Discrete Effects Research Articles

Use of Pharyngeal High-Resolution Manometry to Evaluate Dysphagia in Adults with Motor Neurone Disease: A Scoping Review

There has been a recent shift towards proactive dysphagia intervention in motor neurone disease (MND) to maintain physiological reserve. Pharyngeal high-resolution manometry (PHRM) can quantify swallowing pathophysiology to inform and evaluate proactive dysphagia intervention. This study aims to explore the current use of PHRM as a dysphagia evaluation in adults with MND. A scoping review based on the Joanna Briggs Framework was completed. Four electronic databases (PubMed, EMBASE, CINAHL and Web of Science core) were searched (inception to March 2021) by two independent researchers. Data were analysed according to (i) PHRM protocol and analysis methods and the feasibility of same, (ii) swallow biomechanics data and (iii) dysphagia intervention effects as measured by PHRM. Six studies with 78 people with MND (PwMND) were included. There was considerable variation in PHRM protocol and analysis methods. Five studies reported a 100% completion rate and three studies reported no adverse events. Swallow biomechanics data were reported across all studies. The effects of sensory stimulation, increased bolus consistency, effortful swallow and cricopharyngeal myotomy were evaluated using PHRM with 20 PwMND across four studies with varying effects. Literature on the use of PHRM in PwMND is limited. Variability in PHRM methods restricts comparison of metrics. PHRM appears to be a feasible tool for PwMND. PHRM can provide novel swallow physiology data in PwMND and quantify discrete effects of compensatory and surgical dysphagia interventions not detectable by videofluoroscopy or FEES. Further research on the effects of proactive dysphagia intervention as measured by PHRM is required.

Effect of fractal dimension on sand-geosynthetic interface shear strength

In this research, the effects of particle shape and surface structure on sand-geosynthetic interface shear strength were quantitatively investigated using fractal theory. Three different sand samples were prepared by considering the particle shape with overall regularity. Three geomembranes with different surface roughness and three EPS geofoams with various densities were selected to include the effect of surface roughness and hardness on the interface shear strength. Sand particles and geosynthetic surfaces were analyzed using image processing technique to measure the fractal dimension of the materials. Modified direct shear tests were performed to reveal the relationship between fractal dimension and interface shear strength. The shear tests pointed out that interface shear strength between sand and geosynthetic depends on both fractal dimension of materials (sand particles and geosynthetics) and surface hardness of geosynthetics. The proposed interface shear strength requires a complete approach rather than focusing on discrete effects.

Local Equilibrium and Discretization Effects on the Prediction of Scalar Dissipation Rates in Large Eddy Simulation of Turbulent Non-Premixed Combustion

ABSTRACT The effects of discretization and local equilibrium on the prediction of scalar dissipation rates are investigated by performing large-eddy simulation (LES) of a turbulent-piloted jet diffusion flame, Sandia Flame D. As a way to reduce the discretization errors on the prediction of scalar dissipation, an approach to use a higher-order finite difference scheme only for the evaluation of scalar gradients in a scalar dissipation model, while keeping the overall accuracy of the numerical method at second order, is investigated. Results indicate that the fourth-order scheme improves the accuracy with negligible addition to computational cost. With the improved evaluation of scalar gradients, the local equilibrium assumption, which is used in the algebraic model, is investigated by solving the subgrid-scale variance transport equation, where a model coefficient in a scaling-based relaxation model for subgrid-scale scalar dissipation is varied. It is found that the conditional mean scalar dissipation rates are insensitive to the model coefficient. This insensitivity is attributed to the prevalence of local equilibrium. A rapid decay of imbalance between production and dissipation of subgrid-scale scalar fluctuations is seen in both the predicted scalar dissipation and the transport budget in the variance equation. It is argued that since, at high Reynolds numbers, the transport of the scalar fluctuations occurs over a timescale larger than the subgrid-scale mixing timescale, its contribution to the evolution of subgrid-scale variance is statistically insignificant except near the nozzle exit where different streams begin to mix and scalar layers evolve rapidly. Consequently, the conditional (and unconditional) mean scalar dissipation rates in LES tend to depend solely on the production of subgrid-scale scalar fluctuations in most regions of turbulent jet flames, when the modeling is based on the Kolmogorov scaling.

