bluuebunny/crossref_metadata_2025_split huggingface dataset:
Secure semi‐automated GDPR compliance service with restrictive fine‐grained access control
Authors: Hashem Eiza Max , Thong Ta Vinh , Shi Qi , Cao Yue 
Published: August 2024

AbstractSharing personal data with service providers is a contentious issue that led to the birth of data regulations such as the EU General Data Protection Regulation (GDPR) and similar laws in the US. Complying with these regulations is a must for service providers. For users, this compliance assures them that their data is handled the way the service provider says it will be via their privacy policy. Auditing service providers' compliance is usually carried out by specific authorities when there is a need to do so (e.g., data breach). Nonetheless, these irregular compliance checks could lead to non‐compliant actions being undetected for long periods. Users need an improved way to make sure their data is managed properly, giving them the ability to control and enforce detailed, restricted access to their data, in line with the policies set by the service provider. This work addresses these issues by providing a secure semi‐automated GDPR compliance service for both users and service providers using smart contracts and attribute‐based encryption with accountability. Privacy policies will be automatically checked for compliance before a service commences. Users can then upload their personal data with restrictive access controls extracted from the approved privacy policy. Operations' logs on the personal data during its full lifecycle will be immutably recorded and regularly checked for compliance to ensure the privacy policy is adhered to at all times. Evaluation results, using a real‐world organization policy and example logs, show that the proposed service achieves these goals with low time overhead and high throughput.
Using WindTunneling to document emergent knowledge to explore common perceptions of well‐being
Authors: Winn Karrin 
Published: August 2024

AbstractThe purpose of this paper is to discuss using WindTunneling to document emergent knowledge to explore common perceptions of well‐being. WindTunneling is a systemic research methodology to help groups navigate complex issues. In 2022, I adapted WindTunneling to document sensory‐based emergent knowledge from 978 international participants exploring 52 somatic movement activities designed to promote well‐being. Well‐being is a complex subjective condition that is difficult to measure and maintain the richness of diverse perspectives. Discovering common perceptions of well‐being using WindTunneling would partially substantiate the efficacy of movement as a well‐being intervention in context specific situations. If successful, this research design would add to the rigor of WindTunneling as a way to develop a holistic understanding of how participants perceive well‐being in relationship to their lived experience. Developing WindTunneling methodology to meet appropriate qualitative research standards would have practical significance to researchers working to measure the subjective dimension of well‐being.
Preparing Inclusive Early Childhood Educators (PIECE): A conceptualization of multilingualism, English learning, and inclusivity
Authors: Evans Leanne M. , Joseph Tatiana , Jozwik Sara , Bartlett Maggie 
Published: August 2024

AbstractThe purpose of this article is to share the examination of inclusivity as a paradigm for fostering authenticity and agency (Moore, 2017) among teacher candidates. This framing challenges the notion of inclusion as a tool of meritocracy used to manage learners through expectations that uphold monolingualism, decenter racial histories, and rely on rigid behavior plans. In this work, the authors interrogate the impact inclusion as assimilation has on English learners' authentic ways of knowing and being. Thus, they present a conceptualization of spaces of difference (Agbenyaga & Klibthong, 2012) within the context of an Inclusive Early Childhood Teacher Education (IECTE) program and the objectives of the Preparing Inclusive Early Childhood Educators (PIECE) project. With its rigorous coursework, clinical experiences, multi‐tiered mentorship, and practice‐based professional development, the PIECE project aims to develop inclusive early childhood educators at the preservice and in‐service levels. Infused throughout the PIECE project is an emphasis on cultivating the knowledge and skills needed to provide high‐quality instruction that improves educational outcomes for English learners (ELs). Frameworks of transformative theory and intersectionality perspectives provided the authors with a grounding for the work within the PIECE project community of learners (i.e., teacher candidates, teacher educators, and school district partners). This article summarizes critical concepts of inclusivity centered in the PIECE project work. These concepts include (1) understanding oneself to look beyond; (2) disrupting notions of normalcy and naturalized language; and (3) reconceptualizing inclusivity as a social justice act.
Theranostic nanoparticles for detection and treatment of pancreatic cancer
Authors: Agarwal Happy , Bynum Ryan C. , Saleh Nada , Harris Danielle , MacCuaig William M. , Kim Vung , Sanderson Emma J. , Dennahy Isabel S. , Singh Rohit , Behkam Bahareh , Gomez‐Gutierrez Jorge G. , Jain Ajay , Edil Barish H. , McNally Lacey R. 
Published: August 2024

