Design of a Monitoring System for the identification of Gas Concentration in the district of Mi Perú – Callao, Perú

In recent years, the contamination of toxic gases in society is a very controversial problem because of the various consequences and effects they generate on health. There are several studies which highlight that the main polluting gases to the environment such as carbon monoxide, lead, cadmium, among others are the main causes of the increase in various acute diseases, such as pneumonia, or chronic diseases, such as cardiovascular diseases or lung cancer. That is why, faced with this problem, this research work proposes a monitoring system that determines the concentration of toxic gases, in such a way that it can contribute as an informative medium which can be implemented in various focused points where high rates of pollution are concentrated. The system has a very efficient MQ 135 gas sensor which includes a reading of 5 to 600 ppm (parts per million) at 3m with a temperature of 25ºC. It should be noted that it is important to keep the sensor on 24 hours beforehand to obtain a correct reading. Thus, concluding that this system of toxic gases can be easily applied to society because it is economical and because it has a free software which will be responsible for informing through a web server the level of ppm that you want to analyze at a certain point. Keywords- Toxic Gases, Pollution, Gas Sensor, Environment, Air Quality

Low-Cost Education Kit for Teaching Basic Skills for Industry 4.0 Using Deep-Learning in Quality Control Tasks

The main purposes of this paper are to offer a low-cost solution that can be used in engineering education and to address the challenges that Industry 4.0 brings with it. In recent years, there has been a great shortage of engineering experts, and therefore it is necessary to educate the next generation of experts, but the hardware and software tools needed for education are often expensive and access to them is sometimes difficult, but most importantly, they change and evolve rapidly. Therefore, the use of cheaper hardware and free software helps to create a reliable and suitable environment for the education of engineering experts. Based on the overview of related works dealing with low-cost teaching solutions, we present in this paper our own low-cost Education Kit, for which the price can be as low as approximately EUR 108 per kit, for teaching the basic skills of deep learning in quality-control tasks in inspection lines. The solution is based on Arduino, TensorFlow and Keras, a smartphone camera, and is assembled using LEGO kit. The results of the work serve as inspiration for educators and educational institutions.

The Neuroscience Experiments System (NES)–A Software Tool to Manage Experimental Data and Its Provenance

Computational tools can transform the manner by which neuroscientists perform their experiments. More than helping researchers to manage the complexity of experimental data, these tools can increase the value of experiments by enabling reproducibility and supporting the sharing and reuse of data. Despite the remarkable advances made in the Neuroinformatics field in recent years, there is still a lack of open-source computational tools to cope with the heterogeneity and volume of neuroscientific data and the related metadata that needs to be collected during an experiment and stored for posterior analysis. In this work, we present the Neuroscience Experiments System (NES), a free software to assist researchers in data collecting routines of clinical, electrophysiological, and behavioral experiments. NES enables researchers to efficiently perform the management of their experimental data in a secure and user-friendly environment, providing a unified repository for the experimental data of an entire research group. Furthermore, its modular software architecture is aligned with several initiatives of the neuroscience community and promotes standardized data formats for experiments and analysis reporting.

TRANSFORMATION OF FREE AND OPEN SOURCE SOFTWARE DEVELOPMENT PROJECTS: GOVERNANCE BETWEEN THE CATHEDRAL AND BAZAAR

ABSTRACT It is common for community-based free software projects to be associated with an organizational scenario that resembles “a bazaar more than a cathedral,” and to differ from the traditional, or ‘bureaucratic’ way of organizing work. This paper analyzes the governance of these organizations from the perspective of their structure and control, considering the development trajectory of three community-based free software projects in Brazil. Results show that the constant need to produce modern technologies gives rise to external pressures that promote change - albeit temporary - in the governance of these projects, making them resemble a cathedral more than a bazaar. Governance does not follow a cycle of sequential improvement; it changes depending on the external organizational actors present, such as sponsors. This suggests the need for strategic and flexible governance to deal with the acquisition and allocation of organizational resources. Governance of the projects described here varies along a spectrum of (in)formality that allows both production models - cathedral or bazaar - to exist in the same organization at different periods.

