bluuebunny/crossref_metadata_2025_split huggingface dataset:
A fast and robust constraint-based online re-optimization approach for automated online adaptive intensity modulated proton therapy in head and neck cancer
Authors: Oud Michelle , Breedveld Sebastiaan , Rojo-Santiago Jesús , Giżyńska Marta Krystyna , Kroesen Michiel , Habraken Steven , Perkó Zoltán , Heijmen Ben , Hoogeman Mischa 
Published: February 2024

Abstract

Objective. In head-and-neck cancer intensity modulated proton therapy, adaptive radiotherapy is currently restricted to offline re-planning, mitigating the effect of slow changes in patient anatomies. Daily online adaptations can potentially improve dosimetry. Here, a new, fully automated online re-optimization strategy is presented. In a retrospective study, this online re-optimization approach was compared to our trigger-based offline re-planning (offlineTB re-planning) schedule, including extensive robustness analyses. Approach. The online re-optimization method employs automated multi-criterial re-optimization, using robust optimization with 1 mm setup-robustness settings (in contrast to 3 mm for offlineTB re-planning). Hard planning constraints and spot addition are used to enforce adequate target coverage, avoid prohibitively large maximum doses and minimize organ-at-risk doses. For 67 repeat-CTs from 15 patients, fraction doses of the two strategies were compared for the CTVs and organs-at-risk. Per repeat-CT, 10.000 fractions with different setup and range robustness settings were simulated using polynomial chaos expansion for fast and accurate dose calculations. Main results. For 14/67 repeat-CTs, offlineTB re-planning resulted in <50% probability of D
98% ≥ 95% of the prescribed dose (D
pres) in one or both CTVs, which never happened with online re-optimization. With offlineTB re-planning, eight repeat-CTs had zero probability of obtaining D
98% ≥ 95%D
pres for CTV7000, while the minimum probability with online re-optimization was 81%. Risks of xerostomia and dysphagia grade ≥ II were reduced by 3.5 ± 1.7 and 3.9 ± 2.8 percentage point [mean ± SD] (p < 10−5 for both). In online re-optimization, adjustment of spot configuration followed by spot-intensity re-optimization took 3.4 min on average. Significance. The fast online re-optimization strategy always prevented substantial losses of target coverage caused by day-to-day anatomical variations, as opposed to the clinical trigger-based offline re-planning schedule. On top of this, online re-optimization could be performed with smaller setup robustness settings, contributing to improved organs-at-risk sparing.
Testing validity of 1D models for impurity fraction scaling for divertor detachment with EDGE2D-EIRENE
Authors: Chankin A V , Corrigan G , Huber A ,   JET Contributors
Published: February 2024

Abstract
Predictions of the Huber–Chankin (HC) scaling for the upstream impurity fraction were verified in a series of EDGE2D-EIRENE (‘code’) runs for highly radiating plasmas with nitrogen injection. The main quantity extracted from the code was poloidally averaged, from X-point to X-point, separatrix impurity fraction cZ
in the main scrape-off layer (SOL). Variation of the main working gas (H, D and T) revealed a qualitative agreement between the model and code results owing to the very large isotope difference in the predicted cZ
values caused primarily by the inverse isotope mass dependence of the H-mode power threshold assumed in the HC model and implemented in the code. At the same time, the variation of the toroidal field and safety factor in deuterium cases yielded no correlation between the model predictions and code results. The code showed much higher local impurity fractions (fZ
) in the divertor compared to the main SOL, as well as large case-to-case variations in the divertor to the main SOL ratio of impurity fractions. The analysis of code results has wide-ranging consequences not only for the HC model, but also for other similar 1D models which use simple geometry ignoring strong neutral recycling in the divertor/ Different topology makes plasma parameters in the divertor and main SOL very different, resulting in different impurity charge state composition. Missing mechanisms in 1D codes (e.g. friction and thermo-forces exerted on impurity ions by main working gas ions) lead to impurity density redistribution. Neglecting all above factors, 1D models assume a constant impurity fraction along field lines.
Theoretical investigation of the effect of mole fraction on the electronic and optical properties of a binary armchair antimonene−phosphorene nanoribbon
Authors: Allahverdikhani Tayyebe , Barvestani Jamal , Meshginqalam Bahar 
Published: February 2024

