Variability in leaf rust susceptibility among peach cultivars

The aim of this work was to estimate the susceptibility of thirty-six peach cultivars to leaf rust caused by Tranzschelia discolor f. sp. persica. The incidence and severity of the disease as well as defoliation in peach trees of an experimental orchard of Parana Federal University of Technology, Campus Dois Vizinhos were evaluated on the growing seasons 2004/2005 and 2005/2006. Immunity to this disease was not observed in the studied cultivars. There was difference in leaf rust intensity depending on the growing season conditions. Cultivars 'Pilcha', 'Sinuelo', 'Chirua', 'Sulina', 'Eldorado' and 'Pampeano' showed tolerance to leaf rust, whereas cultivars 'Vila Nova', 'Fla 1372', 'Coral 2', 'Chimarrita', 'Della Nona', 'BR-1 ' and 'Guaiaca' showed high susceptibility.

Ensuring dynamic strategic fit of firms that compete globally in alliances and networks: proposing the Global SNA - Strategic Network Analysis - framework

In order to sustain their competitive advantage in the current increasingly globalized and turbulent context, more and more firms are competing globally in alliances and networks that oblige them to adopt new managerial paradigms and tools. However, their strategic analyses rarely take into account the strategic implications of these alliances and networks, considering their global relational characteristics, admittedly because of a lack of adequate tools to do so. This paper contributes to research that seeks to fill this gap by proposing the Global Strategic Network Analysis - SNA - framework. Its purpose is to help firms that compete globally in alliances and networks to carry out their strategic assessments and decision-making with a view to ensuring dynamic strategic fit from both a global and relational perspective.

Peroral susceptibility of Aedes albifasciatus and Culex pipiens complex mosquitoes (Diptera: Culicidae) from Argentina to western equine encephalitis virus

The transmission cycle of western equine encephalitis (WEE) virus in South America is unknown. A WEE virus strain was isolated from Aedes albifasciatus in Argentina during the WEE epizootic of 1982-83. Also, Culex pipiens from Argentina was reported to be able to transmit WEE virus experimentally, but other results indicate that Cx. pipiens from the USA is refractory to this virus. We determined the susceptibility of Argentina strains of Ae. albifasciatus and Culex pipiens complex mosquites to infection by WEE virus by the oral route. Adult females were fed on chicks infected with a WEE virus strain isolated in Cordoba Province, Argentina, or were fed on a blood/virus suspension. Each mosquito ingested between 10(1.6) to 10(6.4) vero cell plaque-forming units of virus. Each of 28 Ae. albifasciatus was positive for virus from the fourth day postfeeding, and there was evidence for virus replication. In contrast, 0/44 Cx. p. quinquefasciatus and only 1/15 Cx. p. pipiens was positive. Aedes albifasciatus is susceptible to infection by WEE virus and should be considered a potential vector of this virus in Argentina. Both subspecies of Cx. pipiens are refractory to peroral infection by WEE virus and probably do not play a role in the WEE virus cycle in Argentina.

Susceptibility of Aedes aegypti larvae to temephos and Bacillus thuringiensis var israelensis in integrated control

The susceptibility of field collected Aedes aegypti larvae was evaluated in terms of median lethal time (LT50) and final mortality, when treated with temephos, Bacillus thuringiensis var israelensis as well as mixtures of these two agents. Third instar larvae were shown to be more susceptible than early and late fourth instar ones to the entomopathogen. Survival of some individuals when exposed to temephos suggest possible resistance. Temporal synergism in early fourth instar larvae was detected when they were exposed to mixtures of Bti-temephos. The possibility of this integrated treatment is commented on.

Predictive Optimal Matrix Converter Control for a Dynamic Voltage Restorer with Flywheel Energy Storage

This paper presents a predictive optimal matrix converter controller for a flywheel energy storage system used as Dynamic Voltage Restorer (DVR). The flywheel energy storage device is based on a steel seamless tube mounted as a vertical axis flywheel to store kinetic energy. The motor/generator is a Permanent Magnet Synchronous Machine driven by the AC-AC Matrix Converter. The matrix control method uses a discrete-time model of the converter system to predict the expected values of the input and output currents for all the 27 possible vectors generated by the matrix converter. An optimal controller minimizes control errors using a weighted cost functional. The flywheel and control process was tested as a DVR to mitigate voltage sags and swells. Simulation results show that the DVR is able to compensate the critical load voltage without delays, voltage undershoots or overshoots, overcoming the input/output coupling of matrix converters.

