bluuebunny/crossref_metadata_2025_split huggingface dataset:
A novel dielectric elastomer with low modulus and fast response
Authors: Wang Qinqin , Shuai Changgeng , Yang Xue , Wu Weibin , Lu Gang 
Published: January 2025

Abstract
Dielectric elastomers (DEs) are highly valued in massive fields of actuators and sensors due to their unique advantages of large actuation strain, fast response speed, high energy density and excellent elasticity. The challenge of balancing the elastic modulus, actuation strain and response speed of DE actuators to stably enhance the actuation performance remains a major issue. In this work, a novel DE was prepared by employing polyurethane acrylate (CN9021) as a crosslinker, n-butyl acrylate as a base monomer and 2-ethylhexyl acrylate (2-EHA) as a functional flexible monomer via a UV curing method. The swelling test indicates a reduction of crosslinking density with the increment of 2-EHA concentration in EHA films. As a consequence, the elastic modulus displays a notable decline while the dielectric constant slightly rises, leading to an enhancement of the actuation sensitivity. More specifically, the elastic modulus of our fabricated EHA-1 is only one-third of the commercial VHB-4910. The developed DEs achieve an actuation strain of nearly 150% with low viscoelasticity and mechanical loss resulting in high response speed and broad operating frequency range to the input dynamic voltages. All these actuation performances are superior to VHB-4910. This work provides a promising strategy for developing DEs with balanced performance and superior actuation characteristics.
Testing the robustness of the BAO determination in the presence of massive neutrinos
Authors: Nadal-Matosas Adriana , Gil-Marín Héctor , Verde Licia 
Published: January 2025

Abstract
We study the robustness of the Baryon Acoustic Oscillation (BAO) feature in the large-scale structure in the presence of massive neutrinos. In the standard BAO analysis pipeline a reference cosmological model is assumed to boost the BAO peak through the so-called reconstruction technique and in the modelling of the BAO feature to extract the cosmological information. State-of-the art spectroscopic BAO measurements, such as the Dark Energy Spectroscopic Instrument claim an aggregate precision of 0.52% on the BAO scale, with a systematic error of 0.1% associated to the assumption of a reference cosmology when measuring and analyzing the BAO feature. While the systematic effect induced by this arbitrary choice of fiducial cosmology has been studied for a wide range of ΛCDM-like models, it has not yet been tested for reference cosmologies with massive neutrinos with the precision afforded by next generation surveys. In this context, we employ the Quijote high-resolution dark-matter simulations with haloes above a mass of M ∼ 2×1013
h
-1
M
⊙, with different values for the total sum of neutrinos masses, ∑mν
[eV] = 0, 0.1, 0,2, 0.4 to study and quantify the impact of the pipeline's built-in assumption of massless neutrinos on the measurement of the BAO signal, with a special focus on the BAO reconstruction technique. We determine that any additional systematic bias introduced by the assumption of massless neutrinos is no greater than 0.1% (0.2%) for the isotropic (anisotropic) measurement. We expect these conclusions also hold for galaxies provided that neutrino properties do not alter the galaxy-halo connection.
Modified Masses and Parallaxes of the Close Visual Triple System HD 2893
Authors: Masda Suhail , Al-Wardat Mashhoor , Aljboor Hussam , Benchi L. R. , Yassin Mariam I. , Aldywailah Reem , Pramod Punnya 
Published: January 2025

Abstract
We present the essential stellar parameters of the close visual triple system HD 2893 using Al-Wardat's method for analyzing binary and multiple star systems in conjunction with Kurucz's model atmospheres. This method accurately computes the spectrophotometric stellar masses through a combined synthetic spectral energy distribution approach that compares the results with observed data. The vigorous approach uses spectroscopic, photometric, and dynamical analysis to yield precise results. The method implements Gaia DR3 measurements and other measurements like those of Hipparcos and 2MASS All-Sky Catalog as a guide for the best fit between the synthetic spectra and observed photometry. The analysis gives precise spectrophotometric stellar masses for the system being

