The INTERNODES method for the treatment of non-conforming multipatch geometries in Isogeometric Analysis

In this paper we apply the INTERNODES method to solve second order elliptic problems discretized by Isogeometric Analysis methods on non-conforming multiple patches in 2D and 3D geometries. INTERNODES is an interpolation-based method that, on each interface of the configuration, exploits two independent interpolation operators to enforce the continuity of the traces and of the normal derivatives. INTERNODES supports non-conformity on NURBS spaces as well as on geometries. We specify how to set up the interpolation matrices on non-conforming interfaces, how to enforce the continuity of the normal derivatives and we give special attention to implementation aspects. The numerical results show that INTERNODES exhibits optimal convergence rate with respect to the mesh size of the NURBS spaces an that it is robust with respect to jumping coefficients.Comment: Accepted for publication in Computer Methods in Applied Mechanics and Engineerin

Time dependent Ginzburg-Landau equation for an N-component model of self-assembled fluids

We study the time evolution of an N-component model of bicontinuous microemulsions based on a time dependent Ginzburg-Landau equation quenched from an high temperature uncorrelated state to the low temperature phases. The behavior of the dynamical structure factor $\tilde C(k,t)$ is obtained, in each phase, in the framework of the large-$N$ limit with both conserved (COP) and non conserved (NCOP) order parameter dynamics. At zero temperature the system shows multiscaling in the unstructured region up to the tricritical point for the COP whereas ordinary scaling is obeyed for NCOP. In the structured phase, instead, the conservation law is found to be irrelevant and the form $\tilde C(k,t) \sim t^{\alpha / z} f((|k-k_m| t^{1/z})$, with $\alpha=1$ and $z=2$, is obtained in every case. Simple scaling relations are also derived for the structure factor as a function of the final temperature of the thermal bath.Comment: 9 pages,Apste

Suitable classification of mortars from ancient roman and renaissance frescoes using thermal analysis and chemometrics

Background Literature on mortars has mainly focused on the identification and characterization of their components in order to assign them to a specific historical period, after accurate classification. For this purpose, different analytical techniques have been proposed. Aim of the present study was to verify whether the combination of thermal analysis and chemometric methods could be used to obtain a fast but correct classification of ancient mortar samples of different ages (Roman era and Renaissance). Results Ancient Roman frescoes from Museo Nazionale Romano (Terme di Diocleziano, Rome, Italy) and Renaissance frescoes from Sistine Chapel and Old Vatican Rooms (Vatican City) were analyzed by thermogravimetry (TG) and differential thermal analysis (DTA). Principal Component analysis (PCA) on the main thermal data evidenced the presence of two clusters, ascribable to the two different ages. Inspection of the loadings allowed to interpret the observed differences in terms of the experimental variables. Conclusions PCA allowed differentiating the two kinds of mortars (Roman and Renaissance frescoes), and evidenced how the ancient Roman samples are richer in binder (calcium carbonate) and contain less filler (aggregate) than the Renaissance ones. It was also demonstrated how the coupling of thermoanalytical techniques and chemometric processing proves to be particularly advantageous when a rapid and correct differentiation and classification of cultural heritage samples of various kinds or ages has to be carried out

The Hierarchic treatment of marine ecological information from spatial networks of benthic platforms

Measuring biodiversity simultaneously in different locations, at different temporal scales, and over wide spatial scales is of strategic importance for the improvement of our understanding of the functioning of marine ecosystems and for the conservation of their biodiversity. Monitoring networks of cabled observatories, along with other docked autonomous systems (e.g., Remotely Operated Vehicles [ROVs], Autonomous Underwater Vehicles [AUVs], and crawlers), are being conceived and established at a spatial scale capable of tracking energy fluxes across benthic and pelagic compartments, as well as across geographic ecotones. At the same time, optoacoustic imaging is sustaining an unprecedented expansion in marine ecological monitoring, enabling the acquisition of new biological and environmental data at an appropriate spatiotemporal scale. At this stage, one of the main problems for an effective application of these technologies is the processing, storage, and treatment of the acquired complex ecological information. Here, we provide a conceptual overview on the technological developments in the multiparametric generation, storage, and automated hierarchic treatment of biological and environmental information required to capture the spatiotemporal complexity of a marine ecosystem. In doing so, we present a pipeline of ecological data acquisition and processing in different steps and prone to automation. We also give an example of population biomass, community richness and biodiversity data computation (as indicators for ecosystem functionality) with an Internet Operated Vehicle (a mobile crawler). Finally, we discuss the software requirements for that automated data processing at the level of cyber-infrastructures with sensor calibration and control, data banking, and ingestion into large data portals.Peer ReviewedPostprint (published version

