Mixup-Inf-Net: A data augmentation algorithm for segmentation of new coronary pneumonia infections

In 2020, the global spread of Coronavirus Disease 2019 exposed entire world to a severe health crisis. This has limited fast and accurate screening of suspected cases due to equipment shortages and and harsh testing environments. The current diagnosis of suspected cases has benefited greatly from the use of radiographic brain imaging, also including X-ray and scintigraphy, as a crucial addition to screening tests for new coronary pneumonia disease. However, it is impractical to gather enormous volumes of data quickly, which makes it difficult for depth models to be trained. To solve these problems, we obtained a new dataset by data augmentation Mixup method for the used chest CT slices. It uses lung infection segmentation (Inf-Net [1]) in a deep network and adds a learning framework with semi-supervised to form a Mixup-Inf-Net semi-supervised learning framework model to identify COVID-19 infection area from chest CT slices. The system depends primarily on unlabeled data and merely a minimal amount of annotated data is required;therefore, the unlabeled data generated by Mixup provides good assistance. Our framework can be used to improve improve learning and performance. The SemiSeg dataset and the actual 3D CT images that we produced are used in a variety of tests, and the analysis shows that Mixup-Inf-Net semi-supervised outperforms most SOTA segmentation models learning framework model in this study, which also enhances segmentation performance. © 2023 SPIE.

Managing disruptions in the maritime industry – a systematic literature review

PurposeThis paper presents a systematic review of the literature in the domain of maritime disruption management, upon which future research framework and agenda are proposed. Two review questions, i.e. the measures that are employed to manage disruptions and how these contribute to resilience performance, were pursued.Design/methodology/approachThe systematic literature review procedure was strictly followed, including identification and planning, execution, selection and synthesis and analysis. A review protocol was developed, including scope, databases and criteria guiding the review. Following this, 47 articles were eventually extracted for the systematic review to identify themes for not only addressing the review questions but also highlighting future research opportunities.FindingsIt was found that earlier studies mainly focused on measures, which are designed using mathematical models, management frameworks and other technical support systems, to analyse and evaluate risks, and their impacts on maritime players at the levels of organisation, transport system and region in which the organisation is embedded. There is, however, a lack of research that empirically examines how these measures would contribute to enhancing the resilience performance of maritime firms and their organisational performance as a whole. Subsequently, a Digitally Embedded and Technically Support Maritime Disruption Management (DEST-MDM) model is proposed.Research limitations/implicationsThis review is constrained by studies recorded by the Web of Science only. Nevertheless, the proposed research model would expectedly contribute to enhancing knowledge building in the specific domain of maritime disruption management and supply chain management overall while providing meaningful managerial implications to policymakers and managers in the maritime industry.Originality/valueThis research is perhaps one of the first studies which presents a systematic review of literature in maritime disruption management and proposes a future research framework that establishes the link between disruption management and resilience and organisational performance for empirical validation.

Research on Chest X-Ray Image Diagnosis of Covid-19 Based on Improved ResNet

With the outbreak of covid-19 in 2020, timely and effective diagnosis and treatment of each covid-19 patient is particularly important. This paper combines the advantages of deep learning in image recognition, takes RESNET as the basic network framework, and carries out the experiment of improving the residual structure on this basis. It is tested on the open source new coronal chest radiograph data set, and the accuracy rate is 82.3%. Through a series of experiments, the training model has the advantages of good generalization, high accuracy and fast convergence. This paper proves the feasibility of the improved residual neural network in the diagnosis of covid-19. © 2023 SPIE.

Using Community-Based Implementation Frameworks and Strategies to Address Food Insecurity During the COVID-19 Pandemic: A Scoping Review

This scoping review aims to describe the main barriers to food security imposed by the COVID-19 pandemic in low-income U.S. households, identify effective community-based implementation frameworks and strategies, and discuss the lessons learned from implementing community-based approaches during the COVID-19 pandemic. Most cited barriers were categorized into the Community/Society-Policy category of "Social determinants of health in communities." Out of the twelve included studies, only five (42%) adopted an implementation framework in their food-insecurity interventions. This study can guide the development and sustainability of food programming during emergencies with possible transfer of lessons learned to food programs in low-income populations.Copyright © 2022 Taylor & Francis Group, LLC.

