Interdisciplinary research,
education and capacity building
2014 Call for R&D Projects at UT Austin
University of Texas at Austin:
Wenhong Chen, Sharon Strover, Joseph Straubhaar, Artur Matos Alves, Kye-Hyoung Lee (PhD student), Xiaoqian Li (PhD student), Hogeun Seo (MA student)
University of Porto:
José Azevedo, Nuno Moutinho, Raquel Meneses, Carlos Figueiredo (PhD student)
Atlântica University:
Artur Matos Alves
UTAP-ICDT/IVC-ESCT/0020/2014
Principal Investigator: Maria da Conceição Gonçalves Costa, Lusofona University
GAMILearning Team and partners:
José Rogado (COPELABS), ECATI – Universidade Lusófona de Humanidades e Tecnologias
Sara Henriques, ECATI – Universidade Lusófona de Humanidades e Tecnologias
Kathleen Tyner, University of Austin-Texas
Carlos Santos, Universidade de Aveiro
João Batista, Universidade de Aveiro
Luis Pedro, Universidade de Aveiro
Pedro Figueira Torres, SAPO-PT
Working with cohorts of youth aged 9 to 12 in Portugal and Austin, Texas, GAMILearning builds on field-tested research to address the need for student awareness and skill in managing their digital identities with game play and production. In the process, the project explores the way that the game analysis and production supports a wide range of media literacy and learning skills.
There is a generalized consensus that “promoting and enhancing media literacy, for child and adult populations, is of growing importance, in a context of digital media convergence and a highly complex media and information ecology” (Livingstone, Bulguer, & Zaborowski, 2013, p. 4; Hobbs, 2008, p. 431). In Portugal, media literacy and education policies are available; schools already have computers with internet access, a Guideline for Media Education in Pre-school, Elementary and Secondary School was recently launched by Direção Geral da Educação (DGE). Nonetheless, there is a general consensus about the lack of teachers’ training and content in formal education (Costa, Jorge, & Pereira, 2013). Furthermore, several initiatives in promoting media literacy are already in place but they lack user-based design and outcome measurement.
One of the strengths of GAMILearning consortium lies in an international team of researchers (ULHT, UAveiro and UT-Austin) and a partner from Industry (PTC-SAPO) that already has in place a social network (SAPO Campus) with nearly 100 Portuguese schools. SAPO campus is a secure and private social network where each school could configure the degree of communication and sharing with other schools. Since SAPO Campus is not mandatory (it’s not an institutional platform) one can expect motivation and creativity from its members as well diversity in practitioners’ pedagogical approaches.
Capitalizing on the above opportunities and strengths, the researchers will focus on advancing the methodologies to create and measure an innovative approach to the usage of digital games in classroom. Indeed, a substantial part of the project deals with research and creation of such methodologies and tools that will enable the usage of a digital gamification system in a classroom ecosystem, by teachers and children.
A key challenge of the GAMILearning project is to go beyond deploying games to be played in the classroom: indeed, we will create conditions that allow teachers and students to construct their own games, as they perform other learning activities. The Consortium brings significant experience with games-based education that will ensure the achievement of the GAMILearning objectives. Furthermore, through comparing critical media literacy development of participants in GAMILearning with non-participants of similar age, demographic and media access profiles, this project will assess the separate but related impacts of game design, pedagogy and peer community experiences on MIL development in the learning process.
UTAP-ICDT/EEI-CTP/0022/2014
Principal Investigator: Álvaro Pedro de Barros Borges Reis Figueira, University of Porto
Executive Summary
In project REMINDS we will develop systems to perform an analysis of public information transmitted through Social Networks, to automatically filter and show the information that is potentially relevant to a general audience.
Although Social Networks are a source for a tremendous amount of information, much of the information is either private (yet granting public access in most cases), personal, not important or simply irrelevant to the general audience. Despite this situation, we have witnessed in the last years many important news and mass opinions on relevant issues being conveyed by social networks, usually surpassing in speed the broadcast through the traditional media of important events.
The main issue that REMINDS tackles is then to create a system capable of detecting, in the social networks sea of data, “relevant information”, while filtering and ignoring private comments and personal information.
As Saracevic (2007) says, “relevance is a, if not even the, key notion in information science in general and information retrieval in particular”. For the author, relevance can assume different manifestations in information science, such as “system or algorithmic”, “topical or subject”, “cognitive relevance or pertinence”, “situational relevance or utility” and “affective relevance”.
