Acoustic-Based Deep Learning Architectures for Lung Disease Diagnosis: A Comprehensive Overview.

Lung auscultation has long been used as a valuable medical tool to assess respiratory health and has gotten a lot of attention in recent years, notably following the coronavirus epidemic. Lung auscultation is used to assess a patient's respiratory role. Modern technological progress has guided the growth of computer-based respiratory speech investigation, a valuable tool for detecting lung abnormalities and diseases. Several recent studies have reviewed this important area, but none are specific to lung sound-based analysis with deep-learning architectures from one side and the provided information was not sufficient for a good understanding of these techniques. This paper gives a complete review of prior deep-learning-based architecture lung sound analysis. Deep-learning-based respiratory sound analysis articles are found in different databases including the Plos, ACM Digital Libraries, Elsevier, PubMed, MDPI, Springer, and IEEE. More than 160 publications were extracted and submitted for assessment. This paper discusses different trends in pathology/lung sound, the common features for classifying lung sounds, several considered datasets, classification methods, signal processing techniques, and some statistical information based on previous study findings. Finally, the assessment concludes with a discussion of potential future improvements and recommendations.

On-Site Whole-Genome Sequencing of Sars-Cov-2 Reveals C3037t Mutation in Patient with Atrioventricular Nodal Reentry Tachycardia (Avnrt)

Intro: The spike protein of the SARS-CoV-2 virus targets the human cell receptor of angiotensin-converting enzyme (ACE2), including the myocardium and heart's conduction system. Patients diagnosed with COVID-19 have also been found to exhibit cardiac arrhythmia. Here, a whole-genome sequencing analysis using long-read sequencing was proposed to evaluate the virus genome in a patient who presented with AVNRT as a main presentation of COVID-19. Method(s): The sample was recovered from nasopharyngeal and oropharyngeal swab specimens of a 46-year-old female with no comorbidities who presented with palpitation, and ECG showed typical AVNRT features. The RT-qPCR of SARS- CoV-2 was confirmed positive with a CT-value of 15.82. The total RNAs were extracted and proceeded for RT-qPCR and proceeded with Oxford Nanopore Flongle sequencing. The genomics data of the virus was deposited in GISAID (EPI_ISL_3241561) and further analysed using online bioinformatics tools such as Nextclade CLI 2.3.0. Ethical approval (IREC 2021-080) for the study was obtained from IIUM Research Ethics Committee. Finding(s): Here, we reported a total of 29,775 bp near-complete whole-genome belonging to clade 21J (Delta) of AY.79 lineage (also known as B.1.617.2.79), which formed a dominant variant in Malaysia during the time of sampling. Discussion(s): While a previous study showed an association between Delta variant infection with fulminant myocarditis, the present study reported the benign AVNRT as the main presentation of SARS-CoV-2 infection. Furthermore, we observed the presence of the C3037T mutation previously described in the endomyocardial biopsy of a patient with persistent arrhythmia. Conclusion(s): Even though SARS-CoV-2 targets the respiratory tract, the present study supports the evidence that the ACE2 receptors are present in the heart. In addition, COVID19 is causing more and more damage to heart tissue, and viral transcription has been confirmed on cardiomyocytes. Further functional studies are needed to explore the associated mutations and their relation to cardiac manifestation.Copyright © 2023

Modeling The Effect of Contaminated Object, Vaccination and Treatment on The Diseases Epidemiology

In this paper, the effect of contaminated objects on a SIRS Model with vaccination and hospitalization compartments is modeled. Positivity and boundedness properties of the solutions of model are proved, basic reproduction number of the model is founded through criteria which make the eigenvalues of the Jacobean matrix at the disease-free equilibrium point, negative. Globally stability analysis of the disease-free equilibrium point is proved when the basic reproduction number is less than unity. The existence, uniqueness of the endemic equilibrium point is investigated when the basic reproduction number is greater than unity. Parameter values regarding to spreading covid-19 in Kurdistan region are estimated. Finally, sensitivity analysis of the reproduction number is carried out. © 2022 Production by the University of Garmian. This is an open access article under the LICENSE.

