A Video-based Physiotherapy Exercise Dataset

A patient recovering from a stroke, injury, or physical pain needs continuous physiotherapy and rehabilitation to achieve a quick and complete recovery. It is often difficult for elderly people to visit clinics to undertake exercises. Finding physiotherapists and relevant treatments becomes more difficult, particularly in an epidemic condition like covid-19. AI-driven at-home physiotherapy exercise monitoring and assessment systems can be the straightforward feasible solution in this regard. Accurate recognition of particular exercises, exercise assessments, providing feedback, etc. are parts of the whole system, which a machine typically learns through a data-heavy training process. A key issue in this regard is the lack of specific training data for physiotherapy exercises. There exist only a few datasets in the literature that are designed for physiotherapy exercises;most of them however are based on multiple body sensors or Kinect device. Sensor devices are quite costly, and their availability is not guaranteed everywhere. In contrast, video data can be a better alternative, where video can be acquired easily from an available smartphone camera or desktop/laptop webcam. Addressing this issue, we present a new video-based physiotherapy exercise database containing 1237 video clips of 14 physiotherapy exercises that were carefully elicited from an extensively conducted survey from multiple physiotherapists. Exercises were recorded with 28 male and female subjects within various lighting conditions, camera angles, and camera jitters to simulate the real-world setting. Several machine learning algorithms were utilized to carry out an experimental study on the dataset, and the results are provided for future reference. © 2022 IEEE.

Status of Antibody against Severe Acute Respiratory Syndrome Coronavirus 2: Preliminary Reports on Seroprevalence of Covid 19 in among Health Care Workers

Introduction: Large number of health care workers (HCW) were infected and died due to COVID-19 infection. It is needed to know the actual seroprevalence of COVID in HCWs to assess the risk and to take protective measures. This study was aimed to measure IgG antibodies against nucleocapsid protein (N) of COVID as a serological marker for detection of viral status in risk prone HCW of Bangladesh and possible association with reno-cardio-metabolic risk factors Methods: This longitudinal study was conducted from May 2021 to January 2022 among physicians and non-physician health care workers (HCW) in three non- COVID designated tertiary hospitals in Bangladesh. Participants' demographic data, medical history and information on past COVID-19 infection and vaccination status were collected. Serial blood samples were collected at 1.5 month in all (n=633) later at 3, 6 and 9 months in vaccinated group. A qualitative measurement of IgG antibody against nucleocapsid protein (N) of SARS-CoV-2 was done by was done by CMIA developed by Abbott (FDA-EUA approved). Result(s): The mean age was 35+/-10years where70% were female. Physician 32%, Nurse 45% and others was 23%. Diabetics were 9.5%, hypertensive 9% and asthma in 5.1%. The two doses of vaccine against COVID-19was completed in 56%. History of past COVID-19 infection was found among 20% participants at recruitment, out of which 13% was diagnosed by rt-PCR. History of past COVID-19 infection was found among 18% participants based on 1gG against N protein. But the subjects in two groups were different. Combination of RTPCR and N protein igG showed 35% seropositive for covid. Comparisons between covid infection positive vs. negative showed only age was different (37+/-11 vs. 34+/-9, years p<0.001) but other risk factors like BMI, SBP, DBP, S Albumin, glucose, hemoglobin were not different (P=NS) between the two groups. Further comparisons for eGFR cut-offs showed higher infection in lower eGFR (infection present vs. absent for >90ml/min group was 17% & 83% and in 60-90 ml/min group 32% &. 68 %). Prevalence of COVID 19 infection based on presence of N antibody (cutoff value >1.5) among vaccinated HCWs at 1.5, 6 and 9 month was 13.6%, 8.8% and 7.7% respectively. The mean titer of IgG (against N protein) >1.5 among vaccinated HCWs at 1.5 month was 3.1+/-1.5 and reduced to 0.87+/-0.96 at month 6 (p<0.001). Conclusion(s): The prevalence of COVID-19 infection in HCWs during the second wave was 35% based on test for RTPR or IgG against N protein positivity. In vaccinated persons, based on antibody against N protein, re-infection rate was around 8% up to 9 months post vaccine. Although no difference was seen for covid infection for cardio-metabolic risk factors, there seems to have some relation of higher infectivity with decreased GFR level. No conflict of interestCopyright © 2023

Neonatal necrotizing enterocolitis due to COVID-19. A case report.

