Online University Teaching During COVID-19: The Malaysian Experience

Malaysia, like the rest of the world, was hard hit by SARS-CoV-2, also known as COVID-19. After the first COVID-19 case was detected in Malaysia (on January 25, 2020) and traced back to three Chinese nationals, the country was put under Movement Control Order (MCO), a partial lockdown, initially for two weeks, on 18th March. Among MCO consequences: close major economic sectors and educational institutions. Public universities, which began a new semester under a Ministry of Higher Education ruling, switched to online teaching and learning. This chapter chronicles public university experiences with online teaching and learning during the COVID-19 period. A brief background captures the measures taken by the government;how these steps affected university education is appraised next;and finally, the steps taken by the universities to activate online teaching and learning. What challenges cropped up and how to deal with them are acknowledged before drawing conclusions from the online teaching and learning experiences of Malaysian universities. © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023.

The COVID-19 Pandemic and Daily Steps in the General Population: Meta-analysis of Observational Studies.

BACKGROUND: The COVID-19 pandemic has the potential to accelerate another pandemic: physical inactivity. Daily steps, a proxy of physical activity, are closely related to health. Recent studies indicate that over 7000 steps per day is the critical physical activity standard for minimizing the risk of all-cause mortality. Moreover, the risk of cardiovascular events has been found to increase by 8% for every 2000 steps per day decrement. OBJECTIVE: To quantify the impact of the COVID-19 pandemic on daily steps in the general adult population. METHODS: This study follows the guidelines of the MOOSE (Meta-analysis Of Observational Studies in Epidemiology) checklist. PubMed, EMBASE, and Web of Science were searched from inception to February 11, 2023. Eligible studies were observational studies reporting monitor-assessed daily steps before and during the confinement period of the COVID-19 pandemic in the general adult population. Two reviewers performed study selection and data extraction independently. The modified Newcastle-Ottawa Scale was used to assess the study quality. A random effects meta-analysis was conducted. The primary outcome of interest was the number of daily steps before (ie, January 2019 to February 2020) and during (ie, after January 2020) the confinement period of COVID-19. Publication bias was assessed with a funnel plot and further evaluated with the Egger test. Sensitivity analyses were performed by excluding studies with low methodological quality or small sample sizes to test the robustness of the findings. Other outcomes included subgroup analyses by geographic location and gender. RESULTS: A total of 20 studies (19,253 participants) were included. The proportion of studies with subjects with optimal daily steps (ie, ≥7000 steps/day) declined from 70% before the pandemic to 25% during the confinement period. The change in daily steps between the 2 periods ranged from -5771 to -683 across studies, and the pooled mean difference was -2012 (95% CI -2805 to -1218). The asymmetry in the funnel plot and Egger test results did not indicate any significant publication bias. Results remained stable in sensitivity analyses, suggesting that the observed differences were robust. Subgroup analyses revealed that the decline in daily steps clearly varied by region worldwide but that there was no apparent difference between men and women. CONCLUSIONS: Our findings indicate that daily steps declined substantially during the confinement period of the COVID-19 pandemic. The pandemic further exacerbated the ever-increasing prevalence of low levels of physical activity, emphasizing the necessity of adopting appropriate measures to reverse this trend. Further research is required to monitor the consequence of long-term physical inactivity. TRIAL REGISTRATION: PROSPERO CRD42021291684; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=291684.

Salutogenesis for Thriving Societies

This chapter is this handbook's ‘grand finale', addressing the potential of salutogenesis to nurture thriving societies. The handbook's editors reflect on the advancement of salutogenesis concerning theory development, applying the salutogenic model in community settings and helping society tackle crises such as COVID-19. © The Editor(s) (if applicable) and The Author(s);first edition published by Springer International Publishing, 2017, 2022 This book is an open access publication.

Doffing Corridor: Establishing Expedited High-Volume Doffing With Exposure Reduction to Contaminated Personal Protective Equipment (PPE) in a COVID-19 Hospital in India.

