BUSCADOR RECOLECTA

STM-ncAFM from IMDEA Nanociencia Institute and CATRIN under ultra-high vacuum conditions at 4K, acquired between 2018 and 03.2023, *.txt *.jpg *.docx files, *.WSxM files can be opened with Origin

Esta base de datos contiene resultados de dos experimentos (RADxTEMP y RADxNIT) a escala de microcosmos referentes a variables de crecimiento, morfológicas, metabólicas y de composición estequiométrica de 2 especies de macroalgas de agua dulce, concretamente carófitos (Chara hispida y Chara vulgaris) procedentes de dos sistemas (el lago de Somolinos en Guadalajara y el Ullal de Quartons en Castellón), por tanto, 4 poblaciones (2 especies x 2 orígenes). En estos dos experimentos de diseño factorial, los individuos de las 4 poblaciones fueron sometidos a dos niveles de radiación, dos niveles de temperatura (RADxTEMP) y dos niveles de concentración de nitrato (RADxNIT). En esta matriz de datos, las filas son los individuos (réplicas) y las columnas son las diferentes variables medidas. La primera hoja de cálculo contiene todos los metadatos. La segunda y tercera hojas contienen los datos en bruto de las variables consideradas en el experimento (RADxTEMP y RADxNIT, respectivamente)., This data set contains results of two microcosm-scale experiments (RADxTEMP and RADxNIT) about variables related to growth, morphology, metabolism and stoichiometric composition of two species of freshwater macroalgae, in particular, charophytes (Chara hispida and C. vulgaris) from two systems (Somolinos Lake in Guadalajara and Quartons Spring in Castellón), thus, 4 populations (2 species x 2 origins). In these factorial-design experiments, individuals of the 4 populations were submitted to 2 levels of radiation, 2 levels of temperature (in RADxTEMP experiment) and 2 levels of nitrate concentration (in RADxNIT experiment). The first sheet contains all metadata. Second and third sheets contain raw data of the considered variables in the experiment (RADxTEMP and RADxNIT, respectively).

Climatic information recorded by the physician Francisco Fernández Navarrete in Granada (southern Spain) during the first third of the 18th century. Observations are included in the book “Cielo y suelo granadino” (Sky and soil in Granada), and consist of qualitative comments relating climatic conditions to illness and diseases from 1706 to 1730, as well as instrumental observations (using an “English barometer” and a “Florentine thermometer”) from December 1728 to February 1730.

New meteorological data from southern Spain corresponding to the period 1785-1830. Data sources are early newspapers and medical studies interested in the influence of environment conditions on health and illness. Data correspond to five cities in the area (Cádiz, Sevilla, Málaga, Granada, and Cartagena). Around 19.000 new meteorological observations (temperature, pressure, number of rainy days, wind direction, and qualitative statements on rainfall, wind force, cloudiness, fog, and storms) are recorded.

This repository contains datasets and scripts for timbre classification experiments conducted as part the Ph.D. thesis. Two datasets were used. The first one concentrates on drum/percussion sounds while the other generalises to orchestral sounds. See the relevant iPython notebooks to re-run experiments. The orchestral sample is quite large, there is a script that pulls N number samples randomly in the folder, for performing smaller analyses. Each episode directory contains word-level and segment-level information of the whole episode and also parallel samples extracted under segments_eng and segments_spa subdirectories. Each sample is stored as an WAV audio file, text file and a CSV file containing word timing information and word-level paralinguistic and prosodic features.

