Genetics of resistance to powdery mildew (Microsphaera diffusa) in Brazilian soybean populations

Crosses between resistant and susceptible soybean cultivars were performed and the F2 populations were obtained to study the inheritance of soybean resistance to powdery mildew and to estimate the number and action of genes related to resistance. The reaction to powdery mildew was studied in a greenhouse and pots carrying plants with symptoms were distributed among the pots carrying the genotypes to be tested as a source of inoculum. Individual plants were scored according to the method of Yorinori (1997), with modifications, and classified as resistant or susceptible. The results showed that adult soybeans plants can present resistance to powdery mildew, which is controlled by one major gene with a dominant effect.

Análise e síntese de antenas e superfícies seletivas de frequência utilizando computação evolucionária e inteligência de enxames

The frequency selective surfaces, or FSS (Frequency Selective Surfaces), are structures consisting of periodic arrays of conductive elements, called patches, which are usually very thin and they are printed on dielectric layers, or by openings perforated on very thin metallic surfaces, for applications in bands of microwave and millimeter waves. These structures are often used in aircraft, missiles, satellites, radomes, antennae reflector, high gain antennas and microwave ovens, for example. The use of these structures has as main objective filter frequency bands that can be broadcast or rejection, depending on the specificity of the required application. In turn, the modern communication systems such as GSM (Global System for Mobile Communications), RFID (Radio Frequency Identification), Bluetooth, Wi-Fi and WiMAX, whose services are highly demanded by society, have required the development of antennas having, as its main features, and low cost profile, and reduced dimensions and weight. In this context, the microstrip antenna is presented as an excellent choice for communications systems today, because (in addition to meeting the requirements mentioned intrinsically) planar structures are easy to manufacture and integration with other components in microwave circuits. Consequently, the analysis and synthesis of these devices mainly, due to the high possibility of shapes, size and frequency of its elements has been carried out by full-wave models, such as the finite element method, the method of moments and finite difference time domain. However, these methods require an accurate despite great computational effort. In this context, computational intelligence (CI) has been used successfully in the design and optimization of microwave planar structures, as an auxiliary tool and very appropriate, given the complexity of the geometry of the antennas and the FSS considered. The computational intelligence is inspired by natural phenomena such as learning, perception and decision, using techniques such as artificial neural networks, fuzzy logic, fractal geometry and evolutionary computation. This work makes a study of application of computational intelligence using meta-heuristics such as genetic algorithms and swarm intelligence optimization of antennas and frequency selective surfaces. Genetic algorithms are computational search methods based on the theory of natural selection proposed by Darwin and genetics used to solve complex problems, eg, problems where the search space grows with the size of the problem. The particle swarm optimization characteristics including the use of intelligence collectively being applied to optimization problems in many areas of research. The main objective of this work is the use of computational intelligence, the analysis and synthesis of antennas and FSS. We considered the structures of a microstrip planar monopole, ring type, and a cross-dipole FSS. We developed algorithms and optimization results obtained for optimized geometries of antennas and FSS considered. To validate results were designed, constructed and measured several prototypes. The measured results showed excellent agreement with the simulated. Moreover, the results obtained in this study were compared to those simulated using a commercial software has been also observed an excellent agreement. Specifically, the efficiency of techniques used were CI evidenced by simulated and measured, aiming at optimizing the bandwidth of an antenna for wideband operation or UWB (Ultra Wideband), using a genetic algorithm and optimizing the bandwidth, by specifying the length of the air gap between two frequency selective surfaces, using an optimization algorithm particle swarm

Técnicas inteligentes hídridas para o controle de sistemas não lineares

A neuro-fuzzy system consists of two or more control techniques in only one structure. The main characteristic of this structure is joining one or more good aspects from each technique to make a hybrid controller. This controller can be based in Fuzzy systems, artificial Neural Networks, Genetics Algorithms or rein forced learning techniques. Neuro-fuzzy systems have been shown as a promising technique in industrial applications. Two models of neuro-fuzzy systems were developed, an ANFIS model and a NEFCON model. Both models were applied to control a ball and beam system and they had their results and needed changes commented. Choose of inputs to controllers and the algorithms used to learning, among other information about the hybrid systems, were commented. The results show the changes in structure after learning and the conditions to use each one controller based on theirs characteristics

