Purpose: To determine whether face perception can be equalized across the visual field by scaling size and contrast simultaneously.
Methods: Contrast sensitivities were measured for detection (N = 1) and identification (N = 2-8) of a target face as a function of size (0.4 degrees-10 degrees) across eccentricities (E = 0 degrees-10 degrees).
Results: In all conditions contrast sensitivity first increased and then saturated, as a function of stimulus size. Maximum sensitivity (Smax) decreased, whereas critical size (where S = Smax/square root(2)) increased with eccentricity and set size (N). At each set size, sensitivities from all eccentricities could be equated by double scaling--i.e., translation in horizontal (size) and vertical (contrast) dimensions on log-log axes. Similarly, at each eccentricity, data from all set sizes could be superimposed using double scaling. Furthermore, all data could be superimposed onto the foveal detection curve when double scaled according to the equation F = 1 + E/E2i + logN/logN2i + E(logN)/K, where i is horizontal or vertical. This equation incorporates the eccentricity (E2) and set size (N2), where contrast and size double, as well as the interaction term (K).
Conclusions: Double scaling superimposes data. Not only is this possible across set sizes or eccentricities separately, but by combining their effects, a function is provided that collapses all data to a single curve, explaining all performance variation across eccentricity and set size. Our results support the proposition based on numeral recognition that failures of spatial scaling across eccentricities may simply reflect the need for scaling both size and contrast.
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The idea of self-organized signal processing in the cerebral cortex has become a focus of research since Beggs and Plentz reported avalanches in local field potential recordings from organotypic cultures and acute slices of rat somatosensory cortex. How the cortex intrinsically organizes signals remains unknown. A current hypothesis was proposed by the condensed matter physicists Bak, Tang, and Wiesenfeld when they conjectured that if neuronal avalanche activity followed inverse power law distributions, then brain activity may be set around phase transitions within self-organized signals.
View Article and Find Full Text PDFWe introduce a computational topology-based approach with unsupervised machine-learning algorithms to estimate the database size and content of RNA-like graph topologies. Specifically, we apply graph theory enumeration to generate all 110,667 possible 2D dual graphs for vertex numbers ranging from 2 to 9. Among them, only 0.
View Article and Find Full Text PDFFront Endocrinol (Lausanne)
January 2025
Department of Ultrasound Diagnosis, Affiliated Kunshan Hospital of Jiangsu University, Kunshan, China.
Objectives: This study aims to develop a nomogram to predict high-volume (> 5) lymph node metastases (HVLNM) in papillary thyroid carcinoma concomitant with Hashimoto's thyroiditis by combining ultrasound with clinicopathologic data.
Materials And Methods: The study reviewed 187 patients diagnosed with papillary thyroid cancer (PTC) concomitant with Hashimoto's thyroiditis from the First People's Hospital of Kunshan between March 2018 and December 2022. These patients underwent preoperative ultrasound and postoperative examinations.
Front Plant Sci
January 2025
School of Computer Science and Technology, Henan Institute of Science and Technology, Xinxiang, China.
Introduction: With the advent of technologies such as deep learning in agriculture, a novel approach to classifying wheat seed varieties has emerged. However, some existing deep learning models encounter challenges, including long processing times, high computational demands, and low classification accuracy when analyzing wheat seed images, which can hinder their ability to meet real-time requirements.
Methods: To address these challenges, we propose a lightweight wheat seed classification model called LWheatNet.
Nanoscale
January 2025
Nanomaterials for BioImaging Group (nanoBIG), Departamento de Física de Materiales, Universidad Autónoma de Madrid (UAM), Madrid 28049, Spain.
All-optical theranostic systems are sought after in nanomedicine, since they combine in a single platform therapeutic and diagnostic capabilities. Commonly in these systems the therapeutic and diagnostic/imaging functions are accomplished with plasmonic photothermal agents and luminescent nanoparticles (NPs), respectively. For maximized performance and minimized side effects, these two modalities should be independently activated, , in a decoupled way, using distinct near infrared (NIR) wavelengths: a radiation window wherein photon-tissue interaction is reduced.
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