Abstract
In this work, the electronic and optical properties of a binary armchair antimonene-phosphorene nanoribbon have been studied with a variation of the P mole fraction by first-principles calculation method based on density functional theory. The calculated cohesive energy shows that the stability of the binary SbP nanoribbon increases by increasing the molar fraction of phosphorus to 100%. We have demonstrated that the band gap of SbP nanoribbons can be modified by applying different mole fractions. The band gap value of SbP nanoribbon increases firstly up to mole fractions of approximately 50% and decreases up to 80% and then increases. A direct-to-indirect and an indirect-to-direct gap transitions occur at 5 to 75% (except for 35%) and 80 to 100% mole fractions, respectively. The optical properties of the mentioned structures with different mole fractions are analyzed, and it is found that the optical properties of binary SbP nanoribbons changed by P mole fraction; and also, the light absorption peak is mainly concentrated in the ultraviolet region. Compared with the pure antimonene, the light absorption is significantly enhanced after increasing the mole fraction of phosphorus to 100%. From a theoretical point of view, our results can offer promising applications in electronic and optical nanodevices.
Fabrication of highly sensitive memristive device using NiO nanoparticles synthesized by single step wet chemical method
Authors: Pathak B , Kalita P K , Choudhury J P Roy , Dutta A 
Published: February 2024

Abstract
Single step wet chemical method is used to prepare molar concentration varied NiO nanoparticle using PVP as the capping agent. Structural, optical and electrical properties are investigated on the prepared samples and are correlated with growth. TEM shows particle size distribution ∼ 3–4 nm synthesized in the range 0.001–1 M which agrees with XRD and optical measurements. Red shift in absorption is observed in optical measurement with enhancing molarity. Because of lesser size distribution of NiO nanoparticles, larger native defect in the form of oxygen vacancies is expected which may beutilized in fabrication of memristive devices. The sensitivity of the devices is estimated through Roff/Ron and area of pinched hysteresis loopwhich shows promising result. Higher sensitivity is explained due to incorporation of more oxygen vacancies during the growth of NiO nanoparticles synthesized at higher concentration. The experimental memristive characteristics are validated through theoretical model fitting using different window functions.
Numerical solution of fuzzy fractional volterra integro differential equations with boundary conditions
Authors: Agilan K , Parthiban V 
Published: February 2024

Abstract
In this study, the boundary value problem of fuzzy fractional nonlinear Volterra integro differential equations of order 1 < ϱ ≤ 2 is addressed. Fuzzy fractional derivatives are defined in the Caputo sense. To show the existence result, the Krasnoselkii theorem from the theory of fixed points is used, where as the well-known contraction mapping concept is utilized in order to show the solution is unique to the proposed problem. Moreover, a novel Adomian decomposition method is utilized to get numerical solution; the approach behind deriving the solution is from Adomian polynomials, and it is organized according to the recursive relation that is obtained. The proposed method significantly decreases the numerical computations by obtaining solutions without the need of discretization or constrictive assumptions. According to the results, there is substantial agreement between the series solutions produced by the fuzzy Adomian decomposition method. Finally, using MATLAB, the symmetry between the lower and upper-cut representations of the fuzzy solutions is demonstrated in the numerical result.
Nanomechanical-ferroelastics behavior, and the low-temperature ferroelectric manifestation of BiMnO3 thin films
Authors: Umoh G V , Gómez-Ovalle A E , Cruz M P , Leal-Pérez J E , Obot Okure U , Berrio Héctor Urzola , Herrera-Basurto Raúl , Mercader-Trejo F , Hurtado-Macias A 
Published: February 2024

