bluuebunny/crossref_metadata_2025_split huggingface dataset:
Between Realities: Information Sharing Practices of Deepfake Creators
Authors: Vera Nick 
Published: October 2023

ABSTRACTDeepfakes are AI‐generated multimedia that convincingly graft or replace one person's likeness onto another, resulting in remarkably realistic yet fabricated content. These sophisticated manipulations challenge users' ability to discern factual visual information as they portray individuals engaging in actions and uttering words that never occurred. This research takes a unique approach by delving into the perspective of deepfake creators through the analysis of 15 tutorial videos on YouTube. By examining creators' information‐sharing practices, this study aims to identify creators' motivations for disseminating knowledge on deepfake creation and their understanding or lack of understanding of the ethical implications of sharing such information. Achieving such an understanding can play a vital role in informing the development of regulatory measures. By examining creators' intentions and comprehending their societal impact, patterns, and characteristics, this research can contribute to the creation of effective detection technologies and strengthen content platform guidelines. Analyzing deepfake creation tutorials can facilitate the implementation of targeted and comprehensive regulatory measures, enhancing protection against potential risks and misuse.
Nonsuicidal Self‐Injury and Content Moderation on TikTok
Authors: Vera Valerie 
Published: October 2023

ABSTRACTOnline nonsuicidal self‐injury communities commonly create and share information on harm reduction strategies and exchange social support on social media platforms, including the short‐form video sharing platform TikTok. While TikTok's Community Guidelines permit users to share personal experiences with mental health topics, TikTok explicitly bans content depicting, promoting, normalizing, or glorifying activities that could lead to self‐harm. As such, TikTok may moderate user‐generated content, leading to exclusion and marginalization in this digital space. Through semi‐structured interviews with eight TikTok users with a history of nonsuicidal self‐injury, this pilot study explores how users experience TikTok's algorithm to create and engage with content on nonsuicidal self‐injury. Findings demonstrate that users understand how to circumnavigate TikTok's algorithm through algospeak (i.e., codewords or turns of phrases) and signaling to maintain visibility on the platform. Further, findings emphasize that users actively engage in self‐surveillance and self‐censorship to create a safe online community. In turn, content moderation can ultimately hinder progress toward the destigmatization of nonsuicidal self‐injury and restrict social support exchanged within online nonsuicidal self‐injury communities.
Beyond Boundaries: Unraveling the Interactions between Science and Technology through Linked Topics
Authors: Wang Jiajie , Hou Wanfang , Wu Keye , Sun Jianjun 
Published: October 2023

ABSTRACTUnderstanding the interactions between science and technology (S&T) is crucial for driving major innovations. Previous studies have typically focused on identifying scientific and technical topics separately and analyzing their association through semantic or citation. In this study, we propose a novel approach to identifying linked topics that directly reflect the interactions within the S&T domain. Our approach integrates semantic characteristics and citation relationships, allowing for a comprehensive analysis of the specific content and structure of these interactions. We test our approach using a dataset of 2,821 patents and 4,626 papers from the field of genetic engineering vaccines, spanning the years 1980 to 2020. The results demonstrate that our approach provides a more direct and detailed understanding of the content and structural characteristics of S&T interactions. This research contributes to the methodology of linked topics identification in the field of S&T, offering new insights and analytical perspectives for related studies.
Differences in Open Government Information among Departments with Different Responsibilities
Authors: Wei Jingzhu , Zhang Tongrui 
Published: October 2023

ABSTRACTAlthough open government information awareness has enhanced since China implemented the Open Government Information Regulation, the complaints about the information disclosure work also increased. Previous research has ignored the impact of the department's responsibilities on information disclosure, which are essential as some departments handle information that should not be disclosed. From this standpoint, this paper is the first to analyze the differences in departments' open government information performance from their annual information openness reports. Variance and correlation analysis show that the potential harm of disclosure to third parties' legitimate rights and interests, the availability of relevant information, and duplicate requests can explain their differences in government information disclosure on request. Besides, this paper calls for an elastic criterion for openness evaluation and finds that the benchmark effect in previous research does not apply to departments with different responsibilities.
Multilingual Knowledge Organization of Cultural Routes: The Case of the Grand Canal
Authors: Wen Xinyue , Liang Shaobo , Wu Dan 
Published: October 2023

