ABSTRACT
The Covid-19 pandemic ushered in multiple paradigms of personal health data sharing with particular emphasis on Person-to-Institution sharing and Institution-to-Institution sharing. While the data aggregated by technology companies and health authorities was instrumental in the development of vaccines and ultimately flattening the curve of infection rates, egregious abuses of privacy occurred. In many instances acceptable guarantees of appropriate utility for the data were not made available. Personal health data sharing for the containment of infections with privacy limitations present a classic case of collaboration among mutually distrustful entities. In this regard the blockchain network and attendant protocols for data integrity, transaction transmission and provenance can prove useful. Thus, in this paper we present a blockchain-based method for disease surveillance in a smart environment where smart contracts are deployed to monitor public locations instead of individuals. The data aggregated is analysed and tagged with a lifetime commensurate with the time for infection. Once the data utility period has elapsed the monitored data are removed from the active surveillance pool and the entities involved can be notified. Such a method of continual surveillance protects privacy by shifting the emphasis from individuals to locations. Experimental data suggests this method is efficient and can be implemented on top of existing disease surveillance strategies for later pandemics.
ABSTRACT
To meet the growing demand for sustainable development and ecofriendliness, hydrogels based on biopolymers have attracted widespread attention for developing flexible pressure sensors. Natural globular proteins exhibit great potential for developing biobased pressure sensors owing to their advantages of high water solubility, easy gelation, biocompatibility, and low production cost. However, realizing globular protein hydrogel-based sensors with interfacial and bulk toughness for pressure sensing and use in wearable devices remains a challenge. This study focuses on developing a high-performance flexible pressure sensor based on a biobased protein hydrogel. Consequently, a flexible protein/polyacrylamide (PAM) hydrogel with a featured double-network (DN) structure linked covalently with hydrogen bonds was first synthesized via a one-pot method based on natural ovalbumin (OVA). The unique DN structure of the as-synthesized OVA/PAM hydrogel affords excellent mechanical performance, flexibility, and adhesion properties. The mechanical properties of the DN hydrogel were enhanced after further cross-linking with Fe3+ and treatment with glycerol. Subsequently, the flexible pressure sensor was constructed by sandwiching a microstructured OVA/PAM dielectric layer between two flexible silver nanowire electrodes. The obtained sensor exhibits a high sensitivity of 2.9 kPa-1 and a short response time of 18 ms, ensuring the ability to monitor physiological signals. Based on its excellent performance, the fabricated sensor was used for monitoring the signals obtained using practical applications such as wrist bending, finger knocking, stretching, international Morse code, and pressure distribution. Particularly, we implemented a contactless delivery system using the fabricated OVA-based pressure sensors linked to unmanned vehicles and global positioning systems, providing a solution for low-risk commodity distribution during Coronavirus disease 2019 (COVID-19).
ABSTRACT
The Covid-19 pandemic ushered in multiple paradigms of personal health data sharing with particular emphasis on Person-to-Institution sharing and Institution-toInstitution sharing. While the data aggregated by technology companies and health authorities was instrumental in the development of vaccines and ultimately flattening the curve of infection rates, egregious abuses of privacy occurred. In many instances acceptable guarantees of appropriate utility for the data were not made available. Personal health data sharing for the containment of infections with privacy limitations present a classic case of collaboration among mutually distrustful entities. In this regard the blockchain network and attendant protocols for data integrity, transaction transmission and provenance can prove useful. Thus, in this paper we present a blockchain-based method for disease surveillance in a smart environment where smart contracts are deployed to monitor public locations instead of individuals. The data aggregated is analysed and tagged with a lifetime commensurate with the time for infection. Once the data utility period has elapsed the monitored data are removed from the active surveillance pool and the entities involved can be notified. Such a method of continual surveillance protects privacy by shifting the emphasis from individuals to locations. Experimental data suggests this method is efficient and can be implemented on top of existing disease surveillance strategies for later pandemics. © 2023 IEEE.
