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Twitter dataset for a research on the 2015 Spanish General Election. The tweets were obtained through the Twitter API's Search function since November 2 to December 21, 2015. Three criteria for filtering tweets were established: two general terms linked to the elections ("#20D", "20-D"); the name and usernames of the four main parties (PP, PSOE, Podemos and Ciudadanos), and the name and usernames of the four candidates from those parties. The research assessed the tweet's issue according to Patterson (1980)'s typology for evaluating political mediatisation. The dataset contains three files: the unlabelled collection of the 15.8 million tweet ids obtained through the API, the annotated sample of the 3,117 tweet ids for assessing the issue via machine learning, and the readme.txt file. It is recommended to open the file from a text editor or through a script. The id_str must be handled as a string. If the file is open from Excel, the id_str will be interpreted as a number, and then converted into a float, losing information in this transformation

Social media platforms have had a significant impact on the public image of sports in recent years. Through the relational dynamics of the communication on these networks, many users have emerged whose opinions can exert a great deal of influence on public conversation online. This research aims to identify the influential Twitter users during the 2016 UCI Track Cycling World Championships using different variables which, in turn, represent different dimensions of influence (popularity, activity and authority). Mathematical variables of the social network analysis and variables provided by Twitter and Google are compared. As a result, no single variable assessed is sufficient to identify the different kinds of influential Twitter users. Having a certain type of account is not enough to make a user an influencer if they do not engage (actively or passively) in the conversation. Choosing some influencers or others will depend on the objectives pursued.

Here you will find a model of the cooling system of a PEMFC-based micro-CHP system. This model is implemented in Matlab/Simulink, version 9.3.0.713579 (R2017b). The model and the tests conducted for its development are described in detail in the following paper: Title: Control-Oriented Modeling of the Cooling Process of a PEMFC-Based micro-CHP System Authors: SANTIAGO NAVARRO GIMÉNEZ, JUAN MANUEL HERRERO DURÁ, FRANCESC XAVIER BLASCO FERRAGUD and RAÚL SIMARRO FERNÁNDEZ. Instituto Universitario de Automática e Informática Industrial Universidad Politécnica de Valencia In this folder (uCHP_Cooling_System), you will find the following files: Complete_Model_M.slx Complete_Model_V.slx Filter.m Modeling_Test.mat Parameters.mat S_Complete_Model_M.m S_Complete_Model_V.m Validation_Test.mat In both Complete_Model_M.slx and Complete_Model_V.slx you will find the implementation of the complete model in Simulink. The only difference between them is that the former is prepared for the data set from the modeling test (Modeling_Test.mat) and the latter for the data set from the modeling test (Validation_Test.mat). In order to launch the simulations, you have to run the scripts S_Complete_Model_M.m and S_Complete_Model_V.m, respectively. The file Parameters.mat contain the values of the parameters of the model. The file Filter.m is just a filter, which is used in both scripts. Please, read the comments in the scripts mentioned for more information. Thanks.

Computational 3D models of human atria and torso with encoded anatomical and functional heterogeneity. The finite element model of the atria is a multi-layer mesh with a homogeneous wall thickness between 600 and 900 μm (754.893 nodes and 515.010 elements), built with linear hexahedral elements and with regular spatial resolution of 300 µm. The model consists of: 21 regions with 53 sub-divisions representing the detailed description of fibre orientation; electrophysiological heterogeneity represented by 8 cellular models with differences in the action potential properties; and conduction velocities and anisotropy ratios tuned to each atrial region. The torso was modelled using a dataset obtained from the online open repository at the Centre for Integrative Biomedical Computing (CBIC) from University of Utah. The torso model has 190.804 nodes and 1.149.531 tetrahedral elements with a spatial resolution of 0.6 mm. It has 6 different regions: lungs, bones, liver, ventricle, blood pools, and flesh.

Se incluye una muestra de 60 rankings globales de universidades, categorizados en función de una taxonomía propuesta. Estos contenidos constituyen los datos utilizados en un capítuo de libro de futura publicación.

The sponsored content on social networks has raised new questions and research objectives, including discussions regarding the budget invested in these sites by political parties, as well as the new central role that technology corporations play in electoral contexts. This dataset comprises 10,485 Facebook Ad corpus obtained from the Facebook Ad Library through a web crawler developed in Pyhton. The dataset elements correspond to the Facebook Ads paid by the main national political parties during the two 2019 Spanish General Elections precampaign and campaign. The parties are the following: Partido Socialista Obrero Español (PSOE), Partido Popular (PP), Ciudadanos, Unidas Podemos (coalition of Podemos and Izquierda Unida) and Vox. The General Elections were held on April 28 and November 10., We would like to thank Exponentia CIO Juan Besari for providing the appropriate hardware to carry out the Facebook Ad extraction processes.

Novel standardised data model for collaborative manufacturing environments (CMData), building a taxonomy of data concepts to represent information related to the replenishment, production and delivery planning domains, The authors would like to acknowledge the support of the researchers participating in the collaborative projects “Cloud Collaborative Manufacturing Network” (C2NET) (www.c2net-project.eu) and “Zero Defects Manufacturing Platform” (ZDMP) (www.zdmp.eu).

The dataset contains the input data that has been entered into the mathematical model to develop the case study. The data is provided by the company and the values have been structured according to the indices defined in the model. Input data details have been added to make the model replicable.

Mesures del camp de velocitat del vent (3 components), temperatura sònica i de l'aire a alta freqüència (8-10 Hz) separades per fitxers en base temporal cada 30 min.

Dataset of Tie and Tag: A Study of Tie Strength and Tags for Photo Sharing