Abstract Prostate cancer (PCa) is one of the most frequently diagnosed cancers in men. PCa growth is dependent on the androgen receptor (AR) which regulates transcription directly as well as through interactions with other transcription factors (TFs). While androgen deprivation therapy is often successful upon progression, a fraction of PCa cases possess constitutively active AR that functions independently of hormonal regulation. Understanding the TF regulatory landscape, especially androgen-dependent versus androgen-independent PCa, is critical to developing better therapeutic strategies. Here we investigated the epigenomic landscape of two prostate cancer cell lines, VCaP (androgen-dependent) and 22Rv1 (androgen-independent), using ATAC-seq to map chromatin accessibility and a high-resolution version of ChIP-seq (ChIP-exo) that characterizes binding of proteins to the genome at base-pair resolution. We identified distinct AR binding between cell lines in response to androgen-treatment, with a subset of AR sites showing strong enhancer enrichment and preferential colocalization with FoxA1 at characteristic spacing, consistent with cooperative AR–FoxA1 regulation. Interestingly, many FoxA1 binding events occurred independently of AR and were enriched in quiescent chromatin, suggesting a context-dependent role for FoxA1. Together, these findings highlight how differential AR–FoxA1 crosstalk and chromatin states contribute to hormone sensitivity versus resistance in PCa.

We quantify the observation by Kender and Freudenstein (1987) that degenerate views occupy a significant fraction of the viewing sphere surrounding an object. For a perspective camera geometry, we introduce a computational model that can be used to estimate the probability that a view degeneracy will occur in a random view of a polyhedral object. For a typical recognition system parameterization, view degeneracies typically occur with probabilities of 20 percent and, depending on the parameterization, as high as 50 percent. We discuss the impact of view degeneracy on the problem of object recognition and, for a particular recognition framework, relate the cost of object disambiguation to the probability of view degeneracy. To reduce this cost, we incorporate our model of view degeneracy in an active focal length control paradigm that balances the probability of view degeneracy with the camera field of view. In order to validate both our view degeneracy model as well as our active focal length control model, a set of experiments are reported using a real recognition system operating on real images.

We quantify the observation by Kender and Freudenstein (1987) that degenerate views occupy a significant fraction of the viewing sphere surrounding an object. This demonstrates that systems for recognition must explicitly account for the possibility of view degeneracy. We show that view degeneracy cannot be detected from a single camera viewpoint. As a result, systems designed to recognize objects from a single arbitrary viewpoint must be able to function in spite of possible undetected degeneracies, or else operate with imaging parameters that cause acceptably low probabilities of degeneracy. To address this need, we give a prescription for active control of focal length that allows a principled tradeoff between the camera field of view and probability of view degeneracy.>

This paper deals with coordinating behaviour in a multi-autonomous robot system. When two or more autonomous robots must interact in order to accomplish some common goal, communication between the robots is essential. Different inter-robot communications strategies give rise to different overall system performance and reliability. After a brief consideration of some theoretical approaches to multiple robot collections, we present concrete implementations of different strategies for convoy-like behaviour. The convoy system is based around two RWI B12 mobile robots and uses only passive visual sensing for inter-robot communication. The issues related to different communication strategies are considered.

This paper describes the integration of 2D stimulus-driven robot localization and positioning with a token-based correspondence method in a practical robot navigation system. The approach allows for modular acquisition and update of world knowledge for navigation, and robustness of navigation to low-level errors. No special marking of the world is necessary, so the robot may operate in quite general environments. Tests in a real industrial environment confirm the potential of the method.

This paper describes research on the ARK (Autonomous Mobile Robot in a Known Environment) project. The technical objective of the project is to build a robot that can navigate and carry out survey/inspection tasks in a complex but known industrial environment. Rather than altering the robots environment by adding easily identifiable beacons the robot relies on naturally occurring objects to use as visual landmarks for navigation. The robot is equipped with various sensors that are used to detect unmapped obstacles, landmarks and objects. This paper describes the robot's industrial environment, it's control architecture, and some results in processing the robot's range and vision sensor data for navigation.>

Probabilistic algorithms are presented for efficient storage and retrieval of sets of feature vectors, given a known error process operating on the query set, that perturbs the query set away from the corresponding stored set. The algorithms operate by mapping each set to a corresponding generalized indicator vector and then performing a pruned search of a tree containing stored indicator vectors. The pruning is based on the probability of the query, given the stored items below the current position in the tree. Analysis and trial results show that this approach requires less total computation than existing methods based on parallel architectures. The indicator vector retrieval method can also cope efficiently with query vectors of much higher dimensionality than existing serial algorithms for nearest-neighbor searches.>

In many cases several mobile robots (autonomous agents) can be used together to accomplish tasks that would be either more difficult or impossible for a robot acting alone. Many different models have been suggested for the makeup of such collections of robots. In this paper the authors present a taxonomy of the different ways in which such a collection of autonomous robotic agents can be structured. It is shown that certain swarms provide little or no advantage over having a single robot, while other swarms can obtain better than linear speedup over a single robot. There exist both trivial and non-trivial problems for which a swarm of robots can succeed where a single robot will fail. Swarms are more than just networks of independent processors - they are potentially reconfigurable networks of communicating agents capable of coordinated sensing and interaction with the environment.

The concept of active object recognition is introduced, and a proposal for its solution is described. The camera is mounted on the end of a robot arm on a mobile base. The system exploits the mobility of the camera by using low-level image data to drive the camera to a standard viewpoint with respect to an unknown object. From such a viewpoint, the object recognition task is reduced to a two-dimensional pattern recognition problem. The system uses an efficient tree-based, probabilistic indexing scheme to find the model object that is likely to have generated the observed data, and for line tracking uses a modification of the token-based tracking scheme of J.L. Crowley et al. (1988). The system has been successfully tested on a set of origami objects. Given sufficiently accurate low-level data, recognition time is expected to grow only logarithmically with the number of objects stored.>

Addressed is the problem of robotic exploration of a graphlike world, where no distance or orientation metric is assumed of the world. The robot is assumed to be able to autonomously traverse graph edges, recognize when it has reached a vertex, and enumerate edges incident upon the current vertex relative to the edge via which it entered the current vertex. The robot cannot measure distances, and it does not have a compass. It is demonstrated that this exploration problem is unsolvable in general without markers, and, to solve it, the robot is equipped with one or more distinct markers that can be put down or picked up at will and that can be recognized by the robot if they are at the same vertex as the robot. An exploration algorithm is developed and proven correct. Its performance is shown on several example worlds, and heuristics for improving its performance are discussed.>