bluuebunny/crossref_metadata_2025_split huggingface dataset:
Improving respiratory signal prediction with a deep neural network and simple changes to the input and output data format
Authors: Hirai Ryusuke , Mori Shinichiro , Suyari Hiroki , Ishikawa Hitoshi 
Published: February 2024

AbstractObjective.To improve respiratory gating accuracy and radiation treatment throughput, we developed a generalized model based on a deep neural network (DNN) for predicting any given patient’s respiratory motion.Approach.Our model uses long short-term memory (LSTM) based on a recurrent neural network (RNN), and improves upon common techniques. The first improvement is that the data input is not a one-dimensional sequence, but two-dimensional block data. This shortens the input sequence length, reducing computation time. Second, the output is not a scalar, but a sequence prediction. This increases the amount of available data, allowing improved prediction accuracy. For training and evaluation of our model, 434 sets of real-time position management data were retrospectively collected from clinical studies. The data were separated in a ratio of 4:1, with the larger set used for training models and the remaining set used for testing. We measured the accuracy of respiratory signal prediction and amplitude-based gating with prediction windows equaling 133, 333, and 533 ms. This new model was compared with the original LSTM and a non-recurrent DNN model.Main results.The mean absolute errors with the prediction window at 133, 333 and 533 ms were 0.036, 0.084, 0.119 with our model; 0.049, 0.14, 0.246 with the original LSTM-based model; and 0.041, 0.119, 0.16 with the non-recurrent DNN model, respectively. The computation time were 0.66 ms with our model; 0.63 ms the original LSTM-based model; 1.60 ms the non-recurrent DNN model, respectively. The accuracies of amplitude-based gating with the same prediction window settings and a duty cycle of approximately 50% were 98.3%, 95.8% and 92.7% with our model, 97.6%, 93.9% and 87.2% with the original LSTM-based model; and 97.9%, 94.3% and 89.5% with the non-recurrent DNN model, respectively.Significance.Our RNN algorithm for respiratory signal prediction successfully estimated tumor positions. We believe it will be useful in respiratory signal prediction technology.
A combined analytical and Monte Carlo method for detailed simulations of antiscatter grids in x-ray medical imaging: implementing scatter within the grid
Authors: Massera Rodrigo T , Bosmans Hilde , Rodriguez Perez Sunay , Marshall Nicholas 
Published: February 2024

Abstract

Objective. To implement a hybrid method, which combines analytical tracking and interaction simulation using Monte Carlo (MC) techniques, in order to model photon transport inside antiscatter grids (ASG) for x-ray imaging. Approach. A new tally was developed for PENELOPE (v.2018) and penEasy (v. 2020) MC code to simulate photon transmission through ASGs. Two established analytical algorithms from the literature were implemented in this tally. In addition, a new hybrid method was introduced by extending one of the analytical algorithms to include photon-interactions inside the grid, while preserving the imaged grid structure. Calculations of primary

(
T

P

)
,

scatter

(
T

S

)
,

and total

(
T

T

)

grid transmissions in addition to the Q factor (Q =

T

P

2

/

T

T

) were performed. The new tally was validated for a quadric geometry ASG, and experimental measurements with a PMMA phantom of several thicknesses. In addition, the contribution of the scatter inside the grid was studied for three interspace materials, and a high resolution image of the grid was simulated. Main results. An excellent agreement was found between the two analytical models compared with the quadric grid without scatter, and the hybrid method with the geometrical grid with scatter. Average deviations of 0.2% and 1.4% were found between

T

P

and

T

S

for the hybrid method and quadric grid, while for the hybrid method and experimental measurements these values were 1% and 20%. Antiscatter grids with aluminium as interspace material had the highest amount of scatter from inside the grid to the final image, followed up by paper fibre and air. The high resolution image of the grid was equivalent using the quadric geometry or the hybrid mode. Significance. The hybrid method provides a means of studying scattered radiation from the antiscatter grid with the advantage of higher performance, with results that are consistent with a full quadric geometry simulation of the ASG.
S-Net: an S-shaped network for nodule detection in 3D CT images
Authors: Zhang JingYu , Zou Wei , Hu Nan , Zhang Bin , Wang Jiajun 
Published: February 2024

