Effect Of Skewness Research Articles

Skewness impact through distributional evaluation (SITDE) method: a new method in multi-criteria decision making

In this article, we propose the Skewness Impact Through Distributional Evaluation (SITDE) method for multi-criteria decision-making. Unlike traditional methods ignoring criteria distribution asymmetry, SITDE enhances the decision quality. We use a case-study on electric vehicle selection to illustrate the efficiency of SITDE relative to conventional methods. The comprehensive decision support with SITDE across multiple thresholds is an important aspect of a detailed and balanced decision-making virtue as our results show in case the skewness effects are included. Theoretical backgrounds, typologies practical applications and statistical justifications to confirm the accuracy of SITDE in regarding to limit complexities MCDM scenarios are explained this paper. SITDE enhances a robust decision-making process by accounting for the inherent biases of symmetric assumption models. Moreover, SITDE proves to be extremely useful in cases for dealing with asymmetrical data distributions and skewed datasets humanitarian cause as infected situations are always overwhelming. This broad applicability indicates the potential for wider use with respect to different domains, such as in environmental management and financial risk assessment. Future studies should investigate the adequacy or insufficiency of its fusion with different MCDM methods and explore if this approach would apply a more efficient and valid insight that might enhance decision making in multiple sectors.

Social gradients in employment during and after the COVID-19 pandemic

AbstractWe examine employment effects of the COVID-19 crisis in Norway from March 2020 through June 2022: during the initial lockdown, through the subsequent recovery, and after the dust had settled. While we identify large and socially skewed effects of the crisis through its early phases, we find no long-term effects on employees exposed to early risk of job loss. For those employed at the onset of the pandemic, both the level and the socioeconomic composition of employment quickly returned to normal. In contrast, we find considerable negative long-term employment effects on people who were neither in employment nor in education when the crisis hit. We argue that these patterns can be explained by social insurance policies that gave priority to protecting existing jobs and to distribute benefits to those who were temporarily laid off. Given the extreme increase in the social insurance caseload, an almost unavoidable side-effect was reduced capacity for providing services to the already non-employed.

Economic and legal principles of social protection of military personnel: World experience and Ukraine

The article considers principles of military personnel’ social protection in Ukraine, USA, Australia, and New Zealand in a comparative perspective. The framework used for the analysis is the dilemma of two opposing concepts of countries’ development and security – ‘warfare state’ and ‘welfare state’. The detrimental effect of skewing towards warfare state, manifested in skyrocketing growth of military field expenditures, is shown, backed up with an array of statistical data, scholars’ publications and expert analytics. It is demonstrated that the arising and essence of this opposition is rooted in the growing trends of securitization throughout the world, and detrimental effects of over-securitization on the overall welfare of country are justified. It is emphasized that for Ukraine, these concerns are particularly important, especially in the current conditions of war and the need, on the one hand, to effectively protect the country from aggression and on the other hand, enable economic and social resilience.

Skewness preferences: Evidence from online poker

We test for skewness preferences in a large set of observational panel data on online poker games (n=4,450,585). Each observation refers to a choice between a safe option and a binary risk of winning or losing the game. Our setting offers a real-world choice situation with substantial incentives where probability distributions are simple, transparent, and known to the decision-makers. Individuals reveal a strong and robust preference for skewness, which is inconsistent with expected utility theory. The effect of skewness is most pronounced among experienced and unsuccessful players but remains significant in all subsamples that we investigate, in contrast to the effect of variance.

Influence of cnoidal wave-induced seepage force on shields number in shallow water

Sediment incipient motion in shallow water is a major concern for coastal engineers. Wave-induced seepage force has reportedly had an important impact on the sediment incipience. The effect of wave asymmetry and skewness is important for defining nearshore wave motions and the resulting sediment movement, but it has been discounted in most previous studies considering seepage. Using analytical and numerical models, this study examines the influence of two-dimensional nonlinear wave-induced seepage forces on sediment incipient motions in shallow water. A new modified Shields number was derived, which better addresses the problem of seepage. The results indicate that seepage force could stabilize the sand particles by lowering the maximum Shields number by up to 38.0%; in the linear wave cases, the opposite is true. This discrepancy is subject to the nonlinearity and asymmetry of shallow wave motions, as well as the decreasing “suction” force and increasing “injection” force. Besides, disregarding horizontal seepage would greatly underestimate the contribution of seepage to sediment incipient motions, especially in situations with steeper waves or an unsaturated and less permeable seabed. A lower Young's modulus, larger saturation, permeability, and water depth would all considerably decrease the maximum Shields number.

