bluuebunny/crossref_metadata_2025_split huggingface dataset:
Large Skull Metastasis in Follicular Thyroid Carcinoma: A Comprehensive Case Presentation and Systematic Review
Authors: Scalia Gianluca , Porzio Massimiliano , Costanzo Roberta , Giurato Eliana , Gibilisco Fabio , Iacopino Domenico Gerardo , Maugeri Rosario , Nicoletti Giovanni Federico , Umana Giuseppe Emmanuele , Alessandrello Raffaele 
Published: April 2024

Abstract
Background Skull metastases from follicular thyroid carcinoma (FTC) are infrequent but clinically significant, often presenting with localized pain, neurologic deficits, and cranial nerve dysfunction. Early detection and accurate diagnosis pose challenges due to their asymptomatic nature in some cases.
Methods A systematic literature review, conducted following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, identified and analyzed 15 relevant studies focusing on large skull metastases in FTC. Data extraction and synthesis included clinical presentation, diagnostic methods, treatment strategies, and patient outcomes.
Results The systematic review encompassed 20 patients with secondary skull metastases from FTC, offering insights into the clinical diversity of this rare condition. Clinical presentations varied, with localized pain (70% of cases) and headaches being predominant symptoms. Imaging techniques, including computed tomography (CT) and magnetic resonance imaging (MRI), played a pivotal role in diagnosis. Surgical resection was considered in select cases, achieving complete or near-complete tumor removal in 30 to 50% of patients. Radiotherapy, including external beam radiation therapy (EBRT) and stereotactic radiosurgery (SRS), provided local control and symptom relief in 70 to 80% of cases. Systemic therapies, such as tyrosine kinase inhibitors (TKIs), showed promise in disease stabilization or regression (45% of patients). Prognosis remained poor, with a median overall survival of 6 to 12 months, reflecting an advanced and aggressive disease state.
Conclusion Managing secondary skull metastases from FTC requires a comprehensive approach, including surgical intervention, radiotherapy, and potential systemic therapies. The rarity of these metastases underscores the need for further research to establish standardized treatment guidelines, explore molecular profiling, and investigate immunotherapy and combination therapies, offering hope for improved outcomes in this challenging clinical scenario.
The Oral–Lung Microbiome Axis in Connective Tissue Disease-Related Interstitial Lung Disease
Authors: Bongers Kale S. , Massett Angeline , O'Dwyer David N. 
Published: April 2024

AbstractConnective tissue disease-related interstitial lung disease (CTD-ILD) is a frequent and serious complication of CTD, leading to high morbidity and mortality. Unfortunately, its pathogenesis remains poorly understood; however, one intriguing contributing factor may be the microbiome of the mouth and lungs. The oral microbiome, which is a major source of the lung microbiome through recurrent microaspiration, is altered in ILD patients. Moreover, in recent years, several lines of evidence suggest that changes in the oral and lung microbiota modulate the pulmonary immune response and thus may play a role in the pathogenesis of ILDs, including CTD-ILD. Here, we review the existing data demonstrating oral and lung microbiota dysbiosis and possible contributions to the development of CTD-ILD in rheumatoid arthritis, Sjögren's syndrome, systemic sclerosis, and systemic lupus erythematosus. We identify several areas of opportunity for future investigations into the role of the oral and lung microbiota in CTD-ILD.
The Usefulness of YouTube Videos Related to Endoscopic Sinus Surgery for Surgical Residents
Authors: Shapiro Justin , Levin Marc , Sunba Saud , Steinberg Emily , Wu Vince , Lee John M. 
Published: April 2024

