Super-diffusion versus competitive advection: a simulation

Magnetic element tracking is often used to study the transport and diffusion of the magnetic field on the solar photosphere. From the analysis of the displacement spectrum of these tracers, it has been recently agreed that a regime of super-diffusivity dominates the solar surface. Quite habitually this result is discussed in the framework of fully developed turbulence. But the debate whether the super-diffusivity is generated by a turbulent dispersion process, by the advection due to the convective pattern, or by even another process, is still open, as is the question about the amount of diffusivity at the scales relevant to the local dynamo process. To understand how such peculiar diffusion in the solar atmosphere takes places, we compared the results from two different data-sets (ground-based and space-borne) and developed a simulation of passive tracers advection by the deformation of a Voronoi network. The displacement spectra of the magnetic elements obtained by the data-sets are consistent in retrieving a super-diffusive regime for the solar photosphere, but the simulation also shows a super-diffusive displacement spectrum: its competitive advection process can reproduce the signature of super-diffusion. Therefore, it is not necessary to hypothesize a totally developed turbulence regime to explain the motion of the magnetic elements on the solar surface

Occurrence and persistence of magnetic elements in the quiet Sun

Turbulent convection efficiently transports energy up to the solar photosphere, but its multi-scale nature and dynamic properties are still not fully understood. Several works in the literature have investigated the emergence of patterns of convective and magnetic nature in the quiet Sun at spatial and temporal scales from granular to global. Aims. To shed light on the scales of organisation at which turbulent convection operates, and its relationship with the magnetic flux therein, we studied characteristic spatial and temporal scales of magnetic features in the quiet Sun. Methods. Thanks to an unprecedented data set entirely enclosing a supergranule, occurrence and persistence analysis of magnetogram time series were used to detect spatial and long-lived temporal correlations in the quiet Sun and to investigate their nature. Results. A relation between occurrence and persistence representative for the quiet Sun was found. In particular, highly recurrent and persistent patterns were detected especially in the boundary of the supergranular cell. These are due to moving magnetic elements undergoing motion that behaves like a random walk together with longer decorrelations ($\sim2$ h) with respect to regions inside the supergranule. In the vertices of the supegranular cell the maximum observed occurrence is not associated with the maximum persistence, suggesting that there are different dynamic regimes affecting the magnetic elements

Interdisciplinary study for knowledge and dating of the San Francesco convent in Stampace, Cagliari – Italy (XIII-XXI century)

The Franciscan monastery, situated in the historic center of Cagliari (Sardinia), was founded in the thirteenth century, and transformed during the later centuries, up to the present day. The complexity of the case and the lack of objective data about its history has led us to carry out an interdisciplinary inquiry, in order to achieve a better knowledge of the building, preliminary for the drafting of a restoration project that respects all the signs that the time left. Starting from a deep examination of the indirect sources, turned out to be incomplete, the investigation continued with the execution of a survey with laser scanner and with the characterization of materials and related diseases of degradation. For the laser scanner survey we used a Faro Focus 3D, versatile and lightweight instrument that allows to perform scans with high speed point acquisition and high accuracy. For data elaboration we used the JRC 3D Reconstructor Software by the Gexcel srl. The characterization of the materials was performed on a reasoned sampling of natural and artificial materials, referring to masonry, interstitial mortars and plasters, carried out at strategic points, representative of the various phases of the construction. The samples were studied through mineralogical-petrographic methods with instrumental techniques for the analysis of component materials (OM, X-Ray diffraction). The data obtained, crossed with the results of the reconstruction of historical maps, of the examination of masonry techniques and of the analysis of pattern elements (arches, vaults, decorative elements), have facilitated stratigraphic analysis and helped to advance chronological reasoned hypothesis referring to the building. Besides, an interdisciplinary approach for the study of cultural heritage is very important to define a proper restoration and conservation intervention

A decrease of calcitonin serum concentrations less than 50 percent 30 minutes after thyroid surgery suggests incomplete C-cell tumor tissue removal

The prognosis of medullary thyroid carcinoma (MTC) depends on the completeness of the first surgical treatment. To date, it is not possible to predict whether the tumor has been completely removed after surgery. The aim of this study was to evaluate the reliability of an intraoperative calcitonin monitoring as a predictor of the final outcome after surgery in patients with MTC

Analysis and Geographical Representation of Cilento’s Monastic Architecture

This paper is part of a wider research on the Cilento monastic architec-tures of Italo-Greek origin located in southern Campania (Italy). The investigationconcentrates on the study, updating and analysis of the existing constructions forthe enrichment of the geographical information databases of the Cilento. On thisopportunity, the analysis focuses specifically on two monuments of Basilian foun-dation: the Abbey of Santa Maria di Pattano, in Vallo della Lucania, and the churchof San Nicola di Myra in Sacco Vecchia. The first case study presents superfe-tations that make it difficult to read the architectural languages and to interpretits conformation. On the other hand, the church of San Nicola in Myra, despitebeing located in one of the most famous ghost towns of the Cilento countrysideand showing important deterioration, still preserves its original morphology, char-acterized by a splendid hieratic character that is completely Basilian. The study ofthese constructions was carried out with digital models and geographic informa-tion systems, in order to obtain the original conformation of the Badia of Pattano.The comparative analysis of the information gathered on the other monument wasused to obtain the necessary data to clarify and identify the main constructionpatterns of the Byzantine and Basilian architectures of the area. These data willserve to enrich the current information and, furthermore, to develop more specificmultidisciplinary analyses in the future

Forecasting SYM-H Index: A Comparison Between LongShort-Term Memory and Convolutional Neural Networks

Forecasting geomagnetic indices represents a key point to develop warning systems for the mitigation of possible effects of severe geomagnetic storms on critical ground infrastructures. Here we focus on SYM‐H index, a proxy of the axially symmetric magnetic field disturbance at low and middle latitudes on the Earth's surface. To forecast SYM‐H, we built two artificial neural network (ANN) models and trained both of them on two different sets of input parameters including interplanetary magnetic field components and magnitude and differing for the presence or not of previous SYM‐H values. These ANN models differ in architecture being based on two conceptually different neural networks: the long short‐term memory (LSTM) and the convolutional neural network (CNN). Both networks are trained, validated, and tested on a total of 42 geomagnetic storms among the most intense that occurred between 1998 and 2018. Performance comparison of the two ANN models shows that (1) both are able to well forecast SYM‐H index 1 h in advance, with an accuracy of more than 95% in terms of the coefficient of determination R2; (2) the model based on LSTM is slightly more accurate than that based on CNN when including SYM‐H index at previous steps among the inputs; and (3) the model based on CNN has interesting potentialities being more accurate than that based on LSTM when not including SYM‐H index among the inputs. Predictions made including SYM‐H index among the inputs provide a root mean squared error on average 42% lower than that of predictions made without SYM‐H