The k0-INRIM software version 2.0: presentation and an analysis vademecum

The k0-INRIM software was developed at INRIM to perform k(0)-standardization Neutron Activation Analysis and evaluate combined uncertainty through application of the spreadsheet method. However, the presence of some limitation made its use, as a tool for routine NAA, impractical. With the aim to participate to the 2021 IAEA k(0)-NAA software intercomparison to evaluate the effect on mass fraction results due to software used, the k0-INRIM was sizably updated in order to meet the agreed functionality requirements to take part to the exercise. In this work, the version 2.0 of the software is presented and a point-by-point example analysis is displayed. The software version here described is available for download together with the corresponding updated user's manual

On the vacuum of the minimal nonsupersymmetric SO(10) unification

We study a class of nonsupersymmetric SO(10) grand unified scenarios where the first stage of the symmetry breaking is driven by the vacuum expectation values of the 45-dimensional adjoint representation. Three decade old results claim that such a Higgs setting may lead exclusively to the flipped SU(5) x U(1) intermediate stage. We show that this conclusion is actually an artifact of the tree level potential. The study of the accidental global symmetries emerging in various limits of the scalar potential offers a simple understanding of the tree level result and a rationale for the drastic impact of quantum corrections. We scrutinize in detail the simplest and paradigmatic case of the 45_{H} + 16_{H} Higgs sector triggering the breaking of SO(10) to the standard electroweak model. We show that the minimization of the one-loop effective potential allows for intermediate SU(4)_C x SU(2)_L x U(1)_R and SU(3)_c x SU(2)_L x SU(2)_R x U(1)_{B-L} symmetric stages as well. These are the options favoured by gauge unification. Our results, that apply whenever the SO(10) breaking is triggered by , open the path for hunting the simplest realistic scenario of nonsupersymmetric SO(10) grand unification.Comment: 22 pages, 1 figure. Refs added. To appear in Phys. Rev.

Mapping Orientational Order of Charge-Probed Domains in a Semiconducting Polymer

Structure–property relationships are of fundamental importance to develop quantitative models describing charge transport in organic semiconductor based electronic devices, which are among the best candidates for future portable and lightweight electronic applications. While microstructural investigations, such as those based on X-rays, electron microscopy, or polarized optical probes, provide necessary information for the rationalization of transport in macromolecular solids, a general model predicting how charge accommodates within structural maps is not yet available. Therefore, techniques capable of directly monitoring how charge is distributed when injected into a polymer film and how it correlates to structural domains can help fill this gap. Supported by density functional theory calculations, here we show that polarized charge modulation microscopy (p-CMM) can unambiguously and selectively map the orientational order of the only conjugated segments that are probed by mobile charge in the few nanometer thick accumulation layer of a high-mobility polymer-based field-effect transistor . Depending on the specific solvent-induced microstructure within the accumulation layer, we show that p-CMM can image charge-probed domains that extend from submicrometer to tens of micrometers size, with markedly different degrees of alignment. Wider and more ordered p-CMM domains are associated with improved carrier mobility, as extracted from device characteristics. This observation evidences the unprecedented opportunity to correlate, directly in a working device, electronic properties with structural information on those conjugated segments involved in charge transport at the buried semiconductor–dielectric interface of a field-effect device

Hierarchical Self-Assembly of Halogen-Bonded Block Copolymer Complexes into Upright Cylindrical Domains

Self-assembly of block copolymers into well-defined, ordered arrangements of chemically distinct domains is a reliable strategy for preparing tailored nanostructures. Microphase separation results from the system, minimizing repulsive interactions between dissimilar blocks and maximizing attractive interactions between similar blocks. Supramolecular methods have also achieved this separation by introducing small-molecule additives binding specifically to one block by noncovalent interactions. Here, we use halogen bonding as a supramolecular tool that directs the hierarchical self-assembly of low-molecular-weight perfluorinated molecules and diblock copolymers. Microphase separation results in a lamellar-within-cylindrical arrangement and promotes upright cylindrical alignment in films upon rapid casting and without further annealing. Such cylindrical domains with internal lamellar self-assemblies can be cleaved by solvent treatment of bulk films, resulting in separated and segmented cylindrical micelles stabilized by halogen-bond-based supramolecular crosslinks. These features, alongside the reversible nature of halogen bonding, provide a robust modular approach for nanofabricatio

Deformed Special Relativity as an effective theory of measurements on quantum gravitational backgrounds

In this article we elaborate on a recently proposed interpretation of DSR as an effective measurement theory in the presence of non-negligible (albeit small) quantum gravitational fluctuations. We provide several heuristic arguments to explain how such a new theory can emerge and discuss the possible observational consequences of this framework.Comment: 11 pages, no figure

A Fast Deep Learning Technique for Wi-Fi-Based Human Activity Recognition

Despite recent advances, fast and reliable Human Activity Recognition in confined space is still an open problem related to many real-world applications, especially in health and biomedical monitoring. With the ubiquitous presence of Wi-Fi networks, the activity recognition and classification problems can be solved by leveraging some characteristics of the Channel State Information of the 802.11 standard. Given the well-documented advantages of Deep Learning algorithms in solving complex pattern recognition problems, many solutions in Human Activity Recognition domain are taking advantage of those models. To improve the time and precision of activity classification of time-series data stemming from Channel State Information, we propose herein a fast deep neural model encompassing concepts not only from state-of-the-art recurrent neural networks, but also using convolutional operators with added randomization. Results from real data in an experimental environment show promising results

Stellar evolution confronts axion models

Axion production from astrophysical bodies is a topic in continuous development, because of theoretical progress in the estimate of stellar emission rates and, especially, because of improved stellar observations. We carry out a comprehensive analysis of the most informative astrophysics data, revisiting the bounds on axion couplings to photons, nucleons and electrons, and reassessing the significance of various hints of anomalous stellar energy losses. We confront the performance of various theoretical constructions in accounting for these hints, while complying with the observational limits on axion couplings. We identify the most favorable models, and the regions in the mass/couplings parameter space which are preferred by the global fit. Finally, we scrutinize the discovery potential for such models at upcoming helioscopes, namely IAXO and its scaled versions

Modelling of autogenous healing for regular concrete via a discrete model

In this paper a numerical model for autogenous healing of normal strength concrete is presented in detail, along with preliminary results of its validation, which is planned to be achieved by comparing the results of numerical analyses with those of a dedicated experimental campaign. Recently the SMM (Solidification-Microprestress-Microplane model M4) model for concrete, which makes use of a modified microplane model M4 and the solidification-microprestress theory, has been extended to incorporate the autogenous healing effects. The moisture and heat fields, as well as the hydration degree, are obtained from the solution of a hygro-thermo-chemical problem, which is coupled with the SMM model. The updated model can also simulate the effects of cracking on the permeability and the restoring effect of the self-healing on the mechanical constitutive laws, i.e. the microplane model. In this work, the same approach is introduced into a discrete model, namely the Lattice Discrete Particle Model (LDPM). A numerical example is presented to validate the proposed computational model employing experimental data from a recent test series undertaken at Politecnico di Milano