Corrosion protection of PVD and paint coatings for selective solar absorber surfaces

The selective solar absorber surface is a fundamental part of a solar thermal collector, as it is responsible for the solar radiation absorption and for reduction of radiation heat losses. The surface’s optical properties, the solar absorption (á) and the emittance (å), have great impact on the solar thermal collector efficiency. In this work, two coatings types were studied: coatings obtained by physical vapor deposition (PVDs) and coatings obtained by projection with different paints (PCs) on aluminum substrates. The most common industrial high performing solar selective absorbers are nowadays produced by vacuum deposition methods, showing some disadvantages, such as lower durability, lower resistance to corrosion, adhesion and scratch, higher cost and complex production techniques. Currently, spectrally selective paints are a potential alternative for absorbing surfaces in low temperature applications, with attractive features such as ease of processing, durability and commercial availability with low cost. Solar absorber surfaces were submitted to accelerated ageing tests, specified in ISO 22975-3. This standard is applicable to the evaluation of the long term behavior and service life of selective solar absorbers for solar collectors working under typical domestic hot water system conditions. The studied coatings have, in the case of PVDs solar absorptions between 0.93 and 0.96 and emittance between 0.07 and 0.10, and in the case of PCs, solar absorptions between 0.91 and 0.93 and emittance between 0.40 and 0.60. In addition to evaluating long term behavior based on artificial ageing tests, it is also important to know the degradation mechanism of different coatings that are currently in the market. Electrochemical impedance spectroscopy (EIS) allows for the assessment of mechanistic information concerning the degradation processes, providing quantitative data as output, which can easily relate to the kinetic parameters of the system. EIS measures were carried out on Gamry FAS2 Femostat coupled with a PCL4 Controller. Two electrolytes were used, 0.5 M NaCl and 0.5 M Na2SO4, and the surfaces were tested at different immersion times up to 4 weeks. The following types of specimens have been tested: Aluminium with/without surface treatment, 3 selective paint coatings (one with a poly(urethane) binder and two with silicone binders) and 2 PVD coatings. Based on the behaviour of the specimens throughout the 4 weeks of immersion, it is possible to conclude that the coating showing the best protective properties corresponds to the selective paint coating with a polyurethane resin followed by the other paint coatings, whereas both the PVD coatings do not confer any protection to the substrate, having a deleterious effect as compared to the untreated aluminium reference.

Learning Binary Code Representations for Effective and Efficient Image Retrieval

The size of online image datasets is constantly increasing. Considering an image dataset with millions of images, image retrieval becomes a seemingly intractable problem for exhaustive similarity search algorithms. Hashing methods, which encodes high-dimensional descriptors into compact binary strings, have become very popular because of their high efficiency in search and storage capacity. In the first part, we propose a multimodal retrieval method based on latent feature models. The procedure consists of a nonparametric Bayesian framework for learning underlying semantically meaningful abstract features in a multimodal dataset, a probabilistic retrieval model that allows cross-modal queries and an extension model for relevance feedback. In the second part, we focus on supervised hashing with kernels. We describe a flexible hashing procedure that treats binary codes and pairwise semantic similarity as latent and observed variables, respectively, in a probabilistic model based on Gaussian processes for binary classification. We present a scalable inference algorithm with the sparse pseudo-input Gaussian process (SPGP) model and distributed computing. In the last part, we define an incremental hashing strategy for dynamic databases where new images are added to the databases frequently. The method is based on a two-stage classification framework using binary and multi-class SVMs. The proposed method also enforces balance in binary codes by an imbalance penalty to obtain higher quality binary codes. We learn hash functions by an efficient algorithm where the NP-hard problem of finding optimal binary codes is solved via cyclic coordinate descent and SVMs are trained in a parallelized incremental manner. For modifications like adding images from an unseen class, we propose an incremental procedure for effective and efficient updates to the previous hash functions. Experiments on three large-scale image datasets demonstrate that the incremental strategy is capable of efficiently updating hash functions to the same retrieval performance as hashing from scratch.

EasyInterface: a toolkit for the rapid development of GUIs for research prototype tools

During the lifetime of a research project, different partners develop several research prototype tools that share many common aspects. This is equally true for researchers as individuals and as groups: during a period of time they often develop several related tools to pursue a specific research line. Making research prototype tools easily accessible to the community is of utmost importance to promote the corresponding research, get feedback, and increase the tools’ lifetime beyond the duration of a specific project. One way to achieve this is to build graphical user interfaces (GUIs) that facilitate trying tools; in particular, with web-interfaces one avoids the overhead of downloading and installing the tools. Building GUIs from scratch is a tedious task, in particular for web-interfaces, and thus it typically gets low priority when developing a research prototype. Often we opt for copying the GUI of one tool and modifying it to fit the needs of a new related tool. Apart from code duplication, these tools will “live” separately, even though we might benefit from having them all in a common environment since they are related. This work aims at simplifying the process of building GUIs for research prototypes tools. In particular, we present EasyInterface, a toolkit that is based on novel methodology that provides an easy way to make research prototype tools available via common different environments such as a web-interface, within Eclipse, etc. It includes a novel text-based output language that allows to present results graphically without requiring any knowledge in GUI/Web programming. For example, an output of a tool could be (a structured version of) “highlight line number 10 of file ex.c” and “when the user clicks on line 10, open a dialog box with the text ...”. The environment will interpret this output and converts it to corresponding visual e_ects. The advantage of using this approach is that it will be interpreted equally by all environments of EasyInterface, e.g., the web-interface, the Eclipse plugin, etc. EasyInterface has been developed in the context of the Envisage [5] project, and has been evaluated on tools developed in this project, which include static analyzers, test-case generators, compilers, simulators, etc. EasyInterface is open source and available at GitHub2.

