bluuebunny/crossref_metadata_2025_split huggingface dataset:
The network of sports: using network analysis to understand the relationship between sports and socio-physiological factors in contemporary China
Authors: Bi Xiangyang , Sun Zhanning , Hu Boran 
Published: June 2024

AbstractThis study examines sports and physical activities among Chinese aged 18–65, using network analysis on a significant random sample. It categorizes sports into 11 groups based on public selection, with a community detection algorithm aiding classification. Variables like age, gender, and education were integrated, revealing how life stages, gender disparities, and social class influence activity participation. The mixed graph model shows both positive and negative correlations among activities, highlighting the role of sports as both a social integrator and divider, reflective of broader societal norms and inequalities. The exponential random graph model further illustrates a complex network of demographic-driven participation patterns. The purpose of this investigation is twofold: to advance methodological approaches in the study of sports-related social networks and to explore the broader implications such networks may have on individual and collective behaviors within this field.
Empirische Unterrichtsforschung – quo vadis?
Authors: Reusser Kurt 
Published: June 2024

ZusammenfassungDie quantitative pädagogisch-psychologische Unterrichtsqualitätsforschung (UQF) hat durch die Identifikation von generischen Basismerkmalen zu einem tieferen Verständnis von Unterrichtsqualität beigetragen. In Kontrast dazu steht, dass die Forschungsergebnisse die Schulpraxis kaum oder wenig verständnistief erreichen. Der Text plädiert für eine allgemein und fachdidaktische Fundierung der Unterrichtsqualitätsforschung und sieht darin einen Beitrag zur Weiterentwicklung ihrer Qualitätskonzepte und zu einer an das Unterrichtshandeln stärker anschlussfähigen, theoretisch und methodisch weniger eng geführten Forschungspraxis.
Characterisation of Cryphonectria hypovirus 1 strains in Turkey and their transmission to various vegetative compatibility types of Cryphonectria parasitica
Authors: Çakar Deniz , Özer Göksel , Şimşek Seçil Akıllı , Maden Salih 
Published: June 2024

AbstractCharacterization of the Cryphonectria parasitica population was initially done by a phenotypical assessment of 40 in vitro grown isolates obtained from 52 healing cankers collected from eight important chestnut-growing provinces of Turkey. The results of Bavendamm test, often correlated indirectly to hypovirulence, suggested 31 possibly hypovirulent and 9 virulent isolates. PCR tests amplified two regions of ORFs A and B of Cryphonectria hypovirus 1 (CHV-1) from 36 of 40 isolates. The PCR test confirmation was more sensitive than the Bavendamm test. Partial ORFA sequencing revealed 36 CHV-1 haplotypes belonging to Italian subtype (I), with all hypovirulent isolates being of EU-1 vc type. The CHV-1 from 10 native EU-1 isolates were first transferred to six European vc type testers, EU-2, EU-3, EU-5, EU-7, EU-26, and EU-44, having heteroallelism at one vic locus. The presence of the vic locus difference generally reduces virus transmission. The easiest and highest frequency virus transfer was obtained by vic4 and vic6 allelic differences, while the differences vic2 and vic7 made the transfer more challenging. Finally, in this study we successfully transferred CHV-1 to an EU-1 isolate obtained from the Bursa province to an EU-12 European tester isolate.
Dynamic Color Regulation of the Lycaenid Butterfly Wing Scales
Authors: Sun Mingxia , Meng Weihao , Yin Haiwei , Fan Lingjie , Shi Lei , Watson Gregory S. , Watson Jolanta A. , Wang Jingxia , Jiang Lei , Liang Aiping 
Published: June 2024

