bluuebunny/crossref_metadata_2025_split huggingface dataset:
AWARE. A web application to rapidly assess cardiovascular risk in Type 2 Diabetes Mellitus.
Authors: Berra Cesare Celeste , Manfrini Roberto , Mirani Marco , Bucciarelli Loredana , Zakaria Amhed S , Piccini Sara , Ghelardi Renata , Lunati Maria Elena , Rodovalho Sylka , Bifari Francesco , Fiorina Paolo , Folli Franco 
Published: December 2022

Abstract
Background
Cardiovascular (CV) risk assessment may result unpractical in real-world clinical practice, although being considered a key step for choosing appropriate therapies for patients with Type 2 Diabetes Mellitus (T2DM). In order to streamline this process in the diabetes clinic, we have developed the web application “AWARE”.
Methods
The AWARE App is based on 2019 ESC/EASD criteria for cardiovascular risk (CVR) stratification in T2DM, which divides patients into 3 categories: very high (VHCVR), high (HCVR) and moderate (MCVR) CV risk. In this retrospective clinical study, we employed the AWARE App to assess CV risk of consecutive T2DM patients attending Diabetes Clinics in Lombardy (Italy).
Results
Overall, 2243 T2DM patients underwent CV risk assessment with the AWARE App. 1619 patients (72.2%) had a VHCVR, 199 (8.9%) an HCVR, and only 17 (0.8%) had an MCVR. 408 patients (18.2%) did not fit into any of the ESC/EASD risk categories and we included them in the additional “moderate-to-high” (MHCVR) group. Patients with VHCVD were more frequently ≥65 years old (68.9%), with a longer disease duration (≥10 years [56.8%]), history of CV disease (41.4%), organ damage (35.5%) and higher numbers of CV risk factors compared with other risk groups. Patients with MHCVD generally had disease duration <10 years (96%), younger age (50-60 years [55%]), no history of CV disease and no organ damage, and 1-2 CV risk factors (89%). GLP-1 RA or SGLT-2i were prescribed only to 26.3% of the patients with VHCVR and to 24.7% of those with HCVR. Glycaemic control was unsatisfactory, both in the overall population and in each CV risk group (mean A1c level of 58.7 ± 13.44 mmol/mol [7.5 ± 3.4%]).
Conclusions
The AWARE App is a practical tool for CV risk stratification of T2DM patients in real-world clinical practice. Despite a generally severe CV risk and unsatisfactory glycaemic control, T2DM patients are rarely treated to achieve HbA1c < 7% and with newer cardioprotective medications.
LEVYEFO-WTMTOA: The hybrid of the multi-tracker optimization algorithm and the electromagnetic field optimization
Authors: Esfahani Faramarz Safi , Mirjalili Ali , Mohamadhoseini Leili 
Published: December 2022

Abstract
Many engineering optimization problems can be solved using meta-heuristics. Despite their merits, such algorithms face common challenges of early convergence rate and the imbalance between the exploitation and exploration phases. These algorithms have strengths and weaknesses considering the convergence rate, local search, and global search criteria. This study presents the new algorithm called the LEVYEFO-WTMTOA that combines the Modified Multi-Tracker Optimization Algorithm (MTOA) and the electromagnetic field optimization (EFO) approach. The LEVYEFO-WTMTOA applies the following proposals to escape from local optima: 1) the Morlet wavelet transform is used to determine the Radius of Search (RS) of the MTOA; 2) a mutation phase based on the combination of the best global position in the electromagnetic field optimization algorithm and the levy law is used in the exploration phase to update the new position 3) it has focused on balancing local and global search and escaping from the local optima trap of the MTOA. To evaluate the proposed LEVYEFO-WTMTOA algorithm, the CEC2018 benchmark suite is used, and the results are compared with the original MTOA, EFO, MEFO, MVO Levy, GSA, and COA algorithms in terms of mean error. The results demonstrate that the proposed algorithm performs better than the baseline algorithms. The applications of LEVYEFO-WTMTOA on several classical engineering problems are included as well.
Increased Interleukin-6 is Associated with Long COVID-19: Evidence from a Systematic Review and Meta-analysis
Authors: Yin Jing-Xian , Agbana Yannick Luther , Sun Zhi-Shan , Fei Si-Wei , Zhao Han-Qing , Zhou Xiao-Nong , Chen Jun-Hu , Kassegne Kokouvi 
Published: December 2022