Abstract
Ferroelastic-nanomechanical behavior of BiMnO3 thin films on (100) Nb-doped SrTiO3 substrate is studied at the nanoscale, for the first time using the theories of depth sensing indentation and finite element analysis. This was to understand the redirection of polarization in ferroelastic behavior using piezoelectric direct effect and applying a controlled local force by nanoindentation. The values of the nanomechanical properties Young’s modulus (E), hardness (H), and Stiffness (S) were measured to be E = 142 ± 3 GPa, H = 8 ± 0.2 GPa, and S = 44072 ± 45 N m−1 respectively. Using the experimental mechanical properties, a finite element analysis was carried out to understand the relationship between the irreversible work versus depth curve and plastic-deformation evolution of the thin film-interface-substrate system, associated with the pop-in observed. Von Mises stress maps are presented to clearly illustrate the deformations, mechanical failures, and influences between the BiMnO3 film and the SrTiO3 Substrate. The ferroelastic range for BiMnO3 material was observed between 0 to 12 nm, and the yield strength was Y = 2.6 ± 0.7 GPa. The ferroelectric properties through hysteresis curves were evaluated at two different temperatures of 200 K and 300 K in order to observe the effect of polarization with temperature. Providing better polarization performance at lower temperatures; P

s
= 9.14 ± 0.01 (

μ

C cm–2), P

r
= 2.23 ± 0.02 (

μ

C cm–2) and H

c
= 0.77 kV cm−1.
Propagation of collisional among multi-soliton, multi-singular solition and rogue wave around the critical values in an unmagetized plasma
Authors: Akter Shahrina , Hafez M G , Sakthivel R 
Published: February 2024

Abstract
Progress in understanding the propagation characteristics of (i) collisional acoustic among multi-soliton and multi-singular soliton around the critical values and their corresponding phase shifts and (ii) collision between two rogue waves (RWs) propagating toward each in a plasma environment is presented. The considered plasma environment consists of mobile cold positrons, immobile positive ions and (r, q)-distributed hot positrons, and electrons. To accomplish our goal, the coupled modified Korteweg–de Vries equations (mKdVEs) and nonlinear Schrödinger equations (NLSEs) are derived from the considered plasma environment. Based on the concept of Hirota's bilinear method, the multi-soliton and multi-singular soliton solutions of the coupled mKdVEs are determined directly. In addition, the analytical unstable RWs solutions of the coupled NLSEs are determined. With the impact of physical parameters, (i) the trajectories are described for double, triple, quadruple and quintuple positron acoustic bi-directional multi-soliton and (ii) the variation of collisional RWs profiles are displayed with physical interpretation. The results described by the coupled mKdVEs also show that the scattered double-, triple-, quadruple-, and quintuple-soliton are elastic and preserved their original features oppositely after the collision around the critical value of any specific plasma parameter.
Efficient parameter inference for gravitational wave signals in the presence of transient noises using temporal and time-spectral fusion normalizing flow*
Authors: Sun 孙 Tian-Yang 天阳 , Xiong 熊 Chun-Yu 春雨 , Jin 金 Shang-Jie 上捷 , Wang 王 Yu-Xin 钰鑫 , Zhang 张 Jing-Fei 敬飞 , Zhang 张 Xin 鑫 
Published: February 2024

Abstract
Glitches represent a category of non-Gaussian and transient noise that frequently intersects with gravitational wave (GW) signals, thereby exerting a notable impact on the processing of GW data. The inference of GW parameters, crucial for GW astronomy research, is particularly susceptible to such interference. In this study, we pioneer the utilization of a temporal and time-spectral fusion normalizing flow for likelihood-free inference of GW parameters, seamlessly integrating the high temporal resolution of the time domain with the frequency separation characteristics of both time and frequency domains. Remarkably, our findings indicate that the accuracy of this inference method is comparable to that of traditional non-glitch sampling techniques. Furthermore, our approach exhibits a greater efficiency, boasting processing times on the order of milliseconds. In conclusion, the application of a normalizing flow emerges as pivotal in handling GW signals affected by transient noises, offering a promising avenue for enhancing the field of GW astronomy research.
First-principle based predictions of the effects of negative triangularity on DTT scenarios
Authors: Mariani A. , Balestri A. , Mantica P. , Merlo G. , Ambrosino R. , Balbinot L. , Brioschi D. , Casiraghi I. , Castaldo A. , Frassinetti L. , Fusco V. , Innocente P. , Sauter O. , Vlad G. 
Published: February 2024

Abstract
Plasmas with negative triangularity (NT) shape have been recently shown to be able to achieve H-mode levels of confinement in L-mode, avoiding detrimental edge localised modes. Therefore, this plasma geometry is now studied as a possible viable option for a future fusion reactor. Within this framework, an NT option is under investigation for the full power scenario of the Divertor Tokamak Test (DTT) facility, under construction in Italy, with

