Empathic Accuracy and Mental Effort During Remote Assessments of Emotions

Observing users in remote settings is unfavorable because it adds filters altering the information that underlie judgement. Still, the COVID pandemic led to an unprecedented popularity of remote user experience tests. In this work, we revisited the question, which information is most important for evaluators to assess users' emotions successfully and efficiently. In an online study, we asked N=55 participants to assess users' emotions from short videos of 30 interaction situations. As independent variable, we manipulated the combination of the information channels video of users, video of the interactive technology, and audio within subjects. Our findings indicate that empathic accuracy is highest and mental effort is lowest when all stimuli are present. Surprisingly, empathic accuracy was lowest and mental effort highest, when only video of users was available. We discuss these findings in the light of emotion literature focusing on persons' facial expressions and derive practical implications for remote observations. © 2023 ACM.

L-Moments and calibration-based variance estimators under double stratified random sampling scheme: Application of Covid-19 pandemic

Extreme events gives rise to outrageous results in terms of population-related parameters and their estimates are usually done using traditional moments. Traditional moments are usually affected by extreme observations. This study aims to propose some new calibration estimators considering the L-Moments scheme for variance, which is one of the most important population parameters. a number of suitable calibration constraints under double stratified random sampling were defined for these estimators. The proposed estimators, which were based on L-Moments, were relatively more robust despite extreme values. The empirical efficiency of the proposed estimators was also assessed through simulation. Covid-19 pandemic data from January 22, 2020 to August 23, 2020 was taken into account in the simulation study. (c) 2023 Sharif University of Technology. All rights reserved.

A QGIS plugin for BONDS project: integrating field data with geographical, remote sensing and health information

Open source Geographic Information System (GIS) have been fostering spatial data research such as Earth observation and environmental monitoring for more than 30 years. More recently, globally available geospatial information combined with web technologies are providing new environments and tools for data handling. Thus, binding the mapping and processing capabilities of traditional GIS to the accessibility and reliability of web-based data providers can bring new opportunities for research. In this paper, we built a QGIS plugin to explore the integration of different public data providers in Brazil along with field data produced by the BONDS project. The biOdiversity conservatioN with Development in Amazon wetlandS project (BONDS) proposes to develop biodiversity scenarios for the Amazonian floodplains aiming to support solutions to preserve biodiversity and ecosystem services. The use of web services enabled dynamic and fast access to several products ranging from remote sensing images, land use and land cover, territorial cartography, water quality, to COVID-19 health data, and more. © 2022 National Institute for Space Research, INPE. All rights reserved.

Changes in Tropospheric Nitrogen Dioxide Vertical Column Densities over Japan and Korea during the COVID-19 Using Pandora and MAX-DOAS

We investigated the impact of human activity during COVID-19 on the tropospheric nitrogen dioxide vertical column density (NO2 TropVCD) at three urban sites (Gwangju and Busan in Korea and Yokosuka in Japan) and one remote site (Cape Hedo in Japan) from Multi-Axis Differential Optical Absorption Spectroscopy (MAX-DOAS) and Pandora. Compared to the monthly mean NO2 TropVCD from 2015 to 2018 and in 2019, the values were lower in 2020 due to social distancing in Korea and Japan. High negative relative changes were observed from May to September (-30% to -18%) at the three urban sites;Cape Hedo, a remote site, did not show a significant difference in relative changes between previous years and 2020, suggesting that only anthropogenic emission sources decreased dramatically. In the case of Yokosuka, the 15-day moving average of the NO2 TropVCD exhibited a good relationship with transportation (R = 0.48) and industry (R = 0.54) mobility data. In contrast, the NO2 TropVCD at the Korean sites showed a moderate to low correlation with the industrial sector and insignificant correlations with transportation. The differences in correlations might be caused by the different social distancing policies in Korea (voluntary) and Japan (mandatory). By applying generalized boosted models to exclude meteorological and seasonal effects associated with NO2 TropVCD variations, we revealed that the decreasing trend from 2019 to 2020 was much steeper than that from 2015 to 2020 (a factor of two), and a significant change was identified in January 2020, when the first cases of COVID-19 were observed in both Korea and Japan. This result confirmed that the reduction in NO2 can be largely explained by the NOx emission reduction resulting from social distancing for COVID-19 rather than annual meteorological differences;however, in December 2020, NO2 recovered suddenly to its previous level due to an increase in human activities.