There is work in the area of event detection and also about influence, and detection of controversial topics. For instance, Diakopoulos (2010) studied the polarity of the opinions given by Twitter users. Based on the polarity and on the identified events, they were able to understand the general feeling of the opinions. They also used the “Pearson correlation” between positive and negative responses to measure the degree of controversy of the discussed topics, identifying strong oppositions in the opinions. Thelwall (2010) studied the sentiment polarity in the MySpace social network and discovered that nearly 2/3 of the users express emotions. Gomez-Rodriguez (2012) defined an information cascade model and developed an algorithm capable of inferring networks of influence and diffusion for the propagated topics. Leskovec (2006) have before that studied information cascades, i.e. the propagation of actions or ideas due the influence of others. Bakshy (2011) have recently quantified the relative influence of users on Twitter. They found a correlation between the largest cascades and the most influential users, as well as between the number of followers and the past local influence.
It is interesting to notice that despite relevance being 80 years old and many attempts to define its contributing factors have been drawn, no conclusive results have been drawn and debate continues. Xu and Chen in 2006 wrote: “...there is no agreement on factors beyond topicality, neither in terms of what they should be nor of how important they are… Naturalistic inquiry with qualitative research methods has been advocated and adopted by many researchers… [yet] almost no study of relevance judgment had adopted a confirmatory approach.”
The REMINDS team has experience in text-mining, information retrieval and community detection. Our system from a previous project (“Breadcrumbs”) allows us already to automatically detect in news fragments the answers to three standard journalistic questions: Who? / Where? / When?. Our team has also experience in sentiment analysis (important to understand if topic is being polemic or controversial) and on ranking comments on the social web.
Our partner company in this research – INTERRELATE – is a startup whose business is “mining, interrelating, sensing and analyzing online information”.
Therefore, we propose creation and analysis of an automatic relevancy detection system. Our methodology will be based on two standard, realistic, yet new from the technological point of view, approaches, to detect relevancy, plus a third “speculative” approach. The first approach will be trying to test for irrelevance (and eventually failing, concluding for some degree of relevance); the second one will be using journalistic factors to assess relevancy. Finally, the third one will be to try to find correlation and causality between interaction patterns and relevance in social networks.
Those two “and a half” approaches will then be confronted with a “gold-standard” model of relevance to validate the system and for testing the relative importance of factors used in these models. The result will inform the weights and aggregation functions of the system into a single ranking of relevant fragments of information.
As a result we will create a model of relevance that embodies better understanding of how people make relevance decisions and which enables making automatic relevance predictions at a large scale.
UTAP-EXPL/EEI-ESS/0031/2014
Principal Investigator: Paula Cristina Quaresma da Fonseca Carvalho, INESC (Institute for Systems Engineering and Computers)
The main goal of this project is to systematically analyze the expression of irony and sarcasm in social media, in a cross-lingual and multicultural perspective, aiming at its automatic detection.
Automating the detection of irony and sarcasm is yet an unsolved problem. Previous efforts to achieve this aim have been limited in their approach, tending to focus on shallow textual cues indicative of ironic intent. Research has not systematically explored specific linguistic patterns and rhetorical strategies typically used to express verbal and situational irony in text. Moreover, previous studies usually consider these phenomena as a whole, instead of analyzing independently the mechanisms involved in expressing it.
This project aims to answer the following open research questions that are critical to improving irony and sarcasm detection in text mining activities:
i. In social media content, are the linguistic and extra-linguistic mechanisms used to express irony and sarcasm language-dependent?
ii. To what extent does irony expression and representativeness differ across domains, geographical regions, and targets involved?
iii. Which are the most representative linguistic and extra-linguistic devices used to express irony in different types of domains and topics?
iv. How reliable are individuals with respect to identifying and processing ironic messages?
v. Which rhetorical devices are easier to recognize, and which ones are particularly hard to detect, especially by humans not sharing the same cultural and pragmatic context?
vi. Which types of approaches best suit the automatic detection of irony and sarcasm in text? Are we capable of training shallow models to learn these phenomena? Or should we explicitly explore contextual and linguistic information, using advanced NLP strategies?
The research will be based on the creation of fine-grained annotated corpora, exploring the explicit and implicit information conveyed inside and outside utterances previously identified as ironic and non-ironic (literal). Using the labeled data, we will investigate new machine learning methods for irony detection that improve on the state of the art. Specifically,
i. We will introduce new features that attempt to capitalize on the insights gleaned from the annotation process and subsequent analyses.
ii. In light of our exploration concerning variation of irony usage across languages and topics, we will investigate adaptive irony detection models, i.e., models that adjust their parameters to make predictions for specific domains.
iii. Taking this adaptation paradigm further, we will experiment with cross-lingual irony detection, exploiting extra-lingual features.
