4,626 research outputs found
Hawaiian Picture‐Winged Drosophila Exhibit Adaptive Population Divergence along a Narrow Climatic Gradient on Hawaii Island
1. Anthropogenic influences on global processes and climatic conditions are increasingly affecting ecosystems throughout the world. 2. Hawaii Island’s native ecosystems are well studied and local long‐term climatic trends well documented, making these ecosystems ideal for evaluating how native taxa may respond to a warming environment. 3.This study documents adaptive divergence of populations of a Hawaiian picture‐winged Drosophila, D. sproati, that are separated by only 7 km and 365 m in elevation. 4.Representative laboratory populations show divergent behavioral and physiological responses to an experimental low‐intensity increase in ambient temperature during maturation. The significant interaction of source population by temperature treatment for behavioral and physiological measurements indicates differential adaptation to temperature for the two populations. 5.Significant differences in gene expression among males were mostly explained by the source population, with eleven genes in males also showing a significant interaction of source population by temperature treatment. 6.The combined behavior, physiology, and gene expression differences between populations illustrate the potential for local adaptation to occur over a fine spatial scale and exemplify nuanced response to climate change
Political Parties and Foreign Direct Investment Inflows Among Developing Countries
This paper focuses on the nature of party systems to explain variations in FDI inflows within developing democracies. We hypothesize a positive relationship between the effective number of parliamentary parties (ENPPs) and FDI inflows. Large ENPPs are indicative of the expropriation risks as well as stability of the political environment of host countries. We thus argue that expropriation risks are low when the presence of multiple parties makes drastic, impulsive changes in economic policies difficult. We also suggest that a larger number of parties represent diverse societal interests better, reducing the chances of under-represented social groups driving political instability. The relationship between ENPP and FDI inflows is tested on a sample of 56 developing democracies from 1985 to 2011. The evidence presented lends strong support to the argument and is found robust to a number of alternative empirical scenarios
Predicting Physical Parameters of Cepheid and RR Lyrae variables in an Instant with Machine Learning
We present a machine learning method to estimate the physical parameters of
classical pulsating stars such as RR Lyrae and Cepheid variables based on an
automated comparison of their theoretical and observed light curve parameters
at multiple wavelengths. We train artificial neural networks (ANNs) on
theoretical pulsation models to predict the fundamental parameters (mass,
radius, luminosity, and effective temperature) of Cepheid and RR Lyrae stars
based on their period and light curve parameters. The fundamental parameters of
these stars can be estimated up to 60 percent more accurately when the light
curve parameters are taken into consideration. This method was applied to the
observations of hundreds of Cepheids and thousands of RR Lyrae in the
Magellanic Clouds to produce catalogs of estimated masses, radii, luminosities,
and other parameters of these stars.Comment: Proceedings of IAU GA Symposium - Machine Learning in Astronomy:
Possibilities and Pitfalls, in Busan, South Korea, 202
Inverse analysis of asteroseismic data: a review
Asteroseismology has emerged as the best way to characterize the global and
internal properties of nearby stars. Often, this characterization is achieved
by fitting stellar evolution models to asteroseismic observations. The star
under investigation is then assumed to have the properties of the best-fitting
model, such as its age. However, the models do not fit the observations
perfectly. This is due to incorrect or missing physics in stellar evolution
calculations, resulting in predicted stellar structures that are discrepant
with reality. Through an inverse analysis of the asteroseismic data, it is
possible to go further than fitting stellar models, and instead infer details
about the actual internal structure of the star at some locations in its
interior. Comparing theoretical and observed stellar structures then enables
the determination of the locations where the stellar models have discrepant
structure, and illuminates a path for improvements to our understanding of
stellar evolution. In this invited review, we describe the methods of
asteroseismic inversions, and outline the progress that is being made towards
measuring the interiors of stars.Comment: 12 pages, 1 figure. Invited review, Dynamics of the Sun and Star
Observational predictions for Thorne-\.Zytkow objects
Thorne-ytkow objects (TO) are potential end products of the merger
of a neutron star with a non-degenerate star. In this work, we have computed
the first grid of evolutionary models of TOs with the MESA stellar
evolution code. With these models, we predict several observational properties
of TOs, including their surface temperatures and luminosities, pulsation
periods, and nucleosynthetic products. We expand the range of possible TO
solutions to cover and
. Due to the much
higher densities our TOs reach compared to previous models, if TOs
form we expect them to be stable over a larger mass range than previously
predicted, without exhibiting a gap in their mass distribution. Using the GYRE
stellar pulsation code we show that TOs should have fundamental pulsation
periods of 1000--2000 days, and period ratios of 0.2--0.3. Models
computed with a large 399 isotope fully-coupled nuclear network show a
nucleosynthetic signal that is different to previously predicted. We propose a
new nucleosynthetic signal to determine a star's status as a TO: the
isotopologues and , which will
have a shift in their spectral features as compared to stable
titanium-containing molecules. We find that in the local Universe (~SMC
metallicities and above) TOs show little heavy metal enrichment,
potentially explaining the difficulty in finding TOs to-date.Comment: 17 pages, 16 figures, 3 Tables, Sumbitedd to MNRAS, Zenodo data
available https://doi.org/10.5281/zenodo.453442
Geometry of the LMC based on multi-phase analysis of multi-wavelength Cepheid light curves using OGLE-IV and Gaia DR3 data
The period-luminosity (PL) relation of Cepheids in the Large Magellanic Cloud
(LMC) plays a pivotal role in extra-galactic distance measurement and the
determination of the Hubble constant . In this work, we probe the
geometry of the LMC through a detailed study of multi-phase PL relations of
these Cepheids, leveraging data from the OGLE-IV and Gaia DR3 databases. We
analyse the light curves of a combined sample of 3300 fundamental (FU)
and first overtone (FO) mode classical Cepheids. We obtain multi-phase data
with phase points over a complete pulsation cycle from the OGLE
and Gaia photometric bands. We determine the
distance modulus and reddening values of individual Cepheids by fitting a
simultaneous reddening law to the apparent distance modulus values. We
calculate the LMC viewing angle parameters: the inclination angle and
position angle of line of nodes by fitting a plane of the
form to the three-dimensional distribution of Cepheids in
Cartesian coordinates . The values of LMC viewing angles from
multi-phase PL relations are found to be: , , respectively. The use of multi-phase PL relations in
multiple bands results in lower uncertainties for the LMC viewing angle
parameters as compared to those derived from the mean light PL relations. This
shows that the use of multi-phase PL relations with multi-wavelength photometry
significantly improves the precision of these measurements, allowing better
constraints on the morphology and the structure of the LMC.Comment: 16 pages, 11 figure
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