The Effects of the COVID-19 Pandemic on the Coworking Spaces in Poland

The chapter deals with the changes occurring during the COVID-19 pandemic in the coworking sector. We have collected data and information from primary and secondary sources. The latter include in-depth interviews, covert participant observations and computer-assisted telephone interviews (CATI). We analysed the changes of the number of coworking spaces (CSs) and main mechanisms behind them. The findings reveal the relatively limited scale of decrease in the number of coworking spaces and illustrate how the pandemic outbreak influenced the effects of CS operations, especially on the real estate market. It is argued that independently-run CSs suffered the most, whereas corporate CSs with a stable core of corporate clients, central location and limited competition have been more resilient. With regard to the changes generated by the COVID-19 pandemic, the most significant transformations are seen in the decreasing number of non-virtual events organised by CSs, whereas the scale of the other impacts of CSs on the local milieu decreased slightly. © 2023, The Author(s).

Patchwork: The Hidden, Human Labor of AI Integration within Essential Work

This paper examines the rapid introduction of AI and automation technologies within essential industries amid the COVID-19 pandemic. Drawing on participant observation and interviews within two sites of waste labor in the United States, we consider the substantial effort performed by frontline workers who smooth the relationship between robotics and their social and material environment. Over the course of the research, we found workers engaged in continuous acts of calibration, troubleshooting, and repair required to support AI technologies over time. In interrogating these sites, we develop the concept of "patchwork": human labor that occurs in the space between what AI purports to do and what it actually accomplishes. We argue that it is necessary to consider the often-undervalued frontline work that makes up for AI's shortcomings during implementation, particularly as CSCW increasingly turns to discussions of Human-AI collaboration. © 2023 Owner/Author.

A Cross-Sectional Study and Observational Assessment of Shoppers' COVID-19 Prevention Behaviors in Southwestern Ontario, Canada.

OBJECTIVE: The aim of this study was to observe the level of alcohol-based sanitizer, mask use, and physical distancing across indoor community settings in Guelph, ON, Canada, and to identify potential barriers to practicing these behaviors. METHODS: Shoppers were observed in June 2022 across 21 establishments. Discrete in-person observations were conducted and electronically recorded using smartphones. Multilevel logistic regression models were fitted to identify possible covariates for the 3 behavioral outcomes. RESULTS: Of 946 observed shoppers, 69% shopped alone, 72% had at least 1 hand occupied, 26% touched their face, 29% physically distanced ≥ 2 m, 6% used hand sanitizer, and 29% wore masks. Sanitizer use was more commonly observed among people who wore masks and in establishments with coronavirus disease (COVID-19) signage posted at the entrance. Mask use was more commonly observed during days without precipitation and in establishments with some or all touch-free entrances. Shoppers more commonly physically distanced ≥ 2 m when they were shopping alone. CONCLUSIONS: This supports evidence for environmental context influencing COVID-19 preventive behaviors. Intervention efforts aimed at visible signage, tailored messaging, and redesigning spaces to facilitate preventive behaviors may be effective at increasing adherence during outbreaks.

COVID-19 Impact on the Italian Community-based System of Mental Health Care: Reflections and Lessons Learned for the Future

Surface longwave downward radiation (LWDR) is a key factor affecting the surface energy balance. The daily LWDR and the diurnal variations of LWDR are of great significance for studies of climate change and surface processes. How to obtain LWDR at an averaged temporal scale from instantaneous LWDR is one of the longstanding problems in the field of radiation budget from remote sensing. In this paper, two temporal upscaling methods are introduced, namely, a method based on the diurnal variations of LWDR (diurnal variation based, DVB) and a method based on random forest regression (RFR). The results reveal that: (1) The DVB method has a global hourly and daily LWDR root-mean-square error (RMSE) of less than 21 W/m2 and 15 W/m2, respectively, and the RMSE of the daily LWDR based on RFR is less than 7 W/m2;(2) When compared with four existing statistical interpolation methods, the DVB method can not only ensure the accuracy, but also can overcome the problem of missing samples and/or an abnormal samples during upscaling;(3) Except for directly predict daily LWDR, the DVB methods can also obtain more accurate LWDR diurnal variations such as hourly, half-hourly etc. The RFR method enables high-efficiency and accurate estimation of daily averaged LWDR from instantaneous measurements. Compared with existing methods and products, the proposed methods are not only efficient, but also have a superior applicability and reliable accuracy. The proposed strategies provide new ideas for the community in estimating LWDR at continuous temporal scales from remotely sensed measurements.

