CMB in a box: Causal structure and the Fourier-Bessel expansion

This paper makes two points. First, we show that the line-of-sight solution to cosmic microwave anisotropies in Fourier space, even though formally defined for arbitrarily large wavelengths, leads to position-space solutions which only depend on the sources of anisotropies inside the past light cone of the observer. This foretold manifestation of causality in position (real) space happens order by order in a series expansion in powers of the visibility gamma = e(-mu), where mu is the optical depth to Thomson scattering. We show that the contributions of order gamma(N) to the cosmic microwave background (CMB) anisotropies are regulated by spacetime window functions which have support only inside the past light cone of the point of observation. Second, we show that the Fourier-Bessel expansion of the physical fields (including the temperature and polarization momenta) is an alternative to the usual Fourier basis as a framework to compute the anisotropies. The viability of the Fourier-Bessel series for treating the CMB is a consequence of the fact that the visibility function becomes exponentially small at redshifts z >> 10(3), effectively cutting off the past light cone and introducing a finite radius inside which initial conditions can affect physical observables measured at our position (x) over right arrow = 0 and time t(0). Hence, for each multipole l there is a discrete tower of momenta k(il) (not a continuum) which can affect physical observables, with the smallest momenta being k(1l) similar to l. The Fourier-Bessel modes take into account precisely the information from the sources of anisotropies that propagates from the initial value surface to the point of observation-no more, no less. We also show that the physical observables (the temperature and polarization maps), and hence the angular power spectra, are unaffected by that choice of basis. This implies that the Fourier-Bessel expansion is the optimal scheme with which one can compute CMB anisotropies.

Network of recurrent events for the Olami-Feder-Christensen model

We numerically study the dynamics of a discrete spring-block model introduced by Olami, Feder, and Christensen (OFC) to mimic earthquakes and investigate to what extent this simple model is able to reproduce the observed spatiotemporal clustering of seismicity. Following a recently proposed method to characterize such clustering by networks of recurrent events [J. Davidsen, P. Grassberger, and M. Paczuski, Geophys. Res. Lett. 33, L11304 (2006)], we find that for synthetic catalogs generated by the OFC model these networks have many nontrivial statistical properties. This includes characteristic degree distributions, very similar to what has been observed for real seismicity. There are, however, also significant differences between the OFC model and earthquake catalogs, indicating that this simple model is insufficient to account for certain aspects of the spatiotemporal clustering of seismicity.

Dynamical generation of mass in the D = (2+1) Wess-Zumino model

In this work we study the dynamical generation of mass in the massless N = 1 Wess-Zumino model in a three-dimensional spacetime. Using the tadpole method to compute the effective potential, we observe that supersymmetry is dynamically broken together with the discrete symmetry A(x) -> A(x). We show that this model, different from nonsupersymmetric scalar models, exhibits a consistent perturbative dynamical generation of mass after two-loop corrections to the effective potential.

Non-Markovian dynamics of quantum discord

We evaluate the quantum discord dynamics of two qubits in independent and common non-Markovian environments. We compare the dynamics of entanglement with that of quantum discord. For independent reservoirs the quantum discord vanishes only at discrete instants whereas the entanglement can disappear during a finite time interval. For a common reservoir, quantum discord and entanglement can behave very differently with sudden birth of the former but not of the latter. Furthermore, in this case the quantum discord dynamics presents sudden changes in the derivative of its time evolution which is evidenced by the presence of kinks in its behavior at discrete instants of time.

