bluuebunny/crossref_metadata_2025 huggingface dataset:
Machine learning approaches improve risk stratification for secondary cardiovascular disease prevention in multiethnic patients
Authors: Sarraju Ashish , Ward Andrew , Chung Sukyung , Li Jiang , Scheinker David , Rodríguez Fàtima
Published: October 2021

Objectives

Identifying high-risk patients is crucial for effective cardiovascular disease (CVD) prevention. It is not known whether electronic health record (EHR)-based machine-learning (ML) models can improve CVD risk stratification compared with a secondary prevention risk score developed from randomised clinical trials (Thrombolysis in Myocardial Infarction Risk Score for Secondary Prevention, TRS 2°P).

Methods

We identified patients with CVD in a large health system, including atherosclerotic CVD (ASCVD), split into 80% training and 20% test sets. A rich set of EHR patient features was extracted. ML models were trained to estimate 5-year CVD event risk (random forests (RF), gradient-boosted machines (GBM), extreme gradient-boosted models (XGBoost), logistic regression with an L2 penalty and L1 penalty (Lasso)). ML models and TRS 2°P were evaluated by the area under the receiver operating characteristic curve (AUC).

Results

The cohort included 32 192 patients (median age 74 years, with 46% female, 63% non-Hispanic white and 12% Asian patients and 23 475 patients with ASCVD). There were 4010 events over 5 years of follow-up. ML models demonstrated good overall performance; XGBoost demonstrated AUC 0.70 (95% CI 0.68 to 0.71) in the full CVD cohort and AUC 0.71 (95% CI 0.69 to 0.73) in patients with ASCVD, with comparable performance by GBM, RF and Lasso. TRS 2°P performed poorly in all CVD (AUC 0.51, 95% CI 0.50 to 0.53) and ASCVD (AUC 0.50, 95% CI 0.48 to 0.52) patients. ML identified nontraditional predictive variables including education level and primary care visits.

Conclusions

In a multiethnic real-world population, EHR-based ML approaches significantly improved CVD risk stratification for secondary prevention.
Upadacitinib in patients with psoriatic arthritis and an inadequate response to non-biological therapy: 56-week data from the phase 3 SELECT-PsA 1 study
Authors: McInnes Iain B , Kato Koji , Magrey Marina , Merola Joseph F , Kishimoto Mitsumasa , Pacheco-Tena César , Haaland Derek , Chen Liang , Duan Yuanyuan , Zueger Patrick , Liu John , Lippe Ralph , Pangan Aileen L , Behrens Frank
Published: October 2021

Background

In SELECT-PsA 1, a randomised double-blind phase 3 study, upadacitinib 15 mg and 30 mg were superior to placebo and non-inferior to adalimumab in ≥20% improvement in American College of Rheumatology (ACR) criteria at 12 weeks in patients with psoriatic arthritis (PsA). Here, we report 56-week efficacy and safety in patients from SELECT-PsA 1.

Methods

Patients received upadacitinib 15 mg or 30 mg once daily, adalimumab 40 mg every other week for 56 weeks or placebo through week 24 switched thereafter to upadacitinib 15 mg or 30 mg until week 56. Efficacy endpoints included the proportion of patients achieving ≥20%/50%/70% improvement in ACR criteria (ACR20/50/70), ≥75%/90%/100% improvement in Psoriasis Area and Severity Index (PASI75/90/100), minimal disease activity (MDA) and change from baseline in modified total Sharp/van der Heijde Score. Treatment-emergent adverse events per 100 patient years (PY) were summarised.

Results

Consistent with results through week 24, ACR20/50/70, PASI75/90/100 and MDA responses were maintained with upadacitinib through week 56 and were generally numerically higher than with adalimumab; inhibition of radiographic progression was also maintained. Patients who switched from placebo to upadacitinib exhibited comparable improvements at week 56 as patients originally randomised to upadacitinib. The rates of serious adverse events were 9.1 events/100 PY with upadacitinib 15 mg and 12.3 events/100 PY with upadacitinib 30 mg. Two deaths were reported in each of the upadacitinib groups.

Conclusion

Efficacy across various domains of PsA were maintained with upadacitinib 15 mg and 30 mg through week 56 with no new safety signals observed.
Potential effect of beetroot juice supplementation on exercise economy in well-trained females
Authors: Forbes Stacey P.A. , Spriet Lawrence L.
Published: October 2021

This study examined if acute dietary nitrate supplementation (140 mL beetroot juice, BRJ) would reduce oxygen consumption (V̇O2) during cycling at power outputs of 50 and 70% maximal oxygen consumption in 14 well-trained female Canadian University Ringette League athletes. BRJ had no effect on V̇O2 or heart rate but significantly reduced ratings of perceived exertion (RPE) at both intensities. Individually, 4 participants responded to BRJ supplementation with a ≥3% reduction in V̇O2 at the higher power output.

