bluuebunny/crossref_metadata_2025 huggingface dataset:
Who Should Act? Distancing and Vulnerability in Technology Practitioners' Accounts of Ethical Responsibility
Authors: Popova Kristina , Figueras Clàudia , Höök Kristina , Lampinen Airi
Published: April 2024

Attending to emotion can shed light on why recognizing an ethical issue and taking responsibility for it can be so demanding. To examine emotions related to taking or not taking responsibility for ethical action, we conducted a semi-structured interview study with 23 individuals working in interaction design and developing AI systems in Scandinavian countries. Through a thematic analysis of how participants attribute ethical responsibility, we identify three ethical stances, that is, discursive approaches to answering the question 'who should act': an individualised I-stance ("the responsibility is mine"), a collective we-stance ("the responsibility is ours"), and a distanced they-stance ("the responsibility is someone else's"). Further, we introduce the concepts of distancing and vulnerability to analyze the emotion work that these three ethical stances place on technology practitioners in situations of low- and high-scale technology development, where they have more or less control over the outcomes of their work. We show how the we- and they-stances let technology practitioners distance themselves from the results of their activity, while the I-stance makes them more vulnerable to emotional and material risks. By illustrating the emotional dimensions involved in recognizing ethical issues and embracing responsibility, our study contributes to the field of Ethics in Practice. We argue that emotions play a pivotal role in technology practitioners' decision-making process, influencing their choices to either take action or refrain from doing so.
Designing for Agonism: 12 Workers' Perspectives on Contesting Technology Futures
Authors: Jing Felicia S. , Berger Sara E. , Becerra Sandoval Juana Catalina , Pepper Kristin , Wheeler April M. , Mayoral Paula Redondo , Lokesh Divya , Feng Alice , Mijalkovic Marija , Bao Chaoyun , Dholakia Sara , Goyal Mohit
Published: April 2024

In this paper, we gather 12 workers from a large technology company, as recent participants of a research initiative on the social impact of emerging technologies, to present a collaborative analysis of the opportunities and limitations of dissensus-based approaches to technology research and design. We introduce a series of speculative and deconstructive probes and present findings from their use in four collaborative design sessions. We then draw on the theoretical tradition of Agonism to identify moments of friction, refusal, and disagreement over the course of these sessions. We contend that this approach offers a politically important alternative to consensus-based collaborative design methods and can even surface new rhetorics of contestation within discourses on technology futures. We conclude with a discussion of the importance of worker-authored research and an initial set opportunities, challenges, and paradoxes as a resource for future efforts to "Design for Agonism."
Form-From: A Design Space of Social Media Systems
Authors: Zhang Amy X. , Bernstein Michael S. , Karger David R. , Ackerman Mark S.
Published: April 2024

Social media systems are as varied as they are pervasive. They have been almost universally adopted for a broad range of purposes including work, entertainment, activism, and decision making. As a result, they have also diversified, with many distinct designs differing in content type, organization, delivery mechanism, access control, and many other dimensions. In this work, we aim to characterize and then distill a concise design space of social media systems that can help us understand similarities and differences, recognize potential consequences of design choice, and identify spaces for innovation. Our model, which we call Form-From, characterizes social media based on (1) the form of the content, either threaded or flat, and (2) from where or from whom one might receive content, ranging from spaces to networks to the commons. We derive Form-From inductively from a larger set of 62 dimensions organized into 10 categories. To demonstrate the utility of our model, we trace the history of social media systems as they traverse the Form-From space over time, and we identify common design patterns within cells of the model.
The Hidden Burden: Encountering and Managing (Unintended) Stigma in Children with Serious Illnesses
Authors: Su Zhaoyuan , Kamath Sunil P. , Tirakitsoontorn Pornchai , Chen Yunan
Published: April 2024

Families managing serious health conditions in children are often burdened not only by the challenge of health management but also by the heavy weight of stigma. To assist these families, various physical and digital support systems have been established to address their emotional and informational needs. We interviewed 32 children and parents living with serious chronic pulmonary illnesses to gain insights into their experiences with both their conditions and support systems. We discovered that, although a wide range of support systems were available, most participants chose to engage selectively with or completely withdraw from them. Using the ecological systems theory, we elucidate the presence of health-related and unintended stigmas associated with support systems across different ecological layers. Our work provides a comprehensive and dynamic perspective on these stigmas, considering technological, interpersonal, institutional, and social factors. By examining how stigma arises in social interactions, we introduce and delve into the concept of "stigma work" and offer design considerations for more empathetic support systems that attend to individuals and groups with stigmatized health conditions, identities, or experiences.
What Makes Digital Support Effective? How Therapeutic Skills Affect Clinical Well-Being
Authors: Yang Wenjie , Fang Anna , Shah Raj Sanjay , Mathur Yash , Yang Diyi , Zhu Haiyi , Kraut Robert E.
Published: April 2024

