bluuebunny/crossref_metadata_2025_split huggingface dataset:
COVID19 - A Correlation Study of Infection Fatality Rate vs Age
Authors: DATTA JAYDIP 
Published: February 2021

Abstract
In this article one of the most important epidemiological parameter ie Infection fatality rate [ 1 ] is correlated with age of the population through a sigmoid statistics of Logistic model. The IFR is a special case of case fatality rate ( CFR ) . The CFR ( 1 ) is termed as the number of deaths due to symptomatic Covid infection within entire population per unit time . The IFR is a special case of CFR where number of deaths to be considered as total number of deaths due to symptomatic as well as asymptomatic infection within the same population per unit time .The sigmoid fit can also be approximated to modified quadratic fit [ 4-5 ]. CFR can be more specifically correlated to comorbidities [8 ]through linear regression analysis. co morbidities due to SARS-COV-2 infection for different chronic diseases like heart , Lung , Kidney , related chronic failure are analysed by a significant Pearson statistics ( 10 ) are discussed here . The IFR can be realised from mild to hospitalisation under ICU , critical care and finally severity to death( 9,12).
Nebulization Therapy With Umbilical Cord Mesenchymal Stem Cell -Derived Exosomes For COVID-19 Pneumonia
Authors: Chu Meiping , Wang Hao , Bian Linjie , Huang Jiehui , Wu Danping , Fei Fangli , Zhang Ruiting , Chen Yigang , Xia Jiazeng 
Published: February 2021

Abstract
Background: Scientists have been facing numerous challenges in the development of an effective therapeutic strategy for the treatment of COVID-19 pneumonia. Several studies have suggested that improving patient immunity and reducing lung injury induced by SARS-CoV-2 may be effective for treating patients with COVID-19.Methods: A pilot trial of nebulization therapy with exosomes of mesenchymal stem cells (MSCs) was performed on seven patients with COVID-19 pneumonia. Exosomes secreted from MSCs were collected and purified using multiple ultrafiltration steps. All patients were treated with nebulization of MSC-derived exosomes, and primary safety and efficacy outcomes were evaluated.Results: Our clinical study demonstrated that nebulization of MSC-derived exosomes is a novel method that might be utilized in the treatment of COVID-19 pneumonia. Nebulization of MSC-derived exosomes did not induce acute allergic or secondary allergic reactions but did promote the absorption of pulmonary lesions and reduce the time of hospitalization for mild cases of COVID-19 pneumonia.Conclusions: Nebulization of MSC-derived exosomes is a safe, effective, and simple method, and their application at the beginning of treatment may be more beneficial.Trial registration: Chinese Clinical Trial Registry, ChiCTR2000030261. Registered on 26 February 2020 – Retrospective registered, http://www.chictr.org.cn
Improving sand flow rate measurement using the wavelet transform and ultrasonic sensors
Authors: Seraj H. , Evans B. , Sarmadivaleh M. 
Published: February 2021

Abstract
Accurate sand flow rate measurement is needed to minimize the side effects of sand production in gas fields. There are concerns about the accuracy of sand flow measurement using the sand measuring devices available on the market. In this paper, ultrasonic sensors and discrete wavelet transform signal analysis method is used to measure the sand flow rate. It is found that the strength of the discrete wavelet coefficients in the frequency range of 15–62 kHz has a linear relationship with sand flow rate. This finding provides a new methodology to accurately measure sand flow rate. The proposed method does not need fluid velocity as a prerequisite for sand rate measurement, so it greatly simplifies the system design when flow meters are not used for fluid velocity measurement. Also, this method has a much simpler calibration procedure compared to that of the sand detectors commonly used in the industry.
Dental Orthopedic Morbidity Among Drafted Men Residing in Ivano-Frankivsk Region
Authors: Rachinsky Sergey , Labynets Olha , Schnayder Stanislav , Dieva Tetiana , Labunets Vasyl 
Published: February 2021