AbstractPancreatic ductal adenocarcinoma (PDAC) is one of the most recalcitrant cancers due to its late diagnosis, poor therapeutic response, and highly heterogeneous microenvironment. Nanotechnology has the potential to overcome some of the challenges to improve diagnostics and tumor‐specific drug delivery but they have not been plausibly viable in clinical settings. The review focuses on active targeting strategies to enhance pancreatic tumor‐specific uptake for nanoparticles. Additionally, this review highlights using actively targeted liposomes, micelles, gold nanoparticles, silica nanoparticles, and iron oxide nanoparticles to improve pancreatic tumor targeting. Active targeting of nanoparticles toward either differentially expressed receptors or PDAC tumor microenvironment (TME) using peptides, antibodies, small molecules, polysaccharides, and hormones has been presented. We focus on microenvironment‐based hallmarks of PDAC and the potential for actively targeted nanoparticles to overcome the challenges presented in PDAC. It describes the use of nanoparticles as contrast agents for improved diagnosis and the delivery of chemotherapeutic agents that target various aspects within the TME of PDAC. Additionally, we review emerging nano‐contrast agents detected using imaging‐based technologies and the role of nanoparticles in energy‐based treatments of PDAC.This article is categorized under:
Implantable Materials and Surgical Technologies > Nanoscale Tools and Techniques in Surgery
Therapeutic Approaches and Drug Discovery > Nanomedicine for Oncologic Disease
Diagnostic Tools > In Vivo Nanodiagnostics and Imaging
Cite-worthiness Detection on Social Media: A Preliminary Study
Authors: Hafid Salim , Ammar Wassim , Bringay Sandra , Todorov Konstantin 
Published: August 2024

AbstractDetecting cite-worthiness in text is seen as the problem of flagging a missing reference to a scientific result (an article or a dataset) that should come to support a claim formulated in the text. Previous work has taken interest in this problem in the context of scientific literature, motivated by the need to allow for reference recommendation for researchers and flag missing citations in scientific work. In this preliminary study, we extend this idea towards the context of social media. As scientific claims are often made to support various arguments in societal debates on the Web, it is crucial to flag non-referenced or unsupported claims that relate to science, as this promises to contribute to improving the quality of the debates online. We experiment with baseline models, initially tested on scientific literature, by applying them on the SciTweets dataset which gathers science-related claims from X. We show that models trained on scientific papers struggle to detect cite-worthy text from X, we discuss implications of such results and argue for the necessity to train models on social media corpora for satisfactory flagging of missing references on social media. We make our data publicly available to encourage further research on cite-worthiness detection on social media.
OCR Cleaning of Scientific Texts with LLMs
Authors: Madarász Gábor , Ligeti-Nagy Noémi , Holl András , Váradi Tamás 
Published: August 2024

AbstractCorrecting Optical Character Recognition (OCR) errors is a major challenge in preprocessing datasets consisting of legacy PDF files. In this study, we develop Large Language Models specially finetuned to correct OCR errors. We experimented with the mT5 model (both the mT5-small and mT5-large configurations), a Text-to-Text Transfer Transformer-based machine translation model, for the post-correction of texts with OCR errors. We compiled a parallel corpus consisting of text corrupted with OCR errors as well as corresponding clean data. Our findings suggest that the mT5 model can be successfully applied to OCR error correction with improving accuracy. The results affirm the mT5 model as an effective tool for OCR post-correction, with prospects for achieving greater efficiency in future research.
RepoFromPaper: An Approach to Extract Software Code Implementations from Scientific Publications
Authors: Stankovski Aleksandar , Garijo Daniel 
Published: August 2024