Hierarchical classification pathway for white maize, defect and foreign material classification using spectral imaging

This study aimed to present the South African maize industry with an accurate and affordable automated analytical technique for white maize grading using near infrared (NIR) spectral imaging. The 17 categories and sub-categories stipulated in South African maize grading legislation were simultaneously classified (1044 samples; 60 kernels of each class) using 25 partial least squares discriminant analysis (PLS-DA) models. The models were assembled in a hierarchical decision pathway that progressed from the most easily classified classes to the most difficult. The full NIR spectrum (288 wavebands) model performed with an overall accuracy of 93.3% for the main categories. Three waveband selection techniques were employed, namely waveband windows (48 wavebands), variable importance in projection (VIP) (21 wavebands) and covariance selection (CovSel) (13 wavebands). Overall, the VIP set based on only 7.3% of the original spectral variables was recommended as the best trade-off between performance and expected cost of a reduced waveband system. © 2020 Elsevier B.V

iSEE: Interactive SummarizedExperiment Explorer

Data exploration is critical to the comprehension of large biological data sets generated by high-throughput assays such as sequencing. However, most existing tools for interactive visualisation are limited to specific assays or analyses. Here, we present the iSEE (Interactive SummarizedExperiment Explorer) software package, which provides a general visual interface for exploring data in a SummarizedExperiment object. iSEE is directly compatible with many existing R/Bioconductor packages for analysing high-throughput biological data, and provides useful features such as simultaneous examination of (meta)data and analysis results, dynamic linking between plots and code tracking for reproducibility. We demonstrate the utility and flexibility of iSEE by applying it to explore a range of real transcriptomics and proteomics data sets.German Federal Ministry of Education and Researc

Proprioceptive training and sports performance

One of the current trends in the field of sports training concerns the integration into training programs of exercises defined as "proprioceptive", which also include balance exercises, used to optimize performance, prevention or recovery from injuries. After introducing and describing the main characteristics of proprioceptive training in sports, the present review aims to set out and analyse the various flaws in this type of training as it is commonly practiced, in order to lay the groundwork for future improvements in proprioceptive training. Our research highlights that it is common practice to combine proprioceptive training with training on unstable surfaces, generally meaning the same for both situations. Such practices are indicative of the confusion surrounding the concepts of proprioception and balance. Indeed, until these two concepts and their respective performance benefits are clearly differentiated, it will be difficult to move beyond the controversy surrounding proprioceptive training and hence. to make advances in the field of proprioceptive training research. In conclusion, therefore, against the comforting theories that accompany the use of proprioceptive training in relation to the improvement of performance, unfortunately there is a literature that shows many variables not yet considered or treated in an approximate way

Authentication of Sorrento walnuts by NIR spectroscopy coupled with different chemometric classification strategie

Walnuts have been widely investigated because of their chemical composition, which is particularly rich in unsaturated fatty acids, responsible for different benefits in the human body. Some of these fruits, depending on the harvesting area, are considered a high value-added food, thus resulting in a higher selling price. In Italy, walnuts are harvested throughout the national territory, but the fruits produced in the Sorrento area (South Italy) are commercially valuable for their peculiar organoleptic characteristics. The aim of the present study is to develop a non-destructive and shelf-life compatible method, capable of discriminating common walnuts from those harvested in Sorrento (a town in Southern Italy), considered a high quality product. Two-hundred-and-twenty-seven walnuts (105 from Sorrento and 132 grown in other areas) were analyzed by near-infrared spectroscopy (both whole or shelled), and classified by Partial Least Squares-Discriminant Analysis (PLS-DA). Eventually, two multi-block approaches have been exploited in order to combine the spectral information collected on the shell and on the kernel. One of these latter strategies provided the best results (98.3% of correct classification rate in external validation, corresponding to 1 misclassified object over 60). The present study suggests the proposed strategy is a suitable solution for the discrimination of Sorrento walnuts. © 2020 by the authors

Chemometric Methods for Spectroscopy-Based Pharmaceutical Analysis

Spectroscopy is widely used to characterize pharmaceutical products or processes, especially due to its desirable characteristics of being rapid, cheap, non-invasive/non-destructive and applicable both off-line and in-/at-/on-line. Spectroscopic techniques produce profiles containing a high amount of information, which can profitably be exploited through the use of multivariate mathematic and statistic (chemometric) techniques. The present paper aims at providing a brief overview of the different chemometric approaches applicable in the context of spectroscopy-based pharmaceutical analysis, discussing both the unsupervised exploration of the collected data and the possibility of building predictive models for both quantitative (calibration) and qualitative (classification) responses