Multiple Locus Variable Number Tandem Repeat Analysis (MLVA) for Typing Pseudomonas Aeruginosa Isolated from Urine Samples of Different Patients

BACKGROUND AND OBJECTIVE: Pseudomonas aeruginosa is considered as one of the important causes of urinary infections in hospitals. The aim of the current study is the genetic typing for the number of bacterial strains isolated from patients using MLVA technique. METHODS: In this study, 70 isolates were collected from different hospitals located in Tehran city. First, DNA extraction was conducted for genotyping analysis by MLVA method. Subsequently, VNTR sequences located in several genes of bacterial genomes such as MS-214, MS-215, MS-217, MS-222, MS-223, MS-142 and MS-173 were amplified by specific primers using PCR technique. After confirming the PCR amplification using electrophoresis and visualization of their bonds on agarose gel, relationship evolutionary graph for the different strains was constructed based on MLVA technique. FINDINGS: After the electrophoresis of PCR products and determination of VNTR copy-numbers, 70 strains were classified as 39 types and genetic evolutionary tree was also constructed based on VNTRs Data. According to the MST algorithm, 70 clinical strains divided into 11 clonal complexes which these criteria is interpreted as genetic distance based on the difference of VNTR copy numbers for each group. CONCLUSION: The present study showed that MLVA could be helpful for typing clinical strains of P. aeruginosa. The results also showed that this method had great potential to differentiate those strains with high phenotypic similarity

WhoLoDancE: Towards a methodology for selecting Motion Capture Data across different Dance Learning Practice

<p>In this paper we present the objectives and preliminary work of WhoLoDancE a Research and Innovation Action funded under the European Union‘s Horizon 2020 programme, aiming at using new technologies for capturing and analyzing dance movement to facilitate whole-body interaction learning experiences for a variety of dance genres. Dance is a diverse and heterogeneous practice and WhoLoDancE will develop a protocol for the creation and/or selection of dance sequences drawn from different dance styles for different teaching and learning modalities. As dance learning practice lacks standardization beyond dance genres and specific schools and techniques, one of the first project challenges is to bring together a variety of dance genres and teaching practices and work towards a methodology for selecting the appropriate shots for motion capturing, to acquire kinetic material which will provide a satisfying proof of concept for Learning scenarios of particular genres. The four use cases we are investigating are 1) classical ballet, 2) contemporary dance, 3) flamenco and 4) Greek folk dance.</p

Brief oral health promotion intervention among parents of young children to reduce early childhood dental decay

Background: Severe untreated dental decay affects a child’s growth, body weight, quality of life as well as cognitive development, and the effects extend beyond the child to the family, the community and the health care system. Early health behavioural factors, including dietary practices and eating patterns, can play a major role in the initiation and development of oral diseases, particularly dental caries. The parent/caregiver, usually the mother, has a critical role in the adoption of protective health care behaviours and parental feeding practices strongly influence children’s eating behaviours. This study will test if an early oral health promotion intervention through the use of brief motivational interviewing (MI) and anticipatory guidance (AG) approaches can reduce the incidence of early childhood dental decay and obesity. Methods: The study will be a randomised controlled study with parents and their new-born child/ren who are seen at 6–12 weeks of age by a child/community health nurse. Consenting parents will complete a questionnaire on oral health knowledge, behaviours, self-efficacy, oral health fatalism, parenting stress, prenatal and peri-natal health and socio-demographic factors at study commencement and at 12 and 36 months. Each child–parent pair will be allocated to an intervention or a standard care group, using a computer-generated random blocks. The standard group will be managed through the standard early oral health screening program; “lift the lip”. The intervention group will be provided with tailored oral health counselling by oral health consultants trained in MI and AG. Participating children will be examined at 24, and 36 months for the occurrence of dental decay and have their height and weight recorded. Dietary information obtained from a food frequency chart will be used to determine food and dietary patterns. Data analysis will use intention to treat and per protocol analysis and will use tests of independent proportions and means. Multivariate statistical tests will also be used to take account of socio-economic and demographic factors in addition to parental knowledge, behaviour, self-efficacy, and parent/child stress. Discussion: The study will test the effects of an oral health promotion intervention to affect oral health and general health and have the potential to demonstrate the "common risk factor" approach to health promotion.Peter Arrow, Joseph Raheb and Margaret Mille

HCI challenges in Dance Education

Dance learning is by nature multimodal, while dance practice presents a wide diversity across genres and contexts. Choreography and artistic contemporary dance performances have been using interactive technologies to support their creative process for several decades. Nevertheless the use of interactive technologies to support dance learning and education is still relatively immature and raises many challenges and interesting questions when it comes to choosing the appropriate human computer interaction methods. In this paper, we present the characteristics of dance teaching and learning in relation to interactive technology and we highlight the points/feedback that dance, as a field of mastering expressive movement, can bring to the design of whole-body interaction experiences

Dance interactive learning systems: A study on interaction workflow and teaching approaches

Motion Capture and whole-body interaction technologies have been experimentally proven to contribute to the enhancement of dance learning and to the investigation of bodily knowledge, innovating at the same time the practice of dance. Designing and implementing a dance interactive learning system with the aim to achieve effective, enjoyable, and meaningful educational experiences is, however, a highly demanding interdisciplinary and complex problem. In this work, we examine the interactive dance training systems that are described in the recent bibliography, proposing a framework of the most important design parameters, which we present along with particular examples of implementations. We discuss the way that the different phases of a common workflow are designed and implemented in these systems, examining aspects such as the visualization of feedback to the learner, the movement qualities involved, the technological approaches used, as well as the general context of use and learning approaches. Our aim is to identify common patterns and areas that require further research and development toward creating more effective and meaningful digital dance learning tools. © 2019 Association for Computing Machinery. All rights reserved

Towards a general framework for the annotation of dance motion sequences: A framework and toolkit for collecting movement descriptions as ground-truth datasets

In this paper, we present a conceptual framework and toolkit for movement annotation. We explain how the design of the annotation systems, based on the framework, if combined with specific strategies for the process of annotation, can enhance the collection of ground-truth datasets for training algorithms. Computational algorithms, such as machine learning, show promising results for massive and scalable automatic movement annotation. Nevertheless, the need for reliable ground-truth datasets annotated by human experts, to train the machine learning algorithms and for bridging the gap between machine measurable and human perceived expressive aspects remains an open issue. This need constitutes a challenging task, due to the complexity of human movement and diversity of possible descriptors, as well as the high subjectivity that accompanies movement characterisation by both experts and non-expert users. We contribute to addressing this problem, by proposing a conceptual framework for dance movement manual annotation which we evaluate through the development and deployment of the toolkit. Finally, we discuss how the different design choices affect the process and the reliability of collecting data sets regarding qualitative aspects of movement. © 2022, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature