305 resultados para Vision Disorders


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This paper details the design and performance assessment of a unique collision avoidance decision and control strategy for autonomous vision-based See and Avoid systems. The general approach revolves around re-positioning a collision object in the image using image-based visual servoing, without estimating range or time to collision. The decision strategy thus involves determining where to move the collision object, to induce a safe avoidance manuever, and when to cease the avoidance behaviour. These tasks are accomplished by exploiting human navigation models, spiral motion properties, expected image feature uncertainty and the rules of the air. The result is a simple threshold based system that can be tuned and statistically evaluated by extending performance assessment techniques derived for alerting systems. Our results demonstrate how autonomous vision-only See and Avoid systems may be designed under realistic problem constraints, and then evaluated in a manner consistent to aviation expectations.

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Background Longitudinal studies examining the risk of depressive and anxiety disorders associated with diabetes are limited. This study examined the association between diabetes and the risk of depressive and anxiety disorders in Australian women using longitudinal data. Methods Datawere froma sample of women who were part of anAustralian pregnancy and birth cohort study. Data comprised self-reported diabetes mellitus and the subsequent reporting of depressive and anxiety disorders. Mood disorders were assessed according to the Diagnostic and Statistical Manual of Mental Disorders, fourth edition, obtained from participants using Composite International Diagnostic Interview (CIDI)-Auto (WHO WMH-CIDI CAPI, version 21.1.3). Multiple regression models with adjustment for important covariates were used. Results Women with diabetes had a higher lifetime prevalence of any depressive and/or anxiety disorder than women without diabetes. About 3 in 10 women with diabetes experienced a lifetime event of any depressive disorder, while 1 in 2 women with diabetes experienced a lifetime event of any anxiety disorder. In prospective analyses, diabetes was only significantly associated with a 30-day episode of any anxiety disorder (odds ratio [OR] 1.53, 95% confidence interval [CI] 1.09–2.15). In the case of lifetime disorders, diabetes was significantly associated with any depressive disorder (OR 1.37, 95% CI 1.03–1.84), major depressive disorder (OR 1.36, 95% CI 1.01–1.85), and posttraumatic stress disorder (OR 1.42, 95% CI 1.01–2.02). Conclusions The findings suggest that the presence of diabetes is a significant risk factor for women experiencing current anxiety disorders. However, in the case of depression, the association with diabetes only held for women who had experienced past episodes, there was no association with current depression. This suggests that the evidence is not strong enough to support a direct effect of diabetes as a cause of mood disorders.

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Background Nurses are at high risk of musculoskeletal disorders (MSDs). Although the prevalence of MSDs of the lower back, upper limbs, neck and shoulders have been reported previously in nursing, few studies have evaluated MSDs of the foot and ankle. This study evaluated the prevalence of foot and ankle MSDs in nurses and their relation to individual and workplace risk factors. Methods A self-administered survey incorporating the Nordic Musculoskeletal Questionnaire (NMQ) was distributed, over a nine-week period, to all eligible nurses (n = 416) working in a paediatric hospital in Brisbane, Australia. The prevalence of MSDs for each of the NMQ body regions was determined. Bivariate and multivariable logistic regression analyses were conducted to examine the relationships between activity-limiting foot/ankle MSDs and risk factors related to the individual (age, body mass index, number of existing foot conditions, smoking history, general physical health [SF36 Physical Component Scale], footwear features) or the workplace (level of nursing position, work location, average hours worked, hours worked in previous week, time since last break from work). Results A 73% response rate was achieved with 304 nurses completing surveys, of whom 276 were females (91%). Mean age of the nurses was 37 years (±10), younger than the state average of 43 years. Foot/ankle MSDs were the most prevalent conditions experienced by nurses during the preceding seven days (43.8%, 95% CI 38.2-49.4%), the second most prevalent MSDs to impair physical activity (16.7%, 95% CI 13.0-21.3%), and the third most prevalent MSD, after lower-back and neck problems, during the preceding 12 months (55.3%, 95% CI 49.6-60.7%). Of the nurse and work characteristics investigated, obesity, poor general physical health, existing foot conditions and working in the intensive care unit emerged as statistically significant (p < 0.05) independent risk factors for activity-limiting foot/ankle MSDs. Conclusions Foot/ankle MSDs are common in paediatric hospital nurses and resulted in physical activity limitations in one out of every six nurses. We recommend targeted education programs regarding the prevention, self-management and treatment strategies for foot/ankle MSDs. Further research is needed into the impact of work location and extended shift durations on foot/ankle MSDs.

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Osteoporosis is a common, increasingly prevalent and potentially debilitating condition of men and women. Genetic factors are major determinants of bone mass and the risk of fracture, but few genes have been definitively demonstrated to be involved. The identification of these factors will provide novel insights into the processes of bone formation and loss and thus the pathogenesis of osteoporosis, enabling the rational development of novel therapies. In this article, we present the extensive genetic and functional data indicating that the LRP5 gene and the Wnt signalling pathway are key players in bone formation and the risk of osteoporosis, and that LRP5 signalling is essential for normal morphology, developmental processes and bone health.

