bluuebunny/crossref_metadata_2025_split huggingface dataset:
Deposition of nanoparticles through a cylindrical tube of human respiratory system
Authors: Akter Mst. Sathi , Ahmmed Mahtab U. , Tanisa Nilufer Yesmin , Hossain Shakib 
Published: December 2024

This paper proposes a mathematical model for nanoparticle deposition in the respiratory bronchiole of the human lung airways. The length of the respiratory bronchiole of the human lung is 1.2 mm, and the diameter is 0.5 mm. Therefore, to investigate the impact of inhaled nanoparticles within the lung bronchioles, first, we used the Navier–Stokes equation by including the Darcy term together with Newton’s equation of motion. Then we non-dimensionalized the governing equation, and numerical solutions are obtained using the finite difference technique. Under the assumption of laminar pulsatile flow conditions and axial symmetry, the problem is simplified to a two-dimensional computational domain. The computational framework is implemented using MATLAB R2018 through user-defined code. Velocity propagation, the Reynolds number, and the Darcy number effect are performed to examine the flow conditions inside the respiratory bronchioles.
Linguistic variation beyond the Indo-European web
Authors: Erten-Johansson Selcen , Skantsi Valtteri , Pyysalo Sampo , Laippala Veronika 
Published: December 2024

Abstract
A register, defined as a text variety with specific situational characteristics and a communicative purpose (Biber & Conrad 2019), is also recognized as a cultural construct (Biber & Egbert 2023). Registers merit thorough investigation due to their pivotal role in reflecting linguistic and cultural landscapes. However, existing studies predominantly focus on Indo-European languages. This study investigates Turkish web registers through the introduction of the Turkish Corpus of Online Registers (TurCORE). Comprising 2,780 web texts, TurCORE was manually annotated using a register taxonomy targeting the entire unrestricted web and identifying 24 web register categories. By employing Text Dispersion Keyword Analysis (Egbert & Biber 2019), the research examines the register characteristics with a specific focus on news reports, interactive discussions, and recipes, drawing comparisons with their English equivalents. Results reveal parallels between Turkish and English news reports while Turkish interactive discussions and recipes exhibit distinctive language- and culture specific features.
An Off-Resonant Quantum Collision Model: Realizing a Qubit Coupled with an Effective Negative-Temperature Bath
Authors: Yan 闫 Wei-Bin 伟斌 , Man 满 Zhong-Xiao 忠晓 , Zhang 张 Ying-Jie 英杰 , Xia 夏 Yun-Jie 云杰 
Published: December 2024

Abstract
The quantum collision model provides a promising tool for investigating system-bath dynamics. Most studies of quantum collision models, however, are in the resonant regime. In quantum dynamics, the off-resonant interactions often result in exciting effects. Therefore, it is important to investigate the quantum collision models in the off-resonant regime. A bath with a negative absolute temperature is expected to be instrumental in the development of thermal devices. The design of an effective bath with negative absolute temperature coupled to a qubit is a significant component for developing such thermal devices. In this study, we establish an effective negative-absolute-temperature bath coupled to a qubit with a quantum collision model in the far-off-resonant regime. We conduct a detailed systematic investigation of the off-resonant collision model and determine the presence of an additional constraint on the collision duration resulting from the far-off resonant collision. The dynamics of the collision model in the far-off-resonant regime are different from those beyond the far-off-resonant regime. Numerical simulations are used to confirm the validity of the proposed approach.
Electrically Tunable Graphene Terahertz Isolator Assisted by Nonreciprocal Plasmon
Authors: Xu 徐 Chen-Ran 晨燃 , Fan 范 Weiru 伟如 , Tang 汤 Yanhao 衍浩 , Wang 王 Dawei 大伟 
Published: December 2024