The effect of (a)symmetry on the optimal toxin allocation

When mathematical models of biological phenomena deal with an unknown parameter, it is often assumed that such a parameter follows a normal distribution. This introduces a symmetry assumption into the model. The purpose of this paper is to investigate and quantify the effect of asymmetry on model prediction. We introduce an asymmetry into a model of sexual conflict and toxin allocation by replacing a normal distribution by a shifted beta distribution. This way, we can naturally consider a large family of continuously changing distributions. We isolate the effect of skewness on the model prediction and demonstrate that in most cases, increasing skewness causes a slight increase in optimal toxicity allocation. We conclude that overall, the effect of the skewness is much smaller than the effect of the mean. In fact, for the particular model we studied, skewness does not seem to affect qualitative predictions.

Frequent winners explain apparent skewness preferences in experience-based decisions

Do people's attitudes toward the (a)symmetry of an outcome distribution affect their choices? Financial investors seek return distributions with frequent small returns but few large ones, consistent with leading models of choice in economics and finance that assume right-skewed preferences. In contrast, many experiments in which decision-makers learn about choice options through experience find the opposite choice tendency, in favor of left-skewed options. To reconcile these seemingly contradicting findings, the present work investigates the effect of skewness on choices in experience-based decisions. Across seven studies, we show that apparent preferences for left-skewed outcome distributions are a consequence of those distributions having a higher value in most direct outcome comparisons, a "frequent-winner effect." By manipulating which option is the frequent winner, we show that choice tendencies for frequent winners can be obtained even with identical outcome distributions. Moreover, systematic choice tendencies in favor of right- or left-skewed options can be obtained by manipulating which option is experienced as the frequent winner. We also find evidence for an intrinsic preference for right-skewed outcome distributions. The frequent-winner phenomenon is robust to variations in outcome distributions and experimental paradigms. These findings are confirmed by computational analyses in which a reinforcement-learning model capturing frequent winning and intrinsic skewness preferences provides the best account of the data. Our work reconciles conflicting findings of aggregated behavior in financial markets and experiments and highlights the need for theories of decision-making sensitive to joint outcome distributions of the available options.

Effects of surface morphology on the performance of water-lubricated thrust bearings

Purpose As the crucial support component of the propeller power system, the reliability of the operation of submersible pumps is influenced by the lubrication performance of water-lubricated thrust bearings. When the water-lubricated thrust bearings are under start-stop or heavy load conditions, the effect of surface morphology is crucial as the mixed lubrication regime is encountered. This paper aims to develop one mixed lubrication model for the water-lubricated thrust bearings to predict the effects of surface skewness, kurtosis and roughness orientation on the loading carrying capacity and tribological behavior. Design/methodology/approach This paper developed one improved mixed lubrication model specifically for the water-lubricated thrust bearing system. In this model, the hydrodynamic model was improved by using the height of the rough surface and its probability density function, combined with the average flow model. The asperity contact model was improved by using the equation for the Pearson system of frequency curves to characterize the non-Gaussian aspect of surface roughness distribution. Findings According to the results, negative skewness, large kurtosis and lateral surface pattern can improve the tribological performance of water-lubricated thrust bearings. Optimizing the surface morphology is a reasonable design method that can improve the performance of water-lubricated thrust bearings. Originality/value In this paper, one mixed lubrication model specifically for the water-lubricated thrust bearing with the effect of surface roughness into consideration was developed. Based on the developed model, the effect of surface morphology on tribological behavior can be evaluated. Peer review The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-08-2023-0247/

Translation, cross-cultural adaptation and validation of the Arabic multimorbidity treatment burden questionnaire (MTBQ-A): A study of adults with multimorbidity

