bluuebunny/crossref_metadata_2025_split huggingface dataset:
5G in construction: from deployment to evaluation for robotic applications
Authors: Lee Hyung Joo , Krishnan Ajith , Brell-Cokcan Sigrid 
Published: April 2024

AbstractA stable, low-latency, and high-bandwidth communication infrastructure is indispensable for effective teleoperation or automated control of construction machinery. Despite the vital importance of this aspect, limited exploration has been undertaken thus far. Our work presents a comprehensive study that begins by detailing the strategic deployment of a 5G network, underscoring its tailored features and functionalities designed specifically to meet the demanding requirements of construction sites. Through a series of diverse experiments involving different types of full-scale construction machines, we vividly demonstrate the tangible benefits of 5G technology in this context. Leveraging comparative studies with WiFi technology and real-world tests, this methodology highlights the improvements in communication facilitated by 5G networks. This holistic exploration not only fills a critical gap in understanding the potential of 5G in construction machinery communication but also offers a roadmap for leveraging this technology to further develop the construction industry.
Climate Variability of Air Temperature and Its Warming Trends in the Arabian Gulf
Authors: Al Senafi Fahad , Al Rushaid Tariq , Al Mukaimi Mohammad 
Published: April 2024

AbstractOver a 41-year period (1979–2019), the climate of the Arabian Gulf (Gulf) exhibited notable variability. This variation, influenced by mesoscale and globalscale meteorological and climatic determinants, showed temperature fluctuations, predominantly in the Northern Gulf (N Gulf). The N Gulf recorded an average temperature of 25.9 °C, a noticeable 3 °C higher than the broader Gulf average. This period marked extreme temperature records, with a peak at 53.8 °C in July 2016, paralleling the highest known temperatures in Asia. Data reveals a warming trend (0.1–0.6 °C per decade) in the region, with the N Gulf’s rise surpassing global trends. The years 2014–2019 were notably warmer, impacting overall trends, and 1997 was the transitional year shifting from cooler to warmer climates. The N Gulf’s seasonal dynamics are also transforming, with extended summers and shortened winters. In this study, we employed empirical orthogonal function (EOF) decomposition analysis to examine the interannual to multidecadal fluctuations in air temperature within the Gulf from 1979 to 2019, using hourly air temperature data from the Watch Forcing Dataset (WFDE5) generated from the fifth generation (ERA5) European Centre for Medium-Range Weather Fore-casts (ECMWF). Through this method, we discerned three principal EOF modes, which together accounted for 82% of the air temperature variability in the Gulf, highlighting external influences such as North Atlantic Oscillation (NAO), El Nino-Southern Oscillation (ENSO), and Atlantic Multidecadal Oscillation (AMO). The data for these external influences were sourced from the National Oceanic and Atmospheric Administration (NOAA) Physical Sciences Laboratory. These findings stress the pressing need for detailed climate studies and mitigation strategies for a rapidly warming Gulf region, especially the N Gulf.
Teaching plant pathology: a forty-five year long journey
Authors: Gullino Maria Lodovica 
Published: April 2024

AbstractThis paper describes the experience of teaching plant pathology in Italy and traces the teaching environment over a period of more than 45 years, split into three main periods: 1975–2000; 2001–2020; and after 2020. The three periods are marked by different attitudes towards agriculture and, consequently, by a variable attractiveness of agricultural study programmes for students, as well as significant changes in the population of teachers and students. The teaching experience has been described by focusing on the changes that have taken place, from the perspectives of both students and teachers, all considered in an environment of continuous transformation. The changing importance of agriculture, the different approaches of people (consumers) towards agriculture, and how it has influenced students’ choices are considered. Data related to student enrolment at the College of Agriculture of the University of Turin have been used to provide real figures, which are useful to obtain a better understanding of the changes in the student population, also considering the different attractiveness of Agricultural Sciences, Forestry and Food Science, as well as the variations in the composition of the female student population, which increased from 28% in the late 1970’s to 38% in 2020. Female students now show the highest interest in Food Science Courses. The changes in the students and teachers’ backgrounds and attitudes, as well as in the teaching and learning methods are considered, and some critical considerations are drawn, also on the basis of the developed personal experience. Moreover, the effects of the Covid-19 pandemic disruption are discussed.
Exploring Information-Gathering Techniques in Medical and Dental Interviews for Child Abuse and Neglect: A Comprehensive Scoping Review of Existing Gaps
Authors: Ko Hayley , Baugerud Gunn Astrid , Köpp Unni-Mette Stamnes , Johnson Miriam S. , Szyszko Hovden Ewa A. 
Published: April 2024