Novelty: Acute BRJ supplementation did not improve exercise economy in well-trained females, but significantly reduced RPE. However, 4/14 subjects did respond with a ≥3% V̇O2 reduction.
Changing winter diet of Thick-billed Murres (Uria lomvia) in southwest Greenland, 1990s versus 2010s
Authors: Merkel Flemming Ravn , Linnebjerg Jannie Fries , Andersen Ole Gorm Norden , Huffeldt Nicholas Per , Jansen Teunis , Hedeholm Rasmus , Frederiksen Morten
Published: October 2021

Southwest Greenland constitutes an internationally important wintering area for seabirds, including Thick-billed Murres (Uria lomvia (Linnaeus, 1758)), but their prey may be affected by the general warming of this sub-Arctic region. We compared murre diet collected in winter in the 1990s and in the 2010s around Nuuk, Greenland. Fish made up 36% of the diet (wet mass) and crustaceans 63% in the 1990s, changing to 22% and 78% in the 2010s, respectively. Capelin (Mallotus villosus (Müller, 1776)) was the dominant fish species, and the smaller contribution in the 2010s coincided with declining densities of capelin around Nuuk. The crustaceans were dominated by two krill species (Meganyctiphanes norvegica (M. Sars, 1857) and Thysanoessa inermis (Krøyer, 1846)). However, M. norvegica was only important in the 2010s (51% wet mass), while T. inermis was dominating the 1990s with 62% wet mass and only 23% in the 2010s. The dominance of M. norvegica in the 2010s confirmed our expectations of a gradual “borealization” of this region due to the generally warming sub-Arctic. The smaller contribution of fish in the diet may also support the hypothesis of deteriorating winter conditions for murres. Apart from the diet, plastic was found in 15% of the birds and 53% had parasitic nematodes.
Exploring multi-Higgs models with softly broken large discrete symmetry groups
Authors: de Medeiros Varzielas Ivo , Ivanov Igor P. , Levy Miguel
Published: October 2021

We develop methods to study the scalar sector of multi-Higgs models with large discrete symmetry groups that are softly broken. While in the exact symmetry limit, the model has very few parameters and can be studied analytically, proliferation of quadratic couplings in the most general softly broken case makes the analysis cumbersome. We identify two sets of soft breaking terms which play different roles: those which preserve the symmetric vacuum expectation value alignment, and the remaining terms which shift it. Focusing on alignment preserving terms, we check which structural features of the symmetric parent model are conserved and which are modified. We find remarkable examples of structural features which are inherited from the parent symmetric model and which persist even when no exact symmetry is left. The general procedure is illustrated with the example of the three-Higgs-doublet model with the softly broken symmetry group $$\Sigma (36)$$

Σ
(
36
)

.
Electrodynamics in noninertial frames
Authors: Obukhov Yuri N.
Published: October 2021

The electromagnetic theory is considered in the framework of the generally covariant approach, that is applied to the analysis of electromagnetism in noninertial coordinate and frame systems. The special-relativistic formulation of Maxwell’s electrodynamics arises in the flat Minkowski spacetime when the general coordinate transformations are restricted to a class of transformations preserving the Minkowski line element. The particular attention is paid to the analysis of the electromagnetism in the noninertial rotating reference system. For the latter case, the general stationary solution of the Maxwell equations in the absence of the electric current is constructed in terms of the two scalar functions satisfying the Poisson and the biharmonic equations with an arbitrary charge density as a matter source. The classic problem of Schiff is critically revisited.
Dynamical gravastars from the interaction between scalar fields and matter
Authors: Cabo Montes de Oca Alejandro , Suarez Fontanella Duvier , Valls-Gabaud David
Published: October 2021

Gravastars are configurations of compact singularity-free gravitational objects which are interesting alternatives to classical solutions in the strong gravitational field regime. Although there are no static star-like solutions of the Einstein–Klein–Gordon equations for real scalar fields, we show that dynamical gravastars solutions arise through the direct interaction of a scalar field with matter. Two configurations presented here show that, within the internal zone, the scalar field plays a role similar to a cosmological constant, while it decays at large distances as the Yukawa potential. Like classical gravastars, these solutions exhibit small values of the temporal metric component near a transitional radial value, although this behaviour is not determined by the de Sitter nature of the internal space-time, but rather by a slowly-varying scalar field. The scalar field-matter interaction is able to define trapping forces that rigorously confine the polytropic gases to the interior of a sphere. At the surface of these spheres, pressures generated by the field-matter interaction play the role of “walls” preventing the matter from flowing out. These solutions predict a stronger scattering of the accreting matter with respect to Schwarzschild black holes.
Temperature profile characterization with fluorescence lifetime imaging microscopy in a thermophoretic chip
Authors: Lee Namkyu , Afanasenkau Dzmitry , Rinklin Philipp , Wolfrum Bernhard , Wiegand Simone
Published: October 2021

This study introduces a thermophoretic lab-on-a-chip device to measure the Soret coefficient. We use resistive heating of a microwire on the chip to induce a temperature gradient, which is measured by fluorescence lifetime imaging microscopy (FLIM). To verify the functionality of the device, we used dyed polystyrene particles with a diameter of 25 nm. A confocal microscope is utilized to monitor the concentration profile of colloidal particles in the temperature field. Based on the measured temperature and concentration differences, we calculate the corresponding Soret coefficient. The same particles have been recently investigated with thermal diffusion forced Rayleigh scattering (TDFRS) and we find that the obtained Soret coefficients agree with literature results. This chip offers a simple way to study the thermophoretic behavior of biological systems in multicomponent buffer solutions quantitatively, which are difficult to study with optical methods solely relying on the refractive index contrast.

