bluuebunny/crossref_metadata_2025_split huggingface dataset:
On ‘There Is’: Logical Investigations into Instantial Sentences
Authors: Ben-Yami Hanoch 
Published: February 2025

Abstract
I distinguish between instantial sentences (There are elephants that swim), particular quantification, and predication of existence in natural language. I explore the logical relation between the first two, while the last one is shown independent of either. I continue to consider the incorporation of the three kinds of sentence in the Quantified Argument Calculus (Quarc). I provide formalisations that preserve the logical relations specified earlier. I also extend the analysis to quantified instantial sentences (There are five elephants that swim) and modal ones. A conclusion of this work is that quantification and instantial sentences provide no guide to ontology.
A size-based contingency approach to family firms’ performance: the role of family power
Authors: Galavotti Ilaria , D’Este Carlotta , Cerrato Daniele 
Published: February 2025

Abstract
This paper aims to analyze the effect played by firm size, as a fundamental dimension of a firm’s architecture, in shaping the relationship between corporate governance and a family firm’s performance. Specifically, we explore whether and how family power, conceptualized through the three governance dimensions of family ownership, family involvement in the board, and family leadership—namely family CEO and CEO duality—affects the firm’s profitability, contingent upon its size. From a theoretical standpoint, we build on agency theory, stewardship theory, and socio-emotional wealth (SEW) theory to develop a unifying contingency framework on the role of the firm's size in determining both the magnitude and direction of the family power effects on performance. Drawing on a dataset of 548 firm-year observations of Italian-listed family firms in the 2014–2021 period, we find evidence that in smaller family firms, where the preservation of the socio-emotional endowment and family legacy is more pronounced, both the benefits and costs associated with agency and stewardship mechanisms are strengthened.
Degrees of Doubt: Overqualification as a Blind Spot at the Base of the Knowledge Economy
Authors: Pantea Maria-Carmen 
Published: February 2025

Abstract
Europe has the most educated generation in its history, yet an alarming number of graduates are overqualified. This paper explores the intersection between education and work from the perspectives of those involved in a sector that is prone to overqualification: the call centres of Romania’s thriving business service sector. Based on over 100 in-depth interviews with young people, human resource personnel, and managerial staff at different levels of seniority, the paper maps subjective views about overqualification. Despite the objective classification of employment in call centres in terms of national occupational codes, most interviewees, regardless of their role, were unlikely to read their employment through the lenses of overqualification. Young people internalised the gap between education and employment and learned not to attach strong employment-related expectations to degrees, especially those in the social sciences and humanities (non-STEM). Managers and HR staff highly regarded company-specific skills and had learned to tap into a group of graduates without clear labour market routes. The paper conceptualises the availability of jobs at the bottom of the ‘knowledge economy’ in connection with employment structures available in the economic semi-periphery and problematises politically the question of overqualification.
Systematic Review of Self-Reported Multidimensional Instruments Used to Measure Quality of Life and Subjective Well-Being of Children and Adolescents
Authors: Winn Kaung Mon , Woode Maame Esi , Aydin Gozde , Chen Gang 
Published: February 2025

Abstract
There is a growing interest in measuring quality of life (QoL) and subjective well-being (SWB) to assess societal progress and well-being. Despite numerous studies exploring the QoL and SWB of adult populations, there has been a limited number of studies focusing on young people. Measuring QoL and SWB of children and adolescents provides valuable insights into shaping public policies aimed at promoting their well-being. This study aims to conduct systematic reviews of self-reported multidimensional measures assessing the QoL and SWB of children and adolescents along with their psychometric properties. The first stage identified the measures of interest, followed by the second stage focused on finding validation studies for the identified measures. Both systematic reviews followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Eight databases were searched to retrieve the studies. During the first stage, a total of 29 measures used to assess the QoL and SWB of children and adolescents were identified. Subsequently, 68 validation studies that met the eligibility criteria were identified during the second stage. This study reports the key characteristics of each instrument and the policy-relevant life domains that are commonly captured by these instruments. Their psychometric properties are discussed. The findings of the study will facilitate policymakers and researchers to make a choice of validated measure(s) for their specific application to improve the well-being of children and adolescents. Besides, they will assist in developing new paediatric QoL or SWB measures when appropriate measures are not available.
Paediatric Renal Tumors: A State-of-the-Art Review
Authors: Salzillo Cecilia , Cazzato Gerardo , Serio Gabriella , Marzullo Andrea 
Published: February 2025

Abstract

Purpose of Review
Pediatric renal tumors comprise a wide range of conditions, both malignant and benign, that affect children and require a multidisciplinary approach for optimal diagnosis and treatment. This review offers an in-depth analysis of the epidemiology, diagnosis, treatment options, outcomes, and survival of major pediatric renal tumors.

