Research Projects

Home 5 Research Projects

OPTIMIZATION OF HIGH-IMPACT POLYSTYRENE PRODUCTION: TOWARDS A CIRCULAR ECONOMY

LEAD DEPARTMENT

Chemical and Petroleum Engineering

CENTER / GROUP / LAB

CIMA – Polymerization Reactors Group

DIRECTOR

Juan M. Maffi, Eng.

DESCRIPTION

The overall goal of the project is to predict the morphology of high-impact polystyrene (HIPS) as a function of polymerization recipes and operational variables, and then to interrelate this morphology with the final properties of the material. Our particular interest to predict the quality variables of the product (admissible stress, impact resistance, copolymer structure, etc.) in order to be able, as our ultimate objective, to develop a tool capable of determining the conditions necessary to produce custom-made polymers.
Likewise, and being aware of the environmental issues linked to the production of oil by-products, the possible ways of degradation of the finished material will be studied in order to transform it again into raw material. In this way, we will try to close a production cycle that takes into account not only its use but also its potential reuse in the polymerization plants. This analysis will be developed both from the technical and the economic perspective.

HYDROCARBON ANALYSIS

LEAD DEPARTMENT

Chemical and Petroleum Engineering

CENTER / GROUP / LAB

DIRECTOR

Silvia Barredo, Ph.D.

DESCRIPTION

This doctorate is within the agreement between Pampa Energía and lTBA. It focuses on the study of the Vaca Muerta Formation with the main objective of improving the quality of its hydraulic fracturing. In particular, the study focuses on the analysis of the controls of the fissility of fine grained rocks and how this property, which in principle is expressed only on the surface (thanks to its exposure to environmental pressures and weathering), potentially affects its behavior when fracturing. For this purpose, there are several crown blocks of the stated formation which will be related to samples extracted from outcrops.

DEVELOPMENT OF STIMULI-SENSITIVE POLYMERS FOR A CONTROLLED RELEASE OF AGROCHEMICALS.

LEAD DEPARTMENT

Chemical Engineering

CENTER / GROUP / LAB

CIMA – Environmental Engineering Center

DIRECTOR

María Inés Errea, Ph.D.

DESCRIPTION

The use of agrochemicals for the preservation of crops is controversial, because it is questioned whether their toxicity could put human and animal health at risk and alter the natural ecosystem; but at the same time, without them, large-scale agricultural production would not be feasible. In order to reduce the quantities of agrochemicals used while minimizing their negative environmental impact, intensive work is being done to develop systems that make their application more efficient. Systems of controlled release of agrochemicals that allow their active principles to reach the target at pre-established concentrations and times could represent a solution to the problem. In this context, the purpose of the Project is to develop new stimuli-sensitive materials, sometimes called “intelligent polymers”, using natural biodegradable raw materials for the controlled release of agrochemicals.

COMPUTATIONAL MODELING AS A TOOL TO ASSESS THE SUSCEPTIBILITY OF ORGANIC COMPOUNDS TO DEGRADATION BY ADVANCED OXIDATION PROCESSES.

LEAD DEPARTMENT

Chemical Engineering

CENTER / GROUP / LAB

CIMA – Environmental Engineering Center

DIRECTOR

María Inés Errea, Ph.D.

DESCRIPTION

In recent years there has been increasing concern about the presence of persistent organic compounds, such as herbicides, dyes and antibiotics in waterways. The use of environmentally friendly technologies for the degradation of these compounds, such as advanced oxidation processes, is one of the most attractive alternatives for the resolution of these compounds and one of the most explored at present. However, in many cases these oxidation processes are not effective and, therefore, the Project is based on studying by means of computational modeling the compounds of interest, so as to predict their susceptibility to this type of treatment, which would allow a rational use of this type of methodology.

COLLECTIVE BEHAVIOR OF ROBOTS INTERACTING WITHIN A CLOSED PERIMETER

LEAD DEPARTMENT

Computer Engineering

CENTER / GROUP / LAB

CAFByS – Center for Physical, Biological and Social Agents

DIRECTOR

Germán A. Patterson, Ph.D.

