bluuebunny/crossref_metadata_2025_split huggingface dataset:
The COVID-19 pandemic and its effect on Otolaryngology trainees: A comprehensive nationwide cross-sectional study.
Authors: Sharhan Salma S. Al , Bar Mohammed H. Al , AlSaied Abdulmalik S. , ALEnazi Abdulaziz S. , Aljubran Hussain J. , AlKhaldi Saud K. , Alghamdi Amal A. 
Published: September 2020

Abstract
Background: As a consequence of the COVID-19 global pandemic, otolaryngology residents are at high risk due to the nature of the specialty and long work hours. Moreover, COVID-19 could have a severe impact on residents from different frontline specialties, particularly otolaryngology. To the best of our knowledge, this is the first nationwide survey providing insights into the impact of COVID-19 on otolaryngology residents.Methods: A cross-sectional questionnaire-based study was conducted among all otolaryngology training centers of Saudi Arabia to investigate the extent of the impact of COVID-19 on otolaryngology residents and the learning process.Results: A total of 152 residents were contacted to participate in the study, and 101 participants were included after successfully completing the questionnaire. The mean age of the participants was 28.12 years (S.D. = 1.89, max = 36, min = 25). There has been a significant impact on outpatient clinics, elective operations, consultations, and working hours. Also, we evaluated the impact on academic training activities, the frequency of training activities per week, and the psychological impact of the COVID-19 pandemic on otolaryngology residents as well.Conclusion: COVID-19 has had a serious impact on residents both physically and mentally; otolaryngology residents have been hit especially hard by this emergency pandemic period. Trainees suffered from excessive worries regarding clinical training, specifically academic concerns for different training levels. Further studies need to be done here in Saudi Arabia to evaluate this impact in greater detail and to protect the residents.
Measuring and Testing Mutual Dependence of Multivariate Functional Data
Authors: Krzyśko Mirosław , Smaga Łukasz 
Published: September 2020

Abstract
This paper considers new measures of mutual dependence between multiple multivariate random processes representing multidimensional functional data. In the case of two processes, the extension of functional distance correlation is used by selecting appropriate weight function in the weighted distance between characteristic functions of joint and marginal distributions. For multiple random processes, two measures are sums of squared measures for pairwise dependence. The dependence measures are zero if and only if the random processes are mutually independent. This property is used to construct permutation tests for mutual independence of random processes. The finite sample properties of these tests are investigated in simulation studies. The use of the tests and the results of simulation studies are illustrated with an example based on real data.
Statistical Properties and Estimation of Power-Transmuted Inverse Rayleigh Distribution
Authors: Hassan Amal S. , Assar Salwa M. , Abdelghaffar Ahmed M. 
Published: September 2020

Abstract
A three-parameter continuous distribution is constructed, using a power transformation related to the transmuted inverse Rayleigh (TIR) distribution. A comprehensive account of the statistical properties is provided, including the following: the quantile function, moments, incomplete moments, mean residual life function and Rényi entropy. Three classical procedures for estimating population parameters are analysed. A simulation study is provided to compare the performance of different estimates. Finally, a real data application is used to illustrate the usefulness of the recommended distribution in modelling real data.
Poisson Weighted Ishita Distribution: Model for Analysis of Over-Dispersed Medical Count Data
Authors: Para Bilal Ahmad , Jan Tariq Rashid 
Published: September 2020

Abstract
A new over-dispersed discrete probability model is introduced, by compounding the Poisson distribution with the weighted Ishita distribution. The statistical properties of the newly introduced distribution have been derived and discussed. Parameter estimation has been done with the application of the maximum likelihood method of estimation, followed by the Monte Carlo simulation procedure to examine the suitability of the ML estimators. In order to verify the applicability of the proposed distribution, a real-life set of data from the medical field has been analysed for modeling a count dataset representing epileptic seizure counts.
Through a Random Route to the Goal: Theoretical Background and Application of the Method in Tourism Surveying in Poland
Authors: Wójcik Sebastian 
Published: September 2020