Recent Findings
Wilms tumor, or nephroblastoma, is the most common form of renal tumor in children, characterized by growth from primitive renal cells. Standard treatment involves a combination of surgery, chemotherapy and, in some cases, radiation therapy, with the aim of removing the tumor, preventing recurrence and maximizing the chances of long-term recovery. Less common pediatric renal tumors, such as renal clear cell sarcoma, renal cell carcinoma, mesoblastic nephroma, and malignant rhabdoid tumor, require similarly careful and individualized management. Therapeutic strategies, which depend on the characteristics of the tumor, the stage of the disease and the individual response to therapy, may include surgery, chemotherapy, radiotherapy and, in some cases, molecular targeted therapies, immunotherapies and genetic and epigenetic therapies.

Summary
The management of pediatric kidney tumors requires the involvement of a multidisciplinary team of specialists to ensure accurate evaluation, optimal treatments and long-term follow-up. The aim is to maximize the prospects for recovery and improve the quality of life of patients and their families. Advances in innovative, personalized therapies represent an important opportunity to further improve clinical outcomes in these patients.
Unlocking EFL learners’ insights into ChatGPT use for L2 writing: The impacts of usage frequency and gender variations
Authors: Aksakallı Canan , Daşer Zeynep 
Published: February 2025

Abstract
The emergence of ChatGPT as a powerful chatbot has revolutionized global education in general and language learning in particular since it can offer opportunities for students and teachers. Against this backdrop, this study aimed to explore whether gender and usage frequency affect English learners’ perceptions of ChatGPT use in second language (L2) writing beyond the classroom. In accordance with the Technology Acceptance Model (Davis, 1989), this research was conducted at English major departments at a state university in Türkiye. Employing a fully integrated mixed methods approach and adopting a sequential explanatory design, the present study recruited 874 Turkish undergraduate students. Quantitative data were collected through the Demographic Information Form and the ChatGPT Perception Scale, whereas qualitative data were gathered through semi-structured interviews. Exploratory and confirmatory factor analyses were performed to assess the reliability and validity of the scale. Descriptive and inferential statistics were run for the quantitative data analysis, while qualitative data were analyzed using thematic analysis. The results revealed that many participants used ChatGPT in second language writing, though rarely, and held positive perceptions of the tool. Gender-based variations were detected in terms of usage frequency but not overall perceptions; furthermore, there was a significant positive correlation between usage frequency and perceptions. Based on the integration of both data sources, contradictory, expanded, and confirmed outcomes emerged, and explicit implications were suggested regarding the use of ChatGPT for L2 writing outside the classroom.
Specific molecular imaging of BALB/c model mice with Graves’ ophthalmopathy based on high expression of insulin-like growth factor 1 receptor
Authors: Zhang Zhiting , Ma Ziyu , Wang Xuan , Zhou Yaqian , Wu Ruixin , Shen Yiming , Li Ning , Jia Qiang , Zhang Hong , Li Wei , Zheng Wei 
Published: February 2025

Abstract

Objective
At present, most of the targeted imaging based on insulin-like growth factor 1 receptor (IGF-1R) is for tumor research, and there is no IGF-1R-targeted imaging for Graves’ ophthalmopathy(GO). This study aims to develop a peptide probe, 99mTc-ZIGF1R:4551-GGGC, targeting the IGF-1R, and to achieve specific imaging in Graves’ disease (GD) animal models exhibiting GO.

Methods
99mTc-ZIGF1R:4551-GGGC probe was synthesized using a direct labeling method and its labeling efficiency assessed via instant thin-layer chromatography (ITLC). Western blot analysis confirmed the overexpression of IGF-1R in malignant melanoma B16F10 cells. Subsequent SPECT/CT whole-body imaging of B16F10 tumor-bearing mice evaluated the probe’s targeting accuracy. In addition, a GO model was established using an electroporation immunoassay, followed by serological and histopathological examinations. The GO models then underwent 99mTc-ZIGF1R:4551-GGGC SPECT/CT imaging to assess eye-targeted imaging capabilities.

Results
The peptide probe exhibited a labeling efficiency exceeding 90%. Both GD and GO models were effectively created via electroporation immunoassay. Imaging results indicated significant accumulation and retention of the peptide probes in the tumors of B16F10 tumor-bearing mice. In the GO models, probe uptake was predominantly observed in retrobulbar tissues, contrasting with primary accumulation in the lungs and gastrointestinal tract in normal mice, where only minimal tracer was observed in retrobulbar tissues. Notably, GO mice demonstrated higher probe uptake and prolonged retention.