Background Considering the virulent nature of the COVID-19, the safety of healthcare workers (HCW) became a challenge for hospital administrators. Wearing a personal protective equipment (PPE) kit, called donning, which can be easily done by the help of another staff. But correctly removing the infectious PPE kit (doffing) was a challenge. The increased number of HCWs for COVID-19 patient care raised the opportunity to develop an innovative method for the smooth doffing of PPEs. Objective We aimed to design and establish an innovative PPE doffing corridor in a tertiary care COVID-19 hospital during the pandemic in India with a heavy doffing rate and minimize the COVID-19 virus spread among healthcare workers. Methodology A prospective, observational cohort study at the COVID-19 hospital, Postgraduate Institute of Medical Education and Research (PGIMER), Chandigarh, India, was conducted from July 19, 2020, to March 30, 2021. The time taken for PPE doffing process of HCWs was observed and compared between the doffing room and doffing corridor. The data was collected by a public health nursing officer using Epicollect5 mobile software and Google forms. The following parameters, like grade of satisfaction, time and volume of doffing, the errors in the steps of doffing, rate of infection, were compared between the doffing corridor and the doffing room. The statistical analysis was done by the use of SPSS software. Result 'Doffing corridor' decreased the overall doffing time by 50% compared to the initial doffing room. The doffing corridor solved the purpose of accommodating more HCWs for PPE doffing and an overall saving of 50% time. Fifty-one percent of HCWs rated the satisfaction rate as Good in the grading scale. The errors in the steps of doffing that occurred in the doffing process were comparatively lesser in the doffing corridor. The HCWs who doffed in the doffing corridor were three times less likely to get self-infection than the conventional doffing room. Conclusion Since COVID-19 was a new pandemic, the healthcare organizations focused on innovations to combat the spread of virus. One of these was an innovative doffing corridor to expedite the doffing process and decrease the exposure time to the contaminated items. The doffing corridor process can be considered at a high-interest rate to any hospital dealing with infectious disease, with high working satisfaction, less exposure to the contagion, and less risk of infection.

Drum Up SUPPORT: Systematic Analysis of Image-Schematic Conceptual Metaphors

Conceptual metaphors represent a cognitive mechanism to transfer knowledge structures from one onto another domain. Image-schematic conceptual metaphors (ISCMs) specialize on transferring sensorimotor experiences to domains. Natural language is believed to provide evidence of such metaphors. However, approaches to verify this hypothesis largely rely on top-down methods, gathering examples by way of introspection, or on manual corpus analyses. In order to contribute towards a method that is systematic and can be replicated, we propose to bring together existing processing steps in a pipeline to detect ISCMs, exemplified for the image schema SUPPORT in the COVID-19 domain. This pipeline consists of neural metaphor detection, dependency parsing to uncover construction patterns, clustering, and BERT-based frame annotation of dependent constructions to analyze ISCMs. © 2022 Association for Computational Linguistics.

A COMPARISON OF HOW THE TRANSPORTATION AND LOGISTICS INDUSTRY AND THE AUTOMOTIVE INDUSTRY'S SUPPLY CHAIN PROCESSES HAVE BEEN AFFECTED BY COVID-19 AND HOW ENTREPRENEURIAL COMPETENCIES COULD BE USED TO ADDRESS THEM

Since it has been established that supply chain management has traditionally been a process-oriented field with not much focus on innovation, in a post-pandemic world, engineering managers have realized that research is needed to identify which aspects of global supply chain management have the greatest need for transformation and could benefit most through the application of entrepreneurial competencies. Along those lines, the authors of this paper have earlier proposed a research model, which includes a mapping between supply chain management process steps and entrepreneurial competencies along with proposed training and organizational changes to facilitate the implementation of a more entrepreneurial approach to supply chain management processes. Using a qualitative, grounded theory approach based on two case studies, the authors focus on two industries. The differences and similarities between the two industries will be compared in this paper;thus, showing engineering managers how the model could be applied to the two different industries considered in this paper. Copyright, American Society for Engineering Management, 2022.

