bluuebunny/crossref_metadata_2025_split huggingface dataset:
Improving graph collaborative filtering with network motifs
Authors: Zhang Yuqi , Yu Jian , Liu Zhizhong , Wang Guiling , Nguyen Minh , Sheng Quan Z. , Wang Nancy 
Published: February 2025

Abstract
Deep learning on graphs, specifically graph convolutional networks (GCNs), has exhibited exceptional efficacy in the domain of recommender systems. Most GCNs have a message-passing architecture that enables nodes to aggregate information from neighbours iteratively through multiple layers. This enables GCNs to learn from higher-order information, but the model does not allow for direct captions of the local structural patterns. Our rationale is to investigate the effectiveness of capturing such local patterns for graph-based collaborative filtering to enhance model’s learning ability per layer. This technique combines lower-order and higher-order interactions during layer-wise propagation. In this paper, we propose MotifGCN to aggregate both lower-order and higher-order information in each graph convolution layer. Specifically, we develop dedicated algorithms of generating motif adjacency matrices. The matrices are then used for motif-enhanced neighbourhood aggregation in each layer. As this paper focuses on recommender systems, MotifGCN is built on the basis of bipartite graphs. Our experiments on four real-world datasets show that MotifGCN has a superior performance compared to various state-of-the-art methods.
Artificial intelligence in managing retinal disease—current concepts and relevant aspects for health care providers
Authors: Riedl Sophie , Birner Klaudia , Schmidt-Erfurth Ursula 
Published: February 2025

Summary
Given how the diagnosis and management of many ocular and, most specifically, retinal diseases heavily rely on various imaging modalities, the introduction of artificial intelligence (AI) into this field has been a logical, inevitable, and successful development in recent decades. The field of retinal diseases has practically become a showcase for the use of AI in medicine. In this article, after providing a short overview of the most relevant retinal diseases and their socioeconomic impact, we highlight various aspects of how AI can be applied in research, diagnosis, and disease management and how this is expected to alter patient flows, affecting also health care professionals beyond ophthalmologists.
Image-based deep learning for smart digital twins: a review
Authors: Islam Md Ruman , Subramaniam Mahadevan , Huang Pei-Chi 
Published: February 2025

Abstract
Smart Digital Twins (SDTs) are being increasingly used to virtually replicate and predict the behaviors of complex physical systems through continual data assimilation, enabling the optimization of the performance of these systems by controlling the actions of systems. Recently, the Deep Learning (DL) models have significantly enhanced the capabilities of SDTs, particularly for tasks such as predictive maintenance, anomaly detection, and optimization. In many domains, including medicine, engineering, and education, SDTs use image data (image-based SDTs) to observe, learn, and control system behaviors. This paper focuses on various approaches and associated challenges in developing image-based SDTs by continually assimilating image data from physical systems. The paper also discusses the challenges in designing and implementing DL models for SDTs, including data acquisition, processing, and interpretation. In addition, insights into the future directions and opportunities for developing new image-based DL approaches to develop robust SDTs are provided. This includes the potential for using generative models for data augmentation, developing multi-modal DL models, and exploring the integration of DL models with other technologies, including Fifth Generation (5 G), edge computing, and the Internet of Things (IoT). In this paper, we describe the image-based SDTs, which enable broader adoption of the Digital Twins (DTs) paradigms across a broad spectrum of areas and the development of new methods to improve the abilities of SDTs in replicating, predicting, and optimizing the behavior of complex systems.
In the Aftermath of an Ethical Violation: Do Family Firms Suffer More Than Non-family Firms and Why?
Authors: Nyffenegger Bettina , Madison Kristen , Lude Maximilian , Prügl Reinhard , Hack Andreas 
Published: February 2025

Abstract
Research indicates that family firms often engender a sense of trustworthiness among stakeholders. However, little is known as to whether this trustworthiness is beneficial or detrimental to family firms in the face of an ethical scandal. Ethical transgressions can profoundly undermine stakeholders’ perceptions of a firm’s integrity and benevolence. Our research examines how stakeholders perceive and react to ethical transgressions committed by family firms, as compared to those committed by non-family firms. Drawing upon expectancy violations theory and social identity theory, we theorize that while family firms inherently enjoy a higher degree of trustworthiness, they suffer significantly more in the aftermath of an ethical transgression. Two scenario-based experimental studies support our theorizing, demonstrating that family firms experience a steeper decline in trustworthiness following an ethical transgression than do non-family firms. We uncover the psychological processes behind this finding, revealing that this vulnerability is attributed to heightened stakeholder expectations and pronounced identification with family firms. We empirically show that expectancy violations primarily diminish integrity perceptions, while identity threats degrade benevolence perceptions of family firms. This research broadens the understanding of ethics in family firms, highlighting how their initially perceived trustworthiness may become a double-edged sword during ethical crises.
Cell-Level Modelling of Homeostasis in Confined Epithelial Monolayers
Authors: Chaithanya KVS , Rozman Jan , Košmrlj Andrej , Sknepnek Rastko 
Published: February 2025

