Last year, there was an increase in the amount of manpower in Malaysia, especially in terms of the numbers of neurosurgeons, cognitive neuroscientists and clinical psychologists. One way to increase the number of cognitive neurotechnologists in the country in 2021 is to allow neuroscientists to register as neurotechnologists with the Malaysian Board of Technologists (MBOT). The Malaysian Brain Mapping project has risen from its humble beginnings as an initiative of the Universiti Sains Malaysia Brain Mapping Group in 2017. There is currently a proposal for its entry into the national arena via the Precision Medicine Initiative with the Academy Science Malaysia, the Ministry of Science, Technology and Innovation, Ministry of Higher Education and Ministry of Health. The current Malaysian Government’s Science, Technology, Innovation and Economy (STIE) plan was launched in 2020, leading to the establishment of neurotechnology as one of 10 STIE drivers. On 14 July 2020, the Prime Minister of Malaysia, Tan Sri Muhyiddin Yassin, chaired the National Science Council with the Ministry of Science, Technology and Innovation’s Minister Khairy Jamaluddin, Deputy Minister Ahmad Amzad Hasim and Secretary-General Datuk Ir Dr Siti Hamisah Tapsir and launched 10 Science, Technology, Innovation and Economy (STIE) drivers in accordance with the Malaysian National Policy on Science, Technology and Innovation (DSTIN) 2021–2030. One of the STIE drivers was neurotechnology  Study. Then, in December 2020, the 10–10 MySTIE framework, which trailblazed a path for prosperity, societal well-being and global competitiveness, was published and officiated by Minister Jamaluddin with the New Science Policy: DSTIN 2030  as part of its efforts to provide additional assistance for small medium enterprises (SMEs) affected by COVID-19. SME project participants in key government programmes involved in research, development and innovation for critical technologies identified under national blueprints from IR 4.0-related technologies, green technology and biotechnology to ensure continuity and the completion of existing projects. These technologies included blockchain, artificial intelligence, big data analytics, internet of things, addictive manufacturing (3D/4D/5D/6D printing), cybersecurity, system integrators, augmented reality, advanced materials, drones and manufacturing systems as well as bioscience technology and neurotechnology  has risen from its humble beginnings as an initiative of the Universiti Sains Malaysia Brain Mapping Group in 2017. There is currently a proposal for its entry into the national arena via the Precision Medicine Initiative with the Academy Science Malaysia, the Ministry of Science, Technology and Innovation, and the Ministry of Health in a recent meeting with the Academy of Science Malaysia in early 2021. This is a Malaysia’s parallel initiative of the successful Cuban Brain Mapping Project which was published recently .Thus, Malaysia must have a Centre of Excellence for Clinical Neuroscience, Psychiatry and Psychology services that, at least, represents the cluster of hospitals and teaching institutions with clinical neurosciences as well as psychiatry and clinical psychological services situated in the east coast of West Malaysia in the 12th Malaysia Plan that emphasises the use of neurotechnology in healthcare. It is also important to consistently build the younger generation of neuroscientists, neurologists, neurosurgeons, neurorehabilitation specialists, clinical psychologists and clinical neuropsychologists since it takes nearly 11 to 16 years to train them to address the needs of the country using neurotechnology to diagnose and cure diseases.


We live in complex times in the health, social, political, and energy spheres, and we must be aware of and implement new trends in intelligent social health systems powered by the Internet of Things (IoT). Sustainable development, energy efficiency, and public health are interrelated parameters that can transform a system or an environment for the benefit of people and the planet. The integration of sensors and smart devices should promote energy efficiency and ensure that sustainable development goals are met. This work is carried out according to a mixed approach, with a literature review and an analysis of the impact of the Sustainable Development Goals on the applications of the Internet of Things and smart systems. In the analysis of results, the following questions are answered about these systems and applications: (a) Are IoT applications key to the improvement of people’s health and the environment? (b) Are there research and case studies implemented in cities or territories that demonstrate the effectiveness of IoT applications and their benefits to public health? (c) What sustainable development indicators and objectives can be assessed in the applications and projects analyzed? Today, technological advances must be accompanied by their applications and implementation in human-inhabited environments, in which public health and energy efficiency play an important role ,2. The sSmart grids and smart cities should facilitate people’s access to environments, facilitate healthcare services, and promote the safety and happiness in our society. Technologies such as the IoT, the Internet of Energy, artificial intelligence, and the installation of sensors in human environments are used to optimize infrastructures, services, and the strategic planning of communities.We must design and implement advanced facilities, equipped with sensors and devices that promote the safety and health of people while maintaining a balance between energy use and efficiency. We must train professionals in the technological and engineering sectors, in universities, to keep humans and sustainability at the heart of their designs and projects.It is essential that the incorporation of intelligent systems is efficient from a technical, safety, and economic point of view. Sensor devices, the Internet of Everything, together with reliable and safe electrical installations and comfortable human environments will lead to cost reduction, higher productivity, and health and safety for people, companies, and institutions.We cannot forget that the implementation of energy audits in environments inhabited by people is based on a reduction in greenhouse gas emissions, which will have direct effects on the improvement of people’s health, the protection of the environment, and profitability. All these parameters that directly or indirectly affect IoT platforms, energy control, and health should be analyzed as a part of all human health research ,10,11,12IoT applications and their multiple developments and advances are unstoppable; sensors, intelligent devices, systems, and advanced technological architectures offer great prospects for development in cities and communities in the present and in the near future .The digitization and application of intelligent systems and IoT devices in urbanized environments and in communities inhabited by people is carried out in blocks of analysis, structured in different disciplines, but all of them have a common center of gravity, the trilogy: human–technology–sustainability. We will analyze this trilogy and its main applications, as an introduction to the research carried out .Cities and human-inhabited environments have come under great digital and technological pressure in recent years, and this has been exacerbated by the global pandemic caused by COVID-19 ,16,17. TIn the analysis of human environment systems, such as cities or communities, it is necessary to carry out an in-depth study of the conflicts and systems in which an advanced society is involved. These systems and environments must also be involuted as an active part of a whole that brings together, for example, waste management, the measurement of environmental pollution ,22,23, eSociety needs efficient and healthy resources and everything depends on their management, improved governance, and projects that stimulate the implementation of advanced technological systems to facilitate the path to sustainable development. The management of water, transportation, and agriculture must be taken into account for social growth and human health, since these fields directly involve healthy food and better air quality ,30,31,32One of the parameters to which we must pay special attention in this study is that of IoT applications for the improvement of people’s health. It will be one of the parameters that we will explore as a common thread throughout the work, in which we will interrelate sustainable development and energy control as necessary elements for its evaluation. Social and public health aspects are at the forefront of the research and work on intelligent systems ,34,35.Many intelligent systems applied to human environments will be developed in the next decade, serving to improve the health and quality of life of our societies. They will be ubiquitous, applied in homes, elderly care facilities, hospitals and health centers, schools, and universities, and many institutions will request sensor devices and IoT systems to be implemented for health management ,37,38.Governments and political management strategy around intelligent devices, technology, sensors, and IoT systems must be effective and take into account sectors and disciplines such as engineering, computer science, architecture, healthcare, etc. There are multiple cities and territories that are applying the Smart City and Smart Human City strategy to address the future and implement technological advances in cities ,41,42,43Smart, sustainable, and efficient cities must be designed with sensor systems and IoT applications; the so-called “sensory city” is an integrative model that will enhance people’s lives, management processes, and, with energy efficiency, environmental sustainability and people’s health as the three main pillars ,47,48,49IoT applications and systems aim to make the Internet even more immersive and integrated into our environment in a natural way. It must be easy to access and interact with any of the devices around us—for example, traffic lights, security cameras, telephones, computers, tablets, vehicles, signs, stores, sensors, health centers, etc. ,51.The analysis and location of intelligent systems within urban, rural, and generally human spaces is complex. Sensors, actuators, and devices are located and move with people; they can be fixed but are increasingly mobile—for example, in cell phones or vehicles. However, there are organized architectures and levels of design around how intelligent systems should or can be arranged in human environments, e.g., in cities, communities, or in any other environment . Figure IoT applications, according to , can be In the most common architecture of IoT systems and their applications, it is usually broken down into layers of performance or system implementation. For example, the following main layers ,15: applEach of these sub-architectures or working layers integrate the different technologies, devices, sensors, systems, etc., which will be interconnected by means of electrical–electronic and wired or wireless connections. The range of connection elements is very wide and each field of action will have its own specific systems.Specifically, speaking of systems applicable to people’s health, we can choose and differentiate some of them. In some cases, research