Improving Radiology Report Generation via Object Dropout Strategy and MLP-based Captioner

Recently, automatically generating radiology reports has been addressed since it can not only relieve the pressure on doctors but also avoid misdiagnosis. Radiology report generation is a fundamental and critical step of auxiliary diagnosis. Due to the COVID-19 pandemic, a more accurate and robust structure for radiology report generation is urgently needed. Although radiology report generation is achieving remarkable progress, existing methods still face two main shortcomings. On the one hand, the strong noise in medical images usually interferes with the diagnosis process. On the other hand, these methods usually require complex structure while ignoring that efficiency is also an important metric for this task. To solve the two aforementioned problems, we introduce a novel method for medical report generation, the termed attention-guided object dropout MLP(ODM) model. In brief, ODM first incorporates a tailored pre-trained model to pre-align medical regions and corresponding language reports to capture text-related image features. Then, a fine-grained dropout strategy based on the attention matrix is proposed to relieve training pressure by dropping content-irrelevant information. Finally, inspired by the lightweight structure of Multilayer Perceptron(MLP), ODM adopts an MLP-based structure as an encoder to simplify the entire framework. Extensive experiments demonstrate the effectiveness of our ODM. More remarkably, ODM achieves state-of-the-art performance on IU X-Ray, MIMIC-CXR, and ROCO datasets, with the CIDEr-D score being increased from 26.8% to 41.4%, 21.1% to 30.2%, and 9.1% to 19.3%, respectively. © 2022 IEEE.

Using Wearable Technology to Quantify Physical Activity Recovery: Secondary Report From the AFTER (App-Facilitated Tele-Rehabilitation) Program for COVID-19 Survivors Randomized Study.

BACKGROUND: Knowledge on physical activity recovery after COVID-19 survival is limited. The AFTER (App-Facilitated Tele-Rehabilitation) program for COVID-19 survivors randomized participants, following hospital discharge, to either education and unstructured physical activity or a telerehabilitation program. Step count data were collected as a secondary outcome, and we found no significant differences in total step count trajectories between groups at 6 weeks. Further step count data were not analyzed. OBJECTIVE: The purpose of this analysis was to examine step count trajectories and correlates among all participants (combined into a single group) across the 12-week study period. METHODS: Linear mixed models with random effects were used to model daily steps over the number of study days. Models with 0, 1, and 2 inflection points were considered, and the final model was selected based on the highest log-likelihood value. RESULTS: Participants included 44 adults (41 with available Fitbit [Fitbit LLC] data). Initially, step counts increased by an average of 930 (95% CI 547-1312; P<.001) steps per week, culminating in an average daily step count of 7658 (95% CI 6257-9059; P<.001) at the end of week 3. During the remaining 9 weeks of the study, weekly step counts increased by an average of 67 (95% CI -30 to 163; P<.001) steps per week, resulting in a final estimate of 8258 (95% CI 6933-9584; P<.001) steps. CONCLUSIONS: Participants showed a marked improvement in daily step counts during the first 3 weeks of the study, followed by more gradual improvement in the remaining 9 weeks. Physical activity data and step count recovery trajectories may be considered surrogates for physiological recovery, although further research is needed to examine this relationship. TRIAL REGISTRATION: ClinicalTrials.gov NCT04663945; https://tinyurl.com/2p969ced.

Protocol for the effectiveness evaluation of an antenatal, universally offered, and remotely delivered parenting programme 'Baby Steps' on maternal outcomes: a Born in Bradford's Better Start (BiBBS) study.

