A note on syndeticity, recognizable sets and Cobham's theorem

In this note, we give an alternative proof of the following result. Let p, q >= 2 be two multiplicatively independent integers. If an infinite set of integers is both p- and q-recognizable, then it is syndetic. Notice that this result is needed in the classical proof of the celebrated Cobham?s theorem. Therefore the aim of this paper is to complete [13] and [1] to obtain an accessible proof of Cobham?s theorem

Coexistence of two main folded G-quadruplexes within a single G-rich domain in the EGFR promoter

EGFR is an oncogene which codifies for a tyrosine kinase receptor that represents an important target for anticancer therapy. Indeed, several human cancers showed an upregulation of the activity of this protein. The promoter of this gene contains some G-rich domains, thus representing a yet unexplored point of intervention to potentially silence this gene. Here, we explore the conformational equilibria of a 30-nt long sequence located at position -272 (EGFR-272). By merging spectroscopic and electrophoretic analysis performed on the wild-type sequence as well as on a wide panel of related mutants, we were able to prove that in potassium ion containing solution this sequence folds into two main G-quadruplex structures, one parallel and one hybrid. They show comparable thermal stabilities and affinities for the metal ion and, indeed, they are always co-present in solution. The folding process is driven by a hairpin occurring in the domain corresponding to the terminal loop which works as an important stabilizing element for both the identified G-quadruplex arrangements

Conformational profiling of a G-rich sequence within the c-KIT promoter

G-quadruplexes (G4) within oncogene promoters are considered to be promising anticancer targets. However, often they undergo complex structural rearrangements that preclude a precise description of the optimal target. Moreover, even when solved structures are available, they refer to the thermodynamically stable forms but little or no information is supplied about their complex multistep folding pathway. To shed light on this issue, we systematically followed the kinetic behavior of a G-rich sequence located within the c-KIT proximal promoter (kit2) in the presence of monovalent cations K + and Na + . A very short-lived intermediate was observed to start the G4 folding process in both salt conditions. Subsequently, the two pathways diverge to produce distinct thermodynamically stable species (parallel and antiparallel G-quadruplex in K + and Na + , respectively). Remarkably, in K + -containing solution a branched pathway is required to drive the wild type sequence to distribute between a monomeric and dimeric G-quadruplex. Our approach has allowed us to identify transient forms whose relative abundance is regulated by the environment; some of them were characterized by a half-life within the timescale of physiological DNA processing events and thus may represent possible unexpected targets for ligands recognition

Emergence of pointer states in a non-perturbative environment

We show that the pointer basis distinguished by collisional decoherence consists of exponentially localized, solitonic wave packets. Based on the orthogonal unraveling of the quantum master equation, we characterize their formation and dynamics, and we demonstrate that the statistical weights arising from an initial superposition state are given by the required projection. Since the spatial width of the pointer states can be obtained by accounting for the gas environment in a microscopically realistic fashion, one may thus calculate the coherence length of a strongly interacting gas.Comment: 8 pages, 1 figure; corresponds to published versio

Spectrogram classification using dissimilarity space

In this work, we combine a Siamese neural network and different clustering techniques to generate a dissimilarity space that is then used to train an SVM for automated animal audio classification. The animal audio datasets used are (i) birds and (ii) cat sounds, which are freely available. We exploit different clustering methods to reduce the spectrograms in the dataset to a number of centroids that are used to generate the dissimilarity space through the Siamese network. Once computed, we use the dissimilarity space to generate a vector space representation of each pattern, which is then fed into an support vector machine (SVM) to classify a spectrogram by its dissimilarity vector. Our study shows that the proposed approach based on dissimilarity space performs well on both classification problems without ad-hoc optimization of the clustering methods. Moreover, results show that the fusion of CNN-based approaches applied to the animal audio classification problem works better than the stand-alone CNNs

Towards a Reproducible Pan-European Soil Erosion Risk Assessment - RUSLE

Soil is a valuable, non-renewable natural resource that offers a multitude of ecosystems goods and services. Given the increasing threat of soil erosion in Europe and the implications this has on future food security and water quality, it is important that land managers and decision makers are provided with accurate and appropriate information on the areas more prone to erosion phenomena. The present study shows an attempt to locate, at regional scale, the most sensitive areas and to highlight any changes of soil erosion trends with climate change. The choice of the input datasets is crucial as they have to offer the most homogeneous and complete covering at the pan-European level and to allow the produced information to be harmonized and easily validated. The model is based on available datasets (HWSD, SGDBE, SRTM, CLC and E-OBS) and The Revised Universal Soil Loss Equation (RUSLE) is used because of its flexibility and least data demanding. A significant effort has been made to select the better simplified equations to be used when a strict application of the RUSLE model was not possible. In particular for the computation of the Rainfall Erosivity factor a validation based on measured precipitation time series (having a temporal resolution of 10-15 minutes) has been implemented to be easily reproducible. The validation computational framework is available as free software. Designing the computational modeling architecture with the aim to ease as much as possible the future reuse of the model in analyzing climate change scenarios has also been a challenging goal of the research

