bluuebunny/crossref_metadata_2025_split huggingface dataset:
Novel methodologies for solving the inverse unsteady heat transfer problem of estimating the boundary heat flux in continuous casting molds
Authors: Morelli Umberto Emil , Barral Patricia , Quintela Peregrina , Rozza Gianluigi , Stabile Giovanni 
Published: November 2022

AbstractIn this article, we investigate the estimation of the transient mold‐slab heat flux in continuous casting molds given some thermocouples measurements in the mold plates. Mathematically, we can see this problem as the estimation of a Neumann boundary condition given pointwise state observations in the interior of the domain. We formulate it in a deterministic inverse problem setting. After introducing the industrial problem, we present the mold thermal model and related assumptions. Then, we formulate the boundary heat flux estimation problem in a deterministic inverse problem setting using a sequential approach according to the sequentiality of the temperature measurements. We consider different formulations of the inverse problem. For each one, we develop novel direct methodologies exploiting a space parameterization of the heat flux and the linearity of the mold model. We construct these methods to be divided into a computationally expensive offline phase that can be computed before the process starts, and a cheaper online phase to be performed during the casting process. To conclude, we test the performance of the proposed methods in two benchmark cases.
A new stable, explicit, and generic third‐order method for simulating conductive heat transfer
Authors: Kovács Endre , Nagy Ádám 
Published: November 2022

AbstractIn this paper we introduce a new type of explicit numerical algorithm to solve the spatially discretized linear heat or diffusion equation. After discretizing the space variables as in standard finite difference methods, this novel method does not approximate the time derivatives by finite differences, but use three stage constant‐neighbor and linear neighbor approximations to decouple the ordinary differential equations and solve them analytically. In the final expression for the new values of the variable, the time step size appears not in polynomial or rational, but in exponential form with negative coefficients, which can guarantee unconditional stability. The scheme contains a free parameter p. We show that the convergence of the method is third‐order in the time step size regardless of the values of p, and, according to von Neumann stability analysis, the method is stable for a wide range of p. We validate the new method by testing the results in a case where the analytical solution exists, then we demonstrate the competitiveness by comparing its performance with several other numerical solvers.
Efficient, linearized high‐order compact difference schemes for nonlinear parabolic equations I: One‐dimensional problem
Authors: Wang Yanjie , Xie Shusen , Fu Hongfei 
Published: November 2022

AbstractA one‐dimensional nonlinear time‐dependent conservative convection–diffusion‐reaction equation is considered, some linearized high‐order compact (HOC) difference schemes are developed and analyzed. Laplace‐modified method and implicit–explicit high‐order approximation technique are considered for the temporal discretization. While for the spatial discretization, the so‐called high‐order narrow stencil approximations are employed for the nonlinear second‐order spatial derivative, and the HOC difference approximations are considered, respectively, for the nonlinear first‐order spatial derivative and the introduced Laplace term. At each time level, the resulting algebraic system arising from the proposed schemes is linear and has the same (periodic) tridiagonal constant‐coefficient matrix, even though the convection–diffusion‐reaction equation itself has time‐dependent variable coefficients or even strongly nonlinear coefficients. Therefore, the proposed schemes are easy to implement in only computational complexity, where is the number of spatial unknowns per time level. The presented high‐order schemes are proved to be unconditionally stable in the linear case, and optimal‐order error estimates for the nonlinear equation in the discrete H1‐norm are obtained under reasonable restrictions on the temporal stepsize ratio by using the inductive arguments. Finally, ample numerical experiments are carried out to show the high accuracy and efficiency of the schemes.
Experimental study on the effect of molecular weight and chemical composition distribution on the mechanical response of high‐density polyethylene
Authors: Jani Farzad , Sepahi Abdolhannan , Afzali Seyyed Kamal , Houshmand Moayed Saeed 
Published: November 2022

