Refinement of defection strategies stabilizes cooperation

Cooperation among unrelated individuals is an enduring evolutionary riddle and a number of possible solutions have been suggested. Most of these suggestions attempt to refine cooperative strategies, while little attention is given to the fact that novel defection strategies can also evolve in the population. Especially in the presence of punishment to the defectors and public knowledge of strategies employed by the players, a defecting strategy that avoids getting punished by selectively cooperating only with the punishers can get a selective benefit over non-conditional defectors. Furthermore, if punishment ensures cooperation from such discriminating defectors, defectors who punish other defectors can evolve as well. We show that such discriminating and punishing defectors can evolve in the population by natural selection in a Prisoner’s Dilemma game scenario, even if discrimination is a costly act. These refined defection strategies destabilize unconditional defectors. They themselves are, however, unstable in the population. Discriminating defectors give selective benefit to the punishers in the presence of non-punishers by cooperating with them and defecting with others. However, since these players also defect with other discriminators they suffer fitness loss in the pure population. Among the punishers, punishing cooperators always benefit in contrast to the punishing defectors, as the latter not only defect with other punishing defectors but also punish them and get punished. As a consequence of both these scenarios, punishing cooperators get stabilized in the population. We thus show ironically that refined defection strategies stabilize cooperation. Furthermore, cooperation stabilized by such defectors can work under a wide range of initial conditions and is robust to mistakes.

A conditional random field-based downscaling method for assessment of climate change impact on multisite daily precipitation in the Mahanadi basin

Downscaling to station-scale hydrologic variables from large-scale atmospheric variables simulated by general circulation models (GCMs) is usually necessary to assess the hydrologic impact of climate change. This work presents CRF-downscaling, a new probabilistic downscaling method that represents the daily precipitation sequence as a conditional random field (CRF). The conditional distribution of the precipitation sequence at a site, given the daily atmospheric (large-scale) variable sequence, is modeled as a linear chain CRF. CRFs do not make assumptions on independence of observations, which gives them flexibility in using high-dimensional feature vectors. Maximum likelihood parameter estimation for the model is performed using limited memory Broyden-Fletcher-Goldfarb-Shanno (L-BFGS) optimization. Maximum a posteriori estimation is used to determine the most likely precipitation sequence for a given set of atmospheric input variables using the Viterbi algorithm. Direct classification of dry/wet days as well as precipitation amount is achieved within a single modeling framework. The model is used to project the future cumulative distribution function of precipitation. Uncertainty in precipitation prediction is addressed through a modified Viterbi algorithm that predicts the n most likely sequences. The model is applied for downscaling monsoon (June-September) daily precipitation at eight sites in the Mahanadi basin in Orissa, India, using the MIROC3.2 medium-resolution GCM. The predicted distributions at all sites show an increase in the number of wet days, and also an increase in wet day precipitation amounts. A comparison of current and future predicted probability density functions for daily precipitation shows a change in shape of the density function with decreasing probability of lower precipitation and increasing probability of higher precipitation.

Application of z-COSY experiment and its variant for accurate chiral discrimination by H-1 NMR

We report the application of z-COSY experiment and a band selected version of it by employing a selective 90 degrees pulse entitled BASE-z-COSY for precise chiral discrimination, quantification of enantiomeric excess and the analyses of the H-1 NMR spectra of chiral molecules aligned in the chiral liquid crystalline solvent poly-gamma-benzyl-L-glutamate (PBLG). We have demonstrated their applicability for obtaining very high resolution in the H-1 NMR spectra of small organic molecules. It is well known that the commonly employed z-COSY experiment disentangles the spectral complexity, provides pure phase spectra with high resolution, aids in the complete spectral analyses, in addition to yielding information on relative signs of the Couplings. The BASE-z-COSY experiment possesses all these properties, permits the measure of enantiomeric excess, in addition to large saving of instrument time.

