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The purpose of this paper is to develop an automatic control system for mechanical ventilation therapy based on the open lung concept (OLC) using artificial intelligence. In addition, mean arterial blood pressure (MAP) is stabilized by means of a decoupling controller with automated noradrenaline (NA) dosage to ensure adequate systemic perfusion during ventilation therapy for patients with acute respiratory distress syndrome (ARDS).

The aim is to develop an automatic control system for mechanical ventilation therapy based on the OLC using artificial intelligence. In addition, MAP is stabilized by means of a decoupling controller with automated NA dosage to ensure adequate systemic perfusion during ventilation therapy for patients with ARDS.

This innovative closed-loop mechanical ventilation system leads to a significant improvement in oxygenation, regulates end-tidal carbon dioxide for appropriate gas exchange and stabilizes MAP to guarantee proper systemic perfusion during the ventilation therapy.

Currently, this automatic ventilation system based on the OLC can only be applied in animal trials; for clinical use, such a system generally requires a mechanical ventilator and sensors with medical approval for humans.

For implementation of a closed-loop ventilation system, reliable signals from the sensors are a prerequisite for successful application.

The experiment with porcine dynamics demonstrates the feasibility and usefulness of this automatic closed-loop ventilation therapy, with hemodynamic control for severe ARDS. Moreover, this pilot study validated a new algorithm for implementation of the OLC, whereby all control objectives are fulfilled during the ventilation therapy with adequate hemodynamic control of patients with ARDS.

Open data are characterized by a number of economic, environmental, technological, innovative, and social benefits. They are seen as a significant contributor to the city’s transformation into smart city. This is all the more so when the society is on the border of Society 5.0, that is, shift from the information society to a super smart society or society of imagination takes place. However, the question constantly asked by open data experts is, what are the key factors to be met and satisfied in order to achieve promised benefits? The current trend of openness suggests that the principle of openness should be followed not only by data but also research, education, software, standard, hardware, etc., it should become a philosophy to be followed at different levels, in different domains. This should ensure greater transparency, eliminating inequalities, promoting, and achieving sustainable development goals (SDGs). Therefore, many agendas (sustainable development strategies, action plans) now have openness as a prerequisite. This chapter deals with concepts of open (government) data and Society 5.0 pointing to their common objectives, providing some success stories of open data use in smart cities or transformation of cities toward smart cities, mapping them to the features of the Society 5.0. We believe that this trend develops a new form of society, which we refer to as “open data-driven society.” It forms a bridge from Society 4.0 to Society 5.0. This chapter attempts to identify the role of openness in promoting human-centric smart society, smart city, and smart living.

The purpose of this paper is to describe and discuss the use of Chinese medicine in the prevention and treatment of coronavirus disease 2019 (COVID-19) in China and Asia.

This paper provides a brief overview of the COVID-19. Based on the syndrome differentiation (辨證論治), the concept of clearing heat and detoxifying lung in traditional Chinese medicine is used to prevent and treat COVID-19 through restoring the vital qi (正氣) in human body and regulating the lung as well as spleen to strengthen the immune system. Traditional Chinese medicine has been used as a complementary therapy for the possible intervention of COVID-19 including traditional Chinese herbal decoctions, Chinese traditional patent medicines, acupuncture and moxibustion as well as the traditional health exercises in China and parts of Asia.

Traditional Chinese medicine plays a significant role in the prevention and treatment of COVID-19 pandemic. The infection cases of China are around 80,000 and a steady decline compared with the USA which has 5,000,000 infection cases and continuous increases. It is shown that more than 90% of patients recovered after the treatment of traditional Chinese herbal decoctions and Chinese traditional patent medicines without any side-effect compared to the use of Remdesivir (GS-5734). Acupuncture (針灸) and moxibustion (艾灸) stimulate the immune and nervous systems for preventing infectious diseases. Taichi (太極) and Baduanjin (八段錦) as the auxiliary aerobic exercise under the theory of Chinese medicine can enhance the immune system and improve the lung function. Thus, an integration of traditional Chinese Medicine and Western medicine is the best strategy for the prevention, treatment and control of COVID-19 pandemic in the future.

This paper describes traditional Chinese medicine as an effective way for the prevention and treatment of COVID-19.

The purpose of this paper is to show an efficient method for the detection of signs of early lung cancer. Various image processing algorithms are presented for different types of lesions, and a scheme is proposed for the combination of results.

A computer aided detection (CAD) scheme was developed for detection of lung cancer. It enables different lesion enhancer algorithms, sensitive to specific lesion subtypes, to be used simultaneously. Three image processing algorithms are presented for the detection of small nodules, large ones, and infiltrated areas. The outputs are merged, the false detection rate is reduced with four separated support vector machine (SVM) classifiers. The classifier input comes from a feature selection algorithm selecting from various textural and geometric features. A total of 761 images were used for testing, including the database of the Japanese Society of Radiological Technology (JSRT).

The fusion of algorithms reduced false positives on average by 0.6 per image, while the sensitivity remained 80 per cent. On the JSRT database the system managed to find 60.2 per cent of lesions at an average of 2.0 false positives per image. The effect of using different result evaluation criteria was tested and a difference as high as 4 percentage points in sensitivity was measured. The system was compared to other published methods.

The study described in the paper proves the usefulness of lesion enhancement decomposition, while proposing a scheme for the fusion of algorithms. Furthermore, a new algorithm is introduced for the detection of infiltrated areas, possible signs of lung cancer, neglected by previous solutions.