Argumentation and Causal Models in Human-Machine Interaction: A Round Trip

In the field of explainable artificial intelligence (XAI), causal models and argumentation frameworks constitute two formal approaches that provide definitions of the notion of explanation. These symbolic approaches rely on logical formalisms to reason by abduction or to search for causalities, from the formal modeling of a problem or a situation. They are designed to satisfy properties that have been established as necessary based on the study of human-human explanations. As a consequence they appear to be particularly interesting for human-machine interactions as well. In this paper, we show the equivalence between a particular type of causal models, that we call argumentative causal graphs (ACG), and argumentation frameworks. We also propose a transformation between these two systems and look at how one definition of an explanation in the argumentation theory is transposed when moving to ACG. To illustrate our proposition, we use a very simplified version of a screening agent for COVID-19. © 2022 Copyright for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0)

Evaluation of the Cross-Platform Framework Flutter Using the Example of a Cancer Counselling App

The advance of digitalization is constantly bringing new solutions to various areas of life in our society. The COVID-19 pandemic, among other things, brought increased attention to the application and support of treatments through digital solutions in the healthcare sector due to contact restrictions. However, the development of digital solutions comes at a high cost in terms of time and expenses. Mobile app development requires the development of two separate apps for the two respective market-leading mobile operating systems iOS and Android. Cross-platform frameworks make it possible to develop apps for both operating systems on a single code base, thus saving the development and maintenance of two separate codes. Flutter is currently the most popular cross-platform framework for the development of mobile apps. This paper has evaluated Flutter based on an existing criteria catalogue. As a usage context for the evaluation, a prototype for Cancer Counselling App of the University Medical Center Freiburg was implemented. According to the gained own prototyping experience with Flutter and a thorough literature analysis in this area, the criteria catalogue was filled out and the result was compared with other mobile App development paradigms. Copyright © 2023 by SCITEPRESS - Science and Technology Publications, Lda. Under CC license (CC BY-NC-ND 4.0)

Labour Reforms and Economic Justice: Inequality, the COVID-19 Pandemic and Regionalism

Analysing the patterns of inequality in India, this paper argues that those at the bottom of the income pyramid lack the enabling conditions of access to good healthcare and education to break out of the cycle of poverty. Addressing extreme inequalities would require not just the redistribution of wealth but also a transformation in the structure of the economy so that the processes of income generation become more equitable. A beginning in this direction would require a fundamental change in the relationship between labour and capital. Analysing recent legislations to reform labour laws within India, the author observes that while they provided some benefits to the unprivileged working classes, the overall effect has been to weaken labour unions and relax labour laws making it easier for them to be exploited. Enduring change will require new development models based on strong normative frameworks for ensuring equity and sustainability. © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023.

Bayesian optimization for artificial neural networks: application to Covid-19 image classification

Training a Convolutional Neural Network (CNN) is a difficult task, especially for deep architectures that estimate a large number of parameters. Advanced optimization algorithms should be used. Indeed, it is one of the most important steps to reduce the error between the ground truth and the model prediction. In this sense, many methods have been proposed to solve the optimization problems. In general, regularization, more specifically, non-smooth regularization, can be used in order to build sparse networks, which make the optimization task difficult. The main aim is to develop a novel optimizer based on Bayesian framework. Promising results are obtained when our optimizer is applied on classification of Covid-19 images. By using the proposed approach, an accuracy rate equal to 94% is obtained surpasses all the competing optimizers that do not exceed an accuracy rate of 86%, and 84% for standard Deep Learning optimizers. © 2022 IEEE.

Design to Improve Social Presence among University Students in Asynchronous Online Learning Environment

Since the COVID-19 pandemic, online lectures are becoming more common in higher education. Specifically, asynchronous online classes have become increasingly popular because of their flexibility. Asynchronous online courses, however, may negatively impact students' academic performance and social development due to the diminished sense of social presence. To explore ways to enhance social presence among students in asynchronous online classes, this paper used a co-design methodology that involved 12 undergraduate students as primary stakeholders. As a result, we developed a design framework for designing in-class interaction to promote social presence in asynchronous online lectures. This framework consists of four high-level elements and sub-categories: interaction topic (direct or peripheral topics related to learning), interaction size (small or entire group), interaction mode (anonymity, synchronicity, instructor involvement), and interaction motivator (lightweightness and entertainment). Our design framework may serve as a guide to future technology for improving asynchronous online classes. © 2023 Owner/Author.

