bluuebunny/crossref_metadata_2025_split huggingface dataset:
Exploring Galactic open clusters with Gaia
Authors: Alfonso Jeison , García-Varela Alejandro , Vieira Katherine 
Published: July 2024

Context. Since the first publication of the Gαία catalogue, a new view of our Galaxy has arrived. Its astrometric and photometric information has improved the precision of the physical parameters of open star clusters obtained from them.
Aims. Using the Gaia Data Release 3 (DR3) catalogue, our aim was to find physical stellar members including faint stars for 370 Galactic open clusters located within 1 kpc. We also estimated the age, metallicity, distance modulus, and extinction of these clusters.
Methods. We employed the HDBSCAN algorithm on both astrometric and photometric data to identify members in the open clusters. Subsequently, we refined the samples by eliminating outliers through the application of the Mahalanobis metric utilizing the χ2 distribution at a confidence level of 95%. Furthermore, we characterized the stellar parameters with the PARSEC isochrones.
Results. We obtained reliable star members for 370 open clusters with an average parallax error of σϖ = 0.16 mas. We identified about ~40% more stars in these clusters compared to previous work using the Gaia DR2 catalogue, including faint stars as new members with G ≥ 17. Before the clustering application we corrected the parallax zero-point bias to avoid spatial distribution stretching that may affect clustering results. Our membership lists include merging stars identified by HDBSCAN with astrometry and photometry. We note that the use of photometry in clustering can recover up to 10% more stars in the fainter limit than clustering based on astrometry only; this combined with the selection of stars filtered out by quality cuts significantly reduces the number of stars with huge σϖ. After clustering, we estimated age, Z, and AV from the photometry of the membership lists.
Conclusions. We carried out a search to extend the membership list for 370 open clusters mainly on the Galactic plane in a neighbourhood of 1 kpc. Our methodology provides a robust estimator for the identification of outliers and also extends the membership lists to fainter stars in most of the clusters. Our findings suggest the need to carefully identify spurious sources that may affect clustering results.
Imprint of the magnetic activity cycle on solar asteroseismic characterisation based on 26 years of GOLF and BiSON data
Authors: Bétrisey J. , Farnir M. , Breton S. N. , García R. A. , Broomhall A.-M. , Amarsi A. M. , Kochukhov O. 
Published: July 2024

Context. Asteroseismic modelling will play a key role in future space-based missions, such as PLATO, CubeSpec, and Roman. Despite remarkable achievements, asteroseismology has revealed significant discrepancies between observations and theoretical predictions of the physics used in stellar models, which have the potential to bias stellar characterisation at the precision level demanded by PLATO. The current modelling strategies largely overlook magnetic activity, assuming that its effects are masked within the parametrisation of the so-called ‘surface effects’. Given the presence of activity cycles in multiple solar-like oscillators and activity variations in a significant fraction of Kepler observations of main-sequence stars, it is therefore relevant to investigate systematic errors in asteroseismic characterisations caused by our incomplete understanding of magnetic activity.
Aims. Based on 26.5 years of GOLF and BiSON observations, we measured the impact of magnetic activity on the asteroseismic characterisation of the Sun as a star, a reference target for assessing the PLATO mission requirements.
Methods. The GOLF and BiSON observations, which fully cover solar cycles 23 and 24, were divided into yearly overlapping snapshots, each delayed by a quarter of a year. For each snapshot, an advanced asteroseismic characterisation, similar to that to be adopted by the PLATO pipeline, was performed with standard prescriptions for the parametrisation of the surface effects. This allowed us to monitor the apparent temporal evolution of fundamental solar parameters such as mass, radius, and age. The correlation of these parameters with the 10.7 cm radio emission flux, a proxy of the solar activity cycle, was then measured.
Results. The effects of magnetic activity are partially absorbed into the parametrisation of the surface effects when suitable prescriptions are used, and they do not significantly affect the measured solar mass or radius. However, contrary to literature expectations, we find a significant imprint on the age determination, with variations of up to 6.5% between solar minima and maxima. This imprint persists across both BiSON and GOLF datasets.
Conclusions. Considering that the Sun exhibits low levels of activity, our study highlights the looming challenge posed by magnetic activity for future photometry missions, and it prompts a potential reevaluation of the asteroseismic characterisation of the most active Kepler targets.
Increasing Generative Artificial Intelligence Competency among Students Enrolled in Doctoral Nursing Research Coursework
Authors: Reading Turchioe Meghan , Kisselev Sergey , Van Bulck Liesbet , Bakken Suzanne 
Published: July 2024

Abstract
Background Generative artificial intelligence (AI) tools may soon be integrated into health care practice and research. Nurses in leadership roles, many of whom are doctorally prepared, will need to determine whether and how to integrate them in a safe and useful way.
Objective This study aimed to develop and evaluate a brief intervention to increase PhD nursing students' knowledge of appropriate applications for using generative AI tools in health care.
Methods We created didactic lectures and laboratory-based activities to introduce generative AI to students enrolled in a nursing PhD data science and visualization course. Students were provided with a subscription to Chat Generative Pretrained Transformer (ChatGPT) 4.0, a general-purpose generative AI tool, for use in and outside the class. During the didactic portion, we described generative AI and its current and potential future applications in health care, including examples of appropriate and inappropriate applications. In the laboratory sessions, students were given three tasks representing different use cases of generative AI in health care practice and research (clinical decision support, patient decision support, and scientific communication) and asked to engage with ChatGPT on each. Students (n = 10) independently wrote a brief reflection for each task evaluating safety (accuracy, hallucinations) and usability (ease of use, usefulness, and intention to use in the future). Reflections were analyzed using directed content analysis.
Results Students were able to identify the strengths and limitations of ChatGPT in completing all three tasks and developed opinions on whether they would feel comfortable using ChatGPT for similar tasks in the future. All of them reported increasing their self-rated competency in generative AI by one to two points on a five-point rating scale.
Conclusion This brief educational intervention supported doctoral nursing students in understanding the appropriate uses of ChatGPT, which may support their ability to appraise and use these tools in their future work.
What Do We Mean by Sharing of Patient Data? DaSH: A Data Sharing Hierarchy of Privacy and Ethical Challenges
Authors: Schreiber Richard , Koppel Ross , Kaplan Bonnie 
Published: July 2024

Abstract
Background Clinical data sharing is common and necessary for patient care, research, public health, and innovation. However, the term “data sharing” is often ambiguous in its many facets and complexities—each of which involves ethical, legal, and social issues. To our knowledge, there is no extant hierarchy of data sharing that assesses these issues.
Objective This study aimed to develop a hierarchy explicating the risks and ethical complexities of data sharing with a particular focus on patient data privacy.
Methods We surveyed the available peer-reviewed and gray literature and with our combined extensive experience in bioethics and medical informatics, created this hierarchy.
Results We present six ways on how data are shared and provide a tiered Data Sharing Hierarchy (DaSH) of risks, showing increasing threats to patients' privacy, clinicians, and organizations as one progresses up the hierarchy from data sharing for direct patient care, public health and safety, scientific research, commercial purposes, complex combinations of the preceding efforts, and among networked third parties. We offer recommendations to enhance the benefits of data sharing while mitigating risks and protecting patients' interests by improving consenting; developing better policies and procedures; clarifying, simplifying, and updating regulations to include all health-related data regardless of source; expanding the scope of bioethics for information technology; and increasing ongoing monitoring and research.
Conclusion Data sharing, while essential for patient care, is increasingly complex, opaque, and perhaps perilous for patients, clinicians, and health care institutions. Risks increase with advances in technology and with more encompassing patient data from wearables and artificial intelligence database mining. Data sharing places responsibilities on all parties: patients, clinicians, researchers, educators, risk managers, attorneys, informaticists, bioethicists, institutions, and policymakers.
Robust Transfer of Optical Frequency over 500km Fiber Link with Instability of 10−21
Authors: Zhou 周 Qian 茜 , Zhang 张 Xiang 翔 , Zang 臧 Qi 琦 , Wu 吴 Mengfan 梦凡 , Wang 王 Dan 丹 , Liu 刘 Jie 杰 , Dong 董 Ruifang 瑞芳 , Liu 刘 Tao 涛 , Zhang 张 Shougang 首刚 
Published: July 2024

Abstract
Our primary objective is to mitigate the adverse effects of temperature fluctuations on the optical frequency transmission system by reducing the length of the interferometer. Following optimization, the phase-temperature coefficient of the optical system is reduced to approximately 1.35 fs/K. By applying a sophisticated temperature control to the remained “out-of-loop” optics fiber, the noise floor of the system has been effectively lowered to 10−21 level. Based on this performance-enhanced transfer system, we demonstrate coherent transmission of optical frequency through 500-km spooled fiber link. After being actively compensated, the transfer instability of 4.5 × 10−16 at the averaging time of 1 s and 5.6 × 10−21 at 10000 s is demonstrated. The frequency uncertainty of received light at remote site relative to that of the origin light at local site is achieved to be 1.15 × 10−19. This enhanced system configuration is particularly well suited for future long-distance frequency transmission and comparison of the most advanced optical clock signals.
Diagnosis for railway point machines using novel derivative multi-scale permutation entropy and decision fusion based on vibration signals
Authors: Sun Yongkui , Cao Yuan , Li Peng , Su Shuai 
Published: July 2024

Abstract
Railway point machines (RPMs) are safety-critical pieces of equipment closely related to train operation safety. Due to their high failure rate, it is urgent to develop an effective diagnosis method for RPMs. Considering the easy-to-collect and anti-interference characteristics of vibration signals, this paper develops a vibration-based diagnosis method. First, to address the difficulty of multi-scale permutation entropy in characterizing the fault information contained in the derivatives of the raw signal, a novel feature named derivative multi-scale permutation entropy is designed, which can further complete the fault information of RPMs. Second, to further improve the diagnosis accuracy of support vector machines, a decision fusion strategy based on three feature sets is developed, which can further improve the diagnosis accuracy, especially in the normal-reverse direction. Finally, the effect and superiority of the proposed method are verified based on the collected vibration signals from Xi’an Railway Signal Co.,Ltd by experiment comparisons. The diagnosis accuracies of reverse-normal and normal-reverse directions reach 99.43% and 100% respectively, indicating its superiority.
CT-based synthetic contrast-enhanced dual-energy CT generation using conditional denoising diffusion probabilistic model
Authors: Gao Yuan , Qiu Richard L J , Xie Huiqiao , Chang Chih-Wei , Wang Tonghe , Ghavidel Beth , Roper Justin , Zhou Jun , Yang Xiaofeng 
Published: July 2024

Abstract

Objective. The study aimed to generate synthetic contrast-enhanced Dual-energy CT (CE-DECT) images from non-contrast single-energy CT (SECT) scans, addressing the limitations posed by the scarcity of DECT scanners and the health risks associated with iodinated contrast agents, particularly for high-risk patients. Approach. A conditional denoising diffusion probabilistic model (C-DDPM) was utilized to create synthetic images. Imaging data were collected from 130 head-and-neck (HN) cancer patients who had undergone both non-contrast SECT and CE-DECT scans. Main Results. The performance of the C-DDPM was evaluated using Mean Absolute Error (MAE), Structural Similarity Index (SSIM), and Peak Signal-to-Noise Ratio (PSNR). The results showed MAE values of 27.37±3.35 Hounsfield Units (HU) for high-energy CT (H-CT) and 24.57±3.35HU for low-energy CT (L-CT), SSIM values of 0.74±0.22 for H-CT and 0.78±0.22 for L-CT, and PSNR values of 18.51±4.55 decibels (dB) for H-CT and 18.91±4.55 dB for L-CT. Significance. The study demonstrates the efficacy of the deep learning model in producing high-quality synthetic CE-DECT images, which significantly benefits radiation therapy planning. This approach provides a valuable alternative imaging solution for facilities lacking DECT scanners and for patients who are unsuitable for iodine contrast imaging, thereby enhancing the reach and effectiveness of advanced imaging in cancer treatment planning.
Non-linear media in weakly curved spacetime: optical solitons and probe pulses for gravimetry
Authors: Belenchia Alessio , Spengler Felix , Rätzel Dennis , Braun Daniel 
Published: July 2024

