bluuebunny/crossref_metadata_2025_split huggingface dataset:
CCQM-P123 number and geometric property of cells adhered to a solid substrate
Authors: Divieto C , Revel L , Pennecchi F , Pavarelli S , Zucco M , Menezes G , Barrias E , Leve F , Lee J Y , Choi J-H , Ellison S L R , Woolford A , Lekishvili T , Pang S , Morley G , Davies J , Campbell J , Braybrook J , Yingying L , Prawettongsopon C , Halter M , Elliot J T , Kummrow A , Runov A L , Naschekina Y , Yudintseva N , Vonsky M S 
Published: January 2025

Main text
Several scientific fields, such as cytology, biochemistry, molecular biology and genetics have cells as their direct topic of study. The cell is a fundamental unit of highly technological systems, employed, for example, in the development of new chemicals and drugs, in the evaluation of compound toxicity, in novel approaches to health, such as regenerative medicine. High content screening technologies are cellular imaging-based assays. In this framework, cell density, cell confluency and cell size are measurands that can describe a biological effect of a molecule under examination. The CCQM-P123 study aimed to demonstrate capability of participants in quantifying 4 measurands using one reference material: number of adherent cells on a planar surface, cell density in the range 0 to 5000 cells/mm2, cell confluency in the range 0 % to 100 % and average cell area. Nine Institutions participated in the study. Reference materials for three levels of cell density and cell confluency were prepared for fluorescence microscopy and circulated among participants. Each reference material was a commercial imaging dish having 400 squares and seeded with human cells, fixed and stained for nucleus and for whole cell. On each dish 4 squares were selected for the analysis as "measurement standards". The use of a calibrated ruler to define the area of measurement assured the traceability to the International System of Units (SI). Results for the 4 measurands showed an overall good agreement between the laboratories. The study allowed fundamental considerations in the frame of a cell-based measurement comparison, in terms of: traceability, comparability of results and complexity of the study protocol. The study has been a preparatory exercise for a key comparison on at least one of the 3 measurements claims (cell density, cell confluency and cell area) related to adhered cells features such as cell proliferation, morphology and size.
To reach the main text of this paper, click on Final Report.
The final report has been peer-reviewed and approved for publication by the CCQM.
Temperature and strain-dependent band bowing effect in Ge1-xSnx alloys
Authors: Wu Songsong , Huang Shihao , Qian Jinghui , Huang Wei , Lin Guangyang , Cheng Songyan , Li Cheng 
Published: January 2025

Abstract
Band-gap-tunable Ge1-x
Sn
x
alloys are one of the most promising materials in silicon photonics. While many studies have focused on the band structure of Ge1-x
Sn
x
alloys, the band bowing effect significantly affects the conversion of Ge1-x
Sn
x
alloys into direct band gap material, which has not been thoroughly researched yet. This work theoretically reports the band bowing effect on Ge1-x
Sn
x
alloys under strain at various temperatures based on 30- band k·p method. Results indicate that band bowing parameters of both Γ-valley and L-valley are reduced by increasing temperature. However, the difference between direct and indirect band gap bowing parameters of Ge1-x
Sn
x
increases with temperature, resulting in a reduction of the critical Sn composition in the direct band gap transition. For the case of biaxial (001)- and uniaxial [001]-strained Ge1-x
Sn
x
alloys, the difference between direct and indirect band gap bowing parameters is increased, which also reduces the Sn composition for Ge1-x
Sn
x
alloys to be direct band gap transition. This work offers a path to find a proper balance between Sn composition, temperature, and strain for the design of Ge1-x
Sn
x
-based optoelectronic devices.
Comment on ‘Klein–Gordon particles in a quasi-pointlike global monopole spacetime and a Wu-Yang magnetic monopole: invariance and isospectrality’
Authors: Fernández Francisco M 
Published: January 2025

Abstract
We analyse a procedure proposed recently for the solution of the radial eigenvalue equation for a shifted harmonic oscillator. We show that the author modified the boundary condition at origin and, consequently, solved a completely different problem. His energies do not depend on one of the model parameters, while the Hellmann–Feynman theorem shows such dependence clearly. It is also shown that the author’s own equations are inconsistent.
High-accuracy iterative 6DoF pose tracking for large-size cabin assembly
Authors: Shen Chentao , Jiang Haolai , Liu Houde , Chen Yihui , He Zaixing , Zhao Xinyue 
Published: January 2025

