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Abstract BackgroundThe imperative arises to study the impact of socioeconomic factors on the acceptance of SARS-CoV-2 and influenza vaccines amid changes in immunization policies during the COVID-19 pandemic. ObjectiveTo enhance targeted public health strategies and improve age-specific policies based on identified risk factors, this study investigated the associations between sociodemographic factors and vaccination behaviors during the COVID-19 pandemic, with emphasis on age-specific vaccine cost policies. MethodsThis study analyzed data from the Korean Community Health Survey 2019‐2022 with 507,964 participants to investigate the impact of age-specific policies on vaccination behaviors during the pandemic period. Cohorts aged 19‐64 years and 65 years or older were stratified based on age (years), sociodemographic factors, and health indicators. The cohorts were investigated to assess the influence of relevant risk factors on vaccine acceptance under the pandemic by using weighted odds ratio and ratio of odds ratio (ROR). ResultsAmong 507,964 participants, the acceptance of the SARS-CoV-2 vaccine (COVID-19 vaccine) was higher among individuals with factors possibly indicating higher socioeconomic status, such as higher education level (age 19‐64 years: ROR 1.34; 95% CI 1.27‐1.40 and age ≥65 years: ROR 1.19; 95% CI 1.01‐1.41) and higher income (age 19‐64 years: ROR 1.67; 95% CI 1.58‐1.76 and age ≥65 years: ROR 1.21; 95% CI 1.06‐1.38) for both age cohorts compared to influenza vaccine acceptance before the pandemic. In the context of influenza vaccination during the pandemic, the older cohort exhibited vaccine hesitancy associated with health care mobility factors such as lower general health status (ROR 0.89; 95% CI 0.81‐0.97). ConclusionsSARS-CoV-2 vaccination strategies should focus on reducing hesitancy among individuals with lower social participation. To improve influenza vaccine acceptance during the pandemic, strategies for the younger cohort should focus on individuals with lower social participation, while efforts for the older cohort should prioritize individuals with limited access to health care services.

BackgroundWorldwide, cardiovascular diseases are the primary cause of death, with hypertension as a key contributor. In 2019, cardiovascular diseases led to 17.9 million deaths, predicted to reach 23 million by 2030. ObjectiveThis study presents a new method to predict hypertension using demographic data, using 6 machine learning models for enhanced reliability and applicability. The goal is to harness artificial intelligence for early and accurate hypertension diagnosis across diverse populations. MethodsData from 2 national cohort studies, National Health Insurance Service-National Sample Cohort (South Korea, n=244,814), conducted between 2002 and 2013 were used to train and test machine learning models designed to anticipate incident hypertension within 5 years of a health checkup involving those aged ≥20 years, and Japanese Medical Data Center cohort (Japan, n=1,296,649) were used for extra validation. An ensemble from 6 diverse machine learning models was used to identify the 5 most salient features contributing to hypertension by presenting a feature importance analysis to confirm the contribution of each future. ResultsThe Adaptive Boosting and logistic regression ensemble showed superior balanced accuracy (0.812, sensitivity 0.806, specificity 0.818, and area under the receiver operating characteristic curve 0.901). The 5 key hypertension indicators were age, diastolic blood pressure, BMI, systolic blood pressure, and fasting blood glucose. The Japanese Medical Data Center cohort dataset (extra validation set) corroborated these findings (balanced accuracy 0.741 and area under the receiver operating characteristic curve 0.824). The ensemble model was integrated into a public web portal for predicting hypertension onset based on health checkup data. ConclusionsComparative evaluation of our machine learning models against classical statistical models across 2 distinct studies emphasized the former’s enhanced stability, generalizability, and reproducibility in predicting hypertension onset.

