bluuebunny/crossref_metadata_2025_split huggingface dataset:
Researcher’s Positioning in a Digital Educational Experiment: Conceptual PlayWorlds in the Home Setting
Authors: Nedovic Sonya , Rai Prabhat , Fleer Marilyn 
Published: July 2024

AbstractIn an overarching capacity, our research sought to investigate how families create conditions for children’s STEM learning in home settings. However, a methodological crisis formed when COVID-19 social distancing protocols contradicted our use of an educational experiment. Traditionally, an intervention into everyday practice such as this requires the researcher to enter the family home and participate in the child’s experience before interpreting how the child is developing through their relational interactions with others. This chapter reports on how the researcher positioned themselves in response to these methodological demands and created a new kind of activity setting fruitful for conceptual development through the use of digital tools. Our methodological approach can be adapted by future researchers to guide interactions and collaborations with families in the digital space.
Resilience in Partnership Research—The Role of Digital Platforms in the Co-creation of Knowledge in Pandemic Times
Authors: Ødegaard Elin Eriksen , Birkeland Johanna , Oen Marion 
Published: July 2024

AbstractThe purpose of this chapter is to narrate and conceptualise the changing processes that occurred when an interdisciplinary team transitioned from face-to-face workshops to a shared digital platform space in a historical time of crisis. The chapter describes how an interdisciplinary partnership project overcame obstacles, such as the respective institutions using different communication systems, to explore possibilities for partnership research through using a common digital platform as a tool for collective writing and for experimenting with writing genres. Inspired by cultural-historical theorisations of collective resilience, we describe how team members reinforced each other to strengthen risk situations, overcome them and use them as sources to support joint development of practices and co-research. We call this collective resilient digital agility. According to a cultural-historical perspective, resilience can be understood as a higher psychological function resulting from collaborative processes (Wertsch JV. Vygotsky and the social formation of mind. Harvard University Press. https://doi.org/10.2307/j.ctv26071b0, 1988). The results show that the pandemic and the shift to using a new artefact, a digital platform, changed what it was possible to do, strengthening resilience and ways of working together and opening up a co-creative writing genre.
Beyond Physical Space: Using Digital Technology to Support a Collaborative Cultural-Historical Educational Experiment
Authors: Wang Yuejiu , Ma Yuwen 
Published: July 2024

AbstractThrough cooperation between researchers and teachers, the educational experiment creates optimal conditions for the development of the participating children, as well as the professional development of teachers. However, how researchers can virtually collaborate in conducting an educational experiment while maintaining their dual roles as participants and researchers is less understood. In order to address this problem, this chapter provides an effective methodological approach by showcasing how two researchers in two countries used digital technology as a relational tool to conduct educational experiments. A dialectical relationship between the research fairy who joined via Zoom and the imaginary situation is established, helping maintain the researcher’s participating role. Additionally, digital technology helped two researchers develop dialectical relationships through mutual conversation, which enhanced theoretical problem-solving through the knowing and re-knowing process in the educational experiment. This multi-layered dialectical relationship was synthesised as a unity and created a new way of collaboration between researchers and participants in the cultural-historical educational experiment.
Constraints on the topology of Type IIB string theory
Authors: Yonekura Kazuya 
Published: July 2024

Abstract
We discuss some topological constraints on Type IIB string theory that cannot be described by elementary characteristic classes. Anomaly cancellation of the worldvolume theory of a D3-brane requires a shifted Dirac quantization condition of the Ramond-Ramond 5-form flux. However, the required shift is sometimes inconsistent depending on the topology of spacetime backgrounds. The obstruction to the existence of a shifted quantization is described by a degree-6 cohomology class whose definition involves spin structure of spacetime manifolds. The cohomology class is interpreted as a background D3-charge, and the Gauss law constraint requires inclusion of additional D3-branes to cancel it.
Distributional celestial amplitudes
Authors: Borji Majdouline , Pano Yorgo 
Published: July 2024

