Judging Time Intevals using a model of perceptuo-motor control

Estimating a time interval and temporally coordinating movements in space are fundamental skills, but the relationships between these different forms of timing, and the neural processes that they incur, are not well understood. While different theories have been proposed to account for time perception, time estimation, and the temporal patterns of coordination, there are no general mechanisms which unify these various timing skills. This study considers whether a model of perceptuo-motor timing, the tau(GUIDE), can also describe how certain judgements of elapsed time are made. To evaluate this, an equation for determining interval estimates was derived from the tau(GUIDE) model and tested in a task where participants had to throw a ball and estimate when it would hit the floor. The results showed that in accordance with the model, very accurate judgements could be made without vision (mean timing error -19.24 msec), and the model was a good predictor of skilled participants' estimate timing. It was concluded that since the tau(GUIDE) principle provides temporal information in a generic form, it could be a unitary process that links different forms of timing.

Integration of shading and texture cues: testing the linear model

One of the first attempts to develop a formal model of depth cue integration is to be found in Maloney and Landy's (1989) "human depth combination rule". They advocate that the combination of depth cues by the visual sysetem is best described by a weighted linear model. The present experiments tested whether the linear combination rule applies to the integration of texture and shading. As would be predicted by a linear combination rule, the weight assigned to the shading cue did vary as a function of its curvature value. However, the weight assigned to the texture cue varied systematically as a function of the curvature value of both cues. Here we descrive a non-linear model which provides a better fit to the data. Redescribing the stimuli in terms of depth rather than curvature reduced the goodness of fit for all models tested. These results support the hypothesis that the locus of cue integration is a curvature map, rather than a depth map. We conclude that the linear comination rule does not generalize to the integration of shading and texture, and that for these cues it is likely that integration occurs after the recovery of surface curvature.

Robust face recognition using posterior union model based neural networks

Face recognition with unknown, partial distortion and occlusion is a practical problem, and has a wide range of applications, including security and multimedia information retrieval. The authors present a new approach to face recognition subject to unknown, partial distortion and occlusion. The new approach is based on a probabilistic decision-based neural network, enhanced by a statistical method called the posterior union model (PUM). PUM is an approach for ignoring severely mismatched local features and focusing the recognition mainly on the reliable local features. It thereby improves the robustness while assuming no prior information about the corruption. We call the new approach the posterior union decision-based neural network (PUDBNN). The new PUDBNN model has been evaluated on three face image databases (XM2VTS, AT&T and AR) using testing images subjected to various types of simulated and realistic partial distortion and occlusion. The new system has been compared to other approaches and has demonstrated improved performance.

Atomistic Insights into Rhodopsin Activation from a Dynamic Model

Rhodopsin, the light sensitive receptor responsible for blue-green vision, serves as a prototypical G protein-coupled receptor (GPCR). Upon light absorption, it undergoes a series of conformational changes that lead to the active form, metarhodopsin II (META II), initiating a signaling cascade through binding to the G protein transducin (G(t)). Here, we first develop a structural model of META II by applying experimental distance restraints to the structure of lumi-rhodopsin (LUMI), an earlier intermediate. The restraints are imposed by using a combination of biased molecular dynamics simulations and perturbations to an elastic network model. We characterize the motions of the transmembrane helices in the LUMI-to-META II transition and the rearrangement of interhelical hydrogen bonds. We then simulate rhodopsin activation in a dynamic model to study the path leading from LUMI to our META II model for wild-type rhodopsin and a series of mutants. The simulations show a strong correlation between the transition dynamics and the pharmacological phenotypes of the mutants. These results help identify the molecular mechanisms of activation in both wild type and mutant rhodopsin. While static models can provide insights into the mechanisms of ligand recognition and predict ligand affinity, a dynamic model of activation could be applicable to study the pharmacology of other GPCRs and their ligands, offering a key to predictions of basal activity and ligand efficacy.

Wildlife tracking data management: a new vision

To date, the processing of wildlife location data has relied on a diversity of software and file formats. Data management and the following spatial and statistical analyses were undertaken in multiple steps, involving many time-consuming importing/exporting phases. Recent technological advancements in tracking systems have made large, continuous, high-frequency datasets of wildlife behavioral data available, such as those derived from the global positioning system (GPS) and other animal-attached sensor devices. These data can be further complemented by a wide range of other information about the animals’ environment. Management of these large and diverse datasets for modelling animal behaviour and ecology can prove challenging, slowing down analysis and increasing the probability of mistakes in data handling. We address these issues by critically evaluating the requirements for good management of GPS data for wildlife biology. We highlight that dedicated data management tools and expertise are needed. We explore current research in wildlife data management. We suggest a general direction of development, based on a modular software architecture with a spatial database at its core, where interoperability, data model design and integration with remote-sensing data sources play an important role in successful GPS data handling.

FROM LINE-DRAWINGS TO IMPRESSIONS OF 3D OBJECTS - DEVELOPING A MODEL TO ACCOUNT FOR THE SHAPES THAT PEOPLE SEE

The interpretations people attach to line drawings reflect shape-related processes in human vision. Their divergences from expectations embodied in related machine vision traditions are summarized, and used to suggest how human vision decomposes the task of interpretation. A model called IO implements this idea. It first identifies geometrically regular, local fragments. Initial decisions fix edge orientations, and this information constrains decisions about other properties. Relations between fragments are explored, beginning with weak consistency checks and moving to fuller ones. IO's output captures multiple distinctive characteristics of human performance, and it suggests steady progress towards understanding shape-related visual processes is possible.