M

Sph

A

=

1.20
±
0.07

M

⊙

,

M

Sph

B

=

1.09
±
0.06

M

⊙

, and

M

Sph

C

=

0.46
±
0.01

M

⊙

. It shows that the three components are main sequence stars with an estimated age of around 1.0 Gyr. When integrated with the dynamical analysis, a new dynamical parallax for the system is obtained, π
dyn = 13.8528 ± 0.20 mas. Additionally, the discussion covers the formation and evolution of the triple system.
Amorphization and siliconization of silicon carbide as a first wall material
Authors: De Aritra , Guterl Jerome , Bergstrom Zachary , Abrams Tyler , Sinclair Gregory , Elder John David , Rudakov Dmitry 
Published: January 2025

Abstract
The understanding and prediction of silicon carbide (SiC) material evolution exposed to SOL plasma conditions is of prime interest because SiC represents a promising main chamber wall plasma-facing material for next-step fusion devices (low hydrogenic diffusion, good mechanical and thermal properties under neutron irradiation). Gross and net Si erosion rates from SiC surfaces in contact with a well-diagnosed L-mode plasma in the DIII-D tokamak have been simulated and the surface concentrations of impurities have been tracked as a function of time. Coupled simulation of surface model and impurity transport demonstrates amorphization of crystalline SiC exposed to L-mode plasma due to the accumulation of displacement damages under ion irradiation. This affects the lifetime of SiC plasma facing components. Surface evolution is tightly coupled to impurity transport in the plasma and therefore needs to be integrated with impurity transport simulations to effectively predict Si erosion rates and sub-surface concentrations as a function of time. The simulation workflow couples a semi-analytical surface model to the impurity transport code GITR. The surface model is a homogeneous mixed-material model that tracks physical & chemical sputtering and reflection of impurities. Gross erosion is primarily influenced by the background plasma parameters and redeposition patterns are mainly influenced by the prompt redeposition due to the gyro-orbits of impurity ions. Although crystalline form of SiC is preferable for fusion wall applications because of resistance to neutron irradiation, this work indicates that crystalline SiC will undergo amorphization under D plasma contact with implications of higher sputtering and fuel retention. These results direct us to explore the effects of amorphization on crystalline SiC and further the physics basis of SiC usage as first wall material for fusion environments.
A construction of random bigraphs and their application to error correction codes*
Authors: Jadav Hareshkumar , Gupta Ashita , Singh Ranveer 
Published: January 2025

Abstract
Recently, it has been shown that almost every (c, d)-bigraph is ‘almost’ Ramanujan. Marcus, Spielman, and Srivastava also demonstrated the existence of infinite sequence of (c, d)-bigraphs that are Ramanujan for all

c
,
d
⩾
3

. In this article, we give a construction of an infinite sequence of random (c, d)-biregular graphs

G
k

,
k
=
1
,
2
,
…
,
∞

, where

G

k
+
1

can be constructed from Gk
in constant time. Experimental results show that they tend to be Ramanujan graphs in very few iterations. Additionally, we use this sequence of random (c, d)-biregular graphs as an error-correcting code proposed by Sipser and Spielman. Experimental results suggest that our graphs, when combined with a bit-flipping algorithm, can successfully correct a significant fraction of errors.
On-detector power distribution for CMS-HGCAL: a busbar-based approach
Authors: Antoszczuk P. , Noy M. , Caregari S. , Almeida J. , Schmidt I. ,   the CMS collaboration
Published: January 2025

Abstract
An on-detector power distribution scheme for the High Granularity Calorimeter (HGCAL) Phase-2 upgrade of CMS is under development. This scheme is based on a heavy-copper flexible printed circuit board (FPC), allowing for an efficient use of the tight integration space, with minimal insulation overhead, excellent electrical and thermal performance and simplified integration, when compared with a wired solution. This work introduces the technology, how it allows the HGCAL challenges to be overcome, and the characterization studies. Prototypes testing are presented to validate the concept and quantify the manufacturability, electrical performance, and safety of the proposed solution.
Development of a 10-bit ultra-low power SAR ADC with programmable threshold in 130 nm CMOS technology
Authors: Prus Patryk , Firlej Mirosław , Fiutowski Tomasz , Idzik Marek , Moroń Jakub , Świentek Krzysztof 
Published: January 2025