AbstractHealthcare providers may regularly encounter victims of suspected child abuse or neglect. Conversations during medical evaluations and examinations may yield essential information and reliable accounts of a child’s experiences of abuse. However, knowledge of appropriate communication skills when interacting with suspected child abuse victims and information gathering techniques have not been well explored in healthcare providers. This scoping review assesses the state of the literature concerning medical interviewing in cases of child abuse and explores the communication and information gathering techniques used by healthcare providers when interacting with suspected child abuse victims. Ten studies were included in the analysis, collectively revealing a limited body of knowledge on information gathering techniques in child abuse cases in healthcare settings. Collecting a comprehensive medical history has emerged as a crucial tool for guiding medical examinations and assessments. The findings also highlight the absence of standardised guidelines for healthcare professionals to gather information from victims of child abuse. This review did not identify any studies that investigated the information gathering skills of oral healthcare providers in the context of child abuse. Further research is needed, and the creation of standardised protocols aimed at improving information gathering techniques within healthcare settings for cases of child abuse could prove beneficial. Improved communication and information gathering techniques can significantly contribute to the management of suspected cases of child abuse, safeguarding the well-being of vulnerable children.
Implementing Decentralized Clinical Trials in Australia through Teletrials: Where to From Here?
Authors: Symons Tanya , Woollett Anne , Zalcberg John , Eckstein Lisa 
Published: April 2024

AbstractImplementation of decentralized approaches can improve access to clinical trials. The Australian government has focused on a teletrial model, which resources and upskills health care organisations to enable collaboration in trials to extend to rural and remote areas. This commentary describes the Australian teletrial model, its context within the established DCT model, its value, and likely challenges moving forward.
SStackGNN: Graph Data Augmentation Simplified Stacking Graph Neural Network for Twitter Bot Detection
Authors: Shi Shuhao , Chen Jian , Wang Zhengyan , Zhang Yuxin , Zhang Yongmao , Fu Chengqi , Qiao Kai , Yan Bin 
Published: April 2024

AbstractEnsemble learning has the potential to enhance the efficacy of feeble classifiers significantly and is increasingly being utilized in Twitter bot detection. Previous methods have utilized stacking techniques to train the primary classifiers, implementing cross-validation to mitigate overfitting and enhance predictive accuracy. However, cross-validation substantially amplifies the computation time associated with stacking. To overcome this challenge, this paper presents a novel approach, the Simplified Stacking Graph Neural Network (SStackGNN), specifically designed for the detection of social bots. Our methodology leverages the power of Graph Neural Networks (GNNs) as base classifiers, enabling effective capturing of inter-account interactions. In addition, a Multilayer Perceptron (MLP) serves as a secondary classifier, amalgamating the outcomes of the foundational classifiers to generate final predictions, thereby enhancing the predictive performance of the GNNs. Instead of relying on cross-validation and distinct base classifier structures, we employ node-level, edge-level, and feature-level graph data augmentation techniques to acquire diverse foundational classifiers. This approach significantly alleviates the computational complexity while achieving superior performance. Experimental results demonstrate that our proposed SStackGNN outperforms other approaches.
Assessing Trends in Hospitalizations for Breast Cancer among Women in Korea: A Utilization of the Korea National Hospital Discharge In-depth Injury Survey (2006–2020)
Authors: Hwang Jieun , Jang Jeong-Hoon 
Published: April 2024

Abstract
Objective
Breast cancer poses a significant health threat globally and particularly in Korea, where mortality rates have risen notably. In this study, we analyzed the characteristics of breast cancer patients discharged in Korea over the past 15 years and explored the association between comorbidities and treatment outcomes to propose effective strategies for managing cancer patients. Understanding these dynamics is vital for informing tailored management strategies and optimizing healthcare system sustainability.

