2,043 research outputs found
European air quality maps 2005 including uncertainty analysis
The objective of this report is (a) the updating and refinement of European air quality maps based on annual statistics of the 2005 observational data reported by EEA Member countries in 2006, and (b) the further improvement of the interpolation methodologies. The paper presents the results achieved and an uncertainty analysis of the interpolated maps and builds upon earlier reports from Horalék et al. (2005; 2007)
Optimization of the gas flow in a GEM chamber and development of the GEM foil stretcher
The gas electron multiplier technology has been proven to tolerate rat e
larger than 50 MHz/cm2 without noticeable aging and to provide sub resolution
on working chambers up to 45 cm x 45 cm. A new gas electron multiplier-based
tracker is under development for the Hall A upgrade at Jefferson Lab. The
chambers of the tracker have been designed in a modular way: each chamber
consists of 3 adjacent gas electron multiplier modules, with an active area
of 40 cm x 50 cm each. We optimized the gas flow inside the gas electron
multiplier module volume, using the COMSOL physics simulator framework; the
COMSOL-based analysis includes the design of the inlet and outlet pipes and
the maximization of the uniformity of the gas flow. We have defined the
procedures for the assembling of the gas electron multiplier modules and
designed a mechanical system (TENDIGEM) that will be used to stretch the GEM
foils at the proper tension (few kg/cm); the TENDIGEM is based on the
original design developed at LNF
Analytical Tachyonic Lump Solutions in Open Superstring Field Theory
We construct a classical solution in the GSO(-) sector in the framework of a
Wess-Zumino-Witten-like open superstring field theory on a non-BPS D-brane. We
use an su(2) supercurrent, which is obtained by compactifying a direction to a
circle with the critical radius, in order to get analytical tachyonic lump
solutions to the equation of motion. By investigating the action expanded
around a solution we find that it represents a deformation from a non-BPS
D-brane to a D-brane-anti-D-brane system at the critical value of a parameter
which is contained in classical solutions. Although such a process was
discussed in terms of boundary conformal field theory before, our study is
based on open superstring field theory including interaction terms.Comment: 17 pages, references adde
Heritability estimates of the novel trait 'suppressed in ovo virus infection' in honey bees (Apis mellifera)
Honey bees are under pressure due to abnormal high colony death rates, especially during the winter. The infestation by the Varroa destructor mite and the viruses that this ectoparasite transmits are generally considered as the bees' most important biological threats. Almost all efforts to remedy this dual infection have so far focused on the control of the Varroa mite alone and not on the viruses it transmits. In the present study, the sanitary control of breeding queens was conducted on eggs taken from drone brood for 4 consecutive years (2015-2018). The screening was performed on the sideline of an ongoing breeding program, which allowed us to estimate the heritabilities of the virus status of the eggs. We used the term 'suppressed in ovo virus infection' (SOV) for this novel trait and found moderate heritabilities for the presence of several viruses simultaneously and for the presence of single viral species. Colonies that expressed the SOV trait seemed to be more resilient to virus infections as a whole with fewer and less severe Deformed wing virus infections in most developmental stages, especially in the male caste. The implementation of this novel trait into breeding programs is recommended
Multilinear Wavelets: A Statistical Shape Space for Human Faces
We present a statistical model for D human faces in varying expression,
which decomposes the surface of the face using a wavelet transform, and learns
many localized, decorrelated multilinear models on the resulting coefficients.
Using this model we are able to reconstruct faces from noisy and occluded D
face scans, and facial motion sequences. Accurate reconstruction of face shape
is important for applications such as tele-presence and gaming. The localized
and multi-scale nature of our model allows for recovery of fine-scale detail
while retaining robustness to severe noise and occlusion, and is
computationally efficient and scalable. We validate these properties
experimentally on challenging data in the form of static scans and motion
sequences. We show that in comparison to a global multilinear model, our model
better preserves fine detail and is computationally faster, while in comparison
to a localized PCA model, our model better handles variation in expression, is
faster, and allows us to fix identity parameters for a given subject.Comment: 10 pages, 7 figures; accepted to ECCV 201
A machine learning pipeline for discriminant pathways identification
Motivation: Identifying the molecular pathways more prone to disruption
during a pathological process is a key task in network medicine and, more in
general, in systems biology.
Results: In this work we propose a pipeline that couples a machine learning
solution for molecular profiling with a recent network comparison method. The
pipeline can identify changes occurring between specific sub-modules of
networks built in a case-control biomarker study, discriminating key groups of
genes whose interactions are modified by an underlying condition. The proposal
is independent from the classification algorithm used. Three applications on
genomewide data are presented regarding children susceptibility to air
pollution and two neurodegenerative diseases: Parkinson's and Alzheimer's.
Availability: Details about the software used for the experiments discussed
in this paper are provided in the Appendix
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