bluuebunny/crossref_metadata_2025_split huggingface dataset:
Understanding Student Perceptions of Artificial Intelligence as a Teammate
Authors: Marrone Rebecca , Zamecnik Andrew , Joksimovic Srecko , Johnson Jarrod , De Laat Maarten 
Published: September 2024

AbstractThis article examines students' opinions regarding the use of artificial intelligence (AI) as a teammate in solving complex problems. The overarching goal of the study is to explore the effectiveness of AI as a collaborative partner in educational settings. In the study, 15 groups of grade 9 students (59 students total) were assigned a challenging problem related to space exploration and were given access to an AI teammate. Following the task, the students participated in focus group discussions to gain insight into their perspectives on collaborating with AI. These discussions were analysed using thematic analysis to identify key themes. Epistemic Network Analysis was then used to quantify and visualise this data. The results suggest that students perceive AI with regard to two main themes: Trust in AI and the Capability of AI. The study's outcomes shed light on how students perceive AI and provide practical recommendations for educators to effectively incorporate AI into classrooms. Specifically, the recommendations include strategies for building student trust in AI systems through Explainable AI processes. This, in turn, encourages collaboration between humans and AI and promotes the development of AI literacy among students. The findings of this study are a valuable addition to the ongoing discussion on AI in education and offer actionable insights for educators to navigate the integration of AI technologies in support of student learning and growth. The scientific contribution of this study lies in its empirical investigation of student-AI interaction, providing evidence-based insights for enhancing educational practices.
“Embracing the essence of student voice…then doing something with the data”: One district’s critical use of evidence
Authors: Duane Addison , Hafen Quinn , Morales Luca , Jones Tiffany M. , Shapiro Valerie B. 
Published: September 2024

Abstract
School climate surveys are frequently used to collect information about student experiences in school. Less is known about how educators use survey data after survey administration. This paper explores one school district’s critical use of evidence to promote equitable change. We conducted eight semi-structured interviews with district and school leaders to investigate their uses of evidence. Through our qualitative, reflexive thematic analysis, we generated six themes: (1) using evidence to provide a common language; (2) bringing attention to trends to shift staff understanding of problems, (3) making structural changes, (4) planning for professional learning, (5) following up directly with students, and (6) engaging with the community. Findings illustrate how education leaders can apply a critical lens to their generation and use of evidence. We explore how the strategic use of evidence is needed to advance the broader goal of fostering school change and improving school climate for all students.
Pathways to success: a machine learning approach to predicting investor dynamics in equity and lending crowdfunding campaigns
Authors: Porro Rosa , Ercole Thomas , Pipitò Giuseppe , Vessio Gennaro , Loglisci Corrado 
Published: September 2024

AbstractCrowdfunding has evolved into a formidable mechanism for collective financing, challenging traditional funding sources such as bank loans, venture capital, and private equity with its global reach and versatile applications across various sectors. This paper explores the complex dynamics of crowdfunding platforms, particularly focusing on investor behaviour and investment patterns within equity and lending campaigns in Italy. By leveraging advanced machine learning techniques, including XGBoost and LSTM networks, we develop predictive models that dynamically analyze real-time and historical data to accurately forecast the success or failure of crowdfunding campaigns. To address the existing gaps in crowdfunding analysis tools, we introduce two novel datasets—one for equity crowdfunding and another for lending. Moreover, our approach extends beyond traditional binary success metrics, proposing novel measures. The insights gained from this study could support crowdfunding strategies, significantly improving project selection and promotional tactics on platforms. By enhancing decision-making processes and providing forward-looking guidance to investors, our computational model aims to empower both campaign creators and platform administrators, ultimately improving the overall efficacy and sustainability of crowdfunding as a financing tool.
Marine heatwave in the Oyashio region in 2022/23 and its impact on subsurface dissolved oxygen
Authors: Kawai Yoshimi , Oka Eitarou , Sato Kanako , Hosoda Shigeki , Kido Shoichiro 
Published: September 2024