Abstract
Objective The use of online teaching modalities to supplement surgical learning has increased recently, demonstrating promising results. Previous studies have analyzed the value and usefulness of YouTube as an educational source to learners, including teaching surgical skills to Otolaryngology–Head and Neck Surgery (OHNS) trainees. YouTube videos on endoscopic sinus surgery (ESS) still need to be explored as ESS remains a common, yet challenging surgery that OHNS residents encounter regularly. This study aimed to objectively evaluate the usefulness of YouTube videos on ESS for surgical education.
Design YouTube was searched using the following keywords: “uncinectomy,” “maxillary antrostomy,” “anterior ethmoidectomy,” and “ethmoid bulla resection.” These represent the initial ESS steps residents learn. Each video was assessed for eligibility by two independent reviewers.
Outcome Measures The LAParoscopic surgery Video Educational Guidelines (LAP-VEGaS) and ESS-specific criteria were used to assess educational quality. Video popularity index (VPI) was used to calculate video popularity.
Results Of the 38 videos that met inclusion criteria, the average LAP-VEGaS score was 6.59 (± ) 3.23 standard deviation. Most videos were designated low quality. There was a weak positive correlation between whether a video included ESS-specific criteria and LAP-VEGaS score (r = 0.269, p = 0.102). There was a significant positive correlation between VPI and LAP-VEGaS scores (r = 0.497, p = 0.003).
Conclusions Overall, the quality of included videos was poor. OHNS residents should not rely solely or primarily on YouTube videos to learn surgical skills relevant to ESS. To maximize potential of online teaching, high-quality videos should be used to compliment other methods of teaching.
Global machine learning potentials for molecular crystals
Authors: Žugec Ivan , Geilhufe R. Matthias , Lončarić Ivor 
Published: April 2024

Molecular crystals are difficult to model with accurate first-principles methods due to large unit cells. On the other hand, accurate modeling is required as polymorphs often differ by only 1 kJ/mol. Machine learning interatomic potentials promise to provide accuracy of the baseline first-principles methods with a cost lower by orders of magnitude. Using the existing databases of the density functional theory calculations for molecular crystals and molecules, we train global machine learning interatomic potentials, usable for any molecular crystal. We test the performance of the potentials on experimental benchmarks and show that they perform better than classical force fields and, in some cases, are comparable to the density functional theory calculations.
Prediction Challenge: Simulating Rydberg photoexcited cyclobutanone with surface hopping dynamics based on different electronic structure methods
Authors: Mukherjee Saikat , Mattos Rafael S. , Toldo Josene M. , Lischka Hans , Barbatti Mario 
Published: April 2024

This research examines the nonadiabatic dynamics of cyclobutanone after excitation into the n → 3s Rydberg S2 state. It stems from our contribution to the Special Topic of the Journal of Chemical Physics to test the predictive capability of computational chemistry against unseen experimental data. Decoherence-corrected fewest-switches surface hopping was used to simulate nonadiabatic dynamics with full and approximated nonadiabatic couplings. Several simulation sets were computed with different electronic structure methods, including a multiconfigurational wavefunction [multiconfigurational self-consistent field (MCSCF)] specially built to describe dissociative channels, multireference semiempirical approach, time-dependent density functional theory, algebraic diagrammatic construction, and coupled cluster. MCSCF dynamics predicts a slow deactivation of the S2 state (10 ps), followed by an ultrafast population transfer from S1 to S0 (&lt;100 fs). CO elimination (C3 channel) dominates over C2H4 formation (C2 channel). These findings radically differ from the other methods, which predicted S2 lifetimes 10–250 times shorter and C2 channel predominance. These results suggest that routine electronic structure methods may hold low predictive power for the outcome of nonadiabatic dynamics.
Evaluating translocation strategies for box turtles in urbanising landscapes
Authors: Hays Elizabeth D. , Royal Ethan J. , Hollender Ethan C. , Willson John D. 
Published: April 2024