Abstract
Classic survey methods are ineffective when surveying a small or rare population. Several methods have been developed to address this issue, but often without providing a full mathematical justification. In this paper we propose estimators of parameters relating to Random Route Sampling and explore their basic properties. A formula for the Horvitz-Thompson estimator weights is presented. Finally, a case of a tourism-related survey conducted in Poland is discussed.
Cardiovascular Risk and Quality of Life in Autosomal Dominant Polycystic Kidney Disease Patients on Therapy With Tolvaptan: A Pilot Study
Authors: Lai Silvia , Mangiulli Marco , Perrotta Adolfo M. , Gigante Antonietta , Napoleoni Ludovica , Cipolloni Elena , Mitterhofer Anna P. , Gasperini Maria L. , Muscaritoli Maurizio , Cianci Rosario , Giovannetti Antonello , Falco Fabiana , Mastroluca Daniela , Mazzaferro Sandro 
Published: September 2020

Introduction:
Cardiovascular (CV) complications are the most frequent cause of morbidity
and mortality in autosomal dominant polycystic kidney disease (ADPKD) patients. In 2017, the
Italian Medicines Agency authorised tolvaptan, a vasopressin V2 receptor antagonist, for the treatment
of ADPKD, based on the Tolvaptan Phase 3 Efficacy and Safety Study in ADPKD (TEMPO
3: 4), TEMPO 4: 4 and Replicating Evidence of Preserved Renal Function: An Investigation of Tolvaptan
Safety and Efficacy (REPRISE) studies.

Aim of the Study:
The aim of the study was to assess the impact of tolvaptan on CV risk and quality
of life, evaluated by nutritional, inflammatory, metabolic, instrumental parameters and psychocognitive
tests on ADPKD patients.

Methods and Materials:
We evaluated 36 patients with ADPKD; 10 patients (7 males, mean age
42.5±7.0 years) treated with tolvaptan and 26 controls (11 males, mean age 36.7±9.1 years). They
underwent, at T0, monthly, and at T1 (1 year) clinical, laboratory and instrumental evaluation, in
addition to psychocognitive tests.

Results:
In ADPKD patients treated with tolvaptan, we found at T1, a decrease in carotid intima--
media thickness (p=0.048), epicardial adipose tissue thickness (p=0.002), C-reactive protein
(p=0.026), sympathovagal balance during night (p=0.045) and increased flow-mediated dilation
(p=0.023) with a reduction in depression (Hamilton and Beck tests, p=0.008 and p=0.002, respectively)
compared with controls.

Conclusions:
These preliminary results suggest that treatment with tolvaptan could improve early
atherosclerosis and endothelial dysfunction markers and improve mood in ADPKD patients (probably
by acting on endothelial cell and adipocyte V2 receptors).
Efficiently Computing Geodesic Loop for Interactive Segmentation of a 3D Mesh
Authors: Meng Yun , Zhu Shaojun , Liu Bangquan , Sun Dechao , Liu Li , Yang Weihua 
Published: September 2020

Introduction:
Shape segmentation is a fundamental problem of computer graphics and geometric modeling.
Although the existence segmentation algorithms of shapes have been widely studied in mathematics community, little
progress has been made on how to compute them on polygonal surfaces interactively using geodesic loops.

Method:
We compute the geodesic distance fields with improved Fast March Method (FMM) proposed by Xin and Wang.
We propose a new algorithm to compute geodesic loops over a triangulate surface and a new interactive shape
segmentation manner on triangulate surface.

Result:
The average computation time on 50K vertices model is less than 0.08s.

Discussion:
In the future, we will use an accurate geodesic algorithm and parallel computing techniques to improve our
algorithm to obtain better smooth geodesic loop.

