Rational use of residential digesters for sewage treatment with Carbon Credits

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Biomimetic sensor based on 5,10,15,20-tetrakis(pentafluorophenyl)-21H,23H- porphyrin iron (III) chloride and MWCNT for selective detection of 2,4-D

Exploitation of the electronic properties of carbon nanotubes for the development of voltammetric and amperometric sensors to monitor analytes of environmental relevance has increased in recent years. This work reports the development of a biomimetic sensor based on a carbon paste modified with 5,10,15,20-tetrakis(pentafluorophenyl)-21H,23H-porphyrin iron (III) chloride (a biomimetic catalyst of the P450 enzyme) and multi-wall carbon nanotubes (MWCNT), for the sensitive and selective detection of the herbicide 2,4- dichlorophenoxyacetic acid (2,4-D). The sensor was evaluated using cyclic voltammetry and amperometry, for electrochemical characterization and quantification purposes, respectively. Amperometric analyses were carried out at -100 mV vs. Ag/AgCl(KClsat), using a 0.1 mol L-1 phosphate buffer solution at pH 6.0 as the support electrolyte. Under these optimized analytical conditions, the sensor showed a linear response between 9.9 × 10-6 and 1.4 × 10-4 mol L-1, a sensitivity of 1.8 × 104 (±429) μA L mol -1, and limits of detection and quantification of 2.1 × 10 -6 and 6.8 × 10-6 mol L-1, respectively. The incorporation of functionalized MWCNT in the carbon paste resulted in a 10-fold increase in the response, compared to that of the biomimetic sensor without MWCNT. In addition, the low applied potential (-100 mV) used to obtain high sensitivity also contributed to the excellent selectivity of the proposed sensor. The viability of the application of this sensor for analysis of soil samples was confirmed by satisfactory recovery values, with a mean of 96% and RSD of 2.1% (n = 3). © 2013 Elsevier B.V.

Development of an electrochemical sensor based on nanostructured hausmannite-type manganese oxide for detection of sodium ions

The preparation and electrochemical characterization of hausmannite-type manganese oxide to use as a sensing material for sodium ion is described. This paper reports a new via synthetic to obtain of the hausmannite-type manganese oxide and its application in the construction of modified electrode as a voltammetric sensor. The electrochemical activity of hausmannite-type manganese oxide is controlled by intercalation/deintercalation of the sodium ions within the oxide lattice. The detection is based on the measurement of anodic current generated by oxidation of MnIII-MnIV at electrode surface. The best electrochemical response was obtained for a sensor composition of 20% (w/w) hausmannite oxide in the paste, a TRIS buffer solution of pH 6.0-7.0 and a scan rate of 50 mV s-1. A sensitive linear voltammetric response for sodium ions was obtained in the concentration range of 2.01 × 10 -5-2.09 × 10-4 mol L-1 with a slope of 355 μA L mmol-1 and a detection limit of 7.50 × 10 -6 mol L-1 using cyclic voltammetry. The use of hausmannite has significantly improved the selectivity of the sensor compared to the birnessite-type manganese oxide modified electrode. Under the working conditions, the proposed method was successfully applied to determination of sodium ions in urine samples. © 2013 Elsevier B.V.

The dimensionality of ecological networks

How many dimensions (trait-axes) are required to predict whether two species interact? This unanswered question originated with the idea of ecological niches, and yet bears relevance today for understanding what determines network structure. Here, we analyse a set of 200 ecological networks, including food webs, antagonistic and mutualistic networks, and find that the number of dimensions needed to completely explain all interactions is small (< 10), with model selection favouring less than five. Using 18 high-quality webs including several species traits, we identify which traits contribute the most to explaining network structure. We show that accounting for a few traits dramatically improves our understanding of the structure of ecological networks. Matching traits for resources and consumers, for example, fruit size and bill gape, are the most successful combinations. These results link ecologically important species attributes to large-scale community structure. © 2013 Blackwell Publishing Ltd/CNRS.