Online mental health support communities, in which volunteer counselors provide accessible mental and emotional health support, have grown in recent years. Despite millions of people using these platforms, the clinical effectiveness of these communities on mental health symptoms remains unknown. Although volunteers receive some training on the therapeutic skills proven effective in face-to-face environments, such as active listening and motivational interviewing, it is unclear how the usage of these skills in an online context affects people's mental health. In our work, we collaborate with one of the largest online peer support platforms and use both natural language processing and machine learning techniques to examine how one-on-one support chats on the platform affect clients' depression and anxiety symptoms. We measure how characteristics of support-providers, such as their experience on the platform and use of therapeutic skills (e.g. affirmation, showing empathy), affect support-seekers' mental health changes. Based on a propensity-score matching analysis to approximate a random-assignment experiment, results shows that online peer support chats improve both depression and anxiety symptoms with a statistically significant but relatively small effect size. Additionally, support providers' techniques such as emphasizing the autonomy of the client lead to better mental health outcomes. However, we also found that the use of some behaviors, such as persuading and providing information, are associated with worsening of mental health symptoms. Our work provides key understanding for mental health care in the online setting and designing training systems for online support providers.
Which Linguistic Cues Make People Fall for Fake News? A Comparison of Cognitive and Affective Processing
Authors: Lutz Bernhard , Adam Marc , Feuerriegel Stefan , Pröllochs Nicolas , Neumann Dirk
Published: April 2024

Fake news on social media has large, negative implications for society. However, little is known about what linguistic cues make people fall for fake news and, hence, how to design effective countermeasures for social media. In this study, we seek to understand which linguistic cues make people fall for fake news. Linguistic cues (e.g., adverbs, personal pronouns, positive emotion words, negative emotion words) are important characteristics of any text and also affect how people process real vs. fake news. Specifically, we compare the role of linguistic cues across both cognitive processing (related to careful thinking) and affective processing (related to unconscious automatic evaluations). To this end, we performed a within-subject experiment where we collected neurophysiological measurements of 42 subjects while these read a sample of 40 real and fake news articles. During our experiment, we measured cognitive processing through eye fixations, and affective processing in situ through heart rate variability. We find that users engage more in cognitive processing for longer fake news articles, while affective processing is more pronounced for fake news written in analytic words. To the best of our knowledge, this is the first work studying the role of linguistic cues in fake news processing. Altogether, our findings have important implications for designing online platforms that encourage users to engage in careful thinking and thus prevent them from falling for fake news.
Understanding the Relationship Between Social Identity and Self-Expression Through Animated Gifs on Social Media
Authors: Wang Marx , Bhuiyan Md Momen , Rho Eugenia Ha Rim , Luther Kurt , Lee Sang Won
Published: April 2024

GIFs afford a high degree of personalization, as they are often created from popular movie and video clips with diverse and realistic characters, each expressing a nuanced emotional state through a combination of characters' own unique bodily gestures and distinctive visual backgrounds. These properties of high personalization and embodiment provide a unique window for exploring how individuals represent and express themselves on social media through the lens of the GIFs they use. In this study, we explore how Twitter users express their gender and racial identities through characters in GIFs. We conducted a behavioral study (n=398) to simulate a series of tweeting and GIF-picking scenarios. We annotated the gender and race identities of GIF characters, and we found that gender and race identities have significant impacts on users' GIF choices: men chose more gender-matching GIFs than women, and White participants chose more race-matching GIFs than Black participants. We also found that users' prior familiarity with the source of a GIF and perceptions about the composition of the audience (viz., having a matching identity) have significant effects on whether a user will choose race- and gender-matching GIFs. This work has implications for practitioners supporting personalized social identity construction and impression management mechanisms online.
Quantum Control Machine: The Limits of Control Flow in Quantum Programming
Authors: Yuan Charles , Villanyi Agnes , Carbin Michael
Published: April 2024

Quantum algorithms for tasks such as factorization, search, and simulation rely on control flow such as branching and iteration that depends on the value of data in superposition. High-level programming abstractions for control flow, such as switches, loops, higher-order functions, and continuations, are ubiquitous in classical languages. By contrast, many quantum languages do not provide high-level abstractions for control flow in superposition, and instead require the use of hardware-level logic gates to implement such control flow.

The reason for this gap is that whereas a classical computer supports control flow abstractions using a program counter that can depend on data, the typical architecture of a quantum computer does not analogously provide a program counter that can depend on data in superposition. As a result, the complete set of control flow abstractions that can be correctly realized on a quantum computer has not yet been established.

In this work, we provide a complete characterization of the properties of control flow abstractions that are correctly realizable on a quantum computer. First, we prove that even on a quantum computer whose program counter exists in superposition, one cannot correctly realize control flow in quantum algorithms by lifting the classical conditional jump instruction to work in superposition. This theorem denies the ability to directly lift general abstractions for control flow such as the λ-calculus from classical to quantum programming.