Graphic abstract
On the angular momentum and spin of generalized electromagnetic field for r-vectors in (k, n) space-time dimensions
Authors: Martinez Alfonso , Colombaro Ivano , Font-Segura Josep
Published: October 2021

This paper studies the relativistic angular momentum for the generalized electromagnetic field, described byr-vectors in (k, n) space-time dimensions, with exterior-algebraic methods. First, the angular-momentum tensor is derived from the invariance of the Lagrangian to space-time rotations (Lorentz transformations), avoiding the explicit need of the canonical tensor in Noether’s theorem. The derivation proves the conservation law of angular momentum for generic values ofr,k, andn. Second, an integral expression for the flux of the tensor across a$$(k+n-1)$$(k+n-1)-dimensional surface of constant$$\ell $$ℓ-th space-time coordinate is provided in terms of the normal modes of the field; this analysis is a natural generalization of the standard analysis of electromagnetism, i. e. a three-dimensional space integral at constant time. Third, a brief discussion on the orbital angular momentum and the spin of the generalized electromagnetic field, including their expression in complex-valued circular polarizations, is provided for generic values ofr,k, andn.
Propagation of diverse ultrashort pulses in optical fiber to Triki–Biswas equation and its modulation instability analysis
Authors: Sulaiman Tukur Abdulkadir , Yusuf Abdullahi , Yusuf Bashir , Baleanu Dumitru
Published: October 2021

This paper presents the modulation instability (MI) analysis and the different types of optical soliton solutions of the Triki–Biswas model equation. The aforesaid model equation is the generalization of the derivative nonlinear Schrödinger equation which describes the ultrashort pulse propagation with non-Kerr dispersion. The study is carried out by means of a novel efficient integration scheme. During this work, a sequence of optical solitons is produced that may have an important in optical fiber systems. The results show that the studied model hypothetically has incredibly rich optical soliton solutions. The constraint conditions for valid soliton solutions are also reported. The gained results show that the applied method is efficient, powerful and can be applied to various complex models with the help of representative calculations.
A Bayesian Inference Reliability Evaluation on the Corrosion-Affected Underground High-Voltage Power Grid
Authors: Zhou Hang , Li Fan , Le Blanc Michelle , Pan Jingzhe
Published: October 2021

The underground high-voltage power transmission cables are high value engineering assets that suffer from multiple deteriorations through-out life cycles. Recent studies identified a new failure mode – the pitting corrosion deterioration on the layer of phosphor bronze reinforcing tape, which protects the oil-filled power transmission cables from oil leakage due to deterioration of the leads heath. Two models estimating the phosphor bronze tape life were established separately in this study. The first model, based on mathematical fitting, is generated using a replacement priority model from the power supply industry. This is considered as an empirical-based model. The second model, based on the corrosion fatigue mechanism, utilizes the information of the pit depth distribution and the concept of pit-to-crack transfer probability. The Bayesian inference approach is the conjunction algorithm to update the existing probability of failure (PoF) model with the newly identified failure modes. Through this algorithm, the integrated PoF model contains a more comprehensive background information while maintaining the empirical knowledge on the engineering assets’ performance.
The existence of n-Auslander–Reiten sequences via determined morphisms
Authors: Xie Zongyang , Liu Zhongkui , Yang Xiaoyan
Published: October 2021

Let [Formula: see text] be a commutative artinian ring and [Formula: see text] a small Ext-finite Krull–Schmidt [Formula: see text]-abelian [Formula: see text]-category with enough projectives and injectives. We introduce two full subcategories [Formula: see text] and [Formula: see text] of [Formula: see text] in terms of the representable functors from the stable category of [Formula: see text] to category of finitely generated [Formula: see text]-modules. Moreover, we define two additive functors [Formula: see text] and [Formula: see text], which are mutually quasi-inverse equivalences between the stable categories of this two full subcategories. We give an equivalent characterization on the existence of [Formula: see text]-Auslander–Reiten sequences using determined morphisms.
Project Success: What is the Role of Project Team Morale and How It Can Be Boosted?
Authors: Aronson Zvi H. , Lechler Thomas G.
Published: October 2021

