Control Situation Research Articles

Validation of a self-perception instrument regarding the experience associated with simulated interprofessional hospital clinical practice

Introduction: clinical simulation is a training method that recreates safe and controlled clinical situations that help develop professional skills and promotes interprofessional collaborative practice through the development of specific competencies.Objective: determine the metric properties of a self-administered questionnaire that accounts for the level of satisfaction with simulated in-hospital clinical practice.Methods: based on expert opinion, an instrument was created that consisted of three dimensions. For statistical validation, it was applied to 291 students belonging to 6 careers distributed in three regions of Chile. Cronbach's Alpha was determined by dimension, in addition to performing a factor analysis to finally develop a standardized index for analysis.Results: a Cronbach's Alpha was obtained in the dimension of Satisfaction with the role of the tutor teacher of 0,928, in that of Satisfaction with the role of the actor/actress of 0,89 and in Satisfaction with the organization and equipment of the CISH of a 0,904. The Factor analysis confirmed the relevance of the questions within the three established dimensions.Conclusions: the developed instrument presented a high internal consistency, being a valid instrument to be applied to students in the area of health sciences in Chile

Synergistic interactions of nanoparticles and plant growth promoting rhizobacteria enhancing soil-plant systems: a multigenerational perspective.

Sustainable food security and safety are major concerns on a global scale, especially in developed nations. Adverse agroclimatic conditions affect the largest agricultural-producing areas, which reduces the production of crops. Achieving sustainable food safety is challenging because of several factors, such as soil flooding/waterlogging, ultraviolet (UV) rays, acidic/sodic soil, hazardous ions, low and high temperatures, and nutritional imbalances. Plant growth-promoting rhizobacteria (PGPR) are widely employed in in-vitro conditions because they are widely recognized as a more environmentally and sustainably friendly approach to increasing crop yield in contaminated and fertile soil. Conversely, the use of nanoparticles (NPs) as an amendment in the soil has recently been proposed as an economical way to enhance the texture of the soil and improving agricultural yields. Nowadays, various research experiments have combined or individually applied with the PGPR and NPs for balancing soil elements and crop yield in response to control and adverse situations, with the expectation that both additives might perform well together. According to several research findings, interactive applications significantly increase sustainable crop yields more than PGPR or NPs alone. The present review summarized the functional and mechanistic basis of the interactive role of PGPR and NPs. However, this article focused on the potential of the research direction to realize the possible interaction of PGPR and NPs at a large scale in the upcoming years.

Near Full-Length Genome Characterization of Two Novel Unique Recombinants (CRF01_AE/CRF07_BC) in Beijing, China.

With the prevalence of human immunodeficiency virus type 1 (HIV-1) CRF01_AE and CRF07_BC subtypes in China, the co-circulation of multiple subtypes in the HIV-1-positive population may result in dual infection or superinfection in the population, leading to the emergence of unique recombinant forms (URFs) of the HIV-1 virus. In this study, two second-generation unique recombinant strains, BI0114 and BI0116, were identified, and their near full-length genome sequences were obtained. Recombination analysis showed that both sequences were isoforms of URF_0107, and they were second-generation unique recombinant strains formed by the recombination of CRF01_AE and CRF07_BC, with the isoforms being CRF01_AE and CRF0107_BC, respectively. The continued emergence of novel CRF01_AE/CRF07_BC recombinant strains suggests that the epidemiological, preventive, and control situation of HIV-1 is complex and that the relevant health authorities urgently need to establish responses to the challenges posed by changes in the pattern of strain recombination.

