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This article presents a short summary of the conclusions we report in a longer manuscript (available in our Supplementary Material) subjecting Lagodny et al.’s new measure of state policy mood to the same set of face validity and construct validity tests we applied earlier to Enns and Koch’s measure. We encourage readers to read this longer manuscript, which contains not only the conclusions herein, but also the evidence justifying these conclusions, before accepting or rejecting any claims we make. Our results show that the characteristics of Enns and Koch’s measure that led us to be doubtful that it is valid are also present in Lagodny et al.’s new measure – leaving us just as doubtful that Lagodny et al.’s measure is valid. Moreover, the low correlation between Lagodny et al.’s measure and Enns and Koch’s measure, combined with evidence from replications of seven published studies that the two measures frequently yield quite different inferences about the impact of policy mood on public policy, indicate that Lagodny et al.’s claim that both their measure and Enns and Koch’s measure are valid is wrong; either neither measure is valid, or one is valid and the other is not. Moreover, extending the replications to include not only Lagodny et al.’s and Enns and Koch’s measures, but also Berry et al.’s measure and Caughey and Warshaw’s measure of mass economic liberalism, shows that each of the four measures yields a substantive conclusion about the effect of policy mood that is dramatically different than each of the other three measures. This suggests that the goal of developing a measure of state policy mood that would be widely accepted as valid remains elusive. [ABSTRACT FROM AUTHOR]

Enns and Koch question the validity of the Berry, Ringquist, Fording, and Hanson measure of state policy mood and defend the validity of the Enns and Koch measure on two grounds. First, they claim policy mood has become more conservative in the South over time; we present empirical evidence to the contrary: policy mood became more liberal in the South between 1980 and 2010. Second, Enns and Koch argue that an indicator’s lack of face validity in cross-sectional comparisons is irrelevant when judging the measure’s suitability in the most common form of pooled cross-sectional timeseries analysis. We show their argument is logically flawed, except under highly improbable circumstances. We also demonstrate, by replicating several published studies, that statistical results about the effect of state policy mood can vary dramatically depending on which of the two mood measures is used, making clear that a researcher’s measurement choice can be highly consequential. [ABSTRACT FROM AUTHOR]

This article analyses the radicalization of all of the five young offenders-aged between fourteen and eighteen years-who have been convicted in Spain between 2004 and 2019 of membership of a jihadist terrorist organization. It is based on: a) unprecedented access to the assessments of these youths produced by the Agency for the Reeducation and Reintegration of Young Offenders in the regional Government of Madrid; b) personal semi-structured interviews with the staff at this Agency responsible for their psycho-socio and educational intervention during their custodial measures; and c) judicial reports related to their cases. The article assesses the main features of the radicalization processes of these minors following a three-dimensional analysis at the micro, meso and macro level. It provides empirical evidence to test the validity of the main hypotheses on the causality of radicalization. [ABSTRACT FROM AUTHOR]

Online experiments are an integral part of the design and evaluation of software infrastructure at Internet firms. To handle the growing scale and complexity of these experiments, firms have developed software frameworks for their design and deployment. Ensuring that the results of experiments in these frameworks are trustworthy--referred to as internal validity--can be difficult. Currently, verifying internal validity requires manual inspection by someone with substantial expertise in experimental design. We present the first approach for checking the internal validity of online experiments statically, that is, from code alone. We identify well-known problems that arise in experimental design and causal inference, which can take on unusual forms when expressed as computer programs: failures of randomization and treatment assignment, and causal sufficiency errors. Our analyses target PlanOut, a popular framework that features a domain-specific language (DSL) to specify and run complex experiments. We have built PlanAlyzer, a tool that checks PlanOut programs for threats to internal validity, before automatically generating important data for the statistical analyses of a large class of experimental designs. We demonstrate PlanAlyzer's utility on a corpus of PlanOut scripts deployed in production at Facebook, and we evaluate its ability to identify threats on a mutated subset of this corpus. PlanAlyzer has both precision and recall of 92% on the mutated corpus, and 82% of the contrasts it generates match hand-specified data. [ABSTRACT FROM AUTHOR]

