The Overlooked Potential of Generalized Linear Models in Astronomy - I: Binomial Regression

Revealing hidden patterns in astronomical data is often the path to fundamental scientific breakthroughs; meanwhile the complexity of scientific inquiry increases as more subtle relationships are sought. Contemporary data analysis problems often elude the capabilities of classical statistical techniques, suggesting the use of cutting edge statistical methods. In this light, astronomers have overlooked a whole family of statistical techniques for exploratory data analysis and robust regression, the so-called Generalized Linear Models (GLMs). In this paper -- the first in a series aimed at illustrating the power of these methods in astronomical applications -- we elucidate the potential of a particular class of GLMs for handling binary/binomial data, the so-called logit and probit regression techniques, from both a maximum likelihood and a Bayesian perspective. As a case in point, we present the use of these GLMs to explore the conditions of star formation activity and metal enrichment in primordial minihaloes from cosmological hydro-simulations including detailed chemistry, gas physics, and stellar feedback. We predict that for a dark mini-halo with metallicity $\approx 1.3 \times 10^{-4} Z_{\bigodot}$, an increase of $1.2 \times 10^{-2}$ in the gas molecular fraction, increases the probability of star formation occurrence by a factor of 75%. Finally, we highlight the use of receiver operating characteristic curves as a diagnostic for binary classifiers, and ultimately we use these to demonstrate the competitive predictive performance of GLMs against the popular technique of artificial neural networks.Comment: 20 pages, 10 figures, 3 tables, accepted for publication in Astronomy and Computin

Using gamma regression for photometric redshifts of survey galaxies

Machine learning techniques offer a plethora of opportunities in tackling big data within the astronomical community. We present the set of Generalized Linear Models as a fast alternative for determining photometric redshifts of galaxies, a set of tools not commonly applied within astronomy, despite being widely used in other professions. With this technique, we achieve catastrophic outlier rates of the order of ~1%, that can be achieved in a matter of seconds on large datasets of size ~1,000,000. To make these techniques easily accessible to the astronomical community, we developed a set of libraries and tools that are publicly available.Comment: Refereed Proceeding of "The Universe of Digital Sky Surveys" conference held at the INAF - Observatory of Capodimonte, Naples, on 25th-28th November 2014, to be published in the Astrophysics and Space Science Proceedings, edited by Longo, Napolitano, Marconi, Paolillo, Iodice, 6 pages, and 1 figur

The Overlooked Potential of Generalized Linear Models in Astronomy-III: Bayesian Negative Binomial Regression and Globular Cluster Populations

In this paper, the third in a series illustrating the power of generalized linear models (GLMs) for the astronomical community, we elucidate the potential of the class of GLMs which handles count data. The size of a galaxy's globular cluster population $N_{\rm GC}$ is a prolonged puzzle in the astronomical literature. It falls in the category of count data analysis, yet it is usually modelled as if it were a continuous response variable. We have developed a Bayesian negative binomial regression model to study the connection between $N_{\rm GC}$ and the following galaxy properties: central black hole mass, dynamical bulge mass, bulge velocity dispersion, and absolute visual magnitude. The methodology introduced herein naturally accounts for heteroscedasticity, intrinsic scatter, errors in measurements in both axes (either discrete or continuous), and allows modelling the population of globular clusters on their natural scale as a non-negative integer variable. Prediction intervals of 99% around the trend for expected $N_{\rm GC}$comfortably envelope the data, notably including the Milky Way, which has hitherto been considered a problematic outlier. Finally, we demonstrate how random intercept models can incorporate information of each particular galaxy morphological type. Bayesian variable selection methodology allows for automatically identifying galaxy types with different productions of GCs, suggesting that on average S0 galaxies have a GC population 35% smaller than other types with similar brightness.Comment: 14 pages, 12 figures. Accepted for publication in MNRA

“Catch 22”: biosecurity awareness, interpretation and practice amongst poultry catchers