Abstract
Background: Coronavirus disease 2019 (COVID-19) can involve persistence, sequelae, and other clinical complications that last weeks to months to evolve into long COVID-19. Exploratory studies have suggested that interleukin-6 (IL-6) is related to COVID-19; however, no correlation between IL-6 and long COVID-19 is known. We designed a systematic review and meta-analysis to assess the relationship between IL-6 levels and long COVID-19.
Methods: Databases were systematically searched for articles with data on long COVID-19 and IL-6 levels published before September 2022. A total of 22 published studies were eligible for inclusion following the PRISMA guidelines. Analysis of data was undertaken by using Cochran's Q test and the Higgins I-squared (I2) statistic for heterogeneity. Random-effect meta-analyses were conducted to pool the IL-6 levels of long COVID-19 patients and to compare the differences in IL-6 levels among the long COVID-19, healthy, non-post-acute sequelae of SARS-CoV-2 infection (non-PASC), and acute COVID-19 populations. The funnel plot and Egger's test were used to assess potential publication bias. Sensitivity analysis was used to test the stability of the results.
Results: An increase in IL-6 levels was observed after severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. The pooled estimate of IL-6 revealed a mean value of 20.92 pg/ml (95% CI = 9.30 – 32.54 pg/ml, I2 = 100%, p < 0.01) for long COVID-19. The forest plot showed high levels of IL-6 for long COVID-19 compared with healthy controls (mean difference = 9.75 pg/ml, 95% CI = 5.75 – 13.75 pg/ml, I2 = 100%, p < 0.00001) and PASC category (mean difference = 3.32 pg/ml, 95% CI = 0.22 – 6.42 pg/ml, I2 = 88%, p = 0.04). The symmetry of the funnel plots was not obvious, and Egger’s test showed that there was no significant small study effect in all groups (long COVID-19 versus healthy controls, p = 0.24; long COVID-19 versus non-PASC, p = 0.31).
Conclusions: This study showed that increased IL-6 correlates with long COVID-19. Such an informative revelation suggests IL-6 as a basic determinant to predict long COVID-19 or at least inform on “early stage” of long COVID-19.
Biomechanical analysis of adjacent segments after spine fusion surgery using a novel geometrically-parametric patient-specific finite element model
Authors: Wang Yuming , Shen Qianyi , Liang Chang , Tang Xiangsheng , Yi Ping 
Published: December 2022

Abstract
OBJECTIVE: This study aimed to perform mechanical analysis of adjacent segments after spine fusion surgery using a novel geometrically-parametric patient-specific finite element model and to elucidate the mechanism of adjacent segments degeneration（ASD）thus providing theoretical evidence for early prevention.
METHODS: Fourteen parameters based on patient specific spinal geometry were extracted from the patient's preoperative computed tomography(CT), and the relative positions of each spinal segment were determined using image match method. A preoperative patient-specific model of spine was established by the above method. The postoperative model of L45 posterior lumbar interbody fusion(PLIF) surgery was constructed using the same method except for removing the lamina and the intervebral disc, and inserting a cage, 4 pedicle screws, and 2 connecting rods. Range of motion(ROM) and stress changes were compared between each anatomic structure of the preoperative and postoperative models.
RESULTS: The overall ROM of the lumbar spine decreased after fusion, while the ROM, stress at facet joint, and stress at the intervertebral disc of adjacent segments all increased. The stress distribution in the annulus fibrosus, nucleus pulposus, and facet joints also showed that not only the maximum stress in these tissues were elevated, but the areas of the moderate-to-high stress region were also expanded. During torsion, the stress at facet joint and annulus fibrosus of the proximal adjacent segment (L34) increased to a larger extent compared with the distal adjacent segment (L5S1).
Conclusion: While fusion surgery causes an overall restriction of motion at the lumbar spine, it also causes more loads sharing by the adjacent segments in order to compensate for the fused segment, thus increasing the risk of ASD. The proximal adjacent segment is more prone to degeneration than the distal adjacent segment after spinal fusion due to the significant increase in stress changes.
Dental Pain Perception and Emotional Changes: On The Relationship Between Dental Anxiety And Olfaction
Authors: Alkanan Sarah Abdulaziz Mohammed , Alhaweri Hadeel Saleh , Khalifa Ghada Amin , Ata Shaimaa Mohamed Saeed 
Published: December 2022