BACKGROUND: Poor perinatal mental health and maternal sensitivity towards a child in the early years can carry a long-term cost to individuals and to society, and result in negative child outcomes such as poor mental health and social emotional issues. Despite the recognition of early intervention and prevention, there is mixed evidence regarding antenatal parenting interventions that aim to enhance perinatal mental health and maternal sensitivity to prevent negative child outcomes. 'Baby Steps' is a relationship-based antenatal and postnatal parenting programme. The service evaluated in this study is delivered in a low-income and ethnically diverse community via Better Start Bradford. This study aims to assess whether the universally, and remotely delivered Baby Steps programme is effective in improving postnatal maternal sensitivity (primary outcome) and postnatal maternal mental health (secondary outcome) when compared to services as usual 6-10 weeks post-birth. It will also assess differences in birth outcomes, and differences in the prevalence of poor perinatal mental ill health through routine data. The feasibility of collecting cost and health related resource use data for a future economic evaluation will be explored. METHODS: The study is a quasi-experimental evaluation in a single centre. All participants are drawn from Born in Bradford's Better Start (BiBBS) interventional family cohort study. Intervention participants will be matched to a demographically comparable control group using propensity score matching. The required minimum sample is n = 130 (ratio 1:1) to detect a medium effect (± 2.35, d = .50) on the primary outcome-maternal-child sensitivity, using the Mothers Object Relations Scale Short Form (MORS-SF). Secondary outcomes include the Patient Health Questionnaire (PHQ-8), Generalised Anxiety Disorder assessment 7 (GAD-7), identification of poor perinatal mental health through routine data, and birth outcomes (delivery method, gestation period, low birth weight). Service delivery costs and health resource use will be gathered from routine data. DISCUSSION: This study will evaluate the effectiveness of Baby Steps for enhancing maternal-child sensitivity and maternal mental health when delivered universally and remotely. The findings regarding programme effectiveness, process, and costs will be relevant for researchers, service commissioners, and service staff. TRIAL REGISTRATION: This study was prospectively registered with ISRCTN (22/04/2022, ISRCTN12196131).

Parenthood and psychological distress among English Millennials during the second wave of the COVID-19 pandemic: evidence from the Next Steps cohort study.

PURPOSE: The COVID-19 pandemic led to disproportionate mental health responses in younger adults and parents. The aim of the study was to investigate how Millennial parents' experiences were associated with psychological distress over the first year of the pandemic. METHODS: We examined data in September 2020 (n men = 994; n women = 1824) and February 2021 (n men = 1054; n women = 1845) from the Next Steps cohort study (started ages 13-14 in 2003-04). In each wave, we examined differences in GHQ-12 scores between parent groups defined by the age and number of children, adjusting for background characteristics at ages 13-14, psychological distress at ages 25-26, and other circumstances during the pandemic. We also examined if differences varied by work status, financial situation before the outbreak and relationship status. RESULTS: Whereas mothers with one or two children and children aged 0-2 reported less distress than non-mothers in September 2020, there were no such differences in February 2021. Fathers with three or more children reported more distress in February 2021. Compared with non-fathers who worked, fathers were also disproportionally distressed if they were working with one child or with children aged 2 or less in September 2020. CONCLUSION: The distribution of psychological distress among Millennial parents and non-parents has varied by age, sex, parenting stage, work status and the timing of the pandemic. Generous family policies are needed, with special attention dedicated to parents combining work and family responsibilities.

A Two-Step Algorithm to Estimate Variable Importance for Multi-State Data: An Application to COVID-19

Survival data with a multi-state structure are frequently observed in follow-up studies. An analytic approach based on a multi-state model (MSM) should be used in longitudinal health studies in which a patient experiences a sequence of clinical progression events. One main objective in the MSM framework is variable selection, where attempts are made to identify the risk factors associated with the transition hazard rates or probabilities of disease progression. The usual variable selection methods, including stepwise and penalized methods, do not provide information about the importance of variables. In this context, we present a two-step algorithm to evaluate the importance of variables for multi-state data. Three different machine learning approaches (random forest, gradient boosting, and neural network) as the most widely used methods are considered to estimate the variable importance in order to identify the factors affecting disease progression and rank these factors according to their importance. The performance of our proposed methods is validated by simulation and applied to the COVID-19 data set. The results revealed that the proposed two-stage method has promising performance for estimating variable importance. © 2023 Tech Science Press. All rights reserved.

Time-varying associations between loneliness and physical activity: Evidence from repeated daily life assessments in an adult lifespan sample.

