bluuebunny/crossref_metadata_2025_split huggingface dataset:
Novel, liquid crystal formula to overcome LTPS LCD image sticking without adjustment of gamma code, optical, VHR and IS evaluation
Authors: Tao Bo‐Cheng , Zhang Wei , Chou Wen‐Chieh , Wang Fangyu , Huang Yapeng , Li Yanan 
Published: September 2023

AbstractIn this article, novel n‐FFS liquid crystal material from Slichem was used in order to elevate the anti‐backlight long aging effect; a trace amount of free radical trap HALS‐like additive was added, the principle of which can be expressed via Denisov cycle, confirmed by measuring the temporal VHR changes in test cells; three different resolution (FHD ~ QHD) models paired with N19 and N21 were selected for testing by comparing the actual panel. It is verified that the optimized material greatly improves the image sticking performance of the panel and keeping optical performance.
Isopropyl‐branched lard and its potential application as a bio‐based lubricant
Authors: Yosief Hailemichael O. , Sarker Majher I. , Bantchev Grigor B. , Dunn Robert O. 
Published: September 2023

AbstractRegular lard (RL) was chemically modified into isopropyl‐branched lard (BL). The isopropyl group was introduced into the triglyceride structure via a reaction of carbon–carbon double with isopropyl bromide in presence of ethylaluminum sesquichloride. The reaction was confirmed with gas chromatography–mass spectroscopy, nuclear magnetic resonance, infrared spectroscopy. The physical, tribological and chemical properties of the RL, BL and their blendings in polyalphaolefin (PAO) and high‐oleic sunflower oil (HOSuO) were investigated. The BL exhibited better solubility both in HOSuO and PAO than RL. Compared to RL, BL exhibited higher density, viscosity, improved oxidative stability and cold flow properties both as a neat material and blendings in HOSuO or PAO. However, BL displayed lower viscosity index (197 vs. 162) compared to RL. Both RL and BL displayed similar lubricity as HOSuO and showed potential such as a good lubricity additive in PAO even in small amounts (~10 wt%). This study reveals introducing alkyl branching into lard can lead to improved physico‐chemical properties and lubrication performance.
Evaluating organic coating performance by EIS: Correlation between long‐term EIS measurements and corrosion of the metal substrate
Authors: Bongiorno Vincenzo , Michailidou Emmanouela , Curioni Michele 
Published: September 2023

AbstractIn this study, the possibility of obtaining a corrosion indicator from a time series of electrochemical impedance spectra acquired during immersion of intact organic coatings was inspected. To generate a wide distribution in performance, coatings with different pigment volume concentrations were applied on AA2024‐T3 and cold‐rolled mild steel and tested in four different electrolytes and for different exposure times. The relative ranking of anticorrosion performance was based on the visual appearance of the metal substrates after stripping the coating and it correlated well with the estimation of the corrosion charge estimated from the time series of electrochemical impedance spectroscopy spectra.
Data‐driven and artificial intelligence accelerated steel material research and intelligent manufacturing technology
Authors: Geng Xiaoxiao , Wang Feiyang , Wu Hong‐Hui , Wang Shuize , Wu Guilin , Gao Junheng , Zhao Haitao , Zhang Chaolei , Mao Xinping 
Published: September 2023

AbstractWith the development of new information technology, big data technology and artificial intelligence (AI) have accelerated material research and development and industrial manufacturing, which have become the key technology driving a new wave of global technological revolution and industrial transformation. This review introduces the data resources and databases related to steel materials. It then examines the fundamental strategies and applications of machine learning (ML) in the design and discovery of steel materials, including ML models based on experimental data, industrial manufacturing data, and simulation data, respectively. Given the advancements in big data, AI/ML, and new communication technologies, an intelligent manufacturing mode featuring digital twins is deemed critical in guiding the next industrial revolution. Consequently, the application of intelligence manufacturing with digital twins in the iron and steel industry is reviewed and discussed. Furthermore, the applications of ML in service performance prediction of steel products are addressed. Finally, the future development trends for data‐driven and AI approaches throughout the entire life cycle of steel materials are prospected. Overall, this work presents an in‐depth examination of the integration of data‐driven and AI technologies in the steel industry, highlighting their potential and future directions.
J‐filter: An experiment to simplify and isolate specific signals in 1H NMR spectra of complex mixtures based on scalar coupling constants
Authors: Góñez Karen V. , García Juan Suárez , Sardina F. Javier , Pazos Yolanda , Saá Ángela , Martín−Pastor Manuel 
Published: September 2023