Abstract
Background: The study aimed to determining the magnitude of the power of the aromatherapy at which it reduces the intensity of dental pain and level of dental anxiety. Also, it aimed to correlate between olfactory aromatherapy, phases of dental visits, and different dental procedures.
Methods: A randomized controlled study was enrolled on female patients. The olfaction was stimulated via lavender oils. Patients were randomly divided into a lavender group in which patients inhaled 2 % of lavender vapors and control group where the patients inhaled water vapors. The variables included pain score, anxiety score, and changes in vital signs. Modified Dental Anxiety Scale (MDAS) and ﻿Speilberger State-Trait Anxiety Inventory (STAI) questionnaires and visual analog scales (VAS) were used to assess anxiety and pain. Vital signs included systolic (SBP) and diastolic blood pressure (DBP), heart rate (HR), respiratory rate (RR), and oxygen saturation (Spo2). Variables were assessed before inhalations, 20 minutes after inhalations, at the end of settings, and on the day after visits.
Results: Each group included 175 subjects. Pain and anxiety scores were significantly reduced and vital signs were also improved, except for DBP. The MDAS, STAI, and pain scores are reduced by 3.4, 4.2, and 2.4 times more than control group, respectively. The greatest effect of the aromatherapy appeared in setting rooms.
Conclusion: The pleasant olfaction minimizes anxiety scores three to four times and pain perception two times more than the control group. It also significantly reduces the fear of dental procedures which have mild to moderate scores.
Modelling green volume using Sentinel-1, -2, PALSAR-2 satellite data and machine learning for urban and semi-urban areas in Germany
Authors: Lehmler Sebastian , Förster Michael , Frick Annett 
Published: December 2022

Abstract
Urban Green Infrastructure (UGI) provides ecosystem services such as cooling of temperatures and is majorly important for climate change adaptation. Green Volume (GV) describes the 3-D space occupied by vegetation and is highly useful for the assessment of UGI. This research uses Sentinel-2 (S-2) optical data; vegetation indices (VIs); Sentinel-1 (S-1) and PALSAR-2 (P-2) radar data to build machine learning models for yearly GV estimation on large scales. Our study compares random and stratified sampling of reference data, assesses the performance of different machine learning algorithms and tests model transferability by independent validation. The results indicate that stratified sampling of training data leads to improved accuracies when compared to random sampling. While the Gradient Tree Boost (GTB) and Random Forest (RF) algorithms show generally similar performance, Support Vector Machine (SVM) exhibits considerably greater model error. The results suggest RF to be the most robust classifier overall, achieving highest accuracies for independent and inter-annual validation. Furthermore, modelling GV based on S-2 features considerably outperforms using only S-1 or P-2 based features. Moreover, the study finds that underestimation of large GV magnitudes in urban forests constitutes the biggest source of model error. Overall, modelled GV explains around 79% of the variability in reference GV at 10m resolution and over 90% when aggregated to 100m resolution. The research shows that accurately modelling GV is possible using openly available satellite data. Resulting GV predictions can be useful for environmental management by providing valuable information for climate change adaptation, environmental monitoring and change detection.
Towards high-throughput many-body perturbation theory: efficient algorithms and automated workflows
Authors: Bonacci Miki , Qiao Junfeng , Spallanzani Nicola , Marrazzo Antimo , Pizzi Giovanni , Molinari Elisa , Varsano Daniele , Ferretti Andrea , Prezzi Deborah 
Published: December 2022