The study described here aims to set forth an analysis approach for a specific biomedical therapeutic device principally involving fluid mechanics and resulting sound generation. The function of the therapeutic device is to clear mucus from the airways of the lungs. Clearance of the airways is a primary means of relief for cystic fibrosis and is also effective in less profound dysfunctions such as asthma. The complete system consists of a device to periodically pulse air pressure and a vest that girdles the abdomen of the patient and receives and discharges the pulsating airflow. The source of pulsed air can be tuned both with respect to the amplitude and frequency of the pressure pulsations.

The key design tools used here are computational fluid dynamics and the theory of turbulence-based sound generation. The fluid flow inside of the device is multidimensional, unsteady and turbulent.

Results provided by the fluid mechanic study include the rates of fluid flow between the device and the inflatable vest, the rates of air supplied to and extracted from the device, the fluid velocity magnitudes and directions that result from the geometry of the device and the magnitude of the turbulence generated by the fluid motion and the rotating component of the device. Both the velocity magnitudes and the strength of the turbulence contribute to the quantitative evaluation of the sound generation.

A comprehensive literature search on this type of therapeutic device to clear mucus from the airways of the lungs revealed no previous analysis of the fluid flow and sound generation inside of the device producing the pulsed airflow. The results presented in this paper pinpoint the locations and causes of sound generation that can cause audible discomfort for patients.

Many of the ethical issues of additive manufacturing (AM) are not well known or understood, and there remains a policy vacuum that needs to be addressed. This paper aims to describe an approach that has been applied successfully to other emerging technologies, referred to as the responsible research and innovation (RRI) framework programme. A case is then made for the application of this approach in the AM industry with an illustration of how it might be used.

The research uses an RRI approach referred to as AREA, an acronym for Anticipate, Reflect, Engage and Act, to assess the ethical implications of AM. For the anticipation phase, horizon scanning was done to explore the ethical issues of AM based on extant literature, while reflective analysis was carried out all through the work to reflect on the data being collected and the research process. The engage phase involved interviews with five participants from small- and medium-sized enterprises (SMEs) involved in 3D printing.

The findings indicate that although AM appears to pose a threat to intellectual property rights, many in the industry do not care about this issue. As AM becomes mainstream, intellectual property will likely become a big problem. Also, very little is known about the health impacts of AM. This study shows that AM can be hazardous.

Only users at SME level were sampled. Other researchers might test the usefulness of AREA at the enterprise level.

The research demonstrates how the AREA framework may be useful in information systems and social science research by enabling a more anticipatory and reflective research process.

The paper responds to the need for a novel approach to identifying ethical issues of AM.

During recent years, web technologies and mass media have become prevalent in the context of medicine and health. Two examples of important web technologies used in health are news media and patient forums. Both have a significant role in shaping patients' perspective and behaviour in relation to health and illness, as well as the way that they might choose or change their treatment. In this paper, the authors investigated the application of web technologies using the data analysis approach. The authors did this analysis from the point of view of topics being discussed and disseminated via patients and journalists in breast and lung cancer. The study also investigated the (dis)alignment amongst these two groups and scientists in terms of topics.

Three data sets comprised documents published between 2014 and 2018 obtained from ProQuest and Web of Science Medline databases, alongside data from three major patient forums on breast and lung cancer. The analysis and visualisation in this paper have been done using the udpipe, igraph R packages and VOSviewer.

The study’s findings showed that in general scientists focussed more on prognosis and treatment of cancer, whereas patients and journalists focussed more on detection, prevention and role of social and emotional support. The only exception was for news coverage of lung cancer where the largest cluster was related to treatment, research in cancer treatment and therapies. However, when comparing coverage by scientists and journalists in terms of treatment, the focus of news articles in both cancer types was mainly on chemotherapy and complimentary therapies. Finally, topics such as lifestyle or pain management were only discussed by breast cancer patients.

The results obtained from this study may provide valuable insights into topics of interest for each group of scientists, journalist and patients as well as (dis)alignment among them in terms of topics. These findings are important as scientific research is heavily dependent on communication, and research does not exist in a bubble. Scientists and journalists can gain insights from patients' experiences and needs, which in turn may help them to have a more holistic and realistic view.

The peer review history for this article is available at: https://publons.com/publon/10.1108/OIR-06-2020-0228

Ventilation of indoor spaces is required for the delivery of fresh air rich in oxygen and the removal of carbon dioxide, pollutants and other hazardous substances. The COVID-19 pandemic brought the topic of ventilating crowded indoors to the front line of health concerns. This study developed a new biologically inspired concept of biomimetic active ventilation (BAV) for interior environments that mimics the mechanism of human lung ventilation, where internal air is continuously refreshed with the external environment. The purpose of this study is to provide a detailed proof-of-concept of the new BAV paradigm using computational models.

This study developed computational fluid dynamic models of unoccupied rooms with two window openings on one wall and two BAV modules that periodically translate perpendicular to or rotate about the window openings. This study also developed a time-evolving spatial ventilation efficiency metric for exploring the accumulated refreshment of the interior space. The authors conducted two-dimensional (2D) simulations of various BAV configurations to determine the trends in how the working parameters affect the ventilation and to generate initial estimates for the more comprehensive three-dimensional (3D) model.

Simulations of 2D and 3D models of BAV for modules of different shapes and working parameters demonstrated air movements in most of the room with good air exchange between the indoor and outdoor air. This new BAV concept seems to be very efficient and should be further developed.

The concept of ventilating interior spaces with periodically moving rigid modules with respect to the window openings is a new BAV paradigm that mimics human respiration. The computational results demonstrated that this new paradigm for interior ventilation is efficient while air velocities are within comfortable limits.