Integrating Mathematics and Educational Robotics: Simple Motion Planning

This paper shows how students can be guided to integrate elementary mathematical analyses with motion planning for typical educational robots. Rather than using calculus as in comprehensive works on motion planning, we show students can achieve interesting results using just simple linear regression tools and trigonometric analyses. Experiments with one robotics platform show that use of these tools can lead to passable navigation through dead reckoning even if students have limited experience with use of sensors, programming, and mathematics

SEQuel: improving the accuracy of genome assemblies

Motivation: Assemblies of next-generation sequencing (NGS) data, although accurate, still contain a substantial number of errors that need to be corrected after the assembly process. We develop SEQuel, a tool that corrects errors (i.e. insertions, deletions and substitution errors) in the assembled contigs. Fundamental to the algorithm behind SEQuel is the positional de Bruijn graph, a graph structure that models k-mers within reads while incorporating the approximate positions of reads into the model

Effect of dietary synbiotics on growth, immune response and body composition of Caspian roach (Rutilus rutilus)

Effects of dietary synbiotics on growth performance, survival, stress resistance, body composition and immune response in the Caspian roach (Rutilus rutilus) were evaluated. Fish with an initial average weight of 4.14±0.25 g were randomly distributed into tanks (50 fish per tank) and triplicate groups were fed a control diet or diets containing 1 g kg^-1 and 2 g kg^-1 synbiotics. After an 8-week feeding period, a general enhanced growth performance and feed efficiency were observed in fish fed on the diet containing 2 g kg^-1 synbiotics (p<0.05). Subsequently, immune responses (Ig levels, lysozyme activity and ACH50) were significantly higher in 2 g kg^-1 synbiotics fed fish (p<0.05). Although all levels of dietary synbiotics significantly increased resistance to a salinity stress challenge (p<0.05), the highest survival rate was observed in this group. The intestinal tract of the fish with synbiotic diet supplementation had higher concentrations of lactic acid bacteria (7.13±0.32 log CFU g^-1). The protein and lipid contents in the whole body increased in the 2 g kg^-1 synbiotics fed group. At the end of experiment the fish fed synbiotics had the highest survival index after 40 hours exposure to salinity stress (13.8 ppt). Results showed that the addition of synbiotics to the diet of Roach (Rutilus rutilus) stimulates the beneficial intestinal microbiota and alters their immune defense system

The effects of online social networks on the quantitative academic performance of secondary high school girls' students in Tehran

Background and Objectives: One of the important indicators in measuring the quality of education is the academic performance of students, which is important from a scientific and practical point of view. Extensive studies have been conducted worldwide on how social networks affect the quantitative academic performance of their students. Many studies on the denial of social media have concluded that these networks have a negative impact on the younger generation and students. These researchers believe that virtual social networks have an effect on students' annual grade point average, drop in academic grades, writing style and spelling, decrease in English language standards, etc., and have measured these variables separately with the use of social networks among students. At the same time, others believe that the emergence of social media has a positive trend on students' performance and their achievement of high grades. These studies have also found that these students spend most of their time doing their homework and research in this way. Therefore, in the review of previous studies, both approaches are discussed separately. The main purpose of this study is to be aware of the impact of virtual social networks on the quantitative academic performance of female high school students. Sub-objectives are to examine the extent of students 'dependence on virtual social networks and awareness of the impact of using virtual social networks on students' quantitative academic performance. Methods: In this research, a survey method has been used and the sample population includes 855 female students of high schools in Tehran. The data gathering instrument is Jeffrey Single's Social Media Dependency Questionnaire, including academic quantitative performance, social networks addiction, educational use, and grammar, writing, reading, and course questions. In this study, descriptive tests (percentage, mean, and analytical tests (chi-square, Pearson correlation coefficient and t-test) were used. Findings: The findings show that there is no relationship between the students' last year GPA and their academic quantitative performance and their use of the online social network; but there is a relationship between their GPAs and their scientific information exchange (test questions) and with their use of online social networks. The findings show that there is no relationship between last year's students' grade point average and their poor academic performance using a virtual social network. There is only a relationship between their grade point average and the exchange of scientific information (exam questions) through social networks. There is also a link between social media use and poor academic performance, social media addiction, learning and receiving questions and course questions. However, the effect of social networks on the quantitative performance of students is moderate and its effect on other educational activities of students is low. Conclusion: Online social networks can be used as an appropriate way of interaction between students, as well as between teachers and students to convey scientific content, share questions and problem-solving skills, and help each other understand the correct path to problem solving. Although in this study, the use of virtual social networks does not have a negative effect on students' quantitative academic performance, but it should be noted that membership in these networks as a group and as a channel if it creates dependency and students spend a lot of time in their school hours. Can affect the quantitative academic performance of students. ===================================================================================== COPYRIGHTS  ©2020 The author(s). This is an open access article distributed under the terms of the Creative Commons Attribution (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, as long as the original authors and source are cited. No permission is required from the authors or the publishers.  ====================================================================================