Abstract
That light propagating in a gravitational field gets frequency-shifted is one of the basic consequences of any metric theory of gravity rooted in the equivalence principle. At the same time, also a time dependent material’s refractive index can frequency-shift light propagating in it. The mathematical analogy between the two effects is such that the latter has been used to study the optical analogue of a black-hole spacetime. Here, we combine these two effects by showing that light propagation in non-linear media in the presence of a moving refractive index perturbation can lead to a gravity-dependent blueshift. We find that the predicted blueshift surpasses the gravitational redshift even if the medium is considered to be perfectly stiff. In realistic scenarios, by far the strongest frequency shift arises due to the deformation of the dielectric medium and the corresponding photoelastic change of refractive index. This has the potential to facilitate optical sensing of small gravity gradients.
A model to predict indoor concentrations and internal radiation doses of radioactive aerosols from nuclear accidents
Authors: Orabi M 
Published: July 2024

Abstract
Spread of radiation contaminations can be affected by several factors. Some of these factors were considered in previous articles. Those studies were based on some Computational Fluid Dynamic (CFD) schemes and gave good results for describing deposition and penetration of aerosol particles. In this paper, those CFD schemes are applied to set a model that can be used to calculate the indoor concentrations of the radioactive aerosols that release from nuclear accidents. The one of the Fukushima nuclear power plant (NPP) that took place in 2011 is taken as an example. Furthermore, the internal radiation doses caused by the intake of the radioactive aerosols are estimated. Considering in particular the radionuclide

C

137

s
,

due to its very long half-life, the internal doses are calculated for the lungs and some of the surrounding vital organs. The radiation transport throughout the body is simulated by codes of the Monte-Carlo N-Particle simulation software, version 5 (MCNP5), with exploiting the human body representation by the phantom of the Oak Ridge National Laboratory-Medical Internal Radiation Dose (ORNL-MIRD). The results show a large spread of the radiation contaminations from outdoors to indoors, and that the whole-body annual dose from

C

137

s

is more than tenfold higher than the annual dose limit set by the International Commission on Radiological Protection (ICRP).
Nuclear acoustic envelope soliton in a relativistically degenerate magneto-rotating stellar plasma
Authors: Chandra Swarniv , Manna Gobinda , Mahanta Deepsikha 
Published: July 2024

Abstract
The study explores a model called Relativistic Degenerate Magneto-Rotating Quantum Plasma (RDMRQP), which comprises a static heavy nucleus, an inertial non-degenerate light nucleus, and warm non-relativistic or ultra-relativistic electrons. The focus is on observing the emergence of Nucleus-Acoustic Envelope Solitons (NAESs). Using the reductive perturbation method, a Nonlinear Schrödinger equation (NLSE) is derived to characterize the properties of NAESs. We have analysed the Peregrine breather soliton solution. The investigation reveals that the temperature of warm degenerate species, plasma system’s rotational speed, and the presence of heavy nucleus species can alter the fundamental features (height and width) of NAESs in the WDMRQP system. The study emphasizes the existence of only positive NA wave potential. Additionally, a phase plane analysis is conducted to gain a deeper understanding of the parametric dependencies. Through detailed mathematical and numerical analysis, the study avoids overloading with complex mathematics while demonstrating parametric dependence via phase portrait analysis. The research augments the envelop soliton model with breather mode solutions and discusses modulation instability using the Benjamin-Feir Index, highlighting the significance of solitons in star formation. Envelop solitons, stable waves within stars and proto-stars, influence energy transport and stellar evolution, playing a crucial role in the accretion process and formation of stable structures. Key findings include the effects of various parameters on NAESs’ generation and propagation in which non-relativistic and ultra-relativistic electrons support NAESs, with amplitude and width influenced by temperature, rotational frequency, inclination angle, and the presence of a static heavy nucleus. The research is applicable to hot white dwarfs and neutron stars, suggesting further exploration of quantum effects and non-planar or arbitrary amplitude NAESs.
Evidence of spin-phonon interactions in MgCu2O3: low temperature Raman studies
Authors: Chandra Somesh , Kaur Gurpreet , Gupta Rajkumar , Chakravarty Sujay , Bhalerao G M , R Govindaraj 
Published: July 2024

