The use of tricaine methanesulfonate, clove oil, metomidate, and 2-phenoxyethanol for anesthesia induction in alewives (Alosa pseudoharengus)

Anesthetics are widely used in routine aquaculture operations to immobilize animals for tagging, spawning, handling, and vaccination. A number of anesthetics are currently available for finfish, but their efficacy and optimal dosage is highly species-specific. The efficacy of the anesthetic agents (tricaine methanesulfonate (MS-222), clove oil, metomidate, and 2-phenoxyethanol (2-PE)) was studied in adult, juvenile (133.3 ± 1.5 mm, 27.5 ± 8.9 g), and larval Alewives (Alosa pseudoharengus Wilson). In an initial trial, wild-caught adults were anesthetized with doses of 87.5-112.5 mg/L MS-222, 25-40 mg/L clove oil 0.5-5.0 mg/L metomidate and 0.125-0.550 mg/L 2-PE. Optimal doses for anesthesia were similar for larvae and juveniles, and were identified as: 75-100 mg/L MS-222, 40 mg/L clove oil, 5-7 mg/L metomidate, and 500 mg/L 2-PE. All juvenile fish survived 48 hours post-exposure to each optimal dose. In a longer-term (24 hour) sedation experiment, juvenile alewives were netted and exposed to low clove oil (2.5 and 5.0 mg/L) and metomidate (0.25 and 0.50 mg/L) doses, and plasma cortisol was measured. Fish exposed to the clove oil treatments exhibited a cortisol stress response that was prolonged in the higher dose treatment. No cortisol stress response was observed in the metomidate treatments. Overall, optimal acute anesthesia doses for alewives were similar to those reported for other species, and metomidate may be useful for longer-term sedation

Decoherence effects on weak value measurements in double quantum dots

We study the effect of decoherence on a weak value measurement in a paradigm system consisting of a double quantum dot continuously measured by a quantum point contact. Fluctuations of the parameters controlling the dot state induce decoherence. We find that, for measurements longer than the decoherence time, weak values are always reduced within the range of the eigenvalues of the measured observable. For measurements at shorter time scales, the measured weak value strongly depends on the interplay between the decoherence dynamics of the system and the detector backaction. In particular, depending on the postselected state and the strength of the decoherence, a more frequent classical readout of the detector might lead to an enhancement of weak values.Comment: published version, new figures and comments added; 15 pages, 7 figure

Weighted Polynomial Approximations: Limits for Learning and Pseudorandomness

Polynomial approximations to boolean functions have led to many positive results in computer science. In particular, polynomial approximations to the sign function underly algorithms for agnostically learning halfspaces, as well as pseudorandom generators for halfspaces. In this work, we investigate the limits of these techniques by proving inapproximability results for the sign function. Firstly, the polynomial regression algorithm of Kalai et al. (SIAM J. Comput. 2008) shows that halfspaces can be learned with respect to log-concave distributions on $\mathbb{R}^n$ in the challenging agnostic learning model. The power of this algorithm relies on the fact that under log-concave distributions, halfspaces can be approximated arbitrarily well by low-degree polynomials. We ask whether this technique can be extended beyond log-concave distributions, and establish a negative result. We show that polynomials of any degree cannot approximate the sign function to within arbitrarily low error for a large class of non-log-concave distributions on the real line, including those with densities proportional to $\exp(-|x|^{0.99})$. Secondly, we investigate the derandomization of Chernoff-type concentration inequalities. Chernoff-type tail bounds on sums of independent random variables have pervasive applications in theoretical computer science. Schmidt et al. (SIAM J. Discrete Math. 1995) showed that these inequalities can be established for sums of random variables with only $O(\log(1/\delta))$-wise independence, for a tail probability of $\delta$. We show that their results are tight up to constant factors. These results rely on techniques from weighted approximation theory, which studies how well functions on the real line can be approximated by polynomials under various distributions. We believe that these techniques will have further applications in other areas of computer science.Comment: 22 page

Free-libre open source software as a public policy choice

Free Libre Open Source Software (FLOSS) is characterised by a specific programming and development paradigm. The availability and freedom of use of source code are at the core of this paradigm, and are the prerequisites for FLOSS features. Unfortunately, the fundamental role of code is often ignored among those who decide the software purchases for Canadian public agencies. Source code availability and the connected freedoms are often seen as unrelated and accidental aspects, and the only real advantage acknowledged, which is the absence of royalty fees, becomes paramount. In this paper we discuss some relevant legal issues and explain why public administrations should choose FLOSS for their technological infrastructure. We also present the results of a survey regarding the penetration and awareness of FLOSS usage into the Government of Canada. The data demonstrates that the Government of Canada shows no enforced policy regarding the implementation of a specific technological framework (which has legal, economic, business, and ethical repercussions) in their departments and agencies

A Little bijection for affine Stanley symmetric functions

David Little developed a combinatorial algorithm to study the Schur-positivity of Stanley symmetric functions and the Lascoux-Sch\"{u}tzenberger tree. We generalize this algorithm to affine Stanley symmetric functions.Comment: 10 page