is focused on simple, low-cost, ubiquitous devices for monitoring people’s health ; in otheTechnological systems in the smart human home: environmental systems, personal systems, data management systems and interfaces, actuators electrical systems and protections, energy efficiency controllers, software, automation systems, augmented reality, etc.Applications to people’s health: smart healthcare, monitoring of activities of daily living, monitoring for medical management, robotic personal assistance devices, fall monitoring and control devices, telecare for social interaction and leisure, automation for human–machine interaction, implantable medical devices, sensors, microsensors and general-purpose devices, intelligent materials, etc.The different existing technologies and systems can be listed, also providing an update and preview of those to come in the future:Innovative projects based on the realization of patents, prototypes, and technological applications using IoT, sensors, and intelligent systems can come from research centers with public or private funding, companies, or public or private institutions, among others. For example, there are large technology companies, such as Telefónica Koa Health , which aThe 2030 Agenda of the United Nations (UN) established the Sustainable Development Goals (SDGs) in 2015. This Agenda is an action plan for people, the planet, and prosperity. The 17 goals are comprehensive and indivisible, balancing the three dimensions of sustainable development: economic, social, and environmental . This paIt is necessary to propose working methods and protocols to implement the SDGs in smart cities, taking into account citizen participation, governance, energy systems, and technological developments . There aThere is no doubt that the systems that will make technological change and progress in sustainable development possible will be the IoT, sensors, communications networks, and all the electrical, electronic, computer, and intelligent material devices that will be flexibly integrated into cities and territories. These advances will also bring major energy savings, which are fundamental to the SDG indicators and criteria and essential for energy efficiency and environmental sustainability .The interrelation of IoT systems, health, and energy efficiency has a common nexus that we want to discuss in this paper: the need to design and implement smart technology projects for cities and human environments in which the welfare and quality of life of people coexist in a sustainable and efficient system, which will inevitably lead to substantial benefits for the planet . This paThere must be clarity, transparency, and efficiency in the mass implementation of technological devices, IoT, and sensors, since society may not be prepared for this great change. Fear and ignorance and the digital divide will be important hurdles in the mass installation of systems unknown to a large majority of people. The use of technology for health and energy efficiency must be approached as an unstoppable process that will affect all areas of life. While the general public will become more acquainted with it, their doubts and fears must be addressed.The pandemic caused by Sars-Cov2 has boosted the research and implementation of useful biosensors and systems capable of obtaining reliable information to prevent, detect, and mitigate the effects of the disease , and theThis work aims to improve knowledge about existing applications and future trends in the implementation of intelligent devices and systems that improve the health of people and communities, from the perspective of energy efficiency and sustainable development. To do this, we will analyze high impact research that is being developed and its effectiveness and whether it really will benefit the health of people and the environment. We will examine its productivity, energy, and economic efficiency and we will address a question that many projects do not take into account: are the sustainable development objectives met in this research?Our aim is to analyze the technology-health-ODS trilogy and prove that it is effective and will lead to a near future in which sustainability and environmental health are achieved hand in hand with technology. A mixed research approach will review the studies and research offered by the literature on IoT solutions, sensors, smart cities, and smart grids and their importance for public health, energy efficiency, and environmental sustainability. Some of the sources and their implications in different territories will be X-rayed through institutions and technology companies and how they implement the SDG indicators.The manuscript is structured as follows: The work followed a mixed approach , in whicFollowing the recommendations of the existing literature in the literature review and case study processes, known as a mixed review ,65,66,67To achieve the objective, we performed a systematic literature review (SLR) in various databases, as set out in In this work, in addition to an SLR, a mixed method was used, so that in the analysis of the results obtained in the database search, we added research and real case studies implemented by companies or institutions, and we analyzed the most notable of these projects, providing a comprehensive range of knowledge to conduct our review .All the answers to the research questions were analyzed through a qualitative analysis of the documents extracted from the literature search and review, as well as a selection of research of international relevance that, due to its origin or good results, we found interesting for our work.In this section, we will analyze the results obtained in the literature search using keywords and filters and also include the selected case studies of the main technology giants, specified in Following the percentages and quantitative parameters, we will begin to evaluate the manuscripts and their main contributions and discussions from a qualitative perspective. We will begin the analysis by following the research questions and examining which of the selected and filtered manuscripts provide answers to the questions. It is interesting to note the main areas of study in the selection of keywords, among which Engineering and Computer Science stand out above the rest, as shown in Sometimes there are conflicts in the definitions given for smart environments and the systems applied to them and in sustainable environments, when both are complementary and necessary and, in this context, we will address the importance of linking both concepts in all aspects. Sustainability and the SDGs, together with energy efficiency protocols, must be applied to the research of intelligent systems and IoT applications, regardless of the field in which it is carried out. We shall make sure to do so in our case, with our emphasis on health protocols and people’s well-being .IoT Applications for Health Improvement;Energy Efficiency Indicators analyzed in research;Projects or case studies analyzed;Sustainable Development Goals.Among the sources in 1.Block 1: Industry 4.0, health at work, carbon emissions, solid waste management.There are a large number of research studies that deal with the health of people from the point of view of industry, occupational health, waste management, and, in general, health research from an industrial and occupational perspective. According to Oztemel , robots Analysis and evaluation of energy efficiency at work: Yes.Analysis of Sustainable Development Goals: Scarce.2.Block 2: E-health, elderly adults, environmental resources.In this block, there are several research studies that focus their analysis on e-health, health, and mobility and focus on the study of elderly people, home care, and disability, among others ,78,79. IAnalysis and evaluation of energy efficiency at work: Yes.Analysis of Sustainable Development Goals: No.3.Block 3: Cybersecurity, health, and privacy.Most of the papers explain the problem of security and privacy of people in studies on IoT and sensors applied to health; however, there are some specifically devoted to this issue, such as Hamamreh  and KoroAnalysis and evaluation of energy efficiency at work: No.Analysis of Sustainable Development Goals: No.4.Block 4: AI, smart cities, governance, urban health, energy efficiency, green IoT.In this block, different studies have been grouped together, some very similar and others different, but they all have the theme of energy efficiency or sustainability in common, which is why we will group them together for analysis ,86,87,88In the field of Artificial Intelligence (AI), Allam  reviews Tuysuz  presentsAnalysis and evaluation of energy efficiency at work: Yes.Analysis of Sustainable Development Goals: Scarce.5.Block 5: Data mining, health systems, wearable biosensors.In this set of research, diverse but all related to the IoT and its applications to health and sustainability, we found some works where the subject matter does not really specify the role of energy efficiency at work clearly, nor relate to any of the SDGs. For this reason, the following studies have been grouped into this block: ,94,95,96Analysis and evaluation of energy efficiency at work: No.Analysis of Sustainable Development Goals: No.6.Block 6: Big Data, cyber-physical systems, mobile health, public health.Rachad Atat  presentsAnalysis and evaluation of energy efficiency at work: No.Analysis of Sustainable Development Goals: No.7.Block 7: Smart buildings, healthcare, health monitoring.In this block, we have grouped research studies that focus on health indoors, in buildings and homes, responding to the needs of people in controlled environments ,104. HimDetailed discussion has been carried out on different factors contributing to thermal comfort, visual comfort and air quality comfort . MahmoodAnalysis and evaluation of energy efficiency at work: Yes.Analysis of Sustainable Development Goals: Scarce.8.Block 8: Computing architectures.We detected in the analysis of the sources that there are some studies on computer architectures  that revAnalysis and evaluation of energy efficiency at work: Yes.Analysis of Sustainable Development Goals: No.9.Block 9: Smart city applications architecture, 5G, circular economy.This block emphasizes the relationship between IoT and its application to health, taking into account the smart city strategy and the circular economy ,113,114.The circular economy in smart cities and related IoT applications is a field of work and analysis that stands out as a novel vision of activity sensorization in business, social, and health applications and many more. However, in the cases studied in this work ,112, no Analysis and evaluation of energy efficiency at work: Yes.Analysis of Sustainable Development Goals: No.10.Block 10: Drones, smart cities, security.We cannot forget the role that drone technology plays in this era where data and location provide crucial information in all fields of study. In , a studyAnalysis and evaluation of energy efficiency at work: Scarce.Analysis of Sustainable Development Goals: No.11.Block 11: Electronic waste, Sustainable Development Goals (SDGs).In all the sources analyzed, we found only one in which the involvement of SDGs in IoT research and applications and the impact on health is referred to and studied in depth  through Analysis and evaluation of energy efficiency at work: Scarce.Analysis of Sustainable Development Goals: