A probabilistic approach to aircraft conflict detection

Conflict detection and resolution schemes operating at the mid-range and short-range level of the air traffic management process are discussed. Probabilistic models for predicting the aircraft position in the near-term and mid-term future are developed. Based on the mid-term prediction model, the maximum instantaneous probability of conflict is proposed as a criticality measure for two aircraft encounters. Randomized algorithms are introduced to efficiently estimate this measure of criticality and provide quantitative bounds on the level of approximation introduced. For short-term detection, approximate closed-form analytical expressions for the probability of conflict are obtained, using the short-term prediction model. Based on these expressions, an algorithm for decentralized conflict detection and resolution that generalizes potential fields methods for path planning to a probabilistic dynamic environment is proposed. The algorithms are validated using Monte Carlo simulations     

Compensation of progressive radial run-out in face-milling by spindle speed variation

This paper investigates the use of spindle speed variation to compensate for progressive radial run-out in the face-milling process. Machine setup errors like spindle axis tilt, cutter axis tilt and cutter center offset result in radial and axial run-out on the inserts. Cutter center offset, in particular, results in progressive radial run-out on the inserts which can be compensated by continuously varying the spindle speed in a sinusoidal pattern. The amplitude and phase of the sinusoidal trajectory significantly influence the capability of this technique for run-out compensation. A method is proposed for selection of optimal values of the speed variation amplitude and phase based on the idea of matching the chip load pattern under variable speed machining conditions in the presence of progressive radial run-out with that of constant speed machining in the absence of any run-out. Experiments performed with optimal values of the speed variation parameters show a significant reduction in the cutting force component at the spindle frequency and a shift in the frequency content of cutting force from the harmonics of the spindle frequency to those of the tooth passing frequency. An industrial implementation strategy of the proposed scheme is also presented that integrates run-out estimation with its subsequent compensation.     

Regulation of Hsp90 ATPase activity by tetratricopeptide repeat (TPR)-domain co-chaperones

The in vivo function of the heat shock protein 90 (Hsp90) molecular chaperone is dependent on the binding and hydrolysis of ATP, and on interactions with a variety of co-chaperones containing tetratricopeptide repeat (TPR) domains. We have now analysed the interaction of the yeast TPR-domain co-chaperones Sti1 and Cpr6 with yeast Hsp90 by isothermal titration calorimetry, circular dichroism spectroscopy and analytical ultracentrifugation, and determined the effect of their binding on the inherent ATPase activity of Hsp90. Sti1 and Cpr6 both bind with sub-micromolar affinity, with Sti1 binding accompanied by a large conformational change. Two co-chaperone molecules bind per Hsp90 dimer, and Sti1 itself is found to be a dimer in free solution. The inherent ATPase activity of Hsp90 is completely inhibited by binding of Sti1, but is not affected by Cpr6, although Cpr6 can reactivate the ATPase activity by displacing Sti1 from Hsp90. Bound Sti1 makes direct contact with, and blocks access to the ATP-binding site in the N-terminal domain of Hsp90. These results reveal an important role for TPR-domain co-chaperones as regulators of the ATPase activity of Hsp90, showing that the ATP-dependent step in Hsp90-mediated protein folding occurs after the binding of the folding client protein, and suggesting that ATP hydrolysis triggers client-protein release.     

Monitoring human blood dendritic cell numbers in normal individuals and in stem cell transplantation

Dendritic cells (DC) originate from a bone marrow (BM) precursor and circulate via the blood to most body tissues where they fulfill a role in antigen surveillance. Little is known about DC numbers in disease, although the reported increase in tissue DC turnover due to inflammatory stimuli suggests that blood DC numbers may be altered in some clinical situations. The lack of a defined method for counting DC has limited patient studies. We therefore developed a method suitable for routine monitoring of blood DC numbers, using the CMRF44 monoclonal antibody (MoAb) and flow cytometry to identify DC. A normal range was determined from samples drawn from 103 healthy adults. The mean percentage of DC present in blood mononuclear cells (MNC) was 0.42%, and the mean absolute DC count was 10 x 10(6) DC/L blood. The normal ranges for DC (mean +/- 1.96 standard deviation [SD]) were 0.15% to 0.70% MNC or 3 to 17 x 10(6) DC/L blood. This method has applications for monitoring attempts to mobilize DC into the blood to facilitate their collection for immunotherapeutic purposes and for counting blood DC in other patients. In preliminary studies, we have found a statistically significant decrease in the blood DC counts in individuals at the time of blood stem cell harvest and in patients with acute illnesses, including allogeneic bone marrow transplant (BMT) recipients with acute graft-versus-host disease (aGVHD).     