Conclusion:
A large number of experimental results show that the algorithm proposed in this paper can effectively
achieve high precision geodesic loop paths, and our method can also be used to interactive shape segmentation in real
time.
A Multi-Layer LSTM-Time-Density-Softmax (LDS) Approach for Protein Structure Prediction Using Deep Learning
Authors: Tejeshwar Gururaj , Mat Siddesh G. 
Published: September 2020

Introduction:
The primary structure of the protein is a polypeptide chain made up of a
sequence of amino acids. What happens due to interaction between the atoms of the backbone is
that it forms within a polypeptide folded structure, which is very much within the secondary
structure. These alignments can be made more accurate by the inclusion of secondary structure
information.

Objective:
It is difficult to identify the sequence information embedded in the secondary structure of
the protein. However, Deep learning methods can be used for solving the identification of the
sequence information in the protein structures.

Methods:
The scope of the proposed work is to increase the accuracy of identifying the sequence
information in the primary structure and the tertiary structure, thereby increasing the accuracy of the
predicted Protein Secondary Structure (PSS). In this proposed work, homology is eliminated by a
Recurrent Neural Network (RNN) based network that consists of three layers, namely bi-directional
Long Short Term Memory (LSTM), time distributed layer and Softmax layer.

Results:
The proposed LDS model achieves an accuracy of approximately 86% for the prediction of
the three-state secondary structure of the protein.

Conclusion:
The gap between the number of protein primary structures and secondary structures is
huge and increasing. Machine learning is trying to reduce this gap. In most of the other pre attempts
in predicting the secondary structure of proteins, the data is divided according to the homology of the
proteins. This limits the efficiency of the predicting model and the inputs given to such models.
Hence, in our model, homology has not been considered while collecting the data for training or
testing out model. This has led to our model to not be affected by the homology of the protein fed to
it and hence remove that restriction, so any protein can be fed to it.
Understanding the Role of HDL during COVID-19 Infection
Authors: Garg Iti , Srivastava Swati , Kumar Bhuvnesh 
Published: September 2020

Background:
Recently emerged COVID-19 pandemic has caused a large number of deaths
with lacs of confirmed cases worldwide posturing a grim situation and severe threat to public health.
There is an imperative necessity of analyzing emerging clinical and laboratory data of COVID-19 patients,
which may contribute to elucidate the pathogenic mechanism and development of effective prevention
and treatment countermeasures.

Methods:
Under this article, the emerging role of High-Density Lipoprotein (HDL) was analyzed by
collecting recently published articles related to this field having clinical data of COVID-19 patients.

Results:
Based on the recently published reports of laboratory-confirmed COVID-19 infected hospitalized
patients it was consistently observed that levels of HDL were low at the time of admission to hospital
and remained relatively low during the disease course i.e., treatment, recovery, and discharge stage. It
was also reported critically that levels of HDL in the patients, those did not survive, decreased continuously
until death.

Conclusion:
These clinical reports of patients have risen the concern about probable infection and
worsen the clinical outcome of a healthy person having a compromised level of HDL for COVID-19
infection. Eventually, these findings stated that there is a strong association of low HDL levels with a
higher risk of COVID-19 infection and further severity of the illness. Proper attention is needed to understand
the significance of altered quantity and quality of HDL in COVID-19 patients compared to
healthy controls, so that appropriate therapies could be given at the right time to combat severity and
mortality due to this infection.
Performance, Cost-Effectiveness, and Representativeness of Facebook Recruitment to Suicide Prevention Research: Online Survey Study
Authors: Lee Sylvia , Torok Michelle , Shand Fiona , Chen Nicola , McGillivray Lauren , Burnett Alexander , Larsen Mark Erik , Mok Katherine 
Published: September 2020

