A Dose Relationship Between Brain Functional Connectivity and Cumulative Head Impact Exposure in Collegiate Water Polo Players.

A growing body of evidence suggests that chronic, sport-related head impact exposure can impair brain functional integration and brain structure and function. Evidence of a robust inverse relationship between the frequency and magnitude of repeated head impacts and disturbed brain network function is needed to strengthen an argument for causality. In pursuing such a relationship, we used cap-worn inertial sensors to measure the frequency and magnitude of head impacts sustained by eighteen intercollegiate water polo athletes monitored over a single season of play. Participants were evaluated before and after the season using computerized cognitive tests of inhibitory control and resting electroencephalography. Greater head impact exposure was associated with increased phase synchrony [r (16) > 0.626, p < 0.03 corrected], global efficiency [r (16) > 0.601, p < 0.04 corrected], and mean clustering coefficient [r (16) > 0.625, p < 0.03 corrected] in the functional networks formed by slow-wave (delta, theta) oscillations. Head impact exposure was not associated with changes in performance on the inhibitory control tasks. However, those with the greatest impact exposure showed an association between changes in resting-state connectivity and a dissociation between performance on the tasks after the season [r (16) = 0.481, p = 0.043] that could also be attributed to increased slow-wave synchrony [F (4, 135) = 113.546, p < 0.001]. Collectively, our results suggest that athletes sustaining the greatest head impact exposure exhibited changes in whole-brain functional connectivity that were associated with altered information processing and inhibitory control

Thermoelectric cross-plane properties on p- and n-Ge/SixGe1-x superlattices

Silicon and germanium materials have demonstrated an increasing attraction for energy harvesting, due to their sustainability and integrability with complementary metal oxide semiconductor and micro-electro-mechanical-system technology. The thermoelectric efficiencies for these materials, however, are very poor at room temperature and so it is necessary to engineer them in order to compete with telluride based materials, which have demonstrated at room temperature the highest performances in literature [1]. Micro-fabricated devices consisting of mesa structures with integrated heaters, thermometers and Ohmic contacts were used to extract the cross-plane values of the Seebeck coefficient and the thermal conductivity from p- and n-Ge/SixGe1-x superlattices. A second device consisting in a modified circular transfer line method structure was used to extract the electrical conductivity of the materials. A range of p-Ge/Si0.5Ge0.5 superlattices with different doping levels was investigated in detail to determine the role of the doping density in dictating the thermoelectric properties. A second set of n-Ge/Si0.3Ge0.7 superlattices was fabricated to study the impact that quantum well thickness might have on the two thermoelectric figures of merit, and also to demonstrate a further reduction of the thermal conductivity by scattering phonons at different wavelengths. This technique has demonstrated to lower the thermal conductivity by a 25% by adding different barrier thicknesses per period

Toward a Coordinated Global Observing System for Seagrasses and Marine Macroalgae

In coastal waters around the world, the dominant primary producers are benthic macrophytes, including seagrasses and macroalgae, that provide habitat structure and food for diverse and abundant biological communities and drive ecosystem processes. Seagrass meadows and macroalgal forests play key roles for coastal societies, contributing to fishery yields, storm protection, biogeochemical cycling and storage, and important cultural values. These socio-economically valuable services are threatened worldwide by human activities, with substantial areas of seagrass and macroalgal forests lost over the last half-century. Tracking the status and trends in marine macrophyte cover and quality is an emerging priority for ocean and coastal management, but doing so has been challenged by limited coordination across the numerous efforts to monitor macrophytes, which vary widely in goals, methodologies, scales, capacity, governance approaches, and data availability. Here, we present a consensus assessment and recommendations on the current state of and opportunities for advancing global marine macrophyte observations, integrating contributions from a community of researchers with broad geographic and disciplinary expertise. With the increasing scale of human impacts, the time is ripe to harmonize marine macrophyte observations by building on existing networks and identifying a core set of common metrics and approaches in sampling design, field measurements, governance, capacity building, and data management. We recommend a tiered observation system, with improvement of remote sensing and remote underwater imaging to expand capacity to capture broad-scale extent at intervals of several years, coordinated with stratified in situ sampling annually to characterize the key variables of cover and taxonomic or functional group composition, and to provide ground-truth. A robust networked system of macrophyte observations will be facilitated by establishing best practices, including standard protocols, documentation, and sharing of resources at all stages of workflow, and secure archiving of open-access data. Because such a network is necessarily distributed, sustaining it depends on close engagement of local stakeholders and focusing on building and long-term maintenance of local capacity, particularly in the developing world. Realizing these recommendations will produce more effective, efficient, and responsive observing, a more accurate global picture of change in vegetated coastal systems, and stronger international capacity for sustaining observations

Driven lattice glass as a ratchet and pawl machine

Boundary-induced transport in particle systems with anomalous diffusion exhibits rectification, negative resistance, and hysteresis phenomena depending on the way the drive acts on the boundary. The solvable case of a 1D system characterized by a power-law diffusion coefficient and coupled to two particles reservoirs at different chemical potential is examined. In particular, it is shown that a microscopic realisation of such a diffusion model is provided by a 3D driven lattice-gas with kinetic constraints, in which energy barriers are absent and the local microscopic reversibility holds.Comment: 12 pages, 4 figures, minor change

Noise in neurons is message-dependent

Neuronal responses are conspicuously variable. We focus on one particular aspect of that variability: the precision of action potential timing. We show that for common models of noisy spike generation, elementary considerations imply that such variability is a function of the input, and can be made arbitrarily large or small by a suitable choice of inputs. Our considerations are expected to extend to virtually any mechanism of spike generation, and we illustrate them with data from the visual pathway. Thus, a simplification usually made in the application of information theory to neural processing is violated: noise {\sl is not independent of the message}. However, we also show the existence of {\sl error-correcting} topologies, which can achieve better timing reliability than their components.Comment: 6 pages,6 figures. Proceedings of the National Academy of Sciences (in press

Polarization squeezing with cold atoms

We study the interaction of a nearly resonant linearly polarized laser beam with a cloud of cold cesium atoms in a high finesse optical cavity. We show theoretically and experimentally that the cross-Kerr effect due to the saturation of the optical transition produces quadrature squeezing on both the mean field and the orthogonally polarized vacuum mode. An interpretation of this vacuum squeezing as polarization squeezing is given and a method for measuring quantum Stokes parameters for weak beams via a local oscillator is developed

Scale-free brain functional networks

Functional magnetic resonance imaging (fMRI) is used to extract {\em functional networks} connecting correlated human brain sites. Analysis of the resulting networks in different tasks shows that: (a) the distribution of functional connections, and the probability of finding a link vs. distance are both scale-free, (b) the characteristic path length is small and comparable with those of equivalent random networks, and (c) the clustering coefficient is orders of magnitude larger than those of equivalent random networks. All these properties, typical of scale-free small world networks, reflect important functional information about brain states.Comment: 4 pages, 5 figures, 2 table