Abstract
The Oyashio region east of northern Japan has experienced frequent marine heatwaves (MHWs) since 2010, and in the summer and fall of 2022, sea surface temperature hit a record high as of that year. This study examined the impact of the 2022/23 MHW on dissolved oxygen (DO) by analyzing observations from a vessel and biogeochemical Argo floats. It was found that warm saline water from the Kuroshio Current intruded at ~ 42°N in July. DO anomalies from the climatology above a depth of 200 m were negatively correlated with the temperature anomalies at the same depth, while the opposite was true for deeper depths. In the density coordinate, DO and temperature anomalies exhibited a strong negative correlation when the potential density (σ
θ) was less than ~ 27.0 kg m−3. Thus, it was demonstrated that subsurface DO anomalies could be statistically predicted from temperature and salinity fields using this relationship. Notably, DO anomalies could be divided into components related to isopycnal mixing and density-surface heaving. This decomposition revealed a dynamical process, whereby the intrusion of the Kuroshio water, which is lighter than the Oyashio water, pushed down the density surfaces, causing oxygenation. Meanwhile, isopycnal mixing tended to mitigate the increase of DO concentration since DO concentration was smaller in the south than in the north on an isopycnal surface of σ
θ < 27.0 kg m−3. This study clarified that, during the 2022/23 MHW, deoxygenation occurred near the surface owing the warming, whereas the DO concentration increased in the subsurface layer.
Load torque estimation for cable failure detection in cable-driven parallel robots: a machine learning approach
Authors: Bettega Jason , Piva Giulio , Richiedei Dario , Trevisani Alberto 
Published: September 2024

AbstractThis paper proposes a method for cable failure detection in cable-driven parallel robots (CDPRs) with arbitrary architecture, which is based on the estimates of the motor load torques, together with machine learning algorithms. By just exploiting the dynamic model of each actuator in the conditions of no load, an open-loop load torque observer is designed for each motor to estimate the presence of a load coupled through a cable. Since such a load instantaneously goes to zero for the motor with a broken cable, a simple but effective and robust signature of failure can be inferred to provide reliable detection even in the case of various model mismatches. Additionally, the load torque observer is not computationally demanding since just motor measurements are required, thus avoiding any direct measurement (and a dynamic model as well) on the end-effector. The detection of a failure is made through supervised classification algorithms based on artificial intelligence. The training of the machine learning algorithm is based on a “hybrid” approach: the dataset includes several failure cases, which are numerically generated through a system digital twin developed through the multibody system theory, together with measurements of the real system in nonfailing conditions. Different classification algorithms are considered, together with different sets of input variables to be fed to the classifier. Four numerical examples are proposed by showing the method capability in handling both fully actuated and redundantly actuated CDPRs under cable failure, both rigid and flexible cables, and also evaluating the response in the presence of cable slackness.
The role of dynamic friction in the appearance of periodic oscillations in mechanical systems
Authors: González-Carbajal J. , García-Vallejo D. , Domínguez J. , Freire E. 
Published: September 2024

AbstractThis article investigates the appearance of periodic mechanical oscillations associated with the transition between static and dynamic friction regimes. The study employs a mechanical system with one degree of freedom and a friction model recently proposed by Brown and McPhee, whose continuity and differentiability properties make it particularly appropriate for an analytical treatment of the equations. A bifurcation study of the system, including stability analysis, transformation to normal form and numerical continuation techniques, reveals that stable periodic orbits can be created either by a supercritical Hopf bifurcation or by a saddle-node bifurcation of limit cycles. The influence of all system parameters on the appearance of periodic oscillations is investigated in detail. In particular, the effect of the friction model parameters (static-to-dynamic friction ratio and transition speed between the static and dynamic regimes) on the bifurcation behavior of the system is addressed.
Spaced recall reduces forgetting of fundamental mathematical concepts in a post high school precalculus course
Authors: Lindquist Diane S. , Sparrow Brenda E. , Lindquist Joseph M. 
Published: September 2024