Yes.12.Block 12: Energy management, wireless sensor networks.Anjum  studies Analysis and evaluation of energy efficiency at work: Yes.Analysis of Sustainable Development Goals: No.13.Block 13: Mobile health applications .This book  addresseLiu  applied Analysis and evaluation of energy efficiency at work: No.Analysis of Sustainable Development Goals: No.14.Block 14: Waste management, logistics.In this block, we have grouped several research papers related to waste management and logistics, as necessary elements for the preservation of health and closely related to energy and the SDGs. However, we found few references in them to energy efficiency or to any sustainability indicator. In , hybrid Another work integrated LoRaWAN communication network (network developed using the Internet of Things) with waste sorting equipment to create a system that provides automated garbage can operation, environmental monitoring, and graphical interface monitoring. The system uses electrostatic capacitance-type proximity sensors to determine the types of waste deposited in the trash cans .Regarding logistics,  reviews Analysis and evaluation of energy efficiency at work: Scarce.Analysis of Sustainable Development Goals: No.15.Block 15: Academia.In this last block, we have reviewed a research paper where the academic field is merged in IoT systems, in which experiences from different educational systems are shared. It discusses digital transformation in academic society and innovative ecosystems in the world .Analysis and evaluation of energy efficiency at work: No.Analysis of Sustainable Development Goals: No.The Millennium Development Goals  led to improved health and well-being through the collaborative efforts of United Nations (UN) agencies and their constituent Member States. In 2015, the 2030 Agenda for Sustainable Development proposed 17 Sustainable Development Goals (SDGs) . The UniThe impact of smart systems on public health is clear, but it is also important to analyze the impact of the SDGs. Therefore, in In In the presented work, a literature review has been carried out taking into account the applications of IoT, its impact on people’s health, and the environment in which we live. Several research questions have been analyzed and examined in the study of the sources investigated, as well as their relationship with the SDGs and their main targets and indicators. We are pleased to observe how a large number of studies and research efforts take into account the SDGs; however, this is generally not done intentionally, as they are not commented on or analyzed in the content of the papers. Therefore, several studies and projects strive to implement IoT designs, installations and applications for people’s health, environmental improvement, environmental protection, and energy efficiency, but not explicitly within the framework provided by the SDGs.Among the blocks and categories that we have proposed in this work, several can be considered essential to people’s health. They correspond to the SDG indicators that take into account the protection of public health, digital health, autonomous energy systems associated with the maintenance and care of healthcare equipment, and educational and training systems needed to train of healthcare staff in all territories.Industry, infrastructures, Smart Communities, Smart Human Cities, and, in general, digitalization in all areas will substantially improve people’s health, which inevitably entails the implementation of IoT systems.We have detected some of the challenges to be addressed by our societies and have put forward proposals for future research, which could bring attention to and increase interest in sustainable development and related goals through the SDGs, as a working protocol for research on IoT applications to protect the health of people and their environments, as well as improve energy efficiency. The first proposal would be the development of a protocol or work methodology in which any research on intelligent systems and IoT applications in all areas and fundamentally in health would pursue a goal or objective within the framework given by the SDGs. For example, if an application is being developed to improve the mobility of the elderly or people with disabilities at home , this coThe second proposal would be the detection of non-compliance with the SDGs in research; in this sense, any research or work that is subsidized by any government institution, through research projects, grants, contracts, etc., must be shown to comply with any of the SDGs and their main goals, in order to ensure that research of the highest quality and related to sustainable development, efficiency, and protection of people and the environment in line with the SDGs is prioritized. In the engineering research required for an energy installation, the technical–economic feasibility study of the project is no longer enough —it must The third proposal and challenge that is yet to be met, and that we have observed in the analyzed literature, is that many of the research studies pay little or no attention to energy efficiency ,99, whicThe fourth challenge proposed is to establish the European Union’s strategy on taxonomy for sustainable activities. The EU taxonomy is a classification system that establishes a list of environmentally sustainable economic activities. The EU taxonomy is an enabler that will increase sustainable investment and to implement the European Green Pact. It will provide a tool for businesses, investors, and governance to formulate policies on economic activities that can be considered environmentally sustainable. This system will be a major step towards improving the implementation of IoT applications in all disciplines and primarily in energy and health .For all the above, from what has been analyzed in the literature review, both from a quantitative and qualitative point of view and in the process of reviewing the SDGs and energy efficiency parameters, we consider that these three proposals could considerably improve future research and work in the field of sustainability and drive progress in the health, social, economic, and environmental spheres.For the implementation of all projects and work in less developed countries through low-cost means, renewable energy systems should be a further objective and indicator, to be considered essential in the research on IoT applications in all fields, especially in public health.The deployment of IoT applications and sensors in our lives is inevitable, and every day there are more connected devices and a greater number of systems that require the implementation of these technologies, especially to improve quality of life, health, safety, and in many other applications. Technology in general and the interconnectedness of different elements integrated in our homes, at work, or in the environment, parks and gardens, street furniture, traffic lights, vehicles, etc., are part of our daily lives and are increasingly essential. IoT technology and applications must be low cost and accessible to a large number of people and environments, so that the implementation of devices and their benefits to society will be enhance equity and, ultimately, will be unstoppable. The tools needed to improve the health of people and their environments, as we have analyzed in this work, are multiple and have no limit: we are developing more and more novel and original systems that are adaptable to any situation and any territory.The fact of being able to demonstrate that IoT applications benefit public health and sustainability by undergoing verification according to the indicators and goals of the SDGs would represent progress in our commitment to integrate technology in all corners of the planet and achieve universal impact, without distinction between countries, races, environments, or populations.At the beginning of this article, we proposed a bibliographic review to examine the research on IoT systems and devices, their applications and their benefit to public health and sustainability. To this end, we posed several research questions, which we have analyzed in the various sections of the work. On this basis, we conclude that there are multiple and very different works, sensor devices, and intelligent systems aimed at promoting and protecting people’s health and, in turn, the territories and the environment they inhabit. Therefore, by including a more detailed analysis of the SDGs and the implications of their goals and objectives on these devices, in Artificial intelligence and its applications in the IoT and integration in society will be essential for the fulfilment of a large part of the SDGs, so it must be integrated extensively. Meanwhile, awareness should be raised on all of the social, health, and environmental benefits that the implementation of AI projects and developments will entail. There are studies and reports that endorse this, such as ,232.To conclude, some of the highlights we have observed are: (a) the proposed analysis offers us filtered information on the research on IoT systems and applications in the field of public health and their benefits to sustainability; (b) to achieve a comprehensive social and institutional system for the protection of public health in different communities and territories, it is necessary to innovate and continue research on sensor technologies and IoT applications, since these offer information, data management, and continuous improvement of healthcare solutions, often at low cost and deployable within people’s family circles and homes; (c) the data obtained from the multiple applications implemented will allow greater control of the security of the population, for the improvement of society and its territories, which will lead to an improvement in institutional management and governance; (d) security will be important and therefore should be taken into account for the management of intelligent systems and applications geared at improving public health and efficiency; (e) the SDGs should be a vehicle for IoT development, offering its goals and objectives as a framework for the design, installation, and management of the technology to be implemented.


The nursing practice environment (NPE) has been analysed and is now recognised as a variable that influences the results of nursing care, since the promotion of favourable environments is fundamental to the quality of care optimisation . The devWe conducted a scoping review, according to Joanna Briggs Institute’s approach . A threeWe retrieved 289 records and selected 12 papers, including quantitative and qualitative studies. Our analysis revealed that positive NPE improves nurses’ satisfaction and, consequently, improves QNC. Additionally, some characteristics of the NPE should be improved, such as the participation of nurses in management decisions, leadership, education, guidance, support and recognition of the work developed by nurses. Autonomy, control over the environment and collaboration between health professionals and managers improve teamwork and QNC.A positive NPE culture in PHC is highlighted as one of the key factors for the satisfaction, retention and recruitment of nurses and is associated with the improvement of the QNC. Concurrently, the development of a teaching-learning culture between managers and the nursing team develops and improves professional skills, with the consequent improvement of nursing practices.