ABSTRACTThis study collects heterogeneous information from multiple sources related to the Grand Canal, a cultural route in China, to construct a multilingual ontology of the Grand Canal. The research designs a data translation, optimization, and multilingual ontology construction method to reveal the internal and external characteristics and associations of the Grand Canal, which can provide users with multilingual and ordered knowledge of the cultural route, providing a feasible solution for digital preservation and global sharing of the cultural routes. On this basis, a multilingual knowledge service system is built.
Novels and the NSTC: A Quantitative Study of Legal Deposit
Authors: Wingate Alexandra 
Published: October 2023

ABSTRACTThe Nineteenth‐Century Short Title Catalog (NSTC) attempts to provide comprehensive coverage of the print record in the English‐speaking world from 1801 to 1918 based primarily on the catalog records of Britain's five legal deposit libraries during the 19th century. Previous studies have used the NSTC to quantitatively study broad trends in Victorian‐era British publishing, but they have not sufficiently acknowledged the NSTC's limitations. This study works within the NSTC's limitations by using it to quantitatively study the phenomena of legal deposit. Analysis of two, 90‐volume random samples of first edition English novels reveals the impact of changing library acquisition practices and legal deposit legislation on the comprehensiveness of Britain's legal deposit libraries, as well as the NSTC's comprehensiveness and how it can be utilized for quantitative book history despite its deficiencies.
Measuring Unequal Knowledge Distance by Network Embedding and Multiple Relationships
Authors: Wu Keye , Kang Lele , Xie Ziyue , Du Jia Tina , Sun Jianjun 
Published: October 2023

ABSTRACTKnowledge distance, representing the dissimilarity between different knowledge units, has been considered as an important dimension of recombination novelty and technological innovation. Previous measurements merely rely on the citation relationship and ignore their directions and weights. To fill this gap, this study proposes a new measurement which not only captures the unequal citation relationship but also integrates multiple information to depict knowledge distance. The results show that our method can accurately portray the knowledge distance in both scientific areas and technical fields.
Untangle the Characteristics of Disruptive and Consolidating Citations of Nobel‐winning Papers
Authors: Yang Alex Jie , Zhao Yuehua , Wang Hao , Deng Sanhong 
Published: October 2023

ABSTRACTScientific breakthroughs have the potential to revolutionize the course of research and shape the trajectory of scientific knowledge. This study investigates the characteristics of Disruptive Citing Papers (DCP) and Consolidating Citing Papers (CCP) associated with Nobel‐winning scientific breakthroughs, aiming to provide insights into the mechanisms of knowledge creation and dissemination. By analyzing a dataset of Nobel‐winning papers and their citation networks, we find that Nobel‐winning papers tend to attract a higher proportion of DCP compared to CCP. However, CCP exhibit a higher impact, as evidenced by their citation counts and likelihood of becoming hit papers. Furthermore, DCP are associated with larger research teams, highlighting the collaborative nature of disruptive research, while CCP employ a higher degree of professional language style characterized by shorter titles and specialized jargon. These findings deepen our understanding of the role played by disruptive and consolidating impact in scientific breakthroughs, shedding light on the dynamics of knowledge creation and dissemination in the scientific community. This research contributes to the broader understanding of scientific progress and provides valuable insights for researchers, policymakers, and stakeholders in the scientific ecosystem.
Female College Students' Perceptions on the Internet Use for Reproductive Health Information
Authors: Yoon Hyunsoo , Oh Sanghee 
Published: October 2023

