Surface crossover exponent for branched polymers in two dimensions

Transfer-matrix methods on finite-width strips with free boundary conditions are applied to lattice site animals, which provide a model for randomly branched polymers in a good solvent. By assigning a distinct fugacity to sites along the strip edges, critical properties at the special (adsorption) and ordinary transitions are assessed. The crossover exponent at the adsorption point is estimated as $\phi = 0.505 \pm 0.015$, consistent with recent predictions that $\phi = 1/2$ exactly for all space dimensionalities.Comment: 10 pages, LaTeX with Institute of Physics macros, to appear in Journal of Physics

Kosterlitz-Thouless transition in three-state mixed Potts ferro-antiferromagnets

We study three-state Potts spins on a square lattice, in which all bonds are ferromagnetic along one of the lattice directions, and antiferromagnetic along the other. Numerical transfer-matrix are used, on infinite strips of width $L$ sites, $4 \leq L \leq 14$. Based on the analysis of the ratio of scaled mass gaps (inverse correlation lengths) and scaled domain-wall free energies, we provide strong evidence that a critical (Kosterlitz-Thouless) phase is present, whose upper limit is, in our best estimate, $T_c=0.29 \pm 0.01$. From analysis of the (extremely anisotropic) nature of excitations below $T_c$, we argue that the critical phase extends all the way down to T=0. While domain walls parallel to the ferromagnetic direction are soft for the whole extent of the critical phase, those along the antiferromagnetic direction seem to undergo a softening transition at a finite temperature. Assuming a bulk correlation length varying, for $T>T_c$, as $\xi (T) =a_\xi \exp [ b_\xi (T-T_c)^{-\sigma}]$, $\sigma \simeq 1/2$, we attempt finite-size scaling plots of our finite-width correlation lengths. Our best results are for $T_c=0.50 \pm 0.01$. We propose a scenario in which such inconsistency is attributed to the extreme narrowness of the critical region.Comment: 11 pages, 6 .eps figures, LaTeX with IoP macros, to be published in J Phys

Sign inversion in the lateral van der Waals force

We consider a single slight protuberance in a perfectly conducting plane, and investigate the van der Waals (vdW) interaction between this surface and a neutral polarizable particle. When the protuberance is sufficiently smooth, so that the proximity force approximation (PFA) is well applicable, for a fixed distance of the particle from the plane, the lateral vdW force always points to the protuberance. On the other hand, by making calculations valid beyond the PFA, we show that nontrivial geometric effects arise when we consider an anisotropic particle, and manipulate the ratio between the characteristic widths of the protuberance and the fixed particle-plane distance. We predict that, as this ratio decreases, a sign inversion in the lateral vdW force can occur, in the sense that, instead of pointing to the protuberance, in certain situations the lateral force points to the opposite direction. Moreover, we show that even when such a sign inversion in the lateral vdW force does not occur for a single protuberance, it can arise when two or more protuberances are put together, distinguishing between sign inversions originated by individual or collective effects. In addition, we show that all these effects have their classical counterparts, involving a neutral particle with a permanent electric dipole moment. The prediction of such geometric effects on the lateral vdW force may be relevant for a better controlling of the interaction between a particle and a corrugated surface in classical and quantum physics.Comment: 6 pages, 7 figure

Heavy metals transport in typical portuguese loamy sand soils

Illegal discharges are of great concern among industry activities, since they occur under uncontrolled conditions. In most cases, effluents are acidic and the concentrations of heavy metals are very high. With this in mind, the main goal of this study was to evaluate the sorption of two of the most toxic heavy metals, Cr(VI) and Pb(II), in those conditions. A loamy sand soil was collected in Oporto, Portugal. Batch equilibrium and kinetic sorption experiments were performed using both metals solutions, with concentrations among 50 mg L-1 and 200 mg L-1, at pH 2 and 5, between 2 h and 288 h. To evaluate the sorption equilibrium, eight isotherm models were fitted. Better adjustments were observed for the Redlich-Peterson and Khan models for the adsorption of chromium (R2 = 0.99), and of lead (R2 = 0.99), respectively. The sorption kinetics was evaluated using three models – Elovich, Pseudo first order and an empirical power function. The retention of lead was almost instantaneous and the empirical power function described better the sorption kinetics of chromium (0.89 < R2 < 0.99). In addition, flow experiments were performed with effluents of both metals (50 mg L-1) at pH 2 and 5, for about 90 h. Results revealed a high retention of chromium, and a weak retention of lead, for low pH values. FTIR analyses to the columns samples revealed that clay minerals have an important role in the retention of both metals

