bluuebunny/crossref_metadata_2025_split huggingface dataset:
Conversational pressures at work: professional roles and communication in mental healthcare settings
Authors: Drożdżowicz Anna 
Published: February 2025

Abstract
What do we owe to each other when communicating? One area where these questions become immediately relevant is that of mental healthcare settings. Mental healthcare relies heavily on communication with patients/clients. However, it has been argued that patients/clients in mental healthcare settings are often vulnerable to various forms of epistemic injustice, e.g., by not being listened to, not being taken seriously, not being considered as a source of knowledge by healthcare professionals (e.g., Crichton et al., 2017; Scrutton, 2017; Kurs & Grinshpoon 2018; Kidd, Spencer& Carel 2023). The paper investigates normative aspects of communication in settings where interlocutors occupy specific social and professional roles. I focus on the conversational pressures account, recently proposed by Goldberg (2020), and communicative interactions in mental healthcare settings, where issues of epistemic injustice and deficient communication are of great importance. I suggest that professional roles in mental healthcare settings have an impact on the normative evaluation of interlocutors, as well as the conversational pressures they are under. I discuss whether and to what extent ethical and epistemic features of the social and professional contexts can be seen as providing a direct normative source for conversational pressures. I close by sketching a map of issues that require further investigation.
The scientific realism debate and consensus reporting
Authors: Pils Raimund 
Published: February 2025

Abstract
This article shows, through both theoretical analysis and empirical evidence, that there is an absence of consensus among philosophers of science, scientists, and science communicators regarding the correctness of realist versus anti-realist interpretations of scientific theories. It is argued that integrating this finding within the current prevalent norm of consensus reporting necessitates a reconsideration of how results from the natural sciences are reported. As such, the article advances a model for science reporting that more accurately represents the complexity of scientific expert opinions, thereby aligning more closely with the actual epistemic conditions within the scientific community.
Transforming Complex Water Quality Monitoring Data into Water Quality Indices
Authors: Shaaban Nashwa A. , Stevens David K. 
Published: February 2025

Abstract
Unplanned urbanization and economic development can deteriorate water quality (WQ) and alter its beneficial usage. Continuous monitoring of biotic and abiotic parameters describing the WQ is essential to track changes and classify water resources to protect public health. Various invest significant effort, money, and time in monitoring programs. Using data from those sources is challenging due to the large number of observations, and inconsistencies in sampling time, date, stations, and gaps. This study aims to design different water quality index (WQI) models to provide policymakers, stakeholders, and water managers with a more comprehensive assessment by converting complex datasets from over 10 years, processed with the statistical software R, into consistent data sets. These datasets are then transformed into small principal components. WQ datasets of lakes and reservoirs in the western USA were chosen as case studies. The strategy of data processing is explained, and the results organized as a descriptive summary of the 12,000 observations for 31 parameters are discussed. Outputs of principal component analysis (PCA) are used to create relative and absolute WQI models for water irrigation usage and protecting cold- and warm-water species of game fish. Weighted arithmetic water quality indices are applied, and the relation between different models is examined.
Transcriptomic profiling of senescence effects on blood–brain barrier-related gene expression in brain capillary endothelial cells in a mouse model of paclitaxel-induced chemobrain
Authors: Patai Roland , Kiss Tamas , Gulej Rafal , Nyul-Toth Adam , Csik Boglarka , Chandragiri Siva Sai , Shanmugarama Santny , Tarantini Stefano , Ungvari Anna , Pacher Pal , Mukli Peter , Yabluchanskiy Andriy , Csiszar Anna , Ungvari Zoltan 
Published: February 2025