Methods
This study utilized cross-sectional data from the Korea National Hospital Discharge In-depth Injury Survey from 2006 to 2020. Each year, among patients discharged from hospital with 100 beds or more, those identified with breast cancer patients were based on their primary diagnosis code (C50) according to the ICD-10, as recorded in their medical records.

Results
Between 2006 and 2020, an estimated 499,281 breast cancer patients were discharged, with an average annual percent change (AAPC) of 5.2% (95% CI 4.2–6.2, p <.05). A notable increase in AAPC was particularly evident among those aged 60 years and old. Across all age groups, there was a consistent increasing trend in the risk of mortality as the CCI score increased (p <.05). The risk of comorbidity was more pronounced in younger age groups compared to older age groups.

Conclusions
The increasing life expectancy is expected to lead to a continued rise in the number of elderly breast cancer patients. Countermeasures are needed to address this trend through appropriate diagnosis and treatment planning. Particularly, considering comorbidities in breast cancer treatment plans is necessary to promote positive treatment outcomes, especially in younger breast cancer patients.
Developing effective prompts to improve communication with ChatGPT: a formula for higher education stakeholders
Authors: Nazari Mostafa , Saadi Golsa 
Published: April 2024

AbstractThe escalating integration of artificial intelligence (AI) technologies, particularly the widespread use of ChatGPT in higher education, necessitates a profound exploration of effective communication strategies. This paper addresses the critical role of prompt development as a skill essential for university instructors engaging with ChatGPT. While emphasizing the practical implications for higher education, the study introduces a novel two-layered AI prompt formula, considering both components and elements. In methodology, the research synthesizes insights from existing models and proposes a tailored approach for ChatGPT, addressing its unique characteristics and the contextual elements within higher education. The results highlight the formula’s flexibility and potential applications in diverse fields, from syllabus planning to assessment. Moreover, the study identifies limitations inherent in ChatGPT, emphasizing the need for instructors to exercise caution in its usage. In conclusion, the paper underscores the evolving landscape of AI in education, envisaging specialized versions of ChatGPT for academic settings and advocating for the proactive adoption of ethical frameworks in the use of AI in higher education. This study serves as a foundational contribution to the discourse on effective AI communication in educational settings.
Compliant mechanism design of combined aircraft wing for stable separation
Authors: Zhang Q. , Jia S. , Chen J. , Zhang J. 
Published: April 2024

AbstractStable separation is a crucial condition that must be met in order for combined aircraft to successfully engage in cooperative flight. In order to achieve the desired fast and controlled separation, this paper proposes a novel design for a torque-driven compliant separation mechanism. By taking into account the compliance characteristics of a sinusoidal acceleration function curve, a mechanical model for the separation mechanism is developed. By utilising the Coulomb friction law, an accurate determination of the aerodynamic load distribution under various conditions is achieved. Subsequently, the relationship between the unlocking moment and the aerodynamic load is derived based on these findings. Through the utilisation of the finite element method, a model of the separation mechanism is generated. To ensure the safety and reliability of the compliant separation mechanism, the mechanical properties of the structural materials are thoroughly analysed under the maximum aerodynamic load. Subsequently, the separation mechanism structure is constructed and subjected to testing in order to showcase the compliance characteristics. In addition, this paper conducts a simulation to analyse the impact of flight speed and angle-of-attack on the separation process. By doing so, the optimal conditions for separation are determined. The methods and findings presented in this study have the potential to contribute valuable insights to the design of combined aircraft.
Artificial neural network for preliminary design and optimisation of civil aero-engine nacelles
Authors: Tejero F. , MacManus D. , Heidebrecht A. , Sheaf C. 
Published: April 2024