This approach will allow us to discern irony where other approaches failed, advancing the state of the art in irony detection, in particular, and in subjective language processing (e.g. sentiment analysis and opinion mining tasks), in general.
Research team:
INESC-ID Lisboa: Paula Carvalho, Bruno Martins, Mário J. Silva, Sílvio Amir, Hugo Rosa
University of Texas at Austin: Byron Wallace
UTAP-EXPL/EEI-SII/0043/2014
Principal Investigator: João Manuel Pereira Barroso, University of Trás-os-Montes and Alto Douro
CE4BLIND Partners: INESC TEC and UT Austin
The CE4BLIND project aims to build upon the advantages of the latest technological developments to create innovative solutions that can strongly contribute to the support and inclusion of people with special needs, specifically the blind community and all people suffering from visual impairment. The project focuses on the creation of a mobile digital platform (CE4Blind) that can contribute to an increase in the autonomy and range of action of the visually impaired, allowing inclusion in a broader set of activities and enhancing quality of life.
Visually impaired people face great challenges in their day-to-day lives that often require the regular help and support of others. Whether in an indoor environment going about daily activities, or an outdoor environment moving from one location to another, challenges faced can lead to a deep sense of isolation and dependency. Using computer vision techniques and enabling technologies, it is possible to integrate knowledge and knowhow from a variety of fields including Digital Media (information and platforms), mathematics (algorithms), Computer Science (hardware and software), and Engineering. Resulting integrated solutions include automatic text reading, recognition of barcodes and QR codes (eg., drugs or packaged foods), and the recognition of specific objects, enabling a significant increase in autonomy and allowing end users to better navigate both indoor and outdoor environments.
The CE4Blind integrates the latest technologies and developments in the use of mobile devices, miniaturized cameras, and software (such as Vuzix Glass, Google Project Tango, 3D Printed models, smartphones with customized apps and accessories, etc). It is also designed with a non-invasive natural interface that is well suited to meet user needs, without requiring a change in habits and routines. CE4Blind is a digital platform of smart support designed to combat the digital infoexclusion of visually impaired people, making them feel more integrated and productive in digital society.
Considering the adoption of a user-centric design methodology, the project involves the collaboration with ACAPO (Association of Blind and Partially Sighted Portugal) to conduct tests with the mobile digital platform.
UTA-Est/MAI/0006/2009
Principal Investigator: Mário Silva, University of Lisbon
This project will take computational journalism to the next level by developing a set of new algorithms, tools and methodologies for media analytics. The project aims to help journalists and researchers make better sense of what is news and what is not among the massive amounts of data produced every day.
UTA-Est/MAI/0007/2009
Principal Investigator: Álvaro Figueira, University of Porto
Project Breadcrumbs will capitalize on public participation in the global news cycle to enable journalists to harness reader participation. It will build bridges between online news and social media so journalists can understand the interests of their readers and the implicit relationships that readers perceive between different articles and events in order to identify valuable contributors and follow new leads for further writing.
UTA-Est/MAI/0008/2009
Principal Investigator: Rui Prada, Instituto Superior Técnico
INVITE will use "serious games" to understand how human partnerships are created, maintained and terminated in virtual environments.
UTA-Est/MAI/0009/2009
Principal Investigator: Verónica Orvalho, University of Porto
LIFEisGAME will embed real-time computer vision/graphics-based facial expression analysis/synthesis into a game in order to teach children with Autism Spectrum Disorder (ASD) to recognize facial emotions.
Visit the LIFEisGAME site
Read about Dr. Orvalho's facial animation software, Fimmie
UTA-Est/MAI/0010/2009
Principal Investigator: João Magalhães, New University of Lisbon
ImTV aims at offering consumers a personalized combination of mainstream TV content and online user-generated content based on algorithms that process content metadata, user and community feedback.
UTA-Est/MAI/0012/2009
Principal Investigator: Manuel Damásio, University of Lusófona
Inclusive services to promote health and wellness via digital interactive television will evaluate the potential of digital interactive television (iDTV) to promote health care and wellness services and information to Portuguese age 55 and older with low technology literacy.