Abstract
Chemotherapy-induced cognitive impairment (CICI), commonly referred to as “chemobrain,” is a frequent and debilitating side effect experienced by cancer survivors treated with paclitaxel (PTX). Preclinical models have shown that PTX promotes cerebromicrovascular endothelial cell senescence, leading to chronic blood–brain barrier (BBB) disruption and neuroinflammation. Conversely, the elimination of senescent cells through senolytic therapies has been shown to restore BBB integrity, reduce neuroinflammation, and alleviate PTX-induced cognitive impairment. In this study, we tested the hypothesis that PTX-induced endothelial senescence alters gene expression patterns associated with BBB integrity. To investigate this, we analyzed a scRNA-seq dataset from the brains of mice treated with a clinically relevant PTX regimen alongside vehicle-treated control mice. We identified capillary endothelial cells by their distinct transcriptomic profiles and matched these profiles to known transcriptomic markers of cellular senescence. Our analysis confirmed that PTX induces senescence in capillary endothelial cells and revealed significant transcriptional alterations linked to impaired BBB function. In senescent endothelial cells, gene set enrichment analysis (GSEA) highlighted downregulated pathways associated with cell junction assembly and upregulated pathways involved in extracellular matrix remodeling and inflammatory signaling, including Vitronectin (VTN) and Pleiotrophin (PTN) pathways. Additionally, cell–cell communication analysis revealed reduced Junctional Adhesion Molecule (JAM) signaling, further implicating senescence in BBB disruption. These findings highlight endothelial senescence as a driver of BBB dysfunction through transcriptional changes and altered intercellular signaling. The enrichment of VTN and PTN pathways in the senescent state indicates a shift toward vascular remodeling and inflammation, exacerbating microvascular fragility and BBB disruption. Supported by prior experimental findings, this study suggests that targeting endothelial senescence and its downstream effects could mitigate PTX-induced BBB dysfunction and associated cognitive impairments. These results advance our understanding of CICI pathogenesis and provide a foundation for developing therapeutic strategies aimed at preserving vascular integrity.
The title of the manuscript: reorienting social relationships in the journey with cancer: a qualitative study
Authors: Erden Sengul , Yıldız Ahmet 
Published: February 2025

Abstract
Cancer threatens millions of lives each year affecting individuals as well as their loved ones in multifaceted ways. Given the far-reaching effects of the disease, the study focuses on how cancer survivors’ treatment experiences transform their perspectives on their social relationships. The data consisted of face-to-face interviews with 17 cancer patients in Turkey. The purposive sampling method was used to identify potential participants for the study and the snowball sampling method was used to reach the participants. The analysis was based on the transformative learning theory, which revealed two main themes concerning the participants’ social networks; (i) transformation in the existing social relations, and (ii) construction of new social networks and changing relationship dynamics. The findings revealed the support received from their social networks was a crucial factor in helping participants’ cope with cancer-related challenges which prompted critical reflection on their social relationships and led to perspective transformation. The participants reorganized their existing relationships, and the disease was a determining factor in their new social relationships. In their new social networks, they developed a more helpful attitude towards others, especially cancer patients. This study is critical in enabling adult educators to understand the social dynamics of transformative learning, and guide healthcare professionals in planning supportive and holistic healthcare services for patients with similar experiences.
Regional Specialization as a Driver of Potential and Realized Absorptive Capacity and Business Innovation
Authors: Sánchez-García Eduardo , Martínez-Falcó Javier , Marco-Lajara Bartolomé , Ruiz-Fernández Lorena 
Published: February 2025

Abstract
This research aims to study the influence of regional agglomeration on business innovation and the effect of absorptive capacity as a mediating variable in this relationship. The investigation has been developed using a sample of 197 firms of the energy sector, from which were obtained primary data that was analyzed using the PLS-SEM technique. The findings evidence that the degree of agglomeration of a region positively influences business innovation, while the acquisition and assimilation of new knowledge do not impact it directly but rather through its transformation and successful application by firms. In this respect, knowledge absorption competences can drive the innovation outcomes exhibited by firms situated in specialized regions. Thus, it is concluded that companies operating in specialized environments should strive to boost their knowledge absorption capabilities to maximize the benefits of their location. In this regard, managers and policymakers must be aware of the importance of fostering the agglomeration of energy enterprises and the development of their internal absorptive capacity, both potential and realized, which drives the existence of specialized knowledge and its effective leverage to promote business innovation, promoting the creation of hubs of concentrated expertise and enhancing regional competitiveness.
Moral Hermeneutics in R&D Teams: Making Sense of Conflicting Responsibilities in Technological Innovation
Authors: Innocenti Marco 
Published: February 2025

