Troubles du comportement alimentaire (TCA), sports de remise en forme et motivations de pratique = Fitness sports, sport motives and eating disorders

Cet article a pour but d'identifier et de mieux comprendre les liens entre les motivations des pratiquantes de sports de remise en forme, les troubles du comportement alimentaire (TCA) et les troubles psychologiques associés (i.e., insatisfaction corporelle, dépendance à l'exercice physique). Au total, 1270 pratiquantes ont répondu à un questionnaire et 40 ont participé à un entretien semi-directif. Les motivations de perte de poids et/ou modification de l'apparence corporelle sont en lien avec les TCA et l'insatisfaction corporelle. La dépendance à l'exercice physique n'est pas systématique chez les femmes avec TCA. Les pratiquantes de sports de remise en forme motivées uniquement par la perte de poids et/ou la modification de l'apparence sont plus à risques dans levdéveloppement des TCA. The aim of this study was to identify and to better understand links between females' motives in fitness sports, eating disorders (ED) and associated psychological disorders (i.e. body dissatisfaction, exercise dependence). In all, 1270 women were asked by questionnaire and 40 by semi-structured interview. Weight loss/body appearance change motives are related to ED and body dissatisfaction. Exercise dependence are not systematic in women with ED. Fitness sports are at risk in the development of ED for women motivated only by weight loss/body appearance change motives

Hyperresolution global land surface modeling: meeting a grand challenge for monitoring Earth's terrestrial water

Monitoring Earth's terrestrial water conditions is critically important to many hydrological applications such as global food production; assessing water resources sustainability; and flood, drought, and climate change prediction. These needs have motivated the development of pilot monitoring and prediction systems for terrestrial hydrologic and vegetative states, but to date only at the rather coarse spatial resolutions (∼10–100 km) over continental to global domains. Adequately addressing critical water cycle science questions and applications requires systems that are implemented globally at much higher resolutions, on the order of 1 km, resolutions referred to as hyperresolution in the context of global land surface models. This opinion paper sets forth the needs and benefits for a system that would monitor and predict the Earth's terrestrial water, energy, and biogeochemical cycles. We discuss six major challenges in developing a system: improved representation of surface‐subsurface interactions due to fine‐scale topography and vegetation; improved representation of land‐atmospheric interactions and resulting spatial information on soil moisture and evapotranspiration; inclusion of water quality as part of the biogeochemical cycle; representation of human impacts from water management; utilizing massively parallel computer systems and recent computational advances in solving hyperresolution models that will have up to 109 unknowns; and developing the required in situ and remote sensing global data sets. We deem the development of a global hyperresolution model for monitoring the terrestrial water, energy, and biogeochemical cycles a “grand challenge” to the community, and we call upon the international hydrologic community and the hydrological science support infrastructure to endorse the effort.

The Joint UK Land Environment Simulator (JULES), model description – part 1: energy and water fluxes

This manuscript describes the energy and water components of a new community land surface model called the Joint UK Land Environment Simulator (JULES). This is developed from the Met Office Surface Exchange Scheme (MOSES). It can be used as a stand alone land surface model driven by observed forcing data, or coupled to an atmospheric global circulation model. The JULES model has been coupled to the Met Office Unified Model (UM) and as such provides a unique opportunity for the research community to contribute their research to improve both world-leading operational weather forecasting and climate change prediction systems. In addition JULES, and its forerunner MOSES, have been the basis for a number of very high-profile papers concerning the land-surface and climate over the last decade. JULES has a modular structure aligned to physical processes, providing the basis for a flexible modelling platform.

Temperature and Photoperiod Effects on Vicia faba Phenology Simulated by CROPGRO-Fababean

Models may be useful tools to design efficient crop management practices provided they are able to accurately simulate the effect of weather variables on crop performance. The objective of this work was to accurately simulate the effects of temperature and day length on the rate of vegetative node expression, time to flowering, time to first pod, and time to physiological maturity of faba bean (Vicia faba L.) using the CROPGRO-Fababean model. Field experiments with multiple sowing dates were conducted in northwest Spain during 3 yr (17 sowing dates: 12 used for calibration and five for validation). Observed daily minimum and maximum air temperatures were within the range of ?9.0 and 39.2°C and observed photoperiods within 10.1 to 16.6 h. Optimization of thermal models to predict leaf appearance raised the base temperature (Tb) from the commonly used value of 0.0 to 3.9°C. In addition, photothermal models detected a small accelerating effect of day length on the rate of leaf appearance. Accurate prediction of the flowering date required incorporating day length, but the solved Tb approached negative values, close to ?4°C. All the reproductive phases after flowering were affected only by temperature, but postanthesis Tb was also mayor que0°C and approached values close to 8°C for time to first pod set and 5.5°C for time from first pod to physiological maturity. Our data indicated that cardinal base temperatures are not the same across all phenological phases.

