scholarly journals Parameterizing neural power spectra

2018 ◽  
Author(s):  
Matar Haller ◽  
Thomas Donoghue ◽  
Erik Peterson ◽  
Paroma Varma ◽  
Priyadarshini Sebastian ◽  
...  
Keyword(s):  
Large Scale ◽  
A Priori ◽  
Power Spectra ◽  
Neuronal Population ◽  
Task Demands ◽  
Center Frequency ◽  
Cognitive State ◽  
Periodic Signal ◽  
Periodic Oscillations ◽  
Aperiodic Signal

AbstractElectrophysiological signals across species and recording scales exhibit both periodic and aperiodic features. Periodic oscillations have been widely studied and linked to numerous physiological, cognitive, behavioral, and disease states, while the aperiodic “background” 1/f component of neural power spectra has received far less attention. Most analyses of oscillations are conducted on a priori, canonically-defined frequency bands without consideration of the underlying aperiodic structure, or verification that a periodic signal even exists in addition to the aperiodic signal. This is problematic, as recent evidence shows that the aperiodic signal is dynamic, changing with age, task demands, and cognitive state. It has also been linked to the relative excitation/inhibition of the underlying neuronal population. This means that standard analytic approaches easily conflate changes in the periodic and aperiodic signals with one another because the aperiodic parameters—along with oscillation center frequency, power, and bandwidth—are all dynamic in physiologically meaningful, but likely different, ways. In order to overcome the limitations of traditional narrowband analyses and to reduce the potentially deleterious effects of conflating these features, we introduce a novel algorithm for automatic parameterization of neural power spectral densities (PSDs) as a combination of the aperiodic signal and putative periodic oscillations. Notably, this algorithm requires no a priori specification of band limits and accounts for potentially-overlapping oscillations while minimizing the degree to which they are confounded with one another. This algorithm is amenable to large-scale data exploration and analysis, providing researchers with a tool to quickly and accurately parameterize neural power spectra.

scholarly journals Aperiodic Flux Variability in A 0535+262

1996 ◽  
Vol 165 ◽  
pp. 313-319
Author(s):  
Mark H. Finger ◽  
Robert B. Wilson ◽  
B. Alan Harmon ◽  
William S. Paciesas
Keyword(s):  
Neutron Star ◽  
Gamma Ray ◽  
Beat Frequency ◽  
Power Spectra ◽  
Center Frequency ◽  
X Ray ◽  
Binary Pulsar ◽  
Transient Source ◽  
Flux Variability ◽  
Burst And Transient Source

A “giant” outburst of A 0535+262, a transient X-ray binary pulsar, was observed in 1994 February and March with the Burst and Transient Source Experiment (BATSE) onboard the Compton Gamma-Ray Observatory. During the outburst power spectra of the hard X-ray flux contained a QPO-like component with a FWHM of approximately 50% of its center frequency. Over the course of the outburst the center frequency rose smoothly from 35 mHz to 70 mHz and then fell to below 40 mHz. We compare this QPO frequency with the neutron star spin-up rate, and discuss the observed correlation in terms of the beat frequency and Keplerian frequency QPO models in conjunction with the Ghosh-Lamb accretion torque model.

scholarly journals Experiment Investigation of Bistable Vibration Energy Harvesting with Random Wave Environment

2021 ◽  
Vol 11 (9) ◽  
pp. 3868
Author(s):  
Qiong Wu ◽  
Hairui Zhang ◽  
Jie Lian ◽  
Wei Zhao ◽  
Shijie Zhou ◽  
...  
Keyword(s):  
Renewable Energy ◽  
Energy Harvesting ◽  
Cantilever Beam ◽  
Large Scale ◽  
Low Frequency ◽  
Vibration Energy ◽  
Random Wave ◽  
Periodic Signal ◽  
Vibration Energy Harvesting ◽  
Motion Activity

The energy harvested from the renewable energy has been attracting a great potential as a source of electricity for many years; however, several challenges still exist limiting output performance, such as the package and low frequency of the wave. Here, this paper proposed a bistable vibration system for harvesting low-frequency renewable energy, the bistable vibration model consisting of an inverted cantilever beam with a mass block at the tip in a random wave environment and also develop a vibration energy harvesting system with a piezoelectric element attached to the surface of a cantilever beam. The experiment was carried out by simulating the random wave environment using the experimental equipment. The experiment result showed a mass block’s response vibration was indeed changed from a single stable vibration to a bistable oscillation when a random wave signal and a periodic signal were co-excited. It was shown that stochastic resonance phenomena can be activated reliably using the proposed bistable motion system, and, correspondingly, large-scale bistable responses can be generated to realize effective amplitude enlargement after input signals are received. Furthermore, as an important design factor, the influence of periodic excitation signals on the large-scale bistable motion activity was carefully discussed, and a solid foundation was laid for further practical energy harvesting applications.

