6,813 research outputs found
Large probe arrays for measuring mean and time dependent local oil volume fraction and local oil velocity component distributions in inclined oil-in-water flows
Arrays of dual-sensor and four-sensor needle conductance probes have been used to measure the mean and time dependent local properties of upward inclined, bubbly oil-in-water flows (also known as dispersed oil-in-water flows) in a 153mm diameter pipe. The flow properties that were measured were (i) the local in-situ oil volume fraction ; (ii) the local oil velocity in the axial direction of the pipe (the direction); and (iii) the local oil velocity in the direction from the lower side of the inclined pipe to its upper side (the direction). Oil velocities in the direction (orthogonal to the and directions) were found to be negligible. For all of the flow conditions investigated it was found that the mean value of varied from a maximum value at the upper side of the inclined pipe to a minimum value at the lower side, and that the rate of decrease of this mean value of with distance in the direction became greater as the pipe inclination angle from the vertical was increased. It was also found that the mean value of was greatest at the upper side of the inclined pipe and decreased towards the lower side of the inclined pipe, the rate of decrease with distance in the direction again becoming greater as was increased. For , a water volumetric flow rate , an oil volumetric flow rate and using a sampling period over a total time interval of , it was found that at the upper side of the inclined pipe the standard deviation in was 31.6% of the mean value of . Furthermore for , , and it was found that the standard deviation in the cross-pipe oil velocity component was approximately equal to the standard deviation in the axial velocity component . These large temporal variations in the local flow properties have been attributed to the presence of large scale Kelvin-Helmholtz waves which intermittently appear in the flow. It is believed that the techniques outlined in this paper for measuring the standard deviation of local flow properties as a function of the sampling period will be of considerable value in validating mathematical models of time dependent oil-water flows. It should be noted that the principal focus of this paper is on the measurement techniques that were used and the methods of data analysis rather than the presentation of exhaustive experimental results at numerous different flow conditions
Detecting series periodicity with horizontal visibility graphs
The horizontal visibility algorithm has been recently introduced as a mapping
between time series and networks. The challenge lies in characterizing the
structure of time series (and the processes that generated those series) using
the powerful tools of graph theory. Recent works have shown that the visibility
graphs inherit several degrees of correlations from their associated series,
and therefore such graph theoretical characterization is in principle possible.
However, both the mathematical grounding of this promising theory and its
applications are on its infancy. Following this line, here we address the
question of detecting hidden periodicity in series polluted with a certain
amount of noise. We first put forward some generic properties of horizontal
visibility graphs which allow us to define a (graph theoretical) noise
reduction filter. Accordingly, we evaluate its performance for the task of
calculating the period of noisy periodic signals, and compare our results with
standard time domain (autocorrelation) methods. Finally, potentials,
limitations and applications are discussed.Comment: To be published in International Journal of Bifurcation and Chao
Design and operation of the wide angular-range chopper spectrometer ARCS at the Spallation Neutron Source
The wide angular-range chopper spectrometer ARCS at the Spallation Neutron Source (SNS) is optimized to provide a high neutron flux at the sample position with a large solid angle of detector coverage. The instrument incorporates modern neutron instrumentation, such as an elliptically focused neutron guide, high speed magnetic bearing choppers, and a massive array of ^3He linear position sensitive detectors. Novel features of the spectrometer include the use of a large gate valve between the sample and detector vacuum chambers and the placement of the detectors within the vacuum, both of which provide a window-free final flight path to minimize background scattering while allowing rapid changing of the sample and sample environment equipment. ARCS views the SNS decoupled ambient temperature water moderator, using neutrons with incident energy typically in the range from 15 to 1500 meV. This range, coupled with the large detector coverage, allows a wide variety of studies of excitations in condensed matter, such as lattice dynamics and magnetism, in both powder and single-crystal samples. Comparisons of early results to both analytical and Monte Carlo simulation of the instrument performance demonstrate that the instrument is operating as expected and its neutronic performance is understood. ARCS is currently in the SNS user program and continues to improve its scientific productivity by incorporating new instrumentation to increase the range of science covered and improve its effectiveness in data collection
Partial Advantage Estimator for Proximal Policy Optimization
This paper proposes an innovative approach to the Generalized Advantage Estimator (GAE) to address the bias-variance trade-off in truncated roll-outs during reinforcement learning. In typical GAE implementations, the k-step advantage is estimated using a lambda-weighted average, until the terminal state. While this method provides constant bias-variance properties at any time step, it often necessitates truncated roll-outs with shorter horizons for faster learning and policy updates within a single episode. This study highlights an unexplored issue: the bias-variance properties differ for small versus considerable time steps within truncated roll-outs. Specifically, smaller time steps may have a significant bias, prompting a need for their increase. The proposed solution involves a partial GAE update, calculating the advantage estimates for all time steps but updating the policy only for a specified range. To prevent data wastage, the data from this range is retained for further processing and policy parameter updates. This partial GAE approach, despite the increased memory requirements, promises enhanced computation speed and optimal data utilization. Empirical validation was conducted on four MuJoCo tasks and microRTS. The results show a performance improvement trend with the partial GAE estimator, outperforming regular GAE in task completion speed in microRTS. These findings offer a promising direction for improving policy update efficiency in reinforcement learning
Does emotional memory enhancement assist the memory-impaired?
