A Data-Driven Context-Aware Health Inference System for Children during School Closures

Many countries have implemented school closures due to the outbreak of the COVID-19 pandemic, which has inevitably affected children's physical and mental health. It is vital for parents to pay special attention to their children's health status during school closures. However, it is difficult for parents to recognize the changes in their children's health, especially without visible symptoms, such as psychosocial functioning in mental health. Moreover, healthcare resources and understanding of the health and societal impact of COVID-19 are quite limited during the pandemic. Against this background, we collected real-world datasets from 1,172 children in Hong Kong during four time periods under different pandemic and school closure conditions from September 2019 to January 2022. Based on these data, we first perform exploratory data analysis to explore the impact of school closures on six health indicators, including physical activity intensity, physical functioning, self-rated health, psychosocial functioning, resilience, and connectedness. We further study the correlation between children's contextual characteristics (i.e., demographics, socioeconomic status, electronic device usage patterns, financial satisfaction, academic performance, sleep pattern, exercise habits, and dietary patterns) and the six health indicators. Subsequently, a health inference system is designed and developed to infer children's health status based on their contextual features to derive the risk factors of the six health indicators. The evaluation and case studies on real-world datasets show that this health inference system can help parents and authorities better understand key factors correlated with children's health status during school closures. © 2023 ACM.

Developing adaptability and agility in leadership amidst the COVID-19 crisis: experiences of early-career school principals

Purpose: During the COVID-19 crisis in Victoria, Australia the complexity of school leadership increased greatly for school principals. This study focused on the lived experiences of early career principals in the independent school sector from March to November 2020 in Victoria, Australia. It investigates transformative work that was undertaken by these leaders in leading their schools over a protracted crisis. Design/methodology/approach: The study builds on constructs of crisis leadership, adaptive leadership, agile leadership and emotional intelligence, exploring the leadership approaches undertaken by twenty-two early career principals in Victoria, Australia. Using a narrative inquiry approach, across three temporal points in 2020, storied productions drawn from the findings present four emergent types of emotionally intelligent leadership approaches undertaken by these principals. These leadership approaches are presented as the commander-leader, the conductor-leader, the gardener-leader and the engineer-leader with each approach demonstrating both organisational leadership approaches as well as individual leadership styles used by these principals as they led their schools. Findings: The findings have direct implications for professional development programs focusing on aspiring principals and early career principals with emphasis on the importance of developing emotionally intelligent skillsets in principals for use during periods of rapid change or high crisis in schools. The findings present insight into the support useful for early career principals in the first five years of principalship. Originality/value: This study uses a unique emotional intelligence approach to understand school leadership during and after a crisis. © 2023, Venesser Fernandes, Winnie Wong and Michael Noonan.

Chest computed tomography analysis of lung sparing morphology: differentiation of COVID-19 pneumonia from influenza pneumonia and bacterial pneumonia using the arched bridge and vacuole signs.

INTRODUCTION: This study evaluated the arched bridge and vacuole signs, which constitute morphological patterns of lung sparing in coronavirus disease 2019 (COVID-19), then examined whether these signs could be used to differentiate COVID-19 pneumonia from influenza pneumonia or bacterial pneumonia. METHODS: In total, 187 patients were included: 66 patients with COVID-19 pneumonia, 50 patients with influenza pneumonia and positive computed tomography findings, and 71 patients with bacterial pneumonia and positive computed tomography findings. Images were independently reviewed by two radiologists. The incidences of the arched bridge sign and/or vacuole sign were compared among the COVID-19 pneumonia, influenza pneumonia, and bacterial pneumonia groups. RESULTS: The arched bridge sign was much more common among patients with COVID-19 pneumonia (42/66, 63.6%) than among patients with influenza pneumonia (4/50, 8.0%; P<0.001) or bacterial pneumonia (4/71, 5.6%; P<0.001). The vacuole sign was also much more common among patients with COVID-19 pneumonia (14/66, 21.2%) than among patients with influenza pneumonia (1/50, 2.0%; P=0.005) or bacterial pneumonia (1/71, 1.4%; P<0.001). The signs occurred together in 11 (16.7%) patients with COVID-19 pneumonia, but they did not occur together in patients with influenza pneumonia or bacterial pneumonia. The arched bridge and vacuole signs predicted COVID-19 pneumonia with respective specificities of 93.4% and 98.4%. CONCLUSION: The arched bridge and vacuole signs are much more common in patients with COVID-19 pneumonia and can help differentiate COVID-19 pneumonia from influenza and bacterial pneumonia.