scholarly journals The anisotropy of the power spectrum in periodic cosmological simulations

2021 ◽  
Vol 503 (4) ◽  
pp. 5638-5645
Author(s):  
Gábor Rácz ◽  
István Szapudi ◽  
István Csabai ◽  
László Dobos
Keyword(s):  
Dark Matter ◽  
Power Spectrum ◽  
Large Scale ◽  
Cold Dark Matter ◽  
Initial Conditions ◽  
Power Spectra ◽  
Cosmological Simulations ◽  
Spherical Collapse ◽  
Lower Amplitude ◽  
Hydrodynamical Simulations

ABSTRACT The classical gravitational force on a torus is anisotropic and always lower than Newton’s 1/r2 law. We demonstrate the effects of periodicity in dark matter only N-body simulations of spherical collapse and standard Lambda cold dark matter (ΛCDM) initial conditions. Periodic boundary conditions cause an overall negative and anisotropic bias in cosmological simulations of cosmic structure formation. The lower amplitude of power spectra of small periodic simulations is a consequence of the missing large-scale modes and the equally important smaller periodic forces. The effect is most significant when the largest mildly non-linear scales are comparable to the linear size of the simulation box, as often is the case for high-resolution hydrodynamical simulations. Spherical collapse morphs into a shape similar to an octahedron. The anisotropic growth distorts the large-scale ΛCDM dark matter structures. We introduce the direction-dependent power spectrum invariant under the octahedral group of the simulation volume and show that the results break spherical symmetry.

scholarly journals Relationships between Southeast Australian Temperature Anomalies and Large-Scale Climate Drivers

2014 ◽  
Vol 27 (4) ◽  
pp. 1395-1412 ◽  
Author(s):  
Alexandre O. Fierro ◽  
Lance M. Leslie
Keyword(s):  
Large Scale ◽  
Southern Oscillation ◽  
Power Spectra ◽  
Warm Season ◽  
Principal Component ◽  
Temperature Variability ◽  
Maximum Temperature ◽  
Past Century ◽  
Tasman Sea ◽  
Australian Continent

Abstract Over the past century, particularly after the 1960s, observations of mean maximum temperatures reveal an increasing trend over the southeastern quadrant of the Australian continent. Correlation analysis of seasonally averaged mean maximum temperature anomaly data for the period 1958–2012 is carried out for a representative group of 10 stations in southeast Australia (SEAUS). For the warm season (November–April) there is a positive relationship with the El Niño–Southern Oscillation (ENSO) and the Pacific decadal oscillation (PDO) and an inverse relationship with the Antarctic Oscillation (AAO) for most stations. For the cool season (May–October), most stations exhibit similar relationships with the AAO, positive correlations with the dipole mode index (DMI), and marginal inverse relationships with the Southern Oscillation index (SOI) and the PDO. However, for both seasons, the blocking index (BI, as defined by M. Pook and T. Gibson) in the Tasman Sea (160°E) clearly is the dominant climate mode affecting maximum temperature variability in SEAUS with negative correlations in the range from r = −0.30 to −0.65. These strong negative correlations arise from the usual definition of BI, which is positive when blocking high pressure systems occur over the Tasman Sea (near 45°S, 160°E), favoring the advection of modified cooler, higher-latitude maritime air over SEAUS. A point-by-point correlation with global sea surface temperatures (SSTs), principal component analysis, and wavelet power spectra support the relationships with ENSO and DMI. Notably, the analysis reveals that the maximum temperature variability of one group of stations is explained primarily by local factors (warmer near-coastal SSTs), rather than teleconnections with large-scale drivers.