In the context of clinical risks, infectious risk, i.e., the probability of contracting an infection during healthcare facilities stays, is the most serious and common adverse effect and/or complication of healthcare. Hospital infections, and more generally, healthcare-associated infections (HAIs), are in fact one of the main problems in terms of morbidity, mortality, and costs that public health is currently facing ,2.The ever-increasing knowledge of the risk factors associated with hospitalisation has undoubtedly improved our ability to control HAIs, but the frequency with which they occur has remained more or less constant over the years. This is also due to an increase in the population that is particularly susceptible, which is in turn attributable, at least in part, to positive factors. Indeed, the progressive ageing of the population and the increased survival of patients with highly debilitating pathologies (made possible by the refinement of diagnostic and therapeutic techniques) means that many of today’s patients requiring care are individuals with reduced immune defences and are therefore more exposed to the risk of infection ,4.Escherichia coli and Klebsiella pneumoniae), but subsequently, as a result of antibiotic pressure and the increased use of plastic medical devices, an increase in infections with Gram-positive bacteria and fungi has been observed. Moreover, HAIs are now increasingly caused by microorganisms that are resistant to first-line drugs and are often also multi-resistant, such as MRSA (Methicillin-Resistant Staphylococcus Aureus), VRE (Vancomycin-Resistant Enterococci), and CPE (Carbapenemase-Producing Enterobacteria) [Like all infections, HAIs are the result of the interaction of three elements: the host, the infecting agent, and the environment. In particular, the habitus of the patient has an important influence on the infectious risk. Consequently, those patients most at risk are mainly the elderly, premature, and immunocompromised. The habitus also partly accounts for the type of microorganisms primarily involved. Those responsible for HAIs are not usually conventional pathogens, but mainly saprophytic microorganisms that find ideal conditions for propagation and development in the characteristics of the patients and the care environment. Until the early 1980s, HAIs were mainly caused by Gram-negative bacteria  ,6. In paacteria) ,8.Like all infections, HAIs have different modes of transmission: direct, interhuman, and indirect. Of critical importance are the cleanliness of workers’ hands, the use of medical devices and diagnostic and/or therapeutic manoeuvres, contaminated instruments, objects, and solutions, as well as other vehicles and vectors.facies of the air, leading to the inhalation of microbial aerosols and the deposition of contaminated particles.Among the various vehicles, air plays a particularly important role. Air is the vehicle through which microorganisms move through the environment, reach surfaces, and settle there, resulting in the risk of exposure through inhalation, contact with contaminated surfaces/objects or ingestion. It has been estimated that about 10% of HAIs are attributable to microbial contamination of the air, i.e., the presence of pathogenic and/or higher-than-acceptable quantities of microorganisms. Furthermore, inappropriate microclimatic conditions can affect the microbial Legionella spp., non-tubercular Mycobacteria, amoebas) [The environment’s structures and plants can also play an important role. In this context, water distribution systems and aerosols released from cooling systems, for example, should be considered, as here, microorganisms of purely environmental origin may be present, which find an ideal habitat in man-made water systems  ,9,10.It is clear that control, prevention, and surveillance measures are the best strategies to contain the spread of HAIs . HoweverNational authorities play important leadership roles in developing policies, recommendations, and guidelines in order to provide the necessary qualified personnel, facilitate the implementation of prevention and control practices in health facilities, monitor progress, and give feedback. In this regard, the identification and implementation of elements that characterise an optimal plan for HAI control and prevention are essential. Such elements include: (i) standard precautions (hand hygiene and the use of barrier measures), (ii) the monitoring of environmental microbial contamination and control of environmental sanitisation procedures, (iii) the disinfection and sterilisation of reusable equipment and devices, (iv) the availability of resources ; (v) the constant monitoring of plant structures ; (vi) the promotion of educational initiatives, as well as specific training, aimed at cultural and behavioural change on the part of health and social service providers and citizens, making best use of the scientific evidence ,13,14,15More generally, given that one of the main responsibilities of the mission of healthcare institutions is to provide quality care while guaranteeing the safety of patients and healthcare workers, the surveillance and control of all risk factors present in healthcare facilities must be an essential aspect of care ,16,17,18The in-depth examination of these issues in a dedicated Special Issue, through a multidisciplinary overview, may represent a further tool available to the scientific community to identify the best practices of proven effectiveness in the field for the implementation of decisive strategies aimed at tackling this crucial phenomenon for public health.Healthcare, primarily aims to increase the international literature evidence and observations in the field regarding the implementation of standard precautions, the adoption of specific infectious disease precautions, the improvement of staff education and responsibility, environmental monitoring, facility audits, and the appropriate use of antimicrobials.With this in mind, the Special Issue “Antimicrobial Resistance, Healthcare-Associated Infections, and Environmental Microbial Contamination”, published in the journal


The combination of physical sensors and computational models to provide additional information about system states, inputs and/or parameters, in what is known as virtual sensing, is becoming more and more popular in many sectors, such as the automotive, aeronautics, aerospatial, railway, machinery, robotics and human biomechanics sectors. While, in many cases, control-oriented models, which are generally simple, are the best choice, multibody models, which can be much more detailed, may have applications, for example, during the design stage of a new product.This Special Issue sought to attract works dealing with the many challenges that must be overcome when developing multibody-based virtual sensors. These challenges include the selection of the fusion algorithm and its parameters, the coupling or the independence between the fusion algorithm and the multibody formulation, the magnitudes to be estimated, the stability and accuracy of the adopted solution, optimization of the computational cost, real-time issues and implementation on embedded hardware. Studies of the application of multibody-based virtual sensors to, for example, vehicles, heavy machinery, mobile or humanoid robots, assistive orthotic and prosthetic devices or the measurement and analysis of human movement were also welcome.In the next paragraphs, a brief description of the content of each contribution forming the Special Issue is provided.The first work  focuses The second work  addresseThe objective of the third work  is to avThe fourth work  is not cThe fifth work  foreseesThe sixth work  deals wiThe field of application of the seventh work  is machiThe eighth work  looks atThe ninth work  intends The tenth work  is a spaIn summary, it can be seen that the papers gathered in the Special Issue contributed either by proposing solutions to the general problem of state, input and/or parameter estimation ,5,7,8,9,Finally, we wish to thank the authors, reviewers and journal staff for their commitment and effort, which made it possible to complete this Special Issue on time.


Co-authors Feiyun Huang and Jialing Tang were unintentionally omitted as authors in the original published article. The corrected author list and Author Contribution Statement appears below.The authors apologize for this error and state that this does not change the scientific conclusions of the article in any way. The original article has been updated.1†, Feiyun Huang2†, Yinan Ma3*, Jialing Tang4*Lin Feng1Sport Hospital Affiliated to Chengdu Sport University, Chengdu Sport University, Chengdu, China2Key Laboratory of Bio-Resources and Eco-Environment (Ministry of Education), College of Life Sciences, Sichuan University, Chengdu, China3Department of Physical Education, Yili Normal University, Yining, China4Department of P.E., Central South University, Changsha, ChinaLF, FH, and YM contributed to the conception of the study; performed the experiment; LF and FH contributed significantly to the analysis and manuscript preparation; LF, FH, YM and TJ performed the data analyses and wrote the manuscript. All authors contributed to the article and approved the submitted version.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


Until recently, studies of precarity have overlooked aging and late life. This poster presents a snapshot of conceptual work in progress on a Canadian Social Sciences and Humanities Research Council (SSHRC) Insight Grant on precarity and aging. The poster outlines existing definitions and theoretical perspectives, key results, a current evolving conceptual model, and a working definition of Precarious Aging. It situates existing knowledge and definitions of precarity, highlights crucial intersectional locations of gender, im/migration and (dis)ability, and clarifies the concept of precarity in later life. Results at this point in the study are based on conceptual reviews, reviews of literature on precarity and aging, and the consideration of allied concepts. In conclusion, the concept of precarity offers a promising lens to guide research in the field of social and critical gerontology, providing a foundation for an enhanced understanding of the lives and realities of older people with regards to aging, disadvantage, and inequality.


