512 research outputs found
Monitoring and thermal performance evaluation of two building envelope solutions in an apartment building
A bio-based multi-layer building envelope assembly has been developed for its integration in newly built and retrofitted buildings. Forest-based materials and biocomposite profiles are used as an alternative to fossil-based insulants and metallic framing, providing a well-insulated and low-thermal-bridge technical solution. The wall assembly has been installed as the external envelope of one apartment of a housing block in Donostia-San Sebastián (Basque Country, Spain). A comparative study has been performed for the bio-based wall and the reference wall of the building. Their in-situ thermal resistance has been obtained by means of three different methods: (1) the steady-state average method, (2) a semi-dynamic method from heat balance at the internal surface, and (3) a dynamic multiple regression method. Reasonably consistent results have been obtained with the three methods: a discussion is provided on the influence of measuring periods and boundary conditions. Outputs from this experimental campaign are valuable as a counterpoint to desktop studies and tests under controlled laboratory conditions. Learnings and outputs from the present study should contribute to a better understanding of the in-situ performance of building envelope assemblies and their assessment methods
Prognostic value of proadrenomedullin in severe sepsis and septic shock patients with community-acquired pneumonia
Synthesis and antiacetylcholinesterase activity of new D-glyceraldehyde heterocyclic derivatives
We report herein the convenient procedures for the syntheses of different heterocyclic compounds from 2,3-O-isopropylidene-D-glyceraldehyde using intramolecular cyclization, 1,3-dipolar cycloaddition or bimolecular coupling reactions. The products were characterized by ¹H and 13C NMR spectroscopy and elemental analysis. The new heterocycles and their derivatives were evaluated as inhibitors of acetylcholinesterase enzyme
A global analysis of Spitzer and new HARPS data confirms the loneliness and metal-richness of GJ 436 b
Context. GJ 436b is one of the few transiting warm Neptunes for which a
detailed characterisation of the atmosphere is possible, whereas its
non-negligible orbital eccentricity calls for further investigation.
Independent analyses of several individual datasets obtained with Spitzer have
led to contradicting results attributed to the different techniques used to
treat the instrumental effects. Aims. We aim at investigating these previous
controversial results and developing our knowledge of the system based on the
full Spitzer photometry dataset combined with new Doppler measurements obtained
with the HARPS spectrograph. We also want to search for additional planets.
Methods. We optimise aperture photometry techniques and the photometric
deconvolution algorithm DECPHOT to improve the data reduction of the Spitzer
photometry spanning wavelengths from 3-24 {\mu}m. Adding the high precision
HARPS radial velocity data, we undertake a Bayesian global analysis of the
system considering both instrumental and stellar effects on the flux variation.
Results. We present a refined radius estimate of RP=4.10 +/- 0.16 R_Earth, mass
MP=25.4 +/- 2.1 M_Earth and eccentricity e= 0.162 +/- 0.004 for GJ 436b. Our
measured transit depths remain constant in time and wavelength, in disagreement
with the results of previous studies. In addition, we find that the
post-occultation flare-like structure at 3.6 {\mu}m that led to divergent
results on the occultation depth measurement is spurious. We obtain occultation
depths at 3.6, 5.8, and 8.0 {\mu}m that are shallower than in previous works,
in particular at 3.6 {\mu}m. However, these depths still appear consistent with
a metal-rich atmosphere depleted in methane and enhanced in CO/CO2, although
perhaps less than previously thought. We find no evidence for a potential
planetary companion, stellar activity, nor for a stellar spin-orbit
misalignment. [ABRIDGED]Comment: 25 pages, 26 figures, 8 tables, accepted for publication in A&
Hot Exoplanet Atmospheres Resolved with Transit Spectroscopy (HEARTS) I. Detection of hot neutral sodium at high altitudes on WASP-49b
High-resolution optical spectroscopy during the transit of HD 189733b, a
prototypical hot Jupiter, allowed the resolution of the Na I D sodium lines in
the planet, giving access to the extreme conditions of the planet upper
atmosphere. We have undertaken HEARTS, a spectroscopic survey of exoplanet
upper atmospheres, to perform a comparative study of hot gas giants and
determine how stellar irradiation affect them. Here, we report on the first
HEARTS observations of the hot Saturn-mass planet WASP-49b. We observed the
planet with the HARPS high-resolution spectrograph at ESO 3.6m telescope. We
collected 126 spectra of WASP-49, covering three transits of WASP-49b. We
analyzed and modeled the planet transit spectrum, while paying particular
attention to the treatment of potentially spurious signals of stellar origin.