Search schemes for random optimization algorithms that preserve the asymptotic distribution

Markovian algorithms for estimating the global maximum or minimum of real valued functions defined on some domain Omega subset of R-d are presented. Conditions on the search schemes that preserve the asymptotic distribution are derived. Global and local search schemes satisfying these conditions are analysed and shown to yield sharper confidence intervals when compared to the i.i.d. case.

Beam Search Algorithms for Minimizing Tool Switches on a Flexible Manufacturing System

In the minimization of tool switches problem we seek a sequence to process a set of jobs so that the number of tool switches required is minimized. In this work different variations of a heuristic based on partial ordered job sequences are implemented and evaluated. All variations adopt a depth first strategy of the enumeration tree. The computational test results indicate that good results can be obtained by a variation which keeps the best three branches at each node of the enumeration tree, and randomly choose, among all active nodes, the next node to branch when backtracking.

Allocation of protective devices in distribution circuits using nonlinear programming models and genetic algorithms

The optimized allocation of protective devices in strategic points of the circuit improves the quality of the energy supply and the system reliability index. This paper presents a nonlinear integer programming (NLIP) model with binary variables, to deal with the problem of protective device allocation in the main feeder and all branches of an overhead distribution circuit, to improve the reliability index and to provide customers with service of high quality and reliability. The constraints considered in the problem take into account technical and economical limitations, such as coordination problems of serial protective devices, available equipment, the importance of the feeder and the circuit topology. The use of genetic algorithms (GAs) is proposed to solve this problem, using a binary representation that does (1) or does not (0) show allocation of protective devices (reclosers, sectionalizers and fuses) in predefined points of the circuit. Results are presented for a real circuit (134 busses), with the possibility of protective device allocation in 29 points. Also the ability of the algorithm in finding good solutions while improving significantly the indicators of reliability is shown. (C) 2003 Elsevier B.V. All rights reserved.

The genetics of hypertension modifies the renal cell replication response induced by experimental diabetes

To investigate whether the genetics of hypertension modifies renal cell responses in experimental diabetes, we studied the renal cell replication and its regulation by two cyclin-dependent kinase (Cdk) inhibitors, p27(Kip1) and p21(Cip1), in prehypertensive spontaneously hypertensive rats (SUR) and their genetically normotensive counterparts, Wistar Kyoto (WKY) rats, with and without streptozotocin-induced diabetes. In diabetic SIIR, the number of proliferating glomerular (0.6 +/- 0.3 positive cells/50 glomeruli) and tubulointerstitial (2.8 +/- 0.6 positive tubulointerstitial cells/50 grid fields) cells assessed by the bromodeoxyuridine technique was significantly (P = 0.0002) lower than in control SIIR (13.2 +/- 1.7 and 48.6 +/- 9.7, respectively) and control (14.0 +/- 1.8 and 63.9 +/- 10.6) and diabetic (14.3 +/- 3.5 and 66.4 +/- 11.5) WKY rats. Proliferating cell nuclear antigen, another marker of cell proliferation, was significantly reduced in replicating glomerular (P = 0.0002) and tubulointerstitial (P < 0.0001) cells in diabetic SHR. In freshly isolated glomeruli, the level of p27(Kip1) detected by Western blotting was significantly higher In diabetic SIIR than in nondiabetic SHR (1.52 +/- 0.14 vs. 1.00 +/- 0.10% of control, P = 0.014). The expression of p21(Cip1) in isolated glomeruli did not differ among the groups of rats. In conclusion, the response of renal cell replication to diabetes differs markedly between prehypertensive SIIR and their WKY control rats. The decreased glomerular cell proliferation in prehypertensive diabetic SIIR is at least partly mediated by a higher expression of the Cdk inhibitor p27(Kip1).

