A novel method for evaluating the critical nucleus and the surface tension in systems with first order phase transition

We introduce a novel method for calculating the size of the critical nucleus and the value of the surface tension in systems with first order phase transition. The method is based on classical nucleation theory, and it consists in studying the thermodynamics of a sphere of given radius embedded in a frozen metastable surrounding. The frozen configuration creates a pinning field on the surface of the free sphere. The pinning field forces the sphere to stay in the metastable phase as long as its size is smaller than the critical nucleus. We test our method in two first-order systems, both on a two-dimensional lattice: a system where the parameter tuning the transition is the magnetic field, and a second system where the tuning parameter is the temperature. In both cases the results are satisfying. Unlike previous techniques, our method does not require an infinite volume limit to compute the surface tension, and it therefore gives reliable estimates even by using relatively small systems. However, our method cannot be used at, or close to, the critical point, i.e. at coexistence, where the critical nucleus becomes infinitely large.Comment: 12 pages, 15 figure

Patch-repetition correlation length in glassy systems

We obtain the patch-repetition entropy Sigma within the Random First Order Transition theory (RFOT) and for the square plaquette system, a model related to the dynamical facilitation theory of glassy dynamics. We find that in both cases the entropy of patches of linear size l, Sigma(l), scales as s_c l^d+A l^{d-1} down to length-scales of the order of one, where A is a positive constant, s_c is the configurational entropy density and d the spatial dimension. In consequence, the only meaningful length that can be defined from patch-repetition is the cross-over length xi=A/s_c. We relate xi to the typical length-scales already discussed in the literature and show that it is always of the order of the largest static length. Our results provide new insights, which are particularly relevant for RFOT theory, on the possible real space structure of super-cooled liquids. They suggest that this structure differs from a mosaic of different patches having roughly the same size.Comment: 6 page

Explosion Behavior of Ethanol-Ethyl Acetate/Air Mixtures

Alcohol-ester mixtures and, among them, ethanol-ethyl acetate mixtures are widely used as solvents in the packaging industry. For the safe use of such mixtures, it is essential to characterize their explosion behavior. Specifically, knowledge is required about maximum pressure and the maximum rate of pressure rise (i.e., the deflagration index), which are among the most important parameters for the assessment of process hazards and the safe design of process equipment. To this aim, in this work, closed-vessel explosion tests were carried out for an ethanol-ethyl acetate composition (mole fraction of ethanol in ethanol + ethyl acetate equal to 0.62) of interest to the packaging industry, varying the fuel/air equivalence ratio from 1.0 to 1.7. Tests were also extended to ethanol/air and ethyl acetate/air to quantify the effects of the possible interaction between the two fuels in the mixture. All tests started from 25°C and 1 bar. Experimental results show that, as the fuel equivalence ratio is increased, a transition occurs from a regime in which synergistic effects arise making the explosion behavior of ethanol-ethyl acetate more severe (i.e., making the rate of explosion pressure rise of ethanol-ethyl acetate higher) than both ethanol and ethyl acetate, to a regime in which, as a result of a completely different interaction between ethanol and ethyl acetate, the explosion behavior of their mixture is less severe than both the individual components. The maximum rate of pressure rise falls within an intermediate regime in which non-linear interaction effects substantially disappear and, thus, the value of deflagration index for the mixture can be obtained by averaging the values of the two fuels according to their molar proportions

Numerical implementation of dynamical mean field theory for disordered systems: Application to the Lotka-Volterra model of ecosystems

Dynamical mean field theory (DMFT) is a tool that allows one to analyze the stochastic dynamics of N interacting degrees of freedom in terms of a self-consistent 1-body problem. In this work, focusing on models of ecosystems, we present the derivation of DMFT through the dynamical cavity method, and we develop a method for solving it numerically. Our numerical procedure can be applied to a large variety of systems for which DMFT holds. We implement and test it for the generalized random Lotka-Volterra model, and show that complex dynamical regimes characterized by chaos and aging can be captured and studied by this framework

