Search

A quantitative study of the neutron environment in the Canfranc Underground Laboratory is being carried out, specially focused on the IGEX Dark Matter Experiment. A set of simulations based on GEANT4 and FLUKA codes together with data obtained in different experimental conditions in the IGEX set-up allow us to quantify the effect of neutrons in the low-energy spectrum of the IGEX-DM detector. As an intermediate result, we have estimated the flux of neutrons from radioactivity of the rock (4 × 10 − 6 n cm − 2 s − 1 ), the flux of muon-induced neutrons in the rock (2 × 10 − 9 n cm − 2 s − 1 ), and the rate of neutron production by muons in the lead shielding (4×10 − 9 n cm − 3 s − 1 ). As a first conclusion, 40 cm of neutron moderator should be enough to push far below the present level of sensitivity of the IGEX-DM detector, the contribution to the low energy region (from 4 to 10 keV) of neutrons coming from fission and ( α ,n) reactions in the rock. The contribution of muon-induced neutrons in the rock is also estimated to be far below the present level of sensitivity, so the residual background of IGEX-DM in the low energy region cannot be attributed to neutrons.

The status of the non-cryogenic dark matter searches at the Canfranc Underground Laboratory is presented. Latest results and future prospects of the IGEX-DM and ANAIS experiments are reported.

The amounts of fissile Pu and U in spent nuclear fuel are of primary concern to the safeguards community. In particular, there are issues when safeguards transitions from an item accountancy basis (such as fuel bundles) to a fissile material mass basis as occurs when spent fuel enters a reprocessing plant. Discrepancies occur because item accountancy requires estimating the content of fissile material using indirect techniques such as the fuel burn-up and item-level measurements of radiation emissions from fission by-products. Direct measurement of the fissile content by monitoring line emissions from fissile species themselves is impossible because the lines are much weaker than those emitted by shorter-lived isotopes in the fuel. The goal of this project is to develop a technique to directly measure these weaker lines despite the presence of overwhelming radiation from other isotopes. This is achieved by using gamma-ray mirrors as a narrow band-pass filter. The mirrors reflect only energies of interest toward a HPGe detector that is shielded from direct view of the spent fuel and its fierce emissions. This can significantly improve the reliability with which the mass of fissile material is tracked.

This paper proposes a Bayesian approach for minimizing the time of finding an object of uncertain location and dynamics using several moving sensing agents with constrained dynamics. The approach exploits twice the Bayesian theory: on one hand, it uses a Bayesian formulation of the objective functions that compare the constrained paths of the agents and on the other hand, a Bayesian optimization algorithm to solve the problem. By combining both elements, our approach handles successfully this complex problem, as illustrated by the results over different scenarios presented and statistically analyzed in the paper. Finally, the paper also discusses other formulations of the problem and compares the properties of our approach with others closely related.

The advances in micro- and nanofabrication technologies enable the preparation of increasingly smaller mechanical transducers capable of detecting the forces, motion, mechanical properties and masses that emerge in biomolecular interactions and fundamental biological processes. Thus, biosensors based on nanomechanical systems have gained considerable relevance in the last decade. This review provides insight into the mechanical phenomena that occur in suspended mechanical structures when either biological adsorption or interactions take place on their surface. This review guides the reader through the parameters that change as a consequence of biomolecular adsorption: mass, surface stress, effective Young's modulus and viscoelasticity. The mathematical background needed to correctly interpret the output signals from nanomechanical biosensors is also outlined here. Other practical issues reviewed are the immobilization of biomolecular receptors on the surface of nanomechanical systems and methods to attain that in large arrays of sensors. We then describe some relevant realizations of biosensor devices based on nanomechanical systems that harness some of the mechanical effects cited above. We finally discuss the intrinsic detection limits of the devices and the limitation that arises from non-specific adsorption.