The objective of the research was to establish the level of dental orthopedic morbidity among draftees in the western region of Ukraine.
Materials and Methods. A clinical dental examination of 294 drafted men residing in Ivano-Frankivsk region was carried out; among them, there were 185 urban residents and 109 rural residents.
Results. There were established a quite high prevalence of dental orthopedic morbidity and intensity of its development, especially among rural residents - 275.7 and 522.9 people per 1,000 population among urban and rural residents, respectively. The amount of orthopedic care in terms of total number of dentition defects and the teeth with destroyed coronal portion requiring orthopedic treatment, was found to be 2.4 times greater among rural residents as compared to urban ones and reached 1899.1 versus 787.6 defects, respectively. There was determined the identical structure of dentition defects among both urban and rural residents; bounded edentulous spaces accounted for 100% of cases, the absence of one tooth was observed in 92.3% of cases.
Conclusions. The urgent need for a radical reform of the system for providing comprehensive orthopedic care to drafted men with a mandatory active dispensary registration was substantiated.
Measuring Criterion Validity of Microinteraction Ecological Momentary Assessment (Micro-EMA): Exploratory Pilot Study With Physical Activity Measurement
Authors: Ponnada Aditya , Thapa-Chhetry Binod , Manjourides Justin , Intille Stephen 
Published: February 2021

Background
Ecological momentary assessment (EMA) is an in situ method of gathering self-report on behaviors using mobile devices. In typical phone-based EMAs, participants are prompted repeatedly with multiple-choice questions, often causing participation burden. Alternatively, microinteraction EMA (micro-EMA or μEMA) is a type of EMA where all the self-report prompts are single-question surveys that can be answered using a 1-tap glanceable microinteraction conveniently on a smartwatch. Prior work suggests that μEMA may permit a substantially higher prompting rate than EMA, yielding higher response rates and lower participation burden. This is achieved by ensuring μEMA prompt questions are quick and cognitively simple to answer. However, the validity of participant responses from μEMA self-report has not yet been formally assessed.

Objective
In this pilot study, we explored the criterion validity of μEMA self-report on a smartwatch, using physical activity (PA) assessment as an example behavior of interest.

Methods
A total of 17 participants answered 72 μEMA prompts each day for 1 week using a custom-built μEMA smartwatch app. At each prompt, they self-reported whether they were doing sedentary, light/standing, moderate/walking, or vigorous activities by tapping on the smartwatch screen. Responses were compared with a research-grade activity monitor worn on the dominant ankle simultaneously (and continuously) measuring PA.

Results
Participants had an 87.01% (5226/6006) μEMA completion rate and a 74.00% (5226/7062) compliance rate taking an average of only 5.4 (SD 1.5) seconds to answer a prompt. When comparing μEMA responses with the activity monitor, we observed significantly higher (P<.001) momentary PA levels on the activity monitor when participants self-reported engaging in moderate+vigorous activities compared with sedentary or light/standing activities. The same comparison did not yield any significant differences in momentary PA levels as recorded by the activity monitor when the μEMA responses were randomly generated (ie, simulating careless taps on the smartwatch).

Conclusions
For PA measurement, high-frequency μEMA self-report could be used to capture information that appears consistent with that of a research-grade continuous sensor for sedentary, light, and moderate+vigorous activity, suggesting criterion validity. The preliminary results show that participants were not carelessly answering μEMA prompts by randomly tapping on the smartwatch but were reporting their true behavior at that moment. However, more research is needed to examine the criterion validity of μEMA when measuring vigorous activities.
Online Medical Record Nonuse Among Patients: Data Analysis Study of the 2019 Health Information National Trends Survey
Authors: Elkefi Safa , Yu Zhongyuan , Asan Onur 
Published: February 2021

Background
Online medical records are being used to organize processes in clinical and outpatient settings and to forge doctor-patient communication techniques that build mutual understanding and trust.

Objective
We aimed to understand the reasons why patients tend to avoid using online medical records and to compare the perceptions that patients have of online medical records based on demographics and cancer diagnosis.

Methods
We used data from the Health Information National Trends Survey Cycle 3, a nationally representative survey, and assessed outcomes using descriptive statistics and chi-square tests. The patients (N=4328) included in the analysis had experienced an outpatient visit within the previous 12 months and had answered the online behavior question regarding their use of online medical records.

