Establishment of virtual education classes as an effort to prevent stunting in Sutera Village, Sukadana District

Sutera Village is one of the villages with a high stunting rate located in North Kayong Regency. The stunting cadres that had been formed previously were unable to carry out their duties due to the Covid-19 pandemic. Finally, the prevention model on stunting nutrition problems in the Covid-19 pandemic era was created with the idea of ​​forming virtual classes for stunting cadres through various communication applications using video. The purpose of this community service is to create educational media for cadres as an effort for stunting prevention in Sutera Village, Sukadana District, North Kayong Regency. Education model was carried out with direct learning and virtual with promotional media such as nutritional calendars, learning books, games, educational materials, stunting symptom forms, and video tutorials for monitoring child nutrition. The Wilcoxon test shows the p-value of 0.004 for the knowledge variable and 0.016 for attitude. So, it was concluded that there was an increase in knowledge and attitudes. In other words, the establishment of virtual education classes as an effort to prevent stunting in Sutera Village, Sukadana District, North Kayong Regency is effective in increasing the knowledge and attitudes of stunting cadres.

Early Warning System for Penalty Constrained Financial Risks of Enterprises under Diversified Investment

Based on the understanding of the main types and purposes of enterprise diversification investment, this paper conducts an in-depth analysis of the environmental, structural, and scale risks of enterprise diversification investment and uses this as the basis for the effective construction of a risk prevention model. It can help enterprises effectively avoid investment risks, avoid bringing huge economic losses to enterprises, and help lay a good foundation for the positive development of enterprises. With the rapid development of social economy, enterprises must realize diversified investment if they want to improve their market economy status. However, due to many factors, they face greater economic risks and even cause serious economic losses to enterprises. Therefore, effective measures must be taken to prevent risks and promote the sustainable development of enterprises so as to obtain more economic benefits.

Online University Students’ Perceptions on the Awareness of, Reasons for, and Solutions to Plagiarism in Higher Education: The Development of the AS&P Model to Combat Plagiarism

Academic plagiarism has remained a major concern for higher education institutions, as it hampers not only the quality of the teaching-learning process and research, but also the overall educational institution. This issue appears to be even more serious in online and distance education institutions. As a result, a qualitative study was conducted on an online university in Pakistan to investigate the determinants of academic plagiarism and to find ways to address this issue. The students were given an open-ended questionnaire to reflect their opinions on the awareness and understanding of plagiarism, its determinants, and ways to address it. The findings revealed that most of the 267 online university students had a poor awareness and understanding of plagiarism. Major reasons for students’ plagiarism turned out to be a lack of a proactive approach to create awareness, an omission of citation conventions from course content, untrained teachers, a lack of strict penalties and their proper implementation, poor time management, a fear of failure, a lack of confidence, laziness, and a culture of plagiarism. The study proposes the Awareness, Support, and Prevention model (AS&P model) to address this issue in higher education institutions.

Suppression of Bone Necrosis around Tooth Extraction Socket in a MRONJ-like Mouse Model by E-rhBMP-2 Containing Artificial Bone Graft Administration

Medication-related osteonecrosis of the jaw (MRONJ) is related to impaired bone healing conditions in the maxillomandibular bone region as a complication of bisphosphonate intake. Although there are several hypotheses for the onset of MRONJ symptoms, one of the possible causes is the inhibition of bone turnover and blood supply leading to bone necrosis. The optimal treatment strategy for MRONJ has not been established either. BMP-2, a member of the TGF-β superfamily, is well known for regulating bone remodeling and homeostasis prenatally and postnatally. Therefore, the objectives of this study were to evaluate whether cyclophosphamide/zoledronate (CY/ZA) induces necrosis of the bone surrounding the tooth extraction socket, and to examine the therapeutic potential of BMP-2 in combination with the hard osteoinductive biomaterial, β-tricalcium phosphate (β-TCP), in the prevention and treatment of alveolar bone loss around the tooth extraction socket in MRONJ-like mice models. First, CY/ZA was intraperitoneally administered for three weeks, and alveolar bone necrosis was evaluated before and after tooth extraction. Next, the effect of BMP-2/β-TCP was investigated in both MRONJ-like prevention and treatment models. In the prevention model, CY/ZA was continuously administered for four weeks after BMP-2/β-TCP transplantation. In the treatment model, CY/ZA administration was suspended after transplantation of BMP-2/β-TCP. The results showed that CY/ZA induced a significant decrease in the number of empty lacunae, a sign of bone necrosis, in the alveolar bone around the tooth extraction socket after tooth extraction. Histological analysis showed a significant decrease in the necrotic alveolar bone around tooth extraction sockets in the BMP-2/β-TCP transplantation group compared to the non-transplanted control group in both MRONJ-like prevention and treatment models. However, bone mineral density, determined by micro-CT analysis, was significantly higher in the BMP-2/β-TCP transplanted group than in the control group in the prevention model only. These results clarified that alveolar bone necrosis around tooth extraction sockets can be induced after surgical intervention under CY/ZA administration. In addition, transplantation of BMP-2/β-TCP reduced the necrotic alveolar bone around the tooth extraction socket. Therefore, a combination of BMP-2/β-TCP could be an alternative approach for both prevention and treatment of MRONJ-like symptoms.

