bluuebunny/crossref_metadata_2025_split huggingface dataset:
Optimal scheduling and management of grid‐connected distributed resources using improved decomposition‐based many‐objective evolutionary algorithm
Authors: Abbas Ghulam , Wu Zhi , Ali Aamir 
Published: July 2024

AbstractThis paper emphasizes the integration of wind and photovoltaic (PV) generation with battery energy storage systems (BESS) in distribution networks (DNs) to enhance grid sustainability, reliability, and flexibility. A novel multi‐objective optimization framework is introduced in this study to minimize energy supply costs, emissions, and energy losses while improving voltage deviation (VD) and voltage stability index (VSI). The proposed framework comprising normal boundary intersection (NBI) and decomposition‐based evolutionary algorithms (DBEA) determines the optimal siting and sizing of renewable‐based distributed resources, considering load demand variations and the intermittency of wind and solar outputs. The comparative analysis establishes that the proposed strategy performs better than many contemporary algorithms, specifically when all the objective functions are optimized simultaneously. The validation of the proposed framework was carried out on the standard IEEE‐33 bus test network, which demonstrates significant percentage savings in energy supply costs (49.6%), emission rate (62.2%), and energy loss (92.3%), along with enormous improvements in VSI (91.9%) and VD (99.8953%). The obtained results categorically underline the efficiency, reliability, and robustness of the proposed approach when employed on any complex distribution network comprising multiple renewable energy sources and battery storage systems.
Dossier : « La recherche au défi de la crise des temporalités » : Mauvais temps sur la métropole grenobloise ? Pour une analyse transdisciplinaire de la relation aléas hydroclimatiques/tempo sociétal/timing organisationnel
Authors: Renou Yvan , Brochet Antoine , Creutin Jean-Dominique , Cartier Stéphane , Kharbouche Mohammed , Blanchet Juliette 
Published: July 2024

Déployant une méthodologie originale, cet article étudie la nature du couplage entre l’évolution climatique à l’échelle métropolitaine et les stratégies d’adaptation socioéconomique mises en œuvre pour y faire face. L’analyse située du système métropolitain grenoblois illustre notamment comment le rythme de l’organisation collective peine à suivre l’évolution climatique locale. Ce « climat de mauvais temps » trace, via la notion de régime de risque d’inondation, la fréquence des extrêmes hydroclimatiques, le rythme d’adaptation des territoires et les modalités concrètes d’organisation collective. Pour affronter ces enjeux temporels, il semble urgent qu’émergent des coalitions transdisciplinaires localisées. Structurées scientifiquement et politiquement, ces dernières sont appelées à coproduire une information climatique robuste et pertinente et à imaginer des stratégies soutenables pour le territoire. Afin de consolider analytiquement cette dynamique, nous invitons à un approfondissement de l’enjeu temporel au sein de la perspective des communs.
Synthesis of Difluoromethyl Chromono[3,2-c]pyrazolines/pyrazoles by [3+2] Cycloaddition Reaction of Difluoroacetohydrazonoyl Bromides with 3-EWG-Chromones
Authors: Wang Ke-Hu , Hu Yulai , Liang Xiuwen , Luo Wenjing , Chen Maizhuo , Wang Junjiao , Huang Danfeng 
Published: July 2024

AbstractA highly convenient and straightforward strategy for the synthesis of difluoromethyl substituted tricyclic fused chromono[3,2-c]pyrazolines/pyrazoles is developed via [3+2]-cycloaddition of difluoroacetohydrazonoyl bromides to chromene derivatives bearing an electron-withdrawing group at the 3-position. The reaction has the advantages of mild conditions, good tolerance of functional groups, and simple operation.
Generalized solutions to the model of compressible viscous fluids coupled with the Poisson equation
Authors: Tan Zhong , Yang Hui 
Published: July 2024