Abstract
Scattering amplitudes are tempered distributions, which are defined through their action on functions in the Schwartz space $$ \mathcal{S}\left(\mathbb{R}\right) $$
S

ℝ

by duality. For massless particles, their conformal properties become manifest when considering their Mellin transform. Therefore we need to mathematically well-define the Mellin transform of distributions in the dual space $$ {\mathcal{S}}^{\prime}\left({\mathbb{R}}^{+}\right) $$

S
′

ℝ
+

. In this paper, we investigate this problem by characterizing the Mellin transform of the Schwartz space $$ \mathcal{S}\left({\mathbb{R}}^{+}\right) $$
S

ℝ
+

. This allows us to rigorously define the Mellin transform of tempered distributions through a Parseval-type relation. Massless celestial amplitudes are then properly defined by taking the Mellin transform of elements in the topological dual of the Schwartz space $$ \mathcal{S}\left({\mathbb{R}}^{+}\right) $$
S

ℝ
+

. We conclude the paper with applications to tree-level graviton celestial amplitudes.
The meaningfulness gap in AI ethics: a guide on how to think through a complex challenge
Authors: Rüther Markus 
Published: July 2024

AbstractTechnological outsourcing is increasingly prevalent, with AI systems taking over many tasks once performed by humans. This shift has led to various discussions within AI ethics. A question that was largely ignored until recently, but is now increasingly being discussed, concerns the meaningfulness of such a lifestyle. The literature largely features skeptical views, raising several challenges. Many of these challenges can be grouped under what I identify as the “meaningfulness gap”. Although this gap is widely acknowledged, there is a notable absence of systematic exploration in the literature. This paper aims to fill this void by offering a detailed, step-by-step guide for systematically exploring the different instances of the meaningfulness gap and aids in navigating their complexities. More specifically, it proposes differentiating the gaps according to their realms and objects, normative nature, scope, and severity. To make these areas manageable, the paper takes several taxonomies and distinctions on board. Finally, the guide is summarized, and some skeptical replies are anticipated and countered by clarificatory remarks.
Remote work and location preferences: a study of post-pandemic trends in Italy
Authors: Jansen Thea , Ascani Andrea , Faggian Alessandra , Palma Alessandro 
Published: July 2024

AbstractThis study investigates how working remotely, by reducing workplace commuting, weakens the limitations connected to residential mobility and enables Tiebout sorting. We focus on the Italian context, where a strong culture of in-person workplace attendance limits workers’ ability to live farther from their workplace. We leverage the natural experiment of COVID-19 containment measures to shed light on the spatial implications of an increased remote work adoption. We overcome the unavailability of official data by collecting primary data in early 2022 through an original survey of our design on a sample of workers in 12 metropolitan areas. To address the challenges of analyzing the phenomenon in a still-developing context, we ask questions on both their actual and intended moving behavior in relation to remote work availability. Using a case–control study design, we find significant evidence that expecting to work remotely more frequently in the long term increases the likelihood of being interested in moving, or having done so already since the pandemic outbreak.
The effect of the interlayer time and deposition speed on the tensile properties of material extrusion components
Authors: Lambiase Francesco , Pace Francesco , Andreucci Elena , Paoletti Alfonso 
Published: July 2024

AbstractThis study investigates the influence of the substrate temperature in material extrusion (MEX) on tensile behavior of PLA samples. A full factorial experimental plan was conducted by varying the deposition speed and the interlayer time. Infrared thermography was conducted to determine the influence of the deposition conditions on the temperature of the substrate just before the deposition of the next layer. Tensile tests were conducted along the “upright direction” to determine the influence of the thermal history on the interlayer adhesion. The results indicate the strong influence of the interlayer time on the thermal history and the mechanical behavior. The temperature of the substrate before subsequent overlying deposition was mainly influenced by the interlayer time, while it was less affected by the deposition speed. The Young modulus of the samples was poorly affected by the adopted process conditions; on the other hand, the maximum strength and the elongation at rupture were strongly affected by the interlayer time. The identified variances in mechanical behavior underscore the pivotal significance of sample dimensions in dictating the ultimate mechanical characteristics of vertically oriented samples. These outcomes illuminate the intricate interaction between deposition speed and interlayer duration, highlighting their substantial influence on mechanical performance.
Sensitivity of GNSS to vertical land motion over Europe: effects of geophysical loadings and common-mode errors
Authors: Hohensinn Roland , Ruttner Pia , Bock Yehuda 
Published: July 2024

