Fecal Coliform Release Studies and Development of a Preliminary Nonpoint Source Transport Model for Indicator Bacteria

The effect of grazing on water quality has been documented by bacteriological studies of streams adjacent to grazed areas. Bacterial release from fecal deposits is a parameter of the pollution transport mechanism that is poorly understood. The objective of this study was to determine a fecal coliform release function for cattle fecal deposits. Standard cowpies were rained on with a rainfall simulator, and the fecal coliform counts were determined using the most probably number (MPN) method of enumeration. The fecal deposits were rained on at ages 2 through 100 days. The effects of rainfall intensity and recurrent rainfall were tested. Naturally occurring fecal deposits were also tested to compare their results with the results from the standard cowpies. A log-log regression was found to describe the decline in peak fecal coliform release with fecal deposit age. The 100-day-old fecal deposits produced peak counts of 4,200 fecal coliforms per 100 milliliters of water. This quantity of release is insignificant compared to the release from fresher fecal material. Rainfall intensity had little effect on peak fecal coliform release from fecal deposits that ere 2 or 10 days old. At age 20 days the effect of rainfall intensity was significant; the highest intensity gave the lowest peak counts, and the lowest intensity gave the highest peak counts. The effect of rainfall intensity appears to be related to the dryness of the fecal deposits. Peak fecal coliform counts were significantly lowered by raining on the fecal deposits more than once. This decline was thought to be produced by the loss of bacteria from the fecal deposits during the previous wettings. Standard cowpies produced a peak release regression that was not significantly different from the regression for the natural fecal deposits. Apparently, grossly manipulating the fecal deposits did not significantly change the release patterns

Decentralized non-communicating multiagent collision avoidance with deep reinforcement learning

Finding feasible, collision-free paths for multiagent systems can be challenging, particularly in non-communicating scenarios where each agent's intent (e.g. goal) is unobservable to the others. In particular, finding time efficient paths often requires anticipating interaction with neighboring agents, the process of which can be computationally prohibitive. This work presents a decentralized multiagent collision avoidance algorithm based on a novel application of deep reinforcement learning, which effectively offloads the online computation (for predicting interaction patterns) to an offline learning procedure. Specifically, the proposed approach develops a value network that encodes the estimated time to the goal given an agent's joint configuration (positions and velocities) with its neighbors. Use of the value network not only admits efficient (i.e., real-time implementable) queries for finding a collision-free velocity vector, but also considers the uncertainty in the other agents' motion. Simulation results show more than 26% improvement in paths quality (i.e., time to reach the goal) when compared with optimal reciprocal collision avoidance (ORCA), a state-of-the-art collision avoidance strategy.Ford Motor Compan

Decentralized non-communicating multiagent collision avoidance with deep reinforcement learning

Finding feasible, collision-free paths for multiagent systems can be challenging, particularly in non-communicating scenarios where each agent's intent (e.g. goal) is unobservable to the others. In particular, finding time efficient paths often requires anticipating interaction with neighboring agents, the process of which can be computationally prohibitive. This work presents a decentralized multiagent collision avoidance algorithm based on a novel application of deep reinforcement learning, which effectively offloads the online computation (for predicting interaction patterns) to an offline learning procedure. Specifically, the proposed approach develops a value network that encodes the estimated time to the goal given an agent's joint configuration (positions and velocities) with its neighbors. Use of the value network not only admits efficient (i.e., real-time implementable) queries for finding a collision-free velocity vector, but also considers the uncertainty in the other agents' motion. Simulation results show more than 26% improvement in paths quality (i.e., time to reach the goal) when compared with optimal reciprocal collision avoidance (ORCA), a state-of-the-art collision avoidance strategy.Ford Motor Compan

Influence of Nitrogen Fertilization on the Quality and Quantity of Streamflow from a Forested Watershed

This project was designed to determine the effects of nitrogen fertilization on the quality and quantity of streamflow eminating from an eastern hardwood forest watershed. A 40.67 ha watershed, located in mountainous eastern Kentucky, was aerially fertilized in late April 1975. The forest stand was principally oak, hickory, and yellow poplar, 50 - 55 years of age and in a relatively undisturbed condition. A helicopter applied anunonium nitrate at a rate of 504 kg/ha. Because a large part of applied nitrogen fertilizer ends up in the highly mobile nitrate nitrogen.form, this is the principal ion monitored in this study. No effort was made to avoid live streams during application and, consequently, very high levels of nitrate nitrogen were detected (640 mg/1) in streamfiow within the watershed. Levels potentially toxic to humans and animals persisted in the streamflow for several days following application. Although elevated concentrations of nitrate nitrogen persisted in streamflow leaving the watershed over a two year period no algal blooms or excessive growth of aquatic plants were noted. Rather high concentrations of nitrate nitrogen were found in the soils of the watershed, with greatest concentrations in the surface layer (0 - 5 cm), intermediate amounts at 15 - 20 cm, and the lowest concentrations at the 41 - 46 cm depth. The effects of the fertilizer application on soils persisted less than one year in the 0 - 46 cm depth sampled. Analysis of streamf1ow records indicated a reduction in water yield the first and second growing seasons after treatment. Gross budgeting of nitrate nitrogen inputs vs. outputs suggests this anion accumulates on these relatively undisturbed watersheds at an annual rate of 3 to 5 kg/ha

Scalable accelerated decentralized multi-robot policy search in continuous observation spaces

