A Multivent System for Non-invasive Ventilation: Solving the Problem of Ventilator Shortage during the COVID-19 Pandemic

The COVID-19 pandemic has caused a severe global problem of ventilator shortage. Placing multiple patients on a single ventilator (ventilator sharing) or dual patient ventilation has been proposed and conducted to increase the cure efficiency for ventilated patients. However, the ventilator-sharing method needs to use the same ventilator settings for all the patients, which cannot meet the ventilation needs of different patients. Therefore, a novel multivent system for non-invasive ventilation has been proposed in this study. The close loop system consists of the proportional valve and the flow-pressure sensor can regulate the airway pressure and flow for each patient. Multiple ventilation circuits can be combined in parallel to meet patients’ventilation demands simultaneously. Meanwhile, the mathematical model of the multivent system is established and validated through experiments. The experiments for different inspired positive airway pressure (IPAP), expired positive airway pressure (EPAP), inspiratory expiratory ratio (I:E), and breath per minute (BPM) have been conducted and analyzed to test the performance of the multivent system. The results show that the multivent system can realize the biphasic positive airway pressure (BIPAP) ventilation mode in non-invasive ventilation without interfering among the three ventilation circuits, no matter the change of IPAP, EPAP, I:E, and BPM. However, pressure fluctuation exists during the ventilation process because of the exhaust valve effect, especially in EPAP control. The control accuracy and stability need to be improved. Nevertheless, the novel designed multivent system can theoretically solve the problem of ventilator shortage during the COVID-19 pandemic and may bring innovation to the current mechanical ventilation system. Author

Nanofibrous Polymeric Membranes for Air Filtration Application: A Review of Progress after the COVID-19 Pandemic

Air pollution is one of the major global problems causing around 7 million dead per year. In fact, a connection between infectious disease transmission, including COVID-19, and air pollution has been proved: COVID-19 consequences on human health are found to be more severe in areas characterized by high levels of particulate matter (PM). Therefore, after the COVID-19 pandemic, the production of air filtration devices with high filtration efficiency has gained more and more attention. Herein, a review of the post-COVID-19 pandemic progress in nanofibrous polymeric membranes for air filtration is provided. First, a brief discussion on the different types of filtration mechanism and the key parameters of air filtration is proposed. The materials recently used for the production of nanofibrous filter membranes are presented, distinguishing between non-biodegradable polymeric materials and biodegradable ones. Subsequently, production technique proposed for the fabrication of nanofibrous membranes, i.e., electrospinning and solution blow spinning, are presented aiming to analyze and compare filtration efficiency, pressure drop, reusability and durability of the different polymeric system processed with different techniques. Finally, present challenges and future perspectives of nanofibrous polymeric membranes for air filtration are discussed with a particular emphasis on strategies to produce greener and more performant devices. © 2023 The Authors. Macromolecular Materials and Engineering published by Wiley-VCH GmbH.

Cardiac Studies Diagnostic Data Informative Features Investigation based on Cumulative Frequency Analysis

The development of information technology in the modern world affects the public health sector on the one hand and accumulates enormous amounts of data on the other hand. The global COVID-19 pandemic has contributed to the digitalization of healthcare. Heart disease is a global problem that causes death worldwide. Therefore, this study proposes a model for determining the information content of signs of diagnostic data of heart diseases based on the cumulative frequency method. The software implementation of the model has been completed. A database of 303 patients, consisting of 14 attributes, was used for the experiments. As a result of the model's work, the features with the most significant information content were identified. The study is promising and can apply diagnostic models in public health practice. ©2022 Copyright for this paper by its authors.

The digital material formatting app prototype 3.0

There is the application prototype 3.0 developed for automatized digital material formatting. It is developed to solve the global problem as digital screen users complain and symptoms due to the huge digital near workload. That significantly increased during the Covid-19 pandemic when all everyday tasks moved to a digital environment, including work tasks and education for all age groups. It can bring severe vision impairments and even blindness in the long term as humans' visual system is not adapted well enough to the digital environment and long-term work via screens by using inappropriate text typographic parameters for digital reading purposes. The latest existing Microsoft technologies for development have been used to reach broader digital document types. As well as, there is the use of the Realm database in the app prototype more straightforward for future modification. © 2022 IEEE.

An Empirical Model of Classifying Lung Affected Diseases to Detect COVID-19 Using Chest X-ray Employing Convolutional Neural Architecture

The earlier detection and accurate diagnosis of COVID seem to be a global problem. It is difficult to make a large number of testing equipment, but then again, their reliability is relatively poor. Recent research indicates the usefulness of chest x-ray pictures in identifying COVID. This study presents a deep learning algorithm developed from the ground up to categorize as well as confirm the existence of COVID in a set of X-ray imaging data. We designed a CNN architecture from the ground up to retrieve elements from provided X-ray data to categorize them and identify the individual contaminated with COVID. Our strategy may aid in mitigating the consistency issues while working with medical data. In contrast to some other classifying activities with a large enough image database, obtaining large X-ray datasets for this classification job is challenging. So, we applied multiple data enhancement techniques to maximize the accurateness, achieving a significant accuracy of 97.75 percent. © 2022 IEEE.

