bluuebunny/crossref_metadata_2025_split huggingface dataset:
Cranial Nerve Dysfunction in Patients with an Occipital Condyle Fracture: Underdiagnosis and Clinical Relevance
Authors: Thevis Madelon , Derks Jolanda , Jansen Thijs T.G. , Hosman Allard J.F. , Kunst Henricus P.M. 
Published: November 2024

Abstract
Objectives This study aims to fill in the knowledge gap about patients with occipital condyle fractures (OCFs) and cranial nerve dysfunction (CND) and give advice about when to test the cranial nerves (CNs) and what to do when CND is diagnosed.
Design A 14-year period observational, retrospective cohort study.
Setting Level-I trauma center study.
Participants All 119 surviving cases admitted with an OCF, whereof all 40 cases with either diagnosed CND (confirmed by clinical examination) or expected CND (reported observations high suspicious for CND) were selected for detailed data collection. Early death was the only exclusion criterion because of missing data and clinical irrelevance.
Main Outcome Measures One-third of all surviving OCF patients have CND (n = 40/119, 33.6%), where three-quarters had more than one CN affected with a median of three CNs. Of the cases with a concomitant lateral skull base fracture (n = 24/40, 60%), one in three cases (36%, n = 13/36) had facial nerve palsy and nearly two in three cases (61%, n = 22/36) had hearing loss.
Results The facial nerve was the most commonly diagnosed CND. Solitary OCF cases often had lower CND (n = 11/14). Fifty-eight percent of all CND cases with follow-up data (n = 19/33)—corresponding to one in six of all surviving OCF cases—had chronic CND sequelae.
Conclusions Multiple and chronic CND is common in patients with an OCF. All CNs should be tested in those patients as soon as clinically possible, and testing should be repeated after 3 to 7 days and before discharge. Patients with CND should be counseled about their prognosis and be potentially referred to (e.g.) a speech and language therapist, ophthalmologist, neurologist, or otorhinolaryngologist for early treatment options.
Race and affect in Gustave de Beaumont’s Marie, ou L’esclavage aux Etats‑Unis
Authors: Dobie Madeleine 
Published: November 2024

Abstract
Gustave de Beaumont’s novel Marie, ou l’esclavage (1835), a companion piece to
Alexis de Tocqueville’s Democracy In America (1835, 1840)
(Beaumont accompanied Tocqueville on his travels through the United States), belongs to a small group of early
nineteenth-century francophone fictions in which the question of slavery is deflected onto the examination of race.
Romantic psychology and epistemology shape Beaumont’s exploration of race as a site of emotional intensity that has no
fixed referent. This treatment of race as an emotional forcefield rather than as the cause of an emotional effect,
anticipates the work of theorists of affect and social emotionality such as Sara Ahmed. While Beaumont strives to
demystify race, thereby exposing the absurdity of racial prejudice, by centering whiteness as an aesthetic value and
metaphor for purity, the novel in the end illustrates its tenacious hold.
Orientalism, slavery and emotion
Authors: Moussa Sarga 
Published: November 2024

Abstract
The oriental travel narratives of the first half of the nineteenth century played an important
role in debates about slavery. An episode in the slave market of Constantinople that appeared in Alphonse de
Lamartine’s Voyage en Orient (1835) created a model followed by later writers. But while Lamartine, a
committed abolitionist, tried to stir up feelings of pity by describing the sale of a black woman and her child, in
Marcellus, Nerval and Pückler-Muskau, similar descriptions evoked different reactions, ranging from the condemnation
of Islamic polygamy to the acceptance of slavery as an ‘oriental fatality.’ Nerval, for his part, reserved pity for
the fate of white slaves. Oriental travel narratives as such represent a kind of emotional barometer that gauges both
the progress of abolitionist discourse and resistance to it.
Affection amidst domination in a post-slavery society
Authors: Cottias Myriam 
Published: November 2024

