Search results for: Javier Fernandez De Canete

Authors: Jesus Carretero, Mario Vasile, Guillermo Izquierdo, Javier Garcia-Blas

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Currently, there is a so called ‘identity crisis’ in cybersecurity caused by the substantial security, privacy and usability shortcomings encountered in existing systems for identity management. Federated Identity Management (FIM) could be solution for this crisis, as it is a method that facilitates management of identity processes and policies among collaborating entities without enforcing a global consistency, that is difficult to achieve when there are ID legacy systems. To cope with this problem, the Connecting Europe Facility (CEF) initiative proposed in 2014 a federated solution in anticipation of the adoption of the Regulation (EU) N°910/2014, the so-called eIDAS Regulation. At present, a network of eIDAS Nodes is being deployed at European level to allow that every citizen recognized by a member state is to be recognized within the trust network at European level, enabling the consumption of services in other member states that, until now were not allowed, or whose concession was tedious. This is a very ambitious approach, since it tends to enable cross-border authentication of Member States citizens without the need to unify the authentication method (eID Scheme) of the member state in question. However, this federation is currently managed by member states and it is initially applied only to citizens and public organizations. The goal of this paper is to present the results of a European Project, named eID@Cloud, that focuses on the integration of eID in 5 cloud platforms belonging to authentication service providers of different EU Member States to act as Service Providers (SP) for private entities. We propose an initiative based on a private eID Scheme both for natural and legal persons. The methodology followed in the eID@Cloud project is that each Identity Provider (IdP) is subscribed to an eIDAS Node Connector, requesting for authentication, that is subscribed to an eIDAS Node Proxy Service, issuing authentication assertions. To cope with high loads, load balancing is supported in the eIDAS Node. The eID@Cloud project is still going on, but we already have some important outcomes. First, we have deployed the federation identity nodes and tested it from the security and performance point of view. The pilot prototype has shown the feasibility of deploying this kind of systems, ensuring good performance due to the replication of the eIDAS nodes and the load balance mechanism. Second, our solution avoids the propagation of identity data out of the native domain of the user or entity being identified, which avoids problems well known in cybersecurity due to network interception, man in the middle attack, etc. Last, but not least, this system allows to connect any country or collectivity easily, providing incremental development of the network and avoiding difficult political negotiations to agree on a single authentication format (which would be a major stopper).

Keywords: cybersecurity, identity federation, trust, user authentication

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Authors: I. Cerrillo, A. Carrillo-Vico, M. A. Ortega, B. Escudero-López, N. Álvarez-Sánchez, F. Martín, M. S. Fernández-Pachón

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Melatonin is a bioactive compound involved in multiple biological activities such as glucose tolerance, circadian rhythm regulation, antioxidant defense or immune system action. In elderly subjects the intake of foods and drinks rich in melatonin is very important due to its endogenous level decreases with age. Alcoholic fermentation is a process carried out in fruits, vegetables and legumes to obtain new products with improved bioactive compounds profile in relation to original substrates. Alcoholic fermentation process carried out by Saccharomycetaceae var. Pichia kluyveri induces an important synthesis of melatonin in orange juice. A novel beverage derived of fermented orange juice could be a promising source of this bioactive compound. The aim of the present study was to determine whether the acute intake of fermented orange juice increase the levels of urinary 6-sulfatoxymelatonin in healthy humans. Nine healthy volunteers (7 women and 2 men), aged between 20 and 25 years old and BMI of 21.1  2.4 kg/m2, were recruited. On the study day, participants ingested 500 mL of fermented orange juice. The first urine collection was made before fermented orange juice consumption (basal). The rest of urine collections were made in the following time intervals after fermented orange juice consumption: 0-2, 2-5, 5-10, 10- 15 and 15-24 hours. During the experimental period only the consumption of water was allowed. At lunch time a meal was provided (60 g of white bread, two slices of ham, a slice of cheese, 125 g of sweetened natural yoghurt and water). The subjects repeated the protocol with orange juice following a 2-wk washout period between both types of beverages. The levels of 6-sulfatoxymelatonin (6-SMT) were measured in urine recollected at different time points using the Melatonin-Sulfate Urine ELISA (IBL International GMBH, Hamburg, Germany). Levels of 6-SMT were corrected to those of creatinine for each sample. A significant (p < 0.05) increase in urinary 6-SMT levels was observed between 2-5 hours after fermented orange juice ingestion with respect to basal values (increase of 67,8 %). The consumption of orange juice did not induce any significant change in urinary 6-SMT levels. In addition, urinary 6-SMT levels obtained between 2-5 hours after fermented orange juice ingestion (115,6 ng/mg) were significantly different (p < 0.05) from those of orange juice (42,4 ng/mg). The enhancement of urinary 6-SMT after the ingestion of 500 mL of fermented orange juice in healthy humans compared to orange juice could be an important advantage of this novel product as an excellent source of melatonin. Fermented orange juice could be a new functional food, and its consumption could exert a potentially positive effect on health in both the maintenance of health status and the prevention of chronic diseases.

Keywords: fermented orange juice, functional beverage, healthy human, melatonin

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Authors: María Luisa Gonzalez-SanJose, Javier Garcia-Lomillo, Raquel Del Pino, Miriam Ortega-Heras, Maria Dolores Rivero-Perez, Pilar Muñiz-Rodriguez

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One of the most preoccupant problems related to the diet of the occidental societies is the high salt intake. In Spain, salt intake is almost twice as recommended by the World Health Organization (WHO). A lot of negative health effects of high sodium intake have been described being the hypertension, cardiovascular and coronary diseases ones of the most important. Due to this fact, government and other institutions are working on the gradual reduction of this consumption. Intake of meat products have been described as the main processed products that bring salt to the diet, followed by snacks and savory crackers. However, fortunately, the food industry has also raised awareness of this problem and is working intensely, and in recent years attempts to reduce the salt content in processed products, and is developing special lines with low sodium content. It is important to consider that processed food are the main source of sodium in occidental countries. One of the possible strategies to reduce the salt content in food is to find substitutes that can emulate their taste properties without adding much sodium or products that mask or substitute salty sensations with other flavors and aromas. In this sense, multiple products have been proposed and used until now. Potassium salts produce similar salty sensations without bring sodium, however their intake should be also limited, by healthy reasons. Furthermore, some potassium salts shows some better notes. Other alternatives are the use of flavor enhancers, spices, aromatic herbs, sea-plant derivate products, etc. The wine pomace is rich in potassium salts, content organic acid and other flavored substances, therefore it could be an interesting raw material to obtain derived products that could be useful as alternative ‘seasonings’. Considering previous comments, the main aim of this study was to evaluate the possible use of a natural seasoning, made from red wine pomace, in two different foods, crackers and burgers. The seasoning was made in the pilot plant of food technology of the University of Burgos, where the studied crackers and patties were also made. Different members of the University, students, docent and administrative personal, taste the products, and a trained panel evaluated salty intensity. The seasoning in addition to potassium contain significant levels of dietary fiber and phenolic compounds, which also makes it interesting as a functional ingredient. Both burgers and crackers made with the seasoning showed better taste that those without salt. Obviously, they showed lower sodium content than normal formulation, and were richer in potassium, antioxidant and fiber. Then, they showed lower values of the relation Na/K. All these facts are correlated with more ‘healthy’ products especially to that people with hypertension and other coronary dysfunctions.

Keywords: healthy foods, low salt, seasoning, wine pomace

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Authors: Ana Paula Soares, Alexandrina Lages, Helena Oliveira, Francisco-Javier Gutiérrez-Domínguez, Marisa Lousada

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From an early age, exposure to a spoken language allows us to implicitly capture the structure underlying the succession of the speech sounds in that language and to segment it into meaningful units (words). Statistical learning (SL), i.e., the ability to pick up patterns in the sensory environment even without intention or consciousness of doing it, is thus assumed to play a central role in the acquisition of the rule-governed aspects of language and possibly to lie behind the language difficulties exhibited by children with development language disorder (DLD). The research conducted so far has, however, led to inconsistent results, which might stem from the behavioral tasks used to test SL. In a classic SL experiment, participants are first exposed to a continuous stream (e.g., syllables) in which, unbeknownst to the participants, stimuli are grouped into triplets that always appear together in the stream (e.g., ‘tokibu’, ‘tipolu’), with no pauses between each other (e.g., ‘tokibutipolugopilatokibu’) and without any information regarding the task or the stimuli. Following exposure, SL is assessed by asking participants to discriminate between triplets previously presented (‘tokibu’) from new sequences never presented together during exposure (‘kipopi’), i.e., to perform a two-alternative-forced-choice (2-AFC) task. Despite the widespread use of the 2-AFC to test SL, it has come under increasing criticism as it is an offline post-learning task that only assesses the result of the learning that had occurred during the previous exposure phase and that might be affected by other factors beyond the computation of regularities embedded in the input, typically the likelihood two syllables occurring together, a statistic known as transitional probability (TP). One solution to overcome these limitations is to assess SL as exposure to the stream unfolds using online techniques such as event-related potentials (ERP) that is highly sensitive to the time-course of the learning in the brain. Here we collected ERPs to examine the neurofunctional correlates of SL in preschool children with DLD, and chronological-age typical language development (TLD) controls who were exposed to an auditory stream in which eight three-syllable nonsense words, four of which presenting high-TPs and the other four low-TPs, to further analyze whether the ability of DLD and TLD children to extract-word-like units from the steam was modulated by words’ predictability. Moreover, to ascertain if the previous knowledge of the to-be-learned-regularities affected the neural responses to high- and low-TP words, children performed the auditory SL task, firstly, under implicit, and, subsequently, under explicit conditions. Although behavioral evidence of SL was not obtained in either group, the neural responses elicited during the exposure phases of the SL tasks differentiated children with DLD from children with TLD. Specifically, the results indicated that only children from the TDL group showed neural evidence of SL, particularly in the SL task performed under explicit conditions, firstly, for the low-TP, and, subsequently, for the high-TP ‘words’. Taken together, these findings support the view that children with DLD showed deficits in the extraction of the regularities embedded in the auditory input which might underlie the language difficulties.