AbstractWe perform a statistical sensitivity analysis on a parametric fit to vertical daily displacement time series of 244 European Permanent GNSS stations, with a focus on linear vertical land motion (VLM), i.e., station velocity. We compare two independent corrections to the raw (uncorrected) observed displacements. The first correction is physical and accounts for non-tidal atmospheric, non-tidal oceanic and hydrological loading displacements, while the second approach is an empirical correction for the common-mode errors. For the uncorrected case, we show that combining power-law and white noise stochastic models with autoregressive models yields adequate noise approximations. With this as a realistic baseline, we report improvement rates of about 14% to 24% in station velocity sensitivity, after corrections are applied. We analyze the choice of the stochastic models in detail and outline potential discrepancies between the GNSS-observed displacements and those predicted by the loading models. Furthermore, we apply restricted maximum likelihood estimation (RMLE), to remove low-frequency noise biases, which yields more reliable velocity uncertainty estimates. RMLE reveals that for a number of stations noise is best modeled by a combination of random walk, flicker noise, and white noise. The sensitivity analysis yields minimum detectable VLM parameters (linear velocities, seasonal periodic motions, and offsets), which are of interest for geophysical applications of GNSS, such as tectonic or hydrological studies.
Consumers’ knowledge and experiences of adverse drug reaction reporting in Australia: a national survey
Authors: Dedefo Mohammed Gebre , Lim Renly , Kassie Gizat M. , Roughead Elizabeth , Ellett Lisa Kalisch 
Published: July 2024

Abstract
This study aimed to investigate the current knowledge and experiences of consumers in Australia on adverse drug reaction (ADR) reporting and their reasons for reporting or not reporting ADRs, with a focus on the use of digital tools for ADR reporting.

Methods
A cross-sectional online survey was conducted among adults who had taken medicine in Australia. A structured questionnaire with multiple choice or Likert scale responses with an option for participants to provide free-text responses and pretested for face validity was used. Consumer characteristics, knowledge, and ADR reporting practices were analyzed using descriptive statistics and the chi-square test or Fisher’s exact test.

Results
A total of 544 survey responses were included in the analysis. The majority of respondents were women (68%), and 22% were aged between 65 and 74 years. Fifty-eight percent (n = 317) of respondents knew that they could report ADRs to either the Therapeutic Goods Administration (TGA), state or territory government health department, or healthcare professionals. Three-quarters (n = 405) of respondents stated that they had experienced an ADR; of these, 36% reported an ADR to either the TGA, state or territory government health department, or healthcare professionals. Among those who reported ADRs, 58% were unaware that they could use digital tools to report ADRs. The main reason for not reporting was that they did not think the ADR was serious enough to report (39%).

Conclusion
Over half of consumers knew that they could report ADR; however, improved consumer awareness about using digital tools for ADR reporting and increased ADR reporting is needed.
Soft tissue hemangioma of the right upper extremity with intraosseous extension and secondary intravascular papillary endothelial hyperplasia
Authors: Bass Rachel , Siegal Gene , Kotha Apoorva , Melenevksy Yulia 
Published: July 2024