Abstract
Nonreciprocal isolators enable unidirectional light propagation without back-reflection. Typical terahertz isolators require magnetic fields to break the time-reversal symmetry. Herein, we propose a nonmagnetic isolator in the terahertz range based on nonreciprocal graphene plasmons operated in a reflection configuration. The bias voltage generates a drift current in graphene, which breaks the time-reversal symmetry and induces nonreciprocal reflection. The isolator device exhibited a high isolation exceeding 20 dB with an insertion loss of less than 3 dB. Moreover, the bandwidth wit isolation exceeding 20 dB can be broadened five times to 1.7 THz by tuning the carrier density. The indexes, including the isolation, insertion loss and bandwidth of the isolator, show a strong dependence on the drift velocity and mobility of graphene, as well as the air-gap thickness. Our study shows great potential in the burgeoning terahertz technology, where nonmagnetic and electrically tunable isolators are still lacking.
Quantifying the Driving Effect of Colored Noise in Brownian Motors
Authors: Zhang Zhichao , Liu Yue , Wu Congmin , He Dahai 
Published: December 2024

Abstract
The colored noise disrupts the detailed balance, enabling directed transport in ratchet systems without additional driving forces. Despite a well-established understanding of the conditions for Brownian motors, quantification of the driving effect of colored noise and its connection to deviations from equilibrium remains unexplored. In this study, we examined the directed motion of an overdamped Brownian motor within an asymmetric traveling potential subjected to Ornstein–Uhlenbeck colored noise. We propose a scheme to quantify the driving effect of colored noise by defining an effective force based on the stopping velocity of the traveling potential where directed transport halts. Our results revealed a nonmonotonic dependence of the effective force on the noise correlation time and a monotonic dependence on the noise strength, corresponding to double and single current reversals, respectively. The nonmonotonicity of the current is attributed to the interplay between the fluctuating characteristics and the driving effects of colored noise.
Atomic Level Insight into the Variation and Tunability of Band Alignment between Si and Amorphous SiO2/HfO2
Authors: Li 李 Wen-Feng 文峰 , Liu 刘 Ting-Wei 亭炜 , Yang 杨 Zheng-Mei 正美 , Wang 汪 Lin-Wang 林望 , Liu 刘 Yue-Yang 岳阳 
Published: December 2024

Abstract
The band alignment between silicon and high-k dielectrics, which is a key factor in device operation and reliability, still suffers from uncontrolled fluctuations and ambiguous understanding. In this study, by conducting atomic-level ab initio calculations on realistic Si/SiO2/HfO2 stacks, we reveal the physical origin of band alignment fluctuations, i.e., the oxygen density-dependent interface and surface dipoles, and demonstrate that band offsets can be tuned without introducing other materials. This is instructive for reducing the gate tunneling current, alleviating device-to-device variation, and tuning the threshold voltage. Additionally, this study indicates that significant attention should be focused on model construction in emerging atomistic studies on semiconductor devices.
Quantum-fluid correspondence in relativistic fluids with spin: from Madelung form to gravitational coupling
Authors: Sato Naoki 
Published: December 2024

Abstract
This paper explores the quantum-fluid correspondence in a charged relativistic fluid with intrinsic spin. We begin by examining the nonrelativistic case, showing that the inclusion of spin introduces a quantum correction to the classical fluid energy. This correction, coupled with Maxwell’s equations, naturally leads to the Schrödinger equation in Madelung form. Building on this foundation, we extend the formalism to a relativistic perfect fluid, identifying the system’s stress-energy-momentum tensor. Our analysis reveals that the trace of the quantum correction to this tensor corresponds to the energy density of an oscillator, with its frequency determined by the vorticity of the spin motion. We then use the stress-energy-momentum tensor to establish the relationship between the Ricci scalar curvature, as dictated by the Einstein field equations, and the fluid density in a static, spherically symmetric configuration. Lastly, we generalize the Madelung transformation to compressible Navier–Stokes flows with vorticity and viscosity by developing a tailored Clebsch representation of the velocity field. This theoretical framework offers potential applications for studying fluid-like systems with internal rotational degrees of freedom, commonly encountered in astrophysical settings.
Testing Newtonian gravitation in educational context
Authors: Giudici Sergio 
Published: December 2024

