DataSheet1_Managing social-educational robotics for students with autism spectrum disorder through business model canvas and customer discovery.PDF

Social-educational robotics, such as NAO humanoid robots with social, anthropomorphic, humanlike features, are tools for learning, education, and addressing developmental disorders (e.g., autism spectrum disorder or ASD) through social and collaborative robotic interactions and interventions. There are significant gaps at the intersection of social robotics and autism research dealing with how robotic technology helps ASD individuals with their social, emotional, and communication needs, and supports teachers who engage with ASD students. This research aims to (a) obtain new scientific knowledge on social-educational robotics by exploring the usage of social robots (especially humanoids) and robotic interventions with ASD students at high schools through an ASD student–teacher co-working with social robot–social robotic interactions triad framework; (b) utilize Business Model Canvas (BMC) methodology for robot design and curriculum development targeted at ASD students; and (c) connect interdisciplinary areas of consumer behavior research, social robotics, and human-robot interaction using customer discovery interviews for bridging the gap between academic research on social robotics on the one hand, and industry development and customers on the other. The customer discovery process in this research results in eight core research propositions delineating the contexts that enable a higher quality learning environment corresponding with ASD students’ learning requirements through the use of social robots and preparing them for future learning and workforce environments.</p

Additional file 5: Figure S3. of The development of lower respiratory tract microbiome in mice

The figure shows the OTUs that are common between a single week point and the rest of the weeks, along with the unique OTUs in that particular week. (PDF 470 kb

Additional file 4: Figure S2. of The development of lower respiratory tract microbiome in mice

Represents the mean abundance measure along with the standard error for the individual phyla. (PDF 65 kb

Additional file 2: Figure S1. of The development of lower respiratory tract microbiome in mice

(a) Inverse SDI follows the same trend as the SDI. (b) The table represents the median and inter-quartile range (IQR). (PDF 29 kb

Additional file 6: Figure S4. of The development of lower respiratory tract microbiome in mice

Represents the mean abundance measure along with the standard error for the individual genera. (PDF 61 kb

Additional file 7: Figure S5. of The development of lower respiratory tract microbiome in mice

Represents the line plot showing the mean percent abundance measure along with the standard error for the 10 genera. (PDF 180 kb

Additional file 3: Table S2. of The development of lower respiratory tract microbiome in mice

The number of replicates per week and reads mapping to each sample. (PDF 180 kb

Lemon Juice Based Extraction of Pectin from Mango Peels: Waste to Wealth by Sustainable Approaches

Valorization of mango peels to recover pectin has the potential to increase the economic viability of a biorefinery utilizing this waste resource. Replacement of conventional mineral acids used for extraction of pectin with natural food grade acids would assist in making the process more environmentally friendly and safe for food applications. In this work, we have evaluated the effect of a natural acidifying agent, lemon juice, in combination with sonication, on pectin extraction. Sonication was used for 20 min at 80 °C, compared to the conventional process which involves boiling for 150 min, thus improving the energy cost of the process considerably. More than 26%w/w of the mass of dried mango peel was extracted as pectin; this was classified as low methoxyl pectin (degree of esterification ≤ 50%). Pectin having this DE is of importance in low calorie food products as a nutraceutical additive

POT1a stimulates telomerase activity of the TER1 RNP.

<p>(A) TP-TRAP analysis from two independent biological replicates wild type, <i>pot1a, ter2</i>, and <i>pot1a ter2</i> mutants. (B) Results of quantitative TRAP (qTRAP). Error bars represent standard error of the mean from three biological replicates.</p

A model for telomere replication in <i>Arabidopsis</i>.

<p>In the un-extendable state, telomeres are bound by the heterotrimeric CST complex. The telomerase RNP is positioned at the chromosome terminus by an unknown recruitment factor (X) during S phase. TEN1 is displaced. POT1a (Pa) contacts STN1 (S) and CTC1 (C) to promote a telomere extendable state. POT1a also stimulates telomerase enzymatic properties. TEN1 represses telomerase activity and thus may help to terminate telomerase action. Telomerase is removed and replaced by POLα for C-strand fill-in and terminal DNA processing. The telomere is then converted into an un-extendable state.</p