ABSTRACT
Two female patients (patient 1, 22-year-old;patient 2, 50-year-old) received IV infusion of ribavirin injection (4 g in the first dose and the next day 1.2 g thrice daily), oral 2 lopinavir and ritonavir tablets twice daily, and aerosol inhalation of recombinant human interferon alpha2b for injection for novel coronavirus pneumonia. There was no obvious abnormality in blood routine and liver function before treatment. Laboratory tests showed red blood cell count (RBC) 2.89x1012/L, hemoglobin (Hb) 75 g/L, alanine aminotransferase (ALT) 22.8 U/L, aspartate aminotransferase (AST) 33.9 U/L, total bilirubin (TBil) 71.2 mumol/L, and indirect bilirubin (IBil) 63.5 mumol/L in patient 1 on the 2nd day of treatment, and RBC 3.46x1012/L, Hb 95 g/L, ALT 17.7 U/L, AST 21.3 U/L, TBil 86.1 mumol/L, and IBil 67.1 mumol/L in patient 2 on the 3rd day of treatment. The direct antiglobulin test was positive, indirect antiglobulin test was negative, and antinuclear antibody test was negative in both patients. They were diagnosed as having acute hemolytic anemia. Con-sidering the relationship to ribavirin, ribavirin was given in reduced dose and then finally discontinued in patient 1, and was discontinued directly in patient 2. On the basis of continued use of the other 2 drugs, both of them were treated with ursodeoxycholic acid. The Hb and bilirubin level of the 2 patients gradually returned to normal.Copyright © 2020 by the Chinese Medical Association.
ABSTRACT
To meet the growing demand for sustainable development and ecofriendliness, hydrogels based on biopolymers have attracted widespread attention for developing flexible pressure sensors. Natural globular proteins exhibit great potential for developing biobased pressure sensors owing to their advantages of high water solubility, easy gelation, biocompatibility, and low production cost. However, realizing globular protein hydrogel-based sensors with interfacial and bulk toughness for pressure sensing and use in wearable devices remains a challenge. This study focuses on developing a high-performance flexible pressure sensor based on a biobased protein hydrogel. Consequently, a flexible protein/polyacrylamide (PAM) hydrogel with a featured double-network (DN) structure linked covalently with hydrogen bonds was first synthesized via a one-pot method based on natural ovalbumin (OVA). The unique DN structure of the as-synthesized OVA/PAM hydrogel affords excellent mechanical performance, flexibility, and adhesion properties. The mechanical properties of the DN hydrogel were enhanced after further cross-linking with Fe3+ and treatment with glycerol. Subsequently, the flexible pressure sensor was constructed by sandwiching a microstructured OVA/PAM dielectric layer between two flexible silver nanowire electrodes. The obtained sensor exhibits a high sensitivity of 2.9 kPa-1 and a short response time of 18 ms, ensuring the ability to monitor physiological signals. Based on its excellent performance, the fabricated sensor was used for monitoring the signals obtained using practical applications such as wrist bending, finger knocking, stretching, international Morse code, and pressure distribution. Particularly, we implemented a contactless delivery system using the fabricated OVA-based pressure sensors linked to unmanned vehicles and global positioning systems, providing a solution for low-risk commodity distribution during Coronavirus disease 2019 (COVID-19). © 2023 American Chemical Society.
ABSTRACT
Health awareness has increased worldwide since the COVID 2019 pandemic, creating a strong demand for wearable electronics. Wearable sensors for monitoring a patient's health are prevalent to reduce medical costs and decrease in-person clinic visits. Integrating electronics into clothes is challenging because most fabrics are porous and incompatible with the existing manufacturing methods, such as screen printing. The indirect printing method was employed to fabricate electrical circuitry on a textile substrate by printing it on a heat transfer polymer (HTP) and attaching it to the target cloths by stitching or glueing. Such a fabrication process has the potential to lead the way in developing new intelligent clothes. However, the durability of the printed circuitry in this manufacturing process on a cloth is still unknown and requires investigation. Therefore, this paper's objective is to study the durability of printed circuitries on fabric by applying constant cyclic loading. The test vehicle is a printed conductive silver interdigitating circuitry on fabric. Another test vehicle on a polyethylene terephthalate (PET) substrate was fabricated for a benchmark. A constant cyclic loading at 1Hz at a 50% duty cycle was applied to the test vehicles 100,000 times. The printed circuitry was monitored by logging the voltage in an electrical voltage divider configuration while the sensor was pressed and released. The result indicates that the fabric test vehicle can still function after the 100,000 cycles of the cyclic loading test and is comparable to that on the PET substrate. The recorded voltage-to-force values of the printed sensor on the fabric drifted upward and downward up to 3% over the loading cycles. The optical microscope observation on the cyclic loading samples showed signs of shear stresses on the printed silver and electrically conductive films, which could cause the tips of the silver interdigitating fingers to shatter. The study indicates that the properly manufactured circuits on fabric can be reliable and utilized for wearable applications. © 2022 IEEE.