Keywords: development language disorder, statistical learning, transitional probabilities, word segmentation

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Authors: María-Luisa Pinto-Salamanca, Wilson-Javier Pérez-Holguín

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Reconstruction of contact forces is a fundamental technique for analyzing the properties of a touched object and is essential for regulating the grip force in slip control loops. This is based on the processing of the distribution, intensity, and direction of the forces during the capture of the sensors. Currently, efficient hardware alternatives have been used more frequently in different fields of application, allowing the implementation of computationally complex algorithms, as is the case with tactile signal processing. The use of hardware for smart tactile sensing systems is a research area that promises to improve the processing time and portability requirements of applications such as artificial skin and robotics, among others. The literature review shows that hardware implementations are present today in almost all stages of smart tactile detection systems except in the force reconstruction process, a stage in which they have been less applied. This work presents a hardware implementation of a model-driven reported in the literature for the contact force reconstruction of flat and rigid tactile sensor arrays from normal stress data. From the analysis of a software implementation of such a model, this implementation proposes the parallelization of tasks that facilitate the execution of matrix operations and a two-dimensional optimization function to obtain a vector force by each taxel in the array. This work seeks to take advantage of the parallel hardware characteristics of Field Programmable Gate Arrays, FPGAs, and the possibility of applying appropriate techniques for algorithms parallelization using as a guide the rules of generalization, efficiency, and scalability in the tactile decoding process and considering the low latency, low power consumption, and real-time execution as the main parameters of design. The results show a maximum estimation error of 32% in the tangential forces and 22% in the normal forces with respect to the simulation by the Finite Element Modeling (FEM) technique of Hertzian and non-Hertzian contact events, over sensor arrays of 10×10 taxels of different sizes. The hardware implementation was carried out on an MPSoC XCZU9EG-2FFVB1156 platform of Xilinx® that allows the reconstruction of force vectors following a scalable approach, from the information captured by means of tactile sensor arrays composed of up to 48 × 48 taxels that use various transduction technologies. The proposed implementation demonstrates a reduction in estimation time of x / 180 compared to software implementations. Despite the relatively high values of the estimation errors, the information provided by this implementation on the tangential and normal tractions and the triaxial reconstruction of forces allows to adequately reconstruct the tactile properties of the touched object, which are similar to those obtained in the software implementation and in the two FEM simulations taken as reference. Although errors could be reduced, the proposed implementation is useful for decoding contact forces for portable tactile sensing systems, thus helping to expand electronic skin applications in robotic and biomedical contexts.

Keywords: contact forces reconstruction, forces estimation, tactile sensor array, hardware implementation

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Authors: Juliana Shimara Pires Ferrão, Letícia Palmeira Pinto, Francisco Palma Rennó, Francisco Javier Hernandez Blazquez

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The ruminant stomach is a complex and multi-chambered organ. Although the true stomach (abomasum) is fully differentiated and functional at birth, the same does not occur with the rumen chamber. At this moment, rumen papillae are small or nonexistent. The papillae only fully develop after weaning and during calf growth. Papillae development and ruminal epithelium specialization during the fetus growth and at birth must be two interdependent processes that will prepare the rumen to adapt to ruminant adult feeding. The microscopic study of rumen epithelium at these early phases of life is important to understand how this structure prepares the rumen to deal with the following weaning processes and its functional activation. Samples of ruminal mucosa of bovine fetuses (110- and 150 day-old) and newborn calves were collected (dorsal and ventral portions) and processed for light and electron microscopy and immunohistochemistry. The basal cell layer of the stratified pavimentous epithelium present in different ruminal portions of the fetuses was thicker than the same portions of newborn calves. The superficial and intermediate epithelial layers of 150 day-old fetuses were thicker than those found in the other 2 studied ages. At this age (150 days), dermal papillae begin to invade the intermediate epithelial layer which gradually disappears in newborn calves. At birth, the ruminal papillae project from the epithelial surface, probably by regression of the epithelial cells (transitory cells) surrounding the dermal papillae. The PCNA cell proliferation index (%) was calculated for all epithelial samples. Fetuses 150 day-old showed increased cell proliferation in basal cell layer (Dorsal Portion: 84.2%; Ventral Portion: 89.8%) compared to other ages studied. Newborn calves showed an intermediate index (Dorsal Portion: 65.1%; Ventral Portion: 48.9%), whereas 110 day-old fetuses had the lowest proliferation index (Dorsal Portion: 57.2%; Ventral Portion: 20.6%). Regarding the transitory epithelium, 110 day-old fetuses showed the lowest proliferation index (Dorsal Portion: 44.6%; Ventral Portion: 20.1%), 150 day-old fetuses showed an intermediate proliferation index (Dorsal Portion: 57.5%; Ventral Portion: 71.1%) and newborn calves presented a higher proliferation index (Dorsal Portion: 75.1%; Ventral Portion: 19.6%). Under TEM, the 110- and 150 day-old fetuses presented thicker and poorly organized basal cell layer, with large nuclei and dense cytoplasm. In newborn calves, the basal cell layer was more organized and with fewer layers, but typically similar in both regions of the rumen. For the transitory epithelium, fetuses displayed larger cells than those found in newborn calves with less electrondense cytoplasm than that found in the basal cells. The ruminal dorsal portion has an overall higher cell proliferation rate than the ventral portion. Thus we can infer that the dorsal portion may have a higher cell activity than the ventral portion during ruminal development. Moreover, the basal cell layer is thicker in the 110- and 150 day-old fetuses than in the newborn calves. The transitory epithelium, which is much reduced, at birth may have a structural support function of the developing dermal papillae. When it regresses or is sheared off, the papillae are “carved out” from the surrounding epithelial layer.

Keywords: bovine, calf, epithelium, fetus, hematoxylin-eosin, immunohistochemistry, TEM, Rumen

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Authors: J. Roberto Lopez, Hened Saade, Graciela Morales, Javier Enriquez, Raul G. Lopez

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Implementation of systems based on nanostructures for drug delivery applications have taken relevance in recent studies focused on biomedical applications. Although there are several nanostructures as drugs carriers, the use of polymeric nanoparticles (PNP) has been widely studied for this purpose, however, the main issue for these nanostructures is the size control below 50 nm with a narrow distribution size, due to they must go through different physiological barriers and avoid to be filtered by kidneys (< 10 nm) or the spleen (> 100 nm). Thus, considering these and other factors, it can be mentioned that drug-loaded nanostructures with sizes varying between 10 and 50 nm are preferred in the development and study of PNP/drugs systems. In this sense, the Semicontinuous Heterophase Polymerization (SHP) offers the possibility to obtain PNP in the desired size range. Considering the above explained, methacrylic copolymer nanoparticles were obtained under SHP. The reactions were carried out in a jacketed glass reactor with the required quantities of water, ammonium persulfate as initiator, sodium dodecyl sulfate/sodium dioctyl sulfosuccinate as surfactants, methyl methacrylate and methacrylic acid as monomers with molar ratio of 2/1, respectively. The monomer solution was dosed dropwise during reaction at 70 °C with a mechanical stirring of 650 rpm. Nanoparticles of poly(methyl methacrylate-co-methacrylic acid) were loaded with acetylsalicylic acid (ASA, aspirin) by a chemical adsorption technique. The purified latex was put in contact with a solution of ASA in dichloromethane (DCM) at 0.1, 0.2, 0.4 or 0.6 wt-%, at 35°C during 12 hours. According to the boiling point of DCM, as well as DCM and water densities, the loading process is completed when the whole DCM is evaporated. The hydrodynamic diameter was measured after polymerization by quasi-elastic light scattering and transmission electron microscopy, before and after loading procedures with ASA. The quantitative and qualitative analyses of PNP loaded with ASA were measured by infrared spectroscopy, differential scattering calorimetry and thermogravimetric analysis. Also, the molar mass distributions of polymers were determined in a gel permeation chromatograph apparatus. The load capacity and efficiency were determined by gravimetric analysis. The hydrodynamic diameter results for methacrylic PNP without ASA showed a narrow distribution with an average particle size around 10 nm and a composition methyl methacrylate/methacrylic acid molar ratio equal to 2/1, same composition of Eudragit S100, which is a commercial compound widely used as excipient. Moreover, the latex was stabilized in a relative high solids content (around 11 %), a monomer conversion almost 95 % and a number molecular weight around 400 Kg/mol. The average particle size in the PNP/aspirin systems fluctuated between 18 and 24 nm depending on the initial percentage of aspirin in the loading process, being the drug content as high as 24 % with an efficiency loading of 36 %. These average sizes results have not been reported in the literature, thus, the methacrylic nanoparticles here reported are capable to be loaded with a considerable amount of ASA and be used as a drug carrier.

