Analysis of a Three-Phase LSPMM by Numerical Method

Line-start permanent magnet motor (LSPMM) is a very attractive alternative to replace induction motors due to its very high efficiency and constant speed operation with load variations. However, designing this kind of hybrid motor is hard work and requires a good understanding of motor behavior. The calculation of load angle is an important step in motor design and can not be neglected. This paper uses the finite element method to show a simple methodology to calculate the load angle of a three-phase LSPMM combining the dynamic and steady-state simulations. The methodology is used to analyze a three-phase LSPMM.

Recruitment of single human low-threshold motor units with increasing loads at different muscle lengths

We investigated the recruitment behaviour of low threshold motor units in flexor digitorum superficialis by altering two biomechanical constraints: the load against which the muscle worked and the initial muscle length. The load was increased using isotonic (low load), loaded dynamic (intermediate load) and isometric (high load) contractions in two studies. The initial muscle position reflected resting muscle length in series A, and a longer length with digit III fully extended in series B. Intramuscular EMG was recorded from 48 single motor units in 10 experiments on five healthy subjects, 21 units in series A and,27 in series B, while subjects performed ramp up, hold and ramp down contractions. Increasing the load on the muscle decreased the force, displacement and firing rate of single motor units at recruitment at shorter muscle lengths (P < 0.001, dependent t-test). At longer muscle lengths this recruitment pattern was observed between loaded dynamic and isotonic contractions, but not between isometric and loaded dynamic contractions. Thus, the recruitment properties of single motor units in human flexor digitorum superficialis are sensitive to changes in both imposed external loads and the initial length of the muscle. (C) 2003 Elsevier Ltd. All rights reserved.

Sucrose Fermentation by Brazilian Ethanol Production Yeasts in Media Containing Structurally Complex Nitrogen Sources

Four Saccharomyces cerevisiae Brazilian industrial ethanol production strains were grown, under shaken and static conditions, in media containing 22% (w/v) sucrose supplemented with nitrogen sources varying from a single ammonium salt (ammonium sulfate) to free amino acids (casamino acids) and peptides (peptone). Sucrose fermentations by Brazilian industrial ethanol production yeasts strains were strongly affected by both the structural complexity of the nitrogen source and the availability of oxygen. Data suggest that yeast strains vary in their response to the nitrogen source`s complex structure and to oxygen availability. In addition, the amount of trehalose produced could be correlated with the fermentation performance of the different yeasts, suggesting that efficient fuel ethanol production depends on finding conditions which are appropriate for a particular strain, considering demand and dependence on available nitrogen sources in the fermentation medium.

Impact of lung remodelling on respiratory mechanics in a model of severe allergic inflammation

We developed a model of severe allergic inflammation and investigated the impact of airway and lung parenchyma remodelling on in vivo and in vitro respiratory mechanics. BALB/c mice were sensitized and challenged with ovalbumin in severe allergic inflammation (SA) group. The control group (C) received saline using the same protocol. Light and electron microscopy showed eosinophil and neutrophil infiltration and fibrosis in airway and lung parenchyma, mucus gland hyperplasia, and airway smooth muscle hypertrophy and hyperplasia in SA group. These morphological changes led to in vivo (resistive and viscoelastic pressures, and static elastance) and in vitro (tissue elastance and resistance) lung mechanical alterations. Airway responsiveness to methacholine was markedly enhanced in SA as compared with C group. Additionally, IL-4, IL-5, and IL-13 levels in the bronchoalveolar lavage fluid were higher in SA group. In conclusion, this model of severe allergic lung inflammation enabled us to directly assess the role of airway and lung parenchyma inflammation and remodelling on respiratory mechanics. (C) 2007 Elsevier B.V. All rights reserved.

Cybertutor: a teaching tool in Dermatology

It was developed a teaching tool in Dermatology for undergraduate medical students, using an interactive website, the Cybertutor. Clinical cases, lectures and updated bibliography were selected. Photographies of dermatological lesions were taken from ambulatory patients. The topics of the lectures were based on the current curriculum of the Federal University of Rio Grande do Sul. The Cybertutor is a dynamic and modern teaching tool, allowing constant innovation.

The Hus1 homologue of Leishmania major encodes a nuclear protein that participates in DNA damage response

The protozoan parasite Leishmania presents a dynamic and plastic genome in which gene amplification and chromosome translocations are common phenomena. Such plasticity hints at the necessity of dependable genome maintenance pathways. Eukaryotic cells have evolved checkpoint control systems that recognize altered DNA structures and halt cell cycle progression allowing DNA repair to take place. In these cells, the PCNA-related heterotrimeric complex formed by the proteins Hus1, Rad9, and Rad1 is known to participate in the early steps of replicative stress sensing and signaling. Here we show that the Hus1 homolog of Leishmania major is a nuclear protein that improves the cell capability to cope with replicative stress. Overexpression of LmHus1 confers resistance to the genotoxic drugs hydroxyurea (HU) and methyl methanesulfonate (MMS) and resistance to HU correlates to reduced net DNA damage upon LmHus1 expression. (C) 2011 Elsevier B.V. All rights reserved.

