The impact of health behaviors on incident and recurrent cancers: a population based analysis

This thesis investigated the role of health behaviours in both incident cancer diagnosis and cancer survivors. First, we evaluated the validity of self-reported cancers in the Lifelines cohort; we found that self-reported cancer in the Lifelines cohort have a moderate to good agreement with pathologically reported cancer diagnoses. We further explored the associations of health behaviours to cancer outcomes using traditional statistical approaches and machine learning algorithms. We found that machine-learning algorithms did not outperform traditional statistical approaches for predicting incident cancer cases, nor for classifying cancer survivors by using health behaviours. It was observed that lifestyle behaviour in cancer survivors and the whole cohort needs much improvement. Moreover, interventions to improve diet quality could be based on the American Cancer Society score, as this score was the one showing better diet benefits for cancer survivors and the general population in the Lifelines cohort

ESTUDIO COMPARATIVO ENTRE LA EFICACIA DE ESMOLOL VS LIDOCAINA, PARA DISMINUIR LOS CAMBIOS HEMODINAMICOS EN LA EXTUBACIÓN DE PACIENTES ADULTOS EN EL “CENTRO MEDICO LIC. ADOLFO LOPEZ MATEOS”.

ESTUDIO COMPARATIVO ENTRE LA EFICACIA DE ESMOLOL VS LIDOCAINA, PARA DISMINUIR LOS CAMBIOS HEMODINAMICOS EN LA EXTUBACIÓN DE PACIENTES ADULTOS Director: Armando Puente Solorio MJSA. Alumno: Héctor Omar Cortés Aceves MC; Introducción: La disminución de los cambios hemodinámicos en el periodo de la extubación se han propuesto múltiples acciones farmacológicas de las cuales en el presente estudio se valora la eficacia entre lidocaína y un B bloqueador selectivo como lo es el esmolol. Objetivo: Demostrar que el esmolol es más efectivo a dosis de 2 mgr/Kg., para la disminución de la respuesta hemodinámica post-extubación, que el uso de lidocaína 1% simple a 1 mgr/Kg Material y métodos: Se conformaron 2 grupos de 25 pacientes cada uno, al primer grupo se manejo con lidocaína a 1 mgr/kg y al segundo grupo se administró esmolol a 2 mgr/kg. Posterior al proceso de intubación y acto quirúrgico se tomaron en cuenta los signos vitales previos al periodo de la extubación como minuto 0 al tener criterios para la extubación y la subsecuente administración de fármaco, posteriormente a los 5, 15, 30, 60 y 120min, Resultados: Con relación a la presión arterial media (PAM) se apreciaron los siguientes resultados: en el grupo 1 (lidocaína) al minuto 0 la PAM fue de 98.0 ± 16 y para el grupo 2 (esmolol) fue de igual forma de 98.0 ± 15; a los 5 minutos la PAM fue de 105.8 ± 17 para el grupo 1 y de 81.4 ± 14 para el grupo 2; a los 15 minutos de 104.0 ± 21 y de 103.9 ±17 a los 30 min una PAM de 104.7 ± 18 y 108.0 ± 14; hacia los 60 minutos de 107.4 ± 26, y 106.2 ± 18; y por último para los 120 minutos se registro 105.0 ± 15 y 107.0 ± 17 Conclusiones: Los resultados obtenidos de la evaluación de las condiciones hemodinámicas en los pacientes de ambos grupos demuestran que existe una notable disminución de los parámetros hemodinámicos en el periodo posterior inmediato de la extubació

Efficient Breast Cancer Classification Using Histopathological Images and a Simple VGG

Breast cancer is the second most deadly disease worldwide. This severe condition led to 627,000 people dying in 2018. Thus, early detection is critical for improving the patients' lifetime or even curing them. In this context, we can appeal to Medicine 4.0, which exploits machine learning capabilities to obtain a faster and more efficient diagnosis. Therefore, this work aims to apply a simpler convolutional neural network, called VGG-7, for classifying breast cancer in histopathological images. Results have shown that VGG-7 overcomes the performance of VGG-16 and VGG-19, showing an accuracy of 98%, a precision of 99%, a recall of 98%, and an F1 score of 98%