Keywords: aspirin, biocompatibility, biodegradable, Eudragit S100, methacrylic nanoparticles

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Authors: Elisa Santana-Monagas, Juan L. Núñez, Jaime León, Samuel Falcón, Celia Fernández, Rocío P. Solís

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Teaching practices have been widely studied in relation to students' outcomes, positioning themselves as one of their strongest catalysts and influencing students' emotional experiences. In the higher education context, teachers become even more crucial as many students ground their decisions on which courses to enroll in based on opinions and ratings of teachers from other students. Unfortunately, sometimes universities do not provide the personal, social, and academic stimulation students demand to be actively engaged. To evaluate their teachers, universities often rely on students' evaluations of teaching (SET) collected via Likert scale surveys. Despite its usefulness, such a method has been questioned in terms of validity and reliability. Alternatively, researchers can rely on qualitative answers to open-ended questions. However, the unstructured nature of the answers and a large amount of information obtained requires an overwhelming amount of work. The present work presents an alternative approach to analyse such data: sentiment analysis. To the best of our knowledge, no research before has included results from SA into an explanatory model to test how students' sentiments affect their emotional engagement in class. The sample of the present study included a total of 225 university students (Mean age = 26.16, SD = 7.4, 78.7 % women) from the Educational Sciences faculty of a public university in Spain. Data collection took place during the academic year 2021-2022. Students accessed an online questionnaire using a QR code. They were asked to answer the following open-ended question: "If you had to explain to a peer who doesn't know your teacher how he or she communicates in class, what would you tell them?". Sentiment analysis was performed using Microsoft's pre-trained model. The reliability of the measure was estimated between the tool and one of the researchers who coded all answers independently. The Cohen's kappa and the average pairwise percent agreement were estimated with ReCal2. Cohen's kappa was .68, and the agreement reached was 90.8%, both considered satisfactory. To test the hypothesis relations among SA and students' emotional engagement, a structural equation model (SEM) was estimated. Results demonstrated a good fit of the data: RMSEA = .04, SRMR = .03, TLI = .99, CFI = .99. Specifically, the results showed that student’s sentiment regarding their teachers’ teaching positively predicted their emotional engagement (β == .16 [.02, -.30]). In other words, when students' opinion toward their instructors' teaching practices is positive, it is more likely for students to engage emotionally in the subject. Altogether, the results show a promising future for sentiment analysis techniques in the field of education. They suggest the usefulness of this tool when evaluating relations among teaching practices and student outcomes.

Keywords: sentiment analysis, students' evaluation of teaching, structural-equation modelling, emotional engagement

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Authors: Elisa Santana-Monagas, Juan L. Núñez, Jaime León, Samuel Falcón, Celia Fernández, Rocío P. Solís

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Students’ emotional experiences have been a widely discussed theme among researchers, proving a central role on students’ outcomes. Yet, up to now, far too little attention has been paid to teaching practices that negatively relate with students’ negative emotions in the higher education. The present work aims to examine the relationship between teachers’ teaching practices (i.e., students’ evaluations of teaching and autonomy support), the students’ feelings of boredom and agentic engagement and motivation in the higher education context. To do so, the present study incorporates one of the most popular tools in natural processing language to address students’ evaluations of teaching: sentiment analysis. Whereas most research has focused on the creation of SA models and assessing students’ satisfaction regarding teachers and courses to the author’s best knowledge, no research before has included results from SA into an explanatory model. A total of 225 university students (Mean age = 26.16, SD = 7.4, 78.7 % women) participated in the study. Students were enrolled in degree and masters’ studies at the faculty of Education of a public university of Spain. Data was collected using an online questionnaire students could access through a QR code they completed during a teaching period where the assessed teacher was not present. To assess students’ sentiments towards their teachers’ teaching, we asked them the following open-ended question: “If you had to explain a peer who doesn't know your teacher how he or she communicates in class, what would you tell them?”. Sentiment analysis was performed with Microsoft's pre-trained model. For this study, we relied on the probability of the students answer belonging to the negative category. To assess the reliability of the measure, inter-rater agreement between this NLP tool and one of the researchers, who independently coded all answers, was examined. The average pairwise percent agreement and the Cohen’s kappa were calculated with ReCal2. The agreement reached was of 90.8% and Cohen’s kappa .68, both considered satisfactory. To test the hypothesis relations a structural equation model (SEM) was estimated. Results showed that the model fit indices displayed a good fit to the data; χ² (134) = 351.129, p < .001, RMSEA = .07, SRMR = .09, TLI = .91, CFI = .92. Specifically, results show that boredom was negatively predicted by autonomy support practices (β = -.47[-.61, -.33]), whereas for the negative sentiment extracted from SET, this relation was positive (β = .23[.16, .30]). In other words, when students’ opinion towards their instructors’ teaching practices was negative, it was more likely for them to feel bored. Regarding the relations among boredom and student outcomes, results showed a negative predictive value of boredom on students’ motivation to study (β = -.46[-.63, -.29]) and agentic engagement (β = -.24[-.33, -.15]). Altogether, results show a promising future for sentiment analysis techniques in the field of education as they proved the usefulness of this tool when evaluating relations among teaching practices and student outcomes.

Keywords: sentiment analysis, boredom, motivation, agentic engagement

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Authors: Federico Herrera, Valle Gomez García de Soria, Itxaso Portero Sainz, Carlos Fernández Arandojo, Mercedes Royg, Ana Marcos Jimenez, Anna Kreutzman, Cecilia MuñozCalleja

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Introduction: Graft-versus-host disease (GVHD) still remains the major complication associated with allogeneic stem cell transplantation (SCT). The pathogenesis involves migration of donor naïve T-cells into recipient secondary lymphoid organs. Two molecules are important in this process: CD62L and CCR7, which are characteristically expressed in naïve/central memory T-cells. With this background, we aimed to study the influence of CCR7 and CD62L on donor lymphocytes in the development and severity of GVHD. Material and methods: This single center study included 98 donor-recipient pairs. Samples were collected prospectively from the apheresis product and phenotyped by flow cytometry. CCR7 and CD62L expression in CD4+ and CD8+ T-cells were compared between patients who developed acute (n=40) or chronic GVHD (n=33) and those who did not (n=38). Results: The patients who developed acute GVHD were transplanted with a higher percentage of CCR7+CD4+ T-cells (p = 0.05) compared to the no GVHD group. These results were confirmed when these patients were divided in degrees according to the severity of the disease; the more severe disease, the higher percentage of CCR7+CD4+ T-cells. Conversely, chronic GVHD patients received a higher percentage of CCR7+CD8+ T-cells (p=0.02) in comparison to those who did not develop the complication. These data were also confirmed when patients were subdivided in degrees of the disease severity. A multivariable analysis confirmed that percentage of CCR7+CD4+ T-cells is a predictive factor of acute GVHD whereas the percentage of CCR7+CD8+ T-cells is a predictive factor of chronic GVHD. In vitro functional assays (migration and activation assays) supported the idea of CCR7+ T-cells were involved in the development of GVHD. As low levels of CD62L expression were detected in all apheresis products, we tested the hypothesis that CD62L was shed during apheresis procedure. Comparing CD62L surface levels in T-cells from the same donor immediately before collecting the apheresis product, and the final apheresis product we found that this process down-regulated CD62L in both CD4+ and CD8+ T cells (p=0.008). Interestingly, when CD62L levels were analysed in days 30 or 60 after engraftment, they recovered to baseline (p=0.008). However, to investigate the relation between CD62L expression and the development of GVHD in the recipient samples after the engraftment, no differences were observed comparing patients with GVHD to those who did not develop the disease. Discussion: Our prospective study indicates that the CCR7+ T-cells from the donor, which include naïve and central memory T-cells, contain the alloreactive cells with a high ability to mediate GVHD (in the case of both migration and activation). Therefore we suggest that the proportion and functional properties of CCR7+CD4+ and CCR7+CD8+ T-cells in the apheresis could act as a predictive biomarker to both acute and chronic GVHD respectively. Importantly, our study precludes that CD62L is lost in the apheresis and therefore it is not a reliable biomarker for the development of GVHD.

Keywords: CCR7, CD62L, GVHD, SCT

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Authors: Flora Xu, Marta Fernandez Olmos

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This article is mainly about critical assessment and comprehensive understanding of the business strategy in the post COVID-19 scenario. This study aims to elucidate how companies are responding to the unique challenges posed by the pandemic and how these measures are shaping the future of the business environment. The pandemic has exposed the fragility and flexibility of the global supply chain, and procurement and production strategies should be reconsidered. It should increase the diversity of suppliers and the flexibility of the supply chain, and some companies are considering transferring their survival to the local market. This can increase local employment and reduce international transportation disruptions and customs issues. By shortening the distance between production and market, companies can respond more quickly to changes in demand and unforeseen events. The demand for remote work and online solutions will increase the adoption of digital technology and accelerate the digital transformation of many organizations. Marketing and communication strategies need to adapt to a constantly changing environment. The business resilience strategy was emphasized as a key component of the response to the COVID-19. The company is seeking to strengthen its risk management capabilities and develop a business continuity plan to cope with future unexpected disruptions. The pandemic has reconfigured human resource practices and changed the way companies manage their employees. Remote work has become the norm, and companies focus on managing workers' health and well-being, as well as flexible work policies to ensure operations and support for employees during crises. This change in human resources practice has a lasting impact on how companies apply talent and labor management in the post COVID-19 world. The pandemic has prompted a significant review of business strategies as companies adapt to constantly changing environments and seek to ensure their sustainability and profitability in times of crisis. This strategic reassessment has led to product diversification, exploring international markets and adapting to the changing market. Companies have responded to the unprecedented challenges brought by the COVID-19. The COVID-19 has promoted innovation effort in key areas and focused on the responsibility in today's business strategy for sustainability and the importance of corporate society. The important challenge of formulating and implementing business strategies in uncertain times. These challenges include making quick and agile decisions in turbulent environments, risk management, and adaptability to constantly changing market conditions. The COVID-19 highlights the importance of strategic planning and informed decision-making - making in a business environment characterized by uncertainty and complexity. In short, the pandemic has reconfigured the way companies handle business strategies and emphasized the necessity of preparing for future challenges in a business world marked by uncertainty and complexity.