This paper deals with the model of compressible viscous and barotropic fluids coupled with the Poisson equation in a bounded domain Ω⊂R3 with C2+α (0 &lt; α &lt; 1) boundary ∂Ω. We prove the existence and weak-strong uniqueness of dissipative solutions when the adiabatic exponent γ &gt; 1. We find that the Poisson term ρ∇Φ is not integrable when γ∈(1,32). We will make full use of the Poisson equation and energy inequality to overcome this difficulty. Finally, we obtain that ρ∇Φ leads to the decrease of Reynolds stress R and the increase of the energy dissipation defect E.
Terminology, popularisation and ideology in contemporary China
Authors: Bertulessi Chiara 
Published: July 2024

Abstract
This paper explores the relationship between terminology, the popularisation of scientific and technical knowledge
and ideology in the People’s Republic of China. Specifically, it presents a study that focuses on an online daily column entitled
‘Scientific & Technical Term of the Day’ (每日科技名词),
a terminology popularisation project promoted by China’s contemporary political leadership and implemented through the digital
institutional platform Xuexi qiangguo 学习强国.
Drawing on the theoretical frameworks of critical discourse studies and legitimation in discourse, as well as
frame analysis and frame semantics, the paper presents an analysis of expository texts designed to complement the knowledge provided by
terminographic definitions of the terms published in the daily column. The focus is on the framing of China and the Party-state in
these texts, which, it is argued, can also be interpreted as legitimation strategies.
Integrating machine learning and the finite element method for assessing stiffness degradation in photovoltaic modules
Authors: Li Weiqing 
Published: July 2024

Abstract
This study introduces a novel machine learning (ML) method utilizing a stacked auto-encoder network to predict stiffness degradation in photovoltaic (PV) modules with pre-existing cracks. The input data for the training process was derived from numerical simulations, ensuring a comprehensive representation of module behavior under various conditions. The findings highlight the robust predictive capability of the model, as evidenced by its impressive R2 value of 0.961 and notably low root mean square error (RMSE) of 4.02%. These metrics significantly outperform those of other conventional methods, including the artificial neural network with R2 of 0.905 and RMSE of 9.43%, the space vector machine with R2 of 0.827 and RMSE of 17.93%, and the random forest (RF) with R2 of 0.899 and RMSE of 11.02%. Moreover, the findings suggest that the predictive dynamics of degradation are affected by the varying weight functions of different input parameters, such as climate temperature (CT), grain size (GS), material effort, and pre-crack size, as the degradation level changes. Furthermore, a geometric analysis reveals model deficiencies where significant overestimations correlate with thicker glass components, while pronounced underestimations are predominantly associated with thinner layers of polycrystalline silicon wafer and Ethylene Vinyl Acetate in the module. As a case study, it demonstrated that to maintain a constant degradation level between 1.30 and 1.32 in a PV module with components featuring consistent geometric attributes, the input parameters must be kept within specific ranges: CT ranging from 33 °C to 57 °C, GS ranging from 36 to 81 μm, material effort ranging from 0.74 to 0.81, and pre-crack size ranging from 24 to 32 μm. Therefore, this underscores that the ML model not only predicts degradation but also delineates the parameter space required to achieve a consistent output value.
Covalent surface modification of single-layer graphene-like BC6N nanosheets with reactive nitrenes for selective ammonia sensing via DFT modeling
Authors: Baachaoui Sabrine , Hajlaoui Rabiaa , Aoun Sami Ben , Fortunelli Alessandro , Sementa Luca , Raouafi Noureddine 
Published: July 2024