AbstractThis article aims to appraise the effect of microstructure comprising molecular weight distribution and chemical composition distribution on the mechanical properties of high‐density polyethylene (HDPE). HDPE resins were synthesized using several titanium–magnesium‐supported Ziegler–Natta catalysts in the industrial gas phase reactor under the same polymerization condition. Gel permeation chromatography and crystallization elution fractionation (CEF) were conducted on the resins to characterize the molecular weight and comonomer distribution. Crystallization, thermal and rheological behavior were evaluated following differential scanning calorimetry, polarization light microscopy, and rheometric mechanical spectrometry. The resins with higher soluble fraction in trichlorobenzene below 80°C (highly branched low molecular weight chains) exhibited longer crystallization time based on the crystallization kinetic obtained from the Avrami model. Rheological determination of the molecular weight between entanglements (Me) and the average lamella thickness based on the Gibbs–Thomson equation revealed that the entanglement density and impact strength decreased, and the average lamella thickness increased with an increase in the ratio of CEF eluted fraction below 80°C to the crystallizable fraction in the range of 80–90°C.
Increasing the recruitment and retention of REM students within school psychology: The potential of diversity committees
Authors: Lim Karissa , Staubi Kayla , Adams Lyndsay , Higa Jamie , Parr Kayla , Frank Elyse , Arora Prerna G. 
Published: November 2022

AbstractRacially and ethnically minoritized (REM) youth have been historically underrepresented in the field of school psychology due, in part, to poor program climate. Numerous strategies to increase the recruitment and retention of REM school psychology students have been put forth. Despite this, concerns regarding program climate remain and calls for the increased diversification of the field continue. The purpose of this article is to put forth the use of diversity committees (DCs) as a way to increase the recruitment and retention of REM students within school psychology. We present two case examples of DCs implemented in school psychology graduate programs. We conclude with implications, as well as future research needs as it relates to the examination of effectiveness and implementation of DCs.
Beyond the (im)mobility and social‐environmental dichotomy: Young adults' motives to reside in rural northwest Europe
Authors: Hofstede Henk , Salemink Koen , Haartsen Tialda 
Published: November 2022

AbstractIn line with the increased attention for residential experiences of young adults in rural areas, this paper explores the diversity of residential motives and combines them into overarching residential orientations. Based on survey data, we distinguish five residential orientations on rural identity, family, livability, housing and employment. These orientations are analysed on the basis of residential history, expectation to stay, agency about residential choices and sociodemographics of young adults. This paper finds that most of the young adults have the expectation to stay in their rural home region for the rest of their lives or at least for the upcoming 10 years. In addition, most of them experience a free choice to reside in their rural home areas. Young adults possess five residential orientations which do not differ much with regard to residential history and the expectation to stay. Nevertheless, whereas the family residential orientation is the most general orientation among young adults, the rural identity residential orientation stands out with specific characteristics among young adults. A stronger rural identity orientation is most likely among independent young adults who experience agency in their residential choice and who expect to stay in the study areas.
Trends in internal migration in Japan, 2012–2020: The impact of the COVID‐19 pandemic
Authors: Kotsubo Masaki , Nakaya Tomoki 
Published: November 2022

AbstractIn the past 10 years or so, there have been growing concerns in Japan that migration trends, such as large in‐migration to the Tokyo metropolitan area (TMA) at the national scale and large movements from the suburbs to the centres at the metropolitan scale, have widened the core–periphery disparities at each scale under national population decline. However, the COVID‐19 pandemic led to unexpected changes in these migration patterns, such as a weakened population concentration in the TMA. This study aims to examine internal migration trends from 2012, on axes of core–periphery in Japan and centre–suburbs in metropolitan areas, and the changes in the migration patterns caused by the pandemic in 2020. First, we prepared intermunicipal origin–destination tables by estimating the suppressed flows in 2012–2020 using the iterative proportional fitting technique, and then we calculated the net migration and migration efficiency indices based on seven area types: centre and suburbs of the TMA, centres and suburbs of major metropolitan areas, centres and suburbs of other metropolitan areas and nonmetropolitan areas. The results indicate that the 2020 migration efficiency in the centre of the TMA drastically dropped to the lowest level during the study period, contrasting with an upward trend in 2012–2019. The pandemic strongly affected the migration patterns from/to and within the TMA, with much net gain in the suburbs from the centre, but the impact of migration efficiencies among the other areas was minimal. These findings can help in providing direction for the postpandemic policy challenge of spatial planning in Japan, for example, the weakened but still widening disparities between the TMA and the other regions and the renewed threat of urban sprawl caused by the increased migration from the centre to the suburbs within the TMA.
Evaluation of machine learning methods for covariate data imputation in pharmacometrics
Authors: Bräm Dominic Stefan , Nahum Uri , Atkinson Andrew , Koch Gilbert , Pfister Marc 
Published: November 2022

