Biological factors affecting sea survival of Atlantic salmon Salmo salar L., in Western Arm Brook and an analysis of selection by the commercial fishery of nearby St. Barbe Bay, Newfoundland

The problems faced by scientists in charge of managing Atlantic salmon (Salmo salar) stocks are : i) how to maintain spawning runs consisting of repeat spawners and large multi-sea-winter (MSW) adults in the face of selective homewater and distant commercial fisheries and , ii) how to more accurately predict returns of adults. Using data from scales collected from maiden Atlantic salmon grilse from two locations on the Northern Peninsula of Newfoundland, St. Barbe Bay and Western Arm Brook, their length at smolting was back calculated. These data were then used to examine whether the St. Barbe commercial fishery is selective for salmon of particular smolt age and/or size. Analysis indicated that come commercial fishery selected larger, but not necessarily older adults that those escaping to Western Arm Brook over the period of this study, 1978-1987. It was determined that less than average size smolts survived better than above average size smolts. Slection for repeat spawners, large MSW salmon, and larger grilse has meant reductions in the proportions of these adults in the spawning runs on Western Arm Brook. This may impact the Western Arm Brook salmon stock by increasing the population instability. Sea survival was significantly correlated with selection by the commercial fishery. Characteristics of adults in Western Arm Brook during the period of study (1978-1987) did not help in explaining yearly variation in sea survival. The characteristics of smolts, however, when subjected to multiple regression analysis explained 57.2 percent of the yearly variation in sea survival.

A ROS-based Workspace Control and Trajectory Planner for a seven degrees of freedom Robotic arm

In this Bachelor Thesis I want to provide readers with tools and scripts for the control of a 7DOF manipulator, backed up by some theory of Robotics and Computer Science, in order to better contextualize the work done. In practice, we will see most common software, and developing environments, used to cope with our task: these include ROS, along with visual simulation by VREP and RVIZ, and an almost "stand-alone" ROS extension called MoveIt!, a very complete programming interface for trajectory planning and obstacle avoidance. As we will better appreciate and understand in the introduction chapter, the capability of detecting collision objects through a camera sensor, and re-plan to the desired end-effector pose, are not enough. In fact, this work is implemented in a more complex system, where recognition of particular objects is needed. Through a package of ROS and customized scripts, a detailed procedure will be provided on how to distinguish a particular object, retrieve its reference frame with respect to a known one, and then allow navigation to that target. Together with technical details, the aim is also to report working scripts and a specific appendix (A) you can refer to, if desiring to put things together.

Evaluación del rendimiento de un planificador de tareas sobre una plataforma heterogénea ARM+DSP de Texas Instruments

El presente trabajo estudia la viabilidad a la hora de aplicar un modelo de programación basado en la extracción de paralelismo a nivel de tareas sobre distintas arquitecturas heterogéneas basadas en un procesador multinúcleo de propósito general acelerado con uno o más aceleradores hardware. Se ha implementado una aplicación completa cuyo objetivo es la detección de bordes en una imagen (implementando el Algoritmo de Canny), y se ha evaluado en detalle su rendimiento sobre distintos tipos de arquitecturas, incluyendo CPUs multinúcleo de última generación, sistemas multi-GPU y una arquitectura objetivo basada en procesadores ARM Cortex-A15 acelerados mediante un DSP C66x de la compañía Texas Instruments. Los resultados experimentales demuestran la viabilidad de este tipo de implementación también para arquitecturas heterogéneas novedosas como esta última, e ilustran la facilidad de programación que introduce este tipo de modelos de programación sobre arquitecturas de propósito específico.

Data feedback and behavioural change intervention to improve primary care prescribing safety (EFIPPS) : multicentre, three arm, cluster-randomised controlled trial

Funding and trial registration: Scottish Government Chief Scientist Office grant CZH/3/17. ClinicalTrials.gov registration NCT01602705.

Control of posture and stability of the double-joint (Shoulder/Elbow) arm

Mémoire numérisé par la Direction des bibliothèques de l'Université de Montréal.

ARM processor modeling at a cycle accurate level in systemC

Mémoire numérisé par la Direction des bibliothèques de l'Université de Montréal.

Control of adaptation to load in point-to-point arm movements

Mémoire numérisé par la Direction des bibliothèques de l'Université de Montréal.

High accuracy mobile robot positioning using an external large volume metrology instrument

A method of accurately controlling the position of a mobile robot using an external Large Volume Metrology (LVM) instrument is presented in this paper. Utilizing a LVM instrument such as the laser tracker in mobile robot navigation, many of the most difficult problems in mobile robot navigation can be simplified or avoided. Using the real- Time position information from the laser tracker, a very simple navigation algorithm, and a low cost robot, 5mm repeatability was achieved over a volume of 30m radius. A surface digitization scan of a wind turbine blade section was also demonstrated, illustrating possible applications of the method for manufacturing processes. © Springer-Verlag Berlin Heidelberg 2010.

Neural Network Evidence for the Coupling of Presaccadic Visual Remapping to Predictive Eye Position Updating.

