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1.
Int J Environ Sci Technol (Tehran) ; : 1-16, 2022 Jun 06.
Article in English | MEDLINE | ID: covidwho-1881542

ABSTRACT

Amid COVID-19, world has gone under environmental reformation in terms of clean rivers and blue skies, whereas, generation of biomedical waste management has emerged as a big threat for the whole world, especially in the developing nations. Appropriate biomedical waste management has become a prime concern worldwide in the pandemic era of COVID-19 as it may affect environment and living organisms up to a great extent. The problem has been increased many folds because of unexpected generations of hazardous biomedical waste which needs extraordinary attentions. In this paper, the impacts and future challenges of solid waste management especially the biomedical waste management on environment and human beings have been discussed amid COVID-19 pandemic. The paper also recommends some guidelines to manage the bulk of medical wastes for the protection of human health and environment. The paper summarizes better management practices for the wastes including optimizing the decision process, infrastructure, upgrading treatment methods and other activities related with the biological disasters like COVID-19. As achieved in the past for viral disinfection, use of UV- rays with proper precautions can also be explored for COVID-19 disinfection. For biomedical waste management, thermal treatment of waste can be an alternative, as it can generate energy along with reducing waste volume by 80-95%. The Asian Development Bank observed that additional biomedical waste was generated ranged from 154 to 280 tons/day during the peak of COVID-19 pandemic in Asian megacities such as Manila, Jakarta, Wuhan, Bangkok, Hanoi, Kuala Lumpur.

2.
International Journal of Logistics Research and Applications ; 2022.
Article in English | Scopus | ID: covidwho-1878675

ABSTRACT

Micro, small, and medium enterprises (MSMEs) play an essential role in economic growth. COVID-19 severely affected this sector, given its dependence on logistics. Logistics 4.0 is a progressive and vital technology for the MSME sector in developed economies. However, certain inhibitors cause MSMEs to face criticality and difficulty when adopting Logistics 4.0. Therefore, the authors first identified fourteen inhibitors through a detailed structured literature review and then used the Delphi method to finalise the inhibitors for further analysis. Furthermore, the modified total interpretive structural modelling (M-TISM) technique was applied to identify the levels and interrelationships among the inhibitors. Subsequently, the inhibitors were categorised into four main clusters by their dependence and driving power using matrice d’impacts croisés multiplication appliquée á un classment (MICMAC) analysis. This study reveals that MSMEs must prioritise five critical inhibitors during the Logistics 4.0 adoption process. The authors also develop five propositions. Timely action on the recommendations can help MSMEs owners, managers, and employees quickly adopt Logistics 4.0. Finally, the authors discuss theoretical and managerial implications and future research directions for a better understanding of adopting Logistics 4.0. © 2022 Informa UK Limited, trading as Taylor & Francis Group.

3.
Acta Neurologica Taiwanica ; 31(4):167-170, 2022.
Article in English | Scopus | ID: covidwho-1877042

ABSTRACT

Purpose: To highlight the factors leading to the delayed diagnosis of basilar artery occlusion and poor outcome in the postpartum period during the prevailing Corona Virus Disease-2019 (COVID-19) pandemic. Case report: We here report a case of a 34-year female who presented with a headache localized to the occipital region after cesarean section under spinal anesthesia. Her headache severity increased over time, and she developed a generalized seizure episode and became unconscious. Subsequently, basilar artery thrombosis was diagnosed. Despite all efforts, she succumbed to death. We believe that we might have saved the patient's life if we could have made the diagnosis beforehand. Conclusion: We recommend that unless shown otherwise, postpartum headache and neck discomfort, even in individuals with no known risk factors, should have a low index of suspicion, early diagnosis using non-invasive radiological study such MRI to rule out this uncommon but deadly illness quickly. © 2022, Neurological Society R.O.C (Taiwan). All rights reserved.

4.
Journal of Family Medicine and Primary Care ; 11(5):1664-1671, 2022.
Article in English | CAB Abstracts | ID: covidwho-1875930

ABSTRACT

Upsurge in mucormycosis cases in the second wave of SARS CoV2 infection in India has been reported. Uncontrolled diabetes is the major predisposing risk factor for these cases. The early diagnosis and surgical intervention with medical treatment may result in good clinical outcomes. The glycaemic control in diabetic patients also favours better treatment outcome in patients suffering from mucormycosis.