Impact of activation through bodyweight vs elastic band exercises on jump capacity and dynamic strength

The aim was to analyze the effect of two activation protocols based on exercises with bodyweight and elastic bands on the improvement of muscle power. Ten male university students of Physical Activity and Sports Sciences (age: 23.1±1.5 years) randomly completed with 48 hours of recovery between sessions, a control situation without warm-up (CON) and a warm-up protocol based in bodyweight (ACA) and elastic band (ACE) exercises. After each protocol, power tests were performed in the squat and bench press with submaximal load (i.e., ~1,00m/s and ~0,79m/s, respectively) and vertical jumps without (SJ) and with countermovement (CMJ), together with a horizontal jump (SHB). Compared to CON, no improvements in strength were observed following ACA and ACE. However, significant improvements (p < 0.05) were obtained in SJ, CMJ, and SHB after ACE, while ACA only improved (p < 0.05) SJ and CMJ. Protocols that use exercises with bodyweight or elastic bands can improve performance in actions without load, but do not improve power at submaximal loads.

Current Status of Cognition and Clinical Practice of Refractory Cancer Pain in Shanghai: A Questionnaire Survey.

This study aimed to assess the current status of clinical practice of refractory cancer pain (RCP) among a sample of physicians specializing in cancer pain management in Shanghai. From 2019 to 2021, a questionnaire survey was conducted among physicians engaged in diagnosis and treatment of cancer pain through the questionnaire WJX network platform in Shanghai, China. A total of 238 responses participated in the survey. This survey reports physicians' understanding and incidence rate of breakthrough cancer pain (BTCP). The choice of analgesics and satisfaction of analgesic effect were investigated. We also investigated doctors' knowledge of the diagnostic criteria for RCP and their tendency to choose analgesics. Oral immediate-release morphine and intravenous or subcutaneous morphine injection have been the common treatment approach for transient cancer pain exacerbations. The main barriers to pain management are lack of standardized treatment methods for RCP, lack of knowledge related to RCP, and single drug dosage form. Doctors believe the most necessary measures to improve the current situation of poor cancer pain control include improving medical staff's understanding and treatment techniques for RCP, updating treatment techniques and methods, and improving the configuration of drug types in medical institutions. Clinicians expect to improve understanding and treatment techniques through systematic training. Despite multiple available analgesic measures, the treatment of RCP remains challenging. Improving the understanding of medical staff towards RCP, improving treatment techniques, and increasing the accessibility of multiple drug types are important ways to improve the satisfaction of cancer pain management in the future.

Effect of conditioning activity absolute intensity on seated shot put performance

Conditioning activities are widely used in sports for improving performance in a subsequent main activity. Therefore, understanding the organization of these exercises is important for athletes. Therefore, the objective this study was to evaluate whether the conditioning activity absolute intensity affects the seated shot put performance. Twenty-four physically active male adults were subjected, every 24 hours apart and in a randomized manner, to the following situations: control (no conditioning activity), seat shot 2 kg ball; seated shot 4 kg ball and; seated shot 6 kg ball. Three minutes after these shots, participants performed the seat shot put main activity (4kg). To record the seat shot put performance, the greatest distance of the six attempts was considered. The shot put distance was greater in conditioning activity compared to the control situation (p < .05). There was no difference in shot put distance among conditioning activity situations (p > .05). In addition, individual analysis using typical error showed that 63% of the participants responded positively to the conditioning activities. In conclusion, despite the beneficial effect of the conditioning activity in relation to the control situation, there was no effect of the absolute intensity of the conditioning activity on shot put performance.

Evaluation of a 3M (mistakes, mentoring and mastery) training program for transfer of control situations in a level 2 automated driving system

Drivers must actively supervise automation as it can only function in limited conditions. A failure to supervise the system has negative consequences in terms of missed requests to take over control and may cause crashes or jeopardize safety. The objective of this study is to determine the effect of a novel, 3M (Mistakes, Mentoring and Mastery) training program on drivers’ behavior while using level 2 driving automation systems. To achieve this, 36 participants were assigned randomly to three different training programs (3M training, User manual, and Placebo) and drove through scenarios on a fixed-based driving simulator. The results showed that drivers in the 3M training Group took back control more effectively when the driving automation system reached its limits compared to drivers who received User manual or Placebo training. Drivers in the 3M training Group also had higher situation awareness and improved trust in automation. The results indicate that an interactive approach to training with regards to vehicle automation can help drivers more safely interact with automation systems.