Advances in application of climate prediction in agriculture

Agricultural ecosystems and their associated business and government systems are diverse and varied. They range from farms, to input supply businesses, to marketing and government policy systems, among others. These systems are dynamic and responsive to fluctuations in climate. Skill in climate prediction offers considerable opportunities to managers via its potential to realise system improvements (i.e. increased food production and profit and/or reduced risks). Realising these opportunities, however, is not straightforward as the forecasting skill is imperfect and approaches to applying the existing skill to management issues have not been developed and tested extensively. While there has been much written about impacts of climate variability, there has been relatively little done in relation to applying knowledge of climate predictions to modify actions ahead of likely impacts. However, a considerable body of effort in various parts of the world is now being focused on this issue of applying climate predictions to improve agricultural systems. In this paper, we outline the basis for climate prediction, with emphasis on the El Nino-Southern Oscillation phenomenon, and catalogue experiences at field, national and global scales in applying climate predictions to agriculture. These diverse experiences are synthesised to derive general lessons about approaches to applying climate prediction in agriculture. The case studies have been selected to represent a diversity of agricultural systems and scales of operation. They also represent the on-going activities of some of the key research and development groups in this field around the world. The case studies include applications at field/farm scale to dryland cropping systems in Australia, Zimbabwe, and Argentina. This spectrum covers resource-rich and resource-poor farming with motivations ranging from profit to food security. At national and global scale we consider possible applications of climate prediction in commodity forecasting (wheat in Australia) and examine implications on global wheat trade and price associated with global consequences of climate prediction. In cataloguing these experiences we note some general lessons. Foremost is the value of an interdisciplinary systems approach in connecting disciplinary Knowledge in a manner most suited to decision-makers. This approach often includes scenario analysis based oil simulation with credible models as a key aspect of the learning process. Interaction among researchers, analysts and decision-makers is vital in the development of effective applications all of the players learn. Issues associated with balance between information demand and supply as well as appreciation of awareness limitations of decision-makers, analysts, and scientists are highlighted. It is argued that understanding and communicating decision risks is one of the keys to successful applications of climate prediction. We consider that advances of the future will be made by better connecting agricultural scientists and practitioners with the science of climate prediction. Professions involved in decision making must take a proactive role in the development of climate forecasts if the design and use of climate predictions are to reach their full potential. (C) 2001 Elsevier Science Ltd. All rights reserved.

A reforma do Estado no contexto latino-americano: coment??rios sobre alguns impasses e poss??veis desdobramentos

O artigo se constitui em uma reflex??o sobre a reforma do Estado nos pa??ses latinoamericanos, em especial no que se refere a seu aparato institucional ??? a "m??quina administrativa". Identificadas como reformas de 2a gera????o (as de 1a s??o as do reajuste macroecon??mico), o conjunto dos esfor??os modernizadores busca a regenera????o das institui????es p??blicas duramente afetadas pela crise econ??mico-financeira dos anos 80, e/ou at?? mesmo a cria????o de novas institui????es, visando a constru????o de um Estado forte, apoiado em uma economia din??mica e competitiva, da qual ?? parceiro e regulador, al??m de desempenhar de forma adequada suas fun????es cl??ssicas. O autor discute as quest??es institucionais e sociais (accountability, governance, conex??es entre as reformas econ??mico-financeiras), a mudan??a de paradigma do papel do Estado e os desafios a serem enfrentados.

Sensor-driven agenda for intelligent home care of the elderly

The exponential increase of home-bound persons who live alone and are in need of continuous monitoring requires new solutions to current problems. Most of these cases present illnesses such as motor or psychological disabilities that deprive of a normal living. Common events such as forgetfulness or falls are quite common and have to be prevented or dealt with. This paper introduces a platform to guide and assist these persons (mostly elderly people) by providing multisensory monitoring and intelligent assistance. The platform operates at three levels. The lower level, denominated ‘‘Data acquisition and processing’’performs the usual tasks of a monitoring system, collecting and processing data from the sensors for the purpose of detecting and tracking humans. The aim is to identify their activities in an intermediate level called ‘‘activity detection’’. The upper level, ‘‘Scheduling and decision-making’’, consists of a scheduler which provides warnings, schedules events in an intelligent manner and serves as an interface to the rest of the platform. The idea is to use mobile and static sensors performing constant monitoring of the user and his/her environment, providing a safe environment and an immediate response to severe problems. A case study on elderly fall detection in a nursery home bedroom demonstrates the usefulness of the proposal.

