18,975 research outputs found
Slitless spectrophotometry with forward modelling: principles and application to atmospheric transmission measurement
In the next decade, many optical surveys will aim to tackle the question of
dark energy nature, measuring its equation of state parameter at the permil
level. This requires trusting the photometric calibration of the survey with a
precision never reached so far, controlling many sources of systematic
uncertainties. The measurement of the on-site atmospheric transmission for each
exposure, or on average for each season or for the full survey, can help reach
the permil precision for magnitudes. This work aims at proving the ability to
use slitless spectroscopy for standard star spectrophotometry and its use to
monitor on-site atmospheric transmission as needed, for example, by the Vera C.
Rubin Observatory Legacy Survey of Space and Time supernova cosmology program.
We fully deal with the case of a disperser in the filter wheel, which is the
configuration chosen in the Rubin Auxiliary Telescope. The theoretical basis of
slitless spectrophotometry is at the heart of our forward model approach to
extract spectroscopic information from slitless data. We developed a publicly
available software called Spectractor (https://github.com/LSSTDESC/Spectractor)
that implements each ingredient of the model and finally performs a fit of a
spectrogram model directly on image data to get the spectrum. We show on
simulations that our model allows us to understand the structure of
spectrophotometric exposures. We also demonstrate its use on real data, solving
specific issues and illustrating how our procedure allows the improvement of
the model describing the data. Finally, we discuss how this approach can be
used to directly extract atmospheric transmission parameters from data and thus
provide the base for on-site atmosphere monitoring. We show the efficiency of
the procedure on simulations and test it on the limited data set available.Comment: 30 pages, 36 figures, submitted to Astronomy and Astrophysic
Using knowledge graphs to infer gene expression in plants
IntroductionClimate change is already affecting ecosystems around the world and forcing us to adapt to meet societal needs. The speed with which climate change is progressing necessitates a massive scaling up of the number of species with understood genotype-environment-phenotype (G×E×P) dynamics in order to increase ecosystem and agriculture resilience. An important part of predicting phenotype is understanding the complex gene regulatory networks present in organisms. Previous work has demonstrated that knowledge about one species can be applied to another using ontologically-supported knowledge bases that exploit homologous structures and homologous genes. These types of structures that can apply knowledge about one species to another have the potential to enable the massive scaling up that is needed through in silico experimentation.MethodsWe developed one such structure, a knowledge graph (KG) using information from Planteome and the EMBL-EBI Expression Atlas that connects gene expression, molecular interactions, functions, and pathways to homology-based gene annotations. Our preliminary analysis uses data from gene expression studies in Arabidopsis thaliana and Populus trichocarpa plants exposed to drought conditions.ResultsA graph query identified 16 pairs of homologous genes in these two taxa, some of which show opposite patterns of gene expression in response to drought. As expected, analysis of the upstream cis-regulatory region of these genes revealed that homologs with similar expression behavior had conserved cis-regulatory regions and potential interaction with similar trans-elements, unlike homologs that changed their expression in opposite ways.DiscussionThis suggests that even though the homologous pairs share common ancestry and functional roles, predicting expression and phenotype through homology inference needs careful consideration of integrating cis and trans-regulatory components in the curated and inferred knowledge graph
Beam scanning by liquid-crystal biasing in a modified SIW structure
A fixed-frequency beam-scanning 1D antenna based on Liquid Crystals (LCs) is designed for application in 2D scanning with lateral alignment. The 2D array environment imposes full decoupling of adjacent 1D antennas, which often conflicts with the LC requirement of DC biasing: the proposed design accommodates both. The LC medium is placed inside a Substrate Integrated Waveguide (SIW) modified to work as a Groove Gap Waveguide, with radiating slots etched on the upper broad wall, that radiates as a Leaky-Wave Antenna (LWA). This allows effective application of the DC bias voltage needed for tuning the LCs. At the same time, the RF field remains laterally confined, enabling the possibility to lay several antennas in parallel and achieve 2D beam scanning. The design is validated by simulation employing the actual properties of a commercial LC medium
A splitting property of the chromatic homology of the complete graph
Khovanov introduced a bigraded cohomology theory of links whose graded Euler
characteristic is the Jones polynomial. The theory was subsequently applied to
the chromatic polynomial of graph, resulting in a categorification known as the
``chromatic homology''. Much as in the Khovanov homology, the chromatic
polynomial can be obtained by taking the Euler characteristic of the chromatic
homology. In the present paper, we introduce a combinatorial description of
enhanced states that can be applied to analysis of the homology in an explicit
way by hand. Using the new combinatorial description, we show a splitting
property of the chromatic homology for a certain class of graphs. Finally, as
an application of the description, we compute the chromatic homology of the
complete graph.Comment: 20 pages, 5 figure
Form and Tonal Spectrum in 12-Tone Music: Approaches to Analysis in Schoenberg, Walker, and Webern
Approaches to analysis in 12-tone music have been predominantly focused around the concept of atonality. Building off of ideas first imagined by theorists such as Heinrich Schenker and Arnold Schoenberg, I propose that all music can be understood as tonal using nature’s model, the overtone series. Through a detailed description of the organic nature of tonality, my work suggests that what was once understood as a dissonance can be reimagined as a new type of consonance. Analyzing passages of 12-tone music from Arnold Schoenberg, George Walker, and Anton Webern, I provide a means for expanding upon traditional Schenkerian Analysis, which has been traditionally limited to music of the 18th and 19th century. I suggest that all music with “tones” can be considered tonal, and that background-level graphs representing higher partials can be used to categorize musical passages as “more” or “less” tonal, in a traditional sense
Transferring Compactness
We demonstrate that the technology of Radin forcing can be used to transfer
compactness properties at a weakly inaccessible but not strong limit cardinal
to a strongly inaccessible cardinal.
