Spatially structured information in attractor neural networks using metric connectivity

Tesis doctoral inédita. Universidad Autónoma de Madrid, Escuela Politécnica Superior, departamento de Ingeniería Informática, noviembre de 201

Ensemble of diluted attractor networks with optimized topology for fingerprint retrieval

The present study analyzes the retrieval capacity of an Ensemble of diluted Attractor Neural Networks for real patterns (i.e., non-random ones), as it is the case of human fingerprints. We explore the optimal number of Attractor Neural Networks in the ensemble to achieve a maximum fingerprint storage capacity. The retrieval performance of the ensemble is measured in terms of the network connectivity structure, by comparing 1D ring to 2D cross grid topologies for the random shortcuts ratio. Given the nature of the network ensemble and the different characteristics of patterns, an optimization can be carried out considering how the pattern subsets are assigned to the ensemble modules. The ensemble specialization splitting into several modules of attractor networks is explored with respect to the activities of patterns and also in terms of correlations of the subsets of patterns assigned to each module in the ensemble network.This work was funded by and UDLA-SIS.MGR.20.01. This research was also funded by the Spanish Ministry of Science and Innovation/FEDER, under the \RETOS" Programme, with grant numbers: TIN2017-84452-R and RTI2018-098019-B-I00; and by the CYTED Network \Ibero-American Thematic Network on ICT Applications for Smart Cities", grant number: 518RT0559

Forecasting Amazon Rain-Forest Deforestation Using a Hybrid Machine Learning Model

The present work aims to carry out an analysis of the Amazon rain-forest deforestation, which can be analyzed from actual data and predicted by means of artificial intelligence algorithms. A hybrid machine learning model was implemented, using a dataset consisting of 760 Brazilian Amazon municipalities, with static data, namely geographical, forest, and watershed, among others, together with a time series data of annual deforestation area for the last 20 years (1999–2019). The designed learning model combines dense neural networks for the static variables and a recurrent Long Short Term Memory neural network for the temporal data. Many iterations were performed on augmented data, testing different configurations of the regression model, for adjusting the model hyper-parameters, and generating a battery of tests to obtain the optimal model, achieving a R-squared score of 87.82%. The final regression model predicts the increase in annual deforestation area (square kilometers), for a decade, from 2020 to 2030, predicting that deforestation will reach 1 million square kilometers by 2030, accounting for around 15% compared with the present 1%, of the between 5.5 and 6.7 millions of square kilometers of the rain-forest. The obtained results will help to understand the impact of man’s footprint on the Amazon rain-forest.This research was funded by DGIV-UDLA grant number SIS.MGR.21.01 and by Spanish Ministry of Science grant number PID2020-114867RB-I00

Urban Traffic Flow Mapping of an Andean Capital: Quito, Ecuador

[EN] Several efforts have been devoted to developing sustainable cities to address global environmental challenges and the growth of urban areas. In particular, transportation has various issues such as air pollution, noise, and traffic, which have to be addressed by collecting significant information of the traffic and road conditions of the cities. Automating the data extraction process and street network construction will allow building more useful models to study traffic behavior. This work presents a network modeling approach to identify interest points (extreme and internal) of the city, through a winner-takes-all edge trimming, and mapping the traffic flow between them. Such points can be considered as entries of an Origin-Destination matrix, where such information can be used to model traffic behavior between interest points. The case study of Quito, Ecuador is considered. Besides, to address environmental issues, this paper encourages the replacement of internal combustion taxis with electric vehicles. From the understanding of the vehicle traffic behavior, a pre-feasibility siting of electric taxi (ET) charging stations was carried out. The results will allow performing the sizing of each charging station considering electric power network constraints. This work aims to ensure a sustainable transportation system based on this crucial information.This work was supported in part by the Universidad de Las Americas, Quito, Ecuador, under Project SIS.JCG.19.03 and Project SIS.MGR.20.01, and in part by the CYTED Network Ibero-American Thematic Network on ICT Applications for Smart Cities under Grant 518RT0559.González-Rodríguez, MS.; Clairand, J.; Soto-Espinosa, K.; Jaramillo-Fuelantala, J.; Escrivá-Escrivá, G. (2020). Urban Traffic Flow Mapping of an Andean Capital: Quito, Ecuador. IEEE Access. 8:195459-195471. https://doi.org/10.1109/ACCESS.2020.3033518S195459195471

