Non-REM dreaming in relation to the cyclic alternating pattern an exploratory study

Includes bibliographical references.Dreaming is yet to be studied in relation to sleep microstructure. By endeavouring to study mentation in relation to the finer neurophysiological processes underlying the rhythmicity of the sleep cycles, dream science stands to benefit from the wealth of knowledge of these processes. While relationships between dreaming and certain of these processes have been identified in the literature, a comprehensive study of dreaming in relation to all of the recognized components of the sleep microstructure is completely lacking. With this in mind, the main aim of this study was to examine sleep microstructure in relation to dreaming and determine whether there is any relationship between dream recall and the various types of phasic arousal phenomena during NREM sleep, as systematised within the global framework of the cyclic alternating pattern (CAP)

The Need for Fairness and Accuracy for Women in Sentencing: Surmounting Challenges to Gender-Specific Statistical Risk Assessment Tools

States across the country have increasingly adopted statistical risk assessment tools in multiple stages of their criminal legal systems with the hope of reducing incarceration without increasing crime. These tools use various characteristics to estimate an individual’s future risk of recidivism, and judges consider the results of these assessments when determining levels of custody or community supervision for convicted individuals. Despite much debate amongst academics and activists on the utility and fairness of these tools, one critique seems beyond debate: the tools are built for men, not women. These tools are based on criteria, statistics, and theory drawn from the experiences of men and thereby result in inaccurate and inequitable sentencing when applied to women. When women are sentenced according to the higher rates of violence and recidivism that are associated with men, they are often incarcerated or under supervision longer than justified by their gender-specific risk to society. The unfairness of these assessments is specifically concerning when one considers that, as of 2019, 1.2 million women in the United States were under the supervision of the criminal legal system, with approximately fifty-eight percent of them leaving at least one minor child at home without a mother’s care and guidance. Separate risk assessment tools for men and women can combat the inaccurate sentencing of women. While many commentators have argued for separate tools for men and women, they have not sufficiently addressed how such an approach would survive legal, theoretical, and policy hurdles. This Comment argues (1) that gender-specific assessments could survive an equal protection challenge; (2) that such assessments for women should be implemented despite the need for further research and work on the conflation of sex and gender and the utilization of a gender binary in the United States criminal legal system; and (3) that they could be adapted for women defendants without opening the floodgates to a demand for assessments designed for every conceivable category of criminal defendant

Subtraction-noise projection in gravitational-wave detector networks

In this paper, we present a successful implementation of a subtraction-noise projection method into a simple, simulated data analysis pipeline of a gravitational-wave search. We investigate the problem to reveal a weak stochastic background signal which is covered by a strong foreground of compact-binary coalescences. The foreground which is estimated by matched filters, has to be subtracted from the data. Even an optimal analysis of foreground signals will leave subtraction noise due to estimation errors of template parameters which may corrupt the measurement of the background signal. The subtraction noise can be removed by a noise projection. We apply our analysis pipeline to the proposed future-generation space-borne Big Bang Observer (BBO) mission which seeks for a stochastic background of primordial GWs in the frequency range $\sim 0.1-1$Hz covered by a foreground of black-hole and neutron-star binaries. Our analysis is based on a simulation code which provides a dynamical model of a time-delay interferometer (TDI) network. It generates the data as time series and incorporates the analysis pipeline together with the noise projection. Our results confirm previous ad hoc predictions which say that BBO will be sensitive to backgrounds with fractional energy densities below $\Omega=10^{-16}$Comment: 54 pages, 15 figure

BBO and the Neutron-Star-Binary Subtraction Problem

The Big Bang Observer (BBO) is a proposed space-based gravitational-wave (GW) mission designed primarily to search for an inflation-generated GW background in the frequency range 0.1-1 Hz. The major astrophysical foreground in this range is gravitational radiation from inspiraling compact binaries. This foreground is expected to be much larger than the inflation-generated background, so to accomplish its main goal, BBO must be sensitive enough to identify and subtract out practically all such binaries in the observable universe. It is somewhat subtle to decide whether BBO's current baseline design is sufficiently sensitive for this task, since, at least initially, the dominant noise source impeding identification of any one binary is confusion noise from all the others. Here we present a self-consistent scheme for deciding whether BBO's baseline design is indeed adequate for subtracting out the binary foreground. We conclude that the current baseline should be sufficient. However if BBO's instrumental sensitivity were degraded by a factor 2-4, it could no longer perform its main mission. It is impossible to perfectly subtract out each of the binary inspiral waveforms, so an important question is how to deal with the "residual" errors in the post-subtraction data stream. We sketch a strategy of "projecting out" these residual errors, at the cost of some effective bandwidth. We also provide estimates of the sizes of various post-Newtonian effects in the inspiral waveforms that must be accounted for in the BBO analysis.Comment: corrects some errors in figure captions that are present in the published versio

