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1. Scattering Delay Mitigation in High-accuracy Pulsar Timing: Cyclic Spectroscopy Techniques

   https://doi.org/10.3847/1538-4357/acb6fd  

   Turner, Jacob E.; Stinebring, Daniel R.; McLaughlin, Maura A.; Archibald, Anne M.; Dolch, Timothy; Lynch, Ryan S. (February 2023, The Astrophysical Journal)

   Abstract We simulate scattering delays from the interstellar medium to examine the effectiveness of three estimators in recovering these delays in pulsar timing data. Two of these estimators use the more traditional process of fitting autocorrelation functions to pulsar dynamic spectra to extract scintillation bandwidths, while the third estimator uses the newer technique of cyclic spectroscopy on baseband pulsar data to recover the interstellar medium’s impulse response function. We find that either fitting a Lorentzian or Gaussian distribution to an autocorrelation function or recovering the impulse response function from the cyclic spectrum are, on average, accurate in recovering scattering delays, although autocorrelation function estimators have a large variance, even at high signal-to-noise ratio (S/N). We find that, given sufficient S/N, cyclic spectroscopy is more accurate than both Gaussian and Lorentzian fitting for recovering scattering delays at specific epochs, suggesting that cyclic spectroscopy is a superior method for scattering estimation in high-quality data. 

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2. What Causes Delays in Admission to Rehabilitation Care? A Structural Estimation Approach

   https://doi.org/10.1287/msom.2022.0377  

   Dong, Jing; Görgülü, Berk; Sarhangian, Vahid (January 2024, Manufacturing & Service Operations Management)

   Problem definition: Delays in admission to rehabilitation care can adversely impact patient outcomes. In addition, delayed patients keep occupying their acute care beds, making them unavailable for incoming patients. Admission delays are mainly caused by a lack of rehabilitation bed capacity and the time required to plan for rehabilitation activities, which we refer to as processing times. Because of non-standard bed allocation decisions and data limitations in practice, quantifying the magnitude of the two sources of delays can be technically challenging yet critical to the design of evidence-based interventions to reduce delays. We propose an empirical approach to understanding the contributions of the two sources of delays when only a single (combined) measure of admission delay is available. Methodology/results: We propose a hidden Markov model (HMM) to estimate the unobserved processing times and the status-quo bed allocation policy. Our estimation results quantify the magnitude of processing times versus capacity-driven delays and provide insights into factors impacting the bed allocation decision. We validate our estimated policy using a queueing model of patient flow and find that ignoring processing times or using simple bed allocation policies can lead to highly inaccurate delay estimates. In contrast, our estimated policy allows for accurate evaluation of different operational interventions. We find that reducing processing times can be highly effective in reducing admission delays and bed-blocking costs. In addition, allowing early transfer—whereby patients can complete some of their processing requirements in the rehabilitation unit—can significantly reduce admission delays, with only a small increase in rehab LOS. Managerial implications: Our study demonstrates the importance of quantifying different sources of delays in the design of effective operational interventions for reducing delays in admission to rehabilitation care. The proposed estimation framework can be applied in other transition-of-care settings with personalized capacity allocation decisions and hidden processing delays. History: This paper was selected for Fast Track in the M&SOM journal from the 2022 MSOM Healthcare SIG Conference. Funding: J. Dong was supported in part by the National Science Foundation [Grant CMMI-1762544]. V. Sarhangian was supported in part by the Natural Sciences and Engineering Research Council of Canada [Grant RGPIN-2018-04518] and the Connaught Fund. Supplemental Material: The e-companion is available at https://doi.org/10.1287/msom.2022.0377 . 

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3. On Robustness of Pre-Asymptotic Stability to Delayed Jumps in Hybrid Systems

   https://doi.org/10.23919/ACC.2018.8431127  

   Altin, Berk; Sanfelice, Ricardo G. (June 2018, 2018 American Control Conference)

   We show that pre-asymptotic stability of a compact set for a hybrid system is semiglobally and practically robust in the presence of delayed jumps under mild conditions on the data. More precisely, when the delay-free system has a pre-asymptotically stable compact set, it is shown that for small enough delays, solutions of the delayed system converge to a neighborhood of a set of interest related to the aforementioned compact set. Unlike prior work, this notion of practical stability also holds for time-varying delays in the presence of Zeno solutions. Simulation results of a state estimator with intermittent and delayed information validate the findings. 

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4. Simulation-Assisted Optimization for Large-Scale Evacuation Planning with Congestion-Dependent Delays

   Islam, K A; Chen, D Q; Marathe, M; Mortveit, H; Swarup, S; Vullikanti, A (August 2023, Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence (IJCAI-23))

   Evacuation planning is a crucial part of disaster management. However, joint optimization of its two essential components, routing and scheduling, with objectives such as minimizing average evacuation time or evacuation completion time, is a computationally hard problem. To approach it, we present MIP-LNS, a scalable optimization method that utilizes heuristic search with mathematical optimization and can optimize a variety of objective functions. We also present the method MIPLNS-SIM, where we combine agent-based simulation with MIP-LNS to estimate delays due to congestion, as well as, find optimized plans considering such delays. We use Harris County in Houston, Texas, as our study area. We show that, within a given time limit, MIP-LNS finds better solutions than existing methods in terms of three different metrics. However, when congestion dependent delay is considered, MIP-LNS-SIM outperforms MIP-LNS in multiple performance metrics. In addition, MIP-LNS-SIM has a significantly lower percent error in estimated evacuation completion time compared to MIP-LNS. 

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5. Partial copying and the role of diversity in social learning performance

   https://doi.org/10.1177/26339137221081849  

   Campbell, Chelsea M; Izquierdo, Eduardo J; Goldstone, Robert L (August 2022, Collective Intelligence)

   One major way that people engage in adaptive problem solving is by imitating others’ solutions. Prominent simulation models have found imperfect imitation advantageous, but the interactions between copying amount and other prevalent aspects of social learning strategies have been underexplored. Here, we explore the consequences for a group when its members engage in strategies with different degrees of copying, solving search problems of varying complexity, in different network topologies that affect the solutions visible to each member. Using a computational model of collective problem solving, we demonstrate that the advantage of partial copying is robust across these conditions, arising from its ability to maintain diversity. Partial copying delays convergence generally but especially in globally connected networks, which are typically associated with diversity loss, allowing more exploration of a problem space. We show that a moderate amount of diversity maintenance is optimal and strategies can be adjusted to find that sweet spot. 

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