In response, we present the necessary and sufficient conditions for control flow to be correctly realizable on a quantum computer. We introduce the quantum control machine, an instruction set architecture featuring a conditional jump that is restricted to satisfy these conditions. We show how this design enables a developer to correctly express control flow in quantum algorithms using a program counter in place of logic gates.
Cocoon: Static Information Flow Control in Rust
Authors: Lamba Ada , Taylor Max , Beardsley Vincent , Bambeck Jacob , Bond Michael D. , Lin Zhiqiang
Published: April 2024

Information flow control (IFC) provides confidentiality by enforcing noninterference, which ensures that high-secrecy values cannot affect low-secrecy values. Prior work introduces fine-grained IFC approaches that modify the programming language and use non-standard compilation tools, impose run-time overhead, or report false secrecy leaks—all of which hinder adoption.

This paper presents Cocoon, a Rust library for static type-based IFC that uses the unmodified Rust language and compiler. The key insight of Cocoon lies in leveraging Rust’s type system and procedural macros to establish an effect system that enforces noninterference. A performance evaluation shows that using Cocoon increases compile time but has no impact on application performance. To demonstrate Cocoon’s utility, we retrofitted two popular Rust programs, the Spotify TUI client and Mozilla’s Servo browser engine, to use Cocoon to enforce limited confidentiality policies
Forge: A Tool and Language for Teaching Formal Methods
Authors: Nelson Tim , Greenman Ben , Prasad Siddhartha , Dyer Tristan , Bove Ethan , Chen Qianfan , Cutting Charles , Del Vecchio Thomas , LeVine Sidney , Rudner Julianne , Ryjikov Ben , Varga Alexander , Wagner Andrew , West Luke , Krishnamurthi Shriram
Published: April 2024

This paper presents the design of
Forge
, a tool for teaching formal methods gradually. Forge is based on the widely-used Alloy language and analysis tool, but contains numerous improvements based on more than a decade of experience teaching Alloy to students. Although our focus has been on the classroom, many of the ideas in Forge likely also apply to training in industry.

Forge offers a
progression of languages
that improve the learning experience by only gradually increasing in expressive power. Forge supports
custom visualization
of its outputs, enabling the use of widely-understood domain-specific representations. Finally, Forge provides a variety of
testing features
to ease the transition from programming to formal modeling. We present the motivation for and design of these aspects of Forge, and then provide a substantial evaluation based on multiple years of classroom use.
PP-CSA: Practical Privacy-Preserving Software Call Stack Analysis
Authors: Wang Zhaoyu , Ma Pingchuan , Wang Huaijin , Wang Shuai
Published: April 2024

Software call stack is a sequence of function calls that are executed during the runtime of a software program. Software call stack analysis (CSA) is widely used in software engineering to analyze the runtime behavior of software, which can be used to optimize the software performance, identify bugs, and profile the software. Despite the benefits of CSA, it has recently come under scrutiny due to concerns about privacy. To date, software is often deployed at user-side devices like mobile phones and smart watches. The collected call stacks may thus contain privacy-sensitive information, such as healthy information or locations, depending on the software functionality. Leaking such information to third parties may cause serious privacy concerns such as discrimination and targeted advertisement.

This paper presents PP-CSA, a practical and privacy-preserving CSA framework that can be deployed in real-world scenarios. Our framework leverages local differential privacy (LDP) as a principled privacy guarantee, to mutate the collected call stacks and protect the privacy of individual users. Furthermore, we propose several key design principles and optimizations in the technical pipeline of PP-CSA, including an encoder-decoder scheme to properly enforce LDP over software call stacks, and several client/server-side optimizations to largely improve the efficiency of PP-CSA. Our evaluation over real-world Java and Android programs shows that our privacy-preserving CSA pipeline can achieve high utility and privacy guarantees while maintaining high efficiency. We have released our implementation of PP-CSA as an open-source project at https://github.com/wangzhaoyu07/PP-CSA for results reproducibility. We will provide more detailed documents to support and the usage and extension of the community.
Exploring the Perspectives of Social VR-Aware Non-Parent Adults and Parents on Children's Use of Social Virtual Reality
Authors: Fiani Cristina , Saeghe Pejman , McGill Mark , Khamis Mohamed
Published: April 2024

Social Virtual Reality (VR), where people meet in virtual spaces via 3D avatars, is used by children and adults alike. Children experience new forms of harassment in social VR where it is often inaccessible to parental oversight. To date, there is limited understanding of how parents and non-parent adults within the child social VR ecosystem perceive the appropriateness of social VR for different age groups and the measures in place to safeguard children. We present results of a mixed-methods questionnaire (N=149 adults, including 79 parents) focusing on encounters with children in social VR and perspectives towards children's use of social VR. We draw novel insights on the frequency of social VR use by children under 13 and current use of, and future aspirations for, child protection interventions. Compared to non-parent adults, parents familiar with social VR propose lower minimum ages and are more likely to allow social VR without supervision. Adult users experience immaturity from children in social VR, while children face abuse, encounter age-inappropriate behaviours and self-disclose to adults. We present directions to enhance the safety of social VR through pre-planned controls, real-time oversight, post-event insight and the need for evidence-based guidelines to support parents and platforms around age-appropriate interventions.
What Does a Downvote Do? Performing Complementary and Competing Knowledge Practices on an Online Platform
Authors: Seredko Alena , Hillman Thomas
Published: April 2024

