Proyectos

The Chilean Coastal Orographic Precipitation Experiment (CCOPE) was conducted during the austral winter of 2015 (May–August) in the Nahuelbuta Mountains (peak elevation 1.3 km MSL) of southern Chile (38ºS). CCOPE used soundings, two profiling Micro Rain Radars, a Parsivel disdrometer, and a rain gauge network to characterize warm and ice-initiated rain regimes and explore their consequences for orographic precipitation

La Piscirickettsiosis es una grave enfermedad bacteriana que resulta en altos niveles de mortalidad en diferentes especies de salmónidos. Las pérdidas totales, incluidos los costos de vacunación y los tratamientos antimicrobianos se han estimado en alrededor de $ 450 millones de dólares por año. Desafortunadamente, las vacunas contra este patógeno han mostrado ser poco efectivas para prevenir esta enfermedad, lo que se ha asociado según estudios de nuestro laboratorio a fenómenos de coinfección de Caligus, variabilidad del patógeno y del hospedero. Recientes estudios muestran, además, que los mecanismos de respuesta inmune innata son los responsables de otorgar protección a los peces frente a un desafío con esta bacteria. De esta manera, la falta de tratamientos eficaces contra Piscirickettsia salmonis fundamentan la necesidad de buscar nuevas alternativas de tratamientos profilácticos, las que deberían estar orientados a reforzar el sistema inmune innato del hospedador. En base a estas necesidades nosotros proponemos evaluar cuerpos de inclusión como inmunoestimulantes de administración oral para el control de P. salmonis en salmón del Atlántico (Salmo salar). Los cuerpos de inclusión son agregados de proteínas recombinantes nanoestructuradas funcionales expresados usualmente en el citoplasma de bacterias recombinantes. Los cuerpos de inclusión pueden expresar cualquier proteína con una función de interés, la cual es liberada gradualmente en el tiempo. Además, son muy estables y resisten duras condiciones fisicoquímicas manteniendo su funcionalidad por lo que no es necesario su encapsulación. Debido a que la producción de los cuerpos de inclusión es altamente escalable en biorreactores bacterianos surgen entonces como una herramienta de biotecnología susceptible de llegar a ser una solución comercial. Recientemente he evaluado con éxito el uso de cuerpos de inclusión de citoquinas como inmunoestimulantes en trucha arcoíris (Onchorhynchuss mykiss) y el pez cebra (Danio rerio). La prueba de concepto de esta tecnología mostró que los cuerpos de inclusión pueden estimular una respuesta inmune en macrófagos de trucha arcoíris. Además, los cuerpos de inclusión administrados por vía intraperitoneal protegen al pez cebra frente a una infección bacteriana letal y al ser administrados oralmente son absorbidos por células presentes en la mucosa intestinal. Postulamos como hipótesis que los cuerpos de inclusión administrados por vía oral otorgan protección al salmón del atlántico contra P. salmonis. Como primer objetivo de este estudio proponemos realizar la producción y caracterización de los cuerpos de inclusión de dos proteínas relacionadas al sistema inmune innato de salmón del Atlántico. En el segundo objetivo, evaluaremos la capacidad de inmunomodulación del sistema inmune por parte de los cuerpos de inclusión al ser administrados en diferentes dosis a través de la intubación de los peces. Para ello usaremos RT-qPCR donde analizaremos la capacidad moduladora de los cuerpos de inclusión a través de la expresión génica de citoquinas proinflamatorias (TNFα, IL-1β, IFNγ), antiinflamatorias (IL-10), enzima proinflamatoria (COX-2), y receptor tipo Toll (TLR9). También analizaremos TNFα e IL-10 a través de ELISA. Igualmente, se analizará si los cuerpos de inclusión marcados con un fluoróforo son endocitados por células intestinales y si son trasladados al bazo a través de citometría de flujo. En el tercer objetivo, analizaremos la eficacia de los cuerpos de inclusión para el control de P. salmonis en salmón del Atlántico administrados a través del alimento en un desafío experimental. Se evaluará a través de técnicas moleculares (RT-qPCR y ELISA) citoquinas proinflamatorias, antiinflamatorias, enzima proinflamatoria, y receptor tipo Toll para analizar la capacidad inmunomoduladora de los cuerpos de inclusión durante un desafío bacteriano. Asimismo, evaluaremos sobrevivencia, carga de P. salmonis y necropsia de los tejidos. Nosotros esperamos como resultado de esta investigación que los cuerpos de inclusión aumenten la sobrevivencia de salmón del Atlántico frente a un desafío de P. salmonis. El desarrollo de un método profiláctico efectivo contra P. salmonis permitirá disminuir las pérdidas económicas asociadas a la Piscirickettsiosis y disminuir el uso excesivo de antibióticos en la industria de cultivo de salmones en Chile.

