scholarly journals Accuracy of Non-Exercise Estimated Cardiorespiratory Fitness in Japanese Adults

2021 ◽  
Vol 18 (23) ◽  
pp. 12288
Author(s):  
Robert A. Sloan ◽  
Marco V. Scarzanella ◽  
Yuko Gando ◽  
Susumu S. Sawada
Keyword(s):  
Cardiorespiratory Fitness ◽  
Cycle Ergometer ◽  
Test Results ◽  
Lower Tertile ◽  
Healthcare Settings ◽  
Japanese Adults ◽  
Activity Measures ◽  
Cross Classification ◽  
Using Data

Cardiorespiratory fitness (CRF) is an independent predictor of morbidity and mortality. In Japan, annual physical exams are mandatory in workplace settings, and most healthcare settings have electronic medical records (EMRs). However, in both settings, CRF is not usually determined, thereby limiting the potential for epidemiological investigations using EMR data. PURPOSE: To estimate CRF (mL/kg/min) using variables commonly recorded in EMRs. METHODS: Participants were 5293 Japanese adults (11.7% women) who completed an annual physical exam at a large gas company in Tokyo, Japan, in 2004. The mean age was 48.3 ± 8.0 years. Estimated CRF (eCRF) was based on age, measured body mass index, resting heart rate, systolic and diastolic blood pressure, and smoking. Measured CRF was determined by a submaximal cycle ergometer graded exercise test. RESULTS: Regression models were used for males and females to calculate Pearson’s correlation and regression coefficients. Cross-classification of measured CRF and eCRF was conducted using the lowest quintile, quartile, and tertile as the unfit categories. R’s for eCRF were 0.61 (MD 4.41) for men and 0.64 (MD 4.22) for women. The overall accuracy level was reasonable and consistent across models, yet the unfit lower tertile model provided the best overall model when considering the positive predictive value and sensitivity. CONCLUSION: eCRF may provide a useful method for conducting investigations using data derived from EMRs or datasets devoid of CRF or physical activity measures.

scholarly journals Quantification and Verification of Cardiorespiratory Fitness in Adults with Prehypertension

Sports ◽  
2021 ◽  
Vol 9 (1) ◽  
pp. 9
Author(s):  
Dharini M. Bhammar ◽  
Lung-Chang Chien
Keyword(s):  
Cardiorespiratory Fitness ◽  
Statistical Difference ◽  
Constant Load ◽  
Cycle Ergometer ◽  
Work Rate ◽  
Test Results ◽  
Incremental Test ◽  
Incremental Exercise Test ◽  
Increased Risk ◽  
Verification Test

Background: Low cardiorespiratory fitness is associated with increased risk of hypertension and atherosclerosis in adults with prehypertension. The purpose of this study was to quantify cardiorespiratory fitness and to examine the utility of supramaximal constant-load verification testing for validating maximal oxygen uptake (VO2max) attainment in adults with prehypertension. Methods: Eleven adults (four women) with prehypertension (22.5 ± 2.9 y; body mass index (BMI): 24.6 ± 3.2 kg·m2) underwent an incremental exercise test followed 15 min later by a verification test at 105% of maximal work rate on a cycle ergometer. Results: There was no statistical difference in VO2 between the incremental (2.23 ± 0.54 L·min−1) and verification tests (2.28 ± 0.54 L·min−1; p = 0.180). Only three out of eleven participants had a higher VO2 during the verification when compared with the incremental test. If the verification test had not been conducted, one participant would have been incorrectly classified as having low cardiorespiratory fitness based on incremental test results alone. Conclusions: Verification testing validates the attainment of VO2max and can potentially reduce the over-diagnosis of functional impairment (i.e., deconditioning) in adults with prehypertension.

Perancangan Aplikasi Prediksi Kelulusan Tepat Waktu Bagi Mahasiswa Baru Dengan Teknik Data Mining (Studi Kasus: Data Akademik Mahasiswa STMIK Dipanegara Makassar)

2015 ◽  
Vol 1 (4) ◽  
pp. 270
Author(s):  
Muhammad Syukri Mustafa ◽  
I. Wayan Simpen
Keyword(s):  
Data Mining ◽  
Nearest Neighbor ◽  
Test Results ◽  
K Nearest Neighbor ◽  
Accuracy Rate ◽  
Sample Data ◽  
New Students ◽  
K Nearest Neighbor Algorithm ◽  
Using Data ◽  
Existing Data

