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Two series of 5’-triphenylmethyl (trityl)-substituted thymidine derivatives were synthesized and tested against Leishmania infantum axenic promastigotes and amastigotes. Several of these compounds show significant antileishmanial activity, with IC50 values in the low micromolar range. Among these, 3’-O-(isoleucylisoleucyl)- 5’-O-(3,3,3-triphenylpropanoyl)thymidine displays particularly good activity against intracellular amastigotes. Assays performed to characterize the nature of parasite cell death in the presence of the tritylthymidines indicated significant alterations in mitochondrial transmembrane potential, an increase in superoxide concentrations, and also significant decreases in DNA degradation during the cell death process. Results point to the mitochondrial nuclease LiEndoG as a target for the action of this family of compounds.

Binding at the interface: We tested the inhibitory activity of a set of peptide sequences derived from an a-helix of the dimeric trypanothione reductase from Leishmania infantum. Replacement of a glutamic acid residue with a lysine promoted monomer dissociation and enzyme inhibition.

The Linearized Auto-Localization (LAL) algorithm estimates the position of beacon nodes in Local Positioning Systems (LPSs), using only the distance measurements to a mobile node whose position is also unknown. The LAL algorithm calculates the inter-beacon distances, used for the estimation of the beacons’ positions, from the linearized trilateration equations. In this paper we propose a method to estimate the propagation of the errors of the inter-beacon distances obtained with the LAL algorithm, based on a first order Taylor approximation of the equations. Since the method depends on such approximation, a confidence parameter τ is defined to measure the reliability of the estimated error. Field evaluations showed that by applying this information to an improved weighted-based auto-localization algorithm (WLAL), the standard deviation of the inter-beacon distances can be improved by more than 30% on average with respect to the original LAL method.

We present a new method to accurately locate persons indoors by fusing inertial navigation system (INS) techniques with active RFID technology. A foot-mounted inertial measuring units (IMUs)-based position estimation method, is aided by the received signal strengths (RSSs) obtained from several active RFID tags placed at known locations in a building. In contrast to other authors that integrate IMUs and RSS with a loose Kalman filter (KF)-based coupling (by using the residuals of inertial- and RSS-calculated positions), we present a tight KF-based INS/RFID integration, using the residuals between the INS-predicted reader-to-tag ranges and the ranges derived from a generic RSS path-loss model. Our approach also includes other drift reduction methods such as zero velocity updates (ZUPTs) at foot stance detections, zero angular-rate updates (ZARUs) when the user is motionless, and heading corrections using magnetometers. A complementary extended Kalman filter (EKF), throughout its 15-element error state vector, compensates the position, velocity and attitude errors of the INS solution, as well as IMU biases. This methodology is valid for any kind of motion (forward, lateral or backward walk, at different speeds), and does not require an offline calibration for the user gait. The integrated INS+RFID methodology eliminates the typical drift of IMU-alone solutions (approximately 1% of the total traveled distance), resulting in typical positioning errors along the walking path (no matter its length) of approximately 1.5 m.

This paper studies the problem of determining the position of beacon nodes in Local Positioning Systems (LPSs), for which there are no inter-beacon distance measurements available and neither the mobile node nor any of the stationary nodes have positioning or odometry information. The common solution is implemented using a mobile node capable of measuring its distance to the stationary beacon nodes within a sensing radius. Many authors have implemented heuristic methods based on optimization algorithms to solve the problem. However, such methods require a good initial estimation of the node positions in order to find the correct solution. In this paper we present a new method to calculate the inter-beacon distances, and hence the beacons positions, based in the linearization of the trilateration equations into a closed-form solution which does not require any approximate initial estimation. The simulations and field evaluations show a good estimation of the beacon node positions.