We spectrally resolve the Na I D lines in the planet atmosphere and show that
these signatures are unlikely to arise from stellar contamination. The large
contrasts of (D) and (D) require the
presence of hot neutral sodium ( K) at high altitudes
(1.5 planet radius or 45,000 km). From estimating the cloudiness
index of WASP-49b, we determine its atmosphere to be cloud free at the
altitudes probed by the sodium lines. WASP-49b is close to the border of the
evaporation desert and exhibits an enhanced thermospheric signature with
respect to a farther-away planet such as HD 189733b.Comment: Accepted for publication in A&A. 14 page
On merging the fields of neural networks and adaptive data structures to yield new pattern recognition methodologies
The aim of this talk is to explain a pioneering exploratory research endeavour that attempts to merge two completely different fields in Computer Science so as to yield very fascinating results. These are the well-established fields of Neural Networks (NNs) and Adaptive Data Structures (ADS) respectively. The field of NNs deals with the training and learning capabilities of a large number of neurons, each possessing minimal computational properties. On the other hand, the field of ADS concerns designing, implementing and analyzing data structures which adaptively change with time so as to optimize some access criteria. In this talk, we shall demonstrate how these fields can be merged, so that the neural elements are themselves linked together using a data structure. This structure can be a singly-linked or doubly-linked list, or even a Binary Search Tree (BST). While the results themselves are quite generic, in particular, we shall, as a prima facie case, present the results in which a Self-Organizing Map (SOM) with an underlying BST structure can be adaptively re-structured using conditional rotations. These rotations on the nodes of the tree are local and are performed in constant time, guaranteeing a decrease in the Weighted Path Length of the entire tree. As a result, the algorithm, referred to as the Tree-based Topology-Oriented SOM with Conditional Rotations (TTO-CONROT), converges in such a manner that the neurons are ultimately placed in the input space so as to represent its stochastic distribution. Besides, the neighborhood properties of the neurons suit the best BST that represents the data
Characterization of the K2-18 multi-planetary system with HARPS: A habitable zone super-Earth and discovery of a second, warm super-Earth on a non-coplanar orbit
The bright M dwarf K2-18 at 34 pc is known to host a transiting
super-Earth-sized planet orbiting within the star's habitable zone; K2-18b.
Given the superlative nature of this system for studying an exoplanetary
atmosphere receiving similar levels of insolation as the Earth, we aim to
characterize the planet's mass which is required to interpret atmospheric
properties and infer the planet's bulk composition. We obtain precision radial
velocity measurements with the HARPS spectrograph and couple those measurements
with the K2 photometry to jointly model the observed radial velocity variation
with planetary signals and a radial velocity jitter model based on Gaussian
process regression. We measure the mass of K2-18b to be
M with a bulk density of g/cm which may correspond
to a predominantly rocky planet with a significant gaseous envelope or an ocean
planet with a water mass fraction %. We also find strong evidence
for a second, warm super-Earth K2-18c at days with a semi-major axis
2.4 times smaller than the transiting K2-18b. After re-analyzing the available
light curves of K2-18 we conclude that K2-18c is not detected in transit and
therefore likely has an orbit that is non-coplanar with K2-18b. A suite of
dynamical integrations with varying simulated orbital eccentricities of the two
planets are used to further constrain each planet's eccentricity posterior from
which we measure and at 99% confidence. The discovery
of the inner planet K2-18c further emphasizes the prevalence of multi-planet
systems around M dwarfs. The characterization of the density of K2-18b reveals
that the planet likely has a thick gaseous envelope which along with its
proximity to the Solar system makes the K2-18 planetary system an interesting
target for the atmospheric study of an exoplanet receiving Earth-like
insolation.Comment: 13 pages, 8 figures including 4 interactive figures best viewed in
Adobe Acrobat. Submitted to Astronomy & Astrophysics. Comments welcom
Semi-supervised classification using tree-based self-organizing maps
This paper presents a classifier which uses a tree-based Neural Network (NN), and uses both, unlabeled and labeled instances. First, we learn the structure of the data distribution in an unsupervised manner. After convergence, and once labeled data become available, our strategy tags each of the clusters according to the evidence provided by the instances. Unlike other neighborhood-based schemes, our classifier uses only a small set of representatives whose cardinality can be much smaller than that of the input set. Our experiments show that, on average, the accuracy of such classifier is reasonably comparable to those obtained by some of the state-of-the-art classification schemes that only use labeled instances during the training phase. The experiments also show that improved levels of accuracy can be obtained by imposing trees with a larger number of nodes
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