Human acetylcholinesterase (AChE) is a significant target for therapeutic drugs. Here we present high resolution crystal structures of human AChE, alone and in complexes with drug ligands; donepezil, ...an Alzheimer’s disease drug, binds differently to human AChE than it does to Torpedo AChE. These crystals of human AChE provide a more accurate platform for further drug development than previously available.
•Formulated parsimonious, continuous model for optimizing the design of hybrid transit networks fed by shared bikes.•Significant cost savings were found in some cases over transit networks accessed ...on foot only and those accessed by feeder buses.•Jointly optimized transit and shared-bike systems can reduce costs for both patrons and the transit agency.•Revenue accrued from system-optimal pricing for shared bikes can often cover their cost, with or without subsidy.
Transit systems are designed in which access and egress can occur via a shared-bike service. Patrons may walk to shared-bike docking stations nearest their origins, and then cycle to their nearest transit stations where they deposit the bikes. The travel pattern is reversed when patrons cycle from their final transit stations on to their destinations. Patrons choose between this option and that of solely walking to or from transit stations. Shared bikes are priced to achieve the system-optimal assignment of the two feeder options.
Transit trunk-line networks are laid-out in hybrid fashion, as proposed in Daganzo (2010). Transit lines thus form square grids inside city centers, and radiate outward in the peripheries. As in Daganzo (2010) and other studies, a set of simplifying assumptions are adopted that pertain primarily to the nature of travel demand. These enable the formulation of a parsimonious, continuous model. The model produces designs that minimize total travel costs, and is ideally suited for high-level (i.e., strategic) planning. A similar model is developed for systems in which access or egress to or from transit can occur solely by walking, or by walking and riding fixed-route feeder buses in combination. The shared-bike and feeder-bus models both complement Daganzo's original model in which access and egress occur solely by walking.
Comparisons of these feeder options are drawn through numerical analyses. These are performed in parametric fashion by varying city size, travel demand, and economic conditions; and for trunk services that are provided either by ordinary buses, Bus Rapid Transit, or metro rail. Designs are produced for cases in which shared-bike and feeder-bus services are made to fit pre-existing and unchangeable trunk-line networks; and for cases in which trunk and feeder services are optimized jointly.
Outcomes reveal that shared-bike feeder systems can often reduce costs over walking alone, with cost savings as high as 7%, even when the shared bikes are made to fit a pre-existing transit network. Shared-biking often outperforms feeder-bus service as well. We further find that the joint optimization of trunk and shared-bike feeder services can reduce costs not only to users, but also to the transit agency that operates these services. Savings to the agency can be used to subsidize shared-bike services. We show that with or without this subsidy, shared-bike systems can always break even when they are suitably priced, and jointly optimized with trunk service.
Audio-driven 3D facial animation has been widely explored, but achieving realistic, human-like performance is still unsolved. This is due to the lack of available 3D datasets, models, and standard ...evaluation metrics. To address this, we introduce a unique 4D face dataset with about 29 minutes of 4D scans captured at 60 fps and synchronized audio from 12 speakers. We then train a neural network on our dataset that factors identity from facial motion. The learned model, VOCA (Voice Operated Character Animation) takes any speech signal as input-even speech in languages other than English-and realistically animates a wide range of adult faces. Conditioning on subject labels during training allows the model to learn a variety of realistic speaking styles. VOCA also provides animator controls to alter speaking style, identity-dependent facial shape, and pose (i.e. head, jaw, and eyeball rotations) during animation. To our knowledge, VOCA is the only realistic 3D facial animation model that is readily applicable to unseen subjects without retargeting. This makes VOCA suitable for tasks like in-game video, virtual reality avatars, or any scenario in which the speaker, speech, or language is not known in advance. We make the dataset and model available for research purposes at http://voca.is.tue.mpg.de.
Measurements taken downstream of freeway/on-ramp merges have previously shown that discharge flow diminishes when a merge becomes an isolated bottleneck. By means of observation and experiment, we ...show here that metering an on-ramp can recover the higher discharge flow at a merge and thereby increase the merge capacity. Detailed observations were collected at a single merge using video. These data revealed that the reductions in discharge flow are triggered by a queue that forms near the merge in the freeway shoulder lane and then spreads laterally, as drivers change lanes to maneuver around slow traffic. Our experiments show that once restrictive metering mitigated this shoulder lane queue, high outflows often returned to the median lane. High merge outflows could be restored in all freeway lanes by then relaxing the metering rate so that inflows from the on-ramp increased. Although outflows recovered in this fashion were not sustained for periods greater than 13
min, the findings are the first real evidence that ramp metering can favorably affect the capacity of an isolated merge. Furthermore, these findings point to control strategies that might generate higher outflows for more prolonged periods and increase merge capacity even more. Finally, the findings uncover details of merge operation that are essential for developing realistic theories of merging traffic.
An agent-based, multichannel simulation of a downtown area reveals the impacts of both time-shifting traffic demand with congestion pricing, and supplying extra capacity by banning left turns. The ...downtown street network was idealized, and loosely resembles central Los Angeles. On the demand-side, prices were set based on time-of-day and distance traveled. On the supply side, left-turn maneuvers were prohibited at all intersections on the network.