BackgroundStudies internationally have found that a high treatment burden is associated with several long-term conditions and poor quality of life. ObjectivesTo translate, culturally adapt, and provide evidence of reliability, validity, and factor structure of the Multimorbidity Treatment Burden Questionnaire for use among Arabic-speaking adults with multimorbidity. MethodsStandard guidelines for the cross-cultural adaptation of self-report measures were followed. The original 10-item MTBQ was translated into Arabic by professional translators using forward-backward translation. An expert group, including the creator of the MTBQ, participated in the cultural adaptation and content validity, followed by cognitive interviewing and pilot testing. The questionnaire was then tested on 177 Arabic-speaking patients with multimorbidity recruited from community pharmacies in the United Arab Emirates. The distribution of responses, dimensionality, internal consistency reliability, and construct validity were examined. ResultsThe content validity of the MTBQ-A was good (Content Validity Index = 0.94), and cognitive interviews found that the items were well understood. The scale showed positive skewness and high floor effects. Factor analysis supported a two-dimensional structure (factor loadings >0.4): factor one was named “Self-management and social support,” and factor two was named “Burden of visiting health care services and health care professionals”. The questionnaire had good internal consistency (α = 0.83). As predicted, a higher MTBQ score in both factors was associated with poor health-related quality of life in all dimensions: mobility, self-care, usual activities, pain/discomfort, and anxiety/depression (p values < 0.05); and negatively correlated with self-efficacy in taking medication (p < 0.01) and in learning about medication (p < 0.01). ConclusionsThe Arabic MTBQ is a valid and reliable measure of treatment burden with good construct validity and internal consistency. This easy-to-understand questionnaire can be used to assess the perceived treatment burden among Arabic-speaking patients with multimorbidity.

RETRACTED: Geometric Parameter Optimization of Switched Reluctance Machines for Renewable Energy Applications using Finite Element Analysis

PAPER RETRACTED April 26, 2024, by the general editor of Periodica Polytechnica, because of plagiarism. Plagiarized paper: Touati, Z., Araújo, R. E., Mahmoud, I., Khedher, A. "Analysis of Skewing Effects on Radial Force for Different Topologies of Switched Reluctance machines: 6/4 SRM, 8/6 SRM, and 12/8 SRM", U.Porto Journal of Engineering, 9(1), pp. 55–71, 2023. https://doi.org/10.24840/2183-6493_009-001_001134

A Methodology for Applying Skew in an Automotive Interior Permanent Magnet Rotor for Robust Electromagnetic and Noise, Vibration and Harshness Performance

Interior permanent magnet (IPM) motors in traction applications often employ discrete rotor skewing constructions to reduce torsional excitations and back-EMF harmonics. Although skewing is very effective in reducing cogging torque, the impact on torque ripple is not well understood and can vary significantly over the operating envelope of a motor. Skewing also leads to the creation of a non-zero axial force that may compromise the bearing life if not considered. This paper introduces a holistic methodology for analyzing the effect of skewing, aiming to minimize torsional excitations, axial forces and back-EMF harmonics whilst mitigating the impact on performance and costs. Firstly, analytical models are employed for calculating cogging torque, torque ripple and axial forces. Then, 2D and 3D finite element analysis are used to incorporate the influence of non-linear material behavior. A detailed structural model of the powertrain is employed to calculate the radiated noise and identify key areas allowing a motor designer to reduce noise, vibration and harshness (NVH). A meticulous selection process for the skewing angle, the number of skew stacks and the orientation of skew stacks is developed, giving particular attention to the effect of the selected pattern on NVH in both forward and reverse rotating directions.

The risk of normative bias in reporting empirical research: lessons learned from prenatal screening studies about the prominence of acknowledged limitations

Empirical data can be an extremely powerful and influential tool in bioethical research. However, when researchers or policy makers look for answers to ethical questions by engaging with empirical research, there can be a tendency (conscious or unconscious) to shape, report, and use empirical research in a way that confirms their own preferred ethical conclusions. This skewing effect - what we call ‘normative bias’ - is often so subtle it falls short of clear misconduct and thus can be difficult to call out. However, we argue that this subtle influence of bias has the potential to significantly influence debate and policy around highly sensitive ethical issues and must be guarded against. In this paper we share the lessons we have learned through a journey of self-reflection around the effect that normative bias can have when reporting on and referring to empirical data relating to ethical issues. We use a variety of papers from our area of the ethics of routine prenatal screening to illustrate these subtle but often powerfully distorting effects of bias. Our aim in doing so is not to criticise the work of others, as we recognise our own normative bias, but to improve awareness of this issue, remind the need for reflexivity to guard against our own biases, and introduce a new criterion - the idea of a ‘limitation prominence assessment’ - that can work as a practical way to evaluate the seriousness of the limitations of an empirical study and thus, the risks of the study being misread or misinterpreted through superficial reading.