Tracking Changes of Social Distancing in the United States of America after Outbreak of Coronavirus Disease (COVID-19) at the Early Stage

Objectives: This research examines social distancing changes over time, and by region of the United States after the COVID-19 pandemic began. Methods: We utilized information on social distancing from the Google Community Mobility Reports. We performed one-way repeated-measure analysis of variance (RM-ANOVA) to examine the overall changes in the 6 types of social distancing from baseline to the 12-week follow-up (March 1 to May 24, 2020). We applied a 2-way RM-ANOVA to evaluate the effects of time and 4 regions on social distancing. Results: According to one-way RM-ANOVA results, social distancing tended to increase until Time 3 (March 30 to April 12) and 4 (April 13 to April 26), before decreasing again, regardless of the area. The 2-way RM-ANOVA results revealed that the social distancing variations in the 6 area types over time were statistically significant in each region, along with the interaction of regions and time. Compared to other regions, social distancing was the highest in the Northeast area, except in park areas. Conclusions: We found that social distancing can be influenced not only by contagion changes, but also by regional differences. Understanding the features of social distancing can play a significant role in helping society build a promising COVID-19 prevention model.

A Study on an Enhanced Autonomous Driving Simulation Model Based on Reinforcement Learning Using a Collision Prevention Model

This paper set out to revise and improve existing autonomous driving models using reinforcement learning, thus proposing a reinforced autonomous driving prediction model. The paper conducted training for a reinforcement learning model using DQN, a reinforcement learning algorithm. The main aim of this paper was to reduce the time spent on training and improve self-driving performance. Rewards for reinforcement learning agents were developed to mimic human driving behavior as much as possible. High rewards were given for greater distance travelled within lanes and higher speed. Negative rewards were given when a vehicle crossed into other lanes or had a collision. Performance evaluation was carried out in urban environments without pedestrians. The performance test results show that the model with the collision prevention model exhibited faster performance improvement within the same time compared to when the model was not applied. However, vulnerabilities to factors such as pedestrians and vehicles approaching from the side were not addressed, and the lack of stability in the definition of compensation functions and limitations with respect to the excessive use of memory were shown.

Understanding Resilience Optimization Architectures With an Optimization Problem Repository

Optimizing a system’s resilience can be challenging, especially when it involves considering both the inherent resilience of a robust design and the active resilience of a health management system to a set of computationally-expensive hazard simulations. While prior work has developed specialized architectures to effectively and efficiently solve combined design and resilience optimization problems, the comparison of these architectures has been limited to a single case study. To further study resilience optimization formulations, this work develops a problem repository which includes previously-developed resilience optimization problems and additional problems presented in this work: a notional system resilience model, a pandemic response model, and a cooling tank hazard prevention model. This work then uses models in the repository at large to understand the characteristics of resilience optimization problems and study the applicability of optimization architectures and decomposition strategies. Based on the comparisons in the repository, applying an optimization architecture effectively requires understanding the alignment and coupling relationships between the design and resilience models, as well as the efficiency characteristics of the algorithms. While alignment determines the necessity of a surrogate of resilience cost in the upper-level design problem, coupling determines the overall applicability of a sequential, alternating, or bilevel structure. Additionally, the application of decomposition strategies is dependent on there being limited interactions between variable sets, which often does not hold when a resilience policy is parameterized in terms of actions to take in hazardous model states rather than specific given scenarios.