Analysis and improvement of the vector quantization in SELP (Stochastically Excited Linear Prediction)

The Stochastically Excited Linear Prediction (SELP) algorithm is described as a speech coding method employing a two-stage vector quantization. The first stage uses an adaptive codebook which efficiently encodes the periodicity of voiced speech, and the second stage uses a stochastic codebook to encode the remainder of the excitation signal. The adaptive codebook performs well when the pitch period of the speech signal is larger than the frame size. An extension is introduced, which increases its performance for the case that the frame size is longer than the pitch period. The performance of the stochastic stage, which improves with frame length, is shown to be best in those sections of the speech signal where a high level of short-term correlations is present. It can be concluded that the SELP algorithm performs best during voiced speech where the pitch period is longer than the frame length

Dynamic Soil-Foundation-Structure Interaction Analyses of Large Caissons

Large cellular reinforced concrete caissons exist as foundations of major long-span bridges across waterways in many parts of the country. This study was conducted to evaluate the important factors affecting the seismic response of large caissons. The paper presents the results of equivalent linear and non-linear analyses performed for a typical caisson idealized based on the cellular caisson at Pier W3 of the West San Francisco Bay Bridge subject to ground motion with a peak rock acceleration of 0.6 g. This caisson is 38.7 m (127 fi) long by 22.9 m (75 ft) wide submerged in about 32.6 m (107 ft) of water. It is embedded in 33.5 m (110 fi) of soil deposits and is founded on rock. Equivalent linear 3-D and 2-D analyses conducted in the direction of the short axis (longitudinal) were performed using a modified version of computer program SASSI. The results of these 3-D and 2-D analyses are similar. Non-linear analyses were performed for 2-D models using computer program FLAC. The results indicate that side gapping, base lifting, interface sliding, and soil yielding reduce the earth pressure, base bearing stress, caisson shear and bending moment, and caisson motions. However, the frequency characteristics of the responses appear to be relatively unaffected

Race/Ethnicity and Retention in Traumatic Brain Injury Outcomes Research: A Traumatic Brain Injury Model Systems National Database Study

Objective: To investigate the contribution of race/ethnicity to retention in traumatic brain injury (TBI) research at 1 to 2 years post-injury. Setting: Community. Participants: 5548 Whites, 1347 Blacks, and 790 Hispanics enrolled in the Traumatic Brain Injury Model Systems National Database with dates of injury between October 1, 2002 and March 31, 2013. Design: Retrospective database analysis. Main Measure: Retention, defined as completion of at least one question on the follow-up interview by the person with TBI or a proxy. Results: Retention rates 1-2 years post-TBI were significantly lower for Hispanic (85.2%) than for White (91.8%) or Black participants (90.5%) and depended significantly on history of problem drug or alcohol use. Other variables associated with low retention included older age, lower education, violent cause of injury, and discharge to an institution versus private residence. Conclusions: The findings emphasize the importance of investigating retention rates separately for Blacks and Hispanics rather than combining them or grouping either with other races or ethnicities. The results also suggest the need for implementing procedures to increase retention of Hispanics in longitudinal TBI researc

Proton Motive Force-Dependent Hoechst 33342 Transport by the ABC Transporter LmrA of Lactococcus lactis

The fluorescent compound Hoechst 33342 is a substrate for many multidrug resistance (MDR) transporters and is widely used to characterize their transport activity. We have constructed mutants of the adenosine triphosphate (ATP) binding cassette (ABC)-type MDR transporter LmrA of Lactococcus lactis that are defective in ATP hydrolysis. These mutants and wild-type LmrA exhibited an atypical behavior in the Hoechst 33342 transport assay. In membrane vesicles, Hoechst 33342 transport was shown to be independent of the ATPase activity of LmrA, and it was not inhibited by orthovanadate but sensitive to uncouplers that collapse the proton gradient and to N,N'-dicyclohexylcarbodiimide, an inhibitor of the F0F1-ATPase. In contrast, transport of Hoechst 33342 by the homologous, heterodimeric MDR transporter LmrCD showed a normal ATP dependence and was insensitive to uncouplers of the proton gradient. With intact cells, expression of LmrA resulted in an increased rate of Hoechst 33342 influx while LmrCD caused a decrease in the rate of Hoechst 33342 influx. Cellular toxicity assays using a triple knockout strain, i.e., L. lactis ΔlmrA ΔlmrCD, demonstrate that expression of LmrCD protects cells against the growth inhibitory effects of Hoechst 33342, while in the presence of LmrA, cells are more susceptible to Hoechst 33342. Our data demonstrate that the LmrA-mediated Hoechst 33342 transport in membrane vesicles is influenced by the transmembrane pH gradient due to a pH-dependent partitioning of Hoechst 33342 into the membrane.

The Pandora multi-algorithm approach to automated pattern recognition of cosmic-ray muon and neutrino events in the MicroBooNE detector.