ABSTRACTThis study aims to explore the factors related to young women's Internet use for reproductive health information, specifically focusing on female college students. The research model is based on the Health Belief Model (HBM) and the Theory of Planned Behavior (TPB). A convenience sample of female college students who have recently used the Internet for reproductive health information will participate in an online survey. The survey will collect demographic information, background details on Internet use for reproductive health, and perceptions of reproductive health behaviors. Data analysis will examine correlations among the perceptions and their association with the intention to continue using the Internet for reproductive health information. The findings will contribute to understanding female college students' influential factors and information behaviors, informing the development of educational programs, intervention strategies, and online resources to improve reproductive health outcomes and empower young women.
Real or Fake: Eliciting Deepfake Identification Strategies through a Diary Study
Authors: Zeng Ruoyao , Song Siyi , Guo Zhengxi , Goh Dion Hoe‐Lian , Lee Chei Sian 
Published: October 2023

ABSTRACTThe prevalence of deepfake technology has led to concerns about the ability of people to spot real videos from fakes. We address these concerns through a diary study to elicit strategies people use to identify deepfake and real videos. Results indicate that different strategies were associated with deepfake and real video identification. Interestingly, popular strategies were often not as effective as less popular ones. Implications of our work are discussed.
The Spatial‐Temporal Trajectories of the Poets and the Sociocultural Environment of the Age
Authors: Zhan Yiying , Wang Xi 
Published: October 2023

ABSTRACTThis research in progress presents a deep learning‐based approach to identifying named entities, including geographical locations and poetic imagery in ancient Chinese poetry. By leveraging association rule mining, this study establishes a connection between historical events, spatial‐temporal trajectories of poets, and sociocultural phenomena of the age. From the perspective of digital humanities, this study hopes to be able to provide new evidence for socioeconomic status, cultural openness, or historical events at different ages and to picture a better view of the development of classical Chinese.
Exploring Laypeople's Engagement with AI Painting: A Preliminary Investigation into Human‐AI Collaboration
Authors: Zhang Xiaoyu , Zhu Sicheng , Zhao Yuxiang (Chris) , Hansen Preben , Zhu Qinghua 
Published: October 2023

ABSTRACTAs advancements in artificial intelligence (AI) technology have opened new avenues for artistic expression and creation, human‐AI collaboration in creative activities has garnered increasing attention. Through semi‐structured interviews with 15 participants, we investigate the intrinsic and extrinsic factors that motivate laypeople's engagement with AI painting, as well as challenges and concerns faced by users. Our findings reveal that laypeople engage with AI painting for emotional needs like entertainment, aesthetics, surprise, and curiosity, personal utilitarian needs such as self‐expression and customization, and social interaction through sharing and communication. Despite the appeal of novelty and unpredictability they also encountered challenges related to technical and system functionality, personal and environmental factors, as well as concerns about algorithm bias, pornography misuse, employment risks, copyright disputes and ethical implications. Findings provide preliminary evidence of the potential and limitations of AI in democratizing creative activities, and offer implications for designing and developing of AI assistance tools.
Understanding the Motivation of Participants in Innovation Open Data Contests: A Task Presentation Affordance Perspective
Authors: Zhang Yan , Liu Zhouying , Zhao Yuxiang (Chris) , Wu Dawei 
Published: October 2023

ABSTRACTInnovation Open Data Contest (IODC) is an effective way to take advantage of public efforts to realize the great potential value of open data in the field of digital humanities. Previous literature focusses more on the challenge open data contest rather than innovation open data contest. Given this, understanding the underlying factors motivating participants to actively engage in the contest is necessary. Based on the task affordance theory and self‐determination theory (SDT), this study aims to identify and examine how task presentation affordances of IODC influence participants' motivations and thereby shape their level of effort. We employ partial least squares structural equation modeling (PLS‐SEM) techniques to analyze the responses from 215 individuals who have previously participated in the IODC. The findings indicate that participants' level of effort in the IODC is contingent upon their perception of relatedness and competence. Moreover, hedonic affordance and connective affordance positively influence participants' perceptions of relatedness and competence. Our findings contribute to the extant literature by proposing a theoretical model to understand the participants' motivation and have practical implications for IODC's organizers.
Refining autonomous vehicle situational awareness due to varying sensor error
Authors: Costello Donald , Hanlon Nicholas , Xu Huan 
Published: October 2023