The importance of managerial discretion on managerial ability–firm cash holding nexus

PurposeThis paper examines the role of managerial discretion in the relation between managerial ability on the level of corporate cash.Design/methodology/approachConjoining the upper echelons theory's premises and the theoretical framework of cash holdings, we posit that the managerial ability's effect on cash policy varies with managerial discretion using firm-level data. To test the empirical prediction, we employ a linear regression model with fixed effects with a sample of US listed firms from 1980 to 2016.FindingsThe findings reveal that the positive association between the ability of chief executive officers and corporate cash savings is weakened by firm-level managerial discretion. The results are robust to various additional analyses, namely lagged independent variables regression, reduced form regression and granger causality test. Overall, the findings are generally consistent with the cash holding motives yielding transaction and precautionary demand for money. However, our findings also shed light on whether managerial discretion moderates or exacerbates agency problems related to top executives' cash holding policies.Originality/valueThis work's distinct characteristic is the investigation of the joint effect of managerial talent and discretion on a firm's cash holding, which remains unexplored in the literature.

R-squared Measures for Multilevel Mixture Models with Random Effects

ABSTRACT Multilevel regression mixtures involving both discrete latent classes and continuous random effects are an increasingly popular approach for accommodating nested data structures. However, their application has outpaced the development of effect size measures to aid model interpretation. In response, we provide a general framework of R-squared measures for multilevel regression mixtures with random effects as well as either classes only at level-1 (L1MIX), or classes only at level-2 (L2MIX), or classes at both levels (L1L2MIX). This work extends and unites a previous suite of R-squared measures for multilevel mixtures with latent classes but no random effects (Rights & Sterba, 2018) and a suite of R-squared measures for multilevel models with random effects but no latent classes (Rights & Sterba, 2019).The general framework provided here includes total and class-specific measures that each allow the researcher to distinguish among distinct sources of explained variance in the fitted model. We provide software for implementing these measures and provide two illustrative empirical examples.

Low Speed Aerodynamic Analysis of the N2A Hybrid Wing–Body

Reduction of atmospheric emissions is currently a mandatory requirement for aircraft manufacturers. Several studies performed on Blended Wing–Body configurations showed a promising capability of reducing fuel consumption by increasing, at the same time, passengers’ transport capabilities. Although several aerodynamic studies are available at transonic speeds, low-speed evaluations of aerodynamic performances of Blended Wing Body aircrafts are less investigated. In this framework, the present paper deals with the aerodynamic performance of the N2A aircraft prototype at low-Mach number conditions. Aircraft longitudinal aerodynamics is addressed at M∞=0.2 with steady state three-dimensional RANS simulations carried out at two Reynolds numbers equal to 6.60×106 and 1.27×108, respectively. The former refers to an experimental test campaign performed at NASA Langley 14-by-22 foot subsonic tunnel, while the latter is related to free-flight conditions close to an approach and landing phase. Flowfield simulations are performed using the Computational Fluid Dynamic code FLUENT and the SU2 open-source code, currently adopted for research applications. Numerical solutions are validated by using available experimental data with reference to lift, drag, pitching moment and drag polar estimations. Pre-stall and post-stall aerodynamic behaviour through mean flow-field visualization along with the comparison of pressure distributions at several AoAs is addressed. Furthermore, the effect of convective discretization on a numerical solution for SU2 is discussed. Results indicate a good agreement with available experimental predictions. The present study aims to bridge existing computations at a Eulerian low-Mach number, with RANS computations and constitutes a further test-case for SU2 code with respect to a full aircraft configuration.

Topological Optimization of Circular SAW Resonators: Overcoming the Discreteness Effects.

Recently, we proposed a ring-shaped surface acoustic wave (SAW) resonator sensitive element design, as well as analyzed its characteristics and suggested its optimization strategy, with major focus on their temperature stability. Here, we focus on further optimization of the design to narrow the bandwidth and improve signal detection, while taking into account typical technological limitations. Additionally, the purpose of design optimization and modeling is to check the preservation of operability in the case of lithography defects, which is the most common technological error. For that, we suggest structural alteration of the interdigital transducer (IDT) that leads to its partial fragmentation. Using COMSOL Multiphysics computer simulations, we validate several IDT options and show explicitly how it could be optimized by changing its pin geometry. Based on the results of the study, prototyping and printing of ring resonators on a substrate using photolithography will be carried out.