In non-hadronic axion models, which have a tree-level axion-electron interaction, the Sun produces a strong axion flux by bremsstrahlung, Compton scattering, and axio-recombination, the "BCA processes." Based on a new calculation of this flux, including for the first time axio-recombination, we derive limits on the axion-electron Yukawa coupling g_ae and axion-photon interaction strength g_ag using the CAST phase-I data (vacuum phase). For m_a < 10 meV/c2 we find g_ag x g_ae< 8.1 x 10^-23 GeV^-1 at 95% CL. We stress that a next-generation axion helioscope such as the proposed IAXO could push this sensitivity into a range beyond stellar energy-loss limits and test the hypothesis that white-dwarf cooling is dominated by axion emission. In non-hadronic axion models, which have a tree-level axion-electron interaction, the Sun produces a strong axion flux by bremsstrahlung, Compton scattering, and axio-recombination, the ``BCA processes.'' Based on a new calculation of this flux, including for the first time axio-recombination, we derive limits on the axion-electron Yukawa coupling gae and axion-photon interaction strength ga(γ) using the CAST phase-I data (vacuum phase). For malesssim10 meV/c(2) we find ga(γ) gae

The advances in micro- and nanofabrication technologies enable the preparation of increasingly smaller mechanical transducers capable of detecting the forces, motion, mechanical properties and masses that emerge in biomolecular interactions and fundamental biological processes. Thus, biosensors based on nanomechanical systems have gained considerable relevance in the last decade. This review provides insight into the mechanical phenomena that occur in suspended mechanical structures when either biological adsorption or interactions take place on their surface. This review guides the reader through the parameters that change as a consequence of biomolecular adsorption: mass, surface stress, effective Young's modulus and viscoelasticity. The mathematical background needed to correctly interpret the output signals from nanomechanical biosensors is also outlined here. Other practical issues reviewed are the immobilization of biomolecular receptors on the surface of nanomechanical systems and methods to attain that in large arrays of sensors. We then describe some relevant realizations of biosensor devices based on nanomechanical systems that harness some of the mechanical effects cited above. We finally discuss the intrinsic detection limits of the devices and the limitation that arises from non-specific adsorption., The authors would like to acknowledge financial support from the Spanish Science Ministry through projects ANEM! (TEC2009-14517-C02), INMUNO-swing (IPT-2011-0821-010000), POLYSENS (PIB2010BZ-0510) and ForceForFuture (CSD2010-00024); and from European Research Council through Starting Grant NANO- FORCELLS (ERC-StG-2011-278860).

The Neutron Induced Fission Fragment Tracking Experiment (NIFFTE) is a double-sided Time Projection Chamber (TPC) with micromegas readout designed to measure the energy-dependent neutron-induced fission cross sections of the major and minor actinides with unprecedented accuracy. The NIFFTE project addresses the challenge of minimizing major sources of systematic uncertainties from previous fission chamber measurements such as: target and beam non-uniformities, misidentification of alpha and light charged particles as fission fragments, and uncertainties inherent to the reference standards used. In-beam tests of the NIFFTE TPC at the Los Alamos Neutron Science Center (LANSCE) started in 2010 and have continued in 2011, 2012 and 2013. An overview of the NIFFTE TPC status and performance at LANSCE will be presented., Comment: Prepared for JINST as proceeding of the MPGD13 Conference

We investigate the effect of controllably induced tapering on the resonant vibrations and sensing performance of silicon nanowires. Simple analytical expressions for the resonance frequencies of the first two flexural modes as a function of the tapering degree are presented. Experimental measurements of the resonance frequencies of singly clamped nanowires are compared with the theory. Our model is valid for any nanostructure with tapered geometry, and it predicts a reduction beyond two orders of magnitude of the mass detection limit for conical resonators as compared to uniform beams with the same length and diameter at the clamp. © 2013 AIP Publishing LLC., This work was partially funded by projects MAT2012-36197, IPT-2011-0821-010000, CSD2010-00024, IOF-2009-254996, and ERC-StG-2011-278860.