The main problem of pedestrian dead-reckoning (PDR) using only a body-attached inertial measurement unit is the accumulation of heading errors. The heading provided by magnetometers in indoor buildings is in general not reliable and therefore it is commonly not used. Recently, a new method was proposed called heuristic drift elimination (HDE) that minimises the heading error when navigating in buildings. It assumes that the majority of buildings have their corridors parallel to each other, or they intersect at right angles, and consequently most of the time the person walks along a straight path with a heading constrained to one of the four possible directions. In this article we study the performance of HDE-based methods in complex buildings, i.e. with pathways also oriented at 45°, long curved corridors, and wide areas where non-oriented motion is possible. We explain how the performance of the original HDE method can be deteriorated in complex buildings, and also, how severe errors can appear in the case of false matches with the building's dominant directions. Although magnetic compassing indoors has a chaotic behaviour, in this article we analyse large data-sets in order to study the potential use that magnetic compassing has to estimate the absolute yaw angle of a walking person. Apart from these analysis, this article also proposes an improved HDE method called Magnetically-aided Improved Heuristic Drift Elimination (MiHDE), that is implemented over a PDR framework that uses foot-mounted inertial navigation with an extended Kalman filter (EKF). The EKF is fed with the MiHDE-estimated orientation error, gyro bias corrections, as well as the confidence over that corrections. We experimentally evaluated the performance of the proposed MiHDE-based PDR method, comparing it with the original HDE implementation. Results show that both methods perform very well in ideal orthogonal narrow-corridor buildings, and MiHDE outperforms HDE for non-ideal trajectories (e.g. c

The localization of persons in indoor environments is nowadays an open problem. There are partial solutions based on the deployment of a network of sensors (Local Positioning Systems or LPS). Other solutions only require the installation of an inertial sensor on the person’s body (Pedestrian Dead-Reckoning or PDR). PDR solutions integrate the signals coming from an Inertial Measurement Unit (IMU), which usually contains 3 accelerometers and 3 gyroscopes. The main problem of PDR is the accumulation of positioning errors due to the drift caused by the noise in the sensors. This paper presents a PDR solution that incorporates a drift correction method based on detecting the access ramps usually found in buildings. The ramp correction method is implemented over a PDR framework that uses an Inertial Navigation algorithm (INS) and an IMU attached to the person’s foot. Unlike other approaches that use external sensors to correct the drift error, we only use one IMU on the foot. To detect a ramp, the slope of the terrain on which the user is walking, and the change in height sensed when moving forward, are estimated from the IMU. After detection, the ramp is checked for association with one of the existing in a database. For each associated ramp, a position correction is fed into the Kalman Filter in order to refine the INS-PDR solution. Drift-free localization is achieved with positioning errors below 2 meters for 1,000-meter-long routes in a building with a few ramps.

These days, mass-produced vehicles benefit from research on Intelligent Transportation System (ITS). One prime example of ITS is vehicle Cruise Control (CC), which allows it to maintain a pre-defined reference speed, to economize on fuel or energy consumption, to avoid speeding fines, or to focus all of the driver’s attention on the steering of the vehicle. However, achieving efficient Cruise Control is not easy in roads or urban streets where sudden changes of the speed limit can happen, due to the presence of unexpected obstacles or maintenance work, causing, in inattentive drivers, traffic accidents. In this communication we present a new Infrastructure to Vehicles (I2V) communication and control system for intelligent speed control, which is based upon Radio Frequency Identification (RFID) technology for identification of traffic signals on the road, and high accuracy vehicle speed measurement with a Hall effect-based sensor. A fuzzy logic controller, based on sensor fusion of the information provided by the I2V infrastructure, allows the efficient adaptation of the speed of the vehicle to the circumstances of the road. The performance of the system is checked empirically, with promising results.

The estimation of the position of a person in a building is a must for creating Intelligent Spaces. State-of-theart Local Positioning Systems (LPS) require a complex sensornetwork infrastructure to locate with enough accuracy and coverage. Alternatively, Inertial Measuring Units (IMU) can be used to estimate the movement of a person; a methodology that is called Pedestrian Dead-Reckoning (PDR). In this paper, we describe and implement a Kalman-based framework, called INSEKF- ZUPT (IEZ), to estimate the position and attitude of a person while walking. IEZ makes use of an Extended Kalman filter (EKF), an INS mechanization algorithm, a Zero Velocity Update (ZUPT) methodology, as well as, a stance detection algorithm. As the IEZ methodology is not able to estimate the heading and its drift (non-observable variables), then several methods are used for heading drift reduction: ZARU, HDR and Compass. The main contribution of the paper is the integration of the heading drift reduction algorithms into a Kalman-based IEZ platform, which represents an extended PDR methodology (IEZ+) valid for operation in indoor spaces with local magnetic disturbances. The IEZ+ PDR methodology was tested in several simulated and real indoor scenarios with a low-performance IMU mounted on the foot. The positioning errors were about 1% of the total travelled distance, which are good figures if compared with other works using IMUs of higher performance.

