Genetic variation in foliar carbon isotope composition in relation to tree growth and foliar nitrogen concentration in clones of the F-1 hybrid between slash pine and Caribbean pine

The objectives of this study were: (1) to quantify the genetic variation in foliar carbon isotope composition (delta(13)C) of 122 clones of ca. 4-year-old F-1 hybrids between slash pine (Pinus elliottii Engelm var. elliottii) and Caribbean pine (Pinus caribaea var. hondurensis Barr.,et Golf.) grown at two field experimental sites with different water and nitrogen availability in southeast Queensland, Australia, in relation to tree growth and foliar nitrogen concentration (N-mass); and (2) to assess the potential of using delta(13)C measurements, in the foliage materials collected from the clone hedges at nursery and the 4-year-old tree canopies in the field, as an indirect index of tree water use efficiency for selecting elite F-1 hybrid pine clones with improved tree growth. There were significant differences in foliar delta(13)C between the nursery hedges and the 4-year-old tree canopies in the field, between the summer and winter seasons, between the two experimental sites, and between the upper outer and lower outer canopy positions sampled. This indicates that delta(13)C measurements in the foliage materials are significantly influenced by the sampling techniques and environmental conditions. Significant differences in foliar delta(13)C, at the upper outer canopy in both field experiments in summer and winter, were detected between the clones, and between the female parents of the clones. Clone means of tree height at age ca. 3 years were positively related to those of the upper outer canopy delta(13)C at both experimental sites in winter, but only for the wetter site in summer. There were positive, linear relationships between clone means of canopy delta(13)C and those of canopy N-mass, indicating that canopy photosynthetic capacity might be an important factor regulating the clonal variation in canopy delta(13)C. Significant correlations were found between clone means of canopy delta(13)C at both experimental sites in summer and winter, and between those at the upper outer and lower outer canopy positions. Mean clone delta(13)C for the nursery hedges was only positively related to mean clone stem diameter at 1.3 m height at age 3 years on the wetter site. The clone by site interaction for foliar delta(13)C at the upper outer canopy was significant only in summer. Overall, the relatively high genetic variance components for foliar delta(13)C and significant, positive correlations between clone means of foliar delta(13)C and tree growth have highlighted the potential of using foliar delta(13)C measurements for assisting in selection of the elite F-1 hybrid pine clones with improved tree growth. (C) 2002 Elsevier Science B.V. All rights reserved.

Key factors in working capital management in the Brazilian market

Many studies have been conducted in corporate finance regarding long-term investment and financing decisions. However, short-term asset investments play a significant role in the balance sheet of companies. Moreover, financial managers dedicate significant amounts of time and effort to the subject of working capital management, balancing current assets and liabilities. This paper provides insights regarding the key factors of working capital management by exploring the internal variables of a number of companies. This study used data from 2,976 Brazilian public companies from 2001 to 2008, and found that debt level, size and growth rate can affect the working capital management of companies.

A DC Voltage-Multiplier Circuit Working as a High-Voltage Pulse Generator

The intensive use of semiconductor devices enabled the development of a repetitive high-voltage pulse-generator topology from the dc voltage-multiplier (VM) concept. The proposed circuit is based on an odd VM-type circuit, where a number of dc capacitors share a common connection with different voltage ratings in each one, and the output voltage comes from a single capacitor. Standard VM rectifier and coupling diodes are used for charging the energy-storing capacitors, from an ac power supply, and two additional on/off semiconductors in each stage, to switch from the typical charging VM mode to a pulse mode with the dc energy-storing capacitors connected in series with the load. Results from a 2-kV experimental prototype with three stages, delivering a 10-mu s pulse with a 5-kHz repetition rate into a resistive load, are discussed. Additionally, the proposed circuit is compared against the solid-state Marx generator topology for the same peak input and output voltages.

A hybrid PSO-ANFIS approach for short-term wind power prediction in Portugal

The increased integration of wind power into the electric grid, as nowadays occurs in Portugal, poses new challenges due to its intermittency and volatility. Wind power prediction plays a key role in tackling these challenges. The contribution of this paper is to propose a new hybrid approach, combining particle swarm optimization and adaptive-network-based fuzzy inference system, for short-term wind power prediction in Portugal. Significant improvements regarding forecasting accuracy are attainable using the proposed approach, in comparison with the results obtained with five other approaches.

