bluuebunny/crossref_metadata_2025_split huggingface dataset:
A comparative study on automatic treatment planning for online adaptive proton therapy of esophageal cancer: which combination of deformable registration and deep learning planning tools performs the best?
Authors: Draguet C , Populaire P , Vera M Chocan , Fredriksson A , Haustermans K , Lee J A , Barragán-Montero A M , Sterpin E 
Published: September 2024

Abstract

Objective. To demonstrate the feasibility of integrating fully-automated online adaptive proton therapy strategies (OAPT) within a commercially available treatment planning system and underscore what limits their clinical implementation. These strategies leverage existing deformable image registration (DIR) algorithms and state-of-the-art deep learning (DL) networks for organ segmentation and proton dose prediction. Approach. Four OAPT strategies featuring automatic segmentation and robust optimization were evaluated on a cohort of 17 patients, each undergoing a repeat CT scan. (1) DEF-INIT combines deformably registered contours with template-based optimization. (2) DL-INIT, (3) DL-DEF, and (4) DL-DL employ a nnU-Net DL network for organ segmentation and a controlling ROIs-guided DIR algorithm for internal clinical target volume (iCTV) segmentation. DL-INIT uses this segmentation alongside template-based optimization, DL-DEF integrates it with a dose-mimicking (DM) step using a reference deformed dose, and DL-DL merges it with DM on a reference DL-predicted dose. All strategies were evaluated on manual contours and contours used for optimization and compared with manually adapted plans. Key dose volume metrics like iCTV D98% are reported. Main results. iCTV D98% was comparable in manually adapted plans and for all strategies in nominal cases but dropped to 20 Gy in worst-case scenarios for a few patients per strategy, highlighting the need to correct segmentation errors in the target volume. Evaluations on optimization contours showed minimal relative error, with some outliers, particularly in template-based strategies (DEF-INIT and DL-INIT). DL-DEF achieves a good trade-off between speed and dosimetric quality, showing a passing rate (iCTV D98% > 94%) of 90% when evaluated against 2, 4 and 5 mm setup error and of 88% when evaluated against 7 mm setup error. While template-based methods are more rigid, DL-DEF and DL-DL have potential for further enhancements with proper DM algorithm tuning. Significance. Among investigated strategies, DL-DEF and DL-DL demonstrated promising within 10 min OAPT implementation results and significant potential for improvements.
DBAII-Net with multiscale feature aggregation and cross-modal attention for enhancing infant brain injury classification in MRI
Authors: Jia Zhen , Huang Tingting , Li Xianjun , Bian Yitong , Wang Fan , Yuan Jianmin , Xu Guanghua , Yang Jian 
Published: September 2024

Abstract

Objectives. Magnetic resonance imaging (MRI) is pivotal in diagnosing brain injuries in infants. However, the dynamic development of the brain introduces variability in infant MRI characteristics, posing challenges for MRI-based classification in this population. Furthermore, manual data selection in large-scale studies is labor-intensive, and existing algorithms often underperform with thick-slice MRI data. To enhance research efficiency and classification accuracy in large datasets, we propose an advanced classification model. Approach. We introduce the Dual-Branch Attention Information Interactive Neural Network (DBAII-Net), a cutting-edge model inspired by radiologists’ use of multiple MRI sequences. DBAII-Net features two innovative modules: (1) the convolutional enhancement module (CEM), which leverages advanced convolutional techniques to aggregate multi-scale features, significantly enhancing information representation; and (2) the cross-modal attention module (CMAM), which employs state-of-the-art attention mechanisms to fuse data across branches, dramatically improving positional and channel feature extraction. Performances (accuracy, sensitivity, specificity, area under the curve (AUC), etc) of DBAII-Net were compared with eight benchmark models for brain MRI classification in infants aged 6 months to 2 years. Main results. Utilizing a self-constructed dataset of 240 thick-slice brain MRI scans (122 with brain injuries, 118 without), DBAII-Net demonstrated superior performance. On a test set of approximately 50 cases, DBAII-Net achieved average performance metrics of 92.53% accuracy, 90.20% sensitivity, 94.93% specificity, and an AUC of 0.9603. Ablation studies confirmed the effectiveness of CEM and CMAM, with CMAM significantly boosting classification metrics. Significance. DBAII-Net with CEM and CMAM outperforms existing benchmarks in enhancing the precision of brain MRI classification in infants, significantly reducing manual effort in infant brain research. Our code is available at https://github.com/jiazhen4585/DBAII-Net.
Modeling magnetic field amplification in supernova remnants driven by laser
Authors: Sun Wei , Lv Chong , Lei Zhu , Ping Yongli , Jin Mengqi , Tian Baoxian , Feng Li , Ren Can , He Cuhangye , Wang Zhao , Zhong Jiayong 
Published: September 2024