Periodic dynamic systems for infected hosts and mosquitoes

A mathematical model for the purpose of analysing the dynamic of the populations of infected hosts anf infected mosquitoes when the populations of mosquitoes are periodic in time is here presented. By the computation of a parameter lambda (the spectral radius of a certain monodromy matrix) one can state that either the infection peters out naturally) (lambda <= 1) or if lambda > 1 the infection becomes endemic. The model generalizes previous models for malaria by considering the case of periodic coefficients; it is also a variation of that for gonorrhea. The main motivation for the consideration of this present model was the recent studies on mosquitoes at an experimental rice irrigation system, in the South-Eastern region of Brazil.

Dynamic equilibrium through reinforcement learning

Reinforcement Learning is an area of Machine Learning that deals with how an agent should take actions in an environment such as to maximize the notion of accumulated reward. This type of learning is inspired by the way humans learn and has led to the creation of various algorithms for reinforcement learning. These algorithms focus on the way in which an agent’s behaviour can be improved, assuming independence as to their surroundings. The current work studies the application of reinforcement learning methods to solve the inverted pendulum problem. The importance of the variability of the environment (factors that are external to the agent) on the execution of reinforcement learning agents is studied by using a model that seeks to obtain equilibrium (stability) through dynamism – a Cart-Pole system or inverted pendulum. We sought to improve the behaviour of the autonomous agents by changing the information passed to them, while maintaining the agent’s internal parameters constant (learning rate, discount factors, decay rate, etc.), instead of the classical approach of tuning the agent’s internal parameters. The influence of changes on the state set and the action set on an agent’s capability to solve the Cart-pole problem was studied. We have studied typical behaviour of reinforcement learning agents applied to the classic BOXES model and a new form of characterizing the environment was proposed using the notion of convergence towards a reference value. We demonstrate the gain in performance of this new method applied to a Q-Learning agent.

Susceptibility of asthmatic children to respiratory infection

OBJECTIVE: A case-control study of patients with pneumonia was conducted to investigate whether wheezing diseases could be a risk factor. METHODS: A random sample was taken from a general university hospital in S. Paulo City between March and August 1994 comprising 51 cases of pneumonia paired by age and sex to 51 non-respiratory controls and 51 healthy controls. Data collection was carried out by two senior paediatricians. Diagnoses of pneumonia and presence of wheezing disease were independently established by each paediatrician for both cases and controls. Pneumonia was radiologically confirmed and repeatability of information on wheezing diseases was measured. Logistic regression analysis was used to identify risk factors. RESULTS: Wheezing diseases, interpreted as proxies of asthma, were found to be an important risk factor for pneumonia with an odds ratio of 7.07 (95%CI= 2.34-21.36), when the effects of bedroom crowding (odds ratio = 1.49 per person, 95%CI= 0.95-2.32) and of low family income (odds ratio = 5.59 against high family income, 95%CI= 1.38-22.63) were controlled. The risk of pneumonia attributable to wheezing diseases is tentatively calculated at 51.42%. CONCLUSION: It is concluded that at practice level asthmatics should deserve proper surveillance for infection and that at public health level pneumonia incidence could be reduced if current World Health Organisation's guidelines were reviewed as to include comprehensive care for this illness.

From unthinned continent to ocean: The deep structure of the West Iberia passive continental margin at 38 degrees N

The crustal and lithospheric mantle structure at the south segment of the west Iberian margin was investigated along a 370 km long seismic transect. The transect goes from unthinned continental crust onshore to oceanic crust, crossing the ocean-continent transition (OCT) zone. The wide-angle data set includes recordings from 6 OBSs and 2 inland seismic stations. Kinematic and dynamic modeling provided a 2D velocity model that proved to be consistent with the modeled free-air anomaly data. The interpretation of coincident multi-channel near-vertical and wide-angle reflection data sets allowed the identification of four main crustal domains: (i) continental (east of 9.4 degrees W); (ii) continental thinning (9.4 degrees W-9.7 degrees W): (iii) transitional (9.7 degrees W-similar to 10.5 degrees W); and (iv) oceanic (west of similar to 10.5 degrees W). In the continental domain the complete crustal section of slightly thinned continental crust is present. The upper (UCC, 5.1-6.0 km/s) and the lower continental crust (LCC, 6.9-7.2 km/s) are seismically reflective and have intermediate to low P-wave velocity gradients. The middle continental crust (MCC, 6.35-6.45 km/s) is generally unreflective with low velocity gradient. The main thinning of the continental crust occurs in the thinning domain by attenuation of the UCC and the LCC. Major thinning of the MCC starts to the west of the LCC pinchout point, where it rests directly upon the mantle. In the thinning domain the Moho slope is at least 13 degrees and the continental crust thickness decreases seaward from 22 to 11 km over a similar to 35 km distance, stretched by a factor of 1.5 to 3. In the oceanic domain a two-layer high-gradient igneous crust (5.3-6.0 km/s; 6.5-7.4 km/s) was modeled. The intra-crustal interface correlates with prominent mid-basement, 10-15 km long reflections in the multi-channel seismic profile. Strong secondary reflected PmP phases require a first order discontinuity at the Moho. The sedimentary cover can be as thick as 5 km and the igneous crustal thickness varies from 4 to 11 km in the west, where the profile reaches the Madeira-Tore Rise. In the transitional domain the crust has a complex structure that varies both horizontally and vertically. Beneath the continental slope it includes exhumed continental crust (6.15-6.45 km/s). Strong diffractions were modeled to originate at the lower interface of this layer. The western segment of this transitional domain is highly reflective at all levels, probably due to dykes and sills, according to the high apparent susceptibility and density modeled at this location. Sub-Moho mantle velocity is found to be 8.0 km/s, but velocities smaller than 8.0 km/s confined to short segments are not excluded by the data. Strong P-wave wide-angle reflections are modeled to originate at depth of 20 km within the lithospheric mantle, under the eastern segment of the oceanic domain, or even deeper at the transitional domain, suggesting a layered structure for the lithospheric mantle. Both interface depths and velocities of the continental section are in good agreement to the conjugate Newfoundland margin. A similar to 40 km wide OCT having a geophysical signature distinct from the OCT to the north favors a two pulse continental breakup.