Pro-environmental behavior and sustainable economic development in college students

The objective of this paper is oriented toward the analysis of behavior proambiental and sustainable economic development, since the Economic Psychology, the Environmental Psychology and the Economic Ecology. The methodological design includes an instrumental study on the Proambiental Behavior and Sustainable Economic Development Scale (Cortés, 2015b), with a random sample of 243 university students. The Cronbach Alpha was index (α:.89) and the correlation indexes item - scale ranged between (r: 364 and r: 624). The findings highlight the concern attitudinal of young people to strengthen their practices behavior and undertake proambiental processes of sustainable economic development.El objetivo del presente artículo se orienta al análisis del comportamiento proambiental y el desarrollo económico sustentable, desde la Psicología Económica, la Psicología Ambiental y la Ecología Económica. El diseño metodológico comprende un estudio instrumental sobre la Escala de Comportamiento Proambiental y Desarrollo Económico Sustentable (Cortés, 2015b), con una muestra aleatoria de 243 estudiantes universitarios. El índice Alfa de Cronbach fue (: .89) y los índices de correlación ítem – escala oscilaron entre (r: .364 y r: .624). Los hallazgos resaltan la preocupación actitudinal de los jóvenes para fortalecer sus prácticas comportamiento proambiental y emprender procesos de desarrollo económico sustentable

Analítica de datos no estructurados para dar soporte a la toma decisiones en el área de comercialización de la Empresa Representaciones Batericar S.A.C. utilizando la metodología ICAV y la plataforma de Microsoft

La empresa “Representaciones Batericar S.A.C.” da inicio a sus operaciones en el año 2010, brindando todo tipo de baterías y repuesto para el sector automotriz de alta performance a precios accesibles en el mercado trujillano, ofertando productos dentro de las más altas expectativas del mercado, logrando así convertirse en una empresa a la vanguardia de las principales empresas del ámbito norteño, teniendo como objetivo mejorar tanto en calidad, productividad y rentabilidad en todas sus líneas de productos. La organizacion no cuenta con herramientas para la extracción, procesamiento, análisis y visualización de datos, especialmente los no estructurados correspondientes al área de comercialización, por lo que dicha información no es analizada y utilizada de la manera más rápida y eficiente por los tomadores de decisiones. El presente trabajo de tesis da una solución para la mejora en el apoyo en la toma de decisiones bajo el desarrollo de una solución de analítica de datos no estructurados en el área de comercialización de la empresa Representaciones Batericar S.A.C., reportando información en forma dinámicas hacia el tomador de decisiones.The company ""Representaciones Batericar S.A.C."" started its operations in 2010, with the commitment to provide all types of batteries and spare parts for the high performance automotive sector at affordable prices in the Trujillo market, offering products that are up to the market demands, becoming one of the main companies in the northern market, aiming to be at the forefront and committed to continuously improving the quality, productivity and profitability of its people, company and products. The company does not have toolsfor the extraction, processing, analysis and visualization of data, especially the unstructured ones corresponding to the commercialization area, so this information is not analyzed and used in the fastest and most efficient way by decision makers. This thesis work provides a solution to improve support in decision-making based on the development of an analytical solution for unstructured data for the commercialization area of the company Representaciones Batericar SAC, reporting information dynamically to the decision maker.Tesi

Real-time on-board pedestrian detection using generic single-stage algorithms and on-road databases