Stochasticity in optimization and game theory is a very important aspect to model more accurately real-world problems in many different areas (see for instance [6]). In optimization problems as well as in one-level games, namely, Nash equilibrium problems, stochasticity aspects have received quite a lot of attention for a while and have also been well studied [22]. However, for the branch of bilevel games quite few studies have included in their analysis stochastic aspects in their models. A bilevel game is basically to split a finite set of players into two levels: the leaders or upper-level players, and the followers or lower-level players. In the model, the followers react in a passive way to the leaders' actions, while the leaders compete in the upper level trying to actively anticipate the followers' reaction. Moreover, in each level, the interaction is non-cooperative as in Nash equilibrium problems. Bilevel games have been recognized as one of the most complex and at the same time very useful models in the literature [17]. Bilevel games, and more precisely the problem of the leaders in a bilevel game, face an ambiguity/uncertainty whenever the followers' reaction is not necessarily uniquely determined for each leaders' decision. To deal with this ambiguity two main approaches are well-known the optimistic and the pessimistic. The weakness of these two approaches is that both are quite extreme and the optimistic one lacks of real modeling foundations, putting the leaders in a quite naive position. Recently, in [9] a general stochastic approach has been proposed to solve this ambiguity, which is seen as an uncertainty of the problem, providing also a specific approach that seems to be more reasonable than the optimistic one, from a modeling point of view. The stochasticity in the stochastic approach is an endogenous one since it corresponds to a decision-dependent uncertainty [1, 23]. But, of course, stochasticity might also come from an exogenous side, that is, when some of the parameters defining the game, such as future demand and prices, 1 forecasts of winds and clouds, are uncertain and possibly follow some probability distribution. This has been considered in [34, 12, 13, 16]. In the second part of the project, which is the applied part, we are interested in using the developed theoretical framework of bilevel games with stochastic aspects to a problem of contaminated water resource management, which has high levels of stochasticity. The scarcity of water resource and its efficient use has been recognized as an extremely important problem in Chile and the whole world, for agricultural, industrial, and human use. Moreover, after any use, there is an outflow of water which has generally more contaminants than the inflow. Depending on the type and quantity of contaminants the outflow of water could be reused, but sometimes giving less profit to the entity. The general situation is full of uncertainties, since the entities do not share their information. Moreover, the main source of information for us will be measurements on the quality of water at different strategic points and punctual events of contamination registered by inspection, which is simply a qualitative data. Therefore, we propose first to apply predictive models and machine learning to do inverse engineering in order to understand the game played by the different actors. Then we want to study the underlying one-level game and study the design of mechanisms (bilevel game) so that we can move the equilibrium to a desired goal. In a somehow similar spirit, in [30, 31, 10] game theory techniques have been used to analyze the behavior of companies sharing contaminated water in the context of eco-industrial parks, while in [36] also a bilevel model is used for a water resource optimal allocation problem.

La Fundación financió las excavaciones arqueológicas y paleontológicas del yacimiento Tagua Tagua 3

