bluuebunny/crossref_metadata_2025_split huggingface dataset:
Time-dependent quantum/continuum modeling of plasmon-enhanced electronic circular dichroism
Authors: Biancorosso L. , D’Antoni P. , Corni S. , Stener M. , Coccia E. 
Published: December 2024

In this work, we present a multiscale real-time approach to study the plasmonic effects of a metal nanoparticle (NP) on the electronic circular-dichroism (ECD) spectrum of a chiral molecule interacting with it. The method is based on the time-evolution of the molecule’s time-dependent wavefunction, expanded in the eigenstates of a perturbed Hamiltonian. A quantum description of the molecular system is coupled to a classical representation of the NP via a continuum model. The method is applied to methyloxirane and peridinin at various distances (1, 3, and 5 nm) with respect to a gold NP surface. While no remarkable effect is observed for methyloxirane at any studied distance, an enhancement appears when the peridinin lies at 1 nm and the pulse is linearly polarized perpendicularly to the molecular axis, with the ECD signal centered at 4.1 eV increased by a factor of around 20. These results are rationalized looking at the gap between the plasmonic peak of the NP at around 2.5 eV and the molecular excitations: the smaller the gap between molecular and plasmonic excitations, the larger the plasmonic enhancement of the ECD signal. Moreover, ECD peaks are selectively enhanced due to the favorable coupling between the pulse polarization and the combined effect of electric and magnetic dipole moments. This approach allows one to go through the electronic structure and dynamics of chiral molecules for obtaining a realistic description of plasmon-mediated ECD spectra, e.g., paving the way to applications to molecules of biological relevance interacting with nanostructures of experimental interest.
Reporting Indigenous status, ethnicity, language and country of birth to build equity in international paediatric clinical trials with Australian sites: a scoping review
Authors: Cunninghame Jacqueline , Takashima Mari , Holland Lorelle , Nguyen Linda , Diaz Abbey , Guo Shuaijun , Dufficy Mitchell , Munns Craig F. , Ullman Amanda 
Published: December 2024

Objective Ensuring equitable access to clinical trials for children from Indigenous and ethnically and linguistically diverse backgrounds should be central to clinical trial design. This review aims to expansively review the reporting of Indigenous status (Aboriginal and/or Torres Strait Islander origin), ethnicity, culture, location, language and country of birth in paediatric clinical trials with Australian sites. Methods This scoping review systematically searched PubMed, CINAHL and Embase for international clinical trials with Australian sites conducted between 2018 and 2022 involving children (aged <18 years) to determine the reporting of Indigenous status, race, ethnicity, language and country of birth. Results Of the 262 studies included, 154 (58.8%) clinical trials did not report any of the variables of interest. When reported, terms used by authors were heterogeneous. ‘Indigenous status’ was most reported (n = 40, 15.3%) and self-identification was the most common method to determine this (n = 14, 35.9%). International clinical trials had higher rates of reporting for ethnicity, cultural background and race. Overall, more than 60 terms were used to categorise study participants in relation to ‘Indigenous status’, 'ethnicity and cultural background', ‘race’, ‘race and ethnicity’ or ‘natural skin colour’. Conclusions This review demonstrated low rates of reporting of demographic variables in paediatric clinical trials. Clear reporting standards, partnering with consumers to co-design trials and self-identification during collection are required. Ensuring adequate access to clinical trials for Indigenous children and children from ethnically, linguistically and geographically diverse backgrounds is essential in building health equity and ensuring patient safety.
Authorship, ownership, and ethics in datafied discourse on Instagram
Authors: McInerney Erin 
Published: December 2024