A potential role of il-6/il-6r in the development and management of colon cancer

Colorectal cancer (CRC) is the third most frequent cancer worldwide and the second greatest cause of cancer deaths. About 75% of all CRCs are sporadic cancers and arise following somatic mutations, while about 10% are hereditary cancers caused by germline mutations in specific genes. Several factors, such as growth factors, cytokines, and genetic or epigenetic alterations in specific oncogenes or tumor-suppressor genes, play a role during the adenoma–carcinoma sequence. Recent studies have reported an increase in interleukin-6 (IL-6) and soluble interleukin-6 receptor (sIL-6R) levels in the sera of patients affected by colon cancer that correlate with the tumor size, suggesting a potential role for IL-6 in colon cancer progression. IL-6 is a pleiotropic cytokine showing both pro-and anti-inflammatory roles. Two different types of IL-6 signaling are known. Classic IL-6 signaling involves the binding of IL-6 to its membrane receptor on the surfaces of target cells; alternatively, IL-6 binds to sIL-6R in a process called IL-6 trans-signaling. The activation of IL-6 transsignaling by metalloproteinases has been described during colon cancer progression and metastasis, involving a shift from membrane-bound interleukin-6 receptor (IL-6R) expression on the tumor cell surface toward the release of soluble IL-6R. In this review, we aim to shed light on the role of IL-6 signaling pathway alterations in sporadic colorectal cancer and the development of familial polyposis syndrome. Furthermore, we evaluate the possible roles of IL-6 and IL-6R as biomarkers useful in disease follow-up and as potential targets for therapy, such as monoclonal antibodies against IL-6 or IL-6R, or a food-based approach against IL-6

Marvels and Pitfalls of the Langevin Algorithm in Noisy High-Dimensional Inference

Gradient-descent-based algorithms and their stochastic versions have widespread applications in machine learning and statistical inference. In this work, we carry out an analytic study of the performance of the algorithm most commonly considered in physics, the Langevin algorithm, in the context of noisy high-dimensional inference. We employ the Langevin algorithm to sample the posterior probability measure for the spiked mixed matrix-tensor model. The typical behavior of this algorithm is described by a system of integrodifferential equations that we call the Langevin state evolution, whose solution is compared with the one of the state evolution of approximate message passing (AMP). Our results show that, remarkably, the algorithmic threshold of the Langevin algorithm is suboptimal with respect to the one given by AMP. This phenomenon is due to the residual glassiness present in that region of parameters. We also present a simple heuristic expression of the transition line, which appears to be in agreement with the numerical results

Assessment of Methods to Pretreat Microalgal Biomass for Enhanced Biogas Production

In anaerobic digestion of microalgae, the intracellular material may remain intact due to the non-ruptured membrane and/or cell wall, reducing the methane yield. Therefore, different pretreatment methods were evaluated for the solubilization of microalgae Scenedesmus sp. The anaerobic digestion of biomass hydrolyzed at 150 °C for 60 min with sulfuric acid 0.1% v/v showed higher methane yield (204-316 mL methane/g volatile solids applied) compared to raw biomass (104-163 mL methane/g volatile solids applied). The replacement of sulfuric acid with carbonic acid (by bubbling carbon dioxide up to pH 2.0) provided results similar to those obtained with sulfuric acid, reaching solubilization of 41.6% of the biomass. This result shows that part of the flue gas (containing carbon dioxide and other acid gases as well as high temperatures) may be used for the hydrolysis of the residual biomass from microalgae, thus lowering operational costs (e.g., energy consumption and chemical input)

Aging and relaxation near Random Pinning Glass Transitions

Pinning particles at random in supercooled liquids is a promising route to make substantial progress on the glass transition problem. Here we develop a mean-field theory by studying the equilibrium and non-equilibrium dynamics of the spherical p-spin model in presence of a fraction c of pinned spins. Our study shows the existence of two dynamic critical lines: one corresponding to usual Mode Coupling transitions and the other one to dynamic spinodal transitions. Quenches in the portion of the c - T phase diagram delimited by those two lines leads to aging. By extending our results to finite dimensional systems we predict non-interrupted aging only for quenches on the ideal glass transition line and two very different types of equilibrium relaxations for quenches below and above it.Comment: 7 pages, 4 figure