Genotype by year interaction for selected quantitative traits in hybrid lines of Triticum aestivum L. with Aegilops kotschyi Boiss. and Ae. variabilis Eig. using the additive main effects and multiplicative interaction model

This study estimated the genotype × environment interactions for ten yield associated traits in advanced generation hybrids of several cultivars of common wheat (Triticum aestivum L.) with Aegilops kotschyi Boiss. and A. variabilis Eig. using the additive main effects and multiplicative interaction (AMMI) models. Tests were ran over five years at one location in replicated field trials. The AMMI model showed significant genotypic and environmental effects for all analysed traits. A majority of the hybrid lines were less stable in the analysed traits than their parental wheats. The older wheat cultivars, with lower environmental sensitivity, were the most stable. The best total genotype selection index, for all ten traits combined, was observed for the oldest cvs. Gama and Rusałka, and among the hybrid lines, for Ae. kotschyi/Rusałka//Smuga and Ae. kotschyi/Rusałka//Muza. The lines Ae. kotschyi/Rusałka//Smuga, Ae. kotschyi/Rusałka//Muza, Ae. kotschyi/Rusałka//Korweta, Ae. kotschyi/Rusałka//Begra///Smuga, and Ae. kotschyi/Rusałka//Begra///Turnia are recommended for inclusion in breeding programmes due to their greater stability and the good average values for the observed traits.

Differences in attitudes toward terrorists: Type of terrorist act, terrorist ethnicity, and observer gender and cultural background

To explore the interrelationship between terrorist acts, terrorist ethnicity, and observer gender and cultural background in Israel, we recruited 211 participants aged 19–75 years. The majority were male (63%). As for the ethnic and religious cultural background, 40% were Jewish, 40% Druze, and 20% Muslim. The participants answered questions about their demographic characteristics, read three scenarios of terrorist acts, addressed attitudes toward terrorists, and suggested the length of imprisonment. We manipulated the type of act (shooting and killing/burning religious institutions/throwing stones at cars) and terrorist ethnicity (Arab/ Jewish). The results indicate significant main effects of the manipulated variables regarding attitudes toward terrorists. Also, Muslim Arab participants expressed more negative attitudes in cases of Jewish terrorists than Arab terrorists, whereas Jewish participants expressed more negative attitudes toward Arab terrorists than Jewish terrorists. Druze participants did not differentiate between Arab and Jewish terrorists. Furthermore, in cases of Arab perpetrators, Jewish participants suggested imprisonment terms 2.4 times longer than in cases of Jewish perpetrators. The discussion addresses the findings in the context of social identity theory and dual social identification. Regarding practical implications, the findings imply the need for education and training on ethnic bias among policymakers and practitioners.

Managing the terror of publication bias: A comprehensive p-curve analysis of the Terror Management Theory literature

A key prediction of Terror Management Theory is that people affirm their cultural worldview after they are reminded of death. This mortality salience (MS) hypothesis has been widely explored, yet the presence of questionable research practices may impact the replicability of this literature. We assess the evidential value of the MS hypothesis by conducting a pre-registered p-curve analysis of 860 published studies. Our results suggest that there are nonzero effects in this literature and that power is larger for studies conducted with multiple delays between the independent and dependent variables, for studies that test for main effects in comparison to those that test for interactions, and for studies conducted more recently. However, since the estimated average power of MS studies is 26%, direct replications are unlikely to succeed. We recommend researchers consider our evidence when planning their samples, and that they anticipate smaller effects by increasing their sample sizes.