Conclusion
This study successfully established GD and GO models, reducing the duration of the immune cycle. Moreover, a peptide probe targeting IGF-1R was synthesized, enabling specific imaging of retrobulbar tissues in GO models.
A pilot study of generative AI video for patient communication in radiology and nuclear medicine
Authors: Badawy Mohamed K. , Kharmwan Kitiwat , Carrion Daniel 
Published: February 2025

Abstract

Purpose
Effective communication for radiation imaging procedures is critical, especially for patients with literacy or language barriers. Generative Artificial Intelligence (GenAI) provides a new approach for creating personalised, multilingual patient education materials. This pilot study evaluates the effectiveness of GenAI, specifically using HeyGen, in creating personalised patient information videos in the Thai language.

Methods
We created an avatar of a medical physicist using HeyGen. Two English health information scripts on nuclear medicine and radiology were translated into Thai using HeyGen’s translation tool, and videos were created with the avatar delivering the content in Thai. Thirteen native Thai-speaking medical physicists and postgraduate students evaluated the videos using a 5-point Likert scale, focusing on translation accuracy, naturalness of delivery, and usefulness as a patient education tool. The Bilingual Evaluation Understudy scoring system was used to assess translation quality objectively.

Results
Both videos received high median scores for translation accuracy (median of 4.0). The BLEU scores were 0.56 and 0.66, indicating good translation quality. Participants reported minor issues with formal language and unnatural phrasing but found the videos understandable and valuable overall. Feedback suggested improving the naturalness of the avatar’s delivery to increase relatability.

Conclusions
Our pilot study shows that GenAI can effectively create and translate personalised patient information videos into Thai, helping to bridge communication gaps in radiation-related procedures. While minor issues remain, the findings indicate that tools like HeyGen could significantly improve patient communication, particularly for those who face language barriers.
Sulfatase modifying factor 2 as a predictive biomarker for urothelial carcinoma
Authors: Kuo Wei-Ting , Lee Yi-Chen , Liao Jia-Bin , Tseng Ching-Jiunn , Yang Yi-Fang 
Published: February 2025

Abstract
Sulfatases mediate the sulfation level of cell-surface heparan sulfates to regulate signal transduction, thereby promoting cancer progression. Sulfatase activation requires a sulfatase modifying factor (SUMF) for the modification of its catalytic domain. The role of the SUMF family in urothelial carcinoma (UC) has not been adequately evaluated. In this study, we used an online database and immunohistochemistry to assess genetic changes and the mRNA and protein expression of SUMFs and related candidate targets in UC. We found that SUMF1 and SUMF2 were amplified in UC tissues. High SUMF2 mRNA levels were associated with poor overall survival (OS) and disease-free survival (DFS) in bladder UC (BLCA) from The Cancer Genome Atlas (TCGA) dataset. High SUMF2 protein levels were associated with grade (P < 0.001), T status (P = 0.01), and stage (P = 0.006) in patients with BLCA. We also examined SUMF2 expression levels in upper tract UC (UTUC). SUMF2 expression was associated with stage (P = 0.046), poor OS (P = 0.0022), and DFS (P = 0.019) in patients with UTUC. Knockdown of SUMF2 significantly reduced the migration and invasion abilities of 5637 cells. Furthermore, SUMF2 mRNA levels negatively correlated with FBXW7 mRNA levels in BLCA. The SUMF2
high/FBXW7
low expression profile predicted the worst survival in BLCA. Taken together, SUMF2 expression is linked to unfavorable clinical outcomes in patients with UC and may serve as a useful prognostic biomarker for UC staging.
Artificial Neural Networks as Digital Twins for Whispering Gallery Mode Optical Sensors in Robotics Applications
Authors: Ali Amir R. , Ramadan Mohamed W. A. 
Published: February 2025

Abstract
This paper investigates the use of artificial neural networks (ANNs) as a viable digital twin or alternative to the typical whispering gallery mode (WGM) optical sensors in engineering systems, especially in dynamic environments like robotics. Because of its fragility and limited endurance, the WGM sensor which is based on micro-optical resonators is inappropriate in these kinds of situations. In order to address these issues, the paper suggests an ANN that is specifically designed for the system and makes use of the WGM sensor’s high-quality factor (Q-factor). By extending the applicability and endurance to dynamic contexts and reducing fragility problems, the ANN seeks to give high-resolution measurement. In order to minimize post-processing requirements and maintain system robustness, the study goal is for the ANN to function as a representative predictor of the WGM sensor output. The GUCnoid 1.0 humanoid robot is used in the paper as an example to show how the WGM optical sensors may improve humanoid robot performance for a variety of applications. The results of the experiments demonstrate that the sensitivity, precision, and resolution of ANN outputs and actual WGM shifts are equivalent. As a consequence, current obstacles to the widespread use of high-precision sensing in the robotics industry are removed, and the potential of ANNs as virtual substitutes or the digital twin for genuine WGM sensors in robotics systems is validated. So, this paper can be very beneficial not only to the sensing technologies that are used in robotics, which are subjected to the dynamic environments, but also to the industrial automation and human-machine interface.
Detection of outliers in dam monitoring time series with autoencoders
Authors: Irazábal Joaquín , Salazar Fernando , Silva-Cancino Nathalia , Vicente David J. 
Published: February 2025

