The role of neutral Rh(PONOP)H, free NMe2H, boronium and ammonium salts in the dehydrocoupling of dimethylamine-borane using the cationic pincer [Rh(PONOP)(η2-H2)]+ catalyst

The σ-amine-borane pincer complex [Rh(PONOP)(η1-H3B·NMe3)][BArF4] [2, PONOP = κ3-NC5H3-2,6-(OPtBu2)2] is prepared by addition of H3B·NMe3 to the dihydrogen precursor [Rh(PONOP)(η2-H2)][BArF4], 1. In a similar way the related H3B·NMe2H complex [Rh(PONOP)(η1-H3B·NMe2H)][BArF4], 3, can be made in situ, but this undergoes dehydrocoupling to reform 1 and give the aminoborane dimer [H2BNMe2]2. NMR studies on this system reveal an intermediate neutral hydride forms, Rh(PONOP)H, 4, that has been prepared independently. 1 is a competent catalyst (2 mol%, ∼30 min) for the dehydrocoupling of H3B·Me2H. Kinetic, mechanistic and computational studies point to the role of NMe2H in both forming the neutral hydride, via deprotonation of a σ-amine-borane complex and formation of aminoborane, and closing the catalytic cycle by reprotonation of the hydride by the thus-formed dimethyl ammonium [NMe2H2]+. Competitive processes involving the generation of boronium [H2B(NMe2H)2]+ are also discussed, but shown to be higher in energy. Off-cycle adducts between [NMe2H2]+ or [H2B(NMe2H)2]+ and amine-boranes are also discussed that act to modify the kinetics of dehydrocoupling

A Predictive Multimodal Framework to Alert Caregivers of Problem Behaviors for Children with ASD (PreMAC)

Autism Spectrum Disorder (ASD) impacts 1 in 54 children in the US. Two-thirds of children with ASD display problem behavior. If a caregiver can predict that a child is likely to engage in problem behavior, they may be able to take action to minimize that risk. Although experts in Applied Behavior Analysis can offer caregivers recognition and remediation strategies, there are limitations to the extent to which human prediction of problem behavior is possible without the assistance of technology. In this paper, we propose a machine learning-based predictive framework, PreMAC, that uses multimodal signals from precursors of problem behaviors to alert caregivers of impending problem behavior for children with ASD. A multimodal data capture platform, M2P3, was designed to collect multimodal training data for PreMAC. The development of PreMAC integrated a rapid functional analysis, the interview-informed synthesized contingency analysis (IISCA), for collection of training data. A feasibility study with seven 4 to 15-year-old children with ASD was conducted to investigate the tolerability and feasibility of the M2P3 platform and the accuracy of PreMAC. Results indicate that the M2P3 platform was well tolerated by the children and PreMAC could predict precursors of problem behaviors with high prediction accuracies