Bayesian Genomic Linear Regression

The Bayesian paradigm for parameter estimation is introduced and linked to the main problem of genomic-enabled prediction to predict the trait of interest of the non-phenotyped individuals from genotypic information, environment variables, or other information (covariates). In this situation, a convenient practice is to include the individuals to be predicted in the posterior distribution to be sampled. We explained how the Bayesian Ridge regression method is derived and exemplified with data from plant breeding genomic selection. Other Bayesian methods (Bayes A, Bayes B, Bayes C, and Bayesian Lasso) were also described and exemplified for genome-based prediction. The chapter presented several examples that were implemented in the Bayesian generalized linear regression (BGLR) library for continuous response variables. The predictor under all these Bayesian methods includes main effects (of environments and genotypes) as well as interaction terms related to genotype × environment interaction.

Bayesian and Classical Prediction Models for Categorical and Count Data

In this chapter, we explain, under a Bayesian framework, the fundamentals and practical issues for implementing genomic prediction models for categorical and count traits. First, we derive the Bayesian ordinal model and exemplify it with plant breeding data. These examples were implemented in the library BGLR. We also derive the ordinal logistic regression. The fundamentals and practical issues of penalized multinomial logistic regression and penalized Poisson regression are given including several examples illustrating the use of the glmnet library. All the examples include main effects of environments and genotypes as well as the genotype × environment interaction term.

B Corp Certification Effects

Compliance with the Sustainable Development Goals (SDGs) and the 2030 Agenda represents a large investment that cannot be obtained solely through public resources. Therefore, it is necessary for the private sector to align itself with the SDGs and integrate them into its business model. In an attempt to align private interests with the SDGs, various impact measurement initiatives have emerged in recent years. However, none of them have been universally accepted, in part, because they still have weaknesses. As an alternative, some companies have chosen to become certified. The figures show that the B Corp certification is one of the most important ones internationally, since it has been growing at a rapid pace since its creation. In fact, there are currently almost 4,000 certified companies throughout the world. Despite this fact, there are very few studies which analyze the main effects of this certification yet. Therefore, the objective of this chapter is to validate a questionnaire that collects these effects through a Delphi study, formed by a panel of experts in the B Corp movement.

Functional Regression

This chapter deals with the main theoretical fundamentals and practical issues of using functional regression in the context of genomic prediction. We explain how to represent data in functions by means of basis functions and considered two basis functions: Fourier for periodic or near-periodic data and B-splines for nonperiodic data. We derived the functional regression with a smoothed coefficient function under a fixed model framework and some examples are also provided under this model. A Bayesian version of functional regression is outlined and explained and all details for its implementation in glmnet and BGLR are given. The examples take into account in the predictor the main effects of environments and genotypes and the genotype × environment interaction term. The examples are done with small data sets so that the user can run them on his/her own computer and can understand the implementation process.

Citizen Involvement in Public Services Design

In the last years new relational systems between citizens and Institutions have been arising. One of the main effects of such transformation is an increasing citizen engagement in designing public services. The motivations, modes, and effects concerning this practice are relevant research topics addressing political, social, and economic issues. In this paper the authors present the SPAC3 project, as it involved the citizens in the design process. The project aims to allow families of the Municipality of Bergamo (Italy) to access services and information dedicated to them in a more effective way. Here, the authors will focus on the analysis carried out in the project, by pointing out the methodology and the main achieved outcomes, and the features of the identified solution. In the end, the SPAC3 project has been a good opportunity to think about the complex relationship between citizens and Institutions in order to strengthen it.

Optimised Reduction of Surgical Gloves Pinholes using Forward Search Method

This research investigates the factors that affect the existence of pinholes in surgical gloves during the manufacturing process. Since eight factors affect the existence of pinholes in surgical gloves, a two-level fractional factorial design 28-4 was used to study the main effects and the first-order interactions of the multiple variables. Multiple linear regressions are used to model the data. This paper also examines the presence of influential points in the data using the influential measures in linear regression such as Cook’s Distance, DFFITS, DFBETAS, Studentized Residual, Standardized Residual, Hadi's measure, and the robust forward search. The impact of influential points is further assessed through deletion of potential influential points and model selection using adjusted R2, information criterion, and stepwise selection to see whether these influential points significantly improved the existing model.