BCI-assisted training for upper limb motor rehabilitation: estimation of effects on individual brain connectivity and motor functions

The aim of the study is to quantify individual changes in scalp connectivity patterns associated to the affected hand movement in stroke patients after a 1-month training based on BCIsupported motor imagery to improve upper limb motor recovery. To perform the statistical evaluation between pre- and post-training conditions at the single subject level, a resampling approach was applied to EEG datasets acquired from 12 stroke patients during the execution of a motor task with the stroke affected hand before and after the rehabilitative intervention. Significant patterns of the network reinforced after the training were extracted and a significant correlation was found between indices related to the reinforced pattern and the clinical outcome indicated by clinical scales

A Comprehensive Analysis of Multilayer Community Detection Algorithms for Application to EEG-Based Brain Networks

Modular organization is an emergent property of brain networks, responsible for shaping communication processes and underpinning brain functioning. Moreover, brain networks are intrinsically multilayer since their attributes can vary across time, subjects, frequency, or other domains. Identifying the modular structure in multilayer brain networks represents a gateway toward a deeper understanding of neural processes underlying cognition. Electroencephalographic (EEG) signals, thanks to their high temporal resolution, can give rise to multilayer networks able to follow the dynamics of brain activity. Despite this potential, the community organization has not yet been thoroughly investigated in brain networks estimated from EEG. Furthermore, at the state of the art, there is still no agreement about which algorithm is the most suitable to detect communities in multilayer brain networks, and a way to test and compare them all under a variety of conditions is lacking. In this work, we perform a comprehensive analysis of three algorithms at the state of the art for multilayer community detection (namely, genLouvain, DynMoga, and FacetNet) as compared with an approach based on the application of a single-layer clustering algorithm to each slice of the multilayer network. We test their ability to identify both steady and dynamic modular structures. We statistically evaluate their performances by means of ad hoc benchmark graphs characterized by properties covering a broad range of conditions in terms of graph density, number of clusters, noise level, and number of layers. The results of this simulation study aim to provide guidelines about the choice of the more appropriate algorithm according to the different properties of the brain network under examination. Finally, as a proof of concept, we show an application of the algorithms to real functional brain networks derived from EEG signals collected at rest with closed and open eyes. The test on real data provided results in agreement with the conclusions of the simulation study and confirmed the feasibility of multilayer analysis of EEG-based brain networks in both steady and dynamic conditions

Oxidative potential associated with urban aerosol deposited into the respiratory system and relevant elemental and ionic fraction contributions

Size-segregated aerosol measurements were carried out at an urban and at an industrial site. Soluble and insoluble fractions of elements and inorganic ions were determined. Oxidative potential (OP) was assessed on the soluble fraction of Particulate Matter (PM) by ascorbic acid (AA), dichlorofluorescein (DCFH) and dithiothreitol (DTT) assays. Size resolved elemental, ion and OP doses in the head (H), tracheobronchial (TB) and alveolar (Al) regions were estimated using the Multiple-Path Particle Dosimetry (MPPD) model. The total aerosol respiratory doses due to brake and soil resuspension emissions were higher at the urban than at the industrial site. On the contrary, the doses of anthropic combustion tracers were generally higher at the industrial site. In general, the insoluble fraction was more abundantly distributed in the coarse than in the fine mode and vice versa for the soluble fraction. Consequently, for the latter, the percent of the total respiratory dose deposited in TB and Al regions increased. Oxidative potential assay (OPAA) doses were distributed in the coarse region; therefore, their major contribution was in the H region. The contribution in the TB and Al regions increased for OPDTT and OPDCFH

Effectiveness of Different Sample Treatments for the Elemental Characterization of Bees and Beehive Products

Bee health and beehive products’ quality are compromised by complex interactions between multiple stressors, among which toxic elements play an important role. The aim of this study is to optimize and validate sensible and reliable analytical methods for biomonitoring studies and the quality control of beehive products. Four digestion procedures, including two systems (microwave oven and water bath) and different mixture reagents, were evaluated for the determination of the total content of 40 elements in bees and five beehive products (beeswax, honey, pollen, propolis and royal jelly) by using inductively coupled plasma mass and optical emission spectrometry. Method validation was performed by measuring a standard reference material and the recoveries for each selected matrix. The water bath-assisted digestion of bees and beehive products is proposed as a fast alternative to microwave-assisted digestion for all elements in biomonitoring studies. The present study highlights the possible drawbacks that may be encountered during the elemental analysis of these biological matrices and aims to be a valuable aid for the analytical chemist. Total elemental concentrations, determined in commercially available beehive products, are presented

Eliminating ambiguities for quantum corrections to strings moving in AdS4×CP3AdS_4\times \mathbb{CP}^3