Provable Security for Cryptocurrencies

The past several years have seen the surprising and rapid rise of Bitcoin and other “cryptocurrencies.” These are decentralized peer-to-peer networks that allow users to transmit money, tocompose financial instruments, and to enforce contracts between mutually distrusting peers, andthat show great promise as a foundation for financial infrastructure that is more robust, efficientand equitable than ours today. However, it is difficult to reason about the security of cryptocurrencies. Bitcoin is a complex system, comprising many intricate and subtly-interacting protocol layers. At each layer it features design innovations that (prior to our work) have not undergone any rigorous analysis. Compounding the challenge, Bitcoin is but one of hundreds of competing cryptocurrencies in an ecosystem that is constantly evolving. The goal of this thesis is to formally reason about the security of cryptocurrencies, reining in their complexity, and providing well-defined and justified statements of their guarantees. We provide a formal specification and construction for each layer of an abstract cryptocurrency protocol, and prove that our constructions satisfy their specifications. The contributions of this thesis are centered around two new abstractions: “scratch-off puzzles,” and the “blockchain functionality” model. Scratch-off puzzles are a generalization of the Bitcoin “mining” algorithm, its most iconic and novel design feature. We show how to provide secure upgrades to a cryptocurrency by instantiating the protocol with alternative puzzle schemes. We construct secure puzzles that address important and well-known challenges facing Bitcoin today, including wasted energy and dangerous coalitions. The blockchain functionality is a general-purpose model of a cryptocurrency rooted in the “Universal Composability” cryptography theory. We use this model to express a wide range of applications, including transparent “smart contracts” (like those featured in Bitcoin and Ethereum), and also privacy-preserving applications like sealed-bid auctions. We also construct a new protocol compiler, called Hawk, which translates user-provided specifications into privacy-preserving protocols based on zero-knowledge proofs.

Processamento e caracterização de compósitos Poli(METACRILATO DE METILA)/Sílica (PMMA/SiO2)

Currently the search for new materials with properties suitable for specific applications has increased the number of researches that aim to address market needs. The poly (methyl methacrylate) (PMMA) is one of the most important polymers of the family of polyacrylates and polymethacrylates, especially for its unique optical properties and weathering resistance, and exceptional hardness and gloss. The development of polymer composites by the addition of inorganic fillers to the PMMA matrix increases the potential use of this polymer in various fields of application. The most commonly used inorganic fillers are particles of silica (SiO2), modified clays, graphite and carbon nanotubes. The main objective of this work is the development of PMMA/SiO2 composites at different concentrations of SiO2, for new applications as engineering plastics. The composites were produced by extrusion of tubular film, and obtained via solution for application to commercial PMMA plates, and also by injection molding, for improved the abrasion and scratch resistance of PMMA without compromising transparency. The effects of the addition of silica particles in the polymer matrix properties were evaluated by the maximum tensile strength, hardness, abrasion and scratch resistance, in addition to preliminary characterization by torque rheometry and melt flow rate. The results indicated that it is possible to use silica particles in a PMMA matrix, and a higher silica concentration produced an increase of the abrasion and scratch resistance, hardness, and reduced tensile strength

Synthetic Circuits for Feedback and Detection in Bacteria

Synthetic biology, by co-opting molecular machinery from existing organisms, can be used as a tool for building new genetic systems from scratch, for understanding natural networks through perturbation, or for hybrid circuits that piggy-back on existing cellular infrastructure. Although the toolbox for genetic circuits has greatly expanded in recent years, it is still difficult to separate the circuit function from its specific molecular implementation. In this thesis, we discuss the function-driven design of two synthetic circuit modules, and use mathematical models to understand the fundamental limits of circuit topology versus operating regimes as determined by the specific molecular implementation. First, we describe a protein concentration tracker circuit that sets the concentration of an output protein relative to the concentration of a reference protein. The functionality of this circuit relies on a single negative feedback loop that is implemented via small programmable protein scaffold domains. We build a mass-action model to understand the relevant timescales of the tracking behavior and how the input/output ratios and circuit gain might be tuned with circuit components. Second, we design an event detector circuit with permanent genetic memory that can record order and timing between two chemical events. This circuit was implemented using bacteriophage integrases that recombine specific segments of DNA in response to chemical inputs. We simulate expected population-level outcomes using a stochastic Markov-chain model, and investigate how inferences on past events can be made from differences between single-cell and population-level responses. Additionally, we present some preliminary investigations on spatial patterning using the event detector circuit as well as the design of stationary phase promoters for growth-phase dependent activation. These results advance our understanding of synthetic gene circuits, and contribute towards the use of circuit modules as building blocks for larger and more complex synthetic networks.

