Building 3D City Models: Testing and Comparing Laser Scanning and Low-Cost UAV Data Using FOSS Technologies

Contém resumo

Temperature influence and social interaction on the frequency of electric organ discharges in Rhamphicthys rostratus.

The frequency of electric organ discharges (EOD) of a gymnotiform fish of "pulse" frequency (40-100 Hz) from South America - Ramphicthys rostratuswas studied. The animals were settled in pairs in a aquarium and thus observed: variation in EOD frequency had at least two components: one more positively correlated with temperature, another less positively correlated due to social interaction.

Development of human central nervous system 3D in vitro models for preclinical research

Neurological disorders are a major concern in modern societies, with increasing prevalence mainly related with the higher life expectancy. Most of the current available therapeutic options can only control and ameliorate the patients’ symptoms, often be-coming refractory over time. Therapeutic breakthroughs and advances have been hampered by the lack of accurate central nervous system (CNS) models. The develop-ment of these models allows the study of the disease onset/progression mechanisms and the preclinical evaluation of novel therapeutics. This has traditionally relied on genetically engineered animal models that often diverge considerably from the human phenotype (developmentally, anatomically and physiologically) and 2D in vitro cell models, which fail to recapitulate the characteristics of the target tissue (cell-cell and cell-matrix interactions, cell polarity). The in vitro recapitulation of CNS phenotypic and functional features requires the implementation of advanced culture strategies that enable to mimic the in vivo struc-tural and molecular complexity. Models based on differentiation of human neural stem cells (hNSC) in 3D cultures have great potential as complementary tools in preclinical research, bridging the gap between human clinical studies and animal models. This thesis aimed at the development of novel human 3D in vitro CNS models by integrat-ing agitation-based culture systems and a wide array of characterization tools. Neural differentiation of hNSC as 3D neurospheres was explored in Chapter 2. Here, it was demonstrated that human midbrain-derived neural progenitor cells from fetal origin (hmNPC) can generate complex tissue-like structures containing functional dopaminergic neurons, as well as astrocytes and oligodendrocytes. Chapter 3 focused on the development of cellular characterization assays for cell aggregates based on light-sheet fluorescence imaging systems, which resulted in increased spatial resolu-tion both for fixed samples or live imaging. The applicability of the developed human 3D cell model for preclinical research was explored in Chapter 4, evaluating the poten-tial of a viral vector candidate for gene therapy. The efficacy and safety of helper-dependent CAV-2 (hd-CAV-2) for gene delivery in human neurons was evaluated, demonstrating increased neuronal tropism, efficient transgene expression and minimal toxicity. The potential of human 3D in vitro CNS models to mimic brain functions was further addressed in Chapter 5. Exploring the use of 13C-labeled substrates and Nucle-ar Magnetic Resonance (NMR) spectroscopy tools, neural metabolic signatures were evaluated showing lineage-specific metabolic specialization and establishment of neu-ron-astrocytic shuttles upon differentiation. Chapter 6 focused on transferring the knowledge and strategies described in the previous chapters for the implementation of a scalable and robust process for the 3D differentiation of hNSC derived from human induced pluripotent stem cells (hiPSC). Here, software-controlled perfusion stirred-tank bioreactors were used as technological system to sustain cell aggregation and dif-ferentiation. The work developed in this thesis provides practical and versatile new in vitro ap-proaches to model the human brain. Furthermore, the culture strategies described herein can be further extended to other sources of neural phenotypes, including pa-tient-derived hiPSC. The combination of this 3D culture strategy with the implemented characterization methods represents a powerful complementary tool applicable in the drug discovery, toxicology and disease modeling.

Peer interaction and learning opportunities in cohesive and less cohesive L2 classrooms

The present study investigates peer to peer oral interaction in two task based language teaching classrooms, one of which was a self-declared cohesive group, and the other a self- declared less cohesive group, both at B1 level. It studies how learners talk cohesion into being and considers how this talk leads to learning opportunities in these groups. The study was classroom-based and was carried out over the period of an academic year. Research was conducted in the classrooms and the tasks were part of regular class work. The research was framed within a sociocognitive perspective of second language learning and data came from a number of sources, namely questionnaires, interviews and audio recorded talk of dyads, triads and groups of four students completing a total of eight oral tasks. These audio recordings were transcribed and analysed qualitatively for interactions which encouraged a positive social dimension and behaviours which led to learning opportunities, using conversation analysis. In addition, recordings were analysed quantitatively for learning opportunities and quantity and quality of language produced. Results show that learners in both classes exhibited multiple behaviours in interaction which could promote a positive social dimension, although behaviours which could discourage positive affect amongst group members were also found. Analysis of interactions also revealed the many ways in which learners in both the cohesive and less cohesive class created learning opportunities. Further qualitative analysis of these interactions showed that a number of factors including how learners approach a task, the decisions they make at zones of interactional transition and the affective relationship between participants influence the amount of learning opportunities created, as well as the quality and quantity of language produced. The main conclusion of the study is that it is not the cohesive nature of the group as a whole but the nature of the relationship between the individual members of the small group completing the task which influences the effectiveness of oral interaction for learning.This study contributes to our understanding of the way in which learners individualise the learning space and highlights the situated nature of language learning. It shows how individuals interact with each other and the task, and how talk in interaction changes moment-by-moment as learners react to the ‘here and now’ of the classroom environment.

