267 research outputs found
The Heumann-Hotzel model for aging revisited
Since its proposition in 1995, the Heumann-Hotzel model has remained as an
obscure model of biological aging. The main arguments used against it were its
apparent inability to describe populations with many age intervals and its
failure to prevent a population extinction when only deleterious mutations are
present. We find that with a simple and minor change in the model these
difficulties can be surmounted. Our numerical simulations show a plethora of
interesting features: the catastrophic senescence, the Gompertz law and that
postponing the reproduction increases the survival probability, as has already
been experimentally confirmed for the Drosophila fly.Comment: 11 pages, 5 figures, to be published in Phys. Rev.
Evidence for the Gompertz Curve in the Income Distribution of Brazil 1978-2005
This work presents an empirical study of the evolution of the personal income
distribution in Brazil. Yearly samples available from 1978 to 2005 were studied
and evidence was found that the complementary cumulative distribution of
personal income for 99% of the economically less favorable population is well
represented by a Gompertz curve of the form , where
is the normalized individual income. The complementary cumulative
distribution of the remaining 1% richest part of the population is well
represented by a Pareto power law distribution . This
result means that similarly to other countries, Brazil's income distribution is
characterized by a well defined two class system. The parameters , ,
, were determined by a mixture of boundary conditions,
normalization and fitting methods for every year in the time span of this
study. Since the Gompertz curve is characteristic of growth models, its
presence here suggests that these patterns in income distribution could be a
consequence of the growth dynamics of the underlying economic system. In
addition, we found out that the percentage share of both the Gompertzian and
Paretian components relative to the total income shows an approximate cycling
pattern with periods of about 4 years and whose maximum and minimum peaks in
each component alternate at about every 2 years. This finding suggests that the
growth dynamics of Brazil's economic system might possibly follow a
Goodwin-type class model dynamics based on the application of the
Lotka-Volterra equation to economic growth and cycle.Comment: 22 pages, 15 figures, 4 tables. LaTeX. Accepted for publication in
"The European Physical Journal B
AT2023fhn (the Finch): a Luminous Fast Blue Optical Transient at a large offset from its host galaxy
Luminous Fast Blue Optical Transients (LFBOTs) - the prototypical example
being AT 2018cow - are a rare class of events whose origins are poorly
understood. They are characterised by rapid evolution, featureless blue spectra
at early times, and luminous X-ray and radio emission. LFBOTs thus far have
been found exclusively at small projected offsets from star-forming host
galaxies. We present Hubble Space Telescope, Gemini, Chandra and Very Large
Array observations of a new LFBOT, AT2023fhn. The Hubble Space Telescope data
reveal a large offset (greater than 3.5 half-light radii) from the two closest
galaxies, both at a redshift of 0.24. The isolated environment of AT 2023fhn is
in stark contrast with previous events, is challenging to explain with most
LFBOT progenitor models, and calls into question the homogeneity of LFBOTs as a
class.Comment: Submitted to MNRASL. 7 pages, 4 figures, 2 table
Exact Solution of an Evolutionary Model without Ageing
We introduce an age-structured asexual population model containing all the
relevant features of evolutionary ageing theories. Beneficial as well as
deleterious mutations, heredity and arbitrary fecundity are present and managed
by natural selection. An exact solution without ageing is found. We show that
fertility is associated with generalized forms of the Fibonacci sequence, while
mutations and natural selection are merged into an integral equation which is
solved by Fourier series. Average survival probabilities and Malthusian growth
exponents are calculated indicating that the system may exhibit mutational
meltdown. The relevance of the model in the context of fissile reproduction
groups as many protozoa and coelenterates is discussed.Comment: LaTeX file, 15 pages, 2 ps figures, to appear in Phys. Rev.
