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Intracellular Material Transport Simulation in Neurons Using Isogeometric Analysis and Deep LearningFree, publiclyaccessible full text available July 1, 2024

Free, publiclyaccessible full text available August 19, 2024

ABSTRACT Along their path from source to observer, gravitational waves may be gravitationally lensed by massive objects leading to distortion in the signals. Searches for these distortions amongst the observed signals from the current detector network have already been carried out, though there have as yet been no confident detections. However, predictions of the observation rate of lensing suggest detection in the future is a realistic possibility. Therefore, preparations need to be made to thoroughly investigate the candidate lensed signals. In this work, we present some followup analyses that could be applied to assess the significance of such events and ascertain what information may be extracted about the lenssource system by applying these analyses to a number of O3 candidate events, even if these signals did not yield a high significance for any of the lensing hypotheses. These analyses cover the strong lensing, millilensing, and microlensing regimes. Applying these additional analyses does not lead to any additional evidence for lensing in the candidates that have been examined. However, it does provide important insight into potential avenues to deal with highsignificance candidates in future observations.

Free, publiclyaccessible full text available January 1, 2024

In this paper, we show that the finite subalgebra A R ( 1 ) \mathcal {A}^\mathbb {R}(1) , generated by S q 1 \mathrm {Sq}^1 and S q 2 \mathrm {Sq}^2 , of the R \mathbb {R} motivic Steenrod algebra A R \mathcal {A}^\mathbb {R} can be given 128 different A R \mathcal {A}^\mathbb {R} module structures. We also show that all of these A \mathcal {A} modules can be realized as the cohomology of a 2 2 local finite R \mathbb {R} motivic spectrum. The realization results are obtained using an R \mathbb {R} motivic analogue of the Toda realization theorem. We notice that each realization of A R ( 1 ) \mathcal {A}^\mathbb {R}(1) can be expressed as a cofiber of an R \mathbb {R} motivic v 1 v_1 selfmap. The C 2 {\mathrm {C}_2} equivariant analogue of the above results then follows because of the Betti realization functor. We identify a relationship between the R O ( C 2 ) \mathrm {RO}({\mathrm {C}_2}) graded Steenrod operations on a C 2 {\mathrm {C}_2} equivariant space and the classical Steenrod operations on both its underlying space and its fixedpoints. This technique is then used to identify the geometric fixedpoint spectra of the C 2 {\mathrm {C}_2} equivariant realizations of A C 2 ( 1 ) \mathcal {A}^{\mathrm {C}_2}(1) . We find another application of the R \mathbb {R} motivic Toda realization theorem: we produce an R \mathbb {R} motivic, and consequently a C 2 {\mathrm {C}_2} equivariant, analogue of the BhattacharyaEgger spectrum Z \mathcal {Z} , which could be of independent interest.more » « less

Free, publiclyaccessible full text available October 1, 2024

In response to COVID19, many countries have mandated social distancing and banned large group gatherings in order to slow down the spread of SARSCoV2. These social interventions along with vaccines remain the best way forward to reduce the spread of SARS CoV2. In order to increase vaccine accessibility, states such as Virginia have deployed mobile vaccination centers to distribute vaccines across the state. When choosing where to place these sites, there are two important factors to take into account: accessibility and equity. We formulate a combinatorial problem that captures these factors and then develop efficient algorithms with theoretical guarantees on both of these aspects. Furthermore, we study the inherent hardness of the problem, and demonstrate strong impossibility results. Finally, we run computational experiments on realworld data to show the efficacy of our methods.more » « less

ABSTRACT Efficient contact tracing and isolation is an effective strategy to control epidemics, as seen in the Ebola epidemic and COVID19 pandemic. An important consideration in contact tracing is the budget on the number of individuals asked to quarantine—the budget is limited for socioeconomic reasons (e.g., having a limited number of contact tracers). Here, we present a Markov Decision Process (MDP) framework to formulate the problem of using contact tracing to reduce the size of an outbreak while limiting the number of people quarantined. We formulate each step of the MDP as a combinatorial problem, MinExposed, which we demonstrate is NPHard. Next, we develop two approximation algorithms, one based on rounding the solutions of a linear program and another (greedy algorithm) based on choosing nodes with a high (weighted) degree. A key feature of the greedy algorithm is that it does not need complete information of the underlying social contact network, making it implementable in practice. Using simulations over realistic networks, we show how the algorithms can help in bending the epidemic curve with a limited number of isolated individuals.more » « less

Efficient contact tracing and isolation is an effective strategy to control epidemics, as seen in the Ebola epidemic and COVID19 pandemic. An important consideration in contact tracing is the budget on the number of individuals asked to quarantine—the budget is limited for socioeconomic reasons (e.g., having a limited number of contact tracers). Here, we present a Markov Decision Process (MDP) framework to formulate the problem of using contact tracing to reduce the size of an outbreak while limiting the number of people quarantined. We formulate each step of the MDP as a combinatorial problem, MinExposed, which we demonstrate is NPHard. Next, we develop two approximation algorithms, one based on rounding the solutions of a linear program and another (greedy algorithm) based on choosing nodes with a high (weighted) degree. A key feature of the greedy algorithm is that it does not need complete information of the underlying social contact network, making it implementable in practice. Using simulations over realistic networks, we show how the algorithms can help in bending the epidemic curve with a limited number of isolated individuals.more » « less

Billard, A. ; Asfour, T. ; Khatib, O. (Ed.)Underwater navigation presents several challenges, including unstructured unknown environments, lack of reliable localization systems (e.g., GPS), and poor visibility. Furthermore, goodquality obstacle detection sensors for underwater robots are scant and costly; and many sensors like RGBD cameras and LiDAR only work inair. To enable reliable mapless underwater navigation despite these challenges, we propose a lowcost endtoend navigation system, based on a monocular camera and a fixed singlebeam echosounder, that efficiently navigates an underwater robot to waypoints while avoiding nearby obstacles. Our proposed method is based on Proximal Policy Optimization (PPO), which takes as input current relative goal information, estimated depth images, echosounder readings, and previous executed actions, and outputs 3D robot actions in a normalized scale. Endtoend training was done in simulation, where we adopted domain randomization (varying underwater conditions and visibility) to learn a robust policy against noise and changes in visibility conditions. The experiments in simulation and realworld demonstrated that our proposed method is successful and resilient in navigating a lowcost underwater robot in unknown underwater environments. The implementation is made publicly available at https://github.com/dartmouthrobotics/deeprluwrobotnavigation.more » « less