Abstract
The origin of magnetic fields and their amplification have always been hot topics in fields such as astrophysics and high-energy-density physics. Among them, the turbulent dynamo effect is an important candidate mechanism, and the interaction between supernova remnants (SNRs) is an important carrier for studying the amplification effect of turbulent magnetic fields. In this paper, we use the radiation magnetohydrodynamic simulation program to carry out a scaling simulation study on the amplification effect of turbulent magnetic fields in the interaction of SNRs driven by powerful lasers. We investigate and compare the evolution of turbulence under different laser driving methods, different directions, and different intensities of initial external environmental magnetic fields. Here, we carefully identify the contributions of Biermann self-generated magnetic fields and environmental magnetic fields in the process of magnetic field amplification, present magnetic energy spectra, and magnetic field amplification factors, and analyze the influence of radiative cooling effect on turbulence and magnetic field evolution. The results show that the collision direction component of the environmental magnetic field dominates the process of magnetic field amplification, and the frequency spectrum of turbulence is consistent with Kolmogorov’s law. The research results are necessary for sorting out and elucidating the physical mechanism of magnetic field amplification in SNRs, and have reference significance for regulating turbulence in strong magnetic fields in the future.
Design of piezoelectric quasi— zero—stiffness metastructures for improved low—frequency vibration isolation
Authors: Jiang Shouqian , Liu Zhiyuan , Yi Kaijun , Zhu Rui , Kovacic Ivana 
Published: September 2024

Abstract
In this paper, a novel type of piezoelectric quasi–zero stiffness (QZS) metastructure is proposed and the improved vibration isolation performance is investigated. A piezoelectric QZS metastructure is composed of curved beams covered with piezoelectric macro–fiber composite patches, to which digital circuits are connected. Based on the principle of minimum potential energy and the mode superposition method, the constrain on the geometry and material parameters of the piezo–curved beams to achieve QZS is given. According to this design criterion, 1D, 2D and 3D piezoelectric QZS metastructures are designed, and their improved low–frequency vibration isolation characteristics are comprehensively analyzed through theoretical, numerical and experimental studies. It is demonstrated that by optimizing the parameters of the resonant transfer functions implemented in the digital circuits, high–level damping localized near the first resonant peak can be introduced into the curved beams. As a result, the resonant peaks of the metastructures can be reduced without compromising the isolation performance beyond those peaks.
Design and manufacture of an ultra-compact, 1.5 T class, controlled-contact resistance, REBCO, brain imaging MRI magnet
Authors: Parkinson B , Bouloukakis K , Weijers H W , Olatunji J , Szmigiel M , Hunter M W , Froelich T , Bailey J , Garwood M 
Published: September 2024

Abstract
Brain imaging MRI comprises a significant proportion of MRI scans, but the requirement for including the shoulders in the magnet bore means there is not a significant size reduction in the magnet compared to whole-body magnets. Here we present a new design approach for brain imaging MRI magnets targeting ±20 kHz B
0 variation over the imaging volume rather than the more usual ±200 Hz making use of novel high-bandwidth MRI pulse sequences and distortion correction. Using this design approach, we designed and manufactured a 1.5 T class ReBCO cryogen-free magnet. The magnet is dome-like in form, completely excludes the shoulders and is <400 mm long. The magnet was wound using no-insulation style coils with a conductive epoxy encapsulant where the contact resistance of the coils was controlled so the emergency shut-down time of the magnet was less than 30 s. Despite acceptable coil testing results ahead of manufacture, during testing of the magnet, several of the epoxy coils showed signs of damage limiting stable performance to <55 A compared to the designed 160 A. These coils were replaced with insulated paraffin encapsulated coils. Subsequently the magnet was re-ramped and was stable at 81 A, generating 0.71 T as several other coils had sustained damage not visible in the first magnet iteration. The magnet has been passive shimmed to ±20 kHz B
0 variation over the imaging volume and integrated into an MRI scanner. The stability of the magnet has been evaluated and found to be acceptable for MRI.
Quantum multiphoton Rabi oscillations in waveguide QED
Authors: Mukhopadhyay Debsuvra , Shen Jung-Tsung 
Published: September 2024