A hybrid approach to multi-agent decision-making

In the aftermath of a large-scale disaster, agents' decisions derive from self-interested (e.g. survival), common-good (e.g. victims' rescue) and teamwork (e.g. fire extinction) motivations. However, current decision-theoretic models are either purely individual or purely collective and find it difficult to deal with motivational attitudes; on the other hand, mental-state based models find it difficult to deal with uncertainty. We propose a hybrid, CvI-JI, approach that combines: i) collective 'versus' individual (CvI) decisions, founded on the Markov decision process (MDP) quantitative evaluation of joint-actions, and ii)joint-intentions (JI) formulation of teamwork, founded on the belief-desire-intention (BDI) architecture of general mental-state based reasoning. The CvI-JI evaluation explores the performance's improvement

Short-term electricity prices forecasting in a competitive market by a hybrid PSO-ANFIS approach

In this paper, a novel hybrid approach is proposed for electricity prices forecasting in a competitive market, considering a time horizon of 1 week. The proposed approach is based on the combination of particle swarm optimization and adaptive-network based fuzzy inference system. Results from a case study based on the electricity market of mainland Spain are presented. A thorough comparison is carried out, taking into account the results of previous publications, to demonstrate its effectiveness regarding forecasting accuracy and computation time. Finally, conclusions are duly drawn. (C) 2012 Elsevier Ltd. All rights reserved.

Human interaction with technology for working, communicating, and learning: advancements

The way humans interact with technology is undergoing a tremendous change. It is hard to imagine the lives we live today without the benefits of technology that we take for granted. Applying research in computer science, engineering, and information systems to non-technical descriptions of technology, such as human interaction, has shaped and continues to shape our lives. Human Interaction with Technology for Working, Communicating, and Learning: Advancements provides a framework for conceptual, theoretical, and applied research in regards to the relationship between technology and humans. This book is unique in the sense that it does not only cover technology, but also science, research, and the relationship between these fields and individuals' experience. This book is a must have for anyone interested in this research area, as it provides a voice for all users and a look into our future.

Occupational accidents among middle and high school students of the state of São Paulo, Brazil

OBJECTIVES: To estimate the prevalence of occupational injuries and identify their risk factors among students in two municipalities. METHODS: A cross-sectional survey was conducted in public schools of the municipalities of Santo Antonio do Pinhal and Monteiro Lobato, Brazil. A stratified probabilistic sample was drawn from public middle and high schools of the study municipalities. A total of 781 students aged 11 to 19 years participated in the study. Students attending middle and high school answered a comprehensive questionnaire on living and working conditions, as well as aspects of work injuries, and health conditions. Multiple logistic regression models were fitted to estimate risk factors of previous and present occupational injuries. RESULTS: Of 781 students, 604 previously had or currently have jobs and 47% reported previous injuries. Among current workers (n=555), 38% reported injuries on their current job. Risk factors for work injuries with statistically significant odds ratio >2.0 included attending evening school, working as a housekeeper, waiter or brickmaker, and with potentially dangerous machines. CONCLUSIONS: The study results reinforce the need of restricting adolescent work and support communities to implement social promotion programs.

Hybrid Wavelet-PSO-ANFIS Approach for Short-Term Electricity Prices Forecasting

A novel hybrid approach, combining wavelet transform, particle swarm optimization, and adaptive-network-based fuzzy inference system, is proposed in this paper for short-term electricity prices forecasting in a competitive market. Results from a case study based on the electricity market of mainland Spain are presented. A thorough comparison is carried out, taking into account the results of previous publications. Finally, conclusions are duly drawn.

Short-term electricity prices forecasting in a competitive market by a hybrid intelligent approach

In this paper, a hybrid intelligent approach is proposed for short-term electricity prices forecasting in a competitive market. The proposed approach is based on the wavelet transform and a hybrid of neural networks and fuzzy logic. Results from a case study based on the electricity market of mainland Spain are presented. A thorough comparison is carried out, taking into account the results of previous publications. Conclusions are duly drawn. (C) 2010 Elsevier Ltd. All rights reserved.

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.

