• Nutrition Research and Practice
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• v.17 no.6
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• pp.1185-1200
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• 2023

BACKGROUND/OBJECTIVES: In the United States, one in every 5 children is obese with greater likelihood in low-income households. The coronavirus disease 2019 (COVID-19) pandemic may have accelerated disparities in child obesity risk factors, such as poor dietary intake and increased sedentary behaviors, among low-income families because of financial difficulties, social isolation and other struggles. This study reveals insights into nutrition and health challenges among low-income families of young children in West Texas to better understand needs and develop interventions. SUBJECTS/METHODS: In-depth individual interviews were performed via Zoom among 11 families of children under the age of 3. A semi-structured interview guide was developed to explore 3 areas: changes in (1) dietary intake and (2) sedentary behaviors and (3) families' preferences regarding a parent nutrition education program. Each interview was audiorecorded, transcribed, and coded using MaxQDA software. RESULTS: Eating together as a family become challenging because of irregular work schedules during the COVID-19 pandemic. Most parents stated that their children's dietary habits shifted with an increased consumption of processed foods. Many parents are unable to afford healthful foods and have utilized food and nutrition assistance programs to help feed their families. All families reported that their children's screen time substantially increased compared to the pre-pandemic times. Moreover, the majority of parents did not associate child screen time with an obesity risk, so this area could be of particular interest for future interventions. Meal preparation ideas, remote modality, and early timing were identified as key intervention strategies. CONCLUSIONS: Online nutrition interventions that emphasize the guidelines for child screen time and regular meal routines will be effective and promising tools to reach low-income parents for early childhood health promotion and obesity prevention.

• Journal of Korean Elementary Science Education
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• v.43 no.1
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• pp.148-157
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• 2024

The purpose of this study was to develop an artificial intelligence-based marine ecological education program to improve the ecological sensitivity of elementary school students. The program was taught 11 times within 4 weeks, and an ecological sensitivity test was conducted before and after the program. The statistical results of the tests showed that the developed program improved the ecological sensitivity of elementary school students. Through in-depth interviews, improvements were found in all the areas, such as empathy for the living things, interest in nature, enjoyment of nature, and wonder about nature. Through the marine ecological classes, which used artificial intelligence and virtual reality, the students were able to get closer to nature, and the student participation activities showed a positive effect on their ecological sensitivity. This indicates that experience-oriented education methods are more effective than simple explanatory classes to improve the students' ecological sensitivity, and artificial intelligence technology proved effective in increasing the students' immersion in the class.

• Journal of Sport and Applied Science
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• v.8 no.1
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• pp.11-17
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• 2024

Purpose: The purpose of the study was to understand a trend of esports in terms of gamers' and fans' perceptions toward esports using social big data. Research design, data, and methodology: In this study, researchers first selected keywords related to esports. Then a total of 10,138 buzz data created at twitter, Facebook, news media, blogs, café and community between November 10, 2022 and November 19, 2023 were collected and analyzed with 'Textom', a big data solution. Results: The results of this study were as follows. Firstly, the news data's main articles were about competitions hosted by local governments and policies to revitalize the gaming industry. Secondly, As a result of esports analysis using Textom, there was a lot of interest in the adoption of the Hangzhou Asian Games as an official event and various esports competitions. As a result of the sentiment analysis, the positive content was related to the development potential of the esports industry, and the negative content was a discussion about the fundamental problem of whether esports is truly a sport. Thirdly, As a result of analyzing social big data on esports and the Olympics, there was hope that it would be adopted as an official event in the Olympics due to its adoption as an official event in the Hangzhou Asian Games. Conclusions: There was a positive opinion that the adoption of esports as an official Olympic event had positive content that could improve the quality of the game, and a negative opinion that games with actions that violate the Olympic spirit, such as murder and assault, should not be adopted as an official Olympic event. Further implications were discussed.