Large-scale online platforms powered by user-generated content are extensively researched as venues of learning and knowledge production. In this ethnographically oriented study, we examine knowledge practices on a community question answering platform for computer programmers in relation to the platform mechanics of voting. Grounded in the practice theoretical perspective and drawing on the analysis of online discussion threads and platform-related online materials, our study unpacks the dominant practice of crowd-based curation, the complementing practice of distributed moderation, and the more marginal practice of providing feedback to content producers. The practices co-exist in tension and consonance, which are embedded in the materiality of the platform and are continuously enacted through user discursive boundary work, sustaining the mentioned practices as intelligible for other users, and outlining what counts as legitimately participation on the platform. The study contributes to existing research on the roles voting plays on online platforms, as well as offers implications for research on social and material organization of users' online practices. The study also discusses that it is the ambiguity around the mechanics of voting that allows practices to co-exist. While this ambiguity is often discussed by users as problematic, we suggest as potential implication of our study that it may be productive to design platforms for workable forms of ambiguity allowing knowledge practices to co-exist in tension and to provide space for user negotiations of these practices.
Modeling Health Video Consumption Behaviors on Social Media: Activities, Challenges, and Characteristics
Authors: Liu Jiaying , Zhang Yan
Published: April 2024

Many people now watch health videos, such as diet, exercise, mental health, COVID-19, and chronic disease videos, on social media. Most existing studies focused on video creators, leaving the motivations and practices of viewers underexplored. We interviewed 18 participants, surveyed 121 respondents, and derived a model characterizing consumers' video consumption practices on social media. The practices include five main activities: deciding to watch videos driven by various motivations, accessing videos on social media through a socio-technical ecosystem, watching videos to meet informational, emotional, and entertainment needs, evaluating the credibility and interestingness of videos, and using videos to achieve health goals. Through an iterative video consumption process, individuals strategically navigate across multiple platforms, seeking better accessibility, higher reliability, and cultivating a stronger motivation. They actively look for longer and more in-depth videos. We further identified challenges consumers face while consuming health videos on social media and discussed design implications and directions for future research.
Narrative Characteristics in Refugee Discourse: An Analysis of American Public Opinion on the Afghan Refugee Crisis After the Taliban Takeover
Authors: Dogan Hulya , Nguyen Kiet , Lourentzou Ismini
Published: April 2024

The United States (U.S.) military withdrawal from Afghanistan in August 2021 was met with turmoil as the Taliban regained control of most of the country, including Kabul. These events have affected many and were widely discussed on social media, especially in the U.S. In this work, we focus on Twitter discourse regarding these events, especially potential opinion shifts over time and the effect social media posts by established U.S. legislators might have had on online public reception. To this end, we investigate two datasets on the war in Afghanistan, consisting of Twitter posts by self-identified U.S. accounts and conversation threads initiated by U.S. politicians. We find that Twitter users' discussions revolve around the Kabul airport event, President Biden's handling of the situation, and people affected by the U.S. withdrawal. Microframe analysis indicates that discourse centers the humanitarianism underlying these occurrences and politically leans liberal, focusing on care and fairness. Lastly, network analysis shows that Republicans are far more active on Twitter compared to Democrats and there is more positive sentiment than negative in their conversations.
A Roadmap for Applying the Contextual Integrity Framework in Qualitative Privacy Research
Authors: Kumar Priya C. , Zimmer Michael , Vitak Jessica
Published: April 2024

Privacy is an important topic in HCI and social computing research, and the theory of contextual integrity (CI) is increasingly used to understand how sociotechnical systems-and the new kinds of information flows they introduce-can violate privacy. In empirical research, CI can serve as a conceptual framework for explaining the contextual nature of privacy as well as an analytical framework for evaluating privacy attitudes and behaviors. Analytical applications of CI in HCI primarily employ quantitative methods to identify appropriate information flows but rarely engage with the full CI framework to evaluate such flows. In this paper, we present a roadmap to guide HCI and social computing researchers on how to apply the full CI framework to qualitative projects. To help researchers envision what such an analysis can look like, each step includes an example analysis using interview data from projects on privacy and fitness tracking. We conclude by discussing how harnessing the full CI framework can address critiques of CI and identify opportunities for further theory development.
A Meta-Analysis of Vulnerability and Trust in Human–Robot Interaction
Authors: Mckenna Peter E. , Ahmad Muneeb I. , Maisva Tafadzwa , Nesset Birthe , Lohan Katrin , Hastie Helen
Published: April 2024

