Miracle-dz/UniFAR-FTUs huggingface dataset:
Safety of House Dust Mite Subcutaneous Immunotherapy with a rush and cluster combination protocol in the build-up phase.

BACKGROUND Conventional and cluster subcutaneous immunotherapy (SCIT) are effective but may be time-consuming. Rush SCIT may offer a more convenient treatment option to patients and be of shorter duration; however, it is also associated with a higher incidence of systemic adverse reactions. Therefore, a combination of protocols between rush and cluster SCIT could have a superior risk-benefit ratio. OBJECTIVE To determine the safety of the combination of rush and cluster HDM-SCIT and to identify the risk factors for local and systemic adverse reactions. METHODS We retrospectively reviewed the charts of patients who received HDM-SCIT, with rush and cluster combination protocols, at a tertiary care hospital between January 2009 and December 2020. Data were collected at the initial visit (demographic data; underlying allergic disease; current medication; and laboratory investigation results including skin prick test, serum specific IgE (sIgE) levels to aeroallergen, total IgE, and eosinophil count) and follow-up visits (rate and severity of local and systemic adverse reactions). RESULTS In total, 698 injections (28 patients) were reviewed. Overall, 13 patients developed systemic adverse reactions, at 3% (21/698) per injection visit. All reactions occurred within 60 minutes. In total, 6 patients experienced large local reactions, at 1.1% (8/698) per injection visit. A high level of sIgE to D. pteronyssinus was significantly associated with systemic adverse reactions (HR = 1.02; P = 0.009). CONCLUSIONS HDM-SCIT with a combination of rush and cluster schedules in the build-up phase could be used as an alternative protocol, given its acceptable systemic adverse reaction rate and shortened duration.
Discovery of potent DNMT1 inhibitors against sickle cell disease using structural-based virtual screening, MM-GBSA and molecular dynamics simulation-based approaches

Abstract Sickle cell disease (SCD) is an autosomal recessive genetic disorder affecting millions of people worldwide. A reversible and selective DNMT1 inhibitor, GSK3482364, has been known to decrease the overall methylation activity of DNMT1, resulting in the increase of HbF levels and percentage of HbF-expressing erythrocytes in an in vitro and in vivo model. In this study, a structure-based virtual screening was done with GSK3685032, a co-crystalized ligand of DNMT1 (PDB ID: 6X9K) with an IC50 value of 0.036 μM and identified 3988 compounds from three databases (ChEMBL, PubChem and Drug Bank). Using this screening method, we identified around 15 compounds with XP docking scores greater than −8 kcal/mol. Further, prime MM-GBSA calculations have been performed and found compound SCHEMBL19716714 with the highest binding free energy of −83.31 kcal/mol. Finally, four compounds were identified based on glide energy and ΔG bind scores that have the most binding with DG7, DG19, DG20 bases and Lys1535, His1507, Trp1510, Ser1230, which were required for the target enzyme inhibition. Furthermore, molecular dynamics simulation studies of top ligands validate the stability of the docked complexes by examining root mean square deviations, root mean square fluctuations, solvent accessible surface area, and radius of gyration graphs from simulation trajectories. These findings suggest that the top four hit compounds may be capable of inhibiting DNMT1 and that additional in vitro and in vivo studies will be essential to prove the clinical effectiveness of the selected lead compounds. Communicated by Ramaswamy H. Sarma
Vertical structure and transient behavior of convective-stratiform heating in TOGA COARE from combined satellite-sounding analysis

Abstract Datasets of daily high-resolution upper-air soundings and Special Sensor Microwave/Imager (SSM/I) passive microwave measurements from the Tropical Ocean and Global Atmosphere Coupled Ocean–Atmosphere Response Experiment (TOGA COARE) intensive operation period are used for large-scale diagnostic budget calculations of the apparent heat source (Q1), the apparent moisture sink (Q2), and latent heating to investigate the mechanisms of diabatic heating and moistening processes within the TOGA COARE Intensive Flux Array (IFA). Latent-heating retrievals are obtained from The Florida State University SSM/I-based precipitation profile retrieval algorithm. The estimates are correlated well with heating calculations from the soundings in which approximately 70% of the total heating arises from latent heat release. Moisture-budget processes also have a strong relationship with the large-scale environment, in which drying from condensation is mainly balanced by large-scale horizontal convergence of moisture f.
A Novel Frequency Estimation of Sinusoid by iterative interpolation DFT algorithm

