The graphic language of Eduardo Chillida as a conceptual contribution to the typographic identity of the University of the Basque Country, UPV/EHU

Este proyecto de investigación financiado por la Universidad del País Vasco/Euskal Herriko Unibertsitatea —UPV/EHU-PES 11/31—, a través de su programa de investigación estratégica, tiene como objetivo la creación de la tipografía de identidad visual corporativa de la Universidad del País Vasco —UPV/EHU—, cuyo inicio conceptual para dotar de unas características de identidad visual corporativa a la UPV/EHU, ha sido planteado desde las especulaciones estéticas sobre la forma, materializadas por Eduardo Chillida. En la producción gráfica de este artista encontramos una sutil coincidencia con principios vitales para la creación tipográfica, en cuanto al planteamiento de formas dinámicas y constructivas, en las que el rigor geométrico es vencido por una suerte de organicidad que parte del núcleo mismo de la estructura —«cursus»—, por: la fuerza vital que imprime la acción modulada del gesto —«ductus»—; por la dialéctica entre lo lleno y lo vacío —forma/contraforma—, por el impulso y la espontaneidad — carácter—, o por la afirmación de un lenguaje plástico en la cultura diferenciada del medio en el que se vive —identidad—.This research project funded by the Universidad del País Vasco/Euskal Herriko Unibertsitatea, UPV/EHU-PES 11/31, is intended as part of its strategic research programme. This project is intended to create a typographic corporate visual identity for the University of The Basque Country, UPV/EHU. The conceptual starting-point is the need to provide the UPV/EHU with a set of corporate visual identity characteristics using a meaningful font style, and the approach has been provided by Eduardo Chillida’s aesthetic reflections on the nature of form. Chillida’s graphic production shows a subtle coincidence with vital principles for typographic creation, in terms of the approach to dynamic and constructive forms, in which geometric rigour is overcome by a kind of organic-ness that arises from the very heart of the structure—“cursus”; by a vital force that imprints the modulated action of the gesture—“ductus”; by the dialectic between what is full and what is empty—form/counter-form; by impulse and spontaneity—character; and by the affirmation of a visual language in the particular culture of the medium in which one is living—identity.Universidad del País Vasco/Euskal Herriko Unibertsitatea —UPV/EHU-PES 11/31—, a través de su programa de investigación estratégica

Evaluating the feasibility of cognitive impairment detection in Alzheimer’s disease screening using a computerized visual dynamic test

Background Alzheimer’s disease (AD) is a neurodegenerative disease without known cure. However, early medical treatment can help control its progression and postpone intellectual decay. Since AD is preceded by a period of cognitive deterioration, the effective assessment of cognitive capabilities is crucial to develop reliable screening procedures. For this purpose, cognitive tests are extensively used to evaluate cognitive areas such as language, attention, or memory. Methods In this work, we analyzed the potential of a visual dynamics evaluation, the rapid serial visual presentation task (RSVP), for the detection of cognitive impairment in AD. We compared this evaluation with two of the most extended brief cognitive tests applied in Spain: the Clock-drawing test (CDT) and the Phototest. For this purpose, we assessed a group of patients (mild AD and mild cognitive impairment) and controls, and we evaluated the ability of the three tests for the discrimination of the two groups. Results The preliminary results obtained suggest the RSVP performance is statistically higher for the controls than for the patients (p-value = 0.013). Furthermore, we obtained promising classification results for this test (mean accuracy of 0.91 with 95% confidence interval 0.72, 0.97). Conclusions Since the RSVP is a computerized, auto-scored, and potentially self-administered brief test, it could contribute to speeding-up cognitive impairment screening and to reducing the associated costs. Furthermore, this evaluation could be combined with other tests to augment the efficiency of cognitive impairment screening protocols and to potentially monitor patients under medical treatment.FEDER/Junta de Andalucía-Council for Economic Transformation, Industry, Knowledge and Universities/ grant (B-TIC-352- UGR20); grant PID2021-128529OA-I00, MCIN / AEI / 10.13039 / 501100011033ERDF A way of making Europe; grant PROYEXCEL_00084, Projects for Excellence Research,Council for Economic Transformation,Industry, Knowledge and Universities, Junta de Andalucía 2021Circuits And Systems for Information Processing (CASIP) research group, TIC-117 (PAIDI Junta de Andalucia)PGC2018-098813-B-C31 and PGC2018-098813-B-C32 (Spanish Ministry of Science, Innovation and Universities

