New Control Chart Based On Neutrosophic Maxwell Distribution with Decision Making Applications

The neutrosophic approach is a potential area to provide a novel framework for dealing with uncertain data. This study aims to introduce the neutrosophic Maxwell distribution (M̃D) for dealing with imprecise data. The proposed notions are presented in such a manner that the proposed model may be used in a variety of circumstances involving indeterminate, ambiguous, and fuzzy data. The suggested distribution is particularly useful in statistical process control (SPC) for processing uncertain values in data collection. The existing formation of VSQ-chart is incapable of addressing uncertainty on the quality variables being investigated. The notion of neutrosophic VSQchart (Ṽ SQ) is developed based on suggested neutrosophic distribution. The parameters of the suggested Ṽ SQ-chart and other performance indicators, such as neutrosophic power curve (P̃C), neutrosophic characteristic curve (C̃C) and neutrosophic run length (R̃L) are established. The performance of the Ṽ SQ-chart under uncertain environment is also compared to the performance of the conventional model. The comparative findings depict that the proposed Ṽ SQ-chart outperforms in consideration of neutrosophic indicators. Finally, the implementation procedure for real data on the COVID-19 incubation period is explored to support the theoretical part of the proposed model © 2023,Neutrosophic Sets and Systems. All Rights Reserved.

Students' employability confidence in COVID-19 pandemic: role of career anxiety and perceived distress

Purpose: The present research aims to investigate the impact of "COVID-19 phobia” factors (psychological, social, economic and psychosomatic) on career anxiety and perceived distress. Further, this research assesses whether career anxiety and perceived distress foster or diminish students' employability confidence. Design/methodology/approach: "Partial Least Squares Structural Equation Modeling (PLS-SEM)” has been used to analyze the data. Findings: The results depict that factors (psychological, economic and psychosomatic) are positively and significantly associated with career anxiety and perceived distress. However, social factors indicate an adverse impact on perceived distress. Further, career anxiety and perceived distress positively influence employability confidence, but the associations are not highly impactful. Originality/value: This research elucidates an unexplored phenomenon in the context of a developing country that coronavirus disease 2019 (COVID-19) phobia scale (i.e. psychological, social, economic and psychosomatic) result in career anxiety and distress. Moreover, no studies highlighted the direct impact of career anxiety and perceived distress on employability confidence. © 2023, Emerald Publishing Limited.

Polyenes and SARS-CoV-2

The new coronavirus (SARS-COV-2) shows structural similarity with SARS COV, which emerged in China in the early 2019. SARS-COV-2 has been declared a pandemic by the WHO (World Health Organization) as it imposed a threat to the world in various aspects. There is no specific drug therapy or vaccine to treat or prevent this disease because of the limited knowledge regarding the pathogenesis and proliferation pathways involved in disease progression. The virus penetrates the human body through ACE2 receptor by interacting with Spike(S) protein and it is assumed that viral entry can be inhibited by targeting the protein-protein interaction. Different drugs have been repurposed for their potential effectiveness against SARS-CoV-2, such as ivermectin, digitoxin, and polyenes. Polyene antibiotics are characterized by the presence of a macrocyclic ring. Furthermore, this group has been known for pharmacological activities, for example, antifungal, antihuman immunodeficiency virus, immunomodulating, and antiprion. Polyene antibiotics inhibit the binding of the virus to the ACE2 receptor. Further investigation should be done to assess the relationship between polyenes and SARS-CoV-2 in considering the development of a novel therapeutic option for the treatment of COVID-19. © 2023 Elsevier Inc. All rights reserved.

Rate Insight: A Comparative Study on Different Machine Learning and Deep Learning Approaches for Product Review Rating Prediction in Bengali Language

In this contemporary era of digital marketing, ecommerce has emerged as one of the most preferred methods for day-to-day shopping. Ever since the COVID-19 pandemic, online shopping behavior has forever changed to less or no human-to-human interaction. As a result, it is getting more difficult for e-commerce enterprises to observe and evaluate market trends, particularly when done through consumer behavior analysis. To identify behavioral patterns and customer review-rating discrepancies, extensive analysis of product reviews is a substantial research field. Lack of benchmark corpora and language processing techniques, predicting review ratings in Bengali has become increasingly problematic. This paper thoroughly analyzes the approach to product review rating prediction for Bengali text reviews exploiting our own constructed dataset that was collected from an e-commerce website called DarazBD1. We acquired product reviews with labels known as ratings of five sentiment classes, from "1"to "5". It is noteworthy that we established a well-balanced dataset using our automated scraping system and a significant amount of time and effort is spent to maintain quality standards through the human annotation process. Exploration of multiple approaches to machine learning models such as logistic regression, random forest, multinomial naïve Bayes, and support vector machine, the best classification accuracy score of 78.63% is achieved by SVM. Subsequently, using Word2Vec, FastText, and GloVe embeddings with three deep neural network(DNN) architectures: CNN, Bi-LSTM, and a combination of CNN and Bi-LSTM, CNN+Bi-LSTM gave the highest accuracy score of 75.25% among the DNN architectures. © 2022 IEEE.