The received signal strength (RSS) of radiofrequency signals emitted from beacons placed at known locations in an environment, can be used by a local positioning system (LPS) to estimate the location of a person or a mobile object. In indoor environments, interference, multipath propagation of RF signals, and the presence of obstacles and people, lead to a complex spatial distribution of the RSS, which is inaccurately described by simple parametric models. In this work, we present a Bayesian method for an indoor RFID location system which uses an observation model based in Gaussian processes (GPs) nonparametric regression to represent the environment-specific RSS distributions for the individual RFID tags. The experimental results in an indoor environment demonstrate the effectiveness of GPs in order to increase positioning accuracy.

Nucleósidos modificados para el tratamiento de infecciones por Leishmania. Compuestos derivados de nucleósidos y su uso para el tratamiento de enfermedades infecciosas causadas por Leishmania. Además la invención se refiere a las composiciones farmacéuticas que contienen dichos compuestos.

In machining, natural oscillations, and elastic, gravitational or temperature deformations, are still a problem to guarantee the quality of fabricated parts. In this paper we present an optical measurement system designed to track and localize in 3D a reference retro-reflector close to the machine-tool’s drill. The complete system and its components are described in detail. Several tests, some static (including impacts and rotations) and others dynamic (by executing linear and circular trajectories), were performed on two different machine tools. It has been integrated, for the first time, a laser tracking system into the position control loop of a machine-tool. Results indicate that oscillations and deformations close to the tool can be estimated with micrometric resolution and a bandwidth from 0 to more than 100 Hz. Therefore this sensor opens the possibility for on-line compensation of oscillations and deformations.

The navigation of autonomous guided vehicles (AGV’s) in industrial environments is often controlled by positioning systems based on landmarks or artificial beacons. In these systems, the position of an AGV navigating in an interior space is determined by the calculation of its relative distance to beacons, whose location is known in advance. A fundamental design problem associated with landmark navigation systems consists of determining the optimal location of the minimum number of beacons necessary to achieve a desired level of accuracy and reliability. A local search procedure coupled with a diversification strategy is developed for this problem. We provide comparisons with an earlier solution method based on genetic algorithms and show that our proposed procedure finds better designs in a fraction of the computational time employed by the genetic algorithm.

[EN] The invention relates to a method enabling selective biomechanical cancellation of pathological tremor. Canceling focuses on the characteristic frequencies of the tremor and has no negative effect upon the voluntary movement of the patient. It can be used in different types of tremors and situations by automatically adapting to the specific characteristics of the tremor signal. The whole system takes the shape of an upper limb orthosis and, therefore, it can be used in a series of day-to-day activities. The characteristics of commercial products are more restricted: they are limited to concrete activities (feeding), they apply non-selective biomechanical action and cannot therefore adapt to the concrete characteristics of the tremor or patient, they are desktop devices and are thus not portable., [ES] Se trata de un método que permite la cancelaci6n biomecénica selectiva del temblor patológico. La acción de cancelación se centra en las frecuencias características del temblor sin incidir negativamente en el movimiento voluntario del paciente. Es valido para distintos tipos de temblor y para distintas situaciones al adaptar automáticamente la acción de cancelación de acuerdo con las características particulares de la señal temblorosa. Todo et sistema adquiere la forma de una ortésis de miembro superior por lo que es aplicable a un conjunto amplio de actividades diarias. Las características de los productos comerciales son mucho más restringidas: están limitados a actividades concretas (alimentación), aplican una acción biomecánica no selectiva por lo que no se pueden adaptar a las características concretas del tipo de temblor o del paciente, son dispositivos de sobremesa por lo que no son portátiles.