In human–robot interaction studies, trust is often defined as a process whereby a trustor makes themselves
vulnerable
to a trustee. The role of vulnerability however is often overlooked in this process but could play an important role in the gaining and maintenance of trust between users and robots. To better understand how vulnerability affects human–robot trust, we first reviewed the literature to create a conceptual model of vulnerability with four vulnerability categories. We then performed a meta-analysis, first to check the overall contribution of the variables included on trust. The results showed that overall, the variables investigated in our sample of studies have a positive impact on trust. We then conducted two multilevel moderator analysis to assess the effect of vulnerability on trust, including: (1) an intercept model that considers the relationship between our vulnerability categories and (2) a non-intercept model that treats each vulnerability category as an independent predictor. Only model 2 was significant, suggesting that to build trust effectively, research should focus on improving robot performance in situations where the users are unsure how reliable the robot will be. As our vulnerability variable is derived from studies of human–robot interaction and researcher reflections about the different risks involved, we relate our findings to these domains and make suggestions for future research avenues.
Enhanced Watermarking for Paper-Based Digital Microfluidic Biochips
Authors: Li Jian-De , Wang Sying-Jyan , Li Katherine Shu-Min , Ho Tsung-Yi
Published: April 2024

Paper-based digital microfluidic biochip (PB-DMFB) technology provides a promising solution to many biochemical applications. However, the PB-DMFB manufacturing process may suffer from potential security threats. For example, a Trojan insertion attack may affect the functionality of PB-DMFBs. To ensure the correct functionality of PB-DMFBs, we propose a watermarking scheme to hide information in the PB-DMFB layout, which allows users to check design integrity and authenticate the source of the PB-DMFB design. As a result, the proposed method serves as a countermeasure against Trojan insertion attacks in addition to proof of authorship.
On the Opportunities and Challenges of Offline Reinforcement Learning for Recommender Systems
Authors: Chen Xiaocong , Wang Siyu , McAuley Julian , Jannach Dietmar , Yao Lina
Published: April 2024

Reinforcement learning serves as a potent tool for modeling dynamic user interests within recommender systems, garnering increasing research attention of late. However, a significant drawback persists: its poor data efficiency, stemming from its interactive nature. The training of reinforcement learning-based recommender systems demands expensive online interactions to amass adequate trajectories, essential for agents to learn user preferences. This inefficiency renders reinforcement learning-based recommender systems a formidable undertaking, necessitating the exploration of potential solutions. Recent strides in offline reinforcement learning present a new perspective. Offline reinforcement learning empowers agents to glean insights from offline datasets and deploy learned policies in online settings. Given that recommender systems possess extensive offline datasets, the framework of offline reinforcement learning aligns seamlessly. Despite being a burgeoning field, works centered on recommender systems utilizing offline reinforcement learning remain limited. This survey aims to introduce and delve into offline reinforcement learning within recommender systems, offering an inclusive review of existing literature in this domain. Furthermore, we strive to underscore prevalent challenges, opportunities, and future pathways, poised to propel research in this evolving field.
gem5-NVDLA: A Simulation Framework for Compiling, Scheduling, and Architecture Evaluation on AI System-on-Chips
Authors: Lai Chengtao , Zhang Wei
Published: April 2024

Recent years have seen an increasing trend in designing AI accelerators together with the rest of the system, including CPUs and memory hierarchy. This trend calls for high-quality simulators or analytical models that enable such kind of co-exploration. Currently, the majority of such exploration is supported by AI accelerator analytical models. But such models usually overlook the non-trivial impact of congestion of shared resources, non-ideal hardware utilization and non-zero CPU scheduler overhead, which could only be modeled by cycle-level simulators. However, most simulators with full-stack toolchains are proprietary to corporations, and the few open-source simulators are suffering from either weak compilers or limited space of modeling. This framework resolves these issues by proposing a compilation and simulation flow to run arbitrary Caffe neural network models on the NVIDIA Deep Learning Accelerator (NVDLA) with gem5, a cycle-level simulator, and by adding more building blocks including scratchpad allocation, multi-accelerator scheduling, tensor-level prefetching mechanisms, and a DMA-aided embedded buffer to map workload to multiple NVDLAs. The proposed framework has been tested and verified on a set of convolution neural networks, showcasing the capability of modeling complex buffer management strategies, scheduling policies, and hardware architectures. As a case study of this framework, we demonstrate the importance of adopting different buffering strategies for activation and weight tensors in AI accelerators to acquire remarkable speedup.
Circular Steel for Fast Decarbonization: Thermodynamics, Kinetics, and Microstructure Behind Upcycling Scrap into High-Performance Sheet Steel
Authors: Raabe Dierk , Jovičević-Klug Matic , Ponge Dirk , Gramlich Alexander , Kwiatkowski da Silva Alisson , Grundy A. Nicholas , Springer Hauke , Souza Filho Isnaldi , Ma Yan
Published: April 2024

