Aalto University

About: Aalto University is a education organization based out in Espoo, Finland. It is known for research contribution in the topics: Population & Carbon nanotube. The organization has 9969 authors who have published 32648 publications receiving 829626 citations. The organization is also known as: TKK & Aalto-korkeakoulu.

The influence of a short-term gluten-free diet on the human gut microbiome

Abstract: A gluten-free diet (GFD) is the most commonly adopted special diet worldwide. It is an effective treatment for coeliac disease and is also often followed by individuals to alleviate gastrointestinal complaints. It is known there is an important link between diet and the gut microbiome, but it is largely unknown how a switch to a GFD affects the human gut microbiome. We studied changes in the gut microbiomes of 21 healthy volunteers who followed a GFD for four weeks. We collected nine stool samples from each participant: one at baseline, four during the GFD period, and four when they returned to their habitual diet (HD), making a total of 189 samples. We determined microbiome profiles using 16S rRNA sequencing and then processed the samples for taxonomic and imputed functional composition. Additionally, in all 189 samples, six gut health-related biomarkers were measured. Inter-individual variation in the gut microbiota remained stable during this short-term GFD intervention. A number of taxon-specific differences were seen during the GFD: the most striking shift was seen for the family Veillonellaceae (class Clostridia), which was significantly reduced during the intervention (p = 2.81 × 10−05). Seven other taxa also showed significant changes; the majority of them are known to play a role in starch metabolism. We saw stronger differences in pathway activities: 21 predicted pathway activity scores showed significant association to the change in diet. We observed strong relations between the predicted activity of pathways and biomarker measurements. A GFD changes the gut microbiome composition and alters the activity of microbial pathways.

PLS marker variable approach to diagnosing and controlling for method variance

Abstract: Partial least squares (PLS) path modeling has been adopted as part of the statistical toolbox of many information systems (IS) scholars, particularly when dealing with survey data. Since these data are susceptible to common method variance, several statistical approaches for diagnosing and controlling for this undesirable feature have been developed. While most of these statistical techniques are only applicable to structural equation modeling (SEM), Liang, Saraf, Hu, and Xue (2007) proposed how one of these techniques can be used with PLS analysis. Since this was the first time that a method for controlling common method variance had been made available for PLS users, the method of Liang et al. quickly gained popularity in IS journals. However, recent analysis on the Liang et all approach shows that the method does neither detect nor control for common method variance. In this paper, we propose an alternative PLS marker variable approach for analyzing data contaminated with method variance and provide simulation evidence for the validity of this new approach.

Ethos at stake: Performance management and academic work in universities

Abstract: Higher education has been subject to substantial reforms as new forms of performance management are implemented in universities across the world. Extant research suggests that in many cases performance management systems have disrupted academic life. We complement this literature with an extensive mixed methods study of how the performance management system is understood by academics across universities and departments in Finland at a time when new management principles and practices are being forcefully introduced. While our survey results enabled us to map the generally critical and negative view that Finnish scholars have of performance management, the qualitative inquiry allowed us to disentangle how and why our respondents resent the ways and means of measuring their work, the assumptions that underlie the measurement, and the university ideal on which the performance management system is rooted. Most significantly, we highlight how the proliferation of performance management can be seen as a catalys...

Suppression of electron–vibron coupling in graphene nanoribbons contacted via a single atom

Abstract: Graphene nanostructures have a tremendous potential for electronic applications, although contacting them with atomic precision remains a challenge. Here, van der Lit and colleagues achieve contacting graphene nanoribbons via only a single atom, without affecting its electronic structure.

Quantifying Controversy on Social Media

Abstract: Which topics spark the most heated debates on social media? Identifying those topics is not only interesting from a societal point of view but also allows the filtering and aggregation of social media content for disseminating news stories. In this article, we perform a systematic methodological study of controversy detection by using the content and the network structure of social media. Unlike previous work, rather than studying controversy in a single hand-picked topic and using domain-specific knowledge, we take a general approach to study topics in any domain. Our approach to quantifying controversy is based on a graph-based three-stage pipeline, which involves (i) building a conversation graph about a topic, (ii) partitioning the conversation graph to identify potential sides of the controversy, and (iii) measuring the amount of controversy from characteristics of the graph. We perform an extensive comparison of controversy measures, different graph-building approaches, and data sources. We use both controversial and non-controversial topics on Twitter, as well as other external datasets. We find that our new random-walk-based measure outperforms existing ones in capturing the intuitive notion of controversy and show that content features are vastly less helpful in this task.