bluuebunny/crossref_metadata_2025_split huggingface dataset:
A simple DIY electrical resistivity apparatus for students
Authors: Mulla Rafiq 
Published: May 2024

Abstract
A simple do-it-yourself (DIY) apparatus is designed and built for the measurement of the electrical resistivity of materials. The tool is portable and easy to operate, and students/new researchers can build their own apparatus with a minimum amount of time and raw materials. The apparatus’ spring-loaded four-point probes help provide a good electrical contact between the sample surface and the probes. It has been checked for its reliability by comparing the resistivity data with literature values and the measurements match well with the previous data. The apparatus is suitable for measurements from room temperature to ∼100 °C.
Prospective validation of clinical deterioration predictive models prior to intensive care unit transfer among patients admitted to acute care cardiology wards
Authors: Keim-Malpass Jessica , Moorman Liza P , Moorman J Randall , Hamil Susan , Yousefvand Gholamreza , Monfredi Oliver J , Ratcliffe Sarah J , Krahn Katy N , Jones Marieke K , Clark Matthew T , Bourque Jamieson M 
Published: May 2024

Abstract

Objective. Very few predictive models have been externally validated in a prospective cohort following the implementation of an artificial intelligence analytic system. This type of real-world validation is critically important due to the risk of data drift, or changes in data definitions or clinical practices over time, that could impact model performance in contemporaneous real-world cohorts. In this work, we report the model performance of a predictive analytics tool developed before COVID-19 and demonstrate model performance during the COVID-19 pandemic. Approach. The analytic system (CoMETⓇ, Nihon Kohden Digital Health Solutions LLC, Irvine, CA) was implemented in a randomized controlled trial that enrolled 10 422 patient visits in a 1:1 display-on display-off design. The CoMET scores were calculated for all patients but only displayed in the display-on arm. Only the control/display-off group is reported here because the scores could not alter care patterns. Main results. Of the 5184 visits in the display-off arm, 311 experienced clinical deterioration and care escalation, resulting in transfer to the intensive care unit, primarily due to respiratory distress. The model performance of CoMET was assessed based on areas under the receiver operating characteristic curve, which ranged from 0.725 to 0.737. Significance. The models were well-calibrated, and there were dynamic increases in the model scores in the hours preceding the clinical deterioration events. A hypothetical alerting strategy based on a rise in score and duration of the rise would have had good performance, with a positive predictive value more than 10-fold the event rate. We conclude that predictive statistical models developed five years before study initiation had good model performance despite the passage of time and the impact of the COVID-19 pandemic.
Noise-based correction for electrical impedance tomography
Authors: Mason Kai , Maurino-Alperovich Florencia , Holder David , Aristovich Kirill 
Published: May 2024

Abstract

Objective. Noisy measurements frequently cause noisy and inaccurate images in impedance imaging. No post-processing technique exists to calculate the propagation of measurement noise and use this to suppress noise in the image. The objectives of this work were (1) to develop a post-processing method for noise-based correction (NBC) in impedance tomography, (2) to test whether NBC improves image quality in electrical impedance tomography (EIT), (3) to determine whether it is preferable to use correlated or uncorrelated noise for NBC, (4) to test whether NBC works with in vivo data and (5) to test whether NBC is stable across model and perturbation geometries. Approach. EIT was performed in silico in a 2D homogeneous circular domain and an anatomically realistic, heterogeneous 3D human head domain for four perturbations and 25 noise levels in each case. This was validated by performing EIT for four perturbations in a circular, saline tank in 2D as well as a human head-shaped saline tank with a realistic skull-like layer in 3D. Images were assessed on the error in the weighted spatial variance (WSV) with respect to the true, target image. The effect of NBC was also tested for in vivo EIT data of lung ventilation in a human thorax and cortical activity in a rat brain. Main results. On visual inspection, NBC maintained or increased image quality for all perturbations and noise levels in 2D and 3D, both experimentally and in silico. Analysis of the WSV showed that NBC significantly improved the WSV in nearly all cases. When the WSV was inferior with NBC, this was either visually imperceptible or a transformation between noisy reconstructions. For in vivo data, NBC improved image quality in all cases and preserved the expected shape of the reconstructed perturbation. Significance. In practice, uncorrelated NBC performed better than correlated NBC and is recommended as a general-use post-processing technique in EIT.
Multimodal wearable EEG, EMG and accelerometry measurements improve the accuracy of tonic-clonic seizure detection
Authors: Zhang Jingwei , Swinnen Lauren , Chatzichristos Christos , Broux Victoria , Proost Renee , Jansen Katrien , Mahler Benno , Zabler Nicolas , Epitashvilli Nino , Dümpelmann Matthias , Schulze-Bonhage Andreas , Schriewer Elisabeth , Ermis Ummahan , Wolking Stefan , Linke Florian , Weber Yvonne , Symmonds Mkael , Sen Arjune , Biondi Andrea , Richardson Mark P , I Abuhaiba Sulaiman , Silva Ana Isabel , Sales Francisco , Vértes Gergely , Paesschen Wim Van , Vos Maarten De 
Published: May 2024

