Cloud Water Content Sensor for Sounding Balloons and Small UAVs

A lightweight, battery-powered sensor was developed for measuring cloud water content, which is the amount of liquid or solid water present in a cloud, generally expressed as grams of water per cubic meter. This sensor has near-zero power consumption and can be flown on standard sounding balloons and small, unmanned aerial vehicles (UAVs). The amount of solid or liquid water is important to the study of atmospheric processes and behavior. Previous sensing techniques relied on strongly heating the incoming air, which requires a major energy input that cannot be achieved on sounding balloons or small UAVs

Multimode pulsation of the ZZ Ceti star GD 154

We present the results of a comparative period search on different time-scales and modelling of the ZZ Ceti (DAV) star GD 154. We determined six frequencies as normal modes and four rotational doublets around the ones having the largest amplitude. Two normal modes at 807.62 and 861.56 microHz have never been reported before. A rigorous test revealed remarkable intrinsic amplitude variability of frequencies at 839.14 and 861.56 microHz over a 50 d time-scale. In addition, the multimode pulsation changed to monoperiodic pulsation with an 843.15 microHz dominant frequency at the end of the observing run. The 2.76 microHz average rotational split detected led to a determination of a 2.1 d rotational period for GD 154. We searched for model solutions with effective temperatures and log g close to the spectroscopically determined ones. The best-fitting models resulting from the grid search have M_H between 6.3 x 10^-5 and 6.3 x 10^-7 M*, which means thicker hydrogen layer than the previous studies suggested. Our investigations show that mode trapping does not necessarily operate in all of the observed modes and the best candidate for a trapped mode is at 2484 microHz.Comment: 11 pages, 11 figures, accepted for publication in MNRA

On Gauge Invariance and Spontaneous Symmetry Breaking

We show how the widely used concept of spontaneous symmetry breaking can be explained in causal perturbation theory by introducing a perturbative version of quantum gauge invariance. Perturbative gauge invariance, formulated exclusively by means of asymptotic fields, is discussed for the simple example of Abelian U(1) gauge theory (Abelian Higgs model). Our findings are relevant for the electroweak theory, as pointed out elsewhere.Comment: 13 pages, latex, no figure

White Dwarf Period Tables I. Pulsators with hydrogen-dominated atmospheres

We aimed at collecting all known white dwarf pulsators with hydrogen-dominated atmospheres and list their main photometric and atmospheric parameters together with their pulsation periods and amplitudes observed at different epochs. For this purpose, we explored the pulsating white dwarf related literature with the systematic use of the SIMBAD and the NASA's Astrophysics Data System (ADS) databases. We summarized our results in four tables listing seven ZZ Ceti stars in detached white dwarf plus main-sequence binaries, seven extremely low-mass DA pulsators, three hot DAVs and 180 ZZ Ceti stars

Glaciation Traces in the Area of the Risnjak Mountain Massif.

The area of the Risnjak mountain massif is a submorphological region - part of the mesomorphological region of the south-western Gorski Kotar. This area exceeds 1,500 metres in height. In the relief structure of the massif, the system of ranges and erosion surfaces - plateaux, has been formed on the folded-block, mostly carbonate base by subsequent microtectonic activity and exomorphological processes. Such relationships of relief under conditions of exceptionally low temperatures and abundance of snow precipitation during the Pleistocene, were prerequisites for the development of glaciation. Glaciation of the mountain massif was marked by formation of the valley, plateau and cirque glaciers, which is proved by the discovery of glacial moraines and other morphological features and corresponding sediments

Common Space of Spin and Spacetime

Given Lorentz invariance in Minkowski spacetime, we investigate a common space of spin and spacetime. To obtain a finite spinor representation of the non-compact homogeneous Lorentz group including Lorentz boosts, we introduce an indefinite inner product space (IIPS) with a normalized positive probability. In this IIPS, the common momentum and common variable of a massive fermion turn out to be ``doubly strict plus-operators''. Due to this nice property, it is straightforward to show an uncertainty relation between fermion mass and proper time. Also in IIPS, the newly-defined Lagrangian operators are self-adjoint, and the fermion field equations are derivable from the Lagrangians. Finally, the nonlinear QED equations and Lagrangians are presented as an example.Comment: 17 pages, a reference corrected, final version published on Foundations of Physics Letters in June of 2005, as a personal tribute to Einstein and Dira

Space of State Vectors in PT Symmetrical Quantum Mechanics

Space of states of PT symmetrical quantum mechanics is examined. Requirement that eigenstates with different eigenvalues must be orthogonal leads to the conclusion that eigenfunctions belong to the space with an indefinite metric. The self consistent expressions for the probability amplitude and average value of operator are suggested. Further specification of space of state vectors yield the superselection rule, redefining notion of the superposition principle. The expression for the probability current density, satisfying equation of continuity and vanishing for the bound state, is proposed.Comment: Revised version, explicit expressions for average values and probability amplitude adde

Effect of age on discrimination learning, reversal learning, and cognitive bias in family dogs

Several studies on age-related cognitive decline in dogs involve laboratory dogs and prolonged training. We developed two spatial tasks that required a single 1-h session. We tested 107 medium-large sized dogs: \u201cyoung\u201d (N=41, aged 2.5\u20136.5 years) and \u201cold\u201d (N=66, aged 8\u201314.5 years). Our results indicated that, in a discrimination learning task and in a reversal learning task, young dogs learned significantly faster than the old dogs, indicating that these two tasks could successfully be used to investigate differences in spatial learning between young and old dogs. We also provide two novel findings. First, in the reversal learning, the dogs trained based on the location of stimuli learned faster than the dogs trained based on stimulus characteristics. Most old dogs did not learn the task within our cut-off of 50 trials. Training based on an object\u2019s location is therefore more appropriate for reversal learning tasks. Second, the contrast between the response to the positive and negative stimuli was narrower in old dogs, compared to young dogs, during the reversal learning task, as well as the cognitive bias test. This measure favors comparability between tasks and between studies. Following the cognitive bias test, we could not find any indication of differences in the positive and negative expectations between young and old dogs. Taken together, these findings do not support the hypothesis that old dogs have more negative expectations than young dogs and the use of the cognitive bias test in older dogs requires further investigation

High-Resolution Image Reconstruction from a Sequence of Rotated and Translated Frames and its Application to an Infrared Imaging System

Some imaging systems employ detector arrays that are not sufficiently dense to meet the Nyquist criterion during image acquisition. This is particularly true for many staring infrared imagers. Thus, the full resolution afforded by the optics is not being realized in such a system. This paper presents a technique for estimating a high-resolution image, with reduced aliasing, from a sequence of undersampled rotated and translationally shifted frames. Such an image sequence can be obtained if an imager is mounted on a moving platform, such as an aircraft. Several approaches to this type of problem have been proposed in the literature. Here we extend some of this previous work. In particular, we define an observation model that incorporates knowledge of the optical system and detector array. The high-resolution image estimate is formed by minimizing a regularized cost function based on the observation model. We show that with the proper choice of a tuning parameter, our algorithm exhibits robustness in the presence of noise. We consider both gradient descent and conjugate-gradient optimization procedures to minimize the cost function. Detailed experimental results are provided to illustrate the performance of the proposed algorithm using digital video from an infrared imager