Large area image sensing structures based on a-SiC : H: a dynamic characterization

In recent works large area hydrogenated amorphous silicon p-i-n structures with low conductivity doped layers were proposed as single element image sensors. The working principle of this type of sensor is based on the modulation, by the local illumination conditions, of the photocurrent generated by a light beam scanning the active area of the device. In order to evaluate the sensor capabilities is necessary to perform a response time characterization. This work focuses on the transient response of such sensor and on the influence of the carbon contents of the doped layers. In order to evaluate the response time a set of devices with different percentage of carbon incorporation in the doped layers is analyzed by measuring the scanner-induced photocurrent under different bias conditions.

Constructing good deals in discrete time arbitrage-free dynamic pricing models

Recent literature has proved that many classical pricing models (Black and Scholes, Heston, etc.) and risk measures (V aR, CV aR, etc.) may lead to “pathological meaningless situations”, since traders can build sequences of portfolios whose risk leveltends to −infinity and whose expected return tends to +infinity, i.e., (risk = −infinity, return = +infinity). Such a sequence of strategies may be called “good deal”. This paper focuses on the risk measures V aR and CV aR and analyzes this caveat in a discrete time complete pricing model. Under quite general conditions the explicit expression of a good deal is given, and its sensitivity with respect to some possible measurement errors is provided too. We point out that a critical property is the absence of short sales. In such a case we first construct a “shadow riskless asset” (SRA) without short sales and then the good deal is given by borrowing more and more money so as to invest in the SRA. It is also shown that the SRA is interested by itself, even if there are short selling restrictions.

Ankle dynamic in stroke patients: agonist vs. antagonist muscle relations

O documento em anexo encontra-se na versão post-print (versão corrigida pelo editor).

Dynamic artificial neural network for electricity market prices forecast

This paper presents an artificial neural network applied to the forecasting of electricity market prices, with the special feature of being dynamic. The dynamism is verified at two different levels. The first level is characterized as a re-training of the network in every iteration, so that the artificial neural network can able to consider the most recent data at all times, and constantly adapt itself to the most recent happenings. The second level considers the adaptation of the neural network’s execution time depending on the circumstances of its use. The execution time adaptation is performed through the automatic adjustment of the amount of data considered for training the network. This is an advantageous and indispensable feature for this neural network’s integration in ALBidS (Adaptive Learning strategic Bidding System), a multi-agent system that has the purpose of providing decision support to the market negotiating players of MASCEM (Multi-Agent Simulator of Competitive Electricity Markets).

Self-optimization for dynamic scheduling in manufacturing systems

Scheduling is a critical function that is present throughout many industries and applications. A great need exists for developing scheduling approaches that can be applied to a number of different scheduling problems with significant impact on performance of business organizations. A challenge is emerging in the design of scheduling support systems for manufacturing environments where dynamic adaptation and optimization become increasingly important. In this paper, we describe a Self-Optimizing Mechanism for Scheduling System through Nature Inspired Optimization Techniques (NIT).

A hybrid intelligent system for distributed dynamic scheduling

This chapter addresses the resolution of dynamic scheduling by means of meta-heuristic and multi-agent systems. Scheduling is an important aspect of automation in manufacturing systems. Several contributions have been proposed, but the problem is far from being solved satisfactorily, especially if scheduling concerns real world applications. The proposed multi-agent scheduling system assumes the existence of several resource agents (which are decision-making entities based on meta-heuristics) distributed inside the manufacturing system that interact with other agents in order to obtain optimal or near-optimal global performances.