SMART, a simple modular architecture research tool: Identification of signaling domains

Accurate multiple alignments of 86 domains that occur in signaling proteins have been constructed and used to provide a Web-based tool (SMART: simple modular architecture research tool) that allows rapid identification and annotation of signaling domain sequences. The majority of signaling proteins are multidomain in character with a considerable variety of domain combinations known. Comparison with established databases showed that 25% of our domain set could not be deduced from SwissProt and 41% could not be annotated by Pfam. SMART is able to determine the modular architectures of single sequences or genomes; application to the entire yeast genome revealed that at least 6.7% of its genes contain one or more signaling domains, approximately 350 greater than previously annotated. The process of constructing SMART predicted (i) novel domain homologues in unexpected locations such as band 4.1-homologous domains in focal adhesion kinases; (ii) previously unknown domain families, including a citron-homology domain; (iii) putative functions of domain families after identification of additional family members, for example, a ubiquitin-binding role for ubiquitin-associated domains (UBA); (iv) cellular roles for proteins, such predicted DEATH domains in netrin receptors further implicating these molecules in axonal guidance; (v) signaling domains in known disease genes such as SPRY domains in both marenostrin/pyrin and Midline 1; (vi) domains in unexpected phylogenetic contexts such as diacylglycerol kinase homologues in yeast and bacteria; and (vii) likely protein misclassifications exemplified by a predicted pleckstrin homology domain in a Candida albicans protein, previously described as an integrin.

A few autoreactive cells in an autoimmune infiltrate control a vast population of nonspecific cells: a tale of smart bombs and the infantry.

Inflammatory infiltrates in tissue-specific autoimmune disease comprise a collection of T cells with specificity for an antigen in the target organ. These specific cells recruit a population of nonspecific T cells and macrophages. The rare tissue-specific T cells in the infiltrate have the capacity to regulate both the influx and the efflux of cells from the tissue. Administration of an altered peptide ligand for the specific T cell which triggers autoimmunity can lead to the regression of the entire inflammatory ensemble in a few hours. Interleukin 4 is a critical cytokine involved in the regression of the inflammatory infiltrate.

Molecular approaches to smart materials via interface recognition and conformationally switchable cavitands

In this thesis the molecular level design of functional materials and systems is reported. In the first part, tetraphosphonate cavitand (Tiiii) recognition properties towards amino acids are studied both in the solid state, through single crystal X-ray diffraction, and in solution, via NMR and ITC experiments. The complexation ability of these supramolecular receptors is then applied to the detection of biologically remarkable N-methylated amino acids and peptides using complex dynamic emulsions-based sensing platforms. In the second part, a general supramolecular approach for surface decoration with single-molecule magnets (SMMs) is presented. The self-assembly of SMMs is achieved through the formation of a multiple hydrogen bonds architecture (UPy-NaPy complexation). Finally we explore the possibility to impart auxetic behavior to polymeric material through the introduction of conformationally switchable monomers, namely tetraquinoxaline cavitands (QxCav). Their interconversion from a closed vase conformation to an extended kite form is studied first in solution, then in polymeric matrixes via pH and tensile stimuli by UV-Vis spectroscopy.

Short-term Load Forecasting Using Neural Network For Future Smart Grid Application

Short-term load forecasting of power system has been a classic problem for a long time. Not merely it has been researched extensively and intensively, but also a variety of forecasting methods has been raised. This thesis outlines some aspects and functions of smart meter. It also presents different policies and current statuses as well as future projects and objectives of SG development in several countries. Then the thesis compares main aspects about latest products of smart meter from different companies. Lastly, three types of prediction models are established in MATLAB to emulate the functions of smart grid in the short-term load forecasting, and then their results are compared and analyzed in terms of accuracy. For this thesis, more variables such as dew point temperature are used in the Neural Network model to achieve more accuracy for better short-term load forecasting results.

Measurement of wide frequency range structural microvibrations with a pocket digital camera and sub-pixel techniques

Analysis of vibrations and displacements is a hot topic in structural engineering. Although there is a wide variety of methods for vibration analysis, direct measurement of displacements in the mid and high frequency range is not well solved and accurate devices tend to be very expensive. Low-cost systems can be achieved by applying adequate image processing algorithms. In this paper, we propose the use of a commercial pocket digital camera, which is able to register more than 420 frames per second (fps) at low resolution, for accurate measuring of small vibrations and displacements. The method is based on tracking elliptical targets with sub-pixel accuracy. Our proposal is demonstrated at a 10 m distance with a spatial resolution of 0.15 mm. A practical application over a simple structure is given, and the main parameters of an attenuated movement of a steel column after an impulsive impact are determined with a spatial accuracy of 4 µm.

Guidance of robot arms using depth data from RGB-D camera

Image Based Visual Servoing (IBVS) is a robotic control scheme based on vision. This scheme uses only the visual information obtained from a camera to guide a robot from any robot pose to a desired one. However, IBVS requires the estimation of different parameters that cannot be obtained directly from the image. These parameters range from the intrinsic camera parameters (which can be obtained from a previous camera calibration), to the measured distance on the optical axis between the camera and visual features, it is the depth. This paper presents a comparative study of the performance of D-IBVS estimating the depth from three different ways using a low cost RGB-D sensor like Kinect. The visual servoing system has been developed over ROS (Robot Operating System), which is a meta-operating system for robots. The experiments prove that the computation of the depth value for each visual feature improves the system performance.

Portable 3D laser-camera calibration system with color fusion for SLAM

Paper submitted to the 43rd International Symposium on Robotics (ISR2012), Taipei, Taiwan, Aug. 29-31, 2012.

