bluuebunny/crossref_metadata_2025_split huggingface dataset:
Classification and parameterization of a large Gaia sample of white dwarfs using XP spectra
Authors: Vincent O. , Barstow M. A. , Jordan S. , Mander C. , Bergeron P. , Dufour P. 
Published: November 2023

Context. The latest Gaia data release in July 2022, DR3, in addition to the refinement of the astrometric and photometric parameters from DR2, added a number of important data products to those available in earlier releases, including radial velocity data, information on stellar multiplicity, and XP spectra of a selected sample of stars. Gaia has proved to be an important search tool for white dwarf stars, which are readily identifiable from their absolute G magnitudes as low luminosity objects in the Hertzsprung–Russell (H–R) diagram. Each data release has yielded large catalogs of white dwarfs, containing several hundred thousand objects, far in excess of the numbers known from all previous surveys (∼40 000). While the normal Gaia photometry (G, GBP, and GRP bands) and astrometry can be used to identify white dwarfs with high confidence, it is much more difficult to parameterize the stars and determine the white dwarf spectral type from this information alone. Observing all stars in these catalogs with follow-up spectroscopy and photometry is also a huge logistical challenge with current facilities.
Aims. The availability of the XP spectra and synthetic photometry presents an opportunity for a more detailed spectral classification and measurement of the effective temperature and surface gravity of Gaia white dwarfs.
Methods. A magnitude limit of G < 17.6 was applied to the routine production of XP spectra for Gaia sources, which would have excluded most white dwarfs. Therefore, we created a catalog of 100 000 high-quality white dwarf identifications for which XP spectra were processed, with a magnitude limit of G < 20.5. Synthetic photometry was computed for all these stars, from the XP spectra, in Johnson, SDSS, and J-PAS, published as the Gaia Synthetic Photometry Catalog – White Dwarfs (GSPC-WD). We took this catalog and applied machine learning techniques to provide a classification of all the stars from the XP spectra. We have then applied an automated spectral fitting program, with χ-squared minimization, to measure their physical parameters (effective temperature and log g) from which we could estimate the white dwarf masses and radii.
Results. We present the results of this work, demonstrating the power of being able to classify and parameterize such a large sample of ≈100 000 stars. We describe what we can learn about the white dwarf population from this dataset. We also explored the uncertainties in the process and the limitations of the dataset.
Rhodium-Catalyzed Direct Vinylene Annulation of 2-Aryloxazolines and Cascade Ring-Opening Using a Vinyl Selenone
Authors: Nishii Yuji , Miura Masahiro , Kitano Junya , Hirano Koji 
Published: November 2023

AbstractOver the past two decades, transition-metal-catalyzed C–H activation and the subsequent oxidative cyclization with alkynes or their surrogates has emerged as a powerful synthetic tool for fused heteroaromatics. We report a Rh(III)-catalyzed annulation and ring-opening cascade reaction with 2-aryloxazolines. By utilizing a vinyl selenone as an oxidizing acetylene surrogate, the target three-component coupling products were obtained in high yields without using a stoichiometric amount of external oxidant.
Synthesis of an Alternating Polycation with the Dense 1,2,3-Triazole Backbone
Authors: Hashidzume Akihito , Omae Tomoki , Nakahata Masaki , Kamon Yuri 
Published: November 2023

AbstractPolycations are an important class of water-soluble polymers because they form polyion complexes with DNA. Thus, the synthesis of polycations with controlled monomer sequences will be of increasing importance for the formation of well-defined polyion complexes. In this study, cationic homopolymer and alternating copolymer with the dense triazole backbone were synthesized by copper(I)-catalyzed azide–alkyne cycloaddition polymerization. The polycations obtained were characterized by potentiometric and turbidimetric titrations, and by complex formation with poly(acrylic acid).
Design of Indole-Functionalized Phosphepines towards New Organic Chromophores
Authors: Ren Yi , Liu Zhaoxin 
Published: November 2023