Compounded Bell-G class of statistical models with applications to COVID-19 and actuarial data

The compounded Bell generalized class of distributions is proposed in this article as an alternative to the compounded Poisson generalized family of distributions. Some properties and actuarial measures are presented. The properties of a special model named Bell Weibull (BellW) are obtained such as the linear representation of density, rth moment, incomplete moment, moment generating function using Wright generalized hypergeometric function and Meijer's G function, the pth moment of order statistics, reliability, stochastic ordering, and residual and reversed residual life. Moreover, some commonly used entropy measures, namely, Rényi, Havrda and Charvat, and Arimoto and Tsallis entropy are obtained for the special model. From the inferential side, parameters are estimated using maximum likelihood estimation. The simulation study is performed to highlight the behavior of estimates. Some actuarial measures including expected shortfall, value at risk, tail value at risk, tail variance, and tail variance premium for the BellW model are presented with the numerical illustration. The usefulness of the proposed family is evaluated using insurance claims and COVID-19 datasets. Convincing results are obtained. © 2023 the author(s), published by De Gruyter.

Development of Diphenyl carbonate-Crosslinked Cyclodextrin Based Nanosponges for Oral Delivery of Baricitinib: Formulation, Characterization and Pharmacokinetic Studies.

Background: The aim of the present investigation is to prepare baricitinib (BAR)-loaded diphenyl carbonate (DPC) ß-cyclodextrin (ßCD) based nanosponges (NSs) to improve the oral bioavailability. Methods: BAR-loaded DPC-crosslinked ßCD NSs (B-DCNs) were prepared prepared by varying the molar ratio of ßCD: DPC (1:1.5 to 1:6). The developed B-DCNs loaded with BAR were characterized for particle size, polydispersity index (PDI), zeta potential (ZP), % yield and percent entrapment efficiency (%EE). Results: Based on the above evaluations, BAR-loaded DPC ßCD NSs (B-CDN3) was optimized with mean size (345.8±4.7 nm), PDI (0.335±0.005), Yield (91.46±7.4%) and EE (79.1±1.6%). The optimized NSs (B-CDN3) was further confirmed by SEM, spectral analysis, BET analysis, in vitro release and pharmacokinetic studies. The optimized NSs (B-CDN3) showed 2.13 times enhancement in bioavailability in comparison to pure BAR suspension. Conclusion: It could be anticipated that NSs loaded with BAR as a promising tool for release and bioavailability for the treatment of rheumatic arthritis and Covid-19.

Willingness of Healthcare Workers to Recommend or Receive a Third COVID-19 Vaccine Dose: A Cross-Sectional Study from Jordan.

BACKGROUND: The availability of COVID-19 vaccines worldwide necessitates measuring healthcare workers' (HCWs') willingness to recommend or receive these vaccines. Therefore, we conducted a local study in Jordan to assess HCWs' willingness to recommend or receive a third dose of a COVID-19 vaccine and the predictors of such a decision. A cross-sectional study investigated Jordanian HCWs' willingness regarding a third dose of a COVID-19 vaccine using a self-administered online questionnaire through WhatsApp, a mobile phone application. A total of 300 HCWs participated in the current study. Of these HCWs, 65.3% were physicians, 25.3% were nurses, and 9.3% were pharmacists. HCWs' overall willingness regarding a third vaccine dose was 68.4% (49.4% certainly and 19.0% probably), whereas the overall willingness of HCWs to recommend a third dose to their patients was 73.3% (49.0% certainly and 24.3% probably). Males had significantly higher willingness than females (82.1% vs. 60.1%, p < 0.05). Physicians reported more willingness than nurses and pharmacists. HCWs' willingness was not significantly affected by direct contact with a patient infected with COVID-19 or by a personal history of COVID-19 infection. Only 31% of HCWs were certainly willing to recommend the vaccine to their patients with chronic diseases, and only 28% of the participants were certainly willing to recommend it to people aged 65 or older. HCWs' willingness to receive a third dose of a COVID-19 vaccine is limited in Jordan. This has affected their certainty in recommending this vaccine to their patients or people older than 60. Decision-makers and health-promotion programs in Jordan should focus on addressing this public health problem.

