56 research outputs found
First Observation of Coherent Production in Neutrino Nucleus Interactions with 2 GeV
The MiniBooNE experiment at Fermilab has amassed the largest sample to date
of s produced in neutral current (NC) neutrino-nucleus interactions at
low energy. This paper reports a measurement of the momentum distribution of
s produced in mineral oil (CH) and the first observation of coherent
production below 2 GeV. In the forward direction, the yield of events
observed above the expectation for resonant production is attributed primarily
to coherent production off carbon, but may also include a small contribution
from diffractive production on hydrogen. Integrated over the MiniBooNE neutrino
flux, the sum of the NC coherent and diffractive modes is found to be (19.5
1.1 (stat) 2.5 (sys))% of all exclusive NC production at
MiniBooNE. These measurements are of immediate utility because they quantify an
important background to MiniBooNE's search for
oscillations.Comment: Submitted to Phys. Lett.
A connectome of the adult drosophila central brain
The neural circuits responsible for behavior remain largely unknown. Previous efforts have reconstructed the complete circuits of small animals, with hundreds of neurons, and selected circuits for larger animals. Here we (the FlyEM project at Janelia and collaborators at Google) summarize new methods and present the complete circuitry of a large fraction of the brain of a much more complex animal, the fruit fly Drosophila melanogaster. Improved methods include new procedures to prepare, image, align, segment, find synapses, and proofread such large data sets; new methods that define cell types based on connectivity in addition to morphology; and new methods to simplify access to a large and evolving data set. From the resulting data we derive a better definition of computational compartments and their connections; an exhaustive atlas of cell examples and types, many of them novel; detailed circuits for most of the central brain; and exploration of the statistics and structure of different brain compartments, and the brain as a whole. We make the data public, with a web site and resources specifically designed to make it easy to explore, for all levels of expertise from the expert to the merely curious. The public availability of these data, and the simplified means to access it, dramatically reduces the effort needed to answer typical circuit questions, such as the identity of upstream and downstream neural partners, the circuitry of brain regions, and to link the neurons defined by our analysis with genetic reagents that can be used to study their functions. Note: In the next few weeks, we will release a series of papers with more involved discussions. One paper will detail the hemibrain reconstruction with more extensive analysis and interpretation made possible by this dense connectome. Another paper will explore the central complex, a brain region involved in navigation, motor control, and sleep. A final paper will present insights from the mushroom body, a center of multimodal associative learning in the fly brain
A connectome and analysis of the adult Drosophila central brain
The neural circuits responsible for animal behavior remain largely unknown. We summarize new methods and present the circuitry of a large fraction of the brain of the fruit fly Drosophila melanogaster. Improved methods include new procedures to prepare, image, align, segment, find synapses in, and proofread such large data sets. We define cell types, refine computational compartments, and provide an exhaustive atlas of cell examples and types, many of them novel. We provide detailed circuits consisting of neurons and their chemical synapses for most of the central brain. We make the data public and simplify access, reducing the effort needed to answer circuit questions, and provide procedures linking the neurons defined by our analysis with genetic reagents. Biologically, we examine distributions of connection strengths, neural motifs on different scales, electrical consequences of compartmentalization, and evidence that maximizing packing density is an important criterion in the evolution of the fly’s brain
Developing a predictive modelling capacity for a climate change-vulnerable blanket bog habitat: Assessing 1961-1990 baseline relationships
Aim: Understanding the spatial distribution of high priority habitats and
developing predictive models using climate and environmental variables to
replicate these distributions are desirable conservation goals. The aim of this
study was to model and elucidate the contributions of climate and topography to
the distribution of a priority blanket bog habitat in Ireland, and to examine how
this might inform the development of a climate change predictive capacity for
peat-lands in Ireland.
Methods: Ten climatic and two topographic variables were recorded for grid
cells with a spatial resolution of 1010 km, covering 87% of the mainland
land surface of Ireland. Presence-absence data were matched to these variables
and generalised linear models (GLMs) fitted to identify the main climatic and
terrain predictor variables for occurrence of the habitat. Candidate predictor
variables were screened for collinearity, and the accuracy of the final fitted GLM
was evaluated using fourfold cross-validation based on the area under the curve
(AUC) derived from a receiver operating characteristic (ROC) plot. The GLM
predicted habitat occurrence probability maps were mapped against the actual
distributions using GIS techniques.
Results: Despite the apparent parsimony of the initial GLM using only climatic
variables, further testing indicated collinearity among temperature and precipitation
variables for example. Subsequent elimination of the collinear variables and
inclusion of elevation data produced an excellent performance based on the AUC
scores of the final GLM. Mean annual temperature and total mean annual
precipitation in combination with elevation range were the most powerful
explanatory variable group among those explored for the presence of blanket
bog habitat.