Steel production accounts for approximately 8% of all global CO2 emissions, with the primary steelmaking route using iron ores contributing approximately 80% of those emissions, mainly due to the use of fossil-based reductants and fuel. Hydrogen-based reduction of iron oxide is an alternative for primary synthesis. However, to counteract global warming, decarbonization of the steel sector must proceed much faster than the ongoing transition kinetics in primary steelmaking. Insufficient supply of green hydrogen is a particular bottleneck. Realizing a higher fraction of secondary steelmaking is thus gaining momentum as a sustainable alternative to primary production. Steel production from scrap is well established for long products (rails, bars, wire), but there are two main challenges. First, there is not sufficient scrap available to satisfy market needs. Today, only one-third of global steel demand can be met by secondary metallurgy using scrap since many steel products have a lifetime of several decades. However, scrap availability will increase to about two-thirds of total demand by 2050 such that this sector will grow massively in the next decades. Second, scrap is often too contaminated to produce high-performance sheet steels. This is a serious obstacle because advanced products demand explicit low-tolerance specifications for safety-critical and high-strength steels, such as for electric vehicles, energy conversion and grids, high-speed trains, sustainable buildings, and infrastructure. Therefore, we review the metallurgical and microstructural challenges and opportunities for producing high-performance sheet steels via secondary synthesis. Focus is placed on the thermodynamic, kinetic, chemical, and microstructural fundamentals as well as the effects of scrap-related impurities on steel properties.
Study on the Terahertz Spectroscopy Properties of Graphene Quantum Dots Based on Microfluidic Chip
Authors: Peng Zhuang , Gao Yang , Zhang Xinrui , Zhang Boyan , Yan Bingxin , Su Bo , Cui Hailin , Zhang Cunlin
Published: April 2024

Graphene quantum dots are quasi-zero-dimensional nanomaterials with unique physical and chemical properties. This study utilized a terahertz (THz) time-domain spectroscopy system to analyze the absorption characteristics of THz-waves by graphene quantum dots at different concentrations. Additionally, we applied electric fields and magnetic field to explore the THz-wave absorption properties of graphene quantum dots in greater detail. The results indicate that the THz absorbance of graphene quantum dots is positively correlated with sample concentration and applied electric field strength. However, it is negatively correlated with the intensity of the applied magnetic field. This work combines THz technology and microfluidic devices to propose a viable methodology for conducting in-depth study on graphene quantum dots.
Supplementary Video 4 from Modeling Myeloma Dissemination In Vitro with hMSC-interacting Subpopulations of INA-6 Cells and Their Aggregation/Detachment Dynamics
Authors: Kuric Martin , Beck Susanne , Schneider Doris , Rindt Wyonna , Evers Marietheres , Meißner-Weigl Jutta , Zeck Sabine , Krug Melanie , Herrmann Marietta , Hartmann Tanja Nicole , Leich Ellen , Rudert Maximilian , Docheva Denitsa , Seckinger Anja , Hose Dirk , Jundt Franziska , Ebert Regina
Published: April 2024

Supplementary Video 4
Supplementary Video 3 from Modeling Myeloma Dissemination In Vitro with hMSC-interacting Subpopulations of INA-6 Cells and Their Aggregation/Detachment Dynamics
Authors: Kuric Martin , Beck Susanne , Schneider Doris , Rindt Wyonna , Evers Marietheres , Meißner-Weigl Jutta , Zeck Sabine , Krug Melanie , Herrmann Marietta , Hartmann Tanja Nicole , Leich Ellen , Rudert Maximilian , Docheva Denitsa , Seckinger Anja , Hose Dirk , Jundt Franziska , Ebert Regina
Published: April 2024

Supplementary Video 3
Supplementary Video 1 from Modeling Myeloma Dissemination In Vitro with hMSC-interacting Subpopulations of INA-6 Cells and Their Aggregation/Detachment Dynamics
Authors: Kuric Martin , Beck Susanne , Schneider Doris , Rindt Wyonna , Evers Marietheres , Meißner-Weigl Jutta , Zeck Sabine , Krug Melanie , Herrmann Marietta , Hartmann Tanja Nicole , Leich Ellen , Rudert Maximilian , Docheva Denitsa , Seckinger Anja , Hose Dirk , Jundt Franziska , Ebert Regina
Published: April 2024

Supplementary Video 1
Supplementary Methods from Modeling Myeloma Dissemination In Vitro with hMSC-interacting Subpopulations of INA-6 Cells and Their Aggregation/Detachment Dynamics
Authors: Kuric Martin , Beck Susanne , Schneider Doris , Rindt Wyonna , Evers Marietheres , Meißner-Weigl Jutta , Zeck Sabine , Krug Melanie , Herrmann Marietta , Hartmann Tanja Nicole , Leich Ellen , Rudert Maximilian , Docheva Denitsa , Seckinger Anja , Hose Dirk , Jundt Franziska , Ebert Regina
Published: April 2024

Supplementary Methods
FIGURE 4 from Modeling Myeloma Dissemination In Vitro with hMSC-interacting Subpopulations of INA-6 Cells and Their Aggregation/Detachment Dynamics
Authors: Kuric Martin , Beck Susanne , Schneider Doris , Rindt Wyonna , Evers Marietheres , Meißner-Weigl Jutta , Zeck Sabine , Krug Melanie , Herrmann Marietta , Hartmann Tanja Nicole , Leich Ellen , Rudert Maximilian , Docheva Denitsa , Seckinger Anja , Hose Dirk , Jundt Franziska , Ebert Regina
Published: April 2024