Abstract
This study adopts a hermeneutic, practice-based approach to Responsible Innovation to explore how a reflective and proactive attitude can be implemented in a start-up context. We hypothesised that a moral hermeneutics framework - rooted in post-phenomenology and theories on technology-induced value change - could provide a way to understand how practitioners in a start-up make sense of the different kinds of responsibilities in their work, balancing professional demands and standards of excellence with broader ecological and social commitments. Using in-depth interviews with the team members of a start-up R&D laboratory, we explored how they interpret their responsibilities-as-(moral)-obligations. Our findings suggest that the syntactical ways team members make sense of the relationship between these responsibilities can be useful for understanding how reflexivity can surface in this environment. We conclude by proposing that less conciliatory interpretations of conflicting responsibilities may lead to a collective search for practical solutions addressing these tensions, as long as it is embedded in a collective dialogue involving the other members’ moral perspectives and technical expertise.
Case report. Benigne urethrale poliepen op kinderleeftijd
Authors: Vermeulen Marlous L. E. , Klijn Aart J. , van der Horst E. H. J. R. , Scheepe Jeroen R. , Lammers Rianne J. M. 
Published: February 2025

Samenvatting
Een benigne urethrale poliep is een zeldzame aandoening op kinderleeftijd die kan leiden tot mictieklachten en/of hematurie. De differentiële diagnose is uitgebreid en bevat onder andere rhabdomyosarcoom. We presenteren vier casussen uit Nederland met een benigne poliep. De klachten en leeftijden variëren. De oorzaak is niet duidelijk. Mogelijk is er sprake van een restant van de buizen van Müller, maar omdat een urethrale poliep ook bij meisjes kan voorkomen, is deze verklaring omstreden. De afwijking bevindt zich meestal ter hoogte van de colliculus en wordt histologisch beschreven als fibro-epitheliale poliep. Als een maligniteit onwaarschijnlijk is, heeft een transurethrale resectie de voorkeur. Cystoscopie wordt gebruikt als diagnosticum en behandeling. Een recidief wordt niet beschreven.
The Search for an Optimal Framework for Licensing Standard-Essential Patents: Is Collective Licensing a Solution?
Authors: Opany Fidelice 
Published: February 2025

Abstract
The emergence of new technological paradigms, particularly the Internet of Things, has given rise to doubts about whether the current framework for licensing standard-essential patents (SEPs) will be effective in the near future. Consequently, there is a renewed interest in exploring multilateral licensing schemes. One such proposal seeks to establish a public quasi-pool Agency to administer SEP licensing by issuing licences, and collecting and distributing royalties among SEP holders. This article analyses the suitability of the said Agency. It finds that the envisaged Agency could improve SEP licensing by, inter alia, alleviating patent holdout and patent holdup, and reducing transactions costs. Weighed against the pursued general interests, i.e. improving SEP licensing and promoting the dissemination of standardised technologies across the EU, we find that licensing SEPs via the envisioned Agency is unlikely to disproportionately interfere with the fundamental rights of patentees.
Data-driven measurement performance evaluation of voltage transformers in electric railway traction power supply systems
Authors: Li Zhaoyang , Sun Muqi , Zhu Jun , Luo Haoyu , Wang Qi , Hu Haitao , He Zhengyou , Wang Ke 
Published: February 2025

Abstract
Critical for metering and protection in electric railway traction power supply systems (TPSSs), the measurement performance of voltage transformers (VTs) must be timely and reliably monitored. This paper outlines a three-step, RMS data only method for evaluating VTs in TPSSs. First, a kernel principal component analysis approach is used to diagnose the VT exhibiting significant measurement deviations over time, mitigating the influence of stochastic fluctuations in traction loads. Second, a back propagation neural network is employed to continuously estimate the measurement deviations of the targeted VT. Third, a trend analysis method is developed to assess the evolution of the measurement performance of VTs. Case studies conducted on field data from an operational TPSS demonstrate the effectiveness of the proposed method in detecting VTs with measurement deviations exceeding 1% relative to their original accuracy levels. Additionally, the method accurately tracks deviation trends, enabling the identification of potential early-stage faults in VTs and helping prevent significant economic losses in TPSS operations.
Operator Solutions of the Multi–valued Operator Equation $$A = BXC$$
Authors: Sandovici Adrian 
Published: February 2025

