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S. Dennis

Publications and source records attributed to S. Dennis.

4 recordsLinked to original sources

Underwater dual-magnification imaging for automated lake plankton monitoring

We present an approach for automated in-situ monitoring of phytoplankton and zooplankton communities based on a dual magnification dark-field imaging microscope/camera. We describe the Dual Scripps Plankton Camera (DSPC) system and associated image processing, and assess its capabilities in detecting and characterizing plankton species of different size and taxonomic categories, and in measuring their abundances in both laboratory and field applications. In the laboratory, body size and abundance estimates by the DSPC significantly and robustly scale with the same measurements derived by traditional microscopy. In the field, a DSPC installed permanently at 3 m depth in Lake Greifensee (Switzerland), delivered images of plankton individuals, colonies, and heterospecific aggregates without disrupting natural arrangements of interacting organisms, their microenvironment or their behavior at hourly timescales. The DSPC was able to track the dynamics of taxa in the size range between ~10 $μ$m to ~ 1 cm, covering virtually all the components of the planktonic food web (including parasites and potentially toxic cyanobacteria). Comparing data from the field-deployed DSPC to traditional sampling and microscopy revealed a general overall agreement in estimates of plankton diversity and abundances, despite imaging limitations in detecting small phytoplankton species and rare and large zooplankton taxa (e.g. carnivorous zooplankton). The most significant disagreements between traditional methods and the DSPC resided in the measurements of community properties of zooplankton, organisms that are heterogeneously distributed spatially and temporally, and whose demography appeared to be better captured by automated imaging. Time series collected by the DSPC depicted ecological succession patterns, algal bloom dynamics and circadian fluctuations with a temporal frequency and morphological [continues...]

q-bio.PE

A Convolutional Neural Network for Multiple Particle Identification in the MicroBooNE Liquid Argon Time Projection Chamber

We present the multiple particle identification (MPID) network, a convolutional neural network (CNN) for multiple object classification, developed by MicroBooNE. MPID provides the probabilities of $e^-$, $γ$, $μ^-$, $π^\pm$, and protons in a single liquid argon time projection chamber (LArTPC) readout plane. The network extends the single particle identification network previously developed by MicroBooNE. MPID takes as input an image either cropped around a reconstructed interaction vertex or containing only activity connected to a reconstructed vertex, therefore relieving the tool from inefficiencies in vertex finding and particle clustering. The network serves as an important component in MicroBooNE's deep learning based $ν_e$ search analysis. In this paper, we present the network's design, training, and performance on simulation and data from the MicroBooNE detector.

hep-ex

GENIE Production Release 2.10.0

GENIE is a neutrino Monte Carlo event generator that simulates the primary interaction of a neutrino with a nuclear target, along with the subsequent propagation of the reaction products through the nuclear medium. It additionally contains libraries for fully-featured detector geometries and for managing various types of neutrino flux. This note details recent updates to GENIE, in particular changes introduced into the newest production release, version 2.10.0.

hep-ph

Evidence of Electron Neutrino Appearance in a Muon Neutrino Beam

The T2K collaboration: reports evidence for electron neutrino appearance at the atmospheric mass splitting, |Δm_{32}^2|=2.4x10^{-3} eV^2. An excess of electron neutrino interactions over background is observed from a muon neutrino beam with a peak energy of 0.6 GeV at the Super-Kamiokande (SK) detector 295 km from the beam's origin. Signal and background predictions are constrained by data from near detectors located 280 m from the neutrino production target. We observe 11 electron neutrino candidate events at the SK detector when a background of 3.3\pm0.4(syst.) events is expected. The background-only hypothesis is rejected with a p-value of 0.0009 (3.1σ), and a fit assuming ν_μ->ν_e oscillations with sin^2(2θ_{23})=1, δ_{CP}=0 and |Δm_{32}^2|=2.4x10^{-3} eV^2 yields sin^2(2θ_{13})=0.088^{+0.049}_{-0.039}(stat.+syst.).

hep-ex