Desenvolvimento de um nó de rede com diferentes interfaces de acordo com o padrão IEEE 1451 utilizando o processador nios II e o sistema operacional embarcado uclinux

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Projeto e implementação de um nodo sensor para aquisição de sinais de extensômetros em redes de sensores sem fio aplicado ao monitoramento de deformações em estruturas

Esta dissertação tem como objetivo principal propor um nodo (ou nó) sensor sem fio para ser utilizado em redes de sensores sem fio, em sistemas de aquisição de dados de extensômetros. O sistema de aquisição para os extensômetros é baseado na ponte de Wheatstone e de modo a permitir várias configurações de extensômetros. O processamento e a comunicação sem fio é realizada pelo ATmega128RFA1, composto por um microcontrolador e um transceiver Rádio-Frequência com o padrão Zigbee. O nodo foi projetado para garantir confiabilidade na aquisição de dados e ser totalmente controlado remotamente. Entre os parâmetros controláveis estão: o ganho do sinal e a taxa de amostragem. Além disso, o nodo possui recursos para efetuar o equilíbrio da ponte de Wheatstone automaticamente. A escolha de seus componentes, baseou-se em critérios relacionados ao consumo de energia do mesmo e ao custo. Foi concebida uma placa de circuito impresso (PCI) para o nodo, e sobre ela foram realizadas estimativas sobre o consumo de energia e valor agregado do protótipo, com o objetivo de analisar a sua viabilidade. Além do projeto do nodo sensor, o trabalho apresenta a proposta de integração do mesmo em uma rede de sensores sem fio (RSSF), incluindo a sugestão do hardware complementar e desenvolvimentos dos softwares. Para os testes do nodo sensor, foi construido experimentalmente um transdutor de força.

Green-Markov models - new optimization strategies: a case study for user allocation in co-channel macro/femto networks

ABSTRACT: The femtocell concept aims to combine fixed-line broadband access with mobile telephony using the deployment of low-cost, low-power third and fourth generation base stations in the subscribers' homes. While the self-configuration of femtocells is a plus, it can limit the quality of service (QoS) for the users and reduce the efficiency of the network, based on outdated allocation parameters such as signal power level. To this end, this paper presents a proposal for optimized allocation of users on a co-channel macro-femto network, that enable self-configuration and public access, aiming to maximize the quality of service of applications and using more efficiently the available energy, seeking the concept of Green networking. Thus, when the user needs to connect to make a voice or a data call, the mobile phone has to decide which network to connect, using the information of number of connections, the QoS parameters (packet loss and throughput) and the signal power level of each network. For this purpose, the system is modeled as a Markov Decision Process, which is formulated to obtain an optimal policy that can be applied on the mobile phone. The policy created is flexible, allowing different analyzes, and adaptive to the specific characteristics defined by the telephone company. The results show that compared to traditional QoS approaches, the policy proposed here can improve energy efficiency by up to 10%.

Decay of interspecific avian flock networks along a disturbance gradient in Amazonia

Our understanding of how anthropogenic habitat change shapes species interactions is in its infancy. This is in large part because analytical approaches such as network theory have only recently been applied to characterize complex community dynamics. Network models are a powerful tool for quantifying how ecological interactions are affected by habitat modification because they provide metrics that quantify community structure and function. Here, we examine how large-scale habitat alteration has affected ecological interactions among mixed-species flocking birds in Amazonian rainforest. These flocks provide a model system for investigating how habitat heterogeneity influences non-trophic interactions and the subsequent social structure of forest-dependent mixed-species bird flocks. We analyse 21 flock interaction networks throughout a mosaic of primary forest, fragments of varying sizes and secondary forest (SF) at the Biological Dynamics of Forest Fragments Project in central Amazonian Brazil. Habitat type had a strong effect on network structure at the levels of both species and flock. Frequency of associations among species, as summarized by weighted degree, declined with increasing levels of forest fragmentation and SF. At the flock level, clustering coefficients and overall attendance positively correlated with mean vegetation height, indicating a strong effect of habitat structure on flock cohesion and stability. Prior research has shown that trophic interactions are often resilient to large-scale changes in habitat structure because species are ecologically redundant. By contrast, our results suggest that behavioural interactions and the structure of non-trophic networks are highly sensitive to environmental change. Thus, a more nuanced, system-by-system approach may be needed when thinking about the resiliency of ecological networks.