DESCRIPTION

This project deals with the study of self-propelled interacting agents. The goals are to typify the behavior of a set of robots in a specific confined space and study the synchronization phenomenon of agents to perform tasks together.

SAR IMAGE AUTOMATIC SEGMENTATION AND INTERPRETATION

LEAD DEPARTMENT

Computer Engineering

CENTER / GROUP / LAB

CIC – Computational Intelligence Center

DIRECTOR

María Juliana Gambini, Ph.D.

DESCRIPTION

SAR (Synthetic Aperture Radar) images are of utmost importance in many applications such as environmental monitoring, damage assessment in natural disasters and urban planning, among others. They pose the difficulty that they are very difficult to analyze because they are contaminated with speckle noise. This noise is non-additive, non-Gaussian and very difficult to remove, so statistical modeling of these images is essential. The purpose of this project is to develop mono-polarimetric and polarimetric SAR image analysis methods by combining statistical modeling with classification techniques based on machine learning.

SPECKLE NOISE REMOVAL IN SAR IMAGES

LEAD DEPARTMENT

Computer Engineering

CENTER / GROUP / LAB

CIC – Computational Intelligence Center

DIRECTOR

María Juliana Gambini, Ph.D.

DESCRIPTION

The interference from reflected waves during the SAR-image acquisition process gives rise to the non-additive, non-Gaussian noise that characterizes them and which is known as speckle noise. This noise makes SAR images very difficult to analyze and interpret automatically, and therefore the development of techniques to remove this noise poses a challenge. Non-local filters use the information present in several pixels, not necessarily in each pixel environment. These filters have been developed with relative success for Gaussian noise removal. In SAR images, the information present in a one- pixel small environment is very confusing, precisely due to the speckle noise. On the other hand, the stochastic nature of these images forces the data to be modeled with appropriate statistical distributions. One of the distributions that can be used in the modeling of this type of data is the GI0 distribution. This project deals with the development of new algorithms to remove speckle noise, using non-local filters and the GI0 distribution.

DEVELOPMENT OF A ROBOT FOR THE INSPECTION OF SMALL DIAMETER RAINWATER PIPES

LEAD DEPARTMENT

Computer Engineering

CENTER / GROUP / LAB

CIC – Computational Intelligence Center

DIRECTOR

Juan Santos, Ph.D.

DESCRIPTION

The inspection of small diameter rainwater pipes is aimed at detecting failures, obstructions or clandestine connections to the storm sewer network that drains into the trunk system. Recently a robot has been developed for inspecting larger diameter pipes but the design criteria and proposed solutions for such a robot cannot be directly scaled up. In this project, the prevailing hypothesis is based on the fact that size restrictions must be addressed by focusing on the morphology of the caterpillar tracks; also, the image capture scheme must be static, and the internal processing scheme must be restricted to handling information packages and controlling the movement of actuators and acquiring sensing data.

DESIGN AND IMPLEMENTATION OF TOOLS FOR THE ADMINISTRATION AND ANALYSIS OF COMPLEX DATA EVOLUTION INTO BIG DATA USING GRAPH DATABASES

LEAD DEPARTMENT

Computer Engineering

CENTER / GROUP / LAB

CI – IT Center

DIRECTOR

Alejandro Vaisman, Ph.D.

DESCRIPTION

The new data analysis paradigms must be not only able to handle alphanumeric data, but must also support operations on different types of data, for example, geographic, raster satellite images, multimedia data (audio/video), unstructured information on social media, among others. These new types of data are characterized by their non-relational nature, and, essentially, by their connectivity, which has been growing exponentially, driven by various initiatives and applications. Graphs are possibly the best data structure to represent the immense network of connections that underlie the applications and problems mentioned above. For this reason the use of graph databases (a particular case of NoSQL technology) as a solution to the problem of storing and analyzing these huge graphs has consistently prevailed. The dimension of time is present in most of the problems and applications mentioned above. As a well-known example, graphs representing social media evolve permanently in time (as in the cases where friends are added and removed, or preferences are modified). The analysis of this temporal information (whether to perform data mining, summarizations, etc.), requires tools that allow it to be managed, consulted, analyzed and visualized efficiently. Surprisingly, in spite of the relevance of this problem, the database community has not paid enough attention to the subject so far. This project aims to occupy that space, by developing techniques and models that allow for the evolution of large volumes of data represented in the form of graphs varying in time to be integrated, published, linked, consulted, analyzed and visualized, and for the solution to be applied to real case studies where traditional solutions are not effective.

