bluuebunny/crossref_metadata_2025_split huggingface dataset:
Dichotomous dynamics of magnetic monopole fluids
Authors: Hsu Chun-Chih , Takahashi Hiroto , Jerzembeck Fabian , Dasini Jahnatta , Carroll Chaia , Dusad Ritika , Ward Jonathan , Dawson Catherine , Sharma Sudarshan , Luke Graeme M. , Blundell Stephen J. , Castelnovo Claudio , Hallén Jonathan N. , Moessner Roderich , Davis J. C. Séamus 
Published: May 2024

A recent advance in the study of emergent magnetic monopoles was the discovery that monopole motion is restricted to dynamical fractal trajectories [J. N. Hallén
et al.
,
Science
378
, 1218 (2022)], thus explaining the characteristics of magnetic monopole noise spectra [R. Dusad
et al., Nature
571
, 234 (2019); A. M. Samarakoon
et al.
,
Proc. Natl. Acad. Sci. U.S.A.
119
, e2117453119 (2022)]. Here, we apply this novel theory to explore the dynamics of field-driven monopole currents, finding them composed of two quite distinct transport processes: initially swift fractal rearrangements of local monopole configurations followed by conventional monopole diffusion. This theory also predicts a characteristic frequency dependence of the dissipative loss angle for AC field–driven currents. To explore these novel perspectives on monopole transport, we introduce simultaneous monopole current control and measurement techniques using SQUID-based monopole current sensors. For the canonical material Dy
2
Ti
2
O
7
, we measure

Φ
(
t
)

, the time dependence of magnetic flux threading the sample when a net monopole current

J

t

=

Φ
˙

(
t
)

/

μ
0

is generated by applying an external magnetic field

B
0

t

.

These experiments find a sharp dichotomy of monopole currents, separated by their distinct relaxation time constants before and after
t
~

600

μ
s

from monopole current initiation. Application of sinusoidal magnetic fields

B
0

t

=
B
c
o
s

ω
t

generates oscillating monopole currents whose loss angle

θ

f

exhibits a characteristic transition at frequency

f
≈
1.8

kHz

over the same temperature range. Finally, the magnetic noise power is also dichotomic, diminishing sharply after
t
~

600

μ
s

. This complex phenomenology represents an unprecedented form of dynamical heterogeneity generated by the interplay of fractionalization and local spin configurational symmetry.
Effects of oxygen vacancies on the optical and electrical performances of silicon-based Er doped Ga2O3 films
Authors: Pang Houwei , Wang Yuan , Wu Yunfeng , Lin Sichen , Li Dongsheng , Yang Deren 
Published: May 2024

Abstract
Effects of oxygen vacancies on the optical and electrical properties of silicon-based Er doped Ga2O3 films are investigated. The content of oxygen vacancies can be tuned by changing the Ar:O2 flow ratios during sputtering, and the films sputtered in pure Ar are proved to possess the most oxygen vacancies by the calculations of energy band structure and carrier concentration. It is found that oxygen vacancies are involved in the process of indirect Er3+ ions related emission. With more oxygen vacancies introduced, the conductivity and energy transfer efficiency of Er doped Ga2O3 films can be enhanced simultaneously, leading to the increasing electroluminescence intensity of the light-emitting devices. The optimized silicon-based devices present the maximum optical power density of ∼2 μW cm−2.
Temperature dependence mechanism of high-temperature oxidation of transition metal silicide MoSi2
Authors: Huang Yang , Zhang Yuhang , Wu Yusong , Yang Zhikang , Wang Na , Fu Tairan 
Published: May 2024

