bluuebunny/crossref_metadata_2025_split huggingface dataset:
A two‐stage Bayesian network model for corporate bankruptcy prediction
Authors: Cao Yi , Liu Xiaoquan , Zhai Jia , Hua Shan 
Published: August 2020

AbstractWe develop a Bayesian network (LASSO‐BN) model for firm bankruptcy prediction. We select financial ratios via the Least Absolute Shrinkage Selection Operator (LASSO), establish the BN topology, and estimate model parameters. Our empirical results, based on 32,344 US firms from 1961–2018, show that the LASSO‐BN model outperforms most alternative methods except the deep neural network. Crucially, the model provides a clear interpretation of its internal functionality by describing the logic of how conditional default probabilities are obtained from selected variables. Thus our model represents a major step towards interpretable machine learning models with strong performance and is relevant to investors and policymakers.
A survey of cariology education in U.S. dental hygiene programs: The need for a core curriculum framework
Authors: McComas Martha J , Hurlbutt Michelle , Fontana Margherita 
Published: August 2020

AbstractObjectiveDental hygienists play a key role in dental caries prevention and management. As the evidence of dental caries risk, prevention, and management becomes more complex, it is essential that dental hygiene (DH) programs have a strong cariology curriculum. This project aimed to assess current cariology content in U.S. DH programs, how content is taught, and interest in development/implementation of a common/core cariology curriculum framework.MethodsDirectors of 336 U.S. DH programs were invited to participate in a voluntary online survey using Qualtrics. The survey consisted of 41 items including demographics, details about the program's cariology content, and how it was delivered, and items related to a core cariology curriculum.ResultsThe overall response rate used for analyses was 27.3%. Some findings include: 61.6% stated their program had a defined cariology curriculum, 35.2% did not have an individual cariology course, 61.5% had preclinical hands‐on experiences in cariology, 79.7% are teaching management strategies related to salivary gland hypofunction, 68.3% are teaching use of silver diamine fluoride (SDF), and 64.2% felt cariology was adequately being taught. Only 17.7% are teaching the International Caries Detection and Assessment System (ICDAS) system. 87.3% indicated support for developing a core curriculum framework for teaching cariology in DH programs.ConclusionsThis study indicated that, although DH programs reported that cariology concepts are being taught both didactically and clinically, discrepancies between concepts taught and the literature exist. Therefore, there is a need to create a more standardized curriculum framework for all U.S. DH programs.
Studies on the cross‐interaction between hIAPP and Aβ25–35 and the aggregation process in binary mixture by electrospray ionization‐ion mobility‐mass spectrometry
Authors: Pang Bo , Zhuang Xiaoyu , Bian Xinyu , Liu Shu , Liu Zhiqiang , Song Fengrui 
Published: August 2020

AbstractA wealth of epidemiological evidence indicates a strong link between type 2 diabetes (T2D) and Alzheimer's disease (AD). The fiber deposition with cross‐β‐sheet structure formed by self‐aggregation and misfolding of amyloidogenic peptides is a common hallmark of both diseases. For the patients with T2D, the fibrils are mainly found in the islets of Langerhans that results from the accumulation of human islet amyloid polypeptide (hIAPP). The major component of aggregates located in the brain of AD patients is amyloid‐β (Aβ). Many biophysical and physiological properties are shared by hIAPP and Aβ, and both peptides show similar cytotoxic mechanisms. Therefore, it is meaningful to investigate the possible cross‐interactions of hIAPP and Aβ in both diseases. In this article, the segment 25–35 of Aβ was selected because Aβ25–35 was a core region in the process of amyloid formation and showed similar aggregation tendency and toxicity with full‐length Aβ. The electrospray ionization‐ion mobility‐mass spectrometry analysis and thioflavin T fluorescence kinetic analysis combined with transmission electron microscopy were used to explore the effects of the coexistence of Aβ25–35 and hIAPP on the self‐aggregation of both peptides and whether there was co‐assembly in fibrillation. The results indicated that the aggregation of hIAPP and Aβ25–35 had two nucleation stages in the binary mixtures. hIAPP and Aβ25–35 had a high binding affinity and a series of hetero‐oligomers formed in the mixtures of hIAPP and Aβ25–35 in the early stage. The cross‐reaction between hIAPP monomers and Aβ25–35 monomers as well as a little of oligomers during primary nucleation stage could accelerate the aggregation of Aβ25–35. However, owing to the obvious difference in aggregation ability between hIAPP and Aβ25–35, this cross‐interaction had no significant impact on the self‐assembly of hIAPP. Our study may offer a better understanding for exploring the molecular mechanism of the association between AD and T2D observed in clinical and epidemiological studies and developing therapeutic strategies against amyloid diseases.
Vitamin A Corrects Tissue Deficits in Diet‐Induced Obese Mice and Reduces Influenza Infection After Vaccination and Challenge
Authors: Penkert Rhiannon R. , Cortez Valerie , Karlsson Erik A. , Livingston Brandi , Surman Sherri L. , Li Yaqi , Catharine Ross A. , Schultz‐Cherry Stacey , Hurwitz Julia L. 
Published: August 2020