AI 거버넌스의 정의와 쟁점 및 발전 과제: 비판적 관점

In the data-driven economy, AI algorithms will eventually drive power interests and value allocation of scarce resources in terms of who gets what, when, and how. However, to date, the decision-making process and internal mechanisms of algorithm-based AI remain “a black box”. Therefore, a critical systematic analysis of the benefits and limitations of AI’s practical utility and applicability, as well as legal and institutional promotion and control measures to enhance transparency in algorithm design, is needed now more than ever. The current structural situation of human oppression, control, and domination by AI power in the name of techno-engineering-based social innovation and development in the age of digital capitalism requires a multidisciplinary approach to governance that utilizes political science, educational politics, and critical theory perspectives. This paper aims to comprehensively review the emerging AI governance definitions, issues, and development plans from critical perspectives.

A stochastic model for neural progenitor dynamics in the mouse cerebral cortex

We have designed a stochastic model of embryonic neurogenesis in the mouse cerebral cortex, using the formalism of compound Poisson processes. The model accounts for the dynamics of different progenitor cell types and neurons. The expectation and variance of the cell number of each type are derived analytically and illustrated through numerical simulations. The effects of stochastic transition rates between cell types, and stochastic duration of the cell division cycle have been investigated sequentially. The model does not only predict the number of neurons, but also their spatial distribution into deeper and upper cortical layers. The model outputs are consistent with experimental data providing the number of neurons and intermediate progenitors according to embryonic age in control and mutant situations.

Rule Based Mamdani Fuzzy Inference System to Analyze Efficacy of COVID19 Vaccines

INTRODUCTION: COVID-19 was declared as most dangerous disease and even after maintaining so many preventive measures, vaccination is the only preventive option from SARS-CoV-2. Vaccination has controlled the risk and spreading of virus that causes COVID-19. Vaccines can help in preventing serious illness and death. Before recommendation of COVID-19 vaccines, clinical experiments are being conducted with thousands of grown person and children. In controlled situations like clinical trials, efficacy refers to how well a vaccination prevents symptomatic or asymptomatic illness.
 OBJECTIVES: The effectiveness of a vaccine relates to how effectively it works in the actual world.
 METHODS: This research presents a novel approach to model the efficacy of COVID’19 vaccines based on Mamdani Fuzzy system Modelling. The proposed fuzzy model aims to gauge the impact of epidemiological and clinical factors on which the efficacy of COVID’19 vaccines.
 RESULTS: In this study, 8 different aspects are considered, which are classified as efficiency evaluating factors. To prepare this model, data has been accumulated from various research papers, reliable news articles on vaccine response in multiple regions, published journals etc. A set of Fuzzy rules was inferred based on classified parameters. This fuzzy inference system is expected to be of great help in recommending the most appropriate vaccine on the basis of several parameters. 
 CONCLUSION: It aims to give an idea to pharmaceutical manufacturers on how they can improve vaccine efficacy and for the decision making that which one to be followed.

A Clustering Study on the Entrepreneurial Policy Texts of Wenzhou University Students

With the success of the 20th National Congress of the Communist Party of China, Chinese path to modernization, the construction of Zhejiang Demonstration Area for Common Prosperity, rural revitalization, and the new situation of epidemic prevention and control, Wenzhou's economy will usher in a new round of growth. As the birthplace of China's private economy, entrepreneurial consciousness is deeply rooted in this land, and college students, as the new generation of entrepreneurial forces, their entrepreneurial activities will be an important force for Wenzhou's private economy to shine again. The entrepreneurship policy for college students, as an important influencing factor driving entrepreneurial activities, is worth exploring whether it can adapt to the current environment and whether there are areas for optimization. This study collected entrepreneurship policies in Wenzhou over the past 8 years and used the research method of co word clustering analysis to quantitatively study the policies. The results show that Wenzhou is currently committed to establishing and improving a high-quality service system for relevant college student entrepreneurship groups. At the same time, the Wenzhou government has fully realized the predicament of the development of local key industries in Wenzhou and has provided targeted assistance for different entrepreneurial problems.