Although both traffic management measures reduced travel costs when used alone, the left-turn ban was much less effective than pricing. When combined with pricing under congested conditions, however, the left-turn ban’s effectiveness increased considerably—it more than doubled in some cases. Furthermore, the two measures combined reduced travel costs in synergistic fashion. In some cases, this synergistic effect was responsible for 30% of the cost reduction. This strong synergy suggests that turning bans should be considered as an added option when contemplating congestion pricing.
Two continuum approximation (CA) optimization models are formulated to design city-wide transit systems at minimum cost. Transit routes are assumed to lie atop a city’s street network. Model 1 ...assumes that the city streets are laid out in ring-radial fashion. Model 2 assumes that the city streets form a grid. Both models can furnish hybrid designs, which exhibit intersecting routes in a city’s central (downtown) district and only radial branching routes in the periphery. Model 1 allows the service frequency and the route spacing at a location to vary arbitrarily with the location’s distance from the center. Model 2 also allows such variation but in the periphery only.
The paper shows how to solve these CA optimization problems numerically, and how the numerical results can be used to design actual systems. A wide range of scenarios is analyzed in this way. It is found among other things that in all cases and for both models: (i) the optimal headways and spacings in the periphery increase with the distance from the center; and (ii) at the boundary between the central district and the periphery both, the optimal service frequency and line spacing for radial lines decrease abruptly in the outbound direction. On the other hand Model 1 is distinguished from Model 2 in that the former produces in all cases: (i) a much smaller central district, and (ii) a high frequency circular line on the outer edge of that central district.
Parametric tests with all the scenarios further show that Model 1 is consistently more favorable to transit than Model 2. Cost differences between the two designs are typically between 9% and 13%, but can top 21.5%. This is attributed to the manner in which ring-radial networks naturally concentrate passenger’s shortest paths, and to the economies of demand concentration that transit exhibits. Thus, it appears that ring-radial street networks are better for transit than grids.
To illustrate the robustness of the CA design procedure to irregularities in real street networks, the results for all the test problems were then used to design and evaluate transit systems on networks of the “wrong” type – grid networks were outfilled with transit systems designed with Model 1 and ring-radial networks designed with Model 2. Cost increased on average by only 2.7%. The magnitude of these deviations suggests that the proposed CA procedures can be used to design transit systems over real street networks when they are not too different from the ideal and that the resulting costs should usually be very close to those predicted.
•Time-varying, but spatially-uniform metering rates generated via model predictive control are redistributed along cordons in spatially-varying fashion.•The redistribution is achieved using ...Reinforcement Learning (RL).•Street networks are conveniently and fully represented as directed graphs, which require adaptations to neural network architectures.•The result is an RL controller that can be trained on data from a single cordon, and thereafter deployed on other cordons elsewhere in a city sans additional learning.•Spatially-varying metering policies generated by the controller are shown to outperform spatially-uniform metering policies.
The work explores how Reinforcement Learning can be used to re-time traffic signals around cordoned neighborhoods. An RL-based controller is developed by representing traffic states as graph-structured data and customizing corresponding neural network architectures to handle those data. The customizations enable the controller to: (i) model neighborhood-wide traffic based on directed-graph representations; (ii) use the representations to identify patterns in real-time traffic measurements; and (iii) capture those patterns to a spatial representation needed for selecting optimal cordon-metering rates. Input to the selection process also includes a total inflow to be admitted through a cordon. The rate is optimized in a separate process that is not part of the present work. Our RL-controller distributes that separately-optimized rate across the signalized street links that feed traffic through the cordon. The resulting metering rates vary from one feeder link to the next. The selection process can reoccur at short time intervals in response to changing traffic patterns. Once trained on a few cordons, the RL-controller can be deployed on cordons elsewhere in a city without additional training.
This portability feature is confirmed via simulations of traffic on an idealized street network. The tests also indicate that the controller can reduce the network’s vehicle hours traveled well beyond what can be achieved via spatially-uniform cordon metering. The extra reductions in VHT are found to grow larger when traffic exhibits greater in-homogeneities over the network.
•A framework is offered for bus network design under spatially-heterogeneous demand.•Dense local networks serve high-demand neighborhoods.•Routes with distinct spacings are aligned using a ...power-of-two scheme.•Optimal designs are obtained through continuum approximations.•Reductions in both agency and user costs are achieved.
A methodological framework is formulated so that continuum approximation techniques can be used to design bus networks for cities where travel demand varies gradually over space. The bus-route configurations that result consist of (i) a main, possibly city-wide grid with relatively large physical spacings between its parallel routes and the stops along those routes; together with (ii) one or more local grids with more closely-spaced routes and stops that serve neighborhoods of higher demand densities. The so-called power-of-two concept is borrowed from the field of inventory control, and is enforced so that local grids can be inserted seamlessly within the main one.
The resulting heterogeneous route configurations can reduce the costs to the bus users and the operating agency combined, as compared against the costs of homogeneous bus-route grids. Differences of as much as 8% are observed for numerical examples that cover wide-ranging patterns in spatially-varying demand. Much of the savings are due to the diminished access costs that users enjoy when high-demand neighborhoods are served by local grids with closely-spaced routes and stops.
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