Scaling in the crossover from random to correlated growth

In systems where deposition rates are high compared to diffusion, desorption and other mechanisms that generate correlations, a crossover from random to correlated growth of surface roughness is expected at a characteristic time t_0. This crossover is analyzed in lattice models via scaling arguments, with support from simulation results presented here and in other authors works. We argue that the amplitudes of the saturation roughness and of the saturation time scale as {t_0}^{1/2} and t_0, respectively. For models with lateral aggregation, which typically are in the Kardar-Parisi-Zhang (KPZ) class, we show that t_0 ~ 1/p, where p is the probability of the correlated aggregation mechanism to take place. However, t_0 ~ 1/p^2 is obtained in solid-on-solid models with single particle deposition attempts. This group includes models in various universality classes, with numerical examples being provided in the Edwards-Wilkinson (EW), KPZ and Villain-Lai-Das Sarma (nonlinear molecular-beam epitaxy) classes. Most applications are for two-component models in which random deposition, with probability 1-p, competes with a correlated aggregation process with probability p. However, our approach can be extended to other systems with the same crossover, such as the generalized restricted solid-on-solid model with maximum height difference S, for large S. Moreover, the scaling approach applies to all dimensions. In the particular case of one-dimensional KPZ processes with this crossover, we show that t_0 ~ nu^{-1} and nu ~ lambda^{2/3}, where nu and lambda are the coefficients of the linear and nonlinear terms of the associated KPZ equations. The applicability of previous results on models in the EW and KPZ classes is discussed.Comment: 14 pages + 5 figures, minor changes, version accepted in Phys. Rev.

Quantum Evolution of Inhomogeneities in Curved Space

We obtain the renormalized equations of motion for matter and semi-classical gravity in an inhomogeneous space-time. We use the functional Schrodinger picture and a simple Gaussian approximation to analyze the time evolution of the $\lambda\phi^4$ model, and we establish the renormalizability of this non-perturbative approximation. We also show that the energy-momentum tensor in this approximation is finite once we consider the usual mass and coupling constant renormalizations, without the need of further geometrical counter-terms.Comment: 22 page

Evidence for entanglement at high temperatures in an engineered molecular magnet

The molecular compound [Fe$_{2}$($\mu_{2}$-oxo)(C$_{3}$H$_{4}$N$_{2}$)$_{6}$(C$_{2}$O$_{4}$)$_{2}$] was designed and synthesized for the first time and its structure was determined using single-crystal X-ray diffraction. The magnetic susceptibility of this compound was measured from 2 to 300 K. The analysis of the susceptibility data using protocols developed for other spin singlet ground-state systems indicates that the quantum entanglement would remain at temperatures up to 732 K, significantly above the highest entanglement temperature reported to date. The large gap between the ground state and the first-excited state (282 K) suggests that the spin system may be somewhat immune to decohering mechanisms. Our measurements strongly suggest that molecular magnets are promising candidate platforms for quantum information processing

Influence of the external pressure on the quantum correlations of molecular magnets

The study of quantum correlations in solid state systems is a large avenue for research and their detection and manipulation are an actual challenge to overcome. In this context, we show by using first-principles calculations on the prototype material KNaCuSi$_{4}$O$_{10}$ that the degree of quantum correlations in this spin cluster system can be managed by external hydrostatic pressure. Our results open the doors for research in detection and manipulation of quantum correlations in magnetic systems with promising applications in quantum information science

Grão de bico e lentilha: duas novas hospedeiras de Sclerotium rolfsii no Planalto Central do Brasil.

Neste trabalho, relata-se, pela primeira vez, a ocorrência da murcha-de-esclerócio, causada por Sclerotium rolfsii em grão-de-bico (Cicer arietinum L.) e em lentilha (Lens culinaris Medikus) na Região do Planalto Central do Brasil.bitstream/item/85036/1/bpd-92.pd

Finite size analysis of a two-dimensional Ising model within a nonextensive approach