Título en el postprint: Sensitive and Specific End-point detection of Immunoreactions by Nanomechanical Biosensors: Statistical approach to response variability, In the last decade, microcantilever biosensors have shown enormous potential for highly sensitive label-free detection of nucleic acid and proteins. Despite the enormous advances, the promise of applications of this technology in the biomedical field has been frustrated because of its low reproducibility. Here we tackle the reproducibility issue in microcantilever biosensors and provide the guidelines to minimize the deviations in the biosensor response between different assays. We use as a model system the label-free end-point detection of horseradish peroxidase. We choose the end-point detection mode because of its suitability for implementation in the clinical field that requires simplicity and point-of-care capability. Our study comprises the analysis of 1012 cantilevers with different antibody surface densities, two blocking strategies based on polyethylene-glycol (PEG) and bovine serum albumin (BSA) and stringent controls. The study reveals that the performance of the assay critically depends on both antibody surface density and blocking strategies. We find that the optimal conditions involve antibody surface densities near but below saturation and blocking with PEG. We find that the surface stress induced by the antibody–antigen binding is significantly correlated with the surface stress generated during the antibody attachment and blocking steps. The statistical correlation is harnessed to identify immobilization failure or success, and thus enhancing the specificity and sensitivity of the assay. This procedure enables achieving rates of true positives and true negatives of 90% and 91% respectively. The detection limit is of 10 ng mL−1 (250 pM) that is similar to the detection limit obtained in our enzyme-linked immunosorbent assay (ELISA) and at least two orders of magnitude smaller than that achieved with well-established label-free biosensors such as a quartz crystal microbalance (QCM) and surface plasmon resonance (SPR) sensor., The authors acknowledge financial support from the Spanish Science Ministry through projects ANEM! (TEC2009-14517-C02) and INMUNO-swing (IPT-2011-0821-010000) and from European Research Council through Starting Grants NANOFORCELLS (ERC-StG-2011-278860) and NANOPUZZLE (ERC-StG-2009-239931).

This paper proposes a new method, oriented to crop row detection in images from maize fields with high weed pressure. The vision system is designed to be installed onboard a mobile agricultural vehicle, i.e. submitted to gyros, vibrations and undesired movements. The images are captured under image perspective, being affected by the above undesired effects. The image processing consists of three main processes: image segmentation, double thresholding, based on the Otsu's method, and crop row detection. Image segmentation is based on the application of a vegetation index, the double thresholding achieves the separation between weeds and crops and the crop row detection applies least squares linear regression for line adjustment. Crop and weed separation becomes effective and the crop row detection can be favorably compared against the classical approach based on the Hough transform. Both gain effectiveness and accuracy thanks to the double thresholding that makes the main finding of the paper.

Microcantilever biosensors in the static operation mode translate molecular recognition into a surface stress signal. Surface stress is derived from the nanomechanical cantilever bending by applying Stoney's equation, derived more than 100 years ago. This equation ignores the clamping effect on the cantilever deformation, which induces significant errors in the quantification of the biosensing response. This leads to discrepancies in the surface stress induced by biomolecular interactions in measurements with cantilevers with different sizes and geometries. So far, more accurate solutions have been precluded by the formidable complexity of the theoretical problem that involves solving the two-dimensional biharmonic equation. In this paper, we present an accurate and simple analytical expression to quantify the response of microcantilever biosensors. The equation exhibits an excellent agreement with finite element simulations and DNA immobilization experiments on gold-coated microcantilevers., The authors acknowledge financial support from the Spanish Science Ministry through projects ANEM! (TEC2009-14517-C02) and INMUNO-swing (IPT-2011-0821-010000); and from European Research Council through starting grant NANOFORCELLS (ERC-StG-2011-278860).

This paper formulates and proposes a discrete solution for the problem of finding a lost target under uncertainty in minimum time (Minimum Time Search). Given a searching region where some information about the target is known but uncertain (i.e. location and dynamics), and a searching agent with constrained dynamics, we provide two decision making algorithms that optimizes the agent actions to find the target in a minimum time. The problem is faced as a discrete optimization: the actions and the sensor are discrete, and the target probabilistic model is described over a graph, where each vertex contains the target's location probability information and each edge defines the agent possible actions. We revisit the mathematical model of the optimal search problem and we propose a novel approach to include the time into the decision making by reinterpreting it as a maximum discounted time reward problem. The optimal decision plan for the agent is obtained by solving this non convex discrete problem using the cross entropy method. By performing statistical simulations we show how the target is found in minimum time.