Abstract
The future of quantum information processing hinges on chip-scale nanophotonics, specifically cavity QED and waveguide QED. One of the foremost processes underpinning quantum photonic technologies is the phenomenon of Rabi oscillations, which manifests when a qubit is irradiated by an intense laser source. Departing from the conventional semiclassical framework, we explore the more general, quantum theoretical case where the optical excitation takes the form of a multiphoton Fock state, and the qubit couples to a continuum of radiation modes. By employing the real-space formalism, we analytically explore the scattering dynamics of the photonic Fock state as it interfaces with a two-level emitter. The resulting amplitude for atomic excitation features a linear superposition of various independent scattering events that are triggered by the potential of sequential, time-delayed photon absorptions and emissions. The lowest-order excitation event, initiated by the stochastic scattering of one of the several photons, appropriately characterizes the dynamics in a weak-field environment. This event is complemented by a multitude of higher-order scattering events ensuing from repeated atom–photon interactions. The temporal evolution of the qubit excitation in our configuration closely mirrors the semiclassical predictions, particularly in the strong-pumping limit where Rabi oscillations unfold. Notably, this compatibility with the semiclassical paradigm transcends beyond the strong-excitation regime and applies both to the weak-driving and large-detuning limits. In a nutshell, our analysis extends the existing results on quantum Rabi oscillations pertinent to single-mode cavity QED, to the multimode, waveguide-QED configurations wherein flying photons are the information carriers. Additionally, we delve into the dynamics of pulsed wave packets, shedding light on the potential to substantially enhance excitation efficiency, even in scenarios involving just a few photons. Beyond their theoretical merit, these findings should hold practical relevance for future Fock-state-based quantum computing and emerging waveguide-integrated photonic technologies such as those involving superconducting circuitry.
Unbounded entropy production and violent fragmentation for repulsive-to-attractive interaction quench in long-range interacting systems
Authors: Molignini Paolo , Chakrabarti Barnali 
Published: September 2024

Abstract
We study the non-equilibrium dynamics of a one-dimensional Bose gas with long-range interactions that decay as

(

1

r

α

)

(
0.5
<
α
<
4.0

). We investigate exotic dynamics when the interactions are suddenly switched from strongly repulsive to strongly attractive, a procedure known to generate super-Tonks-Girardeau gases in systems with contact interactions. We find that relaxation is achieved through a complex intermediate dynamics demonstrated by violent fragmentation and chaotic delocalization. We establish that the relaxed state exhibits classical gaseous characteristics and an asymptotic state associated with unbounded entropy production. The phase diagram shows an exponential boundary between the coherent (quantum) gas and the chaotic (classical) gas. We show the universality of the dynamics by also presenting analogous results for spinless fermions. Weaker quench protocols give a certain degree of control over the relaxation process and induce a slower initial entropy growth. Our study showcases the complex relaxation behavior of tunable long-range interacting systems that could be engineered in state-of-the-art experiments, e.g. in trapped ions or Rydberg atoms.
Cooperative engulfment of nanoparticles by membranes and vesicles
Authors: Bahrami Arash , Bahrami Amir H 
Published: September 2024