Abstract

Objective. This paper aims to investigate the possibility of detecting tonic-clonic seizures (TCSs) with behind-the-ear, two-channel wearable electroencephalography (EEG), and to evaluate its added value to non-EEG modalities in TCS detection. Methods. We included 27 participants with a total of 44 TCSs from the European multicenter study SeizeIT2. The wearable Sensor Dot (Byteflies) was used to measure behind-the-ear EEG, electromyography (EMG), electrocardiography, accelerometry (ACC) and gyroscope. We evaluated automatic unimodal detection of TCSs, using sensitivity, precision, false positive rate (FPR) and F1-score. Subsequently, we fused the different modalities and again assessed performance. Algorithm-labeled segments were then provided to two experts, who annotated true positive TCSs, and discarded false positives. Results. Wearable EEG outperformed the other single modalities with a sensitivity of 100% and a FPR of 10.3/24 h. The combination of wearable EEG and EMG proved most clinically useful, delivering a sensitivity of 97.7%, an FPR of 0.4/24 h, a precision of 43%, and an F1-score of 59.7%. The highest overall performance was achieved through the fusion of wearable EEG, EMG, and ACC, yielding a sensitivity of 90.9%, an FPR of 0.1/24 h, a precision of 75.5%, and an F1-score of 82.5%. Conclusions. In TCS detection with a wearable device, combining EEG with EMG, ACC or both resulted in a remarkable reduction of FPR, while retaining a high sensitivity. Significance. Adding wearable EEG could further improve TCS detection, relative to extracerebral-based systems.
Multi-source deep domain adaptation ensemble framework for cross-dataset motor imagery EEG transfer learning
Authors: Miao Minmin , Yang Zhong , Sheng Zhenzhen , Xu Baoguo , Zhang Wenbin , Cheng Xinmin 
Published: May 2024

Abstract

Objective. Electroencephalography (EEG) is an important kind of bioelectric signal for measuring physiological activities of the brain, and motor imagery (MI) EEG has significant clinical application prospects. Convolutional neural network has become a mainstream algorithm for MI EEG classification, however lack of subject-specific data considerably restricts its decoding accuracy and generalization performance. To address this challenge, a novel transfer learning (TL) framework using auxiliary dataset to improve the MI EEG classification performance of target subject is proposed in this paper. Approach. We developed a multi-source deep domain adaptation ensemble framework (MSDDAEF) for cross-dataset MI EEG decoding. The proposed MSDDAEF comprises three main components: model pre-training, deep domain adaptation, and multi-source ensemble. Moreover, for each component, different designs were examined to verify the robustness of MSDDAEF. Main results. Bidirectional validation experiments were performed on two large public MI EEG datasets (openBMI and GIST). The highest average classification accuracy of MSDDAEF reaches 74.28% when openBMI serves as target dataset and GIST serves as source dataset. While the highest average classification accuracy of MSDDAEF is 69.85% when GIST serves as target dataset and openBMI serves as source dataset. In addition, the classification performance of MSDDAEF surpasses several well-established studies and state-of-the-art algorithms. Significance. The results of this study show that cross-dataset TL is feasible for left/right-hand MI EEG decoding, and further indicate that MSDDAEF is a promising solution for addressing MI EEG cross-dataset variability.
Electron acceleration in the electron dissipation region of asymmetrical magnetic reconnection driven by ultra-intensity lasers
Authors: Zhang Qian , Ping Yongli , An Weiming , Zhong Jiayong 
Published: May 2024