DISTRIBUTION AND FEEDING ECOLOGY OF THE AFRICAN TILAPIA Oreochromis mossambicus (TELEOSTEI, PERCIFORMES, CICHLIDAE) IN SURINAME (SOUTH AMERICA) WITH COMMENTS ON THE TILAPIA-KWIKWI (Hoplosternum littorale) (TELEOSTEI, SILURIFORMEs, CALLICHTHYIDAE) INTERACTION

The geographical distribution of the African Tilapia Oreochromis mossambicusin Suriname is restricted to a narrow strip of land along the Atlantic coast. Within the coastal plain, O. mossambicusoccurs in brackish lagoons, oligohaline canals, and shell-sand pit lakes. Physico-chemical characteristics and phytoplankton composition of representative Tilapia water bodies are described. Blue-green algae and fine flocculent detritus are dominant food items in the diet of the Tilapia, while Rotifera and microcrustacea are also important in the diet of larvae and juveniles. Intraspecific diet overlap among ontogenetic stages of the Tilapia did not differ significantly from 1, which means that these diets showed complete overlap. Interspecific diet overlap between the Tilapia and the indigenous armoured catfish Hoplosternum littoralewere moderate or low. The results are discussed in relation to recent developments in the Surinamese fisheries and aquaculture sector.

PHB-HV 3D Scaffold supports osteoblast growth

Bone tissue engineering requires a biocompatible scaffold that supports cell growth and enhances the native repair process. Poly(3-hydroxybutyrate-co-3-hydroxyvalerate) (PHB-HV) is a biodegradable 3D scaffold with 88.1 â 0.3% porosity and pore size of 163.5 â 0.1 mm. Previous studies demonstrated the potential of PHB-HV as a scaffold in spinal cord repair. The aim of this study was to evaluate PHB-HV as a scaffold for bone regeneration by assessing the cytocompatability of this scaffold.

Cell encapsulated hydrogel microspheres as "building blocks" for producing 3D constructs

Cell encapsulation within hydrogel microspheres shows great promise in the field of tissue engineering and regenerative medicine (TERM). However, the assembling of microspheres as building blocks to produce complex tissues is a hard task because of their inability to place along length scales in space. We propose a proof-of-concept strategy to produce 3D constructs using cell encapsulated as building blocks by perfusion based LbL technique. This technique exploits the â bindingâ potential of multilayers apart from coating

Study of the interaction between asphalt and plastic wastes in new polymer modified binders (PMB)

The aim of this study is evaluating the interaction between several base pen grade asphalt binders (35/50, 50/70, 70/100, 160/220) and two different plastic wastes (EVA and HDPE), for a set of new polymer modified binders produced with different amounts of both plastic wastes. After analysing the results obtained for the several polymer modified binders evaluated in this study, including a commercial modified binder, it can be concluded that the new PMBs produced with the base bitumen 70/100 and 5% of each plastic waste (HDPE or EVA) results in binders with very good performance, similar to that of the commercial modified binder.

Hand gesture recognition for human computer interaction : a comparative study of different image features

Hand gesture recognition for human computer interaction, being a natural way of human computer interaction, is an area of active research in computer vision and machine learning. This is an area with many different possible applications, giving users a simpler and more natural way to communicate with robots/systems interfaces, without the need for extra devices. So, the primary goal of gesture recognition research is to create systems, which can identify specific human gestures and use them to convey information or for device control. For that, vision-based hand gesture interfaces require fast and extremely robust hand detection, and gesture recognition in real time. In this study we try to identify hand features that, isolated, respond better in various situations in human-computer interaction. The extracted features are used to train a set of classifiers with the help of RapidMiner in order to find the best learner. A dataset with our own gesture vocabulary consisted of 10 gestures, recorded from 20 users was created for later processing. Experimental results show that the radial signature and the centroid distance are the features that when used separately obtain better results, with an accuracy of 91% and 90,1% respectively obtained with a Neural Network classifier. These to methods have also the advantage of being simple in terms of computational complexity, which make them good candidates for real-time hand gesture recognition.