STUDY AND DEVELOPMENT OF THE TRANSFORMATION OF IMAGES CAPTURED BY A CAMERA WITH LENSES OF A 180° FIELD OF VIEW TO ITS EQUIRECTANGULAR PROJECTION.

LEAD DEPARTMENT

Computer Engineering

CENTER / GROUP / LAB

CIC – Computational Intelligence Center

DIRECTOR

Juan Santos, Ph.D.

DESCRIPTION

The need for image-capture schemes with static cameras leads to pay special attention to optics with a wider field of view, such as fisheye lenses with a 180° angle. However, the use of such cameras results in images with a spherical projection which are not natural for the ordinary user and it also makes processing for detection, measurement or identification techniques difficult. This project aims to study and research two approaches to deal with the problem. On the one hand, the calibration methods that enable the reconstruction of the image with a suitable projection for its visualization, and on the other hand, the use of transformations that correct the distortions caused by optics.

DEVELOPMENT OF A VISION SYSTEM FOR SENSING AN ELECTRIC AND AUTONOMOUS CAR. IN PARTNERSHIP FOR THE FSAE PROJECT OF ITBA MECHANICS DEPARTMENT.

LEAD DEPARTMENT

Computer Engineering

CENTER / GROUP / LAB

CIC – Computational Intelligence Center

DIRECTOR

Juliana Gambini, Ph.D.
Rodrigo Ramele, Ph.D.
Alan Pierri, Eng.
Juan Santos, Ph.D.

DESCRIPTION

ITBA’s Mechanic Department is currently conducting an important project for the development of an autonomous electric car that can compete in the FSAE category. The project poses challenges of different types and nature, in particular, to provide the car with a sensing system that provides enough information to make the right decisions in terms of steering and acceleration as required by its control system.
The purpose of this project is to assess the possibility of using one or more video cameras to capture images, which after being processed can provide sufficient information on the state of the environment, and eventually, the creation of maps, required for the vehicle’s self-driving. Our hypotheses points both to the use of specific image processing techniques and to the use of artificial neural networks to achieve the objective proposed.

DEVELOPMENT OF AN OXYGEN TRANSPORT ROBOT FOR PULMONARY REHABILITATION THERAPIES.

LEAD DEPARTMENT

Computer Engineering

CENTER / GROUP / LAB

CIC – Computational Intelligence Center

DIRECTOR

Esteban Buniak
Rodrigo Ramele, Ph.D.
Juan Miguel Santos, Ph.D.

DESCRIPTION

This work is performed under the ALPI-ITBA (CEC No. 1 – 2019) agreement.
It consists of the development of a robot for the transport of the oxygen tank in the Pulmonary Rehabilitation procedures that are performed at ALPI. The device consists of a mobile robot with an embedding system to carry the oxygen tank. The robot control system is based on two tethers that serve to determine the direction of movement.

TRAINING A GAMING AGENT THROUGH BRAIN SIGNALS

DPTO. LÍDER

Industrial

CENTER / GROUP / LAB

CIC – Computational Intelligence Center

DIRECTOR

Rodrigo Ramele, Ph.D.
Juan Miguel Santos, Ph.D.

DESCRIPTION

Error-related potentials (ErrP) are generated when a person performs or visualizes an erroneous action, either their own or that of a third party. They can be detected by means of Electroencephalography studies. These potentials can be used to provide reinforcement information for an intelligent agent that has to solve a simple game, through a Reinforcement Learning algorithm.

WATER TREATMENT

LEAD DEPARTMENT

Computer Engineering

CENTER / GROUP / LAB

CIMA – Environmental Engineering Center

DIRECTOR

María Inés Errea, Ph.D.