Abstract
The automation of ab initio simulations is essential in view of performing high-throughput (HT) computational screenings oriented to the discovery of novel materials with desired physical properties. In this work, we propose algorithms and implementations that are relevant to extend this approach beyond density functional theory (DFT), in order to automate many-body perturbation theory (MBPT) calculations. Notably, a novel algorithm pursuing the goal of an efficient and robust convergence procedure for GW and BSE simulations is provided, together with its implementation in a fully automated framework. This is accompanied by an automatic GW band interpolation scheme based on maximally-localized Wannier functions, aiming at a reduction of the computational burden of quasiparticle band structures while preserving high accuracy. The proposed developments are validated on a set of representative semiconductor and metallic systems.
The relationship between components of hypoglycemia worries and avoiding hypoglycemia behavior in type 2 diabetes mellitus with hypoglycemia: a network analysis
Authors: Wu Chao , Wang Wenwen , Cheng Sizhe , Zhang Yinjuan , Li Lu , Zhang Linyuan , Chen Nana , Du Juan , Ren Lei , Lang Hongjuan 
Published: December 2022

Abstract
Background: The fear of hypoglycemia in type 2 diabetes mellitus (T2DM) patients with hypoglycemia has seriously affected their quality of life. They are always afraid of hypoglycemia and often take excessive action to avoid it. Yet, researchers have investigated the relationship between hypoglycemia worries and excessive avoiding hypoglycemia behavior using total scores on self-report measures. However, network analysis studies of hypoglycemia worries and excessive avoiding hypoglycemia behavior in T2DM patients with hypoglycemia are lacking.
Purpose: The present study investigated the network structure of hypoglycemia worries and avoiding hypoglycemia behavior in T2DM patients with hypoglycemia and aimed to identify bridge items to help them correctly treat hypoglycemia and properly deal with hypoglycemia fear.
Methods: A total of 283 T2DM patients with hypoglycemia were enrolled in our study. Hypoglycemia worries and avoiding hypoglycemia behavior were evaluated with the Hypoglycemia Fear Scale. Network analyses were used for the statistical analysis.
Results: B9 “Had to stay at home for fear of hypoglycemia” and W12 “I am worried that hypoglycemia will affect my judgment” have the highest expected influences in the present network. In the community of hypoglycemia worries, W17 “I worry about hypoglycemia during sleep” has the highest bridge expected influence. And in the community of avoiding hypoglycemia behavior, B9 has the highest bridge expected influence.
Conclusion: Complex patterns of associations existed in the relationship between hypoglycemia worries and avoiding hypoglycemia behavior in T2DM patients with hypoglycemia. From the perspective of network analysis, W17 “I worry about hypoglycemia during sleep” aspect of hypoglycemia worries and B9 “Had to stay at home for fear of hypoglycemia” aspect of avoiding hypoglycemia behavior may be the main targets for reducing the fear of hypoglycemia. These results have important implications for clinical practice, which provided potential targets for interventions to reduce hypoglycemia fear and improve the quality of life in T2DM patients with hypoglycemia.
Development and Validation of a New Multivariable Prediction Model to Estimate Risk of Abnormal Vault
Authors: Yang Jing , Zou Zongyin , Wu Minhui , He Runzhang , Nong Yating , Li Hui , Zhou Sheng 
Published: December 2022

Abstract
Purpose:
To develop and validate a new multivariable prediction model to estimate risk of abnormal vault after EVO Implantable Collamer Lens (EVO-ICL) implantation using the preoperative parameters.
Methods:
This retrospective study comprised 282 eyes of 143patients who underwent EVO-ICL surgery between May 2021 and April 2022. We measured preoperative parameters and vaults in 1 week after the operation using swept-source optical coherence tomography (SS-OCT). Risk factors for abnormal vault were determined by univariate and multivariate logistic regression analyses, and a nomogram was developed to forecast the probability of abnormal vault after EVO-ICL implantation. We assessed the performance of nomogram in terms of discrimination and calibration, including concordance index (C-index), area under the curve (AUC), and decision curve analysis (DCA). Bootstrap resampling was used as an internal verification method.
Results:
The logistic regression analysis revealed the independent risk factors for abnormal vault were WTW, ACA, pupil size, and ICL-width, all of them were used to establish a nomogram to predict the risk of abnormal vault. The C-indexes and AUC were 0.669 (95%CI, 0.605, 0.733). The calibration curves of the nomogram showed relatively small bias from the reference line, implicating an acceptable degree of confidence. The DCA indicates the potential clinical significance of the nomogram.
Conclusion:
We developed a new multivariable prediction model to estimate risk of abnormal vault. The model shows good prediction effect and can provide assistance for clinical decision of ICL size.
It All Depends on Which Side of the Fence You Are Standing: Agent and Recipient Perspectives Are Differently Linked With Job Crafting
Authors: Roczniewska Marta , Marszałek Magdalena 
Published: December 2022