Eddy Currents Assessment of Rail Cracks Using Artificial Neural Networks in a Laboratory Setup

Although flaws associated with rolling contact fatigue (RCF) and the corresponding traffic induced damage, which are a cause of failure in railways, have been of great concern in railway system maintenance and safety strategies in many countries for at least two decades, this serious problem has not been yet adequately tackled in the Argentine railway system. The present upgrading activities undertaken in the Argentine railway system (in infrastructure and in rolling stock) are prompting the need for R&amp;D in non-destructive testing techniques and procedures, to satisfy requirements of the new rolling stock and to ensure safe and economic operation of passengers and cargo. RCF damage appears as surface and near surface defects and grows into cracks which in time will propagate along the running surface and through the cross-section. Eddy current testing (ET) is a very efficient in-service inspection method for this task, the near field technique being especially recommended for ferromagnetic components.&#x0D; In the present paper, an artificial neural network (ANN) method for automatic classification of flaws with lift-off compensation is presented and tested. The tests consist on the ET evaluation of right angle artificial cracks on a rail calibration coupon; the depth of the cracks studied ranged from 1 to 7 mm. The technique permitted to compensate the weakening of the signals caused by the lift-off effect, allowing signal cracks classification with lift-off variations of up to 5.4 mm.&#x0D; The effect of crack skewness on the ET signals is also studied. Because the RCF cracks penetrate the rail at oblique angles, (10° to 30° to the rolling surface), an additional uncertainty component is added to the experiments if calibration is made with a piece having perpendicular cracks. In order to estimate this additional uncertainty on the ANN method presented here, further tests were made with a second calibration piece with cracks at 25° to the surface. Comparison of results showed that the peak to peak amplitudes for both types of cracks are not equivalent at all the tested depths.

Vibration characteristics of electric drive system considering rotor-step skewing

Electric vehicle has been gaining popularity in the worldwide market. The drive system for an electric vehicle usually consists of a permanent magnet synchronous motor (PMSM) and a two-stage gear system. The vibration characteristics of electric drive system is of great importance to the noise and durability performance. Recently, rotor-step skewing has drawn attention as a means to reduce the vibration response for the PMSM, since it can effectively reduce the torque ripple as shown in the previous studies. However, the coupling relationship between the torque ripple and the gear transmission system has not been studied thoroughly. To explore the influence of torque ripple on the motor-gear system when considering rotor-step skewing, this paper proposes a coupled electro-mechanical system model to study the vibration characteristics of electric drive system. The effect of rotor-step skewing on cogging torque and torque ripple of PMSM, dynamic transmission error (DTE) of gear transmission system, and vibration characteristics of electric drive system is studied. The simulation results show that the torque ripple has a significant effect on the DTE and the vibration responses of the electric drive system. The rotor-step skewing not only effectively suppress the torque ripple, but also optimize the DTE harmonics induced by the torque ripple.

The skewing effect of outcome evidence

Behaviours are primarily regulated to reduce the risks of a negative outcome to others. This article discusses the use of outcomes as evidence of violations of a legal standard (outcome evidence). The current debate over outcome evidence centres around limited rationality. Opponents argue that factfinders’ estimations are distorted by hindsight bias, while supporters argue that factfinders properly update the probability of fault, given information about the outcome. The article adopts the rationality assumptions and argues that factfinders should nevertheless disregard outcome evidence in most cases unless the outcome can provide evidence that works for or against the defendant or when the law creates inefficient incentives to comply with the legal standard, then using adverse outcomes as evidence may help solve the problem of undercompliance. The article further shows that when evidence cannot be excluded, changes to the law governing primary behaviour are warranted to account for the distortionary effect of outcome evidence.

Treating Iron Deficiency (ID) Anemia in Heart Failure (HF) Patients with IV Iron: A Meta-Analysis.

Findings on the effects of iron on heart failure (HF) hospitalizations and mortalityamong patients with iron deficiency (ID) and HF remain conflicting across different studies. We performed a meta-analysis of clinical trials assessing the clinical, hematic and cardiovascular benefits of treating ID in HF patients. We completed a systematic search for studies comparing IV iron to placebo in HF patients with ID. The primary outcomes were rates of HF hospitalization and all-cause mortality. Secondary outcomes included change in hematic values, New York HeartAssociation (NYHA) class and ejection fraction. We applied a random-effects model with planned sensitivity analyses of studies with skewed effect sizes. Nine studies were included with a total of 2,261 patients. Analysisrevealed that treatment of HF patients with IV iron replacement significantly reduced the odds of HF hospitalization (odds ratio (OR): 0.44; 95% confidence interval (CI): 0.24 to 0.78; p=0.005, I2=67%),) but did not significantly impact all-cause mortality compared to placebo (OR:0.89; 95%, CI:0.67 to 1.19; p=0.44, I2: 0%). Analysis showed that IV iron treatment group had significantly higher serum ferritin, transferrin saturation and hemoglobin (Hb) levels. They also had lower NYHA class -1.90 (95% CI (-2.91 to -0.89); p<0.001, I2:89%) with higher ejection fraction 0.50 (95% CI (0.09 to 0.90) p=0.016, I2:86%). Treatment with IV iron in HF patients with ID is associated with a significant reduction of HF hospitalization but no effects on all-cause mortality. There were also significant increases in hematic values and ejection fraction with a reduction in NYHA class.