AbstractAn increasing amount of scientists link to their research software code implementations in their academic publications in order to support the reusability of their results. However, research papers usually contain many code links (e.g., from reused tools or existing competing efforts) making it challenging to automatically establish clear links between papers and their corresponding implementations. This paper presents RepoFromPaper, an approach for automatically extracting the main code implementation associated with a research paper, based on the context in which that link is mentioned. Our approach uses fine-tuned language models to retrieve the top candidate sentences where a code implementation may be found, and uses custom heuristics to link candidate sentences back to their corresponding URL (footnote, reference or full-text mention). We evaluated RepoFromPaper on 150 research papers, obtaining an F1 score of 0.94. We also run our approach on nearly 1800 papers from the CS.AI Arxiv category, discovering 604 paper-repository links and making them available to the community.
From large to small $$ \mathcal{N} $$ = (4, 4) superconformal surface defects in holographic 6d SCFTs
Authors: Capuozzo Pietro , Estes John , Robinson Brandon , Suzzoni Benjamin 
Published: August 2024

Abstract
Two-dimensional (2d) $$ \mathcal{N} $$
N
= (4, 4) Lie superalgebras can be either “small” or “large”, meaning their R-symmetry is either $$ \mathfrak{so} $$
so
(4) or $$ \mathfrak{so} $$
so
(4) ⊕ $$ \mathfrak{so} $$
so
(4), respectively. Both cases admit a superconformal extension and fit into the one-parameter family $$ \mathfrak{d} $$
d
(2, 1; γ) ⊕ $$ \mathfrak{d} $$
d
(2, 1; γ), with parameter γ ∈ (−∞, ∞). The large algebra corresponds to generic values of γ, while the small case corresponds to a degeneration limit with γ → −∞. In 11d supergravity, we study known solutions with superisometry algebra $$ \mathfrak{d} $$
d
(2, 1; γ) ⊕ $$ \mathfrak{d} $$
d
(2, 1; γ) that are asymptotically locally AdS7×𝕊4. These solutions are holographically dual to the 6d maximally superconformal field theory with 2d superconformal defects invariant under $$ \mathfrak{d} $$
d
(2, 1; γ) ⊕ $$ \mathfrak{d} $$
d
(2, 1; γ). We show that a limit of these solutions, in which γ → −∞, reproduces another known class of solutions, holographically dual to small$$ \mathcal{N} $$
N
= (4, 4) superconformal defects. We then use this limit to generate new small $$ \mathcal{N} $$
N
= (4, 4) solutions with finite Ricci scalar, in contrast to the known small $$ \mathcal{N} $$
N
= (4, 4) solutions. We then use holography to compute the entanglement entropy of a spherical region centered on these small $$ \mathcal{N} $$
N
= (4, 4) defects, which provides a linear combination of defect Weyl anomaly coefficients that characterizes the number of defect-localized degrees of freedom. We also comment on the generalization of our results to include $$ \mathcal{N} $$
N
= (0, 4) surface defects through orbifolding.
Logarithmic correlation functions in 2D critical percolation
Authors: Camia Federico , Feng Yu 
Published: August 2024