This research presents and validates a model of project team morale and its influence on project success. We operationally define morale in project-based work as a multi-faceted variable encompassing suggested definitions offered in former studies. Unlike past research, we investigate the mediating effects between these facets of morale and success. A structural equation model is proposed and empirically tested to investigate the interdependencies between the facets of project team morale and how they promote project success. The results show that project team morale explains 25% of the variance in project success. Findings provide project leaders with a tool to enhance project success by influencing employees’ morale, rather than solely focusing on traditional project planning and controlling activities. We provide practical implications for project team leadership and performance.
Double Roman domination subdivision number in graphs
Authors: Amjadi J. , Sadeghi H.
Published: October 2021

For a graph [Formula: see text], a double Roman dominating function is a function [Formula: see text] having the property that if [Formula: see text], then vertex [Formula: see text] must have at least two neighbors assigned [Formula: see text] under [Formula: see text] or one neighbor with [Formula: see text], and if [Formula: see text], then vertex [Formula: see text] must have at least one neighbor with [Formula: see text]. The weight of a double Roman dominating function [Formula: see text] is the value [Formula: see text]. The double Roman domination number of a graph [Formula: see text], denoted by [Formula: see text], equals the minimum weight of a double Roman dominating function on [Formula: see text]. The double Roman domination subdivision number [Formula: see text] of a graph [Formula: see text] is the minimum number of edges that must be subdivided (each edge in [Formula: see text] can be subdivided at most once) in order to increase the double Roman domination number. In this paper, we first show that the decision problem associated with sd[Formula: see text] is NP-hard and then establish upper bounds on the double Roman domination subdivision number for arbitrary graphs.
Smart Surgical Light: Identification of Surgical Field States Using Time of Flight Sensors
Authors: Itabashi Yuta , Nakamura Fumihiko , Kajita Hiroki , Saito Hideo , Sugimoto Maki
Published: October 2021

This work presents a method for identifying surgical field states using time-of-flight (ToF) sensors equipped with a surgical light. It is important to understand the surgical field state in a smart surgical room. In this study, we aimed to identify surgical field states by using 28 ToF sensors with a surgical light installed on each. In the experimental condition, we obtained a sensor dataset by changing the number of people, posture, and movement state of a person under the surgical light. The identification accuracy of the proposed system was evaluated by applying machine learning techniques. This system can be realized simply by attaching ToF sensors to the surface of an existing surgical light.
Tracking Anthropomorphizing Behavior in Human-Robot Interaction
Authors: Fischer Kerstin
Published: October 2021

Existing methodologies to describe anthropomorphism in human-robot interaction often rely either on specific one-time responses to robot behavior, such as keeping the robot's secret, or on post hoc measures, such as questionnaires. Currently, there is no method to describe the dynamics of people's behavior over the course of an interaction and in response to robot behavior. In this paper, I propose a method that allows the researcher to trace anthropomorphizing and non-anthropomorphizing responses to robots dynamically moment-by-moment over the course of human-robot interactions. I illustrate this methodology in a case study and find considerable variation between participants, but also considerable intrapersonal variation in the ways the robot is anthropomorphized. That is, people may respond to the robot as if it was another human in one moment and to its machine-like properties in the next. These findings may influence explanatory models of anthropomorphism.
Psychometric Evaluation of the Cybersecurity Concept Inventory
Authors: Poulsen Seth , Herman Geoffrey L. , Peterson Peter A. H. , Golaszewski Enis , Gorti Akshita , Oliva Linda , Scheponik Travis , Sherman Alan T.
Published: October 2021

We present a psychometric evaluation of a revised version of theCybersecurity Concept Inventory (CCI), completed by 354 students from 29 colleges and universities. The CCI is a conceptual test of understanding created to enable research on instruction quality in cybersecurity education. This work extends previous expert review and small-scale pilot testing of the CCI. Results show that the CCI aligns with a curriculum many instructors expect from an introductory cybersecurity course, and that it is a valid and reliable tool for assessing what conceptual cybersecurity knowledge students learned.
An Interpretable Machine Learning Model Enhanced Integrated CPU-GPU DVFS Governor
Authors: Park Jurn-Gyu , Dutt Nikil , Lim Sung-Soo
Published: October 2021

Modern heterogeneous CPU-GPU-based mobile architectures, which execute intensive mobile gaming/graphics applications, use software governors to achieve high performance with energy-efficiency. However, existing governors typically utilize simple statistical or heuristic models, assuming linear relationships using a small unbalanced dataset of mobile games; and the limitations result in high prediction errors for dynamic and diverse gaming workloads on heterogeneous platforms. To overcome these limitations, we propose an interpretable machine learning (ML) model enhanced integrated CPU-GPU governor: (1) It builds tree-based piecewise linear models (i.e., model trees) offline considering both high accuracy (low error) and interpretable ML models based on mathematical formulas using a simulatability operation counts quantitative metric. And then (2) it deploys the selected models for online estimation into an integrated CPU-GPU Dynamic Voltage Frequency Scaling governor. Our experiments on a test set of 20 mobile games exhibiting diverse characteristics show that our governor achieved significant energy efficiency gains of over 10% (up to 38%) improvements on average in energy-per-frame with a surprising-but-modest 3% improvement in Frames-per-Second performance, compared to a typical state-of-the-art governor that employs simple linear regression models.
Impact of Anthropomorphic Robot Design on Trust and Attention in Industrial Human-Robot Interaction
Authors: Onnasch Linda , Hildebrandt Clara Laudine
Published: October 2021