Abstract

Objective. Accurate and automatic detection of pulmonary nodules is critical for early lung cancer diagnosis, and promising progress has been achieved in developing effective deep models for nodule detection. However, most existing nodule detection methods merely focus on integrating elaborately designed feature extraction modules into the backbone of the detection network to extract rich nodule features while ignore disadvantages of the structure of detection network itself. This study aims to address these disadvantages and develop a deep learning-based algorithm for pulmonary nodule detection to improve the accuracy of early lung cancer diagnosis. Approach. In this paper, an S-shaped network called S-Net is developed with the U-shaped network as backbone, where an information fusion branch is used to propagate lower-level details and positional information critical for nodule detection to higher-level feature maps, head shared scale adaptive detection strategy is utilized to capture information from different scales for better detecting nodules with different shapes and sizes and the feature decoupling detection head is used to allow the classification and regression branches to focus on the information required for their respective tasks. A hybrid loss function is utilized to fully exploit the interplay between the classification and regression branches. Main results. The proposed S-Net network with ResSENet and other three U-shaped backbones from SANet, OSAF-YOLOv3 and MSANet (R+SC+ECA) models achieve average CPM scores of 0.914, 0.915, 0.917 and 0.923 on the LUNA16 dataset, which are significantly higher than those achieved with other existing state-of-the-art models. Significance. The experimental results demonstrate that our proposed method effectively improves nodule detection performance, which implies potential applications of the proposed method in clinical practice.
Reversed-direction 2-point modelling applied to divertor conditions in DIII-D
*
Authors: Nichols J H , Stangeby P C , McLean A G , Canik J M , Moser A L , Shafer M W , Wang H Q 
Published: February 2024

Abstract
A predictive form of the extended 2-point model known as the ‘reverse 2-point model’, Rev2PM, is applied to a range of detachment levels in the open lower divertor of DIII-D, showing that the experimentally measured electron temperature (Te
) and pressure (pe
) at the divertor entrance can be calculated within 50% from target measurements, if and only if a posteriori corrections for convective heat flux are included in the model. Unlike the standard 2-point model, the Rev2PM calculates upstream scrape-off layer (SOL) quantities (such as separatrix Te
and pe
) from target conditions (such as Te
and parallel heat flux), with volumetric power and momentum losses depending solely on target Te
. The Rev2PM is tested against a database of DIII-D inter-ELM divertor Thomson scattering measurements, built from a series of 6 MW, 1.3 MA, LSN H-mode discharges with varied main ion density, drift direction, and nitrogen puffing rate. Measured target Te
ranged from 0.4–25 eV over this database, and upstream Te
ranged from 5–60 eV. Poor agreement is found between upstream measurements and Rev2PM calculations that assume purely conductive parallel heat transport. However, introducing a posteriori corrections to account for convective heat transport brings the Rev2PM calculations within 50% of the measured upstream values across the dataset. These corrections imply that up to 99% of the parallel heat flux is carried by convection in detached conditions in the DIII-D open lower divertor, though further work is required to assess any potential dependencies on device size or divertor closure.
Quantification of plasma enabled surface cooling by electron emission from high temperature materials
Authors: Bak Junhwi , Tropina Albina , Creel James , Miles Richard B 
Published: February 2024

Abstract
In this work, the potential for hypersonic leading edge cooling by electron emission is demonstrated. To overcome space charge limitations the experiments are carried out in an argon discharge at 1 Torr. Cooling is observed with time-resolved measurements of the electron emission current and surface temperature, taking advantage of well controlled laser heating of the emitting surface and time accurate surface pyrometry. For the ignited mode of the plasma discharge, surface cooling by the electron emission is directly observed, leading to an estimated cooling rate of

