I+D Tecnológico

Artificial Intelligence prototype for damage prediction in electric induction motors

2025-09-29T14:51:15+00:00

Electric induction motors are the most used today to carry out industrial processes, so keeping them in optimal conditions guarantees their efficiency. Maintaining a predictive maintenance plan guarantees us to prevent major damages and avoid stopping production lines or normal operations in common faults such as in bearings, stator and rotor. The purpose of this project is to create a prototype using a convolutional neural network (CNN) with supervised learning that processes its layers imitating the visual cortex of the human eye to identify different punctual characteristics of an image, this methodology is based on the "pre-processing" of data. With this, the idea arises of creating an APP from the cell phone to detect engine failures through the audio spectrogram collected with the microphone of a mobile device so that a prediction can be made in a practical way at any moment.

Tacaco (Sechium tacaco): characterization of fruits of five accessions without thorns in the fruit

2025-09-08T14:28:45+00:00

Objectives: The morphological characterization of the fruits of five accessions of tacaco (Sechium tacaco) was carried out. Methodology: Between July 2017 and September 2019, fruits of five tacaco accessions, whose fruits did not have thorns, were collected from five sites in Costa Rica; between 62 and 88 fruits were collected per accession. The variables evaluated in the fruits were: weight, length, width, thickness, number of complete longitudinal sutures, number of incomplete longitudinal sutures, total number of longitudinal sutures, number of thorns, length/width ratio, length/thickness ratio, and width/thickness ratio. Results: There were statistically significant differences between accessions for all variables, except the number of thorns. Conclusions: There is an important variability in the morphological characteristics of the fruits of the various accessions of thornless tacaco, which constitutes a key factor in the plant breeding process in this species.

Review: Identification and diagnosis of hospital-important microorganisms using MALDITOF and metagenomic NGS.

2025-09-04T15:45:17+00:00

The identification and diagnosis of pathogenic microorganisms are important for the treatment, management, and prognosis of hospital infections. However, many microorganisms are difficult to identify using conventional diagnostic methods. Advanced techniques such as MALDI-TOF MS and mNGS offer advantages for identifying microorganisms of hospital importance. MALDI-TOF MS is a rapid and precise method that creates a mass spectral fingerprint for microbial identification down to strain levels. This technique is quick, sensitive, and economical, allowing the identification of different types of microorganisms. MALDI-TOF MS can only identify new microorganisms if the spectral database contains peptide mass fingerprints of specific strains, which is a limitation of the technique. Meanwhile, metagenomics allows the analysis of DNA segments from multiple microorganisms within a community, either through amplicon-based or shotgun sequencing. Advances in clinical next-generation metagenomic sequencing (mNGS) increase diagnostic capacity by rapidly detecting rare pathogens and antibiotic resistance genes. This technique presents some limitations in its accuracy and logistical complexity but can perform comprehensive analyses of microbial communities. Both methods complement traditional diagnostic techniques, and their integration into clinical microbiology improves pathogen identification, guides treatment strategies, and supports outbreak investigations. This review summarizes MALDI-TOF MS and metagenomics as alternative methods for identifying and diagnosing microorganisms in hospitals.

Parameter estimation of harmonic loads connected to the electrical distribution network

2025-08-22T19:46:48+00:00

The increasing amount of nonlinear loads in industrial electrical distribution systems has generated harmonic loads that affect power quality. In this study, a Weighted Least Squares based WLS algorithm has been developed for the location and identification of harmonic load parameters. While employing the IP following the Interior Point or IP method to solve the optimization, real models validated the accuracy of the algorithm. With analysis in additional case studies, the algorithm has demonstrated high accuracy in parameter estimation. This allowed the best modeling of loads for understanding the electrical behavior of the industry. Even a poor estimation of one or more of the initial points has mainly affected the efficiency and convergence of our algorithm.

Theoretical analysis of the vulnerability and mitigation of flexible pavements in the face of climate change in Panama

2025-08-21T13:36:36+00:00

Climate change poses a significant challenge to road infrastructure, particularly for flexible pavements in tropical countries like Panama. Adverse effects of climate change, such as rising temperatures and intensified rainfall, threaten the durability and performance of these vital structures. This study aims to assess the vulnerability of flexible pavements in Panama to climate change and propose mitigation strategies to enhance their resilience and extend their service life. A comprehensive literature review and a detailed theoretical analysis of the phenomena involved were conducted, including viscoelasticity and thermal fatigue models. Previous studies on the impact of climate change on flexible pavements were examined, and mitigation strategies, such as the use of modified materials and advanced drainage technologies, were analysed. The analysis revealed that flexible pavements in Panama are particularly vulnerable to increased temperatures and intense rainfall. The use of polymer modifiers in asphalt mixtures and the implementation of advanced drainage systems were identified as effective strategies to improve pavement resilience. It is concluded that adapting current flexible pavement designs is crucial to address the challenges of climate change in Panama. The implementation of customized mitigation strategies for the different regions of the country and the conduct of empirical studies to validate the proposed theoretical models are recommended.