The relative decision self-information is a crucial evaluation function of feature selection in information system. It encapsulates classification information in upper and lower approximations and pays attention to the boundary region of samples. Nevertheless, with the frequent replacement of data, the static feature selection neglects the previous information of samples, which diminishes the computational efficiency. With the purpose of adapting to the evolution of the era, incremental learning is widely exerted in the field of data mining. In combination with incremental technique, it is not cumbersome to update the reduct in time. Enlightened by this, our work focuses on the mechanism of incremental feature selection due to the variation of objects in IvFDIS. Firstly, we construct λ -fuzzy similarity relation and introduce λ -fuzzy similarity self-information into IvFDIS based on relative decision self-information. Besides, with the assistance of matrix operation, we recommend static feature selection according to λ -fuzzy similarity self-information. Furthermore, two relevant incremental algorithms involving the insertion and removal of objects in IvFDIS are made a research. Finally, some comparative experiments are conducted on twelve public data sets to certify the validity of our incremental algorithms. Experimental results show that comparable to three tested algorithms, the proposed incremental algorithms lessen the computation time greatly, and they select fewer features in most instances without decreasing classification accuracy in IvFDIS. [ABSTRACT FROM AUTHOR]

For the multi-input single-output (MISO) system corrupted by colored noise, we transform the original system model into a new MISO output error model with white noise through data filtering technology. Based on the newly obtained model and the bias compensation principle, a novel data filtering-based bias compensation recursive least squares (BCRLS) identification algorithm is developed for identifying the parameters of the MISO system with colored noise disturbance. Unlike the exiting BCRLS method for the MISO system (see, in Section 3), without computing the complicated noise correlation functions, still the proposed method can achieve the unbiased parameters estimation of the MISO system in the case of colored process noises. The proposed algorithm simplifies the implementation of and further expands the application scope of the existing BCRLS method. Three numerical examples clearly illustrate the validity of and the good performances of the proposed method, including its superiority over the BCRLS method and so on. [ABSTRACT FROM AUTHOR]

In order to further explore the link between social inclusion/exclusion and perceived diversity, the present paper reports on the validation process of AATOS, a quali-quantitative instrument adopting a non-categorical approach in the study of adolescents’ attitudes towards their perceived “different” peers. Its psychometric properties were tested with a sample of 490 secondary school students. The reliability and construct validity of the attitude scale were assessed using factor analysis and testing several validation hypotheses. Moreover, two rounds of intercoder agreement were conducted to establish the consistency of the coding categories developed for the qualitative analysis. All in all, the findings of the current study suggest that the AATOS can be considered a robust instrument. [ABSTRACT FROM AUTHOR]

Due to the “curse of dimensionality” issue, how to discard redundant features and select informative features in high-dimensional data has become a critical problem, hence there are many research studies dedicated to solving this problem. Unsupervised feature selection technique, which does not require any prior category information to conduct with, has gained a prominent place in preprocessing high-dimensional data among all feature selection techniques, and it has been applied to many neural networks and learning systems related applications, e.g., pattern classification. In this article, we propose an efficient method for unsupervised feature selection via orthogonal basis clustering and reliable local structure preserving, which is referred to as OCLSP briefly. Our OCLSP method consists of an orthogonal basis clustering together with an adaptive graph regularization, which realizes the functionality of simultaneously achieving excellent cluster separation and preserving the local information of data. Besides, we exploit an efficient alternative optimization algorithm to solve the challenging optimization problem of our proposed OCLSP method, and we perform a theoretical analysis of its computational complexity and convergence. Eventually, we conduct comprehensive experiments on nine real-world datasets to test the validity of our proposed OCLSP method, and the experimental results demonstrate that our proposed OCLSP method outperforms many state-of-the-art unsupervised feature selection methods in terms of clustering accuracy and normalized mutual information, which indicates that our proposed OCLSP method has a strong ability in identifying more important features. [ABSTRACT FROM AUTHOR]

Many important traits of state legislatures vary across chambers within a state. Yet according to existing typologies in the comparative study of bicameralism, the 49 bicameral American state legislatures would be deemed quite homogeneous. To resolve this disjuncture, I identify a novel dimension of bicameralism that distinguishes among state legislatures by capturing the extent to which the two chambers serve as meaningfully different venues for influence. Based on this framework, I develop an index of bicameral "distinctiveness" rooted in three traits that speak to policy influence across chambers: the ratio of seats, bipartisan representation, and constituency dissimilarity. This measure reveals sizable variation across states and a conspicuous geographic pattern, with considerably greater bicameral distinctiveness in the Eastern United States. In turn, I assess the construct validity of this measure, showing how patterns of second chamber bill amendment vary systematically with the level of bicameral distinctiveness. [ABSTRACT FROM AUTHOR]