Abstract
Intravascular papillary endothelial hyperplasia (IPEH), also known as Masson’s tumor, is an uncommon exuberant form of organizing thrombus that may occur within a vessel, vascular tumor, or hematoma and may change the imaging appearance to mimic an aggressive process. It must be distinguished pathologically from angiosarcoma. They have been most commonly reported within superficial soft tissue tumors, and rapid growth and effect on bone are rarely described. We present a case of a patient with a soft tissue hemangioma with IPEH with intraosseous extension that presented with a pathologic fracture of her right humerus with an aggressive appearing osseous lesion. CT and MRI demonstrated a multifocal ill-defined soft tissue mass throughout the right upper extremity with underlying cortical tunneling and scalloping of the proximal humerus. Similar imaging findings were also present in the distal humerus and ipsilateral scapula and evolved during her hospitalization. Following percutaneous biopsy revealing hemangioma with features of papillary endothelial hyperplasia with intraosseous extension, the patient died in the ICU secondary to unrelated septic shock. Diagnosis was confirmed at autopsy. Primary and secondary IPEH have been generally characterized as well-defined solitary masses, most often in the superficial soft tissues. This case of a deep soft tissue hemangioma with type II IPEH, intraosseous extension, and imaging findings of regional multicompartmental involvement is very unusual. Reporting of this case in the literature should be beneficial for pathologic correlation with similar confounding masses as well as propose a possible mechanism for intraosseous extension of soft tissue hemangiomas.
Urologic prosthetics: an imaging review of short- and long-term complications
Authors: Raikin Jared , Woodruff Mary , Meshekow Gabriel , Debski Nicole D. , Germaine Pauline , Gor Ronak 
Published: July 2024

Abstract
Purpose
Urologic prosthetics offer significant quality of life enhancements for patients with stress urinary incontinence and erectile dysfunction. Artificial urinary sphincter and penile prosthesis are the most commonly used prosthetics for these patients. Radiographic imaging offers important insight, guiding treatment when patients present with complications. Herein, we pictorialize normal radiographic findings and complications alike.

Methods
We reviewed our IRB-approved prosthetics database, highlighting patients with prosthetic complications with available imaging. We collected imaging from patients without complications for baseline reference.

Results
The radiographic appearance of orthotopic genitourinary prosthetics and a review of short- and long-term complications including hematoma, infection, malpositioning, leak and erosion are pictorialized.

Conclusion
Radiologic imaging serves as a vital complement to history and physical examination, aiding in the identification of complications and potentially streamlining surgical preparations. It is important for radiologists to familiarize themselves with standard prosthetic nomenclature, normal positioning and appearance, along with imaging findings of common complications.

Graphical abstract
ChatGPT’s diagnostic performance based on textual vs. visual information compared to radiologists’ diagnostic performance in musculoskeletal radiology
Authors: Horiuchi Daisuke , Tatekawa Hiroyuki , Oura Tatsushi , Shimono Taro , Walston Shannon L. , Takita Hirotaka , Matsushita Shu , Mitsuyama Yasuhito , Miki Yukio , Ueda Daiju 
Published: July 2024

Abstract
Objectives
To compare the diagnostic accuracy of Generative Pre-trained Transformer (GPT)-4-based ChatGPT, GPT-4 with vision (GPT-4V) based ChatGPT, and radiologists in musculoskeletal radiology.

Materials and methods
We included 106 “Test Yourself” cases from Skeletal Radiology between January 2014 and September 2023. We input the medical history and imaging findings into GPT-4-based ChatGPT and the medical history and images into GPT-4V-based ChatGPT, then both generated a diagnosis for each case. Two radiologists (a radiology resident and a board-certified radiologist) independently provided diagnoses for all cases. The diagnostic accuracy rates were determined based on the published ground truth. Chi-square tests were performed to compare the diagnostic accuracy of GPT-4-based ChatGPT, GPT-4V-based ChatGPT, and radiologists.

Results
GPT-4-based ChatGPT significantly outperformed GPT-4V-based ChatGPT (p < 0.001) with accuracy rates of 43% (46/106) and 8% (9/106), respectively. The radiology resident and the board-certified radiologist achieved accuracy rates of 41% (43/106) and 53% (56/106). The diagnostic accuracy of GPT-4-based ChatGPT was comparable to that of the radiology resident, but was lower than that of the board-certified radiologist although the differences were not significant (p = 0.78 and 0.22, respectively). The diagnostic accuracy of GPT-4V-based ChatGPT was significantly lower than those of both radiologists (p < 0.001 and < 0.001, respectively).