Generic system for human-computer gesture interaction: applications on sign language recognition and robotic soccer refereeing

Hand gestures are a powerful way for human communication, with lots of potential applications in the area of human computer interaction. Vision-based hand gesture recognition techniques have many proven advantages compared with traditional devices, giving users a simpler and more natural way to communicate with electronic devices. This work proposes a generic system architecture based in computer vision and machine learning, able to be used with any interface for human-computer interaction. The proposed solution is mainly composed of three modules: a pre-processing and hand segmentation module, a static gesture interface module and a dynamic gesture interface module. The experiments showed that the core of visionbased interaction systems could be the same for all applications and thus facilitate the implementation. For hand posture recognition, a SVM (Support Vector Machine) model was trained and used, able to achieve a final accuracy of 99.4%. For dynamic gestures, an HMM (Hidden Markov Model) model was trained for each gesture that the system could recognize with a final average accuracy of 93.7%. The proposed solution as the advantage of being generic enough with the trained models able to work in real-time, allowing its application in a wide range of human-machine applications. To validate the proposed framework two applications were implemented. The first one is a real-time system able to interpret the Portuguese Sign Language. The second one is an online system able to help a robotic soccer game referee judge a game in real time.

Generic system for human-computer gesture interaction

Hand gestures are a powerful way for human communication, with lots of potential applications in the area of human computer interaction. Vision-based hand gesture recognition techniques have many proven advantages compared with traditional devices, giving users a simpler and more natural way to communicate with electronic devices. This work proposes a generic system architecture based in computer vision and machine learning, able to be used with any interface for humancomputer interaction. The proposed solution is mainly composed of three modules: a pre-processing and hand segmentation module, a static gesture interface module and a dynamic gesture interface module. The experiments showed that the core of vision-based interaction systems can be the same for all applications and thus facilitate the implementation. In order to test the proposed solutions, three prototypes were implemented. For hand posture recognition, a SVM model was trained and used, able to achieve a final accuracy of 99.4%. For dynamic gestures, an HMM model was trained for each gesture that the system could recognize with a final average accuracy of 93.7%. The proposed solution as the advantage of being generic enough with the trained models able to work in real-time, allowing its application in a wide range of human-machine applications.

Evaluating ubiquitous computing environments using 3D simulation

Human activity is very dynamic and subtle, and most physical environments are also highly dynamic and support a vast range of social practices that do not map directly into any immediate ubiquitous computing functionally. Identifying what is valuable to people is very hard and obviously leads to great uncertainty regarding the type of support needed and the type of resources needed to create such support. We have addressed the issues of system development through the adoption of a Crowdsourced software development model [13]. We have designed and developed Anywhere places, an open and flexible system support infrastructure for Ubiquitous Computing that is based on a balanced combination between global services and applications and situated devices. Evaluation, however, is still an open problem. The characteristics of ubiquitous computing environments make their evaluation very complex: there are no globally accepted metrics and it is very difficult to evaluate large-scale and long-term environments in real contexts. In this paper, we describe a first proposal of an hybrid 3D simulated prototype of Anywhere places that combines simulated and real components to generate a mixed reality which can be used to assess the envisaged ubiquitous computing environments [17].

Interaction paradigms versus age-related user profiles: an evaluation on content selection

Novel input modalities such as touch, tangibles or gestures try to exploit human's innate skills rather than imposing new learning processes. However, despite the recent boom of different natural interaction paradigms, it hasn't been systematically evaluated how these interfaces influence a user's performance or whether each interface could be more or less appropriate when it comes to: 1) different age groups; and 2) different basic operations, as data selection, insertion or manipulation. This work presents the first step of an exploratory evaluation about whether or not the users' performance is indeed influenced by the different interfaces. The key point is to understand how different interaction paradigms affect specific target-audiences (children, adults and older adults) when dealing with a selection task. 60 participants took part in this study to assess how different interfaces may influence the interaction of specific groups of users with regard to their age. Four input modalities were used to perform a selection task and the methodology was based on usability testing (speed, accuracy and user preference). The study suggests a statistically significant difference between mean selection times for each group of users, and also raises new issues regarding the “old” mouse input versus the “new” input modalities.

Development of a new 3D OpenFOAM® solver to model the cooling stage in profile extrusion

[Excerpt] The advantages resulting from the use of numerical modelling tools to support the design of processing equipment are almost consensual. The design of calibration systems in profile extrusion is not an exception . H owever , the complex geome tries and heat exchange phenomena involved in this process require the use of numerical solvers able to model the heat exchange in more than one domain ( calibrator and polymer), the compatibilization of the heat transfer at the profile - calibrator interface and with the ability to deal with complex geometries. The combination of all these features is usually hard to find in commercial software. Moreover , the dimension of the meshes required to ob tain accurate results, result in computational times prohibitive for industrial application. (...)

(Un)suitability of the use of pH buffers in biological, biochemical and environmental studies and their interaction with metal ions - a review

The use of buffers to maintain the pH within a desired range is a very common practice in chemical, biochemical and biological studies. Among them, zwitterionic N-substituted aminosulfonic acids, usually known as Good's buffers, although widely used, can complex metals and interact with biological systems. The present work reviews, discusses and updates the metal complexation characteristics of thirty one commercially available buffers. In addition, their impact on biological systems is also presented. The influences of these buffers on the results obtained in biological, biochemical and environmental studies, with special focus on their interaction with metal ions, are highlighted and critically reviewed. Using chemical speciation simulations, based on the current knowledge of the metal-buffer stability constants, a proposal of the most adequate buffer to employ for a given metal ion is presented.