Abstract
The design and simulation results of an ultra-low power, fast 10-bit Successive Approximation Register (SAR) Analog-to-Digital Converter (ADC) in CMOS 130 nm technology are presented. This ADC is an extension of an experimentally verified 10-bit SAR ADC (INL, DNL < 0.5 LSB, ENOB > 9.5), working up to 50 MSps and consuming 680 μW at 40 MSps. The goal of the present work was to add a programmable threshold for the processed input signal, to stop the conversion and thus greatly reduce power consumption in case the signal is below the threshold. The new ADC works up to around 40 MSps and consumes around 350 μW at 40 MSps for low particle occupancy.
Advancement of 3D biofabrication in repairing and regeneration of cartilage defects
Authors: Zheng Zenghui , Yu Dongmei , Wang Haoyu , Wu Hao , Tang Zhen , Wu Qi , Cao Pengfei , Chen Zhiyuan , Huang Hai , Li Xiaokang , Liu Chaozong , Guo Zheng 
Published: January 2025

Abstract
Three-dimensional (3D) bioprinting, an additive manufacturing technology, fabricates biomimetic tissues that possess natural structure and function. It involves precise deposition of bioinks, including cells, and bioactive factors, on basis of computer-aided 3D models. Articular cartilage injuries, a common orthopedic issue. Current repair methods, for instance microfracture procedure (MF), autologous chondrocyte implantation (ACI), and osteochondral autologous transfer surgery have been applied in clinical practice. However, each procedure has inherent limitation. For instance, MF surgery associates with increased subchondral cyst formation and brittle subchondral bone. ACI procedure involves two surgeries, and associate with potential risks infection and delamination of the regenerated cartilage. In addition, chondrocyte implantation’s efficacy depends on the patient’s weight, joint pathology, gender-related histological changes of cartilage, and hormonal influences that affect treatment and prognosis. So far, it is a still a grand challenge for achieving a clinical satisfactory in repairing and regeneration of cartilage defects using conditional strategies. 3D biofabrication provide a potential to fabricate biomimetic articular cartilage construct that has shown promise in specific cartilage repair and regeneration of patients. This review reported the techniques of 3D bioprinting applied for cartilage repair, and analyzed their respective merits and demerits, and limitations in clinical application. A summary of commonly used bioinks has been provided, along with an outlook on the challenges and prospects faced by 3D bioprinting in the application of cartilage tissue repair. It provided an overall review of current development and promising application of 3D biofabrication technology in articular cartilage repair.
New era towards autonomous additive manufacturing: a review of recent trends and future perspectives
Authors: Fan Haolin , Liu Chenshu , Bian Shijie , Ma Changyu , Huang Junlin , Liu Xuan , Doyle Marshall , Lu Thomas , Chow Edward , Chen Lianyi , Fuh Jerry Ying Hsi , Lu Wen Feng , Li Bingbing 
Published: January 2025

Abstract
The additive manufacturing (AM) landscape has significantly transformed in alignment with Industry 4.0 principles, primarily driven by the integration of artificial intelligence (AI) and digital twins (DT). However, current intelligent AM (IAM) systems face limitations such as fragmented AI tool usage and suboptimal human-machine interaction. This paper reviews existing IAM solutions, emphasizing control, monitoring, process autonomy, and end-to-end integration, and identifies key limitations, such as the absence of a high-level controller for global decision-making. To address these gaps, we propose a transition from IAM to autonomous AM, featuring a hierarchical framework with four integrated layers: knowledge, generative solution, operational, and cognitive. In the cognitive layer, AI agents notably enable machines to independently observe, analyze, plan, and execute operations that traditionally require human intervention. These capabilities streamline production processes and expand the possibilities for innovation, particularly in sectors like in-space manufacturing. Additionally, this paper discusses the role of AI in self-optimization and lifelong learning, positing that the future of AM will be characterized by a symbiotic relationship between human expertise and advanced autonomy, fostering a more adaptive, resilient manufacturing ecosystem.
Deep(er) reconstruction of imaging Cherenkov detectors with swin transformers and normalizing flow models
Authors: Fanelli C , Giroux J , Stevens J 
Published: January 2025

