Fenología y capacidad de dispersión de Monochamus galloprovincialis (Olivier 1795) en la Península Ibérica = Phenology and dispersal ability of Monochamus galloprovincialis (Olivier 1795) at Iberian Peninsula

La aparición y avance de la enfermedad del marchitamiento del pino (Pine Wilt Desease, PWD), causada por Bursaphelenchus xylophilus (Nematoda; Aphelenchoididae), el nematodo de la madera del pino (NMP), en el suroeste de Europa, ha puesto de manifiesto la necesidad de estudiar la fenología y la dispersión de su único vector conocido en Europa, Monochamus galloprovincialis (Col., Cerambycidae). El análisis de 12 series de emergencias entre 2010 y 2014, registradas en Palencia, València y Teruel, con material procedente de diversos puntos de la península ibérica, demostró una alta variabilidad en la fenología de M. galloprovincialis y la divergencia térmica respecto de las poblaciones portuguesas. Para éstas, el establecimiento de los umbrales térmicos de desarrollo de las larvas post-dormantes del vector (12,2 y 33,5ºC) permitió la predicción de la emergencia mediana para la fecha en la que se acumulaban de 822 grados-día. Ninguna de las series analizadas en este trabajo necesitó de dichos grados-día estimados para la emergencia mediana. Asimismo, la emergencia se adelantó en las regiones más calurosas, mientras que se retrasó en las zonas más templadas. Más allá de la posible variabilidad entre poblaciones locales peninsulares, se detectaron indicios de que la diferencia en la acumulación de calor durante el otoño puede afectar el grado de maduración de las larvas invernantes, y su posterior patrón temporal de emergencia. Por último, también fueron observados comportamientos de protandria en las emergencias. Respecto a la fenología de su vuelo, entre los años 2010 y 2015, fueron ejecutados un total de 8 experimentos de captura de M. galloprovincialis mediante trampas cebadas con atrayentes en diferentes regiones (Castellón, Teruel, Segovia y Alicante) permitiendo el seguimiento del periodo de vuelo. Su análisis permitió constatar la disminución de las capturas y el acortamiento del periodo de vuelo con la altitud, el inicio del vuelo en el mes de mayo/junio a partir de los 14ºC de temperatura media diaria, la influencia de las altas temperaturas en la disminución de las capturas estivales (potencial causante de perfiles bimodales en las curvas de vuelo en las zonas menos frías), la evolución de la proporción de sexos a lo largo del periodo de vuelo (que muestra una mayor captura de hembras al inicio y de machos al final) y el comportamiento diurno y ligado a las altas temperaturas del vuelo circadiano del insecto. Dos redes de muestreo sistemático de insectos saproxílicos instaladas en la Comunitat Valencia (Red MUFFET, 15 parcelas, año 2013) y en Murcia (Red ESFP, 20 parcelas, años 2008-2010) permitieron el estudio de la comunidad de insectos relacionada con M. galloprovincialis. Cada una de las parcelas contaba con una trampa cebada con atrayentes y una estación meteorológica. El registro de más de 250 especies de coleópteros saproxílicos demostró el potencial que tiene el empleo de redes de trampas vigía para la detección temprana de organismos exóticos, además de permitir la caracterización y evaluación de las comunidades de entomofauna útil, representando una de las mejores herramientas de la gestión integrada de plagas. En este caso, la comunidad de saproxílicos estudiada mostró ser muy homogénea respecto a la variación ambiental de las zonas de muestreo, y que pese a las pequeñas variaciones entre las comunidades de los diferentes ecosistemas, el rol que M. galloprovincialis desempeña en ellas a lo largo de todo el gradiente estudiado es el mismo. Con todo, el análisis mediante redes de interacción mostró su relevancia ecológica al actuar de conector entre los diferentes niveles tróficos. Por último, un total de 12 experimentos de marcaje-liberación-recaptura desarrollados entre 2009 y 2012 en Castellón, Teruel, Valencia y Murcia permitieron evaluar el comportamiento dispersivo de M. galloprovincialis. Las detecciones mediante trampas cebadas de los insectos liberados se dieron por lo menos 8 días después de la emergencia. La abundancia de población pareció relacionada con la continuidad, la naturalización de la masa, y con la afección previa de incendios. La dispersión no estuvo influida por la dirección ni la intensidad de los vientos dominantes. La abundancia de material hospedante (en lo referente a las variables de masa y a los índices de competencia) influyó en la captura del insecto en paisajes fragmentados, aunque la ubicación de las trampas optimizó el número de capturas cuando se ubicaron en el límite de la masa y en zonas visibles. Por último también se constató que M. galloprovincialis posee suficiente capacidad de dispersión como para recorrer hasta 1500 m/día, llegando a alcanzar distancias máximas de 13600m o de 22100 m. ABSTRACT The detection and expansion of the Pine Wilt Desease (PWD), caused by Bursaphelenchus xylophilus (Nematoda; Aphelenchoididae), Pine Wood Nematode (PWN), in southwestern Europe since 1999, has triggered off the study of the phenology and the dispersion of its unique vector in the continent, Monochamus galloprovincialis (Coleoptera, Cerambycidae). The analysis of 12 emergence series between 2010 and 2014 registered in Palencia, Teruel and Valencia (Spain), registered from field colonized material collected at several locations of the Iberian Peninsula, showed a high variability in the emergence phenology of M. galloprovincialis. In addition, these patterns showed a very acute thermal divergence regarding a development model fitted earlier in Portugal. Such model forecasted the emergence of 50% of M. galloprovincialis individuals in the Setúbal Peninsula (Portugal) when an average of 822 degree-days (DD) were reached, based on the accumulation of heat from the 1st of March until emergence and lower and upper thresholds of 12.2 ºC and 33,5 °C respectively. In our results, all analyzed series needed less than 822 DD to complete the 50% of the emergence. Also, emergency occurred earlier in the hottest regions, while it was delayed in more temperate areas. Beyond the possible variability between local populations, the difference in the heat accumulation during the fall season may have affected the degree of maturation of overwintering larvae, and subsequently, the temporal pattern of M. galloprovincialis emergences. Therefore these results suggest the need to differentiate local management strategies for the PWN vector, depending on the location, and the climatic variables of each region. Finally, protandrous emergence patterns were observed for M. galloprovincialis in most of the studied data-sets. Regarding the flight phenology of M. galloprovincialis, a total of 8 trapping experiments were carried out in different regions of the Iberian Peninsula (Castellón, Teruel, Segovia and Alicante) between 2010 and 2015. The use of commercial lures and traps allowed monitoring of the flight period of M. galloprovincialis. The analyses of such curves, helped confirming different aspects. First, a decline in the number of catches and a shortening of the flight period was observed as the altitude increased. Flight period was recorded to start in May / June when the daily average temperature went over 14 ° C. A significant influence of high temperatures on the decrease of catches in the summer was found in many occasions, which frequently lead to a bimodal profile of the flight curves in warm areas. The evolution of sex ratio along the flight period shows a greater capture of females at the beginning of the period, and of males at the end. In addition, the circadian response of M. galloprovincialis to lured traps was described for the first time, concluding that the insect is diurnal and that such response is linked to high temperatures. Two networks of systematic sampling of saproxylic insects were installed in the Region of Valencia (Red MUFFET, 15 plots, 2013) and Murcia (Red ICPF, 20 plots, 2008-2010). These networks, intended to serve the double purpose of early-detection and long term monitoring of the saproxylic beetle assemblies, allowed the study of insect communities related to M. galloprovincialis. Each of the plots had a trap baited with attractants and a weather station. The registration of almost 300 species of saproxylic beetles demonstrated the potential use of such trapping networks for the early detection of exotic organisms, while at the same time allows the characterization and evaluation of useful entomological fauna communities, representing one of the best tools for the integrated pest management. In this particular case, the studied community of saproxylic beetles was very homogeneous with respect to environmental variation of the sampling areas, and despite small variations between communities of different ecosystems, the role that M. galloprovincialis apparently plays in them across the studied gradient seems to be the same. However, the analysis through food-webs showed the ecological significance of M. galloprovincialis as a connector between different trophic levels. Finally, 12 mark-release-recapture experiments were carried out between 2009 and 2012 in Castellón, Teruel, Valencia and Murcia (Spain) with the aim to describe the dispersive behavior of M. galloprovincialis as well as the stand and landscape characteristics that could influence its abundance and dispersal. No insects younger than 8 days were caught in lured traps. Population abundance estimates from mark-release-recapture data, seemed related to forest continuity, naturalization, and to prior presence of forest fires. On the other hand, M. galloprovincialis dispersal was not found to be significantly influenced by the direction and intensity of prevailing winds. The abundance of host material, very related to stand characteristics and spacing indexes, influenced the insect abundance in fragmented landscapes. In addition, the location of the traps optimized the number of catches when they were placed in the edge of the forest stands and in visible positions. Finally it was also found that M. galloprovincialis is able to fly up to 1500 m / day, reaching maximum distances of up to 13600 m or 22100 m.

