Feedback (F) Fueling Adaptation (A) Network Growth (N) and Self-Organization (S): A Complex Systems Design and Evaluation Approach to Professional Development

This paper reports on the efficacy of a professional development framework premised on four complex systems design principles: Feedback, Adaptation, Network Growth and Self-organization (FANS). The framework is applied to the design and delivery of the first two years of a three-year study aimed at improving teacher and student understanding of computational modeling tools. We demonstrate that structuring a professional development program around the FANS framework facilitates the development of important strategies and processes for program organizers such as the identification of salient system variables, effectively distributing expertise, adaptation and improvement of professional development resources and activities and building technological, human and social capital. For participants, there is evidence to show that the FANS framework encourages: professional goal setting, engagement in a strong professional community and personal autonomy by enabling individualized purpose—all fundamental components in promoting self-organization. We discuss three meta-level themes that may account for the success of the FANS framework: structure vs. agency, exploration vs. exploitation and short-term vs. long-term goals. Each illustrates the tension that exists between competing variables that need to be considered in order to work effectively in real world complex educational systems

Food and Nutrition Research Institute, Philippines

Poster created by students in the 2016 IWU Freeman Asia Internship Program

Are dual and single exposures differently associated with clinical levels of trauma symptoms? Examining physical abuse and witnessing intimate partner violence among young children

A significant portion of children living in the United States have experienced trauma. Informed by the developmental traumatology model, we explored the effects of physical abuse and witnessing intimate partner violence (IPV) on childhood trauma symptoms. This study utilizes a convenience sample of 580 high- risk children between 3 and 12 years who received services from one- child advocacy centre during a 12- month period. We performed a series of binary logistic regression analyses to examine if physical abuse, exposure to IPV, and dual exposure (i.e., both physical abuse and IPV) are distinctly associated with six trauma symptoms, including anxiety, depression, posttraumatic stress (PTS), dissociation, anger, and sexual concerns. The results indicated that dual exposure was predictive of all trauma symptoms, except for dissociation. Additionally, physical abuse was associated with PTS, anger, and sexual concerns, whereas exposure to IPV was associated with depression, PTS, and sexual concerns. Research and implications for practitioners working with young children are discussed.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/154965/1/cfs12700.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/154965/2/cfs12700_am.pd

Identifying Bayesian Optimal Experiments for Uncertain Biochemical Pathway Models

Pharmacodynamic (PD) models are mathematical models of cellular reaction networks that include drug mechanisms of action. These models are useful for studying predictive therapeutic outcomes of novel drug therapies in silico. However, PD models are known to possess significant uncertainty with respect to constituent parameter data, leading to uncertainty in the model predictions. Furthermore, experimental data to calibrate these models is often limited or unavailable for novel pathways. In this study, we present a Bayesian optimal experimental design approach for improving PD model prediction accuracy. We then apply our method using simulated experimental data to account for uncertainty in hypothetical laboratory measurements. This leads to a probabilistic prediction of drug performance and a quantitative measure of which prospective laboratory experiment will optimally reduce prediction uncertainty in the PD model. The methods proposed here provide a way forward for uncertainty quantification and guided experimental design for models of novel biological pathways

Super-resolution imaging of fluorescently labeled, endogenous RNA Polymerase II in living cells with CRISPR/Cas9-mediated gene editing

Live cell imaging of mammalian RNA polymerase II (Pol II) has previously relied on random insertions of exogenous, mutant Pol II coupled with the degradation of endogenous Pol II using a toxin, α-amanitin. Therefore, it has been unclear whether over-expression of labeled Pol II under an exogenous promoter may have played a role in reported Pol II dynamics in vivo. Here we label the endogenous Pol II in mouse embryonic fibroblast (MEF) cells using the CRISPR/Cas9 gene editing system. Using single-molecule based super-resolution imaging in the living cells, we captured endogenous Pol II clusters. Consistent with previous studies, we observed that Pol II clusters were short-lived (cluster lifetime ~8 s) in living cells. Moreover, dynamic responses to serum-stimulation, and drug-mediated transcription inhibition were all in agreement with previous observations in the exogenous Pol II MEF cell line. Our findings suggest that previous exogenously tagged Pol II faithfully recapitulated the endogenous polymerase clustering dynamics in living cells, and our approach may in principle be used to directly label transcription factors for live cell imaging.National Cancer Institute (U.S.) (Award DP2CA195769)Massachusetts Institute of Technology. Department of Physic

A Decade of Supply Chain Management Literature: Past, Present and Future Implications

This study covers a decade of academic research in the Supply Chain Management (SCM) field, offering an in-depth analytical review focused on the existing trends and gaps in the supply chain literature. Nine academic journals were investigated and a subject categorization is developed for SCM research. A content analysis was then conducted on 405 articles, focusing on the categories covered within the SCM literature, various levels of the chain examined and sample populations and industries studied, as well as the research methods employed. Finally, a conceptual framework of the most highly researched categories in SCM indicates that there is a need for more research that seeks to understand the nature of multiple links in SCM chains and networks, as opposed to focusing on dyadic and inter-firm relationships

The Path to Graduate School in Science and Engineering for Underrepresented Students of Color

Over the past decade, the numnber of Black, Hispanic, and American Indian/Alaska Native students attaining bachelor\u27s degrees in science and engineering fields has increased substantially. In 2004, 13.9% of all bachelor\u27s degrees in science and engineering fields were awarded to students from these three groups, up from 11.2% in 1995 (Hill & Green, 2007). Although Blacks, Hispanics, and American Indians continue to be underrepresented among bachelor\u27s degree recipients in science and engineering fields relative to their representation among all bachelor\u27s degree recipients (13.9% versus 16.9% in 2004, Hill & Green, 2007), these trends suggest that progress is being made