gamma Cassiopeiae: an X-ray Be star with personality

An exciting unsolved problem in the study of high energy processes of early type stars concerns the physical mechanism for producing X-rays near the Be star gamma Cassiopeiae. By now we know that this source and several ""gamma Cas analogs"" exhibit an unusual hard thermal X-ray spectrum, compared both to normal massive stars and the non-thermal emission of known Be/X-ray binaries. Also, its light curve is variable on almost all conceivable timescales. In this study we reanalyze a high dispersion spectrum obtained by Chandra in 2001 and combine it with the analysis of a new (2004) spectrum and light curve obtained by XMM-Newton. We find that both spectra can be fit well with 3-4 optically thin, thermal components consisting of a hot component having a temperature kT(Q) similar to 12-14 keV, perhaps one with a value of similar to 2.4 keV, and two with well defined values near 0.6 keV and 0.11 keV. We argue that these components arise in discrete (almost monothermal) plasmas. Moreover, they cannot be produced within an integral gas structure or by the cooling of a dominant hot process. Consistent with earlier findings, we also find that the Fe abundance arising from K-shell ions is significantly subsolar and less than the Fe abundance from L-shell ions. We also find novel properties not present in the earlier Chandra spectrum, including a dramatic decrease in the local photoelectric absorption of soft X-rays, a decrease in the strength of the Fe and possibly of the Si K fluorescence features, underpredicted lines in two ions each of Ne and N (suggesting abundances that are similar to 1.5-3x and similar to 4x solar, respectively), and broadening of the strong NeXLy alpha and OVIII Ly alpha lines. In addition, we note certain traits in the gamma Cas spectrum that are different from those of the fairly well studied analog HD110432 - in this sense the stars have different ""personalities."" In particular, for gamma Cas the hot X-ray component remains nearly constant in temperature, and the photoelectric absorption of the X-ray plasmas can change dramatically. As found by previous investigators of gamma Cas, changes in flux, whether occurring slowly or in rapidly evolving flares, are only seldomly accompanied by variations in hardness. Moreover, the light curve can show a ""periodicity"" that is due to the presence of flux minima that recur semiregularly over a few hours, and which can appear again at different epochs.

Gene Expression Complex Networks: Synthesis, Identification, and Analysis

Thanks to recent advances in molecular biology, allied to an ever increasing amount of experimental data, the functional state of thousands of genes can now be extracted simultaneously by using methods such as cDNA microarrays and RNA-Seq. Particularly important related investigations are the modeling and identification of gene regulatory networks from expression data sets. Such a knowledge is fundamental for many applications, such as disease treatment, therapeutic intervention strategies and drugs design, as well as for planning high-throughput new experiments. Methods have been developed for gene networks modeling and identification from expression profiles. However, an important open problem regards how to validate such approaches and its results. This work presents an objective approach for validation of gene network modeling and identification which comprises the following three main aspects: (1) Artificial Gene Networks (AGNs) model generation through theoretical models of complex networks, which is used to simulate temporal expression data; (2) a computational method for gene network identification from the simulated data, which is founded on a feature selection approach where a target gene is fixed and the expression profile is observed for all other genes in order to identify a relevant subset of predictors; and (3) validation of the identified AGN-based network through comparison with the original network. The proposed framework allows several types of AGNs to be generated and used in order to simulate temporal expression data. The results of the network identification method can then be compared to the original network in order to estimate its properties and accuracy. Some of the most important theoretical models of complex networks have been assessed: the uniformly-random Erdos-Renyi (ER), the small-world Watts-Strogatz (WS), the scale-free Barabasi-Albert (BA), and geographical networks (GG). The experimental results indicate that the inference method was sensitive to average degree k variation, decreasing its network recovery rate with the increase of k. The signal size was important for the inference method to get better accuracy in the network identification rate, presenting very good results with small expression profiles. However, the adopted inference method was not sensible to recognize distinct structures of interaction among genes, presenting a similar behavior when applied to different network topologies. In summary, the proposed framework, though simple, was adequate for the validation of the inferred networks by identifying some properties of the evaluated method, which can be extended to other inference methods.

On the k-restricted structure ratio in planar and outerplanar graphs

A planar k-restricted structure is a simple graph whose blocks are planar and each has at most k vertices. Planar k-restricted structures are used by approximation algorithms for Maximum Weight Planar Subgraph, which motivates this work. The planar k-restricted ratio is the infimum, over simple planar graphs H, of the ratio of the number of edges in a maximum k-restricted structure subgraph of H to the number edges of H. We prove that, as k tends to infinity, the planar k-restricted ratio tends to 1/2. The same result holds for the weighted version. Our results are based on analyzing the analogous ratios for outerplanar and weighted outerplanar graphs. Here both ratios tend to 1 as k goes to infinity, and we provide good estimates of the rates of convergence, showing that they differ in the weighted from the unweighted case.

Gibbs random graphs on point processes

Consider a discrete locally finite subset Gamma of R(d) and the cornplete graph (Gamma, E), with vertices Gamma and edges E. We consider Gibbs measures on the set of sub-graphs with vertices Gamma and edges E` subset of E. The Gibbs interaction acts between open edges having a vertex in common. We study percolation properties of the Gibbs distribution of the graph ensemble. The main results concern percolation properties of the open edges in two cases: (a) when Gamma is sampled from a homogeneous Poisson process; and (b) for a fixed Gamma with sufficiently sparse points. (c) 2010 American Institute of Physics. [doi:10.1063/1.3514605]

On the asymptotic enumeration of accessible automata

We simplify the known formula for the asymptotic estimate of the number of deterministic and accessible automata with n states over a k-letter alphabet. The proof relies on the theory of Lagrange inversion applied in the context of generalized binomial series.