DEVELOPMENT OF A BIOMIMETIC SENSOR MODIFIED WITH HEMIN AND GRAPHENE OXIDE FOR MONITORING OF CARBOFURAN IN FOOD

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

Determination of carbofuran and diuron in FIA system using electrochemical sensor modified with organometallic complexes and graphene oxide

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

Tool condition monitoring of aluminum oxide grinding wheel in dressing operation using acoustic emission and neural networks

The grinding operation gives workpieces their final finish, minimizing surface roughness through the interaction between the abrasive grains of a tool (grinding wheel) and the workpiece. However, excessive grinding wheel wear due to friction renders the tool unsuitable for further use, thus requiring the dressing operation to remove and/or sharpen the cutting edges of the worn grains to render them reusable. The purpose of this study was to monitor the dressing operation using the acoustic emission (AE) signal and statistics derived from this signal, classifying the grinding wheel as sharp or dull by means of artificial neural networks. An aluminum oxide wheel installed on a surface grinding machine, a signal acquisition system, and a single-point dresser were used in the experiments. Tests were performed varying overlap ratios and dressing depths. The root mean square values and two additional statistics were calculated based on the raw AE data. A multilayer perceptron neural network was used with the Levenberg-Marquardt learning algorithm, whose inputs were the aforementioned statistics. The results indicate that this method was successful in classifying the conditions of the grinding wheel in the dressing process, identifying the tool as "sharp''(with cutting capacity) or "dull''(with loss of cutting capacity), thus reducing the time and cost of the operation and minimizing excessive removal of abrasive material from the grinding wheel.

Ultrasonic sensor signals and optimum path forest classifier for the microstructural characterization of thermally-aged inconel 625 alloy

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Structure-semantics interplay in complex networks and its effects on the predictability of similarity in texts

The classification of texts has become a major endeavor with so much electronic material available, for it is an essential task in several applications, including search engines and information retrieval. There are different ways to define similarity for grouping similar texts into clusters, as the concept of similarity may depend on the purpose of the task. For instance, in topic extraction similar texts mean those within the same semantic field, whereas in author recognition stylistic features should be considered. In this study, we introduce ways to classify texts employing concepts of complex networks, which may be able to capture syntactic, semantic and even pragmatic features. The interplay between various metrics of the complex networks is analyzed with three applications, namely identification of machine translation (MT) systems, evaluation of quality of machine translated texts and authorship recognition. We shall show that topological features of the networks representing texts can enhance the ability to identify MT systems in particular cases. For evaluating the quality of MT texts, on the other hand, high correlation was obtained with methods capable of capturing the semantics. This was expected because the golden standards used are themselves based on word co-occurrence. Notwithstanding, the Katz similarity, which involves semantic and structure in the comparison of texts, achieved the highest correlation with the NIST measurement, indicating that in some cases the combination of both approaches can improve the ability to quantify quality in MT. In authorship recognition, again the topological features were relevant in some contexts, though for the books and authors analyzed good results were obtained with semantic features as well. Because hybrid approaches encompassing semantic and topological features have not been extensively used, we believe that the methodology proposed here may be useful to enhance text classification considerably, as it combines well-established strategies. (c) 2012 Elsevier B.V. All rights reserved.