Penelitian ini dimaksudkan untuk melakukan prediksi terhadap kemungkian mahasiswa baru dapat menyelesaikan studi tepat waktu dengan menggunakan analisis data mining untuk menggali tumpukan histori data dengan menggunakan algoritma K-Nearest Neighbor (KNN). Aplikasi yang dihasilkan pada penelitian ini akan menggunakan berbagai atribut yang klasifikasikan dalam suatu data mining antara lain nilai ujian nasional (UN), asal sekolah/ daerah, jenis kelamin, pekerjaan dan penghasilan orang tua, jumlah bersaudara, dan lain-lain sehingga dengan menerapkan analysis KNN dapat dilakukan suatu prediksi berdasarkan kedekatan histori data yang ada dengan data yang baru, apakah mahasiswa tersebut berpeluang untuk menyelesaikan studi tepat waktu atau tidak. Dari hasil pengujian dengan menerapkan algoritma KNN dan menggunakan data sampel alumni tahun wisuda 2004 s.d. 2010 untuk kasus lama dan data alumni tahun wisuda 2011 untuk kasus baru diperoleh tingkat akurasi sebesar 83,36%.This research is intended to predict the possibility of new students time to complete studies using data mining analysis to explore the history stack data using K-Nearest Neighbor algorithm (KNN). Applications generated in this study will use a variety of attributes in a data mining classified among other Ujian Nasional scores (UN), the origin of the school / area, gender, occupation and income of parents, number of siblings, and others that by applying the analysis KNN can do a prediction based on historical proximity of existing data with new data, whether the student is likely to complete the study on time or not. From the test results by applying the KNN algorithm and uses sample data alumnus graduation year 2004 s.d 2010 for the case of a long and alumni data graduation year 2011 for new cases obtained accuracy rate of 83.36%.

PENGEMBANGAN PERANGKAT PEMBELAJARAN MENGGUNAKAN PENDEKATAN CONTEXTUAL TEACHING AND LEARNING (CTL) DENGAN INTEGRASI NILAI-NILAI KARAKTER DI SMAN I TUGUMULYO

2014 ◽  
Vol 13 (3) ◽  
Author(s):  
Sri Wahyu Widyaningsih ◽  
Irfan Yusuf
Keyword(s):  
Teaching And Learning ◽  
Lesson Plan ◽  
Development Stage ◽  
Design Stage ◽  
Learning Tools ◽  
Test Results ◽  
Learning Materials ◽  
Is Research ◽  
Efficacy Trials

<p>The research is motivated not yet using CTL approach. In addition, the study provided yet foster the character value of students. This study aimed to the development of learning materials by using CTL approach with the integration of character value are valid, practical, and effective. The type of this research is research and development by using 4-D models. The stages of this research are define, design, and development. The define stage consists of analyzing of curriculum, students, and concept. Then, the learning materials as lesson plan, handout, student’s worksheet, and evaluation, were designed at design stage. The development stage was doing validity, practicality, and effectiveness test. The data of this research was collected by using validation instruments, questionnaire of students and teacher, observation and test instruments. The result of research with validity of the test results showed that the syllabus, lesson plans, teaching materials, worksheets and assessment sheets (cognitive, affective and psychomotor) developed very valid. The test results showed that the learning practicalities developed very practical. Based on the results of efficacy trials, it was stated that the developed learning very effectively used as learning tools are developed to improve the activity and competence of students in the cognitive, affective and psychomotor and behavioral character. And Those, learning materials by using CTL approach with the integration of character values are classification of very valid, very practical, and effective.</p>

scholarly journals UAV Image Multi-Labeling with Data-Efficient Transformers

2021 ◽  
Vol 11 (9) ◽  
pp. 3974
Author(s):  
Laila Bashmal ◽  
Yakoub Bazi ◽  
Mohamad Mahmoud Al Rahhal ◽  
Haikel Alhichri ◽  
Naif Al Ajlan
Keyword(s):  
Data Augmentation ◽  
Feature Representation ◽  
Aerial Image ◽  
Remote Sensing Images ◽  
Training Set ◽  
Proposed Model ◽  
Class Labels ◽  
Using Data ◽  
Uav Image

In this paper, we present an approach for the multi-label classification of remote sensing images based on data-efficient transformers. During the training phase, we generated a second view for each image from the training set using data augmentation. Then, both the image and its augmented version were reshaped into a sequence of flattened patches and then fed to the transformer encoder. The latter extracts a compact feature representation from each image with the help of a self-attention mechanism, which can handle the global dependencies between different regions of the high-resolution aerial image. On the top of the encoder, we mounted two classifiers, a token and a distiller classifier. During training, we minimized a global loss consisting of two terms, each corresponding to one of the two classifiers. In the test phase, we considered the average of the two classifiers as the final class labels. Experiments on two datasets acquired over the cities of Trento and Civezzano with a ground resolution of two-centimeter demonstrated the effectiveness of the proposed model.

scholarly journals Confinement, partial sleep deprivation and defined physical activity–influence on cardiorespiratory regulation and capacity

