bluuebunny/crossref_metadata_2025_split huggingface dataset:
Investigating mechanical properties and energy absorption of elastomeric polymer nanocomposites containing cellulose nanofibers in tensile, quasi-static compression, and high strain rate tests
Authors: Ghiaskar Ahmad , Taghipoor Hossein 
Published: July 2024

Abstract
In this study, mechanical properties and energy absorption of elastomeric nanocomposites reinforced with cellulose nanofibers are investigated from tensile, Quasi-static Compression (QSC), and Split-Hopkinson Pressure Bar (SHPB) tests. For this purpose, the design and preparation of rubber nanocomposites with different loadings of cellulose nanofibers (CNFs) were carried out, and the optimal cure temperature (T90) of the rubber compound containing cellulose nanofibers was determined from the rheometer test. In the continuation of this study, the effects of adding cellulose nanofibers on the tensile strength, elongation to break, and energy absorption of the proposed Nano-composites were investigated. The results showed that the nanocomposite containing 6 phr increases the ultimate strength and elastic modulus of 300% by 33.5% and 22.7%, respectively, compared to the control rubber (0 phr). Similarly, these numbers are about 10 and 65% for loading 12 phr cellulose nanofibers. From the results of the quasi-static compression test for different amounts of cellulose nanofibers at a strain rate of 50%, it was found that the lowest and highest compressive stress due to the resistance of elastomeric nanocomposites is related to the control sample (0 phr) and the 12 phr sample, respectively. Also, from high strain rate tests of Split Hopkinson Pressure Bar, it was found that the fracture mechanism of flexible composites containing cellulose nanofibers changes in response to a high-speed impact, and the samples respond to high-pressure impact with brittle fractures. It was also found that rubber nanocomposites reinforced with cellulose nanofibers are very sensitive to strain rates. As the strain rate increases, the energy absorption of rubber nanocomposites increases. The optimal loading (6 phr) of cellulose nanofibers in rubber compounds makes them suitable for energy absorption applications. Cellulosic nanofibers provide acceptable dispersion of nanomaterials through good interaction with natural rubber and lignin-carbon fillers. Therefore, through the physical interweaving of fillers with polymer chains, CNF provide better binding of polymer chains to improve properties.
Response analysis of NMRG system considering Rb–Xe coupling
Authors: Zhang 张 Yi 燚 , Jiang 江 Qiyuan 奇渊 , Sun 孙 Bingfeng 兵锋 , Wei 魏 Jiahu 加湖 , Yang 杨 Lin 麟 , Li 李 Yongyuan 永远 , Wang 汪 Zhiguo 之国 , Yang 杨 Kaiyong 开勇 , Luo 罗 Hui 晖 
Published: July 2024

Abstract
The dynamic range of the nuclear magnetic resonance gyroscope can be effectively improved through the closed-loop control scheme, which is crucial to its application in inertial measurement. This paper presents the analytical transfer function of Xe closed-loop system in the nuclear magnetic resonance gyroscope considering Rb–Xe coupling effect. It not only considers the dynamic characteristics of the system more comprehensively, but also adds the influence of the practical filters in the gyro signal processing system, which can obtain the accurate response characteristics of signal frequency and amplitude at the same time. The numerical results are compared with an experimentally verified simulation program, which indicate great agreement. The research results of this paper are of great significance to the practical application and development of the nuclear magnetic resonance gyroscope.
An assessment of the ageing of the absolute spectral responsivity of trap detectors at krypton ion laser emission wavelengths
Authors: Dury Martin , Harris Subrena , Goodman Teresa , Servantes William , White Malcolm 
Published: July 2024

