Data collapse, scaling functions, and analytical solutions of generalized growth models

We consider a nontrivial one-species population dynamics model with finite and infinite carrying capacities. Time-dependent intrinsic and extrinsic growth rates are considered in these models. Through the model per capita growth rate we obtain a heuristic general procedure to generate scaling functions to collapse data into a simple linear behavior even if an extrinsic growth rate is included. With this data collapse, all the models studied become independent from the parameters and initial condition. Analytical solutions are found when time-dependent coefficients are considered. These solutions allow us to perceive nontrivial transitions between species extinction and survival and to calculate the transition's critical exponents. Considering an extrinsic growth rate as a cancer treatment, we show that the relevant quantity depends not only on the intensity of the treatment, but also on when the cancerous cell growth is maximum.

ZETA DETERMINANT AND OPERATOR DETERMINANTS

We apply techniques of zeta functions and regularized products theory to study the zeta determinant of a class of abstract operators with compact resolvent, and in particular the relation with other spectral functions.

Generalized connectivity between any two nodes in a complex network

This article focuses on the identification of the number of paths with different lengths between pairs of nodes in complex networks and how these paths can be used for characterization of topological properties of theoretical and real-world complex networks. This analysis revealed that the number of paths can provide a better discrimination of network models than traditional network measurements. In addition, the analysis of real-world networks suggests that the long-range connectivity tends to be limited in these networks and may be strongly related to network growth and organization.

Cloud condensation nuclei in pristine tropical rainforest air of Amazonia: size-resolved measurements and modeling of atmospheric aerosol composition and CCN activity

Atmospheric aerosol particles serving as cloud condensation nuclei (CCN) are key elements of the hydrological cycle and climate. We have measured and characterized CCN at water vapor supersaturations in the range of S=0.10-0.82% in pristine tropical rainforest air during the AMAZE-08 campaign in central Amazonia. The effective hygroscopicity parameters describing the influence of chemical composition on the CCN activity of aerosol particles varied in the range of kappa approximate to 0.1-0.4 (0.16+/-0.06 arithmetic mean and standard deviation). The overall median value of kappa approximate to 0.15 was by a factor of two lower than the values typically observed for continental aerosols in other regions of the world. Aitken mode particles were less hygroscopic than accumulation mode particles (kappa approximate to 0.1 at D approximate to 50 nm; kappa approximate to 0.2 at D approximate to 200 nm), which is in agreement with earlier hygroscopicity tandem differential mobility analyzer (H-TDMA) studies. The CCN measurement results are consistent with aerosol mass spectrometry (AMS) data, showing that the organic mass fraction (f(org)) was on average as high as similar to 90% in the Aitken mode (D <= 100 nm) and decreased with increasing particle diameter in the accumulation mode (similar to 80% at D approximate to 200 nm). The kappa values exhibited a negative linear correlation with f(org) (R(2)=0.81), and extrapolation yielded the following effective hygroscopicity parameters for organic and inorganic particle components: kappa(org)approximate to 0.1 which can be regarded as the effective hygroscopicity of biogenic secondary organic aerosol (SOA) and kappa(inorg)approximate to 0.6 which is characteristic for ammonium sulfate and related salts. Both the size dependence and the temporal variability of effective particle hygroscopicity could be parameterized as a function of AMS-based organic and inorganic mass fractions (kappa(p)=kappa(org) x f(org)+kappa(inorg) x f(inorg)). The CCN number concentrations predicted with kappa(p) were in fair agreement with the measurement results (similar to 20% average deviation). The median CCN number concentrations at S=0.1-0.82% ranged from N(CCN,0.10)approximate to 35 cm(-3) to N(CCN,0.82)approximate to 160 cm(-3), the median concentration of aerosol particles larger than 30 nm was N(CN,30)approximate to 200 cm(-3), and the corresponding integral CCN efficiencies were in the range of N(CCN,0.10/NCN,30)approximate to 0.1 to N(CCN,0.82/NCN,30)approximate to 0.8. Although the number concentrations and hygroscopicity parameters were much lower in pristine rainforest air, the integral CCN efficiencies observed were similar to those in highly polluted megacity air. Moreover, model calculations of N(CCN,S) assuming an approximate global average value of kappa approximate to 0.3 for continental aerosols led to systematic overpredictions, but the average deviations exceeded similar to 50% only at low water vapor supersaturation (0.1%) and low particle number concentrations (<= 100 cm(-3)). Model calculations assuming aconstant aerosol size distribution led to higher average deviations at all investigated levels of supersaturation: similar to 60% for the campaign average distribution and similar to 1600% for a generic remote continental size distribution. These findings confirm earlier studies suggesting that aerosol particle number and size are the major predictors for the variability of the CCN concentration in continental boundary layer air, followed by particle composition and hygroscopicity as relatively minor modulators. Depending on the required and applicable level of detail, the information and parameterizations presented in this paper should enable efficient description of the CCN properties of pristine tropical rainforest aerosols of Amazonia in detailed process models as well as in large-scale atmospheric and climate models.