Physical activity is a behavior that promotes physical and mental health; yet physical activity has decreased during the COVID-19 pandemic. To promote health during times of challenge, it is important to identify potential barriers to this key health behavior, such as loneliness. This brief report extends previous research on physical activity and loneliness that mainly focused on between-person differences to examine their time-varying associations at the within-person level using repeated daily life assessments. From April 2020 to August 2020, data were collected from a sample of 139 community-dwelling Canadian adults (M age = 40.65 years, SD = 18.37; range = 18-83 years). Each evening for 10 consecutive days, participants reported their loneliness, number of steps, and minutes of moderate-to-vigorous physical activity. Results revealed that, in line with our hypotheses, on days when participants reported more loneliness they also engaged in less moderate-to-vigorous physical activity than on less lonely days (estimate = -0.24, p = 0.007); there was a significant negative association between loneliness and daily number of steps (estimate = -18.42, p = 0.041). In contrast, at the between-person level, overall loneliness was not associated with overall physical activity engagement after accounting for within-person differences and control variables (age, sex, day in study). From an intervention perspective, our findings suggest that it is promising to tackle loneliness on a day-to-day basis to increase physical activity one day at a time. This may be especially relevant during times mandating social-distancing, but also at other times when individuals experience greater feelings of loneliness.

Mental health inequalities during the second COVID-19 wave among Millennials who grew up in England: Evidence from the Next Steps cohort study.

BACKGROUND: There is relatively little evidence on socioeconomic inequalities in mental health among young adults after the end of the first COVID-19 wave in the UK, despite this group having faced the worse mental health and economic shocks across age groups at the start of the pandemic. METHODS: We examined differences in mental health across two points - September 2020 and February 2021 - in a cohort of 4167 Millennials aged 30-31 using life dissatisfaction, psychological distress (GHQ-12), anxiety (GAD-2), and depressive symptoms (PHQ-2). We report adjusted prevalence ratios (aPR) from random-intercept models, testing differences by educational attainment and time-varying conditions (relationship status, living arrangements with adults and children, work status, and financial changes compared with before the outbreak), adjusting for baseline covariates at ages 13-14 and health covariates at ages 25-26. RESULTS: Only dissatisfaction with life changed between time points (PR = 1.26, 95%CI 1.02-1.55). Educational attainment was not significantly associated with mental health. Being single (aPRs from 1.36 to 1.89) and being financially worse off since the start of the pandemic (aPRs from 1.58 to 1.76) were each associated with worse mental health. These associations did not further vary by educational attainment. CONCLUSION: Among Millennials who grew up in England, educational attainment was not associated with mental health whereas negative social and financial conditions were associated with worse mental health during the second COVID-19 wave. Mental health inequalities in this generation are likely to have continued increasing after the end of the first COVID-19 wave.

Protocol Design for Surveillance of Risk Factors of Non-communicable Diseases During the COVID-19 Pandemic: An Experience from Iran STEPS Survey 2021

Background: Regarding the growing burden of non-communicable diseases (NCDs) and exposure to their risk factors, and the continuous need for nationwide data, we aimed to develop the latest round of the STEPwise Approach to NCD Risk Factor Surveillance (STEPS) survey in 2021 in Iran, while the COVID-19 pandemic was still present.Methods: In addition to the three main steps of this survey, including questionnaires, physical measurements, and laboratory assessments, we adapted the survey with the situation caused by the COVID-19 pandemic, by adding to various aspects of study phases and changing some scientific and executive procedures in this round of STEPS survey in Iran. These changes were beyond the initial novelties embedded within the survey before the pandemic, by refining the study protocol benefiting from the previous experiences of the STEPS survey.Results: By amending the required changes, we could include a total of 27 874 individuals in the first step of the survey. This number was 27 745 and 18119 for the second and third steps. Comparing the preliminary results with the previous nationwide surveys, this study was highly representative on both national and provincial levels. Also, implementing the COVID-19 prevention and control strategies in all stages of survey led to the least infection transmission between the study investigators and participants.Conclusion: The novel initiatives and developed strategies in this round of Iran STEPS survey provide a state-of-the-art protocol for national surveys in the presence of an overwhelming catastrophe like the COVID-19 pandemic and the triggered limitations and shortages of resources.