Campylobacter contamination of chicken on sale in the UK remains at high levels and has a substantial public health impact. This has prompted the application of many interventions in the supply chain, including enhanced biosecurity measures on-farm. Catching and thinning are acknowledged as threats to the maintenance of good biosecurity, yet the people employed to undertake this critical work (i.e. ‘catchers’) are a rarely studied group. This study uses a mixed methods approach to investigate catchers’ (n = 53) understanding of the biosecurity threats posed by the catching and thinning, and the barriers to good biosecurity practice. It interrogated the role of training in both the awareness and practice of good biosecurity. Awareness of lapses in biosecurity was assessed using a Watch-&-Click hazard awareness survey (n = 53). Qualitative interviews (n = 49 catchers, 5 farm managers) explored the understanding, experience and practice of catching and biosecurity. All of the catchers who took part in the Watch-&-Click study identified at least one of the biosecurity threats with 40% detecting all of the hazards. Those who had undergone training were significantly more likely to identify specific biosecurity threats and have a higher awareness score overall (48% compared to 9%, p = 0.03). Crucially, the individual and group interviews revealed the tensions between the high levels of biosecurity awareness evident from the survey and the reality of the routine practice of catching and thinning. Time pressures and a lack of equipment rather than a lack of knowledge appear a more fundamental cause of catcher-related biosecurity lapses. Our results reveal that catchers find themselves in a ‘catch-22′ situation in which mutually conflicting circumstances prevent simultaneous completion of their job and compliance with biosecurity standards

Combining frequency and time domain approaches to systems with multiple spike train input and output

A frequency domain approach and a time domain approach have been combined in an investigation of the behaviour of the primary and secondary endings of an isolated muscle spindle in response to the activity of two static fusimotor axons when the parent muscle is held at a fixed length and when it is subjected to random length changes. The frequency domain analysis has an associated error process which provides a measure of how well the input processes can be used to predict the output processes and is also used to specify how the interactions between the recorded processes contribute to this error. Without assuming stationarity of the input, the time domain approach uses a sequence of probability models of increasing complexity in which the number of input processes to the model is progressively increased. This feature of the time domain approach was used to identify a preferred direction of interaction between the processes underlying the generation of the activity of the primary and secondary endings. In the presence of fusimotor activity and dynamic length changes imposed on the muscle, it was shown that the activity of the primary and secondary endings carried different information about the effects of the inputs imposed on the muscle spindle. The results presented in this work emphasise that the analysis of the behaviour of complex systems benefits from a combination of frequency and time domain methods

An outbreak of abortions, stillbirths and malformations in a Spanish sheep flock associated with a bovine viral diarrhoea virus 2-contaminated orf vaccine

Bovine viral diarrhoea virus (BVDV) is a pestivirus that affects both cattle and sheep, causing an array of clinical signs, which include abortions and malformations in the offspring. Manufacturing of modified live virus (MLV) vaccines often includes the use of bovine-derived products, which implies a risk of contamination with viable BVDV. Recently, the circulation of a specific strain of BVDV 2b among Spanish sheep flocks, associated with outbreaks of abortions and malformations, and whose origin was not determined, has been observed. On February 2018, a MLV orf vaccine was applied to a 1, 600 highly prolific sheep flock in the Northeast of Spain that included 550 pregnant ewes. In May 2018, during the lambing season, an unusual high rate (72.7%) of abortions, stillbirths, congenital malformations and neurological signs in the offspring was observed. It was estimated that about 1, 000 lambs were lost. Three 1- to 3-day-old affected lambs and a sealed vial of the applied vaccine were studied. Lambs showed variable degrees of central nervous system malformations and presence of pestiviral antigen in the brain. Molecular studies demonstrated the presence of exactly the same BVDV 2b in the tissues of the three lambs and in the orf vaccine, thus pointing to a pestivirus contamination in the applied vaccine as the cause of the outbreak. Interestingly, sequencing at the 5'-untranslated region-(UTR) of the contaminating virus showed a complete match with the virus described in the previously reported outbreaks in Spain, thus indicating that the same contaminated vaccine could have also played a role in those cases. This communication provides a clear example of the effects of the application of this contaminated product in a sheep flock. The information presented here can be of interest in putative future cases of suspected circulation of this or other BVDV strains in ruminants

If cooperation is likely punish mildly: Insights from economic experiments based on the snowdrift game