Risk-taking behaviors of adult bedridden patients in neurosurgery are frequent, however little analyzed. We aimed to estimate from the literature and our clinical experience the incidence of the different clinical pictures. Risk-taking behaviors seem to be more frequent than reported. They are often minor, but they can lead to death, irrespective of the prescription of physical or chemical constraints. We also aimed to contextualize the risks, and to describe the means reducing the consequences for the patients. Two main conditions were identified, the loss of awareness of risk-taking behaviors by the patient, and uncontrolled body motions. Besides, current experience feedback analyses and new non-exclusive technological solutions could limit the complications, while improving prevention with wearable systems, neighborhood sensors, or room monitoring and service robots. Further research is mandatory to develop efficient and reliable systems avoiding complications and saving lives. Ethical and legal issues must also be accounted for, notably concerning the privacy of patients and caregivers. Agitated, confused, and also moderately disabled in-hospital patients can injure themselves, even if they are bedridden. Indeed, as soon as a patient cannot manage wide-amplitude movements, purposeful or not, and either during motion or control of body stability, of the head, the trunk, and limbs, there is a risk of injury and even death. In neurosurgery, a large population of patients is potentially concerned because of the large typology of diseases such as traumas, tumors, strokes, neuralgia, and functional disorders. The risks are all the more important and frequent as the population accessing the care increases inevitably as patients get older and are more vulnerable and frail, whatever the causes. As a result, the number of neurological diseases increases regardless of the symptoms at admission. This in turn affects the risk of developing neuropsychological disorders during primary care.. The magnitude of the risk, however, should be limited  the loss of awareness of risk-taking behaviors by the patient, and (ii) uncontrolled body motions. The loss of awareness of risk-taking behaviors is typically observed with confused patients or patients suffering from disorders of consciousness. Loss of consciousness is a common feature, at least partially, of the self and the environment, without coma, that leads to a confusion fluctuating state with a dream-like experience. The anosognosia, or the loss of awareness of deficit, can be associated with confusion. Hence the clinical pictures can be very different and complex, all the more, when the patients are agitated. This condition of loss of awareness of risk-behaviors is caused or worsened by a lot of acquired and preexisting pathologies, such as pain, mood fluctuations, biologic disorders, neuropsychiatric disease, or sequelae of head injury. Uncontrolled body motions can also lead to risk-taking behaviors. Of course, this is always the case for loss of awareness risk-taking behaviors, but also for conscious patients who move their body, head, trunk, and limbs where the motion is not controlled, whether by clumsiness, or because of restraining systems or any kind of obstacle , or due to neuro-orthopedic troubles. In neurosurgery, a particular condition is the cranial traction of a patient with instable cervical fractures, where hazardous mobilization, whatever the cause, can be dramatic.There are different ways to anticipate and to monitor risk-taking behaviors of bedridden patients, in general, and notably in neurosurgery. The challenge is ambitious and should include all the actors from the ground to the decision-makers and biomedical companies.Everyone has the right to respect for his private life.” However, the patient can sign an authorization allowing the hospital to film or take a picture for a purpose that must be determined. Indeed it should be noted that to be operational and enforceable, the authorization must define the terms of dissemination of the image with regard to duration, medium, and geographic area. For research and future medical monitoring aiming to protect patients, such as those bedridden with risk-taking behaviors, filming should become legal provided that the patient or the representative has been able to consent to the use of a device. The images should of course not be used for any purpose other than prevention of risks and will therefore only be used by the healthcare and medical team in charge of the patient in strict compliance with the General Data Protection Regulation (The prevention relies on the awareness of such behaviors, and the deep analysis of the conditions that can generate them, as from the level of care teams. There are different ways to optimize the risk in the context of risk-taking behaviors of bedridden patients, for instance, following an International Organization for Standardization risk approach, by reducing the likelihood of falls, reducing the consequences of such falls, losing the minimum of benefits for the well-being of a patient, and preventing the introduction of new risks because of the treatment of the first one. The aim is to minimize and optimize all elements, from those which can be seen as insignificant such as clearing the bed and its surroundings of all unnecessary objects and checking the efficiency of the alarm systems, to more evident parameters such as optimal pain treatments, optimization of sedative drugs and restraints systems, and appropriate organized schedules of visits, either nurses or relatives. These elements can be improved directly in the frame of experience feedback forms  and withgulation . Neverthgulation , 32. To gulation –35. Thergulation , to imprgulation .estimate that monitoring could also be useful to assess the impact and efficacy of physical and chemical restraints, like for any treatments (There is no doubt that the monitoring of risk-taking behaviors of bedridden patients will emerge in the very near future, enabling health care providers to save lives and avoid severe complications. In the meantime, besides the technical issues, ethical and legal concerns must be solved, according to each country. It is also reasonable to eatments , 38, andeatments . Legal, eatments .J-JL, RC, and FB: conceptualization. J-JL, FB, RC, M-AC, AS, JC, KA, and LM: writing—original draft. CD, MS, CM, SR, AU, BP, and YE: writing—substantial review and corrections. J-JL and FB: supervision. All authors have read and agreed to the submission of the manuscript.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


Purpose: To analyze how individual characteristics and the social context are associated with mental distress symptoms in the Brazilian population.Method: A multilevel cross-sectional study with data from the 2013 National Health Survey. There were two dependent variables: (a) decreased vital energy and somatic symptoms, (b) the presence of depressive thoughts. The independent variables were biological characteristics, education and income, habits and lifestyle, and context variables. Bivariate analysis was performed, and Prevalence Ratios calculated in a Poisson Regression (95% CI). A multilevel Poisson Regression was performed to verify the effect of individual and contextual variables.Results: Regarding depressive thoughts, young and middle-aged individuals, low education, women, absence of partner, smokers or former smokers, and absence of health insurance were the categories at highest risk; belonging to classes D-E and living in states with lower expected years of schooling proved to be protective factors. Similar results were found for the second outcome.Conclusions: Symptoms of mental distress were associated with the individual characteristics and contextual aspects of the federation unit. These findings indicate the importance of strengthening psychosocial care aimed at vulnerable groups. Characterized by depressive symptoms, anxiety state, and a set of non-specific somatic complaints , in the period from 2005 to 2015 there was an increase of 18.4% in the number of people with depression, and the prevalence of this health condition in Brazil is 5.8%, being the highest rate of Latin America. Regarding anxiety disorder, the worldwide prevalence is 3.6% and Brazil has the highest number of cases among all countries in the world, affecting 9.3% of the population  are characterized by depressive symptoms, states of anxiety, irritability, fatigue, insomnia, memory and concentration problems, and somatic complaints , is part of the Unified Health System (SUS), is an articulated and effective network that assists different levels of health care, qualified to meet people in distress or presenting demands arising from mental disorders or chemical dependence. It works based on a territorial perspective, with emphasis on community-based services aimed at meeting the needs of users and their families, highlighting care centered on people's needs Brasil, .In 2013, in order to monitor these themes, Brazil conducted the National Health Survey (NHS) with a national scope and at domestic level, which aims to produce data about the health situation and lifestyles of the Brazilian population in the country. The NHS was conducted in partnership with the Brazilian Institute of Geography and Statistics (IBGE) and the Ministry of Health of Brazil, and estimated that 7.6% of people aged 18 or older had been diagnosed with depression by mental health professionals, accounting for 11.2 million of people  database of Brazil of the year 2013. This nationwide research was conducted to know and characterize through a household-based survey the Brazilian population profile in terms of the health situation, lifestyle, surveillance of chronic diseases, risk factors, access, and use of health services. The NHS uses an instrument designed specifically for the survey, consisting of three questionnaires: the household, the one related to all household residents, and the individual. All methodological details of the NHS are described elsewhere  and on the nomenclature of symptom classes described in the Self-Reporting Questionnaire (SRQ-20), already validated in several countries .The “Brazil Criteria for Economic Classification” is based on the possession of goods, such as a car, computer, refrigerator, TV, washing machine, DVD player, microwave, motorcycle, and cell phone. There is also a bathroom, a maid, and the head of the family's educational level. Each item has different weights, and the variable represents the family's purchasing power. The score is defined between 0 and 100 points and divided into five classes  in which class A represents the highest socioeconomic level while class E the lowest level.This set of variables ensures the inclusion of individual characteristics, lifestyle, and socioeconomic conditions.For the contextual level, socioeconomic variables that can influence self-perceived health were selected. The variables included were Gini index, Human Development Index (HDI) and expected years of schooling for individuals over 18 years old related to the Federation Units.p ≤ 0.20) were inserted in the multivariate model. In the first step, the contextual effect was evaluated based on a null model using the likelihood ratio test to verify significance. Two models were then tested, the first one with the individual level only, and the final model with the individual and contextual levels, with variables that remained significant in the model. Analyses were performed using the Stata 13 statistical software.Prevalence rates were presented in absolute and relative values in each category, and the effect was estimated through Prevalence Ratios (PR) and their respective confidence intervals (95% CI). Variables with significant associations in bivariate analyses  and the Gini index were not associated with the studied outcomes. It was thus demonstrated that these context variables have little explanatory power over the prevalence of mental suffering in the Brazilian population.One of the limitations of this study has to do with the response bias, since the theme is surrounded by ethical, moral and cultural issues, and these factors strongly influence the responses of people. There may have been omission of information on mental distress when individuals were questioned directly, out of fear or embarrassment of