BackgroundOsteoarthritis and rheumatoid arthritis (RA) are prevalent chronic joint disorders, with prevalence rates varying by sex. However, few studies have comprehensively documented the factors contributing to the sex-specific prevalence of osteoarthritis and RA, including sociological factors and the impact of the COVID-19 pandemic. ObjectiveThis study aims to identify long-term trends in the sex-specific prevalence of osteoarthritis and RA from 2005 to 2021 while examining the factors that serve as vulnerabilities specific to each sex within the context of the COVID-19 pandemic. MethodsData were collected from a nationally representative sample of 110,225 individuals through the Korea National Health and Nutrition Examination Survey from 2005 to 2021. The study included patients aged 19 years and older diagnosed with osteoarthritis or RA in South Korea. Data were analyzed using weighted trends to accurately represent the sample population, with a 95% CI. Weighted logistic and regression models were used to identify vulnerable groups at risk of osteoarthritis or RA during the pandemic to assess sex-specific trends. ResultsIn total, 110,225 individuals (n=48,410, 43.92% male participants) were analyzed from 2005 to 2021, with prevalence rates remaining stable over time and higher in female than in male participants. Notably, during the pandemic, female participants aged 60 years and older exhibited a prevalence of osteoarthritis that was 4.92 times greater than male participants and a prevalence of RA that was 6.44 times greater (osteoarthritis: prevalence ratio [PR] 69.78, 95% CI 41.66-116.88; RA: PR 17.27, 95% CI 8.75-34.07). In terms of osteoarthritis, male participants did not show a significant association with BMI (PR 1.40, 95% CI 1.21-1.61; P=.47), whereas female participants exhibited a significantly higher vulnerability within the obese group (PR 1.68, 95% CI 1.55-1.83; P

Background: The COVID-19 pandemic has dramatically altered daily routines and lifestyle behaviors worldwide, potentially significantly impacting physical activity levels, especially among adolescents. Understanding these changes is crucial for developing targeted interventions to promote health and well-being in this vulnerable population. This paper will explore longitudinal trends of physical activities (PA) in Korean adolescents, focusing on changes between the pre and late-COVID-19 pandemic periods. Methods: The data used were from the Korea Youth Risk Behavior Web-Based Survey for consecutive years from 2009 to 2022. In this study, we have separated data into the pre-COVID-19 pandemic (2009–2019) and the pandemic. Following the World Health Organization (WHO)'s guideline, we analyzed adolescent self-reported moderate-to-vigorous physical activity (MVPA) Results: A total of 890,941 adolescents, people aged between 12 and 18 years old. The 14-year trends in MVPA showed an upward trend both before the pandemic (β, 0.005; 95 % confidence interval [CI], 0.004–0.005) and during the pandemic (β, 0.004; 0.002–0.006). Furthermore, the prevalence of MVPA recovered/increased in 2022 (5.61 % in 2020, 5.22 % in 2021, and 6.34 % in 2022). Similar to the MVPA patterns, the mean metabolic equivalent task (MET) score increased during before the pandemic (β, 15.392; 12.523–18.261) and during the pandemic (β, 49.518; 41.948–57.088). However, unlike MVPA patterns, the MET slope changed positively (βdiff, 34.126; 26.031–42.221). Conclusion: Present findings suggest that Korean adolescents achieving the recommended PA levels by the WHO remained steady despite the pandemic. This stability in PA levels during a significant disruption (i.e. the COVID-19 pandemic) is noteworthy and warrants further investigation into the factors that may have contributed to this resilience, including potential influences from various societal and environmental elements.

The maximal Lyapunov exponent (MLE) has been used to quantify the dynamic stability of human locomotion. The method for estimating MLE requires selecting a proper time series of kinematic variables and reconstructing phase space using proper time delay. The data length also affects the reliability of the measured MLE. However, there has been no criterion for the choice of the time series, time delay or data length. Here, we quantified the effect of these factors on the test–retest reliability of MLE estimations. We recruited 15 young and healthy adults and let them walk on a treadmill three times. We calculated MLE employing various lengths of time series of 18 frequently used kinematic variables and two typical choices of time delay: fixed delay and delay selected by average mutual information algorithm. Then, we measured the intraclass correlation coefficient (ICC) of the measured MLE under each condition. Our results show that the choice of time delay does not affect reliability. Five among the 18 kinematic variables enabled excellent reliability with ICC above 0.9 within 450 strides and also enabled ICC above 0.75 even with 60 or less strides. These findings can contribute to establishing the criteria for measuring the dynamic stability of human walking.