Abstract
Novel graphene-like nanomaterials with a non-zero bandgap are important for the design of gas sensors. The selectivity toward specific targets can be tuned by introducing appropriate functional groups on their surfaces. In this study, we use first-principles simulations, in the form of density functional theory (DFT), to investigate the covalent functionalization of a single-layer graphitized BC6N with azides to yield aziridine-functionalized adducts and explore their possible use to realize ammonia sensors. First, we determine the most favorable sites for physical adsorption and chemical reaction of methylnitrene, arising from the decomposition of methylazide, onto a BC6N monolayer. Then, we examine the thermodynamics of the [1 + 2]–cycloaddition reaction of various phenylnitrenes and perfluorinated phenylnitrenes para-substituted with (R = CO2H, SO3H) groups, demonstrating favorable energetics. We also monitor the effect of the functionalization on the electronic properties of the nanosheets via density of states and band structure analyses. Finally, we test four dBC6N to gBC6N substrates in the sensing of ammonia. We show that, thanks to their hydrogen bonding capabilities, the functionalized BC6N can selectively detect ammonia, with interaction energies varying from −0.54 eV to −1.37 eV, even in presence of competing gas such as CO2 and H2O, as also confirmed by analyzing the change in the electronic properties and the values of recovery times near ambient temperature. Importantly, we model the conductance of a selected substrate alone and in presence of NH3 to determine its effect on the integrated current, showing that humidity and coverage conditions should be properly tuned to use HO2C-functionalized BC6N-based nanomaterials to develop selective gas sensors for ammonia.
Robust optimization strategies for contour uncertainties in online adaptive radiation therapy
Authors: Smolders A , Bengtsson I , Forsgren A , Lomax A , Weber D C , Fredriksson A , Albertini F 
Published: July 2024

Abstract

Objective. Online adaptive radiation therapy requires fast and automated contouring of daily scans for treatment plan re-optimization. However, automated contouring is imperfect and introduces contour uncertainties. This work aims at developing and comparing robust optimization strategies accounting for such uncertainties. Approach. A deep-learning method was used to predict the uncertainty of deformable image registration, and to generate a finite set of daily contour samples. Ten optimization strategies were compared: two baseline methods, five methods that convert contour samples into voxel-wise probabilities, and three methods accounting explicitly for contour samples as scenarios in robust optimization. Target coverage and organ-at-risk (OAR) sparing were evaluated robustly for simplified proton therapy plans for five head-and-neck cancer patients. Results. We found that explicitly including target contour uncertainty in robust optimization provides robust target coverage with better OAR sparing than the baseline methods, without increasing the optimization time. Although OAR doses first increased when increasing target robustness, this effect could be prevented by additionally including robustness to OAR contour uncertainty. Compared to the probability-based methods, the scenario-based methods spared the OARs more, but increased integral dose and required more computation time. Significance. This work proposed efficient and beneficial strategies to mitigate contour uncertainty in treatment plan optimization. This facilitates the adoption of automatic contouring in online adaptive radiation therapy and, more generally, enables mitigation also of other sources of contour uncertainty in treatment planning.
A non-neutral 1D fluid model of hall thruster discharges: full electron inertia and anode sheath reversal
Authors: Poli D , Fajardo P , Ahedo E 
Published: July 2024

Abstract
A non-neutral model (NNM) of the axial plasma discharge in a Hall thruster, including full electron inertia, is presented. In the finite-volume formulation, two types of sheath boundary conditions previously used in the literature are tested and proven to behave practically identically in this model. Both normal and reversed (i.e. electron repelling and attracting, respectively) anode sheaths are admitted. This model is compared with the quasineutral model developed in a previous work, which includes only azimuthal electron inertia and normal anode sheaths. Both models agree excellently within the parametric region where steady-state solutions with a normal anode sheath exist. The NNM shows the absence of steady-state solutions with a reversed anode sheath. Nonetheless, a reversed sheath can appear during the transient to a steady-state solution with a normal sheath and the periodic transition from a normal to a reversed sheath can be observed in the presence of breathing-mode oscillations. In other cases, the reversed sheath leads to the discharge shut-off. Full electron inertia is always important in the presence of a reversed sheath. The parametric threshold of the wall accommodation parameter from a stationary solution to a breathing mode one differs slightly between the non-neutral and the quasi-neutral model.
Parity violation in primordial tensor non-Gaussianities from matter bounce cosmology
Authors: Akama Shingo , Zhu Mian 
Published: July 2024