AbstractMissing data create challenges in clinical research because they lead to loss of statistical power and potentially to biased results. Missing covariate data must be handled with suitable approaches to prepare datasets for pharmacometric analyses, such as population pharmacokinetic and pharmacodynamic analyses. To this end, various statistical methods have been widely adopted. Here, we introduce two machine‐learning (ML) methods capable of imputing missing covariate data in a pharmacometric setting. Based on a previously published pharmacometric analysis, we simulated multiple missing data scenarios. We compared the performance of four established statistical methods, listwise deletion, mean imputation, standard multiple imputation (hereafter “Norm”), and predictive mean matching (PMM) and two ML based methods, random forest (RF) and artificial neural networks (ANNs), to handle missing covariate data in a statistically plausible manner. The investigated ML‐based methods can be used to impute missing covariate data in a pharmacometric setting. Both traditional imputation approaches and ML‐based methods perform well in the scenarios studied, with some restrictions for individual methods. The three methods exhibiting the best performance in terms of least bias for the investigated scenarios are the statistical method PMM and the two ML‐based methods RF and ANN. ML‐based approaches had comparable good results to the best performing established method PMM. Furthermore, ML methods provide added flexibility when encountering more complex nonlinear relationships, especially when associated parameters are suitably tuned to enhance predictive performance.
The accuracy of a novel self‐tapping bone fiducial marker for frameless robot‐assisted stereo‐electro‐encephalography implantation and registration techniques
Authors: Liu Qiangqiang , Mao Ziyu , Wang Junjie , Wang Changquan , Chen Wenze , Chen Wenzhen , Ye Xiaolai , Zhang Chencheng , Lu Yong , Xu Jiwen 
Published: November 2022

AbstractBackgroundWe aimed to evaluate the accuracy and safety of a novel self‐tapping bone fiducial as a registration technique for stereoelectroencephalography (SEEG) implantation.MethodsEach patient was installed with five bone fiducial markers. All procedures were performed using the same Sinovation robot system. The accuracy was determined by calculating the target point error (TPE) and the entry point error (EPE) of electrodes.ResultsFourteen patients underwent SEEG implantation surgery; and the average installation time of the markers per patient was 86.1 s. In the operating theatre, the average registration time was 206.6 s, and the average registration error was 0.18 mm. The average TPE of 174 electrodes was 1.98 mm and the average EPE was 0.88 mm.ConclusionOur study provided a bone fiducial marker installation and registration technique that was convenient and fast, highly accurate in registration, and highly tolerated by patients.
Influence of growth temperature on microstructural and electromagnetic properties of nickel thin films
Authors: Rizwan Muhammad Nawaz , Kalyar Mazhar Ali , Anwar ul Haq Muhammad , Bell Chris , Makhdoom Ata ur Rehman 
Published: November 2022

Nickel thin films were grown on quartz substrates in ultra‐high vacuum at laser fluence of 98 J/cm2 using pulsed laser deposition. Effects of substrate temperature on the electromagnetic properties of the films were investigated. XRD data reveal crystalline growth at substrate temperature (Ts) of 500°C. Roughness of the thin films at Ts of 100°C was noted as 8 nm which was decreased to 3 nm at 500°C. Coercive field and electrical resistivity were decreased from 10 to 5 mT and 0.71 to 0.064 μΩ‐m, respectively, at higher substrate temperature. Magnetoresistance for both modes of configuration and Hall mobility were decreased, while carrier density and Hall coefficient showed opposite behavior with increased substrate temperature.
Self‐Healable Metallogels for Selective Dye Adsorption
Authors: Dutta Mita , Karan Chandan Kumar , Bhattacharjee Manish 
Published: November 2022