BackgroundUnderstanding the association between hypertension prevalence and socioeconomic and behavioral variables during a pandemic is essential, and this analysis should extend beyond short-term trends. ObjectiveThis study aims to examine long-term trends in the prevalence of participants diagnosed with and receiving treatment for hypertension, using data collected by a nationally representative survey from 2009 to 2022, which includes the COVID-19 pandemic era. MethodsA nationwide, population-based, cross-sectional study used data collected from the South Korea Community Health Survey between 2009 and 2022. The study sample comprised 3,208,710 Korean adults over a period of 14 years. We aimed to assess trends in the prevalence of participants diagnosed with and receiving treatment for hypertension in the national population from 2009 to 2022, with a specific focus on the COVID-19 pandemic, using weighted linear regression models. ResultsAmong the included 3,072,546 Korean adults, 794,239 (25.85%) were aged 19-39 years, 1,179,388 (38.38%) were aged 40-59 years; 948,097 (30.86%) were aged 60-79 years, and 150,822 (4.91%) were aged 80 years or older. A total of 1,426,379 (46.42%) were men; 761,896 (24.80%) and 712,264 (23.18%) were diagnosed with and received treatment for hypertension, respectively. Although the overall prevalence over the 14-year period increased, the upward trends of patients diagnosed with and receiving treatment for hypertension decreased during the COVID-19 pandemic era compared with the prepandemic era (β difference for trend during vs before the pandemic –.101, 95% CI –0.107 to –0.094 vs –.133, 95% CI –0.140 to –0.127). Notably, the trends in prevalence during the pandemic were less pronounced in subgroups of older adults (≥60 years old) and individuals with higher alcohol consumption (≥5 days/month). ConclusionsThis nationwide representative study found that the national prevalence of participants diagnosed with and receiving treatment for hypertension increased during the prepandemic era. However, there was a marked decrease in these trends during the prepandemic era, compared with the pandemic era, particularly among specific subgroups at increased risk of negative outcomes. Future studies are needed to evaluate the factors associated with changes in the prevalence of hypertension during the COVID-19 pandemic.

AIM: To analyze the effect of systemic high-dose corticosteroid on the choroid in patients with unilateral optic neuritis. METHODS: A retrospective comparative cohort study. Seventy-six eyes of 38 patients with unilateral optic neuritis that received systemic high-dose corticosteroid treatment were enrolled. Choroidal thickness (CT) and choroidal vascularity index (CVI) were measured in both affected and the fellow eyes at baseline, 1wk, 1 and 3mo. Changes in CT and CVI were analyzed in both eyes and compared between eyes. RESULTS: The mean CT and CVI were 349 μm and 0.70 in the affected eyes and 340 μm and 0.69 in the fellow eyes at baseline (P=0.503 and 0.440, respectively). Decrement of CT and CVI at month 3 were significant in affected eyes (P=0.017 and P

IntroductionMechanical cardiopulmonary resuscitation (CPR) devices are widely used to rescue patients from cardiac arrest. This study aimed to compare hemodynamic effects and resuscitation outcomes between a motor-driven, automatic simultaneous sterno-thoracic cardiopulmonary resuscitation device and the Lund University cardiac arrest system (LUCAS).Material and methodsAfter 2 minutes of electrically induced ventricular fibrillation (VF), Yorkshire pigs (weight 35-60 kg) received CPR with an automatic simultaneous sterno-thoracic CPR device (X-CPR group, n = 13) or the Lund University cardiac arrest system (LUCAS group, n = 12). Basic life support for 6 minutes and advanced cardiovascular life support for 12 minutes, including defibrillation and epinephrine administration, were provided. Hemodynamic parameters and resuscitation outcomes, including return of spontaneous circulation (ROSC), 24-hour survival, and cerebral performance category (CPC) at 24 hours, were evaluated.ResultsHemodynamic parameters, including aortic pressures, coronary perfusion pressure, carotid blood flow, and end-tidal carbon dioxide pressure were not significantly different between the two groups. Resuscitation outcomes were also not significantly different between the groups (X-CPR vs. LUCAS; rate of ROSC: 31% vs 25%, p = 1.000; 24-hour survival rate: 31% vs 17%, p = 0.645; neurological outcome with CPC ≤2: 31% vs 17%, p = 0.645). Also no significant difference in incidence complications associated with resuscitation was found between the groups.ConclusionsCPR with a motor-driven X-CPR and CPR with the LUCAS produced similar hemodynamic effects and resuscitation outcomes in a swine model of cardiac arrest.