The effect of mesh discretisation on damage and wear predictions using the Discrete Element Method

Assessing wear, damage and time to failure of industrial granular systems using the Discrete Element Method (DEM) is an area of limited research. In this paper, wear and damage are calculated using the Archard, Finnie, Bitter and Clark wear models of abrasion, ductile, brittle and a combined erosion model respectively using a DEM simulation with an underlying triangular surface mesh to capture and aggregate wear effects. These are compared for varying surface mesh discretisations to determine the effect of mesh refinement on wear distribution and prediction. It was found that the wear pattern remains similar for different discretisations, but the prediction of the maximum wear location varies. Therefore, the ratio between the particle area to surface element area needs to be carefully considered when looking at wear in an industrial setting using DEM. The amount of wear remained approximately constant with 1 -4 % and 1 - 2 % variations for abrasion and ductile erosion respectively. A linear damage accumulation model is presented based on the Palgrem-Miner model which shows a large variation in lifetime prediction for different surface mesh discretisations. The lifetime prediction needs to be compared to a real-world industrial system for both calibration and validation due to the non-converging nature of wear and damage modelling inside of DEM. To assist in determining a point for accurate wear and damage assessment the formation of holes in the model is studied. The total cumulative hole area is tracked and is found to converge at the impact area of the particles impacting the plate as the mesh is refined. The point of convergence is found to be when particle and element size are approximately equal. This particle to element size ratio is suggested to be a good choice for this type of DEM simulation as it balances accuracy and computational time for both wear and damage assessment.

Employee's subjective-well-being and job discretion: Designing gendered happy jobs

This paper analyses the influence of job discretion on employees’ subjective well-being (SWB) from a gender-based approach. Specifically, it explores whether the level of discretion given to employees in performing their jobs influences their SWB and whether this impact differs between women and men. Data from 20 European countries from Round 8 of the European Social Survey (ESS) are used to undertake an ordered probit analysis. Job discretion is approached through autonomy at work, supervision of other employees and influence on organisational policy decisions. Additionally, the individual's educational level is controlled to further explore gendered differences of job characteristics on SWB. The results show that job discretion does indeed affect SWB, and this effect is different for women and men. Moreover, the effect of job discretion on SWB is not homogeneous across different education levels.

Addition of grapes to both a standard and a high-fat Western pattern diet modifies hepatic and urinary metabolite profiles in the mouse.

The benefits of fruit and vegetable dietary consumption are largely defined in epidemiological terms. Relatively little is known about the discrete effects on metabolic pathways elicited by individual dietary fruits and vegetables. To address this, grape powder was added to both a standard and a high-fat Western pattern diet given to 10-week-old female C57BL/6J mice for a period of 91 days, whereupon 24 h urines were collected and the mice euthanized after a 12 h fast for the collection of liver tissue. Alterations in hepatic and urinary metabolite patterns were determined by gas chromatography-mass spectrometry-based metabolomics. Urinary excretion of the gut microbiota metabolites 4-hydroxyphenylacetic acid, 5-hydroxyindole, glyceric acid, gluconic acid and myo-inositol was attenuated when grape was added to the standard diet but the gut microbiota metabolites gluconic acid, scyllo-inositol, mannitol, xylitol, 5-hydroxyindole and 2-deoxyribonic acid were increased in urine when grape was added to the high-fat diet. Increased hepatic ascorbic acid and 5-oxoproline levels indicated the anti-oxidant effect of grape powder on the liver. Pathway enrichment analysis demonstrated that for both standard and high-fat diets, grape addition significantly upregulated the malate-aspartate shuttle indicating enhanced hepatic utilization of glucose via cytosolic glycolysis for mitochondrial ATP production. It is concluded that a grape diet reprogrammes gut microbiota metabolism, attenuates the hepatic oxidative stress of a high-fat diet and increases the efficiency of glucose utilization by the liver for energy production.