AbstractThe retention of fundamental mathematical skills is imperative to provide a foundation on which new skills are developed. Educators often lament about student retention. Cognitive scientists and educators have explored teaching methods that produce learning which endures over time. We wanted to know if using spaced recall quizzes would prevent our students from forgetting fundamental mathematical concepts at a post high school preparatory school where students attend for 1 year preparing to enter the United States Military Academy (USMA). This approach was implemented in a Precalculus course to determine if it would improve students’ long-term retention. Our goal was to identify an effective classroom strategy that led to student recall of fundamental mathematical concepts through the end of the academic year. The concepts that were considered for long-term retention were 12 concepts identified by USMA’s mathematics department as being fundamental for entering students. These concepts are taught during quarter one of the Precalculus with Introduction to Calculus course at the United States Military Academy Preparatory School. It is expected that students will remember the concepts when they take the post-test 6 months later. Our research shows that spaced recall in the form of quizzing had a statistically significant impact on reducing the forgetting of the fundamental concepts while not adversely effecting performance on current instructional concepts. Additionally, these results persisted across multiple sections of the course taught at different times of the day by six instructors with varying teaching styles and years of teaching experience.
PSMA PET/CT imaging and its application to prostate cancer treatment
Authors: Otani Tomoaki , Nakamoto Ryusuke , Umeoka Shigeaki , Nakamoto Yuji 
Published: September 2024

AbstractRecognition of the importance of prostate-specific membrane antigen (PSMA) PET/CT in the diagnosis of prostate cancer has steadily increased following the publication of extensive data on its diagnostic accuracy and impact on patient management over the past decade. Several recent clinical trials and investigations regarding PSMA PET/CT have been ongoing in our country, and this examination is expected to become increasingly widespread in the future. This review explains the characteristics of PSMA PET/CT, its diagnostic capabilities and superiority over other modalities, the three proposed PSMA PET/CT interpretation criteria (the European Association of Nuclear Medicine [EANM], the Prostate Cancer Molecular Imaging Standardized Evaluation [PROMISE], and the PSMA Reporting and Data System [PSMA-RADS]), and the application of PSMA PET/CT to prostate cancer treatment (improvement of local control, irradiation of oligometastases, and salvage radiotherapy), incorporating actual clinical images and the latest findings.
Hsa_circYARS interacts with miR-29a-3p to up-regulate IREB2 and promote laryngeal squamous cell carcinoma progression
Authors: Guo Zizhao , Zhao Yuxia , Guo Naicai , Xu Meng , Wang Xiaolei 
Published: September 2024

Abstract
Objective
This study was to investigate the carcinogenic capacity of circYARS in laryngeal squamous cell carcinoma (LSCC) and to reveal its potential mechanism as a competitive endogenous RNA.

Methods
The differentially expressed circRNA and mRNA in LSCC were detected by RT-qPCR. Dual luciferase reporter assay and RIP were conducted to test the interaction between circYARS, miR-29a-3p, and IREB2. The functional effects of these molecules were investigated by CCK-8, flow cytometry, colony formation assay, Transwell, Western blot, and xenotransplantation mouse models.

Results
In LSCC tissues and cell lines, circYARS and IREB2 levels were enhanced, while miR-29a-3p level was lowered. Depleting circYARS led to decreased IREB2 by promoting miR-29a-3p expression. As a result of miR-29a-3p enhancement or circYARS silence, the proliferative, migratory, and invasion of cancer cells were suppressed and apoptosis was stimulated.