Exposure to SARS-CoV-2 Aerosols in U.S. Residences: Sample analysis Using Two Detection Criteria

Uniform practices and quality control methods are needed to detect and quantify airborne viruses across sampling and analysis platforms. We compared detection of airborne SARSCoV-2 RNA in residences of individuals with COVID-19 using two commonly used criteria: environmental (at least one SARS-CoV-2-specific gene and internal control amplified by PCR with Ct ≤ 40) and clinical (at least two SARS-CoV-2-specific genes and internal control amplified with Ct ≤ 37). 24-hr total aerosol samples were collected in a self-isolation room and an additional room without manipulating subjects' behavior/activities. Under the environmental criterion, 7/16 samples in primary rooms and 7/15 samples in secondary rooms were positive. Comparable but lower positive sample proportions were observed using the more rigorous clinical criterion: 6/16 primary rooms and 5/15 secondary rooms. A consensus SARS-CoV-2 environmental sampling and analysis framework is needed for comparisons between studies. © 2022 17th International Conference on Indoor Air Quality and Climate, INDOOR AIR 2022. All rights reserved.

Special Issue on Application of Implementation Science to Improve Outcomes for Students With Disabilities: Synthesis and Future Directions

Over the last 20 years, researchers examining the education of students with disabilities have made a concerted effort to develop evidence-based practices (EBP) and enact policies to promote and support their usage to raise expectations and improve outcomes. However, the promised results of EBP are still elusive. This special issue illustrates the potential and impact of using implementation science across various educational contexts to develop enabling conditions for leaders and educators to support the use of evidence. We summarize the special issue's articles on the use of implementation science to support progress toward obtaining outcomes for students with disabilities. Specifically, key takeaways from each article and connections between articles are made. The summary concludes with key recommendations for policymakers, education agencies at each level of the system, and our practitioners who make use of implementation science methods and practices. © Hammill Institute on Disabilities 2023.

An Iot-Based Covid Patient Health Control System

Healthcare monitoring frameworks emerged as one of the most essential frameworks and innovations established over the last decade. As a result of failing to provide adequate clinical attention to patients at the appropriate time, many people are facing the possibility of an untimely death. Ultimately, the goal was to develop an IoT-based integrated healthcare monitoring framework that could be relied upon by healthcare professionals to screen their patients, whether they were in the hospital or at home, to ensure that they were being well-cared for. A mobile phone-based remote healthcare monitoring framework has been constructed with the help of sensors, an information acquisition unit, a microcontroller (such as Arduino), and a product modification. This framework has the potential to provide continuous web-based data regarding a patient's physiological states (i.e., JAVA). Before transmitting it to the specialist's portable device along with the application, the framework examines the patient's temperature, heart rate, and EEG data. It then displays and saves this information. An Internet of Things-based patient monitoring framework may monitor a patient's health condition in an efficient manner and save the patient's life at the appropriate moment. © 2023 IEEE.

Building health service management workforce capacity in the era of health informatics and digital health - A scoping review.

INTRODUCTION: Health informatics and digital health, two rapidly growing disciplines, are becoming increasingly important to the sustainability of health service provision, highlighted especially through the COVID-19 pandemic. To maximise the benefits of the adoption and growth of health informatics and digital health, health service managers play a critical role in leading and managing the implementation and transformation of the system, both strategically and operationally, whilst still needing to manage 'business as usual'. OBJECTIVES: The objectives of the paper are to present and discuss the findings from a scoping review identifying: 1) competencies required for health service managers leading the implementation and transformation of informatics and digital technology in the health sector; and 2) factors that are critical to building the management workforce capacity in the era of health informatics and digital health. METHODS: A scoping review of the literature was conducted in 2020 focussing on identifying empirical articles published in the English language since the year 2000 using a number of keywords such as 'health informatics', 'digital health', 'electronic health', 'competencies', 'capability', 'proficiency', 'qualification', 'certification', 'health manager', 'health executive' and 'health administrator'. The literature search was guided by a PRISMA approach searching within eight databases: Scopus, ProQuest, Web of Science, ACM Digital Library, CINAHL, PubMed, Google Scholar and ProQuest Dissertations. RESULTS: After duplicates were removed, 941 publications were included for title screening as the result of an initial review. Title screening selected 185 articles to be included for abstract screening by two reviewers confirming 19 papers relevant to the focus of the current paper which were included in data extraction and content analysis. The analysis identified the additional competency of 'information and data management' be included as a core competency for health service managers. The analysis also confirmed additional elements for the following four core management competencies that are important to health service managers working in the digital health context, including: 1) leadership; 2) operational and resource management; 3) personal, interpersonal and professional qualities, and 4) understanding the industry and environment. Factors that are critical to developing the system and organization capacity in the use of health informatics and digital health technology, and leading and managing the adoption in the healthcare organizations were identified in three categories: 1) policy/system; 2) organizational structure and processes; and 3) people factors. CONCLUSIONS: This paper has taken an important step in confirming the competency requirements for health services managers that are relevant to leading and managing in the health informatics and digital health space, consequently indicating the directions for developing a competent workforce in meeting the existing and emerging healthcare delivery challenges, both now and in the future.