5.
1st International Conference on Technologies for Smart Green Connected Society 2021, ICTSGS 2021 ; 107:6607-6620, 2022.
Article in English | Scopus | ID: covidwho-1874796

ABSTRACT

Predictable and unexpected events have long threatened the continuity and profitability of supply chains, especially multinational ones. Human-made catastrophes and natural tragedies can cause supply chain interruptions. Several events, such as the earthquakes in Gujarat (2001). The COVID-19 epidemic has thrown supply and demand into disarray, and most businesses have yet to devise a strategy for enhancing their resilience and recovery. Industry 4.0 refers to a series of principles, enabling technologies, and methods to make manufacturing systems more evolving, autonomous, adaptable, and precise. The Proposed hypothesis is that the Impact of Industry 4.0 practices positively impacts Supply Chain Resilience, and different Artificial Intelligence techniques are incorporated have a significant effect on Supply chain resilience. The study's findings indicate that industry 4.0 technologies, i.e., artificial intelligence have a substantial importance on the supply chain and its resilience. © The Electrochemical Society

6.
2022 International Conference on Sustainable Computing and Data Communication Systems, ICSCDS 2022 ; : 1583-1590, 2022.
Article in English | Scopus | ID: covidwho-1874295

ABSTRACT

The world is witnessing an unprecedented catastrophe as a result of the COVID-19 (Coronavirus Disease) epidemic, which has spread to approximately 216 nations and territories throughout the globe. A COVID-19 infection may progress to pneumonia, which can be diagnosed by CXR (Chest X-Ray) examination and should be treated as soon as possible after diagnosis. This work is intended to examine the use of Artificial Intelligence (AI) in speedy precise diagnosis of COVID-19 pneumonia utilizing digital CXR pictures, as well as to construct a robust computer-aided application for automated classification of COVID-19 pneumonia from other pneumonia as well as normal images. In this research, we use a standard machine learning (ML) technique that is effective. The SVM (Support Vector Machine) classification technique was used in the development of the model. The purpose of this research has been to determine the role of machine learning, image processing, image segmentation, and feature extraction in fast or accurate identification of COVID19 chest X-ray or CT images. We assessed the performance of ML techniques on chest X-ray pictures as well as CT scans to COVID-19 diagnosis in this paper. The model's performance was assessed using relevant classification measures, such as accuracy, precision, recall, F1 score, among others. The model is capable of identifying COVID-19 patients from CXRs with training accuracy of 100 percent. We believe this high-accuracy reasonably fast Computer-Aided Diagnosis (CAD) technique might be extremely beneficial in the containment of the pandemic. © 2022 IEEE.

7.
Data Science for COVID-19: Volume 2: Societal and Medical Perspectives ; : 167-189, 2021.
Article in English | Scopus | ID: covidwho-1872847

ABSTRACT

Witness the coronavirus disease 2019 (COVID-19) virus becoming more deadly. Artificial intelligence (AI) scientists are using social media, the web, and other knowledge machine learning techniques to look for subtle signs that the disease may spread elsewhere. AI is a weapon in the battle against the infectious pandemic that has had impacts on the whole planet since early 2020. It echoes the high hopes of data science to confront the coronavirus in the press and the scientific community. The AI approach is used in the battle for cure, prediction, and pandemic predictors. Improving AI is a good step toward growing such uncertainties, one of the essential data analytics tools built over the past decade or so. Data scientists have approached the task of motivation. The index is growing exponentially as work information surface, beyond the potential of humans to do it alone. AI describes large data models, and this chapter should clarify how this challenge has become one of the ace cards of humanity. Advances in AI software, such as natural language processing, expression understanding, data mining, etc., are used for diagnosis as well as traceability and production of vaccines. AI has supported and contributed to the control of the COVID-19 pandemic. We include an initial overview of the real and potential contribution of AI to the fight against COVID-19 and the existing constraints on these contributions. In this chapter, different technologic solutions using AI for COVID-19 have been discussed. © 2022 Elsevier Inc.