Development of a hand-gesture recognition system for human-computer interaction

The aim of this Master Thesis is the analysis, design and development of a robust and reliable Human-Computer Interaction interface, based on visual hand-gesture recognition. The implementation of the required functions is oriented to the simulation of a classical hardware interaction device: the mouse, by recognizing a specific hand-gesture vocabulary in color video sequences. For this purpose, a prototype of a hand-gesture recognition system has been designed and implemented, which is composed of three stages: detection, tracking and recognition. This system is based on machine learning methods and pattern recognition techniques, which have been integrated together with other image processing approaches to get a high recognition accuracy and a low computational cost. Regarding pattern recongition techniques, several algorithms and strategies have been designed and implemented, which are applicable to color images and video sequences. The design of these algorithms has the purpose of extracting spatial and spatio-temporal features from static and dynamic hand gestures, in order to identify them in a robust and reliable way. Finally, a visual database containing the necessary vocabulary of gestures for interacting with the computer has been created.

Interactions between tRNA identity nucleotides and their recognition sites in glutaminyl-tRNA synthetase determine the cognate amino acid affinity of the enzyme.

Sequence-specific interactions between aminoacyl-tRNA synthetases and their cognate tRNAs both ensure accurate RNA recognition and prevent the binding of noncognate substrates. Here we show for Escherichia coli glutaminyl-tRNA synthetase (GlnRS; EC 6.1.1.18) that the accuracy of tRNA recognition also determines the efficiency of cognate amino acid recognition. Steady-state kinetics revealed that interactions between tRNA identity nucleotides and their recognition sites in the enzyme modulate the amino acid affinity of GlnRS. Perturbation of any of the protein-RNA interactions through mutation of either component led to considerable changes in glutamine affinity with the most marked effects seen at the discriminator base, the 10:25 base pair, and the anticodon. Reexamination of the identity set of tRNA(Gln) in the light of these results indicates that its constituents can be differentiated based upon biochemical function and their contribution to the apparent Gibbs' free energy of tRNA binding. Interactions with the acceptor stem act as strong determinants of tRNA specificity, with the discriminator base positioning the 3' end. The 10:25 base pair and U35 are apparently the major binding sites to GlnRS, with G36 contributing both to binding and recognition. Furthermore, we show that E. coli tryptophanyl-tRNA synthetase also displays tRNA-dependent changes in tryptophan affinity when charging a noncognate tRNA. The ability of tRNA to optimize amino acid recognition reveals a novel mechanism for maintaining translational fidelity and also provides a strong basis for the coevolution of tRNAs and their cognate synthetases.

Real-time detection of DNA hybridization and melting on oligonucleotide arrays by using optical wave guides.

The challenge of the Human Genome Project is to increase the rate of DNA sequence acquisition by two orders of magnitude to complete sequencing of the human genome by the year 2000. The present work describes a rapid detection method using a two-dimensional optical wave guide that allows measurement of real-time binding or melting of a light-scattering label on a DNA array. A particulate label on the target DNA acts as a light-scattering source when illuminated by the evanescent wave of the wave guide and only the label bound to the surface generates a signal. Imaging/visual examination of the scattered light permits interrogation of the entire array simultaneously. Hybridization specificity is equivalent to that obtained with a conventional system using autoradiography. Wave guide melting curves are consistent with those obtained in the liquid phase and single-base discrimination is facile. Dilution experiments showed an apparent lower limit of detection at 0.4 nM oligonucleotide. This performance is comparable to the best currently known fluorescence-based systems. In addition, wave guide detection allows manipulation of hybridization stringency during detection and thereby reduces DNA chip complexity. It is anticipated that this methodology will provide a powerful tool for diagnostic applications that require rapid cost-effective detection of variations from known sequences.