Separation and gene expression of INA-6 subpopulations. A, Schematic of WPSC separating nMA-INA6 from MA-INA6. A coculture 96-well plate is turned upside down and attached on top of a “catching plate,” forming a “well-plate sandwich.” nMA-INA6 cells are collected in the catching plate by subsequent rounds of centrifugation and gentle washing. MA-INA6 are enzymatically dissociated from hMSCs or by rough pipetting. Subsequent RNA-seq of MSC-interacting subpopulations reveals distinct expression clusters [right, multidimensional scaling plot (n = 5)]. B, Separation was microscopically tracked after each centrifugation step. C–E, qRT-PCR of genes derived from RNA-seq results. Expression was normalized to the median of CM-INA6. Samples include those used for RNA-seq and six further cocultures (n = 11; non-detects were discarded). C, Adhesion factors, ECM proteins and matrix metalloproteinases. D, Factors involved in bone remodeling and bone homing chemokines. E, Factors involved in (immune) signaling. Statistics: (C–E): Paired t-test. Datapoints represent the mean of three (B–E) technical replicates. INA-6 were isolated from independent cocultures with hMSCs from 5 (A, B), 9 (C--E) unique donors.
FIGURE 1 from Modeling Myeloma Dissemination In Vitro with hMSC-interacting Subpopulations of INA-6 Cells and Their Aggregation/Detachment Dynamics
Authors: Kuric Martin , Beck Susanne , Schneider Doris , Rindt Wyonna , Evers Marietheres , Meißner-Weigl Jutta , Zeck Sabine , Krug Melanie , Herrmann Marietta , Hartmann Tanja Nicole , Leich Ellen , Rudert Maximilian , Docheva Denitsa , Seckinger Anja , Hose Dirk , Jundt Franziska , Ebert Regina
Published: April 2024

INA-6 growth conformations and survival on hMSCs. A, Interaction of INA-6 (green) with hMSCs (black, negative staining) at different INA-6 densities (constant hMSC densities). Scale bar = 200 µm. B, Frequency of single hMSCs (same as B) that are covered by INA-6 of varying group sizes. Technical replicates = three per datapoint; 100 single hMSCs were evaluated per technical replicate. C, Interaction of INA-6 with hMSCs at different hMSC densities (constant INA-6 densities). Scale bar = 300 µm. D, Two types of homotypic interaction: Attachment after cell contact and sustained attachment of daughter cells after cell division. Datapoints represent one of four independent time-lapse recordings, each evaluating 116 interaction events. E, Effects of hMSC-density on the viability (ATP, top) and apoptosis (Caspase3/7 activity, bottom). INA-6:MSC ratio = 4:1; Technical replicates = four per datapoint; E, Left: Signals were measured in INA-6 washed off from hMSCs and normalized by INA-6 cultured in MSC-CM (= red line; n = 4). E, Right: Signals were measured in cocultures and normalized by the sum of the signals measured in hMSC and INA-6 cultured separately ( = red line; n = 3). Statistics: Paired t test, two-factor RM-ANOVA. Datapoints represent independent cocultures with hMSCs from 3 (A, B, D, E right), 4 (E left) unique donors. Confl. = Confluent.
Machine Learning to Improve Accuracy of Transcutaneous Bilirubinometry
Authors: Morimoto Daisaku , Washio Yosuke , Fukuda Kana , Sato Takeshi , Okamura Tomoka , Watanabe Hirokazu , Yoshimoto Junko , Tanioka Maki , Tsukahara Hirokazu
Published: April 2024

Introduction: This study aimed to develop models for predicting total serum bilirubin by correcting errors of transcutaneous bilirubin using machine learning based on neonatal biomarkers that could affect spectrophotometric measurements of tissue bilirubin. Methods: This retrospective study included infants born at our hospital (≥36 weeks old, ≥2,000 g) between January 2020 and December 2022. Infants without a phototherapy history were included. Robust linear regression, gradient boosting tree, and neural networks were used for machine learning models. A neural network, inspired by the structure of the human brain, was designed comprising three layers: input, intermediate, and output. Results: Totally, 683 infants were included. The mean (minimum-maximum) gestational age, birth weight, participant age, total serum bilirubin, and transcutaneous bilirubin were 39.0 (36.0–42.0) weeks, 3,004 (2,004–4,484) g, 2.8 (1–6) days of age, 8.50 (2.67–18.12) mg/dL, and 7.8 (1.1–18.1) mg/dL, respectively. The neural network model had a root mean square error of 1.03 mg/dL and a mean absolute error of 0.80 mg/dL in cross-validation data. These values were 0.37 mg/dL and 0.28 mg/dL, smaller compared to transcutaneous bilirubin, respectively. The 95% limit of agreement between the neural network estimation and total serum bilirubin was −2.01 to 2.01 mg/dL. Unnecessary blood draws could be reduced by up to 78%. Conclusion: Using machine learning with transcutaneous bilirubin, total serum bilirubin estimation error was reduced by 25%. This integration could increase accuracy, lessen infant discomfort, and simplify procedures, offering a smart alternative to blood draws by accurately estimating phototherapy thresholds.
Speech Comprehension by Cochlear Implant Users Assessed with Evoked Potentials and Response Times
Authors: Deshpande Pushkar , Van Yper Lindsey , Christiansen Stine , Brandt Chrisitian , Debener Stefan , Neher Tobias
Published: April 2024