Abstract
We performed 3D Particle-In-Cell simulations to study electron acceleration in the electron dissipation region of asymmetrical electron magnetic reconnection driven by ultra-intensity lasers, which is similar to the Earth’s magnetosphere reconnection process. Within the electron dissipation region, electrons exhibit a nonthermal distribution, and as the asymmetry increases, the power-law spectrum becomes steeper. Remarkably, the electron spectrum closely resembles a delta distribution, arising from the intense acceleration imparted by the reconnection electric field near the X-line. Both parallel electric field acceleration and the Betatron acceleration mechanism play pivotal roles in this reconnection process. Furthermore, as the magnetic reconnection asymmetry intensifies, the parallel electric acceleration mechanism becomes stronger near the X-point region, whereas the Betatron acceleration mechanism wanes, primarily concentrated in the outflow region.
Bidirectional large strain monitoring using a novel graphene film-based patch antenna sensor
Authors: Weng Shun , Peng Tingjun , Gao Ke , Zhu Hongping , Yan Yongyi , Yu Hong , He Daping 
Published: May 2024

Abstract
This study proposes a rectangular microstrip patch antenna sensor based on a high-conductivity graphene film for bidirectional strain detection in structural health monitoring (SHM). By using a highly conductive graphene film instead of traditional metal foil to produce a patch antenna, the antenna possesses a higher flexibility and a larger sensing range. The mechanical, electromagnetic, and radiative properties were investigated. The strain sensing principle based on the resonant frequency offset of the graphene film antenna was proposed. The relationships between the resonant frequency shift and structural strain were quantitatively explored through theoretical deductions, finite element simulations, and experiments. According to the experimental results, the shift in the resonant frequency was linearly related to the lateral and longitudinal strains. The sensitivity coefficients for the lateral and longitudinal strains were 2.2037 kHz/μϵ and 3.6198 kHz/μϵ, respectively. The thermal strain can be distinguished based on the linear resonant frequency-temperature relationship. The results demonstrated the advantages and prospects of the proposed novel patch antenna for SHM.
Comprehensive compensation of dynamic hysteresis and creep for piezoelectric actuator
Authors: Jin Jiaxi , Sun Xuan , Chen Zhaobo 
Published: May 2024

Abstract
This paper addresses the modeling of dynamic hysteresis and creep in piezoelectric actuators, and employs feedforward open-loop control based on inverse models to compensate for hysteresis and creep phenomena. The comprehensive model consists of quasi-dynamic and dynamic components. The quasi-dynamic model combines the quasi-dynamic Prandtl–Ishlinskii (PI) model with an PI-based linear time-invariant model, while the dynamic part utilizes the auto-regressive exogenous model. The model accurately describes creep and dynamic hysteresis with modeling errors of less than 0.01 μm and 0.14 μm, respectively. The inversion of the comprehensive model has been proven to exhibit unique convergence. Under inverse feedforward control, the improvement in dynamic hysteresis and hysteresis with creep can be achieved at 94% and 83%, respectively. The comprehensive model proposed in this paper accurately describes the dynamic hysteresis and creep phenomena in piezoelectric actuators and realizes open-loop compensation control, achieving precise actuation of piezoelectric actuators.
On the behavior of auxetic inserts: a numerical analysis to derive design guidelines
Authors: Di Brizzi Diego , Graziosi Serena , Bondin William , Grima Joseph N , Airoldi Alessandro 
Published: May 2024

Abstract
Auxetics are a class of materials and metamaterials with a negative Poisson’s ratio (ν) and have gained tremendous popularity over the last three decades. Many studies have focused on characterizing designs that allow obtaining a negative ν. However, some open issues remain concerning understanding the auxetic behavior in operational conditions. Studies have been centered on analyzing the response of specific auxetic topologies instead of treating auxeticity as a property to be analyzed in a well-defined structural context. This study aims to contribute to the investigation of auxetic materials with a structural application, focusing on maximizing performance. The field of application of auxetics for designing inserts was selected and a model of a nail-cavity system was created to determine the effects of different design choices on the system behavior by exploring relationships between selected parameters and the auxetic insert behavior. The exploration combines finite element modeling analyses with their surrogate models generated by supervised learning algorithms. This approach allows for exploring the system’s behavior in detail, thus demonstrating the potential effectiveness of auxetics when used for such applications. A list of design guidelines is elaborated to support the exploitation of auxetics in nail-cavity systems.
Hund’s three rules in actinide-containing superatoms with spin-orbit coupling calculations
Authors: Zhong Xiaoxue , Wang Peng , Qiu Ruizhi , Yuan Hongkuan 
Published: May 2024