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There is limited research on the driving performance and safety of bioptic drivers and even less regarding the driving skills that are most challenging for those learning to drive with bioptic telescopes. This research consisted of case studies of five trainee bioptic drivers whose driving skills were compared with those of a group of licensed bioptic drivers (n = 23) while they drove along city, suburban, and controlled-access highways in an instrumented dual-brake vehicle. A certified driver rehabilitation specialist was positioned in the front passenger seat to monitor safety and two backseat evaluators independently rated driving using a standardized scoring system. Other aspects of performance were assessed through vehicle instrumentation and video recordings. Results demonstrate that while sign recognition, lane keeping, steering steadiness, gap judgments and speed choices were significantly worse in trainees, some driving behaviors and skills, including pedestrian detection and traffic light recognition were not significantly different to those of the licensed drivers. These data provide useful insights into the skill challenges encountered by a small sample of trainee bioptic drivers which, while not generalizable because of the small sample size, provide valuable insights beyond that of previous studies and can be used as a basis to guide training strategies.

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Metabolic programming during the perinatal period as a consequence of early nutrition is an emerging area of great interest. This concept is known as the "fetal origins of adult disease" theory (1). Numerous epidemiological studies published over the past 20 years or so have suggested that small body size at birth and during infancy and, more specifically, intrauterine growth retardation are associated later in life with lowered cognitive performance and increased rates of coronary heart disease and its major biological risk factors, ie, raised blood pressure, insulin resistance, coronary artery disease, and abnormalities in lipid metabolism. The molecular mechanisms that govern this phenomenon in humans, however, are unknown and need to be elucidated.

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In summary, although many factors are likely to be involved in regulating calcification and ossification processes, studies of the causation of articular chondrocalcinosis and disorders of spinal ossification, such as DISH and OPLL, implicate control over inorganic pyrophosphate levels as being one of the most important factors in their aetiopathogenesis. The findings of these studies may prove relevant to other rheumatic diseases in which ectopic ossification occurs, such as AS.

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Although robotics research has seen advances over the last decades robots are still not in widespread use outside industrial applications. Yet a range of proposed scenarios have robots working together, helping and coexisting with humans in daily life. In all these a clear need to deal with a more unstructured, changing environment arises. I herein present a system that aims to overcome the limitations of highly complex robotic systems, in terms of autonomy and adaptation. The main focus of research is to investigate the use of visual feedback for improving reaching and grasping capabilities of complex robots. To facilitate this a combined integration of computer vision and machine learning techniques is employed. From a robot vision point of view the combination of domain knowledge from both imaging processing and machine learning techniques, can expand the capabilities of robots. I present a novel framework called Cartesian Genetic Programming for Image Processing (CGP-IP). CGP-IP can be trained to detect objects in the incoming camera streams and successfully demonstrated on many different problem domains. The approach requires only a few training images (it was tested with 5 to 10 images per experiment) is fast, scalable and robust yet requires very small training sets. Additionally, it can generate human readable programs that can be further customized and tuned. While CGP-IP is a supervised-learning technique, I show an integration on the iCub, that allows for the autonomous learning of object detection and identification. Finally this dissertation includes two proof-of-concepts that integrate the motion and action sides. First, reactive reaching and grasping is shown. It allows the robot to avoid obstacles detected in the visual stream, while reaching for the intended target object. Furthermore the integration enables us to use the robot in non-static environments, i.e. the reaching is adapted on-the- fly from the visual feedback received, e.g. when an obstacle is moved into the trajectory. The second integration highlights the capabilities of these frameworks, by improving the visual detection by performing object manipulation actions.

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Stress is a major driving force in alcohol use disorders (AUDs). It influences how much one consumes, craving intensity and whether an abstinent individual will return to harmful alcohol consumption. We are most vulnerable to the effects of stress during early development, and exposure to multiple traumatic early life events dramatically increases the risk for AUDs. However, not everyone exposed to early life stress will develop an AUD. The mechanisms determining whether an individual’s brain adapts and becomes resilient to the effects of stress or succumbs and is unable to cope with stress remain elusive. Emerging evidence suggests that neuroplastic changes in the nucleus accumbens (NAc) following early life stress underlie the development of AUDs. This review discusses the impact of early life stress on NAc structure and function, how these changes affect cholinergic signaling within the mesolimbic reward pathway and the role nicotinic acetylcholine receptors (nAChRs) play in this process. Understanding the neural pathways and mechanism determining stress resilience or susceptibility will improve our ability to identify individuals susceptible to developing AUDs, formulate cognitive interventions to prevent AUDs in susceptible individuals and to elucidate and enhance potential therapeutic targets, such as the nAChRs, for those struggling to overcome an AUD.