BackgroundResearchers are increasingly using social media advertisements to recruit participants because of their many advantages over traditional methods. Although there is growing evidence for the effectiveness and cost-effectiveness of social media recruitment in the health sciences, no studies have yet examined this in the context of suicide prevention, which remains to be a highly stigmatized and sensitive topic.ObjectiveThis study aims to recruit a general community sample to complete a survey on suicide literacy, stigma, and risk via Facebook advertisements. Specifically, we aim to establish the performance of the advertisements, cost-effectiveness, sample representativeness, and the impact of gender-specific advertising on recruiting men into the study.MethodsFrom June 2017 to March 2019, we released Facebook advertisements targeted at adults 18 years or older, residing in the New South Wales (NSW) trial or control regions, and involved in the LifeSpan suicide prevention trial. Cost-effectiveness was examined descriptively using metrics provided by Facebook. Chi-square analyses were conducted to determine demographic differences between our sample and the general NSW population as well as the impact of gender-specific advertisements on gender engagement.ResultsThe 14 Facebook advertisement campaigns reached a total of 675,199 people, yielding 25,993 link clicks and resulting in 9603 individuals initiating the survey (7487 completions) at an overall cost of Aus $2.81 (US $2.01) per participant. There was an overrepresentation of younger (P=.003), female (P=.003), highly educated (P<.001) participants and mental health conditions (P<.001) compared with the total NSW population. The use of male-specific advertisements resulted in a significantly higher proportion of men completing the survey relative to gender-neutral advertisements (38.2% vs 24.6%; P<.001).ConclusionsThis study demonstrates the potential of Facebook to be an effective, low-cost strategy for recruiting a large sample of general community participants for suicide prevention research. Strategies to improve sample representativeness warrant further investigation in future research.
Chronological Age Assessment in Young Individuals Using Bone Age Assessment Staging and Nonradiological Aspects: Machine Learning Multifactorial Approach
Authors: Dallora Ana Luiza , Kvist Ola , Berglund Johan Sanmartin , Ruiz Sandra Diaz , Boldt Martin , Flodmark Carl-Erik , Anderberg Peter 
Published: September 2020

Background
Bone age assessment (BAA) is used in numerous pediatric clinical settings as well as in legal settings when entities need an estimate of chronological age (CA) when valid documents are lacking. The latter case presents itself as critical as the law is harsher for adults and granted rights along with imputability changes drastically if the individual is a minor. Traditional BAA methods have drawbacks such as exposure of minors to radiation, they do not consider factors that might affect the bone age, and they mostly focus on a single region. Given the critical scenarios in which BAA can affect the lives of young individuals, it is important to focus on the drawbacks of the traditional methods and investigate the potential of estimating CA through BAA.

Objective
This study aims to investigate CA estimation through BAA in young individuals aged 14-21 years with machine learning methods, addressing the drawbacks of research using magnetic resonance imaging (MRI), assessment of multiple regions of interest, and other factors that may affect the bone age.

Methods
MRI examinations of the radius, distal tibia, proximal tibia, distal femur, and calcaneus were performed on 465 men and 473 women (aged 14-21 years). Measures of weight and height were taken from the subjects, and a questionnaire was given for additional information (self-assessed Tanner Scale, physical activity level, parents' origin, and type of residence during upbringing). Two pediatric radiologists independently assessed the MRI images to evaluate their stage of bone development (blinded to age, gender, and each other). All the gathered information was used in training machine learning models for CA estimation and minor versus adult classification (threshold of 18 years). Different machine learning methods were investigated.

Results
The minor versus adult classification produced accuracies of 0.90 and 0.84 for male and female subjects, respectively, with high recalls for the classification of minors. The CA estimation for the 8 age groups (aged 14-21 years) achieved mean absolute errors of 0.95 years and 1.24 years for male and female subjects, respectively. However, for the latter, a lower error occurred only for the ages of 14 and 15 years.