Democratising large scale instrument-based science through e-Infrastructure

Modern scientific instruments are becoming essential for discoveries because they provide unprecedented insight into physical or biological events - often in real time. However, these instruments may generate large amounts of data, and increasingly they require sophisticated e-infrastructure for analysis, storage and archive. The increasing complexity and scale of the data, processing steps and systems has made it difficult for domain scientists to perform their research, narrowing the user base to a select few. In this paper, we present a framework that democratises large-scale instrument-based science, increasing the number of researchers who can engage. We discuss a prototype at the University of Queensland. The system is illustrated through two case studies, one involving light microscopy imaging of the innate immune system, and the other electron microscopy imaging of the SARS-CoV-2 viral proteins. © 2022 IEEE.

The levels of BMI and patterns of obesity and overweight during the COVID-19 pandemic: Experience from the Iran STEPs 2021 survey.

Background: Obesity and its increasing burden have become an urgent health problem all over the world. Benefiting from a national representative sample, the present study aimed to estimate the distribution of body mass index (BMI) levels and its association with metabolic and lifestyle risk factors in an Iranian adult population by sex, age, and geographical distribution. Methods: This study involves a national survey of noncommunicable disease risk factor surveillance (STEPs) in Iran. Through systematic random sampling, in compliance with safety considerations during the COVID-19 pandemic, of the 28,520 adults who gave voluntary consent and included in the study, 27,874 participants completed the questionnaires (step 1), 27,745 individuals were anthropometrically measured (step 2), and 18,119 individuals completed laboratory evaluation (step 3). Anthropometric measurements followed based on standard protocols and by using calibrated instruments. Results: In 2021, the national prevalence of normal weight, obesity, and overweight/obesity in ≥18-year-old Iranian adults was estimated at 33.61% (95% CI: 32.99-34.23), 24.96% (24.39-25.53), and 63.02% (62.39-63.65), respectively. Compared to women, Iranian men had a lower mean BMI [25.54 (24.95-26.13 vs. 27.6 (27.07-28.12) kg/m2] (p < 0.001). There was also a significant difference in the national prevalence rate of overweight/obesity [women: 66% (61-71), men: 53% (46-60) (p < 0.001)]. The prevalence of obesity was significantly higher in participants suffering from metabolic and lifestyle risk factors. The study of the geographical extent of obesity and overweight shows that compared to national levels, the highest prevalence of being underweight was seen in the southeastern provinces. On the other hand, the highest prevalence of obesity belonged to the northeastern and central provinces. The highest provincial prevalence of obesity was almost 2.5-fold higher than the lowest provincial prevalence. Conclusion: The study reveals a significant difference between the prevalence of obesity in male and female participants and between different regions of the country. These findings will help policymakers, clinicians, and researchers to more accurately estimate the obesity/overweight problem and to implement more effective interventional programs to promote strategies of prevention and control of weight gain.

Consumer-Based Activity Trackers as a Tool for Physical Activity Monitoring in Epidemiological Studies During the COVID-19 Pandemic: Development and Usability Study.

BACKGROUND: Consumer-based physical activity trackers have increased in popularity. The widespread use of these devices and the long-term nature of the recorded data provides a valuable source of physical activity data for epidemiological research. The challenges include the large heterogeneity between activity tracker models in terms of available data types, the accuracy of recorded data, and how this data can be shared between different providers and third-party systems. OBJECTIVE: The aim of this study is to develop a system to record data on physical activity from different providers of consumer-based activity trackers and to examine its usability as a tool for physical activity monitoring in epidemiological research. The longitudinal nature of the data and the concurrent pandemic outbreak allowed us to show how the system can be used for surveillance of physical activity levels before, during, and after a COVID-19 lockdown. METHODS: We developed a system (mSpider) for automatic recording of data on physical activity from participants wearing activity trackers from Apple, Fitbit, Garmin, Oura, Polar, Samsung, and Withings, as well as trackers storing data in Google Fit and Apple Health. To test the system throughout development, we recruited 35 volunteers to wear a provided activity tracker from early 2019 and onward. In addition, we recruited 113 participants with privately owned activity trackers worn before, during, and after the COVID-19 lockdown in Norway. We examined monthly changes in the number of steps, minutes of moderate-to-vigorous physical activity, and activity energy expenditure between 2019 and 2020 using bar plots and two-sided paired sample t tests and Wilcoxon signed-rank tests. RESULTS: Compared to March 2019, there was a significant reduction in mean step count and mean activity energy expenditure during the March 2020 lockdown period. The reduction in steps and activity energy expenditure was temporary, and the following monthly comparisons showed no significant change between 2019 and 2020. A small significant increase in moderate-to-vigorous physical activity was observed for several monthly comparisons after the lockdown period and when comparing March-December 2019 with March-December 2020. CONCLUSIONS: mSpider is a working prototype currently able to record physical activity data from providers of consumer-based activity trackers. The system was successfully used to examine changes in physical activity levels during the COVID-19 period.