On predictors for band-limited and high-frequency time series

Pathwise predictability and predictors for discrete time processes are studied in deterministic setting. It is suggested to approximate convolution sums over future times by convolution sums over past time. It is shown that all band-limited processes are predictable in this sense, as well as high-frequency processes with zero energy at low frequencies. In addition, a process of mixed type still can be predicted if an ideal low-pass filter exists for this process.Comment: 10 pages. arXiv admin note: text overlap with arXiv:0708.034

Predictability of band-limited, high-frequency, and mixed processes in the presence of ideal low-pass filters

Pathwise predictability of continuous time processes is studied in deterministic setting. We discuss uniform prediction in some weak sense with respect to certain classes of inputs. More precisely, we study possibility of approximation of convolution integrals over future time by integrals over past time. We found that all band-limited processes are predictable in this sense, as well as high-frequency processes with zero energy at low frequencies. It follows that a process of mixed type still can be predicted if an ideal low-pass filter exists for this process.Comment: 10 page

Particle Swarm Optimization and gravitational wave data analysis: Performance on a binary inspiral testbed

The detection and estimation of gravitational wave (GW) signals belonging to a parameterized family of waveforms requires, in general, the numerical maximization of a data-dependent function of the signal parameters. Due to noise in the data, the function to be maximized is often highly multi-modal with numerous local maxima. Searching for the global maximum then becomes computationally expensive, which in turn can limit the scientific scope of the search. Stochastic optimization is one possible approach to reducing computational costs in such applications. We report results from a first investigation of the Particle Swarm Optimization (PSO) method in this context. The method is applied to a testbed motivated by the problem of detection and estimation of a binary inspiral signal. Our results show that PSO works well in the presence of high multi-modality, making it a viable candidate method for further applications in GW data analysis.Comment: 13 pages, 5 figure

The confinement of phonon propagation in TiAlN/Ag multilayer coatings with anomalously low heat conductivity

TiAlN/Ag multilayer coatings with a different number of bilayers and thicknesses of individual layers were fabricated by DC magnetron co-sputtering. Thermal conductivity was measured in dependence of Ag layer thickness. It was found anomalous low thermal conductivity of silver comparing to TiAlN and Ag bulk standards and TiAlN/TiN multilayers. The physical nature of such thermal barrier properties of the multilayer coatings was explained on the basis of reflection electron energy loss spectroscopy. The analysis shows that nanostructuring of the coating decreases the density of states and velocity of acoustic phonons propagation. At the same time, multiphonon channels of heat propagation degenerate. These results demonstrate that metal-dielectric interfaces in TiAlN/Ag coatings are insurmountable obstacles for acoustic phonons propagation

The Effect of the LISA Response Function on Observations of Monochromatic Sources

The Laser Interferometer Space Antenna (LISA) is expected to provide the largest observational sample of binary systems of faint sub-solar mass compact objects, in particular white-dwarfs, whose radiation is monochromatic over most of the LISA observational window. Current astrophysical estimates suggest that the instrument will be able to resolve about 10000 such systems, with a large fraction of them at frequencies above 3 mHz, where the wavelength of gravitational waves becomes comparable to or shorter than the LISA arm-length. This affects the structure of the so-called LISA transfer function which cannot be treated as constant in this frequency range: it introduces characteristic phase and amplitude modulations that depend on the source location in the sky and the emission frequency. Here we investigate the effect of the LISA transfer function on detection and parameter estimation for monochromatic sources. For signal detection we show that filters constructed by approximating the transfer function as a constant (long wavelength approximation) introduce a negligible loss of signal-to-noise ratio -- the fitting factor always exceeds 0.97 -- for f below 10mHz, therefore in a frequency range where one would actually expect the approximation to fail. For parameter estimation, we conclude that in the range 3mHz to 30mHz the errors associated with parameter measurements differ from about 5% up to a factor of 10 (depending on the actual source parameters and emission frequency) with respect to those computed using the long wavelength approximation.Comment: replacement version with typos correcte