AbstractPilots use their senses and training to generate situational awareness (SA). They then use this SA to make sound aeronautical decisions. Autonomous vehicles, by contrast, cannot rely on pilot expertise in off‐nominal situations. They must rely on their onboard sensors to build SA of the environment. As these sensors degrade, it is hypothesized that a point exists where the SA generated by these sensors is inadequate to allow the autonomous vehicle to make sound aeronautical decisions. In previous work, a point was defined based on broad assumptions within a modeling and simulation environment (i.e., the error within each sensor was known and not random). This research used a larger data set that contained random errors within the sensors. The data was then used to build predictive equations through a Monte Carlo simulation in the same simulation environment as previous work. While the data showed there was a statistically significant relationship between the error values in each sensor and the fused distance value, the resulting predictive equations were not able to provide adequate SA to make sound aeronautical decisions. This research highlights multiple issues the test and evaluation community will face when trying to develop new techniques for the verification and validation of autonomous systems.
Quality Performance Indicators for the Surgical Management of Oesophageal Cancer: A Systematic Literature Review
Authors: Kulasegaran Suheelan , Wang Yijiao , Woodhouse Braden , MacCormick Andrew , Srinivasa Sanket , Koea Jonathan 
Published: October 2023

AbstractBackgroundThe objective of this systematic review was to identify pre‐existing quality performance indicators (QPIs) for the surgical management of oesophageal cancer (OC). These QPIs can be used to objectively measure and compare the performance of individual units and capture key elements of patient care to improve patient outcomes.MethodsA systematic literature search of PubMed, MEDLINE, Scopus and Embase was conducted. Articles reporting on the quality of healthcare in relation to oesophageal neoplasm or cancer and the surgical treatment of OC available until the 1st of March 2022 were included.ResultsThe final list of articles included retrospective reviews (n = 13), prospective reviews (n = 8), expert guidelines (n = 1) and consensus (n = 1). The final list of QPIs was categorized as process, outcome or structural measures. Process measures included multidisciplinary involvement, availability of multimodality diagnostic and treatment pathways and surgical metrics. Outcome measures included reoperation and readmission rates, the achievement of RO resection and length of hospital stay. Structural measures include multidisciplinary meetings.ConclusionsThis systematic review summarizes QPIs for the surgical treatment of OC. The data will serve as an introduction to establishing a quality initiative project for OC resections.
The Association between Mindful Parenting, and Internalizing and Externalizing Symptoms in Adolescence
Authors: Royuela-Colomer Estíbaliz , Orue Izaskun , Visu-Petra Laura , Fernández-González Liria 
Published: October 2023

