1,458 research outputs found
A comparative study of the estimators for the demand of engineering courses in Portugal
For the purpose of modeling the demand of Engineering Courses in Portugal we analyzed the possible regression models for panel count data models by establishing a comparison between the estimators obtained and then finding the most appropriate ones for our dataset. A precise quantification of the demand for each academic program is facilitated by the rules of access to higher education, in National Contest for Access and Admission to Higher Education, where candidates must list up to six preferences of institution and program. The data used in this paper covers the results of the national contest from 1997 to 2015 provided by the Portuguese Ministry of Education and Science. Multivariate methodologies were performed in order to allow a better understanding of the students’ allocation behavior. The results seem to indicate that the negative binomial estimates fit better the dataset analyzed.A. Manuela Gonc¸alves and Raquel Oliveira were supported by the Research
Centre of Mathematics of the University of Minho with the Portuguese Funds from the ”FCT Fundac¸ao para a Ci ˜ encia e a Tecnologia”, through the Project PEstOE/MAT/UI0013/2014. Rosa ˆ
M. Vasconcelos was supported by the Foundation through ”FCT - Fundac¸ao para a Ci ˜ encia e Tec- ˆ
nologia”, within the Project UID/MAT/00013/2013, by FEDER funds through the Competitivity
Factors Operational Programme - COMPET and by national funds through FCT within the scope
of the project POCI-01-0145-FEDER-007136
Deep Convolutional Neural Networks for Breast Cancer Histology Image Analysis
Breast cancer is one of the main causes of cancer death worldwide. Early
diagnostics significantly increases the chances of correct treatment and
survival, but this process is tedious and often leads to a disagreement between
pathologists. Computer-aided diagnosis systems showed potential for improving
the diagnostic accuracy. In this work, we develop the computational approach
based on deep convolution neural networks for breast cancer histology image
classification. Hematoxylin and eosin stained breast histology microscopy image
dataset is provided as a part of the ICIAR 2018 Grand Challenge on Breast
Cancer Histology Images. Our approach utilizes several deep neural network
architectures and gradient boosted trees classifier. For 4-class classification
task, we report 87.2% accuracy. For 2-class classification task to detect
carcinomas we report 93.8% accuracy, AUC 97.3%, and sensitivity/specificity
96.5/88.0% at the high-sensitivity operating point. To our knowledge, this
approach outperforms other common methods in automated histopathological image
classification. The source code for our approach is made publicly available at
https://github.com/alexander-rakhlin/ICIAR2018Comment: 8 pages, 4 figure
Wideband THz time domain spectroscopy based on optical rectification and electro-optic sampling
We present an analytical model describing the full electromagnetic propagation in a THz time-domain spectroscopy (THz-TDS) system, from the THz pulses via Optical Rectification to the detection via Electro Optic-Sampling. While several investigations deal singularly with the many elements that constitute a THz-TDS, in our work we pay particular attention to the modelling of the time-frequency behaviour of all the stages which compose the experimental set-up. Therefore, our model considers the following main aspects: (i) pump beam focusing into the generation crystal; (ii) phase-matching inside both the generation and detection crystals; (iii) chromatic dispersion and absorption inside the crystals; (iv) Fabry-Perot effect; (v) diffraction outside, i.e. along the propagation, (vi) focalization and overlapping between THz and probe beams, (vii) electro-optic sampling. In order to validate our model, we report on the comparison between the simulations and the experimental data obtained from the same set-up, showing their good agreement
Network Physiology reveals relations between network topology and physiological function
The human organism is an integrated network where complex physiologic
systems, each with its own regulatory mechanisms, continuously interact, and
where failure of one system can trigger a breakdown of the entire network.
Identifying and quantifying dynamical networks of diverse systems with
different types of interactions is a challenge. Here, we develop a framework to
probe interactions among diverse systems, and we identify a physiologic
network. We find that each physiologic state is characterized by a specific
network structure, demonstrating a robust interplay between network topology
and function. Across physiologic states the network undergoes topological
transitions associated with fast reorganization of physiologic interactions on
time scales of a few minutes, indicating high network flexibility in response
to perturbations. The proposed system-wide integrative approach may facilitate
the development of a new field, Network Physiology.Comment: 12 pages, 9 figure
d=3 Bosonic Vector Models Coupled to Chern-Simons Gauge Theories
We study three dimensional O(N)_k and U(N)_k Chern-Simons theories coupled to
a scalar field in the fundamental representation, in the large N limit. For
infinite k this is just the singlet sector of the O(N) (U(N)) vector model,
which is conjectured to be dual to Vasiliev's higher spin gravity theory on
AdS_4. For large k and N we obtain a parity-breaking deformation of this
theory, controlled by the 't Hooft coupling lambda = 4 \pi N / k. For infinite
N we argue (and show explicitly at two-loop order) that the theories with
finite lambda are conformally invariant, and also have an exactly marginal
(\phi^2)^3 deformation.
For large but finite N and small 't Hooft coupling lambda, we show that there
is still a line of fixed points parameterized by the 't Hooft coupling lambda.