As an application, relative to the existence of large cardinals, we construct
a model of set theory in which there is a cardinal that is
--stationary for all but not weakly compact. This is in
sharp contrast to the situation in the constructible universe , where
being --stationary is equivalent to being
-indescribable. We also show that it is consistent that there
is a cardinal such that is
-stationary for all and , answering a
question of Sakai.Comment: Corrected some typo
Introduction to Facial Micro Expressions Analysis Using Color and Depth Images: A Matlab Coding Approach (Second Edition, 2023)
The book attempts to introduce a gentle introduction to the field of Facial
Micro Expressions Recognition (FMER) using Color and Depth images, with the aid
of MATLAB programming environment. FMER is a subset of image processing and it
is a multidisciplinary topic to analysis. So, it requires familiarity with
other topics of Artifactual Intelligence (AI) such as machine learning, digital
image processing, psychology and more. So, it is a great opportunity to write a
book which covers all of these topics for beginner to professional readers in
the field of AI and even without having background of AI. Our goal is to
provide a standalone introduction in the field of MFER analysis in the form of
theorical descriptions for readers with no background in image processing with
reproducible Matlab practical examples. Also, we describe any basic definitions
for FMER analysis and MATLAB library which is used in the text, that helps
final reader to apply the experiments in the real-world applications. We
believe that this book is suitable for students, researchers, and professionals
alike, who need to develop practical skills, along with a basic understanding
of the field. We expect that, after reading this book, the reader feels
comfortable with different key stages such as color and depth image processing,
color and depth image representation, classification, machine learning, facial
micro-expressions recognition, feature extraction and dimensionality reduction.
The book attempts to introduce a gentle introduction to the field of Facial
Micro Expressions Recognition (FMER) using Color and Depth images, with the aid
of MATLAB programming environment.Comment: This is the second edition of the boo
Topological Characterization of Consensus Solvability in Directed Dynamic Networks
Consensus is one of the most fundamental problems in distributed computing.
This paper studies the consensus problem in a synchronous dynamic directed
network, in which communication is controlled by an oblivious message
adversary. The question when consensus is possible in this model has already
been studied thoroughly in the literature from a combinatorial perspective, and
is known to be challenging. This paper presents a topological perspective on
consensus solvability under oblivious message adversaries, which provides
interesting new insights. Our main contribution is a topological
characterization of consensus solvability, which also leads to explicit
decision procedures. Our approach is based on the novel notion of a
communication pseudosphere, which can be seen as the message-passing analog of
the well-known standard chromatic subdivision for wait-free shared memory
systems. We further push the elegance and expressiveness of the "geometric"
reasoning enabled by the topological approach by dealing with uninterpreted
complexes, which considerably reduce the size of the protocol complex, and by
labeling facets with information flow arrows, which give an intuitive meaning
to the implicit epistemic status of the faces in a protocol complex
On uniquely packable trees
An -packing in a graph is a set of vertices that are pairwise distance
more than apart. A \emph{packing colouring} of is a partition
of such that each colour class
is an -packing. The minimum order of a packing colouring is called the
packing chromatic number of , denoted by . In this paper we
investigate the existence of trees for which there is only one packing
colouring using colours. For the case , we
completely characterise all such trees. As a by-product we obtain sets of
uniquely --packable trees with monotone -coloring
and non-monotone -coloring respectively
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