bluuebunny/crossref_metadata_2025_split huggingface dataset:
Safeguarding Iguana diversity: enabling rapid and low-effort tracking of non-native iguanas through terrestrial eDNA innovations
Authors: van Kuijk Jeroen L. , van den Burg Matthijs P. , Didaskalou Emilie A. , de Boer Mark , Debrot Adolphe O. , Wielstra Ben , Stewart Kathryn A. 
Published: January 2025

Abstract
Reptiles have among the highest extinction risk across terrestrial vertebrates, with habitat fragmentation, habitat destruction, and invasive alien species being the primary causes of reptile species loss on a global scale. Invasive hybridization (i.e. hybridization between native and invasive alien species) is increasing globally, causing the extinction of native genotypes, and this phenomenon is particularly pervasive in Caribbean iguanas. The Lesser Antillean Iguana (Iguana delicatissima), a keystone species of Caribbean coastal ecosystems, has become critically endangered mainly due to ongoing hybridization with the invasive Common Green Iguana (I. iguana). For impactful conservation intervention, the need for early detection of invasive animals and their progeny, or detection of surviving pure native animals, is urgent. We aimed to develop a novel environmental DNA (eDNA) toolkit using Kompetitive Allele Specific PCR (KASP) technology, a method of allele-specific amplification for cost-effective and efficient sampling of terrestrial substrates to aid in mapping the distribution of native I. delicatissima, invasive I. iguana, and signal potential invasive hybridization. We demonstrate proof-of-concept and successfully identified I. delicatissima, I. iguana, and their hybrids via blood samples using our primer sets, as well as successful detection of I. delicatissima in several ex-situ (Rotterdam Zoo) and in-situ (St. Eustatius) eDNA samples, collected with environmental swabs and tape-lifting. We found that sampling potential perching spots yielded the highest number of positive detections via environmental swabbing and tape-lifting. Our toolkit demonstrates the potential of terrestrial eDNA sampling for iguana conservation, enabling faster detection of putative invasive hybridization. Additionally, the method holds promise for other terrestrial cryptic species, contributing to broader collection of population-level information.
AI-powered language learning: Developing the chatGPT usage scale for foreign language learners
Authors: ÇOBANOĞULLARI Ferdiye , ÖZBEK Özge 
Published: January 2025

Abstract
This study introduces the "ChatGPT Usage Scale for Foreign Language Learners," designed to evaluate the usage of AI chatbots in language learning. The scale was developed based on a comprehensive literature review and expert evaluations, ensuring a strong theoretical foundation and content validity. It comprises three sub-dimensions Usability, Learning, and Development that collectively explain 62.896% of the total variance, exceeding standard expectations. Data were collected from 1006 university students (657 female, 349 male) from foreign language departments at three Turkish state universities during the 2023–2024 fall semester. The scale demonstrated excellent internal consistency (Cronbach’s Alpha = 0.93) and validity, supported by robust Confirmatory Factor Analysis results. A test–retest analysis with a subset of participants confirmed the scale's reliability over time. Future research should apply this measurement tool in diverse educational contexts to enhance its generalizability and further refine its psychometric properties, providing deeper insights into the role of AI tools in language education.
Interactions between contaminants and the trophic ecology of two seabirds in a coastal lagoon of the Gulf of California
Authors: Castillo-Guerrero José Alfredo , González-Medina Erick , Piña-Ortiz Alberto , Betancourt-Lozano Miguel , García-Hernández Jaqueline , Hernández-Vázquez Salvador , Fernández Guillermo 
Published: January 2025

