Effects of seasonal management programs on PM2.5 in Seoul and Beijing using DN-PMF: Collaborative efforts from the Korea-China joint research.

South Korea and China have implemented increasingly stringent mitigation measures to reduce the health risks from PM2.5 exposure, jointly conducting a ground-based air quality observation study in Northeast Asia. Dispersion normalized positive matrix factorization (DN-PMF) was used to identify PM2.5 sources in Seoul and Beijing and assess the effectiveness of the seasonal management programs (SMPs) through a comparative study. Samples were collected during three periods: January-December 2019, September 2020-May 2021, and July 2021-March 2022. In Seoul, ten sources were resolved (Secondary nitrate: 8.67 µg/m3, 34 %, Secondary sulfate: 5.67 µg/m3, 22 %, Motor vehicle: 1.83 µg/m3, 7.2 %, Biomass burning: 2.30 µg/m3, 9.1 %, Residual oil combustion: 1.66 µg/m3, 6.5 %, Industry: 2.15 µg/m3, 8.5 %, Incinerator: 1.39 µg/m3, 5.5 %, Coal combustion: 0.363 µg/m3, 1.4 %, Road dust/soil: 0.941 µg/m3, 3.7 %, Aged sea salt: 0.356 µg/m3, 1.4 %). The SMP significantly decreased PM2.5 mass concentrations and source contributions of motor vehicle, residual oil combustion, industry, coal combustion, and biomass burning sources (p-value < 0.05). For Seoul, the reduction effects of the SMPs were evident even considering the influence of the natural meteorological variations and the responses to COVID-19. In Beijing, nine sources were resolved (Secondary nitrate: 12.6 µg/m3, 28 %, Sulfate: 8.27 µg/m3, 18 %, Motor vehicle: 3.77 µg/m3, 8.4 %, Biomass burning: 2.70 µg/m3, 6.0 %, Incinerator: 4.50 µg/m3, 10 %, Coal combustion: 3.52 µg/m3, 7.8 %, Industry: 5.01 µg/m3, 11 %, Road dust/soil: 2.92 µg/m3, 6.5 %, Aged sea salt: 1.63 µg/m3, 3.6 %). Significant reductions in PM2.5 mass concentrations and source contributions of industry, coal combustion, and incinerator (p-value < 0.05) were observed, attributed to the SMP and additional measures enforced before the 2022 Beijing Winter Olympics. Unlike comparing PM2.5 mass concentration variations using conventional methods, investigation of the source contribution variations of PM2.5 by using DN-PMF can provide a deeper understanding of the effectiveness of the air quality management policies.

Assistive technology for adults on the autism spectrum: A systematic survey.

While the needs and care for children on the autism spectrum have been widely investigated, the intervention and services available to autistic adults have been overlooked for a long time. This survey paper reviewed 32 articles that described and evaluated assistive technologies that have been developed and evaluated through a complete circle of interactive product design from ideation, prototype, and user evaluation. These assistive technologies aim to improve independence and living quality in autistic adults. We extracted information from the perspective of requirement gathering, technology designing, and effectiveness of evaluation in the design cycle. We found a general lack of requirements-driven design, and the evaluation process was not standardized either. The lack of requirement gathering results in designs purely based on existing literature without targeting actual user needs. Our synthesis of included paper contributes to developing iterative design considerations in assistive technologies for autistic adults. We also suggest that assistive technologies for autistic adults shift some attention from assisting only autistic adults who require at least substantial support to embracing also those who have been living independently but rather have difficulties in social interaction. Assistive technologies for them have the potentials to help them consolidate and enhance their experiences in independent living.

Reliable and transparent in-vehicle agents lead to higher behavioral trust in conditionally automated driving systems.

