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Developmental Growth Control Exerted via the Protein A Kinase Tpk2 in Ashbya gossypii.

Sporulation in Ashbya gossypii is induced by nutrient-limited conditions and leads to the formation of haploid spores. Using RNA-seq, we have determined a gene set induced upon sporulation, which bears considerable overlap with that of Saccharomyces cerevisiae but also contains A. gossypii-specific genes. Addition of cyclic AMP (cAMP) to nutrient-limited media blocks sporulation and represses the

Sustainable entrepreneurship undergraduate education: A community of practice perspective

This chapter explores how an undergraduate elective course employs a community of practice to change students’ perceptions on sustainable entrepreneurship. For this purpose, the authors conducted a case study of an undergraduate elective course in a Swedish business school re-designed to adopt sustainability and sustainable entrepreneurship education. The authors found evidence that, when students

Territories and networks in Europe : In search of a spatial order

Medieval Europe was characterized by geopolitical disorder and territorial disunion. Around 1500 AD, as the modern era dawned, Europe comprised some 1,500 districts which were largely politically independent. Gradually, medium sized territories emerged around cores made up of cultural, economic, and political centres. The Lake Malar area in Sweden was such a territory; London, Paris, Berlin-Potsda

What do the researchers say?

- here is a selection of their thoughts on the Pufendorf IAS Since 2009, the Pufendorf Institute for Advanced Studies has welcomed hundreds of interdisciplinary groups and thousands of researchers from Lund University. Here we have collected a selection of quotes and links to news articles that all, in different ways, convey messages from researchers to researchers. One researcher's words about th

https://www.pi.lu.se/en/about-pufendorf-ias-0/what-do-researchers-say - 2026-06-07

Learning characteristic decision trees

Decision trees constructed by ID3-like algorithms suffer from an inability of detecting instances of categories not present in the set of training examples, i.e., they are discriminative representations. Instead, such instances are assigned to one of the classes actually present in the training set, resulting in undesired misclassifications. Two methods of reducing this problem by learning charact