Improving Content Knowledge and Technological Skill of University Instructors: A Case Study for Online Learning Implementation during and after the COVID-19 Pandemic

The objectives of this study were to investigate and improve the university instructor's content knowledge and technological skills relating to digital learning. The research participants involved 260 lecturers from eleven education departments that teach 260 subject matters at a private university in NTB Province, Indonesia. We verified the instructor's content knowledge through the availability of course materials suitable to students' competencies needed and their potential. Then, it identified the instructor's skill in using information and communications technology (ICT) devices and analyzed the data. Enforcing an online learning workshop for the instructors who still had low digital knowledge, we evaluated their efforts during workshop activities. This research found that in the online learning process during and post the COVID-19 pandemic, the lecturers' course material preparation was generally unsatisfactory, even though they had good competencies in the use of ICT tools. This study gave information that the instructors who had abilities to digital devices did not automatically provide good services in online learning and technology adaptation processing for students. Fortunately, by training lecturers in the e-learning platform, the institution's efforts have to be successful in solving this problem. The training approach appertained dealing with the content knowledge improvement could affect their productivity in creating the learning media based on ICT and the presentation to be interesting. The instructors could enrich the content quality. The simulation exercise of the e-learning platform improved the instructors' competency related to the benefits of e-learning devices, the arranging of course materials, and students' learning activities management. For future development, we suggest that the institution must provide progressive support and training to ensure the continuity of online learning in the university. © 2022, City University of Hong Kong Press. All rights reserved.

Assessment of challenges and problems in supply chain among retailers during COVID-19 epidemic through AHP-TOPSIS hybrid MCDM technique

Framework and objectives: COVID-19 epidemic has sparked concern and has elevated the need for therapeutic tools, health equipment's, and day-to-day necessities for healthcare workers' well-being. The goal of this study is to uncover the operational problems that suppliers encounter when it comes to offering effective services. The research also intends to offer an Industry 4.0 strategy for reducing COVID-19's effect. The problems are weighed and priority is assigned by multi-criteria decision making to identify the most essential parameter which impacts the suppliers. Methods: A comprehensive literature assessment on the rampant eruption of COVID 19 and supply chain is conducted with the aid of literatures available on SCOPUS, Science Direct, and Google Scholar using appropriate keywords. To get further insights, certain pertinent and applicable industry reports and blogs are also used. Problems were analysed with AHP method and priority was assigned by technique for order performance by similarity to ideal solution (TOPSIS). Weights are calculated by AHP method and assigned to each criteria attribute. Results: We recognized eleven key problems that serve as an operational obstacle in the retail industry and proposed the use of Industry 4.0 technology to address them. The contemporary study is accomplished by using hybrid combination of two Multi Criteria Estimators methods- Analytical Hierarchical Process (AHP) and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). Further, the most significant problem comes out to be Maintenance of an appropriate balance among supply and demand followed by Lack of Viability. Key findings: Prioritization of supply chain problems are arranged in descending order Maintenance of an appropriate balance among supply and demand ​> ​Lack of Viability ​> ​Absence of government funding ​> ​Lack of access ​> ​Absence of Confidence ​> ​Scarcity of work force ​> ​Lack of security and safety ​> ​Deficiency of surplus medical amenities ​> ​Consumer attitude ​> Absence of Supply Chain flexibility ​> ​Communication problems. Conclusion: In order to combat the pandemic, Industry 4.0 can play a key role in lowering the effect of identified issues on retailers. For the successful administration of healthcare basics, trust and openness are required. To enhance services, suppliers, distributors and policy makers should make informed decisions during COVID-19 and other comparable events. Therefore, suggested guidelines and framework will offer upcoming directions for research in fields of pandemic check, business logistics management, and catastrophe administration. Balance in supply and demand is the most significant attribute as its percentage contribution is the maximum (27.52%) followed by Safety of employees (26.51%). Furthermore, the research then ranks these models on the basis of their attributes with the aid of TOPSIS. Among all these problems, Maintenance of an appropriate balance among supply and demand and lack of viability are identified as the prime most and common concern for retailers in supply chain management during the COVID-19 pandemic. © 2022 The Authors