Cultural foundations of a national system of education in a COVID-19 pandemic

The article aims to characterize the key components of cultural constants of the upbringing system from the national perspective. The objectives are to analyze the differences between traditional and prospective elements of the national upbringing system. Using general scientific (analysis, comparison), philosophical and scientific (synergetic, dialectics) and culturological (structural and functional, axiological and semiotic) methods allow characterizing culturological foundations of the national upbringing system. Currently, there is an urgent need to develop new priorities of the national policy of upbringing of children, youth, and in some cases the older generation in the context of new challenges facing society.

The coronavirus global pandemic and its impacts on society

The aim of the study is to assess the impact of various nationalities, cultures, and religions on the spread of the coronavirus in the human environment. Particular attention was paid to compliance with legal and ethical standards during a pandemic. Different cultures, nationalities, and religions have a significant influence on the development and spread of the coronavirus in the world. During the COVID-19 pandemic, due to the tightening of legal standards, it is necessary to ensure: protection of patient confidentiality;of freedom of the expression;accesses to critical information;the opportunities to belong to social organizations and civil society;the accesses to professionals healthcare;ensure equal rights for women and guarantee the right to water and sanitation;continuity of humanitarian aid and targeted economic aid. Travel locks and bans should comply with legal standards;the right to education should be strictly respected. Artificial intelligence can be used in the fight against the crown. © 2022 Elsevier Inc. All rights reserved.

Masked Face Detection Using Transfer Learning

COVID-19 pandemic has created chaos all over the world thereby reducing productivity and affecting day to day life of people. Wearing a face mask has become the need of the hour. In the future, it is expected that masks will become an integral part of human lifestyle and people have to wear masks to avail certain services. Therefore, the detection of face mask has become a global problem to avoid the spread of this virus. This paper presents a deep learning approach to detect faces with masks from an image or from a video stream, which can be used in surveillance tasks. The method attains accuracy up to 99% on Simulated Face Mask Dataset. We have manually tested this model on webcam, and it detects the presence of masks correctly without overfitting. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

Visualization and Analysis of COVID-19 Impact on PM2.5 Concentration in Guwahati city

By the end of year 2019, the whole world got effected by a very dangerous disease, COVID-19. It first originated in the city of Wuhan, China. Eventually this disease which is highly infectious became a pandemic worldwide [1]. Most of the countries of the world initiated the process of lockdown to lessen the impact of infection. Air pollution is a major global problem. Specially in Guwahati growing air pollution has emerged as a major concern. Guwahati is one of the place which has a very high Black Carbon level of pollution in the world. Out of all the pollutants PM2.5 is the most dangerous one. PM2.5 is less than 2.5 micrometer in diameter and is responsible for causing many serious health issues related to human respiratory system, cardiovascular and cardiopulmonary diseases. So it is utmost necessary to study the PM2.5 level in Guwahati city. As a result of the implementation of the lockdown, there was reduction of atmospheric pollution in many metropolitan cities and in Guwahati also [2]. In this paper, we have done a analysis on the trend of PM2.5 concentration prior-lockdown, during lockdown and after-lockdown for Guwahati city. We have proposed an efficient visualization algorithm to represent PM2.5 pollutant trend prior-lockdown, during lockdown and after-lockdown and analyze the results in a quick, direct and clear manner. © 2021 IEEE.

GLOBAL PANDEMIC IN TERMS OF OBJECTIVE CAUSES AND SUBJECTIVE SPECULATIONS

The coronavirus pandemic has generated a lot of talk about the post-coronavirus future of the global community and has drawn close attention to the processes of globalization. The article notes that something similar in the public consciousness took place after the publication of the first report to the Club of Rome, when there quickly came the awareness of the danger posed by global problems. Now, one of the global problems – the coronavirus pandemic – has changed the usual rhythm of life of the entire world community in a matter of weeks. The relevance of the topic is urgent since even those who used to show no interest both in the problems of medicine and global problems, now have actively joined the discussion. As a result, on the pages of many printed and electronic publications, along with serious and verified information, all sorts of guesses and speculations about the nature and correlation of coronavirus and globalization are multiplied. According to the authors, only knowledge can be opposed to this. © 2021, Uchitel Publishing House. All rights reserved.

Importance of International R&D Collaboration Between Companies: The CollaborativeHealth Use Case

International R&D activities are strategical to provide solutions that can solve global problems by creating interdisciplinary and multicultural teams. One of the current challenges that international collaboration could solve is related to outbreaks of infectious diseases, which have a devastating impact on society. Influenza in Spain was responsible of 4000 deaths during 2019, despite having a vaccine. Tropical infectious diseases, such as Dengue or Zika, are transmitted through mosquitoes and proliferate in hot and humid conditions. Brazil reported more than 3 million cases and more than a thousand deaths during the dengue fever epidemic that started in 2019. New coronavirus have once again shown the consequences that infectious diseases have both for the society and for the economy, claiming thousands of lives and forcing many countries to take restrictive lockdowns. Preventive measures can mitigate the devastating consequences of outbreaks of infectious diseases. In this sense, infodemiological systems compile data regarding public-health concerns to forecast new outbreaks. In this manuscript we describe the CollaborativeHealth tool and we report three case-studies carried out with this tool: Influenza in Spain, Zika and Dengue in Ecuador, and COVID-2019 in Spanish-speaking countries. © 2021, Springer Nature Switzerland AG.