The frequency estimation of sinusoidal signal based on discrete fourier transform (DFT) is investigated, which performance is caused to decline due to the error of interpolation direction when the signal frequency is close to quantized frequency of DFT. To solve this problem, a new algorithm without weighting window is proposed. Firstly, a coarse frequency estimation in DFT spectrum is acquired, then a high-accuracy frequency near the coarse frequency by iterative interpolation is estimated. The simulation results show that errors caused by a mistaken location of the spectral line can be significantly reduced and the algorithm is simple and has good performance in mean square error and accuracy.
Low Froude Number Flow Past Three-Dimensional Obstacles. Part I: Baroclinically Generated Lee Vortices

Abstract We study the flow of a density-stratified fluid past a three-dimensional obstacle, using a numerical model. Our special concern is the response of the fluid when the Froude number is near or less than unity. Linear theory is inapplicable in this range of Froude number, and the present numerical solutions show the rich variety of phenomena that emerge in this essentially nonlinear flow regime. Two such phenomena, which occupy Parts I and II of this study, are the formation of a pair of vertically oriented vortices on the lee side and a zone of flow reversal on the windward side of the obstacle. The Ice vortices have been explained as a consequence of the separation of the viscous boundary layer from the obstacle however, this boundary layer is absent (by design) in the present experiments and lee vortices still occur. We argue that a vertical component of vorticity develops on the lee side owing to the tilting of horizontally oriented vorticity produced baroclinically as the isentropes deform in r.
Distributed Governance of a Complex Ecosystem: How R&D Consortia Orchestrate the Alzheimer’s Knowledge Ecosystem

Orchestrating an ecosystem requires coordination to create value, but prior research has tended to emphasize centralized ecosystem control over solutions involving distributed governance. By studying multilateral public-private collaborations to develop scientific knowledge to find a cure for Alzheimer’s disease, we identify a new model of ecosystem control—indirect and distributed governance using R&D consortia. We report archival and interview data on 46 consortia with overlapping corporate, nonprofit, and governmental membership. We find three models of consortia that allow member organizations to jointly orchestrate an ecosystem without centralized control. We discuss the broader implications of this model for orchestrating ecosystems.
Mind and Body: The Complex Role of Social Resources in Understanding and Managing Depression in Older Adults

Depression is the most common mental health problem in older adults; however, a lack of understanding in the interaction between physical and social causes hinders effective treatment. Unique issues such as age-specific increases in comorbid physical problems and alienation from social contact can make it difficult for health providers to identify instances of depression. These also make it difficult for depressed older adults to communicate with their social resources, such as friends, family, and health providers. Integrating technology-assisted collaboration with members of patients' social network to observe and manage multi-dimensional factors in depressed older adults' states is a potential way to improve the quality of practitioners' treatment-planning around these multi-dimensional factors, as well as provide assistance for family and friends' involvement in managing the depression. We conducted an interview study on stakeholders' perceptions of depression and communication to understand the opportunities and challenges involved in implementing such collaborative design. Interviewees included 16 depressed older adult patients, 10 of their family members, and two psychiatrists. Our findings reveal new insights into 1) patients' and families' social values and understandings of patients' condition, as well as 2) how these values and understandings influenced decision-making on communicating with each other and acting on depression. These insights have implications for the consideration of information and communication systems to aid depressed older adults' recovery and engagement with social network members.
Face Work: A Human-Centered Investigation into Facial Verification in Gig Work

Through intensive research on datasets, benchmarks, and models, the computer-vision community has taken great strides to identify the societal biases intrinsic to these technologies. Less is known about the last mile of the computer-vision machine-learning pipeline: on-the-ground integration into the real world. In this paper, I analyze facial verification technology (FVT) through its use as account verification in ride-hail work. Using a sociotechnical framework combined with empirical qualitative research methods, including interviews and analysis of an online community of workers, this research is a deep dive into recognition technologies at the level of local practice. Findings reveal the high-stakes articulation labor demanded of workers to be recognized by these systems, including maintaining multiple mobile devices, repeatedly uploading requisite images, spending time and resources visiting customer-service centers, and making physical changes to their bodies and environments. These strategies constitute repairs to the failures of computer vision in dynamic environments and are required to successfully engage in the sociotechnical interaction protocols demanded by FVT. Drawing on Erving Goffman's terminology around social interaction rituals, I term these cognitive and behavioral negotiations "face work. " Drivers' dynamic, responsive, and ad-hoc attempts to become machine-readable have significant implications for relations between identity and power in spaces of security and work, as well as for the integration of machine-learning systems into safety-critical infrastructures. Ultimately, this research emphasizes the crucial role of end users who create and maintain the conditions required for computer vision to produce judgment.
Coproducing Support Together: Sustainable and Reciprocal Civic Disaster Relief during COVID-19