The impact of age and gender on mortality from COVID19 at A UK Hospital

Rationale: Age poses greater mortality risk to COVID-19 patients. This may be due to co-morbidities and age-related impairment of immunity. It has been shown that females are more likely to be infected however, severe disease is more often seen in males, which could be explained by greater levels of interferon-gamma promoter activity driven by oestrogen in females in addition to higher levels of IgG antibody providing more protection. We aim to investigate the effects of age and gender on the mortality rate in patients with COVID-19. Method(s): A retrospective study of all in-patients aged >= 18 years with a confirmed diagnosis of COVID-19 during the first and second waves of the pandemic. Admission CXRs were analysed. Statistical analysis was performed using the Chi-Squared Test for independence. Result(s): 1759 COVID-19 patients were included in the study, of which 481 were aged <65 years and 982 were aged > 65 years. The study had 967 males and 792 females. We found a higher mortality rate in those aged > 65 (41%) compared to those aged <65 years (18%) (P<0.001). There were no significant differences in the mortality rates between both genders. However, interestingly males had a greater severity of pneumonitis (22%) on CXRs compared to females (13%) (P=0.01). Conclusion(s): Our study demonstrated a positive correlation between increasing age and mortality with males showing a greater disease severity. This data should be considered when stratifying at risk groups and prioritising them for early intervention.

To assess the diagnostic and prognostic ability of CXRs in COVID-19 pneumonitis

Rationale: The COVID-19 pandemic has led to the deaths of millions with its ability to cause severe pneumonia. Diagnosis is based on PCR testing which has many limitations: lengthy turnaround times, lack of universal availability and variance in sensitivity. Imaging such as CXR could be a valuable and faster aid in diagnosing COVID-19 compared to PCR. It is widely available, cheap and can be performed at the bedside- enabling a rapid turnover of patients whilst minimising cross-link infection. However only a few studies have assessed its prognostic value. We aim to analyse the diagnostic accuracy of CXR in COVID-19 and to assess if severity of COVID pneumonitis on CXR correlated with mortality. Method(s): A retrospective study of all in-patients aged >= 18 years with a confirmed diagnosis of COVID-19 during the first and second waves of the pandemic. Admission CXRs and in-patient CT Thorax scans were analysed. Statistical analysis was performed using the Chi-Squared Test for independence. Result(s): 999 COVID-19 patients were included in the study. Severity of COVID pneumonitis on CXR correlated with mortality when patients were grouped into the following categories: normal (n=161, mortality=42%), mild (n=220,mortality=33%) moderate, (n=328, mortality=42%) and severe (n=290, mortality=58%) (P<0.001). 251 patients had both CT and CXRs. CT scans were superior in diagnosing COVID pneumonitis (63%) compared to CXR (47%) (P<0.001). Conclusion(s): Our study showed a positive correlation between the severity of COVID pneumonitis on CXR and mortality, supporting the use of CXR in the ED to help rapidly identify and treat patients at high risk of death.

Comparing the mortality of COPD and non-COPD patients with COVID-19 in a UK hospital