Results
Patients who were nonusers of online medical records consisted of 58.36% of the sample (2526/4328). The highest nonuser rates were for patients who were Hispanic (460/683, 67.35%), patients who were non-Hispanic Black (434/653, 66.46%), and patients who were older than 65 years (968/1520, 63.6%). Patients older than 65 years were less likely to use online medical records (odds ratio [OR] 1.51, 95% CI 1.24-1.84, P<.001). Patients who were White were more likely to use online medical records than patients who were Black (OR 1.71, 95% CI 1.43-2.05, P<.001) or Hispanic (OR 1.65, 95% CI 1.37-1.98, P<.001). Patients who were diagnosed with cancer were more likely to use online medical records compared to patients with no cancer (OR 1.31, 95% CI 1.11-1.55, 95% CI 1.11-1.55, P=.001). Among nonusers, older patients (≥65 years old) preferred speaking directly to their health care providers (OR 1.76, 95% CI 1.35-2.31, P<.001), were more concerned about privacy issues caused by online medical records (OR 1.79, 95% CI 1.22-2.66, P<.001), and felt uncomfortable using the online medical record systems (OR 10.55, 95% CI 6.06-19.89, P<.001) compared to those aged 18-34 years. Patients who were Black or Hispanic were more concerned about privacy issues (OR 1.42, 1.09-1.84, P=.007).

Conclusions
Studies should consider social factors such as gender, race/ethnicity, and age when monitoring trends in eHealth use to ensure that eHealth use does not induce greater health status and health care disparities between people with different backgrounds and demographic characteristics.
Usability of a Fall Risk mHealth App for People With Multiple Sclerosis: Mixed Methods Study
Authors: Hsieh Katherine , Fanning Jason , Frechette Mikaela , Sosnoff Jacob 
Published: February 2021

Background
Multiple sclerosis (MS) is a chronic, neurodegenerative disease that causes a range of motor, sensory, and cognitive symptoms. Due to these symptoms, people with MS are at a high risk for falls, fall-related injuries, and reductions in quality of life. There is no cure for MS, and managing symptoms and disease progression is important to maintain a high quality of life. Mobile health (mHealth) apps are commonly used by people with MS to help manage their health. However, there are limited health apps for people with MS designed to evaluate fall risk. A fall risk app can increase access to fall risk assessments and improve self-management. When designing mHealth apps, a user-centered approach is critical for improving use and adoption.

Objective
The purpose of this study is to undergo a user-centered approach to test and refine the usability of the app through an iterative design process.

Methods
The fall risk app Steady-MS is an extension of Steady, a fall risk app for older adults. Steady-MS consists of 2 components: a 25-item questionnaire about demographics and MS symptoms and 5 standing balance tasks. Data from the questionnaire and balance tasks were inputted into an algorithm to compute a fall risk score. Two iterations of semistructured interviews (n=5 participants per iteration) were performed to evaluate usability. People with MS used Steady-MS on a smartphone, thinking out loud. Interviews were recorded, transcribed, and developed into codes and themes. People with MS also completed the System Usability Scale.

Results
A total of 3 themes were identified: intuitive navigation, efficiency of use, and perceived value. Overall, the participants found Steady-MS efficient to use and useful to learn their fall risk score. There were challenges related to cognitive overload during the balance tasks. Modifications were made, and after the second iteration, people with MS reported that the app was intuitive and efficient. Average System Usability Scale scores were 95.5 in both iterations, representing excellent usability.

Conclusions
Steady-MS is the first mHealth app for people with MS to assess their overall risk of falling and is usable by a subset of people with MS. People with MS found Steady-MS to be usable and useful for understanding their risk of falling. When developing future mHealth apps for people with MS, it is important to prevent cognitive overload through simple and clear instructions and present scores that are understood and interpreted correctly through visuals and text. These findings underscore the importance of user-centered design and provide a foundation for the future development of tools to assess and prevent scalable falls for people with MS. Future steps include understanding the validity of the fall risk algorithm and evaluating the clinical utility of the app.
Understanding Concerns, Sentiments, and Disparities Among Population Groups During the COVID-19 Pandemic Via Twitter Data Mining: Large-scale Cross-sectional Study
Authors: Zhang Chunyan , Xu Songhua , Li Zongfang , Hu Shunxu 
Published: February 2021