Conclusion
GPT-4-based ChatGPT demonstrated significantly higher diagnostic accuracy than GPT-4V-based ChatGPT. While GPT-4-based ChatGPT’s diagnostic performance was comparable to radiology residents, it did not reach the performance level of board-certified radiologists in musculoskeletal radiology.

Clinical relevance statement
GPT-4-based ChatGPT outperformed GPT-4V-based ChatGPT and was comparable to radiology residents, but it did not reach the level of board-certified radiologists in musculoskeletal radiology. Radiologists should comprehend ChatGPT’s current performance as a diagnostic tool for optimal utilization.

Key Points

This study compared the diagnostic performance of GPT-4-based ChatGPT, GPT-4V-based ChatGPT, and radiologists in musculoskeletal radiology.

GPT-4-based ChatGPT was comparable to radiology residents, but did not reach the level of board-certified radiologists.

When utilizing ChatGPT, it is crucial to input appropriate descriptions of imaging findings rather than the images.

Graphical Abstract
The value of deep learning-based X-ray techniques in detecting and classifying K-L grades of knee osteoarthritis: a systematic review and meta-analysis
Authors: Zhao Haoming , Ou Liang , Zhang Ziming , Zhang Le , Liu Ke , Kuang Jianjun 
Published: July 2024

Abstract
Objectives
Knee osteoarthritis (KOA), a prevalent degenerative joint disease, is primarily diagnosed through X-ray imaging. The Kellgren-Lawrence grading system (K-L) is the gold standard for evaluating KOA severity through X-ray analysis. However, this method is highly subjective and non-quantifiable, limiting its effectiveness in detecting subtle joint changes on X-rays. Recent researchers have been directed towards developing deep-learning (DL) techniques for a more accurate diagnosis of KOA using X-ray images. Despite advancements in these intelligent methods, the debate over their diagnostic sensitivity continues. Hence, we conducted the current meta-analysis.

Methods
A comprehensive search was conducted in PubMed, Cochrane, Embase, Web of Science, and IEEE up to July 11, 2023. The QUADAS-2 tool was employed to assess the risk of bias in the included studies. Given the multi-classification nature of DL tasks, the sensitivity of DL across different K-L grades was meta-analyzed.

Results
A total of 19 studies were included, encompassing 62,158 images. These images consisted of 22,388 for K-L0, 13,415 for K-L1, 15,597 for K-L2, 7768 for K-L3, and 2990 for K-L4. The meta-analysis demonstrated that the sensitivity of DL was 86.74% for K-L0 (95% CI: 80.01%–92.28%), 64.00% for K-L1 (95% CI: 51.81%–75.35%), 75.03% for K-L2 (95% CI: 66.00%–83.09%), 84.76% for K-L3 (95% CI: 78.34%–90.25%), and 90.32% for K-L4 (95% CI: 85.39%–94.40%).

Conclusions
The DL multi-classification methods based on X-ray imaging generally demonstrate a favorable sensitivity rate (over 50%) in distinguishing between K-L0-K-L4. Specifically, for K-L4, the sensitivity is highly satisfactory at 90.32%. In contrast, the sensitivity rates for K-L1-2 still need improvement.

Clinical relevance statement
Deep-learning methods have been useful to some extent in assessing the effectiveness of X-rays for osteoarthritis of the knee. However, this requires further research and reliable data to provide specific recommendations for clinical practice.

Key Points

X-ray deep-learning (DL) methods are debatable for evaluating knee osteoarthritis (KOA) under The Kellgren-Lawrence system (K-L).

Multi-classification deep-learning methods are more clinically relevant for assessing K-L grading than dichotomous results.

For K-L3 and K-L4, X-ray-based DL has high diagnostic performance; early KOA needs to be further improved.