Abstract
Large-size cabin assembly is a challenging and labor-intensive task, while visual pose estimation of the cabin could enhance its efficiency and precision. The existing frameworks are mainly based on ellipse detection and projection calculation, leading to a limitation of accuracy and generalization. In this paper, we introduce a novel framework for pose tracking of large-size cabins based on iterative optimization of manipulation points to reduce the impact caused by 6DoF pose coupling, where four manipulation points iteratively transform the docking surface contour and align it with captured image. The method is applicable to arbitrary shapes of cabin docking surface and also extended to multiple perspectives. Both actual cabin assembly experiments and simulation experiments are performed, the results demonstrate that the proposed method is more accurate and robust than conventional methods.
A hybrid-driven soft sensor model with symbolic representation for enhanced self-interpretability
Authors: Wei Lingyun , Liu Han , Guo Runyuan , Wang Wenqing , Tian Xueqiong 
Published: January 2025

Abstract
Deep learning-based soft sensors often encounter the challenge of black-box problems, which lack interpretability and fail to provide intuitive mapping relationships. In complex industrial processes, physical sensors are susceptible to wear and tear, causing a divergence between test data distributions and training data, thus undermining sensing performance stability. To address these challenges, this paper proposes a hybrid-driven and self-interpretable soft sensor with symbolic representation, called the Kolmogorov–Arnold conditional autoencoder (KACAE). This framework employs symbolic representation to intuitively express the mapping relationships between variables, providing the model’s self-interpretability. It also incorporates domain knowledge to determine specific activation function types and simplify the network structure, achieving an effective balance between performance and computational complexity. Furthermore, an adaptive weighted mechanism is introduced to eliminate correlations between hidden features, enhancing model stability. Finally, the effectiveness, self-interpretability, and stability of the KACAE are validated through two industrial case studies.
Data-driven sensor selection for industrial gearbox fault diagnosis using principal component analysis
Authors: Goswami Priyom , Rai Rajiv Nandan 
Published: January 2025

Abstract
The failure of gearboxes, a critical component of mechanical power transmission systems, can significantly disrupt process cycle times and decrease production line throughput. Predicting failures in gear transmission systems is notably challenging due to their complex geometry and the interaction of simultaneous faults, which complicates fault isolation. Typically, multiple sensors are deployed at various locations to isolate and analyse faults in gearboxes. However, not all sensor data yield reliable results, making it crucial to select the most effective sensors. This study employs a principal component analysis-based approach to select the best sensor for fault detection. The results show an 18% increase in fault detection accuracy when using the most effective sensor. To validate the proposed approach, experiments were conducted under four gear conditions, considering different speeds, loads, fault severities, and fault types.
Development and investigation of novel negative stiffness metamaterial based on ring-shaped elastic deformation element
Authors: Patel Sandip T , Dave Harshit K 
Published: January 2025

Abstract
In the last few years, the concept of mechanical-type negative stiffness metamaterial (NSM) has gained greater attention and developed into an emergent field of research, partly due to advancements in additive manufacturing technologies that enable rapid fabrication of materials. In this work, a versatile bistable unit cell design is proposed, which exhibits large deformation. A theoretical model is developed and verified with experimental testing to accurately estimate the snap-through behaviour of the unit cell. The bulk of the theoretical model findings fall within a 10% range of the experimental results. This study demonstrates that the theoretical model proposed is accurate in its ability to predict the snap-through transition. Furthermore, a methodical parametric investigation is conducted into how geometric factors affect the snap-through characteristics. By adjusting the geometrical parameters of the unit cell, the required mechanical behaviour of the NSM may be tailored for specific applications. Finally, a 2D NSM lattice structure is developed, which exhibits multistability, tunable deformation, and a deterministic deformation sequence. These tunable behaviours can be controlled by setting proper values for geometrical parameters across the lattice. This study contributes to the design, development, and manufacture of tunable NSM and multistable structures.
High-reflective cylindrical-nanostructure multilayer mirrors for extreme ultraviolet radiation
Authors: Wang Chih-Chung , Lee Chao-Te , Chen Hung-Pin , Li Jia-Han 
Published: January 2025