UTA-Exp/MAI/0025/2009
Principal Investigator: Tomás Henriques, New University of Lisbon
The perception and cognition of space and its features by mapping visual information into sound and sound structures is an exploratory project. "This grant reflects the fact that digital media is multidisciplinary and to do meaningful work you need talent and insight from people across multiple areas," said Sharon Strover, director of CoLab's Digital Media program and professor of Radio-TV-Film at UT Austin. "We hope this project will create a foundation for developing and working with the future leadership in the area of digital media."
UTAustin/CD/0052/2008
Principal Investigator: Carlos Guedes, University of Porto
This joint research project will develop new techniques and strategies for computer-assisted composition in the context of real-time user control with non-standard human interface devices for applications in electronic art and digital entertainment systems. The research team will design and implement real-time software, hardware and specialized human-interfaces that will provide tools and resources for music, dance, theatre, installation artists, interactive kiosks, computer games, internet/web information systems.
The outcome of the project will be the creation of a modular toolbox for real-time dynamic music generation that will allow for easy creation of software applications for the purposes described above. The toolbox will be highly flexible allowing its use both by trained musicians and the general public.
INESC-Porto, Universidade Nova de Lisboa, University of Texas at Austin, with industrial affiliates Casa da Música and YDreams as partners make up the consortium for this joint research project.
UTAustin/CD/0016/2008
Principal Investigator: Cristina Ponte (Universidade Nova de Lisboa)
In those societies with access to new media, concern continues to grow about the digital divide, between generations and between majority and minority social groups. In Portuguese society, this challenge presents some specific characteristics, marked by major cultural and educational differences and by the very different levels of digital literacy that distinguish the access and use of these media by adults and children. Children and youth younger than 18 year are ahead of adults in access and use, to the contrary of what happens in the majority of other European countries.
Portugal has passed from being a country of emigrants to becoming a country of immigrants, from its old colonies in Africa and Brazil in the last few decades, and more recently of immigrants from the countries of Eastern Europe. Access and use of the digital media also vary between children that have these media at home and in their room, and those who only get to use them at school and in public access where their use is limited and conditioned by circumstances.
This project thus intends to contribute to knowledge of the critical factors that facilitate or make more difficult the access and use of digital media by social groups that are considered socially disadvantaged. With this research it will be possible to bring together indicators that will contribute to helping digital content industries reach and include segments of the market that are not yet reached by their productions; that may help design public policies for digital inclusion that will be more effective and sustainable; that may strengthen local networks and agencies, including the production of contents by the groups that have been digitally excluded until now.
2014 Call for R&D Projects at UT Austin
University of Texas at Austin:
Thomas J.R. Hughes, Shaolie S. Hossain
Instituto Superior Técnico (IST):
Adelia Sequeira
UTAP-EXPL/QEQ-COM/0019/2014
Principal Investigator: Joaquim Armando Pires Jorge, INESC (Institute for Systems Engineering and Computers)
Algorithms for Macro-Molecular Pocket Detection is an exploratory project that aims to develop more efficient algorithms to detect pockets in very large molecules. Such algorithms are important in the design of new drugs, as they can predict the location where drugs can bind to a specific protein and, consequently, determine its implications on protein function.
The challenge of structure-based drug design (SBDD) lies in correctly predicting which small molecule (i.e., ligand) would bind to a specific protein and, consequently, which are the implications on its function. It is clear that SBDD requires a profound understanding of how a ligand interacts with the protein; more specifically, how a ligand fits in its binding site on the protein surface because such information is very useful to predict which other ligands might bind and how strong their bindings will be.
In the last few years, SBDD experienced a major boost owing to the increasingly number of known protein structures. This is largely due to the appearance of many structural genomics projects that unearthed X-ray crystal structures of proteins either with unknown or poorly known function. In fact, it was noted that while some of these proteins contained co-crystallized ligands, most of them were un-liganded. It was then clear that these latter “incomplete” protein structures would end up raising new challenges in respect to the prediction and characterization of protein-ligand interactions.
Searching for binding sites remains a challenge on both the size of proteins that current approaches can handle and the time required to find cavities. This project aims at devising efficient algorithms for detecting pockets/cavities on the surface of large (>500K atoms) proteins capable of binding to small molecules. More specifically, we aim to develop new and efficient geometric algorithms to determine pockets and other cavities in macromolecules, where we employ novel techniques in geometric modeling, computer graphics and visualizatiom combined with high performance parallel computing.