AbstractButterfly coloration originates from the finely structured scales grown on the underlying wing cuticle. Most researchers who study butterfly scales are focused on the static optic properties of cover scales, with few works referring to dynamic optical properties of the scales. Here, the dynamic coloration effect of the multiple scales was studied based on the measurements of varying-angle reflection and the characterization of scale flexibility in two species of Lycaenid, Plebejus argyrognomon with violet wings and Polyommatus erotides with blue wings. We explored the angle-dependent color changeability and the color-mediating efficiency of wing scales. It was found that the three main kinds of flexible scales (cover, ground and androconia scales) were asynchronously bent during wing rotation, which caused the discoloration effect. The three layers of composite scales broaden the light signal when compared to the single scale, which may be of great significance to the recognition of insects. Specifically, the androconia scales were shown to strongly contribute to the overall wing coloration. The cover scale coloration was ascribed to the coherence scattering resulted from the short-range order at intermediate spatial frequencies from the 2D Fourier power spectra. Our findings are expected to deepen the understanding of the complex characteristics of biological coloration and to provide new inspirations for the fabrication of biomimetic flexible discoloration materials.
Dynamic output feedback control strategy for a satellite orbital model within negative-imaginary systems theory framework
Authors: Choudhary Santosh Kumar , Chokkadi Shreesha 
Published: June 2024

AbstractThis article presents the synthesis of a dynamic output feedback controller for a satellite orbital system confronted with uncertainties. The investigated method transforms the closed-loop system, synthesized by the controller, into an $$\alpha $$
α
-strictly negative-imaginary system. It utilizes the DC-loop gain condition associated with negative-imaginary systems theory to demonstrate robust stability of the satellite orbital system in the presence of uncertainties. Furthermore, the synthesized negative-imaginary closed-loop system exhibits notable time-domain performance. The numerical simulation outcomes presented in this article validate the investigated synthesis method.
Enabling Civil Single-Pilot Operations: A State-of-the-Art Review
Authors: Puca Nicola , Guglieri Giorgio 
Published: June 2024

AbstractAdvanced avionics and automation technologies have significantly transformed cockpit operations, resulting in a gradual reduction of the crew members on-board. Single-pilot operations (SPO) concept is gaining significant attention in the aviation industry due to its potential for cost savings and to cope with the anticipated pilot shortage and the increasing air traffic demand. This paper conducts a scoping literature review on SPOs, serving as an initial step to map the scientific peer-reviewed content on the subject. The survey focuses on three thematic domains, which are, respectively, operations, automation, and the emerging field of digital and cognitive flight assistants. The methodology involved the use of Google Scholar and IEEE Xplore databases. Sources were selected adapting the search criteria to the proposed sub-topics and prioritizing either the most cited and recent contributions. The analysis of the literature reveals a growing body of work in the recent years. This review also highlights interest in the human-centered design for automation solutions which are responsive to cognitive and behavioral states of the pilot. While acknowledging the potential safety and operational challenges associated with SPOs and the pilot-automation cooperation, this work suggests that great research efforts should be made on the human factor and regulatory subjects to pave the way for a feasible and safe implementation of the single-pilot paradigm in commercial aviation.
Executing Ad-Hoc Queries on Large Geospatial Data Sets Without Acceleration Structures
Authors: Bormann Pascal , Krämer Michel , Würz Hendrik M. , Göhringer Patrick 
Published: June 2024

AbstractIn this case study, we investigate if it is possible to harness the capabilities of modern commodity hardware to perform ad-hoc queries on large raw geospatial data sets. Normally, this requires building an index structure, which is a time-consuming process. We aim to provide means to individual users who receive a new or updated geospatial data set and want to directly start working with it without having to build such an index structure first. To this end, we conduct various experiments on two distinct types of data: 3D building models and point clouds. For the former, we demonstrate that well-known algorithms such as fast string search allow a wide range of queries to be answered in at most a few seconds on data sets with over a million buildings. The usage of progressive indexing additionally improves query run time by more than a factor of two. Regarding point clouds, we achieve similar run times using the popular LAS file format and a query throughput of up to a billion points per second when using a columnar memory layout. The run time of ad-hoc queries is often on par with that of database-driven solutions, sometimes even outperforming them. Considering that ad-hoc queries require no preprocessing, our results show that they are a viable alternative to acceleration structures when working with geospatial data.
A green binder for cold weather applications: enhancing mechanical performance of alkali-activated slag through modulus, alkali dosage, and Portland cement substitution
Authors: Dener Murat , Altunhan Ufuk , Benli Ahmet 
Published: June 2024

