The Partial Visibility Representation Extension Problem

For a graph $G$, a function $\psi$ is called a \emph{bar visibility representation} of $G$ when for each vertex $v \in V(G)$, $\psi(v)$ is a horizontal line segment (\emph{bar}) and $uv \in E(G)$ iff there is an unobstructed, vertical, $\varepsilon$-wide line of sight between $\psi(u)$ and $\psi(v)$. Graphs admitting such representations are well understood (via simple characterizations) and recognizable in linear time. For a directed graph $G$, a bar visibility representation $\psi$ of $G$, additionally, puts the bar $\psi(u)$ strictly below the bar $\psi(v)$ for each directed edge $(u,v)$ of $G$. We study a generalization of the recognition problem where a function $\psi'$ defined on a subset $V'$ of $V(G)$ is given and the question is whether there is a bar visibility representation $\psi$ of $G$ with $\psi(v) = \psi'(v)$ for every $v \in V'$. We show that for undirected graphs this problem together with closely related problems are \NP-complete, but for certain cases involving directed graphs it is solvable in polynomial time.Comment: Appears in the Proceedings of the 24th International Symposium on Graph Drawing and Network Visualization (GD 2016

Knuthian Drawings of Series-Parallel Flowcharts

Inspired by a classic paper by Knuth, we revisit the problem of drawing flowcharts of loop-free algorithms, that is, degree-three series-parallel digraphs. Our drawing algorithms show that it is possible to produce Knuthian drawings of degree-three series-parallel digraphs with good aspect ratios and small numbers of edge bends.Comment: Full versio

Planar Embeddings with Small and Uniform Faces

Motivated by finding planar embeddings that lead to drawings with favorable aesthetics, we study the problems MINMAXFACE and UNIFORMFACES of embedding a given biconnected multi-graph such that the largest face is as small as possible and such that all faces have the same size, respectively. We prove a complexity dichotomy for MINMAXFACE and show that deciding whether the maximum is at most $k$ is polynomial-time solvable for $k \leq 4$ and NP-complete for $k \geq 5$. Further, we give a 6-approximation for minimizing the maximum face in a planar embedding. For UNIFORMFACES, we show that the problem is NP-complete for odd $k \geq 7$ and even $k \geq 10$. Moreover, we characterize the biconnected planar multi-graphs admitting 3- and 4-uniform embeddings (in a $k$-uniform embedding all faces have size $k$) and give an efficient algorithm for testing the existence of a 6-uniform embedding.Comment: 23 pages, 5 figures, extended version of 'Planar Embeddings with Small and Uniform Faces' (The 25th International Symposium on Algorithms and Computation, 2014

Decoherence in Ion Trap Quantum Computers

The {\it intrinsic} decoherence from vibrational coupling of the ions in the Cirac-Zoller quantum computer [Phys. Rev. Lett. {\bf 74}, 4091 (1995)] is considered. Starting from a state in which the vibrational modes are at a temperature $T$, and each ion is in a superposition of an excited and a ground state, an adiabatic approximation is used to find the inclusive probability $P(t)$ for the ions to evolve as they would without the vibrations, and for the vibrational modes to evolve into any final state. An analytic form is found for $P(t)$ at $T=0$, and the decoherence time is found for all $T$. The decoherence is found to be quite small, even for 1000 ions.Comment: 11 pages, no figures, uses revte

Oxypred: prediction and classification of oxygen-binding proteins

This study describes a method for predicting and classifying oxygen-binding proteins. Firstly, support vector machine (SVM) modules were developed using amino acid composition and dipeptide composition for predicting oxygen-binding proteins, and achieved maximum accuracy of 85.5% and 87.8%, respectively. Secondly, an SVM module was developed based on amino acid composition, classifying the predicted oxygen-binding proteins into six classes with accuracy of 95.8%, 97.5%, 97.5%, 96.9%, 99.4%, and 96.0% for erythrocruorin, hemerythrin, hemocyanin, hemoglobin, leghemoglobin, and myoglobin proteins, respectively. Finally, an SVM module was developed using dipeptide composition for classifying the oxygen-binding proteins, and achieved maximum accuracy of 96.1%, 98.7%, 98.7%, 85.6%, 99.6%, and 93.3% for the above six classes, respectively. All modules were trained and tested by five-fold cross validation. Based on the above approach, a web server Oxypred was developed for predicting and classifying oxygen-binding proteins (available from http://www.imtech.res.in/raghava/oxypred/)

Abstract Learning Frameworks for Synthesis

We develop abstract learning frameworks (ALFs) for synthesis that embody the principles of CEGIS (counter-example based inductive synthesis) strategies that have become widely applicable in recent years. Our framework defines a general abstract framework of iterative learning, based on a hypothesis space that captures the synthesized objects, a sample space that forms the space on which induction is performed, and a concept space that abstractly defines the semantics of the learning process. We show that a variety of synthesis algorithms in current literature can be embedded in this general framework. While studying these embeddings, we also generalize some of the synthesis problems these instances are of, resulting in new ways of looking at synthesis problems using learning. We also investigate convergence issues for the general framework, and exhibit three recipes for convergence in finite time. The first two recipes generalize current techniques for convergence used by existing synthesis engines. The third technique is a more involved technique of which we know of no existing instantiation, and we instantiate it to concrete synthesis problems