Abstract
Monitoring the dynamics of contaminants in ecosystems helps understand their potential effects. Seabirds have been used as biomonitors of marine ecosystems for this purpose. However, exposure and vulnerability to pollutants are understudied in tropical species, and the relationships between various pollutants and the trophic ecology of seabirds are poorly understood. In this study, we quantified mercury (Hg), lead (Pb), cadmium (Cd), and organochlorine pesticide (OC) concentrations in the blood of Laughing Gulls and Magnificent Frigatebirds breeding in Bahía Santa María, México. Using carbon and nitrogen isotopic ratios (δ
13C and δ
15N), we examined the interaction between contaminants and trophic ecology. Laughing Gulls exhibited higher concentrations of dichlorodiphenyltrichloroethane and its metabolites (ΣDDTs), endrins (ΣDrins), and chlordanes, while Magnificent Frigatebirds had elevated levels of Hg and hexachlorocyclohexane isomers (ΣHCHs). Both species displayed temporal and sex-related variations in isotopic signatures. Some blood pollutant concentrations in Laughing Gulls were explained by diet: ΣOCs in plasma were directly related to trophic levels, indicating biomagnification, whereas higher Hg levels were associated with changes in habitat use. In contrast, the differences in sex-related isotopic signatures in Magnificent Frigatebirds did not reflect pollutant accumulation patterns, possibly due to their opportunistic feeding habits.
Nonlinear Rayleigh–Taylor instability in an accelerated soap film
Authors: Stewart Peter S. , Roy Alasdair T. , Hilgenfeldt Sascha 
Published: January 2025

Abstract
Rupture and fragmentation of thin liquid films are of great importance in manufacturing, agriculture, disease transmission, and other fields. An individual rupture event typically results from the nonlinear growth of small perturbations excited by the classical Rayleigh–Taylor mechanism and opposed by surface tension on the film interfaces. We study an initially uniform liquid film accelerated in the direction perpendicular to its interfaces, constructing a new reduced description of the flow in the limit of large surface tension consisting of three coupled (nonlinear) partial differential equations. This system is linearly unstable to disturbances of small wavenumber; we derive a simplified asymptotic description to gain analytical understanding of the nonlinear development until rupture. An initial phase of exponential film thinning leads to the accumulation of liquid in a central bulge. At a well-defined time, a localised pinch-off mechanism, driven by a mismatch in the interfacial curvature at the edge of the bulge, results in a self-similar thinning that breaks the film in finite time. Across a wide parameter range, the resultant droplet formed from the central bulge contains a significant fraction of the initial film volume.
Focusing on microvascular function in heart failure with preserved ejection fraction
Authors: Velollari Ornela , Rommel Karl-Philipp , Kresoja Karl-Patrik , Lurz Philipp , Gori Tommaso 
Published: January 2025

Abstract
Heart failure is a prevalent global health issue. Heart failure with preserved ejection fraction (HFpEF), which already represents half of all heart cases worldwide, is projected to further increase, driven by aging populations and rising cardiovascular risk factors. Effective therapies for HFpEF remain limited, particularly due to its pathophysiological heterogeneity and incomplete understanding of underlying pathomechanisms and implications. Coronary microvascular dysfunction (CMD), characterized by structural and functional changes in the coronary microcirculation, is increasingly recognized as a significant factor in HFpEF even though the exact nature of their causal relationship is still unclear. This review explores prevalence, prognostic implications, and potential therapeutic targets for CMD in HFpEF. CMD’s role in HFpEF might involve impaired coronary blood flow regulation, leading to myocardial ischemia, impaired relaxation, and/or adverse remodeling. Vice versa, increased wall stress in patients with HFpEF might elevate coronary resistances, further worsening microvascular perfusion. Finally, abnormalities in substrate metabolism might cause both CMD and HFpEF. Current treatments, including pharmacotherapy and device-based therapies, show limited success, highlighting the need for more targeted approaches. New possible therapies, such as the coronary sinus reducer device, may show promise in improving myocardial perfusion and function. However, further large-scale studies are required to elucidate the mechanistic links between CMD and HFpEF and to develop specialized treatments for distinct heart failure phenotypes.
Measuring Self-Referent Memory Bias as Marker for Depression: Overview, New Insights, and Recommendations
Authors: Duyser Fleur A. , Eijndhoven Philip F. Van , Collard Rose M. , Vassena Eliana , Koekkoek Bauke , Tendolkar Indira , Vrijsen Janna N. 
Published: January 2025