We show that, at infinite N, the interacting non-parity-invariant theory with
finite lambda has the same spectrum of primary operators as the free theory,
consisting of an infinite tower of conserved higher-spin currents and a scalar
operator with scaling dimension \Delta=1; however, the correlation functions of
these operators do depend on lambda. Our results suggest that there should
exist a family of higher spin gravity theories, parameterized by lambda, and
continuously connected to Vasiliev's theory. For finite N the higher spin
currents are not conserved.Comment: 34 pages, 29 figures. v2: added reference
Pre-cooling for endurance exercise performance in the heat: a systematic review.
PMCID: PMC3568721The electronic version of this article is the complete one and can be found online at: http://www.biomedcentral.com/1741-7015/10/166.
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.Endurance exercise capacity diminishes under hot environmental conditions. Time to exhaustion can be increased by lowering body temperature prior to exercise (pre-cooling). This systematic literature review synthesizes the current findings of the effects of pre-cooling on endurance exercise performance, providing guidance for clinical practice and further research
Molecular mechanisms of drug resistance in natural Leishmania populations vary with genetic background
The evolution of drug-resistance in pathogens is a major global health threat. Elucidating the molecular basis of pathogen drug-resistance has been the focus of many studies but rarely is it known whether a drug-resistance mechanism identified is universal for the studied pathogen; it has seldom been clarified whether drug-resistance mechanisms vary with the pathogen's genotype. Nevertheless this is of critical importance in gaining an understanding of the complexity of this global threat and in underpinning epidemiological surveillance of pathogen drug resistance in the field. This study aimed to assess the molecular and phenotypic heterogeneity that emerges in natural parasite populations under drug treatment pressure. We studied lines of the protozoan parasite Leishmania (L.) donovani with differential susceptibility to antimonial drugs; the lines being derived from clinical isolates belonging to two distinct genetic populations that circulate in the leishmaniasis endemic region of Nepal. Parasite pathways known to be affected by antimonial drugs were characterised on five experimental levels in the lines of the two populations. Characterisation of DNA sequence, gene expression, protein expression and thiol levels revealed a number of molecular features that mark antimonial-resistant parasites in only one of the two populations studied. A final series of in vitro stress phenotyping experiments confirmed this heterogeneity amongst drug-resistant parasites from the two populations. These data provide evidence that the molecular changes associated with antimonial-resistance in natural Leishmania populations depend on the genetic background of the Leishmania population, which has resulted in a divergent set of resistance markers in the Leishmania populations. This heterogeneity of parasite adaptations provides severe challenges for the control of drug resistance in the field and the design of molecular surveillance tools for widespread applicability
Ordinary-derivative formulation of conformal totally symmetric arbitrary spin bosonic fields
Conformal totally symmetric arbitrary spin bosonic fields in flat space-time
of even dimension greater than or equal to four are studied. Second-derivative
(ordinary-derivative) formulation for such fields is developed. We obtain gauge
invariant Lagrangian and the corresponding gauge transformations. Gauge
symmetries are realized by involving the Stueckelberg and auxiliary fields.
Realization of global conformal boost symmetries on conformal gauge fields is
obtained. Modified de Donder gauge condition and de Donder-Stueckelberg gauge
condition are introduced. Using the de Donder-Stueckelberg gauge frame,
equivalence of the ordinary-derivative and higher-derivative approaches is
demonstrated. On-shell degrees of freedom of the arbitrary spin conformal field
are analyzed. Ordinary-derivative light-cone gauge Lagrangian of conformal
fields is also presented. Interrelations between the ordinary-derivative gauge
invariant formulation of conformal fields and the gauge invariant formulation
of massive fields are discussed.Comment: 51 pages, v2: Results and conclusions of v1 unchanged. In Sec.3,
brief review of higher-derivative approaches added. In Sec.4, new
representations for Lagrangian, modified de Donder gauge, and de
Donder-Stueckelberg gauge added. In Sec.5, discussion of interrelations
between the ordinary-derivative and higher-derivative approaches added.
Appendices A,B,C,D and references adde
The stellar halo of the Galaxy
Stellar halos may hold some of the best preserved fossils of the formation
history of galaxies. They are a natural product of the merging processes that
probably take place during the assembly of a galaxy, and hence may well be the
most ubiquitous component of galaxies, independently of their Hubble type. This
review focuses on our current understanding of the spatial structure, the
kinematics and chemistry of halo stars in the Milky Way. In recent years, we
have experienced a change in paradigm thanks to the discovery of large amounts
of substructure, especially in the outer halo. I discuss the implications of
the currently available observational constraints and fold them into several
possible formation scenarios. Unraveling the formation of the Galactic halo
will be possible in the near future through a combination of large wide field
photometric and spectroscopic surveys, and especially in the era of Gaia.Comment: 46 pages, 16 figures. References updated and some minor changes.
Full-resolution version available at
http://www.astro.rug.nl/~ahelmi/stellar-halo-review.pd
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