This paper presents the first ever approach for solving continuous-observation Decentralized Partially Observable Markov Decision Processes (Dec-POMDPs) and their semi-Markovian counterparts, Dec-POSMDPs. This contribution is especially important in robotics, where a vast number of sensors provide continuous observation data. A continuous-observation policy representation is introduced using Stochastic Kernel-based Finite State Automata (SK-FSAs). An SK-FSA search algorithm titled Entropy-based Policy Search using Continuous Kernel Observations (EPSCKO) is introduced and applied to the first ever continuous-observation Dec-POMDP/Dec-POSMDP domain, where it significantly outperforms state-of-the-art discrete approaches. This methodology is equally applicable to Dec-POMDPs and Dec-POSMDPs, though the empirical analysis presented focuses on Dec-POSMDPs due to their higher scalability. To improve convergence, an entropy injection policy search acceleration approach for both continuous and discrete observation cases is also developed and shown to improve convergence rates without degrading policy quality.Boeing Compan

Semantic-level decentralized multi-robot decision-making using probabilistic macro-observations

Robust environment perception is essential for decision-making on robots operating in complex domains. Intelligent task execution requires principled treatment of uncertainty sources in a robot's observation model. This is important not only for low-level observations (e.g., accelerom-eter data), but also for high-level observations such as semantic object labels. This paper formalizes the concept of macro-observations in Decentralized Partially Observable Semi-Markov Decision Processes (Dec-POSMDPs), allowing scalable semantic-level multi-robot decision making. A hierarchical Bayesian approach is used to model noise statistics of low-level classifier outputs, while simultaneously allowing sharing of domain noise characteristics between classes. Classification accuracy of the proposed macro-observation scheme, called Hierarchical Bayesian Noise Inference (HBNI), is shown to exceed existing methods. The macro-observation scheme is then integrated into a Dec-POSMDP planner, with hardware experiments running onboard a team of dynamic quadrotors in a challenging domain where noise-agnostic filtering fails. To the best of our knowledge, this is the first demonstration of a real-time, convolutional neural net-based classification framework running fully onboard a team of quadrotors in a multi-robot decision-making domain.Boeing Compan

Stability of string defects in models of non-Abelian symmetry breaking

In this paper we describe a new type of topological defect, called a homilia string, which is stabilized via interactions with the string network. Using analytical and numerical techniques, we investigate the stability and dynamics of homilia strings, and show that they can form stable electroweak strings. In SU(2)xU(1) models of symmetry breaking the intersection of two homilia strings is identified with a sphaleron. Due to repulsive forces, the homilia strings seperate, resulting in sphaleron annihilation. It is shown that electroweak homilia string loops cannot stabilize as vortons, which circumvents the adverse cosmological problems associated with stable loops. The consequences for GUT scale homilia strings are also discussed.Comment: 15 pages, revtex, with 8 figures. Submitted to PR

A Profile of Biomass Stove Use in Sri Lanka

A large body of evidence has confirmed that the indoor air pollution (IAP) from biomass fuel use is a major cause of premature deaths, and acute and chronic diseases. Over 78% of Sri Lankans use biomass fuel for cooking, the major source of IAP in developing countries. We conducted a review of the available literature and data sources to profile biomass fuel use in Sri Lanka. We also produced two maps (population density and biomass use; and cooking fuel sources by district) to illustrate the problem in a geographical context. The biomass use in Sri Lanka is limited to wood while coal, charcoal, and cow dung are not used. Government data sources indicate poor residents in rural areas are more likely to use biomass fuel. Respiratory diseases, which may have been caused by cooking emissions, are one of the leading causes of hospitalizations and death. The World Health Organization estimated that the number of deaths attributable to IAP in Sri Lanka in 2004 was 4300. Small scale studies have been conducted in-country in an attempt to associate biomass fuel use with cataracts, low birth weight, respiratory diseases and lung cancer. However, the IAP issue has not been broadly researched and is not prominent in Sri Lankan public health policies and programs to date. Our profile of Sri Lanka calls for further analytical studies and new innovative initiatives to inform public health policy, advocacy and program interventions to address the IAP problem of Sri Lanka

Hubble Space Telescope Ultraviolet Spectroscopy of Fourteen Low-Redshift Quasars

We present low-resolution ultraviolet spectra of 14 low redshift (z<0.8) quasars observed with HST/STIS as part of a Snap project to understand the relationship between quasar outflows and luminosity. By design, all observations cover the CIV emission line. Nine of the quasars are from the Hamburg-ESO catalog, three are from the Palomar-Green catalog, and one is from the Parkes catalog. The sample contains a few interesting quasars including two broad absorption line (BAL) quasars (HE0143-3535, HE0436-2614), one quasar with a mini-BAL (HE1105-0746), and one quasar with associated narrow absorption (HE0409-5004). These BAL quasars are among the brightest known (though not the most luminous) since they lie at z<0.8. We compare the properties of these BAL quasars to the z1.4 Large Bright Quasar samples. By design, our objects sample luminosities in between these two surveys, and our four absorbed objects are consistent with the v ~ L^0.62 relation derived by Laor & Brandt (2002). Another quasar, HE0441-2826, contains extremely weak emission lines and our spectrum is consistent with a simple power-law continuum. The quasar is radio-loud, but has a steep spectral index and a lobe-dominated morphology, which argues against it being a blazar. The unusual spectrum of this quasar resembles the spectra of the quasars PG1407+265, SDSSJ1136+0242, and PKS1004+13 for which several possible explanations have been entertained.Comment: Uses aastex.cls, 21 pages in preprint mode, including 6 figures and 2 tables; accepted for publication in The Astronomical Journal (projected vol 133