Study of the influence of indium segregation on the optical properties of InGaAs/GaAs quantum wells via split-operator method

In the case of quantum wells, the indium segregation leads to complex potential profiles that are hardly considered in the majority of the theoretical models. The authors demonstrated that the split-operator method is useful tool for obtaining the electronic properties in these cases. Particularly, they studied the influence of the indium surface segregation in optical properties of InGaAs/GaAs quantum wells. Photoluminescence measurements were carried out for a set of InGaAs/GaAs quantum wells and compared to the results obtained theoretically via split-operator method, showing a good agreement.

Generalized Sznajd model for opinion propagation

In the last decade the Sznajd model has been successfully employed in modeling some properties and scale features of both proportional and majority elections. We propose a version of the Sznajd model with a generalized bounded confidence rule-a rule that limits the convincing capability of agents and that is essential to allow coexistence of opinions in the stationary state. With an appropriate choice of parameters it can be reduced to previous models. We solved this model both in a mean-field approach (for an arbitrary number of opinions) and numerically in a Barabaacutesi-Albert network (for three and four opinions), studying the transient and the possible stationary states. We built the phase portrait for the special cases of three and four opinions, defining the attractors and their basins of attraction. Through this analysis, we were able to understand and explain discrepancies between mean-field and simulation results obtained in previous works for the usual Sznajd model with bounded confidence and three opinions. Both the dynamical system approach and our generalized bounded confidence rule are quite general and we think it can be useful to the understanding of other similar models.

Coexistence of interacting opinions in a generalized Sznajd model

The Sznajd model is a sociophysics model that mimics the propagation of opinions in a closed society, where the interactions favor groups of agreeing people. It is based in the Ising and Potts ferromagnetic models and, although the original model used only linear chains, it has since been adapted to general networks. This model has a very rich transient, which has been used to model several aspects of elections, but its stationary states are always consensus states. In order to model more complex behaviors, we have, in a recent work, introduced the idea of biases and prejudices to the Sznajd model by generalizing the bounded confidence rule, which is common to many continuous opinion models, to what we called confidence rules. In that work we have found that the mean field version of this model (corresponding to a complete network) allows for stationary states where noninteracting opinions survive, but never for the coexistence of interacting opinions. In the present work, we provide networks that allow for the coexistence of interacting opinions for certain confidence rules. Moreover, we show that the model does not become inactive; that is, the opinions keep changing, even in the stationary regime. This is an important result in the context of understanding how a rule that breeds local conformity is still able to sustain global diversity while avoiding a frozen stationary state. We also provide results that give some insights on how this behavior approaches the mean field behavior as the networks are changed.

Emergent and reentrant fractional quantum Hall effect in trilayer systems in a tilted magnetic field

Magnetotransport measurements in triple-layer electron systems with high carrier density reveal fractional quantum Hall effect at total filling factors nu>2. With an in-plane magnetic field we are able to control the suppression of interlayer tunneling which causes a collapse of the integer quantum Hall plateaus at nu=2 and nu=4, and an emergence of fractional quantum Hall states with increasing tilt angles. The nu=4 state is replaced by three fractional quantum Hall states with denominator 3. The state nu=7/3 demonstrates reentrant behavior and the emergent state at nu=12/5 has a nonmonotonic behavior with increasing in-plane field. We attribute the observed fractional quantum Hall plateaus to correlated states in a trilayer system.

High-order fractional microwave-induced resistance oscillations in two-dimensional systems

We report on the observation of microwave-induced resistance oscillations associated with the fractional ratio n/m of the microwave irradiation frequency to the cyclotron frequency for m up to 8 in a two-dimensional electron system with high electron density. The features are quenched at high microwave frequencies independent of the fractional order m. We analyze temperature, power, and frequency dependencies of the magnetoresistance oscillations and discuss them in connection with existing theories.

Measurement of D* mesons in jets from p plus p collisions at root s=200 GeV

We report the measurement of charged D* mesons in inclusive jets produced in proton-proton collisions at a center-of-mass energy root s = 200 GeV with the STAR experiment at the Relativistic Heavy Ion Collider. For D* mesons with fractional momenta 0.2< z< 0.5 in inclusive jets with 11.5 GeV mean transverse energy, the production rate is found to be N(D*(+) + D*(-))/N(jet) = 0.015 +/- 0.008(stat) +/- 0.007(sys). This rate is consistent with perturbative QCD evaluation of gluon splitting into a pair of charm quarks and subsequent hadronization.