Hybrid Transfer Learning with ECOC Ensemble Configuration for COVID-19 CXR Detection

Coronavirus Disease 2019 (COVID-19) is a viral pneumonia that causes symptoms in the lungs of those infected. The presence of the symptoms must be diagnosed as soon as possible. If no test kits are available, the next best alternative is a computer-aided diagnostic of a patient's chest X-ray scan for a quick and accurate diagnosis. This paper proposes a hybrid transfer learning method with Error-Correction Output Codes (ECOC) by combining networks including GoogLeNet, ResNet-18, and ShuffleNet for feature extraction. X-ray input data are collected from open-source repositories. In this implementations, Support Vector Machine (SVM) as the base classifier. The proposed network attempts to categorize the input data into one of three categories: COVID-19, healthy, and non-COVID-19 pneumonia. The mean accuracy of our method is 96.21%, compared fine tuning existing pre-trained model which yielded 89.1% for GoogLeNet, 88.95% for ResNet-18, and 89.31% for ShuffleNet. © 2022 IEEE.

The effect of oral paracetamol on [18F]FDG PET/CT in oncology patients following COVID-19 vaccination

Aim/Introduction: [18F]FDG PET/CT plays an important role in diagnosis, staging, response assessment and follow-up care for oncology patients. Since mass Coronavirus Disease 2019 (COVID-19) vaccination program in many countries, vaccineassociated hypermetabolic lymphadenopathy (VAHL) may cause misinterpretation, unnecessary lymph node biopsy and alteration of therapy. Prophylactic use of paracetamol has been shown to alleviate the vaccine side-effects;whether it can also reduce the incidence of VAHL is not well studied. In the present study, we aimed to evaluate whether paracetamol can also reduce the incidence of VAHL in suspected or confirmed lung cancer patients. Material(s) and Method(s): This was a single-centre retrospective study. All consecutive patients with suspected or confirmed cancers who underwent [18F]FDG PET/CT between 1 May 2021 and 30 September 2021 and received at least one dose of COVID-19 vaccine within 6 weeks before were investigated. Demographic and clinical history (including details of COVID-19 vaccination, use of oral paracetamol) were collected, and the occurrence of VAHL was measured. Result(s): Among 96 patients (M:F = 40:56, mean age 60 +/- 11 years), 43.8% (42/96) demonstrated VAHL with median SUVmax of 3.2 (range, 1.5-13.8), median size of 7 mm (range, 3-17 mm) and median number of 3 (range, 1-15). Patients with oral paracetamol (63 +/- 11 years) and those without oral paracetamol (60 +/- 11 years) showed no statistically significant difference in the incidence (p = 0.751), SUVmax (p = 0.174), size (p = 0.932) and number of VAHL (p = 0.208). In addition, positive uptake at vaccine injection site was seen in 38.5% (37/96) of patients;use of oral paracetamol or not did not result in statistically significant difference in the incidence of positive deltoid uptake (p>0.05). Conclusion(s): This study demonstrated that intake of oral paracetamol may not prevent the occurrence of VAHL on [18F]FDG PET/CT in suspected or confirmed cancer patients following COVID-19 vaccination. On the other hand, paracetamol seems not to affect patients' immune response to the vaccine, which is a desirable attribute for a medication commonly prescribed for mitigation of the adverse effects of the vaccine.

The ground zero of teaching and learning evolution: A case study of Malaysian universities

In December 2019, the world was shaken by the discovery of a novel type of pneumonia virus that had not been observed before. The disease was caused by severe acute respiratory syndrome coronavirus 2, and the disease was officially named COVID-19 by the World Health Organization (WHO) in March 2020. Also in that month, the WHO announced that COVID-19 could be categorized as a pandemic. © 1988-2012 IEEE.