Abstract
Imaging Cherenkov detectors are crucial for particle identification (PID) in nuclear and particle physics experiments. Fast reconstruction algorithms are essential for near real-time alignment, calibration, data quality control, and efficient analysis. At the future electron–ion collider (EIC), the ePIC detector will feature a dual Ring Imaging Cherenkov (RICH) detector in the hadron direction, a Detector of Internally Reflected Cherenkov (DIRC) in the barrel, and a proximity focus RICH in the electron direction. This paper focuses on the DIRC detector, which presents complex hit patterns and is also used for PID of pions and kaons in the experiment at JLab. We present Deep(er)RICH, an extension of the seminal DeepRICH work, offering improved and faster PID compared to traditional methods and, for the first time, fast and accurate simulation. This advancement addresses a major bottleneck in Cherenkov detector simulations involving photon tracking through complex optical elements. Our results leverage advancements in Vision Transformers, specifically hierarchical Swin Transformer and normalizing flows. These methods enable direct learning from real data and the reconstruction of complex topologies. We conclude by discussing the implications and future extensions of this work, which can offer capabilities for PID for multiple cutting-edge experiments like the future EIC.
Maximizing information in neuron populations for neuromorphic spike encoding
Authors: Ferdaoussi Ahmad El , Plourde Eric , Rouat Jean 
Published: January 2025

Abstract
One of the ways neuromorphic applications emulate the processing performed by the brain is by using spikes as inputs instead of time-varying analog stimuli. Therefore, these time-varying stimuli have to be encoded into spikes, which can induce important information loss. To alleviate this loss, some studies use population coding strategies to encode more information using a population of neurons rather than just one neuron. However, configuring the encoding parameters of such a population is an open research question. This work proposes an approach based on maximizing the mutual information between the signal and the spikes in the population of neurons. The proposed algorithm is inspired by the information-theoretic framework of Partial Information Decomposition. Two applications are presented: blood pressure pulse wave classification, and neural action potential waveform classification. In both tasks, the data is encoded into spikes and the encoding parameters of the neuron populations are tuned to maximize the encoded information using the proposed algorithm. The spikes are then classified and the performance is measured using classification accuracy as a metric. Two key results are reported. First, adding neurons to the population leads to an increase in both mutual information and classification accuracy beyond what could be accounted for by each neuron separately, showing the usefulness of population coding strategies. Second, the classification accuracy obtained with the tuned parameters is near-optimal and it closely follows the mutual information as more neurons are added to the population. Furthermore, the proposed approach significantly outperforms random parameter selection, showing the usefulness of the proposed approach. These results are reproduced in both applications.
Heterogeneous long-term changes in larch forest and shrubland cover in the Kolyma lowland are not captured by coarser-scale greening trends
Authors: Kropp Heather , Loranty Michael M , Epstein Howard , Frost Gerald V , Koplik Adam , Berner Logan T 
Published: January 2025

