Heat stress adaptation in hyperthermophiles: bosynthesis of inositol-containing compatible solutes

Dissertation presented to obtain the Ph.D. degree in Biochemistry

Electrospun Polyaniline-Reduced Graphene Oxide Composite Nanofibers Based High Sensitive Ammonia Gas Sensor

Ammonia is an important gas in many power plants and industrial processes so its detection is of extreme importance in environmental monitoring and process control due to its high toxicity. Ammonia’s threshold limit is 25 ppm and the exposure time limit is 8 h, however exposure to 35 ppm is only secure for 10 min. In this work a brief introduction to ammonia aspects are presented, like its physical and chemical properties, the dangers in its manipulation, its ways of production and its sources. The application areas in which ammonia gas detection is important and needed are also referred: environmental gas analysis (e.g. intense farming), automotive-, chemical- and medical industries. In order to monitor ammonia gas in these different areas there are some requirements that must be attended. These requirements determine the choice of sensor and, therefore, several types of sensors with different characteristics were developed, like metal oxides, surface acoustic wave-, catalytic-, and optical sensors, indirect gas analyzers, and conducting polymers. All the sensors types are described, but more attention will be given to polyaniline (PANI), particularly to its characteristics, syntheses, chemical doping processes, deposition methods, transduction modes, and its adhesion to inorganic materials. Besides this, short descriptions of PANI nanostructures, the use of electrospinning in the formation of nanofibers/microfibers, and graphene and its characteristics are included. The created sensor is an instrument that tries to achieve a goal of the medical community in the control of the breath’s ammonia levels being an easy and non-invasive method for diagnostic of kidney malfunction and/or gastric ulcers. For that the device should be capable to detect different levels of ammonia gas concentrations. So, in the present work an ammonia gas sensor was developed using a conductive polymer composite which was immobilized on a carbon transducer surface. The experiments were targeted to ammonia measurements at ppb level. Ammonia gas measurements were carried out in the concentration range from 1 ppb to 500 ppb. A commercial substrate was used; screen-printed carbon electrodes. After adequate surface pre-treatment of the substrate, its electrodes were covered by a nanofibrous polymeric composite. The conducting polyaniline doped with sulfuric acid (H2SO4) was blended with reduced graphene oxide (RGO) obtained by wet chemical synthesis. This composite formed the basis for the formation of nanofibers by electrospinning. Nanofibers will increase the sensitivity of the sensing material. The electrospun PANI-RGO fibers were placed on the substrate and then dried at ambient temperature. Amperometric measurements were performed at different ammonia gas concentrations (1 to 500 ppb). The I-V characteristics were registered and some interfering gases were studied (NO2, ethanol, and acetone). The gas samples were prepared in a custom setup and were diluted with dry nitrogen gas. Electrospun nanofibers of PANI-RGO composite demonstrated an enhancement in NH3 gas detection when comparing with only electrospun PANI nanofibers. Was visible higher range of resistance at concentrations from 1 to 500 ppb. It was also observed that the sensor had stable, reproducible and recoverable properties. Moreover, it had better response and recovery times. The new sensing material of the developed sensor demonstrated to be a good candidate for ammonia gas determination.

Desenvolvimento de um oxímetro de pulso e de um sensor de medição de pressão arterial

Dissertação para obtenção do Grau de Mestre em Engenharia Biomédica

Replication vs erasure coding in data centric storage for wireless sensor networks

In-network storage of data in wireless sensor networks contributes to reduce the communications inside the network and to favor data aggregation. In this paper, we consider the use of n out of m codes and data dispersal in combination to in-network storage. In particular, we provide an abstract model of in-network storage to show how n out of m codes can be used, and we discuss how this can be achieved in five cases of study. We also define a model aimed at evaluating the probability of correct data encoding and decoding, we exploit this model and simulations to show how, in the cases of study, the parameters of the n out of m codes and the network should be configured in order to achieve correct data coding and decoding with high probability.

Distributed Forest Fire Monitoring Using Wireless Sensor Networks

Disaster management is one of the most relevant application fields of wireless sensor networks. In this application, the role of the sensor network usually consists of obtaining a representation or a model of a physical phenomenon spreading through the affected area. In this work we focus on forest firefighting operations, proposing three fully distributed ways for approximating the actual shape of the fire. In the simplest approach, a circular burnt area is assumed around each node that has detected the fire and the union of these circles gives the overall fire’s shape. However, as this approach makes an intensive use of the wireless sensor network resources, we have proposed to incorporate two in-network aggregation techniques, which do not require considering the complete set of fire detections. The first technique models the fire by means of a complex shape composed of multiple convex hulls representing different burning areas, while the second technique uses a set of arbitrary polygons. Performance evaluation of realistic fire models on computer simulations reveals that the method based on arbitrary polygons obtains an improvement of 20% in terms of accuracy of the fire shape approximation, reducing the overhead in-network resources to 10% in the best case.