δ

t
o
p

=
−
0.32

/

δ

b
o
t
t
o
m

≃
0.02

top/bottom triangularity values at the separatrix. The transport properties of this scenario are studied in this work. Gyrokinetic GENE simulations and integrated modelling using ASTRA with the quasi-linear trapped gyro-Landau fluid (TGLF) model have been performed. The emerging picture from the ASTRA-TGLF runs with boundary conditions at

ρ

t
o
r

=
0.94

is that, in the L-mode NT option, the larger peaking of the kinetic profiles in the edge region is not sufficient to recover the loss of the PT H-mode pedestal, and reach similar central temperature values. Two additional shapes are also considered, obtained by flipping the triangularity of the scenarios, to single out the effect of the triangularity sign. A negligible ‘direct’ effect of the triangularity is found for the L-mode, while a small beneficial effect is observed for the H-mode. The ASTRA-TGLF results are validated by GENE and TGLF stand-alone at two selected radii. GENE shows ITG dominant micro-instability and explains the small beneficial effect of the NT for the H-mode as due to a strong reduction of the heat fluxes, when reversing the triangularity, with a relatively high

T

i

stiffness. An improvement of the predicted performances of the NT DTT scenario could come from

ρ

tor

≳
0.9

, as indicated by some recent experiments at the tokamak à configuration variable (TCV) and ASDEX Upgrade.
Extremal statistics for first-passage trajectories of drifted Brownian motion under stochastic resetting
Authors: Guo Wusong , Yan Hao , Chen Hanshuang 
Published: February 2024

Abstract
We study the extreme value statistics of first-passage trajectories generated from a one-dimensional drifted Brownian motion subject to stochastic resetting to the starting point with a constant rate r. Each stochastic trajectory starts from a positive position x
0 and terminates whenever the particle hits the origin for the first time. We obtain an exact expression for the marginal distribution

P
r

(
M

|

x
0

)

of the maximum displacement M. We find that stochastic resetting has a profound impact on

P
r

(
M

|

x
0

)

and the expected value

⟨
M
⟩

of M. Depending on the drift velocity v,

⟨
M
⟩

shows three distinct trends of change with r. For

v
⩾
0

,

⟨
M
⟩

decreases monotonically with r, and tends to

2

x
0

as

r
→
∞

. For

v
c

<
v
<
0

,

⟨
M
⟩

shows a nonmonotonic dependence on r, in which a minimum

⟨
M
⟩

exists for an intermediate level of r. For

v
⩽

v
c

,

⟨
M
⟩

increases monotonically with r. Moreover, by deriving the propagator and using a path decomposition technique, we obtain, in the Laplace domain, the joint distribution of M and the time tm
at which the maximum M is reached. Interestingly, the dependence of the expected value

⟨

t
m

⟩

of tm
on r is either monotonic or nonmonotonic, depending on the value of v. For

v
>

v
m

, there is a nonzero resetting rate at which

⟨

t
m

⟩

attains its minimum. Otherwise,

⟨

t
m

⟩

increases monotonically with r. We provide an analytical determination of two critical values of v,

v
c

≈
−
1.694
15
D

/

x
0

and

v
m

≈
−
1.661
02
D

/

x
0

, where D is the diffusion constant. Finally, numerical simulations are performed to support our theoretical results.
Quantitative evaluation method of operation reliability of substation relay protection device based on improved neural network algorithm
Authors: Wen Tao , Liu Wei , Jiao Shaolin , Zhu Jia 
Published: February 2024

Abstract
With the increase in power demand and the increasing complexity of the power grid, the operation of relay protection devices in substations is often unreasonable. Therefore, a quantitative evaluation method of operation reliability of relay protection devices in substations based on an improved neural network algorithm is proposed. The time-varying probability of misoperation of relay protection in substation is calculated based on the improved neural network algorithm, identifying misoperation behavior of relay protection device, obtaining the optimal hyperplane decision function, selecting kernel function, and construct a quantitative evaluation function of operation reliability of relay protection device. In the evaluation process, two stages of the evaluation process are carried out, namely, reliability block diagram analysis, failure mode evaluation, and verification of relay protection device operation state, so as to complete the reliability quantitative evaluation. The experimental results show that this method can minimize the error of evaluation training and improve evaluation efficiency. At the same time, the error rate is small, which can be controlled within 0.5%.
Energy flow optimization of an electric-gas-heat integrated energy system based on the energy circuit theory
Authors: Cheng Qian , Zhang Xuexia , Gao Yuhan 
Published: February 2024