Abstract
Negative self-referent memory bias (the preferential memory for negative self-referent information) is a well-known symptom of depression and a risk factor for its development, maintenance, and recurrence. Evidence shows its potential as an add-on tool in clinical practice. However, it is unclear which self-referent memory bias measure(s) could be clinically relevant. Here, as a first step, we investigate which measures best differentiate current depression status and track depressive symptom severity most closely. The total sample (N = 956) from three (naturalistic) psychiatric cohorts with matched controls was divided into a current depression, remitted depression, and non-disordered control group. Self-referent memory bias task measures were calculated and the drift diffusion model (DDM) was applied to assess underlying components of the cognitive self-referent decision making process. Measures were compared between groups and linear regression models were applied to assess their association with depressive symptom severity. The number of negative endorsed words differentiated best between depression status while a combination of the number of positive endorsed words, self-referent negative memory bias, and positive drift rate was most strongly associated with depressive symptom severity. Our results give direction to the clinical implementation of this task. Its value in assessing, monitoring, and predicting depressive state and trait in clinical settings requires further investigation.
Approximations of unbounded convex projections and unbounded convex sets
Authors: Kováčová Gabriela , Rudloff Birgit 
Published: January 2025

Abstract
We consider the problem of projecting a convex set onto a subspace or, equivalently formulated, the problem of computing a set obtained by applying a linear mapping to a convex feasible set. This includes the problem of approximating convex sets by polyhedrons. The existing literature on convex projections provides methods for bounded convex sets only, in this paper we propose a method that can handle both bounded and unbounded problems. The algorithms we propose build on the ideas of inner and outer approximation. In particular, we adapt the recently proposed methods for solving unbounded convex vector optimization problems to handle also the class of projection problems.
Selection and evaluation of a set of attributes appropriate for detection of antisocial behaviour in online media
Authors: Machová Kristína , Balara Viliam , Mach Marian , Kožík Štefan 
Published: January 2025

Abstract
Nowadays the world of modern technologies brings new ways of communication and interaction between people. Online communication becomes faster and more convenient, but it also enables an exchange of more dangerous information. Antisocial behaviour in online web discussions becomes one of the most serious problems. This paper is focused on the analysis and identification of the most typical attributes of antisocial behaviour in the online space. Our research attempts to distinguish the most characteristic features of suspicious contributors to identify attributes that can define antisocial behaviour in the best way. The main objective is to evaluate the success of these attributes in the automatic detection of the suspicious contributors—trolls using classification methods of machine learning such as naïve Bayes, decision trees, random forest, logistic regression, and support vector machine. The methods were selected from the point of view of evaluation of suitability of individual attributes and evaluation of selected sets of attributes. The results of test of models learned using mentioned methods are discussed from this point of view and lead to a selection of a small set of attributes from all considered attributes.
Adapting to the stream: an instance-attention GNN method for irregular multivariate time series data
Authors: Han Kun , Koay Abigail M. Y. , Ko Ryan K. L. , Chen Weitong , Xu Miao 
Published: January 2025

Abstract
Multivariate time series (MTS) data are vital for various applications, particularly in machine learning tasks. However, challenges such as sensor failures can result in irregular and misaligned data with missing values, thereby complicating their analysis. While recent advancements use graph neural networks (GNNs) to manage these Irregular Multivariate Time Series (IMTS) data, they generally require a reliable graph structure, either pre-existing or inferred from adequate data to properly capture node correlations. This poses a challenge in applications where IMTS data are often streamed and waiting for future data to estimate a suitable graph structure becomes impractical. To overcome this, we introduce a dynamic GNN model suited for streaming characteristics of IMTS data, incorporating an instance-attention mechanism that dynamically learns and updates graph edge weights for realtime analysis. We also tailor strategies for high-frequency and low-frequency data to enhance prediction accuracy. Empirical results on real-world datasets demonstrate the superiority of our proposed model in both classification and imputation tasks.
Development of Deterministic Reaction Triggering in UF4 Magnesiothermic Reduction
Authors: Kalpana Pasupuleti , Gupta Sonal , Thakkar U. R. , Raina Amulya , Satpati S. K. , Verma Rishi 
Published: January 2025