The application of anthropomorphic features to robots is generally considered beneficial for
human-robot interaction (HRI
). Although previous research has mainly focused on social robots, the phenomenon gains increasing attention in industrial human-Robot interaction as well. In this study, the impact of anthropomorphic design of a collaborative industrial robot on the dynamics of trust and visual attention allocation was examined. Participants interacted with a robot, which was either anthropomorphically or non-anthropomorphically designed. Unexpectedly, attribute-based trust measures revealed no beneficial effect of anthropomorphism but even a negative impact on the perceived reliability of the robot. Trust behavior was not significantly affected by an anthropomorphic robot design during faultless interactions, but showed a relatively steeper decrease after participants experienced a failure of the robot. With regard to attention allocation, the study clearly reveals a distracting effect of anthropomorphic robot design. The results emphasize that anthropomorphism might not be an appropriate feature in industrial HRI as it not only failed to reveal positive effects on trust, but distracted participants from relevant task areas which might be a significant drawback with regard to occupational safety in HRI.
Social Robot Co-Design Canvases: A Participatory Design Framework
Authors: Axelsson Minja , Oliveira Raquel , Racca Mattia , Kyrki Ville
Published: October 2021

Design teams of social robots are often multidisciplinary, due to the broad knowledge from different scientific domains needed to develop such complex technology. However, tools to facilitate multidisciplinary collaboration are scarce. We introduce a framework for the participatory design of social robots and corresponding canvas tool for participatory design. The canvases can be applied in different parts of the design process to facilitate collaboration between experts of different fields, as well as to incorporate prospective users of the robot into the design process. We investigate the usability of the proposed canvases with two social robot design case studies: a robot that played games online with teenage users and a librarian robot that guided users at a public library. We observe through participants’ feedback that the canvases have the advantages of (1) providing structure, clarity, and a clear process to the design; (2) encouraging designers and users to share their viewpoints to progress toward a shared one; and (3) providing an educational and enjoyable design experience for the teams.
Horizontal Auto-Scaling for Multi-Access Edge Computing Using Safe Reinforcement Learning
Authors: Ray Kaustabha , Banerjee Ansuman
Published: October 2021

Multi-Access Edge Computing (MEC) has emerged as a promising new paradigm allowing low latency access to services deployed on edge servers to avert network latencies often encountered in accessing cloud services. A key component of the MEC environment is an auto-scaling policy which is used to decide the overall management and scaling of container instances corresponding to individual services deployed on MEC servers to cater to traffic fluctuations. In this work, we propose a Safe Reinforcement Learning (RL)-based auto-scaling policy agent that can efficiently adapt to traffic variations to ensure adherence to service specific latency requirements. We model the MEC environment using a Markov Decision Process (MDP). We demonstrate how latency requirements can be formally expressed in Linear Temporal Logic (LTL). The LTL specification acts as a guide to the policy agent to automatically learn auto-scaling decisions that maximize the probability of satisfying the LTL formula. We introduce a quantitative reward mechanism based on the LTL formula to tailor service specific latency requirements. We prove that our reward mechanism ensures convergence of standard Safe-RL approaches. We present experimental results in practical scenarios on a test-bed setup with real-world benchmark applications to show the effectiveness of our approach in comparison to other state-of-the-art methods in literature. Furthermore, we perform extensive simulated experiments to demonstrate the effectiveness of our approach in large scale scenarios.
Social Catalysts: Characterizing People Who Spark Conversations Among Others
Authors: Saveski Martin , Kooti Farshad , Morelli Vitousek Sylvia , Diuk Carlos , Bartlett Bryce , Adamic Lada A.
Published: October 2021

People assume different and important roles within social networks. Some roles have received extensive study: that of influencers who are well-connected, and that of brokers who bridge unconnected parts of the network. However, very little work has explored another potentially important role, that of creating opportunities for people to interact and facilitating conversation between them. These individuals bring people together and act as social catalysts. In this paper, we test for the presence of social catalysts on the online social network Facebook. We first identify posts that have spurred conversations between the poster's friends and summarize the characteristics of such posts. We then aggregate the number of catalyzed comments at the poster level, as a measure of the individual's "catalystness." The top 1% of such individuals account for 31% of catalyzed interactions, although their network characteristics do not differ markedly from others who post as frequently and have a similar number of friends. By collecting survey data, we also validate the behavioral measure of catalystness: a person is more likely to be nominated as a social catalyst by their friends if their posts prompt discussions between other people more frequently. The measure, along with other conversation-related features, is one of the most predictive of a person being nominated as a catalyst. Although influencers and brokers may have gotten more attention for their network positions, our findings provide converging evidence that another important role exists and is recognized in online social networks.
Understanding Families' Non-/Use Practices and Choices: The Case of Smart Speakers and Smart Interactive Toys
Authors: Garg Radhika
Published: October 2021

