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The paper gives a review of experiments for the application of biodegradable, sustainable polymers as a wiring board material. In the paper two different biobased materials and the standard PCB materials FR4 and FR2 were compared. The investigations refer to mechanical, electrical performance, surface quality the flammability and applicability for Polymer Thick Film Technology (PTFT) of the biobased material. The biobased materials are polylactic acid (PLA) mixed with different contents of cellulose acetate (CA) or flame retardant zinc pyrophosphate (ZnPP) and polyurethane (PU) with CA. The results show that the addition of CA to the polymers leads to a change of different properties for PLA and to a significant change in mechanical properties for PU. The use of ZnPP in PLA shows major improvements regarding the flammability of the polymer. The properties of the samples are in the same order of magnitude as the properties of FR2.

Purpose Analysis of connected speech in the field of adult neurogenic communication disorders is essential for research and clinical purposes, yet time and expertise are often cited as limiting factors. The purpose of this project was to create and evaluate an automated program to score and compute the measures from the Quantitative Production Analysis (QPA), an objective and systematic approach for measuring morphological and structural features of connected speech. Method The QPA was used to analyze transcripts of Cinderella stories from 109 individuals with acute–subacute left hemisphere stroke. Regression slopes and residuals were used to compare the results of manual scoring and automated scoring using the newly developed C-QPA command in CLAN, a set of programs for automatic analysis of language samples. Results The C-QPA command produced two spreadsheet outputs: an analysis spreadsheet with scores for each utterance in the language sample, and a summary spreadsheet with 18 score totals from the analysis spreadsheet and an additional 15 measures derived from those totals. Linear regression analysis revealed that 32 of the 33 measures had good agreement; auxiliary complexity index was the one score that did not have good agreement. Conclusions The C-QPA command can be used to perform automated analyses of language transcripts, saving time and training and providing reliable and valid quantification of connected speech. Transcribing in CHAT, the CLAN editor, also streamlined the process of transcript preparation for QPA and allowed for precise linking of media files to language transcripts for temporal analyses.

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