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This paper proposes new metrics and a performance-assessment framework for vision-based weed and fruit detection and classification algorithms. In order to compare algorithms, and make a decision on which one to use fora particular application, it is necessary to take into account that the performance obtained in a series of tests is subject to uncertainty. Such characterisation of uncertainty seems not to be captured by the performance metrics currently reported in the literature. Therefore, we pose the problem as a general problem of scientific inference, which arises out of incomplete information, and propose as a metric of performance the(posterior) predictive probabilities that the algorithms will provide a correct outcome for target and background detection. We detail the framework through which these predicted probabilities can be obtained, which is Bayesian in nature. As an illustration example, we apply the framework to the assessment of performance of four algorithms that could potentially be used in the detection of capsicums (peppers).

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This paper provides a comprehensive review of the vision-based See and Avoid problem for unmanned aircraft. The unique problem environment and associated constraints are detailed, followed by an in-depth analysis of visual sensing limitations. In light of such detection and estimation constraints, relevant human, aircraft and robot collision avoidance concepts are then compared from a decision and control perspective. Remarks on system evaluation and certification are also included to provide a holistic review approach. The intention of this work is to clarify common misconceptions, realistically bound feasible design expectations and offer new research directions. It is hoped that this paper will help us to unify design efforts across the aerospace and robotics communities.

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Recent interest in affect and the body have mobilized a contemporary review of aesthetics and phenomenology within architecture to unpack how environments affect spatial experience. Emerging spatial studies within the neuro-sciences, and their implications for architectural research as raised by architectural theorists Juhani Pallasmaa (2014) and Harry Mallgrave (2013) has been well supported by a raft of scientists and institutions including the prestigious Salk Institute. Although there has been some headway in spatial studies of the vision impaired (Cattaneo et al, 2011) to understand the role of their non-visual systems in assisting navigation and location, little is discussed in terms of their other abilities in sensing particular qualities of space which impinge upon emotion. This paper reviews a collection of studies exploring face vision and echo-location, amongst others, which provide insight into what might be termed affective perception of the vision impaired, and how further interplay between this research and the architectural field can contribute new knowledge regarding space and affect. By engaging with themes from the Aesthetics, Phenomenology and indeed Neuro-science fields, the paper provides background of current and potential cross disciplinary research, and highlights the role wearable technologies can play in enhancing knowledge of affective spatial experience.

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The vision sense of standalone robots is limited by line of sight and onboard camera capabilities, but processing video from remote cameras puts a high computational burden on robots. This paper describes the Distributed Robotic Vision Service, DRVS, which implements an on-demand distributed visual object detection service. Robots specify visual information requirements in terms of regions of interest and object detection algorithms. DRVS dynamically distributes the object detection computation to remote vision systems with processing capabilities, and the robots receive high-level object detection information. DRVS relieves robots of managing sensor discovery and reduces data transmission compared to image sharing models of distributed vision. Navigating a sensorless robot from remote vision systems is demonstrated in simulation as a proof of concept.

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There is now a widespread recognition of the importance of mental imagery in a range of clinical disorders (1). This provides the potential for a transdiagnostic route to integrate some aspects of these disorders and their treatment within a common framework. This opinion piece argues that we need to understand why imagery is such a central and recurring feature, if we are to progress theories of the origin and maintenance of disorders. This will aid us in identifying therapeutic techniques that are not simply targeting imagery as a symptom, but as a manifestation of an underlying problem. As papers in this issue highlight, imagery is a central feature across many clinical disorders, but has been ascribed varying roles. For example, the involuntary occurrence of traumatic memories is a diagnostic criterion for PTSD (2), and it has been suggested that multisensory imagery of traumatic events normally serves a functional role in allowing the individual to reappraise the situation (3), but that this re-appraisal is disabled by extreme affective responses. In contrast to the disabling flashbacks associated with PTSD, depressed adults who experience suicidal ideation often report “flash forward” imagery related to suicidal acts (4), motivating them to self-harm. Socially anxious individuals who engage in visual imagery about giving a talk in public become more anxious and make more negative predictions about future performance than others who engage in more abstract, semantic processing of the past event (5). People with Obsessive Compulsive Disorder (OCD) frequently report imagery of past adverse events, and imagery seems to be associated with severity (6). The content of intrusive imagery has been related to psychotic symptoms (7), including visual images of the catastrophic fears associated with paranoia and persecution. Imagery has been argued (8) to play a role in the maintenance of psychosis through negative appraisals of imagined voices, misattribution of sensations to external sources, by the induction of negative mood states that trigger voices, and through maintenance of negative schemas. In addiction and substance dependence, Elaborated Intrusion (EI) Theory (9, 10) emphasizes the causal role that imagery plays in substance use, through its role in motivating an individual to pursue goals directed toward achieving the pleasurable outcomes associated with substance use...