Agronomic performance of 27 cocoa progenies and plant selection based on productivity, self-compatibility and disease resistance

The objective of the present work was to evaluate 27 progenies of cocoa crosses considering the agronomic traits and select F1 plants within superior crosses. The experiment was installed in March 2005, in the Experimental Station Joaquim Bahiana (ESJOB), in Itajuipe, Bahia. The area of the experiment is of approximately 3 ha, with a total of 3240 plants. Thirteen evaluations of vegetative brooms, five of cushion brooms and 15 of number of pods per plant were accomplished. Thirty pollinations were made for each selected plant to test for self-compatibility. The production, based on the number of pods per plant, and resistance to witches´ broom indicated CEPEC 94 x CCN 10, RB 39 x CCN 51 and CCN 10 x VB 1151 as superior progenies. All selections tested were self-compatible. The analyses of progenies and individual tree data, associated to visual field observations, allowed the selection of 17 plants which were included in a network of regional tests to determine the phenotypic stability.

Effect of neutralization and cross-linking on the thermal degradation of chitosan electrospun membranes

Thermal degradation of as electrospun chitosan membranes and samples subsequently treated with ethanol and cross-linked with glutaraldehyde (GA) have been studied by thermogravimetry (TG) coupled with an infrared spectrometer (FTIR). The influence of the electrospinning process and cross-linking in the electrospun chitosan thermal stability was evaluated. Up to three degradation steps were observed in the TG data, corresponding to water dehydration reaction at temperatures below 100 ºC, loss of side groups formed between the amine groups of chitosan and trifluoroacetic acid between 150 – 270 ºC and chitosan thermal degradation that starts around 250 ºC and goes up to 400 ºC. The Kissinger model was employed to evaluate the activation energies of the electrospun membranes during isothermal experiments and revealed that thermal degradation activation energy increases for the samples processed by electrospinning and subsequent neutralization and cross-linking treatments with respect to the neat chitosan powder.

Remote Patient Monitoring Based on ZigBee: Lessons from a Real-World Deployment

AIM: This work presents detailed experimental performance results from tests executed in the hospital environment for Health Monitoring for All (HM4All), a remote vital signs monitoring system based on a ZigBee® (ZigBee Alliance, San Ramon, CA) body sensor network (BSN). MATERIALS AND METHODS: Tests involved the use of six electrocardiogram (ECG) sensors operating in two different modes: the ECG mode involved the transmission of ECG waveform data and heart rate (HR) values to the ZigBee coordinator, whereas the HR mode included only the transmission of HR values. In the absence of hidden nodes, a non-beacon-enabled star network composed of sensing devices working on ECG mode kept the delivery ratio (DR) at 100%. RESULTS: When the network topology was changed to a 2-hop tree, the performance degraded slightly, resulting in an average DR of 98.56%. Although these performance outcomes may seem satisfactory, further investigation demonstrated that individual sensing devices went through transitory periods with low DR. Other tests have shown that ZigBee BSNs are highly susceptible to collisions owing to hidden nodes. Nevertheless, these tests have also shown that these networks can achieve high reliability if the amount of traffic is kept low. Contrary to what is typically shown in scientific articles and in manufacturers' documentation, the test outcomes presented in this article include temporal graphs of the DR achieved by each wireless sensor device. CONCLUSIONS: The test procedure and the approach used to represent its outcomes, which allow the identification of undesirable transitory periods of low reliability due to contention between devices, constitute the main contribution of this work.

Effect of cylindrical filler aggregation on the electrical conductivity of composites

This work reports on the effect of carbon nanotube aggregation on the electrical conductivity and other network properties of polymer/carbon nanotube composites by modeling the carbon nanotubes as hard-core cylinders. It is shown that the conductivity decreases for increasing filler aggregation, and that this effect is more significant for higher cylinder volume fractions. It is also demonstrated, for volume fractions at which the giant component is present, that increasing the fraction of cylinders within clusters leads to a break of the giant component and the formation of a set of finite clusters. The decrease of the giant component with the increase of the fraction of cylinders within the cluster can be related to a decrease of the spanning probability due to a decrease of the number of cylinders between the clusters. Finally, it is demonstrated that the effect of aggregation can be understood by employing the network theory.

Network dynamics in scientific knowledge acquisition: an analysis in three public universities in the state of Bahia

This paper aims to cast some light on the dynamics of knowledge networks in developing countries by analyzing the scientific production of the largest university in the Northeast of Brazil and its influence on some of the remaining regional research institutions in the state of Bahia. Using a methodology test to be employed in a larger project, the Universidade Federal da Bahia (UFBA) (Federal University of Bahia), the Universidade do Estado da Bahia (Uneb) (State of Bahia University) and the Universidade Estadual de Santa Cruz (Uesc)'s (Santa Cruz State University) scientific productions are discussed in one of their most traditionally expressive sectors in academic production - namely, the field of chemistry, using social network analysis of co-authorship networks to investigate the existence of small world phenomena and the importance of these phenomena in research performance in these three universities. The results already obtained through this research bring to light data of considerable interest concerning the scientific production in unconsolidated research universities. It shows the important participation of the UFBA network in the composition of the other two public universities research networks, indicating a possible occurrence of small world phenomena in the UFBA and Uesc networks, as well as the importance of individual researchers in consolidating research networks in peripheral universities. The article also hints that the methodology employed appears to be adequate insofar as scientific production may be used as a proxy for scientific knowledge.

