bluuebunny/crossref_metadata_2025_split huggingface dataset:
Kinematic alignment in total knee arthroplasty: a five-year prospective, multicentre, survivorship study
Authors: Tran Ton , McEwen Peter , Peng Yi , Trivett Adrian , Steele Robert , Donnelly William , Clark Gavin 
Published: August 2022

Aims The mid-term results of kinematic alignment (KA) for total knee arthroplasty (TKA) using image derived instrumentation (IDI) have not been reported in detail, and questions remain regarding ligamentous stability and revisions. This paper aims to address the following: 1) what is the distribution of alignment of KA TKAs using IDI; 2) is a TKA alignment category associated with increased risk of failure or poor patient outcomes; 3) does extending limb alignment lead to changes in soft-tissue laxity; and 4) what is the five-year survivorship and outcomes of KA TKA using IDI? Methods A prospective, multicentre, trial enrolled 100 patients undergoing KA TKA using IDI, with follow-up to five years. Alignment measures were conducted pre- and postoperatively to assess constitutional alignment and final implant position. Patient-reported outcome measures (PROMs) of pain and function were also included. The Australian Orthopaedic Association National Joint Arthroplasty Registry was used to assess survivorship. Results The postoperative HKA distribution varied from 9° varus to 11° valgus. All PROMs showed statistical improvements at one year (p < 0.001), with further improvements at five years for Knee Osteoarthritis Outcome Score symptoms (p = 0.041) and Forgotten Joint Score (p = 0.011). Correlation analysis showed no difference (p = 0.610) between the hip-knee-ankle and joint line congruence angle at one and five years. Sub-group analysis showed no difference in PROMs for patients placed within 3° of neutral compared to those placed > 3°. There were no revisions for tibial loosening; however, there were reports of a higher incidence of poor patella tracking and patellofemoral stiffness. Conclusion PROMs were not impacted by postoperative alignment category. Ligamentous stability was maintained at five years with joint line obliquity. There were no revisions for tibial loosening despite a significant portion of tibiae placed in varus; however, KA executed with IDI resulted in a higher than anticipated rate of patella complications. Cite this article: Bone Jt Open 2022;3(8):656–665.
Dual-mode microstrip leaky-wave antenna for pattern diversity application
Authors: Du Xiaoyu , Ren Jian , Li Huidong , Yin Yingzeng 
Published: August 2022

We present a dual-mode microstrip leaky-wave antenna (LWA), which is characterized by radiating a single beam or dual symmetrical beam. Different from the conventional single-mode microstrip LWA, the designed antenna is based on the odd mode and the even mode of the employed shorted microstrip line. The working principle of these two modes is fully studied by analyzing the electric-field distributions and their dispersion curves. Additionally, it can be found that the odd mode and the even mode are capable of realizing different radiation patterns. Furthermore, a mode translator is particularly designed in order to efficiently excite the concerned two modes. Finally, the presented antenna is simulated, fabricated, and measured, and the simulated results agree well with the measurements. The tested far-field results show that the designed dual-mode LWA realized single-beam scanning from 39° to 64° when the frequency ranges from 4.5 to 5.0 GHz and dual symmetrical beam scanning from 44° to 60° as the frequency varies from 4.5 to 4.9 GHz, respectively.
5D-fusion imaging for surface shape, polarization, and hyperspectral measurement
Authors: Luo Jing , Forsberg Erik , He Sailing 
Published: August 2022

We present a five-dimensional (5D) imager that is capable of simultaneous detection of the surface shape, spectral characteristics, and polarization states of macroscopic objects, and straightforwardly fuse collected data into a 5D data set. A polarized module that uses a polarized camera obtains polarized images, while a 3D hyperspectral module reconstructs the target as a 3D point cloud using a fringe projection technique. A liquid-crystal tunable filter is placed in front of the camera of this module to acquire spectral data that can be assigned to corresponding point clouds directly. The two modules are coupled by a dual-path configuration that allows the polarization information to be merged into a comprehensive point cloud with spectral information, generating a new 5D model. The 5D imager shows excellent performance, with a spectral resolution of 10 nm, depth accuracy of 30.7 µm, and imaging time of 8 s. Sample experiments on a toy car with micro scratch defects and a yellowing plant are presented to demonstrate the capabilities of the 5D imager and its potential for use in a broad range of applications, such as industrial manufacturing inspection, plant health monitoring, and biological analysis.
What If…? Pandemic policy-decision-support to guide a cost-benefit-optimised, country-specific response
Authors: Mannarini Giorgio , Posa Francesco , Bossy Thierry , Massemin Lucas , Fernandez-Castanon Javier , Chavdarova Tatjana , Cañas Pablo , Gupta Prakhar , Jaggi Martin , Hartley Mary-Anne 
Published: August 2022

