bluuebunny/crossref_metadata_2025_split huggingface dataset:
Technical note: Comprehensive evaluations of gantry and couch rotation isocentricities for implementing proton stereotactic radiosurgery
Authors: Shen Jiajian , Robertson Daniel G. , Bues Martin , Shipulin Konstantin , Liu Wei , Stoker Joshua , Ashman Jonathan B. , Lara Pedro , Keole Sameer R. , Wong William , Vora Sujay A. 
Published: March 2023

AbstractBackgroundMechanical accuracy should be verified before implementing a proton stereotactic radiosurgery (SRS) program. Linear accelerator (Linac)‐based SRS systems often use electronic portal imaging devices (EPIDs) to verify beam isocentricity. Because proton therapy systems do not have EPID, beam isocentricity tests of proton SRS may still rely on films, which are not efficient.PurposeTo validate that our proton SRS system meets mechanical precision requirements and to present an efficient method to evaluate the couch and gantry's rotational isocentricity for our proton SRS system.MethodsA dedicated applicator to hold brass aperture for proton SRS system was designed. The mechanical precision of the system was tested using a metal ball and film for 11 combinations of gantry and couch angles. A more efficient quality assurance (QA) procedure was developed, which used a scintillator device to replace the film. The couch rotational isocentricity tests were performed using orthogonal kV x‐rays with the couch rotated isocentrically to five positions (0°, 315°, 270°, 225°, and 180°). At each couch position, the distance between the metal ball in kV images and the imaging isocenter was measured. The gantry isocentricity tests were performed using a cone‐shaped scintillator and proton beams at five gantry angles (0°, 45°, 90°, 135°, and 180°), and the isocenter position and the distance of each beam path to the isocenter were obtained. Daily QA procedure was performed for 1 month to test the robustness and reproducibility of the procedure.ResultsThe gantry and couch rotational isocentricity exhibited sub‐mm precision, with most measurements within ±0.5 mm. The 1‐month QA results showed that the procedure was robust and highly reproducible to within ±0.2 mm. The gantry isocentricity test using the cone‐shaped scintillator was accurate and sensitive to variations of ±0.2 mm. The QA procedure was efficient enough to be completed within 30 min. The 1‐month isocentricity position variations were within 0.5 mm, which demonstrating that the overall proton SRS system was stable and precise.ConclusionThe proton SRS Winston–Lutz QA procedure using a cone‐shaped scintillator was efficient and robust. We were able to verify radiation delivery could be performed with sub‐mm mechanical precision.
Agreement of Clinician‐Administered and Modified Parent‐Administered House‐Brackmann Scales in Children with Bell's Palsy
Authors: Babl Franz E. , Eapen Nitaa , Herd David , Borland Meredith L. , Kochar Amit , Zhang Michael , Oakley Ed , Hopper Sandy M. , Berkowitz Robert G. , Wilson Catherine L. , Williams Amanda , Mackay Mark T. , Lee Katherine J. , Hearps Stephen ,   the PREDICT (Paediatric Research in Emergency Departments International Collaborative) research network
Published: March 2023

AbstractObjectiveCurrently there is no parent administered scale for facial nerve function in children. We set out to assess the agreement between a newly developed parent‐administered modified version of the House‐Brackmann (HB) scale and the standard clinician‐administered HB scale in children with Bell's palsy.Study DesignSecondary analysis of a triple‐blind, randomized, placebo‐controlled trial of corticosteroids to treat idiopathic facial paralysis (Bell's palsy) in children (6 months to <18 years).SettingMulticenter study at pediatric hospitals with recruitment in emergency departments.MethodsChildren were recruited within 72 hours of symptom onset and assessed using the clinician‐administered and the parent‐administered modified HB scales at baseline, and at 1, 3, and 6 months until recovered. Agreement between the 2 scales was assessed using intraclass coefficient (ICC) and a Bland‐Altman plot.ResultsData were available for 174 of the 187 children randomized from at least 1 study time point. The mean ICC between clinician and parent HB scores across all time points was 0.88 (95% confidence interval, CI: 0.86, 0.90). The ICC for the data collected at baseline was 0.53 (95% CI: 0.43, 0.64), at 1 month was 0.88 (95% CI: 0.84, 0.91), at 3 months was 0.80 (95% CI: 0.71, 0.87) and at 6 months was 0.73 (95% CI: 0.47, 0.89). A Bland‐Altman plot indicated a mean difference between the 2 scores (clinician‐reported minus parent‐reported) of only −0.07 (95% limits of agreement −1.37 to 1.23).ConclusionThere was good agreement between the modified parent‐administered and the clinician‐administered HB scales.
Trends in Swallowing Outcomes Following Deintensified Treatment in Selected p16+ Oropharyngeal Carcinoma
Authors: Lee Esther , Magge Hari , Park Isabel , Shakhtour Leyn , Li Ning‐Wei , Schottler Jennifer , Joshi Arjun S. , Thakkar Punam G. , Goodman Joseph F. 
Published: March 2023