Coarse particulate matter air quality in East Asia: implications for fine particulate nitrate

Air quality network data in China and South Korea show very high year-round mass concentrations of coarse particulate matter (PM), as inferred by the difference between PM10 and PM2.5. Coarse PM concentrations in 2015 averaged 52 µg m-3 in the North China Plain (NCP) and 23 µg m-3 in the Seoul Metropolitan Area (SMA), contributing nearly half of PM10. Strong daily correlations between coarse PM and carbon monoxide imply a dominant source from anthropogenic fugitive dust. Coarse PM concentrations in the NCP and the SMA decreased by 21 % from 2015 to 2019 and further dropped abruptly in 2020 due to COVID-19 reductions in construction and vehicle traffic. Anthropogenic coarse PM is generally not included in air quality models but scavenges nitric acid to suppress the formation of fine particulate nitrate, a major contributor to PM2.5 pollution. GEOS-Chem model simulation of surface and aircraft observations from the Korea–United States Air Quality (KORUS-AQ) campaign over the SMA in May–June 2016 shows that consideration of anthropogenic coarse PM largely resolves the previous model overestimate of fine particulate nitrate. The effect is smaller in the NCP which has a larger excess of ammonia. Model sensitivity simulations for 2015–2019 show that decreasing anthropogenic coarse PM directly increases PM2.5 nitrate in summer, offsetting 80 % the effect of nitrogen oxide and ammonia emission controls, while in winter the presence of coarse PM increases the sensitivity of PM2.5 nitrate to ammonia and sulfur dioxide emissions. Decreasing coarse PM helps to explain the lack of decrease in wintertime PM2.5 nitrate observed in the NCP and the SMA over the 2015–2021 period despite decreases in nitrogen oxide and ammonia emissions. Continuing decrease of fugitive dust pollution means that more stringent nitrogen oxide and ammonia emission controls will be required to successfully decrease PM2.5 nitrate.

Global Atmospheric Composition Needs from Future Ultraviolet–Visible–Near-Infrared (UV–Vis–NIR) NOAA Satellite Instruments

Presentations spanned a range of applications: the public health impacts of poor air quality and environmental justice;greenhouse gas measuring, monitoring, reporting, and verification (GHG MMRV);stratospheric ozone monitoring;and various applications of satellite observations to improve models, including data assimilation in global Earth system models. The combination of methane (CH4), carbon dioxide (CO2), carbon monoxide (CO), and NO2 retrievals can improve confidence in emissions inventories and model performance, and together these data products would be of use in future air quality management tools. The ability to retrieve additional trace gases (e.g., ethane, isoprene, and ammonia) in the thermal IR along with those measured in the UV–Vis–NIR region would be extremely useful for air quality applications, including source apportionment analysis (e.g., for oil/natural gas extraction, biogenic, and agricultural sources). Ground-level ozone is one of six criteria pollutants for which the EPA sets National Ambient Air Quality Standards (NAAQS) to protect against human health and welfare effects.

Assimilation of aircraft observations over the Indian monsoon region: Investigation of the effects of COVID-19 on a reanalysis

Since March 2020, the COVID-19 pandemic has significantly reduced the availability of global aircraft-based observations (ABOs), which has been restored later in 2021. This study focuses on the impact of ABOs on a regional reanalysis. Indian Monsoon Data Assimilation and Analysis (IMDAA) is a regional reanalysis for a period from 1979 to 2020 (originally up to 2018) over India and surrounding regions produced at the National Centre for Medium Range Weather Forecasting (NCMRWF), India, in collaboration with the UK Met Office. A comparison of the impact of ABOs on other conventional and satellite observations assimilated in the NCMRWF global model and IMDAA during 2019 and 2020 revealed the importance of ABOs, particularly in IMDAA, since it did not assimilate the latest satellite data as the IMDAA system was frozen in October 2016. A data denial experiment that removes all the ABOs from the IMDAA assimilation system for a period from March to November 2019 is designed. The results from the IMDAA reanalysis run, which assimilates ABOs during the same period, are compared with the data denial experiment. Assimilation of ABOs strengthened the upper tropospheric circulation, the Tropical Easterly Jet (TEJ), during the Indian summer monsoon compared to the data denial experiment. Analysis of the features of two cyclones that developed over the North Indian Ocean during the study period revealed that ABO assimilation played a key role in simulating the track and intensity of these cyclones when they were in the ‘severe' category. Since the sample is small, more cyclone cases need to be analysed to consolidate the result. © 2023 Royal Meteorological Society.

Financial Auditor Efficiency and Effectiveness in Remote Audit Transition Due to Pandemic of Covid-19

The pandemic of Covid-19 requires people in any profession to do large-scale social restrictions, this also lead in financial/external auditors experiencing difficulties in conducting audits in the common daily activity, which is by visiting clients physically to make observations. In this condition, online observation using remote audit become one of the solution. The purpose of this study is to analyze the effectiveness and efficiency of external auditors in transition to remote auditing due to the Covid-19 Pandemic. The data collection technique is using primary data from questionnaire. We distribute questionnaire to Public Accounting Firms located in DKI Jakarta using simple random sampling method technique. The method for data analysis is using partial least squares conducted with Software of SmartPLS 3. The result of this study indicates that remote audit efficiency and remote audit efficiency have positive and significant effect on audit quality. Meanwhile, institutional support has no significant effect on audit quality. © 2022 IEEE.