BackgroundSince the beginning of the COVID-19 pandemic in late 2019, its far-reaching impacts have been witnessed globally across all aspects of human life, such as health, economy, politics, and education. Such widely penetrating impacts cast significant and profound burdens on all population groups, incurring varied concerns and sentiments among them.ObjectiveThis study aims to identify the concerns, sentiments, and disparities of various population groups during the COVID-19 pandemic through a cross-sectional study conducted via large-scale Twitter data mining infoveillance.MethodsThis study consisted of three steps: first, tweets posted during the pandemic were collected and preprocessed on a large scale; second, the key population attributes, concerns, sentiments, and emotions were extracted via a collection of natural language processing procedures; third, multiple analyses were conducted to reveal concerns, sentiments, and disparities among population groups during the pandemic. Overall, this study implemented a quick, effective, and economical approach for analyzing population-level disparities during a public health event. The source code developed in this study was released for free public use at GitHub.ResultsA total of 1,015,655 original English tweets posted from August 7 to 12, 2020, were acquired and analyzed to obtain the following results. Organizations were significantly more concerned about COVID-19 (odds ratio [OR] 3.48, 95% CI 3.39-3.58) and expressed more fear and depression emotions than individuals. Females were less concerned about COVID-19 (OR 0.73, 95% CI 0.71-0.75) and expressed less fear and depression emotions than males. Among all age groups (ie, ≤18, 19-29, 30-39, and ≥40 years of age), the attention ORs of COVID-19 fear and depression increased significantly with age. It is worth noting that not all females paid less attention to COVID-19 than males. In the age group of 40 years or older, females were more concerned than males, especially regarding the economic and education topics. In addition, males 40 years or older and 18 years or younger were the least positive. Lastly, in all sentiment analyses, the sentiment polarities regarding political topics were always the lowest among the five topics of concern across all population groups.ConclusionsThrough large-scale Twitter data mining, this study revealed that meaningful differences regarding concerns and sentiments about COVID-19-related topics existed among population groups during the study period. Therefore, specialized and varied attention and support are needed for different population groups. In addition, the efficient analysis method implemented by our publicly released code can be utilized to dynamically track the evolution of each population group during the pandemic or any other major event for better informed public health research and interventions.
Capacidad de mitigación de tres materiales constructivos de acuerdo con su desempeño térmico en Zonas Áridas, Caso de estudio: Torreón, Coahuila
Authors: Quiroa Herrera Jaime Andrés , Villanueva Solís Jorge , González Calderón Alleck Johnnathan , Retana Olvera Alaidé 
Published: February 2021

El principal objetivo del presente artículo es presentar los resultados obtenidos del estudio que se realizó en tres módulos experimentales con los materiales: bloque de tierra comprimida (BTC) como material alternativo; block de concreto como material convencional; y adobe como material tradicional. Para el registro de las temperaturas superficiales y de aire internas de los tres módulos, así como para el monitoreo de la temperatura externa se utilizaron sensores hobo. Para el análisis de datos se utilizó la climatología dinámica en el espacio construido, definiendo el periodo de mediciones, así como el episodio y día representativos para una situación de calor. Los resultados obtenidos muestran cómo el material tradicional es el mejor adaptado a las condiciones climáticas, es decir, el de mayor capacidad de mitigación de los tres casos analizados; también, el material alternativo analizado tuvo mejor desempeño que el convencional, por lo que tanto el adobe como el BTC tienen una capacidad de mitigación mayor al block, además de la viabilidad de la utilización de ambos en la zona de estudio, aprovechando así la mayor capacidad de mitigación que ofrecen estas tecnologías en tierra en zonas áridas.
PENINGKATAN KREATIVITAS SISWA DALAM PEMBELAJARAN MATEMATIKA DENGAN GOOGLE CLASSROOM SEBAGAI KELAS DIGITAL BERBANTUAN APLIKASI GEOGEBRA
Authors: Pianda Didi 
Published: February 2021

