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Conference on Silicon Photonics XVII Part of SPIE Photonics West OPTO Conference ; 12006, 2022.
Article in English | Web of Science | ID: covidwho-1986323

ABSTRACT

The advent of the SARS-CoV-2 pandemic has rekindled the demand for inexpensive, point-of-care and at-home diagnostic systems that offer high degrees of scalability, sensitivity, and specificity. While several options of sensing modalities have been researched and subsequently commercialized, these sensing systems are yet to simultaneously satisfy the spiked demand for higher accuracy and scalable manufacturing. In this context, the prospect of integrated photonics-enabled biosensors has garnered immense attention from both scientific and business communities. However, realizing low group indices of the photonic structures required for higher bulk sensitivities at commonly used telecom operation wavelengths is typically achieved using design approaches incompatible with foundry process constraints. Siphox Inc., founded in 2020, developed an ensemble biosensing platform by merging the benefits of CMOS-friendly integrated photonic structures with proprietary biochemical assays to realize low-cost, highly sensitive, label and label-free, multiplexed diagnostic system. As a first demonstration, we present our results of 15-plex biosensing utilizing low-loss (<3.5dB/cm) Si3N4 strip-waveguide ring resonators fabricated using 248 nm deep UV (DUV) stepper lithography. We describe the design, simulation, and measurement results of bulk and surface sensitivities and detection limits for our TE-polarized waveguide resonator structures operating at O-band (1310 nm). We demonstrate a bulk sensitivity of >117 nm/RIU and an intrinsic limit of detection of 1.87x10(-4) RIU.

2.
Silicon Photonics XVII 2022 ; 12006, 2022.
Article in English | Scopus | ID: covidwho-1891718

ABSTRACT

The advent of the SARS-CoV-2 pandemic has rekindled the demand for inexpensive, point-of-care and at-home diagnostic systems that offer high degrees of scalability, sensitivity, and specificity. While several options of sensing modalities have been researched and subsequently commercialized, these sensing systems are yet to simultaneously satisfy the spiked demand for higher accuracy and scalable manufacturing. In this context, the prospect of integrated photonics-enabled biosensors has garnered immense attention from both scientific and business communities. However, realizing low group indices of the photonic structures required for higher bulk sensitivities at commonly used telecom operation wavelengths is typically achieved using design approaches incompatible with foundry process constraints. Siphox Inc., founded in 2020, developed an ensemble biosensing platform by merging the benefits of CMOS-friendly integrated photonic structures with proprietary biochemical assays to realize low-cost, highly sensitive, label and label-free, multiplexed diagnostic system. As a first demonstration, we present our results of 15-plex biosensing utilizing low-loss (<3.5dB/cm) Si3N4 strip-waveguide ring resonators fabricated using 248 nm deep UV (DUV) stepper lithography. We describe the design, simulation, and measurement results of bulk and surface sensitivities and detection limits for our TE-polarized waveguide resonator structures operating at O-band (1310 nm). We demonstrate a bulk sensitivity of >117 nm/RIU and an intrinsic limit of detection of 1.87×10-4 RIU. © COPYRIGHT SPIE. Downloading of the is permitted for personal use only.

5.
Acta Medica Mediterranea ; 37(5):2599-2606, 2021.
Article in English | Scopus | ID: covidwho-1449393

ABSTRACT

Objective: During the COVID-19 pandemie period, weight control became an important health issue because of physical inactivity. Developing a valid and convenient tool to estimate energy consumption is a pressing task. Methods: This research investigates the invention patent method of rhythm speech test, introduces the smartphone sport supported fat & glucose calculator (SSFGC) program, applies it to estimation of fat and sugar consumption in endurance exercise of bicycle, and compares it with the results measured by gas analysis indirect calorimetry. The research recruited 12 males (age: 31.8±3.2 yrs, height: 171.6 ± 7.9 cm, weight: 71.2 ± 5.0 kg, peak oxygen uptake: 46.2 ± 5. 6 mL/min/kg, maximum power: 240 ± 50 watts, 15 watts/min progressive exercise load exhaustion time: 982 ± 197 sec and RER: 1.1 ± 0.1). Before the research, the research objects must be measured for peak oxygen uptake and basic physiological data. Participants must follow the SSFGC method of use during the 1 hour' s endurance exercise (30% V• O2peak -80% V• O2peak). The data derived from each analysis are expressed as mean ± standard deviation. The significance is set to p ≦.05. Results: According to SSFGC and gas analysis indirect calorimetry, estimated consumption of sugar (r =. 994, p <. 05) and fat (30% V• O2peak to 50% V• O2peak: r=.888, p <. 05;60% V• O2peak to 80% V• O2peak r=.817, p <. 05) exhibited high positive correlation between the two. Conclusion: The invention patent method of rhythm speech test, by importing SSFGC calorimeter program, can estimate the energy consumption of fat and sugar in stable endurance exercise, and provide the theoretical basis/or further application in the future. © 2021 A. CARBONE Editore. All rights reserved.