[EN] Pedestrian detection is a particular case of object detection that helps to reduce accidents in advanced driver-assistance systems and autonomous vehicles. It is not an easy task because of the variability of the objects and the time constraints. A performance comparison of object detection methods, including both GPU and non-GPU implementations over a variety of on-road specific databases, is provided. Computer vision multi-class object detection can be integrated on sensor fusion modules where recall is preferred over precision. For this reason, ad hoc training with a single class for pedestrians has been performed and we achieved a significant increase in recall. Experiments have been carried out on several architectures and a special effort has been devoted to achieve a feasible computational time for a real-time system. Finally, an analysis of the input image size allows to fine-tune the model and get better results with practical costs.The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was supported by PRYSTINE project which had received funding within the Electronic Components and Systems for European Leadership Joint Undertaking (ECSEL JU) in collaboration with the European Union's H2020 Framework Programme and National Authorities, under grant agreement no. 783190. It was also funded by Generalitat Valenciana through the Instituto Valenciano de Competitividad Empresarial (IVACE).Ortiz, V.; Del Tejo Catala, O.; Salvador Igual, I.; Perez-Cortes, J. (2020). Real-time on-board pedestrian detection using generic single-stage algorithms and on-road databases. International Journal of Advanced Robotic Systems. 17(5). https://doi.org/10.1177/1729881420929175S175Zhang, S., Benenson, R., Omran, M., Hosang, J., & Schiele, B. (2018). Towards Reaching Human Performance in Pedestrian Detection. IEEE Transactions on Pattern Analysis and Machine Intelligence, 40(4), 973-986. doi:10.1109/tpami.2017.2700460Viola, P., Jones, M. J., & Snow, D. (2005). Detecting Pedestrians Using Patterns of Motion and Appearance. International Journal of Computer Vision, 63(2), 153-161. doi:10.1007/s11263-005-6644-8Dollar, P., Appel, R., Belongie, S., & Perona, P. (2014). Fast Feature Pyramids for Object Detection. IEEE Transactions on Pattern Analysis and Machine Intelligence, 36(8), 1532-1545. doi:10.1109/tpami.2014.2300479Dollar, P., Wojek, C., Schiele, B., & Perona, P. (2012). Pedestrian Detection: An Evaluation of the State of the Art. IEEE Transactions on Pattern Analysis and Machine Intelligence, 34(4), 743-761. doi:10.1109/tpami.2011.155Munder, S., & Gavrila, D. M. (2006). An Experimental Study on Pedestrian Classification. IEEE Transactions on Pattern Analysis and Machine Intelligence, 28(11), 1863-1868. doi:10.1109/tpami.2006.217Enzweiler, M., & Gavrila, D. M. (2009). Monocular Pedestrian Detection: Survey and Experiments. IEEE Transactions on Pattern Analysis and Machine Intelligence, 31(12), 2179-2195. doi:10.1109/tpami.2008.260He, K., Zhang, X., Ren, S., & Sun, J. (2015). Spatial Pyramid Pooling in Deep Convolutional Networks for Visual Recognition. IEEE Transactions on Pattern Analysis and Machine Intelligence, 37(9), 1904-1916. doi:10.1109/tpami.2015.2389824McGehee, D. V., Mazzae, E. N., & Baldwin, G. H. S. (2000). Driver Reaction Time in Crash Avoidance Research: Validation of a Driving Simulator Study on a Test Track. Proceedings of the Human Factors and Ergonomics Society Annual Meeting, 44(20), 3-320-3-323. doi:10.1177/15419312000440202

Creación de un plan de negocio para una microempresa dedicada a la elaboración y comercialización de embutidos "Chorizo" a base de pescado en la ciudad de Villavicencio.

Diseñar plan de negocio para la creación de una microempresa dedicada a la producción y comercialización de chorizos de pescado denominada Chorizos el Dorado S.A.S. en la ciudad de Villavicencio Meta.La necesidad de incursionar en el mercado con nuevas ideas o mejoras de lo existente es clave para el desarrollo tanto social como económico. Actualmente el desarrollo mundial ha obligado a que los diferentes sectores innoven o reestructuren sus procesos, pero acompañados de proyectos sostenibles y amigables con los recursos naturales. La oferta alimentaria es basta sin embargo la acuicultura como también las demás actividades económicas han sido propulsadas no solo por dicho desarrollo sino también por los avances tecnológicos e investigativos. En Colombia durante los últimos diez años las principales tendencias relacionadas con el desarrollo de la acuicultura se ven influenciadas por la motivación de los colombianos hacia el consumo del pescado, la diversificación agropecuaria, mayor rentabilidad que ofrece la acuicultura sobre otros sectores de la producción agropecuaria tradicional, Políticas del Gobierno Nacional de impulsar este sector con fines de abastecer el mercado interno y externo y contribuir a las políticas de seguridad alimentaria y alivio de la pobreza. El Departamento del Meta es un gran productor de pescado y principalmente en tilapia, siendo más una actividad artesanal, y sin ningún nivel de industrialización, con relación a la comercialización se realiza en su mayor parte a nivel local y una parte llega al mercado de la capital de Colombia y su consumo tradicional se ofrece en diferentes formas primarias como sudada, frita y asad