Skewness in energy returns: estimation, testing and implications for tail risk

In this paper we estimate the skewness of the unconditional distribution of energy returns and test its statistical significance. We compare the performance of traditional and robust tests for skewness with those based on the implied unconditional skewness in a TGARCH model with Gram-Charlier (TGARCH-GC) innovations. We also analyze the implications of TGARCH-GC skewness for tail risk through evaluation of Value-at-Risk (VaR) and expected shortfall (ES) accuracy. Our results show that crude oil (Brent and WTI) and Gasoline returns are negatively skewed, while we do not find evidence of skewed distribution for other energy returns such as Heating oil, Kerosene and Natural gas. This indicates that the returns of the former are likely to encapsulate more largely the effect of negative shocks and so present higher tail risk than those of the latter. These results differ from traditional and robust tests for skewness providing important information on how to improve mean-variance risk management measures. Indeed, we find that the three-moment VaR and ES measures based on the third-order Cornish Fisher (CF3) expansion for the unconditional distribution of returns considerably improve their corresponding two-moment ones. We adopt CF3 to disentangle skewness effects from kurtosis in tail risk.

Systematic roughness variation to model the influence of skewness on wall bounded flows

In recent years, the research on roughness has focused on various roughness features, rather than the roughness height only, in order to improve the understanding of roughness effects on wall bounded flows. A special focus is placed on the skewness of the roughness height profile. The skewness measures whether the height profile is dominated by negative or positive roughness elements. Surfaces with both features can be found on worn blades: On the leading edge, roughness is caused by the impact of particles resulting in a negative skewness. Rough surfaces around the trailing edge, however, develop due to depositions leading to a positive skewness. In this paper, rough surfaces taken from a compressor blade of an aero engine are systematically varied to investigate the isolated effect of skewness on aerodynamic losses. By direct numerical simulations of a periodic flow channel. The results show that the skewness has a major influence on loss generation. Based on these results, an existing model which essentially uses the shape-and-density parameter, is extended by a skewness factor. The modified correlation predicts the influence of the rough surfaces investigated well.

Guided wave skew velocity correction in anisotropic laminates

Guided ultrasonic wave propagation in anisotropic structures results in directional dependency of velocity and wave skewing effects that can impact the accuracy of damage detection. Phase and group velocities of the A0 guided wave mode, propagating in a unidirectional carbon fiber reinforced laminate, were investigated experimentally and through finite element analysis. A correction for the significant offset in phase and group velocities due to wave skewing effects is illustrated for both point and short line sources, achieving good agreement with theoretical calculations assuming planar wave fronts. The influence of the line excitation length on velocity measurements is discussed.

Understanding the genomic selection for crop improvement: current progress and future prospects

Although increased use of modern breeding techniques and technology has resulted in long-term genetic gain, the pace of genetic gain must be sped up to satisfy global agricultural demand. However, marker-assisted selection has proven its potential for improving qualitative traits with largeeffectsregulated by one to few genes. Its contribution to the improvement of the quantitative traits regulated by a number of small-effect genes is modest. In this context, genomic selection (GS) has been regarded as the most promising method for genetically enhancing complicated features that are regulated by several genes, each of which has minor effects. By examining a population's phenotypes and high-density marker scores, genomic selection can forecast the breeding potential of individual lines. The fact that GS uses all marker data in the prediction model prevents skewed marker effect estimations and maximizes the amount of variation caused by small-effect QTL. It has the ability to speed up the breeding cycle and as a consequence of which superior genotypes are selected rapidly. Developing the best GS models while taking into account non-additive effects, genotype-by-environment interaction, and cost-effectiveness will enable the widespread implementation of GS in plants. These steps will also increase heritability estimation and prediction accuracy. This review focuses on the shift from conventional selection methods to GS, underlying statistical tools and methodologies, the state of GS research in agricultural plants, and prospects for its effective use in the creation of climate-resilient crops.