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

Context: Inventory control and distribution are key processes in the loss of both efficiency and effectiveness in the field of logistics at the global level. According to the Colombian National Planning Department, for the year 2020, the items of transportation, storage, and inventory account for 73.9% of the total logistics costs. Solving the multi-vehicle Inventory Routing Problem (IRP) is an alternative to making cycle times shorter, more flexible, and less expensive. Method: This article describes and compares mathematical models in the literature for the basic problem, adapting it to its multi-vehicle variant and solving it by means of mixed-integer programming models, via the solution of instances of low and medium mathematical complexity, proposing two ways to manage the inventory and three ways to eliminate the creation of sub-tours. To obtain the results, the AMPL software is used in a computer with an Intel Core i5-5200U CPU@ 2.2 GHz processor and 4 GB RAM, considering a maximum runtime of one hour. Results: The flow model shows the best performance in terms of computational times and response quality regarding the maximum level (ML) policy, and the MTZ variant is the second-best model. Finally, the overall variation exhibits longer execution times and higher GAP values. The models perform well for small- and medium-sized instances. Conclusions: This research presents a general methodology that can be adapted to different applications of the integrated problem of inventory and routing with multiple vehicles. It was verified that the responses generated are of good quality, highlighting the elimination of sub-tours through the flow model and inventory management under the ML policy. Future work should be directed towards finding new alternatives to exact optimization, such as heuristics and metaheuristics, which allow being as close as possible to the optimum in shorter computation times. In addition, stochastic demands could be considered, as well as the handling of perishable products, among others.

Context: This study evaluates the structural stability of a Savonius-type rotor by implementing a multiblade profile, with the purpose of reducing the resistance to movement and consequently improving aerodynamic performance. The rotor with the profile under study was compared against rotors with conventional semicircular and split Bach profiles. Method: The fluid-structure interaction was analyzed by numerically simulating the three rotors, and the state of stresses and deformations was determined under a normal operating regime. The rotors were assigned the same construction material, and they were studied under the same parameters and models of fluid dynamics and computational mechanics via the ANSYS software. Results: The results obtained showed a better structural behavior in the rotor with the multiblade configuration, reducing the maximum equivalent stress by 59,10 and 42,87\% and the deformations by 47,40 and 33,59\% with respect to the rotors with the conventional semicircular and split Bach profiles, respectively. Conclusions: The multiblade configuration allows for greater aerodynamic and structural performance while preserving the construction and operation simplicity that characterize Savonius-type rotors.

Context: The healthcare sector has continuously faced the challenges of reducing costs and improving quality of care. Research on the supply chain in the health sector has aroused a higher level of interest in the scientific community. Several articles have been published on the subject, focusing on aspects such as chain performance, management approaches, inventory management, supplier evaluation and selection, and some others with broader areas of focus. Method: This article presents a literature review and a bibliometric analysis. The analysis begins by identifying studies published in the last ten years. Then, bibliometric tools are used to identify key research topics, their interrelationships, and patterns of collaboration. Results: This research helps to graphically illustrate publications on hospital supply chain management, present their evolution over time, and identify areas of current research interest and possible lines of research for the future. The results identify the state of development and the main trends in terms of impact, main journals, articles, topics, authors, and countries. Conclusions: Future research can focus on more innovative studies from multiple dimensions: supply chain, management and organization, health services, operations management, sustainability, performance, context, and trends.

Context: Based on an analysis of the development of biodigester technology, a recurring problem with the rigorous quantification of methane was observed. A bibliographical review evidenced systems that are inefficient or have high costs. This work proposes an accessible and effective system that seeks to contribute to related academic and research projects. Method: Methane quantification is used an MQ-4 series sensor coupled with a capsule, thus creating a partially closed medium in which a dilution of sample gases and ambient air is injected by using a syringe, thus extending the measurement range of the sensor. Results: A calibration curve was elaborated, extending the measurement range from 0,02-1% concentration to 10-80%v/v, with a variance of ± 5%. Conclusions: An efficient and accessible prototype for methane quantification for academic and re- search purposes was developed. A guide for replicating the process is added as a complement.