• Propose spread-based indices to measure vagueness of judgments in TFARPRs. • Develop an actual triangular fuzzy extension of Tanino's additive consistency. • Devise a method to generate consistent TFARPRs from fuzzy utility vectors. • Build a linear program to derive normalized fuzzy utility vectors from TFARPRs. • Obtain an analytical solution of normalized utility vectors for consistent TFARPRs. This paper focuses on extending Tanino's additive consistency to triangular fuzzy additive reciprocal preference relations (TFARPRs) and deriving normalized optimal fuzzy utility vectors from TFARPRs. Spread based indices are introduced to measure vagueness of [0, 1]-valued triangular fuzzy judgments and TFARPRs. A transitivity equation with parameters is devised to define additive consistency of TFARPRs. Values of parameters are then determined to introduce an equivalent definition of additively consistent TFARPRs. Pivotal properties of additively consistent TFARPRs are put forward and a computational formula is designed to obtain additive consistency indices of TFARPRs. A novel method is proposed to generate additively consistent TFARPRs from [0, 1]-valued triangular fuzzy utility vectors. By examining the equivalency of [0, 1]-valued triangular fuzzy utility vectors, a framework is presented to normalize triangular fuzzy utility vectors. A goal programming model is subsequently built to derive normalized triangular fuzzy utility vectors from TFARPRs. This optimization model is transformed into a linear program and its analytical solution is achieved for additively consistent TFARPRs. The performance and validity of the proposed models are demonstrated by three illustrations with comparative analysis. [ABSTRACT FROM AUTHOR]

Numerical modeling of electromagnetic waves is an important tool for understanding the interaction of light and matter, and lies at the core of computational electromagnetics. Traditional approaches to injecting and evolving electromagnetic waves, however, can be prohibitively expensive and complex for emerging problems of interest and can restrict the comparisons that can be made between simulation and theory. As an alternative, we demonstrate that electromagnetic waves can be incorporated analytically by decomposing the physics equations into analytic and computational parts. In particle-in-cell simulation of laser–plasma interaction, for example, treating the laser pulse analytically enables direct examination of the validity of approximate solutions to Maxwell's equations including Laguerre–Gaussian beams, allows lower-dimensional simulations to capture 3-D–like focusing, and facilitates the modeling of novel space–time structured laser pulses such as the flying focus. The flexibility and new routes to computational savings introduced by this analytic pulse technique are expected to enable new simulation directions and significantly reduce computational cost in existing areas. [ABSTRACT FROM AUTHOR]

Purpose: This paper aims to compare the performance of flow pulsation versus flow stirring in the context of mixing of a passive scalar at moderate Reynolds numbers in confined flows. This comparison has been undertaken in two limits: diffusion can be neglected as compared to convection (very large Peclet) and diffusion and convection effects are comparable. The comparison was performed both in terms of global parameters: pumping power and mixing efficiency and local flow topology. Design/methodology/approach: The study has been addressed by setting up a common conceptual three-dimensional problem that consisted of the mixing of two parallel streams in a square section channel past a square section prism. Stirring and pulsation frequencies and amplitudes were changed and combined at an inlet Reynolds number of 200. The numerical model was solved using a finite volume formulation by adapting a series of open-source OpenFOAM computational fluid dynamic (CFD) libraries. For cases with flow pulsation, the icoFoam solver for laminar incompressible transient flows was used. For cases with stirring, the icoDyMFoam solver, which uses the arbitrary Lagrangian–Eulerian method for the description of the moving dynamical mesh, was used to model the prism motion. At the local flow topology level, a new method was proposed to analyze mixing. Time evolution of folding and wrinkling of sheets made up of virtual particles that travel along streak lines was quantified by generating lower rank projections of the sheets onto the spaces spanned by the main eigenvectors of an appropriate space-temporal data decomposition. Findings: In the limit when convection is dominant, the results showed the superior performance of stirring versus flow pulsation both in terms of mixing and required pumping power. In the cases with finite Peclet, the mixing parameters by stirring and flow pulsation were comparable, but pulsation required larger pumping power than stirring. For some precise synchronization of stirring and pulsation, the mixing parameter reached its maximum, although at the expense of higher pumping power. At the local flow topology level, the new method proposed to quantify mixing has been found to correlate well with the global mixing parameter. Originality/value: A new systematic comparative study of two methods, stirring and pulsation, to achieve mixing of passive scalars in the mini scale for confined flows has been presented. The main value, apart from the conclusions, is that both methods have been tested against the same flow configuration, which allows for a self-consistent comparison. Of particular interest is the fact that it has been found that accurate synchronization of both methods yields mixing parameters higher than those associated to both methods taken separately. This suggests that it is possible to synchronize mixing methods of a different nature to achieve optimum designs. The new theoretical method that has been proposed to understand the mixing performance at the local level has shown promising results, and it is the intention of the authors to test its validity in a broader range of flow parameters. All these findings could be taken as potential guidelines for the design of mixing processes in the mini scale in the process industry. [ABSTRACT FROM AUTHOR]