Digestive symptoms have been reported in an important proportion of children with COVID-19, and the clinical expression of critical patients with COVID-19 is thought to result from progressive increase of inflammation and an unusual trend of hypercoagulation. We report a newborn received with abdominal distension, green vomiting and imaging suggestive for enterocolitis. He had a close contact with COVID-19 and the PCR for SARS-CoV-2 came back positive. Despite the supportive measures, his condition deteriorated and a surgery was decided. The surgical exploration found an ischemic bowel. The therapeutic measures were ineffective as the child passed away a few hours after surgery despite the resuscitation treatment performed. The confirmed enterocolitis happening within the period of acute infection by SARS-CoV-2, the NEC was likely a manifestation of COVID-19.

Developing an analytical framework for estimating food security indicators in the United Arab Emirates: A review.

Rapid population growth, climate change, limited natural resources, and the COVID-19 pandemic contribute to increased global hunger, necessitating intensive efforts to ensure food security and nutrition (FSN). Previous FSN approaches covered some dimensions, but not all, resulting in significant gaps in food security indicators. The Gulf Cooperation Council (GCC) and the Middle East and North Africa (MENA) regions have received less attention in food security studies, thus far necessitating considerable effort to develop an appropriate analytical framework. This study reviewed articles and international reports of FSN indicators, drivers and policies, methods, and models and extracted the challenges and gaps from the global and UAE contexts. The UAE and the world have gaps in FSN drivers, indicators, and methods, necessitating potential solutions to meet future challenges such as rapid population growth, pandemics, and limited natural resources. As a result, we created a newly developed analytical framework that addresses the shortcomings of previous approaches such as sustainable food systems developed by FAO and the Global Food Security Index (GFSI) and covers all aspects of food security. Gaps in knowledge in FSN drivers and policies, indicators, big data, methods, and models were considered in the developed framework, which has specific advantages. The novel developed framework addresses all food security dimensions (access, availability, stability, and utilization), ensuring poverty reduction, food security, and nutrition security while outperforming previous approaches (i.e., FAO and GFSI). The developed framework could be used successfully not only in the UAE and MENA, but also, globally, helping to solve food insecurity and malnutrition for future generations. The scientific community and policymakers should disseminate such solutions to address global food insecurity and ensure nutrition for future generations in the face of rapid population growth, limited natural resources, climate change, and spreading pandemics. Supplementary Information: The online version contains supplementary material available at 10.1007/s10668-023-03032-3.

COVID-19 Tracheostomy Outcomes.

OBJECTIVES: (1) Assess overall COVID-19 mortality in ventilated patients with and without tracheostomy. (2) Determine the impact of tracheostomy on mechanical ventilation duration, overall length of stay (LOS), and intensive care unit (ICU) LOS for patients with COVID-19. STUDY DESIGN: Case series with planned chart review. SETTING: Single-institution tertiary care center. METHODS: Patients with COVID-19 who were ≥18 years old and requiring invasive positive pressure ventilation (IPPV) met inclusion criteria. Patients were stratified into 2 cohorts: IPPV with tracheostomy and IPPV with intubation only. Cohorts were analyzed for the following primary outcome measures: mortality, LOS, ICU LOS, and IPPV duration. RESULTS: An overall 258 patients with IPPV met inclusion criteria: 46 (18%) with tracheostomy and 212 (82%) without (66% male; median age, 63 years [interquartile range, 18.75]). Average LOS, time in ICU, and time receiving IPPV were longer in the tracheostomy cohort (P < .01). Ability to wean from IPPV was similar between cohorts (P > .05). The number of deaths in the nontracheostomy cohort (54%) was significantly higher than the tracheostomy cohort (29%, P < .01). CONCLUSIONS: While tracheostomy placement in patients with COVID-19 did not shorten overall LOS, mechanical ventilation duration, or ICU LOS, patients with a tracheostomy experienced a significantly lower number of deaths vs those without. One goal for tracheostomy is improved pulmonary toilet with associated shortened IPPV requirements. Our study did not identify this advantage among the COVID-19 population. However, this study demonstrates that the need for tracheostomy in the COVID-19 setting does not portent a poor prognostic factor, as patients with a tracheostomy experienced a significantly higher survival rate than their nontracheostomy counterparts.