Punishment may deter antisocial behavior. Yet to punish is costly, and the costs often do not offset the gains that are due to elevated levels of cooperation. However, the effectiveness of punishment depends not only on how costly it is, but also on the circumstances defining the social dilemma. Using the snowdrift game as the basis, we have conducted a series of economic experiments to determine whether severe punishment is more effective than mild punishment. We have observed that severe punishment is not necessarily more effective, even if the cost of punishment is identical in both cases. The benefits of severe punishment become evident only under extremely adverse conditions, when to cooperate is highly improbable in the absence of sanctions. If cooperation is likely, mild punishment is not less effective and leads to higher average payoffs, and is thus the much preferred alternative. Presented results suggest that the positive effects of punishment stem not only from imposed fines, but may also have a psychological background. Small fines can do wonders in motivating us to chose cooperation over defection, but without the paralyzing effect that may be brought about by large fines. The later should be utilized only when absolutely necessary.Comment: 15 pages, 6 figures; accepted for publication in PLoS ON

The overlooked potential of Generalized Linear Models in astronomy, I: Binomial regression

Revealing hidden patterns in astronomical data is often the path to fundamental scientific breakthroughs; meanwhile the complexity of scientific inquiry increases as more subtle relationships are sought. Contemporary data analysis problems often elude the capabilities of classical statistical techniques, suggesting the use of cutting edge statistical methods. In this light, astronomers have overlooked a whole family of statistical techniques for exploratory data analysis and robust regression, the so-called Generalized Linear Models (GLMs). In this paper – the first in a series aimed at illustrating the power of these methods in astronomical applications – we elucidate the potential of a particular class of GLMs for handling binary/binomial data, the so-called logit and probit regression techniques, from both a maximum likelihood and a Bayesian perspective. As a case in point, we present the use of these GLMs to explore the conditions of star formation activity and metal enrichment in primordial minihaloes from cosmological hydro-simulations including detailed chemistry, gas physics, and stellar feedback. We predict that for a dark mini-halo with metallicity ≈ 1.3 × 10−4ZJ, an increase of 1.2 × 10−2 in the gas molecular fraction, increases the probability of star formation occurrence by a factor of 75%. Finally, we highlight the use of receiver operating characteristic curves as a diagnostic for binary classifiers, and ultimately we use these to demonstrate the competitive predictive performance of GLMs against the popular technique of artificial neural networks

Peripheral infusion of rat bone marrow derived endothelial progenitor cells leads to homing in acute lung injury

<p>Abstract</p> <p>Background</p> <p>Bone marrow-derived progenitors for both epithelial and endothelial cells have been observed in the lung. Besides mature endothelial cells (EC) that compose the adult vasculature, endothelial progenitor cells (EPC) are supposed to be released from the bone marrow into the peripheral blood after stimulation by distinct inflammatory injuries. Homing of <it>ex vivo </it>generated bone marrow-derived EPC into the injured lung has not been investigated so far. We therefore tested the hypothesis whether homing of EPC in damaged lung tissue occurs after intravenous administration.</p> <p>Methods</p> <p>Ex vivo generated, characterized and cultivated rat bone marrow-derived EPC were investigated for proliferation and vasculogenic properties in vitro. EPC were tested for their homing in a left-sided rat lung transplant model mimicking a severe acute lung injury. EPC were transplanted into the host animal by peripheral administration into the femoral vein (10⁶cells). Rats were sacrificed 1, 4 or 9 days after lung transplantation and homing of EPC was evaluated by fluorescence microscopy. EPC were tested further for their involvement in vasculogenesis processes occurring in subcutaneously applied Matrigel in transplanted animals.</p> <p>Results</p> <p>We demonstrate the integration of intravenously injected EPC into the tissue of the transplanted left lung suffering from acute lung injury. EPC were localized in vessel walls as well as in destructed lung tissue. Virtually no cells were found in the right lung or in other organs. However, few EPC were found in subcutaneous Matrigel in transplanted rats.</p> <p>Conclusion</p> <p>Transplanted EPC may play an important role in reestablishing the endothelial integrity in vessels after severe injury or at inflamatory sites and might further contribute to vascular repair or wound healing processes in severely damaged tissue. Therapeutic applications of EPC transplantation may ensue.</p