Abstract
Transition metal silicides represented by MoSi2 have excellent oxidation resistance and are widely used as high-temperature anti-oxidation coatings in hot end components of power equipment. However, the mechanism of temperature-dependent growth of MoSi2 oxidation products has not been revealed. Therefore, this study investigated the formation characteristics of oxide film and silicide-poor compound on MoSi2 at temperatures of 1000 °C–1550 °C through high-temperature oxidation experiments, combined with microscopic Raman spectroscopy, scanning electron microscope, and x-ray diffraction (XRD) characterizations. The result showed that MoSi2 underwent high-temperature selective oxidation reactions at 1000 °C–1200 °C, forming MoO2 and SiO2 oxide film on the substrate. As the oxidation temperature increased to 1550 °C, after 100 h of oxidation, along with the disappearance of MoO2 and the phase transformation of SiO2, a continuous Mo5Si3 layer with a thickness of approximately 47 μm was formed at the SiO2–MoSi2 interface. Thermodynamics and kinetic calculations further revealed the mechanism of temperature-dependent growth of oxidation products (MoO2 and Mo5Si3) during high-temperature oxidation process of MoSi2. As the temperature increased, the diffusion flux ratio of O and Si decreased, leading to a decrease in oxygen concentration at the interface and promoting the growth of the Mo5Si3 layer. Its thickness is an important indicator for evaluating the oxidation resistance of MoSi2 coatings during service. This study provides experimental and mechanistic insights into the temperature-dependent growth behavior of Mo5Si3 during the high-temperature oxidation of MoSi2 coating, and provides guidance for predicting the service life and improving the oxidation resistance of silicide coatings.
Signature of excitonic insulators in phosphorene nanoribbons
Authors: Felipe Pereira de Oliveira Andre , Luisa da Rosa Andréia , Cavalheiro Dias Alexandre 
Published: May 2024

Abstract
Phosphorene is a recently developed two-dimensional (2D) material that has attracted tremendous attention because of its unique anisotropic optical properties and quasi-one-dimensional (1D) excitons. We use first-principles calculations combined with the maximally localized Wannier function tight binding Hamiltonian and Bethe–Salpeter equation (BSE) formalism to investigate quasiparticle effects of 2D and quasi-1D blue and black phosphorene nanoribbons. Our electronic structure calculations shows that both blue and black monolayered phases are semiconductors. On the other hand black phosphorene zigzag nanoribbons are metallic. Similar behavior is found for very thin blue phosphorene zig-zag and armchair nanoribbon. As a general behavior, the exciton binding energy decreases as the ribbon width increases, which highlights the importance of quantum confinement effects. The solution of the BSE shows that the blue phosphorene monolayer has an exciton binding energy four times higher than that of the black phosphorene counterpart. Furthermore, both monolayers show a different linear optical response with respect to light polarization, as black phosphorene is highly anisotropic. We find a similar, but less pronounced, optical anisotropy for blue phosphorene monolayer, caused exclusively by the quasi-particle effects. Finally, we show that some of the investigated nanoribbons show a spin-triplet excitonic insulator behavior, thus revealing exciting features of these nanoribbons and therefore provides important advances in the understanding of quasi-one dimensional phosphorus-based materials.
Real time conditioning monitoring of MOSFET using artificial neural network regression
Authors: Choudhary Khilawan , Babu Raja , Christie Latha , Mahto Manpuran 
Published: May 2024

Abstract
The metal–oxide–semiconductor field-effect transistor (MOSFET) is a critical semiconductor device widely used in electrical and electronic systems. The performance of systems depends on the component’s reliability. More than 30% of failures of electronic and electrical systems are due to MOSFET failure. Industries are paying more apprehension towards the improvement of MOSFET reliability. Temperature stress is one of the key parameters to examine the reliability performance of semiconductor devices and to predict the lifetime of the components. This article provides a quick analysis of the MOSFET degradation models. The primary failure precursor metric that reflects the level of degradation is the MOSFET on-resistance R
DS(on). In this paper, a linear, non-linear, and artificial neural network (ANN) deterioration model of MOSFETs is presented with the experimental data. The coefficient of determination (R-square), and root mean square error (RMSE) are used to compare the real data. Finally, it is demonstrated that the proposed model works well with experimental data. More than 500 data were trained for the proposed model. It can therefore predict the real-time conditioning monitoring of MOSFETs to increase the reliability of electrical systems.
The vertical accuracy improvement method considering gravitational anomaly for SINS/GNSS
Authors: Qin Fang-Jun , Qian Lei-Yuan , Li Kai-Long , Zhu Tian-Gao 
Published: May 2024