Sistema de contagem de tráfego e classificação automática de veículos, em tempo real e sem fios

Esta tese tem por objectivo o desenho e avaliação de um sistema de contagem e classificação de veículos automóveis em tempo-real e sem fios. Pretende, também, ser uma alternativa aos actuais equipamentos, muito intrusivos nas vias rodoviárias. Esta tese inclui um estudo sobre as comunicações sem fios adequadas a uma rede de equipamentos sensores rodoviários, um estudo sobre a utilização do campo magnético como meio físico de detecção e contagem de veículos e um estudo sobre a autonomia energética dos equipamentos inseridos na via, com recurso, entre outros, à energia solar. O projecto realizado no âmbito desta tese incorpora, entre outros, a digitalização em tempo real da assinatura magnética deixada pela passagem de um veículo, no campo magnético da Terra, o respectivo envio para servidor via rádio e WAN, Wide Area Network, e o desenvolvimento de software tendo por base a pilha de protocolos ZigBee. Foram desenvolvidas aplicações para o equipamento sensor, para o coordenador, para o painel de controlo e para a biblioteca de Interface de um futuro servidor aplicacional. O software desenvolvido para o equipamento sensor incorpora ciclos de detecção e digitalização, com pausas de adormecimento de baixo consumo, e a activação das comunicações rádio durante a fase de envio, assegurando assim uma estratégia de poupança energética. Os resultados obtidos confirmam a viabilidade desta tecnologia para a detecção e contagem de veículos, assim como para a captura de assinatura usando magnetoresistências. Permitiram ainda verificar o alcance das comunicações sem fios com equipamento sensor embebido no asfalto e confirmar o modelo de cálculo da superfície do painel solar bem como o modelo de consumo energético do equipamento sensor.

Design of a sea-level tsunami detection network for the Gulf of Cadiz

The devastating impact of the Sumatra tsunami of 26 December 2004, raised the question for scientists of how to forecast a tsunami threat. In 2005, the IOC-UNESCO XXIII assembly decided to implement a global tsunami warning system to cover the regions that were not yet protected, namely the Indian Ocean, the Caribbean and the North East Atlantic, the Mediterranean and connected seas (the NEAM region). Within NEAM, the Gulf of Cadiz is the more sensitive area, with an important record of devastating historical events. The objective of this paper is to present a preliminary design for a reliable tsunami detection network for the Gulf of Cadiz, based on a network of sea-level observatories. The tsunamigenic potential of this region has been revised in order to define the active tectonic structures. Tsunami hydrodynamic modeling and GIS technology have been used to identify the appropriate locations for the minimum number of sea-level stations. Results show that 3 tsunameters are required as the minimum number of stations necessary to assure an acceptable protection to the large coastal population in the Gulf of Cadiz. In addition, 29 tide gauge stations could be necessary to fully assess the effects of a tsunami along the affected coasts of Portugal, Spain and Morocco.

Fabrication of Three-Dimensional Dendritic Ni-Co Films By Electrodeposition on Stainless Steel Substrates

Co-deposition of nickel and cobalt was carried out on austenitic stainless steel (AISI 304) substrates by imposing a square waveform current in the cathodic region. The innovative procedure applied in this work allows creating a stable, fully developed, and open porous three-dimensional (3D) dendritic structure, which can be used as electrode for redox supercapacitors. This study investigates in detail the influence of the applied current density on the morphology, mass, and chemical composition of the deposited Ni-Co films and the resulting 3D porous network dendritic structure. The morphology and the physicochemical composition were studied by scanning electron microscopy (SEM), energy dispersive X-ray spectroscopy (EDS) and X-ray diffraction (W). The electrochemical behavior of the materials was evaluated by cyclic voltammetry (CV). The results highlight the mechanism involved in the coelectrodeposition process and how the lower limit current density tailors the film composition and morphology, as well as its electrochemical activity.