Abstract
Datafication, or the translation of our everyday actions into quantifiable metrics, underwrites a wide set of
contemporary discursive practices. With a specific focus on the social media platform Instagram, this paper analyzes mediatized
landscape signs as ‘datafied discourse’ enmeshed in an entangled apparatus of platforms, algorithms, and online networks. Using a
corpus of 404 public Instagram posts gathered from the Café de Flore geotag, I examine how the vernacular practices of geotagging,
mediatization, and remediatization reflexively construct this ostensibly ‘user-generated’ landscape. I then consider the
implications of these and other discursive practices occurring at the ‘online-offline nexus’ through the dimensions of authorship
and ownership. Finally, amid a confluence of new LL work, I propose to orient scholarship toward an ‘infrastructural’ perspective,
in which datafication, online platforms, and algorithms are understood to exert considerable influence over our landscapes, thus
emerging as relevant to scholars engaged in any genre of LL analysis.
Noncommutative lightcones from quantum SO(2,1) conformal groups
Authors: Adamo Martina , Ballesteros Angel , Mercati Flavio 
Published: December 2024

Abstract
Five new families of noncommutative lightcones in

2
+
1

dimensions are presented as quantizations of the inequivalent Poisson homogeneous structures that emerge when the lightcone is constructed as a homogeneous space of the SO(2,1) conformal group. Each of these noncommutative lightcones maintains covariance under the action of the respective quantum deformation of the SO(2,1) conformal group. We discuss the role played by SO(2,1) automorphisms in the classification of inequivalent Poisson homogeneous lightcones, as well as the geometric aspects of this construction. The localization properties of the novel quantum lightcones are analyzed and shown to be deeply connected with the geometric features of the Poisson homogeneous spaces.
Estimating the internal friction and the rotational inertia of a homemade oscillatory system
Authors: Santos D S , Bispo P A B , Júnior D A S V , Rego V V A , Pereira L O , Dutra R S 
Published: December 2024

Abstract
In this work, we apply the dynamics of translation and rotation to a real system-a homemade mass-spring system composed of a cart-in which the rolling without slipping constraint of the cart's wheels may be violated at any moment. In this case, we demonstrate how modeling combined with video analysis can be powerful in determining the constraint forces acting on the system. In this case, the translational and rotational accelerations are determined, and the temporal behavior of all constraint forces can be identified. Initially, we show how rotations with slipping of the cart's wheels at the return points of the system's motion impact the system's kinematics. Finally, we apply the developed methodology to estimate the system's internal friction and rotational inertia. The estimates are compared with results from the literature and with a theoretical limit, in the case of rotational inertia, achieving good agreement.
Theory and fast learned solver for

ℓ

1

-TV regularization
Authors: Liu Xinling , Wang Jianjun , Jin Bangti 
Published: December 2024

Abstract
The

ℓ

1

and total variation (TV) penalties have been used successfully in many areas, and the combination of the

ℓ

1

and TV penalties can lead to further improved performance. In this work, we investigate the mathematical theory and numerical algorithms for the

ℓ

1

-TV model in the context of signal recovery: we derive the sample complexity of the

ℓ

1

-TV model for recovering signals with sparsity and gradient sparsity. Also we propose a novel algorithm (PGM-ISTA) for the regularized

ℓ

1

-TV problem, and establish its global convergence and parameter selection criteria. Furthermore, we construct a fast learned solver (LPGM-ISTA) by unrolling PGM-ISTA. The results for the experiment on ECG signals show the superior performance of LPGM-ISTA in terms of recovery accuracy and computational efficiency.
W-state generation and verification in linearly coupled waveguide arrays
Authors: Bugarski Kolja , Maluckov Aleksandra , Petrovic Jovana 
Published: December 2024

Abstract
W states are maximally entangled states with excellent robustness to loss. They have been studied in ion, photon and waveguide-mode bases, however the entanglement verification has remained challenging. Here, we theoretically study W-state generation by the quantum walk of a single photon through a linearly coupled waveguide array (WGA) that supports self-imaging of light. We design W states in symmetric and asymmetric arrays with even and odd number of waveguides. Bipartite entanglement is formally proven using the von Neumann entropy of the reduced density matrix. We further use the self-imaging to construct an entanglement witness based on the exclusion principle. A key to verification is the interferometer which extends the length of a W-state generator to the revival length where the photon is fully recombined into a single waveguide mode. In addition, W-state coherence is proven by numerically demonstrating the far-field interference. The sensitivities of the proposed W-state generation and verification protocols to the fabrication tolerances are numerically evaluated in glass, silicon nitride and silicon-on-insulator WGAs, indicating the feasibility of their realisation by high-precision e-beam lithography and laser writing.
A method to determine the phase-space distribution of a pulsed molecular beam
Authors: Mooij Maarten C , Bethlem Hendrick L , Boeschoten Alexander , Borschevsky Anastasia , Fikkers Ties H , Hoekstra Steven , van Hofslot Joost W F , Jungmann Klaus , Marshall Virginia R , Meijknecht Thomas B , Timmermans Rob G E , Touwen Anno , Ubachs Wim , Willmann Lorenz ,   (NL-eEDM collaboration)
Published: December 2024