COVID-19 changed society in terms of employment, food security, and mental health, affecting all segments of the population. Surging demands for a wide range of support could not be met solely by government-led disaster assistance that experienced breakdowns in the initial phase of the pandemic. The nature of the pandemic as a global, long-haul disaster necessitated sustained, diverse, and extensive civic disaster relief to complement government response. In this paper, we explore how civic disaster relief groups carry out online and offline coordination activities to engage different actors and their positive effects on individuals and local communities, drawing on interviews with civic disaster relief organizers and volunteers in the United States. We interpret our findings with the lens of coproduction that can increase the sustainability, diversity, and extent of civic relief efforts. We then suggest design implications for coproducing disaster relief and discuss the importance and benefits of involving stakeholders who are less likely to be engaged in producing relief.
Tidal and centripetal stress in a model human falling deep into a Kerr black hole

I calculate the tidal and centripetal stress in the Misner–Thorne–Wheeler model human—a rigid prism—falling into a high-spin supermassive Kerr black hole at a constant, near-equatorial latitude with high energy, enough to surmount the radial potential barrier near the throat of the black hole. The stress in the model human would be nonlethal.
Transparency, Trust, and Security Needs for the Design of Digital News Authentication Tools

Americans' trust in news is declining, and authenticity and transparency challenges in digital publishing contexts pose unique challenges to the ability to effectively gratify their information-seeking needs via online media. Cryptographic technologies and web-based provenance indicators have the potential to enhance the trustworthiness and transparency of digital communication, but better understandings of news consumers practices and needs are required to develop practical tools. Through a representative online survey of 400 digital news consumers and 19 follow-up interviews, we investigate how users authenticate and assign trust to news content, and identify specific needs pertaining to news transparency and authentication that could be met by digital news authentication tools. While many users currently rely on political ideology to assess news trustworthiness, we find that users of all political orientations see value in independent provenance and authentication tools for digital news.
Privacy Legislation as Business Risks: How GDPR and CCPA are Represented in Technology Companies' Investment Risk Disclosures

Power exercised by large technology companies has led to concerns over privacy and data protection, evidenced by the passage of legislation including the EU's General Data Protection Regulation (GDPR) and the California Consumer Privacy Act (CCPA). While much privacy research has focused on how users perceive privacy and interact with companies, we focus on how privacy legislation is discussed among a different set of relationships-those between companies and investors. This paper investigates how companies translate the GDPR and CCPA into business risks in documents created for investors. We conduct a qualitative document analysis of annual regulatory filings (Form 10-K) from nine major technology companies. We outline five ways that technology companies consider GDPR and CCPA as business risks, describing both direct and indirect ways that the legislation may affect their businesses. We highlight how these findings are relevant for the broader CSCW and privacy research communities in research, design, and practice. Creating meaningful privacy changes within existing institutional structures requires some understanding of the dynamics of these companies' decision-making processes and the role of capital.
Enacting Data Feminism in Advocacy Data Work

In this paper, we present the results of a study that examines the role of data in nonprofit advocacy work. We conducted semi-structured interviews with 25 individuals who play critical roles in the data work of 18 different advocacy organizations. Our analysis reveals five key stakeholders in advocacy data work-beneficiaries, policymakers, funding and partner organizations, gatekeepers, and local publics. It also contributes a framework of four functions of data work in nonprofit organizations-data as amplifier, activator, legitimizer, and incubator. We characterize the challenges in data work that exist, particularly in widespread attempts to reappropriate data work across functions. These challenges in reappropriation are often rooted in participants' effects to enact data feminist principles from the margins of the data economy. Finally, we discuss how nonprofit institutions operate outside of the dominant data work goals known as the three Ss (surveillance, selling, and science) and propose a fourth S, social good, that is working to challenge the norms of the data economy and should be considered in research regarding the data economy moving forward.
The Stage and the Theatre: AltspaceVR and its Relationship to Discord