Abstract
This article considers the relationship between compensation and intimacy, focusing on the
relationship between the colonist Pierre Dessalles, who owned a plantation in the French colony of Martinique in the
mid-nineteenth century, i.e. the period of the abolition of slavery, and Nicaise, one of his slaves. It shows slavery
to be a relation of property and domination that did not, however, foreclose the possibility of emotional ties ranging
from fear, anger and disgust to love. Readings of the diary of this planter — an exceptional document for its time —
show how intimacy and “emotion” in all senses of the word — feelings but also, in French, something closer to
“stirring” or “revolt” — both shape and are shaped by the political situation in which they develop.
Optimizing solar cell models: a multi-objective parameter estimation algorithm for improved photovoltaic system performance
Authors: Singla Manish Kumar , Aljaidi Mohammad , Gupta Jyoti , Safaraliev Murodbek , Kumar Ramesh , Ali Ziad M , Alsharif Mohammed H , Kim Mun-Kyeom 
Published: November 2024

Abstract
Accurate models of solar cells are required to improve the performance of solar photovoltaic (PV) systems. Due to a lack of precise parameters in the manufacturer’s datasheet, the solar cell model is often inaccurate. Estimating the parameters needed improperly makes it impossible to build up a reliable solar PV cell model. This paper proposes an algorithm for estimating cell parameters by multi-objective optimization to solve this issue. Several optimizers attempted to address the suboptimal results of optimization due to local minima and premature convergence. This work aims to evaluate the effectiveness of the proposed algorithm with those other popular algorithms to understand its reliability. The efficiency of this algorithm is proven using empirical results and statistical figures. It has important features, including simplicity and high accuracy, which imply that the algorithm is better suited to estimating solar PV models when compared with other algorithms. This algorithm is robust as it is computationally efficient and easy to use, which makes this method applicable for solving a wide variety of problems related to solar energy.
Structural, electronic, vibrational, optical and thermoelectric properties of 1T-Na2O monolayer via MD and DFT study
Authors: Rueshwin S Chellaiya Thomas , Eithiraj R D 
Published: November 2024

Abstract
Density Functional Theory (DFT) was implemented to determine the physical properties of the 1T-Na2O monolayer with the aid of WIEN2k software. To determine the electronic property exchange correlation such as GGA and hybrid functionals were implemented. The electronic property studies unveiled the 1T-Na2O monolayer as a direct bandgap semiconductor that has band gap values of 1.68 eV and 2.75 eV with GGA and hybrid correlation functionals. The dynamical stability of the 1T-Na2O monolayer was established by harnessing Phonon dispersion analysis, while the thermal stability was established by harnessing the Ab-initio Molecular Dynamics (AIMD). The optical properties investigation revealed that the 1T-Na2O monolayer shows an excellent absorption coefficient in the UV region and has a potential application in optoelectronic applications. The 1T-Na2O monolayer shows promise for waste heat recovery systems due to its thermoelectric properties, with a figure of merit of 0.82 at 400 K. The effective masses of electrons and holes (charge carriers) are determined. The relative ratio was estimated to determine the recombination rate of charge carriers and was found to be limited.
Coport: a new public code for polarized radiative transfer in a covariant framework
Authors: Huang Jiewei , Zheng Liheng , Guo Minyong , Chen Bin 
Published: November 2024

Abstract
General relativistic radiative transfer calculations are essential for comparing theoretical models of black hole accretion flows and jets with observational data. In this work, we introduce Coport,[The public version of Coport is available at the following URL: https://github.com/JieweiHuang/Coport.] a novel public code specifically designed for covariant polarized ray-tracing radiative transfer computations in any spacetime. Written in Julia, Coport includes an interface for visualizing numerical results obtained from HARM, a publicly available implementation of the general relativistic magnetohydrodynamics code. We validate the precision of our code by comparing its outputs with the results from a variety of established methodologies. This includes the verification against analytical solutions, the validation through thin-disk assessments, and the evaluation via thick-disk analyses. Notably, our code employs a methodology that eliminates the need for separating the computations of spacetime propagation and plasma propagation. Instead, it directly solves the coupled, covariant, polarized radiative transfer equation in curved spacetime, seamlessly integrating the effects of gravity with plasma influences. This approach sets our code apart from the existing alternatives and enhances its accuracy and efficiency.
Fast likelihood-free inference in the LSS Stage IV era
Authors: Franco-Abellán Guillermo , Cañas-Herrera Guadalupe , Martinelli Matteo , Savchenko Oleg , Sciotti Davide , Weniger Christoph 
Published: November 2024