Supply chain accountability, COVID-19, and violations of workers' rights in the global clothing supply chain

Purpose: This study aims to contribute to the debate on the efficacy of softer regulations to prevent violations of workers' rights in the global clothing supply chain. Design/methodology/approach: This study draws on value trap and adverse incorporations as a theoretical lens to understand the reasons behind the continued violations of workers' rights. The empirical findings are based on an analysis of 24 semi-structured interviews with workers and owners. Extensive documentary evidence to track the plight of workers in Bangladeshi clothing factories during the pandemic. Findings: The study demonstrates how imbalances in supply chain relationships allow retailers to take advantage of the pandemic. The authors find that some retailers worsened the working conditions by cancelling orders, demanding discounts on old orders and forcing suppliers to agree to a lower price for new orders. Large brands and retailers' responses to the COVID-19 pandemic remind us that softer regulations, such as third-party audits, are likely to be ineffective given the power imbalance at the heart of the supply chain. Practical implications: The study presents a case for regulatory frameworks and intense stakeholder activism to encourage large retailers and brands to behave responsibly. This is especially important when a supply chain is value-trapped and workers are adversely incorporated and unprotected. Originality/value: Drawing on studies on adverse incorporations, value-trapped supply chains and the plight of workers during the COVID-19 pandemic, the study offers a broader understanding of the continued violation of workers' rights and the efficacy of softer regulations. © 2023, Emerald Publishing Limited.

Geo-Spatial Disease Clustering for Public Health Decision Making

An explosion of interest has been observed in disease mapping with the developments in advanced spatial statistics, data visualization and geographic information system (GIS) technologies. This technique is known as "Geo-Spatial Disease Clustering," mainly used for visualization and future disease expansion prediction. Its importance has been overwhelmingly observed since the COVID-19 pandemic outbreak. Government, Medical Institutes, and other medical practices gather large amounts of data from surveys and other sources. This data is in the form of notes, databases, spread sheets and text data files. Mostly this information is in the form of feedback from different groups like age group, gender, provider (doctors), region, etc. Incorporating such heterogeneous nature of data is quite challenging task. In this regard, variety of techniques and algorithms have been proposed in the literature, but their effectiveness varies due to data types, volume, format and structure of data and disease of interest. Mostly, the techniques are confined to a specific data type. To overcome this issue, in this research, a data visualization technique combined with data warehousing and GIS for disease mapping is proposed. This includes data cleansing, data fusion, data dimensioning, analysis, visualization, and prediction. Motivation behind this research is to create awareness about the disease for the guidance of patients, healthcare providers and government bodies. By this, we can extract information that describes the association of disease with respect to age, gender, and location. Moreover, the temporal analysis helps earlier prediction and identification of disease, to be care of and necessary avoiding arrangements can be taken.

The Role of Government Reform in Improving Voluntary Tax Compliance in the Digital Economy: The Bangladesh Experience

This chapter analyzes the role of government reforms concerning digitalization and automation of the tax system in enhancing voluntary tax compliance in a developing country, using Bangladesh as a case study. Through an online, two-stage, key-informants survey, the study identified the advantages, weaknesses, and challenges of implementing government reforms in tax administration based on digitalization. The study also incorporated the impact of the coronavirus disease pandemic to understand how a digitalized tax system can help manage a revenue system in the face of a pandemic. The empirical results revealed that, in general, participants perceived that digitalization and automation of the tax system play an important role in improving domestic revenue mobilization through improving good governance in Bangladesh's income tax administration. A majority (88%) of the participants perceived that a digitalized tax administration can help collect tax revenues during a situation like the coronavirus disease pandemic. The study therefore highlighted the need to implement a digitalized tax system as a key policy option to improve voluntary tax compliance effectively and make it more accurate and efficient. JEL Classifications: H21, H24, H26 © 2023 selection and editorial matter, Asian Development Bank Institute;individual chapters, the contributors

A Comparative Study on COVID-19 Fake News Detection Using Different Transformer Based Models

The rapid advancement of social networks and the convenience of internet availability have accelerated the rampant spread of false news and rumors on social media sites. Amid the COVID-19 epidemic, this misleading information has aggravated the situation by putting people's mental and physical lives in danger. To limit the spread of such inaccuracies, identifying the fake news from online platforms could be the first and foremost step. In this research, the authors have conducted a comparative analysis by implementing five transformer-based models such as BERT, BERT without LSTM, ALBERT, RoBERTa, and a Hybrid of BERT & ALBERT in order to detect the fraudulent news of COVID-19 from the internet. COVID-19 Fake News Dataset has been used for training and testing the models. Among all these models, the RoBERTa model has performed better than other models by obtaining an F1 score of 0.98 in both real and fake classes. © 2022 IEEE.