Effects of the Pandemic on Observing the Global Ocean

The years since 2000 have been a golden age in in situ ocean observing with the proliferation and organization of autonomous platforms such as surface drogued buoys and subsurface Argo profiling floats augmenting ship-based observations. Global time series of mean sea surface temperature and ocean heat content are routinely calculated based on data from these platforms, enhancing our understanding of the ocean's role in Earth's climate system. Individual measurements of meteorological, sea surface, and subsurface variables directly improve our understanding of the Earth system, weather forecasting, and climate projections. They also provide the data necessary for validating and calibrating satellite observations. Maintaining this ocean observing system has been a technological, logistical, and funding challenge. The global COVID-19 pandemic, which took hold in 2020, added strain to the maintenance of the observing system. A survey of the contributing components of the observing system illustrates the impacts of the pandemic from January 2020 through December 2021. The pandemic did not reduce the short-term geographic coverage (days to months) capabilities mainly due to the continuation of autonomous platform observations. In contrast, the pandemic caused critical loss to longer-term (years to decades) observations, greatly impairing the monitoring of such crucial variables as ocean carbon and the state of the deep ocean. So, while the observing system has held under the stress of the pandemic, work must be done to restore the interrupted replenishment of the autonomous components and plan for more resilient methods to support components of the system that rely on cruise-based measurements. © 2023 American Meteorological Society.

Language Learners' Disengagement in e-Learning during COVID-19: Secondary Teachers' Views

The study looked at language teachers' views of their students' disengagement in e-learning during COVID-19. It described their efforts on how to engage the learners beyond the screen, where teachers have no control, and how to overcome the issues disturbing students' engagement, motivation, and achievement. The study looked at learning engagement as an important requirement in e-learning, which is influenced by social factors including teachers' communication with students, students' interaction among themselves, and their collaboration in learning activities. This study used interviews, reports, and notes of 15 teachers to collect data from 15 language teachers in some Saudi secondary schools during the academic year 2020–2021. That year was completely delivered in e-learning platforms. The findings show that teachers ran into several difficulties to engage their learners in online sessions during that year;students lacked some ethics and requirements for e-learning;and technical issues disabled both teachers and learners from remaining in the learning engagement. These three main results propose a framework for educators, students, parents, and policymakers to deal with the obstacles and threats of learning engagement in online lessons. The study ends with suggestions for future studies. Copyright for this article is retained by the author(s)

Digital Technologies in Orientation and Mobility Instruction for People Who are Blind or Have Low Vision

This paper investigates the tools and practices used by Orientation and Mobility (O&M) specialists in instructing people who are blind or have low vision in concepts, skills, and techniques for safe and independent travel. Based on interviews with experienced instructors who practice in different O&M settings we find that a shortage of qualified specialists and restrictions on in-person activities during COVID-19 has accelerated interest in remote instruction and assessment, while widespread adoption of smartphones with accessibility support has driven interest in assistive apps. This presents both opportunities and challenges for a practice that is traditionally conducted in-person and assessed through qualitative observations. In response we identify multiple opportunities for HCI research in service of O&M, including: supporting a 'physician's assistant' model of remote O&M instruction and assessment, matching O&M instructors' clients with guide dogs, highlighting clients' progress towards O&M goals, and collaboratively planning routes and monitoring clients' independent travel progress. © 2022 ACM.

Using Service Blueprint to Optimize the Process Management of Group Package Tour in Kinmen

The COVID-19 led to a global border blockade, and domestic group package tours have become Taiwan tourism industry's main economic source. This study takes 30 group package tours in Kinmen by non-participatory observation method and in-depth interviews with eight tour guides, and four components based on the service design optimization are categorized as follows: (1) accommodation;(2) restaurant;(3) attractions visit;and (4) shopping. The research data indicates that: (1) Tourism operators should consider both the input of service manpower and the supervision of the quality of service delivery. (2) Tour guides are the most important key in multiple delivery services. Practical implications and future research directions are also proposed for application and management. © 2022, Chinese Society for Quality. All rights reserved.

Surface, satellite ozone variations in Northern South America during low anthropogenic emission conditions: a machine learning approach.