UTAustin/CA/0056/2008
Principal Investigator: Prof. João Luís Sobral, Universidade do Minho
Over the past thirty years, the parallel programming community has invented many tools and techniques for parallel programming of computational science applications like FFTs and finite-differences that are organized around defense matrices. However, new applications such as data-mining and social network analysis involve irregular computations that are performed on large, sparse graphs and trees. Little is known about how to write parallel programs for these kinds of irregular applications. The Portugal-UT Austin team is studying the use of optimistic parallel execution and program refinements to address this problem.
UTAustin/CA/0047/2008
Principal Investigator: Prof. Adélia Sequeira, IST
Starting from high-resolution volumetric medical imaging, researchers are developing spatially realistic physiological models of the human heart and vasculature, with its pathologies and malformations. The long term goal is the development of a semi-automated software framework for accurate structure elucidation from imaging, geometric processing for high fidelity finite element models with quantified uncertainties, as well as the physics simulations of pulsatile blood flow through the heart and vasculature models. The Portugal-UT Austin team is developing and deploying state-of-the-art techniques for key geometric and biophysics modeling and analysis steps that are essential for the ultimate development of this computational framework.
Read more about Project SIMCARD
UTAustin/CA/0012/2008
Principal investigator: Prof. José Carlos Ferreira Maia Neves, U.Minho
This project has as an objective to apply and to test in a full scale and real time conditions a new approach to model the asphalt pavement behavior based on soft computing tools being developed at the DI/UMinho. Data from sensors installed in a highway with information about vehicles, climate and structural answer for one full cycle of service life of the pavement will be used as a source database and will be provided by the Mn/Road Project. The data will optimized in order to generate a model in the form of a matrix of data with billions of records. The matrix will be used as source of experiences and “intelligence” to train a Neural Network (NN) set. Trained, the NN will be able to predict the service life time for asphalt pavement design and management. This research intends to create a new paradigm, allowing for the asphalt pavement modeling in a true scientific way, surpassing the well know problems of the most used methods today, which are empiric and empiric-mechanistic.
UTAustin/CA/0053/2008
Principal investigator: Prof. José Carlos Fernandes Pereira, IST
Many industrial and transportation devices involve combustion in jet diffusion flames where the combustion reaction takes place at the edge of the jet which separates the fuel from the oxidizer. Improving the understanding and the accuracy of the simulations of turbulent reactive jets is therefore crucial to improve the fuel economy and to decrease the emissions in numerous combustion systems. The two regions (fuel/ oxidizer) are separated by a sharp interface where the "turbulent entrainment" takes place. It has been shown recently that the physical mechanisms occurring at this region are considerably different from previously thought. In particular recent works showed that the turbulent entrainment is mainly caused by small scale motions ("nibbling") and not by large-scale eddy motions ("engulfment"). Moreover, the classical turbulent variables displays sharp gradients and a very particular dynamics to this region. The goal of the present work is to (i) carry these new results into the analysis of the dynamics of a scalar field across the interface fuel/ oxidizer and, (ii) develop, assess and improve the modeling of the sub-filter scalar dissipation in this region with applications to large-eddy simulation (LES) of turbulent reacting jets.
2014 Call for R&D Projects at UT Austin
University of Texas at Austin:
Luis Caffarelli (PI), Alessio Figalli, Alexis Vasseur, Clint Dawson, Francesco Maggi
Instituto Superior Técnico (IST):
Juha Videman, Margarida Baía, Farid Bozorgnia (postdoc), Léonard Monsaingeon (postdoc)
The University of Coimbra:
Dmitry Vorotnikov, José Miguel Urbano (co-PI), Anderson Maia (PhD student)
MAT/0006/2009
Principal Investigator: Cláudia Rita Ribeiro Coelho Nunes Philippart, Instituto Superior Técnico (IST)
MAT/0007/2009
Principal Investigator: Diogo Luís de Castro V. de Aguiar Gomes, Instituto Superior Técnico (IST)
UTAustin/MAT/0057/2008
Principal Investigator: Prof. Diogo Gomes, IST
Researchers from several disciplines are joining efforts in applied mathematics including dynamical systems, financial mathematics, game theory, optimal control, viscosity solutions, number theory, and cryptography. In dynamical systems the main focus research areas are Aubry-Mather theory, renormalization and attractors of semilinear parabolic equations. In financial mathematics focus is being placed on developing forward price models, interest rate models and stochastic volatility models, and first passage times in diffusion processes. Game theory oligopoly models are being considered to investigate the following issues: uncertainty, signaling, dynamic price discrimination (linear prices and non linear pricing), research and development programs, location decisions, advertising strategies and their effects, trade policy models and competitive strategies in spatial networks, as well as mean-field games and its applications. Optimal control theory and viscosity solutions of Hamilton-Jacobi equations are essential to understand important problems in dynamical systems (Aubry-Mather theory) and in mathematical finance. These directions are being pursued, as well as certain problems in multiple criteria decision-making. Finally, in the emerging applied area of cryptography, the group is examining post-quantum cryptography in order to propose cryptosystems based on rational points on curves over function fields and show that they are robust to quantum adversaries.