Abstract
We demonstrate a method to determine the longitudinal phase-space distribution of a cryogenic buffer gas cooled beam of barium-fluoride molecules based on a two-step laser excitation scheme. Temporal resolution is achieved by a transversely aligned laser beam that drives molecules from the ground state

X
2

Σ
+

to the

A
2

Π

1

/

2

state around 860  nm, while the velocity resolution is obtained by a laser beam that is aligned counter-propagating with respect to the molecular beam and that drives the Doppler shifted

A
2

Π

1

/

2

to

D
2

Σ
+

transition around 797  nm. Molecules in the D-state are detected background-free by recording the fluorescence from the D − X transition at 413 nm. A temporal resolution of 11  μs and a velocity resolution of 6  m s−1 is obtained. In order to calibrate the absolute velocity, we have determined the Doppler free transition frequencies for the X − A and X − D transitions with an absolute accuracy below 0.3  MHz. The high resolution of the phase-space distributions allows us to observe a variation of the average velocity and velocity spread over the duration of the molecular beam pulse. Our method hence gives valuable insight into the dynamics in the source.
Quantum state transfer in a magnetic atoms chain using a scanning tunneling microscope
Authors: Acosta Coden Diego Sebastian , Osenda Omar , Ferrón Alejandro 
Published: December 2024

Abstract
The electric control of quantum spin chains has been an outstanding goal for the few last years due to its potential use in technologies related to quantum information processing. In this work, we show the feasibility of the different steps necessary to perform controlled quantum state transfer and excitation transmission in a

S
=
1

/

2

titanium atoms chain employing the electric field produced by a scanning tunneling microscope (STM). Our results show that the initialization and transmission of a single excitation state is achievable in short times, and with high fidelity. Our study uses spin Hamiltonians to model the magnetic atoms chain, the tip of the STM, the interaction between it and the atoms chain and the electronic response to the fields applied by the tip, employing sets of parameters compatible with the latest experiments and ab initio calculations. The time dynamical evolution is considered in the full Hilbert space and the control pulses frequencies exerted by the tip of the microscope are within the reach of present day technology.
Effect of Fe doping on the electronic properties of CoSn Kagome semimetal
Authors: Vijay Kritika , Ali Kawsar , Bano Najnin , Ahlawat Anju , Gupta Mukul , Choudhary Ram Janay , Shukla D K , Arya Ashok , Banik Soma 
Published: December 2024

Abstract
Quantum phenomena in two-dimensional Kagome materials lead to exotic topological states and complex magnetism. Here, we have investigated the detailed electronic properties of Co

1
−
x

Fe
x
Sn as a function of composition (x) to explore the competing electronic interactions for the origin of complex magnetism and topological properties. We find that the screening effect in the valence electrons increases while the correlation effect decreases with an increase in the Fe doping. Valence fluctuations observed at Co and Fe L

2
,
3

edges showed systematic changes in the magnitude of divalent and trivalent states with the increase in x. Fe 3d states are found to be more screened by the conduction electrons than the Co 3d states. A comparison of the theoretical and experimental density of states showed different natures of localized states with strong screening effects on the surface and dominating correlation effects in the bulk for x

>

0. We have observed localized flat bands on the CoSn (001) surface while quasi-localized flat bands on the Co0.94Fe0.06Sn (001) surface. The distinct character of the bulk and surface band structure is confirmed in the Fe-doped composition. Hence, the bulk-surface interaction present in Co