Abstract
Vertical information (vertical velocity and altitude) is important in three-dimensional navigation. In order to improve the vertical accuracy of strapdown inertial navigation system/global navigation satellite system integrated navigation (SINS/GNSS) while reducing costs, firstly, the propagation laws of vertical error sources in two types of SINS/GNSS (vertical velocity set to 0 and not set to 0) are systematically analyzed. Furthermore, a vertical accuracy improvement method considering the gravitational anomaly is proposed. In this method, the gravitational anomaly is considered as one of the vertical error sources. Then, the processing method of error sources in integrated navigation is referenced, and two processing modes of gravitational anomaly are designed. The first method is to represent the gravitational anomaly as one of the system states of SINS/GNSS. The number of dimensions for the system is expanded from 15 to 16. The corresponding mathematical model is derived to ‘absorb’ the vertical errors caused by the gravitational anomaly. The second is to represent the gravitational anomaly as one of the vertical system noises. Thereby, the Kalman filter is adjusted in real time using the above adaptive method to improve the accuracy of the estimated state. The corresponding errors are then suppressed. Field experiments show that both modes of the proposed method can effectively improve the vertical accuracy.
Introduction and application of a new approach for model-based optical bidirectional measurements
Authors: Krüger Jan , Manley Phillip , Bergmann Detlef , Köning Rainer , Bodermann Bernd , Eder Christian , Heinrich Andreas , Schneider Philipp-Immanuel , Hammerschmidt Martin , Zschiedrich Lin , Manske Eberhard 
Published: May 2024

Abstract
Accurate measurements of micro- and nanoscale features in optical microscopy demand comprehensive modelling approaches. In this study, we introduce an enhanced evaluation method, utilizing rigorous simulations based on a finite element method algorithm within an advanced Bayesian optimization framework. We provide an in-depth explanation of the measurement process, including the dimension reduction techniques applied to the acquired measurement data. Additionally, we employ Hopkins’ approximation or also referred to as local Hopkins’ methods for an efficient microscopic image simulation, resulting in a significant reduction of the computing time. We applied this method to measure the linewidths of six different chrome lines, nominally 300 nm–1000 nm wide, on a glass substrate. Our results show an excellent agreement with previous investigations conducted using various measurement systems, including atomic force microscopy, scanning electron microscopy, and optical microscopy in combination with different measurement evaluation techniques.
Ultra-long-term spatiotemporal feature fusion network for bearing remaining life prediction under strong interference
Authors: Yin Zhongxi , Tan Jinbiao , Wan Jiafu 
Published: May 2024

Abstract
Under high noise conditions and random impacts, which constitute strong interference, models often exhibit limited capability in capturing long-term dependencies, leading to lower accuracy in predicting the remaining useful life (RUL) of bearings. To address this issue, a spatiotemporal fusion network capable of ultra-long-term feature analysis is proposed to enhance the accuracy of bearing RUL prediction under substantial interference. This network utilizes a dilated convolution-based lightweight vision transformer encoder to extract spatial features reflecting the short-term degradation state of the bearing. Then, these features are sequentially fed into an adaptive tiered memory unit, based on the multiple attention mechanism and the neuron layering mechanism, to analyze temporal features indicative of long-term degradation. Subsequently, short-term spatial and long-term temporal features are fused for RUL prediction. To validate the robustness and predictive accuracy of the proposed approach under strong interference, a gearbox-rolling bearing accelerated platform is constructed, simulating high noise and random impact conditions. Experiments confirm the high robustness and predictive accuracy of the proposed method under strong interference conditions.
Crystal plasticity based constitutive model for deformation in metastable β titanium alloys
Authors: Christie P , Siddiq M A , Asim U B , McMeeking R M , Kartal M E 
Published: May 2024

Abstract
Due to attractive mechanical properties, metastable β titanium alloys have become very popular in many industries including aerospace, marine, biomedical, and many more. It is often the complex interplay among the different deformation mechanisms that produces many of the sought-after properties, such as enhanced ductility, super-elasticity, and shape memory effects. Stress induced martensitic transformation is an important deformation mechanism for these alloys. Understanding of it and the influence it has on the microstructural evolution of materials is of great importance. To this end we have developed a crystal plasticity based constitutive model which accounts for both martensitic phase transformation and slip based plasticity simultaneously in metastable