8.
2nd International Conference on Communication and Artificial Intelligence, ICCAI 2021 ; 435:399-407, 2022.
Article in English | Scopus | ID: covidwho-1872370

ABSTRACT

During the most recent two years of Covid-19, the vast majority of the work will be performed web based utilizing normal correspondence channel by associations including significant reports trade. Trading significant reports are unsafe to send straightforwardly, even we are seeing different extortion cases, data burglary cases, identity robbery, marital cheats, Internet shopping fakes, and so on. In these cases assailant takes your own data or reports and abuses them for some off-base purposes. To ensure your data or report during trading them online steganography is a valuable methodology. In this paper, we will propose a significant and inventive plan utilizing LSB method with shading pictures. To work on the security of the message, we will apply AES encryption plan and afterward utilize the picture steganography with LSB method. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

9.
Journal of Experimental Biology and Agricultural Sciences ; 10(2):396-404, 2022.
Article in English | Scopus | ID: covidwho-1863450

ABSTRACT

Severe acute respiratory syndrome coronavirus-2 (S ARS-CoV-2) emerging variants particularly those of concern contain numerous mutations that influence the behavior and transmissibility of the virus and could adversely affect the efficacies of existing coronavirus disease 2019 (COVID-19) vaccines and immunotherapies. The emerging SARS-CoV-2 variants have resulted in different waves of the pandemic within the ongoing COVID-19 pandemic. On 26 November 2021 World Health Organization designated omicron (B.1.1.529) as the fifth variant of concern which was first reported from South Africa on November 24, 2021, and thereafter rapidly spread across the globe owing to its very high transmission rates along with impeding efficacies of existing vaccines and immunotherapies. Omicron contains more than 50 mutations with many mutations (26-32) in spike protein that might be associated with high transmissibility. Natural compounds particularly phytochemicals have been used since ancient times for the treatment of different diseases, and owing to their potent anti-viral properties have also been explored recently against COVID-19. In the present study, molecular docking of nine phytochemicals (Oleocanthal, Tangeritin, Coumarin, Malvidin, Glycitein, Piceatannol, Pinosylnin, Daidzein, and Naringenin) with omicron spike protein (7QNW (electron microscopy, resolution 2.40 Å) was done. The docking study revealed that selected ligands interact with the receptor with binding energy in the range of-6.2 to-7.0 kcal/mol. Pinosylnin showed the highest binding energy of-7.0 kcal/mol which may be used as potential ligands against omicron spike protein. Based on the docking studies, it was suggested that these phytochemicals are potential molecules to be tested against omicron SARS-CoV-2 and can be used to develop effective antiviral drugs. © 2022, Editorial board of Journal of Experimental Biology and Agricultural Sciences. All rights reserved.

10.
International Journal of Interactive Mobile Technologies ; 16(8):138-164, 2022.
Article in English | Scopus | ID: covidwho-1863009

ABSTRACT

The drastic change in the technological environment has transformed the entire world including the education sector which was and is largely dominated by classroom teaching. In the last decade, a new entrant in the education sector has been e-learning. The COVID-19 pandemic has forced educational institutes to look at e-learning as a path to continue the learning process. The present paper aims to propose a model highlighting the enablers that encourage the smooth and effective delivery of e-learning process and highlight the barriers that cause hurdles in the effective delivery of e-learning. The researchers have followed the Total Interpretive Structural Modelling and Fuzzy Matriced’ Impacts Croise’s Multiplication Appliquée a UN Classement (MICMAC) analysis approach of extant literature review, expert opinion and multiple iterations to arrive at the proposed model. The findings of the present research study show the linkages between the identified enablers: institutional culture, institutional capability and support, flexibility in the teaching-learning process, e-readiness, motivation, knowledge management practices, and technology. Knowledge management practices that include practices of capturing knowledge and sharing knowledge have emerged as the most significant enabler of e-learning. The model on barriers to e-learning shows the relationship between lack of required skills, lack of access to technology, quality concerns, time as a barrier, learner engagement as barriers to effective e-learning. Modelling of enablers and barriers and effective e-learning is a less explored area, particularly in the Indian context with special emphasis on the pandemic. The study was carried out to address this research gap © 2022. International Journal of Interactive Mobile Technologies.All Rights Reserved.

11.
PubMed; 2022.
Preprint in English | PubMed | ID: ppcovidwho-337376

ABSTRACT

The current SARS-CoV-2 pandemic has highlighted a need for easy and safe blood sampling in combination with accurate serological methodology. Venipuncture is usually performed by trained staff at health care centers. Long travel distances may introduce a bias of testing towards relatively large communities with close access to health care centers. Rural regions may thus be overlooked. Here, we demonstrate a sensitive method to measure antibodies to the S-protein of SARS-CoV-2. We adapted and optimized this assay for clinical use together with capillary blood sampling to meet the geographical challenges of serosurveillance. Finally, we tested remote at-home capillary blood sampling together with centralized assessment of S-specific IgG in a rural region of northern Scandinavia that encompasses 55,185 sq kilometers. We conclude that serological assessment from capillary blood sampling gives comparable results as analysis of venous blood. Importantly, at-home sampling enabled citizens living in remote rural areas access to centralized and sensitive laboratory antibody tests.