Online Learning-based Robust Visual Tracking for Autonomous Landing of Unmanned Aerial Vehicles

Autonomous landing is a challenging and important technology for both military and civilian applications of Unmanned Aerial Vehicles (UAVs). In this paper, we present a novel online adaptive visual tracking algorithm for UAVs to land on an arbitrary field (that can be used as the helipad) autonomously at real-time frame rates of more than twenty frames per second. The integration of low-dimensional subspace representation method, online incremental learning approach and hierarchical tracking strategy allows the autolanding task to overcome the problems generated by the challenging situations such as significant appearance change, variant surrounding illumination, partial helipad occlusion, rapid pose variation, onboard mechanical vibration (no video stabilization), low computational capacity and delayed information communication between UAV and Ground Control Station (GCS). The tracking performance of this presented algorithm is evaluated with aerial images from real autolanding flights using manually- labelled ground truth database. The evaluation results show that this new algorithm is highly robust to track the helipad and accurate enough for closing the vision-based control loop.

Robust Real-time Vision-based Aircraft Tracking From Unmanned Aerial Vehicles.

Aircraft tracking plays a key and important role in the Sense-and-Avoid system of Unmanned Aerial Vehicles (UAVs). This paper presents a novel robust visual tracking algorithm for UAVs in the midair to track an arbitrary aircraft at real-time frame rates, together with a unique evaluation system. This visual algorithm mainly consists of adaptive discriminative visual tracking method, Multiple-Instance (MI) learning approach, Multiple-Classifier (MC) voting mechanism and Multiple-Resolution (MR) representation strategy, that is called Adaptive M3 tracker, i.e. AM3. In this tracker, the importance of test sample has been integrated to improve the tracking stability, accuracy and real-time performances. The experimental results show that this algorithm is more robust, efficient and accurate against the existing state-of-art trackers, overcoming the problems generated by the challenging situations such as obvious appearance change, variant surrounding illumination, partial aircraft occlusion, blur motion, rapid pose variation and onboard mechanical vibration, low computation capacity and delayed information communication between UAVs and Ground Station (GS). To our best knowledge, this is the first work to present this tracker for solving online learning and tracking freewill aircraft/intruder in the UAVs.

Online Learning-based Robust Visual Tracking for Autonomous Landing of Unmanned Aerial Vehicles

Autonomous landing is a challenging and important technology for both military and civilian applications of Unmanned Aerial Vehicles (UAVs). In this paper, we present a novel online adaptive visual tracking algorithm for UAVs to land on an arbitrary field (that can be used as the helipad) autonomously at real-time frame rates of more than twenty frames per second. The integration of low-dimensional subspace representation method, online incremental learning approach and hierarchical tracking strategy allows the autolanding task to overcome the problems generated by the challenging situations such as significant appearance change, variant surrounding illumination, partial helipad occlusion, rapid pose variation, onboard mechanical vibration (no video stabilization), low computational capacity and delayed information communication between UAV and Ground Control Station (GCS). The tracking performance of this presented algorithm is evaluated with aerial images from real autolanding flights using manually- labelled ground truth database. The evaluation results show that this new algorithm is highly robust to track the helipad and accurate enough for closing the vision-based control loop.

Real-Time Adaptive Multi-Classifier Multi-Resolution Visual Tracking Framework for Unmanned Aerial Vehicles

This paper presents a novel robust visual tracking framework, based on discriminative method, for Unmanned Aerial Vehicles (UAVs) to track an arbitrary 2D/3D target at real-time frame rates, that is called the Adaptive Multi-Classifier Multi-Resolution (AMCMR) framework. In this framework, adaptive Multiple Classifiers (MC) are updated in the (k-1)th frame-based Multiple Resolutions (MR) structure with compressed positive and negative samples, and then applied them in the kth frame-based Multiple Resolutions (MR) structure to detect the current target. The sample importance has been integrated into this framework to improve the tracking stability and accuracy. The performance of this framework was evaluated with the Ground Truth (GT) in different types of public image databases and real flight-based aerial image datasets firstly, then the framework has been applied in the UAV to inspect the Offshore Floating Platform (OFP). The evaluation and application results show that this framework is more robust, efficient and accurate against the existing state-of-art trackers, overcoming the problems generated by the challenging situations such as obvious appearance change, variant illumination, partial/full target occlusion, blur motion, rapid pose variation and onboard mechanical vibration, among others. To our best knowledge, this is the first work to present this framework for solving the online learning and tracking freewill 2D/3D target problems, and applied it in the UAVs.