Rationale: Initial reports during the pandemic have shown that COPD patients with COVID-19 have a poorer prognosis due to an increased risk of respiratory failure. It is well known that in COPD, there is an increased expression of angiotensin converting enzyme-2 (ACE2), the receptor which plays a role in SARS-CoV-2 entry into cells. In the absence of infection, ACE2 converts angiotensin-2 (AngII) to angiotensin-1-7- helping regulate inflammation. During COVID-19 infection, ACE2 activity is reduced due to receptor occupancy, resulting in greater levels of AngII- leading to a pro-inflammatory state. We aim to investigate the impact of COPD and COVID-19 on mortality, length of in-patient stay and gender. Method(s): A retrospective study of all in-patients aged >= 18 years with a confirmed diagnosis of COVID-19 during the first wave of the pandemic. Statistical analysis was performed using the Chi-Squared Test for independence. Result(s): 445 COVID-19 patients were included in the study, out of whom 52 (12%) had COPD. Mortality in COPD patients (65%) was found to be significantly higher than non-COPD patients (49%) (P=0.03) There were no significant differences in mortality between COPD and non-COPD patients when grouped for male and female (P=0.68). Furthermore, there were no significant differences in length of in-patient stays of >7 days between COPD and non-COPD patients (P=0.79). Conclusion(s): Our study demonstrated how COPD increases mortality in COVID-19. This data should be considered when highlighting at risk groups- prioritising them for treatment, isolation, and preventative public health measures such as the COVID-19 vaccination programme.

Returns and volatility spillover between agricultural commodities and emerging stock markets: new evidence from COVID-19 and Russian-Ukrainian war

Purpose: This study investigate the return and volatility spillover among agricultural commodities and emerging stock markets during various crises, including the COVID-19 pandemic and the Russian-Ukrainian war. Design/methodology/approach: This return and volatility spillover is estimated using Diebold and Yilmaz (2012, 2014) approach. Findings: The results reveal the weak connectedness between agricultural commodities and emerging stock markets. Corn and sugar are the highest and lowest transmitters, respectively, whereas soya bean and coffee are the largest and smallest recipients of spillover over time. Most equity indices are the net recipient except for India, China, Indonesia, Argentina and Mexico, during the entire sample period. Most commodities are net transmitters of volatility spillover except coffee and soya bean. At the same time, major equity indices are the net recipient of the volatility spillover except for India, Indonesia, China, Argentina, Malaysia and Korea. In addition, the return and volatility spillover increase during various crises like the COVID-19 pandemic and the Russian-Ukrainian war, but the major increase in spillovers occurs during the COVID-19 pandemic. Practical implications: The empirical results show a weak relationship between agricultural commodities and emerging stock markets which is helpful for investors and portfolio managers in the construction and reallocation of their portfolios under different periods, most notably under COVID-19 and the Russian-Ukrainian war. Originality/value: It is an original paper. © 2023, Emerald Publishing Limited.

Increasing teleconsultation utilisation for pre-operative anaesthesia evaluation in the COVID-19 pandemic era: a qualityimprovement project

The COVID-19 pandemic has accelerated the growth of telemedicine. Advantages include patient convenience, reduced waiting time, minimising hospital commute and the risk of virus transmission and healthcare cost-savings [1]. Compared with other specialties, anaesthesiology is less engaged with telemedicine- based clinical work and challenges in implementation exist [2]. To align with the Ministry of Health, Singapore COVID-19-safe management measures, pre-anaesthetic assessment via video consultation (VC) workflow was implemented in Sengkang General Hospital, Singapore, in December 2020;however, the referral rate amongst our surgical colleagues remained low. Therefore the aim was to increase the number of VCs by 50% within 12 months (from June 2021) and evaluate patients' experiences. Methods Eligibility criteria included low-risk surgeries (duration < 4 h) with minimal expected blood loss, patients aged 21-65 years, ASA status 1 or 2, body mass index < 35 and the patient's ability to use the Zoom video-conferencing application. Post-consultation, patients were invited to complete an electronic patient satisfaction survey. The main reasons for the low VC referral rate were identified based on ground engagement and feedback. Two plan-do-study-act (PDSA) cycles were conducted to address these issues. PDSA cycle 1 (June 2021): to increase awareness amongst surgeons, surgical champions were engaged to promote VC within their departments;however, the VC referral rate remained low. Therefore, a second PDSA cycle was undertaken. PDSA cycle 2 (October 2021): to increase patient and staff awareness by placing posters publicising VC and enlisting the help of Patient Service Associates (PSAs) to screen for patient eligibility. This led to a significant increase in VC referrals. The current workflow will be evaluated for sustainability. Results Pre-intervention, the average number of monthly VCs was 3, and remained unchanged during PDSA cycle 1. This was increased to 14 during PDSA cycle 2. Discussion VC referrals have increased after the modified workflow, achieving high patient satisfaction and no surgical cancellations. Future work includes developing an automated VC workflow for low-risk surgeries. (Figure Presented).