AbstractOne‐dimensional selective NMR experiments relying on a J‐filter element are proposed to isolate specific signals in crowded 1H spectral regions. The J‐filter allows the edition or filtering of signals in a region of interest of the spectrum by exploiting the specific values of their 1H‐1H coupling constants and certain parameters of protons coupled to them that appear in less congested parts of the spectrum (chemical shifts and coupling constants). The new experiments permitted the isolation of specific peaks of phytosterol components in a sample obtained from a liquid nutraceutical recommended for lowering blood cholesterol levels in regions with complete overlap in the 1H spectrum.
Stage‐parallel preconditioners for implicit Runge–Kutta methods of arbitrarily high order, linear problems
Authors: Axelsson Owe , Dravins Ivo , Neytcheva Maya 
Published: September 2023

AbstractFully implicit Runge–Kutta methods offer the possibility to use high order accurate time discretization to match space discretization accuracy, an issue of significant importance for many large scale problems of current interest, where we may have fine space resolution with many millions of spatial degrees of freedom and long time intervals. In this work, we consider strongly A‐stable implicit Runge–Kutta methods of arbitrary order of accuracy, based on Radau quadratures. For the arising large algebraic systems we introduce efficient preconditioners, that (1) use only real arithmetic, (2) demonstrate robustness with respect to problem and discretization parameters, and (3) allow for fully stage‐parallel solution. The preconditioners are based on the observation that the lower‐triangular part of the coefficient matrices in the Butcher tableau has larger in magnitude values, compared to the corresponding strictly upper‐triangular part. We analyze the spectrum of the corresponding preconditioned systems and illustrate their performance with numerical experiments. Even though the observation has been made some time ago, its impact on constructing stage‐parallel preconditioners has not yet been done and its systematic study constitutes the novelty of this article.
An LBB‐stable P1/RNP0 finite element based on a pseudo‐random integration method for incompressible and nearly incompressible material flows
Authors: Feulvarch Eric , Brosse Alexandre , Vincent Yannick 
Published: September 2023

AbstractThe aim of this work is to propose a new nodal treatment of the pressure for tetrahedral or triangular meshes devoted to the simulation of incompressible and nearly incompressible material flows. The approach proposed has the interest of fulfilling numerically the LBB condition for P1‐type discretizations over a wide range of element sizes. Thus, the existence of an error estimate is ensured and there is no need for a stabilization technique. For more convenience, the new P1/RNP0 formulation is first detailed for the Stokes problem. It is based on a RNP0 (Random Nodal P0) approximation of the pressure with constant values on nodal subcells whose size is defined by means of a pseudo‐random number generator. For nearly incompressible material flows, the numerical approach is extended to problems involving von Mises elasto‐plasticity. Examples are presented to show the relevance of the new approach for Eulerian and Lagrangian formalisms.
Failure Patterns Within Different Histological Types in Sinonasal Malignancies: Making the Complex Simple
Authors: Liu Qian , Sun Meng , Wang Zekun , Qu Yuan , Zhang Jianghu , Wang Kai , Wu Runye , Zhang Ye , Huang Xiaodong , Chen Xuesong , Wang Jingbo , Xiao Jianping , Yi Junlin , Xu Guozhen , Luo Jingwei 
Published: September 2023

AbstractObjectiveTo analyze the failure patterns in patients with different histological subtypes of sinonasal malignancies (SNMs).Study DesignRetrospectively gathered data.SettingAcademic university hospital.MethodsPatients with SNMs treated at a tertiary referral center between January 1999 and January 2019 were included. We assessed the failure patterns within different histological subtypes.ResultsThe study included 897 patients. The median follow‐up time was 100 months. Adenoid cystic carcinoma (ACC) had a moderate risk of developing local recurrence (LR) and distant metastasis (DM). Compared with ACC, squamous cell carcinoma (SCC), adenocarcinoma (AC), soft tissue sarcoma (STS), and mucosal melanoma (MM) were classified as a high LR risk group. For DM, neuroendocrine carcinoma (NEC), STS, and MM were in the high‐risk group.ConclusionsACC had intermediate local and distant failure risks, while SCC, AC, STS, and MM were at high LR risks. NEC, STS, and MM were at high DM risk.
The Role of the Otolaryngologist in Sexual Health
Authors: Haugen Thorsen , Pichardo Priscilla , Hellums Ryan , Lindemann Logan , Altman Kenneth 
Published: September 2023