"Constrained medical oxygen supply chain in India during COVID-19: Red-tapism, the elephant in the room?"

BACKGROUND: Recent disruption of medical oxygen during second wave of COVID-19 has caused nationwide panic. This study attempts to objectively analyze the medical oxygen supply chain in India along the principles of value stream mapping (VSM), identify bottlenecks and recommend systemic improvements. METHODOLOGY: Process mapping of the medical oxygen supply chain in India was done. Different licenses & approvals, their conditions, compliances, renewals among others were factored-in. All relevant circulars (Government Notices), official orders, amendments and gazette notifications pertaining to medical oxygen from April 2020-April 2021 were studied and corroborated with information from Petroleum & Explosives Safety Organization (PESO) official website. FINDINGS: Steps of medical oxygen supply chain right from oxygen manufacture to filling, storage and transport up to the end users; have regulatory bottlenecks. Consequently flow of materials is sluggish and very poor information flow has aggravated the inherent inefficiencies of the system. Government of India has been loosening regulatory norms at every stage to alleviate the crisis. CONCLUSION: Regulatory bottlenecks have indirectly fueled the informal sector over the years, which is not under Government's control with difficulty in controlling black-marketing and hoarding. Technology enabled, data-driven regulatory processes with minimum discretionary human interface can make the system more resilient.

Health System Shock Frameworks Between Theory, Application, and Assessment Comment on "The COVID-19 System Shock Framework: Capturing Health System Innovation During the COVID-19 Pandemic".

The COVID-19 System Shock Framework (CSSF) tested the resilience of service providers throughout the coronavirus disease 2019 (COVID-19) pandemic in Australia. In this commentary, we tackle the topic of the CSSF applicability in less mature health systems and propose elements or dimensions that could be added to provide comprehensive response to future shocks. We acknowledge the fact that information systems, telehealth, and standard operation procedures constitute important pillars of system shock frameworks. However, there are doubts on the applicability of such pillars in middle- and low-income countries where the infrastructure is weaker compared to high-income countries and the digital divide is wider. Moreover, while it provided a paramount solution to deliver health services during the pandemic, the negative impact of telehealth should be addressed. In addition, we propose that CSSF should consider focusing on the continuity of the other medical conditions, which may have been affected due to the mitigation policies. Finally, we propose adding a dimension on the evaluation of CSSF to provide quantifiable and comparable assessment with other providers or systems.

Electrospray-on-Electrospun Breathable, Biodegradable, and Robust Nanofibrous Membranes with Photocatalytic Bactericidal Activity

The increasing emergence of infectious diseases like COVID-19 has created an urgent need for filtration/purification materials coupled with multifunctional features such as mechanical integrity, excellent airflow/filtration, and antibacterial/antimicrobial properties. Polymer membranes and metal-organic frameworks (MOFs) have demonstrated high effectiveness in air filtration and purification. MOF nanoparticles have been introduced into electrospun polymer nanofibrous membranes through embedding or postsolution growth. However, the derived hybrids are still facing the issue of (1) limited MOF exposure, which leads to low efficacy;and (2) uncontrollable growth, which leads to pore blocking and low breathability. In this work, we customized an electrospray-on-electrospinning in situ process to dynamically integrate MOF nanoparticles into a robust and elastic continuous nanofibrous membrane for advanced properties including high mechanical strength and flexibility, excellent breathability, particle filtration, and good antimicrobial performance. Biodegradable polylactic acid was reinforced by the poly(hydroxybutyrate)-di-poly(DLA-CL)x copolymer (PHBR) and used as an electrospinning matrix, while MOF nanoparticles were simultaneously electrically sprayed onto the nanofibers with easily controllable MOF loading. The MOF nanoparticles were homogeneously deposited onto nanofibers without clogging the pores in the membrane. The collision of PLA and MOF under the wet status during electrospinning and the hydrogen bonding through C=O and N-H bonds strengthen the affinity between PLA nanofibers and MOF nanoparticles. Because of these factors, the MOF-incorporated PLA/PHBR nanofibrous membrane achieved over 95% particle filtration efficiency with enhanced mechanical properties while maintaining high breathability. Meanwhile, it exhibits excellent photocatalytic antibacterial performance, which is necessary to kill microbes. The electrospray-on-electrospinning in situ process provides an efficient and straightforward way to hybridize one-dimensional (1D) or two-dimensional (2D) nanomaterials into a continuous nanofibrous membrane with strong interaction and controllable loading. Upon integrating proper functionalities from the materials, the obtained hybrids are able to achieve multifunctionalities for various applications.

