Cyclotron Resonance Study of the Two-Dimensional Electron Layers and Double-Layers in Tilted Magnetic Fields

The far-infrared absorption in two-dimensional electron layers subject to magnetic field of general orientation was studied theoretically. The Kubo formula is employed to derive diagonal components of the magneto-conductivity tensor of two-dimensional electron single-layers and double-layers. The parabolic quantum well is used to model a simple single-layer system. Both single-layer and double-layer systems can be realized in a pair of tunnel-coupled, strictly two-dimensional quantum wells. Obtained results are compared to experimental data.Comment: 4 pages, 6 figures, elsart/PHYEAUTH macros; presented on the EP2DS-15 Conference in Nara, Japan. To be published in Physica

Broadcasting through a noisy one-dimensional network

We study the expected time complexity of two graph partitioning problems: the graph coloring and the cut into equal parts. If $k=o(\sqrt{n/\log n})$, we can test whether two vertices of a $k$-colorable graph can be $k$-colored by the same color in time $O(k\log n)$ per pair of vertices with $O(k^4\log^3n)$-time preprocessing in such a way that for almost all $k$-colorable graphs the answer is correct for all pairs of vertices. As a consequence, we obtain a sublinear (with respect to the number of edges) expected time algorithm for $k$-coloring of $k$-colorable graphs (assuming the uniform input distribution). Similarly, if $c\le (1/8-\epsilon)n^2$, $\epsilon>0$ a constant, and $G$ is a graph having cut of the vertex set into two equal parts with at most $c$ cross-edges, we can test whether two vertices belong to the same class of some $c$-cut in time $O(\log n)$ per vertex with $O(\log^3n)$-time preprocessing in such a way that for almost all graphs having a $c$-cut the answer is correct for all pairs of vertices. The methods presented in the paper can also be used to other graph partitioning problems, e.g. the largest clique or independent subset

Arithmetic complexity via effective names for random sequences

We investigate enumerability properties for classes of sets which permit recursive, lexicographically increasing approximations, or left-r.e. sets. In addition to pinpointing the complexity of left-r.e. Martin-L\"{o}f, computably, Schnorr, and Kurtz random sets, weakly 1-generics and their complementary classes, we find that there exist characterizations of the third and fourth levels of the arithmetic hierarchy purely in terms of these notions. More generally, there exists an equivalence between arithmetic complexity and existence of numberings for classes of left-r.e. sets with shift-persistent elements. While some classes (such as Martin-L\"{o}f randoms and Kurtz non-randoms) have left-r.e. numberings, there is no canonical, or acceptable, left-r.e. numbering for any class of left-r.e. randoms. Finally, we note some fundamental differences between left-r.e. numberings for sets and reals

Sensitivity to species selection indicates the effect of nuisance variables on marine microfossil transfer functions

The species composition of many groups of marine plankton appears well predicted by sea surface temperature (SST). Consequently, fossil plankton assemblages have been widely used to reconstruct past SST. Most applications of this approach make use of the highest possible taxonomic resolution. However, not all species are sensitive to temperature, and their distribution may be governed by other parameters. There are thus reasons to question the merit of including information about all species, both for transfer function performance and for its effect on reconstructions. Here we investigate the effect of species selection on planktonic foraminifera transfer functions. We assess species importance for transfer function models using a random forest technique and evaluate the performance of models with an increasing number of species. Irrespective of using models that use the entire training set (weighted averaging) or models that use only a subset of the training set (modern analogue technique), we find that the majority of foraminifera species does not carry useful information for temperature reconstruction. Less than one-third of the species in the training set is required to provide a temperature estimate with a prediction error comparable to a transfer function that uses all species in the training set. However, species selection matters for paleotemperature estimates. We find that transfer function models with a different number of species but with the same error may yield different reconstructions of sea surface temperature when applied to the same fossil assemblages. This ambiguity in the reconstructions implies that fossil assemblage change reflects a combination of temperature and other environmental factors. The contribution of the additional factors is site and time specific, indicating ecological and geological complexity in the formation of the sedimentary assemblages. The possibility of obtaining multiple different reconstructions from a single sediment record presents a previously unrecognized source of uncertainty for sea surface temperature estimates based on planktonic foraminifera assemblages. This uncertainty can be evaluated by determining the sensitivity of the reconstructions to species pruning.</p

Multivariate calibration approach for quantitative determination of cell-line cross contamination by intact cell mass spectrometry and artificial neural networks

Cross-contamination of eukaryotic cell lines used in biomedical research represents a highly relevant problem. Analysis of repetitive DNA sequences, such as Short Tandem Repeats (STR), or Simple Sequence Repeats (SSR), is a widely accepted, simple, and commercially available technique to authenticate cell lines. However, it provides only qualitative information that depends on the extent of reference databases for interpretation. In this work, we developed and validated a rapid and routinely applicable method for evaluation of cell culture cross-contamination levels based on mass spectrometric fingerprints of intact mammalian cells coupled with artificial neural networks (ANNs). We used human embryonic stem cells (hESCs) contaminated by either mouse embryonic stem cells (mESCs) or mouse embryonic fibroblasts (MEFs) as a model. We determined the contamination level using a mass spectra database of known calibration mixtures that served as training input for an ANN. The ANN was then capable of correct quantification of the level of contamination of hESCs by mESCs or MEFs. We demonstrate that MS analysis, when linked to proper mathematical instruments, is a tangible tool for unraveling and quantifying heterogeneity in cell cultures. The analysis is applicable in routine scenarios for cell authentication and/or cell phenotyping in general

Electronic Structure of Three-Dimensional Superlattices Subject to Tilted Magnetic Fields

Full quantum-mechanical description of electrons moving in 3D structures with unidirectional periodic modulation subject to tilted magnetic fields requires an extensive numerical calculation. To understand magneto-oscillations in such systems it is in many cases sufficient to use the quasi-classical approach, in which the zero-magnetic-field Fermi surface is considered as a magnetic-field-independent rigid body in k-space and periods of oscillations are related to extremal cross-sections of the Fermi surface cut by planes perpendicular to the magnetic-field direction. We point out cases where the quasi-classical treatment fails and propose a simple tight-binding fully-quantum-mechanical model of the superlattice electronic structure.Comment: 8 pages, 7 figures, RevTex, submitted to Phys. Rev.

Priming Older Adults and People with Alzheimer’s Disease Analogical Problem Solving with True and False Memories

We investigated the extent to which activation of specific information in associative networks during a memory task could facilitate subsequent analogical problem solving in healthy older adults as well as those with early onset Alzheimer’s disease. We also examined whether these priming effects were stronger when the activation of the critical solution term during the memory task occurred when the item was actually presented (true memories) or when this item arose due to spreading activation to a related but nonpresented item (false memory). Older adult controls (OACs) and people with Alzheimer’s disease (AD) were asked to solve 9 verbal proportional analogies, 3 of which had been primed by Deese/Roediger-McDermott lists where the critical lure (and problem solution) was presented as a word in the list (true memory), 3 of which were primed by DRM lists whose critical lures were spontaneously activated during list presentation (false memory), and 3 of which were unprimed. As expected, OACs were better (both in terms of speed and accuracy) at solving problems than people with AD and both groups were better when false memories were primes than when true memories were primes or there were no primes. There were no reliable differences between unprimed and true prime problems. These findings demonstrate that (a) priming of problem solutions extends to verbal proportional analogies in OACs and people with AD, (b) false memories are more effective at priming problem solutions than true memories, and (c) there are clear positive consequences to the production of false memories