Study on the Harmfulness of Coal Mine Dust to Human Health and its Prevention and Control Measures

Coal mine production is a special operation with certain occupational hazards. A large amount of coal dustin the production en- vironment poses a great threat to the health of workers and is the main pathogenic factor of miners occupational disease, pneumoconiosis. Pneumoconiosis is the largest and most serious occupational disease in China. Statistical data show that the number of diagnosed cases of pneumoconiosis in China has exceeded 600,000, accounting for more than 90% of the total number of occupational diseases, more than 6000 people die of pneumoconiosis every year, and more than 90% of the new cases of pneumoconiosis occur in coal mines. Therefore, the great harm of coal mine dust and the serious situation of prevention and control of coal mine occupational diseases in China are shown.

Cancer incidence and mortality in China, 2022

Objective: The National Central Cancer Registry estimates the number of new cancer cases and deaths in China in 2022, using incidence and mortality data collected by the National Cancer Center. Methods: According to the data of 700 cancer registries in 2018 and the data of 106 cancer registries from 2010 to 2018, the age-period-cohort model was used to estimate the incidence rate and mortality rate of all cancers and 23 types of cancer in 2022, stratified by gender and urban and rural areas. We estimated the number of new cancer cases and deaths in China in 2022 based on the estimated rate and population data in 2022. Results: The estimated results showed that in 2022, there were approximately 4 824 700 new cancer cases in China (2 533 900 in males and 2 290 800 in females), with an age-standardized incidence rate of Chinese population (ASIR) of 208.58 per 100 000 (212.67 per 100 000 for males and 208.08 per 100 000 for females). Approximately 2 903 900 new cancer cases occurred in urban areas, with an ASIR of 212.95 per 100 000. It was estimated about 1 920 800 new cancer cases in rural areas, and the ASIR was 199.65 per 100 000. The top five cancers (lung cancer 1 060 600, colorectal cancer 517 100, thyroid cancer 466 100, liver cancer 367 700 and female breast cancer 357 200) accounted for 57.4% of all new cases. The estimated number of deaths from cancer in China in 2022 was 2 574 200 (1 629 300 in males and 944 900 in females), with an age-standardized mortality rate of Chinese population (ASMR) of 97.08 per 100 000 (127.70 per 100 000 in males and 68.67 per 100 000 in females). The number of deaths from cancer in urban and rural areas was about 1 400 600 and 1 173 400, with the ASMR of 92.37 and 103.97 per 100 000 in urban and rural areas, respectively. The top five leading cause of cancers death (lung cancer 733 300, liver cancer 316 500, gastric cancer 260 400, colorectal cancer 240 000 and esophageal cancer 187 500) accounted for 67.5% of all cancer deaths. Lung cancer ranked first in the incidence and mortality in men and women. The incidence rate in urban areas was higher than that in rural areas, while the mortality rate was lower than that in rural areas. Conclusions: The burden of cancer in China is still relatively heavy, with significant differences in cancer patterns in gender, urban-rural, and regional. The burden of cancer presents a coexistence of developed and developing countries, and the situation of cancer prevention and control is still serious in China.

Modelling operator control work across traffic management domains: implications for interaction design

Traffic management in aviation, shipping, and rail transport shows similarities and dissimilarities in the work process. For example, they share the temporal aspect, but different levels of urgency in the control work set different requirements on monitoring, decisions, and actions. However, few studies have been presented that model and compare the different domains in terms of temporal decision-making. The Joint Control Framework (JCF) is an approach to analyse and temporally model operators’ control processes from a cognitive systems engineering perspective. In this study, we have used JCF to map, and compare, cognitive joints, such as perceptions, decisions, and actions, in temporally challenging control situations in air traffic control, maritime vessel traffic service, and train traffic management. Data was collected collaboratively with traffic operators, focusing on (1) identifying challenging traffic situations and (2) jointly modelling the temporal decision-making patterns of these situations using simplified JCF. Post-analysis was done by breaking down the results into different processes and comparing domains to ascertain how operators maintain control. An intermediate level of activity—between general monitoring and work with specific vehicles—was identified: processes-in-focus. A shared problem arises in the shift between general monitoring and the processes-in-focus. All processes-in-focus comprise cognitive joint cycles of perceptions, decisions, and actions. However, depending on the framing of processes-in-focus, the patterns of joints, such as temporal extension and complexity, differ. In the remainder of the article, implications for the interaction design, in particular the potential for human–AI/automation teaming with higher levels of automation and cognitive autonomy, are discussed.