exposure. However, population surveys provide us with representative samples of the population from all regions of the country and can serve to compare these results with those of other countries, as well as support the organization of public policies aimed at minimizing the problem. The prevention of these events represents a major challenge because of the need for the response to articulate different areas, requiring interdisciplinary action, as well as the involvement of various sectors of civil society and governmental organizations.Recognizing the magnitude of common mental disorders in Brazil through population-based researches and a methodology that takes into account each individual's context is invaluable for assessment and planning of the health system, contributing to the advancement of knowledge and improvements in health care policies.The present study reveals that symptoms of mental distress were mainly associated with individual characteristics such as young and middle-aged adults, women, low education, absence of partner, smoking habit, and absence of health insurance. Belonging to income classes D and E and living in states with lower expected years of schooling proved to be protective factors for the outcome variable “depressive thoughts.” Context variables lost their significance after the final multilevel analysis model.The present findings indicate the importance of strengthening the health care network, especially in psychosocial care services aimed at the most vulnerable groups, and thus develop preventive strategies for these groups in order to reduce the incidence rates of mental illnesses. Therefore, the present research is of fundamental importance for the area of collective public health because it stimulates a reflection on mental health policies in Brazil, influencing their re-evaluation and restructuring. It is necessary that further studies be developed on this theme in Brazil and in other countries in order to seek innovations and other relevant findings in this area.The original contributions presented in the study are included in the article, further inquiries can be directed to the corresponding authors.HSB and RMA contributed to the conceptualization, data curation, formal analysis, and methodology. IRB contributed to the conceptualization, data curation, formal analysis, methodology, supervision, and validation. TAS and AAM contributed to the data curation, formal analysis, and methodology. All authors contributed to the writing and final approval of the manuscript.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Alexander Gaskov, Prof., Dr. Sci., 1944–2021.Professor Alexander Gaskov, our dear colleague, friend and teacher, passed away on 18 January 2021, from COVID-19. He was a brilliant scientist in the area of chemistry of semiconductor materials for physical and chemical sensors. He spent his entire research career, which began in 1966, in the Division of Inorganic Chemistry of the Department of Chemistry, Moscow State University. During all his career, he kept generating new ideas, seeking new directions in research and the application of results in practice. He generously shared his knowledge with students and staff, resulting in the emergence of dozens of talented new researchers. The publications produced by the laboratory achieved international recognition. Alexander Gaskov is an Eastern Siberia-born scientist. While at school, he showed an aptitude for physics and chemistry. He graduated from high school with a gold medal. In 1961, as the winner of the School Chemistry Olympiad, he was awarded a grant for a trip to Moscow, which he used to enter the Moscow State University (MSU). The entire life of Prof. Alexander Gaskov was inextricably linked to the MSU, at which he has passed all the ranks from a Junior Researcher to the Chief Researcher and Professor of the Moscow State University. In 1966, he was awarded a Ph.D. in Chemistry. The beginning of his research activity was devoted to the development of materials for IR photodetectors and emitters based on single crystals and epitaxial heterostructures of lead and tin chalcogenides. In 1988, he successfully defended the thesis “Directed synthesis of three-component solid solutions of lead and tin chalcogenides for optoelectronics” and was awarded the Advanced Doctoral Degree in Chemistry, which is the highest academic award of the USSR/Russia. In 1993, he received the title of Professor in Inorganic Chemistry. In 2008, Prof. Gaskov was appointed to lead the newly established Laboratory of Chemistry and Physics of Semiconductor and Sensor Materials.In the 1990s, Prof. Gaskov began exploring a new area of research of the synthesis of nanocrystalline semiconductors with high gas sensitivity. Comprehensive experimental studies of the wide-band semiconductor metal oxides allowed determining an innovative strategy for a direct synthesis of nanocrystalline materials for the chemical gas sensors [Later on, the focus of research in the laboratory was placed on active centers located on the surface of nanocrystalline semiconductor oxides ,3,4. ThiResearch of Alexander Gaskov’s lab in the field of nanocrystalline semiconductors, in addition to oxide materials, involved the binary compounds based on chalcogenides, the so-called quantum dots . These mIn the past decade, Prof. Gaskov’s laboratory has been exploring the issues of reliability, stability and power-consumption of semiconductor gas sensors, which are crucial for the successful functioning of sensors in real operational conditions. These areas include the development of synthesis methods that allowed producing the highly dispersed materials in high-temperature processing conditions, as well as the creation of sensitized and hybrid materials with photo-and gas sensitivity for the light-activated gas sensors . The useAlthough Prof. Gaskov was a strong proponent of fundamental science, he always sought ways of practical implementation of the experimental results. The highly sensitive selective semiconductor sensors created in his lab are the key elements of the Foxy-lab gas analyzer specially designed for detecting highly toxic organophosphorus substances as well as for automatic continuous determination of rocket fuel components. These gas analyzers were installed at Baikonur and Vostochny cosmodromes in 2016 and remain operational.Alexander Gaskov was a genuine scientist, passionate about his work, with a vision of the global picture, but very strict regarding the accuracy of details. In this vein, he taught his graduate students and this he demanded from colleagues. His enthusiasm and passion for results influenced the people around him, making them achieve and accomplish. As a professor of the MSU, he trained dozens of graduates and post-graduates who opted for specialization in inorganic chemistry, solid state chemistry, and materials science. In recent years, he lectured on the fundamentals of the chemistry of semiconductors, principles of inorganic synthesis, and chemistry of new materials. He was also the organizer and head of the interfaculty course “Functional materials of the XXI century”. Under his supervision, 23 Ph.D. graduates successfully completed their studies. He provided guidance for the two dissertations of the Advanced Doctoral Degree in Chemistry.Alexander Gaskov was a member of the Academic Council of the Chemistry Department and a member of the Dissertation Council for Chemical Sciences of Moscow State University. In 2009, he was awarded the title of the “Distinguished Researcher of Moscow University”, and 2020, the title of the “Honorary Worker of Science and High Technologies of the Russian Federation” from the Ministry of Science and Higher Education of Russia.Above all, Alexander Gaskov loved life, his work, his laboratory, and his family. In the “sensor community”, he will be remembered as a genuine scientist who made an important contribution to the understanding of the chemical foundations of the nature of semiconductor materials. By his colleagues, he will be remembered as a leader, teacher and a dear friend. With sadness for our common loss, but with vivid memories and gratitude for Alexander’s precious time lived with us, we will continue our work, bringing his ideas and plans further.


Resilience is usually defined as one's ability to “bounce back” from adversity and is a salient indicator of the quality of life and psychosocial functions of patients facing chronic diseases, for instance, cancer, hypertension, irritable bowel syndrome, and heart failure, etc. , 2. ThusResilience in Chronic Disease received a great response. The collection consists of 12 studies with a total of over 7,100 participants from different countries. A diversified array of populations including the general population in the COVID-19 pandemic , patients with chronic pain , cancer , irritable bowel disease , cardiovascular disease , neurocognitive disorders , renal transplant , and rheumatoid arthritis , as well as caregivers for children with chronic illness , patients with liver cancer , and maintenance hemodialysis , were examined. Findings derived from the current collection echo the existing positive-psychology literature emphasizing the importance of psychological and social resilience in the move forward with chronic disease. Scientists from multi disciplines have contributed to this collection, providing contributions that raise awareness, educate, and reduce the impact of different chronic diseases on patients and their caregivers. However, several limitations should be emphasized here. First, most articles used observational designs , describing resilience and its associations with other aspects of the psychological, social, and physical well-being of patients with chronic disease. Our specific aim was first, to recognize distinct resilience trajectories during diagnosis, treatment, and survivorship throughout the course of chronic disease, which was not achieved in the current collection , the Humanity and Social Science Youth Foundation of the Ministry of Education of China (No. 19YJCZH227), the Humanity and Social Science Foundation of Department of Education of Guangdong Province (No. 2020WTSCX009), the Humanity and Social Science Foundation of Guangzhou (No. 2021GZGJ57), and the Humanity and Social Science Foundation of Guangzhou University of Chinese Medicine (Nos. 2020SKXK01 and 2021SKYB07).The author declares that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


The accurate identification of urban functional areas is of great significance for optimizing urban spatial structure, rationally allocating spatial elements, and promoting the sustainable development of the city. This paper proposes a method to precisely identify urban functional areas by coupling Open Street Map (OSM) and Point of Interest (POI) data. It takes the central urban area of Hangzhou as a case study to analyze the spatial distribution characteristics of the functional areas. The results show that: (1) The central urban areas of Hangzhou are divided into 21 functional areas . (2) The single functional areas and the mixed functional areas show the geographical distribution characteristics of the looping stratification, which means “Core-periphery” differentiation is obvious, and the comprehensive functional area is relatively scattered. (3) The mixed degree of regional function with ecological function and production function is low while comprehensive functional areas are usually associated with higher potential and vitality. (4) The identification results are in great agreement with the actual situation of Hangzhou central urban area, and the method is feasible. Therefore, this paper can provide a reference for urban development planning and management. The functional area is the basic unit of urban planning, management and resource allocation. Urban functional areas are important geospatial attributes of urban land, in which people carry out various socio-economic activities, which are usually determined by two perspectives of land use type and human activities, including residential land, industrial land, commercial and business facilities land , 2, 7. AThe traditional urban function zoning is mainly based on remote sensing images, land use data, panel data and so on . Zhong eCompared with the above studies, the POI data is a kind of point-shaped geographic space big data of real geographic entities. The results of this research could finely characterize the dynamic and real-time nature of urban land functions, and reflect the diversity and mixed degree of various facilities , 23. ZhaTherefore, this paper takes Open Street Map (OSM) road network data and POI data as the main data source, and proposes a method for accurate identification of urban functional areas based on kernel density estimation, functional area identification, mixed degree calculation and other technical means. Taking the main urban area of Hangzhou as a case, this paper further identifies urban single functional land, mixed and comprehensive functional land, and analyzes the distribution characteristics of the functional structure in the research area. The improvements of this study are shown as follows: 1) Taking the irregular grid formed by the road network as the research unit, the segmentation of urban functional areas is more reasonable. 