DESCRIPTION

Water deterioration over recent decades, due to industrial, domestic and agricultural waste generated by human activities, is very worrying and stimulates the search for new materials and technologies aimed at its remediation. In particular, heavy metals are of particular concern because they are toxic at very low concentrations and, for that reason, do not alter the organoleptic properties of water, preventing the consumer from perceiving the risk of consuming it. In this context, the main goal of this project is to develop new adsorbents for the remediation of water contaminated with heavy metals, using raw materials from renewable, abundant and biodegradable biomass.

COMBINATION OF MODEL CHECKING AND SAT-SOLVING TO IMPROVE CODE ANALYSIS.

LEAD DEPARTMENT

Computer Sciences

CENTER / GROUP / LAB

CI – Computer Sciences Center

DIRECTOR

Marcelo F. Frías, Ph.D.

DESCRIPTION

The general purpose of this project is to improve the state of the art in program analysis and automatic test case generation. To this end we will concentrate on the following specific goals:
1) Code analysis and test generation for the code that manipulates XML; 2) Use of dimensions to improve the performance of model checking; 3) Analysis of the performance of the code that manipulates complex objects.

SCALABLE MODEL AND APPLICATION ANALYSIS USING SAT-SOLVING.

LEAD DEPARTMENT

Computer Sciences

CENTER / GROUP / LAB

CI -Computer Sciences Center

DIRECTOR

Marcelo F. Frías, Ph.D.

DESCRIPTION

The goal of this project is the search for new techniques (and the implementation of tools that support these techniques) for the analysis of models and applications using SAT-solving as the central technique. Due to the theoretical limitations that SAT-solving has, we will concentrate on the search for scalable techniques.

AUTOMATIC MEASUREMENT OF OCCUPANCY AT LARGE EVENTS BASED ON AIRBORNE SENSORS.

LEAD DEPARTMENT

Computer Sciences

CENTER / GROUP / LAB

CAFByS – Center for Physical, Biological and Social Agents

DIRECTOR

Daniel Parisi, Ph.D.

DESCRIPTION

The goal is to develop the foundations of a system to quantify the number of people attending a large, open-air event such as a concert, a street demonstration, etc. This system will consist of an unmanned aerial vehicle (UAV / drone) equipped with a DUAL camera (visible+infrared). Since the UAV will be designed to fly over people, it is necessary to equip it with safety systems to avoid failures and possible falls. In that sense, the UAV will have control algorithms tolerant to partial failures and a parachute that will be activated in case of emergency. The data and images recorded by the sensors will be processed off-line in order to obtain a detailed density map of the area surveyed, which will also allow the total audience to be calculated.

T-CELL CROWD CONTROL

LEAD DEPARTMENT

Computer Sciences

CENTER / GROUP / LAB

CAFByS – Center for Physical, Biological and Social Agents

DIRECTOR

Daniel Parisi, Ph.D.

DESCRIPTION

International project funded by the Human Frontier Science Program (HFSP) consortium granted to a multidisciplinary team made up of three research centers in three universities in three countries: Canada (McGill University), The Netherlands (Radboud University) and Argentina (ITBA).
T-cells are key agents of the adaptive immunity that are constantly on the move, can enter most tissues and operate in large crowds and extremely high densities. It is not clear how they achieve this: although new microscopy modalities can visualize T cells migrating into the living tissue, studies of T cell movement have focused primarily on individual cells and have not addressed the possible collective effects of traffic jams and bottlenecks that normally hinder movement. The goal of the project is to study experimentally in vitro and in vivo the dynamics of this cellular system in order to develop physical-computational models to simulate this type of systems. And to advance in understanding why this dynamic of the T cells is affected by not being able to enter some types of tumor tissues.

MULTILEVEL CURRENT SOURCE INVERTER (MCSI)

LEAD DEPARTMENT

Electrical and Electronics

CENTER / GROUP / LAB

CIDEI

DIRECTOR

D. Eng. Miguel Aguirre

DESCRIPTION

Development, modeling and control of a modular MCSI prototype with fault tolerant operating capacity. There is a development platform for different topologies of MCSI converters, with up to 10kW power capacity and 9 levels. All the associated electronics to develop complex control techniques on both on-grid and off-grid (connected or not to the power grid) converters is also available, through the use of the CIDEI’s internal instrumented microgrid.

MICROGRID WITH HIGH PENETRATION OF SOLAR PHOTOVOLTAIC ENERGY.

