College of Engineering (COE)
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Note: The Department of Biological Systems Engineering is listed within the College of Agriculture and Life Sciences (CALS).
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Browsing College of Engineering (COE) by Content Type "Editorial material"
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- Algorithm-derived feature representations for explainable AI in catalysisOmidvar, Noushin; Xin, Hongliang (Elsevier, 2021-12-01)Machine learning (ML) has emerged as a critical tool in catalysis, attributed to its capability of finding complex patterns in high dimensional and heterogeneous data. A recently published article in Chem Catalysis (Esterhuizen et al.) used unsupervised ML for uncovering electronic and geometric descriptors of the surface reactivity of metal alloys and oxides.
- Celebrate the 10th Anniversary of IEEE Electrification Magazine and Embrace a New EraRahman, Saifur (IEEE, 2023-09)
- Editorial: Local Hydrodynamics of Benthic Marine OrganismsStaples, Anne E.; Miller, Laura A.; Khatri, Shilpa; Hossain, Md Monir (Frontiers, 2023-03-28)
- Editorial: Multiscale soft tissue biomechanics and cell mechanobiology: Towards coupling extracellular biophysical cues and cellular functionKim, Oleg V.; Li, Xuejin; Baljon, Arlette R. C. (Frontiers, 2022-11-17)
- First person - Mary SalcedoSalcedo, Mary (2019-10)First Person is a series of interviews with the first authors of a selection of papers published in Biology Opens, helping early-career researchers promote themselves alongside their papers. Mary Salcedo is first author on 'Computational analysis of size, shape and structure of insect wings', published in BiO. Mary conducted the research described in this article while a Graduate Student in L. Mahadevan's lab at Harvard University, Cambridge, USA. She is now a NSF Postdoctoral Researcher in Biology in the lab of Jake Socha at Virginia Tech, USA, investigating insect wing shapes, venation patterns and circulation within the wings.
- IEEE Access Special Section: Intelligent Data Sensing, Collection, and Dissemination in Mobile ComputingLiu, Xuxun; Liu, Anfeng; Tadrous, John; He, Ligang; Ji, Bo; Zheng, Zhongming (IEEE, 2020)
- Opinion: Mathematical models: A key tool for outbreak responseLofgren, Eric T.; Halloran, M. Elizabeth; Rivers, Caitlin; Drake, John M.; Porco, Travis C.; Lewis, Bryan L.; Yang, Wan; Vespignani, Alessandro; Shaman, Jeffrey; Eisenberg, Joseph N.S.; Eisenberg, Marisa C.; Marathe, Madhav V.; Scarpino, Samuel V.; Alexander, Kathleen A.; Meza, Rafael; Ferrari, Matthew J.; Hyman, James M.; Meyers, Lauren Ancel; Eubank, Stephen (NAS, 2015-01-13)The 2014 outbreak of Ebola in West Africa is unprecedented in its size and geographic range, and demands swift, effective action from the international community. Understanding the dynamics and spread of Ebola is critical for directing interventions and extinguishing the epidemic; however, observational studies of local conditions have been incomplete and limited by the urgent need to direct resources to patient care. Mathematical and computational models can help address this deficiency through work with sparse observations, inference on missing data, and incorporation of the latest information. These models can clarify how the disease is spreading and provide timely guidance to policymakers. However, the use of models in public health often meets resistance (1), from doubts in peer review about the utility of such analyses to public skepticism that models can contribute when the means to control an epidemic are already known (2). Even when they are discussed in a positive light, models are often portrayed as arcane and largely inaccessible thought experiments (3). However, the role of models is crucial: they can be used to quantify the effect of mitigation efforts, provide guidance on the scale of interventions required to achieve containment, and identify factors that fundamentally influence the course of an outbreak.
- Recognizing and controlling airborne transmission of SARS-CoV-2 in indoor environmentsAllen, Joseph G.; Marr, Linsey C. (Wiley, 2020-07-01)Sharing indoor space has been confirmed as a major risk factor in transmission of SARS-CoV-2. A study of over 7000 cases found that all outbreaks involving three or more people occurred indoors. Thus, identifying the dominant modes of transmission is an urgent public health priority so that appropriate control strategies can be selected and deployed. Here, we present three lines of evidence supporting the potential for airborne transmission and recommend steps to mitigate the risk in indoor environments.