Deep learning for missing value imputation of continuous data and the effect of data discretization

Often real-world datasets are incomplete and contain some missing attribute values. Furthermore, many data mining and machine learning techniques cannot directly handle incomplete datasets. Missing value imputation is the major solution for constructing a learning model to estimate specific values to replace the missing ones. Deep learning techniques have been employed for missing value imputation and demonstrated their superiority over many other well-known imputation methods. However, very few studies have attempted to assess the imputation performance of deep learning techniques for tabular or structured data with continuous values. Moreover, the effect on the imputation results when the continuous data need to be discretized has never been examined. In this paper, two supervised deep neural networks, i.e., multilayer perceptron (MLP) and deep belief networks (DBN), are compared for missing value imputation. Moreover, two differently ordered combinations of data discretization and imputation steps are examined. The results show that MLP and DBN significantly outperform the baseline imputation methods based on the mean, KNN, CART, and SVM, with DBN performing the best. On the other hand, when considering the discretization of continuous data, the order in which the two steps are combined is not the most important, but rather, the chosen imputation algorithm. That is, the final performance is much better when using DBN for imputation, regardless of whether discretization is performed in the first or second step, than the other imputation methods.

Multi-omics integration and interactomics reveals molecular networks and regulators of the beneficial effect of yoga and exercise.

Background:Yoga is a multifaceted spiritual tool that helps in maintaining health, peace of mind, and positive thoughts. In the context of asana, yoga is similar to physical exercise. This study aims to construct a molecular network to find hub genes that play important roles in physical exercise and yoga.Methodology:We combined differentially expressed genes (DEGs) in yoga and exercise using computational bioinformatics from publicly available gene expression omnibus (GEO) datasets and identified the codifferentially expressed mRNAs with GEO2R. The co-DEGs were divided into four different groups and each group was subjected to protein–protein interaction (PPI) network, pathways analysis, and gene ontology.Results:Our study identified immunological modulation as a dominant target of differential expression in yoga and exercise. Yoga predominantly modulated genes affecting the Th1 and NK cells, whereas Cytokines, Macrophage activation, and oxidative stress were affected by exercise. We also observed that while yoga regulated genes for two main physiological functions of the body, namely Circadian Rhythm (BHLHE40) and immunity (LBP, T-box transcription factor 21, CEACAM1), exercise-regulated genes involved in apoptosis (BAG3, protein kinase C alpha), angiogenesis, and cellular adhesion (EPH receptor A1).Conclusion:The dissimilarity in the genetic expression patterns in Yoga and exercise highlights the discrete effect of each in biological systems. The integration and convergences of multi-omics signals can provide deeper and comprehensive insights into the various biological mechanisms through which yoga and exercise exert their beneficial effects and opens up potential newer research areas.

A machine learning framework for LES closure terms

In the present work, we explore the capability of artificial neural networks (ANN) to predict the closure terms for large eddy simulations (LES) solely from coarse-scale data. To this end, we derive a consistent framework for LES closure models, with special emphasis laid upon the incorporation of implicit discretization-based filters and numerical approximation errors. We investigate implicit filter types that are inspired by the solution representation of discontinuous Galerkin and finite volume schemes and mimic the behavior of the discretization operator, and a global Fourier cutoff filter as a representative of a typical explicit LES filter. Within the perfect LES framework, we compute the exact closure terms for the different LES filter functions from direct numerical simulation results of decaying homogeneous isotropic turbulence. Multiple ANN with a multilayer perceptron (MLP) or a gated recurrent unit (GRU) architecture are trained to predict the computed closure terms solely from coarse-scale input data. For the given application, the GRU architecture clearly outperforms the MLP networks in terms of accuracy, whilst reaching up to 99.9% correlation between the networks' predictions and the exact closure terms for all considered filter functions. The GRU networks are also shown to generalize well across different LES filters and resolutions. The present study can thus be seen as a starting point for the investigation of data-based modeling approaches for LES, which not only include the physical closure terms, but account for the discretization effects in implicitly filtered LES as well.

NON-PLANAR TOOLPATH FOR LARGE SCALE ADDITIVE MANUFACTURING

The parts produced by additive manufacturing are inherently subjected to discretization effects due to their layer-based addition. The stair-stepping effect on the surface quality is inevitable for most of the techniques and it becomes more dominant for the regions having small surface inclinations. The stair-stepping influences the mechanical properties as well as the aesthetic perception. Many researchers have been presented several approaches to overcome or minimize the stair-stepping effects and improve the surface quality of additively manufactured parts. The attempts have been made generally for the FDM-printed objects, however, there is no or fewer efforts have been made for parts of large-scale additive manufacturing (LSAM). Due to higher deposition rates (up to 50 kg/hrs.) and larger nozzle diameters (i.e. bead size) the discretization effect is more in large-scale additive manufacturing. In this paper, the presented methods to mitigate the stair-stepping effect and improving the surface quality of additive manufacturing are reviewed and practicing in large-scale 3D printing is discussed. A preliminary experimental study of 3D printing with a non-planar toolpath was carried out and the results were presented.