β

titanium alloys. We present a new formulation for the evolution of martensite transformation, based on physical principles and crystal plasticity theory. To understand and demonstrate this feature of the model, a parametric assessment of the newly developed constitutive model is conducted. This is followed by first of its kind analyses of stress induced martensitic transformation in metastable

β

titanium alloys. We firstly present validations against uniaxial loading experiments for different metastable

β

titanium alloys exhibiting stress induced martensite transformation. As part of this, single crystal simulations in metastable

β

titanium alloys are used for the first time to investigate the interaction of individual transformation systems during unconstrained transformation. This study shows good agreement between the experimental and simulated responses during all stages of deformation in which elastic, transformation and finally the slip stage are exhibited. Relatively ‘strong’ and ‘weak’ orientations for transformation are observed, consistent with experimental studies. The work done here demonstrates the ability of this crystal plasticity finite element method to capture physical mechanisms while bringing new insight about the interaction of different deformation mechanisms in metastable

β

titanium alloys.
A parylene/graphene UV photodetector with ultrahigh responsivity and long term stability
Authors: Huang Liting , Zhu Zhaowei , Cheng Chuantong , Gao Y 
Published: May 2024

Abstract
Long term stability, high responsivity, and fast response speed are essential for the commercialization of graphene photodetectors (GPDs). In this work, a parylene/graphene UV photodetector with long term stability, ultrahigh responsivity and fast response speed, is demonstrated. Parylene as a stable physical and chemical insulating layer reduces the environmental sensitivity of graphene, and enhances the performances of GPDs. In addition, utilizing bilayer electrodes reduces the buckling and damage of graphene after transferring. The parylene/graphene UV photodetector exhibits an ultrahigh responsivity of 5.82 × 105 AW−1 under 325 nm light irradiation at 1 V bias. Additionally, it shows a fast response speed with a rise time of 80 μs and a fall time of 17 μs, and a long term stability at 405 nm wavelength which is absent in the device without parylene. The parylene/graphene UV photodetector possesses superior performances. This paves the way for the commercial application of the high-performance graphene hybrid photodetectors, and provides a practical method for maintaining the long term stability of two dimensional (2D) materials.
Remarks on the smoothness of the

C

1
,
α

asymptotically self-similar singularity in the 3D Euler and 2D Boussinesq equations
Authors: Chen Jiajie 
Published: May 2024

Abstract
We show that the constructions of

C

1
,
α

asymptotically self-similar singularities for the three-dimensional (3D) Euler equations by Elgindi, and for the 3D Euler equations with large swirl and 2D Boussinesq equations with boundary by Chen-Hou can be extended to construct singularity with velocity

u

∈

C

1
,
α

that is not smooth at only one point. The proof is based on a carefully designed small initial perturbation to the blowup profile, and a BKM-type continuation criterion for the one-point nonsmoothness. We establish the criterion using weighted Hölder estimates with weights vanishing near the singular point. Our results are inspired by the recent work of Cordoba, Martinez-Zoroa and Zheng that it is possible to construct a

C

1
,
α

singularity for the 3D axisymmetric Euler equations without swirl and with velocity

u

∈

C

∞

(

R

3

∖
{
0
}
)

.
Human-like intelligent automatic treatment planning of head and neck cancer radiation therapy
Authors: Gao Yin , Kyun Park Yang , Jia Xun 
Published: May 2024

Abstract

Objective. Automatic treatment planning of radiation therapy (RT) is desired to ensure plan quality, improve planning efficiency, and reduce human errors. We have proposed an Intelligent Automatic Treatment Planning framework with a virtual treatment planner (VTP), an artificial intelligence robot built using deep reinforcement learning, autonomously operating a treatment planning system (TPS). This study extends our previous successes in relatively simple prostate cancer RT planning to head-and-neck (H&N) cancer, a more challenging context even for human planners due to multiple prescription levels, proximity of targets to critical organs, and tight dosimetric constraints. Approach. We integrated VTP with a real clinical TPS to establish a fully automated planning workflow guided by VTP. This integration allowed direct model training and evaluation using the clinical TPS. We designed the VTP network structure to approach the decision-making process in RT planning in a hierarchical manner that mirrors human planners. The VTP network was trained via the Q-learning framework. To assess the effectiveness of VTP, we conducted a prospective evaluation in the 2023 Planning Challenge organized by the American Association of Medical Dosimetrists (AAMD). We extended our evaluation to include 20 clinical H&N cancer patients, comparing the plans generated by VTP against their clinical plans. Main results. In the prospective evaluation for the AAMD Planning Challenge, VTP achieved a plan score of 139.08 in the initial phase evaluating plan quality, and 15 min of planning time with the first place ranking in the adaptive phase competing for planning efficiency while meeting all plan quality requirements. For clinical cases, VTP-generated plans achieved an average VTP score of

