141 resultados para SPECKLE-TRACKING
Resumo:
Background and objectives: Cognitive models suggest that attentional biases are integral in the maintenance of obsessive-compulsive symptoms (OCS). Such biases have been established experimentally in anxiety disorders; however, the evidence is unclear in Obsessive Compulsive disorder (OCD). In the present study, an eye-tracking methodology was employed to explore attentional biases in relation to OCS.
Methods: A convenience sample of 85 community volunteers was assessed on OCS using the Yale-Brown Obsessive Compulsive Scale-self report. Participants completed an eye-tracking paradigm where they were exposed to OCD, Aversive and Neutral visual stimuli. Indices of attentional bias were derived from the eye-tracking data.
Results: Simple linear regressions were performed with OCS severity as the predictor and eye-tracking measures of the different attentional biases for each of the three stimuli types were the criterion variables. Findings revealed that OCS severity moderately predicted greater frequency and duration of fixations on OCD stimuli, which reflect the maintenance attentional bias. No significant results were found in support of other biases.
Limitations: Interpretations based on a non-clinical sample limit the generalisability of the conclusions, although use of such samples in OCD research has been found to be comparable to clinical populations. Future research would include both clinical and sub-clinical participants.
Conclusions: Results provide some support for the theory of maintained attention in OCD attentional biases, as opposed to vigilance theory. Individuals with greater OCS do not orient to OCD stimuli any faster than individuals with lower OCS, but once a threat is identified, these individuals allocate more attention to OCS-relevant stimuli.
Resumo:
We have designed software that can â€â€™look’’ at recorded ultrasound sequences. We analyzed fifteen video sequences representing recorded ultrasound scans of nine fetuses. Our method requires a small amount of user labelled pixels for processing the first frame. These initialize GrowCut 1 , a background removal algorithm, which was used for separating the fetus from its surrounding environment (segmentation). For each subsequent frame, user input is no longer necessary as some of the pixels will inherit labels from the previously processed frame. This results in our software’s ability to track movement. Two sonographers rated the results of our computer’s â€vision’ on a scale from 1 (poor fit) to 10 (excellent fit). They assessed tracking accuracy for the entire video as well as segmentation accuracy (the ability to identify fetus from non-fetus) for every 100th processed frame. There was no appreciable deterioration in the software’s ability to track the fetus over time. I
Resumo:
The stock structure of turbot was investigated between samples from S-Norway, the Irish Sea and the Kattegat, using 12 microsatellite loci and compared to the turbot caught in Icelandic waters. Highly significant genetic differentiation was observed between samples from Kattegat and other areas. Significant genetic differentiation was also observed between the Irish Sea sample on one hand and Iceland and S-Norway on the other hand. No significant genetic differentiation was observed between Iceland and S-Norway. Otoliths of 25 turbot, age ranging from 3 to 19 years, were subjected to nearly 300 mass spectrometry determinations of stable oxygen and carbon isotopes. Oxygen isotope composition (δ18O) in the otolith samples was used to estimate ambient temperature at time of otolith accretion, and yielded estimated temperatures experienced by the turbot ranging from 3 to 15°C. Overall, the genetic analysis indicates panmixia between turbot in Icelandic and Norwegian waters. While the extensive migration of larvae between Norway and Iceland is unlikely, passive drift of turbot larva from other areas (e.g. Ireland) cannot be ruled out.
Resumo:
At QUB we have constructed a system that allows students to self-assess their capability on the fine grained learning outcomes for a module and to update their record as the term progresses. In the system each of the learning outcomes are linked to the relevant teaching session (lectures and labs) and to [online] resources that students can access at any time. Students can structure their own learning experience to their needs to attain the learning outcomes. The system keeps a history of the student’s record, allowing the lecturer to observe how the students’ abilities progress over the term and to compare it to assessment results. The system also keeps of any of the resource links that student has clicked on.