Abstract
Tissue homeostasis, the biological process of maintaining a steady state in tissue via control of cell proliferation and death, is essential for the development, growth, maintenance, and proper function of living organisms. Disruptions to this process can lead to serious diseases and even death. In this study, we use the vertex model for the cell-level description of tissue mechanics to investigate the impact of the tissue environment and local mechanical properties of cells on homeostasis in confined epithelial tissues. We find a dynamic steady state, where the balance between cell divisions and removals sustains homeostasis, and characterise the homeostatic state in terms of cell count, tissue area, homeostatic pressure, and the cells’ neighbour count distribution. This work, therefore, sheds light on the mechanisms underlying tissue homeostasis and highlights the importance of mechanics in its control.
Uses and challenges of digital twins-based augmented reality in operator training and data visualization in process manufacturing lines
Authors: Perno Matteo , Hvam Lars , Haug Anders 
Published: February 2025

Abstract
Despite the widespread interest in Industry 4.0 technologies, only a few empirical studies focus on augmented reality (AR) coupled with digital twins (DTs). Thus, little is known about the usefulness and challenges of these in manufacturing contexts. To address this gap in the literature, the present study conducts an action research study of a DT-based AR project in a process manufacturing company. Specifically, first, two DT-based AR applications for training new operators and live data visualizations, respectively, are developed. These applications are tested by relevant employees, who are subsequently interviewed. Through analysis of interview transcripts, four overall uses of DT-based AR are identified: (1) training of new staff; (2) data visualization; (3) plant design validation; and (4) maintenance. Furthermore, several challenges related to the use of this technology are identified, which are organized under four themes: (1) safety issues; (2) cost issues; (3) convenience issues; and (4) accessibility issues. These findings are organized into a model illustrating the relationships between the uses and challenges of DT-based AR in process manufacturing.
An Investigation Into the Notion of Complex Systems
Authors: Mazzocchi Fulvio 
Published: February 2025

Abstract
This article investigates the concept of ‘complex systems’. While not searching for some necessary and sufficient conditions that are valid for all of them, it acknowledges that complex systems can take different shapes, mainly depending on the features of their internal organization and how they interact with their environment. It then advocates a networked notion of complex systems that can accommodate their rich phenomenology and the various circumstances making them, focusing on two types of these systems: (i) one that is mainly characterized by the generation of stable patterns through self-reinforcing dynamics at the lower levels (Bénard convection) and (ii) a distinct one characterized by a more complex organization that makes them ‘minimally decomposable’ and showing autonomy (living systems). The article also assumes that the complexity of a system is analyzable by focusing on two distinct yet interrelated aspects: (i) the features of the system itself and (ii) the relationship between the system and an observer. Its final part discusses how complex systems cannot be adequately represented by a single model or description and how this is another distinctive aspect of their complexity.
Towards neural-network-guided program synthesis and verification
Authors: Kobayashi Naoki , Sekiyama Taro , Sato Issei , Unno Hiroshi 
Published: February 2025

Abstract
We propose a novel framework of program and invariant synthesis called neural network-guided synthesis (NeuGuS). We first show that, by suitably designing and training neural networks, we can extract logical formulas over integers from the weights and biases of the trained neural networks. Based on the idea, we have implemented a tool to synthesize formulas from positive/negative examples and implication constraints, and obtained promising experimental results. We also discuss two applications of our synthesis method. One is the use of our tool for qualifier discovery in the framework of ICE-learning-based CHC solving, which can in turn be applied to program verification and inductive invariant synthesis. Another application is to a new program development framework called oracle-based programming, which is a neural-network-guided variation of Solar-Lezama’s program synthesis by sketching.
Phase field approach for managing multi-fragment interactions in load-bearing fractured media
Authors: Chao Correas A. , Acquesta D. , Corrado M. 
Published: February 2025

Abstract
This work introduces a novel approach for characterizing the residual load bearing capacity of fractured components based on the Phase Field fracture model. The underlying idea involves exploiting this well-established framework for fracturing materials and applying it to mechanically loaded domains in which fracture has already occurred. Hence, the continuous phase field here portrays the smeared representation of known crack patterns, based on which the unilateral contact interactions between the crack lips are enforced through a suitable strain energy decomposition. This allows for a theoretically robust and implicit treatment of the originally discontinuous problem while remaining in a continuum framework. As such, the proposed approach avoids the numerically challenging definition and management of conventional contact pairs, thus proving to be especially promising for its application to domains with multiple fragments. Besides presenting the theoretical foundation and algorithmic convenience of the approach, its accuracy and representativeness are proven against theoretical predictions and numerical results from Finite Element models featuring conventional contact interactions.
Baumol’s cost disease in acute versus long-term care: Do the differences loom large?
Authors: Celebi Kaan , Hartwig Jochen , Sandqvist Anna Pauliina 
Published: February 2025