Effect of fault discretization on geodetic source inversion and usefulness of the trans-dimensional inversion approach

SUMMARYEarthquake source inversion, which estimates the heterogeneous slip distribution on fault from geophysical data, is a fundamental technique for estimating earthquake rupture process and obtaining information about the physics of fault rupture. Source inversion requires the spatial discretization of fault, which can be performed uniformly and non-uniformly. Uniform fault discretization is a conventional approach that requires smoothing and/or non-negative constraints of slips as prior information to obtain a stable and reliable solution; however, the combination of uniform discretization and these prior constraints may distort a source-inversion solution. As a non-uniform discretization approach, source inversion using a trans-dimensional inversion approach has recently attracted attention. To study the effect of fault discretization on geodetic source inversion, through the analysis of geodetic data on the 2015 Gorkha, Nepal, earthquake and synthetic tests, we investigated what kind of solution the conventional source inversion with uniform discretization and the trans-dimensional source inversion provide and what kind of uncertainty their solutions have. We found that the combination of uniform discretization and non-negative constraint led to excessively smooth solutions with poor data fit. Even without using the non-negative constraint, the conventional inversion with uniform discretization provided distorted and sometimes overfitted solutions, which could not be identified based on uncertainty information. In contrast, the trans-dimensional source inversion provided reasonable solutions composed only of meaningful slips, which were required to explain the data. We also found that uncertainty information depends on the source-inversion method; consequently, the evaluation of method-induced uncertainty is difficult. This suggests that we look at earthquake ruptures through the lens of source inversion with inherent method-dependent bias.

The Third-Order Elastic Constants and Mechanical Properties of 30° Partial Dislocation in Germanium: A Study from the First-Principles Calculations and the Improved Peierls–Nabarro Model

The elastic constants, core width and Peierls stress of 30° partial dislocation in germanium has been investigated based on the first-principles calculations and the improved Peierls–Nabarro model. Our results suggest that the predictions of lattice constant and elastic constants given by LDA are in better agreement with experiment results. While the lattice constant is overestimated at about 2.4% and most elastic constants are underestimated at about 20% by the GGA method. Furthermore, when the applied deformation is larger than 2%, the nonlinear elastic effects should be considered. And with the Lagrangian strains up to 8%, taking into account the third-order terms in the energy expansion is sufficient. Except the original γ—surface generally used before (given by the first-principles calculations directly), the effective γ—surface proposed by Kamimura et al. derived from the original one is also used to study the Peierls stress. The research results show that when the intrinsic−stacking−fault energy (ISFE) is very low relative to the unstable−stacking−fault energy (USFE), the difference between the original γ—surface and the effective γ—surface is inapparent and there is nearly no difference between the results of Peierls stresses calculated from these two kinds of γ—surfaces. As a result, the original γ—surface can be directly used to study the core width and Peierls stress when the ratio of ISFE to the USFE is small. Since the negligence of the discrete effect and the contribution of strain energy to the dislocation energy, the Peierls stress given by the classical Peierls–Nabarro model is about one order of magnitude larger than that given by the improved Peierls–Nabarro model. The result of Peierls stress estimated by the improved Peierls–Nabarro model agrees well with the 2~3 GPa reported in the book of Solid State Physics edited by F. Seitz and D. Turnbull.

