The Green Choice: Learning and Influencing Human Decisions on Shared Roads

Autonomous vehicles have the potential to increase the capacity of roads via platooning, even when human drivers and autonomous vehicles share roads. However, when users of a road network choose their routes selfishly, the resulting traffic configuration may be very inefficient. Because of this, we consider how to influence human decisions so as to decrease congestion on these roads. We consider a network of parallel roads with two modes of transportation: (i) human drivers who will choose the quickest route available to them, and (ii) ride hailing service which provides an array of autonomous vehicle ride options, each with different prices, to users. In this work, we seek to design these prices so that when autonomous service users choose from these options and human drivers selfishly choose their resulting routes, road usage is maximized and transit delay is minimized. To do so, we formalize a model of how autonomous service users make choices between routes with different price/delay values. Developing a preference-based algorithm to learn the preferences of the users, and using a vehicle flow model related to the Fundamental Diagram of Traffic, we formulate a planning optimization to maximize a social objective and demonstrate the benefit of the proposed routing and learning scheme.Comment: Submitted to CDC 201

Modulation of macrophage and microglial responses to axonal injury in the peripheral and central nervous systems

Journal ArticleOBJECTIVE: After axonal injury, macrophages rapidly infiltrate and become activated in the mammalian peripheral nervous system (PNS) but not the central nervous system (CNS). We used the dorsal root pathway to study factors that modulate the response of macrophages to degenerating axons in both the PNS and the CNS. METHODS: Lewis rats underwent transection of dorsal roots (Group I), stab within the spinal cord (Group II), crush at the dorsal root entry zone (Group III), transection of dorsal roots combined with a CNS lesion (Group IV), or systemic administration of a known activator of macrophages, lipopolysaccharide, alone (Group V) or combined with transection of dorsal roots (Group VI). ED-1 antibody stained for macrophages and activated microglia at 7, 14, and 42 days postinjury. RESULTS: At early time points, Group I demonstrated ED-1 cells in the PNS but not the CNS portion of the degenerating dorsal roots. Group II revealed ED-1 cells near the stab lesion. Group III demonstrated ED-1 cells adjacent to the dorsal root entry zone crush site. Group IV revealed ED-1 cells along both the PNS and the CNS portions of the degenerating dorsal roots when the CNS lesion was placed near the transected roots. Group V demonstrated few ED-1 cells in the PNS and the CNS, whereas Group VI revealed a marked ED-1 cellular response along both the PNS and the CNS portions of the transected dorsal roots. CONCLUSION: Local CNS trauma and systemic administration of lipopolysaccharide can "prime" macrophages/microglia, resulting in an enhanced response to degenerating axons in the CNS. Such priming might prove useful in promoting axonal regeneration

The Proto-Oncogene Int6 Is Essential for Neddylation of Cul1 and Cul3 in Drosophila

Int6 is a proto-oncogene implicated in various types of cancer, but the mechanisms underlying its activity are not clear. Int6 encodes a subunit of the eukaryotic translation initiation factor 3, and interacts with two related complexes, the proteasome, whose activity is regulated by Int6 in S. pombe, and the COP9 signalosome. The COP9 signalosome regulates the activity of Cullin-Ring Ubiquitin Ligases via deneddylation of their cullin subunit. We report here the generation and analysis of two Drosophila mutants in Int6. The mutants are lethal demonstrating that Int6 is an essential gene. The mutant larvae accumulate high levels of non-neddylated Cul1, suggesting that Int6 is a positive regulator of cullin neddylation. Overexpression in Int6 in cell culture leads to accumulation of neddylated cullins, further supporting a positive role for Int6 in regulating neddylation. Thus Int6 and the COP9 signalosome play opposing roles in regulation of cullin neddylation

Identification of linear and nonlinear sensory processing circuits from spiking neuron data

Inferring mathematical models of sensory processing systems directly from input-output observations, while making the fewest assumptions about the model equations and the types of measurements available, is still a major issue in computational neuroscience. This letter introduces two new approaches for identifying sensory circuit models consisting of linear and nonlinear filters in series with spiking neuron models, based only on the sampled analog input to the filter and the recorded spike train output of the spiking neuron. For an ideal integrate-and-fire neuron model, the first algorithm can identify the spiking neuron parameters as well as the structure and parameters of an arbitrary nonlinear filter connected to it. The second algorithm can identify the parameters of the more general leaky integrate-and-fire spiking neuron model, as well as the parameters of an arbitrary linear filter connected to it. Numerical studies involving simulated and real experimental recordings are used to demonstrate the applicability and evaluate the performance of the proposed algorithms