Intelligent Firefly Algorithm Deep Transfer Learning Based COVID-19 Monitoring System

With the increasing and rapid growth rate of COVID-19 cases, the healthcare scheme of several developed countries have reached the point of collapse. An important and critical steps in fighting against COVID-19 is powerful screening of diseased patients, in such a way that positive patient can be treated and isolated. A chest radiology image-based diagnosis scheme might have several benefits over traditional approach. The accomplishment of artificial intelligence (AI) based techniques in automated diagnoses in the healthcare sector and rapid increase in COVID-19 cases have demanded the requirement of AI based automated diagnosis and recognition systems. This study develops an Intelligent Firefly Algorithm Deep Transfer Learning Based COVID-19 Monitoring System (IFFA-DTLMS). The proposed IFFA-DTLMS model majorly aims at identifying and categorizing the occurrence of COVID19 on chest radiographs. To attain this, the presented IFFA-DTLMS model primarily applies densely connected networks (DenseNet121) model to generate a collection of feature vectors. In addition, the firefly algorithm (FFA) is applied for the hyper parameter optimization of DenseNet121 model. Moreover, autoencoder-long short term memory (AE-LSTM) model is exploited for the classification and identification of COVID19. For ensuring the enhanced performance of the IFFA-DTLMS model, a wide-ranging experiments were performed and the results are reviewed under distinctive aspects. The experimental value reports the betterment of IFFA-DTLMS model over recent approaches. © 2023 Tech Science Press. All rights reserved.

Relationship Between the Number of Steps Taken During Lockdown Caused by the COVID-19 Pandemic and Low Back Pain

Introduction: In 2020, the whole world was overwhelmed by the SARS-CoV-2 coronavirus threat. In order to prevent the spread of the virus, national governments introduced restrictions of movement in public spaces, closing schools and universities, while many companies switched to remote working. In addition to the obvious benefits of the above changes, numerous side-effects could be observed. One of them is pain in the locomotive organs caused by a sedentary lifestyle. Objective: The main objective of the study was to assess the relationship between physical activity during quarantine, caused by the COVID-19 pandemic, and the occurrence of spinal pain. Material and methods: The study comprised 55 participants (29 women and 26 men) who attended physiotherapeutic consultations due to low back pain. For comparative purposes, they were divided into 2 groups: Group 1 (n=24) included active persons, while Group 2 (n=31) consisted of inactive persons. The survey was conducted in June 2020. In the study, the reading of pedometers from mobile phones was used, as well as the Rolland-Morris Questionnaire, Laitinen’s Pain Scale and the authors’ own questionnaire. The respondents were asked to share the pedometer results from given weeks before, during and after restrictions caused by COVID-19. Results: Physically active persons (those carrying out health training) performed more steps before introduction of the restrictions (p<0.001). After their implementation, all-day activity significantly decreased in both groups. The evaluation of pain characteristics revealed significant differences (between groups) in 2 categories – pain intensity and physical activity limitation. Group 2 individuals also reported greater functional limitations. Conclusion: In physically inactive people, the intensity of low back pain was much higher. This proves a relationship between activity levels and pain. © AWF Krakow.