We explore gender differences in individuals’ motivations. We focus on guilt aversion and moral commitment. Our experiment supports the idea that men are more guilt-averse than women, while moral motivations drive more women's actions in a random dictator game with pre-play communication.

Ensuring fairness in instruments like survey questionnaires or educational tests is crucial. One way to address this is by a Differential Item Functioning (DIF) analysis, which examines if different subgroups respond differently to a particular item, controlling for their overall latent construct level. DIF analysis is typically conducted to assess measurement invariance at the item level. Traditional DIF analysis methods require knowing the comparison groups (reference and focal groups) and anchor items (a subset of DIF-free items). Such prior knowledge may not always be available, and psychometric methods have been proposed for DIF analysis when one piece of information is unknown. More specifically, when the comparison groups are unknown while anchor items are known, latent DIF analysis methods have been proposed that estimate the unknown groups by latent classes. When anchor items are unknown while comparison groups are known, methods have also been proposed, typically under a sparsity assumption – the number of DIF items is not too large. However, DIF analysis when both pieces of information are unknown has not received much attention. This paper proposes a general statistical framework under this setting. In the proposed framework, we model the unknown groups by latent classes and introduce item-specific DIF parameters to capture the DIF effects. Assuming the number of DIF items is relatively small, an $L_1$\documentclass[12pt]{minimal}\usepackage{amsmath}\usepackage{wasysym}\usepackage{amsfonts}\usepackage{amssymb}\usepackage{amsbsy}\usepackage{mathrsfs}\usepackage{upgreek}\setlength{\oddsidemargin}{-69pt}\begin{document}$$L_1$$\end{document}-regularised estimator is proposed to simultaneously identify the latent classes and the DIF items. A computationally efficient Expectation-Maximisation (EM) algorithm is developed to solve the non-smooth optimisation problem for the regularised estimator. The performance of the proposed method is evaluated by simulation studies and an application to item response data from a real-world educational test.

What should we do about populism? In recent years, this question has become more urgent as populist leaders and parties have taken center stage in many countries across the globe. No longer a “minor” political phenomenon, populism has forced scholars to grapple with how to address its potential “threat” to “liberal democracy while also harnessing its “corrective” properties (Rovira Kaltwasser 2012). In this debate, the two questions of who “we” are—that is, who should respond—and how to do it often have taken different forms.

The recent rise of ‘qualified neutrality’ has proven highly controversial. Some have suggested that the separation between the jus ad bellum and the jus in bello under international law may prevent the reform of ‘traditional neutrality’ into qualified neutrality. This article will seek to resolve academic debate on this topic, arguing that the principle of separation is of limited relevance to perpetuation and reform within the law of neutrality. Although the principle of separation is prima facie incompatible with qualified neutrality, it does not have the required characteristics as a legal rule to inhibit reform of the law of neutrality and the recognition of qualified neutrality as a positive rule under international law.

By considering reaction to revolution in Europe during the late eighteenth and early nineteenth centuries in relation to the rise of the Gothic Revival, this article offers a bold assessment of the interplay between responses to the Middle Ages and political culture. It examines the Church of Santa Maria delle Grazie (1801–05) at the Vaccheria of the royal site of San Leucio, Caserta, in southern Italy, with a view to exploring the reciprocity between what can be seen as a neo-Gothic ’revolution’, wider political and industrial upheaval, and the historic ties between southern Italy and Sicily within the Mezzogiorno. In focusing on this neglected church, which was commissioned by Ferdinand IV of Naples and III of Sicily, the article aims to transcend the tendency in modern scholarship to discount the Gothic Revival in Italy as merely a superficial matter of taste. Recognising revivalism’s political agency, it is argued that Santa Maria delle Grazie bore witness to a profound stylistic crisis as classicism’s absolutist hegemony waned amid the epochal crisis of monarchical absolutism during the period. In tracing architectural and urban experimentation with respect to reactionism, proto-industrialism and medievalism in southern Italy, both before and after late eighteenth-century revolutionary activity, the Gothic Revival is situated within its proper revolutionary context. By extending considerations to Sicily and situating Santa Maria delle Grazie within the Mezzogiorno — through resonances with its medieval histories, including Norman and Swabian rule, and with contemporary ambitions for cohesion between the Kingdoms of Naples and Sicily — the article argues for the reactionary yet transnational visual and political dimensions of neo-medievalism. In so doing, it elucidates a symbiosis between architecture and medievalism as a formidable conduit for expressing and enacting power in the Age of Revolutions.

