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 $G(x)=\exp [\exp (A-Bx)]$, where $x$ 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 $P(x)= \beta x^{-\alpha}$. This result means that similarly to other countries, Brazil's income distribution is characterized by a well defined two class system. The parameters $A$, $B$, $\alpha$, $\beta$ 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

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 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

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 (${f}_{\nu }\propto {t}^{-1.96\pm 0.07}$) 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 (${t}_{j,\mathrm{radio}}\gt 10\times {t}_{j,\mathrm{optical}}$) 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

Evidence for a luminosity-decay correlation in GRB GeV light curves

Correlations between intrinsic properties of gamma-ray burst (GRB) light curves provide clues to the nature of the central engine, the jet, and a possible means to standardize GRBs for cosmological use. Here, we report on the discovery of a correlation between the intrinsic early-time luminosity, LG,10 s, measured at rest frame 10 s, and the average decay rate measured from rest frame 10 s onward, αG,avg>10 s, in a sample of 13 Fermi Large Area Telescope long GRB light curves. We note that our selection criteria, in particular the requirement for a redshift to construct luminosity light curves, naturally limits our sample to energetic GRBs. A Spearman’s rank correlation gives a coefficient of –0.74, corresponding to a confidence level of 99.6 per cent, indicating that brighter afterglows decay faster than less luminous ones. Assuming a linear relation with log(LG,10s), we find αG,avg>10 s= −0.31+0.12 −0.09 log(LG,10s) + 14.43+4.55 −5.97. The slope of −0.31 is consistent at 1σ with previously identified correlations in the optical/ultraviolet and X-ray light curves. We speculate that differences in the rate at which energy is released by the central engine or differences in observer viewing angle may be responsible for the correlation