AbstractForthcoming large-scale structure (LSS) Stage IV surveys will provide us with unprecedented data to probe the nature of dark matter and dark energy. However, analysing these data with conventional Markov Chain Monte Carlo (MCMC) methods will be challenging, due to the increase in the number of nuisance parameters and the presence of intractable likelihoods. In light of this, we present the first application of Marginal Neural Ratio Estimation (MNRE) (a recent approach in simulation-based inference) to LSS photometric probes: weak lensing, galaxy clustering and the cross-correlation power spectra. In order to analyse the hundreds of spectra simultaneously, we find that a pre-compression of data using principal component analysis, as well as parameter-specific data summaries lead to highly accurate results. Using expected Stage IV experimental noise, we are able to recover the posterior distribution for the cosmological parameters with a speedup factor of ∼ 10-60 compared to classical MCMC methods. To illustrate that the performance of MNRE is not impeded when posteriors are significantly non-Gaussian, we test a scenario of two-body decaying dark matter, finding that Stage IV surveys can improve current bounds on the model by up to one order of magnitude. This result supports that MNRE is a powerful framework to constrain the standard cosmological model and its extensions with next-generation LSS surveys.
Timing Calibration of the Follow-up X-Ray Telescope On Board the Einstein Probe Satellite
Authors: Zhao Xiaofan , Cui Weiwei , Wang Hao , Zhang Yifan , Zhao Zijian , Hou Dongjie , Zhu Yuxuan , Wang Yusa , Xu Jingjing , Luo Laidan , Han Dawei , Yang Yanji , Wang Juan , Ma Jia , Yang Xiongtao , Huo Jia , Li Wei , Zhang Ziliang , Geng Haoyang , Chen Yong 
Published: November 2024

Abstract
The Follow-up X-ray Telescope (FXT) is one of the main scientific instruments on board the Einstein Probe astronomical satellite, which was launched in 2024 January. FXT consists of two Wolter I type nested telescopes (FXT-A and FXT-B) with a focal length of 1600 mm. The focal plane detector employs a PNCCD with 384 × 384 pixels. The timing mode of FXT serves as the primary operating mode for fast X-ray timing observations. To evaluate and validate the timing performance of FXT prior to launch, a comprehensive timing calibration was performed at the 100 m X-ray test facility. By simulating various periodic Crab-like profiles using the Grid Controlled X-ray Tube (GCXT) in conjunction with a pulsar simulation module, it was verified that the relative time accuracy of FXT exceeds 5 × 10−9. Furthermore, employing GCXT with a voltage pulse generation module enabled the determination of the time resolutions for FXT-A and FXT-B, recorded as 45.6 ± 2.7 μs and 47.1 ± 2.8 μs, respectively. An absolute timing calibration for FXT-B was carried out using the GCXT and a time interval analyzer, revealing a measured time delay of 3.9 ± 2.1 μs for FXT-B.
Three-dimensional Reverse Time Migration for Detecting Tree Trunk Defects Using Ground Penetrating Radar
Authors: Liu Y , Feng D , Wang X 
Published: November 2024

Abstract
Due to environmental degradation and external intrusions, trees may develop various defects that diminish their stability and survival rates, leading to significant losses. Ground penetrating radar (GPR), characterized by its rapid and non-destructive advantages, has been regarded as a potentially effective method for assessing tree health conditions. However, existing GPR-based tree imaging techniques are predominantly two-dimensional (2D), making it difficult to diagnose three-dimensional (3D) structural features of defects. Therefore, this paper introduces, for the first time, 3D reverse time migration (RTM) into trunk defect detection. Compared to 2D RTM, 3D RTM can simultaneously back-propagate in-line and cross-line signals, accurately locate reflection waves, and focus diffracted waves, reconstructing the true interfaces and defect positions within the tree trunk. Experimental results on irregular trunk models containing a cavity demonstrate the feasibility of 3D RTM in trunk defect detection, providing specific and comprehensive guidance for formulating tree protection and restoration measures.
Preliminary results of the interior features inferred from radargrams, Ulanhada Volcano, Inner Mongolia, China
Authors: Dai S , Su Y , Ding C Y , Xue X P , Li C , Zhu X Y 
Published: November 2024