Conclusion
circYARS is involved in the tumorigenicity and progression of LSCC through the miR-29a-3p/IREB2 axis, providing strategies and targets for therapeutic intervention of LSCC.
Composition operators on the algebra of Dirichlet series
Authors: Contreras Manuel D. , Gómez-Cabello Carlos , Rodríguez-Piazza Luis 
Published: September 2024

AbstractThe algebra of Dirichlet series $$\mathcal {A}({{\mathbb {C}}}_+)$$

A
(

C
+

)

consists on those Dirichlet series convergent in the right half-plane $${{\mathbb {C}}}_+$$

C
+

and which are also uniformly continuous there. This algebra was recently introduced by Aron, Bayart, Gauthier, Maestre, and Nestoridis. We describe the symbols $$\Phi :{{\mathbb {C}}}_+\rightarrow {{\mathbb {C}}}_+$$

Φ
:

C
+

→

C
+

giving rise to bounded composition operators $$C_{\Phi }$$

C
Φ

in $$\mathcal {A}({{\mathbb {C}}}_+)$$

A
(

C
+

)

and denote this class by $$\mathcal {G}_{\mathcal {A}}$$

G
A

. We also characterise when the operator $$C_{\Phi }$$

C
Φ

is compact in $$\mathcal {A}({{\mathbb {C}}}_+)$$

A
(

C
+

)

. As a byproduct, we show that the weak compactness is equivalent to the compactness for $$C_{\Phi }$$

C
Φ

. Next, the closure under the local uniform convergence of several classes of symbols of composition operators in Banach spaces of Dirichlet series is discussed. We also establish a one-to-one correspondence between continuous semigroups of analytic functions $$\{\Phi _t\}$$

{

Φ
t

}

in the class $$\mathcal {G}_{\mathcal {A}}$$

G
A

and strongly continuous semigroups of composition operators $$\{T_t\}$$

{

T
t

}

, $$T_tf=f\circ \Phi _t$$

T
t

f
=
f
∘

Φ
t

, $$f\in \mathcal {A}({{\mathbb {C}}}_+)$$

f
∈
A
(

C
+

)

. We conclude providing examples showing the differences between the symbols of bounded composition operators in $$\mathcal {A}({{\mathbb {C}}}_+)$$

A
(

C
+

)

and the Hardy spaces of Dirichlet series $$\mathcal {H}^p$$

H

p

and $$\mathcal {H}^{\infty }$$

H

∞

.
Dynamic Harmonic Distortion Analysis and Mitigation Strategies for DC Third Rail Systems
Authors: Hoo Dick Sang , Chua Kein Huat , Lim Yun Seng , Wang Li , Rajasekar N. 
Published: September 2024

AbstractHarmonic distortions in DC third rail systems can cause overheating of electric motors and transformers. Single-tuned filters and shunt active harmonic filters (SAHFs) are often used to mitigate the harmonic distortions. However, there is a lack of studies on the effects of train dynamics on harmonic distortions. This paper aims to investigate the influence of dynamic train behaviors for a DC third rail system and provide recommendations for the design of single-tuned filters and SAHFs to mitigate the harmonic distortions. The traction power supply system of a DC third rail system in Malaysia is modeled using ETAP-eTraX and MATLAB-Simulink software for the investigation. The ETAP-eTraX software is used to accurately compute the dynamic behavior of the train, while MATLAB-Simulink allows for the assessment of the impact of train behavior on the rail track, as well as the harmonic effect of the railway power network on the train. The findings showed that the SAHF exhibits strong adaptability and superior filtering performance compared to the single-tuned filter in addressing dynamic harmonic distortion in traction power supply systems. This study emphasizes the significance of incorporating harmonic mitigation devices, particularly for managing dynamic harmonic distortion based on actual train consumption patterns.
Human-centered approaches in working environments needs ethical reflection—Experiences from KARL
Authors: Krings Bettina-Johanna , Frey Philipp 
Published: September 2024

