Sistema Regional de Información
en línea para Revistas Científicas de América Latina,
el Caribe, España y Portugal

The global COVID-19 pandemic has shocked the world. Since the virus gave rise to health problems and often ended in deaths, the count of the contagion and the deceased has been an open issue. Such statistics are vital for every nation and even every city or district and suburb as these numbers decide the level of intervention and the subsequent reduction of its given spread. Worldwide data show a mortality rate of around two percent prior to successful vaccination campaigns. However, Ecuador's statistical data indicate an abnormal amount of excess mortality, which is officially denied in each of the studied countries. These numbers have been projected on a monthly basis and exceed up to 300% of the official COVID-19 deaths. In particular, the average mortality rate in Ecuador, prior to and close to the pandemic, has been about 6083.4±234.6, while in the worst month during the sanitary crisis, deaths piled up to 21,000 people, and only 1180 were recognized as deceased by COVID-19. The reasons are widespread but based on an insufficient financed health sector, political incompetence, lack of leadership, and a long-lasting economic crisis. Therefore, premature endings of confinements or lockdowns have contributed to an accelerated contagion and seem to even counteract the vaccination phase, in middle 2021, shortly before excess mortality ceased completely.

Blood cell analysis is an important part of the health and immunity assessment. There are three major components of the blood: red blood cells, white blood cells, and platelets. The count and density of these blood cells are used to find multiple disorders like blood infections (anemia, leukemia, among others). Traditional methods are time-consuming, and the test cost is high. Thus, it arises the need for automated methods that can detect different kinds of blood cells and count the number of cells. A convolutional neural network-based framework is proposed for detecting and counting the cells. The neural network is trained for the multiple iterations, and a model having lower validation loss is saved. The experiments are done to analyze the performance of the detection system and results with high accuracy in the counting of the cells. The mean average precision is achieved when compared to ground truth provided to respective labels. The value of the average precision is found to be ranging from 70% to 99.1%, with a mean average precision value of 85.35%. The proposed framework had much less time complexity: it took only 0.111 seconds to process an image frame with dimensions of 640×480 pixels. The system can also be implemented in low-cost, single-board computers for rapid prototyping. The efficiency of the proposed framework to identify and count different blood cells can be utilized to assist medical professionals in finding disorders and making decisions based on the obtained report.

[Objective] This study seeks to characterize the specialized mathematical knowledge that preservice teachers make use of when solving tasks that involve comparison of areas of flat figures. [Methodology] Seventy (70) preservice teachers, in the third year of the Primary Education degree at the Universidad Autónoma de Barcelona during the period 2020-21, participated in the study. Preservice teachers answered a semi-structured open-ended questionnaire, which included eight tasks. A qualitative content analysis was carried out to analyze the procedures and justifications used by preservice teachers when solving two tasks. The analysis focuses on two of the subdomains of the Mathematics Teacher’s Specialized Knowledge model, Knowledge of Topics and of the Structure of Mathematics. [Results] The use of procedures related to the decomposition and reorganization of surfaces facilitates making use of categories of specialized knowledge, and establishing connections with other types of mathematical content. Furthermore, coordination of different registers of representation makes it possible to establish intra conceptual connections in the solution of the two tasks presented. [Conclusions] Representations, in their discursive and non-discursive registers, are presented as key indicators which assist in making explicit the procedures used by preservice teachers, and based on them, the justifications, properties and geometric principles that support the resolution process.

[Objective] The objective of this study was to analyze the cognitive and social skills of a group of students and their teacher in an exercise based on Collaborative Problem Solving (CPR) in Mathematics. [Methodology] A study was carried out by selecting one of the 8 groups of 4 students randomly assigned in a non-curricular exercise scheduled in 24 biweekly sessions of 90 minutes. The group selected consisted of 4 female students. The sessions were recorded, and data on the interactions between subjects (students and teacher) were coded at the beginning and at the end of the exercise for factors including skills of representation, regulation, communication and roles assumed in group work, and interaction with the teacher. The coded data were subsequently analyzed using asymmetric graph analysis techniques to measure the intensity of interactions, and correspondence analysis to determine the significance of relationships between the sub-skills involved. Rstudio software was used to carry out the analysis. [Results] A significant change in the intensity of interactions between participants was observed throughout the implementation with respect to the centrality and closeness indices associated with the graphs obtained. [Conclusions] The systematic CPR work in mathematics carried out in the exercise promotes and modifies social and cognitive skills and their interaction.

In this paper we propose a new method for symmetry calculation in wearable devices. The problem in this domain is that only discrete features such as stride length, stride duration, or duration of gait phases are used for the symmetry calculation. However, this can lead to failures, since the use of features can result in partial loss of information from the time series. From this we present a possibility to calculate the symmetry by using Dynamic Time Warping (DTW). DTW uses the complete time series for the analysis and is therefore independent of certain features.