AbstractInternalizing and externalizing symptoms are common among adolescents, and mindful parenting can play a pivotal role in their prevention. Study 1 explores the association between internalizing and externalizing symptoms and the moderating role of mindful parenting. Study 2 explores the longitudinal association between mindful parenting and externalizing symptoms and whether mindful parenting moderates the longitudinal stability of externalizing symptoms. In Study 1, 420 parents (81.9% mothers) of children aged 12 to 17 (M = 14) completed measures of mindful parenting and their children’s emotional symptoms and conduct problems. In Study 2, 151 adolescents (65.6% girls) aged 12 to 17 (M = 13.9) from Study 1 completed a measure of antisocial behavior two times one year apart. Study 1 found an association between adolescents’ emotional symptoms and conduct problems, and this association was moderated by mindful parenting. The association was significant only in adolescents whose parents reported low levels of the mindful parenting factor called “being in the moment with the child.” Study 2 found an association between antisocial behavior at Wave 1 and 2, and this longitudinal association was moderated by mindful parenting. The longitudinal relationship was statistically significant exclusively among adolescents whose parents reported low levels of “mindful discipline.” Mindful parenting seems to be a protective factor for adolescents’ externalizing symptoms. Specifically, “being in the moment with the child” can diminish the association between emotional symptoms and conduct problems, while “mindful discipline” can be beneficial for reducing the stability of antisocial behavior over time.
Fully metallic frequency selective surface (FSS) circular polarizer based on cost‐effective chemical etching manufacturing technique
Authors: Yong Wai Yan , Velkers Arjen , Glazunov Andrés Alayón 
Published: October 2023

AbstractThis letter presents a fully metallic circular polarizer based on a bandpass frequency selective surface (FSS) that converts linear polarization (LP) to circular polarization (CP) in the Ka‐band. The proposed FSS circular polarizer consists of three cascaded identical perforated metal screens. The Jerusalem slot is used as the element of the FSS circular polarizer to produce an entirely metallic screen with a compact footprint. The Jerusalem slot allows the all‐metallic design to be realized without mechanical issues. A 35 × 35 elements prototype has been designed and manufactured using a cost‐effective chemical metallic etching technique, and performed measurements agree well with the numerical simulations. At broadside direction (), the proposed polarizer operates from 27.5–30.1 GHz, while at the oblique angle of incidence , the operating frequency is reduced to 27.7–29.4 GHz. The manufactured prototype has a low insertion loss (IL), i.e. dB and a good axial ratio performance, i.e. AR ⩽ 2 dB at the desired operating frequency band. Thus, based on a cost‐effective manufacturing technique, the proposed circular polarizer demonstrates an excellent approach to devising all‐metallic FSS polarizers with good IL.
Depression recognition from facial videos: Preprocessing and scheduling choices hide the architectural contributions
Authors: Lage Cañellas Manuel , Álvarez Casado Constantino , Nguyen Le , Bordallo López Miguel 
Published: October 2023

AbstractDeep learning models have been widely applied in video‐based depression detection. It is observed that the diversity of preprocessing, data augmentation, and optimization techniques makes it difficult to fairly compare model architectures. In this study, the typical ResNet‐50 model is enhanced by using specific face alignment methods, improved data augmentation, optimization, and scheduling techniques. The extensive experiments on two popular benchmark datasets (AVEC2013 and AVEC2014) obtained competitive results, compared to sophisticated spatio‐temporal models for single streams. Moreover, the score‐level fusion approach based on two texture streams outperformed the state‐of‐the‐art methods. It achieved mean square errors of 5.82 and 5.50 on AVEC2013 and AVEC2014, respectively. These findings suggest that the preprocessing and training configurations result in noticeable improvements, which have been originally attributed to the network architectures.
Minimum detection velocity performance analysis for air moving target detection in a spaceborne surveillance radar system
Authors: Ma Jingtao , Wang Lingyu , Huang Penghui , Liao Guisheng , Zhang Xuepan 
Published: October 2023

AbstractDue to the advantages of wide coverage, continuous remote monitoring, and high measurement accuracy, the spaceborne multi‐channel surveillance radar has been widely used for the air moving target detection and tracking. In this paper, the minimum detection velocity (MDV) definition for the aerial target detection performance evaluation in a spaceborne multi‐channel radar system is analysed, where three kinds of MDV definitions based on empirical formula, output signal‐to‐clutter‐plus‐noise ratio (SCNR) loss criterion, and output SCNR criterion are discussed in detail based on theoretical analysis and simulation verification. The analysis results will provide valuable reference for the practical spaceborne radar system designment with the air target detection mode.