125.33
±
11.12

, which outperformed the corresponding clinical plans with an average score of

117.76
±
13.56

. Significance. We successfully integrated VTP with the clinical TPS to achieve a fully automated treatment planning workflow. The compelling performance of VTP demonstrated its potential in automating H&N cancer RT planning.
Innovations in dedicated PET instrumentation: from the operating room to specimen imaging
Authors: Arabi Hossein , Manesh Abdollah Saberi , Zaidi Habib 
Published: May 2024

Abstract
This review casts a spotlight on intraoperative positron emission tomography (PET) scanners and the distinctive challenges they confront. Specifically, these systems contend with the necessity of partial coverage geometry, essential for ensuring adequate access to the patient. This inherently leans them towards limited-angle PET imaging, bringing along its array of reconstruction and geometrical sensitivity challenges. Compounding this, the need for real-time imaging in navigation systems mandates rapid acquisition and reconstruction times. For these systems, the emphasis is on dependable PET image reconstruction (without significant artefacts) while rapid processing takes precedence over the spatial resolution of the system. In contrast, specimen PET imagers are unburdened by the geometrical sensitivity challenges, thanks to their ability to leverage full coverage PET imaging geometries. For these devices, the focus shifts: high spatial resolution imaging takes precedence over rapid image reconstruction. This review concurrently probes into the technical complexities of both intraoperative and specimen PET imaging, shedding light on their recent designs, inherent challenges, and technological advancements.
Modeling and analysis of a hydraulic electric energy harvesting suspension
Authors: Liu Xujin , Kang Shuangyuan , Wu Zhifei 
Published: May 2024

Abstract
To enhance the performance of the hydraulic electric energy harvesting suspension, several steps were taken. Firstly, a resistance feedback control strategy was proposed in this paper based on the controllable damping characteristics. Subsequently, a model of the suspension was established based on its structure and working principle. And a simulation model was created, the tracking effect of current as well as the enhancement of suspension performance, were investigated to preliminarily validate the effectiveness of the control strategy. Finally, a bench test was conducted to verify the proposed strategy. Experimental results demonstrated that the peak harvesting can reach about300 W, and the average is 190.3 W. The vertical acceleration of the body in the hydraulic electric energy harvesting suspension decreased by 18.01% when employing the control strategy compared to the passive suspension.
Decoding trust: a reinforcement learning perspective
Authors: Zheng Guozhong , Zhang Jiqiang , Zhang Jing , Cai Weiran , Chen Li 
Published: May 2024

Abstract
Behavioral experiments on the trust game have shown that trust and trustworthiness are commonly seen among human beings, contradicting the prediction by assuming Homo economicus in orthodox Economics. This means some mechanism must be at work that favors their emergence. Most previous explanations, however, need to resort to some exogenous factors based upon imitative learning, a simple version of social learning. Here, we turn to the paradigm of reinforcement learning, where individuals revise their strategies by evaluating the long-term return through accumulated experience. Specifically, we investigate the trust game with the Q-learning algorithm, where each participant is associated with two evolving Q-tables that guide one’s decision-making as trustor and trustee, respectively. In the pairwise scenario, we reveal that high levels of trust and trustworthiness emerge when individuals appreciate both their historical experience and returns in the future. Mechanistically, the evolution of the Q-tables shows a crossover that resembles human psychological changes. We also provide the phase diagram for the game parameters, where the boundary analysis is conducted. These findings are robust when the scenario is extended to a latticed population. Our results thus provide a natural explanation for the emergence of trust and trustworthiness, and indicate that the long-ignored endogenous factors alone are sufficient to drive. More importantly, the proposed paradigm shows the potential to decipher many puzzles in human behaviors.