AbstractThe low molecular weight gelator, disodium L‐(3,5‐di‐tert‐butyl‐2‐hydroxy‐benzyl)amino aspartic acid (Na2HL), has been used to prepare three metal‐organic hydrogels (metallogel) with the metal ions Ni2+ (MOG 1), Co2+ (MOG 2), and VO2+ (MOG 3). The gels have been prepared by mixing the aqueous solutions (0.5 mL) of the Na2HL(0.01 to 0.05 mmol) and M(CH3COO)2⋅4H2O {M=Ni or Co} or VO(SO)4⋅H2O (0.01 to 0.05 mmol). The gels have been characterized by IR spectroscopic studies, MALDI TOF spectrometry and various microscopic studies. All the gels are multi‐responsive in nature to different external stimuli, and among them, MOG 1 and MOG‐2 show the self‐healable property indicating a strong metal‐ligand interaction and hydrogen bonding interactions in the gel network. The thixotropic behavior and viscoelastic nature of the self‐healable metallogels have been confirmed by time dependent step‐strain experiment at room temperature. It was observed that MOG 1 shows rapid and more efficient selective dye adsorption of cationic dyes, rhodamine B (RhB) {61.7 mg g−1}, and malachite green (MG) {15.3 mg g−1} from mixtures of cationic, anionic dyes, and neutral dyes. MOG 2 also selectively adsorb cationic dyes from the mixture of dyes. The gel, MOG 3, selectively degrades fluorescein (FL) dye.
Stronger together: Country‐of‐origin agglomeration and multinational enterprise location choice in an adverse institutional environment
Authors: Li Yong , Li Jing , Zhang Peng , Gwon Sunhwan 
Published: November 2022

AbstractResearch SummaryResearch suggests that multinational enterprises (MNEs) are attracted to locations with concentrated firms from the same home country to benefit from interactions with market forces, but it remains an open question whether such agglomeration facilitates MNEs' interactions with nonmarket actors such as the host government. We submit that since country‐of‐origin agglomeration can enable collective actions and create collective gains, colocation with compatriot firms will help MNEs navigate an adverse institutional environment. In line with this reasoning, we hypothesize that MNEs are more attracted to locations with country‐of‐origin agglomeration when MNEs face an exogenous shock that increases their regulatory burden in the host country. Our analysis offers corroborative evidence. The study adds to research on agglomeration, institutional environment, and location strategy.Managerial SummaryWhy do multinational enterprises (MNEs) locate near compatriot firms in a foreign location? The commonly recognized benefits include resource access and knowledge spillover from interactions with market forces such as suppliers and customers. We submit that colocation with compatriot firms can also help MNEs navigate an adverse institutional environment by generating “stronger‐together” benefits. Colocation can enable collective actions and create collective gains for MNEs in their interactions with the host government. We find that after a diplomatic dispute, Korean MNEs are more attracted to locations in China that already have a cluster of Korean firms, whether in the same/related industries or in unrelated industries; this is particularly the case for small MNEs and in locations with weak institutions.
Cascade Catalytically Released Nitric Oxide‐Driven Nanomotor with Enhanced Penetration for Antibiofilm
Authors: Zheng Jia , Wang Wei , Gao Xinyu , Zhao Senfeng , Chen Wansong , Li Jianghua , Liu You‐Nian 
Published: November 2022

AbstractNanodrugs are becoming increasingly important in the treatment of bacterial infection, but their low penetration ability to bacterial biofilm is still the main challenge hindering their therapeutic effect. Herein, nitric oxide (NO)‐driven nanomotor based on L‐arginine (L‐Arg) and gold nanoparticles (AuNPs) loaded dendritic mesoporous silica nanoparticles (AG‐DMSNs) is fabricated. AG‐DMSNs have the characteristics of cascade catalytic reaction, where glucose is first catalyzed by the asymmetrically distributed AuNPs with their glucose oxidase (GOx)‐&nbsp;mimic property, which results in unilateral production of hydrogen peroxide (H2O2). Then, L‐Arg is oxidized by the produced H2O2 to release NO, leading to the self‐propelled movement. It is found that the active movement of nanomotor promotes the AG‐DMSNs ability to penetrate biofilm, thus achieving good biofilm clearance in vitro. More importantly, AG‐DMSNs nanomotor can eliminate the biofilm of methicillin‐resistant Staphylococcus aureus (MRSA) in vivo without causing damage to normal tissues. This nanomotor provides a new platform for the treatment of bacterial infections.
The Mechanism of Li Deposition on the Cu Substrates in the Anode‐Free Li Metal Batteries
Authors: Lai Genming , Jiao Junyu , Fang Chi , Jiang Yao , Sheng Liyuan , Xu Bo , Ouyang Chuying , Zheng Jiaxin 
Published: November 2022