Abstract
It has been shown that primordial tensor non-Gaussianities from a cubic Weyl action with a
non-dynamical coupling are suppressed by the so-called slow-roll parameter in a conventional framework of slow-roll inflation. In this paper, we consider matter bounce cosmology in which the background spacetime is no longer quasi-de Sitter, and hence one might expect that the matter bounce models could predict non-suppressed non-Gaussianities. Nevertheless, we first show that the corresponding non-Gaussian amplitudes from the cubic Weyl term with a non-dynamical coupling are much smaller than those from the conventional slow-roll inflation, in spite of the fact that there is no slow-roll suppression. We then introduce a dynamical coupling that can boost the magnitude of graviton cubic interactions and clarify that there is a parameter region where the tensor non-Gaussianities can be enhanced and can potentially be tested by cosmic microwave background experiments.
Initial testing of Alfvén eigenmode feedback control with machine-learning observers on DIII-D
Authors: Rothstein Andrew , Jalalvand Azarakhsh , Abbate Joseph , Erickson Keith , Kolemen Egemen 
Published: July 2024

Abstract
A first of its kind fully data-driven system has been developed and implemented into the DIII-D plasma control system to detect and control Alfvén eigenmodes (AE) in real-time. Susceptibility to fast ion-induced AE is a challenge in fully non-inductive tokamak operation, which significantly reduces fast-particle confinement and results in degraded fusion gain. Controlling AEs in real-time to improve fast-ion confinement is, hence, important for future advanced tokamak fusion reactors. The models were implemented and tested in experiments which showed that neural networks (NN) are highly effective in detecting 5 types of AE (BAE, EAE, LFM, RSAE, TAE) using high resolution ECE. To estimate the neutron deficit, a NN has been trained that outputs the classical neutron rate using similar inputs to NUBEAM. Also a preliminary ML-based proportional control has been designed and gone through initial testing in experiment to use feedback-control on the neutral beam power to achieve desired amplitude of AE modes and neutron deficits. The effect of AEs on fast-ion confinement is measured by analysing the gap in classical neutron rate from the proposed NN-based NUBEAM and the measured neutron rate.
Reusable optically stimulated luminescence dosimetry films for 2D dose verification of proton therapy
Authors: Clausen S. J. G. , Jensen M. L. , Nielsen C. L. , Jensen M. F. , Muren L. , Søndergaard C. S. , Skyt P. S. , Stick L. B. , Yates E. , Vindbæk S. H. , Balling P. 
Published: July 2024

Abstract
Accurate surface-dose measurements in proton therapy are challenging and often of poor spatial resolution for most dosimeter types. However, optically stimulated luminescence (OSL) based 2D dosimeters could provide the required spatial dose resolution. The aim of this study was to investigate the dosimetric precision and energy dependence of an in-house made reusable dosimeter composed of a silicone-film containing OSL-active nanoparticles. The dosimeter was irradiated with a clinical proton therapy field and the readout dose was compared to the results from a commercial dosimeter. The pixelwise noise-to-signal ratio for the OSL dosimeter remained below 2% for doses above 1 Gy, and the energy dependence was negligible in the investigated energy range.
Effects of signal source to camera distance in Cherenkov dosimetry using polarized imaging
Authors: Poher Audran , Michaud Gérémy , Archambault Louis , Beaulieu Luc 
Published: July 2024

Abstract
As Cherenkov emissions are related to dose, they can be used as signal for dosimetric purposes using polarized imaging. However, when using this method, angular corrections must be applied because of Cherenkov anisotropy. Several Cherenkov light source-to-camera distances were tested to characterize its impact on the deviations from reference values of the calculated dose distributions. Average relative differences ranging from −1.6% to −11% between Cherenkov-based results and scintillation results were extracted. It is observed that an increase in Cherenkov light source-to-camera distance decreases the difference between the Cherenkov optical signal and the dose. This reduces the importance of angular corrections at higher distances (4 m and beyond).
Sorbitol to reduce Fe diffusion in a Fricke gel dosimeter and enhance its resistance to elongation
Authors: Piotrowski Michał , Maras Piotr , Kozicki Marek 
Published: July 2024