UTAustin/MAT/0009/2008
Principal Investigator: Isabel Maria Narra de Figueíredo, Univ. of Coimbra.
This project focuses on the mathematical modeling and endoscopic imaging processing of aberrant polyps and aberrant crypt foci (ACF, which statistically precede polyp formation). Multiscale methods are used in a modeling process which involves partial differential equations and level set methods, to simulate the dynamics and shape of ACF and polyps populations. The project’s aim in image processing is to develop computerized and fast algorithms to identify and assess ACF and polyps patterns, captured in vivo by endoscopy in order to facilitate and speed up screening methods towards CRC prevention.
UTAustin/MAT/0035/2008
Principal Investigator: José Miguel Urbano, Univ. of Coimbra.
Nonlinear partial differential equations (PDEs) are central in modern applied mathematics, both in view of the significance of the concrete problems they model and the novel techniques that their analysis generates. This project explores some of the new applications of these equations in biomathematics, against eight tasks:
Advancement in understanding of these equations can be related to many applications such as the motion of multiphase fluids in porous media, the melting of crushed ice (and phase transitions in general), the behavior of composite materials, the pricing of assets in financial markets, or the quantum drift diffusion in semiconductors.
UTAustin/MAT/0066/2008
Principal Investigator: José Ferreira, Univ. of Coimbra.
In recent decades, diffusion in porous media has attracted researchers from several disciplines, such as geosciences, environmental sciences, mechanics, biology, chemistry, petroleum engineering, biomedical engineering, physics and mathematics. Diffusion in porous media has applications to problems such as groundwater contamination, diffusion in polymers, and flow in oil reservoirs. The fundamental equation governing diffusion in porous media is the equation of mass conservation, which is of parabolic type. It is established assuming that the dispersive mass flux is given by Fick´s law where the dispersion tensor is assumed to be independent of the concentration and its gradient. It is well-known that this equation gives rise to an infinite speed of propagation. Smallscale and large-scale heterogeneities in porous matrix and/or fluid properties are the main sources of deviations of the so-called Fickian dispersion behavior. In order to overcome this deviation, a certain memory effect should be included in the flux modeling. The aim of this project is to introduce memory effects in the models for fluid flows in porous media characterized by small-scale and large-scale heterogeneities in several contexts.
2014 Call for R&D Projects at UT Austin
University of Texas at Austin:
Nicholas A. Peppas (PI), Amey Puranik (postdoc), Heidi Culver (graduate student), John Clegg (graduate student)
University of Minho:
Rui Reis, Manuela Gomes
University of Porto:
Pedro Granja
2014 Call for R&D Projects at UT Austin
University of Texas at Austin:
Carolyn Conner Seepersad (PI), David Bourell
University of Aveiro:
Paula Vilarinho
UTAP-ICDT/DTP-FTO/0016/2014
Principal Investigator: Helena Isabel Fialho Florindo Roque Ferreira, University of Lisbon
UT PI: Professor Nicholas Peppas
Abstract
Cancer vaccines are expected to induce a tumor specific immune response able to either eliminate the malignant cells or keep it under constant restraint, delaying tumor recurrence and prolonging survival. Polymeric nanotechnology-based strategies have been explored to entrap and deliver tumor associated antigens (TAA) to antigen presenting cells (APCs), mainly DCs, which are vital cells within tumor immunology. These nanoparticles (NPs) present a good potential for site-selective delivery to APCs by binding recognition ligands to NP surface, which can enhance NP endocytosis, influencing their intracellular trafficking and thus inducing prolonged antigen cross-presentation.
Even though, additional strategies should be devised to overcome immunosuppressive properties of tumor microenvironment. This collaborative study proposes the development of a combined therapeutic approach using engineered multicomponent nanoscale systems to deliver TAA, siRNA and/or miRNA, to promote TAA presentation by DCs and suppress cancer cell invasiveness within tumor site based on the understanding of the molecular mechanism underlying cellular cross-talk.