Contrary to the enduring image of Israelite priests as enveloped in an aura of serene sanctity, there is a darker side of the priesthood––one which associates its members and their ancestors with disturbing acts of interpersonal violence. The motif of priestly violence is a significant, albeit overlooked literary trope in the Hebrew Bible and post-biblical Jewish literature. This article identifies this motif and episodes in its reception, demonstrating how it relates to human sacrifice and the slaughter of animals in the sacrificial cult, and illuminating these connections with contemporary theories of religious and workplace violence. Finally, this study makes clear that certain negative portrayals of the priesthood are part-and-parcel of the Jewish interpretive tradition and should not be reflexively dismissed as reflective of anti-clericalism or anti-ritualism.

Article 58 of the European Convention on Human Rights (ECHR) contains a provision which allows for the involuntary withdrawal, or expulsion, of a State from the ECHR if it has been expelled from, or ceased to be a member of, the Council of Europe (CoE). By comparing Russia's exit from the ECHR in 2022 with that of Greece in 1969, this article demonstrates that involuntary withdrawal poses a number of legal problems—partly as a result of it not having been considered during the drafting of the ECHR or the Statute of the CoE, and partly because of the highly unclear basis on which involuntary withdrawal operates. The article then conducts a comparative analysis of other regional human rights systems and public international law principles on treaty withdrawal in order to suggest a more comprehensive legal foundation for expulsion.

Metabolic enzymes are the catalysts that drive the biochemical reactions essential for sustaining life. Many of these enzymes are tightly regulated by feedback mechanisms. To fully understand their roles and modulation, it is crucial to investigate the relationship between their structure, catalytic mechanism, and function. In this perspective, by using three examples from our studies on Mycobacterium tuberculosis (Mtb) isocitrate lyase and related proteins, we highlight how an integrated approach combining structural, activity, and biophysical data provides insights into their biological functions. These examples underscore the importance of employing fast-fail experiments at the early stages of a research project, emphasise the value of complementary techniques in validating findings, and demonstrate how in vitro data combined with chemical, biochemical, and physiological knowledge can lead to a broader understanding of metabolic adaptations in pathogenic bacteria. Finally, we address the unexplored questions in Mtb metabolism and discuss how we expand our approach to include microbiological and bioanalytical techniques to further our understanding. Such an integrated and interdisciplinary strategy has the potential to uncover novel regulatory mechanisms and identify new therapeutic opportunities for the eradication of tuberculosis. The approach can also be broadly applied to investigate other biochemical networks and complex biological systems.

PCA is a popular tool for exploring and summarizing multivariate data, especially those consisting of many variables. PCA, however, is often not simple to interpret, as the components are a linear combination of the variables. To address this issue, numerous methods have been proposed to sparsify the nonzero coefficients in the components, including rotation-thresholding methods and, more recently, PCA methods subject to sparsity inducing penalties or constraints. Here, we offer guidelines on how to choose among the different sparse PCA methods. Current literature misses clear guidance on the properties and performance of the different sparse PCA methods, often relying on the misconception that the equivalence of the formulations for ordinary PCA also holds for sparse PCA. To guide potential users of sparse PCA methods, we first discuss several popular sparse PCA methods in terms of where the sparseness is imposed on the loadings or on the weights, assumed model, and optimization criterion used to impose sparseness. Second, using an extensive simulation study, we assess each of these methods by means of performance measures such as squared relative error, misidentification rate, and percentage of explained variance for several data generating models and conditions for the population model. Finally, two examples using empirical data are considered.

Metabolism is at the core of all functions of living cells as it provides Gibbs free energy and building blocks for synthesis of macromolecules, which are necessary for structures, growth, and proliferation. Metabolism is a complex network composed of thousands of reactions catalyzed by enzymes involving many co-factors and metabolites. Traditionally it has been difficult to study metabolism as a whole network and most traditional efforts were therefore focused on specific metabolic pathways, enzymes, and metabolites. By using engineering principles of mathematical modeling to analyze and study metabolism, as well as engineer it, that is, design and build, new metabolic features, it is possible to gain many new fundamental insights as well as applications in biotechnology. Here, we present the history and basic principles of engineering metabolism, as well as the newest developments in the field. We are using examples of applications in: (1) production of protein pharmaceuticals and chemicals; (2) basic studies of metabolism; and (3) impacting health care. We will end by discussing how engineering metabolism can benefit from advances in artificial intelligence (AI)-based models.