Abstract
Experimental low temperature Raman spectroscopy studies upto the temperature of 83 K were performed on MgCu2O3 compound using 785 nm excitation source. Experimentally obtained Raman spectra compare well with those obtained from DFPT calculations. Phonon modes show different behaviour below and above the Néel temperature ∼95 K. Anharmonic contribution is prominent above the Néel temperature but a significant departure from the anharmonic behaviour was observed for certain

A

g

and

B

3
g

modes below the Néel temperature. This behaviour is attributed to spin-phonon coupling present in the compound. The spin-phonon coupling arises due to modulation in the exchange integral by the lattice vibrations. The atomic vibrations of each mode and their effect on the exchange integral are discussed.
Artificial bee colony optimization algorithm with full dimensional updating strategy and its application
Authors: Li Yuangang , Deng Wu 
Published: July 2024

Abstract
For the low accuracy and slow convergence speed of artificial bee colony(ABC) algorithm in solving complex optimization problems, an improved artificial bee colony(ABC) algorithm based on the new full dimensional updating ABC/best /1 strategy, namely FNABC was proposed in this paper. In the FNABC, for the low efficiency of one-dimensional search, the full dimensional updating search strategy and ABC/best /1 strategy were combined to design a new full dimensional updating ABC/best/1 strategy, which expanded the search space, improved the mining ability and search efficiency. Then, a new evolutionary phase is designed to balance the global search ability and local mining ability to avoid falling into local optimum and improve the convergence accuracy. Finally, the FNABC is compared with eight state-of-the-art ABC variants such as AABC, iqABC, MEABC, ABCVSS, GBABC, DFSABC, MABC-NS, MGABC in solving 12 complex functions. All functions have obtained the best optimal values among 9 algorithms. Additionally, FNABC is applied to solve a real-world train operation adjustment problem. The experiment results indicate that the FNABC has better optimization ability, scalability and robustness. It obtains the ideal train operation adjustment results.
Size-dependent nonlinear free vibration of magneto-electro-elastic nanobeams by incorporating modified couple stress and nonlocal elasticity theory
Authors: Zhou Yang , Zheng Yu-fang , Wang Feng , Chen Chang-ping 
Published: July 2024

Abstract
Magneto-Electro-Elastic (MEE) Composites, as an innovative functional material blend, are composed of multiple materials, boasting exceptional strength, rigidity, and an extraordinary magneto-electric interaction effect. This paper establishes a nonlocal modified couple stress (NL-MCS) magneto-electro-elastic nanobeam dynamic model. To accurately capture the intricate influences of scale effects on nanostructures, This model meticulously examines scale effects from two distinct perspectives: leveraging nonlocal elasticity theory to elucidate the softening phenomena in nanostructures stemming from long-range particle interactions, and employing modified couple stress theory to reveal the hardening effects attributed to the rotational behavior of particles within the structure. By incorporating Von Karman geometric nonlinearity, Reddy’s third-order shear deformation theory and Maxwell’s equations, the governing equations for the nonlinear free vibration of MEE nanobeams are derived using Hamilton’s principle. Finally, a two-step perturbation method is employed to solve these equations. Two-step perturbation method disintegrates the solution process into two stages, iteratively approximating and refining the solution, thereby progressively unraveling the intricate details and enhancing the precision of the solution in a systematic manner. Finally, the nonlinear free vibration behavior of MEE nanobeams is explored under the coupled magnetic-electric-elastic fields, with a focus on the effects of various factors that including length scale parameters, nonlocal parameters, Winkler-Pasternak coefficients, span-to-thickness ratios, applied voltages and magnetic potentials.