2021 ◽  
Author(s):  
Jessica Koschate ◽  
Uwe Drescher ◽  
Uwe Hoffmann
Keyword(s):  
Physical Activity ◽  
Cardiorespiratory Fitness ◽  
Space Mission ◽  
Cycle Ergometer ◽  
Work Rate ◽  
Binary Sequences ◽  
Kinetics Parameters ◽  
Slow Heart Rate ◽  
Partial Sleep Deprivation ◽  
Sleep Schedule

Abstract Introduction Adequate cardiorespiratory fitness is of utmost importance during spaceflight and should be assessable via moderate work rate intensities, e.g., using kinetics parameters. The combination of restricted sleep, and defined physical exercise during a 45-day simulated space mission is expected to slow heart rate (HR) kinetics without changes in oxygen uptake ($${\dot{\text{V}}\text{O}}_{{2}}$$ V ˙ O 2 ) kinetics. Methods Overall, 14 crew members (9 males, 5 females, 37 ± 7 yrs, 23.4 ± 3.5 kg m−2) simulated a 45-d-mission to an asteroid. During the mission, the sleep schedule included 5 nights of 5 h and 2 nights of 8 h sleep. The crew members were tested on a cycle ergometer, using pseudo-random binary sequences, changing between 30 and 80 W on day 8 before (MD-8), day 22 (MD22) and 42 (MD42) after the beginning and day 4 (MD + 4) following the end of the mission. Kinetics information was assessed using the maxima of cross-correlation functions (CCFmax). Higher CCFmax indicates faster responses. Results CCFmax(HR) was significantly (p = 0.008) slower at MD-8 (0.30 ± 0.06) compared with MD22 (0.36 ± 0.06), MD42 (0.38 ± 0.06) and MD + 4 (0.35 ± 0.06). Mean HR values during the different work rate steps were higher at MD-8 and MD + 4 compared to MD22 and MD42 (p < 0.001). Discussion The physical training during the mission accelerated HR kinetics, but had no impact on mean HR values post mission. Thus, HR kinetics seem to be sensitive to changes in cardiorespiratory fitness and may be a valuable parameter to monitor fitness. Kinetics and capacities adapt independently in response to confinement in combination with defined physical activity and sleep.

scholarly journals Physical Activity, Sedentary Behavior, and Cardiorespiratory Fitness in Hazardous and Non-Hazardous Alcohol Consumers

2021 ◽  
pp. 089011712098583
Author(s):  
Mats Hallgren ◽  
Davy Vancampfort ◽  
Thi-Thuy-Dung Nguyen ◽  
Elin Ekblom-Bak ◽  
Peter Wallin ◽  
...  
Keyword(s):  
Physical Activity ◽  
Sedentary Behavior ◽  
Cardiorespiratory Fitness ◽  
Leisure Time ◽  
Health Assessment ◽  
Cross Sectional Study ◽  
Cycle Ergometer ◽  
Cross Sectional ◽  
Physically Active ◽  
Alcohol Abstainers

Purpose: To describe physical activity habits, sedentary behavior, and cardiorespiratory fitness levels among alcohol abstainers, hazardous and non-hazardous drinkers. Design: Cross-sectional study with data collected between 2017-19. Setting: Sweden. Subjects: Adults aged 18-65 years (n = 47,559; 59.4% male). Measures: During a routine health assessment, participants answered validated single-item questions regarding: habitual physical activity, structured exercise, and the percentage of time spent sedentary during leisure-time (past 30 days), and completed a 6-minute cycle ergometer test (V02max) to determine cardiorespiratory fitness (CRF). Participants were categorized as alcohol abstainers, non-hazardous drinkers or hazardous drinkers (low/high) based on the Alcohol Use Disorders Identification Test (AUDIT-C) cut-points for men and women. Analysis: Logistic regression models stratified by sex and age. Results: Compared to non-hazardous drinkers, the heaviest drinkers were less physically active (males: OR = 1.38, CI = 1.13-1.67, p = .001; females: OR = 1.41, CI = 1.01-1.97, p = .040) and more sedentary during leisure time (males: OR = 1.94, CI = 1.62-2.32, p = .000; females: OR = 1.62, CI = 1.21-2.16, p = .001). Apart from young females, the heaviest drinkers also did less structured exercise than non-hazardous drinkers (males: OR = 1.22, CI = 1.15-1.51, p = .000; females: OR = 1.43, CI = 1.15-1.78, p = .001). The strongest associations were seen among adults aged 40-65 years (shown here). High-hazardous drinking was associated with low CRF among older males only (OR = 1.19, CI = 1.00-1.41). Conclusion: Middle-aged adults with AUDIT-C scores of ≥6 (women) and ≥7 (men) were less physically active and more sedentary during leisure time and may be appropriate targets for physical activity interventions.

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