During the last taking data campaigns of the CAST experiment, the micromegas detectors have achieved background levels of $\approx 5 \times 10^{-6}$keV$^{-1}$cm$^{-2}$s$^{-1}$ between 2 and 9 keV. This performance has been possible thanks to the introduction of the microbulk technology, the implementation of a shielding and the development of discrimination algorithms. It has motivated new studies towards a deeper understanding of CAST detectors background. One of the working lines includes the construction of a replica of the set-up used in CAST by micromegas detectors and its installation in the Canfranc Underground Laboratory. Thanks to the comparison between the performance of the detectors underground and at surface, shielding upgrades, etc, different contributions to the detectors background have been evaluated. In particular, an upper limit $< 2 \times 10^{-7}$keV$^{-1}$cm$^{-2}$s$^{-1}$ for the intrinsic background of the detector has been obtained. This work means a first evaluation of the potential of the newest micromegas technology in an underground laboratory, the most suitable environment for Rare Event Searches., 6 pages, 8 figures. To appear in the proceedings of the 2nd International Conference on Technology and Instrumentation for Particle Physics (TIPP 2011)

Yıldız, Süleyman Cenk (Dogus Author) -- The conference paper was firstly submitted to 12th International Conference on Topics in Astroparticle and Underground Physics. Micromegas readouts are an attractive option for many of the rare event searches, due to their performance regarding energy resolution, gain stability, homogeneity and material budget. The T-REX project aims at developing further these novel readout techniques for Time Projection Chambers and their potential use in experiments searching for rare events. Here we will refer to the latest results regarding the use and prospects of Micromegas read-outs in axion physics (CAST and the future helioscope), as well as the R&D carried out within NEXT, to search for the neutrinoless double-beta decay.

The T-REX project aims at developing novel readout techniques for Time Projection Chambers in experiments searching for rare events. The enhanced performance of the latest Micromegas readouts in issues like energy resolution, gain stability, homogeneity, material budget, combined with low background techniques, is opening new windows of opportunity for their application in this field. Here we review the latest results regarding the use and prospects of Micromegas readouts in axion physics (CAST and the future helioscope), as well as the R&D carried out within NEXT, to search for the neutrinoless double-beta decay., Comment: Proceedings of the 3rd International conference on Directional Detection of Dark Matter (CYGNUS 2011), Aussois, France, 8-10 June 2011

Stereoscopic vision systems have been used manually for decades to capture threedimensional information of the environment in different applications. With the growth experienced in recent years by the techniques of computer image processing, stereoscopic vision has been increasingly incorporating automated systems of different nature. The central problem in the automation of a stereoscopic vision system is the determination of the correspondence between pixels of the pair of stereoscopic images that come from the same point in three-dimensional scene. The research undertaken in this work comprises the design of a global strategy to solve the stereoscopic correspondence problem for a specific kind of hemispherical image from forest environments. The images are obtained through an optical system based on the lens known as fisheye because this optic system can recover 3D information in a large field-of-view around the camera; in our system it is 183o×360o. This is an important advantage because it allows one to image the trees in the 3D scene close to the system from the base to the top, unlike in systems equipped with conventional lenses where close objects are partially mapped (Abraham & Forstner, 2005). The focus is on obtaining this information from tree trunks using stereoscopic images. The technicians carry out forest inventories which include studies on wood volume and tree density as well as the evolution and growth of the trees with the measurements obtained. Because the trees appear completely imaged, the stereoscopic system allows the calculation of distances from the device to significant points into the trees in the 3D scene, including diameters along the stem, heights and crown dimensions to be measured, as well as determining the position of the trees. These data may be used to obtain precise taper equations, leaf area or volume estimations (Montes et al., 2009). As the distance from the device to each tree can be calculated, the density of trees within a determined area can be also surveyed and growing stock; tree density, basal area (the section of stems at 1.30 m height in a hectare) and other interesting variables may be estimated at forest stand level using statistical inference (Gregoire, 1998).