Wireless sensor networks (WSNs) are gaining tremendous importance thanks to their broad range of commercial applications. Out of the contemporary fields of research in WSNs, the virtualization of wireless sensor network (VSN) is a brand new research approach. In this age of economic recession, this state-of-the-art technology can provide the opportunity to build an economic business model for application area such as smart home. Building smart home is a big challenge for worldwide increasing elderly populations which are the largest demographic group of developed countries. In this paper, we propose a VSN based business model for implementing smart home for the rapidly growing elderly populations of the world in a cost-effective way. We also propose the virtualization architecture of fully functional sensor node known as sensor gateway router and mathematical model for the embedding of VSN node and link to the physical sensor node and links. Finally, we have implemented and evaluated the sensor virtualization scheme in embedded Linux environment. The evaluation method shows that the virtualization of sensor network technology reduces the overall cost and complexity significantly for the implementation of smart home.

Despite limitations in payload and range, cargo drones have promising applications in emergency logistics and remote delivery. In this study, we tackle these challenges by developing a high-capacity 3.84 kW battery specifically designed for a 50-kg-payload cargo drone operating in demanding terrains. Focusing on the transport of emergency goods, we investigate key drone design aspects and details of the battery pack development, including cell selection, internal configuration, and critical circuits for cell balancing, charging/discharging, and advanced battery management. A key innovation is the integration of a backpropagation artificial neural network (BPANN) algorithm to predict the depth of discharge (DoD) and the state of charge (SoC). Research results show that BPANN offers highly accurate predictions, with error percentages as low as 0.12% for DoD and 0.02% for SoC, ensuring optimized and safe battery operation. Comprehensive field testing is carried out to evaluate the effectiveness of the proposed cell balancing strategy, robust battery management system (BMS), and BPANN implementation. We investigate the drone's performance in terms of DoD, SoC, and overall field operation with the designed battery pack and demonstrate its feasibility and potential for realworld applications. [ABSTRACT FROM AUTHOR]

Background: Insulin resistance is common in individuals with non-alcoholic fatty liver disease (NAFLD). Because insulin resistance is a predictive factor for advanced liver diseases in people with NAFLD, efforts have been made to predict it through anthropometric variables. Recently, neck circumference (NC) has been regarded as a reliable alternative marker for metabolic disorders. This study verified the association between NC and insulin resistance in patients with NAFLD. Methods: We analyzed data from 847 people with NAFLD who participated in the 2019 Korean National Health and Nutrition Examination Survey. NAFLD was defined by a hepatic steatosis index score of =36 points, and insulin resistance was defined by a homeostatic model assessment of insulin resistance score of =2.5 points. Participants were divided according to sex-specific NC tertiles (T1, lowest; T2, middle; T3, highest). Results: In the analysis of the area under the receiver operating characteristic curve (AUC), NC displayed a greater predictive power than body mass index (BMI) for insulin resistance in women (AUC of NC=0.625 vs. AUC of BMI=0.573, P=0.035). NC and the odds ratio (OR) for insulin resistance showed a cubic relationship in both men and women. In the weighted multiple logistic regression analysis, the ORs with 95% confidence intervals for insulin resistance in people with NAFLD in T2 and T3 compared to the reference tertile (T1) were 1.06 (0.47-2.41) and 1.13 (0.41-3.11), respectively, in men and 1.12 (0.64-1.97) and 2.54 (1.19-5.39), respectively, in women, after adjusting for confounding factors. Conclusion: NC was positively correlated with insulin resistance in women with NAFLD. [ABSTRACT FROM AUTHOR]