Context: Copper or copper oxide nanoparticles are materials of interest in the field of agriculture due to their multiple properties, including their antimicrobial activity, which is useful in the biological control of pests. Several authors have reported that nanoparticles smaller than 50 nm have a greater antimicrobial effect. Accordingly, this study aimed to compare different synthesis protocols, with the purpose of obtaining copper or copper oxide nanoparticles with adequate size for their subsequent evaluation in the biological control of species that commonly affect crops in Colombia. Method: Five synthesis protocols were evaluated, four of them classified as green chemical synthesis methods, and the other as biological synthesis. The obtained nanoparticles were characterized via UV-Vis spectroscopy, DLS, TEM, FTIR, XRD, SEM, and EDS. Results: Protocol 3, which uses copper sulfate pentahydrate as precursor salt, ascorbic acid as reducing agent, and starch as stabilizer, proved to be the most suitable, as spherical metallic copper nanoparticles with a size of 4,5 nm were obtained with it. Conclusions: It was possible to compare methodologies for copper and copper oxide nanoparticles production, analyze the effect of synthesis conditions on their characteristics, and finally obtain a protocol to synthesize copper nanoparticles with an adequate size for potential use in biological control applications.

Context: This article presents the real-time estimation of temperature (°C) and relative humidity ( %) (interval of 16 seconds) for the city of Bogota DC via the Internet of Things (IoT). Method: This prototype is based on the Arduino ESP8266 NodeMCU module and the DHT11 sensor, as well as on a server-client HTPP communication protocol viaWi-Fi, with remote access to information. 16 sensors were installed in Bogota DC. These sensors send the observed data to the MATLAB storage cloud (ThingSpeak) via theWi-Fi module and can be downloaded in real-time. The temperature (°C) and relative humidity ( %) values were calibrated based on measurements made by the TTH002-certified digital thermo-hygrometer. Results: Based on the average temperature and relative humidity obtained, two maps were elaborated by implementing QGis: one with the isotherms and another one with isohumes. The inverse distance weighting (IDW) interpolation algorithm was used. Conclusions: The use of monitoring devices based on the IoT significantly contributes to automating meteorological data and structuring and utilizing robust databases in the field of Civil Engineering. Thus, the real-time transmission of temperature and relative humidity data allows for the online analysis of variables. Finally, the term adaptive dynamic cartography is proposed, which is associated with the generation of maps via the IoT, through which changes in the observed variables are displayed in real time, which allows monitoring the variables making adjustments based on an interpolation algorithm, as well as automatically and instantaneously generating isolines, which significantly reduces the uncertainty implied by the spatial-temporal resolution of current cartography.

Context: Self-sovereign identity (SSI) enables the creation of user-centric, privacy-by-design, secure, and decentralized identity-management systems. The aim of this paper is to carry out a bibliometric analysis of the scientific production on SSI during the period 2017-2022.Method: A complete bibliometric analysis of all publications on SSI indexed in Scopus and Web of Science was carried out. A corpus of 143 articles was examined by processing their bibliographic metadata on a bibliometric tool. In order to do this, the Bibliometrix packageand the R programming language were used.Results: A bibliometric characterization of the publications on SSI was obtained for the 2017 − 2022 period. The most important keywords used in these publications were identified, as well as their use tendencies throughout this period. Moreover, the most influential authors in the area and the most relevant publication sources were also identified.Conclusions: The results of the bibliometric analysis show that Lotka’s and Bradford’s laws apply for academic publications on SSI, which means that the most relevant publications in this area are concentrated in a relatively small group of authors and journals. Paul Jenkins, Nitin Naik, Yang Liu and Aijun An were the most impactful authors, and Lecture notes in computer science, Frontiers in blockchain and IEEE were the most influential journals. Finally, the keyword analysis showed that Blockchain, Authentication, Identity management, Electronic document identification systems, and Digital identity are currently the most relevant concepts for SSI.

Background: Recommender systems are one of the most widely used technologies by electronic businesses and internet applications as part of their strategies to improve customer experiences and boost sales. Recommender systems aim to suggest content based on its characteristics and on user preferences. The best recommender systems are able to deliver recommendations in the shortest possible time and with the least possible number of errors, which is challenging when working with large volumes of data. Method: This article presents a novel technique to optimize recommender systems using particle swarm algorithms. The objective of the selected genetic algorithm is to find the best hyperparameters that minimize the difference between the expected values and those obtained by the recommender system. Results: The algorithm demonstrates viability given the results obtained, highlighting its simple implementation and the minimal and easily attainable computational resources necessary for its execution. Conclusions: It was possible to develop an algorithm using the most convenient properties of particle swarms in order to optimize recommender systems, thus achieving the ideal behavior for its implementation in the proposed scenario.