Abstract
In both Upper Secondary School and first-level university courses, Newtonian gravitation is typically taught with a primary focus on theoretical aspects, particularly on solving the two-body problem. The solution is claimed reproduce Kepler's empirical laws, but little attention is given to the details of the validation.&#xD; &#xD;In the past, the emphasis on theory could be justified by the technical difficulties associated with accessing and analyzing data. Today, however, the availability of open-access data and advanced computational tools makes it feasible to construct empirical evidence for Newtonian gravitation, even within classroom settings. This work revisits the arguments Newton himself used to support his theory and replicate the validation process through a series of activities designed for educational purposes. This approach includes analyzing astrophotographic and mareographic data, along with revisiting Aristarchus of Samos's method for measuring the distance to the Moon through eclipse analysis.
Photon-assisted tunneling resonantly controlling spin current of a spin–orbit-coupled atom in a toroidal trap
Authors: Li Zhiqiang , Hu Xiaoxiao , Zeng Zhao-Yun , Chen Ai-Xi , Luo Xiaobing 
Published: December 2024

Abstract
The periodic flashing potential has proven to be a powerful tool for investigating directed atomic currents. By applying the flashing ring-shaped potential to spin–orbit (SO) coupled, noninteracting Bose–Einstein condensate (BEC) systems, through photon-assisted tunneling (resonance) techniques, we demonstrate the generation of tunable alternating (AC) spin and atomic mass currents that can be precisely controlled in terms of direction and strength. The underlying mechanism behind this phenomenon is that the flashing potential supplies enough photons to induce Rabi oscillations and provides momentum transfer for spin and atomic transport. As the single-particle ground state of the unperturbed SO-coupled BEC depends on the Raman coupling strength, we demonstrate how to generate and control AC spin currents in the cases where the initial state resides in a single-well or double-well phase. In particular, we realize and explain the mechanism of generating a net AC spin current without mass current through single-photon resonance processes. It is shown that these interesting resonance phenomena can be analytically described only by the simple three-level model, which creates the possibility of transparent controls of spin dynamics.
Structural and spectroscopic characterization of Ba3RE2(Ge3O9)2 (RE = La, Pr, Nd) and Ba3La2−
xEux(Ge3O9)2 cyclogermanates
Authors: Lipina Olga A , Baklanova Yana V , Popov Ilya S , Surat Lyudmila L , Chufarov Alexander Yu , Tyutyunnik Alexander P , Rybnikova Anna A , Zubkov Vladimir G 
Published: December 2024

Abstract
Ba3RE2(Ge3O9)2 (RЕ = La, Pr, Nd) and Ba3La2−x
Eu
x
(Ge3O9)2 germanates were prepared via solid-state reaction for the first time. The crystal structure of the compounds was identified using x-ray powder diffraction. The obtained results indicate that all germanates are isostructural and crystallize in a monoclinic crystal system with the space group С2/c, Z = 4. The crystal lattice consists of two kinds of layers, formed from [Ge3O9]6− rings or from Ba2+/RE3+ cations. The density functional theory calculations performed on a rich set of Ba3RE2(Ge3O9)2 compounds have approved a high thermodynamic stability of monoclinic modification and chair conformation of [Ge3O9]6− rings. The luminescence properties of Ba3La2−x
Eu
x
(Ge3O9)2 phosphors have been studied under 239 nm and 393 nm excitation. The spectra contain narrow lines in the orange–red spectral region, associated with the intraconfiguration f‒f transitions in Eu3+. The most intensive lines are located at 603–635 nm and are caused by 5D0 → 7F2 transition in Eu3+. The concentration dependence indicates an effective energy transfer due to dipole–dipole interaction. The Ba3La2−x
Eu
x
(Ge3O9)2 phosphors possess a high color purity and thermal stability of luminescence that allows one to predict that they may be successfully used in solid state lighting.
Effects of anode voltage and mass flow rate on the erosion of inner permanent magnet conducting cover in a 100 W Hall thruster
Authors: Wang Lei , Li Zijie , Ding Rui , Hou Ernan , Wei Liqiu , Li Hong , Ding Yongjie 
Published: December 2024