Máquina-herramienta con regulación de posición en continuo (ver figura en archivo de texto adjunto). La máquina-herramienta incorpora un sistema de regulación en continuo que permite controlar la posición del cabezal (3) de la máquina durante todo su desplazamiento y, con los datos de desviación obtenidos, actuar inmediatamente sobre los servomotores de la máquina, llevando el cabezal (3) a la posición correcta. El sistema de regulación está compuesto por un emisor láser (6), un primer espejo deflector (14), un segundo espejo deflector (15) y un prisma retrorreflector (5), montado sobre el cabezal (3) de la máquina. Cada uno de los dos espejos deflectores (14) y (15) incorpora su propio motor (17), (18) que permite variar su orientación, de forma independiente, en función de las desviaciones detectadas para el cabezal (3). El sistema se complementa con un receptor de interferómetro (11), un sistema de detección de posición (16) y un sistema de adquisición y tratamiento de datos (19), con la particularidad de que todos los elementos del sistema, excepto el prisma retrorreflector (5), se encuentran dispuestos en una plataforma (4) fija a la estructura o soporte (1) de la máquina, con el fin de reducir las masas suspendidas sobre los elementos móviles y, por tanto, las inercias indeseadas.

This paper presents a new ultrasonic sensor for 3D co-ordinate estimation, which has been especially designed to localize and sketch findings after they are extracted by archaeologists. Classical tasks at paleo-archaeological excavations are: measuring position with metric tapes, drawing a sketch of found object, and introducing all information into a database manually; operations that are not efficient and prone to errors. The positioning system we have designed allows simultaneous characterization of several findings (absolute position, shape, size and orientation) using as a tool a wireless 2-metre-long rod, whose lower tip has to be placed on the object under study. The system contains two ultrasonic emitters and employs the time-of-flight (TOF) the ultrasonic signal takes to reach several fixed receivers, and a robust trilateration algorithm to determine the position of the rod tip with 10 mm accuracy. Object position and contour information are automatically transferred to a database in a central computer avoiding manual typewriting. Airflow is the main source of positioning error in outdoor environments, so a strategy based on a differential emitter fixed at a known position is used, which permits to cancel out the effects of uniform air motion.

We present a computer vision system for measuring the weight of gobs during a glass-forming process, and a control strategy to automatically correct any weight deviation from a given set point. The system is based on a reliable gob area estimation using image-processing algorithms. A monochrome CCD high-resolution camera and a photodetector for synchronizing acquisition are used for registering gob images. Assuming that the gob has symmetry of revolution about the vertical axis, the proposed system estimates the weight of gobs with accuracy better than ±0.75%. A learning weight control strategy is proposed based on a proportional-integral (PI)-repetitive control scheme. The weight deviation from a set point is used as a control signal to adjust the glass flow into the feeder. This regulation scheme enables effective weight control, canceling mid- and long-term effects. The tracking error of ±1.5% means a reduction of 40% when compared with a traditional PI controller.

El objetivo de esta tesis consiste en el estudio y realización de un sistema automático de detección y localización de frutos en árboles mediante telemetría láser. El trabajo se divide en cinco unidades diferenciadas. En la primera se realiza un introducción al problema de la detección de frutos en entornos agrícolas y se revisan diversos trabajos realizados por otros investigadores en este campo. La segunda parte trata del proceso de captación de imágenes utilizando un telémetro láser, estudiando sus características y modelando su comportamiento. El tercer apartado se centra en la restauración de las imágenes captadas, definiendo un índice para evaluar la calidad de la restauración y presentando una nueva técnica adaptativa de restauración. La cuarta unidad presenta una estrategia de reconocimiento y localización de objetos esféricos que a partir de una pareja de imágenes de distancia y reflectancia genera una lista de hipótesis incluyendo la posición tridimensional de cada objeto detectado. Finalmente se realiza una evaluación conjunta del sistema desarrollado, mediante esta se determinan las principales cualidades del sistema así como los aspectos limitantes

This paper presents an analysis of the main sources of error in a 3D-positioning system using ultrasonic waves, coming to different technical improvements. We suggest a new processing algorithm that will overcome the main sources of error encountered in practice. Comparing with existing processing methods, the proposed technique shows an error reduction by a factor of 20, making the system especially robust against outliers measurements.