LEAD DEPARTMENT

Electrical and Electronics

CENTER / GROUP / LAB

CIDEI

DIRECTOR

D. Eng. Miguel Aguirre

DESCRIPTION

Development, instrumentation, modeling and control of a solar energy-based microgrid. We are fitted with a 12 kW installation of solar panels, connected to a microgrid which is in turn connected to the university’s network. Different configurations and control strategies are analyzed by comparing the results of different converters, both commercial and prototypes developed ad-hoc.

WIRELESS CHARGING

LEAD DEPARTMENT

Electrical and Electronics

CENTER / GROUP / LAB

CIDEI

DIRECTOR

D. Eng. Pablo Cossutta

DESCRIPTION

Development, instrumentation, modeling and control of a platform for wireless charging of electronic equipment The project is divided into two parts, due to the special characteristics of each application:
– High power: specially oriented to electric vehicles.
Low power: for low power electronic equipment and devices.
– The practical technical aspects of the technologies involved are studied, as well as advanced techniques of non-linear control, especially suitable due to the particular characteristics of energy transfer through the air.

ARTIFICIAL INTELLIGENCE AND ITS APPLICATION TO POWER CONVERTERS AND ALTERNATIVE ENERGIES.

LEAD DEPARTMENT

Electrical and Electronics

CENTER / GROUP / LAB

CIDEI

DIRECTOR

D. Eng. Pablo Cossutta

DESCRIPTION

Development and implementation of Artificial Intelligence techniques (Deep Learning) for the modulation and control of power converters, especially those used as alternative energy interfaces. It has been proved that practical results of excellent performance are achieved with minimum computing power requirements.

DEVELOPMENT, CHARACTERIZATION AND MODELING OF MATERIALS AND STRUCTURES FOR APPLICATION IN ADDITIVE MANUFACTURING.

LEAD DEPARTMENT

Industrial

CENTER / GROUP / LAB

Digital Manufacturing Lab

DIRECTOR

Leopoldo De Bernardez, Ph.D.

DESCRIPTION

Numerical models, including the properties of the materials used and the effects of the manufacturing process parameters, are developed and experimentally validated to predict the in-service behavior of industrial and medical products obtained through additive manufacturing.

FORECASTING METHODOLOGIES FROM AGENT-BASED SIMULATION AND DEEP LEARNING.

LEAD DEPARTMENT

Industrial

CENTER / GROUP / LAB

Center for Optimization and Simulation Studies

DIRECTOR

Leopoldo De Bernardez, Ph.D.

DESCRIPTION

Advanced forecasting techniques based on agents and deep learning are used to estimate and forecast future demand for a service based on previous decisions and results obtained by users, maximizing the use of historical data.

OPTIMIZATION HEURISTICS AND MACHINE LEARNING FOR NETWORKS DESIGN AND COMPLEX SYSTEMS MANAGEMENT.

LEAD DEPARTMENT

Industrial

CENTER / GROUP / LAB

Center for Optimization and Simulation Studies

DIRECTOR

Leopoldo De Bernardez, Ph.D.

DESCRIPTION

Different algorithms are proposed to optimize both the design of distribution networks and the operational strategies of inventory management applicable in particular to logistics systems.

ALTERNATIVE TRANSPORT FUELS.

LEAD DEPARTMENT

Industrial

CENTER / GROUP / LAB

Integrated Logistics and Operations Center

DIRECTOR

Leopoldo De Bernardez, Ph.D.

DESCRIPTION

Description: Possible options to facilitate the adoption of alternative fuels are assessed and quantified with a focus on improving transport costs and sustainability.

REGIONAL SURVEY ON THE STATUS OF SUSTAINABLE LOGISTICS.

LEAD DEPARTMENT

Industrial

CENTER / GROUP / LAB

CLIO / OLS

DIRECTOR

Gonzalo López Escrivá

DESCRIPTION

The purpose of the Sustainable Logistics Survey is to measure the degree of interest that companies have concerning regulations, policies, applied practices and the corresponding measurement of impact on sustainability and logistics. The OLS, started in 2014, carries out the survey once a year, with the participation of companies from different sectors, both industrial and service, associated with the logistics sector as well as others. In 2020 the seventh edition is being carried out in Argentina and the second at a regional level. Since 2019, the work is being done together with 7 Latin American countries (Uruguay, Brazil, Chile, Peru, Colombia and Bolivia), presenting a report of Argentina and its regional comparison.