Guidelines to Establish an Office of Student Accessibility Services in Higher Education Institutions

The objective of this paper is to propose a set of guidelines to establish an office of Student Accessibility Services (SAS) in Higher Education Institutions (HEIs). The proposed guidelines help to integrate disjointed knowledge to facilitate its interpretation and implementation during deployment of basic support services in favor of students with disability. These guidelines can help to mitigate complexity in providing SAS for the first time in HEIs. These guidelines cover both the design and implementation of an office of SAS and its management. Knowledge was found through a multivocal literature review (MLR), which allowed to capture not only academic approaches but also vantage points and experiences from practice. Key concepts and aspects were organized into eight components (five related to the design and implementation, and three associated with the management context). An expert appraisal method was used as a proof of concept, which complemented a previously performed preliminary implementation example. Obtained results demonstrated the pertinence of the conceptual proposal and confirmed guidelines capability for full implementation in a real-world scenario.This research work has been co-funded by the Erasmus+ Programme of the European Union, project EduTech (609785-EPP-1-2019-1-ES-EPPKA2-CBHE-JP)

Design of a HACCP Plan for Vacuum-Packed Beef Cuts

Objective: To elaborate a HACCP plan, for the process of vacuum-packed cuts of meat, in a federal inspection type trail (TIF) located in the East of the State of Mexico, in order to improve its hygiene and safety conditions. Design / Methodology / approach: The research has a mixed approach that consists of two phases, a field phase where the HACCP methodology was applied in terms of reviewing the activities carried out in the company, the second phase is a cabinet where they were analyzed the hazards identified during the first phase, in order to determine if the hazard found is significant for the safety of the food, to finally conclude whether or not it is a critical control point (CCP). Results: A PCC (Critical Control Point) was identified, in the metal detection phase, the identified hazards were: the passage of metal chips from the transfer rails, pieces of knives or saws and pieces of needles coming from previous steps in the process. Study limitations / implications: Bibliographic documentation on meat cut case studies as well as the management of their CCPs is limited. Findings / Conclusions: The PCC1 Metal Detection is a control measure carried out by the company, however when analyzing it, an opportunity for improvement in the current operation was evidenced, so the adaptation of formats for records that allowed monitoring was also proposed. and verify the control of the PCC.Objective: To elaborate a Hazard Analysis and Critical Control Points (HACCP) plan for the process of vacuum-packed beef cuts, in a Federal Inspection Type (FIT) meat processor located in eastern Estado de México, with the aim of improving its conditions of hygiene and innocuousness. Design/Methodology/Approximation: The activities performed in the business were revised applying the HACCP methodology and the dangers identified were analyzed, to determine whether the danger found was significant for the innocuousness of the food, finally concluding if it represented, or not, a critical control point (CCP). Results: A CCP was identified in the phase of metal detection, the dangers identified were the passing of metal      shards from the transport rails, pieces of knives or saws, and pieces of needles from prior steps in the process. Study limitations/implications: Documentation about case studies of beef cuts, as well as about management of their CCP is limited. Findings/Conclusions: The CCP1 Metal Detection is a control measure that the business performs; however, under analysis, there was evidence of an opportunity to improve the current operation, which is why the adaptation of registry formats that could allow monitoring and controlling the CCP was proposed

Age-Adjusted Endothelial Activation and Stress Index for Coronavirus Disease 2019 at Admission Is a Reliable Predictor for 28-Day Mortality in Hospitalized Patients With Coronavirus Disease 2019

