Purpose: We have developed a new test suitable for measuring stereopsis in young children and individuals with communication difficulties. It consists of a drifting, computer-generated red and green, dynamic random dot, disparate shape. The motion direction is indicated by the subject (subjective response) or by a naive observer judging the eye movements of the subject (objective response). Disparity is maintained at 616 sec arc and the dependent variable is the angular subtense of the target, which varies from 11 degrees to 11 ft. In this study, precision (ie, measuring repeatability and objective-subjective agreement) and validity were assessed.
Subjects And Methods: Sixteen subjects with normal vision participated in the repeatability study and 10 in the validity studies. A two-up/one-down, 2 alternative forced choice staircase procedure was used to measure objective and subjective threshold on two occasions with a 1-week separation. Sensitivity for detecting anisometropia was estimated with simulated anisometropia (0 to 3 D) and by comparison with the Randot test. Sensitivity for detecting amblyopia or strabismus was tested in 10 subjects.
Results: Subjective repeatability was 0.31 log units (2 levels of the test) and objective repeatability was 0.49 log units (3.2 levels of the test). The test was able to detect 2.0 D of simulated anisometropia in 8 of 10 cases (above the 95% confidence interval). None of the amblyopic subjects demonstrated stereopsis.
Conclusion: This test of dynamic global stereopsis has potential as a clinical or screening tool for anisometropia, amblyopia, and strabismus.
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http://dx.doi.org/10.3928/0191-3913-20031101-07 | DOI Listing |
ACS Nano
January 2025
Department of Physics and Astronomy, University of Manitoba, Winnipeg R3T 2N2, Canada.
Theory and simulations are used to demonstrate implementation of a variational Bayes algorithm called "active inference" in interacting arrays of nanomagnetic elements. The algorithm requires stochastic elements, and a simplified model based on a magnetic artificial spin ice geometry is used to illustrate how nanomagnets can generate the required random dynamics. Examples of tracking and PID control are demonstrated and shown to be consistent with the original stochastic differential equation formulation of active inference.
View Article and Find Full Text PDFMicrosc Microanal
January 2025
Fritz-Haber-Institut der Max-Planck-Gesellschaft, Berlin 14195, Germany.
In catalysis research, the amount of microscopy data acquired when imaging dynamic processes is often too much for nonautomated quantitative analysis. Developing machine learned segmentation models is challenged by the requirement of high-quality annotated training data. We thus substitute expert-annotated data with a physics-based sequential synthetic data model.
View Article and Find Full Text PDFEcol Evol
January 2025
Department of Agricultural, Food and Environmental Sciences Università Politecnica delle Marche Ancona Italy.
This study investigates climate change impacts on spontaneous vegetation, focusing on the Mediterranean basin, a hotspot for climatic changes. Two case study areas, Monti Sibillini (central Italy, temperate) and Sidi Makhlouf (Southern Tunisia, arid), were selected for their contrasting climates and vegetation. Using WorldClim's CMCC-ESM2 climate model, future vegetation distribution was predicted for 2050 and 2080 under SSP 245 (optimistic) and 585 (pessimistic) scenarios.
View Article and Find Full Text PDFEcol Evol
January 2025
Dynamic Macroecology/Land Change Science Swiss Federal Institute for Forest, Snow and Landscape Research WSL Birmensdorf Switzerland.
High-Arctic environments are facing an elevated pace of warming and increasing human activities, making them more susceptible to the introduction and spread of alien species. We investigated the role of human disturbance in facilitating the spread of a native plant () in a high-Arctic natural environment close to Isfjord Radio station and along adjacent hiking trails at Kapp Linné, Svalbard. We reconstructed the spatial pattern of the arrival and spread of at Kapp Linné by combining historical records of the species occurrence (1928-2018) with a contemporary survey of the plant abundance along the main hiking trail (2023 survey) and tested the relative effects of altitude and proximity to hiking trails on the species density via a generalised linear model (GLM).
View Article and Find Full Text PDFBackground: Though European Respiratory Society and American Thoracic Society (ERS/ATS) guidelines for pulmonary function test (PFT) interpretation recommend the use of the forced vital capacity (FVC) lower limit of normal (LLN) to exclude restriction, recent data suggest that the negative predictive value (NPV) of the FVC LLN is lower than has been accepted, particularly among non-Hispanic Black patients. Using a machine learning (ML) model-rather than the FVC LLN-to exclude restriction may improve the accuracy and equity of PFT interpretation. We sought to develop and externally validate a ML model to predict restriction from spirometry and to assess the potential impact of this model on PFT interpretation.
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