Main conclusions: The results confirm that this habitat distribution in general
can be modelled well using the non-collinear climatic and terrain variables tested
at the grid resolution used. Mapping the GLM-predicted distribution to the
observed distribution produced useful results in replicating the projected
occurrence of the habitat distribution over an extensive area. The methods
developed will usefully inform future climate change predictive modelling for
Irelan
Test of Lorentz and CPT violation with Short Baseline Neutrino Oscillation Excesses
The sidereal time dependence of MiniBooNE electron neutrino and anti-electron
neutrino appearance data are analyzed to search for evidence of Lorentz and CPT
violation. An unbinned Kolmogorov-Smirnov test shows both the electron neutrino
and anti-electron neutrino appearance data are compatible with the null
sidereal variation hypothesis to more than 5%. Using an unbinned likelihood fit
with a Lorentz-violating oscillation model derived from the Standard Model
Extension (SME) to describe any excess events over background, we find that the
electron neutrino appearance data prefer a sidereal time-independent solution,
and the anti-electron neutrino appearance data slightly prefer a sidereal
time-dependent solution. Limits of order 10E-20 GeV are placed on combinations
of SME coefficients. These limits give the best limits on certain SME
coefficients for muon neutrino to electron neutrino and anti-muon neutrino to
anti-electron neutrino oscillations. The fit values and limits of combinations
of SME coefficients are provided.Comment: 14 pages, 3 figures, and 2 tables, submitted to Physics Letters
A connectome and analysis of the adult Drosophila central brain
The neural circuits responsible for animal behavior remain largely unknown. We summarize new methods and present the circuitry of a large fraction of the brain of the fruit fly Drosophila melanogaster. Improved methods include new procedures to prepare, image, align, segment, find synapses in, and proofread such large data sets. We define cell types, refine computational compartments, and provide an exhaustive atlas of cell examples and types, many of them novel. We provide detailed circuits consisting of neurons and their chemical synapses for most of the central brain. We make the data public and simplify access, reducing the effort needed to answer circuit questions, and provide procedures linking the neurons defined by our analysis with genetic reagents. Biologically, we examine distributions of connection strengths, neural motifs on different scales, electrical consequences of compartmentalization, and evidence that maximizing packing density is an important criterion in the evolution of the fly's brain
Uncovering the heterogeneity and temporal complexity of neurodegenerative diseases with Subtype and Stage Inference
The heterogeneity of neurodegenerative diseases is a key confound to disease understanding and treatment development, as study cohorts typically include multiple phenotypes on distinct disease trajectories. Here we introduce a machine-learning technique\u2014Subtype and Stage Inference (SuStaIn)\u2014able to uncover data-driven disease phenotypes with distinct temporal progression patterns, from widely available cross-sectional patient studies. Results from imaging studies in two neurodegenerative diseases reveal subgroups and their distinct trajectories of regional neurodegeneration. In genetic frontotemporal dementia, SuStaIn identifies genotypes from imaging alone, validating its ability to identify subtypes; further the technique reveals within-genotype heterogeneity. In Alzheimer\u2019s disease, SuStaIn uncovers three subtypes, uniquely characterising their temporal complexity. SuStaIn provides fine-grained patient stratification, which substantially enhances the ability to predict conversion between diagnostic categories over standard models that ignore subtype (p = 7.18
7 10 124 ) or temporal stage (p = 3.96
7 10 125 ). SuStaIn offers new promise for enabling disease subtype discovery and precision medicine
Factors Associated with Revision Surgery after Internal Fixation of Hip Fractures
Background: Femoral neck fractures are associated with high rates of revision surgery after management with internal fixation. Using data from the Fixation using Alternative Implants for the Treatment of Hip fractures (FAITH) trial evaluating methods of internal fixation in patients with femoral neck fractures, we investigated associations between baseline and surgical factors and the need for revision surgery to promote healing, relieve pain, treat infection or improve function over 24 months postsurgery. Additionally, we investigated factors associated with (1) hardware removal and (2) implant exchange from cancellous screws (CS) or sliding hip screw (SHS) to total hip arthroplasty, hemiarthroplasty, or another internal fixation device. Methods: We identified 15 potential factors a priori that may be associated with revision surgery, 7 with hardware removal, and 14 with implant exchange. We used multivariable Cox proportional hazards analyses in our investigation. Results: Factors associated with increased risk of revision surgery included: female sex, [hazard ratio (HR) 1.79, 95% confidence interval (CI) 1.25-2.50; P = 0.001], higher body mass index (fo
Proof of Stimulated Emission in Silicon-Germanium
We have investigated a hexagonal Silicon-Germanium NW on top of a microstadium resonator using time resolved photoluminescence. Clear indications of fast stimulated emission from hex-SiGe are observed, showing that we approach lasing
- …