Energy efficiency using Distributed Generation; Cafeteria of Engineer Faculty Campeche, Mexico

In the present work, an integral design of the cafeteria located at Faculty of Engineering of Autonomous University of Campeche is carried out. Four scenarios of Photo Voltaic (PV) generation have been studied. A 14 PV modules arrangement of 440 each, with azimuthal angle of 180º and a slope angle of 15º; the other is similar to the previous, but the slope angle was 19.85º. The following was a 24 PV modules arrangement of 440, with an azimuthal angle of 218º and a slope angle of 15º. The last arrangement consists of 24 PV modules arrangement of 440, with azimuthal angle of 218º and a slope angle of 19.85º. Where all of them are associated with the economic aspect to obtain greater efficiency of the plant with minimum recovery time. The free software System Advisor Model (SAM) developed by the National Renewable Energy Laboratory (NREL) has been employed. Complete seasonal analysis has also been performed considering Gran Demanda Media Ordinaria en México (GDMO de CFE in Mexico) within the period January 2020 to March 2021. The best results are energy generation 17,570 kWh. Capacity factor 19%. Energy performance 1,671 kWh/kW. Performance relation 0.74. Leveled cost 5.39 ¢/kWh. And return on investment in 0.6 years. The GD-PV plant prevents the emission into the atmosphere of 778.85 kg of CO2 equivalent.

An Introduction to Factored Regression Models with Blimp

In this paper, we provide an introduction to the factored regression framework. This modeling framework applies the rules of probability to break up or “factor” a complex joint distribution into a product of conditional regression models. Using this framework, we can easily specify the complex multivariate models that missing data modeling requires. The article provides a brief conceptual overview of factored regression and describes the functional notation used to conceptualize the models. Furthermore, we present a conceptual overview of how the models are estimated and imputations are obtained. Finally, we discuss how users can use the free software package, Blimp, to estimate the models in the context of a mediation example.

Methodology of Calculating the Number of Trees Based on ALS Data for Forestry Applications for the Area of Samławki Forest District

Airborne Laser Scanning (ALS) is a technology often used to study forest areas. The main area of application of ALS in forests is collecting data to determine the height of individual trees and entire stands, tree density and stand biomass. The content of the ALS data is also classified, i.e., registered objects are identified, including the species affiliation of individual trees. Important information for forest districts includes other parameters related to the structure and share of stands and the number of trees in the forest district. The main goal of this study was to propose the new ALS data processing methodology for detecting single trees in the Samławki Forest District. The idea of the proposed methodology is to indicate a free and accessible solution for any user (at least in Poland). This new ALS data processing methodology contributes to research on the use of ALS data in forest districts to maintain up-to-date and accurate stand statistics. This methodology was based on free data from the geoportal.gov.pl portal and free software, which allowed to minimize the costs of preparing data for the needs of forestry activities. In cooperation with the Samławki Forest District, the proposed methodology was used to detect the number and heights of trees for two forest addresses 13b and 30a, and then to calculate the volume of stands. As a result, the volume of the analyzed stands was calculated, obtaining values differing from the nominal ones included in the FMP (Forest Management Plan) by about 25% and 5%, respectively, for larch and oak.

Predicted Symptomatic Effectiveness of Pfizer-BioNTech BNT162b2 Vaccine Against Omicron Variant of SARS-CoV-2

This paper presents predictions of the symptomatic effectiveness of the Pfizer-BioNTech BNT162b2 (Comirnaty) vaccine against Omicron B.1.1.529, the latest SARS-CoV-2 variant of concern. They were obtained assuming fold decreases in Omicron neutralisation by vaccine-induced antibodies versus neutralisation of the virus Wild Type. A 25-fold decrease was assumed based on Omicron pseudovirus neutralisation study by Pfizer and BioNTech; a 94-fold, based on live-Omicron neutralisation study in South Africa; and 40, 80 and 120 folds, hypothesised based on genetic information. The effectiveness of two vaccine doses was predicted as 66% (42, 86), 48% (25, 72) and 42% (20, 66) for up to five months starting 2-4 weeks after the second dose, for the 25, 80 and 120 folds, respectively. The effectiveness of booster vaccination was predicted under a highly conservative assumption that the third dose would increase neutralisation by only 3.3 folds compared to the second dose. The predictions of effectiveness for up to five months, starting 2-4 weeks after the third dose, were 81% (59, 95), 67% (43, 87) and 61% (37, 82) for the 25, 80 and 120 folds, respectively. Despite the large fold decreases considered, the vaccine could still provide substantial protection, particularly after a booster and against severe disease. The paper is accompanied by free software which can be used to predict the symptomatic effectiveness of Comirnaty against Omicron under different neutralisation folds, including those obtained experimentally.