Two-channel charge-Kondo physics in graphene quantum dots

Nanoelectronic quantum dot devices exploiting the charge-Kondo paradigm have been established as versatile and accurate analog quantum simulators of fundamental quantum impurity models. In particular, hybrid metal-semiconductor dots connected to two metallic leads realize the two-channel Kondo (2CK) model, in which Kondo screening of the dot charge pseudospin is frustrated. Here, we consider theoretically a two-channel charge-Kondo device made instead from graphene components, realizing a pseudogapped version of the 2CK model. We solve the model using Wilson's Numerical Renormalization Group method, and uncover a rich phase diagram as a function of dot-lead coupling strength, channel asymmetry, and potential scattering. The complex physics of this system is explored through its thermodynamic properties, scattering T-matrix, and experimentally measurable conductance. We find that the strong coupling pseudogap Kondo phase persists in the channel-asymmetric two-channel context, while in the channel-symmetric case frustration results in a novel quantum phase transition. Remarkably, despite the vanishing density of states in the graphene leads at low energies, we find a finite linear conductance at zero temperature at the frustrated critical point, which is of non-Fermi liquid type. Our results suggest that the graphene charge-Kondo platform offers a unique possibility to access multichannel pseudogap Kondo physics.Comment: 12 pages, 4 figure

Evidence of a biodiversity crisis documented on a peritidal carbonate succession from western Tethys (Sicily): new data on the End Triassic Mass Extinction

A biodiversity crisis was observed in the latest Triassic on both macro-and micro-benthic communities from a western Tethyan carbonate platform. The studied succession represented by the Monte Sparagio section consists of a continuous Upper Triassic to Lower Jurassic peritidal limestones organized in shallowing upward cycles. The subtidal facies in the lower part of this section (Unit A) contains very abundant and highly diverse fossiliferous assemblages consisting of very large megalodontoids (up to 40 cm). Up-section, a reduction of biodiversity, abundance and shell size of megalodontoids (up to 15 cm) tipifies Unit B. Similarly, in this last Unit, the average dimensions of the benthic foraminifer T. hantkeni decreases (ca. 30%). After a short interval marked by a bloom of the problematic alga T. parvovesiculifera, the overlying Unit C accounts for the recovery of the Jurassic benthic community. The geochemical analyses of stable isotopes (C, O and S) seem correlative to the drastic reduction in the Rhaetian biodiversity between Unit A and Unit B. These biodiversity crises in the Rhaetian horizons can be interpreted as a precursor of the End Triassic Extinction and provide new insights into the existence of two extinction pulses at the end of Triassic. These data are in accordance with the environmental parameters of survival in a modern tropical shallow water platform (T-factory). In particular, the sea surface temperature (SST) of a T-factory ranges from 18 degrees C to 30.5 degrees C representing respectively the minimum SST for the carbonate factory persistence and the maximum SST that a T-factory can tolerate

Computational performance of risk-based inspection methodologies for offshore wind support structures

Offshore wind turbines are dynamically responding structures reaching around 70 million of stress cycles per year due to the combined action of waves and wind loading. Therefore, the assessment of fatigue deterioration becomes crucial. Besides, fatigue assessment is characterized by large uncertainties associated with both fatigue loads and strength. Inspections can be undertaken to detect potential cracks and therefore improve our belief about the condition of the structure. However, offshore wind inspections are costly and complex operations, involving the deployment of ROVs or divers for the case of underwater components. Risk-based inspection aims to identify the optimal maintenance policy by balancing the risk of structural failure against maintenance efforts (inspections and repairs). Introduction of a risk-based inspection plan can lead to reductions in the expected life-cycle costs as already demonstrated in the Oil & Gas sector. Inspection planning is a complex sequential decision problem where the decision about whether to go or not for an inspection must consider the outcomes from the previous inspections. In theory, it is possible to find the optimal policy by solving a pre-posterior decision analysis. Nevertheless, for the real case of an offshore wind structure standing a lifetime of 20 years, it is not possible to solve a decision tree which is exponentially growing over time and it becomes computationally intractable. Due to the computational limitations, assumptions are generally introduced within the risk-based analysis leading to approximate optimal policies. Traditional risk-based inspection techniques encompass FORM/SORM or Monte Carlo simulations to estimate and update the probability of failure as well as the inclusion of heuristic decision rules to solve the decision problem. However, novel methods and algorithms have been proposed recently to improve the computational efficiency of the risk-based analyses such as Dynamic Bayesian Networks (DBNs) or Partially Observable Markov Decision Processes (POMDPs). The aim of this work is to compare the existing risk-based inspection planning methodologies applicable to offshore wind structures. The computational performance and life-cycle expected costs corresponding to the different methodologies are explored. Additionally, the challenges which risk-based inspection planning is facing in the present are presented and potential solutions are suggested, for instance, on how to incorporate the correlation between structural components or “system-effects” into the risk-based analysis. In order to explore the main aspects involved during the application of the existing risk-based methodologies, the following step are pursued: 1) identification of the most relevant random variables within the deterioration models, 2) calibration of SN/Miner’s fatigue model to a fracture mechanics model, 3) comparison of the methods available for updating the failure probability when information from inspections is available and 4) comparison of the methods available to solve the pre-posterior decision problem corresponding to inspection planning. The optimal inspection plan for an offshore wind tubular joint is then identified by employing the different risk-based methodologies. Thereby, the methodologies are reviewed in terms of: 1) computational time to set up the model, 2) computation time required by the simulation and 3) obtained life-cycle expected costs. The results highlight the computational advantages of modern methods such as DBNs or POMDP which facilitate the identification of more optimal inspection policies