ABSTRACT
The Chest X-ray (CXR) images of COVID-19 patients are different from those of normal people, which has been an effective base for making correct diagnosis. It is an important way to help medicine doctors to make the fast and accurate diagnosis for patients by using com puter aided automatic classification technique based on the patient chest X-ray images. The new COVID-SERA-NeXt model was proposed in this paper for classifying COVID-19 CXR images by introducing the cross-stacked channel attention module and residual attention module, as well as the proposed dimensional reduction module, into the ResNeXt model. The performance of the proposed COVID-SERA-NeXt model was tested on the open accessed COVIDx dataset by extensive experiments. The experimental results show that the proposed COVID-SERA-NeXt model is superior to its base model ResNeXt. It achieves the accuracy and Macro_Recall of 96. 11 % and 95. 46%, respectively. Further experiments demonstrate that the proposed COVID-SERA-NeXt model achieves better performance to classify COVID-19 CXR images when it is pre-trained using ChestX-ray8 dataset. © 2022, Taiyuan University of Technology. All rights reserved.
ABSTRACT
Nature has healing powers that provide physical and mental benefits to tourists and reduce their anxiety related to COVID-19. However, few empirical studies have examined the emotional mechanism that induces tourists to feel satisfied with, rather than anxious about, their lives. We explain the underlying impact mechanism that connects nature and subjective well-being in a natural heritage context by analyzing data collected from a sample of 534 tourists in Wulingyuan (south-central China). Our study revealed interesting and meaningful findings: (a) nature has healing powers that directly and indirectly (via awe and place attachment) influence tourists' sub-jective well-being;(b) tourists with a relatively low level of positive emotions who become attached to a destination, subsequently experience a greater degree of healing;and (c) there are significant gender differences concerning the healing powers of nature among tourists. These findings contribute to well-being research by highlighting the underlying emotional mechanism whereby nature influences tourists' subjective well-being. The paper also demonstrates the moderating effects of positive emotions and gender in the proposed model, which offers valuable practical insights for governments in tourist destinations.
ABSTRACT
Using the data of global COVID-19 vaccine development, ordering, donation and vaccination, and through GIS and other technical methods, this paper depicts the development, circulation pattern and their dynamics of global COVID-19 vaccine. In order to provide a cognitive basis, this paper further discusses the spatial and temporal differentiation of global COVID-19 vaccination. The conclusions are as follows: (1) The global development pattern of COVID-19 vaccine is not balanced, with three cores in Western Europe, North America and Asia as a whole. Among them, the United States, China and the UK are the representative countries for the development of COVID-19 vaccine. (2) In the early stage, the global COVID-19 vaccine ordering was mainly distributed among developed countries in Western Europe and North America. Nevertheless, with the continuous expansion of the global ordering network, the ordering of COVID-19 vaccine has gradually expanded to Asian, African and Latin American countries. On the whole, the global COVID-19 vaccine ordering has formed two expansion modes, including directed expansion and non-directed expansion. (3) China and the United States are the two core countries of the global COVID-19 vaccine donation network. The United States mainly donates vaccines to Southeast Asia, South Asia, Latin America and other countries that have close relationship with the United States. China mainly donates vaccines to South Asia, Southeast Asia, West Asia and Africa. The donation of COVID-19 vaccine is mainly affected by the contact and relationship between countries, the national strategies and the need to fulfill international obligations of donor countries, but their focuses are different. (4) The development, ordering and donation pattern of global COVID-19 vaccine determines the evolution of global vaccination pattern. The vaccination process in developed countries in Western Europe and North America is ahead of most Asian, African and Latin American countries, but the gap is gradually narrowing. China's vaccination rate has jumped from a higher to the highest level, making China a representative of developing countries. © 2022, Science Press. All right reserved.
ABSTRACT
This study explored the socioemotional experiences of Wuhan preschool children and their parents, focusing on father-child relationships during lockdown. Mixed methods were employed with semi-structured interviews with 12 families and an online questionnaire involving 748 parents. The results show that the parents were generally positive about the emotional experiences associated with caring for their young children all-day-long, although some parents expressed concerns about their children's educational issues. About 62.9% of fathers and 44.7% of mothers reported an improvement in father-child relationships. Children's gender affected the fathers' views. The rate of positive changes in father-son relationships is significantly higher than in father-daughter relationships. The parents' attitudes influenced children who demonstrated compliant behaviours for meeting the lockdown requirements, yet the children's emotions presented a mixture of positive and negative components. These findings reveal the complexity of family life, which has implications for imposing lockdown policies when addressing future emergencies.