ObjectiveIndividuals with obesity suffer from an increased susceptibility to severe respiratory viral infections and respond poorly to vaccinations, making it imperative to identify interventions. Recent evidence suggesting that obesity leads to tissue‐specific vitamin A deficiency led to an investigation of whether high‐dose oral vitamin A, a treatment used for remediating vitamin A deficiency in developing countries, could correct obesity‐associated tissue deficits.MethodsAdult C57BL/6 diet‐induced obese mice were supplemented with vitamin A for 4 weeks. A subset of mice were then vaccinated with inactivated influenza virus and challenged. Following supplementation, tissue vitamin A levels, lung immune cell composition, blood inflammatory cytokines, antibody responses, and viral clearance were evaluated.ResultsSupplementation significantly improved vitamin A levels in lung and adipose tissues in diet‐induced obese mice. Additionally, supplementation decreased inflammatory cytokines in the blood and altered the lung immune environment. Importantly, vaccinated, vitamin A–treated diet‐induced obese mice exhibited improved antibody responses and significantly reduced viral loads post challenge compared with PBS‐treated mice.ConclusionsResults demonstrate a low‐cost intervention that may correct vitamin A tissue deficits and help control respiratory viral infections in individuals with obesity.
The effects of participants’ sex and the facial trustworthiness of proposers on third‐party decision‐making in a dictator game
Authors: Shang Junchen , Li Yutong 
Published: August 2020

AbstractThis study investigated the effects of participants’ sex and the facial trustworthiness of proposers on third‐party decision‐making. Sixty‐three participants participated in this study. The participant's task was to act as an interest‐free third party who observed a dictator game in which proposers with either trustworthy or untrustworthy faces made offers to recipients, to evaluate the reasonableness of the offers, and to express their intentions to punish the proposers. The results showed that offers from trustworthy proposers were rated as more reasonable than offers from untrustworthy proposers. Similarly, the participants were more likely to punish untrustworthy proposers than trustworthy proposers. In addition, there was a trend that male participants punished proposers more severely than female participants when proposers made unfair offers. These results demonstrate that an individual's facial trustworthiness affects other people's judgment and decisions.
Psychological aspects of gestational cancer: A systematic review
Authors: Leung Vivien , Bryant Christina , Stafford Lesley 
Published: August 2020