12.
Springer Protocol. Handb. ; : 363-377, 2022.
Article in English | EMBASE | ID: covidwho-1858946

ABSTRACT

Infectious disease outbreaks keep challenging human and veterinary health worldwide since decades. Disease outbreaks such as smallpox, influenza, polio, SARS, Ebola, foot-and-mouth disease, African swine fever, and the most recent and devastating COVID-19, all point to the need for a more proactive approach to developing diagnostics and treatment methods for these deadly diseases. Because the pathogenic agents that cause these diseases are highly transmissible, careful containment of these agents within the laboratories is necessary, with little or no exposure to working personnel. Different regulatory authorities across the world provide guidelines and procedures to ensure that research and diagnostic laboratories operate safely. This chapter delves into the many events that occur as a result of lab-mediated disease spread, as well as the need for, importance of, and guidelines for good lab practices and biosafety.

13.
PLoS Global Public Health ; 2(4), 2022.
Article in English | CAB Abstracts | ID: covidwho-1854959

ABSTRACT

Background & objectives: Presence of cardiovascular (CV) risk factors enhance adverse outcomes in COVID-19. To determine association of risk factors with clinical outcomes in India we performed a study.

14.
Journal of the American College of Cardiology ; 79(9):3384-3384, 2022.
Article in English | Web of Science | ID: covidwho-1849268
16.
2022 IEEE Delhi Section Conference, DELCON 2022 ; 2022.
Article in English | Scopus | ID: covidwho-1846079

ABSTRACT

Human's inhale oxygen which is then transported to the lungs, where it is then delivered into the bloodstream. As a result, breathing entails inhaling oxygen and exhaling carbon dioxide, which a healthy individual accomplishes roughly 25000 times every day. COVID-19, Pneumonia, and Lung Opacity all cause the lungs to stop working properly, which can lead to respiratory failure. Some diseases can be fatal;COVID-19 is one of the deadly diseases that the world is now dealing with. For the detection of lung disease, different prediction models are developed using deep learning algorithms, and their performances are computed and assessed using various performance metrics. The proposed methodology comprises of analyzing the performance of the CNN model after it has been trained on a dataset of 8,462 images. During the performance training, the proposed model obtained an accuracy rate of 90.83 percent. The study also discusses how the pre-trained models VGG-16 and ResNet-50 were implemented and evaluated for the dataset. The Flask app has also been used to create a user interface that accepts the user's X-ray images as input and forecasts lung illness as an output. © 2022 IEEE.

17.
2022 IEEE Delhi Section Conference, DELCON 2022 ; 2022.
Article in English | Scopus | ID: covidwho-1846069

ABSTRACT

This paper provides an effective method for optimal sizing and allocation of DGs & D-STATCOM placement to minimize the actual power losses and improve voltage profile in RDS (Radial Distribution System) with incorporating effect of load growth & load modelling. The technique's legitimacy is tried on the standard IEEE 33-bus RDS by performing load flow analysis after compensating the candidate bus. The outcomes acquired are contrasted with and without the Solar Photovoltaic Panel based DG (PVDG), Wind Turbine based DG (WTDG) and D-STATCOM for minimum actual power loss. Further the changes in the operational circumstances of PVDG and WTDG as well as D-STATCOM, are also investigated in order to fulfil the shifting load profile while preserving the voltage constraint and minimizing real power loss owing to the COVID-19 pandemic. The variation in operational setting and the power supplied to the grid for compensating the coal-based generation during the lockdown, pan-India lights off event and Unlock 1 are also studied in the paper. © 2022 IEEE.

18.
2021 International Conference on Computational Performance Evaluation, ComPE 2021 ; : 90-93, 2021.
Article in English | Scopus | ID: covidwho-1831744

ABSTRACT

In the current scenario of the COVID-19 pandemic estimating the count of number of people present in public places at a particular time has become a significant task. Crowd count is attracting a lot of researchers from the computer vision and deep learning field. It has been found that to achieve this objective computer vision techniques such as deep learning, machine learning, etc. outperform traditional ways of estimating crowd count that uses handcrafted features such as Histogram of gradients, Haar, Scale Invariant Feature Transform and gives better results with higher accuracy. The paper studies the effect of dilation on convolution layers in estimating the crowd count. We have also done a comparative analysis of the developed model with different dilation rates on the ShanghaiTech dataset (part A and part B). The model is trained with images containing occluded and restricted visibility of heads. The model outputs the result with substantial accuracy in estimating the headcount in images of the dense crowd in a sensibly less amount of time. © 2021 IEEE.

