Macroecology and ecoinformatics: evaluating the accuracy of the ecological niche models calibrated with species occurrence data with biases and/or errors

Hoy en día es común estudiar los patrones globales de biodiversidad a partir de las predicciones generadas por diferentes modelos de nicho ecológico. Habitualmente, estos modelos se calibran con datos procedentes de bases de datos de libre acceso (e.g. GBIF). Sin embargo, a pesar de la facilidad de descarga y de la accesibilidad de los datos, la información almacenada sobre las localidades donde están presentes las especies suele tener sesgos y errores. Estos problemas en los datos de calibración pueden modificar drásticamente las predicciones de los modelos y con ello pueden enmascarar los patrones macroecológicos reales. El objetivo de este trabajo es investigar qué métodos producen resultados más precisos cuando los datos de calibración incluyen sesgos y cuáles producen mejores resultados cuando los datos de calibración tienen, además de sesgos, errores. Para ello creado una especie virtual, hemos proyectado su distribución en la península ibérica, hemos muestreado su distribución de manera sesgada y hemos calibrado dos tipos de modelos de distribución (Bioclim y Maxent) con muestras de distintos tamaños. Nuestros resultados indican que cuando los datos sólo están sesgados, los resultados de Bioclim son mejores que los de Maxent. Sin embargo, Bioclim es extremadamente sensible a la presencia de errores en los datos de calibración. En estas situaciones, el comportamiento de Maxent es mucho más robusto y las predicciones que proporciona son más ajustadas.In spite of the biases and errors of the open access biodiversity databases we need to take advantage of the occurrences stored in those databases for analyzing the global patterns of biodiversity. Here, we aimed to test which modelling method produces better predictions when calibrated with data samples that have biases and errors. We tested two different methods, a complex one, Maxent, and a simple one, Bioclim. We created a virtual species, sampled its distribution with both, bias and errors, and calibrated the models with those samples. Results indicated that Bioclim produces better predictions than Maxent when calibrated with biased data sets. Bioclim did not overestimate the species’ range and it was able to produce accurate predictions even when calibrated with small and biased data samples (25-50 points). However, when wrong occurrences were included in the calibration samples, Bioclim over-predicted the species’ range. Our experiments indicated that in that case, Maxent predictions remained robust and provided accurate maps. Thus, if the calibration data samples have just biases, Bioclim provided better maps than Maxent. However, when samples have both, biases and wrong occurrences, Maxent model provided better results than Bioclim.Este trabajo se enmarca dentro de los proyectos: “Support of establishment, development and mobility of quality research teams at the Charles University” CZ.1.07/2.3.00/30.0022, financiado por la European Science Foundation y la República Checa (S.Varela); y “Potential effects of climate change on Natura 2000 conservation targets in Castilla-La Mancha (CLICHE)” (Ref. no.: POIC10-0311-0585), financiado por el gobierno de Castilla La-Mancha, España (S. Varela, R. G. Mateos, R. García-Valdés, and F. Fernández-González)

Head-mounted display-based application for cognitive training

Virtual Reality (VR) has had significant advances in rehabilitation, due to the gamification of cognitive activities that facilitate treatment. On the other hand, Immersive Virtual Reality (IVR) produces outstanding results due to the interactive features with the user. This work introduces a VR application for memory rehabilitation by walking through a maze and using the Oculus Go head-mounted display (HMD) technology. The mechanics of the game require memorizing geometric shapes while the player progresses in two modes, autonomous or manual, with two levels of difficulty depending on the number of elements to remember. The application is developed in the Unity 3D video game engine considering the optimization of computational resources to improve the performance in the processing and maintaining adequate benefits for the user, while the generated data is stored and sent to a remote server. The maze task was assessed with 29 subjects in a controlled environment. The obtained results show a significant correlation between participants’ response accuracy in both the maze task and a face–pair test. Thus, the proposed task is able to perform memory assessments

Fog computing for assisting and tracking elder patients with neurodegenerative diseases

