bluuebunny/crossref_metadata_2025_split huggingface dataset:
Change point detection in high dimensional covariance matrix using Pillai’s statistics
Authors: Cho Seonghun , Shin Minsup , Cho Young Hyun , Lim Johan 
Published: November 2024

AbstractThis research proposes a method to test and estimate change points in the covariance structure of high-dimensional multivariate series data. Our method uses the trace of the beta matrix, known as Pillai’s statistics, to test the change in covariance matrix at each time point. We study the asymptotic normality of Pillai’s statistics for testing the equality of two covariance matrices when both sample size and dimension increase at the same rate. We test the existence of a single change point in a given time period using Cauchy combination test, the test using an weighted sum of Cauchy transformed p-values, and estimate the change point as the point whose statistic is the greatest. To test and estimate multiple change points, we use the idea of the wild binary segmentation and repeatedly apply the procedure for a single change point to each segmented period until no significant change point exists. We numerically provide the size and power of our method. We finally apply our procedure to finding abnormal behavior in the investment of a private equity fund.
Exploring the interaction of design variability and stochastic operational uncertainties in software-intensive systems through the lens of modeling
Authors: Cámara Javier 
Published: November 2024

Abstract
In software-intensive systems, navigating the complexities that emerge from the interaction of design variability and stochastic operational uncertainties presents a daunting challenge. This paper delves into the dynamics between these two dimensions of uncertainty, offering novel insights about how modeling can contribute to the analysis of their combined impact upon system properties. By elevating the abstraction level at which probabilistic models are conceptualized, our approach enables an integrated analysis framework that considers both structural and quantitative dimensions of design spaces. Through the introduction of novel language constructs, our methodology facilitates the direct referencing of structural relationships within probabilistic behavioral specifications. Furthermore, the adoption of novel quantifiers in probabilistic temporal logic enables evaluating complex properties across diverse design variants, thereby streamlining the assessment of guarantees within the solution space. We demonstrate the feasibility of this approach on four case studies, showcasing its potential to offer comprehensive insights into the trade-offs and decision-making processes inherent in managing different types of structural design variability and operational uncertainties in software-intensive systems.
A case study for automated attribute extraction from legal documents using large language models
Authors: Adhikary Subinay , Sen Procheta , Roy Dwaipayan , Ghosh Kripabandhu 
Published: November 2024

AbstractThe escalating number of pending cases is a growing concern worldwide. Recent advancements in digitization have opened up possibilities for leveraging artificial intelligence (AI) tools in the processing of legal documents. Adopting a structured representation for legal documents, as opposed to a mere bag-of-words flat text representation, can significantly enhance processing capabilities. With the aim of achieving this objective, we put forward a set of diverse attributes for criminal case proceedings. To enhance the effectiveness of automatically extracting these attributes from legal documents within a sequence labeling framework, we propose the utilization of a few-shot learning approach based on Large Language Models (LLMs). Moreover, we demonstrate the efficacy of the extracted attributes in downstream tasks, such aslegal judgment prediction and legal statute prediction.
Exploring the Implications of Working Conditions for Corporate Sustainability in Last-Mile Delivery Platform Companies
Authors: Longoni Annachiara , Salas Sergio , Sancha Cristina , Sierra Vicenta , Wiengarten Frank 
Published: November 2024

AbstractLast-mile delivery platforms have recently emerged as effective business models to match supply and demand, even though they have been criticized for potentially exploiting their workers. This paper investigates the corporate sustainability and socio-economic trade-offs of platform companies in relation to working conditions (i.e., work relationships, social subsystems, and technical subsystem). A survey of 392 paid-per-order workers from six food delivery platforms across Spain was conducted to validate our research framework. Our findings provide a nuanced understanding of the impact of working conditions on corporate sustainability in platform companies. On the one hand, there are positive implications for both social and economic sustainability in the presence of higher earnings, rights and protections, and empowerment for workers. Conversely, prolonged work relationships between workers and platform companies are negatively related to workers’ perceived stress and individual performance. Based on these insights, we advance our understanding of how platform companies can deal with conflicting objectives regarding working conditions by adopting an instrumental approach in the case of short-term workers and an integrative approach with long-term workers.
Students’ perceptions of ‘AI-giarism’: investigating changes in understandings of academic misconduct
Authors: Chan Cecilia Ka Yuk 
Published: November 2024