The last generation of micromegas, called microbulk, are ahead of classical gas detectors (or even other kind of micro-pattern gas detectors) in gain stability, efficiency (by operation at high pressure), simplicity, robustness, energy resolution, readout features and radiopurity. This makes them a competent solution in the field of Rare Event Searches, a field where low background is the most appreciated feature of a detector. The CAST (CERN Axion Solar Telescope) experiment is the best example of their application in the X-rays range. In CAST, these detectors have achieved background rates as low as 6 × 10−6 counts keV−1 cm−2 s−1. Beyond this nominal operation, there have been several periods where the background has been reduced to a level of 2 × 10−7 counts keV−1 cm−2 s−1, due to reasons which are under investigation. The CAST experiment will be presented, paying special attention to their microbulk micromegas, as well as the procedures to achieve low background. Latest news about the operation of these kinds of detectors for the first time in underground conditions will be advanced here. Copyright © 2011 John Wiley & Sons, Ltd.

We present a novel strategy for computing disparity maps from omni-directional stereo images obtained with fish-eye lenses in forest environments. At a first segmentation stage, the method identifies textures of interest to be either matched or discarded. Two of them are identified by applying the powerful Support Vector Machines approach. At a second stage, a stereovision matching process is designed based on the application of four stereovision matching constraints: epipolarity, similarity, uniqueness and smoothness. The epipolarity guides the process. The similarity and uniqueness are mapped once again through the Support Vector Machines, but under a different way to the previous case; after this an initial disparity map is obtained. This map is later filtered by applying the Discrete Simulated Annealing framework where the smoothness constraint is conveniently mapped. The combination of the segmentation and stereovision matching approaches makes the main contribution. The method is compared against the usage of simple features and combined similarity matching strategies. (C) 2011 Elsevier Ltd. All rights reserved.

The CERN Axion Solar Telescope (CAST) has extended its search for solar axions by using (3)He as a buffer gas. At T=1.8 K this allows for larger pressure settings and hence sensitivity to higher axion masses than our previous measurements with (4)He. With about 1 h of data taking at each of 252 different pressure settings we have scanned the axion mass range 0.39 eV≲m(a)≲0.64 eV. From the absence of excess x rays when the magnet was pointing to the Sun we set a typical upper limit on the axion-photon coupling of g(aγ)≲2.3×10(-10) GeV(-1) at 95% C.L., the exact value depending on the pressure setting. Kim-Shifman-Vainshtein-Zakharov axions are excluded at the upper end of our mass range, the first time ever for any solar axion search. In the future we will extend our search to m(a)≲1.15 eV, comfortably overlapping with cosmological hot dark matter bounds.

We present a novel strategy for computing disparity maps from hemispherical stereo images obtained with fish-eye lenses in forest environments. At a first segmentation stage, the method identifies textures of interest to be either matched or discarded. This is achieved by applying a pattern recognition strategy based on the combination of two classifiers: Fuzzy Clustering and Bayesian. At a second stage, a stereovision matching process is performed based on the application of four stereovision matching constraints: epipolar, similarity, uniqueness and smoothness. The epipolar constraint guides the process. The similarity and uniqueness are mapped through a decision making strategy based on a weighted fuzzy similarity approach, obtaining a disparity map. This map is later filtered through the Hopfield Neural Network framework by considering the smoothness constraint. The combination of the segmentation and stereovision matching approaches makes the main contribution. The method is compared against the usage of simple features and combined similarity matching strategies.

This paper describes a device, based on stereovision, which is designed for forest inventories purposes. It captures pairs of omni-directional stereoscopic images through a fish-eye lens, from which different tri-dimensional measures can be obtained by applying a stereovision process, including image acquisition, feature and attribute extraction, feature matching and depth determination. This paper explains and summarizes two specific methods for solving the matching problem, as the key step in stereovision. They are pixel-based and region-based, applied in two kinds of forests environments, the first one highly illuminated and the second one with poor illumination. The performance achieved validates both designs.