Context Translocation is a common management strategy for wildlife populations, yet hard-release of reptiles, including box turtles (Terrapene spp.), has often proven ineffective due to homing attempts and wandering. Soft-release translocation has been presented as a possible method for mitigation of the negative effects of hard-release translocation, but studies incorporating standard soft-release strategies have produced mixed results and often see persistent homing attempts by soft-released study animals. Aims The aim of this study was to examine long-term holding (>1 year) of box turtles at an off-site location prior to translocation as a means to reduce homing attempts and wandering commonly observed in immediate-release box turtles. Methods We radiotracked translocated Terrapene carolina triunguis to compare movements of nine immediate-release box turtles and nine box turtles that had been maintained for >1 year at a nearby off-site holding facility (long-term holding) prior to a 750–1000 m translocation. Key results Box turtles held long-term before a short-distance translocation moved significantly shorter distances each day post-release than immediate-release turtles. Turtles held long-term moved in non-directional, random orientations, whereas immediate-release turtles exhibited consistent directionality in movements back towards their initial capture (home) locations. Conclusions Our results demonstrated that turtles held off-site remained within the translocation site more reliably than the immediate-release turtles, which had a higher tendency to home. Implications Long-term holding of turtles prior to translocation could significantly reduce homing responses and wandering, thus increasing translocation efficacy while reducing intensity of post-translocation management.
Enhancing strategic deployment of baiting transects for invasive species control – a case study for feral pig baiting in north-eastern Australia
Authors: Wilson Cameron , Gentle Matthew , Marshall Darren 
Published: April 2024

Context Baits are used to deliver lethal or other substances in wildlife management programs across the globe. Successful baiting campaigns are contingent upon the availability of baits to target animals. Bait density is often increased in an attempt to improve bait encounter probabilities. However, this comes with a concomitant increase in cost and may result in significant bait wastage if deployed in areas of low target species activity. Aims The aim of this study was to assess the effectiveness, efficiency and cost of different bait transect methods in intersecting home and core ranges of feral pigs as a case study to determine optimal spacing and placement of baiting transects. Methods The authors simulated a variety of systematically spaced aerial transects, watercourse-aligned aerial transects and ground transects along property boundaries and farm tracks, and compared them with home and core ranges of feral pigs, at two study sites in Queensland, Australia. Transect effectiveness at intersecting pig ranges was determined through beta-regression and estimated marginal means (emmeans); efficiency was considered as emmeans per unit of transect length. Key results The study found that systematically spaced aerial transects at 4 km intervals were the most efficient means of intersecting both home and core ranges of feral pigs. Additionally, no alternate transect method, either aerial or ground, provided significantly greater effectiveness at intersecting feral pig home and core ranges at these study sites. Ground transects along farm tracks and property boundaries were also between 113% and 192% more expensive than aerial transects at 4 km spaced intervals for either fixed-wing or rotary aircraft. Conclusion Systematically spaced aerial transects at 4 km intervals are among the most effective and are the most efficient means of intersecting feral pig ranges at the study sites examined. Implications Our methodology offers a blueprint for both vaccination and toxin baiting programs to assess and compare bait transect placements. More specifically for feral pig control, aerial transects with 4 km systematic spacing provide an effective and efficient means for intersecting feral pig ranges. Furthermore, additional data on bait encounter and interaction probabilities are required to determine transect effectiveness at bait uptake by the target species.
A user-friendly corpus tool for disciplinary data-driven learning
Authors: Crosthwaite Peter , Baisa Vít 
Published: April 2024

Abstract
Most corpus tools commonly used for corpus-based data-driven learning (DDL) are designed for research rather than
teaching purposes, with much DDL research suggesting learners and their teachers often stop DDL after initial training due to
tool-related issues like complex user interfaces and system settings. Based on feedback from secondary-age language learners and
their teachers in the Australian context, we present CorpusMate (https://corpusmate.com), a new, user-friendly corpus tool that incorporates several publicly available written and
spoken corpora across 20 disciplinary subjects. It offers a range of flexible concordancing, n-gram and data visualisation options
to ensure a fast, smooth and simple DDL experience for end users.
Worldline path integrals for the graviton
Authors: Bastianelli Fiorenzo , Damia Paciarini Mattia 
Published: April 2024

