Intramuscular fatty acid composition in beef from Aosta cattle breeds

The aim of this research was to compare fat quality of three categories of the Aosta cattle breeds by fatty acid composition. Samples of longissimus thoracis et lumborum from 12 calves, 11 young bulls and 11 cows of Aosta Red Pied and Black Pied were bought at retail. Fatty acids content showed in most cases, except for C18:1, significant differences between the three categories. Veal calves had the lowest proportion of SFA and highest of PUFA, therefore they had the best PUFA/SFA ratio but the worst n-6/n-3 ratio due to the highest proportion of C18:2n-6. Besides veal calves was healthier by having best atherogenicity and thrombogenicity indices. Black Pied young bulls, in comparison to Red Pied young bulls, showed a significant lower proportion of C10:0, C18:1, and a significant higher proportion of C18:2n-6, C18:3n-3 and C20:4n-6. Consequently they had a significant lower MUFA content but a higher PUFA content therefore a significant better PUFA/SFA ratio

The emotional side of software developers in JIRA

Issue tracking systems store valuable data for testing hypotheses concerning maintenance, building statistical prediction models and (recently) investigating developer affectiveness. For the latter, issue tracking systems can be mined to explore developers emotions, sentiments and politeness |affects for short. However, research on affect detection in software artefacts is still in its early stage due to the lack of manually validated data and tools. In this paper, we contribute to the research of affects on software artefacts by providing a labeling of emotions present on issue comments. We manually labeled 2,000 issue comments and 4,000 sentences written by developers with emotions such as love, joy, surprise, anger, sadness and fear. Labeled comments and sentences are linked to software artefacts reported in our previously published dataset (containing more than 1K projects, more than 700K issue reports and more than 2 million issue comments). The enriched dataset presented in this paper allows the investigation of the role of affects in software development

Cryptocurrency ecosystems and social media environments: An empirical analysis through Hawkes’ models and natural language processing

Copyright © 2021 The Author(s). We analyse, using a mixture of statistical models and natural language process techniques, what happened in social media from June 2019 onwards to understand the relationships between Cryptocurrencies’ prices and social media, focusing on the rise of the Bitcoin and Ethereum prices. In particular, we identify and model the relationship between the cryptocurrencies market price changes, and sentiment and topic discussion occurrences on social media, using Hawkes’ Model. We find that some topics occurrences and rise of sentiment in social media precedes certain types of price movements. Specifically, discussions concerning governments, trading, and Ethereum cryptocurrency as an exchange currency appear to negatively affect Bitcoin and Ethereum prices. Those concerning investments, appear to explain price rises, whilst discussions related to new decentralized realities and technological applications explain price falls. Finally, we validate our model using a real case study: the already famous case of ”Wallstreetbet and GameStop”1 that took place in January 2021.Funding: No funding was received for this work

Do developers really worry about refactoring re-test? An empirical study of open-source systems

© Springer Nature Switzerland AG 2018. In this paper, we explore the extent to which a set of over 12000 refactorings fell into one of four re-test categories defined by van Deursen and Moonen; the ‘least disruptive’ of the four categories contains refactorings requiring only minimal re-test. The ‘most disruptive’ category of refactorings on the other hand requires significant re-test effort. We used multiple versions of three open-source systems to answer one research question: Do developers prefer to undertake refactorings in the least disruptive categories or in the most disruptive? The simple answer is that they prefer to do both. We provide insights into these refactoring patterns across the systems and highlight a fundamental weakness with software metrics trying to capture the refactoring process

On the Relationship Between Coupling and Refactoring: An Empirical Viewpoint

[Background] Refactoring has matured over the past twenty years to become part of a developer's toolkit. However, many fundamental research questions still remain largely unexplored. [Aim] The goal of this paper is to investigate the highest and lowest quartile of refactoring-based data using two coupling metrics - the Coupling between Objects metric and the more recent Conceptual Coupling between Classes metric to answer this question. Can refactoring trends and patterns be identified based on the level of class coupling? [Method] In this paper, we analyze over six thousand refactoring operations drawn from releases of three open-source systems to address one such question. [Results] Results showed no meaningful difference in the types of refactoring applied across either lower or upper quartile of coupling for both metrics; refactorings usually associated with coupling removal were actually more numerous in the lower quartile in some cases. A lack of inheritance-related refactorings across all systems was also noted. [Conclusions] The emerging message (and a perplexing one) is that developers seem to be largely indifferent to classes with high coupling when it comes to refactoring types - they treat classes with relatively low coupling in almost the same way

A model to explain angular distributions of J/ψJ/\psi and ψ(2S)\psi(2S) decays into ΛΛ‾\Lambda\overline{\Lambda} and Σ0Σ‾0\Sigma^0\overline{\Sigma}^0

BESIII data show a particular angular distribution for the decay of the $J/\psi$ and $\psi(2S)$ mesons into the hyperons $\Lambda\overline{\Lambda}$ and $\Sigma^0\overline{\Sigma}^0$. More in details the angular distribution of the decay $\psi(2S) \to \Sigma^0\overline{\Sigma}^0$ exhibits an opposite trend with respect to that of the other three channels: $J/\psi \to \Lambda\overline{\Lambda}$, $J/\psi \to \Sigma^0\overline{\Sigma}^0$ and $\psi(2S) \to \Lambda\overline{\Lambda}$. We define a model to explain the origin of this phenomenon.Comment: 6 pages, 7 figures, to be published in Chinese Physics