AbstractBelow 5 °C, Portland cement (PC) experiences delayed hydration, slowing strength development, making it unsuitable for winter. Alkali-activated slag (AAS) emerges as a viable alternative with continuous hydration in low-temperature conditions. The effect of the activator nature on the performance of AAS cured at normal temperatures is well known, but further studies are required for low-temperature conditions. This study investigates the synergistic impact of activator modulus (1.2 and 1.5), alkali dosage (5, 7, and 9%), and PC substitution rates (0, 10, and 20%), on low-temperature cured AAS properties. Eighteen mixtures were prepared and cured at 2 °C. Compression and ultrasonic pulse velocity tests were conducted after 7, 28, and 90 days. Fourier transform infrared spectroscopy (FTIR) and scanning electron microscopy analyses were performed to examine the microstructure of the samples. Elevating alkali dosage enhanced early age strength but resulted in a drop in 90-day strength. Simultaneous increases in modulus and PC substitution rate reduced strength due to shrinkage-induced crack formation. Optimal mixture design options included using 10% PC in the 1.2 modulus and omitting PC when the 1.5 modulus was selected. Despite low temperatures, the use of PC significantly accelerated the setting time. Altering modulus and alkali dosage caused a considerable change in the intensity of the peaks in the FTIR spectrum. The findings indicate that AAS shows promise when adjusting the mixture design for temperatures below 5 °C, which are unfavorable for the hydration of PC.
Comparing cognitive load in learning spatial ability: immersive learning environment vs. digital learning media
Authors: Jian Yi , Abu Bakar Juliana Aida 
Published: June 2024

AbstractSpatial ability is an important skill for art students, and its learning difficulty lies in the students' need to form abstract three-dimensional thinking and spatial perception. Common digital learning media (DLM) consume many cognitive resources and result in a limited spatial ability for students to learn. Previous studies have shown that virtual reality (VR) technology has unique advantages in improving spatial ability and training design thinking. This study uses VR technology to design an immersive learning environment (ILE) and discusses the differences between students' learning performance and cognitive load in DLM mode based on slides and ILE mode based on VR technology. Twenty-eight first-year university students participated in the experiment, divided into control and experimental groups based on their entrance grades and gender. The student's learning performance and cognitive load were obtained through academic ability tests and questionnaires. The experimental results show that the main effect of the learning environment is significant. Students in ILE have lower cognitive load and higher learning performance, and gender does not significantly influence cognitive load and academic performance. However, DLM increases students' cognitive load, and the cognitive load of females is higher than that of males. The results of this study provide a reference for future spatial ability learning and the impact of cognitive load on learning performance while also supporting efforts towards sustainable development by promoting innovative educational approaches aligned with the Sustainable Development Goals (SDG).
Human feedback enhanced autonomous intelligent systems: a perspective from intelligent driving
Authors: Yuan Kang , Huang Yanjun , Guo Lulu , Chen Hong , Chen Jie 
Published: June 2024

AbstractArtificial intelligence empowers the rapid development of autonomous intelligent systems (AISs), but it still struggles to cope with open, complex, dynamic, and uncertain environments, limiting its large-scale industrial application. Reliable human feedback provides a mechanism for aligning machine behavior with human values and holds promise as a new paradigm for the evolution and enhancement of machine intelligence. This paper analyzes the engineering insights from ChatGPT and elaborates on the evolution from traditional feedback to human feedback. Then, a unified framework for self-evolving intelligent driving (ID) based on human feedback is proposed. Finally, an application in the congested ramp scenario illustrates the effectiveness of the proposed framework.
Application of Artificial Intelligence Technology in Vulnerability Analysis of Intelligent Ship Network
Authors: Lan Dan , Xu Peilong , Nong Jia , Song Junkang , Zhao Jie 
Published: June 2024