Abstract
This work presents a 2D Fricke dosimeter with xylenol orange (XO), gelatine matrix and addition of sorbitol. The dosimeter was irradiated with various monitor units ranging from 500 to 10000 MU (3.6-72 Gy). The addition of sorbitol significantly reduced the diffusion coefficient of Fe3+ ions and improved the mechanical properties of the gel, while the chemical stability of the dosimeter decreased.
Scintillation Imaging as Versatile Tool for Validation of UHDR Treatment Plans Across Modalities
Authors: Clark Megan , Vasytlsiv Roman , Gladstone David , Mascia Anthony , Harms Joseph , Bruza Petr 
Published: July 2024

Abstract
Scintillation imaging has been shown to provide high spatio-temporal surface dose information for delivery verification of ultra-high dose rate (UHDR) beams. To obtain higher dose rates, modified clinical machines are often utilized, requiring extensive re-characterization and treatment validation. The goal of this work was to demonstrate the utility of 1.) projecting surface images to depth and 2.) quinine-doped water tank imaging for 3D beam verification across different UHDR treatment modalities.
Polymer gel dosimetry of added High-Z elements in radiation fields of electrons and photons with low and high photon energy
Authors: Buchner Katharina , Gober Manuela , Berg Andreas 
Published: July 2024

Abstract
A dose enhancement in tumors can in principle be achieved using an enrichment of elements with high atomic number (“High-Z therapy”). The proof of dose enhancement at low non-toxic concentrations remains difficult with standard dosimeters due to the small distance of secondary electrons of X-ray photon energies. We investigated within an exploratory research approach the dose enhancement in tissue equivalent environment using MRI analysis of polymer gel dosimeters doped with molecules containing high-Z elements: bismuth, silver iodide and iopromide, a radio-diagnostic contrast agent for X-ray imaging, in photon fields of low (200 kV X-ray) and high energy (6 MV) and in an electron field (6 MeV). An enhancement of the dose response up to a relative dose enhancement factor rDEexp≌1.4 was observed for low concentrations (w/w=0.006) of iopromide, already approved for vascular angiography with X-rays. Experimental limitations and challenging interpretations are outlined.
Development and verification of a Geant4 model of the electron beam mode in a clinical linear accelerator
Authors: Miloichikova I. , Bulavskaya A. , Bushmina E. , Dusaev R. , Gargioni E. , Gavrikov B. , Grigorieva A. , Stuchebrov S. 
Published: July 2024

Abstract
At present, a significant number of studies are focused on the development of novel methodologies for the fabrication of dosimetry phantoms. One of these methods is to produce heterogeneous samples by 3D printing. In order to select the most appropriate parameters for such products, it is necessary to conduct numerical simulations. In this work, we developed the model of a beam-forming system using a medical linear accelerator as a reference. This model was used to determine simulation parameters and corresponding dose distributions of an electron beam with nominal energies of 6, 12, and 15 MeV in a homogeneous water phantom. These parameters were, in fact, adapted to provide maximum agreement between simulated distributions and those experimentally obtained with the clinical linear accelerator. The beam simulation was performed using the Geant4 Monte Carlo toolkit. The simulation geometry of the accelerator treatment head includes scattering foil and a flattening filter, which are designed for electron beam broadening. Additionally, the beam-forming system was incorporated to collimate the beam to the required size. A metal applicator was included to reduce the contribution of electron scattering in air. The main simulation parameters were iteratively tuned by comparing simulation results with experimentally obtained data. It is shown that the simulated percentage depth dose and transverse profiles for electron beams in water phantom are in good agreement with the experimental data obtained with a cylindrical ionization chamber. This demonstrates that the methodology employed in the development of the numerical model of the medical linear accelerator is vendor-independent, readily implementable, and allows for rapid calculations. Furthermore, the model can be applied for a variety of purposes, including the selection of parameters for the fabrication of heterogeneous dosimetry phantoms.