Abstract
We have assessed the absolute spectral responsivities of three-element trap detectors calibrated against the National Physical Laboratory primary standard cryogenic radiometer at eight krypton ion laser emission wavelengths over an approximate period of 20 years. As expected, we observed that the absolute spectral responsivities decrease with time. Additionally, we found that as the wavelength decreases, the ageing rate increases. At 356.4 nm, an average responsivity decrease of around −1800 ppm yr−1 is reported. While at longer wavelengths, the slowest rate of ageing, approximately −40 ppm yr−1, occurs at 799.3 nm. Interestingly, the year-on-year changes exhibit a relatively linear trend, allowing us to predict the future performance of the trap detectors. It is important to note, however, that predicted performance cannot be guaranteed and regular recalibration against a primary standard is essential, especially if low calibration uncertainties are required.
Calibrating the global network of gravitational wave observatories via laser power calibration at NIST and PTB
Authors: Bhattacharjee D , Savage R L , Bajpai R , Betzwieser J , Bossilkov V , Chen D , Grimaud C , Hido S , Karki S , Kück S , Lagabbe P , Lecher H , Lehman J , Llamas F , López M , Rolland L , Sanchez A , Spidell M , Stephens M 
Published: July 2024

Abstract
Current gravitational wave (GW) observatories rely on photon calibrators that use laser radiation pressure to generate displacement fiducials used to calibrate detector output signals. Reducing calibration uncertainty enables optimal extraction of astrophysical information such as source distance and sky position from detected signals. For the ongoing O4 observing run that started on 24 May 2023, the global GW detector network is employing a new calibration scheme with transfer standards calibrated at both the National Institute of Standards and Technology (NIST) and the Physikalisch-Technische Bundesanstalt (PTB). These transfer standards will circulate between the observatories and the metrology institutes to provide laser power calibration traceable to the International System of Units (SI) and enable assessment and reduction of relative calibration errors for the observatory network. The Laser Interferometer Gravitational-Wave Observatory (LIGO) project and the Virgo project are currently participating in the new calibration scheme. The Large-scale Cryogenic Gravitational-wave Telescope project (KAGRA) is expected to join in 2024, with the LIGO Aundha Observatory in India joining later. Before implementing this new scheme, a NIST-PTB bilateral comparison was conducted. It validated the scale representation by both laboratories, with a degree of equivalence of −0.2% and an associated expanded uncertainty of 0.32% (k = 2) which is significantly lower than previous studies. We describe the transfer of power sensor calibration, including detailed uncertainty estimates, from the transfer standards calibrated by NIST and PTB to the sensors operating continuously at the interferometer end stations. Finally, we discuss the ongoing calibration of Pcal-induced displacement fiducials for the O4 observing run. Achieved combined standard uncertainty levels as low as 0.3% facilitate calibrating the interferometer output signals with sub-percent accuracy.
Neural activity shaping in visual prostheses with deep learning
Authors: Castro Domingos , Grayden David B , Meffin Hamish , Spencer Martin 
Published: July 2024

Abstract

Objective. The visual perception provided by retinal prostheses is limited by the overlapping current spread of adjacent electrodes. This reduces the spatial resolution attainable with unipolar stimulation. Conversely, simultaneous multipolar stimulation guided by the measured neural responses—neural activity shaping (NAS)—can attenuate excessive spread of excitation allowing for more precise control over the pattern of neural activation. However, defining effective multipolar stimulus patterns is a challenging task. Previous attempts focused on analytical solutions based on an assumed linear nonlinear model of retinal response; an analytical model inversion (AMI) approach. Here, we propose a model-free solution for NAS, using artificial neural networks (ANNs) that could be trained with data acquired from the implant. Approach. Our method consists of two ANNs trained sequentially. The measurement predictor network (MPN) is trained on data from the implant and is used to predict how the retina responds to multipolar stimulation. The stimulus generator network is trained on a large dataset of natural images and uses the trained MPN to determine efficient multipolar stimulus patterns by learning its inverse model. We validate our method in silico using a realistic model of retinal response to multipolar stimulation. Main results. We show that our ANN-based NAS approach produces sharper retinal activations than the conventional unipolar stimulation strategy. As a theoretical bench-mark of optimal NAS results, we implemented AMI stimulation by inverting the model used to simulate the retina. Our ANN strategy produced equivalent results to AMI, while not being restricted to any specific type of retina model and being three orders of magnitude more computationally efficient. Significance. Our novel protocol provides a method for efficient and personalized retinal stimulation, which may improve the visual experience and quality of life of retinal prosthesis users.
Detecting rhythmic spiking through the power spectra of point process model residuals
Authors: Cox Karin M , Kase Daisuke , Znati Taieb , Turner Robert S 
Published: July 2024