AbstractThe improvement in transportation efficiency, security, safety, and environmental effects may be possible due to the impending advent of autonomous ships. Automatic situational awareness, risk detection, and intelligent decision-making are the key features of the intelligent ship network, differentiating it from conventional ships. There is an immediate need to implement a system for marine information management and network security due to the growing importance of this field, which poses a risk to national and societal stability due to factors, such as the diversity and complexity of marine information types, the challenges associated with data collection, and other similar factors. By recognizing different vulnerabilities and through research cases of the ship systems and Artificial Intelligence (AI) technologies, this paper presents Adaptive Fuzzy Logic-assisted Vulnerability Analysis of Intelligent Ship Networks (AFL-VA-ISN) in various cyberattack scenarios for autonomous ship intrusion detection and information management. Fuzzy logic has been combined with AI, providing a framework for handling uncertainty and imprecision in intelligent ship networks and effective decision-making. This work presents a method for detecting anomalies in risk data based on the collaborative control structure of the Ship Information System. Maintaining the network security of intelligent ships is the primary focus of this research, which mainly employed multi-sensor nodes to evaluate data containing information about malicious attacks and placed self-execution protection organize generating nodes into place to intercept and protect against attacks. The experimental outcomes demonstrate that the suggested AFL-VA-ISN model increases the data transmission rate by 99.2%, attack detection rate by 98.5%, risk assessment rate by 97.5%, and access control rate of 96.3%, and reduces the network latency rate of 11.4% compared to other existing models.
Age-specific Multimorbidity Patterns and Burden on All-Cause Mortality and Public Direct Medical Expenditure: A Retrospective Cohort Study
Authors: Hong Sabrina Nan , Lai Francisco Tsz Tsun , Wang Boyuan , Choi Edmond Pui Hang , Wong Ian Chi Kei , Lam Cindy Lo Kuen , Wan Eric Yuk Fai 
Published: June 2024

Abstract
Objective
To evaluate age-specific multimorbidity patterns and morbidity burden on mortality and healthcare expenditure across age groups.

Patients and Methods
Retrospective observational study between January 1, 2009 to December 31, 2017 using electronic health records in Hong Kong: Individuals were stratified by age (< 50, 50–64, 65–79, ≥ 80), and sub-classified by number of morbidities (0, 1, 2, 3, ≥ 4) out of 21 common chronic conditions. Clustering analyses were conducted to identify specific patterns of multimorbidity. Association between the number as well as combinations of morbidities and all-cause mortality and public expenditure was examined.

Results
4,562,832 individuals with a median follow-up of 7 years were included. Mental disorders were the top morbidities among young individuals, while cardiovascular diseases were prevalent in the elderly. An increased number of morbidities was associated with a greater relative risk for mortality and medical expenditure, and this relationship was stronger among younger patients. Compared to individuals in the same age group without morbidity, the hazard ratios (HR; 95% CI) of all-cause mortality in patients aged < 50 and ≥ 80 with two comorbidities 3.81 (3.60–4.03) and 1.38 (1.36–1.40), respectively, which increased to 14.22 (9.87–20.47) and 2.20 (2.13–2.26), respectively, as the number of morbidities increased to ≥ 4. The stroke-hypertension cluster was shown to be associated with the highest HR of mortality 2.48 (2.43–2.53) among all identified clusters arising from the clustering analysis.