AbstractOrganic chromophores emerged as diverse functional materials in the areas of organic catalysis, toxic materials sensing, bio-imaging, and organic electronic devices. With rich chemical and electronic structures, main-group elements have been extensively implanted in organic chromophores to fine-tune the chemical/electronic structures and optoelectronic properties. In this Synpact article, we present a concise overview of the development of phosphorus (P)-containing organic chromophores, further highlighting our recent contributions in the field. A new aspect of combining the P element with the indole moiety was pursued to construct a new series of seven-membered P-organic chromophores; namely, indole-functionalized phosphepines. The new combination endowed the system with rich chemical and electronic structures, for which intriguing photophysical properties were consequently revealed. The combination provided an efficient synthetic protocol to access new P-heterocycles and also offered a new strategy to design functional organic chromophores.
The Cyanopyridine–Aminothiol Click Reaction: Expanding Horizons in Chemical Biology
Authors: Nitsche Christoph 
Published: November 2023

AbstractBioorthogonal reactions hold significant promise for applications in chemical biology. Despite their potential, nitriles have often been overlooked as reactive functional groups for selective bioconjugation. The condensation reaction between cyanopyridines and 1,2-aminothiols stands out as a particularly favorable nitrile modification strategy that proceeds under biocompatible conditions. Cyanopyridines can be seamlessly incorporated into peptides and proteins through both chemical and biotechnological approaches. Similarly, the selective integration of 1,2-aminothiols into peptides and proteins is achievable, leveraging the uniquely reactive N-terminal cysteine functional group.1	Introduction2	The Biocompatible Condensation Reaction3	Peptide Macrocyclisation4	Orthogonality to Cysteine5	Combination with Genetic Encoding6	Conclusion
Synthesis of the Hexasaccharide Repeating Unit Corresponding to the Cell Wall O-Antigen of Providencia alcalifaciens O9:H8 Strain
Authors: Misra Anup Kumar , Rana Abhijit 
Published: November 2023

AbstractA straightforward synthesis of the hexasaccharide repeating unit of the O-specific polysaccharide of Providencia alcalifaciens O9:H8 strain was achieved in very good yield by applying a stereo- and regioselective [4+2] block glycosylation strategy. The tetrasaccharide acceptor and disaccharide donor were synthesized by sequential stereo- and regioselective glycosylations. Thioglycoside and glycosyl trichloroacetimidate derivatives were used as glycosyl donors in the synthetic strategy. The glycosylation steps were high-yielding and gave satisfactory stereochemical outcomes.
Interaction in prevention: a general theory and an application to COVID-19 pandemic
Authors: Battiston Pietro , Menegatti Mario 
Published: November 2023

AbstractWe study a model introducing interactions in agents’ prevention effort, including both the case where agents’ efforts reinforce each others and the case where they are conflicting. We characterize best response functions, distinguishing the case of strategic complementarity and the case of strategic substitutability, and determine the features of Nash equilibria in both cases. We find conditions for under- and over-provision of prevention compared to its socially optimal level. Finally, we specialize our model to describe the risk of COVID-19 infection. We show the features of contagion are consistent with the existence of asymmetric equilibria and we provide arguments in favor of policy interventions, such as making face masks mandatory, despite the possibility that they reduce some agents’ effort.
Tax holidays and profit-repatriation rates for FDI firms: the case of the Czech Republic
Authors: Vu Duong Hoang , Pavelková Drahomíra , Damborský Milan 
Published: November 2023

