bluuebunny/crossref_metadata_2025_split huggingface dataset:
Large-angle analytical solution of magnetization precession in ferromagnetic resonance
Authors: Jia Zhen-Lin , Wang Shu-Chen , Li Tong , Jin Xiao-Wei , Xue De-Sheng 
Published: September 2024

Abstract
Dynamics of magnetization M driven by microwave are derived analytically from the nonlinear Landau–Lifshitz–Gilbert equation. Analytical M and susceptibility are obtained self-consistently under a positive circularly polarized microwave field,

h

=

(
h
cos
⁡
ω
t
,
h
sin
⁡
ω
t
,
0
)

, with frequency

ω

, which is perpendicular to a static field,

H

=

(
0
,
0
,
H
)

. It is found that the orbital of M is always a cone along H. However, with increasing h the polar angle

θ

of M initially increases, then keeps 90° when

h

⩾

h

0

=
α
ω

/

γ

in ferromagnetic resonance (FMR) mode, where

α

is Gilbert damping constant and

γ

is gyromagnetic ratio. These effects result in a nonlinear variation of FMR signal as h increases to

h
⩾

h

0

, where the maximum of resonance peak decreases from a steady value, linewidth increases from a decreasing trend. These analytical solutions provide a complete picture of the dynamics of M with different h and H.
Space-time structures, light trajectories and shadows for Kerr-Newman-AdS black hole with surrounding perfect fluid matter in Rastall gravity
Authors: Ma Ju , Wang Jian-cheng , Qin Long-hua , Gao Quan-gui 
Published: September 2024

Abstract
We present the horizon structures and the shadows for Kerr-Newman-AdS black hole located in perfect fluid matter field in Rastall gravity. By considering the Hamilton-Jacobi equation and Carter constant separable method, we obtain the null geodesic equations of the black hole space-time as well as the unstable circular photon orbits in terms of the impact parameters. The horizon structures of the space-time are calculated numerically. The results show that there are four roots for a general case of the horizon equation (the Cauchy horizon

r

−

h

, the event horizon

r

+

h

, the cosmological horizon r

q
of Rastall gravity and the cosmological horizon r

c
of cosmological constant), which lead to a specific characteristic with the subregions of the space-time. The influences of the cosmological horizons r

q
and r

c
on the light trajectories around the black hole are also investigated. Furthermore, we study the effects of the parameters, including the perfect fluid matter intensity N

s
, the Rastall parameter k
λ, the cosmological constant Λ, the black hole spin a and the black hole charge Q on black hole shadows in detail.
Radiation shielding properties of gold nanoparticle-dispersed bismuth borate glasses using Phy-X/PSD software
Authors: Abhishek  , Mahendru Nancy , Gupta Indu , Bansal Naveen , Singla Shivani 
Published: September 2024

Abstract
With the increasing use of radioactive materials in various sectors, effective radiation shielding has become a critical concern. The present study explores the potential of bismuth borate glasses doped with gold nanoparticles for gamma-ray shielding applications. Glass samples with a base composition of 30Bi2O3:70B2O3, containing varying concentrations of 10 nm gold nanoparticles, were synthesized using the melt quenching technique. The physical and morphological properties of the samples were characterized, confirming the presence of uniformly dispersed gold nanoparticles of size (4 nm) smaller than the size of precursor nanoparticles. Shielding parameters, including mass attenuation coefficient (MAC), half value layer (HVL), ten value layer (TVL), mean free path (MFP), and effective atomic number (Zeff), were analyzed using the Phy-X/PSD program. Results showed that the obtained highest MAC value is 155.864 cm2/g which is superior to other reported materials. The HVL and TVL values increased with the increase in energy range, indicating effective gamma-ray shielding potential. These findings suggest that optimizing the dispersion and concentration of gold nanoparticles in bismuth borate glasses could enhance their performance as radiation shielding materials, making them promising candidates for various applications.
Gamma rays from dark matter spikes in EAGLE simulations
Authors: Aschersleben J. , Bertone G. , Horns D. , Moulin E. , Peletier R.F. , Vecchi M. 
Published: September 2024

