A Case Study of the "Who is NOBODY?" Project: A Character Development Program for Children with Learning Disabilities

This research study explored a support system for children with learning disabilities. The Learning Disabilities Association of Niagara Region (LDANR) recently expanded its Better Emotional and Social Times (B.E.S.T.) program to incorporate an innovative, character education initiative called the “Who is NOBODY?” program. The objective of this qualitative case study was two-fold. First, the study aimed to support the LDANR in assessing the efficacy of the “Who is NOBODY?” program, providing the LDANR with empirical support for their programs. Second, the study enabled a more in-depth understanding of how to best support children with LD in regards to their social and emotional well-being. The study explored the “Who is NOBODY?” program through three lenses: design, implementation, and experiences of participating children. Three primary themes emerged from these three data lenses: positive character traits, prosocial behaviour, and strong self-efficacy – leading to the promotion of strong character development and self-esteem. Taken together, the “Who is NOBODY?” program was shown to be a successful remediation program for supporting vulnerable children with LD.

The Clinical Translation Gap in Child Health Exercise Research: A Call for Disruptive Innovation

In children, levels of play, physical activity, and fitness are key indicators of health and disease and closely tied to optimal growth and development. Cardiopulmonary exercise testing (CPET) provides clinicians with biomarkers of disease and effectiveness of therapy, and researchers with novel insights into fundamental biological mechanisms reflecting an integrated physiological response that is hidden when the child is at rest. Yet the growth of clinical trials utilizing CPET in pediatrics remains stunted despite the current emphasis on preventative medicine and the growing recognition that therapies used in children should be clinically tested in children. There exists a translational gap between basic discovery and clinical application in this essential component of child health. To address this gap, the NIH provided funding through the Clinical and Translational Science Award (CTSA) program to convene a panel of experts. This report summarizes our major findings and outlines next steps necessary to enhance child health exercise medicine translational research. We present specific plans to bolster data interoperability, improve child health CPET reference values, stimulate formal training in exercise medicine for child health care professionals, and outline innovative approaches through which exercise medicine can become more accessible and advance therapeutics across the child health spectrum.

Properties and Algorithms of the KCube Interconnection Networks

The KCube interconnection network was first introduced in 2010 in order to exploit the good characteristics of two well-known interconnection networks, the hypercube and the Kautz graph. KCube links up multiple processors in a communication network with high density for a fixed degree. Since the KCube network is newly proposed, much study is required to demonstrate its potential properties and algorithms that can be designed to solve parallel computation problems. In this thesis we introduce a new methodology to construct the KCube graph. Also, with regard to this new approach, we will prove its Hamiltonicity in the general KC(m; k). Moreover, we will find its connectivity followed by an optimal broadcasting scheme in which a source node containing a message is to communicate it with all other processors. In addition to KCube networks, we have studied a version of the routing problem in the traditional hypercube, investigating this problem: whether there exists a shortest path in a Qn between two nodes 0n and 1n, when the network is experiencing failed components. We first conditionally discuss this problem when there is a constraint on the number of faulty nodes, and subsequently introduce an algorithm to tackle the problem without restrictions on the number of nodes.