1.6
±
0.2

MW m−2. Higher cooling rates with self sustained plasmas for space charge mitigation are expected using cesium transpiration. A two-dimensional model of heat transfer has been developed, which reproduces well the experimentally observed cooling dynamics. Parametric tests of emitter materials with various work functions show that for effective surface cooling by electron emission, the optimal work function must be less than 3.0 eV. This result indicates that electron cooling can be a promising thermal protection method for leading edges of hypersonic vehicles in flight.
Memristive effects in YBa2Cu3O7-x devices with transistor-like structure
Authors: Lagarrigue Aurélien , de Dios Carolina , Carreira Santiago J , Humbert Vincent , Mesoraca Salvatore , Briatico Javier , Trastoy Juan , Villegas Javier E 
Published: February 2024

Abstract
Cuprate superconductors are highly sensitive to disorder and oxygen stoichiometry; even minute variations of those parameters drastically change their electronic properties. In this work, we exploit this characteristic to engineer a memristive device based on the high-TC
superconductor YBa2Cu3O7−x
(YBCO), in which local changes of the oxygen content and induced disorder are harnessed to produce memory effects. These effects are electrically triggered in a three-terminal device whose structure is reminiscent of a transistor, consisting of a YBCO channel and an Al gate. The Al/YBCO interface, which controls the gate conductance, displays a large, bipolar, reversible switching across a continuum of non-volatile conductance states spanning over two decades. This phenomenon is controlled by the gate voltage magnitude and is caused by the oxygen exchange between YBCO and Al. Concomitantly, the channel shows a gradual, irreversible superconductor-to-insulator transition that retains a memory of the power dissipated in the device and can be explained by induced bulk disorder. The observed effects, and the understanding of the interplay between the underlying mechanisms, constitute interesting ingredients for the design and realization of novel memristors and switches for superconducting electronics.
Development of persistent joints for superconducting Bi-2212 coils
Authors: Zagura Petr , Kim Ingon , Follows Frederick , Barker Clara , Melhem Ziad , Twin Andrew , Ball Steven , Grovenor Chris , Speller Susannah , Mousavi Tayebeh 
Published: February 2024

Abstract
Bi2Sr2CaCu2O8+x
(Bi-2212) multifilamentary wire is the only high-temperature superconductor manufactured in the form of an isotropic round wire, and so offers a number of advantages for the designers of high field magnets. However, for high-field (>25 T), high-stability magnet applications, ultra-low resistance superconducting joints (R < 10−12 Ω) will be needed to take advantage of the excellent properties of the Bi-2212 wire. This study focuses on the fabrication of compact melt processed joints in small coils of Bi-2212/Ag multifilamentary round wires and the testing of their superconducting performance by inductive resistance measurements. Microstructural analysis is carried out to correlate the microstructure to the superconducting performance of the joints. Our optimized technique led to a reliable process for the preparation of small coils with melt processed joints that occupy very small volumes but can still carry the highest persistent currents reported so far for Bi-2212.
Energetics of magnetized Kerr-MOG and Kerr-Taub-NUT black holes within magnetic Penrose process
Authors: Alibekov Husan , Abdujabbarov Ahmadjon , Ahmedov Bobomurat 
Published: February 2024

Abstract
In this research paper, we have examined the impact of a gravitomagnetic charge on extracting energy from a rotating Kerr-Taub-NUT black hole and Kerr-MOG (MOdified Gravity known as Scalar-Tensor-Vector-Gravity (STVG)) black hole embedded in the magnetic field via the magnetic Penrose process (MPP). Our findings demonstrate that the gravitomagnetic monopole and MOG parameters both significantly influence the extraction of energy from a rotating black hole, exceeding the MPP for the Kerr black hole in terms of energy efficiency. After comparing the results of this study with the observational data, we were confident that our findings on the amplification of MPP by MOG and NUT parameters are nearly in line with the observations of ultrarelativistic particles in the cosmic rays.
Stationary rotating and axially symmetric dust systems as peculiar General Relativistic objects
Authors: Ruggiero Matteo Luca 
Published: February 2024