U.S. hospitals transmit and manage great amounts of information with the avenue of Internet of things. This work departs from a real need detected by healthcare centers and hospitals in U.S., Spain and Ecuador. This work focuses on the application of fog computing for obtaining an app rich in visual content that will not overload U.S. hospital infrastructures even if it was used massively. The simulation results showed that the proposed fog-based approach could support a regular use (one day out of three on average) by 1% of patients of one of the most common neurodegenerative diseases in 14 states in U.S (i.e. 36, 400 patients in total) with only a traffic of 528 KB per day on average when using one hospital per state

Extracting Hα\alpha flux from photometric data in the J-PLUS survey

We present the main steps that will be taken to extract H$\alpha$ emission flux from Javalambre Photometric Local Universe Survey (J-PLUS) photometric data. For galaxies with $z\lesssim0.015$, the H$\alpha$+[NII] emission is covered by the J-PLUS narrow-band filter $F660$. We explore three different methods to extract the H$\alpha$ + [NII] flux from J-PLUS photometric data: a combination of a broad-band and a narrow-band filter ($r'$ and $F660$), two broad-band and a narrow-band one ($r'$, $i'$ and $F660$), and a SED-fitting based method using 8 photometric points. To test these methodologies, we simulated J-PLUS data from a sample of 7511 SDSS spectra with measured H$\alpha$ flux. Based on the same sample, we derive two empirical relations to correct the derived H$\alpha$+[NII] flux from dust extinction and [NII] contamination. We find that the only unbiased method is the SED fitting based one. The combination of two filters underestimates the measurements of the H$\alpha$ + [NII] flux by a 28%, while the three filters method by a 9%. We study the error budget of the SED-fitting based method and find that, in addition to the photometric error, our measurements have a systematic uncertainty of a 4.3%. Several sources contribute to this uncertainty: differences between our measurement procedure and the one used to derive the spectroscopic values, the use of simple stellar populations as templates, and the intrinsic errors of the spectra, which were not taken into account. Apart from that, the empirical corrections for dust extinction and [NII] contamination add an extra uncertainty of 14%. Given the J-PLUS photometric system, the best methodology to extract H$\alpha$ + [NII] flux is the SED-fitting based one. Using this method, we are able to recover reliable H$\alpha$ fluxes for thousands of nearby galaxies in a robust and homogeneous way.Comment: 11 pages, 14 figures. Minor changes to match the published versio

A virtual reality-based cognitive telerehabilitation system for use in the covid-19 pandemic

The COVID-19 pandemic has changed people’s lives and the way in which certain services are provided. Such changes are not uncommon in healthcare services and they will have to adapt to the new situation by increasing the number of services remotely offered. Limited mobility has resulted in interruption of treatments that traditionally have been administered through face-to-face modalities, especially those related to cognitive impairments. In this telerehabilitation approach, both the patient and the specialist physician enter a virtual reality (VR) environment where they can interact in real time through avatars. A spaced retrieval (SR) task is implemented in the system to analyze cognitive performance. An experimental group (n = 20) performed the SR task in telerehabilitation mode, whereas a control group (n = 20) performed the SR task through a traditional face-to-face mode. The obtained results showed that it is possible to carry out cognitive rehabilitation processes through a telerehabilitation modality in conjunction with VR. The costeffectiveness of the system will also contribute to making healthcare systems more efficient, overcoming both geographical and temporal limitations

COPEPODS OR ROTIFERS? EVALUATING THE USE OF DIFFERENT FEEDING PROTOCOLS FOR LARVAE OF ATLANTIC BLUEFIN TUNA (Thunnus thynnus. L)