AbstractThe Czech Republic has been a promising destination for foreign investors due to its locational advantages and tax-incentive policy. However, the profit-repatriation rate in the country is extremely high, which results in less capital being available for development. This paper studies the differences in profit-repatriation rates among FDI (foreign direct investment) firms in the Czech Republic after the appearance of tax-holiday incentives from 2008 to 2019. The precondition is to find the determinants of the repatriation rate of FDI firms, and the results show that the profit repatriation rate of FDI firms is positively affected by firm size and the liquidity of firms and negatively affected by investment opportunities and leverage. The paper divides FDI firms into several groups and examines the differences in repatriation rates between them before revealing the determinants of these differences. Firstly, there is no difference in profit repatriation between FDI firms with tax incentives and those without tax incentives. Next, we divide the FDI firms with tax incentives into two groups: those who still enjoy the tax incentives and those who no longer enjoy the tax incentives. The FDI firms with tax incentives that are in the tax-incentive period repatriate less than FDI firms with tax incentives that are not in the tax period any longer. The difference stems from the endowment effect, and three determinants that can reduce the repatriation rate of FDI firms that are no longer in the tax period are investment opportunities, leverage, and firm size.
Liquid-metal/NdFeB/Ni composites for high wettability, patternable, stretchable electronic wire
Authors: Zhu Zhifang , Zhao Ran , Ye Bingliang , Wang Huan 
Published: November 2023

Room-temperature liquid-metal (LM) has high conductivity, which is an ideal material for manufacturing stretchable electronic wires. However, its high surface tension and fluidity make it extremely difficult to adhere to or encapsulate on flexible substrates. This work developed LM/NdFeB/Ni composites for stretchable electronic wires. The composites were composed of Ga68.5In21.5Sn10 (with a melting point at −19 °C) alloys, Nd2Fe14B (5 μm), and Ni (50–500 nm) microparticles. The SEM and EDS results showed the porous structure of the composites. Ni particles were added to improve the magnetic properties of LM/NdFeB composites, as well as the porous structure composed of magnetized NdFeB particles. Thereby the structure exhibited a heightened capacity for LM locking. Test results indicate that the liquid metal wires have good wettability and adhesion on different surfaces and could be manufactured using different patterning methods. Moreover, its anti-extrusion and anti-leakage characteristics were suitable for constructing stretchable circuits in open channels or on flat surfaces. The proposed LM/NdFeB/Ni composites are expected to manufacture low-cost, patternable, and anti-extrusion stretchable electronic wires.
An improved algorithm for thermal compensation of synchrotron radiation optical mirrors based on Hessian matrix
Authors: Li Tong , Zhang Haipeng , Jin Limin , Zhu Wanqian , Chen Jiahua , Xue Song 
Published: November 2023

The heaters-based thermal-compensated adaptive adjustment of a reflection mirror at Shanghai high repetition rate X-ray Free-Electron Laser and extreme light facility (SHINE) is presented here based on finite element analysis. The correction performance of different control algorithms [singular value decomposition and gradient descent (GD)] is analyzed and compared. This study has demonstrated that a significant control algorithm can further improve the surface shape accuracy of the mirror. After optimizing the mirror control algorithm, the calculated slope errors and height errors of the mirror are reduced to nearly less than 50 nrad rms and 0.5 nm rms, respectively. The optimization result indicates that the GD control algorithm based on the Hessian matrix exhibits superior performance and practicality compared to the control algorithm before optimization.
Language contact, identity building and attitudes towards the use of a minoritized language in the public
space
Authors: Arias Álvarez Alba , Bernardo-Hinesley Sheryl 
Published: November 2023

Abstract
Recent sociolinguistic studies have emphasized the role of the Linguistic Landscape in analyzing language
attitudes and identities in relation to minoritized languages. The present study examines language attitudes and perceptions of
Asturian speakers towards the use of Asturian, a minoritized regional language spoken in Asturies, Spain, in the public space.
Data was gathered through a survey questionnaire distributed amongst residents of Mieres, a municipality located in the center of
Asturies. Through qualitative and quantitative analyses, results show that the presence of Asturian linguistic and semiotic
resources reinforces participants’ Asturian identity. Findings reveal positive language attitudes: not only do participants
believe that speaking Asturian is an essential part of being Asturian, but they want Asturians to continue learning and speaking
the language. This study shows how the Linguistic Landscape is a valuable tool in uncovering language attitudes and perceptions,
which are inextricably linked to one’s identity within a community.
Recovering critical parameter for nonlinear Allen–Cahn equation by fully discrete continuous data assimilation algorithms
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Authors: Wang Wansheng , Jin Chengyu , Huang Yunqing 
Published: November 2023

