Study2

Generated data and R code for Experiment

Phosphate-Functionalized Stabilized F127 Nanoparticles: Introduction of Discrete Surface Charges and Electrophoretic Determination of Aggregation Number

Pluronic F127 forms spherical micelle with a defined number of molecules aggregated in aqueous environments. Such self-assembled micelles dissociate into unimers below certain concentration and temperature. We stabilized the micelles by semi-interpenetrating network (sIPN) formation within the hydrophobic core in the presence of a fluorescent dye. Additionally, by varying the mixing ratio of negatively charged and pristine F127s we prepared thermally stable polymeric nanoparticles with discrete surface charges within nearly same sizes. Using the nanomaterials with prescribed number of charges, we demonstrate that the electrophoretic mobility of nanoparticles is solely depending on number of surface charges. Finally, the aggregation number (Nagg) of F127 was further determined by electrophoresis

Insights into the accuracy of social scientists' forecasts of societal change

How well can social scientists predict societal change, and what processes underlie their predictions? To answer these questions, we ran two forecasting tournaments testing the accuracy of predictions of societal change in domains commonly studied in the social sciences: ideological preferences, political polarization, life satisfaction, sentiment on social media, and gender-career and racial bias. After we provided them with historical trend data on the relevant domain, social scientists submitted pre-registered monthly forecasts for a year (Tournament 1; N = 86 teams and 359 forecasts), with an opportunity to update forecasts on the basis of new data six months later (Tournament 2; N = 120 teams and 546 forecasts). Benchmarking forecasting accuracy revealed that social scientists' forecasts were on average no more accurate than those of simple statistical models (historical means, random walks or linear regressions) or the aggregate forecasts of a sample from the general public (N = 802). However, scientists were more accurate if they had scientific expertise in a prediction domain, were interdisciplinary, used simpler models and based predictions on prior data. How accurate are social scientists in predicting societal change, and what processes underlie their predictions? Grossmann et al. report the findings of two forecasting tournaments. Social scientists' forecasts were on average no more accurate than those of simple statistical models