EARRINGS: an efficient and accurate adapter trimmer entails no a priori adapter sequences

2021 ◽  
Author(s):  
Ting-Hsuan Wang ◽  
Cheng-Ching Huang ◽  
Jui-Hung Hung
Keyword(s):  
Open Source Software ◽  
Large Scale ◽  
A Priori ◽  
Supplementary Information ◽  
Supplementary Data ◽  
Comparable Accuracy ◽  
Meta Analyses ◽  
Next Generation Sequencing Ngs ◽  
Adapter Trimming ◽  
Generation Sequencing

Abstract Motivation Cross-sample comparisons or large-scale meta-analyses based on the next generation sequencing (NGS) involve replicable and universal data preprocessing, including removing adapter fragments in contaminated reads (i.e. adapter trimming). While modern adapter trimmers require users to provide candidate adapter sequences for each sample, which are sometimes unavailable or falsely documented in the repositories (such as GEO or SRA), large-scale meta-analyses are therefore jeopardized by suboptimal adapter trimming. Results Here we introduce a set of fast and accurate adapter detection and trimming algorithms that entail no a priori adapter sequences. These algorithms were implemented in modern C++ with SIMD and multithreading to accelerate its speed. Our experiments and benchmarks show that the implementation (i.e. EARRINGS), without being given any hint of adapter sequences, can reach comparable accuracy and higher throughput than that of existing adapter trimmers. EARRINGS is particularly useful in meta-analyses of a large batch of datasets and can be incorporated in any sequence analysis pipelines in all scales. Availability and implementation EARRINGS is open-source software and is available at https://github.com/jhhung/EARRINGS. Supplementary information Supplementary data are available at Bioinformatics online.

scholarly journals A simple conceptual model to interpret the 100 000 years dynamics of paleo-climate records

2010 ◽  
Vol 17 (5) ◽  
pp. 585-592 ◽  
Author(s):  
C. S. Quiroga Lombard ◽  
P. Balenzuela ◽  
H. Braun ◽  
D. R. Chialvo
Keyword(s):  
Large Scale ◽  
Power Spectra ◽  
Greenland Ice Sheet ◽  
Ice Age ◽  
Solar Cycles ◽  
The Holocene ◽  
De Vries ◽  
Last Ice Age ◽  
Paleoclimate Records ◽  
Dominant Frequencies

Abstract. Spectral analyses performed on records of cosmogenic nuclides reveal a group of dominant spectral components during the Holocene period. Only a few of them are related to known solar cycles, i.e., the De Vries/Suess, Gleissberg and Hallstatt cycles. The origin of the others remains uncertain. On the other hand, time series of North Atlantic atmospheric/sea surface temperatures during the last ice age display the existence of repeated large-scale warming events, called Dansgaard-Oeschger (DO) events, spaced around multiples of 1470 years. The De Vries/Suess and Gleissberg cycles with periods close to 1470/7 (~210) and 1470/17 (~86.5) years have been proposed to explain these observations. In this work we found that a conceptual bistable model forced with the De Vries/Suess and Gleissberg cycles plus noise displays a group of dominant frequencies similar to those obtained in the Fourier spectra from paleo-climate during the Holocene. Moreover, we show that simply changing the noise amplitude in the model we obtain similar power spectra to those corresponding to GISP2 δ18O (Greenland Ice Sheet Project 2) during the last ice age. These results give a general dynamical framework which allows us to interpret the main characteristic of paleoclimate records from the last 100 000 years.

scholarly journals Research on Efficacy Evaluation of Large-Scale Networked Intelligent Perception System

2022 ◽  
Vol 2022 ◽  
pp. 1-11
Author(s):  
Suqiong Ge ◽  
Xiaopeng Huang
Keyword(s):  
Evaluation System ◽  
Large Scale ◽  
Task Demands ◽  
Prototype System ◽  
Engineering System ◽  
Conceptual System ◽  
Efficacy Evaluation ◽  
Perception System ◽  
Service Oriented ◽  
Evaluation Platform

Under the smart engineering system (SES), there is a huge demand for evaluating the efficacy of a large-scale networked intelligent perception system (IPS). Considering the large-scale, distributed, and networked system characteristics and perception task demands, this paper proposes a conceptual system for IPS efficacy evaluation and, on this basis, designs the architecture of the efficacy evaluation system. A networked IPS model is constructed based on domain ontology, an index system is quickly established for efficacy evaluation, the evaluation methods are assembled automatically, and adaptive real-time organization strategies are generated for networked perception based on efficacy estimate. After exploring these key technologies, a prototype system is created for the service-oriented integrated efficacy evaluation platform and used to verify and integrate research results. The research provides support for the efficacy evaluation theories and methods of large-scale networked IPS.

scholarly journals Anti-symmetric clustering signals in the observed power spectrum