A Low Consumption Real Time Environmental Monitoring System for Smart Cities based on ZigBee Wireless Sensor Network

Nowadays, there is an increasing interest in wireless sensor networks (WSN) for environmental monitoring systems because it can be used to improve the quality of life and living conditions are becoming a major concern to people. This paper describes the design and development of a real time monitoring system based on ZigBee WSN characterized by a lower energy consumption, low cost, reduced dimensions and fast adaptation to the network tree topology. The developed system encompasses an optimized sensing process about environmental parameters, low rate transmission from sensor nodes to the gateway, packet parsing and data storing in a remote database and real time visualization through a web server.

Development and characterization of a distributed measurement system for the evaluation of voltage quality in electric power networks

The research activity carried out during the PhD course in Electrical Engineering belongs to the branch of electric and electronic measurements. The main subject of the present thesis is a distributed measurement system to be installed in Medium Voltage power networks, as well as the method developed to analyze data acquired by the measurement system itself and to monitor power quality. In chapter 2 the increasing interest towards power quality in electrical systems is illustrated, by reporting the international research activity inherent to the problem and the relevant standards and guidelines emitted. The aspect of the quality of voltage provided by utilities and influenced by customers in the various points of a network came out only in recent years, in particular as a consequence of the energy market liberalization. Usually, the concept of quality of the delivered energy has been associated mostly to its continuity. Hence the reliability was the main characteristic to be ensured for power systems. Nowadays, the number and duration of interruptions are the “quality indicators” commonly perceived by most customers; for this reason, a short section is dedicated also to network reliability and its regulation. In this contest it should be noted that although the measurement system developed during the research activity belongs to the field of power quality evaluation systems, the information registered in real time by its remote stations can be used to improve the system reliability too. Given the vast scenario of power quality degrading phenomena that usually can occur in distribution networks, the study has been focused on electromagnetic transients affecting line voltages. The outcome of such a study has been the design and realization of a distributed measurement system which continuously monitor the phase signals in different points of a network, detect the occurrence of transients superposed to the fundamental steady state component and register the time of occurrence of such events. The data set is finally used to locate the source of the transient disturbance propagating along the network lines. Most of the oscillatory transients affecting line voltages are due to faults occurring in any point of the distribution system and have to be seen before protection equipment intervention. An important conclusion is that the method can improve the monitored network reliability, since the knowledge of the location of a fault allows the energy manager to reduce as much as possible both the area of the network to be disconnected for protection purposes and the time spent by technical staff to recover the abnormal condition and/or the damage. The part of the thesis presenting the results of such a study and activity is structured as follows: chapter 3 deals with the propagation of electromagnetic transients in power systems by defining characteristics and causes of the phenomena and briefly reporting the theory and approaches used to study transients propagation. Then the state of the art concerning methods to detect and locate faults in distribution networks is presented. Finally the attention is paid on the particular technique adopted for the same purpose during the thesis, and the methods developed on the basis of such approach. Chapter 4 reports the configuration of the distribution networks on which the fault location method has been applied by means of simulations as well as the results obtained case by case. In this way the performance featured by the location procedure firstly in ideal then in realistic operating conditions are tested. In chapter 5 the measurement system designed to implement the transients detection and fault location method is presented. The hardware belonging to the measurement chain of every acquisition channel in remote stations is described. Then, the global measurement system is characterized by considering the non ideal aspects of each device that can concur to the final combined uncertainty on the estimated position of the fault in the network under test. Finally, such parameter is computed according to the Guide to the Expression of Uncertainty in Measurements, by means of a numeric procedure. In the last chapter a device is described that has been designed and realized during the PhD activity aiming at substituting the commercial capacitive voltage divider belonging to the conditioning block of the measurement chain. Such a study has been carried out aiming at providing an alternative to the used transducer that could feature equivalent performance and lower cost. In this way, the economical impact of the investment associated to the whole measurement system would be significantly reduced, making the method application much more feasible.