19.
Indian Journal of Endocrinology and Metabolism ; 26(Suppl 1):S13-S13, 2022.
Article in English | EuropePMC | ID: covidwho-1824525

ABSTRACT

Coronavirus disease 2019 (COVID-19) is a global pandemic where several comorbidities have been shown to have a significant effect on mortality. Patients with diabetes mellitus (DM) have a higher mortality rate than non-DM patients if they get COVID-19. Recent studies have indicated that patients with a history of diabetes can increase the risk of severe acute respiratory syndrome coronavirus 2 infection. Additionally, patients without any history of diabetes can acquire new-onset DM when infected with COVID-19. Thus, there is a need to explore the bidirectional link between these two conditions, confirming the vicious loop between “DM/COVID-19”. This narrative review presents (1) the bidirectional association between the DM and COVID-19, (2) the manifestations of the DM/COVID-19 loop leading to cardiovascular disease, (3) an understanding of primary and secondary factors that influence mortality due to the DM/COVID-19 loop, (4) the role of vitamin-D in DM patients during COVID-19, and finally, (5) the monitoring tools for tracking atherosclerosis burden in DM patients during COVID-19 and “COVID-triggered DM” patients. We conclude that the bidirectional nature of DM/COVID-19 causes acceleration towards cardiovascular events. Due to this alarming condition, early monitoring of atherosclerotic burden is required in “Diabetes patients during COVID-19” or “new-onset Diabetes triggered by COVID-19 in non-Diabetes patients”.

20.
Journal of Parenteral and Enteral Nutrition ; 46(SUPPL 1):S127-S128, 2022.
Article in English | EMBASE | ID: covidwho-1813569

ABSTRACT

Background: The consequences of the COVID-19 pandemic in long-term care facilities could be severe for frail and immunocompromised older adults.1 These older adult patients are hypermetabolic due to pressure ulcers, infection, fever, and elevated inflammatory labs such as CRP.1 They experience decreased appetite due to taste and smell changes. The inadequate intake, fat, and muscle loss due to prolonged hospitalization and increased nutrition demands create a negative nutrient balance, leading to unintentional weight loss (UWL).1 According to the Center for Medicare and Medicaid Services (CMS), UWL is defined as a weight loss of 5% in 30 days, 7.5% in 90 days, and 10% in 180 days.2 In this proposal, our focus was unintentional weight loss (UWL) in long-term skilled care patients and how collaborative nursing and dietitian intervention impacts the UWL in this specific population. Methods: The data were collected retrospectively for all patients admitted between May 2020 to March 2021. The patient's demographic data was collected from the chart review using the point click care program. The top five patient diagnoses were retrieved using MDS coding for the study period. Additionally, the most common chronic disease in the geriatric population was used. The red napkin program was initiated in Oct 2020. The red napkin program was initiated to alert the nursing staff for patients with UWL and who also have pressure ulcers. Results: The results indicated that the average census was 152 patients during the study period. The majority of the patients (84%) were long-term care, with more females than males (59 vs 40%). Most of the patients were African American and Caucasian ethnic group. Nearly 40-45% of patients had diabetes, hypertension;one-fourth of the patients had CHF, dialysis, and dementia. During this period, there was a total of 77 patients who had unintentional weight loss as defined by CMS criteria. There were 60 patients before the intervention, and the numbers declined significantly to 33 patients post-intervention. Out of these 33 post-intervention patients, only 17 patients were new, and 16 were from the previous months of the preintervention period. The number has also declined from 12 to 7 expected weight loss related to hospice and comfort care patients. Most patients received oral nutrition supplements to halt weight loss. Four patients received alternate routes of nutrition support (TPN/EN) in addition to an oral diet. Almost 40% of patients had COVID-19 infection, and 38% of patients had pressure ulcers, which may have affected unintentional weight loss. Conclusion: The results indicated that appropriate and timely collaborative dietitian and nursing efforts improve patient outcomes or quality of care to halt unintentional weight loss in long-term skilled care facilities.

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