1
−
x

Fe
x
Sn gives rise to the origin of valence fluctuation, complex magnetism, and topological properties.
Adaptive evolutionary neural architecture search based on one-dimensional convolutional neural network for electric rudder fault diagnosis
Authors: Shi Xinjie , Guo Chenxia , Yang Ruifeng , Song Yizhe 
Published: December 2024

Abstract
The electric rudder is the core actuator of the flight control system. Fault diagnosis of rudders is essential for the production and repair of rudders. While existing methods for rudder fault diagnosis are effective, the manual design of neural network models is a time-consuming and challenging process. Therefore, this paper proposes a fault diagnosis framework for the electric rudder based on an adaptive evolutionary neural architecture search (AENAS-FD). AENAS-FD employs an adaptive strategy to guide the evolution of a one-dimensional convolutional neural network towards achieving optimal diagnostic accuracy. This adaptive strategy adjusts the relevant parameters of the genetic operator based on the relationship between individual and population fitness. This leads to improved algorithm search performance and mitigates premature convergence. The experiments on the real electric rudder dataset demonstrate that AENAS-FD can generate superior network architectures for diagnosing rudder faults, exhibiting better diagnostic accuracy when compared to manually designed networks.
Detection method for microleakage acoustic wave signals in natural gas pipelines based on chaotic oscillators
Authors: Chen Hongyu , Yi Kang , Cai Changxin , Liao Jinwei , Zhao Sheng , Dai Xing , Hong Bin 
Published: December 2024

Abstract
To address the issue of the low signal-to-noise ratio in detecting microleakage acoustic wave signals in natural gas pipelines, this paper combines the whale optimization algorithm-based variational mode decomposition (WOA-VMD) algorithm with the Duffing chaotic oscillator to propose a new method for detecting such signals. Firstly, the WOA-VMD algorithm is utilized to adaptively decompose the signal, thereby improving the signal decomposition capability. The cubic spline interpolation algorithm is then introduced to reconstruct the characteristic signal obtained from the decomposition. Subsequently, frequency transformation and array are employed to creatively enhance a Duffing chaotic oscillator, enabling the detection of signals with arbitrary frequencies and initial phases, which is applied to the detection microleakage acoustic wave signals in natural gas pipelines. Finally, through systematic simulation analysis and practical experimental verification, it is concluded that the proposed system exhibits strong anti-noise interference capabilities and can effectively detect multi-frequency and multi-phase signals even with the SNR as low as −76.99 dB.
Data imbalanced fault diagnosis of gearbox transmission system under various speeds based on dynamic dual-scale normalized fusion network
Authors: Wang Chaoge , Tian Xinyu , Shao Xinhao , Wang Ran , Wang Lijun 
Published: December 2024

Abstract
Gearboxes play a pivotal role in industrial production, and their reliability and safety are essential for production safety and efficiency. However, gearboxes frequently encounter challenges such as variable rotational speeds and unknown operating conditions. Unfortunately, most existing traditional fault diagnosis methods face the following issues: (1) They heavily rely on expert experience and pre-existing knowledge bases, making them unable to tackle fault diagnosis in unknown working conditions. (2) While addressing various speed issues, they seldom consider the problem of data imbalance in real-world industrial environments. (3) Many transfer learning methods primarily focus on global distribution alignment and knowledge transfer between source and target domains, neglecting the importance of fine-grained distribution alignment between subdomains. To address these issues, a dynamic dual-scale normalized fusion network is proposed for cross-domain fault diagnosis under variable speed and data imbalance. Firstly, the two parallel graph convolution frameworks constructed are used to extract multi-scale fault features. Subsequently, a dual-scale normalization fusion module is adopted to integrate the global and local fault feature information within the subdomains of both the source and target domains, thereby aligning their fine-grained distributions to obtain domain-invariant features. Finally, a dynamic soft threshold feedback strategy is introduced, which assigns pseudo labels to the target domain data, enabling the model to give equal attention to each class of data samples, even under data imbalance conditions, thereby improving the recognition accuracy of minority fault classes. Validating the proposed method on two real cases, our method achieved the highest accuracy compared to other advanced approaches.
Computer vision methods for side scan sonar imagery
Authors: Motylinski Michal , Plater Andrew J , Higham Jonathan E 
Published: December 2024