Vision-Based Tracking, Odometry and Control for UAV Autonomy

El principal objetivo de este trabajo es proporcionar una solución en tiempo real basada en visión estéreo o monocular precisa y robusta para que un vehículo aéreo no tripulado (UAV) sea autónomo en varios tipos de aplicaciones UAV, especialmente en entornos abarrotados sin señal GPS. Este trabajo principalmente consiste en tres temas de investigación de UAV basados en técnicas de visión por computador: (I) visual tracking, proporciona soluciones efectivas para localizar visualmente objetos de interés estáticos o en movimiento durante el tiempo que dura el vuelo del UAV mediante una aproximación adaptativa online y una estrategia de múltiple resolución, de este modo superamos los problemas generados por las diferentes situaciones desafiantes, tales como cambios significativos de aspecto, iluminación del entorno variante, fondo del tracking embarullado, oclusión parcial o total de objetos, variaciones rápidas de posición y vibraciones mecánicas a bordo. La solución ha sido utilizada en aterrizajes autónomos, inspección de plataformas mar adentro o tracking de aviones en pleno vuelo para su detección y evasión; (II) odometría visual: proporciona una solución eficiente al UAV para estimar la posición con 6 grados de libertad (6D) usando únicamente la entrada de una cámara estéreo a bordo del UAV. Un método Semi-Global Blocking Matching (SGBM) eficiente basado en una estrategia grueso-a-fino ha sido implementada para una rápida y profunda estimación del plano. Además, la solución toma provecho eficazmente de la información 2D y 3D para estimar la posición 6D, resolviendo de esta manera la limitación de un punto de referencia fijo en la cámara estéreo. Una robusta aproximación volumétrica de mapping basada en el framework Octomap ha sido utilizada para reconstruir entornos cerrados y al aire libre bastante abarrotados en 3D con memoria y errores correlacionados espacialmente o temporalmente; (III) visual control, ofrece soluciones de control prácticas para la navegación de un UAV usando Fuzzy Logic Controller (FLC) con la estimación visual. Y el framework de Cross-Entropy Optimization (CEO) ha sido usado para optimizar el factor de escala y la función de pertenencia en FLC. Todas las soluciones basadas en visión en este trabajo han sido probadas en test reales. Y los conjuntos de datos de imágenes reales grabados en estos test o disponibles para la comunidad pública han sido utilizados para evaluar el rendimiento de estas soluciones basadas en visión con ground truth. Además, las soluciones de visión presentadas han sido comparadas con algoritmos de visión del estado del arte. Los test reales y los resultados de evaluación muestran que las soluciones basadas en visión proporcionadas han obtenido rendimientos en tiempo real precisos y robustos, o han alcanzado un mejor rendimiento que aquellos algoritmos del estado del arte. La estimación basada en visión ha ganado un rol muy importante en controlar un UAV típico para alcanzar autonomía en aplicaciones UAV. ABSTRACT The main objective of this dissertation is providing real-time accurate robust monocular or stereo vision-based solution for Unmanned Aerial Vehicle (UAV) to achieve the autonomy in various types of UAV applications, especially in GPS-denied dynamic cluttered environments. This dissertation mainly consists of three UAV research topics based on computer vision technique: (I) visual tracking, it supplys effective solutions to visually locate interesting static or moving object over time during UAV flight with on-line adaptivity approach and multiple-resolution strategy, thereby overcoming the problems generated by the different challenging situations, such as significant appearance change, variant surrounding illumination, cluttered tracking background, partial or full object occlusion, rapid pose variation and onboard mechanical vibration. The solutions have been utilized in autonomous landing, offshore floating platform inspection and midair aircraft tracking for sense-and-avoid; (II) visual odometry: it provides the efficient solution for UAV to estimate the 6 Degree-of-freedom (6D) pose using only the input of stereo camera onboard UAV. An efficient Semi-Global Blocking Matching (SGBM) method based on a coarse-to-fine strategy has been implemented for fast depth map estimation. In addition, the solution effectively takes advantage of both 2D and 3D information to estimate the 6D pose, thereby solving the limitation of a fixed small baseline in the stereo camera. A robust volumetric occupancy mapping approach based on the Octomap framework has been utilized to reconstruct indoor and outdoor large-scale cluttered environments in 3D with less temporally or spatially correlated measurement errors and memory; (III) visual control, it offers practical control solutions to navigate UAV using Fuzzy Logic Controller (FLC) with the visual estimation. And the Cross-Entropy Optimization (CEO) framework has been used to optimize the scaling factor and the membership function in FLC. All the vision-based solutions in this dissertation have been tested in real tests. And the real image datasets recorded from these tests or available from public community have been utilized to evaluate the performance of these vision-based solutions with ground truth. Additionally, the presented vision solutions have compared with the state-of-art visual algorithms. Real tests and evaluation results show that the provided vision-based solutions have obtained real-time accurate robust performances, or gained better performance than those state-of-art visual algorithms. The vision-based estimation has played a critically important role for controlling a typical UAV to achieve autonomy in the UAV application.