Improving the understanding of web user behaviors through machine learning analysis of eye-tracking data

Eye-tracking techniques are widely used to analyze user behavior. While eye-trackers collect valuable quantitative data, the results are often described in a qualitative manner due to the lack of a model that interprets the gaze trajectories generated by routine tasks, such as reading or comparing two products. The aim of this work is to propose a new quantitative way to analyze gaze trajectories (scanpaths) using machine learning. We conducted a within-subjects study (N = 30) testing six different tasks that simulated specific user behaviors in web sites (attentional, comparing two images, reading in different contexts, and free surfing). We evaluated the scanpath results with three different classifiers (long short-term memory recurrent neural network—LSTM, random forest, and multilayer perceptron neural network—MLP) to discriminate between tasks. The results revealed that it is possible to classify and distinguish between the 6 different web behaviors proposed in this study based on the user’s scanpath. The classifier that achieved the best results was the LSTM, with a 95.7% accuracy. To the best of our knowledge, this is the first study to provide insight about MLP and LSTM classifiers to discriminate between tasks. In the discussion, we propose practical implications of the study results

New developments in lycopene analysis by spectroscopic and chromatographic techniques, accompanied by mathematical modelling

Comunicación Oral sobre los resultados obtenidos en el estudio de las propiedades del lycopeno presente en el tomate como compuesto bioactivo. Se realizó la identificación y cuantificación por diferentes metodologías experimentales. Se muestran los resultados analíticos comapartivamente con distintas técnicas

Extended a Priori Probability (EAPP): A Data-Driven Approach for Machine Learning Binary Classification Tasks

[EN] The a priori probability of a dataset is usually used as a baseline for comparing a particular algorithm's accuracy in a given binary classification task. ZeroR is the simplest algorithm for this, predicting the majority class for all examples. However, this is an extremely simple approach that has no predictive power and does not describe other dataset features that could lead to a more demanding baseline. In this paper, we present the Extended A Priori Probability (EAPP), a novel semi-supervised baseline metric for binary classification tasks that considers not only the a priori probability but also some possible bias present in the dataset as well as other features that could provide a relatively trivial separability of the target classes. The approach is based on the area under the ROC curve (AUC ROC), known to be quite insensitive to class imbalance. The procedure involves multiobjective feature extraction and a clustering stage in the input space with autoencoders and a subsequent combinatory weighted assignation from clusters to classes depending on the distance to nearest clusters for each class. Class labels are then assigned to establish the combination that maximizes AUC ROC for each number of clusters considered. To avoid overfit in the combined feature extraction and clustering method, a cross-validation scheme is performed in each case. EAPP is defined for different numbers of clusters, starting from the inverse of the minority class proportion, which is useful for a fair comparison among diversely imbalanced datasets. A high EAPP usually relates to an easy binary classification task, but it also may be due to a significant coarse-grained bias in the dataset, when the task is previously known to be difficult. This metric represents a baseline beyond the a priori probability to assess the actual capabilities of binary classification models.This work was supported in part by the Generalitat Valenciana through the Valencian Institute of Business Competitiveness (IVACE) Distributed Nominatively to Valencian Technological Innovation Centers under Project IMAMCN/2021/1, in part by the Cervera Network of Excellence Project in Data-Based Enabling Technologies (AI4ES) Co-Funded by the Centre for Industrial and Technological Development¿E. P. E. (CDTI), and in part by the European Union through the Next Generation EU Fund within the Cervera Aids Program for Technological Centers under Project CER-20211030.Ortiz, V.; Pérez-Benito, FJ.; Del Tejo Catalá, O.; Salvador Igual, I.; Llobet Azpitarte, R.; Perez-Cortes, J. (2022). Extended a Priori Probability (EAPP): A Data-Driven Approach for Machine Learning Binary Classification Tasks. IEEE Access. 10:120074-120085. https://doi.org/10.1109/ACCESS.2022.32219361200741200851