Browsing by Author "Ramirez, Cristian"

Now showing 1 - 7 of 7
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    Children's Mental Health: Discrepancy between Child Self-Reporting and Parental Reporting
    (2022) Caqueo-Urizar, Alejandra; Urzua, Alfonso; Villalonga-Olives, Ester; Atencio-Quevedo, Diego; Irarrazaval, Matias; Flores, Jerome; Ramirez, Cristian
    (1) Background: Discrepancies between children's self-reports and their parents' reports on mental health indicators are associated with measurement errors or informant bias. However, they are a valuable tool in understanding the course of child psychopathology. This study aims to determine the level of discrepancies between parents' perceptions and children's self-reports in mental health indicators in Northern Chile. (2) Methods: A System of Evaluation of Children and Adolescents self-report (Sistema de Evaluacion de Ninos y Adolescentes, SENA) was responded to by 408 students between 8 and 13 years old and their parents. (3) Results: Children reported a significantly higher frequency of emotional problems, defiant behavior, and executive functions as compared to their parents' responses. (4) Conclusions: There is a disjunction between the report of parents and children, which could originate in poor family communication.
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    Determination of a representative area element (RAE) based on nonparametric statistics in bread
    (ELSEVIER SCI LTD, 2011) Ramirez, Cristian; Aguilera, Jose M.
    The concept of representative area element (RAE) was applied to quantify the air cell present in pre-sliced bread. Ten slices from bread were selected and each divided into nine subareas where 60 air cells were measured. To determine the RAE, one to nine sampling areas were considered and five positions in the image were randomly selected and compared by nonparametric statistic and the fluctuation of mean air cell area method. The RAE was attained when the air cell area size distribution curves for each sampling area did not present significant differences. Hence, the RAE size was 67% of the image using the nonparametric method (equivalent to six subareas of the nine subareas that form the image), whereas the RAE could not be estimated using the fluctuation of mean air cell area method. Therefore, nonparametric statistics are a useful tool to determine the RAE in structures with size distributions that do not fit a normal distribution. (C) 2010 Elsevier Ltd. All rights reserved.
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    Enalapril attenuates downregulation of angiotensin-converting enzyme 2 in the late phase of ventricular dysfunction in myocardial infarcted rat
    (LIPPINCOTT WILLIAMS & WILKINS, 2006) Ocaranza, Maria Paz; Godoy, Ivan; Jalil, Jorge E.; Varas, Manuel; Collantes, Patricia; Pinto, Melissa; Roman, Maritza; Ramirez, Cristian; Copaja, Miguel; Diaz Araya, Guillermo; Castro, Pablo; Lavandero, Sergio
    The early and long-term effects of coronary artery ligation on the plasma and left ventricular angiotensin-converting enzyme (ACE and ACE2) activities, ACE and ACE2 mRNA levels, circulating angiotensin (Ang) levels [Ang I, Ang-(1-7), Ang-(1-9), and Ang II], and cardiac function were evaluated 1 and 8 weeks after experimental myocardial infarction in adult Sprague Dawley rats. Sham-operated rats were used as controls. Coronary artery ligation caused myocardial infarction, hypertrophy, and dysfunction 8 weeks after surgery. At week 1, circulating Ang II and Ang-(1-9) levels as well as left ventricular and plasma ACE and ACE2 activities increased in myocardial-infarcted rats as compared with controls. At 8 weeks post-myocardial infarction, circulating ACE activity, ACE mRNA levels, and Ang II levels remained higher, but plasma and left ventricular ACE2 activities and mRNA levels and circulating levels of Ang-(1-9) were lower than in controls. No changes in plasma Ang-(1-7) levels were observed at any time. Enalapril prevented cardiac hypertrophy and dysfunction as well as the changes in left ventricular ACE, left ventricular and plasmatic ACE2, and circulating levels of Ang II and Ang-(1-9) after 8 weeks postinfafction. Thus, the decrease in ACE2 expression and activity and circulating Ang-(1-9) levels in late ventricular dysfunction post-myocardial infarction were prevented with enalapril. These findings suggest that in this second arm of the renin-angiotensin system, ACE2 may act through Ang-(1-9), rather than Ang-(1-7), as a counterregulator of the first arm, where ACE catalyzes the formation of Ang II.