Immersive virtual reality (VR) has seen growth in usage over the last few years and that growth is expected to accelerate. Correspondingly, many VR-based online communities have begun to emerge, and several social VR applications such as AltspaceVR have gained significant popularity. However, virtual reality can be isolating. Users can meet and connect with people in VR, but inevitably, when a user removes their headset, their friends are no longer there. In this paper, we look at how communities in AltspaceVR, a popular social VR application, handle this challenge. We conduct fourteen interviews and over 70 hours of participant observation and find that AltspaceVR users and communities have turned to Discord to solve many of their needs, such as facilitating more ubiquitous communication, planning community activities and AltspaceVR Events, and hosting casual social discussion. By using the communicative ecology model for our analysis, we find that AltspaceVR, Discord, and the communities that intersect the two have formed a tightly-coupled communicative ecology, which we call the "stage" and "theater". Discord acts as the "theater," where actors and crew collaborate and communicate to prepare for the main event, all the while building important social bonds. AltspaceVR acts as the "stage," where those efforts manifest in ephemeral but high-value experiences that bring the community together. Finally, we compare the communities we studied with those found in massively-multiplayer online games (MMOGs) and provide insights regarding the design of social VR applications and online communities.
Machine Learning Enabled Solutions for Design and Optimization Challenges in Networks-on-Chip based Multi/Many-Core Architectures

Due to the advancement of transistor technology, a single chip processor can now have hundreds of cores. Network-on-Chip (NoC) has been the superior interconnect fabric for multi/many-core on-chip systems because of its scalability and parallelism. Due to the rise of dark silicon with the end of Dennard Scaling, it becomes essential to design energy efficient and high performance heterogeneous NoC-based multi/many-core architectures. Because of the large and complex design space, the solution space becomes difficult to explore within a reasonable time for optimal trade-offs of energy-performance-reliability. Furthermore, reactive resource management is not effective in preventing problems from happening in adaptive systems. Therefore, in this work, we explore machine learning techniques to design and configure the NoC resources based on the learning of the system and applications workloads. Machine learning can automatically learn from past experiences and guide the NoC intelligently to achieve its objective on performance, power, and reliability. We present the challenges of NoC design and resource management and propose a generalized machine learning framework to uncover near-optimal solutions quickly. We propose and implement a NoC design and optimization solution enabled by neural networks, using the generalized machine learning framework. Simulation results demonstrated that the proposed neural networks-based design and optimization solution improves performance by 15% and reduces energy consumption by 6% compared to an existing non-machine learning-based solution while the proposed solution improves NoC latency and throughput compared to two existing machine learning-based NoC optimization solutions. The challenges of machine learning technique adaptation in multi/many-core NoC have been presented to guide future research.
Toward a Feminist Social Media Vulnerability Taxonomy

Vulnerability intimately shapes the lived human experience and continues to gain attention in computer-supported cooperative work and human-computer interaction scholarship broadly, and in social media studies specifically. Social media comprise sociotechnical affordances that may uniquely shape lived experiences with vulnerability, rendering existing frameworks inadequate for comprehensive examinations of vulnerability as mediated on social media. Through interviews with social media users in the United States (N = 20) and drawing on feminist conceptualizations of vulnerability and social media disclosure and privacy scholarship, we propose a feminist taxonomy of social media vulnerability (FSMV). The FSMV taxonomy reflects vulnerabilitysources, states, andvalences, within which we introduce the state ofnetworked vulnerability andambivalent, desired, andundesired valences. We describe how social media enable forms of vulnerability different from in-person settings, challenge framings that synonymize vulnerability with risk/harm, and facilitate interdisciplinary theory-building. Additionally, we discuss hownetworked, ambivalent, andun/desired vulnerability extend and diverge from prior work to create a theoretically rich taxonomy that is useful for future work on social media and vulnerability. Finally, we discuss implications for design related to granular control over profile, content, and privacy settings, as well as implications for platform accountability, as they pertain to social media vulnerability.
“We are Researchers, but we are also Humans”: Creating a Design Space for Managing Graduate Student Stress

Graduate students are facing a mental health crisis due to a combination of individual, community, and societal factors. Many existing stress management interventions engage with one factor at a time, typically focusing on providing a user with data about their stress state. We conducted co-design workshops with graduate students who work closely together to explore their strategies for managing stress and to learn about what types of technologies they envision to help address their stress. Using Ecological Systems Theory as an conceptual framework, our analysis of the designs and discussions from these workshops contributes an expanded design space for stress management—one that foregrounds the affordances and challenges of designing interventions that cut across ecological systems levels along with designs that approach stress management using a broader diversity of strategies: controlling, disconnecting, and normalizing stress. We argue that this expanded design space embraces a more holistic and human approach to designing stress management technologies.