Conditional Probability-Based Significance Tests for Sequential Patterns in Multineuronal Spike Trains

We consider the problem of detecting statistically significant sequential patterns in multineuronal spike trains. These patterns are characterized by ordered sequences of spikes from different neurons with specific delays between spikes. We have previously proposed a data-mining scheme to efficiently discover such patterns, which occur often enough in the data. Here we propose a method to determine the statistical significance of such repeating patterns. The novelty of our approach is that we use a compound null hypothesis that not only includes models of independent neurons but also models where neurons have weak dependencies. The strength of interaction among the neurons is represented in terms of certain pair-wise conditional probabilities. We specify our null hypothesis by putting an upper bound on all such conditional probabilities. We construct a probabilistic model that captures the counting process and use this to derive a test of significance for rejecting such a compound null hypothesis. The structure of our null hypothesis also allows us to rank-order different significant patterns. We illustrate the effectiveness of our approach using spike trains generated with a simulator.

Sequential split vector quantization of LSF parameters using conditional PDF

A better performing product code vector quantization (VQ) method is proposed for coding the line spectrum frequency (LSF) parameters; the method is referred to as sequential split vector quantization (SeSVQ). The split sub-vectors of the full LSF vector are quantized in sequence and thus uses conditional distribution derived from the previous quantized sub-vectors. Unlike the traditional split vector quantization (SVQ) method, SeSVQ exploits the inter sub-vector correlation and thus provides improved rate-distortion performance, but at the expense of higher memory. We investigate the quantization performance of SeSVQ over traditional SVQ and transform domain split VQ (TrSVQ) methods. Compared to SVQ, SeSVQ saves 1 bit and nearly 3 bits, for telephone-band and wide-band speech coding applications respectively.

Strain-Temperature Discrimination Using a Single Fiber Bragg Grating

The out-diffusion of germanium from the core of a photosensitive fiber under elevated temperature is exploited to form a Fabry-Perot filter within a single fiber Bragg grating, by subjecting the diffused region to a single exposure using the standard phase-mask technique. A key aspect of our work is the measurement of the out-diffusion through energy dispersive X-ray analysis. Furthermore, we demonstrate the use of the above single-grating filter for discrimination and simultaneous measurement of strain and temperature. The proposed technique provides a significant advantage over other existing methods that require at least two gratings.

Non-destructive discrimination of Bell states by NMR using a single ancilla qubit

Discrimination of Bell states plays an important role in a number of quantum computational protocols such as teleportation and secret sharing. However, most of the protocols dealing with Bell state discrimination in the literature either involve performing correlated measurements or destroying the entanglement of the system. Here, we demonstrate an NMR-based experimental realization of a protocol for Bell state discrimination, following a scheme proposed by Gupta et al (quant-ph/0504183v1, 23 April 2005), which does not destroy the Bell state under consideration. Using the proposed protocol, one can deterministically distinguish the Bell states, without performing a measurement using the entangled basis. State discrimination is performed through two independent measurements on one ancilla qubit, which leaves the Bell states unchanged.

Conditional linearization in nonlinear random vibration

In this paper, an improved probabilistic linearization approach is developed to study the response of nonlinear single degree of freedom (SDOF) systems under narrow-band inputs. An integral equation for the probability density function (PDF) of the envelope is derived. This equation is solved using an iterative scheme. The technique is applied to study the hardening type Duffing's oscillator under narrow-band excitation. The results compare favorably with those obtained using numerical simulation. In particular, the bimodal nature of the PDF for the response envelope for certain parameter ranges is brought out.

Modulation of lifetimes and diastereomeric discrimination in triplet-excited substituted butane-1,4-diones through intramolecular charge-transfer quenching

Triplet lifetimes have been determined for the diastereomers of a broad set of butane-l,4-dione derivatives (1-3). A remarkable dependence of lifetimes on conformational preferences is revealed in that the lifetimes are shorter for the meso diastereomers of 1-3 than those for the racemic ones. The intramolecular beta-phenyl quenching is promoted in the case of meso diastereomers by virtue of the gauche relationship between the excited carbonyl group and the beta-aryl ring, while a distal arrangement in the lowest energy conformation (H-anti) in racemic diastereomers prevents such a deactivation. The involvement of charge transfer in the intramolecular beta-phenyl quenching is suggested by the correlation of the triplet lifetimes of the meso diastereomers of compounds 2 with the nature of the substituent on the beta-phenyl rings. In the case of racemic diastereomers, beta-methoxy substitution on the beta-phenyl ring (2-OCH3, 3-OCH3) also led to a decrease of the triplet lifetimes when compared to those of the nonsubstituted compounds (2-H, 3-H). This shortening is accounted for by the deactivation of a small proportion of the excited molecules through beta-phenyl quenching. In addition to the above factors, the lifetimes in the case of meso diastereomers can further be controlled by increasing the energy spacing between the T-1 and T-2 states, since beta-phenyl quenching occurs from the latter for compounds 2 and 3. Through a rational conformational control, a surprisingly long triplet lifetime (300 ns) has been measured for the first time for a purely n,pi* triplet-excited beta-phenylpropiophenone dimer (1-rac).

