Falling is one of the most critical outcomes of loss of consciousness during triage in emergency department (ED). It is an important sign requires an immediate medical intervention. This paper presents a computer vision-based fall detection model in ED. In this study, we hypothesis that the proposed vision-based triage fall detection model provides accuracy equal to traditional triage system (TTS) conducted by the nursing team. Thus, to build the proposed model, we use MoveNet, a pose estimation model that can identify joints related to falls, consisting of 17 key points. To test the hypothesis, we conducted two experiments: In the deep learning (DL) model we used the complete feature consisting of 17 keypoints which was passed to the triage fall detection model and was built using Artificial Neural Network (ANN). In the second model we use dimensionality reduction Feature-Reduction for Fall model (FRF), Random Forest (RF) feature selection analysis to filter the key points triage fall classifier. We tested the performance of the two models using a dataset consisting of many images for real-world scenarios classified into two classes: Fall and Not fall. We split the dataset into 80% for training and 20% for validation. The models in these experiments were trained to obtain the results and compare them with the reference model. To test the effectiveness of the model, a t-test was performed to evaluate the null hypothesis for both experiments. The results show FRF outperforms DL model, and FRF has same accuracy of TTS.

Background: Despite China’s 1.4 billion population and massive investment in improving medical education, there is no transformational national or international course focused on emergency trauma care. In order to overcome recognized deficiencies, we developed an affordable knowledge and skills workshop called Essential Trauma Critical Care China (ETCCC). Methods: Pre-course and post-course MCQs were used to test knowledge and simulation scenarios quantified clinical competence. Structured feedback was obtained. To evaluate the effect of ETCCC on staff performance, we analyzed the clinical records and questioned resuscitation team peers for trauma patients requiring resuscitation room intervention in the 10 consecutive patients before and after the workshops. Results: During 2022–2023, five workshops were delivered to participants from six hospitals in two Chinese provinces. Cost per participant did not exceed US$125. Fifty-eight doctors and 37 nurses participated. For all delegates pre-course knowledge scores increased from mean 35% to 70% post-course. 99% (n = 82/83) participants reached the required standard in the post-course written test. Post-course skills tests scores were mean 67% for doctors and 84% for nurses. Nurses demonstrated significant improvements in the rate and quality of trauma history acquisition as well as triage skills after the course (all p < 0.01). Doctors scored significant improvement in the areas of leadership and teamwork, care of cervical spine, circulation assessment and fluid resuscitation (all p < 0.02). Conclusion: Essential Trauma Critical Care China (ETCCC) is the first economically developed medical educational tool shown to improve performance of emergency room staff. Its success may have relevance for trauma-care education in similar medium-resource environments.

A state of emergency allows authorities to exercise special powers, including the temporary suspension of regular legal provisions and human rights standards. This scenario engenders a conflict between extraordinary powers and the foundational principles of the rule of law. This paper investigates one of the most contentious legal dilemmas concerning emergency powers: whether these powers must be exercised within the bounds of legal constraints. This paper also explores whether ordinary principles of legality apply in situations involving emergency powers. This study aims to examine how this tension is approached from different perspectives. It focuses on discussing the challenges for the rule of law in the state of emergency. It also studies Vietnam’s approach to addressing these challenges during the COVID-19 pandemic.

The question of whether legal gun ownership is a positive security factor in the Czech Republic is subject to expert debate and depends on several factors, including available crime data, public attitudes, and the legal framework. Some argue that legal gun ownership can dissuade criminals because they know victims may be armed. Many advocates argue that the right to own guns is a fundamental right that should be protected. Sometimes, it is difficult to clearly demonstrate that legal gun ownership directly contributes to crime reduction. Statistical data can be interpreted in different ways. In contrast, the presence of guns can in some situations escalate conflicts that could otherwise be resolved nonviolently. In the Czech Republic, legal gun ownership is relatively strictly regulated. Citizens must meet the conditions established by law, including criminal integrity and passing a theoretical-practical examination of professional competence. This regulation aims to ensure that only responsible and qualified individuals own guns. Therefore, the presented article discusses legal gun ownership as an internal factor of state security. Using statistical data, it analyses the amount of violent crime committed with firearms in relation to the possibility of holding and carrying a gun in the conditions of the Czech Republic and in selected EU countries. Furthermore, with the help of a questionnaire survey, it identifies that legal gun ownership can be considered a positive safety factor in certain situations, if it is associated with strict regulation and a responsible attitude of gun owners. The resulting effect on security depends on a combination of legal frameworks, gun culture, and effective law enforcement.

Given the rising threat of terror attacks and the increasing frequency of natural disasters attributed to climate change, enhancing evacuation capacities in various spaces has become crucial for saving lives and accelerating recovery processes. This study investigates the influence of altruistic behavior on evacuation efficiency by developing a social force model that categorizes individuals into three demographic groups: youth, middle-aged, and seniors. Simulation experiments based on the model were conducted to evaluate the impact of altruistic behavior on evacuation efficiency under different conditions, such as evacuation capacity, reliability, and recovery time. The simulation results show that a higher probability of falling leads to longer evacuation times. While an increase in the probability of altruistic behavior improves evacuation efficiency, excessive altruistic behavior causes evacuation times to vary in a zigzag pattern. When the help range exceeds 0.7m, evacuation efficiency fluctuates without a clear trend of improvement.

The continuous escalation of social risks has exacerbated the challenges faced by aging urban communities. In this context, resilience building emerges as a critical approach, offering new perspectives and innovative solutions to address these issues. This paper applies the theories of risk society and resilience governance to establish an analytical framework for resilience governance, specifically examining the current status of resilience construction within the Jin Guang Men community in Xi’an. The findings indicate that resilience building within these aging urban communities is hindered by issues such as weak grassroots governance, deficient repair mechanisms, inadequate infrastructure, and a slow pace of information technology adoption. To effectively manage social risks, it is imperative to strengthen party leadership in governance, enhance community self-repair capacities, upgrade infrastructure, and accelerate the application of information technology. These measures are essential for bolstering the risk management capabilities of aging urban communities.