AbstractThis novel study explores AI-giarism, an emergent form of academic dishonesty involving AI and plagiarism, within the higher education context. The objective of this study is to investigate students’ perception of adopting generative AI for research and study purposes, and their understanding of traditional plagiarism and their perception of AI-plagiarism. A survey, undertaken by 393 undergraduate and postgraduate students from a variety of disciplines, investigated their perceptions of diverse AI-giarism scenarios. The findings portray a complex landscape of understanding with clear disapproval for direct AI content generation and ambivalent attitudes towards subtler uses of AI. The study introduces a novel instrument to explore conceptualisation of AI-giarism, offering a significant tool for educators and policy-makers. This scale facilitates understanding and discussions around AI-related academic misconduct, contributing to pedagogical design and assessment in an era of AI integration. Moreover, it challenges traditional definitions of academic misconduct, emphasising the need to adapt in response to evolving AI technology. The study provides pivotal insights for academics and policy-makers concerning the integration of AI technology in education.
Problems of the public good in higher education: building the common amid sovereign individualism, capital and the state
Authors: Marginson Simon 
Published: November 2024

Abstract
Anglophone societies in which the sovereign individual is primary vis and vis social relations, and policy focuses on economic competition and consumption in education, find it hard to grasp non-pecuniary outcomes in higher education. These include the self-formation of students as persons and collective goods like knowledge, technological capability, social inclusion, political connectedness, tolerance and global understanding. While other cultures generate insights into non-pecuniary outcomes, the paper focuses critically on meanings of ‘public’ in English: (1) public as state, (2) public good as universal well-being, (3) public as inclusive-communicative as in ‘public opinion’, (4) public and private goods in economics. None of these meanings of ‘public’ enables the resolution of the non-pecuniary outcomes of higher education. The paper tackles four central questions. First, why is there an undue emphasis on the individual and individualised pecuniary benefits, vis a vis social relations, in Euro-American and especially Anglophone societies? Second, can these societies strengthen public or common goods by augmenting the state in higher education? Third, what other practices of public and common might advance non-pecuniary outcomes? Fourth, how to advance collective outcomes beyond the nation-state? The paper finds that while Anglophone public good is constrained by the state in capitalist society, higher education’s role in the production and distribution of common good through primarily local networks, while also pressuring central states to provide support, offers a promising way forward.
Crystallization behavior and thermal properties of octa-phenyl-substituted silsesquioxane-modified polylactide (PLA)
Authors: Barczewski Mateusz , Paszkiewicz Sandra , Cañavate Javier , Aniśko Joanna , Hejna Aleksander , Piasecki Adam , Dudziec Beata 
Published: November 2024

AbstractThis study aims to understand the effects of adding octa-phenyl-substituted silsesquioxane (phSQ) on the crystallization process and thermal stability of polylactide (PLA). Nowadays, PLA is the most industrially used compostable polymer, but its uses are limited by its low crystallization and thermal degradation during processing. The possibility of introducing functionalized silsesquioxanes (SQs) to improve thermal stability and increase its crystallinity and ductility in a controlled way is desirable. The nanometric size of the Si-O-Si cage, coupled with the influence of the functional groups attached to its structure, enables it to function as a heterogeneous nucleating agent. In this work, a specially synthesized octa-phenyl-substituted SQ (phSQ) was added to the PLA in 0.5–5 wt%. Crystallization in non-isothermal and isothermal conditions was conducted and monitored using differential scanning calorimetry (DSC); the course of the spherulite formation under identical conditions to DSC was also assessed using optical microscopy in polarized light. The results showed that phSQ increases the degree of crystallinity of PLA by introducing additional sites of heterogeneous nucleation but does not increase the spherulite growth coefficient. Additionally, the analysis of thermal properties indicates that the presence of phSQ could not have a positive impact on thermal stability. The agglomeration of the nanometric particles and changes in the main structural features of the polymeric matrix could be present in the samples, affecting the obtained results.
Graphical abstract
Learning to leverage teachers’ ideas: facilitators’ growth in moderation practices with simultaneously strong goal focus and participant focus
Authors: Pöhler-Friedrich Birte , Prediger Susanne , Schwarts Gil , Karsenty Ronnie 
Published: November 2024

AbstractWhen novice facilitators start to lead teachers’ professional development (PD), they have been found to struggle to combine a strong participant focus (i.e., valuing and working with participating teachers’ needs and ideas) and goal focus (working toward the PD goals), whereas expert facilitators seem to be more able to integrate both focus. Empirical studies have identified these challenges across contexts and several situational demands, for example, when facilitators set goals, plan a PD activity, notice teachers’ ideas, and moderate video-based discussions. In this paper, we contribute to this line of research by investigating another situational demand in a longitudinal perspective: We studied how two novice facilitators moderated the discussion after the same PD activity several times. The qualitative comparative analysis of transcribed videos from PD sessions revealed that each facilitator used several practices with varying degrees of goal and participant focus. Over time, they learned to apply more practices that were, simultaneously, strongly goal and participant focused: By leveraging teachers’ ideas toward the PD content goals, they achieved integration of both focus, which have sometimes previously been experienced as conflicting. We discuss implications for facilitator preparation programs in terms of unpacking facilitation practices and explicitly working with the content elements for finer-grained goals.
When the past becomes future-like: A phenomenological study of memory, time, and self-familiarity
Authors: Ratcliffe Matthew 
Published: November 2024

