Application of MSCs therapy in COVID-19

The year 2019 ended with the official report of an unknown pneumonia outbreak in Wuhan, Hubei Province, China. Subsequently, this novel pneumonia was named COVID-19, which mainly attacks the respiratory system, causing severe damage. Although vaccination has relieved the stress of combating pandemics around the world after one year, there are still unknowns and challenges that come with hope. In this regard, stem cell therapy has been proposed as an effective approach to treating COVID-19. Mesenchymal stem cells (MSCs) can potentially be used as a hopeful tool in the cell-based therapy due to their ability to regenerate and regulate immune response. Although research and clinical results have shown encouraging achievement in patients who were treated with MSCs, drawbacks and challenges still exist in the face of new opportunities. This review aims to introduce the challenges of the COVID-19 vaccine and the possible clinical use of MSC-based therapy. Through analysis of COVID-19 and MSC-based therapy, the author aims to find the possibilities and feasibility of using MSCs to treat acute respiratory diseases, such as COVID. As a result, the author finds that MSC treatment is very practical, and it shows significant potential to treat COVID-19. © 2023 SPIE.

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.

Tolerance limits for mixture-of-normal distributions with application to COVID-19 data

Tolerance intervals (TIs) are widely used in various applications including manufacturing engineers, clinical research, and pharmaceutical industries. TIs can be used to construct limits of control charts for monitoring quality characteristics. For manufacturing processes where multiple factors may contribute to defects or multiple-stream processes, a mixture distribution of several suitable probabilistic models may be a better choice than a simple distribution for modeling the data. TIs for the normal mixture distribution have been studied in the literature. This article reviews the TIs of the normal mixture distribution, the applications of the mixture distribution, and the control charts of the mixture distribution. A rule for constructing modified two-sided TIs of the normal mixture distribution is summarized, and this rule may be extended to construct modified two-sided TIs for general mixture distributions. The feasibility of using TIs to build control charts for mixture distributions is also discussed. A real data example of coronavirus disease 2019 is used to illustrate the method by linking the TI to control charts. This article is categorized under: Statistical Learning and Exploratory Methods of the Data Sciences > Clustering and Classification. © 2023 Wiley Periodicals LLC.

Diagnosing and quantifying post-COVID-19 fluctuations in the architecture billings indices

Purpose: The purpose of this paper is to understand the post-COVID-19 fluctuations in the building construction demand from various angles at the national, regional, and sectoral levels. Despite the significant impact of COVID-19 on the building construction industry, a detailed quantitative analysis of the COVID-19 impact on the building construction demand is still lacking. The current study aims to (1) establish a statistical approach to quantify the COVID-19 impact on the building construction demand;(2) investigate the post-COVID-19 fluctuations in the construction demand of different building services, regional markets, and building sectors using the historical time series of the architecture billings index (ABI);and (3) identify vulnerable market and sector and discuss the post-COVID-19 recovery strategies. Design/methodology/approach: The research methodology follows four steps: (1) collecting national, regional, and sectoral ABIs;(2) creating seasonal autoregressive integrated moving average models;(3) illustrating cumulative sum control charts to identify significant ABI deviations;and (4) quantifying the post-COVID-19 ABI fluctuations. Findings: The results show that all the ABIs experienced a statistically significant decrease after COVID-19. The project inquiries index reduced more but recovered faster than billings and design contracts indices. The midwest billings index decreased the most among the regional ABIs and the commercial/industrial billing index dropped the most among the sectoral ABIs. Originality/value: This study is unique in the way that it utilized the ABI data and the approach using SARIMA models and CUSUM control charts to assess the post-COVID-19 building construction demand represented by ABI fluctuations. © 2022, Emerald Publishing Limited.

Biopolymeric sustainable materials and their emerging applications

Advancements in polymer science and engineering have helped the scientific community to shift its attention towards the use of environmentally benign materials for reducing the environmental impact of conventional synthetic plastics. Biopolymers are environmentally benign, chemically versatile, sustainable, biocompatible, biodegradable, inherently functional, and ecofriendly materials that exhibit tremendous potential for a wide range of applications including food, electronics, agriculture, textile, biomedical, and cosmetics. This review also inspires the researchers toward more consumption of biopolymer-based composite materials as an alternative to synthetic composite materials. Herein, an overview of the latest knowledge of different natural- and synthetic-based biodegradable polymers and their fiber-reinforced composites is presented. The review discusses different degradation mechanisms of biopolymer-based composites as well as their sustainability aspects. This review also elucidates current challenges, future opportunities, and emerging applications of biopolymeric sustainable composites in numerous engineering fields. Finally, this review proposes biopolymeric sustainable materials as a propitious solution to the contemporary environmental crisis. © 2022 Elsevier Ltd.