Abstract
Extreme ultraviolet (EUV) is used in current semiconductor fabrication processes, and molybdenum (Mo) and silicon (Si) multilayers are often used for reflection mirrors. We propose hybrid structure multilayers that utilize cylindrical Mo and Si with vacuum space in each layer, and we call it cylindrical-nanostructure multilayer mirror which can be fabricated by current semiconductor processes. This practicality of our design is a crucial factor, as it leads to an increase in the refractive index and a decrease in the extinction coefficient in each layer, and it results in an enhancement of constructive interference within the multilayer stack. Based on the numerical simulation results using the finite-difference time-domain method, the reflectivity can be increased from 73–75% for a conventional 40-period Mo/Si multilayer to add more 2–3% for our proposed cylindrical-nanostructure multilayer mirror. As it often needs 8 to 12 reflection mirrors in EUV lithography, our proposed design can be used as high-reflectivity mirrors for EUV radiation and to increase the chip production under the same EUV light source.
Full Modeling and parameter compression methods in configuration space for DESI 2024 and beyond
Authors: Ramirez-Solano S. , Icaza-Lizaola M. , Noriega H.E. , Vargas-Magaña M. , Fromenteau S. , Aviles A. , Rodríguez-Martínez F. , Aguilar J. , Ahlen S. , Alves O. , Brieden S. , Brooks D. , Claybaugh T. , Cole S. , de la Macorra A. , Dey Arjun , Dey B. , Doel P. , Fanning K. , Forero-Romero J.E. , Gaztañaga E. , Gil-Marín H. , Gontcho S.Gontcho A. , Honscheid K. , Howlett C. , Juneau S. , Lai Y. , Landriau M. , Manera M. , Maus M. , Miquel R. , Mueller E. , Muñoz-Gutiérrez A. , Myers A.D. , Nadathur S. , Nie J. , Percival W.J. , Poppett C. , Rezaie M. , Rossi G. , Sanchez E. , Schlegel D. , Schubnell M. , Seo H. , Sprayberry D. , Tarlé G. , Verde L. , Weaver B.A. , Wechsler R.H. , Yuan S. , Zarrouk P. , Zou H. 
Published: January 2025

Abstract
In the contemporary era of high-precision spectroscopic surveys, led by projects like DESI, there is an increasing demand for optimizing the extraction of cosmological information from clustering data. This work conducts a thorough comparison of various methodologies for modeling the full shape of the two-point statistics in configuration space. We investigate the performance of both direct fits (Full Modeling) and the parameter compression approaches (ShapeFit and Standard). We utilize the ABACUS-SUMMIT simulations, tailored to exceed DESI's precision requirements. Particularly, we fit the two-point statistics of three distinct tracers (LRG, ELG, and QSO), by employing a Gaussian Streaming Model in tandem with Convolution Lagrangian Perturbation Theory and Effective Field Theory. We explore methodological setup variations, including the range of scales, the set of galaxy bias parameters, the inclusion of the hexadecapole, as well as model extensions encompassing varying ns
and allowing for w
0
w

a
CDM dark energy model. Throughout these varied explorations, while precision levels fluctuate and certain configurations exhibit tighter parameter constraints, our pipeline consistently recovers the parameter values of the mocks within 1σ in all cases for a 1-year DESI volume. Additionally, we compare the performance of configuration space analysis with its Fourier space counterpart using three models: PyBird, FOLPS and velocileptors, presented in companion papers. We find good agreement with the results from all these models.
Synthetic spectra for Lyman-α forest analysis in the Dark Energy Spectroscopic Instrument
Authors: Herrera-Alcantar Hiram K. , Muñoz-Gutiérrez Andrea , Tan Ting , González-Morales Alma X. , Font-Ribera Andreu , Guy Julien , Moustakas John , Kirkby David , Armengaud E. , Bault A. , Cabayol-Garcia L. , Chaves-Montero J. , Cuceu A. , de la Cruz R. , García L.Á. , Gordon C. , Iršič V. , Karaçaylı N.G. , Le Goff J.M. , Montero-Camacho P. , Niz G. , Pérez-Ràfols I. , Ramírez-Pérez C. , Ravoux C. , Walther M. , Aguilar J. , Ahlen S. , Brooks D. , Claybaugh T. , Dawson K. , de la Macorra A. , Doel P. , Forero-Romero J.E. , Gaztañaga E. , Gontcho S.Gontcho A. , Honscheid K. , Kehoe R. , Kisner T. , Landriau M. , Levi Michael E. , Manera M. , Martini P. , Meisner A. , Miquel R. , Nie J. , Palanque-Delabrouille N. , Poppett C. , Rezaie M. , Rossi G. , Sanchez E. , Seo H. , Tarlé G. , Weaver B.A. , Zhou Z. 
Published: January 2025