Abstract
Cellular uptake and expulsion of nanoparticles and viruses often involves a substantial particle concentration at the cell membrane. These particles, many of which are distributed across the cell at relatively large distances, cooperate to enter or exit the cell, highlighting the importance of engulfment cooperativity. Here, we explore the cooperative entry and exit of two and multiple distant nanoparticles to and from curved vesicles, representing cellular endocytosis and exocytosis, respectively. We discover indirect engulfment cooperativity between distant nanoparticles wrapped by vesicles, driven by vesicle curvature, which is absent for particles engulfed by a flat bilayer. For the cooperative entry of two identical particles into the vesicle, we identify a counter-intuitive symmetry-breaking in which one fully-engulfed and one non-engulfed particle is more likely than two fully-engulfed or two non-engulfed particles. As a result, with a high concentration of closely-sized external particles, only half of the particles are expected to be successfully internalized by the vesicle, while the remaining half remains unwrapped, and partially engulfed particles are unlikely. In contrast, the cooperative exit of internal particles from the vesicle is characterized by the simultaneous partial engulfment of the particles that are continuously wrapped by the vesicle. This explains how evolution has harnessed membrane curvature for the simultaneous budding of multiple viral particles, a crucial step in viral infection. Our findings for the cooperative entry of multiple particles have significant implication for achieving efficient drug concentration in drug delivery applications.
2D Skyrmion topological charge of spin textures with arbitrary boundary conditions: a two-component spinorial BEC as a case study
Authors: Sánchez-Reséndiz S , Neri E , González-Hernández S , Romero-Rochín V 
Published: September 2024

Abstract
We derive the most general expression for the Skyrmion topological charge for a two-dimensional spin texture, valid for any type of boundary conditions or for any arbitrary spatial region within the texture. It reduces to the usual one for the appropriate boundary conditions. The general expression resembles the Gauss-Bonet theorem for the Euler-Poincaré characteristic of a 2D surface, but it has definite differences, responsible for the assignment of the proper signs of the Skyrmion charges. Additionally, we show that the charge of a single Skyrmion is the product of the value of the normal component of the spin texture at the singularity times the Index or winding number of the transverse texture, a generalization of a Poincaré theorem. We illustrate our general results analyzing in detail a two-component spinor Bose–Einstein condensate (BEC) in 2D in the presence of an external magnetic field, via the Gross-Pitaevskii equation. The condensate spin textures present Skyrmions singularities at the spatial locations where the transverse magnetic field vanishes. We show that the ensuing superfluid vortices and Skyrmions have the same value for their corresponding topological charges, in turn due to the structure of the magnetic field.
Study of nonlinear optical properties of ZnCo2O4/GQD nanocomposite and their correlation with microstructure
Authors: Ebrahimi Mahdi , Sadeghi Farzad , Soleimanian Vishtasb , Ghasemi Mohsen , Nekoeinia Mohsen 
Published: September 2024

Abstract
In this study, ZnCo2O4/Graphene quantum dots (ZCO/GQDs) nanocomposite was fabricated by carbonization and hydrothermal methods in four volume ratios (40.0 ml/0.0, 37.5 ml/2.5 ml, 35.0 ml/5.0 ml, and 32.5 ml /7.5 ml) of ZCO/GQD where the total volume was fixed at 40 ml. To characterize the structural, morphological, and optical properties of the nanocomposites, x-ray diffraction, scanning electron microscopy, energy dispersive x-ray, UV-visible spectrometry, and Z-scan analysis were conducted. The variance and Williamson-Smallman methods were applied to calculate the microstructure features. The results illustrate that the crystallite size and strain are minimum while the dislocation density has a maximum value for 37.5 ml/2.5 ml of volume ratio. Band gap and nonlinear optical coefficients were obtained by Tauc and Z-scan techniques and the results show they are maximum in this ratio. These results confirm a correlation between microstructure and optical properties. Such a correlation can be applied to improve the optoelectronic applications of the nanocomposite.
Transport mechanism investigation of β-Ga2O3 based fin-shape heterojunction PN diodes
Authors: Liu Peng , He Yunlong , Lu Xiaoli , Wang Xichen , Song Xianqiang , Sheng Baisong , Chen Weiwei , Wang Lei , Yang Jun , Wang Zhan , Li Yuan , Zheng Xuefeng , Ma Xiaohua , Hao Yue 
Published: September 2024