Nutritional Intervention for the Treatment and Prevention Against Novel Coronavirus-19

Introduction: The ongoing pandemic of Severe Acute Respiratory Syndrome coronavirus-2 (SARS COV-2) has jeopardized people's health and the global economy. The infection caused by these viruses inflicts immunosuppression and an unprecedented range of symptoms leading to mortality. At this stage, there are no countermeasures or medicines to overcome rapid disease proliferation and aberrant immunological response. Objective(s): The study aims to determine different immunomodulatory therapeutics that could be potential agents to alleviate viral and other lethal infections and possibly rejuvenate immunological and tissue repair response against this disease. Method(s): A review of the literature was performed by screening different scientific databases to procure various immunomodulatory therapies for the treatment of SAR COV-2. Result(s): A comprehensive literature review indicated that different foods rich in vitamins (A-D), selenium and iron can enhance immunological response against various deleterious infections, whereas different nutritious drinks that include hydrogen-enriched water and green tea alleviate inflammation and elicit wound healing properties. Black cumin seeds and Garlic have a myriad of biological activities due to abundant bioactive phytochemicals that play an important role in the elimination of various bacterial and viral infections. Conclusion(s): These foods/supplements are relatively safe to consume and possess high toxicity profile and could be a potential nutritional intervention in order to create adequate immunity within a population to fight against this prevailing infection.Copyright © 2021 Bentham Science Publishers.

Paxlovid ( Nirmatrelvir/Ritonavir ) and Cyclosporin in a Kidney Transplant Patient with Covid-19 Infection

Introduction: COVID-19 infection causes high morbidity,mortality and burden to the healthcare system.Solid organ transplant patients with COVID-19 have been reported to have between 13-30% rate of mortality.Over the past 2 years,treatment of COVID-19 has evolved with new drugs being introduce such as Molnupiravir which reported to reduce death and hospitalization up to 50%.Recently a new novel drug Paxlovid (Nirmatrelvir/Ritonavir) develop by Pfizer has shed much hope in terms of managing COVID-19 patient especially in those with solid organ transplant.However,there is not much data in using Paxlovid for kidney transplant with COVID-19.Paxlovid is known to have drug-drug interaction with medication that is highly dependent on CYP3A4 which is a member of Cytochrome P450 enzyme for clearance.It is advice to withhold certain calcineurin inhibitor drugs if on Paxlovid.However,there was no mention on withholding cyclosporin which is one of the drugs in in kidney transplant patient.We've reported the first case in literature of a kidney transplant patient on cyclosporin diagnose with COVID 19 on Paxlovid. Method(s): Our patient is a End Stage Renal Disease on regular hemodialysis for a year.He subsequently had a living related renal transplant.He was vaccinated and boosted with SARS-CoV-2 Vaccine from Pfizer BioNTech.Baseline creatinine level was 126 umol/L.Immunosuppressants are Cyclosporin 50mg BD,Prednisolone 7.5mg OD and Azathioprine 50mg OD.Baseline cyclosporin trough level was 113ng/ml.He was well until SARS-CoV-2 Rapid Test Kit was positive on day four of illness.Serum Creatinine level was 137 umol/L.His estimated Glomerular Filtration Rate was 53 ml/min/1.73m2.Chest Radiograph shows ground glass opacity on both lower zone.Patient was treated for COVID-19 Pneumonia Category 3A.In view eGFR was 53 ml/min/1.73m2,Paxlovid was started at adjusted dose (Nirmatrelvir 150mg/Ritonavir 100mg BD).Patient had four doses of Paxlovid before we were able to send cyclosporin level on day three of his admission due to logistic problem.Cyclosporin trough level was 737 ng/ml and we withheld his cyclosporin.Paxlovid was continued and there was improvement in terms of his symptoms.Serial chest radiographs showed improvement as in Figure 1.We were able to monitor his cyclosporin trough level and serum creatinine on daily basis as shown in Figure 2 and Figure 3 respectively.He completed five days of Paxlovid.On day seven of admission,cyclosporin was restarted back at 25mg BD. [Formula presented] [Formula presented] [Formula presented] Results: He was discharged well with cyclosporin dose being adjusted back to his old dose.We followed him up as outpatient and monitor his cyclosporin level which was stable and continued on his old immunosuppressant regime. Conclusion(s): This case highlights the potential treatment with Paxlovid in patients with kidney transplant on cyclosporin diagnosed to have COVID-19 infection.Drug-drug interaction between cyclosporin and Paxlovid needs to be taken into account.Moving forward in the endemic era,there will be increase usage of Paxlovid that can help to reduce severity,hospital admission and mortality in solid organ transplant with COVID-19 infection.Close monitoring of cyclosporin level,proper mitigation strategy,adjustment of immunosuppressants and safe prescription of Paxlovid will be beneficial for kidney transplant patient infected with COVID-19.This can help in reducing morbidity and mortality in our kidney transplant patients. No conflict of interestCopyright © 2023