Adaptive deblocking filter for transform domain Wyner-Ziv video coding

Wyner-Ziv (WZ) video coding is a particular case of distributed video coding, the recent video coding paradigm based on the Slepian-Wolf and Wyner-Ziv theorems that exploits the source correlation at the decoder and not at the encoder as in predictive video coding. Although many improvements have been done over the last years, the performance of the state-of-the-art WZ video codecs still did not reach the performance of state-of-the-art predictive video codecs, especially for high and complex motion video content. This is also true in terms of subjective image quality mainly because of a considerable amount of blocking artefacts present in the decoded WZ video frames. This paper proposes an adaptive deblocking filter to improve both the subjective and objective qualities of the WZ frames in a transform domain WZ video codec. The proposed filter is an adaptation of the advanced deblocking filter defined in the H.264/AVC (advanced video coding) standard to a WZ video codec. The results obtained confirm the subjective quality improvement and objective quality gains that can go up to 0.63 dB in the overall for sequences with high motion content when large group of pictures are used.

Matrix Converter-Based Unified Power-Flow Controllers: Advanced Direct Power Control Method

This paper presents a direct power control (DPC) for three-phase matrix converters operating as unified power flow controllers (UPFCs). Matrix converters (MCs) allow the direct ac/ac power conversion without dc energy storage links; therefore, the MC-based UPFC (MC-UPFC) has reduced volume and cost, reduced capacitor power losses, together with higher reliability. Theoretical principles of direct power control (DPC) based on sliding mode control techniques are established for an MC-UPFC dynamic model including the input filter. As a result, line active and reactive power, together with ac supply reactive power, can be directly controlled by selecting an appropriate matrix converter switching state guaranteeing good steady-state and dynamic responses. Experimental results of DPC controllers for MC-UPFC show decoupled active and reactive power control, zero steady-state tracking error, and fast response times. Compared to an MC-UPFC using active and reactive power linear controllers based on a modified Venturini high-frequency PWM modulator, the experimental results of the advanced DPC-MC guarantee faster responses without overshoot and no steady-state error, presenting no cross-coupling in dynamic and steady-state responses.

Intelligent Bio-Inspired system for manufacturing scheduling under uncertainties

A novel approach to scheduling resolution by combining Autonomic Computing (AC), Multi-Agent Systems (MAS), Case-based Reasoning (CBR), and Bio-Inspired Optimization Techniques (BIT) will be described. AC has emerged as a paradigm aiming at incorporating applications with a management structure similar to the central nervous system. The main intentions are to improve resource utilization and service quality. In this paper we envisage the use of MAS paradigm for supporting dynamic and distributed scheduling in Manufacturing Systems with AC properties, in order to reduce the complexity of managing manufacturing systems and human interference. The proposed CBR based Intelligent Scheduling System was evaluated under different dynamic manufacturing scenarios.

Metalearning in ALBidS: A Strategic Bidding System for electricity markets

Metalearning is a subfield of machine learning with special pro-pensity for dynamic and complex environments, from which it is difficult to extract predictable knowledge. The field of study of this work is the electricity market, which due to the restructuring that recently took place, became an especially complex and unpredictable environment, involving a large number of different entities, playing in a dynamic scene to obtain the best advantages and profits. This paper presents the development of a metalearner, applied to the decision support of electricity markets’ negotia-tion entities. The proposed metalearner takes advantage on several learning algorithms implemented in ALBidS, an adaptive learning system that pro-vides decision support to electricity markets’ participating players. Using the outputs of each different strategy as inputs, the metalearner creates its own output, considering each strategy with a different weight, depending on its individual quality of performance. The results of the proposed meth-od are studied and analyzed using MASCEM - a multi-agent electricity market simulator that models market players and simulates their operation in the market. This simulator provides the chance to test the metalearner in scenarios based on real electricity market´s data.

Self-optimizing through CBR learning

In this paper, we foresee the use of Multi-Agent Systems for supporting dynamic and distributed scheduling in Manufacturing Systems. We also envisage the use of Autonomic properties in order to reduce the complexity of managing systems and human interference. By combining Multi-Agent Systems, Autonomic Computing, and Nature Inspired Techniques we propose an approach for the resolution of dynamic scheduling problem, with Case-based Reasoning Learning capabilities. The objective is to permit a system to be able to automatically adopt/select a Meta-heuristic and respective parameterization considering scheduling characteristics. From the comparison of the obtained results with previous results, we conclude about the benefits of its use.

Autonomic computing for scheduling in manufacturing systems

We describe a novel approach to scheduling resolution by combining Autonomic Computing (AC), Multi-Agent Systems (MAS) and Nature Inspired Optimization Techniques (NIT). Autonomic Computing has emerged as paradigm aiming at embedding applications with a management structure similar to a central nervous system. A natural Autonomic Computing evolution in relation to Current Computing is to provide systems with Self-Managing ability with a minimum human interference. In this paper we envisage the use of Multi-Agent Systems paradigm for supporting dynamic and distributed scheduling in Manufacturing Systems with Autonomic properties, in order to reduce the complexity of managing systems and human interference. Additionally, we consider the resolution of realistic problems. The scheduling of a Cutting and Treatment Stainless Steel Sheet Line will be evaluated. Results show that proposed approach has advantages when compared with other scheduling systems.