Abstract
We study an exact solution of Einstein's equations describing a self-gravitating system, made of dust, distributed with axial symmetry and in stationary rotation, and we prove that this type of system has no Newtonian analogue. In a low-energy limit, its existence depends on the solution of a Grad-Shafranov equation in vacuum which can be interpreted as a Laplace equation for the toroidal component of the gravitomagnetic potential; in particular, in this system the relativistic rotational effects are of the order of magnitude of Newtonian ones. We therefore argue that this exact solution should contain singularities and discuss the possible consequences of using such a system as simplified model for galactic dynamics.
Simultaneous detection of boosted dark matter and neutrinos from the semi-annihilation at DUNE
Authors: Aoki Mayumi , Toma Takashi 
Published: February 2024

Abstract
Dark matter direct detection experiments impose the strong bounds on thermal dark matter
scenarios. The bound can naturally be evaded if the cross section is momentum transfer or
velocity dependent. One can test such thermal dark matter scenarios if dark matter particles are
boosted by some mechanism. In this work, we consider a specific semi-annihilation χχ̅→νχ where χ(χ̅) is dark matter (anti-dark matter), and search
for simultaneous detection of the neutrino and the boosted dark matter in the final state at DUNE.
We find that the energies of the neutrino and boosted dark matter are reconstructed by kinematics.
In addition, we find that both signals can be testable at DUNE if the dark matter mass is below
8 GeV, and the scattering cross section is momentum transfer dependent. Even for
larger dark matter masses, the two signals can be tested by combination of DUNE and the other
experiments such as IceCube/DeepCore and Hyper-Kamiokande.
Sub-50 fs pulses generation from an all-fiber monolithic gain-managed nonlinear amplifier with CFBG-based pre-compressor
Authors: Li Qianglong , Li Feng , Liu Hongjun , Zhao Wei , Cao Xue , Zhao Hualong , Wang Yishan , Wen Wenlong , Si Jinhai 
Published: February 2024

Abstract
We demonstrate an all-fiber monolithic laser source from a gain-managed nonlinear (GMN) fiber amplifier with a CFBG-based pre-compressor that generates high-contrast pulses with a repetition rate of 80 MHz, average power of 1.6 W, and pulse duration of sub-50 fs. The compressed pulse quality can be optimized by tuning the parameters of the seed pulses injected into the GMN amplifier by controlling the pump power of the fiber pre-amplifier. This compact and cost-effective laser system is a simplified design of the GMN amplification-based femtosecond fiber laser systems. With alignment-free characteristics in the amplifiers and clean compressed pulses, it is easy to assemble and use in applications such as multi-photon microscopy.
The 23 Factorial Design in R
Authors: Hodžić D , Crnkić A , Rošić H , Hasanagić R 
Published: February 2024

Abstract
The paper describes the factorial design of the experiment with three input factors that change on two levels. For given values of the input parameters, it is shown how to obtain a variance analysis table and which factors and interactions between factors are significant. The example was done in the software intended for the design of the experiment and in the software R. It is shown how to use the software R to arrive at the final solution of the given example.
A Review on artificial pancreas mathematical models
Authors: Gavrila B T , Balas V E , Balas M M 
Published: February 2024

Abstract
The development of an artificial pancreas (AP) has been a topic of interest in the field of diabetes management for several decades. An AP system is designed to mimic the function of the pancreas by continuously monitoring blood glucose levels and delivering insulin or glucagon in response to changes in glucose concentration. Mathematical models play a crucial role in the development and evaluation of AP systems, as they enable the simulation and prediction of the system’s performance. This review paper provides an overview of the mathematical models used in AP research. The paper discusses the strengths and limitations of each type of model, as well as their applications in AP research. The review also highlights the challenges and opportunities in AP model development, such as the need for personalized models and the integration of data from multiple sources. Overall, this review provides a comprehensive understanding of the role of mathematical models in AP research and their potential for improving diabetes management.
An automated approach for traffic light control at pedestrian crossings
Authors: Stroia M D , Hațiegan C , Preduș M F , Muscai C 
Published: February 2024

