Publications
314
Thesis
1
Department
29
Researchers
285
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  • Publication
    Women's voices in engineering: academic experiences, obstacles, and facilitators of career tenure
    (2022-08-01)
    Martínez-Galaz, Carolina P.
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    Palomera-Rojas, Pamela V.
    The main objective of this research study was to explore the academic experiences that favor or hinder women’s permanence and academic progression in engineering careers. Data is gathered by applying a qualitative and exploratory-descriptive methodology. The study was conducted at 3 universities and 103 individuals from the academic community were surveyed through interviews and discussion groups to identify relevant thematic nuclei. The results showed that one of the obstacles that women must overcome was gender stereotype inside and outside the classroom. The facilitators for academic progression included female references and peer support. It is concluded that obstacles such as academic interaction with peers and faculty may limit women’s permanence in their careers, which highlights the importance of implementing institutional mechanisms to help women overcome barriers.
  • Publication
    (g-2) anomalies and neutrino mass
    (2020-10-08) ;
    Cepedello, Ricardo
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    Fonseca, Renato M.
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    Hirsch, Martin
    Motivated by the experimentally observed deviations from standard model predictions, we calculate the anomalous magnetic moments 𝑎𝛼=(𝑔−2)𝛼 for 𝛼=𝑒, 𝜇 in a neutrino mass model originally proposed by Babu, Nandi, and Tavartkiladze (BNT). We discuss two variants of the model: the original model, and a minimally extended version with an additional hypercharge-zero triplet scalar. While the original BNT model can explain 𝑎𝜇, only the variant with the triplet scalar can explain both experimental anomalies. The heavy fermions of the model can be produced at the high-luminosity LHC, and in the part of parameter space where the model explains the experimental anomalies it predicts certain specific decay patterns for the exotic fermions.
  • Publication
    An Assessment of the Metal Removal Capability of Endemic Chilean Species
    (2022-03-01) ;
    Lazo, Pamela
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    Lobos, María Gabriela
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    Hansen, Henrik K.
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    Gutiérrez, Claudia
    In Chile, there are several abandoned mine tailing impoundments near population centers that need to be remediated. In this study, the ability of Oxalis gigantea, Cistanthe grandiflora, and Puya berteroniana to remove Zn, Ni, and Cr from mine tailings was evaluated. The plants’ removal efficiency, bioconcentration, and translocation factors regarding these metals were determined to assess the ability of certain endemic species from Northern and Central Chile to extract or stabilize metals. After a period of seven months, the chemical analysis of plants and tailings, together with the statistical treatment of data, indicated the inability of all the species to translocate Ni, Cr, or Zn with a translocation factor lower than one. The results showed the stabilizing character of Oxalis gigantea, Puya berteroniana, and Cistanthe grandiflora for Zn, with a bioconcentration factor close to 1.2 in all cases, and the same ability of the latter two species for Cr, with a bioconcentration factor of 1.5 in the case of Cistanthe grandiflora and 1.7 for Puya berteroniana. Finally, a removal efficiency of 9.3% was obtained with Cistanthe grandiflora for Cr and 15% for Ni; values lower than 6.4% were obtained for Zn in all cases. Improvements in the process should be sought to enhance the performance of these species for the accumulation of the target metals.