Applications in Sciences in the prevention of COVID-19

Purpose: The main purpose of this work is to provide an overview of the COVID-19 issue, this article discusses in detail and fully the important and meaningful applications of Decision Sciences to the prevention of COVID-19. Because COVID-19 is an extremely hot topic and the most fascinating question in recent years, the research on this topic is very interesting and noticed by scientists. Design/methodology/approach: In the scope of this study, we first introduce definitions and issues related to COVID-19 and study the negative impacts of COVID-19 diseases on all sectors of society. We then provide a comprehensive introduction to the applied aspects of Decision Science in the prevention of COVID-19. Findings: The findings of our research help people have a correct, complete, overview,and comprehensive view of the COVID-19 issue. All COVID-19 issues are discussed in great detail and completeness in this article. Originality/value: All the issues discussed in this study are original and new in the literary literature. Practical implications: This will help the countries'leaders have the best way to fight the COVID-19 pandemic more effectively and cost-effectively. © 2022 Hindawi Limited. All rights reserved.

How Can We Improve Gynecological Surgery Webinars during the COVID-19 Pandemic?

The COVID-19 pandemic prevented doctors from attending surgical meetings or conferences where they learned surgical skills from others and shared surgical experiences. It also resulted in the rapid use of webinars in obstetrics and gynecology meetings. While webinars or virtual meetings enable distance learning and replace face-to-face meetings using various teleconferencing software programs, many attendees are not satisfied and find it difficult to learn surgical techniques using commercially available telecommunication programs. Therefore, dedicated webinars are necessary to present emerging surgical technologies, satisfy the attendees, and achieve a successful outcome. This article reviews the existing telecommunication programs, new presentation technologies, and proposed webinars developments to improve its delivery of surgical techniques and training during the COVID-19 pandemic and in the future.

What is an Optimal Allocation in Hong Kong Stock, Real Estate, and Money Markets: An Individual Asset, Efficient Frontier Portfolios, or a Naïve Portfolio? Is This a New Financial Anomaly?

To test for arbitrage opportunities and market efficiency in the Hong Kong money, stock, and real estate markets, we find that the money market stochastically dominates both the stock and real estate markets. Furthermore, the real estate market dominates the stock market, the money market dominates nearly all the efficient frontier portfolios, none of the efficient portfolios dominates the money market, and the money market also dominates the equal-weighting portfolio. This infers that in some cases investors could achieve higher expected ex-ante utility by investing in an individual asset rather than a portfolio. Our conclusions drawn from the pre-COVID-19 period are the same as those drawn from the entire period and the conclusions drawn from the COVID-19 period are the same as those drawn from the entire period except that the money market only stochastically dominates some of the efficient frontier portfolios. Our findings question diversification benefits in the Hong Kong capital market during our sample period, including both the pre-COVID-19 and COVID-19 periods. © 2022 Taylor & Francis Group, LLC.

An Overview of Healthcare Data Analytics With Applications to the COVID-19 Pandemic

In the era of big data, standard analysis tools may be inadequate for making inference and there is a growing need for more efficient and innovative ways to collect, process, analyze and interpret the massive and complex data. We provide an overview of challenges in big data problems and describe how innovative analytical methods, machine learning tools and metaheuristics can tackle general healthcare problems with a focus on the current pandemic. In particular, we give applications of modern digital technology, statistical methods,data platforms and data integration systems to improve diagnosis and treatment of diseases in clinical research and novel epidemiologic tools to tackle infection source problems, such as finding Patient Zero in the spread of epidemics. We make the case that analyzing and interpreting big data is a very challenging task that requires a multi-disciplinary effort to continuously create more effective methodologies and powerful tools to transfer data information into knowledge that enables informed decision making.