Abstract
Synthetic data sets are used in cosmology to test analysis procedures, to verify that systematic errors are well understood and to demonstrate that measurements are unbiased. In this work we describe the methods used to generate synthetic datasets of Lyman-α quasar spectra aimed for studies with the Dark Energy Spectroscopic Instrument (DESI). In particular, we focus on demonstrating that our simulations reproduces important features of real samples, making them suitable to test the analysis methods to be used in DESI and to place limits on systematic effects on measurements of Baryon Acoustic Oscillations (BAO).
We present a set of mocks that reproduce the statistical properties of the DESI early data set with good agreement. Additionally, we use a synthetic dataset to forecast the BAO scale constraining power of the completed DESI survey through the Lyman-α forest.
Forward modeling fluctuations in the DESI LRGs target sample using image simulations
Authors: Kong H. , Ross A.J. , Honscheid K. , Lang D. , Porredon A. , de Mattia A. , Rezaie M. , Zhou R. , Schlafly E.F. , Moustakas J. , Rosado-Marin A. , Aguilar J. , Ahlen S. , Brooks D. , Chaussidon E. , Claybaugh T. , Cole S. , de la Macorra A. , Dey Arjun , Dey Biprateep , Doel P. , Fanning K. , Forero-Romero J.E. , Gaztañaga E. , Gontcho S.Gontcho A. , Gutierrez G. , Howlett C. , Juneau S. , Kremin A. , Landriau M. , Levi M.E. , Manera M. , Martini P. , Meisner A. , Miquel R. , Mueller E. , Myers A.D. , Newman J.A. , Nie J. , Niz G. , Percival W.J. , Poppett C. , Prada F. , Rossi G. , Sanchez E. , Schlegel D. , Schubnell M. , Seo H. , Sprayberry D. , Tarlé G. , Vargas-Magaña M. , Weaver B.A. , Zou H. 
Published: January 2025

Abstract
We use
the forward modeling pipeline, Obiwan, to study the imaging systematics of
the Luminous Red Galaxies (LRGs) targeted by the Dark Energy Spectroscopic Instrument
(DESI). Imaging systematics refers to the false fluctuation of galaxy densities due to varying
observing conditions and astrophysical foregrounds corresponding to the imaging surveys from which
DESI LRG target galaxies are selected. We update the Obiwan pipeline, which we
previously developed to simulate the optical images used to target DESI data, to further simulate
WISE images in the infrared. This addition allows simulating the DESI LRGs sample, which
utilizes WISE data in the target selection. Deep DESI imaging data combined with a method to
account for biases in their shapes is used to define a truth sample of potential LRG targets. We
inject these data evenly throughout the DESI Legacy Imaging Survey footprint at declinations
between -30 and 32.375 degrees. We simulate a total of 15 million galaxies to obtain a simulated
LRG sample (Obiwan LRGs) that predicts the variations in target density due to imaging
properties. We find that the simulations predict the trends with depth observed in the data,
including how they depend on the intrinsic brightness of the galaxies. We observe that faint LRGs
are the main contributing source of the imaging systematics trend induced by depth. We also find
significant trends in the data against Galactic extinction that are not predicted by
Obiwan. These trends depend strongly on the particular map of Galactic extinction chosen
to test against, implying systematic contamination in the Galactic extinction maps is a likely
root cause (e.g., Cosmic-Infrared Background, dust temperature correction). We additionally
observe a morphological change of the DESI LRGs population evidenced by a correlation
between OII emission line average intensity and the size of the z-band PSF. This effect most
likely results from uncertainties in background subtraction. The detailed findings we present
should be used to guide any observational systematics mitigation treatment for the clustering of
the DESI LRGs sample.
How different immersive environments affect intracortical brain computer interfaces
Authors: Tortolani Ariana F , Kunigk Nicolas G , Sobinov Anton R , Boninger Michael L , Bensmaia Sliman J , Collinger Jennifer L , Hatsopoulos Nicholas G , Downey John E 
Published: January 2025