AbstractWithin the context of preliminary aerodynamic design with low order models, the methods have to meet requirements for rapid evaluations, accuracy and sometimes large design space bounds. This can be further compounded by the need to use geometric and aerodynamic degrees of freedom to build generalised models with enough flexibility across the design space. For transonic applications, this can be challenging due to the non-linearity of these flow regimes. This paper presents a nacelle design method with an artificial neural network (ANN) for preliminary aerodynamic design. The ANN uses six intuitive nacelle geometric design variables and the two key aerodynamic properties of Mach number and massflow capture ratio. The method was initially validated with an independent dataset in which the prediction error for the nacelle drag was 2.9% across the bounds of the metamodel. The ANN was also used for multi-point, multi-objective optimisation studies. Relative to computationally expensive CFD-based optimisations, it is demonstrated that the surrogate-based approach with ANN identifies similar nacelle shapes and drag changes across a design space that covers conventional and future civil aero-engine nacelles. The proposed method is an enabling and fast approach for preliminary nacelle design studies.
The Sale of Offices, Corruption, and Formalization: A Comparative Study of China and France in the Seventeenth and Eighteenth Centuries
Authors: Huang Xinyu 
Published: April 2024

AbstractThis paper provides a detailed exploration of the sale of offices in China and France in the seventeenth and eighteenth centuries. In France, the sale of offices became deeply integrated into the officialdom, effectively serving as a formal institution. It was a part of the financial framework and contributed to the operation of the bureaucracy. However, this practice led to public dissatisfaction due to concerns about the fairness of the judicial system. Conversely, in China, the sale of offices was less formalized and more directly associated with corruption due to the close connection with informal income and the challenge to the formal system of imperial civil examinations. It was considered an ad hoc, informal, and pragmatic solution to financial emergencies. The sale of offices, in a different context, was seen as having both positive and negative aspects, with its impact varying, depending on the specific function it served.
Epidemiology of carbapenem-resistant organisms in Alameda County, California, 2019–2021
Authors: Marusinec Rachel , Shemsu Munira , Lloyd Tyler , Kober Brendan M. , Heaton Dustin T. , Herrera Jade A. , Gregory Misha , Varghese Vici , Nadle Joelle , Trivedi Kavita K. 
Published: April 2024

Abstract

Objective:
Carbapenem-resistant organisms (CROs) are an urgent health threat. Since 2017, Alameda County Health Public Health Department (ACPHD) mandates reporting of carbapenem-resistant Enterobacterales (CRE) and encourages voluntary reporting of non-CRE CROs including carbapenem-resistant Acinetobacter baumannii (CRAB) and carbapenem-resistant Pseudomonas aeruginosa (CRPA). Surveillance data from ACPHD were analyzed to describe the epidemiology of CROs and target public health interventions.

Methods:
Healthcare facilities in Alameda County reported CRO cases and submitted isolates to ACPHD to characterize carbapenemase genes; deaths were identified via the California Electronic Death Registration System. CRO cases with isolates resistant to one or more carbapenems were analyzed from surveillance data from July 2019 to June 2021.

Results:
Four hundred and forty-two cases of CROs were reported to Alameda County from 408 patients. The county case rate for CROs was 29 cases per 100,000 population, and cases significantly increased over the 2-year period. CRPA was most commonly reported (157 cases, 36%), and cases of CRAB increased 1.83-fold. One-hundred eighty-six (42%) cases were identified among residents of long-term care facilities; 152 (37%) patients had died by January 2022. One hundred and seven (24%) cases produced carbapenemases.