Abstract
Side-scan sonar (SSS) data presents a significant challenge to analysts due to the size of the material that requires processing. Automatic recognition systems can help in the interpretation and filtration of the data, reducing the time needed for analysis. Deep learning architectures have been employed for computer vision tasks in the underwater domain. The objective of this work is to review current deep learning methods for automatic image classification, object detection, semantic segmentation, and instance segmentation through statistical analysis of published studies. Further, this work includes an inventory of publicly available SSS data followed by a discussion on augmentation methods applied to SSS imagery. The study discusses current challenges in the automatic underwater target detection field, highlights main gaps within the domain and identifies potential research directions. Our proposal includes the creation of a standardised benchmark and the use of a common set of metrics allowing for consistent evaluation of future research works.
IFAL-SLAM: an approach to inertial-centered multi-sensor fusion, factor graph optimization, and adaptive Lagrangian method
Authors: Liu Jiaming , Qi Yongsheng , Yuan Guoshuai , Liu Liqiang , Li Yongting 
Published: December 2024

Abstract
In response to the issues of low accuracy, perception degradation, and poor reliability of single-sensor simultaneous localization and mapping (SLAM) technologies in complex environments, this study presents a novel Inertial Measurement Unit (IMU)-centered multi-sensor fusion SLAM algorithm (IFAL-SLAM) integrating Light Detection and Ranging (LiDAR), vision, and IMU, based on factor graph elimination optimization (IMU-centered multi-sensor Fusion, Adaptive Lagrangian methods). The proposed system leverages a multi-factor graph model, centering on the IMU, and applies a covariance matrix to fuse visual-inertial and LiDAR-inertial odometries for bias correction, using loop closure factors for global adjustments. To minimize the optimization costs post-fusion, a sliding window mechanism is incorporated, coupled with a QR decomposition elimination method based on Householder transformation to convert the factor graph into a Bayesian network. Finally, an adaptive Lagrangian relaxation method is proposed, employing matrix-form penalty parameters and adaptive strategies to enhance convergence speed and robustness under high rotational dynamics. Experimental results indicate that the proposed algorithm achieves absolute trajectory errors of approximately 0.58 m and 0.24 m in large and small complex scenes, respectively, surpassing classic algorithms in terms of accuracy and reliability.
Mechanical behavior of supersonic fine particle bombardment single crystal γ-TiAl alloys based on atomistic simulation: effects of velocity and crystal plane
Authors: Yu Zhaoliang , Cao Hui , Zhou Baocheng , Yang Wenle , Li Haiyan , Chen Tao , Feng Ruicheng 
Published: December 2024

Abstract
The crystal orientation significantly affects the plastic deformation and mechanical properties of γ-TiAl alloys. However, there are few studies on the mechanical behavior of supersonic fine particle bombardment (SFPB) of single-crystal γ-TiAl alloys impacted with different crystal planes and velocities at the nanoscale. And the characterization of the mechanical properties in the presence of dislocation defects after impact is lacked. Therefore, in this paper, molecular dynamics is used to simulate the impact response and post-impact mechanical response of SFPB single-crystal γ-TiAl alloy. The results show that: at a certain impact velocity, the different ways of inducing dislocation slip due to the number of slip system initiations under crystal anisotropy lead to a smaller depth of subsurface damage on the (001) crystallographic plane compared to the other crystallographic planes; moreover, the yield strength and Young’s modulus of the (111) and (1

1
¯

0) crystallographic planes are the largest after the impact, respectively. Under the same crystal plane, the subsurface damage depths of all crystal planes decrease with the increase of impact velocity; the yield strength of the (111) crystal plane of γ-TiAl alloy gradually increases, the yield strength of the (001) and (1

1
¯

0) crystal planes decreases, and the modulus of elasticity of the (001) and (111) crystal planes after impact is less sensitive to velocity. The angle between the two slip surfaces formed by the L-C dislocation during impact is 70.24°, while the angle between the two slip surfaces formed by the Hirth dislocation is 109.76°. This will provide atomic-scale deformation details of the plastic deformation and mechanical response of single-crystal γ-TiAl alloys bombarded by supersonic fine particles.