There are still many issues that require to be solved in larval rearing of Atlantic bluefin tuna (Thunnus thynnus; ABT) to prevent “mass-mortality” during this developmental stage. Initial data related to the feeding sequence of ABT larvae suggested that mortality observed during the first stages of life could be due partly to nutritional deficiencies. Previous studies demonstrated that copepods appeared to be a superior live prey compared to rotifers during the first two weeks of life. Our overarching aim was to evaluate different feeding strategies during first feeding of ABT larvae from a performance, compositional and molecular perspective. In order to do so, two groups of ABT larvae were fed with either copepod (Acartia tonsa; C) nauplii or rotifers (Brachionus rotundiformis; R) enriched with Algamac 3050® from mouth opening to 13 days after hatching (dah). After this, the group C-larvae was fed either Artemia enriched with Algamac 3050® (CA), Acartia nauplii and copepodites (CC) or sea bream (Sparus aurata) yolk-sac larvae (CY), while the R group passed on to being fed on Artermia enriched with Algamac 3050® (RA) up to 18 dah. After 13 dah, larvae fed C grew more than those fed R although there were no differences in survival. ABT larvae fed R accumulated highest eicosapentaenoate (EPA) but lowest docosahexaenoate (DHA) and total n-3 long-chain polyunsaturated fatty acids (LC-PUFA) than C-fed larvae, reflecting dietary contents. Indeed, there was no activation in the expression of the enzymes involved in LC-PUFA biosynthesis. However, the different live prey elicited regulation of transcription factor, digestive enzyme, lipid metabolism and oxidative stress genes. At 18 dah larvae fed CY and CA were the largest size with larvae fed RA displaying the lowest growth with no differences in survival among the dietary treatments. The highest DHA contents were found in ABT larvae fed CC and CY, whereas the lowest contents were found in RA-fed larvae. Indeed, RA-fed larvae showed the highest level of the intermediate product n-3 docosapentaenoate, which could be reflecting up-regulation in the biosynthetic pathway although this was not supported by gene expression data

Dietary Fat Patterns and Outcomes in Acute Pancreatitis in Spain

Background/Objective: Evidence from basic and clinical studies suggests that unsaturated fatty acids (UFAs) might be relevant mediators of the development of complications in acute pancreatitis (AP). Objective: The aim of this study was to analyze outcomes in patients with AP from regions in Spain with different patterns of dietary fat intake. Materials and Methods: A retrospective analysis was performed with data from 1,655 patients with AP from a Spanish prospective cohort study and regional nutritional data from a Spanish cross-sectional study. Nutritional data considered in the study concern the total lipid consumption, detailing total saturated fatty acids, UFAs and monounsaturated fatty acids (MUFAs) consumption derived from regional data and not from the patient prospective cohort. Two multivariable analysis models were used: (1) a model with the Charlson comorbidity index, sex, alcoholic etiology, and recurrent AP; (2) a model that included these variables plus obesity. Results: In multivariable analysis, patients from regions with high UFA intake had a significantly increased frequency of local complications, persistent organ failure (POF), mortality, and moderate-to-severe disease in the model without obesity and a higher frequency of POF in the model with obesity. Patients from regions with high MUFA intake had significantly more local complications and moderate-to-severe disease; this significance remained for moderate-to-severe disease when obesity was added to the model. Conclusions: Differences in dietary fat patterns could be associated with different outcomes in AP, and dietary fat patterns may be a pre-morbid factor that determines the severity of AP. UFAs, and particulary MUFAs, may influence the pathogenesis of the severity of AP

The GALANTE photometric survey of the northern Galactic plane: Project description and pipeline

The GALANTE optical photometric survey is observing the northern Galactic plane and some adjacent regions using seven narrow- and intermediate-filters, covering a total of 1618 square degrees. The survey has been designed with multiple exposure times and at least two different air masses per field to maximize its photometric dynamic range, comparable to that of Gaia, and ensure the accuracy of its photometric calibration. The goal is to reach at least 1% accuracy and precision in the seven bands for all stars brighter than AB magnitude 17 while detecting fainter stars with lower values of the signal-to-noise ratio.The main purposes of GALANTE are the identification and study of extinguished O+B+WR stars, the derivation of their extinction characteristics, and the cataloguing of F and G stars in the solar neighbourhood. Its data will be also used for a variety of other stellar studies and to generate a high-resolution continuum-free map of the H{\alpha} emission in the Galactic plane. We describe the techniques and the pipeline that are being used to process the data, including the basis of an innovative calibration system based on Gaia DR2 and 2MASS photometry.Comment: 18 pages, accepted for publication in MNRA