Cortical connections of the frontoparietal opercular areas in the rhesus monkey

The connections of the frontoparietal opercular areas were studied in rhesus monkeys by using antero- and retrograde tracer techniques. The rostral opercular cortex including the gustatory and proisocortical motor (ProM) areas is connected with precentral areas 3, 1, and 2 as well as with the rostral portion of the opercular area which resembles the second somatosensory type of cortex (area SII) and the ventral portion of area 6. Its distant connections are with the ventral portion of prefrontal areas 46, 11, 12, and 13 as well as with the rostral insula and cingulate motor area (CMAr). The mid opercular region (areas 1 and 2) is connected with pre- and postcentral areas 3, 1, and 2 as well as SII. Additionally, it is connected with the ventral portion of area 6, area 44, area ProM, the gustatory area, and the rostral insula. Its distant connections are with area 4, the ventral portion of area 46, area 7b, and area POa in the intraparietal sulcus (IPS). The rostral parietal opercular region is connected with the postcentral portions of areas 3, 1, and 2; areas 5, 7, and SII; the gustatory area; and the vestibular area. Its other connections are with area 4, area 44, the ventral portion of area 46, area ProM, CMAr, and the supplementary motor area (SMA). The caudal opercular region is connected with the dorsal portion of area 3; areas 2, 5, and 7a; and areas PEa as well as IPd of IPS. It is also connected with area SII, insula, and the superior temporal sulcus. Its distant connections are with area 44; the dorsal portion of area 8 and the ventral portion of area 46; as well as CMAr, SMA, and the supplementary sensory area. This connectivity suggests that the ventral somatosensory areas are involved in sensorimotor activities mainly related to head, neck, and face structures as well as to taste. Additionally, these areas may have a role in frontal (working) and temporal (tactile) memory systems.     

Editorial

Mobile Networks and Applications -     

New algorithms for learning and pruning oblique decision trees

We present methods for learning and pruning oblique decision trees. We propose a new function for evaluating different split rules at each node while growing the decision tree. Unlike the other evaluation functions currently used in the literature (which are all based on some notion of purity of a node), this new evaluation function is based on the concept of degree of linear separability. We adopt a correlation based optimization technique called the Alopex algorithm (K.P. Unnikrishnaan and K.P. Venugopal, 1994) for finding the split rule that optimizes our evaluation function at each node. The algorithm we present is applicable only for 2-class problems. Through empirical studies, we demonstrate that our algorithm learns good compact decision trees. We suggest a representation scheme for oblique decision trees that makes explicit the fact that an oblique decision tree represents each class as a union of convex sets bounded by hyperplanes in the feature space. Using this representation, we present a new pruning technique. Unlike other pruning techniques, which generally replace heuristically selected subtrees of the original tree by leaves, our method can radically restructure the decision tree. Through empirical investigation, we demonstrate the effectiveness of our method     

LANDING AN UNMANNED AIR VEHICLE: VISION BASED MOTION ESTIMATION AND NONLINEAR CONTROL

In this paper, we use computer vision as a feedback sensor in a control loop for landing an unmanned air vehicle (UAV) on a landing pad. The vision problem we address here is then a special case of the classic ego-motion estimation problem since all feature points lie on a planar surface (the landing pad). We study together the discrete and differential versions of the ego-motion estimation, in order to obtain both position and velocity of the UAV relative to the landing pad. After briefly reviewing existing algorithm for the discrete case, we present, in a unified geometric framework, a new estimation scheme for solving the differential case. We further show how the obtained algorithms enable the vision sensor to be placed in the feedback loop as a state observer for landing control. These algorithms are linear, numerically robust, and computationally inexpensive hence suitable for real-time implementation. We present a thorough performance evaluation of the motion estimation algorithms under varying levels of image measurement noise, altitudes of the camera above the landing pad, and different camera motions relative to the landing pad. A landing controller is then designed for a full dynamic model of the UAV. Using geometric nonlinear control theory, the dynamics of the UAV are decoupled into an inner system and outer system. The proposed control scheme is then based on the differential flatness of the outer system. For the overall closed-loop system, conditions are provided under which exponential stability can be guaranteed. In the closed-loop system, the controller is tightly coupled with the vision based state estimation and the only auxiliary sensor are accelerometers for measuring acceleration of the UAV. Finally, we show through simulation results that the designed vision-in-the-loop controller generates stable landing maneuvers even for large levels of image measurement noise. Experiments on a real UAV will be presented in future work.