A Genetically Encoded AND Gate for Cell-Targeted Metabolic Labeling of Proteins

We describe a genetic AND gate for cell-targeted metabolic labeling and proteomic analysis in complex cellular systems. The centerpiece of the AND gate is a bisected methionyl-tRNA synthetase (MetRS) that charges the Met surrogate azidonorleucine (Anl) to tRNAMet. Cellular protein labeling occurs only upon activation of two different promoters that drive expression of the N- and C-terminal fragments of the bisected MetRS. Anl-labeled proteins can be tagged with fluorescent dyes or affinity reagents via either copper-catalyzed or strain-promoted azide–alkyne cycloaddition. Protein labeling is apparent within 5 min after addition of Anl to bacterial cells in which the AND gate has been activated. This method allows spatial and temporal control of proteomic labeling and identification of proteins made in specific cellular subpopulations. The approach is demonstrated by selective labeling of proteins in bacterial cells immobilized in the center of a laminar-flow microfluidic channel, where they are exposed to overlapping, opposed gradients of inducers of the N- and C-terminal MetRS fragments. The observed labeling profile is predicted accurately from the strengths of the individual input signals

CDD: a Conserved Domain Database for the functional annotation of proteins

NCBI’s Conserved Domain Database (CDD) is a resource for the annotation of protein sequences with the location of conserved domain footprints, and functional sites inferred from these footprints. CDD includes manually curated domain models that make use of protein 3D structure to refine domain models and provide insights into sequence/structure/function relationships. Manually curated models are organized hierarchically if they describe domain families that are clearly related by common descent. As CDD also imports domain family models from a variety of external sources, it is a partially redundant collection. To simplify protein annotation, redundant models and models describing homologous families are clustered into superfamilies. By default, domain footprints are annotated with the corresponding superfamily designation, on top of which specific annotation may indicate high-confidence assignment of family membership. Pre-computed domain annotation is available for proteins in the Entrez/Protein dataset, and a novel interface, Batch CD-Search, allows the computation and download of annotation for large sets of protein queries. CDD can be accessed via http://www.ncbi.nlm.nih.gov/Structure/cdd/cdd.shtml

CDD: specific functional annotation with the Conserved Domain Database

NCBI's Conserved Domain Database (CDD) is a collection of multiple sequence alignments and derived database search models, which represent protein domains conserved in molecular evolution. The collection can be accessed at http://www.ncbi.nlm.nih.gov/Structure/cdd/cdd.shtml, and is also part of NCBI's Entrez query and retrieval system, cross-linked to numerous other resources. CDD provides annotation of domain footprints and conserved functional sites on protein sequences. Precalculated domain annotation can be retrieved for protein sequences tracked in NCBI's Entrez system, and CDD's collection of models can be queried with novel protein sequences via the CD-Search service at http://www.ncbi.nlm.nih.gov/Structure/cdd/wrpsb.cgi. Starting with the latest version of CDD, v2.14, information from redundant and homologous domain models is summarized at a superfamily level, and domain annotation on proteins is flagged as either ‘specific’ (identifying molecular function with high confidence) or as ‘non-specific’ (identifying superfamily membership only)

Full design automation of multi-state RNA devices to program gene expression using energy-based optimization

[EN] Small RNAs (sRNAs) can operate as regulatory agents to control protein expression by interaction with the 59 untranslated region of the mRNA. We have developed a physicochemical framework, relying on base pair interaction energies, to design multi-state sRNA devices by solving an optimization problem with an objective function accounting for the stability of the transition and final intermolecular states. Contrary to the analysis of the reaction kinetics of an ensemble of sRNAs, we solve the inverse problem of finding sequences satisfying targeted reactions. We show here that our objective function correlates well with measured riboregulatory activity of a set of mutants. This has enabled the application of the methodology for an extended design of RNA devices with specified behavior, assuming different molecular interaction models based on Watson-Crick interaction. We designed several YES, NOT, AND, and OR logic gates, including the design of combinatorial riboregulators. 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