AbstractDue to the rapid growth in the demand for high‐energy‐density Lithium (Li) batteries and insufficient global Li reserves, the anode‐free Li metal batteries are receiving increasing attention. Various strategies, such as surface modification and structural design of copper (Cu) current collectors, have been proposed to stabilize the anode‐free Li metal batteries. Unfortunately, the mechanism of Li deposition on the Cu surfaces with the different Miller indices is poorly understood, especially on the atomic scale. Here, the large‐scale molecular dynamics simulations of Li deposition on the Cu substrates are performed in the anode‐free Li metal batteries. The results show that the surface properties of the Li panel can be altered through the different Cu substrate surfaces. Through surface similarity analysis, potential energy distributions,and inhomogeneous deposition simulations, it is found that the Li atoms exhibit different potential energy variances and kinetic characteristics on the different Cu surfaces. Furthermore, a proposal to reduce the fraction of the (110) facet in commercial Cu foils is made to improve the reversibility and stability of Li plating/stripping in the anode‐free Li metal batteries.
Anomaly detection on OpenStack logs based on an improved robust principal component analysis model and its projection onto column space
Authors: Kalaki Parisa Sadat , Shameli‐Sendi Alireza , Abbasi Behzad Khalaji Emamzadeh 
Published: November 2022

AbstractWith the advent of technology and the development of more complex software systems, the size of logs generated by these systems has increasingly risen so that the anomaly detection for remediating common errors has been more difficult than ever. The cloud emergence in the information technology (IT) industry has led to the immigration of enterprises toward it, which has extended the application of cloud management stacks such as OpenStack. By using the OpenStack platform, users can access resource infrastructure and manage virtual machines (VMs). The anomaly detection in OpenStack logs is not realized conveniently due to the substantial size of logs, and it is required to automate this process. Since there is no appropriate open‐source dataset for OpenStack logs, we have generated 25,000 logs by injecting three types of anomalies to propose a more efficient technique in terms of performance and time in detecting anomalies in OpenStack logs relative to recent studies by proper OpenStack log parsing and analyzing these logs by data mining algorithms. To this end, compared to the previous research study, we could improve the anomaly detection performance in terms of F1 score, recall, and precision by 9%, 4%, and 14%, respectively, and decrease the running time relative to the log size by at least 30 s.
Numerical modeling techniques and investigation into the flexural behavior of two‐way posttensioned concrete slabs with profiled steel sheeting
Authors: Dinh Phuoc Tho , Doh Jeung‐Hwan , Fragomeni Sam , Ho Nhat Minh , Peters Tim 
Published: November 2022

AbstractIn recent years, the combined use of posttensioning methods with steel decking in the concrete slabs has provided significant benefits in both economic and structural terms. In construction practice, this prestressed composite floor has extensive use in two‐way spanning slab systems. However, this application still has inherent limitations due to its novelty and lack of research in this specific field. Hence, this study aims to gain the first insight into the flexural behavior of a two‐way posttensioned composite (PTC) slab system based on a numerical approach. Scientific software is utilized for the derived model validation with a focus on models' geometric and material nonlinearity. Available modeling techniques used to perform the posttensioning process and interaction of composite slabs are verified with existing experiments. A comparative study was conducted between PTC slabs and various conventional slab systems on two different support conditions. The findings in this study consider the structural effects of posttensioning and profiled steel sheeting on the flexural behavior of PTC slabs. In addition, numerical results from this research might help structural engineers to modify the design input parameters and make judgments on the bending stiffness of this two‐way slab structure. Further studies are required since the shear behavior, flexural, and punching shear conditions in the column regions are not addressed in this article.