Abstract
Although technology has evolved explosively in past years in all aspects of our lives and should make our work easier, it still seems like we don’t have enough time and we are in a constant rush. We hurry when we go to work or shopping, when we drive, when we cross the street. Nevertheless, we have clear traffic rules that aim to protect us from possible road accidents, has the thought ever occurred that we could cross the street if no one is crossing, even if the traffic light is red? In this idea, we thought of a different approach to control the alternation of the traffic light, other than through the timer, so as to reduce the waiting times at the traffic light crossing. This traffic light automation solution is detailed in the present paper in which we describe the structural components and operating principles of an improved traffic light model. The main objective for implementing this improved model is to eliminate the waiting dead times at the traffic light crossing.
Impact of electrical equipment on the power factor
Authors: Spunei E , Piroi I , Piroi F 
Published: February 2024

Abstract
A large proportion of electricity consumers alter the electricity quality through the equipment they use. The alteration is caused by a drop in the power factor, which leads to additional losses in the power grid and additional reactive power costs. In order to identify the consumers’ electrical equipment that alter the power factor, we monitor their electricity use in a production hall looking at the variation of the effective average values of voltages, currents, powers and power factor. The analysis of these records gives us the difference between the power factor and cos φ (the phase difference between phase voltage and phase current in single-phase operation). Our monitoring shows, at the same time, the necessity of an individual analysis of each electrical equipment in the production hall under observation, as well the necessity to locally compensate the power factor.
Dynamic simulation of the differential gear in road vehicles
Authors: Miklos I Zs , Miklos C C , Alic C I 
Published: February 2024

Abstract
The differential gear is a mechanism that is part of the kinematic chain of the vehicle’s transmission. The differential gear has the role of dividing the self-propulsion power flow received from the main drive into two branches, each transmitted to a drive wheel, giving them the possibility to rotate with different angular velocities, depending on the driving conditions. The present work presents the possibilities of computer-aided design and 3D modeling of the main drive and differential gear, respectively the bevel pinion, the crown wheel, the planet pinions and the satellites, using Autodesk Inventor Professional. The 3D model of the main drive - differential gear assembly, considered as a mechanism, was subjected to a dynamic study, using the Dynamic Simulation module. This involves the modeling of the kinematic couplings, the definition of the drive movement parameters and the external loads, respectively the graphical visualization of the kinematic and kinetostatic results for the various components of the mechanism, in real operating conditions, during a kinematic cycle. At the same time, based on the obtained results, the analysis by the finite element method of the most critical component elements, under straight-line driving and turning conditions, is presented.
Fast coherent control of nitrogen-14 spins associated with nitrogen-vacancy centers in diamonds using dynamical decoupling
Authors: Mizuno Kosuke , Fujisaki Ikuya , Tomioka Hiroyoshi , Ishiwata Hitoshi , Onoda Shinobu , Iwasaki Takayuki , Arai Keigo , Hatano Mutsuko 
Published: February 2024

Abstract
A nitrogen-vacancy (NV) center in a diamond enables the access to an electron spin, which is expected to present highly sensitive quantum sensors. Although exploiting a nitrogen nuclear spin improves the sensitivity, manipulating it using a resonant pulse requires a long gate time owing to its small gyromagnetic ratio. Another technique to control nuclear spins is a conditional rotation gate based on dynamical decoupling, which is faster but unavailable for nitrogen spins owing to the lack of transverse hyperfine coupling with the electron spin. In this study, we generated effective transverse coupling by applying a weak off-axis magnetic field. An effective coupling depends on the off-axis field; the conditional rotation gate on the nitrogen-14 spins of an NV center was demonstrated within 4.2 μs under an 1.8% off-axis field and a longitudinal field of approximately 280 mT. We estimated that a population transfer from the electron to nitrogen spins can be implemented with 8.7 μs. Our method is applicable to an ensemble of NV centers, in addition to a single NV center.