Estimating Effective Reproduction Number for SIR Compartmental Model: A Stochastic Evolutionary Approach

Compartmental pandemic models have become a significant tool in the battle against disease outbreaks. Despite this, pandemic models sometimes require extensive modification to accurately reflect the actual epidemic condition. The Susceptible-Infectious-Removed (SIR) model, in particular, contains two primary parameters: the infectious rate parameter ß and the removal rate parameter y, in addition to additional unknowns such as the initial infectious population. Adding to the complexity, there is an obvious challenge to track the evolution of these parameters, especially ß and y, over time which leads to the estimation of the reproduction number for the particular time window, RT. This reproduction number may provide better understanding on the effectiveness of isolation or control measures. The changing RT values (evolving over time window) will lead to even more possible parameter scenarios. Given the present Coronavirus Disease 2019 (COVID-19) pandemic, a stochastic optimization strategy is proposed to fit the model on the basis of parameter changes over time. Solutions are encoded to reflect the changing parameters of ßT and γt, allowing the changing RT to be estimated. In our approach, an Adaptive Differential Evolution (ADE) and Particle Swarm Optimization (PSO) are used to fit the curves into previously recorded data. ADE eliminates the need to tune the parameters of the Differential Evolution (DE) to balance the exploitation and exploration in the solution space. Results show that the proposed optimized model can generally fit the curves well albeit high variance in the solutions. © 2020 Tsinghua University Press.

SARILUMAB in PATIENTS with RELAPSING POLYMYALGIA RHEUMATICA: A PHASE 3, MULTICENTER, RANDOMIZED, DOUBLE BLIND, PLACEBO CONTROLLED TRIAL (SAPHYR)

Background: Interleukin-6 (IL-6) is elevated in patients with active polymyalgia rheumatica (PMR) and is associated with disease activity, relapse and severity. Clinical trials with IL-6 receptor (IL-6R) inhibitors in PMR showed higher remission rates and reduced glucocorticoid (GC) use vs GC alone.1-4 Objectives: The SAPHYR study (NCT03600818) assessed the efficacy and safety of sarilumab (SAR), a fully human anti IL-6Rα monoclonal antibody, with a 14 week (wk) GC taper in patients with steroid resistant active PMR who fared on ≥7.5 mg/day prednisone or equivalent. Methods: Patients were randomized (1:1) to 52 wks of treatment with SAR 200 mg every 2 wks (Q2W) + 14 wk GC tapered regimen (SAR arm) OR placebo Q2W + 52 wk GC tapered regimen (comparator arm). The primary endpoint was the proportion of patients achieving sustained remission at wk 52, defned as disease remission by wk 12, absence of disease fare, CRP normalization from wks 12 to 52 and adherence to the per protocol GC taper from wks 12 to 52. Results: The study was terminated early due to protracted recruitment timelines during the COVID-19 pandemic, resulting in 118 of the intended 280 patients recruited between Oct 2018 and Jul 2020, and 117 were treated (SAR n=59, comparator n=58). The demographics were balanced;patients were primarily female, Caucasian, and a median age of ~70 years (Table 1). Overall, 78 patients completed the treatment (SAR n=42;comparator n=36). Primary reasons for treatment discontinuation were adverse events (AEs;SAR n=7, comparator n=4) and lack of efficacy (SAR n=4, comparator n=9). Sustained remission rate was signifcantly higher in the SAR arm vs the comparator arm (28.3% vs 10.3%;P=0.0193). Results of a sensitivity analysis excluding CRP from the sustained remission defnition was consistent with the primary analysis (31.7% vs 13.8%;P=0.0280). All sustained remission components favored SAR (Figure 1). Patients in the SAR arm were 44% less likely to have a fare after achieving clinical remission vs the comparator arm (16.7% vs 29.3%;HR 0.56;95% CI 0.35-0.90;P=0.0158). The comparator arm required more additional GCs vs the SAR arm, mainly due to PMR fare (median difference in actual and expected cumulative dose 199.5 mg vs 0.0 mg;P=0.0189). The cumulative GC toxicity index scores numerically favored SAR but the difference was not statistically signifcant. PMR activity scores improved in the SAR arm vs the comparator arm (LS mean-15.57 vs-10.27, nominal P=0.0002). Patient reported outcomes (eg, physical and mental health component scores, disability index, etc) favored SAR (Figure 1). Incidence of treatment-emergent AEs (TEAEs) was numerically higher in the SAR arm vs the comparator arm (94.9% vs 84.5%) and included neutropenia (15.3%) and arthralgia (15.3%) in the SAR arm, and insomnia (15.5%) in the comparator arm. Conversely, the frequency of serious AEs was higher in the comparator arm vs the SAR arm (20.7% vs 13.6%). No deaths were reported. Conclusion: SAR + 14 wk GC taper demonstrated signifcant efficacy vs the comparator arm in steroid refractory PMR patients, including clinically meaningful improvement in quality of life. Safety was consistent with the known safety profile of SAR.