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    Fractional Factorial Design to Evaluate the Synthesis and Electrochemical Transfer Parameters of h-BN Coatings
    (2023) Figueroa, Helen; Aristizabal, Juliet; Reinoso-Guerra, Elias; Arce, Barbara; Vargas-Straube, Maria Jose; Gentil, Dana; Ramirez, Cristian; Cordero, Jose; Barrera, Nelson P.; Parra, Carolina
    In this study, we present a fractional factorial design approach for exploring the effects and interactions of key synthesis and electrochemical transfer parameters on the roughness and wettability of hexagonal boron nitride (h-BN) coatings, due to their essential role in biofilm formation. The studied parameters for the synthesis process include precursor mass, growth time, and substrate conditioning, whereas for the transfer process, applied voltage and aqueous medium concentration were studied. Through this polynomial model, we confirmed the strong influence of precursor mass and medium concentration parameters on h-BN surface roughness and its resulting antibiofilm properties.
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    Image Analysis of Representative Food Structures: Application of the Bootstrap Method
    (WILEY, 2009) Ramirez, Cristian; Germain, Juan C.; Aguilera, Jose M.
    Images (for example, photomicrographs) are routinely used as qualitative evidence of the microstructure of foods. In quantitative image analysis it is important to estimate the area (or volume) to be sampled, the field of view, and the resolution. The bootstrap method is proposed to estimate the size of the sampling area as a function of the coefficient of variation (CVBn) and standard error (SEBn) of the bootstrap taking sub-areas of different sizes. The bootstrap method was applied to simulated and real structures (apple tissue). For simulated structures, 10 computer-generated images were constructed containing 225 black circles (elements) and different coefficient of variation (CVimage). For apple tissue, 8 images of apple tissue containing cellular cavities with different CVimage were analyzed. Results confirmed that for simulated and real structures, increasing the size of the sampling area decreased the CVBn and SEBn. Furthermore, there was a linear relationship between the CVimage and CVBn. For example, to obtain a CVBn = 0.10 in an image with CVimage = 0.60, a sampling area of 400 x 400 pixels (11% of whole image) was required, whereas if CVimage = 1.46, a sampling area of 1000 x 100 pixels (69% of whole image) became necessary. This suggests that a large-size dispersion of element sizes in an image requires increasingly larger sampling areas or a larger number of images.
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    The degradation of performance of a state-of-the-art skin image classifier when applied to patient-driven internet search
    (2022) Han, Seung Seog; Navarrete-Dechent, Cristian; Liopyris, Konstantinos; Kim, Myoung Shin; Park, Gyeong Hun; Woo, Sang Seok; Park, Juhyun; Shin, Jung Won; Kim, Bo Ri; Kim, Min Jae; Donoso, Francisca; Villanueva, Francisco; Ramirez, Cristian; Chang, Sung Eun; Halpern, Allan; Kim, Seong Hwan; Na, Jung-Im
    Model Dermatology (; Build2021) is a publicly testable neural network that can classify 184 skin disorders. We aimed to investigate whether our algorithm can classify clinical images of an Internet community along with tertiary care center datasets. Consecutive images from an Internet skin cancer community ('RD' dataset, 1,282 images posted between 25 January 2020 to 30 July 2021; ) were analyzed retrospectively, along with hospital datasets (Edinburgh dataset, 1,300 images; SNU dataset, 2,101 images; TeleDerm dataset, 340 consecutive images). The algorithm's performance was equivalent to that of dermatologists in the curated clinical datasets (Edinburgh and SNU datasets). However, its performance deteriorated in the RD and TeleDerm datasets because of insufficient image quality and the presence of out-of-distribution disorders, respectively. For the RD dataset, the algorithm's Top-1/3 accuracy (39.2%/67.2%) and AUC (0.800) were equivalent to that of general physicians (36.8%/52.9%). It was more accurate than that of the laypersons using random Internet searches (19.2%/24.4%). The Top-1/3 accuracy was affected by inadequate image quality (adequate = 43.2%/71.3% versus inadequate = 32.9%/60.8%), whereas participant performance did not deteriorate (adequate = 35.8%/52.7% vs. inadequate = 38.4%/53.3%). In this report, the algorithm performance was significantly affected by the change of the intended settings, which implies that AI algorithms at dermatologist-level, in-distribution setting, may not be able to show the same level of performance in with out-of-distribution settings.
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    The effect of within-firm vertical pay disparity in occupational safety
    (2022) Ramirez, Cristian; Tarzijan, Jorge; Singer, Marcos