Abstract
We present an extension to arbitrary dimensions of a worldline path integral approach to one-loop quantum gravity, which was previously formulated in four spacetime dimensions. By utilizing this method, we recalculate gauge invariant coefficients related to the UV divergences of quantum gravity. These gauge invariant coefficients were previously obtained in arbitrary dimensions through two alternative techniques: the quantization of the

N

=
4

spinning particle that propagates the graviton on Einstein spaces and the more conventional heat kernel approach. Our worldline path integrals are closer to the latter method and are employed to compute the trace of the heat kernel.
Bayesian model error method for the passive inverse scattering problem
Authors: Yin Yunwen , Yan Liang 
Published: April 2024

Abstract
This paper focuses on the passive inverse scattering problem, which uses passive measurements corresponding to randomly distributed incident sources to recover the shape of the sound-soft obstacle from a Bayesian perspective. Due to the unpredictability and randomness of incident sources, the classical Bayesian inversion framework may be unable to capture the likelihood involving the passive forward model for this inverse problem. We present the Bayesian model error method (BMEM), a novel passive imaging technique, to overcome this difficulty. The cross-correlations and the Helmholtz–Kirchhoff identity are specifically used to build an approximate active scattering model. This approximate model and the model error that it produces can be combined effectively by the suggested BMEM. The well-posedness of the posterior measure in the BMEM is proved. To further estimate the model error, an online scheme is utilized in conjunction with a preconditioned Crank–Nicolson Markov Chain Monte Carlo method to numerically approximate the posterior. Numerical experiments illustrate the effectiveness of the proposed method and also show that the online evaluation of model error can significantly improve reconstruction accuracy.
Dipolar focusing in laser-assisted positronium formation
Authors: Ambalampitiya H B , Matfunjwa M K , Fabrikant I I 
Published: April 2024

Abstract
We consider positronium formation in collisions of positrons with excited hydrogen atoms H(n) in an infrared laser field theoretically. This process is assisted by the dipolar focusing effect: a positron moving in a superposition of a laser field and the dipolar field can approach the atomic target even if its trajectory starts with a very large impact parameter, leading to a significant enhancement of the Ps formation cross section. The classical trajectory Monte Carlo method, which is justified for

n
⩾
3

, allows efficient calculation of this enhancement. A similar effect can occur in collisions of positrons with other atoms in excited states, which can lead to improvements in the efficiency of positronium formation.
Ultra-ventilated sound absorption metamaterial lamina
Authors: Wu Chaolin , Yuan Xiaonan , Ye Yangsong , Wang Li , Li Haitao , Gao Cong , Huang Yingzhou , Wu Xiaoxiao 
Published: April 2024

Abstract
We propose a lamina-shaped metamaterial absorber based on the coherently coupled weak resonances of high-order Helmholtz resonators in this work. Such an ultra-thin lamina metamaterial can achieve broadband tunable absorption (maximal absorption >0.9), which exhibits near-perfect ventilation performance (ventilated area ratio >0.8, ratio of wind velocity >0.95). Benefiting from coherently coupled weak resonances between units with different structure parameters, the lamina metamaterial presents a broadband absorption (506–659 Hz with 2 × 3 units and 480–679 Hz with 2 × 4 units). The ultra-thin and simple structure shape of this sound absorption metamaterial lamina leads to not only an efficient ventilation performance but also high potential value in various scenarios of ventilated sound absorption, especially in ventilation tubes with high noise.
An interpretable RUL prediction method of aircraft engines under complex operating conditions using spatio-temporal features
Authors: Gao Jiahao , Wang Youren , Sun Zejin 
Published: April 2024

