were associated with adult non-verbal intelligence and literacy. These findings provide evidence of tracking of cognition over time in a transitioning low-income setting.
Value of stakeholder engagement in improving newborn care in Kenya: a qualitative description of perspectives and lessons learned
Authors: Nzinga Jacinta , Jones Caroline , Gathara David , English Mike 
Published: June 2021

ObjectiveEmbedding researchers within health systems results in more socially relevant research and more effective uptake of evidence into policy and practice. However, the practice of embedded health service research remains poorly understood. We explored and assessed the development of embedded participatory approaches to health service research by a health research team in Kenya highlighting the different ways multiple stakeholders were engaged in a neonatal research study.MethodsWe conducted semistructured qualitative interviews with key stakeholders. Data were analysed thematically using both inductive and deductive approaches.SettingOver recent years, the Health Services Unit within the Kenya Medical Research Institute (KEMRI)-Wellcome Trust Research Programme in Nairobi Kenya, has been working closely with organisations and technical stakeholders including, but not limited to, medical and nursing schools, frontline health workers, senior paediatricians, policymakers and county officials, in developing and conducting embedded health research. This involves researchers embedding themselves in the contexts in which they carry out their research (mainly in county hospitals, local universities and other training institutions), creating and sustaining social networks. Researchers collaboratively worked with stakeholders to identify clinical, operational and behavioural issues related to routine service delivery, formulating and exploring research questions to bring change in practiceParticipantsWe purposively selected 14 relevant stakeholders spanning policy, training institutions, healthcare workers, regulatory councils and professional associations.ResultsThe value of embeddedness is highlighted through the description of a recently completed project, Health Services that Deliver for Newborns (HSD-N). We describe how the HSD-N research process contributed to and further strengthened a collaborative research platform and illustrating this project’s role in identifying and generating ideas about how to tackle health service delivery problemsConclusionsWe conclude with a discussion about the experiences, challenges and lessons learned regarding engaging stakeholders in the coproduction of research.
Air quality, Environment and Respiratory Outcomes in Bronchopulmonary Dysplasia, the AERO-BPD cohort study: design and adaptation during the SARS-CoV-2 pandemic
Authors: Ruran Hana B , Adamkiewicz Gary , Cunningham Amparito , Petty Carter R , Greco Kimberly F , Gunnlaugsson Sigfus , Stamatiadis Natalie , Sierra Gabriella , Vallarino Jose , Alvarez Marty , Hayden Lystra P , Sheils Catherine A , Weller Edie , Phipatanakul Wanda , Gaffin Jonathan M 
Published: June 2021

IntroductionAlmost half of all school-age children with bronchopulmonary dysplasia (BPD) have asthma-like symptoms and more suffer from lung function deficits. While air pollution and indoor respiratory irritants are known to affect high-risk populations of children, few studies have objectively evaluated environmental contributions to long-term respiratory morbidity in this population. This study aimed to examine the role of indoor environmental exposures on respiratory morbidity in children with BPD.Methods and analysisThe Air quality, Environment and Respiratory Ouctomes in BPD (AERO-BPD) study is a prospective, single-centre observational study that will enrol a unique cohort of 240 children with BPD and carefully characterise participants and their indoor home environmental exposures. Measures of indoor air quality constituents will assess the relationship of nitrogen dioxide (NO2), particulate matter (PM2.5), nitric oxide (NO), temperature and humidity, as well as dust concentrations of allergens, with concurrently measured respiratory symptoms and lung function.Adaptations to the research protocol due to the SARS-CoV-2 pandemic included remote home environment and participant assessments.Ethics and disseminationStudy protocol was approved by the Boston Children’s Hospital Committee on Clinical Investigation. Dissemination will be in the form of peer-reviewed publications and participant information products.Trial registration numberNCT04107701.
Randomised trial of a serious illness decision aid (Plan Well Guide) for patients and their substitute decision-makers to improve engagement in advance care planning
Authors: Howard Michelle , Elston Dawn , Borhan Sayem , Hafid Abe , Arora Neha , Forbes Ruth , Bernard Carrie , Heyland Daren K 
Published: June 2021

ObjectiveTo evaluate the feasibility and efficacy of a serious illness decision aid (Plan Well Guide) in increasing the engagement of substitute decision-makers (SDM) in advance care planning (ACP).MethodsThis trial was conducted (2017–2019) in outpatient settings in Ontario, Canada, aiming to recruit 90 dyads of patients aged 65 years and older at high risk of needing future medical decisions and their SDM. Participants were randomised to receive the intervention immediately or to a 3-month wait period. The Plan Well Guide was administered to the patient and SDM by a facilitator. Outcomes were change on the validated 17-item SDM ACP Engagement Survey (primary) and 15-item patient ACP Engagement Survey (secondary).ResultsOf 136 dyads approached, 58 consented and were randomised and 45 completed the study (28 immediate intervention, 17 delayed intervention). The trial was stopped early because of difficulties with enrolling and following up participants. The mean changes on the SDM ACP Engagement Survey and the patient ACP Engagement Survey favoured the first group but were not statistically significant (mean difference (MD)=+0.2 (95% CI: −0.3 to 0.6) and MD=+0.4 (95% CI: −0.1 to 0.8), respectively). In a post-hoc subgroup analysis, significant treatment effects were seen in SDMs with a lower-than-median baseline score compared with those at or above the median.ConclusionsIn this statistically underpowered randomised trial, differences in SDM ACP engagement between groups were small. Further information is needed to overcome recruitment challenges and to identify people most likely to benefit from the Plan Well Guide.Trial registration numberNCT03239639
Auxiliary diagnostic value of D2-40 in early lung adenocarcinoma and precursor lesions
Authors: Hongxia Wang , Qingqing Yi , Chunfang Zhang , Jun Chen , Jing Li , Guofeng Lu , Rong Yang 
Published: June 2021

AimsObjective to investigate whether D2-40 can be used as a marker of early lung adenocarcinoma and precursor lesions.MethodsIn order to explore the value of D2-40, a monoclonal antibody that recognises the podoplanin, as an auxiliary diagnostic marker to aid the diagnosis of these conditions, we performed the immunohistochemical (IHC) staining using early lung adenocarcinoma, infiltrating adenocarcinoma, benign lung lesions and relevant peritumour normal tissues. The microscopic examination was performed to analyse the D2-40 IHC staining.ResultsWe found that there was no D2-40 staining in 47 cases of early stage lung adenocarcinoma and precursor lesions; only 1 of the 32 cases (3.13%) of infiltrating adenocarcinoma stained positive. There was 100% D2-40 staining in 30 cases of benign lung lesions and 79 cases of peritumour normal tissues. The positivity rate in carcinoma group was 1.27% and the normal tissue group was 100%, (p<0.01). Based on our findings, we concluded that D2-40 IHC staining in lung adenocarcinoma and precursor lesions compared with normal alveolar epithelia displayed the ‘none or all’ phenomenon.ConclusionsThe results from our study suggested that D2-40 can be sued as auxiliary diagnostic tool in early lung adenocarcinoma and its precursor lesions.