Abstract
Uranium metal ingot is routinely produced by magnesiothermic reduction (MTR) at plant scale. In the conventional process, heating of the reaction vessel is continued till self-initiation or self-firing of the reaction occurs. A novel deterministic reaction triggering (DRT) method has been developed for the MTR process on a 5 kg uranium ingot scale, which makes the firing definite and decreases specific energy consumption and batch duration by about 33.8% and 30–50%, respectively, without affecting the process recovery. The pre-heat time and pre-heat temperature required for initiating the external trigger were estimated using COMSOL simulations and thermodynamic evaluation of the final product temperature, respectively. The process recovery with DRT (~93%) was comparable to that of the conventional self-firing process. A well-consolidated uranium ingot with a recovery of about 93% was obtained with 100 ppm Cr and 97 ppm Ni in the scaled up (50 kg) batch by employing deterministic triggering. This DRT method is applicable and useful for similar reaction processes for augmenting process capacity and energy utilization.
A Review of the Prospera Spinal Cord Stimulation System with Multiphase Stimulation and Proactive Care
Authors: Naidu Ramana K. , Kapural Leonardo , Li Sean , Tourjé Caitlin , Rutledge Joseph , Dickerson David , Lubenow Timothy R. 
Published: January 2025

Abstract

Purpose of Review
The purpose of this review is to describe the development and key features of the Prospera™ Spinal Cord Stimulation (SCS) System, as well as the clinical evidence supporting its use. Prospera delivers therapy using a proprietary multiphase stimulation paradigm and is the first SCS system to offer proactive care through automatic, objective, daily, remote device monitoring and remote programming capabilities.

Recent Findings
Results from the recently published BENEFIT-02 trial support the short-term safety and efficacy of multiphase stimulation in patients with chronic pain. BENEFIT-03 is an ongoing, multicenter, single-arm study with 24-month follow-up; interim analyses suggest that multiphase therapy is safe and effective and that patients and clinicians have positive experiences with remote device management.

Summary
Preliminary evidence suggests that the Prospera SCS System represents an opportunity to improve patient care by combining an effective multiphase stimulation paradigm with an efficient proactive care model.
Unveiling subjective well-being: the role of reward processing and resilience
Authors: Oltean Lia-Ecaterina , Șoflău Radu , Miu Andrei C. , Szentágotai-Tătar Aurora 
Published: January 2025

Abstract
Clarifying factors contributing to subjective well-being (SWB) is paramount to the understanding optimal functioning and positive human experience. Among these, reward processing appears promising, with evidence suggesting it may contribute to resilience, to further promote SWB. However, direct evidence for this hypothesis is lacking, and indirect evidence is scant and scattered. Building on these caveats, this study sought (1) to investigate associations between reward processing and resilience with SWB, and (2) to test the mediating role of resilience in the association between reward processing and SWB. Aligned with recommendations suggesting that using multiple indicators and distinguishing between cognitive and affective dimensions of SWB may refine its understanding, multiple SWB measures were employed. Participants (N = 300; m age = 32.53; SD = 12.30) completed cognitive (i.e., satisfaction with life) and affective measures of SWB (i.e., positive and negative affect), and stress, as well as scales evaluating reward processing and resilience. Findings indicated that reward processing was positively associated with resilience, and all SWB dimensions including satisfaction with life and positive affect, and negatively associated with negative affect and stress. Moreover, resilience mediated associations between reward processing and all SWB dimensions. These findings extend existing knowledge on SWB and provide a refined understanding of this construct through the lens of reward processing and resilience. If replicated in longitudinal and experimental studies, they may have important practical implications for interventions targeting reward processing and resilience.
Subscale modeling of material flow in orthogonal metal cutting
Authors: Erturk Ahmet Semih , Larsson Ragnar 
Published: January 2025