Background
After 18 months of responding to the COVID-19 pandemic, there is still no agreement on the optimal combination of mitigation strategies. The efficacy and collateral damage of pandemic policies are dependent on constantly evolving viral epidemiology as well as the volatile distribution of socioeconomic and cultural factors. This study proposes a data-driven approach to quantify the efficacy of the type, duration, and stringency of COVID-19 mitigation policies in terms of transmission control and economic loss, personalised to individual countries.

Methods
We present What If…?, a deep learning pandemic-policy-decision-support algorithm simulating pandemic scenarios to guide and evaluate policy impact in real time. It leverages a uniquely diverse live global data-stream of socioeconomic, demographic, climatic, and epidemic trends on over a year of data (04/2020–06/2021) from 116 countries. The economic damage of the policies is also evaluated on the 29 higher income countries for which data is available. The efficacy and economic damage estimates are derived from two neural networks that infer respectively the daily R-value (RE) and unemployment rate (UER). Reinforcement learning then pits these models against each other to find the optimal policies minimising both RE and UER.

Findings
The models made high accuracy predictions of RE and UER (average mean squared errors of 0.043 [CI95: 0.042–0.044] and 4.473% [CI95: 2.619–6.326] respectively), which allow the computation of country-specific policy efficacy in terms of cost and benefit. In the 29 countries where economic information was available, the reinforcement learning agent suggested a policy mix that is predicted to outperform those implemented in reality by over 10-fold for RE reduction (0.250 versus 0.025) and at 28-fold less cost in terms of UER (1.595% versus 0.057%).

Conclusion
These results show that deep learning has the potential to guide evidence-based understanding and implementation of public health policies.
A standardized assessment of moldability parameters of thermoplastic materials used in orthotic manufacturing
Authors: Andrade Martinez Rodrigo , Bolzan Agnelli Martinez Luciana , Marcondes Agnelli José Augusto , Meirelles Carril Elui Valéria 
Published: August 2022

Objective
To establish parameters for standardized assessment of the moldability of thermoplastic materials used in orthotic manufacturing and to develop tests for quantification of moldability parameters by simulating the demands of clinical practice, in order to enable accurate and controlled analysis of material properties.

Primary outcome measurements
Two commercially available materials were submitted to tests for standardized measurement of moldability. Results were correlated with manufacturer information. Moldability assessment was based on two parameters (conformation and fit), expressed as percentages.

Results
Tests, standardized molding procedures and measurements were described. Quantitative data (conformation and fit expressed in percentages) were derived from a pilot study comparing Aquaplast-T™ and Ezeform™. Findings of that study revealed that Aquaplast-T™ is more moldable than Ezeform™ and support technical information provided by the manufacturer.

Conclusions
The assessment method described enabled objective and repeatable measurement of the moldability of materials used in orthotic manufacturing and represent a significant advancement in comparative analysis of materials, with potential positive impacts on therapeutic procedures and clinical decision-making. Tests developed in this study can be used to quantify data provided by manufacturers in order to allow their use by researchers and professionals in rehabilitation.
Convolutional neural networks to predict brain tumor grades and Alzheimer’s disease with MR spectroscopic imaging data
Authors: Acquarelli Jacopo , van Laarhoven Twan , Postma Geert J. , Jansen Jeroen J. , Rijpma Anne , van Asten Sjaak , Heerschap Arend , Buydens Lutgarde M. C. , Marchiori Elena 
Published: August 2022

