Sensitivity to atypical mycobacterial antigens in patients with Crohn's disease

Twenty-two patients with Crohn's disease were investigated for the presence of delayed cutaneous reactions and precipitating antibodies to atypical mycobacterial antigens of Runyon's Groups I, II and III as well as standard PPD. The results obtained, when compared to the control groups, do not show an increased incidence of sensitivity to such antigens in patients with Crohn's disease. However, their potential relevance to the pathogenesis of this disorder remains to be determined.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/44374/1/10620_2005_Article_BF02236026.pd

A Constraint Programming Approach to Multi-Robot Task Allocation and Scheduling in Retirement Homes

We study the application of constraint programming (CP) to the planning and scheduling of multiple social robots interacting with residents in a retirement home. The robots autonomously organize and facilitate group and individual activities among residents. The application is a multi-robot task allocation and scheduling problem in which task plans must be determined that integrate with resident schedules. The problem involves reasoning about disjoint time windows, inter-schedule task dependencies, user and robot travel times, as well as robot energy levels. We propose mixed-integer programming (MIP) and CP approaches for this problem and investigate methods for improving our initial CP approach using symmetry breaking, variable ordering heuristics, and large neighbourhood search. We introduce a relaxed CP model for determining provable bounds on solution quality. Experiments indicate substantial superiority of the initial CP approach over MIP, and subsequent significant improvements in the CP approach through our manipulations. This work is one of the few, of which we are aware, that applies CP to multi-robot task allocation and scheduling problems. Our results demonstrate the promise of CP scheduling technology as a general optimization infrastructure for such problems

Mixed-Integer and Constraint Programming Techniques for Mobile Robot Task Planning

This paper was recommended for publication by Editor J. Li upon evaluation of the Associate Editor and Reviewers’ comments.We investigate the use of optimization-based techniques to model and solve two real-world single robot task planning problems. In the first problem, a robot must plan a set of tasks, each with different temporal constraints. In the second problem, a socially interacting robot must plan a set of tasks while considering the schedules of multiple human users, as well as physical constraints including battery level. We apply existing mixed-integer programming and constraint programming techniques, yielding two exact methods for each problem. Numerical experiments show that both approaches produce better solutions in less time compared to techniques previously proposed for these problems. In order to confirm their physical utility, we implement the plans for the second problem in both simulated and real environments on Tangy, a socially interacting robot. We conclude that both mixed-integer programming and constraint programming are promising general approaches to robot task planning that should be considered when solving these problems.This research has been funded by the Natural Sciences and Engineering Council of Canada (NSERC), Dr. Robot Inc., and the Canada Research Chairs (CRC) Program

Robots in Retirement Homes: Person Search and Task Planning for a Group of Residents by a Team of Assistive Robots

The authors present a general multirobot task planning and execution architecture for a team of heterogeneous mobile robots that interact with multiple human users. The designed architecture is implemented in an environment where such robots provide daily assistance to residents in a retirement home setting. The robots are able to allocate and schedule activities throughout the day and find the appropriate residents with whom to engage in assistive activities. Upon finding users, the robot queries each user for his or her availability and interest in various activities. The authors then use constraint programming within a multirobot task allocation and scheduling system to plan and schedule the robot team to facilitate individual and group activities, ensuring consistency with user-expressed availability and activity preferences. The authors test the components of the architecture on a physical multirobot system to verify the utility of the design. Experiments indicate the design can effectively plan and execute assistive activities for multiple users

The challenge of drug resistance in cancer treatment: a current overview

It is generally accepted that recent advances in anticancer agents have contributed significantly to the improvement of both the disease-free survival and quality of life in cancer patients. However, in many instances, a favorable initial response to treatment changes afterwards, thereby leading to cancer relapse and recurrence. This phenomenon of acquired resistance to therapy, it is a major problem for totally efficient anticancer therapy. The failure to obtain an initial response reflects a form of intrinsic resistance. Specific cell membrane transporter proteins are implicated in intrinsic drug resistance by altering drug transport and pumping drugs out of the tumor cells. Moreover, the gradual acquisition of specific genetic and epigenetic abnormalities in cancer cells could contribute greatly to acquired drug resistance. A critical issue in the clinical setting, is that the problem of drug resistance appears to have a negative effect on also the new molecularly-targeted anticancer drugs. Several ongoing efforts are being made by the medical community aimed to the identification of such resistance mechanisms and the development of novel drugs that could overcome them. In this review, the major drug resistance mechanisms and strategies to overcome them are critically discussed, and also possible future directions are suggested