Abstract
Intermediate Mass Black Holes (IMBHs) with a mass range between 100 M⊙ and 106 M⊙ are expected to be surrounded by high dark matter densities, so-called dark matter spikes.
The high density of self-annihilating Weakly Interacting Massive Particles (WIMPs) in these spikes leads to copious gamma-ray production. Sufficiently nearby IMBHs could therefore appear as unidentified gamma-ray sources.
However, the number of IMBHs and their distribution within our own Milky Way is currently unknown. In this work, we provide a mock catalogue of IMBHs and their dark matter spikes obtained from the EAGLE simulations, in which black holes with a mass of 105 M⊙/h are seeded into the centre of halos greater than 1010 M⊙/h to model black hole feedback influencing the formation of galaxies.
The catalogue contains the coordinates and dark matter spike parameters for about 2500 IMBHs present in about 150 Milky Way-like galaxies. We expect about 15+9
-6 IMBHs within our own galaxy, mainly distributed in the Galactic Centre and the Galactic Plane. In the most optimistic scenario, we find that current and future gamma-ray observatories, such as Fermi-LAT, H.E.S.S. and CTAO, would be sensitive enough to probe the cross section of dark matter self-annihilation around IMBHs down to many orders of magnitude below the thermal relic cross section for dark matter particles with masses from GeV to TeV.
We have made the IMBH mock catalogue and the source code for our analysis publicly available, providing the resources to study dark matter self-annihilation around IMBHs with current and upcoming gamma-ray observatories.
Gauss-Bonnet Cosmology: large-temperature behaviour and bounds from Gravitational Waves
Authors: Biswas Anirban , Kar Arpan , Lee Bum-Hoon , Lee Hocheol , Lee Wonwoo , Scopel Stefano , Velasco-Sevilla Liliana , Yin Lu 
Published: September 2024

Abstract
We provide a transparent discussion of the high temperature asymptotic behaviour of Cosmology in a dilaton-Einstein-Gauss-Bonnet (dEGB) scenario of modified gravity with vanishing scalar potential. In particular, we show that it has a clear interpretation in terms of only three attractors (stable critical points) of a set of autonomous differential equations: w = -1/3, w = 1 and 1 < w < 7/3, where w ≡ p/ρ is the equation of state, defined as the ratio of the total pressure and the total energy density. All the possible different high-temperature evolution histories of the model are exhausted by only eight paths in the flow of the set of the autonomous differential equations. Our discussion clearly explains why five out of them are characterized by a swift transition of the system toward the attractor, while the remaining three show a more convoluted evolution, where the system follows a meta-stable equation of state at intermediate temperatures before eventually jumping to the real attractor at higher temperatures. Compared to standard Cosmology, the regions of the dEGB parameter space with w = -1/3 show a strong enhancement of the expected Gravitational Wave stochastic background produced by the primordial plasma of relativistic particles of the Standard Model. This is due to the very peculiar fact that dEGB allows to have an epoch when the energy density ρ
rad of the relativistic plasma dominates the energy of the Universe while at the same time the rate of dilution with T of the total energy density is slower than what usually expected during radiation dominance. This allows to use the bound from Big Bang Nucleosynthesis (BBN) to put in dEGB a constraint T
RH ≲ (108 – 109) GeV on the reheating temperature of the Universe T
RH. Such BBN bound is complementary to late-time constraints from compact binary mergers.
The Simons Observatory: impact of bandpass, polarization angle and calibration uncertainties on small-scale power spectrum analysis
Authors: Giardiello S. , Gerbino M. , Pagano L. , Alonso D. , Beringue B. , Bolliet B. , Calabrese E. , Coppi G. , Errard J. , Fabbian G. , Harrison I. , Hill J.C. , Jense H.T. , Keating B. , La Posta A. , Lattanzi M. , Lonappan A.I. , Puglisi G. , Reichardt C.L. , Simon S.M. 
Published: September 2024

Abstract
We study the effects due to mismatches in passbands, polarization angles, and temperature and polarization calibrations in the context of the upcoming cosmic microwave background experiment Simons Observatory (SO). Using the SO multi-frequency likelihood, we estimate the bias and the degradation of constraining power in cosmological and astrophysical foreground parameters assuming different levels of knowledge of the instrumental effects. We find that incorrect but reasonable assumptions about the values of
all the systematics examined here can have significant effects on cosmological
analyses, hence requiring marginalization approaches at the likelihood level.
When doing so, we find that the most relevant effect is due to bandpass shifts. When marginalizing over them, the posteriors of parameters describing astrophysical microwave foregrounds (such as radio point sources or dust) get degraded, while cosmological parameters constraints are not significantly affected.
Marginalization over polarization angles with up to 0.25° uncertainty causes an irrelevant bias ≲ 0.05 σ in all parameters.
Marginalization over calibration factors in polarization broadens the constraints on the effective number of relativistic degrees of freedom Neff by a factor 1.2, interpreted here as a proxy parameter for non standard model physics targeted by high-resolution CMB measurements.
PINN for solving forward and inverse problems involving integrable two-dimensional nonlocal equations
Authors: Chen Xi , Peng Wei-Qi 
Published: September 2024