PurposeTo evaluate the value of convolutional neural network (CNN) in the diagnosis of human brain tumor or Alzheimer’s disease by MR spectroscopic imaging (MRSI) and to compare its Matthews correlation coefficient (MCC) score against that of other machine learning methods and previous evaluation of the same data. We address two challenges: 1) limited number of cases in MRSI datasets and 2) interpretability of results in the form of relevant spectral regions.MethodsA shallow CNN with only one hidden layer and an ad-hoc loss function was constructed involving two branches for processing spectral and image features of a brain voxel respectively. Each branch consists of a single convolutional hidden layer. The output of the two convolutional layers is merged and fed to a classification layer that outputs class predictions for the given brain voxel.ResultsOur CNN method separated glioma grades 3 and 4 and identified Alzheimer’s disease patients using MRSI and complementary MRI data with high MCC score (Area Under the Curve were 0.87 and 0.91 respectively). The results demonstrated superior effectiveness over other popular methods as Partial Least Squares or Support Vector Machines. Also, our method automatically identified the spectral regions most important in the diagnosis process and we show that these are in good agreement with existing biomarkers from the literature.ConclusionShallow CNNs models integrating image and spectral features improved quantitative and exploration and diagnosis of brain diseases for research and clinical purposes. Software is available athttps://bitbucket.org/TeslaH2O/cnn_mrsi.
A latent class analysis to identify socio-economic and health risk profiles among mothers of young children predicting longitudinal risk of food insecurity
Authors: Daundasekara Sajeevika Saumali , Schuler Brittany R. , Hernandez Daphne C. 
Published: August 2022

BackgroundThe purpose of the current study was to use a social determinants of health (SDOH) framework and latent class analysis (LCA) to identify risk classes among mothers with young children. The risk classes were then used to predict food insecurity severity and stability/change of food insecurity over time.MethodThe secondary data from the Fragile Families and Child Wellbeing Study (n = 2,368; oversampled for non-marital births) was used in this study. Household food insecurity was assessed using the 18-items USDA Food Security Survey. A seventeen-item inventory of educational, economic stability, incarceration (i.e. social context), neighborhood safety (i.e. neighborhood and built environment), health and health care, and substance use behaviors at baseline/Year-1 were included to identify SDOH risk indicators in the LCA. Covariate-adjusted multinomial logistic regression models were used to examine the relation between risk classes at Year-1 and the severity of food insecurity at Year-3 and stability/change of food insecurity between Year-3 and Year -5.ResultsLCA identified five risk classes: High utility and medical hardship (Class 1), high housing and employment hardship, high substance use, and incarceration (Class 2), high housing and medical hardship, poor health, and health care (Class 3), high employment hardship and low-income (Class 4) and low-risk (Class 5). The Class 1, Class 2 and Class 3 had greater odds of low food security and very low food security at Year-3 compared to Class 4. In addition, compared to Class 4, Class 1, Class 2 and Class 3 had greater odds unstable food insecurity and persistent food insecurity over time.ConclusionsLCA could be used to identify distinctive family system risk profiles predictive of food insecurity. The generated risk profiles could be used by health care providers as an additional tool to identify families in need for resources to ensure household food security.
The Key Driver Implementation Scale (KDIS) for practice facilitators: Psychometric testing in the “Southeastern collaboration to improve blood pressure control” trial
Authors: Stover Angela M. , Wang Mian , Shea Christopher M. , Richman Erica , Rees Jennifer , Cherrington Andrea L. , Cummings Doyle M. , Nicholson Liza , Peaden Shannon , Craft Macie , Mackey Monique , Safford Monika M. , Halladay Jacqueline R. 
Published: August 2022

Background
Practice facilitators (PFs) provide tailored support to primary care practices to improve the quality of care delivery. Often used by PFs, the “Key Driver Implementation Scale” (KDIS) measures the degree to which a practice implements quality improvement activities from the Chronic Care Model, but the scale’s psychometric properties have not been investigated. We examined construct validity, reliability, floor and ceiling effects, and a longitudinal trend test of the KDIS items in the Southeastern Collaboration to Improve Blood Pressure Control trial.