Abstract

Objective. Oscillations figure prominently as neurological disease hallmarks and neuromodulation targets. To detect oscillations in a neuron’s spiking, one might attempt to seek peaks in the spike train’s power spectral density (PSD) which exceed a flat baseline. Yet for a non-oscillating neuron, the PSD is not flat: The recovery period (‘RP’, the post-spike drop in spike probability, starting with the refractory period) introduces global spectral distortion. An established ‘shuffling’ procedure corrects for RP distortion by removing the spectral component explained by the inter-spike interval (ISI) distribution. However, this procedure sacrifices oscillation-related information present in the ISIs, and therefore in the PSD. We asked whether point process models (PPMs) might achieve more selective RP distortion removal, thereby enabling improved oscillation detection. Approach. In a novel ‘residuals’ method, we first estimate the RP duration (nr
) from the ISI distribution. We then fit the spike train with a PPM that predicts spike likelihood based on the time elapsed since the most recent of any spikes falling within the preceding nr
milliseconds. Finally, we compute the PSD of the model’s residuals. Main results. We compared the residuals and shuffling methods’ ability to enable accurate oscillation detection with flat baseline-assuming tests. Over synthetic data, the residuals method generally outperformed the shuffling method in classification of true- versus false-positive oscillatory power, principally due to enhanced sensitivity in sparse spike trains. In single-unit data from the internal globus pallidus (GPi) and ventrolateral anterior thalamus (VLa) of a parkinsonian monkey—in which alpha-beta oscillations (8–30 Hz) were anticipated—the residuals method reported the greatest incidence of significant alpha-beta power, with low firing rates predicting residuals-selective oscillation detection. Significance. These results encourage continued development of the residuals approach, to support more accurate oscillation detection. Improved identification of oscillations could promote improved disease models and therapeutic technologies.
Single-trial movement intention detection estimation in patients with Parkinson’s disease: a movement-related cortical potential study
Authors: Jochumsen Mads , Poulsen Kathrin Battefeld , Sørensen Sascha Lan , Sulkjær Cecilie Sørenbye , Corydon Frida Krogh , Strauss Laura Sølvberg , Roos Julie Billingsø 
Published: July 2024

Abstract

Objectives. Parkinson patients often suffer from motor impairments such as tremor and freezing of movement that can be difficult to treat. To unfreeze movement, it has been suggested to provide sensory stimuli. To avoid constant stimulation, episodes with freezing of movement needs to be detected which is a challenge. This can potentially be obtained using a brain–computer interface (BCI) based on movement-related cortical potentials (MRCPs) that are observed in association with the intention to move. The objective in this study was to detect MRCPs from single-trial EEG. Approach. Nine Parkinson patients executed 100 wrist movements and 100 ankle movements while continuous EEG and EMG were recorded. The experiment was repeated in two sessions on separate days. Using temporal, spectral and template matching features, a random forest (RF), linear discriminant analysis, and k-nearest neighbours (kNN) classifier were constructed in offline analysis to discriminate between epochs containing movement-related or idle brain activity to provide an estimation of the performance of a BCI. Three classification scenarios were tested: 1) within-session (using training and testing data from the same session and participant), between-session (using data from the same participant from session one for training and session two for testing), and across-participant (using data from all participants except one for training and testing on the remaining participant). Main results. The within-session classification scenario was associated with the highest classification accuracies which were in the range of 88%–89% with a similar performance across sessions. The performance dropped to 69%–75% and 70%–75% for the between-session and across-participant classification scenario, respectively. The highest classification accuracies were obtained for the RF and kNN classifiers. Significance. The results indicate that it is possible to detect movement intentions in individuals with Parkinson’s disease such that they can operate a BCI which may control the delivery of sensory stimuli to unfreeze movement.
Permutation conditional mutual information to quantify TMS-evoked cortical connectivity in disorders of consciousness
Authors: Zhao Zhibin , Wang Yong , Xia Xiaoyu , Li Xiaoli 
Published: July 2024