Over the past few years, in-home smart technologies have dramatically increased and changed. This paper aims to investigate how families of different socioeconomic status use or forgo the use of smart devices, specifically smart speakers and smart interactive toys. To this end, we interviewed 14 parents with low socioeconomic status and 16 parents with high socioeconomic status from varied races and different levels of education, lifestyles, and occupations. Our findings reveal how socioeconomic differences reflect and impact use of these devices in terms of parenting aids, parents' regulation of children's use, and the non-use practices of families. In the end, we discuss the implications of our findings and provide design recommendations for smart speakers and smart toys that address the diverse values and preferences of families from different socioeconomic backgrounds.
Exploring the Experiences of Streamers with Visual Impairments
Authors: Jun Joonyoung , Seo Woosuk , Park Jihyeon , Park Subin , Jung Hyunggu
Published: October 2021

Live streaming refers to the broadcast of real-time videos, allowing people to have synchronous interactions. While researchers' interest in live streaming has increased recently, the accessibility of live streaming for people with visual impairments is still under-examined. Further studies are necessary to gain a better understanding of how streamers with visual impairments (SVI) engage in various activities on live streaming platforms. Based on semi-structured interviews with 14 participants, we identified SVI's motivations for live streaming, their unique interactions with videos and people on live streaming platforms, and the challenges they face during live streaming. Our analysis of the identified themes revealed the absence of an SVI-centered community and accessibility issues for SVI while learning to live stream, use tools, and interact with people. Based on the results of this study, we present design opportunities to better support SVI on live streaming platforms.
"The Smartest Decision for My Future": Social Media Reveals Challenges and Stress During Post-College Life Transition
Authors: Gong Crystal , Saha Koustuv , Chancellor Stevie
Published: October 2021

The post-college transition is a critical period where individuals experience unique challenges and stress before, during, and after graduation. Individuals often use social media to discuss and share information, advice, and support related to post-college challenges in online communities. These communities are important as they fill gaps in institutional support between college and post-college plans. We empirically study the challenges and stress expressed on social media around this transition as students graduate college and move into emerging adulthood. We assembled a dataset of about 299,000 Reddit posts between 2008 and 2020 about the post-college transition from 10 subreddits. We extracted top concerns, challenges, and conversation points using unsupervised Latent Dirichlet Allocation (LDA). Then, we combined the results of LDA with binary transfer learning to identify stress expressions in the dataset (classifier performance at F1=0.94). Finally, we explore temporal patterns in stress expressions, and the variance of per-topic stress levels throughout the year. Our work highlights more deliberate and focused understanding of the post-college transition, as well as useful research and design impacts to study transient cohorts in need of support.
Hide and Seek: Choices of Virtual Backgrounds in Video Chats and Their Effects on Perception
Authors: Hwang Angel Hsing-Chi , Wang Cheng Yao , Yang Yao-Yuan , Won Andrea Stevenson
Published: October 2021

In two studies, we investigate how users choose virtual backgrounds and how these backgrounds influence viewers' impressions. In Study 1, we created a web prototype allowing users to apply different virtual backgrounds to their camera views and asked users to select backgrounds that they believed would change viewers' perceptions of their personality traits. In Study 2, we then applied virtual backgrounds picked by participants in Study 1 to a subset of videos drawn from the First Impression Dataset. We then ran a series of three online experiments on Amazon Mechanical Turk (MTurk) to compare participants' personality trait ratings for subjects (1) with the selected virtual backgrounds, (2) with the original video backgrounds, and (3) with a gray screen as a background. The selected virtual backgrounds did not change the personality trait ratings in the intended direction. Instead, virtual background use of any kind results in a consistent "muting effect" that mitigates very high or low ratings (i.e., compressing ratings to the mean level) compared to the ratings of the video with the original background.
Parental Facilitation of Young Children's Technology-based Learning Experiences from Nondominant Groups During the COVID-19 Pandemic
Authors: Yu Junnan , Granados Julisa , Hayden Ronni , Roque Ricarose
Published: October 2021

The COVID-19 pandemic has dramatically shifted family life across home, work, and education, especially families from nondominant groups. As schools and other educational programs moved online, parents became the primary facilitators for their children's learning. In this work, we conducted semi-structured interviews with 22 parents from nondominant groups. Insights from interviews highlight the technology-based learning experiences of young children during the pandemic, how parents facilitated these learning experiences, and the challenges parents and children encountered in these learning experiences. We summarize four parental facilitation patterns for children's learning (i.e., designing learning, finding resources, managing, and teaching) and highlight equity issues in distance learning, such as unequal access to learning resources and quality education. Finally, we further reflect on potential solutions to address the challenges parents have reported and share implications for designing technologies that better address children's and parents' needs during a crisis.
Seeing Like an Infrastructure: Low-resolution Citizens and the Aadhaar Identification Project
Authors: Singh Ranjit , Jackson Steven
Published: October 2021