Conclusions:
The high burden of CROs in Alameda County highlights the need for continued partnership on reporting, testing, and infection prevention to limit the spread of resistant organisms. A large proportion of cases were identified in vulnerable long-term care residents, and CRAB was an emerging CRO among this population. Screening for CROs and surveillance at the local level are important to understand epidemiology and implement public health interventions.
Achromobacter cluster related to COVID-19 supply chain issues
Authors: Scales Mary Ellen , Gallagher Megan C. , Haessler Sarah , Lindsey Kristy , Maryanski Michele , Mathew Manju , Moore Franklin , Hogan Karen , Gilmore Morgan , Peters Stacey , Smith Kristin 
Published: April 2024

Abstract
Isolation of an unusual organism, Achromobacter xylosoxidans, from 2 cardiac surgical patients on the same day prompted an investigation to search for cases and cause. An extensive review demonstrated a pseudo-outbreak related to practices to conserve laboratory saline due to short supply resulting from supply chain shortage from the coronavirus disease 2019 pandemic.
Third-Party and Bankruptcy Effects under Chinese Trust Law: Comparisons with English Trust Law
Authors: Jing Hui 
Published: April 2024

AbstractIn English law, the trust's third-party and bankruptcy effects contribute significantly to its wide use in commercial transactions. In view of the trust's attractiveness in conducting commercial dealings, China has also introduced the trust model into its domestic legal system to enhance its financial infrastructure. However, given the extent to which Chinese law has been influenced by the Roman-Germanic tradition, China's replication of the trust's third-party and bankruptcy effects has encountered doctrinal obstacles. Drawing upon the experience of its Northeast Asian forerunners, China has established two mechanisms to achieve the third-party and bankruptcy effects: the regime of trust fund independence and the granting of the right of rescission to beneficiaries. These two mechanisms represent the adjustments made by Chinese legislators in the process of transplanting the trust model into the Chinese legal context. Adopting a comparative law perspective, this article examines these mechanisms in the Chinese law setting for two reasons: first, to explore the mechanisms’ constituent elements and their operation, as well as the roles of both mechanisms in the Chinese trust law system; and second, to furnish comparative law scholarship with broader insights into rule transplantation and reconciliation.
Blue versus red: partisan firm leaders and corporate culture
Authors: Jiao Anqi , Ren Honglin 
Published: April 2024

AbstractThis paper documents significant partisan divides across a range of corporate cultural values. Using panel data of 2,424 S&P 1500 firms spanning the period from 2001 to 2018, we find that firms whose top management teams lean toward the Democratic Party exhibit higher cultural values of integrity, teamwork, innovation, respect, and quality, in comparison with firms with executives leaning toward the Republican Party. In addition, we find that the partisan gap diminishes when firms have less entrenched management or locate in states with stronger judicial accountability. Our findings lend support to earlier research suggesting that leader characteristics are associated with corporate culture.
Open data, workplace relations law compliance, and digital regulation
Authors: Chen Colleen , Howe John , Kariotis Timothy , Jackson Shirley 
Published: April 2024

Abstract
This paper discusses the challenges and opportunities in accessing data to improve workplace relations law enforcement, with reference to minimum employment standards such as wages and working hours regulation. Our paper highlights some innovative examples of government and trade union efforts to collect and use data to improve the detection of noncompliance. These examples reveal the potential of data science as a compliance tool but also suggest the importance of realizing a data ecosystem that is capable of being utilized by machine learning applications. The effectiveness of using data and data science tools to improve workplace law enforcement is impacted by the ability of regulatory actors to access useful data they do not collect or hold themselves. Under “open data” principles, government data is increasingly made available to the public so that it can be combined with nongovernment data to generate value. Through mapping and analysis of the Australian workplace relations data ecosystem, we show that data availability relevant to workplace law compliance falls well short of open data principles. However, we argue that with the right protocols in place, improved data collection and sharing will assist regulatory actors in the effective enforcement of workplace laws.