Abstract
Changes in shrub and tree cover concurrent with rising air temperatures are a widespread phenomenon in Arctic–Boreal ecosystems. The expansion of tall shrubs and trees can alter ground thermal regimes and soil moisture impacting permafrost and biogeochemical cycling. Changes in shrub and tree cover can be difficult to characterize with limited in-situ observations and moderate/coarse resolution satellite imagery, thereby posing challenges in disentangling changes in vegetation growth from shifts in vegetation composition. We pair high resolution historical (KeyHole9 1971) and current satellite imagery (WorldView-3 2020) with a convolutional neural network approach to predict forest, shrubland, and surface water cover within a region of the Kolyma lowland (171 km2) in eastern Siberia. The overall accuracy of the predictions was 0.90 for 1971 and 0.92 for 2020. We found an overall net increase in shrubland cover of 14 km2 (8% of study extent) and little net change in forest cover, but changes in both land cover classes were highly heterogenous across the landscape. Increases in shrubland cover were highest in proximity to surface water (<100 m) and in close proximity to areas with stable shrubland cover. We found that changes in shrubland and forest cover did not correspond with trends in vegetation greenness (i.e., NDVI) derived from moderate resolution satellite data time series, which were fairly uniform among the land cover classes. Our findings highlight that ongoing land cover change in Siberian lowlands is highly heterogeneous and the need for a better quantification of the drivers and consequences of landscape change in these carbon- and ice- rich permafrost ecosystems.
Measurement error in remotely sensed fractional snow cover datasets: implications for ecological research
Authors: Jacques-Hamilton Rowan , Valcu Mihai , Kwon Eunbi , Versluijs Tom S L , Kempenaers Bart 
Published: January 2025

Abstract
Snow cover and snow melt patterns are important features of the Arctic environment, with wide-ranging repercussions for ecology. Datasets based on satellite imaging—often freely available—provide a powerful means for estimating snow cover. However, researchers should be aware of the possible error and bias in such datasets. Here, we quantify measurement error in commonly used data on snow cover, and demonstrate how biases have the potential to alter conclusions of ecological studies. We established 38 quadrats (80 m × 50 m) across a study site of Arctic tundra near Utqiaġvik, Alaska. At each quadrat, we estimated fractional snow cover (FSC) and the timing of snow melt using data from moderate resolution imaging spectroradiometer (MODIS), visible infrared imaging radiometer suite (VIIRS), and Sentinel-2 satellites. We compared satellite-based estimates with data from drone imagery to quantify measurement error and bias. We then evaluated whether the measurement error and bias alter conclusions about the relationship between the timing of snow melt and the breeding phenology of a population of pectoral sandpipers Calidris melanotos. We found that satellite datasets tended to overestimate FSC, leading to late estimates for snow melt dates. The Sentinel-2 dataset gave the most accurate results, followed by VIIRS, with MODIS giving the least accurate results. The degree of error varied substantially with the level of FSC, with biases reaching up to 60% for MODIS and VIIRS datasets at intermediate FSC values. Consequently, these datasets resulted in substantially different conclusions about how snow melt patterns were related to settlement and nesting dates of pectoral sandpipers. Our study indicates that measurement error in FSC can be large with substantial variation in the degree of error among satellite products. We show that these biases can impact conclusions of ecological studies. Therefore, ecologists should be conscious of the limitations of satellite-derived estimates of snow melt, and where possible should consult studies validating snow measurements in environments comparable to that of their study system.
Don’t Rock the Boat—the Devil You Know Is in It: MONUC/MONUSCO in the Democratic Republic of Congo
Authors: von Billerbeck Sarah , Gippert Birte Julia , Oksamytna Kseniya , Tansey Oisín 
Published: January 2025

Abstract
Chapter 4 examines the case of the UN Mission in the Democratic Republic of Congo / Mission de l’Organisation des Nations Unies en République Démocratique du Congo (MONUC) and the UN Stabilization Mission in the Democratic Republic of Congo / Mission de l’Organisation des Nations Unies pour la Stabilisation en RD Congo (MONUSCO) in Congo from 2003 to 2018. We ascribe enabling in Congo to numerous factors, in particular the tension between maintaining stability and supporting democratization, government mistrust of the United Nations (UN) and the need to maintain working relations with Congolese officials, and the need to deliver concrete successes in the short term. We then examine how the UN enabled authoritarian behavior through the capacity-building and signaling mechanisms. First, we demonstrate how the UN built the capacity of political and security institutions, including support to the presidency and the armed forces, which in turn enabled these institutions to engage in repression and political exclusion. Second, we show how the UN created a permissive environment through signaling and mild responses to authoritarian moves by the government, in particular during presidential elections and episodes of violence and repression.