MOTIVATION: Efficient assessment of the blood-brain barrier (BBB) penetration ability of a drug compound is one of the major hurdles in central nervous system drug discovery since experimental methods are costly and time-consuming. To advance and elevate the success rate of neurotherapeutic drug discovery, it is essential to develop an accurate computational quantitative model to determine the absolute logBB value (a logarithmic ratio of the concentration of a drug in the brain to its concentration in the blood) of a drug candidate. RESULTS: Here, we developed a quantitative model (LogBB_Pred) capable of predicting a logBB value of a query compound. The model achieved an R2 of 0.61 on an independent test dataset and outperformed other publicly available quantitative models. When compared with the available qualitative (classification) models that only classified whether a compound is BBB-permeable or not, our model achieved the same accuracy (0.85) with the best qualitative model and far-outperformed other qualitative models (accuracies between 0.64 and 0.70). For further evaluation, our model, quantitative models, and the qualitative models were evaluated on a real-world central nervous system drug screening library. Our model showed an accuracy of 0.97 while the other models showed an accuracy in the range of 0.29-0.83. Consequently, our model can accurately classify BBB-permeable compounds as well as predict the absolute logBB values of drug candidates. AVAILABILITY AND IMPLEMENTATION: Web server is freely available on the web at http://ssbio.cau.ac.kr/software/logbb_pred/. The data used in this study are available to download at http://ssbio.cau.ac.kr/software/logbb_pred/dataset.zip.

Automated target acquisition and docking is key to enabling various applications of autonomous mobile robots in indoor environments. For the purpose, many researches have been devoted to the development of location sensing techniques employing the latest in RFID or GPS. However, it has not yet become possible to attain high accuracy in those techniques, particularly in cluttered or dynamically changing environments. In this paper, we propose a novel location sensing RFID reader equipped with a dual directional antenna that communicates with controllable RF transponders. The dual directional antenna estimates the direction of arrival (DOA) of signals from various transponders by using the ratio of the received strength between two antennas. This enables the robot to continuously monitor the changes in the ratio and find its way to the target transponder. To verify the validity of the proposed system in real environments populated with unknown obstacles, we perform detailed experiments using simulations and hardware implementations. Specifically, the target acquisition and docking guidance are demonstrated in a multiple transponder environment under various circumstances.

It is known that parallel type mechanisms have many singularities than serial type mechanisms. In haptic application, these singularities deteriorate the force reflecting performance. Moreover, different from general manipulators, haptic systems can't avoid the singular point, because they are operated by the user's random motion command. Although many singularity-free load distribution algorithms for kinematically redundant manipulators have been proposed, singularity-free load distribution algorithms for parallel haptic application have not been deeply discussed. In this work, various singularity-free load distribution algorithms that are appropriate to parallel haptic system are discussed. A new 6 DOF parallel mechanism equipped with four sub-chains is employed as a test device. To cope with singularity problem, four task-priority algorithms and redundant actuation algorithm are discussed and compared through simulation, and also experiments have been performed to show the effectiveness of those algorithms at the presence of singularity.

A haptic rendering system is proposed for a puncture task of a virtual vertebra model. To build a mesh model from medical images, Delaunay triangulation is applied and physical models are based on elasticity theory. Also, a redundant actuated 6 DOF parallel type haptic device is designed to display large force and to resolve the singularity problem of parallel type mechanisms. Haptic feeling of puncture task and the performance of the proposed haptic device are tested by two puncture task experiments.

It is known that parallel-type mechanisms have more singularities than serial-type mechanisms. In haptic application, these singularities deteriorate the system performance generating reflecting force. Moreover, different from general manipulators, haptic systems can't avoid the singular point, because they are operated by user random command. Although many singularity-free algorithms for serial mechanisms have been proposed and studied, singularity-free algorithms for parallel haptic application have not been deeply discussed. In this paper various singularity-free algorithms, which are appropriate to parallel haptic system, will be discussed. Furthermore, to overcome singularity problems, a new design including redundant actuation is proposed. The proposed mechanism has fairly large workspace and is relatively light by employing non-floating actuators.

This paper presents a design method of transparency optimized feedback controller with robustness for a parallel 6-DOF haptic system. A disturbance observer is employed to eliminate coupling effects that exist in a mechanically coupled structure. A performance index for the transparency is defined by admittance matching, and by solving the H/sub 2/ optimal problem. The optimal solution that minimizes the performance index is obtained.