Abstract
It is believed that the large-scale geometric properties of two-dimensional critical percolation are described by a logarithmic conformal field theory, but it has been challenging to exhibit concrete examples of logarithmic singularities and to find an explanation and a physical interpretation, in terms of lattice observables, for their appearance. We show that certain percolation correlation functions receive independent contributions from a large number of similar connectivity events happening at different scales. Combined with scale invariance, this leads to logarithmic divergences. We study several logarithmic correlation functions for critical percolation in the bulk and in the presence of a boundary, including the four-point function of the density (spin) field. Our analysis confirms previous findings, provides new explicit calculations and explains, in terms of lattice observables, the physical mechanism that leads to the logarithmic singularities we discover. Although we adopt conformal field theory (CFT) terminology to present our results, the core of our analysis relies on probabilistic arguments and recent rigorous results on the scaling limit of critical percolation and does not assume a priori the existence of a percolation CFT. As a consequence, our results provide strong support for the validity of a CFT description of critical percolation and a step in the direction of a mathematically rigorous formulation of a logarithmic CFT of two-dimensional critical percolation.
Aktueller Behandlungsstandard und Trends der Systemtherapie beim metastasierten hormonsensiblen Prostatakarzinom – Anwendung der Studiendaten in der Praxis
Authors: Wenzel Mike , Banek Séverine , Chun Felix K. H. , Mandel Philipp 
Published: August 2024

Zusammenfassung
Hintergrund
Die Therapielandschaft des metastasierten hormonsensiblen Prostatakarzinoms (mHSPC) hat sich in den letzten Dekaden grundlegend von einer alleinigen Androgendeprivationstherapie (ADT) hin zu einer intensivierten Kombinationstherapien gewandelt.

Fragestellung
Inwieweit haben die Daten der prospektiven Phase-III-Studien Einzug in den klinischen Alltag in der Behandlung des mHSPC innerhalb der letzten 5 bzw. 10 Jahre erhalten.

Ergebnisse
Insgesamt konnten für die vorliegende Studie 1098 mHSPC-Patienten mit einem medianen Alter bei Metastasierung von 70 Jahre und einem medianen prostataspezifischen Antigen (PSA) von 43 ng/ml inkludiert werden. Signifikante Unterschiede zeigten sich bzgl. des PSA-Nadirs beim mHSPC nach Jahresstratifizierung. Ebenso zeigten sich signifikante Unterschiede bezüglich der eingesetzten Systemtherapien beim mHSPC und metastasierten kastrationsresistenten Prostatakarzinom (mCRPC; p < 0,001). Bezüglich der jährlichen Änderungsraten („estimated annual percentage changes“, EAPC) der letzten 10 Jahre zeigte sich ein signifikanter Abfall der ADT-Monotherapie von 85 % (2013) zu 29 % (2023, EAPC: −12 %, p < 0,001). Umgekehrter Weise zeigt sich ein signifikanter Anstieg von Substanzen zur Blockade des Androgenrezeptorsignalweges (ARSI) von 6 % in 2013 auf 55 % in 2023 (EAPC: +21,7 %, p < 0,001). Bezüglich der Docetaxel-Chemotherapie zeigt sich über die letzten 10 Jahre ein glockenhafter Verlauf von 8 % in 2013 zu 25 % in 2019 und einem Abfall auf 0 % in 2023. Der Anteil der Triplet-Therapien lag 2023 bei 16 %.

Schlussfolgerung
Innerhalb der letzten 10 Jahre zeigt sich eine Adaptation der Phase-III-Studien zur intensivierten Kombinationstherapien beim mHSPC in der klinischen Realität mit dem häufigsten Einsatz von ARSI und Triplet-Therapie beim mHSPC.
Understanding model power in social AI
Authors: Brandtzaeg Petter Bae , Skjuve Marita , Følstad Asbjørn 
Published: August 2024

AbstractGiven the widespread integration of Social AI like ChatGPT, Gemini, Copilot, and MyAI, in personal and professional contexts, it is crucial to understand their effects on information and knowledge processing, and individual autonomy. This paper builds on Bråten’s concept of model power, applying it to Social AI to offer a new perspective on the interaction dynamics between humans and AI. By reviewing recent user studies, we examine whether and how models of the world reflected in Social AI may disproportionately impact human-AI interactions, potentially leading to model monopolies where Social AI impacts human beliefs, behaviour and homogenize the worldviews of its users. The concept of model power provides a framework for critically evaluating the impact and influence that Social AI has on communication and meaning-making, thereby informing the development of future systems to support more balanced and meaningful human-AI interactions.
Design and destructive testing of high-value hook fabricated by laser metal deposition
Authors: Leary Martin , Fordyce Ian , Lui Edward , Downing David , Khorasani Mahyar , Watts Jarrod , Brandt Milan 
Published: August 2024

