Dynamic Modeling of Multi-Elastic Body Systems using Kane’s Method and Congruency Transformations

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Impacts of using a social robot to teach music to children with low-functioning autism

This article endeavors to present the impact of conducting robot-assisted music-based intervention sessions for children with low-functioning (LF) autism. To this end, a drum/xylophone playing robot is used to teach basic concepts of how to play the instruments to four participants with LF autism during nine educational sessions. The main findings of this study are compared to similar studies conducted with children with high-functioning autism. Our main findings indicated that the stereotyped behaviors of all the subjects decreased during the course of the program with an approximate large Cohen’s d effect size. Moreover, the children showed some improvement in imitation, joint attention, and social skills from the Pre-Test to Post-Test. In addition, regarding music education, we indicated that while the children could not pass a test on the music notes or reading music phrases items because of their cognitive deficits, they showed acceptable improvements (with a large Cohen’s d effect size) in the Stambak Rhythm Reproduction Test, which means that some rhythm learning occurred for the LF participants. In addition, we indicated that parenting stress levels decreased during the program. This study presents some potential possibilities of performing robot-assisted interventions for children with LF autism

Drosophila Muller F Elements Maintain a Distinct Set of Genomic Properties Over 40 Million Years of Evolution

The Muller F element (4.2 Mb, ~80 protein-coding genes) is an unusual autosome of Drosophila melanogaster; it is mostly heterochromatic with a low recombination rate. To investigate how these properties impact the evolution of repeats and genes, we manually improved the sequence and annotated the genes on the D. erecta, D. mojavensis, and D. grimshawi F elements and euchromatic domains from the Muller D element. We find that F elements have greater transposon density (25–50%) than euchromatic reference regions (3–11%). Among the F elements, D. grimshawi has the lowest transposon density (particularly DINE-1: 2% vs. 11–27%). F element genes have larger coding spans, more coding exons, larger introns, and lower codon bias. Comparison of the Effective Number of Codons with the Codon Adaptation Index shows that, in contrast to the other species, codon bias in D. grimshawi F element genes can be attributed primarily to selection instead of mutational biases, suggesting that density and types of transposons affect the degree of local heterochromatin formation. F element genes have lower estimated DNA melting temperatures than D element genes, potentially facilitating transcription through heterochromatin. Most F element genes (~90%) have remained on that element, but the F element has smaller syntenic blocks than genome averages (3.4–3.6 vs. 8.4–8.8 genes per block), indicating greater rates of inversion despite lower rates of recombination. Overall, the F element has maintained characteristics that are distinct from other autosomes in the Drosophila lineage, illuminating the constraints imposed by a heterochromatic milieu

Socially Assistive Robots Serving Children with Special Needs (Autism, Cancer, Deafness/Hearing Loss)

One of the main challenges in social and cognitive research is relevant to our understanding of how to perceive and interact with others in the world around us. With the dramatic growth of emerging technologies in our societies, such as social robots, computer graphic generated avatars, and virtual reality devices, the complexity of this challenge is growing. As a result, interdisciplinary educators and researchers strive to determine the extent neurocognitive mechanisms, which support human interaction with artificial agents and tools, have evolved. Hence, a growing number of researchers working within the field of social robotics and engineering are engaged in collaboration with other scientists to utilize their expertise in social cognition, neuroscience, linguistics, and psychology with mutual interests that benefits naturally developing children as well as children with some form of disability and/or illness (i.e. Kids with: autism, cancer, deafness/hearing loss, down syndrome, diabetes, etc.). With the advancement of robotics technology, robots applications have been extended to more general-purpose practices in society such as: the use of robots in clinical and rehabilitation, nursing and elderly care, search and rescue operations, etc. However, for robotics technology to be successful in such environments it is necessary to gain new levels of strength, robustness, physical skills, and improved cognitive ability and intelligence. One faces many challenges on the path to design and construction of social-cognitive robots, the biggest is to build robots that comply with the needs and expectations of the human mind. How we communicate with machines with a higher quality physical and life-like appearance would differ with the way we interact with a computer, cell phone, or other smart devices. Therefore, as a follow up to the classical view of robotic systems, “socially interactive robots” with the capability of engaging social scenarios and interacting with humans have recently become a trendy and upto- date topic. In recent years, the impacts of employing social robots as teaching assistants on enhancing learners’ achievements notably in children with special needs were investigated by various researchers. In addition, these robots can be effectively employed in diverse healthcare applications. For instance, the positive effects of utilizing social robots in decreasing the distress level of children with cancer through establishing affective connection with patients was highlighted. Furthermore, they have been successfully utilized to improve the imitation skills of children with Autism Spectrum Disorder (ASD), which is known to be one of the core symptoms. In addition, social robots have been designed to play an assistive role in expanding the communication level of deaf and ordinary children in teaching them Sign Language. For instance, it has been noted that for social robots to achieve success in their mission, adaptive user interfaces lead to greater user acceptance and increased teaching efficiency compared to non-adaptive ones. Hence, one need to design and build a robotic architecture capable of simultaneously adjusting the robot’s teaching parameters according to both the user’s past and present performance, adapt the content of training, and then implement it on the social robot to teach sign language based on these parameters in a manner similar to a human teacher. On the other hand, empowering a robot to direct its attention to the most appropriate target at all times during multi-party interactions is another interesting and useful task to establish natural communication between the robot and users. Implementing a social gaze control system suitable for multiperson interactions with the social robot is another challenging topic, which may be done such that the system takes some important verbal and non-verbal social cues into account and at each moment enable the robot to decide socially at which human it should direct its gaze.</jats:p