Keywords: business strategy, crisis, digitalization, uncertainty

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Authors: Britt Erni, Aldara Vazquez Fernandez, Roland Maurer

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Visuospatial perspective taking (VSPT) is a process that allows to integrate spatial information from different points of view, and to transform the mental images we have of the environment to properly orient our movements and anticipate the location of landmarks during navigation. VSPT is also related to egocentric perspective transformations (imagined rotations or translations of one's point of view) and to infer the visuospatial experiences of another person (e.g. if and how another person sees objects). This process is deeply related to a wide-ranging capacity called the theory of mind (ToM), an essential cognitive function that allows us to regulate our social behaviour by attributing mental representations to individuals in order to make behavioural predictions. VSPT is often considered in the literature as the starting point of the development of the theory of mind. VSPT and ToM include several levels of knowledge that have to be assessed by specific tasks. Unfortunately, the lack of tasks assessing these functions in clinical neuropsychology leads to underestimate, in brain-damaged patients, deficits of these functions which are essential, in everyday life, to regulate our social behaviour (ToM) and to navigate in known and unknown environments (VSPT). Therefore, this study aims to create and standardize a VSPT task in order to explore the cognitive requirements of VSPT and ToM, and to specify their relationship in healthy adults and thereafter in brain-damaged patients. Two versions of a computerized VSPT task were administered to healthy participants (M = 28.18, SD = 4.8 years). In both versions the environment was a 3D representation of 10 different geometric shapes placed on a circular base. Two sets of eight pictures were generated from this: of the environment with an avatar somewhere on its periphery (locations) and of what the avatar sees from that place (views). Two types of questions were asked: a) identify the location from the view, and b) identify the view from the location. Twenty participants completed version 1 of the task and 20 completed the second version, where the views were offset by ±15° (i.e., clockwise or counterclockwise) and participants were asked to choose the closest location or the closest view. The preliminary findings revealed that version 1 is significantly easier than version 2 for accuracy (with ceiling scores for version 1). In version 2, participants responded significantly slower when they had to infer the avatar's view from the latter's location, probably because they spent more time visually exploring the different views (responses). Furthermore, men significantly performed better than women in version 1 but not in version 2. Most importantly, a sensitive task (version 2) has been created for which the participants do not seem to easily and automatically compute what someone is looking at yet which does not involve more heavily other cognitive functions. This study is further completed by including analysis on non-clinical participants with low and high degrees of schizotypy, different socio-educational status, and with a range of older adults to examine age-related and other differences in VSPT processing.

Keywords: mental transformation, spatial cognition, theory of mind, visuospatial perspective taking

Procedia PDF Downloads 203

Authors: Javier E. García-Gallo, Nelson J. Fonseca-Ruiz, John F. Duitama-Munoz

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Sepsis is a syndrome that occurs with physiological and biochemical abnormalities induced by severe infection and carries a high mortality and morbidity, therefore the severity of its condition must be interpreted quickly. After patient admission in an intensive care unit (ICU), it is necessary to synthesize the large volume of information that is collected from patients in a value that represents the severity of their condition. Traditional severity of illness scores seeks to be applicable to all patient populations, and usually assess in-hospital mortality. However, the use of machine learning techniques and the data of a population that shares a common characteristic could lead to the development of customized mortality prediction scores with better performance. This study presents the development of a score for the one-year mortality prediction of the patients that are admitted to an ICU with a sepsis diagnosis. 5650 ICU admissions extracted from the MIMICIII database were evaluated, divided into two groups: 70% to develop the score and 30% to validate it. Comorbidities, demographics and clinical information of the first 24 hours after the ICU admission were used to develop a mortality prediction score. LASSO (least absolute shrinkage and selection operator) and SGB (Stochastic Gradient Boosting) variable importance methodologies were used to select the set of variables that make up the developed score; each of this variables was dichotomized and a cut-off point that divides the population into two groups with different mean mortalities was found; if the patient is in the group that presents a higher mortality a one is assigned to the particular variable, otherwise a zero is assigned. These binary variables are used in a logistic regression (LR) model, and its coefficients were rounded to the nearest integer. The resulting integers are the point values that make up the score when multiplied with each binary variables and summed. The one-year mortality probability was estimated using the score as the only variable in a LR model. Predictive power of the score, was evaluated using the 1695 admissions of the validation subset obtaining an area under the receiver operating characteristic curve of 0.7528, which outperforms the results obtained with Sequential Organ Failure Assessment (SOFA), Oxford Acute Severity of Illness Score (OASIS) and Simplified Acute Physiology Score II (SAPSII) scores on the same validation subset. Observed and predicted mortality rates within estimated probabilities deciles were compared graphically and found to be similar, indicating that the risk estimate obtained with the score is close to the observed mortality, it is also observed that the number of events (deaths) is indeed increasing as the outcome go from the decile with the lowest probabilities to the decile with the highest probabilities. Sepsis is a syndrome that carries a high mortality, 43.3% for the patients included in this study; therefore, tools that help clinicians to quickly and accurately predict a worse prognosis are needed. This work demonstrates the importance of customization of mortality prediction scores since the developed score provides better performance than traditional scoring systems.

Keywords: intensive care, logistic regression model, mortality prediction, sepsis, severity of illness, stochastic gradient boosting

Procedia PDF Downloads 222

Authors: Alvarez M., Chapela M. J., Balboa E., Rubianes D., Sinde E., Fernandez de Ana C., Rodríguez-Blanco A.

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The gut microbiota plays an important role as gut inflammation could contribute to colorectal cancer development; however, this role is still not fully understood, and tools able to prevent this progression are yet to be developed. The main objective of this study was to monitor the effects of a mushroom extracts formulation in gut microbial community composition of an Azoxymethane (AOM)/Dextran sodium sulfate (DSS) mice model of inflammation-linked carcinogenesis. For the in vivo study, 41 adult male mice of the C57BL / 6 strain were obtained. 36 of them have been induced in a state of colon carcinogenesis by a single intraperitoneal administration of AOM at a dose of 12.5 mg/kg; the control group animals received instead of the same volume of 0.9% saline. DSS is an extremely toxic polysaccharide sulfate that causes chronic inflammation of the colon mucosa, favoring the appearance of severe colitis and the production of tumors induced by AOM. Induction by AOM/DSS is an interesting platform for chemopreventive intervention studies. This time the model was used to monitor gut microbiota changes as a result of supplementation with a specific mushroom extracts formulation previously shown to have prebiotic activity. The animals have been divided into three groups: (i) Cancer + mushroom extracts formulation experimental group: to which the MicoDigest2.0 mushroom extracts formulation developed by Hifas da Terra S.L has been administered dissolved in drinking water at an estimated concentration of 100 mg / ml. (ii) Control group of animals with Cancer: to which normal water has been administered without any type of treatment. (iii) Control group of healthy animals: these are the animals that have not been induced cancer or have not received any treatment in drinking water. This treatment has been maintained for a period of 3 months, after which the animals were sacrificed to obtain tissues that were subsequently analyzed to verify the effects of the mushroom extract formulation. A microbiological analysis has been carried out to compare the microbial communities present in the intestines of the mice belonging to each of the study groups. For this, the methodology of massive sequencing by molecular analysis of the 16S gene has been used (Ion Torrent technology). Initially, DNA extraction and metagenomics libraries were prepared using the 16S Metagenomics kit, always following the manufacturer's instructions. This kit amplifies 7 of the 9 hypervariable regions of the 16S gene that will then be sequenced. Finally, the data obtained will be compared with a database that makes it possible to determine the degree of similarity of the sequences obtained with a wide range of bacterial genomes. Results obtained showed that, similarly to certain natural compounds preventing colorectal tumorigenesis, a mushroom formulation enriched the Firmicutes and Proteobacteria phyla and depleted Bacteroidetes. Therefore, it was demonstrated that the consumption of the mushroom extracts’ formulation developed could promote the recovery of the microbial balance that is disrupted in the mice model of carcinogenesis. More preclinical and clinical studies are needed to validate this promising approach.

Keywords: carcinogenesis, microbiota, mushroom extracts, inflammation

Procedia PDF Downloads 149

Authors: Olga Hernán-Vega, Patricia López-Rodríguez, David Escot-Bocanegra, Raúl Fernández-Recio, Ignacio Bravo

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Non-Cooperative Target Identification has become a key research domain in the Defense industry since it provides the ability to recognize targets at long distance and under any weather condition. High Resolution Range Profiles, one-dimensional radar images where the reflectivity of a target is projected onto the radar line of sight, are widely used for identification of flying targets. According to that, to face this problem, an approach to Non-Cooperative Target Identification based on the exploitation of Singular Value Decomposition to a matrix of range profiles is presented. Target Identification based on one-dimensional radar images compares a collection of profiles of a given target, namely test set, with the profiles included in a pre-loaded database, namely training set. The classification is improved by using Singular Value Decomposition since it allows to model each aircraft as a subspace and to accomplish recognition in a transformed domain where the main features are easier to extract hence, reducing unwanted information such as noise. Singular Value Decomposition permits to define a signal subspace which contain the highest percentage of the energy, and a noise subspace which will be discarded. This way, only the valuable information of each target is used in the recognition process. The identification algorithm is based on finding the target that minimizes the angle between subspaces and takes place in a transformed domain. Two metrics, F1 and F2, based on Singular Value Decomposition are accomplished in the identification process. In the case of F2, the angle is weighted, since the top vectors set the importance in the contribution to the formation of a target signal, on the contrary F1 simply shows the evolution of the unweighted angle. In order to have a wide database or radar signatures and evaluate the performance, range profiles are obtained through numerical simulation of seven civil aircraft at defined trajectories taken from an actual measurement. Taking into account the nature of the datasets, the main drawback of using simulated profiles instead of actual measured profiles is that the former implies an ideal identification scenario, since measured profiles suffer from noise, clutter and other unwanted information and simulated profiles don't. In this case, the test and training samples have similar nature and usually a similar high signal-to-noise ratio, so as to assess the feasibility of the approach, the addition of noise has been considered before the creation of the test set. The identification results applying the unweighted and weighted metrics are analysed for demonstrating which algorithm provides the best robustness against noise in an actual possible scenario. So as to confirm the validity of the methodology, identification experiments of profiles coming from electromagnetic simulations are conducted, revealing promising results. Considering the dissimilarities between the test and training sets when noise is added, the recognition performance has been improved when weighting is applied. Future experiments with larger sets are expected to be conducted with the aim of finally using actual profiles as test sets in a real hostile situation.