Abstract
Enhanced simulation capability for the cutting process is crucial to making quick evaluations of cutting forces and temperatures, which are significant for assessing the machinability of the workpiece material and predicting tool wear. In this paper, the material flow in orthogonal cutting, including primary and secondary shear zones, is represented by a viscous/viscoplastic model that includes the temperature-sensitive Johnson-Cook flow stress model. A stabilized staggered finite element procedure is developed to handle incompressible Navier-Stokes material flow in combination with convection-dominated hardening and thermomechanical interaction. To handle material flow at tool-workpiece contact, a mixed method is used to reduce spurious oscillations in contact stresses along with simplified heat transfer in the tool-workpiece interface. A novel feature is that the velocity field is resolved as a subscale field to the velocity field of the distributed primary zone deformation model. It appears that the finite element solution to the subscale material flow model is significantly more cost-effective in contrast to directly addressing the velocity field and compared to the chip-forming simulations (DEFORM 2D). The cutting forces, temperature, and stress-strain state of the material in the critical deformation regions can be accurately estimated using the subscale model. The results obtained show that the trend of the estimated forces and temperatures is consistent with our experimental measurements, the DEFORM 2D simulations, and the experimental data from the literature.
Guidance on selecting and evaluating AI auto-segmentation systems in clinical radiotherapy: insights from a six-vendor analysis
Authors: Rusanov Branimir , Ebert Martin A. , Sabet Mahsheed , Rowshanfarzad Pejman , Barry Nathaniel , Kendrick Jake , Alkhatib Zaid , Gill Suki , Dass Joshua , Bucknell Nicholas , Croker Jeremy , Tang Colin , White Rohen , Bydder Sean , Taylor Mandy , Slama Luke , Mukwada Godfrey 
Published: January 2025

Abstract
Artificial Intelligence (AI) based auto-segmentation has demonstrated numerous benefits to clinical radiotherapy workflows. However, the rapidly changing regulatory, research, and market environment presents challenges around selecting and evaluating the most suitable solution. To support the clinical adoption of AI auto-segmentation systems, Selection Criteria recommendations were developed to enable a holistic evaluation of vendors, considering not only raw performance but associated risks uniquely related to the clinical deployment of AI. In-house experience and key bodies of work on ethics, standards, and best practices for AI in Radiation Oncology were reviewed to inform selection criteria and evaluation strategies. A retrospective analysis using the criteria was performed across six vendors, including a quantitative assessment using five metrics (Dice, Hausdorff Distance, Average Surface Distance, Surface Dice, Added Path Length) across 20 head and neck, 20 thoracic, and 19 male pelvis patients for AI models as of March 2023. A total of 47 selection criteria were identified across seven categories. A retrospective analysis showed that overall no vendor performed exceedingly well, with systematically poor performance in Data Security & Responsibility, Vendor Support Tools, and Transparency & Ethics. In terms of raw performance, vendors varied widely from excellent to poor. As new regulations come into force and the scope of AI auto-segmentation systems adapt to clinical needs, continued interest in ensuring safe, fair, and transparent AI will persist. The selection and evaluation framework provided herein aims to promote user confidence by exploring the breadth of clinically relevant factors to support informed decision-making.
The genetics of non-syndromic dentinogenesis imperfecta: a systematic review
Authors: Gilani M. , Saikia A. , Anthonappa R. 
Published: January 2025

Abstract

Purpose
This systematic review aims to consolidate existing genetic and clinical data on non-syndromic dentinogenesis imperfecta (DI) to enhance understanding of its etiology.

Methods
Electronic databases were searched for genetic familial linkage studies published in English without time restrictions. Genetic familial linkage studies that reported cases of Shield’s classifications: DI-II, DI-III or DD-II were included. After removing duplicates and excluding non-eligible articles, two reviewers screened relevant articles independently, followed by data extraction.

Results
The systematic search identified 3475 articles, with 135 suitable for full-text review and a final 41 that met inclusion criteria. Within this set of studies, 10 conducted a histopathologic examination of teeth from affected participants. DSPP mutations were the most frequently reported, with 59 documented mutations. Four studies identified mutations in COL1A1 and COL1A2, revealing non-syndromic DI cases, predominantly in individuals of Asian descent. Histopathological analysis of affected teeth showed variations in pulp chamber size, dentinal tubule irregularities, enamel malformations, and mineral density reductions, depending on DI phenotype.

Conclusions
This review consolidates genetic and clinical data to advance the understanding of non-syndromic DI. It highlights the role of DSPP, COL1A1 and COL1A2 and the potential involvement of other genes, emphasizing the effectiveness of whole-exome sequencing in identifying causative mutations.