We propose that any theory of visual awareness must explain the gradient of different awareness measures over experimental conditions, especially when those measures form double dissociations among each other. Theories meeting this requirement must be specific to the measured facets of awareness, such as motion, contrast, or color. Integrated information theory (IIT) lacks such specificity because it is an underconstrained theory with unspecific predictions.
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http://dx.doi.org/10.1017/S0140525X21001874 | DOI Listing |
Rev Esc Enferm USP
January 2025
Universidade Federal do Rio de Janeiro, Escola de Enfermagem Anna Nery, Departamento de Enfermagem Médico-Cirúrgica, Rio de Janeiro, RJ, Brazil.
Objective: To analyze the influence of proxemic factors on communication and care provided by nursing professionals during transfusion in hemotherapy.
Method: A descriptive, exploratory and qualitative study with 25 nursing professionals from a hospital specializing in onco-hematological diseases in Rio de Janeiro, based on a systematized script, individual records of proxemic factors described by Edward Hall and recorded situational interviews. The analysis considered data thematic content and used the SketchUp 3D Modeling Software Review program to visually demonstrate the behavioral mapping of the interaction of nursing professionals with patients during care.
Eur J Phys Rehabil Med
January 2025
Preventive Medicine, Epidemiology and Public Health Area, Department of Biomedical and Diagnostic Sciences, University of Salamanca, Institute for Biomedical Research of Salamanca (IBSAL), Salamanca, Spain -
Background: Neck and back pain pathologies are currently the main cause of absenteeism from work in Spain and in the European Union, and represent a high socio-labor, economic and health cost for the Health Systems.
Aim: To assess the effectiveness of a Back School Program of a Spanish mutual insurance company (risk factors, pain and disability scales) in women workers with low back or neck pain.
Design: We combined a descriptive study of first-session data collected in the total sample and a prospective multicenter intervention study in those participants who completed the second and third check-up at 6 and 9 months.
Sci Rep
January 2025
Department of Computer Science and Engineering, E.G.S. Pillay Engineering College, Nagapattinam, 611002, Tamil Nadu, India.
In response to the pressing need for the detection of Monkeypox caused by the Monkeypox virus (MPXV), this study introduces the Enhanced Spatial-Awareness Capsule Network (ESACN), a Capsule Network architecture designed for the precise multi-class classification of dermatological images. Addressing the shortcomings of traditional Machine Learning and Deep Learning models, our ESACN model utilizes the dynamic routing and spatial hierarchy capabilities of CapsNets to differentiate complex patterns such as those seen in monkeypox, chickenpox, measles, and normal skin presentations. CapsNets' inherent ability to recognize and process crucial spatial relationships within images outperforms conventional CNNs, particularly in tasks that require the distinction of visually similar classes.
View Article and Find Full Text PDFSchizophrenia (Heidelb)
January 2025
School of Psychology, Northwest Normal University, Lanzhou, China.
Controversy exists regarding whether the spontaneity of altercentric intrusion is impaired in patients with schizophrenia during implicit visual perspective-taking tasks. This study explored the characteristics of spontaneous visual perspective-taking in patients with schizophrenia and the effect of an avatar identity on their perspective-taking. We recruited 65 patients with schizophrenia and 65 healthy participants to complete 4 visual perspective-taking experiments for uncued other-avatar and self-avatar tasks and cued other-avatar and self-avatar tasks.
View Article and Find Full Text PDFSensors (Basel)
January 2025
The Higher Educational Key Laboratory for Measuring & Control Technology and Instrumentation of Heilongjiang Province, Harbin University of Science and Technology, Harbin 150080, China.
Video instance segmentation, a key technology for intelligent sensing in visual perception, plays a key role in automated surveillance, robotics, and smart cities. These scenarios rely on real-time and efficient target-tracking capabilities for accurate perception and intelligent analysis of dynamic environments. However, traditional video instance segmentation methods face complex models, high computational overheads, and slow segmentation speeds in time-series feature extraction, especially in resource-constrained environments.
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