Abstract
This paper proposes a new type of Fin-shape Ga2O3 heterojunction PN diode (Fin-PND), it not only maintains a high breakdown voltage, but also increases the current density, thereby reducing the on-resistance. The conventional Schottky barrier diode (SBD) and PN diode (PND) are also prepared for comparison. The I-V characteristics, breakdown characteristics, and temperature stability of these three devices have been studied. It has been found that the Fin-PND has a lower turn-on voltage of 2.05 V due to the lower ND caused by Cl-based etching. Furthermore, the Fin-PND has a higher current density of 692.1 A cm−2 and specific on-resistance (Ron,sp) of 7.31 mΩ·cm2 compared to the conventional PND. In addition, the breakdown voltage of the Fin-PND is similar to that of the PND and higher than that of the SBD, reaching a value of 2380 V. The Fin-PND overcomes the contradiction of the current density rising at the expense of the breakdown voltage. Moreover, under the same variable temperature test conditions, the Fin-PND shows more favorable temperature stability.
Effects of PEO and BN-PVD coatings on the wear, corrosion, and surface properties of AZ31 magnesium alloy
Authors: Senocak Taha Cagri 
Published: September 2024

Abstract
This study investigates the effects of Plasma Electrolytic Oxidation (PEO) and subsequent Boron Nitride (BN) coatings applied via Physical Vapor Deposition (PVD) on the wear, corrosion, and surface properties of AZ31 magnesium alloy. The AZ31 alloy samples were first coated using the PEO process, forming a ceramic-like layer that enhances surface properties. However, inherent microcracks and pores in PEO coatings can compromise corrosion resistance. To mitigate these issues, a BN layer was applied over the some of PEO coating using RF-PVD, significantly improving wear resistance, corrosion protection, and surface integrity. The coatings were characterized using x-ray diffraction (XRD), scanning electron microscopy (SEM), x-ray photoelectron spectroscopy (XPS), and electrochemical testing. The results indicate that the PEO-BN coatings provide the highest wear resistance, lowest friction coefficient, and most effective barrier against corrosion among the samples tested. These findings highlight the potential of PEO-BN coatings to enhance the durability and performance of magnesium alloys, making them suitable for demanding applications.
Extreme multi-stability and circuit implementation for a two-ReLU-memristor-based jerk oscillator
Authors: Lu Rending , Chen Zhuguan , Lu Haikong , Bao Bocheng 
Published: September 2024

Abstract
Memristor-based oscillation circuits are prone to produce coexisting infinite attractors depending on the initial conditions of memristors, leading to the appearance of extreme multi-stability. In this paper, we propose a novel memristive jerk oscillator by bringing two ReLU-type memristors in a simple jerk oscillator and investigate its dynamical behaviors associated with the coupling parameters using bifurcation plots and Lyapunov exponent plots. Further, we discuss the planar equilibrium state and its stability, and then numerically explore the coexisting infinite attractors driven by the initial conditions of two ReLU-type memristors. Because of the intervention of the two ReLU-type memristors, the memristive jerk oscillator has a planar equilibrium state whose stability closely relies on the initial conditions of two ReLU-type memristors, and different initial conditions cause different attractors to coexist, resulting in bidirectional extreme multi-stability. Finally, the memristive jerk oscillator is implemented by analog circuit and digital hardware platform, and the numerical results are confirmed by circuit simulations and hardware experiments.
Quantum superposing algorithm for quantum encoding
Authors: Kim Jaehee , Kim Taewan , Baek Kyunghyun , Hwang Yongsoo , Huh Joonsuk , Bang Jeongho 
Published: September 2024

Abstract
Efficient encoding of classical data into quantum state—currently referred to as quantum encoding—holds crucial significance in quantum computation. For finite-size databases and qubit registers, a common strategy of the quantum encoding entails establishing a classical mapping that correlates machine-recognizable data addresses with qubit indices that are subsequently superposed. Herein, the most imperative lies in casting an algorithm for generating the superposition of any given number of qubit indices. This algorithm is formally known as quantum superposing algorithm. In this work, we present an efficient quantum superposing algorithm, affirming its effectiveness and superior computational performance in a practical quantum encoding scenario. Our theoretical and numerical analyses demonstrate a substantial enhancement in computational efficiency compared to existing algorithms. Notably, our algorithm has a maximum of 2n − 3 controlled-not (CNOT) counts, representing the most optimized result to date.