Keywords: HRRP, NCTI, simulated/synthetic database, SVD

Procedia PDF Downloads 354

Authors: Rebeca P Ramos-Bueno, Maria Jose Gonzalez-Fernandez, Rosa M. Moreno-Zamora, Antonia Barros Heras, Yolanda Serrano Alonso, Carolina Sanchez Barranco

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Insects are a new source of fatty acids (FA), so they are considered a sustainable and environmentally friendly alternative for both animal feed and the human diet, and furthermore, their harvesting/rearing require a low-tech and low capital investment. For that reason, lipids obtained by insect breeding open interesting possibilities with alimentary and industrial purposes, i.e., the production of biodiesel. Particularly, certain insect species, especially during the larval stage, contain high proportions of fat which is highly dependent on their feed and stage of development. Among them, Hermetia illucens larvae can be bred on food wastes to produce fat- and protein-rich raw materials for food by-product management. So, insects can act as excellent bioconverters of organic waste to nutrient-rich materials. In this regard, the aim of the study was to evaluate the effects of fruit byproducts on the FA compositions of Tenebrio molitor, Zophoba morio, and H. illucens larvae. Firstly, oil was extracted with the green solvent ethyl acetate, and FA methyl ester was obtained and analyzed by GC to show the FA profile. In addition, the triacylglycerol (TAG) profile was obtained by HPLC. Dehydrated watermelon, tomato, and papaya by-products, as well as wheat-based control feed, were assayed. High FA content was reached by Z. morio larvae fed with all fruits; however, no differences were shown in lipid profile with any change. It is worth highlighting that both Z. morio and H. illucens could be selected as the best candidates for biodiesel production due to their high content of saturated FA. On the other hand, T. molitor larvae showed a higher content of monounsaturated FA than control larvae, whereas the n-6 polyunsaturated FA content decreased in larvae fed with fruits. This result indicates that the improvement of the FA profile of Tenebrio can depend on both the type of feeding and the intended use. The lipid profile of H. illucens larvae fed with papaya and tomato showed a slight increase in the content of α-linoleic acid (ALA, 18:3n3). This FA is the precursor of docosahexaenoic acid (DHA, 22:6n3), which plays an important role as a component of structural lipids in cell membranes as well as in the synthesis of eicosanoids, protecting and resolving. Also, it was evaluated the TAG profile of Z. morio larvae due to their highest oil content. The results showed a high oleic acid (OA, 18:1n9) content, which displays modulatory effects in a wide range of physiological functions, having anti-inflammatory and anti-atherogenic properties. In conclusion, this study clearly shows that Z. morio and H. illucens larvae constitute an alternative source of OA- and ALA-rich oils, respectively, which can be devoted for food use, as well as for using in the food and pharmaceutical industries, with agronomic implications. Finally, although the profile of Z. morio was not improved with fruit feeding, this kind of feeding could be used due to its low environmental impact.

Keywords: fatty acids, fruit byproducts, Hermetia illucens, Zophoba morio, Tenebrio molitor, insect rearing

Procedia PDF Downloads 147

Authors: Ernest Moles, Patricia Urbán, María Belén Jiménez-Díaz, Sara Viera-Morilla, Iñigo Angulo-Barturen, Maria Antònia Busquets, Xavier Fernàndez-Busquets

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Bearing in mind the absence of an effective vaccine against malaria and its severe clinical manifestations causing nearly half a million deaths every year, this disease represents nowadays a major threat to life. Besides, the basic rationale followed by currently marketed antimalarial approaches is based on the administration of drugs on their own, promoting the emergence of drug-resistant parasites owing to the limitation in delivering drug payloads into the parasitized erythrocyte high enough to kill the intracellular pathogen while minimizing the risk of causing toxic side effects to the patient. Such dichotomy has been successfully addressed through the specific delivery of immunoliposome (iLP)-encapsulated antimalarials to Plasmodium falciparum-infected red blood cells (pRBCs). Unfortunately, this strategy has not progressed towards clinical applications, whereas in vitro assays rarely reach drug efficacy improvements above 10-fold. Here, we show that encapsulation efficiencies reaching >96% can be achieved for the weakly basic drugs chloroquine (CQ) and primaquine using the pH gradient active loading method in liposomes composed of neutrally charged, saturated phospholipids. Targeting antibodies are best conjugated through their primary amino groups, adjusting chemical crosslinker concentration to retain significant antigen recognition. Antigens from non-parasitized RBCs have also been considered as targets for the intracellular delivery of drugs not affecting the erythrocytic metabolism. Using this strategy, we have obtained unprecedented nanocarrier targeting to early intraerythrocytic stages of the malaria parasite for which there is a lack of specific extracellular molecular tags. Polyethylene glycol-coated liposomes conjugated with monoclonal antibodies specific for the erythrocyte surface protein glycophorin A (anti-GPA iLP) were capable of targeting 100% RBCs and pRBCs at the low concentration of 0.5 μM total lipid in the culture, with >95% of added iLPs retained into the cells. When exposed for only 15 min to P. falciparum in vitro cultures synchronized at early stages, free CQ had no significant effect over parasite viability up to 200 nM drug, whereas iLP-encapsulated 50 nM CQ completely arrested its growth. Furthermore, when assayed in vivo in P. falciparum-infected humanized mice, anti-GPA iLPs cleared the pathogen below detectable levels at a CQ dose of 0.5 mg/kg. In comparison, free CQ administered at 1.75 mg/kg was, at most, 40-fold less efficient. Our data suggest that this significant improvement in drug antimalarial efficacy is in part due to a prophylactic effect of CQ found by the pathogen in its host cell right at the very moment of invasion.

Keywords: immunoliposomal nanoparticles, malaria, prophylactic-therapeutic polyvalent activity, targeted drug delivery

Procedia PDF Downloads 375

Authors: Andrés Lara Guillén, José M. Soriano Disla, Gemma Castejón Martínez, David Fernández-Gutiérrez

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The worldwide population is exponentially increasing, which causes a rising demand for food, energy and non-renewable resources. These demands must be attended to from a circular economy point of view. Under this approach, the obtention of strategic products from biowaste is crucial for the society to keep the current lifestyle reducing the environmental and social issues linked to the lineal economy. This is the main objective of the VALUEWASTE project. VALUEWASTE is about valorizing urban biowaste into proteins for food and feed and biofertilizers, closing the loop of this waste stream. In order to achieve this objective, the project validates three value chains, which begin with the anaerobic digestion of the biowaste. From the anaerobic digestion, three by-products are obtained: i) methane that is used by microorganisms, which will be transformed into microbial proteins; ii) digestate that is used by black soldier fly, producing insect proteins; and iii) a nutrient-rich effluent, which will be transformed into biofertilizers. VALUEWASTE is an innovative solution, which combines different technologies to valorize entirely the biowaste. However, it is also required to demonstrate that the solution is greener than other traditional technologies (baseline systems). On one hand, the proteins from microorganisms and insects will be compared with other reference protein production systems (gluten, whey and soybean). On the other hand, the biofertilizers will be compared to the production of mineral fertilizers (ammonium sulphate and synthetic struvite). Therefore, the aim of this study is to provide that biowaste valorization can reduce the environmental impacts linked to both traditional proteins manufacturing processes and mineral fertilizers, not only at a pilot-scale but also at an industrial one. In the present study, both baseline system and VALUEWASTE solution are evaluated through the Environmental Life Cycle Assessment (E-LCA). The E-LCA is based on the standards ISO 14040 and 14044. The Environmental Footprint methodology was the one used in this study to evaluate the environmental impacts. The results for the baseline cases show that the food proteins coming from whey have the highest environmental impact on ecosystems compared to the other proteins sources: 7.5 and 15.9 folds higher than soybean and gluten, respectively. Comparing feed soybean and gluten, soybean has an environmental impact on human health 195.1 folds higher. In the case of biofertilizers, synthetic struvite has higher impacts than ammonium sulfate: 15.3 (ecosystems) and 11.8 (human health) fold, respectively. The results shown in the present study will be used as a reference to demonstrate the better environmental performance of the bio-based products obtained through the VALUEWASTE solution. Other originalities that the E-LCA performed in the VALUEWASTE project provides are the diverse direct implications on investment and policies. On one hand, better environmental performance will serve to remove the barriers linked to these kinds of technologies, boosting the investment that is backed by the E-LCA. On the other hand, it will be a germ to design new policies fostering these types of solutions to achieve two of the key targets of the European Community: being self-sustainable and carbon neutral.

Keywords: anaerobic digestion, biofertilizers, circular economy, nutrients recovery

Procedia PDF Downloads 88

Authors: A. Gonzalez Aguna, J. M. Santamaria Garcia, J. L. Gomez Gonzalez, R. Barchino Plata, M. Fernandez Batalla, S. Herrero Jaen

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Background: Computer Science is a field that transcends other disciplines of knowledge because it allows to support all kinds of physical and mental tasks. Health centres have a greater number and complexity of technological devices and the population consume and demand services derived from technology. Also, nursing education plans have included competencies related to and, even, courses about new technologies are offered to health professionals. However, nurses still limit their performance to the use and evaluation of products previously built. Objective: Develop a teaching-learning methodology for acquiring skills on designing applications for care. Methodology: Blended learning teaching with a group of graduate nurses through official training within a Master's Degree. The study sample was selected by intentional sampling without exclusion criteria. The study covers from 2015 to 2017. The teaching sessions included a four-hour face-to-face class and between one and three tutorials. The assessment was carried out by written test consisting of the preparation of an IEEE 830 Standard Specification document where the subject chosen by the student had to be a problem in the area of care. Results: The sample is made up of 30 students: 10 men and 20 women. Nine students had a degree in nursing, 20 diploma in nursing and one had a degree in Computer Engineering. Two students had a degree in nursing specialty through residence and two in equivalent recognition by exceptional way. Except for the engineer, no subject had previously received training in this regard. All the sample enrolled in the course received the classroom teaching session, had access to the teaching material through a virtual area and maintained at least one tutoring. The maximum of tutorials were three with an hour in total. Among the material available for consultation was an example of a document drawn up based on the IEEE Standard with an issue not related to care. The test to measure competence was completed by the whole group and evaluated by a multidisciplinary teaching team of two computer engineers and two nurses. Engineers evaluated the correctness of the characteristics of the document and the degree of comprehension in the elaboration of the problem and solution elaborated nurses assessed the relevance of the chosen problem statement, the foundation, originality and correctness of the proposed solution and the validity of the application for clinical practice in care. The results were of an average grade of 8.1 over 10 points, a range between 6 and 10. The selected topic barely coincided among the students. Examples of care areas selected are care plans, family and community health, delivery care, administration and even robotics for care. Conclusion: The applied methodology of learning-teaching for the design of technologies demonstrates the success in the training of nursing professionals. The role of expert is essential to create applications that satisfy the needs of end users. Nursing has the possibility, the competence and the duty to participate in the process of construction of technological tools that are going to impact in care of people, family and community.