Abstract
The effects of anode voltage and mass flow rate on the erosion of the inner permanent magnet conducting cover in a 100 W Hall thruster were studied in this paper. To accelerate erosion, an inner permanent magnet conducting cover made of aluminum alloy was employed. Experimental results indicate that the erosion rate of the inner conducting cover increases with higher anode voltage and mass flow rate. When the anode mass flow rate is set at 3.8 sccm and the anode voltage increases from 200 V to 300 V and 350 V, the erosion rate at the center of the inner conducting cover increases from 6.54 mm kh−1 to 9.29 mm kh−1 and 13.79 mm kh−1, respectively, reflecting increases of 42.0% and 110.8% compared to the initial erosion rate. When the anode voltage is 200 V and the anode mass flow rate increases from 3.8 sccm to 5.4 sccm and 6.9 sccm, the erosion rate at the center of the cover increases from 6.54 mm kh−1 to 9.00 mm kh−1 and 10.91 mm kh−1, indicating increases of 37.6% and 66.9%, respectively. These findings underscore the challenges of maintaining the lifespan of the inner conducting cover when thruster is operated under the conditions of high specific impulse and high thrust discharge. Further investigation reveals that the potential difference between the channel exit and the inner conducting cover is a significant factor driving ions near the channel exit bombardment of the inner conducting cover. Increased anode voltage and mass flow rate enhance this potential difference and increase the ion density near the channel exit, resulting in greater current density and energy of ions bombarding the inner conducting cover, thereby accelerating its erosion. This study provides a reference for the lifespan analysis of the inner conducting cover in low-power thrusters operating under multi-mode conditions.
Descriptive overview of AI applications in x-ray imaging and radiotherapy
Authors: Damilakis John , Stratakis John 
Published: December 2024

Abstract
Artificial intelligence (AI) is transforming medical radiation applications by handling complex data, learning patterns, and making accurate predictions, leading to improved patient outcomes. This article examines the use of AI in optimising radiation doses for x-ray imaging, improving radiotherapy outcomes, and briefly addresses the benefits, challenges, and limitations of AI integration into clinical workflows. In diagnostic radiology, AI plays a pivotal role in optimising radiation exposure, reducing noise, enhancing image contrast, and lowering radiation doses, especially in high-dose procedures like computed tomography (CT). Deep learning (DL)-powered CT reconstruction methods have already been incorporated into clinical routine. Moreover, AI-powered methodologies have been developed to provide real-time, patient-specific radiation dose estimates. These AI-driven tools have the potential to streamline workflows and potentially become integral parts of imaging practices. In radiotherapy, AI’s ability to automate and enhance the precision of treatment planning is emphasised. Traditional methods, such as manual contouring, are time-consuming and prone to variability. AI-driven techniques, particularly DL models, are automating the segmentation of organs and tumours, improving the accuracy of radiation delivery, and minimising damage to healthy tissues. Moreover, AI supports adaptive radiotherapy, allowing continuous optimisation of treatment plans based on changes in a patient’s anatomy over time, ensuring the highest accuracy in radiation delivery and better therapeutic outcomes. Some of these methods have been validated and integrated into radiation treatment systems, while others are not yet ready for routine clinical use mainly due to challenges in validation, particularly ensuring reliability across diverse patient populations and clinical settings. Despite the potential of AI, there are challenges in fully integrating these technologies into clinical practice. Issues such as data protection, privacy, data quality, model validation, and the need for large and diverse datasets are crucial to ensuring the reliability of AI systems.
How much resources are reasonable to spend on radiological protection?
Authors: Engström A , Isaksson M , Javid R , Larsson P A , Lundh C , Wikström J , Båth M 
Published: December 2024