Trust is critical for human-automation collaboration, especially under safety-critical tasks such as driving. Providing explainable information on how the automation system reaches decisions and predictions can improve system transparency, which is believed to further facilitate driver trust and user evaluation of the automated vehicles. However, what the optimal level of transparency is and how the system communicates it to calibrate drivers' trust and improve their driving performance remain uncertain. Such uncertainty becomes even more unpredictable given that the system reliability remains dynamic due to current technological limitations. To address this issue in conditionally automated vehicles, a total of 30 participants were recruited in a driving simulator study and assigned to either a low or a high system reliability condition. They experienced two driving scenarios accompanied by two types of in-vehicle agents delivering information with different transparency types: "what"-then-wait (on-demand) and "what + why" (proactive). The on-demand agent provided some information about the upcoming event and delivered more information if prompted by the driver, whereas the proactive agent provided all information at once. Results indicated that the on-demand agent was more habitable, or naturalistic, to drivers and was perceived with faster system response speed compared to the proactive agent. Drivers under the high-reliability condition complied with the takeover request (TOR) more (if the agent was on-demand) and had shorter takeover times (in both agent conditions) compared to those under the low-reliability condition. These findings inspire how the automation system can deliver information to improve system transparency while adapting to system reliability and user evaluation, which further contributes to driver trust calibration and performance correction in future automated vehicles.

A systematic review of automatic text summarization for biomedical literature and EHRs.

OBJECTIVE: Biomedical text summarization helps biomedical information seekers avoid information overload by reducing the length of a document while preserving the contents' essence. Our systematic review investigates the most recent biomedical text summarization researches on biomedical literature and electronic health records by analyzing their techniques, areas of application, and evaluation methods. We identify gaps and propose potential directions for future research. MATERIALS AND METHODS: This review followed the PRISMA methodology and replicated the approaches adopted by the previous systematic review published on the same topic. We searched 4 databases (PubMed, ACM Digital Library, Scopus, and Web of Science) from January 1, 2013 to April 8, 2021. Two reviewers independently screened title, abstract, and full-text for all retrieved articles. The conflicts were resolved by the third reviewer. The data extraction of the included articles was in 5 dimensions: input, purpose, output, method, and evaluation. RESULTS: Fifty-eight out of 7235 retrieved articles met the inclusion criteria. Thirty-nine systems used single-document biomedical research literature as their input, 17 systems were explicitly designed for clinical support, 47 systems generated extractive summaries, and 53 systems adopted hybrid methods combining computational linguistics, machine learning, and statistical approaches. As for the assessment, 51 studies conducted an intrinsic evaluation using predefined metrics. DISCUSSION AND CONCLUSION: This study found that current biomedical text summarization systems have achieved good performance using hybrid methods. Studies on electronic health records summarization have been increasing compared to a previous survey. However, the majority of the works still focus on summarizing literature.

[Studies on the remote measurement of the distribution of city gaseous pollutant by mobile passive differential optical absorption spectroscopy].

An optical remote sensing method based on passive differential optical absorption spectroscopy for the measurement of the distribution of city gaseous pollutant was studied. The passive DOAS system, which was installed in a car, successively measures the interested area (such as city, industrial area) and the column density was obtained by DOAS fitting process using the zenith scattered sunlight. The mobile DOAS was applied to measurement in Shenzhen City during the continuous six days and got the distribution of SO2, NO2 in this paper. It showed that the pollution in the west is higher than in the east. The average concentration in the west is 2.0 times higher than the eastern for SO2 and 3.6 times for NO2. And comparison of the values between mobile DOAS and the point instrument was carried out in Baguang site. There was an agreement between the two instruments, the correlation coefficient was 0.86 for SO2, while 0.57 for NO2. The results indicate that this optical remote sensing method based on passive DOAS is an effective means of rapidly determining the distribution of city gaseous pollutant.

[Atmospheric HCHO gradient monitoring and analysis in Beijing City with a scanning DOAS system].

Scanning differential optical absorption spectroscopy (DOAS) technique combined with meteorological tower was used for monitoring vertical profiles of SO2, NO2, O3, HCHO and HONO along three light paths in Beijing City during July 28, 2009 to August 13, 2009. As a result, the time series of concentrations and vertical gradient of HCHO as well as other gases were acquired. By analyzing the vertical distribution frequency characteristics of HCHO, data of other gases and meteorological data, it was concluded that the main source of HCHO is vehicles emissions around the measurement site. The photochemical reaction as the secondary source accounts for a significant proportion of the source of HCHO at certain times of day (around noon, for a few hours).