Keywords: care, learning, nursing, technology

Procedia PDF Downloads 136

Authors: T. N. Tran Thi, J. Morse, C. Detlefs, P. K. Cook, C. Yıldırım, A. C. Jakobsen, T. Zhou, J. Hartwig, V. Zurbig, D. Caliste, B. Fernandez, D. Eon, O. Loto, M. L. Hicks, A. Pakpour-Tabrizi, J. Baruchel

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The ability to grow boron-doped diamond epilayers of high crystalline quality is a prerequisite for the fabrication of diamond power electronic devices, in particular high voltage diodes and metal-oxide-semiconductor (MOS) transistors. Boron and intrinsic diamond layers are homoepitaxially overgrown by microwave assisted chemical vapour deposition (MWCVD) on single crystal high pressure, high temperature (HPHT) grown bulk diamond substrates. Various epilayer thicknesses were grown, with dopant concentrations ranging from 1021 atom/cm³ at nanometer thickness in the case of 'delta doping', up 1016 atom/cm³ and 50µm thickness or high electric field drift regions. The crystalline quality of these overgrown layers as regards defects, strain, distortion… is critical for the device performance through its relation to the final electrical properties (Hall mobility, breakdown voltage...). In addition to the optimization of the epilayer growth conditions in the MWCVD reactor, other important questions related to the crystalline quality of the overgrown layer(s) are: 1) what is the dependence on the bulk quality and surface preparation methods of the HPHT diamond substrate? 2) how do defects already present in the substrate crystal propagate into the overgrown layer; 3) what types of new defects are created during overgrowth, what are their growth mechanisms, and how can these defects be avoided? 4) how can we relate in a quantitative manner parameters related to the measured crystalline quality of the boron doped layer to the electronic properties of final processed devices? We describe synchrotron-based techniques developed to address these questions. These techniques allow the visualization of local defects and crystal distortion which complements the data obtained by other well-established analysis methods such as AFM, SIMS, Hall conductivity…. We have used Grazing Incidence X-ray Diffraction (GIXRD) at the ID01 beamline of the ESRF to study lattice parameters and damage (strain, tilt and mosaic spread) both in diamond substrate near surface layers and in thick (10–50 µm) overgrown boron doped diamond epi-layers. Micro- and nano-section topography have been carried out at both the BM05 and ID06-ESRF) beamlines using rocking curve imaging techniques to study defects which have propagated from the substrate into the overgrown layer(s) and their influence on final electronic device performance. These studies were performed using various commercially sourced HPHT grown diamond substrates, with the MWCVD overgrowth carried out at the Fraunhofer IAF-Germany. The synchrotron results are in good agreement with low-temperature (5°K) cathodoluminescence spectroscopy carried out on the grown samples using an Inspect F5O FESEM fitted with an IHR spectrometer.

Keywords: synchrotron X-ray diffaction, crystalline quality, defects, diamond overgrowth, rocking curve imaging

Procedia PDF Downloads 261

Authors: Jesus Carretero, Mario Vasile, Javier Garcia-Blas, Felix Garcia-Carballeira

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Supporting cross-border secure and reliable exchange of data and documents and to promote data interoperability is critical for Europe to enhance sector (like eFinance, eJustice and eHealth). This work presents the status and results of the European Project MADE, a Research Project funded by Connecting Europe facility Programme, to provide secure e-invoicing and e-document exchange systems among Europe countries in compliance with the eIDAS Regulation (Regulation EU 910/2014 on electronic identification and trust services). The main goal of MADE is to develop six new AS4 Access Points and SMP in Europe to provide secure document exchanges using the eDelivery DSI (Digital Service Infrastructure) amongst both private and public entities. Moreover, the project demonstrates the feasibility and interest of the solution provided by providing several months of interoperability among the providers of the six partners in different EU countries. To achieve those goals, we have followed a methodology setting first a common background for requirements in the partner countries and the European regulations. Then, the partners have implemented access points in each country, including their service metadata publisher (SMP), to allow the access to their clients to the pan-European network. Finally, we have setup interoperability tests with the other access points of the consortium. The tests will include the use of each entity production-ready Information Systems that process the data to confirm all steps of the data exchange. For the access points, we have chosen AS4 instead of other existing alternatives because it supports multiple payloads, native web services, pulling facilities, lightweight client implementations, modern crypto algorithms, and more authentication types, like username-password and X.509 authentication and SAML authentication. The main contribution of MADE project is to open the path for European companies to use eDelivery services with cross-border exchange of electronic documents following PEPPOL (Pan-European Public Procurement Online) based on the e-SENS AS4 Profile. It also includes the development/integration of new components, integration of new and existing logging and traceability solutions and maintenance tool support for PKI. Moreover, we have found that most companies are still not ready to support those profiles. Thus further efforts will be needed to promote this technology into the companies. The consortium includes the following 9 partners. From them, 2 are research institutions: University Carlos III of Madrid (Coordinator), and Universidad Politecnica de Valencia. The other 7 (EDICOM, BIZbrains, Officient, Aksesspunkt Norge, eConnect, LMT group, Unimaze) are private entities specialized in secure delivery of electronic documents and information integration brokerage in their respective countries. To achieve cross-border operativity, they will include AS4 and SMP services in their platforms according to the EU Core Service Platform. Made project is instrumental to test the feasibility of cross-border documents eDelivery in Europe. If successful, not only einvoices, but many other types of documents will be securely exchanged through Europe. It will be the base to extend the network to the whole Europe. This project has been funded under the Connecting Europe Facility Agreement number: INEA/CEF/ICT/A2016/1278042. Action No: 2016-EU-IA-0063.

Keywords: security, e-delivery, e-invoicing, e-delivery, e-document exchange, trust

Procedia PDF Downloads 265

Authors: Alejandra Martin-Dominguez, Javier Canto-Rios, Velitchko Tzatchkov

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Electrocoagulation is a water treatment technology that consists of generating coagulant species in situ by electrolytic oxidation of sacrificial anode materials triggered by electric current. It removes suspended solids, heavy metals, emulsified oils, bacteria, colloidal solids and particles, soluble inorganic pollutants and other contaminants from water, offering an alternative to the use of metal salts or polymers and polyelectrolyte addition for breaking stable emulsions and suspensions. The method essentially consists of passing the water being treated through pairs of consumable conductive metal plates in parallel, which act as monopolar electrodes, commonly known as ‘sacrificial electrodes’. Physicochemical, electrochemical and hydraulic processes are involved in the efficiency of this type of treatment. While the physicochemical and electrochemical aspects of the technology have been extensively studied, little is known about the influence of the hydraulics. However, the hydraulic process is fundamental for the reactions that take place at the electrode boundary layers and for the coagulant mixing. Electrocoagulation reactors can be open (with free water surface) and closed (pressurized). Independently of the type of rector, hydraulic head loss is an important factor for its design. The present work focuses on the study of the total hydraulic head loss and flow velocity and pressure distribution in electrocoagulation reactors with single or multiple concentric annular cross sections. An analysis of the head loss produced by hydraulic wall shear friction and accessories (minor head losses) is presented, and compared to the head loss measured on a semi-pilot scale laboratory model for different flow rates through the reactor. The tests included laminar, transitional and turbulent flow. The observed head loss was compared also to the head loss predicted by several known conceptual theoretical and empirical equations, specific for flow in concentric annular pipes. Four single concentric annular cross section and one multiple concentric annular cross section reactor configuration were studied. The theoretical head loss resulted higher than the observed in the laboratory model in some of the tests, and lower in others of them, depending also on the assumed value for the wall roughness. Most of the theoretical models assume that the fluid elements in all annular sections have the same velocity, and that flow is steady, uniform and one-dimensional, with the same pressure and velocity profiles in all reactor sections. To check the validity of such assumptions, a computational fluid dynamics (CFD) model of the concentric annular pipe reactor was implemented using the ANSYS Fluent software, demonstrating that pressure and flow velocity distribution inside the reactor actually is not uniform. Based on the analysis, the equations that predict better the head loss in single and multiple annular sections were obtained. Other factors that may impact the head loss, such as the generation of coagulants and gases during the electrochemical reaction, the accumulation of hydroxides inside the reactor, and the change of the electrode material with time, are also discussed. The results can be used as tools for design and scale-up of electrocoagulation reactors, to be integrated into new or existing water treatment plants.