GOOD SUSTAINABILITY PRACTICES IN ARGENTINE PORTS – 2020 UPDATE.

LEAD DEPARTMENT

Industrial

CENTER / GROUP / LAB

CLIO / OLS

DIRECTOR

Gonzalo López Escrivá

DESCRIPTION

In 2017 exploratory work was carried out regarding the current situation of sustainability in the Argentine port sector. The purpose was to identify good practices and initiatives concerning this issue and to provide a starting point for future development. In 2020, the issue is being updated in order to detect the progress made in good practices.

STUDY OF THE CONSOLIDATION, REACTIVATION AND INTEGRATION OF NEW MEMORIES DURING SLEEP AND WAKEFULNESS.

LEAD DEPARTMENT

Life Sciences Department

CENTER / GROUP / LAB

Sleep & Memory Lab

DIRECTOR

Cecilia Forcato, Ph.D

DESCRIPTION

Memories after their acquisition go through a period of lability, in which they are sensitive to amnesic and facilitating agents. This period is followed by a stabilization process known as consolidation. Once consolidated, memories can be reactivated during wakefulness, by a reminder, thus returning to a new state of lability followed by a process of re-stabilization (reconsolidation). In turn, recently acquired memories are spontaneously reactivated during sleep. These reactivations can also be induced in the lab by presenting cues during sleep to the learned task and an improvement in the reactivated memory is observed. Thus, reactivations during slow-wave sleep (SW) would promote the consolidation of associative memories and details, by allowing the hippocampal-cortical communication, while the reactivation during sleep of rapid eye movements (REM) would facilitate the integration of new memories to cortical circuits favoring the generalization and formation of memory schemes. In this project we study the role of sleep in the formation, modification and integration of declarative memories, at behavioral and electrophysiological level, as well as the differences and similarities between consolidation and reconsolidation during wakefulness and sleep. To this end, we also design algorithms for the automatic detection of specific events during sleep in partnership with Rodrigo Ramele, PH.D. (Computational Intelligence Center, ITBA).

LUCID DREAMING AND OUT-OF-THE-BODY EXPERIENCES INITIATED FROM SLEEP PARALYSIS AS TOOLS FOR THE STUDY OF CONSCIOUSNESS AND DEVELOPMENT OF A LUCIDITY INDUCING DEVICE.

LEAD DEPARTMENT

Life Sciences Department

CENTER / GROUP / LAB

Sleep & Memory Lab

DIRECTOR

Cecilia Forcato, Ph.D.

DESCRIPTION

Understanding what consciousness is constitutes one of the cutting-edge topics in the area of neuroscience. In the lab we are investigating states of consciousness other than wakefulness: Lucid Dreaming and Out-of-the-Body Experiences. Lucid dreaming, which occurs mainly during Rapid Eye Movement (REM) sleep, is characterized by the reappearance of higher cognitive abilities found in wakefulness: the dreamer becomes aware that he is dreaming, has all the mnésic capacities of wakefulness, and can control sleep at will. Out-of-the-Body Experience (OBE) is defined as the experience in which the observer perceives the world from another point of view, outside of his physical body. The subjective perception of the state of consciousness in lucid dreaming differs from the state of consciousness in OBE. Lucid dreamers report a state of consciousness similar to wakefulness while OBEs report an increased state of consciousness and timelessness. Our goal is to study these physiological states of consciousness. With a basic approach we work with participants’ accounts, perform polysomnographic studies and an Electroencephalogram (EEG) analysis to establish, in partnership with Pablo Gleiser, Ph.D. (CNEA, Bariloche), topographic properties of the networks of global brain activity for different states of consciousness. On the other hand, we study dream reporting during these states of consciousness through the graph analysis in partnership with Daniela Godoy, Ph.D. (UNICEN). Moreover, given the ability to control lucid dreams at will, they have been proposed as a possible strategy to combat recurrent nightmares, mainly in post-traumatic stress disorder (PTSD). To that end, we are working with Rodrigo Ramele, Ph.D. (Computational Intelligence Center, ITBA) in the design and development of a new device to induce lucid dreams.

