811 research outputs found
Stable, metastable and unstable states in the mean-field RFIM at T=0
We compute the probability of finding metastable states at a given field in
the mean-field random field Ising model at T=0. Remarkably, this probability is
finite in the thermodynamic limit, even on the so-called ``unstable'' branch of
the magnetization curve. This implies that the branch is reachable when the
magnetization is controlled instead of the magnetic field, in contrast with the
situation in the pure system.Comment: 10 pages, 3 figure
PVS: a web server for protein sequence variability analysis tuned to facilitate conserved epitope discovery
We have developed PVS (Protein Variability Server), a web-based tool that uses several variability metrics to compute the absolute site variability in multiple protein-sequence alignments (MSAs). The variability is then assigned to a user-selected reference sequence consisting of either the first sequence in the alignment or a consensus sequence. Subsequently, PVS performs tasks that are relevant for structure-function studies, such as plotting and visualizing the variability in a relevant 3D-structure. Neatly, PVS also implements some other tasks that are thought to facilitate the design of epitope discovery-driven vaccines against pathogens where sequence variability largely contributes to immune evasion. Thus, PVS can return the conserved fragments in the MSA—as defined by a user-provided variability threshold—and locate them in a relevant 3D-structure. Furthermore, PVS can return a variability-masked sequence, which can be directly submitted to the RANKPEP server for the prediction of conserved T-cell epitopes. PVS is freely available at: http://imed.med.ucm.es/PVS/
Reverse engineering of biochar
This study underpins quantitative relationships that account for the combined effects that starting biomass and peak pyrolysis temperature have on physico-chemical properties of biochar. Meta-data was assembled from published data of diverse biochar samples (n = 102) to (i) obtain networks of intercorrelated properties and (ii) derive models that predict biochar properties. Assembled correlation networks provide a qualitative overview of the combinations of biochar properties likely to occur in a sample. Generalized Linear Models are constructed to account for situations of varying complexity, including: dependence of biochar properties on single or multiple predictor variables, where dependence on multiple variables can have additive and/or interactive effects; non-linear relation between the response and predictors; and non-Gaussian data distributions. The web-tool Biochar Engineering implements the derived models to maximize their utility and distribution. Provided examples illustrate the practical use of the networks, models and web-tool to engineer biochars with prescribed properties desirable for hypothetical scenarios
Training-induced criticality in martensites
We propose an explanation for the self-organization towards criticality
observed in martensites during the cyclic process known as `training'. The
scale-free behavior originates from the interplay between the reversible phase
transformation and the concurrent activity of lattice defects. The basis of the
model is a continuous dynamical system on a rugged energy landscape, which in
the quasi-static limit reduces to a sandpile automaton. We reproduce all the
principal observations in thermally driven martensites, including power-law
statistics, hysteresis shakedown, asymmetric signal shapes, and correlated
disorder.Comment: 5 pages, 4 figure
One-side heating test and modeling of tubular receivers equipped with turbulence promoters for solar tower applications
Tubular receivers in central tower systems suffer the high mechanical stresses caused by the temperature gradient typically established along the tube and across its circumference due to the one-side heating. In the present work, the thermal behavior of three different absorber tubes is investigated both experimentally and numerically. The tubes, manufactured in Cr alloy 718 (Inconel®), were smooth or with repeated rib-roughness (annular or helical ribs), and were tested at the solar furnace SF60 of the Plataforma Solar de Almería (PSA) in 2017 within the international access program of SFERA II project, financed by the EU. The specific focus of the tests was the assessment of the role of turbulence promoters in reducing the peak wall temperature when a strong one-side heating is present, contributing to the reduction of the thermal gradients between the irradiated and the non-irradiated (back) side of the tube. The experimental results show that the use of turbulence promoters reduce the wall temperature with respect to the case of a smooth tube, as expected, although the comparison between the samples is not trivial in view of the change in the optical properties induced by the progressive oxidation of the irradiated surface. Computational Fluid Dynamic (CFD) 3D models have been developed for the three samples and they have proven the capability to very-well reproduce the experimental results. A fair comparison between the different simulated tubes in the same controlled conditions of one-side heating has been performed numerically, assessing quantitatively the temperature reduction induced by the turbulence promoters, and the best performance of the Inconel® tube equipped with helices
Towards the knowledge-based design of universal influenza epitope ensemble vaccines
Motivation: Influenza A viral heterogeneity remains a significant threat due to unpredictable antigenic drift in seasonal influenza and antigenic shifts caused by the emergence of novel subtypes. Annual review of multivalent influenza vaccines targets strains of influenza A and B likely to be predominant in future influenza seasons. This does not induce broad, cross protective immunity against emergent subtypes. Better strategies are needed to prevent future pandemics. Cross-protection can be achieved by activating CD8+ and CD4+ T cells against highly-conserved regions of the influenza genome. We combine available experimental data with informatics-based immunological predictions to help design vaccines potentially able to induce cross-protective T-cells against multiple influenza subtypes. Results: To exemplify our approach we designed two epitope ensemble vaccines comprising highly-conserved and experimentally-verified immunogenic influenza A epitopes as putative non-seasonal influenza vaccines; one specifically targets the US population and the other is a universal vaccine. The USA-specific vaccine comprised 6 CD8+ T cell epitopes (GILGFVFTL, FMYSDFHFI, GMDPRMCSL, SVKEKDMTK, FYIQMCTEL, DTVNRTHQY) and 3 CD4+ epitopes (KGILGFVFTLTVPSE, EYIMKGVYINTALLN, ILGFVFTLTVPSERG). The universal vaccine comprised 8 CD8+ epitopes: (FMYSDFHFI, GILGFVFTL, ILRGSVAHK, FYIQMCTEL, ILKGKFQTA, YYLEKANKI, VSDGGPNLY, YSHGTGTGY) and the same 3 CD4+ epitopes. Our USA-specific vaccine has a population protection coverage (portion of the population potentially responsive to one or more component epitopes of the vaccine, PPC) of over 96% and 95% coverage of observed influenza subtypes. The universal vaccine has a PPC value of over 97% and 88% coverage of observed subtypes
Prominent effect of soil network heterogeneity on microbial invasion
Using a network representation for real soil samples and mathematical models for microbial spread, we show that the structural heterogeneity of the soil habitat may have a very significant influence on the size of microbial invasions of the soil pore space. In particular, neglecting the soil structural heterogeneity may lead to a substantial underestimation of microbial invasion. Such effects are explained in terms of a crucial interplay between heterogeneity in microbial spread and heterogeneity in the topology of soil networks. The main influence of network topology on invasion is linked to the existence of long channels in soil networks that may act as bridges for transmission of microorganisms between distant parts of soil
Zero-temperature random-field Ising model on a bilayered Bethe lattice
Peer reviewedPublisher PD
- …