A SURVEY on ACCEPTANCE of COVID-19 VACCINATION among PATIENTS with RHEUMATIC DISEASES-A SINGLE CENTER EXPERIENCE in MALAYSIA

Background: According to Statista, 78.5% of the population in Malaysia have completed their vaccination as of 6th january 2022 [1].The acceptance of patients with rheumatic diseases on Covid-19 vaccination is crucial in the long term protection against Covid-19 infection. We conducted a survey to determine the acceptance of Covid-19 vaccination amongst patients with underlying rheumatic disease. Objectives: To fnd out the reasons of vaccination refusal amongst rheumatology patients. Methods: This was an interview survey. All rheumatology patients who were follow up in rheumatology clinic Hospital Sultan Ismail, Malaysia from 26th April 2021 to 25th July 2021 (total 3 months) were interviewed. Demographic and diagnosis of the patients were collected. Results: A total of 952 patients were identified. 83.7% of them were female patients (797/952) and majority of them were Malay (46.4%). This was followed by Chinese (36.1%), Indian (16.3%) and others (1.2%). The mean age group was 48 (range from 13-85). 97.6% of the respondents were categorized as having inactive disease during the interview sessions. 36.6% of the patients were diagnosed to have rheumatoid arthritis and 29.1% of them were having systemic lupus erythematosus. These were followed by psoriatic arthritis (10.9%), mixed connective tissue disease (5.5%), systemic sclerosis (2.9%), gout (2.6%), Sjogren syndrome (1.9%), ankylosing spondylitis (1.6%), myositis (1.5%), vascu-litis (1.3%), osteoarthritis (1.2%), antiphospholipid syndrome (0.9%), non-specific arthralgia (0.8%), juvenile idiopathic arthritis (0.8%), seronegative spondyloarthropathy (0.8%), undifferentiated connective tissue disease (0.7%), adult onset still's disease 0.5%) and others (< 0.5% each for Ig G 4 related disease, soft tissue rheumatism and fibro-myalgia). 87.3% of them were keen or have already received Covid-19 vaccination. 12.7% of them were not keen for the vaccination with various reasons. 48.8% of them were worrying about worsening clinical condition, 12.4% of them were not keen as they concerned about side effects (3 worry about fever, 1 worry about hepatitis, 1 for nausea, 1 for dizziness, 1 for breathlessness, and 7 for non-specific reasons). 10.7% of them were not keen due to pregnancy, 5.79% of them were not keen as worried about allergic reactions, 4.9% of them were worrying about sudden cardiac death, 4% were not keen as on chemotherapy treatment, 3 % of them doubted the efficacy of vaccination, 2.5% were not keen as they worried about heart disease, 2.5% worried about increase risks of infection and others (2 for old age, 2 for thrombotic event, 2 for drug interaction and 1 patient due to hemodialysis). Conclusion: The overall acceptance rate of Covid-19 vaccination amongst patients with rheumatic diseases is very encouraging with the percentage of >85% despite of lacking knowledge about vaccine Covid-19. This result can assist our Ministry of Health to plan for future battle to improve vaccine uptake that hopefully can lead to herd immunity against COVID-19 infection. More counseling sessions are required to clear up the doubts of vaccination and increase the vaccination rate amongst rheumatic patients.