Abstract
The purpose of this study is to recover the diffuse interface width parameter for nonlinear Allen–Cahn equation by a continuous data assimilation algorithm proposed recently. We obtain the large-time error between the true solution of the Allen–Cahn equation and the data assimilated solution produced by implicit–explicit one-leg fully discrete finite element methods due to discrepancy between an approximate diffuse interface width and the physical interface width. The strongly A-stability of the one-leg methods plays key roles in proving the exponential decay of initial error. Based on the long-time error estimates, we develop several algorithms to recover both the true solution and the true diffuse interface width using only spatially discrete phase field function measurements. Numerical experiments confirm our theoretical results and verify the effectiveness of the proposed methods.
Operation stage division and RUL prediction of bearings based on 1DCNN-ON-LSTM
Authors: Guo Runxia , Li Haonan , Huang Chao 
Published: November 2023

Abstract
Remaining useful life (RUL) prediction of bearings is significantly important to ensure reliable operation of bearings. In practice, it is routinely impossible to obtain the full life cycle degradation data of bearings that needs to be used in prediction. The accuracy of the RUL prediction of bearings is often affected by incomplete degradation data. Regarding this situation, this paper proposes a multi-sensor three-stage RUL prediction framework based on the one-dimensional convolutional ordered neuron long short-term memory (1DCNN-ON-LSTM) neural network. Firstly, 1DCNN is used to extract spatial features adaptively from multi-sensor’s data and fuse them into one-dimensional feature. Next, the unsupervised hierarchy mechanism of time series information based ON-LSTM is developed to determine the ‘initial degradation stage point’ and ‘rapid degradation stage point’ of the bearing from the one-dimensional feature. Once the signal features collected by sensors input to the model reach the degradation stage point, select the corresponding sensitive features as input and construct the 1DCNN-ON-LSTM model that performs RUL prediction after the degradation stage point to improve the prediction accuracy of the model. Based on the proposed hierarchy mechanism, the bearings’ operation process is divided into three operation stages: normal stage, initial degradation stage and rapid degradation stage. Finally, the experiments verify that the proposed method can effectively divide the operation stages of bearings to predict the RUL and improve the generalization ability and prediction accuracy of the model.
A lightweight high-resolution algorithm based on deep learning for layer-wise defect detection in laser powder bed fusion
Authors: Yan Hualin , Cai Jian-Feng , Zhao Yingjian , Jiang Zimeng , Zhang Yingjie , Ren Hang , Zhang Yuhui , Li Huaping , Long Yu 
Published: November 2023

Abstract
The quality of the powder bed is critical in the laser powder bed fusion (LPBF) process, and defects in the powder bed likely affect the quality of the final part. With the development of artificial intelligence technology, machine learning methods have been widely applied in powder-bed defect detection. However, to achieve high-precision defect detection, it is often necessary to construct complex network models and use high-resolution powder bed image data. To address these issues, this study used an off-axis industrial camera to capture layer-wise powder bed image data and proposed a defect detection model based on YOLOv7x and channel pruning to achieve defect identification and localization of powder bed patch images. Furthermore, an end-to-end defect detection pipeline based on image processing methods was proposed to detect defects in layer-wise powder bed images. Finally, the gradient-based class activation map technique (Grad CAM++) was used to analyze the interpretability of the detection results of the model. The results indicated that the proposed model was more lightweight than other models (YOLOv7x, Faster R-CNN, and SSD), with a model size of only 12.4MB. The average time for detecting powder bed image patches was significantly reduced to only 3.4 ms, and the average detection accuracy was as high as 97.4%. This demonstrates that the proposed detection method has the advantages of faster detection speed, higher detection accuracy, and simpler models, providing a reference for the real-time online detection of powder bed defects.
Effects of tissue heterogeneity and comparisons of collapsed cone and Monte Carlo fast neutron patient dosimetry using the University of Washington clinical neutron therapy system (CNTS)
Authors: Moffitt Gregory B , Sandison George A , Argento David C , Emery Robert , Wootton Landon S , Parvathaneni Upendra , Liao Jay J , Laramore George E , Stewart Robert D 
Published: November 2023