Improvements in Hardware Transactional Memory for GPU Architectures

In the multi-core CPU world, transactional memory (TM)has emerged as an alternative to lock-based programming for thread synchronization. Recent research proposes the use of TM in GPU architectures, where a high number of computing threads, organized in SIMT fashion, requires an effective synchronization method. In contrast to CPUs, GPUs offer two memory spaces: global memory and local memory. The local memory space serves as a shared scratch-pad for a subset of the computing threads, and it is used by programmers to speed-up their applications thanks to its low latency. Prior work from the authors proposed a lightweight hardware TM (HTM) support based in the local memory, modifying the SIMT execution model and adding a conflict detection mechanism. An efficient implementation of these features is key in order to provide an effective synchronization mechanism at the local memory level. After a quick description of the main features of our HTM design for GPU local memory, in this work we gather together a number of proposals designed with the aim of improving those mechanisms with high impact on performance. Firstly, the SIMT execution model is modified to increase the parallelism of the application when transactions must be serialized in order to make forward progress. Secondly, the conflict detection mechanism is optimized depending on application characteristics, such us the read/write sets, the probability of conflict between transactions and the existence of read-only transactions. As these features can be present in hardware simultaneously, it is a task of the compiler and runtime to determine which ones are more important for a given application. This work includes a discussion on the analysis to be done in order to choose the best configuration solution.

Avaliação histopatológica do fígado de bovinos mantidos em pastagens de Brachiaria spp. provenientes de abatedouros no Brasil

Dissertação (mestrado)—Universidade de Brasília, Faculdade de Agronomia e Medicina Veterinária, Programa de Pós-Graduação em Saúde Animal, 2016.

Canine mesenchymal stem cells are neurotrophic and angiogenic:an in vitro assessment of their paracrine activity

Mesenchymal stem cells (MSCs) have been used in cell replacement therapies for connective tissue damage, but also can stimulate wound healing through paracrine activity. In order to further understand the potential use of MSCs to treat dogs with neurological disorders, this study examined the paracrine action of adipose-derived canine MSCs on neuronal and endothelial cell models. The culture-expanded MSCs exhibited a MSC phenotype according to plastic adherence, cell morphology, CD profiling and differentiation potential along mesenchymal lineages. Treating the SH-SY5Y neuronal cell line with serum-free MSC culture-conditioned medium (MSC CM) significantly increased SH-SY5Y cell proliferation (P < 0.01), neurite outgrowth (P = 0.0055) and immunopositivity for the neuronal marker βIII-tubulin (P = 0.0002). Treatment of the EA.hy926 endothelial cell line with MSC CM significantly increased the rate of wound closure in endothelial cell scratch wound assays (P = 0.0409), which was associated with significantly increased endothelial cell proliferation (P < 0.05) and migration (P = 0.0001). Furthermore, canine MSC CM induced endothelial tubule formation in EA.hy926 cells in a soluble basement membrane matrix. Hence, this study has demonstrated that adipose-derived canine MSC CM stimulated neuronal and endothelial cells probably through the paracrine activity of MSC-secreted factors. This supports the use of canine MSC transplants or their secreted products in the clinical treatment of dogs with neurological disorders and provides some insight into possible mechanisms of action.

Random walk with restart over dynamic graphs

Random Walk with Restart (RWR) is an appealing measure of proximity between nodes based on graph structures. Since real graphs are often large and subject to minor changes, it is prohibitively expensive to recompute proximities from scratch. Previous methods use LU decomposition and degree reordering heuristics, entailing O(|V|^3) time and O(|V|^2) memory to compute all (|V|^2) pairs of node proximities in a static graph. In this paper, a dynamic scheme to assess RWR proximities is proposed: (1) For unit update, we characterize the changes to all-pairs proximities as the outer product of two vectors. We notice that the multiplication of an RWR matrix and its transition matrix, unlike traditional matrix multiplications, is commutative. This can greatly reduce the computation of all-pairs proximities from O(|V|^3) to O(|delta|) time for each update without loss of accuracy, where |delta| (<<|V|^2) is the number of affected proximities. (2) To avoid O(|V|^2) memory for all pairs of outputs, we also devise efficient partitioning techniques for our dynamic model, which can compute all pairs of proximities segment-wisely within O(l|V|) memory and O(|V|/l) I/O costs, where 1<=l<=|V| is a user-controlled trade-off between memory and I/O costs. (3) For bulk updates, we also devise aggregation and hashing methods, which can discard many unnecessary updates further and handle chunks of unit updates simultaneously. Our experimental results on various datasets demonstrate that our methods can be 1–2 orders of magnitude faster than other competitors while securing scalability and exactness.