AT2023fhn (the Finch):a luminous fast blue optical transient at a large offset from its host galaxy
Luminous fast blue optical transients (LFBOTs) – the prototypical example being AT 2018cow – are a rare class of events whose origins are poorly understood. They are characterized by rapid evolution, featureless blue spectra at early times, and luminous X-ray and radio emission. LFBOTs thus far have been found exclusively at small projected offsets from star-forming host galaxies. We present Hubble Space Telescope, Gemini, Chandra, and Very Large Array observations of a new LFBOT, AT 2023fhn. The Hubble Space Telescope data reveal a large offset (>3.5 half-light radii) from the two closest galaxies, both at redshift z ∼ 0.24. The location of AT 2023fhn is in stark contrast with previous events, and demonstrates that LFBOTs can occur in a range of galactic environments
The Late-time Afterglow Evolution of Long Gamma-Ray Bursts GRB 160625B and GRB 160509A
We present post-jet-break Hubble Space Telescope, Very Large Array, and Chandra observations of the afterglow of the long γ-ray bursts GRB 160625B (between 69 and 209 days) and GRB 160509A (between 35 and 80 days). We calculate the post-jet-break decline rates of the light curves and find the afterglow of GRB 160625B is inconsistent with a simple t −3/4 steepening over the break, expected from the geometric effect of the jet edge entering our line of sight. However, the favored optical post-break decline () is also inconsistent with the f ν ∝ t −p decline (where p ≈ 2.3 from the pre-break light curve), which is expected from exponential lateral expansion of the jet; perhaps suggesting lateral expansion that only affects a fraction of the jet. The post-break decline of GRB 160509A is consistent with both the t −3/4 steepening and with f ν ∝ t −p . We also use boxfit to fit afterglow models to both light curves and find both to be energetically consistent with a millisecond magnetar central engine, but the magnetar parameters need to be extreme (i.e., E ~ 3 × 1052 erg). Finally, the late-time radio light curves of both afterglows are not reproduced well by boxfit and are inconsistent with predictions from the standard jet model; instead, both are well represented by a single power-law decline (roughly f ν ∝ t −1) with no breaks. This requires a highly chromatic jet break () and possibly a two-component jet for both bursts
Incorporating prior knowledge improves detection of differences in bacterial growth rate
BACKGROUND: Robust statistical detection of differences in the bacterial growth rate can be challenging, particularly when dealing with small differences or noisy data. The Bayesian approach provides a consistent framework for inferring model parameters and comparing hypotheses. The method captures the full uncertainty of parameter values, whilst making effective use of prior knowledge about a given system to improve estimation. RESULTS: We demonstrated the application of Bayesian analysis to bacterial growth curve comparison. Following extensive testing of the method, the analysis was applied to the large dataset of bacterial responses which are freely available at the web-resource, ComBase. Detection was found to be improved by using prior knowledge from clusters of previously analysed experimental results at similar environmental conditions. A comparison was also made to a more traditional statistical testing method, the F-test, and Bayesian analysis was found to perform more conclusively and to be capable of attributing significance to more subtle differences in growth rate. CONCLUSIONS: We have demonstrated that by making use of existing experimental knowledge, it is possible to significantly improve detection of differences in bacterial growth rate
The diversity of kilonova emission in short gamma-ray bursts
The historic first joint detection of both gravitational-wave and electromagnetic emission from a binary neutron star merger cemented the association between short gamma-ray bursts (SGRBs) and compact object mergers, as well as providing a well-sampled multi-wavelength light curve of a radioactive kilonova (KN) for the first time. Here, we compare the optical and near-infrared light curves of this KN, AT 2017gfo, to the counterparts of a sample of nearby (z < 0.5) SGRBs to characterize their diversity in terms of their brightness distribution. Although at similar epochs AT 2017gfo appears fainter than every SGRB-associated KN claimed so far, we find three bursts (GRBs 050509B, 061201, and 080905A) where, if the reported redshifts are correct, deep upper limits rule out the presence of a KN similar to AT 2017gfo by several magnitudes. Combined with the properties of previously claimed KNe in SGRBs this suggests considerable diversity in the properties of KN drawn from compact object mergers, despite the similar physical conditions that are expected in many NS–NS mergers. We find that observer angle alone is not able to explain this diversity, which is likely a product of the merger type (NS–NS versus NS–BH) and the detailed properties of the binary (mass ratio, spins etc.). Ultimately disentangling these properties should be possible through observations of SGRBs and gravitational-wave sources, providing direct measurements of heavy element enrichment throughout the universe
When the optimal is not the best: parameter estimation in complex biological models
Background: The vast computational resources that became available during the
past decade enabled the development and simulation of increasingly complex
mathematical models of cancer growth. These models typically involve many free
parameters whose determination is a substantial obstacle to model development.
Direct measurement of biochemical parameters in vivo is often difficult and
sometimes impracticable, while fitting them under data-poor conditions may
result in biologically implausible values.
Results: We discuss different methodological approaches to estimate
parameters in complex biological models. We make use of the high computational
power of the Blue Gene technology to perform an extensive study of the
parameter space in a model of avascular tumor growth. We explicitly show that
the landscape of the cost function used to optimize the model to the data has a
very rugged surface in parameter space. This cost function has many local
minima with unrealistic solutions, including the global minimum corresponding
to the best fit.
Conclusions: The case studied in this paper shows one example in which model
parameters that optimally fit the data are not necessarily the best ones from a
biological point of view. To avoid force-fitting a model to a dataset, we
propose that the best model parameters should be found by choosing, among
suboptimal parameters, those that match criteria other than the ones used to
fit the model. We also conclude that the model, data and optimization approach
form a new complex system, and point to the need of a theory that addresses
this problem more generally
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