We present the results of a search for a high-energy axion emission signal from 7Li (0.478 MeV) and D(p,gamma)3He (5.5 MeV) nuclear transitions using a low-background gamma-ray calorimeter during Phase I of the CAST experiment. These so-called "hadronic axions" could provide a solution to the long-standing strong-CP problem and can be emitted from the solar core from nuclear M1 transitions. This is the first such search for high-energy pseudoscalar bosons with couplings to nucleons conducted using a helioscope approach. No excess signal above background was found., 20 pages, 8 figures, final version to be published in JCAP

Computer vision is an emerging area which is demanding solutions for solving different problems. The data to be processed are bi-dimensional (2D) images captured from the tri-dimensional (3D) scene. The objects in 3D are generally composed of related parts that joined form the whole object. Fortunately, the relations in 3D are preserved in 2D. Hence, we can exploit this fact by considering specific and basic elements which are related to other elements in the 2D images. The relations with other elements allow establishing a link among them. Hence, we have the necessary ingredients to build a structure under the Fuzzy Cognitive Maps (FCMs) paradigm. FCMs have been satisfactorily used in several areas of computer vision including: pattern recognition, image change detection or stereo vision matching. In this chapter we establish the general framework of fuzzy cognitive maps in the context of 2D images and describe three applications in the three mentioned areas of computer vision. We also give some details about the performance of this paradigm in these applications.

A new Micromegas manufacturing technique, based on kapton etching technology, has been developed recently, resulting in further improvement of the characteristics of the detector, such as uniformity and stability. Excellent energy resolution has been obtained, reaching 11% FWHM for the 5.9 keV photon peak of the 55Fe X-ray source and 1.8% FWHM (with possible evidence of less than 1%) for the 5.5 MeV alpha peak of the 241Am source. The new Microbulk detector shows several advantages like flexible structure, low material and high radio-purity, opening thus new possibilities for both accelerator and low counting-rate experiments. The detector has already been used in CAST and n-TOF, while it is being tested for future neutrinoless double-beta decay experiments like NEXT. Details of the production of several types of Microbulk detectors will be described. First benchmark results will be presented, demonstrating the enhanced performance of Microbulk detectors.

This work presents a strategy to track and describe the boundary of an environmental surface using a sequence of incomplete boundary images coming from an UAV with a camera onboard. The algorithm uses all captured images to feed the trajectory, which drives the UAV towards the next point to take the next shot, until the identification is completed. The multiple patterns of the input image make the problem difficult. Our approach orders the points of the image to identify the existent edges, and computes the trajectory as a minimization problem using a multi-objective function that gathers information about the boundary and the polynomial that fit in these edges.

This paper describes a novel stereovision matching approach based on omni-directional images obtained with fish-eye lenses in forest environments. The goal is to obtain a disparity map as a previous step for determining the volume of wood in the imaged area. The interest is focused on the trunks of the trees. Due to the irregular distribution of the trunks, the most suitable features are the pixels. A set of six attributes is used for establishing the matching between the pixels in both images of each stereo pair analysed. The final decision about the matched pixels is taken based on a well tested Fuzzy Multi-Criteria Decision Making approach, where the attributes determine the criteria and the potential matches in one image of the stereo pair for a given pixel in the other one determine the alternatives. The application of this decision making approach makes the main finding of the paper. The full procedure is based on the application of three well known matching constraints. The proposed approach is compared favourably against the usage of simple features.

This paper describes a novel stereovision matching approach by combining several attributes at the pixel level for omni-directional images obtained with fish-eye lenses in forest environments. The goal is to obtain a disparity map as a previous step for determining distances to the trees and then the volume of wood in the imaged area. The interest is focused on the trunks of the trees. Because of the irregular distribution of the trunks, the most suitable features are the pixels. A set of six attributes is used for establishing the matching between the pixels in both images of the stereo pair. The final decision about the matched pixels is taken by combining the attributes. Two combined strategies are proposed: the Sugeno Fuzzy Integral and the Dempster-Shafer theory. The combined strategies, applied to our specific stereo vision matching problem, make the main finding of the paper. In both, the combination is based on the application of three well known matching constraints. The proposed approaches are compared among them and favourably against the usage of simple features.

