A note on dimer models and McKay quivers

We give one formulation of an algorithm of Hanany and Vegh which takes a lattice polygon as an input and produces a set of isoradial dimer models. We study the case of lattice triangles in detail and discuss the relation with coamoebas following Feng, He, Kennaway and Vafa.Comment: 25 pages, 35 figures. v3:completely rewritte

Gravity duals of supersymmetric gauge theories on three-manifolds

We study gravity duals to a broad class of N=2 supersymmetric gauge theories defined on a general class of three-manifold geometries. The gravity backgrounds are based on Euclidean self-dual solutions to four-dimensional gauged supergravity. As well as constructing new examples, we prove in general that for solutions defined on the four-ball the gravitational free energy depends only on the supersymmetric Killing vector, finding a simple closed formula when the solution has U(1) x U(1) symmetry. Our result agrees with the large N limit of the free energy of the dual gauge theory, computed using localization. This constitutes an exact check of the gauge/gravity correspondence for a very broad class of gauge theories with a large N limit, defined on a general class of background three-manifold geometries.Comment: 74 pages, 2 figures; v2: minor change

Giant reed (Arundo donax L.) harvesting system, an economic and technical evaluation

The giant reed is a herbaceous energy crop that demonstrates a good adaptability for areas of central-northern Italy. However, its size and stem resistance to cutting pose problems for harvesting in relation both to the availability of suitable machinery and costs of the operation. A technical and economic evaluation has been conducted of a harvesting system based on an experimental machine, the biotriturator, developed by University of Bologna in collaboration with the Nobili Company (Bologna, Italy) and adapted to field operating conditions. The harvesting system consists of cutting-shredding and baling in a single pass. The system was evaluated by performing a winter harvest when the crop was in quiescence and had a low moisture content. The total harvesting costs were evaluated as 11.6 € Mg-1 dry biomass. Given that the estimated area that can be covered by the harvesting system was 123 hectares per year the system represents an effective solution for not very large areas and is therefore suitable for the Italian environment where average farm sizes are slightly over seven hectares (ISTAT, 2011)

The viroses and virus-like diseases of the grapevine

A bibliographic report, 1979-198

Detection performance assessment of the FM-based AULOS® passive radar for air surveillance applications

In this paper, we report the latest developments obtained with the FM-based configuration of the AULOS® passive radar system designed by Leonardo SpA for air surveillance applications. Specifically, aiming at improving the target detection capability of the sensor, a robust disturbance cancellation technique is adopted. Moreover, to counteract the time-varying performance of the single FM channel we consider the joint exploitation of multiple FM radio channels. For the purposes, the recent processing techniques developed by the research group of Sapienza University of Rome have been successfully applied. The benefits of the proposed solutions have been extensively tested and validated against both traffic of opportunity and small cooperative targets. The reported results clearly show that the choice of appropriate processing strategies is critical for the performance of the resulting system and the exploitation of effective techniques allows a significant widening of its coverage

Flow Equations for Non-BPS Extremal Black Holes

We exploit some common features of black hole and domain wall solutions of (super)gravity theories coupled to scalar fields and construct a class of stable extremal black holes that are non-BPS, but still can be described by first-order differential equations. These are driven by a "superpotential'', which replaces the central charge Z in the usual black hole potential. We provide a general procedure for finding this class and deriving the associated "superpotential''. We also identify some other cases which do not belong to this class, but show a similar behaviour.Comment: LaTeX, 21 pages, 2 figures. v2: reference added, JHEP versio

Multidomain switching in the ferroelectric nanodots

Controlling the polarization switching in the ferroelectric nanocrystals, nanowires and nanodots has an inherent specificity related to the emergence of depolarization field that is associated with the spontaneous polarization. This field splits the finite-size ferroelectric sample into polarization domains. Here, based on 3D numerical simulations, we study the formation of 180$^{\circ }$ polarization domains in a nanoplatelet, made of uniaxial ferroelectric material, and show that in addition to the polarized monodomain state, the multidomain structures, notably of stripe and cylindrical shapes, can arise and compete during the switching process. The multibit switching protocol between these configurations may be realized by temperature and field variations

Machine learning solutions for predicting protein–protein interactions

Proteins are social molecules. Recent experimental evidence supports the notion that large protein aggregates, known as biomolecular condensates, affect structurally and functionally many biological processes. Condensate formation may be permanent and/or time dependent, suggesting that biological processes can occur locally, depending on the cell needs. The question then arises as to which extent we can monitor protein-aggregate formation, both experimentally and theoretically and then predict/simulate functional aggregate formation. Available data are relative to mesoscopic interacting networks at a proteome level, to protein-binding affinity data, and to interacting protein complexes, solved with atomic resolution. Powerful algorithms based on machine learning (ML) can extract information from data sets and infer properties of never-seen-before examples. ML tools address the problem of protein–protein interactions (PPIs) adopting different data sets, input features, and architectures. According to recent publications, deep learning is the most successful method. However, in ML-computational biology, convincing evidence of a success story comes out by performing general benchmarks on blind datasets. Results indicate that the state-of-the-art ML approaches, based on traditional and/or deep learning, can still be ameliorated, irrespectively of the power of the method and richness in input features. This being the case, it is quite evident that powerful methods still are not trained on the whole possible spectrum of PPIs and that more investigations are necessary to complete our knowledge of PPI-functional interaction

Finding functional motifs in protein sequences with deep learning and natural language models

Recently, prediction of structural/functional motifs in protein sequences takes advantage of powerful machine learning based approaches. Protein encoding adopts protein language models overpassing standard procedures. Different combinations of machine learning and encoding schemas are available for predicting different structural/functional motifs. Particularly interesting is the adoption of protein language models to encode proteins in addition to evolution information and physicochemical parameters. A thorough analysis of recent predictors developed for annotating transmembrane regions, sorting signals, lipidation and phosphorylation sites allows to investigate the state-of-the-art focusing on the relevance of protein language models for the different tasks. This highlights that more experimental data are necessary to exploit available powerful machine learning methods

Operator Counting and Eigenvalue Distributions for 3D Supersymmetric Gauge Theories

We give further support for our conjecture relating eigenvalue distributions of the Kapustin-Willett-Yaakov matrix model in the large N limit to numbers of operators in the chiral ring of the corresponding supersymmetric three-dimensional gauge theory. We show that the relation holds for non-critical R-charges and for examples with {\mathcal N}=2 instead of {\mathcal N}=3 supersymmetry where the bifundamental matter fields are nonchiral. We prove that, for non-critical R-charges, the conjecture is equivalent to a relation between the free energy of the gauge theory on a three sphere and the volume of a Sasaki manifold that is part of the moduli space of the gauge theory. We also investigate the consequences of our conjecture for chiral theories where the matrix model is not well understood.Comment: 27 pages + appendices, 5 figure