Browsing by Author "Gonzalez, Luis A."

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    Genetic Diversity and Population Structure of Jubaea chilensis, an Endemic and Monotype Gender from Chile, Based on SNP Markers
    (2022) Jara-Arancio, Paola; da Silva Carvalho, Carolina; Carmona-Ortiz, Martin R.; Bustamante, Ramiro O.; Schmidt Villela, Priscilla M.; da Silva Andrade, Sonia C.; Pena-Gomez, Francisco T.; Gonzalez, Luis A.; Fleury, Marina
    Jubaea chilensis (Molina) Baill., also named Chilean palm, is an endemic species found in the coastal area of Mediterranean sclerophyllous forest in Chile. It has a highly restricted and fragmented distribution along the coast, being under intense exploitation and anthropogenic impact. Based on 1038 SNP markers, we evaluated the genetic diversity and population structure among six J. chilensis natural groups encompassing 96% of the species distribution. We observed low levels of genetic diversity, a deficit of heterozygotes (mean H-E = 0.024; H-O = 0.014), and high levels of inbreeding (mean F-IS = 0.424). The fixation index (F-ST) and Nei's genetic distance pairwise comparisons indicated low to moderate structuring among populations. There was no evidence of isolation by distance (r = -0.214, p = 0.799). In the cluster analysis, we observed a closer relationship among Culimo, Cocalan, and Candelaria populations. Migration rates among populations were low, except for some populations with moderate values. The K value that best represented the spatial distribution of genetic diversity was Delta K = 3. Habitat fragmentation, deterioration of the sclerophyllous forest, lack of long-distance dispersers, and a natural regeneration deficit may have driven inbreeding and low levels of genetic diversity in the palm groves of J. chilensis. Although extant populations are not at imminent risk of extinction, the rate of inbreeding could increase and migration could decrease if the effects of climate change and human impact become more acute.
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    Improving learning experiences in software engineering capstone courses using artificial intelligence virtual assistants
    (2022) Gonzalez, Luis A.; Neyem, Andres; Contreras-McKay, Ignacio; Molina, Danilo
    Students of Software Engineering Capstone Courses face situations and challenges that grant them valuable experiences. However, as this knowledge is acquired through real-life exposure, it is difficult to transmit it across different generations. To deal with this problem, it has been proposed that students record their learnings through a lesson learned model. But the question of how future students can best benefit from these records remains unanswered. This study addresses this problem through the use of Artificial Intelligence (AI) Virtual Assistant combined with a recommender system. Artificial Intelligence Virtual Assistants, as conversational chatbots, are a manifestation of AI via the simulation of conversation with human users. The technology has the potential to provide personalized service to a range of stakeholders. Thus, we seek to move this trend forward by now pushing these capabilities into the field of higher education. Consequently, we aim to assist software engineering students by leveraging collective knowledge to enhance learning experiences.