This paper describes a novel stereovision matching approach based on omni-directional images obtained with fish-eye lenses in forest environments. The goal is to obtain a disparity map as a previous step for determining the volume of wood in the imaged area. The interest is focused on the trunks of the trees, due to the irregular distribution of the trunks; the most suitable features are the pixels. A set of six attributes is used for establishing the matching between the pixels in both images of the stereo pair. The final decision about the matched pixel is taken based on the Choquet Fuzzy Integral paradigm, which is a technique well tested for combining classifiers. The use and adjusting of this decision approach to our specific stereo vision matching problem makes the main finding of the paper. The procedure is based on the application of three well known matching constraints. The proposed approach is compared favourably against the usage of simple features and other fuzzy strategy that combines the simple ones.

This paper describes a novel feature-based stereovision matching process based on a pair of omnidirectional images in forest stands acquired with a stereovision sensor equipped with fish-eye lenses. The stereo analysis problem consists of the following steps image acquisition, camera modelling, feature extraction, image matching and depth determination. Once the depths of significant points on the trees are obtained, the growing stock volume can be estimated by considering the geometrical camera modelling, which is the final goal. The key steps are feature extraction and image matching. This paper is devoted solely to these two steps. At a first stage a segmentation process extracts the trunks, which are the regions used as features, where each feature is identified through a set of attributes of properties useful for matching. In the second step the features are matched based on the application of the following four well known matching constraints, epipolar, similarity, ordering and uniqueness. The combination of the segmentation and matching processes for this specific kind of sensors make the main contribution of the paper. The method is tested with satisfactory results and compared against the human expert criterion. © 2009 by the authors.

Recently, micropattern detectors and in particular micromegas are receiving much attention from the community of rare event searches. The main features that make these detectors rather promising for this field of research and which distinguish them from other gaseous structures are their very stable operation, their homogeneity and granularity which result in very good energy and spatial resolution. In this paper we summarize the latest results on the development of new generation micromegas detectors focusing on rare event searches; more specifically their performance in the search of axions and their possible application to double beta decay experiments.

This paper presents an approach to trajectory generation for unmanned aerial vehicles (UAV) by using mixed integer linear programming (MILP) and a modification of the A* algorithm to optimize paths in dynamic environments, particularly having pop-ups with a known future probability of appearance. Each pop-up leads to one or several possible evasion maneuvers, characterized with a set of values used as decision making parameters in an integer linear programming (ILP) model that optimizes the final route by choosing the most suitable alternative trajectories, according to the imposed constrains such as maximum fuel consumption and spent time. The model of the system in MILP and A* algorithms is presented, as well as the ILP formulation for decision making. Results and discussions are given to promote future real time implementations.

Sunset solar axions traversing the intense magnetic field of the CERN Axion Solar Telescope (CAST) experiment may be detected in a Time Projection Chamber (TPC) detector, as X-rays signals. These signals could be masked, however, by the inhomogeneous background of materials in the experimental site. A detailed analysis, based on the detector characteristics, the background radiation at the CAST site, simulations and experimental results, has allowed us to design a shielding which reduces the background level by a factor of ~4 compared to the detector without shielding, depending on its position, in the energy range between 1 and 10 keV. Moreover, this shielding has improved the homogeneity of background measured by the TPC., 14 pages, 5 figures, accepted in New Journal of Physics

A low background Micromegas detector has been operating in the CAST experiment at CERN for the search of solar axions during the first phase of the experiment (2002-2004). The detector, made out of low radioactivity materials, operated efficiently and achieved a very low level of background rejection (5 x 10^-5 counts/keV/cm^2/s) without shielding., 13 pages, 12 figures and images, submitted to New Journal of

This paper outlines a neural network model based on the Fuzzy Cognitive Maps (FCM) framework for solving the automatic image change detection problem. Each pixel in the reference image is assumed to be a node in the network. Each node has associated a fuzzy value, which determines the magnitude of the change. Each fuzzy value is updated by a trade-off between the influences received from the fuzzy values from other neurons and its own fuzzy value. Classical approaches in the literature have been designed assuming that the mutual influences between two nodes are symmetric. The main finding of this paper is the assumption that mutual influences could not be symmetric. This non symmetric relationship can be embedded by the FCM paradigm. The performance of the proposed method is illustrated by comparative analysis against some recent image change detection methods.

