University of Waterloo

About: University of Waterloo is a education organization based out in Waterloo, Ontario, Canada. It is known for research contribution in the topics: Population & Poison control. The organization has 36093 authors who have published 93906 publications receiving 2948139 citations. The organization is also known as: UW & uwaterloo.

Antidepressants and their metabolites in municipal wastewater, and downstream exposure in an urban watershed

Abstract: Antidepressants are a widely prescribed group of pharmaceuticals that can be biotransformed in humans to biologically active metabolites. In the present study, the distribution of six antidepressants (venlafaxine, bupropion, fluoxetine, sertraline, citalopram, and paroxetine) and five of their metabolites was determined in a municipal wastewater treatment plant (WWTP) and at sites downstream of two WWTPs in the Grand River watershed in southern Ontario, Canada. Fathead minnows (Pimephales promelas) caged in the Grand River downstream of a WWTP were also evaluated for accumulated antidepressants. Finally, drinking water was analyzed from a treatment plant that takes its water from the Grand River 17 km downstream of a WWTP. In municipal wastewater, the antidepressant compounds present in the highest concentrations (i.e., >0.5 microg/L) were venlafaxine and its two demethylation products, O- and N-desmethyl venlafaxine. Removal rates of the target analytes in a WWTP were approximately 40%. These compounds persisted in river water samples collected at sites up to several kilometers downstream of discharges from WWTPs. Venlafaxine, citalopram, and sertraline, and demethylated metabolites were detected in fathead minnows caged 10 m below the discharge from a WWTP, but concentrations were all < microg/kg wet weight. Venlafaxine and bupropion were detected at very low (<0.005 microg/L) concentrations in untreated drinking water, but these compounds were not detected in treated drinking water. The present study illustrates that data are needed on the distribution in the aquatic environment of both the parent compound and the biologically active metabolites of pharmaceuticals.

A survey of naming and routing in information-centric networks

Abstract: The concept of information-centric networking (ICN) defines a new communication model that focuses on what is being exchanged rather than which network entities are exchanging information. From the ICN perspective, contents are first class network citizens instead of hosts. ICN's primary objective is to shift the current host-oriented communication model toward a content-centric model for effective distribution of content over the network. In recent years this paradigm shift has generated much interest in the research community and sprung several research projects around the globe to investigate and advance this stream of thought. Content naming and content-based routing are core research challenges in this research community. In this survey, we analyze, compare, and contrast the naming and routing mechanisms proposed by some of the most prominent ICN research projects.

Optimal rejection of persistent bounded disturbances

Abstract: In this paper, we formulate the problem of optimal disturbance rejection in the case where the disturbance is generated as the output of a stable system in response to an input which is assumed to be of unit amplitude, but is otherwise arbitrary. The objective is to choose a controller that minimizes the maximum amplitude of the plant output in response to such a disturbance. Mathematically, this corresponds to requiring uniformly good disturbance rejection over all time. Since the problem of optimal tracking is equivalent to that of optimal disturbance rejection if a feedback controller is used (see [7, sect. 5.6]), the theory presented here can also be used to design optimal controllers that achieve uniformly good tracking over all time rather than a tracking error whose L 2 -norm is small, as is the case with the currently popular H_{\infty} theory. The present theory is a natural counterpart to the existing theory of optimal disturbance rejection (the so-called H_{\infty} theory) which is based on the assumption that the disturbance to be rejected is generated by a stable system whose input is square-integrable and has unit energy. It is shown that the problem studied here has quite different features from its predecessor. Complete solutions to the problem are given in several important cases, including those where the plant is minimum phase or when it has only a single unstable zero. In other cases, procedures are given for obtaining bounds on the solution and for obtaining suboptimal controllers.

Constraining self-interacting dark matter with the Milky Way’s dwarf spheroidals

Abstract: Self-Interacting Dark Matter is an attractive alternative to the Cold Dark Matter paradigm only if it is able to substantially reduce the central densities of dwarf-size haloes while keeping the densities and shapes of cluster-size haloes within current constraints. Given the seemingly stringent nature of the latter, it was thought for nearly a decade that Self-Interacting Dark Matter would be viable only if the cross section for self-scattering was strongly velocitydependent. However, it has recently been suggested that a constant cross section per unit mass of T=m 0:1cm 2 g 1 is sufficient to accomplish the desired effect. We explicitly investigate this claim using high resolution cosmological simulations of a Milky-Way size halo and find that, similarly to the Cold Dark Matter case, such cross section produces a population of massive subhaloes that is inconsistent with the kinematics of the classical dwarf spheroidals, in particular with the inferred slopes of the mass profiles of Fornax and Sculptor. This problem is resolved if T=m 1cm 2 g 1 at the dwarf spheroidal scales. Since this value is likely inconsistent with the halo shapes of several clusters, our results leave only a small window open for a velocity-independent Self-Interacting Dark Matter model to work as a distinct alternative to Cold Dark Matter.