Abstract
In this paper, the physics informed neural network (PINN) deep learning method is applied to solve two-dimensional nonlocal equations, including the partial reverse space y-nonlocal Mel’nikov equation, the partial reverse space-time nonlocal Mel’nikov equation and the nonlocal two-dimensional nonlinear Schrödinger (NLS) equation. By the PINN method, we successfully derive a data-driven two soliton solution, lump solution and rogue wave solution. Numerical simulation results indicate that the error range between the data-driven solution and the exact solution is relatively small, which verifies the effectiveness of the PINN deep learning method for solving high dimensional nonlocal equations. Moreover, the parameter discovery of the partial reverse space-time nonlocal Mel’nikov equation is analysed in terms of its soliton solution for the first time.
A robust time scale for space applications using the student’s t-distribution
Authors: McPhee Hamish , Tourneret Jean-Yves , Valat David , Delporte Jérôme , Grégoire Yoan , Paimblanc Philippe 
Published: September 2024

Abstract
In this article, the principles of robust estimation are applied to the standard basic time scale equation to obtain a new method of assigning weights to clocks. Specifically, the Student’s t-distribution is introduced as a new statistical model for an ensemble of clocks that are experiencing phase jumps, frequency jumps or anomalies in their measurement links. The proposed robust time scale is designed to mitigate the effects of these anomalies without necessarily identifying them, but through applying a method of robust estimation for the parameters of a Student’s t-distribution. The proposed time scale algorithm using the Student’s t-distribution (ATST) is shown to achieve comparable robustness to phase jumps, frequency jumps, and anomalies in the measurements with respect to the AT1 oracle time scale. The AT1 oracle is a special realization of the AT1 time scale which corrects all anomalies by having prior knowledge of their occurrences. The similar performance of ATST and AT1 oracle suggests that the ATST algorithm is efficient for obtaining robustness with no prior knowledge or detection of the occurrences of anomalies.
Time division interferometer setups
Authors: Fernandez-Guasti M 
Published: September 2024

Abstract
A time division interferometer (TDI) in the optical regime is presented, where a wavetrain is temporally split into two distinct parts that are superimposed at a subsequent stage. At any one time, the photons have no alternatives, only one possible path is possible. There is no path bifurcation in the setup, i.e. no ‘Y’ where the photons can take left or right. The photons choice, if any, is to arrive/collapse before or after the time t
1 when the time modulated medium changes its state. In time-varying media, as energy can be exchanged between the wave and medium, the wave frequency is modified. Thus, the diverted photons become doubly tagged, in their wave vector direction as well as their frequency. A streak camera detector array resolves both, the fringe pattern as well as the frequency beats, in a space versus time interferogram. This apparatus has

0.66

ns

temporal resolution and

70

μ
m

spatial resolution. Several TDI configurations are described, two of them are implemented: a spatio-temporal interferometer where the ‘which path’ criterion is readily observed and an all temporal TDI where only temporal interference is present. Novel possibilities of TDI schemes are discussed.
Investigation of machining performance of waspaloy using copper-graphite composite electrodes in electric discharge machining
Authors: Putta Priyanka , V Jayakumar , PK Giridharan 
Published: September 2024