Assessing health-related quality-of-life in Australian Multiple Sclerosis Longitudinal Study participants using six multi-attribute utility instruments: implications for healthcare decision-making

Background: Despite important discoveries/advances in treating multiple sclerosis (MS), people with MS (pwMS) can experience delays in accessing new treatments if decision-makers lack robust health economic evidence including health-related quality-of-life (HRQoL) benefits of the intervention. Health state utilities (HSU) are a HRQoL input for cost-utility analysis. Objective(s): Several multi-attribute utility instruments (MAUIs) are available from which HSUs can be derived, but the most appropriate MAUI for use in MS has not been identified. We aimed to determine the preferentially sensitive MAUI(s) that capture the full impact of MS on HRQoL. Method(s): Participants in this study came from a comprehensive HRQoL survey (mid-2020) of the Australian MS Longitudinal Study. The survey included six MAUIs (EQ-5D-5L/ EQ-5D5LPsychosocial, SF-6D versions 1 and 2, AQoL-8D and PropR), and sociodemographic, Covid19-related and subjective wellbeing data. HSUs were generated from Australian value sets. Ceiling and floor effects were investigated. Bland-Altman plots and Shannon's Indices were examined. Minimal important differences and population norms were sourced from the literature. Result(s): N=1,683 pwMS completed the survey (67% response). HSUs were derived for >97% of respondents. Mean age 58.6 years, 80% female, 19% reported severe disease and 63% had relapsing-remitting MS. Mean (SD) HSUs ranged from 0.45+/-0.29 (SF-6Dv1) to 0.63+/-0.22 (AQoL-8D). EQ-5D-5L revealed the highest ceiling (HSU=1.0;n=157,10%) and floor (HSU<=0;n=113,7%) effects. PwMS with EQ-5D-5L HSU<=0/HSU=1 reported mean HSUs of 0.37/0.91, 0.35/0.90, and 0.08/0.85 for the AQoL-8D, EQ-5D5LPsychosocial and SF-6D, respectively. Conclusion(s): While the EQ-5D is the most commonly cited MAUI (in 85% of health technology assessment guidelines), our preliminary comparison results suggest the EQ-5D-5L is not preferentially sensitive in assessing the complex HRQoL domains for pwMS.

Analysis Model of Toddlers Factor as Stunting Risk Predisposition Factor Due to Covid 19 in Stunting Locus Village Area of Indonesia

BACKGROUND: Stunting is one of the global health and nutrition problems faced by toddlers because of the height growth problem caused by the lack of nutrition intake both the micro nutrition and macro nutrition and also infection diseases in long terms. OBJECTIVE(S): This research aims at analyzing the toddler factors as the stunting risk predisposition factor due to Covid 19 pandemic in stunting locus village area of Indonesia. DESIGN: This study applied case control study research design. This research was conducted for seven months (May 27th - November 20th 2022) in Stunting Locus Pudun Jae Village area, Padangsidimpuan City. PARTICIPANTS: This case control study took 112 toddlers as the samples who were divided into two groups;56 stunting toddlers were included in case group and 56 normal toddlers were included in control group. The sampling technique used was purposive sampling. KEY RESULTS: This research found that the poor eating frequency (OR=3,619), monotonous eating habit (OR=0,440), and exclusive breastfeeding history (OR=0,070) were stunting risk predisposition factors on toddlers. In addition, the result of multivariate analysis on the three stunting risk factors showed that the eating frequency (OR=3,619) was the most dominant factor leading to stunting. CONCLUSION(S): This research findings summary confirmed that eating habit, eating frequency, and exclusive breastfeeding history were the stunting risk predisposition factors with the value of OR > 1. Thus, any intervention which can overcome those predisposition factors to prevent stunting is needed such as family-based nutrition education and accurate nutrition intervention. Copyright © 2023 Wolters Kluwer Medknow Publications. All rights reserved.