AbstractSexual health is an often neglected topic in otolaryngology. Ironically, most sexually transmitted diseases (STDs) demonstrate head and neck manifestations. Furthermore, many aspects of human sexuality, both pathologic and nonpathologic, are also integral to the head and neck. The human papillomavirus (HPV) serves as a prime example of the otolaryngologist's increasingly important role. In recent decades, HPV‐mediated head and neck cancer has surpassed HPV‐mediated cancer in other parts of the body. This dramatic rise has led to not only a change in the staging system, but also a fundamental shift in the treatment paradigm. Similarly, when considering all aspects of sexual health pertaining to the head and neck, a comparable paradigm shift is needed due to the changing needs of our patients. To accomplish this, otolaryngologists must be better educated and take a leading role when it comes to sexual health.
Importance of PET/CT in Initial Workup of Head and Neck Squamous Cell Carcinoma
Authors: Hellums Ryan N. , Pichardo Priscilla F. A. , Altman Kenneth W. , Penn Ellen , Stavrides Kevin P. , Purdy Nicholas C. 
Published: September 2023

AbstractObjectiveAssess the impact of positron emission tomography/computed tomography (PET/CT) on disease staging at presentation in patients with head and neck squamous cell carcinoma.Study DesignRetrospective cross‐sectional review.SettingAcademic multicenter single institution (Geisinger Health System).MethodsAll patients who had PET/CT imaging during workup for head and neck squamous cell carcinoma were included in the study. Pre‐ and post‐PET/CT clinical staging were recorded. Statistical analyses were performed for patients with a change in clinical staging or detection of second primary malignancies on PET/CT.ResultsA total of 292 patients were included in the study, 238 of whom underwent PET/CT imaging as part of their initial workup. Twenty‐eight (11.9%) patients were clinically upstaged on PET/CT with 7 patients having treatment alterations based on imaging. Eighteen (7.6%) patients were found to have second primary malignancies on PET/CT.ConclusionThe current study further illustrates the importance of PET/CT in the workup of head and neck squamous cell carcinoma. Without the inclusion of PET/CT imaging, 19.3% of patients would have either been staged inappropriately or had second primary malignancies missed, again confirming the necessity of comprehensive functional imaging during the initial pretreatment workup.
Model order reduction methods applied to neural network training
Authors: Freitag M.A. , Nicolaus J.M. , Redmann M. 
Published: September 2023

AbstractNeural networks have emerged as powerful and versatile tools in the field of deep learning. As the complexity of the task increases, so do size and architectural complexity of the network, causing compression techniques to become a focus of current research. Parameter truncation can provide a significant reduction in memory and computational complexity. Originating from a model order reduction framework, the Discrete Empirical Interpolation Method is applied to the gradient descent training of neural networks and analyze for important parameters. The approach for various state‐of‐the‐art neural networks is compared to established truncation methods. Further metrics like L2 and Cross‐Entropy Loss, as well as accuracy and compression rate are reported.
Introduction to the numerical flow iteration for the Vlasov–Poisson equation
Authors: Wilhelm Rostislav‐Paul , Kirchhart Matthias , Torrilhon Manuel 
Published: September 2023

AbstractWe present a novel approach to solve the Vlasov–Poisson equation: the numerical flow iteration. It evaluates the numerical solution by storing the low‐dimensional electric potentials and uses these to iteratively reconstruct the characteristics. This reduces the total memory footprint by several orders of magnitude as complexity gets shifted from memory access to computation on‐the‐fly. Furthermore, this ansatz yields strong conservation properties due to the exploitation of the solution structure.
Surface Crouzeix‐Raviart element for the Bochner Laplacian equation
Authors: Mehlmann Carolin 
Published: September 2023

AbstractRecently, a nonconforming finite element method has been derived for vector valued flow problems on the sphere. In the approach, the flow is approximated via edge integration through the Crouzeix‐Raviart element. The discretization is realized on local flat triangles which coincide with the surface of the sphere on the edge midpoints. In this contribution, we derive an energy error estimate for this discretization that takes into account the geometric error as well as the error to the solution of the partial differential equation. The analysis is performed for a vector Laplace problem which includes covariant derivatives of tangential vector fields. The latter are closely related to operators that occur in flow problems on the surface.
Mixed‐integer NMPC for real‐time supervisory energy management control in residential buildings
Authors: Bitner Dimitri , Burda Artyom , Grotjahn Martin , Kirches Christian , Schild Axel , Luck Bennet 
Published: September 2023

AbstractIn recent years, building energy supply and distribution systems have become more complex, with an increasing number of energy generators, stores, flows, and possible combinations of operating modes. This poses challenges for supervisory control, especially when balancing the conflicting goals of maximizing comfort while minimizing costs and emissions to contribute to global climate protection objectives. Mixed‐integer nonlinear model predictive control is a promising approach for intelligent real‐time control that is able to properly address the specific characteristics and restrictions of building energy systems. We present a strategy that utilizes a decomposition approach, combining partial outer convexification with the Switch‐Cost Aware Rounding procedure to handle switching behavior and operating time constraints of building components in real‐time. The efficacy is demonstrated through practical applications in a single‐family home with a combined heat and power unit and in a multi‐family apartment complex with 18 residential units. Simulation studies show high correspondence to globally optimal solutions with significant cost savings potential of around 19%.
On dynamic crack propagation in a lattice Boltzmann method for elastodynamics in 2D
Authors: Müller Henning , Schlüter Alexander , Faust Erik , Müller Ralf 
Published: September 2023