Establishment of Hong Kong Neuromuscular Disorder Patient Registry

Introduction: Neuromuscular disorders (NMDs) are a group of diseases affecting the peripheral nervous system (1). Many NMDs cause disability or even premature death (2). We aim to design and establish a robust NMD patient registry in Hong Kong. Methods: By modelling international NMD patient registries, we designed patient-professional reported questionnaires to collect the demographic, clinical c haracteristics, genetic details, family history, investigation findings and specific treatment of NMD patients. Patients were recruited through Hong Kong West Cluster (DKCH, QMH) and Kowloon Central Cluster (HKCH). We also developed self-registration online platform. p<0.05 was considered statistically significant. Findings: Since June 2019, 125 NMD patients have been enrolled in the registry with 12 participants registered online. The registry recruited 13 types of NMDs, including spinal muscular atrophy (SMA) (n=31), Duchenne muscular dystrophy (DMD) (n=19) and congenital myopathy (n=18). The age range was 7 months to 63 years old. 65.6% of those enrolled were children (<18 years old). 63.2% were male. 64.8% of the patients had genetic diagnosis. The registry has contributed to two studies. The first one is a prospective study of clinical efficiency of Nusinersen in SMA patients (n=22). 14/16 SMA patients showed improvement in at least one of motor performance (CHOP intend/RULM/HINE/HFMSE) and health-related quality of life after 1st year of treatment. The second study is the reactogenicity and immunogenicity study of the COVID-19 vaccine in DMD patients (n=4). Data will be available in October. Conclusion: Hong Kong Patient registry has contributed to ongoing and new research study to optimise medical care.

Impact of School Closure on Children'S Sleep Pattern During the COVID-19 Pandemic

Background: School closure is one of the main global health policies performed worldwide during the coronavir us di sease 2019 (COVID-19) outbreak. Despite all of the advantages, there may be some risks for children who are quarantined. This study aimed to objectively measure and compares the sleep patterns of Hong Kong school students before and during the COVID-19 outbreak. Methods: Baseline assessment was performed before the first wave of the COVID-19 outbreak in Hong Kong. The sleep pattern was recorded by a physical activity monitor (Actigraph wGT3X-BT, Pensacola, Florida, USA). The follow-up assessment was conducted in early 2020. Findings: In total, 718 students were collected in the baseline . Sub sequently 1 40 students joined t he reassessment between March and April 2020. Analysis of sleep timing shows that 98.0% primary students, 78.0% secondary students and 79.9% primary school students and 58.8% secondary school students go to bed before midnight before and after the outbreak, respectively (p<0.001). Mean sleep duration (hours) was 6.81 (0.62) and 8.09 (0.07) at baseline and during the outbreak, respectively. The differences in the mean sleep features for total sleep time, sleep fragmentation index and sleep fragmentation were 0.92 (1.64), 1.64 (6.95) and 2.49 (9.18), respectively. The overall sleep quality was poorer as evidenced by delays in bedtime and wake up time, increased duration in bed, longer sleep latency, increases in the movement and fragmentation indices. Conclusion: This exceptional longitudinal study reported objective data on the change in sleep patterns before and during the COVID-19 outbreak with school closures.

Public Sentiment Analysis and Topic Modeling Regarding COVID-19's Three Waves of Total Lockdown: A Case Study on Movement Control Order in Malaysia

The COVID-19 pandemic has affected many aspects of human life. The pandemic not only caused millions of fatalities and problems but also changed public sentiment and behavior. Owing to the magnitude of this pandemic, governments worldwide adopted full lockdown measures that attracted much discussion on social media platforms. To investigate the effects of these lockdown measures, this study performed sentiment analysis and latent Dirichlet allocation topic modeling on textual data from Twitter published during the three lockdown waves in Malaysia between 2020 and 2021. Three lockdown measures were identified, the related data for the first two weeks of each lockdown were collected and analysed to understand the public sentiment. The changes between these lockdowns were identified, and the latent topics were highlighted. Most of the public sentiment focused on the first lockdown as reflected in the large number of latent topics generated during this period. The overall sentiment for each lockdown was mostly positive, followed by neutral and then negative. Topic modelling results identified staying at home, quarantine and lockdown as the main aspects of discussion for the first lockdown, whilst importance of health measures and government efforts were the main aspects for the second and third lockdowns. Governments may utilise these findings to understand public sentiment and to formulate precautionary measures that can assure the safety of their citizens and tend to their most pressing problems. These results also highlight the importance of positive messaging during difficult times, establishing digital interventions and formulating new policies to improve the reaction of the public to emergency situations.