Genotype by environment interaction for 450-day weight of Nelore cattle analyzed by reaction norm models

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Using Amino Acid Correlation and Community Detection Algorithms to Identify Functional Determinants in Protein Families

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

Genetics of neotropical fish: from chromosomes to populations

The Neotropical freshwater fish fauna is very rich-according to the most recent catalogue 71 families and 4,475 species have been described. However, only a small amount of general information is available on the composition of Neotropical marine fishes. In Brazil, 1,298 marine species have been recorded. General analysis of available cytogenetic and population genetic data clearly indicates research has been mainly concentrated on freshwater fishes. Thus, today, cytogenetic information is available for 475 species of Characiformes, 318 species of Siluriformes, 48 species of Gymnotiformes, 199 freshwater species that do not belong to the superorder Ostariophysi, and only 109 species of marine fishes. For the species studied, only about 6% have sex chromosomes and about 5% have supernumerary or B chromosomes. A review of the cytogenetic studies shows that these data have provided valuable information about the relationships between fish groups, the occurrence of cryptic species and species complexes, the mechanism of sex determination and sex chromosome evolution, the distribution of nucleolus organizer regions, the existence supernumerary chromosomes, and the relationship between polyploidy and evolution. In relation to populations in Neotropical marine waters, the studies have shown the presence of cryptic species, which has important implications for fishery management. Different levels of genetic structuring can be found among Neotropical freshwater migratory fish species. This raises important implications for fish population genetic diversity and consequently its sustainable utilization in inland fisheries and aquaculture, specifically for conservation of ichthyo-diversity and survival.

The influence of landscape characteristics and home-range size on the quantification of landscape-genetics relationships

A common approach used to estimate landscape resistance involves comparing correlations of ecological and genetic distances calculated among individuals of a species. However, the location of sampled individuals may contain some degree of spatial uncertainty due to the natural variation of animals moving through their home range or measurement error in plant or animal locations. In this study, we evaluate the ways that spatial uncertainty, landscape characteristics, and genetic stochasticity interact to influence the strength and variability of conclusions about landscape-genetics relationships. We used a neutral landscape model to generate 45 landscapes composed of habitat and non-habitat, varying in percent habitat, aggregation, and structural connectivity (patch cohesion). We created true and alternate locations for 500 individuals, calculated ecological distances (least-cost paths), and simulated genetic distances among individuals. We compared correlations between ecological distances for true and alternate locations. We then simulated genotypes at 15 neutral loci and investigated whether the same influences could be detected in simple Mantel tests and while controlling for the effects of isolation-by distance using the partial Mantel test. Spatial uncertainty interacted with the percentage of habitat in the landscape, but led to only small reductions in correlations. Furthermore, the strongest correlations occurred with low percent habitat, high aggregation, and low to intermediate levels of cohesion. Overall genetic stochasticity was relatively low and was influenced by landscape characteristics.

Use of genetic algorithms and solvation potential to study peptides structure

In this work, genetic algorithms concepts along with a rotamer library for proteins side chains and implicit solvation potential are used to optimize the tertiary structure of peptides. We starting from the known PDB structure of its backbone which is kept fixed while the side chains allowed adopting the conformations present in the rotamer library. It was used rotamer library independent of backbone and a implicit solvation potential. The structure of Mastoporan-X was predicted using several force fields with a growing complexity; we started it with a field where the only present interaction was Lennard-Jones. We added the Coulombian term and we considered the solvation effects through a term proportional to the solvent accessible area. This paper present good and interesting results obtained using the potential with solvation term and rotamer library. Hence, the algorithm (called YODA) presented here can be a good tool to the prediction problem. (c) 2007 Elsevier B.V. All rights reserved.

Mating system in Myracrodruon urundeuva (Anarcadiaceae): implications for conservation genetics

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