Generating a Multipliciy of Policies for Agent Steering in Crowd Simulation

Pedestrian steering algorithms range from completely procedural to entirely data-driven, but the former grossly generalize across possible human behaviors and suffer computationally, whereas the latter are limited by the burden of ever-increasing data samples. Our approach seeks the balanced middle ground by deriving a collection of machine-learned policies based on the behavior of a procedural steering algorithm through the decomposition of the space of possible steering scenarios into steering contexts. The resulting algorithm scales well in the number of contexts, the use of new data sets to create new policies, and in the number of controlled agents as the policies become a simple evaluation of the rules asserted by the machine-learning process. We also explore the use of synthetic data from an “oracle algorithm” that serves as an as-needed source of samples, which can be stochastically polled for effective coverage. We observe that our approach produces pedestrian steering similar to that of the oracle steering algorithm, but with a significant performance boost. Runtime was reduced from hours under the oracle algorithm with 10 agents to on the order of 10 frames per second (FPS) with 3000 agents. We also analyze the nature of collisions in such a framework with no explicit collision avoidance

Dynamic Search on the GPU

Path finding is a fundamental, yet computationally expensive problem in robotics navigation. Often times, it is necessary to sacrifice optimality to find a feasible plan given a time constraint due to the search complexity. Dynamic environments may further invalidate current computed plans, requiring an efficient planning strategy that can repair existing solutions. This paper presents a massively parallelized wavefront-based approach to path planning, running on the GPU, that can efficiently repair plans to accommodate world changes and agent movement, without having to restart the wavefront propagation process. In addition, we introduce a termination condition which ensures the minimum number of GPU iterations while maintaining strict optimality constraints on search graphs with non-uniform costs

Pedestrian Anomaly Detection Using Context-Sensitive Crowd Simulation

Detecting anomalies in crowd movement is an area of considerable interest for surveillance and security applications. The question we address is: What constitutes an anomalous steering choice for an individual in the group? Deviation from “normal” behavior may be defined as a subject making a steering decision the observer would not, provided the same circumstances. Since the number of possible spatial and movement configurations is huge and human steering behavior is adaptive in nature, we adopt a context-sensitive approach to assess individuals rather than assume population-wide homogeneity. When presented with spatial trajectories from processed surveillance data, our system creates a shadow simulation. The simulation then establishes the current, local context for each agent and computes a predicted steering behavior against which the person’s actual motion can be statistically compared. We demonstrate the efficacy of our technique with preliminary results using real-world tracking data from the Edinburgh Pedestrian Dataset

Studies leading to potent, dual inhibitors of bcl-2 and Bcl-xL

verexpression of the antiapototic proteins Bcl-2 and Bcl-xL provides a common mechanism through which cancer cells gain a survival advantage and become resistant to conventional chemotherapy. Inhibition of these prosurvival proteins is an attractive strategy for cancer therapy. We recently described the discovery of a selective Bcl-xL antagonist that potentiates the antitumor activity of chemotherapy and radiation. Here we describe the use of structure-guided design to exploit a deep hydrophobic binding pocket on the surface of these proteins to develop the first dual, subnanomolar inhibitors of Bcl-xL and Bcl-2. This study culminated in the identification of 2, which exhibited EC50 values of 8 nM and 30 nM in Bcl-2 and Bcl-xL dependent cells, respectively. Compound 2 demonstrated single agent efficacy against human follicular lymphoma cell lines that overexpress Bcl-2, and efficacy in a murine xenograft model of lymphoma when given both as a single agent and in combination with etoposide.close14213

Loss of Caspase-9 Reveals Its Essential Role for Caspase-2 Activation and Mitochondrial Membrane Depolarization

Caspase-9 plays an important role in apoptosis induced by genotoxic stress. Irradiation and anticancer drugs trigger mitochondrial outer membrane permeabilization, resulting in cytochrome c release and caspase-9 activation. Two highly contentious issues, however, remain: It is unclear whether the loss of the mitochondrial membrane potential ΔΨ(M) contributes to cytochrome c release and whether caspases are involved. Moreover, an unresolved question is whether caspase-2 functions as an initiator in genotoxic stress-induced apoptosis. In the present study, we have identified a mutant Jurkat T-cell line that is deficient in caspase-9 and resistant to apoptosis. Anticancer drugs, however, could activate proapoptotic Bcl-2 proteins and cytochrome c release, similarly as in caspase-9–proficient cells. Interestingly, despite these alterations, the cells retained ΔΨ(M). Furthermore, processing and enzyme activity of caspase-2 were not observed in the absence of caspase-9. Reconstitution of caspase-9 expression restored not only apoptosis but also the loss of ΔΨ(M) and caspase-2 activity. Thus, we provide genetic evidence that caspase-9 is indispensable for drug-induced apoptosis in cancer cells. Moreover, loss of ΔΨ(M) can be functionally separated from cytochrome c release. Caspase-9 is not only required for ΔΨ(M) loss but also for caspase-2 activation, suggesting that these two events are downstream of the apoptosome