Virtual Reality as a Portable Alternative to Chromotherapy Rooms for Stress Relief: A Preliminary Study

Chromotherapy rooms are comfortable spaces, used in places like special needs schools, where stimuli are carefully selected to cope with stress. However, these rooms are expensive and require a space that cannot be reutilized. In this article, we propose the use of virtual reality (VR) as an inexpensive and portable alternative to chromotherapy rooms for stress relief. We recreated a chromotherapy room stress relief program using a commercial head mounted display (HD). We assessed the stress level of two groups (test and control) through an EEG biomarker, the relative gamma, while they experienced a relaxation session. First, participants were stressed using the Montreal imaging stress task (MIST). Then, for relaxing, the control group utilized a chromotherapy room while the test group used virtual reality. We performed a hypothesis test to compare the selfperceived stress level at di erent stages of the experiment and it yielded no significant di erences in reducing stress for both groups, during relaxing (p-value: 0.8379, = 0.05) or any other block. Furthermore, according to participant surveys, the use of virtual reality was deemed immersive, comfortable and pleasant (3.9 out of 5). Our preliminary results validate our approach as an inexpensive and portable alternative to chromotherapy rooms for stress relief.Spanish Ministry of Science, Innovation and Universities PGC2018-098813-B-C31 TIN2016-75097-PEuropean Union (EU) PGC2018-098813-B-C31Nicolo Association for the R&D in Neurotechnologies for disabilit

Virtual Reality Customized 360-Degree Experiences for Stress Relief

The latest studies in virtual reality (VR) have evidenced the potential of this technology to reproduce environments from multiple domains in an immersive way. For instance, in stress relief research, VR has been presented as a portable and inexpensive alternative to chromotherapy rooms, which require an adapted space and are expensive. In this work, we propose a portable and versatile alternative to the traditional chromotherapy color-loop treatment through four different 360-degree virtual experiences. A group of 23 healthy participants (mean age 22.65 ± 5.48) were conducted through a single-session experience divided into four phases while their electroencephalography (EEG) was recorded. First, they were stressed via the Montreal imaging stress task (MIST), and then relaxed using our VR proposal. We applied the Wilcoxon test to evaluate the relaxation effect in terms of the EEG relative gamma and self-perceived stress surveys. The results that we obtained validate the effectiveness of our 360-degree proposal to significantly reduce stress (p-value = 0.0001). Furthermore, the participants deemed our proposal comfortable and immersive (score above 3.5 out of 5). These results suggest that 360-degree VR experiences can mitigate stress, reduce costs, and bring stress relief assistance closer to the general public, like in workplaces or homes

A self-driven approach for multi-class discrimination in Alzheimer’s disease based on wearable EEG

Early detection is critical to control Alzheimer’s disease (AD) progression and postpone cognitive decline. Traditional medical procedures such as magnetic resonance imaging are costly, involve long waiting lists, and require complex analysis. Alternatively, for the past years, researchers have successfully evaluated AD detection approaches based on machine learning and electroencephalography (EEG). Nonetheless, these approaches frequently rely upon manual processing or involve non-portable EEG hardware. These aspects are suboptimal regarding automated diagnosis, since they require additional personnel and hinder porta- bility. In this work, we report the preliminary evaluation of a self-driven AD multi-class discrimination approach based on a commercial EEG acquisition system using sixteen channels. For this purpose, we recorded the EEG of three groups of participants: mild AD, mild cognitive impairment (MCI) non-AD, and controls, and we implemented a self-driven analysis pipeline to discriminate the three groups. First, we applied automated artifact rejection algorithms to the EEG recordings. Then, we extracted power, entropy, and complexity features from the preprocessed epochs. Finally, we evaluated a multi-class classification problem using a multi-layer perceptron through leave-one-subject-out cross-validation. The preliminary results that we obtained are comparable to the best in literature (0.88 F1-score), what suggests that AD can potentially be detected through a self-driven approach based on commercial EEG and machine learn- ing. We believe this work and further research could contribute to opening the door for the detection of AD in a single consultation session, therefore reducing the costs associated to AD screening and poten- tially advancing medical treatment.Spanish Government PGC2018-098813-B-C31European Commission Operative Program FEDER 2014-2020 BTIC-352-UGR20Economy, Universities and Science Office of the Andalusian Regional GovernmentUniversidad de Granada/CBU