Abstract
The Ulanhada Volcano Group is located in Inner Mongolia, China. It is an important Quaternary volcanic geological relic with different types of volcanic cones, craters, lava platforms, and other structures. Ground penetrating radar (GPR) can play an important role in volcanic exploration. We used pulse EKKO radar combined with 100MHz and 250MHz antennas to detect the No.1 Redhill volcanic. The results indicate that there are significant differences in reflection characteristics in radargrams of different frequencies, which can be used to analyze the material composition, eruption period, and stratigraphic coverage relationship of volcanic eruptions. At the same time, an accurate analysis of the region will also be used as an evaluation basis for the field scientific verification experiments of China’s Asteroid Core Scan Radar (ACSR) and Lunar Penetrating Radar (LPR).
Construction of electric dyadic Green’s functions in free space based on elliptic cylindrical coordinate system
Authors: Luo Xiangdong 
Published: November 2024

Abstract
A set of vector wave functions is defined in the elliptic cylindrical coordinate system. These vector wave functions can not only describe the propagation characteristics of electromagnetic waves in the elliptic cylindrical coordinate system but also meet the requirements of the electromagnetic field equation. By studying the orthogonality of these vector wave functions, the free space magnetic dyadic Green function is derived by the Ohm-Rayleigh method. The free space electric dyadic Green function is derived from the magnetic dyadic Green function. The special electromagnetic field boundary value problem is transformed into a Green function problem by the electric dyadic Green function. The distribution of the electromagnetic field on the boundary can be obtained by solving the Green function, and then the characteristics of the electromagnetic field can be analyzed. The core of this method is to transform the electromagnetic field problem into a Green function problem, thus simplifying the solving process. This method enriches the electromagnetic field theory and provides a new way to solve the practical electromagnetic field problem.
Utilizing BIC for the intelligent selection of functional data with principal components
Authors: Yu Zhixuan , Chai Xiaolong 
Published: November 2024

Abstract
Functional Principal Component Analysis (FPCA) is a technique for dimension reduction of functional data. Considering the impact of different data ownership, the paper innovatively proposes a weighted B-spline basis function and provides a continuous curve fitting function. Then, smoothing processing is carried out through the basis function expansion method and the maximum penalized likelihood function method. Subsequently, the process of selecting the number of principal components based on the BIC criterion is elaborated. Parameter estimation is realized through the newly proposed BIC-FPCA optimization algorithm. In the empirical analysis section, the paper uses student performance data randomly generated by Python to demonstrate the application of FPCA in data reconstruction. The results show that although the reconstructed data is smoother, there is still room for improvement in the selection of principal components. Finally, the paper summarizes the research findings, suggesting that the BIC criterion be combined with the cumulative variance contribution rate to improve the method of principal component selection, and the algorithm be optimized to reduce computational load. With these improvements, the application effect of FPCA in functional data analysis can be further enhanced.
Space environment simulation and analyses for the DAMPE mission
Authors: Chang Liang , Jiang Hu 
Published: November 2024

Abstract
DAMPE was sent into space orbit for nearly nine years. Since its expected lifespan is only three years, DAMPE has surpassed its expected lifespan by almost six years. Due to its long stay in orbit, some of its components have met with such puzzles as the capabilities of the equipment are partially degrading. The effects of the space environment are responsible for some of its degradation. So, the knowledge of the space environment in the coming year is vital for DAMPE operation. We focus on the following factors: 1) electrons and protons trapped in Earth’s radiation belts; 2) solar proton effect; 3) cosmic ray effect; 4) atom oxygen distribution. Based on the powerful analytic software SPENVIS, some typical effects of space environments are simulated and analyzed respectively, providing supportive constraints when the task team of DAMPE decides when to lengthen the lifespan, or when to start the reentry to Earth’s atmosphere.
Research and application of heteroskedasticity diagnostic method of matrix factor modeling
Authors: Jin Qiaotong , Ma Weijun 
Published: November 2024

