The purpose of this study was to investigate whether naming speed makes a contribution to the prediction of reading comprehension, after taking into account the product of word decoding and listening comprehension (i.e., the Simple View of Reading; [Gough, P.B. & Tunmer, W.E. (1986). Remedial and Special Education 7, 6-10]), and phonological awareness. In grade 3, word decoding was measured with the Woodcock [(1998). Woodcock Reading Mastery Tests -Revised. Circle Pines, MN: American Guidance Services]. Word Identification and Word Attack subtests, listening comprehension with the Woodcock (1991) [Woodcock Language Proficiency BatteryRevised. Chicago: Riverside Publishing Company] test of Listening Comprehension, naming speed with a picture naming task, and 4 measures assessed phonological awareness.Reading comprehension was assessed in grades 3, 4, and 5 with the Woodcock (1998) Passage Comprehension subtest and in grade 5 with the GatesMacGinitie reading test. The Simple View was evaluated twice: first, with a pseudoword measure for decoding (Grapheme-Phoneme-conversion product) and, second, with a word identification measure for decoding (word recognition product). Hierarchical regression and commonality analyses indicated that the decoding and listening comprehension products accounted for considerable variance in reading comprehension. Naming speed had a small but significant effect after accounting for the GraphemePhoneme-conversion product (2-3%), but little effect after accounting for the wordrecognition product (0-2%). Subgroup analyses indicated that naming speed had its primary effect for less able readers. Commonality analyses supported the interpretation that naming speed contributes after the Grapheme-Phoneme-conversion product but not after the word recognition product because naming speed has already had its effect upon word recognition. These results indicate that it is important how the Simple View decoding term is defined, and that the Simple View may be incomplete, especially for less able readers.
<p class="MsoNormal" style="text-align: justify; margin: 0in 0.5in 0pt; mso-pagination: none;"><span style="color: black; font-size: 10pt;"><span style="font-family: Times New Roman;">Emerging peer-to-peer communication via social media, and the role of influential peers, is changing the way that marketers communicate with prospects.<span style="mso-spacerun: yes;"> </span>The model is changing from a sender-receiver model to one that includes influential peer-to-peer and receiver-to-sender communication.<span style="mso-spacerun: yes;"> </span>This research examines this phenomenon in the context of student choice of a university.<span style="mso-spacerun: yes;"> </span>What is the relative influence that various sources of information have on students’ choice of university?<span style="mso-spacerun: yes;"> </span>How does the influence of friends and family members compare to the influence of non-personal media?<span style="mso-spacerun: yes;"> </span>How do high-touch tools like campus visits compare to high-tech tools such as social media sites?<span style="mso-spacerun: yes;"> </span>Results of a survey of students showed that parents, along with other family and friends, were the most influential sources of information.<span style="mso-spacerun: yes;"> </span>Outside of personal contacts, a student’s visit to campus was highly influential.<span style="mso-spacerun: yes;"> </span>Surprisingly, social media was not rated as highly influential compared to traditional media.<span style="mso-spacerun: yes;"> </span>Results of a second survey of university employees generally predicted student responses well, although employees underestimated the influence of university representatives (faculty members, staff, and coaches) and underestimated the impact of a visit to campus as sources of information for prospective students.</span></span></p>
Bacterial luciferase is a heterodimeric enzyme comprising two nonidentical but homologous subunits, alpha and beta, encoded by adjacent genes, luxA and luxB. The two genes from Vibrio harveyi were separated and expressed from separate plasmids in Escherichia coli. If both plasmids were present within the same E. coli cell, the level of accumulation of active dimeric luciferase was not dramatically less than within cells containing the intact luxAB sequences. Cells carrying the individual plasmids accumulated large amounts of individual subunits, as evidenced by two-dimensional polyacrylamide gel electrophoresis. Mixing of a lysate of cells carrying the luxA gene with a lysate of cells carrying the luxB gene resulted in formation of very low levels of active heterodimeric luciferase. However, denaturation of the mixed lysates with urea followed by renaturation resulted in formation of large amounts of active luciferase. These observations demonstrate that the two subunits, alpha and beta, if allowed to fold independently in vivo, fold into structures that do not interact to form active heterodimeric luciferase. The encounter complex formed between the two subunits must be an intermediate structure on the pathway to formation of active heterodimeric luciferase.
Mistranslated derivatives of the coat protein of the bacteriophage MS2 were isolated from infected cells starved for asparagine. This protein contains a high level of lysine for asparagine substitutions. By peptide analysis and amino acid sequencing we show that there is a six-fold greater frequency of errors at AAU codons than at AAC codons. This ratio is the same as that found in unstarved cells where the overall error frequency is 100-fold less. We also demonstrate that, at least for AAC codons, context affects error frequency.
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