AbstractThis paper sets out a phenomenological account of how the autobiographical past can, on occasion, assume certain future-like qualities. I begin by reflecting on the analogy of a bore wave, as employed in a novel by Julian Barnes. Building on this, I turn to Simone de Beauvoir and Jean-Paul Sartre in order to address how our memories are revised in light of our current concerns and vice versa. Then, by adapting Edmund Husserl’s conception of temporal “protention,” I show how acts of remembering are integral to a process of ongoing reconciliation between our current orientation towards the future and the autobiographical past. They sustain, disrupt, and reconsolidate a non-localized, dynamic sense of who we are, in ways that are inseparable from how we experience time.
The Rise of Global Health Emergency Governance
Authors: Rabi Michael 
Published: November 2024

AbstractIn this paper I shed new light on contemporary developments in global health governance, policymaking, and knowledge production. Specifically, by investigating the historical roots and emergence of global health emergency governance. Drawing on the Foucauldian notion of “problematisation” and on Science and Technology Studies of disaster, I trace, examine, and elucidate three main axes through which, I argue, health emergencies became a problem of global governance. I show, first, the formation of emergency management as a distinct professional field. Second, the migration of emergency management into global health governance and its proliferation within it. And third, the move from global health emergency management to the global governance of health emergencies. Overall, I suggest the rise of global health emergency governance provides crucial context for understanding social, political, and epistemic tensions and controversies in health emergencies such as COVID-19. Through the analysis, I identify a particular rationale that is rooted in emergency management and had become embedded in global health emergency governance. A rationale that involves “temporal compression” and “structural plasticity.” I discuss possible implications of this rationale for global health governance, policy, and knowledge.
Future-Oriented Science Learning and its Effects on Students’ Emotions, Futures Literacy and Agency in the Anthropocene
Authors: Chan Jessica , Erduran Sibel 
Published: November 2024

AbstractScience education bears the broader objective of nurturing students today to be scientifically-literate citizens of tomorrow who are able to foresee challenges, invent solutions and make responsible decisions for global issues. As a prelude to the new focus of agency in the Anthropocene, this paper presents an intervention on climate change with upper secondary students in a museum of natural history in England. Instructional strategies such as infusing scenarios and arts into scientific discussions were adopted to induce imagination, future-oriented thinking and emotional responses. Statistical results showed that the intervention significantly enhanced participants’ futures literacy, environmental agency and positive emotions. However, it did not increase their interests in learning science in out-of-school context. Implications of this study will shed light on futurising science and climate education in research and practice.
Education for Agonistic Democracy: Reclaiming the Political Insights of Agonism
Authors: Kråkenes Lars Ørjan 
Published: November 2024

AbstractWhile education for democracy has been heavily influenced by the deliberative perspective on democracy, a recent turn towards an agonistic perspective on democracy places a great deal of faith in the role of political emotion and conflict. Educational scholars have mostly interpreted agonism in relation to the emotional and conflictual experiences that occur within school. Some scholars draw general pedagogical insights from this perspective, while others use it to propose conflictual approaches to classroom discussions. Overestimating, however, the extent to which experiences of agonism within school applies to politically experienced agonisms beyond the school, is problematic. Such overestimations undermine the core political insights of agonistic theory, concerning the democratic potential of radical collective movements. Agonistic theory acknowledges the psychological need among disgruntled citizens for radical alternatives enabling them to oppose and rearticulate the established power dynamics in society. The purpose of agonistic democracy is to enable rearticulations of hegemony through the institutions of representative democracy, rather than as opposed to them. Important for this paper, however, is the argument that such rearticulations depend on the rhetorical force of collective movements. Emphasizing that we cannot assume the presence of such movements in everyday school life, the paper revisits the following question: What are the didactical implications of an agonistic perspective on democracy? The democratic potential of collective movements is not easily captured through experiences within the pedagogical context alone, but proposals are made as to how this potential can be grasped in other ways.
Exploring the Potential of Spray-Dried Blackberry Powder Enriched with Zinc and Folic Acid as a Nutritional Alternative for Children and Pregnant Women
Authors: Vega-Castro Oscar , Diego Vargas-Marulanda , Santiago Castro-Tobón , Laura Vallejo-Marulanda , Valentina Vanegas-Arboleda , Daniel Henao-González , Faver Gómez-Narváez 
Published: November 2024

