Search

ABSTRACTThe relation between religiosity and well-being is one of the most researched topics in the psychology of religion, yet the directionality and robustness of the effect remains debated. Here, we adopted a many-analysts approach to assess the robustness of this relation based on a new cross-cultural dataset (participants from 24 countries). We recruited 120 analysis teams to investigate (1) whether religious people self-report higher well-being, and (2) whether the relation between religiosity and self-reported well-being depends on perceived cultural norms of religion (i.e., whether it is considered normal and desirable to be religious in a given country). In a two-stage procedure, the teams first created an analysis plan and then executed their planned analysis on the data. For the first research question, all but 3 teams reported positive effect sizes with credible/confidence intervals excluding zero (median reported ). For the second research question, this was the case for 65% of the teams (median reported ). While most teams applied (multilevel) linear regression models, there was considerable variability in the choice of items used to construct the independent variables, the dependent variable, and the included covariates.

The electrochemical energy storage in organic compounds has gained increasing interest in recent years. The acetone reduction can serve simultaneously as a model compound for electrochemical ketone reduction and as an electrochemical liquid organic hydrogen carrier. This study investigates the influence of temperature and concentration on the electrochemical acetone reduction reaction (ARR) to isopropanol (2-propanol) in a membrane electrode assembly. It reports, in particular, on the faradaic efficiency and performance of the system both in fuel cell mode (above 0 V vs RHE) and in hydrogen pumping mode (below 0 V vs RHE). This investigation is performed by applying cyclovoltammetry, electrochemical impedance spectroscopy (EIS), and amperometry. Shape analysis of the recorded EIS data is performed, and mass transport limitation is identified as one major problem of this configuration. Additionally, thermocatalytic experiments are conducted to ensure comparability, and the specific reaction rates of both approaches are compared to each other, thus emphasizing the importance of referencing when performing electrochemical reduction experiments. Propane formation has been found as a relevant side reaction of the ARR in thermocatalytic and electrocatalytic experiments.

This study investigates the influence of anode flow channel depth on the performance of a polymer electrolyte membrane water electrolyser (PEMWE). The channel depth was varied from 3 to 8 mm and the cell performance was studied at current densities up to 2.0 A cm-2 using electrochemical impedance spectroscopy (EIS). The effect of flow channel depth on performance was negligible at low and medium current densities, but significant at high current densities. Results show a non-monotonic dependence of channel depth on performance at high current density which was attributed to the coupled effect of flow velocity and mass transfer characteristics. Optimization of the dimensions and shape of the flow-field is crucial to reduce mass transport losses and improve electrolyser performance especially at high current densities.

Corporate social responsibility (CSR) and innovation are common keywords in management research and practice. Both of them are understood in different ways. To discover the boundaries of CSR and innovation, this paper sheds light on the traditional view of CSR, with a focus on its (CSR) integration into the corporate strategy and its linkages to innovation. On the basis of a systematic literature review, a conceptual framework is developed. This framework categorises socio-political stakeholders and identifies other relevant stakeholders on the basis of a theoretical typology. Finally, dialogue strategies are examined regarding their fit within the corporate innovation process. In this regard, stakeholder collaboration is suggested as the appropriate strategy of engaging strategically significant stakeholders. The paper concludes with implications, limitations and further research suggestions.

In the past, the agency theory was used to analyse problems within supply networks. This theory suggested different solutions to bring about a reduction in information asymmetries. However, doing so in the future will prove to be difficult owing to the increasing complexity of supply networks. Moreover, along with the fourth industrial revolution - industry 4.0 - new technologies such as cyber physical systems are fast gaining popularity. Hence, based on the analysis of relevant literature, we further develop the supply chain committee model, developed by Kaluza et al. (2003) to demonstrate how upcoming technologies can be integrated. This may help manage agency problems, despite the growth in complexity in supply networks.

Meta-analyses are essential for cumulative science, but their validity can be compromised by publication bias. To mitigate the impact of publication bias, one may apply publication-bias-adjustment techniques such as precision-effect test and precision-effect estimate with standard errors (PET-PEESE) and selection models. These methods, implemented in JASP and R, allow researchers without programming experience to conduct state-of-the-art publication-bias-adjusted meta-analysis. In this tutorial, we demonstrate how to conduct a publication-bias-adjusted meta-analysis in JASP and R and interpret the results. First, we explain two frequentist bias-correction methods: PET-PEESE and selection models. Second, we introduce robust Bayesian meta-analysis, a Bayesian approach that simultaneously considers both PET-PEESE and selection models. We illustrate the methodology on an example data set, provide an instructional video (https://bit.ly/pubbias) and an R-markdown script (https://osf.io/uhaew/), and discuss the interpretation of the results. Finally, we include concrete guidance on reporting the meta-analytic results in an academic article.

The default use of an alpha level of .05 is suboptimal for two reasons. First, decisions based on data can be made more efficiently by choosing an alpha level that minimizes the combined Type 1 and Type 2 error rate. Second, it is possible that in studies with very high statistical power, pvalues lower than the alpha level can be more likely when the null hypothesis is true than when the alternative hypothesis is true (i.e., Lindley’s paradox). In this article, we explain two approaches that can be used to justify a better choice of an alpha level than relying on the default threshold of .05. The first approach is based on the idea to either minimize or balance Type 1 and Type 2 error rates. The second approach lowers the alpha level as a function of the sample size to prevent Lindley’s paradox. An R package and Shiny app are provided to perform the required calculations. Both approaches have their limitations (e.g., the challenge of specifying relative costs and priors) but can offer an improvement to current practices, especially when sample sizes are large. The use of alpha levels that are better justified should improve statistical inferences and can increase the efficiency and informativeness of scientific research.

Identification of the state-of-health (SoH) of Li-ion cells is a vital tool to protect operating battery packs against accelerated degradation and failure. This is becoming increasingly important as the energy and power densities demanded by batteries and the economic costs of packs increase. Here, ultrasonic time-of-flight analysis is performed to demonstrate the technique as a tool for the identification of a range of defects and SoH in Li-ion cells. Analysis of large, purpose-built defects across multiple length scales is performed in pouch cells. The technique is then demonstrated to detect a microscale defect in a commercial cell, which is validated by examining the acoustic transmission signal through the cell. The location and scale of the defects are confirmed using X-ray computed tomography, which also provides information pertaining to the layered structure of the cells. The demonstration of this technique as a methodology for obtaining direct, non-destructive, depth-resolved measurements of the condition of electrode layers highlights the potential application of acoustic methods in real-time diagnostics for SoH monitoring and manufacturing processes.

This study investigates the influence of anode flow channel depth on the performance of a polymer electrolyte membrane water electrolyser (PEMWE). The channel depth was varied from 3 to 8 mm and the cell performance was studied at current densities up to 2.0 A cm-2 using electrochemical impedance spectroscopy (EIS). The effect of flow channel depth on performance was negligible at low and medium current densities, but significant at high current densities. Results show a non-monotonic dependence of channel depth on performance at high current density which was attributed to the coupled effect of flow velocity and mass transfer characteristics. Optimization of the dimensions and shape of the flow-field is crucial to reduce mass transport losses and improve electrolyser performance especially at high current densities.