AbstractObjectiveIdentify trends in swallowing outcomes in p16+ oropharyngeal squamous cell carcinoma following neoadjuvant chemotherapy+surgery (NAC+S) versus neoadjuvant chemotherapy+surgery+radiation (NAC+S+R).Study DesignCohort study.SettingSingle academic institution.MethodsSwallowing outcome was measured using a validated questionnaire, MD Anderson Dysphagia Inventory (MDADI). MDADI scores were compared between NAC+S and NAC+S+R groups in short‐term (<1 year), middle‐term (1‐3 years), and long‐term (>3 years). Clinical factors associated with MDADI scores were explored using a linear mixed model. Statistical significance was established at p < .05.ResultsSixty‐seven patients met the inclusion criteria and were divided into 2 groups: NAC+S (57 [85.1%]) and NAC+S+R (10 [14.9%]). All patients had improved MDADI scores in the middle‐term compared to short‐term (NAC+S: score increase = 3.43, p = .002; NAC+S+R: score increase = 11.18, p = .044), long‐term compared to short‐term (NAC+S: score increase = 6.97, p < .001; NAC+S+R: score increase = 20.35, p < .001), and long‐term compared to middle‐term (NAC+S: score increase = 3.54, p = .043; NAC+S+R: score increase = 9.18, p = .026). NAC+S patients had better MDADI scores than NAC+S+R patients at short‐term (83.80 vs 71.26, p = .001). There was no significant difference in swallowing function in the middle‐term or long‐term.ConclusionRegardless of treatment type, swallowing will likely be improved in the middle‐term and long‐term compared to the short‐term. Patients treated with NAC+S+R will have worse short‐term swallowing function. However, in the middle‐term and long‐term, there is no significant difference in swallowing function between patients treated with NAC+S and NAC+S+R.
Simulation models investigating the dynamic characteristics of shock isolators
Authors: Clasen Michael , Sachau Delf 
Published: March 2023

AbstractIn the marine environment, naval vessels are often influenced by underwater compression waves. Transport and dangerous goods require advanced protection beyond linear, static considerations. Therefore with regard to shock influence, the dynamic characteristics of helical wire‐cable‐isolators are investigated. The shock impact is given by basepoint acceleration measurement data exciting a mechanical model observing nonlinear stiffness as well as hysteretic damping effects. Three simulation models are presented here: the advanced Kelvin‐Voigt model, the join patch model and the modified Bouc‐Wen‐Model. A comparison between simulation and measurement results is given.
A Machine Learning Enabled Image‐data‐driven End‐to‐end Mechanical Field Predictor For Dual‐Phase Steel
Authors: Lin Binbin , Medghalchi Setareh , Korte-Kerzel Sandra , Xu Bai-Xiang 
Published: March 2023