As we look around a scene, we perceive it as continuous and stable even though each saccadic eye movement changes the visual input to the retinas. How the brain achieves this perceptual stabilization is unknown, but a major hypothesis is that it relies on presaccadic remapping, a process in which neurons shift their visual sensitivity to a new location in the scene just before each saccade. This hypothesis is difficult to test in vivo because complete, selective inactivation of remapping is currently intractable. We tested it in silico with a hierarchical, sheet-based neural network model of the visual and oculomotor system. The model generated saccadic commands to move a video camera abruptly. Visual input from the camera and internal copies of the saccadic movement commands, or corollary discharge, converged at a map-level simulation of the frontal eye field (FEF), a primate brain area known to receive such inputs. FEF output was combined with eye position signals to yield a suitable coordinate frame for guiding arm movements of a robot. Our operational definition of perceptual stability was "useful stability," quantified as continuously accurate pointing to a visual object despite camera saccades. During training, the emergence of useful stability was correlated tightly with the emergence of presaccadic remapping in the FEF. Remapping depended on corollary discharge but its timing was synchronized to the updating of eye position. When coupled to predictive eye position signals, remapping served to stabilize the target representation for continuously accurate pointing. Graded inactivations of pathways in the model replicated, and helped to interpret, previous in vivo experiments. The results support the hypothesis that visual stability requires presaccadic remapping, provide explanations for the function and timing of remapping, and offer testable hypotheses for in vivo studies. We conclude that remapping allows for seamless coordinate frame transformations and quick actions despite visual afferent lags. With visual remapping in place for behavior, it may be exploited for perceptual continuity.

Control of posture and stability of the double-joint (Shoulder/Elbow) arm

Mémoire numérisé par la Direction des bibliothèques de l'Université de Montréal.

ARM processor modeling at a cycle accurate level in systemC

Mémoire numérisé par la Direction des bibliothèques de l'Université de Montréal.

Control of adaptation to load in point-to-point arm movements

Mémoire numérisé par la Direction des bibliothèques de l'Université de Montréal.

Seawater carbonate chemistry and morphometric coordinates and morphology of the control 8-arm pluteus of brittlestar Ophiothrix fragilis, 2008

The world's oceans are slowly becoming more acidic. In the last 150 yr, the pH of the oceans has dropped by ~0.1 units, which is equivalent to a 25% increase in acidity. Modelling predicts the pH of the oceans to fall by 0.2 to 0.4 units by the year 2100. These changes will have significant effects on marine organisms, especially those with calcareous skeletons such as echinoderms. Little is known about the possible long-term impact of predicted pH changes on marine invertebrate larval development. Here we predict the consequences of increased CO2 (corresponding to pH drops of 0.2 and 0.4 units) on the larval development of the brittlestar Ophiothrix fragilis, which is a keystone species occurring in high densities and stable populations throughout the shelf seas of northwestern Europe (eastern Atlantic). Acidification by 0.2 units induced 100% larval mortality within 8 d while control larvae showed 70% survival over the same period. Exposure to low pH also resulted in a temporal decrease in larval size as well as abnormal development and skeletogenesis (abnormalities, asymmetry, altered skeletal proportions). If oceans continue to acidify as expected, ecosystems of the Atlantic dominated by this keystone species will be seriously threatened with major changes in many key benthic and pelagic ecosystems. Thus, it may be useful to monitor O. fragilis populations and initiate conservation if needed.

Computational models for improved diagnosis and prognosis of stroke using robot-based biomarkers

Stroke is a leading cause of death and permanent disability worldwide, affecting millions of individuals. Traditional clinical scores for assessment of stroke-related impairments are inherently subjective and limited by inter-rater and intra-rater reliability, as well as floor and ceiling effects. In contrast, robotic technologies provide objective, highly repeatable tools for quantification of neurological impairments following stroke. KINARM is an exoskeleton robotic device that provides objective, reliable tools for assessment of sensorimotor, proprioceptive and cognitive brain function by means of a battery of behavioral tasks. As such, KINARM is particularly useful for assessment of neurological impairments following stroke. This thesis introduces a computational framework for assessment of neurological impairments using the data provided by KINARM. This is done by achieving two main objectives. First, to investigate how robotic measurements can be used to estimate current and future abilities to perform daily activities for subjects with stroke. We are able to predict clinical scores related to activities of daily living at present and future time points using a set of robotic biomarkers. The findings of this analysis provide a proof of principle that robotic evaluation can be an effective tool for clinical decision support and target-based rehabilitation therapy. The second main objective of this thesis is to address the emerging problem of long assessment time, which can potentially lead to fatigue when assessing subjects with stroke. To address this issue, we examine two time reduction strategies. The first strategy focuses on task selection, whereby KINARM tasks are arranged in a hierarchical structure so that an earlier task in the assessment procedure can be used to decide whether or not subsequent tasks should be performed. The second strategy focuses on time reduction on the longest two individual KINARM tasks. Both reduction strategies are shown to provide significant time savings, ranging from 30% to 90% using task selection and 50% using individual task reductions, thereby establishing a framework for reduction of assessment time on a broader set of KINARM tasks. All in all, findings of this thesis establish an improved platform for diagnosis and prognosis of stroke using robot-based biomarkers.