ABSTRACT
Developing emergency drugs in time is key to responding to public health emergencies such as the coronavirus disease 2019 (COVID-19) pandemic. This research constructs patent assignee citation networks based on COVID-19 drug patents and applies technology life cycle analysis and social network analysis to examine these networks. The results reveal the evolution and structure of the emergency drug innovation network and identify innovation entities with different research and development (R&D) capabilities or a foundation for cooperation. This study attempts to provide the basis for theories and policies to accelerate R&D of emergency drugs. The key results are as follows: (1) Technologies of the emergency drug innovation network show fluctuating growth aligned closely with public health emergencies. (2) The network presents a sparse structure with many active factions, whose members have the advantage of cooperating. (3) Three types of innovation entities are identified: the main technology suppliers, potential suppliers of other supporting technologies, and peripheral suppliers of other supporting technologies.
ABSTRACT
The recent coronavirus (COVID-19) pandemic has brought the world to an apocalyptic standstill with huge economic burden and catastrophic healthcare consequences. COVID-19 pandemic has neither clinically proven vaccine nor drugs so far. It is now obvious that the world is in dire need for non-clinical, real-time, faster and cost-effective and secure smart solutions for monitoring, contact tracing, and diagnosing/detecting COVID-19 patients and hence mitigating the burden on healthcare systems. Therefore, Machine learning approaches can be leveraged in all aspects that could impact the patients and the future care guidelines. However, ensuring the data privacy, security and the conformity to data protection regulations will become even more of a challenge. This leads to the requirement for secured and privacy-preserving machine learning mechanisms for COVID-19-based healthcare applications. In this paper, we present a blockchain-based privacy-preserving support vector machine (SVM) classification over vertically partitioned IoMT data for a clinical decision support (CDS) system. The proposed system does not require any intervention or direct interactions between data owners. Both local training and building the global classification model run on verifiable and private smart contracts rather than relying on untrusted third parties. We find that the proposed system is more secure and efficient. © 2021 ACM.
ABSTRACT
Two female patients (patient 1, 22-year-old;patient 2, 50-year-old) received IV infusion of ribavirin injection (4 g in the first dose and the next day 1.2 g thrice daily), oral 2 lopinavir and ritonavir tablets twice daily, and aerosol inhalation of recombinant human interferon α2b for injection for novel coronavirus pneumonia. There was no obvious abnormality in blood routine and liver function before treatment. Laboratory tests showed red blood cell count (RBC) 2.89×1012/L, hemoglobin (Hb) 75 g/L, alanine aminotransferase (ALT) 22.8 U/L, aspartate aminotransferase (AST) 33.9 U/L, total bilirubin (TBil) 71.2 μmol/L, and indirect bilirubin (IBil) 63.5 μmol/L in patient 1 on the 2nd day of treatment, and RBC 3.46×1012/L, Hb 95 g/L, ALT 17.7 U/L, AST 21.3 U/L, TBil 86.1 μmol/L, and IBil 67.1 μmol/L in patient 2 on the 3rd day of treatment. The direct antiglobulin test was positive, indirect antiglobulin test was negative, and antinuclear antibody test was negative in both patients. They were diagnosed as having acute hemolytic anemia. Con-sidering the relationship to ribavirin, ribavirin was given in reduced dose and then finally discontinued in patient 1, and was discontinued directly in patient 2. On the basis of continued use of the other 2 drugs, both of them were treated with ursodeoxycholic acid. The Hb and bilirubin level of the 2 patients gradually returned to normal. Copyright © 2020 by the Chinese Medical Association.
ABSTRACT
In the prevention and control of infectious diseases in novel coronavirus, the primary health care settings played an important role in community epidemic prevention and control, which was the most effective defense line for external import and internal non-proliferation.Faced with the local outbreak or regional epidemic of novel coronavirus infection in the present and even in the future for a long time, primary health care settings need to normalize the epidemic prevention work and make up for the shortcomings in the prevention and control of the major epidemic in time, including: the environmental construction was not standardized, the emergency materials reserve was insufficient, the system construction was a mere formality, and the ability to build primary emergency teams was insufficient.In the future, it is suggested to strengthen the standardization of primary health care in terms of site environment, system improvement, team building, and primary emergency response capability, and attach importance to the labor value of primary health care professionals. Copyright © 2020 by the Chinese General Practice.