SEVERITY OF INFLAMMATION IN COVID-19 PATIENTS WITH DIABETIC CO-MORBIDITIES-A HOSPITAL BASED STUDY

Background: Diabetic co-morbidities in recent past pandemic were becoming a challenge to the clinicians. COVID-19 is a respiratory infectious disease caused by SARS-COV-2 virus. World health organization declared COVID-19 pandemic in Feb 2020. The objective of this study was to determine the severity of inflammation in COVID-19 patients with diabetic co-morbidities in a hospital based study. Material and methods: This descriptive study covering 176 patients was conducted in Hayatabad Medical Complex Peshawar from 25 April 2021 to 21st October 2021. Receiver operating characteristics (ROC) curve was used as statistical tool to determine the relationship of clinical sensitivity of different inflammatory markers in diabetic COVID-19 patients to predict the outcome. Post-stratification Chi square test was used at 5% level of significance. Results: Out of 176 patients, 149 (84.7%) patients were discharged satisfactorily while 27 patients expired during hospitalization. Mean with SD for age was 53.28±13.73 years, for D dimer was 13.14±2.61 ug/ml and for CRP was 16.73+11.78 mg/l. Median of serum Ferritin was 1120 ng/ml. There was a significantly higher inflammatory markers values of D-dimer (p=0.001 and ferritin (p=0.001) in diabetic versus non diabetic COVID Patients. D-Dimer was main decisive prognostic indicator in diabetics with COVID-19 to predict mortality/worst outcome with an Area under Curve (AUC) of (0.929 95%CI 0.88-0.96) followed by Serum ferritin (0.868 95%CI 0.78-0.95). There was a significant association of Diabetes with Mortality (p<0.001) in COVID-19 patients. Conclusion: The clinical sensitivity of d-dimer and ferritin toward mortality in COVID-19 patients with diabetic co-morbidities is significantly high in our population. Diabetes alone has a significant positive association with worst outcome in covid-19. © 2022. Hamzullah Khan, et al.

SARS-CoV-2 RNAEMIA AS A BIOMARKER of LOWER RESPIRATORY VIRAL LOAD in COVID-19

Background: SARS-CoV-2 plasma RNAemia correlates strongly with COVID-19 severity and predicts clinical outcome, but how RNAemia levels relate to viral load in the lower respiratory tract has not been well-defined. Delineating the relationship of viral load in the lung and blood compartments in COVID-19 may help guide therapeutic interventions and could provide insight into the viral dynamics of these two compartments. Here we compared SARS-CoV-2 RNA levels in plasma to those in lower respiratory secretions. Methods: We used an internally-controlled, ultrasensitive (1 copy/extraction) qRT-PCR assay for SARS-CoV-2 N gene RNA to test plasma and endotracheal aspirate (ETA) samples collected on the same day from mechanically-ventilated patients with COVID-19 prospectively enrolled from three hospitals in Pittsburgh. Samples were collected at enrollment on day 1 (D1), D5, and D10. Results: SARS-CoV-2 RNA was detected in 22/33 (67%) plasma (median 32 cps/mL, IQR [<3-2608 cps/mL]) and 28/33 (85%) ETA samples (median 66,300 cps/mL, IQR [2395-1,028,500 cps/mL]) collected on D1. Of the 28 ETA samples with detectable SARS-CoV-2 RNA, 22 (79%) had detectable RNAemia. Viral RNA levels were more than 2,000-fold higher in ETA than plasma, but plasma and ETA viral RNA levels were strongly correlated (Spearman r=0.83, p<0.0001, Fig 1A). Viral RNA levels generally decreased concordantly over time in both plasma and ETA samples (Fig 1B and C). Conclusion: SARS-CoV-2 viral RNA levels in plasma and lower respiratory tract secretions are strongly correlated in patients with severe COVID-19. This finding provides support for plasma viral RNA as a biomarker of lung infection, which could prove to be useful in guiding therapeutic interventions and monitoring response to therapies.

