Efeitos de maré no movimento orbital de satélites artificiais

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Avaliação clínica, morbi-mortalidade e desenvolvimento de bezerros da raça Brahman produzidos por fertilização in vitro e inseminação artificial

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Efeito da utilização de antioxidante no diluidor para a criopreservação de sêmen bovino avaliado através de testes complementares, inseminação artificial e fecundação in vitro

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Avaliação da taxa de concepção de novilhas e vacas (Bos taurus x Bos indicus) com o uso de sêmen sexado na inseminação artificial ou embriões produzidos in vivo e in vitro

Pós-graduação em Medicina Veterinária - FCAV

A Unitary Approach to Information and Estimation Theory in Digital Communication Systems

This thesis presents the outcomes of a Ph.D. course in telecommunications engineering. It is focused on the optimization of the physical layer of digital communication systems and it provides innovations for both multi- and single-carrier systems. For the former type we have first addressed the problem of the capacity in presence of several nuisances. Moreover, we have extended the concept of Single Frequency Network to the satellite scenario, and then we have introduced a novel concept in subcarrier data mapping, resulting in a very low PAPR of the OFDM signal. For single carrier systems we have proposed a method to optimize constellation design in presence of a strong distortion, such as the non linear distortion provided by satellites' on board high power amplifier, then we developed a method to calculate the bit/symbol error rate related to a given constellation, achieving an improved accuracy with respect to the traditional Union Bound with no additional complexity. Finally we have designed a low complexity SNR estimator, which saves one-half of multiplication with respect to the ML estimator, and it has similar estimation accuracy.

Environmental weathering of natural and artificial stones used in historical architecture: influence of microstructure and new restoration methods

For some study cases (the Cathedral of Modena, Italy, XII-XIV century; the Ducal Palace in Mantua, Italy, XVI century; the church of San Francesco in Fano, Italy, XIV-XIX century), considered as representative of the use of natural and artificial stones in historical architecture, the complex interaction between environ-mental aggressiveness, materials’ microstructural characteristics and degradation was investigated. From the results of such analyses, it was found that materials microstructure plays a fundamental role in the actual extent to which weathering mechanisms affect natural and artificial stones. Consequently, the need of taking into account the important role of material microstructure, when evaluating the environmental aggressiveness to natural and artificial stones, was highlighted. Therefore, a possible quantification of the role of microstructure on the resistance to environmental attack was investigated. By exposing stone samples, with significantly different microstructural features, to slightly acidic aqueous solutions, simulating clean and acid rain, a good correlation between weight losses and the product of carbonate content and specific surface area (defined as the “vulnerable specific surface area”) was found. Alongside the evaluation of stone vulnerability, the development of a new consolidant for weathered carbonate stones was undertaken. The use of hydroxya-patite, formed by reacting the calcite of the stone with an aqueous solution of di-ammonium hydrogen phosphate, was found to be a promising consolidating tech-nique for carbonates stones. Indeed, significant increases in the mechanical prop-erties can be achieved after the treatment, which has the advantage of simply con-sisting in a non-hazardous aqueous solution, able to penetrate deeply into the stone (> 2 cm) and bring significant strengthening after just 2 days of reaction. Furthermore, the stone sorptivity is not eliminated after treatment, so that water and water vapor exchanges between the stone and the environment are not com-pletely blocked.

Artificial metaplasticity prediction model for cognitive rehabilitation outcome in acquired brain injury patients

Objective The main purpose of this research is the novel use of artificial metaplasticity on multilayer perceptron (AMMLP) as a data mining tool for prediction the outcome of patients with acquired brain injury (ABI) after cognitive rehabilitation. The final goal aims at increasing knowledge in the field of rehabilitation theory based on cognitive affectation. Methods and materials The data set used in this study contains records belonging to 123 ABI patients with moderate to severe cognitive affectation (according to Glasgow Coma Scale) that underwent rehabilitation at Institut Guttmann Neurorehabilitation Hospital (IG) using the tele-rehabilitation platform PREVIRNEC©. The variables included in the analysis comprise the neuropsychological initial evaluation of the patient (cognitive affectation profile), the results of the rehabilitation tasks performed by the patient in PREVIRNEC© and the outcome of the patient after a 3–5 months treatment. To achieve the treatment outcome prediction, we apply and compare three different data mining techniques: the AMMLP model, a backpropagation neural network (BPNN) and a C4.5 decision tree. Results The prediction performance of the models was measured by ten-fold cross validation and several architectures were tested. The results obtained by the AMMLP model are clearly superior, with an average predictive performance of 91.56%. BPNN and C4.5 models have a prediction average accuracy of 80.18% and 89.91% respectively. The best single AMMLP model provided a specificity of 92.38%, a sensitivity of 91.76% and a prediction accuracy of 92.07%. Conclusions The proposed prediction model presented in this study allows to increase the knowledge about the contributing factors of an ABI patient recovery and to estimate treatment efficacy in individual patients. The ability to predict treatment outcomes may provide new insights toward improving effectiveness and creating personalized therapeutic interventions based on clinical evidence.

Intermediary equatorial orbits of an artificial satellite,

"NBS project 1104-12-11440."

Artificial reefs concentrate nutrients and alter benthic community structure in an oligotrophic, subtropical estuary

The construction of artificial reefs in the oligotrophic seagrass meadows of central Florida Bay attracted large aggregations of fish and invertebrates, and assays of nutrient availability indicated increases in availability of nutrients to sediment microalgae, periphyton, and seagrasses around reefs. An average of 37.8 large (> 10 cm) mobile animals were observed on each small artificial reef. The dominant fish species present was the gray snapper (Lutjanus griseus Linnaeus, 1758). Four yrs after the establishment of the artificial reefs, microphytobenthos abundance was twice as high in reef plots (1.7 ± 0.1 μg chl-a cm-2) compared to control plots (0.9 ± 0.1 μg chl-a cm-2). The accumulation of periphyton on glass periphytometers was four times higher in artificial reef plots (200.1 ± 45.8 mg chl-a m-2) compared to control plots (54.8 ± 6.8 mg chl-a m-2). The seagrass beds surrounding the artificial reefs changed rapidly, from a sparse Thalassia testudinum (Banks & Soland. ex König) dominated community, which persisted at control plots, to a community dominated by Halodule wrightii (Ascherson). Such changes mirror the changes induced in experimentally fertilized seagrass beds in Florida, strongly suggesting that the aggregations of animals attracted by artificial reefs concentrated nutrients in this oligotrophic seascape, favoring the growth of fast-growing primary producers like microphytobenthos and periphyton, and changing the competitively dominant seagrass from slow-growing T. testudinum to faster-growing H. wrightii in the vicinity of the reefs.

Design optimisation using advanced artificial intelligent system coupled to hybrid-game strategies

One of the main aims in artificial intelligent system is to develop robust and efficient optimisation methods for Multi-Objective (MO) and Multidisciplinary Design (MDO) design problems. The paper investigates two different optimisation techniques for multi-objective design optimisation problems. The first optimisation method is a Non-Dominated Sorting Genetic Algorithm II (NSGA-II). The second method combines the concepts of Nash-equilibrium and Pareto optimality with Multi-Objective Evolutionary Algorithms (MOEAs) which is denoted as Hybrid-Game. Numerical results from the two approaches are compared in terms of the quality of model and computational expense. The benefit of using the distributed hybrid game methodology for multi-objective design problems is demonstrated.