Search results for "STATISTICS"
showing 10 items of 7671 documents
Prevalence and Correlates of Physical activity in a sample of UK adults observing social distancing during the COVID-19 pandemic
2020
ObjectiveTo investigate the levels and correlates of physical activity during COVID-19 social distancing in a sample of the UK public.MethodsThis paper presents analyses of data from a cross-sectional study. Levels of physical activity during COVID-19 social distancing were self-reported. Participants also reported on sociodemographic and clinical data. The association between several factors and physical activity was studied using regression models.ResultsNine hundred and eleven adults were included (64.0% were women and 50.4% of the participants were aged 35–64 years). 75.0% of the participants met the physical activity guidelines during social distancing. Meeting these guidelines during …
Multi-scale morphology of the galaxy distribution
2006
Many statistical methods have been proposed in the last years for analyzing the spatial distribution of galaxies. Very few of them, however, can handle properly the border effects of complex observational sample volumes. In this paper, we first show how to calculate the Minkowski Functionals (MF) taking into account these border effects. Then we present a multiscale extension of the MF which gives us more information about how the galaxies are spatially distributed. A range of examples using Gaussian random fields illustrate the results. Finally we have applied the Multiscale Minkowski Functionals (MMF) to the 2dF Galaxy Redshift Survey data. The MMF clearly indicates an evolution of morpho…
3D Image Based Modelling Using Google Earth Imagery for 3D Landscape Modelling
2019
In recent years SfM technique experiments have been innumerable and increasingly refined under metric profiles. The techniques rely on photographic datasets of the objects or landscapes which can require in most cases time consuming and expensive surveys. Recently however there have been increases in the available 3D data of sites worldwide on the Google Earth (GE) platform. This paper presents a unique experimentation that considers integrating readily available datasets from GE and images taken during surveys on ground level for 3D replication without the use of expensive aerial surveys. This will enable practitioners the ability to more easily create 3D models of cultural heritage signif…
Autonomy-Supportive and Controlling Styles of Teaching
2015
Autonomy-supportive and controlling styles of teaching are usually considered to be the opposite ends of a single continuum. An alternative view, however, is that individuals can perceive both styles simultaneously, which suggests that they are different constructs ( Bartholomew, Ntoumanis, Ryan, Bosch, & Thøgersen-Ntoumani, 2011 ). Using cluster analysis, Study 1 (N = 160) confirmed that both teaching styles were perceived by students. Four clusters appeared depending on the student’s score on the measures of autonomy and controlling styles (high autonomy–high control; low autonomy–low control; high autonomy–low control; low autonomy–high control). Participants in the high autonomy–lo…
GRB 090313 AND THE ORIGIN OF OPTICAL PEAKS IN GAMMA-RAY BURST LIGHT CURVES: IMPLICATIONS FOR LORENTZ FACTORS AND RADIO FLARES
2010
We use a sample of 19 gamma-ray bursts (GRBs) that exhibit single-peaked optical light curves to test the standard fireball model by investigating the relationship between the time of the onset of the afterglow and the temporal rising index. Our sample includes GRBs and X-ray flashes for which we derive a wide range of initial Lorentz factors (40 < Γ < 450). Using plausible model parameters, the typical frequency of the forward shock is expected to lie close to the optical band; within this low typical frequency framework, we use the optical data to constrain εe and show that values derived from the early time light-curve properties are consistent with published typical values derived from …
On singular integral and martingale transforms
2007
Linear equivalences of norms of vector-valued singular integral operators and vector-valued martingale transforms are studied. In particular, it is shown that the UMD(p)-constant of a Banach space X equals the norm of the real (or the imaginary) part of the Beurling-Ahlfors singular integral operator, acting on the X-valued L^p-space on the plane. Moreover, replacing equality by a linear equivalence, this is found to be the typical property of even multipliers. A corresponding result for odd multipliers and the Hilbert transform is given.
A Universal Length-Dependent Vibrational Mode in Graphene Nanoribbons
2019
Graphene nanoribbons (GNRs) have attracted considerable interest as their atomically tunable structure makes them promising candidates for future electronic devices. However, obtaining detailed information about the length of GNRs has been challenging and typically relies on low-temperature scanning tunneling microscopy. Such methods are ill-suited for practical device application and characterization. In contrast, Raman spectroscopy is a sensitive method for the characterization of GNRs, in particular for investigating their width and structure. Here, we report on a length-dependent, Raman active low-energy vibrational mode that is present in atomically precise, bottom-up synthesized armch…
Constraining Uncertainty in Projected Gross Primary Production With Machine Learning
2020
The terrestrial biosphere is currently slowing down global warming by absorbing about 30% of human emissions of carbon dioxide (CO2). The largest flux of the terrestrial carbon uptake is gross primary production (GPP) defined as the production of carbohydrates by photosynthesis. Elevated atmospheric CO2 concentration is expected to increase GPP (“CO2 fertilization effect”). However, Earth system models (ESMs) exhibit a large range in simulated GPP projections. In this study, we combine an existing emergent constraint on CO2 fertilization with a machine learning approach to constrain the spatial variations of multimodel GPP projections. In a first step, we use observed changes in the CO2 sea…
Rough McKean-Vlasov dynamics for robust ensemble Kalman filtering
2021
Motivated by the challenge of incorporating data into misspecified and multiscale dynamical models, we study a McKean-Vlasov equation that contains the data stream as a common driving rough path. This setting allows us to prove well-posedness as well as continuity with respect to the driver in an appropriate rough-path topology. The latter property is key in our subsequent development of a robust data assimilation methodology: We establish propagation of chaos for the associated interacting particle system, which in turn is suggestive of a numerical scheme that can be viewed as an extension of the ensemble Kalman filter to a rough-path framework. Finally, we discuss a data-driven method bas…
Inattention and Uncertainty in the Predictive Brain
2021
Negative effects of inattention on task performance can be seen in many contexts of society and human behavior, such as traffic, work, and sports. In traffic, inattention is one of the most frequently cited causal factors in accidents. In order to identify inattention and mitigate its negative effects, there is a need for quantifying attentional demands of dynamic tasks, with a credible basis in cognitive modeling and neuroscience. Recent developments in cognitive science have led to theories of cognition suggesting that brains are an advanced prediction engine. The function of this prediction engine is to support perception and action by continuously matching incoming sensory input with to…