Methods
The KDIS items assess a practice’s progress toward implementing: a clinical information system (using their own data to drive change); standardized care processes; optimized team care; patient self-management support; and leadership support. We assessed construct validity and estimated reliability with a multilevel confirmatory factor analysis (CFA). A trend test examined whether the KDIS items increased over time and estimated the expected number of months needed to move a practice to the highest response options.

Results
PFs completed monthly KDIS ratings over 12 months for 32 primary care practices, yielding a total of 384 observations. Data was fitted to a unidimensional CFA model; however, parameter fit was modest and could be improved. Reliability was 0.70. Practices started scoring at the highest levels beginning in month 5, indicating low variability. The KDIS items did show an upward trend over 12 months (all p < .001), indicating that practices were increasingly implementing key activities. The expected time to move a practice to the highest response category was 9.1 months for standardized care processes, 10.2 for clinical information system, 12.6 for self-management support, 13.1 for leadership, and 14.3 months for optimized team care.

Conclusions
The KDIS items showed acceptable reliability, but work is needed in larger sample sizes to determine if two or more groups of implementation activities are being measured rather than one.
A simple surgical mask modification to pass N95 respirator-equivalent fit testing standards during the COVID-19 pandemic
Authors: Dardas Agnes Z. , Serra Lopez Viviana M. , Boden Lauren M. , Gittings Daniel J. , Heym Kevin , Koerber Emily , Grosh Taras , Ahn Jaimo 
Published: August 2022

BackgroundThe COVID-19 pandemic has infected hundreds of millions of people resulting in millions of deaths worldwide. While N95 respirators remain the gold standard as personal protective equipment, they are resource-intensive to produce and obtain. Surgical masks, easier to produce and obtain, filter ≥95% submicron particles but are less protective due to a lack of seal around a user’s face. This study tested the ability of a simple surgical mask modification using rubber bands to create a seal against particle exposure that would pass N95 standards.Methods and findingsForty healthcare workers underwent TSI PortaCount mask fit testing using an ASTM Level 1 surgical mask modified with rubber bands. Fit Factor was determined after testing four standard OSHA N95 fit testing scenarios. Performance of the properly-modified surgical mask was compared to that of a poorly-modified surgical mask, an unmodified standard surgical mask, and an N95 respirator. Thirty-one of forty (78%) healthcare workers passed Fit Factor testing using a properly-modified mask. The Fit Factor success rate significantly improved by subsequent test date (p = 0.043), but was not associated with any other participant characteristics. The average Fit Factor score for the properly-modified mask was 151 (SD 65.2), a significantly better fit than the unmodified mask score of 3.8 (SD 3.1, p<0.001) and the poorly-modified mask score of 24.6 (SD 48.4, p<0.001) but significantly lower than a properly fitted N95 score of 199 (SD 4.5, p<0.001).do.ConclusionsRubber bands, a low-cost and easily-accessible modification, can improve the seal and protective ability of a standard surgical mask to the level of an N95 respirator. This could mitigate N95 respirator shortages worldwide and provide individuals in under-resourced regions a practical means for increased personal respiratory protection.
Hearing impairment among adult foreign-born and Swedish-born individuals: A national Swedish study
Authors: Wändell Per , Li Xinjun , Carlsson Axel , Sundquist Jan , Sundquist Kristina 
Published: August 2022

Objectives
To analyze the risk of hearing impairment in adult first-generation immigrants, i.e., foreign-born individuals as compared to Swedish-born individuals.

Study design
A register-based study follow-up study.

Methods
A nationwide study of individuals 25 years of age and older (N = 5 464 245; 2 627 364 men and 2 836 881 women) in Sweden. Hearing impairment was defined as at least one registered diagnosis in the National Patient Register between January 1st, 1998 and December 31st, 2015. Cox regression analysis was used to estimate the relative risk (hazard ratios (HR) with 95% confidence intervals (CI)) of incident hearing impairment in foreign-born compared to Swedish-born individuals. Cox regression models were stratified by sex and adjusted for age, comorbidities, and socioeconomic status.