2021 ◽  
Vol 2021 (12) ◽  
pp. 003
Author(s):  
José Fonseca ◽  
Chris Clarkson
Keyword(s):  
Dark Matter ◽  
Power Spectrum ◽  
Euler Equation ◽  
Large Scale ◽  
Signal To Noise Ratio ◽  
Power Spectra ◽  
Large Scale Structure ◽  
Scale Structure ◽  
Signal To Noise ◽  
Peculiar Velocities

Abstract In this paper, we study how to directly measure the effect of peculiar velocities in the observed angular power spectra. We do this by constructing a new anti-symmetric estimator of Large Scale Structure using different dark matter tracers. We show that the Doppler term is the major component of our estimator and we show that we can measure it with a signal-to-noise ratio up to ∼ 50 using a futuristic SKAO HI galaxy survey. We demonstrate the utility of this estimator by using it to provide constraints on the Euler equation.

scholarly journals Integrating Multiple and Fine Scale Predictors of Habitat Selection and Landscape Resistance for Amphibian Distribution Modelling at Large Scale

2021 ◽  
Author(s):  
Florence Matutini ◽  
Jacques Baudry ◽  
Marie-Josée Fortin ◽  
Guillaume Pain ◽  
Joséphine Pithon
Keyword(s):  
Large Scale ◽  
A Priori ◽  
Species Level ◽  
Fine Scale ◽  
Landscape Resistance ◽  
Amphibian Species ◽  
Distribution Modelling ◽  
Multi Scale ◽  
Functional Grain ◽  
Level Analysis

Abstract Context – Species distribution modelling is a common tool in conservation biology but two main criticisms remain: (1) the use of simplistic variables that do not account for species movements and/or connectivity and (2) poor consideration of multi-scale processes driving species distributions. Objectives – We aimed to determine if including multi-scale and fine-scale movement processes in SDM predictors would improve accuracy of SDM for low-mobility amphibian species over species-level analysis.Methods – We tested and compared different SDMs for nine amphibian species with four different sets of predictors: (1) simple distance-based predictors; (2) single-scale compositional predictors; (3) multi-scale compositional predictors with a priori selection of scale based on knowledge of species mobility and scale-of-effect (4) multi-scale compositional predictors calculated using a friction-based functional grain to account for resource accessibility with landscape resistance to movement.Results - Using friction-based functional grain predictors produced slight to moderate improvements of SDM performance at large scale. The multi-scale approach, with a priori scale selection led to ambiguous results depending on the species studied, in particular for generalist species.Conclusion - We underline the potential of using a friction-based functional grain to improve SDM predictions for species-level analysis.

Power spectral density of magnetic field and ion velocity fluctuations from inertial to kinetic ranges

2021 ◽  
Author(s):  
Jana Šafránková ◽  
Zdeněk Němeček ◽  
František Němec ◽  
Luca Franci ◽  
Alexander Pitňa
Keyword(s):  
Magnetic Field ◽  
Solar Wind ◽  
Large Scale ◽  
Collisionless Plasma ◽  
Power Spectra ◽  
Physical Parameters ◽  
Particle In Cell ◽  
High Reynolds ◽  
Experimental Findings ◽  
Turbulent Cascade

<p>The solar wind is a unique laboratory to study the turbulent processes occurring in a collisionless plasma with high Reynolds numbers. A turbulent cascade—the process that transfers the free energy contained within the large scale fluctuations into the smaller ones—is believed to be one of the most important mechanisms responsible for heating of the solar corona and solar wind. The paper analyzes power spectra of solar wind velocity, density and magnetic field fluctuations that are computed in the frequency range around the break between inertial and kinetic scales. The study uses measurements of the Bright Monitor of the Solar Wind (BMSW) on board the Spektr-R spacecraft with a time resolution of 32 ms complemented with 10 Hz magnetic field observations from the Wind spacecraft propagated to the Spektr-R location. The statistics based on more than 42,000 individual spectra show that: (1) the spectra of both quantities can be fitted by two (three in the case of the density) power-law segments; (2) the median slopes of parallel and perpendicular fluctuation velocity and magnetic field components are different; (3) the break between MHD and kinetic scales as well as the slopes are mainly controlled by the ion beta parameter. These experimental results are compared with high-resolution 2D hybrid particle-in-cell simulations, where the electrons are considered to be a massless, charge-neutralizing fluid with a constant temperature, whereas the ions are described as macroparticles representing portions of their distribution function. In spite of several limitations (lack of the electron kinetics, lower dimensionality), the model results agree well with the experimental findings. Finally, we discuss differences between observations and simulations in relation to the role of important physical parameters in determining the properties of the turbulent cascade.</p>

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