Subjects classified visible 2-digit numbers as larger or smaller than 55. Target numbers were preceded by masked 2-digit primes that were either congruent (same relation to 55) or incongruent. Experiments 1 and 2 showed prime congruency effects for stimuli never included in the set of classified visible targets, indicating subliminal priming based on long-term semantic memory. Experiments 2 and 3 went further to demonstrate paradoxical unconscious priming effects resulting from task context. For example, after repeated practice classifying 73 as larger than 55, the novel masked prime 37 paradoxically facilitated the "larger" response. In these experiments task context could induce subjects to unconsciously process only the leftmost masked prime digit, only the rightmost digit, or both independently. Across 3 experiments, subliminal priming was governed by both task context and long-term semantic memory.
Download full-text PDF |
Source |
---|---|
http://dx.doi.org/10.1037/0278-7393.29.2.235 | DOI Listing |
Waste Manag
January 2025
Department of Civil and Environmental Engineering, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong, China; Research Centre for Resources Engineering towards Carbon Neutrality, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong, China. Electronic address:
Determination of the relative compositions of the mixed construction waste is crucial and an important step to enhance resource management. This information influences the design of construction waste recycling and sorting facilities, and aids in formulating effective management strategies for recycled and sorted waste products. However, different methods for waste sorting and composition recognition possess distinct characteristics and only apply to specific practical scenarios.
View Article and Find Full Text PDFOphthalmologie
January 2025
Augenklinik Sulzbach, Knappschaftsklinikum Saar, An der Klinik 10, 66280, Sulzbach/Saar, Deutschland.
Background: The increasing bureaucratic burden in everyday clinical practice impairs doctor-patient communication (DPC). Effective use of digital technologies, such as automated semantic speech recognition (ASR) with automated extraction of diagnostically relevant information can provide a solution.
Objective: The aim was to determine the extent to which ASR in conjunction with semantic information extraction for automated documentation of the doctor-patient dialogue (ADAPI) can be integrated into everyday clinical practice using the IVI routine as an example and whether patient care can be improved through process optimization.
Sensors (Basel)
December 2024
Department of Computer Science and Software Engineering, Concordia University, Montreal, QC H3G 1M8, Canada.
Drowsy driving is a leading cause of commercial vehicle traffic crashes. The trend is to train fatigue detection models using deep neural networks on driver video data, but challenges remain in coarse and incomplete high-level feature extraction and network architecture optimization. This paper pioneers the use of the CLIP (Contrastive Language-Image Pre-training) model for fatigue detection.
View Article and Find Full Text PDFCerebellum
January 2025
Center for Language and Cognition, University of Groningen, PO box 716, 9700 AS, Groningen, the Netherlands.
Pediatric cerebellar tumor survivors may present with spontaneous language impairments following treatment, but the nature of these impairments is still largely unclear. A recent study by Svaldi et al. (Cerebellum.
View Article and Find Full Text PDFSci Rep
January 2025
School of Information and Communication Engineering, North University of China, Taiyuan, 030051, China.
The Insulated Gate Bipolar Transistor (IGBT) is a crucial power semiconductor device, and the integrity of its internal structure directly influences both its electrical performance and long-term reliability. However, the precise semantic segmentation of IGBT ultrasonic tomographic images poses several challenges, primarily due to high-density noise interference and visual distortion caused by target warping. To address these challenges, this paper constructs a dedicated IGBT ultrasonic tomography (IUT) dataset using Scanning Acoustic Microscopy (SAM) and proposes a lightweight Multi-Scale Fusion Network (LMFNet) aimed at improving segmentation accuracy and processing efficiency in ultrasonic images analysis.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!