Background: Endothelial Activation and Stress Index (EASIX) predict death in patients undergoing allogeneic hematopoietic stem cell transplantation who develop endothelial complications. Because coronavirus disease 2019 (COVID-19) patients also have coagulopathy and endotheliitis, we aimed to assess whether EASIX predicts death within 28 days in hospitalized COVID-19 patients. Methods: We performed a retrospective study on COVID-19 patients from two different cohorts [derivation (n = 1,200 patients) and validation (n = 1,830 patients)]. The endpoint was death within 28 days. The main factors were EASIX [(lactate dehydrogenase * creatinine)/thrombocytes] and aEASIX-COVID (EASIX * age), which were log2-transformed for analysis. Results: Log2-EASIX and log2-aEASIX-COVID were independently associated with an increased risk of death in both cohorts (p 7) of 47.6% (95% CI = 44.2-50.9%). The cutoff of log2 aEASIX-COVID = 6 showed a positive predictive value of 31.7% and negative predictive value of 94.7%, and log2 aEASIX-COVID = 7 showed a positive predictive value of 47.6% and negative predictive value of 89.8%. Conclusion: Both EASIX and aEASIX-COVID were associated with death within 28 days in hospitalized COVID-19 patients. However, aEASIX-COVID had significantly better predictive performance than EASIX, particularly for discarding death. Thus, aEASIX-COVID could be a reliable predictor of death that could help to manage COVID-19 patients.This study was supported by grants from Instituto de Salud Carlos III [grant number COV20/1144 [MPY224/20) to AF-R/MÁJ-S]. MÁJ-S and AF-R are supported by Instituto de Salud Carlos III (grant numbers CP17CIII/00007 and CP14CIII/00010, respectively).S

Seminario de Economía Mexicana

Serie de ponencias referentes al Seminario de Economía Mexicana. Memorias del Seminario de Economía Mexicana de 199

The polygenic basis of relapse after a first episode of schizophrenia

Little is known about genetic predisposition to relapse. Previous studies have linked cognitive and psychopathological (mainly schizophrenia and bipolar disorder) polygenic risk scores (PRS) with clinical manifestations of the disease. This study aims to explore the potential role of PRS from major mental disorders and cognition on schizophrenia relapse. 114 patients recruited in the 2EPs Project were included (56 patients who had not experienced relapse after 3 years of enrollment and 58 patients who relapsed during the 3-year follow-up). PRS for schizophrenia (PRS-SZ), bipolar disorder (PRS-BD), education attainment (PRS-EA) and cognitive performance (PRS-CP) were used to assess the genetic risk of schizophrenia relapse.Patients with higher PRS-EA, showed both a lower risk (OR=0.29, 95% CI [0.11–0.73]) and a later onset of relapse (30.96± 1.74 vs. 23.12± 1.14 months, p=0.007. Our study provides evidence that the genetic burden of neurocognitive function is a potentially predictors of relapse that could be incorporated into future risk prediction models. Moreover, appropriate treatments for cognitive symptoms appear to be important for improving the long-term clinical outcome of relapse

Prodromal symptoms and the duration of untreated psychosis in first episode of psychosis patients: what differences are there between early vs. adult onset and between schizophrenia vs. bipolar disorder?

To assess the role of age (early onset psychosis-EOP < 18 years vs. adult onset psychosis-AOP) and diagnosis (schizophrenia spectrum disorders-SSD vs. bipolar disorders-BD) on the duration of untreated psychosis (DUP) and prodromal symptoms in a sample of patients with a first episode of psychosis. 331 patients with a first episode of psychosis (7–35 years old) were recruited and 174 (52.6%) diagnosed with SSD or BD at one-year follow-up through a multicenter longitudinal study. The Symptom Onset in Schizophrenia (SOS) inventory, the Positive and Negative Syndrome Scale and the structured clinical interviews for DSM-IV diagnoses were administered. Generalized linear models compared the main effects and group interaction. 273 AOP (25.2 ± 5.1 years; 66.5% male) and 58 EOP patients (15.5 ± 1.8 years; 70.7% male) were included. EOP patients had significantly more prodromal symptoms with a higher frequency of trouble with thinking, avolition and hallucinations than AOP patients, and significantly different median DUP (91 [33–177] vs. 58 [21–140] days; Z = − 2.006, p = 0.045). This was also significantly longer in SSD vs. BD patients (90 [31–155] vs. 30 [7–66] days; Z = − 2.916, p = 0.004) who, moreover had different profiles of prodromal symptoms. When assessing the interaction between age at onset (EOP/AOP) and type of diagnosis (SSD/BD), avolition was significantly higher (Wald statistic = 3.945; p = 0.047), in AOP patients with SSD compared to AOP BD patients (p = 0.004). Awareness of differences in length of DUP and prodromal symptoms in EOP vs. AOP and SSD vs. BD patients could help improve the early detection of psychosis among minors