Estimación del tiempo de respuesta en los experimentos de banda de frecuencia espacial que implican percepción visual

The present study aimed to determine the optimum response time (RT) needed to identify images of everyday objects when filtered using different spatial frequency bands. Subjects were randomly presented with different images of familiar objects that were both serialized and progressive in their spatial frequencies. The time needed to recognize them was then measured. The results showed that the optimum RT for identifying an image filtered in different spatial frequency bands was approximately 2000 ms of exposure. Specifically, stimuli presented using spatial frequency bands with Gaussian filters of variance V26-V32, which were familiar and of medium size to the viewer, were recognized in a mean time of 2126 ms.The present study aimed to determine the optimum response time (RT) needed to identify images of everyday objects when filtered using different spatial frequency bands. Subjects were randomly presented with different images of familiar objects that were both serialized and progressive in their spatial frequencies. The time needed to recognize them was then measured. The results showed that the optimum RT for identifying an image filtered in different spatial frequency bands was approximately 2000 ms of exposure. Specifically, stimuli presented using spatial frequency bands with Gaussian filters of variance V26-V32, which were familiar and of medium size to the viewer, were recognized in a mean time of 2126 ms

Operating the Helicon Double Layer Thruster in a Space Simulation Chamber

A prototype of the helicon double layer thruster (HDLT) is designed and manufactured. Initial tests with the thruster mounted on a small vacuum chamber (pumping speed of 700 1 · s-1) show successful operation in xenon with the formation of the double la

MACVIA Clinical Decision Algorithm in Allergic Rhinitis in adolescents and adults

International audienceThe selection of pharmacotherapy for patients with allergic rhinitis depends on several factors, including age, prominent symptoms, symptom severity, control of allergic rhinitis, patient preferences and cost. Allergen exposure and resulting symptoms vary and treatment adjustment is required. Clinical decision support systems (CDSS) may be beneficial for the assessment of disease control. Clinical decision support systems should be based on the best evidence and algorithms to aid patients and health care professionals to jointly determine the treatment and its step-up or step-down strategy depending on AR control. MACVIA-LR (Fighting chronic diseases for active and healthy ageing) one of the reference sites of the European Innovation Partnership on Active and Healthy Ageing, has initiated an allergy sentinel network (MASK: MACVIA-ARIA Sentinel networK). A clinical decision support system is currently being developed to optimize allergic rhinitis control. An algorithm developed by consensus is presented in this paper. This algorithm should be confirmed by appropriate trials