Abstract

Objective. To improve the understanding and diagnostic accuracy of disorders of consciousness (DOC) by quantifying transcranial magnetic stimulation (TMS) evoked electroencephalography connectivity using permutation conditional mutual information (PCMI). Approach. PCMI can characterize the functional connectivity between different brain regions. This study employed PCMI to analyze TMS-evoked cortical connectivity (TEC) in 154 DOC patients and 16 normal controls, focusing on optimizing parameter selection for PCMI (Data length, Order length, Time delay). We compared short-range and long-range PCMI values across different consciousness states—unresponsive wakefulness syndrome (UWS), minimally conscious state (MCS), and normal (NOR)—and assessed various feature selection and classification techniques to distinguish these states. Main results. (1) PCMI can quantify TEC. We found optimal parameters to be Data length: 500 ms; Order: 3; Time delay: 6 ms. (2) TMS evoked potentials (TEPs) for NOR showed a rich response, while MCS patients showed only a few components, and UWS patients had almost no significant components. The values of PCMI connectivity metrics demonstrated its usefulness for measuring cortical connectivity evoked by TMS. From NOR to MCS to UWS, the number and strength of TEC decreased. Quantitative analysis revealed significant differences in the strength and number of TEC in the entire brain, local regions and inter-regions among different consciousness states. (3) A decision tree with feature selection by mutual information performed the best (balanced accuracy: 87.0% and accuracy: 83.5%). This model could accurately identify NOR (100.0%), but had lower identification accuracy for UWS (86.5%) and MCS (74.1%). Significance. The application of PCMI in measuring TMS-evoked connectivity provides a robust metric that enhances our ability to differentiate between various states of consciousness in DOC patients. This approach not only aids in clinical diagnosis but also contributes to the broader understanding of cortical connectivity and consciousness.
A supersymmetric quantum perspective on the explicit large deviations for reversible Markov jump processes, with applications to pure and random spin chains
Authors: Monthus Cécile 
Published: July 2024

Abstract
The large deviations at various levels that are explicit for Markov jump processes satisfying detailed balance are revisited in terms of the supersymmetric quantum Hamiltonian H that can be obtained from the Markov generator via a similarity transformation. We first focus on the large deviations at level 2 for the empirical density

p
^

(
C
)

of the configurations C seen during a trajectory over the large time window

[
0
,
T
]

, and rewrite the explicit Donsker–Varadhan rate function as the matrix element

I

[
2
]

[

p
^

(
.
)
]
=
⟨

p
^

|
H
|

p
^

⟩

involving the square-root ket

|

p
^

⟩

. (The analog formula is also discussed for reversible diffusion processes as a comparison.) We then consider the explicit rate functions at higher levels, in particular for the joint probability of the empirical density

p
^

(
C
)

and the empirical local activities

a
^

(
C
,

C

′

)

characterizing the density of jumps between two configurations

(
C
,

C

′

)

. Finally, the explicit rate function for the joint probability of the empirical density

p
^

(
C
)

and of the empirical total activity

A
^

that represents the total density of jumps of a long trajectory is written in terms of the two matrix elements

⟨

p
^

|
H
|

p
^

⟩

and

⟨

p
^

|

H
off

|

p
^

⟩

, where

H
off

represents the off-diagonal part of the supersymmetric Hamiltonian H. This general framework is then applied to pure or random spin chains with single-spin-flip or two-spin-flip transition rates, where the supersymmetric Hamiltonian H corresponds to quantum spin chains with local interactions involving Pauli matrices of two or three neighboring sites. It is then useful to introduce the quantum density matrix

ρ
^

=
|

p
^

⟩
⟨

p
^

|

associated with the empirical density

p
^

(
.
)

in order to rewrite the various rate functions in terms of reduced density matrices involving only two or three neighboring sites.
A tactile sensing system capable of recognizing objects based on bioinspired self-sensing soft pneumatic actuator
Authors: Yu Meng , Cheng Xiang , Peng Shigang , Zhao Liangyu , Wang Pengfei 
Published: July 2024