Aiming at the information description and aggregation of group decision-making (GDM), this study develops an innovative GDM method based on Z-numbers and their aggregation techniques. The Z-number is a powerful tool for describing real-life information and reflecting information reliability. However, Z-numbers have a complicated three-dimensional structure, and many existing studies did not manage Z-numbers appropriately. Besides, no study has investigated Z-number aggregation considering Z-numbers' potential probability distributions. To remove the above defects, many valid techniques are introduced. An optimisation model is constructed to determine the potential probability distributions involved in Z-numbers. Then, a mean function for comparing Z-numbers is presented, and a series of Z-number operations are defined based on Archimedean t -norms and t -conorms. Moreover, a Z-number Bonferroni mean aggregation operator for integrating Z-number information is proposed. To test the applicability and validity of the developed Z-number GDM method, a new energy investment selection problem is addressed, and the sensitivity analysis and comparison discussion are conducted. The sensitivity results show that the developed method possesses favourable stability and effectiveness. In addition, the comparison results demonstrate that it outperforms other existing methods, and it can handle existing defects effectively. [ABSTRACT FROM AUTHOR]

The theoretical researches of three-way decision have become saturated. Hence, more and more researchers have focused on the applications and expansions of three-way decision. Combining three-way decision ideas with multi-criteria decision-making is a feasible research direction. In light of this, this paper proposes a novel TOPSIS method based on three-way decision models. First of all, for two types of fuzzy concepts with opposite characteristics, we establish the corresponding three-way decision models. Then, based on the decision regions calculated by these two types of fuzzy concepts, we analyze and study two ranking regulations for objects belonging to the same (different) decision regions, respectively. On the basis of these two regulations, we define the concept of a united decision region and further explore two ranking rules for objects belonging to the same (different) united decision regions, respectively. Subsequently, the positive ideal distance fuzzy set and the negative ideal distance fuzzy set obtained by the core idea of the TOPSIS method are respectively seen as "Cost fuzzy concept" and "Benefit fuzzy concept". Using the established decision rules based on the united decision regions, the classification and ranking of all objects are obtained. Finally, for the TOPSIS method based on three-way decision models, we test the feasibility and validity of the method from the perspectives of qualitative and quantitative analyses. [ABSTRACT FROM AUTHOR]

When involution affects individuals, their efforts do not augment resources but merely compete for limited resources. From entrance exams to company overtime, such efforts lead to unnecessary costs, undermining group welfare. Meanwhile, the individual advantages or collective disadvantages from this unnecessary effort may accumulate over time, such as the long-term validity of test scores. To identify the role of this memory factor, we propose a memory-based involution game model. In a more competitive environment, our findings suggest: (i) with scant social resources, increasing memory length curbs involution, (ii) with moderate resources, increasing memory length initially intensifies involution but later reduces it, and (iii) with abundant social resources, increasing memory length amplifies involution. Conversely, in a less competitive environment, involution consistently decreases with a larger memory length. Our research provides insights into mitigating involution by considering memory effects. • Investigated memory impacts in spatial involution games. • Strategies evolve based on historical payoffs. • In high-competition, memory inhibits involution with limited resources. • In low-competition, memory consistently inhibits involution. [ABSTRACT FROM AUTHOR]