Avaliação de acessos de melancia (Citrullus lanatus) do Banco Ativo de Germoplasma (BAG) de cucurbitáceas da Embrapa Semi-Árido.

Avaliou-se o número de dias para o aparecimento da primeira flor feminina

A Location-allocation model for fog computing infrastructures

The trend of an ever-increasing number of geographically distributed sensors producing data for a plethora of applications, from environmental monitoring to smart cities and autonomous driving, is shifting the computing paradigm from cloud to fog. The increase in the volume of produced data makes the processing and the aggregation of information at a single remote data center unfeasible or too expensive, while latency-critical applications cannot cope with the high network delays of a remote data center. Fog computing is a preferred solution as latency-sensitive tasks can be moved closer to the sensors. Furthermore, the same fog nodes can perform data aggregation and filtering to reduce the volume of data that is forwarded to the cloud data centers, reducing the risk of network overload. In this paper, we focus on the problem of designing a fog infrastructure considering both the location of how many fog nodes are required, which nodes should be considered (from a list of potential candidates), and how to allocate data flows from sensors to fog nodes and from there to cloud data centers. To this aim, we propose and evaluate a formal model based on a multi-objective optimization problem. We thoroughly test our proposal for a wide range of parameters and exploiting a reference scenario setup taken from a realistic smart city application. We compare the performance of our proposal with other approaches to the problem available in literature, taking into account two objective functions. Our experiments demonstrate that the proposed model is viable for the design of fog infrastructure and can outperform the alternative models, with results that in several cases are close to an ideal solution

Domain scaling and marginality breaking in the random field Ising model

A scaling description is obtained for the $d$--dimensional random field Ising model from domains in a bar geometry. Wall roughening removes the marginality of the $d=2$ case, giving the $T=0$ correlation length $\xi \sim \exp\left(A h^{-\gamma}\right)$ in $d=2$, and for $d=2+\epsilon$ power law behaviour with $\nu = 2/\epsilon \gamma$, $h^\star \sim \epsilon^{1/\gamma}$. Here, $\gamma = 2,4/3$ (lattice, continuum) is one of four rough wall exponents provided by the theory. The analysis is substantiated by three different numerical techniques (transfer matrix, Monte Carlo, ground state algorithm). These provide for strips up to width $L=11$ basic ingredients of the theory, namely free energy, domain size, and roughening data and exponents.Comment: ReVTeX v3.0, 19 pages plus 19 figures uuencoded in a separate file. These are self-unpacking via a shell scrip

A Decision Support System for Multi-Trip Vehicle Routing Problems

Emerging trends, driven by industry 4.0 and Big Data, are pushing to combine optimization techniques with Decision Support Systems (DSS). The use of DSS can reduce the risk of uncertainty of the decision-maker regarding the economic feasibility of a project and the technical design. Designing a DSS can be very hard, due to the inherent complexity of these types of systems. Therefore, monolithic software architectures are not a viable solution. This paper describes the DSS developed for an Italian company based on a micro-services architecture. In particular, the services handle geo-referenced information to solve a multi-trip vehicle routing problem with time windows. To face the problem, we follow a two-step approach. First, we generate a set of routes solving a vehicle routing problem with time windows using a metaheuristic algorithm. Second, we calculate the interval in which each route can start and end, and then combine the routes together, with an integer linear programming model, to minimize the number of used vehicles. Computational tests are conducted on real and random instances and prove the efficiency of the approach