AbstractThis contribution presents convolutional neural nets (CNN) based surrogate models for prediction of von Mises stress and equivalent plastic strain fields of commonly used Dual‐Phase (DP) steels in automotive applications. The models predict field quantities in an end‐to‐end manner, driven by segmented phase images from real experimental scanning electron micrographs as inputs and FEM calculations as outputs. Hereby, we train CNN models with the U‐net neural network structure based on around 900 elastoplastic FEM simulations of various DP steel microstructure samples under tensile test. The trained CNN models are validated and tested on 250 and 50 samples, respectively. Thereby CNN models are employed sequentially for different tasks , from the real micrographs to segmented phase maps, then from segmented phase maps to stress, strain field predictions, in an end‐to‐end manner. The field predictor model results show good agreement with the test data and convincing performance on unseen microstructural dataset. This work demonstrates the large potential of a Machine Learning model to make accumulatively use of the physics‐based simulation data of large number of boundary value problems with varying microstructure. It recaptures not only the physics, implied in each simulation training data obtained from the partial different governing equations of mechanics, but also the overarching correlation between the microstructure and the stress and strain field responses.
Eigenvalue Optimization with respect to Shape‐Variations in Electromagnetic Cavities
Authors: Herter Christine , Schöps Sebastian , Wollner Winnifried 
Published: March 2023

AbstractThe article considers the optimization of eigenvalues in electromagnetic cavities by means of shape variations. The field distribution and its frequency in a radio‐frequency cavity are governed by Maxwell's eigenvalue problem. To this end, we utilize a mixed formulation by Kikuchi (1987) and a mixed finite element discretization by means of Nédélec and Lagrange elements. The shape optimization is based on the method of mappings, where a Piola transformation is utilized to assert conformity of the mapped spaces. We derive the derivatives by the use of adjoint calculus for the constraining Maxwell eigenvalue problem. In two numerical examples, we demonstrate the functionality of this method.
Enhanced Hamiltonian Monte Carlo simulations using Hamiltonian neural networks
Authors: Thaler Denny , Dhulipala Somayajulu L. N. , Bamer Franz , Markert Bernd , Shields Michael D. 
Published: March 2023

AbstractMarkov Chain Monte Carlo simulations form an essential tool for exploring high‐dimensional target distributions. Metropolis developed a fundamental random walk algorithm which was improved by Hastings later. The result is known as the Metropolis‐Hastings algorithm, which enables the exploration of multi‐dimensional distributions. The main drawbacks of this algorithm are its high auto‐correlation and slow exploration of the target distribution space. In order to increase efficiency, researchers have proposed various modifications to this algorithm. In particular, the Hamiltonian Monte Carlo simulation enhances the efficient exploration of the target probability density. The algorithm uses mechanisms inspired by Hamiltonian dynamics to propose a new sample for the target distribution. For reliability analysis, the incorporation of subset simulation and Hamiltonian Monte Carlo methods has shown promising results. However, using the Hamiltonian Monte Carlo method to sample is computationally expensive, especially when dealing with high‐dimensional problems and performing several steps to propose a new state. In this contribution, we show the general applicability of Hamiltonian neural networks to speed up the proposal of new samples within the Hamiltonian Monte Carlo method.
Numerical analysis of stress tensor mapping without an external solver
Authors: Wagner Jérôme , Dröder Klaus , Thater Raphael , Hürkamp André 
Published: March 2023

AbstractTo further the accuracy of a virtual process, links between sequenced numerical methods are established to create a process chain, which considers all influences on a manufactured part in its early design stages. In order to transform numerical results into initial conditions of a preceding simulation method, the data is “mapped" from a source to a target finite element mesh. The data transfer depends heavily on the difference in mesh discretization as well as the utilized interpolation method. Errors occur using different inter‐ and extrapolation methods. This contribution aims to establish a hybrid interpolation method to transfer tensorial stress data between FEM meshes without using an external solver. The applied method consists partly of a radial basis and of a weighted areas interpolation.
Phenomenological material model for damage in steel‐fiber reinforced high performance concrete during low cycle fatigue
Authors: Pise Mangesh , Brands Dominik , Schröder Jörg , Gebuhr Gregor , Anders Steffen 
Published: March 2023

AbstractA phenomenological material model is developed to understand the pseudo‐ductile material behavior of steel fiber reinforced high performance concrete (HPC) during failure. In that respect, an energy function is formulated using an additive composition of a transversal isotropic elasto‐plastic model and an elasto‐plastic phase‐field model representing the individual behavior of the steel fibers and the concrete material, respectively. Comparing the experimental data and numerical results of three‐point bending beam tests at low cycle for steel fiber reinforced HPCs, the efficiency of the presented model is verified.
Modeling simultaneous momentum and passive scalar transfer in turbulent annular Poiseuille flow
Authors: Tsai Pei-Yun , Schmidt Heiko , Klein Marten 
Published: March 2023