Risk Communication During COVID-19 Pandemic: Impacting Women in Bangladesh

Risk communication during COVID-19 is essential to have support, but it is challenging in developing countries due to a lack of communication setup. It is more difficult for the low-income, marginal communities, and specifically, women in developing countries. To understand this, particularly during the COVID-19 pandemic, we conducted a qualitative study among N = 37 women (urban 20, rural = 17) across Bangladesh that presents the risk communication factors related to social and financial challenges. It reveals that the majority of the urban communities lack communication with local authorities, where urban low-income communities are the worst sufferers. Due to that, the majority of the urban participants could not get financial support, whereas the rural participants received such support for having communications with local authorities during the pandemic. However, access to technology helped some participants share and receive pandemic-related information about risk communication, and the adoption of financial technology helped to get emergency financial support through risk communication. Moreover, this work is expected to understand the role of risk communication during the COVID-19 pandemic among women in Bangladesh.

Successful Project Completion During the COVID-19 Pandemic - A Lesson Learnt

COVID-19 pandemic has taught us how to continue with the day-to-day activities interacting and working from remote locations. In this paper, we have highlighted the positive approach necessary to complete a project with success under this constraint by interacting regularly with the relevant stakeholders keeping focus on the final project deliverables. The salient points with supporting references are chalked out which might be helpful for others to follow if faced with stressful situations that COVID-19 pandemic taught us. © 2022, Springer Nature Switzerland AG.

Covidaroundus: Social distancing made easier

To reduce the dispersion of COVID - 19, people need to maintain safe distance from each other. This paper proposes a mobile application solution that keeps track of the COVID - 19 positive individuals in a certain area. With the help of the infected person's position uploaded in the cloud system, a location-based recommendation (i.e. informing people about a danger zone) is provided to the related users. Taking the pandemic into consideration, a proper visualization of users' location is made on the map using geospatial hotspot and location-based services. This paper describes the development of the mobile application that uses GPS data to pinpoint the infected person's location and create a danger zone based on the information. The accuracy of the services (provided by the application) was tested and confirmed through experiments. © 2021 IEEE.

Developing new lines of Japonica rice for higher quality and yield under arid conditions.

Rice is the world's largest food crop, and its production needs to be doubled by 2050 to cope with population growth and associated demand. In addition to the value of improving yields, quality is also important for breeders and consumers, but it pays less attention in arid regions. During two successive summer growing seasons, the experimental material focused on 34 genotypes developed from different crosses on Fn generation after fixation as well as six of the most recent commercial cultivars used for comparisons. The results showed that a high yield of grain followed by high milling and grain quality characteristics were observed among the 34 genotypes used in this analysis. Highly important and positive correlations between the percentage of hulling and the percentage of milling (0.424) and the yield ability could be accomplished by choosing the number of panicles per plant and the weight of the panicles. Selection criteria for good quality should be met by the percentage of head rice and many mineral elements, particularly zinc and iron. As a consequence, the genotypes M.J 5460S/SK105-1, M.J 5460S/GZ7768-1, M.J 5460S/G177-1, M.J 5460S/SK105-3 and M.J 5460S/SK106-4 had desirable high yield and quality characteristics and could be used as promising accessions to the rice breeding program in arid regions. In addition to commercial genotypes, improved Japonica rice genotypes could be produced in arid conditions for higher yield and quality, leading to an increase in total production, supporting food security and nutrition.

Electrochemical determination of hydrazine in surface water on Co(OH)2 nanoparticles immobilized on functionalized graphene interface

Still the whole world is straggling for the pure surface water monitoring which is time consuming and expensive work. Thus, a quick, selective and authentic measuring tool is anticipated for continuous monitoring the addition of chemical contaminants, such as hydrazine (N2H4). In this study, we have developed a Co(OH)2 nanoparticles decorated benzaldehyde-functionalized graphene (denoted as RGO/DHB/Co(OH)2) electrochemical sensor for selective determination of N2H4 from surface water. The electrochemical experiments are signifying its potential catalytic activity towards the oxidation of N2H4. Amperometric response suggests that this electrode can perform at the broad linear concentration range from 5 to 1700 µM at a lower limit of detection of 0.165 µM with good sensitivity of 1446.82 µA mM−1 cm−2 by <2 s. The RGO/DHB/Co(OH)2 exhibits nonsignificant interference during N2H4 detection in presence of several interferents such as primary amines, biomolecules and some common anions/cations. The admirable stability, repeatability, reproducibility and trace-level detection of N2H4 in various surface water samples have proven that the RGO/DHB/Co(OH)2 is an efficient tool for real-time application towards N2H4 detection and can contribute its potentiality against the current worldwide pandemic COVID-19. Importantly, the reaction mechanism of N2H4 oxidation has revealed at the RGO/DHB/Co(OH)2 surface by easy demonstration. © 2020