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1. Genomics and the Contrasting Dynamics of Annual and Perennial Domestication

   https://doi.org/10.1016/j.tig.2015.10.002  

   Gaut, Brandon S.; Díez, Concepción M.; Morrell, Peter L. (December 2015, Trends in Genetics)
2. Abstracts From the 2018 Annual Meeting

   https://doi.org/10.1177/1545968318817151  

   Augenstein, T; Washabaugh, E; Remy, C; Krishnan, C (November 2018, Neurorehabilitation and Neural Repair)

   Muscle weakness and loss of independent joint control are the 2 most common neuromotor impairments after stroke. While there are a number of approaches to improve poststroke muscle weakness, there are currently no rehabilitation strategies that directly target a patient’s inability to match and independently activate the normal patterned muscle coordination strategies, or “muscle synergies.” Our goal is to develop an EMG-based controller for retraining healthy muscle synergies in patients with stroke-related disabilities. The controller can be integrated into rehabilitation robots for their ability to structure the robot’s force output based on input EMG activity. However, developing such a controller would require a clear understanding of the relationship between the applied force from a rehabilitation robot and the resulting changes to a patient’s muscle synergies. Therefore, this study was performed to quantify how the muscle synergies of horizontal planar-reaching are affected by direction of an applied force at the end-effector (ie, hand). A 2 DOF, 10 muscle model was developed in MATLAB using parameters obtained from the OpenSim (version 3.3) open source software system. Simulation experiments were then performed in MATLAB to investigate the relationship between the applied force and the resulting muscle synergies. The simulated event was composed of several trials of the same righthanded, planar, multidirectional reaching task from 0° (to the right) to 360°. Each trial applied a different steering force direction at the subject’s hand, varying from −45° to 45° relative to the reaching direction. The simulation trials were also validated by evaluating the EMG patterns of a healthy subject when performing the same reaching task with varying steering force directions. For the 0° steering force trials, the muscle synergies and their activation timings were extracted using nonnegative matrix factorization (NMF). For all other trials, the synergy matrix was fixed and the activation timings were extracted from the product of the EMG of that trial and the pseudo-inverse of the synergy matrix from the 0° steering force trial. By fixing the synergy matrix in the trials with steering forces, we can directly track activation changes of a certain synergy as steering force is varied. For both simulation and experimental trials, circular statistics revealed a linear relationship between changes in steering force direction and principal direction of synergy activation. These results suggest that the activation of a synergy can be controlled directly by the direction of an applied steering force. This has relevant implications in synergy-based controller design because a computer can easily manipulate a patient’s muscle synergies and track the changes while avoiding the computational expense of NMF. In addition, similar analysis could be used to extract the relationship between applied forces and changes in synergies for other types of motion. 

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3. Abstracts from the 2018 OAS Annual Meeting

   https://doi.org/10.18061/ojs.v118i1.6338  

   Ohio Academy of Science, The (March 2018, The Ohio Journal of Science)

   Abstracts from the 2018 Ohio Academy of Science Annual Meeting 

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4. Proceedings of the 2019 IISE Annual Conference

   Paul, Shubra; Davis, Lauren (May 2019, Predicting Food Donor Contribution Behavior Using Support Vector Regression)

   Hunger and food insecurity are present in each American county. Government and non-government organizations are working to address food insecurity in the United States. Food banks are nonprofit hunger relief organizations that collect food and monetary donations from donors and distribute food to local agencies which serve people in need. Contributions come from retail donors, communities, and food manufacturers. The uncertainty of donation amounts and frequency is a challenge for food banks in the fight against hunger. In this research, we analyze local food bank donation data and propose a predictive model to forecast the contribution of different donors. Our study shows the necessary behavioral attributes to classify donors and the best way to cluster donor data to improve the prediction model. We also compare the accuracy of prediction for different conventional forecasting techniques with the proposed Support Vector Regression (SVR) model. 

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5. Proceedings of the 2018 IISE annual conference

   Islam, M.; Ivy, J. (May 2018, Modeling for Efficient Assignment of Multiple Distribution Centers for the Equitable and Effective Distribution of Donated Food)

   Food insecurity affects more than 41 million people annually in the United States. Within the Feeding America network, approximately 200 food banks are working throughout the US to serve people in need with donated food. Satisfying hunger need of food insecure people with limited supply is a challenge for these food banks. A numerical study is performed on data from Food Bank of Central and Eastern North Carolina (FBCENC) to capture the major attributes controlling its food distribution system. FBCENC seeks to distribute donated food equitably so that each service area (county) receives food proportional to its demand while minimizing the undistributed food donations. In addition to seeking equitable and effective food distribution policies, FBCENC wants to identify distribution branches to maximize the accessibility of the counties to donated food. An assignment and distribution model is developed to minimize the cost of maintaining a user-specified cap on the maximum inequity in food distribution. A sensitivity analysis between the user-specified maximum inequity cap and effectiveness shows the effectiveness of donated food distribution can be improved significantly by sacrificing equitable distribution slightly. 

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