CONSTRUCTION OF FALSE MEMORIES IN WITNESSES OF A CRIMINAL EVENT: INTERVENTION OF CONSOLIDATION, RECONSOLIDATION, PHARMACOLOGY, MOODS, AGE, PERSONALITY AND SLEEP STAGES.

LEAD DEPARTMENT

Life Sciences Department

CENTER / GROUP / LAB

Sleep & Memory Lab

DIRECTOR

Cecilia Forcato, Ph.D.

DESCRIPTION

Testimonial evidence is the most important source of evidence for a large number of court decisions. However, declarative memory is not a video camera that faithfully reproduces the past; on the contrary, it is highly malleable, subject to distortion, and can lead to the formation of false memories, that is to say, memories of events that never happened. Research in Cognitive Psychology showed that witnesses can give confident but incorrect reports, and that suggestions, as well as erroneous information that witnesses receive after the event can easily modify the memory of the witness. Moreover, not only can the details of a memory be modified, but entire memories of events that never occurred can be implanted. It should be noted that about 70% of cases of wrongful convictions are the result of errors in photographic recognition or lineups. We are currently working in partnership with the NGO Innocence Project Argentina investigating how sleep, specific cortical oscillatory activity, consolidation and reconsolidation processes, different neurotransmission types, age and personality, influence the generation of false memories of criminal events.

NON-INVASIVE STIMULATION DURING SLEEP: IMPROVEMENT OF MEMORIES AND DEVELOPMENT OF THERAPEUTIC STRATEGIES IN OLDER ADULTS WITH NEUROCOGNITIVE DISORDERS AND DEVELOPMENT OF A SLOW WAVE INDUCTION DEVICE.

LEAD DEPARTMENT

Life Sciences Department

CENTER / GROUP / LAB

Sleep & Memory Lab

DIRECTOR

Errea, María Inés

DESCRIPTION

Sleep is essential for recovering energy sources, restoring tissues, thermoregulating, cleaning the brain of aberrant proteins and free radicals, regulating the metabolism, restoring of the immune system and for the acquisition, consolidation and reconsolidation of memory. Sleep deprivation and sleep disruption cause severe cognitive impairment and emotional problems. It has been observed that animals deprived of sleep for several weeks show a failure to regulate temperature and weight, and eventually die from infections and tissue damage. The very structure of sleep changes as we age, with a reduction in slow wave (SW) sleep (both in SW time and in the quality and quantity of slow cortical waves) and rapid eye movement (REM) sleep, as well as an increase in sleep fragmentation. In this project we study the mechanisms linked to the improvement of declarative memories during sleep and wakefulness in healthy older adults with mild cognitive impairment. We further investigate the impact on sleep quality, coding, consolidation and evocation of episodic memories, and the emotion variables of combined treatments involving sleep hygiene guidelines. At the same time, we are developing a closed-loop Acoustic Stimulation device, in partnership with Rodrigo Ramele, PH.D. (Computational Intelligence Center, ITBA) to increase the quality of slow waves in the study population, and evaluate their impact on different cognitive processes.

IMPACT OF COVID-19 CONTAINMENT POLICIES ON COGNITIVE ABILITIES, THE EMOTIONAL STATE OF THE POPULATION AND THE HEALTH SYSTEM FUNCTIONING IN THE ARGENTINE REPUBLIC.

LEAD DEPARTMENT

Life Sciences Department

CENTER / GROUP / LAB

Biology of Memory and Translational Neuroscience Lab

DIRECTOR

Diego Moncada
Fabricio Ballarini, Ph.D.

DESCRIPTION

The general goal of this project is to evaluate the effect of COVID-19 and ASPO (preventive and compulsory social isolation) on health from the individual and social point of view, focusing on its impact on people’s cognitive abilities and on the health system’s capacity for attention and prevention. It is a project that involves multiple researchers from different universities and research institutes.

CELLULAR MECHANISMS. BEHAVIOR LABELING DURING MEMORY RECONSOLIDATION: STUDY OF THE MECHANISMS ASSOCIATED WITH THE IMPROVEMENT OR DETERIORATION OF MEMORIES.