Abstract
Assume that A, B and C are three linear relations on certain linear spaces. The main objective of this note is to present some necessary and sufficient conditions for the existence of the solutions X of the operator equation

$$A = BXC$$

A
=
B
X
C

. The obtained characterizations extend and complete some known operator factorization results due to R.G. Douglas, Z. Sebestyén and D. Popovici.
On extreme value theory-based estimation of surface quality for metal additive manufacturing
Authors: Nikfar Mohsen , Irfan Shehzaib , Baugh Loren , Mahmood Samsul , Ahmad Nabeel , Liu Jia , Jackson Robert L. , Schulze Kyle , Shao Shuai , Silva Daniel F. , Vinel Alexander , Shamsaei Nima 
Published: February 2025

Abstract
Surface roughness of additively manufactured metal parts has significant impacts on the part’s performance (e.g., fatigue resistance) and poses a significant roadblock to the wider adoption of metal additive manufacturing. This work aims to show that, in some cases, it is possible to estimate the depth of the deepest valley of an additively manufactured part with a relatively high accuracy using either only line measurements from a contact profilometer (and limited areal scans used for calibration) or areal scans from optical areal scanners of a considerably smaller area of the same specimen or even another specimen produced in the same batch under the same conditions. Both problems are approached by employing the block-maxima method from extreme value theory, whereby the underlying distribution of the depth of individual valleys is modeled with a Gumbel distribution. The experimental results from additively manufactured Ti-6Al-4V specimens demonstrate that the proposed methods can produce estimates that significantly outperform more straightforward benchmarks (e.g., simply using linear parameters for areal ones), and the proposed methods achieve a relatively accurate estimation with mean errors of 5–15%. The proposed methodology can contribute to enabling a cheaper and more efficient way to quantify and estimate surface roughness, consequently facilitating a more efficient investigation of its impacts on mechanical performance (especially fatigue) and the quality control of additively manufactured parts.
Topological and iterated structures of the superposition operator on Fock spaces
Authors: Felke Yonas Eshetu , Mengestie Tesfa , Takele Mollalgn Haile 
Published: February 2025

Abstract
We characterize various topological structures of the weighted superposition operator on Fock spaces. The global homeomorphism property of the operator is described by its ray-invertibility condition. We further consider its iterated structures and prove that the operator is power bounded if and only if it is mean ergodic. However, Fock spaces do not support cyclic weighted superposition operators, and as a result, no orbit of the operator forms a frame. We also identify a condition under which the operator preserves frames and Riesz bases. Finally, we examine the semigroups generated by the operator. In the end, we investigate the semigroups of the operator. This work provides a systematic investigation of a wide range of properties of the operator, and can serve as a valuable exposition, illustrating the interplay between fundamental operator-theoretic concepts in both linear and nonlinear analysis.
AI Meets the Eye of the Storm: Machine Learning-Driven Insights for Hurricane Damage Risk Assessment in Florida
Authors: Arachchige Sameera Maha , Pradhan Biswajeet 
Published: February 2025