Automatic Prediction of Facial Trait Judgments: Appearance vs. Structural Models

Evaluating other individuals with respect to personality characteristics plays a crucial role in human relations and it is the focus of attention for research in diverse fields such as psychology and interactive computer systems. In psychology, face perception has been recognized as a key component of this evaluation system. Multiple studies suggest that observers use face information to infer personality characteristics. Interactive computer systems are trying to take advantage of these findings and apply them to increase the natural aspect of interaction and to improve the performance of interactive computer systems. Here, we experimentally test whether the automatic prediction of facial trait judgments (e.g. dominance) can be made by using the full appearance information of the face and whether a reduced representation of its structure is sufficient. We evaluate two separate approaches: a holistic representation model using the facial appearance information and a structural model constructed from the relations among facial salient points. State of the art machine learning methods are applied to a) derive a facial trait judgment model from training data and b) predict a facial trait value for any face. Furthermore, we address the issue of whether there are specific structural relations among facial points that predict perception of facial traits. Experimental results over a set of labeled data (9 different trait evaluations) and classification rules (4 rules) suggest that a) prediction of perception of facial traits is learnable by both holistic and structural approaches; b) the most reliable prediction of facial trait judgments is obtained by certain type of holistic descriptions of the face appearance; and c) for some traits such as attractiveness and extroversion, there are relationships between specific structural features and social perceptions.

Stop bugging me! : diversity in appearance of warning coloration

In nature, many animals use body coloration to communicate with each other. For example, colorations can be used as signals between individuals of the same species, but also to recognise individuals of other species, and if they may comprise a threat or not. Many animals use protective coloration to avoid predation. The two most common strategies of protective coloration are camouflage and aposematism. Camouflaged animals have coloration that minimises detection, usually by matching colours or structures in the background. Aposematic animals, on the other hand, signal to predators that they are defended. The defence can be physical structures, such as spikes and hairs, or chemical compounds that make the animal distasteful or even deadly toxic. In order for the warning signal to be effective, the predator has to recognise it as such. Studies have shown that birds for example, that are important visual predators on insects, learn to recognise and avoid unpalatable prey faster if they contrast the background or have large internal contrasts. Typical examples of aposematic species have conspicuous colours like yellow, orange or red, often in combination with black. My thesis focuses on the appearance and function of aposematic colour patterns. Even though researchers have studied aposematism for over a century, there is still a lot we do not know about the phenomenon. For example, as it is crucial that the predators recognise a warning signal, aposematic colorations should assumingly evolve homogeneously and be selected for maximal conspicuousness. Instead, there is an extensive variation of colours and patterns among warning colorations, and it is not uncommon to find typical cryptic colours, such as green and brown in aposematic colour patterns. One hypothesis to this variation is that an aposematic coloration does not have to be maximally signalling in order to be effective, instead it is sufficient to have distinct features that can be easily distinguished from edible prey. To be maximally conspicuous is one way to achieve this, but not the only way. Another hypothesis is that aposematic prey that do not exhibit maximal conspicuousness can exploit both camouflage and aposematism in a distance-dependent fashion, by being signalling when seen close up but camouflaged at a distance. Many prey animals also make use of both strategies by shifting colour at different ecological conditions such as seasonal variations, fluctuations in food resources or between life stages. Yet another explanation for the variation may be that prey animals are usually exposed to several predator species that vary in visual perception and tolerance towards various toxins. The aim with this thesis is, by studying their functions, to understand why aposematic warning signals vary in appearance, specifically in the level of conspicuousness, and if warning coloration can be combined with camouflage. In paper I, I investigated if the colour pattern of the aposematic larva of the Apollo butterfly (Parnassius apollo) can switch function with viewing distance, and be signalling at close range but camouflaged at a distance, by comparing detection time between different colour variants and distances. The results show that the natural coloration has a dual distance-dependent function. Moreover, the study shows that an aposematic coloration does not have to be selected for maximal conspicuousness. A prey animal can optimise its coloration primarily by avoiding detection, but also by investing in a secondary defence, which presence can be signalled if detected. In paper II, I studied how easily detected the coloration of the firebug (Pyrrhocoris apterus), a typical aposematic species, is at different distances against different natural backgrounds, by comparing detection time between different colour variants. Here, I found no distance-dependent switch in function. Instead, the results show that the coloration of the firebug is selected for maximal conspicuousness. One explanation for this is that the firebug is more mobile than the butterfly larva in study I, and movement is often incompatible with efficient camouflage. In paper III, I investigated if a seasonal related colour change in the chemically defended striated shieldbug (Graphosoma lineatum) is an adaptation to optimise a protective coloration by shifting from camouflage to aposematism between two seasons. The results confirm the hypothesis that the coloration expressed in the late summer has a camouflage function, blending in with the background. Further, I investigated if the internal pattern as such increased the effectiveness of the camouflage. Again, the results are in accordance with the hypothesis, as the patterned coloration was more difficult to detect than colorations lacking an internal pattern. This study shows how an aposematic species can optimise its defence by shifting from camouflage to aposematism, but in a different fashion than studied in paper I. The aim with study IV was to study the selection on aposematic signals by identifying characteristics that are common for colorations of aposematic species, and that distinguish them from colorations of other species. I compared contrast, pattern element size and colour proportion between a group of defended species and a group of undefended species. In contrast to my prediction, the results show no significant differences between the two groups in any of the analyses. One explanation for the non-significant results could be that there are no universal characteristics common for aposematic species. Instead, the selection pressures acting on defended species vary, and therefore affect their appearance differently. Another explanation is that all defended species may not have been selected for a conspicuous aposematic warning coloration. Taken together, my thesis shows that having a conspicuous warning coloration is not the only way to be aposematic. Also, aposematism and camouflage is not two mutually exclusive opposites, as there are prey species that exploit both strategies. It is also important to understand that prey animals are exposed to various selection pressures and trade-offs that affect their appearance, and determines what an optimal coloration is for each species or environment. In conclusion, I hold that the variation among warning colorations is larger and coloration properties that have been considered as archetypically aposematic may not be as widespread and representative as previously assumed.