Introduction: Cochlear implant (CI) users differ greatly in their rehabilitation outcomes, including speech understanding in noise. This variability may be related to brain changes associated with intact senses recruiting cortical areas from stimulation-deprived senses. Numerous studies have demonstrated such cross-modal reorganization in individuals with untreated hearing loss. How it is affected by regular use of hearing devices remains unclear, however. To shed light on this, the current study measured cortical responses reflecting comprehension abilities in experienced CI users and normal-hearing controls. Methods: Using multichannel electroencephalography, we tested CI users who had used their devices for at least 12 months and closely matched controls (N = 2 × 13). Cortical responses reflecting comprehension abilities – the N400 and late positive complex (LPC) components – were evoked using congruent and incongruent digit-triplet stimuli. The participants’ task was to assess digit-triplet congruency by means of timed button presses. All measurements were performed in speech-shaped noise 15 dB above individually measured speech recognition thresholds. Three stimulus presentation modes were used: auditory-only, visual-only, and visual-then-auditory. Results: The analyses revealed no group differences in the N400 and LPC responses. In terms of response times, the CI users were slower and differentially affected by the three stimulus presentation modes relative to the controls. Conclusion: Compared to normal-hearing controls, experienced CI users may need more time to comprehend speech in noise. Response times can serve as a proxy for speech comprehension by CI users.
The Relation of Sleep Characteristics and Cognitive Impairment in Community-Dwelling Middle-Aged and Older Adults: Ardakan Cohort Study on Aging (ACSA)
Authors: Delbari Ahmad , Tabatabaei Fatemeh Sadat , Jannatdoust Payam , Azimi Amirali , Bidkhori Mohammad , Saatchi Mohammad , Foroughan Mahshid , Hooshmand Elham
Published: April 2024

Introduction: The rise in the elderly population has brought attention to mild cognitive impairment (MCI). Sleep disorders also affect many older adults, indicating an important area of research for disturbed sleep and faster brain aging. This population-based study aimed to investigate the association of several sleep indicators with cognitive performance. Methods: This cross-sectional study focused on adults over 50 in the Ardakan Cohort Study on Aging (ACSA). MCI was evaluated using the Mini-Mental State Examination (MMSE) and the Abbreviated Mental Test score (AMTS) in literate and illiterate individuals. Sleep characteristics were collected using the Pittsburgh Sleep Quality Index (PSQI), Epworth Sleepiness Scale, and Berlin questionnaire. The logistic regression models were used to analyze the data. Results: Overall, 3,380 literate and 1,558 illiterate individuals were included. In both groups, participants with MCI had a significantly higher PSQI global score (p < 0.05). Also, among the literate individuals, a significantly higher risk of having sleep-disordered breathing and poor sleep quality was observed in participants with MCI (p < 0.05). In illiterate individuals, higher sleep latency than 15 min increased odds of MCI (p < 0.05). However, after adjusting for all variables, only literate individuals with a sleep duration of more than 8 h had 66 percent increased odds of having MCI (p = 0.033). Conclusion: Sleep duration might be associated with cognitive function in the older Iranian population. Our findings underscore the importance of considering sleep patterns in relation to cognitive health.
Safety of Percutaneous Dilatational Tracheostomy in Critically Ill Patients with Liver Cirrhosis
Authors: Noy Roee , Macsi Flóra , Shkedy Yotam , Simchon Omri , Gvozdev Natalia , Epstein Danny
Published: April 2024

Introduction: Percutaneous dilatational tracheostomy (PDT) is a safe and cost-effective alternative to surgical tracheostomy. Cirrhotic patients often require ICU admission and prolonged mechanical ventilation. Patients with liver cirrhosis (LC) are known to have coagulopathy and relatively safe and simple procedures such as tracheostomy may be associated with high complication rates, specifically high bleeding rates. Current guidelines are unable to make a specific recommendation on the safety of PDT among cirrhotic patients. We aimed to evaluate the safety of PDT in critically ill patients with LC. Methods: A retrospective chart review identified critically ill patients who underwent PDT between January 2012 and March 2023. The study group was defined as all patients with a diagnosis of LC. The primary outcome was early (7-day) bleeding, categorized as minor or major. Secondary outcomes were PDT-related and 30-day all-cause mortality. Propensity score matching was performed to adjust the imbalances between the groups. Results: A total of 1,628 were included in the analysis. Thirty-three of them (2.0%) had LC. In the LC group, only 1 patient (3.0%, 95% CI: 0.0–15.8%) developed early bleeding. Intra-operative, early, late bleeding, and PDT-related mortality rates did not differ significantly between those with LC and those without. Conclusion: This retrospective cohort study indicates that PDT can be safely performed in critically ill cirrhotic patients, without significantly increasing the risk of bleeding complications.