Abstract
This study endeavoured to investigate the machining of Waspaloy using Electric Discharge Machining (EDM), utilizing copper-graphite composites as the tool material. Given the limited existing research on machining Waspaloy with composite tools, this study aims to address this gap by employing a copper-graphite composite tool. In this work, pure copper electrode and three composite electrodes with varying graphite percentages in copper, viz. copper containing 5%, 10%, and 15% graphite (CuGr-5, CuGr-10, and CuGr-15), are utilized for experimentation. Composite electrodes are fabricated by the stir-casting process. The scanning electron microscope reveals that the graphite specks are homogeneously disseminated over the matrix material. The Taguchi mixed orthogonal array was used for developing experimental runs. By varying the current, polarity, pulse on and off times, tool materials, and gap, machining performance was measured in terms of Material Removal Rate (MRR), Tool Wear Rate (TWR), and Surface Roughness (Ra). It was observed that CuGr-5 provides an enhancement in MRR due to the improved electric conductivity, bridging effect, and increased energy concentration at the spark gap. Diverse characteristics witnessed on the surface morphology include black dots, globules, remelted layers, micro-cracks, and scratches. When machined with a CuGr5 electrode, the surface quality improved owing to the completed flushing and uniform distribution of generated heat as confirmed through worn surface morphology. The parameters were optimized utilizing the PROMETHEE optimization technique; it was found that the CuGr-5 electrode with the assessment value 0.02458 was optimal for machining of Waspaloy.
Defect prediction and performance optimization of A413 vertical centrifugal castings through FEA-based simulation
Authors: Mazloum Kamar , Al Njjar Ameen , Sata Amit 
Published: September 2024

Abstract
This study benefits from advanced simulation based on finite element analysis, where finite element analysis possesses robust numerical algorithms to confront critical industrial challenges, including prediction and optimization techniques. The primary goal is to predict the location and quantity of shrinkage porosity and air entrainment, and to mitigate them by optimizing key casting process factors while considering the geometric effects. Virtual experiments designed through the Taguchi method, with three parameters (aspect ratio, pouring temperature, and mold rotation speed) at five levels each, were conducted using the finite element analysis software ProCAST. Post-experimentation, comprehensive data analyses, including signal-to-noise ratio and response surface methods, were employed to determine optimal conditions. Additionally, a sophisticated regression model was developed to clarify the complex relationship between key parameters and defect aspects. Optimal conditions to reduce shrinkage porosity were identified within parameter ranges of (50–75) rpm, (750–800) °C, and (1.75–2) aspect ratio. Similarly, optimal parameters to reduce air entrainment were identified as 150 rpm, 800 °C, and (1) aspect ratio.
Effects of an Intervention on Black Family Incomes on Self-Rated Health and Obesity in Black and White Adolescents and Young Adults
Authors: Polos Jessica , Alexandria Shaina , Hargrove Taylor , Koning Stephanie , McDade Thomas W , Kershaw Kiarri N 
Published: September 2024

Abstract
Structural racism contributes to health disparities between U.S. non-Hispanic Black and non-Hispanic white populations by differentially distributing resources used to maintain health. Policies that equitably redistribute resources may mitigate racialized health disparities. Using National Longitudinal Study of Adolescent to Adult Health data and time-to-event parametric g-formula methods, we investigate a hypothetical intervention to reduce Black-white family income inequities on racialized differences in self-rated health (N=11,312) and obesity (N=10,547). We first intervene to increase individual Black family incomes by $11,000, creating Black-white equity in median incomes in 1995. Then, we measure social multiplier effects by additionally increasing county-level Black median household incomes by $11,000. By Wave 4, individual, direct effects models comparing Black intervention to Black control groups show no risk differences in self-rated health (RD=-0.009; 95% CI: -0.026, 0.008) or obesity (RD=0.003; 95% CI: -0.017, 0.023). Social multiplier effects models suggestively reduce Black-white inequalities in obesity by increasing obesity in white intervention versus white control groups (RD=0.050=; 95% CI: -0.011, 0.110), but exacerbate Black-white disparities in self-rated health by reducing self-rated health in Black intervention versus white control groups (RD=0.184; 95% CI: 0.018, 0.351). In this cohort, income transfers may not reduce racialized disparities in obesity and self-rated health.
Can algorithms Replace Expert Knowledge for Causal Inference? A Case Study on Novice Use of Causal Discovery
Authors: Gururaghavendran Rajesh , Murray Eleanor J 
Published: September 2024

Abstract

Background
With growing interest in causal inference and machine learning among epidemiologists, there is increasing discussion of causal discovery algorithms for guiding covariate selection. We present a case study of novice application of causal discovery tools and attempt to validate the results against a well-established causal relationship.

Methods
As a case study, we attempted causal discovery of relationships relevant to the effect of adherence on mortality in the placebo arm of the Coronary Drug Project (CDP) dataset. We used four algorithms available as existing software implementations and varied several model inputs.