Toward seamless prediction: calibration of climate change projections using seasonal forecasts

The CWRF is developed as a climate extension of the Weather Research and Forecasting model (WRF) by incorporating numerous improvements in the representation of physical processes and integration of external (top, surface, lateral) forcings that are crucial to climate scales, including interactions between land, atmosphere, and ocean; convection and microphysics; and cloud, aerosol, and radiation; and system consistency throughout all process modules. This extension inherits all WRF functionalities for numerical weather prediction while enhancing the capability for climate modeling. As such, CWRF can be applied seamlessly to weather forecast and climate prediction. The CWRF is built with a comprehensive ensemble of alternative parameterization schemes for each of the key physical processes, including surface (land, ocean), planetary boundary layer, cumulus (deep, shallow), microphysics, cloud, aerosol, and radiation, and their interactions. This facilitates the use of an optimized physics ensemble approach to improve weather or climate prediction along with a reliable uncertainty estimate. The CWRF also emphasizes the societal service capability to provide impactrelevant information by coupling with detailed models of terrestrial hydrology, coastal ocean, crop growth, air quality, and a recently expanded interactive water quality and ecosystem model. This study provides a general CWRF description and basic skill evaluation based on a continuous integration for the period 1979– 2009 as compared with that of WRF, using a 30-km grid spacing over a domain that includes the contiguous United States plus southern Canada and northern Mexico. In addition to advantages of greater application capability, CWRF improves performance in radiation and terrestrial hydrology over WRF and other regional models. Precipitation simulation, however, remains a challenge for all of the tested models.

Can outcome prediction data change patient outcomes and organizational outcomes?

PURPOSE OF REVIEW: Intensive care medicine consumes a high share of healthcare costs, and there is growing pressure to use the scarce resources efficiently. Accordingly, organizational issues and quality management have become an important focus of interest in recent years. Here, we will review current concepts of how outcome data can be used to identify areas requiring action. RECENT FINDINGS: Using recently established models of outcome assessment, wide variability between individual ICUs is found, both with respect to outcome and resource use. Such variability implies that there are large differences in patient care processes not only within the ICU but also in pre-ICU and post-ICU care. Indeed, measures to improve the patient process in the ICU (including care of the critically ill, patient safety, and management of the ICU) have been presented in a number of recently published papers. SUMMARY: Outcome assessment models provide an important framework for benchmarking. They may help the individual ICU to spot appropriate fields of action, plan and initiate quality improvement projects, and monitor the consequences of such activity.