Could you be a brain in a vat, with all your experiences of people, plants, pebbles, planets and more being generated solely by computer inputs? It might seem difficult to know that you aren’t, since everything in the world would still appear just as it is. In his 1981 book, Reason, Truth, and History, Hilary Putnam argues that if you were in such a predicament, your statement ‘I am a brain in a vat’’, would be false since, as an envatted brain, your word ‘vat’ would refer to the vats you encounter in your experienced reality, and in your experienced reality, you are not in one of those but are instead a full-bodied human being with head, torso, arms, and legs living in the wide open world. The following extended thought experiment is intended to illustrate that, contrary to Putnam’s view, you, as an envatted brain, could truthfully believe that you are a brain in a vat.

An overwhelming majority of articles in psychology compare means, often between multiple groups. However, sometimes we do not know the exact group membership, but only a probability to be in one of the groups. Such information may come from classifiers trained on other datasets, prevalence of group memberships for some parts of the sample, multi-level situations where the group membership is only known as a ratio in an upper level, or expert ratings (e.g., whether a person has a pathological condition or not). We present a simple method that allows to compare group means in the absence of exact knowledge about group membership and investigate the loss of information depending on the probability values theoretically and in a large-scale simulation.

The classical missing at random (MAR) assumption, as defined by Rubin (Biometrika 63:581–592, 1976), is often not required for valid inference ignoring the missingness process. Neither are other assumptions sometimes believed to be necessary that result from misunderstandings of MAR. We discuss three strategies that allow us to use standard estimators (i.e., ignore missingness) in cases where missingness is usually considered to be non-ignorable: (1) conditioning on variables, (2) discarding more data, and (3) being protective of parameters.

The pelagic thresher shark Alopias pelagicus is an Evolutionarily Distinct and Globally Endangered species primarily threatened by overfishing. Indonesia is the world's largest shark fishing nation, and in Alor Island, thresher sharks have been a primary target for small-scale fishing communities for decades, sustaining subsistence livelihoods and serving as a protein source. With thresher shark populations continuously declining, there is a need for conservation measures to reduce shark mortality from fishing, while also securing the well-being of coastal communities. This study presents results and lessons learnt from a multi-faceted effort to reduce communities’ dependence on this Endangered shark species through a livelihood-based intervention complemented by collaborative species management and community outreach. Using a theory-based and statistical research design, we describe the approach taken in our intervention and its conservation outcomes. Total thresher shark catches were 91% lower among fishers who participated in our intervention compared to non-participants. Participating fishers also experienced increases in their income, in some cases by up to 525% relative to the income before the intervention. Occasional violations and challenges in the form of socio-political conflicts also occurred, yet these incidents acted as catalysts for regulatory change and reinforced stakeholder collaboration. This suggests overall positive outcomes and the potential for continued social change in shark conservation in the region over the long term. Our findings outline some generalizable lessons learnt for designing and implementing bottom-up livelihood-based interventions in other contexts.

It is essential to control self-reported trait measurements for response style effects to ensure a valid interpretation of estimates. Traditional psychometric models facilitating such control consider item responses as the result of two kinds of response processes—based on the substantive trait, or based on response styles—and they assume that both of these processes have a constant influence across the items of a questionnaire. However, this homogeneity over items is not always given, for instance, if the respondents’ motivation declines throughout the questionnaire so that heuristic responding driven by response styles may gradually take over from cognitively effortful trait-based responding. The present study proposes two dynamic IRTree models, which account for systematic continuous changes and additional random fluctuations of response strategies, by defining item position-dependent trait and response style effects. Simulation analyses demonstrate that the proposed models accurately capture dynamic trajectories of response processes, as well as reliably detect the absence of dynamics, that is, identify constant response strategies. The continuous version of the dynamic model formalizes the underlying response strategies in a parsimonious way and is highly suitable as a cognitive model for investigating response strategy changes over items. The extended model with random fluctuations of strategies can adapt more closely to the item-specific effects of different response processes and thus is a well-fitting model with high flexibility. By using an empirical data set, the benefits of the proposed dynamic approaches over traditional IRTree models are illustrated under realistic conditions.