Abstract
Due to Florida’s exposure to hurricanes originating from both the Atlantic Ocean and the Gulf of Mexico, hurricane risk assessments serve as a critical tool for mitigating potential impacts. This is the first novel study to develop a machine learning based risk assessment for hurricane induced flood damage, which demonstrates the potential of granular building level insurance data from 1985 to 2024, enriched with remote sensing derived variables. The stacked ensemble machine learning model predicted hurricane flood damage with an MAE of 11.3% at a granular ZIP Code Tabulation Area level (ZCTA). The model’s explainability tools determined that building property value was a significant predictor of hurricane damage, as it correlated with property size, complex architectural design, and proximity to waterfront locations, all of which affect potential repair costs. Other predictive factors include construction year, occupancy type, and flood zone designation. Partial dependency plots (PDPs) identified that northwest Florida is particularly susceptible to hurricane damage, attributed to the Gulf of Mexico’s warm and shallow waters than eastern Florida’s cooler Atlantic conditions and steep ocean floor. Miami’s significant coastal urbanisation, rendered it a hotspot despite southeast Florida’s overall low hurricane risk. Similarly Jacksonville in north-eastern Florida was identified as a hotspot due to compounded flooding from storm surge and nearby river systems. Partial dependency plots also quantified the significant positive impact of 1970s building code regulation. Future studies should examine coastal morphology, landfall angle, and proximity to barrier islands. A study limitation is that insurance data may be an imperfect representation of Florida, due to underinsurance and inability to afford insurance.
Plasma modification of the structural, morphological, and catalytic activity of Fe3O4@SiO2@TiO2 core–shell system
Authors: Gangan Amr , Fahmy Alaa , Shaban Seham A. , El-Bahy Zeinhom M. 
Published: February 2025

Abstract
Pulsed DC plasma-liquid interaction was used to prepare Ag-doped Fe3O4@SiO2@TiO2 (PP-FST) core–shell in a very short time compared to conventional methods. Tetraethyl orthosilicate (TEOS) and Ti(IV) isopropoxide precursors were employed as sources of SiO2 and TiO2, respectively, under the influence of plasma-liquid interaction using silver metal electrodes. TEM images and EDS mapping proved the successful formation of Fe3O4@SiO2@TiO2 core–shell structure without the detection of Ag NPs on the PP-FST surface. This proposed the dispersion of Ag NPs within TiO2 lattice during the synthesis process using the plasma-liquid technique. The XRD patterns show an increase of the crystallinity of the sample after exposure to plasma. Furthermore, structural and optical properties were studied using XPS and UV–Vis, respectively. The synthesized FST core–shell exhibited outstanding light absorption capabilities which may be attributed to the strong surface plasmon resonance (SPR) effect at the interface of the Ag nanoparticles and the TiO2 semiconductor. This interaction lowers the energy band gap of PP-FST to 2.05 eV, compared to 2.73 eV for FST. The specific surface area determined by BET analysis was 53.9 m2/g for PP-FST, whereas it was 34.1 m2/g for FST. Moreover, the activity of both the plasma-prepared and conventionally synthesized FST core–shell nano-catalysts was evaluated for the removing of toxic dyes such as Acid Orange 142 (AO). The degradation efficiency significantly increased to 99.6% for PP-FST compared to 80% for FST, highlighting the effect of plasma treatment.
PhytoCluster: a generative deep learning model for clustering plant single-cell RNA-seq data
Authors: Wang Hao , Fu Xiangzheng , Liu Lijia , Wang Yi , Hong Jingpeng , Pan Bintao , Cao Yaning , Chen Yanqing , Cao Yongsheng , Ma Xiaoding , Fang Wei , Yan Shen 
Published: February 2025

Abstract
Single-cell RNA sequencing (scRNA-seq) technology enables a deep understanding of cellular differentiation during plant development and reveals heterogeneity among the cells of a given tissue. However, the computational characterization of such cellular heterogeneity is complicated by the high dimensionality, sparsity, and biological noise inherent to the raw data. Here, we introduce PhytoCluster, an unsupervised deep learning algorithm, to cluster scRNA-seq data by extracting latent features. We benchmarked PhytoCluster against four simulated datasets and five real scRNA-seq datasets with varying protocols and data quality levels. A comprehensive evaluation indicated that PhytoCluster outperforms other methods in clustering accuracy, noise removal, and signal retention. Additionally, we evaluated the performance of the latent features extracted by PhytoCluster across four machine learning models. The computational results highlight the ability of PhytoCluster to extract meaningful information from plant scRNA-seq data, with machine learning models achieving accuracy comparable to that of raw features. We believe that PhytoCluster will be a valuable tool for disentangling complex cellular heterogeneity based on scRNA-seq data.