• Analytical Science and Technology
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• v.37 no.2
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• pp.79-86
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• 2024

Among the nutrients in feed, amino acids and minerals are important for the growth and development of pets. In particular, interest in nutritional components related to the health of pets is increasing as pet-raising households and pet food markets have recently grown. Therefore, in this study, 55 pet food products distributed in South Korea were purchased, and the content of 3 essential and conditionally essential amino acids (taurine, lysine, arginine) and 4 minerals (Ca, P, Na, K) was investigated. Among the three amino acids, arginine was found to have the highest content, and the average content was 1.79 and 1.37 % in cat and dog foods, respectively. On the other hand, the taurine content was the lowest, but it was found to be higher than the minimum requirement of 0.10 % for cats set by the American Association for Feed Control (AAFCO) and the European Federation of Pet Food Industries (FEDIAF). As a result of the four-component analysis of minerals, the content of Ca was found to be the highest, and the average content was confirmed to be 1.64 and 1.25 % in cat and dog food, respectively. On the other hand, Na was the lowest, but it was higher than the AAFCO minimum requirement and FEDIAF minimum requirement for young cat and dog food. Among all 55 samples examined, the content of the three amino acids and the four inorganic components was confirmed to be suitable for the recommended minimum intake and maximum allowable intake presented by AAFCO and FEDIAF.

• Journal of Biomedical Engineering Research
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• v.45 no.2
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• pp.90-94
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• 2024

Diagnosing wounds presents a significant challenge in clinical settings due to its complexity and the subjective assessments by clinicians. Wound deep learning algorithms quantitatively assess wounds, overcoming these challenges. However, a limitation in existing research is reliance on specific datasets. To address this limitation, we created a comprehensive dataset by combining open dataset with self-produced dataset to enhance clinical applicability. In the annotation process, machine learning based on Gradient Vector Flow (GVF) was utilized to improve objectivity and efficiency over time. Furthermore, the deep learning model was equipped U-net with residual blocks. Significant improvements were observed using the input dataset with images cropped to contain only the wound region of interest (ROI), as opposed to original sized dataset. As a result, the Dice score remarkably increased from 0.80 using the original dataset to 0.89 using the wound ROI crop dataset. This study highlights the need for diverse research using comprehensive datasets. In future study, we aim to further enhance and diversify our dataset to encompass different environments and ethnicities.

• Journal of Biomedical Engineering Research
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• v.45 no.2
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• pp.95-100
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• 2024

Vitiligo is a condition characterized by the destruction or dysfunction of melanin-producing cells in the skin, resulting in a loss of skin pigmentation. Facial vitiligo, specifically affecting the face, significantly impacts patients' appearance, thereby diminishing their quality of life. Evaluating the efficacy of facial vitiligo treatment typically relies on subjective assessments, such as the Facial Vitiligo Area Scoring Index (F-VASI), which can be time-consuming and subjective due to its reliance on clinical observations like lesion shape and distribution. Various machine learning and deep learning methods have been proposed for segmenting vitiligo areas in facial images, showing promising results. However, these methods often struggle to accurately segment vitiligo lesions irregularly distributed across the face. Therefore, our study introduces a framework aimed at improving the segmentation of vitiligo lesions on the face and providing an evaluation of vitiligo lesions. Our framework for facial vitiligo segmentation and lesion evaluation consists of three main steps. Firstly, we perform face detection to minimize background areas and identify the face area of interest using high-quality ultraviolet photographs. Secondly, we extract facial area masks and vitiligo lesion masks using a semantic segmentation network-based approach with the generated dataset. Thirdly, we automatically calculate the vitiligo area relative to the facial area. We evaluated the performance of facial and vitiligo lesion segmentation using an independent test dataset that was not included in the training and validation, showing excellent results. The framework proposed in this study can serve as a useful tool for evaluating the diagnosis and treatment efficacy of vitiligo.

• Journal of Practical Engineering Education
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• v.16 no.2
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• pp.129-141
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• 2024

In recent times, there has been a shift towards student-centered higher education policies, leading to a growing interest among universities to improve students' learning outcomes. To aid in this endeavor, this study aims to provide guidance for University K to enhance their learning outcome management by comparing and analyzing their learning outcome indicators with those of other domestic and foreign universities. The study examined detailed measurement questions from major learning outcome measurement tools such as AHELO, NSSE, and CLA+. Upon comparison and analysis of University K's major learning outcome indicators with those of other universities, it was found that most of the indicators overlapped. However, some indicators such as student support/facilities for learning, instructor quality, and communication were absent from University K. Therefore, it is crucial to decide whether to add these indicators to the existing learning outcomes or to confirm them through other surveys. Moreover, even for the same indicator, some indicators with different measurement need to consider changing the measurement.