Results
A total of 244 171 cases (124 349 men and 119 822 women) of hearing impairment were registered. Hearing impairment risk expressed as fully adjusted HRs (99% CI) was somewhat lower among immigrant men 0.95 (0.92–97) but not among immigrant women 0.97 (0.95–1.00), with significantly higher fully adjusted HRs among men and women from Asia, and Eastern Europe, and women from Africa.

Conclusions
We observed a somewhat lower risk of hearing impairment among foreign-born men, but there was a higher risk among men and women from some regions.
Longitudinal changes and correlates of meeting WHO recommended levels of physical activity in the UK during the COVID-19 pandemic: Findings from the HEBECO study
Authors: Mitchell John J. , Dicken Samuel J. , Kale Dimitra , Herbec Aleksandra , Beard Emma , Shahab Lion 
Published: August 2022

Background
The COVID-19 pandemic has seen repeated government enforced restrictions on movement. This study aimed to evaluate longitudinal trends in physical activity (PA) in a self-selected UK-based sample and identify the key correlates of these trends.

Methods
From 23 April 2020 to 30 January 2021, measures of PA engagement were collected in a sample of 1,947 UK-based adults. Generalised estimating equations (GEE) explored trends in PA engagement over time, and how sociodemographic, health and contextual factors impacted participant’s attainment of World Health Organization (WHO) recommended levels of PA (constituting muscle strengthening activity (MSA), and moderate or vigorous PA (MVPA)).

Results
While one in five achieved the recommended levels of PA in the first UK lockdown in April-June 2020 (19.5%, 95%CI: 17.8–21.3%) and a similar proportion in June-July 2020 (17.7%, 95%CI: 16.1–19.5%), this reduced during the period of eased restrictions in August-September 2020 (15.2%, 95%CI: 13.7–16.9%) and the second UK lockdown in November 2020-January 2021 (14.1%, 95%CI: 12.6–15.9%). Similar trends were observed for MSA and MVPA individually. Better quality of life, higher socioeconomic position and pre-COVID-19 PA levels were associated with meeting the WHO recommended levels of PA, while those living with overweight or obesity, a limiting health condition, or isolating showed the inverse associations. Time-specific associations with MSA or MVPA were observed for gender and age.

Conclusion
Reductions in PA levels throughout the first strict lockdown continued without reversal during the ensuing period. The association of negative change with socioeconomic and health-related indices points towards deepening health inequities during the pandemic.
Two-minute walk distance reference equations for middle-aged and elderly Chinese individuals with obesity
Authors: Zhang Jia , Zou Yingying , Wang Zibin , Chen Xiaoshu , Pan Jingye , Yu Haizhu , Li Enci , Zou He 
Published: August 2022

Background and objective
While the six-minute walk test (6MWT) is often used to assess exercise capacity, the less well-known two-minute walk test (2MWT) is more feasible for some patients. In previous studies, we developed reference equations for the two-minute walk distance (2MWD) for healthy Chinese adults. However, our study did not recruit people with obesity, and the reference equations did not apply to participants with a body mass index (BMI) > 30 kg/m2. The main objective of this study was to establish reference equations for the 2MWD among middle-aged and elderly Chinese individuals with obesity.

Methods
A total of 295 individuals were recruited. The participants underwent two 2MWTs, with the longer of the two 2MWDs used for further analyses. The reference equations for the 2MWD were developed using stepwise multiple regression analysis. The newly established equations for the 2MWD were then compared with the existing equations.

Results
The mean 2MWD of the participants was 176±20 m. Age and BMI were identified as independent factors that influenced the 2MWD and explained 28% and 32% of the variance in walking distance for the male and female groups, respectively. The reference equations for the 2MWD were as follows:

Male:2MWD(m)=443.058−[age(yr)x6.782]+[BMI(kg/m2)x0.847];r2=0.283Female:2MWD(m)=300.160−[age(yr)x0.841]−[BMI(kg/m2)x2.541];r2=0.315

Conclusion
This study resulted in the development of reference equations for predicting 2MWD among middle-aged and elderly Chinese people with obesity. These equations will be a clinically valuable tool for evaluating functional capacity, determining prognoses and monitoring treatment in middle-aged and elderly Chinese people with obesity.