Scheduling maintenance activities of electric power transmission networks using an hybrid constraint method

In this paper we present a Constraint Logic Programming (CLP) based model, and hybrid solving method for the Scheduling of Maintenance Activities in the Power Transmission Network. The model distinguishes from others not only because of its completeness but also by the way it models and solves the Electric Constraints. Specifically we present a efficient filtering algorithm for the Electrical Constraints. Furthermore, the solving method improves the pure CLP methods efficiency by integrating a type of Local Search technique with CLP. To test the approach we compare the method results with another method using a 24 bus network, which considerers 42 tasks and 24 maintenance periods.

Hybrid fuzzy Monte Carlo technique for reliability assessment in transmission power systems

This paper proposes a new methodology to reduce the probability of occurring states that cause load curtailment, while minimizing the involved costs to achieve that reduction. The methodology is supported by a hybrid method based on Fuzzy Set and Monte Carlo Simulation to catch both randomness and fuzziness of component outage parameters of transmission power system. The novelty of this research work consists in proposing two fundamentals approaches: 1) a global steady approach which deals with building the model of a faulted transmission power system aiming at minimizing the unavailability corresponding to each faulted component in transmission power system. This, results in the minimal global cost investment for the faulted components in a system states sample of the transmission network; 2) a dynamic iterative approach that checks individually the investment’s effect on the transmission network. A case study using the Reliability Test System (RTS) 1996 IEEE 24 Buses is presented to illustrate in detail the application of the proposed methodology.

Hybrid fuzzy Monte Carlo and logic programming model for distribution network reconfiguration in the presence of outages

This paper presents a methodology for distribution networks reconfiguration in outage presence in order to choose the reconfiguration that presents the lower power losses. The methodology is based on statistical failure and repair data of the distribution power system components and uses fuzzy-probabilistic modelling for system component outage parameters. Fuzzy membership functions of system component outage parameters are obtained by statistical records. A hybrid method of fuzzy set and Monte Carlo simulation based on the fuzzy-probabilistic models allows catching both randomness and fuzziness of component outage parameters. Once obtained the system states by Monte Carlo simulation, a logical programming algorithm is applied to get all possible reconfigurations for every system state. In order to evaluate the line flows and bus voltages and to identify if there is any overloading, and/or voltage violation a distribution power flow has been applied to select the feasible reconfiguration with lower power losses. To illustrate the application of the proposed methodology to a practical case, the paper includes a case study that considers a real distribution network.

Study on influence of the new CoDeSys V3.0 on the existing CoDeSys discipline of the Mind8 Engineering Center

CoDeSys "Controller Development Systems" is a development environment for programming in the area of automation controllers. It is an open source solution completely in line with the international industrial standard IEC 61131-3. All five programming languages for application programming as defined in IEC 61131-3 are available in the development environment. These features give professionals greater flexibility with regard to programming and allow control engineers have the ability to program for many different applications in the languages in which they feel most comfortable. Over 200 manufacturers of devices from different industrial sectors offer intelligent automation devices with a CoDeSys programming interface. In 2006, version 3 was released with new updates and tools. One of the great innovations of the new version of CoDeSys is object oriented programming. Object oriented programming (OOP) offers great advantages to the user for example when wanting to reuse existing parts of the application or when working on one application with several developers. For this reuse can be prepared a source code with several well known parts and this is automatically generated where necessary in a project, users can improve then the time/cost/quality management. Until now in version 2 it was necessary to have hardware interface called “Eni-Server” to have access to the generated XML code. Another of the novelties of the new version is a tool called Export PLCopenXML. This tool makes it possible to export the open XML code without the need of specific hardware. This type of code has own requisites to be able to comply with the standard described above. With XML code and with the knowledge how it works it is possible to do component-oriented development of machines with modular programming in an easy way. Eplan Engineering Center (EEC) is a software tool developed by Mind8 GmbH & Co. KG that allows configuring and generating automation projects. Therefore it uses modules of PLC code. The EEC already has a library to generate code for CoDeSys version 2. For version 3 and the constant innovation of drivers by manufacturers, it is necessary to implement a new library in this software. Therefore it is important to study the XML export to be then able to design any type of machine. The purpose of this master thesis is to study the new version of the CoDeSys XML taking into account all aspects and impact on the existing CoDeSys V2 models and libraries in the company Harro Höfliger Verpackungsmaschinen GmbH. For achieve this goal a small sample named “Traffic light” in CoDeSys version 2 will be done and then, using the tools of the new version it there will be a project with version 3 and also the EEC implementation for the automatically generated code.