Keywords: electrocoagulation reactors, hydraulic head loss, concentric annular pipes, computational fluid dynamics model

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Authors: B. R. Campomanes-Alvarez, P. Quiros, B. Fernandez

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Automatic Speech Recognition (ASR) is a machine-based process of decoding and transcribing oral speech. A typical ASR system receives acoustic input from a speaker or an audio file, analyzes it using algorithms, and produces an output in the form of a text. Some speech recognition systems use Hidden Markov Models (HMMs) to deal with the temporal variability of speech and Gaussian Mixture Models (GMMs) to determine how well each state of each HMM fits a short window of frames of coefficients that represents the acoustic input. Another way to evaluate the fit is to use a feed-forward neural network that takes several frames of coefficients as input and produces posterior probabilities over HMM states as output. Deep neural networks (DNNs) that have many hidden layers and are trained using new methods have been shown to outperform GMMs on a variety of speech recognition systems. Acoustic models for state-of-the-art ASR systems are usually training on massive amounts of data. However, audio files with their corresponding transcriptions can be difficult to obtain, especially in the Spanish language. Hence, in the case of these low-resource scenarios, building an ASR model is considered as a complex task due to the lack of labeled data, resulting in an under-trained system. Semi-supervised learning approaches arise as necessary tasks given the high cost of transcribing audio data. The main goal of this proposal is to develop a procedure based on acoustic semi-supervised learning for Spanish ASR systems by using DNNs. This semi-supervised learning approach consists of: (a) Training a seed ASR model with a DNN using a set of audios and their respective transcriptions. A DNN with a one-hidden-layer network was initialized; increasing the number of hidden layers in training, to a five. A refinement, which consisted of the weight matrix plus bias term and a Stochastic Gradient Descent (SGD) training were also performed. The objective function was the cross-entropy criterion. (b) Decoding/testing a set of unlabeled data with the obtained seed model. (c) Selecting a suitable subset of the validated data to retrain the seed model, thereby improving its performance on the target test set. To choose the most precise transcriptions, three confidence scores or metrics, regarding the lattice concept (based on the graph cost, the acoustic cost and a combination of both), was performed as selection technique. The performance of the ASR system will be calculated by means of the Word Error Rate (WER). The test dataset was renewed in order to extract the new transcriptions added to the training dataset. Some experiments were carried out in order to select the best ASR results. A comparison between a GMM-based model without retraining and the DNN proposed system was also made under the same conditions. Results showed that the semi-supervised ASR-model based on DNNs outperformed the GMM-model, in terms of WER, in all tested cases. The best result obtained an improvement of 6% relative WER. Hence, these promising results suggest that the proposed technique could be suitable for building ASR models in low-resource environments.

Keywords: automatic speech recognition, deep neural networks, machine learning, semi-supervised learning

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Authors: C. Fernandez-Plaza, I. Abad, E. Diaz, I. Diaz

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Births occurring before the 37th week of gestation are considered preterm births. A threat of preterm is defined as the beginning of regular uterine contractions, dilation and cervical effacement between 23 and 36 gestation weeks. To author's best knowledge, the factors that determine the beginning of the birth are not completely defined yet. In particular, the incidence of sleep habits on preterm births is weekly studied. The aim of this study is to develop a model to predict the factors affecting premature delivery on pregnancy, based on the above potential risk factors, including those derived from sleep habits and light exposure at night (introduced as 12 variables obtained by a telephone survey using two questionnaires previously used by other authors). Thus, three groups of variables were included in the study (maternal, fetal and sleep habits). The study was approved by Research Ethics Committee of the Principado of Asturias (Spain). An observational, retrospective and descriptive study was performed with 481 births between January 1, 2015 and May 10, 2016 in the University Central Hospital of Asturias (Spain). A statistical analysis using SPSS was carried out to compare qualitative and quantitative variables between preterm and term delivery. Chi-square test qualitative variable and t-test for quantitative variables were applied. Statistically significant differences (p < 0.05) between preterm vs. term births were found for primiparity, multi-parity, kind of conception, place of residence or premature rupture of membranes and interruption during nights. In addition to the statistical analysis, machine learning methods to look for a prediction model were tested. In particular, tree based models were applied as the trade-off between performance and interpretability is especially suitable for this study. C5.0, recursive partitioning, random forest and tree bag models were analysed using caret R-package. Cross validation with 10-folds and parameter tuning to optimize the methods were applied. In addition, different noise reduction methods were applied to the initial data using NoiseFiltersR package. The best performance was obtained by C5.0 method with Accuracy 0.91, Sensitivity 0.93, Specificity 0.89 and Precision 0.91. Some well known preterm birth factors were identified: Cervix Dilation, maternal BMI, Premature rupture of membranes or nuchal translucency analysis in the first trimester. The model also identifies other new factors related to sleep habits such as light through window, bedtime on working days, usage of electronic devices before sleeping from Mondays to Fridays or change of sleeping habits reflected in the number of hours, in the depth of sleep or in the lighting of the room. IF dilation < = 2.95 AND usage of electronic devices before sleeping from Mondays to Friday = YES and change of sleeping habits = YES, then preterm is one of the predicting rules obtained by C5.0. In this work a model for predicting preterm births is developed. It is based on machine learning together with noise reduction techniques. The method maximizing the performance is the one selected. This model shows the influence of variables related to sleep habits in preterm prediction.

Keywords: machine learning, noise reduction, preterm birth, sleep habit

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Authors: E. Mas de les Valls, M. Castells-Sanabra, R. Capdevila, N. Pla, Rosa M. Fernandez-Canti, V. de Medina, A. Mujal, C. Barahona, E. Velo, M. Vigo, M. A. Santos, T. Soto

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Absenteeism in universities, including polytechnical universities, is influenced by a variety of factors. Some factors overlap with those causing absenteeism in schools, while others are specific to the university and work-related environments. Indeed, these factors may stem from various sources, including students, educators, the institution itself, or even the alignment of degree curricula with professional requirements. In Spain, there has been an increase in absenteeism in polytechnical university studies, especially after the Covid crisis, posing a significant challenge for institutions to address. This study focuses on Universitat Politècnica de Catalunya• BarcelonaTech (UPC) and aims to quantify the current level of absenteeism and identify its main causes. The study is part of the teaching innovation project ASAP-UPC, which aims to minimize absenteeism through the redesign of teaching methodologies. By understanding the factors contributing to absenteeism, the study seeks to inform the subsequent phases of the ASAP-UPC project, which involve implementing methodologies to minimize absenteeism and evaluating their effectiveness. The study utilizes surveys conducted among students and polytechnical companies. Students' perspectives are gathered through both online surveys and in-person interviews. The surveys inquire about students' interest in attending classes, skill development throughout their UPC experience, and their perception of the skills required for a career in a polytechnical field. Additionally, polytechnical companies are surveyed regarding the skills they seek in prospective employees. The collected data is then analyzed to identify patterns and trends. This analysis involves organizing and categorizing the data, identifying common themes, and drawing conclusions based on the findings. This mixed-method approach has revealed that higher levels of absenteeism are observed in large student groups at both the Bachelor's and Master's degree levels. However, the main causes of absenteeism differ between these two levels. At the Bachelor's level, many students express dissatisfaction with in-person classes, perceiving them as overly theoretical and lacking a balance between theory, experimental practice, and problem-solving components. They also find a lack of relevance to professional needs. Consequently, they resort to using online available materials developed during the Covid crisis and attending private academies for exam preparation instead. On the other hand, at the Master's level, absenteeism primarily arises from schedule incompatibility between university and professional work. There is a discrepancy between the skills highly valued by companies and the skills emphasized during the studies, aligning partially with students' perceptions. These findings are of theoretical importance as they shed light on areas that can be improved to offer a more beneficial educational experience to students at UPC. The study also has potential applicability to other polytechnic universities, allowing them to adapt the surveys and apply the findings to their specific contexts. By addressing the identified causes of absenteeism, universities can enhance the educational experience and better prepare students for successful careers in polytechnical fields.

Keywords: absenteeism, polytechnical studies, professional skills, university challenges

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Authors: F. Uriel, M. M. Fernandez Liporace

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In the last decade, academic achievement in higher education has become a topic of agenda in Argentina, regarding the high figures of adjustment problems, academic failure and dropout, and the low graduation rates in the context of massive classes and traditional teaching methods. Psychological variables, such as perceived social support, academic motivation and learning styles and strategies have much to offer since their measurement by tests allows a proper diagnose of their influence on academic achievement. Framed in a major research, several studies analysed multiple samples, totalizing 5135 students attending Argentinean public universities. The first goal was aimed at the identification of statistically significant differences in psychological variables -perceived social support, learning styles, learning strategies, and academic motivation- by age, gender, and degree of academic advance (freshmen versus sophomores). Thus, an inferential group differences study for each psychological dependent variable was developed by means of student’s T tests, given the features of data distribution. The second goal, aimed at examining associations between the four psychological variables on the one hand, and academic achievement on the other, was responded by correlational studies, calculating Pearson’s coefficients, employing grades as the quantitative indicator of academic achievement. The positive and significant results that were obtained led to the formulation of different predictive models of academic achievement which had to be tested in terms of adjustment and predictive power. These models took the four psychological variables above mentioned as predictors, using regression equations, examining predictors individually, in groups of two, and together, analysing indirect effects as well, and adding the degree of academic advance and gender, which had shown their importance within the first goal’s findings. The most relevant results were: first, gender showed no influence on any dependent variable. Second, only good achievers perceived high social support from teachers, and male students were prone to perceive less social support. Third, freshmen exhibited a pragmatic learning style, preferring unstructured environments, the use of examples and simultaneous-visual processing in learning, whereas sophomores manifest an assimilative learning style, choosing sequential and analytic processing modes. Despite these features, freshmen have to deal with abstract contents and sophomores, with practical learning situations due to study programs in force. Fifth, no differences in academic motivation were found between freshmen and sophomores. However, the latter employ a higher number of more efficient learning strategies. Sixth, freshmen low achievers lack intrinsic motivation. Seventh, models testing showed that social support, learning styles and academic motivation influence learning strategies, which affect academic achievement in freshmen, particularly males; only learning styles influence achievement in sophomores of both genders with direct effects. These findings led to conclude that educational psychologists, education specialists, teachers, and universities must plan urgent and major changes. These must be applied in renewed and better study programs, syllabi and classes, as well as tutoring and training systems. Such developments should be targeted to the support and empowerment of students in their academic pathways, and therefore to the upgrade of learning quality, especially in the case of freshmen, male freshmen, and low achievers.