  • Publication
    Evaluation of Indigenous Candida oleophila and Candida boidinii in Monoculture and Sequential Fermentations: Impact on Ethanol Reduction and Chemical Profile in Chilean Sauvignon Blanc Wines
    (2022-03-01)
    Benavides, Sergio
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    Franco, Wendy
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    Ceppi De Lecco, Consuelo
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    The study of non-Saccharomyces yeasts in wine fermentations allows the exploration of new alternatives for the reduction of ethanol in wines. The objective of this work was to evaluate the fermentation capacity of two indigenous Candida yeasts (C. oleophila and C. boidinii) in monoculture and sequential fermentations (laboratory and microvinification scale) to produce Chilean Sauvignon Blanc wine. Fermentations were monitored by the determination of ethanol, glycerol, organic acids, and residual sugars. The results indicated that at the laboratory scale for both the monoculture and sequential fermentations it was possible to reduce the ethanol concentration on 0.77% v/v (monoculture) and 1.5% v/v (sequential) for C. oleophila and 0.50% v/v (monoculture) and 0.04% v/v (sequential) for C. boidinii compared to S. cerevisiae (12.87% v/v). Higher glycerol concentrations were produced in monoculture than sequential fermentations (C. oleophila: 9.47 g/L and C. boidinii 10.97 g/L). For microvinifications, the monoculture and sequential fermentations with C. boidinii managed to reduce ethanol content by 0.17% v/v and 0.54% v/v, respectively, over the S. cerevisiae control (13.74% v/v). In the case of C. oleophila, the reduction was only observed in sequential fermentations with 0.62% v/v. Interestingly, grapes with higher sugar concentration resulted in wines with lees ethanol concentrations. This might be associated to the use of C. oleophila (13.12% v/v) and C. boidinii (13.20% v/v) in sequential fermentations microvinification scale.
  • Publication
    Robust self-organizing maps
    (2004-01-01) ;
    Moreno, Sebastian
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    Rogel, Cristian
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    Salas, Rodrigo
    The Self Organizing Map (SOM) model is an unsupervised learning neural network that has been successfully applied as a data mining tool. The advantages of the SOMs are that they preserve the topology of the data space, they project high dimensional data to a lower dimension representation scheme, and are able to find similarities in the data. However, the learning algorithm of the SOM is sensitive to the presence of noise and outliers as we will show in this paper. Due to the influence of the outliers in the learning process, some neurons (prototypes) of the ordered map get located far from the majority of data, and therefore, the network will not effectively represent the topological structure of the data under study. In this paper, we propose a variant to the learning algorithm that is robust under the presence of outliers in the data by being resistant to these deviations. We call this algorithm Robust SOM (RSOM). We will illustrate our technique on synthetic and real data sets.
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  • Publication
    Equivalent availability index for the performance measurement of haul truck fleets
    (2020-01-01) ; ;
    Zio, Enrico
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    Pascual, Rodrigo
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    Aranda, Oscar
    This article presents a model of performance analysis for a truck fleet system in an openpit mine, considering special characteristics of haul fleets. In these systems, the expected availability of each piece of equipment and its operating capacity are the fundamental variables to construct a global fleet performance function. Our analytical algorithm considers heterogeneous fleets with known individual characteristics of transport capacity and failure and repair behavior. The results converge to a new indicator denominated “Equivalent Availability” (EA), which arises from the need to evaluate the capacity of the truck fleet to operate at a lower payload than required using different combinations of equipment to achieve an availability goal. EA is a key indicator to determine the productive capacity of a process, and for selecting equipment and their combinations to achieve production objectives. To exemplify the potentialities of the EA, a case study is implemented in a Chilean copper truck fleet mining process.
  • Person
    VALENCIA ARAYA, PEDRO LUIS
    INVESTIGADOR
  • Person
    Marin, Tatiane
    PROFESOR
  • Publication
    Cone-like graphene nanostructures: Electronic and optical properties
    (2013-01-01)
    Ulloa, Pablo
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    Latgé, Andrea
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    Oliveira, Luiz E.
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    Abstract Abstract A theoretical study of electronic and optical properties of graphene nanodisks and nanocones is presented within the framework of a tight-binding scheme. The electronic densities of states and absorption coefficients are calculated for such structures with different sizes and topologies. A discrete position approximation is used to describe the electronic states taking into account the effect of the overlap integral to first order. For small finite systems, both total and local densities of states depend sensitively on the number of atoms and characteristic geometry of the structures. Results for the local densities of charge reveal a finite charge distribution around some atoms at the apices and borders of the cone structures. For structures with more than 5,000 atoms, the contribution to the total density of states near the Fermi level essentially comes from states localized at the edges. For other energies, the average density of states exhibits similar features to the case of a graphene lattice. Results for the absorption spectra of nanocones show a peculiar dependence on the photon polarization in the infrared range for all investigated structures.