• Journal of Practical Engineering Education
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• v.16 no.2
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• pp.167-177
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• 2024

In nursing education, there has been efforts for enhancing the quality, with a growing interest in the utilization of digital technologies. In clinical training of nursing curriculum, the emphasis on digital technology is pronounced, as it has the potential to offer learners effective and accessible educational experience while enabling the integrated management of individualized learning outcomes. This study developed a digital nursing education platform, allowing educators and learners to select functionalities based on the educational content and characteristics of the learning tools. Additionally, the user interface was designed to facilitate learners' accurate understanding and execution of assigned tasks and objectives. The detailed design and implementation process of the platform are elaborated and then the validation of its usefulness was provided based on feedback from ten educators who are responsible for diverse subjects. The high usability of the digital nursing practicum education platform was confirmed, with potential implications for significant improvements in learner performance. The potential of this digital platform is to lead to innovative shifts in educational methodologies within the field of integrative nursing education.

• Journal of Pharmacopuncture
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• v.27 no.2
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• pp.70-81
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• 2024

Objectives: Cognitive impairments, ranging from mild to severe, adversely affect daily functioning, quality of life, and work capacity. Despite significant efforts in the past decade, more than 200 promising drug candidates have failed in clinical trials. Herbal remedies are gaining interest as potential treatments for dementia due to their long history and safety, making them valuable for drug development. This review aimed to examine the mechanisms behind the effect of Polygonum multiflorum on cognitive function. Methods: This study focused primarily on the effects of Polygonum multiflorum and its chemical constituents on cognitive behavioral outcomes including the Morris water maze, the passive avoidance test, and the Y maze, as well as pathogenic targets of cognitive impairment and Alzheimer's disease (AD) like amyloid deposition, amyloid precursor protein, tau hyperphosphorylation, and cognitive decline. Additionally, a thorough evaluation of the mechanisms behind Polygonum multiflorum's impact on cognitive function was conducted. We reviewed the most recent data from preclinical research done on experimental models, particularly looking at Polygonum multiflorum's effects on cognitive decline and AD. Results: According to recent research, Poligonum multiflorum and its bioactive components, stilbene, and emodin, influence cognitive behavioral results and regulate the pathological target of cognitive impairment and AD. Their mechanisms of action include reducing oxidative and mitochondrial damage, regulating neuroinflammation, halting apoptosis, and promoting increased neurogenesis and synaptogenesis. Conclusion: This review serves as a comprehensive compilation of current experiments on AD and other cognitive impairment models related to the therapeutic effects of Polygonum multiflorum. We believe that these findings can serve as a basis for future clinical trials and have potential applications in the treatment of human neurological disorders.

• The Journal of Advanced Prosthodontics
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• v.16 no.3
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• pp.189-199
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• 2024

PURPOSE. This study was conducted to evaluate the effects of plasma treatment of sandblasted and acid-etched (SLA) titanium implants on surface cleansing and osseointegration in a beagle model. MATERIALS AND METHODS. For morphological analysis and XPS analysis, scanning electron microscope and x-ray photoelectron spectroscopy were used to analyze the surface topography and chemical compositions of implant before and after plasma treatment. For this animal experiment, twelve SLA titanium implants were divided into two groups: a control group (untreated implants) and a plasma group (implants treated with plasma). Each group was randomly located in the mandibular bone of the beagle dog (n = 6). After 8 weeks, the beagle dogs were sacrificed, and volumetric analysis and histometric analysis were performed within the region of interest. RESULTS. In morphological analysis, plasma treatment did not alter the implant surface topography or cause any physical damage. In XPS analysis, the atomic percentage of carbon at the inspection point before the plasma treatment was 34.09%. After the plasma treatment, it was reduced to 18.74%, indicating a 45% reduction in carbon. In volumetric analysis and histometric analysis, the plasma group exhibited relatively higher mean values for new bone volume (NBV), bone to implant contact (BIC), and inter-thread bone density (ITBD) compared to the control group. However, there was no significant difference between the two groups (P > .05). CONCLUSION. Within the limits of this study, plasma treatment effectively eliminated hydrocarbons without changing the implant surface.