Conclusion
Given the stronger association between multimorbidity and all-cause mortality and greater opportunity costs in younger populations, prevention and management of early-onset multimorbidity are warranted. (248 words)
Engaging science across cultures: building a research community of Buddhist monastics and undergraduate and faculty mentors
Authors: Goldberg David , Poppitz George , Sonsurkar Sayli , Manuel Joshua , Klaus Jacob , Zhang Eric , Goldberg Michael , Gray Kelsey , Eisen Arri 
Published: June 2024

AbstractEmory University has had a long relationship with His Holiness the Dalai Lama through the Emory-Tibet Science Initiative. Recently the Tenzin Gyatso Science Scholars, who are Tibetan Buddhist monastics that reside and take courses on Emory’s campus, were enrolled in a novel science research course designed and taught by undergraduate students at Emory. The goal of this study was to build a research community of Buddhist monastics who worked alongside undergraduate and graduate mentors to complete projects in R1 research laboratories, and the course was designed as preparation for these efforts. The course covered aspects of the scientific method and focused on enhancing engagement and motivation of the Scholars to pursue science research. Knowledge acquisition was assessed through quizzes, affect changes were assessed through focus group interviews, and overall course success was measured through Principal Investigator surveys. Conceptual knowledge and overall average improvement increased significantly week-to-week. Changes in affect for self-efficacy, belonging, knowledge, and future applications/drive trended towards improvement in each respective category. Finally, all seven Monastic Scholars who participated in the research curriculum were enrolled in R1 research experiences after conclusion of the course, and their principal investigators positively evaluated the preparedness and motivation of the monastics. The curriculum detailed here and its implementation facilitated cross-cultural education and successfully transitioned students from the classroom into research laboratories.
The measurement errors of google trends data
Authors: Liu Kerry 
Published: June 2024

AbstractGoogle Trends is a popular data source that has been utilized in hundreds of studies across various fields, including information technology, business, economics, healthcare, and political science. While several previous research has addressed sampling error issues, this article focuses on the measurement errors resulting from changes in Google Trends' data collection method. By examining key phrases such as ‘covid-19,’ ‘decoupling China,’ and ‘debt trap diplomacy,’ this article reveals that, after 2022 when the data collection method was updated, Google Trends generates search results for terms that were not yet coined or yields too few results. These ‘strange’ search results indicate the presence of measurement errors in Google Trends data. Scholars are advised to validate the contents of Google Trends data through additional steps. In particular, authors in fields like business, economics, and healthcare are encouraged to replicate their research conducted before 2022 to assess the forecasting errors arising from the new data sets retrieved after that period.
Can ChatGPT provide high-quality patient information on male lower urinary tract symptoms suggestive of benign prostate enlargement?
Authors: Puerto Nino Angie K. , Garcia Perez Valentina , Secco Silvia , De Nunzio Cosimo , Lombardo Riccardo , Tikkinen Kari A. O. , Elterman Dean S. 
Published: June 2024

Abstract

Background
ChatGPT has recently emerged as a novel resource for patients’ disease-specific inquiries. There is, however, limited evidence assessing the quality of the information. We evaluated the accuracy and quality of the ChatGPT’s responses on male lower urinary tract symptoms (LUTS) suggestive of benign prostate enlargement (BPE) when compared to two reference resources.

Methods
Using patient information websites from the European Association of Urology and the American Urological Association as reference material, we formulated 88 BPE-centric questions for ChatGPT 4.0+. Independently and in duplicate, we compared the ChatGPT’s responses and the reference material, calculating accuracy through F1 score, precision, and recall metrics. We used a 5-point Likert scale for quality rating. We evaluated examiner agreement using the interclass correlation coefficient and assessed the difference in the quality scores with the Wilcoxon signed-rank test.

Results
ChatGPT addressed all (88/88) LUTS/BPE-related questions. For the 88 questions, the recorded F1 score was 0.79 (range: 0–1), precision 0.66 (range: 0–1), recall 0.97 (range: 0–1), and the quality score had a median of 4 (range = 1–5). Examiners had a good level of agreement (ICC = 0.86). We found no statistically significant difference between the scores given by the examiners and the overall quality of the responses (p = 0.72).

Discussion
ChatGPT demostrated a potential utility in educating patients about BPE/LUTS, its prognosis, and treatment that helps in the decision-making process. One must exercise prudence when recommending this as the sole information outlet. Additional studies are needed to completely understand the full extent of AI’s efficacy in delivering patient education in urology.