Abstract
Dam monitoring is crucial for behavior analysis and safety assessment. The data recorded by monitoring systems are the basis of behavioral models. Ensuring the quality of these data is vital for making informed decisions and improving prediction accuracy. However, monitoring data often contain errors that need to be corrected before use. As data acquisition systems become increasingly automated, the resulting large databases present challenges that conventional methods cannot effectively address. This work proposes a methodology based on autoencoders for the automatic detection of outliers in dam monitoring data. The model is calibrated with a general procedure, which showed to be effective in all situations considered. The application of this method to data series from deformations, piezometers, joint openings and seepage flow in two different dams demonstrates its ability to detect all strong outliers without false positives. Only a few potential outliers, some of which are hard to classify after an exploratory analysis, were overlooked by the model. While the final decision on record validation should be made by experienced technicians, this approach can effectively screen large databases of measurements, aiding in the efficient identification of outliers.
Accelerating the computation of Shapley effects for datasets with many observations
Authors: Rabitti Giovanni , Tzougas George 
Published: February 2025

Abstract
Shapley effects are enjoying increasing popularity as importance measures. These indices allocate the variance of the quantity of interest among every risk factor, and a risk factor explaining more variance than another one is more important. Recently, Vallarino et al. (ASTIN Bull J IAA, 2023. https://doi.org/10.1017/asb.2023.34) propose a computational strategy for Shapley effects using the idea of cohorts of similar observations. However, this strategy becomes extremely computationally demanding if the dataset contains many observations. In this work we propose a computational shortcut based on design of experiments and clustering techniques to speed up the computational time. Using the well-known French claim frequency dataset, we demonstrate the huge reduction in computational time, without a significant loss of accuracy in the estimation of the Shapley effects.
Pristine graphene oxide treatment of wastewater from a typical sub-tropical mine in Chegutu, Zimbabwe
Authors: Kalitsilo F. R. , Hashemi H. , Mombeshora E. T. 
Published: February 2025

Abstract
Mining activities in sub-tropical regions are one of the major contributors to environmental contamination and therefore require monitoring and mitigation methodologies. The study investigated the composition of the real-world wastewater from mine explosions and explored the potential of graphene oxide as an adsorbent. Heavy metals, namely, Fe (12.10 ppm), Cu (40.70 ppm), Cr (148 ppm) and Pb (0.03 ppm) were present. The optimal pH, adsorbent dose, temperature, and contact time for heavy metal removal were 12.08, 0.5 g, 25 °C and 0.5 h, respectively. The basic conditions were favourable for efficient removal through the adsorption method. Kinetic modelling indicated adsorption via pseudo-second-order kinetics, insinuating the influence of oxygen moieties of graphene oxide. Furthermore, the Langmuir isotherm revealed favourable removal of Fe, Cu, and Cr. The study indicated potential hazards of current mining activities, especially unmonitored illegal mines in sub-tropical regions. These findings highlight the prospects of graphene oxide as a practical and effective adsorbent for water resource recovery facilities. Therefore, the study demonstrated the capability to adopt pristine graphene oxide in a simple protocol using simple setups for wastewater recovery in the sub-tropical regions in a natural matrix.
Hyperammonemic encephalopathy requiring hemodialysis in a child with distal renal tubular acidosis
Authors: Huseynli Behruz , Akkuzu Emine , Büyükkaragöz Bahar , Bakkaloğlu Sevcan A. 
Published: February 2025

Abstract
A 3.5-year-old girl with genetically proven distal renal tubular acidosis presented with lethargy, after numerous episodes of vomiting and poor feeding. Laboratory investigations revealed severe metabolic acidosis, hypokalemia and a serum ammonia level of 515 mmol/L (normal range: 19–50 mmol/L). Despite treatment with sodium bicarbonate, potassium supplementation, sodium benzoate and carglumic acid, her condition required hemodialysis, which resulted in rapid improvement in clinical and metabolic parameters. Hyperammonemia in distal renal tubular acidosis results from impaired ammonium excretion and increased ammoniagenesis due to hypokalemia and chronic metabolic acidosis, particularly during metabolic decompensation. This case had the highest ever reported serum ammonia level in distal renal tubular acidosis with encephalopathic findings, necessitating hemodialysis treatment. Routine monitoring of serum ammonia levels in distal renal tubular acidosis patients during metabolic stress is essential.

Graphical Abstract