Penelitian ini adalah Penelitian Tindakan Kelas yang bertujuan untuk meningkatkan kreativitas siswa Kelas X SMK Negeri 6 Lhokseumawe melalui pendekatan Google Classroom sebagai Kelas Digital dengan Aplikasi Geogebra. Subjek penelitian ini adalah siswa Kelas X-NKPI SMK Negeri 6 Lhokseumawe dengan jumlah 18 orang, Siklus I dilaksanakan selama 4 kali pertemuan dan siklus II dilaksanakan 3 kali pertemuan. Pengambilan data dilakukan dengan menggunakan lembar observasi untuk mengetahui tingkat kreativitas siswa selama pembelajaran berlangsung, angket kreativitas untuk mengetahui tingkat kreativitas siswa setelah pemberian tindakan, dan tes hasil belajar sebagai data tambahan untuk mengetahui sejauh mana peningkatan hasil belajar siswa. Hasil penelitian menunjukkan bahwa (a) skor rata-rata kreativitas siswa pada siklus siklus I sebesar 56,11 dengan kategori rendah dan siklus II 83,22 dengan kategori tinggi (b) nilai rata-rata hasil belajar siswa pada siklus I yaitu 69,72 dari skor ideal 100 dengan kategori hasil belajar sedang sedangkan pada siklus II yaitu 81,22 dari skore ideal 100 dengan kategori hasil belajar tinggi. Dari hasil penelitian ini dapat disimpulkan bahwa dengan diterapkannya pendekatan Google Classroom sebagai Kelas Digital dengan Aplikasi Geogebra maka kreativitas belajar matematika siswa Kelas X-NKPI SMK Negeri 6 Lhokseumawe mengalami peningkatan.
CON VOZ PROPIA: LA EXPERIENCIA FÍSICO-DEPORTIVA DE DOS PERSONAS CON SÍNDROME DE ASPERGER
Authors: González Alba Blas , Prados Megías Esther 
Published: February 2021

O presente trabalho mostra alguns dos resultados derivados do estudo de investigação realizado na tese de doutorado “Pedagogía de la Posibilidad. Estudio narrativo sobre el proceso educativo y resiliente de dos personas diagnosticadas de Síndrome de Asperger”. A partir do enfoque da investigação biográfica narrativa e das análises dos relatos de vida de Isabel e Emmit, abordamos suas respectivas experiências desportivas intra e extraescolares. O objetivo deste trabalho é analisar as potencialidades e debilidades destas práticas como veículos de socialização. Suas narrativas nos transportam a cenários escolares em que a Educação Física tem estado limitada a certos esportes de equipe e a atividades desportivas que não estão adaptadas a suas necessidades motoras e/ou hipersensoriais, e a atividades desportivas extraescolares que em certa medida têm potencializado o desenvolvimento de um processo resiliente. Seus relatos mostram cenários desportivos que por limitações formativas ou desinteresse dos professores não estão adaptados as suas necessidades pessoais e sociais.
Pemodelan Identifikasi Trafik Bittorrent Dengan Pendekatan Correlation Based Feature Selection (CFS) Menggunakan Algoritme Decision Tree (C4.5)
Authors: Yanti Hesmi Aria , Sukoco Heru , Neyman Shelvie Nidya 
Published: February 2021

Abstract— BitTorrent is a P2P file sharing software protocol that allows clients to apply data to other clients and can affect network performance. Bittorent client traffic data collection uses secondary data taken from official sources on the link https://unb.ca/cic/datasets/index.html in 2016. Traffic data is used as a model for BitTorrent traffic identification using feature-based correlation selection (CFS) and traffic analysis model analysis using Decision Tree Algorithm (C4.5). Feature selection is done to clean irrelevant features so that they can affect the results of the accuracy value. The results of feature selection obtained 7 features and 1 category with 244,689 records and the system connecting the rule tree data training model selected the four best accuracy values. Furthermore, the model training data is carried out by testing the BitTorrent traffic trial data. The results of data testing obtained the best BitTorrent traffic accuracy value of 98.82% with 73,406 records on the 30% data test. Keywords— BitTorrent, C4.5 algorithm, correlation based feature selection, traffic identification, modeling.