FlaBase (Flamenco Knowledge Base) is the acronym of a new knowledge base of flamenco music. Its ultimate aim is to gather all available online editorial, biographical and musicological information related to flamenco music. A first version is just being released. Its content is the result of the curation and extraction processes. FlaBase is stored in JSON format, and it is freely available for download. This first release of FlaBase contains information about 1,102 artists, 74 palos (flamenco genres), 2,860 albums, 13,311 tracks, and 771 Andalusian locations. Data was compiled and curated from different sources: Wikipedia, DBpedia, Andalucia.org, elartedevivirelflamenco.com, MusicBrainz, flun.cica.es/index.php/grabaciones/base-datos-grabaciones and juntadeandalucia.es/institutodeestadisticaycartografia/sima

This data-set contains high resolution GPS records from a single day home-to-school pedestrian mobility of 10 schools in the Barcelona Metropolitan Area (Spain). The experiment for data acquisition took place in November 2018. The data-set provides pedestrian mobility from an age-homogeneous group of people and is particularly valuable to bring insights in an urban microscopic level and can characterize micro-mobility patterns and pedestrians’ micro-motives. The study shares processed records with specific filtering, cleaning, and interpolation procedures (83 individual journeys and 41,053 GPS records) that can facilitate and accelerate data usage. Citizen science practices were employed during the whole research process (co-design, crowd-sourced protocols for the experiment, collective data interpretation and policy recommendations).

The HuGCDN2014 database was provided by the sleep unit of the Dr. Negrín University Hospital (Canary Islands, Spain). It is made up of 77 single-lead ECG recordings, digitized at 200 Hz. The labeling process was performed by an expert based on the simultaneous polysomnography, indicating the presence or absence of apnea in each minute. The database is divided into two groups: 1º) CONTROL: Forty healthy subjects with an AHI lower than 5 (30 men and 10 women). 2º) APNEA: Thirty-seven OSA patients with an AHI higher than 25 (30 men and 7 women). The learning set (L) consists of the first 20 recordings of control subjects and the first 18 OSA patients. The rest belong to the test set (T). The single-lead ECG signal is divided into 5-minute frames, that are shifted in time in increments of 1 minute. The scoring for each segment is assigned to the minute located in the middle position. The RR interval series is constructed as a sequence of time differences between the successive heartbeats.

Dades associades a l' article publicat: Cefalì,M.E., Ballesteros, E., Riera, J.L., Chappuis, E., Terradas, M., Mariani, S., i Cebrian, E. (2018). The optimal sampling design for littoral habitats modelling: a case study from the north-western Mediterranean. PLoS ONE, vol. 13, núm. 5, p. e0197234. Disponible a https://doi.org/10.1371/journal.pone.0197234, Spatial distribution of six coastal habitats of red algae on the Catalan coast, significantly influenced by environmental variables. The red algae mentioned in the database are: Rissoella verruculosa, Lithophyllum byssoides /Lithophyllum byssoides rims ("Trottoir"), Neogoniolithon brassica-florida, Hildenbrandia rubra /Phymatolithon lenormandi and Cystoseira mediterranea. Data on littoral habitat distribution and environmental variables were collected along the whole coast of Catalonia (North-Western Mediterranean between 3º 10' 28.072" E, 42º 26' 17.619" N and 0º 30' 57.001" E, 40º 31' 26.302" N), The file called 'Full data base' contains for each point, the projected coordinates, the environmental variables and the presence/absence (1/0) of each habitat. Slope code: 1 = 0º-10.8º; 2 = 10.8º-22.8º; 3 = 22.8º-45.1º; 4 = 45.1º-68.2º; 5 = 68.2º-87.8º. Habitats code: Riv = Rissoella verruculosa; Lby = Lithophyllum byssoides; Tro = Lithophyllum byssoides rims ("Trottoir”); Neo = Neogoniolithon brassica-florida; Hph = Hildenbrandia rubra/ Phymatolithon lenormandi.\nTables A-F contain results of logistic regression models. Results of logistic regression models for all sampling strategy designs are presented for each habitat and for all sample sizes. For training data, the number (N) and frequency (F) of the habitat occurrence are presented. Results of null models are shown with the mead and standard deviation of the 10 models calculated. The D2 is the Deviance of the model in the training data; AUC is the area under the receiver operating characteristic (ROC) curve, se and spe are the sensitivity and specificity respectively, for the predictive model in the test data