Human emissions of size-resolved fluorescent bioaerosols in control situations

Human bioaerosols contribute significantly to indoor air quality. This study used a Wideband Integrated Bioaerosol Sensor (WIBS-4A) instrument for real-time measurement of particle size distribution and count to differentiate fluorescent bioaerosols from non-fluorescent aerosols. Through an experiment involving 12 subjects (six men and six women) wearing standard cotton clothing in a 2 m × 2 m × 2 m environmental chamber, we established a quantitative method to obtain the bioaerosol emission rate of a single subject, aiming to explore the effects of masks and sex on bioaerosol emissions from different individuals. The mean emission rates of fluorescent bioaerosols in the particle size ranges of 0.5–2.5 μm and 2.5–10 μm were 3.192±2.11×104 counts/(person·h) and 13.98±9.34×104 counts/(person·h), respectively. A comparison between those wearing and not wearing masks revealed no significant differences in the emissions of fluorescent bioaerosols. This suggests respiratory sources may not significantly impact the emissions of fluorescent bioaerosols from individuals under seated breathing conditions. Significant disparities in the fluorescent bioaerosol emission rates of different biological sexes were observed through independent sample analysis. Males exhibited 41 % and 15 % higher emission rates than females for particle size ranges of 0.5–2.5 μm and 2.5–10 μm, respectively, possibly because of different metabolic rates. A significant correlation between metabolic rates and fluorescent bioaerosols (sig = 0.044 < 0.05) was observed in all the subjects. These findings underscore the individual variations that affect bioaerosol emission rates. The data provided by this study will facilitate further analysis of the on-site measured data and source analysis.

A Liver Cancer Question-Answering System Based on Next-Generation Intelligence and the Large Model Med-PaLM 2

Chronic diseases are the "number one killer" threatening human life and health. In recent years, the incidence of chronic diseases has been rising, and the trend is younger, and the prevention and control situation is very serious. This study introduces a Liver Cancer Question-Answering System (LCQAS) that leverages next-generation artificial intelligence and the large model Med-PaLM 2 The Med-PaLM 2 medical question answering system, powered by next-generation intelligence and large language models, represents a cutting-edge tool in the healthcare domain. Leveraging advanced artificial intelligence techniques and the capabilities of large language models like Med-PaLM 2, this system aims to provide accurate and comprehensive responses to medical inquiries and queries. With its intuitive interface and contextually relevant answers, LCQAS represents a significant advancement in medical information retrieval for liver cancer management.

A step-by-step guide to include key electroencephalography (EEG) parameters in the study of human performance applied to air traffic control

The study of human performance of air traffic controllers (ATCOs) is an interesting line of research to improve operational safety. In recent years, there has been an increase in the number of techniques available to develop this research based on massive data analysis. This study presents the use of certain electroencephalography (EEG) parameters to study the human performance of ATCOs. Although software and applications are now available to calculate these parameters, there are often problems in understanding the detailed process used to calculate them. The parameters presented in this study are intended to overcome this limitation and are applicable in real air traffic control (ATC) situations. Six parameters are analysed: excitement, stress, relaxation, boredom, engagement, and attention. As an application case for the parameters, a total of 50 data samples obtained during the development of real-time simulations on a highly realistic ATC platform are analysed. From these data, the above-mentioned EEG parameters and their trends are calculated. In addition, the evolution of these parameters is studied in relation to two other variables that characterise the operational situation of the sector during the simulations: the taskload based on ATC events and the number of simultaneous aircraft in the sector per minute.