Effect of TGF-β2 and anti-TGF-β2 antibody in a new in vivo rodent model of posterior capsule opacification

PURPOSE. This study evaluated the effect of transforming growth factor (TGF)-ß2 and anti-TGF-ß2 antibody in a rodent model of posterior capsule opacification (PCO). METHODS. An extracapsular lens extraction (ECLE) was performed in 72 Sprague-Dawley rats. At the end of the procedure, 10 µL TGF-ß2 (TGF-ß2-treated group), fetal calf serum (FCS)/phosphate- buffered saline (PBS; FCS/PBS-treated control group), a human monoclonal TGF-ß2 antibody (anti-TGF-ß2-treated group), or a null control IgG4 antibody (null antibody-treated control group) was injected into the capsule. Animals were killed 3 and 14 days postoperatively. Eyes were evaluated clinically prior to euthanatization, then enucleated and processed for light microscopy and immunohistochemistry afterward. PCO was evaluated clinically and histopathologically. Student's t-test and ? were used to assess differences between groups. RESULTS. There were no statistically significant clinical or histopathological differences in degree of PCO between the TGF-ß2- and FCS/PBS-treated groups at 3 and 14 days after ECLE. Nor were there differences between the anti-TGF-ß2- and the null antibody-treated groups, with the exception of the histopathology score for capsule wrinkling 3 days after ECLE (P = 0.02). a-Smooth-muscle actin staining was observed in the lens capsular bag only in areas where there was close contact with the iris. CONCLUSIONS. No sustained effect of TGF-ß2 or anti-TGF-ß2 antibody on PCO was found in rodents at the dose and timing administered in this study. Iris cells may play a role in the process of epithelial mesenchymal transition linked to PCO. Copyright © Association for Research in Vision and Ophthalmology.

Episodic Reasoning for Vision-Based Human Action Recognition

Smart Spaces, Ambient Intelligence, and Ambient Assisted Living are environmental paradigms that strongly depend on their capability to recognize human actions. While most solutions rest on sensor value interpretations and video analysis applications, few have realized the importance of incorporating common-sense capabilities to support the recognition process. Unfortunately, human action recognition cannot be successfully accomplished by only analyzing body postures. On the contrary, this task should be supported by profound knowledge of human agency nature and its tight connection to the reasons and motivations that explain it. The combination of this knowledge and the knowledge about how the world works is essential for recognizing and understanding human actions without committing common-senseless mistakes. This work demonstrates the impact that episodic reasoning has in improving the accuracy of a computer vision system for human action recognition. This work also presents formalization, implementation, and evaluation details of the knowledge model that supports the episodic reasoning.

Counselling for sight loss: Using systematic case study research to build a client informed practice model

There is compelling evidence to suggest that acquired sight loss negatively impacts on emotional well-being. Despite increasing recognition of the need to provide emotional support for people with sight loss, we still do not fully understand what counselling interventions help and why they help. The aim of this study was to examine the process and outcome of counselling for a 70-year-old client who had experienced complete, irreversible, post-operative sight loss in order to gain a deeper understanding of client-defined helpful aspects of therapy. A Hermeneutic Single-Case Efficacy Design study was undertaken having received ethical approval from the University's Research Ethics Committee. The client received six sessions of counselling from a vision-impaired counsellor working within a pluralistic framework. Measures were completed by the client at every session, as well as at pre-and post-counselling. All sessions were recorded and transcribed. The client also participated in pre-and post-counselling interviews. Data formed a rich case record that was analysed by a quasi-judicial enquiry team. Results suggested that this was a successful outcome case. Client-defined helpful aspects of therapy were (1) feeling understood; (2) being able to express emotions around the loss of sight; (3) finding a new identity; (4) finding ways to cope with fear, loss, dependency, and other people's perceptions; (5) exploring the possibility of a positive future without sight; (6) making sense of things; and (7) finding ways to become more socially connected. Relevant therapeutic tasks are proposed, and four key aspects of therapy are identified, which may have implications for the development of a practice model.

3D Morphable Model Construction for Robust Ear and Face Recognition

Recent work suggests that the human ear varies significantly between different subjects and can be used for identification. In principle, therefore, using ears in addition to the face within a recognition system could improve accuracy and robustness, particularly for non-frontal views. The paper describes work that investigates this hypothesis using an approach based on the construction of a 3D morphable model of the head and ear. One issue with creating a model that includes the ear is that existing training datasets contain noise and partial occlusion. Rather than exclude these regions manually, a classifier has been developed which automates this process. When combined with a robust registration algorithm the resulting system enables full head morphable models to be constructed efficiently using less constrained datasets. The algorithm has been evaluated using registration consistency, model coverage and minimalism metrics, which together demonstrate the accuracy of the approach. To make it easier to build on this work, the source code has been made available online.

The CACTOS Vision of Context-Aware Cloud Topology Optimization and Simulation

Recent advances in hardware development coupled with the rapid adoption and broad applicability of cloud computing have introduced widespread heterogeneity in data centers, significantly complicating the management of cloud applications and data center resources. This paper presents the CACTOS approach to cloud infrastructure automation and optimization, which addresses heterogeneity through a combination of in-depth analysis of application behavior with insights from commercial cloud providers. The aim of the approach is threefold: to model applications and data center resources, to simulate applications and resources for planning and operation, and to optimize application deployment and resource use in an autonomic manner. The approach is based on case studies from the areas of business analytics, enterprise applications, and scientific computing.