Stochasticity in optimization and game theory is a very important aspect to model more accurately real-world problems in many different areas (see for instance [6]). In optimization problems as well as in one-level games, namely, Nash equilibrium problems, stochasticity aspects have received quite a lot of attention for a while and have also been well studied [22]. However, for the branch of bilevel games quite few studies have included in their analysis stochastic aspects in their models. A bilevel game is basically to split a finite set of players into two levels: the leaders or upper-level players, and the followers or lower-level players. In the model, the followers react in a passive way to the leaders' actions, while the leaders compete in the upper level trying to actively anticipate the followers' reaction. Moreover, in each level, the interaction is non-cooperative as in Nash equilibrium problems. Bilevel games have been recognized as one of the most complex and at the same time very useful models in the literature [17]. Bilevel games, and more precisely the problem of the leaders in a bilevel game, face an ambiguity/uncertainty whenever the followers' reaction is not necessarily uniquely determined for each leaders' decision. To deal with this ambiguity two main approaches are well-known the optimistic and the pessimistic. The weakness of these two approaches is that both are quite extreme and the optimistic one lacks of real modeling foundations, putting the leaders in a quite naive position. Recently, in [9] a general stochastic approach has been proposed to solve this ambiguity, which is seen as an uncertainty of the problem, providing also a specific approach that seems to be more reasonable than the optimistic one, from a modeling point of view. The stochasticity in the stochastic approach is an endogenous one since it corresponds to a decision-dependent uncertainty [1, 23]. But, of course, stochasticity might also come from an exogenous side, that is, when some of the parameters defining the game, such as future demand and prices, 1 forecasts of winds and clouds, are uncertain and possibly follow some probability distribution. This has been considered in [34, 12, 13, 16]. In the second part of the project, which is the applied part, we are interested in using the developed theoretical framework of bilevel games with stochastic aspects to a problem of contaminated water resource management, which has high levels of stochasticity. The scarcity of water resource and its efficient use has been recognized as an extremely important problem in Chile and the whole world, for agricultural, industrial, and human use. Moreover, after any use, there is an outflow of water which has generally more contaminants than the inflow. Depending on the type and quantity of contaminants the outflow of water could be reused, but sometimes giving less profit to the entity. The general situation is full of uncertainties, since the entities do not share their information. Moreover, the main source of information for us will be measurements on the quality of water at different strategic points and punctual events of contamination registered by inspection, which is simply a qualitative data. Therefore, we propose first to apply predictive models and machine learning to do inverse engineering in order to understand the game played by the different actors. Then we want to study the underlying one-level game and study the design of mechanisms (bilevel game) so that we can move the equilibrium to a desired goal. In a somehow similar spirit, in [30, 31, 10] game theory techniques have been used to analyze the behavior of companies sharing contaminated water in the context of eco-industrial parks, while in [36] also a bilevel model is used for a water resource optimal allocation problem.

Desarrollo de réplicas fidedignas e interactives de objetos deformables del mundo real. La principal aplicación estudiada serán los phantomas de órganos humanos, que permitirán la validación de intervenciones así como ayudar durante la formación de especialistas.

In the previous project the research focus was on the sensing principle and the development of prototype modules for a tactile proximity sensor (TPS). In the current project the focus is on the methods and algorithms with which the events in the near proximity of the robots can be modelled by means of these sensors. Collectively, the TPS on the robot surface and gripper constitute a smart skin. The application scenarios here are the Active Exploration of the Environment, Grasping and the Safe Human-Robot-Interaction. The methods to be developed will improve significantly on the quality of state of the art methods and expand the horizon of possible solutions for these problems. The capacitive measuring principle and the spatial resolution in both, the tactile and proximity modalities, enable an area-wide and distance based coverage of the robot surroundings. It is the first time that algorithms for Exploration, Grasping and Safe-Human-Robot-Interaction are presented that rely simultaneously on both tactile and proximity sensing with spatial resolution. The goal of the Exploration is to research which methods and strategies enable the robot to acquire a contact- and proximity-based world-model by means of TPS. The quality of state of the art solutions for grasping should be improved significantly. For the Safe-Human-Robot-Interaction algorithms should be developed that adapt the robots path and velocity according to the current situation as determined by the TPS. Also, new algorithms should make a TPS-based Interaction possible with the goal of robot controlling and programming by the human through tactile and proximity input. Finally, according to the context of the task and situation at hand (Exploration, Manipulation and Interaction) the robot should show an appropriate behaviour which is given by a behavioural strategy that will also be developed. The starting point in the project is the TPS-modules which were successfully developed in the previous project. At the beginning, research will be focused on the algorithms for signal processing that extract robust features from TPS for higher level tasks. This step is followed by the integration of TPS into a robot system realizing the smart skin. Building on these steps the methods for Exploration, Manipulation and Safe-Human-Interaction are developed. Finally, the results of the project will be shown and evaluated in a combined demonstration scenario that includes a robot endowed with TPS.

Fondos para apoyar la realizacion de la Third Latin American Summer School on Cognitive Robotics (LACORO 2024). La primera edición se realizó online en octubre de 2020; la segunda fue presencial en enero de 2023; la tercera versión tendrá lugar entre el 9 y el 13 de diciembre de 2024 en la Universidad de O'Higgins en Rancagua, Chile. https://lacoro.org/ Esta Escuela de Verano beneficiará principalmente a Estudiantes y Académicos de las Américas interesados en la Investigación en Inteligencia Artificial aplicada a la Robótica. Nuestro objetivo es fomentar la colaboración nacional y regional en esta área de investigación. Para la primera edición, alcanzamos 241 inscripciones para actividades online de todo el mundo, y la segunda versión tuvo 166 inscripciones para actividades presenciales en enero de 2023, principalmente de Chile, México, Argentina, Brasil y Uruguay.

KhipuX support grant for organizing the Third Latin American Summer School on Cognitive Robotics (LACORO) https://www.lacoro.org/