By Sixth&Spring Books
Splendidly smooth, superbly textured, and remarkably cheap, Cascade 220 is likely one of the hottest yarns out there. during this beautiful quantity of all-new tasks, a lot of today’s best knitwear designers come jointly to create an impossible to resist number of hats, scarves, and mittens—all in Cascade 220. There’s whatever for everybody, from an cute monkey-face hat and a stunning mosaic development shawl to a vintage muffler and reasonable Isle flower mittens. Knitters will locate lots of concept and sweetness the following!
Read or Download 60 Quick Knits: 20 Hats*20 Scarves*20 Mittens in Cascade 220 PDF
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Additional resources for 60 Quick Knits: 20 Hats*20 Scarves*20 Mittens in Cascade 220
Haynes and Carr (1990) found that the pseudoword advantage over random strings in visual same-different matching—a task especially sensitive to visual encoding (Carr, Pollatsek, & Posner, 1981)—predicted not only reading comprehension but the ability to learn new word meanings from context among Taiwanese young adults learning to read English as a second language. These results indicate that the gradual education of the visual system about orthographic structure and how to map orthography onto phonology and meaning discovered by Gibson and colleagues is in fact an accompaniment to learning to read a new writing system regardless of age and past experience with other writing systems, not a developmentally driven phenomenon limited to young children learning to read for the first time.
Low-frequency exception words, in contrast, are pronounced 10% to 25% slower, and with higher error rates, than low-frequency regular-consistent words. Errors, though of course much less frequent than in surface dyslexia, follow the same tendency toward regularizations in which the exception word is pronounced as if it were a pseudoword. As word-specific associative knowledge about a particular word's pronunciation gets weaker and less accessible, the impact of the weight of evidence from generalizable patterns increases.
Replication of these imaging results and further investigation of what kinds of codes are being generated or operated on by posterior versus anterior brain structures is needed before these suggestions about division of computational labor in the neural machinery of spelling-to-pronunciation translation can be regarded as more than speculation. Regardless of how the results obtained so far are ultimately interpreted, however, they do demonstrate that sensitivity to factors that influence selecting and producing a pronunciation are widely distributed through the brain.
60 Quick Knits: 20 Hats*20 Scarves*20 Mittens in Cascade 220 by Sixth&Spring Books