In addition, it is widely recognized that the successful development of translational research is dependent on a collaborative work performed by a multidisciplinary team of academia, companies and policy makers to close resource gaps. Therefore, this is a translational research project that aims to leverage collaborative research across Portugal and UT, to use a modular and stepwise approach at intracellular, modelling and computational levels to guide and support the development of safe advanced and effective translational immunotherapeutic nanosystems. Portuguese and UT teams will work together to develop advanced nanotechnologies following protocols established to ensure scalable GLP/GMP processes, promoting reduced time-to-market for these nanoscale products.
The cross-disciplinary team of renowned Portuguese and UT Austin researchers will provide a unique approach to the problems addressed here. Indeed, expertise ranging from nanoscience and nanotechnology to molecular biology field will ensure the successful achievement of the proposed goals, including the establishment of new practices to support a faster and cost-effective transfer of novel technologies to targeted industries. Therefore, this collaboration will definitely lead to special opportunities for faculty/researchers and students who will share new experiences, knowledge and highly advanced infrastructures/equipments that will certainly support and improve the educational research and training in Portugal.
The closer contact between these Portuguese teams and a world top university as UT Austin will nurture the creation of new companies in Portugal able to use the most advanced and innovative technologies, fostering the economic development of our country. Professor Nicholas Peppas from UT Austin is the leading researcher and inventor in molecular sciences. He developed a multidisciplinary strategy covering areas as biotechnology, materials, polymers, biomedical engineering, nanotechnology and mathematical modelling to design new and advanced delivery systems.
Professor Nicholas Peppas’ impressive professional and educational experience has certainly had an overwhelming impact in the research and education of the next generation in various countries worldwide, due to his ability to live and recognize collaboration on every level. As a result, one can easily anticipate that this project will constitute in fact a single opportunity in life for this Portuguese faculty/researchers and students, being expected to have a profound impact in their future research and educational activities.
UTAP-ICDT/CTM-BIO/0023/2014
Principal Investigator: Rui Luís Gonçalves dos Reis, University of Minho
UTAP-ICDT/CTM-NAN/0025/2014
Principal Investigator: Ana Cristina Moreira Freire, University of Porto
Acronym: FOTOCATGRAF
Starting date: 1st June 2015 (36 months)
Principal Contractor: REQUIMTE – Rede de Química e Tecnologia – Associação
Research Unit: Laboratório Associado para a Química Verde (REQUIMTE, Universidade do Porto), Faculdade de Ciências, Universidade do Porto
SCTN Participating Institutions: Instituto de Engenharia de Sistemas e Computadores do Porto (INESC Porto/FE/UP) and Universidade de Aveiro
Research Units:
INESC Tecnologia e Ciência (INESC TEC), Professor Luis Lopes (lblopes@dcc.fc.up.pt)
Centro de Investigação em Materiais Cerâmicos e Compósitos (CICECO/UA), Professor Tito Trindade (tito@ua.pt)
LAQV, Instituto Superior de Engenharia do Porto, Professor Cristina Matos (cmm@isep.ipp.pt)
Participating Company: Águas do Centro Litoral (AdCL), S.A., Grupo Águas de Portugal
UT: Professor Brian Korgel
In the last decades, the growth of population and worldwide industry processes is having a tremendous impact on the environment. New emerging pollutants are being detected in water/wastewater, such as pharmaceuticals, hormones and their metabolites, which can cause adverse effects on fauna, flora and human health. In this context, the quest for new advanced technologies to ensure a safe and sustainable water supply is growing at an accelerating pace, being one of the grand global challenges of the 21st century.
Nanotechnology-enabled photocatalytic water treatment processes are emerging as new opportunities to develop the next-generation of water supply and wastewater treatments to produce higher quality water using less energy and with lower costs. In particular, nanocomposites of graphene and semiconductor nanoparticles stand out as new advanced photocatalytic solutions for efficient and sustainable removal of water pollutants, with a triple role as photocatalysts, adsorbents and antimicrobial agents.
In this Project we endeavor to produce a new generation of high-performance graphene-based photocatalysts for the removal of emerging pollutants – pharmaceuticals – from the wastewater treatment plants (WWTPs) of center region of Portugal, monitored by AdCL, Grupo Águas de Portugal.
To achieve this goal, graphene flakes will be produced in large scale by cost-effective top-down approaches. The new graphene-based nanocomposites will be produced through the combination of different semiconductors with complementary roles in a single material. The synergy between the different components will improve their photocatalytic activity by promoting charge separation, by increasing photon harvesting within a wider spectral range and prolonging their lifetime.