The development and operation of liquid-argon time-projection chambers for neutrino physics has created a need for new approaches to pattern recognition in order to fully exploit the imaging capabilities offered by this technology. Whereas the human brain can excel at identifying features in the recorded events, it is a significant challenge to develop an automated, algorithmic solution. The Pandora Software Development Kit provides functionality to aid the design and implementation of pattern-recognition algorithms. It promotes the use of a multi-algorithm approach to pattern recognition, in which individual algorithms each address a specific task in a particular topology. Many tens of algorithms then carefully build up a picture of the event and, together, provide a robust automated pattern-recognition solution. This paper describes details of the chain of over one hundred Pandora algorithms and tools used to reconstruct cosmic-ray muon and neutrino events in the MicroBooNE detector. Metrics that assess the current pattern-recognition performance are presented for simulated MicroBooNE events, using a selection of final-state event topologies

Convolutional Neural Networks Applied to Neutrino Events in a Liquid Argon Time Projection Chamber

We present several studies of convolutional neural networks applied to data coming from the MicroBooNE detector, a liquid argon time projection chamber (LArTPC). The algorithms studied include the classification of single particle images, the localization of single particle and neutrino interactions in an image, and the detection of a simulated neutrino event overlaid with cosmic ray backgrounds taken from real detector data. These studies demonstrate the potential of convolutional neural networks for particle identification or event detection on simulated neutrino interactions. We also address technical issues that arise when applying this technique to data from a large LArTPC at or near ground level

Design and construction of the MicroBooNE Cosmic Ray Tagger system

The MicroBooNE detector utilizes a liquid argon time projection chamber (LArTPC) with an 85 t active mass to study neutrino interactions along the Booster Neutrino Beam (BNB) at Fermilab. With a deployment location near ground level, the detector records many cosmic muon tracks in each beam-related detector trigger that can be misidentified as signals of interest. To reduce these cosmogenic backgrounds, we have designed and constructed a TPC-external Cosmic Ray Tagger (CRT). This sub-system was developed by the Laboratory for High Energy Physics (LHEP), Albert Einstein center for fundamental physics, University of Bern. The system utilizes plastic scintillation modules to provide precise time and position information for TPC-traversing particles. Successful matching of TPC tracks and CRT data will allow us to reduce cosmogenic background and better characterize the light collection system and LArTPC data using cosmic muons. In this paper we describe the design and installation of the MicroBooNE CRT system and provide an overview of a series of tests done to verify the proper operation of the system and its components during installation, commissioning, and physics data-taking

The Pandora multi-algorithm approach to automated pattern recognition of cosmic-ray muon and neutrino events in the MicroBooNE detector

The development and operation of Liquid-Argon Time-Projection Chambers for neutrino physics has created a need for new approaches to pattern recognition in order to fully exploit the imaging capabilities offered by this technology. Whereas the human brain can excel at identifying features in the recorded events, it is a significant challenge to develop an automated, algorithmic solution. The Pandora Software Development Kit provides functionality to aid the design and implementation of pattern-recognition algorithms. It promotes the use of a multi-algorithm approach to pattern recognition, in which individual algorithms each address a specific task in a particular topology. Many tens of algorithms then carefully build up a picture of the event and, together, provide a robust automated pattern-recognition solution. This paper describes details of the chain of over one hundred Pandora algorithms and tools used to reconstruct cosmic-ray muon and neutrino events in the MicroBooNE detector. Metrics that assess the current pattern-recognition performance are presented for simulated MicroBooNE events, using a selection of final-state event topologies.Comment: Preprint to be submitted to The European Physical Journal

Determination of muon momentum in the MicroBooNE LArTPC using an improved model of multiple Coulomb scattering

We discuss a technique for measuring a charged particle's momentum by means of multiple Coulomb scattering (MCS) in the MicroBooNE liquid argon time projection chamber (LArTPC). This method does not require the full particle ionization track to be contained inside of the detector volume as other track momentum reconstruction methods do (range-based momentum reconstruction and calorimetric momentum reconstruction). We motivate use of this technique, describe a tuning of the underlying phenomenological formula, quantify its performance on fully contained beam-neutrino-induced muon tracks both in simulation and in data, and quantify its performance on exiting muon tracks in simulation. Using simulation, we have shown that the standard Highland formula should be re-tuned specifically for scattering in liquid argon, which significantly improves the bias and resolution of the momentum measurement. With the tuned formula, we find agreement between data and simulation for contained tracks, with a small bias in the momentum reconstruction and with resolutions that vary as a function of track length, improving from about 10% for the shortest (one meter long) tracks to 5% for longer (several meter) tracks. For simulated exiting muons with at least one meter of track contained, we find a similarly small bias, and a resolution which is less than 15% for muons with momentum below 2 GeV/c. Above 2 GeV/c, results are given as a first estimate of the MCS momentum measurement capabilities of MicroBooNE for high momentum exiting tracks

Noise Characterization and Filtering in the MicroBooNE Liquid Argon TPC

The low-noise operation of readout electronics in a liquid argon time projection chamber (LArTPC) is critical to properly extract the distribution of ionization charge deposited on the wire planes of the TPC, especially for the induction planes. This paper describes the characteristics and mitigation of the observed noise in the MicroBooNE detector. The MicroBooNE's single-phase LArTPC comprises two induction planes and one collection sense wire plane with a total of 8256 wires. Current induced on each TPC wire is amplified and shaped by custom low-power, low-noise ASICs immersed in the liquid argon. The digitization of the signal waveform occurs outside the cryostat. Using data from the first year of MicroBooNE operations, several excess noise sources in the TPC were identified and mitigated. The residual equivalent noise charge (ENC) after noise filtering varies with wire length and is found to be below 400 electrons for the longest wires (4.7 m). The response is consistent with the cold electronics design expectations and is found to be stable with time and uniform over the functioning channels. This noise level is significantly lower than previous experiments utilizing warm front-end electronics.Comment: 36 pages, 20 figure