A new approach for semi-automatic rock mass joints recognition from 3D point clouds

Rock mass characterization requires a deep geometric understanding of the discontinuity sets affecting rock exposures. Recent advances in Light Detection and Ranging (LiDAR) instrumentation currently allow quick and accurate 3D data acquisition, yielding on the development of new methodologies for the automatic characterization of rock mass discontinuities. This paper presents a methodology for the identification and analysis of flat surfaces outcropping in a rocky slope using the 3D data obtained with LiDAR. This method identifies and defines the algebraic equations of the different planes of the rock slope surface by applying an analysis based on a neighbouring points coplanarity test, finding principal orientations by Kernel Density Estimation and identifying clusters by the Density-Based Scan Algorithm with Noise. Different sources of information —synthetic and 3D scanned data— were employed, performing a complete sensitivity analysis of the parameters in order to identify the optimal value of the variables of the proposed method. In addition, raw source files and obtained results are freely provided in order to allow to a more straightforward method comparison aiming to a more reproducible research.

Improving 3D Keypoint Detection from Noisy Data Using Growing Neural Gas

3D sensors provides valuable information for mobile robotic tasks like scene classification or object recognition, but these sensors often produce noisy data that makes impossible applying classical keypoint detection and feature extraction techniques. Therefore, noise removal and downsampling have become essential steps in 3D data processing. In this work, we propose the use of a 3D filtering and down-sampling technique based on a Growing Neural Gas (GNG) network. GNG method is able to deal with outliers presents in the input data. These features allows to represent 3D spaces, obtaining an induced Delaunay Triangulation of the input space. Experiments show how the state-of-the-art keypoint detectors improve their performance using GNG output representation as input data. Descriptors extracted on improved keypoints perform better matching in robotics applications as 3D scene registration.

RGBD Human-Hand recognition for the Interaction with Robot-Hand

New low cost sensors and the new open free libraries for 3D image processing are permitting to achieve important advances for robot vision applications such as tridimensional object recognition, semantic mapping, navigation and localization of robots, human detection and/or gesture recognition for human-machine interaction. In this paper, a method to recognize the human hand and to track the fingers is proposed. This new method is based on point clouds from range images, RGBD. It does not require visual marks, camera calibration, environment knowledge and complex expensive acquisition systems. Furthermore, this method has been implemented to create a human interface in order to move a robot hand. The human hand is recognized and the movement of the fingers is analyzed. Afterwards, it is imitated from a Barret hand, using communication events programmed from ROS.

Examination of lane change crashes and potential IVHS countermeasures. Final report.

National Highway Traffic Safety Administration, Washington, D.C.

Research on vehicle-based driver status/performance monitoring; development, validation, and refinement of algorithms for detection of driver drowsiness.

National Highway Traffic Safety Administration, Washington, D.C.

Examination of backing crashes and potential IVHS countermeasures. Final report.

National Highway Traffic Safety Administration, Washington, D.C.

Modeling the relationships between adult attachment patterns and borderline personality disorder: The role of impulsivity and aggressiveness

To obtain a better understanding of the associations among Borderline Personality Disorder (BPD), adult attachment patterns, impulsivity, and aggressiveness, we tested four competing models of these relationships: a) BPD is associated with the personality traits of impulsivity and aggressiveness, but adult attachment patterns predict neither BPD nor impulsive/aggressive features; b) adult attachment patterns are significant predictors of BPD but not of impulsive/aggressive traits, although these traits correlate with BPD; c) adult attachment patterns are significant predictors of impulsive and aggressive traits, which in turn predict BPD; and d) adult attachment patterns significantly predict both BPD and impulsive/aggressive traits. We assessed 466 consecutively admitted outpatients using the Structured Clinical Interview for DSM-IV Axis II Personality Disorders (V. 2.0), the Attachment Style Questionnaire, the Barratt Impulsiveness Scale-11, and the Aggression Questionnaire. Maximum likelihood structural equation modeling of the covariance matrix showed that model (c) was the best fitting model (chi(2) (21) = 31.67, p >.05, RMSEA = .023, test of close fit p >.85). This result indicates that adult attachment patterns act indirectly as risk factors for BPD because of their relationships with aggressive/impulsive personality traits.

Multigradient field-active contour model for multilayer boundary detection of ultrasound rectal wall image

Extraction and reconstruction of rectal wall structures from an ultrasound image is helpful for surgeons in rectal clinical diagnosis and 3-D reconstruction of rectal structures from ultrasound images. The primary task is to extract the boundary of the muscular layers on the rectal wall. However, due to the low SNR from ultrasound imaging and the thin muscular layer structure of the rectum, this boundary detection task remains a challenge. An active contour model is an effective high-level model, which has been used successfully to aid the tasks of object representation and recognition in many image-processing applications. We present a novel multigradient field active contour algorithm with an extended ability for multiple-object detection, which overcomes some limitations of ordinary active contour models—"snakes." The core part in the algorithm is the proposal of multigradient vector fields, which are used to replace image forces in kinetic function for alternative constraints on the deformation of active contour, thereby partially solving the initialization limitation of active contour for rectal wall boundary detection. An adaptive expanding force is also added to the model to help the active contour go through the homogenous region in the image. The efficacy of the model is explained and tested on the boundary detection of a ring-shaped image, a synthetic image, and an ultrasound image. The experimental results show that the proposed multigradient field-active contour is feasible for multilayer boundary detection of rectal wall