Measurement of wide frequency range structural microvibrations with a pocket digital camera and sub-pixel techniques

Analysis of vibrations and displacements is a hot topic in structural engineering. Although there is a wide variety of methods for vibration analysis, direct measurement of displacements in the mid and high frequency range is not well solved and accurate devices tend to be very expensive. Low-cost systems can be achieved by applying adequate image processing algorithms. In this paper, we propose the use of a commercial pocket digital camera, which is able to register more than 420 frames per second (fps) at low resolution, for accurate measuring of small vibrations and displacements. The method is based on tracking elliptical targets with sub-pixel accuracy. Our proposal is demonstrated at a 10 m distance with a spatial resolution of 0.15 mm. A practical application over a simple structure is given, and the main parameters of an attenuated movement of a steel column after an impulsive impact are determined with a spatial accuracy of 4 µm.

Parallel Computational Intelligence-Based Multi-Camera Surveillance System

In this work, we present a multi-camera surveillance system based on the use of self-organizing neural networks to represent events on video. The system processes several tasks in parallel using GPUs (graphic processor units). It addresses multiple vision tasks at various levels, such as segmentation, representation or characterization, analysis and monitoring of the movement. These features allow the construction of a robust representation of the environment and interpret the behavior of mobile agents in the scene. It is also necessary to integrate the vision module into a global system that operates in a complex environment by receiving images from multiple acquisition devices at video frequency. Offering relevant information to higher level systems, monitoring and making decisions in real time, it must accomplish a set of requirements, such as: time constraints, high availability, robustness, high processing speed and re-configurability. We have built a system able to represent and analyze the motion in video acquired by a multi-camera network and to process multi-source data in parallel on a multi-GPU architecture.

Conversion of a digital camera into a non-contact colorimeter for use in stone cultural heritage: The application case to Spanish granites

In this study, a digital CMOS camera was calibrated for use as a non-contact colorimeter for measuring the color of granite artworks. The low chroma values of the granite, which yield similar stimulation of the three color channels of the camera, proved to be the most challenging aspect of the task. The appropriate parameters for converting the device-dependent RGB color space into a device-independent color space were established. For this purpose, the color of a large number of Munsell samples (corresponding to the previously defined color gamut of granite) was measured with a digital camera and with a spectrophotometer (reference instrument). The color data were then compared using the CIELAB color formulae. The best correlations between measurements were obtained when the camera works to 10-bits and the spectrophotometric measures in SCI mode. Finally, the calibrated instrument was used successfully to measure the color of six commercial varieties of Spanish granite.

Monitoring and Prevention the Smart Cities

Nowadays, the intensive use of Technology Information (TI) provide solutions to problems of the high population density, energy conservation and cities management. This produces a newest concept of the city, Smart City. But the inclusion of TI in the city brings associated new problems, specifically the generation of electromagnetic fields from the available and new technological infrastructures installed in the city that did not exist before. This new scenario produces a negative effect on a particular group of the society, as are the group of persons with electromagnetic hypersensitivity pathology. In this work we propose a system that would allow you to detect and prevent the continuous exposure to such electromagnetic fields, without the need to include more devices or infrastructure which would only worsen these effects. Through the use of the architecture itself and Smart City services, it is possible to infer the necessary knowledge to know the situation of the EMF radiation and thus allow users to avoid the areas of greatest conflict. This knowledge, not only allows us to get EMF current map of the city, but also allows you to generate predictions and detect future risk situations.

Smart Sentinel: Monitoring and Prevention System in the Smart Cities

Today, faced with the constant rise of the Smart cities around the world, there is an exponential increase of the use and deployment of information technologies in the cities. The intensive use of Information Technology (IT) in these ecosystems facilitates and improves the quality of life of citizens, but in these digital communities coexist individuals whose health is affected developing or increasing diseases such as electromagnetic hypersensitivity. In this paper we present a monitoring, detection and prevention system to help this group, through which it is reported the rates of electromagnetic radiation in certain areas, based on the information that the own Smart City gives us. This work provides a perfect platform for the generation of predictive models for detection of future states of risk for humans.

Disposable electrochromic polyaniline sensor based on a redox response using a conventional camera: A first approach to handheld analysis

We present a disposable optical sensor for Ascorbic Acid (AA). It uses a polyaniline based electrochromic sensing film that undergoes a color change when exposed to solutions of ascorbic acid at pH 3.0. The color is monitored by a conventional digital camera working with the hue (H) color coordinate. The electrochromic film was deposited on an Indium Tin Oxide (ITO) electrode by cyclic voltammetry and then characterized by atomic force microscopy, electrochemical and spectroscopic techniques. An estimation of the initial rate of H, as ΔH/Δt, is used as the analytical parameter and resulted in the following logarithmic relationship: ΔH/Δt = 0.029 log[AA] + 0.14, with a limit of detection of 17 μM. The relative standard deviation when using the same membrane 5 times was 7.4% for the blank, and 2.6% (for n = 3) on exposure to ascorbic acid in 160 μM concentration. The sensor is disposable and its applicability to pharmaceutical analysis was demonstrated. This configuration can be extended for future handheld configurations.

Using a RGB-D camera for 6DoF SLAM

This paper presents a method for fast calculation of the egomotion done by a robot using visual features. The method is part of a complete system for automatic map building and Simultaneous Localization and Mapping (SLAM). The method uses optical flow in order to determine if the robot has done a movement. If so, some visual features which do not accomplish several criteria (like intersection, unicity, etc,) are deleted, and then the egomotion is calculated. We use a state-of-the-art algorithm (TORO) in order to rectify the map and solve the SLAM problem. The proposed method provides better efficiency that other current methods.