We review recent work on emotional memory enhancement in older adults and patients with mild cognitive impairment (MCI) or Alzheimer dementia (AD) and evaluate the viability of incorporating emotional components into cognitive rehabilitation for these groups. First, we identify converging evidence regarding the effects of emotional valence on working memory in healthy aging. Second, we introduce work that suggests a more complex role for emotional memory enhancement in aging and identify a model capable of unifying disparate research findings. Third, we survey the neuroimaging literature for evidence of a special role for the amygdala in MCI and early AD in emotional memory enhancement. Finally, we assess the theoretical feasibility of incorporating emotional content into cognitive rehabilitation given all available evidence
A -polycosymplectic Marsden-Weinstein reduction
This work reviews and slightly improves the known -polysymplectic
Marsden-Weinstein reduction theory by removing some technical conditions
concerning -polysymplectic momentum maps and the existence of manifold
structures. This is mainly accomplished by developing a theory of affine Lie
group actions for -polysymplectic momentum maps, which removes the necessity
of their co-adjoint equivariance. Then, we focus on the analysis of a
particular case of -polysymplectic manifolds, the so-called fibred ones, and
we study their -polysymplectic Marsden-Weinstein reductions. Previous
results allow us to devise a k-polycosymplectic Marsden-Weinstein reduction
theory, which represents one of our main results. Our findings are applied to
study coupled vibrating strings and, more generally, -polycosymplectic
Hamiltonian systems with field symmetries. As a very relevant byproduct, we
show that -polycosymplectic geometry can be understood as a particular type
of -polysymplectic geometry.Comment: 49 pages. Revised version. Added a reduction procedure of the
space-time coordinate
Deforestation in South America's tri-national Parana Atlantic Forest: Trends and associational factors
South America's Tri-national Parana Atlantic Forest, an ecological region spanning across the nations of Argentina, Brazil and Paraguay, is one of the most diverse in the world but also one of the most vulnerable to deforestation. A review of public policy interventions shows all three governments have taken major legislative steps to protect remaining forests, but studies evaluating deforestation trends and associated factors in this region are scarce or non-existent. Here, we make a direct contribution to this knowledge gap by assessing deforestation trends within Pararna Atlantic forests of Argentina's Misiones, Brazil's Parana, and Paraguay's Alto Parana be-tween 2000 and 2020. Over this period about 20% of forest cover was lost in Misiones, 13% in Parana, and 18% in Alto Parana. The odds of observed deforestation, else constant, showed nuanced associations with proximity to nearest roads, cities, and ports. Higher levels of economic growth were directly associated with deforestation, as were increases in population density over the entire period. Protected area designation between years 2000 and 2020 showed effectiveness in lowering odds of deforestation with heterogeneous associations across countries. Our results reflect associational inferences with estimated deforestation; future research should investigate causal effects of protected designation, and assess its role in avoided degradation and wider socio-economic impacts
Spitzer Mid-Infrared Photometry of 500 - 750 K Brown Dwarfs
Mid-infrared data, including Spitzer warm-IRAC [3.6] and [4.5] photometry, is
critical for understanding the cold population of brown dwarfs now being found,
objects which have more in common with planets than stars. As effective
temperature (T_eff) drops from 800 K to 400 K, the fraction of flux emitted
beyond 3 microns increases rapidly, from about 40% to >75%. This rapid increase
makes a color like H-[4.5] a very sensitive temperature indicator, and it can
be combined with a gravity- and metallicity-sensitive color like H-K to
constrain all three of these fundamental properties, which in turn gives us
mass and age for these slowly cooling objects. Determination of mid-infrared
color trends also allows better exploitation of the WISE mission by the
community. We use new Spitzer Cycle 6 IRAC photometry, together with published
data, to present trends of color with type for L0 to T10 dwarfs. We also use
the atmospheric and evolutionary models of Saumon & Marley to investigate the
masses and ages of 13 very late-type T dwarfs, which have H-[4.5] > 3.2 and
T_eff ~ 500 K to 750 K.Comment: To be published in the on-line version of the Proceedings of Cool
Stars 16 (ASP Conference Series). This is an updated version of Leggett et
al. 2010 ApJ 710 1627; a photometry compilation is available at
http://www.gemini.edu/staff/slegget
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