2020 presented the ideal conditions for studying the air quality response to several emission reductions due to the COVID-19 lockdowns. Numerous studies found that the tropospheric ozone increased even in lockdown conditions, but its reasons are not entirely understood. This research aims to better understand the ozone variations in Northern South America. Satellite and reanalysis data were used to analyze regional ozone variations. An analysis of two of the most polluted Colombian cities was performed by quantifying the changes of ozone and its precursors and by doing a machine learning decomposition to disentangle the contributions that precursors and meteorology made to form O3. The results indicated that regional ozone increased in most areas, especially where wildfires are present. Meteorology is associated with favorable conditions to promote wildfires in Colombia and Venezuela. Regarding the local analysis, the machine learning ensemble shows that the decreased titration process associated with the NO plummeting owing to mobility reduction is the main contributor to the O3 increase (≈50%). These tools lead to conclude that (i) the increase in O3 produced by the reduction of the titration process that would be associated with an improvement in mobile sources technology has to be considered in the new air quality policies, (ii) a boost in international cooperation is essential to control wildfires since an event that occurs in one country can affect others and (iii) a machine learning decomposition approach coupled with sensitivity experiments can help us explain and understand the physicochemical mechanism that drives ozone formation. Supplementary Information: The online version contains supplementary material available at 10.1007/s11869-023-01303-6.

Digital distributive leadership in the time of the Covid-19 pandemic-New light on the transition from physical workplaces to digital spaces in Swedish eldercare

The Covid-19 pandemic has had a huge effect on working life in many welfare sectors. An ongoing qualitative study on distributed leadership work in Swedish eldercare has highlighted the premises of needs assessment during the pandemic. This article applies the concepts of distributed leadership, space and temporality to shed new light on the transition from physical workplaces to digital spaces. The article stresses the importance of co-working, co-responsibility and close interaction between leaders and employees, and argues that the ongoing pandemic can help us understand how the digital transition is changing the premises for leadership work in eldercare needs assessments. The empirical material was derived from several organisational levels of needs assessment and both individual interviews and participant observations were conducted. The results confirm how managerial work is in a state of transition that changes the interaction between managers and the needs assessors. Both the challenges and the importance of interaction are enhanced in the digital space.

"I'm still learning”: Experienced Mathematics Teachers' Development of Adaptive Expertise Amidst the COVID-19 Pandemic

In 2020, the global COVID-19 pandemic disrupted education across the country, requiring a re-organization of instruction on a large scale. This study examines the experiences of highly-committed secondary mathematics teachers in a large urban U.S. public school district as they shifted their instruction online for an entire year. Using the framework of adaptive expertise - processes and dispositions that can enable teachers to extend their knowledge to novel situations - this paper contrasts the cases of three teachers' development of adaptive practices over time. Drawing on data gathered from semi-structured interviews, participant observation, and content analysis, we discuss how teachers' engagement in the processes of identification and negotiation contributed to their adaptive orientations. By documenting how highly-reflective educators adjusted their instruction to respond to unprecedented teaching demands, this study contributes to the field's understanding of adaptive expertise in mathematics teaching. © ISLS.

Cleaner Skies during the COVID-19 Lockdown

During spring 2020, the COVID-19 pandemic caused massive reductions in emissions from industry and ground and airborne transportation. To explore the resulting atmospheric composition changes, we conducted the BLUESKY campaign with two research aircraft and measured trace gases, aerosols, and cloud properties from the boundary layer to the lower stratosphere. From 16 May to 9 June 2020, we performed 20 flights in the early COVID-19 lockdown phase over Europe and the Atlantic Ocean. We found up to 50% reductions in boundary layer nitrogen dioxide concentrations in urban areas from GOME-2B satellite data, along with carbon monoxide reductions in the pollution hot spots. We measured 20%-70% reductions in total reactive nitrogen, carbon monoxide, and fine mode aerosol concentration in profiles over German cities compared to a 10-yr dataset from passenger aircraft. The total aerosol mass was significantly reduced below 5 km altitude, and the organic aerosol fraction also aloft, indicative of decreased organic precursor gas emissions. The reduced aerosol optical thickness caused a perceptible shift in sky color toward the blue part of the spectrum (hence BLUESKY) and increased shortwave radiation at the surface. We find that the 80% decline in air traffic led to substantial reductions in nitrogen oxides at cruise altitudes, in contrail cover, and in resulting radiative forcing. The light extinction and depolarization by cirrus were also reduced in regions with substantially decreased air traffic. General circulation-chemistry model simulations indicate good agreement with the measurements when applying a reduced emission scenario. The comprehensive BLUESKY dataset documents the major impact of anthropogenic emissions on the atmospheric composition.