Abstract
The energy flow optimization of the integrated energy system (IES) can not only decrease the operating cost of the IES but also maximize the utilization rate of renewable energy. To deal with the problem that the optimization results fall into the local optimal solution due to the over-limit of IES state variables, based on the IES energy circuit theory, this paper established an energy flow optimization model of the electric-gas-heat integrated energy system by taking the weighted sum of the operating cost, state variables over-limit penalty cost, and wind and light abandonment penalty cost as the optimization objective. The growth optimizer (GO) algorithm can avoid the local convergence of the optimization results and accelerate the solving speed of the model. Therefore, the effectiveness and feasibility of the model and the optimization method are confirmed by the simulation example.
Assessment method for 220 kv cable outer sheath damage based on bp neural network
Authors: Li Hongke , Xu Han , Wang Siyi , Zhai Yuxin , Liu Bokai 
Published: February 2024

Abstract
220 kV high-voltage submarine cables find extensive application in offshore wind power transmission systems. Ensuring the safe operation of these cables involves accurately detecting and assessing the extent of damage to the cable sheath. This study begins by constructing a finite element simulation model for the cable based on its actual model. Subsequently, a method for evaluating the cable sheath’s damage state is proposed by using a BP neural network. The network takes ambient temperature, current, and six-point temperatures of the damaged section as input characteristics. Results indicate a correct rate of 94.29% for the BP neural network, demonstrating its effective discrimination of cable sheath damage levels. This approach introduces a novel evaluation method for cable sheath damage.
A comprehensive localization and assessment method for SSO in power systems with wind power
Authors: Lv Wan , Xu Peixin , Zhou Feng , Gao Mingyang , Zhao Zhiqin 
Published: February 2024

Abstract
Subsynchronous Oscillation (SSO) is a common dynamic stability issue in power systems that integrate wind power. This paper proposes a comprehensive method for assessing the localization of SSO in wind power integrated systems. The localization method applies the transient energy flow approach to identify SSO sources in systems with wind power. Additionally, a relevant SSO index system is established where the value of each index is calculated. By using the Fuzzy Inference System (FIS) to judge the index, the SSO disturbance source contribution rating of each area is obtained. Simulation cases demonstrate that the localization method of the transient energy flow approach can effectively identify the SSO disturbance source. Moreover, the SSO disturbance source contribution rating method based on FIS can determine the SSO contribution degree of each area, thus identifying the dominant oscillation disturbance sources. The proposed method can provide valuable insights for formulating emergency control measures.
Ultra-short-term forecast of distributed photovoltaic power based on satellite cloud image and LSTM model
Authors: Wang Xunting , Xu Bin , Li Jianglei , Ding Jinjin , Lou Wei 
Published: February 2024

Abstract
Photovoltaic (PV) power generation, with its volatile, intermittent, and random characteristics, and large-scale PV access pose a threat to grid stability. For this reason, predicting the photovoltaic output will help keep the grid safe and stable. On the basis of the influence of cloud groups on solar radiation, a very short-term forecast of distributed PV energy will be made using satellite cloud picture information to improve the forecast accuracy of PV energy production. The paper presents a method to predict distributed PV power at very short notice based on satellite clouds and a network model with Long Short-Term Memory (LSTM). First, extract a subset of meteorological and PV power data from the forecast area as training samples., and the abnormal part of the samples is cleaned by an isolated forest algorithm. Secondly, the occlusion feature is extracted from the satellite cloud image in the same period. Finally, the measured solar irradiance, meteorological information, and obscuration features are input into the LSTM network for prediction, and the photovoltaic power prediction results in the next 4 hours are obtained. The measured PV power of Jinghai Guangfu Power Station in Hefei, Anhui province on the 5th day was the training sample for the prediction of PV power on the 6th day. The prediction results show that the prediction error is 2.73% when a satellite cloud image is added, and 16.15% when a satellite cloud image is not added, and the prediction error is reduced by 13.42%.