Large-scale data systems play a central role in how state bureaucracies come to know and manage citizens. Such systems are endemically uneven in implementation, producing distributed and exclusionary consequences that are among their most important effects. These systems also operate as infrastructures in the rich and complex sense of the term that has been a core contribution of CSCW to the wider computing and social science fields. Building on James Scott's work on 'seeing like a state', we conceptualize 'seeing like an infrastructure' as a more supple analytic perspective that maps the distributed work and uneven consequences through which designers, bureaucrats, and users (here, citizens) assign or claim representation in the consequential data systems that increasingly shape and define citizenship. Drawing on eighteen months of ethnographic fieldwork into Aadhaar, India's biometrics-based identification project, and studies of infrastructure, marginalization, and citizenship in CSCW and allied fields, we argue that this perspective provides crucial insight into the strategies and mechanisms by which effective access to the basic rights and entitlements of citizenship are granted, claimed, and at times undermined. More specifically, we show how challenges in implementing Aadhaar's three key processes-enrollment, seeding, and authentication-give rise to a spectrum of resolution in which the rights and entitlements of 'high-resolution citizens' are expanded, while those of 'low-resolution citizens' are curtailed.?
Do Datasets Have Politics? Disciplinary Values in Computer Vision Dataset Development
Authors: Scheuerman Morgan Klaus , Hanna Alex , Denton Emily
Published: October 2021

Data is a crucial component of machine learning. The field is reliant on data to train, validate, and test models. With increased technical capabilities, machine learning research has boomed in both academic and industry settings, and one major focus has been on computer vision. Computer vision is a popular domain of machine learning increasingly pertinent to real-world applications, from facial recognition in policing to object detection for autonomous vehicles. Given computer vision's propensity to shape machine learning research and impact human life, we seek to understand disciplinary practices around dataset documentation - how data is collected, curated, annotated, and packaged into datasets for computer vision researchers and practitioners to use for model tuning and development. Specifically, we examine what dataset documentation communicates about the underlying values of vision data and the larger practices and goals of computer vision as a field. To conduct this study, we collected a corpus of about 500 computer vision datasets, from which we sampled 114 dataset publications across different vision tasks. Through both a structured and thematic content analysis, we document a number of values around accepted data practices, what makes desirable data, and the treatment of humans in the dataset construction process. We discuss how computer vision datasets authors value efficiency at the expense of care; universality at the expense of contextuality; impartiality at the expense of positionality; and model work at the expense of data work. Many of the silenced values we identify sit in opposition with social computing practices. We conclude with suggestions on how to better incorporate silenced values into the dataset creation and curation process.
Contestability For Content Moderation
Authors: Vaccaro Kristen , Xiao Ziang , Hamilton Kevin , Karahalios Karrie
Published: October 2021

Content moderation systems for social media have had numerous issues of bias, in terms of race, gender, and ability among many others. One proposal for addressing such issues in automated decision making is by designing for contestability, whereby users can shape and influence how decisions are made. In this study, we conduct a series of participatory design workshops with participants from communities that have experienced problems with social media content moderation in the past. Together with participants, we explore the idea of designing for contestability in content moderation and find that users' designs suggest three fruitful, practical avenues: adding representation, improving communication, and designing with compassion. We conclude with design recommendations drawn from participants' proposals, and reflect on the challenges that remain.
Aging in Place Together: The Journey Towards Adoption and Acceptance of Stairlifts in Multi-Resident Homes
Authors: Soubutts Ewan , Ayobi Amid , Eardley Rachel , Cater Kirsten , O'Kane Aisling Ann
Published: October 2021

Stairlifts are a widely-used technology in the home that help people with mobility issues to go up and down stairs. However, it is unclear how stairlifts are experienced by all household members and what this understanding implies for home healthcare technologies. We investigated the impact of stairlift installations on older adults' households in the UK through a qualitative study investigating the lived experience of the adoption and acceptance of this technology. Interviews and focus groups with primary users, household residents and service providers showed how the wider household identify misalignments between simplified stairlift installation models from service providers and describe a more complex, nuanced emotional journey which involves decision making, conflict and trauma and catharsis and independence. Findings provide transferrable outcomes for the smart home domain by highlighting the multi-resident home, the emotional intrusiveness of home healthcare technologies and the diversity that comes with providing care, unique to every household.
With Help from Afar: Cross-Local Communication in an Online COVID-19 Pandemic Community
Authors: Tsai Chun-Hua , Gui Xinning , Kou Yubo , Carroll John M.
Published: October 2021