We have searched for solar axions or similar particles that couple to two photons by using the CERN Axion Solar Telescope (CAST) setup with improved conditions in all detectors. From the absence of excess X-rays when the magnet was pointing to the Sun, we set an upper limit on the axion-photon coupling of 8.8 x 10^{-11} GeV^{-1} at 95% CL for m_a, Comment: 24 pages, 8 figures, 1 table, to be submitted to JCAP; v2: minor changes in the exclusion plot; v3: minor changes to match accepted version

The CERN Axion Solar Telescope (CAST) is searching for solar axions using the 9.0 T strong and 9.26 m long transverse magnetic field of a twin aperture LHC test magnet, where axions could be converted into X-rays via reverse Primakoff process. Here we explore the potential of CAST to search for 14.4 keV axions that could be emitted from the Sun in M1 nuclear transition between the first, thermally excited state, and the ground state of 57Fe nuclide. Calculations of the expected signals, with respect to the axion-photon coupling, axion-nucleon coupling and axion mass, are presented in comparison with the experimental sensitivity., Comment: 4 pages, 1 figure. Submitted to Nucl. Instr. and Meth. A

The CERN Axion Solar Telescope (CAST) experiment searches for axions from the Sun converted into photons with energies up to around 10 keV via the inverse Primakoff effect in the high magnetic field of a superconducting Large Hadron Collider (LHC) prototype magnet. A backside illuminated pn‐CCD detector in conjunction with an X‐ray mirror optics is one of the three detectors used in CAST to register the expected photon signal. Since this signal is very rare a detailed study of the detector background has been undertaken with the aim to understand and further reduce the background level of the detector. The analysis is based on measured data taken during the data taking period of 2003 and 2004 of CAST and on Monte Carlo simulations of background with different origin. The background study performed for this detector show that the level of background (8.00±0.07)×10−5 counts cm−2 s−1 keV−1 between 1 and 7 keV is dominated by the external gamma background due to natural activities at the experimental site, wh...

A low background Micromegas X-ray detector has been used to search for solar axions in the CAST experiment at CERN. The detector has an active area of 7cm times 7cm, excellent spatial resolution (~70nm), and good energy resolution. It is built using low radioactivity materials and the obtained background level is below 5times10-5 counts/keV/cm2/s. The detector is being upgraded for the second phase of the experiment (2006-2007) with a reduced active area. A focusing X-Ray optic and improved shielding will be used to further reduce the background by approximately two orders of magnitude.

This paper presents an approach to trajectories optimization for unmanned aerial vehicle (UAV) in presence of obstacles, waypoints, and threat zones such as radar detection regions, using mixed integer linear programming (MILP). The main result is the linear approximation of a nonlinear radar detection risk function with integer constraints and indicator 0-1 variables. Several results are presented to show that the approach can yields trajectories depending on the acceptable risk of detection.

Hypothetical axion‐like particles with a two‐photon interaction would be produced in the sun by the Primakoff process. In a laboratory magnetic field they would be transformed into X‐rays with energies of a few keV. The CAST experiment at CERN is using a decommissioned LHC magnet as an axion helioscope in order to search for these axion‐like particles. The analysis of the 2003 data showed no signal above the background, thus implying an upper limit to the axion‐photon coupling of gaγ < 1.16 × 10−10 GeV−1 at 95% CL for ma ≲ 0.02 eV. The stable operation of the experiment during 2004 data taking allowed us to lower down this parameter to a preliminary value of gaγ < 0.9 × 10−10 GeV−1.

Under illumination variations image change detection becomes a difficult task. Some existing image change detection methods try to compensate this effect. It is assumed that an image can be expressed in terms of its illumination and reflectance components. Detection of changes in the reflectance component is directly related to scene changes. In general, scene illumination varies slowly over space, whereas the reflectance component contains mainly spatially high frequency details. The intention is to apply the image change detection algorithm to the reflectance component only. The aim of this work is to analyze the performance of different homomorphic pre-filtering schemes for extracting the reflectance component so that the image change detection algorithm is applied only to this component. This scheme is not suitable for scenes without spatial high frequency details.