Trade credit promotes industrial growth during the COVID-19 pandemic: Evidence from the textile sector of Pakistan

Relevance. The rapid spread of COVID-19 around the world is disastrous to low-income countries. The pandemic was a serious threat to developing countries. In the case of Pakistan’s textile industry, small and medium-sized enterprises (SMEs) have been hit hard. Importantly, the textile sector is the largest industrial sector in Pakistan. Purpose of the study. The purpose of the article is to identify the challenges that SMEs are facing due to the pandemic and to consider trade credit as a possible tool to resolve them. Data and Methods. The data were collected through the questionnaire survey among the representatives of SMEs in the textile industry in Pakistan. In total, representatives of 150 textile industries were surveyed, but due to incomplete data only 115 were used for the analysis. The survey was conducted from March 2020 to March 2021. Then, the structural equation model (SEM) was applied to ensure the accuracy of the results. Results. The COVID-19 pandemic has impacted the textile industry in Pakistan and the buying process as well as the satisfaction level. The study highlights the industrial safety issues during the pandemic which exacerbated the economic difficulties. The study also explains the mechanism how perceived control over buying, perceived satisfaction, and perceived trust in science relate to trade credit and COVID-19 pandemic. Conclusions. The Pakistani government has taken many proactive measures, but there is still no consistent policy to attract more agents to the small textile business. Thus, a trade loan is the best solution for SMEs as it does not require immediate cash payments. The lack of government support has exacerbated the general pandemic-related economic crisis. In this light, trade loans may be considered as one of the most effective tools to keep SMEs afloat. © 2022, Ural University Press. All rights reserved.

Bioinformatic Analysis of Antiviral Medicinal Compounds Against Sars Cov-2 Proteases

The world is under siege from a global pandemic caused by a novel class of coronaviruses called severe acute respiratory syndrome coronavirus-2 (SARS CoV-2). These viruses cause severe respiratory illness leading to death. Molecular studies reveal that SARS CoV-2 proteases are involved in the processing of viral polyproteins. This study was conducted to obtain antiviral agents for SARS CoV-2 proteases. An extensive library of antiviral medicinal compounds was scrutinized to determine the probable interaction with both main and 3-chymotrypsin like proteases. Six antiviral compounds (Abietic Acid, Gallic Acid, Piceatannol, Piperine, Sinomenine, and Triptolide) were capable of establishing hydrogen bonds with the active pocket residues of the viral proteases, with appreciable binding energy. These compounds were subjected to root mean square analysis and tested not only for acute toxicity, but also for absorption, distribution, metabolism, excretion, and toxicity properties. Results were favourable for use in the treatment of SARS COV-2 infection.

Hadoop with Wavelet Support for Medical Big Data

Medical data is becoming more dense and complicated day by data. After COVID-19, the medical information is entirely expended from terabytes and petabytes. An accurate diagnosis needs a sophisticated mechanism and the support of information technology. Hadoop ecosystem is facilitating big data management for various health care applications. As dense patient history leads to better diagnosis;Hadoop architecture supports patient data accommodation, retrieval, update, and many similar functions like information assortment, information intricacy, information stockpiling, information investigation, information security, and protection. © 2021 IEEE.

Artificial Intelligence as a Service for Immoral Content Detection and Eradication

Social media is referred to as active global media because of its seamless binding thanks to COVID-19. Connecting software such as Facebook, Twitter, WhatsApp, WeChat, and others come with a variety of capabilities. They are well-known for their low-cost, quick, and effective communication. Because of the seclusion and travel constraints caused by COVID-19, concerns, such as low physical involvement in many possible activities, have arisen. Depending on their information, knowledge, nature, experience, and way of behavior, various types of human beings have diverse responses to any scenario. As the number of net subscribers grows, inappropriate material has become a major concern. The world's most prestigious and trustworthy organizations are keenly interested in conducting practical research in this field. The research contributes to using Artificial Intelligence (AI) as a service (AIaaS) for preventing the spread of immoral content. As software as a service (SaaS) and infrastructure as a service (IaaS), AIaaS for immoral content detection and eradication can use effective cloud computing models to leverage this service. It is highly adaptable and dynamic. AIaaS-based immoral content detection is mostly effective for optimizing the outcomes based on big data training data samples. Immoral content is identified for semantic and sentiment evaluation, and content is divided into immoral, cyberbullying, and dislike components. The suggested paper's main issue is the polarity of immoral content that can be processed using an AI-based optimization approach to control content proliferation. To finish the class and statistical analysis, support vector machine (SVM), selection tree, and Naive Bayes classifiers are employed. © 2022 Fadia Shah et al.