AbstractIn recent years, the development of lattice Boltzmann methods (LBMs) for solids has gained attention. Fracture mechanics as a viable application for these methods has been presented before, albeit for mode III cracks in the context of an LBM for antiplane shear deformation. The performance of the LBM itself is promising, while the usage of a regular lattice simplifies the modelling of fractures significantly. Recent advancements in LBMs for solids, especially the description of Dirichlet‐ and Neumann‐type boundary conditions, now make it possible to extend the LBM simulation of crack propagation to the plane strain case with modes I and II crack opening, including growth with non‐uniform speed in arbitrary directions. For this, the configurational force acting on a crack tip is utilised. The definition of the moments of the LBM, which are based on the balance laws of continuum mechanics, render the evaluation of macroscopic fields in the configuration straightforward. In this work, the general in‐plane case of dynamic crack propagation is shown and necessary considerations for the implementation are discussed. Lastly, numerical examples showcase the capabilities of the proposed method to model dynamic fractures and establish a proof‐of‐concept.
Computational modeling of fracture in polymer nano‐composites undergoing large deformations via the graded‐interphase‐enhanced phase‐field fracture approach
Authors: Kumar Paras , Mergheim Julia 
Published: September 2023

AbstractThe phenomenon of fracture in polymer composites, polymer nano‐composites in particular, entails a multitude of intricate mechanisms including branching and merging of several cracks along with particle debonding and subsequent plastic void growth. This work involves an extension of the standard phase‐field fracture approach by means of the graded interphase concept in order to facilitate the modeling of a wide‐spectrum of fracture responses, which can be observed in experimental studies concerning the fracture behavior of polymer nano‐composites. Herein, motivated by the microstructure morphology of polymer nano‐composites, a continuous grading of the elastic and fracture properties is considered within a finite thickness interphase region around the filler particles. Appropriate tuning of the graded‐interphase model parameters enables to capture a variety of fracture responses, including cohesive failure between the filler particle and the matrix, as demonstrated via the presented numerical examples, which focus on polymer nano‐composites undergoing large deformations prior to fracture.
Toward coupled fire‐structure simulations for forecasting smoke leakage in case of concrete structures under fire
Authors: Palani A. , Kandekar C. , Breuer M. , Weber W. E. 
Published: September 2023

AbstractComputational modeling of the fire‐structure interaction demands the coupling between several models typically implemented in independent simulation software describing distinct physical processes. For instance, in the event of a fire breakout or building on fire, the fire not only increases the temperature of the immediate area but also initiates structural damage, leading to the spalling of the concrete along with the propagation of the smoke, heat, and radiation originating from the fire. As a result of the progressive structural damage caused by the fire such as macro cracks or breakthroughs in the wall, smoke and other hazardous gases begin to disperse and spread into previously unaffected zones. Thus, it represents a coupled multi‐physics problem, which is not well addressed in the scientific community, yet. Therefore, the investigation of such fire‐structure interactions requires a comprehensive computational modeling and simulation framework that couples the consequences of various phenomena with minimal invasive solver modifications. In this work, the structural model treats concrete as a multi‐phase porous material exposed to high temperatures resulting from the fire. For this purpose, the structural solver is at the moment manually coupled with a computational fluid dynamics (CFD) solver to setup a computational framework for such fire‐structure simulations. Herein, the combustion process of the fire and the smoke propagation is carried out using the open‐source software denoted as Fire Dynamics Simulator (FDS) and the thermo–hydro–mechanical fracture is computed using a FEniCS‐based solver. The finite‐difference method based FDS solves the filtered Navier–Stokes equations using the large‐eddy simulation technique to describe the turbulent flow and heat transfer including radiation and combustion inside the fluid domain. The concrete damage such as cracks, holes, or spalling is computed using a phase‐field method in a separate solver based on the thermal boundary conditions from the fire simulation. Subsequently, both solvers are coupled using the open‐source coupling framework preCICE. Based on the rate at which the crack or spalling is developing, the computational domain of the fluid solver has to be adapted taking the generated holes in the wall structure into account for the ongoing CFD simulation. It allows for the leakage of smoke gases through the concrete wall structure and thus the spreading of the fire scenario. The proposed model is illustrated by an exemplary case that forecasts the leakage of smoke and hazardous gases from the successive damage caused by the thermal spalling induced on a concrete wall structure.