In this work we present a thorough analysis of the phase transitions that occur in a ferromagnetic 2D Ising model, with only nearest-neighbors interactions, in the framework of the Tsallis nonextensive statistics. We performed Monte Carlo simulations on square lattices with linear sizes L ranging from 32 up to 512. The statistical weight of the Metropolis algorithm was changed according to the nonextensive statistics. Discontinuities in the m(T) curve are observed for $q\leq 0.5$. However, we have verified only one peak on the energy histograms at the critical temperatures, indicating the occurrence of continuous phase transitions. For the $0.5<q\leq 1.0$ regime, we have found continuous phase transitions between the ordered and the disordered phases, and determined the critical exponents via finite-size scaling. We verified that the critical exponents $\alpha$, $\beta$ and $\gamma$ depend on the entropic index $q$ in the range $0.5<q\leq 1.0$ in the form $\alpha (q)=(10 q^{2}-33 q+23)/20$, $\beta (q)=(2 q-1)/8$ and $\gamma (q)=(q^{2}-q+7)/4$. On the other hand, the critical exponent $\nu$ does not depend on $q$. This suggests a violation of the scaling relations $2 \beta +\gamma =d \nu$ and $\alpha +2 \beta +\gamma =2$ and a nonuniversality of the critical exponents along the ferro-paramagnetic frontier.Comment: accepted for publication in Phys. Rev.

Reducing prostaglandin E2 production to raise cancer immunogenicity

Cyclooxygenases (COX), commonly upregulated in numerous cancers, generate prostaglandin E2 (PGE2), which has been implicated in key aspects of malignant growth including proliferation, invasion and angiogenesis. Recently, we showed that production of PGE2 by cancer cells dominantly enables progressive tumor growth via immune escape and that cyclooxygenase inhibitors synergize with immunotherapy to enhance tumor eradication

Implications of different spatial (and temporal) resolutions for integrated assessment modelling on the regional to local scale – nesting, coupling, or model integration?

Integrated assessment modelling (IAM) in general is currently applied to a range of environmental problems addressing aspects of air pollution and climate change, water pollution and many more. While different branches have emerged from applications within different disciplines, they share a similar view of the core features of IAM, i.e. multi-disciplinary approaches, integration across environmental compartments, and the application of models with the aim to provide decision support for complex problems. Examples of IAMs on a regional scale are the RAINS/GAINS model suite (International Institute for Applied Systems Analysis, IIASA), with versions for Europe and Asia. On a national scale, several European countries are currently developing and applying IAMs for policy development, in some cases using special adaptations of the IIASA RAINS/GAINS model (e.g. Italy), or own models (UK, Germany). IAMs have been extensively used in the preparation of the Multi-Effect Protocol (United Nations Convention on Long-Range Transboundary Air Pollution, CLRTAP) and the European Clean Air For Europe (CAFE) strategy. In these applications, target setting included a mixture of health and ecosystem related indicators. State-of-the-art IAMs are typically operating on rigid spatial scales, and in most cases do not take into account the temporal patterns of emissions and effects in their assessment approaches. IAM results are typically provided on national or regional level (e.g. control measures, costs, benefits due to reduced environmental and health impacts) and for annual indicators (e.g. critical load exceedances or morbidity/mortality effects. However, scientific evidence is today capable of providing a better foundation to identify major aspects for uncertainties in these larger scale assessments, for instance investigating the distinct temporal patterns of air quality throughout the year and the detailed modelling and mapping of human exposure to air pollutants beyond statistical average exposures on total population level. This requires a more advanced and flexible design of IAMs to better model the temporal and spatial domains which are of relevance for the key issues to be assessed. First steps towards bridging the gap between regional and national, respectively national and local scale models for integrated assessments have taken the route to derive parameters for e.g. the urban differential in ambient air quality outside of the models regular domain and integrate these parametric values into the IAMs assessments. While this approach is moderately labour intensive, the major flaw is the integration of static values into an intrinsically dynamic model. In other words, if input datasets and external drivers (e.g. meteorology, atmospheric composition and chemistry) change, all other parameters have to be recalculated and re-integrated. This paper will discuss emerging trends for IAMs with a specific focus on spatial and temporal aspects and aims to elaborate on the policy context which is a key driver for the development of IAMs. The growing understanding of how complex interactions e.g. between/within the nitrogen and carbon cycles, where both management options and effects arise/occur on different spatial scales and with different time scales, both feeds into and requires the development of next generation IAMs, which are capable of tackling these problems

Experimental determination of the non-extensive entropic parameter qq

We show how to extract the $q$ parameter from experimental data, considering an inhomogeneous magnetic system composed by many Maxwell-Boltzmann homogeneous parts, which after integration over the whole system recover the Tsallis non-extensivity. Analyzing the cluster distribution of La$_{0.7}$Sr$_{0.3}$MnO$_{3}$ manganite, obtained through scanning tunnelling spectroscopy, we measure the $q$ parameter and predict the bulk magnetization with good accuracy. The connection between the Griffiths phase and non-extensivity is also considered. We conclude that the entropic parameter embodies information about the dynamics, the key role to describe complex systems.Comment: Submitted to Phys. Rev. Let