AbstractObjectiveGestational cancer is defined as any type of cancer diagnosed during pregnancy or within 12 months of delivery. To date, existing studies on the psychological aspects of this type of cancer have not been evaluated for methodological quality. The aim of this systematic review was to identify the psychological aspects of gestational cancer.MethodsFive journal databases were searched to identify peer‐reviewed articles reporting upon the psychological aspects of women with gestational cancer. Studies published from journal inception to December 2019 were included, and Preferred Reporting Items for Systematic Reviews and Meta‐analyses (PRISMA) guidelines were followed. The Mixed‐Method Appraisal Bias Tool was used, to assess the methodological quality of the studies. A narrative description was developed for the psychological outcomes reported in quantitative studies. Qualitative data was synthesized using thematic analysis.ResultsFive papers were eligible for inclusion (two qualitative and three quantitative studies). Factors that contributed to women's psychological distress during gestational cancer included disease characteristics, sociodemographic factors, the baby's health, pregnancy‐related factors and cognitive emotion regulation. Four main themes emerged from the qualitative studies; concerns about the baby's health, lost opportunities, “not fitting in,” and healthcare decision‐making.ConclusionsThese findings suggest that (a) women with gestational cancer experience psychological distress that is associated with concerns about their babies' health, and (b) their healthcare experiences are affected by communication within multidisciplinary care teams.
Forward and backward risk assessment throughout a system life cycle using dynamic Bayesian networks: A case in a petroleum refinery
Authors: Ashrafi Maryam 
Published: August 2020

AbstractIn this paper, risk modeling was conducted based on the defined risk elements of a conceptual risk framework. This model allows for the estimation of a variety of risks, including human error probability, operational risk, financial risk, technological risk, commercial risk, health risk, and social and environmental risks. Bayesian network (BN) structure learning techniques were used to determine the relationships among the model variables. By solving a bi‐objective optimization problem applying the genetic algorithm (GA) with the Pareto ranking approach, the network structure was learned. Then, risk modeling was performed for a petroleum refinery focusing on HydroDeSulfurization (HDS) technology throughout its life cycle. To extend the model horizontally and make it possible to evaluate the risk trend throughout the technology life cycle, we developed a dynamic Bayesian network (DBN) with three‐time slices. A two‐way forward and backward approach was used to analyze the model. The model validation was performed by applying the leave‐one‐out cross‐validation method.
Performance optimization of an ion funnel driven by novel radiofrequency waveforms
Authors: Zhou Shao , Tang Keqi , Wu Huanming , Xie Zhijun , Wu Yong , Yu Jiancheng 
Published: August 2020

RationaleIn mass spectrometry, ion transmission is usually achieved by driving an ion funnel with a reversed sine wave radiofrequency. However, the mass range of this conventional ion funnel is limited. In order to overcome this limitation, and to improve the transmission efficiency of the ion funnel, we explore the use of different radiofrequency waveforms for different m/z ranges.MethodsRight triangle, sawtooth, and variable phase sine (VPS) waves are used in different m/z ranges to improve ion transmission efficiency. We use SIMION‐based numerics to simulate their potential field distributions and ion flight trajectories. We compare transmission and focusing performances with those of a conventional ion funnel.ResultsIons with high m/z values require a larger potential gradient to limit their flight trajectory. Right triangle waves can quickly adjust electrode potential through a step change. The equipotential line distribution of VPS waves is wider than that of a sine wave which improves focusing performance. At the same time, the local ion trap effect at the outlet of the ion funnel is improved because of the “snake potential”. The maximum effective potential of the sawtooth wave is smaller than that of the sine wave, which is suitable for low m/z ion transmission.ConclusionsSawtooth and VPS waves may improve the transmission performance of the ion funnel in the low m/z regime whereas right triangle waves may improve the transmission performance in the high m/z regime.
Automatic three‐dimensional mapping for tree diameter measurements in inventory operations
Authors: Tremblay Jean‐François , Béland Martin , Gagnon Richard , Pomerleau François , Giguère Philippe 
Published: August 2020