Hadronic resonance production in d+Au collisions at root S(NN) = 200 GeV measured at the BNL Relativistic Heavy Ion Collider

We present the first measurements of the rho(770)(0),K(*)(892),Delta(1232)(++),Sigma(1385), and Lambda(1520) resonances in d+Au collisions at s(NN)=200 GeV, reconstructed via their hadronic decay channels using the STAR detector (the solenoidal tracker at the BNL Relativistic Heavy Ion Collider). The masses and widths of these resonances are studied as a function of transverse momentum p(T). We observe that the resonance spectra follow a generalized scaling law with the transverse mass m(T). The < p(T)> of resonances in minimum bias collisions are compared with the < p(T)> of pi,K, and p. The rho(0)/pi(-),K(*)/K(-),Delta(++)/p,Sigma(1385)/Lambda, and Lambda(1520)/Lambda ratios in d+Au collisions are compared with the measurements in minimum bias p+p interactions, where we observe that both measurements are comparable. The nuclear modification factors (R(dAu)) of the rho(0),K(*), and Sigma(*) scale with the number of binary collisions (N(bin)) for p(T)> 1.2 GeV/c.

Nonempirical hyper-generalized-gradient functionals constructed from the Lieb-Oxford bound

A simple and completely general representation of the exact exchange-correlation functional of density-functional theory is derived from the universal Lieb-Oxford bound, which holds for any Coulomb-interacting system. This representation leads to an alternative point of view on popular hybrid functionals, providing a rationale for why they work and how they can be constructed. A similar representation of the exact correlation functional allows to construct fully nonempirical hyper-generalized-gradient approximations (HGGAs), radically departing from established paradigms of functional construction. Numerical tests of these HGGAs for atomic and molecular correlation energies and molecular atomization energies show that even simple HGGAs match or outperform state-of-the-art correlation functionals currently used in solid-state physics and quantum chemistry.

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.

Inference of gene regulatory networks from time series by Tsallis entropy

Background: The inference of gene regulatory networks (GRNs) from large-scale expression profiles is one of the most challenging problems of Systems Biology nowadays. Many techniques and models have been proposed for this task. However, it is not generally possible to recover the original topology with great accuracy, mainly due to the short time series data in face of the high complexity of the networks and the intrinsic noise of the expression measurements. In order to improve the accuracy of GRNs inference methods based on entropy (mutual information), a new criterion function is here proposed. Results: In this paper we introduce the use of generalized entropy proposed by Tsallis, for the inference of GRNs from time series expression profiles. The inference process is based on a feature selection approach and the conditional entropy is applied as criterion function. In order to assess the proposed methodology, the algorithm is applied to recover the network topology from temporal expressions generated by an artificial gene network (AGN) model as well as from the DREAM challenge. The adopted AGN is based on theoretical models of complex networks and its gene transference function is obtained from random drawing on the set of possible Boolean functions, thus creating its dynamics. On the other hand, DREAM time series data presents variation of network size and its topologies are based on real networks. The dynamics are generated by continuous differential equations with noise and perturbation. By adopting both data sources, it is possible to estimate the average quality of the inference with respect to different network topologies, transfer functions and network sizes. Conclusions: A remarkable improvement of accuracy was observed in the experimental results by reducing the number of false connections in the inferred topology by the non-Shannon entropy. The obtained best free parameter of the Tsallis entropy was on average in the range 2.5 <= q <= 3.5 (hence, subextensive entropy), which opens new perspectives for GRNs inference methods based on information theory and for investigation of the nonextensivity of such networks. The inference algorithm and criterion function proposed here were implemented and included in the DimReduction software, which is freely available at http://sourceforge.net/projects/dimreduction and http://code.google.com/p/dimreduction/.

A NEW PROOF OF OKAJI'S THEOREM FOR A CLASS OF SUM OF SQUARES OPERATORS

Let P be a linear partial differential operator with analytic coefficients. We assume that P is of the form ""sum of squares"", satisfying Hormander's bracket condition. Let q be a characteristic point; for P. We assume that q lies on a symplectic Poisson stratum of codimension two. General results of Okaji Show that P is analytic hypoelliptic at q. Hence Okaji has established the validity of Treves' conjecture in the codimension two case. Our goal here is to give a simple, self-contained proof of this fact.