La contribución de la ALFIN a la Ciencia Abierta

O campo de atuação da Ciência Aberta traduz-se num processo colaborativo, transparente, de disseminação, criação e de transferência de conhecimento, acessível à investigação e assente nos princípios do acesso aberto. Os diferentes agentes do processo de investigação, munidos de um conjunto de competências de literacia da informação, adquirem a aptidão, em ambientes de informação impressa ou digital, e tendo por base o seu próprio pensamento crítico e reflexivo, de transformar a informação em novo conhecimento. Este artigo explora a integração dos conceitos da Ciência Aberta na literacia da informação. Apresenta-se uma reflexão teórica que evidencia os contributos da literacia da informação em contexto académico e na dinâmica da produção de ciência. Conclui-se que a literacia da informação se assume como uma ferramenta de aprendizagem essencial para o desenvolvimento da Ciência Aberta, potenciando o entendimento crítico dos conteúdos, a par do desenvolvimento e do progresso da investigação.The scope of Open Science translates into a collaborative, transparent process of dissemination, creation, and transfer of knowledge, accessible to research and based on the principles of open access. The different agents of the research process, equipped with a set of information literacy skills, acquire the ability, in print or digital information environments, and based on their own critical and reflexive thinking, to transform information into new knowledge. This article explores the integration of Open Science concepts in information literacy. It presents a theoretical reflection that shows the contributions of information literacy in the academic context and in the dynamics of the production of science. It is concluded that information literacy is an essential learning tool for the development of Open Science, enhancing the critical understanding of content, as well as the development and progress of research.info:eu-repo/semantics/publishedVersio

Feeding kinematics of S. aurata obtained with the 3D system

Feeding kinematics of 93 feeding attempts of S. aurata on rotifers, obtained with the 3D system. larval age is in Days Post Hatching (DPH). time to minimal prey distance (MPD) is in units of TTPG cycles

Feeding kinematics of S. aurata, obtained with the continuous high speed system

Feeding kinematics in 246 feeding attempts of S. aurata on rotifers, obtained with the continuous high speed system. larval age is in Days Post Hatching (DPH). viscosity is relative to that of of unmanipulated sea water (at 19 deg C). time to minimal prey distance (MPD) is in units of TTPG cycles

Appendix B. Parameter estimates.

Parameter estimates

Supplementary methods, ESM figures S1-S3 and ESM tables S1-S7 from Hydrodynamic regime determines the feeding success of larval fish through the modulation of strike kinematics

Supplementary methods, ESM figures S1-S3 and ESM tables S1-S

Supplement 1. The WinBUGS code.

<h2>File List</h2><blockquote> <p><a href="Lessepsian_WinBUGS.txt">Lessepsian_WinBUGS.txt</a> -- WinBUGS code </p> </blockquote><h2>Description</h2><blockquote> <p>The file "Lessepsian_WinBUGS.txt" contains the code for fitting the Bayesian model. To execute the code, the text must be pasted into a document window in WinBugs. To insert one's own data, replace the original data with the new data, which must include the number of sampling intervals (<i>T</i>), two vectors containing the number of new endemic and introduced species recorded at time <i>t</i> (new_species and new_species_L, respectively) and two vectors containing the cumulative number of endemic and introduced species recorded at time <i>t</i> (SM1 and SR1, respectively). It will probably be necessary to change the values of the initials before the model can run on a different data set. To construct a full model that allows for a linear monotonic trend in <i>u</i> through time, simply remove the # sing from the parameter "<i>beta1</i>" and replace the # signs between the two versions of logit(u[1]) and logit(u[i]). Note, that under the full model it is invalid to estimate <i>z</i>.</p> <p><em>Note</em>: WinBUGS parameterizes the normal distribution in terms of the precision parameter "<i>tau</i>" which is the reciprocal of the variance parameter.</p> </blockquote

Appendix A. The SC model.

The SC model