Conclusions
This study investigates CA estimation through BAA using machine learning methods in 2 ways: minor versus adult classification and CA estimation in 8 age groups (aged 14-21 years), while addressing the drawbacks in the research on BAA. The first achieved good results; however, for the second case, the BAA was not precise enough for the classification.
Efficacy of an Online Physical Activity Intervention Coordinated With Routine Clinical Care: Protocol for a Pilot Randomized Controlled Trial
Authors: Rockette-Wagner Bonny , Fischer Gary S , Kriska Andrea M , Conroy Molly B , Dunstan David , Roumpz Caroline , McTigue Kathleen M 
Published: September 2020

Background
Most adults are not achieving recommended levels of physical activity (150 minutes/week, moderate-to-vigorous intensity). Inadequate activity levels are associated with numerous poor health outcomes, and clinical recommendations endorse physical activity in the front-line treatment of obesity, diabetes, dyslipidemia, and hypertension. A framework for physical activity prescription and referral has been developed, but has not been widely implemented. This may be due, in part, to the lack of feasible and effective physical activity intervention programs designed to coordinate with clinical care delivery.

Objective
This manuscript describes the protocol for a pilot randomized controlled trial (RCT) that tests the efficacy of a 13-week online intervention for increasing physical activity in adult primary care patients (aged 21-70 years) reporting inadequate activity levels. The feasibility of implementing specific components of a physical activity clinical referral program, including screening for low activity levels and reporting patient program success to referring physicians, will also be examined. Analyses will include participant perspectives on maintaining physical activity.

Methods
This pilot study includes a 3-month wait-listed control RCT (1:1 ratio within age strata 21-54 and 55-70 years). After the RCT primary end point at 3 months, wait-listed participants are offered the full intervention and all participants are followed to 6 months after starting the intervention program. Primary RCT outcomes include differences across randomized groups in average step count, moderate-to-vigorous physical activity, and sedentary behavior (minutes/day) derived from accelerometers. Maintenance of physical activity changes will be examined for all participants at 6 months after the intervention start.

Results
Recruitment took place between October 2018 and May 2019 (79 participants were randomized). Data collection was completed in February 2020. Primary data analyses are ongoing.

Conclusions
The results of this study will inform the development of a clinical referral program for physical activity improvement that combines an online intervention with clinical screening for low activity levels, support for postintervention behavior maintenance, and feedback to the referring physician.

Trial Registration
ClinicalTrials.gov NCT03695016; https://clinicaltrials.gov/ct2/show/NCT03695016.

International Registered Report Identifier (IRRID)
DERR1-10.2196/18891
Responses to Concerning Posts on Social Media and Their Implications for Suicide Prevention Training for Military Veterans: Qualitative Study
Authors: Teo Alan R , Strange Wynn , Bui Ricky , Dobscha Steven K , Ono Sarah S 
Published: September 2020

Background
A “concerning post” is a display of a user’s emotional crisis on a social media platform. A better understanding of concerning posts is relevant to suicide prevention, but little is known about social media users’ attitudes and responses to concerning posts. Military veterans in the United States are disproportionately affected by suicide, often use social media, and may have exposure to individuals with elevated suicide risk via concerning posts.

Objective
The objective of the study was (1) to obtain insight into whether and how US military veterans respond to members of their social network on social media (ie, “friends”) who are experiencing substantial emotional distress, and (2) to identify potential interventions that could assist in users’ response to concerning posts.

Methods
We recruited veterans through Facebook and conducted semistructured interviews with 30 participants between June and December 2017. We used a summary template for rapid analysis of each interview, followed by double-coding using a codebook based on topic domains from the interview guide. Members of the research team met regularly to discuss emerging patterns in the data, generate themes, and select representative quotes for inclusion in the manuscript.

Results
Veterans were reluctant to disclose emotional and health issues on Facebook, but they were open to reaching out to others’ concerning posts. There was a complex calculus underlying whether and how veterans responded to a concerning post, which involved considering (1) physical proximity to the person posting, (2) relationship closeness, (3) existing responses to the post, and (4) ability to maintain contact with the person. Veterans desired additional training, backed by community-based veteran organizations, in how to respond to concerning posts from peers.

Conclusions
There is a need to incorporate features that will help veterans effectively respond to concerning posts from peers into suicide prevention training and to expand access for veterans to such training.