AbstractForestry is a major industry in many parts of the world, yet this potential domain of application area has been overlooked by the robotics community. For instance, forest inventory, a cornerstone of efficient and sustainable forestry, is still traditionally performed manually by qualified professionals. The lack of automation in this particular task, consisting chiefly of measuring tree attributes, limits its speed, and, therefore, the area that can be economically covered. To this effect, we propose to use recent advancements in three‐dimensional mapping approaches in forests to automatically measure tree diameters from mobile robot observations. While previous studies showed the potential for such technology, they lacked a rigorous analysis of diameter estimation methods in challenging and large‐scale forest environments. Here, we validated multiple diameter estimation methods, including two novel ones, in a new publicly‐available dataset which includes four different forest sites, 11 trajectories, totaling 1458 tree observations, and 14,000 m2. From our extensive validation, we concluded that our mapping method is usable in the context of automated forest inventory, with our best diameter estimation method yielding a root mean square error of 3.45 cm for our whole dataset and 2.04 cm in ideal conditions consisting of mature forest with well‐spaced trees. Furthermore, we release this dataset to the public (https://norlab.ulaval.ca/research/montmorencydataset), to spur further research in robotic forest inventories. Finally, stemming from this large‐scale experiment, we provide recommendations for future deployments of mobile robots in a forestry context.
Directing Group Assisted Unsymmetrical Multiple Functionalization of Arene C−H Bonds
Authors: Ghosh Koushik , Rit Raja K. , Shankar Majji , Mukherjee Kallol , Sahoo Akhila K. 
Published: August 2020

AbstractMultiple C−H bond functionalizations promptly install diverse groups on the molecular framework and consequently fabricate complex molecular entities. This review briefly surveys the conceptual development of directing group assisted unsymmetrical multiple functionalization of arene C(sp2)−H bonds, which is exceedingly appealing and highly important.
Polarized U.S. publics, Pope Francis, and climate change: Reviewing the studies and data collected around the 2015 Papal Encyclical
Authors: Landrum Asheley R. , Vasquez Rosalynn 
Published: August 2020

AbstractAs soon as it was clear that Pope Francis's 2015 Encyclical, Laudato Si’: On Care for Our Common Home, would discuss, among other issues, the moral imperative to address global climate change, U.S. scholars and research institutions rushed to collect data surrounding its release. These groups aimed to determine whether there would be a “Francis Effect,” in which U.S. Conservatives (and Conservative Catholics in particular) would show greater concern about the negative effects of global climate change. Here, we first provide context by discussing the history of political polarization in the U.S. over global climate change. Then, we review the published literature and publicly available data that aimed to examine potential influences of Laudato Si’ on people's climate change attitudes. Taken together, the available scholarship provides strong evidence that U.S. publics were differentially responsive to the Pope's messaging (with political Conservatives expressing less climate change concern and viewing Pope Francis as less credible), but there is correlational evidence of an overall “Francis Effect.” U.S. population data collected following the encyclical's release show small, potentially temporary, increases in perceptions of papal credibility, climate change concern, and the perspective that global climate change is a moral issue.This article is categorized under:
Trans‐Disciplinary Perspectives > Humanities and the Creative Arts
Perceptions, Behavior, and Communication of Climate Change > Communication
HPS Accelerated Spectral Solvers for Time Dependent Problems: Part II, Numerical Experiments
Authors: Babb Tracy , Martinsson Per-Gunnar , Appelö Daniel 
Published: August 2020

AbstractThis is the second of a two part series describing a spectrally accurate “Hierarchial Poincaré–Steklov (HPS)” solver for time-dependent problems with a leading order elliptic spatial operator. In this second part we provide numerical experiments and in the first part we provide a detailed description of the method.
Discrete Equivalence of Adjoint Neumann–Dirichlet div-grad and grad-div Equations in Curvilinear 3D Domains
Authors: Zhang Yi , Jain Varun , Palha Artur , Gerritsma Marc 
Published: August 2020

AbstractIn this paper, we will show that the equivalence of a div-grad Neumann problem and a grad-div Dirichlet problem can be preserved at the discrete level in 3-dimensional curvilinear domains if algebraic dual polynomial representations are employed. These representations will be introduced. Proof of the equivalence at the discrete level follows from the construction of the algebraic dual representations. A 3-dimensional test problem in curvilinear coordinates will illustrate this approach.
Spectral Analysis of Isogeometric Discretizations of 2D Curl-Div Problems with General Geometry
Authors: Mazza Mariarosa , Manni Carla , Speleers Hendrik 
Published: August 2020