Proteoma de la saliva de Ornithodoros moubata: comparativa entre machos y hembras

Comunicaciones a congreso

An Automated Approach for the Detection of Alzheimer’s Disease From Resting State Electroencephalography

Early detection is crucial to control the progression of Alzheimer’s disease and to postpone intellectual decline. Most current detection techniques are costly, inaccessible, or invasive. Furthermore, they require laborious analysis, what delays the start of medical treatment. To overcome this, researchers have recently investigated AD detection based on electroencephalography, a non-invasive neurophysiology technique, and machine learning algorithms. However, these approaches typically rely on manual procedures such as visual inspection, that requires additional personnel for the analysis, or on cumbersome EEG acquisition systems. In this paper, we performed a preliminary evaluation of a fully-automated approach for AD detection based on a commercial EEG acquisition system and an automated classification pipeline. For this purpose, we recorded the resting state brain activity of 26 participants from three groups: mild AD, mild cognitive impairment (MCI-non-AD), and healthy controls. First, we applied automated data-driven algorithms to reject EEG artifacts. Then, we obtained spectral, complexity, and entropy features from the preprocessed EEG segments. Finally, we assessed two binary classification problems: mild AD vs. controls, and MCI-non-AD vs. controls, through leave-one-subject-out cross-validation. The preliminary results that we obtained are comparable to the best reported in literature, what suggests that AD detection could be automatically detected through automated processing and commercial EEG systems. This is promising, since it may potentially contribute to reducing costs related to AD screening, and to shortening detection times, what may help to advance medical treatment.PID2021-128529OA-I00 Spanish Ministry of Science, Innovation and UniversitiesEuropean Regional Development FundsBTIC- 352-UGR20Operative Program FEDER 2014–2020Economy, Universities and Science Office of the Andalusian Regional Governmen

Immunohistochemical distribution of secretagogin in the mouse brain

Introduction: Calcium is essential for the correct functioning of the central nervous system, and calcium-binding proteins help to finely regulate its concentration. Whereas some calcium-binding proteins such as calmodulin are ubiquitous and are present in many cell types, others such as calbindin, calretinin, and parvalbumin are expressed in specific neuronal populations. Secretagogin belongs to this latter group and its distribution throughout the brain is only partially known. In the present work, the distribution of secretagogin-immunopositive cells was studied in the entire brain of healthy adult mice. Methods: Adult male C57BL/DBA mice aged between 5 and 7 months were used. Their whole brain was sectioned and used for immunohistochemistry. Specific neural populations were observed in different zones and nuclei identified according to Paxinos mouse brain atlas. Results: Labelled cells were found with a Golgi-like staining, allowing an excellent characterization of their dendritic and axonal arborizations. Many secretagogin-positive cells were observed along different encephalic regions, especially in the olfactory bulb, basal ganglia, and hypothalamus. Immunostained populations were very heterogenous in both size and distribution, as some nuclei presented labelling in their entire extension, but in others, only scattered cells were present. Discussion: Secretagogin can provide a more complete vision of calcium-buffering mechanisms in the brain, and can be a useful neuronal marker in different brain areas for specific populations.This work was supported by the Ministry of Economy, Industry and Competitiveness (MINECO) (SAF2016-79668- R to EW), the Ministry of Science and Innovation (PID2019- 106943RB-I00 to EW), the Ministry of Universities (MIU) (FPU20/03457 to PT), the Regional Government of Castile and Leon (SA178U13 to EW; EDU/556/2019 to LP-R), the Centre for Regenerative Medicine and Cell Therapy of Castile and Leon (EW), and the University of Salamanca (EW)

Simulation of atmospheric microbursts using a numerical mesoscale model at high spatiotemporal resolution