LEAD DEPARTMENT

Life Sciences Department

CENTER / GROUP / LAB

Biology of Memory and Translational Neuroscience Lab

DIRECTOR

Diego Moncada

DESCRIPTION

The general goal of this work is to study the process of behavior labeling during memory reconsolidation in order to understand how extrinsic events at the time of evocation can affect the trace. In this way, strategies can be developed to attenuate or enhance memories in a specific way. In particular, we will study the neurotransmission systems and the cellular mechanisms associated to the proteins synthesis and to the establishment of behavior labelling during memory reconsolidation in contexts that enhance or attenuate previously established memories.

RECONFIGURABLE SENSOR NETWORKS FOR ENVIRONMENTAL DATA CAPTURE VIA MULTI-DOMAIN ROBOTS

LEAD DEPARTMENT

Mathematics

CENTER / GROUP / LAB

CESYC – Systems and Control Center

DIRECTOR

Ignacio Mas, Ph.D.

DESCRIPTION

The goals of this project are to make progress in the development of cooperative techniques for airborne and marine robots, with emphasis on environmental monitoring tasks; to evaluate the technology at pilot scale to demonstrate technical feasibility in the deployment of autonomous sensor networks that can be reconfigured and adapted to data of interest; to generate technology and know-how for the development of autonomous vehicles with on-board sensing instruments; and to experimentally demonstrate through proof of concept the advantages of using robots operating in different domains to improve the quality of environmental data collection.

CLOSED-LOOP OPTOGENETIC CONTROL OF NEURAL ACTIVITY

LEAD DEPARTMENT

Mathematics

CENTER / GROUP / LAB

CESYC – Systems and Control Center

DIRECTOR

Ricardo Sánchez Peña, Ph.D.

DESCRIPTION

Neurons communicate through changes in their electrical activity that can be measured at the level of individual neurons or at the population level. It has been postulated that communication between different brain areas is based on the synchronization of the activity of groups of neurons in distributed networks. However, this hypothesis has not been formally tested. In recent years the emergence of optogenetics has made it possible to overcome this limitation. Optogenetics refers to a technological advance characterized by the identification and optimization of light-activated proteins (opsins), which can be introduced in neurons and which increase or decrease the neuronal activity rapidly. The combination of electric activity records and optogenetic action through light would enable the activation or inhibition of specific neural groups and would eliminate or generate neural activity patterns. This manipulation of neural activity could lead to control the brain. However, there are no commercial systems that allow the combination of both technologies in a single device. The main goal of this project is the creation and implementation of a system for data acquisition and intervention in biological systems, focused on the area of Neurobiology. In addition to the usual techniques, based on electronic software and hardware, optogenetics will be the technology chosen to act. In turn, electronics will be based on modified acquisition platelets and FPGA programming for this particular application. This will generate a closed-loop system that will allow the identification and/or control of neurons and/or groups of neurons. The applications of this development are varied and range from the refinement of electrical stimulation therapy in Parkinson’s disease or Epilepsy, to the demonstration of working hypotheses in the area of Neurosciences.

HYDROGEN TECHNOLOGIES

LEAD DEPARTMENT

Mechanical Engineering

CENTER / GROUP / LAB

CIDIM – Integrated Development Center in Mechanical Engineering

DIRECTOR

Ricardo Lauretta (ITBA) / KIT Cecilia Smoglie

DESCRIPTION

Production, purification, storage and combustion of hydrogen: development of a self-pressurized alkaline electrolyzer, catalytic purification, innovation in storage tanks, design and simulation of Otto cycle engine fed with H2 or gas and hydrogen mixtures.

GEOTHERMAL ENERGY

LEAD DEPARTMENT

Mechanical Engineering

CENTER / GROUP / LAB

Master’s degree Professors

DIRECTOR

Dietmar Kuhn, Ph.D. (KIT)
KIT Cecilia Smoglie

DESCRIPTION

Study of the geothermal energy potential in Argentina: feasibility of using low, medium and high enthalpy heat for direct use and/or electricity generation with ORC (Organic Rankine Cycle) technology.