Keywords: academic achievement, academic motivation, coping, learning strategies, learning styles, perceived social support

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Authors: Jose A. Alvarez Aldegunde, Adrian Fernandez Sanchez, Matthew D. Menden, Bernardo Vila Rodriguez

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Up to five statistical pre-processings have been carried out considering the pollutant records of the stations present in Cartagena de Indias, Colombia, also taking into account the childhood asthma incidence surveys conducted in hospitals in the city by the Health Ministry of Colombia for this study. These pre-processings have consisted of different techniques such as the determination of the quality of data collection, determination of the quality of the registration network, identification and debugging of errors in data collection, completion of missing data and purified data, as well as the improvement of the time scale of records. The characterization of the quality of the data has been conducted by means of density analysis of the pollutant registration stations using ArcGis Software and through mass balance techniques, making it possible to determine inconsistencies in the records relating the registration data between stations following the linear regression. The results obtained in this process have highlighted the positive quality in the pollutant registration process. Consequently, debugging of errors has allowed us to identify certain data as statistically non-significant in the incidence and series of contamination. This data, together with certain missing records in the series recorded by the measuring stations, have been completed by statistical imputation equations. Following the application of these prior processes, the basic series of incidence data for respiratory disease and pollutant records have allowed the characterization of the influence of pollutants on respiratory diseases such as, for example, childhood asthma. This characterization has been carried out using statistical correlation methods, including visual correlation, simple linear regression correlation and spectral analysis with PAST Software which identifies maximum periodicity cycles and minimums under the formula of the Lomb periodgram. In relation to part of the results obtained, up to eleven maximums and minimums considered contemporary between the incidence records and the particles have been identified taking into account the visual comparison. The spectral analyses that have been performed on the incidence and the PM2.5 have returned a series of similar maximum periods in both registers, which are at a maximum during a period of one year and another every 25 days (0.9 and 0.07 years). The bivariate analysis has managed to characterize the variable "Daily Vehicular Flow" in the ninth position of importance of a total of 55 variables. However, the statistical correlation has not obtained a favorable result, having obtained a low value of the R2 coefficient. The series of analyses conducted has demonstrated the importance of the influence of pollutants such as PM2.5 in the development of childhood asthma in Cartagena. The quantification of the influence of the variables has been able to determine that there is a 56% probability of dependence between PM2.5 and childhood respiratory asthma in Cartagena. Considering this justification, the study could be completed through the application of the BenMap Software, throwing a series of spatial results of interpolated values of the pollutant contamination records that exceeded the established legal limits (represented by homogeneous units up to the neighborhood level) and results of the impact on the exacerbation of pediatric asthma. As a final result, an economic estimate (in Colombian Pesos) of the monthly and individual savings derived from the percentage reduction of the influence of pollutants in relation to visits to the Hospital Emergency Room due to asthma exacerbation in pediatric patients has been granted.

Keywords: Asthma Incidence, BenMap, PM2.5, Statistical Analysis

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Authors: Manon Frédout, Laëtitia Bucari, Mathias Aloui, Gaëtan Duhamel, Olivier Rovellotti, Javier Blanco

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Ecosystems must be resilient to ensure cleaner air, better water and soil quality, and thus healthier citizens. Technology can be an excellent tool to support urban ecosystem restoration projects, especially when based on Open Source and promoting Open Data. This is the goal of the ecoTeka application: one single digital tool for tree management which allows decision-makers to improve their urban forestry practices, enabling more responsible urban planning and climate change adaptation. EcoTeka provides city councils with three main functionalities tackling three of their challenges: easier biodiversity inventories, better green space management, and more efficient planning. To answer the cities’ need for reliable tree inventories, the application has been first built with open data coming from the websites OpenStreetMap and OpenTrees, but it will also include very soon the possibility of creating new data. To achieve this, a multi-source algorithm will be elaborated, based on existing artificial intelligence Deep Forest, integrating open-source satellite images, 3D representations from LiDAR, and street views from Mapillary. This data processing will permit identifying individual trees' position, height, crown diameter, and taxonomic genus. To support urban forestry management, ecoTeka offers a dashboard for monitoring the city’s tree inventory and trigger alerts to inform about upcoming due interventions. This tool was co-constructed with the green space departments of the French cities of Alès, Marseille, and Rouen. The third functionality of the application is a decision-making tool for urban planning, promoting biodiversity and landscape connectivity metrics to drive ecosystem restoration roadmap. Based on landscape graph theory, we are currently experimenting with new methodological approaches to scale down regional ecological connectivity principles to local biodiversity conservation and urban planning policies. This methodological framework will couple graph theoretic approach and biological data, mainly biodiversity occurrences (presence/absence) data available on both international (e.g., GBIF), national (e.g., Système d’Information Nature et Paysage) and local (e.g., Atlas de la Biodiversté Communale) biodiversity data sharing platforms in order to help reasoning new decisions for ecological networks conservation and restoration in urban areas. An experiment on this subject is currently ongoing with Montpellier Mediterranee Metropole. These projects and studies have shown that only 26% of tree inventory data is currently geo-localized in France - the rest is still being done on paper or Excel sheets. It seems that technology is not yet used enough to enrich the knowledge city councils have about biodiversity in their city and that existing biodiversity open data (e.g., occurrences, telemetry, or genetic data), species distribution models, landscape graph connectivity metrics are still underexploited to make rational decisions for landscape and urban planning projects. This is the goal of ecoTeka: to support easier inventories of urban biodiversity and better management of urban spaces through rational planning and decisions relying on open databases. Future studies and projects will focus on the development of tools for reducing the artificialization of soils, selecting plant species adapted to climate change, and highlighting the need for ecosystem and biodiversity services in cities.

Keywords: digital software, ecological design of urban landscapes, sustainable urban development, urban ecological corridor, urban forestry, urban planning

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Authors: Maria João Ferreira, Natalia Sierra-Garcia, Javier Cremades, Carla António, Ana M. Rodrigues, Helena Silva, Ângela Cunha

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Salicornia ramosissima, a halophyte that grows naturally in coastal areas of the northern hemisphere, is often considered the most promising halophyte candidate for extensive crop cultivation and saline agriculture practices. The expanding interest in this plant surpasses its use as gourmet food and includes their potential application as a source of bioactive compounds for the pharmaceutical industry. Despite growing well in saline soils, sustainable and ecologically friendly techniques to enhance crop production and the nutritional value of this plant are still needed. The root microbiome of S. ramosissima proved to be a source of taxonomically diverse plant growth-promoting bacteria (PGPB). Halotolerant strains of Bacillus, Salinicola, Pseudomonas, and Brevibacterium, among other genera, exhibit a broad spectrum of plant-growth promotion traits [e.g., 3-indole acetic acid (IAA), 1-aminocyclopropane-1-carboxylic acid (ACC) deaminase, siderophores, phosphate solubilization, Nitrogen fixation] and express a wide range of extracellular enzyme activities. In this work, three plant growth-promoting bacteria strains (Brevibacterium casei EB3, Pseudomonas oryzihabitans RL18, and Bacillus aryabhattai SP20) isolated from the rhizosphere and the endosphere of S. ramosissima roots from different saltmarshes along the Portuguese coast were inoculated in S. ramosissima seeds. Plants germinated from inoculated seeds were grown for three months in pots filled with a mixture of perlite and estuarine sediment (1:1) in greenhouse conditions and later transferred to a growth chamber, where they were maintained two months with controlled photoperiod, temperature, and humidity. Pots were placed on trays containing the irrigation solution (Hoagland’s solution 20% added with 10‰ marine salt). Before reaching the flowering stage, plants were collected, and the fresh and dry weight of aerial parts was determined. Non-inoculated seeds were used as a negative control. Selected dried stems from the most promising treatments were later analyzed by GC-TOF-MS for primary metabolite composition. The efficiency of inoculation and persistence of the inoculum was assessed by Next Generation Sequencing. Inoculations with single strain EB3 and co-inoculations with EB3+RL18 and EB3+RL18+SP20 (All treatment) resulted in significantly higher biomass production (fresh and dry weight) compared to non-inoculated plants. Considering fresh weight alone, inoculation with isolates SP20 and RL18 also caused a significant positive effect. Combined inoculation with the consortia SP20+EB3 or SP20+RL18 did not significantly improve biomass production. The analysis of the profile of primary metabolites will provide clues on the mechanisms by which the growth-enhancement effect of the inoculants operates in the plants. These results sustain promising prospects for the use of rhizospheric and endophytic PGPB as biofertilizers, reducing environmental impacts and operational costs of agrochemicals and contributing to the sustainability and cost-effectiveness of saline agriculture. Acknowledgments: This work was supported by project Rhizomis PTDC/BIA-MIC/29736/2017 financed by Fundação para a Ciência e Tecnologia (FCT) through the Regional Operational Program of the Center (02/SAICT/2017) with FEDER funds (European Regional Development Fund, FNR, and OE) and by FCT through CESAM (UIDP/50017/2020 + UIDB/50017/2020), LAQV-REQUIMTE (UIDB/50006/2020). We also acknowledge FCT/FSE for the financial support to Maria João Ferreira through a PhD grant (PD/BD/150363/2019). We are grateful to Horta dos Peixinhos for their help and support during sampling and seed collection. We also thank Glória Pinto for her collaboration providing us the use of the growth chambers during the final months of the experiment and Enrique Mateos-Naranjo and Jennifer Mesa-Marín of the Departamento de Biología Vegetal y Ecología, the University of Sevilla for their advice regarding the growth of salicornia plants in greenhouse conditions.

Keywords: halophytes, PGPB, rhizosphere engineering, biofertilizers, primary metabolite profiling, plant inoculation, Salicornia ramosissima

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