Abstract
In short terms, a society’s available resources are finite and must be prioritised. The more resources that are spent on radiological protection, the lesser resources are available for other needs. The ALARA principle states that exposure of ionising radiation should be kept as low as reasonably achievable, taking into account economic and societal factors. In practice, one of several approaches to determine what is considered as reasonably achievable is cost-benefit analysis. A demanding part of cost-benefit analysis is to decide on an α value, which stipulates the value of radiological protection. There are different conversion methods on how to convert societal costs into an α value. However, with the assistance of recent developments within both health economics and radiological protection room for improvements was found. Therefore, the aims of the present study were to develop a new conversion method (on how to convert societal costs into an α value) and to provide recommendations of α values for each member country of The Organisation for Economic Co-operation and Development (OECD). With the help of systematic reviews of societal costs (the value of a statistical life, productivity losses and healthcare costs) and discount rates, as well as Monte Carlo simulations of the number of years between exposure and cancer diagnosis, a new conversion method and recommendations of α values could be presented. The new conversion method was expressed as a discounted nominal risk of exposure with a median (interquartile range) of 175 (136–222) per 10 000 persons per Sv for the public and 169 (134–207) per 10 000 persons per Sv for workers. For OECD in general, recommendations of α values were determined to be $56–170 per man.mSv for the public and $61–162 per man.mSv for workers (2023-USD).
A lightweight and rapidly converging transformer based on separable linear self-attention for fault diagnosis
Authors: Yin Kexin , Chen Chunjun , Shen Qi , Deng Ji 
Published: December 2024

Abstract
Reaching reliable decisions on equipment maintenance is facilitated by the implementation of intelligent fault diagnosis techniques for rotating machineries. Recently, the Transformer model has demonstrated exceptional capabilities in global feature modeling for fault diagnosis tasks, garnering significant attention from the academic community. However, it lacks sufficient prior knowledge regarding rotation invariance, scale, and shift, necessitating pre-training on extensive datasets. In comparison, contemporary convolutional neural networks exhibit greater ease of optimization. This limitation becomes particularly evident when applying the Transformer model in fault diagnosis scenarios with limited data availability. Moreover, the increasing the number of parameters and FLOPs. Pose a challenge to its suitability for mobile services due to the limited computational resources available on edge devices. To mitigate these issues, this paper introduces a novel lightweight Transformer (SepFormer) based on separable linear self-attention (LSA) for fault diagnosis task. The SepFormer performs a novel sequence-level feature embedding to better leverage the inductive bias inherent in the convolutional layers. Furthermore, it integrate a novel separable LSA mechanism into the Transformer architecture, effectively mitigating the computational burden concerns and significantly enhancing the training convergence speed. Extensive experiments are conducted extensively on a bearing fault dataset and gear fault dataset. The experimental results demonstrate that the SepFormer achieves a top-1 accuracy exceeding state-of-the-art approaches by more than 5%, while utilizing the fewest FLOPs. Moreover, the optimizability of SepFormer surpasses that of CNN, ensuring its superior preservation of inductive bias.
Detection of group-housed pigs feeding behavior using deep learning and edge devices
Authors: Gong Junjie , Deng Minghui , Li Guiping , Zheng Piaoyi , Yin Yanling 
Published: December 2024

Abstract
The detection of feed behavior at pig farms is essential in monitoring the welfare and health of pigs. Addressing the low automation level of feeding behavior detection in group-housed pig farming, this study proposes a lightweight feeding behavior detection model, GAB-YOLO, based on YOLOv8s. The model employs GhostNet with a Convolution and Self-Attention Mixed Module as the backbone, enhancing feature extraction capability while reducing parameters. Wise-IoU is utilized as the bounding box loss function to improve sensitivity to piglets. To integrate features of pigs with different body types, a feature fusion module called Bi-directional Multi Feature Pyramid Network is proposed as the neck part of the model. Experimental results demonstrate that the improved model achieves detection accuracies of 98.40% for drinking behavior and 98.66% for eating behavior in group-housed pigs, representing improvements of 2.79% and 2.99%, respectively, over the original YOLOv8s algorithm, with a 14.5% reduction in parameters. The Deep Simple Online and Realtime Tracking (DeepSORT) algorithm is integrated into the improved model to address the issue of inaccurate video behavior judgment by YOLO, forming the lightweight model GAB-YOLO-DeepSORT. Finally, GAB-YOLO-DeepSORT is deployed on the NVIDIA Jetson Nano. The practical operation on the Jetson Nano shows that the proposed model can track multiple targets for pigs of different sizes and varieties in a group-housed environment, thus ensuring the accuracy of pig feeding behavior recognition and providing support for the subsequent establishment of pig health systems.