Comparing Autopsy Thoracic Injury Patterns between In-Hospital CPR Patients Receiving LUCAS Device vs Manual Chest Compressions

Background: Current research comparing CPR-associated injuries between those receiving LUCAS device and manual CPR has primarily focused on patients who suffered out-of-hospital cardiac arrest. During the SARS-CoV-2 pandemic, more hospitals leveraged mechanical CPR devices to provide distant yet high quality chest compressions for in-hospital cardiac arrest (IHCA) patients. We sought to investigate autopsy thoracic injury patterns in in-hospital non-traumatic cardiac arrests, comparing traditional manual compressions with the mechanical LUCAS device compressions. Design: Autopsies were screened for a history of in-hospital cardiopulmonary resuscitation in the absence of prior traumatic injuries at a single, large quaternary care center from 1/1/2018 to 06/30/2021. 20 received LUCAS compressions and 40 received manual compressions. Student's T-Tests were used to compare means for continuous variables, while chi-squared and Fischer's exact tests were used for categorical variables. An alpha of 0.05 was chosen as the threshold for statistical significance. Results: A statistically significant decrease in the rate of sternal fractures and rate of multiple sternal fractures during mechanical CPR was found. A statistically significant increase in other soft tissue injuries, such as pleural wall or lung injuries was seen in mechanical CPR cases, while an increased rate of bilateral rib fractures was noted in manual compression cases. Conversely, no difference in the number or laterality of rib fractures were noted. There was no significant difference in age, biological sex, or rate of scoliosis or kyphosis between cohorts. Results are listed in table 1. (Table Presented) Little research has looked at the injury patterns of mechanical CPR in the IHCA patient population. These results point to a potential difference in thoracic injury patterns from manual compressions when compared to LUCAS device compressions. The statistically significant decrease in sternal fractures with mechanical compressions is noteworthy. Conversely, the increase in other soft tissue injury demands further examination. The decrease in bilateral rib fractures with LUCAS use suggests that placement of the device may play a role in the epidemiology of rib injuries, but not in the number of ribs injured. Further research should examine rib injuries in more detail, and quantify additional comorbidities in both survivors and non-survivors of cardiac arrest.

The effects of selected financial ratios on profitability: En empirical analysis of real estate firms in Vietnam

The paper examines the determinants of profitability of real estate companies by using panel data of Vietnamese listed companies on the Hanoi stock exchange (HNX) and Ho Chi Minh City stock exchange (HOSE) from 2007 to 2020. Profitability ratios are measured by return on assets (ROA) and return on equity (ROE). The results indicate that the cost on revenue ratio, debt-to-equity ratio and the crisis and COVID-19 pandemic are negatively correlated with firm profitability. Meanwhile, the sales to current assets ratio, money supply growth rate and economic growth rate (GDPG) provide a positive correlation with profitability. We find that firm size and equity to total assets have positive effects on ROA, while there is a negative relationship between equity to total assets and ROE, and not enough evidence to conclude how firm size affects ROE. The study thereby provides suggestions and recommendations for the administrators of the government, real estate companies and investors in Vietnam. © 2022 World Scientific Publishing Company.

Digitization of Fused Deposited Methods (FDM) Printer for Smart Additive Manufacturing (AM)

The panic buying during Covid-19 caused farmers to amped-up production. However, farm equipment is costly to purchase. Therefore, some farmers utilized Additive Manufacturing (AM) to manufacture farming tools at low cost. However, the lack of in-situ monitoring in AM to stop printing failed parts can waste materials and time. Thus, this research aims to deploy a low-cost smart remote monitoring system using OctoPrint and Node-red to integrate a 3D printer and Teachable Machine and train a model to pre-emptively detect print errors. The result was satisfactory as the 3D printer stopped when the camera detected a defect with 75% accuracy. Furthermore, the user can easily customize the model to enhance the system versatility via the developed code-free platform. © 2021 IEEE.