Chitosan/AuNPs Modified Graphene Electrochemical Sensor for Label-Free Human Chorionic Gonadotropin Detection

A new immunosensor is presented for human chorionic gonadotropin (hCG), made by electrodepositing chitosan/gold-nanoparticles over graphene screen-printed electrode (SPE). The antibody was covalently bound to CS via its Fc-terminal. The assembly was controlled by electrochemical Impedance Spectroscopy (EIS) and followed by Fourier Transformed Infrared (FTIR). The hCG-immunosensor displayed linear response against the logarithm-hCG concentration for 0.1–25 ng/mL with limit of detection of 0.016 ng/mL. High selectivity was observed in blank urine and successful detection of hCG was also achieved in spiked samples of real urine from pregnant woman. The immunosensor showed good detection capability, simplicity of fabrication, low-cost, high sensitivity and selectivity.

A microscope for the data center

Nowadays, data centers are large energy consumers and the trend for next years is expected to increase further, considering the growth in the order of cloud services. A large portion of this power consumption is due to the control of physical parameters of the data center (such as temperature and humidity). However, these physical parameters are tightly coupled with computations, and even more so in upcoming data centers, where the location of workloads can vary substantially due, for example, to workloads being moved in the cloud infrastructure hosted in the data center. Therefore, managing the physical and compute infrastructure of a large data center is an embodiment of a Cyber-Physical System (CPS). In this paper, we describe a data collection and distribution architecture that enables gathering physical parameters of a large data center at a very high temporal and spatial resolution of the sensor measurements. We think this is an important characteristic to enable more accurate heat-flow models of the data center and with them, find opportunities to optimize energy consumptions. Having a high-resolution picture of the data center conditions, also enables minimizing local hot-spots, perform more accurate predictive maintenance (failures in all infrastructure equipments can be more promptly detected) and more accurate billing. We detail this architecture and define the structure of the underlying messaging system that is used to collect and distribute the data. Finally, we show the results of a preliminary study of a typical data center radio environment.

A molecularly imprinted sensor for sensitive detection of 8-hydroxy-2'-deoxyguanosine (8-OHdG) oxidative stress biomarker

6th Graduate Student Symposium on Molecular Imprinting

A biomimetic sensor for monitoring oxidative stress biomarker in point-of-care

1st ASPIC International Congress

Uma abordagem a sistemas de crescimento celular apical: síntese de um sensor para iões citosólicos de potássio

Dissertação para obtenção do Grau de Mestre em Bioorgânica

Distributed Sensing of Fluid Dynamic Phenomena with the XDense Sensor Grid Network

IEEE International Conference on Cyber Physical Systems, Networks and Applications (CPSNA'15), Hong Kong, China.

Biomimetic Sensor Potentiometric System for Doxycycline Antibiotic Using a Molecularly Imprinted Polymer as an Artificial Recognition Element

Molecular imprinting is a useful technique for the preparation of functional materials with molecular recognition properties. A Biomimetic Sensor Potentiometric System was developed for assessment of doxycycline (DOX) antibiotic. The molecularly imprinted polymer (MIP) was synthesized by using doxycycline as a template molecule, methacrylic acid (MAA) and/or acrylamide (AA) as a functional monomer and ethylene glycol dimethacrylat (EGDMA) as a cross-linking agent. The sensing elements were fabricated by the inclusion of DOX imprinted polymers in polyvinyl chloride (PVC) matrix. The sensors showed a high selectivity and a sensitive response to the template in aqueous system. Electrochemical evaluation of these sensors under static (batch) mode of operation reveals near-Nernstian response. MIP/MAA membrane sensor was incorporated in flow-through cells and used as detectors for flow injection analysis (FIA) of DOX. The method has the requisite accuracy, sensitivity and precision to assay DOX in tablets and biological fluids.

A new biomimetic sensor for detecting carnitine, a potential biomarker in ovarian cancer

1st ASPIC International Congress

Metabolic flux analysis of neural cell metabolism in primary cultures

Dissertation presented to obtain the Ph.D degree in Biochemistry, Neuroscience

XDense: A Dense Grid Sensor Network for Distributed Feature Extraction

XXXIII Simpósio Brasileiro de Redes de Computadores e Sistemas Distribuídos (SBRC 2015). 15 to 19, May, 2015, III Workshop de Comunicação em Sistemas Embarcados Críticos. Vitória, Brasil.