A novel goodness-of-fit test for assessing the validity of maximum likelihood estimates of normal mixture densities with known number of components is introduced. The theoretical contributions include analytic quantification of the test statistic's size and power functions under fixed and local alternatives. These are used to derive a closed-form bandwidth rule which optimizes the test's power while keeping its size constant at a given significance level, and a cut-off point suitable for finite sample implementations of the test. An extensive simulation study compares the performance of the new test to well-established tests in the literature and demonstrates the superiority of the former in all examples considered. Finally, its practical usefulness is demonstrated in the analysis of two real world datasets. [ABSTRACT FROM AUTHOR]

An introduction is presented in which the authors briefly describe an article in the journal about the use of a tool called PlanAlyzer to test the validity of online experiments.

Fake news and manipulated information affect the social, economic and emotional growth of the world's population. For the identification of fake news, several classification systems are available, but no such system was found fast, secure and reliable as per the need of the hour. In this work, an efficient framework based on the federated architecture for the classification of fake news was proposed, while maintaining the data privacy constraints for sensitive text news datasets. The proposed federated-Fake New Classification (f-FNC) framework utilized the distributed client–server architecture with data privacy of all client or connected edge devices. For the testing and evaluation of the proposed f-FNC framework, the non-identical data was gathered from several online resources and was disseminated in a pre-processed format. To test the validity of federated deep learning models, the experiments were performed under various scenarios such as traditional learning, federated learning single client, and federated learning multi-clients. The performance of f-FNC framework was evaluated through various computational parameters such as accuracy and loss validation along with available resource parameters including CPU and RAM utilization. It was observed from the resultant outcome that the proposed f-FNC framework worked significantly well in both single-client and multi-client (N -clients) scenarios in comparison to traditional distributed deep learning based classifiers. The additional features of low cost and data-privacy of edge devices with limited resources made this proposed framework unique and the best alternative to existing fake news classifier tools. [ABSTRACT FROM AUTHOR]

This paper investigates the stabilization of uncertain neutral-type delay fractional systems. Both static and dynamic output feedback control design methods are proposed. A guaranteed cost-based feedback control design is considered and closed-loop robust stability is investigated using the Lyapunov theorem. Asymptotic stability conditions of the closed-loop system is described in terms of linear matrix inequalities (LMIs). A simulation study, encompassing a numerical example of a fractional order system and a two stage chemical reactor, is considered to assess the performance and validity of the proposed control design. • Investigates the stabilization of uncertain neutral-type fractional delay systems. • Develops static and dynamic output-feedback guaranteed cost control design methods for uncertain neutral-type fractional delay systems. • Derives criteria for the guaranteed cost stability against time-varying parametric uncertainty. [ABSTRACT FROM AUTHOR]

The conservativeness of the Simes test under dependence is a key issue in developing many other new test procedures and new error rate criteria. In this paper, we consider several p -variable models and investigate the validity and failure conditions of the Simes test under these models. The main results have some impact on testing concerns and can give us some insight on the interaction between validity of Simes test and dependence structure. [ABSTRACT FROM AUTHOR]

The thermal Sunyaev-Zeldovich effect contains information about the thermal history of the Universe, which is observable in maps of the Compton y parameter; however, it does not contain information about the redshift of the sources. Recent papers have utilized a tomographic approach, by cross correlating the Compton y map with the locations of galaxies with known redshift in order to deproject the signal along the line of sight. In this paper, we test the validity and accuracy of this tomographic approach to probe the thermal history of the Universe. We use the state-of-the-art, cosmological, and hydrodynamical simulation, Magneticum, for which the thermal history of the Universe is a known quantity. The key ingredient is the Compton-y-weighted halo bias, by, which is computed from the halo model. We find that, at redshifts currently available, the method reproduces the correct mean thermal pressure (or the density-weighted mean temperature) with high accuracy, validating and confirming the results of previous papers. At higher redshifts (z ≳ 2), there is significant disagreement between by from the halo model and the simulation. [ABSTRACT FROM AUTHOR]