Abstract
Long short-term memory (LSTM) based prediction methods have achieved remarkable achievements in remaining useful life (RUL) prediction for aircraft engines. However, their prediction performance and interpretability are unsatisfactory under complex operating conditions. For aircraft engines with high hazard levels, it is important to ensure the interpretability of the models while maintaining excellent prediction accuracy. To address these issues, an interpretable RUL prediction method of aircraft engines under complex operating conditions using spatio-temporal features (STFs), referred to as iSTLSTM, is proposed in this paper. First, we develop a feature extraction framework called Bi-ConvLSTM1D. This framework can effectively capture the spatial and temporal dependencies of sensor measurements, significantly enhancing the feature extraction capabilities of LSTM. Then, an interpretation module for STFs based on a hybrid attention mechanism is designed to quantitatively assess the contribution of STFs and output interpretable RUL predictions. The effectiveness of iSTLSTM is evidenced by extensive experiments on the C-MAPSS and N-CMAPSS datasets, confirming the superiority and reliability of our method for aircraft engine RUL prediction.
Bearing fault diagnosis method based on angular domain resampling, relative position matrix and transfer learning
Authors: Zhang Xun , Xu Guanghua , Chen Xiaobi , Chen Ruiquan , Xie Jieren , Tian Peiyuan , Zhang Sicong , Wu Qingqiang 
Published: April 2024

Abstract
Bearings are key components in mechanical equipment, which are widely used in various fields such as automobiles and airplanes. Aiming at the analysis of vibration signal processing under the variable speed condition of bearings, this paper proposes a new bearing fault diagnosis method, which firstly resamples the vibration signals in the angular domain, and then converts the resampled signals into images by the relative position matrix method, and finally uses the transfer learning to automatically extract the features and classify them. To verify the effectiveness of the method, it is tested on the Case Western Reserve University bearing fault dataset and University of Ottawa bearing fault dataset respectively. Compared with other time series to image methods (Recurrence Plot, etc) and other pre-trained models (GoogLeNet, etc), the proposed method has some advantages in terms of accuracy, image generation time, training time, and testing time. The accuracy of the proposed method in this paper reaches more than 90%, which suggests its potential effectiveness in the classification of bearing faults under variable speed working conditions.
A lightweight white blood cells detection network based on CenterNet and feature fusion modules
Authors: Wu Lianghong , Zou Yujie , Zuo Cili , Chen Liang , Zhou Bowen , Zhang Hongqiang 
Published: April 2024

Abstract
White blood cells (WBCs) detection is significant to the diagnosis of many diseases. However, the detection accuracy can be influenced by the significant differences in color, size and morphology of WBCs in the images. In this paper, an improved CenterNet with smaller model size, fewer parameters, and lower computational complexity is proposed for the WBCs accurate detection. Firstly, the lightweight backbone GhostNetv2 is selected to reduce the model size, parameters and computational complexity of the network. Then, a feature pyramid network with the efficient channel attention (ECA) attention mechanism and the multi-scale feature extraction modules is constructed to enhance the capability of feature extraction and focus more on WBCs. Finally, the heatmap loss function is modified by proposing an improved mean squared error loss function to enhance the fitting ability between the predicted values and the ground truth of the heatmap. Experimental results show that the model size of the proposed lightweight CenterNet is only 19.9 MB, and the mAP.5 is 97.36%. The model size is reduced by 84% while the mAP.5 and FPS are increased by 0.7% and 10.4 compared to the original CenterNet. Moreover, the detection accuracy of the proposed lightweight CenterNet is comparable to the existing mainstream networks and its detection performance on different datasets is good, while the model size, parameters and computational complexity of the network is significantly reduced, and can be used for WBCs detection effectively.
Entropic transfer operators
Authors: Junge Oliver , Matthes Daniel , Schmitzer Bernhard 
Published: April 2024

Abstract
We propose a new concept for the regularization and discretization of transfer and Koopman operators in dynamical systems. Our approach is based on the entropically regularized optimal transport between two probability measures. In particular, we use optimal transport plans in order to construct a finite-dimensional approximation of some transfer or Koopman operator which can be analyzed computationally. We prove that the spectrum of the discretized operator converges to the one of the regularized original operator, give a detailed analysis of the relation between the discretized and the original peripheral spectrum for a rotation map on the n-torus and provide code for three numerical experiments, including one based on the raw trajectory data of a small biomolecule from which its dominant conformations are recovered.