To unfold the energy spectrum of two kilovoltage (kV) X-ray beams from transmission curves through a mathematical methodology based on Laplace transform and the generalized simulated annealing algorithm. Energy spectra of photon beams and transmission data were associated by means of a mathematical expression derived from the analytical solution of Laplace transform. Transmission data was calculated by relating the air kerma of the attenuated beams, passing through aluminium plates of different thickness, to that of the non-attenuated beam. Generalized simulated annealing function, developed in an early work, was employed to find the parameters of the expression and so determine the spectra. Validation of the methodology was done by the comparison of the half-value layers obtained from transmission curves and the spectra. The mean square percentage error between transmission data and fitting curve of each spectrum defined from the parameters found was lower than 1% indicating a good adjustment. The same error was observed when the first half-value layer (HVL) from the transmission curves and those of each reconstructed spectrum were compared. Calculation time of parameters was 5 sec for 80 kV and 14 sec for 120 kV. In no case, non-realistic solution of energy spectra was obtained. These results were better than an early work where least-squares were used. The reconstruction methodology based on generalized simulated annealing employed in this manuscript can efficiently derive the spectra of two X-ray beams with comparable accuracy to previous work. A limitation is that validation was not done by comparing data with the equipment’s spectra.

Recently, measurement uncertainty estimation has become a topic of great interest for the reporting of greenhouse gas (GHG) inventories in Costa Rica. In this context, a national methodological guide published by the National Carbon Neutrality Program (PPCN, for its Spanish acronym) has emerged as the basis for the local development of this issue. However, a few aspects of its content lack a clear explanation to justify its implementation. The present study assesses the validity of the use of correction factors, proposed by this guide, that enlarges the standard uncertainty estimated from a triangular distribution, in the presence of a 95 % coverage interval. To achieve this, 3124 triangular distribution scenarios were simulated. Two standard uncertainties were estimated for each scenario: one considering that the simulated limits delimit a 100 % coverage interval (u100) and another considering a 95 % coverage interval (u95), with two possible interpretations about the location of the interval being considered for the latter. The correction factors FC were estimated for four different groups of scenarios as the slopes between u95 and u100 with a least-squares regression using R statistical software. Results between 1.23 and 1.29 were obtained, with a global value of 1.25. These values ​​are consistent with those found in the national methodological guide, thus verifying their validity and applicability. Finally, the use of the correction factor of 1.25 is suggested as a practical approximation for all the evaluated scenarios, which is expected to facilitate its implementation by users.

It is necessary to analyze pedestrian behavior at crossings to improve their safety and mobility. Mid-block pedestrian crossings are structures that facilitate the mobility of pedestrians, safeguarding them from vehicular traffic; however, illegal crossing by pedestrians is an everyday occurrence and represents a risk to their safety. The purpose of this study is to evaluate the relationship between different human and road factors and the decision to illegally cross signalized mid-block crossings. Several human factors such as age, gender, waiting time in traffic light, use of the pushbutton and individual or group crossing, as well as road characteristics such as the length of traffic light phase, length of crossing, and vehicular volume were analyzed. To collect information about these variables this study recorded a one-hour video in six selected crosswalks within the Montes de Oca County in Costa Rica. A total of 1,707 crossings were recorded, 10.6% of which corresponded to instances of illegal crossing. After applying a logit model, this research found that traffic volume, pedestrian red-light time, waiting time, vehicle illegal crossing and group crossings reduced the probability of violations by pedestrians. On the other hand, minimum traffic light time and crossing length increased the possibility of pedestrian illegal crossings. This study concluded that the traffic light cycle is an important variable that must be rigorously analyzed to ensure pedestrian's compliance with traffic lights, which will improve the safety of the pedestrian mid-block crossings.

Costa Rica has approximately 1 500 km of coastline, with wetlands that offer a wide variety of ecosystem services, including coastal protection. The quantification of this service requires research in these wetlands, and for this, it is necessary to gather them in an inventory that includes their localization and basic characteristics. This type of inventory does not exist specifically for coastal wetlands in Costa Rica. Thus, the objective of this research is to create the first version of an inventory of wetlands that offer coastal protection in the country. The National Wetland Inventory (INH), and a 2005 mangrove cartography were used as the starting point. The coastal wetlands that were not included in these two sources were identified with a semi-automatic procedure, based on the analysis of vegetation indexes derived from a Sentinel 2 satellite image, and a manual delimitation using an ortophoto of 2017. The new inventory includes 464 coastal wetlands, from which 180 are not included in the INH. These new areas were characterized with the same information included in the INH, to assure the compatibility between both databases. In addition, all 464 wetlands were characterized with some of the natural and anthropic conditions that might affect future research related to coastal protection. The result is a free access geographic database that includes the localization and general characteristics of the Costa Rican wetlands that offer coastal protection, and could be used in future research not only in this topic, but in coastal studies in general.

The use of standard procedures and methodologies for nonlinear dynamic analysis (NLDA) is increasing. In NLDA guidelines, many aspects are open to expert judgement, and alternative interpretations can be adopted; such is the case of the selection of the input ground motions. In Eurocode 8 (EC8), for example, a group of ground motions can be chosen and scaled so that their response spectra appropriately represent the target design spectrum and spectral matching techniques can be applied. However, the EC8 and other seismic codes do not take into account relevant seismic parameters or different intensity measures on the selection procedure. Inappropriate selection of seismic actions can lead to unrealistic results. This study aims to analyse the influence of the Arias intensity and the significant duration of spectral matched records on NLDA. Particularly, variations in the damage of a building were studied using four different accelerograms adjusted to a specific design spectrum. Results have shown significant differences in the expected structural damage. Records with larger Arias intensity and significant durations resulted in a greater structural damage, even though they all share the same response spectrum. It is concluded that these parameters should be also taken into account in the selection of design ground motions for NLDA.