AbstractSimultaneous momentum and passive scalar transfer in weakly heated pressure‐driven turbulent concentric annular pipe flow is numerically investigated using the cylindrical formulation of the stochastic one‐dimensional turbulence (ODT) model, which is utilized here as standalone tool. In the present study, we focus on the model calibration for heated annular pipes based on recent reference direct numerical simulations (DNS) from Bagheri and Wang (Int. J. Heat Fluid Flow 86, 108725, 2020; Phys. Fluids 33, 055131, 2021). It is shown that the model is able to individually capture scalar and momentum transfer, but not both equally well at the same time. We attribute this to less dissimilar scalar and momentum transport in the model at the low Reynolds number investigated. It is argued that the model prefers a fully developed turbulent state due to its construction. Nevertheless, it is demonstrated that ODT is able to reasonably capture the radial inner‐outer asymmetry of the scalar and momentum boundary layers which yields better predictive capabilities than wall‐function‐based approaches.
A mesoscale model of non‐crimp fabrics based on a deep learning framework
Authors: Zhou Shuang , Hillgärtner Markus , Abdusalamov Rasul , X. Duong Thang , Itskov Mikhail 
Published: March 2023

AbstractNon‐crimp fabrics (NCFs) are a type of textile characterized by straight and long fibers. Due to their lightweight structures, they are widely used for fiber‐reinforced composites in automotive, aerospace, and other fields. NCFs consist of several differently oriented layers of unidirectional fibers, stacked on top of each other, and stitched together by stitching yarns. Due to this structure, constitutive modeling of the anisotropic properties of NCFs is still challenging requiring an accurate description, especially for multi‐axial loading.In this work, a deep learning framework constructed by artificial neural networks (ANNs) is presented that describes the constitutive behavior of NCFs. Such a framework is able to learn not only from the provided load‐displacement relation by experimental data of existing materials, but also from additional relevant information, such as geometric characteristics. The framework allows predicting the constitutive behavior of new fabric materials, whose experimental data are unavailable yet.This contribution aims to establish a constitutive model of dry NCFs based on a deep learning framework trained from virtual experimental data provided by finite element simulations of representative volume elements (RVEs) at the mesoscale. NCFs with only two families of fibers perpendicular to each other and stitched together are considered. The proposed constitutive model is capable of predicting the in‐plane material response of NCFs under arbitrary multi‐axial loading conditions. To this end, a procedure of training ANN for reaction forces responding to displacements of RVEs is investigated.In order to guarantee the predictive capability for various NCFs under multi‐axial loading conditions, the artificial neural network is used to learn from simulations of the same RVE provided by changing its fiber bundle properties (tensile moduli and shear moduli) and loading directions at the mesoscale. Finally, the proposed constitutive model is verified by comparing the predictive results with reference data sets for various materials in arbitrary axial loading.
Graph Neural Network enhanced Finite Element modelling
Authors: Gulakala Rutwik , Markert Bernd , Stoffel Marcus 
Published: March 2023

AbstractIn this study, we introduce a Graph network‐enhanced Finite Element approach to accelerate Finite Element simulations. We utilize the discretized geometry from a Finite Element pre‐processor to establish the graph and use the Graph Neural Network to solve the boundary value problem of the discretized domain. The advantage of graph neural networks is that they have a similar structure as compared to a discretized domain with nodes and elements. The underlying dynamics of the system are computed via a learned message‐passing. The goal here is to enhance and accelerate the FEM simulations using the proposed GNN network by incorporating the underlying mechanics knowledge into the network to enhance the generalizing ability of the network on various loading and boundary conditions. All the proposed studies in the literature where graph networks are applied to Finite Element Methods use images as input and output. The advantage of the proposed model is that it takes inputs such as the nodal information, their corresponding edges, nodal coordinates and the boundary conditions for each particular node from a Finite Element pre‐processor and computes the von‐Mises stress at each node along with their edge connections as output that can be read by a Finite Element post‐processor.
Characteristics and completeness of spontaneous reports by reporter's role in Germany: An analysis of the EudraVigilance database using the example of opioid‐associated abuse, dependence, or withdrawal
Authors: Jobski Kathrin , Bantel Carsten , Hoffmann Falk 
Published: March 2023