Modeling temporal dual variations for return air temperature prediction of mK-level temperature-controlled clean chamber

Clean chamber with mK-level temperature stability is required for precision manufacturing and optical equipment to achieve nanoscale manufacturing tolerances and measurement accuracy, however, the equipped precision air conditioning system cannot respond immediately to temperature fluctuation in the chamber due to large time delay. Predicting the future return air temperature gives the control module a prescient ability to act in advance, thus aiding in temperature regulation. To this end, this paper deals with the mK-level temperature prediction problem under a high-precision temperature control situation, and a novel prediction network model dubbed TDVNet is designed based on convolutional neural network (CNN) and gated recurrent unit (GRU), where Temporal Dual Variations of time series data, namely variations-between-phases and variations-across-periods, are modeled to achieve a higher accuracy of return air temperature prediction. Utilizing chamber temperature data collected on-site for model training and evaluation, the experimental results show that capturing data change patterns from dual perspectives has reduced the root mean square error (RMSE) and mean absolute percentage error (MAPE) of the TDVNet model by 21.4% and 24.3%, respectively, compared to the model only capturing the variations-between-phases. Under a signal sampling interval of 10 s and a temperature fluctuation of (66.9 ± 25.8) mK@10min, the TDVNet model can accurately predict the return air temperature change in the next 5 min, and the proportion of prediction errors within 15 mK in the test set can reach over 90.1%.

Development and application of a comprehensive assessment method of regional flood disaster risk based on a refined random forest model using beluga whale optimization

To scientifically characterize regional flood disaster risks, a comprehensive regional flood disaster risk assessment index system was constructed based on the R cluster-factor analysis method. To improve the regional flood disaster risk identification ability, a random forest model refined by the beluga whale optimization (BWO-RF) was proposed. It was applied to the flood disaster risk assessment of the Jiansanjiang Branch of the Beidahuang Agricultural Reclamation Group in Heilongjiang Province, China. The research results show that the constructed BWO-RF model has strong generalization ability and optimization efficiency. The evaluation results have high rationality and stability, which fully demonstrates the applicability of the BWO-RF model in flood disaster risk assessment. On a time scale, the flood risk of the Jiansanjiang Branch shows a clear downward trend. However, due to weak economic development and insufficient water conservancy and flood control planning and construction, the risk of flood disasters fluctuates greatly in the later period, and the prevention and control situation is still not optimistic. On a spatial scale, the risk of flood disasters on farms in the northeast of Jiansanjiang Branch is low, while the risk on farms in the southwest is higher. Future flood control and drainage should focus on this area. The research results provide a technical method system for reference in flood disaster risk assessment and provide valuable information for reducing regional flood disaster risks.

High-density lipoprotein in diabetes: Structural and functional relevance.

Low levels of high-density lipoprotein-cholesterol (HDL-C) is considered a major cardiovascular risk factor. However, recent studies have suggested a more U-shaped association between HDL-C and cardiovascular disease. It has been shown that the cardioprotective effect of HDL is related to the functions of HDL particles rather than their cholesterol content. HDL particles are highly heterogeneous and have multiple functions relevant to cardiometabolic conditions including cholesterol efflux capacity, anti-oxidative, anti-inflammatory, and vasoactive properties. There are quantitative and qualitative changes in HDL as well as functional abnormalities in both type 1 and type 2 diabetes. Non-enzymatic glycation, carbamylation, oxidative stress, and systemic inflammation can modify the HDL composition and therefore the functions, especially in situations of poor glycemic control. Studies of HDL proteomics and lipidomics have provided further insights into the structure-function relationship of HDL in diabetes. Interestingly, HDL also has a pleiotropic anti-diabetic effect, improving glycemic control through improvement in insulin sensitivity and β-cell function. Given the important role of HDL in cardiometabolic health, HDL-based therapeutics are being developed to enhance HDL functions rather than to increase HDL-C levels. Among these, recombinant HDL and small synthetic apolipoprotein A-I mimetic peptides may hold promise for preventing and treating diabetes and cardiovascular disease.