Development and evaluation of a youth mental health community awareness campaign - The Compass Strategy

Background: Early detection and treatment of mental disorders in adolescents and young adults can lead to better health outcomes. Mental health literacy is a key to early recognition and help seeking. Whilst a number of population health initiatives have attempted to improve mental health literacy, none to date have specifically targeted young people nor have they applied the rigorous standards of population health models now accepted as best practice in other health areas. This paper describes the outcomes from the application of a health promotion model to the development, implementation and evaluation of a community awareness campaign designed to improve mental health literacy and early help seeking amongst young people. Method: The Compass Strategy was implemented in the western metropolitan Melbourne and Barwon regions of Victoria, Australia. The Precede-Proceed Model guided the population assessment, campaign strategy development and evaluation. The campaign included the use of multimedia, a website, and an information telephone service. Multiple levels of evaluation were conducted. This included a cross-sectional telephone survey of mental health literacy undertaken before and after 14 months of the campaign using a quasi-experimental design. Randomly selected independent samples of 600 young people aged 12 - 25 years from the experimental region and another 600 from a comparison region were interviewed at each time point. A series of binary logistic regression analyses were used to measure the association between a range of campaign outcome variables and the predictor variables of region and time. Results: The program was judged to have an impact on the following variables, as indicated by significant region-by-time interaction effects ( p < 0.05): awareness of mental health campaigns, self-identified depression, help for depression sought in the previous year, correct estimate of prevalence of mental health problems, increased awareness of suicide risk, and a reduction in perceived barriers to help seeking. These effects may be underestimated because media distribution error resulted in a small amount of print material leaking into the comparison region. Conclusion: We believe this is the first study to apply the rigorous standards of a health promotion model including the use of a control region to a mental health population intervention. The program achieved many of its aims despite the relatively short duration and moderate intensity of the campaign.

Seizure detection algorithm for neonates based on wave-sequence analysis

Objective: The description and evaluation of the performance of a new real-time seizure detection algorithm in the newborn infant. Methods: The algorithm includes parallel fragmentation of EEG signal into waves; wave-feature extraction and averaging; elementary, preliminary and final detection. The algorithm detects EEG waves with heightened regularity, using wave intervals, amplitudes and shapes. The performance of the algorithm was assessed with the use of event-based and liberal and conservative time-based approaches and compared with the performance of Gotman's and Liu's algorithms. Results: The algorithm was assessed on multi-channel EEG records of 55 neonates including 17 with seizures. The algorithm showed sensitivities ranging 83-95% with positive predictive values (PPV) 48-77%. There were 2.0 false positive detections per hour. In comparison, Gotman's algorithm (with 30 s gap-closing procedure) displayed sensitivities of 45-88% and PPV 29-56%; with 7.4 false positives per hour and Liu's algorithm displayed sensitivities of 96-99%, and PPV 10-25%; with 15.7 false positives per hour. Conclusions: The wave-sequence analysis based algorithm displayed higher sensitivity, higher PPV and a substantially lower level of false positives than two previously published algorithms. Significance: The proposed algorithm provides a basis for major improvements in neonatal seizure detection and monitoring. Published by Elsevier Ireland Ltd. on behalf of International Federation of Clinical Neurophysiology.

Influential DMUs and outlier detection in data envelopment analysis with an application to health care

This paper explains some drawbacks on previous approaches for detecting influential observations in deterministic nonparametric data envelopment analysis models as developed by Yang et al. (Annals of Operations Research 173:89-103, 2010). For example efficiency scores and relative entropies obtained in this model are unimportant to outlier detection and the empirical distribution of all estimated relative entropies is not a Monte-Carlo approximation. In this paper we developed a new method to detect whether a specific DMU is truly influential and a statistical test has been applied to determine the significance level. An application for measuring efficiency of hospitals is used to show the superiority of this method that leads to significant advancements in outlier detection. © 2014 Springer Science+Business Media New York.