AbstractWe study the spectral distribution of matrices arising in Galerkin isogeometric methods for weighted curl-div operators defined on a general planar domain. It can be compactly described by means of a spectral symbol which depends on the characteristic parameters of the problem: the weight parameters, the basic curl and div operators, the degree of the B-spline approximation, and the geometry map used to represent the computational domain.
Performance of Preconditioners for Large-Scale Simulations Using Nek5000
Authors: Offermans N. , Peplinski A. , Marin O. , Merzari E. , Schlatter P. 
Published: August 2020

AbstractBoomerAMG, the algebraic multigrid solver from the hypre library, is used to solve a coarse grid problem which is part of the preconditioning strategy for the pressure equation arising from the numerical resolution of the Navier–Stokes equations. A set of optimal parameters for the setup phase is determined and used for selected strong scaling tests on two different supercomputers, namely Mira and Hazel Hen, on up to 131, 072 compute cores. The results are compared to an existing algebraic multigrid solver, designed specifically for the coarse grid problem at hand. It is shown that the BoomerAMG solver is fast and scalable, and that performance depends on the computer architecture. The test cases considered are the turbulent flow past a NACA4412 airfoil and the turbulent flow inside wire-tapped pin bundles.
High-Order Propagation of Jet Noise on a Tetrahedral Mesh Using Large Eddy Simulation Sources
Authors: Moratilla-Vega M. A. , Saini V. , Xia H. , Page G. J. 
Published: August 2020

AbstractJet noise is an important area of research in commercial aviation due to its high contribution to the overall noise generated by an aircraft. Conventionally, CFD combined with surface integral methods is used to study jet noise because of its low cost. However, it is not always trivial to define integration surfaces around complex geometries. This study employs a different two-step approach that can handle complex geometries. It combines a large-eddy simulation (LES) to obtain the acoustic sources from the flow field, and an acoustic perturbation equations (APE) solver to propagate the sound to the far field. The LES is performed with an industrial 2nd-order finite volume solver. The APE code is a high-order discontinuous Galerkin (DG) spectral/hp solver of the Nektar+ + framework. The APE solver is validated on a canonical test case. A study on different polynomial expansion orders and meshes is further performed to estimate the mesh size for noise propagation in the high-order spectral/hp DG context. Finally, a three-dimensional jet noise case (Re = 10, 000 and Mach =  0.9) is simulated using unstructured tetrahedral mesh for the APE solver and improved noise results for high frequencies are obtained. The results demonstrate that the present approach is capable of predicting noise in complex geometry scenarios, such as installed jets under the aircraft wings.
Dynamical Degree Adaptivity for DG-LES Models
Authors: Tugnoli M. , Abbà A. , Bonaventura L. 
Published: August 2020

AbstractWe present a first dynamically adaptive test of a physically based p-refinement criterion for DG-LES approaches recently proposed by the authors and applied so far to static adaptation only. The results, albeit preliminary, are encouraging and show that, also in the dynamically adaptive case, the proposed criterion allows to reduce significantly the number of degrees of freedom employed in a LES simulation without a major loss of accuracy.
A Novel Eighth-Order Diffusive Scheme for Unstructured Polyhedral Grids Using the Weighted Least-Squares Method
Authors: Albuquerque Duarte M.  S. , Vasconcelos Artur G.  R. , Pereira Jose C.  F. 
Published: August 2020

AbstractA new very high-order scheme for elliptic operators in unstructured polyhedral grids is proposed, based on the weighted least-squares technique. It can go up to eighth-order accuracy and uses face centred reconstructions for the integration of the diffusive fluxes. In order to maintain the local high-order, a new stencil extension algorithm is applied near the boundaries of the computational domain. The algorithm maintains the intended accuracy order independently of the grid type or the perturbation imposed to the grid. Concerning Neumann boundary conditions, a new approach is proposed that is better than the classic one used in schemes based in weighted least-squares.