Customized Luminescent Multiplexed Quick-Response Codes as Reliable Temperature Mobile Optical Sensors for eHealth and Internet of Things

The need to sense and track in real time through sustainable and multifunctional labels is exacerbated by the COVID-19 pandemic, where the simultaneous measurement of body temperature and the fast tracking of people is required. One of the big challenges is to develop effective low-cost systems that can promote healthcare provision everywhere and for that, smarter and personalized Internet of things (IoT) devices are a pathway in large exploration, toward cost reduction and sustainability. Using the concept of color-multiplexed quick response (QR) codes, customized smart labels formed by two independent layers and smart location patterns provide simultaneous tracking and multiple synchronous temperature reading with maximum sensitivity values of 8.5% K-1 in the physiological temperature range, overwhelming the state-of-the-art optical sensor for healthcare services provided electronically via the internet (eHealth) and mobile sensors (mHealth).

Universal health coverage mitigated COVID-19 health-related consequences in Asia Oceania.

The COVID-19 pandemic has been a continual challenge since 2020, and it continues to impact people and industries as a disaster caused by a biological hazard. This study examined universal health coverage (UHC) scores in relation to the performance in combating COVID-19 in the Southeast Asian region (SEAR) and the Western Pacific region (WPR), along with the State Party Self-Assessment Annual Reporting (SPAR) index under the international health regulations (IHC). The numbers of infections and deaths per million population from December 2019 to June 2022 were used as primary outcomes to measure countries' performance. Countries with UHC scores of 63 or higher had a significantly lower number of infected patients and deaths. In addition, several inter-capacity correlations within the SPAR capacities, including with C8 (the National Health Emergency Framework), as well as a very strong correlation to C4 (Food Safety), C5 (Laboratory), and C7 (Human Resources). Furthermore, C9 (Health Service Provisions) has a very strong correlation to C1 (Legislation and Financing), C2 (International Health Regulation Coordination and a National IHR Focal Point function), and C4 (Food Safety), suggesting that the capability to manage an emerging infectious disease form blocks of capacities. In conclusion, UHC clearly mitigated the health-related consequences of COVID-19 in South-East Asia Region (SEAR) and Western Pacific Region (WPR). Investigating the correlation between the SPAR capacities and UHC is a promising approach for future research, including the importance of the provision of health services, points of entry, and, most importantly, risk communications as critical factors for managing pandemic. This study constitutes a good opportunity to apply the SPAR index to define which capacities correlate with the outcome of the pandemic in terms of infections and deaths.

Immune Literacy: a Call to Action for a System-Level Change.

Immune literacy-the ability to hear, learn, read, write, explain, and discuss immunological content with varied audiences-has become critically important in recent years. Yet, with its complex terminology and discipline-specific concepts, educating individuals about the immune system and its role in health and disease may seem daunting. Here, we reflect on how to demystify the discipline and increase its accessibility for a broader audience. To address this, a working group of immunology educators from diverse institutions associated with the research coordination network, ImmunoReach, convened virtually. As a result of these discussions, we request a call to action for a system-level change and present a set of practical recommendations that novice and experienced educators from diverse institutions, professional societies, and policymakers may adopt to foster immune literacy in their classrooms and communities.

Developing a Conceptual Framework for Smart Education Environment Integrating IoT in Architectural Education Adapting Global Competence

Information and communication technology (ICT) advancements have an impact on many aspects of life and society, including the educational system. A key component of smart cities and the educational system alike, the IoT (Internet of Things) is becoming increasingly crucial. The COVID-19 epidemic, which began in March 2020, has accelerated educational reform and compelled institutions of higher learning to integrate ICT. Despite this, the Internet of Things (IoT) is still in its infancy in the education system, and its influence is still largely unknown. The research is an attempt to explore the potential of IoT in architectural education pedagogy which is primarily relying on creativity and innovation. Re-thinking about the student-centered pedagogies which acquires critical thinking skills, polite communication skills, conflict resolution skills, perspective taking skills, and adaptability towards global competence is the demand of the time which is the focus of the research. The outcome of the article is to propose a conceptual framework for smart education environment integrating IoT in Architectural Education adapting Global Competence for the future generations. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.