Abstract
The intriguing and challenge issue in magnetic superatoms is searching for the suitable candidates to validate the Hund’s rules. Here, early actinide elements (An: Ac, Th, Pa, U, Np, Pu, Am) whose 5f electrons may crossover the localization and delocalization characteristics have been chosen to alloy with Al atoms in designing magnetic An@Al12 superatoms. By doing the global minimum structure search and the spin-orbital coupling density functional theory calculations, we provide an original idea to give theoretical argument that Hund’s three rules are still applicable in superatoms, which can be related to the fillings of highly localized An-5f orbitals into large exchange-splitting 2 F superatom orbitals. Specifically, selective 5f sub-orbitals of several An dopants can exhibit a dual nature in superatomic bonding, i.e. partial 5f electrons of Pa, U and Pu are reactive whereas all 5f electrons of Np and Am are highly localized. The molecular orbital analyses, combined with the qualitative interpretation of the phenomenological superatom sub-shell model, address the intricate interplays between the structure symmetry, electronic structure, spin and orbital magnetic moments. These findings have important implications for understanding the bonding and magnetic behaviors of An-containing superatoms and pave the way for designing novel magnetic superatoms.
Power-exponential and fixed-time consensus of conformable fractional-order quantum cellular neural networks via event-triggered control
Authors: Xiong Yao , Li Yesheng , Xiong Zhonglong , Lv Haifei , Chen Mengwei , Hu Changkui , Li Min 
Published: May 2024

Abstract
Quantum neural networks (QNNs) are considered to be superior to classical ANNs in machine learning, memory capacity, information processing, and quantum system simulation. However, In a practical and complex system, the dynamic behavior of an open quantum system could not be accurately described by an integer-ordered Schrödinger equation. In this paper, the conformable time-fractional-order Schrödinger equation is proposed, and accordingly, the model of conformable fractional-order quantum cellular neural networks (CFOQCNNs) is established and derived from the as-proposed equation. The properties of the conformable fractional-order derivative are studied and several new inequalities regarding the power-exponential and fixed-time convergence of conformable fractional-order systems are obtained. To save the communication resource, we introduce the event-triggered mechanism to construct the controllers and then the power-exponential and fixed-time synchronizations of the master-slave systems derived from the above CFOQCNNs are studied. We also prove the absence of Zeno behaviors regarding the event-triggered strategies. According to the numerical simulation, the dynamic behavior of the CFOQCNNs is discussed and the dissipativity of the CFOQCNNs is briefly revealed. Then the synchronization behaviors of the master and slave CFOQCNNs under power-exponential and fixed-time event-triggered control are demonstrated, where the effectiveness of the event-triggered control strategy is verified. Control behaviors with different fractional orders are also presented. We also discuss the hybrid of power-exponential control and fixed-time control and illustrate the advantages of the hybrid strategy. In the last, we conclude our studies, analyze the drawbacks of this work, and briefly introduce our future research.
‘The ‘Vector-Model’ wavefunction: spatial description and wavepacket formation of quantum-mechanical angular momenta’
Authors: Rakitzis T Peter , Koutrakis Michail E , Katsoprinakis Georgios E 
Published: May 2024

Abstract
We introduce the concept of an asymptotic spatial angular-momentum wavefunction,

X

m

j

φ
,
θ
,
χ

=

e

im
φ

δ

θ
−

θ

m

e

i

j
+

1

2

χ

,

which treats

j

in the

j
m

state as a three-dimensional entity; φ, θ, χ are the Euler angles, and

θ

m

is the Vector-Model polar angle, given by

cos

θ

m

=
m
/

j

.

A wealth of geometric information about

j

can be deduced from the eigenvalues and spatial transformation properties of the

X

m

j

φ
,
θ
,
χ

.