Atmospheric microbursts are low‐level meteorological events that can produce significant damage on the surface and pose a major risk to aircraft flying close to the ground. Studies and ad hoc numerical models have been developed to understand the origin and dynamics of the microburst; nevertheless, there are few researches of the phenomenon using global and mesoscale models. This is mainly due to the limitations in resolution, as microbursts normally span for less than 4 km and 20 min. In this paper, the Weather esearch and Forecasting model is used at resolutions of 400 m and 3 min to test if it can properly capture the variables and dynamics of high‐reflectivity microbursts. Several microphysics and planetary boundary layer parametrizations are tested to find the best model configuration for the simulation of this kind of episodes. General conditions are evaluated by using thermodynamic diagrams. Surface and vertical wind speed, reflectivity, precipitation, and other variables for each simulated event are compared with observations, and the model's sensitivity to the variables is assessed. The dynamics and evolution of the microburst is evaluated using different plots of a chosen event. The results show that the model is able to reproduce high‐reflectivity microbursts in accordance with observations, although there is a tendency to underestimate the intensity of variables, most markedly on the wind vertical velocity. Regarding the microphysics schemes, the Morrison parametrization performs better than the WRF single‐moment 6‐class scheme. No major differences are found between the Mellor‐Yamada‐Janjic and the Mellor‐Yamada‐Nakanishi‐Niino planetary boundary layer parametrizations.This work is supported by the Interdisciplinary Mathematics Institute of the Complutense University of Madrid and the following research projects: METEORISK (RTC‐2014‐1872‐5), PCIN‐2014‐013‐C07‐04, PCIN‐2016‐080 (UE ERANET Plus NEWA Project), ESP2013‐47816‐C4‐4‐P, CGL2010‐15930, CGL2016‐81828‐REDT, FEI‐EU‐17‐16, and SAFEFLIGHT GL2016‐78702‐C2‐1‐R and CGL2016‐78702‐C2‐2‐R). This research is founded by the Spanish Ministry of Economy and Enterprise under the framework of the SAFEFLIGHT research project (CGL2016‐78702‐C2‐1‐R and CGL2016‐78702‐C2‐2‐R)

Estimating Stand and Fire-Related Surface and Canopy Fuel Variables in Pine Stands Using Low-Density Airborne and Single-Scan Terrestrial Laser Scanning Data

In this study, we used data from a thinning trial conducted on 34 different sites and 102 sample plots established in pure and even-aged Pinus radiata and Pinus pinaster stands, to test the potential use of low-density airborne laser scanning (ALS) metrics and terrestrial laser scanning (TLS) metrics to provide accurate estimates of variables related to surface and canopy fires. An exhaustive field inventory was carried out in each plot to estimate the main stand variables and the main variables related to fire hazard: surface fuel loads by layers, fuel strata gap, surface fuel height, stand mean height, canopy base height, canopy fuel load and canopy bulk density. In addition, the point clouds from low-density ALS and single-scan TLS of each sample plot were used to calculate metrics related to the vertical and horizontal distribution of forest fuels. The comparative performance of the following three non-parametric machine learning techniques used to estimate the main stand- and fire-related variables from those metrics was evaluated: (i) multivariate adaptive regression splines (MARS), (ii) support vector machine (SVM), and (iii) random forest (RF). The selection of the best modeling approach was based on a comparison of the root mean square error (RMSE), obtained by optimizing the parameters of each technique and performing cross-validation. Overall, the best results were obtained with the MARS techniques for data from both sensors. The TLS data provided the best results for variables associated with the internal characteristics of canopy structure and understory fuel but were less reliable for estimating variables associated with the upper canopy, due to occlusion by mid-canopy foliage. The combination of ALS and TLS metrics improved the accuracy of estimates for all variables analyzed, except the height and the biomass of the understory shrubs. The variability demonstrated by the combined use of both types of metrics ranged from 43.11% for the biomass of duff litter layers to 94.25% for dominant height. The results suggest that the combination of machine learning techniques and metrics derived from low-density ALS data, drawn from a single-scan TLS or a combination of both metrics, may represent a promising alternative to traditional field inventories for obtaining valuable information about surface and canopy fuel variables at large scalesinfo:eu-repo/semantics/publishedVersio