In this study, the possibilities of noise tailoring in filamentary resistive switching memory devices are investigated. To this end, the resistance and frequency scaling of the low-frequency 1/-type noise properties are studied in representative mainstream material systems. It is shown that the overall noise floor is tailorable by the proper material choice, as demonstrated by the order-of-magnitude smaller noise levels in TaO and NbO transition-metal oxide memristors compared to Ag-based devices. Furthermore, the variation of the resistance states allows orders-of-magnitude tuning of the relative noise level in all of these material systems. This behavior is analyzed in the framework of a point-contact noise model highlighting the possibility for the disorder-induced suppression of the noise contribution arising from remote fluctuators. These findings promote the design of multipurpose resistive switching units, which can simultaneously serve as analog-tunable memory elements and tunable noise sources in probabilistic computing machines.
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http://dx.doi.org/10.1021/acsami.0c21156 | DOI Listing |
Ultrasound Obstet Gynecol
January 2025
Robinson Research Institute, University of Adelaide, Adelaide, Australia.
Objectives: The development of valuable artificial intelligence (AI) tools to assist with ultrasound diagnosis depends on algorithms developed using high-quality data. This study aimed to test the intra- and interobserver agreement of a proposed image-quality scoring system to quantify the quality of gynecological transvaginal ultrasound (TVS) images, which could be used in clinical practice and AI tool development.
Methods: A proposed scoring system to quantify TVS image quality was created following a review of the literature.
Sci Adv
January 2025
James Watt School of Engineering, University of Glasgow, Glasgow G12 8QQ, UK.
The time-resolved detection of mid- to far-infrared electric fields absorbed and emitted by molecules is among the most sensitive spectroscopic approaches and has the potential to transform sensing in fields such as security screening, quality control, and medical diagnostics. However, the sensitivity of the standard detection approach, which relies on encoding the far-infrared electric field into amplitude modulation of a visible or near-infrared probe laser pulse, is limited by the shot noise of the latter. This constraint cannot be overcome without using a quantum resource.
View Article and Find Full Text PDFImages are important information carriers in our lives, and images should be secure when transmitted and stored. Image encryption algorithms based on chaos theory emerge in endlessly. Based on previous various chaotic image fast encryption algorithms, this paper proposes a color image sector fast encryption algorithm based on one-dimensional composite sinusoidal chaotic mapping.
View Article and Find Full Text PDFPLoS One
January 2025
Department of Otolaryngology-Head and Neck Surgery, Icahn School of Medicine at Mount Sinai, New York, NY, United States of America.
Objective: What we hear may influence postural control, particularly in people with vestibular hypofunction. Would hearing a moving subway destabilize people similarly to seeing the train move? We investigated how people with unilateral vestibular hypofunction and healthy controls incorporated broadband and real-recorded sounds with visual load for balance in an immersive contextual scene.
Design: Participants stood on foam placed on a force-platform, wore the HTC Vive headset, and observed an immersive subway environment.
Elife
January 2025
National Centre for Biological Sciences, Tata Institute of Fundamental Research, Bangalore, India.
Co-active or temporally ordered neural ensembles are a signature of salient sensory, motor, and cognitive events. Local convergence of such patterned activity as synaptic clusters on dendrites could help single neurons harness the potential of dendritic nonlinearities to decode neural activity patterns. We combined theory and simulations to assess the likelihood of whether projections from neural ensembles could converge onto synaptic clusters even in networks with random connectivity.
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