2) The kernel density method reduces the noise effect of POI data, improves the recognition accuracy of mixed functional areas and weakens the discretization of results. 3) The recognition model considers the mixed functional areas and comprehensive functional areas to make the results more in line with the real situation. 4) The mixed degree calculation and accuracy verification of the identification results of urban functional areas are conducted to make the results more convincing. In terms of literature, it is expected to provide a typical case and research methods for the research of urban spatial structure in China driven by spatial big data. In practice, it provides the reference for urban managers to understand the urban spatial structure, accurately grasp the development status of urban functions, and formulate reasonable urban planning schemes.2. It is and one of the central cities in the Yangtze River Delta. In 2019, the city’s GDP reached 222.85 billion US dollars, with a permanent population of 10.36 million. The central urban areas are located in the northeast of Hangzhou, including Xihu District, Gongshu District, Shangcheng District, Binjiang District, Jianggan District, and Xiacheng District, with a total area of 706.27km2. The central urban areas are concentrated areas of business, population and services in Hangzhou. The urbanization process of Hangzhou is the epitome of China’s rapid development. At the same time, the urban development mode of Hangzhou, which takes into account science and technology, industry, humanities and ecology, represents the development direction of the future city. Moreover, the rapid change of urban functions of such cities brings challenges to urban management and operation. Therefore, this area is selected as the research area. An overview of the research area is shown in Hangzhou, the capital city of Zhejiang Province, is located in the northern part of Zhejiang Province, the lower reaches of the Qiantang River, and the southern end of the Beijing-Hangzhou Grand Canal. The central geographical coordinates are E120°19’, N30°26’. The city governs 10 districts, 2 counties and 1 county-level city, with a total area of 16853.57kmhttp://www.ngcc.cn/ngcc/html/1//391/392/16114.html), the satellite map data comes from Auto Navi Map (https://www.amap.com/), and they all can be obtained free of charge. The urban road network data of Hangzhou comes from the Open Street Map (OSM) geographic data platform (https://www.openstreetmap.org/). OSM aims to provide users with free and easy-to-access digital map resources, which is currently the most popular spontaneous geographic information platform. We preprocessed the collected OSM road network data: select highways, railways, township main roads, urban main roads and roads, delete sidewalks, residential lanes, chaotic road network and other lines which are less important and do not affect the analysis results, delete duplicate lines. Filter to delete other redundant paths and broken paths and paths below 100 meters, and finally, fill the broken paths. POI (Point of Interest) data comes from AutoNavi Maps Open Platform (https://lbs.amap.com/). AutoNavi Maps is China’s leading provider of digital map content, navigation, and location services. This research uses the open API interface provided by AutoNavi Maps to obtain 168607 POI data of six districts in Hangzhou in December 2020, and each POI data contains attribute information such as geographical entity name, address, affiliation type, longitude, and latitude, administrative region and so on. There are many problems in the original POI data, such as various classifications, the repeated crossover between different classifications, classification errors, information missing, and inconsistent coordinate system. Moreover, some types of POI have low public awareness, such as public toilets, newspaper pavilions, and bus stations. These types of POI are not significant in the identification of functional areas and are not convenient for research and discussion. Therefore, it is necessary to unify the coordinate of POI data, clean the data, delete wrong POI points, delete repeated abnormal values, screen and delete low public awareness points, and reclassify them. According to the "Code for classification of urban land use and planning standards of development land" (GB_50137–2011) and combined with the actual conditions of Hangzhou, we divided POI into six types: residential, administration and public services, commercial and business facilities, industrial, green space, science and education [Before collecting the open source data required for the article, we have carefully examined all relevant platform service terms to ensure that our research is fully compliant with the agreement. The administrative division data is from the 1:250,000 basic geographic database provided the National Geomatics Center of China , n is the number of research objects j within the bandwidth R.In the formula, r is the bandwidth, SD is the standard distance value, Dm is the median of the distance between the average center of the point and all points, n is the number of points, xi and yi are the coordinates of points, respectively, and The result shows that the choice of bandwidth R has a critical impact on the result of kernel density analysis , 32. GenThe above formula is used for calculation in GIS to obtain the search radius of POI data of various functional areas. Among them, the residential area is 1095 m, the administration and public services area is 1102 m, the commercial and business facilities area is 745 m, the industrial area is 970 m, the green space is 1224 m, the science and education area is 1013 m, and the overall search radius of POI data is 837 m. Hinnerburg et al. researched the relationship between the bandwidth and the number of density-attractor and found that there are a certain number of bandwidth intervals that keep the density-attractor stable, and it is reasonable to choose the bandwidth in these intervals . Based oIt is not only the distribution density of POI but also the size of geographical objects represented by POI and the degree of public recognition to affect the function of the plot. In this paper, the occupied area of POI points is selected as one of the weights , and theFi, di, and Wi are the frequency density, sum of nuclear density, weight of the POI of class I in the unit, respectively. Due to the complex and diverse urban functional structure, there are both single-use functional areas and areas with two or more mixed functions. Therefore, this paper further compares the frequency density of POI in the functional area: When the frequency density of POI in the unit is more than or equal to 50%, the functional area is a single function area. When the two kinds of values of higher frequency density of POI in the unit are between 20% and 50%, the unit is defined as a mixed functional area with two types of POI. When the frequency density of all kinds of POI in the unit is 0, it is defined as no data area, and the rest of the unit is the comprehensive functional area.According to the weight calculation of each POI, the frequency density of each POI in the land use unit is calculated, which can be used as the basis of functional zoning . The calpi is the proportion of class I POI kernel density value to the total value of each class of POI kernel density in the functional area unit, and n is the number of POI classes. If the kernel density of some POI in the unit is 0, it does not participate in the calculation.According to the mixed index of land use, the mixed degree of functional areas in the research area is further evaluated . The for2), residential land , administration and public services land , green space land , industrial land , science and education land . The mixed functional areas include the combination of commercial and business facilities land, and administration and public services land , the combination of commercial and business facilities land, and residential land , the combination of commercial and business facilities land, science and education land , the combination of commercial and industrial facilities land , the combination of commercial and business facilities land, and green space land, the combination of administration and public services land, and residential land , the combination of administration and public services and green space land , the combination of administration and public services and industrial land , the combination of administration and public services land, and science and education land , the combination of industrial and residential land , the combination of residential and green space land , the combination of science and education, and residential land , the combination of science and education, and industrial land , the combination of science and education, and green space land . There are 103 comprehensive functional areas, covering an area of 39.801km2. The remaining units are no data areas . Because of the small statistics of various POIs in this block, the kernel density value is small too.Through OSM network grading and buffer operation, the central urban area of Hangzhou is divided into 1542 block units. After calculating the weight and frequency density of various POI in each block unit, the identification result of functional areas in the Hangzhou central district is obtained . It can The single functional areas in the central urban area of Hangzhou are mainly commercial and business facilities land and residential land . Among t2, accounting for 55% of the total area of the research area, which indicates that the mixed degree of urban functions in the downtown area of Hangzhou is relatively high. Mixed functional areas are mainly the combination of commercial and business facilities land and administration and public services land, which occupy the largest area, accounting for 25% of the total research area. In terms of spatial distribution, the central part is more and concentrated, while the periphery is less and scattered. Specifically, they are primarily concentrated in Shangcheng District and Xiacheng District, the south of Gongshu District, the east and west of the Xihu District, and the west of Jianggan District. Next is the combination of commercial and business facilities land and residential land, accounting for 14% of the total research area, intersperses in various functional areas. The number of other mixed functional areas is 223, accounting for 14% of the total area of the research area, and the area of other mixed functional areas accounted for 16% of the total area of the research area. The layout of other mixed functional areas is more dispersed. Among them, the number of the combination of residential and green space land and the combination of science and education and the industry land are the least, with 1 each. The area of the combination of industrial and residential land is the smallest, accounting for only 0.04% of the total area of the research area. The overall layout of the comprehensive functional urban areas in the central city area of Hangzhou is scattered , making research in this field not detailed enough. With the development and popularization of computer technology, remote sensing technology and big data are applied in the research of urban functional area recognition, but there are still problems such as tedious classification methods and the