ABSTRACT
Nucleic acid detection has been one of the most valued tools in point-of-care diagnostics from life science, agriculture, food safety and environmental surveillance, because of its high sensitivity, great specificity and simple operation. Since polymerase chain reactions (PCR) were discovered, more and more researchers attach importance to exploring ultrafast nucleic acid amplification methods for further expediting the process of detection and curbing infectious diseases' high spread rate, especially after the coronavirus disease 2019 (COVID-19) worldwide pandemic event. Nowadays, nanotechnology as one of the most cut-ting-edge technologies has aroused growing attention. In this review, we describe new advances in na-notechnology research for ultrafast nucleic acid amplification. We have introduced commonly used nanotechnologies, namely nanofluidics, nanoporous materials, nanoparticles and so on. Recent advances in these nanotechnologies for ultrafast sample pretreatments, accelerated enzymatic amplification and rapid heating/cooling processes was summarized. Finally, challenges and perspectives for the future applications of ultrafast nucleic acid amplification are presented.(c) 2022 Elsevier Ltd. All rights reserved.
ABSTRACT
PurposeThis study aims to unlock a ritual chain mechanism that promotes socio-mental (or socio-psychological) resilience. This study draws on interaction ritual chains theory and the concept of transformative service to answer the question of how people could be inspired toward an elevated level of group solidarity, emotional energy, morality and, thus, socio-mental resilience. Design/methodology/approachThis study took a qualitative approach resting upon online reviews and observations from an augmented food festival about hot pot delicacies dedicated to medical workers fighting hard amid the early coronavirus outbreak. FindingsThe results of this study point to four primary ritual outcomes (e.g. emotional energy, group solidarity, symbols of relationships and standards of morality) along with a two-tier micro-macro socio-mental resilience sustainability paradigm. Research limitations/implicationsEmpirical findings from this study could help operators to justify their transformative initiatives as means for customers to replenish their depleted physical and mental resources. Originality/valueThis inquiry presents new nuances to interaction ritual chains. This study also extends the transformative role of hospitality services to accentuate a linkage among individuals, communities and the society.
ABSTRACT
In this study, three greenhouse gases (CO2, CH4, and N2O) and one conventional gas (CO) were observed at a roadside station in Shenzhen from September, 2019 to July, 2020. The average concentration of CO2, CH4, N2O, and CO was (430.8±6.1)×10-6, (2318.5±137.9)×10-9, (332.6±1.6)×10-9, and (333.4±121.2)×10-9, respectively. Seasonal variation of CO2 and CO were high in winter and low in summer, Seasonal variation of CH4 and N2O were high in autumn and low in summer. The high concentration in autumn and winter is due to the long-distance transmission of fossil fuel emissions during the heating period, and the low concentration in summer is mainly due to the reduction of long-distance transmission sources and the enhancement of sinks such as plant photosynthesis and photochemical reactions. The diurnal variation of CO2 concentration showed a two-peak and one-valley pattern, which was mainly affected by plant photosynthesis and morning and evening traffic peak;The diurnal variation of CO concentration showed a two-peak pattern, which was mainly affected by the morning and evening traffic peaks. The diurnal variation of CH4 and N2O concentration was high at night and low at day, which was mainly affected by daytime photochemical reaction. Among them, the concentration of CO2 and CO is more sensitive to the emission of traffic sources. In addition, this study compared the COVID-19 lockdown period in 2020 with the same period in 2021, and the results showed that the concentration of CO2, CH4, N2O, and CO decreased by 3.1%, 10.6%, 0.5% and 13.9%, respectively, indicating that traffic control can play an important role in reducing urban greenhouse gas emissions. © 2022, Editorial Board of China Environmental Science. All right reserved.
ABSTRACT
In the diagnosis of severe contagious diseases such as Ebola, severe acute respiratory syndrome, and COVID-19, there is an urgent need for protein sensors with large refractive index sensitivities. Current terahertz metamaterials cannot be used to develop such protein sensors due to their low refractive index sensitivities. A simple method is proposed that is compatible with all geometrical structures of terahertz metamaterials to increase their refractive index sensitivities. This method uses patterned photoresist to float the split-ring resonators (SRRs) of a terahertz metamaterial at a height of 30 μm from its substrate that is deposited with complementary SRRs. The floating terahertz metamaterial has an extremely large refractive index sensitivity of 532 GHz/RIU because its near field is not distributed over the substrate and also because the complementary SRRs confine the field above the substrate. The floating terahertz metamaterial senses bovine serum albumin (BSA) and the protein binding of BSA and anti-BSA as BSA, and anti-BSA solutions with low concentrations that are smaller than 0.150 μmol/L are sequentially dropped onto it. The floating terahertz metamaterial is a great achievement to develop protein sensors with extremely large refractive index sensitivities, and has the potential to sense dangerous viruses. © 2021 Chinese Laser Press.
ABSTRACT
This paper studies the feasibility of detecting the pneumonia due to the COVID-19 with microwave medical imaging. One challenge while formulating such a problem is to identify the disease in lungs whose dielectric permittivity is dynamically fluctuating with the respiration. In this paper, we utilize this feature by assuming that the permittivity of the disease has minor variation at microwave frequencies during the respiration, and thus the dielectric variance of the pixels at the diseased site over a number of consecutive images significantly differs from those of the other tissues in the thorax. Based on this assumption, we propose two approaches that make use of the a priori information (API) on the position of the heart and the symmetry of the thorax, respectively, to identify a diseased lung. Finally, these two approaches are numerically validated on a thorax phantom, and their performance is compared.