Evaluation of intermolecular interactions in thioxanthone derivatives: substituent effect on crystal diversity

A family of 9H-thioxanthen-9-one derivatives and two precursors, 2-[(4-bromophenyl) sulfanyl]-5-nitrobenzoic acid and 2-[(4-aminophenyl) sulfanyl]-5-nitrobenzoic acid, were synthesized and studied in order to assess the role of the different substituent groups in determining the supramolecular motifs. From our results we can conclude that Etter's rules are obeyed: whenever present the -COOH head to head strong hydrogen bonding dimer, R-2(2)(8) synthon, prevails as the dominant interaction. As for -NH2, the best donor when present also follows the expected hierarchy, an NH center dot center dot center dot O(COOH) was formed in the acid precursor (2) and an NH center dot center dot center dot O(C=O) in the thioxanthone (4). The main role played by weaker hydrogen bonds such as CH center dot center dot center dot O, and other intermolecular interactions, pi-pi and Br center dot center dot center dot O, as well as the geometric restraints of packing patterns shows the energetic interplay governing crystal packing. A common feature is the relation between the p-p stacking and the unit cell dimensions. A new synthon notation, R`, introduced in this paper, refers to the possibility of accounting for intra- and intermolecular interactions into recognizable and recurring aggregate patterns.

Virtual power players demand response programs management based on locational marginal prices

Power systems have been suffering huge changes mainly due to the substantial increase of distributed generation and to the operation in competitive environments. Virtual power players can aggregate a diversity of players, namely generators and consumers, and a diversity of energy resources, including electricity generation based on several technologies, storage and demand response. Resource management gains an increasing relevance in this competitive context, while demand side active role provides managers with increased demand elasticity. This makes demand response use more interesting and flexible, giving rise to a wide range of new opportunities.This paper proposes a methodology for managing demand response programs in the scope of virtual power players. The proposed method is based on the calculation of locational marginal prices (LMP). The evaluation of the impact of using demand response specific programs on the LMP value supports the manager decision concerning demand response use. The proposed method has been computationally implemented and its application is illustrated in this paper using a 32 bus network with intensive use of distributed generation.

ANN-Based LMP forecasting in a distribution network with large penetration of DG

In recent years, power systems have experienced many changes in their paradigm. The introduction of new players in the management of distributed generation leads to the decentralization of control and decision-making, so that each player is able to play in the market environment. In the new context, it will be very relevant that aggregator players allow midsize, small and micro players to act in a competitive environment. In order to achieve their objectives, virtual power players and single players are required to optimize their energy resource management process. To achieve this, it is essential to have financial resources capable of providing access to appropriate decision support tools. As small players have difficulties in having access to such tools, it is necessary that these players can benefit from alternative methodologies to support their decisions. This paper presents a methodology, based on Artificial Neural Networks (ANN), and intended to support smaller players. In this case the present methodology uses a training set that is created using energy resource scheduling solutions obtained using a mixed-integer linear programming (MIP) approach as the reference optimization methodology. The trained network is used to obtain locational marginal prices in a distribution network. The main goal of the paper is to verify the accuracy of the ANN based approach. Moreover, the use of a single ANN is compared with the use of two or more ANN to forecast the locational marginal price.

Reentrant Phase Diagram of Network Fluids

We introduce a microscopic model for particles with dissimilar patches which displays an unconventional "pinched'' phase diagram, similar to the one predicted by Tlusty and Safran in the context of dipolar fluids [Science 290, 1328 (2000)]. The model-based on two types of patch interactions, which account, respectively, for chaining and branching of the self-assembled networks-is studied both numerically via Monte Carlo simulations and theoretically via first-order perturbation theory. The dense phase is rich in junctions, while the less-dense phase is rich in chain ends. The model provides a reference system for a deep understanding of the competition between condensation and self-assembly into equilibrium-polymer chains.

Study of distribution network demand response events in the Portuguese system

In competitive electricity markets with deep concerns for the efficiency level, demand response programs gain considerable significance. As demand response levels have decreased after the introduction of competition in the power industry, new approaches are required to take full advantage of demand response opportunities. Grid operators and utilities are taking new initiatives, recognizing the value of demand response for grid reliability and for the enhancement of organized spot markets’ efficiency. This paper proposes a methodology for the selection of the consumers that participate in an event, which is the responsibility of the Portuguese transmission network operator. The proposed method is intended to be applied in the interruptibility service implemented in Portugal, in convergence with Spain, in the context of the Iberian electricity market. This method is based on the calculation of locational marginal prices (LMP) which are used to support the decision concerning the consumers to be schedule for participation. The proposed method has been computationally implemented and its application is illustrated in this paper using a 937 bus distribution network with more than 20,000 consumers.

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).

Day-ahead resource scheduling in smart grids considering Vehicle-to-Grid and network constraints

Energy resource scheduling becomes increasingly important, as the use of distributed resources is intensified and massive gridable vehicle use is envisaged. The present paper proposes a methodology for dayahead energy resource scheduling for smart grids considering the intensive use of distributed generation and of gridable vehicles, usually referred as Vehicle- o-Grid (V2G). This method considers that the energy resources are managed by a Virtual Power Player (VPP) which established contracts with V2G owners. It takes into account these contracts, the user´s requirements subjected to the VPP, and several discharge price steps. Full AC power flow calculation included in the model allows taking into account network constraints. The influence of the successive day requirements on the day-ahead optimal solution is discussed and considered in the proposed model. A case study with a 33 bus distribution network and V2G is used to illustrate the good performance of the proposed method.