Abstract
Matrix-type time series data are widely used in the fields of finance, medical environment, etc. Matrix factor models can effectively downscale such data and reveal their underlying structures. Based on the popular matrix factor model, this paper proposes a diagnostic method for its heteroskedasticity and verifies the effectiveness of the method through numerical simulation. Finally, this paper applies the method to Fama-French portfolio data and finds heteroskedasticity, so that a matrix factor model based on heteroskedasticity can be considered for analyzing this data, thus improving the robustness of the analysis results.
Analysis of light pollution risk assessment level
Authors: Zhai Kunzhi , Zhao Jiahao , Shu Yujie , Zhang Yanyan , Tu Xiaoguang , Lu Jian 
Published: November 2024

Abstract
We develop a widely applicable metric to determine the level of light pollution risk at a site. In general, the appropriate comprehensive evaluation model entropy weight method is used to evaluate and further quantify the risk level of light pollution. We find some factors related to the level of light pollution to solve the data selection and list typical regions for data statistics, classify and pretreatment the obtained data, and then comprehensively analyze the data of influencing factors by entropy weight method to obtain a comprehensive evaluation value. The higher the value is, the higher the risk level of light pollution is. After obtaining the results, it is returned to the original data, taking the pollution risk level as the independent variable, observing the trend of the factors affecting the risk level of light pollution with the change of the degree of light pollution risk level, and analyzing the trend of the curve and find out certain rules. Combined with this law and the actual situation, the light pollution factors are analyzed logically. The direction of light pollution prevention and control can be determined according to the analysis results.
Light culling based on the limitations of human visual perception
Authors: Chen Huiwen , Chen Chunyi 
Published: November 2024

Abstract
We propose a method to remove virtual point light sources (VPLs) in the scene to reduce the time overhead of lighting calculation for shading points in non-visually sensitive areas. We quantify the degree of light stimulation to the human eye and use it to calculate the lighting contribution of VPLs in the scene to visually sensitive areas. Based on this contribution, we remove VPLs that contribute less to visually sensitive areas to improve rendering speed. Experimental results show that the FLIP evaluation index difference between this method and FLC [1] is only 0.00077, while the average number of frames is 1.15 times that of the method in FLC. This proves that this paper can effectively improve rendering speed.
Numerical simulation of high moisture well based on DPM model
Authors: Li Feifei , Liu Chengting , Wei Hongfei , Wang Luna 
Published: November 2024

Abstract
In view of the deposition of high water-cut sand grains in horizontal shaft, this study uses the DPM module in Fluent to track the sand movement trajectory, and the realizable k-e model analyzes the key influence of sand size and sedimentation velocity under the influence of gravity, Saffman lift and friction resistance. CFD simulation results show that the deposition rate of sand grains in the bore and the rate increases with the particle diameter. The results of this study provide a clear direction for the deposition of sand particles in the high water content period and point out that the velocity, viscosity, and particle diameter of the fluid in the shaft can be used as an effective method to eliminate the deposition of sand particles in the high water content period.
Multi-task-based detection and prediction of epileptic EEGs
Authors: Li Bing , Guo Yu , Ni Shuo 
Published: November 2024

Abstract
Epilepsy is a common neurological disorder. Electroencephalography (EEG) is a common method of diagnosing epilepsy. However, it requires long-term supervision by clinical experts to provide alerts. In this paper, we propose a multi-task based epilepsy detection and prediction network (LFMA-Net) for epilepsy detection and prediction, which consists of a lightweight spatiotemporal attention network (LSTAF-Net), a multiscale spatiotemporal attention network (LSTAM-Net), and an AITM. Both LSTAF-Net and LSTAM-Net introduce a spatial spatiotemporal attention module (STAM) and a Lightweight Residual Module (LRM) for feature extraction. Then the 2-second interictal and preictal time intervals were classified using the Shallow and Deep Feature Fusion (SDF) module and the Multiscale Spatio-Temporal Model (MSTM), respectively. Finally, the CHB-MIT dataset was used to test how well the method worked. It made predictions that were 99.25% accurate, 99.34% sensitive, and 99.11% specific. The results show that the multitask-based method suggested in this paper can successfully use EEG data for finding and predicting epilepsy. It can also be used as a model for finding and predicting seizures in the real world.