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1. 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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2. Proceedings of the IISE 2019 Annual Conference

   Odubela, Kehinde; Jiang, Steven; Delpish, Ritson; Davis, Lauren (May 2019, Effect of underlying factors on food distribution forecasts using visual analytics)

   Non-profit hunger relief organizations rely on the goodwill of donors for their in-kind cash, food donations and other supplies to alleviate hunger, reduce human suffering and save lives. However, these organizations struggle with changing demand and supply patterns, disruptions caused by very low donations even though they must make strategic distribution decisions. Food distribution forecasts based on times series models can be useful for these decisions. Yet, it is plausible that food distribution by hunger relief organizations (and demand by the people in need) are driven by certain underlying factors. In this research, we used Visual Analytics (VA) to study the effect of certain underlying factors on the forecast generated for food distribution to the aid recipients. Specifically, we used already tested forecasting techniques to predict the expected quantity of distributed food for the underlying factors identified. 

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3. "We need a better system": Maryland crop growers' perspectives on reducing food loss through donation

   https://doi.org/10.5304/jafscd.2023.124.002  

   Ceryes, Caitlin; Heley, Kathryn; Edwards, Danielle; Gao-Rittenberg, Chergai; Seifu, Leah; Khan Sohail, Saifra; Neff, Roni (January 2023, Journal of Agriculture, Food Systems, and Community Development)

   The donation of unharvested or unsold crops to rescue organizations has been promoted as a strat­egy to improve healthy food access for food inse­cure households while reducing production-level food loss and waste (FLW). In this study, we aimed to assess the motivations, barriers, and facili­tators for crop donation as a FLW reduction strat­egy among Maryland farmers. We interviewed 18 Maryland-based food producers (nine frequent crop donors and nine infrequent, by self-report) in 2016 – 2017, soliciting their perspectives on crop donation motivators, process feasibility, and inte­r­ventions aimed at increasing crop donation. The interviews were thematically coded. All respond­ents were aware of crop donation as an option, and most expressed interest in reducing FLW by divert­ing crop surpluses for human consumption. While financial barriers represented one aspect influenc­ing donation decisions, respondents also cited con­venience, process knowledge, and liability as key considerations. In contrast to frequent donors, many of whom considered donation a moral imperative, some infrequent donors questioned the expectation that they would donate crops without compensation. Both frequent and infrequent donors were aware of pro-donation tax incentives, and infrequent donors reported being unlikely to use them. This research demonstrates that crop donation motivations, barriers, and facilitators can be diverse. Given the existence of crop surpluses and their potential benefits as emergency food, our results suggest that multiple interventions and poli­cies may contribute to incentivizing and facilitating crop donation (or enabling the purchase of surplus crops) rather than one-size-fits-all approaches. Our findings also highlight a need to prioritize crop recovery methods that enhance growers’ financial stability. 

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4. Predicting and optimizing the fair allocation of donations in hunger relief supply chains

   https://doi.org/10.1016/j.ijforecast.2024.06.004  

   Sharmile, Nowshin; Nuamah, Isaac A; Davis, Lauren; Samanlioglu, Funda; Jiang, Steven; Crain, Carter (July 2024, International Journal of Forecasting)

   Non-profit hunger relief organizations primarily depend on donors’ benevolence to help alleviate hunger in their communities. However, the quantity and frequency of donations they receive may vary over time, thus making fair distribution of donated supplies challenging. This paper presents a hierarchical forecasting methodology to determine the quantity of food donations received per month in a multi-warehouse food aid network. We further link the forecasts to an optimization model to identify the fair allocation of donations, considering the network distribution capacity in terms of supply chain coordination and flexibility. The results indicate which locations within the network are under-served and how donated supplies can be allocated to minimize the deviation between overserved and underserved counties. 

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5. A comparison of structure, bonding and non-covalent interactions of aryl halide and diarylhalonium halogen-bond donors

   https://doi.org/10.3762/bjoc.20.125  

   Javaly, Nicole; McCormick, Theresa M; Stuart, David R (January 2024, Beilstein Journal of Organic Chemistry)

   Halogen bonding permeates many areas of chemistry. A wide range of halogen-bond donors including neutral, cationic, monovalent, and hypervalent have been developed and studied. In this work we used density functional theory (DFT), natural bond orbital (NBO) theory, and quantum theory of atoms in molecules (QTAIM) to analyze aryl halogen-bond donors that are neutral, cationic, monovalent and hypervalent and in each series we include the halogens Cl, Br, I, and At. Within this diverse set of halogen-bond donors, we have found trends that relate halogen bond length with the van der Waals radii of the halogen and the non-covalent or partial covalency of the halogen bond. We have also developed a model to calculate ΔGof halogen-bond formation by the linear combination of the % p-orbital character on the halogen and energy of the σ-hole on the halogen-bond donor. 

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