Specifically, the

X

m

j

φ
,
θ
,
χ

wavefunction gives a computationally simple description of the sizes of the particle and orbital-angular-momentum wavepackets (constructed from Gaussian distributions in

j

and

m

), given by effective wavepacket angular uncertainty relations for

Δ
m
Δ
φ
,

Δ
j
Δ
χ
,

and

Δ
φ
Δ
θ
.

The

X

m

j

φ
,
θ
,
χ

also predicts the position of the particle-wavepacket angular motion in the orbital plane, so that the particle-wavepacket rotation can be experimentally probed through continuous and non-destructive

j

-rotation measurements. Finally, we use the

X

m

j

(
φ
,
θ
,
χ
)

to determine geometrically well-known asymptotic expressions for Clebsch–Gordan coefficients, Wigner d-functions, the gyromagnetic ratio of elementary particles,

g
=
2
,

and the

m

-state-correlation matrix elements. Interestingly, for low

j
,

even down to

j
=
1
/
2
,

these expressions are either exact (the last two) or excellent approximations (the first two), showing that the

X

m

j

(
φ
,
θ
,
χ
)

give a useful spatial description of quantum-mechanical angular momentum, and provide a smooth connection with classical angular momentum.
Polarization detection for cylindrical vector beams empowered by pixelated metasurfaces
Authors: Li Hui , Xu Wenhui , Xu Hang , Tan Qi , Song Chunyu , Yao Jianquan 
Published: May 2024

Abstract
Polarimetry plays an indispensable role in the light–matter interactions. Nevertheless, conventional components developed for polarization measurements suffer from bulky volume and spatial alignment schemes, causing them to reveal limited performance in determining inhomogeneous polarization distributions. Here, we propose a polarization detection scheme based on pixelated all-dielectric metasurfaces using spin-multiplexing coding techniques. The polarization resolving capability of the pixelated metasurface under homogeneous linearly polarized illumination was first evaluated, and the extracted peak coordinates were used to establish an exact functional relationship with the azimuthal angle. Subsequently, the measurement of spatial inhomogeneous polarization was further explored with a focusing matrix assembled from pixelated metasurfaces. The proposed polarization detection strategy can be extended to other spectral bands without discrimination, stimulating potential applications in high-resolution imaging, sensing and data communication.
Constraining dark photons with self-consistent simulations of globular cluster stars
Authors: Dolan Matthew J. , Hiskens Frederick J. , Volkas Raymond R. 
Published: May 2024

Abstract
We revisit stellar constraints on dark photons. We undertake dynamical stellar evolution simulations which incorporate the resonant and off-resonant production of transverse and longitudinal dark photons. We compare our results with observables derived from measurements of globular cluster populations, obtaining new constraints based on the luminosity of the tip of the red-giant branch (RGB), the ratio of populations of RGB to horizontal branch (HB) stars (the R-parameter), and the ratio of asymptotic giant branch to HB stars (the R
2-parameter). We find that previous bounds derived from static stellar models do not capture the effects of the resonant production of light dark photons leading to overly conservative constraints, and that they over-estimate the effects of heavier dark photons on the RGB-tip luminosity. This leads to differences in the constraints of up to an order of magnitude in the kinetic mixing parameter.
Did we hear the sound of the Universe boiling? Analysis using the full fluid velocity profiles and NANOGrav 15-year data
Authors: Ghosh Tathagata , Ghoshal Anish , Guo Huai-Ke , Hajkarim Fazlollah , King Stephen F. , Sinha Kuver , Wang Xin , White Graham 
Published: May 2024

Abstract
In this paper, we analyse sound waves arising from a cosmic phase transition where the full velocity profile is taken into account as an explanation for the gravitational wave spectrum observed by multiple pulsar timing array groups. Unlike the broken power law used in the literature, in this scenario the power law after the peak depends on the macroscopic properties of the phase transition, allowing for a better fit with pulsar timing array (PTA) data. We compare the best fit with that obtained using the usual broken power law and, unsurprisingly, find a better fit with the gravitational wave (GW) spectrum that utilizes the full velocity profile. Even more importantly, the thermal parameters that produce the best fit are quite different. We then discuss models that can produce the best-fit point and complementary probes using CMB experiments and searches for light particles in DUNE, IceCUBE-Gen2, neutrinoless double β-decay, and forward physics facilities (FPF) at the LHC like FASERν, etc.