Pressure-induced amorphization, crystal-crystal transformations and the memory glass effect in interacting particles in two dimensions

We study a model of interacting particles in two dimensions to address the relation between crystal-crystal transformations and pressure-induced amorphization. On increasing pressure at very low temperature, our model undergoes a martensitic crystal-crystal transformation. The characteristics of the resulting polycrystalline structure depend on defect density, compression rate, and nucleation and growth barriers. We find two different limiting cases. In one of them the martensite crystals, once nucleated, grow easily perpendicularly to the invariant interface, and the final structure contains large crystals of the different martensite variants. Upon decompression almost every atom returns to its original position, and the original crystal is fully recovered. In the second limiting case, after nucleation the growth of martensite crystals is inhibited by energetic barriers. The final morphology in this case is that of a polycrystal with a very small crystal size. This may be taken to be amorphous if we have only access (as experimentally may be the case) to the angularly averaged structure factor. However, this `X-ray amorphous' material is anisotropic, and this shows up upon decompression, when it recovers the original crystalline structure with an orientation correlated with the one it had prior to compression. The memory effect of this X-ray amorphous material is a natural consequence of the memory effect associated to the underlying martensitic transformation. We suggest that this kind of mechanism is present in many of the experimental observations of the memory glass effect, in which a crystal with the original orientation is recovered from an apparently amorphous sample when pressure is released.Comment: 13 pages, 13 figures, to be published in Phys. Rev.

Quantum Relaxation of Magnetisation in Magnetic Particles

At temperatures below the magnetic anisotropy energy, monodomain magnetic systems (small particles, nanomagnetic devices, etc.) must relax quantum mechanically. This quantum relaxation must be mediated by the coupling to both nuclear spins and phonons (and electrons if either particle or substrate is conducting. We analyze the effect of each of these couplings, and then combine them. Conducting systems can be modelled by a "giant Kondo" Hamiltonian, with nuclear spins added in as well. At low temperatures, even microscopic particles on a conducting substrate (containing only $10-50$ spins) will have their magnetisation frozen over millenia by a combination of electronic dissipation and the "degeneracy blocking" caused by nuclear spins. Raising the temperature leads to a sudden unblocking of the spin dynamics at a well defined temperature. Insulating systems are quite different. The relaxation is strongly enhanced by the coupling to nuclear spins. At short times the magnetisation of an ensemble of particles relaxes logarithmically in time, after an initial very fast decay; this relaxation proceeds entirely via the nuclear spins. At longer times phonons take over, but the decay rate is still governed by the temperature-dependent nuclear bias field acting on the particles - decay may be exponential or power-law depending on the temperature. The most surprising feature of the results is the pivotal role played by the nuclear spins. The results are relevant to any experiments on magnetic particles in which interparticle dipolar interactions are unimportant. They are also relevant to future magnetic device technology.Comment: 30 pages, RevTex, e:mail , Submitted to J.Low Temp.Phys. on 1 Nov. 199

Planar L-Drawings of Directed Graphs

We study planar drawings of directed graphs in the L-drawing standard. We provide necessary conditions for the existence of these drawings and show that testing for the existence of a planar L-drawing is an NP-complete problem. Motivated by this result, we focus on upward-planar L-drawings. We show that directed st-graphs admitting an upward- (resp. upward-rightward-) planar L-drawing are exactly those admitting a bitonic (resp. monotonically increasing) st-ordering. We give a linear-time algorithm that computes a bitonic (resp. monotonically increasing) st-ordering of a planar st-graph or reports that there exists none.Comment: Appears in the Proceedings of the 25th International Symposium on Graph Drawing and Network Visualization (GD 2017

Spectrum of lactobacillus species present in healthy vagina of Indian women

Background & objectives: Lactobacilli are depleted in vagina of women suffering from recurring episodes of bacterial vaginosis with vaginal pH≥5. With the objective of making available probiotic lactobacilli for replenishment in such women, a study was undertaken to isolate and characterize the Lactobacilli present in women with eco-healthy vagina in Delhi. No information is so far available on the species of Lactobacilli resident in vagina of women in India. Methods: Vaginal swabs were taken from 80 women with informed consent after ethical approval and grown in MRS broth. Gram-positive, catalase-negative bacilli generating about 200 bp amplicon by PCR with Lactobacillus genus specifi c primers were further characterized by employing species specifi c primers followed by sequencing of 16S rDNA. Isolates of the same species were differentiated by random amplifi ed polymorphic DNA (RAPD) profi les. Results: The predominant species isolated were L. reuteri present in 26 (32.5%) women, L. fermentum in 20 (25%), and L. salivarius in 13 (16.25%) women. Sequencing of 16S rDNA of 20 isolates showed that except for two isolates of L. plantarum, sequences of the remaining agreed well with PCR identification. None of the isolates had similar RAPD profile. Interpretation & conclusions: Our fi ndings showed lactobacilli species present in healthy vagina of women in India differ from those reported from other countries. This information would be useful to development of probiotic tablets seeking to replenish the missing lactobacilli for reproductive health of women in India