AbstractLaser metal deposition (LMD) provides an emerging opportunity for the economic fabrication of high-value components at low production volume. Despite the technical and commercial opportunities associated with LMD, there exist potential failure-modes that differ from those typical of traditional manufacture; concurrently, LMD is typically applied to high-value components associated with a high consequence of failure. This report contributes to the emerging literature on LMD component design and failure analysis by documenting the design and destructive testing of a high-value tensile loaded hook component, including numerical structural simulation, manufacture characterisation, microstructural analysis and instrumented destructive testing. This systematic design contributes to the understanding of LMD design for structural integrity and supports the application of LMD as a robust commercial additive technology.
Sensory characterization and identification of odorants in birch wood (Betula pendula Roth)
Authors: Wang Qifan , Baum Adina , Schreiner Linda , Slavik Benedikt , Buettner Andrea , Loos Helene M. 
Published: August 2024

AbstractAs one of the most common tree species, birch wood (Betula pendula Roth) is widely used as a material of furniture and decoration indoors for its many excellent characteristics. Whereas there are some studies on the volatile composition of the essential oil from the leaves of Betula pendula Roth, only limited information is available on the odor-active constituents of birch wood. To close this gap, the odorants of birch wood were investigated by means of instrumental and sensory analyses, including techniques such as gas chromatography-flame ionization detection/olfactometry, high-resolution gas chromatography-mass spectrometry, and heart-cut two-dimensional high-resolution gas chromatography-mass spectrometry/olfactometry. Overall, a total of 20 odorants was (tentatively) identified on the basis of their respective odor qualities and retention indices and mass spectra by comparison with reference compounds. It was shown that birch wood odor is dominated by a series of terpenes, terpenoids and phenyl compounds originating from the degradation of lignin and aldehydes, ketones and acids originating from fatty acid degradation. By a sensory evaluation of the birch wood, the predominant odor attributes were determined to be earthy, pencil-like, corky/mouldy, grassy, fatty, fruity, green tea-like, herb-like, vanilla-like, and vinegar-like.
Pollen signal of modern vegetation registered in surface soil samples along an elevation gradient from Iztaccíhuatl volcano, central Mexico
Authors: Rodríguez-Pérez Erandi , Vázquez Selem Lorenzo , Cañellas-Boltà Núria , Trapote María del Carmen , Sosa Susana , Lozano-García Socorro , Montoya Encarni 
Published: August 2024

AbstractCharacterising the vegetation-pollen signal is a crucial task for enhancing the interpretation of fossil pollen records. This study analyses 28 surface soil samples collected in the surroundings of Iztaccíhuatl volcano, between 2,650 and 4,024 m asl. Pollen zones and ordination analysis were assessed to establish a qualitative connection between the pollen signal and the distribution of plant communities along the elevation gradient. The results show: (i) the predominant pollen type in the pollen assemblage is Pinus; (ii) pollen grains of Quercus and Alnus are present along the elevation gradient, even at high elevations where the parental plants are not typically found; (iii) samples taken between 2,650 and 3,338 m asl., where fir forests dominate, exhibit higher values of Abies pollen compared to samples above 3,405 m asl.; (iv) the locally-dispersed pollen of the hemiparasite Arceuthobium results key in identifying the presence of pine forests; and (v) pollen taxa such as Apiaceae, Eryngium, Valerianaceae, and Caryophyllaceae are linked to higher elevations, specifically where the plant communities of Pinus hartwegii and alpine grassland occur. The study suggests that the pollen signal along the elevation gradient is useful to characterise the main plant communities of the study site (fir forest, pine forest and alpine grassland). Additionally, the percentage variations of Abies in the pollen signal below 3,600 m asl. show the reduction of fir forest communities resulting from recent human activities in the area.