Distribution function of nuclei from e± scattering in the presence of a strong primordial magnetic field

The amplitude of the primordial magnetic field (PMF) is constrained from observational limits on primordial nuclear abundances. Within this constraint, it is possible that nuclear motion is regulated by Coulomb scattering with electrons and positrons ($e^\pm$'s), while $e^\pm$'s are affected by a PMF rather than collisions. For example, at a temperature of $10^9$ K, thermal nuclei typically experience $\sim 10^{21}$ scatterings per second that are dominated by very small angle scattering leading to minuscule changes in the nuclear kinetic energy of order $\mathcal{O}$(1) eV. In this paper the upper limit on the effects of a possible discretization of the $e^\pm$ momenta by the PMF on the nuclear momentum distribution is estimated under the extreme assumptions that the momentum of the $e^\pm$ is relaxed before and after Coulomb scattering to Landau levels, and that during Coulomb scattering the PMF is neglected. This assumption explicitly breaks the time reversal invariance of Coulomb scattering, and the Maxwell-Boltzmann distribution is not a trivial steady state solution of the Boltzmann equation under these assumptions. We numerically evaluate the collision terms in the Boltzmann equation, and show that the introduction of a special direction in the $e^\pm$ distribution by the PMF generates no directional dependence of the collisional destruction term of nuclei. Large anisotropies in the nuclear distribution function are then constrained from big bang nucleosynthesis. Ultimately, we conclude that a PMF does not significantly affect the isotropy or BBN.

EFFECT OF THE SPANWISE DISCRETISATION ON TURBULENT FLOW PAST A CIRCULAR CYLINDER

The effect of the spanwise discretisation on numerical calculations of the turbulent flow around a circular cylinder is systematically assessed at a subcritical Reynolds number of 10000 in the frame of three-dimensional large-eddy simulation. The eddy-viscosity k-equation subgrid scale model is implemented to evaluate unsteady turbulent flow field. Large-eddy simulation is known to be a reliable method to resolve such a challenging flow field, however, the high computational efforts restrict to low Reynolds number flow or two-dimensional calculations. Therefore, minimum spatial density in the spanwise direction or cylinder axis direction needs to be carefully evaluated in order to reduce high computational resources. In the present study, the influence of the spanwise resolutions to satisfactorily represent three- dimensional complex flow features is discussed in detail and minimum spatial density for high Reynolds flow is suggested.

Weakly Bound H Dibaryon from SU(3)-Flavor-Symmetric QCD.

We present the first study of baryon-baryon interactions in the continuum limit of lattice QCD, finding unexpectedly large lattice artifacts. Specifically, we determine the binding energy of the H dibaryon at a single quark-mass point. The calculation is performed at six values of the lattice spacing a, using O(a)-improved Wilson fermions at the SU(3)-symmetric point with m_{π}=m_{K}≈420 MeV. Energy levels are extracted by applying a variational method to correlation matrices of bilocal two-baryon interpolating operators computed using the distillation technique. Our analysis employs Lüscher's finite-volume quantization condition to determine the scattering phase shifts from the spectrum and vice versa, both above and below the two-baryon threshold. We perform global fits to the lattice spectra using parametrizations of the phase shift, supplemented by terms describing discretization effects, then extrapolate the lattice spacing to zero. The phase shift and the binding energy determined from it are found to be strongly affected by lattice artifacts. Our estimate of the binding energy in the continuum limit of three-flavor QCD is B_{H}^{SU(3)_{f}}=4.56±1.13_{stat}±0.63_{syst} MeV.

Examining the Gap Between Prosecutor Attitudes and Decisions: Case Prioritization Through Case Elimination Mechanisms in Driving With a Suspended License Cases

Prosecutors are granted considerable discretion, particularly for misdemeanors. The current study assesses the processing of misdemeanor driving with suspended license (DWSL) cases. Using interview and administrative data from a Florida jurisdiction, the study first examines prosecutorial attitudes about case elimination mechanisms—declination, dismissal, and diversion—then evaluates the extent to which prosecutors’ views about handling DWSL cases and racial disparities in the legal system are reflective of case processing outcomes. Results indicate prosecutors view case prioritization as important, though it is unclear how they achieve it. Despite a reluctance to decline cases when the elements of an offense are supported by evidence, prosecutors acknowledge they cannot pursue all offenses if there is only marginal public safety return. Contemporaneous administrative data show that DWSL cases were routinely pursued in 2017: nearly all DWSL cases were filed, a third were dismissed, and 11% were diverted. Regression analysis also demonstrates that prosecutors’ views on racial and ethnic disparities are somewhat aligned with the case processing decisions for DWSL cases processed in 2017. These findings are discussed in terms of their implications for prosecutorial policy, practice, and the effects of prosecutorial discretion for low-level cases on communities.