Self-organized distribution of periodicity and chaos in an electrochemical oscillator

We report a detailed numerical investigation of a prototype electrochemical oscillator, in terms of high-resolution phase diagrams for an experimentally relevant section of the control (parameter) space. The prototype model consists of a set of three autonomous ordinary differential equations which captures the general features of electrochemical oscillators characterized by a partially hidden negative differential resistance in an N-shaped current-voltage stationary curve. By computing Lyapunov exponents, we provide a detailed discrimination between chaotic and periodic phases of the electrochemical oscillator. Such phases reveal the existence of an intricate structure of domains of periodicity self-organized into a chaotic background. Shrimp-like periodic regions previously observed in other discrete and continuous systems were also observed here, which corroborate the universal nature of the occurrence of such structures. In addition, we have also found a structured period distribution within the order region. Finally we discuss the possible experimental realization of comparable phase diagrams.

Meiobenthic communities of seagrass beds (Zostera capricorni) and unvegetated sediments along the coast of New South Wales, Australia

Seagrass beds have higher biomass, abundance, diversity and productivity of benthic organisms than unvegetated sediments. However, to date most studies have analysed only the macrofaunal component and ignored the abundant meiofauna present in seagrass meadows. This study was designed to test if meiobenthic communities, especially the free-living nematodes, differed between seagrass beds and unvegetated sediments. Sediment samples from beds of the eelgrass Zostera capricorni and nearby unvegetated sediments were collected in three estuaries along the coast of New South Wales, Australia. Results showed that sediments below the seagrass were finer, with a higher content of organic material and were less oxygenated than sediments without seagrass. Univariate measures of the fauna (i.e. abundance, diversity and taxa richness of total meiofauna and nematode assemblages) did not differ between vegetated and unvegetated sediments. However multivariate analysis of meiofaunal higher taxa showed significant differences between the two habitats, largely due to the presence and absence of certain taxa. Amphipods, tanaidacea, ostracods, hydrozoans and isopods occurred mainly in unvegetated sediments, while kinorhyncs, polychaetes, gastrotrichs and turbellarians were more abundant in vegetated sediments. Regarding the nematode assemblages, 32.4% of the species were restricted to Z. capricorni and 25% only occurred in unvegetated sediments, this suggests that each habitat is characterized by a particular suite of species. Epistrate feeding nematodes were more abundant in seagrass beds, and it is suggested that they graze on the microphytobenthos which accumulates underneath the seagrass. Most of the genera that characterized these estuarine unvegetated sediments are also commonly found on exposed sandy beaches. This may be explained by the fact that Australian estuaries have very little input of freshwater and experience marine conditions for most of the year. This study demonstrates that the seagrass and unvegetated sediments have discrete meiofaunal communities, with little overlap in species composition. (C) 2010 Elsevier Ltd. All rights reserved.

Kernel machines for epilepsy diagnosis via EEG signal classification: A comparative study

Objective: We carry out a systematic assessment on a suite of kernel-based learning machines while coping with the task of epilepsy diagnosis through automatic electroencephalogram (EEG) signal classification. Methods and materials: The kernel machines investigated include the standard support vector machine (SVM), the least squares SVM, the Lagrangian SVM, the smooth SVM, the proximal SVM, and the relevance vector machine. An extensive series of experiments was conducted on publicly available data, whose clinical EEG recordings were obtained from five normal subjects and five epileptic patients. The performance levels delivered by the different kernel machines are contrasted in terms of the criteria of predictive accuracy, sensitivity to the kernel function/parameter value, and sensitivity to the type of features extracted from the signal. For this purpose, 26 values for the kernel parameter (radius) of two well-known kernel functions (namely. Gaussian and exponential radial basis functions) were considered as well as 21 types of features extracted from the EEG signal, including statistical values derived from the discrete wavelet transform, Lyapunov exponents, and combinations thereof. Results: We first quantitatively assess the impact of the choice of the wavelet basis on the quality of the features extracted. Four wavelet basis functions were considered in this study. Then, we provide the average accuracy (i.e., cross-validation error) values delivered by 252 kernel machine configurations; in particular, 40%/35% of the best-calibrated models of the standard and least squares SVMs reached 100% accuracy rate for the two kernel functions considered. Moreover, we show the sensitivity profiles exhibited by a large sample of the configurations whereby one can visually inspect their levels of sensitiveness to the type of feature and to the kernel function/parameter value. Conclusions: Overall, the results evidence that all kernel machines are competitive in terms of accuracy, with the standard and least squares SVMs prevailing more consistently. Moreover, the choice of the kernel function and parameter value as well as the choice of the feature extractor are critical decisions to be taken, albeit the choice of the wavelet family seems not to be so relevant. Also, the statistical values calculated over the Lyapunov exponents were good sources of signal representation, but not as informative as their wavelet counterparts. Finally, a typical sensitivity profile has emerged among all types of machines, involving some regions of stability separated by zones of sharp variation, with some kernel parameter values clearly associated with better accuracy rates (zones of optimality). (C) 2011 Elsevier B.V. All rights reserved.