6.
Aerosol and Air Quality Research ; 21(8):17, 2021.
Article in English | Web of Science | ID: covidwho-1359350

ABSTRACT

COVID-19, which is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), first broke out at the end of 2019. Despite rapidly spreading around the world during the first half of 2020, it remained well controlled in Taiwan without the implementation of a nationwide lockdown. This study aimed to evaluate the PM2.5 concentrations in this country during the 2020 COVID-19 pandemic and compare them with those during the corresponding period from 2019. We obtained measurements (taken every minute or every 3 minutes) from approximately 1,500 PM2.5 sensors deployed in industrial areas of northern and southern Taiwan for the first quarters (January-March) of both years. Our big data analysis revealed that the median hourly PM2.5 levels decreased by 3.70% (from 16.3 to 15.7 mu g m(-3)) and 10.6% (from 32.4 to 29.3 mu g m(-3)) in the north and south, respectively, between these periods owing to lower domestic emissions of PM2.5 precursors (viz., nitrogen dioxide and sulfur dioxide) and, to a lesser degree, smaller transported emissions of PM2.5, e.g., from China. Additionally, the spatial patterns of the PM2.5 in both northern and southern Taiwan during 2020 resembled those from the previous year. Finally, controlling local PM2.5 emission sources critically contributes to reducing the number of COVID-19 cases.

7.
2020 International Symposium on Computer, Consumer and Control ; : 154-157, 2021.
Article in English | Web of Science | ID: covidwho-1338786

ABSTRACT

After the Covid-19 pandemic, it has gradually threatened human health. The current preliminary detection method is to measure body temperature;especially Covid-19 has been confirmed by the World Health Organization (WHO) that it can be spread from person to person. Fever is one of the easiest ways to judge. After the system has completed the automatic measurement, the user's information and forehead temperature can be imported into the database, and the data can be exported according to the manager's usage habits.

8.
Nurse Educ Today ; 104: 104985, 2021 Sep.
Article in English | MEDLINE | ID: covidwho-1243137

ABSTRACT

BACKGROUND: Previous studies suggest that increased learning satisfaction may encourage learning engagement in an online learning environment. OBJECTIVES: To evaluate the level of learning engagement and its relationship with students' perceived learning satisfaction in an online clinical nursing elective course. DESIGN: A prospective interventional study. SETTINGS: A nursing course was converted to an online format because of the coronavirus disease COVID pandemic. PARTICIPANTS: Part-time post-registration nursing undergraduates enrolled in an elective online clinical course. METHODS: Related teaching and learning strategies were deployed in the course using the Community of Inquiry framework. All students who completed the course were invited to complete an online survey that included a validated Online Student Engagement questionnaire (OSE). Pearson's correlations were used to determine the association between perceived learning satisfaction and learning engagement. A logistic regression model was used to explore the associations of gender, age, working experience and perceived learning satisfaction with higher learning engagement. RESULTS: The questionnaires were completed by 56 of 68 students (82%). The Pearson's correlation coefficient between the mean perceived learning satisfaction and OSE scores was 0.75 (p < .001). Twenty-five students (45%) were identified as highly engaged, using a cut-off of ≥3.5 for the mean OSE score. The mean perceived learning satisfaction (SD) score differed significantly between highly engaged and not highly engaged students [4.02 (0.49) vs. 3.27 (0.62), p < .001]. The logistic regression model showed that a greater perceived learning satisfaction [adjusted odds ratio (OR): 17.2, 95% C.I.: 3.46-86.0, p = .001] was associated with an increased likelihood of higher learning engagement, and >1 year of working experience (adjusted OR: 0.11, 95% C.I.: 0.01-0.89, p = .0039) was associated with a decreased likelihood of higher learning engagement. CONCLUSIONS: The study findings suggest that perceived learning satisfaction predicts learning engagement among nursing students in this online learning course.


Subject(s)
COVID-19 , Education, Distance , Students, Nursing , Humans , Prospective Studies , SARS-CoV-2
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