Abstract
Tactile sensors play an important role when robots perform contact tasks, such as physical information collection, force or displacement control to avoid collision. For these manipulations, excessive contact may cause damage while poor contact cause information loss between the robotic end-effector and the objects. Inspired by skin structure and signal transmission method, this paper proposes a tactile sensing system based on the self-sensing soft pneumatic actuator (S-SPA) capable of providing tactile sensing capability for robots. Based on the adjustable height and compliance characteristics of the S-SPA, the contact process is safe and more tactile information can be collected. And to demonstrate the feasibility and advantage of this system, a robotic hand with S-SPAs could recognize different textures and stiffness of the objects by touching and pinching behaviours to collect physical information of the various objects under the positive work states of the S-SPA. The result shows the recognition accuracy of the fifteen texture plates reaches 99.4

%

, and the recognition accuracy of the four stiffness cuboids reaches 100

%

by training a KNN model. This safe and simple tactile sensing system with high recognition accuracies based on S-SPA shows great potential in robotic manipulations and is beneficial to applications in domestic and industrial fields.
The effect of Skyrme–Chern–Simons dynamics on gauged Skyrmions in

2
+
1

dimensions
Authors: Navarro-Lérida Francisco , Radu Eugen , Tchrakian D H 
Published: July 2024

Abstract
We study the Skyrmion of the SO(2) gauged O(3) sigma model in

2
+
1

dimensions in the presence of a Skyrme–Chern–Simons (SCS) term, and compare its properties with the corresponding properties of the Skyrmion in the presence of the usual Chern–Simons (CS) term. We find that these properties are qualitatively largely similar in both cases, meaning that the SCS density can be employed as an alternative to the CS term also in higher dimensions, most importantly in even dimensions where no CS term is defined,

e
.
g
.
,

in

3
+
1

dimensions. The SCS density employed here is defined in terms of the pair of

S
O
(
2
)
×
S
O
(
2
)

gauge fields and an auxiliary O(5) Skyrme scalar, which is contracted to an effective O(3) Skyrme scalar. Technically, this study maps the methods to be applied in higher dimensional examples.
Free fermions in the repeated interactions scheme
Authors: Karevski Dragi 
Published: July 2024

Abstract
We discuss collision models made of fermions colliding repeatedly with an extended fermionic system whose hamiltonian is quadratic. After a review of the general theory of collision models, we derive a general Lyapunov dynamical equation that governs the covariance matrix of the fermionic extended system. We solve explicitly, in a wide range of physical parameters, several situations of interest such as the case of a boundary driven chain or the replication of entanglement leading to a rainbow like state.
Enhancing neovascularization post-myocardial infarction through injectable hydrogel functionalized with endothelial-derived EVs
Authors: Maiullari Fabio , Milan Marika , Chirivì Maila , Ceraolo Maria Grazia , Bousselmi Salma , Fratini Nicole , Galbiati Matteo , Fortunato Orazio , Costantini Marco , Brambilla Francesca , Mauri Pierluigi , Di Silvestre Dario , Calogero Antonella , Sciarra Tommaso , Rizzi Roberto , Bearzi Claudia 
Published: July 2024

Abstract
Over the past three decades, cell therapy development has fallen short of expectations, with many cellular sources demonstrating a ‘Janus effect’ and raising safety concerns. Extracellular vesicles (EVs), supported by advanced technologies, present a promising avenue in regenerative medicine, offering benefits such as immune tolerance and avoidance of negative aspects associated with cell transplants. Our previous research showcased enhanced and organized subcutaneous vascularization using three-dimensional bioprinted patches containing HUVEC-derived EVs in immunodeficient animal models. In this context, stress conditions on the cells of origin further boosted the EVs’ neoangiogenic potential. Since neovascularization is the first regenerative target requiring restoration, the present study aims to complement our previous work by employing an injectable gelatin methacrylate (GelMA) hydrogel functionalized with HUVEC-derived EVs in a pathological condition of acute myocardial infarction. This bioactive hydrogel resulted in reduced fibrosis, improved contractility, and promoted angiogenesis, showing promise in countering tissue deterioration and addressing vascular deficits. Moreover, the molecular characterization of EVs through miRNome and proteomic analyses further supports their potential as bio-additives for hydrogel functionalization. This cell-free approach mitigates immune rejection and oncogenic risks, offering innovative therapeutic advantages.