Crisis informatics research has examined geographically bounded crises, such as natural or man-made disasters, identifying the critical role of local and hyper-local information focused on one geographic area in crisis communication. The COVID-19 pandemic represents an understudied kind of crisis that simultaneously hits locales across the globe, engendering an emergent form of crisis communication, which we term cross-local communication. Cross-local communication is the exchange of crisis information between geographically dispersed locales to facilitate local crisis response. To unpack this notion, we present a qualitative study of an online migrant community of overseas Taiwanese who supported fellow Taiwanese from afar. We detail four distinctive types of cross-local communication: situational updates, risk communication, medical consultation, and coordination. We discuss how the current pandemic situation brings new understandings to crisis informatics and online health community literature, and what role digital technologies could play in supporting cross-local communication.
Infrastructuring Telehealth in (In)Formal Patient-Doctor Contexts
Authors: Bhat Karthik S , Jain Mohit , Kumar Neha
Published: October 2021

Telehealth technologies have long remained on the peripheries of healthcare systems that prioritize in-person healthcare provision. The spread of the COVID-19 pandemic has foregrounded the need to formalize telehealth infrastructures, particularly teleconsultations, to ensure continued care provision through remote mechanisms. In the Indian healthcare context, prior to the pandemic, teleconsultations have been used to substitute for in-person consultations when possible, and to facilitate remote follow-up care without exacerbating pressures on limited personal resources. We conducted a survey and interview study to investigate doctors' and patients' perceptions, experiences, and expectations around teleconsultations, and how these contribute towards supplementing healthcare infrastructures in India, focusing on the changes brought about by the COVID-19 pandemic. In this paper, we describe the efforts of our participants towards infrastructuring telehealth, examining how technologies were adapted to support teleconsultation, how expectations shifted, and how the dynamics of caregiving evolved through this transition. We present implications for the future design and uptake of telehealth, arguing that COVID-19's impact on teleconsultations lays the foundation for new telehealth infrastructures for more inclusive and equitable care.
Implications for Supporting Marginalized Job Seekers: Lessons from Employment Centers
Authors: Dillahunt Tawanna R. , Garvin Matthew , Held Marcy , Hui Julie
Published: October 2021

Rapid changes in technology are expected to limit the availability of decent work for millions of people worldwide. This particularly disadvantages socially and economically marginalized job seekers who are already being pushed into lower-wage precarious work with increasing levels of job insecurity. While the number of employment support tools that match job seekers to employers has been growing, marginalized job seekers still significantly rely on physical employment centers that have a track record of supporting the specific needs associated with marginalization and economic constraints. We drew from prior HCI and CSCW literature uncovering the employment and technology-related challenges that marginalized job seekers face and from the Psychology of Working Theory to frame our research questions and results. To complement this prior work, we investigated how employment center staff work with marginalized job seekers and moderate factors to securing decent work. We found in an interview of 21 employment center staff--career advisors and business services coordinators--that they performed significant work to prepare and encourage marginalized job seekers in applying to positions, while also training employers to be more inclusive and open-minded. Career advisors worked directly with job seekers to connect them with external resources, provide encouragement, strategize long-term goals, and mitigate feelings of stigma. Business services coordinators worked directly with employers to prepare job positions and employee support programs. Drawing from the expertise of employment centers, we contribute a framework for designing employment support tools that better serve the needs of marginalized job seekers, and outline tangible design implications that complement the support these organizations provide.
Tensions and Mitigations: Understanding Concerns and Values around Smartphone Data Collection for Public Health Emergencies
Authors: Watson Colin , Ali Ridita , Smeddinck Jan David
Published: October 2021

Smartphones increasingly serve as the source for, or to aggregate, a considerable amount of data that can be relevant in public health emergencies. Hence the sharing and utilisation of mobile health data, for example to help control the spread of communicable diseases, has become a relevant issue, with the COVID-19 pandemic adding a sudden urgency mirrored in debates around contact tracing apps. Building on exploratory work that indicated user perceptions and values around consent, and the notion that smartphones and mobile health data can be perceived as elements of self-embodiment, we present an online study comparing three scenarios of representative diseases undertaken during the first wave lockdown in the UK. Using a mixed-methods analysis of responses from 86 participants, we identify tensions and mitigations in user values and from those present the description of four characteristic user-groups that can inform considerations for design and development activities in this space.
Reporting the Community Beat: Practices for Moderating Online Discussion at a News Website
Authors: McInnis Brian , Ajmani Leah , Sun Lu , Hou Yiwen , Zeng Ziwen , Dow Steven P.
Published: October 2021

Due to challenges around low-quality comments and misinformation, many news outlets have opted to turn off commenting features on their websites. The New York Times (NYT), on the other hand, has continued to scale up its online discussion resources to reach large audiences. Through interviews with the NYT moderation team, we present examples of how moderators manage the first ~24 hours of online discussion after a story breaks, while balancing concerns about journalistic credibility. We discuss how managing comments at the NYT is not merely a matter of content regulation, but can involve reporting from the "community beat" to recognize emerging topics and synthesize the multiple perspectives in a discussion to promote community. We discuss how other news organizations---including those lacking moderation resources---might appropriate the strategies and decisions offered by the NYT. Future research should investigate strategies to share and update the information generated about topics in the news through the course of content moderation.