We apply a physical principle, previously used to eliminate ambiguities in quantum corrections to the 2 dimensional kink, to the case of spinning strings moving in $AdS_4\times \mathbb{CP}^3$, thought of as another kind of two dimensional soliton. We find that this eliminates the ambiguities and selects the result compatible with AdS/CFT, providing a solid foundation for one of the previous calculations, which found agreement. The method can be applied to other classical string "solitons".Comment: 18 pages, latex; references added, comments added at end of section 4, a few words changed; footnote added on page 1

Base cation mobility in vineyard soils of the Colli Albani volcanic district (Central Italy)

The quality of the Colli Albani volcanic soils has certainly contributed to the vine cultivars hence the name of one of the oldest wines (i.e., Alban wine). The alkali up to 15 wt%, SiO2 ≤ 52 wt% and the emplacement at high temperature (≤ 600 °C) are the bedrock features that have deeply influenced the soil-forming processes in the vineyards. However, the peculiar features of the Colli Albani soils are not well known. Field survey and textural, mineralogical, and chemical data obtained with SEM, EMP, XRD, and ICP-OES were used to characterize the vineyard soils of the Colli Albani. Leucite (Lct)-bearing soils and quartz (Qz)-bearing soils occur in the studied vineyard. The Qz-bearing soils represent more weathered volcanic material, depleted in primary minerals and enriched in clays, which show a lower cation exchange capacity (CEC) than the Lct-bearing soils. CEC is a misleading definition for the Colli Albani soils because the base cation mobility in the vineyard is independent from clay mineral enrichment in the soil. Actually, the release of K, Na, Ca, and Mg depends by (i) the complete dissolution of leucite and analcime, (ii) the oxy-reaction affecting the phlogopite, which releases K + Mg, and (iii) the incongruent dissolution of clinopyroxene characterized by the “gothic texture.” This texture highlights the capacity of clinopyroxene to release Ca and Mg in volcanic soils. Quantification of the texture and abundance of the primary minerals are mandatory for the management of the vineyard soils in the Colli Albani and, in general, it is significative for the vineyards in volcanic areas

Influence of scattering coefficient on the prediction of room acoustic parameters in a virtual concert hall.

The scattering coefficient is one of the most important input parameters in room acoustics simulations. Together with absorption coefficient they belong to main descriptors of interior surface properties in the calculation process based on ray or radiosity method algorithms. This paper investigates the influence of scattered sound on the objective room acoustical parameters in the example of a virtual concert hall. Six different alternatives were simulated, where scattering coefficients s = 10, 30, 50, 60, 70 and 90 % respectively, were applied to the interior surfaces of the ceiling, side and rear walls. Analysis has been performed by studying the results of objective room acoustical parameters predicted by simulations done in the software Catt-Acoustic®

Causality estimates among brain cortical areas by Partial Directed Coherence: simulations and application to real data

The problem of the definition and evaluation of brain connectivity has become a central one in neuroscience during the latest years, as a way to understand the organization and interaction of cortical areas during the execution of cognitive or motor tasks. Among various methods established during the years, the Partial Directed Coherence (PDC) is a frequency-domain approach to this problem, based on a multivariate autoregressive modeling of time series and on the concept of Granger causality. In this paper we propose the use of the PDC method on cortical signals estimated from high resolution EEG recordings, a non invasive method which exhibits a higher spatial resolution than conventional cerebral electromagnetic measures. The principle contributions of this work are the results of a simulation study, testing the performances of PDC, and a statistical analysis (via the ANOVA, analysis of variance) of the influence of different levels of Signal to Noise Ratio and temporal length, as they have been systematically imposed on simulated signals. An application to high resolution EEG recordings during a foot movement is also presented

Wind turbine systematic yaw error: Operation data analysis techniques for detecting IT and assessing its performance impact

The widespread availability of wind turbine operation data has considerably boosted the research and the applications for wind turbine monitoring. It is well established that a systematic misalignment of the wind turbine nacelle with respect to the wind direction has a remarkable impact in terms of down-performance, because the extracted power is in first approximation proportional to the cosine cube of the yaw angle. Nevertheless, due to the fact that in the wind farm practice the wind field facing the rotor is estimated through anemometers placed behind the rotor, it is challenging to robustly detect systematic yaw errors without the use of additional upwind sensory systems. Nevertheless, this objective is valuable because it involves the use of data that are available to wind farm practitioners at zero cost. On these grounds, the present work is a two-steps test case discussion. At first, a new method for systematic yaw error detection through operation data analysis is presented and is applied for individuating a misaligned multi-MW wind turbine. After the yaw error correction on the test case wind turbine, operation data of the whole wind farm are employed for an innovative assessment method of the performance improvement at the target wind turbine. The other wind turbines in the farm are employed as references and their operation data are used as input for a multivariate Kernel regression whose target is the power of the wind turbine of interest. Training the model with pre-correction data and validating on post-correction data, it is estimated that a systematic yaw error of 4◦ affects the performance up to the order of the 1.5% of the Annual Energy Production