Abstract
Background
In social contexts, people may view themselves as agents, who are in control of the environment, or recipients, who succumb to what others have decided. Here, we investigated how these perspectives determine job crafting (JC)—self-initiated employee behaviors targeted at altering job characteristics to fit them with one’s needs.
Methods
Study 1 tested the relationships between chronic agent–recipient tendencies and JC in a cross-lagged panel design. Study 2 was a randomized experiment where agent–recipient perspectives were manipulated to predict JC intentions in the week to follow.
Results
Supporting our predictions, while agents sought structural job resources and increased challenging demands, recipients resorted to reducing hindering demands (Study 1). Study 2 revealed that activating an agent perspective led to stronger intentions to increase structural job resources and challenging demands.
Conclusions
We conclude that agent and recipient perspectives are linked with differential patterns of JC behaviors. Strengthening agency is a vital step in forming job redesign goals during JC interventions.
Sociodemographic, mental health, and physical health factors associated with participation within re-contactable mental health cohorts: an investigation of the GLAD Study
Authors: Bright Steven J. , Hübel Christopher , Young Katherine S. , Bristow Shannon , Peel Alicia J. , Rayner Christopher , Mundy Jessica , Palmos Alish B. , Purves Kirstin L. , Kalsi Gursharan , Armour Cherie , Jones Ian R. , Hotopf Matthew , McIntosh Andrew M. , Smith Daniel J. , Walters James T. R. , Rogers Henry C. , Thompson Katherine N. , Adey Brett N. , Monssen Dina , Kakar Saakshi , Malouf Chelsea M. , Hirsch Colette , Glen Kiran , Kelly Emily J. , Veale David , Eley Thalia C. , Breen Gerome , Davies Molly R. 
Published: December 2022

Abstract
Background: The Genetic Links to Anxiety and Depression (GLAD) Study is a large cohort of individuals with lifetime anxiety and/or depression, designed to facilitate re-contact of participants for mental health research. At the start of the pandemic, participants from three cohorts, including the GLAD Study, were invited to join the COVID-19 Psychiatry and Neurological Genetics (COPING) study to monitor mental and neurological health. However, previous research suggests that participation in longitudinal studies follows a systematic, rather than random, process, which can ultimately bias results. Therefore, this study assessed participation biases following the re-contact of GLAD Study participants.
Methods: In April 2020, all current GLAD Study participants (N = 36,770) were invited to the COPING study. Using logistic regression, we investigated whether sociodemographic, mental, and physical health characteristics were associated with participation in the COPING baseline survey. Subsequently, we used a zero-inflated negative binomial regression examined whether these factors were related to participation in the COPING follow-up surveys.
Results: For aim one, older age, female gender identity, non-binary or prefer to self-define gender identity, having one or more physical health disorders, and providing a saliva kit for the GLAD Study were associated with an increased odds of completing the COPING baseline survey. In contrast, lower educational attainment, Asian or Asian British ethnic identity, Black or Black British ethnic identity, higher alcohol consumption at the GLAD sign-up survey and current or ex-smoking were associated with a reduced odds. For aim 2, older age, female gender, and saliva kit provision were associated with greater COPING follow-up survey completion. On the other hand, lower educational attainment, ex-smoking, higher alcohol consumption at the GLAD Study sign-up, and self-reported attention deficit hyperactivity disorder had negative relationships.
Conclusions: Participation biases surrounding sociodemographic and physical health characteristics were particularly evident when re-contacting the GLAD Study volunteers. Future researchers re-contacting participants from existing cohorts/BioResources should be mindful of participation bias and how it may affect results obtained from analyses.