Results
We identified 15 adjustment sets from 17 model parameterizations. When applied to a baseline covariate adjustment analysis, these 15 adjustment sets returned effect estimates with similar magnitude and direction of bias as prior published results. When using methods to control for time-varying confounding, there was generally more residual bias than compared to expert-selected adjustment sets.

Conclusion
Although causal discovery algorithms can perform on par with expert knowledge, we do not recommend novice use of causal discovery without the input of experts in causal discovery. Expert support is recommended to aid in choosing the algorithm, selecting input parameters, assessing underlying assumptions, and finalizing selection of the adjustment variables.
The role of imagination in making water from moon rocks: How scientists use imagination to break constraints on imagination
Authors: Stuart Michael T , Sargeant Hannah 
Published: September 2024

Abstract
Scientists recognize the necessity of imagination for solving tough problems. But how does the cognitive faculty responsible for daydreaming also help in solving scientific problems? Philosophers claim that imagination is informative only when it is constrained to be maximally realistic. However, using a case study from space science, we show that scientists use imagination intentionally to break reality-oriented constraints. To do this well, they first target low-confidence constraints, and then progressively higher-confidence constraints until a plausible solution is found. This paper exemplifies a new approach to epistemology of imagination that focuses on sets of imaginings (rather than individual imaginings), and responsible (rather than reliable) imaginings.
SnapHiC-G: identifying long-range enhancer–promoter interactions from single-cell Hi-C data via a global background model
Authors: Liu Weifang , Zhong Wujuan , Giusti-Rodríguez Paola , Jiang Zhiyun , Wang Geoffery W , Sun Huaigu , Hu Ming , Li Yun 
Published: September 2024

Abstract
Harnessing the power of single-cell genomics technologies, single-cell Hi-C (scHi-C) and its derived technologies provide powerful tools to measure spatial proximity between regulatory elements and their target genes in individual cells. Using a global background model, we propose SnapHiC-G, a computational method, to identify long-range enhancer–promoter interactions from scHi-C data. We applied SnapHiC-G to scHi-C datasets generated from mouse embryonic stem cells and human brain cortical cells. SnapHiC-G achieved high sensitivity in identifying long-range enhancer–promoter interactions. Moreover, SnapHiC-G can identify putative target genes for noncoding genome-wide association study (GWAS) variants, and the genetic heritability of neuropsychiatric diseases is enriched for single-nucleotide polymorphisms (SNPs) within SnapHiC-G-identified interactions in a cell-type-specific manner. In sum, SnapHiC-G is a powerful tool for characterizing cell-type-specific enhancer–promoter interactions from complex tissues and can facilitate the discovery of chromatin interactions important for gene regulation in biologically relevant cell types.
Large language model produces high accurate diagnosis of cancer from end-motif profiles of cell-free DNA
Authors: Liu Jilei , Shen Hongru , Chen Kexin , Li Xiangchun 
Published: September 2024

Abstract
Instruction-tuned large language models (LLMs) demonstrate exceptional ability to align with human intentions. We present an LLM-based model—instruction-tuned LLM for assessment of cancer (iLLMAC)—that can detect cancer using cell-free deoxyribonucleic acid (cfDNA) end-motif profiles. Developed on plasma cfDNA sequencing data from 1135 cancer patients and 1106 controls across three datasets, iLLMAC achieved area under the receiver operating curve (AUROC) of 0.866 [95% confidence interval (CI), 0.773–0.959] for cancer diagnosis and 0.924 (95% CI, 0.841–1.0) for hepatocellular carcinoma (HCC) detection using 16 end-motifs. Performance increased with more motifs, reaching 0.886 (95% CI, 0.794–0.977) and 0.956 (95% CI, 0.89–1.0) for cancer diagnosis and HCC detection, respectively, with 64 end-motifs. On an external-testing set, iLLMAC achieved AUROC of 0.912 (95% CI, 0.849–0.976) for cancer diagnosis and 0.938 (95% CI, 0.885–0.992) for HCC detection with 64 end-motifs, significantly outperforming benchmarked methods. Furthermore, iLLMAC achieved high classification performance on datasets with bisulfite and 5-hydroxymethylcytosine sequencing. Our study highlights the effectiveness of LLM-based instruction-tuning for cfDNA-based cancer detection.