17,887 research outputs found
Whole-stream metabolism: strategies for measuring and modeling diel trends of dissolved oxygen
Stream metabolism is used to characterize the allochthonous and autochthonous basis of stream foodweb production. The metabolic rates of respiration and gross primary production often are estimated from changes in dissolved O2 concentration in the stream over time. An upstream–downstream O2 accounting method (2-station) is used commonly to estimate metabolic rates in a defined length of stream channel. Various approaches to measuring and analyzing diel O2 trends have been used, but a detailed comparison of different approaches (e.g., required reach length, method of measuring aeration rate [k], and use of temperature-corrected metabolic rates) is needed. We measured O2 upstream and downstream of various reaches in Kings Creek, Kansas. We found that 20 m was the approximate minimum reach length required to detect a significant change in O2, a result that matched the prediction of a calculation method to determine minimum reach length. We assessed the ability of models based on 2-station diel O2 data and k measurements in various streams around Manhattan, Kansas, to predict k accurately, and we tested the importance of accounting for temperature effects on metabolic rates. We measured gas exchange directly with an inert gas and used a tracer dye to account for dilution and to measure velocity and discharge. Modeled k was significantly correlated with measured k (Kendall's τ, p < 0.001; regression adjusted R²  =  0.70), but 19 published equations for estimating k generally provided poor estimates of measured k (only 6 of 19 equations were significantly correlated). Temperature correction of metabolic rates allowed us to account for increases in nighttime O2, and temperature-corrected metabolic rates fit the data somewhat better than uncorrected estimates. Use of temperature-correction estimates could facilitate cross-site comparisons of metabolism
Solar Sources of Interplanetary Magnetic Clouds Leading to Helicity Prediction
This study identifies the solar origins of magnetic clouds that are observed
at 1 AU and predicts the helical handedness of these clouds from the solar
surface magnetic fields. We started with the magnetic clouds listed by the
Magnetic Field Investigation (MFI) team supporting NASA's WIND spacecraft in
what is known as the MFI table and worked backwards in time to identify solar
events that produced these clouds. Our methods utilize magnetograms from the
Helioseismic and Magnetic Imager (HMI) instrument on the Solar Dynamics
Observatory (SDO) spacecraft so that we could only analyze MFI entries after
the beginning of 2011. This start date and the end date of the MFI table gave
us 37 cases to study. Of these we were able to associate only eight surface
events with clouds detected by WIND at 1 AU. We developed a simple algorithm
for predicting the cloud helicity which gave the correct handedness in all
eight cases. The algorithm is based on the conceptual model that an ejected
flux tube has two magnetic origination points at the positions of the strongest
radial magnetic field regions of opposite polarity near the places where the
ejected arches end at the solar surface. We were unable to find events for the
remaining 29 cases: lack of a halo or partial halo CME in an appropriate time
window, lack of magnetic and/or filament activity in the proper part of the
solar disk, or the event was too far from disk center. The occurrence of a
flare was not a requirement for making the identification but in fact flares,
often weak, did occur for seven of the eight cases.Comment: 18 pages, 8 figures, 2 table
Using Monte Carlo Search With Data Aggregation to Improve Robot Soccer Policies
RoboCup soccer competitions are considered among the most challenging
multi-robot adversarial environments, due to their high dynamism and the
partial observability of the environment. In this paper we introduce a method
based on a combination of Monte Carlo search and data aggregation (MCSDA) to
adapt discrete-action soccer policies for a defender robot to the strategy of
the opponent team. By exploiting a simple representation of the domain, a
supervised learning algorithm is trained over an initial collection of data
consisting of several simulations of human expert policies. Monte Carlo policy
rollouts are then generated and aggregated to previous data to improve the
learned policy over multiple epochs and games. The proposed approach has been
extensively tested both on a soccer-dedicated simulator and on real robots.
Using this method, our learning robot soccer team achieves an improvement in
ball interceptions, as well as a reduction in the number of opponents' goals.
Together with a better performance, an overall more efficient positioning of
the whole team within the field is achieved
A note on leapfrogging vortex rings
In this paper we provide examples, by numerical simulation using the Navier-Stokes equations for axisymmetric laminar flow, of the 'leapfrogging' motion of two, initially identical, vortex rings which share a common axis of symmetry. We show that the number of clear passes that each ring makes through the other increases with Reynolds number, and that as long as the configuration remains stable the two rings ultimately merge to form a single vortex ring
Control of perennial weeds based on weed biology and environmental considerations
Timing, type and duration of tillage operations and cropping practices are of importance for reducing the regeneration of perennial weeds and also for minimizing the environmental impacts of such operations. In the present work and with reference to previous publications we find that, based on the knowledge gained on growth patterns, sensitivity to competition, growth potential of roots and mechanical and management measures it is possible to coordinate control of perennial weeds with considerations of yield and reduced environmental impact
Flow losses in flexible hose, volume 1 Final report
Empirical method for predicting flow loss of gas or liquid in flexible hose
Cyclic loading of tendon fascicles using a novel fatigue loading system increases interleukin-6 expression by tenocytes
Repetitive strain or ‘overuse’ is thought to be a major factor contributing to the development of tendinopathy. The aims of our study were to develop a novel cyclic loading system, and use it to investigate the effect of defined loading conditions on the mechanical properties and gene expression of isolated tendon fascicles. Tendon fascicles were dissected from bovine-foot extensors and subjected to cyclic tensile strain (1 Hz) at 30% or 60% of the strain at failure, for 0 h (control), 15 min, 30 min, 1 h, or 5 h. Post loading, a quasi-static test to failure assessed damage. Gene expression at a selected loading regime (1 h at 30% failure strain) was analyzed 6 h post loading by quantitative real-time polymerase chain reaction. Compared with unloaded controls, loading at 30% failure strain took 5 h to lead to a significant decrease in failure stress, whereas loading to 60% led to a significant reduction after 15 min. Loading for 1 h at 30% failure strain did not create significant structural damage, but increased Collagen-1-alpha-chain-1 and interleukin-6 (IL6) expression, suggesting a role of IL6 in tendon adaptation to exercise. Correlating failure properties with fatigue damage provides a method by which changes in gene expression can be associated with different degrees of fatigue damage
Study of space shuttle environmental control and life support problems
Four problem areas were treated: (1) cargo module environmental control and life support systems; (2) space shuttle/space station interfaces; (3) thermal control considerations for payloads; and (4) feasibility of improving system reusability
Simulator study of the effect of control-system time delays on the occurrence of pilot-induced oscillations and on pilot tracking performance with a space-shuttle-orbiter configuration
Using a six degree-of-freedom motion-base simulator, the effect of control-system time delays on the occurrence of pilot-induced oscillations (PIO's) on the vehicle handling qualities and on pilot tracking performance for a landing-approach configuration of the Space Shuttle orbiter was studied. A linearized math model was employed which represented a 300-knot orbiter with almost all time delays removed. Additional time delays were then inserted following the pilot's hand-controller signals. Only pitch and roll commands were used for vehicle control. The simulation employed an air to air tracking task as a means of emphasizing PIO tendencies. Two astronauts, two research pilots, and one simulation engineer served as test subjects. Results showed that PIO's occurred when the amount of added time delay approximated that existing for the orbiter configuration flown in the approach and landing tests. Increasing the amount of delay increased PIO occurrences and resulted in degraded tracking performance. Decreasing the amount of time delay eliminated the PIO's
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