AbstractSpontaneous reporting is based on the experience of all healthcare professionals (HCPs) but also consumers/non‐HCPs and therefore reveals a broad picture of a drug's adverse reactions. Recent studies found substantial differences between reports from these varying sources including the reports' completeness. Using the example of opioid‐associated abuse, dependence, or withdrawal, this study analyzed the completeness and characteristics of spontaneous reports from Germany focusing on the reporter. Based on EudraVigilance data, we included all cases of abuse, dependence, or withdrawal associated with opioids indicated for pain therapy and filed from Germany until 2018. Completeness and characteristics were analyzed by a reporter (physician, pharmacist, other HCPs, consumers/non‐HCPs) and also by time period to account for other influencing factors. In total, 1721 cases were included, mainly filed by physicians (38.5%) and pharmacists (30.7%). Completeness of demographics varied from 74.5% (other HCPs) to 42.7% (consumers/non‐HCPs). Consumers/non‐HCPs most often provided any indication/comorbidity (75.2%), whereas this was the case for only 20.2% of pharmacists. Large differences between the reporters were found for almost all characteristics. Other HCPs far more often coded a history of drug abuse, dependence, or withdrawal than other reporters (46.9% vs. 11.6%–24.2%, respectively), and fatal outcomes were also mainly filed by other HCPs (68.1% vs. 14.8%–20.4% by all other reporters). Differences in completeness and characteristics were also observed over time. Studies analyzing spontaneous data should consider potential differences between the various reporting groups in terms of completeness and characteristics. Further, the impact of other influencing factors has to be assessed.
Exploring Zn doped η′‐Cu6Sn5: Structural stability, fracture toughness and thermal conductivity
Authors: Li Bo , Yang Ancang , Peng Mingjun , Duan Yonghua 
Published: March 2023

AbstractIn order to investigate the effect of alloying elements on mechanical properties of η′‐Sn‐Cu alloys, the effect of Zn‐doping on the structural stability, elasticity, electrical and thermodynamic properties of η′‐Cu6Sn5 intermetallic in Sn‐Cu alloys have been calculated by first‐principles calculations. The results show that the Zn‐doped η′‐Cu6Sn5 are thermodynamically and dynamically stable. The doped phase is the most stable when Zn replaces Cu1 site. The bulk modulus and shear modulus of η′‐Cu6Sn5 with Zn‐doped Sn1 site are the highest. When Zn replaces Sn, the stiffness is stronger than that when Zn replaces Cu, and the stiffness order is Zn–Sn > Zn–Cu > η′‐Cu6Sn5. Compared with other doping sites, the 3D surface configurations of elastic modulus of Zn–Sn1 η′‐Cu6Sn5 are the largest. In addition, Zn doping improves the fracture toughness and chemical bond strength of the material. The thermal conductivity and electron thermal conductivity of η′‐Cu6Sn5 also increased.
Structure and thermodynamic properties of adducts based on cucurbit[6]uril and Fe(III)/Fe(II) aqua complexes: A DFT examination
Authors: Masliy A. N. , Grishaeva T. N. , Kuznetsov A. M. 
Published: March 2023

AbstractThis study carried out a detailed step‐by‐step PBE/TZVP level analysis of the inclusion of Fe(III)/Fe(II) aqua complexes into the cavity of cucurbit[6]urils (CB[6]). The structural characteristics of all intermediate stable structures formed during the inclusion process from the bulk of aqueous solution to the inclusion compound were obtained. To account for solvation effects, a molecular‐continuum model was used in which six water molecules of the first coordination sphere of aqua complexes and 12 water molecules of the second coordination sphere were taken into account, while the interaction of such a supermolecule with a dielectric medium was accounted within the continuum model (PCM) [Correction added on 9 June 2023, after first online publication. The word molecular continual has been changed to molecular‐continuum in the sentence.]. The process of incorporation of the aqua complex into the cavity was found to be accompanied by a partial desolvation of the second coordination sphere of the aqua complex and a change in the structure of the first coordination sphere. Additionally, the standard electrode potential of the half‐reaction Fe3+(aq) + e = Fe2+(aq) was estimated for all adducts formed in the reaction.