AbstractIn our paper, we discuss some insights from our work in the regional Centre of Competence of Artificial Intelligence (KARL), which deals with the implementation and application of Artificial Intelligence in working and learning environments. We present a conceptual framework that we have developed to define social, legal and ethical dimensions of AI in working environments. As a first step, the article describes the definition of these aspects within the technical development processes in KARL with an emphasis on ethical issues. Furthermore, a practical example is used to illustrate how normative premises can be elaborated to inform the design process of AI-systems. Next, the process of development and implementation of AI-systems in working environments is taken into account. The article explicitly emphasises the importance of ethical reflection, i.e. on norms such as fairness, social sustainability and the creation of meaningful work, to inform in human-centered approaches to AI-based work.Practical Relevance: This paper discusses a process-oriented, human-centred approach to AI-based work. The joint negotiation and definition of “human-centred work with AI” in each specific context with all concerned stakeholders lies at its heart. The concretisation of these implications is of great importance for the practical implementation of the overarching concept, as it is only in practice that it becomes clear whether and how a participatory design approach is successful, which areas of tension and problems arise and how these can be dealt with.
Reliability and validity assessment of instrument to measure sustainability practices at shipping ports in India
Authors: Kishore L. , Pai Yogesh P. , Shanbhag Parthesh 
Published: September 2024

AbstractSustainability has emerged as one of the most critical factors influencing the competitiveness of maritime shipping ports. This emergence has led to a surge in research publications on port sustainability-related topics. However, despite the increasing awareness and adoption of sustainability practices, documented literature on empirical studies with survey and interview data is very limited. Moreover, the existence of validated instruments to objectively assess sustainability through sustainability practices for shipping ports in India needs to be traced. This study contributes by validating an instrument to evaluate objectively sustainability practices in shipping ports by adopting a four-stage process, starting with item identification based on an extensive literature review, instrument evaluation by subject matter experts, assessing of the instrument with suitable content validation indices, and finally evaluating the validity and reliability of the hypothesized theoretical model. For content validation, Content Validity Index, Cohens Kappa coefficient, and Lawshe’s Content Validity Ratio were computed with the assessment by a subject matter expert panel comprising six members from the port industry as well as academicians cum researchers in the field of shipping ports. The content-validated instrument was administered to 200 samples comprising officer category port employees. The measurement model was evaluated and validated using the Confirmatory Factor Analysis to assess the extent to which the measured variables represent the theoretical construct of the study and ascertain the factor structure. The empirically validated instrument met the required guidelines of model fit, reliability, and construct validity measures and was found to be a confirmed model for measuring sustainability practices in shipping ports. Structural Equation Modeling methodology was adopted to explain the variance and the path relationship between the higher-order and lower-order constructs of sustainability. The results indicate that the economic dimensions are the major contributors to the overall sustainability of the port as they drive investments in environmental and social dimensions, leading to overall sustainable development. The study’s findings will be helpful for researchers, academicians, policymakers, and industry practitioners working towards sustainability practices that contribute to sustainable growth and development in the shipping industry.
Large language models, politics, and the functionalization of language
Authors: Kudina Olya , de Boer Bas 
Published: September 2024

AbstractThis paper critically examines the political implications of Large Language Models (LLMs), focusing on the individual and collective ability to engage in political practices. The advent of AI-based chatbots powered by LLMs has sparked debates on their democratic implications. These debates typically focus on how LLMS spread misinformation and thus hinder the evaluative skills of people essential for informed decision-making and deliberation. This paper suggests that beyond the spread of misinformation, the political significance of LLMs extends to the core of political subjectivity and action. It explores how LLMs contribute to political de-skilling by influencing the capacities of critical engagement and collective action. Put differently, we explore how LLMs shape political subjectivity. We draw from Arendt’s distinction between speech and language and Foucault’s work on counter-conduct to articulate in what sense LLMs give rise to political de-skilling, and hence pose a threat to political subjectivity. The paper concludes by considering how to reconcile the impact of LLMs on political agency without succumbing to technological determinism, and by pointing to how the practice of parrhesia enables one to form one’s political subjectivity in relation to LLMs.