Abstract

Objective. As brain–computer interface (BCI) research advances, many new applications are being developed. Tasks can be performed in different virtual environments, and whether a BCI user can switch environments seamlessly will influence the ultimate utility of a clinical device. Approach. Here we investigate the importance of the immersiveness of the virtual environment used to train BCI decoders on the resulting decoder and its generalizability between environments. Two participants who had intracortical electrodes implanted in their precentral gyrus used a BCI to control a virtual arm, both viewed immersively through virtual reality goggles and at a distance on a flat television monitor. Main results. Each participant performed better with a decoder trained and tested in the environment they had used the most prior to the study, one for each environment type. The neural tuning to the desired movement was minimally influenced by the immersiveness of the environment. Finally, in further testing with one of the participants, we found that decoders trained in one environment generalized well to the other environment, but the order in which the environments were experienced within a session mattered. Significance. Overall, experience with an environment was more influential on performance than the immersiveness of the environment, but BCI performance generalized well after accounting for experience.
Clinical Trial: NCT01894802
Bayes-optimal learning of deep random networks of extensive-width*
Authors: Cui Hugo , Krzakala Florent , Zdeborová Lenka 
Published: January 2025

Abstract
We consider the problem of learning a target function corresponding to a deep, extensive-width, non-linear neural network with random Gaussian weights. We consider the asymptotic limit where the number of samples, the input dimension and the network width are proportionally large. We propose a closed-form expression for the Bayes-optimal test error, for regression and classification tasks. We further compute closed-form expressions for the test errors of ridge regression, kernel and random features regression. We find, in particular, that optimally regularized ridge regression, as well as kernel regression, achieve Bayes-optimal performances, while the logistic loss yields a near-optimal test error for classification. We further show numerically that when the number of samples grows faster than the dimension, ridge and kernel methods become suboptimal, while neural networks achieve test error close to zero from quadratically many samples.
Breaking the wire: the impact of critical length on melting pathways in silver nanowires
Authors: Ridings K M , Vaka’uta E E L , Croot S M 
Published: January 2025

Abstract
We explore the melting mechanisms of silver nanowires through molecular dynamics simulations and theoretical modelling, where we observe that two distinct mechanisms or pathways emerge that dictate how the solid-liquid interface melts during the phase transition. For wires longer than a critical length (L > L
crit), an Arrhenius-type diffusion model successfully predicts the solid-liquid interface velocity, highlighting diffusion-driven melting pathways. In contrast, wires shorter than the critical length (L ≤ L
crit) exhibit unique behaviours driven by non-equilibrium effects, including rapid overheating of the solid core, stabilization of the solid-liquid interface, and the pronounced impact of higher energy densities. These mechanisms lead to accelerated melting and distinct phase transition dynamics. Our findings reveal how geometry and nanoscale effects critically shape melting behaviour, offering insights for the design and stability of nanostructures in advanced applications.
Niobium-buffered tantalum for a superconducting fluxonium qubit
Authors: Li Zi shuo , Guo Ting ting , Xu Wen qu , Shi Li li , Zhang Kai xuan , Zuo Quan , Zhou Tian shi , Sun Guo zhu , Wu Pei heng 
Published: January 2025

Abstract
We use a magnetron sputtering system to grow a tantalum film on a sapphire substrate with a niobium buffer layer at room temperature. The tantalum film is in α-phase, which is preferred for superconducting quantum devices. We fabricate a superconducting heavy fluxonium qubit with this niobium-buffered tantalum film, which demonstrates good performance. Forbidden transitions and sideband transition phenomena between specific energy levels are observed. Due to the specific design parameters, the fluxonium described herein exhibits high anharmonicity while maintaining a long decoherence time in the higher energy states, making it well-suited for use as a qudit and enabling high-dimensional quantum computation. With further optimization of the film deposition process, superconducting qubits other than fluxoniums with higher performance are expected to be obtained using these multilayer films grown at room temperature.