result precision cannot be guaranteed. Based on the kernel density estimation algorithm, this paper proposes an urban functional area identification method that combines OSM and POI data. It has a high reference value for the analysis of urban overall patterns and spatial optimization. At the same time, the availability of OSM and POI data makes this method can be easily used in other cities.Firstly, POI data can provide a spatial location and attribute information of various urban facilities. Real-time and efficient data acquisition methods simplify the cost and uncertainty of traditional identification methods such as remote sensing, field research and questionnaire survey. The application of big data breaks through the problems of poor timeliness and a small sample of traditional data, improves the accuracy of urban functional area identification, and is convenient for larger-scale research.Then, the OSM road network is used to generate road space, and the research area is divided into independent block units so that the segmentation of urban functional areas is more reasonable. The kernel density estimation method is used to realize the influence diffusion of POI in the adjacent location, weaken the discrete phenomenon of POI points, and identify the functional areas through the optimal bandwidth selection. The results are basically consistent with the actual situation. Through the calculation of the mixed index of urban functional areas, it is convenient to express the mixed degree of land use in the central urban area of Hangzhou. Although in the process of urban planning and construction, urban land use layout planning emphasizes functional zoning, mixed land use planning should also be adhered to promote economic development and facilitate the lives of residents.Finally, compare the identified functional areas with the image of AMap, the verification of the results shows that the method has a high degree of recognition for urban functional areas, which can make up for the disadvantages of the traditional method and has certain feasibility. It can support the spatial layout research of urban functional areas, so that the decision-making organs can find the shortcomings of the existing urban planning, and can coordinate the development direction of the existing planning functional areas, improve the vitality of urban space, and carry more human activities.However, this method also has some shortcomings. For example, the verification of the results is only carried out through the comparison of typical regions, and there is no true value as a comparison. Therefore, it is hard to determine the accurate identification accuracy of this method. In addition, this method is based on the OSM road network to divide urban units, and the basic road network data have the problems of low density and the lack of data in suburban and rural areas, which leads to the excessive division of functional units in such areas, resulting in poor local recognition results.The urban functional area projects each element of the city in space and forms a closely related organism. The identification of Hangzhou urban functional areas based on big data is not only beneficial to the adjustment of urban spatial layout and the creation of good conditions for the development of urban economy and society but also can improve the efficiency of urban land use  through On the whole, the single functional areas are mainly distributed in the periphery of the city. For example, the single residential areas are mainly distributed in the north and south of West Lake District, the east of Jianggan District, and the southern edge of the Binjiang District. The single industrial areas are mainly distributed in the eastern part of the Jianggan District and the southern part of the Xihu District. The single areas for science and education are mainly distributed in the northern part of the main urban area of Hangzhou. In general, the more single functional land, the more it affects the mobility of the city . For exaThe mixed functional areas are distributed in the whole research area and nested with single functional areas, which indicates the rationality of the spatial structure of the main urban area of Hangzhou. For example, residential land forms residential-industrial zones around enterprises, commercial-residential lands around businesses, and public service-residential lands around public services. From the perspective of different administrative regions, each administrative region has an area with a higher degree of mixed, as well as an area with a lower degree of mixed. In line with the law of urban growth and development in urban areas, it revolves around multiple economic activity centers , 47. HowThe comprehensive functional area means that there are three or more urban functions in the plot, reflecting the organic integration of different urban functions. For example, the southernmost comprehensive functional area of Binjiang District is the location of China Network Writers’ Village and the core for the development of China’s network literature industry. Meanwhile, the high-quality environment and supporting facilities attract more writers. Similarly, in the easternmost comprehensive functional area of Jianggan District, there are enterprise platforms with functions of scientific research and industrial incubation, such as ABO Biopharmaceuticals (Hangzhou) Co., Ltd., Sanhua Academia Sinica, as well as high-grade residential areas, the supporting facilities are relatively complete. These regions are very typical innovation areas in Hangzhou, and the mixing of functions is also the most prominent feature of high-quality urban innovation space , 51.In the research area, the mixed degree of some areas is deliberately controlled, mainly in the areas that undertake ecological functions, such as the Qiantang River, Xixi Wetland, West Lake Scenic Area, and the areas that undertake production functions, such as Zhejiang Qiosi Farm in Jianggan District. This is because the strategy of ecological civilization and the protection of cultivated land both are China’s basic state policies , which rThe rapid evolution of cities and the promotion of China’s urbanization policy have brought many new challenges to urban planning and management. The spatial division of urban functional areas and urban zoning management of the city could provide a new idea for planners and managers to a certain extent. The government could plan different functional areas of the city according to the social, economic and natural geographical conditions, and realize the change from the traditional " unitary and extensive " management mode to the modern " diversified and refined " management mode , 54.Based on the above analysis of the comprehensive judgment of the current situation, we believe that the current urban functions of the central city area of Hangzhou are becoming diversified and individualized. However, with the continuous evolution of urban spatial structure, there are many potential problems . First oTherefore, in the future, the urban land use function of the central urban area of Hangzhou should be optimized from the following aspects: (1) Developing mixed-use areas based on actual needs, guiding the optimization of urban mixed areas to improve the efficiency of land use. (2) Reducing single-use land types and promoting the transition from single-use land to mixed-use land. (3) Adhering to the construction of the multi-center distribution pattern of urban spatial structure and promote the fair distribution of social-spatial elements . (4) WhiThis article takes the central urban area of Hangzhou as the research area and proposes a method of city functional area identification based on the kernel density estimation algorithm that integrates OSM road network and POI data: Firstly, the OSM network divides the urban area into research units with the same social and economic functions. The influence diffusion of POI facilities is realized based on the kernel density estimation algorithm, which weakens the discretization of POI. At the same time, kernel density bandwidth and POI weight are set to identify the functional urban areas and projected to different plots. Finally, the land-use mixed index is calculated. The results show that: (1) There are three types of urban functions in the central urban area of Hangzhou: single, mixed, and comprehensive. The central urban areas of Hangzhou are divided into 21 functional areas and the commercial function land is the dominant function of the research area. (2) The single functional areas and the mixed functional areas show the geographical distribution characteristics of the looping stratification, which means the “Core-periphery” differentiation is obvious. Mixed functional areas are widely distributed, but the areas with ecological and production functions have a low degree of mixed. Comprehensive functional areas are widely distributed and with higher potential and vitality. (3) The results of identification are in good consistent with the actual situation of the central urban area of Hangzhou. Therefore, the kernel density weighting method which considered public awareness and general area has high accuracy and feasibility, which can provide a reference for urban development planning and management. (4) The real-time and high efficiency of OSM and POI data acquisition methods and the scientific accuracy of big data application make the method of identifying urban functional area which combined OSM and POI data available. This method can be easily used in the identification of other urban regional functional areas to help people to understand the urban spatial structure more intuitively. And this method has high potential in assisting government departments and researchers in the scientific analysis of urban planning and land use.There are some deficiencies of this paper: Because of the data defect of POI, the identification ability of areas such as small building density, unused land in cities and farmland is weak. At the same time, the integrity of POI data, the rationality of data cleaning and the accuracy of reclassification need further research. In view of the defects of the results test in research methods, a variety of verification methods can be added to future research for a horizontal comparison of results. Finally, due to the lack of historical POI, the evolution characteristics of urban functional areas cannot be identified. So combining mobile signaling data, sharing vehicle (bicycle) data, social media big data and other multi-source data to analyze the evolutionary logic and driving mechanism of urban functional areas will be the direction of future research.


In the original publication, the name of the fourth author should be: Takafumi Sangai and his affiliation should be:Department of Breast and Thyroid Surgery, Chiba University Hospital, Chiba, JapanThe corrected name and affiliation are given in this correction.


In Japan, there are key healthcare professionals for home nursing care for elderly people called Care Managers. The care manager coordinates the service while adjusting the family situation and the user's intentions. The purpose of this study was to examine the practical structure of support for adjusting the intentions of family members and users regarding care service use. Data from seven cases, where family members and users have different intentions regarding care service use, were analyzed using the grounded theory approach. The phenomenon of "confirmation of discrepancies" was discovered with six sub-categories: adjusting the intentions of users and their families, effort to restore relationships, expression of intention to refuse involvement, expression of desire for adjustment, arrangement of opportunities for adjustment of intentions, and appropriate service adjustment. Four patterns occurred in the process of "confirmation of discrepancies": smooth adjustment, restoration and promotion of mutual relationships, failure to reach an agreement, and negative feedback loops. These patterns were based on a combination of the care managers' degree of understanding strength, the managers' degree of insistence, the managers' degree of representation of mutual feelings, the degree of managers' prediction of life prospects, the degree of trust in care managers, and the degree of expression of family anxiety.