BUSCADOR RECOLECTA

“ACCIDENTAL CUT SS22” enfatiza los orígenes del método de patronaje experimental Accidental Cutting, propiedad intelectual de Eva Iszoro, que se basa el proceso creativo en cortes y patrones accidentales, abstractos y aleatorios a través de los cuales se pueden construir volúmenes únicos y desconocidos, inexistentes hasta ahora. Este enfoque representa la identidad distintiva de la marca. No sólo se exploran nuevas formas de construcción volumétrica, sino en general el propio concepto de corte accidental, estableciendo un paralelismo entre cualquier tipo de incisiones, incluidas las que provocan heridas y los cortes con patrones abstractos. Al mismo tiempo, esto hace referencia directa y refuerza la imagen y el nombre de la marca. La construcción virtual puede considerarse como un enfoque sostenible, renunciando a la construcción física en el prototipado, desfiles de moda e incluso presentación comercial del producto. Por otro lado, se explora la virtualidad como medio de creación y comunicación de realidades impensables en el mundo físico, escapando de la gravedad y abriendo posibilidades de filmación sin recurrir a medios extravagantes y costosos propios del mundo real. En este sentido, la moda se convierte en arte, un volumen escultórico virtual en movimiento., “ACCIDENTAL CUT” es una colección de moda virtual, para la primavera verano 2022, presentada en la Semana de la Moda de Londres (London Fashion Week), que explora el proceso creativo del método de patronaje experimental Accidental Cuttting, propiedad intelectual de Eva Iszoro, al igual que la marca de moda del mismo nombre. Esta película fue nominada a premio en el Festival de Cine de Moda de Berlín en la categoría de Animaciones Digitales 2D y 3D. La música fue compuesta por Johnny Paradiso. https://accidentalcutting.com/accidental-cut-ss-22_virtual-fashion-animation/ https://youtu.be/I8WEnDd3kFw?si=ZeTFGbGBQBcuNFSW

Lava dating by means of Ar / Ar radiometric analysis performed by the University of Oregon de La Esfinge y Tamaraceite (Gran Canaria, Canary Islands)

Lava dating by means of Ar / Ar radiometric analysis performed by the University of Oregon de las Salinas de Janubio (Lanzarote, Canary Islands).

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.

Data set of morbidity items from Canary Health Survey, 1997

Data set of morbidity items form Canary Health Survey, 2004

Data set of morbidity items from Canary Health Survey, 2009

List of diocesan architects in Spain, between 1876-1955, Relació d'arquitectes diocesans a Espanya, entre 1876-1955

Dades associades amb el material complementari (gràfics, taules, figures, ...) de l'article publicat a la revista 'ACS Catalysis', 2021, vol. 11, núm. 12, p.7327-7338. Disponible a https://doi.org/10.1021/acscatal.1c00847, Strategies for primer design, sequences of the utilized UPOs, kinetic plots, GC parameters and original GC chromatograms, activities and selectivities of all tested variants, reaction conditions, calibration curves, and figures of docking studies and MD simulations

Dades relacionades amb l'article "Use of Twitter to share news in higher education: the risk of magnification of engagement and learning", enviat a la revista 'The Internet and Higher Education' d'Elsevier, Data on tweets, tweet counts and tweet interaction counts were downloaded from https://twitter.com and https://analytics.twitter.com/user/GeoHumana_UV/home. Data on student performance and self-assessment were provided by participants during the development of the subject 34956 Human Geography in the year 2020-2021 at the University of Valencia, Datasheets are provided as Open Document Format for Office Applications (ODF), extended from xml, with .ods extension. The most common office packages, such as Libreoffice, can open the format, The dataset contains two data sheets, summarizing the results of a class activity involving the use of Twitter to share information and to learn. Table S1 is a summary of the tweets produced by user GeoHumana_UV (teacher/subject account) between 2020-09-16 and 2020-12-15, plus interactions recorded for each tweet (including number of impressions, URL clicks, likes, retweets and replies). All data provided by Twitter Analytics. Table S2 is a summary of student activity related to the class activity for the same period of time. It includes anonymized data on tweeting activity, level of interaction, performance and self-assessment by each participating student. Data provided by Twitter Analytics and the participants