Volatility contagion (spillover) between Chinese and Pakistani stock markets during COVID-19: pre and post analysis of trade-level data

This research study examines volatility contagion (spillover) before and during the COVID period from the Chinese stock market (Shanghai stock market) to the Pakistani stock market (Karachi stock market). We used aggregate market datasets and various industry datasets (11 industries according to GICS classification), employed the EGARCH model to investigate the volatility spillover. Our results indicate that volatility demonstrates different characteristics in aggregate data samples as compared to industrial data samples. Moreover, this study finds return spillover and volatility spillover in both datasets (aggregate and industries). This study suggests that stakeholders should analyse both datasets (aggregate and industry) before taking investment decisions. Copyright © 2022 Inderscience Enterprises Ltd.

Depression, Anxiety and Stress Level among University Students of Class Reentry Post Covid-19 Pandemic

Since the breakdown of the COVID-19, tertiary education in Malaysia is still using online classes. Returning to normal study routines might have some positive effects or opposite and causes anxiety for other students as with class reentry. Therefore, this study is evaluating the depression, anxiety, and stress in reentry classes of university students post covid-19 from all over Malaysia. Observational study was conducted using online questionnaire that was developed by adapting the Patient Health questionnaire (PHQ-9), Generalized Anxiety Disorder (GAD-7), and Perceived stress scale (PSS). The results show higher levels of anxiety and perceived stress among Malaysian university students towards class reentry which causes moderate depression. The findings revealed a significant correlation between depression, anxiety, and perceived stress. Thus, policies should be implemented by educational institutions and instructors to help understand the students' mental strain and deal with future pandemic to overcome students' anxiety and emotional distress.

Workplace Determinants of Depression, Anxiety, and Stress in U.S. Mariners during the COVID-19 Pandemic.

United States (U.S.) mariners continued sailing throughout COVID-19. Many aspects of their work could make them prone to adverse mental health outcomes but research on workplace determinants of their mental health during COVID-19 is limited. Between January and July 2021 an online survey assessed the outcomes of increased depressive symptoms, increased anxiety symptoms, and increased perceived stress in addition to concerns, worries, and experiences when sailing during COVID-19, job satisfaction, and safety climate in n = 1384 U.S. mariners. Demographic measures were also collected. Logistic regression models (for depression and anxiety) and a linear regression model (for stress) were developed. We found that increased COVID-19 concerns and poor self-reported mental health were related to increased odds of likely depression and anxiety and higher stress. Mariners who experienced more adverse experiences aboard a vessel had increased stress and increased odds of depression. Poor sleep quality was also related to increased odds of depression, and poor vessel support/safety culture was related to higher stress. Differences in outcomes were seen by vessel type, age, and credential in regression analyses. Results from this study will help to prioritize interventions to minimize the mental health impacts of COVID-19, and influence evidence-based recommendations to improve the mental health of mariners going forward.

Indonesia Covid-19 Pandemic Social Media Analysis With Text Mining

This research aimed to analyze public opinion regarding Indonesia's situation in facing community restrictions (PPKM) during the Covid-19 pandemic. This research used the text mining approach to classify public opinion into two classes of the Pro and Cons classes regarding the policies, along with comparing the accuracy, precision, and recall values using two text classification methods of Naive Bayes and Support Vector Machine (SVM). The data collected were 217 tweets from Indonesia in November 2020. The Naive Bayes method showed 64% accuracy, 72% precision, and 53% recall, while the SVM method showed 63% accuracy, 70% precision, and 53 % recall. Based on these classification text methods results, researchers concluded that SVM's accuracy, precision, and recall values were not higher than Naive Bayes. © 2022 IEEE.