The pharmaceuticals to be removed will be selected taking into account the results obtained by the Team in different campaigns. A data mining network system will be developed and implemented at WWTP to monitor in a continuous mode (geographic and seasonal variations) the most persistent pharmaceuticals at the entrance/exit of AdCL.
Based on continuous interaction AdCL – Research Teams REQUIMTE, CICECO and INESC-TEC, with the collaboration of UT Austin (USA), the photocatalytic performance of graphene-based materials will be firstly evaluated at laboratorial scale in the degradation of wastewater samples supplied by AdCL. The most efficient nanophotocatalysts will be produced at pilot scale and introduced in a pilot WWTP of AdCL. Complementary toxicity studies will be considered as an assessment factor for the selection of the best treatment.
Finally, an electrochemical sensor will be designed to read the electric impulse associated with graphene-based electrocatalyst detectors. That sensor will be integrated with off-the-shelf microcontrollers to form wireless sensor networks that can be deployed on the pilot WWTP and allow for automatic, high cadence or even real-time, collection of data to monitor the concentration of the most persistent and prejudicial pharmaceuticals for the environment. The resulting data can then be mined to detect patterns that will allow a deeper understanding of the usage and life-cycle of these pollutants in the environment and, also, to make the photocatalyst requirements in the wastewater treatment station more sustainable and cost-effective.
UTAP-EXPL/CTM-NAN/0018/2014
Principal Investigator: Ana Maria Oliveira Rocha Senos, University of Aveiro
UTAP-EXPL/BBB-ECT/0050/2014
Principal Investigator: Joana Catarina da Silva Correia, University of Minho
Acronym: EPIDisc
Abstract
Lower back pain (LBP) is one of the most frequently reported age- and work-related disorder in actual society, which presents a huge socio-economic impact in industrialized European countries. Several factors can cause LBP, but degeneration of intervertebral disc (IVD) seems to be strongly connected to the majority of cases. IVD degeneration is a challenging clinical problem that urgently demands for viable implant materials. Recently, there is a growing interest in the potential of cell-based tissue engineering (TE) approaches aimed to regenerate the damaged IVD and restore full disc function. Although several biomaterials have been tested for regeneration of IVD nucleus pulposus (NP) and annulus fibrosus (AF), an effective substitute for each structure has yet to be identified. Moreover, an efficient closure of the annulus is also a big challenge that still remains to be achieved. In fact, it has been suggested that hydrogels that are able to mimic NP mechanical behaviour may fail in restoring the mechanical behaviour of the disc if an appropriate AF closure is not achieved. Recent research directions are addressing IVD substitution/regeneration using total custom-made implants which adequately mimic the native IVD. In this context, the EPIDisc project (Ref. UTAP-EXPL/BBB-ECT/0050/2014) aims to provide patient-specific therapeutic tools for TE of IVD through the pre-clinical development of a new generation of hierarchical structured cell-loaded scaffolds that better mimic the human AF and NP tissues. A total IVD implant is proposed based on a personalized approach by means of using reverse engineering, i.e. combining imaging techniques (e.g. MRI and micro-CT) and 3D-bioprinting technology. The proposed construct will be obtained after analysis of the data obtained from MRI and micro-CT datasets by bioprinting the biodegradable and bio-adhesive silk/elastin hydrogel combined with the non-angiogenic methacrylated gellan gum (iGG-MA) hydrogel. The innovative concept of EPIDisc consist in achieving an anatomical total IVD substitute that is obtained entirely by bioplotting, and in gathering in this construct several properties essential for reproducing the in vivo conditions observed in IVD (i.e. high organization, non-angiogenic ability, adequate mechanical properties, improved adhesion within surrounding structures). Cell-loaded (i.e. adipose stem cells) multilayered constructs that reproduce the lamellar structure of AF will be obtained by bioprinting alternate layers of silk/elastin hydrogels and cell-loaded iGG-MA hydrogels. The NP-like structure will be composed by cell-loaded iGG-MA hydrogel, which will be plotted into the central part of the total implant. The developed anatomical cell-loaded construct will be physico-chemically and biologically characterized in vitro. Studies are being conducted in the state-of-the-art facilities of ICVS/3B’s PT Associated Laboratory – University of Minho (PT), which is involved in several projects in the field of biomedical applications, namely the development of natural polymeric scaffolds for human TE and regenerative medicine (e.g., hydrogels). The EPIDisc research team, coordinated by Dr. Joana Silva-Correia, is composed by experts in the field of TE from ICVS/3B’s and one experienced researcher from The University of Texas at Austin (UT Austin).