Two new species in the genera Diploicia and Physcia are described from the tropical dry forest of Mexico. Both species are supported by morphological, chemical and molecular evidence. Diploicia edulis, a species heavily consumed by invertebrates, is characterized by lecanorine apothecia, a dull brown epihymenium not diffused by a green pigment (K−), a subhymenium conspicuously inspersed with oil droplets, and the diploicin chemosyndrome. We provide the first molecular evidence to support the inclusion of species with lecanorine apothecia in the genus Diploicia. Physcia ornamentalis, previously reported under the name Physcia undulata s. lat. as one of the main construction materials for the bags of a moth caterpillar species (Psychidae), is characterized by a frosted-pruinose thallus, soralia originating in the lobe sinuses, and by lacking soralia in the thalline margin of the apothecia.

A multivariate generalization of the log-normal model for response times is proposed within an innovative Bayesian modeling framework. A novel Bayesian Covariance Structure Model (BCSM) is proposed, where the inclusion of random-effect variables is avoided, while their implied dependencies are modeled directly through an additive covariance structure. This makes it possible to jointly model complex dependencies due to for instance the test format (e.g., testlets, complex constructs), time limits, or features of digitally based assessments. A class of conjugate priors is proposed for the random-effect variance parameters in the BCSM framework. They give support to testing the presence of random effects, reduce boundary effects by allowing non-positive (co)variance parameters, and support accurate estimation even for very small true variance parameters. The conjugate priors under the BCSM lead to efficient posterior computation. Bayes factors and the Bayesian Information Criterion are discussed for the purpose of model selection in the new framework. In two simulation studies, a satisfying performance of the MCMC algorithm and of the Bayes factor is shown. In comparison with parameter expansion through a half-Cauchy prior, estimates of variance parameters close to zero show no bias and undercoverage of credible intervals is avoided. An empirical example showcases the utility of the BCSM for response times to test the influence of item presentation formats on the test performance of students in a Latin square experimental design.

This article considers how section 116 of the Australian Constitution applies to executive power. Notwithstanding that the express terms of s 116 apply only to legislative power, we argue that s 116 should be interpreted to also limit the exercise of executive power. A literal interpretation would have the effect that the Commonwealth can circumvent a constitutional limitation on legislative power through the exercise of executive power and would undermine the fundamental constitutional principle of legislative supremacy. An implication that s 116 restricts executive power in the same fashion as legislative power enhances the coherence of the Constitution as creating an integral polity and eliminates disconnect between legislative power and executive power with respect to the same subject matter.

Social scientists are often faced with data that have a nested structure: pupils are nested within schools, employees are nested within companies, or repeated measurements are nested within individuals. Nested data are typically analyzed using multilevel models. However, when data sets are extremely large or when new data continuously augment the data set, estimating multilevel models can be challenging: the current algorithms used to fit multilevel models repeatedly revisit all data points and end up consuming much time and computer memory. This is especially troublesome when predictions are needed in real time and observations keep streaming in. We address this problem by introducing the Streaming Expectation Maximization Approximation (SEMA) algorithm for fitting multilevel models online (or “row-by-row”). In an extensive simulation study, we demonstrate the performance of SEMA compared to traditional methods of fitting multilevel models. Next, SEMA is used to analyze an empirical data stream. The accuracy of SEMA is competitive to current state-of-the-art methods while being orders of magnitude faster.

This study delves into the comprehensive examination of an anta capital discovered during the 2008 excavations at the ancient site of Alabanda in Caria, now housed in the Aydın Archaeological Museum. Employing a typological and stylistic analysis, the research attributes the capital to the latter part of the fifth century BC, emphasising its intricate architectural ornamentation and sculptural details that reflect significant artistic and cultural developments of the period. The capital features elaborate ornament bands and mythological reliefs, including depictions of Bellerophon-Pegasus and Chimera, and a griffin attacking a horse, which are analysed for their iconographic and symbolic significance within the broader Anatolian and Mediterranean contexts. The study also explores the potential original architectural setting of the capital, suggesting its use in a monumental tomb, a hypothesis supported by its dimensions and decorative complexity. Furthermore, the article discusses the role of such imagery in asserting local identities and engaging with wider Hellenic cultural and political themes, particularly considering the complex interactions between local Carian traditions and the dominant Greek culture of the period. The findings not only contribute to our understanding of Carian art and architecture but also highlight the region’s active participation in the cultural dialogues of the Classical world.