AbstractCurrently, strategies to achieve the Sustainable Development Goals (SDGs) are being sought worldwide. Accordingly, this study seeks to contribute to achieving SDGs 2 (Zero Hunger) and 3 (Good Health and Well-being) by addressing nutritional deficiencies in pregnant women and children. These vulnerable populations worldwide have malnutrition problems associated with a lack of zinc and folic acid, causing them health problems. This research aimed to develop a blackberry powder fortified with zinc and folic acid obtained by spray drying as a nutritional alternative for children and pregnant women. The blackberry was characterized according to the AOAC, an optimization of the spray drying process with a central composite experimental design. The powder’s bulk and tapped density, solubility, and anthocyanin content were determined. The variation in zinc and folic acid content over a storage period was measured. The moisture content of the fresh blackberries was 89%. The solubility and anthocyanin content of blackberry powder were 86% and 0.263 mg cyanidin-3-glucose/g, respectively. The optimal spray drying conditions were: 23.6% solid content and an air inlet temperature of 167.92 °C. The bulk density of the powder did not change with storage time (p > 0.05); the zinc and folic acid content in blackberry powder was 144 and 90 (µg/100 g), respectively. A blackberry powder fortified with zinc and folic acid was obtained by spray drying, guaranteeing 30% of the daily nutritional requirement for pregnant women and children, in a 50-gram portion of powder.
Speed and Shape of Population Fronts with Density-Dependent Diffusion
Authors: Stokes Beth M. , Rogers Tim , James Richard 
Published: November 2024

AbstractThere is growing empirical evidence that animal movement patterns depend on population density. We investigate travelling wave solutions in reaction-diffusion models of animal range expansion in the case that population diffusion is density-dependent. We find that the speed of the selected wave depends critically on the strength of diffusion at low density. For sufficiently large low-density diffusion, the wave propagates at a speed predicted by a simple linear analysis. For small or zero low-density diffusion, the linear analysis is not sufficient, but a variational approach yields exact or approximate expressions for the speed and shape of population fronts.
High-precision MRI of liver and hepatic lesions on gadoxetic acid-enhanced hepatobiliary phase using a deep learning technique
Authors: Kiyoyama Haruka , Tanabe Masahiro , Hideura Keiko , Kawano Yosuke , Miyoshi Keisuke , Kamamura Naohiko , Higashi Mayumi , Ito Katsuyoshi 
Published: November 2024

Abstract
Purpose
The purpose of this study was to investigate whether the high-precision magnetic resonance (MR) sequence using modified Fast 3D mode wheel and Precise IQ Engine (PIQE), that was collected in a wheel shape with sequential data filling in the k-space in the phase encode-slice encode plane, is feasible for breath-hold (BH) three-dimensional (3D) T1-weighted imaging of the hepatobiliary phase (HBP) of gadoxetic acid-enhanced MRI in comparison to the compressed sensing (CS) sequence using Advanced Intelligent Clear-IQ Engine (AiCE).

Methods
This retrospective study included 54 patients with focal hepatic lesions who underwent dynamic contrast-enhanced MRI. Both standard HBP images using CS with AiCE and high-precision HBP images using modified Fast 3D mode wheel and PIQE were obtained. Image quality, signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR) were evaluated using the Wilcoxon signed-rank test. p values of < 0.05 were considered to be statistically significant.

Results
Scores for image noise, conspicuity of liver contours and intrahepatic structures, and overall image quality in high-precision HBP imaging using modified Fast 3D mode wheel and PIQE were significantly higher than those in HBP imaging using CS and AiCE (all p < 0.001). There was no significant difference in the presence of artifact and motion-related blurring. There were no significant differences between the sequences in SNR (p = 0.341) or CNR (p = 0.077). The detection rate of focal hepatic lesions was 71.4–85.3% in CS with AiCE, and 82.2–95.8% in modified Fast 3D mode wheel and PIQE.

Conclusion
A high-precision MR sequence using a modified Fast 3D mode wheel and PIQE is applicable for the HBP of BH 3D T1-weighted imaging.
Large language models for generative information extraction: a survey
Authors: Xu Derong , Chen Wei , Peng Wenjun , Zhang Chao , Xu Tong , Zhao Xiangyu , Wu Xian , Zheng Yefeng , Wang Yang , Chen Enhong 
Published: November 2024

AbstractInformation Extraction (IE) aims to extract structural knowledge from plain natural language texts. Recently, generative Large Language Models (LLMs) have demonstrated remarkable capabilities in text understanding and generation. As a result, numerous works have been proposed to integrate LLMs for IE tasks based on a generative paradigm. To conduct a comprehensive systematic review and exploration of LLM efforts for IE tasks, in this study, we survey the most recent advancements in this field. We first present an extensive overview by categorizing these works in terms of various IE subtasks and techniques, and then we empirically analyze the most advanced methods and discover the emerging trend of IE tasks with LLMs. Based on a thorough review conducted, we identify several insights in technique and promising research directions that deserve further exploration in future studies. We maintain a public repository and consistently update related works and resources on GitHub (LLM4IE repository).