Abstract
Baumol’s (Am Econ Rev 57: 415–426, 1967) model of ‘unbalanced growth’ yields a supply-side explanation for the ‘cost explosion’ in health care. Applying a testing strategy suggested by Hartwig (J Health Econ 27: 603–623, 2008), a sprawling literature affirms that the ‘Baumol effect’ has both a statistically and economically significant impact on health care expenditure growth. Skeptics maintain, however, that the proliferation of hi-tech medicine in acute care is clearly at odds with the assumption underlying Baumol’s model that productivity-enhancing machinery and equipment is only installed in the ‘progressive’ (i.e. manufacturing) sector of the economy. They argue that Baumol’s cost disease may affect long-term care, but not acute care. Our aim in this paper is to test whether Baumol’s cost disease affects long-term care and acute care differently. Our testing strategy consists in combining Extreme Bounds Analysis (EBA) with an outlier-robust MM estimator. Using panel data for 23 OECD countries, our results provide robust and statistically significant evidence that expenditures on both acute care and long-term care are driven by Baumol’s cost disease, even though the effect on long-term care expenditures is more pronounced.
“Slow” Network Research? A Mixed-Methods Approach Towards Funeral Status Representation in the Late Urnfield Period
Authors: Deicke Aline 
Published: February 2025

Abstract
From its earliest stages on, the rise of computational approaches in the humanities—whether in archaeology, history, or digital humanities more generally—has been accompanied by discussions and critical reflections on the way in which data-driven research methods are informed by the representation of research objects as data structures. Various dimensions, challenges, and characteristics can be roughly divided into three intersecting aspects: the subjectivity of data, their complexity, and their size. Archaeological network analysis as a formal, quantitative method is situated firmly within the tension between these fields, and many authors focus on the application of network research to archaeological data while respecting their complex nature. This paper adds to this growing body of work by focusing on the specificities of a medium-sized data set that offers multiple perspectives on a complex question of social archaeology: the study of intersecting social identities and their materialisation in funeral assemblages, particularly of a collective identity of high status-individuals or “elites”, during the Late Urnfield Period. It offers a mixed-methods approach that centres quantitative results and qualitative contextualization across different scales, and minimises loss of information and context, while transparently disclosing its practices of data selection, pre-processing, and analysis. In doing so, it aims to make the reflective positionings of “slow data” and “slow technology” productive for a methodology of “slow networks”.
CEO personality traits and compensation: evidence from investment efficiency
Authors: Du Yao , Hasan Iftekhar , Lin Chih-Yung , Lu Chien-Lin 
Published: February 2025

Abstract
We examine the effects of the big five personalities of CEOs (openness, conscientiousness, extroversion, agreeableness, and neuroticism) on their annual compensation. We hand-collect the tweets of S&P 1500 CEOs and use IBM’s Watson Personality Insights to measure their personalities. CEOs with high ratings of agreeableness and conscientiousness get more compensation. We further find that the firms with these CEOs outperform their peers due to better investment efficiency. Firms are willing to pay higher compensation for talent, especially for firms with better operations, located in states with higher labor unionization, or facing higher competition in the product market. Overall, CEO personality is a valid predictor of CEOs’ compensation.
Bronchial foreign body caused by a grasshopper in a dog
Authors: Maggi Giulia , Rosi Elena , Cupido Simone , Palma Salvatore , Marchesi Maria Chiara 
Published: February 2025

Abstract
An 11-year-old dog living in a rural area of Italy was evaluated for a persistent cough. Diagnostic imaging findings, combined with the clinical history and physical examination, revealed focal pneumonia, raising suspicion of a vegetal foreign body. Bronchoscopy identified a foreign body (a grasshopper) partially obstructing the left caudal bronchus, and its removal was successfully performed. Insects should be considered potential bronchial foreign bodies in the differential diagnosis.
Population parameters of an expanding Iberian wild goat population in Southern Pyrenees, Spain
Authors: Herrero Juan , García-Serrano Alicia , Prada Carlos , García-González Ricardo 
Published: February 2025

