Global magnetic attitude control of spacecraft in the presence of gravity gradient

Published versio

Venous Thromboembolism Within Professional American Sport Leagues.

Background: Numerous reports have described players in professional American sports leagues who have been sidelined with a deep vein thrombosis (DVT) or a pulmonary embolism (PE), but little is known about the clinical implications of these events in professional athletes. Purpose: To conduct a retrospective review of injury reports from the National Hockey League (NHL), Major League Baseball (MLB), the National Basketball Association (NBA), and the National Football League (NFL) to take a closer look at the incidence of DVT/PE, current treatment approaches, and estimated time to return to play in professional athletes. Study Design: Descriptive epidemiology study. Methods: An online search of all team injury and media reports of DVT/PE in NHL, MLB, NBA, and NFL players available for public record was conducted by use of Google, PubMed, and SPORTDiscus. Searches were conducted using the professional team name combined with blood clot, pulmonary embolism, and deep vein thrombosis. Results: A total of 55 venous thromboembolism (VTE) events were identified from 1999 through 2016 (NHL, n = 22; MLB, n = 16; NFL, n = 12; NBA, n = 5). Nineteen athletes were reported to have an upper extremity DVT, 15 had a lower extremity DVT, 15 had a PE, and 6 had DVT with PE. Six athletes sustained more than 1 VTE. The mean age at time of VTE was 29.3 years (range, 19-42 years). Mean (±SD) time lost from play was 6.7 ± 4.9 months (range, 3 days to career end). Seven athletes did not return to play. Players with upper extremity DVT had a faster return to play (mean ± SD, 4.3 ± 2.7 months) than those with lower extremity DVT (5.9 ± 3.8 months), PE (10.8 ± 6.8 months), or DVT with PE (8.2 ± 2.6 months) (F = 5.69, P = .002). No significant difference was found regarding time of return to play between sports. Conclusion: VTE in professional athletes led to an average of 6.7 months lost from play. The majority of athletes were able to return to play after a period of anticoagulation or surgery. Those with an upper extremity DVT returned to play faster than those with other types of VTE. Further study is needed to look into modifiable risk factors for these events and to establish treatment and return-to-play guidelines to ensure the safety of these athletes

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

Application of a Fault Detection and Isolation System on a Rotary Machine

The paper illustrates the design and the implementation of a Fault Detection and Isolation (FDI) system to a rotary machine like a multishaft centrifugal compressor. A model-free approach, that is, the Principal Component Analysis (PCA), has been employed to solve the fault detection issue. For the fault isolation purpose structured residuals have been adopted while an adaptive threshold has been designed in order to detect and to isolate the faults. To prove the goodness of the proposed FDI system, historical data of a nitrogen centrifugal compressor employed in a refinery plant are considered. Tests results show that detection and isolation of single as well as multiple faults are successfully achieved

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

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

THERMODYNAMIC ORC CYCLE DESIGN OPTIMIZATION FOR MEDIUM-LOW TEMPERATURE ENERGY SOURCES

In the large spectrum of organic fluids suitable for Rankine cycles, a fluid that is already wellknown and available on industrial scale but currently excluded from this kind of application has been selected. This choice is due to the remarkable characteristics of the fluid, such as its high molecular weight, good thermal stability, non-flammability, and atoxicity. Compared to those fluids nowadays common in the ORC market, its thermodynamic properties and fluid dynamic behavior lead to a peculiar configuration of the cycle: • Supercritical cycle, when heat input is at medium-high temperature; • Massive regeneration, to obtain higher efficiency; • Low specific work of the turbine; • Relatively high volumetric expansion ratio and relatively low absolute inlet volumetric flow; Accordingly, an innovative cycle design has been developed, including a once-through Hairpin primary heat exchanger and a multi-stage radial outflow expander. This last innovative component has been designed to get the best performance with the chosen fluid: • The high inlet/outlet volumetric flow ratio is well combined with the change in cross section across the radius; • Compared to an axial turbine, the lower inlet volumetric flow is compensated by higher blades at the first stage. It is feasible thanks to the change in section available along the radius, so that there is no need for partial admission; • The prismatic blade leads to constant velocity diagrams across the blade span; • It minimizes tip leakages and disk friction losses, due to the single disk / multi-stage configuration; • The intrinsical limit of a radial outflow expander to develop high enthalpy drop is not relevant for this cycle, presenting itself a very low enthalpy drop. Moreover the tip speed is limited by the low speed of sound and consequently this kind of expander suits well with this cycle arrangement. The results of this study, conducted through thermodynamic simulations, CFD, stress analysis and economic optimization show an ORC system that reaches high efficiencies, comparable to those typical of existing system

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

Effect Of The Ambient Temperature On The Performance Of Small Size SCO2 Based Pulverized Coal Power Plants

The present work focuses on the analysis of a novel coal fired sCO2 power plant concept developed in the frame of sCO2-Flex H2020 EU funded project. Fossil fuel fired power plants are expected to improve their flexibility in the future energy scenario characterized by a large share of non-predictable and nondispatchable renewable energy sources. This upcoming context requires a new generation of coal fired power plants with a smaller size, a high flexibility and minor requirements for the installation site like no need of water consumption. Carbon dioxide in supercritical cycles is recognized to be a possible solution for this technology shift and could replace in the future common steam Rankine cycles. This paper focuses on the impact of ambient temperature variation on a small size coal fired sCO2 power plants equipped with a dry cooling heat rejection unit, with the aim of understanding the effect on plant operability and system performance. A dedicate tool is implemented for offdesign behavior assessment and different control strategies are investigated. Results show that without a proper design of the heat rejection unit a small increase of ambient temperature may drastically limit the maximum attainable power output of the plant. This penalizing effect is more pronounced in hot locations, but this issue can be limited by adopting a sufficient over-sizing of the cycle heat rejection unit (HRU) or wet-and-dry solutions

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