An opinion dynamics model for the diffusion of innovations

We study the dynamics of the adoption of new products by agents with continuous opinions and discrete actions (CODA). The model is such that the refusal in adopting a new idea or product is increasingly weighted by neighbor agents as evidence against the product. Under these rules, we study the distribution of adoption times and the final proportion of adopters in the population. We compare the cases where initial adopters are clustered to the case where they are randomly scattered around the social network and investigate small world effects on the final proportion of adopters. The model predicts a fat tailed distribution for late adopters which is verified by empirical data. (C) 2009 Elsevier B.V. All rights reserved.

Somesthetic, gustatory, olfactory function and salivary flow in patients with neuropathic trigeminal pain

OBJECTIVES: To determine somesthetic, olfactory, gustative and salivary abnormalities in patients with burning mouth syndrome (BMS), idiopathic trigeminal neuralgia (ITN) and trigeminal postherpetic neuralgia (PHN). SUBJECTS AND METHODS: Twenty patients from each group (BMS, ITN, PHN) and 60 healthy controls were evaluated with a systematized quantitative approach of thermal (cold and warm), mechanical, pain, gustation, olfaction and salivary flow; data were analyzed with ANOVA, Tukey, Kruskal Wallis and Dunn tests with a level of significance of 5%. RESULTS: There were no salivary differences among the groups with matched ages; the cold perception was abnormal only at the mandibular branch of PHN (P = 0.001) and warm was abnormal in all trigeminal branches of PHN and BMS; mechanical sensitivity was altered at the mandibular branch of PHN and in all trigeminal branches of BMS. The salty, sweet and olfactory thresholds were higher in all studied groups; the sour threshold was lower and there were no differences of bitter. CONCLUSION: All groups showed abnormal thresholds of gustation and olfaction; somesthetic findings were discrete in ITN and more common in PHN and BMS; central mechanisms of balance of sensorial inputs might be underlying these observations. Oral Diseases (2010) 16, 482-487

Facial sensibility of patients with trigeminal neuralgias

Objectives: Idiopathic trigeminal neuralgia (ITN) is an excruciating shock-like paroxysmal pain restricted to the trigeminal area of innervation, with discrete loss of sensibility (thermal, tactile and painful). Trigeminal postherpetic neuralgia (PHN) is a neuropathic pain at the trigeminal territory that persists after Herpes zoster infection, which also is associated to sensorial compromise. The objective of this study was to evaluate the somesthetic facial sensibility (pain, thermal and tactile) and to compare the findings between PHN and ITN. Methods: 18 patients with PHN and 26 patients with ITN were diagnosed by the IASP criteria. They were evaluated with a systematic approach, which included mechanical, thermal (cold and warm) and painful stimuli. Results: We found statistical significance at the ophthalmic branch of PHN in pain (p=0.001), tactile (p=0.002), cold (p=0.016) and warm (p=0.013); in ITN, the maxillary branch had higher threshold with pinpricks (p=0.016) and the mandibular branch had higher tactile threshold. Conclusions: The trigeminal area affected by the disease had the higher sensorial losses (ophthalmic branch in PHN and maxillary/mandibular branches in ITN). PHN patients had losses in large and small fibers; therefore, ITN patients had the losses mostly in large fibers, which support different peripheral neural mechanisms for these neuropathic diseases. (C) 2010 Elsevier B.V. All rights reserved.