Abstract
The escape and establishment of Iberian wild goats, Capra pyrenaica, from an enclosure in the 1990s marked the beginning of the recovery of the species in the Pyrenees. This population has occupied part of the Prepyrenees and has contacted another population reintroduced in France since 2014. It coexists with other wild ungulates, including the feral and domestic goats Capra hircus that has been living free since the 1960s. Today it’s the largest Iberian wild goat Pyrenean population. Between 2006 and 2022 we monitored the population and its expansion based on vantage points, itineraries and testimonies. The results indicate: (i) a population, of uncertain genetic origin, in numerical (15% average annual growth) and areal expansion, with the capacity to connect with other populations; (ii) an estimate of at least 500 individuals; (iii) in the process of expansion in contact with Iberian wild goats from France; (iv) sympatry with feral and domestic goat population in its main nucleus whose estimate exceeds 2000 specimens and (v) hybridization with feral and domestic goats. In 2022 sustainable hunt started with a hunting quota of 20 individuals. Genetic characterization and the establishment of an international coordinated monitoring are two of the current priorities.
Narrative meaning-making at the crossroads between life and death: a qualitative study into contemplating literary texts with advanced cancer patients.
Authors: van Poecke Niels , Scherer-Rath Michael , Weeseman Yvonne , Bood Zoë , Christophe Nirav , Dörr Henny , de Vos-Geelen Judith , Beeker Aart , de Klerk Gerty , Bras Eric , Vlug Hugo , Bossink Frans , Savelkoul Frans , Timmermans Liesbeth M. , Helmich Esther , Sprangers Mirjam A. G. , van Laarhoven Hanneke W. M. 
Published: February 2025

Abstract

Purpose
Advanced cancer patients may perceive their disease as an experience of contingency: a (sudden) disruption of the life-narrative evoking existential concerns such as loss of meaning and identity. The research project In Search of Stories aimed to investigate whether and how reading and discussing literary texts assisted participants in integrating their diagnosis as the experience of contingency into their life-narrative.

Methods
This qualitative study reports on interviews with 25 advanced cancer patients, who read a story from a curated collection of 10 literary texts. They discussed the story with a spiritual caregiver, using a reading guide to structure the conversation. The interviews were thematically analyzed using template analysis.

Results
Participants identified with contingency experiences and related existential concerns presented in the texts, including loss of meaning and identity, bodily alienation, and social estrangement. Reading and discussing literary texts also enabled participants to engage in self-regulation; in exploring how to relate to devalued emotions and attitudes, and in further developing their identity post-diagnosis.

Conclusions
A structured reading of literary texts revolving around contingency experiences enables advanced cancer patients to identify with and articulate emotions, attitudes, and existential concerns such as loss of meaning and identity. This allows them to break down barriers in talking about their illness experiences and to transition towards acceptance of their diagnosis as the experience of contingency.

Implications for Cancer Survivors
Reading and discussing literary texts about contingency may support people with advanced cancer to integrate their own experience of contingency into the life-narrative.
Procedural and Functional Sources of Trust in Police in Pakistan
Authors: Hassan Bilal 
Published: February 2025

Abstract
Police in Pakistan is one of the least trusted institutions, yet limited research has explored the underlying causes of this distrust. This study examines trust in police in the provinces of Punjab (Lahore) and Khyber Pakhtunkhwa (KP; Peshawar) using performance and procedural justice frameworks. Based on survey data collected in 2016 from individuals with direct interactions with the police, the study investigates factors influencing public trust in these provinces, which have adopted distinct policing approaches. The findings show that procedural evaluations, such as satisfaction with investigation time, access to information, and adherence to human rights, are strong predictors of trust in police in both provinces. However, functional evaluations, including the ability to detect crimes, prevent crime, and apprehend criminals, significantly influence trust only in KP. The trust model performs better in KP, where the police benefit from greater administrative autonomy and reduced political interference compared to Punjab. These findings underscore that police reforms, such as depoliticization and administrative autonomy, are essential for improving police performance and fostering public trust.
Psychometric properties of the Warwick-Edinburgh Mental Well-being Scale (WEMWBS) in the general Romanian population and professionals working with autistic students
Authors: Iacob Claudia Iuliana , Dumitru Tabacaru Cristina , Yildiz Mustafa , Folostina Ruxandra 
Published: February 2025

Abstract
This study aimed to translate the Warwick-Edinburgh Mental Well-being Scale (WEMWBS) into the Romanian language and to examine its psychometric properties on two samples: the general adult population (N = 508) and specialists working with autistic students (N = 204). Specifically, we assessed construct validity, convergent validity with overall well-being and life satisfaction, divergent validity with prodromal symptoms and general health status, test-retest reliability at two weeks, and social desirability bias. The Romanian WEMWBS demonstrated robust construct, convergent, and divergent validity, supported by good internal consistency (Cronbach's alpha = 0.90 for the general population and 0.91 for professionals) and two-week test-retest reliability. These results are similar to those reported for samples from other countries. Despite concerns about social desirability bias, the study revealed no evidence of respondents consciously providing socially desirable answers, although a slight tendency toward unconsciously favourable responses was observed. Caution is warranted in generalising the results due to age- and gender-related sample limitations. In conclusion, the Romanian WEMWBS is a valid tool for assessing mental well-being, offering cross-cultural applicability and the potential for methodological comparisons across various professional groups.