Gaster flagging by fire ants (Solenopsis spp.): Functional significance of venom dispersal behavior

Behavioral and chemical studies with laboratory colonies indicate that the imported fire antSolenopsis invicta Buren (Myrmicinae) disperses venom through the air by raising and vibrating its gaster (i.e., gaster flagging). This mechanism of airborne venom dispersal is unreported for any ant species. Foraging workers utilize this air-dispersed venom (up to 500 ng) to repel heterospecifics encountered in the foraging arena, while brood tenders dispense smaller quantities ( 1 ng) to the brood surface, presumably as an antibiotic. Brood tenders removed from the brood cell and tested in heteropspecific encounters in the foraging arena exhibited the complete repertoire of agonistic gaster flagging behavior. These observations suggest that airborne venom dispersal by workers is context specific rather than temporal caste specific and that workers can control the quantity of venom released.     

An analysis of the Miller Analogies Test for a scientific population.

On 50 subjects "… who are actively engaged in research in an industrial organization… " a correlation of .58 between the Miller Analogies Test and the Full Scale Wechsler-Bellevue was obtained; a correlation of .77 between the Miller Analogies Test and the W-B vocabulary subtest was obtained. Confirmation of these results with a representative graduate school population would suggest "… that a more discriminating vocabulary test than the W-B subtest for graduate school populations might closely approximate the efficiency of the MAT in predicting success in graduate school." (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

On a Refined Analysis of Some Problems in Interval Arithmetic Using Real Number Complexity Theory

We study some problems in interval arithmetic treated in Kreinovich et al. [13]. First, we consider the best linear approximation of a quadratic interval function. Whereas this problem (as decision problem) is known to be NP-hard in the Turing model, we analyze its complexity in the real number model and the analogous class NP . Our results substantiate that most likely it does not any longer capture the difficulty of NP in such a real number setting. More precisely, we give upper complexity bounds for the approximation problem for interval functions by locating it in (a real analogue of). This result allows several conclusions: the problem is not (any more) NP -hard under so called weak polynomial time reductions and likely not to be NP -hard under (full) polynomial time reductions; for fixed dimension the problem is polynomial time solvable; this extends the results in Koshelev et al. [12] and answers a question left open in [13].We also study several versions of interval linear systems and show similar results as for the approximation problem.Our methods combine structural complexity theory with issues from semi-infinite optimization theory.     

Segregation of colony odor in the desert ant Cataglyphis niger

There are two separate, and presumably opposing, processes that affect colony odor in the desert ant Cataglyphis niger: (1) biosynthesis and turnover of these chemicals by individual ants, and (2) homogenization of colony odor through exchange of cues. The first increases signal variability; the latter decreases it. The impact of these factors was tested by splitting colonies and monitoring the profile changes occurring in the postpharyngeal glands (PPG) and cuticular hydrocarbons.From each of two polygynous nests four daughter colonies were formed, three monogynous and one queenless. Thereafter, 10 ants from each were randomly selected each month, for three successive months, for analyses of their PPG and cuticular hydrocarbons. From two colonies we also obtained ants from a known matriline. Over time, there was a shift in hydrocarbon profiles of both the PPG and cuticular washes in each of the tested colonies. Moreover, by subjecting selected hydrocarbon constituents to a discriminant analyses based on their relative proportions, all of the daughter colonies (queenright and queenless) were distinguishable from each other and from their respective mother colonies. In each of the queenright daughter colonies, the queen profile was indiscriminable from that of the workers and often was in the center of the group. Full sisters were clearly distinguishable from their nestmates, emphasizing the genetic versus environmental processes that govern colony odor. The effect of time was always superior to the separation effect in contributing to odor segregation. Comparison of the Mahalanobis distances indicated that the shift in hydrocarbon seems to proceed along parallel lines rather than in divergence. However, there was no overt aggression between ants that originated from the different subgroups in dyadic encounters. It appears that in this species a three-month separation period is not sufficient to change the hydrocarbon profile beyond the recognition threshold.     

Limitations of shift-and-ratio based Leff extractiontechniques for MOS transistors with halo or pocket implants

The shift-and-ratio method has been considered as one of the most accurate and consistent techniques for extracting the effective channel-length of the MOS transistor. This method assumes the effective mobility of a long channel and a short channel transistor to be equal. Scaling down the MOS transistor urges the need of including halo (or pocket) implants in the fabrication process. Due to this implant, however, the short channel MOSFET features a degraded effective mobility compared to the long channel reference device. This affects the channel-length extraction and results in unrealistic high values for the extracted effective channel-length for deep submicron transistors with high-dose halo (or pocket) implants     

Prediction based collaborative trackers (PCT): a robust and accurate approach toward 3D medical object tracking

Robust and fast 3D tracking of deformable objects, such as heart, is a challenging task because of the relatively low image contrast and speed requirement. Many existing 2D algorithms might not be directly applied on the 3D tracking problem. The 3D tracking performance is limited due to dramatically increased data size, landmarks ambiguity, signal drop-out or complex nonrigid deformation. In this paper, we present a robust, fast, and accurate 3D tracking algorithm: prediction based collaborative trackers (PCT). A novel one-step forward prediction is introduced to generate the motion prior using motion manifold learning. Collaborative trackers are introduced to achieve both temporal consistency and failure recovery. Compared with tracking by detection and 3D optical flow, PCT provides the best results. The new tracking algorithm is completely automatic and computationally efficient. It requires less than 1.5 s to process a 3D volume which contains millions of voxels. In order to demonstrate the generality of PCT, the tracker is fully tested on three large clinical datasets for three 3D heart tracking problems with two different imaging modalities: endocardium tracking of the left ventricle (67 sequences, 1134 3D volumetric echocardiography data), dense tracking in the myocardial regions between the epicardium and endocardium of the left ventricle (503 sequences, roughly 9000 3D volumetric echocardiography data), and whole heart four chambers tracking (20 sequences, 200 cardiac 3D volumetric CT data). Our datasets are much larger than most studies reported in the literature and we achieve very accurate tracking results compared with human experts' annotations and recent literature.     

Kernel-based object tracking

A new approach toward target representation and localization, the central component in visual tracking of nonrigid objects, is proposed. The feature histogram-based target representations are regularized by spatial masking with an isotropic kernel. The masking induces spatially-smooth similarity functions suitable for gradient-based optimization, hence, the target localization problem can be formulated using the basin of attraction of the local maxima. We employ a metric derived from the Bhattacharyya coefficient as similarity measure, and use the mean shift procedure to perform the optimization. In the presented tracking examples, the new method successfully coped with camera motion, partial occlusions, clutter, and target scale variations. Integration with motion filters and data association techniques is also discussed. We describe only a few of the potential applications: exploitation of background information, Kalman tracking using motion models, and face tracking.     

Distribution Free Decomposition of Multivariate Data

We present a practical approach to nonparametric cluster analysis of large data sets. The number of clusters and the cluster centres are automatically derived by mode seeking with the mean shift procedure on a reduced set of points randomly selected from the data. The cluster boundaries are delineated using a k-nearest neighbour technique. The proposed algorithm is stable and efficient, a 10,000 point data set being decomposed in only a few seconds. Complex clustering examples and applications are discussed, and convergence of the gradient ascent mean shift procedure is demonstrated for arbitrary distribution and cardinality of the data. Received: 7 October 1998?Accepted: 9 October 1998