353 research outputs found
Desarrollo de un servicio experimental de teledetección en los riegos del Porma (León) para el cálculo ajustado de necesidades hídricas y mejora en la gestión del regadío
El proyecto de innovación tecnológica OPTIREG Eficiencia Hídrica, impulsado por el
Grupo Tragsa, tiene entre sus objetivos principales introducir el uso de la teledetección,
como tecnología de apoyo a la gestión hídrica. Para ello se está desarrollando un servicio
web gis experimental que servirá de repositorio único de imágenes y de sus productos
derivados y que facilitará, tanto a los regantes, como a los gestores del riego, el seguimiento
de los cultivos y de sus necesidades hídricas.
Diversos estudios científicos han demostrado la buena relación lineal existente entre el
índice de vegetación normalizado (NDVI), derivado de las imágenes de satélite, y el
coeficiente de cultivo, Kc (Torres, 2010), utilizado en el cálculo de la evapotranspiración y las
necesidades hídricas. Una primera evaluación de los resultados obtenidos en la campaña
2015 para los principales cultivos en regadío en la zona de estudio del Porma (León), indica
que el Kc calculado a partir del NDVI, se ajusta mejor que el de FAO. Por ello, se considera
un sistema muy válido como referencia para ajustar no sólo la cantidad de agua, sino
también para determinar el momento más adecuado de riego, que redundará en una mayor
eficiencia hídrica
Huntington's disease-specific mis-splicing unveils key effector genes and altered splicing factors
Correction of mis-splicing events is a growing therapeutic approach for neurological diseases such as spinal muscular atrophy or neuronal ceroid lipofuscinosis 7, which are caused by splicing-affecting mutations. Mis-spliced effector genes that do not harbour mutations are also good candidate therapeutic targets in diseases with more complex aetiologies such as cancer, autism, muscular dystrophies or neurodegenerative diseases. Next-generation RNA sequencing (RNA-seq) has boosted investigation of global mis-splicing in diseased tissue to identify such key pathogenic mis-spliced genes. Nevertheless, while analysis of tumour or dystrophic muscle biopsies can be informative on early stage pathogenic mis-splicing, for neurodegenerative diseases, these analyses are intrinsically hampered by neuronal loss and neuroinflammation in post-mortem brains. To infer splicing alterations relevant to Huntington's disease pathogenesis, here we performed intersect-RNA-seq analyses of human post-mortem striatal tissue and of an early symptomatic mouse model in which neuronal loss and gliosis are not yet present. Together with a human/mouse parallel motif scan analysis, this approach allowed us to identify the shared mis-splicing signature triggered by the Huntington's disease-causing mutation in both species and to infer upstream deregulated splicing factors. Moreover, we identified a plethora of downstream neurodegeneration-linked mis-spliced effector genes that-together with the deregulated splicing factors-become new possible therapeutic targets. In summary, here we report pathogenic global mis-splicing in Huntington's disease striatum captured by our new intersect-RNA-seq approach that can be readily applied to other neurodegenerative diseases for which bona fide animal models are available.Extremadura Research Centre for Advanced Technologies (CETA-CIEMAT), funded by the European Regional Development Fund (ERDF). CETA-CIEMAT belongs to CIEMAT and the Government of Spai
Exploring the chemoselectivity towards cysteine arylation by cyclometalated Au(III) compounds: new mechanistic insights
To gain more insight into the factors controlling the efficient cysteine arylation by cyclometalated Au(III) complexes, the reaction between selected gold compounds and different peptides was investigated by high‐resolution liquid chromatography electrospray ionization mass spectrometry (HR‐LC‐ESI‐MS). The deducted mechanisms of C–S cross‐coupling, also supported by density functional theory (DFT) and quantum mechanics/molecular mechanics (QM/MM) calculations, evidenced the key role of secondary peptidic gold binding sites in favouring the process of reductive elimination
Sporadic Creutzfeldt-Jakob disease VM1: phenotypic and molecular characterization of a novel subtype of human prion disease
The methionine (M)-valine (V) polymorphic codon 129 of the prion protein gene (PRNP) plays a central role in both susceptibility and phenotypic expression of sporadic Creutzfeldt-Jakob diseases (sCJD). Experimental transmissions of sCJD in humanized transgenic mice led to the isolation of five prion strains, named M1, M2C, M2T, V2, and V1, based on two major conformations of the pathological prion protein (PrPSc, type 1 and type 2), and the codon 129 genotype determining susceptibility and propagation efficiency. While the most frequent sCJD strains have been described in codon 129 homozygosis (MM1, MM2C, VV2) and heterozygosis (MV1, MV2K, and MV2C), the V1 strain has only been found in patients carrying VV. We identified six sCJD cases, 4 in Catalonia and 2 in Italy, carrying MV at PRNP codon 129 in combination with PrPSc type 1 and a new clinical and neuropathological profile reminiscent of the VV1 sCJD subtype rather than typical MM1/MV1. All patients had a relatively long duration (mean of 20.5 vs. 3.5 months of MM1/MV1 patients) and lacked electroencephalographic periodic sharp-wave complexes at diagnosis. Distinctive histopathological features included the spongiform change with vacuoles of larger size than those seen in sCJD MM1/MV1, the lesion profile with prominent cortical and striatal involvement, and the pattern of PrPSc deposition characterized by a dissociation between florid spongiform change and mild synaptic deposits associated with coarse, patch-like deposits in the cerebellar molecular layer. Western blot analysis of brain homogenates revealed a PrPSc type 1 profile with physicochemical properties reminiscent of the type 1 protein linked to the VV1 sCJD subtype. In summary, we have identified a new subtype of sCJD with distinctive clinicopathological features significantly overlapping with those of the VV1 subtype, possibly representing the missing evidence of V1 sCJD strain propagation in the 129MV host genotype
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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
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