Abstract
Fast neutron therapy is a high linear energy transfer (LET) radiation treatment modality offering advantages over low LET radiations. Multileaf collimator technology reduces normal-tissue dose (toxicity) and makes neutron therapy more comparable to MV x-ray treatments. Published clinical-trial and other experiences with fast neutron therapy are reported. Early comparative studies failed to consider differences in target-dose spatial conformality between x-ray and neutron treatments, which is especially important for organs-at-risk close to tumor targets. Treatments planning systems (TPS) for high-energy neutrons lag behind TPS tools for MV x-rays, creating challenges for comparative studies of clinical outcomes. A previously published Monte Carlo model of the University of Washington (UW) Clinical Neutron Therapy System (CNTS) is refined and integrated with the RayStation TPS as an external dose planning/verification tool. The collapsed cone (CC) dose calculations in the TPS are based on measured dose profiles and output factors in water, with the absolute dose determined using a tissue-equivalent ionization chamber. For comparison, independent (external) Monte Carlo simulation computes dose on a voxel-by-voxel basis using an atlas that maps Hounsfield Unit (HU) numbers to elemental composition and density. Although the CC algorithm in the TPS accurately computes neutron dose to water compared to Monte Carlo calculations, calculated dose to water differs from bone or tissue depending largely on hydrogen content. Therefore, the elemental composition of tissue and bone, rather than the material or electron density, affects fast neutron dose. While the CC algorithm suffices for reproducible patient dosimetry in fast neutron therapy, adopting methods that consider tissue heterogeneity would enhance patient-specific neutron dose accuracy relative to national standards for other types of ionizing radiation. Corrections for tissue composition have a significant impact on absolute dose and the relative biological effectiveness (RBE) of neutron treatments compared to other radiation types (MV x-rays, protons, and carbon ions).
Collective behavior of self-propelled particles with multiple delays in cross-domain scenario
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Authors: Zhou Yongjian , Wang Tonghao , Peng Xingguang 
Published: November 2023

Abstract
In cross-domain scenarios, the simultaneous presence of multiple sensing delays exerts a profound influence on collective behavior. Motivated by this, our paper presents a system based on self-propelled particles that consists of two swarms containing two intra-swarm sensing delays and an inter-swarm sensing delay. Three state emerges from the system, namely translating state, ring state, and rotating state. Employing mean field approximation and bifurcation analysis, we theoretically examine the parameter space’s boundaries that govern these three states. Our detailed findings emphasize that within the translating and rotating states, variations in the two intra-swarm delays can lead to the separation of the two swarms. Meanwhile, the extent of separation is influenced by the inter-swarm delay. Finally, we conduct numerical simulations to validate the accuracy of our theoretical derivations.
New variable separation solutions and localized waves for (2+1)-dimensional nonlinear systems by a full variable separation approach
Authors: Quan Jingfeng , Tang Xiaoyan 
Published: November 2023

Abstract
A full variable separation approach is firstly proposed for (2+1)-dimensional nonlinear systems by extending the well-established multilinear variable separation approach through the assumption that the expansion function is composed of full variable separated functions, namely, functions with respect to only one spacial or temporal argument. Taking the (2+1)-dimensional Boiti-Leon-Manna-Pempinelli equation, the Nizhnik-Novikov-Veselov equation and the dispersive long wave equation as examples, new full variable separation solutions are obtained with several arbitrary one dimensional functions. Especially, a common formula for some suitable physical quantities is discovered. By taking the arbitrary functions in different explicit expressions, the solutions can be used to describe plentiful novel nonlinear localized waves, which might be non-travelling waves as the spacial and temporal variables are fully separated into different functions. In particular, some new hybrid solitary waves, which can pulsate periodically, appear and/or decay with an adjustable lifetime, are discovered through the on-site interactions between a doubly periodic wave and a ring soliton, a four-humped dromion and a four-humped lump, and a doubly periodic wave and a cross type solitary wave. Nonlinear wave structures and their dynamical behaviours are discussed and graphically displayed in detail.