Assessment of conditional moment closure models of turbulent autoignition using DNS data

A systematic assessment of the submodels of conditional moment closure (CMC) formalism for the autoignition problem is carried out using direct numerical simulation (DNS) data. An initially non-premixed, n-heptane/air system, subjected to a three-dimensional, homogeneous, isotropic, and decaying turbulence, is considered. Two kinetic schemes, (1) a one-step and (2) a reduced four-step reaction mechanism, are considered for chemistry An alternative formulation is developed for closure of the mean chemical source term , based on the condition that the instantaneous fluctuation of excess temperature is small. With this model, it is shown that the CMC equations describe the autoignition process all the way up to near the equilibrium limit. The effect of second-order terms (namely, conditional variance of temperature excess sigma(2) and conditional correlations of species q(ij)) in modeling is examined. Comparison with DNS data shows that sigma(2) has little effect on the predicted conditional mean temperature evolution, if the average conditional scalar dissipation rate is properly modeled. Using DNS data, a correction factor is introduced in the modeling of nonlinear terms to include the effect of species fluctuations. Computations including such a correction factor show that the species conditional correlations q(ij) have little effect on model predictions with a one-step reaction, but those q(ij) involving intermediate species are found to be crucial when four-step reduced kinetics is considered. The "most reactive mixture fraction" is found to vary with time when a four-step kinetics is considered. First-order CMC results are found to be qualitatively wrong if the conditional mean scalar dissipation rate is not modeled properly. The autoignition delay time predicted by the CMC model compares excellently with DNS results and shows a trend similar to experimental data over a range of initial temperatures.

Implementation of conditional phase-shift gate for quantum information processing by NMR, using transition-selective pulses

Experimental realization of quantum information processing in the field of nuclear magnetic resonance (NMR) has been well established. Implementation of conditional phase-shift gate has been a significant step, which has lead to realization of important algorithms such as Grover's search algorithm and quantum Fourier transform. This gate has so far been implemented in NMR by using coupling evolution method. We demonstrate here the implementation of the conditional phase-shift gate using transition selective pulses. As an application of the gate, we demonstrate Grover's search algorithm and quantum Fourier transform by simulations and experiments using transition selective pulses. (C) 2002 Elsevier Science (USA). All rights reserved.

Development of recombinant coat protein antibody based IC-RT-PCR for detection and discrimination of sugarcane streak mosaic virus isolates from Southern India

Sugarcane streak mosaic virus (SCSMV), causes mosaic disease of sugarcane and is thought to belong to a new undescribed genus in the family Potyviridae. The coat protein (CP) gene from the Andhra Pradesh (AP) isolate of SCSMV (SCSMV AP) was cloned and expressed in Escherichia coli. The recombinant coat protein was used to raise high quality antiserum. The CP antiserum was used to develop an immunocapture reverse transcription-polymerase chain reaction (IC-RT-PCR) based assay for the detection and discrimination of SCSMV isolates in South India. The sequence of the cloned PCR products encoding 3'untranslated region (UTR) and CP regions of the virus isolates from three different locations in South India viz. Tanuku (Coastal Andhra Pradesh), Coimbatore (Tamil Nadu) and Hospet (Karnataka) was compared with that of SCSMV AP The analysis showed that they share 89.4, 89.5 and 90% identity respectively at the nucleotide level. This suggests that the isolates causing mosaic disease of sugarcane in South India are indeed strains of SCSMV In addition, the sensitivity of the IC-RT-PCR was compared with direct antigen coating-enzyme linked immunosorbent assay (DAC-ELISA) and dot-blot immunobinding assays and was found to be more sensitive and hence could be used to detect the presence of virus in sugarcane breeding, germplasm centres and in quarantine programs.