scCross: efficient search for rare subpopulations across multiple single-cell samples.

Motivation: Identifying rare cell types is an important task to capture the heterogeneity of single-cell data, such as scRNA-seq. The widespread availability of such data enables to aggregate multiple samples, corresponding for example to different donors, into the same study. Yet, such aggregated data is often subject to batch effects between samples.

Decision trees: from efficient prediction to responsible AI.

This article provides a birds-eye view on the role of decision trees in machine learning and data science over roughly four decades. It sketches the evolution of decision tree research over the years, describes the broader context in which the research is situated, and summarizes strengths and weaknesses of decision trees in this context. The main goal of the article is to clarify the broad relevance to machine learning and artificial intelligence, both practical and theoretical, that decision trees still have today.

Applying persuasive messages to reduce public outdoor smoking: A pseudo-randomized controlled trial.

Despite efforts to create dedicated smoking areas and no-smoking signs, many smokers continue to light their cigarettes in front of public building entrances-leading to concerns over health consequences for non-smokers passing by. To increase compliance with no-smoking requests, behavioral interventions that tap into habitual and automatic processes seem promising. A pseudo-randomized controlled trial was conducted to assess the differential impact of seven behavioral interventions based on Cialdini's principles of persuasion.